995 research outputs found
Management techniques for employee engagement in contemporary organizations/ Naman Sharma, Narendra Chaudhary, and Vinod Kumar Singh, editors.
No full text"This book identifies the various issues which affect the employee engagement and propose the various solutions to resolve the ongoing issues. It helps to unfold the various facets of the employee engagement and related aspects"--1 online resource
Residue Management and Nutrient Stoichiometry Control Greenhouse Gas and Global Warming Potential Responses in Alfisols
Full text linkAlthough crop residue returns are extensively practiced in agriculture, large uncertainties remain about greenhouse gas (GHG) emissions and global warming potential (GWP) responses to residue return (RR) rates under different residue placements and nutrient supplements. We conducted a laboratory mesocosm experiment in Alfisol in central India to investigate the responses of soil GHG emissions (CO2, N2O, and CH4) and the global warming potential to four wheat RR rates (R0: no residue; R5: 5 Mg/ha; R10: 10 Mg/ha; R15: 15 Mg/ha) and two placements (surface [Rsur] and incorporated [Rinc]) under three nutrient supplement levels (NSLs) (NS0: no nutrients, NS1: nutrients (N and P) added to balance the stoichiometry of C:N:P to achieve 30% humification in RR at 5 t/ha, NS2: 3 × NS1). The results demonstrated a significant (p R5 (3.8) > R15 (2.6) > R0 (1.6). Our results demonstrated a significant linear response of total GWP to RR rates R15 > R10 > R5 > R0, ranging from 201.4 to 1563.6 mg CO2 eq kg−1 soil. In conclusion, quadratic/linear responses of GHGs to RR rates underscore the need to optimize RR rates with nutrient supplements and residue placement to reduce GHG emissions and GWP while ensuring optimal soil health and crop productivity.This article is published as Singh, Dharmendra, Sangeeta Lenka, Narendra Kumar Lenka, Dinesh Kumar Yadav, Shashi S. Yadav, Rameshwar S. Kanwar, Abhijit Sarkar, and Jitendra Kushwaha. "Residue Management and Nutrient Stoichiometry Control Greenhouse Gas and Global Warming Potential Responses in Alfisols." Sustainability 16, no. 10 (2024): 3997. doi: https://doi.org/10.3390/su16103997
Systematic Review of Library and Information Research in SAARC Countires
Full text linkThis study provides a systematic review of library and information science research in SAARC countries. The data were taken from the Scopus database for the period 2002-2021. A total of 1183 records were found in this study. VOSviewer software was then used to visualize the data. The results show that the growth rate of publications is very constant. The most prolific author was Ameen, K., who produced 26 articles and 158 citations. Furthermore, India was the leading country for LIS research in SAARC countries, with 863 documents, whereas Library Philosophy and Practice was the most favored source, with 301 documents. This study can be useful in identifying trends in library and information research in SAARC countries
Analysis of genetic variability and genotype 3 environment interactions for iron and zinc content among diverse genotypes of lentil
No full textDeficiencies of iron (Fe) and zinc (Zn) are major problems in developing countries especially for woman and preschool children. Biofortification of staple food crops is a sustainable approach to improve human mineral intake via daily diet. Objectives of this study were to (1) determine the genetic variability for Fe and Zn content in cultivated indigenous and exotic lentil genotypes, and (2) determine the effect of genetic (G) 9 environmental (E) interaction on Fe and Zn content in 96 lentil genotypes grown in India over the 2 years. Significant genetic variability was observed for Fe and Zn content in lentil genotypes. Content ranged from 71.3 to 126.2 mg/kg for Fe, and 40.1 to 63.6 mg/kg for Zn. For Fe, cultivars and parental lines (71.3–126.2 mg/kg) showed slightly higher content than the breeding lines (76.8–124.3 mg/kg). For Zn, content were similar for both cultivars and breeding lines. However, year and the genotype 9 year interaction were significant for both Fe and Zn. Broad sense heritability estimates were found to be 45.8, 45.4 and 40.1 for Fe; 30.0, 63.0 and 69.0 for Zn content in breeding lines, cultivars/parental lines, and exotic lines, respectively. These heritability estimates indicated the potential of these lentil genotypes towards genetic improvement for increased Fe and Zn content using hybridization and selection over several generations. Significant positive correlation of Fe content and seed weight suggested a selection strategy for developing large seeded lentil for accumulation of more Fe in the seeds. No correlation was observed between Fe and Zn content. Further, recombination of Fe and Zn content is possible by developing recombination breeding. Thus present study findings would be useful in future for mapping and tagging the genes/QTL controlling Fe and Zn content and developing the improved biofortified cultivars
Deep Learning Paradigm and Its Bias for Coronary Artery Wall Segmentation in Intravascular Ultrasound Scans: A Closer Look
Full text linkBackground and motivation: Coronary artery disease (CAD) has the highest mortality rate; therefore, its diagnosis is vital. Intravascular ultrasound (IVUS) is a high-resolution imaging solution that can image coronary arteries, but the diagnosis software via wall segmentation and quantification has been evolving. In this study, a deep learning (DL) paradigm was explored along with its bias. Methods: Using a PRISMA model, 145 best UNet-based and non-UNet-based methods for wall segmentation were selected and analyzed for their characteristics and scientific and clinical validation. This study computed the coronary wall thickness by estimating the inner and outer borders of the coronary artery IVUS cross-sectional scans. Further, the review explored the bias in the DL system for the first time when it comes to wall segmentation in IVUS scans. Three bias methods, namely (i) ranking, (ii) radial, and (iii) regional area, were applied and compared using a Venn diagram. Finally, the study presented explainable AI (XAI) paradigms in the DL framework. Findings and conclusions: UNet provides a powerful paradigm for the segmentation of coronary walls in IVUS scans due to its ability to extract automated features at different scales in encoders, reconstruct the segmented image using decoders, and embed the variants in skip connections. Most of the research was hampered by a lack of motivation for XAI and pruned AI (PAI) models. None of the UNet models met the criteria for bias-free design. For clinical assessment and settings, it is necessary to move from a paper-to-practice approach
Analysis of genetic variability and genotype × environment interactions for iron and zinc content among diverse genotypes of lentil
No full textDeficiencies of iron (Fe) and zinc (Zn) are major problems in developing countries especially for woman and preschool children. Biofortification of staple food crops is a sustainable approach to improve human mineral intake via daily diet. Objectives of this study were to (1) determine the genetic variability for Fe and Zn content in cultivated indigenous and exotic lentil genotypes, and (2) determine the effect of genetic (G) 9 environmental (E) interaction on Fe and Zn content in 96 lentil genotypes grown in India over the 2 years. Significant genetic variability was observed for Fe and Zn content in lentil genotypes. Content ranged from 71.3 to 126.2 mg/kg for Fe, and 40.1 to 63.6 mg/kg for Zn. For Fe, cultivars and parental lines (71.3–126.2 mg/kg) showed slightly higher content than the breeding lines (76.8–124.3 mg/kg). For Zn, content were similar for both cultivars and breeding lines. However, year and the genotype 9 year interaction were significant for both Fe and Zn. Broad sense heritability estimates were found to be 45.8, 45.4 and 40.1 for
Fe; 30.0, 63.0 and 69.0 for Zn content in breeding lines, cultivars/parental lines, and exotic lines, respectively. These heritability estimates indicated the potential of these lentil genotypes towards genetic improvement for increased Fe and Zn content using hybridization and selection over several generations. Significant positive correlation of Fe content and seed weight suggested a selection strategy for developing large seeded lentil for accumulation of more Fe in the seeds. No correlation was observed between Fe and Zn content. Further, recombination of Fe and Zn content is possible by developing recombination breeding. Thus present study findings would be useful in future for mapping and tagging the genes/QTL controlling Fe and Zn content and developing the improved biofortified cultivars
An Analytical Study on Research Data Management in Higher Educational Institutions with Special Reference to India
No full textThe present era witnesses an exponential growth in research data generated by Higher Educational Institutions (HEIs) across the globe. As this data becomes increasingly critical for advancing scientific knowledge, it is essential to ensure its efficient management, preservation, and accessibility. This Ph.D. thesis titled "An Analytical Study on Research Data Management in Higher Educational Institutions with Special Reference to India" addresses the pressing need for effective research data management practices in Indian HEIs.
Under the esteemed guidance of Dr. Biswanath Dutta, Associate Professor at the Documentation Research and Training Centre (DRTC), Indian Statistical Institute (ISI) in Bangalore, the researcher embarks on an in-depth exploration of research data management practices within the context of Indian higher education.
The primary objective of this Ph.D. thesis is to conduct an analytical study to understand the current state of research data management practices in Indian HEIs. The research will delve into identifying the existing infrastructural capabilities, policies, and frameworks governing research data management in these institutions. Furthermore, the study aims to evaluate the adoption of best practices among researchers, faculty, and other stakeholders involved in research data management.
Intellectual Property Rights Statement: The ideas presented in this Ph.D. thesis project belong to Narendra Kumar Bhoi and are protected by copyright laws. Any unauthorized use, reproduction, distribution, or adaptation of the content without proper acknowledgment or permission is strictly prohibited. All rights are reserved by the author
Effect of Plant Geometry and Nutrient Inputs from Organic and Inorganic Sources on the Growth and Yield Attributes of Rice (Oryza sativa L.) in Eastern U.P.
Full text linkRice (Oryza sativa L.) is the most important staple food of the Indian population. The presentstudy was conducted at Agronomy Research Farm, Acharya Narendra Deva University ofAgriculture and Technology, Kumar Ganj, Ayodhya, Uttar Pradesh, on silty loam soil during2023–24 and 2024–25 to study the productivity of rice
Optimizing residue return with soil moisture and nutrient stoichiometry reduced greenhouse gas fluxes in Alfisols
Full text linkOptimum soil moisture and high crop residue return (RR) can increase the active pool of soil organic carbon and nitrogen, thus modulating the magnitude of greenhouse gas (GHG) fluxes. To determine the effect of soil moisture on the threshold level of RR for the wheat production system, we analyzed the relationship between GHG fluxes and RR at four levels, namely 0, 5, 10, and 15 Mg ha−1 (R0, R5, R10, and R15) under two soil moisture content (80% FC and 100% FC) and three levels of nutrient management (NS0: no nutrient; NS1, NS2= 3x NS1). Nutrient input (N and P) in NS1 balanced the residue C/nutrient stoichiometry to achieve 30% stabilization of the residue C input in RR (R5). All RR treatments (cf. R0) were found to significantly reduce N2O emission in moderate soil moisture content (80% FC) by 22–56% across nutrient management due to enhanced soil C mineralization, microbial biomass carbon, and N immobilization. However, averaged across nutrient management, a linear increase in N2O emission was observed with increasing RR under 100% FC soil moisture. A significant decrease in CH4 emission by ca. 46% in most RR treatments was observed in 100% FC compared with the R0. The N2O emission was negatively correlated (p= 0.8) to management variables (RR rate, nitrogen (N) input rate, soil moisture, and nutrient stoichiometry of C: N) and post-incubation soil properties (SMBC and NO3-N) in Alfisols. This study demonstrated that the mechanisms responsible for RR effects on soil N2O, CH4 fluxes, and carbon mineralization depend on soil moisture and nutrient management, shifting the nutrient stoichiometry of residue C: N: P.This article is published as Singh, Dharmendra, Sangeeta Lenka, Narendra Kumar Lenka, Dinesh Kumar Yadav, Shashi S. Yadav, Rameshwar S. Kanwar, Abhijit Sarkar, and Madhumonti Saha. "Optimizing residue return with soil moisture and nutrient stoichiometry reduced greenhouse gas fluxes in Alfisols." Frontiers in Sustainable Food Systems 8 (2024): 1490523. https://doi.org/10.3389/fsufs.2024.1490523
Assessment of combining ability and heterosis in bottle gourd (Lagenaria siceraria L.) for yield and attributes character through line × tester design
Full text linkGeneral and specific combining ability variance and their effects were studied for thirteen characters in line × tester mating design in bottle gourd. Based on overall per se performance and among the parents, Narendra Dharidar, Punjab Long, and parents Narendra Rashmi were identified as good specific combiners for a maximum of 5 to 6 attributes, including yield for other contributing traits, suggesting that these parents may be used in the hybridization program aimed at the development of superior genotypes/varieties in bottle guard. Tester Arka Bahar and Narendra Madhuri were considered to be good general combiners for 6 to 8 characters. These parents must be utilized in a suitable breeding programme visa-vis selection breeding for improvement productivity of yield and per unit area in bottle gourd. Based on overall results and per se performance, the F1 hybrids, i.e. Pusa Sandesh × Kashi Ganga, IC-321747 × Narendra Madhuri, and NDBG-132 × Narendra Madhuri emerged to be the good specific combiners for maximum traits, including yield, which may be utilized for obtaining transgressive segregants in the next generation. Out of sixty-four cross combinations, only seventeen hybrids revealed superiority over better parents for yield. The seventeen cross combinations that showed more than 24% heterobeltiosis over better parents include: IC-498541×Narendra Madhuri, IC-592210×Arka bahar, Pusa Sandesh×Narendra Madhuri, NDBG-132×Pusa Naveen, Narendra Rashmi×Kashi Ganga, IC-321412×Pusa Naveen, Narendra Rashmi×Arka bahar, Narendra Rashmi×Pusa Naveen, Narendra Dharidar×Narendra Madhuri, Pusa Sandesh×Kashi Ganga, NDBG-132×Arka bahar, NDBG-132×Narendra Madhuri, Punjab long×Narendra Madhuri, Narendra Jyothi×Narendra Madhuri, IC-592210×Arka bahar, IC-338119×Arka bahar and IC- 498541×Kashi Ganga. This suggests that there is a great possibility to produce higher yielding varieties/genotypes
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