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Delayed atomoxetine or fluoxetine treatment coupled with limited voluntary running promotes motor recovery in mice after ischemic stroke

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Neural Regeneration Research 2021年第7期16卷 1244-1251页

作者： faisal f.alamri Abdullah Al Shoyaib Nausheen Syeara Anisha Paul Srinidhi Jayaraman Serob T.Karamyan Thiruma V.Arumugam Vardan T.Karamyan Department of Pharmaceutical Sciences School of PharmacyTexas Tech University Health Sciences CenterAmarilloTXUSA Department of Pharmacology Faculty of PharmacyYerevan State Medical UniversityYerevanArmenia Department of Physiology Anatomy and MicrobiologySchool of Life SciencesLa Trobe UniversityMelbourneAustralia Center for Blood Brain Barrier Research School of PharmacyTexas Tech University Health Sciences CenterAmarilloTXUSA College of Sciences and Health Profession King Saud bin Abdulaziz University for Health Sciences and King Abdullah International Medical Research CenterJeddahSaudi Arabia

Currently, there is an unmet need for treatments promoting post-stroke functional *** aim of this study was to evaluate and compare the dose-dependent effect of delayed atomoxetine or fluoxetine therapy(starting on post-stroke day 5), coupled with limited physical exercise(2 hours daily voluntary wheel running;post-stroke days 9 to 42), on motor recovery of adult male mice after photothrombotic *** drugs are selective norepinephrine or serotonin reuptake inhibitors indicated for disorders unrelated to *** predetermined primary end-point for this study was motor function measured in two tasks of spontaneous motor behaviors in grid-walking and cylinder ***, we quantified the running distance and speed throughout the study, the number of parvalbumin-positive neurons in the medial agranular cortex and infarct *** sensorimotor tests revealed that neither limited physical exercise nor a drug treatment alone significantly facilitated motor recovery in mice after ***, combination of physical exercise with either of the drugs promoted restoration of motor function by day 42 post-stroke, with atomoxetine being a more potent *** was accompanied by a significant decrease in parvalbumin-positive inhibitory interneurons in the ipsilateral medial agranular cortex of mice with recovering motor function, while infarct volumes were comparable among experimental *** further validated in larger studies, our observations suggest that add-on atomoxetine or fluoxetine therapy coupled with limited, structured physical rehabilitation could offer therapeutic modality for stroke survivors who have difficulty to engage in early, high-intensity ***, in light of the recently completed Assessment o f fluoxet INe In s Troke recover Y(AffINITY) and Efficacy o f fluoxetine-a randomis Ed Controlled Trial in Stroke(EffECTS) trials, our observations call for newly designed studies where fluoxetine or atomoxeti

关键词： drug repurposing neural repair physical exercise physiotherapy post-stroke recovery pre-clinical trial fLAME trial selective norepinephrine reuptake inhibitor selective serotonin reuptake inhibitor stroke pharmacotherapy

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DeBERTa-GRU: Sentiment Analysis for Large Language Model

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Computers, Materials & Continua 2024年第6期79卷 4219-4236页

作者： Adel Assiri Abdu Gumaei faisal Mehmood Touqeer Abbas Sami Ullah Department of Informatics for Business College of BusinessKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou450001China Department of Computer Science and Technology Beijing University of Chemical TechnologyBeijing100029China Department of Computer Science Government College University FaisalabadFaisalabadPunjab38000Pakistan

Modern technological advancements have made social media an essential component of daily *** media allow individuals to share thoughts,emotions,and *** analysis plays the function of evaluating whether the sentiment of the text is positive,negative,neutral,or any other personal emotion to understand the sentiment context of the *** analysis is essential in business and society because it impacts strategic *** analysis involves challenges due to lexical variation,an unlabeled dataset,and text distance *** execution time increases due to the sequential processing of the sequence ***,the calculation times for the Transformer models are reduced because of the parallel *** study uses a hybrid deep learning strategy to combine the strengths of the Transformer and Sequence models while ignoring their *** particular,the proposed model integrates the Decoding-enhanced with Bidirectional Encoder Representations from Transformers(BERT)attention(DeBERTa)and the Gated Recurrent Unit(GRU)for sentiment *** the Decoding-enhanced BERT technique,the words are mapped into a compact,semantic word embedding space,and the Gated Recurrent Unit model can capture the distance contextual semantics *** proposed hybrid model achieves f1-scores of 97%on the Twitter Large Language Model(LLM)dataset,which is much higher than the performance of new techniques.

关键词： DeBERTa GRU Naive Bayes LSTM sentiment analysis large language model

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Anomaly-Based Intrusion DetectionModel Using Deep Learning for IoT Networks

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 823-845页

作者： Muaadh A.Alsoufi Maheyzah Md Siraj fuad A.Ghaleb Muna Al-Razgan Mahfoudh Saeed Al-Asaly Taha Alfakih faisal Saeed faculty of Computing Universiti Teknologi Malaysia(UTM)Johor Bahru81310Malaysia DAAI Research Group College of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11345Saudi Arabia

The rapid growth of Internet of Things(IoT)devices has brought numerous benefits to the interconnected ***,the ubiquitous nature of IoT networks exposes them to various security threats,including anomaly intrusion *** addition,IoT devices generate a high volume of unstructured *** intrusion detection systems often struggle to cope with the unique characteristics of IoT networks,such as resource constraints and heterogeneous data *** the unpredictable nature of network technologies and diverse intrusion methods,conventional machine-learning approaches seem to lack *** numerous research domains,deep learning techniques have demonstrated their capability to precisely detect *** study designs and enhances a novel anomaly-based intrusion detection system(AIDS)for IoT ***,a Sparse Autoencoder(SAE)is applied to reduce the high dimension and get a significant data representation by calculating the reconstructed ***,the Convolutional Neural Network(CNN)technique is employed to create a binary classification *** proposed SAE-CNN approach is validated using the Bot-IoT *** proposed models exceed the performance of the existing deep learning approach in the literature with an accuracy of 99.9%,precision of 99.9%,recall of 100%,f1 of 99.9%,false Positive Rate(fPR)of 0.0003,and True Positive Rate(TPR)of *** addition,alternative metrics,such as training and testing durations,indicated that SAE-CNN performs better.

关键词： IoT anomaly intrusion detection deep learning sparse autoencoder convolutional neural network

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Heat and mass transfer of a circular porous moist object located in a triangular shaped vented cavity

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Journal of Central South University 2024年第6期31卷 1956-1972页

作者： SELIMEfENDIGIL fatih OZCAN COBAN Seda OZTOP Hakan f Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl Ahsa 31982Saudi Arabia Department of Mechanical Engineering Manisa Celal Bayar UniversityManisa 45140Turkey Department of Mechanical Engineering Technology FacultyFırat UniversityElazığTurkey

Heat and mass transfer of a circular-shaped porous moist object inside a two-dimensional triangle cavity is investigated by using finite element *** porous object is considered to be a moist food sample,located in the middle of the cavity with inlet and outlet ports with different configurations of inlet/outlet *** drying performance is numerically assessed for different values of Reynolds numbers(between 50 and 250),dry air inlet temperature(between 40 and 80℃)and different locations of the *** is observed that changing the port locations has significant impacts on the flow recirculaitons inside the triangular chamber while convective drying performance is highly *** moisture content reduces with longer time and for higher Reynolds number(Re)*** P4 where inlet and outlet ports are in the middle of the walls provides the most effective configuration in terms of convective drying performance while the worst case is seen for P1 case where inlet and outlet are closer to the corners of the *** is a 192% difference between the moisture reduction of these two cases at Re=250,T=80℃ and t=120 min.

关键词： convective drying porous domain cavity flow inlet/exit port finite element method

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Assessment of Breast Cancer Prevention Practices among Women Attending Primary Health Care in Abha City, Aseer Region, Saudi Arabia

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International Journal of Clinical Medicine 2024年第2期15卷 31-54页

作者： Sabah Mohammed Asiri Sultan Yahia Alfifii Tagreed Khairan Al-Rashidi Sager Misfer Alqahtani faiz Abdulrahman Alshafa fayez Mari alamri Amal Mohammed Asiri fatima Mohammed Ali Almagadi Thuraya Mohammed Asiri Department of Therapeutic Assistance Management General Directorate of Health Affairs Asser Region Abha Saudi Arabia Department of Health Affairs General Directorate of Health Affairs Asser Region Abha Saudi Arabia Department of Kidney King Khaled Hospital Hail Saudi Arabia Department of Nursing Sarat Abida Hospital Aseer Saudi Arabia Department of Radiation Oncology King Faisal Medical City Abha Saudi Arabia Department of Health Affairs KSA MOH Department of Kidney Dialysis Centers General Directorate of Health Affairs Aseer Region Abha Saudi Arabia Department of Operation Ahad Rafidah Hospital General Directorate of Health Affairs in Asseer Region Abha Saudi Arabia South Qunfudah General Hospital Jizan Saudi Arabia Armed forces Southern Region Hospital Aseer Saudi Arabia

Cancer is a leading cause of death worldwide, with breast cancer being the most common (2.26 million new cases and 685,000 deaths). In Saudi Arabia, breast cancer ranked the first among females in 2014, accounting for 15.9% of all cancers reported among Saudi nationals and 28.7% of all cancers reported among females of all ages. Early detection of breast cancer could decrease the risks, have a better prognosis, and have better outcomes/more successful treatments. Prevalence of breast cancer reached more than 25% of all diagnosed cancer in the kingdom among women. Aim: This study aims to assess the knowledge and performance of women attending primary care centers about breast self-examination and mammogram screening for prevention and early detection of breast cancer in Abha city primary healthcare centers, Kingdom of Saudi Arabia. Research Method: cross sectional design was conducted by using questionnaire, which was distributed to primary care center nurses. The collected data was statistically analyzed using the Statistical Package for Social Sciences, version 25. Results: The study found that participants had poor awareness and knowledge about breast self-examination, risk factors for breast cancer, and trends and practices in early diagnosis of breast cancer. Conclusion and Recommendations: It recommends increasing awareness campaigns and providing educational programs to improve knowledge and practices.

关键词： Assessment Breast Cancer Prevention Practices Women Attending Health Care Centers Abha City

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Highly sensitive,scalable,and rapid SARS-CoV-2 biosensor based on In_(2)O_(3)nanoribbon transistors and phosphatase

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Nano Research 2022年第6期15卷 5510-5516页

作者： Mingrui Chen Dingzhou Cui Zhiyuan Zhao Di Kang Zhen Li Shahad Albawardi Shahla Alsageer faisal alamri Abrar Alhazmi Moh.R.Amer Chongwu Zhou Mork family Department of Chemical Engineering and Materials Science University of Southern CaliforniaLos AngelesCalifornia 90089USA Ming Hsieh Department of Electrical Engineering University of Southern CaliforniaLos AngelesCalifornia 90089USA Department of Physics and Astronomy University of Southern CaliforniaLos AngelesCalifornia 90089USA Center of Excellence for Green Nanotechnologies King Abdulaziz City for Science and TechnologyRiyadhSaudi Arabia Department of Electrical Engineering 420 Westwood Plaza5412 Boelter HallUniversity of CaliforniaLos AngelesLos AngelesCalifornia 90095USA eDNA Biotech PasadenaCalifornia 91107USA

Developing convenient and accurate SARS-CoV-2 antigen test and serology test is crucial in curbing the global COVID-19 *** this work,we report an improved indium oxide(In2O3)nanoribbon field-effect transistor(fET)biosensor platform detecting both SARS-CoV-2 antigen and *** fET biosensors,which were fabricated using a scalable and cost-efficient lithography-free process utilizing shadow masks,consist of an In_(2)O_(3)channel and a newly developed stable enzyme *** the biosensing process,the phosphatase enzymatic reaction generated pH change of the solution,which was then detected and converted to electrical signal by our In_(2)O_(3)*** biosensors applied phosphatase as enzyme reporter,which has a much better stability than the widely used urease in fET based *** proof-of-principle studies,we demonstrate the detection of SARS-CoV-2 spike protein in both phosphate-buffered saline(PBS)buffer and universal transport medium(UTM)(limit of detection[LoD]:100 fg/mL).following the SARS-CoV-2 antigen tests,we developed and characterized additional sensors aimed at SARS-CoV-2 IgG antibodies,which is important to trace past infection and *** spike protein IgG antibody tests exhibit excellent detection limits in both PBS and human whole blood((LoD):1 pg/mL).Our biosensors display similar detection performance in different mediums,demonstrating that our biosensor approach is not limited by Debye screening from salts and can selectively detect biomarkers in physiological *** newly selected enzyme for our platform performs much better performance and longer shelf life which will lead our biosensor platform to be capable for real clinical diagnosis usage.

关键词： biosensor indium oxide transistor phosphatase SARS-CoV-2 spike protein SARS-CoV-2 spike IgG antibody

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Blockchain Based Secured Load Balanced Task Scheduling Approach for fitness Service

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Computers, Materials & Continua 2022年第5期71卷 2599-2616页

作者： Muhammad Ibrahim faisal Jamil YunJung Lee DoHyeun Kim Big Data Research Center Department of Computer Science and StatisticsJeju National UniversityKoreaJeju-si63243Korea Department of Computer Engineering(and Advanced Technology Research Institute) Jeju National UniversityJeju 63243Korea

In recent times,the evolution of blockchain technology has got huge attention from the research community due to its versatile applications and unique security *** IoT has shown wide adoption in various applications including smart cities,healthcare,trade,business,*** these applications,fitness applications have been widely considered for smart fitness *** users of the fitness system are increasing at a high rate thus the gym providers are constantly extending the fitness ***,scheduling such a huge number of requests for fitness exercise is a big ***,the user fitness data is critical thus securing the user fitness data from unauthorized access is also *** overcome these issues,this work proposed a blockchain-based load-balanced task scheduling approach.A thorough analysis has been performed to investigate the applications of IoT in the fitness industry and various scheduling *** proposed scheduling approach aims to schedule the requests of the fitness users in a load-balanced way that maximize the acceptance rate of the users’requests and improve resource *** performance of the proposed task scheduling approach is compared with the state-of-the-art approaches concerning the average resource utilization and task rejection *** obtained results confirm the efficiency of the proposed scheduling *** investigating the performance of the blockchain,various experiments are performed using the Hyperledger Caliper concerning latency,throughput,resource *** Solo approach has shown an improvement of 32%and 26%in throughput as compared to Raft and Solo-Raft approaches *** obtained results assert that the proposed architecture is applicable for resource-constrained IoT applications and is extensible for different IoT applications.

关键词： Load balancing resource scheduling task scheduling Internet of things blockchain fitness applications

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An Ensemble Learning Based Approach for Detecting and Tracking COVID19 Rumors

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Computers, Materials & Continua 2022年第1期70卷 1721-1747页

作者： Sultan Noman Qasem Mohammed Al-Sarem faisal Saeed Computer Science Department College of Computer and Information SciencesAl Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Computer Science Department Faculty of Applied ScienceTaiz UniversityTaiz6803Yemen College of Computer Science and Engineering Taibah UniversityMedinaSaudi Arabia Information System Department Saba’a Region UniversityMareebYemen

Rumors regarding epidemic diseases such as COVID 19,medicines and treatments,diagnostic methods and public emergencies can have harmful impacts on health and political,social and other aspects of people’s lives,especially during emergency situations and health *** huge amounts of content being posted to social media every second during these situations,it becomes very difficult to detect fake news(rumors)that poses threats to the stability and sustainability of the healthcare sector.A rumor is defined as a statement for which truthfulness has not been *** COVID 19,people found difficulty in obtaining the most truthful news easily because of the huge amount of unverified information on social *** methods have been applied for detecting rumors and tracking their sources for COVID 19-related ***,very few studies have been conducted for this purpose for the Arabic language,which has unique ***,this paper proposes a comprehensive approach which includes two phases:detection and *** the detection phase of the study carried out,several standalone and ensemble machine learning methods were applied on the Arcov-19 dataset.A new detection model was used which combined two models:The Genetic Algorithm Based Support Vector Machine(that works on users’and tweets’features)and the stacking ensemble method(that works on tweets’texts).In the tracking phase,several similarity-based techniques were used to obtain the top 1%of similar tweets to a target tweet/post,which helped to find the source of the *** experiments showed interesting results in terms of accuracy,precision,recall and f1-Score for rumor detection(the accuracy reached 92.63%),and showed interesting findings in the tracking phase,in terms of ROUGE L precision,recall and f1-Score for similarity techniques.

关键词： Rumor detection rumor tracking similarity techniques COVID-19 social media analytics

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Blockchain-Based Decentralized Authentication Model for IoT-Based E-Learning and Educational Environments

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Computers, Materials & Continua 2023年第5期75卷 3133-3158页

作者： Osama A.Khashan Sultan alamri Waleed Alomoush Mutasem K.Alsmadi Samer Atawneh Usama Mir Research and Innovation Centers Rabdan AcademyP.O.Box 114646Abu DhabiUnited Arab Emirates College of Computing and Informatics Saudi Electronic UniversityRiyadh13316Saudi Arabia School of Information Technology Skyline University CollegeP.O.Box 1797SharjahUnited Arab Emirates Department of MIS College of Applied Studies and Community ServicesImam Abdulrahman Bin Faisal UniversityP.O.Box 1982DammamSaudi Arabia Department of Computer Science University of WindsorWindsorN9J3Y1Canada

In recent times,technology has advanced significantly and is currently being integrated into educational environments to facilitate distance learning and interaction between *** the Internet of Things(IoT)into education can facilitate the teaching and learning process and expand the context in which students ***,learning data is very sensitive and must be protected when transmitted over the network or stored in data ***,the identity and the authenticity of interacting students,instructors,and staff need to be verified to mitigate the impact of ***,most of the current security and authentication schemes are centralized,relying on trusted third-party cloud servers,to facilitate continuous secure *** addition,most of these schemes are resourceintensive;thus,security and efficiency issues arise when heterogeneous and resource-limited IoT devices are being *** this paper,we propose a blockchain-based architecture that accurately identifies and authenticates learners and their IoT devices in a decentralized manner and prevents the unauthorized modification of stored learning records in a distributed university *** allows students and instructors to easily migrate to and join multiple universities within the network using their identity without the need for user *** proposed architecture was tested using a simulation tool,and measured to evaluate its *** simulation results demonstrate the ability of the proposed architecture to significantly increase the throughput of learning transactions(40%),reduce the communication overhead and response time(26%),improve authentication efficiency(27%),and reduce the IoT power consumption(35%)compared to the centralized authentication *** addition,the security analysis proves the effectiveness of the proposed architecture in resisting various attacks and ensuring the security requirements of learning data in the unive

关键词： Blockchain decentralized authentication Internet of Things(IoT) E-learning IoT security

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Hybrid Renewable Energy Resources Management for Optimal Energy Operation in Nano-Grid

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Computers, Materials & Continua 2022年第5期71卷 2091-2105页

作者： faiza Qayyum faisal Jamil Shabir Ahmad Do-Hyeun Kim Department of Computer Engineering Jeju National UniversityJeju-siJeju Special Self-Governing Province63243Korea Department of IT Convergence Engineering Gachon UniversitySujeong-GuSeongnam-SiGyeonggi-Do461-701Korea

Renewable energy resources are deemed a potential energy production source due to their cost efficiency and harmless reaction to the environment,unlike non-renewable energy ***,they often fail to meet energy requirements in unfavorable weather *** concept of Hybrid renewable energy resources addresses this issue by integrating both renewable and non-renewable energy resources to meet the required energy *** this paper,an intelligent cost optimization algorithm is proposed to maximize the use of renewable energy resources and minimum utilization of non-renewable energy resources to meet the energy requirement for a nanogrid *** actual data set comprising information about the load and demand of utility grids is used to evaluate the performance of the proposed nanogrid energy management *** objective function is formulated to manage the nanogrid operation and implemented using a variant of Particle Swarm Optimization(PSO)named recurrent PSO(rPSO).firstly,rPSO algorithm minimizes the installation cost for ***,the proposed NEMS ensures cost efficiency for the post-installation period by providing a daily operational plan and optimizing renewable ***-of-the-art optimization models,including Genetic Algorithm(GA),bat and different Mathematical Programming Language(AMPL)solvers,are used to evaluate the *** study’s outcomes suggest that the proposed work significantly reduces the use of diesel generators and fosters the use of renewable energy resources and beneficiates the eco-friendly environment.

关键词： Smart grid nanogrid distributed generation(DG) renewable energy optimization machine learning

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