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Nano Research 2022年第4期15卷 2905-2912页

作者： Song-Song Peng Xiang-Bin Shao Yu-Xia Li Yao Jiang Chen Gu manish kumar dinker Xiao-Qin Liu(✉) Lin-Bing Sun State Key Laboratory of Materials-Oriented Chemical Engineering Jiangsu National Synergetic Innovation Center for Advanced Materials(SICAM)College of Chemical EngineeringNanjing Tech University30 South Puzhu RoadNanjing 211816China

Ordered porous solid strong bases(OPSSBs)have attracted great research interest due to the excellent performance as heterogeneous catalysts in various *** main obstacle for fabricating OPSSBs is the requirement of high temperature to produce strong basicity on ordered porous *** example,the temperatures of 600-650℃ are required for the decomposition of base precursor NaNO_(3)to basic sites on mesoporous silica SBA-15 and zeolite *** high decomposition temperatures are energy-intensive and harmful to the structure of ***,we report the fabrication of OPSSBs by utilizing the redox interaction between base precursor and low-valence metal centers(e.g.,Cr^(3+))in metal-organic frameworks(MOFs).The base precursor NaNO_(3)on MIL-101(Cr)can be converted to basic sites entirely at 300℃,which is quite lower than those of the conventional thermal conversion on SBA-15 and zeolite Y(600-650℃).The exploration on decomposition mechanism reveals that the valence change of Cr^(3+)to Cr^(6+)takes place during the conversion of NaNO_(3)to basic *** this way,MOFs-derived base catalysts have been synthesized successfully by the host-guest redox strategy and exhibit high catalytic activity in typical base-catalyzed reactions.

关键词： metal-organic frameworks ordered porous solid strong bases host–guest redox interaction transesterification reaction Cr centers

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

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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Endoscopic ultrasound-guided pancreatic fluid collection drainage: Where are we?

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World Journal of Gastrointestinal Endoscopy 2024年第6期16卷 273-281页

作者： Anupam kumar Singh manish Manrai Rakesh Kochhar Department of Gastroenterology Postgraduate Institute of Medical Education and ResearchChandigarh 160012India Department of Gastroenterology Command HospitalLucknow 226002India Department of Gastroenterology Paras HospitalPanchkula 134109India

Pancreatic fluid collections(PFCs)result from injury to the pancreas from acute or chronic pancreatitis,surgery,or *** of these collections has evolved over the last 2 *** choice of interventions includes percu-taneous,endoscopic,minimally invasive surgery,or a combined *** drainage is the drainage of PFCs by creating an artificial communication between the collection and gastrointestinal lumen that is maintained by placing a stent across the fistulous *** this editorial,we endeavored to update the current status of endoscopic ultrasound-guided drainage of PFCs.

关键词： Pancreatic fluid collections Endoscopic ultrasound-guided drainage Endoscopic necrosectomy Lumen apposing metal stent Review

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钒技术在难减排行业和能源转型中的作用评估

钢铁钒钛 2024年第4期45卷 84-94页

作者： David ASantos manish KDixit Pranav Pradeep kumar Sarbajit Banerjee 德克萨斯农工大学化学系德克萨斯农工大学材料科学和工程系德克萨斯农工大学建筑科学系德克萨斯农工大学土木与环境工程学院

重工业的减碳和可再生能源技术的出现皆与获得矿物资源有着密不可分的联系。因此，迫切需要对关键元素在减少温室气体排放方面的作用进行基准评估。考察了钒作为微合金元素在建筑碳减排以及作为电网储能用液流电池的主要成分在能源转型... 详细信息

重工业的减碳和可再生能源技术的出现皆与获得矿物资源有着密不可分的联系。因此，迫切需要对关键元素在减少温室气体排放方面的作用进行基准评估。考察了钒作为微合金元素在建筑碳减排以及作为电网储能用液流电池的主要成分在能源转型中的作用。研究结果表明，钒可使每年减少总计1.85亿t碳排放。其中，中国和欧盟的减排幅度分别为各自排放量的1.15%和0.18%。研究结果强调了关键金属在发展低碳基础设施中的作用，同时指出了进行全面评估并施加政策干预减轻供应链风险的必要性。

关键词：钒微合金化液流电池碳减排

Species richness,phylogenetic diversity and phylogenetic structure patterns of exotic and native plants along an elevational gradient in the Himalaya

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Ecological Processes 2021年第1期10卷 877-889页

作者： kumar manish Department of Environmental Studies Dr.Bhim Rao Ambedkar CollegeUniversity of DelhiDelhiIndia

Background:So far,macroecological studies in the Himalaya have mostly concentrated on spatial variation of overall species richness along the elevational *** few studies have attempted to document the diference in elevational richness patterns of native and exotic *** this study,this knowledge gap is addressed by integrating data on phylogeny and elevational distribution of species to identify the variation in species richness,phylogenetic diversity and phylogenetic structure of exotic and native plant species along an elevational gradient in the ***:Species distribution patterns for exotic and native species difered;exotics tended to show maximum species richness at low elevations while natives tended to predominate at *** species assemblages showed higher phylogenetic diversity than the exotic species assemblages over the entire elevational gradient in the *** terms of phylogenetic structure,exotic species assemblages showed majorly phylogenetic clustering while native species assemblages were characterized by phylogenetic overdispersion over the entire ***:The fndings of this study indicate that areas with high native species richness and phylogenetic diversity are less receptive to exotic species and vice versa in the *** assemblages with high native phylogenetic overdispersion are less receptive to exotic species than the phylogenetically clustered *** ecological processes(ecological fltering in case of exotics and resource and niche competition in case of natives)may govern the distribution of exotic and native species along the elevational gradient in the Himalaya.

关键词： Exotic species Native species Himalaya Elevational gradient Richness pattern

A Novel Approach for Enhancement of Geometric and Contrast Resolution Properties of Low Contrast Images

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 628-638页

作者： Koushlendra kumar Singh manish kumar Bajpai Rajesh kumar Pandey Department of Computer Science and Engineering National Institute of Technology Jamshedpur 831014 India Indian Institute of Information Technology Design & Manufacturing Jabalpur MP 482005 India Department of Mathematical Sciences In- dian Institute of Technology Varanasi U.P. 221005 India

The present work encompasses a new image enhancement algorithm using newly constructed Chebyshev fractional order differentiator. We have used Chebyshev polynomials to design Chebyshev fractional order differentiator. We have generated the high pass filter corresponding to it. The designed filters are applied for decomposing the input image into four bands and low-low(L-L) sub-band is updated using correction coefficients. Reconstructed image with updated L-L sub-band provides the enhanced image. The visual results obtained are encouraging for image enhancement. The applicability of the developed algorithm is illustrated on three different test *** effects of order of differentiation on the edges of images have also been presented and discussed.

关键词： Index Terms-Chebyshev polynomial based approximation contrast enhancement fractional order differentiator.

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Machine Learning-based Electric Load Forecasting for Peak Demand Control in Smart Grid

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Computers, Materials & Continua 2023年第3期74卷 4785-4799页

作者： manish kumar Nitai Pal Department of Electrical Engineering Indian Institute of Technology(ISM)Dhanbad826004India Department of Nuclear Science&Technology Pandit Deendayal Energy UniversityGandhinagarIndia

Increasing energy demands due to factors such as population,globalization,and industrialization has led to increased challenges for existing energy *** ways of energy generation and energy consumption like smart grids and smart homes are implemented to face these challenges with reliable,cheap,and easily available sources of *** integration of renewable energy and other clean distributed generation is increasing continuously to reduce carbon and other air pollutants *** the integration of distributed energy sources and increase in electric demand enhance instability in the ***-term electrical load forecasting reduces the grid fluctuation and enhances the robustness and power quality of the *** load forecasting in advance on the basic historical data modelling plays a crucial role in peak electrical demand control,reinforcement of the grid demand,and generation balancing with cost *** accurate forecasting of electrical data is a very challenging task due to the nonstationary and nonlinearly nature of the *** learning and artificial intelligence have recognized more accurate and reliable load forecastingmethods based on historical load *** purpose of this study is to model the electrical load of Jajpur,Orissa Grid for forecasting of load using regression type machine learning algorithms Gaussian process regression(GPR).The historical electrical data and whether data of Jajpur is taken for modelling and simulation and the data is decided in such a way that the model will be considered to learn the connection among past,current,and future dependent variables,factors,and the relationship among *** on this modelling of data the network will be able to forecast the peak load of the electric grid one day *** study is very helpful in grid stability and peak load control management.

关键词： Artificial intelligence electric load forecasting machine learning peak-load control renewable energy smart grids

Recognition of newspaper printed in Gurumukhi script

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Journal of Central South University 2019年第9期26卷 2495-2503页

作者： Rupinder Pal Kaur manish kumar Jindal Munish kumar Post Graduate Department of Computer Science Guru Nanak College for GirlsSri Muktsar SahibPunjabIndia Department of Computer Science&Applications Panjab University Regional CentreSri Muktsar SahibPunjabIndia Department of Computational Sciences Maharaja Ranjit Singh Punjab Technical UniversityBathindaPunjabIndia

In this work,a system for recognition of newspaper printed in Gurumukhi script is *** feature extraction techniques,namely,zoning features,diagonal features,parabola curve fitting based features,and power curve fitting based features are considered for extracting the statistical properties of the characters printed in the *** combinations of these features are also applied to improve the recognition *** recognition,four classification techniques,namely,k-NN,linear-SVM,decision tree,and random forest are used.A database for the experiments is collected from three major Gurumukhi script newspapers which are Ajit,Jagbani and Punjabi *** 5-fold cross validation and random forest classifier,a recognition accuracy of 96.19%with a combination of zoning features,diagonal features and parabola curve fitting based features has been reported.A recognition accuracy of 95.21%with a partitioning strategy of data set(70%data as training data and remaining 30%data as testing data)has been achieved.

关键词： newspaper recognition feature extraction classification Gurumukhi script random forest

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Emergence of blockchain-technology application in peer-to-peer electrical-energy trading: a review

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Clean Energy 2021年第1期5卷 104-123页

作者： manish kumar Thukral Manipal University Jaipur Electrical Engineering DepartmentJaipurIndia

Renewable-energy resources require overwhelming adoption by the common masses for safeguarding the environment from *** this context,the prosumer is an important emerging concept.A prosumer in simple terms is the one who consumes as well as produces electricity and sells it either to the grid or to a *** the present scenario,peer-to-peer(P2P)energy trading is gaining momentum as a new vista of research that is viewed as a possible way for prosumers to sell energy to *** P2P energy trading is the only method of making renewable-energy sources popular among the common *** making P2P energy trading successful,blockchain technology is sparking considerable interest among *** with smart contracts,a blockchain provides secure tamper-proof records of transactions that are recorded in distributed ledgers that are *** paper explores,using a thorough review of recently published research work,how the existing power sector is reshaping in the direction of P2P energy trading with the application of blockchain *** challenges that are being faced by researchers in the implementation of blockchain technology in the energy sector are ***,this paper presents different start-ups that have emerged in the energy-sector domain that are using blockchain *** give insight into the application of blockchain technology in the energy sector,a case of the application of blockchain technology in P2P trading in electrical-vehicle charging is *** the end,some possible areas of research in the application of blockchain technology in the energy sector are discussed.

关键词： blockchain consensus algorithms microgrid peer-to-peer energy trading distributed energy resources electric-vehicle charging