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Tech & Engineering

Updates every hour. Last Updated: 1-Sep-2025 21:11 ET (2-Sep-2025 01:11 GMT/UTC)

Charge-separated state: Excited-state traps enhancing radio-luminescence of organic scintillators

Science China Press
Peer-Reviewed Publication

Due to the inherent low atomic number of organic materials, their ability to absorb high-energy rays is relatively weak. Coupled with the low utilization rate of excited-state excitons, the radio-luminescence intensity of organic scintillators is generally lower than that of inorganic scintillators. Recently, the research team led by Professor Shuang-Quan Zang from Zhengzhou university innovatively utilized charge-separated (CS) state traps to capture high-energy carriers, significantly enhancing the radio-luminescence intensity of organic scintillators. The related paper was published in National Science Review.

Journal: National Science Review

Refining Siberia’s land cover data: A leap forward for climate science

Chiba University
Peer-Reviewed Publication

Researchers from Chiba University and Nagoya University, Japan, have developed a highly accurate land cover map for Siberia, providing insights into climate change and predictions. Using advanced machine learning techniques and existing multiple land cover maps, they were able to address the significant discrepancies found in the previous datasets. Being one of the world’s most climate-sensitive regions, Siberia’s newly developed map marks a breakthrough, providing critical details crucial for understanding the region’s extreme environmental changes.

Journal: Progress in Earth and Planetary Science
Funder: JSPS KAKENHI

Low-threshold anisotropic polychromatic emission from monodisperse quantum-dots

Science China Press
Peer-Reviewed Publication

This work demonstrates a novel method of manipulating the QDs’ optical properties beyond controlling their size, composition or structure, and reveals great potential for achieving full-color emission using monodisperse QDs.

Journal: National Science Review

Study shows how retinal cells know when to keep their distance

Okinawa Institute of Science and Technology (OIST) Graduate University
Peer-Reviewed Publication

In vertebrate retinas, specialized photoreceptors responsible for color vision (cone cells) arrange themselves in patterns known as the “cone mosaic”. Researchers at the Okinawa Institute of Science and Technology (OIST) have discovered that a protein called Dscamb acts as a "self-avoidance enforcer" for color-detecting cells in the retinas of zebrafish, ensuring they maintain perfect spacing for optimal vision. Their findings have been published in Nature Communications.

Journal: Nature Communications
Funder: Okinawa Institute of Science and Technology Graduate University

Radiation belt electron wisp inside South Atlantic anomaly due to terrestrial VLF transmitter observed by MSS-1

Science China Press
Peer-Reviewed Publication

The South Atlantic Anomaly represents a region within near-Earth space characterized by a significantly weaker geomagnetic field and a higher flux of energetic particles compared to other areas. It is a space weather hazards to Low-Earth-Orbit satellites. There has been evidence that the Very Low Frequency (VLF) waves from the powerful ground VLF radio transmitter in Australia, known as NWC, have the capacity to scatter energetic electrons’ pitch angle in the inner radiation belt. In a paper published in Science China: Earth Sciences, scientists report the initial observation of a 'wisp' precipitation resulted from NWC, an unusual occurrence with peak intensity detected inside the SAA. With the full pitch angle distribution observed via the Macao Science Satellite – 1 at Low-Earth-Orbit, scientists attribute the 'wisp' within the anomaly to a specific pitch angle range just outside the drift loss cone.

Journal: Science China Earth Sciences

The rise of DeepSeek: technology calls for the “catfish effect”

National Center for Respiratory Medicine
Reports and Proceedings

Keywords: Artificial intelligence (AI); DeepSeek; catfish effect; open source; medical applications During the 2025 Chinese Spring Festival, a topic that garnered widespread attention was DeepSeek. On January 20, the Hangzhou-based DeepSeek company released its latest large language model, DeepSeek-R1. This release sent shockwaves through the technology sector and attracted attention from top scientific journals such as Nature and Science (1,2). With its powerful performance and open-source characteristics, DeepSeek-R1 has created substantial pressure on existing artificial intelligence (AI) competitors, exemplifying the “catfish effect” in the AI domain. This concept originates from a classical management theory: Norwegian fishermen placed catfish, a natural predator, in sardine transport tanks, significantly reducing mortality rates by triggering the sardines’ survival instincts. By analogy, in other fields, the introduction of strong competitors often activates industry innovation dynamics. DeepSeek’s emergence has injected new momentum into the AI field, driving rapid technological iteration and innovation.

Journal: Journal of Thoracic Disease

DeepSeek: the “Watson” to doctors—from assistance to collaboration

National Center for Respiratory Medicine
Reports and Proceedings

DeepSeek is an AI platform based on deep learning and natural language processing, featuring core products DeepSeek-R1 and DeepSeek-V3 models. Using efficient Mixture of Experts (MoE) architecture and multimodal data fusion capabilities, it achieves performance comparable to OpenAI's GPT-4o-mini while significantly reducing training costs .

In healthcare applications, DeepSeek rapidly extracts valuable information from massive datasets, providing intelligent information retrieval and analysis solutions that:

- Assist physicians with diagnosis and treatment - Optimize doctor-patient communication - Improve medical efficiency - Supplement professional knowledge - Provide humanized medical interactions - Identify potential blind spots

DeepSeek enhances clinical decision-making efficiency, supports scientific research, optimizes patient management and assists patients with medical decision-making .

However, the platform faces challenges including data quality issues, algorithm stability and accuracy concerns, multimodal data fusion problems, lack of automated information collection, and dynamic update delays .

Future developments may bring breakthroughs in personalized medicine, telemedicine, and public health management .

Journal: Journal of Thoracic Disease