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Correlations between serum kidney injury molecule-1,cystatin C and immunosuppressants:A cross-sectional study of renal transplant patients in Bahrain

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Journal of Biomedical Research 2024年第3期38卷 269-277页

作者： Kannan Sridharan Shamik Shah Mona Al Hammad fatima ali mohammed Sindhan Veeramuthu Mona Abdulla Taher Mustafa Mohamed Hammad Lamees Jawad Eman Farid Department of Pharmacology and Therapeutics College of Medicine and Medical SciencesArabian Gulf UniversityManamaKingdom of Bahrain Department of Nephrology Salmaniya Medical ComplexManamaKingdom of Bahrain Department of Internal Medicine College of Medicine and Medical SciencesArabian Gulf UniversityManamaKingdom of Bahrain Salmaniya Medical Complex ManamaKingdom of Bahrain Department of Laboratory Medicine Salmaniya Medical ComplexManamaKingdom of Bahrain Department of Microbiology Immunologyand Infectious DiseasesCollege of Medicine and Medical SciencesArabian Gulf UniversityManamaKingdom of Bahrain

Renal transplant patients receive several immunosuppressive drug regimens that are potentially nephrotoxic for *** creatinine is the standard for monitoring kidney function;however,cystatin C(Cys C)and kidney injury molecule-1(KIM-1)have been found to indicate kidney injury earlier than serum creatinine and provide a better reflection of kidney ***,we assessed Cys C and KIM-1 serum levels in renal transplant patients receiving mycophenolate mofetil,tacrolimus,sirolimus,everolimus,or cyclosporine to evaluate kidney *** used both the Chronic Kidney Disease Epidemiology Collaboration(CKD-EPI)2021 equation,which is based on creatinine and combined creatinine with Cys C,and the CKD-EPI 2012 equation,which is based on Cys C alone,to estimate glomerular filtration rate(GFR).Then,we assessed the association between serum KIM-1 and GFR<90 mL per minute per 1.73 *** observed significantly higher serum Cys C levels in patients with the elevated serum creatinine,compared with those with normal serum *** estimated GFRs based on creatinine were significantly higher than those based on the other equations,while a significant positive correlation was observed among all *** KIM-1 levels were negatively correlated with the estimated GFRs by the CKD-EPI Cys C and the combined creatinine with Cys C equations.A serum KIM-1 level above 0.71 ng/mL is likely to indicate GFR<90 mL per minute per 1.73 *** observed a significant correlation between serum creatinine and Cys C in our renal transplant ***,serum KIM-1 may be used to monitor renal function when using potentially nephrotoxic drugs in renal transplants.

关键词： KIM-1 cystatin C mycophenolate mofetil tacrolimus everolimus sirolimus cyclosporine

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Assessment of Breast Cancer Prevention Practices among Women Attending Primary Health Care in Abha City, Aseer Region, Saudi Arabia

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International Journal of Clinical Medicine 2024年第2期15卷 31-54页

作者： Sabah mohammed Asiri Sultan Yahia Alfifii Tagreed Khairan Al-Rashidi Sager Misfer Alqahtani Faiz Abdulrahman Alshafa Fayez Mari Alamri Amal mohammed Asiri fatima mohammed ali Almagadi Thuraya mohammed Asiri Department of Therapeutic Assistance Management General Directorate of Health Affairs Asser Region Abha Saudi Arabia Department of Health Affairs General Directorate of Health Affairs Asser Region Abha Saudi Arabia Department of Kidney King Khaled Hospital Hail Saudi Arabia Department of Nursing Sarat Abida Hospital Aseer Saudi Arabia Department of Radiation Oncology King Faisal Medical City Abha Saudi Arabia Department of Health Affairs KSA MOH Department of Kidney Dialysis Centers General Directorate of Health Affairs Aseer Region Abha Saudi Arabia Department of Operation Ahad Rafidah Hospital General Directorate of Health Affairs in Asseer Region Abha Saudi Arabia South Qunfudah General Hospital Jizan Saudi Arabia Armed Forces Southern Region Hospital Aseer Saudi Arabia

Cancer is a leading cause of death worldwide, with breast cancer being the most common (2.26 million new cases and 685,000 deaths). In Saudi Arabia, breast cancer ranked the first among females in 2014, accounting for 15.9% of all cancers reported among Saudi nationals and 28.7% of all cancers reported among females of all ages. Early detection of breast cancer could decrease the risks, have a better prognosis, and have better outcomes/more successful treatments. Prevalence of breast cancer reached more than 25% of all diagnosed cancer in the kingdom among women. Aim: This study aims to assess the knowledge and performance of women attending primary care centers about breast self-examination and mammogram screening for prevention and early detection of breast cancer in Abha city primary healthcare centers, Kingdom of Saudi Arabia. Research Method: cross sectional design was conducted by using questionnaire, which was distributed to primary care center nurses. The collected data was statistically analyzed using the Statistical Package for Social Sciences, version 25. Results: The study found that participants had poor awareness and knowledge about breast self-examination, risk factors for breast cancer, and trends and practices in early diagnosis of breast cancer. Conclusion and Recommendations: It recommends increasing awareness campaigns and providing educational programs to improve knowledge and practices.

关键词： Assessment Breast Cancer Prevention Practices Women Attending Health Care Centers Abha City

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Experimental and numerical study of effecting core configurations on the static and dynamic behavior of honeycomb plate with aluminum material

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Defence Technology（防务技术） 2024年第9期39卷 177-192页

作者： Nehad Abid Allah Hamza fatima mohammed K.AL-Fatlwe Muna ali Talib Engineering College Al-Qasim Green University51013BabylonIraq Engineering Technical College of Al-Najaf Al-Furat Al-Awsat Technical University(ATU)Najaf54003Iraq

The sandwich panel incorporated a honeycomb core,a widely utilized composite structure recognized as a fundamental classification of composite *** a core resembling a honeycomb,possessing thickness and softness,and is flank by rigid face sheets that sandwich various shapes and *** paper presents an examination of the static and dynamic analysis of lightweight plates made of aluminum honeycomb sandwich *** sandwich plate samples are 300 mm long,and 300 mm wide,the heights of the core have been varied at four values ranging from 10 to 25 *** honeycomb core is manufactured from Aluminum material by using a novel technique namely resistance spot welding(RSW)instead of using adhesive material,which is often used when an industrial flaw is *** optimization based on response surface methodology(RSM)and design of experiment software(DOE)was used to verify the current work.A theoretical examination of the crashworthiness behavior(maximum bending load,maximum deflection)and vibration attributes(natural frequency,damping ratio,transient temporal response)of honeycomb sandwich panels with different design parameters was also carried *** addition,the finite element method-based ANSYS software was used to confirm the theoretical *** findings of the present work showed that the relationship between the natural frequency,core height,and cell size is *** contrast,the relationship between the natural frequency and the thickness of the cell wall is ***,the damping ratio is inversely proportional to the core height and cell size but directly proportional to the thickness of the cell *** study indicates that altering the core height within 10-25 mm leads to a significant increase of 82%in the natural frequency and a notable decrease of 49%in the damping *** findings are based on a specific cell size value of 0.01 m and a cell wall thickness of 0.001 ***,the results indicate

关键词： Honeycomb Load Transient response Free vibration Natural frequency

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Integrated photonic fractional convolution accelerator

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Photonics Research 2024年第8期12卷 1828-1839页

作者： KEVIN ZELAYA mohammed-ali MIRI Department of Physics Queens College of the City University of New YorkQueensNew York 11367USA Physics Program The Graduate Center of the City University of New YorkNew YorkNew York 10016USA

An integrated photonic circuit architecture to perform a modified-convolution operation based on the discrete fractional Fourier transform(DFrFT) is introduced. This is accomplished by utilizing two nonuniformly coupled waveguide lattices with equally spaced eigenmode spectra, the lengths of which are chosen so that the DFrFT and its inverse operations are achieved. A programmable modulator array is interlaced so that the required fractional convolution operation is performed. Numerical simulations demonstrate that the proposed architecture can effectively perform smoothing and edge detection tasks even for noisy input signals, which is further verified by electromagnetic wave simulations. Notably, mild lattice defects do not jeopardize the architecture performance, showing its resilience to manufacturing errors.

关键词： fractional convolution utilizing

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MoBShield:A Novel XML Approach for Securing Mobile Banking

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Computers, Materials & Continua 2024年第5期79卷 2123-2149页

作者： Saeed Seraj ali Safaa Sadiq OmprakashKaiwartya Mohammad Aljaidi Alexandros Konios mohammed ali mohammed Abazeed Department of Computer Science Nottingham Trent UniversityClifton LaneNottinghamNG118NSUK Department of Computer Science Faculty of Information TechnologyZarqa UniversityZarqa13110Jordan Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Mobile banking security has witnessed significant R&D attention from both financial institutions and *** is due to the growing number of mobile baking applications and their reachability and usefulness to ***,these applications are also attractive prey for cybercriminals,who use a variety of malware to steal personal banking *** literature in mobile banking security requiresmany permissions that are not necessary for the application’s intended security *** this context,this paper presents a novel efficient permission identification approach for securing mobile banking(MoBShield)to detect and prevent malware.A permission-based dataset is generated for mobile banking malware detection that consists large number of malicious adware apps and benign apps to use as training *** dataset is generated from 1650 malicious banking apps of the Canadian Institute of Cybersecurity,University of New Brunswick and benign apps from Google Play.A machine learning algorithm is used to determine whether amobile banking application ismalicious based on its permission ***,an eXplainable machine learning(XML)approach is developed to improve trust by explaining the reasoning behind the algorithm’s *** evaluation tests that the approach can effectively and practically identify mobile banking malware with high precision and reduced false ***,the adapted artificial neural networks(ANN),convolutional neural networks(CNN)and XML approaches achieve a higher accuracy of 99.7%and the adapted deep neural networks(DNN)approach achieves 99.6%accuracy in comparison with the state-of-the-art *** promising results position the proposed approach as a potential tool for real-world scenarios,offering a robustmeans of identifying and thwarting malware inmobile-based banking ***,MoBShield has the potential to significantly enhance the security and trustworthiness of

关键词： Security malware detection deep learning convolutional neural networks deep neural networks

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Explicit solutions to the time-fractional generalized dissipative Kawahara equation

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Journal of Ocean Engineering and Science 2024年第4期9卷 348-352页

作者： Marwan Alquran mohammed ali Omar Alshboul Department of Mathematics and Statistics Jordan University of Science and TechnologyIrbid 22110Jordan

In this paper,the generalized dissipative Kawahara equation in the sense of conformable fractional derivative is presented and solved by applying the tanh-coth-expansion and sine-cosine function *** quadratic-case and cubic-case are investigated for the proposed *** solutions are obtained with highlighting to the effect of the presence of the alternative fractional-derivative and the effect of the added dissipation term to the generalized Kawahara *** graphical analysis is presented to support the findings of the ***,we believe that the obtained results in this work will be important and valuable in nonlinear sciences and ocean engineering.

关键词： Time-fractional Kawahara equation Conformable-derivative Tanh-coth-expansion method Sine-cosine function method

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Classification and Comprehension of Software Requirements Using Ensemble Learning

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Computers, Materials & Continua 2024年第8期80卷 2839-2855页

作者： Jalil Abbas Arshad Ahmad Syed Muqsit Shaheed Rubia fatima Sajid Shah Mohammad Elaffendi Gauhar ali School of Computer Science and Technology Anhui UniversityHefei230039China School of Computing Sciences Pak Austria FachhochschuleInstitute of Applied Sciences and TechnologyHaripur22620Pakistan Department of Computer Science and IT University of LahoreLahore55150Pakistan Department of Computer Science Emerson UniversityPunjabMultan60000Pakistan EIAS(Emerging Intelligent Autonomous Systems)Data Science Lab Prince Sultan UniversityRiyad12435Saudi Arabia

The software development process mostly depends on accurately identifying both essential and optional ***,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional *** address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human ***,existing techniques often struggle with complex instructions and large-scale *** our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer *** results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT *** datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse *** findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.

关键词： Ensemble learning machine learning non-functional requirements requirement engineering accuracy sliding window

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Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad ali Zeb Hani Alshahrani mohammed Hamdi Mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information System College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

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Kaoline-based catalyst for a high stability desulfurization of sour heavy naphtha in a three-phase oscillatory baffled reactor

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Particuology 2024年第1期84卷 249-260页

作者： Hassan M.Hmood Saba A.Gheni Safaa M.R.Ahmed Mudheher M.ali Hamid Yonis Saleh mohammed H.mohammed Awad E.mohammed Marwan A.Mahomood Hiba R.mohammed Ahmed A.Hassan Adam Harvey North Refineries Company Ministry of OilIraq Chemical Engineering Department Tikrit UniversityIraq Ministry of Oil Iraq AL-Hawija Technical Institute Northern Technical UniversityMoselIraq School of Engineering Newcastle UniversityUK

To meet the rapidly increasing demand for energy and the dramatic depletion of conventional crude oil,it is imperative to utilize sour *** no coke being produced,oxidative desulfurization(ODS)of naphtha lowers its sulfur content and average molecular *** this article,we outline a method for heavy naphtha non-extractive ODS using a very stable *** technique involves the use of a solid catalyst with oxygen gas as the *** necessitated relatively high mixing intensities;hence a three-phase Oscillatory Baffled Reactor(OBR)was *** catalyst was based on the zeolite ZSM-5,prepared from natural kaolin by a series of delamination and activation steps and impregnated with Fe.A TiO2 nanolayer was applied,using the sol-gel method,to prevent rapid *** reactor performance was evaluated to minimize the sulfur content in the naphtha *** to the protective coating,the sulfur conversion stabilized at 90%.The results of this work establish the use of natural clay-based catalysts in a continuous,three-phase ODS,particularly with regard to proving long-term *** also showed that modest ODS can be achieved using an environmentally friendly oxidant,at mild operating conditions,whilst maintaining stability.

关键词： Natural kaoline Desulfurization Three-phase Oscillatory baffled reactor

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AMachine Learning Approach to Cyberbullying Detection in Arabic Tweets

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Computers, Materials & Continua 2024年第7期80卷 1033-1054页

作者： Dhiaa Musleh Atta Rahman mohammed Abbas Alkherallah Menhal Kamel Al-Bohassan Mustafa mohammed Alawami Hayder ali Alsebaa Jawad ali Alnemer Ghazi Fayez Al-Mutairi May Issa Aldossary Dalal A.Aldowaihi Fahd Alhaidari Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Information Systems College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Networks and Communications College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

With the rapid growth of internet usage,a new situation has been created that enables practicing *** has increased over the past decade,and it has the same adverse effects as face-to-face bullying,like anger,sadness,anxiety,and *** the anonymity people get on the internet,they tend to bemore aggressive and express their emotions freely without considering the effects,which can be a reason for the increase in cyberbullying and it is the main motive behind the current *** study presents a thorough background of cyberbullying and the techniques used to collect,preprocess,and analyze the ***,a comprehensive review of the literature has been conducted to figure out research gaps and effective techniques and practices in cyberbullying detection in various languages,and it was deduced that there is significant room for improvement in the Arabic *** a result,the current study focuses on the investigation of shortlisted machine learning algorithms in natural language processing(NLP)for the classification of Arabic datasets duly collected from Twitter(also known as X).In this regard,support vector machine(SVM),Naive Bayes(NB),Random Forest(RF),Logistic regression(LR),Bootstrap aggregating(Bagging),Gradient Boosting(GBoost),Light Gradient Boosting Machine(LightGBM),Adaptive Boosting(AdaBoost),and eXtreme Gradient Boosting(XGBoost)were shortlisted and investigated due to their effectiveness in the similar ***,the scheme was evaluated by well-known performance measures like accuracy,precision,Recall,and ***,XGBoost exhibited the best performance with 89.95%accuracy,which is promising compared to the state-of-the-art.

关键词： Supervised machine learning ensemble learning cyberbullying Arabic tweets NLP

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