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metabolic complications of psychotropic medications in psychiatric disorders:Emerging role of de novo lipogenesis and therapeutic consideration

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World Journal of Psychiatry 2024年第6期14卷 767-783页

作者： m.ham.ad m.khan Zaw Ali khan mohsin Ali khan Laboratory of Translational Neurology and molecular Psychiatry Department of BiotechnologyEra’s Lucknow Medical College and Hospitaland Faculty of ScienceEra UniversityLucknow 226003India Era’s Lucknow medical College and Hospital Era UniversityLucknow 226003India

Although significant advances have been made in understanding the pathophysiology of psychiatric disorders(PDs),therapeutic advances have not been very *** psychotropic medications can reduce classical symptoms in patients with PDs,their long-term use has been reported to induce or exaggerate various pre-existing metabolic abnormalities including diabetes,obesity and non-alcoholic fatty liver disease(NAFLD).The mechanism(s)underlying these metabolic abnormalities is not clear;however,lipid/fatty acid accumulation due to enhanced de novo lipogenesis(DNL)has been shown to reduce membrane fluidity,increase oxidative stress and inflammation leading to the development of the aforementioned metabolic ***,emerging evidence suggest that DNL dysregulation and fatty acid accumulation could be the major mechanisms associated with the development of obesity,diabetes and NAFLD after long-term treatment with psychotropic medications in patients with *** support of this,several adjunctive drugs comprising of anti-oxidants and antiinflammatory agents,that are used in treating PDs in combination with psychotropic medications,have been shown to reduce insulin resistance and development of *** conclusion,the above evidence suggests that DNL could be a potential pathological factor associated with various metabolic abnormalities,and a new avenue for translational research and therapeutic drug designing in PDs.

关键词： Psychotropic medications metabolic complications De novo lipogenesis Obesity Diabetes Non-alcoholic fatty liver disease

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Enhancement of coercivity,permeability,and dielectric properties of Co_(0.2)Zn_(0.3)Ni_(0.5)Eu_(x)Fe_(2-x)O_(4) ferrites for memory and high frequency devices

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Journal of Rare Earths 2024年第6期42卷 1128-1135,I0005页

作者： I.Sardar m.D.Hossain m.S.Sikder m.N.I.khan m.R.Rahman Physics Discipline Khulna UniversityKhulna9208Bangladesh Department of Physics Khulna University of Engineering&TechnologyKhulna9203Bangladesh Department ofComputer Science and Engineering Northern University of Business&Technology KhulnaKhulna9100Bangladesh material Science Division Atomic Energy CentreDhaka1000Bangladesh

Spinel cubic ferrites have huge applications in me mory and high frequency *** the improvement of these modern devices,the magnetic coercivity,permeability,and dielectric properties of a ferrite are the important *** article focuses on improving the magnetic coercivity,magnetic permeability,and dielectric properties of Co_(0.2)Zn_(0.3)Ni_(0.5)Eu_(x)Fe_(2-x)O_(4) ferrites,where x=0.00,0.06,and *** X-ray diffraction(XRD),Fourier transform infrared spectroscopy(FTIR),field emission scanning electron microscopy(FESEm),energy dispersive X-ray(EDX),vibrating sample magnetometer(VSm),and an impedance analyzer were used to characterize the structural,magnetic,and dielectric properties of the *** XRD patterns indicate the formation of spinel cubic structure of the samples with a secondary peak(EuFeO_(3))for Eu doped *** densities and porosities of the samples follow an inverse trend,where the doped samples’lattice parameters are increased with the increment of rare earth Eu *** FTIR analysis also proves the spinel cubic phase of the *** average grain size of the ferrites is obtained via FESEm images,and it is increased from 121 to 198 *** analysis confirms that doping of the Eu content also changes other hysteresis loop properties of Co_(0.2)Zn_(0.3)Ni_(0.5)Eu_(x)Fe_(2-x)O_(4) ***,the coercivity of the Eu doped samples is greater than that of the mother alloy(x=0.00).The EDX study shows that there is no impurity contamination in the *** permeability and dielectric measurements show an improved quality factor of the Eu-doped samples with low magnetic and dielectric *** dependent resistivity and impedance analysis also show the improved *** the observed properties of the samples,all the investigated ferrites might be strong candidates for potential applications in memory devices,magnetic sensors,and high frequency applications.

关键词： Ferrites Raree arths Coercivity Permeability EDX Resistivity

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Acceleration of solar wind particles due to inertial Alfvén waves

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Communications in Theoretical Physics 2024年第6期76卷 137-141页

作者： Kiran Batool Imran A khan m Shamir Abdul Kabir S Ayaz Theoretical Physics Department National Centre for PhysicsIslamabad 44000Pakistan Department of Space Sciences Institute of Space TechnologyIslamabad 44000Pakistan Space and Astrophysics Research Lab(SARL) National Center of GIS and Space Applications(NCGSA)Islamabad 44000Pakistan Salam Chair Department of PhysicsGC University LahoreKatchery RoadLahorePunjab 54000Pakistan Department of Space Science and CSPAR University of Alabama in HuntsvilleHuntsvilleAL 35899United States of America

Gaining an understanding of the effects and dynamics of the solar wind is crucial for the study of space weather,Earth's magnetosphere,spacecraft protection,the dynamics of the Solar System,and various other *** show that Alfvén waves effectively transfer energy to resonant *** study demonstrates how inertial Alfvén waves deliver their energy to resonant plasma particles in different solar environments under certain *** analysis shows that inertial Alfvén waves experience more rapid damping with increasing parallel wavenumber,ambient magnetic field strength,and particle number density,coupled with a decrease in *** rate of energy transfer to resonant particles intensifies with higher temperatures and reduced parallel wavenumber and particle number *** with higher initial velocities actively participate in Landau damping,especially in regions with a stronger ambient magnetic field.

关键词： solar wind inertial Alfven waves resonant particles

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Cervical Cancer Prediction Empowered with Federated machine Learning

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Computers, materials & Continua 2024年第4期79卷 963-981页

作者： m.ham.ad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy m.A.khan khan m.ham.ad adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi20009UAE Department of Computing Skyline University CollegeSharjah999041UAE Department of Computer Science Taibah UniversityMedina42315Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam13120Korea

Cervical cancer is an intrusive cancer that imitates various women around the world. Cervical cancer ranks in thefourth position because of the leading death cause in its premature stages. The cervix which is the lower end of thevagina that connects the uterus and vagina forms a cancerous tumor very slowly. This pre-mature cancerous tumorin the cervix is deadly if it cannot be detected in the early stages. So, in this delineated study, the proposed approachuses federated machine learning with numerous machine learning solvers for the prediction of cervical cancer totrain the weights with varying neurons empowered fuzzed techniques to align the neurons, Internet of medicalThings (IomT) to fetch data and blockchain technology for data privacy and models protection from hazardousattacks. The proposed approach achieves the highest cervical cancer prediction accuracy of 99.26% and a 0.74%misprediction rate. So, the proposed approach shows the best prediction results of cervical cancer in its early stageswith the help of patient clinical records, and all medical professionals will get beneficial diagnosing approachesfrom this study and detect cervical cancer in its early stages which reduce the overall death ratio of women due tocervical cancer.

关键词： Cervical cancer federated machine learning neurons blockchain technology

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Classification and technical target of water electrolysis for hydrogen production

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Journal of Energy Chemistry 2024年第8期95卷 554-576,I0012页

作者： Kahyun ham Sooan Bae Jaeyoung Lee Ertl Center for Electrochemistry and Catalysis Gwangju Institute of Science and Technology(GIST)123 Cheomdangwagi-RoBuk-guGwangju 61005South Korea Department of Heterogeneous Reactions Max Planck Institute for Chemical Energy ConversionStiftstr.34-36Mülheim an der RuhrGermany School of Earth Sciences and Environmental Engineering GIST123 CheomdangwagiroBuk-guGwangju 61005South Korea International Future Research Center of Chemical Energy Storage and Conversion Processes GIST123 CheomdangwagiroBuk-guGwangju 61005South Korea eSuS Co. Ltd.#408S6 BuildingSchool of Environment and Energy EngineeringGIST123 CheomdangwagiroBuk-guGwangju 61005South Korea

Continuous efforts are underway to reduce carbon emissions worldwide in response to global climate *** electrolysis technology,in conjunction with renewable energy,is considered the most feasible hydrogen production technology based on the viable possibility of large-scale hydrogen production and the zero-carbon-emission nature of the ***,for hydrogen produced via water electrolysis systems to be utilized in various fields in practice,the unit cost of hydrogen production must be reduced to$1/kg H_(2).To achieve this unit cost,technical targets for water electrolysis have been suggested regarding components in the *** this paper,the types of water electrolysis systems and the limitations of water electrolysis system components are *** suggest guideline with recent trend for achieving this technical target and insights for the potential utilization of water electrolysis technology.

关键词： Water electrolysis Hydrogen production Technical target Electrochemistry

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Dust particle surface potential in an argonhelium plasma using the(r,q)-distribution function

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Communications in Theoretical Physics 2024年第9期76卷 141-148页

作者： Bahaaudin m Raffah A A Abid Abdullah khan Amin Esmaeili Yas Al-Hadeethi m N S Qureshi Department of Physics Faculty of SciencesKing Abdulaziz UniversityJeddah 21589Saudi Arabia Lithography in Devices Fabrication and Development Research Group Deanship of Scientific ResearchKing Abdulaziz UniversityJeddah 21589Saudi Arabia Joint Laboratory of Plasma Application Technology Institute of Advanced TechnologyUniversity of Science and Technology of ChinaHefei230026China CAS Key Laboratory of Geospace Environment University of Science and Technology of ChinaHefei230026China Department of Physics Zhejiang Normal UniversityJinhua321005China Department of Physics Graduate School of ScienceTokyo Metropolitan UniversityMinami-Osawa 1-1Hachioji City192-0397Japan Department of Physics GC UniversityLahore 54000Pakistan

In this paper,the dust particle surface potential for argon-helium plasma is evaluated analytically and numerically in the context of negatively charged dust particles by employing a power-law(r,q)-distribution *** studies have reported the argon-helium plasma and conducted a brief theoretical and experimental *** deepen our understanding further,this study aims to analyze the argon-helium plasma comprehensively using the same pattern but with the(r,q)-distribution *** this purpose,the current balance equations are derived for electron,helium and argon ions,when these charge species attain the quasineutrality *** numerically examined the currents of plasma species for a broad range of effective distribution function parameters r and *** is revealed that the surface potential of dust particles is significantly affected by the parameters r and q,helium ion-to-electron temperature ratio,argon ion-to-electron temperature ratio,and helium ion to argon ion number density *** incorporating the multi-ion(argon-helium)species,the significance of low-temperature nonmaxwellian dusty(complex)plasma is briefly examined.

关键词： dusty plasma dust charge potential plasma physics helium argon plasma r q distribution function non-maxwellian distribution

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machine learning-based multi-objective optimization and thermal assessment of supercritical CO_(2) Rankine cycles for gas turbine waste heat recovery

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Energy and AI 2024年第2期16卷 363-384页

作者： Asif Iqbal Turja Ishtiak Ahmed khan Sabbir Rahman Ashraf mustakim m.ham.ad Ishraq Hossain m monjurul Ehsan Yasin khan Department of mechanical and Production Engineering(mPE) Islamic University of Technology(IUT)Board BazarGazipur1704Bangladesh

Technologies for utilizing waste heat for power generation have attracted significant attention in recent years due to their potential to enhance energy efficiency and reduce greenhouse gas *** research focuses on the comparative and optimization analysis of three supercritical carbon dioxide(sCO_(2))Rankine cycles(simple,cascade,and split)for gas turbine waste heat *** study begins with parametric analysis,investigating the significant effects of key variables,including turbine inlet temperature,condenser inlet temperature,and pinch point temperature,on the thermal performance of advanced sCO_(2) power *** identify the most efficient cycle configuration,a multi-objective optimization approach is *** approach combines a Genetic Algorithm with machine learning regression models(Random Forest,XGBoost,Artificial Neural Network,Ridge Regression,and K-Nearest Neighbors)to predict cycle performance using a dataset extracted from cycle *** decision-making process for determining the optimal cycle configuration is facilitated by the TOPSIS(technique for order of preference by similarity to the ideal solution)*** study's major findings reveal that the split cycle outperforms the simple and cascade configurations in terms of power generation across various operating *** optimized split cycle not only demonstrates superior power output but also exhibits enhanced net power output,heat recovery,system and exergy efficiency of 7.99 mW,76.17%,26.86%and 57.96%,respectively,making it a promising choice for waste heat recovery *** research has the potential to contribute to the advancement and widespread adoption of waste heat recovery in energy technologies boosting system efficiency and economic *** provides a new perspective for future research,contributing to the improvement of energy generation infrastructure.

关键词： Supercritical co2 Rankine cycle Waste heat recovery Gas turbine Thermodynamic analysis machine Learning Optimization

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multi-objective performance optimization&thermodynamic analysis of solar powered supercritical CO_(2)power cycles using machine learning methods&genetic algorithm

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Energy and AI 2024年第1期15卷 193-216页

作者： Asif Iqbal Turja md mahmudul Hasan m.monjurul Ehsan Yasin khan Department of mechanical and Production Engineering(mPE) Islamic University of Technology(IUT)Board BazarGazipur1704Bangladesh

The present study is focused on multi-objective performance optimization&thermodynamic analysis from the perspectives of energy and exergy for Recompression,Partial Cooling&main Compression Intercooling supercritical CO_(2)(sCO_(2))Brayton cycles for concentrated solar power(CSP)applications using machine learning *** novelty of this work lies in the integration of artificial neural networks(ANN)and genetic algorithms(GA)for optimizing the performance of advanced sCO_(2)power cycles considering climatic variation,which has significant implications for both the scientific community and engineering applications in the renewable energy *** methodology employed includes thermodynamic analysis based on energy,exergy&environmental factors including system performance *** system is modelled for net power production of 15 mW thermal output utilizing equations for the energy and exergy balance for each ***,thermodynamic model extracted dataset used for prediction&evaluation of Random Forest,XGBoost,KNN,adaBoost,ANN and LightGBm ***,considering climate conditions,multi-objective optimization is carried out for the CSP integrated sCO_(2)Power cycle for optimal power output,exergy destruction,thermal and exergetic *** algorithm and TOPSIS(technique for order of preference by similarity to ideal solution),multi-objective decision-making tool,were used to determine the optimum operating *** major findings of this work reveal significant improvements in the performance of the advanced sCO_(2)cycle by 1.68%and 7.87%compared to conventional recompression and partial cooling cycle,*** research could advance renewable energy technologies,particularly concentrated solar power,by improving power cycle designs to increase system efficiency and economic *** advanced supercritical CO_(2)power cycles in concentrated solar power plants might increase renewable energy use

关键词： Supercritical CO_(2) Concentrated solar power Thermodynamic analysis machine learning Artificial neural network multi-objective optimization

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Analysis of travelling wave solutions of double dispersive sharma-Tasso-Olver equation

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Journal of Ocean Engineering and Science 2024年第5期9卷 461-474页

作者： Kamruzzaman khan Henk Koppelaar m.Ali Akbar Syed Tauseef mohyud-Din Department of mathematics Pabna University of Science and TechnologyPabna 6600Bangladesh Fac.of Electrical Eng. Mathematics and Comp.ScienceUniversity of DelftNetherlands Department of Applied mathematics University of RajshahiRajshahi 6205Bangladesh Department of mathematics HITEC University Taxila CanttPakistan School of Science and Technology University of New EnglandArmidaleNSW 2351Australia

Travelling wave solutions have been played a vital role in demonstrating the wave character of nonlinear problems arising in the field of ocean engineering and *** describe the propagation of the nonlinear wave phenomenon in the ocean(for example,wind waves,tsunami waves),a variety of evolution equations have been suggested and investigated in the existing *** paper studies the dynamic of travelling periodic and solitary wave behavior of a double-dispersive non-linear evolution equation,named the Sharma-Tasso-Olver(STO)*** evolution equations with double dispersion enable us to describe nonlinear wave propagation in the ocean,hyperplastic rods and other mediums in the field of science and *** analyze the wave solutions of this model using a combination of numerical simulations and Ansatz *** analysis shows that the travelling wave solutions involve a range of parameters that displays important and very interesting properties of the wave *** relevance of the parameters in the travelling wave solutions is also *** simulating numerically,we demonstrate how parameters in the solutions influence the phase speed as well as the travelling and solitary ***,we discuss instantaneous streamline patterns among the obtained solutions to explore the local direction of the components of the obtained solitary wave solutions at each point in the coordinate(x,t).

关键词： Travelling wave Solitary wave Streamline Enhanced(G'/G)-expansion method STO equation

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Potential of eNose Technology for monitoring Biological CO2 Conversion Processes

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Transactions of Tianjin University 2024年第5期30卷 381-394页

作者： m.ham.ad Awais Syed m.ham.ad Zaigham Abbas Naqvi Sami Ullah khan m.Ijaz khan Sherzod Abdullaev Junfeng Wu Wei Zhang Jiandong Hu Department of Electrical Engineering Henan Agricultural University Henan International Joint Laboratory of Laser Technology in Agriculture Sciences State Key Laboratory of Wheat and maize Crop Science Department of mathematics Namal University Department of mechanical Engineering Prince Mohammad Bin Fahd University Faculty of Chemical Engineering New Uzbekistan University Scientific and Innovation Department Tashkent State Pedagogical University

Electronic nose（eNose） is a modern bioelectronic sensor for monitoring biological processes that convert CO2into valueadded products, such as products formed during photosynthesis and microbial fermentation. eNose technology uses an array of sensors to detect and quantify gases, including CO2, in the air. This study briefly introduces the concept of eNose technology and potential applications thereof in monitoring CO2conversion processes. It also provides background information on biological CO2conversion processes. Furthermore, the working principles of eNose technology vis-à-vis gas detection are discussed along with its advantages and limitations versus traditional monitoring methods. This study also provides case studies that have used this technology for monitoring biological CO2conversion processes. eNose-predicted measurements were observed to be completely aligned with biological parameters for R2values of 0.864, 0.808, 0.802, and 0.948. We test eNose technology in a variety of biological settings, such as algae farms or bioreactors, to determine its effectiveness in monitoring CO2conversion processes. We also explore the potential benefits of employing this technology vis-à-vis monitoring biological CO2conversion processes, such as increased reaction efficiency and reduced costs versus traditional monitoring methods. moreover, future directions and challenges of using this technology in CO2capture and conversion have been discussed. Overall, we believe this study would contribute to developing new and innovative methods for monitoring biological CO2conversion processes and mitigating climate change.

关键词： Bioelectronic nose Biological monitoring CO2 conversion Electronic nose (eNose) Gas detection

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