The influence of iodide on glass transition temperature of high-pressure nuclear waste glasses

The glass transition temperature (T_g) is a key parameter to investigate for application in nuclear waste immobilization in borosilicate glasses. T_g for several glasses containing iodine (I) has been measured in order to determine the I effect on T_g. Two series of glass composition (ISG and NH) containing up to 2.5 mol% I and synthesized under high pressure (0.5 to 1.5 GPa) have been investigated using differential scanning calorimetry (DSC). The I local environment in glasses has been determined using X-ray photoelectron spectroscopy and revealed that I is dissolved under its iodide form (I⁻). Results show that T_g is decreased with the I addition in the glass in agreement with previous results. We also observed that this T_g decrease is a strong function of glass composition. For NH, 2.5 mol% I induces a decrease of 24°C in T_g, whereas for ISG, 1.2 mol% decreases the T_g by 64°C. We interpret this difference as the result of the I dissolution mechanism and its effect on the polymerization of the boron network. The I dissolution in ISG is accompanied by a depolymerization of the boron network, whereas it is the opposite in NH. Although ISG corresponds to a standardized glass, for the particular case of I immobilization it appears less adequate than NH considering that the decrease in T_g for NH is small in comparison to ISG.     

Towards deterministic downscaling of SMOS soil moisture using MODIS derived soil evaporative efficiency

A deterministic approach for downscaling ～ 40 km resolution Soil Moisture and Ocean Salinity (SMOS) observations is developed from 1 km resolution MODerate resolution Imaging Spectroradiometer (MODIS) data. To account for the lower soil moisture sensitivity of MODIS surface temperature compared to that of L-band brightness temperature, the disaggregation scale is fixed to 10 times the spatial resolution of MODIS thermal data (10 km). Four different analytic downscaling relationships are derived from MODIS and physically-based model predictions of soil evaporative efficiency. The four downscaling algorithms differ with regards to i) the assumed relationship (linear or nonlinear) between soil evaporative efficiency and near-surface soil moisture, and ii) the scale at which soil parameters are available (40 km or 10 km). The 1 km resolution airborne L-band brightness temperature from the National Airborne Field Experiment 2006 (NAFE'06) are used to generate a time series of eleven clear sky 40 km by 60 km near-surface soil moisture observations to represent SMOS pixels across the three-week experiment. The overall root mean square difference between downscaled and observed soil moisture varies between 1.4% v/v and 1.8% v/v depending on the downscaling algorithm used, with soil moisture values ranging from 0 to 15% v/v. The accuracy and robustness of the downscaling algorithms are discussed in terms of their assumptions and applicability to SMOS.     

Bench-Scale Testing of Nanofiltration for Seawater Desalination

A dual-staged nanofiltration process is being evaluated as an alternative to reverse osmosis for seawater desalination. The primary goal of this system is to reduce energy consumption while producing potable water at an acceptable recovery rate. Investigation of this system at the bench-scale level focused on membrane surface characterization, ion rejection (including boron, bromide, and iodide rejection), and flux decline. Results from this study showed that two commercially available nanofiltration membranes can effectively desalinate seawater. Although fouling was apparent—and resulted in approximately 20% flux decline over 3 days—a critical flux was not identifiable. Operation of the system at different cross-flow velocities revealed the significance of hydrodynamic conditions on the polarization modulus, and hence on membrane performance.     

Toward automatic phenotyping of developing embryos from videos.

We describe a trainable system for analyzing videos of developing C. elegans embryos. The system automatically detects, segments, and locates cells and nuclei in microscopic images. The system was designed as the central component of a fully automated phenotyping system. The system contains three modules 1) a convolutional network trained to classify each pixel into five categories: cell wall, cytoplasm, nucleus membrane, nucleus, outside medium; 2) an energy-based model, which cleans up the output of the convolutional network by learning local consistency constraints that must be satisfied by label images; 3) a set of elastic models of the embryo at various stages of development that are matched to the label images.     

Structural features of an arabinan fragment isolated from the water-soluble fraction of dehulled rapeseed

A water-soluble polysaccharide fraction was prepared from dehulled rapeseed meal (winter rapeseed variety Casino). Further purification yielded two major fractions having a high content of arabinose and galactose residues, with Ara/Gal ratios of 5.4 (G1) and 1.8 (G2). The Ara/Gal ratio of the high molecular weight fraction G1 was stable over the whole gel filtration peak, indicating that the arabinose and galactose residues are part of the same polysaccharide. The high molecular weight fraction G1 was studied further by methylation analysis and several NMR techniques. Structural studies showed G1 to consist mainly of arabian fragments, which have terminal alpha-L-arabinofuranosyl groups with anomeric carbons bound (1-->5) (A) or (1-->2) (B), and 2,5-substituted arabinosyl residues with anomeric carbons bound (1-->5) (D) or (1-->2) (C) to adjacent arabinosyl residues. The A:B:C:D ratios were 2:1:1:1 according to results from NMR and methylation analysis.     

A multipurpose audio watermarking algorithm with synchronization and encryption

We propose a new multipurpose audio watermarking scheme in which two complementary watermarks are used.For audio copyright protection,the watermark data with copyright information or signature are first encrypted by Arnold transformation.Then the watermark data are inserted in the low frequency largest significant discrete cosine transform(DCT) coefficients to obtain robustness performance.For audio authentication,a chaotic signal is inserted in the high frequency insignificant DCT coefficients to detect tampered regions.Furthermore,the synchronization code is embedded in the audio statistical characteristics to resist desynchronization attacks.Experimental results show that our proposed method can not only obtain satisfactory detection and tampered location,but also achieve imperceptibility and robustness to common signal processing attacks,such as cropping,shifting,and time scale modification(TSM).Comparison results show that our method outperforms some existing methods.     

An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k‐means clustering and improved ensemble learning

In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k‐means clustering and improved ensemble‐driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f‐measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k‐means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree‐based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods.