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Rare earth based MgPm_(2)X_(4)(X=S,Se) spinel chalcogenides for spintronic and thermoelectric applications

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Journal of Rare Earths 2024年第8期42卷 1577-1585,I0006页

作者： Tariq M.al-Daraghmeh omar Zayed Ghulam M.Mustafa Taharh Zelai Bisma Younas Hind albalawi S.Bouzgarrou Othman Hakami Q.Mahmood Khaild I.Hussein Basic Sciences Department King Abdullah Ⅱ School of EngineeringPrincess Sumaya University For TechnologyP.O.Box 1438Al-jubaiha11941AmmanJordan Department of Physics Division of Science&TechnologyUniversity of EducationLahorePakistan Department of Physics Faculty of ScienceJazan University JazanSaudi Arabia Department of Physics The University of LahoreLahorePakistan Department of Physics College of SciencesPrincess Nourah bint Abdulrahman University(PNU)P.O.Box 84428Riyadh11671Saudi Arabia Department of Physics College of ScienceQassim UniversityPo.64BuraidahSaudi Arabia Laboratoire de Microelectronique et Instrumentation(UR 03/13-04) Faculte des Sciences de MonastirAvenue de I'Environnement 5000MonastirTunisia Department of Chemistry Faculty of ScienceJazan University JazanSaudi Arabia Basic&Applied Scientific Research Center Department of PhysicsCollege of ScienceImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam 31441Saudi Arabia Department of Radiological Sciences College of Applied Medical SciencesKing Khalid UniversityAbha61421Saudi Arabia

In current report,the structural,magnetic,and thermoelectric properties of RE doped MgPm_(2)X_(4)(X=S,Se) spinels were *** energy difference in ferromagnetic and antiferromagnetic states reveals the stability of MgPm_(2)(S/Se)_(4) in the ferromagnetic *** co mputation of enthalpy of formation also ascertains thermodynamic stability of crystal ***-dependent band structure and density of states a.alysis reveal ferromagnetic semiconducting character showing different electronic behavior in both spin *** room temperature ferromagnetism,spin polarization and Curie temperature are estimated from exchange energies *** addition,exchange constants(N_(0)α and N_(0)β),exchange energy Δ_(x)(pd),crystal ifeld energy,and double exchange mechanism were studied to explore the magnetic ***,the electrical conductivity,thermal conductivity,Seebeck co-efficient,and power factor show effect on electrons spin and their potential for thermoelectric devices.

关键词： Rare earth elements Spintronic applications Thermoelectric effects Exchange energies

Genotype-based precision nutrition strategies for the prediction and clinical management of type 2 diabetes mellitus

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World Journal of Diabetes 2024年第2期15卷 142-153页

作者： omar Ramos-Lopez Medicine and Psychology School Autonomous University of Baja CaliforniaTijuana 22390Baja CaliforniaMexico

Globally,type 2 diabetes mellitus(T2DM)is one of the most common metabolic disorders.T2DM physiopathology is influenced by complex interrelationships between genetic,metabolic and lifestyle factors(including diet),which differ between populations and geographic *** fact,excessive consumptions of high fat/high sugar foods generally increase the risk of developing T2DM,whereas habitual intakes of plant-based healthy diets usually exert a protective ***,genomic studies have allowed the characterization of sequence DNA variants across the human genome,some of which may affect gene expression and protein functions relevant for glucose *** comprehensive literature review covers the impact of gene-diet interactions on T2DM susceptibility and disease progression,some of which have demonstrated a value as biomarkers of personal responses to certain nutritional ***,novel genotype-based dietary strategies have been developed for improving T2DM control in comparison to general lifestyle ***,progresses in other omics areas(epigenomics,metagenomics,proteomics,and metabolomics)are improving current understanding of genetic insights in T2DM clinical *** more investigation is still needed,the a.alysis of the genetic make-up may help to decipher new paradigms in the pathophysiology of T2DM as well as offer further opportunities to personalize the screening,prevention,diagnosis,management,and prognosis of T2DM through precision nutrition.

关键词： Type 2 diabetes mellitus Nutrigenetics Single nucleotide polymorphism Genotype Diet Precision nutrition

Malware Attacks Detection in IoT Using Recurrent Neural Network(RNN)

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Intelligent Automation & Soft Computing 2024年第2期39卷 135-155页

作者： Abeer Abdullah alsadhan Abdullah a.al-Atawi Hanen karamti Abid Jameel Islam Zada Tan N.Nguyen Computer Science Department Imam Abdulrahman Bin Faisal UniversityDamam32232Saudi Arabia Department of Computer Science Applied CollegeUniversity of TabukTabuk47512Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences and Information Technology Hazara UniversityMansehraPakistan Faculty of Computing Department of Software EngineeringInternational Islamic UniversityIslamabadPakistan Department of Architectural Engineering Sejong UniversitySeoul05006Korea

IoT(Internet of Things)devices are being used more and more in a variety of businesses and for a variety of tasks,such as environmental data collection in both civilian and military *** are a desirable attack target for malware intended to infect specific IoT devices due to their growing use in a variety of applications and their increasing computational and processing *** this study,we investigate the possibility of detecting IoT malware using recurrent neural networks(RNNs).RNNis used in the proposed method to investigate the execution operation codes of ARM-based Internet of Things apps(OpCodes).To train our algorithms,we employ a dataset of IoT applications that includes 281 malicious and 270 benign pieces of *** trained model is then put to the test using 100 brand-new IoT malware samples across three separate LSTM *** exposure was not previously conducted on these *** newly crafted malware samples with 2-layer neurons had the highest accuracy(98.18%)in the 10-fold cross validation experiment.A comparison of the LSTMtechnique to other machine learning classifiers shows that it yields the best results.

关键词： Malware malicious code code obfuscation IoT machine learning deep learning

Assessment of Heavy Metals Contamination of Topsoil and Street Dust around Cement Factory in Southern Jordan

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Journal of Environmental Protection 2024年第6期15卷 672-696页

作者： omar ali al-Khashman alia omar al-Khashman Navasingh Rajesh Jesudoss Hynes Hani M. alnawafleh Pitchumani Shenbaga Velu Department of Environmental Engineering Al-Hussein Bin Talal University Maan Jordan MD/Ministry of Health Amman Jordan Department of Mechanical Engineering Mepco Schlenk Engineering College Si-vakasi India Department of Mining and Mineral Engineering Al-Hussein Bin Talal University Maan Jordan Department of Mechanical Engineering PSR Engineering College Sivakasi India

Evaluation of assessment of the metal processes governing the metals distribution in soil and dust samples is very significant and protects the health of human and ecological system. Recently, special attention has given to the assessment of metals pollution impact on soil and dust within industrial areas. This study aims to assess the metal contamination levels in the topsoil and street dust around the cement factory in Qadissiya area, southern Jordan. The levels of seven metals (namely Fe, Zn, Cu, Pb, Cr, Cd, and Mn) were a.alyzed using Flame Atomic Absorption Spec-trophotometer (FAAS) to monitor, evaluate, and to compare topsoil and road dust pollution values of metals of the different types of urban area. The physicochemical parameters which believed to affect the mobility of metals in the soil of the study area were determined such as pH, EC, TOM, CaCO3 and CEC. The levels of metal in soil samples are greater on the surface but decrease in the lower part as a result of the basic nature of soil. The mean values of the metals in soil can be arranged in the following order: Zn > Pb > Mn > Fe > Cu > Cr > Cd. The relatively high concentration of metals in the soil sample was attributed to anthropogenic activities such as traffic emissions, cement factory and agricultural activities. Correlation coefficient a.alysis and the spatial distribution of indices and the results of statistical a.alysis indicate three groups of metals: Fe and Mn result by natural origin, Zn, Pb, Cu and Zn result by anthropogenic origin (mainly motor vehicle traffic and abrasion of tires) while Cd is mixed origin. The higher content level values of metals of anthropogenic source in soil samples indicate that it is a source of contamination of air in the studied area. .

关键词： Cement Dust Heavy Metals Contamination Risk Assessment Statistical a.alysis Jordan

Melittin a.alog p5RHH enhances recombinant adeno-associated virus transduction efficiency

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Journal of Integrative Medicine 2024年第1期22卷 72-82页

作者： Jing-shun Meng Yun He Heng-bin Yang Li-ping Zhou Si-yuan Wang Xi-lin Feng omar Yahya.al-shargi Xiao-min Yu Li-qing Zhu Chang-quan Ling Shanghai University of Traditional Chinese Medicine Shanghai 201203China Oncology Department of Traditional Chinese Medicine Changhai HospitalNaval Medical UniversityShanghai 200433China Faculty of Traditional Chinese Medicine Naval Medical UniversityShanghai 200043China State Key Laboratory of Genetic Engineering and Engineering Research Center of Gene Technology(Ministry of Education) School of Life SciencesZhongshan HospitalFudan UniversityShanghai 200438China Yantai Fuheng Biological Technology Co. Ltd.YantaiShandong Province 264006China. Department of Clinical Laboratory the First Affiliated Hospital of Wenzhou Medical UniversityWenzhou 325000Zhejiang ProvinceChina

Objective Melittin and its derivatives have been characterized to establish effective gene delivery *** capability of facilitating endosomal release enhances the nanoparticles-based gene ***,little investigation has been conducted to explore its potential application in the context of viral *** Various melittin-derived peptides were inserted into the loop VIII of the capsid proteins of recombinant adeno-associated virus *** vectors carrying either gfp or fluc genes were subjected to qPCR assays and transduction assays of HEK293T cells to investigate the efficiency of vector production and gene *** addition,the ability of a specific p5RHH-rAAV vector to deliver genes was examined through in vitro transduction of different cultured cells and in vivo tail vein administration to C57BL/6 ***,the intricate details of the vector-mediated transduction mechanisms were revealed by specific pharmacological inhibitors of every stage of the rAAV2 intracellular life *** A total of 76 melittin-related peptides were compiled from existing *** them,cMA2,Melt13,p5RHH and aAR3 were found to significantly enhance the gene delivery efficiency of rAAV2 *** p5RHH-rAAV2 vectors efficiently transduced not only rAAV-potent cell lines but also cell lines previously considered resistant to ***,bafilomycin A1,a vacuolar endosome acidification inhibitor,completely inhibited the transgene expression mediated by the p5RHH-rAAV2 *** importantly,p5RHH-rAAV8 vectors also demonstrated increased hepatic transduction in vivo in C57BL/6 *** The incorporation of melittin a.alogues into the rAAV capsids results in a significant improvement in rAAV-mediated transgene *** further modifications remain an area of interest,our studies have substantially broadened the pharmacological prospects of melittin in the context of viral vector-mediated gene delivery.

关键词： Melittin Recombinant adeno-associated virus Capsid engineering Transduction efficiency

Advanced Optimized Anomaly Detection System for IoT Cyberattacks Using Artificial Intelligence

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Computers, Materials & Continua 2024年第2期78卷 1525-1545页

作者： ali Hamid Farea omar H.alhazmi Kerem Kucuk Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Department of Software Engineering Kocaeli UniversityKocaeli41001Turkey

While emerging technologies such as the Internet of Things(IoT)have many benefits,they also pose considerable security challenges that require innovative solutions,including those based on artificial intelligence(AI),given that these techniques are increasingly being used by malicious actors to compromise IoT *** an ample body of research focusing on conventional AI methods exists,there is a paucity of studies related to advanced statistical and optimization approaches aimed at enhancing security *** contribute to this nascent research stream,a novel AI-driven security system denoted as“AI2AI”is presented in this ***2AI employs AI techniques to enhance the performance and optimize security mechanisms within the IoT *** also introduce the Genetic algorithm Anomaly Detection and Prevention Deep Neural Networks(GAADPSDNN)sys-tem that can be implemented to effectively identify,detect,and prevent cyberattacks targeting IoT ***,this system demonstrates adaptability to both federated and centralized learning environments,accommodating a wide array of IoT *** evaluation of the GAADPSDNN system using the recently complied WUSTL-IIoT and Edge-IIoT datasets underscores its *** an impressive overall accuracy of 98.18%on the Edge-IIoT dataset,the GAADPSDNN outperforms the standard deep neural network(DNN)classifier with 94.11%***,with the proposed enhancements,the accuracy of the unoptimized random forest classifier(80.89%)is improved to 93.51%,while the overall accuracy(98.18%)surpasses the results(93.91%,94.67%,94.94%,and 94.96%)achieved when alternative systems based on diverse optimization techniques and the same dataset are *** proposed optimization techniques increase the effectiveness of the anomaly detection system by efficiently achieving high accuracy and reducing the computational load on IoT devices through the adaptive selection of active features.

关键词： Internet of Things security anomaly detection and prevention system artificial intelligence optimization techniques

Mapping the global research landscape on nonalcoholic fatty liver disease and insulin resistance:A visualization and bibliometric study

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World Journal of Hepatology 2024年第6期16卷 951-965页

作者： Sa'ed H Zyoud omar E Hegazi Samer O a.alalmeh Muna Shakhshir Faris Abushamma Shadi Khilfeh Samah W al-Jabi Department of Clinical and Community Pharmacy College of Medicine and Health SciencesAn-Najah National UniversityNablus 44839Palestine Clinical Research Center An-Najah National University HospitalNablus 44839Palestine College of Pharmacy and Health Sciences Ajman UniversityAjman 346United Arab Emirates Department of Nutrition An-Najah National University HospitalNablus 44839Palestine Department of Medicine College of Medicine and Health SciencesAn-Najah National UniversityNablus 44839Palestine Department of Urology An-Najah National University HospitalNablus 44839Palestine Department of Gastroenterology Hepatology and EndoscopyAn-Najah National University HospitalNablus 44839Palestine

BACKGROUND Nonalcoholic fatty liver disease(NAFLD)is a liver condition that is prevalent worldwide and associated with significant health risks and economic *** it has been linked to insulin resistance(IR),this study aimed to perform a bibliometric a.alysis and visually represent the scientific literature on IR and *** To map the research landscape to underscore critical areas of focus,influential studies,and future directions of NAFLD and *** This study conducted a bibliometric a.alysis of the literature on IR and NAFLD indexed in the SciVerse Scopus database from 1999 to *** search strategy used terms from the literature and medical subject headings,focusing on terms related to IR and *** software was used to visualize research trends,collaborations,and key thematic *** a.alysis examined publication type,annual research output,contributing countries and institutions,funding agencies,journal impact factors,citation patterns,and highly cited *** This a.alysis identified 23124 documents on NAFLD,revealing a significant increase in the number of publications between 1999 and *** search retrieved 715 papers on IR and NAFLD,including 573(80.14%)articles and 88(12.31%)*** most productive countries were China(n=134;18.74%),the United States(n=122;17.06%),Italy(n=97;13.57%),and Japan(n=41;5.73%).The leading institutions included the Universitàdegli Studi di Torino,Italy(n=29;4.06%),and the Consiglio Nazionale delle Ricerche,Italy(n=19;2.66%).The top funding agencies were the National Institute of Diabetes and Digestive and Kidney Diseases in the United States(n=48;6.71%),and the National Natural Science Foundation of China(n=37;5.17%).The most active journals in this field were Hepatology(27 publications),the Journal of Hepatology(17 publications),and the Journal of Clinical Endocrinology and Metabolism(13 publications).The main research hotspots were“therapeutic approaches for IR and NAFLD”and“inflamma

关键词： Nonalcoholic fatty liver disease Insulin resistance Bibliometric Visualization

Single image super-resolution:a comprehensive review and recent insight

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Frontiers of Computer Science 2024年第1期18卷 139-156页

作者： Hanadi al-MEKHLAFI Shiguang LIU College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Super-resolution(SR)is a long-standing problem in image processing and computer vision and has attracted great attention from researchers over the *** main concept of SR is to reconstruct images from low-resolution(LR)to high-resolution(HR).It is an ongoing process in image technology,through up-sampling,de-blurring,and *** neural network(CNN)has been widely used to enhance the resolution of images in recent *** alternative methods use deep learning to improve the progress of image super-resolution based on ***,we review the recent findings of single image super-resolution using deep learning with an emphasis on distillation knowledge used to enhance image super-resolution.,it is also to highlight the potential applications of image super-resolution in security monitoring,medical diagnosis,microscopy image processing,satellite remote sensing,communication transmission,the digital multimedia industry and video ***,we present the challenges and assess future trends in super-resolution based on deep learning.

关键词： super-resolution deep learning single-image interpolation-based learning-based reconstruction-based

RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad Saad al-Ahmadi Ja.al al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as a.alicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning