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In recent years, Yoga practice has seen a rapid rise in popularity with many positive consequences, both physical and mental attributed to its practice. Ashtanga Yoga has been less well researched in this area and is the specific focus on this work. The aim of this study is to investigate the possible positive impact of long-term Ashtanga Yoga on psychological well-being.

In total, 213 long-term Ashtanga Yoga practitioners were asked to complete the positive emotion, engagement, relationships, meaning, accomplishment (PERMA) 23 scale (Butler and Kern, 2016) which measures psychological well-being. The values given by these individuals were then compared against a larger sample of 31,966 representative of the general population.

Scores were then compared with a PERMA data set representative of the general population (see Butler and Kern, 2016), primarily using a test of difference to compare samples. Secondly, the causal relationship between time spent in practice upon well-being scores.

Findings indicated that those individuals engaged in long-term Ashtanga Yoga practice significantly outperformed the control group on all dimensions of psychological well-being.

This work has demonstrated specific benefits to the practice of Ashtanga Yoga on psychological well-being. Yoga is a form of exercise that is now widely available across the globe, and as such, represents an accessible form of physical practice, which has important psychological benefits.

To the authors’ knowledge, this is the first work investigating differences in psychological well-being profiles using PERMA, as a function of Yoga practice.

Despite the importance of top management team (TMT) gender diversity in a firm's strategic decisions and the high degree of innovation activities that several firms have experienced in recent years, little or no research has examined how TMT gender diversity affects a firm's open innovation decision. The authors examine how TMT gender diversity impacts firms' open innovation activities. The authors further examine how this impact is affected by women executives' personal attributes and institutional conditions.

The sample comprised of 62,745 firm-year observations (9,831 firms) from 25 countries from 1990 to 2010. The authors employed the system generalized method of moments (GMM) estimation technique to estimate the results.

Employing novel panel data on co-owned patents across 25 economies, the authors find that proportion of women in TMTs has a positive impact on open innovation activities. Moreover, the authors find that women managers' power and institutional gender parity strengthen the association between gender diversity and open innovation.

The findings of this study indicate that firms committed to optimizing their open innovation policies and practices should include women in TMTs and create such conditions that are supportive for women executives to effectively express their innate inclinations. Importantly, our study supports the business case for gender diversity in top leadership positions by providing a compelling evidence for the positive impact of TMT gender diversity on open innovation.

This study contributes to the gender diversity literature by showing how women leaders' values and character become embedded in their companies' strategy and present empirical evidence that having women in TMTs increase the likelihood of conducting open innovation. Further, the authors show how women executives' power and institutional level gender parity provide boundary conditions that moderate the relationship between TMT gender diversity and open innovation.

The research focused on analysing a unique type of heat exchanger that uses swirling air flow over heated tubes. This heat exchanger includes a round baffle plate with holes and opposite-oriented trapezoidal air deflectors attached at different angles. The deflectors are spaced at various distances, and the tubes are arranged in a circular pattern while maintaining a constant heat flux.

This setup is housed inside a circular duct with airflow in the longitudinal direction. The study examined the impact of different inclination angles and pitch ratios on the performance of the heat exchanger within a specific range of Reynolds numbers.

The findings revealed that the angle of inclination significantly affected the flow velocity, with higher angles resulting in increased velocity. The heat transfer performance was best at lower inclination angles and pitch ratios. Flow resistance decreased with increasing angle of inclination and pitch ratio.

The average thermal enhancement factor decreased with higher inclination angles, with the maximum value observed as 0.94 at a pitch ratio of 1 at an angle of 30°.

This paper discussed quantifying architect, engineer and contractor (AEC) professionals' cross-work culture productivity by comparing between Malaysian and United Kingdom (UK) projects during industrialized building project delivery. This study addressed the second part of a mixed method research design study.

This study hypothesized that with understanding of cultural work knowledge between professionals during design phase coupled with competent technological support, productivity can be improved. It utilized Cognitive Organizational Theory (COT) protocols to test conceptual models in SimVision®. Organizational structure, project intensity, and statistical validations parameters were performed to obtain the reliability and generalization of the result.

This study found that with Building Information Modeling (BIM) technology intervention, the handling of exception, coordination and decision-making time could be improved, resulting in better project performances. The result also indicated that in choosing organizational fit, national culture factor needed to be considered; otherwise, organizational change would be unacceptable. By changing the operational process from intensive to reciprocal task intensity with BIM technology intervention, the effect on productivity would be similar to changing hierarchical organizational structure to flatter organizational structure.

Project discrepancies issues are limitedly discussed due to companies' confidentiality. The paper only focuses on understanding the effects of human factors during the integrated project delivery phase.

The findings could support developing countries' professionals to collaborate effectively with developed countries' professionals.

The development of the project's cultural knowledge experimentations will provide guidance to teams involved in international projects from developed and developing countries in pursuing joint ventures in project deliveries in either country successfully.

Consumer goods firms often tie up inventory and accounts receivable resources, creating cost and liquidity issues. Dynamic working capital management (DWCM) can mitigate these concerns and enhance operational profitability. The study investigates DWCM's impact on operational efficiency (OE).

The empirical estimation uses pooled ordinary least squares (OLS), random effect and system generalized method moments (GMM) regression analysis of consumer goods firms in Scandinavia from 2005 to 2022 to present the results.

The findings indicate that DWCM has an inverse relationship with operating cost, while positively impacting operating profit. The final outcome demonstrates that DWCM enhances OE. Furthermore, the working capital ratio (WCR) consistently exceeds the cash conversion cycle (CCC) in all models, indicating that prudent management of cash in accounts receivable, inventory and accounts payable leads to higher cost savings and superior performance.

The results suggest that organizations that prioritize the management of the absolute cash committed to inventory, receivables and payables as much as the CCC experience improved OE.

This paper adds to the literature on how DWCM affects OE in the consumer goods sector. It also highlights the impact of time management and cash management in WCM on OE. Additionally, it analyzes how DWCM variables affect operating costs and profits, shedding light on their efficiency impact.

The ionization of the air surrounding the phase conductor in high-voltage transmission lines results in a phenomenon known as the Corona effect. To avoid this, Corona rings are used to dampen the electric field imposed on the insulator. The purpose of this study is to present a fast and intelligent surrogate model for determination of the electric field imposed on the surface of a 120 kV composite insulator, in presence of the Corona ring.

Usually, the structural design parameters of the Corona ring are selected through an optimization procedure combined with some numerical simulations such as finite element method (FEM). These methods are slow and computationally expensive and thus, extremely reducing the speed of optimization problems. In this paper, a novel surrogate model was proposed that could calculate the maximum electric field imposed on a ceramic insulator in a 120 kV line. The surrogate model was created based on the different scenarios of height, radius and inner radius of the Corona ring, as the inputs of the model, while the maximum electric field on the body of the insulator was considered as the output.

The proposed model was based on artificial intelligence techniques that have high accuracy and low computational time. Three methods were used here to develop the AI-based surrogate model, namely, Cascade forward neural network (CFNN), support vector regression and K-nearest neighbors regression. The results indicated that the CFNN has the highest accuracy among these methods with 99.81% R-squared and only 0.045468 root mean squared error while the testing time is less than 10 ms.

To the best of the authors’ knowledge, for the first time, a surrogate method is proposed for the prediction of the maximum electric field imposed on the high voltage insulators in the presence Corona ring which is faster than any conventional finite element method.

This study aims to integrate the theory of planned behavior (TPB) and the value-belief-norm (VBN) theory into a meta-analytic framework to synthesize green consumption literature.

By integrating the findings from 173 studies, a meta-analysis was performed adopting several analytical methods: bivariate analysis, moderation analysis and path analysis.

VBN- and TPB-based psychological factors (adverse consequences, ascribed responsibility, personal norms, subjective norms, attitude and perceived behavioral control) mediate the effects of altruistic, biospheric and egoistic values on green purchase intention. Further, inconsistencies in the proposed relationships are due to cultural factors (i.e. individualism-collectivism, power distance, uncertainty avoidance, masculinity–femininity, short- vs long-term orientation and indulgence-restraint) and countries’ human development status.

The authors selected papers published in English; hence, other relevant papers in this domain published in other languages might have been missed.

The findings are useful to marketers of green offerings in designing strategies, i.e. specific messages, targeting different customers based on countries’ cultural score and human development index, to harvest positive customer responses.

This study is the pioneering attempt to synthesize the TPB- and VBN-based quantitative literature on green consumer behavior to resolve the reported inconsistent findings.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

In this study, the central objective is to foresee stock market signals with the use of a proper structure to achieve the highest accuracy possible. For this purpose, three hybrid models have been developed for the stock markets which are a combination of support vector machine (SVM) with meta-heuristic algorithms of particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).All the analyses are technical and are based on the Japanese candlestick model.

Further as per the results achieved, the most suitable algorithm is chosen to anticipate sell and buy signals. Moreover, the authors have compared the results of the designed model validations in this study with basic models in three articles conducted in the past years. Therefore, SVM is examined by PSO. It is used as a classification agent to search the problem-solving space precisely and at a faster pace. With regards to the second model, SVM and ICA are tested to stock market timing, in a way that ICA is used as an optimization agent for the SVM parameters. At last, in the third model, SVM and GA are studied, where GA acts as an optimizer and feature selection agent.

As per the results, it is observed that all new models can predict accurately for only 6 days; however, in comparison with the confusion matrix results, it is observed that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.

In this study, the data for stock market of the years 2013–2021 were analyzed; the long length of timeframe makes the input data analysis challenging as they must be moderated with respect to the conditions where they have been changed.

In this study, two methods have been developed in a candlestick model; they are raw-based and signal-based approaches in which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

The suction pipes are important in agriculture and are used widely in water management and agricultural–mechanical industry in ASEAN. Thus, this paper aims to present design of new impeller in suction pipe and include shape blade impeller to optimize for suction head, which has been higher than efficiency local-type by the performance. It mostly depends on the hydrodynamic characteristics, e.g. lift, drag and ratio, which is known as the “Thai Phaya-Nakh pipe”.

By approach NACA methodology and use applied technique: leading edge of blade, skew-line, cambered-line, developed area and advanced number etc., for analyzing data which the result of CFD simulation.

The models were tested in field by using motor at rotation speed 1500 rpm and found that the summarized average suction efficiency of the new impeller was estimated to be 72%, which has been greater than that of the local-type impeller with an average suction efficiency of 28% to 2.6 times. In addition, the amount of required electrical energy was reduced by 18%.

Then after analyzing the data from the static pressure distribution flow rate of impeller models, it is found that the new curved impeller has higher flow rate than the local type impeller. Thus, this study suggests the shape new impeller has higher flow rate than the local type impeller.