基于IMOCS-BP神经网络的锂离子电池SOH估计

锂离子电池随着循环充放电次数的增长,其健康状态SOH(state-of-health)会随之发生一定程度的衰减。针对以上问题,设计了一种基于改进的多目标布谷鸟搜索IMOCS(improved multi-objective Cuckoo search)-BP神经网络的锂离子电池健康状态估计方法,在避免算法陷入局部最优的同时自适应改变布谷鸟搜索CS(Cuckoo search)算法更新概率和搜索步长,解决CS算法收敛速度慢和求解精度低的问题。以IMOCS算法和BP神经网络结合,对节点空间范围进行全局搜索,降低权值和阈值的初值对BP神经网络的影响,实现参数优化。通过Matlab仿真,验证了基于IMOCS-BP神经网络的SOH估计算法误差低、性能强,实现了锂电池SOH的精准预测。

基于EKF算法的纯电动汽车锂电池SOC与SOH联合估算

为提高对动力电池的荷电状态(state of charge, SOC)估算精度、动力电池的健康状态(state of health, SOH)对锂电池性能的影响,提出一种扩展卡尔曼滤波(extended kalman filtering, EKF)联合估算算法。根据现有的实验数据,分析锂电池特性,构建二阶RC等效电路模型,并进行参数辨识,搭建MATLAB仿真平台联合EKF算法进行SOC估算,将仿真结果与真实数据进行对比,结果表明,EKF联合估算SOC比EKF估算SOC误差精度约高1.2%,且抗干扰能力更强。

基于改进DELM在不同放电工况下的锂电池SOH预测方法研究

锂电池性能受到多种因素的影响,尤其在不同放电工况下其健康状态(SOH)预测难度极大增加.因此,研究以基于深度极限学习机为基础的锂电池SOH预测方法为基础,利用改进鲸鱼优化算法解决深度极限学习机中存在的随机权重和偏置问题,旨在提高锂电池SOH预测的精确率.对比实验结果表明,研究提出的预测方法算法的误差在[-0.02,0.04]之间,平均精确率达到96.23%,相比利用麻雀搜索算法、灰狼优化算法,改进的深度极限学习机算法分别提升了9.67%和5.05%.平均召回率为90.83%,平均误报率为3.75%.此外,高负载工况下,100次充放电循环后锂电池SOH值仅有0.221,下降幅度最大.不同工况下研究提出的预测方法平均精确率达到96.07%.研究提出的锂电池健康状态预测方法对于提高电池性能、延长寿命、提高安全性和降低环境影响具有重要的实际意义.

全健康(One Health)视角下绿色健康社区景观设计体系构建

以全健康(OneHealth)视角为出发点,保障人、环境和动物的健康对于社区健康环境规划与设计具有重要意义。在现有健康社区景观设计体系中,人、环境、物种三者关系虽被提及,但未被系统探究,健康社区建设实践也需要系统性的景观设计体系支持。基于全健康理念中人、环境和物种的相互关系,结合生态系统服务功能、康复景观理论和园艺疗法,进一步探讨人、环境、物种健康之间的关联途径。通过对全健康理念视角下的3个层次进行演绎发展,归纳总结了人的健康、环境健康和物种健康的组成要素及内容,构建了以人的健康需求为导向的社区健康设计框架,提出了以人与人际、人与环境和人与物种为三大圈层的健康社区景观设计体系。全健康视角为社区健康环境设计提供了一个系统性、整合性且具有操作性的框架,未来应重视健康社区体系中各类疗愈空间的设计与使用,以增进社区居民共享的健康福祉。

基于迁移学习与GRU神经网络结合的锂电池SOH估计

为解决退役电池梯次利用过程中单体剩余使用寿命估计困难、测试流程复杂与能耗高等问题,提出迁移学习与GRU网络结合的锂离子电池健康状态估计方法;设计的基础模型结构为输入层+GRU层+全连接层+输出层;根据健康因子的得分,选择训练基础模型的数据集、划分电池相似度等级并制定对应的迁移学习策略。实验结果表明:与其他模型相比,分别使用数据集的前40%与前25%训练得到的基础模型与迁移学习模型,两者的精度分别最大提高42.48%与95.28%,而预测稳定性分别最大提高55.38%与93.55%。

基于非参数模型与粒子滤波的锂电池SOH估计

健康状态(state of health,SOH)是电池管理系统的重要参考依据,准确的SOH估计对保证电池安全稳定运行具有重大意义,其中提取可靠有效的健康特征描述电池老化状态以及构建精确稳定的估计模型是目前面临的主要问题。为了提高SOH估计精度,提出了一种基于模糊熵和粒子滤波(particle filter,PF)的锂离子电池SOH估计方法。首先,通过分析电池老化过程中的放电电压数据,提取模糊熵值作为电池的老化特征;其次,基于代谢灰色模型(metabolic grey model,MGM)和时间卷积网络(temporal convolutional network,TCN)构建描述锂电池老化特征的非参数状态空间模型;最后,通过PF实现锂电池SOH的闭环估计。此外,利用NASA锂电池数据集对所提出的SOH估计方法进行了验证,并与该领域其他方法进行对比实验。结果表明,所提方法最大估计误差在5%左右,相比于同类方法其估计精度提升了约50%,且在不同训练周期数条件下表现出较好的鲁棒性,验证了所提方法的可行性与优越性。

基于融合健康因子和集成极限学习机的锂离子电池SOH在线估计

锂离子电池健康状态(SOH)的在线估计对电池管理系统的安全稳定运行至关重要.为克服传统基于数据驱动的锂离子电池SOH估计方法训练时间长、计算量大、调试过程复杂的问题,提出一种基于融合健康因子和集成极限学习机的锂离子电池SOH估计方法.该方法通过dQ/dV和dT/dV曲线分析,筛选出与电池SOH相关性较高的数据区间进行多维健康特征提取,并对其进行主成分分析降维处理得到间接健康因子;利用极限学习机的随机学习算法建立间接健康因子和SOH之间的非线性映射关系.在此基础上,针对单一模型输出不稳定的特点,提出一种集成极限学习机模型,通过对估计结果设置可信度评价规则剔除单一极限学习机不可靠的输出,从而提高锂离子电池SOH的估计精度.使用NASA和牛津大学的锂离子电池老化数据集对该方法进行验证,结果表明该方法的平均绝对百分比误差小于1%,具有较高的准确性和可靠性.

Challenges and opportunities for battery health estimation:Bridging laboratory research and real-world applications

Addressing climate change demands a significant shift away from fossil fuels,with sectors like electricity and transportation relying heavily on renewable energy.Integral to this transition are energy storage systems,notably lithium-ion batteries.Over time,these batteries degrade,affecting their efficiency and posing safety risks.Monitoring and predicting battery aging is essential,especially estimating its state of health(SOH).Various SOH estimation methods exist,from traditional model-based approaches to machine learning approaches.

适用于无人水下潜航器电池管理系统的SOC-SOH联合估计

为了提高无人水下潜航器(UUV)电池管理系统状态的估计精度,提出荷电状态-健康状态(SOC-SOH)联合估计方法.搭建测试台架,采用4组锂离子电池进行全寿命周期下的充放电测试,获取不同老化程度下的特性数据.经理论推导和实验分析设计四维表征因子,建立基于改进支持向量回归(SVR)的SOH估计模型.探究电池状态的耦合关系,建立基于扩展卡尔曼滤波(EKF)的SOC估计模型,采用遗忘因子递推最小二乘算法(RLS)更新模型参数,利用SOH对SOC估计结果进行修正.通过不同工况的实验进行验证,结果表明:四维表征因子和电池容量相关性好,SOH估计模型精度高,SOC估计模型精度在联合修正后得到提升.所提的联合估计方法具有较高的通用性和可靠性,可以作为有效的嵌入式电池管理系统状态估计算法.

基于V2G与XGBoost技术的锂电池SOH估计与RUL预测分析

阐述针对锂离子电池特征提取困难导致SOH预测精确度较低的问题,提出一种基于V2G技术的充放电过程与XGBoost的锂电池SOH预测及RUL预测方法。通过从充电曲线中提取的滤波后曲线峰值与峰值对应点电压作为充电过程中的健康因子,以及放电过程中的周期放电电压达到最低点的时间和平均电压衰减,作为放电过程中的健康因子XGBoost模型的输入,进行电池SOH预测,结合SOH估计值和估算模型实现RUL的长期预测。实验结果表明,改进后的模型具有更高的估算精度,SOH估计和RUI预测精度较高。

基于多模型组合和EIS的锂电池SOH和RUL预测

电池健康状态(state of health, SOH)和剩余使用寿命(remaining useful life, RUL)是评价电池健康程度和剩余寿命的重要技术指标。SOH和RUL的估计是电池管理系统的重要组成部分,是实现电池管理系统智能监控和科学运营的基础。电池电化学阻抗谱(electrochemical impedance spectroscopy, EIS)是一种用于表征电池内部电化学过程的测试方法,它具备精度高和非侵入性损害等优点。多种研究表明,电池阻抗谱EIS与电池的SOH和RUL存在一些内在的联系,因此成为电化学领域的研究热点。基于EIS预测SOH和RUL,传统机器学习方法比较成熟,但预测精度和稳定性仍有局限,难以完全挖掘电池衰减规律。因此,需要与深度学习等方法相结合才能提高预测性能。将降维模型和多种深度学习模型引入SOH和RUL预测领域,并对模型进行有效组合,取得了很好的效果。将EIS所有频率对应的实部和虚部数据依次排列作为频率特征,首先使用主成分分析(principle component analysis, PCA)模型对EIS值进行降维,提炼出10个精炼的主成分,然后使用卷积神经网络(convolution neural network, CNN)模型提取EIS的空间特征,使用双向长短期记忆网络(bidirectional long short-term memory, BiLSTM)模型提取EIS时间序列变化规律,使用注意力(attention)机制进一步选取EIS数据的时空特征中的重要部分,共同预测SOH和RUL。在测试数据上进行实验表明,SOH预测的均方误差(root mean square error, RMSE)达到0.146 8,RUL预测的均方误差达到2.614 5,效果均好于传统的方法。

How University Athletics Can Impact Mental Health among Student Athletes at the University of Evansville

In recent years, the NCAA student athlete population in the United States has surpassed 500,000, and is continuing to rise each year [1]. These student athletes work their entire lives academically and athletically to reach the ultimate goal: competing in university athletics. However, when these athletes reach university, they are met with non-stop training, homework, exams, and evolving social lives. We have conducted a study at the University of Evansville evaluating how participation in university athletics may impact mental health status among these student athletes, as well as measuring players’ awareness of accessible mental health resources. Over fifty percent of participants reported experiencing at least one mental health condition while competing in their sport;eighty percent reported having knowledge of the mental health resources available to them on campus, however, nearly thirty percent of those knowledgeable reported not knowing how to access these resources. This has indicated a gap in awareness and utilization of mental health resources among student athletes at the University of Evansville.

Health Systems Strengthening to Tackle the Global Burden of Pediatric and Congenital Heart Disease: A Diagonal Approach

1 Background Congenital heart disease(CHD)is the most common major congenital anomaly,affecting approximately one in every 100 live births[1].Among congenital anomalies,66%of preventable deaths are due to CHD,and 58%of the avertable morbidity and mortality due to congenital anomalies would result from scaling congenital heart surgery services[2].Every year,nearly 300,000 children and adults die from CHD,the majority of whom live in low-and middle-income countries(LMICs)[3].Approximately 49%of all individuals with CHD will require surgical or interventional care at some point in their lifetime[4];as a result of advances in access to and the delivery of such services,over 95%of children born with CHD in high-income countries now live into adulthood[3].Here,adults have surpassed children in the number of CHD cases at a ratio of 2:1[5].

世界动物卫生组织One Health总体框架及最新关注方向

近年来,人兽共患病在全球越来越多的地方影响人类和动物的健康。在此背景下,由联合国粮食及农业组织(FAO)、世界卫生组织(WHO)和世界动物卫生组织(WOAH)三方国际组织提出了“One Health”的概念。2021年底,FAO、WOAH、WHO和联合国环境规划署(UNEP)共同成立了One Health高级别委员会(One Health High Level Expert Panel,OHHLEP),并将“One Health”重新定义。论文就“One Health”的概念、提出的背景、重要发展进程、总体框架和协调机制以及未来应用展望进行了全面的介绍和阐述,为我国进一步深入了解“One Health”理念,实践并更好地应用“One Health”方法,从而解决我国人兽共患病、抗生素耐药等对人类、动物和环境危害严重的问题提供思路和参考。

美国《保健物理》(Health Physics)杂志英文摘要(2023年126卷第2期)

Statistical Analysis of Radioactivity:Lamprecht Uranium Mine in Texas Mark C.Harvey1 and Nancy L.Glenn Griesinger2(1.Department of Physics,Texas Southern University,Houston,TX 77004;2.Department of Mathematical Sciences,Texas Southern University,Houston,TX 77004)Abstract:The former Lamprecht uranium mine facility in Texas ceased operations well before the new millennium.However,decommissioning activities were never completed by the licensee.Consequently,a legal proceeding was authorized between state and licensee representatives.Meanwhile,state funds were used to hire an independent contractor to perform radiological surveys and assess the magnitude of residual radioactivity across the terrain at the site.The purpose of this study was to apply advanced spatial statistical methods to the survey data measured by contractors at the Lamprecht site to precisely predict remaining radioactive hotspot locations post soil remediation activities.

Observation on the Effect of Health Education in Health Management of Chronic Disease Patients

Objective: By the end of 2021, the aging rate of China’s population is 18.9%, and the prevalence rate of chronic diseases in the elderly population is increasing year by year, and chronic diseases have become the main causes of death and health threats of Chinese residents. Therefore, how to manage this huge group well is crucial. This paper analyzes the value of health education in the process of health management for patients with chronic diseases. Methods: 102 patients with chronic diseases treated from January 2021 to December 2021 were divided into control group and experimental group by random number table method. The control group was given routine health management while the experimental group was given health education based on the control group, and the implementation effect was analyzed. Results: After management, the scores of chronic disease knowledge in the experimental group were significantly higher than those in the control group, and the dimensions of ESCA were higher than those in the control group, and P < 0.05;Conclusion: The implementation of health education in the process of chronic disease health management is helpful to improve patients’ self-care ability and better control disease progression.

美国《保健物理》(Health Physics)杂志英文摘要(2023年125卷第6期)

Evaluation of the Performance of Different Types of Radiation Protection Gloves: A Cross-sectional Study Mitsuyoshi Yasuda1,2 , Syoji Manabu2 , Tomoki Fuji2 , Noritaka Seino3 , Hiroyuki Watanabe1,2 , Hisaya Sato1,4 , Kyoichi Kato1,5 (1. Graduate School of Health Sciences, Showa University, 1865 Tokaichiba, Midori- ku, Yokohama, Kanagawa 226 - 0025, Japan;2. Department of Radiological Technology, Showa University Hospital, 1- 5- 8 Hatanodai, Shinagawa - ku, Tokyo 142 - 8666, Japan;3. Department of Radiology, Showa University, 1-5-8 Hatanodai, Shinagawa-ku, Tokyo 142-8666, Japan;4. Department of Radiology, Showa University Fujigaoka Hospital, 1-30 Fujigaoka Aoba-ku, Yokohama, Kanagawa 227-8501, Japan;5. Department of Radiological Technology, Showa University, Tokyo, Japan)

Alexa,let's train now!——A systematic review and classification approach to digital and home-based physical training interventions aiming to support healthy cognitive aging

Background:There is mounting evidence that regular physical activity is an important prerequisite for healthy cognitive aging.Consequently,the finding that almost one-third of the adult population does not reach the recommended level of regular physical activity calls for further public health actions.In this context,digital and home-based physical training interventions might be a promising alternative to center-based intervention programs.Thus,this systematic review aimed to summarize the current state of the literature on the effects of digital and home-based physical training interventions on adult cognitive performance.Methods:In this pre-registered systematic review(PROSPERO;ID:CRD42022320031),5 electronic databases(PubMed,Web of Science,Psyclnfo,SPORTDiscus,and Cochrane Library)were searched by 2 independent researchers(FH and PT)to identify eligible studies investigating the effects of digital and home-based physical training interventions on cognitive performance in adults.The systematic literature search yielded 8258 records(extra17 records from other sources),of which 27 controlled trials were considered relevant.Two reviewers(FH and PT)independently extracted data and assessed the risk of bias using a modified version of the Tool for the assEssment of Study qualiTy and reporting in EXercise(TESTEX scale).Results:Of the 27 reviewed studies,15 reported positive effects on cognitive and motor-cognitive outcomes(i.e.,performance improvements in measures of executive functions,working memory,and choice stepping reaction test),and a considerable heterogeneity concerning study-related,population-related,and intervention-related characteristics was noticed.A more detailed analysis suggests that,in particular,interventions using online classes and technology-based exercise devices(i.e.,step-based exergames)can improve cognitive performance in healthy older adults.Approximately one-half of the reviewed studies were rated as having a high risk of bias with respect to completion adherence(≤85%)and monitoring of the level of regular physical activity in the control group.Conclusion:The current state of evidence concerning the effectiveness of digital and home-based physical training interventions is mixed overall,though there is limited evidence that specific types of digital and home-based physical training interventions(e.g.,online classes and step-based exergames)can be an effective strategy for improving cognitive performance in older adults.However,due to the limited number of available studies,future high-quality studies are needed to buttress this assumption empirically and to allow for more solid and nuanced conclusions.

Shifting the Paradigm:A Fresh Look at Physical Activity Frequency and Its Impact on Mental Health,Life Satisfaction,and Self-Rated Health in Adolescents

As adolescent mental health problems are becoming a more serious issue globally,this paper explores the relationship of physical activity in adolescents and its frequency on mental health as well as examines the mediating effects of life satisfaction and self-rated health in order to provide a reference for the promotion of mental health in adolescents.A sample of 3578 Chinese high school students completed questionnaires assessing their mental health,physical activity frequency,life satisfaction,and self-rated health.The mean SCL-90 value for adolescents was found to be 1.629%,and 24.73%of adolescents had varying degrees of mental health issue.Increased physical activity frequency is positively associated with improved mental health(p<0.001).Additionally,life satisfaction and self-rated health were found to play significant mediating roles in the relationship between physical activity frequency and mental health.Specifically,low-frequency physical activity had the most pronounced mediating effect on mental health through life satisfaction,while high-frequency physical activity exerted the most significant mediating effect on mental health through self-rated health.These findings underscore the importance of promoting physical activity among adolescents and highlight the distinct pathways through which physical activity frequency can influence mental health outcomes.Further research is needed to explore these relationships in diverse populations and settings,as well as to develop targeted intervention.

A Blockchain and CP-ABE Based Access Control Scheme with Fine-Grained Revocation of Attributes in Cloud Health

The Access control scheme is an effective method to protect user data privacy.The access control scheme based on blockchain and ciphertext policy attribute encryption(CP–ABE)can solve the problems of single—point of failure and lack of trust in the centralized system.However,it also brings new problems to the health information in the cloud storage environment,such as attribute leakage,low consensus efficiency,complex permission updates,and so on.This paper proposes an access control scheme with fine-grained attribute revocation,keyword search,and traceability of the attribute private key distribution process.Blockchain technology tracks the authorization of attribute private keys.The credit scoring method improves the Raft protocol in consensus efficiency.Besides,the interplanetary file system(IPFS)addresses the capacity deficit of blockchain.Under the premise of hiding policy,the research proposes a fine-grained access control method based on users,user attributes,and file structure.It optimizes the data-sharing mode.At the same time,Proxy Re-Encryption(PRE)technology is used to update the access rights.The proposed scheme proved to be secure.Comparative analysis and experimental results show that the proposed scheme has higher efficiency and more functions.It can meet the needs of medical institutions.