This script is used to batch modify author information in Git history, rewriting commit records using git filter-branch

The Peking Union Medical Center “4+4” program (4 years of non-medical undergraduate + 4 years of medical PhD), emphasizing interdisciplinary elite training, was exposed in 2025 due to the Dong Xiying incident. Her entry into the program allegedly leveraged family background (a lineage of medical professionals/researchers), raising questions about her educational qualifications and allegations of plagiarism. This highlights a conflict between the program’s elitist admissions practices and fairness, alongside unresolved issues regarding shortened training periods and supervised practice concerns.

Recently, global stock markets have experienced sharp volatility, largely due to new comprehensive tariff measures announced by U.S. President Donald Trump, sparking market concerns about a global trade war and economic recession.

I’m tired of colorful, flashy homepages; I suddenly want to go for a minimalist style and design a Chinese ink-wash theme

I always wanted to buy a solid blue-chip stock and just leave it, but I never managed to do it. When it fell, I didn’t add to my position, and when it rose, I sold it off.

Finding suitable blue-chip stocks is troublesome; it’s better to choose a broad index and buy an ETF. The current plan is: securities ETF, Hang Seng Tech Index.

This trading strategy has a professional term: left-side dip buying

Please provide the Chinese text you want me to translate. I am ready when you are!

We tested Cursor last month, but due to free tier limitations, we didn’t develop complex features, just simple testing. We noticed that ByteDance also released a similar product at the time, both using the same underlying large language model: Claude-3.5.

ByteDance’s product, Trae, initially launched a Mac version and finally released a Windows version this February. Big company products are just good – you can use them for free without paying, with unlimited access to Claude-3.5, which is a very impressive model.

Artificial intelligence (AI) has undoubtedly been one of the most discussed topics in technology in recent years, especially with its rapid advancements over the past two years. From deep learning and natural language processing to computer vision and automated decision systems, AI applications are constantly emerging. However, despite continuous technological breakthroughs, AI still faces a bottleneck similar to that of Docker before its release – a lack of a killer application to truly ignite the market.

US stocks have three trading periods: pre-market, intra-market, and post-market. The data push logic (to minimize bandwidth usage) sends the full dataset once initially, then pushes incremental updates for all subsequent fields.

Why not use the optimal solution? It involves different project teams, some of which have been live for many years. We are newly integrated, so we can only try to maintain compatibility.