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This paper aims to solve the problems of large hard switching loss and unclear resonant parameter design in the existing inverter power supply topology.

This paper proposes a simple and reliable two-stage isolated inverter composed of series quasi-resonant push-pull and external freewheeling diode full-bridge inverter. The power supply topology is analyzed, the topology mode is analyzed, the mathematical model of the converter is established and the DC gain of the converter is deduced. The relationship between the load and the output gain of the resonant tank is presented, a new resonant parameter design method is proposed, and the parameter design of the resonant element of the converter is clarified.

The resonant components of the converter are designed according to the proposed resonant parameter design method, and the correctness of the method is verified by simulation and the development and testing of a 500 W experimental prototype. After experimental tests, the peak efficiency of the experimental prototype can reach 94%. Because the experimental prototype achieves soft switching, the heat generation of the switch is greatly reduced, so the heavy heat sink is removed, and the volume is reduced by about 30% compared with the traditional power supply, and the total harmonic distortion of the output voltage is about 2%.

The feasibility of the scheme is verified by experiments, which is of great significance for improving the efficiency of the inverter power supply and parameter optimization.

The growth of the Indian economy is accompanied by the rising trend of energy utilisation and its devastating effect on the environment. It is vital to understand the nexus between energy utilisation, climate and environment degradation and growth to devise a constructive policy framework for achieving the goal of sustainable growth. This study aims to analyse the long- and short-run association and direction of association between energy utilisation, carbon emission and growth of the Indian economy in the presence of structural break.

The study probes the association and direction of association between variables at both aggregate (total energy utilisation, total carbon emission and gross domestic product [GDP]) and disaggregates level (coal utilisation and coal emission, oil utilisation and oil emission, natural gas utilisation and natural gas emission along with GDP) over the time period of 50 years, i.e. 1971–2020. Autoregressive distributed lag model is used to examine the association between the variables and presence of structural break is confirmed with the help of Zivot–Andrews unit root test. To check the direction of association, vector error correction model Granger causality is performed.

Aggregate carbon emissions are affected positively by aggregate energy consumption and GDP in both short and long run. Bidirectional causality exists between total emissions and GDP, whereas a unidirectional causality runs from energy consumption towards carbon emission and GDP in the long run. At disaggregate level, consumption of coal energy impacts positively, whereas GDP influences coal emission negatively in the long run only. Furthermore, consumption of oil and GDP influences oil emissions positively in the long run. Lastly, natural gas is the energy source that has the fewest emissions in both short and long run.

There is a rapidly growing body of research on the connections and cause-and-effect relationships between energy use, economic growth and carbon emissions, but it has not conclusively proved how important the presence of structural breaks or changes within the economy is in shaping the outcomes of the aforementioned variables, especially when focusing on the Indian economy. By including the impact of structural break on the association between energy use, carbon emission and growth, where energy use and carbon emission are evaluated at both aggregate and disaggregate level, the current study aims to fill this gap in Indian literature.

This paper aims to investigate the diners’ preference and perception on six acoustic classifications in eatery places during their casual dining. These classifications’ relationship with diners’ experience and significant impacts on diners’ preferences and perceptions during casual dining will be analyzed.

The data was collected quantitatively with randomly distributed self-administrated questionnaires during the restaurants' operating hours; 449 respondents who dined in at two casual dining restaurants in Melaka city area participated.

Analysis of Variance (ANOVA) tests revealed that the majority of the diners were not adversely affected by the noise level, and they did not have difficulties with their conversations. The results also indicated that the respondents felt that the noise did not stop them from returning to the restaurants. This study's findings may lay the groundwork for future studies to provide the acoustic comfort classification in eatery places, which can also be integrated and synthesized to be used as a reference for acoustic design and practice.

The number of participants used simple random sampling method. Therefore, the sample cannot be typical for the target population, and there is a limited possibility of generalizing the present findings. The data collection was only gathered from two eatery places with similar typologies at the similar demographic background of customers because it was collected at Melaka city. Thus, the impacts of customers may differ at other typologies and locate in different regions, and the physical environment and the quality offered are also different in other places. The measured determinant factors only focus on the diners’ characteristics; thus, future research should be done to investigate other determinant factors impacting the preference and perceived acoustical comfort in eatery places.

The findings in this study would provide a basis reference to assess and evaluate the acoustic classification in eatery places that suits the customers’ perceived satisfaction.

This study identified that demographic characteristic, gender and age are not the prominent determinant factors influencing the diners’ preference and perceived acoustical comfort in eatery places. Moreover, the days and dining hours were also found to be the determinants that will influence the preferences.

This paper has developed determining factors on acoustics classification that can be applied upon designing eatery places as well as a fundamental approach in developing rating for acoustics comfort index as reference for the diners to choose where to dine based on their preference and activities.

The purpose of this review paper is to address the substantial challenges of the outdated exoskeletons used for rehabilitation and further study the current advancements in this field. The shortcomings and technological developments in sensing the input signals to enable the desired motions, actuation, control and training methods are explained for further improvements in exoskeleton research.

Search platforms such as Web of Science, IEEE, Scopus and PubMed were used to collect the literature. The total number of recent articles referred to in this review paper with relevant keywords is filtered to 143.

Exoskeletons are getting smarter often with the integration of various modern tools to enhance the effectiveness of rehabilitation. The recent applications of bio signal sensing for rehabilitation to perform user-desired actions promote the development of independent exoskeleton systems. The modern concepts of artificial intelligence and machine learning enable the implementation of brain–computer interfacing (BCI) and hybrid BCIs in exoskeletons. Likewise, novel actuation techniques are necessary to overcome the significant challenges seen in conventional exoskeletons, such as the high-power requirements, poor back drivability, bulkiness and low energy efficiency. Implementation of suitable controller algorithms facilitates the instantaneous correction of actuation signals for all joints to obtain the desired motion. Furthermore, applying the traditional rehabilitation training methods is monotonous and exhausting for the user and the trainer. The incorporation of games, virtual reality (VR) and augmented reality (AR) technologies in exoskeletons has made rehabilitation training far more effective in recent times. The combination of electroencephalogram and electromyography-based hybrid BCI is desirable for signal sensing and controlling the exoskeletons based on user intentions. The challenges faced with actuation can be resolved by developing advanced power sources with minimal size and weight, easy portability, lower cost and good energy storage capacity. Implementation of novel smart materials enables a colossal scope for actuation in future exoskeleton developments. Improved versions of sliding mode control reported in the literature are suitable for robust control of nonlinear exoskeleton models. Optimizing the controller parameters with the help of evolutionary algorithms is also an effective method for exoskeleton control. The experiments using VR/AR and games for rehabilitation training yielded promising results as the performance of patients improved substantially.

Robotic exoskeleton-based rehabilitation will help to reduce the fatigue of physiotherapists. Repeated and intention-based exercise will improve the recovery of the affected part at a faster pace. Improved rehabilitation training methods like VR/AR-based technologies help in motivating the subject.

The paper describes the recent methods for signal sensing, actuation, control and rehabilitation training approaches used in developing exoskeletons. All these areas are key elements in an exoskeleton where the review papers are published very limitedly. Therefore, this paper will stand as a guide for the researchers working in this domain.

This study aims to offer a bibliometric analysis of the already substantial and growing literature on global virtual teams (GVTs).

Using a systematic literature review approach, it identifies all articles in the Web of Science from 1999 to 2021 that include the term GVTs (in the title, the abstract or keywords) and finds 175 articles. The VOSviewer software was applied to analyze the bibliometric data.

The analysis revealed three dialogizing research clusters in the GVTs literature: a pioneering management information systems and organizational cluster, a general management cluster and a growing international management and behavioural studies cluster. Furthermore, it highlights the most cited articles, authors, journals and nations, and the network of strong and weak links regarding co-authorships and co-citations. Additionally, this study shows a change in research patterns regarding topics, journals and disciplinary approaches from 1999 to 2021. Finally, the analysis illustrates the position and centrality in the network of the most relevant actors.

The findings can guide management practitioners, educators and researchers to the most meaningful clusters of publications on GVTs, and help navigate and make sense of the vast body of the available literature. The importance of GVTs has been growing in the past two decades, and Covid-19 has accelerated the trend.

This study provides an updated and comprehensive systematic literature review on GVTs. To the best of the authors’ knowledge, it is also the first systematic literature review and bibliometry on GVTs. It concludes by suggesting future research paths.

This paper aims to focus on the contribution of segregated renewable energy (RE) sources such as solar, wind, bagasse, biomass, small hydropower (SHP) and waste to heat in driving sustainable industrial production in India.

This study uses non-linear modelling techniques such as quantile regression and the non-linear Granger causality test to explore the interplay between segregated RE generation and industrial production in India.

The study findings support the role of segregated RE sources generation, especially SHP and bagasse, on industrial production in India. This paper finds unidirectional non-linear Granger causality running from segregated RE sources to industrial production. Bidirectional non-linear Granger causality has been established from biomass, waste-heat to index of industrial production and vice versa, supporting an asymmetric feedback hypothesis.

The study findings will aid the energy policymaker in framing policies for RE sources, especially bagasse-based and SHP generation for the sustainable industrial growth of India.

To the best of the authors’ knowledge, this is one of the first studies to explore the role of segregated RE sources generation to drive sustainable industrial growth in India using non-linear techniques.

Despite numerous studies, our understanding of the determinants of disability insurance (DI) claim rates in the USA is clouded. When the unemployment (UE) rate soars during an economic downturn such as the spread of COVID-19, assuming a linear positive relationship between the two variables, as the prior literature has suggested, forewarns a large spike in DI claim rates. Yet, if the model is misspecified, it can lead to misinformed decisions such as reducing DI awards during an economic downturn when such awards are needed the most. This study aims to improve the accuracy of the DI claims' prediction.

This study suggests that the relationship between the UE rate and DI claim rate is nonlinear and examines this hypothesis using a panel dataset of 866 state-year observations from 2002–2018.

The results provided compelling evidence in support of the proposed quadratic relationship between the UE rate and DI claim rate and revealed that compared to a quadratic model, the linear model overestimated the DI claim rate by approximately 18 percent or 172,000 claims per year.

Given that DI awards represent hundreds of thousands of dollars in present value terms, the impact of increase in DI claims on the Social Security Disability Fund during an economic downturn might not be as high as some model might forecast.

To our knowledge, no other studies have examined a quadratic relationship between the UE rate and the DI claim rate. This study is especially relevant during the coronavirus (COVID-19) pandemic and its aftermath. In April 2020, the UE rate spiked to nearly 15 percent nationwide, with Nevada and Michigan at 28 percent and 22.7 percent, respectively. The nonlinear model used in this study suggests that, as the UE increases, DI claims increase, albeit at a decreasing rate. On the contrary, a linear relationship between the UE rate and DI claim rates implies that the increase in the DI claim rate would be constant regardless of the UE rate. This misspecification can result in misinformed decisions, such as the reduction of DI awards because of the overestimation of claims during economic downturns. This can lead to lower award rates during economic turmoil when this assistance is most needed.

This research examined the impacts of diversified income from trading caterpillar fungus on pastoral households' livestock production and income. The specific objectives were to identify the main factors underlying participation in caterpillar fungus trade and to explore the impacts of a diversified income from trading fungus on livestock production activities and income.

Data were collected from a pastoral household survey (n = 503) in five Tibetan Autonomous Prefectures. The authors employed propensity score matching (PSM) procedures to estimate the effects of participation in trading caterpillar fungus.

Pastoral households participating in caterpillar fungus activities maintain smaller herds, sell fewer animals for profit, slaughter more livestock for family consumption and experience fewer livestock deaths compared to nonparticipants. There is also some evidence that pastoral households participating in caterpillar fungus activities have a higher annual income compared to nonparticipants.

A direct measure of grassland degradation was not included due to the data limitation. The estimated average treatment effects could differ under different observed households' characteristics.

This study fills a gap in the literature on the impacts of diversified income on livestock production activities. The authors provide a new perspective on the controversy over the extraction of caterpillar fungus. This study contributes to exploring the dual role of income diversification in addressing poverty and grassland resource degradation for Tibetan pastoral communities.

This study aims to propose a series of numerical and surrogate models to investigate the aerodynamic pressure inside cracks in high-speed railway tunnel linings and to predict the stress intensity factors (SIFs) at the crack tip.

A computational fluid dynamics (CFD) model is used to calculate the aerodynamic pressure exerted on two cracked surfaces. The simulation uses the viscous unsteady κ-ε turbulence model. Using this CFD model, the spatial and temporal distribution of aerodynamic pressure inside longitudinal, oblique and circumferential cracks are analyzed. The mechanism behind the pressure variation in tunnel lining cracks is revealed by the air density field. Furthermore, a response surface model (RSM) is proposed to predict the maximum SIF at the crack tip of circumferential cracks and analyze its influential parameters.

The initial compression wave amplifies and oscillates in cracks in tunnel linings, resulting from an increase in air density at the crack front. The maximum pressure in the circumferential crack is 2.27 and 1.76 times higher than that in the longitudinal and oblique cracks, respectively. The RSM accurately predicts the SIF at the crack tip of circumferential cracks. The SIF at the crack tip is most affected by variations in train velocities, followed by the depth and length of the cracks.

The mechanism behind the variation of aerodynamic pressure in tunnel lining cracks is revealed. In addition, a reliable surrogate model is proposed to predict the mechanical response of the crack tip under aerodynamic pressures.

Intumescent coatings are nowadays a dominant passive system used to protect structural materials in case of fire. Due to their reactive swelling behaviour, intumescent coatings are particularly complex materials to be modelled and predicted, which can be extremely useful especially for performance-based fire safety designs. In addition, many parameters influence their performance, and this challenges the definition and quantification of their material properties. Several approaches and models of various complexities are proposed in the literature, and they are reviewed and analysed in a critical literature review.

Analytical, finite-difference and finite-element methods for modelling intumescent coatings are compared, followed by the definition and quantification of the main physical, thermal, and optical properties of intumescent coatings: swelled thickness, thermal conductivity and resistance, density, specific heat capacity, and emissivity/absorptivity.

The study highlights the scarce consideration of key influencing factors on the material properties, and the tendency to simplify the problem into effective thermo-physical properties, such as effective thermal conductivity. As a conclusion, the literature review underlines the lack of homogenisation of modelling approaches and material properties, as well as the need for a universal modelling method that can generally simulate the performance of intumescent coatings, combine the large amount of published experimental data, and reliably produce fire-safe performance-based designs.

Due to their limited applicability, high complexity and little comparability, the presented literature review does not focus on analysing and comparing different multi-component models, constituted of many model-specific input parameters. On the contrary, the presented literature review compares various approaches, models and thermo-physical properties which primarily focusses on solving the heat transfer problem through swelling intumescent systems.

The presented literature review analyses and discusses the various modelling approaches to describe and predict the behaviour of swelling intumescent coatings as fire protection for structural materials. Due to the vast variety of available commercial products and potential testing conditions, these data are rarely compared and combined to achieve an overall understanding on the response of intumescent coatings as fire protection measure. The study highlights the lack of information and homogenisation of various modelling approaches, and it underlines the research needs about several aspects related to the intumescent coating behaviour modelling, also providing some useful suggestions for future studies.