Efficient implementation of the implicit error correction nVoD schema

Implicit Error Correction is a near Video-on-Demand (nVoD) schema that trades bandwidth utilization for initial playback delay while potentially allowing an infinite number of users. Additionally, it provides error protection without further bandwidth increase by exploiting the implicit redundancy of nVoD protocols, using linear combinations of the segments transmitted in a given time slot. This paper introduces a new implementation that outperforms the original schema by adding two new mechanisms: redundancy channels and feedback error correction.     

Charge Migration in Organic Materials: Can Propagating Charges Affect the Key Physical Quantities Controlling Their Motion?

Charge migration is a ubiquitous phenomenon with profound implications throughout many areas of chemistry, physics, biology, and materials science. The long-term vision of designing functional materials with tailored molecular-scale properties has triggered an increasing quest to identify prototypical systems where truly molecular conduction pathways play a fundamental role. Such pathways can be formed due to the molecular organization of various organic materials and are widely used to discuss electronic properties at the nanometer scale. Here, we present a computational methodology to study charge propagation in organic molecular stacks at nano and sub-nanoscales and exploit this methodology to demonstrate that moving charge carriers strongly affect the values of the physical quantities controlling their motion. The approach is also expected to find broad application in the field of charge migration in soft matter systems.     

Fuzzy methodology for frequency response estimation of uncertain dynamic systems

Fuzzy frequency response: definition and analysis for uncertain dynamic systems is proposed in this paper. In terms of transfer function, the uncertain dynamic system is partitioned into several linear sub‐models and organized according to Takagi–Sugeno fuzzy representation. The main contribution of this paper is to demonstrate through the proposal of a Theorem that fuzzy frequency response is a boundary in the magnitude and phase Bode plots. Low‐ and high‐frequency analysis of fuzzy dynamic model is obtained by varying the frequency ω from zero to infinity. Copyright © 2011 John Wiley & Sons, Ltd.     

Preliminary Developments of Miniplate-Type Fuel of U-2.5Zr-7.5Nb Alloy Dispersed and Cladded in Zircaloy

Nuclear fuel based on uranium metal alloys is utilized in research and test reactors. For the purpose of the reduction of fuel enrichment, high densities of uranium-235 in this kind of fuel are needed. This can be achieved when uranium alloys are used containing elements such as Zr, Mo and Nb. The construction of fuel element with high-uranium density requires materials with low cross sections for neutron absorption, stability under irradiation and absence of the chemical interactions between the fuel and cladding elements. In case of U-Zr-Nb alloys, Zry （zircaloy） cladding is a better option due to the fact that they have a higher chemical compatibility when compared with the use of aluminum alloys. This study aims to develop plate type nuclear fuel using the U-2.5Zr-7.5Nb alloy dispersed in Zry. Powders of this uranium based alloy and Zry were obtained by hydriding-dehydriding process. These powders were homogenized, compacted in pellet that was sandwiched in plates and frame of Zry. This assembly was hot rolled forming the dispersion fuel miniplate.     

Neuroprotective Role of Liver Growth Factor “LGF” in an Experimental Model of Cerebellar Ataxia

Cerebellar ataxias (CA) comprise a heterogeneous group of neurodegenerative diseases characterized by a lack of motor coordination. They are caused by disturbances in the cerebellum and its associated circuitries, so the major therapeutic goal is to correct cerebellar dysfunction. Neurotrophic factors enhance the survival and differentiation of selected types of neurons. Liver growth factor (LGF) is a hepatic mitogen that shows biological activity in neuroregenerative therapies. We investigate the potential therapeutic activity of LGF in the 3-acetylpiridine (3-AP) rat model of CA. This model of CA consists in the lesion of the inferior olive-induced by 3-AP (40 mg/kg). Ataxic rats were treated with 5 µg/rat LGF or vehicle during 3 weeks, analyzing: (a) motor coordination by using the rota-rod test; and (b) the immunohistochemical and biochemical evolution of several parameters related with the olivo-cerebellar function. Motor coordination improved in 3-AP-lesioned rats that received LGF treatment. LGF up-regulated NeuN and Bcl-2 protein levels in the brainstem, and increased calbindin expression and the number of neurons receiving calbindin-positive projections in the cerebellum. LGF also reduced extracellular glutamate and GABA concentrations and microglia activation in the cerebellum. In view of these results, we propose LGF as a potential therapeutic agent in cerebellar ataxias.     

Semi-automated and fully automated mammographic density measurement and breast cancer risk prediction

The task of breast density quantification is becoming increasingly relevant due to its association with breast cancer risk. In this work, a semi-automated and a fully automated tools to assess breast density from full-field digitized mammograms are presented. The first tool is based on a supervised interactive thresholding procedure for segmenting dense from fatty tissue and is used with a twofold goal: for assessing mammographic density (MD) in a more objective and accurate way than via visual-based methods and for labeling the mammograms that are later employed to train the fully automated tool. Although most automated methods rely on supervised approaches based on a global labeling of the mammogram, the proposed method relies on pixel-level labeling, allowing better tissue classification and density measurement on a continuous scale. The fully automated method presented combines a classification scheme based on local features and thresholding operations that improve the performance of the classifier. A dataset of 655 mammograms was used to test the concordance of both approaches in measuring MD. Three expert radiologists measured MD in each of the mammograms using the semi-automated tool (DM-Scan). It was then measured by the fully automated system and the correlation between both methods was computed. The relation between MD and breast cancer was then analyzed using a case–control dataset consisting of 230 mammograms. The Intraclass Correlation Coefficient (ICC) was used to compute reliability among raters and between techniques. The results obtained showed an average ICC = 0.922 among raters when using the semi-automated tool, whilst the average correlation between the semi-automated and automated measures was ICC = 0.838. In the case–control study, the results obtained showed Odds Ratios (OR) of 1.38 and 1.50 per 10% increase in MD when using the semi-automated and fully automated approaches respectively. It can therefore be concluded that the automated and semi-automated MD assessments present a good correlation. Both the methods also found an association between MD and breast cancer risk, which warrants the proposed tools for breast cancer risk prediction and clinical decision making. A full version of the DM-Scan is freely available.     

A two-way coupled multiscale model for predicting damage-associated performance of asphaltic roadways

This paper presents a quasi-static multiscale computational model with its verification and rational applications to mechanical behavior predictions of asphaltic roadways that are subject to viscoelastic deformation and fracture damage. The multiscale model is based on continuum thermo-mechanics and is implemented using a finite element formulation. Two length scales (global and local) are two-way coupled in the model framework by linking a homogenized global scale to a heterogeneous local scale representative volume element. With the unique multiscaling and the use of the finite element technique, it is possible to take into account the effect of material heterogeneity, viscoelasticity, and anisotropic damage accumulation in the small scale on the overall performance of larger scale structures. Along with the theoretical model formulation, two example problems are shown: one to verify the model and its computational benefits through comparisons with analytical solutions and single-scale simulation results, and the other to demonstrate the applicability of the approach to model general roadway structures where material viscoelasticity and cohesive zone fracture are involved.     

Remote sensing of wetlands in South America: status and challenges

South America has a large proportion of wetlands compared with other continents. While most of these wetlands were conserved in a relatively good condition until a few decades ago, pressures brought about by land use and climate change have threaten their integrity in recent years. The aim of this article is to provide a bibliometric analysis of the available scientific literature relating to the remote sensing of wetlands in South America. From 1960 to 2015, 153 articles were published in 63 different journals, with the number of articles published per year increasing progressively since 1990. This rise is also paralleled by an increase in the contribution of local authors. The most intensively studied regions are the wetland macrosystems of South American mega-rivers: the Amazon and Paraná Rivers, along with the Pantanal at the headwaters of Paraguay River. Few studies spanned more than two countries. The most frequent objectives were mapping, covering all types of wetlands with optical data, and hydrology, focusing on floodplain wetlands with microwave data as the preferred data source. The last decade substantial growth reflects an increase in technological and scientific capacities. Nevertheless, the state of the art regarding the remote sensing of wetlands in South America remains enigmatic. Fundamental questions and guidelines which may contribute to the understanding of the functioning of these ecosystems are yet to be fully defined and there is considerable dispersion in the use of data and remote-sensing approaches.