Scientific, engineering, and medical research papers are the backbone of global innovation and progress. They set the future. These documents not only chronicle new discoveries and technological advances but also serve as the primary means for researchers to communicate, validate, and build upon one another’s work. I believe awareness of what research papers are, why they matter, who writes them, and especially how the United States and China compare in research output is more relevant than ever.
A scientific, engineering, or medical research paper is a formal, structured document reporting the results of original research, experimentation, or analysis. Whether the focus is a new material, a medical breakthrough, or a novel algorithm, these papers share a common format to ensure clarity and reproducibility. In 2024, the estimated number of scientific, engineering, and medical research papers published worldwide was about 3.5 million. Research papers all have the same basic format as follows:[1]
This standardized structure is used across disciplines, from biomedical engineering to clinical medicine and theoretical physics, ensuring research can be evaluated and understood by peers. Research papers are important for several reasons:[2]
The typical authors of scientific, engineering, and medical research papers are researchers, scientists, engineers, and clinicians affiliated with universities, research institutes, hospitals, or industry. Authorship is governed by strict criteria. Authors must have contributed to the conception, design, data collection, or analysis. They must help draft or critically revise the paper. All authors must approve the final version and take responsibility for its integrity.
In practice, research papers are often collaborative, with multiple authors from different specialties or even countries. The issue of sharing research knowledge with China has become a political issue in the U.S. The first author listed usually did the most work, the last author is often the senior supervisor, and the corresponding author manages communication with the research journal. The trend toward larger, multi-author teams reflects the increasing complexity and interdisciplinary nature of modern research.
The global landscape of research publication has shifted dramatically in recent years, particularly between the U.S. and China. China is now the world leader in research output. In 2000, 1,076,635 papers were published. Papers by Chinese authors were 43,065, or 4%. In 2024, approximately 3.3 million papers were published. Papers by Chinese authors were 891,000, or 27%.[3] China’s largest share of publications is in engineering, while the U.S. leads in health sciences. As a percentage of total output, 13% of China’s research papers are among the top 10% most cited globally, on par with the U.S. at 12%.[4] In some fields, such as engineering and technology, China’s share of highly cited papers is now higher than the U.S.[5] For the first time, China now has more world-leading scientists (defined by highly cited papers in top journals) than the U.S., 32,511 in China versus 31,781 in the U.S. as of 2024.[6]
Science is increasingly collaborative, with over 30% of high-impact U.S. research involving Chinese scientists and vice versa. This cross-border teamwork has been vital for both countries’ research ecosystems. While China leads in volume, the U.S. remains highly influential, especially in fields like health sciences and artificial intelligence. U.S. research tends to receive more international citations, reflecting its global impact.
In summary, scientific, engineering, and medical research papers are the foundation of progress in science, technology, and healthcare. Authored by diverse, often international teams, these papers document and disseminate new knowledge, guide evidence-based practice, and foster global collaboration. Today, China leads the world in research output, with the U.S. maintaining a strong position in research quality and influence. The dynamic competition and cooperation between these two nations will continue to shape the future of global innovation. I hope the trade wars do not negatively impact U.S. research
Epilogue: I am not a research scientist, but I have had some experience in research writing. The dissertation summarizing the research study for my doctorate, published in 2014, was “THE EFFECT OF CARDIONET HOME TELEMONITORING FOR CONGESTIVE HEART FAILURE PATIENTS: AN OBSERVATIONAL RESEARCH STUDY”. In 2015, I joined the mHealth journal Editorial Board. I have published two papers there. All 50 of my publications are here.
Sources for this blog post.
[1] “Biomedical Engineering,” Penn State University Libraries (2024), https://guides.libraries.psu.edu/c.php?g=318448&p=8995871
[2] Nesrine Saad Farrag Abdel-Hady El-Gilany, “Authorship in Medical Research: What Should Authors Know?,” Journal of Health Science Research (2022), https://jhsronline.com/authorship-in-medical-research-what-should-authors-know/
[3] Dannie Peng, “China Surpasses Us in Tally of Top Scientists for the First Time: Report,” myNEWS (2025), https://www.scmp.com/news/china/science/article/3295011/china-surpasses-us-tally-top-scientists-first-time-report
[4] Ritu Dhand, “Research Pulse: China,” SpringerNature (2024), https://stories.springernature.com/global-research-pulse-china/index.html
[5] Ibid.
[6] Peng, “China Surpasses Us in Tally of Top Scientists for the First Time: Report”.
In this section, I share what I am up to, pictures of the week, what is new in AI and crypto, and more.
I am pleased to announce I have joined the board of the Digital Democracy Project (DDP). DDP is a free civic engagement platform which connects voters with the legislative process. Using the secure Voatz app, registered voters (only in Florida at this time) can express their point of view on the app to tell their legislators their preference on pending bills. Anyone can see how voters expressed themselves and then compare what voters wanted to how legislators voted. I think this is the future.
John,
Your article really opened my eyes as I had no concept or awareness of the importance of magnetic technologies. Indeed, we are in an interconnected world which, beyond government policies and its impacts, effects the manner in which we conduct our daily lives. Simply, thank you…
Joel M. Koblentz
Senior Partner
The Koblentz Group
John,
I just wanted to take a moment to let you know how much I thoroughly enjoy reading your newsletter. Every single time, I find myself learning something new and fascinating from the diverse and in-depth subjects you cover. Your recent blog post on magnets was particularly intriguing!
Jean-Claude Monney
Hybrid Intelligence Advisor
The Monney Group, LLC
Former Chief Knowledge Office at Microsoft
My next presentation will be at the Senior Spectacular Expo in Ridgefield, CT on Saturday, April 26.
Heritage Hills in Somers, NY has invited me back for another talk on AI and Bitcoin. It will be on June 10.
Ridgefield
I love to read books. All the books I have written and the books I have read are in profile. Feel free to view it here. I am currently reading The Gates of Europe – A History of Ukraine by Serhii Plokhy. I don’t read a lot of history books but this one is very interesting.
Last Saturday was a sunny and warm day in Connecticut. My first motorcycle ride for the Spring was to the local grocery store.
The following is from David Sparks (MacSparky). His web site is here.
There’s a rumor that Apple is working on an on-device medical AI. The idea is that your iPhone or Apple Watch could use its onboard silicon to privately analyze your health data and offer recommendations, without sending that sensitive information to the cloud.
The general vibe I’m seeing in response to this rumor is justified skepticism. Plenty of folks out there think there’s no way Apple can pull this off, but I think this is exactly the kind of thing they should be doing. This idea presents an opportunity for Apple.
Apple has been steadily building up its health tech for years. With features like Atrial fibrillation (AFib) detection, ECG, and Fall Detection, they’ve proven they can deliver meaningful health tools. And they’ve done it with an eye toward user privacy and accessible design.
Now, imagine layering a personalized AI model on top of that foundation — something smart enough to notice patterns in your vitals, flag potential concerns, or even offer preventative guidance. And because Apple controls the hardware, they could run that AI model entirely on-device. That means your health data stays private, living only on your phone or watch, not bouncing around in the cloud.
Apple’s unique position here — owning both the hardware and the operating system — gives them access to a depth of personal health data that no off-the-shelf Large Language Model could ever touch. Combine that with their Neural Engine and you have a real opportunity to do something both powerful and private.
This also feels like a moment for Apple to make a statement with “Apple Intelligence.” So far, Apple’s AI initiative has been underwhelming and disappointing. This could be a way for them to reset expectations with something carefully designed, respectful of privacy, and genuinely useful.
Of course, this only works if they get it right. Rushing something half-baked out the door won’t cut it, especially when people’s health (and Apple’s AI reputation) is at stake. But if they take their time and nail the execution, this could be a defining moment for Apple’s AI efforts and one more key feature that saves lives.
I hope the rumor’s true and that Apple gives this the time and resources it deserves. It could be something special.
This week in AI saw major developments across technology, policy, research, and business.
OpenAI launched two new models, o3 and o4-mini, designed for advanced reasoning and efficiency. The o3 model excels at multi-step logic and memory retention, while o4-mini is optimized for low-latency dialogue and task completion, making both ideal for applications on mobile devices and in resource-constrained environments. OpenAI also released GPT-4.1, which features a 128,000-token context window for handling lengthy documents, persistent system fingerprinting for consistent behavior, and improved function calling for software integrations. These updates are particularly significant for industries like law and research that require deep contextual understanding and reliable outputs[5][6].
Google responded by introducing Gemini 2.5 Flash, a streamlined reasoning model for its Gemini app, and expanded access to Gemini Live’s screen-sharing and camera vision tools for Android users. The top-performing model according to LMArena is currently Gemini 2.5 Pro, with ChatGPT 4o and Grok-3 Preview following[6].
A standout research highlight came from Google DeepMind, which unveiled DolphinGemma, a model trained to decode and emulate dolphin vocalizations. This project, developed in collaboration with Georgia Tech and the Wild Dolphin Project, aims to advance understanding of non-human communication systems and could aid marine research and conservation[5][6].
AI’s application in mental health also advanced, with new tools using natural language processing and voice analysis to monitor emotional well-being and detect signs of anxiety or depression. These platforms are being integrated into wellness apps and employee support systems, offering scalable and privacy-focused mental health support[5].
In robotics, humanoid robots participated in a half-marathon in Beijing, demonstrating improvements in real-world navigation and endurance. Their performance, enabled by AI-driven obstacle detection and adaptive movement, highlights the growing potential for AI-powered robots in logistics, disaster recovery, and healthcare[5].
On the policy front, the Trump administration issued new AI memoranda and an executive order to accelerate federal AI adoption and acquisition. Agencies are now required to maximize the use of American AI, appoint Chief AI Officers, and assess AI maturity. High-impact AI use cases must comply with minimum practices, or be discontinued by April 2026. The administration also announced the Stargate Project, a public-private initiative aiming to invest $500 billion in US AI infrastructure by 2029, focusing on data centers, job creation, and maintaining US leadership in AI[1][7].
Nvidia made headlines with plans to build AI supercomputers in Texas and manufacture chips in Arizona, committing $500 billion to US AI infrastructure over the next few years[6][7].
Overall, this week’s developments reflect rapid progress in AI model capabilities, real-world applications, government policy, and infrastructure investment, underscoring AI’s expanding influence across society and industry.
The crypto market experienced a strong rally this week, marked by several significant developments and shifts in sentiment.
Bitcoin surged above $94,000, reaching its highest level in over a month, while Ethereum jumped 13%, helping push the total crypto market capitalization up 6.7% to nearly $2.94 trillion[2][9][11]. This rally was driven by a combination of easing U.S.-China trade tensions, a massive short squeeze that liquidated $545 million in bearish bets, and a technical breakout above key resistance levels[2][9].
Renewed optimism followed comments from U.S. officials suggesting that tariffs on Chinese imports could be reduced soon, which boosted risk appetite across global markets and encouraged capital flows into digital assets[2]. Additionally, President Trump’s clarification that he would not remove Federal Reserve Chair Jerome Powell helped calm concerns about central bank instability[2].
A major technical factor was the market’s breakout from a multimonth falling wedge pattern, signaling a bullish trend reversal. The relative strength index (RSI) also climbed sharply, indicating growing buying momentum[2]. On-chain data revealed a dramatic spike in institutional interest, with Bitcoin ETF net inflows rising 500 times above the daily average, highlighted by a single-day inflow of $917 million on April 23[9].
Divergence signals emerged as a key theme. Bitcoin decoupled from both the U.S. dollar and the NASDAQ index, suggesting it is increasingly viewed as a standalone asset and a potential safe haven amid global economic uncertainty[1]. Long-term Bitcoin holders resumed accumulation, while short-term holders sold off, a pattern often seen before price rebounds[1].
Altcoins also showed signs of recovery. Fewer altcoins hit new yearly lows despite a dip in total market capitalization, indicating waning negative sentiment and the potential for an “altcoin season,” where altcoins outperform Bitcoin[1]. Technical indicators, such as a bearish divergence on the Bitcoin Dominance chart, suggest capital may soon rotate from Bitcoin into altcoins[1].
Other notable news included:
– Kraken launched stock and ETF trading for U.S. crypto users and expanded its derivatives offerings[5].
– Hong Kong approved Ethereum staking ETFs, and Canada is set to launch the first spot Solana ETFs with staking[5].
– MicroStrategy increased its Bitcoin holdings to over 531,000 BTC[5].
– The market remains attentive to upcoming Federal Reserve policy decisions, which could further influence crypto prices[5].
Overall, the crypto market is showing resilience and renewed bullish momentum, fueled by macroeconomic optimism, institutional inflows, and technical signals pointing to further gains for both Bitcoin and altcoins.
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