A Model of Artificial Genotype and Norm of Reaction in a Robotic System

The genes of living organisms serve as large stores of information for replicating their behavior and morphology over generations. The evolutionary view of genetics that has inspired artificial systems with a Mendelian approach does not take into account the interaction between species and with the environment to generate a particular phenotype. In this paper, a genotype model is suggested to shape the relationship with the phenotype and the environment in an artificial system. A method to obtain a genotype from a population of a particular robotic system is also proposed. Finally, we show that this model presents a similar behavior to that of living organisms in what regards the concept of norm of reaction.This paper describes research done at the UJI Robotic Intelligence Laboratory. Support for this laboratory is provided in part by Ministerio de Econom´ıa y Competitividad (DPI2015-69041-R), by Generalitat Valenciana (PROMETEOII/2014/028) and by Universitat Jaume I (P1-1B2014-52, PREDOC/ 2013/06)

Predicting the internal model of a robotic system from its morphology

The estimation of the internal model of a robotic system results from the interaction of its morphology, sensors and actuators, with a particular environment. Model learning techniques, based on supervised machine learning, are widespread for determining the internal model. An important limitation of such approaches is that once a model has been learnt, it does not behave properly when the robot morphology is changed. From this it follows that there must exist a relationship between them. We propose a model for this correlation between the morphology and the internal model parameters, so that a new internal model can be predicted when the morphological parameters are modified. Di erent neural network architectures are proposed to address this high dimensional regression problem. A case study is analyzed in detail to illustrate and evaluate the performance of the approach, namely, a pan-tilt robot head executing saccadic movements. The best results are obtained for an architecture with parallel neural networks due to the independence of its outputs. Theses results can have a great significance since the predicted parameters can dramatically speed up the adaptation process following a change in morpholog

Robot depth estimation inspired by fixational movements

Distance estimation is a challenge for robots, human beings and other animals in their adaptation to changing environments. Different approaches have been proposed to tackle this problem based on classical vision algorithms or, more recently, deep learning. We present a novel approach inspired by mechanisms involved in fixational movements to estimate a depth image with a monocular camera. An algorithm based on microsaccades and head movements during visual fixation is presented. It combines the images generated by these micromovements with the ego-motion signal, to compute the depth map. Systematic experiments using the Baxter robot in the Gazebo/ROS simulator are described to test the approach in two different scenarios, and evaluate the influence of its parameters and its robustness in the presence of noise

Integrating sensor models in deep learning boosts performance: application to monocular depth estimation in warehouse automation

Deep learning is the mainstream paradigm in computer vision and machine learning, but performance is usually not as good as expected when used for applications in robot vision. The problem is that robot sensing is inherently active, and often, relevant data is scarce for many application domains. This calls for novel deep learning approaches that can offer a good performance at a lower data consumption cost. We address here monocular depth estimation in warehouse automation with new methods and three different deep architectures. Our results suggest that the incorporation of sensor models and prior knowledge relative to robotic active vision, can consistently improve the results and learning performance from fewer than usual training samples, as compared to standard data-driven deep learning

Dos intents metodològics d'apropar els recursos arqueològics a l'aula

La voluntat de millorar la infraestructura museística per part dels responsables del Museu d'Alcoi, i el treball coordinat amb un grup de professors adscrits al CEP de la mateixa localitat, ha fet realitat l'elaboració de materials didàctics adients per apropar el museu - i amb ell la història- al públic escolar. Aquesta comunicació mostra les possibilitats divulgatives que emanen d'un treball a dues bandes, ensenyants i arqueòlegs, que fructifica en la realitat d'uns serveis pedagògics a l'abast dels centres educatius que desitgin aproparse al Museu.La voluntad de mejorar la infraestructura museística por parte de los responsables del Museo de Alcoi, y el trabajo coordinado con un grupo de professores adscritos al CEP de la misma localidad, ha hecho realidad la elaboración de materiales didácticos adecuados para acercar el museo - i con él la historia- al público escolar. Esta comunicación muestra las posibilidades divulgativas que emanan de un trabajo a dos bandas, enseñantes y arqueólogos, que fructifica en la realidad de unos servicios pedagógicos al alcance de los centros educativos que deseen acercarse al Museo

Quantum simulation of Anderson and Kondo lattices with superconducting qubits

We introduce a mapping between a variety of superconducting circuits and a family of Hamiltonians describing localized magnetic impurities interacting with conduction bands. This includes the Anderson model, the single impurity one- and two-channel Kondo problem, as well as the 1D Kondo lattice. We compare the requirements for performing quantum simulations using the proposed circuits to those of universal quantum computation with superconducting qubits, singling out the specific challenges that will have to be addressed.Comment: Longer versio

Caracterización de una red hídrica fuertemente alterada : el caso del arroyo de El Partido

En el ámbito de la hidrología fluvial y los eventos torrenciales que ocurren en los cauces, hay situaciones en las que la simple caracterización de la red hídrica no es obvia. Este es el caso del arroyo del Partido y la gran llanura de sedimentación sobre la que se asienta. La primera alteración del régimen hidráulico natural del lugar se llevó a cabo en 1981, con la construcción de un encauzamiento que provocó un gran desequilibrio sedimentario y serias alteraciones geomorfológicas en las décadas siguientes; tanto en la aldea de El Rocío como en el Parque Nacional de Doñana. Estudios realizados en el lugar, pusieron de manifiesto que el comportamiento original de la red hídrica comprendía la participación de otro cauce aledaño en los momentos de avenida, que hacía imprescindible su incorporación en un proyecto de restauración que se llevó a cabo en 2006. La observación de relevamientos del terreno de estudios precedentes y la experiencia en el lugar, junto con la inclusión más recientemente de herramientas informáticas de manejo de información detallada del terreno, a partir de tecnología LIDAR y la simulación hidráulica en 2D con software especializado (IBER); ha permitido realizar la caracterización de la red hídrica más completa hasta el momento de este paraje geomorfológicamente complejo. Ello se ha obtenido, no solamente para la situación restaurada presente, sino también para los momentos anteriores al encauzamiento y a los periodos entre éste y las obras de restauración

Super-Nernstian Shifts of Interfacial Proton-Coupled Electron Transfers : Origin and Effect of Noncovalent Interactions

The support of the University of Aberdeen is gratefully acknowledged. C.W. acknowledges a summer studentship from the Carnegie Trust for the Universities of Scotland. E.P.M.L. acknowledges SeCYT (Universidad Nacional de Cordoba), ́ CONICET- PIP 11220110100992, Program BID (PICT 2012-2324), and PME 2006-01581 for financial support.Peer reviewedPostprin

From caging to Rouse dynamics in polymer melts with intramolecular barriers: a critical test of the Mode Coupling Theory

By means of computer simulations and solution of the equations of the Mode Coupling Theory (MCT), we investigate the role of the intramolecular barriers on several dynamic aspects of non-entangled polymers. The investigated dynamic range extends from the caging regime characteristic of glass-formers to the relaxation of the chain Rouse modes. We review our recent work on this question, provide new results and critically discuss the limitations of the theory. Solutions of the MCT for the structural relaxation reproduce qualitative trends of simulations for weak and moderate barriers. However a progressive discrepancy is revealed as the limit of stiff chains is approached. This disagreement does not seem related with dynamic heterogeneities, which indeed are not enhanced by increasing barrier strength. It is not connected either with the breakdown of the convolution approximation for three-point static correlations, which retains its validity for stiff chains. These findings suggest the need of an improvement of the MCT equations for polymer melts. Concerning the relaxation of the chain degrees of freedom, MCT provides a microscopic basis for time scales from chain reorientation down to the caging regime. It rationalizes, from first principles, the observed devations from the Rouse model on increasing the barrier strength. These include anomalous scaling of relaxation times, long-time plateaux, and non-monotonous wavelength dependence of the mode correlators.Comment: 15 pages, 14 figure

A data generator for covid-19 patients’ care requirements inside hospitals

[EN] A Spanish version of the article is provided (see section before references). This paper presents the generation of a plausible data set related to the needs of COVID-19 patients with severe or critical symptoms. Possible illness’ stages were proposed within the context of medical knowledge as of January 2021. The parameters chosen in this data set were customized to fit the population data of the Valencia region (Spain) with approximately 2.5 million inhabitants. They were based on the evolution of the pandemic between September 2020 and March 2021, a period that included two complete waves of the pandemic. Contrary to expectation and despite the European and national transparency laws (BOE-A2013-12887, 2013; European Parliament and Council of the European Union, 2019), the actual COVID-19 pandemic-related data, at least in Spain, took considerable time to be updated and made available (usually a week or more). Moreover, some relevant data necessary to develop and validate hospital bed management models were not publicly accessible. This was either because these data were not collected, because public agencies failed to make them public (despite having them indexed in their databases), the data were processed within indicators and not shown as raw data, or they simply published the data in a format that was difficult to process (e.g., PDF image documents versus CSV tables). Despite the potential of hospital information systems, there were still data that were not adequately captured within these systems. Moreover, the data collected in a hospital depends on the strategies and practices specific to that hospital or health system. This limits the generalization of "real" data, and it encourages working with "realistic" or plausible data that are clean of interactions with local variables or decisions (Gunal, 2012; Marin-Garcia et al., 2020). Besides, one can parameterize the model and define the data structure that would be necessary to run the model without delaying till the real data become available. Conversely, plausible data sets can be generated from publicly available information and, later, when real data become available, the accuracy of the model can be evaluated (Garcia-Sabater and Maheut, 2021). This work opens lines of future research, both theoretical and practical. From a theoretical point of view, it would be interesting to develop machine learning tools that, by analyzing specific data samples in real hospitals, can identify the parameters necessary for the automatic prototyping of generators adapted to each hospital. Regarding the lines of research applied, it is evident that the formalism proposed for the generation of sound patients is not limited to patients affected by SARS-CoV-2 infection. The generation of heterogeneous patients can represent the needs of a specific population and serve as a basis for studying complex health service delivery systems.[ES] En este trabajo se presenta cómo se ha generado un conjunto de datos verosímiles relacionados con las necesidades de pacientes covid-19 con síntomas severe or critical. Se considerarán las etapas posibles con los conocimientos médicos a fecha de enero de 2021. Los parámetros elegidos en este data set están personalizados para adecuarse a los valores poblacionales de la región de Valencia (Spain), unos 2.5 Millones de habitantes y la evolución de la pandemia entre los meses de septiembre 2020 y marzo 2021, un periodo de tiempo que contemple dos olas completas de pandemia.En contra de lo que cabría esperar, a pesar de la ley de transparencia europea y nacional (BOE-A-2013-12887, 2013; Parlamento Europeo y del Consejo de la Unión Europea, 2019), los datos reales relacionados con la pandemia covid-19, al menos en España, tardan mucho en actualizarse y estar disponibles (normalmente una semana o más días). Además, algunos datos relevantes para trabajar los modelos de gestión de camas de hospital no están accesibles públicamente. Bien porque no se hayan recogido esos datos, o porque los organismos públicos no los ofrecen (a pesar de tenerlos indexados en sus bases de datos), o los ofrecen camuflados en indicadores procesados y no muestran los datos en bruto, o simplemente los publican en un formato de difícil reutilización (por ejemplo, en documentos PDF en lugar de en tablas CSV). A pesar de que los sistemas de información de los hospitales son bastante potentes, siguen existiendo datos que ni siquiera están recogidos adecuadamente en el sistema de información de salud.Por otra parte, los datos recogidos en un hospital dependen de las estrategias y practicas propias de ese hospital o sistema de salud. Este efecto limita la generalización de los datos “reales” y es necesario trabajar con datos “realistas” o verosímiles que están limpios de interacciones con variables o decisiones locales (Gunal, 2012; Marin-Garcia et al., 2020). Por un lado, se puede parametrizar el modelo y definir la estructura de datos que sería necesaria para ejecutar el modelo con datos reales. Por otro lado, se pueden generar conjuntos de datos verosímiles a partir de la información pública disponible y, posteriormente, cuando se disponga de los datos reales evaluar la bondad del modelo (Garcia-Sabater & Maheut, 2021).Marin-Garcia, JA.; Ruiz, A.; Julien, M.; Garcia-Sabater, JP. (2021). A data generator for covid-19 patients’ care requirements inside hospitals. WPOM-Working Papers on Operations Management. 12(1):76-115. https://doi.org/10.4995/wpom.1533276115121Alexander, G. L. (2007). The nurse-patient trajectory framework. Medinfo. MEDINFO, 12(Pt 2), 910- 914.Belciug, S., Bejinariu, S. I., & Costin, H. (2020). An artificial immune system approach for a multicompartment queuing model for improving medical resources and inpatient bed occupancy in pandemics. 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