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The Anxiolytic and Antidepressant Effect of Stachys Lavandulifolia in the Experimental Pentylenetetrazole-Induced Rat Model of Acute Seizure

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World Journal of Traditional Chinese Medicine 2024年第1期10卷 114-120页

作者： Vahid Azizi Farzin Allahyari Abdolkarim Hosseini department of Animal sciences Faculty of Life Sciences and BiotechnologyShahid Beheshti UniversityTehranIran

Objective:In traditional medicine,Stachys lavandulifolia or mountain tea has been used in the treatment of arthritis and rheumatoid arthritis.A leaf extract from this plant is also thought to be effective in treating epilepsy as well as other neurological *** assess the effect of *** extract(SLE),rats were exposed to a stress and anxiety model caused by *** and Methods:A challenge dose of pentylenetetrazole(PTZ)(60 mg/kg)was used to induce seizures in male Wistar rats(200-250 g).Animal treated with an intraperitoneal injection of either SLE(50 mg/kg)or sodium valproate(100 mg/kg)alone or in combination 30 min before PTZ *** effect of stress and anxiety was assessed using an open field test(OFT),forced swim test(FST),and elevated plus maze(EPM).At the end of the experiment,anesthesia was used to euthanize rats,and their blood serum was collected for measurements of glutathione(GSH),malondialdehyde(MDA),and GSH peroxidase(GPx).Results:In contrast to the control group,those treated with PTZ exhibited depressive *** 50 mg/kg,SLE provided protection against seizures induced by *** also reduced seizure-induced stress and anxiety,significantly improving FST,EPM,and OFT compared with the PTZ-treated *** decreasing MDA levels and restoring the antioxidant enzymes GSH and GPx,SLE treatment protects against seizure-induced anxiety and ***:SLE inhibits oxidative stress damage and seizure-induced stress by inhibiting seizures'inhibitory effects.

关键词： Anxiety behavior depression oxidative stress traditional medicine

On Polar Decomposition of Tensors with Einstein Product and a Novel Iterative Parametric Method

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Numerical Mathematics(Theory,Methods and Applications) 2024年第1期17卷 69-92页

作者： Raziyeh Erfanifar Masoud Hajarian Khosro Sayevand department of Applied Mathematics Faculty of Mathematical SciencesShahid Beheshti UniversityTehranIran Faculty of Mathematics and Statistics Malayer UniversityMalayerIran

This study aims to investigate the polar decomposition of tensors with the Einstein product for theﬁrst *** polar decomposition of tensors can be computed using the singular value decomposition of the tensors with the Einstein *** the following,some iterative methods forﬁnding the polar decomposi-tion of matrices have been developed into iterative methods to compute the polar decomposition of ***,we propose a novel parametric iterative method toﬁnd the polar decomposition of *** the obtained conditions,we prove that the proposed parametric method has the order of convergence *** every iteration of the proposed method,only four Einstein products are required,while other iterative methods need to calculate multiple Einstein products and one tensor inversion in each ***,the new method is superior in terms of efﬁciency ***,the numerical comparisons performed among several well-known methods,show that the proposed method is remarkably efﬁcient and accurate.

关键词： Iterative methods Einstein product polar decomposition of a tensor polar factor order of convergence

A Novel Iterative Method to Find theMoore-Penrose Inverse of a Tensor with Einstein Product

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Numerical Mathematics(Theory,Methods and Applications) 2024年第1期17卷 37-68页

In this study,based on an iterative method to solve nonlinear equations,a third-order convergent iterative method to compute the Moore-Penrose inverse of a tensor with the Einstein product is presented and *** compar-isons of the proposed method with other methods show that the average number of iterations,number of the Einstein products,and CPU time of our method are considerably less than other *** some applications,partial and fractional differential equations that lead to sparse matrices are considered as *** use the iterates obtained by the method as a preconditioner,based on tensor form to solve the multilinear system A∗N X=***,several practical numerical examples are also given to display the accuracy and efﬁciency of the new *** presented results show that the proposed method is very robust for obtaining the Moore-Penrose inverse of tensors.

关键词： Tensor iterative methods Moore-Penrose inverse Einstein product

Electrospun Aloe Vera Extract Loaded Polycaprolactone Scaffold for Biomedical Applications:A Promising Candidate for Corneal Stromal Regeneration

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Journal of Bionic Engineering 2024年第4期21卷 1949-1959页

作者： Amin Orash Mahmoud Salehi Mohammad Rafienia Narsimha Mamidi Saeed Heidari Keshel Alireza Baradaran-Rafii department of Chemistry and Nanotechnology School of Engineering and ScienceTecnologico de MonterreyMonterreyNuevo Leon64849Mexico Biosensor Research Center Isfahan University of Medical SciencesIsfahan81746-73461Iran Wisconsin Center for NanoBioSystems School of PharmacyUniversity of Wisconsin-MadisonMadisonWisconsin53705USA Medical Nanotechnology Research Center Shahid Beheshti University of Medical SciencesTehran19857-17443Iran department of Ophthalmology Ophthalmic Research CenterLabbafinejad Medical CenterShahid Beheshti University of Medical SciencesTehran19395-4631Iran department of Ophthalmology Morsani College of MedicineUniversity of South FloridaTampaFL33612USA department of Tissue Engineering and Applied Cell Science School of Advanced Technologies in MedicineShahid Beheshti University of Medical SciencesTehran19857-17443Iran

Corneal diseases,the second leading cause of global vision loss affecting over 10.5 million people,underscores the unmet demand for corneal tissue *** the scarcity of fresh donor corneas and the associated risks of immune rejection,corneal tissue engineering becomes *** nanofibrous scaffolds that mimic the natural corneal structure is crucial for creating transparent and mechanically robust corneal equivalents in tissue ***,Aloe Vera Extract(AVE)/Polycaprolactone(PCL)nanofibrous scaffolds were primed using *** electrospun AVE/PCL fibers exhibit a smooth,bead-free morphology with a mean diameter of approximately 340±95 nm and appropriate light *** measurements reveal Young’s modulus and ultimate tensile strength values of around 3.34 MPa and 4.58 MPa,respectively,within the range of stromal *** addition,cell viability of AVE/PCL fibers was measured against Human Stromal Keratocyte Cells(HSKCs),and improved cell viability was *** cell-fiber interactions were investigated using scanning electron *** conclusion,the incorporation of Aloe Vera Extract enhances the mechanical,optical,hydrophilic,and biological properties of PCL fibers,positioning PCL/AVE fiber scaffolds as promising candidates for corneal stromal regeneration.

关键词： Corneal stromal regeneration Aloe vera extract Polycaprolactone Electrospinning

Evaluating the characteristics of geological structures in karst groundwater inflow, Nowsud Tunnel

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Journal of Mountain Science 2024年第10期21卷 3434-3452页

作者： BAYAT Narges SADEGHI Erfan NASSERY Hamid Reza department of Minerals and Groundwater Resources Faculty of Earth SciencesShahid Beheshti UniversityEvin AveTehran ***Iran Ministry of Energy Kordestan ExpyTehran ***Iran

Highly permeable geological structures such as dissolution channels, open fractures, and faults create environmental challenges regard to hydrological and hydrogeological aspects of underground construction, often causing significant groundwater inflow during drilling due to the limitations of empirical and analytical methods. This study aims to identify the geological factors influencing water flow into the tunnel. High-flow zones' geological features have been identified and examined for this purpose. According to the geological complexity of the Nowsud tunnel, presence of different formations with different permeability and karstification have led to a high volume of underground inflow water (up to 4700 L/s) to the tunnel. The Nowsud tunnel faces significant geological and hydrogeological challenges due to its passage through the Ilam formation's LI2 unit, characterized by dissolution channels, faults, and fractures. The highest inflow rate (4700 L/s) occurred in the Hz-9 zone within the Zimkan anticline. The relationship between geological features and groundwater inflow indicates that anticlines are more susceptible to inflow than synclines. Additionally, different types of faults exhibit varying hydraulic effects, with strike-slip faults having the most significant impact on groundwater inflow, thrust faults conducting less water into the tunnel, and inflow through normal faults being negligible compared to the other two types of faults. The novelty of this paper lies in its detailed analysis of geological features influencing groundwater inflow into the Nowsud tunnel, providing empirical data on high-flow zones and differentiating the hydraulic effects of various fault types, which enhances the understanding and prediction of groundwater inflow in underground constructions.

关键词： Geological structures Groundwater inflow Hydrogeology Nowsud tunnel Karst

Rice Husk at a Glance:From Agro-Industrial to Modern Applications

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Rice science 2024年第1期31卷 14-32页

作者： Masoumeh KORDI Naser FARROKHI Martin I.PECH-CANUL Asadollah AHMADIKHAH department of Cell&Molecular Biology Faculty of Life Sciences and BiotechnologyShahid Beheshti UniversityTehran ***Iran 1062 Metallurgical Industry Avenue Industrial Park Saltillo-Ramos ArizpeRamos ArizpeCoahuila 25900Mexico

Excessive waste production has led to the concept of a circular bioeconomy to deliver valuable by-products and improve environmental *** annual worldwide rice production accounts for more than 750 million tons of grain and 150 million tons of *** husk(RH)contains valuable biomaterials with extensive applications in various *** proportions of each component depend primarily on rice genotype,soil chemistry,and climatic *** and its derivatives,including ash,biochar,hydrochar,and activated carbon have been placed foreground of applications in agriculture and other *** the investigation on RH’s compositions,microstructures,and by-products has been done copiously,owing to its unique features,it is still an open-ended area with enormous scope for innovation,research,and ***,we reviewed the latest applications of RH and its derivatives,including fuel and other energy resources,construction materials,pharmacy,medicine,and nanobiotechnology to keep this versatile biomaterial in the spotlight.

关键词： circular bioeconomy rice husk activated carbon rice husk ash rice husk biochar rice husk hydrochar rice husk application

An Online Fake Review Detection Approach Using Famous Machine Learning Algorithms

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computers, Materials & Continua 2024年第2期78卷 2767-2786页

作者： Asma Hassan Alshehri department of computer sciences College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl KharjSaudi Arabia

Online review platforms are becoming increasingly popular,encouraging dishonest merchants and service providers to deceive customers by creating fake reviews for their goods or *** Sybil accounts,bot farms,and real account purchases,immoral actors demonize rivals and advertise their *** academic and industry efforts have been aimed at detecting fake/fraudulent product or service evaluations for *** primary hurdle to identifying fraudulent reviews is the lack of a reliable means to distinguish fraudulent reviews from real *** paper adopts a semi-supervised machine learning method to detect fake reviews on any website,among other *** reviews are classified using a semi-supervised approach(PU-learning)since there is a shortage of labeled data,and they are ***,classification is performed using the machine learning techniques Support Vector Machine(SVM)and Nave *** performance of the suggested system has been compared with standard works,and experimental findings are assessed using several assessment metrics.

关键词： Security fake review semi-supervised learning ML algorithms review detection

Novel Framework for an Intrusion Detection System Using Multiple Feature Selection Methods Based on Deep Learning

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Tsinghua Science and Technology 2024年第4期29卷 948-958页

作者： A.E.M.Eljialy Mohammed Yousuf Uddin Sultan Ahmad department of Information Systems College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia department of computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection systems (IDSs) are deployed to detect anomalies in real time. They classify a network’s incoming traffic as benign or anomalous (attack). An efficient and robust IDS in software-defined networks is an inevitable component of network security. The main challenges of such an IDS are achieving zero or extremely low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with minimal resources. This situation makes deploying traditional IDSs in IoT networks unfeasible. Machine learning (ML) techniques are extensively applied to build robust IDSs. Many researchers have utilized different ML methods and techniques to address the above challenges. The development of an efficient IDS starts with a good feature selection process to avoid overfitting the ML model. This work proposes a multiple feature selection process followed by classification. In this study, the Software-defined networking (SDN) dataset is used to train and test the proposed model. This model applies multiple feature selection techniques to select high-scoring features from a set of features. Highly relevant features for anomaly detection are selected on the basis of their scores to generate the candidate dataset. Multiple classification algorithms are applied to the candidate dataset to build models. The proposed model exhibits considerable improvement in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost

Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

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computers, Materials & Continua 2024年第1期78卷 1189-1205页

作者： K.Akilandeswari Nithya Rekha Sivakumar Hend Khalid Alkahtani Shakila Basheer Sara Abdelwahab Ghorashi department of computer sciences Government Arts College(Autonomous)Salem636007India department of computer sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

In this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and *** exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and *** many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during ***,this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning(SPR-SVIAL)for Smart Healthcare *** first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction ***,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable *** attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced *** that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and *** evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several *** quantitatively analyzed results indicate the better performance of our proposed SPR-SVIAL method when compared with two state-of-the-art methods.

关键词： Internet of Things smart health care monitoring human activity recognition intelligent agent learning statistical partial regression support vector