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Recently, the North Tropical Atlantic (NTA) Sea Surface Temperature (SST) anomalies emerge as a key-driver in the biennial transitions of El Niño Southern Oscillation (ENSO) and by extension of the whole ENSO-Indian Summer Monsoon (ISM) system. In this context, we utilized a suite of Coupled Model Intercomparison Project Phase 6 (CMIP6) models with the Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5) and historical simulations to investigate whether the ENSO-ISM teleconnections as well as its biennial signature undergoes significant modulations in the future warming climate as mediated through the NTA SSTs. Our results reveal a pronounced increase in NTA variability under greenhouse warming, associated with an enhanced two-way teleconnection between NTA and ENSO, while the increase of ENSO variability is more modest. There is an exaggerated signature for the previous ENSO SSTs impacting boreal spring NTA SSTs, compared to a modest enhancement in NTA forcing on the following ENSO state. However, intriguingly, this later signature of NTA damping the ENSO variability seems to strengthen steadily from the historical simulation to the SSP5-8.5, implying an enhanced NTA forcing and biennial rhythm in future projections. In consonance with this emerging NTA signal, there is a significant increase in the variability of ISM rainfall by 21st century, together with a modest strengthening of the ENSO-ISM relationships in the future warming scenarios. We also noted consistent future strengthening of a biennial signature in the ENSO-ISM teleconnection. It is further inferred that the Pacific equatorial zonal SST gradient in conjunction with the NTA relative warming act as important sources for the future intensification of this biennial signal in ENSO variability and for the inter-model spread in the projections. In contrast to this, the future intensification in ISM rainfall variability and its biennial signature are not uniquely driven by these factors. [ABSTRACT FROM AUTHOR]

In last few decades, there is massive growth in electric and electronics industry which leads to a high rate of obsolesce resulting decline in end of life (EOL) or end of use of the product. Circular economy is a concept used to close the material cycle loop in product ecosystem. The current situation of developing countries like India has a variety of issues in managing the e-waste generated, and only viable answer is to reduce waste output and practice recycling. To change into circular economy, it is necessary to identify the barriers affecting the circular economy for effective e-waste management. The aim of the article is to identify the barriers affecting circular economy of e-waste with previous literature and expert opinion from industries and academia, then analyses of barriers have been done using interpretive structural modeling (ISM) and fuzzy MICMAC technique. The result shows that lack of incentives, lack of customer awareness toward circular economy, and lack of government policies are the key barriers affecting circular economy of e-waste in India. This paper will assist organizations, recycling industries, and policymakers in building a sustainable environment strategy to achieve the effective circular economy of e-waste. [ABSTRACT FROM AUTHOR]

The purpose of this research is to identify effective factors in the evaluation of organizational performance in Iran Telecommunication Company using the fuzzy hierarchical analysis method of Mikhailov along with interpretive structural modelling. First, by studying the literature and research history, more than 14 general factors affecting the evaluation of organizational performance were identified, which were identified using a questionnaire and based on the opinions of 22 experts, among them 9 factors with a total of about 90% of the opinions that have the most importance in influencing were determined to be considered for levelling. The levelling of these factors in terms of importance was based on the FAHP method and the ISM method. Due to the use of Mikhailov’s fuzzy hierarchical analysis method along with interpretive structural modelling to identify and stratify the influencing factors on the evaluation of organizational performance, this research is considered an innovative model for studying the evaluation of organizational performance. According to the findings of the review of the above factors, which was based on ISM, the “public environment” factor has gained the most importance, and this factor, along with the “strategy” factors, as well as “processes and methods” and “interactive environment” as basic factors in The final research model was determined. [ABSTRACT FROM AUTHOR]

The escalation of carbon emissions has propelled global warming into a global issue requiring urgent attention. As primary contributors to global carbon emissions, cities constitute the central battleground for efforts aimed at carbon emission reduction. Notably, China, the world's largest carbon emitter, has channeled substantial human and financial resources towards the development of low‐carbon cities. However, the multifaceted challenges confronting Chinese low‐carbon city construction (LCC), including the lack of clearly defined construction strategies and deficiencies in government policy implementation, underscore the need for a systematic exploration of the influencing factors and mechanisms to overcome these obstacles. In response to this pressing need, this study utilizes a conceptual framework that is deeply rooted in the complex urban social‐economic‐natural‐management ecosystem. Within this framework, the study meticulously identified 12 influencing factors and, employing the pressure‐state‐response (PSR) model, categorized them to elucidate the dynamic and multidimensional nature of low‐carbon city construction. Subsequently, the DEMATEL method was employed to explore the causality and centrality of these 12 factors, and the ISM method was used to analyze the hierarchical structure and influencing factors and mechanisms of LCC. Three paths from LCC pressure to LCC response were established. Finally, three major implications were proposed to help Chinese LCC: (i) improve urban strategic planning applicability in a one‐city‐one‐policy manner, (ii) strengthen the green economy's long‐term development mechanism, and (iii) use the enthusiasm of market forces and public participation. [ABSTRACT FROM AUTHOR]

The COVID-19 global pandemic, over the last year and a half, has managed to create massive disruptions in global supply chains and exposed their vulnerabilities, thereby reemphasizing the importance of resiliency. The current study aims to identify and prioritize, through the quantitative decision-making technique of Interpretive Structural Modelling (ISM), a set of barriers to resiliency for the pharmaceutical supply chain in India. The rationale behind choosing the Indian pharmaceutical supply chain was that the pharmaceutical sector in India supplies over half of the global demand for vaccines and generic drugs, and the trajectory of growth is indicated around US$100 billion by the year 2025, along with exporting pharmaceutical products to nearly 200 destination countries. The findings of the current study are expected to aid the decision-makers in evaluating the relative criticality and the interrelationship between the potential (and critical) barriers to supply chain resiliency, and in turn to develop strategic plans. This, in turn, can help to combat unforeseen supply chain disruptors such as COVID-19. This methodology and the findings of the study can be generalized for other supply chains. [ABSTRACT FROM AUTHOR]

This research endeavored to provide an analysis of the barriers related to the agri-food supply chain in the context of the Indian agro-industry. The methodology used is based on an Interpretive Structural Modeling with a Matrix of Cross Impacts-Multiplication Applied to a Classification (MICMAC) technique. There is a need for specificity in defining Agro-food supply chain barriers before they can be eliminated. Therefore, the goal of this study is to look at the factors which are emerging as constraints to the growth of the agri-food supply chain. The findings show that transparency and traceability, inadequate infrastructure, difficulty in implementing government schemes, and inadequate risk management measures constitute important barriers to agri-food supply chains. This study provides an understanding of supply-chain barriers related to the agro-food industry. Managers/owners of agricultural enterprises can use the findings of this study to more easily identify the prominent barriers which affect agri-food supply chains. Furthermore, this study can be used as a guide to deal with the supply chain problems facing agri-enterprises in the face of high demand for agri-products. [ABSTRACT FROM AUTHOR]

Copyright of Comparative & International Education is the property of Canadian & International Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Accurate collisional rate coefficients for collisional transitions between 15 rotational levels of methanimine, colliding with p-H2 molecule, are available. Methanimine is a planar, asymmetric top molecule having electric dipole moment with components μa = 1.3396 Debye and μb = 1.4461 Debye, and thus, producing both the a and b type spectral lines of nearly equal intensities. Therefore, all the rotational levels need to be considered together. Between 15 rotational levels, 105 collisional transitions are considered in an investigation by others. We have discussed that each level is not connected with all others through the collisions, and therefore, there should be 77 instead of 105 collisional transitions between 15 levels of methanimine. With availability of accurate collisional rate coefficients, it is worth to perform the Sobolev analysis of methanimine. We have found six weak MASER transitions, 110-111, 211-212, 312-313, 41.3-41.4, 303-212 and 40.4-31.3, and one transition 111-202, showing anomalous absorption. These seven lines may play important role for the methanimine. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy Delphi-ISM approach to determine the enablers and establish a hierarchical relationship of the enablers of the three strategies suggested by National Institution for Transforming India (NITI) Aayog and Rocky Mountain Institute (RMI) report i.e., cleaner technologies, modal shift, and operational efficiency. The enablers are categorized based on the PETTOHI framework. Twenty enablers each for cleaner technologies and modal shift, and fourteen enablers for operational efficiency, respectively, were shortlisted after the fuzzy defuzzification process using the fuzzy Delphi method. Three hierarchical models were then developed using Interpretive Structural Modelling (ISM) to identify the interrelationships among the enablers of each strategy. A Cross Impact Matrix Multiplication Applied to a Classification (MICMAC) analysed the enablers based on their driving and dependence powers. ISM model for enablers of cleaner technologies reveals that the policy and organisation related enablers like implementation of BS VI norms, public private sector collaborations are the major enablers. Study on the enablers of modal shift identifies the importance of policy and infrastructure related items. The development of Multi-modal logistic parks, imposition of eco taxes are the driving enablers in this ISM model. Implementation of PM Gati Shakti, development of highways, waterways, freight corridors are the key enablers for improving operational efficiency. Enablers pertaining to policy, organisation, and infrastructure such as imposing eco taxes and infrastructure development are critical. [ABSTRACT FROM AUTHOR]

Green construction practices (GCPs) are essential for the construction industry to achieve carbon neutral and sustainable development. However, the promotion of GCPs faces multifaceted challenges, particularly within the context of recent global uncertainties. The COVID-19 pandemic has wrought substantial disruption upon the construction sector, which makes it a good candidate as a case study for enhancing future risk management strategies. Currently, there is limited research on the factors influencing GCPs in the global uncertainty context. To bridge this research gap, this study first identifies 26 factors affecting GCPs in the context of the COVID-19 pandemic through a comprehensive literature review. Subsequently, based on feedback from 22 experts, Interpretative Structural Modeling (ISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) methodologies are adopted to illustrate the intricate relationships among influencing factors and further classify their relative importance. The results underscore the pivotal role of factors such as technology development, the difficulty of construction, materials, and equipment performance, as well as identify 13 factors that have a fundamental impact. This research provides insights for decision-makers to enhance risk management strategies for GCPs in the global uncertainty context, prioritize the determinants, and facilitate the optimal allocation of resources to advance GCPs. [ABSTRACT FROM AUTHOR]

A four-port annular ring patch antenna with a symmetrical slotted partial ground structure for mid-band 5G/Bluetooth/Wi-Fi/ISM band/WLAN and IoT applications at an operating frequency of 2.5 GHz is proposed. The proposed geometry is fabricated over the FR-4 epoxy substrate with dielectric constant 4.4, thickness of the substrate 1.6 mm, and loss tangent of 0.02. Moreover, the complete electrical dimension of presented design is 0.62 λ 0 × 0.48 λ 0 × 0.013 λ 0 , where λ 0 is wavelength in the free space corresponding to the resonating frequency (i.e., 2.5 GHz). In the proposed work, for enhancing the isolation a vertical slotted strip is used in the middle of the ground plane. Furthermore, we also enhanced the MIMO parameters performances, such as a low envelope correlation coefficient (ECC) between antenna elements, good diversity gain (DG), low channel capacity loss (CCL), acceptable mean effective gain (MEG), and better total active reflection coefficient (TARC) in the operating band. Moreover, due to four elements the presented work provide the higher data rates, excellent throughput of the signals and improve communication reliability as well as signal strength. The values of different parameters obtained for the proposed structure are as follows; antenna realized gain of 4.65 dBi, total efficiency of 96%, ECC < 0.025, DG is 9.98 dB, CCL < 0.012 bits/s/Hz, and MEG lies in between - 3 dB and - 12 dB. Throughout the band, the maximum isolation achieved among all ports is < - 26.4 dB. The overall frequency range for which reflection coefficient < - 10 dB is 2.36 to 2.99 GHz. [ABSTRACT FROM AUTHOR]

Literature suggests that the international student industry faces increasing risk, given the substantial dependence on a few source countries. Inbound international student mobility (ISM) data of leading higher education (HE) destination countries were examined, with China and India as the source countries. This study classifies Australia, Canada, and the USA as host countries with a high international student source country dependency risk; the UK as a host country with a moderate dependency risk. By exploring the issue from a dependency risk mitigation perspective, this study identifies an elaborate two-step market diversification approach involving international market selection and marketing strategy. [ABSTRACT FROM AUTHOR]

Low-carbon supply chain management (LCSCM) strategies are required in the Indian manufacturing industries due to rapidly growing energy usage for financial and environmental reasons. LCSCM technologies face several challenges that limit their adoption. Eleven hurdles were selected from the literature and the recommendations of one business expert and one academic expert. These barriers are defined by several factors, including a lack of information, financial worries, environmental concerns, and governmental limits, among others. In addition, efforts are being made to quantify the most optimal relevant barriers using multi-criteria decision-making (MCDM) techniques such as interpretive structural modeling (ISM) and the decision-making trial and evaluation laboratory (DEMATEL). The MICMAC analysis estimates the sensitivity and priority of barriers based on dependency and driving power. One of these barriers is a needed factor; three are driving elements; four barriers are linked factors; and three are self-sufficient factors. The findings of this study can help academic specialists, industry representatives, and practitioners in their ongoing attempts to adopt "LCSCM techniques" in Indian manufacturing industries. The model is appropriately explained and applies the link between the barriers. The objective of this paper is to evaluate and select the most influential barriers to adopting LCSCM in the Indian manufacturing sector that are interrelated. [ABSTRACT FROM AUTHOR]

In response to compelling environmental and societal imperatives, the real estate sector is increasingly compelled to adopt environmentally sustainable practices, prompting a significant “green” shift. Drawing upon an extensive literature review and insights garnered through expert interviews, this study identifies 15 critical factors influencing the green supply chain in the Indian real estate domain. Employing the Interpretive Structural Modeling–Dynamic Multi-Attribute Decision-Making Trial and Evaluation Laboratory (ISM–DEMATEL) approach, the hierarchical and contextual relationships among these factors are systematically examined. The ISM–DEMATEL analysis unveils that government policies and legislation, developer orientation and commitment, and green financing emerge as the top three pivotal drivers steering the green supply chain in the Indian real estate sector. To further categorize these drivers, a Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis is employed, resulting in the classification of factors into independent, dependent, autonomous, and linkage categories. The research offers practical insights that may prove invaluable to stakeholders within the real estate industry as well as academicians.

The paper explores the potential of CRM as a strategic element (along with performance, customer and bank perspectives, and demographic changes) for employee retention (using the Indian banking system as an example). The banking industry was chosen for this study because it is a service sector where transactions involving sensitive products (financial instruments) attract maximum attention from both employees and customers in the long run. To achieve this goal, the authors identified the main factors of customer relationship management that make it effective. The study investigated the relationship between CRM practices, the efficiency of banking operations, and the retention of bank employees. The analysis showed that bank employees have a much greater potential to influence the effectiveness of its activities than clients. Therefore, banks’ management should pay more attention to the recruitment of personnel, not only to the CRM system. The article specifically investigated the rationality of the relationship between CRM, bank branch efficiency, employee retention, and demographic variables. This allowed for several options for banks’ strategies in forming a stable staff of employees to be proposed. An important result of the study was the justification of the modification and addition of the ISM (Interpretive Structural Modelling) mechanism, which received a new name - RISM (Rational Interpretive Structural Modelling). Without violating the basic rules of ISM, the new mechanism allows to achieve better results, as it enables the development of a strategy for independent variables with a more accurate prediction of results.

Today age of advancement one of the fastest growing fields of the technology is wearable electronics and device. In the recent advancement the wearable devices for on and off body communication is going expeditiously. For the wearable wireless communication, wearable antennas are mostly used due to its compact size, self powered, light weight, low profile, portable wireless communication and sensing. This paper throws light on wearable antennas for on body and off body communication including their applications, advantages and disadvantages. A comparative study is conducted on designing of different on body and off body wearable antennas and parameters of designed antenna such as their size, shape, gain, SAR have been compared and analyzed. In this paper also discussed the impact of the wearable antenna on human body and impact of human body on antenna.

Super‐resolution fluorescence microscopy is of great interest in life science studies for visualizing subcellular structures at the nanometer scale. Among various kinds of super‐resolution approaches, image scanning microscopy (ISM) offers a doubled resolution enhancement in a simple and straightforward manner, based on the commonly used confocal microscopes. ISM is also suitable to be integrated with multi‐photon microscopy techniques, such as two‐photon excitation and second‐harmonic generation imaging, for deep tissue imaging, but it remains the twofold limited resolution enhancement and requires expensive femtosecond lasers. Here, the super‐linear ISM (SL‐ISM) pushes the resolution enhancement beyond the factor of two is presented and experimentally demonstrated, with a single low‐power, continuous‐wave, and near‐infrared laser, by harnessing the emission nonlinearity within the multiphoton excitation process of lanthanide‐doped upconversion nanoparticles (UCNPs). Based on a modified confocal microscope, a resolution of ≈120 nm, 1/8th of the excitation wavelength is achieved. Furthermore, a parallel detection strategy of SL‐ISM with the multifocal structured excitation pattern is demonstrated, to speed up the acquisition frame rate. This method suggests a new perspective for super‐resolution imaging or sensing, multi‐photon imaging, and deep‐tissue imaging with simple, low‐cost, and straightforward implementations. [ABSTRACT FROM AUTHOR]

Summary In this research work, the design and analysis of a compact microstrip antenna having a monopole structure with 64.86% of wide bandwidth is presented. The main radiator of the structure is a fractal‐based geometry with the shape of a half‐Koch snowflake, and the ground plane is partial (defected ground). The design methodology of the antenna is presented using analytical modeling, and the structure prototype is fabricated to verify the performance. Measurement outcomes confirm the −10 dB bandwidth in range of 4–7.84 GHz, thus covering approximately the C‐band with omnidirectional radiation patterns. The proposed antenna shows a peak realized gain of 3.4 dBi at 7.2 GHz and has an overall dimension of 0.33λ × 0.49λ × 0.03λ, at 5.8 GHz. The structure is found compact compared to some recently reported designs and the read range is found to be 1.98 cm at 5.8 GHz. The read range and validation of the propagation test indicate the suitability of the compact and wideband planar antenna in various short‐range reader applications. [ABSTRACT FROM AUTHOR]

This work is dedicated to the study of interstellar medium (ISM) along the line of sight (LOS) of the transient low-mass X-ray binary, MXB 1659-298, capitalizing the high resolving power of XMM-Newton in the soft energy range. We emphasized the analysis of reflection grating spectrometer (RGS) data in the energy range 0.5–2.15 keV, suitable for the study of ISM. The paper includes an explanation of why, in the soft X-ray energy range, only two observations (out of seven) were deemed eligible for analysis. Three absorption lines associated with highly ionized Fe XX (1s22p2-2p2 (3p) 4d), Si XIV (1s2-1s2p), and Mg XI (1s2-1s6p) were identified in the observations, with IDs of 8620701(2001) and 748391601(2015). These new absorption lines and the absorption edge due to the neutral oxygen K edge seen in the spectra validate the multiphase structure of ISM. The predominance of interstellar medium over the ionized absorber is established along the direction of the source. The equivalent hydrogen column density measured is nearly equal to the galactic HI value derived previously. The small value of the ionic column density of Fe, Si, and Mg in the site of the high-temperature region resembles previous findings. [ABSTRACT FROM AUTHOR]

Copyright of Financial & Business Studies Journal / Maǧallaẗ Al-Dirāsāt Al-Māliyyaẗ wa Al-Tiǧāriyyaẗ is the property of Beni Suef University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We analysed the BSi (Biogenic Silica) contents of the marine core SK-313/1 from the southeastern Arabian Sea which is dated up to ~14.5 kyr BP. Results show that the maximum and minimum BSi contents are 2.5 and 0.5%, respectively. This is because of the low supply of silica skeleton and the high dissolution and dilution of terrigenous materials. The BSi mass accumulation rates indicate a trend of reduced paleoproductivity during the late Glacial period and increase during the Holocene, with global climatic shifts. Insolation changes at low latitudes, which regulate temperatures, may affect nutrient availability and, consequently productivity variations on a glacial–interglacial timescale. Notably, millennial events like the Younger Dryas (YD) periods, exhibited lower paleoproductivity, in contrast to the Bølling/Allerød (B-A) period and the middle Holocene, which displayed elevated levels of paleoproductivity. These millennial-scale fluctuations in siliceous productivity may be due to the changes in nutrient supply caused by the Indian summer monsoon (ISM). The period of increased paleoproductivity could be influenced by intensified chemical weathering and a boosted nutrient supply, which are consequences of the strengthened ISM during periods of relatively higher temperature. [ABSTRACT FROM AUTHOR]

The present research is aimed at evaluating the climate coupled models with respect to the observational datasets for the investigation of the characteristics of the Indian summer monsoon (ISM). The monthly averaged historical simulations from 12 coupled climate models that participated in Coupled Model Intercomparison Project Phase 6 (CMIP6) are compared with the ground based observational data, satellite and reanalysis datasets for the study period of 1980–2014. This study uses these high‐resolution models to investigate monsoon features, onset and withdrawal dates, primarily focusing on individual model performances rather than highly documented multi‐model mean performance. Performance evaluation of the models suggests that sea surface temperature (SST) simulations by the models are in better agreement for the Arabian Sea than the Bay of Bengal with respect to the ERA5 reanalysis data sets. Further, inter‐model differences amongst the CMIP6 models in estimating the spatial distribution of various monsoon system variables during pre‐monsoon and monsoon seasons are noted which may be attributed to the different model components and varying physics configuration, nonetheless, models like NESM3 and INM‐CN5 are able to reproduce ISM pattern reasonably well. The annual precipitation cycle demonstrates a good agreement between most climate models and IMD data. Evolution of tropospheric temperature gradient (ΔTT) estimated from the CMIP6 models mimics the temporal pattern of the annual rainfall and therefore, is used to estimate the onset and withdrawal dates from CMIP6 models; however, high variability is noted amongst the CMIP6 models in retrieving the onset and withdrawal dates when compared with the IMD observations. Most of the models show a shorter rainy season except NorESM2‐MM. Overall our results suggest that the CMIP6 models can be used for the seasonal mean evaluation of monsoon system parameters and process‐based studies to improve our present understanding of the ISM system. [ABSTRACT FROM AUTHOR]

The paper explores the potential of CRM as a strategic element (along with performance, customer and bank perspectives, and demographic changes) for employee retention (using the Indian banking system as an example). The banking industry was chosen for this study because it is a service sector where transactions involving sensitive products (financial instruments) attract maximum attention from both employees and customers in the long run. To achieve this goal, the authors identified the main factors of customer relationship management that make it effective. The study investigated the relationship between CRM practices, the efficiency of banking operations, and the retention of bank employees. The analysis showed that bank employees have a much greater potential to influence the effectiveness of its activities than clients. Therefore, banks’ management should pay more attention to the recruitment of personnel, not only to the CRM system. The article specifically investigated the rationality of the relationship between CRM, bank branch efficiency, employee retention, and demographic variables. This allowed for several options for banks’ strategies in forming a stable staff of employees to be proposed. An important result of the study was the justification of the modification and addition of the ISM (Interpretive Structural Modelling) mechanism, which received a new name - RISM (Rational Interpretive Structural Modelling). Without violating the basic rules of ISM, the new mechanism allows to achieve better results, as it enables the development of a strategy for independent variables with a more accurate prediction of results. [ABSTRACT FROM AUTHOR]

The rapid growth of healthcare sector, especially after the COVID-19 pandemic, has augmented the emission of healthcare waste globally. The healthcare waste is a major concern for developing economies like India instead of developed ones due to ineffective waste management systems. However, the circular economy is a proven approach to efficient waste management. Thus, this study has recognised and prioritised the criticality of critical success factors for the adoption of a circular economy in Indian healthcare to minimise waste generation. Initially, an analysis of variance followed by questionnaire surveys and descriptive statistics is executed to identify the substantial differences in the adoption of circular economy in healthcare having different sizes or domains of expertise. Finally, the interpretive structural modelling embedded fuzzy-decision-making trial and evaluation laboratory method is used to identify the most significant critical success factors for adopting a circular economy in health care. Among 17 finalised critical success factors, 12 are identified in a causal group, while the remaining five are in the effect group. The government's responsibility and stakeholders' participation have the highest driving potential, whereas the segregation and collection of healthcare waste 1depend highly on other causal-critical success factors. This study also shows the suitable extent to Indian policymakers for developing strategies and assigning the resources and efforts to enhance the adoption of a circular economy in health care from an Indian perspective. However, the results obtained are India-specific, but this can be a platform to understand and analyse the adoption of a circular economy in health care for other developing economies. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Distance Education (1672-0008) is the property of Zhejiang Open University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The worsening of environmental pollution has compelled industrial organizations to implement improvements across the board and work to inspire staff to engage in active green behavior. However, the majority of recent studies are restricted to a certain perspective, and there is a dearth of study on the variables influencing employees' green behavior in general. This research is grounded in a comprehensive viewpoint. Experts evaluate the relevant aspects using fuzzy language, and they combine their individual judgements using the central ordered weighted operator to get a more scientific conclusion. The outcomes of expert judgment are then examined using a variety of analytical techniques, including decision-making trail and evaluation laboratory method, interpretative structural model, and MICMAC Matrix, to identify the critical variables that influence employees' adoption of environmentally friendly behavior. The findings indicate that the most important variables impacting workers' green behavior are employee motivation, values, and responsible leadership. The attitudes, practices, and leadership philosophies of leaders regarding green conduct have an impact on employee motivation and values. The enterprise's sustainable development idea is also shown to be impacted by leaders' attitudes toward green conduct in a number of other areas, including the organizational environment, organizational and human resource management, and other areas. All of these elements have an impact on employees' values and drive to adopt green practices, either internally or outside. This research can assist businesses in identifying the critical influencing elements that impact workers' green behavior and provide focused recommendations to enhance employee green behavior. [ABSTRACT FROM AUTHOR]

The high cost of centralized photovoltaic power generation projects is an important problem affecting industrial development, which needs to be solved urgently. It is particularly important to explore the influencing factors of cost control and the interaction between them. This paper takes a centralized photovoltaic power generation project as the research object, and determines the index system of influencing factors of cost control from the perspective of the life cycle. Secondly, the logical relationship between influencing factors is judged by the method of combining DEMATEL (decision-making trial and evaluation laboratory) and ISM (interpretive structural modelling). Finally, the multi-order recursive interpretation structure model is obtained, and the action mechanism between various factors is obtained. The results show that national policies and standards are the most profound influencing factors, and their cause degree reaches 2.155; the reason degree of market changes is the second, which is 1.586; bidding and contract management are the factors with the highest centrality, which is 7.120; and transmission and the storage of electricity and equipment repair and maintenance are the most direct factors affecting cost control. Finally, some suggestions are put forward for different types of influencing factors. The research results can better help photovoltaic power generation enterprises solve the problem of cost control. [ABSTRACT FROM AUTHOR]

A novel, compact, monopole apple-shaped, triple-band metamaterial-printed wearable antenna backed by a uniplanar compact electromagnetic bandgap (UC-EBG) structure is introduced in this paper for wearable wireless and medical body area network (WBAN/MBAN) applications. A tri-band UC-EBG structure has been utilized as a ground plane to minimize the impact of antenna radiation on the human body and improve antenna performance for the proposed wearable antenna. Metamaterial triangular complementary split ring resonators (TCSRRs) are incorporated into the antenna and UC-EBG structure, resulting in a compact UC-EBG-backed antenna with an overall size of 39 × 39 × 2.84 mm3 (0.41 λg × 0.41 λg × 0.029 λg). The printed textile antenna operates at 2.45 GHz for the wireless local area network (WLAN), 3.5 GHz for 5G new radio (NR), and 5.8 GHz for the industrial, scientific, and medical (ISM) bands with improved gain and high-efficiency values. Furthermore, the performance of the antenna is analyzed on the human body, where three models of curved body parts are considered: a child's arm (worst case) with a 40 mm radius, an adult's arm with a 60 mm radius, and an adult's leg with a 70 mm radius. The results demonstrate that the proposed antenna is an attractive candidate for wearable healthcare and fitness monitoring devices and other WBAN/MBAN applications due to its compact size, high performance, and low SAR values. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Oxidation reactions catalysed by O2‐dependent enzymes are gaining increasing interest in the chemical industry due to their potential to provide a more selective and sustainable alternative to conventional chemical oxidation methods. O2‐dependent enzymes, like oxidases and oxygenases, catalyse a versatile range of oxidative reactions using only molecular oxygen as an oxidant. However, their practical application on a larger scale has been limited up to this point, primarily due to factors like their low catalytic rates combined with a narrow substrate spectrum and low stability. Nonetheless, enzyme engineering studies have significantly addressed these challenges in recent years and moved O2‐dependent enzymes closer towards industrial utilisation. This review aims to concisely overview the most recent engineering approaches to O2‐dependent enzymes. We will highlight recent studies that have targeted various aspects of O2‐dependent enzymes, including activity, selectivity, stability, and substrate spectrum, focusing on engineering studies where the engineered enzymes catalysed synthetically valuable reactions. [ABSTRACT FROM AUTHOR]

This research is devoted to forecast the distortion of aileron brackets by means of generative design (GD) and multi-scaled numerical simulation comprising meso- and macro-scaled simulation based on thermomechanical method (TMM) and inherent strain method (ISM), respectively. The multi-scaled simulation began with TMM-based virtual calibration test (VCT) including mesh sensitivity and volume fraction analysis to identify the best meshing voxel size. In finding inherent strain tensors, optimization was implemented using pattern search algorithm referring to the minimum relative error. Further, macro-scaled simulation was implemented to estimate bracket distortion behavior by applying the inherent strain tensors in ISM. For experiment, the conventional aileron bracket shape was first improved by complying the internal rules of GD throughout the desired design space with respect to stress goal and weight reduction based on iterative material distribution. After obtaining the new generatively designed component, linear static analysis was implemented to improve the stress magnitude and surface smoothness level by mesh and material sculpting. Then, the component is manufactured using laser powder bed fusion with manual postprocessing of support structure followed by sand blasting. The finished aileron bracket was then measured using a 3D scanner GOM Atos Q. As conclusion, this novel multi-scaled simulation method based on GD, static stress, and virtual calibration test allows a forecast of an acceptable surface deviation within relative single point and mean errors up to 11% and 5% respectively. By neglecting the tedious and time-consuming procedure of real calibration, a huge time reduction for preparation up to a few days and for computation up to 35% compared to pure TMM can be achieved. [ABSTRACT FROM AUTHOR]

Technology has revolutionized various industries; notably, chatbots impact healthcare through the efficient streamlining of medical procedures, cost reductions, and improved accessibility to healthcare services. Consequently, understanding how to promote the adoption of healthcare chatbots has become crucial for enhancing the healthcare industry and medical service quality. Despite numerous studies identifying factors influencing healthcare chatbot adoption, there is a notable lack of empirical verification regarding their interrelationships, leading to a significant knowledge gap. Therefore, this study aims to address this gap by developing a decision-making model to analyze the relationships among key factors regarding three dimensions: technology, user, and society. The model begins by filtering out insignificant factors based on experts' opinions. Subsequently, it employs DEMATEL (Decision Making Trial and Evaluation Laboratory) to construct a causal relationships graph and the ISM (interpretive structural modeling) method to categorize these factors into a hierarchical order. To mitigate uncertainties stemming from the topic's complexity, this study utilizes fuzzy sets and Z-number theory in the assessment process. The findings reveal a predominance of causal factors within the technological dimension. Notably, the quality of information provided by chatbots stands out as the most influential causal factor. The insights from this study suggest implications for both enterprises and governments to boost chatbot adoption in society. [ABSTRACT FROM AUTHOR]

In the era of digital economy, the digital innovation of manufacturing enterprises has become the main trend of development. This paper constructs an effective and reliable hierarchical framework for identifying critical factors of digital innovation in manufacturing enterprises based on the three stage hybrid DEMATEL–ISM–MICMAC method. Through literature reading and expert judgment, this paper determines the 19 factors that affect the digital innovation of manufacturing enterprises. The DEMATEL technique is used to establish the causal relationship between the factors, the ISM technique is used to stratify the factors, and the MICMAC technique is used to divide the types of influencing factors according to the driving force and dependence, and analyze the correlation between each level and its influence on the digital innovation of manufacturing enterprises. The results show that social capital, learning organization, digital technology, and knowledge are the most important influencing factors in the process of digital innovation in manufacturing enterprises. In particular, the two key factors of social capital and learning organization should be paid attention to by manufacturing enterprises. This research can help the managers of manufacturing enterprises to find out the key influencing factors of the digital innovation of manufacturing enterprises, and give targeted suggestions to promote the process of enterprise digitalization. [ABSTRACT FROM AUTHOR]

Sustainable supply chain management (SSCM) is a tactical concern for managers seeking a longterm result. Different managers are attempting to apply SSCM in order to get a competitive advantage. One of the critical processes is the identification of strategy implementation hurdles, which has been a research focus. As a result, this paper identifies these obstacles and analyzes their interrelationships. A list of obstacles was initially established by a survey of the literature and expert judgment in the form of the fuzzy Delphi approach. Next, an investigation was designed to collect expert opinions on the interrelationships between these obstacles. The fuzzy DEMATEL (FDEMATEL) approach was employed for examining the causal linkages and interdependencies of these obstacles. Subsequently, the interpretative structural modeling (ISM) technique was utilized to create a classified structure and to identify the driving and dependent connections. A fuzzy MICMAC analysis was applied for categorizing the obstacles based on driving and dependent power. The results reveal that barriers, "cost of implementation sustainability (B1)", "lack of financial resources (B2)", "institutional complexity (B3)", "complexity in measuring and monitoring sustainability practices (B4)", "lack of effective regulations (B5)", "lack of a proper evaluation system for suppliers (B6)", "lack of sustainability knowledge (B7)", and "strategic and structural restraints (B8)", are the influence-forwarding obstacles. These obstacles influence "inadequate government support (B9)", "high investments for sustainability and less return-oninvestments (B10)", "old equipment and machinery (B11)", and "lack of management commitment (B12)", which are the greatest influences on SSCM practices. Identifying the important obstacles and their interdependences can help policymakers in the manufacturing sector minimize or overcome them, boosting the possibilities of effectively incorporating sustainable principles into these projects. [ABSTRACT FROM AUTHOR]

We present the results of a spectral survey towards a dense molecular condensation and young stellar objects (YSOs) projected on the border of the H II region RCW 120 and discuss the emission of the 20 molecules that produce the brightest lines. The survey is performed with the APEX telescope in the 200–260 GHz frequency range. We provide evidences for two outflows in the dense gas. The first one is powered by the RCW 120 S2 YSO and oriented along the line of sight. The second outflow around RCW 120 S1 is aligned almost perpendicular to the line of sight. We show that the areas with bright emission of CH OH, CH CCH and CH CN are organised into an onion-like structure, where CH CN traces warmer regions around the YSOs than the other molecules. Methanol seems to be released into the gas phase by shock waves in the vicinity of the outflows while thermal evaporation still does not work towards the YSOs. We find only a single manifestation of the UV radiation in the molecules, namely, enhanced abundances of small hydrocarbons CCH and c-C H in the photo-dissociation region. [ABSTRACT FROM AUTHOR]

Strategic decision-making is often complex and uncertain, especially in turbulent environments. A large number of frequently conflicting indicators, rapid and unpredictable environmental changes, and the long-term consequences of making a decision have revealed the need for managers to use more efficient tools. Today, for tomorrow, conventional tools such as Quantitative Strategic Planning Matrix (QSPM) and MADM help us make the best decision based on yesterday's information. In some scenario planning approaches, the number of scenarios is so few that it cannot represent future uncertainty. In MADM methods, the problem of calculation complexity arises due to the increase in the number of elements. To address these issues, this research proposed an alternative approach for choosing the best strategy in which the alternative strategies are defined by SWOT analysis, future scenarios are determined by applying a matrix approach, irrational scenarios are eliminated by using interpretive structural modelling, and strategies are assessed by implementing Robustness Analysis (RA). The proposed method involves a case study related to a distributing centre for a food and beverage company located west of Mazandaran province, Iran. Nine alternative strategies' performances were evaluated in twenty-two scenarios based on six significant indicators shaping the future environment, and the best strategy was selected. Finally, some directions for future studies were presented. This study provides managerial implications by showing that despite the classic strategy selection approach being appropriate for austere environments and the MADM models being reasonable for complex environments, RA produces more reliable results when dealing with turbulent environments. [ABSTRACT FROM AUTHOR]

The ongoing pandemic coronavirus (COVID-19) outbreak has resulted a greater burden and loss to farmers in India in view of number of restrictions on movement as well as social interactions, during which scenario the "artificial intelligence (AI)" could act as a catalyst in accelerating their progress in agriculture. This paper provided an evaluation of application and benefits of AI in agriculture and the challenging parameters for implementing AI in Indian agricultural sectors against COVID-19 crisis period. A survey based data was collected from 523 farmers, and interpreted using Interpretive Structural Modelling (ISM) and MICMAC. The associated challenging parameters to implement AI were identified as "responsive time and accuracy levels; the absence of standardisation; a need for huge data; big data costs; method of implementation; versatility; insufficient awareness of context; and loss of employment;" respectively. [ABSTRACT FROM AUTHOR]

To solve the problem of complex and difficult to quantify factors affecting investment returns and risks in clean energy power grids, this study comprehensively applies the interpretive structural model and Monte Carlo model to the analysis of investment risk-returns in clean energy power grid projects. The interpretive structural model is utilized to analyze project investment returns, while the Monte Carlo model is used to analyze project investment risks. The project investment risk is based on the factor analysis of project investment returns, and key risk factors are identified through 1000 simulations, and the impact of these risks on project returns is quantified. By combining the two, the investability of the project is analyzed. The results showed that grid electricity prices, kilowatt hour subsidies, technology learning rates, total annual sunshine hours, and system power generation efficiency were key factors driving investment returns. The average expected value of investment return was about 20%, and the probability of investment return below 6% was close to 0. The overall project is worth investing in. From this, it can be seen that the research designed investment risk-return analysis methods for clean energy grid projects can effectively distinguish the main factors affecting investment returns and risks, and pre simulate the risk situation of returns. This study can provide reference for investor decision-making.

Global environmental concerns are leading to paradigm shift in the automobile eco-system. This comprehensive study of the automobile ecosystem, incorporates technical, economic, and environmental-social-governance (ESG) dimensions. An “integrated multi-criteria decision-making” (MCDM) methodology using “interpretive structural modelling” (ISM) and “fuzzy analytical hierarchy process” (FAHP) is deployed, The ISM models highlights prominent drivers and critical barriers, establishes their hierarchy, and depicts interrelationships. The FAHP rankings for drivers favours electric vehicles and hydrogen fuel vehicles over others, while barriers promote hybrids and alternate fuels like Biofuel, CNG/LNG. Unlike previous works, this study considers all eco-system factors, both critical drivers and barriers, and demonstrates hierarchy using a unique V-model. This is an innovative extension of V-model from traditional systems engineering to strategic project management domain. This holistic approach, in sync with the natural state of things, will enable government, industry, and academia in formulating a strategic framework towards future automobile sustainability.