The University of Málaga (UMA, Universidad de Málaga) is a public university ranked 23 among all Spanish universities and 683 in the world. It was established in 1972 and has, as of 2016, 30,203 Bachelor students and 2576 on a Master's program, 1255 tenured and 1056 temporary teachers. The UMA offers 65 degree courses and 6 double degrees, over 21 doctoral programmes, 64 master's Degrees, and 100 courses throughout the academic year. Education takes place in 18 centres by appointed teachers from 81 departments. The great majority of the teaching is organised within the two campuses, although classes also take place in locations spread around the city centre, as well as in Ronda and Antequera.
This study analyses visitor experience in Palaeolithic rock art caves through sentiment analysis applied to online reviews. A total of 4,709 opinions posted between 2017 and 2025 on Google Reviews are examined for four caves open to the public: El Castillo and Tito Bustillo (Spain), and Font-de-Gaume and Rouffignac (France), all of which are inscribed on the UNESCO World Heritage List. Using text mining techniques and lexical co-occurrence analysis, the main semantic and emotional axes structuring visitors' discourse are identified. The results show that the tourist experience is shaped by cultural mediation, the symbolic construction of rock art, and predominantly positive emotional evaluations associated with the exceptional nature of the resource. Organisational aspects appear as peripheral dimensions, suggesting a degree of social acceptance of conservation-related restrictions.
Generative search shifts information evaluation from comparing ranked documents to assessing synthesised answers. This study examines how users' perceptions of answer quality are associated with trust and credibility in Google AI Overviews and explores whether visible interface cues may foster trust without systematic source verification. Study 1 analysed survey data from 510 Spanish users using a consistent partial least squares structural equation modelling approach. Study 2 combined eye tracking and interviews with 20 Spanish users. The model explained 75.7% of the variance in trust and 91.0% of the variance in credibility. Clarity and context ( beta = .419, p < .001) and access to additional information and supporting sources ( beta = .335, p = .002) showed the strongest observed associations with trust, whereas response immediacy was not significant ( beta = .008, p = .874). Trust ( beta = .834) and perceived usefulness ( beta = .229) were positively associated with credibility (both p < .001), which, in turn, was associated with recommendation following ( beta = .877) and intention to use ( beta = .553; both p < .001). Eye tracking recorded no analysable fixations on the AI-error warning, while the interviews indicated that participants in this subsample did not routinely verify the displayed sources and often interpreted visible references as indicators of reliability. Taken together, Study 1 identifies associations between perceived answer-quality cues, trust, and credibility, whereas Study 2 suggests that visual prominence and visible references appeared to operate as authority cues for some participants and may encourage reliance without active source verification.
The integration of stochastic renewable energy sources has made flecan be reformuxibility aggregators crucial for power system balancing, yet the uncertainty they introduce challenges system security and market efficiency. Current trends show a move towards probabilistic reliability rules for bid qualification, but a key research gap remains: how can a Transmission System Operator (TSO) optimally set these reliability thresholds while considering competitive aggregators in the market? This paper proposes a novel methodology using a Strengthened Faster Linear Approximation (SFLA) to reformulate the game-theoretic problem, which includes lower-level distributionally robust joint chance constraints, into a tractable single-level optimization problem. A case study with real-world data from Spanish Reserve Markets demonstrates the method’s ability to balance system costs and security, quantifying the trade-off between reserve procurement and delivery risk. This research provides TSOs with a computationally tractable decision-making tool to set reliability thresholds for aggregators while ensuring security.
This study investigates the integration of bio-oxygenated fuel formulation with an electrically heated catalytic system to mitigate low-temperature cold-start emissions in compression-ignition engines. Four 20 % v/v oxygenated blends, comprising linear alcohols (butanol, pentanol) and cyclic compounds (cyclopentanol, cyclopentanone), were evaluated in a single-cylinder research engine coupled to a diesel oxidation catalyst. Linear alcohol blending reduced the CO light-off threshold (T50,CO) by 26 degrees C (butanol) and 16 degrees C (pentanol) relative to neat diesel by suppressing heavy hydrocarbon precursors and limiting active-site blocking on platinum group metals, whereas engine-out measurements showed that cyclic fuels yielded an initial particulate number reduction exceeding 85 % (reaching up to 90 % for cyclopentanone) compared to neat diesel. Active thermal management at DOC inlet temperatures of 355 degrees C to 415 degrees C achieved approximately 99 % CO conversion and 72 % total hydrocarbon reduction and increased the downstream NO2/NOx ratio up to 0.34. Catalytic posttreatment further reduced total particle number concentration by 41.1 % to 57.2 % with a simultaneous increase in count median diameter. These results, constrained by the single-cylinder steady-state operating conditions and specific engine loads evaluated, indicate that coupling tailored fuel formulations with active electrical heating offers an integrated methodological framework with the potential to resolve cold-start emissions limitations in low-exhaust-temperature applications.
Electric carsharing fleets can provide not only sustainable urban mobility, but also flexible storage services to the power system through Vehicle-to-Grid (V2G) operation. However, coordinating charging and discharging decisions for large fleets while preserving trip feasibility remains computationally challenging when vehicles are modeled individually. This paper proposes a single-stage aggregated linear programming model for the optimal charging and discharging of carsharing fleets. The formulation represents vehicles at depot level, explicitly incorporates mobility demand through deterministic transition data, and uses effective connection time to capture the fraction of each time interval during which vehicles remain available for grid interaction. The model is validated using real telemetry data from the AutoTel carsharing system in Tel Aviv-Yafo. A microscopic individual-vehicle formulation is also developed as a benchmark to assess the consistency and scalability of the aggregated approach. Results show that the proposed model preserves the main economic and operational trends of the individual formulation while significantly improving computational scalability, since the number of decision variables does not increase with fleet size. In the analyzed case study, smart charging substantially reduces charging costs, while V2G profitability strongly depends on the sell-to-purchase price ratio and battery degradation costs. These results support the feasibility of aggregated V2G-enabled carsharing fleets as scalable and economically relevant flexibility resources for urban energy systems.
