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This paper aims to gain insight on the perception and role of the local government officials on climate change and resilience in Uttarakhand, India. Uttarakhand, being a sensitive mountainous region in India, faces the brunt of frequent climate-related disasters and their severe impacts. Therefore, it is crucial to understand how authorities perceive the issue of climate-related disasters and their level of commitment toward mitigation and adaptation programs.

The literature review method was used for a holistic understanding of the impact of climate change and consequential disasters. A questionnaire survey method, comprising open- and closed-ended questions, was also used on officials of different departments.

Among the noteworthy findings of the study include the understanding of the perceptions of authorities and their role in decision-making on mitigating impacts of climate change-related disasters, their support or lack of it, for measures toward capacity building and spreading awareness of the intervention programs by the government. The study analyzes the perception of decision-making officials at state and district levels and infers that the variation on opinions may be attributable to multiple factors, including their past experiences of dealing with disasters.

This study offers insights into the role of perception of local government officials concerning climate change-related disasters and alleviation of their consequences through related programs. The findings have the unique potential to serve as a guide for the government at state and district levels to assess various aspects of different disaster mitigation measures based on sectors and departments.

The purpose of this study is to empirically investigate the variables having an impact on profitability of public private partnerships (PPPs) in India using a balanced panel data of 171 unlisted PPPs from different infrastructure sectors such as road, power generation, real estate and ports.

Estimations were done using Arellano–Bond dynamic panel data estimation and seemingly unrelated regression models on a balanced panel data of 855 firm-years for 171 unlisted PPPs in India. To further test the estimation robustness, panel-corrected standard errors model was used.

The study findings indicate that in firm-specific factors, leverage, size, non-debt tax shield, growth and risk have significant positive impact on PPPs’ profitability, whereas in macroeconomic factors, only inflation has significant positive relationship. Although the relationship of all determinants is in sync with various theories and approaches, but these are not significant. Using the robustness test, the results are found to be robust and consistent with resource-based view and strategy-structure-performance approaches.

As PPPs are gaining prominence in the development of infrastructural resources, their profitability is of significant importance to drive private investments in infrastructure development, the identification of factors which determine profitability is critical for researchers, practitioners, policymakers and fund providers such as equity investors and debt providers.

The empirical literature on profitability determinants is focused on various sectors including small and mid-size enterprises (SMEs) and micro firms, but to the best of the authors’ knowledge, this is the first study, in both developed and developing economies, to empirically investigate the determinants of profitability for PPPs.

The purpose of this paper is to design a cascaded Multilevel inverter with reduce number of switches for high power applications. This paper came up with an innovative three-phase multilevel inverter (MLI) topology, which is a cascaded structure based on classical three-legged voltage source inverter (VSI) bridges as an individual module. The prominent advantage of this topology is that it requires only one direct current (DC) link system. The main characteristic of it is that a higher number of voltage levels can be achieved with considerably a smaller number of semiconductor switches, which improves the reliability, power quality, cost and size of the system significantly.

The individual modules are cascaded through three-phase transformers to provide higher voltage at the output with the higher number of voltage levels. In this work, the phase-shifted pulse width modulation technique is implemented to verify the result.

The proposed topology is compared with three-phase cascaded H-bridge MLI (CHB-MLI) and a modified CHB-MLI topology and found better in many aspects. The proposed MLI can produce a higher number of voltage levels with fewer semiconductor switches and associated triggering circuitry. As the device count in the proposed MLI is less compared to other MLI discussed, it tends to have less switching and conduction loss which increases the efficiency and reliability. As the number of level increases, the voltage profile and the total harmonic distortion of the proposed MLI improves.

This is a transformer-based modular cascaded MLI, which is based on classical VSI bridges. Here in this topology, a single module provides all three phases. So, a single string of cascaded modules is enough for three-phase multilevel voltage generation.

Condition monitoring of squirrel cage induction motors (SCIMs) is indispensible for achieving fault-free working environment. As broken rotor bars (BRBs) are one of the more frequent faults in a SCIM especially where direct-on-line starting is indispensible, as in underground mines, a priori knowledge of fault severity in terms of the number of BRBs assists in effective fault monitoring. In this regard, this paper aims to propose a unique empirical relation to facilitate the determination of number of BRB.

Fast Fourier transform is used to obtain fault sideband amplitudes under varying number of BRBs and load torque for 5.5 kW, 7.5 kW, 10 kW, three-phase, 415 V, 50 Hz SCIMs in MATLAB/Simulink. The nature of variation is decided by an appropriate curve fitting technique for comprehending a unique empirical relation. The proposed empirical relation is validated by bootstrapping and z-test. Furthermore, hardware validation is done using 1 kW laboratory prototype with Labview interface.

The analytical study reveals the dependence of lower and upper sideband amplitudes on the number of BRBs, load torque and machine rating. Therefore, fault severity in terms of number of BRBs is accurately calculated using the proposed empirical relation if load torque, machine rating and amplitudes of lower and upper sidebands are known.

The unique empirical relation proposed in the present work provides accurate knowledge of fault severity in terms of the number of BRBs. This facilitates maintenance scheduling which shall reduce effective downtime and improve production.

This paper aims to create a better understanding of the challenges posed by work from home (WFH) during the ongoing COVID-19 pandemic, to investigate the public sentiment toward this transition, and to develop a conceptual model incorporating the relationships among the factors that influence the effectiveness of WFH.

This paper uses netnography method to collect data from the Twitter platform and uses Python programming language, Natural Language Processing techniques and IBM SPSS 26 to conduct sentiment analysis and directed content analysis on the data. The findings are combined with an extensive review of the remote work literature to develop a conceptual model.

Results show the majority of tweets about WFH during the pandemic are positive and objective with technology and cyber security as the most repeated topics in the tweets. New challenges to WFH during pandemic include future uncertainty, health concerns, home workspaces, self-isolation, lack of recreational activities and support mechanisms. In addition, exhaustion and technostress mediate the relationship between the antecedents and outcomes of WFH during the ongoing COVID-19 pandemic. Finally, the fear of pandemic and coping strategies moderates these relationships.

This paper is one of the first efforts to comprehensively investigate the challenges of WFH during a crisis and to extend the remote work literature by developing a conceptual model incorporating the moderating effects of fear of pandemic and coping strategies. Moreover, it is the first paper to investigate the tweeting behavior of different user types on Twitter who shared posts about WFH during the ongoing pandemic.

The study uses the multivariate GARCH-BEKK model (which was first proposed by Baba et al. (1990) and then further developed by Engle and Kroner (1995)) to examine the return and volatility spillover between India and four leading Asian (namely, China, Japan, Singapore and Hong Kong) and two global (namely, the United Kingdom and the United States) equity markets.

The study employs a multivariate GARCH-BEKK model to quantify return correlation and volatility transmission across the pre- and post-2008 global financial crisis periods (apart from other conventional time series modelling like cointegration, Granger causality using vector error correction model (VECM)).

The results show a tendency of the Indian stock market index to move along with the US and Hong Kong market indices. The decrease in the value of the co-integration coefficient during the recession was explained by reduced investor confidence in developing countries. The result further shows a clear distinction in terms of volatility spillover between the Asian market vis-a-vis US and UK markets. Volatility transmission from India to Asian markets was found to be significantly higher as compared to the US and UK. So also, the study’s results show a puzzling result giving us comparable co-integration ranks for phase 2 (expansion) and phase 3 (slow-down) of the business cycle in most cases.

In Granger causality testing, the results were unable to ascertain the difference between phase 2 (expansion) and phase 3 (slowdown). However, the multivariate GARCH (MGARCH)-BEKK model showed a clear reduction in volatility transmission to NIFTY50 (is the flagship index on the National Stock Exchange of India Ltd. (NSE)) as India entered slow-down. This shows that the Indian economy does go through different business cycles, and the changes in parameters hence prove hypothesis 3 to be true with respect to volatility transmission to India from International markets.

The results show that for all countries, the volatility transmitted to India increases significantly going from phase 1 (recession) to phase 2 (expansion) and reduces again once the countries enter slow-down in phase 3 (slowdown). This shows that during expansion shocks and impulses in international markets affect the Indian markets significantly, supporting the increase in co-integration in phase 2 (expansion). During expansion, developing markets like India become profitable for investors, due to the high growth rate when compared to developed countries. This implies that a significant amount of capital enters Indian markets, which is susceptible to the volatility of international markets. The volatility transmission from India to the US and UK was insignificant in phase 1 (recession and recovery) and phase 3 (slow-down) showing a weak linkage between the markets during volatile time periods.

Economies and societies are not digitally isolated. Digital technologies are widely recognised as key drivers of information dissemination, knowledge sharing, income and employment. Digital technologies also influence the interlinkages of digitalisation, gender and labour market outcomes. Digital technologies impact every sphere of day-to-day life. It impacts ways of communication, trade and business; influences networking abilities; shapes societal norms, attitudes and behaviours. It is hence argued that digital technologies may have crucial implications for women's participation in the workforce.

Gender equality and increasing women's workforce participation is an important goal under the United Nations Sustainable Development Goals (SDGs). Research indicates that women are mainly involved in agricultural work, blue-collar formal work, while collar formal work, and entrepreneurship. Digital technologies significantly impact the ways of working in all these sectors. Consequently, it is argued that digital technologies influence women's participation across all such types of work.

This chapter aims at unravelling the linkages between digital technologies and women's workforce participation. To this end, the influences of digital technologies on women's participation in agricultural work, blue-collar formal work, white-collar formal work and entrepreneurship are discussed. The implications and impacts of the use of broadband, internet and mobile technologies are also discussed. This chapter also includes important theories of women's workforce participation and discusses them in light of digitalisation.

This research lies in the domain of Vedic mathematics, and it explores the application of the related Vedic sutras in different branches of mathematics, science, education, and engineering across Asia and Europe.

The study embraced a qualitative research design followed by a systematic literature review (SLR) approach which describes the significance of Vedic mathematics. The study made use of purposive sampling through which the data were collected from 102 articles by using inclusion and exclusion criteria. It includes publication years, the types of research methods, and uses of Vedic mathematics sutras in different branches of knowledge stated by the researchers. Its goal is to offer a more thorough explanation and an evaluation of how the inquiry affected the conclusions. The articles examined in this review included all the journal articles and doctoral theses from the databases of Google Scholar, Science Direct, Scopus, and Sodhganga which were published during the period 2010–2022.

The research found that the application of the sutras of Vedic mathematics has been increasing immensely in India. The researchers in this area are fond of qualitative research methods. This research has shown that sutras of Vedic mathematics especially “Urdhvatiryakbhyam” and “Nikhilam Navatascaramana Dasastah” have been frequently used in mathematics and engineering in technical higher education. The impact of other sutras has been quite useful, which augments that in many disciplines where the applications of Vedic mathematics are prevalent, it can be functional. The study concludes by reprising the result, its limitations, and the use of Vedic mathematics as a sustainable source of knowledge.

Vedic mathematics is an area where a lot of potential applications are created in science, mathematics, engineering, and education. Even with the latest technological advancements like learning analytics, artificial intelligence has its connection with this branch of learning, which is the greatest treasure of the Indian knowledge system. The research in this area is not reported in any databases or any standard format so researchers find it difficult to locate and study this broad conceptual domain.

It will help the reader and other academic stakeholders to widen their view on the new and innovative techniques of Vedic mathematics. It is advised that additional studies would look at and evaluate papers published after this time so that readers may get a wider view of the concept of Vedic mathematics.

It will help society to know the essence of Vedic mathematics that how useful it is. Vedic mathematics helps learners to learn in a very factual and accurate manner especially while dealing with mathematical calculations. It will enhance the problem-solving skills among learners. It will be beneficial for all types of learners which will help them to become better individuals for a nation.

The paper enriches understanding of the potential applications of different sutras from Vedic literature in different fields of knowledge. The outcome of the research encourages educationists and policymakers to include Vedic mathematics in the curriculum to foster quantitative reasoning and problem-solving at varied levels of learning.