Reingreso de puérperas adolescentes/adultas por infecciones prevenibles en etapa del alta conjunta

Lugar de estudio: Hospital Lagomaggiore, Servicio 1er y 3er piso Maternidad, periodo mayo, junio, julio y agosto del año 2017. Introducción: Los cuidados que debe tener la mujer luego del alta conjunta son primordiales, ya sea cesárea o parto normal. No deberá descuidar del recién nacido. En casos de madres adolescentes y madres mayores de edad que no tengan suficientes conocimientos, enfermería deberá actuar en forma de educadora, promoviendo la salud y previniendo riesgos y complicaciones puerperales relacionadas a la mujer. Objetivo: Determinar que conocimientos sobre salud de la mujer tienen las mujeres que reingresan a la maternidad. Método: Tipo de estudio descriptivo, cuantitativo de corte transversal. Población y Muestra: Para la recolección de datos se encuestaron a 35 mujeres, entre ellas adolescentes menores de edad. Del Servicio Maternidad del Hospital Luis Carlos Lagomaggiore. Resultados: Se observó que un 29% de puérperas reingresa por algún tipo de infección por falta de conocimientos sobre cuidados, falta de necesidades básicas como agua potable, falta de interés en aprender. Destacamos que el 14 % son provenientes de Lavalle y su reingreso está relacionado con la falta de conocimiento en los cuidados de salud. Dejamos la escolaridad de lado, a pesar de que tengan casa con baño adentro. Conclusión: Los resultados de esta investigación determinaron que la gran mayoría de las mujeres desconocen acerca de las infecciones posparto, riesgos y complicaciones luego del alta conjunta. Los datos también lanzan como resultado que las madres tienen déficits de conocimientos, acompañado mayormente en la interrupción de la escolaridad en embarazadas adolescentes. Expectativas: Se determina instruir, explicar y fomentar el conocimiento y aprendizaje sobre los diferentes tipos de autocuidados, tipos de infección y posibles complicaciones. Enfermería reunirá a las madres y su familia antes de abandonar la maternidad, para promoción de la salud y prevención.Fil: Rivera, Yesica Johanna.Fil: Sánchez, Lorena Belén.Fil: Valencia, Janet Gabriela

How to Improve Soil Anti-adhesion by Studying the Micro Relief of the Cuticle Surface of Digging Beetles: Exploring the Sulcophanaeus batesi Pronotum Using Translucent Replicas

For some years, we have been studying the microtopography of soil diggers beetles fromArgentina to find the anti-adhesion pattern to decrease a soil particle adhesion for agricultural machinery components. In 2018, we designed a macro topographic pattern for the upper surface of a steel shovel for tilling (agricultural tool) fromthe study of the microtopography (microrelief) of the cuticular surface of the pronotum of Diloboderus abderus (Coleoptera, Scarabaeidae), whose main feature is the presence of dimples randomly distributed.Fil: Guillén, Noelia Belén. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Setten, Lorena María. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; ArgentinaFil: Fil: Sánchez, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales; ArgentinaFil: Favret, Eduardo A. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

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

A clinical staging model for bipolar disorder : longitudinal approach.

Bipolar disorder (BD) has been identified as a life-course illness with different clinical manifestations from an at-risk to a late stage, supporting the assumption that it would benefit from a staging model. In a previous study, we used a clustering approach to stratify 224 patients with a diagnosis of BD into five clusters based on clinical characteristics, functioning, cognition, general health, and health-related quality of life. This study was design to test the construct validity of our previously developed k-means clustering model and to confirm its longitudinal validity over a span of 3 years. Of the 224 patients included at baseline who were used to develop our model, 129 (57.6%) reached the 3-year follow-up. All life domains except mental health-related quality of life (QoL) showed significant worsening in stages (p < 0.001), suggesting construct validity. Furthermore, as patients progressed through stages, functional decline (p < 0.001) and more complex treatment patterns (p = 0.002) were observed. As expected, at 3 years, the majority of patients remained at the same stage (49.6%), or progressed (20.9%) or regressed (23.3%) one stage. Furthermore, 85% of patients who stayed euthymic during that period remained at the same stage or regressed to previous stages, supporting its longitudinal validity. For that reason, this study provides evidence of the construct and longitudinal validity of an empirically developed, comprehensive staging model for patients with BD. Thus, it may help clinicians and researchers to better understand the disorder and, at the same time, to design more accurate and personalized treatment plans

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)

Obtention and characterization of ferrous chloride FeCl_2•4H_2O from water pickling liquors

As a hazardous waste, water pickling liquors must be properly treated. An alternative consists of promoting the formation of ferrous salts from this residue due to their higher ferrous content. Since FeCl_2•4H_2O is widely used in several applications, obtaining pure crystals of this material appears to be an interesting prospect. However, this compound has scarcely been investigated. In the present work, FeCl_2•4H_2O crystals were obtained from water pickling liquors. Their structural and morphological characteristics were investigated by X-ray diffraction, scanning electron microscopy as well as Mossbauer spectroscopy. In addition, the photoluminescence study of the obtained samples was also assessed. It was observed that after some aging time, the obtained crystals changed in colour from green to more yellowish. As such, the aged sample was also evaluated, and their structural characteristics were compared with the original crystals. Despite this, the obtained crystals exhibit a FeCl_2•4H_2O structure, which is not modified with the aging of the sample

Application of a Pharmacogenetics-Based Precision Medicine Model (5SPM) to Psychotic Patients That Presented Poor Response to Neuroleptic Therapy

[EN] Antipsychotics are the keystone of the treatment of severe and prolonged mental disorders. However, there are many risks associated with these drugs and not all patients undergo full therapeutic profit from them. The application of the 5 Step Precision Medicine model(5SPM), based on the analysis of the pharmacogenetic profile of each patient, could be a helpful tool to solve many of the problematics traditionally associated with the neuroleptic treatment. In order to solve this question, a cohort of psychotic patients that showed poor clinical evolution was analyzed. After evaluating the relationship between the prescribed treatment and pharmacogenetic profile of each patient, a great number of pharmacological interactions and pharmacogenetical conflicts were found. After reconsidering the treatment of the conflictive cases, patients showed a substantial reduction on mean daily doses and polytherapy cases, which may cause less risk of adverse effects, greater adherence, and a reduction on economic costs

Búsqueda de agonistas de PPARγ para el tratamiento de la enfermedad de Huntington

La enfermedad de Huntington (EH) es una enfermedad autosómica dominante que se caracteriza por un deterioro neurológico progresivo. Es uno de los trastornos hereditarios monogénicos más comunes en países occidentales, y el tiempo de supervivencia medio es de 15-20 años tras la manifestación de los primeros síntomas [1]. Actualmente no se ha desarrollado ningún fármaco que permita la remisión de la enfermedad, solo existen tratamientos paliativos. La fisiopatología de esta enfermedad se caracteriza por la acumulación de más de 35 repeticiones de trinucleótidos CAG (cola poliQ) en el gen que codifica para la proteína huntingtina (Htt). La presencia de Htt mutada da lugar a la acumulación de agregados intracelulares tóxicos y a la alteración de diferentes procesos celulares: desregulación de la expresión génica, alteración de la degradación y el plegamiento de proteínas, interrupción de la señalización sináptica y alteración del metabolismo energético, donde tiene un papel importante el receptor nuclear PPARγ [2]. En base a estos procesos, sugerimos dos dianas moleculares que aparecen principalmente alteradas en EH: Htt y PPARγ. Existen fármacos antidiabéticos agonistas de PPARγ que han demostrado efectos neuroprotectores en modelos experimentales de EH, como la Rosiglitazona, retirado por cardiotoxicidad [3]. Por tanto, proponemos iniciar una búsqueda de agonistas de PPARγ mediante la obtención de una colección de nuevas moléculas y la síntesis de compuestos derivados de la Rosiglitazona, con el fin de disminuir su cardiotoxicidad. Estas moléculas se someterían a un cribado de alto rendimiento mediante dos ensayos in vitro: uno de activación de PPARγ, y otro de paso de barrera hematoencefálica. Por último, habría que realizar ensayos preclínicos adicionales para determinar la eficacia y los posibles efectos secundarios de los fármacos seleccionado

Improved Short-Term Load Forecasting Based on Two-Stage Predictions with Artificial Neural Networks in a Microgrid Environment

Short-Term Load Forecasting plays a significant role in energy generation planning, and is specially gaining momentum in the emerging Smart Grids environment, which usually presents highly disaggregated scenarios where detailed real-time information is available thanks to Communications and Information Technologies, as it happens for example in the case of microgrids. This paper presents a two stage prediction model based on an Artificial Neural Network in order to allow Short-Term Load Forecasting of the following day in microgrid environment, which first estimates peak and valley values of the demand curve of the day to be forecasted. Those, together with other variables, will make the second stage, forecast of the entire demand curve, more precise than a direct, single-stage forecast. The whole architecture of the model will be presented and the results compared with recent work on the same set of data, and on the same location, obtaining a Mean Absolute Percentage Error of 1.62% against the original 2.47% of the single stage model.Hernández, L.; Baladrón Zorita, C.; Aguiar Pérez, JM.; Calavia Domínguez, L.; Carro Martínez, B.; Sanchez-Esguevillas, A.; Sanjuan, J.... (2013). Improved Short-Term Load Forecasting Based on Two-Stage Predictions with Artificial Neural Networks in a Microgrid Environment. Energies. 6(9):4489-4507. doi:10.3390/en6094489S4489450769Brooks, A., Lu, E., Reicher, D., Spirakis, C., & Weihl, B. (2010). Demand Dispatch. IEEE Power and Energy Magazine, 8(3), 20-29. doi:10.1109/mpe.2010.936349Chan, S. C., Tsui, K. M., Wu, H. C., Hou, Y., Wu, Y.-C., & Wu, F. (2012). Load/Price Forecasting and Managing Demand Response for Smart Grids: Methodologies and Challenges. IEEE Signal Processing Magazine, 29(5), 68-85. doi:10.1109/msp.2012.2186531Mohan Saini, L., & Kumar Soni, M. (2002). Artificial neural network-based peak load forecasting using conjugate gradient methods. IEEE Transactions on Power Systems, 17(3), 907-912. doi:10.1109/tpwrs.2002.800992Hyndman, R. J., & Fan, S. (2010). Density Forecasting for Long-Term Peak Electricity Demand. IEEE Transactions on Power Systems, 25(2), 1142-1153. doi:10.1109/tpwrs.2009.2036017McSharry, P. E., Bouwman, S., & Bloemhof, G. (2005). Probabilistic Forecasts of the Magnitude and Timing of Peak Electricity Demand. IEEE Transactions on Power Systems, 20(2), 1166-1172. doi:10.1109/tpwrs.2005.846071Amin-Naseri, M. R., & Soroush, A. R. (2008). Combined use of unsupervised and supervised learning for daily peak load forecasting. Energy Conversion and Management, 49(6), 1302-1308. doi:10.1016/j.enconman.2008.01.016Maksimovich, S. M., & Shiljkut, V. M. (2009). The Peak Load Forecasting Afterwards Its Intensive Reduction. IEEE Transactions on Power Delivery, 24(3), 1552-1559. doi:10.1109/tpwrd.2009.2014267Moazzami, M., Khodabakhshian, A., & Hooshmand, R. (2013). A new hybrid day-ahead peak load forecasting method for Iran’s National Grid. Applied Energy, 101, 489-501. doi:10.1016/j.apenergy.2012.06.009Hernández, L., Baladrón, C., Aguiar, J., Carro, B., & Sánchez-Esguevillas, A. (2012). Classification and Clustering of Electricity Demand Patterns in Industrial Parks. Energies, 5(12), 5215-5228. doi:10.3390/en5125215Hernandez, L., Baladrón, C., Aguiar, J., Carro, B., Sanchez-Esguevillas, A., & Lloret, J. (2013). Short-Term Load Forecasting for Microgrids Based on Artificial Neural Networks. Energies, 6(3), 1385-1408. doi:10.3390/en6031385Razavi, S., & Tolson, B. A. (2011). A New Formulation for Feedforward Neural Networks. IEEE Transactions on Neural Networks, 22(10), 1588-1598. doi:10.1109/tnn.2011.2163169Hernández, L., Baladrón, C., Aguiar, J., Calavia, L., Carro, B., Sánchez-Esguevillas, A., … Lloret, J. (2013). Experimental Analysis of the Input Variables’ Relevance to Forecast Next Day’s Aggregated Electric Demand Using Neural Networks. Energies, 6(6), 2927-2948. doi:10.3390/en6062927Hernandez, L., Baladron, C., Aguiar, J. M., Carro, B., Sanchez-Esguevillas, A., Lloret, J., … Cook, D. (2013). A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants. IEEE Communications Magazine, 51(1), 106-113. doi:10.1109/mcom.2013.640044

La libertad en la obra de Miguel Delibes. Aplicaciones intermediales en las aulas de Magisterio y de Filología

Memoria ID2022-227 Ayudas de la Universidad de Salamanca para la innovación docente, curso 2022-2023