Vestimentas compartidas y otros cuidados : Las formas de la generosidad en el Ms. K-III-4 (Libro de Apolonio, Vida de Santa María Egipciaca, Libre dels tres reys d'Orient)

El artículo lleva a cabo una revisión de las formas de la generosidad presentes en los tres poemas que componen el Ms. K-III-4 de la Biblioteca de San Lorenzo de El Escorial (Libro de Apolonio, Vida de Santa María Egipciaca, Libre dels tres reys d'Orient), para dar cuenta -a través de las referencias compartidas, los motivos comunes y las configuraciones similares- de la organización unitaria del códice y de su singularidad

Vestimentas compartidas y otros cuidados : Las formas de la generosidad en el Ms. K-III-4 (Libro de Apolonio, Vida de Santa María Egipciaca, Libre dels tres reys d'Orient)

El artículo lleva a cabo una revisión de las formas de la generosidad presentes en los tres poemas que componen el Ms. K-III-4 de la Biblioteca de San Lorenzo de El Escorial (Libro de Apolonio, Vida de Santa María Egipciaca, Libre dels tres reys d'Orient), para dar cuenta -a través de las referencias compartidas, los motivos comunes y las configuraciones similares- de la organización unitaria del códice y de su singularidad

Vestimentas compartidas y otros cuidados : Las formas de la generosidad en el Ms. K-III-4 (Libro de Apolonio, Vida de Santa María Egipciaca, Libre dels tres reys d'Orient)

El artículo lleva a cabo una revisión de las formas de la generosidad presentes en los tres poemas que componen el Ms. K-III-4 de la Biblioteca de San Lorenzo de El Escorial (Libro de Apolonio, Vida de Santa María Egipciaca, Libre dels tres reys d'Orient), para dar cuenta -a través de las referencias compartidas, los motivos comunes y las configuraciones similares- de la organización unitaria del códice y de su singularidad

Table 1. Mean geochemical values for Baseline (pre-injection) and Monitor-1 (post-injection) samples, and the percent change between the two weighted means

The Weyburn Oil Field, Saskatchewan is the site of a large (5000 tonnes/day of CO2) CO2-EOR injection project By EnCana Corporation. Pre- and post-injection samples (Baseline and Monitor-1, respectively) of produced fluids from approximately 45 vertical wells were taken and chemically analyzed to determine changes in the fluid chemistry and isotope composition between August 2000 and March 2001. After 6 months of CO2 injection, geochemical parameters including pH, [HCO3], [Ca], [Mg], and ?13CO2(g) point to areas in which injected CO2 dissolution and reservoir carbonate mineral dissolution have occurred. Pre-injection fluid compositions suggest that the reservoir brine in the injection area may be capable of storing as much as 100 million tonnes of dissolved CO2. Modeling of water-rock reactions show that clay minerals and feldspar, although volumetrically insignificant, may be capable of acting as pH buffers, allowing injected CO2 to be stored as bicarbonate in the formation water or as newly precipitated carbonate minerals, given favorable reaction kinetics.

Quality assessment by region in spot images fused by means dual-tree complex wavelet transform

This work is motivated in providing and evaluating a fusion algorithm of remotely sensed images, i.e. the fusion of a high spatial resolution panchromatic image with a multi-spectral image (also known as pansharpening) using the dual-tree complex wavelet transform (DT-CWT), an effective approach for conducting an analytic and oversampled wavelet transform to reduce aliasing, and in turn reduce shift dependence of the wavelet transform. The proposed scheme includes the definition of a model to establish how information will be extracted from the PAN band and how that information will be injected into the MS bands with low spatial resolution. The approach was applied to Spot 5 images where there are bands falling outside PAN’s spectrum. We propose an optional step in the quality evaluation protocol, which is to study the quality of the merger by regions, where each region represents a specific feature of the image. The results show that DT-CWT based approach offers good spatial quality while retaining the spectral information of original images, case SPOT 5. The additional step facilitates the identification of the most affected regions by the fusion process.

Comparison of different stomatal conductance algorithms for ozone flux modelling

A multiplicative and a semi-mechanistic, BWB-type [Ball, J.T., Woodrow, I.E., Berry, J.A., 1987. A model predicting stomatalconductance and its contribution to the control of photosynthesis under different environmental conditions. In: Biggens, J. (Ed.), Progress in Photosynthesis Research, vol. IV. Martinus Nijhoff, Dordrecht, pp. 221–224.] algorithm for calculating stomatalconductance (gs) at the leaf level have been parameterised for two crop and two tree species to test their use in regional scale ozone deposition modelling. The algorithms were tested against measured, site-specific data for durum wheat, grapevine, beech and birch of different European provenances. A direct comparison of both algorithms showed a similar performance in predicting hourly means and daily time-courses of gs, whereas the multiplicative algorithm outperformed the BWB-type algorithm in modelling seasonal time-courses due to the inclusion of a phenology function. The re-parameterisation of the algorithms for local conditions in order to validate ozone deposition modelling on a European scale reveals the higher input requirements of the BWB-type algorithm as compared to the multiplicative algorithm because of the need of the former to model net photosynthesis (An)

B-Neck: A Distributed and Quiescent Max-Min Fair Algorithm

The problem of fairly distributing the capacity of a network among a set of sessions has been widely studied. In this problem, each session connects via a single path a source and a destination, and its goal is to maximize its assigned transmission rate (i.e., its throughput). Since the links of the network have limited bandwidths, some criterion has to be defined to fairly distribute their capacity among the sessions. A popular criterion is max-min fairness that, in short, guarantees that each session i gets a rate λi such that no session s can increase λs without causing another session s' to end up with a rate λs/ <; λs. Many max-min fair algorithms have been proposed, both centralized and distributed. However, to our knowledge, all proposed distributed algorithms require control data being continuously transmitted to recompute the max-min fair rates when needed (because none of them has mechanisms to detect convergence to the max-min fair rates). In this paper we propose B-Neck, a distributed max-min fair algorithm that is also quiescent. This means that, in absence of changes (i.e., session arrivals or departures), once the max min rates have been computed, B-Neck stops generating network traffic. Quiescence is a key design concept of B-Neck, because B-Neck routers are capable of detecting and notifying changes in the convergence conditions of max-min fair rates. As far as we know, B-Neck is the first distributed max-min fair algorithm that does not require a continuous injection of control traffic to compute the rates. The correctness of B-Neck is formally proved, and extensive simulations are conducted. In them, it is shown that B-Neck converges relatively fast and behaves nicely in presence of sessions arriving and departing.

Prediction of PM10 concentrations using Fuzzy c-Means and ANN

Salamanca has been considered among the most polluted cities in Mexico. The vehicular park, the industry and the emissions produced by agriculture, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Particulate Matter less than 10 μg/m3 in diameter (PM10). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of pollutant concentration. A database used to train the Neural Network corresponds to historical time series of meteorological variables (wind speed, wind direction, temperature and relative humidity) and air pollutant concentrations of PM10. Before the prediction, Fuzzy c-Means clustering algorithm have been implemented in order to find relationship among pollutant and meteorological variables. These relationship help us to get additional information that will be used for predicting. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of PM10 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results shown that the information obtained in the clustering step allows a prediction of an hour ahead, with data from past 2 hours

Hand Image Segmentation by means of Gaussian Multiscale Aggregation for biometric applications

Applying biometrics to daily scenarios involves demanding requirements in terms of software and hardware. On the contrary, current biometric techniques are also being adapted to present-day devices, like mobile phones, laptops and the like, which are far from meeting the previous stated requirements. In fact, achieving a combination of both necessities is one of the most difficult problems at present in biometrics. Therefore, this paper presents a segmentation algorithm able to provide suitable solutions in terms of precision for hand biometric recognition, considering a wide range of backgrounds like carpets, glass, grass, mud, pavement, plastic, tiles or wood. Results highlight that segmentation accuracy is carried out with high rates of precision (F-measure 88%)), presenting competitive time results when compared to state-of-the-art segmentation algorithms time performance

Stress Detection by means of Stress Physiological Template

This paper describes a stress detection system based on fuzzy logic and two physiological signals: Galvanic Skin Response and Heart Rate. Instead of providing a global stress classification, this approach creates an individual stress templates, gathering the behaviour of individuals under situations with different degrees of stress. The proposed method is able to detect stress properly with a rate of 99.5%, being evaluated with a database of 80 individuals. This result improves former approaches in the literature and well-known machine learning techniques like SVM, k-NN, GMM and Linear Discriminant Analysis. Finally, the proposed method is highly suitable for real-time applications