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The purpose of this paper is to provide an overview of the J-Gate Plus Discovery and Resource Sharing Model, and to examine the interlending and document delivery service within the Indian university system and the UGC-Infonet Digital Library Consortium.

This paper describes the functionalities of J-Gate Plus services and discusses how it become a successful product in the Indian academic sector. Finally, the paper analyses the search trends and document delivery request reports.

Information and Library Network, Inter-library loan Centres (universities) and J-Gate@UGC-Infonet are cooperating to facilitate resource sharing in India and to gradually expand their roles to other academic library systems.

The paper is an up-to-date study of resource sharing in the Indian university system through the J-Gate@UGC-Infonet service.

The purpose of this study was to optimize meat slices for processing attributes to produce better sensory features in developed products from buffalo veal and chevon. The processing parameters such as meat particle size, fat content and binding ability without chopping were the subject of this study.

The study involved three experiments where the particle size, fat content and tumbling time were optimized for optimum binding and improvement in different sensory attributes of product followed by physico-chemical analysis.

The sensory scores clearly indicated that meat slices prepared from 3 mm meat particle size, 10% fat content and 1 h tumbling time were having best sensory features. The selected product was analyzed for different physico-chemical properties. Emulsion stability and cooking yield revealed significantly (p = 0.01) higher values of 91.6% and 89.7%, respectively, in buffalo veal than in values of 87.6% and 84.9%, respectively, in the chevon product. Similarly the results showed that buffalo veal slices had significantly (p = 0.01) higher (17.4%) protein than the chevon (15.2%), whereas chevon slices had significantly (p = 0.01) higher (10.3%) fat content. The texture profile analysis indicated that cohesiveness (p = 0.01) and chewiness (p = 0.05) were significantly higher in chevon product than in buffalo veal.

The study was conducted to explore the buffalo veal as a potential source of quality meat, as majority of buffalo meat produced in India from spent animals have compromised quality attributes. The comparison was done with chevon, the most popular red meat in the country for the comparative study.

The purpose of this paper is to examine the nature of relationship between ethical leadership and employee voice behavior. Study of employee voice behavior is important, because leaders in organizations make numerous decisions based on employees’ work-related inputs which do influence the decision quality and team performance.

Survey data were collected through structured questionnaire from Indian organizations. Data were analysed through statistical techniques such as confirmatory factor analysis and structural equation modeling.

The findings showed that ethical leadership did impact the employee voice in a positive and significant but moderate manner. The study also found no significant differences in ethical leadership and voice behavior across demographic variables such as gender, age, educational qualification and job level in the Indian context.

The study is conducted using single cross-sectional research design, and for better causal inferences of the relationship between various variables, future research studies may be conducted with longitudinal research design, multiple data sources and variety of industries with large sample size.

With erosion of ethical values and corporate scandals, managers need to develop and display ethical leadership as employees emulate their leaders’ ethical behavior because ethical leadership, or its perception, relates positively and significantly to employee voice behavior.

There is less study to understand ethical leadership and its influence on voice behavior in developing countries, especially in India. Ethical leadership behavior encourages employees to voice their work-related constructive opinions and concerns for improved decision-making and reduced unethical practices. Also, there is scarcity of research that explores the impact of demographic variables and this study is an effort to understand this gap.

This paper aims to study the effects of plum powder and apple pomace powder additions on the quality properties of buffalo meat emulsion.

Buffalo meat emulsions were prepared using different levels (2%, 4% and 6%) of plum powder and apple pomace powder, respectively. The meat emulsions were analysed for the physico-chemical, sensory and textural properties of the meat emulsion.

The pH of meat emulsions decreased significantly (p < 0.05) with an increased level of plum powder and apple pomace powder. Water-holding capacity (43.1%–48.1%), emulsion stability (80.2%–92.2%) and cooking yield (85.4%–91.0%) were significantly (p < 0.05) higher in plum powder and apple pomace powder added than the water-holding capacity (42.1%), emulsion stability (79.7%) and cooking yield (85.0%) of control emulsion. The moisture content was decreased significantly (p < 0.05), and crude fibre content was increased significantly (p < 0.05) with the increase in plum powder and apple pomace powder additions in meat emulsions. The total phenolic content and colour values (a* and b*) were significantly higher in plum powder and apple pomace powder added to meat emulsions. The sensory scores of meat emulsions were affected by the addition of plum powder and apple pomace powder. The meat emulsion added with 6% plum powder and 6% apple pomace powder showed significantly lower values of sensory overall acceptability. The hardness of meat emulsions increased with the addition of plum powder and apple pomace powder.

The results indicated that meat emulsions with a good cooking yield, fibre content, sensory acceptability and textural properties can be prepared by using plum powder and apple pomace powder.

This paper aims to study the effect of orange peel and moringa leaves extracts on microbiological safety, sensory quality, lipid oxidation and color properties of chicken sausages under frozen storage.

Chicken sausages were prepared by using orange peel, moringa leaves extracts and butylated hydroxytoluene (BHT). The sausages were stored in a freezer at −18°C. Samples were taken at a regular interval of 20 days from the day of production to spoilage of sausages and analyzed for microbiological safety, sensory quality, lipid oxidation and color properties.

In comparison to the control sausage, sausages having BHT, orange peel and moringa leaves extract had a significantly (p < 0.05) lower bacterial, yeast and mold count. All the sausages were microbiologically safe for consumption till the 100th day, and the results of the 120th day crossed the permissible limits. Sensory acceptability scores of sausages were good (>6) throughout the storage period. The color values of sausages were not affected by the addition of orange peel and moringa leaves extract. The extent of lipid oxidation increased during storage, and sausages with BHT, orange peel and moringa leaves extract had significantly (p < 0.05) lower values of thiobarbituric acid reactive substances and free fatty acids (FFAs) toward the end of the storage period.

The observations of this paper endorse the use of orange peel and moringa leaves extract in meat products formulation for acceptable storage stability under frozen conditions.

In this research work, the general form of reliability measures, which include availability, mean time to failure (MTTF), and sensitivity analysis, are investigated with their graphical representation, which would help designers and engineers improve the reliability of the system. Along with reliability assessment, a mathematical model is developed and solved to achieve the minimum cost of the system as well as maximum reliability.

In the proposed work, a general model of a solar seed sowing machine is considered for reliability evaluation using the Markov model process. The proposed system is a series-parallel arrangement of components where three components, namely the solar panel, batteries and direct current (DC) motor, are connected in series while all the operators are connected in parallel. The implemented Markov model approach assesses several parameters of reliability, which opens the scope for improvement in reliability and other measures like mean time to failure (MTTF) and sensitivity of the proposed system. So that the machine can deliver the desired output on the field. Also, the particle swarm optimization (PSO) algorithm is applied to optimize the cost of the system with the desired level of reliability.

Implementation of PSO provides the optimal cost for the proposed system with a predetermined level of reliability, which shows the relationship between reliability and cost of the system. Also, the Markov process approach provides the availability function, reliability function, reliability at different time values, MTTF and sensitivity of the proposed system.

This work evaluates the crucial characteristics of reliability for the proposed solar seed sowing machine using the Markov model which is a stochastic model. The assessment of reliability measures such as MTTF, availability and sensitivity plays a vital role in measuring and improving the performance of the machine in the actual environment. Examining the data obtained in this research is of great importance for the manufactures and system designers. Also, the powerful optimization technique PSO is implemented to solve a non-linear mixed-integer programming problem that provides the optimal cost for the system with desired reliability.

The objective of this study is to analyse the integration of technology in Human Resources Management (HRM) with a special focus on Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT) and Big Data.

This study aims to contribute to the understanding of these trends by conducting a thorough bibliometric analysis using the Scopus database, encompassing research on HRM and Technology from 1991 to 2022. By employing citation analysis, co-citation analysis and co-word analysis, the study uncovers key patterns and trends in the field.

The findings indicate that AI, Big Data and ML are the focal points of research when exploring the intersection of Technology and HRM. These technologies offer promising prospects for enhancing Human Resource processes, such as Talent Acquisition, Performance Management and Employee Engagement.

In our study, we showcase the practical implications that offer guidance for HR researchers and professionals, enabling them to make informed decisions regarding the adoption and implementation of Information Technology.

This research can provide valuable insights to HR managers on the use of cutting-edge technology in HRM. It aims to enhance the manager’s awareness of how technology-enabled HRM can improve HR performance.

This study adds to the existing body of knowledge on how Modern Technology empowers HRM. It also proposes a conceptual framework for the use of Modern Technology along with Strategic Management and Knowledge Management to improve Human Resource Performance.

Agriculture, since time immemorial, has been a major sector in reducing poverty, accelerating economic activities and source of sustainability of a nation. As most of the youth in the 21st century are targeting the youth's career in the non-agricultural sector, attracting and involving the youths in agribusinesses is the need of the hour. In this regard, the research tries to understand the awareness and involvement of youth farmers in agripreneurship in Western Nepal.

Using a structured questionnaire, data were collected from both primary and secondary sources. On the basis of descriptive and inferential analysis, the ordered logit model is employed in the study. The research is based on explanatory research design through identifying farmers' awareness of agriculture entrepreneurship from 324 farmers of Bedkot Municipality, Kanchanpur, Nepal.

Study findings have shown that agricultural knowledge with overall awareness is statistically significant. Ordered logistic regression indicated that sex has somehow influenced technical and entrepreneur skills while agriculture information highly influenced education and training. The result shows that agricultural training is still the requirement of one-fourth of the farmers, whereas another quarter of farmers need subsidies.

The study suggests that in order to enhance awareness, training, subsidy, market management and development program are widely needed. In the backdrop of declining agro-products and food security challenges, the study targets to offer an understanding to policymakers and stakeholders on addressing the dire need of agripreneurship among the youths around the world.

The study summarizes the state of knowledge of agripreneurship of Nepalese farmers, identifies emerging issues and policy implications and priorities for future applied research.

This research introduces an innovation strategy aimed at bolstering the reliability of a renewable energy resource, which is hybrid energy systems, through the application of a metaheuristic algorithm. The growing need for sustainable energy solutions underscores the importance of integrating various energy sources effectively. Concentrating on the intermittent characteristics of renewable sources, this study seeks to create a highly reliable hybrid energy system by combining photovoltaic (PV) and wind power.

To obtain efficient renewable energy resources, system designers aim to enhance the system’s reliability. Generally, for this purpose, the reliability redundancy allocation problem (RRAP) method is utilized. The authors have also introduced a new methodology, named Reliability Redundancy Allocation Problem with Component Mixing (RRAP-CM), for optimizing systems’ reliability. This method incorporates heterogeneous components to create a nonlinear mixed-integer mathematical model, classified as NP-hard problems. We employ specially crafted metaheuristic algorithms as optimization strategies to address these challenges and boost the overall system performance.

The study introduces six newly designed metaheuristic algorithms. Solve the optimization problem. When comparing results between the traditional RRAP method and the innovative RRAP-CM method, enhanced reliability is achieved through the blending of diverse components. The use of metaheuristic algorithms proves advantageous in identifying optimal configurations, ensuring resource efficiency and maximizing energy output in a hybrid energy system.

The study’s findings have significant social implications because they contribute to the renewable energy field. The proposed methodologies offer a flexible and reliable mechanism for enhancing the efficiency of hybrid energy systems. By addressing the intermittent nature of renewable sources, this research promotes the design of highly reliable sustainable energy solutions, potentially influencing global efforts towards a more environmentally friendly and reliable energy landscape.

The research provides practical insights by delivering a comprehensive analysis of a hybrid energy system incorporating both PV and wind components. Also, the use of metaheuristic algorithms aids in identifying optimal configurations, promoting resource efficiency and maximizing reliability. These practical insights contribute to advancing sustainable energy solutions and designing efficient, reliable hybrid energy systems.

This work is original as it combines the RRAP-CM methodology with six new robust metaheuristics, involving the integration of diverse components to enhance system reliability. The formulation of a nonlinear mixed-integer mathematical model adds complexity, categorizing it as an NP-hard problem. We have developed six new metaheuristic algorithms. Designed specifically for optimization in hybrid energy systems, this further highlights the uniqueness of this approach to research.

This study aims to conduct a comprehensive review and network-based analysis by exploring future research directions in the nexus of circular economy (CE) and sustainable business performance (SBP) in the context of digitalization.

A systematic literature review methodology was adopted to present the review in the field of CE and SBP in the era of digitalization. WOS and SCOPUS databases were considered in the study to identify and select the articles. The bibliometric study was carried out to analyze the significant contributions made by authors, various journal sources, countries and different universities in the field of CE and SBP in the era of digitalization. Further, network analysis is carried out to analyze the collaboration among authors from different countries.

The study revealed that digitalization could be a great help in developing sustainable circular products. Moreover, the customers' involvement is necessary for creating innovative sustainable circular products using digitalization. A move toward the product-service system was suggested to accelerate the transformation toward CE and digitalization.

The paper discusses digitalization and CE practices' adoption to enhance the SP of the firms. This work's unique contribution is the systematic literature analysis and bibliometric study to explore future research directions in the nexus of CE and SP in the context of digitalization. The present study has been one of the first efforts to examine the literature of CE and SBP integration from a digitalization perspective along with bibliometric analysis.