Freedom, Earth, World: An Arendtian Eco-politics of Dissent

This article draws upon Arendt offering a phenomenological defence of democratic freedom and the right to dissent. There are, broadly speaking, three parts to the paper. The first part investigates the distinction between the artificiality of the world and materiality of the earth (that cannot be entirely separated) which has important consequences for her discussion of alienation. Therefore, under an Arendtian diagnosis, as we seek to rebalance human life on the planet, we may also need to re-acquaint ourselves with the complex space that constitutes the common world. The second part concentrates on Arendt’s descriptions of the world which are underscored by a sense of distance which both relates and separates members. The third part connects this phenomenology of world to Arendt’s more explicitly political works. By looking at its relationship to her notion of freedom, I propose a reading of the concept which emphasises the role of dissent, as a key element of her understanding of political intersubjectivity. Within the context of environmentalist politics, this account can be used to critique the tendency to reduce politics to a techne; which may resist both romantic calls for an organic return to nature, or promises to technologically liberate humankind from the limitations prescribed by our planetary condition.This article draws upon Arendt offering a phenomenological defence of democratic freedom and the right to dissent. There are, broadly speaking, three parts to the paper. The first part investigates the distinction between the artificiality of the world and materiality of the earth (that cannot be entirely separated) which has important consequences for her discussion of alienation. Therefore, under an Arendtian diagnosis, as we seek to rebalance human life on the planet, we may also need to re-acquaint ourselves with the complex space that constitutes the common world. The second part concentrates on Arendt’s descriptions of the world which are underscored by a sense of distance which both relates and separates members. The third part connects this phenomenology of world to Arendt’s more explicitly political works. By looking at its relationship to her notion of freedom, I propose a reading of the concept which emphasises the role of dissent, as a key element of her understanding of political intersubjectivity. Within the context of environmentalist politics, this account can be used to critique the tendency to reduce politics to a techne; which may resist both romantic calls for an organic return to nature, or promises to technologically liberate humankind from the limitations prescribed by our planetary condition

Extending the mutual information measure to rank inferred literature relationships

BACKGROUND: Within the peer-reviewed literature, associations between two things are not always recognized until commonalities between them become apparent. These commonalities can provide justification for the inference of a new relationship where none was previously known, and are the basis of most observation-based hypothesis formation. It has been shown that the crux of the problem is not finding inferable associations, which are extraordinarily abundant given the scale-free networks that arise from literature-based associations, but determining which ones are informative. The Mutual Information Measure (MIM) is a well-established method to measure how informative an association is, but is limited to direct (i.e. observable) associations. RESULTS: Herein, we attempt to extend the calculation of mutual information to indirect (i.e. inferable) associations by using the MIM of shared associations. Objects of general research interest (e.g. genes, diseases, phenotypes, drugs, ontology categories) found within MEDLINE are used to create a network of associations for evaluation. CONCLUSIONS: Mutual information calculations can be effectively extended into implied relationships and a significance cutoff estimated from analysis of random word networks. Of the models tested, the shared minimum MIM (MMIM) model is found to correlate best with the observed strength and frequency of known associations. Using three test cases, the MMIM method tends to rank more specific relationships higher than counting the number of shared relationships within a network

On the relative importance of agglomeration economies in the location of FDI across British regions

The paper examines the relative importance for industrial location of production linkages and knowledge spillovers, distinguishing between intermediate and non-intermediate goods that are backwards or forwards in nature. A novel approach is used to construct proxies for non-intermediate goods at a sub-national industry level based on an Input-Output transaction table. Taking data on location decisions by foreign-owned plants across British regions over 1985-2007, the paper finds support for the new economic geography explanation of location based on linkages over that due to spillovers. However, the importance of intermediate and non-intermediate linkages differs between manufacturing and service industries

Truth, Probability, and Frameworks

Yeshttp://www.plosmedicine.org/static/editorial#pee

Economic integration, border costs and FDI location: evidence from the fifth European enlargement

Little is known about the effect of border costs on FDI location. This paper explores this for the fifth European Union (EU) enlargement that integrated the ten Central and Eastern European countries (CEECs). It regresses count data for 35,105 FDI projects locating in 25 European countries over the period 1997–2010. Four EU accession events are examined for the more- and less-liberalized CEECs. It finds that the lower border costs doubled FDI in the CEECs at EU membership, of which 60% is diverted from the ‘old’ Europe. This membership effect is threetimes greater for the more-liberalized countries, for which earlier accession events are unimportant

Data-Mining Analysis Suggests an Epigenetic Pathogenesis for Type 2 Diabetes

The etiological origin of type 2 diabetes mellitus (T2DM) has long been controversial. The body of literature related to T2DM is vast and varied in focus, making a broad epidemiological perspective difficult, if not impossible. A data-mining approach was used to analyze all electronically available scientific literature, over 12 million Medline records, for “objects” such as genes, diseases, phenotypes, and chemical compounds linked to other objects within the T2DM literature but were not themselves within the T2DM literature. The goal of this analysis was to conduct a comprehensive survey to identify novel factors implicated in the pathology of T2DM by statistically evaluating mutually shared associations. Surprisingly, epigenetic factors were among the highest statistical scores in this analysis, strongly implicating epigenetic changes within the body as causal factors in the pathogenesis of T2DM. Further analysis implicates adipocytes as the potential tissue of origin, and cytokines or cytokine-like genes as the dysregulated factor(s) responsible for the T2DM phenotype. The analysis provides a wealth of literature supporting this hypothesis, which—if true—represents an important paradigm shift for researchers studying the pathogenesis of T2DM

Electronic Journals in Business Schools: Legitimacy, Acceptance, and Use

This research provides insight into perceptions regarding electronic journals: a technological innovation in academia. Acceptance of electronic journals among business school faculty has two hurdles to overcome: technological and, more challenging, garnering legitimacy within the academic community. A survey targeted at business school faculty in the United States was conducted investigating faculty perceptions about the acceptance of electronic journals in their academic discipline. The findings suggest that at the time of publication, electronic publications were seen as less desirable than paper counterparts for tenure and review. However, it appears that electronic counterparts of existing journals would maintain their legitimacy from a promotion and tenure perspective, suggesting that the perceived legitimacy of the journal is the critical hurdle to overcome

Predicting gene ontology from a global meta-analysis of 1-color microarray experiments

<p>Abstract</p> <p>Background</p> <p>Global meta-analysis (GMA) of microarray data to identify genes with highly similar co-expression profiles is emerging as an accurate method to predict gene function and phenotype, even in the absence of published data on the gene(s) being analyzed. With a third of human genes still uncharacterized, this approach is a promising way to direct experiments and rapidly understand the biological roles of genes. To predict function for genes of interest, GMA relies on a guilt-by-association approach to identify sets of genes with known functions that are consistently co-expressed with it across different experimental conditions, suggesting coordinated regulation for a specific biological purpose. Our goal here is to define how sample, dataset size and ranking parameters affect prediction performance.</p> <p>Results</p> <p>13,000 human 1-color microarrays were downloaded from GEO for GMA analysis. Prediction performance was benchmarked by calculating the distance within the Gene Ontology (GO) tree between predicted function and annotated function for sets of 100 randomly selected genes. We find the number of new predicted functions rises as more datasets are added, but begins to saturate at a sample size of approximately 2,000 experiments. For the gene set used to predict function, we find precision to be higher with smaller set sizes, yet with correspondingly poor recall and, as set size is increased, recall and F-measure also tend to increase but at the cost of precision.</p> <p>Conclusions</p> <p>Of the 20,813 genes expressed in 50 or more experiments, at least one predicted GO category was found for 72.5% of them. Of the 5,720 genes without GO annotation, 4,189 had at least one predicted ontology using top 40 co-expressed genes for prediction analysis. For the remaining 1,531 genes without GO predictions or annotations, ~17% (257 genes) had sufficient co-expression data yet no statistically significantly overrepresented ontologies, suggesting their regulation may be more complex.</p

clustermq enables efficient parallelization of genomic analyses

Motivation: High performance computing (HPC) clusters play a pivotal role in large-scale bioinformatics analysis and modeling. For the statistical computing language R, packages exist to enable a user to submit their analyses as jobs on HPC schedulers. However, these packages do not scale well to high numbers of tasks, and their processing overhead quickly becomes a prohibitive bottleneck.Results: Here we present clustermq, an R package that can process analyses up to three orders of magnitude faster than previously published alternatives. We show this for investigating genomic associations of drug sensitivity in cancer cell lines, but it can be applied to any kind of parallelizable workflow.</p