This study explores the determinants of control loss in eating behaviors, employing decision tree regression analysis on a sample of 558 participants. Guided by Self-Determination Theory, the findings highlight amotivation (β = 0.48, p < 0.001) and external regulation (β = 0.36, p < 0.01) as primary predictors of control loss, with introjected regulation also playing a significant role (β = 0.24, p < 0.05). Consistent with Self-Determination Theory, the results emphasize the critical role of autonomous motivation and its deficits in shaping self-regulation. Physical characteristics, such as age and weight, exhibited limited predictive power (β = 0.12, p = 0.08). The decision tree model demonstrated reliability in explaining eating behavior patterns, achieving an R² value of 0.39, with a standard deviation of 0.11. These results underline the importance of addressing motivational deficits in designing interventions aimed at improving self-regulation and promoting healthier eating behaviors.

Education is one of the basic needs that every child should have. Information communication technology has a significant influence on special needs children’s schooling. Instead of considering learning a difficult chore, the adoption of measures such as ICT can simplify it and make inclusive education a reality. Aim: This current systematic literature review aims to determine the extent of ICT adoptions in special education scenarios. Method: This paper examined pertinent literature on ICT in special education in the period 2000 to 2023. The key articles extracted through keyword search were gathered from databases indexed in Web of Science and Scopus. The collected data were then screened using a VOS viewer for the most relevant information. From the web of Science, 31 articles were found to have connections with one another while the same process when applied to the Scopus database, helped obtain 8 articles. Results: A total of 39 articles fulfilled the search inclusion criteria of minimum two keyword occurrences. These articles were all written in English and published between 2000 and 2023. The in-depth analysis of all these articles was performed along three broad themes, viz., availability of SEN based ICTs and their impact on children with disabilities, quality of available ICT integrated curriculum for SEN and the challenges in promoting ICTs for inclusive education. Conclusions: The paper concludes that ICT integration in special education would make learning easier for children with disabilities when compared to learning using traditional methods. Implications: The paper pinpoints significant limitations in ICT use found in existing literature and the lack of it to support inclusive education. The authors make recommendations for improved ICT integrated curriculum to improve inclusivity.

This research aims to examine the influence of IHRMP, recruitment and selection, training, compensation, and performance appraisal on the productivity of Faculty Members (FM) productivity working in private universities in the UAE. The study also examines the mediating role of Organizational Commitment (OC) and the moderating role of the Entrepreneurial Mind-set (EM). The research adopted the social exchange theory. A survey was conducted comprising 160 FM. The data was analyzed using Structural Equation Modelling, Smart-PLS. The findings indicate a positive relationship between IHRMP and the productivity of the FM. The findings also show that OC mediates the relationship between IHRMP and the productivity of FM. Finally, an EM was found to moderate the relationship between IHRMP and the productivity of FM.

The health of employees is so paramount for employee productivity. While emphasis is often placed on the physical health of employees, less emphasis is placed on the psychological or mental health of the employees. Similarly, it seems as if health challenges are more occurring in manufacturing industries, but the service organizations employees are as well susceptible to mental health challenges. Understanding the predictive factors to mental health challenges therefore becomes imperative. It is on this note that the present research examines how employee mental health is predicted by work safety measures like perceived workplace safety, work overload and pay satisfaction. The workplace safety variables include perception of job, co-worker, supervisor, management, and safety programs. A cross sectional survey method was adopted, using ex-post-facto research design. Data were gathered from 258 employees, including 150 (58.1%) females and 108 (41.9%) males of a non-governmental organization. Correlation and regression analyses were used to analyze data obtained from the standardized psychological scales that were administered. The results showed that mental health correlated positively with perceived job safety, but negatively with perceived co-worker, supervisor, management, safety programs and pay satisfaction. Workplace safety variables jointly predicted mental health, accounting for 23% variance, but only perceived job safety and supervisor safety were significant. The higher employees perceived job safety, the lower their mental health challenges. Similarly, the higher they perceived supervisor safety, the lower their mental health issues. Pay satisfaction accounted for 3% variance in mental health, and the higher the pay satisfaction, the lower the level of employee mental health issues. It is implied that the human resource unit of service organizations should intermittently examine their organizations to identify and prevent possible job and supervisor safety threats. Supervisors should be trained on how to be discrete in communicating safety measures to subordinates so that it will not boomerang to hamper mental health. The human resources unit should also intermittently organize workshop, training, and employee-assisted programs for younger and lower grade employees on adaptive mechanisms for reducing mental health challenges.

Uncontrolled economic development often leads to land degradation, a decline in ecosystem services, and negative impacts on community welfare. This study employs water yield (WY) modeling as a method for environmental management, aiming to provide a comprehensive understanding of the relationship between Land Use Land Cover (LULC), Land Use Intensity (LUI), and WY to support sustainable natural resource management in the Cisadane Watershed, Indonesia. The objectives include: (1) analyzing changes in WY for 2010, 2015, and 2021; (2) predicting WY for 2030 and 2050 under two scenarios—Business as Usual (BAU) and Protected Forest Area (PFA); (3) assessing the impacts of LULC and climate change on WY; and (4) exploring the relationship between LUI and WY. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model calculates actual and predicted WY conditions, while the Coupling Coordination Degree (CCD) analyzes the LULC-WY relationship. Results indicate that the annual WY in 2021 was 215.8 × 108 m³, reflecting a 30.42% increase from 2010. Predictions show an increasing trend in WY under both scenarios for 2030 and 2050 with different magnitudes. Rainfall contributes 88.99% more dominantly to WY than LULC. Additionally, around 50% of districts exhibited unbalanced coordination between LUI and WY in 2010 and 2020. This study reveals the importance of ESs in sustainable watershed management amidst increasing demand for natural resources due to population growth.

The telecommunications services market faces essential challenges in an increasingly flexible and customer-adaptable environment. Research has highlighted that the monopolization of the spectrum by one operator reduces competition and negatively impacts users and the general dynamics of the sector. This article aims to present a proposal to predict the number of users, the level of traffic, and the operators’ income in the telecommunications market using artificial intelligence. Deep Learning (DL) is implemented through a Long-Short Term Memory (LSTM) as a prediction technique. The database used corresponds to the users, revenues, and traffic of 15 network operators obtained from the Communications Regulation Commission of the Republic of Colombia. The ability of LSTMs to handle temporal sequences, long-term dependencies, adaptability to changes, and complex data management makes them an excellent strategy for predicting and forecasting the telecom market. Various works involve LSTM and telecommunications. However, many questions remain in prediction. Various strategies can be proposed, and continued research should focus on providing cognitive engines to address further challenges. MATLAB is used for the design and subsequent implementation. The low Root Mean Squared Error (RMSE) values and the acceptable levels of Mean Absolute Percentage Error (MAPE), especially in an environment characterized by high variability in the number of users, support the conclusion that the implemented model exhibits excellent performance in terms of precision in the prediction process in both open-loop and closed-loop.