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Heilongjiang, located in the cold region, is China's largest rice-producing and commercializing province. The variety selection of rice in cold regions (RCR) is indispensable in promoting the rice industry's development, and technological innovation in breeding theory plays a significant role in breeding breakthrough. Based primarily on long-term research, contemplation, and breeding practices, the 4S (selected topic, selected breeding, selected progenies, and selected promotion) phenotypic-design breeding technical system for RCR, which has revolutionized the theoretical basis and deepened the conceptual model, has been developed through systematic analyses and generalization. The system covers several key aspects such as scientific question formulation, breeding objective optimization, parental taxa hybridization, progeny population selection, and innovation dissemination, aiming to improve the foresight, precision, and efficiency of breeding. Furthermore, the system has demonstrated successful cases of rice variety breeding over the past 20 years, such as for Suijing 3, Suijing 4, Suijing 18, and a series of other rice varieties, providing theoretical and technical supports for cold-region rice breeding. [ABSTRACT FROM AUTHOR]

Mahjong, a complex game with hidden information and sparse rewards, poses significant challenges. Existing Mahjong AIs require substantial hardware resources and extensive datasets to enhance AI capabilities. The authors propose a transformer‐based Mahjong AI (Tjong) via hierarchical decision‐making. By utilising self‐attention mechanisms, Tjong effectively captures tile patterns and game dynamics, and it decouples the decision process into two distinct stages: action decision and tile decision. This design reduces decision complexity considerably. Additionally, a fan backward technique is proposed to address the sparse rewards by allocating reversed rewards for actions based on winning hands. Tjong consists of 15M parameters and is trained using approximately 0.5 M data over 7 days of supervised learning on a single server with 2 GPUs. The action decision achieved an accuracy of 94.63%, while the claim decision attained 98.55% and the discard decision reached 81.51%. In a tournament format, Tjong outperformed AIs (CNN, MLP, RNN, ResNet, VIT), achieving scores up to 230% higher than its opponents. Furthermore, after 3 days of reinforcement learning training, it ranked within the top 1% on the leaderboard on the Botzone platform. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the clinical significance of an optimized approach to improve surgical field visualization and simplify anastomosis techniques using robotic-assisted sleeve lobectomy for lung or bronchial carcinoma. Method: A total of 26 consecutive patients who underwent sleeve lobectomy between January 2017 and April 2020 were enrolled in the study. The cohort included 11 cases of robotic-assisted surgery (RAS group) and 15 cases of mini-thoracotomy (MT group). RAS was performed via an exclusive optimized approach utilizing the “3 to 4-6 to 8/9” four-port technique. Retrieved demographical and clinical data included operation time, anastomosis time, blood loss, chest drainage time and volume, postoperative pain scores, complications, white blood cell (WBC) levels, and duration of hospital stay and follow-up. Results: No cases of perioperative death were recorded. Compared to MT group, the RAS group had a similar anastomosis time (30.82 ± 6.08 vs 33.20 ± 7.73 min, respectively, p > 0.05) and shorter operation time (189.73 ± 36.41 vs 225.33 ± 38.19 min, respectively, p 0.05) and satisfactory disease-free survival (eight cases, 72.73% and 12 cases, 80%, respectively). Conclusion: The optimized approach to RA sleeve lobectomy is convenient and efficient and provides satisfactory clinical outcomes. Further study with a large sample size and evaluation of long-term survival are warranted. Key points: (i) we present a novel, convenient, and efficient approach for robotic-assisted sleeve lobectomy, ie, “3 to 4-6 to 8/9” four-port technique. The optimized approach for RA sleeve lobectomy is convenient and efficient and provides satisfactory clinical outcomes; (ii) details for the “3 to 4-6 to 8/9” four-port method: the assistant port was located at the fourth intercostal space. The 1-cm camera port was inserted at the sixth intercostal space in the posterior axillary line. The 0.5-cm da Vinci ports of the instrument arms were placed at the third intercostal space in the anterior axillary line and the eighth or ninth intercostal space in the posterior axillary line. The patient cart was inserted from the back of the patient's head and shoulders at 75° to the longitudinal line.

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In vitro and in vivo studies implicate occludin in the regulation of paracellular macromolecular flux at steady state and in response to tumor necrosis factor (TNF). To define the roles of occludin in these processes, we established intestinal epithelia with stable occludin knockdown. Knockdown monolayers had markedly enhanced tight junction permeability to large molecules that could be modeled by size-selective channels with radii of ~62.5 Å. TNF increased paracellular flux of large molecules in occludin-sufficient, but not occludin-deficient, monolayers. Complementation using full-length or C-terminal coiled-coil occludin/ELL domain (OCEL)-deficient enhanced green fluorescent protein (EGFP)-occludin showed that TNF-induced occludin endocytosis and barrier regulation both required the OCEL domain. Either TNF treatment or OCEL deletion accelerated EGFP-occludin fluorescence recovery after photobleaching, but TNF treatment did not affect behavior of EGFP-occludin(ΔOCEL). Further, the free OCEL domain prevented TNF-induced acceleration of occludin fluorescence recovery, occludin endocytosis, and barrier loss. OCEL mutated within a recently proposed ZO-1-binding domain (K433) could not inhibit TNF effects, but OCEL mutated within the ZO-1 SH3-GuK-binding region (K485/K488) remained functional. We conclude that OCEL-mediated occludin interactions are essential for limiting paracellular macromolecular flux. Moreover, our data implicate interactions mediated by the OCEL K433 region as an effector of TNF-induced barrier regulation.

The characteristic features of underactuated finger are compact structure, large grasping force, and simple operation. It has a wide application prospect in the fields of industrial robot, humanoid robot, human artificial limb, and space robot. A new type of fully rotating joint linkage-based underactuated mechanism is proposed, and a new method based on the law of minimum resistance is presented to realize the equivalent mechanism at different contact conditions of the finger and the kinematical analysis based on the equivalent mechanism. The kinematic equations and the limit moving position of the mechanism are derived using the proposed method. Finally, the numerical simulation is carried out by MATLAB program. The correctness and effectiveness of the proposed method are verified. The simulation results show that the proposed mechanism has a large grasp space and can achieve good grasp trajectory.

Biosensors are a class of smart devices fabricated for target analyte detection. A biosensor is commonly made of three basic components: a specific bioreceptor, a physicochemical transducer, and a signal processing device. The bioreceptor part features one of the more crucial technologies of a biosensor to perform specific detection of analytes. They commonly make use of various molecular recognition elements, such as enzymes, natural receptors, antibodies, nucleic acid aptamers, and even synthetic receptors. Then, the molecular recognition events of these bioreceptors can be translated into readable signals in various forms like electrochemical, optical, piezo/pyro electric, etc. Finally, these signals are mathematically processed for quantitative analysis. Nowadays, the great advances in biomimetic materials, in particular the synthetic receptors based on molecularly imprinted polymers (MIPs), promote tremendous development of biosensors. Integration of this field with artificial intelligence enables emerging design of advanced biosensors, which has moved from concept to implementation, meanwhile facing new opportunities and challenges. With no doubt, bioreceptor innovation based on molecular imprinting is an emerging driving force for biosensors development. In this review paper, we provide an overview of MIP‐based biosensors, and also their challenges and opportunities moving forward toward wearable devices are discussed. [ABSTRACT FROM AUTHOR]