Efficiently capturing multi-scale local information and building long-range dependencies among pixels are essential for medical image segmentation because of the various sizes and shapes of the lesion regions or organs. In this paper, researchers propose the multi-scale cross-axis attention (MCA) mechanism to address these challenges through enhanced axial attention. To address the issues of insufficient learning of positional bias and limited long-distance interaction in axial attention caused by the small dataset, researchers propose using a dual cross-attention mechanism instead of axial attention to enhance global information capture. Meanwhile, to compensate for the lack of explicit attention to local information in axial attention, researchers use multiple convolutions of strip-shaped kernels with different kernel sizes in each axial attention path, which improves the efficiency of MCA in local information encoding. By integrating MCA into the multi-scale cross-axis attention network (MSCAN) backbone, researchers develop their network architecture, termed MCANet. With merely 4 M+ parameters, MCANet outperforms previous heavyweight approaches (e.g., swin transformer-based methods) across four challenging tasks: skin lesion segmentation, nuclei segmentation, abdominal multi-organ segmentation, and polyp segmentation. The code is available at https://github.com/haoshao-nku/medical_seg. 

Researchers at Kumamoto University have uncovered a previously unknown molecular mechanism by which human T-cell leukemia virus type I (HTLV-1) drives the development of adult T-cell leukemia-lymphoma (ATL), one of the most aggressive and difficult-to-treat blood cancers. The findings provide critical insight into why only a small fraction of HTLV-1 carriers develop leukemia—and point toward new strategies for targeted therapy.

Geothermal energy is clean and renewable, derived from the heat stored within accessible depths of the Earth’s crust. The adoption of a single-well system for medium-deep and deep geothermal energy extraction has attracted significant interest from the scientific and industrial communities because it effectively circumvents issues such as downhole inter-well connections and induced seismicity. However, the low heat transfer capacity in geothermal formations limits the heat extraction performance of single-well systems and hinders their commercial deployment. This review covers various enhancement concepts for optimizing the heat transfer within single-well systems, emphasizing critical parameters such as heat transfer area, heat transfer coefficient, and temperature difference. Additionally, it presents the thermo-economic evaluation of different configurations of single-well borehole heat exchangers and superlong gravity heat pipes (SLGHPs). The SLHGP, utilizing phase-change heat transfer, is recognized as a highly effective and continuously productive technology, capable of extracting over 1 MW of heat. Its pumpless operation and ease of installation in abandoned wells make it cost-effective, offering a promising economic advantage over traditional geothermal systems. It also highlights the challenges and potential research opportunities that can help identify gaps in research to enhance the performance of single-well geothermal systems.

A study published in Frontiers in Energy by researchers from Harbin Institute of Technology, Shenzhen University, Ningbo Institute of Materials Technology and Engineering, and Nanyang Technological University addresses these challenges. They developed a multi-physical model to analyze and optimize the operation of large-area SOFCs.

In a study published in Frontiers in Energy, Frederik Wiesmann and collaborators from TU Wien, Shanghai Jiao Tong University (SJTU) and Friedrich-Alexander-Universität Erlangen-Nürnberg introduced a refined oxidation mechanism for OME_1-6. The new SJTU mechanism modifies key reaction rates in the Niu mechanism based on sensitivity analysis and validation against jet-stirred reactor (JSR) experiments and shock tube IDT data from the literature. This mechanism improves the prediction of intermediate species and ignition behavior while maintaining compatibility with CFD frameworks.

A review paper by scientists at Beijing Institute of Graphic Communication presented  a thorough review of the existing research landscape, encapsulating the notable progress in swiftly expanding field.

A research paper by scientists at Beijing Friendship Hospital develop a systematic approach for automated ossicular-chain segmentation and measurement using ultra-high-resolution computed tomography (U-HRCT).

Enzymatic biofuel cells (EBFCs), which generate electricity through electrochemical reactions between metabolites and O₂/air, are considered a promising alternative power source for wearable and implantable bioelectronics. However, the main challenges facing EBFCs are the poor stability of enzymes and the low electron transfer efficiency between enzymes and electrodes. To enhance the efficiency of EBFCs, researchers have been focusing on the development of novel functional nanomaterials. This mini-review first introduces the working principles and types of EBFCs, highlighting the key roles of nanomaterials, such as enzyme immobilization and stabilization, promotion of electron transfer and catalytic activity. It then summarizes the recent advancements in their application in wearable and implantable devices. Finally, it explores future research direction and the potential of high-performance EBFCs for practical applications.