Recently, there has been a burgeoning fascination with the influence of urban green spaces (UGS) on physical activity (PA) and health. This interest has been accompanied by a mounting body of evidence that establishes a connection between UGS and residents’ PA levels. Numerous studies have been conducted to investigate the significance of UGS and have generally agreed on their connection with health. However, there is still considerable variation in viewpoints regarding the intermediate factors contributing to this association. The primary objective of this study was to investigate the potential correlation between different qualitative factors of UGS and PA. The study involved the collection of data from four parks located in Edinburgh. Four trained observers utilised the Environmental Assessment of Public Recreational Spaces (EARPS Mini) tool to code various environmental characteristics. Additionally, the Method for Observing Physical Activity and Wellbeing (MOHAWk) observation tool was employed to code instances of on-site incivility and the characteristics and behaviours of residents engaging in UGS activities. The results of this study show that the facilities and environment, area and socioeconomic status (SES) of UGS positively affect the type of PA and the level of PA, as well as influence residents’ attentiveness to the environment and their interactions with each other. Demographics such as gender and age group are also significantly related to the level and type of PA. Significant differences in the level and type of PA, and race only differed significantly in the choice of activity type. These results suggest that the quality of the UGS environment affects the level, type, and status of PA among residents and that resident characteristics also have an impact. Future research suggests increasing data collection related to PA frequency and PA duration and considering longitudinal observations over time for refinement.

In the highly competitive employment environment, most college students have left their jobs for a short time after employment, and attention should be paid to students’ career adaptation. However, the further influence of skilled goal orientation, social support and career-determined self-efficacy on college students’ career adaptation needs to be confirmed. This study analyzes the effects of these factors on college students’ career adaptation. This study aims to analyze the impact of mastery goal orientation, social support, and vocational decision self-efficacy on career adaptation among 224 university students in East China. The results indicated that university students generally exhibit positive levels of mastery goal orientation, social support, vocational decision self-efficacy, and overall career adaptation. Female students demonstrate higher levels of mastery goal orientation, social support, vocational decision self-efficacy, and career adaptation compared to male students. As students progress in their academic years, their levels of mastery goal orientation, social support, vocational decision self-efficacy, and career adaptation tend to increase. Students majoring in humanities and social sciences have higher level than students majoring in science and engineering in all factors. Students majoring in humanities and social sciences exhibit more optimism in all factors compared to students in science and technology fields. The relationships among these factors show positive correlations. Mastery goal orientation, social support, and vocational decision self-efficacy all have positive effects on career adaptation. Among these, family support stands out as the most influential subordinate factor of social support on career adaptation. The most influential subordinate factor of vocational decision self-efficacy on career adaptation is conscious decision-making. Therefore, male, lower grade, science and engineering college students are the groups that need to be paid attention to in improving career adaptation. Skilled goal orientation, family support and conscious decision making have a better effect on the improvement of career adaptation. These results can provide important reference information for universities, counselors and college students in the training of career planning, and theoretically enrich the relevant research on college students’ career adaptation, and provide certain enlightenment for future researchers.

Creating a crop type map is a dominant yet complicated model to produce. This study aims to determine the best model to identify the wheat crop in the Haridwar district, Uttarakhand, India, by presenting a novel approach using machine learning techniques for time series data derived from the Sentinel-2 satellite spanned from mid-November to April. The proposed methodology combines the Normalized Difference Vegetation Index (NDVI), satellite bands like red, green, blue, and NIR, feature extraction, and classification algorithms to capture crop growth's temporal dynamics effectively. Three models, Random Forest, Convolutional Neural Networks, and Support Vector Machine, were compared to obtain the start of season (SOS). It is validated and evaluated using the performance metrics. Further, Random Forest stood out as the best model statistically and spatially for phenology parameter extraction with the least RMSE value at 19 days. CNN and Random Forest models were used to classify wheat crops by combining SOS, blue, green, red, NIR bands, and NDVI. Random Forest produces a more accurate wheat map with an accuracy of 69% and 0.5 MeanIoU. It was observed that CNN is not able to distinguish between wheat and other crops. The result revealed that incorporating the Sentinel-2 satellite data bearing a high spatial and temporal resolution with supervised machine-learning models and crop phenology metrics can empower the crop type classification process.

This study examines the rapid convergence of the tourism industry with other sectors, driven by the expanding experience economy. A conceptual model was introduced encompassing industry convergence patterns, paths, and effects to assess this convergence’s effectiveness. Using a survey of 392 tourists in Macau, these findings reveal that the tourism industry convergence path and mode positively influence the convergence effect, thereby shaping tourists’ perceived value. Moreover, this study identifies that convergence mode and effect mediate the relationship between the tourism industry convergence path and perceived value. This study validates the efficacy of industrial convergence paths and models in fostering regional industry convergence within the tourism sector. Additionally, it contributes a theoretical framework for evaluating industry convergence effects at a micro level, enhancing both the theoretical understanding and practical applications of Macao’s tourism industry and industrial convergence theory.

Solar energy is a reliable and abundant resource for both heating and power generation. The current research examines how the novel class of nano-embedded Bees wax phase change materials (NEBPCMs) improves heat storage qualities. The synthetic NEBPCMs were subjected to experimental testing using, XRD, Bees wax and Al2O3 FESEM. A typical solar water heating system features a flat plate collector unit incorporating Bees Wax phase change material (NEBPCM) combined with varying concentrations of Al2O3 (0.01%, 0.015%, and 0.02%). The absorber plate surface is coated with a Nano-hybrid coating consisting of Black Paint, Al2O3, and additional Fe3O4 at a 2% concentration. Pure water is frequently used in these solar water heaters (SWH), with performance evaluations conducted using different Bees Wax and Al2O3 concentrations of NEBPCM (Bees Wax + Al2O3). The system’s efficiency is assessed across different flow rates (60, 90, and 120 kg/hr) and tilt angles (15, 30, and 45 degrees). This study aims to examine the feasibility of using PCMs to store solar energy for night time water heating, ensuring a continuous supply of hot water maximum efficiency achieved by using NEBPCM in solar water heater 52.26% at a flow rate of 120 Kg/hr, at angle of 45 degrees and Concentration 0.015%.

The present study investigates the relationship between audit quality and earnings management in banks listed on the Stock Exchange of Iraq and Oman. This paper used audit firm size, auditors’ industry expertise, audit report timeliness, auditor change, and auditors’ opinions to measure audit quality. Financial statements, notes attached to financial statements, and reports of independent auditors of 28 banks listed on the Iraqi Stock Exchange and 8 banks listed on the Oman Stock Exchange during the financial period of 7 years (2015 to 2021), and hypotheses were tested using EViews software and panel data. The results of the hypothesis testing showed no significant relationship between the firm size and the auditors’ change and earnings management for both countries (Iraq and Oman). This is while the relationship between the auditor’s industry expertise, the timely presentation of the audit report, and the auditor’s opinion and earnings management for both countries (Iraq and Oman) is negative.