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Functional outcome of surgical management of low mid-grade lumbar spondylolisthesis when considering the sagittal balance parameters preoperatively:a prospective study

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Chinese Neurosurgical Journal 2023年第1期9卷 27-38页

作者： Sameh Elmorsy Hassan Elmorsy hazem abdelsattar abulnasr Yousry Hassan Magdy Samra Ehab Mohamed Eissa Shiekh Zayed Al-nahian Hospital CairoEgypt Neurosurgery Cairo University CairoEgypt

Background:Prospective study objectives.A sagittal balance is a good tool to improve the functional outcome of spine spondylolisthesis surgeries,primarily noted that it has a good impact in deformity surgery and then applied to every spine surgery and the aim of this study is to evaluate its functional outcome when considered in preoperative planning for non-dysplastic low-and mid-grade spondylolisthesis ***:Forty patients diagnosed as low-or mid-grade non-dysplastic spondylolisthesis had undergone surgery at Cairo University after failed medical treatment had been evaluated preoperatively by measuring the sagittal balance parameters which include SVA,spinopelvic angles,lumbar lordosis,pelvic tilt,sacral slope,and pelvic incidence and then measure it along a follow-up period of 1 year postoperatively started from February 2018 and correlate it with functional outcome using Oswestry score(ODI)and *** of parameters has been estimated preoperatively by manual estimation and Surgimap application then applied during the ***:All patients were treated by surgical treatment through posterior transpedicular screw fixation with conventional or reduction screws and fusion±TLIF *** mean of lumbar lordosis and mean spinopelvic angles were increased in a statistically significant *** tilt was decreased in a statistically insignificant *** mean of pelvic incidence was not changed and statistically insignificant,and this is matching the fact that pelvic incidence is a constant *** sacral slope was increased in a statistically insignificant *** results showed that 37 had a statistically significant improvement in their ODI>20%at the last *** patients had a poor clinical outcome with ODI scorFinal results showed that 37 had a statistically significant improvement in their ODI>20%at the last *** patients had a poor clinical outcome with ODI score of>20%improvement,and we noticed that the le

关键词： Spondylolisthesis Low-grade spondylolisthesis Sagittal balance Lumbar lordosis

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A Practical Study of Intelligent Image-Based Mobile Robot for Tracking Colored Objects

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Computers, Materials & Continua 2024年第8期80卷 2181-2197页

作者： Mofadal Alymani Mohamed Esmail Karar hazem Ibrahim Shehata College of Computing and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Faculty of Electronic Engineering Menoufia UniversityMenouf32952Egypt Faculty of Engineering Zagazig UniversityZagazig44519Egypt

Object tracking is one of the major tasks for mobile robots in many real-world ***,artificial intelligence and automatic control techniques play an important role in enhancing the performance of mobile robot *** contrast to previous simulation studies,this paper presents a new intelligent mobile robot for accomplishing multi-tasks by tracking red-green-blue(RGB)colored objects in a real experimental ***,a practical smart controller is developed based on adaptive fuzzy logic and custom proportional-integral-derivative(PID)schemes to achieve accurate tracking results,considering robot command delay and tolerance *** design of developed controllers implies some motion rules to mimic the knowledge of experienced *** scenarios of three colored object combinations have been successfully tested and evaluated by using the developed controlled image-based robot *** PID control failed to handle some tracking scenarios in this *** proposed adaptive fuzzy PID control achieved the best accurate results with the minimum average final error of 13.8 cm to reach the colored targets,while our designed custom PID control is efficient in saving both average time and traveling distance of 6.6 s and 14.3 cm,*** promising results demonstrate the feasibility of applying our developed image-based robotic system in a colored object-tracking environment to reduce human workloads.

关键词： Mobile robot autonomous systems fuzzy logic control real-time image processing

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Eco-toxicity and health risk assessment of polycyclic aromatic hydrocarbons in surface sediments of Burullus Lake in Egypt

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China Geology 2024年第3期7卷 460-468页

作者： Hanan E Osman Mohamed H E El-Morsy hazem T Abd El-Hamid Department of Biology Faculty of Applied ScienceUmm Al-Qura UniversityMecca 24382Saudi Arabia Deanship of Scientific Research Umm Al-Qura UniversityMakkah 24372Saudi Arabia National Institute of Oceanography and Fisheries(NIOF) Cairo 11865Egypt Botany and Microbiology Department Faculty of ScienceAl-Azhar UniversityCairo 11651Egypt

Polycyclic aromatic hydrocarbons(PAHs)are ubiquitous environmental contaminants of growing concern due to their potential ecological and human health *** study presents a comprehensive assessment of PAHs contamination in the surface sediments of Burullus Lake,a vital and second largest delta lake in *** aim was to evaluate the eco-toxicity and potential health risks associated with the presence of these *** seven sediment samples were collected from various drains in the southern part of Burullus *** extraction method was employed to extract PAHs(16PAHs)from the sediment ***,target compounds were located using *** results showed that samples contained PAHs levels ranging from 0.038×10^(-6)to 0.459×10^(-6),which is considered heavily polluted by the European standard for PAHs ***,there was no apparent source of PAHs in the ElKhashah drain or the Brinbal Canal,as HPLC found none of the *** most prevalent compound in sediment samples along the study area was *** diagnostic indices in the present study indicated that the hydrocarbons in the region originated from pyrolytic and man-made sources along the drains of Burullus *** principal component analysis(PCA)and diagnostic ratios revealed that coal combustion and pyrolytic sources were responsible for the PAHs contamination in the surface *** non-carcinogenic risk(HI),which is the product of the HQs for the adult and child populations,respectively,was *** values under 1,therefore,demonstrated that they had no carcinogenic effects on human *** and MEQs in the sediments of Burullus Lake do not have a cancer-causing impact on *** the safety of nearby wildlife,aquatic life,and people,all activities that raise petroleum hydrocarbon levels in Burullus Lake must be adequately regulated and *** to the ecological risk assessment,there is little chance that PAHs will be found

关键词： Polycyclic aromatic hydrocarbons Diagnostic indices Toxicity Delta lake sediment Burullus Lake Human health risk Aquatic ecosystem HPLC Coal combustion

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Performance Comparison of Field-oriented Control,Direct Torque Control,and Model-predictive Control for SynRMs

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Chinese Journal of Electrical Engineering 2022年第1期8卷 24-37页

作者： hazem Hadla Fernando Santos Polytechnic Institute of Viseu Higher School of Technology and Management of LamegoLamego 5100-074Portugal

Simulation studies of three synchronous reluctance motor(SynRM)control strategies are presented:field-oriented control(FOC),direct torque control(DTC),and finite-set model-predictive control(FS-MPC).FOC uses linear controllers and pulse-width modulation to control the fundamental components of the load voltages *** contrast,DTC and FS-MPC are nonlinear strategies wherein the voltage vectors are directly generated in the absence of a *** operating principles and control structures of these control strategies are ***,a comparative analysis of the static and dynamic performance of the control strategies is conducted using Matlab/Simulink to identify their advantages and *** is confirmed that each of the control strategies has merits and that all three of them satisfy the requirements of modern high-performance drives.

关键词： Field-oriented control direct torque control model-predictive control synchronous reluctance motor

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Exome sequencing identifies a likely causative variant in 53%of families with ciliopathy-related features on renal ultrasound after excluding NPHP1 deletions

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Genes & Diseases 2024年第5期11卷 40-43页

作者： Konstantin Deutsch Verena Klambt Thomas M.Kitzler Tilman Jobst-Schwan Ronen Schneider Florian Buerger Steve Seltzsam Sherif El Desoky Jameela A.Kari Farkhanda Hafeez Maria Szczepanska Loai A.Eid hazem S.Awad Muna Al-Saffar Neveen A.Soliman Velibor Tasic Camille Nicolas-Frank Kirollos Yousef Luca M.Schierbaum Sophia Schneider Abdul Halawi Izzeldin Elmubarak Katharina Lemberg Shirlee Shril Shrikant M.Mane Nancy Rodig Friedhelm Hildebrandt Division of Nephrology Department of PediatricsBoston Children’s HospitalHarvard Medical SchoolBostonMA 02215USA Department of Pediatric Gastroenterology Nephrology and Metabolic DiseasesCharite Universitatsmedizin BerlinBerlin 13353Germany Berlin Institute of Health at Charitee Universitatsmedizin Berlin BIH Biomedical Innovation AcademyBIH Charite Clinician Scientist ProgramBerlin 10178Germany Department of Nephrology and Hypertension FriedrichAlexander-Universitat Erlangen-NurnbergErlangen 91054Germany Department of Pediatrics Faculty of Medicine King Abdulaziz UniversityPediatric Nephrology Center of ExcellenceKing Abdulaziz University HospitalJeddah 21589Saudi Arabia Department of Pediatric Nephrology The Children’s Hospital and Institute of Child HealthLahore 54000Pakistan Department of Pediatrics Faculty of Medical Sciences in ZabrzeMedical University of Silesia in KatowiceKatowice 40-752Poland Dubai Hospital and Al-Jalila Children’s Specialty Hospital Kidney Center of ExcellenceDubai 4545United Arab Emirates Department of Genetics and Genomics UAE UniversityAbu Dhabi 15551United Arab Emirates Department of Pediatrics Division of Genetics and GenomicsBoston Children’s HospitalHarvard Medical SchoolBostonMA 02215USA Department of Pediatrics Center of Pediatric Nephrology and TransplantationKasr Al Ainy School of MedicineCairo UniversityCairo 11562Egypt Egypt Center for Research and Regenerative Medicine(ECRRM) Cairo 11511Egypt Medical Faculty Skopje University Children’s HospitalSkopje 1000North Macedonia Department of Genetics Yale University School of MedicineNew HavenCT 06520USA

Nephronophthisis-related ciliopathies(NPHP-RC)represent one of the most common causes of chronic kidney disease in the first three decades of life and are characterized by a broad genetic and clinical heterogeneity.1 To date,more than 90 genes have been identified that cause autosomalrecessive NPHP-RC if mutated,accounting for up to 60%of cases.1 Among these,homozygous deletions of NPHP1 are the most common *** genes localize to primary cilia,basal bodies,or the centrosome and lead to a primary ciliary disruption if mutated,thereby causing a broad phenotypical spectrum.1 Patients that suffer from NPHP-RC can either have an isolated renal phenotype,such as polyuria,polydipsia,decreased urinary concentration ability,and secondary enuresis due to loss of tubular function,or present with extrarenal symptoms including retinal degeneration,cerebellar vermis hypoplasia,or hepatic *** are often diagnosed in early adolescence,reaching end-stage renal disease before 25 years of age,but early onset and rapidly progressive forms of NPHP-RC also exist.1 Renal ultrasound indicates kidneys of normal or reduced renal length with increased echogenicity and corticomedullary cysts.

关键词： degeneration urinary likely

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Developed Fall Detection of Elderly Patients in Internet of Healthcare Things

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Computers, Materials & Continua 2023年第8期76卷 1689-1700页

作者： Omar Reyad hazem Ibrahim Shehata Mohamed Esmail Karar College of Computing and Information Technology Shaqra UniversityP.O.Box 33Shaqra11961Saudi Arabia Faculty of Computers and Artificial Intelligence Sohag UniversitySohag82524Egypt Faculty of Engineering Zagazig UniversityZagazig44519Egypt Faculty of Electronic Engineering Menoufia UniversityMenouf32952Egypt

Falling is among the most harmful events older adults may *** the continuous growth of the aging population in many societies,developing effective fall detection mechanisms empowered by machine learning technologies and easily integrable with existing healthcare systems becomes *** paper presents a new healthcare Internet of Health Things(IoHT)architecture built around an ensemble machine learning-based fall detection system(FDS)for older *** to deep neural networks,the ensemble multi-stage random forest model allows the extraction of an optimal subset of fall detection features with minimal *** number of cascaded random forest stages is automatically *** study uses a public dataset of fall detection samples called SmartFall to validate the developed fall detection *** SmartFall dataset is collected based on the acquired measurements of the three-axis accelerometer in a *** scenario in this dataset is classified and labeled as a fall or a *** comparison to the three machine learning models—K-nearest neighbors(KNN),decision tree(DT),and standard random forest(SRF),the proposed ensemble classifier outperformed the other models and achieved 98.4%*** developed healthcare IoHT framework can be realized for detecting fall accidents of older people by taking security and privacy concerns into account in future work.

关键词： Elderly population fall detection wireless sensor networks Internet of health things ensemble machine learning

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Deep Forest-Based Fall Detection in Internet of Medical Things Environment

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Computer Systems Science & Engineering 2023年第6期45卷 2377-2389页

作者： Mohamed Esmail Karar Omar Reyad hazem Ibrahim Shehata College of Computing and Information Technology Shaqra UniversityP.O.Box 33Shaqra11961Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Faculty of Computers and Artificial IntelligenceSohag UniversitySohag82524Egypt Department of Computer and Systems Engineering Faculty of EngineeringZagazig UniversityZagazig44519Egypt

This article introduces a new medical internet of things(IoT)framework for intelligent fall detection system of senior people based on our proposed deep forest *** cascade multi-layer structure of deep forest classifier allows to generate new features at each level with minimal hyperparameters compared to deep neural ***,the optimal number of the deep forest layers is automatically estimated based on the early stopping criteria of validation accuracy value at each generated *** suggested forest classifier was successfully tested and evaluated using a public SmartFall dataset,which is acquired from three-axis accelerometer in a *** includes 92781 training samples and 91025 testing samples with two labeled classes,namely non-fall and *** results of our deep forest classifier demonstrated a superior performance with the best accuracy score of 98.0%compared to three machine learning models,i.e.,K-nearest neighbors,decision trees and traditional random forest,and two deep learning models,which are dense neural networks and convolutional neural *** considering security and privacy aspects in the future work,our proposed medical IoT framework for fall detection of old people is valid for real-time healthcare application deployment.

关键词： Elderly population fall detection wireless sensor networks internet of medical things deep forest

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A Hybrid Heuristic Algorithm for Solving COVID-19’s Social Distancing at Universities Campus

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Computer Systems Science & Engineering 2022年第6期41卷 933-944页

作者： Hassan Al-Tarawneh Khalid Al-Kaabneh Aysh Alhroob hazem Migdady Issam Alhadid Department of Data sciences and Artificial Intelligence Al-Ahlyyia Amman UniversityAmmanJordan Department of Software Engineering Isra UniversityAmmanJordan Department of CSMIS Oman college of management and technologyMuscatOman Faculty of Information Technology and Systems University of JordanAqabaJordan

Social distancing during COVID-19 has become one of the most important measures in reducing the risks of the spread of the virus. Implementing thesemeasures at universities is crucial and directly related to the physical attendance ofthe populations of students, professors, employees, and other members on campus. This research proposes an automated scheduling approach that can help universities and schools comply with the social distancing regulations by providingassistance in avoiding huge assemblages of people. Furthermore, this paper proposes a novel course timetable-scheduling scheme based on four main ***, a distance of two meters must be maintained between each student inside theclassroom. Second, no classrooms should contain more than 20% of their regularcapacity. Third, there would be no back-to-back classes. Lastly, no lectures shouldbe held simultaneously in adjacent classrooms. The proposed approach wasimplemented using a variable neighborhood search (VNS) approach with an adaptive neighborhood structure (AD-NS) to resolve the problem of scheduling coursetimetables at Al-Ahlyyia Amman University. However, the experimental resultsshow that the proposed techniques outperformed the standard VNS tested on university course timetabling benchmark dataset ITC2007-Track3. Meanwhile, theapproach was tested using datasets collected from the faculty of information technology at Al-Ahlyyia Amman University (Jordan). Where the results showed that,the proposed technique could help educational institutes to resume their regularoperations while complying with the social distancing guidelines.

关键词： COVID-19 social distance variable neighborhood search adaptive neighborhood structure university course timetable

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Residual Attention Deep SVDD for COVID-19 Diagnosis Using CT Scans

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Computers, Materials & Continua 2023年第2期74卷 3333-3350页

作者： Akram Ali Alhadad Omar Tarawneh Reham R.Mostafa hazem M.El-Bakry Information Systems Department Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Computer Science Department Ibb UniversityIbbYemen SE Department Faculty of Computer Sciences and InformaticsAmman Arab UniversityAmman11953Jordan

COVID-19 is the common name of the disease caused by the novel coronavirus(2019-nCoV)that appeared in Wuhan,China in *** the infected people is the most important factor in the fight against the *** gold-standard test to diagnose COVID-19 is polymerase chain reaction(PCR),but it takes 5–6 h and,in the early stages of infection,may produce false-negative *** Computed Tomography(CT)images to diagnose patients infected with COVID-19 has become an urgent *** this study,we propose a residual attention deep support vector data description SVDD(RADSVDD)approach to diagnose *** is a novel approach combining residual attention with deep support vector data description(DSVDD)to classify the CT *** the best of our knowledge,we are the first to combine residual attention with DSVDD in general,and specifically in the diagnosis of *** attention with DSVDD naively may cause model *** in the proposed RADSVDD guides the network during training and enables quick learning,residual connectivity prevents vanishing *** approach consists of three models,each model is devoted to recognizing one certain disease and classifying other diseases as *** models learn in an end-to-end *** proposed approach attained high performance in classifying CT images into intact,COVID-19,and non-COVID-19 *** evaluate the proposed approach,we created a dataset from published datasets and had it assessed by an experienced *** proposed approach achieved high performance,with the normal model attained sensitivity(0.96–0.98),specificity(0.97–0.99),F1-score(0.97–0.98),and area under the receiver operator curve(AUC)0.99;the COVID-19 model attained sensitivity(0.97–0.98),specificity(0.97–0.99),F1-score(0.97–0.99),and AUC 0.99;and the non-COVID pneumoniamodel attained sensitivity(0.97–1),specificity(0.98–0.99),F1-score(0.97–0.99),and AUC 0.99.

关键词： Deep learning deep SVDD residual attention anomaly detection COVID-19 Coronavirus

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Applying Apache Spark on Streaming Big Data for Health Status Prediction

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Computers, Materials & Continua 2022年第2期70卷 3511-3527页

作者： Ahmed Ismail Ebada Ibrahim Elhenawy Chang-Won Jeong Yunyoung Nam hazem Elbakry Samir Abdelrazek Information Systems Department Faculty of Computers and InformationMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computers and InformationEl-Zagazig UniversityZagazigSharqiyah44519Egypt Medical Convergence Research Center Wonkwang UniversityIksanKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Big data applications in healthcare have provided a variety of solutions to reduce costs,errors,and *** work aims to develop a real-time system based on big medical data processing in the cloud for the prediction of health *** the proposed scalable system,medical parameters are sent to Apache Spark to extract attributes from data and apply the proposed machine learning *** this way,healthcare risks can be predicted and sent as alerts and recommendations to users and healthcare *** proposed work also aims to provide an effective recommendation system by using streaming medical data,historical data on a user’s profile,and a knowledge database to make themost appropriate real-time recommendations and alerts based on the sensor’s *** proposed scalable system works by tweeting the health status attributes of *** cloud profile receives the streaming healthcare data in real time by extracting the health attributes via a machine learning prediction algorithm to predict the users’health ***,their status can be sent on demand to healthcare ***,machine learning algorithms can be applied to stream health care data from wearables and provide users with insights into their health *** algorithms can help healthcare providers and individuals focus on health risks and health status changes and consequently improve the quality of life.

关键词： Big data streaming processing healthcare data machine learning IoT data processing Apache Spark

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