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PurposeThe present study intends to study the role of green transformational leadership in promoting green employee behaviour via green employee creativity. The study will draw its foundation from resource-based view and social exchange theory, thereby providing theoretical underpinning to explore the relationship between leadership, creativity and green behaviour.Design/methodology/approachA survey questionnaire was prepared to collect data to examine the relationship among the variables. Responses of 82 human resource (HR) managers and 488 employees of Indian Information Technology/Information Technology Enabled Services (IT/ITES) firms were used for the study. A 2-1-1 multi-level structural equation modelling (ML-SEM) was performed using Mplus version 8.6 software.FindingsThe study reveals significant and positive association for first three hypotheses, i.e. the direct relationship between green transformational leadership, green employee creativity and green employee behaviour. However, the fourth hypothesis is partially supported. Green employee creativity partially mediates the direct relationship between green transformational leadership and green employee behaviour.Originality/valueBy examining how green transformational leadership influences green employee behaviour through the interaction of creativity, the research offers a novel contribution to the field of sustainable organizational practices, enhancing the understanding of leadership, creativity and environmental commitment. The present research addresses pressing societal issues, contributes to more environmentally responsible practices and enhances the understanding of leadership and creativity in today's socially conscious world. Such a holistic examination of these interconnected factors can lead to actionable strategies for organizations to navigate the challenges of environmental responsibility in a rapidly changing world.

PurposeThis study aims to understand the role of employee competencies in terms of the relationship between Human Resource Practices (HRPs) and firm performance.Design/methodology/approachA sample of 60 HR managers and 546 employees from large-scale food processing firms were considered for the study. The study presents a 2-1-2 multilevel mediational analysis in which HRPs and firm performance are measured at the firm level (Level-2) and employee competencies are measured at employee level (Level-1).FindingsPositive relationship was found between HRPs and firm performance, which was partially mediated by employee competencies.Practical implicationsThe study highlights the importance of employee-related factors by focusing on the wider dimensions of human capital (e.g. academic qualification, job experience) in HRPs–performance relationship.Originality/valueThe study undertakes a 2-1-2 multilevel mediational analysis, which is rarely applied in HRM studies; however, this interaction between macro- and microlevel effects will create a better understanding of organization studies from an integrated and multilevel context.

PurposeData science industry is a multidisciplinary field that deals with a large amount of data and derives useful information for taking routine and strategic business decisions. The purpose of this article is to examine the relationship between pricing models, engagement models, and firm performance (FP). This study also aims at uncovering the most effective pricing model and engagement model for improving FP.Design/methodology/approachIndian data scientists were the respondents of the study. A total of 213 responses were carefully chosen. The data were analyzed using structural equations on Statistical Package for Social Sciences-Analysis of Moment Structures (SPSS-AMOS) version 25 software.FindingsThe findings of the study suggested the positive and significant impact of pricing models and engagement models on FP. Value-based pricing strategies have the maximum impact on FP. On the other hand, managed services have a higher influence on FP.Originality/valueBy developing a multi-faceted framework, this study is a novel contribution to the field of business strategy, especially for the data science industry.

Healthcare organizations and Health Monitoring Systems generate large volumes of complex data, which offer the opportunity for innovative investigations in medical decision making. In this paper, we propose a beetle swarm optimization and adaptive neuro-fuzzy inference system (BSO-ANFIS) model for heart disease and multi-disease diagnosis. The main components of our analytics pipeline are the modified crow search algorithm, used for feature extraction, and an ANFIS classification model whose parameters are optimized by means of a BSO algorithm. The accuracy achieved in heart disease detection is 99.1 % with 99.37 % precision. In multi-disease classification, the accuracy achieved is 96.08 % with 98.63 % precision. The results from both tasks prove the comparative advantage of the proposed BSO-ANFIS algorithm over the competitor models.

The advancement of technology is making it difficult for visually impaired people to obtain the most up-to-date and sophisticated phones. The Internet of Things has the potential to improve social interaction for visually challenged people. Hardware devices are constantly being equipped with various electronic sensors for collecting real-time data. However, specially-abled people need an integrated system to access the features of mobile applications and external hardware kits on one platform. Therefore, an integrated framework for the specially-abled is developed. IoT has the potential to improve social integration for people with visual defects. This research is an attempt to design a framework for developing a mobile application using IoT to provide secure and integrated services to the visually impaired people. The findings of the study revealed that the designed framework will help in developing various wireless embedded systems using mobile phones. Furthermore, key features of the designed framework are also highlighted and compared with other frameworks.

The need for metallic biomaterials will always remain high with their growing demand in joint replacement in the aging population. This creates need for the market and researchers to focus on the development and advancement of the biometals. Desirable characteristics such as excellent biocompatibility, high strength, comparable elastic modulus with bones, good corrosion resistance, and high wear resistance are the significant issues to address for medical implants, particularly load-bearing orthopedic implants. The widespread use of titanium alloys in biomedical implants create a big demand to identify and assess the behavior and performance of these alloys when used in the human body. Being the most commonly used metal alloy in the fabrication of medical implants, mainly because of its good biocompatibility and corrosion resistance together with its high strength to weight ratio, the tribological behavior of these alloys have always been an important subject for study. Titanium alloys with improved wear resistance will of course enhance the longevity of implants in the body. In this paper, tribological performance of titanium alloys (medical grades) is reviewed. Various methods of surface modifications employed for titanium alloys are also discussed in the context of wear behavior.

Cardiac rehabilitation (CR) is an evidence-based comprehensive program that includes exercise training, health education, physical activity promotion, and extensive counseling for the management of cardiovascular risk factors. Wearable devices monitor certain physiological functions, providing biometric data such as heart rate, movement, sleep, ECG analysis, blood pressure, energy expenditure, and numerous other parameters. Recent evidence supports wearable devices as a likely relevant component in cardiovascular risk assessment and disease prevention. The purpose of this scoping review is to better understand the role of wearable devices in home-based CR (HBCR) and to characterize the evidence regarding the incorporation of wearable devices in HBCR programs and cardiovascular outcomes. We created a search strategy for multiple databases, including PubMed, Embase (Elsevier), CINAHL (Ebsco), Cochrane CENTRAL (Wiley), and Scopus (Elsevier). Studies were included if the patients were eligible for CR per Medicare guidelines and >18 years of age and if some type of wearable device was utilized during HBCR. Our search yielded 57 studies meeting all criteria. The studies were classified into 4 groups: patients with coronary heart disease (CHD) without heart failure (HF); patients with HF; patients with heart valve repair or replacement; and patients with exposure to center-based CR. In three groups, there was an upward trend toward improvement in quality of life (QOL) and peak VO2, less sedentary time, and an increase in daily step count in the intervention groups compared to control groups. HBCR using wearable devices can be a comparable alternative or adjunct to center-based CR for patients with CHD and HF. More studies are needed to draw conclusions about the comparability of HBCR to center-based CR in patients with heart valve repair or replacement.

PurposeEmployee Stock Options [ESOs] have been used widely as a component of employees' compensation. To maximise the incentive effect of these options it is very important to understand the exercise decision of the employees. This is an important financial decision that is dependent on both rational and psychological factors. This paper aims to study the mediating role of Herding Bias on Personality Traits and the employees' decision to exercise ESOs.Design/methodology/approachThe data were collected through a self-structured questionnaire from 210 employees of Banks and NBFCs [Non-Banking Financial Companies] who have received and exercised the ESOs. SPSS MACRO version 25 was used to understand the mediational effect of Herding Bias on Personality Traits and Employees' decision to exercise their ESOs.FindingsThe results showed that Personality Traits affect the employees' decision to exercise their ESOs. The study also shows a partial negative mediating effect of Herding Bias on Personality Traits and employees' decision to exercise ESOs.Originality/valueLimited study has been conducted on how the employees make their decision to exercise ESOs. Although extant studies have touched upon the importance of including behavioural biases in ascertaining the exercise decision of the employees, the predictors of the behavioural biases have not been studied under this context. To the best of the author's knowledge, this study is the first in itself to study the inter-linkage between Personality Traits, Herding Bias and employees' decision to exercise ESOs.

Muskmelon, a widely cultivated cucurbit crop valued for its delicious fruit, is severely threatened by different biotic stresses, including root - knot nematodes (RKNs). RKN, a soilborne pathogen belonging to the genus Meloidogyne , adversely affects crop yield, causing up to 30% damage in highly susceptible crops such as muskmelon. Developing resistant cultivars through breeding can be an effective approach to combat this disease. In the present study, 110 plants from the F 2:4 mapping population were generated by crossing snapmelon accession “SM2012-1” (resistant parent) with melon cultivar “Punjab Sunehri” (susceptible parent) and used to map RKN resistance genes using genotyping-by-sequencing (GBS). Phenotyping was carried out by artificial screening of F 2:4 plants against nematodes in a net house, in the rainy season, and in the spring season in 2023. Quantitative trait loci (QTL) analysis was conducted using WinQTL Cartographer, by integrating the high-density genetic linkage map (with an average marker density of 5.48 markers/Mb) and corresponding phenotypic data, which identified a total of nine QTLs associated with RKN resistance located on chromosomes 2, 8, 9, and 12. The QTLs were designated as qRKN _ Cm2.1 , qRKN _ Cm2.2 , qRKN _ Cm2.3 , qRKN _ Cm8.1, qRKN _ Cm8.2 , qRKN _ Cm9.1 , qRKN _ Cm9.2 , qRKN _ Cm12.1 , and qRKN _ Cm12.2 , respectively. Among these, three QTLs ( qRKN _ Cm8.1 , qRKN _ Cm12.1 , and qRKN _ Cm12.2 ) were identified in the net house exhibiting phenotypic variance explained (PVE) that ranged from 10.1% to 26.8%. Two QTLs ( qRKN _ Cm2.1 and qRKN _ Cm9.1 ) were detected in the rainy season with a PVE of 8.2% to 8.3%, while four QTLs ( qRKN _ Cm2.2 , qRKN _ Cm2.3 , qRKN _ Cm8.3 , and qRKN _ Cm9.2 ) were identified in the spring season, with a PVE of 8.1% to 10.3%. The logarithm of odds (LOD) score for these QTLs ranged from 2.5 to 3.3. QTL mapping of RKN resistance carried out in the present study will provide linked molecular markers for marker-assisted selection (MAS), thereby providing a valuable resource for effective deployment of RKN resistance in melon breeding programs to developing elite resistant cultivars.

This paper presents a microstrip patch antenna working at MICS (Medical Implant Communication System) band whose core band is 402–405 MHz for the detection of tumor in human breast tissue. The proposed antenna is designed and fabricated on the FR-4 substrate with dielectric constant 4.4, thickness 1.6 mm and loss tangent 0.0024. The actual antenna size is 15 mm × 15 mm which is small enough to be implanted in breast tissue to give satisfactory performance. To analyze the characteristics of antenna, it is embedded in the gel type tissue material whose electrical properties are the same as that of the human skin in case of conductivity and permittivity. MICS band is preferred because of its docility towards higher bandwidth. There is a difference in return loss characteristic of the antenna which has been simulated with and without tumor. This difference in return loss clearly depicts the presence of tumor inside the breast. Various parameters such as return loss, radiation pattern and directivity are also measured for the proposed antenna at 402–405 MHz band.