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Room Temperature Synthesis of Vertically Aligned Amorphous Ultrathin NiCo-LDH Nanosheets Bifunctional Flexible Supercapacitor Electrodes

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Energy & Environmental Materials 2024年第2期7卷 281-290页

作者： Kwadwo Asare Owusu Zhaoyang Wang Ali Saad Felix Ofori Boakye muhammad asim mushtaq muhammad Tahir Ghulam Yasin Dongqing Liu Zhengchun Peng Xingke Cai Institute for Advanced Study Shenzhen University College of Physics and Optoelectronics Shenzhen University School of Chemistry and Materials Science Hubei Engineering University State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of Technology Key Laboratory of Green Printing CAS Research Centre for Excellence in Molecular Science Institute of Chemistry Chinese Academy of Sciences (ICCAS) College of Mechatronics and Control Engineering Shenzhen University

Developing a simple scalable method to fabricate electrodes with high capacity and wide voltage range is desired for the real use of electrochemical supercapacitors. Herein, we synthesized amorphous Ni Co-LDH nanosheets vertically aligned on activated carbon cloth substrate, which was in situ transformed from Co-metal–organic framework materials nano-columns by a simple ion exchange process at room temperature. Due to the amorphous and vertically aligned ultrathin structure of Ni Co-LDH, the Ni Co-LDH/activated carbon cloth composites present high areal capacities of 3770 and1480 m F cm-2as cathode and anode at 2 m A cm-2, and 79.5% and 80%capacity have been preserved at 50 m A cm-2. In the meantime, they all showed excellent cycling performance with negligible change after>10 000 cycles. By fabricating them into an asymmetric supercapacitor, the device achieves high energy densities(5.61 m Wh cm-2and 0.352 m W cm-3).This work provides an innovative strategy for simplifying the design of supercapacitors as well as providing a new understanding of improving the rate capabilities/cycling stability of Ni Co-LDH materials.

关键词： amorphous nanosheets aqueous supercapacitor high volumetric/areal energy density NiCo-LDH room temperature synthesis

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Mn-based MXene with high lithium-ion storage capacity

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Nano Research 2024年第5期17卷 4181-4191页

作者： Yanyan Wu Dongqing Liu Xiaonan Wang Usman Ghani muhammad asim mushtaq Jinfeng Yang Huarui Sun Panagiotis Tsiakaras Xingke Cai School of Science and Ministry of Industry and Information Technology Key Laboratory of Micro-Nano Optoelectronic Information System Harbin Institute of Technology ShenzhenShenzhen 5180552 China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Institute for Advanced Study Shenzhen UniversityShenzhen 518060China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Laboratory of Alternative Energy Conversion Systems Department of Mechanical EngineeringSchool of EngineeringUniversity of ThessalyPedion Areos 38834Greece

3d-transition metal(Fe,Co,Ni,and Mn)-based MXene materials have been predicted to demonstrate exceptional electrochemical performance because of their good electrical conductivity and the presence of metallic atoms with multiple charge ***,until now,there have been no reports on MXenes based on Fe,Co,Ni,and Mn,due to the lack of 3d-metal-layered ***,we successfully synthesized the first 3d-transition metal-based MXenes,Mn_(2)CT_(x) by exfoliating a layered precursor derived from the anti-perovskite bulk *** as-prepared Mn_(2)CT_(x) MXene nanosheets were employed as anode materials in lithium-ion batteries,which exhibited stable storage capacity of 764.7 mAh·g^(-1) at 0.5 C,placing its storage capacities at an upper-middle level compared with other reported MXene materials as well as other Mn-based anode ***,this study opens a new avenue for MXene research by synthesizing 3d-transition metal-based MXenes for electrochemical applications.

关键词： Mn_(3)GaC Mn_(2)CT_(x) MXenes lithium-ion battery anode materials negative fading capacity

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Highly active sites of NiVB nanoparticles dispersed onto graphene nanosheets towards efficient and pH-universal overall water splitting

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Journal of Energy Chemistry 2021年第7期30卷 237-246页

作者： muhammad Arif Ghulam Yasin muhammad Shakeel muhammad asim mushtaq Wen Ye Xiaoyu Fang Shengfu Ji Dongpeng Yan Beijing Key Laboratory of Energy Conversion and Storage Materials College of ChemistryBeijing Normal UniversityBeijing 100875China State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical TechnologyBeijing 100029China College of Chemistry and Molecular Engineering Zhengzhou UniversityZhengzhou 450001HenanChina

Production of hydrogen(H2) and oxygen(O2) through electrocatalytic water splitting is one of the sustainable,green and pivotal ways to accomplish the ever-increasing demands for renewable energy sources,but remains a big challenge because of the uphill reaction during overall water ***,we develop high-performance non-noble metal electrocatalysts for pH-universal water splitting,based on nickel/vanadium boride(NiVB) nanoparticles/reduced graphene oxide(rGO) hybrid(NiVB/rGO)through a facile chemical reduction approach under ambient *** virtue of more exposure to surface active sites,superior electron transfer capability and strong electronic coupling,the asprepared NiVB/rGO heterostructure needs pretty low overpotentials of 267 and 151 mV to deliver a current density of 10 mA cm^(-2) for oxygen evolution reaction(OER) and hydrogen evolution reaction(HER)respectively,with the corresponding Tafel slope of 44 and 88 mV dec^(-1) in 1.0 M ***,the NiVB/rGO electrocatalysts display a promising performance in a wide-pH conditions that require low overpotential of 310,353 and 489 mV to drive a current density of 10 mA cm^(-2) for OER under 0.5 M KOH,0.05 M H2SO4 and 1.0 M phosphate buffer solution(PBS) respectively,confirming the excellent electrocata lytic performance among state-of-the-art Ni-based electrocatalysts for overall water ***,the interfacial tuning based on incorporation of active heterostructure may pave a new route to develop bifunctional,cost-effective and efficient electrocatalyst systems for water splitting and H2 production.

关键词： Electrocatalysis Oxygen evolution reaction Hydrogen evolution reaction NiVB/rGO heterostructure pH-universal

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Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

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Computers, Materials & Continua 2024年第5期79卷 3333-3353页

作者： Aiman muhammad Arshad Bilal Khan Sadique Ahmad muhammad asim Department of Computer Science City University of Science and Information TechnologyPeshawar25000Pakistan EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia School of Computer Science and Technology Guangdong University of TechnologyGuangzhou510006China

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,***, the research on RomanUrdu is not up to the ***, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including J48-Decision Tree (J48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

关键词： Digital forensics author profiling for security AdaBoostM1 random forest ensemble learning

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Acoustofluidic separation of prolate and spherical micro-objects

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Microsystems & Nanoengineering 2024年第1期10卷 217-230页

作者： muhammad Soban Khan mushtaq Ali Song Ha Lee Keun Young Jang Seong Jae Lee Jinsoo Park Department of Mechanical Engineering Chonnam National University77 Yongbong-roBuk-guGwangju 61186Republic of Korea Department of Polymer Engineering The University of Suwon17 Wauan-gilBongdam-eupHwaseongGyeonggi 18323Republic of Korea

Most microfluidic separation techniques rely largely on object size as a separation *** ability to separate micro-objects based on their shape is crucial in various biomedical and chemical ***,we develop an ondemand,label-free acoustofluidic method to separate prolate ellipsoids from spherical microparticles based on traveling surface acoustic wave-induced acoustic radiation force and *** freely rotating non-spherical microobjects were aligned under the progressive acoustic field by the counterrotating radiation torque,and the major axis of the prolate ellipsoids was parallel to the progressive wave *** specific alignment of the ellipsoidal particles resulted in a reduction in the cross-sectional area perpendicular to the wave *** a consequence,the acoustic backscattering decreased,resulting in a decreased magnitude of the radiation *** the variation in radiation force,which depended on the micro-object morphology enabled the acoustofluidic shape-based *** conducted numerical simulations for the wave scattering of spherical and prolate objects to elucidate the working mechanism underlying the proposed method.A series of experiments with polystyrene microspheres,prolate ellipsoids,and peanut-shaped microparticles were performed for *** quantitative analysis of the separation efficiency,we confirmed the high purity and high recovery rate of the proposed acoustofluidic shapebased separation of *** a bioparticle,we utilize Thalassiosira eccentrica to perform shape-based separation,as the species has a variety of potential applications in drug delivery,biosensing,nanofabrication,bioencapsulation and immunoisolation.

关键词： separation spherical rotating

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Phytochemical analysis, antioxidant, acetylcholinesterase, and α-amylase inhibitors from Hippeastrum hybridum extract

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Journal of Traditional Chinese Medicine 2024年第3期44卷 496-504页

作者： Naila Sher mushtaq Ahmed Nadia mushtaq Department of Biotechnology University of Science and Technology Department of Botany University of Science and Technology

OBJECTIVE:To investigate the effects of Hippeastrum hybridum（HH） as a free radical scavenger,and an inhibitor of the two enzymes i-e Alpha-amylase（α-amylase） and acetylcholinesterase（AChE）.METHODS:In this study,HH plant was preliminary analyzed for phytochemical screening and then tested for its antioxidant,anti-α-amylase,and anti-AChE efficiency via standard ***:Phytochemical analysis shows the existence of different compounds;while Coumarins and quinones were *** total phenolic,flavonoid,and tannins content were found to be（78.52±0.69） mg GAE/g,（2.01±0.04） mg RUE/g,and（58.12±0.23） mg TAE/g of plant extract respectively.28.02%±0.02% alkaloid and 2.02%±0.05% saponins were present in the HH *** HH extract showed the anti-oxidant property with IC50（50%inhibition） of（151.01±0.13）(HH),（79.01±0.04）(Ascorbic acid) for ferric reducing,（91.48±0.13）(HH),（48.02±0.11）(Ascorbic acid) against Ammonium molybdenum,（156.02±0.31）(HH),（52.38±0.21）(Ascorbic acid) against DPPH,136.01±0.21（HH）,52.02±0.31（Ascorbic acid） against H2O2,and 154.12±0.03（HH）,（40.05±0.15）(Ascorbic acid)μg/mL against ABTS *** analysis indicated that HH caused a competitive type of inhibition of α-amylase(Vmaxremained constant and Km increases from 10.65 to84.37%) while Glucophage caused the un-competitive type of inhibition i-e both Km and Vmaxdecreased from40.49 to 69.15%and 38.86 to 69.61%*** Ki,（inhibition constant）;KI,（dissociation constant）,Km,（Michaelis-Menten constant）,and IC50 were found to be62,364,68.1,and 38.08±0.22 for HH and 12,101.05,195,34.01±0.21 for ***,HH causes an anon-competitive type of inhibition of AChE i-e Km remains constant while Vmaxdecreases from 60.5%to74.1%.The calculated Ki,KI,Km,and IC50 were found to be 32,36.2,0.05,and 18.117±***:From the current results,it is concluded that HH extract contains bioactive compounds,and could be a good alternative to controlling oxidants,Alzheimer‘s and T

关键词： Hippeastrum hybridum acetylcholinesterase alpha-amylase antioxidant phytochemicals

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Mesenchymal stem cells’“garbage bags”at work:Treating radial nerve injury with mesenchymal stem cell-derived exosomes

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World Journal of Stem Cells 2024年第5期16卷 467-478页

作者： Mazhar mushtaq Doaa Hussein Zineldeen muhammad Abdul Mateen Khawaja Husnain Haider Department of Basic Sciences Sulaiman AlRajhi UniversityAlbukairiyah 52736AlQaseemSaudi Arabia Medical Biochemistry and Molecular Biology Department Faculty of MedicineTanta UniversityTanta 6632110Egypt

Unlike central nervous system injuries,peripheral nerve injuries(PNIs)are often characterized by more or less successful axonal ***,structural and functional recovery is a senile process involving multifaceted cellular and molecular *** contemporary treatment options are limited,with surgical intervention as the gold-standard method;however,each treatment option has its associated limitations,especially when the injury is severe with a large *** advancements in cell-based therapy and cell-free therapy approaches using stem cell-derived soluble and insoluble components of the cell secretome are fast-emerging therapeutic approaches to treating acute and chronic *** recent pilot study is a leap forward in the field,which is expected to pave the way for more enormous,systematic,and well-designed clinical trials to assess the therapeutic efficacy of mesenchymal stem cell-derived exosomes as a bio-drug either alone or as part of a combinatorial approach,in an attempt synergize the best of novel treatment approaches to address the complexity of the neural repair and regeneration.

关键词： Exosome Mesenchymal stem cells Nerve injury Stem cells Secretome Regeneration

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Depression Intensity Classification from Tweets Using Fast Text Based Weighted Soft Voting Ensemble

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Computers, Materials & Continua 2024年第2期78卷 2047-2066页

作者： muhammad Rizwan muhammad Faheem mushtaq Maryam Rafiq Arif Mehmood Isabel de la Torre Diez Monica Gracia Villar Helena Garay Imran Ashraf Department of Artificial Intelligence The Islamia University of BahawalpurBahawalnagar63100Pakistan Department of Information Technology Khwaja Fareed University of Engineering and ITRYKhan64200Pakistan Department of Computer Science&Information Technology The Islamia University of BahawalpurBahawalnagar63100Pakistan Department of Signal Theory and Communications and Telematic Engineering Unviersity of ValladolidPaseo de Belén 15Valladolid47011Spain Faculty of Social Science and Humanities Universidad Europea del Atlántico Isabel Torres 21Santander39011Spain Department of Project Management Universidad Internacional IberoamericanaCampeche24560México Fundación Universitaria Internacional de Colombia Bogotá111611Colombia Universidad Internacional Iberoamericana AreciboPuerto Rico00613USA Universidade Internacional do Cuanza Cuito46703Angola Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541South Korea

Predicting depression intensity from microblogs and social media posts has numerous benefits and applications,including predicting early psychological disorders and stress in individuals or the general public.A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media *** study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces(APIs).A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the ***,an algorithm is developed to annotate the data into three depression classes:‘Mild,’‘Moderate,’and‘Severe,’based on International Classification of Diseases-10(ICD-10)depression diagnostic *** baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the *** FastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model,which significantly increases the depression classification performance to an 84%F1 score and 90%accuracy compared to ***,a FastText-based weighted soft voting ensemble(WSVE)is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual *** proposed WSVE outperformed all baselines as well as FastText alone,with an F1 of 89%,5%higher than FastText alone,and an accuracy of 93%,3%higher than FastText *** proposed model better captures the contextual features of the relatively small sample class and aids in the detection of

关键词： Depression classification deep learning FastText machine learning

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Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

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Computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： muhammad Armghan Latif Zohaib mushtaq Saad Arif Sara Rehman muhammad Farrukh Qureshi Nagwan Abdel Samee Maali Alabdulhafith Yeong Hyeon Gu Mohammed A.Al-masni Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biomedical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

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Securing Cloud-Encrypted Data:Detecting Ransomware-as-a-Service(RaaS)Attacks through Deep Learning Ensemble

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Computers, Materials & Continua 2024年第4期79卷 857-873页

作者： Amardeep Singh Hamad Ali Abosaq Saad Arif Zohaib mushtaq muhammad Irfan Ghulam Abbas Arshad Ali Alanoud Al Mazroa School of Computer Information Sciences University of CumberlandsWilliamsburgKentucky40769USA Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Department of Electrical Engineering The University of LahoreLahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries,especially in light of the growing number of cybersecurity threats.A major and everpresent threat is Ransomware-as-a-Service(RaaS)assaults,which enable even individuals with minimal technical knowledge to conduct ransomware *** study provides a new approach for RaaS attack detection which uses an ensemble of deep learning *** this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is *** the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are ***,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested *** proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%*** empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual *** expanding the field of cybersecurity strategy,this research highlights the significance of combined deep learning models in strengthening intrusion detection systems against sophisticated cyber threats.

关键词： Cloud encryption RaaS ensemble threat detection deep learning cybersecurity

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