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Predicting potential invasion risks of Leucaena leucocephala(Lam.)de Wit in the arid area of saudi Arabia

Journal of Arid Land 2024年第7期16卷 983-999页

作者： haq s marifatul Darwish MOHAMMED Waheed MUHAMMAD Kumar MANOJ siddiqui H MANZER Bussmann W RAINER Department of Ethnobotany Institute of BotanyIlia State UniversityTbilisi 0162Georgia The Centre of Excellence on sustainable Land Management(CoE-sLM) Indian Council of Forestry Research and EducationDehradun 248006India Department of Botany and Microbiology College of ScienceKing Saud UniversityRiyadh 11451Saudi Arabia Department of Botany State Museum for Natural HistoryKarlsruhe 76133Germany

The presence of invasive plant species poses a substantial ecological impact,thus comprehensive evaluation of their potential range and risk under the influence of climate change is *** study uses maximum entropy(MaxEnt)modeling to forecast the likelihood of Leucaena leucocephala(Lam.)de Wit invasion in saudi Arabia under present and future climate change *** the MaxEnt modeling,we integrated climatic and soil data to predict habitat suitability for the invasive *** conducted a detailed analysis of the distribution patterns of the species,using climate variables and ecological *** focused on the important influence of temperature seasonality,temperature annual range,and precipitation *** distribution modeling used robust measures of area under the curve(AUC)and receiver-operator characteristic(ROC)curves,to map the invasion extent,which has a high level of accuracy in identifying appropriate *** complex interaction that influenced the invasion of *** was highlighted by the environmental parameters using Jackknife ***,the actual geographic area where *** was found in saudi Arabia was considerably smaller than the theoretical maximum range,suggesting that it had the capacity to expand *** MaxEnt model exhibited excellent prediction accuracy and produced reliable results based on the data from the ROC *** and temperature were the primary factors influencing the potential distribution of ***,an estimated area of 216,342 km^(2)in saudi Arabia was at a high probability of invasion by *** investigated the potential for increased invasion hazards in the future due to climate change scenarios(shared socioeconomic Pathways(ssPs)245 and 585).The analysis of key climatic variables,including temperature seasonality and annual range,along with soil properties such as clay composition and nitrogen content,unveiled their substanti

关键词： area under the curve invasive species invasion risks climate change MaxEnt model

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Deep Learning Based Efficient Crowd Counting system

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Computers, Materials & Continua 2024年第6期79卷 4001-4020页

作者： Waleed Khalid Al-Ghanem Emad Ul haq Qazi Muhammad Hamza Faheem syed shah Amanullah Quadri Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Centre of Excellence in Cybercrime and Digital Forensics Naif Arab University for Security SciencesRiyadh14812Saudi Arabia Center of Excellence for Information Assurance(COEIA) King Saud UniversityRiyadh12372Saudi Arabia

Estimation of crowd count is becoming crucial nowadays,as it can help in security surveillance,crowd monitoring,and management for different *** is challenging to determine the approximate crowd size from an image of the crowd’s *** in this research study,we proposed a multi-headed convolutional neural network architecture-based model for crowd counting,where we divided our proposed model into two main components:(i)the convolutional neural network,which extracts the feature across the whole image that is given to it as an input,and(ii)the multi-headed layers,which make it easier to evaluate density maps to estimate the number of people in the input image and determine their number in the *** employed the available public benchmark crowd-counting datasets UCF CC 50 and shanghaiTech parts A and B for model training and testing to validate the model’s *** analyze the results,we used two metrics Mean Absolute Error(MAE)and Mean square Error(MsE),and compared the results of the proposed systems with the state-of-art models of crowd *** results show the superiority of the proposed system.

关键词： Crowd counting EfficientNet multi-head attention convolutional neural network transfer learning

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Design of an Efficient and Provable secure Key Exchange Protocol for HTTP Cookies

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Computers, Materials & Continua 2024年第7期80卷 263-280页

作者： Waseem Akram Khalid Mahmood Hafiz Burhan ul haq Muhammad Asif shehzad Ashraf Chaudhry Taeshik shon Graduate school of Engineering science and Technology National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Department of Computer science Lahore Garrison UniversityLahore54920Pakistan Department of Computer science and Information Technology College of EngineeringAbu Dhabi UniversityAbu Dhabi69911United Arab Emirates Department of software Engineering Faculty of Engineering and ArchitectureNisantasi UniversityIstanbul34398Turkey Department of Cybersecurity Ajou UniversitySuwon16499Republic of Korea

Cookies are considered a fundamental means of web application services for authenticating various Hypertext Transfer Protocol(HTTP)requests andmaintains the states of clients’information over the *** cookies are exploited to carry client patterns observed by a *** client patterns facilitate the particular client’s future visit to the corresponding ***,security and privacy are the primary concerns owing to the value of information over public channels and the storage of client information on the *** protocols have been introduced that maintain HTTP cookies,but many of those fail to achieve the required security,or require a lot of resource *** this article,we have introduced a lightweight Elliptic Curve Cryptographic(ECC)based protocol for authenticating client and server transactions to maintain the privacy and security of HTTP *** proposed protocol uses a secret key embedded within a *** proposed protocol ismore efficient and lightweight than related protocols because of its reduced computation,storage,and communication ***,the analysis presented in this paper confirms that proposed protocol resists various known attacks.

关键词： Cookies authentication protocol impersonation attack ECC

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Impact of numerous larval diets on the biology of pink bollworm Pectinophora gossypiella(saunders)(Lepidoptera:Gelechiidae)under laboratory conditions

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Journal of Cotton Research 2024年第1期7卷 69-78页

作者： AKHTAR shamim ARIF Muhammad Jalal GOGI Muhammad Dildar haq Imran-ul Department of Entomology University of Agriculture FaisalabadPunjabPakistan Ayub Agricultural Research Institute(Entomological Research Institute) FaisalabadPunjabPakistan Department of Plant Pathology University of AgricultureFaisalabadPunjabPakistan

Background Pink bollworm,Pectinophora gossypiella(saunders)(Lepidoptera:Gelechiidae)has become a poten-tial pest of cotton by causing substantial yield losses around the world including *** in view the facts like limited research investigations,unavailability,and high cost of artificial diet’s constituents and their premixes,the present research investigations on the dietary aspect of *** were *** larvae of *** were reared on different diets that were prepared using indigenous *** standard/laboratory diet com-prised of wheat germ meal 34.5 g,casein 30.0 g,agar–agar 20.0 g,sucrose 10.0 g,brewer’s yeast 5.0 g,α-cellulose 1.0 g,potassium-sorbate1.5 g,niplagin 0.5 g,decavitamin 0.01 g,choline-chloride 0.06 g,maize-oil 3.30 g,honey 2.0 g,and water 730.0 *** to cotton bolls and wheat germ meal were okra seed sprouts,okra fruit,cottonseed meal,and okra seed meals,which were included in the study to introduce an efficient and economic mass-rearing *** The larval development completed in 19.68d±0.05 d with a weight of 20.18mg±0.20 mg at the fourth instar fed on the cottonseed meal-based diet instead of wheat germ meal based *** the same diet,84.00%±4.00%,17.24 mg±0.03 mg,and 7.76d±0.06 d were recorded as pupae formation,pupal weight,and pupal duration,*** emergence,76.00%±1.00%was recorded from pupae collected from larvae raised on cottonseed meal-based *** male and female moths lived for 40.25d±0.10 d,and 44.34d±0.11 d,*** deposited 21.28±0.04 eggs per day with the viability of 65.78%±0.14%.The larval mortal-ity at the fourth instar was 37.20%±1.36%and malformed pupation of 12.00%±1.41%was *** of wheat germ meal with that of local meals(cottonseed and okra seed)in the standard laboratory diet has saved 463.80 to 467.10 PKR with 1.62 to 1.63 cost economic returns,*** This research is of novel nature as it provides a concis

关键词： Artificial diets Cottonseed meal Laboratory rearing Pectinophora gossypiella Wheat germ meal

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Deep Learning-Based Mask Identification system Using ResNet Transfer Learning Architecture

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Computer systems science & Engineering 2024年第2期48卷 341-362页

作者： Arpit Jain Nageswara Rao Moparthi A.swathi Yogesh Kumar sharma Nitin Mittal Ahmed Alhussen Zamil s.Alzamil MohdAnul haq Department of Computer science and Engineering KoneruLakshmaiah Education FoundationVaddeswaram522302India Department of Computer science and Engineering Sreyas Institute of Engineering and TechnologyHyderabad500068India University Centre for Research and Development Chandigarh UniversityMohali140413India Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Recently,the coronavirus disease 2019 has shown excellent attention in the global community regarding health and the *** Health Organization(WHO)and many others advised controlling Corona Virus Disease in *** limited treatment resources,medical resources,and unawareness of immunity is an essential horizon to *** all resources,wearing a mask is the primary non-pharmaceutical intervention to stop the spreading of the virus caused by severe Acute Respiratory syndrome Coronavirus 2(sARs-CoV-2)*** countries made masks mandatory to prevent *** such enforcement,automatic and effective face detection systems are *** study presents a face mask identification approach for static photos and real-time movies that distinguishes between images with and without *** contribute to society,we worked on mask detection of an individual to adhere to the rule and provide awareness to the public or *** paper aims to get detection accuracy using transfer learning from Residual Neural Network 50(ResNet-50)architecture and works on detection *** experiment is tested with other popular pre-trained models such as Deep Convolutional Neural Networks(AlexNet),Residual Neural Networks(ResNet),and Visual Geometry Group Networks(VGG-Net)advanced *** proposed system generates an accuracy of 98.4%when modeled using Residual Neural Network 50(ResNet-50).Also,the precision and recall values are proved as better when compared to the existing *** outstanding work also can be used in video surveillance applications.

关键词： Transfer learning depth analysis convolutional neural networks(CNN) COVID-19

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Identification of software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

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Computers, Materials & Continua 2024年第3期78卷 4379-4397页

作者： Qazi Mazhar ul haq Fahim Arif Khursheed Aurangzeb Noor ul Ain Javed Ali Khan saddaf Rubab Muhammad shahid Anwar Department of Computer science and Engineering and International Bachelor’s Program in Informatics Yuan Ze UniversityZhongliTaoyuan320315Taiwan Department of Computer science National University of PakistanRawalpindiPunjab46000Pakistan Department of Computer software Engineering MCSNational University of Sciences and TechnologyIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer science School of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Department of AI and software Gachon UniversitySeongnam-SI13120South Korea

software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty *** are exploring machine learning to predict software bugs,but a more precise and general approach is *** bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning ***,these studies are not generalized and efficient when extended to other ***,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification *** methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a *** National Aeronautics and space Administration(NAsA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were *** reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

关键词： Natural language processing software bug prediction transfer learning ensemble learning feature selection

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Extended Deep Learning Algorithm for Improved Brain Tumor Diagnosis system

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Intelligent Automation & soft Computing 2024年第1期39卷 33-55页

作者： M.Adimoolam K.Maithili N.M.Balamurugan R.Rajkumar s.Leelavathy Raju Kannadasan Mohd Anul haq Ilyas Khan Elsayed M.Tag El Din Arfat Ahmad Khan Department of Computer Engineering Government Polytechnic CollegeSevvapetTiruvallurTamil Nadu602025India Department of Computer science and Engineering KG Reddy College of Engineering and TechnologyHyderabadTelangana500075India Department of Computer science and Engineering Sri Venkateswara College of EngineeringSriperumbudurChennai602117India Department of Computer science and Engineering Annamalai UniversityChidambaramTamil Nadu608002India Department of Computer science and Engineering Aarupadai Veedu Institute of TechnologyVinayaka Mission Research FoundationPaiyanurTamil Nadu603104India Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudur602117India Department of Computer science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical Engineering Department Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand

At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)*** various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhancement,particularly accuracy,sensitivity,false positive and false negative,to improve the brain tumor prediction system ***,this work proposed an Extended Deep Learning Algorithm(EDLA)to measure performance parameters such as accuracy,sensitivity,and false positive and false negative *** addition,these iterated measures were analyzed by comparing the EDLA method with the Convolutional Neural Network(CNN)way further using the sPss tool,and respective graphical illustrations were *** results were that the mean performance measures for the proposed EDLA algorithm were calculated,and those measured were accuracy(97.665%),sensitivity(97.939%),false positive(3.012%),and false negative(3.182%)for ten *** in the case of the CNN,the algorithm means accuracy gained was 94.287%,mean sensitivity 95.612%,mean false positive 5.328%,and mean false negative 4.756%.These results show that the proposed EDLA method has outperformed existing algorithms,including CNN,and ensures symmetrically improved *** EDLA algorithm introduces novelty concerning its performance and particular activation *** proposed method will be utilized effectively in brain tumor detection in a precise and accurate *** algorithm would apply to brain tumor diagnosis and be involved in various medical diagnoses *** the quantity of dataset records is enormous,then themethod’s computation power has to be updated.

关键词： Brain tumor extended deep learning algorithm convolution neural network tumor detection deep learning

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Long-term outcomes of titanium-nitride-oxide coated stents and drug-eluting stents in acute coronary syndrome:A systematic review and meta-analysis

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World Journal of Cardiology 2024年第5期16卷 293-305页

作者： Muhammad Ahmed Ali Fahim Afia salman Hira Anas Khan syed Muhammad Hasan Muskan FatimaBhojani sarah Aslam Amna Zia Ul haq Vishal Reddy Bejugam Beena Muntaha Nasir Wajiha Gul Abdul Moeed Abdelrahman s Abdalla Muhammad Majid Muhammad sohaib Asghar Md Al Hasibuzzaman Department of Internal Medicine Dow University of Health SciencesKarachi 74200Pakistan Department of Internal Medicine North Central Bronx HospitalBronxNY 10467United States Department of Urology Center for Academic MedicineStanford University School of MedicinePalo AltoCA 33872United States Department of Cardiovascular Imaging Cleveland ClinicClevelandOH 44195United States Division of Nephrology and Hypertension Mayo Clinic RochesterRochesterMN 55905United States Institute of Nutrition and Food science University of DhakaDhaka 1000Bangladesh

BACKGROUND In severe cases of coronary artery disease,percutaneous coronary intervention provide promising *** stent used could be a drug-eluting stent(DEs)or a titanium-nitride-oxide coated stent(TiNOs).AIM To compare the 5-year effectiveness and safety of the two stent *** The following systematic review and meta-analysis was conducted in accordance with the preferred reporting items for systematic reviews and meta-analysis guidelines,and PubMed/MEDLINE,scopus,and Cochrane Central were searched from inception till August *** outcomes were major adverse cardiac events(MACE),cardiac death,myocardial infarction(MI),cardiac death or MI,and ischemia-driven total lesion revascularization(ID-TLR).REsULTs Four randomized controlled trials(RCT),which analyzed a sum total of 3045 patients with acute coronary syndrome(ACs)after a median follow-up time of 5 years were *** statistically insignificant,an increase in the ID-TLR was observed in patients receiving TiNOss vs *** addition,MI,cardiac death and MI,and definite stent thrombosis(DsT)were significantly decreased in the TiNOs *** analysis revealed no significant results with meta-regression presenting non-sT elevated MI(NsTEMI)as a statistically significant covariate in the outcome of *** TiNOs was found to be superior to DEs in terms of MI,cardiac death or MI,and DsT outcomes,however,the effect of the two stent types on ID-TLR and MACE was not significant.A greater number of studies are required to establish an accurate comparison of patient outcomes in TiNOs and DEs.

关键词： stents Drug-eluting Major adverse cardiac events All-cause death Meta-analysis

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Partial Fusion (F) Gene Analysis of Newcastle Disease Virus Detected in Pakistan during 2021-2022

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Journal of Biosciences and Medicines 2024年第5期12卷 256-275页

作者： Muhammad Danish Mehmood Huma Anwar Ul-haq Rauf Khalid Yasir Amin Muhammad Usman Ghani Muhammad Ismail Rabia Habib Fareeha Arshed Abdul Rasheed shaukat Institute of Molecular Biology & Biotechnology University of Lahore Lahore Pakistan Research & Development Division Ottoman Pharma Lahore Pakistan Quality Assurance Department Ottoman Pharma Lahore Pakistan Veterinary Research and Disease Investigation Center Abbottabad Pakistan Quality Control Department Ottoman Pharma Immuno Lahore Pakistan Production Department Ottoman Pharma Lahore Pakistan Poultry Production Department Sabir&#8217s Poultry Pvt. Ltd. Sabroso Pakistan

Newcastle disease (ND) virus is a leading threat to commercial and domestic poultry in Pakistan. The virus infects and constitutes irreversible impairment to the nervous system, damages the respiratory system, and marks severe gastrointestinal lesions leading to heavy mortality in short-living birds and substantial losses in layers and breeders. The continuous emergence and evolution of the virus made it inclined to evade the humoral response and indirectly the circumvention of artificial active immunization. Newcastle disease is caused by the orthoavula genus of the paramyxoviridae family and has shown high genetic diversity even in their genotypes while information regarding enzootic trends of the virus is scanty in Pakistan. A total of 40 tracheal samples of NDV were collected from different commercial broiler farms and 11 isolates of NDV were identified. In the current study, we determined the genetic diversity of the Newcastle disease virus based on the partial sequencing of the fusion protein gene available in the NCBI database. Genetic analysis showed that seven isolates belonged to class I genotype VII and four belonged to class II genotype II. Interestingly, two isolates had epidemiological connections with vaccine-like class II genotype II. Our findings, concerning the recent outbreaks of class I genotype VII and class II genotype II of NDV in vaccinated commercial flocks, suggest possible potential partial mutations in the fusion protein gene. Genetic diversity and formation of the new cleavage site in an important neutralizing protein of wild strain are linked with the potency of artificial active immunization and a major cause of vaccine failure.

关键词： Newcastle Disease Virus Haemagglutination Inhibition Polymerase Chain Reaction Phylogenetic Tree Mutation Analysis

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storylines of family medicine Ⅴ:ways of thinking—honing the therapeutic self

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Family Medicine and Community Health 2024年第S3期12卷 43-51页

作者： William B Ventres Leslie A stone Johanna F shapiro Cynthia haq Jéssica R B Leao Donald E Nease Jr Liz Grant stewart W Mercer John C M Gillies Pablo González Blasco Maria Auxiliadora C De Benedetto Graziela Moreto Marcelo R Levites Jennifer E DeVoe William R Phillips Jane M Uygur Thomas R Egnew Colette s stanley Family and Preventive Medicine University of Arkansas for Medical Sciences College of MedicineLittle RockArkansasUSA Family Medicine University of California Irvine School of MedicineIrvineCaliforniaUSA Faculty of Medicine University of Sao PauloSao PauloBrazil Family Medicine University of Colorado Anschutz Medical Campus School of MedicineAuroraColoradoUSA Usher Institute Edinburgh Medical SchoolUniversity of EdinburghEdinburghUK sOBRAMFA-Medical Education and Humanism Sao PauloBrazil Family Medicine Oregon Health&Science University School of MedicinePortlandOregonUSA Family Medicine University of Washington School of MedicineSeattleWashingtonUSA General Practice Royal College of Surgeons in IrelandDublinIreland General Internal Medicine Geriatrics&Palliative MedicineTulane University School of MedicineNew OrleansLouisianaUSA

storylines of Family Medicine is a 12-part series of thematically linked essays with accompanying illustrations that explore the many dimensions of family medicine,as interpreted by individual family physicians and medical educators in the UsA and elsewhere around the ***‘Ⅴ:ways of thinking—honing the therapeutic self’,authors present the following sections:‘Reflective practice in action’,‘The doctor as drug—Balint groups’,‘Cultivating compassion’,‘Towards a humanistic approach to doctoring’,‘Intimacy in family medicine’,‘The many faces of suffering’,‘Transcending suffering’and‘The power of listening to stories.’May readers feel a deeper sense of their own therapeutic agency by reflecting on these essays.

关键词： illustration dimensions suffering

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