Analyzing Divisia Rules Extracted from a Feedforward Neural Network

This paper introduces a mechanism for generating a series of rules that characterize the money-price relationship, defined as the relationship between the rate of growth of the money supply and inflation. Division component data is used to train a selection of candidate feedforward neural networks. The selected network is mined for rules, expressed in human-readable and machine-executable form. The rule and network accuracy are compared, and expert commentary is made on the readability and reliability of the extracted rule set. The ultimate goal of this research is to produce rules that meaningfully and accurately describe inflation in terms of Divisia component dataset

Randomized lasso links microbial taxa with aquatic functional groups inferred from flow cytometry

High-nucleic-acid (HNA) and low-nucleic-acid (LNA) bacteria are two operational groups identified by flow cytometry (FCM) in aquatic systems. A number of reports have shown that HNA cell density correlates strongly with heterotrophic production, while LNA cell density does not. However, which taxa are specifically associated with these groups, and by extension, productivity has remained elusive. Here, we addressed this knowledge gap by using a machine learning-based variable selection approach that integrated FCM and 16S rRNA gene sequencing data collected from 14 freshwater lakes spanning a broad range in physicochemical conditions. There was a strong association between bacterial heterotrophic production and HNA absolute cell abundances (R-2 = 0.65), but not with the more abundant LNA cells. This solidifies findings, mainly from marine systems, that HNA and LNA bacteria could be considered separate functional groups, the former contributing a disproportionately large share of carbon cycling. Taxa selected by the models could predict HNA and LNA absolute cell abundances at all taxonomic levels. Selected operational taxonomic units (OTUs) ranged from low to high relative abundance and were mostly lake system specific (89.5% to 99.2%). A subset of selected OTUs was associated with both LNA and HNA groups (12.5% to 33.3%), suggesting either phenotypic plasticity or within-OTU genetic and physiological heterogeneity. These findings may lead to the identification of system-specific putative ecological indicators for heterotrophic productivity. Generally, our approach allows for the association of OTUs with specific functional groups in diverse ecosystems in order to improve our understanding of (microbial) biodiversity-ecosystem functioning relationships. IMPORTANCE A major goal in microbial ecology is to understand how microbial community structure influences ecosystem functioning. Various methods to directly associate bacterial taxa to functional groups in the environment are being developed. In this study, we applied machine learning methods to relate taxonomic data obtained from marker gene surveys to functional groups identified by flow cytometry. This allowed us to identify the taxa that are associated with heterotrophic productivity in freshwater lakes and indicated that the key contributors were highly system specific, regularly rare members of the community, and that some could possibly switch between being low and high contributors. Our approach provides a promising framework to identify taxa that contribute to ecosystem functioning and can be further developed to explore microbial contributions beyond heterotrophic production

Gallus GBrowse: a unified genomic database for the chicken

Gallus GBrowse (http://birdbase.net/cgi-bin/gbrowse/gallus/) provides online access to genomic and other information about the chicken, Gallus gallus. The information provided by this resource includes predicted genes and Gene Ontology (GO) terms, links to Gallus In Situ Hybridization Analysis (GEISHA), Unigene and Reactome, the genomic positions of chicken genetic markers, SNPs and microarray probes, and mappings from turkey, condor and zebra finch DNA and EST sequences to the chicken genome. We also provide a BLAT server (http://birdbase.net/cgi-bin/webBlat) for matching user-provided sequences to the chicken genome. These tools make the Gallus GBrowse server a valuable resource for researchers seeking genomic information regarding the chicken and other avian species

Studying the Enteric Microbiome in Inflammatory Bowel Diseases: Getting through the Growing Pains and Moving Forward

In this commentary, we will review some of the early efforts aimed at understanding the role of the enteric microbiota in the causality of inflammatory bowel diseases. By examining these studies and drawing on our own experiences bridging clinical gastroenterology and microbial ecology as part of the NIH-funded Human Microbiome Project (Turnbaugh et al., 2007), we hope to help define some of the “growing pains” that have hampered these initial efforts. It is our sincere hope that this discussion will help advance future efforts in this area by identifying current challenges and limitations and by suggesting strategies to overcome these obstacles

Studying the Enteric Microbiome in Inflammatory Bowel Diseases: Getting through the Growing Pains and Moving Forward

In this commentary, we will review some of the early efforts aimed at understanding the role of the enteric microbiota in the causality of inflammatory bowel diseases. By examining these studies and drawing on our own experiences bridging clinical gastroenterology and microbial ecology as part of the NIH-funded Human Microbiome Project (Turnbaugh et al., 2007), we hope to help define some of the “growing pains” that have hampered these initial efforts. It is our sincere hope that this discussion will help advance future efforts in this area by identifying current challenges and limitations and by suggesting strategies to overcome these obstacles

An adaptive stereo basis method for convolutive blind audio source separation

NOTICE: this is the author’s version of a work that was accepted for publication in Neurocomputing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in PUBLICATION, [71, 10-12, June 2008] DOI:neucom.2007.08.02

Long-term outcome with the automatic implantable cardioverter-defibrillator

AbstractThe automatic implantable cardioverter-defibrillator was implanted in 270 patients because of life-threatening arrhythmias over a 7 year period. There was a history of sustained ventricular tachycardia or fibrillation, or both, in 96% of these patients, 80% had one or more prior cardiac arrests and 78% had coronary artery disease as their underlying diagnosis. The average ejection fraction was 34%, and 96% of these patients had had an average of 3.4 antiarrhythmic drug failures per patient before defibrillator implantation. There were four perioperative deaths and eight patients had generator infection or generator erosion, or both, during the perioperative period or during long-term follow-up. Concomitant antiarrhythmic drug therapy was given to 69% of patients.Shocks from the device were given to 58% of patients, and 20% received “problematic” shocks. The device was removed from 16 patients during long-term follow-up for a variety of reasons. There were 7 sudden cardiac deaths and 30 nonsudden cardiac deaths, 18 of which were secondary to congestive heart failure. The actuarial incidence of sudden death, total cardiac death and total mortality from all causes was 1%, 7% and 8%, respectively, at 1 year, and 4%, 24% and 26% at 5 years.The automatic implantable cardioverter-defibrillator nearly eliminates sudden death over a long-term follow-up period in a high risk group of patients. It has an acceptable rate of complications or problems, or both, and most late deaths in these patients are nonsudden and of cardiovascular origin

Microhabitats are associated with diversity-productivity relationships in freshwater bacterial communities

Eukaryotic communities commonly display a positive relationship between biodiversity and ecosystem function (BEF) but the results have been mixed when assessed in bacterial communities. Habitat heterogeneity, a factor in eukaryotic BEFs, may explain these variable observations but it has not been thoroughly evaluated in bacterial communities. Here, we examined the impact of habitat on the relationship between diversity assessed based on the (phylogenetic) Hill diversity metrics and heterotrophic productivity. We sampled co-occurring free-living (more homogenous) and particle-associated (more heterogeneous) bacterial habitats in a freshwater, estuarine lake over three seasons: spring, summer and fall. There was a strong, positive, linear relationship between particle-associated bacterial richness and heterotrophic productivity that strengthened when considering dominant taxa. There were no observable BEF trends in free-living bacterial communities for any diversity metric. Biodiversity, richness and Inverse Simpson's index, were the best predictors of particle-associated production whereas pH was the best predictor of free-living production. Our findings show that heterotrophic productivity is positively correlated with the effective number of taxa and that BEF relationships are associated with microhabitats. These results add to the understanding of the highly distinct contributions to diversity and functioning contributed by bacteria in free-living and particle-associated habitats

Continuous measurements of greenhouse gases and atmospheric oxygen at the Namib Desert atmospheric observatory

A new coastal background site has been established for observations of greenhouse gases (GHGs) in the central Namib Desert at Gobabeb, Namibia. The location of the site was chosen to provide observations for a data-poor region in the global sampling network for GHGs. Semi-automated continuous measurements of carbon dioxide, methane, nitrous oxide, carbon monoxide, atmospheric oxygen, and basic meteorology are made at a height of 21 m a.g.l., 50 km from the coast at the northern border of the Namib Sand Sea. Atmospheric oxygen is measured with a differential fuel cell analyzer (DFCA). Carbon dioxide and methane are measured with an early-model cavity ring-down spectrometer (CRDS); nitrous oxide and carbon monoxide are measured with an off-axis integrated cavity output spectrometer (OA-ICOS). Instrument-specific water corrections are employed for both the CRDS and OA-ICOS instruments in lieu of drying. The performance and measurement uncertainties are discussed in detail. As the station is located in a remote desert environment, there are some particular challenges, namely fine dust, high diurnal temperature variability, and minimal infrastructure. The gas handling system and calibration scheme were tailored to best fit the conditions of the site. The CRDS and DFCA provide data of acceptable quality when base requirements for operation are met, specifically adequate temperature control in the laboratory and regular supply of electricity. In the case of the OA-ICOS instrument, performance is significantly improved through the implementation of a drift correction through frequent measurements of a reference cylinder