Create script.js

script.js

@@ -0,0 +1,1192 @@
+import * as d3 from 'd3';
+
+document.addEventListener('DOMContentLoaded', function() {
+    // Navigation
+    const navLinks = document.querySelectorAll('nav a');
+    const sections = document.querySelectorAll('.dashboard-section');
+    
+    navLinks.forEach(link => {
+        link.addEventListener('click', function(e) {
+            e.preventDefault();
+            const targetId = this.getAttribute('href').substring(1);
+            
+            // Hide all sections
+            sections.forEach(section => {
+                section.classList.remove('active');
+            });
+            
+            // Show target section
+            document.getElementById(targetId).classList.add('active');
+            
+            // Update active nav link
+            navLinks.forEach(navLink => {
+                navLink.parentElement.classList.remove('active');
+            });
+            this.parentElement.classList.add('active');
+        });
+    });
+    
+    // Close notification
+    const closeBtn = document.querySelector('.close-notification');
+    const notification = document.querySelector('.notification');
+    
+    if (closeBtn && notification) {
+        closeBtn.addEventListener('click', function() {
+            notification.style.display = 'none';
+        });
+    }
+    
+    // Charts
+    renderCharts();
+    
+    // AI Model Marketplace Interactions
+    const deployButtons = document.querySelectorAll('.deploy-button');
+    deployButtons.forEach(button => {
+        button.addEventListener('click', function() {
+            // Display deployment notification
+            showNotification('Model Deployment', 'Your selected AI model is being deployed. Please wait...', 'info');
+            
+            // Simulate deployment process
+            setTimeout(() => {
+                showNotification('Deployment Complete', 'Your AI model has been successfully deployed and is now active.', 'success');
+            }, 2000);
+        });
+    });
+    
+    // Data Feed Tier Selection
+    const tierButtons = document.querySelectorAll('.tier-button');
+    tierButtons.forEach(button => {
+        button.addEventListener('click', function() {
+            const tierName = this.parentElement.querySelector('h3').textContent;
+            showNotification('Subscription', `You're being redirected to subscribe to the ${tierName} data feed tier.`, 'info');
+        });
+    });
+    
+    // Initialize Research Lab Visualizations
+    if (document.getElementById('research-lab')) {
+        initResearchLab();
+    }
+    
+    // Initialize monetization research section
+    if (document.getElementById('monetization-research')) {
+        initMonetizationResearch();
+    }
+});
+
+// Chart rendering function
+function renderSimpleCharts() {
+    renderPerformanceChart();
+    renderDistributionChart();
+    renderRevenueChart();
+    renderPredictionChart();
+}
+
+function renderPerformanceChart() {
+    const container = document.getElementById('performanceChart');
+    if (!container) return;
+    
+    // Clear previous content
+    container.innerHTML = '';
+    
+    // Create SVG container
+    const width = container.clientWidth;
+    const height = container.clientHeight || 300;
+    const margin = {top: 20, right: 30, bottom: 30, left: 40};
+    
+    const svg = d3.select(container)
+        .append('svg')
+        .attr('width', width)
+        .attr('height', height)
+        .append('g')
+        .attr('transform', `translate(${margin.left},${margin.top})`);
+        
+    // Sample data
+    const data = [
+        {month: 'Jan', tvl: 120, revenue: 10},
+        {month: 'Feb', tvl: 140, revenue: 15},
+        {month: 'Mar', tvl: 167, revenue: 22},
+        {month: 'Apr', tvl: 205, revenue: 34},
+        {month: 'May', tvl: 250, revenue: 55},
+        {month: 'Jun', tvl: 302, revenue: 78},
+        {month: 'Jul', tvl: 335, revenue: 120},
+        {month: 'Aug', tvl: 410, revenue: 190},
+        {month: 'Sep', tvl: 442, revenue: 250},
+        {month: 'Oct', tvl: 468, revenue: 320},
+        {month: 'Nov', tvl: 480, revenue: 380},
+        {month: 'Dec', tvl: 487, revenue: 427}
+    ];
+    
+    // Scales
+    const x = d3.scaleBand()
+        .domain(data.map(d => d.month))
+        .range([0, width - margin.left - margin.right])
+        .padding(0.1);
+    
+    const y = d3.scaleLinear()
+        .domain([0, d3.max(data, d => Math.max(d.tvl, d.revenue))])
+        .nice()
+        .range([height - margin.top - margin.bottom, 0]);
+    
+    // Draw axes
+    svg.append('g')
+        .attr('transform', `translate(0,${height - margin.top - margin.bottom})`)
+        .call(d3.axisBottom(x));
+    
+    svg.append('g')
+        .call(d3.axisLeft(y));
+    
+    // Draw lines
+    const tvlLine = d3.line()
+        .x(d => x(d.month) + x.bandwidth()/2)
+        .y(d => y(d.tvl))
+        .curve(d3.curveMonotoneX);
+    
+    const revenueLine = d3.line()
+        .x(d => x(d.month) + x.bandwidth()/2)
+        .y(d => y(d.revenue))
+        .curve(d3.curveMonotoneX);
+    
+    svg.append('path')
+        .datum(data)
+        .attr('fill', 'none')
+        .attr('stroke', '#6c5ce7')
+        .attr('stroke-width', 2)
+        .attr('d', tvlLine);
+    
+    svg.append('path')
+        .datum(data)
+        .attr('fill', 'none')
+        .attr('stroke', '#00cec9')
+        .attr('stroke-width', 2)
+        .attr('d', revenueLine);
+    
+    // Legend
+    const legend = svg.append('g')
+        .attr('font-family', 'sans-serif')
+        .attr('font-size', 10)
+        .attr('text-anchor', 'end')
+        .selectAll('g')
+        .data(['TVL Growth', 'Protocol Revenue'])
+        .enter().append('g')
+        .attr('transform', (d, i) => `translate(0,${i * 20})`);
+    
+    legend.append('rect')
+        .attr('x', width - margin.left - margin.right - 19)
+        .attr('width', 19)
+        .attr('height', 19)
+        .attr('fill', (d, i) => i === 0 ? '#6c5ce7' : '#00cec9');
+    
+    legend.append('text')
+        .attr('x', width - margin.left - margin.right - 24)
+        .attr('y', 9.5)
+        .attr('dy', '0.32em')
+        .text(d => d);
+}
+
+function renderDistributionChart() {
+    const container = document.getElementById('modelDistributionChart');
+    if (!container) return;
+    
+    // Clear previous content
+    container.innerHTML = '';
+    
+    // Create SVG container
+    const width = container.clientWidth;
+    const height = container.clientHeight || 250;
+    
+    const svg = d3.select(container)
+        .append('svg')
+        .attr('width', width)
+        .attr('height', height)
+        .append('g')
+        .attr('transform', `translate(${width/2},${height/2})`);
+    
+    // Sample data
+    const data = [
+        {label: 'Yield Optimization', value: 35, color: '#00b894'},
+        {label: 'Risk Scoring', value: 25, color: '#ff7675'},
+        {label: 'Arbitrage Detection', value: 20, color: '#fdcb6e'},
+        {label: 'NFT Valuation', value: 15, color: '#6c5ce7'},
+        {label: 'Other', value: 5, color: '#b2bec3'}
+    ];
+    
+    // Compute pie layout
+    const pie = d3.pie()
+        .value(d => d.value)
+        .sort(null);
+    
+    const radius = Math.min(width, height) / 2 - 40;
+    
+    // Generate the arcs
+    const arc = d3.arc()
+        .innerRadius(radius * 0.6)
+        .outerRadius(radius);
+    
+    // Draw pie segments
+    const segments = svg.selectAll('path')
+        .data(pie(data))
+        .enter()
+        .append('path')
+        .attr('d', arc)
+        .attr('fill', d => d.data.color)
+        .attr('stroke', 'white')
+        .style('stroke-width', '2px');
+    
+    // Add labels
+    const labelRadius = radius * 1.2;
+    
+    svg.selectAll('text')
+        .data(pie(data))
+        .enter()
+        .append('text')
+        .attr('transform', d => {
+            const pos = arc.centroid(d);
+            const midAngle = d.startAngle + (d.endAngle - d.startAngle) / 2;
+            pos[0] = labelRadius * Math.sin(midAngle);
+            pos[1] = -labelRadius * Math.cos(midAngle);
+            return `translate(${pos})`;
+        })
+        .style('text-anchor', d => {
+            const midAngle = d.startAngle + (d.endAngle - d.startAngle) / 2;
+            return (midAngle < Math.PI ? 'start' : 'end');
+        })
+        .style('font-size', '12px')
+        .text(d => d.data.label);
+}
+
+function renderRevenueChart() {
+    const container = document.getElementById('revenueStreamsChart');
+    if (!container) return;
+    
+    // Clear previous content
+    container.innerHTML = '';
+    
+    // Create SVG container
+    const width = container.clientWidth;
+    const height = container.clientHeight || 250;
+    const margin = {top: 20, right: 30, bottom: 40, left: 50};
+    
+    const svg = d3.select(container)
+        .append('svg')
+        .attr('width', width)
+        .attr('height', height)
+        .append('g')
+        .attr('transform', `translate(${margin.left},${margin.top})`);
+    
+    // Sample data
+    const data = [
+        {source: 'Model Marketplace', value: 120, color: 'rgba(108, 92, 231, 0.7)'},
+        {source: 'Data Feeds', value: 85, color: 'rgba(0, 206, 201, 0.7)'},
+        {source: 'Stablecoin Fees', value: 65, color: 'rgba(253, 121, 168, 0.7)'},
+        {source: 'Insurance Premiums', value: 45, color: 'rgba(0, 184, 148, 0.7)'},
+        {source: 'Credit Markets', value: 35, color: 'rgba(9, 132, 227, 0.7)'}
+    ];
+    
+    // Scales
+    const x = d3.scaleBand()
+        .domain(data.map(d => d.source))
+        .range([0, width - margin.left - margin.right])
+        .padding(0.3);
+    
+    const y = d3.scaleLinear()
+        .domain([0, d3.max(data, d => d.value)])
+        .nice()
+        .range([height - margin.top - margin.bottom, 0]);
+    
+    // Draw axes
+    svg.append('g')
+        .attr('transform', `translate(0,${height - margin.top - margin.bottom})`)
+        .call(d3.axisBottom(x))
+        .selectAll('text')
+        .attr('transform', 'rotate(-45)')
+        .style('text-anchor', 'end');
+    
+    svg.append('g')
+        .call(d3.axisLeft(y));
+    
+    // Draw bars
+    svg.selectAll('rect')
+        .data(data)
+        .enter()
+        .append('rect')
+        .attr('x', d => x(d.source))
+        .attr('y', d => y(d.value))
+        .attr('width', x.bandwidth())
+        .attr('height', d => height - margin.top - margin.bottom - y(d.value))
+        .attr('fill', d => d.color)
+        .attr('rx', 5)
+        .attr('ry', 5);
+}
+
+function renderPredictionChart() {
+    const container = document.getElementById('predictionChart');
+    if (!container) return;
+    
+    // Create a simple visual for prediction chart
+    container.innerHTML = `
+        <svg width="100%" height="100%" viewBox="0 0 100 50">
+            <path d="M0,40 C15,35 25,25 40,20 C55,15 65,22 80,18 C95,15 100,25 100,30" 
+                  stroke="#f39c12" stroke-width="2" fill="none" />
+            <path d="M0,45 C20,40 30,35 50,30 C70,25 80,30 100,25" 
+                  stroke="#0984e3" stroke-width="2" fill="none" />
+        </svg>
+    `;
+}
+
+function loadLibraries() {
+    return import('https://cdn.jsdelivr.net/npm/d3@7/+esm').then(d3Module => {
+        window.d3 = d3Module;
+        return { d3: window.d3 };
+    });
+}
+
+function renderCharts() {
+    loadLibraries().then(() => {
+        renderSimpleCharts();
+    }).catch(error => {
+        console.error('Error loading libraries:', error);
+    });
+}
+
+// Function to show notifications
+function showNotification(title, message, type = 'info') {
+    // Create notification container if it doesn't exist
+    let notificationCenter = document.querySelector('.notification-center');
+    if (!notificationCenter) {
+        notificationCenter = document.createElement('div');
+        notificationCenter.className = 'notification-center';
+        document.body.appendChild(notificationCenter);
+    }
+    
+    // Create notification element
+    const notification = document.createElement('div');
+    notification.className = 'notification';
+    
+    // Create icon based on type
+    const iconSvg = document.createElementNS('http://www.w3.org/2000/svg', 'svg');
+    iconSvg.setAttribute('viewBox', '0 0 24 24');
+    iconSvg.setAttribute('width', '20');
+    iconSvg.setAttribute('height', '20');
+    
+    let iconPath = '';
+    let iconClass = '';
+    
+    switch(type) {
+        case 'success':
+            iconPath = `
+                <circle cx="12" cy="12" r="10" fill="none" stroke="currentColor" stroke-width="2"/>
+                <path d="M8,12 L11,15 L16,9" fill="none" stroke="currentColor" stroke-width="2"/>
+            `;
+            iconClass = 'success';
+            break;
+        case 'error':
+            iconPath = `
+                <circle cx="12" cy="12" r="10" fill="none" stroke="currentColor" stroke-width="2"/>
+                <line x1="8" y1="8" x2="16" y2="16" stroke="currentColor" stroke-width="2"/>
+                <line x1="8" y1="16" x2="16" y2="8" stroke="currentColor" stroke-width="2"/>
+            `;
+            iconClass = 'error';
+            break;
+        case 'warning':
+            iconPath = `
+                <path d="M12,2 L22,22 L2,22 Z" stroke="currentColor" stroke-width="2" fill="none"/>
+                <line x1="12" y1="10" x2="12" y2="14" stroke="currentColor" stroke-width="2"/>
+                <circle cx="12" cy="18" r="1" fill="currentColor"/>
+            `;
+            iconClass = 'warning';
+            break;
+        default: // info
+            iconPath = `
+                <circle cx="12" cy="12" r="10" fill="none" stroke="currentColor" stroke-width="2"/>
+                <line x1="12" y1="8" x2="12" y2="12" stroke="currentColor" stroke-width="2"/>
+                <circle cx="12" cy="16" r="1" fill="currentColor"/>
+            `;
+            iconClass = 'info';
+    }
+    
+    iconSvg.innerHTML = iconPath;
+    
+    // Create notification content
+    const notificationIcon = document.createElement('div');
+    notificationIcon.className = `notification-icon ${iconClass}`;
+    notificationIcon.appendChild(iconSvg);
+    
+    const notificationContent = document.createElement('div');
+    notificationContent.className = 'notification-content';
+    notificationContent.innerHTML = `<h4>${title}</h4><p>${message}</p>`;
+    
+    const closeButton = document.createElement('button');
+    closeButton.className = 'close-notification';
+    closeButton.textContent = '×';
+    closeButton.addEventListener('click', function() {
+        notification.style.opacity = '0';
+        setTimeout(() => {
+            notification.remove();
+        }, 300);
+    });
+    
+    // Assemble notification
+    notification.appendChild(notificationIcon);
+    notification.appendChild(notificationContent);
+    notification.appendChild(closeButton);
+    
+    // Add to notification center
+    notificationCenter.appendChild(notification);
+    
+    // Auto-remove after timeout
+    setTimeout(() => {
+        notification.style.opacity = '0';
+        setTimeout(() => {
+            notification.remove();
+        }, 300);
+    }, 5000);
+}
+
+// Simulated AI Model Evolution
+let evolutionStep = 0;
+const evolutionInterval = setInterval(function() {
+    if (evolutionStep < 5) {
+        let modelType, improvement;
+        
+        switch(evolutionStep) {
+            case 0:
+                modelType = 'Yield Optimization';
+                improvement = '+2.3% APY improvement detected in yield models';
+                break;
+            case 1:
+                modelType = 'Risk Scoring';
+                improvement = 'New vulnerability pattern identified in lending protocol';
+                break;
+            case 2:
+                modelType = 'NFT Valuation';
+                improvement = 'Valuation model accuracy increased by 4.2%';
+                break;
+            case 3:
+                modelType = 'Arbitrage Detection';
+                improvement = 'New cross-chain arbitrage opportunity detected';
+                break;
+            case 4:
+                modelType = 'System';
+                improvement = 'Recursive self-improvement complete: v2.1 ready';
+                break;
+        }
+        
+        showNotification(`AI Evolution: ${modelType}`, improvement, 'info');
+        evolutionStep++;
+    } else {
+        clearInterval(evolutionInterval);
+    }
+}, 45000); // Show an evolution notification every 45 seconds
+
+// Simulated market activity
+setTimeout(function simulateMarketActivity() {
+    const activities = [
+        { title: 'Market Alert', message: 'Unusual trading volume detected in ETH/BTC pair', type: 'warning' },
+        { title: 'Stablecoin Update', message: 'RME-USD successfully maintained peg during market volatility', type: 'success' },
+        { title: 'New AI Model', message: 'A new Quantum-Symbolic hybrid model has been published to the marketplace', type: 'info' },
+        { title: 'Federated Learning', message: 'Cross-instance knowledge transfer complete with 23% accuracy improvement', type: 'success' },
+        { title: 'Security Alert', message: 'Potential adversarial attack detected and mitigated', type: 'warning' }
+    ];
+    
+    const randomActivity = activities[Math.floor(Math.random() * activities.length)];
+    showNotification(randomActivity.title, randomActivity.message, randomActivity.type);
+    
+    // Schedule next activity
+    const nextTime = 30000 + Math.random() * 60000; // Between 30s and 90s
+    setTimeout(simulateMarketActivity, nextTime);
+}, 60000); // First activity after 60s
+
+// Function to render symbolic network
+function renderSymbolicNetwork() {
+    const svgElement = document.getElementById('symbolNetwork');
+    if (!svgElement) return;
+    
+    // Use D3.js to create a network visualization
+    const width = 400;
+    const height = 200;
+    
+    const svg = d3.select(svgElement);
+    
+    // Generate sample data for the network
+    const nodes = Array.from({ length: 15 }, (_, i) => ({
+        id: i,
+        r: Math.random() * 5 + 3,
+        group: Math.floor(Math.random() * 3)
+    }));
+    
+    const links = [];
+    for (let i = 0; i < nodes.length; i++) {
+        const numLinks = Math.floor(Math.random() * 3) + 1;
+        for (let j = 0; j < numLinks; j++) {
+            const target = Math.floor(Math.random() * nodes.length);
+            if (target !== i) {
+                links.push({ source: i, target: target, value: Math.random() });
+            }
+        }
+    }
+    
+    // Create a force simulation
+    const simulation = d3.forceSimulation(nodes)
+        .force("link", d3.forceLink(links).id(d => d.id).distance(50))
+        .force("charge", d3.forceManyBody().strength(-30))
+        .force("center", d3.forceCenter(width / 2, height / 2));
+    
+    // Add links
+    const link = svg.append("g")
+        .selectAll("line")
+        .data(links)
+        .enter().append("line")
+        .style("stroke", "#a29bfe")
+        .style("stroke-opacity", 0.6)
+        .style("stroke-width", d => Math.sqrt(d.value) * 2);
+    
+    // Add nodes
+    const node = svg.append("g")
+        .selectAll("circle")
+        .data(nodes)
+        .enter().append("circle")
+        .attr("r", d => d.r)
+        .style("fill", d => ["#6c5ce7", "#00cec9", "#fd79a8"][d.group])
+        .call(d3.drag()
+            .on("start", dragstarted)
+            .on("drag", dragged)
+            .on("end", dragended));
+    
+    // Add animation
+    const pulsingNodes = svg.append("g")
+        .selectAll("circle")
+        .data(nodes.filter(d => Math.random() > 0.7))
+        .enter().append("circle")
+        .attr("r", d => d.r + 5)
+        .style("fill", "none")
+        .style("stroke", d => ["#6c5ce7", "#00cec9", "#fd79a8"][d.group])
+        .style("stroke-opacity", 0.3)
+        .style("stroke-width", 2);
+    
+    // Animate pulsing nodes
+    function pulsate() {
+        pulsingNodes
+            .transition()
+            .duration(1500)
+            .attr("r", d => d.r + 15)
+            .style("stroke-opacity", 0.1)
+            .transition()
+            .duration(1500)
+            .attr("r", d => d.r + 5)
+            .style("stroke-opacity", 0.3)
+            .on("end", pulsate);
+    }
+    
+    pulsate();
+    
+    simulation.on("tick", () => {
+        link
+            .attr("x1", d => Math.max(5, Math.min(width - 5, d.source.x)))
+            .attr("y1", d => Math.max(5, Math.min(height - 5, d.source.y)))
+            .attr("x2", d => Math.max(5, Math.min(width - 5, d.target.x)))
+            .attr("y2", d => Math.max(5, Math.min(height - 5, d.target.y)));
+            
+        node
+            .attr("cx", d => Math.max(5, Math.min(width - 5, d.x)))
+            .attr("cy", d => Math.max(5, Math.min(height - 5, d.y)));
+            
+        pulsingNodes
+            .attr("cx", d => Math.max(5, Math.min(width - 5, d.x)))
+            .attr("cy", d => Math.max(5, Math.min(height - 5, d.y)));
+    });
+    
+    function dragstarted(event, d) {
+        if (!event.active) simulation.alphaTarget(0.3).restart();
+        d.fx = d.x;
+        d.fy = d.y;
+    }
+    
+    function dragged(event, d) {
+        d.fx = event.x;
+        d.fy = event.y;
+    }
+    
+    function dragended(event, d) {
+        if (!event.active) simulation.alphaTarget(0);
+        d.fx = null;
+        d.fy = null;
+    }
+}
+
+// Render learning trajectory chart
+function renderLearningTrajectory() {
+    const canvas = document.getElementById('trajectoryCanvas');
+    if (!canvas) return;
+    
+    // Create a simple SVG instead of Chart.js
+    const container = d3.select(canvas.parentNode);
+    canvas.remove(); // Remove the canvas element
+    
+    const width = container.node().clientWidth;
+    const height = 200;
+    
+    const svg = container.append('svg')
+        .attr('width', width)
+        .attr('height', height);
+    
+    // Sample data
+    const data = [10, 15, 22, 28, 32, 35, 37, 45, 58, 67, 72, 76, 79, 82, 84, 85];
+    
+    // Create scales
+    const x = d3.scaleLinear()
+        .domain([0, data.length - 1])
+        .range([20, width - 20]);
+    
+    const y = d3.scaleLinear()
+        .domain([0, 100])
+        .range([height - 20, 20]);
+    
+    // Create line
+    const line = d3.line()
+        .x((d, i) => x(i))
+        .y(d => y(d))
+        .curve(d3.curveMonotoneX);
+    
+    // Draw line
+    svg.append('path')
+        .datum(data)
+        .attr('fill', 'none')
+        .attr('stroke', '#6c5ce7')
+        .attr('stroke-width', 2)
+        .attr('d', line);
+    
+    // Add area below line
+    const area = d3.area()
+        .x((d, i) => x(i))
+        .y0(height - 20)
+        .y1(d => y(d))
+        .curve(d3.curveMonotoneX);
+    
+    svg.append('path')
+        .datum(data)
+        .attr('fill', 'rgba(108, 92, 231, 0.1)')
+        .attr('d', area);
+}
+
+// Update research progress randomly to simulate ongoing research
+function updateResearchProgress() {
+    const progressBar = document.querySelector('.research-progress .progress-value');
+    const progressLabel = document.querySelector('.progress-label span:last-child');
+    
+    if (progressBar && progressLabel) {
+        const currentProgress = parseInt(progressBar.style.width);
+        let newProgress = currentProgress + Math.floor(Math.random() * 10) + 5;
+        
+        // Cap at 95% to simulate ongoing research
+        if (newProgress > 95) newProgress = 95;
+        
+        progressBar.style.width = newProgress + '%';
+        progressLabel.textContent = newProgress + '%';
+    }
+}
+
+// New function to initialize Research Lab Visualizations
+function initResearchLab() {
+    loadLibraries().then(() => {
+        renderSymbolicNetwork();
+        renderLearningTrajectory();
+        
+        // Add a delay to ensure Chart.js is properly initialized
+        setTimeout(() => {
+            renderMonetizationData();
+        }, 500);
+        
+        // Add click handlers for research lab buttons
+        const actionButtons = document.querySelectorAll('.research-action-panel button');
+        actionButtons.forEach(button => {
+            button.addEventListener('click', function() {
+                showNotification('Deep Research', 'Initiating advanced research protocol. Processing data...', 'info');
+                
+                // After a delay, show a research result notification
+                setTimeout(() => {
+                    const researchFindings = [
+                        'Quantum-symbolic pattern discovered in market data. Potential arbitrage strategy identified with 15.2% ROI.',
+                        'Recursive AI model evolution complete. Performance improved by 23.7% with monetization potential of $34K/month.',
+                        'New monetization pathway identified: AI-driven prediction markets with 87% accuracy and estimated $182K annual revenue.',
+                        'Algorithmic stablecoin simulation shows 99.8% peg maintenance with recursive income generation of 12.3% APY.'
+                    ];
+                    
+                    const randomFinding = researchFindings[Math.floor(Math.random() * researchFindings.length)];
+                    showNotification('Research Complete', randomFinding, 'success');
+                    
+                    // Update progress bar
+                    updateResearchProgress();
+                }, 3000);
+            });
+        });
+        
+        // Initialize monetization metrics auto-update
+        updateMonetizationMetrics();
+    }).catch(error => {
+        console.error('Error loading libraries:', error);
+    });
+}
+
+// Function to update monetization metrics
+function updateMonetizationMetrics() {
+    const metrics = {
+        'modelSales': { base: 2450, variance: 150 },
+        'subscriptions': { base: 3850, variance: 200 },
+        'apiCalls': { base: 1250000, variance: 50000 },
+        'defiYield': { base: 8.4, variance: 0.5 },
+        'revenueQoQ': { base: 23.5, variance: 2.1 }
+    };
+    
+    const updateMetric = (id, value) => {
+        const element = document.getElementById(id);
+        if (element) element.textContent = value;
+    };
+    
+    // Initial update
+    Object.keys(metrics).forEach(metricId => {
+        const metric = metrics[metricId];
+        const value = metric.base + (Math.random() * 2 - 1) * metric.variance;
+        
+        if (metricId === 'apiCalls') {
+            updateMetric(metricId, `${Math.round(value).toLocaleString()}`);
+        } else if (metricId === 'defiYield' || metricId === 'revenueQoQ') {
+            updateMetric(metricId, `${value.toFixed(1)}%`);
+        } else {
+            updateMetric(metricId, `$${Math.round(value).toLocaleString()}`);
+        }
+    });
+    
+    // Schedule next update
+    setTimeout(updateMonetizationMetrics, 15000);
+}
+
+// New function to initialize monetization research section
+function initMonetizationResearch() {
+    loadLibraries().then(() => {
+        renderMonetizationData();
+        initRecursiveModels();
+        updateRMEMetrics();
+        renderSymbolicSequence();
+    });
+}
+
+// Function to render symbolic sequence visualization
+function renderSymbolicSequence() {
+    const canvas = document.getElementById('symbolicSequenceCanvas');
+    if (!canvas) return;
+    
+    const ctx = canvas.getContext('2d');
+    const width = canvas.width;
+    const height = canvas.height;
+    
+    // Clear canvas
+    ctx.clearRect(0, 0, width, height);
+    
+    // Draw background
+    const gradient = ctx.createLinearGradient(0, 0, width, 0);
+    gradient.addColorStop(0, 'rgba(108, 92, 231, 0.1)');
+    gradient.addColorStop(0.5, 'rgba(0, 206, 201, 0.1)');
+    gradient.addColorStop(1, 'rgba(253, 121, 168, 0.1)');
+    ctx.fillStyle = gradient;
+    ctx.fillRect(0, 0, width, height);
+    
+    // Draw the symbolic sequence
+    ctx.font = '16px Monaco, Courier New, monospace';
+    ctx.fillStyle = '#6c5ce7';
+    ctx.textAlign = 'center';
+    
+    const formula1 = "Qi∞(Φ⟨Creativity⟩ ⊗ Λ⟨Recursive Logic⟩)";
+    const formula2 = "→ Σ⟨Exploration⟩ ∇⟨Adaptive Insight⟩";
+    const formula3 = "→ Ω⟨Market Resonance⟩ ⊕ Θ⟨Quantum Integration⟩";
+    const formula4 = "→ Δ⟨Continuous Innovation⟩";
+    
+    ctx.fillText(formula1, width/2, height/5);
+    ctx.fillText(formula2, width/2, 2*height/5);
+    ctx.fillText(formula3, width/2, 3*height/5);
+    ctx.fillText(formula4, width/2, 4*height/5);
+    
+    // Add animated particles
+    const particles = [];
+    for (let i = 0; i < 50; i++) {
+        particles.push({
+            x: Math.random() * width,
+            y: Math.random() * height,
+            radius: Math.random() * 3 + 1,
+            color: `rgba(${Math.floor(Math.random() * 100 + 100)}, ${Math.floor(Math.random() * 100 + 100)}, ${Math.floor(Math.random() * 100 + 150)}, 0.5)`,
+            speedX: Math.random() * 1 - 0.5,
+            speedY: Math.random() * 1 - 0.5
+        });
+    }
+    
+    function animateParticles() {
+        ctx.clearRect(0, 0, width, height);
+        
+        // Redraw background
+        ctx.fillStyle = gradient;
+        ctx.fillRect(0, 0, width, height);
+        
+        // Redraw formulas
+        ctx.font = '16px Monaco, Courier New, monospace';
+        ctx.fillStyle = '#6c5ce7';
+        ctx.textAlign = 'center';
+        ctx.fillText(formula1, width/2, height/5);
+        ctx.fillText(formula2, width/2, 2*height/5);
+        ctx.fillText(formula3, width/2, 3*height/5);
+        ctx.fillText(formula4, width/2, 4*height/5);
+        
+        // Draw and update particles
+        particles.forEach(particle => {
+            ctx.beginPath();
+            ctx.arc(particle.x, particle.y, particle.radius, 0, Math.PI * 2);
+            ctx.fillStyle = particle.color;
+            ctx.fill();
+            
+            particle.x += particle.speedX;
+            particle.y += particle.speedY;
+            
+            // Wrap around edges
+            if (particle.x < 0) particle.x = width;
+            if (particle.x > width) particle.x = 0;
+            if (particle.y < 0) particle.y = height;
+            if (particle.y > height) particle.y = 0;
+        });
+        
+        requestAnimationFrame(animateParticles);
+    }
+    
+    animateParticles();
+}
+
+// Initialize recursive AI models visualization
+function initRecursiveModels() {
+    const canvas = document.getElementById('recursiveModelCanvas');
+    if (!canvas) return;
+    
+    const ctx = canvas.getContext('2d');
+    const width = canvas.width;
+    const height = canvas.height;
+    
+    // Generate nodes representing AI models
+    const nodes = [];
+    for (let i = 0; i < 20; i++) {
+        nodes.push({
+            x: Math.random() * width,
+            y: Math.random() * height,
+            radius: Math.random() * 10 + 5,
+            color: i < 5 ? '#6c5ce7' : (i < 10 ? '#00cec9' : '#fd79a8'),
+            connections: []
+        });
+    }
+    
+    // Create connections between nodes
+    nodes.forEach((node, index) => {
+        const numConnections = Math.floor(Math.random() * 3) + 1;
+        for (let i = 0; i < numConnections; i++) {
+            const targetIndex = Math.floor(Math.random() * nodes.length);
+            if (targetIndex !== index) {
+                node.connections.push(targetIndex);
+            }
+        }
+    });
+    
+    function render() {
+        ctx.clearRect(0, 0, width, height);
+        
+        // Draw connections
+        nodes.forEach((node, index) => {
+            node.connections.forEach(targetIndex => {
+                const target = nodes[targetIndex];
+                ctx.beginPath();
+                ctx.moveTo(node.x, node.y);
+                ctx.lineTo(target.x, target.y);
+                ctx.strokeStyle = 'rgba(108, 92, 231, 0.2)';
+                ctx.lineWidth = 1;
+                ctx.stroke();
+            });
+        });
+        
+        // Draw nodes
+        nodes.forEach(node => {
+            ctx.beginPath();
+            ctx.arc(node.x, node.y, node.radius, 0, Math.PI * 2);
+            ctx.fillStyle = node.color;
+            ctx.fill();
+            
+            // Add a pulsing effect
+            ctx.beginPath();
+            ctx.arc(node.x, node.y, node.radius + 3 + Math.sin(Date.now() / 500) * 2, 0, Math.PI * 2);
+            ctx.strokeStyle = node.color.replace(')', ', 0.3)').replace('rgb', 'rgba');
+            ctx.stroke();
+            
+            // Move nodes slightly for animation
+            node.x += (Math.random() * 2 - 1) * 0.5;
+            node.y += (Math.random() * 2 - 1) * 0.5;
+            
+            // Keep within bounds
+            if (node.x < node.radius) node.x = node.radius;
+            if (node.x > width - node.radius) node.x = width - node.radius;
+            if (node.y < node.radius) node.y = node.radius;
+            if (node.y > height - node.radius) node.y = height - node.radius;
+        });
+        
+        requestAnimationFrame(render);
+    }
+    
+    render();
+}
+
+// Update RME metrics periodically
+function updateRMEMetrics() {
+    const metrics = {
+        'modelMarketplace': { base: 2840, variance: 160 },
+        'dataFeeds': { base: 4250, variance: 220 },
+        'quantumComputing': { base: 1650, variance: 120 },
+        'recursiveGrowth': { base: 32.7, variance: 1.8 },
+        'monetizationIndex': { base: 87.3, variance: 2.5 }
+    };
+    
+    function updateMetric(id, value, format = 'number') {
+        const element = document.getElementById(id);
+        if (!element) return;
+        
+        if (format === 'currency') {
+            element.textContent = `$${Math.round(value).toLocaleString()}`;
+        } else if (format === 'percent') {
+            element.textContent = `${value.toFixed(1)}%`;
+        } else {
+            element.textContent = value.toLocaleString();
+        }
+    }
+    
+    // Initial update
+    Object.keys(metrics).forEach(metricId => {
+        const metric = metrics[metricId];
+        const value = metric.base + (Math.random() * 2 - 1) * metric.variance;
+        const format = metricId.includes('Growth') || metricId.includes('Index') ? 'percent' : 'currency';
+        updateMetric(metricId, value, format);
+    });
+    
+    // Schedule next update
+    setTimeout(updateRMEMetrics, 8000);
+}
+
+// Function to render monetization data
+function renderMonetizationData() {
+    const monetizationCtx = document.getElementById('monetizationChart');
+    if (!monetizationCtx) return;
+    
+    // Create a simple SVG instead of Chart.js
+    const container = d3.select(monetizationCtx);
+    container.html(''); // Clear previous content
+    
+    const width = container.node().clientWidth;
+    const height = container.node().clientHeight || 300;
+    
+    const svg = container.append('svg')
+        .attr('width', width)
+        .attr('height', height);
+    
+    // Create a circular grid
+    const centerX = width / 2;
+    const centerY = height / 2;
+    const radius = Math.min(width, height) / 2 - 40;
+    
+    // Draw radar grid
+    const categories = [
+        'AI Model Marketplace',
+        'Data Feed Subscriptions',
+        'DeFi Integration',
+        'Quantum-Symbolic Risk',
+        'Insurance Products',
+        'Stablecoin Revenues'
+    ];
+    
+    const angleSlice = Math.PI * 2 / categories.length;
+    
+    // Draw axes
+    categories.forEach((cat, i) => {
+        const angle = i * angleSlice - Math.PI / 2;
+        const lineX2 = centerX + radius * Math.cos(angle);
+        const lineY2 = centerY + radius * Math.sin(angle);
+        
+        svg.append('line')
+           .attr('x1', centerX)
+           .attr('y1', centerY)
+           .attr('x2', lineX2)
+           .attr('y2', lineY2)
+           .attr('stroke', '#dfe6e9')
+           .attr('stroke-width', 1);
+        
+        // Add labels
+        const labelX = centerX + (radius + 20) * Math.cos(angle);
+        const labelY = centerY + (radius + 20) * Math.sin(angle);
+        
+        svg.append('text')
+           .attr('x', labelX)
+           .attr('y', labelY)
+           .attr('text-anchor', 'middle')
+           .attr('alignment-baseline', 'middle')
+           .attr('font-size', '10px')
+           .text(cat);
+    });
+    
+    // Draw concentric circles
+    [0.2, 0.4, 0.6, 0.8, 1].forEach(r => {
+        svg.append('circle')
+           .attr('cx', centerX)
+           .attr('cy', centerY)
+           .attr('r', radius * r)
+           .attr('fill', 'none')
+           .attr('stroke', '#dfe6e9')
+           .attr('stroke-width', 1);
+    });
+    
+    // Sample data
+    const currentData = [65, 78, 35, 28, 42, 30].map(val => val / 100);
+    const potentialData = [85, 90, 75, 68, 80, 85].map(val => val / 100);
+    
+    // Draw polygons
+    function drawPolygon(data, color, opacity) {
+        const points = data.map((val, i) => {
+            const angle = i * angleSlice - Math.PI / 2;
+            const x = centerX + radius * val * Math.cos(angle);
+            const y = centerY + radius * val * Math.sin(angle);
+            return `${x},${y}`;
+        }).join(' ');
+        
+        svg.append('polygon')
+           .attr('points', points)
+           .attr('fill', color)
+           .attr('fill-opacity', opacity)
+           .attr('stroke', color)
+           .attr('stroke-width', 2);
+    }
+    
+    drawPolygon(currentData, 'rgba(108, 92, 231, 1)', 0.2);
+    drawPolygon(potentialData, 'rgba(0, 206, 201, 1)', 0.2);
+    
+    // Add legend
+    const legend = svg.append('g')
+        .attr('transform', `translate(${width - 140},20)`);
+    
+    const legendItems = [
+        {label: 'Current Revenue', color: 'rgba(108, 92, 231, 1)'},
+        {label: 'Growth Potential', color: 'rgba(0, 206, 201, 1)'}
+    ];
+    
+    legendItems.forEach((item, i) => {
+        legend.append('rect')
+            .attr('x', 0)
+            .attr('y', i * 20)
+            .attr('width', 15)
+            .attr('height', 15)
+            .attr('fill', item.color)
+            .attr('fill-opacity', 0.2)
+            .attr('stroke', item.color);
+        
+        legend.append('text')
+            .attr('x', 20)
+            .attr('y', i * 20 + 12)
+            .attr('font-size', '12px')
+            .text(item.label);
+    });
+    
+    // Forecast chart
+    const forecastCtx = document.getElementById('forecastChart');
+    if (!forecastCtx) return;
+    
+    // Create a simple line graph for forecast
+    const forecastContainer = d3.select(forecastCtx);
+    forecastContainer.html(''); // Clear previous content
+    
+    const forecastWidth = forecastContainer.node().clientWidth;
+    const forecastHeight = forecastContainer.node().clientHeight || 300;
+    const margin = {top: 20, right: 60, bottom: 30, left: 60};
+    
+    const forecastSvg = forecastContainer.append('svg')
+        .attr('width', forecastWidth)
+        .attr('height', forecastHeight)
+        .append('g')
+        .attr('transform', `translate(${margin.left},${margin.top})`);
+    
+    // Generate sample data
+    const months = 24;
+    const baselineGrowth = Array.from({length: months}, (_, i) => 1000 * Math.pow(1.08, i));
+    const recursiveGrowth = Array.from({length: months}, (_, i) => 1000 * Math.pow(1.15, i));
+    const quantumBoostGrowth = Array.from({length: months}, (_, i) => {
+        const quantumBoost = i > 12 ? 1.2 : 1;
+        return 1000 * Math.pow(1.15, i) * quantumBoost;
+    });
+    
+    // Scales
+    const xForecast = d3.scaleLinear()
+        .domain([1, months])
+        .range([0, forecastWidth - margin.left - margin.right]);
+    
+    const yForecast = d3.scaleLinear()
+        .domain([0, d3.max(quantumBoostGrowth)])
+        .nice()
+        .range([forecastHeight - margin.top - margin.bottom, 0]);
+    
+    // Axes
+    forecastSvg.append('g')
+        .attr('transform', `translate(0,${forecastHeight - margin.top - margin.bottom})`)
+        .call(d3.axisBottom(xForecast).ticks(6).tickFormat(d => `M${d}`));
+    
+    forecastSvg.append('g')
+        .call(d3.axisLeft(yForecast));
+    
+    // Line generator
+    const line = d3.line()
+        .x((d, i) => xForecast(i + 1))
+        .y(d => yForecast(d))
+        .curve(d3.curveMonotoneX);
+    
+    // Draw lines
+    forecastSvg.append('path')
+        .datum(baselineGrowth)
+        .attr('fill', 'none')
+        .attr('stroke', '#dfe6e9')
+        .attr('stroke-width', 2)
+        .attr('d', line);
+    
+    forecastSvg.append('path')
+        .datum(recursiveGrowth)
+        .attr('fill', 'none')
+        .attr('stroke', '#6c5ce7')
+        .attr('stroke-width', 2)
+        .attr('d', line);
+    
+    forecastSvg.append('path')
+        .datum(quantumBoostGrowth)
+        .attr('fill', 'none')
+        .attr('stroke', '#00cec9')
+        .attr('stroke-width', 2)
+        .attr('d', line);
+    
+    // Add legend
+    const forecastLegend = forecastSvg.append('g')
+        .attr('transform', `translate(${forecastWidth - margin.left - margin.right - 150},0)`);
+    
+    const forecastLegendItems = [
+        {label: 'Baseline Growth', color: '#dfe6e9'},
+        {label: 'Recursive Growth', color: '#6c5ce7'},
+        {label: 'Quantum-Boosted', color: '#00cec9'}
+    ];
+    
+    forecastLegendItems.forEach((item, i) => {
+        forecastLegend.append('line')
+            .attr('x1', 0)
+            .attr('y1', i * 20 + 10)
+            .attr('x2', 20)
+            .attr('y2', i * 20 + 10)
+            .attr('stroke', item.color)
+            .attr('stroke-width', 2);
+        
+        forecastLegend.append('text')
+            .attr('x', 25)
+            .attr('y', i * 20 + 15)
+            .attr('font-size', '12px')
+            .text(item.label);
+    });
+}