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An indicator model for assessing community resilience to the COVID-19 pandemic and its validation: A case study in Hong Kong

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Journal of Safety Science and Resilience 2024年第2期5卷 222-234页

作者： nan Liao Muhammad Nawaz Departnent of Geography Faculty Art and Social SciencesSingapore 65166666Singapore

The COVID-19 outbreak had a significant negative impact on the world,and the fifth wave of COVID-19 in Hong Kong brought a considerable shock to Chinese *** is a growing call for more resilient ***,empirical evidence and validation of modeling studies of resilience indicators for urban community responses to the COVID-19 pandemic still need to be *** this study,a resilience assessment indicator model comprising 4 subsystems,7 indicators,and 12 variables was developed to assess the resilience of Hong Kong communities in response to COVID-19(i.e.,Resilience Index).Furthermore,this study utilized regression models such as geographically weighted regression(GWR)and multiscale GWR(MGWR)to validate the resilience model proposed in this study at the model and variable *** the regression model,the Resilience Index and the individual variables in the resilience model are explanatory variables,and the outcomes of the COVID-19 pandemic(confirmed cases,confirmation rate,discharged cases,discharge rate)are dependent *** results showed that:(i)the resilience of Hong Kong communities to the COvID-19 pandemic was not strong in general and showed some clustered spatial distribution characteristics;(i)the validation results at the model level showed that the Resilience Index did not explain the consequences of the COvID-19 pandemic to a high degree;(ii)the validation results at the variable level showed that the MGWR model was the best at identifying the relationships between explanatory variables and the dependent variable;and(iv)compared with the model-level assessment results,the variable-level assessment explained the consequences of the COvID-19 pandemic better than the model level assessment *** above analysis and the spatial distribution maps of the resilience variables can provide empirically based and targeted insights for policymakers.

关键词： Resilience Community resilience CoVID-19pandemic Resilience assessment indicator model Resilience model validation MGWR

ACTN1 promotes malignant progression in cutaneous squamous cell carcinoma by downregulating the p53 signaling pathway

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中华医学杂志(英文版) 2024年第14期137卷 1759-1761页

作者： Yuan Tao Lu Xiaohong Jiang Jiahui Chen nan Tang Biao he Caifeng Liu Wenbei Wang Jun Ci Chao Department of Dermatology Yijishan Hospital the First Affiliated Hospital of Wannan Medical College Wuhu Anhui China

Low Surface Brightness Galaxies from BASS+MzLS with Machine Learning

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Research in Astronomy and Astrophysics 2024年第5期24卷 185-197页

作者： Peng-Liang Du Wei Du Bing-qing Zhang Zhen-Ping Yi Min he Hong Wu Key Laboratory of Optical Astronomy National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China School of Astronomy and Space Science University of Chinese Academy of SciencesBeijing 100049China School of Mechanical Electrical and Information EngineeringShandong UniversityWeihai 264209China

From ∼5000 deg^(2) of the combination of the Beijing–Arizona Sky Survey and Mayall z-band Legacy Survey which is also the northern sky region of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, we selected a sample of 31,825 candidates of low surface brightness galaxies (LSBGs) with the mean effective surface brightness 24.2he half-light radius 2.″5 he released photometric catalog and the machine learning model. The distribution of the LSBGs is bimodal in the g−r color, indicating the two distinct populations of the blue (g−r 0.60) LSBGs. The blue LSBGs appear spiral, disk or irregular while the red LSBGs are spheroidal or elliptical and spatially clustered. This trend shows that the color has a strong correlation with galaxy morphology for LSBGs. In the spatial distribution, the blue LSBGs are more uniformly distributed while the red ones are highly clustered, indicating that red LSBGs preferentially populate a denser environment than the blue LSBGs. Besides, both populations have a consistent distribution of ellipticity (median ∈∼ 0.3), half-light radius (median r_(eff) ∼ 4″) and Sérsic index (median n=1), implying the dominance of the full sample by the round and disk galaxies. This sample has definitely extended the studies of LSBGs to a regime of lower surface brightness, fainter magnitude and broader other properties than the previously Sloan Digital Sky Survey-based samples.

关键词： catalogs-galaxies fundamental parameters-galaxies statistics-techniques photometric

Predictive value of machine learning models for lymph node metastasis in gastric cancer: A two-center study

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World Journal of Gastrointestinal Surgery 2024年第1期16卷 85-94页

作者： Tong Lu Miao Lu Dong Wu Yuan-Yuan Ding Hao-nan Liu Tao-Tao Li Da-qing Song Department of Emergency Medicine Jining No.1 People’s HospitalJining 272000Shandong ProvinceChina Wuxi Mental health Center Wuxi 214000Jiangsu ProvinceChina Department of Gastroenterology Jining No.1 People’s HospitalJining 272000Shandong ProvinceChina Department of Oncology The Affiliated Hospital of Xuzhou Medical UniversityXuzhou 221002Jiangsu ProvinceChina

BACKGROUND Gastric cancer is one of the most common malignant tumors in the digestive system,ranking sixth in incidence and fourth in mortality *** 42.5%of metastatic lymph nodes in gastric cancer belong to nodule type and peripheral type,the application of imaging diagnosis is *** To establish models for predicting the risk of lymph node metastasis in gastric cancer patients using machine learning(ML)algorithms and to evaluate their pre-dictive performance in clinical *** Data of a total of 369 patients who underwent radical gastrectomy at the Depart-ment of General Surgery of Affiliated Hospital of Xuzhou Medical University(Xuzhou,China)from March 2016 to November 2019 were collected and retro-spectively analyzed as the training *** addition,data of 123 patients who underwent radical gastrectomy at the Department of General Surgery of Jining First People’s Hospital(Jining,China)were collected and analyzed as the verifi-cation *** ML models,including decision tree,random forest,support vector machine(SVM),gradient boosting machine,naive Bayes,neural network,and logistic regression,were developed to evaluate the occurrence of lymph node metastasis in patients with gastric *** ML models were established fo-llowing ten cross-validation iterations using the training dataset,and subsequently,each model was assessed using the test *** models’performance was evaluated by comparing the area under the receiver operating characteristic curve of each *** Among the seven ML models,except for SVM,the other ones exhibited higher accuracy and reliability,and the influences of various risk factors on the models are *** The ML models developed exhibit strong predictive capabilities for lymph node metastasis in gastric cancer,which can aid in personalized clinical diagnosis and treatment.

关键词： Machine learning Prediction model Gastric cancer Lymph node metastasis

Progress on gas-solid phase photoreactor and its application in CO2 reduction

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Green Chemical Engineering 2024年第3期5卷 290-306页

作者： Litian Liu Yunlong Li Jialun he qing Wang Juan Deng Xiao Chen Chao Yu School of Environmental and Chemical Engineering Jiangsu University of Science and Technology

The burgeoning field of photocatalytic reduction of CO2has emerged as a remarkable promising solution to address some of the most pressing global energy and environmental issues which we face today. Researchers around the global have been striving to augment the efficiency of CO2photocatalytic reduction, employing strategies that range from modifying the fundamental properties of photocatalysts to suppress the electron-hole recombination, optimizing reaction conditions to achieve the highest yield, and conceptualizing and constructing photoreactors to improve the adsorption process. Among these factors, the photoreactor plays a critical role in enhancing the overall photocatalytic efficiency. Understanding the various types of photoreactors and their operational dynamic can significantly influence the experimental design, thus guiding the data collecting and analysis. Compared to the solid-liquid phase, gas-solid phase photocatalytic reduction of CO2is gaining recognition for its potential advantages, such as rapid molecular diffusion rates, adjustable CO2concentrations, and uniform and sufficient light exposure. Nonetheless, the currently reported gas-solid phase photoreactors are still in their infancy. In this review, we dissect the underlying mechanism of photocatalytic CO2reduction and the performance evaluation criteria of photoreactors, and review the development process of gas-solid phase photoreactors. Furthermore, we explore the evolution of gas-solid phase photoreactors, elucidating their growth trajectory and future possibilities. We present a comprehensive classification of gas-solid phase photoreactors,offering a new insight into their design and functionality, summarizing their strengths and inevitable ***, we provide a forward-looking perspective on the future developmental prospects of carbon neutrality.

关键词： Photoreactor Gas-solid phase Carbon dioxide reduction Photocatalysis

Deterministic and Robust Volt-var Control Methods of Power System Based on Convex Deep Learning

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 719-729页

作者： qing Ma Changhong Deng the School of Electrical Engineering and Automation Wuhan UniversityWuhanChina

Volt-var control(VVC)is essentially a non-convex optimization problem due to the non-convexity of power flow(PF)constraints,resulting in the difficulty in obtaining the optimum without convexity *** existing second-order cone method for the convexity conversion often leads to a sharp increase in PF constraints and optimization variables,which in turn increases the optimization difficulty or even leads to optimization *** paper first proposes a deterministic VVC method based on convex deep learning power flow(DLPF).This method uses the input convex neural network(ICNN)to establish a single convex mapping between state parameters and node voltage to complete the convexity conversion while the optimization variables only correspond to reactive power equipment,which can ensure the global optimum with extremely fast computation *** cope with the impact brought by the uncertainty of distributed energy and omit the additional worst scenario search of traditional robust VVC,this paper proposes robust VVC method based on convex deep learning interval power flow(DLIPF),which continues to adopt ICNN to establish another convex mapping between state parameters and node voltage *** DLIPF with DLPF,this method decreases the modeling and optimization difficulty of robust VVC *** results on 30-bus,118-bus,and 200-bus systems prove the correctness and rapidity of the proposed methods.

关键词： Volt-var control convexity conversion convex deep learning power flow

揭示氨对正己酸生产影响的机制——影响途径、关键酶和微生物

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Engineering 2024年第4期35卷 180-190页

作者： qing-Lian Wu Ke-Xin Yuan Wei-Tong Ren Lin Deng Hua-Zhe Wang Xiao-Chi Feng he-Shan Zheng nan-Qi Ren Wan-Qian Guo State Key Laboratory of Urban Water Resource and Environment Harbin Institute of TechnologyHarbin 150090China College of Architecture and Environment Sichuan UniversityChengdu 610065China State Key Laboratory of Urban Water Resource and Environment School of Civil and Environmental EngineeringHarbin Institute of Technology(Shenzhen)Shenzhen 518055China College of Chemistry and Chemical Engineering Qiqihar UniversityQiqihar 161006China

n-Caproate,which is produced via chain elongation(CE)using waste biomass,can supply various fossilderived products,thus advancing the realization of carbon *** released from the degradation of nitrogen-rich waste biomass can act as a nutrient or an inhibitor in anaerobic bioprocesses,including CE,with the distinction being primarily dependent on its ***,the optimal concentration of ammonia and the threshold of toxicity for open-culture n-caproate production using ethanol as an electron donor,along with the underlying mechanisms,remain *** study revealed that the optimal concentration of ammonia for n-caproate production was 2.0 g∙L^(-1),whereas concentrations exceeding this threshold markedly suppressed the CE *** of the mechanism revealed the involvement of two forms of ammonia(i.e.,ammonium ions and free ammonia)in this inhibitory *** ammonia levels(5.0 g∙L^(-1))induced excessive ethanol oxidation and suppressed the reverse β-oxidation(RBO)process,directly leading to the enhanced activities of enzymes(phosphotransacetylase and acetate kinase)responsible for acetate formation and diminished activities of butyryl-coenzyme A(CoA):acetyl-CoA transferase,caproyl-CoA:butyryl-CoA transferase,and caproyl-CoA:acetyl-CoA transferase that are involved in the syntheses of n-butyrate and ***,the composition of the microbial community shifted from Paraclostridium dominance(at 0.1 g∙L^(-1)ammonia)to a co-dominance of Fermentimonas,Clostridium sensu stricto 12,and Clostridium sensu stricto 15 at 2.0 g∙L^(-1)***,these CE-functional bacteria were mostly absent in the presence of excessive ammonia(5.0 g∙L^(-1)ammonia).Metagenomic analysis revealed the upregulation of functions such as RBO,fatty acid synthesis,K^(+)efflux,adenosine triphosphatase(ATPase)metabolism,and metal cation export in the presence of 2.0 g∙L^(-1)ammonia,collectively contributing to enhanced n-caproate produc

关键词： Ammonia inhibition Medium chain fatty acids n-Caproate Enzyme Metagenomics

Enhanced Electrical Properties of Styrene-grafted Polypropylene Insulation for Bulk Power Transmission HVDC Cables

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 361-370页

作者： Hao Yuan Shixun Hu Yao Zhou Chao Yuan Wenbo Song qing Shao Hongwei Shi Juan Li Jun Hu Qi Li Jinliang he SINOPEC Beijing Research Institute of Chemical Industry Beijing 100013China State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

Polypropylene(PP)is considered to be a rather promising material for HVDC cable *** modification has proved to be an effective method on the electrical property improvements of *** paper reports on the highlyenhanced electrical properties of styrene-grafted polypropylene(PP-g-St)and their related *** influence of grafting styrene on crystallization structures,thermal properties and electrical properties of PP-g-St are characterized and *** results show that PP-g-St exhibits remarkably enhanced DC volume resistivity,suppressed space charge accumulation and improved DC breakdown strengths as compared to *** observation shows PP-g-St has small,imperfect spherulites with indistinct boundaries,which is strongly correlated to enhanced electrical *** study provides an effective grafting strategy to design high-performance HVDC cable insulation materials for bulk power transmission systems.

关键词： Electrical properties grafting modification polypropylene styrene

Learning topological defects formation with neural networks in a quantum phase transition

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Communications in Theoretical Physics 2024年第5期76卷 68-76页

作者： Han-qing Shi Hai-qing Zhang Center for Gravitational Physics Department of Space ScienceBeihang UniversityBeijing 100191China Peng Huanwu Collaborative Center for Research and Education Beihang UniversityBeijing 100191China

Neural networks possess formidable representational power,rendering them invaluable in solving complex quantum many-body *** they excel at analyzing static solutions,nonequilibrium processes,including critical dynamics during a quantum phase transition,pose a greater challenge for neural *** address this,we utilize neural networks and machine learning algorithms to investigate time evolutions,universal statistics,and correlations of topological defects in a one-dimensional transverse-field quantum Ising ***,our analysis involves computing the energy of the system during a quantum phase transition following a linear quench of the transverse magnetic field *** excitation energies satisfy a power-law relation to the quench rate,indicating a proportional relationship between the excitation energy and the kink ***,we establish a universal power-law relationship between the first three cumulants of the kink numbers and the quench rate,indicating a binomial distribution of the ***,the normalized kink-kink correlations are also investigated and it is found that the numerical values are consistent with the analytic formula.

关键词： neural networks machine learning transverse-field quantum Ising model kibble-zurek mechanism