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Expansion of human umbilical cord derived mesenchymal stem cells in regenerative medicine

World Journal of Stem Cells 2024年第4期16卷 410-433页

作者： Shafiqa Naeem Rajput Bushra Kiran Naeem Anwar ali Asmat Salim irfan Khan Dr.Panjwani Center for Molecular Medicine and Drug Research International Center for Chemical and Biological SciencesUniversity of KarachiKarachi 75270SindhPakistan Surgical Unit 4 Dr.Ruth KM Pfau Civil HospitalKarachi 74400Pakistan Department of Physiology University of KarachiKarachi 75270Pakistan Center for Regenerative Medicine and Stem Cells Research and Department of Ophthalmology and Visual SciencesThe Aga Khan UniversityKarachi 74800SindhPakistan

BACKGROUND Stem cells are undifferentiated cells that possess the potential for self-renewal with the capacity to differentiate into multiple lineages.In humans,their limited numbers pose a challenge in fulfilling the necessary demands for the regeneration and repair of damaged tissues or organs.Studies suggested that mesenchymal stem cells(MSCs),necessary for repair and regeneration via transplantation,require doses ranging from 10 to 400 million cells.Furthermore,the limited expansion of MSCs restricts their therapeutic application.AIM To optimize a novel protocol to achieve qualitative and quantitative expansion of MSCs to reach the targeted number of cells for cellular transplantation and minimize the limitations in stem cell therapy protocols.METHODS Human umbilical cord(hUC)tissue derived MSCs were obtained and re-cultured.These cultured cells were subjected to the following evaluation pro-cedures:Immunophenotyping,immunocytochemical staining,trilineage differentiation,population doubling time and number,gene expression markers for proliferation,cell cycle progression,senescence-associatedβ-galactosidase assay,human telomerase reverse transcriptase(hTERT)expression,mycoplasma,cytomegalovirus and endotoxin detection.RESULTS Analysis of pluripotent gene markers Oct4,Sox2,and Nanog in recultured hUC-MSC revealed no significant differences.The immunophenotypic markers CD90,CD73,CD105,CD44,vimentin,CD29,Stro-1,and Lin28 were positively expressed by these recultured expanded MSCs,and were found negative for CD34,CD11b,CD19,CD45,and HLA-DR.The recultured hUC-MSC population continued to expand through passage 15.Proliferative gene expression of Pax6,BMP2,and TGFb1 showed no significant variation between recultured hUC-MSC groups.Nevertheless,a significant increase(Pality control assessments co

关键词： Human umbilical cord Mesenchymal stem cells Expansion Cell proliferation In vitro expansion Senescence

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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 operations.This study provides a new approach for RaaS attack detection which uses an ensemble of deep learning models.For this purpose,the network intrusion detection dataset“UNSWNB15”from the Intelligent Security Group of the University of New South Wales,Australia is analyzed.In the initial phase,the rectified linear unit-,scaled exponential linear unit-,and exponential linear unit-based three separate Multi-Layer Perceptron(MLP)models are developed.Later,using the combined predictive power of these three MLPs,the RansoDetect Fusion ensemble model is introduced in the suggested methodology.The proposed ensemble technique outperforms previous studieswith impressive performance metrics results,including 98.79%accuracy and recall,98.85%precision,and 98.80%F1-score.The empirical results of this study validate the ensemble model’s ability to improve cybersecurity defenses by showing that it outperforms individual MLPmodels.In 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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Mechanistic insights toward identification and interaction of plant parasitic nematodes:A review

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Soil Ecology Letters 2024年第1期6卷 11-27页

作者： Bisma Jan ali Haider shah Mudasir Ahmad Bhat Arif Tasleem Jan Ishfaq Ahmad Wani ali Asghar shah Section of Microbiology Baba Ghulam Shah Badshah UniversityRajouriJ&K185234India Department of Biotechnology Baba Ghulam Shah Badshah University RajouriJ&K185234India Department of Botany Baba Ghulam Shah Badshah University RajouriJ&K185234India Department of Zoology School of Biosciences and BiotechnologyBaba Ghulam Shah Badshah University RajouriJ&K185234India

Nematode identification serves as an important param-eter to study their behaviour,importance and pathogenic-ity.Application of classical morphometric based identifica-tion methods prove to be lacking due to insufficient knowledge on morphological variations among closely related taxa.Molecular approaches such as DNA and protein-based information,microarray,probing,sequence-based methods and others have been used to supplement morphology-based methods for nematode identification.Ascarosides and certain protein-based nematode-associated molecular patterns(NAMPs),can be perceived by the host plants,and can initiate a signalling cascade.This review primarily emphasizes on an updated account of different classical and modern tools used for the identification of nematodes.Besides we also summa-rize the mechanism of some important signalling pathways which are involved in the different plant nematode interactions.Nematodes constitute most diverse and least studied group of soil inhabiting invertebrates.They are ecologically and physiologically important,however,wide range of nematodes show harmful impact on the individuals that live within their vicinity.Plant parasitic nematodes(PPNs)are transparent,pseudocoelomate,free living or parasitic microorganisms.PPNs lack morphometric identification methods due to insufficient knowl-edge on morphological variations among closely related taxa.As such,molecular approaches such as DNA and protein-based information,microarray,probing,sequence-based methods and others have been used to supplement morphology-based methods for their identification.To invade the defense response of different plant species,parasitic nematodes have evolved different molecular strategies.Ascarosides and certain protein-based nematode-associated molecular patterns(NAMPs),can be perceived by the host plants,and can initiate a signaling cascade.To overcome the host confrontation and develop certain nematode feeding sites,some members can inject effectors into the cells of susceptible hosts to reprogram the

关键词： nematode identification plant nematode interaction DNA fingerprinting nematode-associated molecular patterns signaling path-ways

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Contrast Normalization Strategies in Brain Tumor Imaging:From Preprocessing to Classification

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1539-1562页

作者： Samar M.Alqhtani Toufique A.Soomro Faisal Bin Ubaid Ahmed ali Muhammad irfan Abdullah A.Asiri Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Electronic Engineering The University of LarkanoLarkanaSindh75660Pakistan Computer Science Department Sukkur IBA UniversitySukkurSindh65200Pakistan Eletrical Engineering Department Sukkur IBA UniversitySukkurSindh65200Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia

Cancer-related to the nervous system and brain tumors is a leading cause of mortality in various countries.Magnetic resonance imaging(MRI)and computed tomography(CT)are utilized to capture brain images.MRI plays a crucial role in the diagnosis of brain tumors and the examination of other brain disorders.Typically,manual assessment of MRI images by radiologists or experts is performed to identify brain tumors and abnormalities in the early stages for timely intervention.However,early diagnosis of brain tumors is intricate,necessitating the use of computerized methods.This research introduces an innovative approach for the automated segmentation of brain tumors and a framework for classifying different regions of brain tumors.The proposed methods consist of a pipeline with several stages:preprocessing of brain images with noise removal based on Wiener Filtering,enhancing the brain using Principal Component Analysis(PCA)to obtain well-enhanced images,and then segmenting the region of interest using the Fuzzy C-Means(FCM)clustering technique in the third step.The final step involves classification using the Support Vector Machine(SVM)classifier.The classifier is applied to various types of brain tumors,such as meningioma and pituitary tumors,utilizing the Contrast-Enhanced Magnetic Resonance Imaging(CE-MRI)database.The proposed method demonstrates significantly improved contrast and validates the effectiveness of the classification framework,achieving an average sensitivity of 0.974,specificity of 0.976,accuracy of 0.979,and a Dice Score(DSC)of 0.957.Additionally,this method exhibits a shorter processing time of 0.44 s compared to existing approaches.The performance of this method emphasizes its significance when compared to state-of-the-art methods in terms of sensitivity,specificity,accuracy,and DSC.To enhance the method further in the future,it is feasible to standardize the approach by incorporating a set of classifiers to increase the robustness of the brain classification method.

关键词： Brain tumor magnetic resonance imaging principal component analysis fuzzy c-clustering support vector machine

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An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

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Computers, Materials & Continua 2024年第5期79卷 2565-2583页

作者： Syed Ayaz ali shah Aamir shahzad Musaed Alhussein Chuan Meng Goh Khursheed Aurangzeb Tong Boon Tang Muhammad Awais Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusAbbottabad22060Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Faculty of Information and Communication Technology University Tunku Abdul RehmanKampar CampusKampar31900Malaysia Centre for Intelligent Signal and Imaging Research University Teknologi PETRONASBandar Seri IskandarPerak32610Malaysia School of Computing Sciences University of East AngliaNorwichNR47TJUK

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

关键词： Line detector vessel detection localization mathematical morphology image processing

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Bond-Slip Behavior of Steel Bar and Recycled Steel Fibre-Reinforced Concrete

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Journal of Renewable Materials 2024年第1期12卷 167-186页

作者： Ismail shah Jing Li Nauman Khan Hamad R.Almujibah Muhammad Mudassar Rehman ali Raza Yun Peng School of Architecture and Civil Engineering Yunnan Agricultural UniversityKunming650000China Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu610041China Yunnan International Joint R&D Center of Smart Agriculture and Water Security Yunnan Agricultural UniversityKunming650201China School of Water Conservancy Yunnan Agricultural UniversityKunming650201China School of Civil Engineering Guizhou UniversityGuiyang550025China Department of Civil Engineering College of EngineeringTaif UniversityP.O.Box 11099Taif City21974Saudi Arabia School of Civil Engineering Zhengzhou UniversityZhengzhou450001China

Recycled steel fiber reinforced concrete is an innovative construction material that offers exceptional mechanical properties and durability.It is considered a sustainable material due to its low carbon footprint and environmental friendly characteristics.This study examines the key influencing factors that affect the behavior of this material,such as the steel fiber volume ratio,recycled aggregate replacement rate,concrete strength grade,anchorage length,and stirrup constraint.The study investigates the bond failure morphology,bond-slip,and bond strength constitutive relationship of steel fiber recycled concrete.The results show that the addition of steel fibers at 0.5%,1.0%,and 1.5%volume ratios can improve the ultimate bond strength of pull-out specimens by 9.05%,6.94%,and 5.52%,respectively.The replacement rate of recycled aggregate has minimal effect on the typical bond strength of pull-out specimens.However,the ultimate bond strengths of pull-out specimens with concrete strength grades C45 and C60 have improved compared to those with C30 grade.The specimens with longer anchorage lengths exhibit lower ultimate bond strength,with a reduction of 33.19%and 46.37%for anchorage lengths of 5D and 7D,respectively,compared to those without stirrups.Stirrup restraint of 1φ8 and 2φ8 improves the ultimate bond strength by 5.29%and 6.90%,respectively.Steel fibers have a significant effect on the behavior of concrete after it cracks,especially during the stable expansion stage,crack instability expansion stage,and failure stage.

关键词： Recycled coarse aggregates(RCA) steel fiber bonding performance bond-slip environmental challenges

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Genuine entanglement under squeezed generalized amplitude damping channels with memory

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Chinese Physics B 2024年第2期33卷 158-163页

作者： Mazhar ali Department of Electrical Engineering Faculty of EngineeringIslamic University MadinahMadinah 107Saudi Arabia

We study genuine entanglement among three qubits undergoing a noisy process that includes dissipation, squeezing,and decoherence. We obtain a general solution and analyze the asymptotic quantum states. We find that most of these asymptotic states can be genuinely entangled depending upon the parameters of the channel, memory parameter, and the parameters of the initial states. We study Greenberger–Horne–Zeilinger(GHZ) states and W states, mixed with white noise,and determine the conditions for them to be genuinely entangled at infinity. We find that for these mixtures, it is possible to start with a bi-separable state(with a specific mixture of white noise) and end with genuine entangled states. However, the memory parameter μ must be very high. We find that in contrast to the two-qubit case, none of the three-qubit asymptotic states for n → ∞ are genuinely entangled.

关键词： genuine entanglement squeezed thermal baths multipartite states

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Simulation of the deformable lateral boundaries in biaxial test using DEM

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Particuology 2024年第5期88卷 161-175页

作者： ali Momeni Barry Clarke Yong Sheng ali Hassanpour WSP 3 Wellington PlaceLeedsLS1 4APUK Hull University HullHU6 7RXUK School of Civil Engineering University of LeedsLeedsLS2 9JTUK School of Computer Science University of HullHullHU6 7RXUK School of Chemical and Process Engineering University of LeedsLeedsLS2 9JTUK

Applying the discrete element method(DEM)in soil mechanics can provide abundant information at the particle-scale and facilitates illustration of the macro-mechanical behaviour of soils based on the inter-particle mechanisms.The triaxial test is one of the most common laboratory methods to study the macro-mechanical behaviour of particulate materials such as soil.However,many problems in geotechnical design can be assumed and simplified as a plane strain phenomenon.Therefore a biaxial test can be conducted to reproduce the macro-mechanical behaviour of soil,where the sample is enclosed by two horizontal rigid platens and a vertical latex membrane,which is a deformable continuous element and allows the enclosed specimen to deform freely while maintaining confining stress during loading.This paper presents an algorithm to represent physical and mechanical characteristics of latex membrane in the 2D DEM simulation of biaxial test using the PFC 2D code.To investigate the impact of the lateral boundary conditions on the micro-macro mechanical behaviours of soil samples,two sets of DEM biaxial tests are conducted,i.***.with rigid and deformable lateral boundary conditions.The DEM modeling results indicate that the lateral boundary conditions have a significant effect on the micro-scale fabric properties,thickness and inclination of the shear band.The comparison between these two simulations also demonstrates that the lateral boundary conditions play a major role in the peak and post-peak stress-strain behaviours as well as the dilation and critical state behaviours of granular soils.

关键词： Discrete element method Biaxial test Deformable boundaries Shear band Critical state Fabric anisotropy Geometrical stability index

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Sensing the heavy water concentration in an H_(2)O-D_(2)O mixture by solid-solid phononic crystals

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Chinese Physics B 2024年第4期33卷 493-498页

作者： Mohammadreza Rahimi ali Bahrami Optoelectronic and Nanophotonics Research Laboratory(ONRL) Faculty of Electrical EngineeringSahand University of TechnologyTabrizIran

A new method based on phononic crystals is presented to detect the concentration of heavy water(D_(2)O)in an H_(2)O-D_(2)O mixture.Results have been obtained and analyzed in the concentration range of 0%-10%and 90%-100%D_(2)O.A proposed structure of tungsten scatterers in an aluminum host is studied.In order to detect the target material,a cavity region is considered as a sound wave resonator in which the target material with different concentrations of D_(2)O is embedded.By changing the concentration of D_(2)O in the H_(2)O-D_(2)O mixture,the resonance frequency undergoes a frequency shift.Each 1%change in D_(2)O concentration in the H_(2)O-D_(2)O mixture causes a frequency change of about 120 Hz.The finite element method is used as the numerical method to calculate and analyze the natural frequencies and transmission spectra of the proposed sensor.The performance evaluation index shows a high Q factor up to 1475758 and a high sensitivity up to 13075,which are acceptable values for sensing purposes.The other figures of merit related to the detection performance also indicate high-quality performance of the designed sensor.

关键词： phononic crystals sensor H_(2)O-D_(2)O mixture cavity

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Experimental Study on Heat Storage Properties Comparison of Paraffin/Metal Foams Phase Change Material Composites

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Journal of Thermal Science 2024年第2期33卷 469-478页

作者： Waqar AHMED Abid HUSSAIN Hanzla shahID Imran ali Hafiz Muhammad ali Department of Mechanical Engineering University of Engineering and TechnologyTaxila47080Pakistan Department of Mechanical Engineering Institute of Space TechnologyIslamabadPakistan Department of Mechanical Mechatronics and Manufacturing EngineeringUniversity of Engineering and Technology LahoreFaisalabad CampusPunjabPakistan Mechanical Engineering Department King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia

Heat storage properties of phase change materials(PCMs) are essential characteristics that perform a key role in thermal heat energy storage systems.The thermal properties of PCMs can be improved by developing metal foam/PCM composites.The addition of metal foam in PCMs has a significant effect on the thermal characteristics of PCMs.In this paper,the heat storage properties of two different metal foam/PCM composites were experimentally examined.The behavior of paraffin in metal foam(copper and iron-nickel)/paraffin composites concerning pure paraffin at a constant heat flux of 1000 W/m^(2) in three directions simultaneously(x,y,and z) was studied.Paraffin was infiltrated into copper and iron-nickel foams to develop composite materials which resulted in enhancing the thermal conductivity of the paraffin.A comparative analysis is made on the heat storage properties of paraffin in copper and iron-nickel foams/paraffin composites.Inner temperature distribution during the phase transition process is experimentally evaluated.This comparison indicates that temperature uniformity in copper foam/paraffin composite is better than in iron-nickel foam/paraffin composite and pure paraffin at the same heat flux.Experimental results show that at heat flux of 1000 W/m^(2),the heat storage time for copper foam/paraffin composite is 20.63% of that of iron-nickel foam/paraffin composite.

关键词： heat storage capacity paraffin/metal foam composite temperature uniformity heat storage rate phase transition process

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