Effects of block shape and inclination on the stability of melange bimrocks

Bulletin of Engineering Geology and the Environment - A wide range of heterogeneous geological units composed of strong rock blocks enclosed in a bonded matrix of fine texture exists worldwide....     

The effects of retinol on in vitro immunoglobulin synthesis by cord blood and adult peripheral blood mononuclear cells

In this study we examined the effects of retinol (ROH), a metabolic precursor of retinoic acid (RA), on Staphylococcus aureus Cowan I (SAC)-induced immunoglobulin synthesis of cord blood mononuclear cells (CBMC) and adult peripheral blood mononuclear cells (PBMC). ROH augmented SAC-induced IgM synthesis of CBMC by 5.9 +/- 1.5-fold (n = 7, mean +/- s.d.), and IgG synthesis of adult PBMC by 16.3 +/- 5.1-fold (n = 3) at optimal concentrations of 10(-6) M and 10(-11) M, respectively. No augmenting effects could be demonstrated for the other immunoglobulin isotypes. Time-course studies showed that the synthesis of IgM by CBMC was accelerated with detectable immunoglobulin in supernatant fluids starting on day 3. ROH augmented immunoglobulin synthesis of CBMC stimulated by Epstein-Barr virus (EBV), a T cell-independent polyclonal activator, and of EBV-transformed B cell clones (2.5 +/- 0.2 and 4.1 +/- 1.5-fold increase, respectively), which suggests that ROH can act directly on B cells to enhance immunoglobulin synthesis. In contrast, when ROH was preincubated with cord blood T cells, washed and added to the B cell-enriched fraction with SAC, no increase (0.9-1.8-fold) in IgM synthesis was obtained. Thus, the principal mechanism(s) by which ROH augments immunoglobulin synthesis is by acting on B cells. This is in contrast to the immunoglobulin-enhancing effects of RA which is mediated by T cells, or T cell products, e.g. cytokine. Our studies suggest that RA and ROH may have different pathways of immunoglobulin-enhancing effects, perhaps mediated by different retinoid binding proteins resulting in gene activation and immunoglobulin synthesis.     

Biclustering meets triadic concept analysis

Biclustering numerical data became a popular data-mining task at the beginning of 2000’s, especially for gene expression data analysis and recommender systems. A bicluster reflects a strong association between a subset of objects and a subset of attributes in a numerical object/attribute data-table. So-called biclusters of similar values can be thought as maximal sub-tables with close values. Only few methods address a complete, correct and non-redundant enumeration of such patterns, a well-known intractable problem, while no formal framework exists. We introduce important links between biclustering and Formal Concept Analysis (FCA). Indeed, FCA is known to be, among others, a methodology for biclustering binary data. Handling numerical data is not direct, and we argue that Triadic Concept Analysis (TCA), the extension of FCA to ternary relations, provides a powerful mathematical and algorithmic framework for biclustering numerical data. We discuss hence both theoretical and computational aspects on biclustering numerical data with triadic concept analysis. These results also scale to n-dimensional numerical datasets.     

Generating Rare Association Rules Using the Minimal Rare Itemsets Family

Rare association rules correspond to rare, or infrequent, itemsets, as opposed to frequent ones that are targeted by conventional pattern miners. Rare rules reflect regularities of local, rather than global, scope that can nevertheless provide valuable insights to an expert, especially in areas such as genetics and medical diagnosis where some specific deviations/illnesses occur only in a small number of cases. The work presented here is motivated by the long-standing open question of efficiently mining strong rare rules, i.e., rules with high confidence and low support. We also propose an efficient solution for finding the set of minimal rare itemsets. This set serves as a basis for generating rare association rules.     

FPGA-based architecture for real time segmentation and denoising of HD video

The identification of moving objects is a basic step in computer vision. The identification begins with the segmentation and is followed by a denoising phase. This paper proposes the FPGA hardware implementation of segmentation and denoising unit. The segmentation is conducted using the Gaussian mixture model (GMM), a probabilistic method for the segmentation of the background. The denoising is conducted implementing the morphological operators of erosion, dilation, opening and closing. The proposed circuit is optimized to perform real time processing of HD video sequences (1,920 × 1,080 @ 20 fps) when implemented on FPGA devices. The circuit uses an optimized fixed width representation of the data and implements high performance arithmetic circuits. The circuit is implemented on Xilinx and Altera FPGA. Implemented on xc5vlx50 Virtex5 FPGA, it can process 24 fps of an HD video using 1,179 Slice LUTs and 291 Slice Registers; the dynamic power dissipation is 0.46 mW/MHz. Implemented on EP2S15F484C3 StratixII, it provides a maximum working frequency of 44.03 MHz employing 5038 Logic Elements and 7,957 flip flop with a dynamic power dissipation of 4.03 mW/MHz.     

Conductivity of Nafion 117 membrane used in polymer electrolyte fuel cells

The membrane electric transport (MC) directly influences the performance of the polymer electrolyte fuel cells (PEMFC). The membrane conductivity is determined by a number of parameters such as: hydration technique, graphite cell geometry and pressure applied when the membrane electrode assembly (MEA) is joined. In addition, the membrane conductivity might be influenced by the electrode position due to the possibility of anisotropic electric conductivity.     

Maximally entangled states of a bimodal cavity field

Abstract

A simple scheme for the generation of a class of maximally entangled two-mode field states is presented. Our proposal provides the possibility of manipulating the quantum coherence between the superposed states, simply varying an experimentally easily controllable parameter. The practical feasibility of the method here reported is carefully discussed.     

Microbiological and physicochemical characterisation of green table olives of Halkidiki and Conservolea varieties processed by the Spanish method on industrial scale

The microbiological and physicochemical changes of industrially fermented Halkidiki and Conservolea green table olives were determined. Samples were analysed to monitor the population of lactic acid bacteria (LAB), yeasts and Enterobacteriaceae, together with changes in pH, acidity, salinity, colour, lactic acid, acetic acid and ethanol. LAB and yeast species diversity was evaluated at the beginning (1 day), middle (75 days) and final (135 days) stages of fermentation by RAPD-PCR genomic fingerprinting. Results revealed vigorous lactic acid processes as indicated by the dominance of LAB over yeasts. No Enterobacteriaceae could be detected after 30 days. Lactiplantibacillus plantarum (formerly Lactobacillus plantarum) dominated in the beginning of fermentation in both varieties. In the end, Lactiplantibacillus pentosus (formerly Lactobacillus pentosus) and Pediococcus ethanolidurans prevailed in Halkidiki and Conservolea varieties, respectively. As for yeasts, Kluyveromyces lactis/marxianus and Pichia manshurica prevailed at the onset of fermentation in Halkidiki and Conservolea varieties, whereas in the end Pichia membranifaciens dominated in both varieties.