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Techno-Economic Optimization of Novel Stand-Alone Renewable Based Electric Vehicle Charging Station near Bahria Town Karachi,Sindh Pakistan

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Energy Engineering 2024年第6期121卷 1439-1457页

作者： Aneel kumar Mahesh kumar Amir Mahmood Soomro Laveet kumar Department of Electrical Engineering Mehran University of Engineering and TechnologyJamshoroPakistan Department of Mechanical Engineering Mehran University of Engineering and TechnologyJamshoroPakistan

Electric vehicles (EVs) are the most interesting and innovative technology in the 21st century because of theirenormous advantages, both technically and economically. Their emissions rate compared to fuel-based vehicles isnegligible as they do not consume fuel and hence do not emit any harmful gases. However, their bulk production,adoption and lack of charging stations increase the stress of power stations due to modern-day lifestyles. If Electricvehicles demand increases drastically then conventional power stations will not bear their demand and if theygenerate electricity by conventional means it will be very costly and may further add greenhouse gases. Therefore,this research provides the techno-economic assessment of a stand-alone renewable-dependent electric vehiclecharging station, excluding any burden on electrical utility. The proposed study is carried out in Bahria Town,Karachi, a city in Pakistan. In this study, HOMER Pro software was utilized for techno-economic assessment. Ahybrid system comprising solar Photovoltaic/Wind Turbine/Fuel cells and battery storage is included in the *** and wind resources were taken from NASA’s website, where charging stations will be integrated. The overallresults show promising in terms of total Net Present Cost and the Cost of Energy which are 2.72M $ and 0.237 $,respectively. The total system generation is 3,598 Megawatt hours per year, and the total energy consumption is 885Megawatt hours per year.

关键词： Electrical vehicle techno economic analysis solar energy wind energy hydrogen energy

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Prediction of bearing capacity of pile foundation using deep learning approaches

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Frontiers of Structural and Civil Engineering 2024年第6期18卷 870-886页

作者： Manish kumar Divesh Ranjan kumar Jitendra KHATTI Pijush SAMUI Kamaldeep Singh GROVER Department of Civil Engineering SRM Institute of Science and Technology Tiruchirappalli CampusTrichy 621105India Department of Civil Engineering National Institute of Technology PatnaBihar 800005India Department of Civil Engineering Faculty of EngineeringThammasat School of EngineeringThammasat UniversityBangkok10200Thailand Department of Civil Engineering Rajasthan Technical UniversityKota 324010India

The accurate prediction of bearing capacity is crucial in ensuring the structural integrity and safety of pile *** research compares the Deep Neural Networks(DNN),Convolutional Neural Networks(CNN),Recurrent Neural Networks(RNN),Long Short-Term Memory(LSTM),and Bidirectional LSTM(BiLSTM)algorithms utilizing a data set of 257 dynamic pile load tests for the first ***,this research illustrates the multicollinearity effect on DNN,CNN,RNN,LSTM,and BiLSTM models’performance and accuracy for the first time.A comprehensive comparative analysis is conducted,employing various statistical performance parameters,rank analysis,and error matrix to evaluate the performance of these *** performance is further validated using external validation,and visual interpretation is provided using the regression error characteristics(REC)curve and Taylor *** from the comparative analysis reveal that the DNN(Coefficient of determination(R^(2))_(training(TR))=0.97,root mean squared error(RMSE)_(TR)=0.0413;R^(2)_(testing(TS))=0.9,RMSE_(TS)=0.08)followed by BiLSTM(R^(2)_(TR)=0.91,RMSE_(TR)=0.782;R^(2)_(TS)=0.89,RMSE_(TS)=0.0862)model demonstrates the highest performance *** is noted that the BiLSTM model is better than LSTM because the BiLSTM model,which increases the amount of information for the network,is a sequence processing model made up of two LSTMs,one of which takes the input in a forward manner,and the other in a backward *** prediction of pile-bearing capacity is strongly influenced by ram weight(having a considerable multicollinearity level),and the effect of the considerable multicollinearity level has been determined for the model based on the recurrent neural network *** this study,the recurrent neural network model has the least performance and accuracy in predicting the pile-bearing capacity.

关键词： deep learning algorithms high-strain dynamic pile test bearing capacity of the pile

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Identification of optimal composition with superior electrochemical properties along the zero Mn^(3+)line in Na_(0.75)(Mn-Al-Ni)O_(2)pseudo ternary system

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Journal of Energy Chemistry 2024年第9期96卷 206-216页

作者： Hari Narayanan Vasavan Manish Badole Samriddhi Saxena Velaga Srihari Asish kumar Das Pratiksha Gami Neha Dagar Sonia Deswal Pradeep kumar Himanshu kumar Poswal Sunil kumar Department of Metallurgical Engineering and Materials Science Indian Institute of Technology IndoreSimrol 453552India High Pressure&Synchrotron Radiation Physics Division Bhabha Atomic Research Centre400085 MumbaiIndia School of Physical Sciences Indian Institute of Technology MandiHimachal Pradesh 175005India Center for Electric Vehicle and Intelligent Transport Systems Indian Institute of Technology IndoreSimrol 453552India

Biphasic layered oxide cathodes,known for their superior electrochemical performance,are prime candidates for commercializing in Na-ion ***,we unveil a series of P3/P2 monophasic and biphasic Al-substituted Na_(3/4)Mn_(5-x/8)Al_(2x/8)Ni_(3-x/8)O_(2)layered oxide cathodes that lie along the‘zero Mn^(3+)line’in the Na_(3/4)(Mn-Al-Ni)O_(2)pseudo-ternary *** structural analysis showed a larger Na^(+)conduction bottleneck area in both P3 and P2 structures with a higher Al3+content,which enhanced their rate *** each composition,the P3/P2 biphasic compound with nearly equal fractions of P3 and P2 phases outperformed their monophasic counterparts in almost all electrochemical performance *** synchrotron XRD measurements obtained for the monophasic P3 and biphasic P2/P3 samples revealed the absence of the O3 phase during *** high structure stability and faster Na^(+)transport kinetics in the biphasic samples underpins the enhancement of electrochemical properties in the Al-substituted P3/P2 *** results highlight fixed oxidation state lines as a novel tool to identify and design layered oxide cathodes for Na-ion batteries in pseudo-ternary diagrams involving Jahn-Teller active cations.

关键词： Layered oxides Biphasic cathode Operando Synchrotron XRD Electrochemical behavior Cyclic performance

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A Cocktail of Natural Compounds Holds Promise for New Immunotherapeutic Potential in Head and Neck Cancer

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Chinese Journal of Integrative Medicine 2024年第1期30卷 42-51页

作者： Sunil kumar Asmita Das Department of Biotechnology Delhi Technological UniversityDelhi(110042)India

Objective: To obtain detailed understanding on the gene regulation of natural compounds in altering prognosis of head and neck squamous cell carcinomas(HNSC). Methods: Gene expression data of HNSC samples and peripheral blood mononuclear cells(PBMCs) of HNSC patients were collected from Gene Expression Omnibus(GEO). Differential gene expression analysis of GEO datasets were achieved by the GEO2R tool. Common differentially expressed gerres(DEGs) were screened by comparing DEGs of HNSC with those of PBMCs. The combination was further analyzed for regulating pathways and biological processes that were affected. Results: Totally 110 DEGs were retrieved and identified to be involved in biological processes related to tumor regulation. Then 102 natural compounds were screened for a combination such that the expressions of all 110 commonly DEGs were altered. A combination of salidroside, ginsenoside Rd, oridonin, britanin, and scutellarein was chosen. A multifaceted, multi-dimensional tumor regression was showed by altering autophagy, apoptosis, inhibiting cell proliferation, angiogenesis, metastasis and inflammatory cytokines production. Conclusions: This study has helped develop a unique combination of natural compounds that will markedly reduce the propensity of development of drug resistance in tumors and immune evasion by tumors. The result is crucial to developing a combinatorial natural therapeutic cocktail with accentuated immunotherapeutic potential.

关键词： natural compounds chemopreventive gene expression head and neck cancer immunomodulator salidroside ginsenoside Rd oridonin britanin scutellarein

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Thermodynamic properties and phase diagram of quark matter within non-extensive Polyakov chiral SU(3)quark mean field model

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Chinese Physics C 2024年第5期48卷 60-71页

作者： Dhananjay Singh Arvind kumar Department of Physics Dr.B R Ambedkar National Institute of Technology JalandharJalandhar–144008PunjabIndia

In the present study,we applied Tsallis non-extensive statistics to investigate the thermodynamic properties and phase diagram of quark matter in the Polyakov chiral SU(3)quark mean field *** this model,the properties of the quark matter were modified through the scalar fieldsσ,ζ,δ,χ,vector fieldsω,ρ,ϕ,and Polyakov fieldsΦandΦ¯at finite temperature and chemical ***-extensive effects were introduced through a dimensionless parameter q,and the results were compared to those of the extensive case(q→1).In the non-extensive case,the exponential in the Fermi-Dirac(FD)function was modified to a q-exponential *** influence of the q parameter on the thermodynamic properties,pressure,energy,and entropy density,as well as trace anomaly,was *** speed of sound and specific heat with non-extensive effects were also ***,the effect of non-extensivity on the deconfinement phase transition as well as the chiral phase transition of u,d,and s quarks was *** found that the critical end point(CEP),which defines the point in the(T−μ)phase diagram where the order of the phase transition changes,shifts to a lower value of temperature,TCEP,and a higher value of chemical potential,μCEP,as the non-extensivity is increased,that is,q>1.

关键词： quark matter quark mean field model QCD phase diagram non-extensive statistics

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A Bayesian multi-model inference methodology for imprecise momentindependent global sensitivity analysis of rock structures

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第3期16卷 840-859页

作者： Akshay kumar Gaurav Tiwari Department of Civil Engineering Indian Institute of Technology(IIT)KanpurKanpur208016India

Traditional global sensitivity analysis(GSA)neglects the epistemic uncertainties associated with the probabilistic characteristics(*** of distribution type and its parameters)of input rock properties emanating due to the small size of datasets while mapping the relative importance of properties to the model *** paper proposes an augmented Bayesian multi-model inference(BMMI)coupled with GSA methodology(BMMI-GSA)to address this issue by estimating the imprecision in the momentindependent sensitivity indices of rock structures arising from the small size of input *** methodology employs BMMI to quantify the epistemic uncertainties associated with model type and parameters of input *** estimated uncertainties are propagated in estimating imprecision in moment-independent Borgonovo’s indices by employing a reweighting approach on candidate probabilistic *** proposed methodology is showcased for a rock slope prone to stress-controlled failure in the Himalayan region of *** proposed methodology was superior to the conventional GSA(neglects all epistemic uncertainties)and Bayesian coupled GSA(B-GSA)(neglects model uncertainty)due to its capability to incorporate the uncertainties in both model type and parameters of *** Borgonovo’s indices estimated via proposed methodology provide the confidence intervals of the sensitivity indices instead of their fixed-point estimates,which makes the user more informed in the data collection *** performed with the varying sample sizes suggested that the uncertainties in sensitivity indices reduce significantly with the increasing sample *** accurate importance ranking of properties was only possible via samples of large ***,the impact of the prior knowledge in terms of prior ranges and distributions was significant;hence,any related assumption should be made carefully.

关键词： Bayesian inference Multi-model inference Statistical uncertainty Global sensitivity analysis(GSA) Borgonovo’s indices Limited data

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Pharmacological potential of Manilkara zapota(L.)***(Sapodilla):a narrative review

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Journal of Traditional Chinese Medicine 2024年第2期44卷 403-407页

作者： Priyanka Sharma Aakash Deep Harish kumar Nitin Bansal Sanjiv kumar Arun Davinder kumar Department of Pharmaceutical Sciences Chaudhary Bansi Lal UniversityBhiwani 127021India Department of Pharmaceutical Sciences Maharishi Dayanand UniversityRohtak 124001India

Herbal medicine is safe and effective in treating various *** herbal medicine plays a tremendous role in treatment of various diseases and accompanying complications,hence herbal medicine requires remarkable attention in further research for the development of numerous active formulations for treatment of health *** plant needs special consideration for development and research of unidentified compound and characterization of novel active molecules that overcome multiple pathological *** genus Manilkara contains 135 plants around the *** overview discusses all the virtues of most important and commonly used plant Manilkara zapota(L.)***(***),also known as *** has various traditional beneficial effects in treatment of various diseases and disorders dating back to prehistoric times and used in ancient traditional system of herbal medicine.

关键词： herbal medicine Manilkara zapota phytoconstituents pharmacological activity review

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An inverse analysis of fluid flow through granular media using differentiable lattice Boltzmann method

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 2077-2090页

作者： Qiuyu Wang Krishna kumar Department of Civil Architectural and Environmental EngineeringUniversity of Texas at AustinAustin78712-2100USA

This study presents a method for the inverse analysis of fluid flow *** focus is put on accurately determining boundary conditions and characterizing the physical properties of granular media,such as permeability,and fluid components,like *** primary aim is to deduce either constant pressure head or pressure profiles,given the known velocity field at a steady-state flow through a conduit containing obstacles,including walls,spheres,and *** lattice Boltzmann method(LBM)combined with automatic differentiation(AD)(AD-LBM)is employed,with the help of the GPU-capable Taichi programming language.A lightweight tape is used to generate gradients for the entire LBM simulation,enabling end-to-end *** AD-LBM approach accurately estimates the boundary conditions for complex flow paths in porous media,leading to observed steady-state velocity fields and deriving macro-scale permeability and fluid *** method demonstrates significant advantages in terms of prediction accuracy and computational efficiency,making it a powerful tool for solving inverse fluid flow problems in various applications.

关键词： Inverse problem Fluid flow Granular media Automatic differentiation(AD) Lattice Boltzmann method(LBM)

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Automatic Rule Discovery for Data Transformation Using Fusion of Diversified Feature Formats

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Computers, Materials & Continua 2024年第7期80卷 695-713页

作者： G.Sunil Santhosh kumar M.Rudra kumar Department of CSE Jawaharlal Nehru Technological UniversityAnantapur515002India Department of CSE Marri Laxman Reddy Institute of Technology and ManagementHyderabad500043India Department of Information Technology Mahatma Gandhi Institute of TechnologyHyderabad500075India

This article presents an innovative approach to automatic rule discovery for data transformation tasks leveraging XGBoost,a machine learning algorithm renowned for its efficiency and *** framework proposed herein utilizes the fusion of diversified feature formats,specifically,metadata,textual,and pattern *** goal is to enhance the system’s ability to discern and generalize transformation rules fromsource to destination formats in varied ***,the article delves into the methodology for extracting these distinct features from raw data and the pre-processing steps undertaken to prepare the data for the *** sections expound on the mechanism of feature optimization using Recursive Feature Elimination(RFE)with linear regression,aiming to retain the most contributive features and eliminate redundant or less significant *** core of the research revolves around the deployment of the XGBoostmodel for training,using the prepared and optimized feature *** article presents a detailed overview of the mathematical model and algorithmic steps behind this ***,the process of rule discovery(prediction phase)by the trained XGBoost model is explained,underscoring its role in real-time,automated data *** employingmachine learning and particularly,the XGBoost model in the context of Business Rule Engine(BRE)data transformation,the article underscores a paradigm shift towardsmore scalable,efficient,and less human-dependent data transformation *** research opens doors for further exploration into automated rule discovery systems and their applications in various sectors.

关键词： XGBoost business rule engine machine learning categorical query language humanitarian computing environment

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DNACDS:Cloud IoE big data security and accessing scheme based on DNA cryptography

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Frontiers of Computer Science 2024年第1期18卷 157-170页

作者： Ashish SINGH Abhinav kumar Suyel NAMASUDRA School of Computer Engineering KIIT Deemed to be UniversityBhubaneshwar 751024India Department of Computer Science and Engineering Indian Institute of Information Technology SuratSurat 394190India Department of Computer Science and Engineering National Institute of Technology AgartalaAgartala 799046India

The Internet of Everything(IoE)based cloud computing is one of the most prominent areas in the digital big data *** approach allows efficient infrastructure to store and access big real-time data and smart IoE services from the *** IoE-based cloud computing services are located at remote locations without the control of the data *** data owners mostly depend on the untrusted Cloud Service Provider(CSP)and do not know the implemented security *** lack of knowledge about security capabilities and control over data raises several security *** Acid(DNA)computing is a biological concept that can improve the security of IoE big *** IoE big data security scheme consists of the Station-to-Station Key Agreement Protocol(StS KAP)and Feistel cipher *** paper proposed a DNA-based cryptographic scheme and access control model(DNACDS)to solve IoE big data security and access *** experimental results illustrated that DNACDS performs better than other DNA-based security *** theoretical security analysis of the DNACDS shows better resistance capabilities.

关键词： IoE based cloud computing DNA cryptography IoE big data security StS KAP feistel cipher IoE big data access

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