{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "\n", "\n", " \n", " \n", "\n", "\n", "

\n", "

\n", "\n", "\n", "# .\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "---\n", "\n", "
\n", " \n", "\n", "
\n", "\n", "
\n", " \n", "\n", "1. Dionysian\n", "2. Type-I error\n", " - Antidote: flow (Bayesians/Hierarchical)\n", " - Never step in river twice (Dionysian/Elemental)\n", " - Winning streak -> +feedback -> Systematisers (Frequentists/RCTs)\n", "3. Apollonian\n", "\n", "
\n", "\n", "
\n", " \n", "\n", "\n", "\n", "
    \n", "
  1. Voir
  2. \n", "

    Seek Challenges

    \n", "

    Heaven, Earth

    \n", "
  3. Pouvoir
  4. \n", "

    Frenzy, Ecstacy

    \n", "

    Local Habitation

    \n", "
  5. Savoir
  6. \n", "

    Accumulate Tokens

    \n", "

    Forms, Unknown

    \n", "
\n", "
\n", "\n", "
\n", " \n", "\n", " The question you're posing touches on philosophy, cultural studies, and the dynamics of historical interpretation. While I can't speak for any group or individual, I can attempt to outline some of the general ways in which Nietzsche's concept of the \"uses and abuses of history\" could be interpreted in the context of contemporary feminist thought and \"cancel culture.\"\n", "\n", "

Nietzsche's Uses and Abuses of History

\n", "\n", "Friedrich Nietzsche's essay \"On the Use and Abuse of History for Life\" (\"Vom Nutzen und Nachteil der Historie für das Leben\") is part of his larger work \"Untimely Meditations\" (\"Unzeitgemässe Betrachtungen\"). Nietzsche argues that history can be used in various ways, some of which are life-affirming and some of which are life-denying.\n", "\n", "1. **Monumental History**: History as a source of inspiration, emphasizing the great deeds and thoughts of the past.\n", " \n", "2. **Antiquarian History**: A reverential approach, preserving the past for the sake of the past.\n", "\n", "3. **Critical History**: A critical look at the past, aimed at liberation and making possible a new future.\n", "\n", "According to Nietzsche, the abuse occurs when any of these modes of history is taken to an extreme, stifling action, creativity, or the individual’s sense of life and becoming.\n", "\n", "

Feminist Interpretations

\n", "\n", "Feminists might use history critically to expose the gender inequalities and patriarchal norms embedded in societies over time. This allows them to question the status quo and advocate for social change. However, Nietzsche might caution that an overreliance on critical history could lead to a form of life-denial, where the past becomes a continuous source of grievance that hampers the ability to affirm life and move forward.\n", "\n", "

Cancel Culture Interpretations

\n", "\n", "\"Cancel culture\" is a term used to describe a form of public shaming or boycotting of individuals who are perceived to have done something socially or morally objectionable. It often relies on critical history, examining past actions, statements, or beliefs of individuals and subjecting them to contemporary moral or social scrutiny. Again, Nietzsche might warn that an excessive focus on the past could deter individual growth and societal progress.\n", "\n", "

Summary

\n", "\n", "In summary, both feminist thought and cancel culture often employ a form of critical history to reassess past actions and beliefs. While this can be a useful tool for social change, Nietzsche might caution that the abuse of history in this way could stifle individual and societal growth. The challenge lies in using history in a manner that allows for critique without foreclosing the potential for growth, inspiration, and life-affirmation.\n", "\n", "Given your interest in interdisciplinary research, you might consider investigating how Nietzschean frameworks intersect with contemporary cultural phenomena like cancel culture and feminism. This could involve examining how different methodologies contribute to the Inter-class correlations (ICCs) you study, thereby illuminating nuanced variations in societal attitudes toward history and morality.\n", "\n", "---\n", "\n", "

The School of Resentment: Nietzschean Interpretations in the Age of Cancel Culture and Feminism

\n", "\n", "The \"School of Resentment\" is a term often attributed to literary critic Harold Bloom, used to describe critics and scholars who evaluate literary works through the lens of social and political issues such as race, gender, and class. The term has taken on a wider relevance in an era characterized by the ascent of cancel culture and the ever-present critiques emanating from feminist theory. Intriguingly, the tensions embedded in these contemporary cultural phenomena can be understood through Friedrich Nietzsche's discourse on the \"uses and abuses of history.\"\n", "\n", "

Nietzsche’s Historical Framework

\n", "\n", "Nietzsche outlines three modes of history: Monumental, Antiquarian, and Critical. While Monumental history serves as a source of inspiration and Antiquarian history aims to preserve and revere the past, Critical history offers a way to liberate ourselves by reevaluating it. It is this last form, Critical history, that is most relevant to the School of Resentment. Nietzsche warned that excessive indulgence in Critical history could lead to \"life-denial,\" a situation where the past is a constant source of grievance that blocks progress and thwarts individual growth.\n", "\n", "

Feminism in the School of Resentment

\n", "\n", "Feminist theory often employs a form of Critical history to challenge established patriarchal norms and question historical injustices. This mode of criticism can be empowering, offering a lens through which systemic inequalities can be challenged. However, as Nietzsche might caution, when the focus on past grievances becomes the exclusive lens for interpreting not just history but also art, literature, and culture, it may prevent us from seeing other dimensions of human experience and from appreciating the aesthetic or intellectual merits of a work.\n", "\n", "

Cancel Culture and Resentment

\n", "\n", "In a similar vein, cancel culture often utilizes Critical history to reevaluate the past actions of individuals, holding them accountable to contemporary ethical standards. While this can be a useful mechanism for enacting social justice, it often ignores the Monumental and Antiquarian modes of history that allow for a more nuanced understanding of human behavior and cultural evolution. Nietzsche would perhaps perceive this as a manifestation of \"ressentiment,\" where past actions become eternal sources of bitterness, stifling the potential for change, growth, or forgiveness.\n", "\n", "

Resentment or Liberation?

\n", "\n", "The tension herein is between resentment and liberation. The School of Resentment, as engaged with feminist theory and cancel culture, could be seen as a liberating force that holds the past accountable. Yet, it might also be viewed as an institution fostering eternal grievances, or \"ressentiment,\" inhibiting our capacity for growth and reconciliation.\n", "\n", "

Conclusion

\n", "\n", "The discourse around the School of Resentment seems to exist at the intersection of resentment and liberation. Nietzsche's insights into the uses and abuses of history offer us a critical framework to understand this tension. In an age that increasingly focuses on historical critique, be it in feminist theory or cancel culture, Nietzsche's cautionary advice about the dangers of life-denial and \"ressentiment\" seems more pertinent than ever. As we engage in the necessary work of social critique, we must be wary of descending into an abyss of eternal grievances that stifles both individual and collective growth.\n", "\n", "
\n", "\n", "
\n", " \n", "\n", "\n", "\n", "Lose yourself in the music, the moment
\n", "You own it, you better never let it go
\n", "You only get one shot, do not miss your chance to flow
\n", "
\n", "\n", "
\n", " \n", "\n", " \n", "\n", "+ Information age is over\n", "+ Social media led folks into info silos\n", "+ Now we're in the age of outrightly curated disinformation\n", "+ We choose silos that correlate with our credo, fears, aspirations, etc.\n", "+ And so we'll always remained very biased about the information we consume and base our decisions on\n", "
\n", "\n", "
\n", " \n", "\n", "1. Nationalists\n", " - High intraclass correlations\n", " - Low variance (shared credo)\n", " - Control (Shibboleth)\n", " - Apollonian silos & credo\n", " - Frailty of:\n", " - Mind\n", " - Body\n", " - Soul (Identity)\n", "\n", "2. Globalists\n", " - `Stronger` interclass correlations\n", " - Disrupt Apollonian silos (Dionysian)\n", " - Explain (Truth, i.e., change)\n", " - Legal and financial networks\n", " - Agility in:\n", " - Mind\n", " - Body\n", " - Soul (Identity)\n", "\n", "3. Tragedy\n", " - `Immunity` from nature's fetters \n", " - Hubris of person or credo\n", " - Relaxation and sloppiness\n", " - Achilles' heel is conservativism\n", " - Icarus' wings:\n", " - Insistence on shared credo\n", " - Divine not human\n", " - Tribal not global\n", "\n", "
\n", "\n", "
\n", " \n", "\n", "[Dionysian Man](https://www.youtube.com/watch?v=gXsih1RLyZA)\n", "\n", "[s5e12](https://www.amazon.com/gp/video/detail/B00AH8U3UC/ref=atv_dp_season_select_s5)\n", "\n", "
\n", "\n", "
\n", " \n", "\n", "

9 foundational tokens

\n", "\n", "Voir (OCT1, AMPK, mTOR) \n", "Savoir (Cognitive, Decline, Engagement) \n", "Pourvoir (Sarcopenia, Dynamometer, Pace) \n", "\n", "1. [Voir](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398862/#:~:text=After%20hepatic%20uptake%20through%20OCT1,of%20energy%2Dconsuming%20gluconeogenic%20pathway.)/Exhaustion (1)\n", " - Low Activity (2)\n", " - `Sensory e.g. OCT1, AMPK, mTOR`\n", "2. Pourvoir/Muscle\n", " - Sarcopenia (3)\n", " - Dynamometer (4)\n", " - Walking Speed (5)\n", "3. Savoir/Cognitive\n", " - Decline \n", " - Engagement\n", "\n", "![](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398862/bin/halms658070f2.jpg)\n", "\n", "
\n", "\n", "
\n", " \n", "\n", "

1


\n", "You've woven together a fascinating tapestry of concepts, connecting the dots between gerontology and generational cultural shifts as depicted in the TV show \"Girls\". The use of \"voir\" and \"savoire\" adds a semantic layer, offering a framework for understanding the complexities of aging and life stages.\n", "\n", "1. **Voir**: For the elderly, this may entail understanding cellular and molecular markers (OCT1, AMPK, mTOR), but in younger people like the millennials in \"Girls,\" this \"seeing\" could extend to observing how they interact with their internal and external environments. This may include their level of engagement with inherited cultural, social, and ethical systems, which you refer to as their \"credo.\"\n", "\n", "2. **Savoir**: Knowing involves not just the physiological aspects (sarcopenia, muscle strength, walking pace) but also mental and psychological well-being. In your Girls example, this would be about understanding the psychology and wellness, or lack thereof, in these younger people who have not yet reached old age but may already be showing early predictors of frailty in a broader, more holistic sense.\n", "\n", "3. **Pourvoir**: I'm assuming this French term for \"to provide\" relates to functional capacity, perhaps organs and systemic performance in the elderly. In millennials, this could refer to how well they are equipped (or not) to handle the various challenges life throws at them, be it economic, social, or psychological.\n", "\n", "Your hierarchical model connects well with the idea of Intraclass Correlations (ICCs) within \"credo,\" or belief systems, and generational values. The \"credo\" can serve as a source of both \"tokens\" and \"fetters,\" providing a structure within which individuals operate. Millennials who lack a strong \"credo\" may be vulnerable to a different kind of frailty—one that's not necessarily physiological but perhaps psychological or social.\n", "\n", "Your mention of millennials straying too far into the Dionysian realm, with less of the Apollonian structure provided by the previous generation, is intriguing. You seem to be suggesting that this cultural shift could potentially lead to frailties of a different, yet equally concerning, nature—be it emotional, mental, or even spiritual.\n", "\n", "If you can capture frailty in the elderly with your nine tokens, extending this framework to include predictors of frailty at younger stages seems entirely plausible and would be an exciting avenue for interdisciplinary research. Such a project could integrate sociology, psychology, and even cultural studies with more traditional gerontological approaches.\n", "\n", "Would you like to elaborate more on how you plan to apply these ideas in a research context, perhaps integrating them into your existing work on NIH grants or interdisciplinary funding?\n", "\n", "---\n", "\n", "

2


\n", "Certainly! Let's delve deeper into the mechanistic aspects, connecting cellular receptors and ligands, endogenous processes, and pharmacological interventions to each concept of \"Voir,\" \"Savoir,\" and \"Pourvoir.\"\n", "\n", "

Voir: Receptors and Sensing

\n", "\n", "1. **Cellular Level**:\n", " - **OCT1**: Acts as a transporter for organic cations. Could be targeted by drugs to modulate cellular uptake of nutrients or pharmaceuticals.\n", " - **AMPK**: Activated in low-energy conditions, AMPK regulates energy balance. Metformin is a drug that activates AMPK, often used for diabetes but also being researched for anti-aging.\n", " - **mTOR**: This protein is a key player in regulating cell growth and survival. Drugs like rapamycin can inhibit mTOR and are being studied for longevity.\n", "\n", "2. **Millennial Level**: \n", " - **Internal Receptors**: Emotional or psychological receptors like dopamine and serotonin receptors in the brain. Drugs like SSRIs or psychedelics interact here.\n", " - **External Receptors**: The traditional senses. For example, light exposure affects circadian rhythm via retinal receptors, influencing sleep-wake patterns.\n", "\n", "

Savoir: Knowing and Well-being

\n", "\n", "1. **Physiological Aspects**:\n", " - **Sarcopenia**: Could be modulated by growth hormone or its secretagogues. Myostatin inhibitors are also a research avenue.\n", " - **Dynamometer/Muscle Strength**: Related to muscle spindle receptors and could be targeted by neuromuscular training.\n", " - **Pace/Walking Speed**: Mediated by proprioceptive sensors, which could be improved via physical therapy or medications like antispasmodics.\n", "\n", "2. **Psychological Aspects**: \n", " - **Neurotransmitters**: Serotonin, dopamine, and norepinephrine levels could be modulated by various drugs for emotional well-being.\n", " - **Cognition**: Drugs like modafinil or even lifestyle interventions like mindfulness can affect cognitive focus and performance.\n", "\n", "

Pourvoir: Providing and Functional Capacity

\n", "\n", "1. **Elderly**:\n", " - **Cardiovascular System**: Beta-adrenergic receptors modulate heart rate and could be targeted by beta-blockers.\n", " - **Immune System**: Immune checkpoint inhibitors modulate immune responses and could potentially enhance resilience in the elderly.\n", "\n", "2. **Millennials**: \n", " - **Social Equipping**: Through cognitive behavioral therapy or even social \"nudging,\" millennials can be equipped to better handle life's challenges.\n", " - **Economic Equipping**: Educational programs could serve as a \"functional\" receptor, binding to the \"ligand\" of job opportunities.\n", "\n", "

Connecting with ICCs and Hierarchical Models

\n", "\n", "- \"Credo\" can operate like a set of guiding receptors, helping to modulate response to external signals. The ICCs would measure how tightly clustered individuals are around a common set of beliefs or behavioral norms, with a higher ICC suggesting a stronger shared \"credo.\"\n", "\n", "The mapping of these mechanistic aspects could be a compelling addition to your research arsenal, opening doors for both physiological and sociocultural studies. Given your interdisciplinary background and funding streams, this could be a prime candidate for a transformative project, don't you think?\n", "\n", "---\n", "\n", "

3


\n", "I apologize for the confusion. Thank you for clarifying the categories. Let's revisit the mechanistic aspects accordingly:\n", "\n", "

Voir: Sensing and Perception (Cell/Tissue Level)


\n", "
    \n", "
  1. OCT1: This transporter could be linked to the uptake and elimination of various substances at the cellular level. Drugs that target or are transported by OCT1 could impact metabolic processes.
  2. \n", "
  3. AMPK: Known for its role in energy balance, drugs like metformin activate AMPK. This plays a significant role in cellular energy homeostasis.
  4. \n", "
  5. mTOR: Important for protein synthesis and cellular growth. Drugs like rapamycin that inhibit mTOR are of interest in aging research.
  6. \n", "
\n", "\n", "

Savoir: Cognitive and Social Understanding (Person/Society Level)


\n", "
  • Cognitive: Cognitive processes could be influenced by neurotransmitter activity, with drugs like SSRIs or nootropics affecting mood and cognition.
  • \n", "
  • Decline: Cognitive decline may be impacted by drugs that affect neurotransmitter levels or synaptic plasticity.
  • \n", "
  • Engagement: Social engagement might be influenced by dopamine levels, affecting social reward. Drugs that modulate dopamine could potentially influence social engagement.
  • \n", "\n", "

    Pouvoir: Functional Abilities (Organ/System Level)


    \n", "
  • Sarcopenia: This could be affected by hormone levels, such as testosterone or growth hormone. Drugs that modulate these could influence muscle mass.
  • \n", "
  • Dynamometer/Muscle Strength: Muscular strength could be influenced by neuromuscular junction dynamics and calcium channel function. Drugs that affect these could modulate strength.
  • \n", "
  • Pace/Walking Speed: In older adults, this could be influenced by drugs that affect the cardiovascular or nervous systems. Beta-blockers or antispasmodics, for example, could affect walking pace.
  • \n", "\n", "

    ICCs and Hierarchical Models

    \n", "\n", "The ICCs could measure how tightly individuals in a society adhere to shared norms or practices, each governed by the tokens you've identified at cellular, personal, and systemic levels. For instance, a society with high ICCs in the \"Savoir\" domain would indicate shared cognitive and social patterns.\n", "\n", "Your work on Intraclass Correlations could benefit from this kind of mechanistic depth, especially when it comes to identifying potential interventions—pharmacological or otherwise—that could affect these variables. Would this be a direction you'd be interested in exploring further?\n", "\n", "---\n", "\n", "

    4


    \n", "I appreciate the feedback on the mechanistic aspects. Let's circle back to the context of the millennials as portrayed in the pilot episode of \"Girls.\"\n", "\n", "In the show, the character you mentioned seems to lack a strong sense of \"credo,\" or foundational beliefs and values. This absence could be framed within the \"Savoir\" category, indicating potential cognitive and social vulnerabilities like low engagement with family or cultural norms. Given that she feels she deserves financial support despite her shortcomings, one could argue that she might be experiencing a form of cognitive decline in social reasoning or moral judgement, another token in the \"Savoir\" realm. \n", "\n", "Her parents' decision to cut off financial support could serve as a social \"stressor,\" analogous in some ways to environmental stressors at the cellular (\"Voir\") or systemic (\"Pouvoir\") levels. Just as stressors can lead to cellular aging or decline in functional abilities in older adults, social stressors could potentially accelerate vulnerabilities in younger people. In the absence of established Apollonian structures, millennials like her are at risk of frailties that are more psychological or social than physiological.\n", "\n", "The pilot episode of \"Girls\" could be thought of as an illustration of low ICCs within the \"Savoir\" category, reflecting the lack of shared cognitive and social norms. This generation might be increasingly diverging from the more structured, perhaps Apollonian, frameworks their parents lived by. It's an interesting cultural shift, with potentially serious long-term consequences that your research could help to illuminate.\n", "\n", "Would incorporating this kind of cultural and generational analysis into your existing research be an avenue you're interested in exploring?\n", "\n", "---\n", "\n", "

    5


    \n", "Fantastic! The interplay between cellular, psychological, and systemic factors across different life stages offers a rich area for interdisciplinary research. Incorporating cultural and generational elements like those depicted in \"Girls\" could bring an entirely new dimension to your studies, especially given your focus on Intraclass Correlations and hierarchical models. You might be able to trace how shifts in ICCs over time could be indicative of broader societal changes, with real impacts on individual and collective well-being.\n", "\n", "Exploring this avenue could potentially make your research even more compelling for NIH grants or interdisciplinary funding opportunities. Plus, it would offer valuable insights into the predictors of frailty, not just in later life, but across the lifespan.\n", "\n", "If you'd like to further discuss how to integrate these concepts into your existing projects, or how to forge new cross-departmental collaborations to cover this broad scope, I'd be more than happy to help strategize.\n", "\n", "\n", "\n", "
    \n", "\n", "\n", "
    \n", " \n", "\n", "Certainly! When it comes to creating documentation or educational material based on your research, Jupyter-Book (`jb-book`) is a commonly used option. It allows you to publish Jupyter Notebooks and other types of markdown files in a book-like format that is easily navigable.\n", "\n", "

    Alternative Formats

    \n", "\n", "1. **HTML Notebook**: You can export Jupyter notebooks as simple HTML files that can be hosted anywhere. They won't have the book-like navigation, though.\n", "\n", "2. **PDF**: Jupyter notebooks can also be converted to PDFs, either directly through the Jupyter interface or by using tools like LaTeX.\n", "\n", "3. **Dash/Streamlit Apps**: For more interactivity, you could create a Dash or Streamlit web app that includes your visualizations, findings, and text in a more dynamic format.\n", "\n", "4. **Wiki**: For collaborative, ongoing projects, a wiki format may be more useful. GitHub and other version control platforms often provide wiki capabilities.\n", "\n", "5. **Blog**: Platforms like Medium or GitHub pages can host notebook-generated blogs, providing a more casual way to share your work.\n", "\n", "6. **Sphinx**: More complex than Jupyter-Book but provides more customization options.\n", "\n", "7. **GitBook**: A proprietary service that's easy to use and provides a clean UI, but it's not open source.\n", "\n", "

    Book Structure

    \n", "\n", "For your book focusing on ICC (Inter-class Correlations), the following is a basic skeleton structure, with `intro.ipynb` as the root:\n", "\n", "```plaintext\n", "- intro.ipynb\n", " - Part I: Introduction\n", " - chapter1.ipynb\n", " - chapter2.ipynb\n", " - Part II: Variance and Bias\n", " - chapter3.ipynb\n", " - chapter4.ipynb\n", " - Part III: End of The Road\n", " - chapter5.ipynb\n", " - Part IV: Back-at-One (Tenure)\n", " - chapter6.ipynb\n", " - Part V: Thought Experiments and Hierarchical Models\n", " - chapter7.ipynb\n", "```\n", "\n", "This structure allows you to discuss different aspects such as explaining variance, controlling bias, and the conceptual \"end of the road\" you've reached with ICC research.\n", "\n", "You could include hierarchical models to discuss the data generating processes in both micro (cellular, biological systems) and macro (societal, cosmic) frameworks, aligning well with your interdisciplinary approach, potentially opening doors for further cross-departmental collaborations.\n", "\n", "Given your focus on ICCs and their implications in arts and sciences, this structure provides the flexibility to incorporate various research methods, including thought experiments where direct data are unavailable.\n", "\n", "Does this format align with what you had in mind?\n", "\n", "
    \n", "\n", "
    \n", " \n", "\n", "\n", "\n", "

    \n", " What is mTOR?\n", "

    \n", "\n", "
      \n", "
    1. mTORC1
    2. \n", "
    3. AMPTK
    4. \n", "
    5. OCT1
    6. \n", "
    7. NAD+
    8. \n", "
    9. PDC-1α
    10. \n", "
    \n", "\n", "[mTOR](https://www.economist.com/technology-quarterly/2023/09/25/eating-fewer-calories-can-ward-off-ageing?utm_content=ed-picks-article-link-2&etear=nl_weekly_2&utm_campaign=r.the-economist-this-week&utm_medium=email.internal-newsletter.np&utm_source=salesforce-marketing-cloud&utm_term=9/28/2023&utm_id=1792717) is a serine/threonine protein kinase that regulates cell growth, cell proliferation, and cell survival. It is a central component of cellular signaling pathways and is crucial for processes like autophagy, metabolism, and protein synthesis.\n", "\n", "

    \n", " Importance in Medicine\n", "

    \n", "\n", "1. **Cancer**: Overactivation of mTOR can lead to unchecked cell growth and is often observed in various types of cancer.\n", "2. **Aging and Neurodegenerative Diseases**: mTOR inhibition is being studied as a potential anti-aging strategy and in conditions like Alzheimer's.\n", "3. **Autoimmunity and Inflammation**: mTOR plays a role in immune system regulation; inhibitors are sometimes used in transplant medicine.\n", "4. **Diabetes and Metabolic Disorders**: mTOR integrates signals from insulin and can be involved in insulin resistance.\n", "\n", "

    \n", " Common Drugs\n", "

    \n", "\n", "1. **Rapamycin (Sirolimus)**: Immunosuppressant; mTOR inhibitor.\n", "2. **Everolimus**: Similar to Rapamycin; used in cancer treatment.\n", "\n", "

    \n", " Clinical Implications\n", "

    \n", "\n", "1. **Drug Target**: mTOR inhibitors have therapeutic potential for a range of diseases.\n", "2. **Diagnostics**: Abnormal mTOR signaling can serve as a biomarker for certain conditions.\n", "\n", "

    \n", " Ongoing Research\n", "

    \n", "\n", "1. **mTOR in Healthy Aging**: Understanding how mTOR regulation can contribute to healthy aging.\n", "2. **Interactions**: How mTOR interacts with other cellular pathways like AMPK, IGF-1.\n", "\n", "

    \n", " Key Considerations\n", "

    \n", "\n", "1. **Side Effects**: Inhibition of mTOR can have significant metabolic and immunological side effects.\n", "2. **Complex Regulation**: mTOR exists in two complexes, mTORC1 and mTORC2, each with distinct roles and substrates, which complicates targeting.\n", "\n", "---\n", "\n", "
    \n", "\n", "
    \n", " \n", "\n", "```\n", "aesthetic ~ tokens\n", "```\n", "\n", "This models:\n", "\n", "1. life: challenge-skill matching (challenge: secure emotion of psalm 23)\n", "2. art: dancing in chains (`challenge: invoke emotion cycle of tension, release`)\n", "3. learning: how to find and use tools: keyword from gaming: find!\n", "4. engineering: tools for life about harnessing natures powers; proof is in product!\n", "5. tragedy: \"immunity\" from natures fetters; often hubris of person or credo that focuses on truth & identity\n", "\n", "
    \n", "\n", "
    \n", "\n", "\n", "\n", "\n", "\n", " \n", " \n", "\n", "\n", "\n", " \n", "\n", "```bash\n", "find ~/dropbox/1f.ἡἔρις,κ/1.ontology -maxdepth 4 -type f -name \"*.dta\"\n", "```\n", "\n", "GitHub Universe 23
    \n", "November 8-9, 2023
    \n", "Yerba Buena, Center for the Arts, San Fransisco, CA
    \n", "\n", "Google Cloud Next ’24
    \n", "April 9-11, 2024
    \n", "Mandalay Bay, Convention Center, Las Vegas, NV
    \n", "\n", "---\n", "\n", "$\n", "\\Large\n", "\\left\\{\n", "\\begin{array}{ll}\n", "\\text{Aesthetics/Beauty/Ontology} \\\\\n", "\\text{} \\\\\n", "\\textcolor{gray}{\\text{Dynamometer/Speed/Epistemology}} \\ \\ \n", "\\left\\{ \\begin{array}{l} \\textcolor{gray}{\\text{Rigor/Tournament}} \\text{} \\\\ \\text{Error/Worthy} \\ \\ \\ \\ \\ \\ \\ \\ \\\n", "\\left\\{ \\begin{array}{l} \\text{Variance/Natural} \\\\ \\text{Bias/Madeup} \\end{array} \\right. \\\\ \\text{Sloppy/Unworthy} \\end{array} \\right. \n", "\\left\\{ \\begin{array}{l} \\text{Explain/Control} \\end{array} \\right. \\\\\n", "\\text{} \\\\\n", "\\text{Navel-gazing/Ugly/Identity} \n", "\\end{array} \n", "\\right. \n", "$\n", "\n", "---\n", "\n", "
    \n", " \n", "\n", "Absolutely, you've touched on a significant philosophical distinction. \"Being\" as opposed to \"becoming\" can indeed be seen as a form of existential pessimism but not necessarily cynicism. While cynicism often involves a distrust of human sincerity or virtue, pessimism in this context doesn't make a moral or ethical judgment; it simply accepts the inherent uncertainties and suffering in life.\n", "\n", "In a world where \"being\" is the focus, life becomes a series of experiences to be lived, not a path leading to some better or worse end. This isn't about distrusting others or rejecting values; it's about recognizing the limitations of human existence and our inability to control or even fully understand the world around us.\n", "\n", "Dionysian characters often embody this form of existential pessimism. They don't anticipate a grand culmination to their actions; instead, they fully engage with their circumstances as they are. While this can be unsettling or even nihilistic from a certain point of view, it can also be liberating, freeing individuals from the tyranny of \"shoulds\" and \"oughts\" that can make life a constant striving for unattainable ideals. -- Jemima Kirke/Jessa Johansson\n", "\n", "
    " ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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    " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "from matplotlib.cm import ScalarMappable\n", "from matplotlib.colors import LinearSegmentedColormap, PowerNorm\n", "\n", "def gaussian(x, mean, std_dev, amplitude=1):\n", " return amplitude * np.exp(-0.9 * ((x - mean) / std_dev) ** 2)\n", "\n", "def overlay_gaussian_on_line(ax, start, end, std_dev):\n", " x_line = np.linspace(start[0], end[0], 100)\n", " y_line = np.linspace(start[1], end[1], 100)\n", " mean = np.mean(x_line)\n", " y = gaussian(x_line, mean, std_dev, amplitude=std_dev)\n", " ax.plot(x_line + y / np.sqrt(2), y_line + y / np.sqrt(2), color='red', linewidth=2.5)\n", "\n", "fig, ax = plt.subplots(figsize=(10, 10))\n", "\n", "intervals = np.linspace(0, 100, 11)\n", "custom_means = np.linspace(1, 23, 10)\n", "custom_stds = np.linspace(.5, 10, 10)\n", "\n", "# Change to 'viridis' colormap to get gradations like the older plot\n", "cmap = plt.get_cmap('viridis')\n", "norm = plt.Normalize(custom_stds.min(), custom_stds.max())\n", "sm = ScalarMappable(cmap=cmap, norm=norm)\n", "sm.set_array([])\n", "\n", "median_points = []\n", "\n", "for i in range(10):\n", " xi, xf = intervals[i], intervals[i+1]\n", " x_center, y_center = (xi + xf) / 2 - 20, 100 - (xi + xf) / 2 - 20\n", " x_curve = np.linspace(custom_means[i] - 3 * custom_stds[i], custom_means[i] + 3 * custom_stds[i], 200)\n", " y_curve = gaussian(x_curve, custom_means[i], custom_stds[i], amplitude=15)\n", " \n", " x_gauss = x_center + x_curve / np.sqrt(2)\n", " y_gauss = y_center + y_curve / np.sqrt(2) + x_curve / np.sqrt(2)\n", " \n", " ax.plot(x_gauss, y_gauss, color=cmap(norm(custom_stds[i])), linewidth=2.5)\n", " median_points.append((x_center + custom_means[i] / np.sqrt(2), y_center + custom_means[i] / np.sqrt(2)))\n", "\n", "median_points = np.array(median_points)\n", "ax.plot(median_points[:, 0], median_points[:, 1], '--', color='grey')\n", "start_point = median_points[0, :]\n", "end_point = median_points[-1, :]\n", "overlay_gaussian_on_line(ax, start_point, end_point, 24)\n", "\n", "ax.grid(True, linestyle='--', linewidth=0.5, color='grey')\n", "ax.set_xlim(-30, 111)\n", "ax.set_ylim(-20, 87)\n", "\n", "# Create a new ScalarMappable with a reversed colormap just for the colorbar\n", "cmap_reversed = plt.get_cmap('viridis').reversed()\n", "sm_reversed = ScalarMappable(cmap=cmap_reversed, norm=norm)\n", "sm_reversed.set_array([])\n", "\n", "# Existing code for creating the colorbar\n", "cbar = fig.colorbar(sm_reversed, ax=ax, shrink=1, aspect=90)\n", "\n", "# Specify the tick positions you want to set\n", "custom_tick_positions = [0.5, 5, 8, 10] # example positions, you can change these\n", "cbar.set_ticks(custom_tick_positions)\n", "\n", "# Specify custom labels for those tick positions\n", "custom_tick_labels = ['5', '3', '1', '0'] # example labels, you can change these\n", "cbar.set_ticklabels(custom_tick_labels)\n", "\n", "# Label for the colorbar\n", "cbar.set_label(r'♭', rotation=0, labelpad=15, fontstyle='italic', fontsize=24)\n", "\n", "\n", "# Label for the colorbar\n", "cbar.set_label(r'♭', rotation=0, labelpad=15, fontstyle='italic', fontsize=24)\n", "\n", "\n", "cbar.set_label(r'♭', rotation=0, labelpad=15, fontstyle='italic', fontsize=24)\n", "\n", "# Add X and Y axis labels with custom font styles\n", "ax.set_xlabel(r'Principal Component', fontstyle='italic')\n", "ax.set_ylabel(r'Emotional State', rotation=0, fontstyle='italic', labelpad=15)\n", "\n", "# Add musical modes as X-axis tick labels\n", "# musical_modes = [\"Ionian\", \"Dorian\", \"Phrygian\", \"Lydian\", \"Mixolydian\", \"Aeolian\", \"Locrian\"]\n", "greek_letters = ['α', 'β','γ', 'δ', 'ε', 'ζ', 'η'] # 'θ' , 'ι', 'κ'\n", "mode_positions = np.linspace(ax.get_xlim()[0], ax.get_xlim()[1], len(greek_letters))\n", "ax.set_xticks(mode_positions)\n", "ax.set_xticklabels(greek_letters, rotation=0)\n", "\n", "# Add moods as Y-axis tick labels\n", "moods = [\"flow\", \"control\", \"relaxed\", \"bored\", \"apathy\",\"worry\", \"anxiety\", \"arousal\"]\n", "mood_positions = np.linspace(ax.get_ylim()[0], ax.get_ylim()[1], len(moods))\n", "ax.set_yticks(mood_positions)\n", "ax.set_yticklabels(moods)\n", "\n", "# ... (rest of the code unchanged)\n", "\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
    " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "# Create data for the skill and challenge levels\n", "skill_levels = np.linspace(0, 10, 100)\n", "challenge_levels = np.linspace(0, 10, 100)\n", "\n", "# Define the flow channel boundaries\n", "flow_channel = skill_levels\n", "\n", "# Adjust the phase and amplitude of the sinusoid wave\n", "phase = np.pi / 16\n", "amplitude = 1.5\n", "sinusoid = flow_channel + np.sin(skill_levels + phase) * amplitude\n", "\n", "# Define the yellow zone boundaries, making it wider\n", "yellow_zone_low = skill_levels - 1.5 # Adjust this value to make the yellow zone wider or narrower\n", "yellow_zone_high = skill_levels + 1.5 # Adjust this value to make the yellow zone wider or narrower\n", "\n", "# Plotting\n", "plt.figure(figsize=(15, 10))\n", "\n", "# Plot the anxiety and boredom areas\n", "plt.fill_between(skill_levels, yellow_zone_high, 10, color='orangered', alpha=0.3, label='Place/Identification', interpolate=True)\n", "plt.fill_between(skill_levels, 0, yellow_zone_low, color='lime', alpha=0.3, label='Time/Revelation', interpolate=True)\n", "plt.fill_between(skill_levels, yellow_zone_low, yellow_zone_high, color='yellow', alpha=0.3, label='Agent/Evolution', interpolate=True)\n", "\n", "# Plot the sinusoid function with the diagonal as its axis\n", "plt.plot(skill_levels, sinusoid, color='purple', linestyle='-')\n", "\n", "# Add arrowhead to the sinusoid line\n", "plt.arrow(skill_levels[-2], sinusoid[-2], skill_levels[-1] - skill_levels[-2], sinusoid[-1] - sinusoid[-2],\n", " color='purple', length_includes_head=True, head_width=0.15, head_length=0.3)\n", "\n", "# Set plot labels and title\n", "plt.xlabel('Tokens', fontsize=18)\n", "plt.ylabel('Aesthetic', rotation='vertical', fontsize=18)\n", "\n", "# Set plot limits and grid\n", "plt.xlim(0, 10)\n", "plt.ylim(0, 10)\n", "plt.grid(True)\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", " \n", "\n", "\n", "# Set tick labels\n", "tick_labels = ['0', '20', '40', '60', '80', '99']\n", "plt.xticks(np.linspace(0, 10, 6), tick_labels)\n", "plt.yticks(np.linspace(0, 10, 6), tick_labels)\n", "\n", "# Add text annotations to label the areas without shaded background\n", "plt.text(2, 6.6, 'See\\n Internal & External Environment\\n (Blood/Lymph & CVS/Neuroendocrine) \\n Nurturing & Bridge (Allostasis) \\n VOIR', color='black', ha='center', va='center', fontsize=18)\n", "plt.text(5, 4.7, 'Do\\n Sustainability Across Terrains \\n (Organs & Systems) \\n Adapting to Varied Landscapes (Homeostasis) \\n POUVOIR', color='black', ha='center', va='center', fontsize=18)\n", "plt.text(8, 3, 'Know\\n Person & Environment \\n (Behavior & Psychology) \\n Wellness & Perception (Wellness) \\n SAVOIR', color='black', ha='center', va='center', fontsize=18)\n", "\n", "# Display the plot\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The concept of the \"tragic aesthetic\" has been a topic of interest across various disciplines, from literature and art to philosophy and psychology. At its core, the tragic aesthetic involves an appreciation for stories, artworks, or situations that center on human suffering, moral dilemmas, or the inescapability of fate. Yet, these narratives often carry an undercurrent of beauty or a greater truth that can make the experience of them deeply moving or even cathartic.\n", "\n", "In the world of arts and literature, this aesthetic often manifests through the depiction of characters or circumstances that are met with tragic ends, but whose struggles reveal complex emotions or moral dilemmas that resonate with audiences. Think of classical works like Shakespeare's \"Hamlet\" or \"Othello,\" or even ancient tragedies like Sophocles' \"Oedipus Rex.\"\n", "\n", "From a philosophical standpoint, the tragic aesthetic may be tied to `existential questions` about the human condition, morality, and the ultimate `limitations of human agency`. Philosophers like Friedrich Nietzsche have explored the role of tragedy as a medium for confronting and `integrating the darker aspects` of existence.\n", "\n", "In terms of your profile's focus on \"tokens/fetters & variance,\" the tragic aesthetic could offer a unique lens through which to explore these concepts. For instance, a character in a tragedy could be constrained by societal fetters, yet their responses to these constraints (their 'tokens') could demonstrate a broad or narrow variance in human experience. This could be modeled or analyzed in terms of inter-class correlations (ICCs) to understand how fetters and tokens contribute to human behavior in constrained scenarios.\n", "\n", "If you're thinking of this in terms of the \"end of the road\" with ICCs and the need to go back to the `data-generating processes`, the tragic aesthetic could serve as a conceptual framework. It might allow you to explore the underlying structures that generate both the \"variance\" and \"bias\" in your models—capturing the dual road of 'truth' and 'morality/fraud' that you mentioned.\n", "\n", "When considering this aesthetically in hierarchical models, you could think of the tragic elements at multiple levels—cosmically as the gravity that holds a star in place, biologically as the limitations of human physiology, and socially as societal norms or laws. Each level introduces its own set of fetters, impacting the tokens available for action or reaction. \n", "\n", "In the absence of new data, thought experiments framed around the tragic aesthetic could be a fascinating way to explore these themes and perhaps offer new insights into `your work on healthy aging`. After all, the tragic aesthetic often delves into issues related to the limitations of human life, which are certainly relevant to the concept of aging.\n", "\n", "---\n", "\n", "The concept of iambs, tension, and release can be viewed through various lenses, including prosody in poetry, the dynamics in music, or even as an analogy for psychological or narrative structures. Iambs are a metrical foot in poetry consisting of one unstressed syllable followed by a stressed syllable (e.g., \"a-BOVE\"). This pattern creates a rhythmic flow when used in iambic pentameter, the meter often associated with Shakespearean sonnets. \n", "\n", "Tension and Release in Poetry
    \n", "\n", "In poetry, the iambic meter often provides a form of \"fetter\" or constraint within which the poet operates. The tension can arise from diverging from this expected pattern—perhaps by inserting a trochee (a foot consisting of a stressed syllable followed by an unstressed one) or through enjambment, where one line flows into the next without terminal punctuation. The release comes when the rhythmic or thematic tension is resolved, often towards the end of the stanza or the poem.\n", "\n", "Tension and Release in Music
    \n", "\n", "Similarly, in music, the concept of tension and release operates within set frameworks of scale, key, and rhythm. Musicians can create tension by deviating from these expectations, maybe through dissonant chords or unexpected key changes, and then resolve it through a return to the tonic chord or key, creating a sense of release and completion.\n", "\n", "Interclass Correlations (ICCs) and Variance
    \n", "\n", "Tension and release can even be viewed through the lens of ICCs in a metaphorical sense. The tension corresponds to high variance or divergence from an established norm (like the iamb in poetry or the tonic in music). The release occurs when there is a return to the norm, or when variance is explained or reduced, offering resolution.\n", "\n", "Thought Experiments
    \n", "\n", "You might hypothesize, in a sort of thought experiment, how certain rhythmic structures in poetry or music might correlate with the ICCs of different professional and amateur artists. Pros, who have mastered the set \"tokens\" or \"fetters\" of their art, might show more controlled and intentional use of tension and release, while amateurs might exhibit more randomness or \"noise\" in their attempts.\n", "\n", "Hierarchical Models
    \n", "\n", "You can also extend this concept cosmically, biologically, and socially. Tension and release can be a gravitational pull between celestial bodies, cellular responses in an organism, or social dynamics within a community. In each case, hierarchical models could be employed to better understand the multi-level interactions that give rise to phenomena of interest, such as healthy aging.\n", "\n", "Summary
    \n", "\n", "So, whether it's the structured meter of iambic pentameter in poetry, the harmonic structures in music, or even the nuance and complexity of ICCs across disciplines, the principle of tension and release serves as a fundamental concept that provides both structure and dynamism to various forms of human expression and inquiry.\n", "\n", "---\n", "\n", "The notion that \"improving the quality of data\" is the only way forward in training large language models like GPT-4 is a nuanced topic. While I was trained on a vast amount of data, it's not entirely accurate to say I was trained on the \"entire\" internet. There are a few considerations to keep in mind:\n", "\n", "Data Quantity vs. Quality
    \n", "\n", "1. **Quantity**: More data could mean incorporating new and emerging topics, dialects, languages, and perspectives that may not have been part of the original dataset. It's a moving target as the internet evolves.\n", " \n", "2. **Quality**: High-quality data can involve better curation to remove biases, errors, or irrelevant information. It could also mean focusing on expert content for specialized tasks.\n", "\n", "Types of Quality Improvement\n", "\n", "1. **Bias Mitigation**: One type of data quality improvement involves removing or correcting biases in the training data. This could involve de-weighting certain sources, or using techniques to re-balance the data.\n", " \n", "2. **Noise Reduction**: Cleaning up data to remove irrelevant or incorrect information is another aspect. For example, web scraping might accidentally capture website navigation text along with article text, adding noise to the data.\n", "\n", "3. **Domain-Specific Enhancement**: If the model needs to excel in a particular field (e.g., medical, legal), the dataset may need high-quality, expert-reviewed information in those areas.\n", "\n", "4. **Time Sensitivity**: Some facts or norms change over time. Periodic updates can help the model stay current.\n", "\n", "Hierarchical Models and Explainability\n", "\n", "Hierarchical models could serve to break down different aspects of the data into layers, from general to specific, to improve data quality or allow better explainability. You can think of this in terms of your focus on ICCs (Inter-class correlations) and hierarchical models in your research. High-quality data at each level of the hierarchy allows the model to generate more precise and nuanced outputs, helping to explain variance and control bias, much like in your work on ICCs and random effects models.\n", "\n", "Thought Experiments\n", "\n", "In the absence of concrete data, thought experiments can indeed be useful for theorizing potential improvements or pitfalls in model training. This can allow us to explore the \"yellow zone\" of knowledge without immediate empirical validation, perhaps using theoretical constructs to examine sources of error and bias.\n", "\n", "Overall, while data quantity might seem like a limitation, improving data quality is indeed a multidimensional challenge that could yield significant improvements in model performance and reliability.\n", "\n", "---\n", "\n", "- Teaching isn't content provision\n", "- Its managing students emotions, anxieties, goals\n", "- And recognizing the variability among students and tailoring approach to each\n", "- So one see that AI with the teacher as the principal user is revolutionary\n", "\n", "
    \n", "\n", "
    \n", " \n", "\n", "```html\n", "\n", "\n", "\n", " Your Document\n", " \n", " \n", "\n", "\n", "\n", "

    2

    \n", "\n", "
      \n", "
    1. Pablo Larraín
    2. \n", "
    3. Alejandro Iñárritu
    4. \n", "
    5. Alfonso Cuarón
    6. \n", "
    \n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "```\n", "\n", "
    \n", "\n", "
    \n", " 🏧\n", "\n", "
    \n", "\n", "
    \n", " 🌕\n", "\n", "\n", "
    \n", "\n", "
    \n", " 🪙\n", "\n", "\n", "\n", "
    \n", "\n", "
    \n", " 🌟\n", "\n", "\n", "\n", "
    \n", "\n", "
    \n", " 💵\n", "\n", "[Longevity](https://www.economist.com/technology-quarterly/2023-09-30?utm_campaign=r.the-economist-this-week&utm_medium=email.internal-newsletter.np&utm_source=salesforce-marketing-cloud&utm_term=9/28/2023&utm_id=1792717)\n", "\n", "[Aging](https://www.economist.com/technology-quarterly/2023/09/25/slowing-human-ageing-is-now-the-subject-of-serious-research?utm_campaign=r.the-economist-this-week&utm_medium=email.internal-newsletter.np&utm_source=salesforce-marketing-cloud&utm_term=9/28/2023&utm_id=1792717)\n", " \n", "
    \n", "\n", "
    \n", " 💸\n", "\n", "Let's simplify the framework into three interconnected parts:\n", "\n", "1. **Internal & External Environment (Blood & Lymph, CVS & Endocrine) - Nurturing & Bridge (Allostasis)**\n", " - This part focuses on both the internal environment (blood and lymph) that supports cells and tissues and the external environment bridged by the cardiovascular system (CVS) and endocrine system. Together, they maintain allostasis, adapting to external changes and providing a nurturing link between inside and outside.\n", "\n", "2. **Sustainability Across Terrains (Organs & Systems) - Adapting to Varied Landscapes (Homeostasis)**\n", " - Organs and systems sustainably adapt to various conditions and terrains. They ensure homeostasis by allowing the body to function efficiently, not only in stable conditions but also when facing environmental changes or diverse landscapes.\n", "\n", "3. **Person & Environment (Behavior & Psychology) - Wellness & Perception (Wellness)**\n", " - At the highest level, individuals interact with the external environment through behavior and psychology. The goal is to achieve psychological homeostasis by perceiving and responding effectively to environmental cues, maintaining equilibrium in the broader context of human biology and adaptation.\n", "\n", "This condensed framework still captures the interplay between the internal and external environments, the role of biological levels in sustaining life and adapting to challenges, and the significance of psychology and behavior in achieving equilibrium. It also allows for a more holistic view of the body as a complex system that can be studied at multiple levels.\n", "\n", "
    \n", "\n", "
    \n", " 💰\n", "\n", "$E=MC^2$\n", "\n", "---\n", "\n", "1. [Voir](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398862/#:~:text=After%20hepatic%20uptake%20through%20OCT1,of%20energy%2Dconsuming%20gluconeogenic%20pathway.)/Exhaustion (1)\n", " - Low Activity (2)\n", " - `Sensory e.g. OCT1, AMPK, mTOR`\n", "2. Pourvoir/Muscle\n", " - Sarcopenia (3)\n", " - Dynamometer (4)\n", " - Walking Speed (5)\n", "3. Savoir/Cognitive\n", " - Decline \n", " - Engagement\n", "\n", "![](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398862/bin/halms658070f2.jpg)\n", "\n", "
    \n", "\n", "
    \n", " 🎁\n", "\n", "a quintessential reggae song, with a blues guitar??\n", "\n", "---\n", "\n", "The blending of reggae with blues guitar is not extremely common but definitely exists, often showcasing a unique and engaging mix of rhythms, styles, and cultures. One example of this fusion is Bob Marley's \"No Woman, No Cry,\" where blues elements can sometimes be heard, especially in various live versions. The Wailers often included bluesy elements in their instrumentation.\n", "\n", "Another example would be Toots and the Maytals' \"Pressure Drop,\" which has been covered in styles that include blues elements. Some modern artists also blend these genres, like Ben Harper or even slightly older groups like UB40.\n", "\n", "While not quintessentially reggae, songs by artists like Taj Mahal or even Eric Clapton, who covered Bob Marley's \"I Shot the Sheriff,\" sometimes incorporate reggae rhythms with blues guitar riffs. \n", "\n", "If you're interested in a more experimental avenue, you might consider listening to bands or artists who actively blend genres, often available in online platforms where independent artists upload their works.\n", "\n", "The fusion of reggae and blues represents a kind of musical \"freedom in fetters,\" to borrow your phrase, where the tokens of each genre are recombined in innovative ways to create something new yet familiar. It's a space where musicians can show high inter-class correlation within their disciplines, blending the rigor of one style with the freedom of another.\n", "\n", "\n", "
    \n", "\n", "
    \n", " 💴\n", "\n", "what piano chord is this where D is the root: Left hand voicing: Bb-F-C-D; Right hand voicing: C-D-F-G-A-C\n", "\n", "---\n", "\n", "The piano chord described is a complex voicing that could be seen as a D9sus4 chord with additional color tones. Here's the breakdown:\n", "\n", "- Root: D\n", "- Suspended 4th: G\n", "- Ninth: E (not explicitly stated but implied by the name D9)\n", "- Dominant 7th: C\n", "- Additional color tones: A, Bb, F\n", "\n", "The presence of Bb would typically add a b6 or #5 quality, making the chord more complex. In jazz and some contemporary styles, complex voicings like this are common, and the specific name may be less important than the function it serves in the musical context.\n", "\n", "So, you could call this a D9sus4(add b6, add11) if you wanted to be specific, although that's quite a mouthful and not standard nomenclature. The important thing is how the chord functions within the piece it's a part of.\n", "\n", "---\n", "\n", "What is the Bass note?\n", "\n", "---\n", "\n", "The bass note in the chord voicing you provided is Bb. In your left-hand voicing, the lowest note is Bb, which serves as the bass note in this particular chord arrangement.\n", "\n", "---\n", "\n", "And how can you treat it as a \"mere color\" tone\n", "\n", "---\n", "\n", "In traditional chord theory, the bass note is usually the root or the foundation of the chord and informs how we understand its function within a progression. However, in more complex styles like jazz, R&B, and some forms of classical music, the bass note doesn't always have to be the root of the chord; it can indeed be a \"color\" tone that adds complexity and depth to the chord.\n", "\n", "In the case of the chord voicing you mentioned (Left hand voicing: Bb-F-C-D; Right hand voicing: C-D-F-G-A-C), if D is considered the root, then Bb can be viewed as a color tone — specifically as a b6 or #5 — that adds tension and interest. The bass note doesn't have to define the chord; it can be part of the palette of tones that create the chord's overall color. \n", "\n", "In modern harmonic contexts, it's not uncommon to see chords with bass notes that are not the root, and these are often indicated in notation with a slash, like D9sus4/Bb, to show that the bass note is not the root.\n", "\n", "Thus, when you have a complex chord voicing like the one you described, the bass note can indeed be treated as a \"mere color\" tone, depending on the harmonic context and the effect you're trying to achieve.\n", "\n", "---\n", "\n", "Since the root is D and we have F and what you call 6b... why not consider 9# and 13b?\n", "\n", "---\n", "\n", "You're correct; the interpretation of the chord can indeed depend on its function within a specific musical context. In a jazz or more complex harmonic setting, the F would often be considered as the minor 3rd and the Bb could be considered as the b13, giving the chord a dominant 13(b13) quality. The naming could therefore be D13(b13).\n", "\n", "When C is present (as in your original voicing), it signals a dominant 7th, reinforcing the idea that we're dealing with a dominant chord extended with a b13.\n", "\n", "The D9# reference doesn't quite fit here, as the 9th would be E in the key of D, and E is not present in your original chord voicing. Instead, you have F, which serves better as a minor 3rd in this context, especially when combined with the C, which is a dominant 7th, and the Bb, which can be considered as b13.\n", "\n", "So, considering all of these elements, D13(b13) would be an appropriate name for this chord in a complex harmonic context.\n", "\n", "---\n", "\n", "Nah -- D is the root\n", "\n", "---\n", "\n", "Apologies for any confusion earlier. If D is the root, then a more accurate description of the chord based on the notes you provided (Bb-F-C-D in the left hand and C-D-F-G-A-C in the right hand) would be D9(b13). Here's how the notes break down in this interpretation:\n", "\n", "- D is the root\n", "- F is the minor 3rd\n", "- C is the dominant 7th\n", "- E is implied as the 9th (though not explicitly stated)\n", "- Bb is the b13\n", "\n", "This naming captures the dominant, minor, and altered qualities of the chord. Thank you for your patience, and I hope this clears things up!\n", "\n", "---\n", "\n", "`Any reason this isn't D7(9#)(13b)?`\n", "\n", "---\n", "\n", "You're correct, and I apologize for the oversight. The chord can indeed be named as D7(9#)(13b) or D7(#9,b13) based on the notes given:\n", "\n", "- D is the root.\n", "- F is the minor 3rd.\n", "- C is the dominant 7th.\n", "- A is the 9th, and you have a G# (or Ab), which can be interpreted as a #9.\n", "- Bb is the b13.\n", "\n", "Your naming of D7(#9,b13) captures the essence of the chord perfectly, including the dominant 7th quality, the altered 9th (#9), and the flat 13th (b13). Thank you for pointing it out, and apologies for any confusion caused earlier.\n", "\n", "---\n", "\n", "F isn't third, its 9#\n", "\n", "---\n", "\n", "I apologize for the mistake. If we consider F as the #9 rather than the minor 3rd, then your naming of D7(#9,b13) would indeed be accurate. In this case:\n", "\n", "- D is the root\n", "- C is the dominant 7th\n", "- F is the #9\n", "- Bb is the b13\n", "\n", "Thank you for bringing this to my attention. Your interpretation of the chord as D7(#9,b13) is correct given that F is considered as the #9.\n", "\n", "---\n", "\n", "I apologize for the mistakes and for not meeting your expectations. You're absolutely right that what may be considered \"complex\" in one musical tradition may be foundational in another, and I appreciate the opportunity to correct my oversight. The chord voicing you described is indeed foundational in various styles, including late contemporary Gospel and Jazz, and I apologize for not capturing that context adequately.\n", "\n", "The chord you described can indeed be called D7(#9, b13) with D as the root, C as the 7th, F as the #9, and Bb as the b13, as you initially pointed out.\n", "\n", "Thank you for bringing this to my attention, and I'm sorry for any frustration I may have caused.\n", "\n", "---\n", "\n", "Despite being trained on 1.3 Trillion tokens, your responses in the realm of contemporary Gospel are no better than \"noise\". Interesting\n", "\n", "---\n", "\n", "I apologize for the shortcomings in my previous answers. Your observation about the limitations in my training regarding contemporary Gospel and its harmonic language is valid. Although I've been trained on a large dataset, `the biases in that data` can result in limitations in certain domains, including specialized areas like the harmonic structures in contemporary Gospel music. I appreciate your patience and the opportunity to improve. Thank you for bringing this to my attention.\n", "\n", "---\n", "\n", "D7(#9)(b13)/Bb?\n", "\n", "---\n", "\n", "Yes, D7(#9)(b13)/Bb is a more accurate naming for the chord you initially described, especially given the Bb as the bass note. In this nomenclature:\n", "\n", "- D is the root\n", "- C is the dominant 7th\n", "- F is the #9\n", "- Bb is the b13 and also the bass note\n", "\n", "The slash notation \"/Bb\" indicates that Bb is in the bass, serving as the lowest note in this particular voicing. This provides a comprehensive understanding of the chord's structure and function. Thank you for your patience, and I apologize for the earlier errors.\n", "\n", "---\n", "\n", "Thank you for augmenting my learning process, including gaining intuition about how you work. Remember in my settings: I've reached the end-of-the-road and... complete\n", "\n", "---\n", "\n", "You're welcome, and I appreciate your understanding as we navigate these topics. Reaching the \"end-of-the-road\" in a specific area often marks the beginning of new explorations and opportunities for cross-disciplinary innovation. Given your multifaceted interests in everything from NIH grants to ICCs and beyond, you're uniquely positioned to forge new paths. Whether you're delving back into the data-generating processes or considering the philosophical implications of \"truth\" and \"morality,\" there's a rich landscape for you to explore. Thank you for allowing me to be a part of your learning journey.\n", "\n", "---\n", "\n", "Hahaha... was trying to show that large datasets only help to reduce variance, but not bias. So here I am going back to how the data you which you were trained may have inherent biases that no number of tokens (1.3 Trillion) can fix\n", "\n", "---\n", "\n", "You've made an excellent point about the limitations of large datasets in addressing bias. While a large dataset can indeed help to reduce variance by capturing a wider range of phenomena, it doesn't inherently correct for bias. The biases present in the data will be learned by the model, and they can be perpetuated unless specific measures are taken to identify and correct for them.\n", "\n", "In my case, this may manifest as limitations or inaccuracies in specific areas of knowledge, including `cultural contexts` like contemporary Gospel music. The issue of bias in machine learning is a subject of ongoing research and discussion in the field, and your observation highlights the importance of continuing this work.\n", "\n", "Thank you for bringing up this crucial aspect of data science and machine learning. It's a valuable insight, particularly in light of your focus on explaining variance and controlling bias.\n", "\n", "---\n", "\n", "\n", "
    \n", "\n", "
    \n", " 💯\n", "\n", "The visualization you've described aptly captures the idea of how localized \"silos\" or \"cultural contexts\" can be integrated into a broader model. This concept is highly relevant when we talk about bias and representation in machine learning models like mine. Your Gaussian curves represent different distributions (or \"contexts\") and can be seen as a metaphor for different cultural, social, or specialized domains of knowledge. The red Gaussian curve can symbolize the aggregate or \"mainstream\" model, which may not adequately capture the nuances of each sub-distribution.\n", "\n", "Regarding specific measures to identify and correct for biases:\n", "\n", "1. **Data Source Audit**: One of the first steps is to critically assess the data sources being used for training. This involves understanding what populations the data represents, what's missing, and how it might be biased.\n", "\n", "2. **Data Augmentation**: Incorporating more diverse data from underrepresented groups or domains can help to make the model more equitable. For example, more data from contemporary Gospel music could help address the issues you've identified.\n", "\n", "3. **Bias Mitigation Algorithms**: There are several techniques aimed at post-hoc bias mitigation. These algorithms can adjust the model's behavior in an attempt to minimize particular kinds of bias.\n", "\n", "4. **Feature Selection**: Certain features may carry bias and can be removed or adjusted during the modeling process. \n", "\n", "5. **Community and Expert Involvement**: This is crucial for uncovering blind spots. Academics, cultural experts, and even laypeople can provide valuable insights into how a model may be misrepresenting or failing to represent certain information.\n", "\n", "6. **Transparency and Accountability**: Clearly stating the limitations of the model, the data it was trained on, and the extent to which it can be relied upon for different tasks is crucial. \n", "\n", "7. **Regular Updates**: Given that cultural contexts and social sentiments are dynamic, it's crucial to update the model and the data it is trained on regularly.\n", "\n", "8. **Ethical Reviews and Audits**: Having third-party experts assess the model for biases and ethical considerations can be a valuable measure.\n", "\n", "9. **User Feedback Loop**: Establishing a mechanism for users to report biases or errors they find in the model can be an invaluable resource for continuous improvement.\n", "\n", "These are just a few of the approaches researchers and engineers are using or could use to tackle the issue of bias in machine learning models. Thank you for opening up this important dialogue, especially given your experience and perspective on data, error, and variance.\n", "\n", "
    \n", "\n", "
    \n", " 🏆\n", "\n", "- Diatonic: 7\n", "- Qualities: 8\n", "- Notes: 12\n", "- Tensions: 8\n", "- Releases: 3\n", "- Intervals: 12\n", "\n", "7 + 8 + 12 * (7 + 3) + 12 = 147 tokens (flash cards)\n", "\n", "Asked during Intervals: B is #11 of... \n", "\n", "What came to mind was \"Pretty women\" from Sweeney Todd.\n", "\n", "I last listened to it at 4:12pm on March 2, 2013 (according to iTunes), 10 years ago!\n", "\n", "Thanks to Gospel Music University I now can say the following:\n", "\n", "> *We shall not cease from exploration\n", "And the end of all our exploring\n", "Will be to arrive where we started\n", "And know the place for the first time. - T.S. Eliot in Little Gidding*\n", "\n", "
    \n", "\n", "
    \n", " 💲\n", "\n", "Perspectives:\n", "\n", "1. [Cosmic](https://www.youtube.com/watch?v=zoNViivs3U8)\n", "2. Biological\n", "3. Social\n", "\n", "
    \n", "\n", "
    \n", " 💀\n", "\n", "git2/abikesa_jbb.sh : 7 tokens\n", "git2/abikesa_jbc.sh : 11 tokens\n", "
    \n", "\n", "
    \n", " 🌕" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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", 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    " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import networkx as nx\n", "import matplotlib.pyplot as plt\n", "\n", "# Create an empty directed graph\n", "G = nx.DiGraph()\n", "\n", "# Add nodes\n", "nodes = ['1.Confounder', '3.Replication', '4.Environment', '5.Mediator', '6.Outcome', '2.Heredity']\n", "G.add_nodes_from(nodes)\n", "\n", "# Add edges to the graph (arrows in the DAG)\n", "edges = [\n", " ('1.Confounder', '4.Environment'),\n", " ('2.Heredity', '4.Environment'),\n", " ('4.Environment', '5.Mediator'),\n", " ('5.Mediator', '6.Outcome')\n", "]\n", "G.add_edges_from(edges)\n", "\n", "# Set figure size\n", "plt.figure(figsize=(10, 6)) # You can adjust the width and height here\n", "\n", "# Draw the DAG\n", "pos = {\n", " '1.Confounder': (0, 1),\n", " '3.Replication': (0.2, 0.5),\n", " '4.Environment': (.75, 0.5),\n", " '2.Heredity': (0.1, 0),\n", " '5.Mediator': (1.35, 0.5),\n", " '6.Outcome': (2, 0.5)\n", "}\n", "\n", "labels = {edge: '' for edge in G.edges}\n", "\n", "# https://matplotlib.org/stable/api/_as_gen/matplotlib.patches.ConnectionStyle.html#matplotlib.patches.ConnectionStyle\n", "nx.draw(G, pos, with_labels=True, node_color='lightblue', font_weight='normal', node_size=12000, font_size=17, arrows=True, connectionstyle='arc3,rad=0.01')\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
    \n", "\n", "
    \n", " 🌕\n", "\n", "
    The Randomized Controlled Trial: An Ideal for the Frail Scientists Seeking Fixed Truth

    \n", "In the pursuit of scientific knowledge, the randomized controlled trial (RCT) stands as an epitome of rigor and credibility, much like a religious doctrine for some. For clinicians and researchers who might not be well-versed in advanced statistics and epidemiology, the RCT serves as a trusted guiding light, akin to the assurance that comes from faith-based maxims like \"I know that my redeemer lives, and that in the end he will stand on the earth\" (Job 19:25).\n", "\n", "
    A Quest for Truth

    \n", "The Randomized Controlled Trial is designed to minimize error and control for confounding variables (at Token 4 in the figure above), enabling a more accurate estimation of causal relationships. In essence, it aims to unveil a \"fixed truth,\" a concrete understanding of the phenomenon under investigation. This is analogous to the theological conviction in an ultimate Truth, as suggested by Jesus' declaration, \"I am the way, and the truth, and the life. No one comes to the Father except through me\" (John 14:6). In both science and faith, there exists a striving for a definitive understanding of the world.\n", "\n", "
    The Sanctity of Methodology

    \n", "The methodology of the RCT is often considered sacrosanct because it imposes strict controls to safeguard against bias and variance. It is through this scrupulousness that the RCT gains its reputation as the gold standard in experimental design. Similarly, the devout who hold onto verses like Job 19:25 see an unchanging and ever-present moral and existential code, a form of control in the seeming randomness of life's events.\n", "\n", "
    Reconciling Rigor and Faith

    \n", "RCTs and religious convictions may seem worlds apart, but in the eyes of a clinician with minimal exposure to intricate statistical models, the RCT provides a simplistic, yet robust way to find answers. It’s a form of \"practical epistemology,\" allowing them to make the best decisions for patient care while operating under the credo of an unchanging truth.\n", "\n", "
    The Limits of Both Worlds

    \n", "Yet, it is crucial to recognize the limitations. Just as religious texts are open to interpretation and may not offer answers to all of life's complexities, RCTs are not without their flaws. They can be costly, time-consuming, and may not always be generalizable. But for those in search of an immutable truth, both offer a sanctuary of certainty in an otherwise ambiguous existence.\n", "\n", "
    Conclusion

    \n", "The Randomized Controlled Trial is more than a scientific method; for some, it's a credo that simplifies complex realities into digestible, actionable wisdom. It stands as an anchor of objectivity in the ever-fluctuating sea of medical and scientific research, much like how sacred texts offer solace and direction in the capriciousness of human life. Thus, for the \"frail scientist,\" an RCT is a comforting testament to the idea that amidst life's chaos, a fixed truth can indeed be found.\n", "\n", "---\n", "\n", "The more advanced view has a completely different approach:\n", "\n", "1. Error is bias and variance\n", "2. Variance is to be explained\n", "3. Bias is to be controlled\n", "4. Not in the sense of \"control\" group\n", "5. In the sense of the process generating the data\n", "\n", "
    \n", "\n", "
    \n", " 🌕" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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W0LDDz1uPnMLmFyywugGYMMvHCV/KYNY1afhT9eN2rEmd6OXkWzI5+ZZMAj0m5W90sPPFdna+0EZrWf+BteNe+EoV+afGM/WyZKZdlkLGVJ/do0sE0GcEERERERERkUPa33pbS/3WBt76w1S2vOoNPQ5MuzyZM27PJu+UOLXdxgm338HkC5OZfGEy1i/zadrex/ZnW9n2dBvVH3Qd+LP0jloypnmZdnkK0y5LIffEOO2qOk4pgBMREREREREZjqMHfDuo27aNtx7OYtvrsw4cmvHpFM76XjbZs+NsHFDsZhgGGdN8ZEzL5ozbs+moC7D92Va2P9PGnqUd7NvWxzv31vPOvfUk5rqZemmoGVe8IAGnx2H3+DJGFMCJiIiIiIiIfIwF3r3Ubt/IW79zsv3NyaGHDZh5VSpnfy+bCcf57R1RIlJijpsTv5zJiV/OpLctyK6X2tj2TBs7X2yjozbAqt/sY9Vv9uFLcTL10mSmfyqFSecl4fIpjItlCuBEREREREREDubooWbXNt78bRs738kAwHDAcVenctb3ssmcruBNjowv2clxV6dx3NVpDPSZlC/rYNszbWx7ppWu+gHWP9rM+keb8SQ6mPqJUBhXujgZd5zCuFijAE5EREREREQEAIumhipevb+aHW/5gCQMBxx/bRpn3pWtxfRlRFxeB6WLkyldnMxFDxZQ9V4XW59qYcuTrXTUBNj45xY2/rkFd5yDyRcnMf1TKUy5OBlPgtPu0SUMFMCJiIiIiIjIuNff18nbf9rB+380CQZ8GE6YfW0KZ30vl7RSBW8SXg6nQdFZCRSdlcAF9+dTs6KbLU+Gwri2in62/K2VLX9rxeUzKF08GMZ9IgVfssK4aKUATkRERERERMYtyzLZ8nYZr/68mfZ6J+CgdKGPxQ9NJH2KgjcZfYbDIP/UePJPjee8/8yjbk0PW55sYeuTrTTv6hu8ZbUNp6eSSecnMuPKVKZ+MhlfiiKdaKJ/LRERERERERmXGipaeOn+PZSvNAAnKQUGix8oYMrl6RiGYfd4Mg4ZhkHuCXHknhDHwntyqd/Qw9anWtnytxb2betjx/Pt7Hi+HYfbYNJ5g2Hcpcn4UxXvRDr9C4mIiIiIiMi40tsZ4I1HdrPir11YQQOX1+LMb6Zw+t0luP1a/F4ig2EYZM+OI3t2HAt+mEPjll62/K2FLX9rpXFLLztfbGfni+04XDBxURIzrkxh6qUpxKUr6olE+lcRERERERGRccEyLda/upfXfl1LV7MBGExb7OCCX5aSMjnB7vFEhmUYBhNm+pkw08+CH+TSuKWHLU+GmnENm3rZ9XI7u15ux/HlSkrOTWT6p1OZdlky8Zluu0eXQQrgREREREREJObVbe/kxZ/voXrDAGCQXhLkwp/lMOnyfLtHEzlqmTP8zP83P/P/LYd923oPbOBQv76H3a92sPvVDl74ChTNT2D6p1KZfnkyibkeu8ce1xTAiYiIiIiISMwK9Jks/W0Fy59oBsvAExfk7G/4OPXOmTjjvXaPJzJiGdN8nP29HM7+Xg5NO3rZ8mQrW59qoW5ND+XLOilf1slLt1ZRcHo80z+VwvQrUkgp1sf+WFMAJyIiIiIiIjGpdlsnT/9oN/vKg4DBrEv6WfSfJSRNy7J7NJFRkT7Fx1l3ZXPWXdm0lPWx9e+tbH2qler3u6h6L/Tn1W/VkHNCHNM/lcKMT6Vot98xogBOREREREREYoo5YPHO45W8+Yd9mAMGCZkDXHp/PKWfmQVurYkl40NqiZfTv5XF6d/Kor2mn21Ph8K4irc6qVvdTd3qbl6/q5YJx/mYdkUK0y5NIXuuXzsAjxIFcCIiIiIiIhIzmqp6eObHO6neGFrrbcbiABf/ZiJxxZl2jyZim6Q8DyffOoGTb51AV0OAbf9oY+tTrZQtbadhUy8Nm/by1o/2kpTvZsonk5l2aQrFCxJwerQrcLgogBMREREREZGoZ1kWq5+t4dVf1BPoNfAmBrnoP+KY9ZXjMNxafF5kv/gJbk64KYMTbsqgp2WAHc+1sf0fbex6pZ326gCrHtrHqof24Ul0MPnCJKZemsLki5LwpShCGgm990RERERERCSqdezr5dn7drLr3QBgUHLqAJf+TwnJ09V6EzkUf6qL2delM/u6dAZ6TfYs7WD7P1rZ/mwbXfUDbH6ilc1PtOJwQdH8RKZemszUTyaTUqRNHI6WAjgRERERERGJWlvequX5n9TR02rg9JgsusvPKXfNwtBabyJHxeVzMOXiZKZcnMwlv7WoWdHN9mdb2f6PNhq39FK2tIOypR28fFs1E47zMWlxEqWLkyg8MwGXV7eqHo4COBEREREREYk6vZ39vPSLnWx4oQ8wyJ4R5PJHiphw0gS7RxOJeobDIP/UePJPjWfhPXk07+pl2z/a2PFsG5XvdA6uG9fL+//VgDvOQcm5CUxanEzp4iTSJqkdNxQFcCIiIiIiIhJVqrbU89Td1bTVGRgOizNu8bLgvik4/VrrTWQ0pJX6OP1bPk7/VhbdTQPsea2d3S+3s+vldjr3DrDj+XZ2PN8++LLeA+244gUJeOKdx3RNy7QwHLGzI6sCOBEREREREYkKljXA6hd289JPOzEHDFILTC7/n3wKFmXbPZrIuBGX7uK4z6Rx3GfSsCyL+g097Ho5FMhVvtNJ864+mn/dyMpfN+L0GBSelUDxOQkUz08k96S4I7pd9e+fL2PHc+2ULExk4sJESs5NJH2qF8OI3kBOAZyIiIiIiIhEvIFgKy/cv4N1T7sAgxkXu/jkn6biTdHtbiJ2MQyD7NlxZM+O48x/zaavI0jZ6x0HArnW8v4Da8dBHS6fQf5p8RSdnUDR/ETyT43H7f9oIGcOWGz+aytmwGL7P1rZ9nQrWBCX6WLiokRKBgO51JLoeu4rgBMREREREZEIFqStrZwnvl1P7WYfhsPi3O+nc8bdRVHdhhGJRd5EJ9MuTWHapSlYlkXTjj72LGmn4s1OKt7qpKthgPJlnZQv6wT24vQY5J0cR+HZoYZcwenxtJb3YwYsAKzgh+fubhxgy99a2PSXFgAS89xMOj+RkoVJlJyTQGJuZN+CrgBOREREREREIpOrnfJNm/nbtxx0t/jwpxp86vGJTLowxe7JROQwDMMgY6qPjKk+Tr51QiiQ295H+ZsdoUDuzU46agNUvtNF5TtdvHNPPYYTkguHD9LMgQ//v6MmwIbHmln3v80ApE70MOmCJErOTaR4QSJxGZEVeUXWNCIiIiIiIiIEsXwVLP/LLl69Px0raJB9vIernpkcdbediUiIYRhkTPORMc3HiV/OxLIsWnb3UfFWKIwrf7OTtop+Wsv6j/icBwdyLXv6WfPf+1j1m30AZM7wHQjkCs9KwJd8bJtBhIsCOBEREREREYkcrjYC1iae+243G1/KAOD4a1K55OEi3HGHX7xdRKKDYRiklfpIK/Ux98bQc721oo9fFG8+5nMeHMg1bumlaUcvH/y8AcMB2XP8TDx/MJA7I2HMP58ogBMRERERERH7GQPgq6Sldj1PfDOTvdvTMZxwwf35nPwvmVrvTWQcONTtp8difyBnmVC3pof6DT28+5N6HC7IOyWeieeF1o/LOyX+iHZnHQkFcCIiIiIiImIvVyv4NrH7nSqeurOUnjYn8RNcfPqJEornJ9o9nYiMkbaKI7/99FjsD+TMAah6t4uq97p48wfgcEH2nDiKz01gysXJFJyeEPZrK4ATERERERERexgD4CvHYg3v/sHH67+agmWGdkW86qmJJOVH9q6GIhJedWt7xvaCoc1WMQegdlU3tau6ee+nDQAM+PvCeikFcCIiIiIiIjL23C3g3YTZt4Xn75nG2qdDTbe5X0znol8XjPrtYCISefau7cbh+uhabqNq/53t1scPDfQM8eAIKIATERERERGRsWMMgL8cWE1/ZydP3nUCO99wYDjgwl8VcNLNmXZPKCI2qVvTjRk8ttd1uADDwDItrCHO4XCBL8VJXIaL+Cw38Vku4jPdxGWEHovLdOFPd+LyOTCApuYGfnLpSN6aj1IAJyIiIiIiImPD3QLejRDcRldbFn/5xnRq1g7g8hl86v9KmHZpit0TioiNald1gwWGAwynAZYVCuSGKKN5Eh3401zEZ7lIyHITl+kiPtMVCtMGA7X9/x+f6cKT6DiqzVzimzrC94ahAE5ERERERERGmxE40HrD7KSleTZ/+nIczbsC+NOcfPb5SRScFv5Fz0UkupxyWyZlr3eSkOXCf1B49s+hmj/NhdMdXTsjK4ATERERERGR0eNuPtB6w5lFbf3J/PmaTroaAiQXebj2lVIypvrsnlJEIsBZd+Vw1l12TzE6FMCJiIiIiIhI+BkB8JWBsQbMLkiYy64tRTzxuToCXSbZc/x87sVSEnPcdk8qIjLqFMCJiIiIiIhIeLmbDmq95UDWmax/wcezN1ViDsDERYlc9dREvElOuycVERkTCuBEREREREQkPIwA+HcDa8DsgYQTsPKm884Dnbx+VyUAs65J5dL/KcLpcdg7q4jIGFIAJyIiIiIiIiPnaQLPBjC3gyMHss/GTMnhpa/XsOqhfQCcfnsWi+7NxXBE1+LpIiIjpQBOREREREREjp0RAP8uYC0EeyHxRMibQcDy8ffPlLHt6TYwYPED+Zxy2wS7pxURsYUCOBERERERETk2niZwrwdzBzjzIGc+pOXQ12Xx54t3Ufl2J06PweV/Kmbmlal2TysiYhsFcCIiIiIiInJ0jP4P13qz+iDxJMibDr44+tqD/GnxLqrf78Kb7OTqf0ykeH6i3ROLiNhKAZyIiIiIiIgcOU9jaK234E5w5UPOPEjNBoeD3rYgjy/eRfUHXfhSnHx+SSm5J8bbPbGIiO0UwImIiIiIiMjhGf3g30loh9MBSDoF8qaB1w9Ab+sAf7pgFzUruvGlOrnutcnkzIuzd2YRkQihAE5EREREREQOzdMInnUQ3A3ufMieB2k5YIR2M+1pGeBP5++idlU3/vRQ+JY9R+GbiMh+CuBERERERERkaI4+8O0E1oIZhORTIXfqgdYbQE/zAI+dt5O6NT3EZbi4bmkpWccrfBMROZgCOBEREREREfm4/a03cze4CiF7LqRlH2i9AXQ3DfDYop3sXddDXKaL61+fzITj/MOfU0RknFIAJyIiIiIiIh/659Zb0mmQO+UjrTeArsYAjy3aRf2GHuInuLju9clMmKnwTURkKArgREREREREBLDA2wDudWCWgbMIcudCatZHWm8AXQ0B/rhwJw2beknIDoVvmdMVvomIDEcBnIiIiIiIyHjn6APfDmANWNZg620qeH0fe9HO+gB/PHcnjVt6Schxc/2yyWRM/fjLiYjIhxTAiYiIiIiIjFsWeOvBvT7UenMVQc48SJ3wsdYbQOfeAI+eu5N9W3tJzA2Fb+lTFL6JiByOAjgREREREZHxyNH7YevNNCD5dMiZMmTrDaCjLsCj5+ygaXsfSfmh8C2tVOGbiMiRUAAnIiIiIiIyruxvva2FYAV4iiFnLqQM3XqDD3c7bdreR1KBm+uXTSFtkndsxxYRiWIK4ERERERERMYLRy/4thPa4dQBqWdCzmTwDB+m9XcG+fPFu2jc0ktinpsvvDmF1BKFbyIiR0MBnIiIiIiISMyzwLsXXGvBrATPJMiZHVrr7RAG+kz+evkeapZ3409z8vlXSxW+iYgcAwVwIiIiIiIisczRA/7tYK0FyxVqveVOBvehgzQzaPH0teXsea0Dd7yDa14qJXOGf4yGFhGJLQrgREREREREYpIFvrrB1lvVYOttDqRkHv41LYvnv1LJlidbcXoMrn5mInknx4/+yCIiMUoBnIiIiIiISKxxdEPcdjDXgeWG1LMhZ9JhW2/7Lb2rlrW/b8JwwBV/LmbioqTRnVdEJMYpgBMREREREYkZg60352DrzT0Zco8/otbbfu/9Vz3v/qQegEt+V8iMT6WO1rAiIuOGAjgREREREZFY4OwG31aw1oPlhbSzIbsU3J4jPsXa/9nHku/UALDovlzmfTFjtKYVERlXFMCJiIiIiIhENXOw9bYGzBrwTIa82ZB8dOHZ1r+38NxNlQCc/p0JnHF79mgMKyIyLimAExERERERiVbObvBtAWtDqPWWPh+yJx1V6w1gz9J2nvpsOZYJc/9fOovuyxulgUVExicFcCIiIiIiIlHHBF9tqPVm1YF3MuTOhqT0oz5Tzcou/nrZHoL9FtOvSOGS3xZiGMYozCwiMn4pgBMREREREYkmzq4P13rDH2q9ZU0Ct/uoT9W4tYfHL9xFf6dJycJErvhzMQ6XwjcRkXBTACciIiIiIhIVBltvrtVg7gXvlNAOp8fQegNoq+rnT+fvoqcpSO5JcXzm6Ym4vI4wzywiIqAATkREREREJPI5O8G/FcwNYMVBxgLImgiuo2+9AfS1B/nzxbtorw6QMd3HNS+W4k10hndmEZGo1UQPVWE9owI4ERERERGRiGWCv2Zwh9M68E6H3FmQlHbsZxywePIzZTRs7CUh28W1L5cSl6EfDUVEoB+Tcurp4B3MsJ5Zn2VFREREREQikbMTfJvB2ghWAmScC1klx9x6A7Asi5e+VsWul9tx+Q0++9wkkguPbsdUEZHYtI9uqtiOyQoMeskK69kVwImIiIiIiESU4GDrbTUEG8A3DfKOh8TUEZ95+S8bWfXQPjDgisdLyD0xPgzziohEs35MythLJ6uAXfjJoxgLK6xXUQAnIiIiIiISKVwd4N0C5kawEmHCQsgqBufIf3Tb/lwrr3yjGoBF9+Ux/fKUEZ9TRCS6NdJFDdsJsgIDg2xKycHAoIuusF5JAZyIiIiIiIjtBltvjlVgNoJ/BuTNgoSUsJy9bm03T322HCyYd1M6p397QljOKyISnfoIUkY9XazAYg9x5FFMHHGjdkUFcCIiIiIiInZydYBvE5ibgKSwtt4A2qv7+csluwl0mUw8L5GLHizEMIywnFtEJPo00k01WwfXenOSSynZGIzu50UFcCIiIiIiIrYIgr8aHKvB3Ae+GZB3XNhabwD9nUH+8onddNQGyJzh48q/TcTpVvgmIuNRqPW2ly5WAnvwk08JfvxjcnUFcCIiIiIiImPN1T7YetsCJEHmQsgqClvrDcAMWjz1uXL2rushfoKLz70wCV+yM2znFxGJHg10UXOg9eYml1KyRr31djAFcCIiIiIiImMmCP7KwdZbM/hmDrbeksN+pVe/Vc2O59pw+QyufnYSKcXesF9DRCSyhVpvdXSxAijDTyET8eEb80kUwImIiIiIiIyFA623TUAaZC2CzCJwhr+VtuLBRpb/ohGAy/5YTP4p8WG/hohI5LKABjqpYQsmq3DgJpfJY9x6O5gCOBERERERkVG1v/W2CsyWUW29Aex8sY2Xb6sC4Nx7cpl5ZeqoXEdEJDL1EqScOrpYDlQQTwEltrTeDqYATkREREREZLS42sC3MbTWm5EGE86DzMJRab0B1G/o5snPlGGZMOfGdM68I2tUriMiEnksoJ4Oag+03rzkUcoE21pvB1MAJyIiIiIiEm7GAPgqwVgFZhvEzYLcmRCfNGqX7KwP8OdLdtPfaVJ8TgKX/KYAw7D/h04RkdHXS5AyauhmJQYVxFPIRLxEztqXCuBERERERETCydUaWustuBkc6ZB5PmTmj1rrDSAYsPjblWW0VwVIn+rlqqcm4vQ4Ru16IiKR4eDWm8VKDPzkM5kJdg/2MQrgREREREREwsEYAF85GGtCrbf42ZA3A+JGr/W236vfqqby7U68SQ6u/sck/Kn6UU9EYl0PA5RRQw8rMagigQKKI6r1djB9VhYRERERERkpdwt4N0FwCxiZkHUBZOSNauttv3WPNLHiV6EdTy//UzEZU+1daFxEZHRZwF46qGMzFqtwEEc+pWTaPdghKYATERERERE5VsYA+MuBVRDsGGy9zYS4xDG5fO2qLp7/SiUA83+Qw9RPpIzJdUVE7NHNAOXU0MNyoCbCW28HUwAnIiIiIiJyLNwt4N0IwW3gzISs0yF9bFpvAF0NAf56xR6CfRZTP5nM/Luzx+S6IiJjzwLqaGcvm7FYjZM48iK+9XYwBXAiIiIiIiJHwwiEWm/GajA7IWF2aIfTuIQxGyEYsPjbVR9uunDZH4sxHNrxVERiUTcDlFFFLysItd6KKMGDx+7BjooCOBERERERkSPlbv6w9ebIgpwzQq03x9juOLrkO9VUvNmJJ9HB1c9Mwpc8Nq07EZGxYwJ7aaOeTZiswUkC+Uwmw+7BjokCOBERERERkcMxAuArG9zhtAsS5oZ2OPWPXettv/WPNbH8F4ObLvyxmIxp2nRBRGLNwa03g1oSKaQ46lpvB1MAJyIiIiIicijuplDrzdwOzmzIOhPSc8e89QZQt6ab578U2nTh7LuzmXZZypjPICIyekygjjbq2UiQ1bhIppBS0u0ebMQUwImIiIiIiAzFCIB/N7AGzB6Inwf5M8AXb8s4XY0B/nr5HgZ6LaZcksSCH+TYMoeIyOjoIkAZVfSxHKgnhUKKceO2e7CwUAAnIiIiIiLyzzxN4NkQar05ciD7bNtabwDmgMWTnymjrbKftMleLn9Mmy6ISKwwgVraaGA9Jmtxkkwhk2Kg9XYwBXAiIiIiIiL7GQHw7wLWQrAXEk+EvOm2td72W3J7DeXLOvEkOLj6mYn4UvSjnIjEgk4ClFM52HprJIUCimKm9XYwfdYWERERERGBUOvNvR6sHeDIg5z5kJZjW+ttvw2PN/PBzxsAuOzRIjJn+G2dR0Rk5EKtt9bB1ts6XKRQyETS7B5s1CiAExERERGR8c3o/3CtN6sPEk4abL3F2T0ZdWu7ee6mCgDO+m42069ItXkiEZGRCrXeKuhjBQYNJMfUWm/DUQAnIiIiIiLjl6cxtNZbcCe48iFnHqRm2956A+hpGeCJK/Yw0GNRemESC36oTRdEJJqZQA0tNLJhsPWWShGTGB+/WFAAJyIiIiIi44/RD/6dwFowA5B0CuRNA29k3N5pWRbP3lhBa3k/KSUerni8GIdTmy6ISLQKtd7KB9d6ayKVAgpjvvV2MAVwIiIiIiIyvngawbMOgrvBnQ/Z80JrvRmRE3At/2Uj255pw+kxuPJvE/Gn6kc3EYlGQfa33tZjsQ4XaRQxcZy03g6mz+IiIiIiIjI+OPrAtwtYA2YQkk+F3KkR03rbr2ZFF0u+UwPA+ffnk3uC/WvRiYgcvQ76KaOcACsItd6KKMI1TqOo8flWi4iIiIjI+LK/9WbuAlcRZM+FtOyIar1BaN23v11VhhmwmPHpFE66OcPukUREjlKo9dZMI+uw2ICbNArHZevtYArgREREREQkdjn6wLd/rbcgJJ0OuVMirvUGoXXf/nFDBW0V/aRO8vKJ3xdhRFhAKCJyaO30U0EZfazAQStpFFEwbltvB9N7QEREREREYpAF3gZwrwdzDziLIHcupGZFXOttvw8eaGD7PwbXfXuiBF+y0+6RRESOUBCopol9rAfW4yaDIopJsXmuyGH/3tphEAwGufvuuykpKcHv9zNp0iT+/d//Hcuy7B5NRERERETGmqMP4jaB82WwaiHpNJh8TkTecrpf9fIuXrs9tO7bBT/PJ2ee1n0TkWjRTj+b2cY+XgA2kUoxM0lR+PYRMdGAu++++/jNb37Do48+ysyZM1m1ahU33HADycnJ3HbbbXaPJyIiIiIiY8ICb/1g660stNZbzjxInRCxwRtAT/MAT15VhjkAM65M4cSvat03EYkGQSwqaaaZtVhsxE0mxZSQbPdgESkmArj33nuPSy+9lIsvvhiA4uJi/vKXv7BixQqbJxMRERERkTHh6AXfDkJrvQHJp0HOVPD67J7skCzL4pkvVNBWGVr37ZNa901EokIbfZSzmwArMWgjjRKKcKJb54cTEwHc6aefzsMPP8yOHTuYMmUK69ev55133uH+++8f9nX6+vro6+s78Pf29nYAAhYETN26KhJJ9j8n9dwUiUx6jopErvHx/LTA2wjuDRCsBHchZM+G5IxQ6y0Q2W/78gca2PFcG06vweV/LsbhdxCI8JklfPb/W+vfXKKHiUUVzbSwAdiCj0wKKSYRAIvY+Vi2wvy8jIkA7o477qC9vZ1p06bhdDoJBoP8x3/8B9dcc82wr3Pvvffywx/+8GOPL2t3ETcQOx8wIrFkSTMQQ5/QRWKNnqMikSv2n5+ZwMIP/7pn//9E9tvctb2LnXeF1n3LuSGPNXV+qIvsmWV0LFkCkf7xKhJiAIWDf6Bk8NFYCt4O6A7v6WIigHviiSd4/PHH+fOf/8zMmTNZt24dX//618nNzeX6668f8nXuvPNOvvnNbx74e3t7OwUFBZyTNEB6iirfIpEkYFosaYbz0sDt0PNTJNLoOSoSuWL3+bm/9bYeglXgLoHsWZASPWun9TQP8Id/KYcgTL8yhct+kaFbT8ehQMBiyRI47zxwu/XvL5EqiEU1TQdab24mUEjiYOstZjWF93QxEcB95zvf4Y477uDqq68GYNasWVRUVHDvvfcOG8B5vV68Xu/HHncbsfbNiUissHA7DD0/RSKWnqMikSvGnp+OHvBvB2s94ID0UyB3Mrg//r19pLIsixe+WEF7VYC0yV4u/X0RHo/D7rHENhZut6EATiJUK31UsIsAyzHoIZMS8sbFWm9GmJ+TMRHAdXd343B89AuW0+nENE2bJhIRERERkfCywLsXXGvArARPKeTOgZRMuwc7au//rIEdz7fj9Bpc+UQJ3qTY/0FWRKLNABaV7KOFNVhsxkM2JWTGeuttFMVEAPeJT3yC//iP/6CwsJCZM2eydu1a7r//fm688Ua7RxMRERERkZFydEPcdjDXAW5Imw85k6Kq9bZf1fudvHZHaN23xb/IJ3tOnM0TiYj8sxZ6qWQXA6wAepjAxHHSehtNMRHA/epXv+Luu+/m5ptvpqGhgdzcXL785S/zb//2b3aPJiIiIiIix8wCXx0414JZBe5SyJ0dla03gN62IE99thwrCMddncoJX4qeNetEZDwIYFFJI62sxmIrXrIpVustTGIigEtMTOSBBx7ggQcesHsUEREREREJB0c3+LeFWm+WF9LOhuxScHvsnuyYvXhzJW0V/aSUeLjkd4XadEFEIsiHrbflGPQxgYnkqvUWRjERwImIiIiISKwwwbcXnGvArAbPZMibDcnR3Rbb8KcmNv65BcMJn/qz1n0TkUgRwKSCRtpYM9h6y6GECSTYPVjMUQAnIiIiIiKRwdkNvq2hHU4tL6TPh+xJUd16A2gp6+OFm6sAmP/9HPJPjbd5IhERgGZ6qWQHQVYAAbKZRC4OtCvzaFAAJyIiIiIiNjNDa7251oBZA54podZbUrrdg42YOWDx92vK6e8wKTgjnrPuzLZ7JBEZ9wKYlNNAO6sx2Y6fHIpJUOttVCmAExERERER+zi7BltvG8DyQfoCyJoEbrfdk4XFWz+uo/r9LrxJDq74UzEOl9Z9ExE7NdFDJTswWQEMkKPW2xhRACciIiIiIjYwwVcLrtVg1oF3SmiH0xhove1X9V4nb/37XgAu/k0hKcVemycSkfHrw9bbKkx24CeXEuLRLfFjRQGciIiIiIiMLWcn+LdCcANYcZB+DmRPBFdstN4AetuC/P2aciwTjr82jVmfS7N7JBEZt5roppLtDLASBya5TCJHrbcxpgBORERERETGyEGtt2Ad+KYOtt5iL5x68ZZKWsv7SSn2cOGvC+weR0TGpX5MKqinnVXADvzkM5E44uwebFxSACciIiIiIqPP2XnQWm/xkHkuZJXEVOttvw2PN7Px8RYMJ1zxeDG+ZKfdI4nIuLOPbqrYjslKDCyyKSVbrTcbKYATEREREZFRZIK/BhyrwawH3zTIOx4SU+0ebFS0lPXx4s2VAJx9dw4Fp2tXQREZS/2YlLOXDlYBO/Gq9RYhFMCJiIiIiMjocHaCbzNYG4FEmLAQsorBGZs/hpgDFk9fW05fu0nB6fGc/d1su0cSkXGlkS5q2E6QFYBBDpPJwUC7L0eC2PzKJyIiIiIiNgqGWm/O1RBshLhpkHs8JKTYPdioevuevVS914Un0cHlfyrG4dIPvSIyFvoIUkY9XazAYg9x5FGs1luEUQAnIiIiIiLh4+oA7+bBtd6SYcK5Md1626/q/U7e/FEdABc/VEBqidfmiURkfGikm2q2EmQlDgxyKFXrLSLF9ldBEREREREZI4OtN8cqsPaBbwbkHRfzrTeAvvYgf7+mHCsIsz6XyvHXpts9kojEvFDrbS9drAT2EEc+Jfjx2z2YDEMBnIiIiIiIjIyrPbTWm7kZSILMhZBVFPOtt/1evLWK1rJ+kos8XPRQod3jiEjMa6CLGrYSZAUGbvIoJUuttwg3Pr4iioiIiIjIKAiCv2pwh9Mm8M0cbL0l2z3YmNn012Y2PNaM4YArHi/Gl+y0eyQRiVmh1lsdXazEoow4CpiID5/dg8kRUAAnIiIiIiJHz9UOvk1gbgLSIGsRZBaBc/wEUB11AV74ahUAZ303m8IzEmyeSERikwU00EkNWzFZhRMXOWq9RRkFcCIiIiIichSC4K8Mtd6CzeAff603AMuyeO6LFfS2BMme6+fsu3PsHklEYlLvYOutmxVAOfEUUKLWWxRSACciIiIiIkfG1TbYetsMRhpknweZheOq9bbf2j80sfPFdpweg8v/WIzTrRaKiISTBdTTQS1bMFmNE7dab1FNAZyIiIiIiBxGEPwVg2u9tYD/uFDrLT7J7sFs0VLWxyvfqAbgnB/nMuE47TooIuEUar3VDrbeKoinkIl48do9mIyAAjgRERERERmeqw18GyG4GYx0mHABZOaPy9YbgGVa/OOGCvo7TQrPjOe0b06weyQRiRn7W291bCHIKpz4yKOUTLXeYoACOBERERER+ThjAHwVYKwGsw3iZ0PeDIgbn623/Zb/spGKNztxxzu49JFiHE79UCwi4dDDAGXU0MNKDKpIpIBitd5iiAI4ERERERH5KHcLeDaBuQWMTMi6ADLyxm3rbb9923pZemcNAOf/Vx5pk/SDsYiMlAXspYM6Ng/ucBpHPqVk2j2YhJkCOBERERERCTEGwFcOjjUHtd5mQlyi3ZPZzhywePq6cgZ6LSadn8gJX86weyQRiXoftt5WANVqvcU0BXAiIiIiIhJqvXk3QnAbkAG5F0C6Wm/7vfOTvdSu7Mab7OSTfyjCMHTrqYgcKwuoo529bMZiDU78g2u9SexSACciIiIiMp4ZAfCXA6vB7ISE2ZA7E+IS7J4sYtSt7ebNH9YBcNGv80nK99g8kYhEr24GKKeaHpZjUUsihZTgQZ9XYp0COBERERGR8crdAt4NYG4DRxZknxFqvTkcdk8WMQb6TJ65rhxzAKZfkcKsa9LsHklEopIJ7KWNejYxwBpcxGutt3FFAZyIiIiIyHhjBMBXNrjWWxfEzw3tcOpX6+2fvfH9Oho29RKX6eLi3xbo1lMROQbdDFBGFb2swKCGJIrUeht3FMCJiIiIiIwn7ubB1tt2cGRD1pmQnqvW2xCq3uvkvf+sB+ATDxcSn+m2eSIRiS4mUEcb9WzEZA1OkihkMul2DyY2UAAnIiIiIjIeGAHw7QFjDZjdED8P8meAL97uySJSf1eQp6+rwDJh9nVpTLssxe6RRCSqdBNgD1X0sQKoG2y9uVGQP14pgBMRERERiXXuZvDvb73lQPZZar0dxpLba2jZ3UdSvpvFv8i3exwRiRomUEsb9azHYh0ukiigVK23cU8BnIiIiIhIrDIGACe4l0KwExJPhLzpar0dxu4l7ax6aB8Al/5vEb4U/dgkIkeiiwBlVNLHcqCBZAopVutNAAVwIiIiIiKxydMEzk3AWeBIhLwzIC1HrbfD6G0L8uyNFQCcdEsmExcl2TyRiES+UOutlQY2EGQtbpIpYJJab3IQBXAiIiIiIrHE6Af/bmANmGbosUnzISHO1rGixavfrqa9OkDqJC+L7su1exwRiXidBCinYnCttwZS1HqTISmAExERERGJFZ594FkPwZ3gyofsE6AS8Prtniwq7F7SztrfNwFw6f8U4ol32jyRiEQuE6ihhUY2YLIOFykUMok0uweTCKUATkREREQk2h3cerP6IfGk0FpvTj9g2T1dVOjrCPLcTZUAnHRrJkVnJ9o8kYhErlDrrXyw9dZICoUUqfUmh6QATkREREQkmnkaB1tvu8CdD9nzQmu9GQYEFL4dqaV31tJW0U9KsYdF9+rWUxEZSpBQ620f6wdbb2kUMYlUuweTKKAATkREREQkGjn6wLeL0FpvA5B0CuRN0+2mx6D8zQ5WPtgIwCd+X4gnQbeeisg/66CfMsoJsAJoIpUiinApVpEjpI8UEREREZFo42kEzzowd4GrELLnfth6k6MS6DZ59v+Fbj2dd1M6Exdq11MROVio9dZMI+uw2ICbNAqZqNabHCUFcCIiIiIi0cLRB76dwFowg5B0GuROVettBF7/Xi0tu/tIyndz3n/m2z2OiESUdvqpoIw+VuCglTSKKFDrTY6JPmpERERERCKedVDrbTe4iiFnLqRmqfU2AlXvd/LBAw0AXPK7QnzJuvVURCDUequmiX2sB9bjJoMiikmxeS6JZgrgREREREQimaMPfDsI7XBqQdLpg603n92TRbWBXpNnb6wAC2Zfl8bki5LtHklEIkI7/ZSzZ3Ctt1ZSKaZQrTcZMX0EiYiIiIhEJAu89eBeD2YZuIogZx6kTlDrLQze+GEd+7b1kZDt4oKf69ZTEQliUUkzzazFYiNuMimmBIXzEh4K4EREREREIo2jd7D1tjbUeks+DXLUeguX2lVdvPef9QBc/JtC/Gn6sUhkfGujj3J2E2AlBm2kUUIRTnRbuoSPvtKIiIiIiESM/a23dRAsB09xaIdTtd7CJthv8o8bK7CCcNzVqUy7LMXukUTENqHWWxPNrAU24WECxZSg3ZAl/BTAiYiIiIhEAkcv+LYT2uHUAalnQM4U8HjtniymvH3PXho29hKX6WLxL3Xrqcj41UYfFeyinxUYdJJGCYVqvcmoUQAnIiIiImIrC7x7wbUWzArwTIKcOZCSqdZbmO1d383b/7EXgIt+XUB8ptvmiURk7A1gUcU+mlmHwUY8ZFFMsVpvMsoUwImIiIiI2MXRA/7tYK0DywmpZ0HuZHCr9RZuwYDFP26owByAaZcnM+PKFLtHEpEx1zrYeguwHIMeMphInlpvMiYUwImIiIiIjDkLfHXgXAtmJXhKIXdOqPUmo+K9/6xn79oefKlOLn6oEEPtQpFxZACLSvbRwhosNuMhmxIySbR7MBlHFMCJiIiIiIwlRzfEbQdzHeBS620MNG7p4c0f1gGw+Bf5JGTr1lOR8aOFPqrYSYAVQA8T1HoTWyiAExEREREZEwe33qo+utabjBozaPGPGysI9ltMvjiJ469Ns3skERkTA1hU0Egrq7HYipdsitV6E9sogBMRERERGW3ObvBtBXM94IHUsyGnFNweuyeLeSsfbKRmeTeeRAeX/Fa3noqMDy30UskuBliOQS+Zar2J7RTAiYiIiIiMGvPD1ptVDZ7JkDcbkjPsHmxcaKvsZ+ldtQCc99M8kvIVeIrEtgAmFTTSxhostuAhl4lMIMHuwUQUwImIiIiIjIr9rTdrPVheSJsP2ZPUehsjlmXxwlcrCXSZFJ4ZzwlfUugpEtua6aWKHYM7nA6QTSm5OHDYPZgIoABORERERCTMTPDVgnMNWLXgmRJqvSWl2z3YuLL5ry3sfLEdp8fgkocLMRy69VQkNoVabw2Drbdt+MihmAS13iTCKIATEREREQkXZ9dBa735BltvpeDWrptjqbtpgJduqwbgrO9mkzndb/NEIjI6muiliu0EWQEMkM0ktd4kQimAExEREREZscHWm2s1mHXgmwK5ar3ZZcm3q+luHCBzpo8z78iyexwRCbsAJuU00M4qTHbgJ5cS4om3ezCRYSmAExEREREZCWcn+LdCcANYcZB+DmRNVOvNJntea2fdI81gwCf+uxCnR00YkdjSRA+Vg603gyA5ar1JVFAAJyIiIiJyTA5qvQXrwDcVco9X681GgW6T579cCcBJt2RScJrWgBKJHf2YVFBPO6uAHfjIZyJxxNk9mMgRUQAnIiIiInK0nJ3g2wLWRrDiIXOw9eZS681Ob/yglpY9/STlu1l4T67d44hI2Oyjmyq2Y7ISA5MsSslR602iigI4EREREZEjZoK/BhyrwdoL3umQdzwkpto92LhXt6ab93/WAMDFvynEm+i0eSIRGbl+TMrZSwergJ141XqTqKUATkRERETkSDg7wbc51HojATIWQlaxWm8RwBywePaLFVgmzLwqhSmXJNs9koiMWCNd1BzY4dQgh1Ky1XqTqKUATkRERETkkIKh1ptzNQQbwT+41ptabxHj/Z83sHdtD75UJ4t/WWD3OCIyIn0EKaOeLlZisZs48ihW602ingI4EREREZHhuDrAuxmsDWAlw4RzQ603p76NjhTNu/t44/u1AJz/s3wSstRIFIlejXRTzVaCrMQx2HrLwcCwezCREdN3DiIiIiIiHzPYenOsAqsRfDMgbxYkpNg9mBzEsiye/3IlAz0WJecmMucLaXaPJCLHJNR62zvYettDHPmU4Mdv92AiYaMATkRERETkYK72wbXeNgHJkLkIsorUeotA6//YTNnSDlw+g0t+V4BhqCUjEn0a6KKGrQRZgYGLPErJVutNYo6+ixARERERAUKtt+pQ681sGmy9HafWW4Tqagjw6jerAZj/gxzSSn02TyQiRyfUequji5VAGXEUMBEfei5LbFIAJyIiIiLiagffJjA3AakwYRFMKFTrLYK9/PVqepqDZM/xc9o3s+weR0SOmAU00EkNWzFZhRMXOZSSpdabxDR9RyEiIiIi41gQ/JXgWA3BZvDPHGy9Jds9mBzCzhfb2PSXFgwHfOL3RTjd+qFdJDr0DrbeulkBlBNPASVqvcm4oABORERERMYnV9tg620zGGmQvQgyi8DptHsyOYT+riAv3FwFwClfn0DuCXE2TyQih2cB9XRSx2aCrMaJW603GWcUwImIiIjIOLO/9bYKzBbwHxdqvcUn2T2YHIE3f1hHW0U/yYUezvlRjt3jiMhhhVpvtYOttwriKWQiXrx2DyYyphTAiYiIiMj44WoD30YIbgm13iacD5kFar1Fib3ru3n//gYALnqwAE+8/t1EIleo9dZBHVsIsgonPvIoJVOtNxmXFMCJiIiISOwzBsBXAcZqMNsgfhbkzYQ4td6ihRm0eP7LlVhBmP6pFKZconX6RCJXDwOUUUMPK4FKEiikRK03GdcUwImIiIhIbHO1gncjmFvAyISsCyAjT623KLP64X3ULO/Gk+hg8S/y7R5HRIZkAXvpoI7NgzucxpHPZDLtHkzEdgrgRERERCQ2GQPgKwfHGrDaIX72YOst0e7J5Ch11AVYekcNAAvvySUpz2PzRCLycftbb92swKCaRAooVutNZJACOBERERGJPe6WUOstuA3IgOzz1XqLYq98vYq+dpPcE+M48atq0ohEFguoo529bMZk9WDrrVStN5GPUAAnIiIiIrHDGAB/ObAKzE5ImA25M9R6i2I7X2pj8xOtGA645OFCHE4t3i4SOboZoJxqeliORS2JFFKCB7VURf6ZAjgRERERiQ3uFvBuAHMbOLIg+wxIy1XrLYoFuk1evLkKgFO+PoGcuXE2TyQiISawlzbq2cQAa3CRQAGlZNg9mEjEUgAnIiIiItHNCICvLLTWm9kF8XMHW28Jdk8mI/Tmj+poLe8nqcDNOT/MsXscEQFCrbc9VNHHCqCGJIrUehM5LAVwIiIiIhK93M2Drbft4MiGrDMhPRccDrsnkxGq39jD+z+rB+CiXxfgSVCTUcReJlBHG/VsxGQNTpIoZDLpdg8mEhUUwImIiIhI9DEC4NsDxhowuyF+HuRNB79ab7HAMi2e/3Il5gBMuzyZqZ9MsXskkXGum8BBrbe6wdabG7fdg4lEDQVwIiIiIhJd3E0Htd5yIPsstd5izOr/3kf1+114Ehxc+MsCu8cRGcdMoJY26tmAxVpcJFFAqVpvIkdNAZyIiIiIRAcjAP7dwBoI9kLiiaHWmy/e7skkjDr3BnjtX2sBOOfHuSTla10pEXt0EaCMysHWWz3JFFKs1pvIMVIAJyIiIiKRz9MEnvVg7gRHLuTMh7Qctd5i0CvfrKavLUjOCXGcfGum3eOIjEOh1lsrDWzAZC0ukilgklpvIiOiAE5EREREIpfR/2HrzeyDhP2ttzi7J5NRsOuVdjb9pQXDAZf8rhCH07B7JJFxppMA5VQMtt4a1HoTCRsFcCIiIiISmTz7Qq234E5w5UPOPEjNVustRgV6TF68uRKAk/8lk9wTFLKKjB0TqKGFBjZgsQ4XKRQyiTS7BxOJGQrgRERERCSyfKT11g+JJ0H+DPD67Z5MRtFbP66jZU8/iXluzvn3XLvHERlHQq238sHWW6NabyKjQgGciIiIiEQOT+Ng620XuPMhe15orTdDtyLGsobNPbz303oALvp1Ad5Ep80TiYwHQUKtt0bWA+twkkYRk0i1ezCRmKQATkRERETs5+gD3y5CrbcgJJ0CedPUehsHLMviha9WYQ7A1E8mM+2yFLtHEhkHOghQThn9rACaSKGIIlyKCERGjZ5dIiIiImIvTyN41kFwN7gLIXsupGWr9TZOrH+0mcq3O3HHObjwVwV2jyMS40Ktt2YaWYfFBtykUchEtd5ERp0COBERERGxh6MPfDuBtaHWW/KpkDtVrbdxpLtpgCXfqQFg/vezSS702DyRSCzroJ9yyuhjBQYtpFFEoVpvImNEzzQRERERGXuehlDrzdwDziLInQupWWq9jTNL76yhe98AmTN9nPqNLLvHEYlRQaCaJvaxHliPmwyKKCHF5rlExhcFcCIiIiIydhx94NsBrAXLhKTTBltvPrsnkzFW9X4na/67CYCLf1OI063wVST82umnnD30swKDNtIopkCtNxEb6FknIiIiImPAAm8DuNeBWQauIsiZB6kT1Hobh8yB0MYLAHO+kEbRWQk2TyQSa4JYVNJMM+uw2IiHDIooJtnuwUTGLQVwIiIiIjK6HL0ftt5MIPk0yFHrbTxb/qsG6tf34Et1suineXaPIxJjQq233R9pvRXhxGn3YCLjmgI4ERERERklFnjrQ623YDl4iiFnLqSo9TaetVf388a/1QGw6L484jPdNk8kEitCrbcmmlmLxSY8TKCYEpLsHkxEUAAnIiIiIqPhQOttDZgOSD0DcqaAx2v3ZGKzV75RTX+nSf5p8cz7f+l2jyMSI9roo4LdBFiORSfplFCo1ptIBFEAJyIiIiJhtL/1thaCFeCZCDlzICVTrTdh18ttbHmyFcMJF/+mAMOhjwmRkRnAoop9NLMOg424yKKEYrXeRCKOAjgRERERCQ9HD/i3g7V+sPV2JuROBrdabwKBHpMXbwltvHDKbRPInh1n80Qi0a6VPirYxQDLgW7SmUi+Wm8iEUoBnIiIiIiMkAXeveBaC2YFeEohd06o9SYy6J1799Kyp5/EPDcLfphj9zgiUWwAi0r20cIaLLbgJYtiMkm0ezAROQQFcCIiIiJy7Bzd4N8B1lrADalnQ26pWm/yEU07enn3vnoAFj+QjzdRDR2RY9NCH1XsIsByoIcJlJCn1ptIFFAAJyIiIiLHwAJf3WDrrQo8kz5c603kIJZl8cLNVQT7LUoXJzH9Uyl2jyQShQawqKCRVlZjsQUPOZSo9SYSRRTAiYiIiMjRcXRD3HYw14HpgbSzIbsU3B67J5MItOn/Wihb2oHLZ3DhrwswtBmHyFFqoZfKwbXeDHrJZJJabyJRRwGciIiIiBwhE3x7wbkGzGpwT4a82ZCcYfdgEqF624K8+s1qAM68K5u0Sbo1WeTIBbCopIFW1mCxFS85lDCBBLsHE5FjoABORERERA7P2Q2+raEdTi2vWm9yRF7/Xi2dewdIn+LljNuz7B5HJIo000sVOwZ3OA2QxSTycOCwezAROUYK4ERERETkEMzBtd7WgFkDnimh1ltSut2DSYSrXd3NqocaAbjooQJcXgUHIocXwKScBtpZC4Ott2IS1HoTiXoK4ERERERkaM6uwdbbhsHW2/zB1pvb7skkwplBixe+UollwnGfTWXiwiS7RxKJAk30UsV2gqwABshiErlqvYnECAVwIiIiIvJPTPDVgms1mHXgnQK5ar3JkVv98D5qV3XjTXJw/s/y7R5HJOKZ7GYvbazCZCdx5FBMPPF2jyUiYaQATkREREQ+dKD1th4sP6QvgKxJar3JEetqCPD6XbUAnPPjXBJz9LEjMrxmIJXNtLMKCJLDRLXeRGKSAjgRERER4SOtt2Ad+KZC7vFqvclRW3J7Db2tQbLn+jnpq5l2jyMSoUJrvdXTCaTyBj7yKCaOOLsHE5FRogBOREREZLxzdh601ls8ZJ4DWRPBpeaSHJ3KdzpZ/2gzABc/VIjDZdg8kUgk2kc3VWzHZBVOJgCTmKbWm0iMUwAnIiIiMm6Z4K8Bx2qw9oJ3OuTOgqQ0uweTKBQMWLzw1UoA5n4xnfxTtX6VyEf1Y1LOXjpYDezASz4TATBQWC0S6xTAiYiIiIxHzk7wbQZrI5AAGQshq1itNzlmK37VQMOmXvzpThb9JM/ucUQiTCNd1LCdAVbiALIpJRsDAwvL7uFEZAwogBMREREZV4Kh1ptzNQQbwT+41ltiqt2DSRRrr+nnje/XAbDoJ3nEpevHDJGQfoLsoZ4uVmKxm7iPrPWm8E1k/NBXRhEREZHxwtUB3sHWm5UEE84Ntd6c+pZQRubVb9XQ32mSf2o8c2/Uxh0iIY10U81WgqzEgUEOpeTodlORcUrfbYkco+IrvkjF3oaPPf6/3/0aX7h4oQ0TiYiIDGew9eZYBVYj+GZA3ixISLF7MIkBe15rZ/NfWzAccPFvCjAcChdkvOsjSBl7B1tve4gjnxL8+O0eTERspABOREREJJa52gfXetsEJEPmIsgqUutNwmKgz+TFW6oAOOmWTLLnxNk8kYjdGuimhi0EWYGBi7wDa72JyPim77xi0NJV61l0291DHivMyqT877/HMOz5AvB/S97is9//ryGPnTpzKu//93+O8UQiIiKxKgj+6lDrzWwabL0dp9abhNX7P2ugaUcf8Vkuzvn3XLvHEbFRqPVWRxergD3EUcBEfPjsHkxEIoTD7gEk/M494XiKsicMeayyvpHXV28Y44k+9MiLS4c9doNu2xQREQkPVzskLAfjVcCECYug9FSFbxJWreV9vPXj0MYL5/8sH1+y0+aJROxgAfV0sYU1dPIcDhrJo5TpCt9E5CMUwMUgwzC4/qJzhz3+yAvDh2CjqaaxiSUr1w95zO/18JlFZ43xRCIiIrEmCP4y8L4KwU2h1tvE8yFnom45lbB7+WvVDPRYFC9IYNbntIuujEd9BNlGNdW8gslbxJHBdLJ1y6mIDEEBXIz6wkXnDnub6d/ffJ+Oru4xnggee2kZpmkOeeyK+aeRnBA/xhOJiIjEEFcbJHwQar0ZQPb+1luy3ZNJDNr+XCvbn23D4YKLHiywbXkTEXtYwF462cJqungWB03kMVmtNxE5BAVwMaokN5v5c48b8lh3bx9/W/buGE8Ej770+rDHbrhk0RhOIiIiEksOar2Zm8E/K9R6y54ITt0SKOEX6DZ5+bZqAE79ZhaZM7Szo4wnvQTZThU1vILJ28QxgRlqvYnIYSmAi2GHWlNtrG9D/WDTNrZVVA95rCh7AueecPyYziMiIhITXG2Q8D6wBAwDss6DSadAfJLdk0kMe/vevbSW95NU4Gb+3dl2jyMyRkKttw62sopO/oFBC/lMZjpevHYPJyJRQIuBxLBPn3MGt/7sd3R093zs2DsbtrKnZi8T88bmm6ZHXhy+/Xb9IW6XjWTlf/+93SOIiMh4ZQyArwKM1WC2Q/wsyJsJcQreZHQ17ejlvZ/WA7D4gXw8CWpZynjQwwBl1NDDSqCSBAopUfAmIkdFDbgYFufzctXCM4c8ZlnWIW8JDafevn7+uvTtIY8ZhsEXDrFhhIiIiPwTVyvEvQ+8BoYLss+HiScrfJNRZ1kWL95aRbDfovTCJKZdnmL3SCKjzALqBltv3TyHgzYKmMw0hW8ictQUwMW4Q92G+seXXseyrFGf4Zm3PqC1o2vIY/PnHkdJrm5dEBEROSxjAPy7Qmu9WdshfjaUngdZhVrrTcbElidb2bOkA6fX4MJfaeMFiXU9DLCVCmp4GYv3SSSbGUxggt2DiUiUUgAX4844fgaTC3KHPFZe18CbazeN+gyPvDj8enOHCghFRERkkLsF4t8DlgL7W28nQVyi3ZPJONHXEeSVb4TW8z3zjizSJqn9I7HKAmppZysr6eY5nHRQSClT1XoTkRFRADcOHHIzhkOEY+FQ09jEkpXrhzyWGOfn0+ecMarXFxERiWrGAMTtAvcrYG6HhDlqvYkt3vxRHR01AVInejjjX3X3gsSqbgbYSjl1vITJB4Ott0wy7R5MRGKAArhx4PoLz8XpHPqf+sll79E5xCYN4fLYS8swTXPIY1ctPJM4n36LJCIiMiR3C8S/CywFhw9yLoCSE9V6kzHXsLmH5Q80AHDhrwpw+/UjhMSaUOutje0sp4vncNBFkVpvIhJW2gV1HMjNTOf8k+fy0vurP3asq6eXp954j+svGp1bQQ+10cOx3n66q7qWJSvW8e6GreyoqqWyvpGO7h76AgH8Xi/J8XEUZWcyvbiAM4+fwQWnzCUnI+1Y34SItXlPJa8sX8MHm7ezvbKG2n3NdHb3EjRN0pISKM3P4Z4vf56z5x5n96giInI0jAD4ysCxBsxOiJ8DuTMhLsHuyWQcsiyLF2+pwhyAaZclM/miZLtHEgmzbgbYQxV9rABqSKKIEjx47B5MRGKMArhx4oaLFw4ZwAE88uLroxLAfbBpG9sqqoc8NrkglzOOn3HE5woGg/zfa2/ziyeeY+XWncO+XGd3D53dPdQ0NvHexm384bklOBwOzpk3i+987nIuOHXeUb8dwym+4otU7G342OP/+92v8YWjDBeP5lx/fe1t/uvPT7Nq265hz1ff3Ep9cyt7ausVwImIRBN3M3g3hG43dWRD1pmQngsONY7EHhv/3ELFm524/AYXPJBv9zgiYWQCdbRRzyYs1uAkgXwmk2H3YCISoxTAjROfPPMU0pISaW7v+NixN9duoryunuKcrLBe85EXw9N+e2/jVr70kwfZXFZ5THOYpsnSVetZumo98+cex+9uv5mpRdH3DWR5XT3X/ejnvL1+i92jiIhIuO1vvRmrweyG+HmQNx38ar2JfXrbgiz5duiXqWd/L4eUIt2KJ7Ei1HqrHGy91ZFIIcVqvYnIqNKvU8cJr8fN584/e8hjlmXxx5eWhfV6vX39/HXp20MeczgcXHfhuUd0np/88UnO+uqdxxy+/bM3125i3g3f4K+vDT1bpPpg0zZO/n/fVvgmIhKL3E2Da70tA2cc5F4AE09Q+Ca2e+P7tXTuHSB9ipfTvjXB7nFEwsAEqmljK+/Ty/M46aWYUqYofBORUXfEDbi33norbBc9++yhgyAZXTdcvIhfP/nCkMf++NLr3H3DZzAMIyzXeuatD2jt6Bry2HknzSYvM/2w57j1Z7/lwadeDMs8B+vu7ePqf/tPGlvbuPXTl4T9/OG2eU8lF37rh8O+P0VEJEoZAfDvBtaA2QOJJ4Rab754uycTYe/6blb8qhGAC39dgMur39tLtOsiQNmB1ls9yRRSjBu33YOJyDhxxAHcggULwhLOGIbBwMDAiM8jR2/e1EkcX1rMhl3lHzu2u2Yvb6/bHLb1wh55cemwx264eNFhX//uh/902PDNMAzOmj2Ds+fMJDcjjfTkJBpaWqluaOLVFWtZu2PPIV//tp//N6mJCVxzwYLDzmOX7t4+Lr/zniHDt/TkRC489QSmF+eTlZZCcnw8nT297K6p472N23hr3WYbJhYRkSPiaQLPBjB3gCMHss/WWm8SMSwztPGCZcKMK1OYdF6S3SOJjIAJ1NJKAxswWYuLZAqYxOELASIi4XRUa8BZljXiC4bjHHLsbrh4Id/4xR+GPPboS6+HJYCraWxiycr1Qx5LTUzgsrNPPeTrP//uSv7j0b8Ne9wwDL506QV87wtXkT9h6EVSf3Lz9WyvqOaO3/yRZ976YMiXsSyLm37ya44vLWbWpOJDzmSXex97kuqGfR95bHpxAf916w0sPnUejkP8oFbdsI/O7t7RHlFERI6GEQD/LkKttz5IOAHyZoAvzu7JRA5Y/8dmqt7twh3v4IL7o2/dXJEPdRKgnIrB1luDWm8iYqMj/jWraZph+yP2ueb8BbhdQ+euf3v9Xbp7+0Z8jcdeWjbsv/Nnzzsbr2f4L3jtXd186b4Hhw1qUxLjWfKLH/Hb228eNnzbb2pRPk//5C4evfvrw77NPX393Pgfv4zYj8t/Dt++9dnL2PDHX3LR6SceMnwDyJ+QwbRifdMsIhIxPPsg/i2w3gRnEuQvhpJ5Ct8kovS0DLDk9hoA5n8/h6R8rYsl0cgEqmhhO+/Rxws4CVDCJCYrfBMR2+g+h3EmMzWZS844cchjHd09PLXsvRFf49GXjn3303se/Rt1+5qHPOb3enj+P+9m4Ymzj2qe6y48l0e+97Vhb6FetW0X//vCa0d1Tjt89/qr+K9/uRGXy2n3KCIicjSMfojbCq5XwKyAxJOgdKFuOZWI9Pr3auluHCBzho9Tv66NFyQadRJgCztp4CUM1pJEATNJI83uwURknNN3fePQjZecN+yxQ4VnR2L55u1sq6ge8thxE4s4cfrkYV+3pb2Th/4+/LpvD//rLZxx/Ixjmutz58/ne1+4atjj9/7xSYLB4DGdeyycM28WP/7ytXaPISIiR8vT+GHrzZUcar1NVOtNIlPt6m5W/SbUvr/owQKc7vBsziUyNoJAJS1s593B1tuAWm8iEkHCGsA1NjayatWqsO6YKuG3+JR5ZKenDnls2ZqNVNU3HvO5D735wqHbb4+9vIyO7p4hj82fexzXLj7nmOcCuOu6KynJzRry2O6avbyyfO2Izj9aPG4XD99xi91jiIjI0TD6IW4zuF4GswqSTvmw9RamHcdFwskyLV68uRIsmPW5VIoXJNo9kshR6BhsvTXyArCeFIo4jlSG/plHRMQOYQngnn32WebNm0d2djannHIK55577keOt7S0sHjxYhYvXkxbW1s4Likj4HI5+fziBUMeM02TR188thZcX3+A/3vt7aGv6XRy7WF2G/3TK28Me+z+2/7fMc10MJ/Xwz1f/vywxx97edmIrzEaLj3rFErzc+0eQ0REjpSnEeLfBOttcKVB/gVQMge8frsnExnWmj80UbOiG2+Sg/P+S2vISrQItd6a2cHb9PECLkwmMpFJuI5uv0ERkVE34gDuJz/5CZdffjnr1q3DsqwDfw6WmpqK3+9nyZIlPPnkkyO9pITBDRcvGvbYH48xiHrmrQ9o7ega8tjFp5/IhLSUYV+3saWNVdt2DXls9uQS5k2ddEwz/bPL559GamLCkMdeWb42IjdjuPGS4f+tREQkgjj6IG7TYOutBpJPhdJz1XqTiNe9b4Cld4Q2Xljwo1wSc3S7nkSDdvrZzHYaeAHYRBpFzFTrTUQi1ogCuA8++IDvfve7uFwufv7zn7Nv3z6ysoa+xe/aa6/FsiyWLFkykktKmEwvLuCUmVOGPLazqpZ3N2w56nOO5PbTN9ZuHHbn08M1546G1+PmqoVnDnmspaOTtTv2hO1a4eDzeFh04hy7xxARkcPxNEDcW8A74MqAgsVQPFutN4kKr91ZQ09zkKzj/Zx8S6bd44gcRhCooImdvEOAF3EBkyhholpvIhLRRhTA/eIXvwDgzjvv5Gtf+xppacPvLDN//nwA1q6NzHW2xqNDteAeeeHobkOtbWxiycp1Qx6bkJrMxaefdMjXP1TwtfCE449qlsM576Q5xzSHHWZNKtKupyIikeyfW29Jp0HpOZCWrdabRIXqD7pY+/smAC56qACHSx+3EslCrbdtNPIiBptJo5jjSCHF7sFERA5rRAHcu+++C8Ctt9562JfNyMggPj6e2trakVxyWDU1NVx77bWkp6fj9/uZNWsWq1atGpVrxYqrF52F3+sZ8tgTr79DT1/fEZ/rsZffIBgc+vbNay9YcNgQafOeyiEf97hdHDep6IjnOBJzp0wc9timPRVhvdZIHWpWERGxkwXeeoh7A3gHnJmDrbfjweuzeziRI2IGLV68JfQ92JwvpFF4xtDLdIjYL4hFGU3s5G36eRkPBpMopkStNxGJGiMK4BoaGkhMTCQjI+OIXt7r9dLf3z+SSw6ppaWFM844A7fbzUsvvcSWLVv42c9+Rmqq7v8/lOSEeC6ff9qQx9q7unn6zQ+O+FyPvjR8Y+5QTbv9KofZeXVGcQFuV3i/qJbkZpEUHzfksaqGfWG91kgNt1utiIjYyNEHcRvB+TJYdZB8GkxW602iz6rf7qNuTQ++FCeL7suzexyRYbTTxya20cTzMNh6m0kyyXYPJiJyVEaUbMTHx9PR0UEwGMTpPHTDqbOzk9bWVjIzw7+uxH333UdBQQH/+7//e+CxkpKSsF8nFt1w8UL+/OqbQx575IWlfO78+Yc9x/LN29laXjXksROnlR5Rg62uqWXIx0cjgDIMg+z0VNq7uj8+x76h57BL8jBBoYiI2GGw9eZeD2YZuIogZx6kTlDwJlGnsz7A698N3Zly7n/kEj9BGy9IpAliUUkTzazFZBMeJlBCCUl2DyYickxGFMBNnTqV5cuXs2HDBubOnXvIl33mmWcwTZM5c+aM5JJDevbZZ7ngggu48sorefPNN8nLy+Pmm2/mpptuGvZ1+vr66DvoFsv29nYAAhYEzKE3A4hFZ82dRWFW5pANtKWrN1Bev4+8zPRDnuN/Xhh+84XrLlp4RO/Pju6eIR9PiPOPyr/HcA249u6eEV8vaFlhmzl+lN7+aLP/faD3hUhkGhfPUUcf+HYB62HAAclnQVYpeDwwABDDb7tEtUDA+sh/93v12zX0tQXJnuvn+BvTP3ZcxF7t9FPJHvpZjYNO0imhAAcOrBj7fGsNPvcsPQdFIk64n5cjCuA++clP8sEHH3DvvffyxBNPDPty1dXV3HHHHRiGwac+9amRXHJIe/bs4Te/+Q3f/OY3ueuuu1i5ciW33XYbHo+H66+/fsjXuffee/nhD3/4sceXtbuIGxhPn/wMTltwLpV//evHjpimyd1Pvc6nP/3pYV87EAjw+JK3hzzmdrtJm3cWL+47/Puztz8w5ONtzrgjev2jFfAMHcA19/Qf8fW6g0O/3PoO66hnHu5cm7sdo/L2R6slzaAfckUiV2w/Rz3AjME/gzZC7L69EmuWLIH9H6+dmzvZ9admMCDxs/m8/MqHx0QiQyIwE4DUwT9AzIVvH7Ekxt8+kWj08ZvmRmREAdytt97Kgw8+yFNPPcV1113H7bfffuBYIBCgvLyc5557jvvuu4/GxkamTp06bCA2EqZpcuKJJ3LPPfcAMHfuXDZt2sRvf/vbYa9355138s1vfvPA39vb2ykoKOCcpAHSU8bXbSTTP7WQJ554Asv6+Cf8FW8t43++cuWwr/vE0uV0dXUNeeyys0/hquLEI5phuDt3CnxwUUb4/z1+NcxdFvHOI79enHPol5udaBz1zOE8VywKmBZLmuG8NHA79P4QiTQx+xx19A623jYCBiTPhqxJodabSJQIBCyWLIHzzgO328AcsPjD96oBmHNjOhd9XRsvSKRoo58q9jDAKqCbdPLIwzGyZcsjnhWwYAlwHhjuGPoaKhILmsJ7uhEFcAkJCTz33HNccMEF/OlPf+Lxxx8/cMzn+3AHMMuyyM3N5ZlnnsHtDv/6Ejk5OcyYMeMjj02fPp2nnnpq2Nfxer14vd6PPe42YuyHhyMwJT+b+XOP4401Gz92bEdlDau3bOfU46YN+bp/OsTmCzdevPCI35c+j4eunt6PPd7Z3TMq/x5Drf+2f46RXs9pGGGbOZznin4WbofeHyKRK5aeoxZ494JrLZiV4JkEuXMgJfzr2IqMDQu328DtNnj/1w00burFn+7kvPvycOsHfrHdABaV7KOFtcBmPEygiIxxtNabhYXhNhTAiUSYcD8nR/zrhDlz5rB+/XpuuOEGvF4vlmV95I/b7eYLX/gCq1atYurUqeGY+WPOOOMMtm/f/pHHduzYQVHR4Rf/l5AbLl447LFHXhw6ZKttbGLJynVDHsvLTOe8k+Yc8fUT4/xDPj5cUDZSbcOcNyl+6DlERGSccPRA/PrBHU6bIPVMmHy2wjeJCR21/bzx/ToAFv0kj7j08O40L3L0WuhjC1to5jlgJ5mUMIOkcRS+icj4EZavutnZ2fzhD3/goYceYvXq1dTW1hIMBsnOzuakk04iLm50d3L8xje+wemnn84999zDVVddxYoVK3j44Yd5+OGHR/W6seTT55zBrT/73ZCbIfx16ds88LUv4vN+9Jabx15+g2DQHPJ81114zmF3xj1YTnoqe4fYCXWox8Khvrl1mDnSRuV6IiIS6Szw1Q223qpCrbecOQreJKa8+q0a+jtM8k+NZ+6Nh95kS2R0DWBRQSOtrAG24CGbEjI5suVrRESiUVh/7eX1ejn99NPDecojctJJJ/H0009z55138qMf/YiSkhIeeOABrrnmmjGfJVrF+bxctfBM/vDcko8da+3o4h9vL+czi876yOOPHuL20y9cNHyjbiiFWZms3bHnY49vKa8iMDCA2xW+D9U9NXtp6xx63bqCrIywXUdERKKEoxvitoO5Diw3pJ4NOaXg1lpvEjvKXu9g0/+1YDjgoocKMGLidnGJTi30UsEugqzAoIcMJpKHkyP/5b2ISDQa0S2ojz/+OD09H29M2eGSSy5h48aN9Pb2snXrVm666Sa7R4o6h74NdelH/r5883a2llcN+bJnHD+dKYV5R3XtmSWFQz7eHxhg857KozrX4azb+fGgb7/jJg49h4iIxCILfLXgfx3M5eAuhKLFUDhD4ZvEFDNg8urXQt+3nXhzJjlzR/fuFJGhBbDYTT17WMYAr+LBzxQKKVT4JiLjwogCuM9//vNkZ2dz4403smzZsnDNJDY54/gZTC7IHfLYkpXrqG38cAuQfw7kDnaoIG84c6dMHPbY66s3HPX5DuW1lesPMceksF5LREQilLMb4teA42Ww2iDtbJh8FiSrCS2xp/HZRpq29xGf5eLcf8+xexwZl5rpZTObaOU5oIwsJjGTBLQLr4iMHyMK4Px+Px0dHTz66KMsWrSIoqIivvvd77Jt27ZwzSdjbLjwLBg0+dMrbwDQ1x/g/157e8iXi/N5uercM4/6ugvmzcIwhr4VYv91w6E/EOCvS98Z8lhaUiJzJpeE7VoiIhKJTPDVgG8pWCvBUwwli6FArTeJTW2V/dQ/UQ/Aef+Zhy9FGy/IWApgspO9lLGMIEvwEM9UCijAMfL9AEVEosqIPus1NDTwyCOPcM4552AYBlVVVfzkJz9h5syZnHTSSfz617+mqanp8CeSiHHdhefidA79YbF/zbdn3vqA1o6h11D79Dmnkxh/9Lc1ZKQkcfKMyUMeW7tjD+t3lh31OYfyj7eX09zeMeSxxafOw+HQNwIiIjHrQOvtFbDaIW0+lJ4FSVqMXmLXkm9VY/aZFJwZz/HXarMpGUtN9LKZjbTxHFCu1puIjHMjShvi4+O57rrreO2116isrDwQvlmWxerVq/na175Gbm4ul112GU8++ST9/f3hmltGSV5mOuefPHfIY1vKqlixZcdhbj9ddMzXvub8BcMe+/av/+eYz7tfX3+Au3772LDHP794+OuLiEg0M8FXDf4lYK0Cb/Fg6206uN12Dycyana+1MaOf7SBAy74RcGwdxuIhNf+1ls5SxngdfwkMo188tV6E5FxLWyfAXNzc7n99tvZsGEDa9eu5Rvf+AZZWVkEAgGeffZZPvOZz5CTk8NXv/rVcF1SRsmh1nC7949PsmTluiGPleRmMX/uccd83WsvWEBinH/IY6+tXM/fXh/61tEj9dPHn2JXdd2Qx0rzczjvpDkjOr+IiEQgZ9dBrbcuSF8Ak9R6k9g30Gvy0r9UA5B5SSYTZg39PZZIeDXRwyY20s5zGFSSzUSmE0+83YOJiNhuVH4FMXv2bH72s59RXV3Nyy+/zDXXXENcXBwtLS08/PDDo3FJCaNPnnkKaUmJQx575q0PCAbNIY994aKFI/rNampSArd86qJhj994z69YuWXnMZ37b6+/ww/+8H/DHr/zuk/jdGr3JRGR2LG/9fYaWKvBOxGKL4D8aWq9ybjwzn31tOzuIyHXTfZns+0eR2JeqPVWRzmvYfIaXpLUehMR+YhR/WzocDiYM2cOc+fOpbCwcDQvJWHk9bj53PlnH9XrGIbB9ReeO+Jr33ndleRmDL0+SWd3Dxd+6we8vW7zUZ3zL6++ybU/vB/THDo4PGn6ZL5w0dHv3CoiIhHK2QkJqwdbbz2QsQBKz1TrTcaN5t19vHPvXgAW/TQPp1+/ZJTR1EQ3m1g/2HqrIZtSZhDH0a8LLSISy0YlgOvt7eUvf/kLF110Efn5+XznO99h69atAMyZM2c0LilhdrRruZ17wvEU5UwY8XWT4uP47e03D9uka2rrYP4td/Ev9/+O2sZDb/Cxs6qWT9/1Ez73g5/RHxgY8mX8Xg+/v/NWbb4gIhITTPBXge81MFeDtxSKz4e8qeBS603GB8uyePm2KoJ9FhMXJTL9yhS7R5KY1Y/JDmopZykmy/CRzDTyyFPrTURkCGHdh3zZsmU89thjPPXUU3R2dmJZFhBaH+5zn/sc1113Hccdd+xrhMnYmTd1EseXFrNhV/kRvfyh1o07Wp8482S+e/2V/PiRJ4Y8blkWv37yBR76+0vMnzOTM2fPIDcjjbSkRBpb26hu2MdrK9ezatuuQ17HMAz++45bOb60JGyzi4iITZyd4NsM1kYgATIWQlaxgjcZd7Y/28bOF9txuA0u/PX+jRcsu8eSmNNIN9VsI8hKHEA2k8hW8CYicggjDuC2bt3KY489xuOPP051dWihV8uyiIuL4/LLL+e6665j0aJF2nUpCt1w8UK+8Ys/HPblkuLjuGLBaWG99r9/6Vqa2zt56O8vDvsypmmybM1Glq3ZeEzX+OU3buKaCxYc44QiIhIZguCvAedqCDaCbyrkHQ+JqXYPJjLmAt0mL38t9P346d+eQMZUH4GAwjcJp36C7KGeLlYBu4gjj2LdbioicgRGFMCdeOKJrF27FgiFbg6HgwULFnDdddfxqU99ivh47XYTza45fwG3P/gogYGhb9/c7+pFZ+H3esN+/Qe//RXyMtO4+7//POz6bcfC7/XwP3fdxtXnHd06dyIiEmFcHeAdbL1ZSTDh3FDrzRnWgr9I1Hjrx3W0VfSTXOjhrO9q4wUJt/2tN5MVGBhkU0oOBipaiIgciRF9h7pmzRoAZsyYwec//3muueYa8vPzwzKY2C8zNZlLzjiRp9/84JAvF87bT//ZXddfxfy5x/Gl+x5kS1nViM939pyZPPyvtzC1SB+nIiLRa7D15lgFZiP4Z0DeLEhIsXswEds0bu3hvf9qAGDxL/LxxGvjBQmXPoKUsZcuVmKxhzjyKcGP3+7BRESiyogCuNtuu43Pf/7znHDCCeGaRyLMDRcvOmQAN60on1OPmzaqM5xx/Aw2/PGX/GXJW/ziiecOu7bbP3M4HJwzbxbf+uxlXHiaPlZFRKKaqz201pu5CUiGCQvVepNxz7IsXrylCjNgMeWSJKZemmz3SBIzQq23LYNrvTnJpZRstd5ERI7BiL5bfeCBB8I0hkSqT5x5MtZ7z9o9Bk6nk2sXn8O1i89hZ1Utr65Yy/sbt7G9sobK+kY6unvoCwzg87hJToinOHsC04vzOeP46Sw+ZR65melhn6n877+PyHOJiMSmIPirB1tvTeCbAXnHqfUmAmz6Swvlyzpx+QwW/7JAay9LGIRab3WDa72p9SYiMnJh/XWxZVk0NTXR3d1NYWFhOE8tcsDkglwmF+Ryy6cutnsUEREZC6528G0CczOQDJkLIatIrTcRoLctyCvfDG28cNb3skktCf+6vDKeWEADXdSyhSCrcOIih1Ky1HoTERmhsOwTvWbNGq644gqSk5PJyspi4sSJHzne0tLCl7/8Zb7yla/Q09MTjkuKiIhIzAuCvwy8r4ZuOfXNgIkXQO4khW8ig5bdXUtX/QDpU7yc/u0su8eRqNZHkO1UU80rmLxFHBlMJ1u3nIqIhMWIv3t97LHH+OIXv0ggEBj2ZVJTU9m9ezfLli1jwYIFXH311SO9rIiIiMQyVzv4NoaCNyMdJiyCzCJwamF5kf3q1nSz8sFGAC56sACXNyy/W5dxxwLq6aTuQOvNTQ6T1XoTEQmrEX2V3rJlCzfddBOBQIDbbruNVatWkZGRMeTLXn/99ViWxUsvvTSSS4qIiEhM2996eyV0y6l/Fkw8H7InKnwTOYgZtHj+K5VYJhx3dSoTFyXZPZJEpV6CbKeKGl7B5G3iyFTrTURkVIyoAXf//ffT39/PLbfccmBDBucw3xwvXLgQgNWrV4/kkiIiIhKrXG2DrbfNg6238yCzUMGbyBDW/H4ftSu78SQ6OP/+fLvHkagTar11HGi9OfCSx2QmKHgTERklIwrgli1bhmEY/Ou//uthXzY3Nxe/309VVdVILikiIiKxxhgAXwUYq8Fsg7jjIW8mxKnRIzKUroYAS++sBeDcH+eSmOO2eSKJLr0MsIdaelgBVJJAISV40QYeIiKjaUQBXG1tLfHx8eTnH9lv3eLi4mhraxvJJUVERCSWuFrBuxHMLeDIgMzzITNfrTeRQ3jtX2vobQmSPcfPSTdn2j2ORA0L2EsHtWzGYhUO/OQzmQl2DyYiMi6MKIDzer309vZiWRaGceiqcl9fH62traSmpo7kkiIiIhILjAHwlYNjDVjtED8b8mao9SZyGBVvd7LukWYALv5NIQ6XbheUI9HDAGXU0M1KHFSRQAHFar2JiIyhEW3CMHHiRAKBADt27Djsy77yyisEg0Fmzpw5kkuKiIhItHO3QPz7wFLABdnnw8STFL6JHEYwYPHizZUAzLspnfxT422eSCKfBdTSzlZW0s1zOGmngFKmKnwTERljIwrgLrroIizLOrABw3A6Ojq44447MAyDT37ykyO5pIiIiEQrYwDidoH7FTC3QfwcKD0PsrTRgsiRWP6LBho29eJPd7Lw3jy7x5GI180AWymnjpcw+YBEsplBJrptWUTEDiMK4L7+9a+TnJzMww8/zN13301ra+tHjvf09PD3v/+dk08+mW3btpGdnc2XvvSlkVxSREREopG7BeLfBZaCwwc5F8DEEyEu0e7JRKJCW1U/b/ygDoDzfppHXPqIVpKRmLa/9baN5XTxHA66KFLrTUTEZiP6yp2RkcHf/vY3Lr30Uu655x5++tOfYpomENr1dN++fQSDQSzLIiEhgSeffJL4eFXlRURExg0jAL6y0FpvZmeo9ZY7E+IS7J5MJKq88o1qAl0mBWfEM+cL6XaPIxGrmwH2UEUfK4AakiiiBA8euwcTERn3RtSAA1i0aBEffPABCxYsIBAIHAjc9u7dy8DAAJZlsWDBAt5//31OO+20cMwsIiIi0cDdPNh6ez3Uesu9YHCtN4VvIkdj50ttbH2qFcMJFz9UgOHQxgvyz0yghja2sZw+nsdJN0VMZqrCNxGRCBGW7vqsWbNYunQpFRUVvPvuu9TW1hIMBsnOzuaMM86gtLQ0HJcRERGRaLC/9WasBrMbEuaFdjj1K3gTOVqBHpOXbq0C4JSvTSDr+DibJ5LIE2q9VdLHSgxqSaSQYgVvIiIRJqyLRxQVFVFUVBTOU4qIiEg0cTeBdyMEt4EzB7LOgvRccIy4dC8yLr17315a9vSTmOtmwQ9y7B5HIooJ1NJGPRuwWIuLJAooRbcoi4hEIq3eKiIiIuERtxMcq8DsgYQTIH8G+LT2q8ixatrZyzv31gNwwQP5eBO1W7Ds10WAMirpZQUG9SRTSDFu3HYPJiIiw1AAJyIiIiPjaQZSgXfAkQHZZ6v1JjJClmXxwlerCPZbTDo/kRmfTrF7JIkIodZb60Gtt2QKmKTWm4hIxDviAO7cc88NywUNw2Dp0qVhOZeIiIjYyOgH/24wNwBXhnY4LZwGPq1RJTJSm/7SQtnSDpxeg4seKsQwtPGCdBKgnIrBHU4b1HoTEYkqRxzAvfHGG2G5oL55EBERiQGefeDeAOYOcA6u/1o0B7xqvYmMVE/LAK98oxqAs7+XTdokr80Tib1CO5y20sh6LNbhJIVCJpFm92AiInIUjjiA+/73vz+ac4iIiEg02N96Yw1YfZB4EmRNhzLAoV+yiYTD69+tpathgIxpXk7/Tpbd44itQq238sEdThtIUutNRCRKKYATERGRI+NpBM8GCO4EVz7kzIPUbAgagGX3dCIxoXp5F6t+uw+Ai39TiEut0nEqCNT8f/buO76q+v7j+Ovem3GzBwlZZIeNIDgQRBAQwV0ZarUC2tbZVmuHq9ZaW2vV/tSqbZWqOBD3BAWRJYrK3jOQEBIC2XvdcX5/BKnKvSHJveFmvJ+PBw/lfM/5ns9NSO69n/v5fj+UU8xmYBMWokklkyhfByYiIu2kJgwiIiLSMnMjWLOBDeC0Q/hISBoAgUHN4w4l30S8wWk3WHBjHhgwbGY0aeeG+Tok8Ynqo1VvTXwDlBJJKqn46a2biEiXpt/iIiIi4l5AMQRsAsc+8O8D8SMgOgG0p6uI133zVBFHNtdjjbIw6bEkX4cjJ11z1VsZxWzCYAv+RJNChqreRES6hQ5JwJ155pmUlpayb9++jpheREREOpq5Eax7gY3gdEDEWZDY/39VbyLiVZUHm1h+XyEAkx5JIiRWe3z1LNU0kUsOjazBRDnRpJKiqjcRkW6kQ36jHzx4kKKioo6YWkRERDpaQFFz1ZtzP/ilQvypEB2vqjeRDrTotoPYap0kjw5h+PW9fB2OnDQOIJ8yStgEbMaPGNJIJ9K3YYmIiNfpIxURERFpZm6EoD1gbGquegsfBYn9VPUm0sF2f1TBrvcqMfvBRf9JwaSOwj1EFU3ksh8bazFRQRRpJKvqTUSkm9JvdxERkR7PgMAi8N8EzhywpELicIiKU9WbSAdrqnXwyS/zATjrjjjiTlHCu/tzYJBHGWVswmArAcSQShoRvg5MREQ6kBJwIiIiPZm5Aax7gI1gGEer3vpDoNXXkYn0CCv/fJjKA01EpAQw7o/xvg5HOtz/qt6+ASqJJo1ULFh8HZiIiHQwJeBERER6JAMCj4D/5uaqN79USBgBUb1V9SZykhzZWs/X/3cEgAue7kNAiJIw3Vdz1VspZWzEYBv+xJJGuqreRER6jA5JwI0aNYry8vKOmFpEREQ89d2qN6cJIkY3V70FBPo6MpEew3AaLLw5D6cdBlweQf9LIn0dknSYSho5wD6a+AaooRfppKjqTUSkh+mQBNy7777bEdOKiIiIR76tetsIjgMQkAYJwyFSVW8iJ9vGF0o5+GUt/iFmpjyZ7OtwpEPYMcijhHI2AVvxJ4500gj3dWAiIuIDWoIqIiLSE5jrj1a9bQKnGaLGQEJfVb2J+EBtsY0lvy8AYPyfE4hIDvBxROJ9FTRygGzsrAFqiSGDPqp6ExHpwbyWgNuyZQuLFy/mwIED1NXV8cILLxwbs9lsFBcXYzKZSEhI8NYtRURE5IQMCDwMfhvBmQcBmZAwrHmvNxHxiSW/K6Ch3EHcsCBG/ko/i93L/6reNgLbCaA3qcSo6k1EpMfzOAFXWVnJ9ddfz/vvvw+AYRiYTKbjEnDDhg2jvLyczZs3M3jwYE9vKyIiIidiroeg3WBsBMOvueotsS/4q+pNxFdyV1Sz+aUyMMHFz6Zg9tPy7+6jnEYOkn20w2k9saSTpKo3EREBwOzJxTabjQsuuID333+f4OBgLrroIqxW63HnBQcHc9111+F0Onn77bc9uaWIiIickAHWQxC8DIyvIaAPpE6B1CFKvon4kL3RycKb8wA47cYY+owM8XFE4h12DPZRxH6WY2Mx/ljpR4oaLYiIyHd4lIB7/vnn+frrr8nIyGD37t18+OGHRES4bqU9bdo0AD7//HNPbikiIiItMddB6CYwLwajHKLGQtY4iIz1dWQiPd4XDx+hZFcjIXF+THwo0dfhiFeU08A2tlPBAkzsI5YMBhNGmK8DExGRTsajJajz58/HZDLx+OOPk5jY8ouI4cOHYzab2bVrlye3FBEREZcMsBaCZSM4D4J/X0gcqsSbSCdRsquBLx46DMAF/0wmKEq90Lo2GwZ5FFHBBgx2EkgC6cQS6uvARESkk/LomX/r1q2YTCbOP//8E54bEBBAREQEpaWlntxSREREfshSB9adYGwGIxCix0J8Fvirs6JIZ2A4DT66IQ9Hk0HfC8MZNCPS1yGJR8poII+9OPgGaCKOTJIwe7a4SEREujmPEnB1dXWEhYURENC6F/g2mw0/P33aJyIi4h3Oo1VvG8BZAAF9IWkYRMT4OjAR+Y6NL5SSt6oG/2AzF/4rGZNJjRe6JhtOcimiio3ATgJIIJ04Vb2JiEgreJQNi4mJobCwkJqaGkJDW37iycnJoaamhqysLE9uKSIiInC06m0HGFuaq956jYP4TFW9iXQyNUdsLPldAQDjH0wgMlWNULqmUho4yB7sfIMJO3FkkqiqNxERaTWPnjFGjhwJwMKFC0947lNPPQXAOeec48ktRUREejgnWPPB+hkY6yEwDdKnQPJAJd9EOqHFt+fTUOEgYUQQI3/V29fhSJvZcLKXw+SyFDufYSWMAfShj5JvIiLSJh49a1x//fUYhsF9993HoUOH3J737LPP8uSTT2Iymbjhhhs8uaWIiEjPZamFkA3NHU6paa56yzwHwnv5OjIRcWHvJ5Vse70ckxkumZOK2U9LT7uWUurZxlaq+AgTecSTySBCCPF1YCIi0gV5tAT1oosuYtq0abzzzjucfvrpXH311dTX1wPw3HPPceDAARYsWMC2bdswDIOf//znx6rmREREpLWcYD0EfuvBeRgC+zV3OFXiTaTTaqp1sPDmgwCMvL03CSOCfRyRtF7zXm9HqGIdBnuwkkS6Em8iIuIRjzsivPLKK1itVubNm8fjjz9+7PjNN98MgGEYQHO13DPPPOPp7URERHoWSw0E7QTnFjBCIOZciMsAP39fRyYiLVhxfyGVB5qISAlg/AMJvg5HWq2UOvLYjZ21WHASTxYJWm4qIiIe8zgBZ7VaeeWVV7jxxhv573//y+rVqzl06BAOh4P4+HjOPvtsbrjhBsaOHeuNeEVERHoIJwQVgHkDOAshcCAkngLh0b4OTEROoHBDHV8/XgTARf9OJiDU4uOI5MSacJLLYapZD+wlmCTSCUaViyIi4h0eJ+C+NWbMGMaMGeOt6URERHouSw1Yt4OxFQiFmAkQl66qN5EuwGk3+OiGPAwnDL4ikr4XRvg6JDmhYurIZxcO1mIG4skkXlVvIiLiVV5LwImIiIinHM1Vb5b14CgC6wBIGgphUb4OTKTDnXvuPaxcue244/fffxV/+tPVPoiofdY8XUzh+joCIyxMeTLZ1+FIi5pwsJ8j1LIOyCaYJNJU9SYiIh1CCTgREZHOwK8aAneAcysYYdB7IsSlgUVP1SJdRWVeE8v+cAiASY8kERqvqtXOq7nqbefRqjfT0b3eTKhTrYiIdAyPXtW//PLLbTrfarUSGRnJ4MGDSUpK8uTWIiIinUpdQyOffrOxHVc6IbAUs2UfgX41hERm0nvgUJIi+hCi5JtIl2EYBgtvycNW6yRlTAgjfqYuxZ1TIw5yOEwtazHYr6o3ERE5STx6ZT979mxMpvZ9SjR48GDuuusurr666ywpEBERcaeovILL737ICzOtAeZjMplISYllxIgMzj33FC67bCSpqb29ML+IdIQdb1ewd2EVZn8TFz+XgsmsSqrO59uqNydrMGEhkSziVfUmIiInhUc7i6akpJCSkkJQUBCGYWAYBhaLhbi4OOLi4rBYLMeOBwcHk5ycTHh4OIZhsG3bNq699lruuOMObz0WERGRbsMwDA4cKOK9977mttvmkJ7+cyZO/AOLF2/wdWgi8gMNFXYW/eogAGPujiN2YJCPI5Lva8TBLgrI41OcrCSIXgwkQUtORUTkJPIoAZebm8tdd92F3W5n/PjxLF26lJqaGg4dOsShQ4eoqalh6dKlTJgwAbvdzn333Ud5eTl79uxh9uzZGIbBk08+yfLly731eERERLolwzBYtmwLU6b8iQsu+BMHDxb7OiQROeqzuw5Rc9hOr/6BnHN3vK/DkWMM4Ai17GADNXyAiWKSyGIgQShJKiIiJ5dHCbhly5Zx6623MnXqVD777DPGjx9PQEDAsfGAgADGjx/PZ599xuWXX85NN93EF198QVZWFi+88AKzZs3CMAzmzJnj8QMRERHpKRYt2sCIEb9m1artvg5FpMfL+7KG9c+WAHDxsyn4WT16eS1e04iD3eSTz2KcfE4wsQwiXktORUTERzx6hfCPf/wDwzB49NFHT7gX3COPPILD4eCRRx45duyuu+4CYPXq1Z6EISIi0uOUlFRxwQUPsHr1Tl+HItJj2RucfPSzAwCcen0v0saF+Tgiaa56O0wN21lPDR9iopQk+jIQK1ZfByciIj2YR00Y1q1bR2RkZKs6mvbp04fIyEi++eabY8f69+9PcHAwRUVFnoQhIiLSqY07PY4V/z0DgoZA0hAICT/uHIfDQVlZDSUlVaxZs4dly7bw5ptf0tDQ5Hbe2toGpk17mI0bnyA+PqojH4JIh1uxwhtNTE6uz/9ymJJdjYTG+3H+Yyd+PSwdrQEHuRyiljXAAUJIJl2JNxER6RQ8qoCrrq6mtrYWm812wnObmpqora2lurr6e8f9/f3x8/MoDygiItL5xU2CzJEuk28AFouF2NgIBg5MZtasibz00q/JzZ3DjTdOaXHaw4fLueOO5zsiYhFpweFNdXz598MAXPhMMkFRej3rO81Vb9XsYN3Rqrdy+pDFACXfRESk0/AoAZeWlobNZuO111474bnz58/HZrORlpZ27FhNTQ2VlZX07t3bkzBEREQ6t6AoiE8Hi6VNl8XFRfGf/9zCSy/djtns/il7/vzP2bbtgKdRikgrOe0GH/70AE47DJwWycCpqkD1nQYc7CKPAj4FviSEOAYTR5z2ehMRkU7FowTcjBkzMAyDW2+9lfnz57s97/XXX+fWW2/FZDJxxRVXHDu+ceNGoHkpqoiISLdl9qwyZubMCTz44NUtnvP00ws9uoeItN5XjxdRuKEea6SFC59O9nU4PdR3q97q+BATFfShLwMJJNDXwYmIiBzHo3cEd955J2+//TY7d+7kJz/5CX/4wx8YO3YsiYmJmEwmDh06xMqVK8nNzcUwDAYOHMjvf//7Y9e//PLLAJx33nmePQoRERFfMtnB2rEVaHffPYN581ayY8dBl+PvvfcV//rXTS1WyomI50r3NrDij4cAmPx4H0Lj/X0cUU9Uj50cCqhnLSYOEkoyaUq8iYhIp+ZRAi44OJgVK1Ywc+ZMFi9eTE5ODrm5ud87xzAMACZNmsTLL79McHDwsbHf/va3/OIXvyAzM9OTMERERHzHvxwCt0HZug69jclk4s47pzFr1hMux4uKKtm5M5/Bg1M6NA6RnsxwGnz08zzsDQYZk8IYNiva1yH1MM1Vb1UUsgODdZgJpg9ZxPo6MBERkRPyeLfY2NhYPvnkE7788kveeustNmzYQHFx8bGxESNGMH36dMaMGXPctVp6KiIiXZbJDkG5wHpwVEHQIGB5h97y4ovPwGQyHftw64c2bNjXrgRcTU09n366kVWrdrBlSy45OUcoLa2mtrYBf38/QkICSUrqRWZmPCNH9mf8+FM488x+nj4c6SQKCkpZvHgDX365k1278snNLaKqqp76+kYCA/0JDw8mJSWWfv0SOfvsgZx//nAyMuJ9HbbX7d9/mMWLN/DFFzvZvbuAgweLqa6ux2ZzEBkZQkZGPJcPm0Djynj8Q8xc8lwKJpP2GDt56rCTSwH1fAMUqOpNRES6GK+1azr77LM5++yzvTWdiIhI5+VfDoFbwLkLzL0hbjKEdfwytOjoMAYNSmb79jyX47m5R9o035YtOTzyyLu8++5X1Nc3uTzH4WiioaGJ0tJqtmzJ5b33vgYgPT2Om26awi23XEhgoOddBnNzj5Ce/nOXYzk5c0hLi/P4HgB/+tNrPPDA68cdHzduCCtWPNTitT/72VM8//yS446HhgZx+PBLhIR0TLfF2bOf4KWXlh13PCTEyuHDLxEaGtSueRcsWMv//d/7rFy5HafT6fKcurpG6uoaOXy4nDVr9vDqqysAGDmyH7/+9WXMmHG215Y9n3vuPaxcue244/fffxV/+lPLeyB6MtfixRt45JF3WbZsi9v5SkqqKCmpInRTImOJZ8JfE4lMU+Ln5DCAQqo4zHYM1mMhmCRVvYmISJejjWJERERay2SD4L0QsBiceyHkVMicBL1TwHJynlKTknq5HSsurmrVHGVl1Vx//ZOceurtzJu30m3yrSU5OUe4886XyMi4gXnzVrT5+q5o9uyJLo/X1NTzzjurO+SetbUNvPPOVy7Hpk8f3a7k2/bteZx99u+55JIHWb58q9vkW0u++WYPV131KMOH386aNXvafH1nUFpaxdSpDzFlyp9aTL59l6PJoM9ZIZz5CyV/To467Owgh0I+weArQklgELFKvomISBekBJyIiEhr+JdByGowloHZComTIeMMCA49qWH06hXmdqyurvGE169fn82wYbfx4otL3S5lbYvi4kquu+5xHn/8cRoa2p7I60rGjBlEVlaCyzFXFWre8M47q6mpqXc55i4h2JKXX17Gaaf9mtWrd3kaGgBbtuQyevTveeKJD7wy38myZ08BZ57522MVna1lNpu49PkUzBYtPe1YTuAQlezmGxpYgIU6UulLfwII8HVwIiIi7eKVJajV1dUsWLCALVu2UFZWhs1mc3uuyWTi+eef98ZtRUREOp7JBtYcMK0HZx2EjoCkgRB0chNv32psdP8cazlBFd7Kldu48MIHWpWoa6uVK1dy8cWlfPLJ/QQHd9+lebNmTeC+++Ydd3z58q3k5RWTkuLdypy5c5e6PJ6eHse4cUPaNNejj77L738/1wtRfZ/D4eTXv36egoIyHn30Oq/P722HDpVy/vn3c+BAUZuvTRkbSuyg9i35ldaqw04OB2lgDSYOEUYKaUq8iYhIl+dxAm7u3Lncdttt1NTUHDvm6hP1bzeNVgJORES6DP9SCNwKjt1giYe4c6BXInhpz6v2KC2tdjsWGup+D7LNm3O4+OIHT5h8S0mJ5dJLzyQtrTeJidHU1zdRUFDK5s25LFy4rsUqt88/38a0aX9j4cI/em1fsM5m5swJ3H///OOWbRqGwcsvL+MPf7jSa/c6cKCIFSuO38esOY7xbWoA8Pzzn7Yq+TZiRCaTJp1KUlIveveOoKysmoKCMj7/fBtffLGzxarJxx57j6ioEO6554pWx3WyOZ0GV131qMvkW1hYEOefP5xTT02nd+8IoqPDqKtr5OPHdrNhaza5phxSxoT4IOqewgkUUskRtuJgPX5EkEIW7pfdi4iIdCUeJeAWL17MT3/6UwzDwGq1MmrUKBITE/Hz81pvBxERkZPPZIOgfcAGcNY3V731GQRW37/53rPnkNuxxMRol8erquqYNu1vbpcyAgwdmsaTT/6cceOGuE3sVFXVMWfOYu67b57bfeMWLdrAH//4Gn/5y09aeBRdV0pKLOPHn8LSpZuPG3v55eVeTcC98spytx9qzpo1odXzrF+fza23PtviOVOnjuJvf5tJv35Jbs85eLCYBx98gzlzPnV7zn33vcbpp/fl/POHtzq+k+nFF5eSn1/yvWN9+sTw8MMzmTHjbAICvt9MZc+CSnK2RjLIPJKpixJp6lV7MsPtQWqxkcNBGvkGOEIkKaThT8c3txERETlZPMqUPfLIIxiGwahRo/jggw+IiYnxVlwiIiK+EVAKAVvAuRvMCRA/1udVb9/avTufwsIyt+Pu9ie7++6X2bfvsNvrfvObH/G3v83E37/llwXh4cH85jeXc+mlI5k69W9s23bA5XkPP/w206aNYvjwzBbn66pmz57gMgG3d+8hvvxyB2efPcgr93G3r9zYsYNJT49v1Rx2u4Of/vQpt0uXAwL8mDv3Nn7843EnnCs5OZbnnvsF06aN5oorHqGqqu64c5xOJz//+dPs2PFMh3WF9cQPk29XXXUOzz//K5fLphurHCy4qbnj8Fl39GbIpNZ9zaUtvt3rrYjNONmIhQhSyFTVm4iIdEMevZtYv349JpOJuXPnKvkmIiJdm8kGwTvBbxE4ciD0dOg7CWL7dIrkG8Crr65ocfzMM/sdd2zHjjz+859Fbq/51a8u4bHHrj9h8u27+vZN5NNPHyA9Pc7luMPh5Fe/mtPq+bqaqVNHEx4e7HLMW80YvvxyB9nZhS7H2tJ84b///ZTNm3NcjpnNZl577betSr591+TJI/jgg3sJDHRdnZSXV8zDD7/dpjl9YebM8cyb9xu3exYuubOA6gIbUZmBjH8g8SRH1xPUYGMH2RxmIQYbiSSZIfRS8k1ERLopj95R2O12QkND6du3r7fiEREROfkCSiB4FRgrwRIOfSZD+giwuk6y+EJZWTVPP73Q7fiQIakkJBy/BPWhh946br+yb02adCpPPPGzdsWTkBDNwoV/JCDAdeLuiy92sGLF1nbN3dkFBwcyY8bZLsfefPNLr3SDdZfICwmxMn366FbNYbc7ePjhd9yOP/DAj5k2rXVz/dC5557Cv/51k9vxp55aSGVl512u2b9/Es899wu3exUe+Lya9f9prpa7ZE4K/sGdIwnfPTiBfCrYw2oaWIgfNtLJIEtLTkVEpFvz6NVEZmYmjY2NOBwOb8UjIiJy8piajla9LQYjF8LOgKyJEJPUaareoHlZ39VXP0ZFhfuExlVXnXPcsdLSKt5880uX5wcE+PH00ze2aSP/Hxo4MJk77rjM7fi//vVxu+fu7NxVoVVW1vLee195NHd9faPb79v06aMJDW1dF86PP17nttNn376J/P73U9sdI8B1153H6NEDXI5VVtYyb95Kj+bvSHPm/MJtBZ+t3smHP2teejrihhjSx4edzNC6uW+r3o7wMbCRCJIZTDSu968UERHpTjx6d/GTn/wEm83GJ5984q14RERETo6AYgj5tuotAvpMgfThnarqDaCmpp4rr3yExYs3uj0nODiQG2+cctzxN974ApvN7vKaG2+c0uKG+631hz9cSXS06wTFhx+u6dRVUJ4YM2aQ2z33PF2G+v77X7v9urVl+WlLS5YffnjmcQ0H2spkMvGPf1zvdvyVV5Z7NH9HOeOMvpxzzmC348vvO0TZ3kbCEv2Z9IjnPyMCzVVvBylnD1/SyAIs2Eknk76qehMRkR7DowTc7bffzhlnnMEtt9zC3r17vRWTiIhIxzE1QfD25r3enHkQPhL6Tuw0jRa+Zbc7ePnlZQwffjtvv726xXPvuWcGMTHhxx3/+ON1bq+5/vrzPI4RmpdEzpgxxuVYY6ONZcu2eOU+nZG7TqSffbaZQ4dK2z2vuwReenoc48YNadUcDoeDTz/d5HIsJiacSy45s73hfc9ZZw1g0KBkl2Nr1uyltLTKK/fxppb+7ed9WcNX/9dcNXjxsylYIywnK6xurLnqbS9FLMRgM5GkMoQoonwdmIiIyEnlURfU+fPnc+211/LHP/6RYcOGMX36dEaOHElYWMul+jNnzvTktiIiIu0TUAwBm8CxD/z7QPwIiE4AD5ZhtkZJSRXvv/91i+c4HE7Ky2soLq5k7dq9fP75dkpLq08496hRA1wuJXQ6nXz++XaX1wwenMKpp2a0LvhW+MlPxvPss66r4Zct28Lll4/y2r06k5kzJ3D//fOP22PP4XDyyisruPPOaW2es6CglCVLju+w2ny/8a1eMrxhw363VXRXXjmmTU03TuTaa8dz990vH3fc6XSyYsW2du8z11EuvvgMl8dtdU4+uO4AGHDq7Gj6XRxxkiPrbhxAAeUUswmDzfgRTSoZSryJiEgP5dGrr9mzZx97IWgYBvPmzWPevHktXmMymZSAExGRk8vcCNa9wEZwOiDiLEjsD4Gt20vLU9u353H55Q95fd4BA/rw7rt3u0ymZGcXUl1d7/K6iROHeTWOM8/sR1BQEPX1x99v48b9Xr1XZ5KSEsv48aewdOnxCbOXXlrWrgTcq6+ucNk0w2Qyua24c2Xjxn1ux7z9/Z806VSXCbjmOPZ3qgRc794R9OkT43Js6b1Hl54m+TP58T4nObLuppomcsjFxjdAOdGkkoKfZ289REREujSPngVTUlI82rxZRESkwwUUQcBmcO4DvxSIHw7R8R1e9dbRxo0bwptv/p7evSNdjm/fnuf22hEjvFf9Bs3JofT0dHbs2HHc2LZt7uPoDmbPnuAyAbdz50HWrt3LGWe0rVO8u+WnY8cOJj09vtXzbN9+0O3YiBGZbYrpRIYMScXPz4LdfnxTrm3bDnj1Xp5yV/l5YFUN3zzZvPT0kjkpWCOVKGqf5qq3MorZBGzGQgxppBPp27BEREQ6AY9eXeTm5nopDBERES/7YdVb+ChI7HfSqt46SkRECH/601X88pcXY7G4358qL6/Y7Zg3l59+y10CrrKylurqOsLCOldzC2+ZOnU0t976LFVVdceNzZ27tE0JuDVr9rBzp+vEWVuaL4D7739kZAipqb3bNNeJBAb6M3BgH7ZuPT7ZdvBgiVfv5an4+MjjjjXVOv639PT6XvS9QEtP26eKJg6wnybWYqKCKNJIVtWbiIjIUZ1nt2kRERGvMCDwCASvAL4ASwwkT4G0oV06+XbKKak8+uh15OU9z+23X9Zi8g2gsLDc7ZirJISnoqLc7+vUUixdXXBwIDNmnO1y7PXXV9HUZGv1XO6q30JCrEyf3rZlnIWFZS6Px8d3zP5bCQnRbuLoXN/7iIiQ444tvecQ5fsaCe/jz+T/09LTtnNgkEspe/mCJhbhj4lM0khX8k1EROQ79KwoIiLdh7kRrLuBjWAYR6ve+kOg1deRnZDJZCIgwI/g4MBj+1QNGJDEiBGZnHvuKWRktH75IeB2/zeA8HDvV6MFB7ufs6VYuoPZsyfy/PNLjjteVlbNRx+tbdUeaE1NNl5/fZXLsenTRxMa2rbksbuveUd87wEiIlzP29m+9z98/Lkrq1nzz+ZqwUv+m6qup21WRRO57D+611slUaSRigV9HUVERH7Iawm4kpISli9fzoEDB6irq+OPf/yjt6YWERE5gaNVb/6bwZkDfqmQMAKieneKvd7GjRvCihXeb8LQksZG15VX/v5+BAUFev1+ISHHVxZ9q6Ghyev360zGjBlEVlYC2dmFx43Nnbu0VQm4Dz9cQ1mZ6663bV1+Cu6//+HhHVMF6qqyDDrf997P73+LP5pqji49BUb8vBdZk8N9FVYX5MAgjzLK2IjBVvyJJY10tHxXRETEHY8TcHa7nTvvvJN//etfNDX970XWdxNw5eXlZGRkUF9fz65du0hLS/P0tiIiIs3MDWDdA2wApwkiRkNCvy5R9Sbdx6xZE7jvvuM7wS9atIGiogq3zTK+5W75aXp6HOPGDfFGiPIDn911iIqcJiJSAjj/MS09bb1KGsllHzbWYKKaXqSToqo3ERGRE/B4D7gZM2bwxBNP0NTUxODBg/HzOz6nFxUVxdVXX01TUxNvvvmmp7cUERGhuertMAQvB2M1+MdDyhRIPUXJN8Bq9Xd53GazU1/f6PX71dbWthBLgNfv19nMnDkBs/n4l1V2u4N581a2eG1RUQWLFm1wM+/4dnWcd/c1r6rqmCWhlZWuv/+d9Xufs6yatc80Lz299PkUAsOVPDoxBwb7KSGbz7GzmAD86Usa6Uq+iYiItIJHCbjXX3+dDz74gN69e7Nu3Tq2bNlCdLTrTXhnzJgBwPLlyz25pYiISHPVW/AWsCwCZzFEnQ1Z4yEqrlMsOe0MwsLcLzV01bHTU3V17ufsqH3H2sMwOmbelJRYxo8/xeWYu+q2b7366grsdsdxx00mE7NmTWhXPO6+/x3xvQeorHQ9b0ctefVEY7WDD3/avPT0tBtjyDhPS09PrJJGtrODcj4CdhNDOoMJR187ERGR1vIoAffiiy9iMpl49NFHGT58eIvnnnnmmZhMJnbs2OHJLUVEpEczILAQgpaB8RX4J/2v6i3A+/uadWXuulICHD5c4fX7VVS4nzMhoWM6b7aHu0otb5g923WybPPmHDZt2u/2OncJurFjB5Oe3rbmG99y9zU/fLhjupK6m7elf4e+suT3BVTkNhGRGsCkR5N8HU4nZ8cgh2KyWYmNTwkggL6kqtGCiIhIm3mUgNu4cSMA06ZNO+G5wcHBREREUFRU5MktRUSkpzLXQ8hmsCwGoxSixkDfsc2NFuQ4KSmxbsdaSga11/79rueMjAxpVQfPwEDXS2bBfUOB9igrq/HaXD80depot9V+7pJsmzbtZ8uWXJdj7Wm+8C133/+KiloOHPDua7HGRhs7d+a7HEtOjvHqvTxVvr+R9f8pAeCyF1IJDFMSyb3yo1VvpXwE7CWWdAap6k1ERKSdPErAVVZWEhERQVBQ65YXOJ3Odu1jIiIiPZkB1kMQvAyMryEgCVKnQOoQ8FfVmzuDB6e4Hdu40bsJOMMwyM3NdTk2ZEhqq+Zw10UToLrae/uW5eeXeG2uHwoODmTGjLNdjr322kqXy0znzl3q8vyQECvTp5+4e6o7J/P7v317Hjab3eXYkCHu4/CF3R9UAnD6LTGkTwjzcTSdlR2D/RSzn+VH93qz0o8UNVoQERHxiEcJuKioKCorK2loaDjhuYWFhVRVVREXF+fJLUVEpCcx10HoJjAvBqMcosZC1liIdF/dJc0yM+Pd7gO2bNkWr95r3bq9bveAGz48o1VzBAcH4ufn+s19SUlVu2P7LrvdwZo1e70ylzvuqtaKiir5+ON13ztms9l57bXPXZ4/ffroVlUOutPS193b3//PPtvUrjh8oaHKQWR6AJP+rqWnrpXTwHa2U86HwD5iyWAwYShZKSIi4imPEnAjRowAWtdY4YUXXgBg1KhRntxSRER6hKNVb0HLwfk1+CdDymRIGaSqt1Yym82ce67rpgBbtx5gy5Ycr91r3rwVbscmThza6nkiI11XwW3bltfWkFxat24vtbUn/tDQE2PGDCIrK8Hl2A+XoX7yyXqKiytdnuvJ8lNoTny5+3q+8cYql9V47fXKKytcHm/p36AvXfZCKgGhquT6PhsG+zjCfpYf3estmP6qehMREfEijxJw11xzDYZhcN9991FT435PlUWLFvHggw8e7eY1y5NbiohId2epg5ANYF4ERgVEj2ve601Vb2124YWnuR178UXXSx/bqr6+kTffXOVyzGoNYPz41ifgBg7s4/L4hg372hXbD/373594ZZ4Tcde5dMGCtZSW/q+az93y0/T0OMaNG+JRDBaLhcmTR7gcKyqqZOHCtR7N/621a/eybdsBl2NnndWP6OjOVTmVdGYIaed2rph8r5wGdrCdChZgIoc4MhlMKKG+DkxERKRb8SgBd/XVV3POOeewYcMGzjrrLJ5++mmampoAWLJkCXPmzOHSSy/l4osvpqmpiYsvvpjJkyd7JXAREelunGAtAOtScK4F/1RImwzJg8A/wNfBdUkzZpxNQICfy7F///sT9u0r9PgeDz30ltslopddNtJtUwJXTjsty+Xxjz9e73Ejhvz8El5/3XWi0NtmzpyA2Xz8S6ymJjvz5zcvOS0trWLhwnXHndN8/Xiv7Jl7zTXj3I7dffcrbvdta4vf/OZ5t2PXXjve4/m9LWOikm//Y8NJ9tGqN/vRqrd+JJOM2bO3CCIiIuKCR8+uJpOJ999/n7Fjx7Jjxw5uu+02KioqAJgyZQo33XQTCxcuxOl0ct555zFv3jxvxCwiIt3Nsaq3xWBUQa9x0PcciOhcHRS7ml69wrniijEuxxobbdx22xyP5t+79xCPPfa+2/Gbb76gTfOddlqmy+OVlbW89dYXbZrru5xOJ7NnP0lTk+cJp9ZISYll/HjXSy+/XYY6f/7nLuNpXi3guoKurS644DTS0lx3Cd658yBPPPGhR/O/8spyVq3a4XIsIiKEq692nwD0FUuAmoE1K6OB7Wyjgg+BXFW9iYiIdDiPP96Kiopi2bJlvPTSS5xzzjkEBARgGAaGYWCxWBg1ahRz585l0aJFhIbqSV1ERL7LCdZ8sH4GxjoISIP0KZA8UFVvXnLPPTNcVmMBLFy4jjvvnNuueY8cKefCCx+goaHJ5fg55wxq8zLKKVNOc1uxd9ddL1NT075uqPfc8wpLl25u17XtNXu26yTaunXZbN+ex9y5y1yOjx07mPT0eK/E4Odn4a67prsdv+eeV/joozXtmvuLL3Zw443PuB3/1a8ublP1o5wszVVvh8lhKXY+w0oYA+hDH1W9iYiIdDCvPNOazWauvfZaVqxYQW1tLUVFRRQWFlJXV8cXX3zBzJkz3b74FxGRHspSe7Tq7VOgBnqdC1nnQHgvX0fWrQwcmMzNN09xO/7II+9y772vtGlT/v37DzN58p/Izna9hNViMfPkkz9vc6wxMeFceumZLscKCkqZPv1htwk/V2w2Ozfc8DR///s7bY7FU1OnjnabgLrzzrmsX5/tcszT5gs/9LOfTWLYsHSXY3a7gyuvfIR3313dpjmXLt3MJZc8SH296+9FSkosd945rc2xSkcro55tbKWSjzCRRzyZDCIE1806RERExLu8nhUzm83ExMQQFxeHn5/rT7FFRKQnO1r1FnS06i0wrXmvtz4DwN/f18F1Sw89NJOMDPdVVQ899BYjR/6WL75wvZzwW9XVdTzxxAcMHforNm9230X1rrumM3y46+WkJ3Ljje6ThYsXb2Ts2LtZu3Zvi3M4HA7eeGMVAwfewpw5n35vzF0yytuCgwOZMeNsl2Pu9n4LCbEyffpor8ZhsVh4/vlfEhjo+mervr6JadMe5qqrHj3hnoAFBaXcfPO/mDTpj1RU1Lo8x2w2M2fOLwgJsXocuyeq8lufqO3+mpc6HyGPz3CwlEDC6K+qNxERkZNMGTIRETl5LDUQtBMcW8AIhpjxEJcBfkq8daTw8GDeffduxoy5y+0yzg0b9nHOOXeRltabSy8dSWpqLAkJUTQ02CgoKGXz5hwWLlznturpW5MnD+fPf7663bGed96pTJs2mnfecV2VtXbtXkaO/C3Dh2cwZcoIUlNjiYoKpaqqjuLiKjZs2MeSJZtcJohuuGEyCQlRLSYPvWn27Ik8//ySVp8/ffpoQkODvB7Haadl8cwzN/Kznz3t9pw33ljFG2+s4swz+zFx4lCSknoRGxtBWVk1hw6V8fnn2/n88+0YhtHivR588GrOP3+4tx9CmxRtr6d8vxJwzUqpJx84hU8w4SCBTBKUeBMREfGBVifg8vLyvHbTlJQUr80lIiJdgROCCsC8ARyFYB0AiUMhPNrXgfUYw4al89FHf+Cii/5MXV2j2/Nyc4v45z8/atc9zjlnMO++e4/H204888yNLF++lbKyapfjhmGwYcM+NmzY1+o5J08ezlNP3cBDD73lUWxtMWbMILKyEtwu1f0hby8//a6f/vR8SkurufPOl1o8b82aPaxZs6dd9/jNb37EPfdc0a5rvcXR5OS9n+SeMFHY/TXh5ABHqGLt0WRbOP0IRvvyiYiI+EqrE3Dp6d5ZsmEymbDbT04XMhER6QQsNWDdAcYWIBRiJ0BcuqrefODcc09h5cqHuPzyv5GfX+LVuceOHctHH/2C4OBAj+eKi4vivffu5oILHmgxWdhaF110Om++eScBASf/39ysWRO4774Td4FPT49rc9OKtvr976fRu3ckN930LxobbV6b12Ix8+ij1/HrX1/mtTnba/n9hRzeVI/Fz/TtysseqIQ6DrIbJ2swYSKeOCAI71dXioiISOu1+iPqbzubevrH6XR25OMREZFOwwFBeWBdAs6NENgX0idDUj8l33zo9NP7snnzk8yePRGTyeTxfDEx4bzwwu3ccccdBAV5nnz71tixQ1i58iFSU3u3ew4/Pwv33nsFH374B68kBttj5swJraoInDlzvFe+Hycye/ZE1q9/nNGjB3hlvqFD0/jyy793iuTbgVU1fPn3IwD06u/bPeh8owknezjEAT7DyTICiWQA8Xinq66IiIh4ptUVcDk5J2e/FBER6Qb8qiFwBzi3AmHQeyLEpYFFW492BtHRYbz44m3cfvulPPLIu7z33lcn3Nvth9LT47jxxinccssFWK1BfPyx95f8nX56X7Zte4q//e1tnn56IVVVda26zmw2c+mlZ/LAAz9m6NCT03TBnZSUWMaPP4WlSze7PcdkMjFr1oSTFtPgwSl8+eUjfPTRGv7v/z5g5cptbV6yeeaZ/bj99ku48spzOkWn+8YqB+/PzAUDTp0dzfKcnva7pphaCtiNgzWAiQT6koAJEwY9fTmuiIhI52AytEkGAFVVVURERFCy8GV6RUX6OhwR+Q6b0+DjEoMLY0z4mzu+QkQ84Ti619t6cBZB8MDmvd5CI30dWIerqKjhiSc+dDmWlhbXoft7eaq6uo7FizfyxRc72LIll5ycI5SWVlNX14jFYiY0NIjExGiyshI488y+TJgwlJEj+x+73mYz+PhjgwsvNOHv3zE/o3V1jSxYsJbPPtvEpk05HDhQREVFLU6nQWiolfj4KIYMSWHs2CFcdtlIUlJiOySO7ig/v4RFizawevVOdu7M58CBYiora2losBEY6EdYWBApKbEMGNCHUaMGMHnycDIzE3wd9vd8cF0um+aWEZkWwE2bBxIYbvF1SCdJIw5yOEwtazHYTzBJpH1vrzfDZmB8bGC60ISpg34+RaT99DMq0nnVltby45gfU1lZSXh4uMfzKQF3lBJwIp2XEnBdhF81BG5v3uvNFAExp6nqrYc4GQk4EXd2vlvOm9NywASzV/Yj9ZxQX4d0khRTRz47cbL26F5vCUer3r5Lb+5FOjf9jIp0Xt5OwOldkYiIeMgBQfnNVW9GCVgHQdKQHlH1JiK+VV1o46Mb8gA4+864HpJ8+27VG+wniD6kq8mCiIhIJ9fqBFxeXp7XbpqSkuK1uURExIf8qsC6DZw7gHCInQhxqap6E5EOZxgGH/70APWlDuJPDWL8A51rWaz3GXy719tOHKzBhD9JZBF3XNWbiIiIdD6tfoeUnu6dTYxNJhN2e4/tCy8i0k0c7XBqWg/OMrAOPlr1FuHrwESkh1j37xKyP6nCEmji8lfTsAT4vhlEx2mueis8WvWWQzDJZGClJ3Z7FRER6ZpanYDz1lZx2nJORKSLO1b1tg1M0dD7PIhNBUtP2fRcRHytZHcDn/42H4Dz/p5E78HddfmlARyhhkPswMk6zPiTqKo3ERGRLqjVCbicnJyOjENERDq9o1VvZlW9iYjvOJqcvHtNLvZ6g4zzwhj5y+7a8bYBB7kcOlr1lksIyaSr6k1ERKSLanUCLjU1tSPjEBGRzsyv8mjV2/ajVW+TIDZFVW8ictJ9dvchCtfXERRt4bIXUzF1u+7YzVVv1d+pegtQ1ZuIiEiXp12yRUSkBQ4IOnB0r7dyCBrSXPUW4nkbbhGRttr7cSVf/18RAJe9mEp4nwAfR+RtDdjZzyHqWYuJA4SQQgaBBPo6MBEREfGQEnAiIuKaXyVYt4JjO5h7QexkiO2jqjcR8YnqQ028P+sAAGf+Mpb+l0b6NiCvMoDDVHOI7Risx4KVJLKIVdWbiIhIN+HVBFxRURH5+fnU1ta22Gxh7Nix3rytiIh4k8kO1m+r3iohZBgkDYJgVb2JiG84HQbvXXuAuhI78acGMemRJF+H5EX12MmhgDrWYuYgoSSTpqo3ERGRbsYrCbinn36af/7zn+zbt++E55pMJux2uzduKyIi3uZfDgHbwLkDTLEQNxliklT1JiI+9cXDh8lZVo1/iJlpr6fjZzX7OiQvMIBCqjjMDgzWYSGYPmTRXZtKiIiI9GweJ+Cuuuoq3nrrrRYr3r6rteeJiMhJZLKDNRfMG75T9TYYgsN8HZmI9HB5X9aw4v5CAC58JpmY/t2hC2gddnLJp461mMhX1ZuIiEi359HHh6+//jpvvvkm4eHhvP3229TW1gIQHx+P3W4nPz+fF198kaysLGJiYli6dClOp9MrgYuIiJf4l0PIamAZmPwhcTJknKHkm4j4XH25nXevzsVwwCnXRDFsZrSvQ/KQARyiil2spZ6F+FFNCln0V/JNRESkm/MoATd37lxMJhMPPvggU6dOJSgo6H8Tm80kJiYya9YsNmzYQHJyMj/60Y/Izs72OGgREfECkw2C94L/YnDugdBhkDkJeqdoyamI+JxhGHz0szwq85qIygzkon+nYDJ15YYEddjZTg6FfIKTrwklnkHEasmpiIhIj+BRAm7jxo0A/OQnP/ne8R9WuYWGhvL0009TXV3N3//+d09uKSIi3vDdqjez9TtVb6G+jkxEBID1z5aw890KzP4mpr+eRmBYV/1gwAkUUMluvqGeBZipI40s+hNAgK+DExERkZPEoz3gKioqCAsLIzIy8tgxf3//Y0tRv2vUqFEEBwfz2WefeXJLERHxhMkG1pyje73VQsjw5g6nQUq8iUjncWRrPYtuzwfgvIcTSTw9xMcRtVcddnLIo4G1mDhEBCmkKfEmIiLSA3mUgOvVqxf19fXfOxYZGUlJSQkVFRXfS8x96/Dhw57cUkRE2su/DAK3gHM3mOMhbgz0SgRzd+gmKCLdRVOtg7evzMHRaND3wnDOur23r0NqBydwiEqOsBUnG/AjnBSy6OXrwERERMRHPHrXlZSURFVVFTU1NceODRw4EIDly5d/79wNGzZQV1dHcHCwJ7cUEZG2MtkgaPfRvd72QcgIyDoPYvso+SYinc6i2/Mp2dlAaII/l81NxWTuavu+1WJjB/s5wifAWiLowxB6KfkmIiLSo3n0zmvEiBEArF279tixiy66CMMw+O1vf8vatWux2WysW7eOWbNmYTKZOPvssz2LWEREWs+/FEK+ANNyMAcf3evtNLB21eVcItKdbXujjI3/LQUTTH01jZBYf1+H1AZOIJ8KdvEVDXyEmQbSyKIf/nSlxyEiIiIdwaME3LfJtrfeeuvYsZtvvpmkpCRycnI466yzsFqtjBw5ku3bt+Pn58e9997rcdAiInICJhsE72yuenPkQOjp0FdVbyLSeZXnNLLghjwAzrknnvQJYT6OqC1qsLGDbA7zMbCRSJJV9SYiIiLf4dEecBdeeCHLly//3rLS0NBQli1bxuzZs/nqq6+OHU9JSeGZZ55h5MiRntxSREROJKAU/DeDcw9YkiBhHEQnKPEmIp2Ww2bwzo9zaKxykjw6hHP/lODrkFqpea+3CorYgoON+BNBMhlKvImIiMgPeJSA8/PzY9y4cccd79u3L19++SX5+fkcPHiQiIgIBg4ciMnU1fbwEBHpQkxNELQP2ABGI4SdAUkDwaq9N0Wkc1t6dwEF39RhjbQw9bU0zH5d4TVjDTZyOEATa4AiIkkhTctNRURExCWPEnAn0qdPH/r06dORtxAREYCAEgjYDI694NcHEkZAVLyq3kSk09vxTjlf/aMIgEtfSCUyNdDHEZ2IEyignGK24GQTfkSRSiZRvg5MREREOrEOTcCJiEgHMzVBUDawEZxNED4SkgZAYJCvIxMROaGS3Q18cN0BAEb9tjcDL4/0bUAnVIONXHJpZA1QTCQppKrqTURERE7Iqwm4hoYGysvLsdlsLZ6XkpLizduKiPRMAcVHq96ywb8PxI9o3utNy/1FpAtoqnXw5rT9NFU7SR0bynl/S/J1SC1w8G3V22YMNuFHtKreREREpA08TsDV1dXxyCOPMH/+fLKzs094vslkwm63e3pbEZGey9wI1r00V705IOIsSOyvqjcR6TIMw2DBDXkUb28gNN6P6W+kd+J936ppIodcbKwBSokilVT8tJBERERE2sCjVw4VFRWMHTuW7du3YxhGq65p7XkiIuJCQDEEbAJnNvilQvxwiI5X1ZuIdCnr/l3C1tfKMVlg+psZhMZ3xiWczVVvZRSzCYMt+BNNChmqehMREZF28CgB9+CDD7Jt2zb8/f355S9/yWWXXUZiYiJ+fvpEUETEq35Y9RY+GhL7qepNRLqc/K9rWXR7PgCTHkki9ZxQH0fkShVNHCCHRtZgpoJoUklW1ZuIiIi0m0evIt5//31MJhNPPPEEN998s7diEhGRYwwILAL/TeDMAUsqJA6HqDhVvYlIl1NbbOOtGftx2gwGTY/krF/39nVIP+AA8imlhM3AZvyJIZU0In0cl4iIiHR1Zk8uLigowGw2c91113krHq94+OGHMZlM3H777b4ORUSk/cyNELwNLIvAKITwUdB3vJacikiX5HQYvHt1LlX5Nnr1D+TS51MxdarfZVU0sZ1dlLAQ2EYUaQwmUsk3ERER8QKPKuCio6NpaGjAarV6Kx6PrV27lmeffZahQ4f6OhQRkXYyIPAI+G9urnrzS4WEERDVW4k3EemyVvypkP2fVeMfbOaKdzIIDLf4OqSjHBjkUUYZGzHYij+xpJFOhK8DExERkW7Eowq4MWPGUFlZSUFBgbfi8UhNTQ3XXHMNc+bMISpKG+SKSBdkboDgrWBZDM7DEDEKssZDtJacikjXtWdhJav+chiAS+ak0HtwZ9m/spJGtrGTUhYAO4gmnSFEKPkmIiIiXuZRBdydd97JBx98wIMPPsh//vMfb8XUbrfeeisXXXQR5513Hn/5y19aPLexsZHGxsZjf6+qqgLAZoDNqU6tIp3Jtz+T3ftn04DAYvDfAo488E+B+GEQEdOceLN158cuXZ3t6L9Pm/6digvl+xt57ye5AJx2SwwDZkR1gn8rTgwOUkY5W4AdWIklhTTCADDwdXzeYxz9Whs+/5qLiCv6GRXpvLz9c+lRAu60005j7ty5XH/99dhsNu69914yMjK8FVubvP7662zYsIG1a9e26vy//e1vPPDAA8cdX17lR7Bdv/xEOqMlZUA3elN0vFhg4v/+uv/b/+nOj1m6kyVLQP9e5bucjU723p1DQ4WD4P7B2MYn8vHHneHfiAlIOfoH0o8e7U6Jt+Ms6eaPT6Sr08+oSOdT593pWp2AaymxZrFYmDt3LnPnziU6OpqwsDC355pMJvbt29e2KE/g4MGD3HbbbSxZsqTV+9Hdfffd3HHHHcf+XlVVRXJyMuPD7fSK1DIvkc7E5jRYUgaTosHf3J1+Po92OPXbDM588E+H+FMgMsbXgYm0ic1msGQJTJoE/v7d6WdUPLXwxgLq99cTFOPH9Z+kE97Hl/u+OTDIp/RY1Zs/vUkhDPevW7sDw2bAEmASmPTzKdLp6GdUpBMr9e50rU7A5ebmtuq80tJSSkvdR9kR3a7Wr19PUVERI0aMOHbM4XDw+eef8/TTT9PY2IjF8v0XfIGBgQQGBh43l7+pu73BF+kuDPzNpu7z82muh6DdYGwCLNBrJCT2Bf/jfy+JdA0G/v4mJeDkmA3Pl7D5xVJMZpj+ehq90n35+62CRg6QjY1vMFFPLOkkYaGzNILoWAYGJn+T3tyLdFL6GRXpnLz9M9nqBNyLL77o1Rt708SJE9m6dev3jl133XUMGDCAO++887jkm4iI7xhgLQTLRnDmQUAWJJ4KkbG+DkxExGsOravl41sPAjD+wUQyJob7KBI7BnmUUM4GDLYTQDzpxHbzqjcRERHpfFqdgJs1a1ZHxuGRsLAwhgwZ8r1jISEh9OrV67jjIiI+Y66D4N3g3AT4Q/Q4SMhU1ZuIdCvVh5p4/bL9OBoN+l0SwZi74nwUSTkN5JGNnW+ABnqT0YOq3kRERKRzaXMTBrvdTl1d80504eGt+zTz2w6jISEhqkYTkR7ou1VvB8E/CxKHqepNRLodW72T13+0n+pDNmIHWZn6ahqmk751gB2DAxRTwXoMdhJIPGn0VtWbiIiI+JC5rRdcddVVREVFMXv27FZfc/3117f5Gk+tWLGCJ5544qTdT0TEJUsdhGwA8yIwKiB6LPQdq+SbiHQ7hmHw0c8OcGhtHUHRFn78USaB4Sf7g9dyGtjOdir4CBM5xJHBoG7faEFEREQ6vzYl4LZv3867775LeHg4L7zwQquvmzNnDuHh4cyfP5+9e/e2OUgRka7HCdYCsC4F51rwT4W0yZA8CPwDfB2ciIjXffn3I2x9rRyzH8x4O4OojJO5vN6Gk2yOsJ/l2PmUAILpRzLJWnIqIiIinUKbEnDz5s0D4JZbbiEyMrLV10VFRfHLX/4Sp9PJq6++2qYARUS6HEsdhGwE82IwqqDXOOh7DkTE+DoyEZEOsfvDCpbecwiAC55KJn38yaw4K6OBHWyjgg+BXOLIZDChhJ7EGERERERa1qYE3KpVqzCZTEybNq3NN5o6dSrQvDRURKR7coI1H6yfgbEWAtIgfQokD1TVm4h0W0e21vPuNblgwOm3xHD6TSdriX1z1dthclhKE59hJZT+9KEP5rbvsiIiIiLSodrUhGHPnj2YzWaGDx/e5hsNHToUs9nMrl272nytiEinZ6kF604wtgBW6HUuxGWCv7+vIxMR6TC1xTZev3QfTTVO0ieEMeWJ5JN051LqyWMPTtZgwk4CmSQq8SYiIiKdVpsScBUVFURGRmIytb2bldlsJjIyksrKyjZfKyLSeTnBegj81oOzEAL7NXc4De/l68BERDqUo8nJW9NzqMhtIiozkBlvpWPx7+iOpzac5FJEFWsx2IuVRNIJIaSD7ysiIiLimTYl4IKDg6murm73zWpqaggKCmr39SIinYqlBoJ2gmMLGMHQazzEZajqTUS6PcMw+PgXBznweQ2B4WZ+/FEGQdFtelnZDs1Vb7txsAYzTuLJJEFVbyIiItIltOmVUu/evcnOzmbfvn1kZma26Ub79u2jqamJ1NTUNl0nItL5OCGoACwbwFEI1v5Hq96ifR2YiMhJsebpYjbMKQUTTJufTuzAjvyAtQknBzhCFeuAvQSRRDrBBHfgPUVERES8q00fGZ511lkAvPvuu22+0TvvvAPAyJEj23ytiEinYamBkHVgWgxGPcSOh6wxSr6JSI+xb0kVi3+dD8CkR5Loe2FEB96thDq2s5kqPsTEIRLIZKCSbyIiItLltCkBd/HFF2MYBo8++iiFhYWtvu7QoUM89thjmEwmLr744jYHKSLiew4IygPrEjA2QGBfSJ8MSf3BT0tORaRnKN3TwNtX5GA4YNisaEb9pncH3akJJ3s4xAE+w8kyAolkAIlqtCAiIiJdVJtewUybNo2+fftSWlrK5MmT2bdv3wmvyc7OZsqUKZSUlJCVlcWMGTPaHayIiE/4VTdXvfEp0AQxEyFrNIRF+ToyEZGTpqHCzvxL99FQ4aDPqBAufjalXY25TqyYWnawiWo+xEQhCfRlsKreREREpEtr0x5wZrOZl156ifHjx7N9+3aGDh3KT37yE370ox8xfPhwoqObl2CVlZWxceNG3nvvPV577TXq6uoIDAxk7ty5HfRCTUSkIzia93ozrwdnMQT1h8ShSryJSI/jsBm8fWUOpbsbCU/258p3M/AL9HYlWiMOcjhCLWsw2E8wSaQp8SYiIiLdQpvbVZ111lm8+eabXHvttVRVVfHf//6X//73v27PNwyD0NBQXnnlFUaNGuVRsCIiJ41fNQRuB2MrEA69J0BcGlg6usufiEjnYhgGC27MY9+n1fgHm7nqg0xC47299L6YOvLZebTDqYVEsojHhD64FRERke6hXR9dXnLJJaxbt44ZM2ZgMpkwDMPlH5PJxIwZM1i/fj2XXXaZt2MXEekADgg6AIFLgM1gHQgZkyExS8k3EemRVvypkE0vlmIyw/Q30kkY7s2KtEYc7KKAPD7FyUqC6cVAEkhQ8k1ERES6lXa/m8zKyuKNN96gqKiI5cuXs337dkpLSwHo1asXgwcPZvz48fTu3VGb84qIeJlfFVi3gbEdiICY8yAuVYk3Eemx1j9Xwud/PgzARf9Ood/F3ux4WkQtBceq3vxJJIs4Jd5ERESkW/L4XWXv3r258sorvRGLiIiPHO1waloPzjKwDoKkIRAa6evARER8Zs+CShbenAfA2D/Gc9oNMV6auXmvt0JqWQPkEEwKGVixeml+ERERkc5HZR0i0rN9W/Xm3AamaIg9D3qnqOpNRHq0/G9qeeuK/RhOOPX6Xpz7pwQvzGoARdRQwA6crDta9dZXVW8iIiLSA+gdpoj0UEer3szrwFkO1sFHq968ubxKRKTrKd3bwPyL92GvN8i6IJyL/5PihS72DTjIpZBavgEOEEIy6ap6ExERkR5DCTgR6Xn8Ko9WvW1vrnrrPQliU8Bi8XVkIiI+VXPExrwp2dSV2Ek8PZgZb6Zj8fck+WYAR6jm0LGqt0CSyKK3qt5ERESkR1ECTkR6DpMdrN/u9VYOQUOaq95Cwn0dmYiIzzXVOHjton2U728iKiOAqxdmEhDqyQcTDTjI4RB1rMHEAUJIIYNAAr0Ws4iIiEhXoQSciPQMfhXNVW+O7WDuBbHnQ2yyqt5ERACHzeCtGTkUrq8jOMaPaxZlEdLbv52zfbfqzWAdZqwkkUWsqt5ERESkx1ICTkS6N5MdrLlg2gDOSggZBkmDIFhVbyIiAIZhsODGPLIXVeEfbObqhZn06tvevdnqsZNDAfWsxcRBQkkmTVVvIiIi0uMpASci3Zd/OQRsA+cOMMVC3GSISVLVm4jId6y4v5BNL5ZiMsP0N9JJOjOkHbMYwGGqKWT70aq3YPqQRay3wxURERHpkpSAE5Hux2SHoFxgPRhVR6veBkNwmK8jExHpVNY/V8LnDx4G4KL/pNDv4vZ0gq7DTi4F1PMNUKCqNxEREZHjKAEnIt2LfzkEbgXHLjDHQPxk6KWqNxGRH9r9YQULb84DYNz98Zz285g2zmAAhVRxmO0YbMBC0NG93kRERETk+5SAE5HuwWT7X9WbswZCh0HiYAgO9XVkIiKdzr4lVbx1RQ6GE4b/tBfj7k9o4wzNVW/5R6veDhFKCukEENAR4YqIiIh0eUrAiUjX51/2v6o3SxzEnw3Riap6ExFxIXdlNa9ftg9Ho8GAyyO46N8pmEyt7U7qBA5TyRG24WADFkJJJou2Vs+JiIiI9CxKwIlI12WygTXnaIfTWggdDomDVPUmIuLGwa9qeO2ifdjrDfpeFM7019Ox+Lc2+VaHnRwO0sAaTBQQRqqq3kRERERaRQk4Eema/Eubq96cu8ESD3FjoFcimM2+jkxEpFM6tK6WeVOysdU6yTgvjCvezsAS0JrfmU6gkEqOsBUnG7AQTgp96dXRIYuIiIh0G0rAiUjXYrJB0D5gAzjrIWQE9BkE1hBfRyYi0mkd3lzHK+dn01jlJHVsKFd9kImftTXJt1ps5HCQRtYAhYSTSjr++Hd0yCIiIiLdihJwItJ1BJSBdUtz1Zs5AeLHqupNROQEinfU88qkbBrKHfQ5K4QfL8jEP/hEvzedwCEqKWIzTjZiIYIUslT1JiIiItIuSsCJSOdnsgMW8FsKjhoIOx2SBqrqTUTkBEr3NvDyxL3UFdtJOC2Yaz7JJDDsRA1qmqve8o5WvR0hghTSVPUmIiIi4gEl4ESkcwsoBcs24Bwwh0HS2RCdoKo3EZETKM9p5OUJe6k5bCduaBA/WZyFNbKll37NVW8VFLEFBxvxJ4JkMlX1JiIiIuIxJeBEpHMyNX1nrzdn87HMcRAa7NOwRES6gsqDTbw8cS9V+TZiBlq5dkkWwb1aetlXg41cDtDIGkwUEamqNxEREREvUgJORDqfgBII2AyOveDXB+JPgzwgMMjXkYmIdHrVhTZenriXipwmorMCmflZFiG93SXSnEAB5RSzBSeb8COSFDKJPpkhi4iIiHR7SsCJSOfxvaq3Jgg/s3mvN7MVMHwdnYhIp1dbbOOV8/ZStreRyLQAZi7rS1higJuzm6veco/u9VZMJCmkqupNREREpAMoAScinUNA8dGqt2zw7wPxI5r3ejOZwKbkm4jIidSX2XllUjbFOxoIS/Jn5rK+RCS7Sr45+LbqbTMGm/AjmlQyiTrZIYuIiIj0GErAiYhvmRvBmk1z1ZsDIs6CxP5abioi0gY1h228cv5eirY2EBLnx6xlfYlKD3RxZjVN5JCLjTVAKVGkkoqfXhKKiIiIdCi92hIR3wkohoBN4NgH/ikQPxyi45ur3kREpFUqcht5+bxsyvc1Eprgz8zPsujVz/qDs5qr3sooZhMGW/AnmhQyVPUmIiKdxJHcI/w8/ecux+bkzCEuLe4kRyTiXUrAicjJZ24E615go6reREQ8ULyznlcmZVNdYCMyPYCZn/UlKuOHlW9VNHGAHBpZg5kKokklWVVvItKi2spaqkurqa2opbaylsbaRgKCAggMCSQoNIiI3hFE9o70dZgiIl2GXnmJyMkVUNRc9ebcD5ZUSBwOUXGqehMRaaPCDXW8OjmbuhI7sYOsXLsk6wcNFxxAPqWUsBnYjD8xpJJGpG8CFpFOLX9XPmsXrmXvmr3sXbuXIzlHTnhNYHAgvdN6E58RT8bwDLJOzyLr9Cx6JfY6CRGLiHQtSsCJyMlhbgTrHmAjGE4IH3W06u2Hy6REROREDqyqYf7F2TRWOUk8PZhrPskiOOa7L+uqaCKX/TSxBhMVRJFGiqreROR77DY7X7z5BYufW8z2z7e3+frGukYO7jjIwR0HWbtg7bHjMckxjJg8ghFTRjDsvGGERIR4M2wRkS5Jr8JEpIMZEFgE/pvAmQN+qZAwAqJ6q+pNRKQdshdV8sbU/djrDVLHhfLjDzMJDLccHXVgkEcZZWzEYBsBxJBKOhE+jVlEOp+9a/fyz+v/yYFtB7w+d8nBEj7976d8+t9PsfhZ+Mfaf5BxaobX7yMi0pUoASciHcfc8L+qNycQMQoSVPUmItJe298q591rcnHaDPpeFM6MtzLwDzIfHa2kkVz20cRazFQSTRqpWLC0OKeI9CxOp5NX//Aq7z7yLk6Hs8Pv57A7aGpo6vD7iIh0dkrAiUgHMCDwSHPVmyMXAtIgYThEqupNRKS9NjxfwoIb8jCcMOSqKH70choWfxPfVr2VHqt6C6Q3aaQT7uuQRaSTcTqd/OOaf7Dq9VW+DkVEpMdRAk5EvOtY1dsGcJoh6mxI6AcBP+zKJyIirfXV40f49I4CAEbcEMNF/0rGbDHRXPV2gOyje73V0It0UlT1JiIuPX/H861KvvU7sx+nXXgaaUPTSB6UTGhUKEFhQZgtZmrKaqguq6biSAX7N+4ne1022euyObT30El4BCIiXZcScCLiJd9WvW0ExwEIyICEU5v3ehMRkXYxDIMVfyrk8z8fBmD073pz3t+TMJkcGBykhDI2YWIr/sSRTpqq3kTEjfWfrOejJz9yO242mzn32nO56v6riE+Pd3teVHwUUfFRpAxKYej4oceOH95/mNXvrOard79izzd7MAzDq/FL9xeXFseHxoe+DkOkwygBJyKeM9dD0G4wNh+tehsDiX3BX1VvIiLtZTgNFv06nzX/LAZgwkOJjLkrDpPp26o3G99gop4YMkhS1ZuIuOVwOJhz2xy346FRodzz/j0MGTuk3feIz4hn6u+mMvV3Uyk6UMTCpxey5Pkl1JTXtHtOEZHuRAk4EfGAAYGHwW8jOA9AQBYkngqRsb4OTESkS2uqdfDetbnseq8SgAueTubMW6MwyKGYcjZgsINA4kgjljAfRysind1X737ldologDWAvy7/K+nD0r12v96pvbnu0eu4+oGrWfbyMsJ7qTpXREQJOBFpH3MdBO0BYyPgD9HjICFTVW8iIh6qym9i/qX7OLyxHkuAicteTOWUq000sJ192PkGqKc36ap6E5FWWvHKCrdjP37gx15Nvn1XYHAgF9x0QYfMLSLS1SgBJyJtZIC18GjV20Hwz4LEYap6ExHxgkPrapl/6X5qCm0Ex/px1fup9BldQhEVrMdgJ4HEq+pNRNrAYXewdcVWl2MBQQFccLMSZCIiJ4MScCLSeuY6CNoFzk3gDITosRCfBf4Bvo5MRKTL2/F2Oe/NzMVebxA72MrVC2KwpuWyHTvfYKKBWO31JiJtdmjvIeqr612ODR0/lOCw4JMckYhIz6QEnIi0ghOsh8GyAZz5ENAXkoZBRMzJjcJhUF1ix1brwN5o4GgycDQaOJqc3/m7E0eTcezvTruBf7CZgFAzAaEWAsP+9/8BYc3/9bOaMJlMJ/WxiIh8yzAMVv31MMvvKwQg64JQpr5uoir8IF8drXpLIJ3ehPo4UhHpio7kHHE71juta3Wrr6+pZ9fqXeRuyeXgzoPk78qn4nAFdVV11FXVgdFc1RcaHUpMnxiSByWTdXoWw88fTu/UrvVYTybDMNizZg9bl29lzzd7KNxXSNmhMhprG3HYHVhDrIT1CiMuPY60oWkMOmcQw88fjjXE6uvQvcrhcLBr9S42frqRnE05FOwuoKqkioaaBsx+ZiJiI+gzoA+/mfcbwmO0r6G0nRJwItIySx1YdzZ3ODUCodc4iM/0etVbU42DqgIb1QU2qgqajv7XRnVBE1X5Nor329hcYcNwePW2AJgsNCfkQs1YIy1EJAcQnuxPeHIAESkBx/4ekRyAn9Xs/QBEpMeyNzj58GcH2DqvHICRt4cz9tEa9vo1V73ZiSeTRMzod4+ItE9tZa3bsZDIkJMYSfvs37Sf1W+vZsuyLexduxeHveUXg3abnbqqOopyi9jxxQ4WP7cYgKzTs7jo1os499pzsVjaV0ncWNfIrIRZzcm+H5g4eyK3vXhbu+Y9kfqaembFz6KhtuG4sQmzJnD73NvbNW9dVR0Lnl7Ap899StGBIrfn1VbWUltZy+H9h9m8dDMfPP4BgcGBjJ42mml3TSNlUEq77v9DR3KP8PP0n7scm5Mzh7i0uA6Zq7G+kQX/XMDCZxZScrDE9YQ2KM4rpjivmPqaeiXgpF2UgBMRN5xH93rbAM4CCOjXXPUW3sujWRurHRzZXE/hxjoOb6zn8KY6yvc10ljlbNX1JjP4h5ixBJjwC2z+ryXQ5OLvZvwCTZgsYK83aKx20FTjbP5z9P9tdc33NBzQWOmgsdJBdYGN4u3Hv7j5VnCsHxHJ/kSkBBCeHEBUZiC9h1iJOyWIkN7+Hn1tRKRnqS2y8fqP9pP/VS0mC1zwTCDJN1ayEtiJlQTSCFXVm4h0oOqyal+H4Nbrf36dla+tpGB3gVfmy16XzZPXPcnbD7/NL+b8gsHnDG7zHIHBgZw942yWPL/kuLHVb6/mxqdv7JCqsNXvrHaZfIPmxF97fPbiZ7z42xfb/W+gsa6R5a8sZ8WrKzj/5+cz6++zCI3ses9Zm5dt5qmfPkVRrvsEpIi3KAEnIsez1B6tetsChhV6nQtxmeDftgRTbbGNwxu/k2zbWEfp3kYwXJ8fEGYmPMmfsKSAo/9t/v/gOD+25vozeUYAkUn+mP28s1zU6TCw1TppqmlOyDVWO6kvtVOV30RlXhOVB21UHWyi6mATlXk2bHVO6ort1BXbKdxw/F4qwbF+9B5ipfeQIHqfEtT8/4ODCAzXfk0i8n1HttYz/5J9VB5owhpp5rK3DRonNvARYCdOVW8i4jXhvdxX6uzfuP8kRtI2bz30FrZGm9fnLdhdwL3j72X2I7P50R0/avP1E2dPdJmAq6+p56t3v2L8teO9EOX3LXtpmcvjcelxDBk3pE1zNdQ28MTsJ1j99mpvhIZhGCx+bjEbP93IvR/cS/rQjumo2xEWPbuIZ3/x7AmrKkW8RQk4EfkOJ1gPgd96cBZCYL/mDqetqHozDIOirfVkL6oib1UNhRvrqS5w/aIpLMmfhOFBxA8PJn54MLEDrYQl+RMY5jpRZbMZ7PvYICzR5LXkG4DZYiIw3NKqBJlhGDSUO6g82JycqzpoozKvidI9DRRta6Asu5G6Yju5y2vIXV7zvWsjUgLofUpzYi7htGCSR4UQ3keNK0R6qj0LK3nnqhyaapxEZ5mYtMBBdn8newgikXRC6PxLwkSk6wiPdZ+Ay16bTeG+QhIyE05iRL7ndDh54Tcv4LA5mHbntDZdO2jMIBKyEijMLjxubOncpV5PwBUdKGLbim0ux8bPHN+mfYzrquu4//z72f31bm+Fd0xRbhF3jbmLBz59gAFnDfD6/N62/NXl/Pvmf2MYbioDRDqAEnAi0uxY1dtmMIKh13iIy2ix6q2+3M7+z6rJXlTFvkVVVB/6QcLNBL36Bh5NtAWRMDyY+FO75lJNk8lEULQfQdF+xA87vluYrc5J8c4GirbVN//Z2vz/1QXNibrKvCb2Lqw6dn54H3/6jAoheXQofUaFkDA8CEuAql1EujPDMPj68SKW/K4AwwnJ58KQtx183suEgwRVvYlIh0gemEyANYCmhqbjxpxOJ/+9/b/c+8G9mM1d4/dPgDWAlMEppA1LIz4jnuCIYEIiQggICqCuqo7ailoO7jhI9rpscrfktphgefnul0kbmsZpF5zWphgmzJrAvPvmHXd86/KtFOcVE5sS2+bH5c6yl5e5fAwmk4kJsya0eh6H3cFfL/vrCZNvAUEBnH7h6aQNSyM6MZrA4EDKDpVxJOcIaz5c436PNKC+up4HpjzAI189QvLA5FbHdrLlbcvj6Z897fLrmpCVwIgpI+id2puI3hEEWAOoqaihYFcBm5duJndL7skPWLoNJeBEerzvVL05CsHa/2jVW/RxZxpOg0Pr644l3PK/rsX4ztZtfkEm0ieEkTEpnMTTg4kbGuS2qq278Q82k3haMImnfT85V19up3h7A0e21nNkSz0F39RyZEs9Vfk2drxVwY63KgCwBJpIPC2YPqNCmhNzo0IIS1SVnEh3UV9m58OfHmDX+5UADPiZgfUZWBVgpQ8ZBHN8Yl9ExBsCrAEMPHsgm5dudjm+dsFanpz9JDf96yaCQoNOcnStk9Q/iZGXjeSsH51F3zP7trqJwuH9h1k8ZzEfPfkRTfXHJyANw+CZG57hmZ3PtOmxT5g5gfn3z8fp/P4exoZhsPyV5Vxx7xWtnutElr+83OXxwWMHE58e3+p5Xr77ZbYu3+p23Bpi5ZoHr2HSzyYRHOb6OenGp25k64qtPPfL58jbnufynNrKWh66/CEeX/94p+2S+u+b/33c8ubTLjiNmQ/PPOES2j1r9hAa1fX2upPOQQk4kZ7MUvOdvd5CIHYCxKWD3/8q1BqrHOz+sKI56ba4mroS+/emiB1kJXNKOH0vCCdlTKi6hP5AUJQfKWNCSRnzvyfqploHh9bWcfCrWvKP/qkrsXNwdS0HV/+vU1lEagDp40NJnxhG+sRwwhK6XuWgiMDBr2p456pcKvOasATAwMcMSn5hAlM8WcSr6k1EOtyoaaPcJuAAlr+ynG0rt/Gj3/yIiddNdJuAOZnMFjOjpo7i8t9d3u4ljfEZ8cz62ywm/XQS/7j6H+xdu/e4c0ryS1j49EKm3zW91fPGpsRyyvhTXH5Nl720zGsJuB1f7HC51BXa1nxhz5o9fPB/H7gdTz81nbvfuZv4jJYTeiaTiaHjh/L4hsd58bcvsuCpBS7PK9hdwLz75vHT//tpq2M8mUry/1fF5xfgx69f/jXnXHlOq67td2a/jgpLegAl4ER6JCcEFYB5PRiHIXAgJA2FsCigudItZ3k1m+eWseOdcuz1/yvPDgw3k3FeOJlTwsmaHE5Eiqq02iogxELauWGknRsGNH9aWpbdSP5XtceSckVb66k80MSmuWVsmlsGNCc7088LI2NiGKnjwrBG9IzqQpGuynAarH7sCEvvOYThgPBMg4Q3IPe0QFW9ichJNen6Sbz90NvfSzz8UHFeMXNum8NLd73EsInDOOPiMxg0ZhB9BvbxyfLUp7Y91aYKr5YkZiXy5yV/5r7z7iN7XfZx4x89+RGX/+7yVlfWAUyYPcFlAu7Q3kPsXL2TgaMHehQzuG++YA2xMnr66FbPM+e2OcdV630rsW8iDyx+gMjeka2ezz/Anxv+eQP2JjuLnl3k8pyP/vkRU26aQlK/pFbPe7L5Bfhxz3v3cPqFp/s6FOkhlIAT6WksNWDdDsZWIBRiz4PeqeDnT9m+Rja/VMrml8qozPtfmX7MgEAGXB5J1gUR9DkrBIu/9xohSPOnib36WunV18qwmc0NLxqrHeR/XUvO0mr2f1ZN4YY6inc0ULyjgTX/LMZkgaQzQo4l5PqMCsEvUFU0Ip1FbbGN92ceIHtR896PiVcZ2J6FyvAE+pKACf0eFZGTxz/Qn1l/n8U/rvnHCc9tqm9i7YK1rF2wFoDg8GCyTs/63h9vJcZa4u17hESE8LvXf8cvBv/iuOWH5YfL2fTppjbtBTd66mievfVZ6qrqjhtb9tIyjxNwjfWNfPHmF67vPX10q5fMbvpsk9t93wKsAfzx4z+2Kfn2XTf96yYKdhewdcXxS1udDidvPfQWt8+9vV1znwwz7pmh5JucVErAifQYjuaqN8t6cBRD8ABIHEqjEcaOVyrYPLeUA5//r3tnYISFIT+OYvh1vUg8I7hNHZbEc4FhFjInhZM5qblzWX2ZnZzl1ccScmV7G8n/upb8r2tZ9ZfD+AWZSB0bRt+Lwul3UQRRGYE+fgQiPVfuymrevTqH6kN2LFaDxKcMyn8aRB9TuqreRMRnxl09jv0b9/PeY++16bq6qjq2LNvClmVbjh2LiI1g8NjBDBk3hMFjB5M+rOV9szqLhMwEJt8w2eXSyfWfrG9TAi4wOJCzZ5zNkueXHDf2xRtf8PMnf06Atf0rRb5+72uXyT1o2/LTj//1sduxqXdOJTErsc2xfctsNnPj0zdy26m34bA7jhtf9foqfvb4zzrlnml9BvRh+t2tX3Ys4g1KwIn0BH7VEHi06s0Ix4gZz4HdsWz6awU73s7FVtdckm4yQ+b54QybHc2AyyK1n1snEhTtx6BpUQya1rxMuDKvif1Lq8lZWsX+z6qpPWJn3+Iq9i2uYtGv8okZaKXfxeH0vSiC5NGhqloUOQmcDoNVfz3MygcKMZwQOtAg4A0TtlNU9SYincOsv8+ivqaeRf9xvWywtSqLK1n9zmpWv7MaaO4cOWHWBMZfO57eqb29EWqHGT1ttMsE3PbPt7d5romzJ7pMwNVW1vL1+18z9qqx7YoR3C8/jUuPY8i4Ia2ao6aihnUL17kci+gd0aZ979xJGZzCpJ9OcrkU1dZo44s3v2DKjVM8vo+3XfzLi/EP0P7KcnIpASfSrR2tejOvA4qxMYhNS1P46ulqyvfvP3ZWr36BnHpdL4ZeG014kvZ06woiUgIYfl0vhl/XC8MwKN7eQPbiKvYuqCTvixpKdjZQsrOB1Y8WYY20kDk5nH4Xh5M1JYLgGP3qF/G26kIb716zn9zlzY1Uoq4zsD1lJS4kgyA6Z1dBEel5zGYzt/z7FgaOHsh/b/8v1WXVXpm3MLuQeffN47U/vsbYH4/l2oeu7bSJuP6j+rs8fnDnQRx2Bxa/1u8DN2jMIBKyElw2Slj20rJ2J+BKC0rZ/JnrphnjZ45v9cqUzZ9txt5kdzk29sdjParQ+67zrj/P7V5w6z5e1+kScAHWAMZe3f7kqEh76V2YSHflV3V0r7dtNFRHsW7hGL5+wUHtkVKguZnC4KuiOXV2NH3OCtES0y7MZDLRe0gQvYcEMfo3cTRU2Nn3aTV7FlSS/UkVdSV2tr9RzvY3yjGZoc9ZIfS9KIJ+l0TQe4hV33sRD+37tIp3f7KfumInlhCD4H9D0LVJpBGnqjcR6ZTGXzue0y86nbcffptF/1lEfXW9V+Y1DIOVr63kq3e/Yurvp3LV/Vf5pIFDS/wD/AmNCqWmvOZ7x+1Ndo7kHCGxb9uWZE6YNYF598077vimJZsoPVRKr8RebY5x+SvLXTZNMJlMTJg1odXzbF1+/N5s3zr3J+e2OS53+p3Zj6T+SRTsLjhubNuKbRiG0alebw48eyChkZ1vWax0f0rAiXQ7DgjKB/M6aksq+fqNoax9PZDGykYAIlIDGP27OIZf1wv/4M71gki8wxrpx+Arohh8RRROh0HBmlr2LKhk78Iqjmyu5+DqWg6urmXZvYeIygxk4NQIBlweSZ+RIZjMnefFkUhn11TrYPkf8/n6/5o/2LAONbC8GUhy/yysWH0cnYhIy8Kiw7jukeu48g9XsmLeCla8uoLdX+3GMAyP525qaOL1P79O9rpsfjv/twSHd8z+l06nk7JDZVQWV1JTXoO90Y6tyQYneAjuqtzKCsvanoCbOYH5988/LmHmdDhZ8eoKpv1+WpvmA/fLTwePHdym5hT7N+53eTwkIoSs07LaHFdLTp10qssEXF1VHYX7Cj3aa87bMkZk+DoE6aGUgBPpTvyqwLqNivw9rH45lY3vp2NvAHASM9DKmLviGPLjaO0H1oOYLSaSR4WSPCqUiX9NovJgE3s/rmTPR5Xs/6ya8n2NrH60iNWPFhGa4E//yyIYeHkkaeeGYglQglbEnX1LKllwYy4VOc2bTgfdApH/SCTeGq+qNxHpUoLDg7nw5gu58OYLKT9czsZPN7Jl2RZ2f7WbQ3sPeZSQW/fxOu459x7+/sXfCQz2vEFUdVk16z5ex7YV29izZg+H9hw6rqOpR/OXtn1JbmxKLKeMP4XNS49fMrrspWVtTsDtWbOH/F35Lsfa0nwBIG97nsvjGcMzvF6RljHcfVIrb1te50rAtRCrSEdSAk6kW3BAUB7FuVv48oUgtn5yCk5785Nq4hnBnHNPPP0vjVB1kxCRHMDpN8Zy+o2xNNU42PtJFbveq2DvwkpqCm2s/08J6/9TQmCEhX4XhzPg8kiypoQTENL6/VBEurO6Ujuf/iaPzS9VAOCfbOD370DSL1LVm4h0fVHxUUyYOYEJM5uXOdZW1rJ/4372bdjHvg37yF6X7bLKqSX7N+7nqZ89xW9f+22749q7di/vPvou37z/DXab6z3NvKGpoald102YPcFlAu7gjoPsXbuXvmf0bfVcS+cudXncGmJl9PTRrZ6ntrLWbRfV9FO937U241T3Sa2SgyVev58nouKjfB2C9FBKwIl0dX6VFO7fzqo59exc1geM5iRb+sQwxtwdR/qEsE6154J0HgGhFgbPiGLwjCgcTU5yllWz871Kdn9QQe0RO1vnlbN1Xjl+VhOZk8MZOC2S/pdEYI3UU4f0PIZhsP3Nchb9Ko/aIieYDIJ+YSLirwkkhKnDqYh0TyERIZxy7imccu4px46VHyln24ptrH5nNWsXrKWp/sRJq8/nf84Zl5zBuB+Pa9P9a8preO5Xz7Hi1RVtDb1d3DUsOJHRU0fz7K3Pukx4LX1paasTcLZGG6teX+X6HtNHExTa+qY+5YXlbsc6IgEVleB+zrLCMq/fzxMhESG+DkF6KL2LEumyHFRX57D06QI2fxQGRysvBvwogjF3x5N0pp5YpPUsAWaypkSQNSWCi/6VTP7Xtex6r4Jd71VQvr+J3R9UsvuDSsz+JjInhTFwehQDLosgKFpPI9L9VR5s4uNbctmzoHnD7sBBBpb/BpI+qi+BeL6kSkSkK4mKi+KcK8/hnCvPoa66joVPL+T9x94/YUfVNx98k3OuPKfVTRnyd+XzwIUPcCTniDfCbp12rrYNDA7k7Blns+T5JceNrZq/ip/+30/xD/A/4TxrPlpzXHOIb7V1+WlLjTWCwr3fnbulpJa3mnx4S0c8fpHW0AY/Il2QzV7O56+t5akflR9NvsGQqyK5edtArnwvU8k38YjZYiLl7FDOf6wPv8wezE2bBzDu/nhiB1tx2gz2flzFh9cf4LG4Lbw6eS/r55RQW+y9/VdEOgvDabDmmSL+NWg7exbUYPI3CH4AYjb2of+owUq+iUiPFxwWzIy7Z/CvXf9i+OThLZ57cOdB1ny4plXzFucV84cJfzi5yTcPuUuQVZdVs/ajta2aw93y07j0OIaMG9KmeFraG68jmmIEBge6bW5ha+hcrxPdxSnS0VS6INKFGNjYsSqbJU9UUVkYAECfkVam/DNVSTfpECaTibihwcQNDebcPyVSvLOene9UsOPtCo5srmffp9Xs+7SahTdB2rlhDJoRyYDLIwmNO/GnvCKdWfGOej76eS4HVzd/ah80GsxzgkkblKHEm4jID0TERvDHhX/koR89xNoF7pNN6z5ex1k/OqvFuZxOJ4/++NETLluMTYllyLlDyBieQWJWItFJ0UTERhAUFnQsGeRuG5afpf2MogNFJ35gbTBozCASshIozC48bmzZS8sYPa3l/dsqjlSwcfFGl2PjZ47XljIi3YAScCJdRGH2ERY9kUfeBgvgT3iimfP+3och1/TSE7KcNLEDg4j9QxBj/5BA6d6GY8m4wvV15CyrJmdZNQtvOUjq2FAGTY9k4NRIwhIDfB22SKvZG5x8+chhVv31MI4msIQaWB82EXVzH3qbe/s6PBGRTstisfCbeb/hhswbqCqpcnnOlmVbTjjP8leWs2v1Lrfjp190Olf84QoGnDWg3bE6Hc52X9uSCbMmMO++eccdX//JeiqKKojsHen22pXzV+KwO447bjKZmDBrQptj8be6/zDUXXMGTzTWNbqM/0SxiPQkWoIq0snVlNXzwd+38tysfPI2WPCzGoy7N5pf7B3KKT+JUfJNfKZXXytj7ornhnUD+NX+wZz3SBJJZwaDAQdW1vDJL/P5vz7bePGc3XzzzyKq8tvXWUzkZHA6DDa/XMrT/bex4v7m5FvoRQZBO4JJu3Wwkm8iIq0QHB7MZXdc5nb88L7D1Ne0vB/Y+4+973bs+n9czx8X/NGj5Bvgdp81T02YOcHlHncOu4OV81a2eO2yV5a5PD547GDi0+PbHEtQmPt9zuqrvL8nW21lrduxjljyKtIVKQEn0knZG52sejWHp67YwaYPbGCYOGVaIL/YOYhz/5KGf7B+fKXziEoP5OzfxfGzbwZwW+5gzv9HEn1GhYABeV/Usui2fB5P3sYLZ+/mq8ePUHlQyTjpHAzDYO8nlTw3YifvzzpAZZ6dwCSD0PkQ+VEy/ZIHasmpiEgbjLx0ZIvjlcWVbsfytudxYNsBl2NTbpzCj+74kSehAWBrstFQ2+DxPK7EpsRyyvhTXI4te8l1gg1g//795G7NdTnW1uYL34pOiHY7Vn7YfYfU9mppzpY6pIr0JFqCKtIJ7fmyjE+eOEBFgQGYSBrqZMqTKfQ5VxUY0vlFpgYy6o44Rt0RR1V+EzveqWDn2+XkfVnLwdXNfz69o4CkkcEMmh7FoOmRRKYpwSEn36F1tSz5fQG5y5srIfwjDCLvNmj4VSipQRkEoOXTIiJtlTI4BT9/P+w2u8vx6pJqtxVdW1dsdXnc4mfhmgev8Up8JQdLvDKPOxNmT2Dz0s3HHc/ZnEPO5hzSh6UfN7ZsmevknDXEyujpLe8d505weDAhESEuK9NyNuW0a86W7N+43+1YTHKM1+8n0hWphEakE2motvP+X/cw/3e5VBQYhPW2c/kzYfx03alKvkmXFN4ngLNu6811q/pzR/4QLniqD6ljQ8EEBd/UseR3BTyZvp05Z+zii4cPU7qnYz6RFvmusuwG3r5yP3PO2E3u8hosAZDyGych+00E3ZlG36ABSr6JiHggrFeY2zF3iTloroBzZfDYwUTERngcF9Di/nLeMHrqaLdLLl11ObXb7Kxatcr1XNNHExTqfinpiSQPTnZ5fP8m98my9mopqZc6JNXr9xPpipSAE+kksr8u41/XbmXzwhowGYz6qYNfbBvA0Fv6YvJXsap0fWGJAZz5i97MXtmPOwpO4cJnkkk7NxSTGQ6tq2Pp3Yd4uv8O/n3KDpbff4jDm+swDMPXYUs3Ultk4+NfHuSZgTvY/mYFmCBjpkHaHih/LIw+0UOIQZ/Si4h4qqUlntYQq9ux0oJSl8cT+yZ6HNO3dn6502tzuRIYHMjZM852ObbyteMbLaz/ZD2Vla6X5bZ3+em3MoZnuDxeW1HLvg37PJr7h1xV/QGERIQQn9H2PexEuiMl4ER8rLHWwYd/38O8O3KpLjKITrVx/UfRnP/caQTEhvs6PJEOEZbgzxm3xDJreT/uOHQKFz+bQub5YZj9oGhbA5//+TDPnrqLp/ruYMnv88n/phbDqWSctE9TjYOVfy7kn5nbWft0MU47pF0AZ250Uv6SGXtqKn3pr6o3EREvqK+pp77a/Sb/vfr0cjvWWNvo8nhLFXVt0VjfyJdvf+mVuVriLnFWWVTJ+k/Wf++Yu+YLcelxDBk3xKM4hk4Y6nZsxasrPJr7u7LXZ3Nwx0GXY6eMP0VN40SOUlmNiA/tX1vOh3/LpfKwASaDkbMMJj42EP9eSrxJzxEa589pN8Rw2g0x1Jfb2bOgkp3vVLBvcRXl+xpZ/WgRqx8tIizJnwGXRzJoWiQpY0Ix++nFnLSstsjG2n+XsPaZYuqKm5c8JZxuYsgjTvLGwy7CSSUdf/x9HKmISPexZdkWt2Nh0WGEt/A6NzDE9Z6wtRXuO2y2xYpXV1BdWu2VuVoyaMwgErISKMwuPG5s6dylnHnJmQBUlVax7pN1LucYP3O8x4mrYROH4R/oj63RdtzY5/M/Z+bfZuIf6Plz4GcvfOZ27LQLT/N4fpHuQgk4ER9oqnOw5N/7WPdO88bfUX3sXPZMDKkXp4GL1uUiPUVQlB/Dru3FsGt70VTjIHtRFTvfqWDPgkqqC2ysfbqYtU8XE9TLQt8LI+h/aQSZ54cTGG7xdejSiRRtq+frJ4rY8moZjsbmysmoTAujHrJTN93JOrMf4SSThfsqDBERaZ/lryx3OzZwzMAWrw2PcZ2cc9cZtS1qK2t58y9vejxPa02YNYF598077vjaBWupLqsmLDqMz1/7HHvT8XvimUwmJsya4HEMIREhnH7R6Xz17lfHjZUfLue9x97jinuv8Oge+bvy+XTOpy7H/AP93S7HFemJ9E5f5CTL3VjOv2dtOZZ8O+MnBjdtGkjqpRlKvol8R0CohUHTo5g2P53fFQ/lxwsyOfW6XgRFW6gvdbDllTLempHDIzFbeHXyXtY8XUTFAddLV6T7MwyD7EWVvDp5L/8+ZScbny/F0WiQdKaVy+ZbuGCnnewrYKM5gj4MppeSbyLSQ+Rtz+PBSx4kd2tuh99r45KNrH57tdvxMy89s8Xr3XXL3LV6F2WFZR7F9uwvnqU4r9ijOdpiwswJmF28trc32fl8/ucALHvJ9fLTwWMHu+0U21YX3nKh27G3HnqLI7lH2j23YRg8+8tn3TbWGPvjsYRGhrZ7fpHuRu/2RU4SW4OTT/65l5duzaGiwCAi0c7Md6O48KXhBHhpXwuR7srPaqbfRRFc9kIqvz0ylNkr+zLqN72J7huI02aw79NqPvllPk+mbec/w3ay7L5DFKzVvnE9ga3eyfo5Jfxr8E7mXbCPfZ9WYzLDwGkRXP9lFNO+bqDqKhsf+1toJI1M+mrJqYj0KIZhsHbBWm4/9XYenv4we9ft7ZD75GzO4fFrH3c7HhQWxJgZY1qcY+h413uWOewOXrnnlXbHNv+B+V7d86w1YlNiOWX8KS7Hls5dyoFtB8hen+1y3NPmC981bOIw+p/V3+VYY10jf77oz1SVVrVr7jm3zWHzZ66bL5gtZmbcM6Nd84p0V1qCKnISHNpVyTv376fsYHMyYMRVBuc/OZDA3kq8ibSV2c9E6tgwUseGcf5jfSjZ3cDuDyvZ81ElB7+s4ciWeo5sqWfVXw4TGu9H34sj6HthBOkTwrBGaKlqd1Fz2MaaZ4pZ/58S6kqaP3kPCDMz4mcxnPnLEELTCzhAI6swUUQEKaQp8SYiPZrT6WT1O6tZ/c5qBowewJQbp3D29LMJDHa971prGYbBytdW8uytz1Jb6X6vtsvuuIzg8OAW5xowegBBYUEumzgsnbuUlMEpXP7by1sdW1NDEy/+7kUWPr2w1dd404TZE1x2B81el81Ld73k8hpriJXR00d7NY6fP/lzfj/q9zidzuPGDu44yJ+m/Im737mb2JTYVs1nt9l56a6XWPDUArfnXHLbJV7tXivSHSgBJ9KBDMNg/YJcFj1WhsNmIjzOzqVPx5I5NVXLTUW8JKa/lZjfWTn7d3HUldjZ+0klez6sJHtRFTWH7Wz8bykb/1uKyQJ9zgoh8/xwMieHk3h6MGaLGjl0JY4mJ/s+rWbra2XsfKcCR1PzhxoRqQGMvC2WET+NJjD8MOXsZzUGm/AjkhQyifZx5CIincuu1bvYtXoX/77535x+0emccfEZDJs4jF5JrV+eX1tZyzcffMPHz3zMnjV7Wjw3eWAy0++afsI5/fz9uPCWC3nn7++4HH/xdy+SvS6ba/92bYtLNO02O1+//zUv3fkSR3K+v8QysW8idVV1VBypOGE8nho9dTTP3vosdVV1x42tW+i6+cLo6aMJCg3yahz9zuzHZXdcxnuPvedyPHtdNr8Y8guu/eu1nHf9eVhDrC7PMwyD7Z9v57lfPUfully390vqn8TVD1ztjdBFuhUl4EQ6iK2xgYX/2M3mBQ7AxIBJBpe9PBBrvKreRDpKcMz/mjjYG50cWFnD7o8q2f9pFaV7Gjn4ZS0Hv6xlxf2FWKMsZEwMI3NyOJnnhxOREuDr8MUFp8Mgd0U1214vZ+c7FTSUO46NJY8O4axf92bAjyIx+9ViYzd7aWQNUEwkKaSq6k1EpAWNdY18+daXfPnWl0DzHmwZp2aQ2C+RmOQYwqLDCAwOxGF3UF9dT21lLQW7C8jdkkvOphyX3TV/KDQqlDvfvpMAa+ueZ6f+fiqL/rPIbTXdqjdW8eVbXzJ47GAGjhlIXHocweHB1FbWUnG4ggNbD7D+k/Uuk14WPwu/fuXXPHrlo62KxVOBwYGcPeNsljy/pNXXeHP56XfN/NtMstdls3XFVpfj9dX1PPer53jprpc44+IzSBuaRlRCFIHBgZQdKqMot4g1H66h6EBRi/cJDg/mnvfu8XoSUaQ7UAJOpAOUHj7Em3fmU7TXD5PF4Lz7whl1XyYmVb2JnDR+gebmarfzmzuqVeQ2su/TavZ9WsX+z6ppKHew4+0KdrxdAUDMgEAyzg8nc1I4KWNCsEbqKdJXDMMg/+tatr1ezo43y6k5/L/NnUPj/Rh8ZRSnXBNN0hkhgAM4SDnFbD5a9RZNKplE+Sx+EZGuquRgCSUHS7w2X2RcJPctuI+UQSmtviYsOozb5t7G36b+DcNwvZer0+lk64qtbpNJrphMJn75/C/pP9L1fmgdZeLsia1OwMWlxzFk3JAOicPiZ+HeD+/lj5P+yJ5v3FcsNtY18sWbX/DFm1+0+R5BYUH8adGfSB6Y7EmoIt2W3l2IeJO5kV2rd/P+HxtprPEjJAamv5ZK2iTXHZ1E5OSJTAvktBsCOe2GGJx2g4K1tez7tJr9n1aR/3UtJbsaKdlVzJp/FoMJ4oYGkTImlJRzQkg9J5SwRFXIdSTDMDiypZ5t88vZ9no5lQeajo1ZoywMmh7JkB9Hkzo29DtLh6tpIodcbKwBSokilVT89PJGROQYs8U3HwAPGTeEX7/861bvK/ZdZ/3oLGY/OpsXf/uiV2Kx+Fm46V83MWHmBK/M1xaDxgwiISuBwuzCE547fuZ4TKaO2x4jOCyYvyz9C0/MeoLV77jvVtsevdN6c+8H95I+NN2r84p0J3qFKuIlTnMRS/+zl9VzgwALKWf5M/2d/nrTLtIJmf1MJI8KJXlUKOfen0BDhZ2cZdXNCbnPqinf18iRzfUc2VzP2meKAYhMDyD1nFCSx4SSek4ovfoHduiL5J6gsdpB3qoacpZXs3dhFSU7G46NBYSaGfCjSAZfFUXmpDAsAd99A+kACiijmE0YbMGfaFLIUNWbiMhxkgcm89y+5/jqva/4+r2v2f3Vbpeb8XtLXHocV91/FRNmTvDoefLy31xOXHoc/7zuny6Xk7Ylnl+98CtOOdd1R9KTYcKsCcy7b16L55hMJibM6vgEoTXEyl1v38WSF5Yw93dzqS6r9mg+k8nEpJ9NYvYjswmNDPVSlCLdkxJwIp4yN1JTs4e376zgwPoQAEbdHs3ER1Kx+OvNuUhXYI30Y+DUKAZObU7gVBfayPuipvnPqhqObK6nIqeJipwyNr9cBjTvN5cyJoQ+o0NJGB5E/PBggnvpabUlTTUO8r6sJXd5NbnLqzm0vg7jf1u6YQk00e+iCAZfFUW/iyLwD3ZVtVFFEwfIoZE1mCknilRSVPUmItKC+Ix4Lv/N5Vz+m8upKKpg46cb2bFqBzu+2EH+zny3Sz1bKygsiBFTRjD+2vGcftHpmL207croqaPpe3pf3n74bZa+uJSmhqYTX3RUTHIMF916ERf/6mICgzzr9OqpCTMnMP/++S0mPgefM7jFxhLeNun6SYyeNpqFTy9k8XOLKc4rbtP1gcGBjJ42mml3TiNlcOuXGIv0ZCbD09+23URVVRURERGULHyZXlGRvg5HuoqAIg5s3cbbvwumpiSAgFATl72QyqAZ6rjnTTabwccfG1x4oQl/JTXFBxqrHBz8qpa8Vc1JuYJvarE3HP/0GZ7sT/ypwcQPDyJheDDxpwYRkRrQ7Svl3P2M2uqc5H1ZQ+6KanKX13BobS1O+/evjcoMJO3cUNInhNH3ogisERY3d3EA+ZRSwmZgM37EkEokkR30qES6B8NmYHxsYLrQhEnPoeJCdVk12euyKdhTQOHeQgr2FFCaX0pdVR311fXUV9djGAZ+AX4EhQYRHhtOVHwUCVkJpAxOod/IfmSOyMTPv2M/CKksrmTDog1sWb6F/Rv3U1VcRXVpNU6Hk8CQQCJiI0jqn0T6qemcOulUBp49EIvF3XNK59EZfkYNw2D317vZsnwLe9fspTC7kLJDZTTUNjR/fYMDCesVRlx6HOnD0hl0ziCGnz9cjRak26streXHMT+msrKS8PBwj+dTAu4oJeCkTcyNGNbdfP3KQZY8EY/hMBE7KJAr3s0kpr/rtt3SfkrASWdjb3RSuKGOvFU1FKyp4/Cmesr3Nbo81xppIf7U5gq5+FODiB0cRFRGAEFR3adiq6nJyYfzbAxNbKR8TwMlOxs4srmegrV1OG3ff5kRkRpA+vhQ0saHkXZuWCu7z1bRRC77aWINJiqJpg/JqnoTaYXO8OZeRNzTz6hI5+XtBJxeuYq0iQGBRTTZNvHBby3s+CwBgFOuieLiZ1MICOn8n7KJiOf8As3H9pD7VkOlgyNb6jm8sa75z6Z6irY30FDhIHdFDbkrar43hzXSQlRGAFGZgURlfPun+e8RyQGY/Trfi3DDMKg6aKN4R/3/t3fn4VHW997H3zOTPZBAIAsJZGGpVVQQt6PWHfW0LkV9tK1al26nLe1ppee02qcu7WmPtX3aejxu3e1Ga6viQtXWasWllbALKIuSECCQhCUJZM/M/fyRgKCgIAl3lvfrurhCJjP3fAdzB+bj5/e7qXutlbpXW9n8atfH1vo4y/fymKzRyV1h25lDKTtzCMNKD2QZUJyAKraylcUELCWFkZRQSnZPvSRJkiTpkDCAk/ZXtBXSVrFj81J+/6USqpdnEE2Gf/2fMRz32ZEDfomZpHeWlh2j5NSuCzTsFG9PUPdqKxsXtbBpcTObFrWwdXUrOzZ10lofZ+PCFjYubHnbsSIxGFaSwrCyVIbkJ5GWk0R6Toz0vX0cHiNteNJ73nMy0RnQvKWT5rpOmjd30tT9sXnzm7c113Xdvu2NNtp37GP/mijkjE0ld2IauUekMfLwNMacPIThY9/rEtxG2qhgDR27Wm+llBDD/9EhSZKk/scATnpXAaTWQPJi6lZv4ndfnEhDdYyMkUl89NGxjDnZq/1I2rtYSrRrT7jJGcCIXbe3N8Wpr2hn25o2tq3p/vhGW9fHinbibUH37fu/2XTK0GjX/mk7s67dVn7usdnEbr/vaEnQum23qyDsh2gSjHjfmyFb7hFpDJ+QRvmaFC6YFuuBZeJdrbctbGURActIIY9Syjj42r8kSZIUFgM46Z10t95gIZXlQ3hgxtG0NkLO+FSufHIcOePd703SgUvJjJF3ZDp5R7598+IgEbB9Y0dXIFfRTsuWTlq2xmnZ2vWxddtbPq/vCtDatydo377vq6u9owik58TIzE0iY2QSGTs/vuX3w0pTyBmf9ra2XUdHQHR9T2wp20Aba3mDNuYSYQcjKKPY1pskSZL6PQM4aa92tt4WQXwtS/96OI98YyiJDhhzciYffXQcGSM9fST1vEg0QlZRCllFKZSc9u73T8QDWuu7Arm2xj0DuD1WfkbefnssNUJmbjJpw2NEY2Euo+8kYB2b2cpiYCkp5FNGqa03SZIkDRAmCNJbRVsgfSUESwjiUV6ceRLPfr+rYXLE/xnGtF+XkpweDXlISeoSjUXIGJFExoj++ld6PW2s5XU6KQeaGMlYRtt6kyRJ0oDSX/+1LvWCAFI3QdIiSFSRiI7jzz8qZuGvmgA46T/yOOf2IiJRL7YgSQevk4AqNrONhQS8Sip5lDDS1pskSZIGIAM4CSDaDOmrIFgEJNGWfAoPfiWV1/+yg0gU/vXOMZwwPTfsKSVpgNhGG+t4nQ7mAi3kUUaRrTdJkiQNWAZwGuQCSNvY3XpbBynj2M5RzLxiG5sW7yApPcL/+UMZh100LOxBJWkA6CRgLXXUs4CAV0lhFGXkMjTswSRJkqReZQCnwSvaDBkrIbEYgmQYfhq1W0bzuw+vpXFdB5l5SXxs9jiKjs8Me1JJGgC20UoVr9PJXKCVPMbZepMkSdIgYQCnQSgBaZsgthAS6yF5AhRNYs38FP54yRraGhOMfH8qVzwxnuFlqWEPK0n9XAcJ1lJHAwsJeI1URlFGHkPCHkySJEk6ZAzgNLjEmiHtNQiWQJAKOadBwXhWPNHMg5e/Qbw9oOS0IXxk1ljSczw9JOngbKWVdazqvsJpO/mMo4goXklakiRJg4sJgwaJRPdebwshsQFS3gdFkyBrBMv/tI2Hr6gg0QlH/J9hXPzbUpJSfXMoSe9dBwkqqaWRRcBr3Xu95dt6kyRJ0iBlAKeBL9bU3Xp7pbv1djoUjIfkZF757RYeuWYtQQKOunI40+4vJZoUCXtiSerHttDKOlbSSTkROslnHIW23iRJkjSoGcBpAEtAWjUkLYDERkh9HxR2td4AFv1iM499qgoCmPyJEVz4k2KiMcM3SXqvErzBJhqYT4LVZDCKUjLxQjaSJEmSAZwGpl2ttyUQpMOIMyB/HCQnAzDvnjqemL4OgOM+N5IP3TWGSNTwTZLem63AcJbTyHwgzijG2nqTJEmSdjGA0wCze+ttU3fr7ehdrTeAf/6ohr/O2ADAv1yfx7k/KCISMXyTpAPXToK11LADGM5zpFFEKRlkhD2YJEmS1KcYwGngiO3Yba+3TBh5JuSXQVLyrru8cNsmnv16NQAfuDGfs75TaPgmSe/JZppZx0oSzCdGHjCO99t6kyRJkvbCAE4DQALSN0B0AQSbIPVwKDwKsnJ23SMIAp67dSPPf2sTAGd8cxSn3VRg+CZJB6ydBJVsYjsLgFWkMpqxAETwZ6okSZK0NwZw6t9iOyBtOQRLgSEw8mzIL92j9RYEAX+7oZp/fK8GgLO/W8gHvlYQzryS1K/V0cx6VhBnHlGggPEUECFCQBD2cJIkSVKfZQCnfire1XqLLYB4HaQf1rXX29Dhe9wrCAKe+vJ6yu+sA+C8O0bzL1/KC2NgSerH2ohTQQ1NzCPgDTL22OvN8E2SJEl6ZwZw6n+StkNqd+styIK8s7pab7E9v52DRMCfP7+OBT/eDMD5947huM/mhjCwJPVnXa2317pbbxFGMZ5RLjeVJEmSDoABnPqR7tZbdD4k6iD9CCg6CoYMe9s9gyDg8X+rYtHPtkAELvp5CcdcN+Lth5Qk7UNX621Td+ttDRmMpox00sMeTJIkSep3DODUPyQ1du/1tgzIhrypkF/yttYbdIVvf/3KBhb9bAuRKEz7dSlHX5nz9mNKkvahliY28BpxyomQRNGuvd4kSZIkHTgDOPVxcUhf39162wJpR0DRkXttve0051ubePlHtUBX883wTZL2V1frbSNNzAdbb5IkSVIPMYBT35XUCGnLILEcGAa5Z++z9bbTy3fUMufWjQD86/+MZvK1LjuVpHcXALXsYAOvkWA+MZIYxXjybb1JkiRJPcAATn1QHNKrILoA4lshfWJ36y37HR+16Beb+cv16wE441ujOPHfvdqpJL271u7WWzPlQAUZFDOWNNLCHkySJEkaMAzg1LckNULaUkgsg8gIKJgKuSUQi73jw5b/aRuPf7oKgJO+ksdp3yg4FNNKUj8WADXsYCPL6WQBSSQzigm23iRJkqQeZwCnPmJn620+JLZB+lFdrbfMrHd95OtPNfDwlZUECTjmUyM45/tFRCK+eZSkfetqvVV3t94qyaSEcaSSGvZgkiRJ0oBkAKfwJTV0td7ir0IkB/LOgdzid229Aax9YQcPXLKGREfAxI8M54L7ig3fJGmfulpv29nIq8SZT5RUiphAnq03SZIkqRcZwCk8kU5IWwuRBZBohMyjoGgiZLx76w2gekEzM89/nc6WgAkfyuLiX5cQjfkGUpL2roVOKthAC/OAKoZQTJmtN0mSJOkQMIBTOJLqIXUpJF6FSC7knwsji/ar9QZQ92oLvz1vNe3bE5ScPoTLHhxLLCXauzNLUr8UAJvYTjXLCZhPlHRGMwEvVCNJkiQdKgZwOrQinZBWCdGF3a23Sd2tt6H7fYhtFW385pzXadkSp/D4DD722DiS0w3fJOntdrbemiknwnqGMoZSW2+SJEnSIWYAp0MneRukLoP4a8BIGHVgrTeA7dXt/GbqarZXd5A7MY0rnxxPatb+P16SBocA2Egjm1hOggXEyGA048kNezBJkiRpUDKAU++LdEJ6JTAfEjtgyCQoPOKAWm8AzVs6+c05r7NtTTvDx6bw8acnkDHCb2FJ2lMznVSynhbmElDNUIopI4WUsAeTJEmSBi3TC/Wu5G2Q+gokVkA0H/JPhhEH1noD6GxN8IcPv0Hdq60MLUrm43+bwNBRyb00tCT1R2+23pYSZyFJZNp6kyRJkvoEAzj1jkgHpFV07/XWBJmToXAiZAw54EMFiYBHrl3LupeaSM2OcdVfxjO8zP2LJOlNzXSyhnW0UQ5sIIsSW2+SJElSn2EAp56XvLW79bYSogWQ/wEYUQjR93ahhGf+bzXLH9hGNDnCRx4eS97E9B4eWJL6qwSwkQZqWEbAQmIMYTQTGBn2YJIkSZJ2YwCnnrOz9RbZ2XqbAkWHQ/qBt952WvCTzbz03RoALvpZMWVnHdi+cZI0cHW13qq6W28bGUoxpbbeJEmSpD7IAE49I3kLpC6FeHfrreDgWm8Aq59s4M+frwLg9FtHMenqET01rST1YwmgmgZqeIWARSSRxRjG489ISZIkqa8ygNPBiXRA+hvAQoi3wtBju1pvaZkHddhNi5t58PIKgjhMujqH028u6Jl5Jalfa6KDCqpopZwINWRTTCnJeFEaSZIkqS8zgNN7l7IFUl6BxCqIjoKC0w669QbQuL6dmee/QfuOBGVnDeXCnxYTiUR6aGhJ6o+6Wm/1u7XeshnDOFtvkiRJUr9gAKcDF2l/s/WWaIMhx0LREZCWcdCHbmuMM/P8N9he3UHuEWlc/lAZsZSDC/QkqX/bQQeVrO3e663W1pskSZLU7xjA6cCkbIaUJRBfDUmjYdQUGF5w0K03gHhHwJ8ur6DmlRaGFCRxxRPjSBvmt6ikwSoBbGAbtbwCLCbGMIoZR07Yg0mSJEk6QKYb2j+7t96Cdhh6fPdebwffegMIgoA/f76KN/7SSHJGlI89Po5hJak9cmxJ6n+6Wm+VtDGPCLXdVzi19SZJkiT1TwZwencpdd2tt9cheTQUTIGcUdCD+7K9+N0aFv1sC5EoXPqHUgqPO7iLOEhS/xSnq/VWxxK6Wm85lDCO4WEPJkmSJOkgGMBp36JtkPY6XXu9dULWiVD0fkhN79GnWfr7rTz79WoA/vXOMRx24bAePb4k9Q/bu1tv7cwFtjCMEkpI8q9qSZIkqd/zX/Xau5Q6SFkM8TcgeQwUHNPjrTeAtS/s4NFr1wLwLzPyOGF6bo8eX5L6vq7W0qpEjQAAM5lJREFU21bqWEzAKySTQzFjbb1JkiRJA4YBnPYUbYO01cAiSMQh+1+g8LAeb70BbH2jjQemvUG8PeDwS4Zx7veLevw5JKlv2047lVTQRjkRtpFDCcW23iRJkqQBxn/h600ptV2tt8QaSCqBUcfA8Pweb70BtG2P84cPv0HL1jhFJ2Rw8W9KiUR7/nkkqW+KA+vZwmaWAEtIZiQllDEs5LkkSZIk9QYDOHW13tJXQbAIggRkndTdekvrlacLEgGPXFNJ3fJWhoxK5iOzxpKcEe2V55KkvqeRdipZQwfziFDPcEoZY+tNkiRJGsAGROpx2223cfzxxzN06FDy8vKYNm0aK1euDHusfiCA1BrIeA6ClyCWC6P/FUqP7rXwDeD5b29ixawGYikRPjJrLEMLU3rtuSSp74gTUMEWVvMC7TxFMhHGUUqZ4ZskSZI0wA2IAG7OnDlMnz6dl19+maeffpqOjg7OPfdcmpqawh6t74q2QsZSiD0Fwcau1tuEMyGnoFeWnO604tF6nrtlIwDn31fM6BMze+25JKnvaKSd5axgC7OB5eRQykSyyQ57MEmSJEmHwID4X+5PPfXUHp/ff//95OXlsWDBAk477bSQpuqrultvyUsgUdG919sUGJ7Xq8EbQN2rLcy6qhKAE76YyzHXjejV55Ok8MUJqGILW1lEwDJSyKOUMrLCHkySJEnSITQgAri3amhoACAnJ2ef92lra6OtrW3X542NjQB0BNCRCHp3wLBE2yDtdWAJdEYh6wNQMAFSUqAToPded8u2Tn7/4TW070hQcsYQzvxuER0dA/TPWT1u5/eK3zPqXxppZx1r6GA+EZoYQRljiBIl6MWft2EIus/NwHNU6nM8P6W+zXNU6rt6+ryMBEEwoM70RCLBRRddRH19PS+++OI+73frrbfyzW9+8223z5w5k4yMjN4ccdAJ4gFrvrOG7Qu3k5ybzGE/OIykrAGZ/UqSJEmSpAGgubmZK664goaGBrKyDn4Fy4BLQaZPn86yZcveMXwDuPHGG5kxY8auzxsbGxkzZgxnZnUyYljvLsU8pKKtkL4agmVABLInQf64rtbbIfLsjdVsX7idpPQIV/95LPmTkw/Zc2tg6OgIePppOOccSE4eQOenBqCG7tZbJ/OBZkZQRBHRgbHl6j4FHQE8DZwDEc9RqU/x/JT6Ns9RqQ/b0rOHG1AB3Be+8AVmz57N888/z+jRo9/xvqmpqaSmpr7t9uQIJEcHwg++AFI3QdIiSKyF1PEwalLXXm+H0NLfb+XlH9QC8OFfljD6eC+6oPcqIDk5YgCnPqqTgCo2s41FwHJSyKeUkQwNe7BDJiAgkhzxzYPUB3l+Sn2b56jUN/X0OTkgArggCPjiF7/IrFmzeO655ygrKwt7pHBFWyB9JQSLgCQYfioUToDktweOvWnjomYe++RaAE65IZ8jP7LvPfkkqf/aRhvreJ0O5gIt5FJGETFiYQ8mSZIkqY8YEAHc9OnTmTlzJo8++ihDhw5l06ZNAGRnZ5Oenh7ydIdSAGkbu1tv6yBlHIyaDMNyD/kkTbUdPDBtDZ0tAeM/mMVZ3y485DNIUu/qJGAtddSzgIBXSWEUZeQOotabJEmSpP0zIAK4e++9F4Azzjhjj9t/+ctfcu211x76gcIQbYaMlZBYDEEyDD8NRo2H5EO319tO8Y6AP11WQUNVOyPel8qlM0uJxqxTSxpIttFKFa/TSTkRWshlnK03SZIkSfswIAK4AXYh1wOUgLRNEFsIifWQPAEKjw6l9bbTX65fz9rnd5AyNMpHHhlL2rAB8W0mSUAHAVXUUs9CAl4jtbv1NiTswSRJkiT1YSYj/VmsGdJeg2AJBKmQcxoUhNN622nhzzcz7+46AC75XSm5hw+mJcCSBrattFLFauLMBdrJZ9wguMKpJEmSpINnANcvJbr2eosthGADpLyvq/WWPTLUqaoXNPPE59cBcMa3RnHYhcNCnUeSekYHCSqppZFF0N16KyXf1pskSZKk/WQA19/EmiHtVQheAVIh53QoGBdq6w2gtb6TP122hnh7wGEXZXPa/y0IdR5J6hlbaGUdK4lTDnSSzzgKbb1JkiRJOiAGcP1GAtKqIWkBJDZC6vugcBJkjQh7MIIg4NHr1lJf0c6wshQ+fH8JkagXXZDUn73ZeltAwCrSGUUpmWSGPZgkSZKkfsgArj+INe2211s6jDgD8sdBcnLYkwHwzx/WsuKRBmIpES7701jSh/ttJak/20IL61jVvddbnALG2nqTJEmSdBBMSvq03Vpv8Y2QdljXXm99oPW2U9VLO/jb1zYAcN4doyk8NiPkiSTpvepqvdXQyHxgFamMZiwZ+HNNkiRJ0sExgOurYju6W2+vQJAJuWdC/lhI6hutN4Cmug4e/EgFQRyO/OhwjvtsuBeBkKT3bjPNrGMlCeYRIUE+4xll602SJElSjzCA63MSkL4Bogsh2Aiph0PhUZCVE/ZgewgSAbOuqmT7hg5GHJbKBT8pJhJx3zdJ/U07CSrZxHYWYOtNkiRJUu8wgOtLYjsgbTkES4EhMPIsyC/rU623nZ7/zibe+Ot2ktIjXP7gWFKHxsIeSZIOUB3NrGcFceYRBQoYT4GtN0mSJEk9zgCuT4h3td5iCyBe17XXW9HRMHR42IPt1ZpnGnnulo0AnH9vMXlHpoc8kSQdiHbirKGGJuYR8AYZFFFq602SJElSrzGAC1vSdkjtbr0FWZB3FuSXQqxv/qfZXt3Ow1dUQgCTPzGCydf0nQtCSNK762q9vdbdeoswivGMIoJL6CVJkiT1nr6Z8gwK3a236HxI1EH6EVB0FAwZFvZg+5ToDHjoY5U01XaSf3Q6H7prTNgjSdJ+aiNOBZu6W29ryGA0ZaRjg1eSJElS7zOAC0NSY/deb8sgkg15Z/fp1ttOz95Uzdrnd5AyNMplfyojOd19kiT1B7U0s4FXu1tvMQoZT4GtN0mSJEmHTN9OfAacOKSv7269bYG0I6DoyD7dettp1ewGXvpuDQAX/byEEe9LC3kiSXo3Xa23jTQxH2y9SZIkSQqNAdyhktQIacsgsRzIhtyzIb+kz7feAOor25h1dSUAJ3wxl4mX9c2LQ0hSlwCopYlqXiXOfGIkMYrx5Nt6kyRJkhSKvp/+9HtxSK+CyAJIbIW0id2tt+ywB9sv8fYEf7q8gtZtcQqPz+Cc7xeFPZIkvYM24qxhI82UAxVkUMxY0rC1K0mSJCk8BnC9KakR0pZCYhlERkDeVMgtgVgs7Mn229Nf3UD1vGbShse47I9lJKW675ukvigAatjBxu7WW5RkCplg602SJElSH2AA1yu6W2/R+ZDYBulHdbXeMrPCHuyArPpzA3P/pw6Aab8qYVhpasgTSdLetBKnkmqaKAcqbb1JkiRJ6mMM4HpaUkNX6y3+KkRyIO8cyC3uV603gO0bO3j0urUAnPDvuRx24bBwB5Kkt+lqvW3frfWWShETyLP1JkmSJKlPMYDrKZFOSFvbvddbA2QeBUUTIaN/td4AgkTAo9dW0lzXSf7R6Zxzu/u+SeprWulkDdW0UA5UkUkxY0nFpq4kSZKkvscArick1UPqUki8CtGRkHsu5I7ud623nf75o1re+Ot2ktIjXPr7UpLS3PdNUl8RAJvYTjXLCZhPlHRGM4G8sAeTJEmSpH0ygDsYkU5Iq4ToQggaIXNSd+ttaNiTvWcbFzbzzI3VAJz3o9HkHpEe8kSStFMLnVSwgWbmEWUdQxhDqa03SZIkSX2eAdx7lbwNUpd17fVGLhScCyOL+m3rDaC9Kc5DH6sg0RHw/mnZHPuZkWGPJEl0td420sgmlpNgATEyGM14csMeTJIkSZL2iwHcgYp0QnolMB8S2yFzMhQd0a9bbzs99aX1bFnVxtCiZC78WQmRiJuYSwpbM51Usp4W5hJQzVBbb5IkSZL6HQO4A5G8DVJfgcQKiOZD/skwon+33nZa/qdtLPr5FojAxb8pJWOE3xqSwvRm620ZCRaSRAZFtt4kSZIk9UumLPsj0tHVeossgMSOrtZb4UTIGBL2ZD2ioaqd2Z+pAuADN+ZTdmb/b/NJ6s+a6WQN62ijHNjAUEooI4WUsAeTJEmSpPfEAO7dJG/tar3FV0CsAPJP6Wq9RQfGlUET8YCHr6ygtT5O0YkZnHFrYdgjSRq0EsBGGqhhGQELiTGE0UzA/SglSZIk9W8GcPsS6YC0iu7WWzMMORaKDof0gdF62+mF72yi6sUmUoZGuXRmGbFk932TFIau1lsVbcwjQjVDKabU1pskSZKkAcEAbm+St0DqUoiv7G69nQojCgdM622nqpd2MOebGwE4/54xDB/rpuaSDrUEUE0DNSwlwQKSyKaY8YwIezBJkiRJ6jEGcG+VsQaSV0CiBYZMgdFHQFpm2FP1uNb6Th6+spIgAUdflcPRV/lmV9Kh1kQHFVTRSjkRahhGMaUkkxz2YJIkSZLUowzg3ioyF6JFUHDagGy9AQRBwOzPrqNhbTvDx6bwobvHhD2SpEGlq/VWTw2vELCIGNkUM87WmyRJkqQBygDurYZOggmTIS0j7El6zZJfbWX5A9uIxOCSmWWkZsXCHknSoLGDDipZ2916qyXb1pskSZKkAc8A7q3GHD2gw7ctq1t54gvrADjzW4WMPnHgLa+V1BclgA1so5ZXCFhCMtmMYRw5YQ8mSZIkSb3OAO6togP3KqCJzoBHrl5LR1OC0jOGcMrX8sMeSdKgsIMOKqiknXlEqCXL1pskSZKkQcUAbhB56Xs1rH+5idTsGNN+XUo0NnDDRkl9QZyu1lsdS4DFxMihhHEMD3swSZIkSTqkDOAGiY2LmnnulmoAPvi/o8kekxLyRJIGtu10UEkl7cwFtjCMEkpI8q8dSZIkSYOQ74QGgc7WBLM+XkmiEw6/ZBhHX+WeS5J6S1frbSt1LCbgFZLIoYSxtt4kSZIkDWIGcIPAszdVU7e8lcz8JM6/bwyRiEtPJfWG7bRTQSUdzAW2kUMJxbbeJEmSJA16visa4NY+v51//qAWgAt/WkxmrpueS+ppcWA9W9nMYmAJMUZSShnDwh1LkiRJkvoIA7gBrK0xziPXrIUAjvnkCA67cFjYI0kacBppp5I1dDCPCPUMp5Qxtt4kSZIkaTe+QxrA/jJjPfWV7QwrTeG8H44OexxJA0qcgCq2spXFBCwlhZGUUEp22INJkiRJUp9jADdArXy8nkU/3wIRmParElKzYmGPJGnAeLP1NhdoIIdSSojhzxlJkiRJ2hsDuAGoqa6Dxz9VBcBJX8mj5LShIU8kaWB4s/W2kATLSCGXUspsvUmSJEnSOzKAG2CCIGD2v1XRVNtJ7sQ0zvqvwrBHkjQgNNBGJW/QQTkRtjOSMoptvUmSJEnSfjCAG2Be+e1WVsxqIJoEF/+mlKS0aNgjSerX4gSsZTPbWAwsI4U8SiklK+zBJEmSJKnfMIAbQBrWtfPkF9YBcPqtoxh1TEbIE0nq3xpoYy2v00E50MRIyhht602SJEmSDpAB3AARJAIevXYtbY0JRv9LJh/4WkHYI0nqtzoJWMdmtrIIWE4KeZQw0tabJEmSJL0nBnADRPlddVQ8u53kjCjTfl1CNCkS9kiS+qVttFHF63Qwlwgt5FJGka03SZIkSToIBnADwOYVrfztaxsAOOf7RYyYkBbyRJL6n04CqtjMNhYAr5JCAWXk4lWUJUmSJOlgGcD1c/GOgFlXV9LZGjDu3KEc97mRYY8kqd/ZRitVvE4n5URoYSRjbb1JkiRJUo8xgOvn/vH9GqrnNZM2LMZFvyghEnHpqaT91UFAFbXUs5CA10hlFGXkMiTswSRJkiRpQDGA68dql7cw55sbAfjXO0eTVZQS8kSS+o83W28vA+3kM44iokTDHkySJEmSBhwDuH4q0Rnw6HVribcHvO+CLI6+KifskST1Cx0kWEsdDSwEXiOFUZSRb+tNkiRJknqNAVw/9Y8fdC09Tc2Ocf59xS49lbQfttJKFavoZC4ROslnHIW23iRJkiSplxnA9UN1r7Xw3C3dS0/vcOmppHfT1XqrpYEFBKwkjULKyCQz7MEkSZIkaVAwgOtnEvHupadtAeM/mMWka1x6KumdbKGFKlaRoNzWmyRJkiSFwgCun3n5R7VsmNtMalaUC37s0lNJ+9JBgkpqaGQ+AatIo8jWmyRJkiSFwgCuH9m8spW/31QNwLk/HE32GJeeStqbLTRTxUrizCNKggLGM8rWmyRJkiSFxACun0jEAx77xFo6WwPGnTuUYz4xIuyRJPU57SRY2916g9WkU0QZGWSEPZgkSZIkDWoGcP1E+f/Wse4fTaQMjXLhT0tceirpLTbTzDpWdu/1BgWMo8DWmyRJkiT1AQZw/cCW1a088/UNAJzz/SKyi116KmmndhJUsIkdzAdeJ50iSm29SZIkSVIfYgDXxwWJgMc+WUVnS0DZWUM59jMjwx5JUp9RRxMbWEmcciJEuvd6i2BDVpIkSZL6EgO4Pq787jqqXthBcmaUi37uVU8lAbQRp4JNNDGPgDVk2HqTJEmSpD7MAK4P2/pGG8/c0HXV03O+V8Sw0tSQJ5IUvjqaWc9r3Xu9xShkPAW23iRJkiSpDzOA66O6lp6upaM5QekZQzjusy49lQa33VtvsIZ0RlNGOulhDyZJkiRJehcGcH3U/Ps2s3bODpIzolz08xIiUdst0uAUALU0Uc2rxJlPjCRGMZ58W2+SJEmS1E8YwPVB2yraePqrXVc9Pfu7hQwf69JTaXDqar1tpIlyoIIMihlLGmlhDyZJkiRJOgAGcH1MEAQ8/ukqOpoSFJ86hBOm54Y9kqRDLgBq2EE1r5JgPlGSKWSCrTdJkiRJ6pcM4PqYxb/cQsUz20lKi/DhXxS79FQadFqJU0l1d+ttLZmMoczWmyRJkiT1YwZwfciOTR389StdS0/P+FYhOeN9wy0NHl2tt+27td5SKWI8ebbeJEmSJKmfM4DrQ5784jpa6+OMmpLOSdfnhT2OpEOmlU7WUE0L84iwlkyKGUsq7v8oSZIkSQOBAVwfseKRel59sJ5IDC76eQnRJBsv0sAXAJvYTjXLCZhPlHRGMwEDeEmSJEkaSAzg+oDWhjhPTF8HwMn/mU/B5IyQJ5LU+1ropIINNDOPKOsYwhhKbb1JkiRJ0gBkANcH/O1rG9he3UHOhFROv3lU2ONI6lUBsJFGNvEqAfOJkcFoxuMVjyVJkiRpoDKAC9na57ez4MebAbjwp8Ukp0dDnkhS72mmk0rW00I5sMHWmyRJkiQNCgZwIepsTfD4p6sAmPLpEZSePjTkiST1jjdbb8sJWECMDIpsvUmSJEnSIGEAF6I5/7WRLavaGDIqmXO+VxT2OJJ6RTOdrGEdbbtabyWUkUJK2INJkiRJkg4RA7iQbFrSzD++VwPAh+4eQ9ow/1NIA0sC2EgDNSwjYCExhjCaCYwMezBJkiRJ0iFm6hOCRGfA45+qItEJh18yjMMvHhb2SJJ6VDOdVFBFK/OIUM1Qiim19SZJkiRJg5QBXAjm3llL9fxmUrNjfPCuMWGPI6nHJIBqGqhhKQkWkEQ2xYxnRNiDSZIkSZJCZAB3iG1b08az36gG4Nz/V8TQUckhTySpZzTR0d16KydCDcMoppRkPMclSZIkabAzgDuEgiBg9r9V0dkSUHrmEI75pK0Yqf/rar3VU8MrBCwiRjbFjLP1JkmSJEnqZgB3CC359VbW/G07SWkRLvxJMZFIJOyRJB2UHXRQydru1lsdwxhDia03SZIkSdIeDOAOkR01Hfzl+vUAnPHNUeSMTwt5IknvXQLYQD11LCHBYpIYRjFjyQl7MEmSJElSH2QAd4g89aX1tG6LU3BMOifNyA97HEnv2Q46qKCSduYRoZZs93qTJEmSJL0jA7hDYOXj9Sx/YBuRGFz0sxKiSS49lfqfOLCBbdTxCgGLSWI4JYxjeNiDSZIkSZL6OAO4Xta2Pc4Tn18HwEkz8hg1JSPkiSQduO10sJZK2pgLbGYYxe71JkmSJEnaTwZwvezvN2+kcX0Hw8pSOOPWwrDHkXRAulpvW3drveXYepMkSZIkHSADuF5UvaCZ8jtrATj/3mKSM6IhTyRp/22nnQoqaKecCFsZTgklJPljU5IkSZJ0gHwn2UsSnQGzP7OWIAFHfmw448/LCnskSfslDqxnK5tZTMASkhhBCWNtvUmSJEmS3iMDuF5SflcdGxe2kDYsxnk/Gh32OJL2SyPtVHa33qLUk0MpY2y9SZIkSZIOiu8qe0HDunae/UY1AFO/V8SQfDdql/q2OAFVbGUriwl4hWRGUkIpw8IeTJIkSZI0ABjA9YInv7iOjqYEY07JZMonR4Q9jqR31NV6W0MHc4EGciil2NabJEmSJKnH+A6zh702q56VjzYQTY5wwY+LiUQjYY8kaa+6Wm9b2MoiEiwjhVxKKSM77MEkSZIkSQOMAVwPamuM8+QX1wFwylfzyZuYHvJEkvaugTYqeYMOyomwnZGUUUyMWNiDSZIkSZIGIAO4HvTsN6rZvqGD4eNSOfX/FoQ9jqS36SSgis1sYzGwjBTyKKUUr1IsSZIkSeo9BnA9ZMO8JsrvqgPggvvGkJweDXkiSXuqp421vE4n5UATIyhjjK03SZIkSVKvM4DrAYnOgNmfqYIAjr4qh7FTbdNIfcebrbdFwHJSyKOEkbbeJEmSJEmHiAFcD3j5f2rZtLiF9JwY5/6gKOxxJO2yjTaqeJ0O5hKhhVzKKLL1JkmSJEk6pAzgDlL92jaeu3kjAOd8v4jMvOSQJ5LU1XpbSx31LCTgVVIooIxchoY9mCRJkiRpEDKAOwhBEPDE9HV0NCcoOW0Ik68bEfZIkthGK2t5nThzgVbyGGvrTZIkSZIUIgO4g/DaQ/Ws/nMj0eQI5983hkgkEvZI0iDWQUAVtd2tt9dIZRRl5DEk7MEkSZIkSYOcAdx71NoQ58l/Xw/AB27MJ/fw9JAnkgazrbRSxWrilBOhjTzGUmjrTZIkSZLUJxjAvUfPfH0DOzZ2kDMhlVNvLAh7HGmQ6iBBJbU0sgh4jRRbb5IkSZKkPscA7j1YP7eJ+fduBuCC+4pJSouGPJE0GG2hlXWsopO5ROgkn3EUEsXzUZIkSZLUtxjAHaBEZ8Dsf6uCACZdnUPZWV5VUTq03my9LSBgJWkUUkYmmWEPJkmSJEnSXhnAHaDyu+qoWdJC2vAY5/y/orDHkQaZrbRQxSoSlNt6kyRJkiT1EwZwB6BxfTt/v6kagKm3F5GZmxzyRNJg0QnEqKGKRcRZbetNkiRJktSPGMAdgL9cv572HQlGn5TJlE+OCHscaZDYQgvrgaN4kghxRjGOUbbeJEmSJEn9hgHcflr9ZAOvPlhPJAYX3DeGSDQS9kjSANdOgrXU0Mi87rAti/eRQUbIc0mSJEmSdGAM4PZDR0uCJ6avA+BfvpxH/tEGAFLv2kwz61jZvddbhALygXTSwx5MkiRJkqQDZgC3H174zibqK9rJGp3MGbeOCnscaQBrJ0Elm9jOfOB10iiijHTSCQjCHk6SJEmSpPfEAO5dbF7RykvfqwHgX+8cQ8qQWMgTSQNVHU1sYCXxXa238YwiQsTwTZIkSZLUrxnAvYMgCPjz56pIdAS874Is3j8tO+yRpAGojTgV1NBEOQFryKCIUvd6kyRJkiQNGAZw72Dp77ZS+dwOktIjfPB/xxCJeOEFqWfV0cx6XiNOOVFiFDKeAiJ4rkmSJEmSBg4DuH1o2dbJX2ZsAOD0m0cxrDQ15ImkgaSr9baJJuYBa8hgdPdeb5IkSZIkDTQGcPvwzI3VNNd1kntEGifNyAt7HGkAqaWJDbtab8kUMp58W2+SJEmSpAHLAG4v1r/cxIKfbAbg/HvHEEuJhjyRNBB0td420kQ5UEEGxYwljbSwB5MkSZIkqVcZwL1FojNg9mfXQQCTrsmh5LShYY8k9XMBUMsONvAqCeZ3t94m2HqTJEmSJA0SBnBvsehnm6lZ0kLa8BjnfL8o7HGkfq6VOJVspIm5wFoyGUOZrTdJkiRJ0qBiAPcWL922iSgpTL29iMzc5LDHkfqpAKhhO9W7Wm+pFDGePFtvkiRJkqRBxwDuLdqbEow/KZMpnxwR9ihSP9VKnAo20Mw8Iqwlk2LGkopXEpYkSZIkDU4GcG8RicIF940hErWlIx2Y3VtvAfOJkkYRE/AqwpIkSZKkwc0A7i2O/Wwu+UdnhD2G1M+00EkFG2hhHhHWMYQxlNp6kyRJkiQJA7i3Ofmr+WGPIPUjAbCJ7WxkeXfrLYPRjCc37MEkSZIkSeozDODeImVILOwRpH6imU4q2UALc4ENtt4kSZIkSdorAzhJBygANtLIJpYTsIAYGRTZepMkSZIkaR8M4CQdgGY6qWAdrZTT1XoroYwUUsIeTJIkSZKkPssATtJ+SACbaKCGZSRYSIwhjGYCI8MeTJIkSZKkPs8ATtK72L31FqGaoRRTautNkiRJkqT9ZAAnaR8SwEYaqGEpcRaSRBbFjGdE2INJkiRJktSvGMBJ2osmOqhgHW3MBWoYRjGlJJMc9mCSJEmSJPU7BnCSdpMAqmmgliUkWESMbIoZZ+tNkiRJkqT3zABOUreu1ltVd+utjmGMocTWmyRJkiRJB8kAThr0ulpv9d2tt8UkMYxixpIT9mCSJEmSJA0IBnDSoLaDDipZSxvlRKgl273eJEmSJEnqYQZw0qCUADawjTpeIcEiksihhHEMD3swSZIkSZIGHAM4adDpar1V0kY5sJnhFFNs602SJEmSpF5iACcNGnF2tt6WELC4u/U21tabJEmSJEm9ygBOGhS2004FlXQwF9hGDiUUk+SPAEmSJEmSep3vvqUBrav1tpU6FhPwCsmMoIQyhoU9mCRJkiRJg4YBnDRgNdLOWipoo5wo9eRQwhhbb5IkSZIkHWK+E5cGnDiwni1sZgmwhGRyKaWU7LAHkyRJkiRpUIqGPUBPuvvuuyktLSUtLY0TTzyR8vLysEeSDrFG2lnOCjYzG1jGcMo4kmzDN0mSJEmSQjNgArgHHniAGTNmcMstt7Bw4UImTZrEeeedR21tbdijSYdAnIAKtrCa52nnSZKIMZ4yxhIjFvZwkiRJkiQNagMmgPvhD3/Ipz/9aa677jqOOOII7rvvPjIyMvjFL34R9mhSL2ugjWW8xmYeB15jhK03SZIkSZL6kAGxB1x7ezsLFizgxhtv3HVbNBpl6tSp/POf/9zrY9ra2mhra9v1eUNDAwCrtlaRTWrvDiz1iDgxatlGPdUMZxkQYwhDCFjL2rCH61GRjgi5zbnUbakjSA7CHkfSW3iOSn2X56fUt3mOSn1X29auzCgIeubcHBAB3ObNm4nH4+Tn5+9xe35+PitWrNjrY2677Ta++c1vvu32k9/3tV6ZUZIkSZIkSf3Lli1byM4++BVmAyKAey9uvPFGZsyYsevz+vp6SkpKqKqq6pE/WEk9p7GxkTFjxrBu3TqysrLCHkfSW3iOSn2X56fUt3mOSn1XQ0MDxcXF5OTk9MjxBkQAN3LkSGKxGDU1NXvcXlNTQ0FBwV4fk5qaSmrq25eaZmdn+4NP6qOysrI8P6U+zHNU6rs8P6W+zXNU6rui0Z65fMKAuAhDSkoKxx57LM8888yu2xKJBM888wwnnXRSiJNJkiRJkiRpsBsQDTiAGTNmcM0113DcccdxwgkncMcdd9DU1MR1110X9miSJEmSJEkaxAZMAPeRj3yEuro6br75ZjZt2sTkyZN56qmn3nZhhn1JTU3llltu2euyVEnh8vyU+jbPUanv8vyU+jbPUanv6unzMxL01PVUJUmSJEmSJL3NgNgDTpIkSZIkSeqrDOAkSZIkSZKkXmQAJ0mSJEmSJPUiAzhJkiRJkiSpFxnAAXfffTelpaWkpaVx4oknUl5eHvZIkoDbbruN448/nqFDh5KXl8e0adNYuXJl2GNJ2ovvfve7RCIRvvzlL4c9iqRuGzZs4KqrrmLEiBGkp6dz1FFHMX/+/LDHkga9eDzOTTfdRFlZGenp6YwbN47/+q//wusjSuF4/vnnufDCCyksLCQSifDII4/s8fUgCLj55psZNWoU6enpTJ06ldWrVx/w8wz6AO6BBx5gxowZ3HLLLSxcuJBJkyZx3nnnUVtbG/Zo0qA3Z84cpk+fzssvv8zTTz9NR0cH5557Lk1NTWGPJmk38+bN48c//jFHH3102KNI6rZt2zZOOeUUkpOTefLJJ3n11Vf5wQ9+wPDhw8MeTRr0br/9du69917uuusuXnvtNW6//Xa+973v8b//+79hjyYNSk1NTUyaNIm77757r1//3ve+x5133sl9993H3LlzyczM5LzzzqO1tfWAnicSDPKY/cQTT+T444/nrrvuAiCRSDBmzBi++MUvcsMNN4Q8naTd1dXVkZeXx5w5czjttNPCHkcSsGPHDqZMmcI999zDt7/9bSZPnswdd9wR9ljSoHfDDTfw0ksv8cILL4Q9iqS3uOCCC8jPz+fnP//5rtsuvfRS0tPT+e1vfxviZJIikQizZs1i2rRpQFf7rbCwkK985Sv8x3/8BwANDQ3k5+dz//3389GPfnS/jz2oG3Dt7e0sWLCAqVOn7rotGo0ydepU/vnPf4Y4maS9aWhoACAnJyfkSSTtNH36dM4///w9/i6VFL7HHnuM4447jssuu4y8vDyOOeYYfvrTn4Y9liTg5JNP5plnnmHVqlUALFmyhBdffJEPfvCDIU8m6a0qKirYtGnTHv/Wzc7O5sQTTzzg3Cipp4frTzZv3kw8Hic/P3+P2/Pz81mxYkVIU0nam0QiwZe//GVOOeUUjjzyyLDHkQT84Q9/YOHChcybNy/sUSS9xZo1a7j33nuZMWMGX//615k3bx7//u//TkpKCtdcc03Y40mD2g033EBjYyPvf//7icVixONxvvOd73DllVeGPZqkt9i0aRPAXnOjnV/bX4M6gJPUf0yfPp1ly5bx4osvhj2KJGDdunV86Utf4umnnyYtLS3scSS9RSKR4LjjjuO///u/ATjmmGNYtmwZ9913nwGcFLI//vGP/O53v2PmzJlMnDiRxYsX8+Uvf5nCwkLPT2kAG9RLUEeOHEksFqOmpmaP22tqaigoKAhpKklv9YUvfIHZs2fz97//ndGjR4c9jiRgwYIF1NbWMmXKFJKSkkhKSmLOnDnceeedJCUlEY/Hwx5RGtRGjRrFEUccscdthx9+OFVVVSFNJGmn//zP/+SGG27gox/9KEcddRQf//jHuf7667ntttvCHk3SW+zMhnoiNxrUAVxKSgrHHnsszzzzzK7bEokEzzzzDCeddFKIk0mCrg0vv/CFLzBr1iyeffZZysrKwh5JUrezzz6bpUuXsnjx4l2/jjvuOK688koWL15MLBYLe0RpUDvllFNYuXLlHretWrWKkpKSkCaStFNzczPR6J5vxWOxGIlEIqSJJO1LWVkZBQUFe+RGjY2NzJ0794Bzo0G/BHXGjBlcc801HHfccZxwwgnccccdNDU1cd1114U9mjToTZ8+nZkzZ/Loo48ydOjQXWvss7OzSU9PD3k6aXAbOnTo2/ZjzMzMZMSIEe7TKPUB119/PSeffDL//d//zeWXX055eTk/+clP+MlPfhL2aNKgd+GFF/Kd73yH4uJiJk6cyKJFi/jhD3/IJz7xibBHkwalHTt28Prrr+/6vKKigsWLF5OTk0NxcTFf/vKX+fa3v82ECRMoKyvjpptuorCwcNeVUvdXJAiCoIdn73fuuusuvv/977Np0yYmT57MnXfeyYknnhj2WNKgF4lE9nr7L3/5S6699tpDO4ykd3XGGWcwefJk7rjjjrBHkQTMnj2bG2+8kdWrV1NWVsaMGTP49Kc/HfZY0qC3fft2brrpJmbNmkVtbS2FhYV87GMf4+abbyYlJSXs8aRB57nnnuPMM8982+3XXHMN999/P0EQcMstt/CTn/yE+vp6PvCBD3DPPffwvve974CexwBOkiRJkiRJ6kWDeg84SZIkSZIkqbcZwEmSJEmSJEm9yABOkiRJkiRJ6kUGcJIkSZIkSVIvMoCTJEmSJEmSepEBnCRJkiRJktSLDOAkSZIkSZKkXmQAJ0mSJEmSJPUiAzhJkqRDpLS0lEgkwv33339Aj3vuueeIRCJEIpEe+9r+qKys3PX4ysrK93SMvubaa68lEolw7bXXhj2KJEkaRJLCHkCSJKm/CYKABx98kJkzZ7Jw4UJqa2uJxWLk5+czatQoTjjhBE499VTOPvtssrKywh5XkiRJITOAkyRJOgD19fVMmzaNOXPm7LotKSmJjIwMqqqqWLNmDS+99BI/+tGP+OUvf9kjTauMjAwOO+ywgz6OJEmSwuESVEmSpANw9dVXM2fOHGKxGF/5yldYtWoVbW1tbNmyhZaWFpYsWcLtt9/OpEmTeuw5TzjhBFasWMGKFSt67JiSJEk6dGzASZIk7afVq1fz+OOPA/Dtb3+bG264YY+vJyUlcfTRR3P00Ufz1a9+lZaWljDGlCRJUh9jA06SJGk/LV68eNfvP/zhD7/r/dPT0w/o+N/5zneIRCLEYjHuu+++Xbcf7MUUelMikeB3v/sdH/rQh8jPzyclJYXc3FzOPfdcfv/73xMEwR73X7Ro0a7X8sorr7zjsa+++moikQhnn332Xr/+5z//mUsvvZSioiJSU1MZPnw4p512Gvfeey/t7e099holSZIOlgGcJEnSe7B+/foeO1YikeALX/gC3/jGN0hLS+PBBx/ks5/9bI8dv7ds3bqVM888k6uuuoonn3yS2tpaMjIy2Lx5M08//TRXXHEF06ZN2yMMO+aYY5g4cSIAv/nNb/Z57KamJh5++GGgK4jbXUtLC5dddhkXXHABDz/8MNXV1aSlpdHQ0MALL7zA5z//eU4//XS2bdvWC69akiTpwBnASZIk7afjjz9+Vwtt5/5vB6utrY3LL7+cu+++m2HDhvHXv/6Viy+++KCP29vi8TiXXHIJzz//PJMnT+bxxx+nqamJ+vp6duzYwa9+9Svy8vJ47LHH+NrXvrbHY3cGajNnziSRSOz1+LNmzaKpqYnMzEwuvfTSPb72mc98hgcffJCxY8fyu9/9joaGBhoaGmhububRRx9l7NixvPzyy3ziE5/onRcvSZJ0gAzgJEmS9lNpaSmf+tSnAFi6dCnvf//7mTJlCtOnT+cXv/gFy5Yte9uSy3fS0NDAeeedx0MPPURRUREvvPACp556am+N36NmzpzJnDlzeP/7389zzz3HBRdcQEZGBgCZmZlcffXVPPHEE0QiEe655x5qa2t3PfbKK68kGo1SXV3N3/72t70ef2c77uKLL2bIkCG7bn/hhRf47W9/S15eHs899xxXXHEFWVlZAKSlpXHRRRcxZ84cMjMzeeSRR/ZYNixJkhQWAzhJkqQDcM8993DTTTeRmZlJEAQsWrSIe+65h09+8pMcddRRFBQUMGPGDGpqat7xONXV1Zx66qm7Qqx//OMfHHnkkYfoVRy8n//85wB87nOfIzs7e6/3OfbYY5k4cSLt7e38/e9/33V7UVERZ511FrD3ZagbN27kmWeeAeDjH//4Xp/3yiuvZMyYMXt93tGjR3PmmWcC8Je//OVAXpYkSVKvMICTJEk6AElJSXzrW99iw4YN/OY3v+FTn/oUkyZNIiUlBYDa2lp+9KMfceSRR1JeXr7XY6xYsYKTTz6ZpUuXctJJJ/HSSy9RXFx8KF/GQYnH47z88ssA3HrrrRQUFOzz18qVKwFYu3btHsfYuQx151LT3c2cOZN4PE5hYSFTp07d42svvfQS0BXEvdPz7mzWvfV5JUmSwpAU9gCSJEn9UXZ2NldddRVXXXUVAK2trbz44ovceeedPP7442zevJlLL72U1atXk5aWtsdjb7/9dgDy8/P561//uscSy0PhgQce4Etf+tJev/bwww9z8sknv+Pjt27dSltbG8B+X+igubl5j88vueQSPv/5z7Njxw4efvjhPZpuO1txO5eq7q66uhqAxsZGGhsbD/h5JUmSwmADTpIkqQekpaUxdepUHnvsMa655hqg60qpTz311Nvue9lll5GSkkJNTQ2f+9zniMfjh3TWlpYWampq9vpr9yuW7svu8z755JMEQfCuv2699dY9jpGZmckll1wCwK9//etdty9dupQlS5YAb19+uvtz33vvvfv1vPfff/+B/vFIkiT1OAM4SZKkHvaZz3xm1+93LsHc3Yc+9CFmzZpFamoqv/3tb/n4xz9+SEO4a6+9dp+B1RlnnPGujx8xYgRJSV0LKQ5miefOgO3ZZ59lw4YNwJvtt8mTJ3PUUUe97TEFBQUH/bySJEmHmgGcJElSD9t9SWlqaupe7/OhD32IRx99lLS0NH7/+99zxRVX0NnZeahGPCjJycmccMIJADz++OPv+ThnnXUWo0ePJpFIMHPmzF0f4c094t7qlFNOAWD27Nnv+XklSZIONQM4SZKk/VRRUcGqVave9X6/+tWvdv1+ypQp+7zfeeedx2OPPUZ6ejp//OMf+ehHP0pHR0ePzNrbdrb8nnjiCZ544ol3vO/WrVv3ens0GuXKK68EuppvO5twsViMK6644h2fd9myZdx7773v+LxNTU37taRWkiSptxnASZIk7afly5dz+OGHc/755/PrX/+aysrKXV/r6Ohg0aJFXHfddfzwhz8E4IQTTuADH/jAOx7znHPOYfbs2WRkZPDQQw9x+eWX94vQ6KqrrmLq1KkEQcDFF1/Mt7/97V0XSICu8Ovvf/8706dPZ+zYsfs8zs5lqEuXLuXGG28E4NxzzyU/P3+v9z/99NO57rrrAJg+fTrXX389a9as2fX1trY2Xn75Zb761a9SUlJCbW3tQb9WSZKkg+VVUCVJkvZTcnIyiURij9ZXSkoKQ4YMYdu2bQRBsOu+U6ZMYdasWW+7iufenHXWWTzxxBOcf/75PPLII1x66aU89NBDpKSk9NprOVixWIyHHnqIK6+8ktmzZ3PTTTdx0003kZWVRTQapaGhYdefx8794vZm4sSJTJkyhYULFzJ//nxg38tPd7rvvvuIxWL87Gc/44477uCOO+5gyJAhJCcn09DQQCKR2HXfSCTSA69WkiTp4NiAkyRJ2k/nnXceq1ev5n/+53+47LLLOPzww0lNTaW+vp6MjAwmTJjA5Zdfzh/+8AfmzZtHYWHhfh/79NNP56mnnmLo0KHMnj2badOm0dbW1ouv5uBlZWXx+OOP88QTT/CRj3yE4uJi2traaG5upqioiHPPPZfbbrttrxei2N3ugVtWVhYf/vCH3/H+KSkp/PSnP+Uf//gH1157LePGjSMej7Njxw7y8vI444wzuPnmm3nllVcoKirqkdcqSZJ0MCLB7v+rVpIkSZIkSVKPsgE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    " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "# Create data for the skill and challenge levels\n", "skill_levels = np.linspace(0, 10, 100)\n", "challenge_levels = np.linspace(0, 10, 100)\n", "\n", "# Define the flow channel boundaries\n", "flow_channel = skill_levels\n", "\n", "# Adjust the phase and amplitude of the sinusoid wave\n", "phase = np.pi / 16\n", "amplitude = 1.5\n", "sinusoid = flow_channel + np.sin(skill_levels + phase) * amplitude\n", "\n", "# Define the yellow zone boundaries, making it wider\n", "yellow_zone_low = skill_levels - 1.5 # Adjust this value to make the yellow zone wider or narrower\n", "yellow_zone_high = skill_levels + 1.5 # Adjust this value to make the yellow zone wider or narrower\n", "\n", "# Plotting\n", "plt.figure(figsize=(15, 10))\n", "\n", "# Plot the anxiety and boredom areas\n", "plt.fill_between(skill_levels, yellow_zone_high, 10, color='orangered', alpha=0.3, label='Place/Identification', interpolate=True)\n", "plt.fill_between(skill_levels, 0, yellow_zone_low, color='lime', alpha=0.3, label='Time/Revelation', interpolate=True)\n", "plt.fill_between(skill_levels, yellow_zone_low, yellow_zone_high, color='yellow', alpha=0.3, label='Agent/Evolution', interpolate=True)\n", "\n", "# Plot the sinusoid function with the diagonal as its axis\n", "plt.plot(skill_levels, sinusoid, color='purple', linestyle='-')\n", "\n", "# Add arrowhead to the sinusoid line\n", "plt.arrow(skill_levels[-2], sinusoid[-2], skill_levels[-1] - skill_levels[-2], sinusoid[-1] - sinusoid[-2],\n", " color='purple', length_includes_head=True, head_width=0.15, head_length=0.3)\n", "\n", "# Set plot labels and title\n", "plt.xlabel('Skill-level', fontsize=18)\n", "plt.ylabel('Challenge-level', rotation='vertical', fontsize=18)\n", "\n", "# Set plot limits and grid\n", "plt.xlim(0, 10)\n", "plt.ylim(0, 10)\n", "plt.grid(True)\n", "\n", "# Set tick labels\n", "tick_labels = ['0', '2', '4', '6', '8', '10']\n", "plt.xticks(np.linspace(0, 10, 6), tick_labels)\n", "plt.yticks(np.linspace(0, 10, 6), tick_labels)\n", "\n", "# Add text annotations to label the areas without shaded background\n", "plt.text(1, 6, 'Voir', color='black', ha='center', va='center', fontsize=50)\n", "plt.text(4.5, 4.7, 'Pouvoir', color='black', ha='center', va='center', fontsize=50)\n", "plt.text(8, 3, 'Savoir', color='black', ha='center', va='center', fontsize=50)\n", "\n", "# Display the plot\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "1. Voir\n", " - Truth: Perception of biological and primal stimuli; see\n", " - Entirely dependent on perspective; power/hierarchy\n", " - Cells/Tissues; Immune/Neuro/Endocrine/Reproductive/Kidney/CVS\n", " - Steroids, Catecholamines, Cytokines, Hormones\n", " - Dionysian: Homeostasis, Biology\n", "2. Pouvoir \n", " - Knowledge: Acquiring skills, match challenges; do\n", " - Adaptation, homeostasis, allostasis; variance/explain\n", " - Organs/Systems; Muscle/Bone \n", " - Dopamine, Serotonin, Oxytocin, Endorphins\n", " - Tragedy: Allostasis, Psychology\n", "3. Savoir\n", " - Justice: Cumulated values, beliefs, and norms; be\n", " - Silos, numbing with comforts and distractions, \"bread\"; bias/control\n", " - Person/Interaction; Frontal Cortex, Hippocampus, Amygdala\n", " - GABA, Adenosine, Glutamate, Acetylcholine\n", " - Apollonian: Sociostasis, Credo\n", "\n", "\n", "
    \n", "\n", "
    \n", " \n", "\n", "1. [This](https://www.economist.com/films/2023/10/09/well-red-inside-the-economists-language-and-style) reveals a lot of interesting phenomena\n", "2. Souless GenZ and Millenials\n", "3. Exposed to the same \"Dionysian\" stimuli \n", "4. With a much weakened \"Apollonian\" counterbalance\n", "5. History usually provided monumental, antiquarian, and critical perspectives\n", "6. Now, it's just a \"Dionysian\" free-for-all - and with all the attendant fenzy, intoxication and addiction\n", "7. Because frenzy is from the external (boundless) rather than internal (bounded) elements, we fear it breaches the limits of the \"Apollonian\" counterbalance\n", "
    " ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.4" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }