Recent theoretical research suggests that charmed baryon decays may exhibit unexpectedly large CP violation, potentially offering new clues to the matter-antimatter asymmetry in the universe. Based on the final-state re-scattering, the study predicts CP violation to be an order of magnitude larger than previous estimates. These findings highlight promising opportunities for experimental verification at current facilities like BESIII, LHCb, and Belle II, as well as the upcoming Super Tau-Charm Facility (STCF). 

A research team at Zhejiang University has developed a PEDOT-based conductive hydrogel with enhanced electrical performance and microscale patterning capability, enabled by a laser-assisted phase separation strategy. The material achieves high conductivity, spatial resolution, interfacial stability, and biocompatibility, providing a scalable platform for soft and implantable bioelectronic devices.

Single-atom nanozymes (SAzymes) hold significant potential for tumor catalytic therapy, but their effectiveness is often compromised by low catalytic efficiency within tumor microenvironment. This efficiency is mainly influenced by key factors including hydrogen peroxide (H₂O₂) availability, acidity, and temperature. Simultaneous optimization of these key factors presents a significant challenge for tumor catalytic therapy. In this study, we developed a comprehensive strategy to refine single-atom catalytic kinetics for enhancing tumor catalytic therapy through dual-enzyme-driven cascade reactions. Iridium (Ir) SAzymes with high catalytic activity and natural enzyme glucose oxidase (GOx) were utilized to construct the cascade reaction system. GOx was loaded by Ir SAzymes due to its large surface area. Then, the dual-enzyme-driven cascade reaction system was modified by cancer cell membranes for improving biocompatibility and achieving tumor homologous targeting ability. GOx catalysis reaction could produce abundant H₂O₂ and lower the local pH, thereby optimizing key reaction-limiting factors. Additionally, upon laser irradiation, Ir SAzymes could raise local temperature, further enhancing the catalytic efficiency of dual-enzyme system. This comprehensive optimization maximized the performance of Ir SAzymes, significantly improving the efficiency of catalytic therapy. Our findings present a strategy of refining single-atom catalytic kinetics for tumor homologous-targeted catalytic therapy.

Researchers have designed a new two-dimensional ferroelectric memtransistor to realize the reward-modulated spike-timing dependent plasticity in a single device for implementing the robotic recognition and tracking tasks.

A team led by Professor Wang Tao at Tianjin University’s School of Life Sciences has uncovered how the Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) suppresses host cell apoptosis, enabling its replication. Their study, published in Science Bulletin, reveals that SFTSV exploits the MDM2-p53 signaling pathway to inhibit the formation of apoptotic complexes, a mechanism countered by the anticancer drug RG7388 (Idasanutlin). By blocking MDM2, RG7388 restores apoptotic sensitivity in infected cells, curbing viral propagation during early infection. The findings also illuminate broader therapeutic strategies for related viral threats.

To enhance the energy density and safety of lithium metal batteries, the research team designed a ternary composite electrolyte additive system PAFE. By leveraging the synergistic coordination between Al(EtO)₃, FEC, and PFPN, an in-situ polymerization reaction occurs at the electrode surface, forming a uniform solid electrolyte interphase. This interphase simultaneously mitigates lattice stress in the Ni-rich cathode and suppresses dendrite formation at the lithium metal anode, significantly improving cycling stability and safety under 4.7 V.

In a paper published in Polymer Science & Technology, an international team of scientists

has, for the first time, introduced oligoethylene glycol side chains into A-A type polymers containing BNBP units, designing a polar side chain-functionalized organic boron polymer, PBN-OEG. The introduction of polar ethylene glycol side chains improves the miscibility between the host material and small molecule dopants, exhibiting a more efficient n-type small molecule doping level compared to the control material PBN-alkyl, which only contains alkyl side chains. Consequently, PBN-OEG possesses superior thermoelectric properties, with an optimal electrical conductivity of up to 1.95 S cm^-1 and a maximum power factor of up to 4.7 μW m^-1 K^-2. Furthermore, the oligoethylene glycol side chains promote the swelling of PBN-OEG films in aqueous electrolyte solutions, facilitating the ionic transport of hydrated cations. Therefore, PBN-OEG can be used as a channel material for organic field-effect transistors (OECTs), achieving a large volumetric capacitance (C*) of 97.7 F cm^-3 and a high figure of merit (μC*) of 2.6 F cm^-1 V^-1 s^-1. This study demonstrates the potential of n-type BNBP-based OMIEC materials in the fields of organic thermoelectric transistors (OTEs) and OECTs. This study is led by Jian Liu (Key Laboratory of Polymer Science and Technology, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China) and Jun Liu (Key Laboratory of Polymer Science and Technology, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China).

The increase in precision agriculture has promoted the development of picking robot technology, and the visual recognition system at its core is crucial for improving the level of agricultural automation. This paper reviews the progress of visual recognition technology for picking robots, including image capture technology, target detection algorithms, spatial positioning strategies and scene understanding. This article begins with a description of the basic structure and function of the vision system of the picking robot and emphasizes the importance of achieving high-efficiency and high-accuracy recognition in the natural agricultural environment. Subsequently, various image processing techniques and vision algorithms, including color image analysis, three-dimensional depth perception, and automatic object recognition technology that integrates machine learning and deep learning algorithms, were analyzed. At the same time, the paper also highlights the challenges of existing technologies in dynamic lighting, occlusion problems, fruit maturity diversity, and real-time processing capabilities. This paper further discusses multisensor information fusion technology and discusses methods for combining visual recognition with a robot control system to improve the accuracy and working rate of picking. At the same time, this paper also introduces innovative research, such as the application of convolutional neural networks (CNNs) for accurate fruit detection and the development of event-based vision systems to improve the response speed of the system. At the end of this paper, the future development of visual recognition technology for picking robots is predicted, and new research trends are proposed, including the refinement of algorithms, hardware innovation, and the adaptability of technology to different agricultural conditions. The purpose of this paper is to provide a comprehensive analysis of visual recognition technology for researchers and practitioners in the field of agricultural robotics, including current achievements, existing challenges and future development prospects.