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Relationships between clozapine and norclozapine plasma concentrations, clozapine dose, and clinical response in Tunisian patients with schizophrenia-treatment resistance

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Open Journal of Psychiatry 2012年第4期2卷 262-268页

作者： Aida Taieb Fatma B’chir Roland Molinié José-Edmundo Nava-Saucedo Jaafer Nakhli Marc-André Fliniaux Bechir Ben Hadj Ali saad saguem Laboratory of Natural Substances National Institute of Research and Physical Chemical Analysis Technopole Sidi Thabet Metabolic Biophysics and Applied Pharmacology Laboratory Department of Biophysics Medicine Faculty of Sousse Sousse Tunisia Psychiatry Department of Central Hospital University (CHU) Sousse Tunisia Unit of Plant Biology and Insect Pests University of Picardy Jules Verne Amiens France

The present study investigated relationships between clozapine dose, clozapine and norclozapine plasma concentrations, and clinical responses to clozapine treatment in Tunisian schizophrenics. Fourteen schizophrenia-treatment resistant patients, recruited for this study, were treated with clozapine for 45 days. Patient health improvement was assessed before and after each cycle of two weeks of clozapine therapy, using the Brief Psychiatric Rating Scale (BPRS). Plasma clozapine and norclozapine concentrations were determined by high-performance liquid chromatography (HPLC). No significant correlations between plasma clozapine and norclozapine concentrations and clinical health improvement among our schizophrenic patients were found. However, a significant correlation was observed between clinical health improvement given by BPRS scores and norclozapine plasma concentration to daily clozapine dose ratio (NCZ/D). Despite the small sample size of our study, our findings suggest that the clozapine therapy response variations observed in our patients may be, in part, explained by the interindividual differences in plasma norclozapine concentration to clozapine dose ratio (NCZ/D). So the NCZ/D parameter could be used as a good indicator for adjusting the clozapine dose-adaptation strategy and consequently for improving the clinical psychopathological state of schizophrenia-treatment resistant patients.

关键词： Clozapine Norclozapine HPLC Tunisian Schizophrenic BPRS

Reinforcement Learning-Empowered Graph Convolutional Network Framework for Data Integrity Attack Detection in Cyber-Physical Systems

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 797-806页

作者： Edeh Vincent Mehdi Korki Mehdi Seyedmahmoudian Alex Stojcevski saad Mekhilef School of Science Computingand Engineering TechnologiesSwinburne University of TechnologyMelbourneAustralia

The massive integration of communication and information technology with the large-scale power grid has enhanced the efficiency, safety, and economical operation of cyber-physical systems. However, the open and diversified communication environment of the smart grid is exposed to cyber-attacks. Data integrity attacks that can bypass conventional security techniques have been considered critical threats to the operation of the grid. Current detection techniques cannot learn the dynamic and heterogeneous characteristics of the smart grid and are unable to deal with non-euclidean data types. To address the issue, we propose a novel Deep-Q-Network scheme empowered with a graph convolutional network (GCN) framework to detect data integrity attacks in cyber-physical systems. The simulation results show that the proposed framework is scalable and achieves higher detection accuracy, unlike other benchmark techniques.

关键词： Deep reinforcement learning graph convolutional network heterogeneous smart grid network

Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

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Computers, Materials & Continua 2024年第7期80卷 819-841页

作者： saad Abdalla Agaili Mohamed Sefer Kurnaz Department of Electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey

VPNs are vital for safeguarding communication routes in the continually changing cybersecurity ***,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork *** present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service *** compile a broad dataset of labeled VPN traffic flows from various apps and usage ***,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous *** effectively process and categorize encrypted packets,the neural network model has input,hidden,and output *** use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral *** also use cutting-edge optimizationmethods to optimize network characteristics and *** suggested ANN-based categorization method is extensively tested and *** show the model effectively classifies VPN traffic *** also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%*** study improves VPN security and protects against new *** VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security *** study advances network security and lays the groundwork for ANN-based cybersecurity solutions.

关键词： VPN network traffic flow ANN classification intrusion detection data exfiltration encrypted traffic feature extraction network security

RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad saad Al-Ahmadi Jalal Al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

Effect of Co on Solidification Characteristics and Microstructural Transformation of Non-equilibrium Solidified Cu-Ni Alloys

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Journal of Wuhan University of Technology(Materials Science) 2024年第2期39卷 444-453页

作者：安红恩 Bih-Lii Chua Ismail saad Willey Yun Hsien Liew Materials Engineering Research Group Faculty of EngineeringUniversity Malaysia Sabah88400 Kota KinabaluSabahMalaysia College of Mechanical and Electronic Engineering Huanghe Jiaotong UniversityJiaozuo 454950China Henan Engineering Technology Research Center on Intelligent Manufacturing Technology and Equipment Jiaozuo 454950China Centre of Research in Energy and Advanced Materials Faculty of EngineeringUniversiti Malaysia SabahJalan UMS88400 Kota KinabaluSabahMalaysia Nano Engineering and Materials Research group Faculty of EngineeringUniversity Malaysia Sabah88400 Kota KinabaluSabahMalaysia

Non-equilibrium solidification structures of Cu55Ni45 and Cu55Ni43Co2 alloys were prepared by the molten glass purification cycle superheating *** variation of the recalescence phenomenon with the degree of undercooling in the rapid solidification process was investigated using an infrared *** addition of the Co element affected the evolution of the recalescence phenomenon in Cu-Ni *** images of the solid-liquid interface migration during the rapid solidification of supercooled melts were captured by using a high-speed *** solidification rate of Cu-Ni alloys,with the addition of Co elements,was ***,the grain refinement structure with low supercooling was characterised using electron backscatter diffraction(EBSD).The effect of Co on the microstructural evolution during nonequilibrium solidification of Cu-Ni alloys under conditions of small supercooling is investigated by comparing the microstructures of Cu55Ni45 and Cu55Ni43Co2 *** experimental results show that the addition of a small amount of Co weakens the recalescence behaviour of the Cu55Ni45 alloy and significantly reduces the thermal strain in the rapid solidification *** the rapid solidification phase,the thermal strain is greatly reduced,and there is a significant increase in the characteristic undercooling ***,the addition of Co and the reduction of Cu not only result in a lower solidification rate of the alloy,but also contribute to the homogenisation of the grain size.

关键词： non-equilibrium solidification recalescence effect solidification character microstructure

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1339-1370页

作者： Ali S.Alghamdi Mohamed A.Zohdy saad Aldoihi Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and Space Science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer Science and Systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

An Adaptive Hate Speech Detection Approach Using Neutrosophic Neural Networks for Social Media Forensics

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Computers, Materials & Continua 2024年第4期79卷 243-262页

作者： Yasmine M.Ibrahim Reem Essameldin saad M.Darwish Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandria21526Egypt Faculty of Computers and Information Technology Egyptian E-Learning University(EELU)Giza12611Egypt Faculty of Computers and Data Science Alexandria UniversityAlexandria21554Egypt

Detecting hate speech automatically in social media forensics has emerged as a highly challenging task due tothe complex nature of language used in such platforms. Currently, several methods exist for classifying hatespeech, but they still suffer from ambiguity when differentiating between hateful and offensive content and theyalso lack accuracy. The work suggested in this paper uses a combination of the Whale Optimization Algorithm(WOA) and Particle Swarm Optimization (PSO) to adjust the weights of two Multi-Layer Perceptron (MLPs)for neutrosophic sets classification. During the training process of the MLP, the WOA is employed to exploreand determine the optimal set of weights. The PSO algorithm adjusts the weights to optimize the performanceof the MLP as fine-tuning. Additionally, in this approach, two separate MLP models are employed. One MLPis dedicated to predicting degrees of truth membership, while the other MLP focuses on predicting degrees offalse membership. The difference between these memberships quantifies uncertainty, indicating the degree ofindeterminacy in predictions. The experimental results indicate the superior performance of our model comparedto previous work when evaluated on the Davidson dataset.

关键词： Hate speech detection whale optimization neutrosophic sets social media forensics

A Framework for Enhancing Privacy and Anonymity in Blockchain-Enabled IoT Devices

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Computers, Materials & Continua 2024年第3期78卷 4263-4282页

作者： Muhammad saad Muhammad Raheel Bhutta Jongik Kim Tae-Sun Chung Department of Artificial Intelligence Ajou UniversitySuwon443-749Korea Department of Electrical and Computer Engineering University of Utah Asia CampusIncheon21985Korea Department of Artificial Intelligence Chungnam National UniversityDaejeon34134Korea

With the increase in IoT(Internet of Things)devices comes an inherent challenge of *** the world today,privacy is the prime concern of every *** one’s privacy and keeping anonymity throughout the system is a desired functionality that does not come without inevitable trade-offs like scalability and increased complexity and is always exceedingly difficult to *** challenge is keeping confidentiality and continuing to make the person innominate throughout the *** address this,we present our proposed architecture where we manage IoT devices using blockchain *** proposed architecture works on and off blockchain integrated with the closed-circuit television(CCTV)security camera fixed at the rental *** this framework,the CCTV security camera feed is redirected towards the owner and renter based on the smart contract *** entity(owner or renter)can see the CCTV security camera feed at one *** is no third-party dependence except for the CCTV security camera deployment *** contributions include the proposition of framework architecture,a novel smart contract algorithm,and the modification to the ring signatures leveraging an existing cryptographic *** are made based on different systems’security and key management *** an empirical study,our proposed algorithm performed better in key generation,proof generation,and verification *** comparing similar existing schemes,we have shown the proposed architectures’*** now,we have developed this system for a specific area in the real ***,this system is scalable and applicable to other areas like healthcare monitoring systems,which is part of our future work.

关键词： Privacy anonymity blockchain IoT smart contracts

Improved combustion stability of biogas at different CO_(2) concentrations using inhomogeneous partially premixed stratified flames

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Global Energy Interconnection 2024年第4期7卷 486-502页

作者： Mohy saad Mansour Maged Kiriakos Lili Hao Mohamed Amr Serag-Eldin Mechanical Power Engineering Department Cairo University1 Gamaa StreetCairo Governorate 12613Egypt Mechanical Engineering Department The American University in CairoAUC AveCairo Governorate 11835Egypt College of Electrical Engineering and Control Science Nanjing Tech UniversityNanjing 211816P.R.China

Biogas is a renewable and clean energy source that plays an important role in the current environment of lowcarbon *** high-content CO_(2) in biogas can be separated,transformed,and utilized,it not only realizes high-value utilization of biogas but also promotes carbon reduction in the biogas *** improve the combustion stability of biogas,an inhomogeneous,partially premixed stratified(IPPS)combustion model was adopted in this *** thermal flame structure and stability were investigated for a wide range of mixture inhomogeneities,turbulence levels,CO_(2) concentrations,air-to-fuel velocity ratios,and combustion energies in a concentric flow slot burner(CFSB).A fine-wire thermocouple is used to resolve the thermal flame *** flame size was reduced by increasing the CO_(2) concentration and the flames became lighter *** flame temperature also decreased with increase in CO_(2) *** stability was reduced by increasing the CO_(2) ***,at a certain level of mixture inhomogeneity,the concentration of CO_(2) in the IPPS mode did not affect the ***,the IPPS mode of combustion should be suitable for the combustion and stabilization of *** should support the design of highly stabilized biogas turbulent flames independent of CO_(2) *** data show that the lower stability conditions are partially due to the change in fuel combustion energy,which is characterized by the Wobbe index(WI).In addition,at a certain level of mixture inhomogeneity,the effect of the WI on flame stability becomes dominant.

关键词： Biogas Renewable energy Effect of CO_(2) Combustion stability Burner design Renewable fuels Partial premixed