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Defining region-specific heatwave in China based on a novel concept of “avoidable mortality for each temperature unit decrease”

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Advances in Climate Change Research 2021年第5期12卷 611-618页

作者： liu jiang-mei AI Si-Qi QI Jin-Lei WANG Li-Jun ZHOU Mai-Geng WANG Chong-Jian YIN Peng LIN Hua-Liang National Center for Chronic and Noncommunicable Disease Control and Prevention Chinese Center for Disease Control and PreventionBeijing100050China Department of Epidemiology School of Public HealthSun Yat-sen UniversityGuangzhou510080China Department of Epidemiology School of Public HealthZhengzhou UniversityZhengzhou450000China

The distribution of temperature and temperature-health association varied largely across different regions in China,a region-specific definition for heatwave was therefore *** collected the data on daily mortality,meteorological factors and air pollution in 84 Chinese cities during 2013–2016,which was divided into seven *** on the association between daily maximum temperature and mortality in each city in a threshold distributed lag non-linear model,where the threshold was defined as the temperature corresponding to the lowest mortality risk,we calculated the number of deaths that could be avoided for 1℃ decrease in maximum temperature under different thresholds,then a random-effect meta-analysis was used to generate regional results,in which the temperature with the highest avoidable mortality number for 1℃ decrease was considered as the most appropriate heatwave *** observed an immediate detrimental effect of high temperature within three lag *** analysis suggested to use 29.5℃,31.5℃,29.0℃,31.5℃,30.0℃,and 28.5℃ as the heatwave standard for east,north,northeast,central,south,and southwest region,with the avoidable mortality number of 1.54(95%Confidence interval(CI):0.88,2.19),0.55(95%CI:0.16,0.94),0.59(95%CI:0.32,0.86),1.14(95%CI:0.68,1.59),1.22(95%CI:0.54,1.90),and 0.78(95%CI:0.01,1.55),respectively,while the estimated number 0.19(95%CI:−0.02,0.40)in northwest region was not statistically *** concept of‘avoidable mortality for 1℃ decrease’was proposed to define the heatwave event,and varied maximum temperature between 28.5 and 31.5℃ was suggested for region-specific heatwave definition in China.

关键词： Heatwave Mortality burden Distributed lag non-linear model

Miyaoka-type inequalities for terminal threefolds with nef anti-canonical divisors

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Science China Mathematics 2025年第1期68卷 1-18页

作者： Masataka Iwai Chen jiang Haidong liu Department of Mathematics Graduate School of ScienceOsaka University Shanghai Center for Mathematical Sciences & School of Mathematical Sciences Fudan University Department of mathematics Sun Yat-sen University

In this paper,we study Miyaoka-type inequalities on Chern classes of terminal projective 3-folds with nef anti-canonical *** X be a terminal projective 3-fold such that-KXis *** show that if c1（X） · c2（X）≠0,then c1（X） · c2（X） ≥ 1/252;if further X is not rationally connected,then c1（X） · c2（X） ≥ 4/5 and this inequality is *** order to prove this,we give a partial classification of such varieties along with many *** also study the nonvanishing of c1（X）dim X-2· c2（X） for terminal weak Fano varieties and prove a Miyaoka-Kawamata-type inequality.

关键词： terminal threefolds Miyaoka-type inequality boundedness

COVID-19 seeding time and doubling time model:an early epidemic risk assessment tool

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Infectious Diseases of Poverty 2020年第3期9卷 3-11页

作者： Lei Zhou jiang-mei liu Xiao-Ping Dong Jennifer M.McGoogan Zun-You Wu Public Health Emergency Center Chinese Center for Disease Control and Prevention155 Changbai RoadChangping DistrictBeijing 102206China National Center for Chronic and Noncommunicable Disease Control and Prevention Chinese Center for Disease Control and Prevention155 Changbai RoadChangping DistrictBeijing 102206China Global Health Center Chinese Center for Disease Control and Prevention155 Changbai RoadChangping DistrictBeijing 102206China National Center for AIDS/STD Control and Prevention Chinese Center for Disease Control and Prevention155 Changbai RoadChangping DistrictBeijing 102206China

Background:As COVID-19 makes its way around the globe,each nation must decide when and how to *** many knowledge gaps persist,and many countries lack the capacity to develop complex models to assess risk and *** paper aimed to meet this need by developing a model that uses case reporting data as input and provides a four-tiered risk assessment ***:We used publicly available,country/territory level case reporting data to determine median seeding number,mean seeding time(ST),and several measures of mean doubling time(DT)for *** then structured our model as a coordinate plane with ST on the x-axis,DT on the y-axis,and mean ST and mean DT dividing the plane into four quadrants,each assigned a risk *** analysis was performed and countries/territories early in their outbreaks were assessed for ***:Our main finding was that among 45 countries/territories evaluated,87%were at high risk for their outbreaks entering a rapid growth phase *** furthermore found that the model was sensitive to changes in DT,and that these changes were consistent with what is officially known of cases reported and control strategies implemented in those ***:Our main finding is that the ST/DT Model can be used to produce meaningful assessments of the risk of escalation in country/territory-level COVID-19 epidemics using only case reporting *** model can help support timely,decisive action at the national level as leaders and other decision makers face of the serious public health threat that is COVID-19.

关键词： Seeding time Doubling time Case report Risk assessment SARS-CoV-2 COVID-19

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Microstructural evolution during the progressive transformation-induced plasticity effect in a Fe-0.1C-5Mnmedium manganese steel

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 369-379页

作者： mei Zhang Wenhao Li Yangfei Chen Yang jiang Xiaofei Guo Han Dong School of Materials Science and Engineering Shanghai UniversityShanghai 200444China State Key Laboratory of Advanced Special Steel Shanghai UniversityShanghai 200444China

The microstructural evolution of a cold-rolled and intercritical annealed medium-Mn steel(Fe-0.10C-5Mn)was investigated during uniaxial tensile ***-situ observations under scanning electron microscopy,transmission electron microscopy,and X-ray diffraction analysis were conducted to characterize the progressive transformation-induced plasticity process and associated fracture initiation *** findings were discussed with the local strain measurements via digital image *** results indicated that Lüders band formation in the steel was limited to 1.5%strain,which was mainly due to the early-stage martensitic phase transformation of a very small amount of the less stable large-sized retained austenite(RA),which led to localized stress concentrations and strain hardening and further retardation of *** small-sized RA exhibited high stability and progressively transformed into martensite and contributed to a stably extended Portevin-Le Chatelier *** volume fraction of RA gradually decreased from 26.8%to 8.2%prior to *** the late deformation stage,fracture initiation primarily occurred at the austenite/martensite and ferrite/martensite interfaces and the ferrite phase.

关键词： medium-Mn steel retained austenite progressive transformation-induced plasticity effect local strain fracture initiation

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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

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

Soft-sensing Modeling Method Based On Continuous Hidden Markov Model For Microbial Fermentation Process

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Soft-sensing Modeling Method Based On Continuous Hidden Mark...

Near-perfect replication on amorphous alloys through active force modulation based on machine learning/neural network parameter prediction

2010 Chinese Control and Decision Conference

作者： Guohai liu,Xingke jiang,Congli mei School of Electrical and Information Engineering,jiangsu University,Zhenjiang,212013

Considering the temporality of microbial fermentation process,a soft-sensing modeling method based on Continuous Hidden Markov Model(CHMM) for microbial fermentation process is ***,in order to improve the robustness of CHMM,multi-observation training sample sequences are used to train the *** the modified Baum- Welch parameters re-estimation formula is used to optimize the parameters of ***,the new observation vector is inputed to the CHMM model library and the emission probability of each CHMM in the model library is calculated using the Viterbi ***,the soft-sensing result can be obtained by computing the weighted *** model is applied to an erythromycin fermentation process,and case studies show that the new approach has better performance compared to the conventional method based on ANN.

关键词： Soft-sensing modeling Continuous Hidden Markov Model(CHMM) Modified Baum-Welch parameters re-estimation formula Fermentation process

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 181-191页

作者： Senkuan Meng Zheng Wang Ruisong Zhu Ruijie liu jiang Ma Lina Hu Weihua Wang Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials (Ministry of Education) School of Materials Science and Engineering Shandong University College of Mechatronics and Control Engineering Shenzhen University Songshan Lake Materials Laboratory Institute of Physics Chinese Academy of Sciences

As a microforming technique, micro/nano-structural replication possesses advantages of high precision and efficiency. With the remarkable superplasticity in the supercooled liquid region, amorphous alloys or metallic glasses(MGs) are regarded as ideal materials for miniature fabrication. However, due to the intrinsic metastable nature of supercooled liquids, the design of imprinting processes for MGs poses a challenge. In the past, process parameters have largely relied on trial-and-error *** this work, a low-frequency active force modulation system is employed to apply a stable, precise, and real-time feedback stress field for imprinting of MG samples. Low-frequency vibrations can facilitate the filling of microstructures on the template surface by reducing the effective viscosity of the supercooled liquid. With the dataset composed of orthogonal experiments, a machine learning strategy based on back-propagation(BP) neural networks was utilized to construct a 3D parameter space for temperature, stress, and time, and to predict the corresponding filling ratio. Furthermore, the optimal combination of imprinting process parameters was identified, and its filling ratio was experimentally validated to reach as high as 0.94. The near-perfect replication of microstructures confirms the superiority of the active force modulation system and the data-driven strategy of machine learning-assisted parameter design. At the same time, this one-step microforming process provides a new approach to addressing the accuracy-cost trade-off dilemma in precision manufacturing.

关键词： metallic glass amorphous alloy microforming imprinting machine learning

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钦州湾海域网采浮游植物群落结构季节变化

海洋科学进展 2017年第1期35卷 83-95页

作者：刘璐姜美洁李艳孙萍王宗灵国家海洋局第一海洋研究所海洋生态研究中心山东青岛266061

基于2013-2014年钦州湾海域4个季度月的现场调查数据,研究了网采浮游植物的群落结构。共鉴定出浮游植物6门54属134种(包括变型和变种),其中硅藻种数共107种,占79.9%;甲藻23种,占17.2%。调查期间的优势种,除球形棕囊藻外其余均为硅藻,并... 详细信息

基于2013-2014年钦州湾海域4个季度月的现场调查数据,研究了网采浮游植物的群落结构。共鉴定出浮游植物6门54属134种(包括变型和变种),其中硅藻种数共107种,占79.9%;甲藻23种,占17.2%。调查期间的优势种,除球形棕囊藻外其余均为硅藻,并多为广温性种。不同季节的浮游植物细胞丰度差异明显,表现为2014-08最高,2013-11最低。相关性分析表明浮游植物丰度与环境因子的相关性存在季节变化,春季受硝酸盐影响显著,夏季与温度、盐度均呈负相关,秋季受盐度和DIN影响显著,冬季则与环境因子相关性不显著。浮游植物群落多样性指数及均匀度指数较高,物种较丰富,群落结构稳定性较高。

关键词：钦州湾浮游植物优势种丰度多样性

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