Polymer engineering for electrodes of aqueous zinc ion batteries

With the increasing demand for scalable and cost-effective electrochemical energy storage,aqueous zinc ion batteries(AZIBs)have a broad application prospect as an inexpensive,efficient,and naturally secure energy storage device.However,the limitations suffered by AZIBs,including volume expansion and active materials dissolution of the cathode,electrochemical corrosion,irreversible side reactions,zinc dendrites of the anode,have seriously decelerated the civilianization process of AZIBs.Currently,polymers have tremendous superiority for application in AZIBs attributed to their exceptional chemical stability,tunable structure,high energy density and outstanding mechanical properties.Considering the expanding applications of AZIBs and the superiority of polymers,this comprehensive paper meticulously reviews the benefits of utilizing polymeric applied to cathodes and anodes,respectively.To begin with,with adjustable structure as an entry point,the correlation between polymer structure and the function of energy storage as well as optimization is deeply investigated in respect to the mechanism.Then,depending on the diversity of properties and structures,the development of polymers in AZIBs is summarized,including conductive polymers,redox polymers as well as carbon composite polymers for cathode and polyvinylidene fluoride-,carbonyl-,amino-,nitrile-based polymers for anode,and a comprehensive evaluation of the shortcomings of these strategies is provided.Finally,an outlook highlights some of the challenges posed by the application of polymers and offers insights into the potential future direction of polymers in AZIBs.It is designed to provide a thorough reference for researchers and developers working on polymer for AZIBs.

Long-Term Performance and Microstructural Characterization of Dam Concrete in the Three Gorges Project

This study investigates the long-term performance of laboratory dam concrete in different curing environments over ten years and the microstructure of 17-year-old laboratory concrete and actual concrete cores drilled from the Three Gorges Dam.The mechanical properties of the laboratory dam concrete,whether cured in natural or standard environments,continued to improve over time.Furthermore,the laboratory dam concrete exhibited good resistance to diffusion and a refined microstructure after 17 years.However,curing and long-term exposure to the local natural environment reduced the frost resistance.Microstructural analyses of the laboratory concrete samples demonstrated that moderate-heat cement and fine fly ash(FA)particles were almost fully hydrated to form compact micro structures consisting of large quantities of homogeneous calcium(alumino)silicate hydrate(C-(A)-S-H)gels and a few crystals.No obvious interfacial transition zones were observed in the microstructure owing to the longterm pozzolanic reaction.This dense and homogenous microstructure was the crucial reason for the excellent long-term performance of the dam concrete.A high FA volume also played a significant role in the microstructural densification and performance growth of dam concrete at a later age.The concrete drilled from the dam surface exhibited a loose microstructure with higher microporosity,indicating that concrete directly exposed to the actual service environment suffered degradation caused by water and wind attacks.In this study,both macro-performance and microstructural analyses revealed that the application of moderate-heat cement and FA resulted in a dense and homogenous microstructure,which ensured the excellent long-term performance of concrete from the Three Gorges Dam after 17 years.Long-term exposure to an actual service environment may lead to microstructural degradation of the concrete surface.Therefore,the retained long-term dam concrete samples need to be further researched to better understand its microstructural evolution and development of its properties.

生态 TOD 模式下城市绿地与公共交通空间耦合研究

近年来受社会经济高速发展的驱动,中国的城市化建设正在如火如荼地进行。一方面,城市化进程的加快给城市发展带来了前所未有的机遇,另一方面也给中国的城市发展带来了一些负面影响。这主要表现为城市人口大幅增加,土地资源相对短缺,环境持续恶化,交通拥堵不断加剧,居民生活幸福指数下降等,因此在TOD模式下城市生态绿化环境空间发展与优化将成为城市交通设计新的模式。本研究探讨生态TOD模式下城市绿地与公共交通空间的耦合关系,提高耦合度和服务质量。

Current status of Helicobacter pylori eradication and risk factors for eradication failure

BACKGROUND The Helicobacter pylori(H.pylori)eradication rate is decreasing in the general population of China.AIM To evaluate the H.pylori eradication status in real-world clinical practice and to explore factors related to eradication failure.METHODS Patients with H.pylori infection who were treated with standard 14-d quadruple therapy and received a test of cure at a provincial medical institution between June 2018 and May 2019 were enrolled.Demographic and clinical data were recorded.Eradication rates were calculated and compared between regimens and subgroups.Multivariate analysis was performed to identify predictors of eradication failure.RESULTS Of 2610 patients enrolled,eradication was successful in 1999(76.6%)patients.Amoxicillin-containing quadruple regimens showed a higher eradication rate than other quadruple therapy regimens(83.0%vs 69.0%,P<0.001).The quadruple therapy containing amoxicillin plus clarithromycin achieved the highest eradication rate(83.5%).Primary therapy had a higher eradication rate than rescue therapy(78.3%vs 66.5%,P<0.001).In rescue therapy,the amoxicillinand furazolidone-containing regimens achieved the highest eradication rate(80.8%).Esomeprazole-containing regimens showed a higher eradication rate than those containing other proton pump inhibitors(81.8%vs 74.9%,P=0.001).Multivariate regression analysis found that older age,prior therapy,and use of omeprazole or pantoprazole were associated with an increased risk of eradication CONCLUSION The total eradication rate is 76.6%.Amoxicillin-containing regimens are superior to other regimens.Age,prior therapy,and use of omeprazole or pantoprazole are independent risk factors for eradication failure.

Effect of Tongluo Shenggu Prescription on ARCO Stage Ⅱ non-traumatic femoral head necrosis: A prospective study

Objective:To observe the clinical results and therapeutic characteristics of Tongluo Shenggu Decoction in the treatment of ARCOⅡnon-traumatic femoral head necrosis.Methods:120 patients with ARCOⅡnon-traumatic femoral head necrosis from January 2016 to January 2017 were studied by prospective matched and controlled design.60 cases in the treatment group were treated with Tongluo Shenggu Formula.The control group(60 cases)received high energy extracorporeal shock wave therapy.The imaging stability rate,Harris score and SF-36 score were used as clinical efficacy indicators,followed up for 24 months,and the follow-up results were statistically analyzed.Results:Among the 120 patients,5 fell off and the rest were followed up.The imaging stability rate is heavy.The imaging stability rate of the patients in the treatment group is 78.95%,while that in the control group is 72.41%.The two groups have the same stability rate(P>0.05).In Harris score,the Harris score of the patients in the treatment group was 92.678.45 points,significantly higher than that of the control group(80.3924.65 points),the difference was statistically significant(p<0.05),and the pain degree,joint function and joint deformity score of the treatment group were better than those of the control group(p<0.05).In the SF-36 score,the scores of physiological function,physiological function,physical pain,overall health,social function and emotional function in the treatment group were significantly higher than those in the control group,the difference was statistically significant(p<0.05).the incidence of adverse events in the treatment period of the two groups was lower and the patients could relieve themselves in the later stage.Conclusion:Tongluo Shenggu prescription has definite curative effect in treating ARCOⅡnon-traumatic femoral head necrosis,especially in improving hip joint function,relieving hip joint pain and improving quality of life.To observe the clinical results and therapeutic characteristics of Tongluo Shenggu Decoction in the treatment of ARCOⅡnon-traumatic femoral head necrosis.Methods:120 patients with ARCOⅡnon-traumatic femoral head necrosis from January 2016 to January 2017 were studied by prospective matched and controlled design.60 cases in the treatment group were treated with Tongluo Shenggu Formula.The control group(60 cases)received high energy extracorporeal shock wave therapy.The imaging stability rate,Harris score and SF-36 score were used as clinical efficacy indicators,followed up for 24 months,and the follow-up results were statistically analyzed.Results:Among the 120 patients,5 fell off and the rest were followed up.The imaging stability rate is heavy.The imaging stability rate of the patients in the treatment group is 78.95%,while that in the control group is 72.41%.The two groups have the same stability rate(P>0.05).In Harris score,the Harris score of the patients in the treatment group was 92.678.45 points,significantly higher than that of the control group(80.3924.65 points),the difference was statistically significant(p<0.05),and the pain degree,joint function and joint deformity score of the treatment group were better than those of the control group(p<0.05).In the SF-36 score,the scores of physiological function,physiological function,physical pain,overall health,social function and emotional function in the treatment group were significantly higher than those in the control group,the difference was statistically significant(p<0.05).the incidence of adverse events in the treatment period of the two groups was lower and the patients could relieve themselves in the later stage.Conclusion:Tongluo Shenggu prescription has definite curative effect in treating ARCOⅡnon-traumatic femoral head necrosis,especially in improving hip joint function,relieving hip joint pain and improving quality of life.

Intention Estimation of Adversarial Spatial Target Based on Fuzzy Inference

Estimating the intention of space objects plays an important role in air-craft design,aviation safety,military and otherfields,and is an important refer-ence basis for air situation analysis and command decision-making.This paper studies an intention estimation method based on fuzzy theory,combining prob-ability to calculate the intention between two objects.This method takes a space object as the origin of coordinates,observes the target’s distance,speed,relative heading angle,altitude difference,steering trend and etc.,then introduces the spe-cific calculation methods of these parameters.Through calculation,values are input into the fuzzy inference model,andfinally the action intention of the target is obtained through the fuzzy rule table and historical weighted probability.Ver-ified by simulation experiment,the target intention inferred by this method is roughly the same as the actual behavior of the target,which proves that the meth-od for identifying the target intention is effective.

Microneedles for Enhanced Topical Treatment of Skin Disorders:Applications,Challenges,and Prospects

Microneedles(MNs)can be used for the topical treatment of skin disorders as they directly deliver therapeutics to the site of skin lesions,resulting in increased therapeutic efficacy while having minimum side effects.MNs are used to deliver different kinds of therapeutics(e.g.,small molecules,macromolecules,nanomedicines,living cells,bacteria,and exosomes)for treating various skin disorders,including superficial tumors,wounds,skin infections,inflammatory skin diseases,and abnormal skin appearance.The therapeutic efficacy of MNs can be improved by integrating the advantages of multiple therapeutics to perform combination therapy.Through careful designing,MNs can be further modified with biomimetic structures for the responsive drug release from internal and external stimuli and to enhance the transdermal delivery efficiency for robust therapeutic outcomes.Some studies have proposed the use of drug-free MNs as a promising mechanotherapeutic strategy to promote wound healing,scar removal,and hair regeneration via a mechanical communication pathway.Although MNs have several advantages,the practical application of MNs suffers from problems related to industrial manufacture and clinical evaluation,making it difficult for clinical translation.In this study,we summarized the various applications,emerging challenges,and developmental prospects of MNs in skin disorders to provide information on ways to advance clinical translation.

The Fusion Model of Catalytic Combustion and Thermal Conductivity

The further development of catalytic elements has been plagued by activation and binary problems.The automatic shift model that has emerged in recent years helps components achieve full range.However,the detection data still remains unstable in the shift area(7%∼13%).This paper proposes a Catalytic Combustion and Thermal Conductivity(CCTC)model for the specified range,which can be explained fromtwo aspects based on the existing methods.On the one hand,it uses iterative location search to process heterogeneous data,judges the prediction position of data points,and then givesweight evaluation.On the other hand,it corrects the abnormal points,determines the abnormal points in the horizontal direction,and gives the replacement value through the data of adjacent points.The experimental results show that the CCTC model reduces the sum of variance from 17 of the automatic shift model to 13,and the comparison of experimental variance is reduced by 23%.In the full-scale real-time data,the experimental variance of CCTC model and automatic shift model is reduced by 18%.In conclusion,CCTC is a cross section stability framework for full-scale methane measurement,in which the specified heterogeneous combination and anomaly point correction methods improve the stability.

Development and validation of a postoperative pulmonary infection prediction model for patients with primary hepatic carcinoma

BACKGROUND There are factors that significantly increase the risk of postoperative pulmonary infections in patients with primary hepatic carcinoma(PHC).Previous reports have shown that over 10%of patients with PHC experience postoperative pulmonary infections.Thus,it is crucial to prioritize the prevention and treatment of postoperative pulmonary infections in patients with PHC.AIM To identify the risk factors for postoperative pulmonary infection in patients with PHC and develop a prediction model to aid in postoperative management.METHODS We retrospectively collected data from 505 patients who underwent hepatobiliary surgery between January 2015 and February 2023 in the Department of Hepatobiliary and Pancreaticospleen Surgery.Radiomics data were selected for statistical analysis,and clinical pathological parameters and imaging data were included in the screening database as candidate predictive variables.We then developed a pulmonary infection prediction model using three different models:An artificial neural network model;a random forest model;and a generalized linear regression model.Finally,we evaluated the accuracy and robustness of the prediction model using the receiver operating characteristic curve and decision curve analyses.RESULTS Among the 505 patients,86 developed a postoperative pulmonary infection,resulting in an incidence rate of 17.03%.Based on the gray-level co-occurrence matrix,we identified 14 categories of radiomic data for variable screening of pulmonary infection prediction models.Among these,energy,contrast,the sum of squares(SOS),the inverse difference(IND),mean sum(MES),sum variance(SUV),sum entropy(SUE),and entropy were independent risk factors for pulmonary infection after hepatectomy and were listed as candidate variables of machine learning prediction models.The random forest model algorithm,in combination with IND,SOS,MES,SUE,SUV,and entropy,demonstrated the highest prediction efficiency in both the training and internal verification sets,with areas under the curve of 0.823 and 0.801 and a 95%confidence interval of 0.766-0.880 and 0.744-0.858,respectively.The other two types of prediction models had prediction efficiencies between areas under the curve of 0.734 and 0.815 and 95%confidence intervals of 0.677-0.791 and 0.766-0.864,respectively.CONCLUSION Postoperative pulmonary infection in patients undergoing hepatectomy may be related to risk factors such as IND,SOS,MES,SUE,SUV,energy,and entropy.The prediction model in this study based on diffusion-weighted images,especially the random forest model algorithm,can better predict and estimate the risk of pulmonary infection in patients undergoing hepatectomy,providing valuable guidance for postoperative management.

Efficacy and risk factors for anxiety and depression after miniincision hip arthroplasty for femoral head osteonecrosis

BACKGROUND Osteonecrosis of the femoral head(ONFH)is a prevalent orthopedic issue,leading to the collapse and fragmentation of the femoral head in its advanced stages,which can severely impair patients'quality of life.Total hip arthroplasty(THA)is a clinical intervention frequently used to alleviate ONFH symptoms and reinstate hip functionality.The conventional surgical technique is invasive and comes with an extended recuperation period,posing significant challenges for patients.With the progression of medical technology,the use of the mini-incision technique in minimally invasive THA(MITHA)has become more prevalent.However,comparative studies examining the effectiveness of these two surgical procedures in treating ONFH remain scarce.Furthermore,understanding patients'psychological well-being is crucial given its profound influence on postoperative recuperation.AIM To evaluate the impact of mini-incision MITHA on ONFH treatment and to identify the risk factors associated with postoperative anxiety and depression.METHODS A retrospective study was conducted on 125 patients treated for ONFH at Xi’an Hong Hui Hospital between February 2020 and January 2022,with the term"consecutive"indicating that these patients were treated in an unbroken sequence without any selection.Among these,60 patients(control group)underwent traditional THA,while 65 patients(observation group)were treated with miniincision MITHA.Variations in the visual analog scale(VAS)score and the Harris hip score were monitored.Additionally,shifts in pre-and posttreatment Hamilton anxiety(HAMA)and Hamilton depression(HAMD)scale scores were recorded.Patients with both postoperative HAMA and HAMD scores of≥8 were identified as those experiencing negative emotions.Logistic regression was utilized to analyze the determinants influencing these negative emotional outcomes.Comparative analyses of surgical and postoperative metrics between the two groups were also conducted.RESULTS Posttreatment results indicated a significantly higher VAS score in the control group than in the observation group,while the Harris score was considerably lower(P<0.0001).The observation group benefited from a notably shorter operation duration,reduced blood loss,diminished incision size,and a decreased postoperative drainage time(P<0.0001),accompanied by a reduced hospital stay and lower treatment costs(P<0.0001).The control group had elevated posttreatment HAMA and HAMD scores in comparison to the observation group(P<0.0001).Multivariate logistic regression revealed that being female[odds ratio(OR):4.394,95%CI:1.689-11.433,P=0.002],having a higher postoperative VAS score(OR:5.533,95%CI:2.210-13.848,P<0.0001),and having higher treatment costs(OR:7.306,95%CI:2.801-19.057,P<0.0001)were significant independent determinants influencing postoperative mood disturbances.CONCLUSION Compared to conventional THA,mini-incision MITHA offers advantages such as reduced operation time,minimal bleeding,and a shorter incision in ONFH patients.Moreover,factors such as sex,postoperative pain(reflected in the VAS score),and treatment costs significantly impact postoperative anxiety and depression.

等通道挤压及热处理制备细晶铀的显微组织及力学性能

采用等通道挤压及热处理相结合的技术制备细晶金属铀,采用激光共聚焦显微镜、电子背散射衍射、霍普金森压杆系统地研究细晶金属铀的显微组织及力学性能。结果表明,粗晶金属铀经3道次等通道挤压及后续热处理后晶粒尺寸由约1000μm细化为6.5μm,相应的动态屈服强度由135 MPa增加至390 MPa。对于等通道挤压铀样品,用经典Hall−Petch公式能描述晶粒尺寸与屈服强度之间的关系,同时获得等通道挤压技术制备细晶金属铀的Hall−Petch拟合关系。

我国氢燃料电池汽车财政补贴政策的系统动力学仿真研究

燃料电池汽车是我国新能源汽车重点发展的方向,借助长三角“氢走廊”有可能率先突破。结合制约氢燃料电池汽车产业发展的四大因素,本文首先构建了由中央政府、氢能源产业链、氢燃料电池汽车整车厂商、基础设施部门和消费者组成的政策研究理论模型,以提高产业政策效用、促进氢燃料电池汽车产业化为目的,运用系统动力学对氢燃料电池汽车的财政补贴政策优化问题进行仿真研究。研究发现:在现有政策补贴的情况下,不能实现2030年100万辆氢燃料电池汽车保有量的目标;在制约氢燃料电池汽车发展的四大瓶颈中,加大对氢能源产业链的财政补贴能够有效提升产业化进程;为实现2030年的目标,需要进一步加大财政补贴力度,并向氢能源产业链倾斜。

面向控域的体系结构:一种智能万物互联的体系结构风格

继PC互联网、移动互联网之后,世界正在进入智能万物互联网时代,也称为人机物三元计算时代.一个主要特征是,"计算机"不只是PC机、智能手机,也会具象成为物理世界中的各种智能物体设备(物端设备).未来的全球智能万物互联网将拥有万亿级物端设备,它们需要多种多样的控制策略,去满足各自的创新自由度、安全隐私保障、依法依规治理、良好用户体验等方面的需求.一套控制策略难以满足全球智能万物互联网的多样化需求,但可将全网划分成多个域(称为控域),每个有自己的控制范围和控制策略.借鉴面向服务的体系结构(service-oriented architecture,SOA)和REST体系结构风格的经验,提出一种面向控域的体系结构(zone-oriented architecture,ZOA)风格.它的基础技术包括:以控域为元素并含有4个算子的控域代数、3个范式和5个体系结构设计原则.最后讨论了面向控域的体系结构针对的5个问题,并通过一个车联网场景显示了该体系结构风格如何有助于现有研究,提出了开放研究问题.

变熵画像:一种数量级压缩物端数据的多粒度信息模型

近年来由物联网边缘和物端设备产生的数据呈现出爆发式的增长,催生了边缘计算、物端计算等新型物联网计算模式,利用"计算向数据源靠近"这一理念从架构上显著地改善了整体系统性能和能耗.然而,大量资源相对受限的物端设备暴露了现有计算模式的2个缺陷:1)由于不能存储海量数据导致部分计算无法下沉至末端;2)由于无法针对多样化的应用需求提供多粒度信息支持导致冗余计算和存储开销.围绕这2个问题,提出了一种数量级压缩物端数据的多粒度信息模型——变熵画像(variant entropy profile,VEP),及其TSR-VEP数据存储原型.基于真实的智能电表数据集和基准测试实验结果表明:VEP能在较低应用观测误差的前提下,实现物端数据的数量级压缩和多粒度信息存储查询.结合测试结果的讨论显示了VEP具备应用于物端设备的可行性与进一步优化边缘计算和物端计算的潜力.

Screening for pancreatic cancer in familial high-risk individuals: A systematic review

AIM:To analyze the benefits and harms of pancreatic cancer screening in familial high-risk individuals(HRIs).METHODS:Studies were identified by searching PubMed,EBSCO,ClinicalTrials.gov and the Cochrane database from database inception to June 2014.We also obtained papers from the reference lists of pertinent studies and systematic reviews.Englishlanguage trials and observational studies were searched.The key words used as search terms were "screening" and "surveillance".Cost-effectiveness,diagnostic rate,survival rate,mortality and adverse events were the outcomes of interest.Age,sex,lifestyle and other confounding factors were also considered.However,anticipating only a few of these studies,we also included observational studies with or without control groups.We also included studies concerning the anxiety associated with pancreatic cancer risk and other psychological changes in familial HRIs.We extracted details on study design,objectives,population characteristics,inclusion criteria,year of enrollment,method of screening,adjusted and unadjusted mortality,cost-effectiveness and adverse events from the included studies.Studies were assessed using the Reporting of Observational studies in Epidemiology(STROBE) checklist.RESULTS:Sixteen studies on pancreatic cancer screening were included.Five studies included control groups,nine were observational studies without control groups,and the other two studies investigated the worry associated with pancreatic cancer risk.We found that pancreatic cancer screening resulted in a high curative resection rate(60%vs 25%,P = 0.011),longer median survival time(14.5 mo vs 4 mo,P < 0.001),and higher 3-year survival rate(20%vs 15.0%,P =0.624).We also found that familial HRIs had a higher diagnostic rate of pancreatic tumors than controls(34%vs 7.2%,P< 0.001).In patients who underwent regular physical examinations,more stage I pancreatic cancers were observed(19%vs 2.6%,P= 0.001).In addition,endoscopic ultrasonography,which was the main means of detection,diagnosed 64.3%of pancreatic cancers.In comparison,endoscopic retrograde cannulation of the pancreas,magnetic resonance imaging,and computed tomography diagnosed 28.6%,42.9%,and21.4%,respectively.For mass lesions,instant surgery was recommended because of the beneficial effects of post-operative chemotherapy.However,in patients with intraductal papillary mucinous neoplasms,we did not find a significant difference in outcome between surgery and follow-up without treatment.Moreover,pancreatic cancer screening in familial HRIs had a greater perceived risk of pancreatic cancer(P< 0.0001),higher levels of anxiety regarding pancreatic cancer(P< 0.0001),and increased economic burden.CONCLUSION:Pancreatic cancer screening in familial HRIs is associated with a higher detection rate and longer survival,although screening may influence psychological function and increase the economic burden.

保滩护岸工程及生态措施应用

针对国内海岸侵蚀现状严峻的问题,对保滩护岸的主要内容及现有的保滩护岸方式进行研究,分析常用工程措施和生态措施的优缺点,并结合实际案例,对现有保滩护岸中的应用模式进行总结。通过多方面对比,发现生态措施能够弥补传统工程措施的不足,充分利用生态环境形成保滩护岸的柔性屏障,符合我国生态文明建设的需要,生态措施在保滩护岸工程中具有良好的应用前景。

长江口和杭州湾北岸生态保滩促淤护岸工程设计与应用研究

长江口和杭州湾北岸的岸线稳定是确保该地区人民生命、财产安全,维持航道与岸线完整的必要因素。本文在分析长江口和杭州湾北岸现有保滩护岸模式的基础上,探讨了丁坝、顺坝、护坎、促淤围垦、扩展滩面等工程措施在冲刷严重的岸段面临的问题。针对长江口和杭州湾北岸护岸遭受严重侵蚀的情况,对常用的保滩护岸工程措施和生态措施的应用研究情况进行了简要总结。从环境影响和可持续发展两个方面着眼,研究了生态材料和适宜植物共同构建生态体系,增强岸坡抗冲击和保护水土的能力。在此基础上,对长江口和杭州湾北岸提出了工程措施与生态类措施相结合的新型护岸模式。

Towards asynchronous federated learning for heterogeneous edge-powered internet of things

The advancement of the Internet of Things(IoT)brings new opportunities for collecting real-time data and deploying machine learning models.Nonetheless,an individual IoT device may not have adequate computing resources to train and deploy an entire learning model.At the same time,transmitting continuous real-time data to a central server with high computing resource incurs enormous communication costs and raises issues in data security and privacy.Federated learning,a distributed machine learning framework,is a promising solution to train machine learning models with resource-limited devices and edge servers.Yet,the majority of existing works assume an impractically synchronous parameter update manner with homogeneous IoT nodes under stable communication connections.In this paper,we develop an asynchronous federated learning scheme to improve training efficiency for heterogeneous IoT devices under unstable communication network.Particularly,we formulate an asynchronous federated learning model and develop a lightweight node selection algorithm to carry out learning tasks effectively.The proposed algorithm iteratively selects heterogeneous IoT nodes to participate in the global learning aggregation while considering their local computing resource and communication condition.Extensive experimental results demonstrate that our proposed asynchronous federated learning scheme outperforms the state-of-the-art schemes in various settings on independent and identically distributed(i.i.d.)and non-i.i.d.data distribution.

Developing a tool for nurses to assess risk of infection in pediatric oncology patients in China:a modified Delphi study

Infections are identified as the most common preventable cause of death in pediatric oncology patients. Assessing and stratifying risk of infections are essential to prevent infection in these patients. To date, no tool can fulfill this demand in China. This study aimed to develop a nursing work-based and Chinese-specific tool for pediatric nurses to assess risk of infection in oncology patients. This research was a modified Delphi study. Based on a literature review, a 37-item questionnaire rating on a 0-5 scale was developed. Twenty-four experts from 8 hospitals in 6 provinces of China were consulted for three rounds. Consensus for each item in the first round was defined as： the rating mean was 〉 3 and the coefficient of variation （CV） was 〈 0.5. Consensus for each item in the second round was defined as CV 〈 0.3. Consensus among experts was defined as： P value of Kendall＇s coefficient of concordance （W） 〈 0.05. After three rounds of consultation, a two-part tool was developed： the Immune Status Scale （ISS） and the Checklist of Risk Factors of Infection （CRFI）. There were 5 items in the ISS and 14 in the CRFI. Based on the ISS score, nurses could stratify children into the low-risk and high-risk groups. For high-risk children, nurses should screen risk factors of infection every day by the CRFI, and twice weekly for low-risk children. Further study is needed to verify this tool＇s efficacy.

Aero-Engine Surge Fault Diagnosis Using Deep Neural Network

Deep learning techniques have outstanding performance in feature extraction and modelfitting.In thefield of aero-engine fault diagnosis,the intro-duction of deep learning technology is of great significance.The aero-engine is the heart of the aircraft,and its stable operation is the primary guarantee of the aircraft.In order to ensure the normal operation of the aircraft,it is necessary to study and diagnose the faults of the aero-engine.Among the many engine fail-ures,the one that occurs more frequently and is more hazardous is the wheeze,which often poses a great threat toflight safety.On the basis of analyzing the mechanism of aero-engine surge,an aero-engine surge fault diagnosis method based on deep learning technology is proposed.In this paper,key sensor data are obtained by analyzing different engine sensor data.An aero-engine surge data-set acquisition algorithm(ASDA)is proposed to sample the fault and normal points to generate the training set,validation set and test set.Based on neural net-work models such as one-dimensional convolutional neural network(1D-CNN),convolutional neural network(RNN),and long-short memory neural network(LSTM),different neural network optimization algorithms are selected to achieve fault diagnosis and classification.The experimental results show that the deep learning technique has good effect in aero-engine surge fault diagnosis.The aero-engine surge fault diagnosis network(ASFDN)proposed in this paper achieves better results.Through training,the network achieves more than 99%classification accuracy for the test set.