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Two MADS-box proteins,AGL9 and AGL15,recruit the FIS-PRC2 complex to trigger the phase transition from endosperm proliferation to embryo development in Arabidopsis

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Molecular Plant 2024年第7期17卷 1110-1128页

作者： Shen Zhang Devasantosh Mohanty adnan Muzaffar Min Ni Department of Plant and Microbial Biology University of Minnesota at Twin CitiesSaint PaulMinnesota MN 55108United States of AmericaUSA

Spatiotemporal regulation of gene expression by polycomb repressive complex 2(PRc2)is critical for animal and plant *** Arabidopsis fertilization independent seed(FIS)-PRC2 complex functions specifically during plant reproduction from gametogenesis to seed *** a double fertilization event,triploid endosperm proliferates early,followed by the growth of a diploid embryo,which replaces the endosperm in Arabidopsis and many *** genes critical for endosperm proliferation such as IKkU2 and MINI3 are activated after *** we report that two MADS-box AGAMOUS-LIKE(AGL)proteins associate with the key endosperm proliferation loci and recruit the FIS-PRC2 repressive complex at 4-5 days after pollination(DAP).Interestingly,AGL9 and AGL15 only accumulate toward the end of endosperm proliferation at 4-5 DAP and promote the deposition of H3K27me3 marks at key endosperm proliferation *** of AGL9 and AGL15 or overexpression of AGL9 or AGL15 significantly influence endosperm proliferation and ***-wide analysis with cleavage Under Targets and tagmentation(CUT&Tag)sequencing and RNA sequencing revealed the landscape of endosperm H3K27me3 marks and gene expression profiles in Col-0 and agl9 ***&Tag qPCR also demonstrated the occupancy of the two MADS-box proteins and FIS-PRC2 on a few representative target *** studies suggest that MADS-box proteins could potentially recruit PRc2 to regulate many other developmental processes in plants or even in fungi and animals.

关键词： AGL9 AGL15 embryo endosperm IKU2 MEDEA MINI3

Knowledge and Practices among Nurses Regarding Patients’ Care Following Cardiac Catheterization at a Tertiary Care Hospital in Karachi, Pakistan

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Open Journal of Nursing 2019年第8期9卷 809-834页

作者： adnan yaqoob Rubina Barolia Ahmed Noor Afshan Nazar Aga Khan University School of Nursing and Midwifery The Indus Hospital Karachi Pakistan

Aims: The purpose of this study was to assess the knowledge and practices among nurses regarding patient care, following cardiac catheterization, at a tertiary care hospital in Karachi, Pakistan. Background: Cardiovascular diseases (CVDs) are the major cause of morbidity and mortality, globally. Nurses are the largest body of health care professionals who attempt to reduce the burden of cardiovascular diseases. Design: This study employed a descriptive analytical cross-sectional study design to answer the research questions. Methodology: The data were collected from 70 participants using two instruments. Knowledge was assessed through a 50-multiple-choice questions-based questionnaire, whereas, to assess the practices, an observational checklist was utilized which comprised of 20 components. Findings: The majority of the nurses, 54.3%, had adequate, 40% nurses had inadequate, and only 5.7% nurses had excellent knowledge scores. Moreover, 87.1% nurses were observed as carrying out unsatisfactory practices, whereas, only 12.9% nurses were found carrying out satisfactory practices. Conclusion: Since variation in the practices was observed in each of the department, therefore, there is a need for further research, to assess nurses’ attitudes through a qualitative approach and to develop and implement a standard post-cardiac catheterization care protocol.

关键词： Nurses’ Knowledge Nurses’ Practices Cardiac Catheterization Post PCI Nursing Care

Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： Muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy Muhammad adnan Khan Muhammad Hasnain Azam Khan Muhammad adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

Secure android IoT mobile and collaborative machine learning for controlling the management of enterprise

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Journal of Control and Decision 2024年第1期11卷 15-25页

作者： Hamza Mohammed Ridha Al-Khafaji Refed adnan Jaleel Biomedical Engineering Department Al-Mustaqbal University CollegeHillahIraq Information and Communication Engineering Department Al-Nahrain UniversityBaghdadIraq

There is a need for increased security measures because of wide variety of android Internet of Thing(IoT)mobile devices that can communicate with each other via networks for controlling the management of *** Curve Deffie Hellman(ECDH)and Rivest Shamir Adleman(RSA)are used to secure data in android IoT phones in efficient *** mobile can store a lot of data,including sensitive *** data saved on mobile has become a critical *** android IoT,Collaborative Machine Learning describes a method for collaboratively mining data,which makes it easier to manage and lowers cost of *** increase security in IoT phones,suggested system uses ECDH,RSA,and CML algorithms,which have been considered novelty of this *** and ECDH are computed using time of decryption,encryption,and key *** show ECDH beats other alternatives like ***,all users of the network have been tested.

关键词： IoT ECDH RSA CML android encryption decryption

Stochastic Computing Convolutional Neural Network Architecture Reinvented for Highly Efficient Artificial Intelligence Workload on Field-Programmable Gate Array

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Research 2024年第2期2024卷 55-79页

作者： Yang Yang Lee Zaini Abdul Halim Mohd Nadhir Ab Wahab Tarik adnan Almohamad School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal 14300 Penang Malaysia School of Computer Sciences Universiti Sains MalaysiaGelugor11800 PenangMalaysia Electrical-Electronics Engineering Department Faculty of EngineeringKarabuk University78050 KarabukTurkiye

Stochastic computing(SC)has a substantial amount of study on application-specific integrated circuit(ASIC)design for artificial intelligence(AI)edge computing,especially the convolutional neural network(CNN)***,SC has little to no optimization on field-programmable gate array(FPGA).Scaling up the ASIC logic without FPGA-oriented designs is inefficient,while aggregating thousands of bitstreams is still challenging in the conventional *** research has reinvented several FPGA-efficient 8-bit SC CNN computing architectures,i.e.,SC multiplexer multiply-accumulate,multiply-accumulate function generator,and binary rectified linear unit,and successfully scaled and implemented a fully parallel CNN model on Kintex7 *** proposed SC hardware only compromises 0.14%accuracy compared to binary computing on the handwriting Modified National Institute of Standards and Technology classification task and achieved at least 99.72%energy saving per image feedforward and 31?more data throughput than modern *** to SC,early decision termination pushed the performance baseline exponentially with minimum accuracy loss,making SC CNN extremely lucrative for AI edge computing but limited to classification *** SC's inherent noise heavily penalizes CNN regression performance,rendering SC unsuitable for regression tasks.

关键词： hardware Highly rendering

Detailed analysis of the relativistic configuration of Bardeen anisotropic spheres in modified f(G)gravity

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Communications in Theoretical Physics 2024年第6期76卷 45-56页

作者： adnan Malik Ayesha Almas Tayyaba Naz Rubab Manzoor M Z Bhatti School of Mathematical Sciences Zhejiang Normal UniversityJinhuaZhejiangChina Department of Mathematics University of Management and TechnologySialkot CampusLahorePakistan National University of Computer and Emerging Sciences Lahore CampusPakistan Department of Mathematics University of Management and TechnologyJohar Town CampusLahore 54782Pakistan Department of Mathematics University of the PunjabQuaid-i-Azam CampusLahore-54590Pakistan

The aim of this work is to investigate anisotropic compact objects within the framework of f(G)modified theory of *** our present work,we utilize Krori-Barua metrics,i.e.,λ(r)=Xr^(2)+Y andβ(r)=Zr^(2).We use some matching conditions of spherically symmetric spacetime with Bardeen's model as an exterior ***,we establish some expressions of energy density and pressure components to analyze the stellar configuration of Bardeen compact stars by assuming viable f(G)*** examine the energy conditions for different stellar structures to verify the viability of our considered ***,we also investigate some other physical features,such as equilibrium condition,equation of state parameters,adiabatic index,stability analysis,mass function,surface redshift,and compactness factor,*** is worthwhile to mention here for the current study that our stellar structure in the background of Bardeen's model is more viable and stable.

关键词： Bardeen compact stars f(G)modified gravity Krori-Barua potential

Adaptive Segmentation for Unconstrained Iris Recognition

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Computers, Materials & Continua 2024年第2期78卷 1591-1609页

作者： Mustafa AlRifaee Sally Almanasra adnan Hnaif Ahmad Althunibat Mohammad Abdallah Thamer Alrawashdeh Faculty of Architecture and Design Al-Zaytoonah University of JordanAmman11733Jordan Faculty of Computer Studies Arab Open UniversityRiyadh11681Saudi Arabia Faculty of Science and Information Technology Al-Zaytoonah University of JordanAmman11733Jordan

In standard iris recognition systems,a cooperative imaging framework is employed that includes a light source with a near-infrared wavelength to reveal iris texture,look-and-stare constraints,and a close distance requirement to the capture *** these conditions are relaxed,the system’s performance significantly deteriorates due to segmentation and feature extraction ***,a novel segmentation algorithm is proposed to correctly detect the pupil and limbus boundaries of iris images captured in unconstrained ***,the algorithm scans the whole iris image in the Hue Saturation Value(HSV)color space for local maxima to detect the sclera *** image quality is then assessed by computing global features in red,green and blue(RGB)space,as noisy images have heterogeneous *** iris images are accordingly classified into seven categories based on their global RGB *** the classification process,the images are filtered,and adaptive thresholding is applied to enhance the global contrast and detect the outer iris ***,to characterize the pupil area,the algorithm scans the cropped outer ring region for local minima values to identify the darkest area in the iris *** experimental results show that our method outperforms existing segmentation techniques using the UBIRIS.v1 and v2 databases and achieved a segmentation accuracy of 99.32 on UBIRIS.v1 and an error rate of 1.59 on UBIRIS.v2.

关键词： Image recognition color segmentation image processing localization

Research on Interpolation Method for Missing Electricity Consumption Data

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Computers, Materials & Continua 2024年第2期78卷 2575-2591页

作者： Junde Chen Jiajia Yuan Weirong Chen adnan Zeb Md Suzauddola Yaser A.Nanehkaran Department of Electronic Commerce Xiangtan UniversityXiangtan411105China School of Information Engineering Yancheng Teachers UniversityYancheng224000China Department of Information and Electrical Engineering Ningde Normal UniversityNingde352100China College of Engineering Southern University of Science and TechnologyShenzhen518005China School of Informatics Xiamen UniversityXiamen361005China

Missing value is one of the main factors that cause dirty *** high-quality data,there will be no reliable analysis results and precise ***,the data warehouse needs to integrate high-quality data *** the power system,the electricity consumption data of some large users cannot be normally collected resulting in missing data,which affects the calculation of power supply and eventually leads to a large error in the daily power line loss *** the problem of missing electricity consumption data,this study proposes a group method of data handling(GMDH)based data interpolation method in distribution power networks and applies it in the analysis of actually collected electricity ***,the dependent and independent variables are defined from the original data,and the upper and lower limits of missing values are determined according to prior knowledge or existing data *** missing data are randomly interpolated within the upper and lower ***,the GMDH network is established to obtain the optimal complexity model,which is used to predict the missing data to replace the last imputed electricity consumption *** last,this process is implemented iteratively until the missing values do not *** a relatively small noise level(α=0.25),the proposed approach achieves a maximum error of no more than 0.605%.Experimental findings demonstrate the efficacy and feasibility of the proposed approach,which realizes the transformation from incomplete data to complete ***,this proposed data interpolation approach provides a strong basis for the electricity theft diagnosis and metering fault analysis of electricity enterprises.

关键词： Data interpolation GMDH electricity consumption data distribution system

Cervical Cancer Prediction Empowered with Federated Machine Learning

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Computers, Materials & Continua 2024年第4期79卷 963-981页

作者： Muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy M.A.Khan Khan Muhammad adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi20009UAE Department of Computing Skyline University CollegeSharjah999041UAE Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam13120Korea

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of MedicalThings (IoMT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

关键词： Cervical cancer federated machine learning neurons blockchain technology