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The purpose of this paper is to establish the importance of land records for urban development. The study focuses on how traditionally land records were managed and presently what are the important parameters impacting the land record management systems in India.

The framework adopted for the study was as follows: 1) literature study: aim to study the historical issues, to study global systems across the globe, various government reforms. 2) Present system of land management: to study the administrative, legal, economic issues, problems and potential in the present system. 3) Technology interventions: to study how technology can help to make the system more robust and trustworthy. 4) Conclusion: to study how the recommended technological measures will work and how to implement it in the system. Several pilot interviews were carried out to understand how the present system of land record management works in India, and important parameters were established through the pilot interviews of various stakeholders in the system.

The study brings out certain striking facts about the inefficiencies in the system since centuries, which are still being carried forward. Any reforms by the authorities have not been able to solve the issues and reduce the number of litigations because digitisation was only a step forward to replicate the wrong entries of records in digitised format. Thus, a paradigm shift in technology is required to bring a considerable change in the present management system.

Various studies worldwide have been done in several countries regarding land records, but all the studies are in piecemeal basis. Very less literature is available on the study that how land records effect large scale urban development projects. This study is an attempt to study impact of land records on urban development and to bring back transparency in the system to reduce the number of litigations on the most important ingredient of built environment, which is land.

This study aims to examine the psycho-emotional and social experiences of caregivers of children with autism spectrum disorder. Various facets of the caregiving experience are explored, including the feelings and thoughts of the parents/caregivers, such as the resilience experienced in their journey, how they coped with the challenges and also their positive experiences.

In this study, these aspects of the caregiving experience are broadly probed using semi-structured interviews subjected to narrative analysis. Lastly, there is a focus on the role of therapist-led intervention, specifically, the Eye to I^© intervention model and its contributions to the parent/caregiver experience.

Findings from this study indicate that parents benefit from interventions that bridge gaps in skills and interpersonal communication which parents/caregivers feel they encounter in their day-to-day activities. Additionally, support groups for parents and caregivers could further address these issues.

This exploration reveals insights about the roles of societal structures and the caregiving journey.

Social enterprises (SEs) operate with a primary goal of meeting a social purpose while creating economic wealth for the fulfillment of their primary mission. These organizations need to develop a certain set of capabilities that facilitates the successful pursuit of their dual mission goals. This paper aims at exploring the micro-foundations of dynamic capabilities (DCs) that enable SEs to recognize and exploit opportunities and reconfigure their resources to pursue their dual-mission goals and adjust with the environmental dynamics.

This study uses a multiple case design and an abductive research approach to conduct an in-depth and in-due course investigation of the development of DCs in two distinct SEs selected on the basis of theoretical-purposive sampling and availability of the richness of the information about them.

This study finds certain generic and exclusive micro-foundations of DCs that contribute to sensing opportunities, seizing opportunities and reconfiguring resources in SEs. The exclusive micro-foundations of DCs of SEs noted in this study are sustainability of beneficiaries, involving beneficiaries in decision-making, defining unique business models and selective suppliers for critical resources.

The limitation of this study lies in its dependence on retrospective data, which may perhaps influence the comprehensiveness and accuracy of the acquired data. This study, although, implemented the measures to minimize the bias, by supplementing the interview data with archival sources.

To the researchers, this study proffers an in-depth and in-due course explanation of the micro-foundations of DCs that facilitate SEs to sense opportunities, seize opportunities and reconfigure their resources with time. To practitioners working in the area of social entrepreneurship, this process study is an outline of reference that answers the how and why concerning the importance of micro-foundations of DCs for SEs.

To the best of the authors’ knowledge, no prior study has explored the micro-foundations of DCs in the context of SEs from emerging economies. The exclusive micro-foundations of DCs for SEs found in this study are the unique and original contribution that outlines the path for future academic inquiry in this evolving research area.

This paper aims to epistemologically extend and explore the present theories from prior research conducted in the area of responsiveness. Furthermore, it determines to benchmark the prominent theories, characteristics, context and methodologies (TCCM) used in the domain since its inception to advance the science and practice of marketing and logistics discipline.

A seven-step methodology (SSM) has been introduced to create a comprehensive dataset. Based upon the selection criteria of high-ranked journals and language, the research studies have been retrieved from Scopus, Web of Science, Business Source Complete and journal homepage to avoid the error of exclusion. Moreover, the dataset has been compiled using manual and electronic searches without any limitation of time.

The search for a suitable dataset retrieved 642 documents by identifying “1969” as the beginning year of research in the subject domain. The analysis found that responsiveness has been prominently studied in the manufacturing industry. The results also advocate responsiveness as the vital antecedent to performance and satisfaction. Frameworks have been proposed with significant propositions for future empirical testing and theory inventiveness by researchers.

The study pioneers its utility for retailers to recognize the firms' inherent abilities and strengths, which can be promoted to create responsiveness more than ever. The analysis results can act as the compelling force to understand the driving power of various factors influencing responsiveness.

Calyx of okra pods is usually cut off and discarded as a waste during processing, whereas the pulp and seeds are being used. This study aims to investigate the nutrient composition and anti-nutritional properties of okra calyx flour.

Calyces from four varieties (Ex-kwadon, Solar, Chalawa and Syria) of okra pods were processed into flour. The proximate composition, mineral content, vitamin content and anti-nutritional composition of the flour samples were analysed by using standard methods.

There were significant differences in moisture content (p = 0.012), crude fat (p = 0.001), crude fibre (p = 0.002), carbohydrate (p = 0.002), sodium (p < 0.001), magnesium (p < 0.001), iron (p < 0.001), zinc (p = 0.006), vitamin A (p < 0.001) and vitamin C (p = 0.001) contents of okra calyx flour. The values of proximate composition ranged 8.1-8.9%, 8.4-9.0%, 14.3-15.3%, 1.4-2.1%, 16.9-18.2% and 47.1-49.4% for moisture content, ash, crude protein, crude fat, crude fibre and carbohydrate, respectively, whereas the values of mineral contents ranged 7.6-8.7 mg/100g, 35.7-41.2 mg/100g, 26.5-28.1 mg/100g, 93.2-95.8 mg/100g, 1.6-1.8 mg/100g and 5.2-5.7 mg/100g for sodium, magnesium, potassium, calcium, iron and zinc, respectively. The values of vitamin contents of okra calyx flour ranged 0.2-0.3 µg/100g, 7.1-8.9 mg/100g and 0.1-0.2 mg/100g for vitamin A, vitamin C and thiamine contents respectively. Also, there were significant differences in the values of phytate (p = 0.023), oxalate (p = 0.011) and saponin (p < 0.001) contents with the values of anti-nutritional properties ranging 1.3-1.5 mg/100g, 2.5-3.3 mg/100g, 7.4-9.7 mg/100g and 2.3-3.6 mg/100g for tannin, phytate, oxalate and saponin contents, respectively.

There are scanty published works/information on proximate composition, mineral content, vitamin content and anti-nutritional composition of okra calyx flour.

The study showed that okra calyx flour could be useful in fortification/supplement of carbohydrate-based foods in food system.

Okra calyx flour comprises high crude fibre, crude protein, ash and vitamin C contents. Also, calcium is the major mineral content of okra calyx flour followed by magnesium and potassium. However, the tannin content reported higher in okra leaf flour, and okra flour is low in okra calyx flour.

Since December 2019, global attention has been drawn to the rapid spread of COVID-19. Corona was discovered in India on 30 January 2020. To date, in India, 178,014 disease cases were reported with 14,011 deaths by the Indian Government. In the meantime, with an increasing spread speed, the COVID-19 epidemic occurred in other countries. The survival rate for COVID-19 patients who suffer from a critical illness is efficiently and precisely predicted as more fatal cases can be affected in advanced cases. However, over 400 laboratories and clinically relevant survival rates of all present critically ill COVID-19 patients are estimated manually. The manual diagnosis inevitably results in high misdiagnosis and missed diagnosis owing to a lack of experience and prior knowledge. The chapter presents an option for developing a machine-based prognostic model that exactly predicts the survival of individual severe patients with clinical data from different sources such as Kaggle data.gov and World Health Organization with greater than 95% accuracy. The data set and attributes are shown in detail. The reasonableness of such a mere three elements may depend, respectively, on their representativeness in the indices of tissue injury, immunity and inflammation. The purpose of this paper is to provide detailed study from the diagnostic aspect of COVID-19, the work updates the cost-effective and prompt criticality classification and prediction of survival before the targeted intervention and diagnosis, in particular the triage of the vast COVID-19 explosive epidemic.

Automated machine learning (ML) provides resources and platforms to render ML available to non-ML experts, to boost efficiency in ML and to accelerate research in machine learning. H2O AutoML is used to generate the results (Dulhare et al., 2020). ML has achieved major milestones in recent years, and it is on which an increasing range of disciplines depend. But this performance is crucially dependent on specialists in human ML to perform the following tasks: preprocess the info and clean it; choose and create the appropriate apps; choose a family that fits the pattern; optimize hyperparameters for layout; and models of computer learning post processes. Review of the findings collected is important.

These days, the concept of automated ML techniques is being used in every field and domain, for example, in the stock market, education institutions, medical field, etc. ML tools play an important role in harnessing the massive amount of data. In this paper, the data set relatively holds a huge amount of data, and appropriate analysis and prediction are necessary to track as the numbers of COVID cases are increasing day by day. This prediction of COVID-19 will be able to track the cases particularly in India and might help researchers in the future to develop vaccines. Researchers across the world are testing different medications to cure COVID; however, it is still being tested in various labs. This paper highlights and deploys the concept of AutoML to analyze the data and to find the best algorithm to predict the disease. Appropriate tables, figures and explanations are provided.

As the difficulty of such activities frequently goes beyond non-ML-experts, the exponential growth of ML implementations has generated a market for off-the-shelf ML solutions that can be used quickly and without experience. We name the resulting work field which is oriented toward the radical automation of AutoML machine learning. The third class is that of the individuals who have illnesses such as diabetes, high BP, asthma, malignant growth, cardiovascular sickness and so forth. As their safe frameworks have been undermined effectively because of a common ailment, these individuals become obvious objectives. Diseases experienced by the third classification of individuals can be lethal (Shinde et al., 2020). Examining information is fundamental in having the option to comprehend the spread and treatment adequacy. The world needs a lot more individuals investigating the information. The understanding from worldwide data on the spread of the infection and its conduct will be key in limiting the harm. The main contributions of this study are as follows: predicting COVID-19 pandemic in India using AutoML; analyzing the data set predicting the patterns of the virus; and comparative analysis of predictive algorithms. The organization of the paper is as follows, Sections I and II describe the introduction and the related work in the field of analyzing the COVID pandemic. Section III describes the workflow/framework for AutoML using the components with respect to the data set used to analyze the patterns of COVID-19 patients.

The research paper examines the impact of perceived social media marketing activities (SMMAs) (interaction, entertainment, customization, trendiness and word of mouth (WOM)) on customer loyalty (CL) toward e-commerce providers. The study also explores the mediating role of customer relationship quality (CRQ) (commitment, trust and satisfaction) on the relationship between perceived SMMAs and CL.

The study is based on the S-O-R model, which states that characteristics of the environment (stimulus) arouse a cognitive state (organism) that results in positive or negative behavior (response). The present study proposes the characteristics of the e-commerce environment as stimuli (S), the inner state of customers as an organism (O) and consumer behavior as the response (R). This study investigated the responses of 487 social media users through structural equation modeling (SEM).

The results offer three crucial findings. First, the study validated that perceived SMMA comprises five dimensions (interaction, entertainment, customization, trendiness and WOM) in the Indian e-commerce context. Second, perceived SMMA significantly influences CRQ (commitment, trust and satisfaction). Third, CRQ significantly mediates the relationship between perceived SMMA and CL.

The study attempts to understand the effect of perceived SMMA on CL via CRQ in an e-commerce context, especially in an emerging economy like India. The present study argues that the SMMA of e-commerce is likely to be reflected in CL when the consumers experience CRQ through commitment, trust and satisfaction. Thus exploring the mediating role of CRQ is the authors' contribution.

The Internet has existed in India for about 18 months. An attempt has been made here to give information about India's Internet service providers and information infrastructure, and to group the Internet information sources originating from India into various categories: viz. art, business, campus wide information systems, companies and organisations, data and software, directories, discussion lists/forums, electronic journals, e‐mail based infoservers, entertainment, investment, medical, multimedia, multipurpose, online information, religion and tourism. The paper also discusses the Internet in the social and commercial context of India and concludes with India's rapid response in providing its resources over the Net to establish its presence, the growth of Web sites, privatisation of access, and PC penetration in the SOHO and home segment.