justify-contentやalign-itemsがcenterのときに両端を見切れさせない 

<ul class="list">
  <li class="item">項目</li>
  <li class="item">項目</li>
  <li class="item">項目</li>
  <li class="item">項目</li>
  <li class="item">項目</li>
  <li class="item">項目</li>
  <li class="item">項目</li>
</ul>

svgフィルターでテキスト縁取り 

<p class="css">CSSで縁取り文字</p>
<p class="svg-dilate">縁取り文字 Dilate</p>
<p class="svg-erode">縁取り文字 Erode</p>

<svg class="for-stroke">
  <filter id="filter-dilate">
    <feMorphology operator="dilate" radius="1" result="DILATED" />
    <feComposite in="DILATED" in2="SourceGraphic" operator="out" />
  </filter>
  <filter id="filter-erode">
    <feMorphology operator="erode" radius="1" result="ERODED" />
    <feComposite in="ERODED" in2="SourceGraphic" operator="xor" />
  </filter>
</svg>

virtualenv 

#instalar
sudo apt-get install python-virtualenv

#creo el entorno
virtualenv -p python3 py3env

#entro al entorno
source py3env/bin/activate

#salgo del entorno
deactivate

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ObjectHook 

/**
 * 全局重写 Object.prototype.hasOwnProperty，实现调用监控。
 */
function hijackGlobalHasOwnProperty() {
    // 1. 备份原生的 hasOwnProperty 方法
    const originalHasOwnProperty = Object.prototype.hasOwnProperty;
    
    if (originalHasOwnProperty.__is_hooked__) {
        console.log("⚠️ hasOwnProperty 已经被 Hook，跳过重写。");
        return;
    }

    // 2. 定义新的监控函数
    function monitoredHasOwnProperty(prop) {
        // 获取当前检查的对象（this 指向被检查的对象）
        // 尝试获取对象名，或使用其字符串表示
        let objectId = t

757. Set Intersection Size At Least Two

You are given a 2D integer array intervals where intervals[i] = [starti, endi] represents all the integers from starti to endi inclusively. A containing set is an array nums where each interval from intervals has at least two integers in nums. For example, if intervals = [[1,3], [3,7], [8,9]], then [1,2,4,7,8,9] and [2,3,4,8,9] are containing sets. Return the minimum possible size of a containing set. 
/**
 * Finds the minimum number of integers needed so that
 * each interval contains at least two chosen numbers.
 *
 * @param {number[][]} intervals - Array of [start, end] intervals
 * @return {number} - Minimum number of integers chosen
 */
var intersectionSizeTwo = function(intervals) {
    // Step 1: Sort intervals
    // - Primary: by end ascending (smaller right boundary first)
    // - Secondary: by start descending (larger left boundary first if ends are equal)
    intervals.sort((a, b)

virtualenv 

# instalar virtualenv

sudo apt-get install python-virtualenv


#crear un entorno virtual para python3

virtualenv -p /usr/bin/python3 py3env


# activar el virtualenv para trabajar ahi adentro

source py3env/bin/activate

#para salir de un entorno virtual 

deactivate


una vez en el entorno virtual puedo instalar pymysql

pip install "pymysql<1.0"

tengo q poner <1.0 porque el python3.4 no soporta f string y da error al instalar.

proxy 

// 定义全局对象，兼容浏览器(window)和Node.js(global)
const globalScope = typeof window !== 'undefined' ? window : globalThis;

/**
 * 批量环境代理函数 (Hook)
 * @param {Array<string>} proxy_array - 需要代理的对象名称数组，例如 ['window', 'location']
 */
function batchProxy(proxy_array) {
    proxy_array.forEach(name => {
        // 1. 获取当前环境中的对象，如果不存在则初始化为空对象
        let target = globalScope[name];
        if (!target) {
            target = {};
            globalScope[name] = target; // 将新建的空对象挂载到全局
        }

Force garbage collection to free up / clean memory 

import gc

## --> here script content or loop-iteration
# clean memory
gc.collect()

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shopifyメモ 

・[Shopify無料テーマ「Dawn」のECサイト参考事例！日本企業の活用例を業界別にご紹介](https://lp.makegift.me/blog/2152/)  
・[[Shopify] ポリシーページをカスタマイズする方法（Debutテーマ）](https://torublog.com/shopify-policy-pages-customize/)

ICWA 

select distinct count(chain_id) as count_wapol, substring(date_of_crash::text,1,4) as crash_date from demog_status ds join chain_main cm on ds.cur_chain=cm.chain_id join crash_wapoldata cw on substring(ds.lpnot,1,11)=cw.lpno where lset_id = 50 group by 2 order by 2;
select distinct count(chain_id) as count_crash_icwa, substring(ci.date_of_crash::text,1,4) as date_of_crash from demog_status ds join chain_main cm on ds.cur_chain=cm.chain_id join crash_icwadata ci on substring(ds.lpnot,1,11)=ci.lp

Adobe Premiere Pro Keyboard Shortcuts

Full list of shortcuts is available via the app and the Adobe website. These are the shortcuts I use most often.
Application		
	Selection Tool	V	
	Track Select Backward Tool	⇧+A	
	Track Select Forward Tool	A	
	Ripple Edit Tool	B	
	Rolling Edit Tool	N	
	Rate Stretch Tool	R	
	Razor Tool	C	
	Slip Tool	Y	
	Slide Tool	U	
	Pen Tool	P	
	Hand Tool	H	
	Zoom Tool	Z	
	Type Tool	T	
	
	Premiere Pro		
			Keyboard Shortcuts...	⌥+⌘+K	
		Quit Premiere Pro	⌘+Q	
		
	File		
		New		
			Project...	⌥+⌘+N	
			Sequence...	⌘+N	
			Bin	⌘+/	

		Open Project...	⌘+O	
		Close	⌘+W	
		Close Project	⇧+⌘+W	
		Save	⌘+S	
		Save As...	⇧+⌘+S

2154. Keep Multiplying Found Values by Two

You are given an array of integers nums. You are also given an integer original which is the first number that needs to be searched for in nums. You then do the following steps: If original is found in nums, multiply it by two (i.e., set original = 2 * original). Otherwise, stop the process. Repeat this process with the new number as long as you keep finding the number. Return the final value of original.
/**
 * @param {number[]} nums
 * @param {number} original
 * @return {number}
 */
var findFinalValue = function(nums, original) {
    // Step 1: Convert nums into a Set for faster lookups.
    // Why? Searching in an array is O(n), but in a Set it's O(1).
    let numSet = new Set(nums);

    // Step 2: Keep checking if 'original' exists in the set.
    // If it does, double it and repeat.
    while (numSet.has(original)) {
        // Found 'original' in nums, so double it
        original = orig

InstallMapMissingComponentKey 

# InstallMapMissingComponentKey

### Definition
|||
|-|-|
|hKey|HKEY\_LOCAL\_MACHINE|
|subKey|\\COMPONENTS\\DerivedData\\VersionedIndex\\_[ServicingStackVersion]_[^1]\\ComponentFamilies\\_[ComponentName\_NonVersioned]_[^2]\\v!_[ComponentVersion]_[^3]|
|Kind|REG_BINARY|
|Name|InstallMapMissingComponentKey|
|Data|00|

### Purpose
This value is written to a ComponentFamilies key when the install map cannot locate the corresponding version information under the Components key.

### Example

```text

DDSSM-DSSS Physical Guided SceneGen

# DDSSM-DSSS Physical Guided SceneGen ## Overview DDSSM-DSSS-Physical-Guided-SceneGen is a research-oriented implementation inspired by the paper *“A film and television dynamic scene generation and special effects synthesis system integrating diffusion model and physical guidance mechanism” by Wenxiao Du and Xupeng Yao*. The system targets the challenges of generating visually compelling, physically consistent, and narratively coherent dynamic scenes for film and television production. :contentReference[oaicite:2]{index=2} Two major components define the framework: - **Diffusion-Driven Scene Synthesis Model (DDSSM)** A multimodal, diffusion-based latent scene generator that iteratively refines noisy latent states into visually detailed and semantically coherent scenes. - **Dynamic Scene Synthesis Strategy (DSSS)** A physics-informed refinement mechanism enforcing realism by embedding motion laws, collision dynamics, and structural constraints throughout generation. Together, these components provide a unified pipeline for synthesizing dynamic scenes that balance creativity with physical correctness. --- ## Core Concepts ### Diffusion-Driven Scene Synthesis Model (DDSSM) DDSSM uses a forward–reverse diffusion process to transform latent representations into high-quality scenes. The forward process gradually injects Gaussian noise into a latent vector, while the reverse process uses a neural network to denoise the representation step by step. Key characteristics include: - A **multimodal encoder** integrating visual, textual, and audio cues (see Figure 2, page 6) to build a unified latent scene space. :contentReference[oaicite:3]{index=3} - A **variational diffusion objective** minimizing reconstruction divergence across the reverse diffusion steps. - A **latent Markov chain** that refines representations by incorporating spatial–temporal structure (Figure 1, page 5). :contentReference[oaicite:4]{index=4} - A **feature refinement mechanism** addressing ambiguities across modalities. This architecture enables the model to generate complex, temporally coherent visual behaviors, such as motion trajectories or special effects dynamics. --- ### Physically-Guided Synthesis Strategy (DSSS) The DSSS module enforces physical plausibility during scene generation. It integrates: - **Gravity constraints** Ensuring objects exhibit proper downward acceleration. - **Momentum and collision laws** Guiding object trajectories and post-collision behavior. - **Structural stability constraints** Maintaining consistent spatial configurations. - **A feedback loop mechanism** Iteratively evaluating and correcting physical errors using: *F(x) = α·C(x) + β·P(x)* (page 7). :contentReference[oaicite:5]{index=5} The feedback loop continuously refines scenes to ensure consistency between visual frames and the physical world. --- ## Multimodal Encoder Design The multimodal encoder (Figure 2, page 6) integrates heterogeneous sources such as: - image streams - audio cues - textual prompts - structural annotations Using multiple Transformer layers, cross-modal attention, and feature stacking, the encoder produces stable and expressive latent codes for downstream diffusion. The model also supports extended multimodal physiological encoders (Figure 4, page 14), which can be incorporated for certain advanced applications. :contentReference[oaicite:6]{index=6} --- ## Model Architecture Summary The full system contains three primary pipelines: ### 1. Multimodal Encoding - Extracts spatial, temporal, and semantic cues. - Aligns modalities through attention integration. - Produces initial latent vector z₀ for diffusion. ### 2. Diffusion-Guided Scene Synthesis - Forward noise injection. - Reverse denoising with physical modifications. - Constraint-based latent refinement. ### 3. Physics-Guided Dynamic Refinement - Ensures consistent movement (e.g., falling, collisions). - Enforces real-world constraints. - Guarantees frame-to-frame temporal coherence. --- ## Applications This project is suited for: - Film & TV special effects generation - Virtual cinematography - Digital scene prototyping - Realistic motion & dynamics simulation - Physically consistent video generation --- ## Limitations While powerful, the system faces constraints: - High computational cost from diffusion processes. - Physiological and motion constraints may reduce creative freedom. (Page 10) :contentReference[oaicite:7]{index=7} - Requires careful tuning of physics–aesthetics balance. --- ## Future Directions Based on the paper’s discussion: - accelerating diffusion steps for real-time use - adaptive physical realism (user-adjustable physical strictness) - richer multimodal integration (speech, depth, optical flow) - hybrid differentiable physics engines --- ## Citation If you find this repository useful, please cite the original authors: > Wenxiao Du and Xupeng Yao. > *A film and television dynamic scene generation and special effects synthesis system integrating diffusion model and physical guidance mechanism.* > Faculty of Art and Design, Qilu University of Technology. --- ## License This implementation is intended for research, education, and prototyping only. 
import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import Optional, Dict, Tuple


# ------------------------------------------------------------
# Helper modules
# ------------------------------------------------------------

class MLP(nn.Module):
    def __init__(self, dim, hidden, out, drop=0.1):
        super().__init__()
        self.net = nn.Sequential(
            nn.Linear(dim, hidden),
            nn.GELU(),
            nn.Dropout(drop),