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.     

A fast compound algorithm for mining generators,closed itemsets,and computing links between equivalence classes

In pattern mining and association rule mining, there is a variety of algorithms for mining frequent closed itemsets (FCIs) and frequent generators (FGs), whereas a smaller part further involves the precedence relation between FCIs. The interplay of these three constructs and their joint computation have been studied within the formal concept analysis (FCA) field yet none of the proposed algorithms is scalable. In frequent pattern mining, at least one suite of efficient algorithms has been designed that exploits basically the same ideas and follows the same overall computational schema. Based on an in-depth analysis of the aforementioned interplay that is rooted in a fundamental duality from hypergraph theory, we propose a new schema that should enable for a more parsimonious computation. We exemplify the new schema in the design of Snow-Touch, a concrete FCI/FG/precedence miner that reuses an existing algorithm, Charm, for mining FCIs, and completes it with two original methods for mining FGs and precedence, respectively. The performance of Snow-Touch and of its closest competitor, Charm-L, were experimentally compared using a large variety of datasets. The outcome of the experimental study suggests that our method outperforms Charm-L on dense data while on sparse one the trend is reversed. Furthermore, we demonstrate the usefulness of our method and the new schema through an application to the analysis of a genome dataset. The initial results reported here confirm the capacity of the method to focus on significant associations.     

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.     

Software assessment using metrics: A comparison across large C++ and Java systems

This paper presents an assessment method to evaluate the quality of object oriented software systems. The assessment method is based on source code abstraction, object–oriented metrics and graphical representation. The metrics used and the underlying model representing the software are presented. The assessment method experiment is part of an industrial research effort with the Bell Canada Quality Engineering and Research Group. It helps evaluators assess the quality and risks associated with software by identifying code fragments presenting unusual characteristics. The assessment method evaluates object–oriented software systems at three levels of granularity: system level, class level and method level. One large C++ and eight Java software systems, for a total of over one million lines of code, are presented as case studies. A critical analysis of the results is presented comparing the systems and the two languages.