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| 1 | Evaluation of thermophilic fungal consortium for organic municipal solid waste composting显示文摘 | Mukesh Kumar Awasthi Akhilesh Kumar Pandey Jamaluddin Khan Pushpendra Singh Bundela Jonathan W.C. Wong Ammaiyappan Selvam | 2014 | Bioresource Technology2014，，： | 1 |
| 2 | Gene networks in hexaploid wheat: interacting quantitative trait loci for grain protein content显示文摘 | Pawan Kulwal Neeraj Kumar Ajay Kumar Raj Kumar Gupta Harindra Singh Balyan Pushpendra Kumar Gupta | 2005 | Functional & Integrative Genomics2005，，4： | 1 |
| 3 | QTL analysis for some quantitative traits in bread wheat显示文摘Quantitative trait loci (QTL) analysis was conducted in bread wheat for 14 important traits utilizing data from four different mapping populations involving different approaches of QTL analysis. Analysis for grain protein content (GPC) sug- gested that the major part of genetic variation for this trait is due to environmental interactions. In contrast, pre-harvest sprouting tolerance (PHST) was controlled mainly by main effect QTL (M-QTL) with very little genetic variation due to environmental interactions; a major QTL for PHST was detected on chromosome arm 3AL. For grain weight, one QTL each was detected on chromosome arms 1AS, 2BS and 7AS. QTL for 4 growth related traits taken together detected by different methods ranged from 37 to 40; nine QTL that were detected by single-locus as well as two-locus analyses were all M-QTL. Similarly, single-locus and two-locus QTL analyses for seven yield and yield contributing traits in two populations respectively allowed detection of 25 and 50 QTL by composite interval mapping (CIM), 16 and 25 QTL by multiple-trait composite interval mapping (MCIM) and 38 and 37 QTL by two-locus analyses. These studies should prove useful in QTL cloning and wheat improvement through marker aided selection. | PUSHPENDRA Kumar Gupta HARINDRA Singh Balyan PAWAN Laxminarayan Kulwal NEERAJ Kumar AJAY Kumar REYAZUL Rouf Mir AMITA Mohan JITENDRA Kumar | 2007 | Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)2007，8，11： | 1 |
| 4 | Anticipa- toryreactive power reserve maximization using differential evo- lution显示文摘 | ARYA L D PUSHPENDRA SINGH TITARE L S | 2012 | International Journal of Electrical Power & Energy Systems2012，35，1： | 1 |
| 5 | Insulin receptor (IR) and insulin-like growth factor receptor 1 (IGF-1R) signaling systems: novel treatment strategies for cancer显示文摘 | Pushpendra Singh Jimi Marin Alex Felix Bast | 2014 | Medical Oncology2014，，1： | 1 |
| 6 | Gene networks in hexaploid wheat: interacting quantitative trait loci for grain protein content显示文摘 | Pawan Kulwal Neeraj Kumar Ajay Kumar Raj Kumar Gupta Harindra Singh Balyan Pushpendra Kumar Gupta | 2005 | Functional & Integrative Genomics2005，，4： | 1 |
| 7 | Glycine Soja-a Source of Resistance for Bihar Hairy Caterpillar, Spilosoma (=Diacrisia) Obliqua Wallace, in Soybean显示文摘 | Pushpendra K Singh Ranjit | 1989 | Soybean Genetic Newsietter1989，16，： | 1 |
| 8 | Particles dispersion on fluid-liquid interfaces显示文摘This paper is concerned with the dispersion of particles on the fluid-liquid interface. In a previous study we have shown that when small particles, e.g., flour, pollen, glass beads, etc., contact an air-liquid interface, they disperse rapidly as if they were in an explosion. The rapid dispersion is due to the fact that the capillary force pulls particles into the interface causing them to accelerate to a large velocity. In this paper we show that motion of particles normal to the interface is inertia dominated; they oscillate vertically about their equilibrium position before coming to rest under viscous drag. This vertical motion of a particle causes a radially-outward lateral (secondary) flow on the interface that causes nearby particles to move away. The dispersion on a liquid-liquid interface, which is the primary focus of this study, was relatively weaker than on an air-liquid interface, and occurred over a longer period of time. When falling through an upper liquid the particles have a slower velocity than when falling through air because the liquid has a greater viscosity. Another difference for the liquid-liquid interface is that the separation of particles begins in the upper liquid before the particles reach the interface. The rate of dispersion depended on the size of the particles, the densities of the particle and liquids, the viscosities of the liquids involved, and the contact angle. For small particles, partial pinning and hysteresis of the three-phase contact line on the surface of the particle during adsorption on liquid-liquid interfaces was also important. The frequency of oscillation of particles about their floating equilibrium increased with decreasing particle size on both air-water and liquid-liquid interfaces, and the time to reach equilibrium decreased with decreasing particle size. These results are in agreement with our analysis. | Sathish Gurupatham Bhavin Dalal Md.Shahadat Hossain Ian S.Fischer Pushpendra Singh Daniel D.Joseph | 2011 | Particuology2011，9，1： | 0 |
| 9 | An Approach Using Fuzzy Sets and Boosting Techniques to Predict Liver Disease显示文摘The aim of this research is to develop a mechanism to help medical practitioners predict and diagnose liver disease.Several systems have been proposed to help medical experts by diminishing error and increasing accuracy in diagnosing and predicting diseases.Among many existing methods,a few have considered the class imbalance issues of liver disorder datasets.As all the samples of liver disorder datasets are not useful,they do not contribute to learning about classifiers.A few samples might be redundant,which can increase the computational cost and affect the performance of the classifier.In this paper,a model has been proposed that combines noise filter,fuzzy sets,and boosting techniques(NFFBTs)for liver disease prediction.Firstly,the noise filter(NF)eliminates the outliers from the minority class and removes the outlier and redundant pair from the majority class.Secondly,the fuzzy set concept is applied to handle uncertainty in datasets.Thirdly,the AdaBoost boosting algorithm is trained with several learners viz,random forest(RF),support vector machine(SVM),logistic regression(LR),and naive Bayes(NB).The proposed NFFBT prediction system was applied to two datasets(i.e.,ILPD and MPRLPD)and found that AdaBoost with RF yielded 90.65%and 98.95%accuracy and F1 scores of 92.09%and 99.24%over ILPD and MPRLPD datasets,respectively. | Pushpendra Kumar Ramjeevan Singh Thakur | 2021 | Computers, Materials & Continua2021，，9： | 0 |
| 10 | Use of methylation filtration and Cot fractionation for analysis of genome composition and comparative genomics in bread wheat显示文摘We investigated the compositional and structural differences in sequences derived from different fractions of wheat genomic DNA obtained using methylation filtration and C0t fractionation.Comparative analysis of these sequences revealed large compositional and structural variations in terms of GC content,different structural elements including repeat sequences(e.g.,transposable elements and simple sequence repeats), protein coding genes,and non-coding RNA genes.A correlation between methylation status[determined on the basis of selective inclusion/ exclusion in methylation-filtered(MF) library]of different repeat elements and expression level was observed.The expression levels were determined by comparing MF sequences with expressed sequence tags(ESTs) available in the public domain.Only a limited overlap among MF, high C0t(HC),and ESTs was observed,suggesting that these sequences may largely either represent the low-copy non-transcribed sequences or include genes with low expression levels.Thus,these results indicated a need to study MF and HC sequences along with ESTs to fully appreciate complexity of wheat gene space. | Rajib Bandopadhyay Sachin Rustgi Rajat Kanti Chaudhuri Paramjit Khuran Jitendra Paul Khurana Akhilesh Kumar Tyagi Harindra Singh Balyan Andreas Houben Pushpendra Kumar Gupta | 2011 | Journal of Genetics and Genomics2011，38，7： | 0 |
| 11 | Implications of future climate change on crop and irrigation water requirements in a semi-arid river basin using CMIP6 GCMs显示文摘Agriculture faces risks due to increasing stress from climate change,particularly in semi-arid regions.Lack of understanding of crop water requirement(CWR)and irrigation water requirement(IWR)in a changing climate may result in crop failure and socioeconomic problems that can become detrimental to agriculture-based economies in emerging nations worldwide.Previous research in CWR and IWR has largely focused on large river basins and scenarios from the Coupled Model Intercomparison Project Phase 3(CMIP3)and Coupled Model Intercomparison Project Phase 5(CMIP5)to account for the impacts of climate change on crops.Smaller basins,however,are more susceptible to regional climate change,with more significant impacts on crops.This study estimates CWRs and IWRs for five crops(sugarcane,wheat,cotton,sorghum,and soybean)in the Pravara River Basin(area of 6537 km^(2))of India using outputs from the most recent Coupled Model Intercomparison Project Phase 6(CMIP6)General Circulation Models(GCMs)under Shared Socio-economic Pathway(SSP)245 and SSP585 scenarios.An increase in mean annual rainfall is projected under both scenarios in the 2050s and 2080s using ten selected CMIP6 GCMs.CWRs for all crops may decline in almost all of the CMIP6 GCMs in the 2050s and 2080s(with the exceptions of ACCESS-CM-2 and ACCESS-ESM-1.5)under SSP245 and SSP585 scenarios.The availability of increasing soil moisture in the root zone due to increasing rainfall and a decrease in the projected maximum temperature may be responsible for this decline in CWR.Similarly,except for soybean and cotton,the projected IWRs for all other three crops under SSP245 and SSP585 scenarios show a decrease or a small increase in the 2050s and 2080s in most CMIP6 GCMs.These findings are important for agricultural researchers and water resource managers to implement long-term crop planning techniques and to reduce the negative impacts of climate change and associated rainfall variability to avert crop failure and agricultural losses. | Kunal KARAN Dharmaveer SINGH Pushpendra K SINGH Birendra BHARATI Tarun P SINGH Ronny BERNDTSSON | 2022 | Journal of Arid Land2022，14，11： | 0 |
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