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Role of psychological well-being, quality of life and distress tolerance in caregivers of geriatric population: an Indian exploratory study
Purpose: This study aims to gain an understanding of how caring for an ageing population affects caregivers psychological well-being, quality of life and ability to tolerate distress. This study provides valuable insights into the challenges faced by family caregivers and underscores the critical need for comprehensive support systems. Design/methodology/approach: A correlational method and cross-sectional research design was used for the study. For this, a sample of 200 caregivers in the age range of 2560 years who were taking care of the geriatric population above the age of 70 years for a minimum of one year were chosen. Four questionnaires ? Burden Scale for Family Caregivers, Psychological Well-Being Scale, World Health Organizations Quality of Life Scale-BRIEF version and Distress Tolerance Scale were chosen. Correlation and multivariate regression were calculated using statistical package for social sciences (SPSS) 21 and Jamovi 3.4.1. Findings: This study found that there is a negative correlation of caregiver burden with psychological well-being, quality of life and distress tolerance. The sub-domains of self-acceptance, psychological health and tolerance levels were most impacted for the caregivers. Through multivariate regression, it was found that the caregiver burden significantly predicted psychological well-being and quality of life. Research limitations/implications: This study focuses on the English-speaking caregivers which may overlook the diverse linguistic and cultural variations within the broader caregiver community in India and the data collection exclusively targeted family caregivers providing support to geriatric population without chronic illnesses. This restriction could potentially limit the generalizability of the findings to the broader caregiving context. Practical implications: The implications of this research are that for caregivers, this study underscores the importance of tailored support programmes that address the negative impact of caregiver burden on psychological well-being and quality of life. Health-care professionals can use the findings to incorporate mental health assessments and interventions within caregiving contexts, recognizing the interconnected nature of these variables. Policymakers can use the findings to inform policies related to caregiver support and health-care resource allocation. Originality/value: In India, the social norm is that children are expected to take care of their parents when they become old. Taking care of elderly parents can be challenging, even emotionally. As a result, this study will focus on how caregivers psychological well-being, quality of life and ability to tolerate distress are affected. Consequently, promoting the creation of community support groups and workplace mental health programmes which could give caregivers a forum to voice their concerns. 2024, Emerald Publishing Limited. -
Stress-Driven Changes in Ascorbic Acid Levels in Raphanus Sativus: A Comparative Study
Abiotic stresses such as extreme temperatures and salinity are known to significantly influence the nutritional quality of vegetables during cultivation and postharvest handling. However comparative study on how different abiotic stresses alter ascorbic acid stability in root vegetables like red radish is understudied. Thus, the present study was conducted to evaluate the effect of various abiotic stresses (heat, cold and salinity) on ascorbic acid (AA) levels and antioxidant activity in red radish (Raphanus sativus L.). DCPIP titration and DNPH UV-Vis spectrophotometric techniques were used to analyse the ascorbic acid content, and the DPPH radical scavenging assay was used to measure antioxidant capacity. The findings showed that as stress duration and intensity increased, the total AA content decreased significantly (p < 0.05). At high temperature (90 C), heat treatment resulted in a progressive decrease from 27.7 mg/100g to 20.8 mg/100g. Under cold stress, AA content increased slightly initially and then dropped by 22% on day 8. A two-phase response to salt stress was seen mild salt concentration leading to a moderately increased AA content, while severe salt concentration caused a 55% reduction after 72 hours. With an IC50 value of 8.27mg/mL, the antioxidant activity increased as extract concentration increased from 3.8% to 62.1% inhibition. According to these findings, red radish exhibits a short-term adaptive defence in mild stress situations but a significant decrease in AA in severe stress situations. These findings are consistent with previous reports in other related vegetables such as tomato, broccoli and spinach, where moderate abiotic stress increases antioxidant defences before degradation occurs. These results suggest the need for efficient postharvest management and stress-aware storage techniques to preserve the functional and health-promoting qualities of red radish. 2026 The Author(s). -
Study of State-of-the-Art Performance Metrics in NLP: Specifically for Text Summarization in the Medical Domain Using the SumPubMed Dataset
Text summarization is becoming very important given the number of documents produced each year across domains. In this paper we explore the various traditional metrics for text summarization, such as ROUGE, BLEU, METEOR, etc., and look at improving the performance of the existing metric by taking the stateof-the-art untrained metric SUPERT, and clubbing it with a readability score and a penalty for long summaries. The SUMPUBMED dataset was used for this research and a BERT extractive summarizer was used for generating the summaries. It was found that using a readability score with an unsupervised metric such as SUPERT helped in assessing the quality of the summary more accurately than earlier metrics. We compared the metrics such as SUPERT scores and BERT scores with and without involving the human annotated summaries in the SUMPUBMED dataset and found that untrained metrics perform better than when involving a reference annotated summary. 2025 Scrivener Publishing LLC. -
Impact of functional inter-dependency on employee satisfaction with performance appraisal in real estate industry
Earlier researches have consistently underlined an intrinsic proportionate relationship between the success of an organization and the effort put in by the employees towards the attainment of the set goals for success. An employee with a higher level of job satisfaction tends to be more positively disposed and productive in the work place, than the opposite of it. A positively charged wok atmosphere contributes much to the overall growth of an organization and is the result of the satisfaction level enjoyed by employees. One major factor that determines employee satisfaction is the organization’s system in place to reward and recognise the employee through performance appraisal. Genuine unbiased performance appraisal tends to bolster the performance of employees. Thus, performance appraisal is one of the most widely researched areas in industrial/organizational psychology (Murphy & Cleveland, 1995). Recent studies among employees indicate several inadequacies with the current performance appraisal system in use as it does not measure the performance in all directions. Thus, there seems to be a gap that needs exploration. Employee’s deliverables depend on external and internal factors. Functional interdependence is one such internal factor which influences the performance of the employee. However, there is limited knowledge available on the role of interdependency factors in the performance of the employee during the performance review. This article presents a conceptual framework to understand the role of functional interdependence in the performance appraisal and the satisfaction of the employee whose deliverables are highly functional interdependence. -
Impact of functional inter dependency on employee satisfaction with performance appraisal in real estate industry
Earlier researches have consistently underlined an intrinsic proportionate relationship between the success of an organization and the effort put in by the employees towards the attainment of the set goals for success. An employee with a higher level of job satisfaction tends to be more positively disposed and productive in the work place, than the opposite of it. A positively charged wok atmosphere contributes much to the overall growth of an organization and is the result of the satisfaction newlinelevel enjoyed by employees. One major factor that determines employee satisfaction is the organization s system in place to reward and recognise the employee through performance appraisal. Genuine unbiased performance appraisal tends to bolster the performance of employees. Thus, performance appraisal is one of the most widely researched areas in newlineindustrial/organizational psychology (Murphy and Cleveland, 1995). Recent studies among employees indicate several inadequacies with the current performance appraisal system in use as it does not measure the performance in all directions. Thus, there seems to be a gap that needs exploration. Employee s deliverables depend on external and internal newlinefactors. Functional interdependence is one such internal factor which influences the performance of the employee. However, there is limited knowledge available on the role of interdependency factors in the performance of the employee during the performance review. This article presents a conceptual framework to understand the role of functional newlineinterdependence in the performance appraisal and the satisfaction of the employee whose deliverables are highly functional interdependence. The framework proposes the relationship between the functional newlineinterdependence in the job, fairness in the performance appraisal by considering that interdependence and subsequently the satisfaction or dissatisfaction of the employee in performance appraisal. -
Ultrasound assisted Friedel-Crafts acylation of aromatics using ferric sulphate as catalyst
The use of ultrasound in the acylation reactions of various aromatics and polyaromatics with different acyl chlorides, in the presence of catalytic amount of ferric sulphate at room temperature, gives good yields of the respective ketones with a short reaction time. A facile and simple synthesis of various aromatic ketones using Friedel-Crafts acylation has been established from the corresponding acid chlorides and aromatic or polyaromatic compounds, respectively under mild reaction conditions with shorter reaction times (30-45 min) and in reasonable yields. This method offers the advantage of low cost and ease of purification of the products because of the small amount of ferric sulphate used in these reactions. -
Corporate governance for sustainable development
Governance relates to structures and processes within an organisation to ensure greater accountability, a higher sense of responsiveness, transparency, and rule of law. Corporate governance balances the interests of a company's many stakeholders, such as shareholders, customers, vendors, financiers, the government, the community, and, very importantly, its own employees. While traditionally corporates had one clear agenda-i.e., make more profits and increase the shareholders' wealth-the 21st century saw the corporates turning a new leaf and looking at their growth from a societal perspective, specifically those relating to sustainable development like environmental protection. In the classical case of poor corporate governance, in the year 1984, the city Bhopal in India witnessed the most nightmarish experience, with the death of 16,000 people due to the leakage of a poisonous gas. 2024, IGI Global. All rights reserved. -
Strengthening Supply Chain Management Through Technology
The removal of trade barriers with the advent of WTO and which led to LPG (liberalization, privatization, and globalization) across the universe increased choices of brands for consumers and even the complexity of products within organization and the expectations of consumers rising daily. Organizations look for better management of their supply chain from end to end, i.e., sourcing of raw materials from vendors to delivering finished products at the doorstep of consumers. This means businesses that used to be operations hubs within the company have moved into the epicenter of business innovation, and this process can not be done manually or by few people within organizations, thus the need to back up business innovations and product complexities through advanced technologies. Using sensors like RFID, CRM, AI, and ML, organizations today collect information at every checkpoint from status of raw materials flow to the location of finished goods. Supply chain management is the process of planning and implementing the operations of the sourcing of quality materials at competitive cost. This chapter explores strengthening supply chain management through technology. 2023 by IGI Global. -
A Study on Motivating Factors Determining the Reasons for Entering into Poultry Farming by Farmers with Special Reference to Suguna Broiler Contract Farms in Coimbatore District
The International Journal's Research Journal of Economics & Business Studies, Vol-3 (5), pp. 61-68. ISSN-2251-1555 -
Understanding The Pastoral Ethnobotany in Koppal and Vijayanagar Districts of Karnataka for Sustainability
The research aimed to comprehensively explore the ethnobotanical significance and nutritional value of wild plants utilized by pastoralists in Koppal and Vijayanagar districts. The study area selection involved meticulous consideration of the geographical and ecological relevance. Determining an appropriate sample size was crucial to ensure representative data collection, achieved through systematic methodologies. Informants were thoughtfully selected to gather newlineindigenous knowledge about the diverse uses of wild plants, emphasizing their fodder, newlineveterinary, edible, and medicinal applications. Employing ethnobotanical research methods, interviews were conducted to document plant usage, elucidate their taxonomical identities, and create an extensive inventory. The collection of plants referenced by pastoralists during interviews was a pivotal step. Detailed assessments of plant categories, habits, habitats, and newlinespecific plant parts used were documented. Herbarium preparation and authentication were newlineconducted meticulously to preserve and validate the collected plant specimens. newlineComparison with ethnobotanical studies from other subtropical regions worldwide was newlineconducted using the Jacquard index, revealing similarities and differences. The evaluation of sustainable utility focused on wild edible plants, analysing their viability for long-term utilization. Furthermore, investigating the forage quality of selected wild fodder and hay supplement plants was carried out. Analysing their proximate provided insights into their nutritional value. In summary, this comprehensive research delved into ethnobotanical practices, taxonomic identification, nutritional evaluation, and sustainable utilization of wild plants among pastoral communities. The findings not only contributed to ethnobotanical knowledge but also provided valuable insights into the potential economic and ecological significance of these plants for the communities involved. -
Machine intelligence security : A methodological blend of fuzzy logic in industry 4.0 algorithms
The way things are made has changed a lot because of Industry 4.0. It has also led to a time with great technology and relationships. The paper discusses way to improve security in Machine Intelligence in the setting of Industry 4.0. The study uses a mix of methods to combine Fuzzy Logic with cutting-edge Industry 4.0 algorithms in order to deal with new hacking problems. Because fuzzy logic can deal with doubt and imprecision, it can be used to make current methods more reliable. This creates a complex and flexible security structure. The merger was carefully planned to make the methods for finding anomalies, reducing threats, and responding to incidents work better. The suggested method aims to make machine intelligence systems more resistant to complex cyber dangers by combining the best parts of Fuzzy Logic with Industry 4.0 algorithms. This study adds to the growing conversation about how to keep smart factory settings safe by focusing on a proactive and dynamic security model. The effects of this mix of methods could be felt in many different industries, making it possible to use advanced technologies in a safer and more reliable way in the age of Industry 4.0. 2024, Taru Publications. All rights reserved. -
An Enhanced Whale Optimization Algorithm for Task Scheduling in Cloud Computing
Task Scheduling is the significant challenge in the environment of Cloud Computing (CC) and has attention in numerous researchers in recent years with respect to attain cost effective computation and improve resource utilization. The existing algorithms has limitations of role and selection criteria of inertia weight was not considered. In this research, Enhanced Whale Optimization Algorithm (EWOA) is proposed for maximize effectiveness of task scheduling in CC. An inertia weight is implemented in WOA algorithm that enhances the convergence and accuracy of algorithm that helps in task scheduling effectiveness. The performance of proposed technique is estimated with performance measure of Makespan (ms), execution time (s) and resource utilization (%). The proposed method attained less execution time of 2304, 2537, 2765, 2983 and 3016s for 200, 400, 600, 800 and 1000 number of tasks. The proposed method attained the superior results when compared with other existing algorithms like Ant Colony Optimization (ACO), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA). The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
A Hybrid Machine Learning Model (NB-SVM) for Cardiovascular Disease Prediction
One of the leading causes of death is heart disease. The prediction of cardiovascular disease remains as a significant challenge in the clinical data analysis domain. Although predicting cardiac disease with a high degree of accuracy is highly challenging, it is possible with Machine Learning (ML) approaches. The implementation of an effective ML system can minimize the need for additional medical testing, minimize human intervention, and predict cardiovascular diseases with high accuracy. This type of assessment can reduce the disease's severity and mortality rate. Only a few studies show how machine learning techniques might forecast cardiac disease. This study presents a method for improving cardiovascular disease prediction accuracy using Machine Learning (ML) technologies. Various feature combinations and many known classification techniques are used to develop various cardio vascular disease prediction models. The proposed hybrid Machine Learning (ML) prediction model for heart disease leverages a higher degree of performance and accuracy. 2023 IEEE. -
The influences of lateral groups on 4-cyanobiphenyl-benzonitrile- based dimers
Cyanobiphenyl-based compounds are known to display RT or low melting liquid crystals in a single-component system or composites. Herein, we discuss the influence of laterally substituted groups (-CN, -F, -H) on 4-[?-(4-cyanobiphenyl-4-yloxy)alk-1-yloxy]benzonitrile. Three series of new dimers were synthesised by using 4-cyano-4-hydroxybiphenyl connected via flexible spacers with different number of carbon atoms to 4-hydroxyphthalonitrile/ 2-fluoro-4-hydroxy benzonitrile/ 4-hydroxy benzonitrile. Their self-assembly in LC phases assessed by polarising optical microscopy (POM), differential scanning calorimetry (DSC) and X-ray diffraction studies, and their behaviours are compared with related non-substituted (-H) model compound. UV-Visible and fluorescent experiments confirm the strong aggregation, the intensities of emission decrease as we move from CN?F?H substitutions. A representative dimer from each series covering the aspect of polarity and flexibility have been simulated using 1000 minimisation steepest descent and CHARMM force filed to examine their self-assembly. This work helps to understand the influence of lateral groups, connecting spacers on the LC behaviour of dimers. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Irreversibility analysis of radiative heat transport of Williamson material over a lubricated surface with viscous heating and internal heat source
Thecurrent research explores the importance of surface lubrication and convective boundary conditions in the flow of non-Newtonian Williamson material. Rosseland radiative heat flux and viscous heating are also considered. The phenomenon of the generation or absorption of internal heat is studied. The conservation laws of momentum, mass, and energy are used to model the problem with suitable boundary conditions. With the help of appropriate transformations and the finite difference method, highly nonlinear equations of governance are solved. The influence of key parameters on Bejan number, velocity, entropy production, temperature profiles are analyzed by parametric analysis. It was found that the entropy generation rate improves due to the presence of the Rosseland radiative heat flux and the convective boundary on the lubricated surface. The sliding condition on the lubricated surface has lengthened the structure of the velocity boundary layer, while this trend is opposite to the thermal field. The dissipation due to the viscous forces of the Williamson material improves the production of entropy. 2021 Wiley Periodicals LLC -
Entropy generation and thermal analyses of a Cross fluid flow through an inclined microchannel with non-linear mixed convection
The temperature difference of the various applications such as microchannel heat exchangers, microelectronics, solar collectors, automotive systems, micro fuel cells, and microelectromechanical systems (MEMS) is relatively large. The buoyancy force (mixed convection) modeled by the conventional Boussinesq approximation is inadequate since the density of the operating fluids fluctuates non-linearly with the temperature difference. Therefore, the mixed non-linear convective transport of the flow of Cross fluid through three different geometric aspects (horizontal, vertical, and inclined) of the microchannel under the non-linear Boussinesq (NBA) approximation is investigated. Mechanisms of internal heat source, Rosseland radiative heat flux, and frictional heating are incorporated into the thermal analysis. The mathematical construction is proposed using the Cross fluid model for a steady-state, and subsequent non-linear differential equations are deciphered by the spectral quasi-linearization method (SQLM). Graphical sketches were constructed and displayed that explore the stimulus of various key parameters on Bejan number, velocity, temperature, and entropy generation. It is found that the Bejan number and entropy production improved due to the non-linear density temperature variation. The convective heating boundary conditions augment the entropy production. The pressure gradient accelerates the transport of fluid in a microchannel. Furthermore, among three different geometries, the velocity, entropy production, and temperature are the highest for the vertical microchannel. 2023 Wiley-VCH GmbH. -
Entropy generation analysis of tangent hyperbolic fluid in quadratic Boussinesq approximation using spectral quasi-linearization method
In many industrial applications, heat transfer and tangent hyperbolic fluid flow processes have been garnering increasing attention, owing to their immense importance in technology, engineering, and science. These processes are relevant for polymer solutions, porous industrial materials, ceramic processing, oil recovery, and fluid beds. The present tangent hyperbolic fluid flow and heat transfer model accurately predicts the shear-thinning phenomenon and describes the blood flow characteristics. Therefore, the entropy production analysis of a non-Newtonian tangent hyperbolic material flow through a vertical microchannel with a quadratic density temperature fluctuation (quadratic/nonlinear Boussinesq approximation) is performed in the present study. The impacts of the hydrodynamic flow and Newtons thermal conditions on the flow, heat transfer, and entropy generation are analyzed. The governing nonlinear equations are solved with the spectral quasi-linearization method (SQLM). The obtained results are compared with those calculated with a finite element method and the bvp4c routine. In addition, the effects of key parameters on the velocity of the hyperbolic tangent material, the entropy generation, the temperature, and the Nusselt number are discussed. The entropy generation increases with the buoyancy force, the pressure gradient factor, the non-linear convection, and the Eckert number. The non-Newtonian fluid factor improves the magnitude of the velocity field. The power-law index of the hyperbolic fluid and the Weissenberg number are found to be favorable for increasing the temperature field. The buoyancy force caused by the nonlinear change in the fluid density versus temperature improves the thermal energy of the system. 2021, Shanghai University. -
Factors influencing dynamic capabilities of entrepreneurial-led organisations to achieve analytical transformation
Entrepreneurial spirit transforms the economic scenario resulting in a significant contribution to society. Analytical transformation enables entrepreneurs with superior effective decision-making capability through information gathering, advanced technology adoption and data analysis. Effective analysis leads to superior organisational performance. However, in entrepreneurial-led large Indian organisations, the adoption of analytics is limited to predicting results. The study aims to identify the key factors that impact analytical transformation. The study also aims to identify key dynamic capabilities to achieve such transformation. This article identifies base theories related to the identified concepts. This article aims to develop an analytical transformation capability model for entrepreneurial-driven large industries. This study also empirically validates the proposed research model. The study concludes that entrepreneurial-led large Indian technology-driven industries lag behind their technology peers in adopting prescriptive analytics. The study also proposes an analytical transformation theory that aims to provide necessary techniques to improve organisational effectiveness. Copyright 2025 Inderscience Enterprises Ltd. -
Best unbiased estimation and CAN property in the stable M/M/1 queue
The Uniform Minimum Variance Unbiased (UMVU) estimators of ??, the probability of having ? or more customers, L, the expected system size, Lq, the expected number of customers in the queue, and, the expected number of customers in a non empty queue, are derived based on a random sample of fixed size n on system size at departure points from the geometric distribution on the support {0, 1, 2,.} with mean, which is the distribution of system size in M/M/1 queueing system in equilibrium. The derivations are based on application of Lehmann-Scheffe theorem. Also, CAN estimators of performance measures are derived. In addition the probability distribution of UMVU estimators are obtained. 2014 Copyright Taylor and Francis Group, LLC. -
Hybrid Quantum Network with Snow Geese-Elk Herd Optimization for Smart Load Shedding in Grids with Electric Vehicles and Photovoltaic Systems
The increasing penetration of variable renewable energy and the growth of electric vehicles (EV) have created an urge for more sophisticated load management methods to ensure grid stability. Conventional load shedding (LS) methods are typically not equipped to manage the unpredictability brought about by these modern additions to the grid. This study introduces an innovative smart load-shedding strategy that uses a hybrid optimization model. At its core is a Quantum Neural Network (QNN), which enables intelligent and data-based load prioritization by evaluating factors such as load criticality, energy usage, responsiveness to demand, and operational flexibility. The required LS amount is calculated through a combined use of Snow Geese Optimization (SGO) and the Elk Herd Optimizer (EHO), with specific attention given to the flexibility offered by EVs to address the variability in photovoltaic (PV) power generation. Testing has been performed on the IEEE 33-bus network reveal a notable decrease in total load demand by around 33%, contributing to improved grid stability, with voltage levels staying close to 0.99 p.u. Additionally, the average load across the network buses dropped by roughly 52%. This hybrid approach not only ensures better performance but also achieves quicker convergence compared to existing optimization methods. The proposed intelligent LS method presents an effective strategy for preserving grid stability amid growing integration of renewables and EV by incorporating QNN with SGO and EHO while accounting for EV adaptability. The Author(s), under exclusive licence to Shiraz University 2025.