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.

This research aims to build an appropriate leadership model for regional heads in mitigating disasters due to climate change that is occurring in Papua. Papua Island is one of the islands that is included in disaster-prone areas, namely earthquakes, flash floods, tidal floods and landslides. This disaster occurred due to Papua’s geological conditions in the form of activity on the Indo-Australian plate (southern part) and the Pacific plate (north-eastern part). Exploitation of nature carried out by companies and communities themselves in a particular area has an impact on the balance of the natural ecosystem. So far, disaster management has only focused on emergency response. Aid movements coordinated by ordinary people also focus more on raising aid for emergency situations. In fact, comprehensive disaster management includes before, during and after a disaster occurs. So a combination of leadership styles is needed that must be carried out at each phase of a disaster so that the right model can be produced. The results of this research found that the leadership model of regional heads in mitigating climate change in Papua is in accordance with the disaster management cycle with leadership styles, and traditional Papuan leadership styles. This combination is called a collaborative leadership model for disaster management in Papua. It is hoped that by implementing this model, climate change disaster mitigation can be effective.

The Heating, Ventilation, Air Conditioning, and Refrigeration (HVAC&R) industry is pivotal to Europe’s goals for energy efficiency, sustainability, and technological advancement. As demand for skilled HVAC&R professionals rises, the effectiveness of educational programs in this field has become a focal point. This article explores the Portuguese case to analyze how pedagogical strategies and student motivation contribute to the quality of HVAC&R training across Europe. The study highlights innovative teaching methodologies such as active and competency-based learning, as well as the use of laboratory training and digital simulations to provide hands-on experience. Additionally, it emphasizes Bloom’s Taxonomy as a framework for curriculum development, ensuring that students advance from foundational knowledge to complex problem-solving abilities. Motivation is also identified as a critical factor for student engagement and long-term career commitment. The article concludes that a balanced integration of theoretical knowledge, practical skills, and motivational support is essential for producing highly qualified HVAC&R professionals. This approach not only meets current industry needs but also aligns with Europe’s broader environmental and technological objectives, offering valuable insights for educators, policymakers, and industry stakeholders.