Metodología de estudio del aprendizaje de niños con parálisis cerebral en el uso de un ratón por movimientos de cabeza

This paper presents a methodology designed to evaluate the learning process for people with cerebral palsy (CP) who are asked to control a computer through an inertial interface. The interface allows users to control the mouse pointer and click with head movements. The metric proposed in order to objectively measure the process of learning is the “throughput”. This parameter has been widely used for the evaluation of pointing devices and is now applied for the first time to people with CP. The results obtained show that the metric can be used to quantify how the user is learning and therefore to assess the usability of the inertial device.[EN]Este artículo presenta un estudio piloto que introduce una metodología para valorar el aprendizaje de una persona con parálisis cerebral (PC) en el manejo del computador con una interfaz inercial, que permite el control del cursor y el clic mediante movimientos de cabeza. Se propone el uso de una métrica denominada rendimiento para medir objetivamente el proceso de aprendizaje. La métrica, ampliamente utilizada para la evaluación de dispositivos apuntadores, se aplica por primera vez en usuarios con PC. Los resultados obtenidos muestran cómo la métrica propuesta permite cuantificar el proceso de aprendizaje del usuario con PC, con lo que puede ser empleada para valorar la usabilidad del dispositivo inercial.[ES]Peer reviewe

Point-of-Care Ultrasound to Identify Rib Osteomyelitis in the Infants: a Case Report

The number of reported cases of rib osteomyelitis is very infrequent. Magnetic resonance is generally the best test in these cases, due to its high sensitivity and specifcity. However, given this technique has some drawbacks, it is usually restricted to cases of bad evolution. A relevant, easy to perform, bedside imaging test is the point of care ultrasound. We present the case of a 2-month-old infant with a rib osteomyelitis detected by point-of-care ultrasound in the context of sepsis after abdominal surgery. The thoracic ultrasound revealed a lesion adjacent to the right sixth rib and round extra-parenchymal collection in the right costophrenic sinus. Chest computed tomography confrmed the presence of a hypodense collection at the costochondral junction of the right seventh rib with pleural thickening and an increase in soft tissues, compatible with osteomyelitis. Our ultrasound fnding in the absence of specifc clinical data of rib osteomyelitis led us to a change in the duration of the antibiotic treatment already established and therefore likely led to an improvement in the patient’s prognosis. The ultrasound has gained increasing prominence due to its usefulness in diagnosis and monitoring, especially in pediatric intensive care, given the ease of use at the patient’s bedside

Cooperative Learning for Disaggregated Delay Modeling in Multidomain Networks

Accurate delay estimation is one of the enablers of future network connectivity services, as it facilitates the application layer to anticipate network performance. If such connectivity services require isolation (slicing), such delay estimation should not be limited to a maximum value defined in the Service Level Agreement, but to a finer-grained description of the expected delay in the form of, e.g., a continuous function of the load. Obtaining accurate end-to-end (e2e) delay modeling is even more challenging in a multi-operator (Multi-AS) scenario, where the provisioning of e2e connectivity services is provided across heterogeneous multi-operator (Multi-AS or just domains) networks. In this work, we propose a collaborative environment, where each domain Software Defined Networking (SDN) controller models intra-domain delay components of inter-domain paths and share those models with a broker system providing the e2e connectivity services. The broker, in turn, models the delay of inter-domain links based on e2e monitoring and the received intra-domain models. Exhaustive simulation results show that composing e2e models as the summation of intra-domain network and inter-domain link delay models provides many benefits and increasing performance over the models obtained from e2e measurements

The Carbonation of Wollastonite: A Model Reaction to Test Natural and Biomimetic Catalysts for Enhanced CO2 Sequestration

One of the most promising strategies for the safe and permanent disposal of anthropogenic CO2 is its conversion into carbonate minerals via the carbonation of calcium and magnesium silicates. However, the mechanism of such a reaction is not well constrained, and its slow kinetics is a handicap for the implementation of silicate mineral carbonation as an effective method for CO2 capture and storage (CCS). Here, we studied the different steps of wollastonite (CaSiO3) carbonation (silicate dissolution -> carbonate precipitation) as a model CCS system for the screening of natural and biomimetic catalysts for this reaction. Tested catalysts included carbonic anhydrase (CA), a natural enzyme that catalyzes the reversible hydration of CO2(aq), and biomimetic metal-organic frameworks (MOFs). Our results show that dissolution is the rate-limiting step for wollastonite carbonation. The overall reaction progresses anisotropically along different [hkl] directions via a pseudomorphic interface-coupled dissolution–precipitation mechanism, leading to partial passivation via secondary surface precipitation of amorphous silica and calcite, which in both cases is anisotropic (i.e., (hkl)-specific). CA accelerates the final carbonate precipitation step but hinders the overall carbonation of wollastonite. Remarkably, one of the tested Zr-based MOFs accelerates the dissolution of the silicate. The use of MOFs for enhanced silicate dissolution alone or in combination with other natural or biomimetic catalysts for accelerated carbonation could represent a potentially effective strategy for enhanced mineral CCS.This research was funded by the Spanish Government (grants CGL2015-70642-R, CGL2015-73103-EXP, CTQ2017-84692-R), EU FEDER funding, the University of Granada (“Unidad Científica de Excelencia” UCE-PP2016-05) and the Junta de Andalucía (grant P11-RNM-7550 and Research Group RNM-179). We thank the personnel of the Centro de Instrumentación Científica (CIC) of the University of Granada for their help during TG-DSC, FESEM, -XRD, and ICP-OES analyses

Evaluación del Impacto del Aprendizaje Auto-Supervisado en la Precisión de Interfaces Cerebro-Ordenador basadas en Imaginación Motora

Las interfaces cerebro-ordenador (BCIs) buscan proporcionar vías de comunicación directas entre el cerebro humano y dispositivos externos. No obstante, la decodificación precisa de las intenciones del usuario es todavía un desafío, en parte por las limitaciones inherentes a la electroencefalografía (EEG), como son una resolución espacial limitada y relación señal-ruido reducida. Este estudio aborda estos desafíos mediante la aplicación de técnicas de aprendizaje auto-supervisado (SSL) en el preentrenamiento de una red basada en la arquitectura de transformer. Nuestra aproximación descompone la señal EEG en segmentos y utiliza un enmascarado y reconstrucción para obtener representaciones más robustas y efectivas. Evaluamos el impacto de estas técnicas en la mejora de la clasificación de un sistema BCI basado en imaginación motora (MI) con una base de datos pública de 109 sujetos, utilizando un esquema de validación cruzada inter-sujeto k-fold (k=5). Comparamos tres escenarios diferentes: un modelo sin preentrenamiento SSL, un modelo con sondeo lineal de las características extraídas, y un modelo con fine tunning de toda la red. Nuestros resultados indican que el preentrenamiento con técnicas de SSL mejora significativamente la precisión de la clasificación de MI. Concretamente, la precisión se incrementa desde un 78.4%±12.2%, hasta un 79.9%±11.9% utilizando sondeo lineal, y alcanza un 82.4%±11.7% cuando se aplica fine tunning a toda la red. Este trabajo demuestra el potencial del SSL aplicado a redes basadas en transformer para avanzar en la interpretación de señales EEG.Este estudio ha sido financiado por los proyectos TED2021-129915B-I00, PID2020-115468RB-I00 y RTC2019-007350-1 financiadas por el Ministerio de Ciencia e Innovación/Agencia Estatal de investigación/10. 13039/501100011033/', FEDER Una forma de hacer Europa; y por ‘Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBERBBN)’ a través de ‘Instituto de Salud Carlos III’. S. Pérez-Velasco y D. Marcos-Martínez son beneficiarios de una ayuda PIF de la Consejería de Educación de la Junta de Castilla y León

Ianus: an Adpative FPGA Computer

Dedicated machines designed for specific computational algorithms can outperform conventional computers by several orders of magnitude. In this note we describe {\it Ianus}, a new generation FPGA based machine and its basic features: hardware integration and wide reprogrammability. Our goal is to build a machine that can fully exploit the performance potential of new generation FPGA devices. We also plan a software platform which simplifies its programming, in order to extend its intended range of application to a wide class of interesting and computationally demanding problems. The decision to develop a dedicated processor is a complex one, involving careful assessment of its performance lead, during its expected lifetime, over traditional computers, taking into account their performance increase, as predicted by Moore's law. We discuss this point in detail

Robust photometric redshift determinations of gamma-ray burst afterglows at z > 2

Theory suggests that about 10% of Swift-detected gamma-ray bursts (GRBs) will originate at redshifts greater than 5 yet a number of high redshift candidates may be left unconfirmed due to the lack of measured redshifts. Here we introduce our code, GRBz, a method of simultaneous multi-parameter fitting of GRB afterglow optical and near infrared, spectral energy distributions. It allows for early determinations of the photometric redshift, spectral index and host extinction to be made. We assume that GRB afterglow spectra are well represented by a power-law decay and model the effects of absorption due to the Lyman forest and host extinction. We use a genetic algorithm-based routine to simultaneously fit the parameters of interest, and a Monte Carlo error analysis. We use GRBs of previously determined spectroscopic redshifts to prove our method, while also introducing new near infrared data of GRB 990510 which further constrains the value of the host extinction. Our method is effective in estimating the photometric redshift of GRBs, relatively unbiased by assumptions of the afterglow spectral index or the host galaxy extinction. Monte Carlo error analysis is required as the method of error estimate based on the optimum population of the genetic algorithm underestimates errors significantly.Comment: Accepted to A&A: 8 pages, 5 figure

Augmented Reality App with AI-based Pervasive Latency Monitoring of RAN and Programmable Metro Packet-Optical Networks

Deep data plane programmability is exploited at different future 6G network technological segments to realize end-to-end application delay telemetry. For the first time, data analytics obtained by RAN controllers and metro network collectors are processed by a Multi Agent System running AI algorithms with the aim of detecting latency anomalies and their location in the network, suggesting the most appropriate recovery countermeasure. The demo is shown applied to Augmented Reality application with extreme low latency requirements

Efecto de las fuentes de polen sobre el rendimiento en la extracción de aceite y perfil de ácidos grasos de las semillas de dátil (Phoenix dactylifera L.) cultivar Medjool de México

The present investigation aimed to assess the effect of pollen sources on the mass, dimension, oil content and fatty acid profile of the seeds from female palms of the Medjool date cultivar. The palms were pollinated with Deglet Noor, Khadrawy, Medjool and Zahidi cultivars. In addition, three palms were pollinated as the treatment control. The fatty acids were evaluated by gas chromatography-mass spectrometry. The surface morphology of date seed powder was examined using SEM, before and after n-hexane interaction. The seeds of the Medjool treatment had the greatest mass (1.42 g), but the lowest oil content (5.37% w/w); the control seeds showed smaller mass (1.21 g), but higher oil content (13.57% w/w). The proportion of fatty acids varied significantly among the treatments with respect to the control. The most abundant fatty acids were oleic (C18:1), lauric (C12:0), myristic (C14:0), palmitic (C16:0), linoleic (C18:2), and stearic (C18:0). Together these fatty acids presented a composition between 98.3 and 98.67% for treatments, and 99.0% for the control. The results indicate that the pollen sources from Deglet Noor, Khadrawy, Medjool and Zahidi cultivars had a significant effect on mass, dimension, oil content and fatty acid profile of the seeds of the date cultivar Medjool. The date seed oil could be used as edible oil, in food products, and in pharmaceutical and cosmetic applications.La presente investigación tuvo como objetivo evaluar el efecto de las fuentes de polen, sobre la masa, dimensión, contenido de aceite y el perfil de ácidos grasos de las semillas de dátil del cultivar Medjool. Las palmas hembras del cultivar Medjool fueron polinizadas con cultivares Deglet Noor, Khadrawy, Medjool y Zahidi. Además, tres palmas fueron polinizadas como tratamiento control. Los ácidos grasos se evaluaron por cromatografía de gases-espectrometría de masas. La morfología de la superficie del polvo de semillas de dátil se examinó utilizando un equipo SEM, antes y después de la interacción n-hexano. Las semillas del tratamiento Medjool resultaron con mayor masa (1,42 g), pero menor contenido de aceite (5,37% p/p); la semilla control, mostró una masa más pequeña (1,21 g), pero un mayor contenido de aceite (13,57% p/p). La composición de ácidos grasos varió significativamente entre los tratamientos con respecto al control. Los ácidos grasos mayoritarios fueron: oleico (C18:1), láurico (C12:0), mirístico (C14:0), palmítico (C16:0), linoleico (C18:2) and esteárico (C18:0). En total, estos ácidos grasos alcanzan una composición entre 98.3 y 98.67% para los tratamientos, y 99.0% para el control. Los resultados indican que la fuente de polen de los cultivares Deglet Noor, Khadrawy, Medjool y Zahidi tiene un efecto significativo sobre la masa, dimensión, contenido de aceite y el perfil de ácidos grasos de la semilla del cultivar de dátil Medjool. El aceite de la semilla de dátil, podría usarse como aceite comestible, productos alimenticios, aplicaciones farmacéuticas y cosméticas

Fibrous Hamartoma of Infancy: A Series of 21 Cases and Review of the Literature

Introducción: El hamartoma fibroso de la infancia (HFI) es tumor poco frecuente de tejidos blandos en lactantes y niños, caracterizado histopatólogicamente por su morfología trifásica y curso benigno. Métodos: Presentamos las características histopatológicas e inmunohistoquímicas de una serie de 21 casos de HFI y revisamos sus principales diagnósticos diferenciales. Resultados: Las lesiones predominaron en varones con una edad media de 3,7 años (5 meses24 años) en localizaciones previamente descritas. Histopatológicamente, se caracterizaron por proporciones variables de tejido fibroblástico, mesenquimal y adiposo maduro. Tres casos (21%) mostraron zonas hialinizadas con artefactos en grietas, que imitaban al fibroblastoma de células gigantes. Presentaron tinción positiva para actina de músculo liso 8/13 (61%) en el componente fibroblástico, CD34 en 6/8 (75%) en el mesenquimal inmaduro y fibroblástico; y S100 en el tejido adiposo en 7/7 (100%). Conclusión: Nuestros hallazgos histopatológicos son superponibles a los descritos en series amplias. No obstante, la heterogeneidad clínica obliga a conocer las variantes de esta entidad dentro de su típica histomorfología trifásica, para lograr un correcto diagnóstico y manejo terapéutico.Background: Fibrous hamartoma of infancy (FHI) is a rare soft-tissue tumor usually seen in infants and young children. Histologically, the tumor is characterized by a triphasic morphology, and the clinical course is benign. Methods: We described the histopathologic and immunohistochemical features in a series of 21 cases of FHI and reviewed the main entities to consider in differential diagnosis. Results: Most patients in the series were male. The mean age was 3.7 years (range, 5 months---24 years), and lesions were found in locations that have been previously reported. Histopathologically, the tumors were composed of variable proportions of fibroblastic, mesenchymal, and mature adipose tissue. Three of the 13 immunohistochemically stained biopsies (14%) contained hyalinized zones with cracking artifacts, mimicking giant cell fibroblastoma. Eight of the 13 stained with smooth-muscle actin (61%) were positive in the fibroblastic component, 6 of the 8 stained with CD34 (75%) were positive in the immature mesenchymal and fibroblastic components, and all 7 stained with S100 were positive (100%) in adipose tissue. Conclusions: Our histopathologic findings are consistent with those described in larger series. However, in order to reach a precise diagnosis and plan treatment, clinical heterogeneity obliges us to become familiar with variations in the characteristic triphasic histology of FHI