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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 reactions.The main obstacle for fabricating OPSSBs is the requirement of high temperature to produce strong basicity on ordered porous materials.For 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 Y.Such high decomposition temperatures are energy-intensive and harmful to the structure of supports.Herein,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 sites.In 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

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 trauma.Management of these collections has evolved over the last 2 decades.The choice of interventions includes percu-taneous,endoscopic,minimally invasive surgery,or a combined approach.Endoscopic drainage is the drainage of PFCs by creating an artificial communi-cation between the collection and gastrointestinal lumen that is maintained by placing a stent across the fistulous tract.In 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

A Clinical Data Analysis Based Diagnostic Systems for Heart Disease Prediction Using Ensemble Method

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Big Data Mining and Analytics 2023年第4期6卷 513-525页

作者： Ankit kumar Kamred Udham Singh manish kumar Department of Computer Engineering and Applications GLA UniversityMathura 281406India School of Computing Graphic Era Hill UniversityDehradun 248002India Department of Electronics and Communication Engineering GLA UniversityMathura 281406India.

The correct diagnosis of heart disease can save lives,while the incorrect diagnosis can be lethal.The UCI machine learning heart disease dataset compares the results and analyses of various machine learning approaches,including deep learning.We used a dataset with 13 primary characteristics to carry out the research.Support vector machine and logistic regression algorithms are used to process the datasets,and the latter displays the highest accuracy in predicting coronary disease.Python programming is used to process the datasets.Multiple research initiatives have used machine learning to speed up the healthcare sector.We also used conventional machine learning approaches in our investigation to uncover the links between the numerous features available in the dataset and then used them effectively in anticipation of heart infection risks.Using the accuracy and confusion matrix has resulted in some favorable outcomes.To get the best results,the dataset contains certain unnecessary features that are dealt with using isolation logistic regression and Support Vector Machine(SVM)classification.

关键词： artificial intelligence support vector machine logistic regression cleveland dataset supervised algorithm human sensing

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 infrastructure.Efficient 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 energy.Grid integration of renewable energy and other clean distributed generation is increasing continuously to reduce carbon and other air pollutants emissions.But the integration of distributed energy sources and increase in electric demand enhance instability in the grid.Short-term electrical load forecasting reduces the grid fluctuation and enhances the robustness and power quality of the grid.Electrical 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 reduction.But accurate forecasting of electrical data is a very challenging task due to the nonstationary and nonlinearly nature of the data.Machine learning and artificial intelligence have recognized more accurate and reliable load forecastingmethods based on historical load data.The 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 data.Based on this modelling of data the network will be able to forecast the peak load of the electric grid one day ahead.The 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

Multiple Forgery Detection in Video Using Convolution Neural Network

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Computers, Materials & Continua 2022年第10期73卷 1347-1364页

作者： Vinay kumar Vineet Kansal manish Gaur Centre for Advanced Studies Dr.A P J Abdul Kalam Technical UniversityLucknowIndia Institute of Engineering and Technology Dr.A P J Abdul Kalam Technical UniversityLucknowIndia

With the growth of digital media data manipulation in today’s era due to the availability of readily handy tampering software,the authenticity of records is at high risk,especially in video.There is a dire need to detect such problem and do the necessary actions.In this work,we propose an approach to detect the interframe video forgery utilizing the deep features obtained from the parallel deep neural network model and thorough analytical computations.The proposed approach only uses the deep features extracted from the CNN model and then applies the conventional mathematical approach to these features to find the forgery in the video.This work calculates the correlation coefficient from the deep features of the adjacent frames rather than calculating directly from the frames.We divide the procedure of forgery detection into two phases–video forgery detection and video forgery classification.In video forgery detection,this approach detect input video is original or tampered.If the video is not original,then the video is checked in the next phase,which is video forgery classification.In the video forgery classification,method review the forged video for insertion forgery,deletion forgery,and also again check for originality.The proposed work is generalized and it is tested on two different datasets.The experimental results of our proposed model show that our approach can detect the forgery with the accuracy of 91%on VIFFD dataset,90%in TDTV dataset and classify the type of forgery–insertion and deletion with the accuracy of 82%on VIFFD dataset,86%on TDTV dataset.This work can helps in the analysis of original and tempered video in various domain.

关键词： Digital forensic forgery detection video authentication video interframe forgery video processing deep learning

Preventable iatrogenic cause of foot-drop in knee injuries with literature review

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Chinese Journal of Traumatology 2022年第4期25卷 224-231页

作者： Anant Krishna Sumit Arora Rakesh Goyal manish kumar Nirup Naik Manoj kumar Department of Orthopaedics All India Institute of Medical SciencesAnsari NagarNew Delhi110029India Department of Orthopaedic Surgery Maulana Azad Medical College&Associated Lok Nayak HospitalNew Delhi110002India

Purpose Common peroneal nerve palsy is quite disabling and every effort should be made to prevent its injury during the treatment.Methods We retrospectively reviewed the prospectively collected data of 7 cases of tibial plateau fractures in association with proximal fibula fracture from January 2019 to September 2019 who presented to emergency room of our hospital.Results In addition to fibular neck fracture,the first case had type 6 tibial plateau displaced fracture and the second case had displaced acetabular fracture with instability of knee with tibial tuberosity avulsion.common peroneal nerve palsy developed following application of distal tibial skeletal traction in both the cases.Other 6 such cases remained neurologically intact as traction was not applied to them.Conclusion Such iatrogenic complication could have been prevented if the injury pattern of"concomitant medial and lateral columns"of the proximal leg is kept in mind by the treating surgeon before applying skeletal traction.

关键词： Common peroneal neuropathies Tibial plateau fractures Proximal fibula fractures Traction palsy

Fabrication and Characterization of Banana Pseudostem Fibre Reinforced Epoxy Hybrid Composite Using Al_(2)O_(3) as Filler

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Journal of Bionic Engineering 2023年第4期20卷 1737-1746页

作者： Ankit Samal Sanjeev kumar manish Bhargava Barnik Saha Roy Mechanical Engineering Department National Institute of Technology AgartalaJiraniaTripura799046India Mechanical Engineering Department Subharti Institute of Technology and EngineeringMeerutUttar Pradesh250005India

Natural fibre-reinforced composites are now becoming incredibly common in various products because of their comparable qualities to conventional materials.Due to its availability,superior mechanical qualities,and low cost,banana pseudostem is extensively used in various applications requiring natural fibres.This study investigates the physical and mechanical properties of epoxy composites reinforced with banana pseudostem fibres that contain Al_(2)O_(3) particulate.In order to produce composites with fibre and filler loadings,manual hand layup was used.Fibre and filler loading effects on composite properties were studied in experiments.The results of the investigations demonstrate that proportion of Al_(2)O_(3) in composites significantly influences their mechanical and physical properties.Additionally,the composite with a fibre content of 30%shows improved mechanical proportions and hardness.Thermogravimetric analysis was used to study the composite's thermal behaviour.Composites are more thermally stable than raw epoxy.Fourier Transform Infrared Spectroscopy and Scanning electron microscopy analyses were used to characterize the composites.

关键词： Banana Pseudostem fibre Al_(2)O_(3) Epoxy Characterization Mechanical properties

Stock Prediction Based on Technical Indicators Using Deep Learning Model

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Computers, Materials & Continua 2022年第1期70卷 287-304页

作者： manish Agrawal Piyush kumar Shukla Rajit Nair Anand Nayyar Mehedi Masud Department of Computer Science&Engineering University Institute of TechnologyRajiv Gandhi Proudyogiki VishwavidyalayaBhopal-462033Madhya PradeshIndia Faculty of Department of Computer Science&Engineering University Institute of TechnologyRajiv Gandhi Proudyogiki VishwavidyalayaBhopal-462033Madhya PradeshIndia Faculty of Department of Computer Science&Engineering School of Engineering and TechnologyJagran Lakecity UniversityBhopal462026Madhya PradeshIndia Graduate School Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Stock market trends forecast is one of the most current topics and a significant research challenge due to its dynamic and unstable nature.The stock data is usually non-stationary,and attributes are non-correlative to each other.Several traditional Stock Technical Indicators(STIs)may incorrectly predict the stockmarket trends.To study the stock market characteristics using STIs and make efficient trading decisions,a robust model is built.This paper aims to build up an Evolutionary Deep Learning Model(EDLM)to identify stock trends’prices by using STIs.The proposed model has implemented the Deep Learning(DL)model to establish the concept of Correlation-Tensor.The analysis of the dataset of three most popular banking organizations obtained from the live stock market based on the National Stock exchange(NSE)-India,a Long Short Term Memory(LSTM)is used.The datasets encompassed the trading days from the 17^(th) of Nov 2008 to the 15^(th) of Nov 2018.This work also conducted exhaustive experiments to study the correlation of various STIs with stock price trends.The model built with an EDLM has shown significant improvements over two benchmark ML models and a deep learning one.The proposed model aids investors in making profitable investment decisions as it presents trend-based forecasting and has achieved a prediction accuracy of 63.59%,56.25%,and 57.95%on the datasets of HDFC,Yes Bank,and SBI,respectively.Results indicate that the proposed EDLA with a combination of STIs can often provide improved results than the other state-of-the-art algorithms.

关键词： Long short term memory evolutionary deep learning model national stock exchange stock technical indicators predictive modelling prediction accuracy

Atrial fibrillation in older adults with cancer

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Journal of Geriatric Cardiology 2022年第1期19卷 1-8页

作者： manish kumar Nerea Lopetegui-Lia Christina Al Malouf Mansour Almnajam Patrick P.Coll Agnes S.Kim Department of Medicine Pat and Jim Calhoun Cardiology CenterUniversity of Connecticut School of MedicineFarmingtonCT 06030USA Department of Hematology and Oncology Cleveland ClinicOhio 44195USA De-partment of Cardiology Mount Sinai Hospital/Icahn School of MedicineNew York 10029USA Department of Fam-ily Medicine UConn Center of AgingUniversity of ConnecticutSchool of MedicineFarmingtonCT 06030USA

Cancer and atrial fibrillation(AF)are common co-morbid conditions in older adults.Both cancer and cancer treatment increase the risk of developing new AF which increases morbidity and mortality.Heart rate and rhythm control along with anticoagulation therapy remain the mainstay of treatment of AF in older adults with both cancer and AF.Adjustments to the treatment may be necessary because of drug interactions with concurrent chemotherapy.Cancer and old age increase the risk of both,thromboembolism and bleeding.The risk of these complications is further enhanced by concomitant cancer therapy,frailty,poor nutrition status and,coexisting geriatric syndromes.Therefore,careful attention needs to be given to the risks and benefits of using anticoagulant medications.This review focuses on the management of AF in older patients with cancer,including at the end-of-life care.

关键词： fibrillation Cancer chemotherapy

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 gradient.Very few studies have attempted to document the diference in elevational richness patterns of native and exotic species.In 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 Himalaya.Results: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 mid-elevations.Native species assemblages showed higher phylogenetic diversity than the exotic species assemblages over the entire elevational gradient in the Himalaya.In terms of phylogenetic structure,exotic species assemblages showed majorly phylogenetic clustering while native species assemblages were characterized by phylogenetic overdispersion over the entire gradient.Conclusions: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 Himalaya.Species assemblages with high native phylogenetic overdispersion are less receptive to exotic species than the phylogenetically clustered assemblages.Diferent 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