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Resilience in the crucible: Compassion fatigue among Indian clinical psychologists and the need for mental health policy reform
Objectives: Compassion fatigue (CF) significantly affects mental health professionals, especially in high-stress, resource-limited contexts. Despite its impact on therapeutic outcomes, little is known about how Indian clinical psychologists experience and manage CF. This study explored the lived experiences of CF among RCI-licensed Indian clinical psychologists, focusing on protective and risk factors in the post-pandemic context. Methods: A qualitative phenomenological design using Interpretative Phenomenological Analysis (IPA) was employed. Ten clinical psychologists from urban and semi-urban India were purposively sampled. Semi-structured interviews explored experiences of CF, resilience, and self-efficacy. Thematic analysis was informed by Figley's Compassion Fatigue Model and the Conservation of Resources Theory. Results: Four major themes emerged: (1) Professional Competence and Growth; (2) Therapeutic Relationship; (3) Professional Challenges, including vicarious trauma and boundary-setting; and (4) Self-Care and Support. Participants frequently reported emotional exhaustion and vicarious trauma, but also described post-traumatic growth and reflective practice as buffers. Conclusions: The findings underscore the need for policy-level interventions to address CF among Indian clinical psychologists. Enhancing clinical supervision, integrating trauma-informed curricula, and strengthening institutional support systems are critical for sustaining practitioner resilience and ethical therapeutic care in India's mental health landscape. Key practitioner message: Addressing compassion fatigue through supervision, policy reform, and resilience-building is vital for therapist well-being and service sustainability. 2026 Elsevier Inc. -
Resilience Strategies and Sustainability in Business
Businesses must develop robust resilience strategies to guarantee durable sustainability in a volatile global environment marked by rapid technological advancements, climate change, and socio-economic uncertainties. This chapter explores the intersection of resilience and sustainability in business, focusing on how companies can adapt to disruptions while fostering sustainable practices that contribute to their longevity and success. Resilience strategies involve the capacity of a business to anticipate, prepare for, and respond to disruptions, whether they stem from economic downturns, natural disasters, or shifts in consumer behavior. These strategies encompass risk management, adaptive leadership, and the integration of flexible operational models. By building resilient infrastructures and cultivating a culture of innovation, businesses can navigate challenges more effectively, maintaining continuity and minimizing losses during crises. Sustainability refers to adopting practices that meet current needs without conceding the strength of future generations to meet theirs. Sustainable business practices include reducing environmental impact, supporting social equity, and guaranteeing economic viability. Incorporating sustainability into core business strategies addresses global challenges like climate change and enhances brand reputation, customer loyalty, and long-term profitability. The synergy between resilience and sustainability is essential for modern businesses. By embedding sustainability into resilience strategies, companies can create value beyond financial performance, contributing to environmental stewardship and social well-being. This holistic approach positions businesses to thrive in an uncertain future, balancing immediate resilience with sustainable growth. As businesses increasingly recognize the significance of these strategies, they are better prepared to withstand disruptions and achieve long-term success in a rapidly evolving world. 2026 Godwin Ayodeji Nwogu -
Resilience-oriented optimal integration of photovoltaic, fast-charging stations, and energy storage systems in radial distribution systems
This study proposes a bilevel, resilience-oriented optimization framework for the coordinated allocation of photovoltaic (PV) and fast-charging stations (FCS) and battery energy storage with DSTATCOM (BESDSTATCOM) in radial distribution networks. Unlike existing approaches, the proposed method captures both the grid-connected performance and islanding resilience within a unified framework. The problem is formulated as a single-objective optimization to minimize the real power loss, while the voltage profile and greenhouse gas (GHG) emissions are evaluated as performance indices. The complexity of the single-objective, multi-constraint, and multivariable optimization problem was solved using the Crayfish Optimization Algorithm (COA), which was selected for its balanced explorationexploitation capability and fast convergence characteristics compared with conventional algorithms. The results on the IEEE 33-bus radial distribution network reveal that the uncoordinated integration of FCSs significantly deteriorates the system performance, increasing the real power losses by 48, 163, and 183% and GHG emissions by 28, 53, and 67% for one, two, and three FCSs, respectively. However, coordinated PV integration effectively mitigates these impacts, achieving up to ?93% loss reduction, improving the minimum voltage from 0.913 p.u. to 0.992 p.u., and reducing GHG emissions by up to ?88%. Furthermore, optimal PV penetration levels (up to 86.6%) are critical for emission reduction. Under islanding conditions, the BESDSTATCOM ensures energy balance and can effectively neutralize grid-based emissions. Comparative analysis confirmed that COA provided robust and consistent convergence compared to HPO and AOA. Overall, the study contributes to the achievement of United Nations goals, particularly Sustainable Development Goal 7 (Affordable and Clean Energy), Sustainable Development Goal 11 (Sustainable Cities and Communities), and Sustainable Development Goal 13 (Climate Action), by promoting sustainable energy integration, cleaner transportation, and reduced environmental emissions within modern power distribution systems. 2026 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/ -
Resilience: Future Trends and Challenges in Small and Medium Enterprises
Small- and medium-sized enterprises (SMEs) are essential drivers of innovation, employment, and economic growth in the global economy. However, the rapid technological advancements associated with Industry 5.0 introduce unprecedented challenges and vulnerabilities for these businesses. This chapter delves into the resilience of SMEs, with a focus on the future trends and challenges that will shape their survival and growth in this ever-evolving environment. By leveraging secondary data from reputable databases such as Scopus and Web of Science, this study synthesizes the available literature to deliver a thorough analysis of SME resilience. In addition to digital transformation, this chapter discusses the growing importance of sustainability in building resilience. It advocates for the adoption of sustainable practices that mitigate environmental risks while aligning with the increasing demand for corporate social responsibility. This chapter also underscores the necessity of fostering a resilient organizational culture capable of withstanding economic and political uncertainties. By leveraging data from previous studies, this chapter offers practical recommendations for enhancing SME resilience. It can be a critical resource for policymakers, business leaders, and researchers seeking to understand and address the factors that will determine the future success and sustainability of SMEs in the age of Industry 5.0. 2026 Mohit Sharma, Rishi Chaudhry, Raj Kumar, Nitika Malik and Kuldeep Chaudhary -
Resilient strategies for sustainable tourism development: a land use analysis of the Kannur-Iritty corridor in Kerala, India
The study explores the resilience of the KannurIritty corridor in northern Kerala, where rapid infrastructural growth following the opening of Kannur International Airport in 2018 has reshaped mobility, land use, and tourism potential. The primary objective is to identify specific areas where challenges exist and provide policy recommendations to promote resilient and sustainable tourism development along the corridor. Integrating spatial, environmental, and perceptual data, the analysis develops a composite framework to assess environmental, infrastructural, socio-economic, and governance resilience. Results reveal strong infrastructural connectivity but moderate ecological and community adaptability. Water quality deterioration and unplanned land conversion reduce ecological resilience, while limited local awareness constrains adaptive tourism diversification. Conversely, peri-urban zones with mixed land use demonstrate higher potential for low-impact tourism such as farm and eco-tourism. Strengthening corridor governance through integrated land-use control, water-quality restoration, and community participation is essential to sustain tourism resilience. The study recommends targeted policy interventions, prioritizing sustainable infrastructure, decentralized waste management, and participatory tourism planning, to align regional development with Keralas responsible tourism agenda and provide a replicable model for other emerging tourism corridors in India. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
Resource allocation in cloud auction-based market by hybrid optimization algorithm
Effective resource allocation is essential in the rapidly changing cloud computing landscape to maximize provider revenue and user satisfaction. Through competitive bidding procedures, the auction-based market model has become a potent tool for allocating cloud resources among users. In this paper, a new method for cloud computing environments is presented: Double Auction-based Resource Allocation (DARA). The auction model and optimal resource allocation are the two main parts of the DARA methodology. The Double Auction mechanism is used as the auction model in the suggested DARA framework. In this model, resource prices and allocations are decided through a competitive auction process that involves both buyers and sellers.The highest price that buyers are willing to pay for resources is expressed in bids, and the lowest price that sellers are willing to accept is expressed in asks. There are many intricate tasks involved in this two-way auction process, including matching bids and asks, determining market prices, and handling transactions. Finding the equilibrium price requires the method to solve complex optimization problems in order to balance supply and demand. In order to overcome these obstacles, the study suggests the Hippopotamus Updated Pufferfish Optimization (HUPO) algorithm for the best possible resource distribution. The HUPO algorithm is made to handle limitations like truthfulness, resource density, execution time, and operating expenses. In order to ensure that users pay fair prices and service providers make the most money, it is crucial to implement effective resource allocation strategies that balance the cost of resources with their availability. According to the mean statistical metric, the resource density for the HUPO model is 17.862, which is greater than the values of all other traditional approaches, including BES at 14.960, AOA at 12.546, ACO at 14.274, COA at 13.693, SMO at 13.452, HOA at 13.686, and POA at 13.907. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025. -
Resource Aware Weighted Least Connection Load Balancing Technique in Cloud Computing
Cloud computing became a pivotal for the most of the real time applications. In cloud computing, the customer demands the services with the best performance even when the application is expanding rapidly. Therefore, it is essential to manage the resources effectively because the number of users and services growing proportionately. The main aim of the load balancing technique is to allocate the customers' requests with the large pool of resources efficiently. The problem is how to evenly distribute the load of requests among the compute nodes according to their capacity. Therefore, there is a need for an effective load balancing technique for smooth continuity of operations in a distributed environment with a heterogeneous server configuration. This paper presents a novel load balancing technique, namely, Resource aware weighted least connection load balancing which addresses the above said problem efficiently. The essence of this work is to assign the requests across multiple servers based on the requested resource and the status of the number of connections presently served by each server. This work used standard score technique to enumerate the weight of each node. Experiments were conducted using Cloud Analyst, a famous cloud simulator breed from CloudSim. Appropriate performance parameters were analysed to measure the effectiveness of the proposed technique. Future directions for the extension of the implemented technique also identified. 2023 IEEE. -
Resource Curse - Impact of Renewable Natural Resources on Economic Growth in the U.S. using ARDL Approach
The analyses of the resource paradox in the United States of 29 years are conducted by the econometric model of ARDL. The dataset taken for the study is from the source of World Bank. After testing the stationarity and cointegration of 4 independent variable and one dependent variables of Gross Domestic product, this study will be giving the conclusion of long term and short-term relations of the variables to show the existence of Resource curse in the US within the 29 years of dataset. Causation test shows that there doesn't exist any particular causal relations between the variables and hence there need to be thorough study in this phenomenon. 2024 IEEE. -
Resource Provisioning in Fog Computing - A Survey
The internet world has created an era where any device can interconnect with each other. Gathering intelligence from streaming data is challenging and can create wonders and valuable innovations for humanity. The shortcomings of connectivity due to the remote location of the cloud induce latency and performance issues in real-time. Thus, a traditional cloud may not be suitable for all applications. A secure, low latent bandwidth infrastructure under research led to Fog Computing. The fog nodes have limited resources, and effective utilization can boost the applications performance. Ensuring effective routing of the tasks and load balancing among the nodes is essential and tedious in any network. Resource management becomes challenging due to heterogeneity, dynamic workload, unpredictability of the computing environment, and so on. In such cases, using Artificial Intelligence (AI) can be promising, provided the complexity and the computing are handled. Proactive load handling based on the changes in network traffic has a huge scope for research. This article gives a detailed survey of the various fog network architectures and the intelligent methodologies in resource allocation in a fog network using machine learning algorithms. Furthermore, the article shows the directions of research in intelligent resource allocation and handling. 2025 Copyright held by the owner/author(s) -
Respectful dialogue in classrooms
Teachers must anticipate problems and be prepared to diffuse them quickly, writes John J Kennedy -
Responding to pandemic challenges: leadership lessons from multinational enterprises (MNEs) in India
Purpose: The business sector plays a major role in achieving comprehensive economic development goals in emerging economies. Consequently, the effects of business responses to the COVID-19 pandemic are receiving increasing research attention from an organizational management development perspective. This article aims to examine the role of leadership in charting the course in an extraordinary crisis context. Design/methodology/approach: Using institutional leadership theory, leadership contingency theory and dynamic leadership capability theory, the authors present a research framework that defines macrochallenges and organizational level responses and outcomes. The article adopts a case study approach, which includes the identification of four target companies and conducting in-depth interviews with senior management professionals within those companies at different time periods. Findings: Based on the interviews, the steps that Indian companies adopted to respond to the COVID-19 challenge are identified. Expanding the insight from the case study, the findings suggest that although feeling overwhelmed at first, organizational leaders combine prudent (i.e. timely and speedy actions for survival first) and bold (i.e. future envisioning for expansion and growth) actions enabling these firms to weather two waves of the COVID-19 pandemic in India. Originality/value: These multiple case studies are unique in exploring MNEs from different industries. This study also highlights the dynamic relationships between leadership practices, risk management strategies and performance outcomes based on a sound theoretical model and rigorous study methods. 2022, Emerald Publishing Limited. -
Responding to the pandemic: A case of the indian hotel industry
The chapter presents a case study on how Indian hotel industry was affected by COVID-19. Three hotels-Lemon Tree, Oyo Rooms, and Taj Hotels-were selected to elaborate. The study found that the hotel industry developed various policies to keep running their hotels during the pandemic. Lemon Tree joined various hospitals to provide rooms to COVID patients, provided free food and face masks to individuals. Oyo Rooms gave employee stock ownership plans of Rs 130 crore to its COVID-hit employees. Taj Hotels did not cut down the salaries of their employees and reduced its seating capacity by 50%. The study concluded that as the hospitality sector battled hard to continue during the pandemic, modernization would become an imperative tool in the post-COVID period to beat obstructions and spotlight advancement. So, the companies should minimize fixed costs and maximize variable costs. They should preferably have liquid cash available that could enable them to mitigate the risk. 2022, IGI Global. -
Response of ChatGPT for Humanoid Robots Role in Improving Healthcare and Patient Outcomes
Humanoid robotics is characterized by constant developments, which are supported by several research facilities across the world. Humanoid robots are used in many different industries. In this setting, this letter, written by people, makes use of ChatGPT answers to examine how humanoid robots might be used in the medical industry, particularly in light of the COVID-19 pandemic and in future. Although humanoid robots can help with certain jobs, it is important to recognize the indispensable importance of human healthcare professionals who have knowledge, empathy, and the capacity for critical judgment. Although humanoid robots can complement healthcare initiatives, they shouldnt be viewed as a full-fledged replacement for human care. 2023, The Author(s) under exclusive licence to Biomedical Engineering Society. -
Response Surface Methodology-Optimized FL0.1@ZIF-8 Fluorescent Probe for High-Throughput Capsaicin Analysis in Chili Products
Capsaicinoids are a group of naturally occurring organic compounds responsible for the pungency of chili. This study aimed at exploring a novel approach with multivariate-assisted Response Surface MethodologyBox Behnken Design (RSM-BBD) optimized fluorescent probe (FL0.1@ZIF-8) for the detection of capsaicin. The probe was solvothermally synthesized and characterized using XRD, FTIR, and SEM to confirm the successful incorporation of fluorescein (FL) into ZIF-8. The experimental parameters, including pH, concentration of the probe, and reaction time, were systematically optimized via RSM-BBD to enhance the sensitivity of FL0.1@ZIF-8. The results demonstrated a quenching response of FL0.1@ZIF-8 emission with capsaicin. The limit of detection (LOD) and limit of quantification (LOQ) were calculated and found to be 1.5 ?M and 4.9 ?M, respectively. The outcome of the study identifies efficient electronic factors as major contributors to the development of FL0.1@ZIF-8 with promising possibilities for the detection of chili hotness for food pungency evaluation, quality control, and assurance in the food industry. 2026 American Chemical Society -
Response surface optimization and process design for glycidol synthesis using potassium modified rice husk silica
Glycerol, an inexpensive by-product from biodiesel production can be converted into many useful products notably glycidol, which has a wide range of uses. In this study, glycidol synthesis has been done using a biowaste mediated catalyst in a single step process. Silica and potassium incorporated silica were synthesized from biowaste rice husk. These catalysts were characterized by different spectroscopic techniques. Basic sites in the catalysts were estimated using temperature-programmed desorption study. Four operational parameters were optimized using Box Behnken Design (BBD) of response surface methodology (RSM). Potassium incorporated rice husk was found to be one of the best catalysts for glycidol production with 60.8% glycerol conversion and 62.9% selectivity within one hour of reaction time. 2020 Elsevier Ltd. All rights reserved. -
Response surface optimization of heat transfer rate in Falkner-Skan flow of ZnO ? EG nanoliquid over a moving wedge: Sensitivity analysis
In this work, the optimization of the heat transfer rate in the Falkner-Skan flow of ethylene glycol-based ZnO nanoliquid passing through a moving wedge is performed using the Response Surface Methodology (RSM). The experimentally estimated nanoliquid properties are included in the calculations for realistic modeling. The heat transfer rate is optimized through the use of the numerical experiment based on the face-centered central composite design (CCF). The sensitivity of the heat transfer rate is evaluated using the obtained quadratic model. The impact of the relevant parameters is displayed graphically using the finite difference method-based solution procedure and analyzed in detail. The interactive impacts of the key parameters are also evaluated using three-dimensional surface plots. The maximum sensitivity of the heat transfer rate is towards the moving wedge parameter. The optimized rate of heat transfer occurs at the high levels of the radiation aspect, moving wedge parameter, and nanoparticle volume fraction. The interactive impacts of the nanoparticles volume fraction and the Falkner-Skan index were found to be non-linear. The movement of the wedge was found to have a significant impact on both the flow field and the rate of heat transfer. 2021 Elsevier Ltd -
RESPONSIBLE AI-READINESS IN HIGHER EDUCATION: VALIDATING A DUAL-MODEL FRAMEWORK FOR FACULTY DEVELOPMENT
Aim/Purpose This study validates a responsible artificial intelligence (AI) framework designed to strengthen AI-readiness among higher education faculty in India. Background With the increasing use of AI in education, faculty require structured support; however, faculty development models for responsible AI integration remain limited. Methodology A mixed-methods pilot study with ten humanities and performing arts faculty used a dual-model evaluation approach. Three sessions from the framework were implemented, and data were collected through knowledge-attitude-practice (KAP) surveys, cognitive-affective-psychomotor (CAP) performance rubrics, and reflective responses. Contribution This study validates a dual-model framework for faculty development regarding responsible AI readiness. Findings The adapted KAP survey demonstrated strong reliability, with higher AI knowledge associated with more positive attitudes. However, knowledge did not consistently translate into practice, highlighting the need for structured hands-on learning. CAP-based performance assessments and reflections indicated improved ethical awareness, critical engagement, and foundational AI-integration skills. Recommendations for Practitioners Institutions should embed structured AI-training for faculty, with authentic instructional tasks. Recommendations for Researchers Future research should test this approach across larger and more diverse institutional contexts. Impact on Society Developing AI-ready faculty can foster ethical and future-focused learning environments. Future Research Future studies should expand across disciplines and examine longer-term outcomes. (2025), (Informing Science Institute). All rights reserved. -
Responsible and sustainable lending by Financial institutions: a literature Review
The subject of the study is to use an extensive literature review to evaluate how academic research on corporate social responsibility (CSR) is developing. The journals and papers in the ISI Web of Science, SCOPUS, and Taylor&Francis databases served as the foundation for this literature review. The purpose of the study is to highlight essential papers, referenced journals importance, and potential future study directions. Determinants that impact the CSR performance of an organization are governance, profitability, firm characteristics, and minimum expenditure. The impact of CSR has been measured using accounting-based market value, risk, excess return on a stock, and moral capital. All the variables are discussed with strongly supported literature and then concluded by giving a framework. The novelty of our study is that it analyses new research trends while concentrating on the CSR research frontiers. The conclusion identifies possible areas for scientists to further develop their expertise, including sustainable and responsible financing and ESG strategy. Sachdeva S., Ramesh L., 2023. -
Restrained domination in signed graphs
A signed graph ? is a graph with positive or negative signs attatched to each of its edges. A signed graph ? is balanced if each of its cycles has an even number of negative edges. Restrained dominating set D in ? is a restrained dominating set of its underlying graph where the subgraph induced by the edges across ?[D: V\D] and within V\D is balanced. The set D having least cardinality is called minimum restrained dominating set and its cardinality is the restrained domination number of ? denoted by ?r(?). The ability to communicate rapidly within the network is an important application of domination in social networks. The main aim of this paper is to initiate a study on restrained domination in the realm of different classes of signed graphs. 2020 Anisha Jean Mathias et al., published by Sciendo 2020. -
Restrained geodetic domination in graphs
Let G = (V,E) be a graph with edge set E and vertex set V. For a connected graph G, a vertex set S of G is said to be a geodetic set if every vertex in G lies in a shortest path between any pair of vertices in S. If the geodetic set S is dominating, then S is geodetic dominating set. A vertex set S of G is said to be a restrained geodetic dominating set if S is geodetic, dominating and the subgraph induced by V - S has no isolated vertex. The minimum cardinality of such set is called restrained geodetic domination (rgd) number. In this paper, rgd number of certain classes of graphs and 2-self-centered graphs was discussed. The restrained geodetic domination is discussed in graph operations such as Cartesian product and join of graphs. Restrained geodetic domination in corona product between a general connected graph and some classes of graphs is also discussed in this paper. 2020 World Scientific Publishing Company.