Factores psicosociales de riesgo para la enfermedad cardiovascular

Segones Jornades de Foment de la Investigació de la FCHS (Any 1996-1997

El apoyo social como modulador del riesgo coronario

Segones Jornades de Foment de la Investigació de la FCHS (Any 1996-1997

Drowsiness detection in drivers with a smartwatch

The main objective of this work is to detect early if a driver shows symptoms of sleepiness that indicate that he/she is falling asleep and, in that case, generate an alert to wake him/her up. To solve this problem, an application has been designed that collects various parameters, through a smartwatch while driving. First, the application detects the driving action. Then, it collects information about the most significant physiological variables of a person while driving. On the other hand, given the high level of sensitivity of the data managed in the designed application, in this work special attention has been paid to the security of the implementation. The proposed solution improves road safety, reducing the number of accidents caused by drowsiness while driving

Feasibility of estimating travel demand using geolocations of social media data

Travel demand estimation, as represented by an origin–destination (OD) matrix, is essential for urban planning and management. Compared to data typically used in travel demand estimation, the key strengths of social media data are that they are low-cost, abundant, available in real-time, and free of geographical partition. However, the data also have significant limitations: population and behavioural biases, and lack of important information such as trip purpose and social demographics. This study systematically explores the feasibility of using geolocations of Twitter data for travel demand estimation by examining the effects of data sparsity, spatial scale, sampling methods, and sample size. We show that Twitter data are suitable for modelling the overall travel demand for an average weekday but not for commuting travel demand, due to the low reliability of identifying home and workplace. Collecting more detailed, long-term individual data from user timelines for a small number of individuals produces more accurate results than short-term data for a much larger population within a region. We developed a novel approach using geotagged tweets as attraction generators as opposed to the commonly adopted trip generators. This significantly increases usable data, resulting in better representation of travel demand. This study demonstrates that Twitter can be a viable option for estimating travel demand, though careful consideration must be given to sampling method, estimation model, and sample size

Vitamin Supplementation and Dementia: A Systematic Review

Background: Dementia is a syndrome characterized by progressive cognitive impairment that interferes with independent function in daily activities. Symptoms of dementia depend on its cause and vary greatly between individuals. There is extensive evidence supporting a relationship between diet and cognitive functions. This systematic review studies the efficacy of using vitamin supplements in the diet as a solution to nutritional deficiencies and the prevention of dementia and mild cognitive impairment. Methods: An intensive search of different databases (PubMed, Web of Science, and Cochrane CENTRAL) was performed. Articles that were published between 2011 and November 2021 were retrieved using the mentioned search strategy. This systematic review has been conducted according to the PRISMA statement. Results: Folic acid supplementation proved to have better outcomes on cognitive tests than their respective control groups. The combined supplementation of folic acid and vitamin B12 showed some discrepancies between studies. Thiamine as supplementation did not only prove to have a positive impact on cognitive performance when given alone but also when given in combination with folic acid. Regarding vitamin D supplementation, the results observed were not so encouraging. A concomitant supplementation of low-dose vitamin E and vitamin C was also not associated with an improvement of cognitive function. Conclusions: The findings of this systematic review suggest that supplementation of B Complex vitamins, especially folic acid, may have a positive effect on delaying and preventing the risk of cognitive decline. Ascorbic acid and a high dose of vitamin E, when given separately, also showed positive effects on cognitive performance, but there is not sufficient evidence to support their use. The results of vitamin D supplementation trials are not conclusive in assessing the potential benefits that vitamin D might have on cognition

Secuencia didáctica: Enseñanza de óxidos y su nomenclatura química en décimo grado

This research aimed to design and develop a didactic sequence for the teaching of inorganic functions (oxides) and their respective nomenclature from the constructivism theory and problem-based learning. This was carried out with 34 students from the 10-03 course of the Enrique Olaya Herrera High School, with the goal of facilitating their construction of meaningful learning. To achieve the above, a qualitative analysis of the different class sessions was conducted to identify issues during the teaching-learning process. This analysis provided pertinent information for the choice of instruments, evaluation strategies, and contents to be addressed from the utility and applicability of knowledge in everyday life. Finally, the results showed a greater content analysis and knowledge acquisition, overcoming misconceptions and shortcomings presented.La presente investigación tuvo como objetivo diseñar y desarrollar una secuencia didáctica para la enseñanza de funciones inorgánicas (óxidos) y su respectiva nomenclatura desde la teoría del constructivismo y el aprendizaje basado en problemas. Esta se realizó con 34 estudiantes del curso 10-03 del Colegio Enrique Olaya Herrera IED, con miras a que ellos construyeran aprendizaje significativo. Para lograr lo anterior, se llevó a cabo un análisis cualitativo de las diferentes sesiones de clase para identificar las problemáticas durante el proceso de enseñanza-aprendizaje. Dicho análisis aportó información pertinente para la elección de instrumentos, estrategias de evaluación y contenidos a abordar desde la utilidad y la aplicabilidad del conocimiento en la cotidianidad. Finalmente, los resultados mostraron un mayor análisis en el contenido y la adquisición del conocimiento, superando concepciones erróneas y falencias presentadas

Phase-measuring time-gated BOCDA

We demonstrate a simple scheme that allows performing distributed Brillouin phase spectrum (BPS) measurements with very high spatial resolution (~7 cm) over long (~4.7 km) optical fibers. This is achieved by inserting a Sagnac interferometer (SI) in a Brillouin optical correlation domain analysis (BOCDA) configuration. Over its already-presented time-domain equivalent (SI-BOTDA), this approach reduces the main source of noise (coherent backscatter noise) thanks to the low-coherence nature of the used signals. On the other hand, over the most usual schemes used for distributed BPS measurements, this implementation presents the key advantage of not requiring high-bandwidth detection or complex modulation while reaching unprecedented values of spatial resolution and number of resolved points for this type of measurement. Thanks to the linear dependence of the BPS feature around the Brillouin frequency shift, this scheme could also have the advantage of requiring shorter scanning ranges than amplitude-based configurations.European CommissionMinisterio de Economía y CompetitividadComunidad de Madri

A Mobility Model for Synthetic Travel Demand from Sparse Traces

Knowing how much people travel is essential for transport planning. Empirical mobility traces collected from call detail records (CDRs), location-based social networks (LBSNs), and social media data have been used widely to study mobility patterns. However, these data suffer from sparsity, an issue that has largely been overlooked. In order to extend the use of these low-cost and accessible data, this study proposes a mobility model that fills the gaps in sparse mobility traces from which one can later synthesise travel demand. The proposed model extends the fundamental mechanisms of exploration and preferential return to synthesise mobility trips. The model is tested on sparse mobility traces from Twitter. We validate our model and find good agreement on origin-destination matrices and trip distance distributions for Sweden, the Netherlands, and Sa\uf5 Paulo, Brazil, compared with a benchmark model using a heuristic method, especially for the most frequent trip distance range (1-40 km). Moreover, the learned model parameters are found to be transferable from one region to another. Using the proposed model, reasonable travel demand values can be synthesised from a dataset covering a large enough population of very sparse individual geolocations (around 1.5 geolocations per day covering 100 days on average)

A Mobility Model for Synthetic Travel Demand from Sparse Individual Traces

Knowing how much people travel is essential for lowering carbon emissions in the transport sector. Empirical mobility traces collected from call detail records (CDRs), location-based social networks (LBSNs), and social media data have been used widely to study mobility patterns. However, these traces suffer from sparsity, an issue that has largely been overlooked. In order to extend the use of these low-cost and easy-to-access data, this study proposes an individual-based mobility model to fill the gaps in sparse mobility traces. The proposed model applies the fundamental mechanisms of exploration and preferential return to synthesise mobility to generate trips, designed to accommodate the sparse individual traces of geolocated social media data. We validated our model and found good agreement on origin-destination matrices and trip distance distributions for Sweden, the Netherlands, and S\ue3o Paulo, Brazil. The proposed model can be used to synthesise mobility at any geographic scale, and the results can later be applied to modelling travel demand. We further apply the model to characterise domestic trip distances for a mixture of cities and countries globally. The trip distance distributions from the model-synthesised trips using sparse geolocations from 22 regions largely follow lognormal distributions and they reflect reasonable characteristics of regional heterogeneity. Further exploration is needed to understand the regional differences between the 22 cities and countries tested