D-mannose transport and metabolism in isolated enterocytes

D-mannose transport and metabolism has been studied in enterocytes isolated from chicken small intestine. In the presence of Na+, the mannose taken up by the cells either remains free, is phosphorylated, is catabolized to H2O, or becomes part of membrane components. The mannose remaining free in the cytosol is released when the cells are transferred to an ice bath. The Na+-dependent D-mannose transport is electrogenic and inhibited by ouabain and dinitrophenol; its substrate specificity differs from SGLT-1 transporter. The Glut2 transporter inhibitors phloretin and cytochalasin B added following 30-min mannose uptake reduced the previously accumulated D-mannose, whereas these two agents increased the cell to external medium 3-O-methyl-glucose (3-OMG) concentration ratio. D-mannose efflux rate from preloaded D-[2-3H]-mannose enterocytes is Na+-independent. Phloretin did not affect D-mannose efflux rate, whereas it inhibited that of 3-OMG. Neither mannose uptake nor efflux rate were affected by fructose. It is concluded that part of the mannose taken up by the enterocytes is rapidly metabolized and that enterocytes have two D-mannose transport systems: one is concentrative and Na+-dependent and the other is Na+-independent and passive.Dirección General de Investiagación Científica y Técnica PM99-012

Sensorless unbalance correction as an ancillary service for LV 4-Wire/3-Phase power converters

IEEE Energy Conversion Congress and Exposition (9th. 2017. Cincinnati

Sensorless Unbalance Modelling and Estimation as an Ancillary Service for LV 4-Wire/3-Phase Power Converters

This paper describes a method to provide LV four-wire three-phase power converters with the capability of unbalance estimation as an ancillary service to the main role that they play in the distribution system (distributed generator, energy storage system, drive, etc). Typically, dedicated grid/load current sensors are needed to effectively comply with unbalance compensation tasks, increasing system cost and reducing reliability. This is due to the difficulties that arises in the extraction of the zero and negative voltage components from the voltages at the point of common coupling, such as the inadequate resolution of full-scaled voltage sensors and limited spectral separation. In this paper, the proposed method does not rely on additional sensors to those typically used in VSCs, and in any case, those sensors are limited to the point of connection of the power converter. Impedance estimation only using converter-side current sensors is implemented by adding a high frequency voltage excitation over the fundamental command. A new model approach is proposed for the real-time extraction of system impedance using a complex-valued compact form. Considering the voltage source at that frequency to be unique in the grid, it will be proved the impedance can be estimated and, thus, the resulting negative sequence current which is used for unbalance compensation. For the zero sequence, an especial arrangement of the converter voltage sensors together with a repetitive controller is used

Approaching Sentiment Analysis by Using Semi-supervised Learning of Multidimensional Classifiers

Sentiment Analysis is defined as the computational study of opinions, sentiments and emotions expressed in text. Within this broad field, most of the work has been focused on either Sentiment Polarity classification, where a text is classified as having positive or negative sentiment, or Subjectivity classification, in which a text is classified as being subjective or objective. However, in this paper, we consider instead a real-world problem in which the attitude of the author is characterised by three different (but related) target variables: Subjectivity, Sentiment Polarity, Will to Influence, unlike the two previously stated problems, where there is only a single variable to be predicted. For that reason, the (uni-dimensional) common approaches used in this area yield suboptimal solutions to this problem. In order to bridge this gap, we propose, for the first time, the use of the novel multi-dimensional classification paradigm in the Sentiment Analysis domain. This methodology is able to join the different target variables in the same classification task so as to take advantage of the potential statistical relations between them. In addition, and in order to take advantage of the huge amount of unlabelled information available nowadays in this context, we propose the extension of the multi-dimensional classification framework to the semi-supervised domain. Experimental results for this problem show that our semi-supervised multi-dimensional approach outperforms the most common Sentiment Analysis approaches, concluding that our approach is beneficial to improve the recognition rates for this problem, and in extension, could be considered to solve future Sentiment Analysis problems

Na+-dependent D-mannose transport at the apical membrane of rat small intestine and kidney cortex

The presence of a Na+/D-mannose cotransport activity in brush-border membrane vesicles (BBMV), isolated from either rat small intestine or rat kidney cortex, is examined. In the presence of an electrochemical Na+ gradient, but not in its absence, D-mannose was transiently accumulated by the BBMV. D-Mannose uptake into the BBMV was energized by both the electrical membrane potential and the Na+ chemical gradient. D-Mannose transport vs. external D-mannose concentration can be described by an equation that represents a superposition of a saturable component and another component that cannot be saturated up to 50 μM D-mannose. D-Mannose uptake was inhibited by D-mannose ≫ D-glucose > phlorizin, whereas for α-methyl glucopyranoside the order was D-glucose = phlorizin ≫ D-mannose. The initial rate of D-mannose uptake increased as the extravesicular Na+ concentration increased, with a Hill coefficient of 1, suggesting that the Na+ :D-mannose cotransport stoichiometry is 1:1. It is concluded that both rat intestinal and renal apical membrane have a concentrative, saturable, electrogenic and Na+-dependent D-mannose transport mechanism, which is different from SGLT1.Dirección General de Investigaciones Científicas y Técnicas PM99-012

Online Impedance Estimation in AC Grids Considering Parallel-Connected Converters

IEEE Energy Conversion Congress and Exposition (ECCE) (10th, 2018, Portland, USA

Energy efficiency in Edge TPU vs. embedded GPU for computer-aided medical imaging segmentation and classification

Manuscrito enviado para su revisión por la revista "Engineering Applications of Artificial Intelligence" (Elsevier) el 25 de noviembre de 2022. Se envió la versión revisada el 26 de julio de 2023. El manuscrito fue aceptado el 11 de octubre de 2023, y desde el 28 de octubre aparece el artículo publicado en el portal ScienceDirect (https://doi.org/10.1016/j.engappai.2023.107298).In this work, we evaluate the energy usage of fully embedded medical diagnosis aids based on both segmentation and classification of medical images implemented on Edge TPU and embedded GPU processors. We use glaucoma diagnosis based on color fundus images as an example to show the possibility of performing segmentation and classification in real time on embedded boards and to highlight the different energy requirements of the studied implementations. Several other works develop the use of segmentation and feature extraction techniques to detect glaucoma, among many other pathologies, with deep neural networks. Memory limitations and low processing capabilities of embedded accelerated systems (EAS) limit their use for deep network-based system training. However, including specific acceleration hardware, such as NVIDIA’s Maxwell GPU or Google’s Edge TPU, enables them to perform inferences using complex pre-trained networks in very reasonable times. In this study, we evaluate the timing and energy performance of two EAS equipped with Machine Learning (ML) accelerators executing an example diagnostic tool developed in a previous work. For optic disc (OD) and cup (OC) segmentation, the obtained prediction times per image are under 29 and 43 ms using Edge TPUs and Maxwell GPUs respectively. Prediction times for the classification subsystem are lower than 10 and 14 ms for Edge TPUs and Maxwell GPUs respectively. Regarding energy usage, in approximate terms, for OD segmentation Edge TPUs and Maxwell GPUs use 38 and 190 mJ per image respectively. For fundus classification, Edge TPUs and Maxwell GPUs use 45 and 70 mJ respectively.Manuscrito de 33 páginas

La Parcialidad de las Medidas de Actualización de Balances Analizada Mediante Un Estudio de las Ausencias más Significativas en la Normativa de 1996: The Partiality of the Balance Sheet Updating Measures, Via a Study of the Most lmportant Absences in the 1996 Law

We think that the balance sheet updating of 1996, adjusted nearly exclusively to the revaluation of the material fixed assets, means, from an accounting point of view, a partial solution to the inflation problem. To give credit to such a hypothesis, we choose the main balance sheet items which, being affected equally by price variations, stay away from their scope -intangible fixed assets, stocks, securities, reversion Fund, and we analyze them having as an aim to determine whether it is justifiable or not, from an economical point of view, the rectification of their values. We can find reasoning behind all of them; although we find out likewise that the solution to inflation effects, in particular certain cases, in the future they will probably have to undergo a deep revision of the criteria in the valuation that they adopt nowadays.La actualización de balances de 1996, por ceñirse casi en exclusiva a la revalorización del inmovilizado material entendemos que contablemente supone una solución parcial al problema de la inflación. Para acreditar dicha hipótesis escogemos las principales partidas del balance que, estando afectadas igualmente por las variaciones de precios, quedan fuera de su ámbito -inmovilizado inmaterial, existencias, valores mobiliarios, Fondo de reversión-, y las analizamos con el fin de determinar si desde un punto de vista económico es justificable o no la rectificación de sus valores. En todas hallamos argumentos para su revaluación, aunque descubrimos asimismo que la solución a los efectos inflacionistas, en particular respecto a ciertos casos, posiblemente tenga que pasar en adelante por una revisión profunda de los criterios de valoración aplicados hoy día

Redes neuronales y patrones de analogías aplicados al downscaling en modelos climáticos

Ponencia presentada en: I Congreso de la Asociación Española de Climatología “La climatología española en los albores del siglo XXI”, celebrado en Barcelona del 1 al 3 de diciembre de 1999.[ES]Este artículo describe un sistema experto para la simulación climática local utilizando las salidas de los modelos climáticos sobre un área limitada supra-peninsular y buscando analogías en las bases de datos de cada modelo. Éste conjunto de analogías entrena a una red neuronal sobre los datos locales de cualquier observatorio resultando un sistema objetivo para interpretar localmente las salidas de los modelos climáticos.[EN]This article describes an expert system for the climatic simulation using the low resolution outputs of the climatic models ver a supra-peninsular limited area and looking for similar configurations in the data bases of each model. These allow to train a neural net using the local data of any observatory as output. It provides an objective system in order to interpret the outputs of the climatic models locally