898 resultados para N-Dimensional Co-occurrence Matrix


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With the overwhelming increase in the amount of texts on the web, it is almost impossible for people to keep abreast of up-to-date information. Text mining is a process by which interesting information is derived from text through the discovery of patterns and trends. Text mining algorithms are used to guarantee the quality of extracted knowledge. However, the extracted patterns using text or data mining algorithms or methods leads to noisy patterns and inconsistency. Thus, different challenges arise, such as the question of how to understand these patterns, whether the model that has been used is suitable, and if all the patterns that have been extracted are relevant. Furthermore, the research raises the question of how to give a correct weight to the extracted knowledge. To address these issues, this paper presents a text post-processing method, which uses a pattern co-occurrence matrix to find the relation between extracted patterns in order to reduce noisy patterns. The main objective of this paper is not only reducing the number of closed sequential patterns, but also improving the performance of pattern mining as well. The experimental results on Reuters Corpus Volume 1 data collection and TREC filtering topics show that the proposed method is promising.

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Grey Level Co-occurrence Matrices (GLCM) are one of the earliest techniques used for image texture analysis. In this paper we defined a new feature called trace extracted from the GLCM and its implications in texture analysis are discussed in the context of Content Based Image Retrieval (CBIR). The theoretical extension of GLCM to n-dimensional gray scale images are also discussed. The results indicate that trace features outperform Haralick features when applied to CBIR.

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Given the spread of antibiotic resistance in bacterial pathogens, antimicrobial peptides that can also modulate the immune response may be a novel approach for effectively controlling periodontal infections. In the present study, we used a three-dimensional (3D) co-culture model of gingival epithelial cells and fibroblasts stimulated with Aggregatibacter actinomycetemcomitans lipopolysaccharide (LPS) to investigate the anti-inflammatory properties of human beta-defensin-3 (hBD-3) and cathelicidin (LL-37) and to determine whether these antimicrobial peptides can act in synergy. The 3D co-culture model composed of gingival fibroblasts embedded in a collagen matrix overlaid with gingival epithelial cells had a synergistic effect with respect to the secretion of IL-6 and IL-8 in response to LPS stimulation compared to fibroblasts and epithelial cells alone. The 3D co-culture model was stimulated with non-cytotoxic concentrations of hBD-3 (10 and 20 mu M) and LL-37 (0.1 and 0.2 mu M) individually and in combination in the presence of A. actinomycetemcomitans LPS. A multiplex ELISA assay was used to quantify the secretion of 41 different cytokines. hBD-3 and LL-37 acted in synergy to reduce the secretion of GRO-alpha, G-CSF, IP-10, IL-6, and MCP-1, but only had an additive effect on reducing the secretion of IL-8 in response to A. actinomycetemcomitans LPS stimulation. The present study showed that hBD-3 acted in synergy with LL-37 to reduce the secretion of cytokines by an LPS-stimulated 3D model of gingival mucosa. This combination of antimicrobial peptides thus shows promising potential as an adjunctive therapy for treating inflammatory periodontitis.

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Objectives: The human antimicrobial peptide cathelicidin (LL-37) possesses anti-inflammatory properties that may contribute to attenuating the inflammatory process associated with chronic periodontitis. Plant polyphenols, including those from cranberry and green tea, have been reported to reduce inflammatory cytokine secretion by host cells. In the present study, we hypothesized that A-type cranberry proanthocyanidins (AC-PACs) and green tea epigallocatechin-3-gallate (EGCG) act in synergy with LL-37 to reduce the secretion of inflammatory mediators by oral mucosal cells. Methods: A three-dimensional (3D) co-culture model of gingival epithelial cells and fibroblasts treated with non-cytotoxic concentrations of AC-PACs (25 and 50 mg/ml), EGCG (1 and 5 mg/ml), and LL-37 (0.1 and 0.2 mM) individually and in combination (AC-PACs + LL-37 and EGCG + LL-37) were stimulated with Aggregatibacter actinomycetemcomitans lipopolysaccharide (LPS). Multiplex ELISA assays were used to quantify the secretion of 54 host factors, including chemokines, cytokines, growth factors, matrix metalloproteinases (MMPs), and tissue inhibitors of metalloproteinases (TIMPs). Results: LL-37, AC-PACs, and EGCG, individually or in combination, had no effect on the regulation of MMP and TIMP secretion but inhibited the secretion of several cytokines. ACPACs and LL-37 acted in synergy to reduce the secretion of CXC-chemokine ligand 1 (GRO-a), granulocyte colony-stimulating factor (G-CSF), and interleukin-6 (IL-6), and had an additive effect on reducing the secretion of interleukin-8 (IL-8), interferon-g inducible protein 10 (IP-10), and monocyte chemoattractant protein-1 (MCP-1) in response to LPS stimulation. EGCG and LL-37 acted in synergy to reduce the secretion of GRO-a, G-CSF, IL-6, IL-8, and IP-10, and had an additive effect on MCP-1 secretion. Conclusion: The combination of LL-37 and natural polyphenols from cranberry and green tea acted in synergy to reduce the secretion of several cytokines by an LPS-stimulated 3D coculture model of oral mucosal cells. Such combinations show promising results as potential adjunctive therapies for treating inflammatory periodontitis.

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The co-occurrence of warm conveyor belts (WCBs), strongly ascending moist airstreams in extratropical cyclones, and stratospheric potential vorticity (PV) streamers, indicators for breaking Rossby waves on the tropopause, is investigated for a 21-yr period in the Northern Hemisphere using Interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) data. WCB outflows and PV streamers are respectively identified as two- and three-dimensional objects and tracked during their life cycle. PV streamers are more frequent than WCB outflows and nearly 15% of all PV streamers co-occur with WCBs during their life cycle, whereas about 60% of all WCB outflows co-occur with PV streamers. Co-occurrences are most frequent over the North Atlantic and North Pacific in spring and winter. WCB outflows are often located upstream of the PV streamers and form earlier, indicating the importance of diabatic processes for downstream Rossby wave breaking. Less frequently, PV streamers occur first, leading to the formation of new WCBs.

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We explore the fuse of information on co-occurrence of domains in multi-domain proteins in predicting protein-protein interactions. The basic premise of our work is the assumption that domains co-occurring in a polypeptide chain undergo either structural or functional interactions among themselves. In this study we use a template dataset of domains in multidomain proteins and predict protein-protein interactions in a target organism. We note that maximum number of correct predictions of interacting protein domain families (158) is made in S. cerevisiae when the dataset of closely related organisms is used as the template followed by the more diverse dataset of bacterial proteins (48) and a dataset of randomly chosen proteins (23). We conclude that use of multi-domain information from organisms closely-related to the target can aid prediction of interacting protein families.

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A high-performance supercapacitor electrode based on unique 1D Co-Ni/Co3O4-NiO core/shell nano-heterostructures is designed and fabricated. The nano-heterostructures exhibit high specific capacitance (2013 F g(-1) at 2.5 A g(-1)), high energy and power density (23Wh kg(-1) and 5.5kW kg(-1), at the discharge current density of 20.8 A g(-1)), good capacitance retention and long cyclicality. The remarkable electrochemical property of the large surface area nano-heterostructures is demonstrated based on the effective nano-architectural design of the electrode with the coexistence of the two highly redox active materials at the surface supported by highly conducting metal alloy channel at the core for faster charge transport. (C) 2014 AIP Publishing LLC.

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Plant community ecologists use the null model approach to infer assembly processes from observed patterns of species co-occurrence. In about a third of published studies, the null hypothesis of random assembly cannot be rejected. When this occurs, plant ecologists interpret that the observed random pattern is not environmentally constrained - but probably generated by stochastic processes. The null model approach (using the C-score and the discrepancy index) was used to test for random assembly under two simulation algorithms. Logistic regression, distance-based redundancy analysis, and constrained ordination were used to test for environmental determinism (species segregation along environmental gradients or turnover and species aggregation). This article introduces an environmentally determined community of alpine hydrophytes that presents itself as randomly assembled. The pathway through which the random pattern arises in this community is suggested to be as follows: Two simultaneous environmental processes, one leading to species aggregation and the other leading to species segregation, concurrently generate the observed pattern, which results to be neither aggregated nor segregated - but random. A simulation study supports this suggestion. Although apparently simple, the null model approach seems to assume that a single ecological factor prevails or that if several factors decisively influence the community, then they all exert their influence in the same direction, generating either aggregation or segregation. As these assumptions are unlikely to hold in most cases and assembly processes cannot be inferred from random patterns, we would like to propose plant ecologists to investigate specifically the ecological processes responsible for observed random patterns, instead of trying to infer processes from patterns

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Bycatch and resultant discard mortality are issues of global concern. The groundfish demersal trawl fishery on the west coast of the United States is a multispecies fishery with significant catch of target and nontarget species. These catches are of particular concern in regard to species that have previously been declared overfished and are currently rebuilding biomass back to target levels. To understand these interactions better, we used data from the West Coast Groundfish Observer Program in a series of cluster analyses to evaluate 3 questions: 1) Are there identifiable associations between species caught in the bottom trawl fishery; 2) Do species that are undergoing population rebuilding toward target biomass levels (“rebuilding species”) cluster with targeted species in a consistent way; 3) Are the relationships between rebuilding bycatch species and target species more resolved at particular spatial scales or are relationships spatially consistent across the whole data set? Two strong species clusters emerged—a deepwater slope cluster and a shelf cluster—neither of which included rebuilding species. The likelihood of encountering rebuilding rockfish species is relatively low. To evaluate whether weak clustering of rebuilding rockfish was attributable to their low rate of occurrence, we specified null models of species occurrence. Results indicated that the ability to predict occurrence of rebuilding rockfish when target species were caught was low. Cluster analyses performed at a variety of spatial scales indicated that the most reliable clustering of rebuilding species was at the spatial scale of individual fishing ports. This finding underscores the value of spatially resolved data for fishery management.

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The rockfishes of the sebastid genus Sebastes are a very important fishery resource off the coasts of California and southern Oregon. How-ever, many of the 54 managed stocks of west coast rockfish have recently reached historically low population levels, leading fishery managers to re-examine current management practices. Management of rockfish stocks as multispecies aggregates, as opposed to independent stocks within the ground-fish fishery, can be more desirable when nontargeted bycatch, discard, and management complexity are considered. Rockfish assemblage structure and species co-occurrences were determined by using data from the Alaska Fisheries Science Center triennial continental shelf bottom trawl survey. The weight of rockfish species in trawl catches was expressed as a catch-per-unit-of-effort (CPUE) statistic, from which species spatial distributions, overlaps, diversity, and richness were analyzed. Multidimensional scaling of transformed CPUE data was employed in indirect gradient and multivariate partitioning analyses to quantify assemblage relationships. Results indicated that rockfish distributions closely match the bathymetry of coastal waters. Indirect gradient analysis suggested that depth and latitude are the principal factors in structuring the spatial distributions of rockfish on trawlable habitat. In addition, four assemblages were identified through the joint evaluation of species’ distributions and multivariate partitioning analyses: 1) deep-water slope; 2) northern shelf; 3) southern shelf; and 4) nearshore. The slope, shelf, and near-shore groups are found in depth ranges of 200–500 m, 100–250 m, and 50–150 m, respectively. The division of northern and southern shelf assemblages occurs over a broad area between Cape Mendocino and Monterey Canyon. The results of this analysis are likely to have direct application in the management of rockfish stocks off the coasts of southern Oregon and California.

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Co-occurrence of double pathogenic mtDNA mutations with different claimed pathological roles in one mtDNA is infrequent. It is tentative to believe that each of these pathogenic mutations would have its own deleterious effect. Here we reported one three-g

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The last few years have seen considerable progress in pedestrian detection. Recent work has established a combination of oriented gradients and optic flow as effective features although the detection rates are still unsatisfactory for practical use. This paper introduces a new type of motion feature, the co-occurrence flow (CoF). The advance is to capture relative movements of different parts of the entire body, unlike existing motion features which extract internal motion in a local fashion. Through evaluations on the TUD-Brussels pedestrian dataset, we show that our motion feature based on co-occurrence flow contributes to boost the performance of existing methods. © 2011 IEEE.