Improvement of the sensory and autonomous capability of robots through olfaction: the IRO Project

Proyecto de Excelencia Junta de Andalucía TEP2012-530Olfaction is a valuable source of information about the environment that has not been su ciently exploited in mobile robotics yet. Certainly, odor information can contribute to other sensing modalities, e.g. vision, to successfully accomplish high-level robot activities, such as task planning or execution in human environments. This paper describes the developments carried out in the scope of the IRO project, which aims at making progress in this direction by investigating mechanisms that exploit odor information (usually coming in the form of the type of volatile and its concentration) in problems like object recognition and scene-activity understanding. A distinctive aspect of this research is the special attention paid to the role of semantics within the robot perception and decisionmaking processes. The results of the IRO project have improved the robot capabilities in terms of efciency, autonomy and usefulness.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Analyzing interference between RGB-D cameras for human motion tracking

Multi-camera RGB-D systems are becoming popular as sensor setups in Computer Vision applications but they are prone to cause interference between them, compromising their accuracy. This paper extends previous works on the analysis of the noise introduced by interference with new and more realistic camera configurations and different brands of devices. As expected, the detected noise increases as distance and angle grows, becoming worse when interference is present. Finally, we evaluate the effectiveness of the proposed solutions of using DC vibration motors to mitigate them. The results of this study are being used to assess the effect of interference when applying these setups to human motion tracking.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Plan Propio de Investigación de la UMA. Junta de Andalucía, proyecto TEP2012-53

Charge model of four-terminal 2D semiconductor FETs

A charge model for four-terminal two-dimensional (2D) semiconductor based field-effect transistors (FETs) is proposed. The model is suitable for describing the dynamic response of these devices under time-varying terminal voltage excitations.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No GrapheneCore2 785219, and from Ministerio de Economía y Competitividad under GrantsTEC2015-67462-C2-1-Rand TEC2017-89955-R(MINECO/FEDER)

Sistemas Avanzados de Asistencia al Conductor

El control inteligente de vehículos autónomos es uno de los retos actuales más importantes de los Sistemas Inteligentes de Transporte. La aplicación de técnicas de inteligencia artificial para la gestión automática de los actuadores del vehículo permite a los diferentes sistemas avanzados de asistencia al conductor (ADAS) y a los sistemas de conducción autónoma, realizar una gestión de nivel bajo de una manera muy similar a la de los conductores humanos, mejorando la seguridad y el confort. En este artículo se presenta un esquema de control para gestionar estos actuadores de bajo nivel del vehículo (dirección, acelerador y freno). Este sistema automático de control de bajo nivel se ha definido, implementado y probado en un vehículo Citroën C3 Pluriel, cuyos actuadores han sido automatizados y pueden recibir señales de control desde un ordenador de a bordo

Slackwater sediments record the increase in sub-daily rain flood due to climate change in a European Mediterranean catchment

In this work we propose an original method to determine the magnitude of the discharge, the intensity of the precipitation and the duration of short-rain floods in small torrential basins (< 2000 km2), extending our earlier approach for long-rain floods in larger basins (Water 2016, 8, 526; Remote Sens. 2017, 9, 727). The studied areas are located in ungauged catchments with high erosion rates where torrents deposit slackwater sediments near the outlet of the basins. Such deposits and erosive morphologies allow us to analyse sub-daily extreme hydrological events by combining standard techniques in paleohydrology, the kinematic wave method and remote-sensed paleostage indicators. The formulation was correctly verified in extreme events through reliable gauge measurements and a high-resolution distributed hydrological model showing the accuracy of our calculations (10% ≤ relative error ≤ 22%). In catchments of the European Mediterranean region where the frequency and magnitude of short-rain floods are increasing (e.g. the Guadalquivir Basin), the main hydrological variables can thus be quantified post-event using the proposed approach. The outputs may serve to construct a new database for this kind of events complementary to the existing daily database for long-rain floods (> 24 h). The need is evident for safety designs of civil infrastructures and flood risk mitigation strategies in the current climate change scenario.This work was supported by the Spanish Ministry of Science, Innovation and Universities (MICINN/FEDER, UE) under Grant SEDRETO CGL2015-70736-R. J.D.d.M.E. was supported by the PhD scholarship BES-2016-079117 (MINECO/FSE, UE) from the Spanish National Programme for the Promotion of Talent and its Employability (call 2016)

Tutorial para el reconocimiento de objetos basado en características empleando herramientas Phyton

El reconocimiento de objetos es algo innato en el ser humano. Cuando las personas miramos una fotografía, somos capaces de detectar sin esfuerzo elementos como animales, señales, objetos de interés, etc. En el campo de la visión por computador este proceso se lleva a cabo mediante herramientas de Inteligencia Artificial, con el fin de obtener información sobre el contenido de una imagen. Esta tarea, aunque ampliamente investigada, a un sigue siendo un campo de estudio activo debido a los grandes retos que conlleva: la detección de objetos en distintas condiciones luminosas, con posibles oclusiones, distintos tamaños y perspectivas, etc. Este artículo describe las tareas a completar en el desarrollo de un sistema de reconocimiento de objetos exitoso, y proporciona al lector una serie de directrices prácticas sobre como realizarlas. El trabajo viene acompañado de una serie de scripts Python para experimentar con las diferentes técnicas descritas, pretendiendo servir de apoyo en tareas docentes o de iniciación a cualquier entusiasta en la materia.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Este trabajo se ha desarrollado en el marco del proyecto WISER (DPI2017-84827-R), financiado por el Ministerio de Ciencia e Innovación contando con fondos del Fondo Europeo de Desarrollo Regional (FEDER)

Causal Scoring Medical Image Explanations: A Case Study On Ex-vivo Kidney Stone Images

On the promise that if human users know the cause of an output, it would enable them to grasp the process responsible for the output, and hence provide understanding, many explainable methods have been proposed to indicate the cause for the output of a model based on its input. Nonetheless, little has been reported on quantitative measurements of such causal relationships between the inputs, the explanations, and the outputs of a model, leaving the assessment to the user, independent of his level of expertise in the subject. To address this situation, we explore a technique for measuring the causal relationship between the features from the area of the object of interest in the images of a class and the output of a classifier. Our experiments indicate improvement in the causal relationships measured when the area of the object of interest per class is indicated by a mask from an explainable method than when it is indicated by human annotators. Hence the chosen name of Causal Explanation Score (CaES

Mind the numt: Finding informative mitochondrial markers in a giant grasshopper genome

H2020 Marie Sklodowska-Curie Actions, Grant/Award Number: 658706; Ministerio de Ciencia, Innovacion y Universidades, Grant/Award Number: PID2019-104952GB-I00/AEI/10.13039/501100011033The barcoding of the mitochondrial COX1 gene has been instrumental in cataloguing the tree of life, and in providing insights in the phylogeographic history of species. Yet, this strategy has encountered difficulties in major clades characterized by large genomes, which contain a high frequency of nuclear pseudogenes originating from the mitochondrial genome (numts). Here, we use the meadow grasshopper (Chorthippus parallelus), which possesses a giant genome of ~13 Gb, to identify mitochondrial genes that are underrepresented as numts, and test their use as informative phylogeographic markers. We recover the same full mitochondrial sequence using both whole genome and transcriptome sequencing, including functional protein‐coding genes and tRNAs. We show that a region of the mitogenome containing the COX1 gene, typically used in DNA barcoding, has disproportionally higher diversity and coverage than the rest of the mitogenome, consistent with multiple insertions of that region into the nuclear genome. By designing new markers in regions of less elevated diversity and coverage, we identify two mitochondrial genes that are less likely to be duplicated as numts. We show that, while these markers show high levels of incomplete lineage sorting between subspecies, as expected for mitochondrial genes, genetic variation reflects their phylogeographic history accurately. These findings allow us to identify useful mitochondrial markers for future studies in C. parallelus, an important biological system for evolutionary biology. More generally, this study exemplifies how non‐PCR‐based methods using next‐generation sequencing can be used to avoid numts in species characterized by large genomes, which have remained challenging to study in taxonomy and evolution.H2020 Marie Sklodowska-Curie Actions 658706Ministerio de Ciencia, Innovacion y Universidades PID2019-104952GB-I00/AEI/10.13039/50110001103

Negative Clinical Evolution in COVID-19 Patients Is Frequently Accompanied With an Increased Proportion of Undifferentiated Th Cells and a Strong Underrepresentation of the Th1 Subset

The severity of SARS-CoV-2 infection has been related to uncontrolled inflammatory innate responses and impaired adaptive immune responses mostly due to exhausted T lymphocytes and lymphopenia. In this work we have characterized the nature of the lymphopenia and demonstrate a set of factors that hinder the effective control of virus infection and the activation and arming of effector cytotoxic T CD8 cells and showing signatures defining a high-risk population. We performed immune profiling of the T helper (Th) CD4+ and T CD8+ cell compartments in peripheral blood of 144 COVID-19 patients using multiparametric flow cytometry analysis. On the one hand, there was a consistent lymphopenia with an overrepresentation of non-functional T cells, with an increased percentage of naive Th cells (CD45RA+, CXCR3-, CCR4-, CCR6-, CCR10-) and persistently low frequency of markers associated with Th1, Th17, and Th1/Th17 memory-effector T cells compared to healthy donors. On the other hand, the most profound alteration affected the Th1 subset, which may explain the poor T cells responses and the persistent blood virus load. Finally, the decrease in Th1 cells may also explain the low frequency of CD4+ and CD8+ T cells that express the HLA-DR and CD38 activation markers observed in numerous patients who showed minimal or no lymphocyte activation response. We also identified the percentage of HLA-DR+CD4+ T cells, PD-1+CD+4/CD8+ T cells in blood, and the neutrophil/lymphocyte ratio as useful factors for predicting critical illness and fatal outcome in patients with confirmed COVID-1