Programa de autocuidados para la salud dirigido a adolescentes: Prevención de infecciones de tracto urinario (ITU) y hábitos higiénicos sexuales

Introducción: Las Infecciones de Tracto Urinario (ITU) son infecciones habitualmente bacterianas, que ascienden a vejiga y vías urinarias, provocando una clínica clave (disuria, polaquiuria, mal estar, etc.). Las ITU tienen diferentes factores de riesgo, entre ellos la inadecuada higiene poscoital. Son más frecuentes en mujeres debido al tamaño y ubicación de la uretra femenina. El tratamiento para esta infección se basa en la antibioterapia, realizando cultivos de orina para analizar qué patógeno es el invasor, siendo comúnmente E. Coli. También se puede actuar preventivamente frente a las infecciones de orina, para que los episodios recurrentes de ITU (rITU) disminuyan.Objetivo: Inferir en la correcta higiene sexual para la prevención de ITU a través de la realización de un programa de educación para la salud (PES). Metodología: Se ha realizado una búsqueda bibliográfica en las principales bases de datos y páginas webs para obtener información sobre las ITU. Además se realiza una encuesta a 421 participantes para recopilar datos acerca de la incidencia de las ITU en jóvenes. Posteriormente, se ha diseñado un programa de educación para la salud para su prevención.Conclusiones: Este PES permite a las enfermeras un acercamiento a los adolescentes, formándoles en prácticas higiénico-sexuales y favoreciendo la prevención de este problema de salud actual. De esta manera se produce una disminución de la incidencia de casos. Además se produce una posible disminución de toma de antibióticos, que mejoraría las actuales resistencias a antibióticos. Palabras Clave: "infección tracto urinario (ITU)", "higiene", "sexual", "adolescentes", "educación". <br /

Mussel shell mortars durability: Study of aggregate replacement limit

[Abstract]: The knowledge acquired through previous experimental phases with coating mortars with mussel shell aggregates led to conclude that irregular, flaky and hydrophobic particles of the mussel shell and the organic matter content introduce entrapped air and entrained air in the mixes. This phenomenon causes different and opposite effects on the main properties of mortars, which are in some way positive and negative (for durability), consequently, their durability cannot be easily predicted. The present work pretends to analyse the results of different durability tests, such as water vapour permeability, adhesive strength, and weathering cycles to recommend the maximum percentage of mussel shell sand used in coating mortars that guarantee the required lifespan. After an in-depth literature review, it can be said that it is not easy to predict the durability of mortars using mussel shell aggregates. This question has been hardly analysed in the existing literature and the maximum substitution percentage of conventional aggregate that can be replaced is not clear. This work aims to answer this issue by analysing different properties: water vapour permeability, adhesive strength, and weathering cycles. Mussel shell content improves the water vapour permeability of both air lime and cement mortars but worsens the adhesive strength and weathering cycle behaviour. For most applications, 25 % of mussel shell aggregate can be employed, but for some applications, 50 % or even 75 % of mussel shell aggregate is feasible and will avoid the undesirable landfilling of this waste.This work has been developed within the framework of the project "Valorización de las conchas de bivalvos gallegos en el ámbito de la construcción" (Valorisation of Galician bivalve shell in the construction sector; Code 00064742/ITC-20133094), funded by CDTI (Centro para el Desarrollo Tecnológico e Industrial) under the FEDER-Innterconecta Program, and co-financed with European Union ERDF funds

Café Bar Pentágono: propuesta de Restyling de la identidad visual corporativa y guía de usos y estilo para redes sociales

Treball Final de Grau en Publicitat i Relacions Públiques. Codi: PU0932. Curs acadèmic: 2019/2020En el siguiente documento veremos el Trabajo Final de Grado (TFG) de dos alumnos del grado de Publicidad y Relaciones Públicas de la Universidad Jaume I. El mismo aborda un restyling de la identidad visual corporativa de la empresa Café Bar Pentágono, así como las premisas básicas para la presencia de ésta en redes sociales mediante una guía de uso y estilo de la misma. El Café Bar Pentágono, el cual nombraremos a partir de este momento “Pentágono”, es una empresa de carácter familiar que realiza su actividad en el municipio valenciano de Albal. Así pues, el Pentágono es una pequeña empresa dedicada a la hostelería que es regentada por los socios fundadores del bar, José Ferrer Alarcón y Francisco Ferrer Alarcón. Como hemos anticipado, la investigación de este trabajo se centra en el estudio de la importancia de varios conceptos como el de identidad visual corporativa de una empresa y la presencia de esta en el medio online a través de las redes sociales. Además, también profundizaremos en las particularidades que presentan las pymes y la comunicación corporativa del comercio local con la finalidad de obtener un producto comunicativo que introduzca a la marca en el contexto comunicativo digital de nuestros días. En definitiva, el objetivo principal de este proyecto es que el Pentágono pase de ser una empresa pasiva a activa en lo que a comunicación se refiere

Influence of the Mixing Procedure on the Fresh State Behaviour of Recycled Mortars

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] The effect of two different mixing protocols on the fresh-state behaviour of self-compacting mortars with and without recycled sand was compared. For this purpose, the mortar mixes were designed considering three solid volume fractions, while maintaining the water to cement ratio and superplasticiser dosage constant. The results conclude that the inclusion of recycled sand harmfully affects the rheological behaviour of the mortars and this effect can be mitigated using mixing protocols with longer mixing times and delayed admixture addition times. Finally, a rheograph was developed to explain the expectable changes in a conventional mix when recycled sand is incorporated, the solid volume fraction is varied and changes are applied to the mixing procedure

Supervised contrastive learning over prototype-label embeddings for network intrusion detection

Producción CientíficaContrastive learning makes it possible to establish similarities between samples by comparing their distances in an intermediate representation space (embedding space) and using loss functions designed to attract/repel similar/dissimilar samples. The distance comparison is based exclusively on the sample features. We propose a novel contrastive learning scheme by including the labels in the same embedding space as the features and performing the distance comparison between features and labels in this shared embedding space. Following this idea, the sample features should be close to its ground-truth (positive) label and away from the other labels (negative labels). This scheme allows to implement a supervised classification based on contrastive learning. Each embedded label will assume the role of a class prototype in embedding space, with sample features that share the label gathering around it. The aim is to separate the label prototypes while minimizing the distance between each prototype and its same-class samples. A novel set of loss functions is proposed with this objective. Loss minimization will drive the allocation of sample features and labels in embedding space. Loss functions and their associated training and prediction architectures are analyzed in detail, along with different strategies for label separation. The proposed scheme drastically reduces the number of pair-wise comparisons, thus improving model performance. In order to further reduce the number of pair-wise comparisons, this initial scheme is extended by replacing the set of negative labels by its best single representative: either the negative label nearest to the sample features or the centroid of the cluster of negative labels. This idea creates a new subset of models which are analyzed in detail. The outputs of the proposed models are the distances (in embedding space) between each sample and the label prototypes. These distances can be used to perform classification (minimum distance label), features dimensionality reduction (using the distances and the embeddings instead of the original features) and data visualization (with 2 or 3D embeddings). Although the proposed models are generic, their application and performance evaluation is done here for network intrusion detection, characterized by noisy and unbalanced labels and a challenging classification of the various types of attacks. Empirical results of the model applied to intrusion detection are presented in detail for two well-known intrusion detection datasets, and a thorough set of classification and clustering performance evaluation metrics are included.Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación - Fondo Europeo de Desarrollo Regional (grant RTI2018-098958-B-I00

Temperature and relative humidity estimation and prediction in the tobacco drying process using artificial neural networks

Producción CientíficaThis paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed.Centro para el Desarrollo Tecnológico Industrial (CDTI), proyecto "Mejora de la competitividad del sector del tabaco en Extremadura: nuevos procesos y productos" (under project IDI-20100986)Junta de Castilla y León, financiado por el Plan Regional de Proyectos de Investigación (proyecto VA034A10-2

A semantic autonomous video surveillance system for dense camera networks in smart cities

Producción CientíficaThis paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network

An intelligent surveillance platform for large metropolitan areas with dense sensor deployment

Producción CientíficaThis paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform’s control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coveraMinisterio de Industria, Turismo y Comercio and the Fondo de Desarrollo Regional (FEDER) and the Israeli Chief Scientist Research Grant 43660 inside the European Eureka Celtic project HuSIMS (TSI-020400-2010-102)