Narrow Results

Systems of data integration using ontologies aim to implement a collaborative environment between sources for sharing data and services to respond a user request for information. Their users’ requests are an exact expression of their needs. However, the multiplicity of data sources, their scalability and the increasing difficulty to control their descriptions and their contents are the reasons behind the implacability of this assumption today. The users now may not know the data sources they questioned, nor their description or content. Consequently, their queries reflect no more a need that must be satisfied but an intention that must be refined according to data sources available at the time of interrogation. In this work, we present a semantic-based approach to enrich user’ queries expressed in SPARQL Language by his preferences in order to adapt the returned results and make them more precise and more relevant. The proposed approach is applied on a movies management system based on the standard MovieLens dataset. The obtained results are compared to existing approaches according to precision and recall measures. Our approach improved the precision with 26% and the recall with 7% comparing to those of previous study using collaborative filtering.

A simple predator–prey system with disease in prey population and alternative food for the predator is proposed and analyzed. The main objective of the present investigation is to observe the conditions for which the disease in prey population will be controlled. It is observed that supply of alternative food to the predator population can make the system disease free. Enrichment also plays an important role in suppressing the infected population in the presence of alternative food. However, in the absence of predator population, enrichment increases the disease prevalence instead of reducing it. We finally conclude that supply of alternative food to the predator provides a healthy disease free system.

Mapping short reads to a reference genome is an essential step in many next-generation sequencing (NGS) analyses. In plants with large genomes, a large fraction of the reads can align to multiple locations of the genome with equally good alignment scores. How to map these ambiguous reads to the genome is a challenging problem with big impacts on the downstream analysis. Traditionally, the default method is to assign an ambiguous read randomly to one of the many potential locations. In this study, we explore two alternative methods that are based on the hypothesis that the possibility of an ambiguous read being generated by a location is proportional to the total number of reads produced by that location: (1) the enrichment method that assigns an ambiguous read to the location that has produced the most reads among all the potential locations, (2) the probability method that assigns an ambiguous read to a location based on a probability proportional to the number of reads the location produces. We systematically compared the performance of the proposed methods with that of the default random method. Our results showed that the enrichment method produced better results than the default random method and the probability method in the discovery of single nucleotide polymorphisms (SNPs). Not only did it produce more SNP markers, but it also produced SNP markers with better quality, which was demonstrated using multiple mainstay genomic analyses, including genome-wide association studies (GWAS), minor allele distribution, population structure, and genomic prediction.

An enrichment technique for accurately modeling two dimensional crack propagation within the framework of the finite element method is presented. The technique uses an enriched basis that spans the asymptotic dynamic crack-tip solution. The enrichment functions and their spatial derivatives are able to exactly reproduce the asymptotic displacement field and strain field for a moving crack. The stress intensity factors for Mode I and Mode II are taken as additional degrees of freedom. An explicit time integration scheme is used to solve the resulting discrete equations. Numerical simulations of linear elastodynamic problems are reported to demonstrate the accuracy and potential of the technique.

Confined bears are deprived of natural stimulus, such as large roaming domains, active foraging and enriched habitats, making them vulnerable to develop stereotypic behaviors. Motivation drives and neuro-pathological imbalance are the causes. Various stereotypic behavior types have been reported, including oral, head and locomotory related behaviors, and pacing are the most commonly seen. Stereotypic behavior level could be monitored using an observation-reporting system or fecal corticoid. Environmental and feeding enrichment are the proposed solutions; however, habituation could be developed. Parallel intermittent and consecutive environmental enrichment and unpredictable feeding schedule would be beneficial. Medication, especially long-term and low-dosage fluoxetine, was found to be effective in alleviating bear stereotypic behaviors.

A composite of chromium (III) terephthalate metal-organic framework and graphene oxide (MIL-101/GO) coated stir bar was prepared by sol–gel technique for the first time and was employed for stir bar sorptive extraction (SBSE) of trace azo dyes amaranth, sunset yellow and carmine from water samples followed by UV–Vis spectrophotometric detection. A MIL-101/GO coating was first created on the glass bar surface. MIL-101/GO and MIL-101/GO coated stir bars were characterized. The enrichment factors of azo dyes by SBSE have been investigated in detail, and the optimized experimental parameters were obtained. Under the optimal conditions, a method for determination of trace amount of azo dyes was setup, and the detection limits of amaranth, sunset yellow and carmine were 2.3 ng/mL, 1.7 ng/mL and 1.6 ng/mL. The proposed method was successfully applied for the analysis of the three azo dyes in water samples.

In this paper, a new methodology to analyze three dimensional crack problems with flexible modeling by means of overlaying mesh method and extended finite element method (X-FEM) is presented. The overlaying mesh method increases the accuracy of analysis locally by superimposing additional mesh of higher resolution on the global mesh which represents rough deformation of structures. In this method the boundaries and nodes in the two meshes do not have to coincide with each other. It makes modeling process becomes very flexible. In X-FEM, discontinuous function and the two-dimensional asymptotic crack-tip displacement fields are added to the finite element approximation to account for the crack using the notion of partition of unity. This technique allows the entire crack to be represented independently of the mesh. As numerical example, an inclined semi-circle surface crack under tension is analyzed.

The anaerobic ammonium oxidation (anammox) microbe in an upflow anaerobic sludge blanket (UASB) bioreactor was successfully enriched under inorganic and dark condition. Seven species were isolated and purified in conventional methods from the activated sludge. Based on the morphological, physiological, biochemical and 16S rRNA analysis, these bacteria belonged to Pseudomonas sp, Clostridium beijerinckii, Bacillus cereus, two kinds of Bacillus sp., Sphingosinicella microcystinivorans and unidentified bacterium. The cells concentration of E1 strain (Pseudomonas sp) (>10⁷ cell/ml) was the highest of these seven kinds of bacteria. The anammox activities of the seven strains were evaluated. Only E1 strain made ammonium oxidize in anaerobic condition. E1 was a denitrifying bacterium and had some anammox activity.

Eighty percent of DNA outside protein coding regions was shown biochemically functional by the ENCODE project, enabling studies of their interactions. Studies have since explored how convergent downstream mechanisms arise from independent genetic risks of one complex disease. However, the cross-talk and epistasis between intergenic risks associated with distinct complex diseases have not been comprehensively characterized. Our recent integrative genomic analysis unveiled downstream biological effectors of disease-specific polymorphisms buried in intergenic regions, and we then validated their genetic synergy and antagonism in distinct GWAS. We extend this approach to characterize convergent downstream candidate mechanisms of distinct intergenic SNPs across distinct diseases within the same clinical classification. We construct a multipartite network consisting of 467 diseases organized in 15 classes, 2,358 disease-associated SNPs, 6,301 SNPassociated mRNAs by eQTL, and mRNA annotations to 4,538 Gene Ontology mechanisms. Functional similarity between two SNPs (similar SNP pairs) is imputed using a nested information theoretic distance model for which p-values are assigned by conservative scale-free permutation of network edges without replacement (node degrees constant). At FDR≤5%, we prioritized 3,870 intergenic SNP pairs associated, among which 755 are associated with distinct diseases sharing the same disease class, implicating 167 intergenic SNPs, 14 classes, 230 mRNAs, and 134 GO terms. Co-classified SNP pairs were more likely to be prioritized as compared to those of distinct classes confirming a noncoding genetic underpinning to clinical classification (odds ratio ∼3.8; p≤10-25). The prioritized pairs were also enriched in regions bound to the same/interacting transcription factors and/or interacting in long-range chromatin interactions suggestive of epistasis (odds ratio ∼ 2,500; p≤10^-25). This prioritized network implicates complex epistasis between intergenic polymorphisms of co-classified diseases and offers a roadmap for a novel therapeutic paradigm: repositioning medications that target proteins within downstream mechanisms of intergenic disease-associated SNPs. Supplementary information and software: http://lussiergroup.org/publications/disease_class