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Photoluminescence behavior and visible light photocatalytic activity of ZnO,ZnO/ZnS and ZnO/ZnS/α-Fe_2O_3 nanocomposites

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Transactions of Nonferrous Metals Society of China 2018年第7期28卷 1387-1397页

作者： gaurav HITKARI Sandhya SINGH Gajanan PANDEY Sophisticated Instrumentation Laboratory Department of Applied Chemistry School for Physical Science Babasaheb Bhimrao Ambedkar University

In order to achieve effective, economic, and easily achievable photocatalyst for the degradation of dye methyl orange（MeO）, ZnO, ZnO/ZnS and ZnO/ZnS/α-Fe2O3 nanocomposites were prepared by simple chemical synthetic route in the aqueous medium. Phase, crystallinity, surface structure and surface behavior of the synthesized materials were determined by X-ray diffraction（XRD） and Brunauer-Emmett-Teller analysis（BET） techniques. XRD study established formation of good crystalline ZnO, ZnO/ZnS and ZnO/ZnS/α-Fe2O3 nanomaterials. By using intensity of constituent peaks in the XRD pattern, the compositions of nanocomposites were determined. From the BET analysis, the prepared materials show mesoporous behavior, type Ⅳ curves along with H4 hysteresis. The ZnO/ZnS/α-Fe2O3 composite shows the largest surface area among three materials. From the UV-visible spectra, the band gap energy of the materials was determined. Photoluminescence spectra（PL） were used to determine the emission behavior and surface defects in the materials. In PL spectra, the intensity of UV peak of ZnO/ZnS is lowered than that of ZnO while in case of ZnO/ZnS/α-Fe2O3, the intensity further decreased. The visible emission spectra of ZnO/ZnS increased compared with ZnO while in ZnO/ZnS/α-Fe2O3 it is further increased compared with ZnO/ZnS. The as-synthesized materials were used as photocatalysts for the degradation of dye MeO. The photo-degradation data revealed that the ZnO/ZnS/α-Fe2O3 is the best photocatalyst among three specimens for the degradation of dye MeO. The decrease of intensity of UV emission peak and the increase of intensity of visible emission cause the decrease of recombination of electrons and holes which are ultimately responsible for the highest photocatalytic activity of ZnO/ZnS/α-Fe2O3.

关键词： nanocomposite ZnO ZnS α-Fe2O3 calcination optical properties photocatalytic activity

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Evolution-aided engineering of plant specialized metabolism

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aBIOTECH 2021年第3期2卷 240-263页

作者： Mohammad Irfan Benjamin Chavez Paride Rizzo John C.D'Auria gaurav D.Moghe Plant Biology Section School of Integrative Plant ScienceCornell UniversityIthacaNYUSA Metabolic Diversity Group Leibniz Institute of Plant Genetics and Crop Plant Research(IPK)06466 SeelandGermany

The evolution of new traits in living organisms occurs via the processes of mutation,recombination,genetic drift,and *** processes that have resulted in the immense biol ogical diversity on our planet are also being employed in metabolic engineering to optimize enzymes and pathways,create new-to-nature reactions,and synthesize complex natural products in heterologous *** this review,we discuss two evolution-aided strategies for metabolic engineering-directed evolution,which improves upon existing genetic templates using the evolutionary process,and combinatorial pathway reconstruction,which brings together genes evolved in different organisms into a single heterol ogous *** discuss the general principles of these strategies,describe the technologies involved and the molecular traits they influence,provide examples of their use,and discuss the roadblocks that need to be addressed for their wider adoption.A better understanding of these strategies can provide an impetus to research on gene function discovery and biochemical evolution,which is foundational for improved metabolic *** evolution-aided approaches thus have a substantial potential for improving our understanding of plant metabolism in general,for enhancing the production of plant metabolites,and in sustainable agriculture.

关键词： Evolution Metabolic engineering Plant biotechnology Synthetic biology

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Peritoneal Membrane Transport Characteristics in Uni-PET with Preceding Icodextrin Dwell as Compared to Classic PET with Preceding Glucose Dwell: A Prospective Study

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Open Journal of Nephrology 2021年第4期11卷 516-522页

作者： gaurav Vohra Army Command Hospital Chandimandir India

Background: In subjects on CAPD who use icodextrin for long night dwell, it has been recommended that nocturnal exchange be replaced by dextrose dwell whenever PET is to be performed as preceding exchange with icodextrin temporarily increases peritoneal membrane permeability and therefore, gives high D/PCr and low D/D0 glucose values. Whether this temporary change is also seen with use of Uni-PET (which involves one hour dwell of 1.5% dextrose followed by 4-hour dwell of 4.25% dextrose) is not known. Methods: In this self, controlled study, subjects on CAPD, who were using icodextrin for long nocturnal dwell for at least 3 months, were screened for enrolment. Pregnancy or lactation, history of any PD related infectious complication in the past one month, present or past malignancy, and poor functional status were exclusion criteria. Enrolled subjects underwent classic PET with preceding 2.5% dextrose long nocturnal dwell on day 1 followed by Uni-PET with preceding 7.5% icodextrin long nocturnal dwell on day 2. Difference in D/PCr and D/D0 glucose between the two PETs was primary objectives. The study was approved by Institute Ethics Committee. Results: 15 out of 26 screened subjects were enrolled over a period of 18 months (July 2015-December 2016). The mean (±SD) age of study population was 60.8±9.1 years. Majority were males and diabetes was the most common cause of CKD. Mean D/PCr were 0.68 ± 0.11 and 0.64 ± 0.08 in classic PET and Uni-PET, respectively. The difference between the two values was not significant [mean difference between D/PCr (classic PET-Uni-PET): 0.040 ± 0.86;95% CI (-0.007 to 0.088);p = 0.09]. Similarly, D/D0 glucose between classic PET and Uni-PET was also similar [mean difference between D/D0 glucose (classic PET-Uni-PET): -0.02 ± 0.09;95% CI (-0.06 to 0.03);p = 0.448]. Conclusion: Peritoneal membrane small solute transport characteristics in Uni-PET wit

关键词： Icodextrin Peritoneal Membrane Peritoneal Equilibration Test Peritoneal Dialysis Fluid Peritoneal Dialysis

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Molecular identification of sex in Hippophae rhamnoides L. using isozyme and RAPD markers

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Forestry Studies in China 2010年第2期12卷 62-66页

作者： Amit SHARMA gaurav ZINTA Satender RANA Poonam SHIRKOT Department of Biotechnology Dr. Yashwant Singh Parmar University of Horticulture & Forestry

In many dioecious plants, gender affects economic value, breeding schemes and opportunities for commercial harvests. Hippophae rhamnoides L. is a dioecious plant species in which female genotypes are commercially preferred over male genotypes. Its berries have rich medicinal, nutritional and pharmaceutical properties because of their large amounts of vitamins, essential oils, proteins, fatty acids, free amino acids and flavanoids. Primary limitation for breeding H. rhamnoides L. is its dioecious nature, since gender cannot be identified by traditional methods. Therefore, some reliable and quick methods need to be developed. This commu- nication deals with the development of isozyme and RAPD markers for early sex identification in this dioecious tree. The isozyme analysis was conducted with four enzyme systems, viz. peroxidase, esterase, malate dehydrogenase and catalase. The peroxidase enzyme system produced a female specific sex marker, which successfully differentiated between the staminate and pistillate geno- types ofH. rhamnoides L. Thirty five random decamer primers were used in our study and one male sex linked marker was identified. OPD-20 （5＇-ACTTCGCCAC-3＇） displayed a band at 911 bp that expressed polymorphism between male and female genotypes. The staminate and pistillate genotypes could be distinguished using RAPD marker OPD-209n. These results revealed the immense poten- tial of peroxidase isozyme patterns and RAPD as genetic markers for sex identification in H. rhamnoides L.

关键词： Hippophae rhamnoides L. sex markers isozyme RAPD dioecism

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Analysis of Protein-Ligand Interactions of SARS-CoV-2 Against Selective Drug Using Deep Neural Networks

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Big Data Mining and Analytics 2021年第2期4卷 76-83页

作者： Natarajan Yuvaraj Kannan Srihari Selvaraj Chandragandhi Rajan Arshath Raja gaurav Dhiman Amandeep Kaur St.Peter’s Institute of Higher Education and Research Information Communication Technology AcademyChennai 600096India Department of Computer Science and Engineering SNS College of Engineering641107India Department of Computer Science and Engineering Jagannath Educational Health and Charitable Trust College of Engineering and TechnologyCoimbatore 641105India B.S.Abdur Rahman Crescent Institute of Science and Technology Chennai 600048India Department of Computer Science Government Bikram College of CommercePatiala 147001India Department of Computer Science and Engineering Sri Guru Granth Sahib World UniversityFatehgarh 140406India

In recent time, data analysis using machine learning accelerates optimized solutions on clinical healthcare systems. The machine learning methods greatly offer an efficient prediction ability in diagnosis system alternative with the clinicians. Most of the systems operate on the extracted features from the patients and most of the predicted cases are accurate. However, in recent time, the prevalence of COVID-19 has emerged the global healthcare industry to find a new drug that suppresses the pandemic outbreak. In this paper, we design a Deep Neural Network(DNN)model that accurately finds the protein-ligand interactions with the drug used. The DNN senses the response of protein-ligand interactions for a specific drug and identifies which drug makes the interaction that combats effectively the virus. With limited genome sequence of Indian patients submitted to the GISAID database, we find that the DNN system is effective in identifying the protein-ligand interactions for a specific drug.

关键词： Deep Neural Network(DNN) coronavirus protein-ligand interactions deep learning clinical healthcare system

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Further contribution to the Neogene petrified wood forest of Mizoram, India

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科学通报 2013年第S1期58卷 104-110页

作者： MEHROTRA Rakesh Chandra TIWARI R P SRIVASTAVA gaurav SHUKLA Anumeha Birbal Sahni Institute of Palaeobotany Department of Geology Mizoram University

Mizoram, a state situated in the northeast corner of India, is very rich in fossil woods belonging to the Tipam Group(Late Miocene-Early Pliocene in age). Four new fossil woods, namely Swintonioxylon hailakandiense Prakash & Tripathi, Bombacacioxylon tertiarum Mehrotra et al., gen. et sp. nov., Dipterocarpoxylon jammuense Guleria et al. and Bischofia palaeojavanica Awasthi are described from there. They resemble the modern taxa, namely Swintonia Griff.(Anacardiaceae), Dipterocarpus C.F. Gaertn.(Dipterocarpaceae), Bischofia Blume(Euphorbiaceae) and the taxa of the family Bombacaceae. The distribution of the modern equivalents of the present and previously described taxa indicates the existence of warm and humid climate in Mizoram during the depositional time.

关键词： fossil wood Tipam Group angiosperms northeast India palaeoclimate

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Carcinoma bladder and sliding bladder hernia: Unusual association of paramount significance

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Asian Journal of Urology 2020年第2期7卷 186-187页

作者： Manav Agrawal gaurav Garg Sunny Goel Manoj Kumar Department of Urology King George’s Medical UniversityLucknowUttar PradeshIndia

A 60-year-old man,a diagnosed case of inguinal hernia was referred for evaluation of voiding lower urinary tract symptoms(LUTS).There was no history of *** local examination,he had right-sided-direct inguinal hernia with right *** biochemical parameters were within normal *** routine microscopy revealed presence of field full of red blood *** uroflowmetry there was presence of decreased peak flow rate(12 mL/s)and average flow rate(8 mL/s).

关键词： bladder hernia Carcinoma

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Archery Algorithm:A Novel Stochastic Optimization Algorithm for Solving Optimization Problems

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Computers, Materials & Continua 2022年第7期72卷 399-416页

作者： Fatemeh Ahmadi Zeidabadi Mohammad Dehghani Pavel Trojovsky Štěpán Hubálovsky Victor Leiva gaurav Dhiman Department of Mathematics and Computer Sciences Sirjan University of TechnologySirjanIran Department of Mathematics Faculty of ScienceUniversity of Hradec Králové50003Hradec KrálovéCzech Republic Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec Králové50003Hradec KrálovéCzech Republic School of Industrial Engineering Pontificia Universidad Católica de ValparaísoValparaíso2362807Chile Department of Computer Science Government Bikram College of CommercePatialaPunjabIndia

Finding a suitable solution to an optimization problem designed in science is a major ***,these must be addressed utilizing proper *** on a random search space,optimization algorithms can find acceptable solutions to *** Algorithm(AA)is a new stochastic approach for addressing optimization problems that is discussed in this *** fundamental idea of developing the suggested AA is to imitate the archer’s shooting behavior toward the target *** proposed algorithm updates the location of each member of the population in each dimension of the search space by a member randomly marked by the *** AA is mathematically described,and its capacity to solve optimization problems is evaluated on twenty-three distinct types of objective ***,the proposed algorithm’s performance is compared *** approaches,including teaching-learning based optimization,marine predators algorithm,genetic algorithm,grey wolf optimization,particle swarm optimization,whale optimization algorithm,gravitational search algorithm,and tunicate swarm *** to the simulation findings,the AA has a good capacity to tackle optimization issues in both unimodal and multimodal scenarios,and it can give adequate quasi-optimal solutions to these *** analysis and comparison of competing algorithms’performance with the proposed algorithm demonstrates the superiority and competitiveness of the AA.

关键词： Archer meta-heuristic algorithm population-based optimization stochastic programming swarm intelligence population-based algorithm Wilcoxon statistical test

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Identification,development,and application of cross-species intron-spanning markers in lentil(Lens culinaris Medik.)

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The Crop Journal 2018年第3期6卷 299-305页

作者： Debjyoti Sen Gupta Jitendra Kumara Sunanda Gupta Sonali Dubey Priyanka Gupta Narendra Pratap Singh gaurav Sablok Division of Crop Improvement ICAR-Institute of Pulses ResearchKanpur 208024UPIndia Division of Plant Biotechnology ICAR-Institute of Pulses ResearchKanpur 208024UPIndia Department of Biodiversity and Molecular Ecology Research and Innovation CentreFondazione Edmund MachVia E.Mach 138010 San Michele all'AdigeTrentoItaly

Lentil(Lens culinaris Medik) is one of the most important food legumes in the world. The use in lentil of molecular marker-assisted breeding is limited, owing to the low availability of polymorphic markers. In the present study, we developed a set of polymorphic intron-spanning markers(ISMs) using a cross-species mapping approach. In this approach, putative unique transcripts(PUTs) of L. culinaris were mapped onto the Medicago truncatula genome, exploiting its closeness with the lentil genome. Spliced alignment of the PUTs resulted in a total of 25,717 alignments, allowing the development of 1703 ISMs. From these, a subset of 105 ISMs were synthesized and validated with a 51% amplification success rate in 32 lentil genotypes. Of these ISMs, 40(74%) were polymorphic and generated 2–11 alleles per locus in a genetically diverse panel of 32 lentil genotypes including wild *** set of polymorphic ISMs along with their functional annotation data will be useful in lentil breeding.

关键词： Allele diversity Cross-species Genotypes Introns Lentil Molecular markers

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An Intelligent Fine-Tuned Forecasting Technique for Covid-19 Prediction Using Neuralprophet Model

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Computers, Materials & Continua 2022年第4期71卷 629-649页

作者： Savita Khurana gaurav Sharma Neha Miglani Aman Singh Abdullah Alharbi Wael Alosaimi Hashem Alyami Nitin Goyal Information Technology Department Seth Jai Parkash Mukand Lal Institute of Engineering and TechnologyRadaurHaryanaIndia Computer Science&Engineering Department Seth Jai Parkash Mukand Lal Institute of Engineering and TechnologyRadaurHaryanaIndia Computer Engineering Department National Institute of TechnologyKurukshetraHaryanaIndia Computer Science&Engineering Department Lovely Professional UniversityJalandharPunjabIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia

COVID-19,being the virus of fear and anxiety,is one of the most recent and emergent of various respiratory *** is similar to the MERS-COV and SARS-COV,the viruses that affected a large population of different countries in the year 2012 and 2002,*** standard models have been used for COVID-19 epidemic prediction but they suffered from low accuracy due to lesser data availability and a high level of *** proposed approach used a machine learning-based time-series Facebook NeuralProphet model for prediction of the number of death as well as confirmed cases and compared it with Poisson Distribution,and Random Forest *** analysis upon dataset has been performed considering the time duration from January 1st 2020 to16th July *** model has been developed to obtain the forecast values till September *** study aimed to determine the pandemic prediction of COVID-19 in the second wave of coronavirus in India using the latest Time-Series model to observe and predict the coronavirus pandemic situation across the *** India,the cases are rapidly increasing day-by-day since mid of Feb *** prediction of death rate using the proposed model has a good ability to forecast the COVID-19 dataset essentially in the second *** empower the prediction for future validation,the proposed model works effectively.

关键词： Covid-19 machine learning neuralprophet model poisson distribution prediction random forest model

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