ClioPatria: A SWI-Prolog Infrastructure for the Semantic Web

ClioPatria is a comprehensive semantic web development framework based on SWI-Prolog. SWI-Prolog provides an efficient C-based main-memory RDF store that is designed to cooperate naturally and efficiently with Prolog, realizing a flexible RDF-based environment for rule based programming. ClioPatria extends this core with a SPARQL and LOD server, an extensible web frontend to manage the server, browse the data, query the data using SPARQL and Prolog and a Git-based plugin manager. The ability to query RDF using Prolog provides query composition and smooth integration with application logic. ClioPatria is primarily positioned as a prototyping platform for exploring novel ways of reasoning with RDF data. It has been used in several research projects in order to perform tasks such as data integration and enrichment and semantic search

Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development

<p>Abstract</p> <p>Background</p> <p>The Gene Ontology project supports categorization of gene products according to their location of action, the molecular functions that they carry out, and the processes that they are involved in. Although the ontologies are intentionally developed to be taxon neutral, and to cover all species, there are inherent taxon specificities in some branches. For example, the process 'lactation' is specific to mammals and the location 'mitochondrion' is specific to eukaryotes. The lack of an explicit formalization of these constraints can lead to errors and inconsistencies in automated and manual annotation.</p> <p>Results</p> <p>We have formalized the taxonomic constraints implicit in some GO classes, and specified these at various levels in the ontology. We have also developed an inference system that can be used to check for violations of these constraints in annotations. Using the constraints in conjunction with the inference system, we have detected and removed errors in annotations and improved the structure of the ontology.</p> <p>Conclusions</p> <p>Detection of inconsistencies in taxon-specificity enables gradual improvement of the ontologies, the annotations, and the formalized constraints. This is progressively improving the quality of our data. The full system is available for download, and new constraints or proposed changes to constraints can be submitted online at <url>https://sourceforge.net/tracker/?atid=605890&group_id=36855</url>.</p

Butyrate restores HFD-induced adaptations in brain function and metabolism in mid-adult obese mice

Item does not contain fulltextOBJECTIVE: Midlife obesity affects cognition and increases risk of developing dementia. Recent data suggest that intake of the short chain fatty acid butyrate could improve memory function, and may protect against diet-induced obesity by reducing body weight and adiposity. SUBJECTS: We examined the impact of a high-fat diet (HFD) followed by intervention with 5% (w/w) dietary butyrate, on metabolism, microbiota, brain function and structure in the low-density-lipoprotein receptor knockout (LDLr-/-) mouse model in mid and late life. RESULTS: In mid-adult mice, 15 weeks of HFD-induced adiposity, liver fibrosis and neuroinflammation, increased systolic blood pressure and decreased cerebral blood flow, functional connectivity assessed with neuroimaging. The subsequent 2 months butyrate intervention restored these detrimental effects to chow-fed control levels. Both HFD and butyrate intervention decreased variance in fecal microbiota composition. In late-adult mice, HFD showed similar detrimental effects and decreased cerebral white and gray matter integrity, whereas butyrate intervention attenuated only metabolic parameters. CONCLUSION: HFD induces detrimental effects in mid- and late-adult mice, which can be attenuated by butyrate intervention. These findings are consistent with reported associations between midlife obesity and cognitive impairment and dementia in humans. We suggest that butyrate may have potential in prevention and treatment of midlife obesity

Typed meta-interpretive learning of logic programs

Meta-interpretive learning (MIL) is a form of inductive logic programming that learns logic programs from background knowledge and examples. We claim that adding types to MIL can improve learning performance. We show that type checking can reduce the MIL hypothesis space by a cubic factor. We introduce two typed MIL systems: Metagol T and HEXMIL T , implemented in Prolog and Answer Set Programming (ASP), respectively. Both systems support polymorphic types and can infer the types of invented predicates. Our experimental results show that types can substantially reduce learning times

Policies for sustainable development in the hillside areas of Honduras: a quantitative livelihoods approach

In this article, we use data for 376 households, 1,066 parcels, and 2,143 plots located in 95 villages in the hillside areas in Honduras to generate information needed by decision makers to assess the needs and opportunities for public investments, and design policies that stimulate natural resource conservation. We develop a quantitative livelihood approach, using factor and cluster analysis to group households based on the use of their main assets. This resulted in seven household categories that pursue similar livelihood strategies. We use a multinomial logit model to show that livelihood strategies are determined by comparative advantages as reflected by a combination of biophysical and socioeconomic variables. While 92% of the rural hillsides population in Honduras lives on US$1.00/capita/day or less, households that follow a livelihood strategy based on basic grain farming are the poorest because they often live in isolated areas with relatively poor agro-ecological and socioeconomic conditions. Opportunities for off-farm work tend to be limited in these areas and household strategies that combine on-farm work with off-farm work earn higher incomes. Per capita incomes can be increased by improving road infrastructure, widening access to land, policies that reduce household size and dependency ratios, and adoption of sustainable land management technologies that restore soil fertility. We used probit models to show that the latter can be promoted by agricultural extension programs and land redistribution. Investments in physical assets should be directed toward households that pursue livelihood strategies based on off-farm employment or coffee production, while agricultural training programs are best focused on livestock producers. Copyright 2006 International Association of Agricultural Economics.