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Journal of Ocean Engineering and Science 2022年第4期7卷 345-352页

作者： Rawya Al-Deiakeh omar abu arqub Mohammed Al-Smadi Shaher Momani Department of Mathematics Faculty of ScienceThe University of JordanAmman 11942Jordan Department of Mathematics Faculty of ScienceAl Balqa Applied UniversitySalt 19117Jordan Nonlinear Analysis and Applied Mathematics(NAAM)Research Group Department of MathematicsFaculty of ScienceKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Applied Science Ajloun CollegeAl-Balqa Applied UniversityAjloun 26816Jordan Nonlinear Dynamics Research Center(NDRC) Ajman UniversityAjmanUnited Arab Emirates Department of Mathematics and Sciences College of Humanities and SciencesAjman UniversityAjmanUnited Arab Emirates

In these analyses,we consider the time-fractional Fisher equation in two-dimensional space.Through the use of the Riemann-Liouville derivative approach,the well-known Lie point symmetries of the utilized equation are derived.Herein,we overturn the fractional fisher model to a fractional differential equation of nonlinear type by considering its Lie point symmetries.The diminutive equation’s derivative is in the Erdélyi-Kober sense,whilst we use the technique of the power series to conclude explicit solutions for the diminutive equations for the first time.The conservation laws for the dominant equation are built using a novel conservation theorem.Several graphical countenances were utilized to award a visual performance of the obtained solutions.Finally,some concluding remarks and future recommendations are utilized.

关键词： Fractional partial differential equation Time-fractional Fisher equation Lie point symmetry Explicit power series Conservation laws

An attractive analytical technique for coupled system of fractional partial differential equations in shallow water waves with conformable derivative

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Communications in Theoretical Physics 2020年第8期72卷 1-17页

作者： Mohammed Al-Smadi omar abu arqub Samir Hadid Department of Applied Science Ajloun CollegeAl-Balqa Applied UniversityAjloun 26816Jordan Department of Mathematics Faculty of ScienceAl-Balqa Applied UniversitySalt 19117Jordan Department of Mathematics and Sciences College of Humanities and SciencesAjman UniversityAjmanUnited Arab Emirates

Mathematical simulation of nonlinear physical and abstract systems is a very vital process for predicting the solution behavior of fractional partial differential equations(FPDEs)corresponding to different applications in science and engineering. In this paper, an attractive reliable analytical technique, the conformable residual power series, is implemented for constructing approximate series solutions for a class of nonlinear coupled FPDEs arising in fluid mechanics and fluid flow, which are often designed to demonstrate the behavior of weakly nonlinear and long waves and describe the interaction of shallow water waves. In the proposed technique the n-truncated representation is substituted into the original system and it is assumed the(n-1) conformable derivative of the residuum is zero. This allows us to estimate coefficients of truncation and successively add the subordinate terms in the multiple fractional power series with a rapidly convergent form. The influence, capacity, and feasibility of the presented approach are verified by testing some real-world applications. Finally, highlights and some closing comments are attached.

关键词： nonlinear coupled system fractional partial differential equations residual power series method conformable fractional derivative

Investigating the therapeutic efficacy of psilocybin in advanced cancer patients: A comprehensive review and meta-analysis

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World Journal of Clinical Oncology 2024年第7期15卷 908-919页

作者： Husam Bader Husam Farraj Joud Maghnam Yazan abu omar Department of Internal Medicine University of MichiganAnn ArborMI 48109United States Department of Internal Medicine University of New MexicoAlbuquerqueNM 87106United States Faculty of Medicine AL-Balqa Applied UniversityAl-Salt 19110Jordan

BACKGROUND Psilocybin,a naturally occurring psychedelic compound found in certain species of mushrooms,is known for its effects on anxiety and depression.It has recently gained increasing interest for its potential therapeutic effects,particularly in patients with advanced cancer.This systematic review and meta-analysis aim to evaluate the effects of psilocybin on adult patients with advanced cancer.AIM To investigate the therapeutic effect of psilocybin in patients with advanced cancer.METHODS A comprehensive search of electronic databases was conducted in PubMed,Cochrane Central Register of Controlled Trials,and Google Scholar for articles published up to February 2023.The reference lists of the included studies were also searched to retrieve possible additional studies.RESULTS A total of 7 studies met the inclusion criteria for the systematic review,comprising 132 participants.The results revealed significant improvements in quality of life,pain control,and anxiety relief following psilocybin-assisted therapy,specifically results on anxiety relief.Pooled effect sizes indicated statistically significant reductions in symptoms of anxiety at both 4 to 4.5 months[35.15(95%CI:32.28-38.01)]and 6 to 6.5 months[33.06(95%CI:28.73-37.40)].Post-administration compared to baseline assessments(P<0.05).Additionally,patients reported sustained improvements in psychological well-being and existential distress fo-llowing psilocybin therapy.CONCLUSION The findings provided compelling evidence for the potential benefits of psilocybin-assisted therapy in improving quality of life,pain control,and anxiety relief in patients with advanced cancer.

关键词： Quality of life Advanced cancer Psilocybin Systemic review Meta analysis

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

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 pathologic.Various cardiotocography measures infer wrongly and give wrong predictions because of human error.The traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as well.Fetal condition is very important to measure at numerous stages and give proper medications to the fetus for its well-being.In 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 results.ML techniques play a pivotal role in detecting fetal disease in its early stages.This research article uses Federated machine learning(FML)and ML techniques to classify the condition of the fetus.This study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the data.So,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,respectively.So,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

Outpatient insulin use in type 2 diabetes mellitus and acute respiratory distress syndrome outcomes:A retrospective cohort study

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World Journal of Clinical Cases 2024年第17期12卷 2966-2975页

作者： Georges Khattar Samer Asmar Laurence Aoun Fares Saliba Shaza Almardini Saif abu Baker Catherine Hong Carolla El Chamieh Fadi Haddadin Toni Habib omar Mourad Zeina Morcos Fatema Arafa Jonathan Mina Khalil El Gharib Mohammad Aldalahmeh Salman Khan Elie Bou Sanayeh Department of Medicine Holy Spirit University of KaslikJounieh 00000Lebanon Department of Internal Medicine Staten Island University HospitalStaten IslandNY 10305United States Public Heath and Biostatistics Independent ResearchBeirut 0000Lebanon Department of Medicine Lebanese UniversityBeirut 00000Lebanon Department of Medicine University of BalamandBeirut 00000Lebanon Department of Medicine Lebanese American UniversityBeirut 00000Lebanon Department of Medicine Northwell Health Staten Island University HospitalNew YorkNY 10305United States

BACKGROUND The impact of type 2 diabetes mellitus(T2DM)on acute respiratory distress syndrome(ARDS)is debatable.T2DM was suspected to reduce the risk and complications of ARDS.However,during coronavirus disease 2019(COVID-19),T2DM predisposed patients to ARDS,especially those who were on insulin at home.AIMTo evaluate the impact of outpatient insulin use in T2DM patients on non-COVID-19 ARDS outcomes.METHODS We conducted a retrospective cohort analysis using the Nationwide Inpatient Sample database.Adult patients diagnosed with ARDS were stratified into insulin-dependent diabetes mellitus(DM)(IDDM)and non-insulindependent DM(NIDDM)groups.After applying exclusion criteria and matching over 20 variables,we compared cohorts for mortality,duration of mechanical ventilation,incidence of acute kidney injury(AKI),length of stay(LOS),hospitalization costs,and other clinical outcomes.RESULTS Following 1:1 propensity score matching,the analysis included 274 patients in each group.Notably,no statistically significant differences emerged between the IDDM and NIDDM groups in terms of mortality rates(32.8%vs 31.0%,P=0.520),median hospital LOS(10 d,P=0.537),requirement for mechanical ventilation,incidence rates of sepsis,pneumonia or AKI,median total hospitalization costs,or patient disposition upon discharge.CONCLUSION Compared to alternative anti-diabetic medications,outpatient insulin treatment does not appear to exert an independent influence on in-hospital morbidity or mortality in diabetic patients with non-COVID-19 ARDS.

关键词： Acute respiratory distress syndrome Type 2 diabetes mellitus Insulin Length of stay Mortality Endotracheal intubation Acute kidney injury Coronavirus disease 2019

Experimental investigation of the impact of water depth, inlet water temperature, and fins on the productivity of a Pyramid Solar Still

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Journal of Groundwater Science and Engineering 2023年第2期11卷 183-190页

作者： Yousef Al-Abed Allah Malik omar abu Abbas Mohammad Department of Mechanical Engineering College of EngineeringKing Fahd University of Petroleum and Minerals(KFUPM)DhahranSaudi Arabia

This experimental study aimed to investigate the impact of water depth, inlet water temperature,and fins on the productivity of a pyramid solar still in producing distilled water. The experiment was conducted in three parts, where the first part explored the variation in water depth from 1 cm to 5 cm, the second part evaluated the effect of increasing inlet water temperature from 30℃ to 50℃, and the third part added fins at the bottom of the still at a specific inlet water depth. Results showed that basin depth had a significant impact on the still's production, with a maximum variation of 40.6% observed when the water level was changed from 1 cm to 5 cm. The daily freshwater production from the pyramid solar still ranged from 3.41 kg/m~2 for a water depth of 1 cm to 2.02 kg/m~2 for a depth of 5 cm. Adding fins at the bottom of the pyramid solar still led to a 7.5% increase in productivity, while adjusting the inlet water temperature from 30℃ to 40℃ and 50℃ resulted in a 15.3% and 21.2% increase, respectively. These findings highlighted the essential factors that can influence the productivity of pyramid solar stills and can be valuable in designing and operating efficient water desalination and purification technologies.

关键词： Pyramid solar still Basin depth Freshwater Efficiency Desalination

Automatic Segmentation and Detection System for Varicocele Using Ultrasound Images

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Computers, Materials & Continua 2022年第7期72卷 797-814页

作者： Ayman M.Abdalla Mohammad abu Awad omar AlZoubi La’aly A.Al-Samrraie Department of Computer Science Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science Jordan University of Science and TechnologyIrbid22110Jordan Department of Water and Environmental Engineering Al-Huson University CollegeAl-Balqa Applied UniversityIrbidJordan

The enlarged veins in the pampiniform venous plexus,known as varicocele disease,are typically identified using ultrasound scans.Themedical diagnosis of varicocele is based on examinations made in three positions taken to the right and left testicles of the male patient.The proposed system is designed to determine whether a patient is affected.Varicocele is more frequent on the left side of the scrotum than on the right and physicians commonly depend on the supine position more than other positions.Therefore,the experimental results of this study focused on images taken in the supine position of the left testicles of patients.There are two possible vein structures in each image:a cross-section(circular)and a tube(non-circular)structure.This proposed system identifies dilated(varicocele)veins of these structures in ultrasound images in three stages:preprocessing,processing,and detection and measurement.These three stages are applied in three different color modes:Grayscale,Red-Green-Blue(RGB),and Hue,Saturation,and Value(HSV).In the preprocessing stage,the region of interest enclosing the pampiniform plexus area is extracted using a median filter and threshold segmentation.Then,the processing stage employs different filters to perform image denoising.Finally,edge detection is applied in multiple steps and the detected veins are measured to determine if dilated veins exist.Overall implementation results showed the proposed system is faster andmore effective than the previous work.

关键词： Varicocele color mode HSV median filter segmentation canny

Big data can help prepare nurses and improve patient outcomes by improving quality,safety,and outcomes

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Frontiers of Nursing 2023年第2期10卷 241-248页

作者： Muayyad Ahmad Salam H.Bani Hani Mohammad abu Sabra omar Almahmoud School of Nursing The University of JordanAmman 11942Jordan Department of Adult Health Nursing Faculty of NursingAl Al-Bayt UniversityMafraq 25113Jordan School of Nursing The University of Jordan-Aqaba CampusAqaba 77111Jordan Faculty of Nursing PharmacyNursing and Health Professions CollegeBirzeit UniversityBirzeit-Ramallah 627Palestine

Objectives:Big data has revolutionized nursing and health care and raised concerns.This research aims to help nurses understand big data sets to provide better patient care.Methods:This study used big data in nursing to improve patient care.Big data in nursing has sparked a global revolution and raised concerns,but few studies have focused on helping nurses understand big data to provide the best patient care.This systematic review was conducted based on PRISMA guidelines.PubMed,MEDLINE,CINAHL,Google Scholar,and ResearchGate were used for 2010-2020 studies.Results:The most common use of big data in nursing was investigated in eight papers between 2015 and 2018.All research showed improvements in patient outcomes and healthcare delivery when big data was used in the medical-surgical,emergency department,critical care unit,community,systems biology,and leadership applications.Big data is not taught to nurses.Conclusions:Big data applications in nursing and health care improve early intervention and decision-making.Big data provides a comprehensive view of a patient’s status and social determinants of health,allowing treatment using all metaparadigms and avoiding a singular focus.Big data can help prepare nurses and improve patient outcomes by improving quality,safety,and outcomes.

关键词： big data health nursing PRISMA quality of care

VISCOMETRIC INVESTIGATIONS OF POLYVINYLPYRROLIDONE IN MIXED SOLVENTS AND WITH VARYING TEMPERATURE

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Chinese Journal of Polymer Science 2005年第4期23卷 367-371页

作者： omar Melad omar abu-Tiem Rajai Baraka Chemistry Department

The viscosity behavior of polyvinylpyrrolidone(PVP)has been determined at 25℃ in mixed solvents comprising water/dimethylformamide(DMF)and water/methanol(MeOH).Analysis of the data has considered the PVP as being both host and guest polymer in solution.The intrinsic viscosity of PVP in DMF is higher than in water and in MeOH,but also increases in a mixed solvent with high water content because of the effect of polymer-solvent interactions.It was also found that the intrinsic viscosity of PVP at finite concentration,[η_(pvp)]_c decreases with an increase in the concentration of PVP in solution.The viscosity behavior of PVP in a mixed solvent is affected by the concentration-dependent intermolecular excluded volume effect,which can be quantitatively expressed by the parameter,b_Y,which reflects the shrinkage of PVP chain coils,resulting in a decrease of[η_(pvp)]_c.The effect of temperature on the viscosity behavior of PVP in MeOH shows that the interaction parameter increases up to a maximum value,and then decreases after a certain temperature.

关键词： Polyvinylpyrrolidone Intermolecular excluded volume effect Intrinsic viscosity