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Endothelial cell metabolism in sepsis

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World Journal of Emergency Medicine 2023年第1期14卷 10-16页

作者： Jue-xian Wei hui-lin jiang Xiao-hui Chen Emergency Department the Second Affiliated HospitalGuangzhou Medical UniversityGuangzhou 510260China

BACKGROUND:Endothelial dysfunction in sepsis is a pathophysiological feature of septic organ *** cells(ECs)exhibit specific metabolic traits and release metabolites to adapt to the septic state in the blood to maintain vascular ***:Web of Science and PubMed were searched from inception to October 1,*** search was limited to the English language *** reviewers independently identified studies related to EC metabolism in *** exclusion criteria were duplicate articles according to multiple search ***:Sixty articles were included,and most of them were cell and animal *** studies reported the role of glycolysis,oxidative phosphorylation,fatty acid metabolism,and amino acid metabolism in EC *** glycolysis,oxidative phosphorylation,fatty acid metabolism and amino acid ***,dysregulation of EC metabolism can contribute to sepsis ***:There are few clinical studies on EC metabolism in *** research mainly focuses on basic research,but some scientific problems have also been ***,this review may provide an overall comprehension and novel aspects of EC metabolism in sepsis.

关键词： Sepsis Endothelium Metabolism Glycolysis Oxidative phosphorylation Fatty acid metabolism Amino acid metabolism

Polaron-pair-dependent equivalent circuit parameters of organic solar cells based on CuPc and C_(60)

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Chinese Science Bulletin 2010年第13期55卷 1317-1324页

作者： HUANG jiang YU JunSheng lin hui jiang YaDong State Key Laboratory of Electronic Thin Films and Integrated Devices School of Optoelectronic Information University of Electronic Scienceand Technology of China (UESTC) Chengdu 610054 China

We present the current-voltage characteristics of organic solar cells based on single and double heterojunction of copper phthalocyanine (CuPc) and C60 by introducing a constant JP instead of photo-current density Jph to represent the density of polaron-pairs generated from excitons at D/A interface. A diode Dext models polaron-pair dissociation, and a diode Drec stands for loss due to polaron-pair recombination. The photovoltaic response under AM 1.5 solar illumination at an intensity of 100 mW/cm2 is parameterized and modeled using the improved equivalent circuit model developed for inorganic pn-junction solar cells. The instinct mechanisms including dissociation, recombination of polaron-pairs and charge carrier collection process are explained by introducing Jph/JP as the dissociation rate of polaron-pairs and |J|/Jph as charge carrier application efficiency ηCA. Especially, we reveal the optimization mechanism for the fill factor FF and series resistance RS of organic solar cells.

关键词：有机太阳能电池极化子等效电路参数 C60 酞菁铜电流电压特性等效电路模型电流密度

Offload Strategy for Edge Computing in Satellite Networks Based on Software Defined Network

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Computers, Materials & Continua 2025年第1期82卷 863-879页

作者： Zhiguo Liu Yuqing Gui lin Wang Yingru jiang Communication and Network Laboratory Dalian UniversityDalian116622China College of Environment and Chemical Engineering Dalian UniversityDalian116622China

Satellite edge computing has garnered significant attention from researchers;however,processing a large volume of tasks within multi-node satellite networks still poses considerable *** sharp increase in user demand for latency-sensitive tasks has inevitably led to offloading bottlenecks and insufficient computational capacity on individual satellite edge servers,making it necessary to implement effective task offloading scheduling to enhance user *** this paper,we propose a priority-based task scheduling strategy based on a Software-Defined Network(SDN)framework for satellite-terrestrial integrated networks,which clarifies the execution order of tasks based on their ***,we apply a Dueling-Double Deep Q-Network(DDQN)algorithm enhanced with prioritized experience replay to derive a computation offloading strategy,improving the experience replay mechanism within the Dueling-DDQN ***,we utilize the Deep Deterministic Policy Gradient(DDPG)algorithm to determine the optimal resource allocation strategy to reduce the processing latency of *** results demonstrate that the proposed d3-DDPG algorithm outperforms other approaches,effectively reducing task processing latency and thus improving user experience and system efficiency.

关键词： Satellite network edge computing task scheduling computing offloading

Ideal Bi‑Based Hybrid Anode Material for Ultrafast Charging of Sodium‑Ion Batteries at Extremely Low Temperatures

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Nano-Micro Letters 2025年第3期17卷 152-167页

作者： Jie Bai Jian hui Jia Yu Wang Chun Cheng Yang Qing jiang Key Laboratory of Automobile Materials(Jilin University) Ministry of EducationSchool of Materials Science and EngineeringJilin UniversityChangchun 130022People’s Republic of China

Sodium-ion batteries have emerged as competitive substitutes for low-temperature applications due to severe capacity loss and safety concerns of lithium-ion batteries at−20°C or ***,the key capability of ultrafast charging at ultralow temperature for SIBs is rarely ***,a hybrid of Bi nanoparticles embedded in carbon nanorods is demonstrated as an ideal material to address this issue,which is synthesized via a high temperature shock *** a hybrid shows an unprecedented rate performance(237.9 mAh g^(−1)at 2 A g^(−1))at−60℃,outperforming all reported SIB anode *** with a Na_(3)V_(2)(PO_(4))_(3)cathode,the energy density of the full cell can reach to 181.9 Wh kg^(−1)at−40°*** on this work,a novel strategy of high-rate activation is proposed to enhance performances of Bi-based materials in cryogenic conditions by creating new active sites for interfacial reaction under large current.

关键词： Bi nanoparticles High temperature shock High-rate activation Ultrafast charging Low-temperature sodium-ion batteries

A new risk stratification score for patients with suspected cardiac chest pain in emergency departments,based on machine learning

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Chinese Medical Journal 2020年第7期133卷 879-880页

作者： Hai-Feng Mao Xiao-hui Chen Yun-Mei Li Si-Yuan Zhang Jun-Rong Mo Min Li Pei-Yi lin Timothy HRainer Colin AGraham hui-lin jiang Department of Emergency The Second Affiliated Hospital of Guangzhou Medical UniversityGuangzhouGuangdong 510260China The Sixth Clinical Medical Institute of Guangzhou Medical University GuangzhouGuangdong 511436China Accident and Emergency Medicine Academic Unit Chinese University of Hong KongPrince of Wales HospitalHong Kong999077China

To the Editor:Chest pain is one of the most common complaints for patients attending emergency departments(EDs)*** is important to accurately stratify risk of possible acute coronary syndrome(ACS)for these patients.[1]Several risk stratification scores such as thrombolysis in myocardial infarction(TIMI),global registry for acute coronary events(GRACE),Banach and HEART are helpful.[2]Previous research in our setting compared these four scores and found that the HEART score,with a C-statistic of 0.731,was the best for predicting 7-day major adverse cardiac events(MACE)The purpose of this study was to develop risk stratification prediction models for 7-day MACE in patients with chest pain,utilizing machine learning algorithms such as eXtreme Gradient Boosting(XGBoost),Support Vector Machine(SVM).

关键词： patients pain cardiac

Wafer‑Scale Vertical 1D GaN Nanorods/2D MoS_(2)/PEDOT:PSS for Piezophototronic Effect‑Enhanced Self‑Powered Flexible Photodetectors

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Nano-Micro Letters 2025年第3期17卷 102-116页

作者： Xin Tang Hongsheng jiang Zhengliang lin Xuan Wang Wenliang Wang Guoqiang Li State Key Laboratory of Luminescent Materials and Devices South China University of TechnologyGuangzhou 510640People’s Republic of China Department of Electronic Materials School of Materials Science and EngineeringSouth China University of TechnologyGuangzhou 510640People’s Republic of China

van der Waals(vdW)heterostructures constructed by lowdimensional(0D,1D,and 2D)materials are emerging as one of the most appealing systems in next-generation flexible ***,hand-stacked vdW-type photodetectors are not compatible with large-areaarray fabrication and show unimpressive performance in self-powered ***,vertical 1D GaN nanorods arrays(NRAs)/2D MoS_(2)/PEDOT:PSS in wafer scale have been proposed for self-powered flexible photodetectors arrays *** as-integrated device without external bias under weak UV illumination exhibits a competitive responsivity of 1.47 A W^(−1)and a high detectivity of 1.2×10^(11)Jones,as well as a fast response speed of 54/71μs,thanks to the strong light absorption of GaN NRAs and the efficient photogenerated carrier separation in type-II ***,the strain-tunable photodetection performances of device have been ***,the device at−0.78%strain and zero bias reveals a significantly enhanced photoresponse with a responsivity of 2.47 A W^(−1),a detectivity of 2.6×10^(11)Jones,and response times of 40/45μs,which are superior to the state-of-the-art self-powered flexible *** work presents a valuable avenue to prepare tunable vdWs heterostructures for self-powered flexible photodetection,which performs well in flexible sensors.

关键词： Vertical nanorod arrays van der Waals heterostructure Piezophototronic effect Self-powered photodetection Flexible sensors

Multi-model ensemble learning for battery state-of-health estimation:Recent advances and perspectives

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Journal of Energy Chemistry 2025年第1期100卷 739-759页

作者： Chuanping lin Jun Xu Delong jiang Jiayang Hou Ying Liang Zhongyue Zou Xuesong Mei State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Shaanxi Key Laboratory of Intelligent Robots School of Mechanical Engineering Xi'an Jiaotong University Department of Electrical Engineering and Automation Luoyang Institute of Science and Technology School of Mechanical Engineering Hangzhou Dianzi University

The burgeoning market for lithium-ion batteries has stimulated a growing need for more reliable battery performance monitoring. Accurate state-of-health(SOH) estimation is critical for ensuring battery operational performance. Despite numerous data-driven methods reported in existing research for battery SOH estimation, these methods often exhibit inconsistent performance across different application scenarios. To address this issue and overcome the performance limitations of individual data-driven models,integrating multiple models for SOH estimation has received considerable attention. Ensemble learning(EL) typically leverages the strengths of multiple base models to achieve more robust and accurate outputs. However, the lack of a clear review of current research hinders the further development of ensemble methods in SOH estimation. Therefore, this paper comprehensively reviews multi-model ensemble learning methods for battery SOH estimation. First, existing ensemble methods are systematically categorized into 6 classes based on their combination strategies. Different realizations and underlying connections are meticulously analyzed for each category of EL methods, highlighting distinctions, innovations, and typical applications. Subsequently, these ensemble methods are comprehensively compared in terms of base models, combination strategies, and publication trends. Evaluations across 6 dimensions underscore the outstanding performance of stacking-based ensemble methods. Following this, these ensemble methods are further inspected from the perspectives of weighted ensemble and diversity, aiming to inspire potential approaches for enhancing ensemble performance. Moreover, addressing challenges such as base model selection, measuring model robustness and uncertainty, and interpretability of ensemble models in practical applications is emphasized. Finally, future research prospects are outlined, specifically noting that deep learning ensemble is poised to advance ens

关键词： Contrastive Learning

Airborne laser communication technology and flight test

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Airborne laser communication technology and flight test

Deep learning-based software engineering: progress,challenges, and opportunities

国防光电子论坛空间光信息与组网技术及应用研讨会

作者： Li-xin MENG Li-zhong ZHANG Xiao-ming LI Ying-chao LI hui-lin jiang Fundamental Science on Space-Ground Laser Communication Technology Laboratory

Reconnaissance aircraft is an important node of the space-air-ground integrated information network, on which equipped with a large number of high-resolution surveillance equipment, and need high speed communications equipment to transmit detected information in real time. Currently RF communication methods cannot meet the needs of communication bandwidth. Wireless laser communication has outstanding advantages high speed, high capacity, security, etc., is an important means to solve the high-speed information transmission of airborne platforms. In this paper, detailed analysis of how the system works, the system components, work processes, link power and the key technologies of airborne laser communication were discussed. On this basis, a prototype airborne laser communications was developed, and high-speed, long-distance communications tests were carried out between the two fixed-wing aircraft, and the airborne precision aiming, atmospheric laser communication impacts on laser communication were tested. The experiments ultimately realize that, the communication distance is 144 km, the communication rate is 2.5Gbps. The Airborne laser communication experiments provide technical basis for the application of the conversion equipment.

关键词： Airborne laser communication flight test atmospheric APT

来源： cnki会议评论

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Science China(Information Sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He jiang Weixing JI Yanjie jiang Yanyan jiang Bo LIU hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey