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A One Health approach to fight antimicrobial resistance in Uganda: Implementation experience, results, and lessons learned

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Biosafety and Health 2024年第2期6卷 125-132页

作者： Reuben Kiggundu J.P.Waswa Niranjan Konduri Hassan Kasuja Marion Murungi Patrick Vudriko Harriet Akello Eric Lugada Cecilia Muiva Esther Were Dinah Tjipura Henry Kajumbula Kate Kikule Emmanuel Nfor mohan P.Joshi UsAID Medicines Technologiesand Pharmaceutical Services ProgramManagement Sciences for HealthKampala 256Uganda UsAID Medicines Technologiesand Pharmaceutical Services ProgramManagement Sciences for HealthArlingtonVA 22203USA College of Veterinary Medicine Animal Resources and BiosecurityMakerere UniversityKampala 256Uganda Ministry of Health Uganda Kampala 256Uganda UsAID strengthening supply Chain systems Activity Management Sciences for HealthKampala 256Uganda UsAID Medicines Technologiesand Pharmaceutical Services ProgramManagement Sciences for HealthNairobi 254Kenya Department of Microbiology College of Health SciencesMakerere UniversityKampala 256Uganda

Uganda has been implementing the Global Health security Agenda(GHsA)since 2015 to build its capacity according to World Health Organization(WHO)Benchmarks on International Health Regulations *** country remains prone to outbreaks,with more than 20 disease outbreaks reported in the past five years,including Ebola virus disease,Crimean-Congo haemorrhagic fever,Marburg haemorrhagic fever,measles,yellow fever,coronavirus disease 2019(COVID-19),and *** resistance(AMR)is an ongoing *** scored capacity level 3 on infection prevention and control(IPC)and antimicrobial stewardship(AMs)in the 2017 Joint External Evaluation(JEE)*** gaps were being addressed after a self-assessment in *** paper describes the technical assistance approaches provided to Uganda by the Medicines,Technologies,and Pharmaceutical services Program,funded by the United states(U.s.)Agency for International Development,and implemented by Management sciences for *** program,through a One Health approach,supported systematic capacity strengthening based on the JEE's capacity advancement framework for global health security,specifically relating to *** program's interventions impacted 32 WHO benchmark actions(7 for AMR multisectoral coordination,16 for IPC,and 9 for AMs),contributing to Uganda's strengthened GHsA *** success built on the AMR platform,the program trained 745 health workers in IPC for the Ebola virus and provided support for simulation exercises by eight district IPC *** program also worked with the Ministry of Health to coordinate IPC for the COVID-19 response in five health regions,covering 45 districts and reaching 5,452 health workers at 858 health facilities.

关键词： One health Antimicrobial resistance Antibiotic resistance Jointexternal evaluation Global health security Uganda Africa WHO Benchmarks for International Health Regulations Capacities

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Role of fecal microbiota transplant in management of hepatic encephalopathy: Current trends and future directions

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World Journal of Hepatology 2024年第1期16卷 17-32页

作者： Yash R shah Hassam Ali Angad Tiwari David Guevara-Lazo Natalia Nombera-Aznaran Bhanu siva mohan Pinnam Manesh Kumar Gangwani Harishankar Gopakumar Amir H sohail sriLakshmiDevi Kanumilli Ernesto Calderon-Martinez Geetha Krishnamoorthy Nimish Thakral Dushyant singh Dahiya Department of Internal Medicine Trinity Health Oakland/Wayne State UniversityPontiacMI 48341United States Division of Gastroenterology and Hepatology East Carolina University/Brody School of MedicineGreenvilleNC 27858United States Department of Internal Medicine Maharani Laxmi Bai Medical CollegeJhansi 284001India Faculty of Medicine Universidad Peruana Cayetano HerediaLima 15102Peru Department of Internal Medicine John H.Stroger Hospital of Cook CountyChicagoIL 60612United States Department of Internal Medicine The University of ToledoToledoOH 43606United States Department of Gastroenterology and Hepatology University of Illinois College of Medicine at PeoriaPeoriaIL 61605United States Department of surgery University of New MexicoAlbuquerqueNM 87106United States Department of Internal Medicine GSL Medical CollegeRajamahendravaram 533296India Department of Internal Medicine Universidad Nacional Autonoma de MexicoCiudad De Mexico 04510Mexico Department of Digestive Diseases and Nutrition University of KentuckyLexingtonKY 40536United States Division of Gastroenterology Hepatology&MotilityThe University of Kansas School of MedicineKansas CityKS 66160United States

Fecal microbiota transplantation(FMT)offers a potential treatment avenue for hepatic encephalopathy(HE)by leveraging beneficial bacterial displacement to restore a balanced gut *** prevalence of HE varies with liver disease severity and *** pathogenesis involves ammonia toxicity,gut-brain communication disruption,and *** aims to restore gut microbiota balance,addressing these ***'s efficacy has been explored in various conditions,including *** suggest that FMT can modulate gut microbiota,reduce ammonia levels,and alleviate *** has shown promise in alcohol-associated,hepatitis B and C-associated,and non-alcoholic fatty liver *** include improved liver function,cognitive function,and the slowing of disease ***,larger,controlled studies are needed to validate its effectiveness in these *** have shown cognitive improvements through FMT,with potential benefits in cirrhotic ***,trials have demonstrated reduced serious adverse events and cognitive enhancements in FMT arms compared to the standard of *** evidence is promising,challenges remain:Limited patient numbers,varied dosages,administration routes,and donor *** large-scale,controlled trials are essential to establish standardized guidelines and ensure FMT's clinical applications and *** FMT holds potential for HE management,ongoing research is needed to address these challenges,optimize protocols,and expand its availability as a therapeutic option for diverse hepatic conditions.

关键词： Hepatic encephalopathy Fecal microbiota transplant Cognitive impairment Liver cirrhosis Chronic liver disease

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深度神经网络后门防御综述

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信息安全学报 2024年第4期9卷 47-63页

作者：江钦辉李默涵孙彦斌广州大学网络空间安全学院/网络空间先进技术研究院广州510006

深度学习在各领域全面应用的同时,在其训练阶段和推理阶段也面临着诸多安全威胁。神经网络后门攻击是一类典型的面向深度学习的攻击方式,攻击者通过在训练阶段采用数据投毒、模型编辑或迁移学习等手段,向深度神经网络模型中植入非法后门... 详细信息

深度学习在各领域全面应用的同时,在其训练阶段和推理阶段也面临着诸多安全威胁。神经网络后门攻击是一类典型的面向深度学习的攻击方式,攻击者通过在训练阶段采用数据投毒、模型编辑或迁移学习等手段,向深度神经网络模型中植入非法后门,使得后门触发器在推理阶段出现时,模型输出会按照攻击者的意图偏斜。这类攻击赋予攻击者在一定条件下操控模型输出的能力,具有极强的隐蔽性和破坏性。因此,有效防御神经网络后门攻击是保证智能化服务安全的重要任务之一,也是智能化算法对抗研究的重要问题之一。本文从计算机视觉领域出发,综述了面向深度神经网络后门攻击的防御技术。首先,对神经网络后门攻击和防御的基础概念进行阐述,分析了神经网络后门攻击的三种策略以及建立后门防御机制的阶段和位置。然后,根据防御机制建立的不同阶段或位置,将目前典型的后门防御方法分为数据集级、模型级、输入级和可认证鲁棒性防御四类。每一类方法进行了详细的分析和总结,分析了各类方法的适用场景、建立阶段和研究现状。同时,从防御的原理、手段和场景等角度对每一类涉及到的具体防御方法进行了综合比较。最后,在上述分析的基础上,从针对新型后门攻击的防御方法、其他领域后门防御方法、更通用的后门防御方法、和防御评价基准等角度对后门防御的未来研究方向进行了展望。

关键词：后门防御后门攻击人工智能安全神经网络深度学习

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Quantifying Kinematic Tremor in an NGLY1-Deficient Individual: A Case study

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Case Reports in Clinical Medicine 2024年第1期13卷 25-36页

作者： Brock Futrell Christopher Alexander Malaya Dacia Martinez Diaz Christian Alfaro Hannah Elizabeth Gustafson subhalakshmi Chandrasekaran Rhea mohan Phatak Bernhard suter Charles shannon Layne Department of Health and Human Performance University of Houston Houston USA Center for Neuromotor and Biomechanics Research University of Houston Houston USA Department of Computer science and Engineering Texas A&M University College Station USA Blue Bird Circle Rett Center Texas Children’s Hospital Houston USA Baylor College of Medicine Houston USA Center for NeuroEngineering and Cognitive science University of Houston Houston USA

NGLY1 Deficiency is an autosomal recessive congenital disorder that has been identified in less than 100 individuals. Most individuals with NGLY1 Deficiency display hyperkinetic movement disorders, including choreiform, athetoid, dystonic myoclonic, dyskinetic, and dysmetric movements. Developing a consistent and concise consensus on the classification and evaluation of tremors is essential to forward the research and treatment of tremors. It has also been reported that some individuals with NGLY1 Deficiency demonstrate tremor, but such tremor has never been formally investigated. The primary objective of this study is to determine if an individual with NGLY1 Deficiency demonstrates an identifiable tremor during a series of arm movements and, if so, describe the frequency and power characteristics of that tremor. Arm movement kinematics were obtained using a 16-camera Vicon system, and time series trajectory waveforms for three planes of a marker placed on the hand were developed. Custom MATLAB scripts were utilized to compute Fast Fourier Transformations of the data within the identified waveform segments. A mean frequency of 2.30 Hz (sD = 1.05) with a mean power of 5.02 |P1(f)| (sD = 4.63) suggests that our participant’s kinematic data did display a persistent tremor in both hands across all tasks and movement planes. Analyses of the reaching hand and the non-reaching hand suggest the participant displayed an action tremor in both postural and intention (kinetic) tremors. Future directions should include assessing additional individuals with NGLY1 Deficiency to determine if the tremor is a distinguishable disorder behavior. Additionally, evaluating other anatomical sites, such as the elbow, head, and lower limbs, would provide further insights into the characteristics of this tremor.

关键词： Tremor NGLY Fast Fourier Transformation Reaching Hyperkinetic Movement

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Association between acute peripancreatic fluid collections and early readmission in acute pancreatitis:A propensity-matched analysis

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World Journal of Experimental Medicine 2024年第2期14卷 75-88页

作者： Hassam Ali Faisal Inayat Waqas Rasheed Arslan Afzal Ahtshamullah Chaudhry Pratik Patel Attiq Ur Rehman Muhammad sajeel Anwar Gul Nawaz Muhammad sohaib Afzal Amir H sohail subanandhini subramanium Dushyant singh Dahiya Deepa Budh Babu P mohan Douglas G Adler Department of Gastroenterology and Hepatology East Carolina University Brody School of MedicineGreenvilleNC 27834United States Department of Internal Medicine Allama Iqbal Medical CollegeLahorePunjab 54550Pakistan Department of Internal Medicine Texas Tech University Health Sciences CenterLubbockTX 79430United States Department of Internal Medicine St.Dominic’s HospitalJacksonMS 39216United States Department of Gastroenterology Mather Hospital and Hofstra University Zucker School of MedicinePort JeffersonNY 11777United States Department of Hepatology Geisinger Wyoming Valley Medical CenterWilkes-BarrePA 18711United States Department of Internal Medicine UHS Wilson Medical CenterJohnson CityNY 13790United States Department of Internal Medicine Louisiana State University HealthShreveportLA 71103United States Department of surgery University of New Mexico School of MedicineAlbuquerqueNM 87106United States Division of Gastroenterology Hepatologyand MotilityThe University of Kansas School of MedicineKansas CityKS 64108United States Department of Internal Medicine St.Barnabas Hospital and Albert Einstein College of MedicineBronxNY 10457United States Department of Gastroenterology and Hepatology University of Utah School of MedicineSalt Lake CityUT 84132United States Center for Advanced Therapeutic Endoscopy Porter Adventist HospitalCentura HealthDenverCO 80210United States

BACKGROUND Patients with acute pancreatitis(AP)frequently experience hospital readmissions,posing a significant burden to healthcare *** peripancreatic fluid collection(APFC)may negatively impact the clinical course of *** could worsen symptoms and potentially lead to additional ***,clinical evidence regarding the specific association between APFC and early readmission in AP remains *** the link between APFC and readmission may help improve clinical care for AP patients and reduce healthcare *** To evaluate the association between APFC and 30-day readmission in patients with *** This retrospective cohort study is based on the Nationwide Readmission Database for *** with a primary diagnosis of AP were *** were categorized into those with and without APFC.A 1:1 propensity score matching for age,gender,and Elixhauser comorbidities was *** primary outcome was early readmission *** outcomes included the incidence of inpatient complications and healthcare *** analyses used Mann-Whitney U andχ2 tests,while Cox regression models assessed 30-day readmission risks and reported them as adjusted hazard ratios(aHR).Kaplan-Meier curves and log-rank tests verified readmission *** A total of 673059 patients with the principal diagnosis of AP were *** these,5.1%had APFC on initial *** propensity score matching,each cohort consisted of 33914 *** with APFC showed a higher incidence of inpatient complications,including septic shock(3.1%vs 1.3%,Ps thrombosis(4.4%vs 0.8%,Ps 0.9%,Pstay(LOs)was longer for APFC patients[4(3-7)vs 3(2-5)days,Ps were hospital charges($29451 vs$24418,Pssions,APFC patients had a higher rate(15.7%vs 6.5%,Pssion LOs(4 vs 3 days,P<0.001).The APF

关键词： Acute pancreatitis Acute peripancreatic fluid collections Readmission predictors Inpatient complications Healthcare utilization and costs

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soft Computing Based Discriminator Model for Glaucoma Diagnosis

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Computer systems science & Engineering 2022年第9期42卷 867-880页

作者： Anisha Rebinth s.mohan Kumar Department of Information science and Engineering NHCEVisvesvaraya Technological UniversityBangaloreIndia Department of Computer science and Engineering Nagarjuna College of Engineering and TechnologyBangaloreIndia

In this study, a Discriminator Model for Glaucoma Diagnosis (DMGD)using soft computing techniques is presented. As the biomedical images such asfundus images are often acquired in high resolution, the Region of Interest (ROI)for glaucoma diagnosis must be selected at first to reduce the complexity of anysystem. The DMGD system uses a series of pre-processing;initial cropping by thegreen channel’s intensity, spatially Weighted Fuzzy C Means (sWFCM), bloodvessel detection and removal by Gaussian Derivative Filters (GDF) and inpaintingalgorithms. Once the ROI has been selected, the numerical features such as colour, spatial domain features from Local Binary Pattern (LBP) and frequencydomain features from LAWs are generated from the corresponding ROI forfurther classification using kernel based support Vector Machine (sVM). TheDMGD system performances are validated using four fundus image databases;ORIGA, RIM-ONE, DRIsHTI-Gs1, and HRF with four different kernels;LinearKernel (LK), Polynomial Kernel (PK), Radial Basis Function (RBFK) kernel,Quadratic Kernel (QK) based sVM classifiers. Results show that the DMGD system classifies the fundus images accurately using the multiple features and kernelbased classifies from the properly segmented ROI.

关键词： Glaucoma support vector classification clustering technique spatial domain and frequency domain features

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Optimal and Effective Resource Management in Edge Computing

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Computer systems science & Engineering 2023年第2期44卷 1201-1217页

作者： Darpan Majumder s.mohan Kumar Department of Information science and Engineering New Horizon College of Engineering Research CentreVisvesvaraya Technological University(VTU)BangaloreIndia Department of CsE Nagarjuna College of Engineering and TechnologyBangaloreIndia

Edge computing is a cloud computing extension where physical compu-ters are installed closer to the device to minimize *** task of edge data cen-ters is to include a growing abundance of applications with a small capability in comparison to conventional data *** this framework,Federated Learning was suggested to offer distributed data training strategies by the coordination of many mobile devices for the training of a popular Artiﬁcial Intelligence(AI)model without actually revealing the underlying data,which is signiﬁcantly enhanced in terms of *** learning(FL)is a recently developed decentralized profound learning methodology,where customers train their localized neural network models independently using private data,and then combine a global model on the core server *** models on the edge server use very little time since the edge server is highly *** the amount of time it takes to download data from smartphone users on the edge server has a signiﬁcant impact on the time it takes to complete a single cycle of FL operations.A machine learning strategic planning system that uses FL in conjunction to minimise model training time and total time utilisation,while recognising mobile appliance energy restrictions,is the focus of this *** further speed up integration and reduce the amount of data,it implements an optimization agent for the establishment of optimal aggregation policy and asylum architecture with several employees’shared *** main solutions and lessons learnt along with the prospects are *** show that our method is superior in terms of the effective and elastic use of resources.

关键词： Federated learning machine learning edge computing resource management

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skin Lesion Classification system Using shearlets

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Computer systems science & Engineering 2023年第1期44卷 833-844页

作者： s.mohan Kumar T.Kumanan Department of Computer science and Engineering Meenakshi Academy of Higher Education and ResearchChennai600078Tamil NaduIndia

The main cause of skin cancer is the ultraviolet radiation of the *** spreads quickly to other body ***,early diagnosis is required to decrease the mortality rate due to skin *** this study,an automatic system for skin Lesion Classification(sLC)using Non-subsampled shearlet Transform(NssT)based energy features and support Vector Machine(sVM)classifier is ***,the NssT is used for the decomposition of input skin lesion images with different directions like 2,4,8 and *** the NssT’s sub-bands,energy fea-tures are extracted and stored in the feature database for *** classifier is used for the classification of skin lesion *** dermoscopic skin images are obtained from PH^(2) database which comprises of 200 dermoscopic color images with melanocytic *** performances of the sLC system are evaluated using the confusion matrix and Receiver Operating Characteristic(ROC)*** sLC system achieves 96%classification accuracy using NssT’s energy fea-tures obtained from 3^(rd) level with 8-directions.

关键词： skin lesion classification non-subsampled shearlet transform sub-band coefficients energy feature support vector machine

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新时代教育家精神融入师范生培养:价值意蕴、现实挑战与实施路径

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信阳师范学院学报（哲学社会科学版） 2024年第5期44卷 75-82页

作者：赵婧杨默晗信阳师范大学文学院河南信阳464000

新时代教育家精神是对教育家教育品质与能力的高度凝练与升华,是教师队伍建设的理论向导与精神支撑。新时代教育家精神既是对中华优秀传统文化和习近平总书记关于教育重要论述的继承,又体现着新时代对教育的现实诉求,其产生有着文化依... 详细信息

新时代教育家精神是对教育家教育品质与能力的高度凝练与升华,是教师队伍建设的理论向导与精神支撑。新时代教育家精神既是对中华优秀传统文化和习近平总书记关于教育重要论述的继承,又体现着新时代对教育的现实诉求,其产生有着文化依据、理论依据和现实依据。其蕴含的六个方面对于师范生的培养具有重要的价值意蕴。然而,师范生在认知、情感、实践等方面存在的问题给新时代教育家精神融入师范生培养带来了现实挑战,要将教育家精神真正融入师范生的培养,需要从问题入手,强化认同接纳,提升师范生主体自觉;加强情感联结,激活师范生内在动力;完善培养机制,保障师范生专业成长。

关键词：新时代教育家精神师范生现实挑战实施路径

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Feature selection with Deep Reinforcement Learning for Intrusion Detection system

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Computer systems science & Engineering 2023年第9期46卷 3339-3353页

作者： s.Priya K.Pradeep mohan Kumar Department of Computer science and Engineering SRM Institute of Science and TechnologyRamapuramChennai600089India Department of Computing Technologies SRM Institute of Science and TechnologyKattankulathurChennai603203India

An intrusion detection system(IDs)becomes an important tool for ensuring security in the *** recent times,machine learning(ML)and deep learning(DL)models can be applied for the identification of intrusions over the network *** resolve the security issues,this paper presents a new Binary Butterfly Optimization algorithm based on Feature selection with DRL technique,called BBOFs-DRL for intrusion *** proposed BBOFsDRL model mainly accomplishes the recognition of intrusions in the *** attain this,the BBOFs-DRL model initially designs the BBOFs algorithm based on the traditional butterfly optimization algorithm(BOA)to elect feature ***,DRL model is employed for the proper identification and classification of intrusions that exist in the ***,beetle antenna search(BAs)technique is applied to tune the DRL parameters for enhanced intrusion detection *** ensuring the superior intrusion detection outcomes of the BBOFs-DRL model,a wide-ranging experimental analysis is performed against benchmark *** simulation results reported the supremacy of the BBOFs-DRL model over its recent state of art approaches.

关键词： Intrusion detection security reinforcement learning machine learning feature selection beetle antenna search

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