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Evaluation of modifi ed Alvarado scoring system and RIPASA scoring system as diagnostic tools of acute appendicitis

World Journal of Emergency Medicine 2017年第4期8卷 276-280页

作者： abdullah Shuaib Ali Shuaib Zainab Fakhra Bader Marafi Khalid Alsharaf abdullah behbehani Department of Surgery Kuwait Mubarak Alkabeer Hospital Jabriya Kuwait Biomedical Engineering Unit Physiology Department Faculty of Medicine Kuwait University Kuwait City Kuwait MD in internship year Kuwait Institute of Medical Specialization Kuwait City Kuwait Department of Surgery Faculty of Medicine Kuwait University Kuwait City Kuwait

BACKGROUND: Acute appendicitis is the most common surgical condition presented in emergency departments worldwide. Clinical scoring systems, such as the Alvarado and modified Alvarado scoring systems, were developed with the goal of reducing the negative appendectomy rate to 5%–10%. The Raja Isteri Pengiran Anak Saleha Appendicitis(RIPASA) scoring system was established in 2008 specif ically for Asian populations. The aim of this study was to compare the modif ied Alvarado with the RIPASA scoring system in Kuwait ***: This study included 180 patients who underwent appendectomies and were documented as having "acute appendicitis" or "abdominal pain" in the operating theatre logbook(unit B) from November 2014 to March 2016. The sensitivity, specificity, positive predictive value(PPV), negative predictive value(NPV), diagnostic accuracy, predicted negative appendectomy and receiver operating characteristic(ROC) curve of the modified Alvarado and RIPASA scoring systems were derived using SPSS statistical ***: A total of 136 patients were included in this study according to our criteria. The cut-off threshold point of the modif ied Alvarado score was set at 7.0, which yielded a sensitivity of 82.8% and a specif icity of 56%. The PPV was 89.3% and the NPV was 42.4%. The cut-off threshold point of the RIPASA score was set at 7.5, which yielded a 94.5% sensitivity and an 88% specif icity. The PPV was 97.2% and the NPV was 78.5%. The predicted negative appendectomy rates were 10.7% and 2.2% for the modif ied Alvarado and RIPASA scoring systems, respectively. The negative appendectomy rate decreased significantly, from 18.4% to 10.7% for the modified Alvarado, and to 2.2% for the RIPASA scoring system, which was a signif icant difference(P<0.001) for both scoring ***: Based on the results of this study, the RIPASA score is a simple scoring system with better sensitivity and specif icity than the modif ied Alvarado scoring system in A

关键词： Acute appendicitis Modifi ed Alvarado score RIPASA score

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Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

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Computers, Materials & Continua 2024年第5期79卷 3139-3173页

作者： Norah abdullah Al-Johany Sanaa abdullah Sharaf Fathy Elbouraey Eassa Reem Abdulaziz Alnanih Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Software Engineering and Distributed System Research Group King Abdulaziz UniversityJeddah21589Saudi Arabia

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed ***, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

关键词： High-performance computing parallel computing software engineering software defect message passing interface deadlock

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Potential role of tubulin glutamylation in neurodegenerative diseases

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Neural Regeneration Research 2024年第6期19卷 1191-1192页

作者： abdullah Md.Sheikh Shatera Tabassum Department of Laboratory Medicine Shimane University Faculty of MedicineShimaneJapan

The differentiation of neuronal stem cells into mature neurons is a complex process that involves both structural and functional *** cells undergo differentiation,there are notable functional changes,including the expression of various transcription factors,cytokines,and ***,structural changes occur as the cells develop various processes from the cell body and establish synaptic contacts with other cells.

关键词： diseases degenerative cytokines

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Machine Learning Enabled Novel Real-Time IoT Targeted DoS/DDoS Cyber Attack Detection System

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Computers, Materials & Continua 2024年第9期80卷 3655-3683页

作者： abdullah Alabdulatif Navod Neranjan Thilakarathne Mohamed Aashiq Department of Cybersecurity College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of ICT Faculty of TechnologyUniversity of ColomboColombo00700Sri Lanka Department of Computer Science and Engineering Faculty of EngineeringSouth Eastern University of Sri LankaOluvil32360Sri Lanka

The increasing prevalence of Internet of Things(IoT)devices has introduced a new phase of connectivity in recent years and,concurrently,has opened the floodgates for growing cyber *** the myriad of potential attacks,Denial of Service(DoS)attacks and Distributed Denial of Service(DDoS)attacks remain a dominant concern due to their capability to render services inoperable by overwhelming systems with an influx of *** IoT devices often lack the inherent security measures found in more mature computing platforms,the need for robust DoS/DDoS detection systems tailored to IoT is paramount for the sustainable development of every domain that IoT *** this study,we investigate the effectiveness of three machine learning(ML)algorithms:extreme gradient boosting(XGB),multilayer perceptron(MLP)and random forest(RF),for the detection of IoTtargeted DoS/DDoS attacks and three feature engineering methods that have not been used in the existing stateof-the-art,and then employed the best performing algorithm to design a prototype of a novel real-time system towards detection of such DoS/DDoS *** CICIoT2023 dataset was derived from the latest real-world IoT traffic,incorporates both benign and malicious network traffic patterns and after data preprocessing and feature engineering,the data was fed into our models for both training and validation,where findings suggest that while all threemodels exhibit commendable accuracy in detectingDoS/DDoS attacks,the use of particle swarmoptimization(PSO)for feature selection has made great improvements in the performance(accuracy,precsion recall and F1-score of 99.93%for XGB)of the ML models and their execution time(491.023 sceonds for XGB)compared to recursive feature elimination(RFE)and randomforest feature importance(RFI)*** proposed real-time system for DoS/DDoS attack detection entails the implementation of an platform capable of effectively processing and analyzing network traffic in *** inv

关键词： Machine learning Internet of Things(IoT),DoS,DDoS cybersecurity intrusion prevention network security,feature optimization,sustainability

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Leveraging User-Generated Comments and Fused BiLSTM Models to Detect and Predict Issues with Mobile Apps

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Computers, Materials & Continua 2024年第4期79卷 735-759页

作者： Wael M.S.Yafooz abdullah Alsaeedi Department of Computer Science College of Computer Science and EngineeringTaibah UniversityMedina42353Saudi Arabia

In the last decade, technical advancements and faster Internet speeds have also led to an increasing number ofmobile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of these apps eases our daily lives, and all customers who need any type of service can accessit easily, comfortably, and efficiently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conflict, unreliability, or user-unfriendliness. Pilgrims comment on these issues on mobile app platformsthrough reviews of their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-functional requirements by utilizing user ***, solving suchissues is a great challenge, and the issues still exist. Therefore, this study aims to propose a hybrid deep learningmodel to classify and predict mobile app software issues encountered by millions of pilgrims during the Hajj andUmrah periods from the user perspective. Firstly, a dataset was constructed using user-generated comments fromrelevant mobile apps using natural language processing methods, including information extraction, the annotationprocess, and pre-processing steps, considering a multi-class classification problem. Then, several experimentswere conducted using common machine learning classifiers, Artificial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the performance of the proposed model. Results show 96% in F1-score and accuracy, and the proposedmodel outperformed the mentioned models.

关键词： Mobile apps issues play store user comments deep learning LSTM bidirectional LSTM

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Interplay of serum biomarkers bilirubin andγ-glutamyltranspeptidase in predicting cardiovascular complications in type-2 diabetes mellitus

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World Journal of Diabetes 2024年第6期15卷 1074-1078页

作者： Ebtesam abdullah Al-Suhaimi abdullah Ahmed Al-Rubaish Scientific Research and Innovation Imam Abdulrahman Bin Faisal UniversityDammam 31441Saudi Arabia King Abdulaziz and his Companions Foundation for Giftedness and Creativity“Mawhiba” Riyadh 11372Saudi Arabia College of Medicine Imam Abdulrahman Bin Faisal UniversityDammam 31441Saudi Arabia

This editorial synthesizes insights from a series of studies examining the interplay between metabolic and oxidative stress biomarkers in cardiovascular disease(CVD),focusing particularly on type-2 diabetes mellitus(T2DM)and acute coronary syndrome(ACS).The central piece of this synthesis is a study that investigates the balance between oxidative stress and antioxidant systems in the body through the analysis of serum bilirubin andγ-glutamyltranspeptidase(γ-GGT)levels in T2DM patients with *** study highlights serum bilirubin as a protective antioxidant factor,while elevatedγ-GGT levels indicate increased oxidative stress and correlate with major adverse cardiovascular *** to this,other research contributions revealγ-GGT’s role as a risk factor in ACS,its association with cardiovascular mortality in broader populations,and its link to metabolic syndrome,further elucidating the metabolic dysregulation in *** collective findings from these studies underscore the critical roles ofγ-GGT and serum bilirubin in cardiovascular health,especially in the context of T2DM and *** providing a balanced view of the body’s oxidative and antioxidative mechanisms,these insights suggest potential pathways for targeted interventions and improved prognostic assessments in patients with T2DM and *** synthesis not only corroborates the pivotal role ofγ-GGT in cardiovascular pathology but also introduces the protective potential of antioxidants like bilirubin,illuminating the complex interplay between T2DM and heart *** studies collectively underscore the critical roles of serum bilirubin andγ-GGT as biomarkers in cardiovascular health,particularly in T2DM and ACS contexts,offering insights into the body’s oxidative and antioxidative *** synthesis of research supports the potential of these biomarkers in guiding therapeutic strategies and improving prognostic assessments for patients with T2DM and some CVD.

关键词： Type-2 diabetes mellitus Acute coronary syndrome Serum biomarkers γ-glutamyltranspeptidase Bilirubin Cardiovascular disease

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A Novel Intrusion Detection Model of Unknown Attacks Using Convolutional Neural Networks

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Computer Systems Science & Engineering 2024年第2期48卷 431-449页

作者： abdullah Alsaleh Department of Information Engineering Florence UniversityFlorenceItaly Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityMajmaahSaudi Arabia

With the increasing number of connected devices in the Internet of Things(IoT)era,the number of intrusions is also *** intrusion detection system(IDS)is a secondary intelligent system for monitoring,detecting and alerting against malicious *** is important in developing advanced security *** study reviews the importance of various techniques,tools,and methods used in IoT detection and/or prevention ***,it focuses on machine learning(ML)and deep learning(DL)techniques for *** paper proposes an accurate intrusion detection model to detect traditional and new attacks on the Internet of *** speed up the detection of recent attacks,the proposed network architecture developed at the data processing layer is incorporated with a convolutional neural network(CNN),which performs better than a support vector machine(SVM).Processing data are enhanced using the synthetic minority oversampling technique to ensure learning *** nearest class mean classifier is applied during the testing phase to identify new *** results using the AWID dataset,which is one of the most common open intrusion detection datasets,revealed a higher detection accuracy(94%)compared to SVM and random forest methods.

关键词： Internet of Vehicles intrusion detection machine learning unknown attacks data processing layer

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Appropriate Combination of Crossover Operator and Mutation Operator in Genetic Algorithms for the Travelling Salesman Problem

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Computers, Materials & Continua 2024年第5期79卷 2399-2425页

作者： Zakir Hussain Ahmed Habibollah Haron abdullah Al-Tameem Department of Mathematics and Statistics College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Kingdom of Saudi Arabia Faculty of Computing Universiti Teknologi MalaysiaJohor Bahru81310Malaysia College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Kingdom of Saudi Arabia

Genetic algorithms(GAs)are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization *** a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter *** uses a crossover operator to create better offspring chromosomes and thus,converges the ***,it uses a mutation operator to explore the unexplored areas by the crossover operator,and thus,diversifies the GA search space.A combination of crossover and mutation operators makes the GA search strong enough to reach the optimal ***,appropriate selection and combination of crossover operator and mutation operator can lead to a very good GA for solving an optimization *** this present paper,we aim to study the benchmark traveling salesman problem(TSP).We developed several genetic algorithms using seven crossover operators and six mutation operators for the TSP and then compared them to some benchmark TSPLIB *** experimental studies show the effectiveness of the combination of a comprehensive sequential constructive crossover operator and insertion mutation operator for the *** GA using the comprehensive sequential constructive crossover with insertion mutation could find average solutions whose average percentage of excesses from the best-known solutions are between 0.22 and 14.94 for our experimented problem instances.

关键词： Travelling salesman problem genetic algorithms crossover operator mutation operator comprehensive sequential constructive crossover insertion mutation

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Unraveling the role of NiSnPH@OOH/CC perovskite hydroxide for efficient electrocatalytic oxidation of methanol to formate

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Nano Research 2024年第4期17卷 2388-2399页

作者： Jing Shao Yusheng Fang Xiaobing Wu Muhammad Imran abdullah Youkun Tao College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518060China School of Science Harbin Institute of TechnologyShenzhen 518055China

The sluggish kinetics of oxygen evolution reaction(OER)is the key tailback for hydrogen production from the water *** OER with thermodynamically auspicious methanol oxidation reaction(MOR)can significantly boost the H_(2) and value-added products ***,it is currently challenging to achieve a synergistic manipulation of product selectivity and performance for MOR ***,we report NiSnPH@OOH/CC(CC=carbon cloth)perovskite hydroxide nanosphere as an efficient MOR electrocatalyst with high activity,stability,and selectivity towards methanol oxidation to formate.A surface amorphous layer of defect rich NiOOH was generated in operando by selective Sn leaching with stable perovskite hydroxide bulk structure,which mitigates the oxidative power and optimizes the local coordination environment of the active NiOOH *** situ Raman combined with electrochemical studies further confirm the key active species,NiOOH,generated in operando enhance the MOR and blocking the over oxidation of methanol to CO_(2).As a result,NiSnPH@OOH/CC effectively masks the OER and attains>99%selectivity with 100%Faradic efficiency for *** results of this study show the advances of NiSnPH@OOH/CC as an efficient electrocatalyst for MOR and also suggest its potential applications for various small organic molecules oxidation.

关键词： perovskite hydroxide small organic molecules nickel oxy(hydroxide) value-added products methanol oxidation reaction

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Comprehensive analysis of glacier recession(2000-2020)in the Nun-Kun Group of Glaciers,Northwestern Himalaya

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Journal of Mountain Science 2024年第3期21卷 768-785页

作者： Shakil Ahmad ROMSHOO Ummer AMEEN Mustafa Hameed BHAT Tariq abdullah Department of Geoinformatics University of KashmirSrinagarKashmir 190006India Islamic University of Science and Technology AwantiporaKashmir 192122India Centre of Excellence for Glacier Studies in the Western Himalaya University of KashmirSrinagarKashmir 190006India

Himalayan glaciers are shrinking rapidly,especially after *** shrinkage,however,shows a differential pattern in space and time,emphasizing the need to monitor and assess glacier changes at a larger *** this study,changes of 48 glaciers situated around the twin peaks of the Nun and Kun mountains in the northwestern Himalaya,hereafter referred to as Nun-Kun Group of Glaciers(NKGG),were investigated using Landsat satellite data during *** in glacier area,snout position,Equilibrium Line Altitude(ELA),surface thickness and glacier velocity were assessed using remote sensing data supplemented by field *** study revealed that the NKGG glaciers have experienced a recession of 4.5%±3.4%and their snouts have retreated at the rate of 6.4±1.6 m·a^(-1).Additionally,there was a 41%increase observed in the debris cover area during the observation *** the geodetic approach,an average glacier elevation change of-1.4±0.4 m·a^(-1)was observed between 2000 and *** observed mass loss of the NKGG has resulted in the deceleration of glacier velocity from 27.0±3.7 m·a^(-1)in 2000 to 21.2±2.2 m·a^(-1)in *** ELA has shifted upwards by 83.0±22 m during the *** morphological and topographic factors showed a strong influence on glacier ***,a higher recession of 12.9%±3.2%was observed in small glaciers,compared to 2.7%±3.1%in larger *** debris-covered glaciers showed lower shrinkage(2.8%±1.1%)compared to the clean glaciers(9.3%±5%).The glacier depletion recorded in the NKGG during the last two decades,if continued,would severely diminish glacial volume and capacity to store water,thus jeopardizing the sustainability of water resources in the basin.

关键词： Nun-Kun range Glacier recession Glacier snout Remote Sensing Himalaya Glacier velocity

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