The internal wave field in Sau reservoir : Observation and modeling of a third vertical mode

Water withdrawal from Mediterranean reservoirs in summer is usually very high. Because of this, stratification is often continuous and far from the typical two-layered structure, favoring the excitation of higher vertical modes. The analysis of wind, temperature, and current data from Sau reservoir (Spain) shows that the third vertical mode of the internal seiche (baroclinic mode) dominated the internal wave field at the beginning of September 2003. We used a continuous stratification two-dimensional model to calculate the period and velocity distribution of the various modes of the internal seiche, and we calculated that the period of the third vertical mode is ;24 h, which coincides with the period of the dominating winds. As a result of the resonance between the third mode and the wind, the other oscillation modes were not excited during this period

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

Precursor nanoscale modulations in ferromagnets: Modeling and thermodynamic characterization

Using a Ginzburg-Landau model for the magnetic degrees of freedom with coupling to disorder, we demonstrate through simulations the existence of stripelike magnetic precursors recently observed in Co-Ni-Al alloys above the Curie temperature. We characterize these magnetic modulations by means of the temperature dependence of local magnetization distribution, magnetized volume fraction, and magnetic susceptibility. We also obtain a temperature-disorder strength phase diagram in which a magnetic tweed phase exists in a small region between the paramagnetic and dipolar phases.

Feature selection for automatic analysis of emotional response based on nonlinear speech modeling suitable for diagnosis of Alzheimer׳s disease

Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.

Probing quantum gravity using photons from a flare of the active galactic nucleus Markarian 501 observed by the MAGIC telescope

We analyze the timing of photons observed by the MAGIC telescope during a flare of the active galactic nucleus Mkn 501 for a possible correlation with energy, as suggested by some models of quantum gravity (QG), which predict a vacuum refractive index similar or equal to 1 + (E/M-QGn)(n), n = 1, 2. Parametrizing the delay between gamma-rays of different energies as Delta t = +/-tau E-1 or Delta t = +/-tau E-q(2), we find tau(1) = (0.030 +/- 0.012) s/GeV at the 2.5-sigma level, and tau(q) = (3.71 +/- 2.57) x 10(-6) s/GeV2, respectively. We use these results to establish lower limits M-QG1 > 0.21 X 10(18) GeV and M-QG2 > 0.26 x 10(11) GeV at the 95% C.L. Monte Carlo studies confirm the MAGIC sensitivity to propagation effects at these levels. Thermal plasma effects in the source are negligible, but we cannot exclude the importance of some other source effect.

Study and modeling of the desintegration kinetics of coated paper

The disintegration of recovered paper is the first operation in the preparation of recycled pulp. It is known that the defibering process follows a first order kinetics from which it is possible to obtain the disintegration kinetic constant (KD) by means of different ways. The disintegration constant can be obtained from the Somerville index results (%lsv and from the dissipated energy per volume unit (Ss). The %slv is related to the quantity of non-defibrated paper, as a measure of the non-disintegrated fiber residual (percentage of flakes), which is expressed in disintegration time units. In this work, disintegration kinetics from recycled coated paper has been evaluated, working at 20 revise rotor speed and for different fiber consistency (6, 8, 10, 12 and 14%). The results showed that the values of experimental disintegration kinetic constant, Ko, through the analysis of Somerville index, as function of time. Increased, the disintegration time was drastically reduced. The calculation of the disintegration kinetic constant (modelled Ko), extracted from the Rayleigh’s dissipation function, showed a good correlation with the experimental values using the evolution of the Somerville index or with the dissipated energy

Determination of corn stalk fibers' strength through modeling of the mechanical properties of its composites

Worldwide cultivation of corn is expanding, due in part to the increasing production of bioethanol. In consequence, huge amounts of corn stalks residues are been produced. Instead of incineration, we transformed the corn stalks into a semichemical pulp and successfully applied it as reinforcement in polypropylene composites. PP composites reinforced with 40% wt corn stalk single fibers were prepared, and their mechanical properties were evaluated. Through mechanical properties modeling of the composites, the intrinsic tensile strength of the cellulosic fibers that constitute the corn stalk have been determined

The Role of the Delay Time in the Modeling of Biological Range Expansions

The time interval between successive migrations of biological species causes a delay time in the reaction-diffusion equations describing their space-time dynamics. This lowers the predicted speed of the waves of advance, as compared to classical models. It has been shown that this delay-time effect improves the modeling of human range expansions. Here, we demonstrate that it can also be important for other species. We present two new examples where the predictions of the time-delayed and the classical (Fisher) approaches are compared to experimental data. No free or adjustable parameters are used. We show that the importance of the delay effect depends on the dimensionless product of the initial growth rate and the delay time. We argue that the delay effect should be taken into account in the modeling of range expansions for biological species