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Persistent Variations in the East Asian Trough from March to April and the Possible Mechanism

Advances in Atmospheric Sciences 2024年第4期41卷 737-753,I0002-I0004页

作者： shui yu Jianqi SUN Nansen-Zhu International Research Center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China

The East Asian trough(EAT)profoundly influences the East Asian spring climate.In this study,the relationship of the EATs among the three spring months is investigated.Correlation analysis shows that the variation in March EAT is closely related to that of April EAT.Extended empirical orthogonal function(EEOF)analysis also confirms the co-variation of the March and April EATs.The positive/negative EEOF1 features the persistent strengthened/weakened EAT from March to April.Further investigation indicates that the variations in EEOF1 are related to a dipole sea surface temperature(SST)pattern over the North Atlantic and the SST anomaly over the tropical Indian Ocean.The dipole SST pattern over the North Atlantic,with one center east of Newfoundland Island and another east of Bermuda,could trigger a Rossby wave train to influence the EAT in March−April.The SST anomaly over the tropical Indian Ocean can change the Walker circulation and influence the atmospheric circulation over the tropical western Pacific,subsequently impacting the southern part of the EAT in March−April.Besides the SST factors,the Northeast Asian snow cover could change the regional thermal conditions and lead to persistent EAT anomalies from March to April.These three impact factors are generally independent of each other,jointly explaining large variations in the EAT EEOF1.Moreover,the signals of the three factors could be traced back to February,consequently providing a potential prediction source for the EAT variation in March and April.

关键词： spring East Asian trough sea surface temperature snow cover

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Meta label associated loss for fine-grained visual recognition

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Science China(Information Sciences) 2024年第6期67卷 230-247页

作者： Yanchao LI Fu XIAO Hao LI Qun LI shui yu School of Computer Science Nanjing University of Posts and Telecommunications School of Network Engineering Zhoukou Normal University School of Computer Science University of Technology Sydney

Recently, intensive attempts have been made to design robust models for fine-grained visual recognition, most notably are the impressive gains for training with noisy labels by incorporating a reweighting strategy into a meta-learning framework. However, it is limited to up or downweighting the contribution of an instance for label reweighting approaches in the learning process. To solve this issue, a novel noise-tolerant method with auxiliary web data is proposed. Specifically, first, the associations made from embeddings of well-labeled data with those of web data and back at the same class are measured. Next, its association probability is employed as a weighting fusion strategy into angular margin-based loss, which makes the trained model robust to noisy datasets. To reduce the influence of the gap between the well-labeled and noisy web data, a bridge schema is proposed via the corresponding loss that encourages the learned embeddings to be coherent. Lastly, the formulation is encapsulated into the meta-learning framework, which can reduce the overfitting of models and learn the network parameters to be noise-tolerant. Extensive experiments are performed on benchmark datasets, and the results clearly show the superiority of the proposed method over existing state-of-the-art approaches.

关键词： label associated loss weighting noisy samples fine-grained visual recognition noise-tolerant learning meta-learning

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The optimization research on the coupled of active and passive energy supplying in public institutions in China

Energy and Built Environment

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Energy and Built Environment 2024年第2期5卷 288-299页

作者： shui yu Xueyan Liu Jianghui Yang Fuhong Han Jiashuai Wei School of Municipal and Environmental Engineering Shenyang Jianzhu UniversityShenyang 110168China

The building sector is one of the largest energy user and carbon emitters globally.To increase the utilization rate of renewable energy and reduce carbon dioxide emissions,the optimal technical scheme of active public institutions and coupled utilization of renewable energy is studied.In this study,the energy consumption of three types of public institutions in various regions of China was simulated by using DeST building energy consumption software,combined with energy conversion efficiency and data released by the National Bureau of Statistics,and the total energy demand and total energy supply of public institutions were predicted using the load density method.Based on the coupling mechanism of the MARKAL model,the optimal proportion of renewable energy in the energy supply of public buildings in different regions is determined.Through the study of the number of public institutions in various regions of China,energy consumption characteristics,construction area,and other related data,the reverse energy flow method is creatively proposed,and the active and renewable energy coupling algorithm from the energy demand side of public institutions to the energy supply side is established.The results show that the central region has the highest utilization rate of renewable energy in the public sector,reaching 36.18%.The use of renewable energy in public buildings in hot summer and warm winter zones decreased to 35.08%,and it was 12.82% in cold zones.By 2025,the proportion of renewable energy resources in China is expected to reach 29.2%.The energy coupling model and algorithm constructed in this paper can provide a basis for the coupling macro configuration of renewable energy in public institutions in China.

关键词： Public institutions Energy demand Energy supply Active and renewable energy coupling ratio Energy conversion efficiency

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Superior and safer lithium sulfur batteries realized by robust polysulfides-retarding dam with high flame retardance

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Journal of Energy Chemistry 2024年第2期89卷 471-486,I0011页

作者： Junling Wang Yanfang Cao Zhirong Wang Yinquan Zhao Chuang He Fudong Zhao Chaoling Han shui yu Jiangsu Key Laboratory of Hazardous Chemicals Safety and Control College of Safety Science and EngineeringNanjing Tech UniversityNanjing 211816JiangsuChina Department of Architecture and Civil Engineering City University of Hong KongHong Kong 999077China School of Mechanical and Power Engineering Nanjing Tech UniversityNanjing 211816JiangsuChina

The unparalleled energy density has granted lithium-sulfur batteries(LSBs)with attractive usages.Unfortunately,LSBs still face some unsurpassed challenges in industrialization,with polysulfides shuttling,dendrite growth and thermal hazard as the major problems triggering the cycling instability and low safety.With the merit of convenience,the method of designing functional separator has been adapted.Concretely,the carbon aerogel confined with CoS_(2)(CoS_(2)-NCA)is constructed and coated on Celgard separator surface,acquiring CoS_(2)-NCA modified separator(CoS_(2)-NCA@C),which holds the promoted electrolyte affinity and flame retardance.As revealed,CoS_(2)-NCA@C cell gives a high discharge capacity 1536.9 mAh/g at 1st cycle,much higher than that of Celgard cell(987.1 mAh/g).Moreover,the thermal runaway triggering time is dramatically prolonged by 777.4 min,corroborating the promoted thermal safety of cell.Noticeably,the higher coulombic efficiency stability and lower overpotential jointly confirm the efficacy of CoS_(2)-NCA@C in suppressing the lithium dendrite growth.Overall,this work can provide useful inspirations for designing functional separator,coping with the vexing issues of LSBs.

关键词： Lithium-sulfur batteries Thermal safety Flame retardancy Separator

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Impact of Polymer Matrix on Polymer Mechanochromism from Excited State Intramolecular Proton Transfer

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Chinese Journal of Chemistry 2024年第6期42卷 611-616页

作者： yu Wu Xin Cheng Huan Hu shui Hu Zhimin Ma Zhiyong Ma Beijing Advanced Innovation Center for Soft Matter Science and Engineering Beijing State Key Laboratory of Organic-Inorganic CompositesCollege of Chemical EngineeringBeijing University of Chemical TechnologyBeijing100029 China Center of Advanced Elastomer Materials College of Materials Science and EngineeringBeijing University of Chemical TechnologyBeijing100029 China College of Engineering Peking UniversityBeijing100871 China

Mechanochromic polymers based on non-covalent changes have attracted much attention recently.Herein,we report the impact of inter/intramolecular hydrogen bonds on polymer mechanochromism from the excited state intramolecular proton transfer (ESIPT) process.PhMz-NH2-OH and PhMz=2A are designed and obtained by simple and high-yield synthesis,and are connected into polyurethane and poly(methyl acrylate-co-2-ethylhexyl acrylate),respectively.In the initial state,the PhMz-NH2-OH@PU sample shows blue fluorescence from the excited enol form (E*) excitons,owing to intermolecular hydrogen bonds that interrupt the ESIPT reactions but the PhMz=2A@PMA-2-EA sample expresses cyan fluorescence belonging to the excited keto form (K*) emission,implying that the intramolecular hydrogen bonds matter.Furthermore,under stretching,external force can tune the emission of the PhMz=2A@PMA-2-EA sample from K* to E* state.Though external force can putatively still promote a bond rotation,ESIPT reactions remain equivalently interrupted in both the relaxed and stressed states in a hydrogen-bond donating environment.DFT calculation confirms the force-induced increase in dihedral angle for the transition of ESIPT-on/off.Thus,PhMz-NH2-OH@PU and PhMz=2A@PMA-2-EA showed disparate initial ESIPT states and further different responses/sensitivity to force.This study reports a novel and efficient strategy for enriching mechanochromic investigation and extending the applications of ESIPT reactions.

关键词： Polymer mechanochromism Excited state intramolecular proton transfer Hydrogen bonding Supramolecular chemistry Elastomers

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C-reactive protein to albumin ratio predict responses to programmed cell death-1 inhibitors in hepatocellular carcinoma patients

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World Journal of Gastrointestinal Oncology 2024年第1期16卷 61-78页

作者： Bai-Bei Li Lei-Jie Chen Shi-Liu Lu Biao Lei Gui-Lin yu shui-Ping yu Department of Hepatobiliary Surgery The First Affiliated Hospital of Guangxi Medical UniversityNanning 530021Guangxi Zhuang Autonomous RegionChina Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor(Guangxi Medical University) Ministry of EducationNanning 530021Guangxi Zhuang Autonomous RegionChina Guangxi Key Laboratory of Immunology and Metabolism for Liver Diseases Guangxi Medical UniversityNanning 530021Guangxi Zhuang Autonomous RegionChina Department of Gastroenterology The Second Xiangya Hospital of Central South UniversityNanning 410011Guangxi Zhuang Autonomous RegionChina Department of Emergency The First Affiliated Hospital of Guangxi Medical UniversityNanning 530021Guangxi Zhuang Autonomous RegionChina

BACKGROUND Over the years,programmed cell death-1(PD-1)inhibitors have been routinely used for hepatocellular carcinoma(HCC)treatment and yielded improved survival outcomes.Nonetheless,significant heterogeneity surrounds the outcomes of most studies.Therefore,it is critical to search for biomarkers that predict the efficacy of PD-1 inhibitors in patients with HCC.AIM To investigate the role of the C-reactive protein to albumin ratio(CAR)in evaluating the efficacy of PD-1 inhibitors for HCC.METHODS The clinical data of 160 patients with HCC treated with PD-1 inhibitors from January 2018 to November 2022 at the First Affiliated Hospital of Guangxi Medical University were retrospectively analyzed.RESULTS The optimal cut-off value for CAR based on progression-free survival(PFS)was determined to be 1.20 using x-tile software.Cox proportional risk model was used to determine the factors affecting prognosis.Eastern Cooperative Oncology Group performance status[hazard ratio(HR)=1.754,95%confidence interval(95%CI)=1.045-2.944,P=0.033],CAR(HR=2.118,95%CI=1.057-4.243,P=0.034)and tumor number(HR=2.932,95%CI=1.246-6.897,P=0.014)were independent prognostic factors for overall survival.CAR(HR=2.730,95%CI=1.502-4.961,P=0.001),tumor number(HR=1.584,95%CI=1.003-2.500,P=0.048)and neutrophil to lymphocyte ratio(HR=1.120,95%CI=1.022-1.228,P=0.015)were independent prognostic factors for PFS.Two nomograms were constructed based on independent prognostic factors.The C-index index and calibration plots confirmed that the nomogram is a reliable risk prediction tool.The ROC curve and decision curve analysis confirmed that the nomogram has a good predictive effect as well as a net clinical benefit.CONCLUSION Overall,we reveal that the CAR is a potential predictor of short-and long-term prognosis in patients with HCC treated with PD-1 inhibitors.If further verified,CAR-based nomogram may increase the number of markers that predict individualized prognosis.

关键词： C-reactive protein to albumin ratio Hepatocellular carcinoma Programmed cell death-1 inhibitors Prognosis Nomogram

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Detachable string magnetically controlled capsule endoscopy for the noninvasive diagnosis of esophageal diseases:A prospective,blind clinical study

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World Journal of Gastroenterology 2024年第9期30卷 1121-1131页

作者： Yan-Ling Yang Huang-Wen Qin Zhao-yu Chen Hui-Ning Fan Yi yu Wei Da Jin-shui Zhu Jing Zhang Department of Gastroenterology Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200233China

BACKGROUND Traditional esophagogastroduodenoscopy(EGD),an invasive examination method,can cause discomfort and pain in patients.In contrast,magnetically controlled capsule endoscopy(MCE),a noninvasive method,is being applied for the detection of stomach and small intestinal diseases,but its application in treating esophageal diseases is not widespread.AIM To evaluate the safety and efficacy of detachable string MCE(ds-MCE)for the diagnosis of esophageal diseases.METHODS Fifty patients who had been diagnosed with esophageal diseases were pros-pectively recruited for this clinical study and underwent ds-MCE and conven-tional EGD.The primary endpoints included the sensitivity,specificity,positive predictive value,negative predictive value,and diagnostic accuracy of ds-MCE for patients with esophageal diseases.The secondary endpoints consisted of visualizing the esophageal and dentate lines,as well as the subjects'tolerance of the procedure.RESULTS Using EGD as the gold standard,the sensitivity,specificity,positive predictive value,negative predictive value,and diagnostic accuracy of ds-MCE for esophageal disease detection were 85.71%,86.21%,81.82%,89.29%,and 86%,respectively.ds-MCE was more comfortable and convenient than EGD was,with 80%of patients feeling that ds-MCE examination was very comfortable or comfortable and 50%of patients believing that detachable string v examination was very convenient.CONCLUSION This study revealed that ds-MCE has the same diagnostic effects as traditional EGD for esophageal diseases and is more comfortable and convenient than EGD,providing a novel noninvasive method for treating esophageal diseases.

关键词： Clinical trial Detachable string magnetically controlled capsule endoscopy Esophagogastroduodenoscopy Noninvasive diagnosis Esophageal diseases

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Security and QoS issues in blockchain enabled next-generation smart logistic networks:A tutorial

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Blockchain(Research and Applications) 2022年第3期3卷 46-59页

作者： Anjali Vaghani Keshav Sood shui yu Deakin University GeelongVIC3220Australia University of Technology SydneyNSW2007Australia

The blockchain-enabled smart logistics market is expected to grow worth USD 1620 billion and at a compound annual growth rate of 62.4%.Smart logistics ensures intelligence infrastructure,logistics automation,real-time analysis of supply chain data synchronization of the logistics process,cost transparency,unbroken shipment tracking all the way down to the transportation route,etc.In the smart logistics domain,significant advancement and growth of the Internet of Things(IoT)sensors are evident.However,the connectivity of IoT systems,including Tactile Internet,without proper safeguards creates vulnerabilities that can still be deliberately or inadvertently cause disruption.In view of this,we primarily notice two key issues.Firstly,the logistics domain can be compromised by a variety of natural or man-made activities,which eventually affect the overall network security.Secondly,there are thousands of entities in the supply chain network that use extensive machine-learning algorithms in many scenarios,and they require high-power computational resources.From these two challenges,we note that the first concern can be addressed by adding blockchain to IoT logistic networks.The second issue can be addressed using 6G.This will support 1-μs latency communications,support seamless computing at the edges of networks,and autonomously predict the best optimal location for edge computing.Motivated by this,we have highlighted motivational examples to show the necessity to integrate 6G and blockchain in smart logistic networks.Then,we have proposed a 6G and blockchain-enabled smart logistic high-level framework.We have presented the key intrinsic issues of this framework mainly from the security and resource management context.In this paper,recent state-of-the-art advances in blockchain enabled next-generation smart logistic networks are analyzed.We have also examined why 6G and not 5G would be compatible with the smart network.We have introduced five different use cases of blockchain technology in smart logistics.Later,this pape

关键词： Blockchain Internet of Things 5G 6G Security Smart logistics

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Intestinal Dopamine Receptor D2 is Required for Neuroprotection Against 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine-induced Dopaminergic Neurodegeneration

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Neuroscience Bulletin 2022年第8期38卷 871-886页

作者： Hairong Peng shui yu yukai Zhang Yanqing Yin Jiawei Zhou Institute of Neuroscience State Key Laboratory of NeuroscienceCAS Center for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghai200031China School of Future Technology University of Chinese Academy of SciencesBeijing100049China Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology Shanghai201210China

A wealth of evidence has suggested that gastrointestinal dysfunction is associated with the onset and progression of Parkinson’s disease(PD).However,the mechanisms underlying these links remain to be defined.Here,we investigated the impact of deregulation of intestinal dopamine D2 receptor(DRD2)signaling in response to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)-induced dopaminergic neurodegeneration.Dopamine/dopamine signaling in the mouse colon decreased with ageing.Selective ablation of Drd2,but not Drd4,in the intestinal epithelium,caused a more severe loss of dopaminergic neurons in the substantia nigra following MPTP challenge,and this was accompanied by a reduced abundance of succinate-producing Alleoprevotella in the gut microbiota.Administration of succinate markedly attenuated dopaminergic neuronal loss in MPTP-treated mice by elevating the mitochondrial membrane potential.This study suggests that intestinal epithelial DRD2 activity and succinate from the gut microbiome contribute to the maintenance of nigral DA neuron survival.These findings provide a potential strategy targeting neuroinflammation-related neurological disorders such as PD.

关键词： Intestine DRD2 Parkinson’s disease MPTP Succinate Mitochondria

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VulnerGAN: a backdoor attack through vulnerability amplification against machine learning-based network intrusion detection systems

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Science China(Information Sciences) 2022年第7期65卷 32-50页

作者： Guangrui LIU Weizhe ZHANG Xinjie LI Kaisheng FAN shui yu School of Cyberspace Science Harbin Institute of Technology School of Computer Science University of Technology Sydney Cyberspace Security Research Center Peng Cheng Laboratory

Machine learning-based network intrusion detection systems(ML-NIDS) are extensively used for network security against unknown attacks. Existing intrusion detection systems can effectively defend traditional network attacks, however, they face AI based threats. The current known AI attacks cannot balance the escape rate and attack effectiveness. In addition, the time cost of existing AI attacks is very high. In this paper, we propose a backdoor attack called VulnerGAN, which features high concealment,high aggressiveness, and high timeliness. The backdoor can make the specific attack traffic bypass the detection of ML-NIDS without affecting the performance of ML-NIDS in identifying other attack traffic.VulnerGAN uses generative adversarial networks(GAN) to calculate poisoning and adversarial samples based on machine learning model vulnerabilities. It can make traditional network attack traffic escape black-box online ML-NIDS. At the same time, model extraction and fuzzing test are used to enhance the convergence of VulnerGAN. Compared with the state-of-the-art algorithms, the VulnerGAN backdoor attack increases33.28% in concealment, 18.48% in aggressiveness, and 46.32% in timeliness.

关键词： AI security adversarial sample data poisoning network intrusion detection generative adversarial network

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