This article addresses the pressing issue of training and mediation for conflict resolution among employees within a corporate setting. Employing a methodology that includes literature analysis, comparative studies, and surveys, we explore various strategies and their effectiveness in mitigating workplace conflicts. Through a comprehensive comparison with metrics and conclusions from other scholarly works, we provide a nuanced understanding of the current landscape of conflict resolution practices. As a result of our research, we implemented a tailored training program focused on conflict resolution for employees within a mobile company, alongside the development of a competency framework designed to enhance conflict resolution skills. This framework comprises five integral components: emotional, operational, motivational, behavioral, and regulatory. Our findings suggest that training in each of these competencies is essential for fostering a healthy workplace environment and must be integrated into organizational practices. The importance of this initiative cannot be overstated; effective conflict resolution skills are not only vital for individual employee wellbeing but also crucial for the overall efficiency and productivity of the organization. By investing in these competencies, companies can reduce turnover, enhance team cohesion, and create a more positive and collaborative workplace culture.

Families are the central nucleus of society; however, they face internal challenges that affect their functioning and stability, often manifesting in incidents of domestic and gender-based violence. The World Health Organization has classified this violence as a severe public health problem and a violation of human rights. To address this issue, the Congress of the Republic of Colombia enacted Law 2126 of 2021, introducing significant changes to the responsibilities of authorities in preventing, restoring, protecting, and repairing the rights of victims. This law provided a three-year implementation period for territorial entities, which concluded on 4 August 2023. In 2023, 119,483 cases were reported, and by June 2024, the number had reached 63,528—the highest recorded to date. This situation continued to escalate uncontrollably throughout 2024, overwhelming functional capacity and resulting in a crisis. Therefore, the objective of this study is to analyze the guarantee of rights for victims of violence in the family context, within the competencies of Family Commissariats, as outlined in Law 2126 of 2021. The methodology focuses on analyzing academic and scientific databases, including studies and articles published in indexed journals, to evaluate government measures and describe the challenges in service provision by Family Commissariats to propose conclusions. The approach is qualitative, with a hermeneutic, documentary, legal-dogmatic orientation and anthropological contributions. The results reveal that the law’s implementation has been gradual, surpassing the established deadline. Administrative, political, and financial factors identified over the three years remain unresolved in 2024. The situation for victims of physical, psychological, economic, and sexual violence within the family context has worsened due to multicausal obstacles to accessing justice in a timely, efficient, and effective manner. Consequently, there is evidence of an exponential increase in violence, underreporting, impunity, setbacks, procedural delays, normalization of violence, and re-victimization, among other issues.

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.

Recognizing the importance of competition analysis in telecommunications markets is essential to improve conditions for users and companies. Several indices in the literature assess competition in these markets, mainly through company concentration. Artificial Intelligence (AI) emerges as an effective solution to process large volumes of data and manually detect patterns that are difficult to identify. This article presents an AI model based on the LINDA indicator to predict whether oligopolies exist. The objective is to offer a valuable tool for analysts and professionals in the sector. The model uses the traffic produced, the reported revenues, and the number of users as input variables. As output parameters of the model, the LINDA index is obtained according to the information reported by the operators, the prediction using Long-Short Term Memory (LSTM) for the input variables, and finally, the prediction of the LINDA index according to the prediction obtained by the LSTM model. The obtained Mean Absolute Percentage Error (MAPE) levels indicate that the proposed strategy can be an effective tool for forecasting the dynamic fluctuations of the communications market.

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.