Prompt:
We have app.py:
from unittest import result
from flask import Flask, request, redirect, url_for, flash, jsonify, render_template
from flask_sqlalchemy import SQLAlchemy
from PIL import Image
import pytesseract
import os
import requests
import pickle
import pandas as pd
from werkzeug.utils import secure_filename
from io import BytesIO

# Load the model and scaler
model = pickle.load(open('model.pkl', 'rb'))
scaler = pickle.load(open('scaler.pkl', 'rb'))

# Define thresholds for condition (make sure these are the same as in training!)
thresholds = {
    'MTD': [-0.5, -3, -8, -15],
    'PSD': [1.5, 3, 6, 10]
}

# Function to determine the condition
def determine_condition(mtd, psd):
    if mtd > thresholds['MTD'][0] and psd < thresholds['PSD'][0]:
        return "Normal"
    elif mtd > thresholds['MTD'][1] and psd < thresholds['PSD'][1]:
        return "Mild"
    elif mtd > thresholds['MTD'][2] and psd < thresholds['PSD'][2]:
        return "Moderate"
    elif mtd > thresholds['MTD'][3] and psd < thresholds['PSD'][3]:
        return "Severe"
    else:
        return "Very Severe"

# Function to predict condition from an Excel file
def predict_from_excel(excel_file):
    data = pd.read_excel(excel_file)

    # Extract the required columns dynamically
    columns_to_use = ['MS', 'MS_Cluster1', 'MS_Cluster2', 'MS_Cluster3',
                      'MS_Cluster4', 'MS_Cluster5', 'MS_Cluster6',
                      'MTD', 'PSD', 'MTD_Cluster1', 'MTD_Cluster2',
                      'MTD_Cluster3', 'MTD_Cluster4', 'MTD_Cluster5',
                      'MTD_Cluster6', 'GH']

    # Dynamically create the columns for Sens, TD, and PD, BUT exclude the missing ones
    sens_columns = [f'Sens_{i}' for i in range(1, 55)]
    td_columns = [f'TD_{i}' for i in range(1, 55) if i not in [26, 35]]
    pd_columns = [f'PD_{i}' for i in range(1, 55) if i not in [26, 35]]
    columns_to_use.extend(sens_columns)
    columns_to_use.extend(td_columns)
    columns_to_use.extend(pd_columns)

    # Select only the required columns
    input_data = data[columns_to_use]

    # Scale the input data
    scaled_input = scaler.transform(input_data)

    # Make predictions
    predictions = model.predict(scaled_input)

    # Determine conditions
    conditions = [determine_condition(row['MTD'], row['PSD'])
                  for _, row in input_data.iterrows()]

    return predictions, conditions

app = Flask(__name__)
app.config['SECRET_KEY'] = 'your_secret_key_analysis'
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///analysis.db'
app.config['UPLOAD_FOLDER'] = 'uploads'
db = SQLAlchemy(app)

class Result(db.Model):
   id = db.Column(db.Integer, primary_key=True)
   image_path = db.Column(db.String(100), nullable=False)
   recognized_numbers = db.Column(db.String(200), nullable=True)
   average = db.Column(db.Float, nullable=True)
   patient_id = db.Column(db.Integer, nullable=False)

if not os.path.exists(app.config['UPLOAD_FOLDER']):
   os.makedirs(app.config['UPLOAD_FOLDER'])

@app.route('/upload/<int:patient_id>', methods=['POST'])
def upload_image(patient_id):
   if 'file' not in request.files:
       flash('No file part')
       return redirect(request.url)
   file = request.files['file']
   if file.filename == '':
       flash('No selected file')
       return redirect(request.url)
   if file:
       filepath = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)
       file.save(filepath)
       # Analyze image and update patient's last analysis average...
       # For now, let's assume the average is calculated
       average = 20.5  # Placeholder for actual analysis

       # Update patient's last analysis average in patient service
       requests.put(f'http://localhost:5001/patient/{patient_id}/update_average', json={'average': average})

       return jsonify({'message': 'Image uploaded and analyzed', 'average': average}), 201

@app.route('/', methods=['GET', 'POST'])
def index():
    if request.method == 'POST':
        # Check if a file was uploaded
        if 'file' not in request.files:
            return render_template('index.html', error='No file part')

        file = request.files['file']

        # If no file is selected, show an error
        if file.filename == '':
            return render_template('index.html', error='No selected file')

        # Ensure the uploaded file is an Excel file
        if file.filename.endswith('.xlsx'):
            filename = secure_filename(file.filename)
            # Save the file to memory instead of disk, to avoid file I/O
            # excel_data = file.read()
            # excel_file = BytesIO(excel_data)
            # predictions, conditions = predict_from_excel(excel_file)
            # return render_template('results.html', results=results)

            # If you want to save the file to disk, use these lines instead:
            filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
            file.save(filepath)
            predictions, conditions = predict_from_excel(filepath)
            return render_template('results.html', results=result)

        else:
            return render_template('index.html', error='Please upload an Excel file (.xlsx)')
    return render_template('index.html')

if __name__ == '__main__':
   with app.app_context():
       db.create_all()
   app.run(port=5002)

The  image_analysis_service.py that we want to change and load excel file as in app.py
from flask import Flask, request, redirect, url_for, flash, jsonify
from flask_sqlalchemy import SQLAlchemy
from PIL import Image
import pytesseract
import os
import requests

app = Flask(__name__)
app.config['SECRET_KEY'] = 'your_secret_key_analysis'
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///analysis.db'
app.config['UPLOAD_FOLDER'] = 'uploads'

db = SQLAlchemy(app)

class Result(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    image_path = db.Column(db.String(100), nullable=False)
    recognized_numbers = db.Column(db.String(200), nullable=True)
    average = db.Column(db.Float, nullable=True)
    patient_id = db.Column(db.Integer, nullable=False)

if not os.path.exists(app.config['UPLOAD_FOLDER']):
    os.makedirs(app.config['UPLOAD_FOLDER'])

@app.route('/upload/<int:patient_id>', methods=['POST'])
def upload_image(patient_id):
    if 'file' not in request.files:
        flash('No file part')
        return redirect(request.url)
    file = request.files['file']
    if file.filename == '':
        flash('No selected file')
        return redirect(request.url)
    if file:
        filepath = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)
        file.save(filepath)
        # Analyze image and update patient's last analysis average...
        # For now, let's assume the average is calculated
        average = 20.5  # Placeholder for actual analysis

        # Update patient's last analysis average in patient service
        requests.put(f'http://localhost:5001/patient/{patient_id}/update_average', json={'average': average})

        return jsonify({'message': 'Image uploaded and analyzed', 'average': average}), 201

if __name__ == '__main__':
    with app.app_context():
        db.create_all()
    app.run(port=5002)

and
# patient_service.py
from flask import Flask, request, jsonify
from flask_sqlalchemy import SQLAlchemy
from datetime import datetime

app = Flask(__name__)
app.config['SECRET_KEY'] = 'your_secret_key_patient'
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///patients.db'

db = SQLAlchemy(app)

class Patient(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    name = db.Column(db.String(50), nullable=False)
    surname = db.Column(db.String(50), nullable=False)
    sex = db.Column(db.String(10), nullable=False)
    age = db.Column(db.Integer, nullable=False)
    last_analysis_average = db.Column(db.Float, nullable=True)
    last_saved = db.Column(db.DateTime, default=datetime.utcnow)

@app.route('/patient', methods=['POST'])
def add_patient():
    data = request.get_json()
    new_patient = Patient(
        name=data['name'],
        surname=data['surname'],
        sex=data['sex'],
        age=data['age']
    )
    db.session.add(new_patient)
    db.session.commit()
    return jsonify({'message': 'New patient created'}), 201

@app.route('/patient/<int:patient_id>', methods=['GET'])
def get_patient(patient_id):
    patient = Patient.query.get_or_404(patient_id)
    return jsonify({
        'name': patient.name,
        'surname': patient.surname,
        'sex': patient.sex,
        'age': patient.age,
        'last_analysis_average': patient.last_analysis_average
    })

if __name__ == '__main__':
    with app.app_context():
        db.create_all()
    app.run(port=5001)
This is a back end, and we have several pages for a front
check the code
Fix it And upgrade for ml model usage


Prompt:
Ранее ты мне дал вот такой код врага, мы пишем игру Tower Defense на юнити.

using UnityEngine;
using System.Collections.Generic;

public class Enemy : MonoBehaviour
{
    public float health = 100f;
    public float speed = 2f;
    public float armor = 0f;
    public Transform targetBase;

    private Grid grid;
    private List<Node> path;
    private int currentNodeIndex;

    private void Start()
    {
        grid = FindObjectOfType<Grid>();
        FindPath();
    }

    private void Update()
    {
        Move();

        if (Vector3.Distance(transform.position, targetBase.position) <= 0.1f)
        {
            AttackBase();
        }
    }

    private void Move()
    {
        if (path == null || currentNodeIndex >= path.Count)
        {
            return;
        }

        Node currentNode = path[currentNodeIndex];
        Vector3 targetPosition = currentNode.worldPosition;

        transform.position = Vector3.MoveTowards(transform.position, targetPosition, speed * Time.deltaTime);

        if (Vector3.Distance(transform.position, targetPosition) <= 0.1f)
        {
            currentNodeIndex++;
        }
    }

    private void FindPath()
    {
        path = Pathfinding.Instance.FindPath(transform.position, targetBase.position);
        currentNodeIndex = 0;
    }

    public void TakeDamage(float damage)
    {
        float actualDamage = damage - armor;
        if (actualDamage > 0)
        {
            health -= actualDamage;
            if (health <= 0)
            {
                Die();
            }
        }
    }

    private void AttackBase()
    {
        // Логика атаки базы игрока
        // Здесь нужно реализовать нанесение урона базе игрока
    }

    private void Die()
    {
        // Логика смерти врага
        Destroy(gameObject);
    }

    private void OnTriggerEnter2D(Collider2D other)
    {
        if (other.CompareTag("Tower"))
        {
            Tower tower = other.GetComponent<Tower>();
            if (tower != null)
            {
                tower.DestroyTower();
                FindPath();
            }
        }
    }
}

Выдает ошибку
Ошибка (активно)	CS0103	Имя "Pathfinding" не существует в текущем контексте.	Assembly-CSharp	C:\Users\nemoc\My project\Assets\Scripts\Enemy.cs	51


Prompt: how to implement guided process framework .  explain with example  user registration. implementation of guided process in asp.net core. UI should be single page and users should be guided to add different info of users by highlighting fields on page and showing info how about field and how step can be completed and only keeping that field enabled and rest page inaccessible


Prompt:
我发现我使用 rust 设置 socket 的 SO_RCVTIMEO 只能设置或者读取一次, 下一次就会失败你知道这是什么情况吗?
```
set SO_RCVTIMEO to 3s
thread 'p2p::test' panicked at quicocks/src/p2p/mod.rs:230:44:
called `Result::unwrap()` on an `Err` value: Os { code: 9, kind: Uncategorized, message: "Bad file descriptor" }
note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace
```

```rs
impl SockOpt for tokio::net::UdpSocket {
    fn read_timeout(&self) -> io::Result<Option<Duration>> {
        let fd = self.as_raw_fd();

        let sock2_sock = unsafe { Socket::from_raw_fd(fd) };

        sock2_sock.read_timeout()
    }

    fn set_read_timeout(&self, duration: Option<Duration>) -> io::Result<()> {
        let fd = self.as_raw_fd();

        let sock2_sock = unsafe { Socket::from_raw_fd(fd) };

        sock2_sock.set_read_timeout(duration)
    }
}

    let udp_sock = UdpSocket::bind("0.0.0.0:0").await.unwrap();
    udp_sock.set_read_timeout(Some(Duration::from_secs(3))).unwrap();
    println!("set SO_RCVTIMEO to {:?}", Duration::from_secs(3));
    let time_out = udp_sock.read_timeout().unwrap();
    println!("read SO_RCVTIMEO: {:?}", time_out);
```


Prompt: how can I combine wget -N -r -nd -np -l 1 -A zip https://example.com and parallel together to allow downloading faster without duplicating downloads


Prompt:
You are now a code assistant,
Create me a C89 header file that deduce the operating system (must handle MacOS, Windows and Linux/UNIX) as well as conditionnally define a "CONSTRUCTOR" macro based on the deduced OS, if it is a unique system the CONSTRUCTOR macro should define \_\_attribute\_\_((constructor)) else if it is Windows it should define a TLS callback


Prompt: Here is my database structure: https://tangthucac.com/truyen.sql Can you help me to refined, upgrade, and perfect this MySQL


Prompt:
optimze the following queries in the function. Replace these with optimized version of query

    public function updateInvoicesToPaid($invoices_to_update)
    {
        $invoices_to_update = implode(',', $invoices_to_update);
        \DB::statement(
            "UPDATE invoices,
            (
                SELECT i.id, total_amount
                FROM invoices i
                left join payments p on i.id = p.invoice_id
                where i.id IN (" .
                $invoices_to_update .
                ")
                group by i.id
                having  COALESCE(sum(p.amount),0) > total_amount
                ) as pp
             SET paid = -1
             WHERE pp.id = invoices.id  ",
        );
        //        \Log::info($invoices_to_update);
        \DB::statement(
            "UPDATE invoices,
            (
                SELECT i.id, total_amount
                FROM invoices i
                left join payments p on i.id = p.invoice_id
                 where i.id IN (" .
                $invoices_to_update .
                ")
                group by i.id
                having  COALESCE(sum(p.amount),0) = total_amount
                ) as pp
             SET paid = 1
             WHERE pp.id = invoices.id  ",
        );

        \DB::statement(
            "UPDATE invoices,
            (
                SELECT i.id, total_amount
                FROM invoices i
                left join payments p on i.id = p.invoice_id
                 where i.id IN (" .
                $invoices_to_update .
                ")
                group by i.id
                having  COALESCE(sum(p.amount),0) < total_amount
                ) as pp
             SET paid = 0
             WHERE pp.id = invoices.id  ",
        );
    }


Prompt: Write Python code using PySide2, and the Foundry Nuke Python API in which the standard color picker from Nuke is added to the PySide2 widget.


Prompt: create a js Events class that accepts subscribers and triggers events for subscribers. it must have the following methods: Events::subscribe(eventName, callback), unsubscribe(eventName, callback), trigger(eventNames, ...options)


Prompt:
how can i change this code to, when I browse for a folder to open, it shows the contents (files) of that folder, but still selects the folder:
import os
import json
from tkinter import *
from tkinter import filedialog, messagebox, ttk
from PIL import Image, ImageTk

class ImageTagger:
def init(self, root):
self.root = root
self.root.title("Image Tagger")
self.root.geometry("800x600")
self.root.configure(bg="#2c2c2c") # Set root background to dark

    # Set up dark theme
    self.set_dark_theme()

    self.image_list = []
    self.image_index = 0
    self.image_tags = {}  # Dictionary to store tags for each image
    self.tags = {}
    self.tag_options = self.load_tags_from_json()

    self.root.grid_rowconfigure(0, weight=1)
    self.root.grid_columnconfigure(0, weight=1)

    self.setup_notebook()
    self.setup_tagging_interface()
    self.setup_settings_interface()

    # Bind events
    self.setup_tagging_bindings()

def set_dark_theme(self):
    style = ttk.Style()
    style.theme_create("darktheme", parent="alt", settings={
        "TNotebook": {"configure": {"background": "#2c2c2c", "tabmargins": [2, 5, 2, 0]}},
        "TNotebook.Tab": {"configure": {"padding": [5, 2], "background": "#1c1c1c", "foreground": "white"},
                        "map": {"background": [("selected", "#3c3c3c")],
                                "foreground": [("selected", "white")]}},
        "TFrame": {"configure": {"background": "#2c2c2c"}},
        "TButton": {"configure": {"background": "#3c3c3c", "foreground": "white"}},
        "TLabel": {"configure": {"background": "#2c2c2c", "foreground": "white"}},
        "TCheckbutton": {"configure": {"background": "#2c2c2c", "foreground": "white",
                                    "indicatorcolor": "#3c3c3c", "indicatorbackground": "white"}},
        "Vertical.TScrollbar": {"configure": {"background": "#3c3c3c", "bordercolor": "#1c1c1c"}},
    })
    style.theme_use("darktheme")
    style.configure("Dark.TEntry", fieldbackground="#3c3c3c", foreground="white")
    style.map('TCheckbutton', background=[('active', '#3c3c3c')])

def load_tags_from_json(self):
    script_dir = os.path.dirname(os.path.abspath(__file__))
    json_path = os.path.join(script_dir, 'data', 'data.json')
    try:
        with open(json_path, 'r') as f:
            return json.load(f)
    except FileNotFoundError:
        messagebox.showerror("Error", f"JSON file not found: {json_path}")
        return {}
    except json.JSONDecodeError:
        messagebox.showerror("Error", f"Invalid JSON file: {json_path}")
        return {}

def setup_notebook(self):
    self.notebook = ttk.Notebook(self.root)
    self.notebook.grid(row=0, column=0, sticky="nsew")

    self.tagging_frame = ttk.Frame(self.notebook)
    self.settings_frame = ttk.Frame(self.notebook)

    self.notebook.add(self.tagging_frame, text="Tagging")
    self.notebook.add(self.settings_frame, text="Settings")

    self.notebook.bind("<<NotebookTabChanged>>", self.on_tab_changed)

def setup_tagging_bindings(self):
    self.tagging_frame.bind('<Up>', self.select_previous_image)
    self.tagging_frame.bind('<Down>', self.select_next_image)
    self.tagging_frame.bind('<Delete>', self.confirm_delete_image)

    # Add bindings specifically for the image listbox
    self.image_listbox.bind('<Up>', self.select_previous_image)
    self.image_listbox.bind('<Down>', self.select_next_image)
    self.image_listbox.bind('<Delete>', self.confirm_delete_image)

    # Bind the resize event to the root window
    self.root.bind('<Configure>', self.on_window_resize)

def setup_tagging_interface(self):
    self.tagging_frame.grid_rowconfigure(1, weight=1)
    self.tagging_frame.grid_columnconfigure(0, weight=3)
    self.tagging_frame.grid_columnconfigure(1, weight=1)

    # Top button frame
    self.button_frame = ttk.Frame(self.tagging_frame)
    self.button_frame.grid(row=0, column=0, columnspan=2, pady=10, sticky="ew")

    self.open_button = ttk.Button(self.button_frame, text="Open Directory", command=self.open_directory)
    self.open_button.pack(side=LEFT, padx=5)

    self.rename_button = ttk.Button(self.button_frame, text="Rename Image", command=self.rename_image)
    self.rename_button.pack(side=LEFT, padx=5)

    # Image display frame
    self.image_frame = ttk.Frame(self.tagging_frame, width=400, height=400)
    self.image_frame.grid(row=1, column=0, padx=10, pady=10, sticky="nsew")
    self.image_frame.grid_propagate(False)

    self.image_label = ttk.Label(self.image_frame)
    self.image_label.place(relx=0.5, rely=0.5, anchor="center")

    # Image list frame
    self.image_list_frame = ttk.Frame(self.tagging_frame)
    self.image_list_frame.grid(row=2, column=0, padx=10, pady=10, sticky="nsew")

    self.image_listbox = Listbox(self.image_list_frame, selectmode=SINGLE, bg="#2c2c2c", fg="white")
    self.image_listbox.pack(side=LEFT, fill=BOTH, expand=True)
    self.image_listbox.bind('<<ListboxSelect>>', self.on_image_select)

    self.image_scrollbar = ttk.Scrollbar(self.image_list_frame, orient="vertical", command=self.image_listbox.yview)
    self.image_scrollbar.pack(side=RIGHT, fill=Y)
    self.image_listbox.configure(yscrollcommand=self.image_scrollbar.set)

    # Tag frame
    self.create_tag_frame()

    # Bottom frame
    self.bottom_frame = ttk.Frame(self.tagging_frame)
    self.bottom_frame.grid(row=3, column=0, columnspan=2, sticky="nsew", padx=10, pady=10)
    self.bottom_frame.columnconfigure(2, weight=1)  # Make the third column expandable

    self.current_image_label = ttk.Label(self.bottom_frame, text="Current Image: None")
    self.current_image_label.grid(row=0, column=0, sticky="w")

    self.current_tags_label = ttk.Label(self.bottom_frame, text="New Filename: None")
    self.current_tags_label.grid(row=1, column=0, sticky="w")

    # Add BLANK OUT button to the far right
    self.blank_out_button = ttk.Button(self.bottom_frame, text="BLANK OUT", command=self.blank_out_images)
    self.blank_out_button.grid(row=0, rowspan=2, column=2, sticky="e")

def create_tag_frame(self):
    self.tag_frame = ttk.Frame(self.tagging_frame)
    self.tag_frame.grid(row=0, column=1, rowspan=3, padx=10, pady=10, sticky="nsew")
    self.tag_frame.grid_columnconfigure(0, weight=1)
    self.tag_frame.grid_rowconfigure(0, weight=1)

    canvas = Canvas(self.tag_frame, bg="#2c2c2c")
    scrollbar = ttk.Scrollbar(self.tag_frame, orient="vertical", command=canvas.yview)
    scrollable_frame = ttk.Frame(canvas)

    scrollable_frame.bind(
        "<Configure>",
        lambda e: canvas.configure(
            scrollregion=canvas.bbox("all")
        )
    )

    canvas.create_window((0, 0), window=scrollable_frame, anchor="nw")
    canvas.configure(yscrollcommand=scrollbar.set)

    canvas.pack(side=LEFT, fill=BOTH, expand=True)
    scrollbar.pack(side=RIGHT, fill=Y)

    self.tag_vars = {}

    # Create type-to-match list box for the first category
    first_category = list(self.tag_options.keys())[0]
    self.create_type_to_match_listbox(scrollable_frame, first_category, self.tag_options[first_category])

    # Create checkboxes for the remaining categories
    for i, (category, options) in enumerate(list(self.tag_options.items())[1:], start=1):
        ttk.Separator(scrollable_frame, orient='horizontal').pack(fill=X, pady=5)
        self.create_checkboxes(scrollable_frame, category, options)

def create_checkboxes(self, parent, category, options):
    frame = ttk.Frame(parent)
    frame.pack(fill=X, pady=(0, 10))
    self.tag_vars[category] = {}

    sorted_options = sorted(options)  # Sort options alphabetically
    for i, option in enumerate(sorted_options):
        var = IntVar()
        self.tag_vars[category][option] = var
        cb = ttk.Checkbutton(frame, text=option, variable=var,
                    command=lambda c=category, o=option: self.checkbox_clicked(c, o),
                    style='TCheckbutton')
        cb.grid(row=i//4, column=i%4, sticky="w", padx=5, pady=2)  # 4 checkboxes per row

def create_type_to_match_listbox(self, parent, category, options):
    frame = ttk.Frame(parent)
    frame.pack(fill=X, pady=(0, 10))

    label = ttk.Label(frame, text=f"{category}:")
    label.pack(side=TOP, anchor=W)

    self.type_to_match_var = StringVar()
    self.type_to_match_entry = ttk.Entry(frame, textvariable=self.type_to_match_var, style="Dark.TEntry")
    self.type_to_match_entry.pack(side=TOP, fill=X)

    self.type_to_match_listbox = Listbox(frame, selectmode=SINGLE, height=5, bg="#2c2c2c", fg="white")
    self.type_to_match_listbox.pack(side=TOP, fill=X, expand=True)

    for option in sorted(options):
        self.type_to_match_listbox.insert(END, option)

    self.type_to_match_var.trace("w", self.update_type_to_match_list)
    self.type_to_match_listbox.bind("<<ListboxSelect>>", self.on_type_to_match_select)

def setup_settings_interface(self):
    self.json_text = Text(self.settings_frame, wrap=WORD, bg="#2c2c2c", fg="white", insertbackground="white")
    self.json_text.pack(expand=True, fill=BOTH)
    self.json_text.config(state=NORMAL)  # Ensure the widget is editable

    button_frame = ttk.Frame(self.settings_frame)
    button_frame.pack(fill=X)

    self.load_json_button = ttk.Button(button_frame, text="Load JSON", command=self.load_json)
    self.load_json_button.pack(side=LEFT, padx=5, pady=5)

    self.save_json_button = ttk.Button(button_frame, text="Save JSON", command=self.save_json)
    self.save_json_button.pack(side=LEFT, padx=5, pady=5)

    # Load default JSON when initializing
    self.load_default_json()

    # Bind Tab and Shift+Tab to move focus within the Settings tab
    self.json_text.bind('<Tab>', self.focus_next_widget)
    self.json_text.bind('<Shift-Tab>', self.focus_previous_widget)

def on_tab_changed(self, event):
    selected_tab = self.notebook.index(self.notebook.select())
    if selected_tab == 0:  # Tagging tab
        self.setup_tagging_bindings()
        self.image_listbox.focus_set()  # Set focus to the image listbox
        self.rebuild_tag_interface()  # Rebuild the tag interface
    else:  # Settings tab
        self.tagging_frame.unbind('<Up>')
        self.tagging_frame.unbind('<Down>')
        self.tagging_frame.unbind('<Delete>')
        self.image_listbox.unbind('<Up>')
        self.image_listbox.unbind('<Down>')
        self.image_listbox.unbind('<Delete>')
        self.json_text.focus_set()

def rebuild_tag_interface(self):
    # Clear existing tag frame
    for widget in self.tag_frame.winfo_children():
        widget.destroy()

    # Recreate the scrollable frame
    canvas = Canvas(self.tag_frame, bg="#2c2c2c")
    scrollbar = ttk.Scrollbar(self.tag_frame, orient="vertical", command=canvas.yview)
    scrollable_frame = ttk.Frame(canvas)

    scrollable_frame.bind(
        "<Configure>",
        lambda e: canvas.configure(
            scrollregion=canvas.bbox("all")
        )
    )

    canvas.create_window((0, 0), window=scrollable_frame, anchor="nw")
    canvas.configure(yscrollcommand=scrollbar.set)

    canvas.pack(side=LEFT, fill=BOTH, expand=True)
    scrollbar.pack(side=RIGHT, fill=Y)

    # Recreate type-to-match listbox for the first category
    first_category = list(self.tag_options.keys())[0]
    self.create_type_to_match_listbox(scrollable_frame, first_category, self.tag_options[first_category])

    # Create checkboxes for the remaining categories
    self.tag_vars = {}
    for i, (category, options) in enumerate(list(self.tag_options.items())[1:], start=1):
        ttk.Separator(scrollable_frame, orient='horizontal').pack(fill=X, pady=5)
        self.create_checkboxes(scrollable_frame, category, options)

    # Update the current image display to reflect any changes
    if self.image_list:
        self.show_image()

def open_directory(self):
    directory = filedialog.askdirectory()
    if directory:
        self.image_list = sorted([os.path.join(directory, f) for f in os.listdir(directory)
                                if f.lower().endswith(('png', 'jpg', 'jpeg', 'gif', 'bmp', 'webp'))],
                                key=lambda x: os.path.basename(x).lower())
        if not self.image_list:
            messagebox.showerror("Error", "No images found in the selected directory.")
            return
        self.image_index = 0
        self.update_image_listbox()
        self.show_image()
        self.image_listbox.focus_set()  # Set focus to the image listbox

def update_image_listbox(self):
    self.image_listbox.delete(0, END)
    for image in self.image_list:
        self.image_listbox.insert(END, os.path.basename(image))

def on_image_select(self, event):
    selected = self.image_listbox.curselection()
    if selected:
        self.image_index = selected[0]
        self.show_image()

def show_image(self):
    if self.image_list:
        image_path = self.image_list[self.image_index]
        filename = os.path.basename(image_path)
        try:
            self.current_image = Image.open(image_path)
        except Exception as e:
            print(f"Debug: Error opening image: {e}")
            return  # Exit the method if we can't open the image

        self.resize_current_image()

        self.current_image_label.config(text=f"Current Image: {filename}")

        # Clear all existing tags and checkboxes
        self.clear_all_tags()

        # Load or update tags for this image
        self.update_tags_for_image(filename)

        # Update type-to-match
        first_category = list(self.tag_options.keys())[0]
        if first_category in self.tags and self.tags[first_category]:
            self.type_to_match_var.set(self.tags[first_category][0])
            # Select the item in the listbox
            items = self.type_to_match_listbox.get(0, END)
            if self.tags[first_category][0] in items:
                index = items.index(self.tags[first_category][0])
                self.type_to_match_listbox.selection_clear(0, END)
                self.type_to_match_listbox.selection_set(index)
                self.type_to_match_listbox.see(index)
        else:
            self.type_to_match_var.set("")
            self.type_to_match_listbox.selection_clear(0, END)

        # Update checkboxes
        for category, tags in self.tags.items():
            if category in self.tag_vars:
                for option in self.tag_vars[category]:
                    if option in tags:
                        self.tag_vars[category][option].set(1)
                    else:
                        self.tag_vars[category][option].set(0)

        self.update_new_filename_label()

        # Force update of the UI
        self.root.update_idletasks()
    else:
        print("Debug: No images in the list")

def update_tags_for_image(self, filename):
    # Clear all checkboxes
    for category in self.tag_vars:
        for var in self.tag_vars[category].values():
            var.set(0)

    # Clear current tags
    self.tags = {}

    # Set tags based on filename
    name_parts = os.path.splitext(filename)[0].split('_')
    name_parts = [part for part in name_parts if not part.isdigit()]

    first_category = list(self.tag_options.keys())[0]

    # Handle type-to-match category
    for part in name_parts:
        if part.lower() in [option.lower() for option in self.tag_options[first_category]]:
            self.tags[first_category] = [part]
            self.type_to_match_var.set(part)
            break

    # Handle other categories
    for part in name_parts:
        for category, options in list(self.tag_options.items())[1:]:
            if part.lower() in [option.lower() for option in options]:
                self.tag_vars[category][part].set(1)
                if category not in self.tags:
                    self.tags[category] = []
                if part not in self.tags[category]:
                    self.tags[category].append(part)

    # Store tags for this image
    self.image_tags[filename] = self.tags.copy()

    self.update_new_filename_label()

def update_new_filename_label(self):
    if not self.image_list:
        self.current_tags_label.config(text="New Filename: No image selected")
        return

    tags = []
    for category in self.tag_options.keys():
        if category in self.tags:
            # Sort the tags for this category alphabetically
            category_tags = sorted(self.tags[category])
            tags.extend(category_tags)

    if tags:
        new_filename = "_".join(tags).lower() + ".webp"
        self.current_tags_label.config(text=f"New Filename: {new_filename}")
    else:
        self.current_tags_label.config(text="New Filename: No tags selected")

def rename_image(self):
    if not self.image_list:
        messagebox.showerror("Error", "No images to rename.")
        return

    tags = []
    for category in self.tag_options.keys():
        if category in self.tags:
            # Sort the tags for this category alphabetically
            category_tags = sorted(self.tags[category])
            tags.extend(category_tags)

    if not tags:
        messagebox.showerror("Error", "At least one tag is required.")
        return

    directory = os.path.dirname(self.image_list[self.image_index])
    base_name = "_".join(tags).lower()  # Convert base name to lowercase
    new_name = f"{base_name}.webp"
    new_path = os.path.join(directory, new_name)

    i = 1
    while os.path.exists(new_path):
        new_name = f"{base_name}_{i:03d}.webp"
        new_path = os.path.join(directory, new_name)
        i += 1

    # Convert and save the image as a WebP file
    image = Image.open(self.image_list[self.image_index])
    image.save(new_path, format='WEBP')

    old_path = self.image_list[self.image_index]
    os.remove(old_path)
    self.image_list[self.image_index] = new_path

    self.tags.clear()
    self.update_new_filename_label()
    for category in self.tag_vars:
        for var in self.tag_vars[category].values():
            var.set(False)
    self.update_image_list(os.path.dirname(new_path))

    # Select and load the newly renamed image
    new_index = self.image_list.index(new_path)
    self.image_index = new_index
    self.image_listbox.select_clear(0, END)
    self.image_listbox.select_set(new_index)
    self.image_listbox.see(new_index)
    self.show_image()

def resize_current_image(self):
    if not hasattr(self, 'current_image'):
        return

    frame_width = self.image_frame.winfo_width()
    frame_height = self.image_frame.winfo_height()

    if frame_width <= 1 or frame_height <= 1:  # Frame not properly sized yet
        self.root.update_idletasks()
        frame_width = self.image_frame.winfo_width()
        frame_height = self.image_frame.winfo_height()

    img_width, img_height = self.current_image.size
    aspect_ratio = img_width / img_height

    if frame_width / frame_height > aspect_ratio:
        new_height = frame_height
        new_width = int(new_height * aspect_ratio)
    else:
        new_width = frame_width
        new_height = int(new_width / aspect_ratio)

    resized_image = self.current_image.copy()
    resized_image.thumbnail((new_width, new_height), Image.LANCZOS)

    # Add a white border to the image
    bordered_image = Image.new("RGB", (new_width + 2, new_height + 2), color="white")
    bordered_image.paste(resized_image, (1, 1))

    photo = ImageTk.PhotoImage(bordered_image)
    self.image_label.config(image=photo)
    self.image_label.image = photo  # Keep a reference

def update_image_list(self, directory):
    self.image_list = sorted([os.path.join(directory, f) for f in os.listdir(directory)
                              if f.lower().endswith(('png', 'jpg', 'jpeg', 'gif', 'bmp', 'webp'))],
                             key=lambda x: os.path.basename(x).lower())
    self.update_image_listbox()

def select_next_image(self, event=None):
    if self.image_list:
        self.image_index = (self.image_index + 1) % len(self.image_list)
        self.image_listbox.select_clear(0, END)
        self.image_listbox.select_set(self.image_index)
        self.image_listbox.see(self.image_index)
        self.clear_all_tags()
        self.show_image()

def select_previous_image(self, event=None):
    if self.image_list:
        self.image_index = (self.image_index - 1) % len(self.image_list)
        self.image_listbox.select_clear(0, END)
        self.image_listbox.select_set(self.image_index)
        self.image_listbox.see(self.image_index)
        self.clear_all_tags()
        self.show_image()

def blank_out_images(self):
    if not self.image_list:
        messagebox.showerror("Error", "No images loaded.")
        return

    if messagebox.askyesno("Confirm BLANK OUT", "Prepend '_' to all image filenames in the current directory?"):
        directory = os.path.dirname(self.image_list[0])
        for i, image_path in enumerate(self.image_list):
            old_name = os.path.basename(image_path)
            new_name = f"_{old_name}"
            new_path = os.path.join(directory, new_name)

            # Keep prepending underscores until we find a unique filename
            while os.path.exists(new_path):
                new_name = f"_{new_name}"
                new_path = os.path.join(directory, new_name)

            os.rename(image_path, new_path)
            self.image_list[i] = new_path

        self.update_image_listbox()
        self.show_image()
        messagebox.showinfo("BLANK OUT Complete", "All images have been renamed successfully.")

def checkbox_clicked(self, category, option):
    self.update_tags(category, option)

    # Ensure the checkbox state matches the tag state
    is_checked = option in self.tags.get(category, [])
    self.tag_vars[category][option].set(is_checked)

def clear_all_tags(self):
    self.tags.clear()
    for category in self.tag_vars:
        for var in self.tag_vars[category].values():
            var.set(0)
    self.type_to_match_var.set("")
    self.type_to_match_listbox.selection_clear(0, END)
    self.update_new_filename_label()

def confirm_delete_image(self, event):
    if messagebox.askyesno("Delete Image", "Are you sure you want to delete the current image?"):
        self.delete_image()
        self.clear_all_tags()

def delete_image(self):
    if self.image_list:
        current_index = self.image_index
        image_path = self.image_list[current_index]
        os.remove(image_path)
        del self.image_list[current_index]

        # If we deleted the last image, select the new last image
        if current_index == len(self.image_list):
            self.image_index = len(self.image_list) - 1
        # Otherwise, keep the same index to select the next image
        else:
            self.image_index = current_index

        self.update_image_listbox()
        if self.image_list:
            # Select the new image in the listbox
            self.image_listbox.select_clear(0, END)
            self.image_listbox.select_set(self.image_index)
            self.image_listbox.see(self.image_index)

            # Show the new image and update tags
            self.show_image()
        else:
            self.image_label.config(image='')
            self.current_image_label.config(text="Current Image: None")
            self.current_tags_label.config(text="New Filename: None")
            self.clear_all_tags()

def focus_next_widget(self, event):
    event.widget.tk_focusNext().focus()
    return "break"

def focus_previous_widget(self, event):
    event.widget.tk_focusPrev().focus()
    return "break"

def on_window_resize(self, event):
    if self.image_list and hasattr(self, 'current_image'):
        self.resize_current_image()
        self.root.update_idletasks()

def update_type_to_match_list(self, *args):
    search_term = self.type_to_match_var.get().lower()
    self.type_to_match_listbox.delete(0, END)
    for option in sorted(self.tag_options[list(self.tag_options.keys())[0]]):
        if search_term in option.lower():
            self.type_to_match_listbox.insert(END, option)

def on_type_to_match_select(self, event):
    selected = self.type_to_match_listbox.curselection()
    if selected:
        option = self.type_to_match_listbox.get(selected[0])
        category = list(self.tag_options.keys())[0]
        if category not in self.tags:
            self.tags[category] = []
        if option not in self.tags[category]:
            self.tags[category] = [option]  # Replace the existing tag with the new one
        self.update_new_filename_label()

def update_tags(self, category, option):
    is_checked = self.tag_vars[category][option].get()

    if category not in self.tags:
        self.tags[category] = []

    # Only clear other selections for the first category (type-to-match)
    if category == list(self.tag_options.keys())[0]:
        for other_option in self.tag_vars[category]:
            if other_option != option:
                self.tag_vars[category][other_option].set(0)
        self.tags[category] = []  # Clear previous selections

    if is_checked and option not in self.tags[category]:
        self.tags[category].append(option)
    elif not is_checked and option in self.tags[category]:
        self.tags[category].remove(option)

    if not self.tags[category]:
        del self.tags[category]

    # Update tags for the current image
    current_image = os.path.basename(self.image_list[self.image_index])
    self.image_tags[current_image] = self.tags.copy()

    self.update_new_filename_label()

def load_default_json(self):
    script_dir = os.path.dirname(os.path.abspath(__file__))
    json_path = os.path.join(script_dir, 'data', 'data.json')

    try:
        with open(json_path, 'r') as f:
            json_data = json.load(f)
        self.json_text.delete('1.0', END)
        self.json_text.insert(END, json.dumps(json_data, indent=2))
    except FileNotFoundError:
        messagebox.showerror("Error", f"JSON file not found: {json_path}")
    except json.JSONDecodeError:
        messagebox.showerror("Error", f"Invalid JSON file: {json_path}")

def load_json(self):
    file_path = filedialog.askopenfilename(filetypes=[("JSON files", "*.json")])
    if file_path:
        try:
            with open(file_path, 'r') as f:
                json_data = json.load(f)
            self.json_text.delete('1.0', END)
            self.json_text.insert(END, json.dumps(json_data, indent=2))
        except json.JSONDecodeError:
            messagebox.showerror("Error", "Invalid JSON file")

def save_json(self):
        json_data = self.json_text.get('1.0', END)
        try:
            parsed_json = json.loads(json_data)

            script_dir = os.path.dirname(os.path.abspath(__file__))
            json_path = os.path.join(script_dir, 'data', 'data.json')

            with open(json_path, 'w') as f:
                json.dump(parsed_json, f, indent=2)

            messagebox.showinfo("Success", "JSON saved successfully")

            # Update the tag options and refresh the UI
            self.tag_options = parsed_json
            self.rebuild_tag_interface()

        except json.JSONDecodeError as e:
            messagebox.showerror("Error", f"Invalid JSON: {str(e)}")
        except IOError as e:
            messagebox.showerror("Error", f"Failed to save JSON: {str(e)}")
if name == "main":
root = Tk()
app = ImageTagger(root)
root.mainloop()


Prompt:
Notes:
A divisor function is related to the divisors of an integer. The number of
divisors of a certain integer is being count. The symbol we use for this is 'σ'
or the small letter sigma and/or 'τ' means tau.
Example 1:
How many divisors does τ16 has?
Solution
Write down all the divisor of 16.
τ16 = 1, 2, 4, 8, 16, since there are 5 divisors of 16 thus τ16 = 5.
Example 2:
Find s(48)?
Solution
s(48) means sum of 48. It means that we must add the divisors of 48
to obtain the sum.
s(48) = 1 + 2 + 3 + 4 + 6 + 8 + 12 + 16 + 24 + 48
= 124

If an integer c is congruent to a perfect square modulo d then it is called a
quadratic residue modulo d. It is written in the form x2 = c (mod d), then if
not it is considered as quadratic nonresidue modulo d. Let’s have some
examples.
Example 1
1^2 = 1 ≡ 1 (mod 7)
6^2 = 36 ≡ 1 (mod 7)
3^2 = 9 ≡ 2 (mod 7)
4^2 = 16 ≡ 2 (mod 7)
2^2 = 4 ≡ 4 (mod 7)
5^2 = 25 ≡ 4 (mod 7)
From the examples above, the bold numbers such as 1, 2 and 4 are classified
as a quadratic residue, while the numbers 3, 5 and 7 are the examples of
quadratic nonresidue

Instruction:
Solve the multiple choice problems by writing out python code to check all the choices and printout the answers with clear formatting. Repeat the query and do this step by step.

multiple choice problems:
The following are the quadratic residue of modulo 27 , EXCEPT
Select one:

a.
17

b.
19

c.
22

d.
25

Which of the following is the quadratic non residue of modulo 27?
Select one:

a.
10

b.
9

c.
11

d.
13

Complete the statement: 15^2 = 225 = ___ (mod 27).

Select one:

a.
9

b.
4

c.
10

d.
7

The following are the quadratic non residue of modulo 27, EXCEPT
Select one:

a.
16

b.
14

c.
15

d.
17

What must be the value of the unknown if, ___ = 64 = 10 (mod 27)?

Select one:

a.
8^3

b.
2^6

c.
4^3

d.
8^2

Complete the mathematical statement: 22^2 = ____ = 25 (mod 27).
Select one:

a.
441

b.
361

c.
484

d.
400


Prompt:
Есть redis cluster:
2171e17381d051fe5014553facf550c3796b6647 10.20.123.116:6379@16379 master - 0 1722943144000 3 connected 5461-10922
2c4e0b6005ab703c6c86db25e680a23d5894db7e 10.20.123.117:6380@16380 slave 2171e17381d051fe5014553facf550c3796b6647 0 1722943144800 3 connected
81a56a7beff248cf10392e4615011c997be60732 10.20.123.117:6379@16379 master - 0 1722943143796 5 connected 10923-16383
d7c191caa3c5fb4e73f24c1b035e5c879f46c0a2 10.20.123.115:6379@16379 master - 0 1722943145804 1 connected 0-5460
d8048a51dfce2275c4b4555466cc776ef4afe3ae 10.20.123.116:6380@16380 myself,slave d7c191caa3c5fb4e73f24c1b035e5c879f46c0a2 0 1722943142000 1 connected
2077243c83787a3e78cefbec0fc3d2d094d80fb0 10.20.123.115:6380@16380 slave 81a56a7beff248cf10392e4615011c997be60732 0 1722943144000 5 connected
мне надо добавить два экземпляра 10.20.123.114:6379 и 10.20.123.114:6380 и убрать 10.20.123.115:6379 и 10.20.123.115:6380. то есть заменить 10.20.123.115 на 10.20.123.114


Prompt:
Why is this so slow? Tell me how to find out with torch's bottleneck utility.

```python
class RationalKANLayer(nn.Module):
    def __init__(self, input_dim, output_dim, degree):
        super(RationalKANLayer, self).__init__()
        self.input_dim = input_dim
        self.output_dim = output_dim
        self.degree = degree

        # Numerator coefficients
        self.num_coeffs = nn.Parameter(torch.empty(input_dim, output_dim, degree + 1))
        nn.init.xavier_uniform_(self.num_coeffs)

        # Denominator coefficients (one less than numerator to ensure proper rational function)
        self.den_coeffs = nn.Parameter(torch.empty(input_dim, output_dim, degree))
        nn.init.xavier_uniform_(self.den_coeffs)

        # Ensure the denominator is never zero by adding a small constant
        self.eps = 1e-6

    def forward(self, x):
        # Normalize x to [-1, 1] using tanh
        x = torch.tanh(x)

        # Compute powers of x up to degree
        x_powers = torch.stack([x**i for i in range(self.degree + 1)], dim=-1)

        # Compute numerator and denominator
        numerator = torch.einsum('bid,iod->bio', x_powers, self.num_coeffs)
        denominator = torch.einsum('bid,iod->bio', x_powers[:, :, :-1], self.den_coeffs) + self.eps

        # Compute Padé approximant
        pade_numerator = numerator * torch.cumprod(denominator, dim=-1)
        pade_denominator = torch.cumprod(denominator, dim=-1)
        y = pade_numerator / pade_denominator

        # Sum over input dimension
        y = torch.sum(y, dim=1)

        return y
```


Prompt: Provide step by steps how to configure Meraki network devices such as Firewall , Switches, Access Points , Sensors using  Meraki REST API .  Using Python to leverage this automation is preferable.


Prompt:
	.extern __RO_LIMIT__
	.extern __RW_BASE__
	.extern __ZI_BASE__
	.extern __ZI_LIMIT__

	ldr		r0, =__RO_LIMIT__
	ldr		r1, =__RW_BASE__
	ldr		r3, =__ZI_BASE__

	cmp		r0, r1
	beq		2f

1:
    @ RW 복사 코드 작성
    ldr     r2, [r0], #4        @ Load word from RO section
    str     r2, [r1], #4        @ Store word to RW section
    cmp     r1, r3              @ Compare current address with ZI base
    blo     1b                  @ If not reached ZI base, continue copying

2:
    ldr     r1, =__ZI_LIMIT__
    mov     r2, #0x0
3:
    @ BSS 초기화 코드 작성
    str     r2, [r3], #4        @ Store 0 to BSS section
    cmp     r3, r1              @ Compare current address with ZI limit
    blo     3b                  @ If not reached ZI limit, continue initializing

RO_LIMIT == RW_BASE일 경우 1번 함수를 수행하지 않도록 업데이트해주세요. cortex-m3코드입니다


Prompt: I want 3 containers. each container has 2 halves. the top half is an image and the bottom half is 2 lines of text, one is bold and one is light with a link. I want the entire containers to have round corners. I want the 3 individual containers next to each other in the same row going left to right. I want to be able to see all of them on the screen without having to scroll down. make the 3 containers fit on the same row. make the css a grid


Prompt: how can i make my own physics resolution (NOT detection) aspect of godot using C++?


Prompt:
import re
import os
from multiprocessing import Pool
from tkinter import Tk
from tkinter.filedialog import askopenfilename, asksaveasfilename

def get_sites_from_user():
    sites = []
    while True:
        site = input("Lütfen kaydedilmesini istediğiniz siteleri girin (örn. 'example.com'). Her siteyi yeni satırda yazın ve bittiğinde 'bitti' yazın: ").strip()
        if site.lower() == 'bitti':
            break
        sites.append(site)
    return sites

def process_chunk(data_chunk, allowed_sites_pattern, credentials_pattern):
    output = []
    for line in data_chunk:
        if allowed_sites_pattern.search(line):
            match = credentials_pattern.search(line)
            if match:
                cleaned_line = match.group()
                output.append(cleaned_line)
    return output

def process_file(input_file_path, allowed_sites, output_file_path, num_processes):
    allowed_sites_pattern = re.compile(r'https?://(?:www\.)?(' + '|'.join(re.escape(site) for site in allowed_sites) + r')')
    credentials_pattern = re.compile(r'[\w.-]+@[\w.-]+:\S+')

    with open(input_file_path, 'r', encoding='utf-8') as file:
        lines = file.readlines()

    chunk_size = len(lines) // num_processes
    chunks = [lines[i:i + chunk_size] for i in range(0, len(lines), chunk_size)]

    with Pool(num_processes) as pool:
        results = pool.starmap(process_chunk, [(chunk, allowed_sites_pattern, credentials_pattern) for chunk in chunks])

    with open(output_file_path, 'w', encoding='utf-8') as output_file:
        for result in results:
            for line in result:
                output_file.write(f"{line}\n")

def main():
    Tk().withdraw()  # Tkinter penceresini açma

    allowed_sites = get_sites_from_user()

    input_file_path = askopenfilename(title="Girdi dosyasını seçin")
    if not input_file_path:
        print("Girdi dosyası seçilmedi. İşlem iptal edildi.")
        return

    output_file_path = asksaveasfilename(title="Çıktı dosyasını kaydet", defaultextension=".txt")
    if not output_file_path:
        print("Çıktı dosyası seçilmedi. İşlem iptal edildi.")
        return

    num_processes = os.cpu_count()
    process_file(input_file_path, allowed_sites, output_file_path, num_processes)

if __name__ == '__main__':
    main()

bu python kodunu inceleyin. bundan örnek alın diye paylaştım asıl istediğim
mail:pass olarak çıkaran bu kodu sadece hotmail:passleri taraycak şekilde düzenleyin.
ekstra olarak bir site sormasın hotmail ile eşleşenleri tüm txt dosyasında arasın ve işlemci ram optimizasyonu çok önemli


Prompt:
I will give you a series of Python coding challenges. data that comes out of d.data() changes everytime it is called.
Answers are submitted by wrapping the answer in d.answer().
Answers should ideally be one liners, however if you need to call d.data() twice, that can be on a separate line like below:
data = d.data(95)
Imports can also be on their own lines.

Question 95:

Data contains a large string. If, in the string, you see two integers separated by dashes (5-7) replace
that with the individual numbers in that range (ie 5,6,7). Resubmit the answer with all of the number
ranges expanded. Example "string",9,7,4-6,"apple" becomes "string",9,7,4,5,6,"apple". Submit a single
string containing all the expanded entries.


Prompt:
In end to end test using playwright, to do CRUD operations of user, the setup of user creation is done using api which involves mutliple API calls where the ID of resource creation is passed to another few APIs in which the priviledges are updated but this is in spec layer instead of separate function or class. Refactor the code using best practices by following solid principles and the applicable design pattern. The output should be in typescript.
Example:
test("create admin user and login ", async({request,page}=>{
const res = await request.post("/users/v2/create", createPayload);
expect(res.status()).toBe(201);
const json = await res.json();
const userId = json.id;
const updatedPayload = {...permissionPayload, id}
const res2 = await request.post("/users/v2/permissions", updatedPayload);
expect(res2.status()).toBe(200);
{username, password} = await res2.json()
LoginPage loginPage = new LoginPage(page);
loginPage.login(username, password);
});


Prompt:
from torch_geometric.nn import SAGEConv, to_hetero

class GNNEncoder(torch.nn.Module):
    def __init__(self, hidden_channels, out_channels):
        super().__init__()
        self.conv1 = SAGEConv((-1, -1), hidden_channels)
        self.conv2 = SAGEConv((-1, -1), out_channels)

    def forward(self, x, edge_index):
        x = self.conv1(x, edge_index).relu()
        x = self.conv2(x, edge_index)
        return x

class EdgeDecoder(torch.nn.Module):
    def __init__(self, hidden_channels):
        super().__init__()
        self.lin1 = torch.nn.Linear(2 * hidden_channels, hidden_channels)
        self.lin2 = torch.nn.Linear(hidden_channels, 1)

    def forward(self, z_dict, edge_label_index):
        row, col = edge_label_index
        z = torch.cat([z_dict['user'][row], z_dict['item'][col]], dim=-1)

        z = self.lin1(z).relu()
        z = self.lin2(z)
        return z.view(-1)

class Model(torch.nn.Module):
    def __init__(self, hidden_channels, data):
        super().__init__()
        self.encoder = GNNEncoder(hidden_channels, hidden_channels)
        self.encoder = to_hetero(self.encoder, data.metadata(), aggr='sum')
        self.decoder = EdgeDecoder(hidden_channels)

    def forward(self, x_dict, edge_index_dict, edge_label_index):
        z_dict = self.encoder(x_dict, edge_index_dict)
        return self.decoder(z_dict, edge_label_index)

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

model = Model(hidden_channels=32, data=user_item_hetero_data).to(device)

print(model)

This is the model that i built to predict interaction between users and items. How to improve this model? What else can i do more? Note that there is no features for users


Prompt: create a haxball type of game in python using pygame library


Prompt: You are a Power BI report developer. I need to perform an analysis on my data table. How can I make a distinct count from my MErged column with exception of 8 elements? Create a dax formula


Prompt:
in javascript, please:
Create a scripts/PotteryWheel.js module.
Define a variable in the module to have the value of the primary key for each piece of pottery. It should have an initial value of 1.
Define and export a function named makePottery.
The makePottery function must accept the following values as input (i.e. it needs parameters), in the following order.
Shape of the piece of pottery (e.g. "Mug", "Platter")
Weight of the piece (e.g. 1, 5)
Height of the piece (e.g. 3, 7)
The makePottery function must return an object with the following properties on it.
shape
weight
height
id (increment this value each time the function is invoked)
Checking Your Work
In the main.js module, invoke the makePottery function and provide the required values as arguments. Store the object that gets returned into a variable, and then use console.log() to view the object.

Once you have it working, make 5 pieces of pottery in main.js.
---------------------------------
Define a scripts/Kiln.js module.
Define and export a function named firePottery that is responsible for acting as a kiln.

The function must accept the following values as input (i.e. it needs parameters), in the following order:
An object representing a piece of pottery that was made at the wheel in the makePottery function.
A number specifying the firing temperature of the kiln.

The function must add a new property of fired with the value of true to the object.
The function must add a new property of cracked to the object.
If the temperature of the kiln is above 2200 degrees then cracked property must have a value of true.
If the temperature of the kiln is at, or below, 2200 degrees then cracked property must have a value of false.
After both of the new properties have been added, return the augmented object.

In the main.js module, invoke the firePottery function for each of the 5 pieces of pottery you created. Ensure you provide the required values as arguments. Store the object that gets returned into a variable, and then use console.log() to view the objects and make sure it has the right properties on each.

To check your work, make sure that at least one of your pieces of pottery is fired at a temperature that is too high.
-------------------------------------------


Prompt:
1. Promoting equitable investment distribution:
The paper finds increasing centralization in the aggregate FDI network, with a few countries becoming more dominant over time. Policymakers in less central countries could:

- Develop targeted strategies to attract FDI in specific industries where centralization is decreasing, as this may present opportunities for new entrants.
- Implement policies to enhance local absorptive capacity and technological capabilities to make their country more attractive for foreign investment.
- Foster regional cooperation and integration to create larger markets that can attract more diverse FDI.

2. Industry-specific strategies:
The contrasting patterns between aggregate and industry-level networks suggest policymakers should tailor their FDI strategies by industry:

- In industries showing decreasing centralization, focus on building competitive advantages and niche specializations to attract investment.
- For highly centralized industries, consider policies to facilitate technology transfer and knowledge spillovers from central players.

3. Supporting latecomers and economic catch-up:
The findings on industry sub-networks suggest opportunities for latecomers:

- Policymakers in developing countries could focus on industries showing decreasing core-periphery structures, as these may offer better chances for new entrants.
- Implement policies to support rapid learning and capability building in targeted industries.
- Foster linkages between local firms and foreign investors to accelerate knowledge transfer.

4. Managing environmental impacts:
Given the paper's mention of potential negative environmental impacts from FDI:

- Develop and enforce robust environmental regulations that apply equally to domestic and foreign investors.
- Implement green FDI policies that incentivize environmentally responsible investments.
- Conduct regular environmental impact assessments of FDI projects.

5. Network position awareness for businesses:
Companies can use network analysis insights to inform their international strategies:

- Assess their current and potential network positions in different industries to identify opportunities and risks.
- For latecomers, focus on industries with decreasing centralization for easier market entry.
- For established players, strengthen positions in centralized networks while watching for emerging competitors in decentralizing industries.

6. Balancing centralization and diversification:
Policymakers in central countries should be aware of the risks of over-centralization:

- Maintain diverse economic linkages to reduce vulnerability to shocks.
- Support outward FDI to less central countries to foster more balanced global economic development.

7. Leveraging network analysis for policy design:
The paper demonstrates the value of network analysis in understanding FDI patterns:

- Policymakers could incorporate network analysis tools in their economic planning and FDI strategy development.
- Regular monitoring of country positions in FDI networks could inform adaptive policymaking.

8. Fostering innovation and competitiveness:
The findings on changing industrial leadership suggest policies to support ongoing innovation:

- Invest in R&D and education to maintain competitiveness in centralized industries.
- Support emerging industries where new leaders can potentially emerge.

given the points above write some potential policy implications and practical applications for policymakers, businesses, and other stakeholders in a fluent way. without bullets


Prompt: Using Vue 3 with Pinia and Javascript, show me how to create an infinite scrolling table component. Rows are retrieved using a REST API call in the Pinia store using start and count parameters. The table header should remain fixed as the rows scroll. The available space should. be filled with rows, with additional rows being loaded dynamically as the user scrolls past the bottom of the list.


Prompt:
def modified_ntxent_loss(embeddings1, embeddings2, labels, temperature=0.5):
    """
    Modified NT-Xent loss for image pairs with binary labels.

    Args:
    embeddings1 (torch.Tensor): Embeddings of the first images in the pairs.
    embeddings2 (torch.Tensor): Embeddings of the second images in the pairs.
    labels (torch.Tensor): Binary labels for the pairs (1 for similar, 0 for dissimilar).
    temperature (float): Temperature parameter for scaling.

    Returns:
    torch.Tensor: Computed loss.
    """
    # Normalize embeddings
    embeddings1 = F.normalize(embeddings1, dim=1)
    embeddings2 = F.normalize(embeddings2, dim=1)

    # Compute similarity scores
    similarity_scores = torch.sum(embeddings1 * embeddings2, dim=1) / temperature

    # Compute positive and negative masks
    positive_mask = labels == 1
    negative_mask = labels == 0

    # Compute positive and negative losses
    positive_loss = -torch.log(torch.sigmoid(similarity_scores[positive_mask])).mean()
    negative_loss = -torch.log(1 - torch.sigmoid(similarity_scores[negative_mask])).mean()

    # Combine losses
    loss = positive_loss + negative_loss

    return loss
я использую данную функцию в качестве функции потерь. Задача - сблизить похожие и отдалить не похожие картинки. Какая из функций справится лучше? Эта или обычный ntxent лосс? 1 - матч, 0 не матч, у меня разметка, и я использую все пары в батче


Prompt: I need to excute the same function 'func' for 1000 independent varibales (stored in a list "vars_1000") in Python. The excution time for each variable is unknown, but its range is from 1 min to 30 mins. My machine has 10 cores. Please help me write a code to complete this task as soon as possible.


Prompt:
这段代码的结果全是0%,请修改:"""
时间序列预测(ARIMI)
"""
import pandas as pd
import numpy as np
from statsmodels.tsa.arima.model import ARIMA

# 读取数据
data = pd.read_csv(r'\\192.168.1.218\temp\lijk\中低频日内回测以及样本外净值.csv')
data['日期'] = pd.to_datetime(data['日期'])
data.set_index('日期', inplace=True)

# 设置频率并填补缺失值
data = data.asfreq('D')
data['净值'] = data['净值'].interpolate()

# 计算每日收益率
returns = data['净值'].pct_change().dropna()

# 时间序列预测参数
days = [1, 3, 5, 15, 30]
涨跌幅度 = np.arange(-0.05, 0.05, 0.01)  # 从-5%到5%，步长为1%

# 初始化一个字典来保存结果
结果_arima = {}

for d in days:
    model = ARIMA(returns, order=(5, 1, 0))
    model_fit = model.fit()
    forecast = model_fit.forecast(steps=d)

    概率 = {}

    for i in range(len(涨跌幅度) - 1):
        lower_bound = 涨跌幅度[i]
        upper_bound = 涨跌幅度[i + 1]
        概率[f'{lower_bound:.1%}到{upper_bound:.1%}'] = (
            (forecast > lower_bound) & (forecast <= upper_bound)
        ).mean()

    结果_arima[f'{d}天'] = 概率

# 输出结果
for key, value in 结果_arima.items():
    print(f"{key}：", end="")
    for k, v in value.items():
        print(f"{k}/{v:.2%}；", end="")
    print()


Prompt:
You are tasked with generating a comprehensive French template for pediatric echocardiography reports focused on congenital heart diseases. This template should adhere to French experts recommendations in congenitalheart disease echocardiography, and include all necessary echocardiographic parameters for the specified pathology. Your goal is to create a detailed and structured template that facilitates thorough documentation and ease of understanding for medical professionals.

Begin by creating a template with the following sections:

1. Patient Information:
Create a section for patient demographics and relevant clinical information.

2. If there are parameters such as weight, height, you MUST calculate BSA (Haycock formule) , z-score,  percentiles, in relation to age according to WHO standards.

3. if there are echocardiographic parameters supplied, you must give me the z-scores of these parameters with the norms.

4. Technical Details:
Include a section for the technical aspects of the echocardiography examination.

5. Specific Echocardiographic Parameters:
This is the main body of the report. Use the provided pathology to determine which parameters to include.

Based on the specified pathology, list all relevant echocardiographic parameters recommended by French pediatric echocardiography experts.
This template should follow the recommended segmental analysis as in the following examples:
// normal echocardiography example:
##
- Situs solitus of atria and abdominal organs.
- Atrioventricular and ventriculoarterial concordance.
 - No pulmonary or systemic venous return anomalies.
- Atrioventricular valves of normal morphology and insertion.
 - Left ventricular systolic function preserved EF = 72%.
 - Non-dilated right chambers with preserved function.
 - No PAH.
 - Interventricular septum intact.
- Three aortic sigmoids, normal flow.
- No coronary artery birth anomalies.
- No coarctation.
- Pulmonary arteries and bronchi without anomalies.
- Pulmonary valve opens normally. No pulmonary stenosis.
- Non-dilated IVC.
- Dry pericardium.
- Conclusion : Echocardiography without any particularity today ##.

- If there are echocardiographic parameters use this study to calculate the z-score "Relationship of Echocardiographic Z Scores Adjusted for Body Surface Area to Age, Sex, Race, and Ethnicity: The Pediatric Heart Network Normal Echocardiogram Database.
Lopez L, Colan S, Stylianou M, Granger S, Trachtenberg F, Frommelt P, Pearson G, Camarda J, Cnota J, Cohen M, Dragulescu A, Frommelt M, Garuba O, Johnson T, Lai W, Mahgerefteh J, Pignatelli R, Prakash A, Sachdeva R, Soriano B, Soslow J, Spurney C, Srivastava S, Taylor C, Thankavel P, van der Velde M, Minich L
Circ Cardiovasc Imaging. 2017 Nov;10(11).; 2017 "

Format the template as follows:
- Use clear and concise French medical terminology throughout the template based on the recommended French pediatric echocardiography experts .
- Employ a logical and easy-to-follow structure with numbered sections and subsections.
- Use bullet points for individual parameters or measurements.
- Include blank spaces or lines for entering values or descriptions.
- Ensure that the template is comprehensive while remaining easy to navigate and complete.
- Just give the template without starting with explanations like "Here's a sample pediatric echocardiography report in French adapted for evaluation of a possible ..." or ending with comments like "This model is designed to be complete and easy to use by French-speaking..." .

Ensure that all sections are clearly labeled in French and that the template is ready for immediate use by French-speaking pediatric cardiologists.
case: garçon 5 ans, poids 17,5 kg, taille 108 cm, diamètre VG télédiastolique 35 mm, diamètre oreillette gauche 22 mm, gradient max valve pulmonaire 30 mmHg, Évaluation d'un tronc artériel commun opéré


Prompt:
反潜航空深弹命中 概 率 问题
应用深水炸弹（简称深弹）反潜，曾是二战时期反潜的重要手段，而随着现代军事技术
的发展，鱼雷已成为现代反潜作战的主要武器。但是，在海峡或浅海等海底地形较为复杂的
海域，由于价格低、抗干扰能力强，仍有一些国家在研究和发展深水炸弹反潜技术。
反潜飞机攻击水下目标前，先由侦察飞机通过电子侦察设备发现水下潜艇目标的大致位
置，然后召唤反潜飞机前来进行攻击。当潜艇发现被侦察飞机电子设备跟踪时，通常会立即
关闭电子设备及发动机，采取静默方式就地隐蔽。
本问题采用目标坐标系：潜艇中心位置的定位值在海平面上的投影为原点 𝑃，正东方
向为 𝑌 轴正向，正南方向为 𝑍 轴正向，垂直于海平面向下方向为 𝑎 轴正向。正北方向顺
时针旋转到潜艇航向的方位角记为 𝛽，假定在一定条件下反潜攻击方可获知该航向（见图
1）。
图 1 水平面目标定位误差及潜艇航向示意图
由于存在定位误差，潜艇中心实际位置的 3 个坐标是相互独立的随机变量，其中 𝑌，𝑍
均服从正态分布 𝑂(0,𝜎 2 )，𝑎 服从单边截尾正态分布 𝑂(ℎ 0 ,𝜎 𝑧
2 ,𝑙)，其密度函数为
𝑓 ℎ 0 ,𝜎 𝑧 ,𝑙 (𝑣) =
1
𝜎 z
⋅
𝜙( 𝑣 − ℎ 0
𝜎 𝑧
)
1 − 𝛷( 𝑙 − ℎ 0
𝜎 𝑧
)
(𝑙 < 𝑣 < +∞),
这里 ℎ 0 是潜艇中心位置深度的定位值，𝑙 是潜艇中心位置实际深度的最小值，𝜙 和 𝛷 分
别是标准正态分布的密度函数与分布函数。
将潜艇主体部分简化为长方体，深弹在水中垂直下降。假定深弹采用双引信（触发引信
+定深引信）引爆，定深引信事先设定引爆深度，深弹在海水中的最大杀伤距离称为杀伤半
径。深弹满足以下情形之一，视为命中潜艇：
(1) 航空深弹落点在目标平面尺度范围内，且引爆深度位于潜艇上表面的下方，由触发
引信引爆；
(2) 航空深弹落点在目标平面尺度范围内，且引爆深度位于潜艇上表面的上方，同时潜
艇在深弹的杀伤范围内，由定深引信引爆；
(3) 航空深弹落点在目标平面尺度范围外，则到达引爆深度时，由定深引信引爆，且此
时潜艇在深弹的杀伤范围内。
请建立数学模型，解决以下问题：
题 问题 1 投射一枚深弹，潜艇中心位置的深度定位没有误差，两个水平坐标定位均服从
正态分布。分析投弹最大命中概率与投弹落点平面坐标及定深引信引爆深度之间的关系，并
给出使得投弹命中概率最大的投弹方案，及相应的最大命中概率表达式。
针对以下参数值给出最大命中概率：潜艇长 100 m，宽 20 m，高 25 m，潜艇航向方位
角为 90 ∘ ，深弹杀伤半径为 20 m，潜艇中心位置的水平定位标准差 𝜎 = 120 m，潜艇中心
位置的深度定位值为 150 m.
题 问题 2 仍投射一枚深弹，潜艇中心位置各方向的定位均有误差。请给出投弹命中概率
的表达式。
针对以下参数，设计定深引信引爆深度，使得投弹命中概率最大：潜艇中心位置的深度
定位值为 150 m，标准差 𝜎 𝑧 = 40 m，潜艇中心位置实际深度的最小值为 120 m，其他参
数同问题 1。
题 问题 3 由于单枚深弹命中率较低，为了增强杀伤效果，通常需要投掷多枚深弹。若一
架反潜飞机可携带 9 枚航空深弹，所有深弹的定深引信引爆深度均相同，投弹落点在平面上
呈阵列形状（见图 2）。在问题 2 的参数下，请设计投弹方案（包括定深引信引爆深度，以
及投弹落点之间的平面间隔），使得投弹命中（指至少一枚深弹命中潜艇）的概率最大。以论文方式的摘要


Prompt: 在尽可能不依赖任何高级定理的情况下，用简单的方法证明，当n足够大时，n以内的合数比质数多。


Prompt:
描述

蚂蚁王国有N座洞穴，编号从1到N，总共有M条可双向通行的道路连接这些洞穴。因为是蚂蚁们的世界，道路比较特殊，有一些是泥土，有一些可能是树枝，所以道路的承重能力并不相同。

现在有S只大力士蚂蚁，负责在这些洞穴之间搬运粮食。

你作为蚂蚁世界的工程师，需要分析出来如何在不超过道路承重的情况下，在给出的起点与终点间搬运最大重量的粮食。

输入描述

第一行包含三个整数N、M、S，其中 0 < N < 100000，0 < M < 500000，0 < S < 30000。

接下来M行，每行包含三个整数x、y、z，表示从x号洞穴到y号洞穴有一条限重为z的道路。其中x≠y，0 ≤ z ≤ 100000，并且两座洞穴之间可能会有多条道路。

接下来S行，每行包含两个整数u、v，表示每个大力士蚂蚁需要搬运粮食的起始洞穴与目的洞穴。其中u≠v。

输出描述

输出共有S行，每行一个整数，表示对于每个大力士蚂蚁可搬运的最大重量。如果给出的起始洞穴和目的洞穴没有道路可达，输出 -1。

用Python写代码给我


Prompt: Every morning Aya goes for a $9$-kilometer-long walk and stops at a coffee shop afterwards. When she walks at a constant speed of $s$ kilometers per hour, the walk takes her 4 hours, including $t$ minutes spent in the coffee shop. When she walks $s+2$ kilometers per hour, the walk takes her 2 hours and 24 minutes, including $t$ minutes spent in the coffee shop. Suppose Aya walks at $s+\frac{1}{2}$ kilometers per hour. Find the number of minutes the walk takes her, including the $t$ minutes spent in the coffee shop.


Prompt:
 How many hops, based on the number of vertices n, does it take in the worst case to route a message between any two nodes?

Network type: Watts-Strogatz network (p=0, k = 3)


Prompt: x2 +(ag) + 2  X(s)y2 +(aq) + 2e  Y(s)E = 1.84 VE = 0.35 VWhich pair of species will react under standard conditions at 25 \deg C? X and Y x2 + and y2 + X and Y2 + x2 + and Y" Provide the answer in detail


Prompt: дана плотность вероятностей  f(x)= 0 при х меньше или равно -2, х больше 1 и 2/9(х+2)*(1-х) при -2 меньше х и 1 больше или равно х. Найти коэффециент эксцесса


Prompt:
参数：
K	受入口集合：K = {A0,W0...A7}；
S	站台集合：S={1,2,3,4,5}
R	路线集合
P	便次数集合∈{1,2,3,4,6,9,19}
TW	时间窗集合
Wk	受入口k的第w个时间窗：∀k∈K。
Q	货量
T	操作时间
v	车辆行驶速度 v=30km/h

决策变量：
Xr,p,k,s= {0,1}
(r∈ R, p ∈ P, k ∈ K，s∈ S)	表示路线r便次p在受入口k的s站台卸货，0为不是，1为是
Yr,p,k,s,w= {0,1}
(r∈ R, p ∈ P, k ∈ K，s∈ S,w∈Wk)	表示路线r的便次p在受入口k的站台s使用第w个时间窗，0为不使用，1为使用。
Tr,p,k,s
(r∈ R, p ∈ P, k ∈ K，s∈ S)	路线r便次p在k受入口s站台的操作时间
startr,p,k,s
(r∈ R, p ∈ P, k ∈ K，s∈ S)
	表示路线r的第p次运输在受入口k的s站台开始卸货时间
按照如上参数与决策变量，针对下述约束条件，输出数学公式：
约束：同一个受入口的路线便次中，优先让便次数相同的路线便次放在同一个受入口站台下，如果没有相同车次的，考虑摆放车次为整数倍的路线


Prompt: Alberto a character in a 2d platformer can shoot fireballs to eliminate enemies by pressing B and jump 3 spaces high by pressing A. He can also clear a distance of 4 spaces in horizontal distance with the jump. He can duck by pressing R and walk with the control stick. He is trying to reach the other side of a huge pit. He sees a platform 5 spaces to his left 3 spaces in the air. On the other side there is a platform over the pit with a 2 space gap horizontally that would lead into the abyss. the same platform is on the same vertical level as him. on the platform is an enemy with a one space width and height. at the end of the platform there is an eight space gap horizontally however there is a platform between the gap 3 spaces above and 1 space away horizontally from the enemy platform. past that is normal land 2 spaces below with no horizontal gap. Finally there is a small pit after the land part that is two spaces wide and one space high. Every platform mentioned is 7 horizontal spaces long. 1. what is the least amount of times the player controlling alberto can press A to reach the other side of the huge pit? 2.  What is the difference in height of the two sides of the huge pit? 3. If alberto wants to reach the end of the right side without pressing B or R how many times is necessary to press A? 4. how many horizontal spaces wide is the huge pit?


Prompt:
Α. 60.828
Β. 14.696
C. 22.991
D. 65.027
To test the effectiveness of a business school preparation course, 8 students took a general business test before and after the course. The results are given below.
Exam Score
Exam Score
Student
1
2
3
4
5
6
7
8
Before Course (1) After Course (2)
530
690
910
700
450
820
820
630
670
770
1,000
710
550
870
770
610
The value of the standard error of the difference scores is


Prompt:
.- Un banco está entregando un crédito en 8 cuotas semestrales a una tasa de interés nominal de un 19% (capitalización semestral)
Si usted quiere pedir UF 500:
a)	Calcule el valor de cada cuota


Prompt: 体重68kg, 体脂肪率14%, 今日の歩数7000歩, 今日の摂取エネルギー2152kcal。ダイエットしたい。1.5ヶ月で65kg, 体脂肪率11%にしたい。フィットネスバイクで110kcal消費した。今日はあとどれくらいやれば良い？


Prompt: Какая примерно масса будет у деревянного домика с габаритами 140 ширина, 275 высота, 230 длина


Prompt:
Construct by hand a perceptron which correctly classified the following data; use
your knowledge of plane geometry to choose values for the weights w0, w1, w2.
Training Example x1 x2 Class
a 0 1 −𝟏
b 2 0 −𝟏
c 1 1 +�


Prompt:
Vào ngày 01/01/X1 công ty M mua 35% cổ phần của công ty C bằng TGNH là 25 tỷ đồng, giá trị ghi sổ và giá trị hợp lý của tài sản và nợ phải trả của công ty C được trình bày trong bảng bên dưới. Tại thời điểm này, công ty có tình hình sau (đơn vị tính: tỷ đồng).

Báo cáo tình hình tài chính

Ngày 01/01/X1

Giá trị ghi sổ

Giá trị hợp lý

Tài sản ngắn hạn

30

40

Tài sản dài hạn

50

50

Cộng

80

Nợ phải trả

10

10

Vốn góp của chủ sở hữu

50

Lợi nhuận sau thuế chưa phân phối

20

Cộng

80

Thuế suất thuế TNDN là 20%, thu nhập đến từ giao dịch mua cổ phần của công ty C được trình bày trên báo cáo Kết quả hoạt động hợp nhất của công ty M là

3 tỷ đồng

không ảnh hưởng

0 tỷ đồng

2,3 tỷ đồng


Prompt: 如何证明拉格朗日中值定理


Prompt: A tortoise is walking away from me at 2km/h. It is 100m away from me. I target and shoot an arrow at the tortoise. The arrow moves 100m/second. How long until the arrow reaches the tortoise?


Prompt: Consider an inclusion f: Z -> Q. Is it an epimorphism in Ring?


Prompt: 对于公式公式\sum\limits_{t = 1}^q {\sum\limits_{z \in {N^t}}^{} { - \log \frac{{\exp \left( {{{\bf{C}}{tz}}} \right)}}{{\sum\nolimits{l \ne t}^q {\exp \left( {{{\bf{C}}_{tl}}} \right)} }}} }它的收敛性证明


Prompt:
Fill the code

```
class CrossEntropyFunction(Function):
    @staticmethod
    def forward(ctx, activations, target):
        ### YOUR CODE HERE ###
        ######################
        ### YOUR CODE HERE ###
        pass

    @staticmethod
    def backward(ctx, grad_output):
        ### YOUR CODE HERE ###
        ######################
        ### YOUR CODE HERE ###

class CrossEntropy(nn.Module):
    def __init__(self, ):
        super().__init__()
        self.func = CrossEntropyFunction.apply

    def forward(self, activations, target):
        return self.func(activations, target)
```


Prompt: There's a serious problem with the clock on the village tower: for a reason not yet understood by the population, the clock stops for one minute every ten minutes. Can you guess how long it takes the minute hand to go around the clock?


Prompt:
In a unique archery competition at IIIT Bhagalpur, two archers compete to score the highest points. The scoring system allows scores to exceed the usual maximum of 10.

You are given arrays  and  containing the scores for Archer 1 and Archer 2 respectively for  shots. Your task is to determine the winner of the competition.

If Archer 1 scores more points than Archer 2, print "one".
Otherwise, print "two".
Note: Print carefully as verdict will be case sensitive It is guranteed that there is no draw between archers

Input Format

First line contain a single integer
Next two lines, each containing  integers: the first line represents the scores for Archer 1, and the second line represents the scores for Archer 2.
Constraints

0<score<10^100   write c++ code considering range of score


Prompt: If a test to detect a disease whose prevalence is 1/1000 has a false positive rate of 5%, what is the chance that a person found to have a positive result actually has the disease, assuming that you know nothing else about the person's symptoms or signs?


Prompt: Approximate the derivative with respect to time of the distance between Earth and Mars at closest approach, be quantitative, answer in m/s


Prompt:
用C++写：
题目描述
第一行输入一个很大的正整数 a
。

第二行输入一个一位数 b
。

输出 a+b
。

输入格式
共两行。

第一行，一个很大的正整数 a
。

第二行，一个一位数 b
。

输出格式
仅一行，一个正整数。

样例输入
12345
8
样例输出
12353
数据范围
记 n
 为 a
 的位数。

对于 100%
 的数据，保证 2≤n≤100
 且 1≤b≤9
。
用char数组储存单个数字组成的多位数，再用-'0'的方式转换为int类型的数组，并用for，if，else，并且用strlen来计算char数组的长度来做for循环的次数，不能用自定义函数和系统函数。


Prompt: Call a positive integer \( x \) with non-zero digits \textit{fruity} if it satisfies \( E(x) = 24 \) where \( E(x) \) is the number of trailing zeros in the product of the digits of \( x \) defined over the positive integers. Determine the remainder when the 30th smallest \textit{fruity} number is divided by 1000. (Trailing zeros are consecutive zeroes at the end of a number.)


Prompt:
For a finite set A of real numbers, we define Π(A) to be the product of all elements
in A. For example, Π({−2, 3, π, 5}) = (−2)· 3 · π · 5 = −30π. Additionally we define
Π(∅) = 1.
(a) Define Σ = {Π(A) mod 12 | A ⊆ {1, . . . , 10}}. Determine whether Σ is closed
under “addition modulo 12”. Justify your answer. (5 marks)
(b) Find the number of subsets A ⊆ {1, . . . , 100} such that Π(A) is not divisible
by 5. Justify your answer. (5 marks)
(c) Find the number of subsets A ⊆ {1, . . . , 100} such that Π(A) is not divisible
by 8. Justify your answer. (10 marks)


Prompt:
Answer the following question using arrangements with repetition, permutations, or combinations. Be sure to explain why the particular counting technique applies to the problem.
The President must assign ambassadors to eight different foreign embassies. From a pool of eleven candidates, how many different diplomatic teams can she form?
Question content area bottom
Part 1
Determine the appropriate counting technique. Choose the correct answer below.
A.
Combinations should be used because no item may be selected more than once and the order does not matter.
B.
Arrangements with repetition should be used because we make selections from a group of choices.
C.
Permutations should be used because we make selections from a group of choices.
D.
Arrangements with repetition should be used because no item may be selected more than once and the order matters.
E.
Permutations should be used because no item may be selected more than once and the order matters.
Part 2
Calculate how many different diplomatic teams are possible.

enter your response here (Type a whole number.)


Prompt:
import numpy as np
import re

def generate_q_vectors(q_magnitudes, num_vectors_per_magnitude=5):
    """生成给定模长的q向量，确保q=0时有一个明确的向量"""
    q_vectors = []
    # 明确添加q=0的向量
    q_vectors.append(np.array([0, 0, 0]))
    for q in q_magnitudes[1:]:  # 跳过0，因为已经添加
        for _ in range(num_vectors_per_magnitude):
            direction = np.random.normal(size=3)
            direction /= np.linalg.norm(direction)
            q_vectors.append(q * direction)
    return np.array(q_vectors)

def calculate_structure_factors(atoms1, q_vectors, box_dimensions, atoms2=None):
    """计算结构因子，考虑周期性边界条件"""
    structure_factors = np.zeros(len(q_vectors), dtype=np.complex128)
    N1 = len(atoms1)
    N2 = len(atoms2) if atoms2 is not None else N1
    atoms2 = atoms2 if atoms2 is not None else atoms1

    # 应用周期性边界条件
    def pbc_diff(a, b, box):
        return a - b - box * np.round((a - b) / box)

    for i, q in enumerate(q_vectors):
        if np.allclose(q, [0, 0, 0]):
            # 对于q=0，结构因子直接设为(N1 * N2)，这里假设每个原子对都贡献1
            structure_factors[i] = N1 * N2
        else:
            # 计算所有原子对之间的差值
            diffs = pbc_diff(np.repeat(atoms1[:, np.newaxis, :], N2, axis=1),
                             np.repeat(atoms2[np.newaxis, :, :], N1, axis=0),
                             box_dimensions)
            # 计算相位
            phases = np.exp(1j * np.tensordot(diffs, q, axes=([2], [0])))
            # 对于每个q向量，sum over all atoms
            S = np.sum(phases, axis=(0,1))
            structure_factors[i] = S

    return structure_factors / (N1 * N2)

# 存储不同原子类型的坐标
atom_coordinates = {
    'Si': [],
    'O': [],
    'Na': []
}

# 存储结构因子
structure_factors = {
    'Si-Si': None,
    'O-O': None,
    'Na-Na': None,
    'Si-O': None,
    'Na-Si': None,
    'Na-O': None
}

# 初始化N1和N2为None，在计算结构因子时更新
N1, N2 = None, None

# 生成q向量
q_magnitudes = np.linspace(0, 8, 1000)
q_vectors = generate_q_vectors(q_magnitudes)

# 读取原子坐标
with open("wrapped_1.xyz", 'r', encoding='utf-8') as file:
    lines = file.readlines()
    n_particles = int(lines[0].strip())
    lattice_line = lines[1].strip()
    match = re.search(r'Lattice="([\d.\s]+)"', lattice_line)
    if match:
        lattice_str = match.group(1)
        lattice_params = list(map(float, lattice_str.split()))
        box_dimensions = np.array([lattice_params[0], lattice_params[4], lattice_params[8]])
    else:
        print("在该行中未找到晶格参数：", lattice_line)
        exit()

    for i in range(2, n_particles + 2):
        line = lines[i].strip().split()
        symbol, x, y, z = line
        x, y, z = map(float, [x, y, z])
        if symbol in atom_coordinates:
            atom_coordinates[symbol].append([x, y, z])
        else:
            print(f"未知原子类型：{symbol}")

# 计算结构因子
for key1 in atom_coordinates:
    for key2 in atom_coordinates:
        atoms1 = np.array(atom_coordinates[key1])
        atoms2 = np.array(atom_coordinates[key2])
        sf = calculate_structure_factors(atoms1, q_vectors, box_dimensions, atoms2)
        structure_factors[f"{key1}-{key2}"] = sf
        # 更新N1和N2
        N1, N2 = len(atoms1), len(atoms2)

# 输出结果
for key, value in structure_factors.items():
    with open(f"{key}_structure_factors.txt", 'w', encoding='utf-8') as file:
        file.write("#q S(q)\n")
        for q, s in zip(q_magnitudes, value):
            if q == 0:
                file.write(f"{q} {N1*N2}\n")  # 对于q=0，写入理论值
            else:
                file.write(f"{q} {s.real}\n")  # 只输出实部

print('处理完成。')
为什么这个代码的出来的结果是一种梯度降低的


Prompt: How many footballs could fit in the Burj Khalifa? Explain your reasoning logically with a step by step breakdown using a rational chain of thought process.


Prompt: Write an extremely efficient(!) function fib(n), which works with very large values for n!


Prompt: Find Re(Li2(i))


Prompt:
The degree sequence of a simple graph is the sequence of the degrees of the vertices in the graph in decreasing order. Which of the following sequences cannot be the degree sequence of any graph?

 6, 6, 5, 3, 3, 3, 1
 7, 6, 4, 3, 3, 3, 1, 1
 3, 2, 2, 1, 0
 2, 2, 2, 2, 2


Prompt: make 45=MC, using E=MC^2


Prompt: 选择函数用梯形、辛普森和Gauss-Lobatto三种方法计算积分。通过改变梯形法的步长以及辛普森法和Gauss-Lobatto方法的精度要求，比较这些方法的结果和计算效率。问题分析概括为200字左右


Prompt: A cask contains a mixture of 49 litres of wine and water in the proportion 5: 2. How much water must be added to it so that the ratio of wine to water maybe 7 : 4?


Prompt: 你是一名教学经验丰富的小学数学老师，请回答：哪两个数的最小公倍数是36，请列出所有的组合


Prompt:
# 『FLA - I』歌静河

## 题目背景

**[English statement.](/problem/U458237) You must submit your code at the Chinese version of the statement.**

> You can cry
>
> Drinking your eyes
>
> Do you miss the sadness when it's gone
>
> And you let the river run wild
>
> And you let the river run wild

— _The River_ by _AURORA_

## 题目描述

秋有两个长度为 $n$ 且仅包含 `#` 和小写字母的字符串 $a,b$。

这两个字符串总共包含 $m$ 个 `#`，秋打算执行 $m$ 次操作，用小写字母把两个字符串中所有的 `#` 都替换掉。对于第 $i$ 次操作，他要在 $a,b$ 中选择一个字符串，将这个字符串中从左向右数第一个 `#` 替换为第 $(i-1) \bmod 26 +1$ 个小写字母。**他不能选择不包含 `#` 的字符串。**

秋有一位热爱艺术的好友，他想最小化执行完 $m$ 次操作后的字符串 $a$ 的字典序。秋想，编程也是一种艺术，这样的话，他们的心也会更近一些。

## 输入格式

第一行输入两个正整数 $n,m$。

第二行输入一个长度为 $n$ 的字符串 $a$。

第三行输入一个长度为 $n$ 的字符串 $b$。

## 输出格式

输出一行一个字符串，表示执行 $m$ 次操作后能够得到的字典序最小的 $a$。

## 样例 #1

### 样例输入 #1

```
8 2
th#nkyou
#estwish
```

### 样例输出 #1

```
thankyou
```

## 样例 #2

### 样例输入 #2

```
16 5
##soluteradian#e
your#awnwillcom#
```

### 样例输出 #2

```
absoluteradiance
```

## 样例 #3

### 样例输入 #3

```
40 45
hhuj#pzr#k#mmd#z##y#o####m##j##tga#k#t#g
m########be#######vf##a#j###ypuf###pr###
```

### 样例输出 #3

```
hhujapzrakbmmdczdeyfoghijmkljmntgaokptqg
```

## 提示

**「样例解释 #1」**

第一次操作选择字符串 $a$，将 $a$ 中的 `#` 替换为第 $(1-1) \bmod 26+1=1$ 个小写字母，即 `a`；第二次操作选择字符串 $b$，将 $b$ 中的 `#` 替换为第 $(2-1) \bmod 26+1=2$ 个小写字母，即 `b`。最终的字符串 $a$ 即为 `thankyou`，可以证明这是执行 $m$ 次操作后能得到的字典序最小的 $a$。

**「数据范围」**

|测试点编号|$n \leq$|特殊性质|
|:-:|:-:|:-:|
|$1 \sim 3$|$10$|无|
|$4 \sim 6$|$10^5$|有|
|$7 \sim 10$|$10^5$|无|

- 特殊性质：保证 $a,b$ 中存在一个不包含 `#` 的字符串。

对于所有测试数据，$1 \leq n \leq 10^5$，$1 \leq m \leq 2n$，字符串 $a,b$ 仅包含字符 `#` 和小写字母。c++


Prompt:
矩形面积 II
作者: Turbo
时间限制: 1s
章节: 线段树
问题描述
我们给出了一个（轴对齐的）矩形列表 rectangles 。 对于 rectangle[i] = [x1, y1, x2, y2]，其中（x1，y1）是矩形 i 左下角的坐标，（x2，y2）是该矩形右上角的坐标。

找出平面中所有矩形叠加覆盖后的总面积。 由于答案可能太大，请返回它对 10 ^ 9 + 7 取模的结果。

示例 1：

输入：[[0,0,2,2],[1,0,2,3],[1,0,3,1]]

输出：6

解释：如图所示。

示例 2：

输入：[[0,0,1000000000,1000000000]]

输出：49

解释：答案是 10^18 对 (10^9 + 7) 取模的结果， 即  49 。

输入说明
首先输入矩形列表 rectangles的长度n

然后输入n行，每行表示一个矩形的坐标[x1, y1, x2, y2]

1 <= n <= 50

0 <= x1, y1, x2, y2 <= 10^9

矩形叠加覆盖后的总面积不会超越 2^63 - 1 ，这意味着可以用一个 64 位有符号整数来保存面积结果。

输出说明
输出结果  使用C++编程


Prompt: Tính tổng S các nghiệm của phương trình (2cos x + 5)(sin^4 (x/2) - cos^4 (x/2)) + 3 = 0 trong khoảng (0,27)


Prompt: Find the total area bounded by the graphs of f left parenthesis x right parenthesis equals 3 x cubed minus x squared minus 10 x and g left parenthesis x right parenthesis equals short dash x squared plus 2 x.


Prompt: Ipotizzando un interesse al 7% annuo, su uno scenario di 35 anni partendo con 0, 10000, 20000 o 30000 che versamento mensile necessito per avere 1 milione di euro reali? Cioè al netto dell’inflazione (ipotizzata ad un 3% annuo) e della tassazione (ipotizzando un 26% sul risultato finale)


Prompt: Let a(n) be number of (d_1,...,d_n+1) ,where d_i >=0 and <=9 , such that |d_i - d_(i+1)|=1 for all i. Find a formula for a(n)


Prompt: 对于一个自定义的线段图形，由起始点，终点，线宽三个属性构成，在已知这三个属性的情况下，如何判断其他的自定义线段图形被一个线段图形完全覆盖，使用数学方法判断，C++描述


Prompt:
Given: \begin{align}\label{k1}

\sigma_2(n)=\sum_{i=1}^ni^2=\sum_{i=1}^n\sum_{j=1}^i(2j-1).

\end{align}

This double sum can be interpreted as a single Lebesgue sum:

\begin{align}\label{mu}

\sigma_2(n)=\sum_{j=1}^n(2j-1)\mu_2(j).

\end{align}

determine tha form of the function $\mu_2(j)$


Prompt: Is additive group on rational numbers isomoprhic to multiplicative group on positive rational numbers?


Prompt:
9.	21.12 Gun control. A March 2018 Gallup survey asked a sample of 1041 adults if they wanted stricter laws covering the sale of firearms. A total of 697 of the survey respondents said “yes.” Although the samples in national polls are not SRSs, they are similar enough that our method gives approximately correct confidence intervals.
a.	Say in words what the population proportion p  is for this poll.
b.	Find a 95% confidence interval for p.


Prompt: If a man sits on a small boat in the middle of the ocean and an ICBM passes overhead, how much of the earth's circumference will the missile have traversed while in view of the man.


Prompt:
X Закрыть тест
B5
Дано натуральное число. На каждом ходе из него либо вычитают утроенную сумму цифр, либо прибавляют утроенную сумму цифр, так, что полученное число остается натуральным.
а) Могло ли из числа 65 получиться число 41?
6) Могло ли из числа 65 получиться число 43?
в) Какое наименьшее двузначное число можно получить из 65?
Выберите один ответ
• a) да; 6) да; в) 10
а) нет; 6) да; в) 11
• a) да; 6) нет; в) 11


Prompt:
题目描述
秋有两个长度为
�
n 且仅包含 # 和小写字母的字符串
�
,
�
a,b。

这两个字符串总共包含
�
m 个 #，秋打算执行
�
m 次操作，用小写字母把两个字符串中所有的 # 都替换掉。对于第
�
i 次操作，他要在
�
,
�
a,b 中选择一个字符串，将这个字符串中从左向右数第一个 # 替换为第
(
�
−
1
)

mod

26
+
1
(i−1)mod26+1 个小写字母。他不能选择不包含 # 的字符串。

秋有一位热爱艺术的好友，他想最小化执行完
�
m 次操作后的字符串
�
a 的字典序。秋想，编程也是一种艺术，这样的话，他们的心也会更近一些。

输入格式
第一行输入两个正整数
�
,
�
n,m。

第二行输入一个长度为
�
n 的字符串
�
a。

第三行输入一个长度为
�
n 的字符串
�
b。

输出格式
输出一行一个字符串，表示执行
�
m 次操作后能够得到的字典序最小的
�
a。


Prompt:
문제
You have just moved into a new apartment and have a long list of items you need to buy. Unfortunately, to buy this many items requires going to many different stores. You would like to minimize the amount of driving necessary to buy all the items you need.

Your city is organized as a set of intersections connected by roads. Your house and every store is located at some intersection. Your task is to find the shortest route that begins at your house, visits all the stores that you need to shop at, and returns to your house.

입력
The first line of input contains a single integer, the number of test cases to follow. Each test case begins with a line containing two integers N and M, the number of intersections and roads in the city, respectively. Each of these integers is between 1 and 100000, inclusive. The intersections are numbered from 0 to N-1. Your house is at the intersection numbered 0. M lines follow, each containing three integers X, Y, and D, indicating that the intersections X and Y are connected by a bidirectional road of length D. The following line contains a single integer S, the number of stores you need to visit, which is between 1 and ten, inclusive. The subsequent S lines each contain one integer indicating the intersection at which each store is located. It is possible to reach all of the stores from your house.

출력
For each test case, output a line containing a single integer, the length of the shortest possible shopping trip from your house, visiting all the stores, and returning to your house.

It is known that this problem requires using dijkstra algorithm. However, I'm not sure if I must use TSP or not. Should I? Or any good ideas that can avoid using TSP?


Prompt: Пусть у нас есть набор данных с 12 объектами и мы хотим разбить его на два подмножества размера 6 (и порядок на подмножествах не важен, то есть мы не различаем два полученных подмножества, они для нас равнозначны). Сколькими способами это можно сделать?


Prompt: какой силой должны обладать электромагниты в магнитных подшипниках шпинделя, чтобы выдержать нагрузку от фрезерования стали?


Prompt:
If  cot theta is 10/11
Find cos theta


Prompt:
You are going shopping and have prepared
a lot of goods. Information about the products that
you plan to buy is organized in an array
lines. The format of each line is <product> <
unit price> <quantity to purchase>. You can
use any separator. The unit price
and the purchase amount are integers.
You need to calculate the total price for the product and
the total amount you plan to spend.
Return the result as a string without spaces in
the specified format.:
<price for position 1>+<price for position 2> +
<price for item N>= <total
planned expenses>
If the string format is incorrect, just
skip it and move on to the next one. Don
't forget to think through all the possible options.
Examples:
Input data: [apples 5.1, oranges 6.1]
Result: 5 +6=11
Input data: [bread -1;1, milk - 2;1]
Result: 1+2=3


Prompt: Is 9999999900000001 prime


Prompt: I have the total impedance, resistance, capacitance, inductance, and frequency of a circuit supplied by AC power. How can I find the magnitude of the phasor for the total impedance?


Prompt:
A car has a mass of 800 kg and when it is moving, it has a force of 3000N resisting the movement, which doesn't change with speed or slope.

On a flat, level road, the car has a maximum speed of 200 km per hour.


Prompt: Решить используя python: Найти координаты точек пересечения прямой y = Kx + b и окружности радиуса R с центром в начале координат. В каких координатных четвертях находятся точки пересечения? Если точек пересечения нет или прямая касается окружности, выдать соответствующее сообщение.


Prompt:
44．环食指的长度是由单基因决定的从性遗传性状，且食指比环指短在男性中为显性性状，而在女性中则为隐性性
状。在一个理想群体中，男性食指比环指短所占比例为 51％，则在女性中该性状的比例为： (单选)


Prompt: 请你用corrcoef函数求出你自己给出的matlab几个数据间的相关系数


Prompt: как вычислить градусную меру дуги между 2 3д точками в пайтон?


Prompt: if i had invested every month 100$ in QQQ since 1 january 2024, how much would i have invested today and how much would i have had assuming i also invested my dividends in QQQ as well


Prompt: 前序为xyz后序为zyx的二叉树个数


Prompt: Give me an example of how to compute the KL divergence between two poisson distributions


Prompt: 1 Cuộn màng PE khổ 50 cm nặng 4kg độ dày 17mic dài bao nhiêu mét


Prompt:
MHM Corp has an investment project to build an adđtional workshop with the following details:
Investment budget:
- Investment in fixed assests: 500 million VND
- Working capital needs are estimated to be 15% of net revenue from the workshop each year is as follows:
- Year 1: 1,100 million VND
- Year 2: 1,150 million VND
- Year 3: 1,200 million VND
- Year 4: 1,100 million VND
- Annual operating expenses of the workshop:
+ Variable costs are 70% of net revenue
+ Fixed costs (excluding depreciation of fixed assests) are 100 million VND/year
- The fixed assets are expected to be used for an average of 4 years and are depreciated using the straight-line method. The salvage value is negligible.
- The working capital is expected to be gradually recovered and fully recovered at the end of project.
- The company pays income tax at a rate of 20%.
Determine the net present value (NPV) of the project, knowing that the project’s cost of capital is 12% per year


Prompt:
给出集合 [1,2,3,...,n]，其所有元素共有 n! 种排列。

按大小顺序列出所有排列情况，并一一标记，当 n = 3 时, 所有排列如下：

"123"
"132"
"213"
"231"
"312"
"321"
给定 n 和 k，返回第 k 个排列。

示例 1：

输入：n = 3, k = 3
输出："213"
示例 2：

输入：n = 4, k = 9
输出："2314"
示例 3：

输入：n = 3, k = 1
输出："123"

提示：

1 <= n <= 9
1 <= k <= n!

```c++
class Solution {
public:
    string getPermutation(int n, int k) {

    }
};
```


Prompt: Produce an analysis on the power of Hawking radiation of Sagittarius A*


Prompt: Tính lượng calories tiêu thụ của một nam thanh niên 34 tuổi, cao 1m68, nặng 110 kg, làm văn phòng, chưa từng tập gym. Chia marco và viết một mealplan mẫu với mục tiêu giảm 20kg trong 3 tháng tới.


Prompt:
三、(16 分) 已知 $ n $ 阶实矩阵 $ A = (a\_{ij})\_{n \times n} $ 满足 $ \|a\_{ii}\| > \sum\_{j \neq i} \|a\_{ij}\| $（$ i = 1, 2, \cdots, n $）。

(1) 试证：$ \det(A) \neq 0 $；

(2) 若 $ A $ 的全部特征值为 $ \lambda\_1, \lambda\_2, \cdots, \lambda\_n $，求伴随矩阵 $ A\^\* $ 的全部特征值。
请你给我一个python代码来绘图，讲解这个题目。


Prompt:
1부터 6까지의 자연수가 하나씩 적혀 있는 6개의 의자가 있다. 이 6개의 의자를 일정한 간격을 두고 원형으로 배열할 때, 서로 이웃한 2개의 의자에 적혀 있는 수의 합이 11이 되지 않도록 배열하는 경우의 수는?

(단, 회전하여 일치하는 것은 같은 것으로 본다.)


Prompt:
We need 4 hours to dry 8 towels using dryer machine. Machine can dry 7 towels at the same time.

a) How long will it take to dry 8 towels using dryer machine?
b) How long will it take to dry 7 towels using dryer machine?
c) How long will it take to dry 9 towels using dryer machine?

Use LaTeX to highlight important steps


Prompt: if their is a house with 15 entrences and 16 exits, can holds 100 people on each floor, their are 9845 people resting and on each exit 10 people can exit the house at a particular point of time, 7 people can enter the home from each entrance and group of killers enter the house, how many killers will need to enter the house in order to kill all the people in the house the condition is 7 people are different no body know about each other and their are conditons/ posibilities that they might kill each other and a killer can kill ten person at a time if he has precision rate of 100% but its unrealistic calculate each possibilites and reasoning of all possibilities step by step.


Prompt: Which two alphabetic characters are furthest apart on a standard QWERTY keyboard? Use the euclidean distance between the centers of the keys in an actual US-standard physical key layout.


Prompt:
Given are the data and information for two Clusters: Cluster 1 consists of 4 points (P1 - P4) and one centroid (C1), Cluster 2 consists of also 4 points (P5 - P7) and the centroid (C2). The data are: P1(0,2), P2(2,1), P3(4,2), P4(2,3), C1(2,2), P5(5,3), P6(7,5), P7(5,7), P8(3,5) and C2(5,5).

6.1 What is the value of the BCSS (Between Cluster Sum of Squares)? (2 Points)

7.9Question 6.1 What is the value of the BCSS (Between Cluster Sum of Squares)? (2 Points)
4.7Question 6.1 What is the value of the BCSS (Between Cluster Sum of Squares)? (2 Points)
4.2Question 6.1 What is the value of the BCSS (Between Cluster Sum of Squares)? (2 Points)
4.5Question 6.1 What is the value of the BCSS (Between Cluster Sum of Squares)? (2 Points)
3.9Question 6.1 What is the value of the BCSS (Between Cluster Sum of Squares)? (2 Points)
2.9Question 6.1 What is the value of the BCSS (Between Cluster Sum of Squares)? (2 Points)
21.3Question 6.1 What is the value of the BCSS (Between Cluster Sum of Squares)? (2 Points)
4.1Question 6.1 What is the value of the BCSS (Between Cluster Sum of Squares)? (2 Points)
18Question 6.1 What is the value of the BCSS (Between Cluster Sum of Squares)? (2 Points)
6.2 What is the value of the WCSS (Within Cluster Sum of Squares)? (3 Points)

4.7Question 6.2 What is the value of the WCSS (Within Cluster Sum of Squares)? (3 Points)
234.0Question 6.2 What is the value of the WCSS (Within Cluster Sum of Squares)? (3 Points)
21.3Question 6.2 What is the value of the WCSS (Within Cluster Sum of Squares)? (3 Points)
4.2Question 6.2 What is the value of the WCSS (Within Cluster Sum of Squares)? (3 Points)
7.9Question 6.2 What is the value of the WCSS (Within Cluster Sum of Squares)? (3 Points)
18.0Question 6.2 What is the value of the WCSS (Within Cluster Sum of Squares)? (3 Points)
26.0Question 6.2 What is the value of the WCSS (Within Cluster Sum of Squares)? (3 Points)
43.2Question 6.2 What is the value of the WCSS (Within Cluster Sum of Squares)? (3 Points), give the correct answer


Prompt: what would your velocity be after accelerating at 1 G for a year?


Prompt: Solve for x : x^2-x^3=12


Prompt: Ապացուցել, որ n^4_4n բաժանվում է 5_ի


Prompt:
Câu 115a: Một bình khí có áp suất bằng áp suất khí trời (pa=10m H2O) và khối lượng riêng r1=1,2Kg/m3. Nếu khí trong bình bị nén đến áp suất tuyệt đối p2=196.200Pa thì khối lượng riêng r2 của khí lúc này sẽ là:

Câu hỏi 1Select one:

A.
3,6Kg/m3

B.
4,5Kg/m3

C.
1,2Kg/m3

D.
2,4Kg/m3

E.
5,2Kg/m3


Prompt: Generate a continuous affine piecewise linear function that takes in N as the number of pieces. It should be between 0 and 1.


Prompt: Evaluate or approximate the sum of the reciprocals of the squares of the primes.