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TaABI19 positively regulates grain development in wheat

Journal of Integrative Agriculture 2023年第1期22卷 41-51页

作者： LIU Yun-chuan WANG Xiao-lu HAO Chen-yang irshad ahsan LI Tian LIU Hong-xia HOU Jian ZHANG Xue-yong National Key Facility for Crop Gene Resources and Genetic Improvement Key Laboratory of Biology and Genetic Improvement of Triticeae CropsMinistry of Agriculture/Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijing 100081P.R.China State Key Laboratory of Plant Physiology and Biochemistry College of Biological SciencesChina Agricultural UniversityBeijing 100193P.R.China Institute of Cotton Research Chinese Academy of Agricultural SciencesAnyang 455000P.R.China National Key Facility for Crop Gene Resources and Genetic Improvement/National Center of Space Mutagenesis for Crop Improvement Institute of Crop SciencesChinese Academy of Agricultural SciencesBeijing 100081P.R.China

Starch is the most important component in the endosperm, and its synthesis is regulated by multiple transcription factors(TFs) in cereals. However, whether the functions of these TFs are conserved among cereals remains unclear. In this study,we cloned a B3 family TF in wheat, named TaABI19, based on its orthologous sequence in maize(Zea mays L.). Alignment of the DNA and protein sequences showed that ABI19 is conserved in maize and wheat(Triticum aestivum L.). We found that TaABI19 is highly expressed in young spikes and developing grains, and encodes a nucleus-localized transcriptional activator in wheat. The taabi19-b1 null mutants obtained by EMS exhibited a down-regulation of starch synthesis, shorter grain length and lower thousand-grain weight(TGW). Furthermore, we proved that TaABI19 could bind to the promoters of TaPBF homologous genes and enhance their expression. Haplotype association showed that TaABI19-B1 is significantly associated with TGW. We found that Hap2 and Hap3 were favored and had undergone positive selection in China’s wheat breeding programs. Less than 50% of the modern cultivars convey the favored haplotypes, indicating that TaABI19 still can be considered as a target locus for marker-assisted selection breeding to increase TGW in China.

关键词： common wheat transcription factor haplotype thousand grain weight

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Ionotropic receptors mediate olfactory learning and memory in Drosophila

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Insect Science 2024年第4期31卷 1249-1269页

作者： Md Zeeshan Ali Anushree Aarif ahsan Mohammad Shamsul Ola Rizwanul Haque Jawaid ahsan Department of Biotechnology Central University of South BiharGayaBiharIndia Department of Radiation Oncology University of MichiganAnn ArborMichiganUSA Department of Biochemistry College of ScienceKing Saud UniversityRiyadhSaudi Arabia

Phenylacetaldehyde(PAH),an aromatic compound,is present in a diverse range of fruits including overripe bananas and prickly pear cactus,the two major host fruits for Drosophila *** acts as a potent ligand for the ionotropic receptor 84a(IR84a)in the adult fruit fly and it is detected by the IR84a/IR8a heterotetrameric *** role in the male courtship behavior through IR84a as an environmental aphrodisiac is of additional *** ***,two distinct kinds of olfactory receptors,that is,odorant receptors(ORs)and ionotropic receptors(IRs),perceive the odorant *** display unique structural,molecular,and functional characteristics in addition to having different evolutionary ***,olfactory cues detected by the ORs such as ethyl acetate,1-butanol,isoamyl acetate,1-octanol,4-methylcyclohexanol,*** as aliphatic esters and alcohols have been employed in olfactory classical conditioning using fruit *** underlines the participation of OR-activated olfactory pathways in learning and memory *** study elucidates that likewise ethyl acetate(EA)(an OR-responsive odorant),PAH(an IR-responsive aromatic compound)too can form learning and memory when associated with an appetitive gustatory *** association of PAH with sucrose(PAH/SUC)led to learning and formation of the long-term memory(LTM).Additionally,the Orco^(1),Ir84a^(MI00501),and Ir8a^(1)mutant flies were used to confirm the exclusive participation of the IR84a/IR8a complex in PAH/SUC olfactory associative *** results highlight the involvement of IRs via an IR-activated pathway in facilitating robust olfactory behavior.

关键词： appetitive conditioning Drosophila melanogaster ethyl acetate ionotropic receptors learning and memory phenylacetaldehyde

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Evaluation of Various Mango Varieties against the Infection Dynamics of Powdery Mildew (<i>Oidium mangiferae</i>Bert.)

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American Journal of Plant Sciences 2014年第15期5卷 2372-2377页

作者： Syed Atif Hasan Naqvi Rashida Perveen Syed Amir Manzoor Hafiz Muhammad Imran Umar Muhammad Tayyab Iqbal Fatima Liaquat Taha Majid ahsan irshad Department of Forestry FAST Bahauddin Zakariya University Multan Pakistan Department of Plant Breeding & Genetics FAST Bahauddin Zakariya University Multan Pakistan Department of Plant Pathology FAST Bahauddin Zakariya University Multan Pakistan Department of Soil Science FAST Bahauddin Zakariya University Multan Pakistan

Mango (Mangifera indica L: Anacardiaceae) is regarded as the most liked fruit in tropical and sub-tropical regions of the world. Powdery mildew of mango caused by Oidium mangiferae Bert. is one of the major plant pathological constraints in growing healthy mango orchards. The apparent symptoms of the disease occurred on young tissues of all parts of flowers, leaves and fruits. Severe blossom infection could result in complete damage to fruit;flower failed to open and drop off from the inflorescence. The inflorescence revealed a pattern of disease from tip to downward and showed itself by the emergence of wefts of white mycelium on the affected parts. Twenty-five mango varieties i.e. Langra, Dusehri, Ratole No.12, Fajri, Sindhri, Chaunsa Samar Bahisht, Anwar ratole, Neelam, Yakta, Tota Pari, Sensation, Saroli, Malda, Ghulab e Khas, Chaunsa Black, Chaunsa white, Anmol, Almas, Shan e Ali, Shan e Mustafa, Mahmood Khan, Armughan, Zafaran, Malda Late and Early Gold were evaluated through the observation of symptoms on young inflorescence to determine the disease incidence, disease severity index and average yield of fruit. The study was carried out in a randomized compete block design with twenty-five treatments and three replications. The mango varieties presented different performance in relation to powdery mildew incidence and could be categorized into eight groups. Maximum disease incidence was observed (33.33%, 26.66% and 26.66%, 26.66%) on Dusehri, Chaunsa Samar Bahisht, Malda and Ratole No.12 respectively and minimum disease incidence was (3.66% and 3.66%) noted on Almas and Sensation. These two varieties showed to be tolerant against the disease. It might be concluded that the presence or absence of symptoms caused by the powdery mildew had no such effect on the fruit yield of the mango cultivars.

关键词： Powdery Mildew Oidium mangiferae Bert. Infection Varieties RCBD

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Deep Learning-Based ECG Classification for Arterial Fibrillation Detection

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Computers, Materials & Continua 2024年第6期79卷 4805-4824页

作者： Muhammad Sohail irshad Tehreem Masood Arfan Jaffar Muhammad Rashid Sheeraz Akram Abeer Aljohani Faculty of Computer Science&Information Technology The Superior UniversityLahore54000Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54000Pakistan Department of Computer Science National University of TechnologyIslamabad45000Pakistan Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of Computer Science Applied CollegeTaibah UniversityMedina42353Saudi Arabia

The application of deep learning techniques in the medical field,specifically for Atrial Fibrillation(AFib)detection through Electrocardiogram(ECG)signals,has witnessed significant *** and timely diagnosis increases the patient’s chances of ***,issues like overfitting and inconsistent accuracy across datasets remain *** a quest to address these challenges,a study presents two prominent deep learning architectures,ResNet-50 and DenseNet-121,to evaluate their effectiveness in AFib *** aim was to create a robust detection mechanism that consistently performs *** such as loss,accuracy,precision,sensitivity,and Area Under the Curve(AUC)were utilized for *** findings revealed that ResNet-50 surpassed DenseNet-121 in all evaluated *** demonstrated lower loss rate 0.0315 and 0.0305 superior accuracy of 98.77%and 98.88%,precision of 98.78%and 98.89%and sensitivity of 98.76%and 98.86%for training and validation,hinting at its advanced capability for AFib *** insights offer a substantial contribution to the existing literature on deep learning applications for AFib detection from ECG *** comparative performance data assists future researchers in selecting suitable deep-learning architectures for AFib ***,the outcomes of this study are anticipated to stimulate the development of more advanced and efficient ECG-based AFib detection methodologies,for more accurate and early detection of AFib,thereby fostering improved patient care and outcomes.

关键词： Convolution neural network atrial fibrillation area under curve ECG false positive rate deep learning classification

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Robust design of sliding mode control for airship trajectory tracking with uncertainty and disturbance estimation

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Journal of Systems Engineering and Electronics 2024年第1期35卷 242-258页

作者： WASIM Muhammad ALI ahsan CHOUDHRY Mohammad Ahmad SHAIKH Inam Ul Hasan SALEEM Faisal Department of Aeronautics and Astronautics Engineering Institute of Space TechnologyIslamabad 44000Pakistan Department of Electrical Engineering University of Engineering and TechnologyTaxila 47080Pakistan Department of Measurements and Control Systems Silesian University of TechnologyGliwice 44-101Poland The Joint Doctoral School Silesian University of TechnologyGliwice 44-100Poland

The robotic airship can provide a promising aerostatic platform for many potential *** applications require a precise autonomous trajectory tracking control for *** has a nonlinear and uncertain *** is prone to wind disturbances that offer a challenge for a trajectory tracking control *** paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed *** uses extended Kalman filter(EKF)for uncertainty and disturbance *** estimated parameters are used by sliding mode controller(SMC)for ultimate control of airship trajectory *** comprehensive algorithm,EKF based SMC(ESMC),is used as a robust solution to track airship *** proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model *** stability and convergence of the proposed method are investigated using the Lyapunov stability *** simulation results show that the proposed method efficiently tracks the desired *** method solves the stability,convergence,and chattering problem of SMC under model uncertainties and wind disturbances.

关键词： airship chattering extended Kalman filter(EKF) model uncertainties estimation sliding mode controller(SMC)

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Compressed Natural Gas (CNG) as a fuel and the associated risks: A quantitative analysis in the scenario of a developing country

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JOURNAL OF SAFETY SCIENCE AND RESILIENCE 2024年第3期5卷 306-316页

作者： Ali, Yousaf Younus, ahsan Khan, Amin Ullah Alrefai, Ahmed H. Fahad Bin Sultan Univ Coll Business & Management POB 15700 Tabuk 71454 Saudi Arabia Ghulam Ishaq Khan GIK Inst Engn Sci & Technol Sch Management Sci Topi Swabi Pakistan Univ Macerata Dept Econ & Law Macerata Italy Fahad Bin Sultan Univ Coll Business & Management Tabuk Saudi Arabia

Excessive dependence on fossil fuels has precipitated various challenges, including Greenhouse Gas (GHG) emissions, health hazards, and the depletion of natural resources. Such perils underscore the importance of conducting requisite risk assessments for alternative fuel sources like Compressed Natural Gas (CNG) to ensure their safe utilization. This study undertakes a quantitative risk assessment encompassing diverse facets of the CNG sector holistically, aiming to pinpoint, analyze, and appraise risks, thus empowering policymakers to devise targeted mitigation strategies. To achieve this goal, the collected data undergoes analysis via an integrated approach combining the Fuzzy Analytic Hierarchy Process (F-AHP) and Fuzzy Technique of Order Preference by Similarity to Ideal Solution (F-TOPSIS). The study's findings reveal a heightened risk of explosion within the CNG sector owing to its highly combustible nature. Additionally, it computes an overall risk index of 0.266 for the CNG sector in a developing nation like Pakistan, indicating a relatively lower risk level compared to other fuel sources. Policymakers are thus advised to undertake requisite measures concerning infrastructure, customer safety, and environmental and economic stability to accrue both immediate and long-term benefits. The application of hybrid techniques for the risk assessment of the CNG sector in the case of a developing country marks the novelty of this study and a study of the first of its kind.

关键词： Risk Safety CNG industry Fuzzy Pakistan FUZZY AHP SUPPLY CHAIN MANAGEMENT SYSTEM

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Sleep Posture Classification Using RGB and Thermal Cameras Based on Deep Learning Model

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1729-1755页

作者： Awais Khan Chomyong Kim Jung-Yeon Kim ahsan Aziz Yunyoung Nam Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea ICT Convergence Research Center Soonchunhyang UniversityAsan31538Korea Emotional and Intelligent Child Care Convergence Research Center Soonchunhyang UniversityAsan31538Korea

Sleep posture surveillance is crucial for patient comfort,yet current systems face difficulties in providing compre-hensive studies due to the obstruction caused by *** posture assessment remains challenging because of the complex nature of the human body and variations in sleep ***,this study introduces an innovative method utilizing RGB and thermal cameras for comprehensive posture classification,thereby enhancing the analysis of body position and *** method begins by capturing a dataset of sleep postures in the form of videos using RGB and thermal cameras,which depict six commonly adopted postures:supine,left log,right log,prone head,prone left,and prone *** study involves 10 participants under two conditions:with and without ***,the database is normalized into a video *** subsequent step entails training a fine-tuned,pretrained Visual Geometry Group(VGG16)and ResNet50 *** the third phase,the extracted features are utilized for *** fourth step of the proposed approach employs a serial fusion technique based on the normal distribution to merge the vectors derived from both the RGB and thermal ***,the fused vectors are passed to machine learning classifiers for final *** dataset,which includes human sleep postures used in this study’s experiments,achieved a 96.7%accuracy rate using the Quadratic Support Vector Machine(QSVM)without the ***,the Linear SVM,when utilized with a blanket,attained an accuracy of 96%.When normal distribution serial fusion was applied to the blanket features,it resulted in a remarkable average accuracy of 99%.

关键词： Human sleep posture VGG16 deep learning ResNet50 fusion machine learning

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Current and further trajectories in designing functional materials for solid oxide electrochemical cells:A review of other reviews

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Journal of Energy Chemistry 2024年第7期94卷 302-331页

作者： Stanislav Baratov Elena Filonova Anastasiya Ivanova Muhammad Bilal Hanif Muneeb irshad Muhammad Zubair Khan Martin Motola Sajid Rauf Dmitry Medvedev Hydrogen Energy Laboratory Ural Federal University620002 EkaterinburgRussia Institute of Natural Sciences and Mathematics Ural Federal University620002 EkaterinburgRussia Department of Inorganic Chemistry Faculty of Natural SciencesComenius University BratislavaIlkovicova 6Mlynska Dolina84215 BratislavaSlovakia State Key Laboratory for Mechanical Behavior of Materials School of Materials Science and EngineeringXi'an Jiaotong UniversityXi'an 710049ShaanxiChina Department of Physics University of Engineering and TechnologyLahore 54890Pakistan Pak-Austria Fachhochschule:Institute of Applied Sciences and Technology Mang Haripur 22621Khyber PakhtunkhwaPakistan College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518000GuangdongChina Laboratory of Electrochemical Devices Based on Solid Oxide Proton Electrolytes Institute of High Temperature Electrochemistry620066 EkaterinburgRussia

Complex oxides are an important class of materials with enormous potential for electrochemical *** on their composition and structure,such complex oxides can exhibit either a single conductivity(oxygen-ionic or protonic,or n-type,or p-type electronic)or a combination thereof gener-ating distinct dual-conducting or even triple-conducting *** properties enable their use as diverse functional materials for solid oxide fuel cells,solid oxide electrolysis cells,permeable membranes,and gas *** literature review shows that the field of solid oxide materials and related electro-chemical cells has a significant level of research engagement,with over 8,000 publications published since *** manual analysis of such a large volume of material is ***,by examining the review articles,it is possible to identify key patterns,recent achievements,prospects,and remaining *** perform such an analysis,the present article provides,for the first time,a comprehensive summary of previous review publications that have been published since 2020,with a special focus on solid oxide materials and electrochemical ***,this study provides an important reference for researchers specializing in the fields of solid state ionics,high-temperature electrochemistry,and energyconversiontechnologies.

关键词： SOFCs SOECs PCFCS Electrochemistry Energy conversion Hydrogen energy,Carbon neutrality

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Advances in Zika virus vaccines and therapeutics:A systematic review

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Asian Pacific Journal of Tropical Medicine 2024年第3期17卷 97-109页

作者： Shiza Malik Khalid Muhammad Omar ahsan Muhammad Tahir Khan Ranjit Sah Yasir Waheed Bridging Health Foundation Rawalpindi 46000Pakistan Department of Biology College of SciencesUAE University15551Al AinUnited Arab Emirates Department of Medicine Foundation University Medical CollegeFoundation University IslamabadIslamabad 44000Pakistan INTI International University Persiaran Perdana BBN Putra Nilai71800 NilaiNegeri SembilanMalaysia Institute of Molecular Biology and Biotechnology the University of LahoreKM Defence RoadLahore 58810Pakistan Zhongjing Research and Industrialization Institute of Chinese Medicine Zhongguancun Scientific ParkNanyang 473006China Department of Microbiology Tribhuvan University Teaching HospitalInstitute of MedicineKathmandu 44600Nepal Department of Microbiology Dr.D.Y.Patil Medical CollegeHospital and Research CentreDr.D.Y.Patil VidyapeethPune 411018MaharashtraIndia Department of Public Health Dentistry Dr.D.Y.Patil Dental College and HospitalDr.D.Y.Patil VidyapeethPune 411018MaharashtraIndia Gilbert and Rose-Marie Chagoury School of Medicine Lebanese American UniversityByblos 1401Lebanon

Zika virus(ZIKV)is the causative agent of a viral infection that causes neurological complications in newborns and adults *** wide transmission route and alarming spread rates are of great concern to the scientific *** trials have been conducted to develop treatment options for ZIKV *** review highlights the latest developments in the fields of vaccinology and pharmaceuticals developments for ZIKV infection.A systematic and comprehensive approach was used to gather relevant and up-to-date data so that inferences could be made about the gaps in therapeutic *** results indicate that several therapeutic interventions are being tested against ZIKV infection,such as DNA vaccines,subunit vaccines,live-attenuated vaccines,virus-vector-based vaccines,inactivated vaccines,virus-like particles,and mRNA-based *** addition,approved anti-ZIKV drugs that can reduce the global burden are *** many vaccine candidates for ZIKV are at different stages of development,none of them have received Food and Drug Authority approval for use up to *** issue of side effects associated with these drugs in vulnerable newborns and pregnant women is a major obstacle in the therapeutic pathway.

关键词： Zika virus Infection Therapeutics Antiviral agents Vaccines Therapies Treatment Novel therapeutic Clinical management

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Outsmarting Android Malware with Cutting-Edge Feature Engineering and Machine Learning Techniques

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Computers, Materials & Continua 2024年第4期79卷 651-673页

作者： ahsan Wajahat Jingsha He Nafei Zhu Tariq Mahmood Tanzila Saba Amjad Rehman Khan Faten S.A.lamri Faculty of Information Technology Beijing University of TechnologyBeijing100124China Artificial Intelligence and Data Analytics(AIDA)Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Information Sciences University of EducationVehari CampusVehari61100Pakistan Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia

The growing usage of Android smartphones has led to a significant rise in incidents of Android malware andprivacy *** escalating security concern necessitates the development of advanced technologies capableof automatically detecting andmitigatingmalicious activities in Android applications(apps).Such technologies arecrucial for safeguarding user data and maintaining the integrity of mobile devices in an increasingly digital *** methods employed to detect sensitive data leaks in Android apps are hampered by two major limitationsthey require substantial computational resources and are prone to a high frequency of false *** meansthat while attempting to identify security breaches,these methods often consume considerable processing powerand mistakenly flag benign activities as malicious,leading to inefficiencies and reduced reliability in *** proposed approach includes a data preprocessing step that removes duplicate samples,managesunbalanced datasets,corrects inconsistencies,and imputes missing values to ensure data *** Minimaxmethod is then used to normalize numerical data,followed by feature vector extraction using the Gain ratio andChi-squared test to identify and extract the most significant characteristics using an appropriate prediction *** study focuses on extracting a subset of attributes best suited for the task and recommending a predictivemodel based on domain expert *** proposed method is evaluated using Drebin and TUANDROMDdatasets containing 15,036 and 4,464 benign and malicious samples,*** empirical result shows thatthe RandomForest(RF)and Support VectorMachine(SVC)classifiers achieved impressive accuracy rates of 98.9%and 98.8%,respectively,in detecting unknown Androidmalware.A sensitivity analysis experiment was also carriedout on all three ML-based classifiers based on MAE,MSE,R2,and sensitivity parameters,resulting in a flawlessperformance for both *** app

关键词： Android malware detection machine learning SVC K-Nearest Neighbors(KNN) RF

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