Differentiability of the Solutions of a Semilinear Abstract Cauchy Problems With Respect to Parameters

The Frechet di®erentiability with respect to a parameter q of the solutions z(t; q) of Cauchy problems of the form d/dt z(t) = A(q)z(t) + F(q; t; z(t)) is analyzed. Su±cient conditions on the operator A(q) and on F are derived and the corresponding sensitivity equations for the Frechet derivative Dqz(t; q) are found.Fil: Spies, Ruben Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentin

Generalized Sparse Discriminant Analysis for Event-Related Potential Classification

A brain computer interface (BCI) is a system which provides direct communication between the mind of a person and the outside world by using only brain activity (EEG). The event-related potential (ERP)-based BCI problem consists of a binary pattern recognition. Linear discriminant analysis (LDA) is widely used to solve this type of classification problems, but it fails when the number of features is large relative to the number of observations. In this work we propose a penalized version of the sparse discriminant analysis (SDA), called generalized sparse discriminant analysis (GSDA), for binary classification. This method inherits both the discriminative feature selection and classification properties of SDA and it also improves SDA performance through the addition of Kullback-Leibler class discrepancy information. The GSDA method is designed to automatically select the optimal regularization parameters. Numerical experiments with two real ERP-EEG datasets show that, on one hand, GSDA outperforms standard SDA in the sense of classification performance, sparsity and required computing time, and, on the other hand, it also yields better overall performances, compared to well-known ERP classification algorithms, for single-trial ERP classification when insufficient training samples are available. Hence, GSDA constitute a potential useful method for reducing the calibration times in ERP-based BCI systems.Fil: Peterson, Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Rufiner, Hugo Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; ArgentinaFil: Spies, Ruben Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentin

Results on Transversal and Axial Motions of a System of Two Beams Coupled to a Joint through Two Legs

In recent years there has been renewed interest in inflatable-rigidizable space structures because of the efficiency they offer in packaging during boost-to-orbit. However, much research is still needed to better understand dynamic response characteristics, including inherent damping, of truss structures fabricated with these advanced material systems. We present results of an ongoing research related to a model consisting of an assembly of two beams with Kelvin-Voight damping, coupled to a simple joint through two legs. The beams are clamped at one end but at the other end they satisfy a boundary condition given in terms of an ODE coupling boundary terms of both beams, which reflects geometric compatibility conditions. The system is then written as a second order differential equation in an appropriate Hilbert space  in which well-posedness, exponential stability as well as other regularity properties of the solutions can be obtained. Two different finite dimensional approximation schemes for the solutions of the system are presented. Numerical results are presented and comparisons are made.Fil: Burns, J. A.. Interdisciplinary Center for Applied Mathematics; Estados UnidosFil: Cliff, E. M.. Interdisciplinary Center for Applied Mathematics; Estados UnidosFil: Liu, Z.. University of Minnesota at Duluth; Estados UnidosFil: Spies, Ruben Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentin

Image restoration with a half-quadratic approach to mixed weighted smooth and anisotropic bounded variation regularization

The problem of restoring a signal or image is often tantamount to approximating the solution of a linear inverse ill-posed problem. In order to find such an approximation one might regularize the problem by penalizing variations on the estimated solution. Among the wide variety of methods available to perform this penalization, the most commonly used is the Tikhonov-Phillips regularization, which is appropriate when the sought signal or image is expected to be smooth, but it results unsuitable whenever preservation of discontinuities and edges is an important matter. Nonetheless, there are other methods with edge preserving properties, such as bounded variation (BV) regularization. However, these methods tend to produce piecewise constant solutions showing the so called “staircasing effect” and their numerical implementations entail great computational effort and cost. In order to overcome these obstacles, we consider a mixed weighted Tikhonov and anisotropic BV regularization method to obtain improved restorations and we use a half-quadratic approach to construct highly efficient numerical algorithms. Several numerical results in signal and image restoration problems are presented.Fil: Ibarrola, Francisco Javier. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Departamento de Matemática; ArgentinaFil: Spies, Ruben Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Matemática Aplicada "Litoral"; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química; Argentin

Estudo da qualidade do leite produzido na linha Santa Cruz, município de Três arroios, RS

The objective of this research was evaluate the milk quality on dairy farms in Linha Sata Cruz, Três Arroios city, Rio Grande do Sul. It aimed to evaluate the Protein index, Fat, Total dry extract (EST), Dry extract degreased (ESD), Total Bacterial Count (TBC) and Somatic Cell Count (SCC), through monthly analyzes, during months of November 2015 to April 2016. Data were tabulated and subsequently attached at the study, with the amount prescribed in the Normative n° 62, which determines the rates at which the product must meet. After the analyses, it was verified that Protein index, Fat and Total dry extract and Dry extract degreased were within required by the Normative n° 62. However, it can be observed that the values of Somatic Cell Count (SCC) and Total Bacterial Count (TBC) exceeded the limits in most cases. It was noted that the quality of milk produced presented Protein values , Fat, Total Dry Extract and Dry Extract degreased within the required company. However, it can be noted that the values of Somatic Cell Count (SCC) and Total Bacterial Count (TBC) exceeded the limits in most cases.O objetivo deste trabalho foi avaliar a qualidade do leite de propriedades leiteiras na Linha Santa Cruz, município de Três Arroios, Rio Grande do Sul. Avaliou-se no presente trabalho os Índices de Proteína, Gordura, Estrato seco Total (EST), Estrato Seco Desengordurado (ESD), Contagem Bacteriana Total (CBT) e Contagem de Células Somáticas (CCS) através das análises mensais realizadas pela própria empresa coletora do leite, durante os meses de Novembro de 2015 a Abril de 2016. Os dados coletados foram tabelados e posteriormente anexados no trabalho, juntamente com o valor mínima exigido pela empresa, no qual determina os índices no qual o produto deve atender. Notou-se que a qualidade do leite produzido apresentou valores de Proteína, Gordura, Extrato Seco Total e Extrato Seco Desengordurado dentro dos exigidos pela Instrução Normativa n°62. Porém, pode-se notar que os valores de Contagem de Células Somáticas (CCS) e Contagem Bacteriana Total (CBT) ultrapassaram os limites na maioria dos casos

Modeling Accuracy and Variability of Motor Timing in Treated and Untreated Parkinson’s Disease and Healthy Controls

Parkinson’s disease (PD) is characterized by difficulty with the timing of movements. Data collected using the synchronization–continuation paradigm, an established motor timing paradigm, have produced varying results but with most studies finding impairment. Some of this inconsistency comes from variation in the medication state tested, in the inter-stimulus intervals (ISI) selected, and in changeable focus on either the synchronization (tapping in time with a tone) or continuation (maintaining the rhythm in the absence of the tone) phase. We sought to re-visit the paradigm by testing across four groups of participants: healthy controls, medication naïve de novo PD patients, and treated PD patients both “on” and “off” dopaminergic medication. Four finger tapping intervals (ISI) were used: 250, 500, 1000, and 2000 ms. Categorical predictors (group, ISI, and phase) were used to predict accuracy and variability using a linear mixed model. Accuracy was defined as the relative error of a tap, and variability as the deviation of the participant’s tap from group predicted relative error. Our primary finding is that the treated PD group (PD patients “on” and “off” dopaminergic therapy) showed a significantly different pattern of accuracy compared to the de novo group and the healthy controls at the 250-ms interval. At this interval, the treated PD patients performed “ahead” of the beat whilst the other groups performed “behind” the beat. We speculate that this “hastening” relates to the clinical phenomenon of motor festination. Across all groups, variability was smallest for both phases at the 500-ms interval, suggesting an innate preference for finger tapping within this range. Tapping variability for the two phases became increasingly divergent at the longer intervals, with worse performance in the continuation phase. The data suggest that patients with PD can be best discriminated from healthy controls on measures of motor timing accuracy, rather than variability

Coherent averaging estimation autoencoders applied to evoked potentials processing

The success of machine learning algorithms strongly depends on the feature extraction and data representation stages. Classification and estimation of small repetitive signals masked by relatively large noise usually requires recording and processing several different realizations of the signal of interest. This is one of the main signal processing problems to solve when estimating or classifying P300 evoked potentials in brain-computer interfaces. To cope with this issue we propose a novel autoencoder variation, called Coherent Averaging Estimation Autoencoder with a new multiobjective cost function. We illustrate its use and analyze its performance in the problem of event related potentials processing. Experimental results showing the advantages of the proposed approach are finally presented.Fil: Gareis, Iván Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina. Universidad Nacional de Entre Ríos; ArgentinaFil: Vignolo, Leandro Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Spies, Ruben Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: Rufiner, Hugo Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina. Universidad Nacional de Entre Ríos; Argentin

A Bayesian approach to convolutive nonnegative matrix factorization for blind speech dereverberation

When a signal is recorded in an enclosed room, it typically gets affected by reverberation. This degradation represents a problem when dealing with audio signals, particularly in the field of speech signal processing, such as automatic speech recognition. Although there are some approaches to deal with this issue that are quite satisfactory under certain conditions, constructing a method that works well in a general context still poses a significant challenge. In this article, we propose a Bayesian approach based on convolutive nonnegative matrix factorization that uses prior distributions in order to impose certain characteristics over the time-frequency components of the restored signal and the reverberant components. An algorithm for implementing the method is described and tested.Comparisons of the results against those obtained with state-of-the-art methods are presented, showing significant improvement.Fil: Ibarrola, Francisco Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Di Persia, Leandro Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Spies, Ruben Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; Argentin

A multi‐scale study of the dominant catchment characteristics impacting low‐flow metrics

Low flows can impact water use and instream ecology. Therefore, reliable predictions of low-flow metrics are crucial. In this study, we assess which catchment characteristics (climate, topography, geology and landcover) can explain the spatial variability of low-flow metrics at two different scales: the regional scale and the small headwater catchment scale. For the regional-scale analysis, we calculated the mean 7-day annual minimum flow (qmin), the mean of the flow that is exceeded 95% of the year (q95), and the master recession constant (C) for 280 independent gauging stations across the Swiss Plateau and the Swiss Alps for the 2000–2018 period. We assessed the relation between 44 catchment characteristics and the three low-flow metrics based on correlation analysis and a random forest model. Low-flow magnitudes across the Swiss Plateau were positively correlated with the fraction of the area covered by sandstone bedrock or alluvium, and with the area that has a slope between 10° and 30°. Across the Swiss Alps, low-flow magnitudes were positively correlated with the fraction of area with slopes between 30° and 60°, and the area with glacial deposits and debris cover. There was good agreement between observations and predictions by the random forest regression model with the top 11 catchment characteristics for both regions: for 80% of the Swiss Plateau catchments and 60% of the Swiss Alpine catchments, we could predict the three low-flow metrics within an error of 30%. The residuals of the regression model, however, varied across short distances, suggesting that local catchment characteristics affect the variability of low-flow metrics. For the local-scale headwater catchments, we conducted 1-day snapshot field campaigns in 16 catchments during low-flow periods in 2015 and 2016. The measurements in these sub-catchments also showed that areas with sandstone bedrock and a good storage-to-river connectivity had above average low-flow magnitudes. Including knowledge on local catchment characteristics may help to improve regional low-flow predictions, however, not all local catchment characteristics were useful descriptors at larger scales

A randomized controlled trial

Objective We report on the effect of hemoadsorption therapy to reduce cytokines in septic patients with respiratory failure. Methods This was a randomized, controlled, open-label, multicenter trial. Mechanically ventilated patients with severe sepsis or septic shock and acute lung injury or acute respiratory distress syndrome were eligible for study inclusion. Patients were randomly assigned to either therapy with CytoSorb hemoperfusion for 6 hours per day for up to 7 consecutive days (treatment), or no hemoperfusion (control). Primary outcome was change in normalized IL-6-serum concentrations during study day 1 and 7. Results 97 of the 100 randomized patients were analyzed. We were not able to detect differences in systemic plasma IL-6 levels between the two groups (n = 75; p = 0.15). Significant IL-6 elimination, averaging between 5 and 18% per blood pass throughout the entire treatment period was recorded. In the unadjusted analysis, 60-day-mortality was significantly higher in the treatment group (44.7%) compared to the control group (26.0%; p = 0.039). The proportion of patients receiving renal replacement therapy at the time of enrollment was higher in the treatment group (31.9%) when compared to the control group (16.3%). After adjustment for patient morbidity and baseline imbalances, no association of hemoperfusion with mortality was found (p = 0.19). Conclusions In this patient population with predominantly septic shock and multiple organ failure, hemoadsorption removed IL-6 but this did not lead to lower plasma IL-6-levels. We did not detect statistically significant differences in the secondary outcomes multiple organ dysfunction score, ventilation time and time course of oxygenation