Street lighting has a big impact on the energy consumption of Spanish municipalities. To decrease this consumption, the Spanish government has developed two different regulations to improve energy savings and efficiency, and consequently, reduce greenhouse-effect gas emissions. However, after these efforts, they have not obtained the expected results. To improve the effectiveness of these regulations and therefore to optimize energy consumption, a study has been done to analyze the different devices which influence energy consumption with the intention of better understanding their behavior and performance. The devices analyzed were lamps, ballasts, street lamp globes, control systems and dimmable lighting systems. To improve their performance, they have been analyzed from three points of view: changes in technology, use patterns and standards. Thanks to this study, some aspects have been found that could be taken into account if we really wanted to use energy efficiently.

This study presents the results of a meta-analysis on teaching methods used in software engineering (SE) courses. The results summarize the most common teaching methods and can be used by both educators and practitioners in better alignment of SE courses with industry-relevant knowledge, tools, and practices.

There are very few countries that have provisions addressing the energy efficiency of the whole street lighting system, such as Spain or the Netherlands. Nevertheless, there is not an agreement about how energy efficiency must be assessed. The Spanish Government contemplates it in the Royal Decree 1890/2008 with the goal of improving energy savings and efficiency. However, this has not obtained the expected results. Nowadays, energy efficiency of this kind of systems is assessed using a label. In the case of Spain, this label only assesses one magnitude. The contributions of this paper are two evaluation systems (kiviat diagram and pie chart) which assess five magnitudes: lamps, energy efficiency index, light pollution, renewable energy contribution, and harness of the luminous flux using dimming. After that, a survey was done to study several subjects: (1) if citizens are aware about the efficiency of street lighting systems, (2) whether the sample of colors used in the label is adequate, and (3) if our proposed systems could replace the current evaluation system. Finally, the paper finishes with the conclusions of the survey.

Energy consumption rose about 28% over the 2001 to 2011 period in the Spanish residential sector. In this environment, domestic hot water (DHW) represents the second highest energy demand. There are several methodologies to estimate DHW consumption, but each methodology uses different inputs and some of them are based on obsolete data. DHW energy consumption estimation is a key tool to plan modifications that could enhance this consumption and we decided to update the methodologies. We studied DHW consumption with data from 10 apartments in the same building during 18 months. As a result of the study, we updated one chosen methodology, adapting it to the current situation. One of the challenges to improve efficiency of DHW use is that most of people are not aware of how it is consumed in their homes. To help this information to reach consumers, we developed a website to allow users to estimate the final electrical energy needed for DHW. The site uses three estimation methodologies and chooses the best fit based on information given by the users. Finally, the application provides users with recommendations and tips to reduce their DHW consumption while still maintaining the desired comfort level.

The Dark Web hosts a variety of Q&A forums that facilitate discussions on topics ranging from technical guidance to illicit activities. This study investigates the linguistic and structural characteristics of three prominent Dark Web Q&A forum onion services—Onion1 (Deepweb Questions and Answers), Onion2 (Deep Answers), and Onion3 (Repostas Ocultas)—using a combination of topic modeling and quantitative text analysis. We employ Sklearn (TF-IDF) and Gensim (LDA) to extract and compare dominant topics, alongside metrics of lexical diversity, semantic diversity and syntactic complexity. Our findings reveal significant differences in topic diversity and linguistic patterns across the forums, with Onion1 exhibiting a focus on technical and financial discussions, Onion2 emphasizing community-driven and security-related topics, and Onion3 showing a narrower thematic scope influenced by its structured Q&A format and language-specific content. Statistical analyses, including Kruskal-Wallis tests and Dunn’s post-hoc comparisons, confirm these differences, highlighting the distinct communicative norms and user behaviors of each forum. The results underscore the importance of considering forum-specific characteristics when analyzing Dark Web communities and provide insights into the thematic and linguistic diversity of these platforms.