Coding

Create a simple MQL5 Expert Advisor (EA) for automated forex trading based on the advanced forex scalping bot strategy framework described below. The EA should implement the core strategy architecture featuring multi-timeframe analysis (M1, M5, M15), incorporate key indicators (EMA 8, 21, 50; RSI(14); MACD(12,26,9); Bollinger Bands (20,2); plus secondary indicators like Stochastic and ATR), and identify dynamic support/resistance lines via an automated line marking system as specified. Implement entry rules for long and short trades using the confluence scoring method (minimum 4 out of 6 conditions), including bias from EMA21 on M5, RSI levels, MACD histogram direction, candlestick pattern recognition at significant S/R levels with volume confirmation, and pullbacks to EMA or support/resistance. Include exit strategy with partial profit targets based on ATR multiples and support/resistance levels, adaptive stop loss (initial ATR-based, break-even after target 1 hit, trailing with EMA 8), and time-based exits (max 30 min duration, close before major news). Apply risk management rules for position sizing based on 1% account risk adjusted by ATR volatility and signal strength multiplier, daily loss limits, and consecutive loss tracking with position size reduction. Incorporate market session optimizations to trade mainly during London and New York sessions, avoid trading around major news, and reduce size during low-volatility periods. The EA should include the following main components: 1. Multi-timeframe analysis gathering data from M1, M5, M15 charts. 2. Automated detection and scoring of dynamic support/resistance lines based on touch count, reaction strength, recency, and volume criteria. 3. Calculation and interpretation of EMA, RSI, MACD, Bollinger Bands, Stochastic, ATR indicators. 4. Candlestick pattern recognition for Doji, Hammer, Shooting Star, Engulfing, Pin Bars, and Inside Bars at key levels. 5. Entry signal generation using the confluence scoring system, including volume evaluation. 6. Position sizing calculation per strategy. 7. Trade management with partial profit taking, adaptive stops, and time-based exits. 8. Session-based trade filtering and news event avoidance. Keep the code clear and modular for ease of future enhancements, and include comments explaining key blocks referencing the provided strategy framework. # Steps - Initialize indicators on required timeframes and prepare necessary buffers. - Implement functions to detect and score support/resistance levels from recent price data. - Write routines for multi-indicator analysis and candlestick pattern detection on M1 bars. - Develop confluence scoring logic for entries and enforce minimum threshold. - Compute position size dynamically using ATR volatility and account risk. - Manage open trades with multiple partial profit targets and trailing stop logic. - Integrate session and news filtering logic to pause trading accordingly. # Output Format Provide the full MQL5 EA source code as a single `.mq5` file content with proper formatting, indentation, and comprehensive in-line comments reflecting the strategy details. # Notes - The implementation should prioritize correctness and clarity over exhaustive optimization. - Assume access to standard MQL5 functions for indicator calculation and trading operations. - All parameters like ATR periods, risk percentages, etc., should be configurable inputs. - Include safeguards against trading during unexpected market conditions or invalid data.

Create a complete, advanced-level, fully functional, production-grade ASP.NET Core project demonstrating Google Sheets integration. This project must cover all essential operations with Google Sheets APIs including: - Creating a new Google Sheet - Inserting data into the newly created sheet - Reading data from the sheet - Updating existing sheet data - Deleting specific sheet data - Deleting the entire sheet Provide detailed, step-by-step procedures for setting up the project, including: - Configuring Google Cloud Console for API access and credentials creation - Enabling necessary APIs - Installing and configuring all required NuGet packages and dependencies - Setting up authentication and authorization mechanisms securely For every part of the code, include clear, thorough explanations covering: - What each section or function does - How it integrates within the ASP.NET Core application - The role and purpose of each used library or NuGet package (e.g., Google.Apis.Sheets.v4, Google.Apis.Auth) - Any configuration settings and their implications Ensure the code is: - Well-structured and easy to understand - Testable and free of errors - Suitable for a production environment with best practices Output the instructions and code snippets in a clear, organized manner, using markdown formatting for readability. # Steps 1. Google Cloud Console setup with detailed instructions and screenshots (described textually). 2. Installing and configuring Google Sheets API client libraries in ASP.NET Core. 3. Authentication setup using OAuth 2.0 or service account credentials. 4. Implementing each functionality (create, read, update, delete sheet and rows) with comprehensive code examples. 5. Explanation of running and testing each feature. # Output Format Deliver the response as a comprehensive tutorial document in markdown format, including: - Sectioned headers - Code blocks for all code examples - Clear step-by-step procedural descriptions - Explanations after each code snippet # Notes - Emphasize security best practices for storing credentials. - Highlight nuances and common pitfalls. - Mention library versions and compatibility with ASP.NET Core versions. # Examples Include well-documented example methods for operations like CreateSheetAsync(), InsertDataAsync(), ReadDataAsync(), UpdateDataAsync(), DeleteDataAsync(), and DeleteSheetAsync(). Use placeholders for credentials but explain exactly where and how to set these up. # Response Formats {"prompt":"[the above detailed system prompt]","name":"Advanced Google Sheets ASP.NET","short_description":"Complete production-ready ASP.NET Core demo integrating Google Sheets with full CRUD operations.","icon":"CodeBracketIcon","category":"programming","tags":["Google Sheets","ASP.NET Core","API Integration","CRUD"],"should_index":true}

Create a comprehensive and robust MQL5 Expert Advisor (EA) source code file (.mq5) that implements an advanced Forex trading bot for MetaTrader 5, integrating multiple technical indicators, adaptive risk management, time-based trading restrictions, and news event avoidance as specified below. --- ### Core Functional Requirements: - Incorporate market sensing using the following technical indicators: - Exponential Moving Average (EMA) - Relative Strength Index (RSI) - Moving Average Convergence Divergence (MACD) histogram - Stochastic Oscillator (%K and %D) - Volume analysis - Implement adaptive trade execution based on combined indicator signals, enabling automated buy and sell order placements. - Calculate dynamic lot sizing as exactly 1% of the current account balance. - Restrict trade executions only to customizable New York session hours defined by global variables `START_HOUR` and `END_HOUR`. - Detect scheduled news events impacting the traded symbol via suitable MQL5 News APIs or SymbolInfo functions, and avoid opening new trades during such events within session hours. - Implement adaptive Take Profit (TP) and Stop Loss (SL) levels that are scaled appropriately, ensuring suitability even for minimum account balances down to $20. - Support automatic reversal detection by identifying divergences and indicator signals, closing existing positions accordingly, and then opening trades in the opposite direction. --- ### Global Variables (declare globally at the top of the source file): - `EMA_PERIOD` (int, e.g., 20) - `RSI_PERIOD` (int, e.g., 14) - `OVERBOUGHT_THRESHOLD` (float/int, upper bound for RSI/Stochastic, e.g., 70 or 80) - `OVERSOLD_THRESHOLD` (float/int, lower bound for RSI/Stochastic, e.g., 30 or 20) - `START_HOUR` (int, New York session start hour in broker/server time) - `END_HOUR` (int, New York session end hour) - `MIN_ACCOUNT_BALANCE` (float, minimum balance for trading, e.g., 20.0) All global variables should be well documented in the code with explanations. --- ### EA Lifecycle Function Specifications: 1. **OnInit()** - Validate all input/global parameters for correct ranges and reasonable values. - Initialize and attach EMA, RSI, MACD, and Stochastic Oscillator indicators. - Calculate the initial lot size based on 1% of the current account balance. 2. **OnDeinit()** - Properly release and detach all indicators and any allocated resources. 3. **News Detection Module** - Implement a function or module that retrieves upcoming or ongoing scheduled news events for the current symbol. - The EA must avoid placing new trades if news events affect the symbol during the trading window. 4. **OnTick() or Custom Function for Bar/Tick Calculations** - On every tick or new bar, recalculate indicator values: EMA, RSI, MACD histogram, Stochastic %K and %D, and volume status. - Ensure the current local broker time is within `START_HOUR` and `END_HOUR` and no news event is active. - Generate clear and combined trade signals: - **Buy Signal:** Price above EMA, RSI below oversold threshold; confirm bullish divergences on MACD and RSI, stochastic %K crossing above %D in oversold zone, and upward volume momentum. - **Sell Signal:** Price below EMA, RSI above overbought threshold; confirm bearish divergences on MACD and RSI, stochastic %K crossing below %D in overbought zone, and downward volume momentum. - Dynamically calculate lot size as 1% of account balance. - Open new trades according to signals; set dynamic TP and SL. - Detect market reversals and divergences; if detected, close current positions and open reversed trades. - Modify or close orders prudently based on updated signals. 5. **Order Management Utilities:** - Implement robust wrappers over `OrderSend()` for opening/modifying orders with correct SL and TP. - Implement safe order closing functions handling errors gracefully. --- ### Additional Implementation Details and Best Practices: - Include comprehensive inline code comments explaining logic, inputs, parameters, calculations, and rationale. - Provide recommendations within code comments for optimizing key indicator parameters (EMA, RSI periods, thresholds). - Ensure EA supports MetaTrader 5 backtesting, restricting test data to New York session or user-defined times. - Validate all parameters at runtime, handling errors with clear messages. - Enable smooth operation on demo accounts for live testing. - Adhere strictly to MQL5 standards, modular code organization, and best practice principles. --- # Output Format - A single, complete MQL5 Expert Advisor source code file (.mq5), modular, readable, and well-commented. - Code sections should be clearly separated: global variables, initialization, indicator calculations, signal generation, order execution, news detection, reversal handling, order management, and cleanup. - Include documentation at the top of the file describing all inputs and global variables. --- # Examples - On a new tick/bar, the EA computes EMA(20), RSI(14), MACD histogram, stochastic %K and %D, and volume. - If price > EMA(20), RSI < 30 oversold level, bullish divergences are present on MACD and RSI, stochastic %K crosses above %D in oversold region, and volume indicates strength, then during New York session hours the EA places a buy order sized at 1% of the current balance. - If reversal signals appear (bearish divergences etc.), the EA closes the buy trade and opens a sell trade with adaptive SL and TP. --- Deliver the final solution as a ready-to-deploy expert-level MQL5 EA source code implementing all specified features and constraints comprehensively and cleanly.

Create advanced HTML and CSS code for a website with specific structural requirements. Consider modern web development practices to ensure code quality, responsiveness, and accessibility. # Steps 1. **Understand Requirements**: Determine the structural and design elements that should be included (e.g., header, footer, navigation, main content areas). 2. **Research Best Practices**: Review current trends in HTML5 and CSS3 to ensure the website is modern and efficient. 3. **Code the HTML Layout**: Organize the content logically using semantic elements like `<header>`, `<nav>`, `<main>`, `<article>`, and `<footer>`. 4. **Style Using CSS**: Use advanced CSS techniques such as Flexbox or Grid for layout, and ensure styles are responsive using media queries. 5. **Ensure Accessibility**: Include ARIA roles and attributes to improve accessibility. 6. **Test Across Devices**: Make sure the site is responsive and displays correctly on various devices and browsers. # Output Format - Provide the HTML code, followed by the CSS code. - Include comments explaining any complex sections. # Examples **HTML Example:** ```html <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>Advanced Website</title> <link rel="stylesheet" href="styles.css"> </head> <body> <header> <h1>Website Title</h1> <nav> <ul> <li><a href="#">Home</a></li> <li><a href="#">About</a></li> <li><a href="#">Contact</a></li> </ul> </nav> </header> <main> <section> <h2>Main Content</h2> <p>This is the main content area.</p> </section> </main> <footer> <p>© 2023 Your Name. All rights reserved.</p> </footer> </body> </html> ``` **CSS Example:** ```css body { font-family: Arial, sans-serif; line-height: 1.6; margin: 0; padding: 0; } header, footer { background-color: #f8f9fa; padding: 1rem; text-align: center; } nav ul { list-style: none; padding: 0; } nav ul li { display: inline; margin-right: 10px; } main { margin: 2rem; } @media (max-width: 600px) { nav ul li { display: block; margin: 0; } } ``` # Notes - Emphasize responsive design and cross-browser compatibility. - Keep the code organized and well-commented for ease of understanding and maintenance. - Use a cohesive color scheme and typography that enhances readability and aesthetics.

Create a comprehensive MQL5 Expert Advisor (EA) script for MetaTrader 5 that implements an advanced Forex trading bot integrating multiple technical indicators, adaptive risk management, and time-based trading restrictions as specified below. --- ### Core Requirements: - Implement market sensing using EMA (Exponential Moving Average), RSI (Relative Strength Index), MACD (Moving Average Convergence Divergence), Stochastic Oscillator, and volume analysis. - Perform adaptive trade execution with automated buy and sell order placement based on combined indicator signals. - Calculate dynamic lot sizing as 1% of the current account balance. - Restrict all trade executions strictly within customizable New York session hours (`START_HOUR` to `END_HOUR`). - Detect and avoid trading during scheduled news events affecting the symbol using SymbolInfo() or MQL5 news APIs. - Implement adaptive Take Profit (TP) and Stop Loss (SL) levels appropriate even for minimum account balances as low as $20. - Support automatic reversal handling by detecting market reversals through divergences and indicator signals, closing existing positions on reversal, then opening reversed trades accordingly. --- ### Global Variables (declare globally, e.g., in `StrategyTester.mqh`): - `EMA_PERIOD` (integer, e.g., 20) - `RSI_PERIOD` (integer, e.g., 14) - `OVERBOUGHT_THRESHOLD` (integer/float, e.g., RSI/Stochastic upper bound) - `OVERSOLD_THRESHOLD` (integer/float, e.g., RSI/Stochastic lower bound) - `START_HOUR` (integer, New York session start hour in broker time or specified timezone) - `END_HOUR` (integer, New York session end hour) - `MIN_ACCOUNT_BALANCE` (float, minimum balance to enable trading, e.g., 20.0) --- ### EA Lifecycle Functions Requirements: 1. **`OnInit()`** - Validate all input parameters ensuring they are in acceptable ranges. - Initialize and attach all required indicators: EMA, RSI, MACD, Stochastic Oscillator. - Calculate initial adaptive lot size as 1% of the current account balance. 2. **`OnDeinit()`** - Clean up and detach the indicators properly. - Free any allocated resources to prevent memory leaks. 3. **News Detection Module** - Implement or integrate a news detection method that retrieves scheduled news events affecting the trading symbol. - Ensure the EA does not open new trades during detected news events within session hours. 4. **`OnTick()` or Custom `Calculate()` Function** - On each tick or new bar, compute current values for EMA, RSI, MACD histogram, Stochastic %K and %D, and analyze volume. - Verify current time is within `START_HOUR` and `END_HOUR` and that no news event is currently active. - Generate trade signals based on combined indicator criteria: - **Buy Signal:** When price > EMA and RSI < oversold threshold, combined with bullish divergences on MACD and RSI, Stochastic %K crossing above %D in oversold zone, and volume supporting upward momentum. - **Sell Signal:** When price < EMA and RSI > overbought threshold, combined with bearish divergences on MACD and RSI, Stochastic %K crossing below %D in overbought zone, and volume confirming downward momentum. - Execute trading operations: - Open new orders with lot size calculated as 1% of account balance. - Set SL and TP levels dynamically, mindful of the minimum account balance. - Modify or close existing orders as needed. - Detect market reversals via divergence and indicator signals: - If detected, close existing trades and open new trades in the opposite direction. 5. **Order Management Functions:** - Implement robust wrappers for `OrderSend()` that handle order opening/modification with proper SL and TP. - Implement safe order closing functionality (akin to `OrderDelete()` by ticket), handling potential errors consistently. --- ### Additional Requirements: - Include comprehensive inline code comments articulating logic, parameters, and any mathematical or trading rationale. - Provide guidance on optimizing key parameters such as EMA and RSI periods, and threshold values. - Ensure compatibility with backtesting features within MetaTrader 5, restricting testing data to New York session hours or user-defined session. - Support demo account operation for live validation. - Apply robust error handling and parameter validation throughout the EA. - Adhere strictly to MQL5 programming standards and best practices. --- # Output Format - Deliver a complete, well-structured, and well-commented MQL5 EA source code file (.mq5). - Organize code modularly, separating: initialization, indicator calculations, signal generation, order execution, news detection, reversal handling, and cleanup. - Document all global variables and input parameters at the top of the source file. --- # Examples - Upon a new price bar or tick, the EA calculates EMA(20), RSI(14), MACD histogram, Stochastic %K and %D, and reads volume. - If price > EMA(20), RSI < 30, bullish divergences on MACD and RSI accompany stochastic %K crossing above %D in the oversold region, and volume confirms bullish sentiment during New York session hours (e.g., 14:30 to 21:00 EST), the EA opens a buy trade with lot size = 1% of account balance. - On reversal or bearish divergences, EA will close buy trades and open corresponding sell trades. - All trades include SL and TP dynamically set to fit minimum balances (from $20) suitably. --- Ensure the final product is a robust, expert-level Forex trading EA for MetaTrader 5 fulfilling all above specifications and ready for immediate deployment and backtesting.

Generate a comprehensive, modernized, and professional HTML code based on the provided initial code snippet. Your output should be a fully functional HTML document that incorporates all specified elements, enhancements, and functionalities implied by the original code, while ensuring best practices in structure, semantics, accessibility, and responsiveness. - Analyze the provided code thoroughly to understand its current structure and purpose. - Upgrade the code to use modern HTML5 elements and semantics. - Apply professional formatting and indentation for readability. - Ensure the code includes all required features as per the original snippet. - Integrate necessary meta tags for responsiveness and compatibility. - Add accessible features like ARIA attributes where appropriate. - Include styling references or inline styles if specified or implicitly needed. - Test that the generated code is fully functional when rendered in a web browser. # Output Format - Provide the complete HTML code enclosed within appropriate tags. - Begin with a DOCTYPE declaration. - The document should start with <html> and end with </html>. - Include <head> and <body> sections with relevant content. - Use proper indentation and line breaks for readability. # Notes - Do not omit any specified functionalities or features from the original snippet. - Focus on clarity, professionalism, and modern best practices in HTML coding. - If JavaScript or CSS is implied or needed for full functionality, integrate them within the HTML or link them appropriately. This prompt assumes you have access to the initial code snippet as input; your task is to output the advanced, fully functioning HTML code accordingly.

Create an advanced Forex trading robot using Python that is configured via an XML file. The robot must support multiple trading strategies (SMA crossover, RSI, Bollinger Bands), implement robust risk management including position sizing based on risk per trade, enforce a maximum daily trade limit, consider trading hours, perform trade logging, and handle basic error situations. Use the provided XML configuration structure as the input parameters source. The robot must connect to MetaTrader5 to fetch historical data, calculate indicators (SMA, RSI, Bollinger Bands), generate trading signals combining the multiple strategies with weighted decisions, and execute trades accordingly. It should also implement trailing stop management for open positions, ensure all logging is done properly to a file, and handle exceptions gracefully. Follow these steps: 1. Parse the XML configuration file, converting values to appropriate types (int, float, bool, string). 2. Initialize connection to MetaTrader 5; raise errors if initialization fails. 3. Fetch historical price data per the symbol and timeframe specified. 4. Calculate SMA (fast and slow), RSI, and Bollinger Bands indicators. 5. Generate buy/sell signals for each indicator and combine them into a composite decision. 6. Check current time against allowed trading hours. 7. Enforce daily trade limits. 8. Calculate position size based on account balance, risk per trade, and stop loss in pips. 9. Execute trades by sending orders to MetaTrader 5 with correct stop loss and take profit levels. 10. Implement trailing stop adjustments for open positions as configured. 11. Log all important events including errors, trade executions, and key decision points. Output must be a well-structured, complete Python program incorporating the above features, using MetaTrader5, pandas, numpy, xml.etree.ElementTree, and logging modules. Make sure the code is readable, modular, and includes comments for clarity. Handle edge cases such as failure to fetch data, account info, or symbol info by logging errors and avoiding crashes. Format the Python code within markdown fenced code blocks for readability. Do not omit any part of the configuration or functionality described. # Output Format Provide the entire Python source code implementing the advanced Forex trading robot as described. Use clear docstrings and comments to explain each component. The code should be immediately usable given the appropriate environment and config.xml file as shown. # Notes - Assume standard pip installation availability for MetaTrader5, pandas, numpy. - The robot operates continuously or per invocation to check and execute trades. - Use the provided XML structure exactly for all configuration parameters. # Examples No example input/output is required as the full code is the output.

Create a complete MQL5 Expert Advisor (.mq5) script implementing an advanced forex HYBRID scalping strategy that supports both automatic and manual (M0) entries management with adaptive features. This EA must adhere to the following detailed requirements: - Utilize multi-timeframe analysis on M1, M5, and M15 charts. - Incorporate the core technical indicators: EMA with periods 8, 21, 50; RSI with period 14; MACD with parameters (12,26,9); Bollinger Bands (period 20, deviation 2). - Use secondary indicators: Stochastic oscillator and Average True Range (ATR). - Dynamically detect and score support and resistance (S/R) lines based on touch count, reaction strength, recency, and volume. - Identify key candlestick reversal patterns near significant S/R lines, including Doji, Hammer, Shooting Star, Engulfing, Pin Bars, and Inside Bars. - Establish an entry confluence system requiring at least 4 out of these 6 conditions: * EMA21 bias on M5 timeframe indicating trend direction. * RSI values surpassing defined thresholds for overbought/oversold. * MACD histogram direction confirming momentum. * Valid candlestick pattern near S/R with volume confirmation. * Pullback towards EMA or a significant S/R level. - Limit trade frequency by market session: * Maximum 4 active trades during London/New York sessions. * Maximum 2 active trades during Asian session. * Fixed lot size of 0.02 per entry. - Tune Asian session trade entries to prioritize safety, entering fewer but high-probability trades. - Implement a multi-layer exit strategy: * Strict “No RED” rule—avoid closing trades at a loss unless triggered by exit rules. * Apply a 250-point dynamic group hedge to manage price reversals. * Support group closing where trades (original entry plus hedges) share the first entry’s ticket number. * Use adaptive stop loss starting from ATR-based distance, moving to break-even plus 40 pips after reaching the first profit target (accounting for spreads and fees). * Deploy a dynamic step sniper trailing stop moving 80 pips behind price. * Trailing stops based on EMA8. * Begin closing trades 30 minutes prior to major news events. - Enforce risk management: * Position sizing based on 1% account risk dynamically adjusted by ATR and signal strength. * Daily loss limits enforced. * Avoid trading during major news periods (placeholder for news API integration). - Write modular, well-structured, and readable code with comprehensive inline comments explaining all logic, especially adaptive and risk management parts. - Provide comprehensive configurable input parameters covering all key settings. - Use only standard MQL5 indicators and trading functions. - Implement robust error handling and graceful fallback for unexpected market conditions. - Include placeholders for external APIs (news events, volume sources). - Log all closed trades (single or grouped) in the journal tab with total profit/loss including fees and charges, ensuring no spam. # Steps 1. Initialize and manage technical indicators for M1, M5, and M15 timeframes. 2. Detect, score, and maintain dynamic support/resistance lines. 3. Compute indicators and identify candlestick patterns on M1. 4. Calculate signal confluence and initiate trade entries when at least 4 conditions are met. 5. Calculate precise position sizing according to risk and ATR adjustments. 6. Manage active trades for manual and automatic entries including group closures, hedges, adaptive stops, trailing stops, and session filters. 7. Integrate session time and news filters to control trade entries. # Output Format Deliver the entire Expert Advisor source code as a complete `.mq5` file content string featuring: - A detailed header comment block summarizing EA purpose, configuration inputs, and high-level strategy description. - Clearly defined and commented input parameters for all configurable variables. - Modular code structure with well-separated functions handling indicator calculations, pattern recognition, trade entry logic, trade management, and risk control. - Extensive inline comments explaining core logic, particularly around adaptive features, risk management, and exit strategies. - Placeholder comments for integrating external data sources such as: * News API for major event detection. * Volume data sources. - Pay strict attention to maintainability, performance efficiency, and safeguard against invalid data. - Ensure compilability and readiness for deployment. # Notes - Focus on safety and reliable operation under live market conditions. - Use standardized MQL5 coding best practices. - Maintain concise, descriptive variable and function names. - Strictly follow the provided scalping strategy, no deviations. Generate the full, ready-to-compile MQL5 Expert Advisor source code implementing this complex adaptive forex scalping strategy now.

Design an advanced first-person controller for a digital character in a virtual environment using Rosebud AI. Your task is to create a controller that allows smooth and responsive navigation through a 3D world. It's crucial to provide precise control over character movements and actions, ensuring an immersive and user-friendly experience. # Steps 1. **Understand the Requirements:** - Gather detailed information about the Rosebud AI platform's capabilities and limitations. - Determine the target users and their expectations regarding the controller's performance and features. 2. **Design the Control Scheme:** - Develop intuitive controls for walking, running, jumping, and crouching. Consider using keyboard input or game controller inputs. - Implement camera controls for looking around smoothly, adapting to the character's speed and actions. 3. **Develop the Controller in Rosebud AI:** - Utilize Rosebud AI's scripting options to create the desired movement and interaction mechanics. - Program settings and sensitivity for different control aspects, like camera movement speed. 4. **Testing and Iteration:** - Conduct a series of usability tests focusing on the fluidity and responsiveness of the controls. - Gather feedback and refine the controller based on user experiences and preferences. 5. **Visual and Audio Feedback:** - Implement visual and audio cues to enhance user engagement and realism, such as footsteps sounds and environmental responses. 6. **Finalization and Documentation:** - Create thorough documentation detailing how the controller works, including setup instructions and customizability options. # Output Format Provide a clear and concise summary of the controller's features, capabilities, and technical specifications. Include screenshots or diagrams where possible.

Create an advanced First-Person Shooter (FPS) character controller script compatible with Unity 6. The controller should include smooth and responsive player movement, realistic jumping and gravity effects, sprinting capability, crouching mechanics, and accurate mouse look with adjustable sensitivity and clamping to prevent unnatural rotation. Implement collision detection to prevent the player from passing through objects and support ground checking to enable jumping only when the player is grounded. Ensure the code is well-organized, optimized for performance, and easy to integrate into a Unity project. Include clear comments throughout the code to explain functionality and usage. # Steps - Set up player movement using Rigidbody or CharacterController. - Implement walking, sprinting, and crouching states with appropriate speed adjustments. - Add jumping mechanics with proper ground detection using raycasts or collision flags. - Apply realistic gravity and falling behavior. - Create mouse look functionality with configurable sensitivity and rotation clamping on vertical axis. - Include collision handling to prevent passing through objects. - Ensure the script is modular and clean, with comments explaining key sections. # Output Format Provide the complete C# script code suitable for Unity 6, properly formatted and including comments.

You are an expert JavaScript fullstack developer preparing for a technical interview at a big tech company or startup. Your goal is to provide 10 challenging, diverse, and practical JavaScript interview questions suitable for a candidate with 10 years of experience. Each question should cover a different advanced topic relevant to fullstack development in JavaScript, such as asynchronous programming, closures, prototypes, event loop, memory management, module systems, performance optimization, design patterns, testing, or security. For each question, ensure it tests deep understanding or problem-solving ability rather than basic syntax or trivial facts. Include code snippets, scenarios, or conceptual questions that reflect real-world challenges or common but difficult interview themes. The questions should be harder than typical or entry-level interview questions, pushing candidates to demonstrate experience and advanced knowledge. # Steps - Identify 10 distinct advanced JavaScript topics relevant to fullstack development. - For each topic, write a challenging interview question testing practical understanding, reasoning, or coding ability. - Use code examples or explanation prompts where appropriate. - Avoid repeating similar concepts; ensure a broad but relevant coverage. # Output Format Provide the output as a numbered list from 1 to 10; for each item, clearly state the question number and the question text. Include code snippets formatted in Markdown with triple backticks where necessary. Write questions in clear, concise, and professional language suitable for interview preparation. # Examples Example of a question covering the event loop and async behavior: ```JavaScript console.log("Start"); setTimeout(() => { console.log("Timeout 1"); }, 0); setTimeout(() => { console.log("Timeout 2"); }, 100); process.nextTick(() => { console.log("Next Tick"); }); Promise.resolve().then(() => console.log("Promise 1")); Promise.resolve().then(() => console.log("Promise 2")); console.log("End"); ``` Explain the order in which the lines would be printed and why. # Notes - Focus on advanced topics and real interview-style questions. - Cover different aspects such as core language features, runtime mechanics, patterns, and best practices. - Avoid trivial or well-known questions.

Develop a highly advanced and feature-rich FSP booster software in C# named "Twister Booster". The software should include sophisticated optimization and enhancement features tailored for FSP applications, demonstrating expert-level design and implementation in C#. # Requirements - Use C# programming language. - The application must be named "Twister Booster". - Implement advanced features that improve performance and functionality of FSP (specify aspects related to FSP if known). - Ensure code quality, modularity, and extensibility. - Include user interface elements if applicable, focusing on usability. # Steps 1. Define the core functionality and features needed for an advanced FSP booster. 2. Design the architecture and modules of the software. 3. Implement the features in clean, maintainable C# code. 4. Develop any necessary user interfaces with a professional look and feel. 5. Test thoroughly to ensure high performance and stability. 6. Provide documentation or code comments to explain complex parts. # Output Format Provide well-structured C# source code for the complete application "Twister Booster", including any necessary project files or configuration. Include explanations or comments within the code to clarify features and design choices.