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Mechanism of Thermally Radiative Prandtl Nanofluids and Double-Diffusive Convection in Tapered Channel on Peristaltic Flow with Viscous Dissipation and Induced Magnetic Field

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1501-1520页

作者： Yasir Khan Safia Akram maria athar Khalid Saeed Alia Razia A.Alameer Department of Mathematics University of Hafr Al-BatinHafr Al-Batin31991Saudi Arabia MCS National University of Sciences and TechnologyIslamabadPakistan SEECS National University of Sciences and TechnologyIslamabadPakistan College of Aeronautical Engineering National University of Sciences and TechnologyIslamabadPakistan

The application of mathematical modeling to biological fluids is of utmost importance, as it has diverse applicationsin medicine. The peristaltic mechanism plays a crucial role in understanding numerous biological flows. In thispaper, we present a theoretical investigation of the double diffusion convection in the peristaltic transport of aPrandtl nanofluid through an asymmetric tapered channel under the combined action of thermal radiation andan induced magnetic field. The equations for the current flow scenario are developed, incorporating relevantassumptions, and considering the effect of viscous dissipation. The impact of thermal radiation and doublediffusion on public health is of particular interest. For instance, infrared radiation techniques have been used totreat various skin-related diseases and can also be employed as a measure of thermotherapy for some bones toenhance blood circulation, with radiation increasing blood flow by approximately 80%. To solve the governingequations, we employ a numerical method with the aid of symbolic software such as Mathematica and *** velocity, magnetic force function, pressure rise, temperature, solute (species) concentration, and nanoparticlevolume fraction profiles are analytically derived and graphically displayed. The results outcomes are compared withthe findings of limiting situations for verification.

关键词： Double diffusion convection thermal radiation induced magnetic field peristaltic flow tapered asymmetric channel viscous dissipation Prandtl nanofluid

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Influence of polymers on drag and heat transfer of nanofluid past stretching surface: A molecular approach

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Journal of Central South University 2022年第12期29卷 3912-3924页

作者： ADEEL Ahmad maria athar YASIR Khan COMSATS University Islamabad Islamabad 46000Pakistan National University of Modern Languages Islamabad 46000Pakistan Department of Mathematics University of Hafr Al BatinHafr Al Batin 31991Saudi Arabia

This article studies the influence of polymers on drag reduction and heat transfer enhancement of a nanofluid past a uniformly heated permeable vertically stretching surface. Our prime focus is on analyzing the possible effects of polymer inclusion in the nanofluid on drag coefficient, Nusselt number and Sherwood number. Dispersion model is considered to study the behavior of fluid flow and heat transfer in the presence of nanoparticles. Molecular approach is opted to explore polymer addition in the base fluid. An extra stress arises in the momentum equation as an outcome of polymer stretching. The governing boundary layer equations are solved numerically. Dependence of physical quantities of engineering interest on different flow parameters is studied. Reduction in drag coefficient, Nusselt number and Sherwood number is noticed because of polymer additives.

关键词： polymers nanofluid stretching concentration drag coefficient relaxation time heat flux

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Towards implementation of alloy-specific thermo-fluid modelling for laser powder-bed fusion of Mg alloys

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Journal of Magnesium and Alloys 2024年第6期12卷 2327-2344页

作者： Mohammad Hoseini-athar Mikael Ersson Peter Hedström Department of Material Science and Engineering KTH Royal Institute of TechnologyStockholmSE-10044 Sweden

Multi-physics thermo-fluid modeling has been extensively used as an approach to understand melt pool dynamics and defect formation as well as optimizing the process-related parameters of laser powder-bed fusion(L-PBF).However,its capabilities for being implemented as a reliable tool for material design,where minor changes in material-related parameters must be accurately captured,is still in *** the present research,first,a thermo-fluid computational fluid dynamics(CFD)model is developed and validated against experimental *** the predicted material properties of the pure Mg and commercial ZK60 and WE43 Mg alloys,parametric studies are done attempting to elucidate how the difference in some of the material properties,i.e.,saturated vapor pressure,viscosity,and solidification range,can influence the melt pool *** is found that a higher saturated vapor pressure,associated with the ZK60 alloy,leads to a deeper unstable keyhole,increasing the keyhole-induced porosity and evaporation mass *** viscosity and wider solidification range can increase the non-uniformity of temperature and velocity distribution on the keyhole walls,resulting in increased keyhole instability and formation of ***,the WE43 alloy showed the best behavior in terms of defect formation and evaporation mass loss,providing theoretical support to the extensive use of this alloy in *** summary,this study suggests an approach to investigate the effect of materials-related parameters on L-PBF melting and solidification,which can be extremely helpful for future design of new alloys suitable for L-PBF.

关键词： Mg alloys Laser powder-bed fusion(L-PBF) Melt pool dynamics Computational fluid dynamics Fluid flow

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Computational and bioinformatics tools for understanding disease mechanisms

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BIOCELL 2024年第6期48卷 935-944页

作者： MOHD athar ANU MANHAS NISARG RANA AHMAD IRFAN Physics Department University of CagliariCittadella UniversitariaMonserrato(CA)09042Italy Department of Chemistry School of Energy TechnologyPandit Deendayal Energy UniversityGandhinagar382426India Department of Chemistry College of ScienceKing Khalid UniversityAbha61413Saudi Arabia

Computational methods have signiﬁcantly transformed biomedical research,offering a comprehensive exploration of disease mechanisms and molecular protein *** article reviews a spectrum of computational tools and network analysis databases that play a crucial role in identifying potential interactions and signaling networks contributing to the onset of disease *** utilization of protein/gene interaction and genetic variation databases,coupled with pathway analysis can facilitate the identiﬁcation of potential drug *** bridging the gap between molecular-level information and disease understanding,this review contributes insights into the impactful utilization of computational methods,paving the way for targeted interventions and therapeutic advancements in biomedical research.

关键词： Interaction database Disease mechanisms Protein function Network analysis Bioinformatics Genetic variations Protein-protein interactions Signaling pathways

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Exploring the molecular landscape of NNK-induced transformation:A comprehensive genome-wide CRISPR/Cas9 screening

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Genes & Diseases 2024年第4期11卷 42-44页

作者： Trang Dinh Mira Rahm Zhenghe Wang Christopher McFarland athar Khalil Department of Genetics and Genome Sciences Case WesternReserve UniversityClevelandOH44106USA

Lung cancer is the leading cause of cancer-related deaths worldwide,with an estimated 1.8 million deaths in 2020 alone.1 While several risk factors are associated with lung cancer,smoking remains the most significant environmental cause of the disease.1 One of the most potent carcinogens in tobacco smoke is 4-(methylnitrosoamino)-1-(3-pyridyl)-1-butanone(NNK),which is produced from nicotine through a series of metabolic reactions.

关键词： CRISPR/Cas9 NNK lung

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Survey of Indoor Localization Based on Deep Learning

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Computers, Materials & Continua 2024年第5期79卷 3261-3298页

作者： Khaldon Azzam Kordi Mardeni Roslee Mohamad Yusoff Alias Abdulraqeb Alhammadi athar Waseem Anwar Faizd Osman Centre for Wireless Technology Faculty of EngineeringMultimedia UniversityCyberjaya63100Malaysia Communication Systems&Networks Research Lab Malaysia-Japan International Institute of TechnologyUniversiti Teknologi MalaysiaKuala Lumpur54100Malaysia Department of Electrical Engineering(DEE) International Islamic UniversityIslamabad44000Pakistan Rohde&Schwarz(M)Sdn Bhd Shah Alam40150Malaysia

This study comprehensively examines the current state of deep learning (DL) usage in indoor *** emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neuralnetworks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this researchexplores the integration of multiple sensor modalities (e.g.,Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expandindoor localization methods, particularly in obstructed environments. It addresses the challenge of precise objectlocalization, introducing a novel hybrid DL approach using received signal information (RSI), Received SignalStrength (RSS), and Channel State Information (CSI) data to enhance accuracy and stability. Moreover, thestudy introduces a device-free indoor localization algorithm, offering a significant advancement with potentialobject or individual tracking applications. It recognizes the increasing importance of indoor positioning forlocation-based services. It anticipates future developments while acknowledging challenges such as multipathinterference, noise, data standardization, and scarcity of labeled data. This research contributes significantly toindoor localization technology, offering adaptability, device independence, and multifaceted DL-based solutionsfor real-world challenges and future advancements. Thus, the proposed work addresses challenges in objectlocalization precision and introduces a novel hybrid deep learning approach, contributing to advancing *** deep learning-based indoor localization techniques have improved accuracy, challenges likedata noise, standardization, and availability of training data persist. However, ongoing developments are expectedto enhance indoor positioning systems to meet real-world demands.

关键词： Deep learning indoor localization wireless-based localization

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Smart Energy Management System Using Machine Learning

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Computers, Materials & Continua 2024年第1期78卷 959-973页

作者： Ali Sheraz Akram Sagheer Abbas Muhammad Adnan Khan Atifa athar Taher M.Ghazal Hussam Al Hamadi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Science COMSATS University IslamabadLahore CampusLahore54000Pakistan School of Information Technology Skyline University CollegeSharjah1797United Arab Emirates Network and Communication Technology Lab Center for Cyber SecurityFaculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia College of Engineering and IT University of DubaiDubaiUnited Arab Emirates

Energy management is an inspiring domain in developing of renewable energy ***,the growth of decentralized energy production is revealing an increased complexity for power grid managers,inferring more quality and reliability to regulate electricity flows and less imbalance between electricity production and *** major objective of an energy management system is to achieve optimum energy procurement and utilization throughout the organization,minimize energy costs without affecting production,and minimize environmental *** energy management is an essential and complex subject because of the excessive consumption in residential buildings,which necessitates energy optimization and increased user *** address the issue of energy management,many researchers have developed various frameworks;while the objective of each framework was to sustain a balance between user comfort and energy consumption,this problem hasn’t been fully solved because of how difficult it is to solve *** inclusive and Intelligent Energy Management System(IEMS)aims to provide overall energy efficiency regarding increased power generation,increase flexibility,increase renewable generation systems,improve energy consumption,reduce carbon dioxide emissions,improve stability,and reduce energy *** Learning(ML)is an emerging approach that may be beneficial to predict energy efficiency in a better way with the assistance of the Internet of Energy(IoE)*** IoE network is playing a vital role in the energy sector for collecting effective data and usage,resulting in smart resource *** this research work,an IEMS is proposed for Smart Cities(SC)using the ML technique to better resolve the energy management *** proposed system minimized the energy consumption with its intelligent nature and provided better outcomes than the previous approaches in terms of 92.11% accuracy,and 7.89% miss-rate.

关键词： Intelligent energy management system smart cities machine learning

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CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

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Computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood Ul Haq Muhammad athar Javed Sethi Najib Ben Aoun Ala Saleh Alluhaidan Sadique Ahmad Zahid farid Department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and Information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan Department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, COMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the COMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence

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Biodegradability of bioplastics in different aquatic environments:A systematic review

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Journal of Environmental Sciences 2024年第8期142卷 169-181页

作者： maria Cristina Lavagnolo Valentina Poli Anna maria Zampini Valentina Grossule Department of Civil Environmental and Architectural Engineering-Laboratory of Environmental EngineeringUniversity of PadovaLungargine Rovetta 8Padova 35100Italy

Bioplastics were first introduced as environmentally friendly materials,with properties similar to those of conventional plastics.A bioplastic is defined as biodegradable if it can be decomposed into carbon dioxide under aerobic degradation,or methane and CO_(2)under anaerobic conditions,inorganic compounds,and new cellular biomass,by the action of naturally occurring *** definition however does not provide any information on the environmental conditions,timescale and extent at which decomposition processes should *** regard to the aquatic environment,recognized standards have been established to assess the ability of plastics to undergo biodegradation;however,these standards fail to provide clear targets to be met to allow labelling of a bioplastic as ***,these standards grant the user an extensive leeway in the choice of process *** these reasons,the comparison of results deriving from different studies is *** authors analysed and discussed the degree of biodegradability of a series of biodegradable bioplastics in aquatic environments(both fresh and salt water)using the results obtained in the laboratory and from on-site testing in the context of different research *** Oxygen Demand(BOD),CO_(2)evolution,surface erosion and weight loss were the main parameters used by researchers to describe the percentage of *** results showed a large variability both in weight loss and BOD,even when evaluating the same type of *** confirms the need for a reference range of values to be established with regard to parameters applied in defining the biodegradability of bioplastics.

关键词： Biodegradation Bioplastic Plastic Natural environment Plastic waste

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Carbon sequestration in a bamboo plantation:a case study in a Mediterranean area

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Journal of Forestry Research 2024年第3期35卷 231-238页

作者： Tommaso Chiti Emanuele Blasi maria Vincenza Chiriaco Department for Innovation in Biological Agro-Food and Forest Systems(DIBAF)University of TusciaVia San C.De Lellis snc01100 ViterboItaly Foundation Euro-Mediterranean Center on Climate Change(CMCC) Division on Climate Change Impacts on AgricultureForests and Ecosystem Services(IAFES)Via Garbini5101100 ViterboItaly

In the Mediterranean region,despite bamboo being an alien species that can seriously alter plant and ani-mal biocoenosis,the area occupied by bamboo plantations continues to increase,especially for the purpose to seques-ter carbon(C).However,the C dynamics in the soil-plant system when bamboo is grown outside its native area are poorly *** we investigated the C mitigation potential of the fast-growing Moso bamboo(Phyllostachys edulis)introduced in Italy for climate-change *** analyzed aboveground(AGB)and belowground(as root/shoot ratio)biomass,litter and soil organic C(SOC)at O-15-and 15-30-cm depths in a 4-year-old bamboo plantation in comparison with the former annual cropland on which the bamboo was *** have an idea of the maximum C stored at an ecosystem level,a natural forest adjacent the two sites was also *** the plantation,C accumulation as AGB was stimulated,with 14.8±3.1 Mg C ha^(-1) stored in 3 years;because thinning was done to remove culms from the first year,the mean sequestration rate was 4.9 Mg C ha^(-1) a^(-1).The sequestration rates were high but comparable to other fast-growing tree species in Italy(e.g.,Pinus nigra).SOC was significantly higher in the bamboo plantation than in the cropland only at the 0-15 cm depth,but SOC stock did not *** 4 years were not enough time for a clear increase in SOC,or the high nutrient uptake by bamboos might have depleted the soil nutrients,thus inhibiting the soil organic matter formation by *** comparison,the natural forest had significantly higher C levels in all the *** C dynamics at an ecosystem level,the bamboo plantation on the former annual cropland led to substantial C removal from the atmosphere(about 12 Mg C ha^(-1) a^(-1)).However,despite the promising C sequestration rates by bamboo,its introduction should be carefully considered due to potential ecological problems caused by this species in overexploited environments such as the Med

关键词： Carbon sequestration Climate change mitigation Mediterranean area Moso bamboo Soil organic carbon

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