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Arrhythmia Detection by Using Chaos Theory with machine Learning Algorithms

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Computers, materials & Continua 2024年第6期79卷 3855-3875页

作者： maie Aboghazalah Passent el-kafrawy Abdelmoty m.Ahmed Rasha elnemr Belgacem Bouallegue Ayman el-sayed math and Computer Science Department Faculty of ScienceMenoufia UniversityShebin El-komEgypt College of Engineering Computer Science DepartmentEffat UniversityJeddahKingdom of Saudi Arabia Department of Computer Engineering College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia Computer Science and Engineering Department Faculty of Electronic EngineeringMenoufia UniversityShebin El-komEgypt Climate Change Information Center and Expert Systems Agriculture Research CenterGizaEgypt

Heart monitoring improves life ***(ECgs or EKgs)detect heart *** learning algorithms can create a few ECg diagnosis processing *** first method uses raw ECg and time-series *** second method classifies the ECg by patient *** third technique translates ECg impulses into Q waves,R waves and S waves(QRS)features using richer *** ECg signals vary naturally between humans and activities,we will combine the three feature selection methods to improve classification accuracy and *** using all three approaches have not been examined till *** researchers found that machine Learning(mL)techniques can improve ECg *** study will compare popular machine learning techniques to evaluate ECg *** algorithms—Support Vector machine(SVm),Decision Tree,Naive Bayes,and Neural Network—compare categorization *** plus prior knowledge has the highest accuracy(99%)of the four mL *** characteristics failed to identify signals without chaos *** 99.8%classification accuracy,the Decision Tree technique outperformed all previous experiments.

关键词： ECg extraction ECg leads time series prior knowledge and arrhythmia chaos theory QRS complex analysis machine learning ECg classification

A hybrid machine-learning model for solar irradiance forecasting

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Clean Energy 2024年第1期8卷 100-110页

作者： Ameera m.Almarzooqi maher maalouf Tarek H.m.el-Fouly Vasileios E.Katzourakis mohamed S.el moursi Constantinos V.Chrysikopoulos Department of Industrial and Systems Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE electrical Engineering and Computer Science Department Khalifa University Abu DhabiUAE Department of Civil Infrastructure and Environmental Engineering Khalifa UniversityAbu DhabiPO Box 127788UAE School of Chemical and Environmental Engineering Technical University of CreteChaniaGreece

Nowcasting and forecasting solar irradiance are vital for the optimal prediction of grid-connected solar photovoltaic(PV)power *** plants face operational challenges and scheduling dispatch difficulties due to the fluctuating nature of their power *** the generation capacity within the electric grid increases,accurately predicting this output becomes increasingly essential,especially given the random and non-linear characteristics of solar irradiance under variable weather *** study presents a novel prediction method for solar irradiance,which is directly in correlation with PV power output,targeting both short-term and medium-term forecast *** proposed hybrid framework employs a fast trainable statistical learning technique based on the truncated-regularized kernel ridge regression *** proposed method excels in forecasting solar irradiance,especially during highly intermittent weather periods.A key strength of our model is the incorporation of multiple historical weather parameters as inputs to generate accurate predictions of future solar irradiance values in its scalable *** evaluated the performance of our model using data sets from both cloudy and sunny days in Seattle and medford,USA and compared it against three forecasting models:persistence,modified 24-hour persistence and least *** on three widely accepted statistical performance metrics(root mean squared error,mean absolute error and coefficient of determination),our hybrid model demonstrated superior predictive accuracy in varying weather conditions and forecast horizons.

关键词： solar power generation kernel ridge regression hybrid model forecasting

genetic Variability and Phenotypic Correlations Study among grain Quality Traits and mineral elements Concentrations in Colored and Non-Colored Rice (Oryza sativa L.)

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Phyton-International Journal of Experimental Botany 2024年第7期93卷 1733-1748页

作者： Adel A.Rezk mohamed m.el-malky Heba I.mohamed Hossam S.el-Beltagi Agricultural Biotechnology Department College of Agricultural and Food ScienceKing Faisal UniversityAl-Ahsa31982Saudi Arabia Plant Pathology Research Institute Agriculture Research CenterGiza12619Egypt Rice Research and Training Center Field Crop Research InstituteAgriculture Research Center33717Egypt Biological and geological Sciences Department Faculty of EducationAin Shams UniversityCairo11511Egypt Biochemistry Department Faculty of AgricultureCairo UniversityGiza12613Egypt

Twenty-four rice genotypes were examined to assess genetic variability,heritability,and correlations for seven-grain quality traits,eight nutritional elements,and *** revealed signiﬁcant differences for the quality traits *** every trait under study,the phenotypic coefﬁcient of variation was higher than the correspon-dence genotypic coefﬁcient of *** in a broad sense varied from 29.75%for grain length to 98.31%for the elongation *** percentage recovery had a highly signiﬁcant positive correlation with milling and head rice ***,milling percentage had a highly positive correlation with head rice *** amylose percentage,all the genotypes belonged to low amylose except the Hassawi-1 variety,which had intermediate amylose *** nutrition contents of m.g.esium(mg),sodium(Na),potas-sium(K),calcium(Ca),copper(Cu),manganese(mn),zinc(Zn),iron(Fe),or protein percentage gave different variations for 24 rice genotypes under all the nutritional *** the 24 genotypes,ten rice genotypes–HighNutrient-1,HighNutrient-2,HighNutrient-9,HighNutrient-8,HighNutrient-3,Hassawi-2,HighNutrient-7,HighNutrient-6,Hassawi-1,and HighNutrient-4–had the highest heist value for all nutritional and protein con-tents,and could be used as a donor to improving new *** was a positive and signiﬁcant correlation between m.g.esium mg,K,Zn and ***,K had a positive correlation with zinc Zn,Fe,and protein *** analysis was divided into two groups:theﬁrst group included all genotypes rich in nutri-ents,while the remaining genotypes with low nutritional content were included in the second group.

关键词： Amylose cluster analysis genotypes grain quality mineral nutrition rice

Cardiac arrest, stony heart, and cardiopulmonary resuscitation: An updated revisit

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World Journal of Cardiology 2024年第3期16卷 126-136页

作者： Ayman el-menyar Bianca m Wahlen Department of Trauma and Vascular Surgery Clinical ResearchHamad Medical CorporationDoha 3050Qatar Department of Clinical medicine Weill Cornell Medical CollegeDoha 24144Qatar Department of Anesthesiology Hamad Medical CorporationDoha 3050Qatar

The post-resuscitation period is recognized as the main predictor of cardiopul-monary resuscitation(CPR)*** first description of post-resuscitation syndrome and stony heart was published over 50 years *** manifestations may include but are not limited to,persistent precipitating pathology,systemic ischemia/reperfusion response,post-cardiac arrest brain injury,and finally,post-cardiac arrest myocardial dysfunction(PAmD)after successful *** do some patients initially survive successful resuscitation,and others do not?Also,why does the myocardium response vary after resuscitation?These ques-tions have kept scientists busy for several decades since the first successful resuscitation was *** modifying the conventional modalities of resu-scitation together with new promising agents,rescuers will be able to salvage the jeopardized post-resuscitation myocardium and prevent its progression to a dismal,stony *** awareness and staff education are crucial for shortening the resuscitation time and improving short-and long-term *** of these components before and early after the restoration of circulation will enhance the resuscitation *** review extensively addresses the underlying pathophysiology,management,and outcomes of post-resuscitation *** pattern,management,and outcome of PAmD and post-cardiac arrest shock are different based on many factors,including in-hospital cardiac arrest vs out-of-hospital cardiac arrest(OHCA),witnessed vs unwitnessed cardiac arrest,the underlying cause of arrest,the duration,and protocol used for *** restoring spontaneous circulation is a vital sign,it should not be the end of the game or lone primary outcome;it calls for better understanding and aggressive multi-disciplinary interventions and *** development of stony heart post-CPR and OHCA remain the main challenges in emergency and critical care medicine.

关键词： Cardiac arrest Out-of-hospital cardiac arrest In-hospital cardiac arrest Post-resuscitation myocardial dysfunction Cardiopulmonary resuscitation Stony heart

Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock mechanics and geotechnical Engineering 2024年第9期16卷 3812-3840页

作者： m.E.Al-Atroush A.E.Aboelela Ezz el-Din Hemdan Civil and Environmental Engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Department of Structural Engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and materials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Computer Science and Engineering Department Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancements in artificial intelligence(AI)have significantly *** that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled *** study undertakes a rigorous evaluation of machine learning(mL)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVms),and least squares support vector machines(LSSVms).It was found that despite mL approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these ***,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter *** extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure mechanisms Physics-informed neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

Assessment of plant diversity of endemic species of the Saharo-Arabian region in Egypt

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Journal of Arid Land 2024年第7期16卷 1000-1021,I0002-I0044页

作者： Asmaa S ABO HATAB Yassin m AL-SODANY Kamal H SHALTOUT Soliman A HAROUN mohamed m el-KHALAFY Botany and microbiology Department Faculty of ScienceKafrelsheikh UniversityKafrelsheikh 33511Egypt Botany Department Faculty of ScienceTanta UniversityTanta 31527Egypt

Savanna, semi-deserts, and hot deserts characterize the Saharo-Arabian region, which includes morocco, mauretania, Algeria, Tunisia, Libya, Egypt, Palestine, Kuwait, Saudi Arabia, Qatar, Bahrain, the United Arab Emirates, Oman, Yemen, southern Jordan, Syria, Iraq, Iran, Afghanistan, Pakistan, and northern India. Its neighboring regions, the Sudano-Zambezian region belonging to the Paleotropical Kingdom and the mediterranean and Irano-Turanian regions included in the Holarctic Kingdom, share a large portion of their flora with the Saharo-Arabian region. Despite the widespread acknowledgment of the region's global importance for plant diversity, an up to date list of the Saharo-Arabian endemics is still unavailable. The available data are frequently insufficient or out of date at both the whole global and the national scales. Therefore, the present study aims at screening and verifying the Saharo-Arabian endemic plants and determining the phytogeographical distribution of these taxa in the Egyptian flora. Hence, a preliminary list of 429 Saharo-Arabian endemic plants in Egypt was compiled from the available literature. Indeed, by excluding the species that were recorded in any countries or regions outside the Saharo-Arabian region based on different literature, database reviews, and websites, the present study has reduced this number to 126 taxa belonging to 87 genera and 37 families. Regarding the national geographic distribution, South Sinai is the richest region with 83 endemic species compared with other eight phytogeographic regions in Egypt, followed by the Isthmic Desert(the middle of Sinai Peninsula, 53 taxa). Sahara regional subzone(SS1) distributes all the 126 endemic species, Arabian regional subzone(SS2) owns 79 taxa, and Nubo-Sindian subzone(SS3) distributes only 14 endemics. Seven groups were recognized at the fourth level of classification as a result of the application of the two-way indicator species analysis(TWINSPAN) to the Saharo-Arabian endemic sp

关键词： endemism phytogeographical regions Saharo-Arabian floristic region Egyptian flora plant diversity two-way indicator species analysis(TWINSPAN)

Optimization of Cooperative Relayingmolecular Communications for Nanomedical Applications

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Computer modeling in Engineering & Sciences 2024年第2期138卷 1259-1275页

作者： Eman S.Attia Ashraf A.m.Khalaf Fathi E.Abd el-Samie Saied m.Abd el-atty Konstantinos A.Lizos Osama Alfarraj Heba m.el-Hoseny Department of electrical Engineering Faculty of EngineeringMinia UniversityMinia61111Egypt Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Informatics Faculty of Mathematics and Natural SciencesUniversity of Oslo(UiO)OsloNorway Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Computer science The Higher Future Institute for Specialized Technological StudiesEl ShoroukEgypt

Recently,nano-systems based on molecular communications via diffusion(mCvD)have been implemented in a variety of nanomedical applications,most notably in targeted drug delivery system(TDDS)***,because the mCvD is unreliable and there exists molecular noise and inter symbol interference(ISI),cooperative nano-relays can acquire the reliability for drug delivery to targeted diseased cells,especially if the separation distance between the nano transmitter and nano receiver is *** this work,we propose an approach for optimizing the performance of the nano system using cooperative molecular communications with a nano relay scheme,while accounting for blood flow effects in terms of drift *** fractions of the molecular drug that should be allocated to the nano transmitter and nano relay positioning are computed using a collaborative optimization problem solved by themodified Central Force Optimization(mCFO)*** the previous work,the probability of bit error is expressed in a closed-form *** is used as an objective function to determine the optimal velocity of the drug molecules and the detection threshold at the nano *** simulation results show that the probability of bit error can be dramatically reduced by optimizing the drift velocity,detection threshold,location of the nano-relay in the proposed nano system,and molecular drug budget.

关键词： Nanomedical system molecular communication cooperative relay optimization

A statistical approach to enhance the productivity of Streptomyces baarensis mH-133 for bioactive compounds

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Synthetic and Systems Biotechnology 2024年第2期9卷 196-208页

作者： mohamed H.Kalaba gamal m.el-Sherbiny Osama m.Darwesh Saad A.m.g.annem Botany and microbiology Department Faculty of Science(Boys)Al-Azhar UniversityCairo 11884Egypt Agricultural microbiology Department National Research CentreDokkiCairoEgypt

The goal of this study was to use statistical optimization to change the nutritional and environmental conditions so that Streptomyces baarensis mH-133 could make more active *** trials were used to screen for critical variables influencing productivity using the Placket-Burman Design *** mH-133 is significantly influenced by elicitation,yeast extract,inoculum size,and incubation period in terms of antibacterial activity.A total of 27 experimental trials with various combinations of these factors were used to carry out the response surface technique using the Box-Behnken *** analyses revealed that the model was highly significant(pmination(R2)of ***,the model predicted that the response as inhibition zone diameter would reach a value of 27 *** optimal conditions,*** mH-133 produced 18.0 g of crude extract to each 35L and was purified with column *** active fraction exhibiting antibacterial activity was characterized using spectroscopic *** mIC and mBC values varied between 37.5 and 300μg/ml and 75 and 300μg/ml,*** conclusion,the biostatistical optimization of the active fraction critical variables,including environmental and nutritional conditions,enhances the production of bioactive molecules by Streptomyces species.

关键词： S.baarensis mH-133 Placket-Burman designBox-Behnken design ESKAPE Antibacterial activity

Nonlinear wave dispersion in monoatomic chains with lumped and distributed masses:discrete and continuum models

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Applied mathematics and mechanics(English Edition) 2024年第4期45卷 633-648页

作者： E.gHAVANLOO S.el-BORgI School of mechanical Engineering Shiraz UniversityShiraz 71963-16548Iran mechanical Engineering Program Texas A&M University at QatarDoha 23874Qatar

The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed *** developed model can represent the wave propagation problem in a non-hom.g.neous material consisting of heavy inclusions embedded in a *** inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed ***,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed *** discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPm).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization *** subsequent use of the second-order method of multiple scales(mmS)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed *** novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPm for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed ***,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum *** parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.

关键词： nonlinear mass-spring chain discrete model continuum model LindstedtPoincare method(LPm) method of multiple scales(mmS) dispersion phase velocity