Training deep retrieval models with noisy datasets

In this thesis we study loss functions that allow to train Convolutional Neural Networks (CNNs) under noisy datasets for the particular task of Content- Based Image Retrieval (CBIR). In particular, we propose two novel losses to fit models that generate global image representations. First, a Soft-Matching (SM) loss, exploiting both image content and meta data, is used to specialized general CNNs to particular cities or regions using weakly annotated datasets. Second, a Bag Exponential (BE) loss inspired by the Multiple Instance Learning (MIL) framework is employed to train CNNs for CBIR under noisy datasets. The first part of the thesis introduces a novel training framework that, relying on image content and meta data, learns location-adapted deep models that provide fine-tuned image descriptors for specific visual contents. Our networks, which start from a baseline model originally learned for a different task, are specialized using a custom pairwise loss function, our proposed SM loss, that uses weak labels based on image content and meta data. The experimental results show that the proposed location-adapted CNNs achieve an improvement of up to a 55% over the baseline networks on a landmark discovery task. This implies that the models successfully learn the visual clues and peculiarities of the region for which they are trained, and generate image descriptors that are better location-adapted. In addition, for those landmarks that are not present on the training set or even other cities, our proposed models perform at least as well as the baseline network, which indicates a good resilience against overfitting. The second part of the thesis introduces the BE Loss function to train CNNs for image retrieval borrowing inspiration from the MIL framework. The loss combines the use of an exponential function acting as a soft margin, and a MILbased mechanism working with bags of positive and negative pairs of images. The method allows to train deep retrieval networks under noisy datasets, by weighing the influence of the different samples at loss level, which increases the performance of the generated global descriptors. The rationale behind the improvement is that we are handling noise in an end-to-end manner and, therefore, avoiding its negative influence as well as the unintentional biases due to fixed pre-processing cleaning procedures. In addition, our method is general enough to suit other scenarios requiring different weights for the training instances (e.g. boosting the influence of hard positives during training). The proposed bag exponential function can bee seen as a back door to guide the learning process according to a certain objective in a end-to-end manner, allowing the model to approach such an objective smoothly and progressively. Our results show that our loss allows CNN-based retrieval systems to be trained with noisy training sets and achieve state-of-the-art performance. Furthermore, we have found that it is better to use training sets that are highly correlated with the final task, even if they are noisy, than training with a clean set that is only weakly related with the topic at hand. From our point of view, this result represents a big leap in the applicability of retrieval systems and help to reduce the effort needed to set-up new CBIR applications: e.g. by allowing a fast automatic generation of noisy training datasets and then using our bag exponential loss to deal with noise. Moreover, we also consider that this result opens a new line of research for CNN-based image retrieval: let the models decide not only on the best features to solve the task but also on the most relevant samples to do it.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Luis Salgado Álvarez de Sotomayor.- Secretario: Pablos Martínez Olmos.- Vocal: Ernest Valveny Llobe

Automatización de una línea de elaboración y acondicionamiento de fármacos

Este trabajo se basa en el diseño y automatización de una línea de elaboración y acondicionamiento de fármacos de forma que esta sea lo más eficiente posible.El desarrollo de este trabajo consta de diferentes apartados, el primero de ellos es la búsqueda de información acerca del sector farmacéutico para poder entender cómo funciona una planta farmacéutica. Después se realiza el diseño de la línea, en el que se seleccionan los elementos necesarios para la planta y se crea una distribución en planos lo más adecuada posible. Ya hecho el diseño se realiza la automatización de la línea de manera que se controlen los elementos a través de autómatas programables. En este caso se utiliza un SIMATIC S7-300 utilizando lenguaje de programación AWL. A continuación, se realiza un SCADA controlado a través de un HMI Panel utilizando WinCC Flexible.Por último, se realiza la programación de la paletización final de la línea por un robot industrial a través del simulador software específicoRobotStudio.<br /

Diseño de software para organización y gestión adaptativa de proyectos

Este trabajo está orientado a diseñar un software informático que permita gestionar de forma automática los recursos humanos en un proyecto. Se considera que esta gestión consiste en la asignación de trabajadores a las tareas de acuerdo a sus características y al estado del proyecto.Para poder automatizar un proceso, el primer paso consiste en desarrollar un modelo teórico de los elementos implicados. El modelado de los trabajadores y las tareas requiere, a su vez, del estudio de un modelo teórico. Se ha escogido el modelo de la gestión por competencias, ya que permite relacionar de forma efectiva los atributos de los trabajadores y las tareas. Este método permite asignar valores numéricos a las aptitudes de los trabajadores y a las necesidades de las tareas, por lo que se facilita su implantación en un sistema informático.Las competencias se emplean para determinar la eficacia de un trabajador en una tarea concreta. Sin embargo, son los conocimientos y destrezas del trabajador las que definen qué tareas puede realizar. Por lo tanto, se deben tener en cuenta ambas características, tanto del trabajador como de la tarea, para realizar el reparto de responsabilidades.Para demostrar la viabilidad del software diseñado y poner a prueba los algoritmos de gestión y asignación, se decide llevar a cabo una demostración práctica con los modelos. Este programa de prueba cuenta con las funciones necesarias para realizar la gestión y asignación de recursos en un proyecto. Además, esta aplicación sirve para adquirir una mayor información acerca de las necesidades de una implementación real a gran escala.En este programa de prueba se pueden introducir tareas, su duración correspondiente y las dependencias entre ellas para su posterior procesado. El primer cómputo consiste en realizar la organización temporal de las tareas, incluyendo el cálculo de la ruta crítica y las holguras temporales. Si también se introducen trabajadores al programa, este los asigna a cada tarea de acuerdo a sus conocimientos, destrezas y competencias. La aplicación comienza por la asignación de las tareas de la ruta crítica, y asigna siempre al trabajador disponible que se considere más adecuado.Tras verificar el correcto funcionamiento de la aplicación de demostración, se procede a realizar el diseño de un programa que permita la implementación a gran escala en una empresa real. Para ello resulta necesario estudiar factores que no afectan directamente a la aplicación de demostración. Entre ellos destacan el diseño de la arquitectura del sistema, los diferentes niveles de acceso, la estructura de la base de datos o la mayor cantidad de información que es necesario procesar.Se considera que la implementación de un software de estas características en una empresa real es posible, siempre que se realicen las modificaciones necesarias. Aun así, sería necesario llevar a cabo un periodo de pruebas y adaptación para asegurar el correcto funcionamiento. Esto sería más importante aún en el caso de integrar el software en un sistema ERP ya implantado. Su principal ventaja sería facilitar la gestión de proyectos y el trabajo del departamento de recursos humanos, resultando útil para empresas de cualquier tamaño.<br /

A Bayesian model for brain tumor classification using clinical-based features

Proceedings of: IEEE International Conference on Image Processing (ICIP 2014). Paris, October 27-30, 2014.This paper tackles the problem of automatic brain tumor classification from Magnetic Resonance Imaging (MRI) where, traditionally, general-purpose texture and shape features extracted from the Region of Interest (tumor) have become the usual parameterization of the problem. Two main contributions are made in this context. First, a novel set of clinical-based features that intend to model intuitions and expert knowledge of physicians is suggested. Second, a system is proposed that is able to fuse multiple individual scores (based on a particular MRI sequence and a pathological indicator present in that sequence) by using a Bayesian model that produces a global system decision. This approximation provides a quite flexible solution able to handle missing data, which becomes a very likely case in a realistic scenario where the number clinical tests varies from one patient to another. Furthermore, the Bayesian model provides extra information concerning the uncertainty of the final decision. Our experimental results prove that the use of clinical-based feature leads to a significant increment of performance in terms of Area Under the Curve (AUC) when compared to a state-of-the art reference. Furthermore, the proposed Bayesian fusion model clearly outperforms other fusion schemes, especially when few diagnostic tests are available.Publicad

Case Report: Prone Positioning and Nasal High Flow Oxygen Therapy - An Alternative Strategy to Invasive and Non-Invasive Ventilation in a Case of Severe Acute Respiratory Distress Syndrome

Acute respiratory distress syndrome (ARDS) is associated with high rates of mortality, which is directly attributed to the pulmonary inflammatory response then compromising gaseous exchange. This case study describes the successful management of a 63-year-old male with severe ARDS who received a strategy which involved the following interventions: Nasal High Flow Oxygen (NHFO) therapy, and prone positioning. It is thought that this strategy improved the lung volume at end expiration to an extent that the patient was able to avoid both noninvasive (NIV) and invasive mechanical ventilation (MV) (and their known associated risks). There is limited evidence describing the use of NHF therapy in patients with ARDS. The use of prone positioning has been demonstrated to significantly improve 28-day mortality in patients with severe ARDS with a PaO2/FiO2&lt; 150 mmHg. The authors acknowledge that until such time that controlled clinical trials considering the efficacy of strategy are conducted it would be premature to recommend it forall suchcases. The prone position is a promising therapy for patients with spontaneous ventilation with high-flow oxygen therapy; controlled and randomized studies should be done to demonstrate its safety and efficacy

Lyophilized biopolymeric beads of chitosan-xanthan with edible fungus Laccaria laccata (Scop.) Cooke as forest ectomycorrhizal biofertilizers

Objective: To evaluate whether the spores of the edible fungus Laccaria laccata (Scop.) Cooke encapsulated in a freeze-dried biopolymeric matrix of chitosan-xanthan are capable of causing ectomycorrhization in Pinus greggii Englem. trees in grenhouse. Methodology: Pearls were made with the biopolymer chitosan-xanthan, in which spores of the edible ectomycorrhizal fungus L. laccata were encapsulated. Embedded spores were analyzed using scanning electron microscopy to assess possible structural damage. Subsequently, these pearls were used as biofertilizers in a greenhouse bioassay using Pinus greggii plants to evaluate their ability to be ectomycorrhized. The bioassay lasted 270 days, when it was evaluated in order to check if there was ectomycorrhizal colonization, using stereoscopic and bright field microscopy. Additionally, it was evaluated if there was an increase in terms of growth in inoculated plants compared to non-inoculated plants 180 and 270 days after sowing. Results: The encapsulated spores of L. laccata in the biopolymeric matrix formed ectomycorrhizae in the P. greggii roots. The percentages of ectomycorrhizal colonization in the plants varied from 80 to 90%, demonstrating that the production of biopolymeric pearls with chitosan-xanthan are capable of maintaining the viability of the spores of the ectomycorrhizal fungus evaluated, and of extensively colonizing the roots of Pinus greggii. Limitations on study /Implications: Pearls encapsulated in a biopolymeric matrix containing spores of the fungus L. laccata are capable of inducing ectomycorrhization in trees of forest importance. Conclusions: Encapsulated spores of an edible ectomycorrhizal fungus in the chitosan-xanthan biopolymer have potential as a forest biofertilizer, which opens the opportunity for industrial scaling.Objective: To evaluate whether or not the spores of the edible fungus Laccaria laccata (Scop.) Cooke encapsulated in a lyophilized biopolymeric matrix of chitosan-xanthan can cause ectomycorrhization in Pinus greggii Englem. trees under greenhouse conditions. Methodology: Spores of the edible ectomycorrhizal fungus L. laccata were encapsulated in beads made with the chitosan-xanthan biopolymer. The embedded spores were analyzed using scanning electron microscopy to evaluate possible structural damage. Next, these beads were used as biofertilizers in a greenhouse bioassay using Pinus greggii plants to evaluate their ability to be ectomycorrhized. The bioassay lasted 270 days. Subsequently, stereoscopic and bright field microscopy was used to determine if the roots of the pines had been subjected to an ectomycorrhizal colonization. Additionally, the growth of inoculated plants was evaluated compared to non-inoculated plants, 180 and 270 days after sowing. Results: The spores of L. laccata encapsulated in the biopolymeric matrix formed ectomycorrhizae in the roots of P. greggii. The percentages of ectomycorrhizal colonization in the plants ranged from 80 to 90%, demonstrating that the production of chitosan-xanthan biopolymeric beads can maintain the viability of the spores of the ectomycorrhizal fungus evaluated and extensively colonize the roots of Pinus greggii. Study Limitations/Implications: The biopolymeric matrix beads that contain spores of the fungus L. laccata can induce ectomycorrhization in trees of forest importance. Conclusions: The spores of an edible ectomycorrhizal fungus encapsulated in the chitosan-xanthan biopolymer have potential as a forest biofertilizer, which opens the opportunity to scale its use up to an industrial level

Frecuencia de desórdenes mentales en adultos mayores residentes en una institución de asistencia social en la Ciudad de México

Resumen: Antecedentes: La Organización Mundial de la Salud ha informado que en los adultos mayores se incrementará y agravará la magnitud de los problemas de salud mental, lo que estará relacionado al incremento de su expectativa de vida y al aumento de las personas que alcanzarán edades avanzadas. Objetivos: Identificar y estimar la frecuencia de desórdenes mentales en adultos mayores. Material y Método: Estudio observacional, descriptivo y transversal. Se aplicó un cuestionario que incluía variables sociodemográficas y la Mini Entrevista Neuropsiquiátrica Internacional (M.I.N.I.). Población de estudio de 60 años y más, residentes en una Institución de Asistencia Social de la Ciudad de México. La muestra se seleccionó aleatoria y sistemáticamente, eligiendo una de cada cuatro. Participó personal previamente capacitado tanto en la metodología como en los procedimientos y aplicación del instrumento. Resultados: De la población de estudio, se obtuvo una muestra ponderada de 80 entrevistas completas (67%). En su mayoría fueron femeninos y viudas, con una media de edad de 80 años y 5 de escolaridad. Encontramos ausencia en el 30%; en un 40% sólo se reportó sintomatología y en el 30% restante se cubrieron diagnósticos psiquiátricos. Conclusiones: La salud mental y los desórdenes psiquiátricos han sido escasamente conocidos y estudiados en esta población. La entrevista MINI permitió identificar y estimar la frecuencia de síntomas y diagnósticos de desórdenes mentales. Nuestra estimación (30%) fue similar a la reportada en otro estudio (29.7%). La prevención, identificación, detección e intervención oportuna a los problemas de salud mental adquieren gran importancia en este contexto. Palabras clabe: Adultos mayores. Envejecimiento. Vejez. Desórdenes mentales. Mini Entrevista Neuropsiquiátrica Internacional. Abstract: Background: World Health Organization has reported that in old adults population will increase and aggravate the magnitude of mental health problems, which will be linked to the increase in his life expectancy and with the rise of individuals who reach old age. Objectives: identify and estimate the frequency of mental disorders in elderly people. Materials and Methods: Study observational, descriptive and transversal. It applies a questionnaire, which included socio-demographic variables and the Mini International Neuropsychiatric Interview (M.I.N.I.). Study population of persons aged 60 and over living in an Institution of Social Assistance in Mexico City, here were selected a systematic random sample, choosing one in four adults. The interviews were available staff previously trained in the handling of the methodology, procedures and application of the instrument Results: Out of a population study, resulting in a weighted sample of 80 completed interviews (67%). The main percentages were females and widower, with a mean age of 80 years and 5 of schooling. We find absence in the 30%, only 40% reported symptoms and the remaining 30% were filled psychiatric diagnoses. Conclusions: Mental health and psychiatric disorders has been scantily known and studied until this moment. The interview M.I.N.I. allowed us to identify and estimate their frequency of symptoms and diagnostics mental disorders. The frequency diagnostic of mental disorders found in our research (30%) is very similar to that obtained in another study (29.7%). In this context, the prevention, detection and opportune intervention for mental health problems are remarkable. Keywords: Elderly. Aging. Oldness. Mental disorders. Mini International Neuropsychiatric Interview

Immune microenvironment characterisation and dynamics during anti-HER2-based neoadjuvant treatment in HER2-positive breast cancer

Despite their recognised role in HER2-positive (HER2+) breast cancer (BC), the composition, localisation and functional orientation of immune cells within tumour microenvironment, as well as its dynamics during anti-HER2 treatment, is largely unknown. We here investigate changes in tumour-immune contexture, as assessed by stromal tumour-infiltrating lymphocytes (sTILs) and by multiplexed spatial cellular phenotyping, during treatment with lapatinib-trastuzumab in HER2+ BC patients (PAMELA trial). Moreover, we evaluate the relationship of tumour-immune contexture with hormone receptor status, intrinsic subtype and immune-related gene expression. sTIL levels increase after 2 weeks of HER2 blockade in HR-negative disease and HER2-enriched subtype. This is linked to a concomitant increase in cell density of all four immune subpopulations (CD3+, CD4+, CD8+, Foxp3+). Moreover, immune contexture analysis showed that immune cells spatially interacting with tumour cells have the strongest association with response to anti-HER2 treatment. Subsequently, sTILs consistently decrease at the surgery in patients achieving pathologic complete response, whereas most residual tumours at surgery remain inflamed, possibly reflecting a progressive loss of function of T cells. Understanding the features of the resulting tumour immunosuppressive microenvironment has crucial implications for the design of new strategies to de-escalate or escalate systemic therapy in early-stage HER2+ BC

Inappropriate antibiotic use in the COVID-19 era: Factors associated with inappropriate prescribing and secondary complications. Analysis of the registry SEMI-COVID

Background: Most patients with COVID-19 receive antibiotics despite the fact that bacterial co-infections are rare. This can lead to increased complications, including antibacterial resistance. We aim to analyze risk factors for inappropriate antibiotic prescription in these patients and describe possible complications arising from their use. Methods: The SEMI-COVID-19 Registry is a multicenter, retrospective patient cohort. Patients with antibiotic were divided into two groups according to appropriate or inappropriate prescription, depending on whether the patient fulfill any criteria for its use. Comparison was made by means of multilevel logistic regression analysis. Possible complications of antibiotic use were also identified. Results: Out of 13,932 patients, 3047 (21.6%) were prescribed no antibiotics, 6116 (43.9%) were appropriately prescribed antibiotics, and 4769 (34.2%) were inappropriately prescribed antibiotics. The following were independent factors of inappropriate prescription: February-March 2020 admission (OR 1.54, 95%CI 1.18-2.00), age (OR 0.98, 95%CI 0.97-0.99), absence of comorbidity (OR 1.43, 95%CI 1.05-1.94), dry cough (OR 2.51, 95%CI 1.94-3.26), fever (OR 1.33, 95%CI 1.13-1.56), dyspnea (OR 1.31, 95%CI 1.04-1.69), flu-like symptoms (OR 2.70, 95%CI 1.75-4.17), and elevated C-reactive protein levels (OR 1.01 for each mg/L increase, 95% CI 1.00-1.01). Adverse drug reactions were more frequent in patients who received ANTIBIOTIC (4.9% vs 2.7%, p < .001). Conclusion: The inappropriate use of antibiotics was very frequent in COVID-19 patients and entailed an increased risk of adverse reactions. It is crucial to define criteria for their use in these patients. Knowledge of the factors associated with inappropriate prescribing can be helpful