检索结果-南通市图书馆

Journal of Systems Science & Complexity 2020年第6期33卷 1804-1846页

作者： al-HUSSEIN AbdulRahman GHERBal Boulakhras Department of Mathematics College of ScienceQassim UniversityBuraydah 51452Saudi Arabia Laboratory of Mathematical Analysis Probability and OptimizationUniversity of Mohamed KhiderBiskrua07000Algeria

This paper derives necessary and sufficient conditions of optimality in the form of a stochastic maximum principle for relaxed and strict optimal control problems with *** problems are governed by multi-dimensional forward-backward doubly stochastic differential equations(FBDSDEs)with Poisson jumps and has firstly relaxed controls,which are measure-valued processes,and secondly,as an application,the authors allow them to have strict *** FBDSDEs with jumps are fully-coupled,the forward and backward equations work in different Euclidean spaces in general,the backward equation is Markovian,and the control problems are considered under full information or partial information in terms ofσ-algebras that provide such *** formulation of these equations as well as performance functionals are given in abstract forms to allow the possibility to cover most of the applications available in the ***,coefficients of such equations are allowed to depend on control variables.

关键词： Adjoint equations forward-backward doubly stochastic differential equations maximum principle necessary conditions Poisson process relaxed control strict control sufficient conditions

Heat shock protein 90 is a potential therapeutic target for ameliorating skeletal muscle abnormalities in Parkinson's disease

在线全文

学校读者我要写书评

暂无评论

Neural Regeneration Research 2014年第6期9卷 616-621页

作者： Nour Erekat Ahed al-Khatib Muhammed al-Jarrah Department of Anatomy Faculty of Medicine Jordan University of Science and Technology (JUST) Department of Pathology Faculty of Medicine Jordan University of Science and Technology Department of Rehabilitation Sciences Faculty of Applied Medical Sciences Jordan University of Science and Technology Fatima College of Health Sciences (FCHS)

Previous studies have confirmed that heat shock protein 90 overexpression can lead to dopami- nergic neuronal death. This study was designed to further investigate what effects are produced by heat shock protein 90 after endurance exercise training. Immunohistochemistry results showed that exercise training significantly inhibited heat shock protein 90 overexpression in the soleus and gastrocnemius in Parkinson＇s disease rats, which is a potential therapeutic target for ameliorating skeletal muscle abnormalities in Parkinso^s disease.

关键词： nerve regeneration heat shock protein 90 Parkinson's disease exerecise soleus muscle gastrocnemius muscle skeletal muscle treadmill excise neural regeneration

Rocket “Eruca sativa”:A salad herb with potential gastric anti-ulcer activity

在线全文

学校读者我要写书评

暂无评论

World Journal of Gastroenterology 2009年第16期15卷 1958-1965页

作者： Saleh alqasoumi Mohammed al-Sohaibani Tawfeq al-Howiriny Mohammed al-Yahya Syed Rafatullah Department of Pharmacognosy and Medicinal Aromatic and Poisonous Plants Research CenterCollege of PharmacyPO Box 2457King Saud University Department of Pathology (32) PO Box 2925King Khalid University HospitalKing Saud University

AIM： To validate gastric anti-ulcer properties of Rocket ＂Eruca sativa＂ on experimentally-induced gastric secretion and ulceration in albino rats. METHODS： Gastric acid secretion studies were undertaken using pylorus-ligated rats. Gastric lesions in the rats were induced by noxious chemicals including ethanol, strong alkalis, indomethacin and hypothermic restraint stress. The levels of gastric wall mucus （GWM）, nonprotein sulfhydryls （NP-SH） and malondialdehyde （MDA） were also measured in the glandular stomach of rats following ethanol administration. The gastric tissue was also examined histologically. The extract was used in two doses （250 and 500 mg/kg body weight） in all experiments. RESULTS： In pylorus-ligated Shay rats, the ethanolic extract of Rocket ＂Eruca sativa L.＂（EER） significantly and dose-dependently reduced the basal gastric acid secretion, titratable acidity and ruminal ulceration. Rocket extract significantly attenuated gastric ulceration induced by necrotizing agents （80% ethanol, 0.2 mol/L NaOH, 25% NaCl）, indomethacin and hypothermic restraint stress. The anti-ulcer effect was further confirmed histologically. On the other hand, the extract significantly replenished GWM and NP-SH levels, as well as the MDA level significantly reduced by extract pretreatment. CONCLUSION： Rocket extract possesses antisecretory, cytoprotective, and anti-ulcer activities against experimentally-induced gastric lesions. The anti-ulcer effect is possibly through prostaglandinmediated activity and/or through its anti-secretory and antioxidant properties.

关键词： Cytoprotection Eruca sativa Gastric ulcer and secretion Malondialdehyde Rocket Sulfhydryls

Neurotrophin receptors,gamma-secretase inhibitors,and neurodegeneration of basal forebrain cholinergic neurons

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Neural Regeneration Research 2022年第7期17卷 1493-1494页

作者： Marçal Vilar Instituto de Biomedicina de València del CSIC ValènciaSpain

The amyloid hypothesis of alzhemer’s disease(AD)postulates that the generation of amyloid-beta(Aβ)peptide from the amyloid precursor protein(APP)by the action of theγ-secretase complex is one of the principal causes of *** idea is supported by the identification of several hereditary mutations in the APP gene or in the PSEN1 and PSEN2 genes that encode Presenilin-1 and Presenilin-2.

关键词： amyloid Aβ cholinergic

Artificial Intelligence Techniques Based Learner Authentication in Cybersecurity Higher Education Institutions

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第8期72卷 3131-3144页

作者： Abdullah Saad al-Malaise al-Ghamdi Mahmoud Ragab Information Systems Department Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt

Education 4.0 is being authorized more and more by the design of artificial intelligence(AI)*** education institutions(HEI)have started to utilize Internet technologies to improve the quality of the service and boost *** to the unavailability of information technology(IT)infrastructures,HEI is vulnerable to *** authentication can be used to authenticate a person based on biological features such as face,fingerprint,iris,and so *** study designs a novel search and rescue optimization with deep learning based learning authentication technique for cybersecurity in higher education institutions,named SRODLLAC *** proposed SRODL-LAC technique aims to authenticate the learner/student in HEI using fingerprint ***,the SRODLLACtechnique designs a median filtering(MF)based preprocessing approach to improving the quality of the *** addition,the Densely Connected Networks(DenseNet-77)model is applied for the extraction of ***,search and rescue optimization(SRO)algorithm with deep neural network(DNN)model is utilized for the classification ***,template matching process is done for fingerprint identification.A wide range of simulation analyses is carried out and the results are inspected under several *** experimental results reported the effective performance of the SRODL-LAC technique over the other methodologies.

关键词： Cybersecurity authentication biometrics security higher education institution deep learning

Numerical investigation of Dufour and Soret effects on unsteadyMHD natural convection flow past vertical plate embedded innon-Darcy porous medium

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Applied Mathematics and Mechanics(English Edition) 2012年第2期33卷 195-210页

作者： M.Q.al-ODAT A.al-GHAMDI Mechanical Engineering Department Faculty of EngineeringUmm Al-Qura UniversityMakkahKingdom of Saudi Arabia Mechanical Engineering Department Al-Huson University CollegeAl-Balqa Applied UniversityIrbidJordan

The Dufour and Soret effects on the unsteady twodimensional magnetonyaro dynamics （MHD） doublediffusive free convective flow of an electrically conducting fluid past a vertical plate embedded in a nonDarcy porous medium are investigated numeri cally. The governing nonlinear dimensionless equations are solved by an implicit finite difference scheme of the CrankNicolson type with a tridiagonal matrix manipulation. The effects of various parameters entering into the problem on the unsteady dimension less velocity, temperature, and concentration profiles are studied in detail. Furthermore, the time variation of the skin friction coefficient, the Nusselt number, and the Sherwood number is presented and analyzed. The results show that the unsteady velocity, tem perature, and concentration profiles are substantially influenced by the Dufour and Soret effects. When the Dufour number increases or the Soret number decreases, both the skin friction and the Sherwood number decrease, while the Nusselt number increases. It is found that, when the magnetic parameter increases, the velocity and the temperature decrease in the boundary layer.

关键词： double-diffusive free convection non-Darcy model magnetohydrodynamic(MHD) porous medium Dufour effect Soret effect numerical solution

Effect of elevated temperature and silica sand particle size on minimum fluidization velocity in an atmospheric bubbling fluidized bed

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Chemical Engineering 2020年第12期28卷 2985-2992页

作者： A.al-Farraji Haidar Taofeeq Chemical Engineering Department College of EngineeringAl-Nahrain UniversityBaghdadIraq Prosthetics and Orthotics Engineering Department College of EngineeringAl-Nahrain UniversityBaghdadIraq

The impact of temperature and particle size on minimumfluidizing velocity was studied and analyzed in a small pilot scale of bubbling fluidized bed *** study was devoted to providing some data about fluidization to the literature under high temperature *** experiments were carried out to evaluate the minimum fluidizing velocity over a vast range of temperature levels from 20℃ to 850℃ using silica sand with a particle size of 300-425μm,425-500μm,500-600μm,and 600-710μ***,the variation in the minimumfluidized voidage was determined experimentally at the same *** experimental data revealed that the Umf directly varied with particle size and inversely with temperature,whileεmf increases slightly with temperature based on the measurements of height at incipient ***,for all particle sizes used in this test,temperatures above 700℃ has a marginal effect on *** results were compared with many empirical equations,and it was found that the experimental result is still in an acceptable range of empirical equations *** which,our findings are not well predicted by the widely accepted correlations reported in the ***,a new predicted equation has been developed that also accounts for the affecting of mean particle size in addition to other parameters.A good mean relative deviation of 5.473% between the experimental data and the predicted values was estimated from the correlation of the effective dimensionless ***,the experimental work revealed that the minimum fluidizing velocity was not affected by the height of the bed even at high temperature.

关键词： Minimum fluidization velocity Voidage Elevated temperature Silica sand Fluidized bed Bed height

A Hybrid Neural Network-based Approach for Forecasting Water Demand

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第10期73卷 1365-1383页

作者： al-Batool al-Ghamdi Souad Kamel Mashael Khayyat Department of Computer Science and Artificial Intelligence College of Computer Sciences and EngineeringUniversity of JeddahJeddah 21959Saudi Arabia Department of Computer and Network Engineering College of Computer Sciences and EngineeringUniversity of JeddahJeddah 21959Saudi Arabia Department of Information Systems and Technology College of Computer Sciences and EngineeringUniversity of JeddahJeddah 21959Saudi Arabia

Water is a vital *** supports a multitude of industries,civilizations,and ***,climatic conditions impact water availability,particularly in desert areas where the temperature is high,and rain is ***,it is crucial to forecast water demand to provide it to sectors either on regular or emergency *** study aims to develop an accurate model to forecast daily water demand under the impact of climatic *** forecasting is known as a multivariate time series because it uses both the historical data of water demand and climatic conditions to forecast the *** on the collected data of Jeddah city,Saudi Arabia in the period between 2004 and 2018,we develop a hybrid approach that uses Artificial Neural Networks(ANN)for forecasting and Particle Swarm Optimization algorithm(PSO)for tuning ANNs’*** on the Root Mean Square Error(RMSE)metric,results show that the(PSO-ANN)is an accurate model for multivariate time series ***,the first day is the most difficult day for prediction(highest error rate),while the second day is the easiest to predict(lowest error rate).Finally,correlation analysis shows that the dew point is the most climatic factor affecting water demand.

关键词： Water demand forecasting artificial neural network multivariate time series climatic conditions particle swarm optimization hybrid algorithm

A New Optimized Wrapper Gene Selection Method for Breast Cancer Prediction

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第6期67卷 3089-3106页

作者： Heyam H.al-Baity Nourah al-Mutlaq Department of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

Machine-learning algorithms have been widely used in breast cancer diagnosis to help pathologists and physicians in the decision-making ***,the high dimensionality of genetic data makes the classification process a challenging *** this paper,we propose a new optimized wrapper gene selection method that is based on a nature-inspired algorithm(simulated annealing(SA)),which will help select the most informative genes for breast cancer *** optimal genes will then be used to train the classifier to improve its accuracy and *** supervised machine-learning algorithms,namely,the support vector machine,the decision tree,and the random forest were used to create the classifier models that will help to predict breast *** different experiments were conducted using three datasets:Gene expression(GE),deoxyribonucleic acid(DNA)methylation,and a combination of the *** measures were used to evaluate the performance of the proposed algorithm,which include the following:Accuracy,precision,recall,specificity,area under the curve(AUC),and execution *** effectiveness of the proposed classifiers was evaluated through comprehensive *** results demonstrated that our approach outperformed the conventional classifiers as expected in terms of accuracy and execution *** accuracy values of 99.77%,99.45%,and 99.45%have been achieved by SA-SVM for GE,DNA methylation,and the combined datasets,*** execution time of the proposed approach was significantly reduced,in comparison to that of the traditional classifiers and the best execution time has been reached by SA-SVM,which was 0.02,0.03,and 0.02 on GE,DNA methylation,and the combined datasets *** regard to precision and specificity,SA-RF obtained the best result of 100 on GE *** SA-SVM attained the best recall result of 100 on GE dataset.

关键词： Breast cancer simulated annealing feature selection classification gene expression DNA methylation DNA microarray

Developing a Model for Parkinson’s Disease Detection Using Machine Learning algorithms

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第6期79卷 4945-4962页

作者： Naif al Mudawi Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia

Parkinson’s disease(PD)is a chronic neurological condition that progresses over *** start to have trouble speaking,writing,walking,or performing other basic skills as dopamine-generating neurons in some brain regions are injured or *** patient’s symptoms become more severe due to the worsening of their signs over *** this study,we applied state-of-the-art machine learning algorithms to diagnose Parkinson’s disease and identify related risk *** research worked on the publicly available dataset on PD,and the dataset consists of a set of significant characteristics of *** aim to apply soft computing techniques and provide an effective solution for medical professionals to diagnose PD *** research methodology involves developing a model using a machine learning *** the model selection,eight different machine learning techniques were adopted:Namely,Random Forest(RF),Decision Tree(DT),Support Vector Machine(SVM),Naïve Bayes(NB),Light Gradient Boosting Machine(LightGBM),K-Nearest Neighbours(KNN),Extreme Gradient Boosting(XGBoost),and Logistic Regression(LR).Subsequently,the concentrated models were validated through 10-fold Cross-Validation and Receiver Operating Characteristic(ROC)—Area Under the Curve(AUC).In addition,GridSearchCV was utilised to measure each algorithm’s best parameter;eventually,the models were trained through the hyperparameter tuning *** 98%accuracy,LightGBM had the highest accuracy in this ***,KNN,and SVM came in second with 96%***,the performance scores of NB and LR were recorded to be 76%and 83%,*** is to be mentioned that after applying 10-fold cross-validation,the average performance score of LightGBM accounted for 93%.At the same time,the percentage of ROC-AUC appeared at 0.92,which indicates that this LightGBM model reached a satisfactory ***,we extracted meaningful insights and figured out potential gaps on top of *** extracting meaningful in

关键词： Light GBM cross-validation ROC-AUC Parkinson’s disease(PD) SVM and XGBoost