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Long-term care (LTC) homes are highly regulated settings that provide care to people living with complex health conditions who are often at the end of their lives. Mental health and quality of life are important concepts in LTC given the inherent poor health and diminished autonomy of residents living in this setting. The COVID-19 pandemic had the potential to further compound these issues through lockdowns limiting movement within and outside of LTC homes, increased fear of severe COVID-19 infections, staff shortages, and impaired communication through personal protective equipment. However, the evidence describing the effect of the pandemic on mental health and quality of life is mixed, with some studies describing increased rates of mental health concerns and others presenting modest increases or decreases. Creative strategies to mitigate negative mental health consequences of lockdown included technology supported and window or outdoor visits, increased access to volunteers, and supports for families. However, the evidence in this area continues to evolve as subsequent waves of the pandemic progress. Future research may present new evidence about other strategies that became important in different stages of the pandemic.

Unmanned aerial vehicles (UAVs) have wide applications in surveillance and reconnaissance without risking human life. Due to unbalanced payload distribution or in-flight deployment, UAVs may undergo lateral center of gravity (c.g.) variations resulting in an asymmetric dynamic having significant longitudinal and lateral/directional coupling and hence more pronounced nonlinearity. Therefore, automatic control of UAVs becomes extremely difficult when it is forced to perform maneuvers under such imbalance in lateral mass distribution. The purpose of this paper is to design adaptive nonlinear control so that the UAV can perform some useful lateral/directional maneuver under lateral c.g. uncertainty.

First the nominal lateral/directional dynamics of a fixed-wing UAV is framed into strict feedback form and then the block backstepping approach is used to design the controller to execute horizontal turn and aileron roll maneuvers under no lateral c.g. variation. Thereafter, an adaptive block backstepping controller is designed to adapt to uncertainty in lateral c.g. position considering an approximate model of the asymmetric dynamics. The proposed adaptive scheme is validated against the same two maneuvers as considered for the nominal case.

First it is shown that the lateral/directional dynamics of a UAV can be converted to a block strict feedback form for executing some lateral/directional maneuvers. However, it was observed that the maneuver performance suffers significant performance degradation under lateral c.g. variations. To mitigate this issue, a simple and computationally inexpensive adaptive block backstepping scheme is proposed and validated. The adaptation law is further proved to be able to asymptotically estimate the actual c.g. location of the UAV.

The proposed control scheme allows the UAV to automatically adapt to lateral c.g. variations so that the intended maneuvers are performed without any noticeable loss in maneuver performance.

There are very few works available in the literature that address nonlinear control designs for executing specific lateral/directional maneuvers and, moreover, they consider symmetric UAVs or aircraft only. This paper addresses the practical problem of autonomous maneuvering for UAVs with unbalanced lateral mass distribution leading to shift of c.g. out of its plane of symmetry.

Using bibliometric techniques, the author analyzes a dataset of 276 articles on cross-border mergers and acquisitions (CBMAs) published in 13 management and international business journals. The author assesses the scientific impact and visualizes the intellectual landscape of research on CBMAs by analyzing publication and citation data and interconnections between publications. First, the author assesses annual publication trends and identifies highly cited articles and productive journals in the dataset that have significantly contributed to our understanding of CBMAs. Second, the author identifies main themes in recent research on CBMAs by focusing on frequently used keywords in publications. Third, the author identifies clusters of related research and explores their interrelationships to outline emerging trends, new perspectives, and directions for future research on CBMAs. Overall, this chapter contributes to the understanding of CBMAs by documenting the progress made to date and providing important insights for future research.

Finding the optimal solution to address problems in sewer management systems has always challenged asset managers. An understanding of deterioration mechanisms in sewers can help asset managers in developing prediction models for estimating whether or not sewer collapse is likely. The effective use of deterioration prediction models along with the development and use of life cycle cost analysis (LCCA) can contribute to the goals of reducing construction, operation and maintenance costs in sewer systems. When sewer system maintenance/rehabilitation options are viewed as investment alternatives, it is important, and in some cases, imperative, to make decisions based on life cycle costs instead of relying totally on initial construction costs. The objective of this paper is to discuss the application of deterioration modelling and life cycle cost principles in sewer system management, and to explore the role of the Markov chain model in decision making regarding sewer rehabilitation. A test case is used to demonstrate the application of the Markov chain decision model for sewer system management. The analysis includes evaluation of this concept using dynamic programming and the policy improvement algorithm.

Given the prevalence of protecting geoheritage tourism sites, Ladakh has enormous potential. However, Ladakh’s potential and developments in its growth as a geotourism destination have received scant consideration. As such, this paper aims to explore Ladakh’s key drivers as a potential geotourism destination through cognitive dissonance and protection motivation theories.

This paper conducted in-depth interviews with 86 geoscientists and tourism professionals to assess Ladakh’s potential as a geotourism destination. This paper used a qualitative approach to congregate four constructs based on the image difference of the consensus map.

Because of the interviewees’ heterogeneity and uniqueness, meaningful constructs in the consensus were included for each figure and cloud words. This paper concluded that four drivers are the main forces behind geotourism development.

This paper explores the drivers – geotourism services, legislative requirements, experiential geotourism and SPARC (scientific, preservation, aesthetic, recreational, cultural) values – affecting geotourism in Ladakh. It is feasible to lessen the negative effects of overtourism and make sure that Ladakh’s distinctive nature is preserved for future generations by implementing sustainable tourism practices.

The structural acoustic problem, wherein an acoustic domain is confined within a partly flexible laminated composite enclosure is presented. From the finite element free vibration analysis of the laminated folded plate structure a mobility relation is derived between the normal velocity of the structure and normal pressure on the structure. A boundary element solver for the Helmholtz equation with quadratic isoparametric elements is developed using pressure‐velocity formulation. Velocity is known over certain parts of the boundary, the rest being the interactive boundary, where the mobility relation correlates nodal pressures and velocities, neither explicitly known. The pressure boundary values are solved from the boundary element and the mobility relations, while the nodal particle velocities and domain pressures are computed at desired points thereafter. New results presented here reveal the effects of the variation in magnitude of structural damping, fiber angles and the thickness of walls.

Ports are a significant link in a global supply chain and an economic entity that contributes to the country's economy. India has around 200 ports along its coastline of about 8,000 Km, yet none of them perform at par with many Asian ports. In the Indian port system, cargo throughput and the turnaround time (TAT) of ships calling at ports constitute the most significant performance measures. These performance metrics do not integrate sustainability measures such as emission levels and energy consumed. The draft is a constraint in many ports and ships visit with less than full shipload cargo. The TAT for such vessels may be lower, but the emission per ton of cargo carried is higher compared to a ship with full shipload cargo. Many ports have old or poorly maintained equipment. This state of equipment increases pollution and consumption of energy. In this paper, an attempt has been made to address the issue of undesirable and right outputs simultaneously in an Indian port system. This paper proposes a framework to ensure zero defects in Indian port operations and a port-sustainability-index to measure sustainable services in Indian ports.

The authors used data envelopment analysis (DEA) to show that all private terminals did not perform efficiently and contradicted the notion of Indian policymakers that privatization will lead to an increase in performance levels. A literature review was carried out to identify the dimensions and factors that affect ports' performance. A case study of a major port in India and expert group discussion was done to ascertain the views of stakeholders on deficiencies in the system. The authors complemented this approach with sentiment analysis of opinions expressed by stakeholders over a while, using SentiStrength analysis software (Thelwell, 2010, 2012). The authors used the combined findings to develop the port-sustainability-index (PSI), identify the research question, and develop an ontology of the port system. The authors use the concepts of ontology-design-pattern (ODP) and logistics-service-map (Glöckner et al., 2014; Glöckner and Ludwig, 2016, 2017), opinion mining (Pang and Lee, 2008) and competency questions (Glöckner and Ludwig, 2017) to develop a port system map followed by the identification of critical elements; and the flows (physical and information flow) that gets disrupted due to defects in the system. The ontology led to the identification of competencies and capabilities a port needs to possess. Based on these identification process competency questions were drawn, and the authors identified the plausible defects that port may encounter. The authors suggested the sustainability metrics for monitoring port performance and policy changes based on the competency questions, defects, and mitigation plans.

The authors introduced four KPIs, namely, port-sustainability-index (PSI), load factor (l_x and l_y), draft ratio (d_r), and turnaround-time ratio (TATR). The authors suggested significant policy changes for Indian ports. These included –(1) Introduction of virtual arrival (VA) policy, reducing randomness in the system by pre-scheduling arrivals and activities. (2) Redefining economic life of equipment and machinery in terms of expenditure, income and desired levels of output. (3) Pricing port charges based on stakeholders’ ability and willingness to pay. The port needs to declare its productivity levels and frame their charges accordingly. (4) The ports need to frame an output-oriented privatization policy where it specifies the growth of the port. (5) Framing vessel pricing policy where a vessel may pay tax for the use of non-clean fuel or a get discount for bringing higher parcel load. (6) Levy lower port charges for the shipper for transporting cargo by rail and barges. (7) Introduce a differential pricing system where port levies lower charges for export cargo compared to import load.

The research work can be extended to develop a simulation model to carry out policy experimentations concerning the improvement of performance and carry out sustainable operations. Alternatively, researchers may develop a multi-criteria optimization model to determine the best course of action, keeping the objective function as minimization of PSI value.

This paper provides the means to the Indian ports to remain competitive, lower emission levels and energy consumption, and optimize emission per ton of cargo handled in the port.

Society significantly benefits from this study as it recommends ways to minimize pollution that has a significant impact on human lives. Besides, the measures suggested in the paper will lower the cost of exports and imports, enhancing the real income of consumers.

The area of sustainable port operations has previously been under-researched in the Indian context. Authors contribute to the sustainable port operation literature by suggesting a port-sustainability-index, a framework to assess the defects in port operation and development of a port-ontology for further research in the area of a port system.

The purpose of this paper is to develop a model for the production planning decision of a dairy plant in a multi-product setting under supply disruption risk and demand uncertainty while determining the optimal product-mix and material planning requirement.

A mixed-integer nonlinear programming model is proposed to determine the optimal product-mix that maximizes the expected profit of a dairy. The data are collected through visits to the dairy site, conducting brainstorming sessions with the plant manager and marketing head at the corporate office. Disruption data are collected from the India Meteorological Department, Odisha.

From the analysis, it is recommended that the dairy should not produce curd during the planning period. Moreover, turnover from toned, double toned and baby food is maximum than that of the curd and these products are produced in the planning period. The expected profit increases from its present value when an optimal product-mix is followed. Sensitivity analysis is performed to analyze the effect of demand uncertainty, supply disruption and production quota. The expected profit decreases as the supply failure probability increases.

The model is implemented in a dairy plant under Orissa State Cooperative Milk Producers Federation, Odisha, India. The proposed methodology has not been validated, theoretically. The concerned dairy is based on the Indian context, but the authors believe that the study is highly relevant to other dairies as well.

This study provides a methodology for dairy plant managers to plan production effectively under supply disruption risk with demand uncertainty. It also suggests material requirement planning at different factories of the dairy plant.

This paper develops a mathematical model for the production planning decision of a dairy plant that determines the optimal product-mix, which maximizes the expected profit of a dairy under disruption risk and demand uncertainty (in the Indian context).

The purpose of the chapter is to integrate the understanding of diversity from different perspectives in Indian context and see how the holistic view emerges.

The methodology used is primarily the literature review of the concepts and their evolution in Indian context and the use of secondary sources to extract praxis information.

It emerged from the exploration on diversity practices at the societal as well as organizational level in India that the country demonstrates intent to mainstream the people from different wakes, but with the changing context the format of the practices has changed.

The basic premise of the chapter needs to be explored further through primary data from practice.

This chapter is novel in a way that it integrates the diversity scholarship of four different streams viz. caste, gender, disability, and generation. Most of the existing research focuses only on a thin slice/one key dimension of diversity.