Smart Footwear Insole for Recognition of Foot Pronation and Supination Using Neural Networks

Abnormal foot postures during gait are common sources of pain and pathologies of the lower limbs. Measurements of foot plantar pressures in both dynamic and static conditions can detect these abnormal foot postures and prevent possible pathologies. In this work, a plantar pressure measurement system is developed to identify areas with higher or lower pressure load. This system is composed of an embedded system placed in the insole and a user application. The instrumented insole consists of a low-power microcontroller, seven pressure sensors and a low-energy bluetooth module. The user application receives and shows the insole pressure information in real-time and, finally, provides information about the foot posture. In order to identify the different pressure states and obtain the final information of the study with greater accuracy, a Deep Learning neural network system has been integrated into the user application. The neural network can be trained using a stored dataset in order to obtain the classification results in real-time. Results prove that this system provides an accuracy over 90% using a training dataset of 3000+ steps from 6 different users.Ministerio de Economía y Competitividad TEC2016-77785-

Augmented and virtual reality evolution and future tendency

Augmented reality and virtual reality technologies are increasing in popularity. Augmented reality has thrived to date mainly on mobile applications, with games like Pokémon Go or the new Google Maps utility as some of its ambassadors. On the other hand, virtual reality has been popularized mainly thanks to the videogame industry and cheaper devices. However, what was initially a failure in the industrial field is resurfacing in recent years thanks to the technological improvements in devices and processing hardware. In this work, an in-depth study of the different fields in which augmented and virtual reality have been used has been carried out. This study focuses on conducting a thorough scoping review focused on these new technologies, where the evolution of each of them during the last years in the most important categories and in the countries most involved in these technologies will be analyzed. Finally, we will analyze the future trend of these technologies and the areas in which it is necessary to investigate to further integrate these technologies into society.Universidad de Sevilla, Spain Telefonica Chair “Intelligence in Networks

Orbitopatía tiroidea, signos y síntomas

La orbitopatía tiroidea es una enfermedad autoinmune y autolimitada del sistema visual, asociada comúnmente a alteraciones de la glándula tiroidea, que provoca cambios en los tejidos blandos de órbita y periórbita por un proceso inflamatorio.Estos cambios en los tejidos blandos asociaran una serie de signos y síntomas que serán reconocidos e identificados en la exploración oftalmológica del paciente, además de mediante otras pruebas endocrinológicas y radiológicas. Con todas las pruebas realizadas será posible realizar un diagnostico de la enfermedad y así poder tratarla, no para eliminarla pero sí para que las secuelas sobre el paciente sean las mínimas. <br /

La investigación cualitativa a través del estudio de casos: referencia a la investigación en turismo

Investigamos para analizar y explicar fenómenos, pero no siempre podemos llevar a cabo las investigaciones mediante el empleo de metodologías basadas en el planteamiento y contraste de hipótesis sobre la base de un marco teórico existente, validado y vigente. En este trabajo trataremos de justificar la utilización de la metodología cualitativa como estrategia de investigación en el área de organización de empresas. Así analizamos los fundamentos, utilidades y limitaciones del estudio de casos, para posteriormente, sugerir, apoyándonos en la literatura consultada, las etapas que debe abordar una investigación con casos de calidad. Finalmente, y con el fin de justificar la relevancia que dicha metodología esta tomando en los últimos años en investigaciones relacionadas con el sector turístico, analizamos la presencia de la misma en los trabajos publicados en las revistas de mayor impacto de la materia.We research to analyze and explain phenomena, but we can not always carry out scientific studies using hypothesis testing methodologies based on an existing, validated and in used theoretical framework. In this paper we try to justify the use of qualitative techniques as a research strategy in the business administration area. The rationale, usefulness and limitations of case study methodology are scrutinized, in order to suggest, based on the existing literature, the stages that a quality cases research should follow. Finally, in order to justify the relevance that this methodology is taking in recent years in the field of tourism, we detail its use in the higher impact journals

Inducible nitric oxide synthase in human lymphomononuclear cells activated by synthetic peptides derived from extracellular matrix proteins.

Synthetic peptides with sequences present in extracellular matrix proteins are capable of causing the expression of the inducible form of nitric oxide synthase (iNOS), detected by immunocytochemistry, and the release of NO by human lymphomononuclear cells incubated in their presence. Active peptides are 15-mers containing a characteristic 2-6-11 motif in which the amino acid residue at position 2 is Leu, Ile, Val, Gly, Ala or Lys; the residue at position 6 is always Pro; and residue 11 is Glu or Asp. The induction of iNOS in human monocytes and macrophages could be involved in the cytotoxicity against tumor cell lines also elicited by these peptides

Evaluación de la velocidad de viento para parques offshore con telemetría y métodos de previsión estadísticos

El objetivo de este Proyecto Fin de Carrera es la evaluación de distintos métodos estadísticos de modelos autorregresivos integrados de media móvil (ARIMA) para la realización de ensayos de predicción de velocidades del viento en territorios marinos cercanos a la costa. Una vez seleccionado del método que más se aproxime a la realidad se realiza un estudio temporal durante un año y otro estudio espacio- temporal del que se han extraído datos, gráficas e imágenes que hacen más fácil la comprensión de lo expuesto en el proyecto. Los datos de partida del estudio han sido obtenidos del satélite orbital QuickSCAT, el cual ha proporcionado información meteorológica a nivel planetario de la superficie de los océanos y mares a lo largo de la última década. Todos las operaciones del proyecto han sido realizadas utilizando el código R language, herramienta muy potente a la hora de trabajar con grandes bases de de datos. Una de las razones de por las que se ha decidido realizar el proyecto acerca de la energía eólica es por el gran potencial de desarrollo que posee este tipo de energía, ya que a corto plazo la eólica offshore será una de las energías más representativas del planeta y se necesitarán técnicas predictivas para obtener el máximo rendimiento

Non-small cell lung cancer diagnosis aid with histopathological images using Explainable Deep Learning techniques

Background: Lung cancer has the highest mortality rate in the world, twice as high as the second highest. On the other hand, pathologists are overworked and this is detrimental to the time spent on each patient, diagnostic turnaround time, and their success rate. Objective: In this work, we design, implement, and evaluate a diagnostic aid system for non-small cell lung cancer detection, using Deep Learning techniques. Methods: The classifier developed is based on Artificial Intelligence techniques, obtaining an automatic classification result between healthy, adenocarcinoma and squamous cell carcinoma, given an histopathological image from lung tissue. Moreover, a report module based on Explainable Deep Learning techniques is included and gives the pathologist information about the image’s areas used to classify the sample and the confidence of belonging to each class. Results: The results show a system accuracy between 97.11 and 99.69%, depending on the number of classes classified, and a value of the area under ROC curve between 99.77 and 99.94%. Conclusions: The classification results obtain a substantial improvement according to previous works. Thanks to the given report, the time spent by the pathologist and the diagnostic turnaround time can be reduced.Andalusian Regional I+D+i FEDER Project DAFNE US-138161

Model-Assisted Bird Monitoring Based on Remotely Sensed Ecosystem Functioning and Atlas Data

Urgent action needs to be taken to halt global biodiversity crisis. To be effective in the implementation of such action, managers and policy-makers need updated information on the status and trends of biodiversity. Here, we test the ability of remotely sensed ecosystem functioning attributes (EFAs) to predict the distribution of 73 bird species with different life-history traits. We run ensemble species distribution models (SDMs) trained with bird atlas data and 12 EFAs describing different dimensions of carbon cycle and surface energy balance. Our ensemble SDMs—exclusively based on EFAs—hold a high predictive capacity across 71 target species (up to 0.94 and 0.79 of Area Under the ROC curve and true skill statistic (TSS)). Our results showed the life-history traits did not significantly affect SDM performance. Overall, minimum Enhanced Vegetation Index (EVI) and maximum Albedo values (descriptors of primary productivity and energy balance) were the most important predictors across our bird community. Our approach leverages the existing atlas data and provides an alternative method to monitor inter-annual bird habitat dynamics from space in the absence of long-term biodiversity monitoring schemes. This study illustrates the great potential that satellite remote sensing can contribute to the Aichi Biodiversity Targets and to the Essential Biodiversity Variables framework (EBV class “Species distribution”)Fieldwork campaigns were carried out within the project “Estudios sobre a biodiversidade do Macizo Central Galego. Lugar de Importancia Comunitaria” (PGIDT99PXI20002B) and “Caracterización de los vertebrados del LIC Macizo Central e Bidueiral de Montederramo”, code: 2008-CE227”, funded by SAYFOR S.L. This work also received funding from Xunta de Galicia through the grant to structure and consolidate competitive research groups of Galicia (ED431B 2018/36). A.R. was funded by the Xunta de Galicia, Spain (post-doctoral fellowship ED481B2016/084-0). S.A.-C. was financially supported by PORBIOTA—E-Infraestrutura Portuguesa de Informação e Investigação em Biodiversidade (POCI-01-0145-FEDER-022127)S

Aliviaderos escalonados sin cajeros laterales. Projecto ALIVESCA

En el presente trabajo se muestran los primeros resultados del proyecto de investigación aplicada colaborativa entre el Instituto de Investigación FLUMEN de la Universidad Politécnica de Catalunya (UPC), el Centro de Estudios Hidrográficos del CEDEX y DRAGADOS, con el objetivo de establecer los criterios hidráulicos para el diseño de rápidas escalonadas sin los tradicionales cajeros laterales que confinan el flujo (proyecto ALIVESCA)