Analyzing First-Person Stories Based on Socializing, Eating and Sedentary Patterns

First-person stories can be analyzed by means of egocentric pictures acquired throughout the whole active day with wearable cameras. This manuscript presents an egocentric dataset with more than 45,000 pictures from four people in different environments such as working or studying. All the images were manually labeled to identify three patterns of interest regarding people's lifestyle: socializing, eating and sedentary. Additionally, two different approaches are proposed to classify egocentric images into one of the 12 target categories defined to characterize these three patterns. The approaches are based on machine learning and deep learning techniques, including traditional classifiers and state-of-art convolutional neural networks. The experimental results obtained when applying these methods to the egocentric dataset demonstrated their adequacy for the problem at hand.Comment: Accepted at First International Workshop on Social Signal Processing and Beyond, 19th International Conference on Image Analysis and Processing (ICIAP), September 201

Recurrent autoencoder with skip connections and exogenous variables for traffic forecasting

The increasing complexity of mobility plus the growing population in cities, together with the importance of privacy when sharing data from vehicles or any device, makes traffic forecasting that uses data from infrastructure and citizens an open and challenging task. In this paper, we introduce a novel approach to deal with predictions of volume, speed and main traffic direction, in a new aggregated way of traffic data presented as videos. Our approach leverages the continuity in a sequence of frames, learning to embed them into a low dimensional space with an encoder and making predictions there using recurrent layers, ensuring good performance through an embedded loss, and then, recovering back spatial dimensions with a decoder using a second loss at a pixel level. Exogenous variables like weather, time and calendar are also added in the model. Furthermore, we introduce a novel sampling approach for sequences that ensures diversity when creating batches, running in parallel to the optimization process.This work is supported by SEAT, S.A., and the Secretariat of Universities and Research of the Department of Economy and Knowledge of the Generalitat de Catalunya, under the Industrial Doctorate Grant 2017 DI 52. This research is also supported by the grant TIN2017-89244-R from MINECO (Ministerio de Economia, Industria y Competitividad) and the recognition 2017SGR-856 (MACDA) from AGAUR (Generalitat de Catalunya).Peer ReviewedPostprint (published version

Can a CNN recognize mediterranean diet?

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2016, Director: Petia RadevaNowadays, we can find several diseases related with the unhealthy diet habits of the population, such as diabetes, obesity, anemia, bulimia and anorexia. In many cases, it is related with the food consumption of the people. Mediterranean diet is scientifically known as a healthy diet that helps to prevent those and other food problems. In particular, our work focuses on the recognition of Mediterranean food and dishes. It is part of a wider project that analyses the daily habits of users with wearable cameras, within the topic of Lifelogging. It appears as an objective tool for the analysis of the patient’s behavior, allowing specialist to discover patterns and understand user’s lifestyle to find unhealthy food patterns. With the aim to automatic recognize a complete diet, we introduce a challenging multilabeled dataset related to Mediterranean diet called FoodCAT. The first kind of labels contains 115 food classes with an average of 400 images per dish, and the second one is composed by 12 food categories with an average of 3800 pictures per class. This dataset will serve as a basis for the development of automatic diet tracking problems. Deep learning and more specifically Convolutional Neural Networks (CNNs), are actually the technologies with the state-of-the-art recognizing food automatically. In our work, we adapt the best, so far, CNNs architectures for image classification, to our objective into the diet tracking. Recognizing food categories, we achieved the highest accuracies top-1 with 72.29%, and top-5 with 97.07%. In a complete diet tracking recognizing dishes from Mediterranean diet, enlarged with the Food-101 dataset, we achieve the highest accuracies top-1 with 68.07%, and top-5 with 89.53%, for a total of 115+101 food classes

A longitudinal comparative study of a multicouple group and single-couple psychosocial intervention while experiencing infertility

This is a quasi-experimental, nonequivalent design study investigating the efficacy of multicouple group and single-couple intervention formats aimed at diminishing the psychosocial impact of infertility. The review studies carried out to date that have assessed this subject do not show consistent findings and although increasing the efficacy and efficiency of intervention formats more than justifies their analysis, there are no studies making this particular comparison. Eighty-seven infertile couples who were in assessment for their infertility and/or were close to undergoing some kind of assisted reproductive technology process participated in a psychosocial intervention either under the multicouple group or single-couple subconditions, or acted as controls. The variables of depression, anxiety, and fertility quality of life were used for evaluating psychosocial impact. Comparisons were made: (a) between the intervention condition and controls and (b) between the two subconditions. The results support the efficacy of the intervention both in the dyadic latent growth curve models analysis carried out and in the treatment effect calculation. Although in the comparison between the multicouple and single-couple format, some differences generally favoring the single format one were found, they were not conclusive. Therefore, the results are in line with review studies that did not find the group format to be more effective. Although this study provides valuable information, its limitations mean that further research needs to be carried out. When selecting the intervention format, therapists should also weigh up others aspects, such as the intervention goal, patient's needs and characteristics, reproductive history, and current stage of infertility

Diseño del instrumento de ayuda para la toma de decisiones: “alternativas de tratamiento para el cáncer de próstata: ¿qué opción prefiero?”

Purpose: To design a Decision-making Aid within the ‘Benign Prostatic Hyperplasia’ healthcare process modelling of the Andalusian Public Health System (SSPA) for the therapeutic approach of early-stage disease. Methods: The Decision Aid design was conducted in four phases: 1) Explore the receptiveness of professionals in the mainstream of the SSPA Decision Aid “Benign Prostatic Hyperplasia” process; 2) Select a Decision Aid from international experiences; 3) Transcultural adaptation of above selected Decision Aid; 4) Decision Aid Validation in the SSPA. Results: The results of the validation of Decision Aid “Alternative treatment for prostate cancer: What option do I prefer?” have shown that the document is well taken by patients, their design is attractive and the quality of clinical information it contains is high. The instrument meets the concerns of patients (95%), the language is simple and suitable (92%) and summarizes the essential information to make the decision (92%). The Decision Aid offers relevant information that help the patient in the decision making process (lack of decisional confl ict: 88.93), generates a sense of support (92.82), concerning the decision (86.88) and a sense of availability of information (90.51). Conclusion: Patients and professionals agree to recommend the use of Decision Aid. To improve information and enhance the tranquillity of the patient, the Decision Aid facilitates communication doctor patient consultation and the involvement of patients during the decision-making process.Objetivo: Diseñar un Instrumento de Ayuda para la Toma de Decisiones (IATD) en el Proceso Asistencial Integrado ‘Hipertrofia benigna de próstata. Cáncer de próstata’ del Sistema Sanitario Público de Andalucía (SSPA) para el abordaje terapéutico de esta enfermedad en estadio inicial. Método: El diseño del IATD se realizó en cuatro fases: 1) Explorar la receptividad de los profesionales del SSPA sobre la incorporación de IATD en el proceso “Cáncer de próstata”. 2. Seleccionar un IATD entre las experiencias internacionales. 3. Adaptar transculturalmente del IATD seleccionado al entorno del SSPA. 4. Validar el IATD en el SSPA. Resultado: Los resultados de la validación del IATD “Alternativas de tratamiento para el cáncer de próstata: ¿Qué opción prefiero?” han mostrado que el documento es bien cogido por los pacientes, su diseño resulta atractivo y la calidad en la información clínica que contiene es elevada. El Instrumento resuelve las dudas de los pacientes (95%), el lenguaje resulta sencillo y asequible (92%) y resume la información esencial para tomar la decisión (92%). El IATD ofrece información relevante que prepara al paciente para la toma de decisiones (ausencia de conflicto decisional: 88,93), genera sentimiento de apoyo (92,82), seguridad en la decisión (86,88) y sensación de disponibilidad de información (90,51). Conclusiones: Pacientes y profesionales coinciden en recomendar la utilización del Instrumento. Al mejorar la información y aumentar la tranquilidad del paciente, el IATD facilita la comunicación médico-paciente en la consulta y la participación en la toma de decisiones

Nowcasting SAF (NWC SAF) led by AEMET

Ponencia presentada en: XIX Congreso de la Asociación Española de Teledetección celebrado en Pamplona del 29 de junio al 1 de julio de 2022.[ES]El objetivo de la red de SAFs de EUMETSAT es obtener productos derivados de satélites para poder optimizar el uso de los datos de los satélites meteorológicos. Cada SAF (Satellite Application Facility) es un consocio de varios servicios meteorológicos y otras instituciones de los estados miembros de EUMETSAT y está especializado en un área concreta: composición atmosférica, clima, análisis de la superficie de la tierra, del océano, hidrología, predicción inmediata, para modelos numéricos y radio ocultación. En particular el SAF de Nowcasting (NWC SAF) es un consorcio liderado por AEMET en el que participan además los servicios meteorológicos de Francia, Austria, Suecia y Rumanía. Su objetivo es la generación de productos para su aplicación en Nowcasting o predicción inmediata y predicción a muy corto plazo. El SAF de Nowcasting desarrolla, implementa y distribuye paquetes de software con los que se pueden generar productos a partir de datos de satélites polares y geoestacionarios. Estos productos incluyen productos de nubes, de inestabilidad atmosférica, de precipitación, de iniciación de convección y de identificación y seguimiento de células convectivas, de vientos, de extrapolación de imágenes e identificación de ciertos fenómenos meteorológicos como el doblamiento de la tropopausa y ondas de gravedad. Estos productos son de utilidad para el seguimiento de fenómenos meteorológicos en tiempo real, con especial interés en el seguimiento de los fenómenos adversos, con aplicaciones también en el ámbito de la meteorología aeronáutica o en asimilación en modelos numéricos. La última versión del software para satélites geoestacionarios y los planes de futuro del NWC SAF son presentados.[EN]The objective of the EUMETSAT SAF Network is the generation of satellite derived products to contribute to the optimum use of the meteorological satellite data. Each SAF (Satellite Application Facility) is a Consortium of meteorological services and other institutions of the EUMETSAT member states, and is specialised in a concrete area: atmospheric composition, climate, land surface analysis, ocean, hydrology, nowcasting, numerical weather prediction and radio occultation. The Nowcasting SAF (NWC SAF) is a Consortium of the meteorological services of Spain, France, Austria, Sweden and Romania and is led by AEMET. Its objective is to ensure the optimum use of the satellite data on its application to nowcasting. For this, the NWC SAF develops, maintains and distributes software packages for geostationary and polar satellites that allow the generation of satellite products for nowcasting applications. These include cloud products, stability products, precipitation products, convection initiation, detection, characterization and tracking of convective cells, image and product extrapolation in time and identification of meteorological phenomena like tropopause folding and gravity waves. These products are of great interest for nowcasting, in particular for the tracking of severe weather, and also have applications in aviation meteorology and assimilation in NWP models. The more recent software version for geostationary satellites and the future plans of the NWC SAF are presented

Acceptance of living liver donation among medical students: A multicenter stratified study from Spain

AIM: To analyze the attitude of Spanish medical students toward living liver donation (LLD) and to establish which factors have an influence on this attitude. METHODS: STUDY TYPE: A sociological, interdisciplinary, multicenter and observational study. STUDY POPULATION: Medical students enrolled in Spain (n = 34000) in the university academic year 2010-2011. SAMPLE SIZE: A sample of 9598 students stratified by geographical area and academic year. Instrument used to measure attitude: A validated questionnaire (PCID-DVH RIOS) was self-administered and completed anonymously. Data collection procedure: Randomly selected medical schools. The questionnaire was applied to each academic year at compulsory sessions. STATISTICAL ANALYSIS: Student´s t test, ?(2) test and logistic regression analysis. RESULTS: The completion rate was 95.7% (n = 9275). 89% (n = 8258) were in favor of related LLD, and 32% (n = 2937) supported unrelated LLD. The following variables were associated with having a more favorable attitude: (1) age (P = 0.008); (2) sex (P < 0.001); (3) academic year (P < 0.001); (4) geographical area (P = 0.013); (5) believing in the possibility of needing a transplant oneself in the future (P < 0.001); (6) attitude toward deceased donation (P < 0.001); (7) attitude toward living kidney donation (P < 0.001); (8) acceptance of a donated liver segment from a family member if one were needed (P < 0.001); (9) having discussed the subject with one's family (P < 0.001) and friends (P < 0.001); (10) a partner's opinion about the subject (P < 0.001); (11) carrying out activities of an altruistic nature; and (12) fear of the possible mutilation of the body after donation (P < 0.001). CONCLUSION: Spanish medical students have a favorable attitude toward LLD

Design a decision-making aid: "alternative treatment for prostate cancer: what option do you prefer?"

Purpose: To design a Decision-making Aid within the ‘Benign Prostatic Hyperplasia’ healthcare process modelling of the Andalusian Public Health System (SSPA) for the therapeutic approach of early-stage disease. Methods: The Decision Aid design was conducted in four phases: 1) Explore the receptiveness of professionals in the mainstream of the SSPA Decision Aid “Benign Prostatic Hyperplasia” process; 2) Select a Decision Aid from international experiences; 3) Transcultural adaptation of above selected Decision Aid; 4) Decision Aid Validation in the SSPA. Results: The results of the validation of Decision Aid “Alternative treatment for prostate cancer: What option do I prefer?” have shown that the document is well taken by patients, their design is attractive and the quality of clinical information it contains is high. The instrument meets the concerns of patients (95%), the language is simple and suitable (92%) and summarizes the essential information to make the decision (92%). The Decision Aid offers relevant information that help the patient in the decision making process (lack of decisional confl ict: 88.93), generates a sense of support (92.82), concerning the decision (86.88) and a sense of availability of information (90.51). Conclusion: Patients and professionals agree to recommend the use of Decision Aid. To improve information and enhance the tranquillity of the patient, the Decision Aid facilitates communication doctor patient consultation and the involvement of patients during the decision-making process