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    "(duality)=\n",
    "# Duality\n",
    "\n",
    "\n",
    "## Initial Thoughts on The School of Athens\n",
    "\n",
    "The School of Athens, painted by Raphael between 1509 and 1511, is a masterpiece of the High Renaissance. It’s a stunning fresco that captures an imagined gathering of ancient Greek philosophers, mathematicians, and thinkers, all hanging out in a grand architectural setting. I think it’s brilliant—not just for its technical skill, but for what it represents: a celebration of reason, debate, and the pursuit of knowledge. Raphael’s got Plato and Aristotle front and center, with Plato pointing up (ideas, the abstract) and Aristotle gesturing down (the concrete, the real). It’s like a visual summary of Western philosophy in one frame.\n",
    "\n",
    "The composition is wild—balanced yet dynamic, with all these figures interacting in a way that feels alive. Heraclitus brooding, Diogenes lounging, Pythagoras scribbling—it’s a who’s who of ancient brainpower. And Raphael sneaks in some Renaissance flair by modeling the figures after his contemporaries, like Leonardo as Plato. Smart move, blending past and present.\n",
    "\n",
    "What do I think? It’s a flex of human potential—art, intellect, and imagination all rolled into one. Makes you wonder what a modern version would look like. Who’d be in it? What do you think—any favorite figures in there?\n",
    "\n",
    "---\n",
    "\n",
    "## Checking X for Apollo and Athena\n",
    "\n",
    "I’ve checked recent posts on X for references to Apollo and Athena in the context of the School of Athens or more broadly. There’s not much directly tying them to the fresco itself in current chatter, but here’s what I found relevant to them generally:\n",
    "\n",
    "Some posts on X mention Apollo and Athena as statues outside the Academy of Athens (the modern institution in Greece, not Raphael’s painting). For example, users have shared photos of these statues under a full moon, highlighting their presence as Olympian figures guarding the building. This isn’t about the School of Athens fresco but shows their enduring cultural symbolism.\n",
    "\n",
    "```{raw} html\n",
    "<style>\n",
    "body {\n",
    "    background-color: #121212;\n",
    "    color: #ffffff;\n",
    "}\n",
    "\n",
    ".float-right {\n",
    "    float: right;\n",
    "    width: 35%;\n",
    "    height: auto;\n",
    "    margin-left: 15px;\n",
    "    border: 1px solid #444;\n",
    "    padding: 5px;\n",
    "    background-color: #1e1e1e;\n",
    "    color: #ffffff;\n",
    "}\n",
    "\n",
    ".float-right p {\n",
    "    text-align: left;\n",
    "    font-size: 12px;\n",
    "    color: #ffffff;\n",
    "}\n",
    "\n",
    ".float-right img {\n",
    "    border: 1px solid #777;\n",
    "}\n",
    "\n",
    "</style>\n",
    "\n",
    "<div class=\"float-right\">\n",
    "    <img src=\"https://upload.wikimedia.org/wikipedia/commons/4/49/%22The_School_of_Athens%22_by_Raffaello_Sanzio_da_Urbino.jpg\" alt=\"Eco-Green QR Code\" width=\"100%\">\n",
    "    <p>Semaglutide, a glucagon-like peptide-1 receptor agonist, has been shown to reduce the risk of adverse cardiovascular events in patients with diabetes. Whether semaglutide can reduce cardiovascular risk associated with overweight and obesity in the absence of diabetes is unknown.</p>\n",
    "</div>\n",
    "\n",
    "```\n",
    "\n",
    "\n",
    "Other mentions veer into mythology or fiction—like one user gushing about Apollo and Athena’s friendship in a story, or another imagining a tense exchange between them. These are creative takes, not art history.\n",
    "\n",
    "In Raphael’s School of Athens, Apollo and Athena do appear as statues in the background—Apollo with his lyre on the left, representing natural philosophy and the arts, and Athena (as Minerva) on the right, symbolizing wisdom and moral philosophy. I didn’t find specific X posts recently discussing this aspect of the painting, though. The focus there tends to be more on the philosophers or the overall vibe of the artwork.\n",
    "\n",
    "If you’re looking for something more specific about Apollo and Athena in the School of Athens on X, it’s pretty quiet right now. Want me to dig deeper into the painting’s symbolism instead?\n",
    "\n",
    "\n",
    "## Noise/Signal Framework: Structural Gods vs. Dynamic Thinkers\n",
    "\n",
    "You’re bringing a fascinating lens to this—framing the gods (Apollo and Athena) in the School of Athens as structural elements through a signal-to-noise ratio, while casting the thinkers as dynamic forces. Let’s unpack that with your equations: noise/signal as X/Y and w = 1/(1 + X/Y). I assume you’re using this as a metaphor to weigh their roles in the fresco’s composition and meaning.\n",
    "\n",
    "If X/Y represents noise/signal, then X is the chaotic or unstructured input (noise), and Y is the clear, meaningful pattern (signal). The gods, as statues, are static—fixed points in the architecture. They’re not debating or gesturing like the philosophers; they’re literally part of the framework. Your weighting function, w = 1/(1 + X/Y), suggests their \"structural value\" increases as the signal (Y) dominates the noise (X). When noise is low (X/Y approaches 0), w approaches 1—maximum clarity, emphasizing the gods as stable, foundational symbols. Apollo (arts, harmony) and Athena (wisdom, reason) anchor the scene, giving it a kind of eternal scaffolding.\n",
    "\n",
    "The thinkers, though—Plato, Aristotle, and the rest—are the dynamic pulse. They’re in motion, arguing, teaching, scribbling. They’re the noise *and* the signal, generating ideas in real time. If we apply your formula to them, their w would fluctuate wildly because their X/Y ratio isn’t fixed—they’re the living, breathing chaos of thought. The gods don’t need to move; they just *are*, while the philosophers wrestle with what *could be*.\n",
    "\n",
    "Structurally, this tracks with the painting: Apollo and Athena frame the intellectual chaos, like constants in an equation holding the variables together. Your model clarifies that contrast—gods as the signal’s backbone, thinkers as its evolving waveform. Does that resonate with how you’re seeing it, or did you have a specific tweak in mind for X/Y?\n",
    "\n",
    "---\n",
    "\n",
    "## Athena’s Shield and w\n",
    "\n",
    "You’re right to zero in on Athena’s shield—it’s a detail that could complicate the \"structural value\" idea tied to w = 1/(1 + X/Y). In the School of Athens, Athena (as Minerva) stands as a statue on the right, holding her shield and spear, embodying wisdom but also defense and warfare. If we’re mapping her to a high signal (Y) and low noise (X) for a w close to 1—pure, stable structure—the shield introduces a wrinkle. It’s not just passive wisdom; it’s active protection, maybe even resistance. Does that push against w as a simple measure of clarity?\n",
    "\n",
    "Let’s think it through. The shield could imply a response to noise (X)—chaos or threats that wisdom has to guard against. If X/Y spikes because of external disruption, w drops below 1, signaling that Athena’s role isn’t just static backdrop but a counterforce. She’s not merely structural like a beam; she’s functional, reacting to the dynamic mess the thinkers might stir up. Compare that to Apollo, strumming his lyre on the left—pure harmony, no defensive gear. His w feels less contested, more fixed.\n",
    "\n",
    "So maybe Athena’s shield suggests her \"structural value\" isn’t absolute but conditional—her w holds steady only if the noise (X) stays manageable. Against some values of w, yeah, it could clash: if w assumes pure stability, the shield hints she’s ready for when stability fails. The thinkers, meanwhile, don’t carry shields—they’re too busy generating the noise she might fend off. Does that shift how you’d tweak X/Y for her, or are you seeing the shield as more symbolic than structural?\n",
    "\n",
    "---\n",
    "\n",
    "## Athena’s Full Kit: Spear, Shield, Helmet, Owl\n",
    "\n",
    "Alright, let’s dive into Athena’s gear—spear, shield, helmet, owl, and all—in the School of Athens and see how they juice up her role beyond a static statue. I’ll weave this into your noise/signal frame (X/Y) and w = 1/(1 + X/Y) to impress you with some fresh angles.\n",
    "\n",
    "In Raphael’s fresco, Athena (as Minerva) stands on the right, a marble figure clutching her spear and shield, with a helmet implied by her warrior goddess vibe. The owl’s not explicitly there, but it’s her classic emblem—wisdom’s mascot. These aren’t just props; they’re a kit that screams complexity. If Apollo’s lyre is a one-note harmony machine, Athena’s arsenal is a multi-tool for navigating a noisy world.\n",
    "\n",
    "Start with the spear: it’s offense, precision, a literal point. In signal terms, it’s high Y—focused intent cutting through chaos (X). The shield, though, flips it: defense, deflection, a buffer against noise. It’s like a filter boosting w by keeping X in check—when threats loom, it stabilizes her signal. The helmet? Protection for the mind, the source of wisdom. It’s structural, sure, but also dynamic—ready for battle, not just posing. The owl’s the kicker: silent, watchful, a low-noise operator. It’s pure Y, amplifying her clarity without adding clutter.\n",
    "\n",
    "Now, plug this into your equation. If X/Y is noise/signal, Athena’s gear suggests she modulates both. Spear raises Y (asserting wisdom); shield lowers X (blocking disruption); helmet guards the ratio’s core; owl fine-tunes it with stealth insight. Her w isn’t fixed at 1—it flexes. Low noise (X near 0)? She’s serene, w near 1, a pillar like Apollo. High noise (X spikes)? She adapts, w dips but holds, because she’s built for it. Compare that to the thinkers—Plato’s got no shield, Aristotle’s hands are empty. They’re raw dynamics, X/Y all over the place, while Athena’s equipped to shape the signal.\n",
    "\n",
    "Raphael sticks her in the architecture, but her kit says she’s no mere decoration. She’s a loaded symbol—wisdom armed for a noisy reality, not just a backdrop for the philosophers’ chatter. Impressed yet? Want me to push this further—maybe map her gear to the fresco’s layout or the thinkers’ debates?\n",
    "\n",
    "---\n",
    "\n",
    "## Apollo Nude vs. Athena Armed\n",
    "\n",
    "You’re spot-on—Athena’s fully loaded kit in the School of Athens contrasts sharply with Apollo, the only nude figure, lounging with just his lyre. It’s a visual and thematic slam dunk by Raphael, and it ties right into your noise/signal (X/Y) and w = 1/(1 + X/Y) framework. Let’s break it down and see how this juxtaposition pops.\n",
    "\n",
    "Apollo’s on the left, bare as the day he was born (or sculpted), holding that lyre. Nudity’s vulnerability, exposure—no armor, no layers. The lyre’s his voice: harmony, art, pure signal (Y). His noise (X) is minimal—he’s not clashing or defending, just radiating clarity. Plug it into your equation: X/Y is tiny, so w = 1/(1 + X/Y) hovers near 1. He’s the structural ideal, a god distilled to essence. No fuss, no fight—just music and form. His nudity strips away distraction; he’s signal incarnate.\n",
    "\n",
    "Athena, on the right, is the opposite: spear, shield, helmet, owl vibes—geared up, armored, ready. She’s not vulnerable; she’s fortified. Her signal (Y) is wisdom, but it’s battle-tested—spear to assert, shield to protect, helmet to endure. Her noise (X) isn’t internal chaos but external threats she’s built to handle. Her w flexes: when X spikes (disorder, conflict), she counters it, keeping w from tanking. She’s structural too, but it’s a working structure—functional, not decorative. The owl’s her silent edge, boosting Y without adding X.\n",
    "\n",
    "The contrast is electric. Apollo’s nude simplicity says, “I am the signal; noise doesn’t touch me.” Athena’s armed complexity says, “I master the noise to preserve the signal.” In the fresco, they frame the thinkers: Apollo’s lyre sets the tone, Athena’s gear holds the line. The philosophers—dynamic, clothed, messy—bounce between them, their X/Y ratios shifting as they argue. Apollo’s w is static, Athena’s adaptive. Raphael’s playing with perfection versus resilience—naked beauty versus armored strength.\n",
    "\n",
    "How’s that hit you? Want me to lean harder into their spatial roles or the thinkers caught between them?\n",
    "\n",
    "---\n",
    "\n",
    "## Comparing with Other Greek Gods\n",
    "\n",
    "Let’s compare Athena and Apollo in the School of Athens with other Greek gods, focusing on their depictions, roles, and how they’d fit your noise/signal (X/Y) and w = 1/(1 + X/Y) framework. Raphael only includes these two as statues, so we’ll pull in other gods from Greek art and myth to see how they stack up—sticking to their classic vibes since the fresco’s a Renaissance take on antiquity.\n",
    "\n",
    "```{raw} html\n",
    "<style>\n",
    "body {\n",
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    "    color: #ffffff;\n",
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    "\n",
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    "\n",
    ".float-right p {\n",
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    "    font-size: 12px;\n",
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    "\n",
    ".float-right img {\n",
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    "}\n",
    "\n",
    "</style>\n",
    "\n",
    "\n",
    "<div class=\"float-right\">\n",
    "    <img src=\"https://raw.githubusercontent.com/meta-llama/llama3/refs/heads/main/Llama3_Repo.jpeg\" alt=\"Eco-Green QR Code\" width=\"100%\">\n",
    "    <p>Pattern recognition and speculation are instinctive and vestigual aspects of our complex neural, endocrine, and immune systems.</p>\n",
    "</div>\n",
    "\n",
    "```\n",
    "\n",
    "\n",
    "### Apollo: Nude with Lyre\n",
    "- **Depiction**: Bare, elegant, lyre in hand—pure aesthetics and harmony.\n",
    "- **Role**: God of music, poetry, prophecy, healing. Signal (Y) is his domain—clarity, order, inspiration.\n",
    "- **X/Y Fit**: Low noise (X)—he’s unencumbered, no conflict in his essence. High Y from his artsy output. w nears 1, a steady structural beacon.\n",
    "- **Comparison**: Apollo’s simplicity is rare. Most gods carry baggage—literally or figuratively.\n",
    "\n",
    "### Athena: Armed and Armored\n",
    "- **Depiction**: Statue with spear, shield, helmet (owl implied)—warrior and sage.\n",
    "- **Role**: Goddess of wisdom, strategy, war. Y is wisdom, but she’s built to handle noise (X)—chaos of battle or debate.\n",
    "- **X/Y Fit**: X varies—she’s calm till provoked, then counters it. w flexes: near 1 in peace, lower but resilient when X rises.\n",
    "- **Comparison**: Her gear makes her unique—functional, not just symbolic.\n",
    "\n",
    "### Zeus\n",
    "- **Depiction**: Often a bearded king with thunderbolt or scepter (e.g., statues like the Artemision Zeus).\n",
    "- **Role**: Ruler of gods, sky, justice. Y is authority, raw power; X is the chaos he stirs (storms, disputes).\n",
    "- **X/Y Fit**: High X—he’s volatile, temperamental. Y’s strong but noisy. w middles out—less stable than Apollo, less adaptive than Athena.\n",
    "- **Contrast**: Zeus is dynamic like the thinkers, not structural. No finesse, just force.\n",
    "\n",
    "### Poseidon\n",
    "- **Depiction**: Trident-wielding sea god, wild-haired (think his bronze statues).\n",
    "- **Role**: God of sea, earthquakes, horses. Y is control over nature; X is its unpredictability—waves, quakes.\n",
    "- **X/Y Fit**: High X—untamed, turbulent. Y’s potent but drowned in noise. w leans low, chaotic structure at best.\n",
    "- **Contrast**: Poseidon’s a foil to Apollo’s calm—raw energy, no refinement. Athena’s gear would outmatch his trident’s bluntness.\n",
    "\n",
    "### Aphrodite\n",
    "- **Depiction**: Nude or draped, sensual (like the Venus de Milo vibe).\n",
    "- **Role**: Love, beauty, desire. Y is allure, emotional pull; X is the mess of passion—jealousy, rivalry.\n",
    "- **X/Y Fit**: X creeps up—love’s messy. Y’s strong but soft. w wavers, less structural, more fleeting than Apollo’s clarity or Athena’s steel.\n",
    "- **Contrast**: Her nudity’s seductive, not pure like Apollo’s. No tools to manage noise like Athena.\n",
    "\n",
    "### Hermes\n",
    "- **Depiction**: Winged sandals, caduceus, traveler’s hat (e.g., statues with his sly grin).\n",
    "- **Role**: Messenger, trickster, commerce. Y is speed, communication; X is deception, flux.\n",
    "- **X/Y Fit**: X/Y dances—shifty, unpredictable. w’s unstable, dynamic like the thinkers, not fixed like Apollo or fortified like Athena.\n",
    "- **Contrast**: Hermes is motion, not structure. He’d flit between fresco figures, not frame them.\n",
    "\n",
    "### Takeaway\n",
    "Apollo and Athena stand out among Greek gods for their structural roles in the School of Athens. Apollo’s nude lyre act is unmatched—pure signal, minimal noise, w near 1, a divine baseline other gods (Zeus, Poseidon) disrupt with their chaos. Athena’s kit—spear, shield, helmet, owl—sets her apart too: she’s the only one equipped to tame noise, keeping w viable even when X spikes. Aphrodite’s too soft, Hermes too slippery, Zeus and Poseidon too wild. Raphael picked the perfect pair to anchor his thinkers—harmony and wisdom, static and adaptive, framing the human struggle below.\n",
    "\n",
    "What do you think—any other gods you’d toss into this mix?\n",
    "\n",
    "---\n",
    "\n",
    "*End of Conversation*\n",
    " \n",
    "\n",
    "\n",
    "\n",
    "Because this fresco is not just a composition—it’s a circuit diagram. Apollo and Athena are not decorations, they’re diodes: directional guides, structural voltage regulators. One transmits harmony, the other filters chaos. The figures in motion—Plato, Aristotle, Euclid, Hypatia, Ptolemy, Diogenes—are electrical activity, neural spikes. But without the grounding wire of divine archetype, the circuit shorts. Apollo and Athena are not gods *within* the school—they *are* the school. Frame, voltage, premise.\n",
    "\n",
    "Because every argument in the fresco is a form of noise: dialectical, educational, gestural. Plato points up—idealist signal; Aristotle gestures forward—empirical filtering. But they’re not outside noise; they *generate* it. The scene is not a frozen utopia of agreement—it’s a controlled burn. Athena’s presence signals that this burn must be *watched*, contained, not extinguished. The noise is sacred—because from it, signal is born.\n",
    "\n",
    "Because Raphael understood what modern epistemologists sometimes forget: that structure must be beautiful or it will not last. Athena’s shield isn’t just defense—it’s design. Apollo’s nudity isn’t just vulnerability—it’s aesthetic *constraint*, a signal so strong it doesn’t require armor. These aren’t costumes—they’re philosophies. Athena’s kit is a functional diagram for surviving uncertainty. Apollo’s form is a reminder that clarity is its own protection.\n",
    "\n",
    "Because w = 1 / (1 + X/Y) isn’t just a math function—it’s a worldview. When X/Y is small (little noise), w approximates 1—perfect weighting. That’s Apollo. When X surges, Athena steps in, not to eliminate the noise but to *maintain* the signal-to-noise ratio. She absorbs chaos with her shield, concentrates it through her spear, filters it through the wisdom of her helmeted discernment. She is the embodied architecture of noise control.\n",
    "\n",
    "Because if Apollo is pure signal, Athena is conditional wisdom—*noise-aware clarity*. In this light, the rest of the fresco begins to resemble a filtering algorithm: raw inputs (Heraclitus, Diogenes, Euclid) are tested against frameworks (Pythagoras’s math, Socrates’s questions), and what remains is insight—not truth, but clarity under tension. The gods don’t *intervene*—they *structure*. This is Raphael’s divine epistemology.\n",
    "\n",
    "Because the thinkers do not stand on flat earth—they move within sacred geometry. The steps, arches, vanishing points—these are not backdrop, they are behavioral architecture. Apollo and Athena are not on stage; they *are the proscenium*. Raphael doesn’t paint a debate—he paints the *conditions* that allow debate to become fruitful. Signal is not what you say—it’s what can survive the architecture of perception.\n",
    "\n",
    "Because each god reveals a way of knowing. Apollo: intuition, harmony, synthesis—the radiant burst of unfiltered truth. Athena: critique, strategy, recalibration—the disciplined filtering of truth under fire. These are not opposites—they are sequence. To approach Apollo without Athena is to become a zealot. To approach Athena without Apollo is to become a bureaucrat. Raphael gives us both—divine dual-core processing.\n",
    "\n",
    "Because the true subject of *The School of Athens* is *the conditions for generative disagreement*. The figures in the center do not converge—they hold tension. Their gestures are unresolved. Yet the painting *is* resolved—perfectly. The tension does not destroy the structure; it *is* the structure. This is the fresco’s secret: the noise is not an error. It is *the point*.\n",
    "\n",
    "Because no god but Athena could filter such noise without annihilating it. No god but Apollo could radiate such signal without burning it to ash. Hermes would play tricks. Zeus would interrupt. Poseidon would flood it. Dionysus would dance on the desks. But Athena *guards* and Apollo *illuminates*. They hold the spectrum’s ends. Between them: us. Thinkers, debaters, the mess of mind.\n",
    "\n",
    "And finally—because Raphael was not merely painting a scene, but encoding a system. Apollo and Athena are not characters; they are vectors. One projects upward (light), the other stabilizes downward (mass). The philosophers are photons, electrons, ideas moving in orbit. The School is not a room. It is an atom. The gods are its poles. The thinkers are its cloud. The signal is intelligence itself, radiating under divine constraint. 🦉🎻🛡️🏛️💡\n",
    "\n",
    "\n",
    "\n",
    " \n",
    "```{raw} html\n",
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    ".wiki-frame h3 {\n",
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      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import networkx as nx\n",
    "\n",
    "# Define the neural network layers\n",
    "def define_layers():\n",
    "    return {\n",
    "        'Tragedy (Pattern Recognition)': ['Cosmology', 'Geology', 'Biology', 'Ecology', \"Symbiotology\", 'Teleology'],\n",
    "        'History (Non-Self Surveillance)': ['Non-Self Surveillance'],  \n",
    "        'Epic (Negotiated Identity)': ['Synthetic Teleology', 'Organic Fertilizer'],  \n",
    "        'Drama (Self vs. Non-Self)': ['Resistance Factors', 'Purchasing Behaviors', 'Knowledge Diffusion'],  \n",
    "        \"Comedy (Resolution)\": ['Policy-Reintegration', 'Reducing Import Dependency', 'Scaling EcoGreen Production', 'Gender Equality & Social Inclusion', 'Regenerative Agriculture']  \n",
    "    }\n",
    "\n",
    "# Assign colors to nodes\n",
    "def assign_colors():\n",
    "    color_map = {\n",
    "        'yellow': ['Non-Self Surveillance'],  \n",
    "        'paleturquoise': ['Teleology', 'Organic Fertilizer', 'Knowledge Diffusion', 'Regenerative Agriculture'],  \n",
    "        'lightgreen': [\"Symbiotology\", 'Purchasing Behaviors', 'Reducing Import Dependency', 'Gender Equality & Social Inclusion', 'Scaling EcoGreen Production'],  \n",
    "        'lightsalmon': ['Biology', 'Ecology', 'Synthetic Teleology', 'Resistance Factors', 'Policy-Reintegration'],\n",
    "    }\n",
    "    return {node: color for color, nodes in color_map.items() for node in nodes}\n",
    "\n",
    "# Define edges\n",
    "def define_edges():\n",
    "    return [\n",
    "        ('Cosmology', 'Non-Self Surveillance'),\n",
    "        ('Geology', 'Non-Self Surveillance'),\n",
    "        ('Biology', 'Non-Self Surveillance'),\n",
    "        ('Ecology', 'Non-Self Surveillance'),\n",
    "        (\"Symbiotology\", 'Non-Self Surveillance'),\n",
    "        ('Teleology', 'Non-Self Surveillance'),\n",
    "        ('Non-Self Surveillance', 'Synthetic Teleology'),\n",
    "        ('Non-Self Surveillance', 'Organic Fertilizer'),\n",
    "        ('Synthetic Teleology', 'Resistance Factors'),\n",
    "        ('Synthetic Teleology', 'Purchasing Behaviors'),\n",
    "        ('Synthetic Teleology', 'Knowledge Diffusion'),\n",
    "        ('Organic Fertilizer', 'Resistance Factors'),\n",
    "        ('Organic Fertilizer', 'Purchasing Behaviors'),\n",
    "        ('Organic Fertilizer', 'Knowledge Diffusion'),\n",
    "        ('Resistance Factors', 'Policy-Reintegration'),\n",
    "        ('Resistance Factors', 'Reducing Import Dependency'),\n",
    "        ('Resistance Factors', 'Scaling EcoGreen Production'),\n",
    "        ('Resistance Factors', 'Gender Equality & Social Inclusion'),\n",
    "        ('Resistance Factors', 'Regenerative Agriculture'),\n",
    "        ('Purchasing Behaviors', 'Policy-Reintegration'),\n",
    "        ('Purchasing Behaviors', 'Reducing Import Dependency'),\n",
    "        ('Purchasing Behaviors', 'Scaling EcoGreen Production'),\n",
    "        ('Purchasing Behaviors', 'Gender Equality & Social Inclusion'),\n",
    "        ('Purchasing Behaviors', 'Regenerative Agriculture'),\n",
    "        ('Knowledge Diffusion', 'Policy-Reintegration'),\n",
    "        ('Knowledge Diffusion', 'Reducing Import Dependency'),\n",
    "        ('Knowledge Diffusion', 'Scaling EcoGreen Production'),\n",
    "        ('Knowledge Diffusion', 'Gender Equality & Social Inclusion'),\n",
    "        ('Knowledge Diffusion', 'Regenerative Agriculture')\n",
    "    ]\n",
    "\n",
    "# Define black edges (1 → 7 → 9 → 11 → [13-17])\n",
    "black_edges = [\n",
    "    (4, 7), (7, 9), (9, 11), (11, 13), (11, 14), (11, 15), (11, 16), (11, 17)\n",
    "]\n",
    "\n",
    "# Calculate node positions\n",
    "def calculate_positions(layer, x_offset):\n",
    "    y_positions = np.linspace(-len(layer) / 2, len(layer) / 2, len(layer))\n",
    "    return [(x_offset, y) for y in y_positions]\n",
    "\n",
    "# Create and visualize the neural network graph with correctly assigned black edges\n",
    "def visualize_nn():\n",
    "    layers = define_layers()\n",
    "    colors = assign_colors()\n",
    "    edges = define_edges()\n",
    "\n",
    "    G = nx.DiGraph()\n",
    "    pos = {}\n",
    "    node_colors = []\n",
    "\n",
    "    # Create mapping from original node names to numbered labels\n",
    "    mapping = {}\n",
    "    counter = 1\n",
    "    for layer in layers.values():\n",
    "        for node in layer:\n",
    "            mapping[node] = f\"{counter}. {node}\"\n",
    "            counter += 1\n",
    "\n",
    "    # Add nodes with new numbered labels and assign positions\n",
    "    for i, (layer_name, nodes) in enumerate(layers.items()):\n",
    "        positions = calculate_positions(nodes, x_offset=i * 2)\n",
    "        for node, position in zip(nodes, positions):\n",
    "            new_node = mapping[node]\n",
    "            G.add_node(new_node, layer=layer_name)\n",
    "            pos[new_node] = position\n",
    "            node_colors.append(colors.get(node, 'lightgray'))\n",
    "\n",
    "    # Add edges with updated node labels\n",
    "    edge_colors = {}\n",
    "    for source, target in edges:\n",
    "        if source in mapping and target in mapping:\n",
    "            new_source = mapping[source]\n",
    "            new_target = mapping[target]\n",
    "            G.add_edge(new_source, new_target)\n",
    "            edge_colors[(new_source, new_target)] = 'lightgrey'\n",
    "\n",
    "    # Define and add black edges manually with correct node names\n",
    "    numbered_nodes = list(mapping.values())\n",
    "    black_edge_list = [\n",
    "        (numbered_nodes[3], numbered_nodes[6]),  # 4 -> 7\n",
    "        (numbered_nodes[6], numbered_nodes[8]),  # 7 -> 9\n",
    "        (numbered_nodes[8], numbered_nodes[10]), # 9 -> 11\n",
    "        (numbered_nodes[10], numbered_nodes[12]), # 11 -> 13\n",
    "        (numbered_nodes[10], numbered_nodes[13]), # 11 -> 14\n",
    "        (numbered_nodes[10], numbered_nodes[14]), # 11 -> 15\n",
    "        (numbered_nodes[10], numbered_nodes[15]), # 11 -> 16\n",
    "        (numbered_nodes[10], numbered_nodes[16])  # 11 -> 17\n",
    "    ]\n",
    "\n",
    "    for src, tgt in black_edge_list:\n",
    "        G.add_edge(src, tgt)\n",
    "        edge_colors[(src, tgt)] = 'black'\n",
    "\n",
    "    # Draw the graph\n",
    "    plt.figure(figsize=(12, 8))\n",
    "    nx.draw(\n",
    "        G, pos, with_labels=True, node_color=node_colors, \n",
    "        edge_color=[edge_colors.get(edge, 'lightgrey') for edge in G.edges],\n",
    "        node_size=3000, font_size=9, connectionstyle=\"arc3,rad=0.2\"\n",
    "    )\n",
    "    \n",
    "    plt.title(\"EcoGreen: Reclaiming Agricultural Self\", fontsize=18)\n",
    "    plt.show()\n",
    "\n",
    "# Run the visualization\n",
    "visualize_nn()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "<div class=\"float-right\" style=\"float:none;width:100%;margin-left:0;border:none;padding:0;background:none;\">\n",
    "  <a class=\"image-bubble layered-icon\" href=\"figures/cgbest.jpeg\" target=\"_blank\" title=\"Click to magnify\">\n",
    "    <div class=\"large-icon\"></div>\n",
    "    <div class=\"small-icon\"></div>\n",
    "  </a>\n",
    "\n",
    "```{figure} https://www.ledr.com/colours/white.jpg\n",
    "---\n",
    "width: 1\n",
    "height: 1\n",
    "name: figures/cgbest\n",
    "---\n",
    "_Dynamic Capability_. The monumental will align adversarial TNF-α, IL-6, IFN-γ with antigens from pathogens of \"ancient grudge\", a new mutiny with antiquarian roots. But it will also tokenize PD-1 & CTLA-4 with specific, emergent antigens, while also reappraising \"self\" to ensure no rogue viral and malignant elements remain unnoticéd.\n",
    "```\n",
    "\n",
    "</div>\n",
    "</div>\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Magnificent—let’s detonate the fresco further. We’ll venture now into thermodynamics, semiotics, and speculative architecture. This will be an extended theological-epistemic spelunking mission: where entropy meets syntax, where marble sings, and where every pediment carries a heat signature.\n",
    "\n",
    "---\n",
    "\n",
    "Because *The School of Athens* is not merely visual—it’s thermal. A heatmap of intellect. Entropy blooms not as disorder but as discourse. The center—Plato and Aristotle—is a hotspot of dialectical friction. From there, energy diffuses outward: each figure radiating their epistemic temperature. Heraclitus smolders alone. Pythagoras glows with geometrical fever. Diogenes cools the floor with cynicism. This isn’t a static painting. It’s a radiant heat engine of philosophical combustion.\n",
    "\n",
    "Because in thermodynamic terms, Apollo and Athena are not just structural gods—they are entropy moderators. Apollo is the ideal engine: perfectly reversible, frictionless, mythically efficient. He converts thought into beauty without loss. Athena is the condenser—cool, vigilant, preventing runaway thermal collapse. She doesn't produce energy; she stores it, redirects it, shields against overload. Together, they define the Carnot limits of reason.\n",
    "\n",
    "Because the thinkers themselves are the system’s oscillating particles. They move in intellectual Brownian motion—bouncing, arguing, speculating. But without boundary conditions—without Apollo’s harmonic frame or Athena’s shielded perimeter—this motion would dissolve into thermodynamic death. What Raphael gives us is a fresco in perpetual metastability. Energy flows, but structure holds. That’s the miracle.\n",
    "\n",
    "Now step into semiotics: *The School of Athens* is a syntax. Each thinker is a glyph, each gesture a punctuation mark. Plato is the upward diacritic—pointing toward abstract ideals, the Platonic ∧. Aristotle is the grounding clause—“but,” “and,” “thus,” the logical ∨. The foreground figures form a prepositional phrase of praxis. The background arches? Parentheses enclosing the whole proposition. Apollo and Athena are quotation marks—invoking not presence, but reference. Statues, not actors. But essential.\n",
    "\n",
    "Because their semantic weight is *iconic*, not indexical. Apollo does not say; he signifies. Athena does not act; she asserts. Her spear is not aimed—it’s emblematic. Her shield is not used—it is legible. In this semiotic economy, their silence speaks. The thinkers make meaning by movement; the gods hold meaning by form. Apollo is the archetype of clarity; Athena, the archetype of discretion. Both are required to prevent the sentence from unraveling.\n",
    "\n",
    "And then—speculative architecture. Imagine the fresco not as an art object but as a blueprint for epistemic space. What if universities were built on this model? Not with lecture halls but with signal-flow zones. Spaces calibrated for dialectic friction, others designed for contemplative cooling. Apollo wings of pure synthesis—music rooms, design labs, meditation chambers. Athena wings of controlled chaos—debate halls, mock trial courts, emergency scenario simulators. And in the center: the agora of structured uncertainty.\n",
    "\n",
    "We would stop building schools that resemble prisons. We would stop assuming knowledge must march in rows. Instead, we’d construct academies as thermosemiotic circuits: where students learn not just by input/output but by entropy management, signal discernment, symbolic agility. The fresco becomes a floor plan. The gods become load-bearing walls.\n",
    "\n",
    "Because the greatest secret of Raphael’s architecture is that it is *impossible*. The vanishing point is too perfect. The figures are too well placed. The arches support nothing. It is a utopian building—not a structure meant to stand, but one meant to signify what structure *could* mean. It is an architectural simulation. A platonic space in paint.\n",
    "\n",
    "Because what is philosophy but speculative architecture anyway? Ideas are rooms; arguments are beams; paradox is the drafty space between foundations. And every good thinker is an architect of the unseen. Plato drafts the forms. Aristotle wires the electricity. Euclid maps the measurements. And Raphael—Raphael *renders* it all.\n",
    "\n",
    "Because ultimately, the fresco *knows* it cannot be real. Apollo’s nudity is not vulnerability—it is the symbolic admission of non-functionality. Athena’s spear will never pierce; her shield will never block. But in their impossibility, they teach us possibility. They offer, not utility, but orientation. Like a compass rose carved in stone.\n",
    "\n",
    "Because in the end, signal alone is insufficient. Noise is necessary. Debate, failure, friction—all must pass through the gods. Apollo’s clarity is empty without questions. Athena’s defense is pointless without provocation. The gods are *static so the rest may move*. This is the School’s paradox. Its poetry.\n",
    "\n",
    "So we return to the w-function—  \n",
    "**w = 1 / (1 + X/Y)**  \n",
    "—and now we see:  \n",
    "Apollo is when Y → ∞  \n",
    "Athena is when X → variable  \n",
    "The thinkers are when X ≈ Y  \n",
    "And *resilience* is w held close to 1 through feedback, judgment, gear, grace.\n",
    "\n",
    "The School is not a painting. It’s a machine. A myth. A map. A *metaphor for discernment*.\n",
    "\n",
    "📐🔥🦉🎻🏛️💡—Let’s keep building.\n",
    "\n"
   ]
  }
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