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This paper aims to draw lessons for telecommunications (telecom) network deployment in India, from a study of policy and regulatory approaches taken by other federal administrations in streamlining processes for site clearances, grant of rights of way (RoW) and approvals for local infrastructure deployment and sharing. With the urgent need for setting up small cells and rapid fiberisation of networks in the 5G era, the importance of such processes has gained prominence.

The authors adopt qualitative thematic content analysis with three-tier coding and classification to identify themes in archival and current documentary data and information obtained from subject-matter experts in the countries studied.

Formulation and implementation of telecom policy is led by national governments. However, national telecom administrations, in recognition of new needs, have co-opted states and local authorities as partners in development of telecom networks, providing the overall framework, guidance and appropriate incentives where required.

This cooperative model could work well in India, where telecom policy making and regulation is the prerogative of the central government, but administration of RoW and local clearances for cable laying, tower siting and associated infrastructure activities for expanding telecom networks are left to decentralised decision-making in the states and local bodies.

This research attempts to sytematise, thematise and draw cross-country comparisons to inform regulatory and administrative policy for 5G infrastructure rollout in India.

The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model.

The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model.

The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity.

The R&D productivity model can be adapted by the R&D laboratories to enhance researchers’ R&D involvement, increased R&D outputs and achieving self-sustenance in long run.

The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers.

Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers’ productivity.

This paper intends to explore the measure for aligning the goals of researchers toward achieving organizational R&D targets. The paper also explores the significance and ordering of R&D outputs and the factors that influence generation of R&D outputs, from the perspective of researchers working in the Indian public sector organizations.

Data were collected in five Indian R&D laboratories, and weighted average method Spearman correlation coefficient and rank regression were utilized for the analysis.

The findings indicated that various groups of researchers prefer to target different R&D outputs and not all the factors are considered as equally significant in influencing the generation of R&D outputs. Further, the R&D organization should include preferred real factors while policy making for achieving collaborative efforts toward fulfilling organizational objectives. The set of selected R&D outputs and influencing factors were also ordered according to the average rankings given by the researchers.

The findings can help R&D managers to identify the expectations of the researchers and include their preferences in R&D Planning. The study could be extended to a larger dataset of researchers working in other government as well as private R&D organizations.

Hardly any studies were found that explored the preferences of researchers with respect to R&D outputs and influencing factors with respect to the Indian public sector R&D laboratories.

Purpose: This chapter explores the two major schemes applicable to skill development in India: Skill Acquisition and Knowledge Awareness for Livelihood Promotion (SANKALP) and Pradhan Mantri Kaushal Vikas Yojana (PMKVY).

Need for the Study: The primary objective of this research is to check the role of these schemes in enhancing the skills of socio-economically stressed community members for their livelihoods. The secondary aim is to analyse the outcomes of these schemes through a qualitative inquiry.

Methodology: A survey was conducted, and the data was collected from trainees of the skill development programmes. Based on the responses, a qualitative content analysis was performed, which showed that most trainees have the thirst and urge to enhance their life skills for a minimalistic livelihood.

Findings: The study concluded that though there are many schemes, only PMKVY is active. They focus on more than just youth communities. Instead, they consider individuals in different age categories.

Practical Implications: The Government of India (GOI) is progressing towards a healthy economy to compete with other countries. For this mission to be achieved, skill and labour development is paramount. Appropriate training must be provided and administrated through government schemes.

Adiponectin, a bioactive molecule produced by adipose tissue, has potential effect in increasing insulin sensitivity. Adiponectin levels reduction is associated with type 2 diabetes mellitus (T2DM) and its complications, including cardiovascular disease (CVD). Triglyceride-to-high-density lipoprotein (TG:HDL) ratio can be used as a predictor of CVD risk in T2DM patients. Whiteleg shrimp (Litopenaeus vannamei) shell contains astaxanthin, macro- and micro-nutrients that may exert synergistic beneficial effects. This study aims to determine the effect of L. vannamei shell powder (LVSP) in improving adiponectin, TG, HDL and TG:HDL of T2DM Wistar rat, and to investigate the presence of any correlations between adiponectin and lipid markers.

A total of 25 male Wistar rats were divided into five equal groups: control negative [C(−)], control positive [C(+)], treatments 1, 2 and 3 (T1, T2 and T3, respectively). C(+), T1, T2 and T3 were maintained on a high-fat diet for 14 days before streptozotocin (STZ) injection. T1 and T2 groups were administered two different doses of LVSP, while T3 group was provided astaxanthin supplement (AST).

LVSP treatments significantly increase adiponectin (p =0.04) and HDL (p <0.001) but reduced TG (p <0.001) and TG:HDL (p <0.001). A higher LVSP dose was more effective in improving all markers than the lower dose; moreover, there was a comparable effect as that of AST in increasing the adiponectin levels. Strong correlations were observed between adiponectin and lipid markers.

This study shows that LVSP as a functional food, can ameliorate adiponectin levels and normalizes blood glucose levels. The LVSP reduces the risk of CVD because of the reduction of TG:HDL.

This study aims to determine the most similar set of recommendation books to the user selections in LibraryThing.

For this purpose, 30,000 tags related to History on the LibraryThing have been selected. Their tags and the tags of the related recommended books were extracted from three different recommendations sections on LibraryThing. Then, four similarity criteria of Jaccard coefficient, Cosine similarity, Dice coefficient and Pearson correlation coefficient were used to calculate the similarity between the tags. To determine the most similar recommended section, the best similarity criterion had to be determined first. So, a researcher-made questionnaire was provided to History experts.

The results showed that the Jaccard coefficient, with a frequency of 32.81, is the best similarity criterion from the point of view of History experts. Besides, the degree of similarity in LibraryThing recommendations section according to this criterion is equal to 0.256, in the section of books with similar library subjects and classifications is 0.163 and in the Member recommendations section is 0.152. Based on the findings of this study, the LibraryThing recommendations section has succeeded in introducing the most similar books to the selected book compared to the other two sections.

To the best of the authors’ knowledge, itis for the first time, three sections of LibraryThing recommendations are compared by four different similarity criteria to show which sections would be more beneficial for the user browsing. The results showed that machine recommendations work better than humans.