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Modelling of debris-flow susceptibility and propagation: a case study from Northwest Himalaya

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Journal of Mountain Science 2024年第1期21卷 200-217页

作者： Hamza DAUD Javed iqbal TANOLI Sardar muhammad ASIF muhammad QASIM muhammad ALI Junaid KHAN Zahid Imran BHATTI Ishtiaq Ahmad Khan JADOON Badong National Observation and Research Station of Geohazards China University of GeosciencesWuhan 430074China Department of Earth Sciences COMSATS University IslamabadAbbottabad Campus 22010Pakistan Department of Earth Sciences Sultan Qaboos UniversityAl-KhoudMascat 123Oman Faculty of Engineering China University of Geosciences(Wuhan)Wuhan 430074China Department of Earth Sciences Abbottabad University of Science and TechnologyHavelian 22500Pakistan

The geological and geographical position of the Northwest Himalayas makes it a vulnerable area for mass movements particularly landslides and debris flows. Mass movements have had a substantial impact on the study area which is extending along Karakorum Highway(KKH) from Besham to Chilas. Intense seismicity, deep gorges, steep terrain and extreme climatic events trigger multiple mountain hazards along the KKH, among which debris flow is recognized as the most destructive geohazard. This study aims to prepare a field-based debris flow inventory map at a regional scale along a 200 km stretch from Besham to Chilas. A total of 117 debris flows were identified in the field, and subsequently, a point-based debris-flow inventory and catchment delineation were performed through Arc GIS analysis. Regional scale debris flow susceptibility and propagation maps were prepared using Weighted Overlay Method(WOM) and Flow-R technique sequentially. Predisposing factors include slope, slope aspect, elevation, Topographic Roughness Index(TRI), Topographic Wetness Index(TWI), stream buffer, distance to faults, lithology rainfall, curvature, and collapsed material layer. The dataset was randomly divided into training data(75%) and validation data(25%). Results were validated through the Receiver Operator Characteristics(ROC) curve. Results show that Area Under the Curve(AUC) using WOM model is 79.2%. Flow-R propagation of debris flow shows that the 13.15%, 22.94%, and 63.91% areas are very high, high, and low susceptible to debris flow respectively. The propagation predicated by Flow-R validates the naturally occurring debris flow propagation as observed in the field surveys. The output of this research will provide valuable input to the decision makers for the site selection, designing of the prevention system, and for the protection of current infrastructure.

关键词： North Pakistan Debris flow Flow-R Propagation Susceptibility mapping Debris-flow inventory Weighted Overlay Method

Enhanced Topic-Aware Summarization Using Statistical Graph Neural Networks

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Computers, Materials & Continua 2024年第8期80卷 3221-3242页

作者： Ayesha Khaliq Salman Afsar Awan Fahad Ahmad muhammad Azam Zia muhammad Zafar iqbal Department of Computer Science University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan School of Computing Faculty of TechnologyUniversity of PortsmouthSouthseaPortsmouthPO12UPUK Department of Mathematics and Statistics University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan

The rapid expansion of online content and big data has precipitated an urgent need for efficient summarization techniques to swiftly comprehend vast textual documents without compromising their original *** approaches in Extractive Text Summarization(ETS)leverage the modeling of inter-sentence relationships,a task of paramount importance in producing coherent *** study introduces an innovative model that integrates Graph Attention Networks(GATs)with Transformer-based Bidirectional Encoder Representa-tions from Transformers(BERT)and Latent Dirichlet Allocation(LDA),further enhanced by Term Frequency-Inverse Document Frequency(TF-IDF)values,to improve sentence selection by capturing comprehensive topical *** approach constructs a graph with nodes representing sentences,words,and topics,thereby elevating the interconnectivity and enabling a more refined understanding of text *** model is stretched to Multi-Document Summarization(MDS)from Single-Document Summarization,offering significant improvements over existing models such as THGS-GMM and Topic-GraphSum,as demonstrated by empirical evaluations on benchmark news datasets like Cable News Network(CNN)/Daily Mail(DM)and *** results consistently demonstrate superior performance,showcasing the model’s robustness in handling complex summarization tasks across single and multi-document *** research not only advances the integration of BERT and LDA within a GATs but also emphasizes our model’s capacity to effectively manage global information and adapt to diverse summarization challenges.

关键词： Summarization graph attention network bidirectional encoder representations from transformers Latent Dirichlet Allocation term frequency-inverse document frequency

Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

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Computers, Materials & Continua 2024年第1期78卷 1207-1225页

作者： Zahid Farooq Khan muhammad Ramzan Mudassar Raza muhammad Attique Khan Khalid iqbal Taerang Kim Jae-Hyuk Cha Department of Computer Science COMSATS University IslamabadWah CampusWah47040Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science COMSATS University IslamabadAttock CampusAttock43600Pakistan Department of Computer Science Hanyang UniversitySeoul04763Korea

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image *** science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous *** to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and *** study makes a small contribution to endoscopic image *** proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and ***,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature *** fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)*** Kvasir-V2 benchmark dataset,and the COMSATS University Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were *** assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private *** approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

关键词： Feature fusion Darknet-53 Xception binary dragonfly algorithm ensemble

Monitoring of Pesticide Residues in Commonly Used Fruits in Hyderabad Region, Pakistan

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American Journal of Analytical Chemistry 2011年第8期2卷 46-52页

作者： Yawar Latif Syed Tufail Hussain Sherazi muhammad iqbal bhanger 不详

A market based survey was carried out to evaluate the level of 26 pesticides in some commonly used fruits in Hyderabad region, Pakistan. Gas chromatography coupled with micro electron capture detector was used to assess the levels of pesticide residues. Gas chromatography-mass spectrometry (GC-MS) was also applied for the confirmation of results. Out of total 131 analyzed samples, 53 (40%) were found contaminated with pesticide residues while only 3 (2%) samples were exceeded the MRLs of some pesticides. Chlorpyrifos and dieldrin were detected in almost all analyzed samples. Residues of chlorpyrifos (1256 μg/kg) and endosulfan sulfate (1236 μg/kg) were found higher in orange and apple samples, respectively. The findings of this study provided important data about contamination of pesticide residue in some fruits sold in Hyderabad, Pakistan, and recommended that monitoring studies should be expanded to other fruits grown in different agro climatic regions, which may serve as basis for future policy about the standards and quality control of pesticides.

关键词： Market Survey Fruit Samples Pesticides Residues GC-μECD

Adsorption and Leaching Potential of Imidacloprid Pesticide through Alluvial Soil

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American Journal of Analytical Chemistry 2012年第8期3卷 604-611页

作者： muhammad Ashraf Bajeer Shafi muhammad Nizamani Syed Tufail Hussain Sherazi muhammad iqbal bhanger National Center of Excellence in Analytical Chemistry University of Sindh Jamshoro Pakistan

This study was aimed to assess the adsorption and leaching potential of imidacloprid pesticide in column and field soil. To visibly understand these actions and factors affecting them, the experiments were carried out under laboratory and field conditions. Adsorption study was divided into kinetic and equilibrium sections. The evaluation of kinetic data was done through pseudo first and second order models. It was found that kinetic adsorption of imidacloprid on soil followed pseudo second order with rate constant value of 4.333 mg/g/h. Langmuir and Freundlich isotherms were used to explain equilibrium adsorption, from these isotherms it was evaluated that Freundlich isotherm was obeyed well with adsorption capacity of 2.190 - 4.573 mol/g. Leaching study was performed in laboratory using column made of poly-vinyl chloride having 30 cm length. Known amount of imidacloprid pesticide was applied to column left for adsorption and then eluted with 500 mL water in five equal portions. These water portions and soil of column which was divided into three sections were analyzed by HPLC. The result revealed that the concentration of imidacloprid was decreased from 0.481 ppm in first portion of water to 0.327 ppm in last portion of water while 0.783 ppm in first section of column soil to 0.038 ppm in last section of column soil. In field the leaching power of imidacloprid was observed up to 60 cm depth, its concentration decreased with soil depth. It was 3.311 ppm in first portion of soil and 0.357 ppm in last portion of soil. The leaching potential of imidacloprid pesticide up to 60 cm soil depth was due to less organic matter, sandy texture, alkaline pH, and low cation exchange capacity.

关键词： Pesticide Adsorption Leaching Imidacloprid Soil

Comparative analysis of SIMILAR to RCD ONE(SRO)family from tetraploid cotton species and their diploid progenitors depict their significance in cotton growth and development

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Journal of Cotton Research 2024年第1期7卷 45-57页

作者： SHABAN muhammad TABASSUM Riaz RANA Iqrar Ahmad ATIF Rana muhammad AZMAT muhammad Abubakkar iqbal Zubair MAJEED Sajid AZHAR muhammad Tehseen Department of Plant Breeding and Genetics University of Agriculture FaisalabadSub-Campus BurewalaVehari 61010Pakistan Department of Chemistry and Biochemistry University of AgricultureFaisalabad 38400Pakistan Centre of Agricultural Biochemistry and Biotechnology University of AgricultureFaisalabad 38400Pakistan Department of Plant Breeding and Genetics University of AgricultureFaisalabad 38400Pakistan Precision Agriculture and Analytics Lab National Centre in Big Data and Cloud ComputingCentre for Advanced Studies in Agriculture and Food SecurityUniversity of Agriculture FaisalabadFaisalabad 38400Pakistan Department of Plant Pathology University of CaliforniaDavisCA 95616USA State Key Laboratory of Cotton Biology Institute of Cotton ResearchChinese Academy of Agricultural SciencesAnyangHenan 455000China Federal Seed Certification and Registration Department Ministry of National Food Security and ResearchIslamabad 44090Pakistan School of Agriculture Sciences Zhengzhou UniversityZhengzhou 450000China

Background SRO(Similar to RCD1)genes family is largely recognized for their importance in the growth,develop-ment,and in responding to environmental ***,genome-wide identification and functional characteri-zation of SRO genes from cotton species have not been reported so *** A total of 36 SRO genes were identified from four cotton *** analysis divided these genes into three groups with distinct *** and chromosomal distribution analysis indicated uneven distribu-tion of GaSRO,GrSRO,GhSRO,and GbSRO genes on A2,D5 genomes,Gh-At,Gh-Dt,Gb-At,and Gb-Dt subgenomes,*** duplication analysis revealed the presence of six duplicated gene pairs among GhSRO *** promoter analysis,several elements responsive to the growth,development and hormones were found in GhSRO genes,implying gene induction during cotton growth and *** miRNAs responsive to plant growth and abiotic stress were predicted to target 12 GhSRO ***-specific expression profiling demonstrated the roles of GhSRO genes in one or more *** addition,specific expression pattern of some GhSRO genes dur-ing ovule development depicted their involvement in these developmental *** The data presented in this report laid a foundation for understanding the classification and functions of SRO genes in cotton.

关键词： Cotton SRO miRNAs Gene duplications Gene expression Ovule development

Evaluation of Pesticide Residues in Human Blood Samples of Agro Professionals and Non-Agro Professionals

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American Journal of Analytical Chemistry 2012年第8期3卷 587-595页

作者： Yawar Latif Syed Tufail Hussain Sherazi muhammad iqbal bhanger Shafi Nizamani National Centre of Excellence in Analytical Chemistry University of Sindh Jamshoro 76080 Pakistan National Centre of Excellence in Analytical Chemistry University of Sindh Jamshoro Pakistan

The aim of the present study was to evaluate the pesticide residues in human blood samples of volunteers related to Hyderabad and Mirpurkhas districts, Pakistan. The volunteers of both districts were divided into four groups on the basis of their exposure period to pesticides i.e. Group A-5 to 9 years, Group B-10 to 14 years, Group C-15 to19 years and Group D-above 20 years. Out of total 188 volunteers, 145 volunteers (77.1%) were agro–professionals and 43 volun- teers (32.9%) were non–agro professionals. Chlorpyrifos, endosulfan, 1, 1, 1-trichloro-2, 2-bis (p-chorophenyl) ethane (p,p'-DDT) and parathion residues were detected in many samples. The predominant pesticides found in blood samples of both district volunteers were chlorpyrifos (with highest mean concentration of 0.37 mg kg-1 in the D group of Mirpurkhas) and endosulfan (with highest mean concentration of 0.30 mg kg-1 in the D group of Hyderabad). The quantity of pesticide residues detected in some blood samples of agro-professionals were found to be at the alarming level.

关键词： Pesticides Exposure to Population Blood Samples

Enhancing Secure Development in Globally Distributed Software Product Lines: A Machine Learning-Powered Framework for Cyber-Resilient Ecosystems

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Computers, Materials & Continua 2024年第6期79卷 5031-5049页

作者： Marya iqbal Yaser Hafeez Nabil Almashfi Amjad Alsirhani Faeiz Alserhani Sadia Ali Mamoona Humayun muhammad Jamal University Institute of Information Technology PMAS-Arid Agriculture UniversityRawalpindiPakistan Department of Software Engineering College of Computer and Information SciencesJouf UniversityAl Jouf72388Saudi Arabia Department of Computer Science College of Computer and Information SciencesJouf UniversityAl Jouf72388Saudi Arabia Department of Computer Engineering&Networks College of Computer and Information SciencesJouf UniversityAl Jouf72388Saudi Arabia Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakaAl Jouf72388Saudi Arabia Department of Mathematics Pir Mehr Ali Shah Arid Agriculture UniversityRawalpindiPakistan

Embracing software product lines(SPLs)is pivotal in the dynamic landscape of contemporary software ***,the flexibility and global distribution inherent in modern systems pose significant challenges to managing SPL variability,underscoring the critical importance of robust cybersecurity *** paper advocates for leveraging machine learning(ML)to address variability management issues and fortify the security of *** the context of the broader special issue theme on innovative cybersecurity approaches,our proposed ML-based framework offers an interdisciplinary perspective,blending insights from computing,social sciences,and ***,it employs ML for demand analysis,dynamic feature extraction,and enhanced feature selection in distributed settings,contributing to cyber-resilient *** experiments demonstrate the framework’s superiority,emphasizing its potential to boost productivity and security in *** digital threats evolve,this research catalyzes interdisciplinary collaborations,aligning with the special issue’s goal of breaking down academic barriers to strengthen digital ecosystems against sophisticated attacks while upholding ethics,privacy,and human values.

关键词： Machine Learning variability management cybersecurity digital ecosystems cyber-resilience

MicroRNAs modulation in lung cancer: exploring dual mechanisms and clinical prospects

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BIOCELL 2024年第3期48卷 403-413页

作者： SHAHID HUSSAIN HABIB BOKHARI XINGXING FAN SHAUKAT iqbal MALIK SUNDAS IJAZ muhammad ADNAN SHEREEN AIMAN FATIMA Department of Biotechnology Kohsar University MurreeMurreePakistan Macao University of Science and Technology State Key Laboratory of Quality Research in Chinese Medicines TaipaMacao Department of Bioinformatics and Biosciences Capital University of Science and TechnologyIslamabadPakistan Department of Microbiology Kohsar University MurreeMurreePakistan

The global incidence of lung cancer is marked by a considerably elevated mortality ***(miRNAs)exert pivotal inﬂuence in the intricate orchestration of gene regulation,and their dysregulation can precipitate dire consequences,notably *** this context,miRNAs encapsulated in exosomes manifest a diversiﬁed impact on the landscape of lung cancer,wherein their actions may either foster angiogenesis,cell proliferation,and metastasis,or counteract these *** comprehensive review article discerns potential targets for the prospective development of therapeutic agents tailored for lung ***-suppressive miRNAs,such as miR-204,miR-192,miR-30a,miR-34a,miR-34b,miR-203,and miR-212,exhibit heightened expression and demonstrate the capacity to inhibit cellular proliferation and ***,the deleterious effects of tumor-promoting miRNAs like miR-21,miR-106a,miR-155,miR-205,and miR-210 can be attenuated through the application of their respective *** miRNAs selectively target various oncogenes,including NUAK Family Kinase 1(NUAK1),Snail Family Transcriptional Repressor 1(Snai1),Astrocyte elevated gene-1(AEG-1),Vimentin,Proliferation and apoptosis adaptor protein 15(PEA-15/PED),Hypoxia-inducible factor 1-alpha(HIF1),as well as tumor suppressor genes such as phosphatase and tensin homolog(PTEN),Suppressor of cytokine signaling 1(SOCS1),Tumor protein P53 binding protein 1(TP53BP1),and PH Domain and Leucine Rich Repeat Protein Phosphatase 2(PHLP22).This investigative approach proves invaluable in elucidating the speciﬁc miRNAs implicated in the deregulation of crucial genes pivotal to the pathogenesis of cancer.

关键词： miRNAs Oncogenes Tumor suppressive genes Lung cancer therapy