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Distinctive clinical and laboratory features of COVID-19 and H1N1 influenza infections among hospitalized pediatric patients

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World Journal of Pediatrics 2021年第3期17卷 272-279页

作者： Ali Alsuheel Asseri Ayed A.Shati Saleh M.Al-Qahtani ibrahim A.Alzaydani Ahmed A.Al-Jarie mohammed J.Alaliani Abdelwahid Saeed Ali Department of Child Health College of MedicineKing Khalid UniversityAbhaSaudi Arabia Department of Pediatrics Abha Maternity and Children HospitalAbhaSaudi Arabia General Directorate of Health Affairs Infection Prevention and Control AdministrationAseer RegionMinistry of HealthAbhaSaudi Arabia Department of Microbiology and Clinical Parasitology College of MedicineKing Khalid UniversityAbhaSaudi Arabia

Background It had been documented in many studies that pediatric coronavirus disease 2019(COVID-19)is characterized by low infectivity rates,low mortalities,and benign disease *** the other hand,influenza type A viruses are recognized to cause severe and fatal infections in children populations *** study is aimed to compare the clinical and laboratory characteristics of COVID-19 and H1N1 influenza *** A retrospective study comprising 107 children hospitalized at Abha Maternity and Children Hospital,Southern region of Saudi Arabia,with laboratory-confirmed COVID-19 and H1N1 influenza infections was carried out.A complete follow-up for all patients from the hospital admission until discharge or death was *** clinical data and laboratory parameters for these patients were collected from the medical records of the *** Out of the total enrolled patients,73(68.2%)were diagnosed with COVID-19,and 34(31.8%)were diagnosed with H1N1 *** median age is 12 months for COVID-19 patients and 36 months for influenza patients.A relatively higher number of patients with influenza had a fever and respiratory symptoms than COVID-19 *** contrast,gastrointestinal symptoms were observed in a higher number of COVID-19 patients than in influenza patients.A statistically significant increase in white cell counts is noted in COVID-19 but not in influenza patients(P<0.05).There are no obvious variations in the mean period of duration of hospitalization between COVID-19 and influenza ***,the total intensive care unit length of stay was longer for influenza compared to COVID-19 *** A considerable number of children infected with COVID-19 and H1N1 influenza were noted and reported in this *** were no significant variations in the severity of the symptomatology and laboratory findings between the two groups of *** differences between these patients in some hospitalization facto

关键词： Children Coronavirus disease 2019 H1N1 influenza.Laboratory indices Symptoms

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Genetic Diversity Analysis of Forty Pearl Millet (<i>Pennisetum glaucum</i>(L.) R. Br) Accessions from Sudan Using Agronomical Descriptors and DNA Molecular Markers

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Advances in Bioscience and Biotechnology 2018年第7期9卷 322-337页

作者： Hanaa ibrahim mohammed Nada Babiker Hamza Agricultural Research Corporation Biotechnology and Biosafety Research Center Khartoum Sudan Commission for Biotechnology & Genetic Engineering National Center for Research Khartoum Sudan

Morphological descriptors and Random Amplification of Polymorphic DNA (RAPD) technique were used to assess the genetic variation among and within forty Pennesitum glaucum accessions from Sudan. Accessions were collected from 30 villages representing Darfur, North Kordofan, South Kordofan, and Blue Nile states. 64 amplified fragments were distinguished using ten primers.? 63 bands were polymorphic among the forty accessions with an average of 6.3 polymorphic bands per primer. Low level of genetic similarity was observed (4% - 43%). The PhiPT (analogue of FST fixation index) value for genetic variability obtained over the four regions was 0.169 with high significance (P = 0.01). AMOVA analysis showed higher variance components within regions (80%) than among regions (20%). The two dendrograms obtained by Random Amplification of Polymorphic DNA (RAPD) data;and morphological data based on 26 descriptors did not fit together. PCA (Principal coordinate’s analysis) showed geographic structuring of pearl millet according to its growing regions in Sudan.

关键词： Millet Accessions RAPD Morphological Sudan

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Federated Learning with Blockchain Assisted Image Classification for Clustered UAV Networks

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Computers, Materials & Continua 2022年第7期72卷 1195-1212页

作者： ibrahim Abunadi Maha M.Althobaiti Fahd N.Al-Wesabi Anwer Mustafa Hilal Mohammad Medani Manar Ahmed Hamza mohammed Rizwanullah Abu Serwar Zamani Department of Information Systems Prince Sultan UniversityRafha StreetRiyadh11586Saudi Arabia Department of Computer Science College of Computing and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a61101Yemen Department of Computer and Self Development Prince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia

The evolving“Industry 4.0”domain encompasses a collection of future industrial developments with cyber-physical systems(CPS),Internet of things(IoT),big data,cloud computing,***,the industrial Internet of things(IIoT)directs data from systems for monitoring and controlling the physical world to the data processing system.A major novelty of the IIoT is the unmanned aerial vehicles(UAVs),which are treated as an efficient remote sensing technique to gather data from large *** are commonly employed in the industrial sector to solve several issues and help decision *** the strict regulations leading to data privacy possibly hinder data sharing across autonomous *** learning(FL)becomes a recent advancement of machine learning(ML)which aims to protect user *** this aspect,this study designs federated learning with blockchain assisted image classification model for clustered UAV networks(FLBIC-CUAV)on IIoT *** proposed FLBIC-CUAV technique involves three major processes namely clustering,blockchain enabled secure communication and FL based image *** UAV cluster construction process,beetle swarm optimization(BSO)algorithm with three input parameters is designed to cluster the UAVs for effective *** addition,blockchain enabled secure data transmission process take place to transmit the data from UAVs to cloud ***,the cloud server uses an FL with Residual Network model to carry out the image classification process.A wide range of simulation analyses takes place for ensuring the betterment of the FLBIC-CUAV *** experimental outcomes portrayed the betterment of the FLBIC-CUAV approach over the recent state of art methods.

关键词： UAV networks clustering secure communication blockchain federated learning image classification

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Integration of Fog Computing for Health Record Management Using Blockchain Technology

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Computers, Materials & Continua 2022年第5期71卷 4135-4149页

作者： Mesfer AI Duhayyim Fahd N.Al-Wesabi Radwa Marzouk Abdalla ibrahim Abdalla Musa Noha Negm Anwer Mustafa Hilal Manar Ahmed Hamza mohammed Rizwanullah Department of Natural and Applied Sciences College of Community AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia&Faculty of Computer and ITSana’a UniversityYemen Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia&Department of MathematicsFaculty of ScienceCairo UniversityGiza12613Egypt Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Science King Khaled UniversityKSA&Faculty of ScienceDepartment of Mathematics and Computer ScienceMenoufia UniversityEgypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia

Internet of Medical Things (IoMT) is a breakthrough technologyin the transfer of medical data via a communication system. Wearable sensordevices collect patient data and transfer them through mobile internet, thatis, the IoMT. Recently, the shift in paradigm from manual data storage toelectronic health recording on fog, edge, and cloud computing has been *** advanced computing technologies have facilitated medical services withminimum cost and available conditions. However, the IoMT raises a highconcern on network security and patient data privacy in the health caresystem. The main issue is the transmission of health data with high security inthe fog computing model. In today’s market, the best solution is blockchaintechnology. This technology provides high-end security and authenticationin storing and transferring data. In this research, a blockchain-based fogcomputing model is proposed for the IoMT. The proposed technique embedsa block chain with the yet another consensus (YAC) protocol building securityinfrastructure into fog computing for storing and transferring IoMT data inthe network. YAC is a consensus protocol that authenticates the input datain the block chain. In this scenario, the patients and their family membersare allowed to access the data. The empirical outcome of the proposedtechnique indicates high reliability and security against dangerous *** major advantages of using the blockchain model are high transparency,good traceability, and high processing speed. The technique also exhibitshigh reliability and efficiency in accessing data with secure transmission. Theproposed technique achieves 95% reliability in transferring a large number offiles up to 10,000.

关键词： Fog computing IoMT block chain YAC security IoT consensus protocol

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Supervised Machine Learning-Based Prediction of COVID-19

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Computers, Materials & Continua 2021年第10期69卷 21-34页

作者： Atta-ur-Rahman Kiran Sultan Iftikhar Naseer Rizwan Majeed Dhiaa Musleh mohammed Abdul Salam Gollapalli Sghaier Chabani Nehad ibrahim Shahan Yamin Siddiqui Muhammad Adnan Khan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of Computer Information System College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of CIT Faculty of Applied StudiesKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science&Information Technology Superior UniversityLahore54000Pakistan Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science Minhaj University LahoreLahore54000Pakistan Department of Computer Science Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan

COVID-19 turned out to be an infectious and life-threatening viral disease,and its swift and overwhelming spread has become one of the greatest challenges for the *** yet,no satisfactory vaccine or medication has been developed that could guarantee its mitigation,though several efforts and trials are *** around the globe are striving to overcome the COVID-19 spread and while they are finding out ways for early detection and timely *** this regard,healthcare experts,researchers and scientists have delved into the investigation of existing as well as new *** situation demands development of a clinical decision support system to equip the medical staff ways to timely detect this *** state-of-the-art research in Artificial intelligence(AI),Machine learning(ML)and cloud computing have encouraged healthcare experts to find effective detection *** study aims to provide a comprehensive review of the role of AI&ML in investigating prediction techniques for the COVID-19.A mathematical model has been formulated to analyze and detect its potential *** proposed model is a cloud-based smart detection algorithm using support vector machine(CSDC-SVM)with cross-fold validation *** experimental results have achieved an accuracy of 98.4%with 15-fold cross-validation *** comparison with similar state-of-the-art methods reveals that the proposed CSDC-SVM model possesses better accuracy and efficiency.

关键词： COVID-19 CSDC-SVM artificial intelligence machine learning cloud computing support vector machine

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The Impact of Salivary pH Value and Dental Caries Index on Periodontal Status among Adult Age Groups of Patients from Aseer Region, Saudi Arabia

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Open Journal of Stomatology 2020年第7期10卷 199-209页

作者： mohammed M. A. Abdullah Al-Abdaly Abdalkarim ibrahim mohammed Assiry Periodontics and Community Dental Sciences Department College of Dentistry King Khalid University Abha Saudi Arabia College of Dentistry King Khalid University Abha Saudi Arabia

Background: The patients’ age is considered a modified risk factor that causes periodontal disease, dental caries, and their development. Objective: The present study was designed to evaluate the impact of salivary pH value and dental caries index on periodontal status among adult age groups of patients from Aseer region, Saudi Arabia. Methods: A cross-sectional analysis carried out in the college of dentistry, King Khalid University on 750 adult patients (400 males and 350 females). The adults patients were divided into three equal groups according to the patients’ age: group I (20 - 30 years), group II (31 - 40 years), and group III (41 - 50 years). Plaque index (PLI), gingival index (GI), clinical attachment loss (CAL), and the dental caries index (DMFT) recorded as well as salivary pH. All findings collected, then analyzed by an ANOVA test and the t-test. A p-value at Results: The clinical findings of the current study showed that there were statistically significant differences in the patients’ age of both males and females. Moreover, there were statistically significant differences in GI. On the other hand, there were highly statistically significant differences in PLI and DMFS, but there were no significant differences in CAL of both males and females Moreover, there were no statistically significant differences in salivary pH. Conclusion: We concluded that DMFT Index correlated to periodontal and oral health status and, it increased with the progression of the pat

关键词： Adult Age Groups of Patients Dental Caries Index Periodontal Status Salivary pH

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Predictors of time-to-nadir serum creatinine after drainage of bilaterally obstructed kidneys due to bladder cancer

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Current Urology 2023年第4期17卷 246-250页

作者： Rabea Ahmed Gadelkareem Ahmed Mahmoud Abdelraouf Abdelfattah ibrahim Ahmed Ahmed mohammed El-Taher Hosny Mahmoud Behnsawy Assiut Urology and Nephrology Hospital Faculty of MedicineAssiut UniversityAssiut71515Egypt

Background:There are persistent controversies about the outcomes and benefits of drainage of malignant ureteral obstruction by percutaneous nephrostomy(PCN).This study aimed to assess the predictors of the time-to-nadir(TTN)of serum creatinine(SCr)levels after drainage of bilaterally obstructed kidneys(BOKs)due to bladder cancer(BC)by *** and methods:This prospective nonrandomized study included patients with BOKs due to BC treated by PCN between April 2019 and March *** primary outcome measure was ***:Of the 55 patients with a median age(range)of 66 years(47-86 years),32(58.2%)had a normal nadir SCr and 23(41.8%)had a high nadir SCr within 21 days after drainage of BOKs due to *** nadir SCr was associated with a higher mean age(p=0.011)and lower body mass index(BMI,p=0.043).However,patients with normal nadir SCr had a significantly shorter TTN(p=0.023)and an increased mean SCr trajectory(p<0.001)during *** multivariate analysis,low urine output at presentation(p=0.021)and high BMI(p=0.006)were associated with longer ***,the mean parenchymal thickness(p=0.428)and laterality of drainage(p=0.466)were not associated with the mean TTN and SCr normalization *** to the modified Clavien-Dindo classification,8 cases of hematuria were managed conservatively(grade 2),and 2 cases of PCN slippage were repositioned using local anesthesia(grade 3).Conclusions:Despite the safety of PCN for drainage of BOKs due to BC,more than 41%of the patients failed to have a normal nadir *** low urine output and high BMI were associated with longer *** of drainage had no significant effects on the TTN and SCr trajectory.

关键词： Bladder cancer Bilaterally obstructed kidneys Malignant ureteral obstruction Percutaneous nephrostomy Time-to-nadir Serum creatinine

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Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

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Computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa Sami Khafaga Faten Khalid Karim Abdelaziz A.Abdelhamid El-Sayed M.El-kenawy Hend K.Alkahtani Nima Khodadadi mohammed Hadwan Abdelhameed ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LSH)and Synthetic Minority Oversampling Technique(SMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

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Interference Mitigation MAC Protocol for Cognitive Radio Networks

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Wireless Engineering and Technology 2012年第2期3卷 63-71页

作者： Nasir Faruk Maaruf Ali mohammed ibrahim Gumel College of Computer Science & Engineering University of Ha’il Ha’il KSA Department of Telecommunication Science University of Ilorin Ilorin Nigeria Huawei Technologies Kano Nigeria

The growing demand for wireless services coupled with the limited availability of suitable electromagnetic spectrum is increasing the need for more efficient RF spectrum utilization. Spectrum allocated to TV operators can potentially be shared by wireless data services, either when the primary service is switched off or by exploiting spatial reuse opportunities. This paper describes a dynamic spectrum access scheme for use in the TV bands which uses cognitive radio techniques to determine the spectrum availability. The approach allows secondary users (SU) to operate in the presence of the primary users (PU) and the OPNET simulation and modelling software has been used to model the performance of the scheme. An analysis of the results shows that the proposed scheme protects the primary users from harmful interference from the secondary users. In comparison with the 802.11 MAC protocol, the scheme improves spectrum utilization by about 27% while limiting the interference imposed on the primary receiver.

关键词： Dynamic Spectrum Access (DSA) Optimized Network Engineering Tool (OPNET) TV White Space Cognitive Radio Networks Signal-to-Interference Ratio (SIR)

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Potential Toxic Effects of Olanzapine on Metabolic Parameters in <i>de Novo</i>Paranoid Schizophrenic Patients. The Role of Adjunctive Aripeprazole: Clinical and Experimental Study

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Occupational Diseases and Environmental Medicine 2019年第3期7卷 91-113页

作者： Hisham mohammed Al-Sayed Wafaa ibrahim Soliman Neuropsychiatric Department Faculty of Medicine Benha University Benha Egypt Department of Forensic Medicine and Clinical Toxicology Faculty of Medicine Zagazig University Zagazig Egypt

Background: Approximately 75% of all deaths in people with schizophrenia are caused by physical illness with cardiovascular disease [CVD] being the commonest cause of death. Factors predisposing people with schizophrenia to CVD include antipsychotic medication. Aim of Work: The aim of this study was to detect metabolic syndrome and its components in de novo paranoid schizophrenics on olanzapine therapy and the metabolic benefits of addition of aripeprazole, clinically and experimentally. Methodology: 1) Clinical study: 200 Outpatients suffered from de novo paranoid schizophrenia according to 10th International Classification of Psychiatric Disorders, Research Criteria [ICD10 RC] were included in the study. None of them had any component of metabolic syndrome. They were maintained on olanzapine [10 - 20 mg]. Patients were assessed clinically, psychometrically using Scale for the Assessment of Negative [SANS] and Positive [SAPS] Symptoms and metabolically at base line and after 6 months. Patients who had metabolic syndrome after 6 month of starting olanzapine therapy, were randomly divided into two groups according to added regime to maintained olanzapine: Group 1: olanzapine [10 mg/day] + placebo [empty hard gelatin capsule]. Group II: olanzapine [10 mg/day] + aripeprazole [10 mg/day]. 2) Experimental study: 40 male albino rats were randomly equally divided into 4 groups: Group 1 [control group]: received a standard diet, Group II [olanzapine treated]: received olanzapine at a dose of 0.5 mg/kg/day, Group III [aripiprazole treatd]: received aripiprazole at a dose of 2 mg/kg/day, Group IV [combined olanzapine and aripiprazole treated]: received olanzapine at a dose of 0.5 mg/kg/day combined with aripiprazole at a dose of 2 mg/kg/day orally. The duration of the study was 16 weeks. All treated rat groups were assessed for metabolic parameters, liver enzymes and histopathology. Results: Clinically, after the 6 months of olanzapine treatment [mean dose 12.75 mg], there wa

关键词： Olanzapine Aripeprazole Paranoid Schizophrenia Metabolic Syndrome Fatty Liver Disease

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