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Novel synthesis and characterization of CuO nanomaterials:Biological applications

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Chinese Chemical Letters 2014年第12期25卷 1615-1619页

作者： Ayekpam Bimolini Devi Dinesh singh Moirangthem Narayan chandra Talukdar M.Damayanti Devi N.Rajen singh Meitram Niraj Luwang Department of Chemistry Manipur University Institute of Bioresources and Sustainable Development Department of Biotechnology Department of Life Sciences Manipur University Chemical Engineering and Process Development National Chemical Laboratory

CuO nanoparticles were synthesized at a relatively low temperature（80 ℃） for 2 h using polyethylene glycol-glycerol mixture which acts as a capping agent.A detailed characterization of the synthesized nanomaterials were performed utilizing X-ray diffraction（XRD）,infra-red spectroscopy（IR）,thermogravimetric analysis（TGA-DTA）,transmission electron microscopy（TEM）,photoluminescence（PL） by studying its crystalline phase,vibrational mode,thermal analysis,morphology and photoluminescence *** effect of annealing on the as-prepared nanoparticles were studied and compared with their corresponding bulk *** synthesized nanoparticles have been screened for in vitro cytotoxicity（1C_（50）） studies against the human cervical adenocarcinoma cell line（HeLa） using WITT assay *** as-prepared nanoparticle inhibits the proliferation of this HeLa *** standard disc diffusion method has been used to study the antibacterial activity of the samples against the human pathogenic bacteria Escherichia coli（MTCC 729）,Proteus mirabilis（MTCC 425） and Klebsiella pneumoniae ***（MTCC 432）.The results have been compared with the positive control antibiotic *** synthesized nanoparticles would provide a potential alternative to antibiotics for controlling some of the microorganisms causing urolithiasis.

关键词： CuO nanoparticles Annealing HeLa cell lines Cytotoxicity Antibacterials

Effect of Co substitution on the structural,dielectric and optical properties of KBiFe_(2)O_(5)

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International Journal of Minerals,Metallurgy and Materials 2021年第11期28卷 1861-1867页

作者： K.chandrakanta R.Jena P.pal Md.F.Abdullah S.D.Kaushik A.K.singh Department of Physics and Astronomy National Institute of TechnologyRourkela-769008OdishaIndia UGC-DAE Consortium for Scientific Research Mumbai Centre R-5 ShedBARCMumbai-400085India

Cobalt(Co)-modified brownmillerite KBiFe_(2)O_(5)(KBFO;[KBiFe_(2(1−x))Co_(2x)O_(5)(x=0,0.05)])polycrystalline is synthesized following the solid-state reaction *** refinement of X-ray diffraction data confirmed the phase purity of KBFO and KBiFe_(1.9)Co_(0.1)O_(5)(KBFCO).The optical bandgap energy(Eg)of KBFO decreased from 1.59 to 1.51 eV because of Co *** decrease in bandgap can be attributed to the tilting of the Fe–O tetrahedral structure of *** observed room-temperature Raman peaks of KBFCO shifted by 3 cm^(−1) toward a lower wavenumber than that of *** shift in Raman active modes can be attributed to the change in the bond angles and bond lengths of the Fe–O tetrahedral structure and modification in response to oxygen deficiency in KBFO because of Co *** with that of KBFO,the frequency-dependent dielectric constant and dielectric loss of KBFCO decrease at room temperature,which is a consequence of the reduction in oxygen migration and modification in response to vibrational modes present in the sample.

关键词： brownmillerite rietveld refinement Raman spectroscopy bandgap

Colouring of COVID-19 Affected Region Based on Fuzzy Directed Graphs

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Computers, Materials & Continua 2021年第7期68卷 1219-1233页

作者： Rupkumar Mahapatra Sovan Samanta Madhumangal pal Jeong-Gon Lee Shah Khalid Khan Usman Naseem Robin singh Bhadoria Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar UniversityMidnapore721102India Department of Mathematics Tamralipta MahavidyalayaTamluk721636India Division of Applied Mathematics Wonkwang UniversityIksan-SiJeonbuk54538Korea School of Engineering RMIT UniversityMelbourne3001Australia School of Computer Science University of Sydney Sydney2006Australia Department of Computer Science&Engineering Birla Institute of Applied Sciences(BIAS)BhimtalUttarakhand263136India

Graph colouring is the system of assigning a colour to each vertex of a *** is done in such a way that adjacent vertices do not have equal *** is fundamental in graph *** is often used to solve real-world problems like traffic light signalling,map colouring,scheduling,***,social networks are prevalent systems in our ***,the users are considered as vertices,and their connections/interactions are taken as *** users follow other popular users’profiles in these networks,and some don’t,but those non-followers are connected directly to the popular *** means,along with traditional relationship(information flowing),there is another relation among *** depends on the domination of the relationship between the *** type of situation can be modelled as a directed fuzzy *** the colouring of fuzzy graph theory,edge membership plays a vital *** membership is a representation of flowing information between end nodes of the *** from the communication relationship,there may be some other factors like domination in *** influence of power is captured *** this article,the colouring of directed fuzzy graphs is defined based on the influence of *** with this,the chromatic number and strong chromatic number are provided,and related properties are *** application regarding COVID-19 infection is presented using the colouring of directed fuzzy graphs.

关键词： Graph colouring chromatic index directed fuzzy graphs

Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India

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Big Data Mining and Analytics 2021年第2期4卷 65-75页

作者： Rajani Kumari Sandeep Kumar Ramesh chandra Poonia Vijander singh Linesh Raja Vaibhav Bhatnagar Pankaj Agarwal Department of Information Technology and Computer Application JECRC UniversityJaipurRajasthan 303905India Bangalore Karnataka 560029India with Amity University Rajasthan JaipurRajasthan 303002India University Jaipur Rajasthan 303007India

The novel coronavirus outbreak was first reported in late December 2019 and more than 7 million people were infected with this disease and over 0.40 million worldwide lost their lives. The first case was diagnosed on30 January 2020 in India and the figure crossed 0.24 million as of 6 June 2020. This paper presents a detailed study of recently developed forecasting models and predicts the number of confirmed, recovered, and death cases in India caused by COVID-19. The correlation coefficients and multiple linear regression applied for prediction and autocorrelation and autoregression have been used to improve the accuracy. The predicted number of cases shows a good agreement with 0.9992 R-squared score to the actual values. The finding suggests that lockdown and social distancing are two important factors that can help to suppress the increasing spread rate of COVID-19.

关键词： COVID-19 regression correlation machine learning prediction

Low-cost high entropy alloy(HEA)for high-efficiency oxygen evolution reaction(OER)

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Nano Research 2022年第6期15卷 4799-4806页

作者： Lalita Sharma Nirmal Kumar Katiyar Arko Parui Rakesh Das Ritesh Kumar chandra Sekhar Tiwary Abhisek K.singh Aditi Halder Krishanu Biswas School of Basic Sciences Advanced Materials Research Centre(AMRC)Indian Institute of Technology Mandi(H.P)KamandMandi 175005India Department of Materials Science and Engineering Indian Institute of Technology KanpurKanpur 208016India School of Engineering London South Bank UniversityLondonSE10 AAUK Materials Research Centre Indian Institute of ScienceBangalore 560012India Metallurgical and Materials Engineering Indian Institute of Technology KharagpurKharagpur 382355India

Oxygen evolution reaction(OER)is the key step involved both in water splitting devices and rechargeable metal-air batteries,and hence,there is an urgent need for a stable and low-cost material for efficient *** the present investigation,Co-Fe-Ga-NiZn(CFGNZ)high entropy alloy(HEA)has been utilized as a low-cost electrocatalyst for ***,after cyclic voltammetry activation,CFGNZ-nanoparticles(NPs)are covered with oxidized surface and form high entropy(oxy)hydroxides(HEOs),exhibiting a low overpotential of 370 mV to achieve a current density of 10 mA/cm^(2)with a small Tafel slope of 71 mV/*** alloy has higher electrochemical stability in comparison to state-of-the art RuO2 electrocatalyst as no degradation has been observed up to 10 h of *** electron microscopy(TEM)studies after 10 h of long-term chronoamperometry test showed no change in the crystal structure,which confirmed the high stability of *** density functional theory(DFT)based calculations show that the closeness of d(p)-band centers to the Fermi level(EF)plays a major role in determining active *** work highlights the tremendous potential of CFGNZ HEA for OER,which is the primary reaction involved in water splitting.

关键词： high entropy alloy cyclic voltammetry activation oxygen evolution reaction electrocatalyst nanocrystalline catalyst

Feature-based augmentation and classification for tabular data

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CAAI Transactions on Intelligence Technology 2022年第3期7卷 481-491页

作者： Balachander Sathianarayanan Yogesh chandra singh Samant Prahalad S.Conjeepuram Guruprasad Varshin B.Hariharan Nirmala Devi Manickam Amrita School of Engineering Amrita Vishwa VidyapeethamCoimbatoreIndia

Generating synthetic samples for a tabular data is a strenuous *** of the time,the columns(features)in the dataset may not follow an ideal distribution *** objective of the proposed algorithm,Histogram Augmentation Technique(HAT),is to generate a dataset whose distribution is similar to that of the original *** augmentation is achieved based on individual columns,where separate algorithms are designed for continuous and discrete *** also use features of an object for *** humans make a judgement,they notice prominent features and characterise the perceived ***,conventional Machine Learning classifiers are designed and trained on the basis of *** the features as the basis for classification,Feature Importance Classifier(FIC)has been attempted in this *** treats every feature independent of each other,and ranks the features based on its dependence with the classified *** has been found that the FIC has the highest accuracy and has improved the accuracy by 5.54%on average,when it's compared to other *** suggested algorithms have been experimented on five datasets and compared with two augmentation algorithms and four state-of-the-art ML classification algorithms.

关键词： function classifier columns

Searching systematics for nonfactorizable contributions to B- and■ hadronic decays

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Chinese Physics C 2022年第7期 49-57页

作者： Maninder Kaur Supreet pal singh R.C.Verma Department of Physics Punjabi University

The two-body weak decays ■and■ are examined using isospin analysis to study nonfactorizable contributions. After determining strong interaction phases and obtaining factorizable contributions from spectator-quark diagrams for Nc=3, we determine nonfactorizable isospin amplitudes from the experimental data for these modes. Our results support the universality of the ratio of nonfactorizable isospin reduced amplitudes for these decays within experimental errors. To demonstrate that these systematics are not coincidental, we also plot our results w. r. t. this ratio.

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Historical variations in autochthonous and allochthonous sediment supplies to the largest freshwater lake in Central India

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International Journal of Sediment Research 2022年第5期37卷 563-575页

作者： Nafees Ahmad Satinder pal singh Aasif Mohmad Lone Abul Qasim Ravi Bhushan Gyana Ranjan Tripathy Chinmay Shah Department of Earth and Environmental Sciences Indian Institute of Science Education and Research Bhopal Geosciences Division Physical Research Laboratory Department of Earth and Climate Science Indian Institute of Science Education and Research

Lacustrine sediment preserves high-resolution biogeochemical records of past variations in watershed processes controlling lake sedimentation. The current study explores historical variations in autochthonous and allochthonous sediment supplies to a large tropical freshwater lake system(Upper Lake, Bhopal) protected under the international Ramsar Convention of 2002 against anthropogenic pressures. For this purpose, multi-proxy biogeochemical data are presented for organic matter(total organic carbon, total nitrogen, phosphorous, and loss on ignition [LOI] at550°C), carbonate(LOI at 950°C), lithic sediment(aluminum, titanium, iron, calcium, magnesium,sodium, potassium, manganese, zirconium, niobium, hafnium, tantalum, thorium, uranium, and rare earth elements), and anthropogenic inputs(lead) measured in a 38 cm long sediment core retrieved from the lake. In addition to the lacustrine sediment core, the samples of catchment bedrock, surface soils, major stream sediment, and eolian dust collected from the lake periphery also are analyzed. The systematic biogeochemical excursions in the upper core section(top ～8 cm) indicate increased anthropogenic inputs, watershed denudation by agricultural activities, artificially reduced fluvial sediment supply, relatively increased dust inputs and lake eutrophication in the last few decades. The current study underscores the roles of anthropogenic land-use and wetland conservation practices in the rapid alteration of autochthonous and allochthonous sediment supplies to open aquatic ecosystems. Further, rising lake eutrophication levels despite a managed reduction in allochthonous sediment supplies seem challenging to control due to dissolved nutrient supply from urban sewage discharge and runoff from agricultural land in the watershed.

关键词： Upper Lake Sediment Geochemistry Sediment provenance Eutrophication Anthropogenic inputs

Disease detection,severity prediction,and crop loss estimation in MaizeCrop using deep learning

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Artificial Intelligence in Agriculture 2022年第1期6卷 276-291页

作者： Nidhi Kundu Geeta Rani Vijaypal singh Dhaka Kalpit Gupta Siddaiah chandra Nayaka Eugenio Vocaturo Ester Zumpano Department of Computer and Communication Engineering Manipal University JaipurJaipurIndia ICAR DOS in Biotechnology University of Mysore ManasagangotriMysore 570005India DIMES(Department of Computer Engineering ModelingElectronics and Systems)University of CalabriaItaly Nanotec Italian National Research Council87036 RendeCSItaly

The increasing gap between the demand and productivity of maize crop is a point of concern for the food industry,and ***'susceptibility to diseases such as Turcicum Leaf Blight,and Rust is a major cause for reducing its *** detection,and classification of these diseases,calculation of disease severity,and crop loss estimation is a time-consuming ***,it requires expertise in disease ***,there is a need to find an alternative for automatic disease detection,severity prediction,and crop loss *** promising results of machine learning,and deep learning algorithms in pattern recognition,object detection,and data analysis motivate researchers to employ these techniques for disease detection,classification,and crop loss estimation in maize *** research works available in literature,have proven their potential in automatic disease detection using machine learning,and deep learning ***,there is a lack none of these works a reliable and real-life labelled dataset for training these ***,none of the existing works focus on severity prediction,and crop loss *** authors in this manuscript collect the real-life dataset labelled by plant *** propose a deep learning-based framework for pre-processing of dataset,automatic disease detection,severity prediction,and crop loss *** uses the K-Means clustering algorithm for extracting the region of ***,they employ the customized deep learning model‘MaizeNet’for disease detection,severity prediction,and crop loss *** model reports the highest accuracy of 98.50%.Also,the authors perform the feature visualization using the ***,the proposed model is integrated with a web application to provide a userfriendly *** efficacy of the model in extracting the relevant features,a smaller number of parameters,low training time,high accuracy favors its importance as an assisting tool for plant pathology experts.T

关键词： Disease detection Crop loss Severity Deep learning Maize