Using Contaminated Garbage Collection and Reference Counting Garbage Collection to Provide Automatic Storage Reclamation for Real-Time Systems

Language support of dynamic storage management simplifies the application programming task immensely. As a result, dynamic storage allocation and garbage collection have become common in general purpose computing. Garbage collection research has led to the development of algorithms for locating program memory that is no longer in use and returning the unused memory to the run-time system for late use by the program. While many programming languages have adopted automatic memory reclamation features, this has not been the trend in Real-Time systems. Many garbage collection methods involve some form of marking the objects in memory. This marking requires time proportional to the size of the head to complete. As a result, the predictability constraints of Real-Time are often not satisfied by such approaches. In this thesis, we present an analysis of several approaches for program garbage collection. We examine two approximate collection strategies (Reference Counting and Contamination Garbage Collection) and one complete collection approach (Mark and Sweep Garbage Collection). Additionally, we analyze the relative success of each approach for meeting the demands of Real-Time computing. In addition, we present an algorithm that attempts to classify object types as good candidates for reference counting. Our approach is conservative and uses static analysis of an application\u27s type system. Our analysis of these three collection strategies leads to the observation that there could be benefits to using multiple garbage collectors in parallel. Consequently we address challenges associated with using multiple garbage collectors in one application

Physical and Electrochemical Area Determination of Electrodeposited Ni, Co, and NiCo Thin Films

The surface area of electrodeposited thin films of Ni, Co, and NiCo was evaluated using electrochemical double-layer capacitance, electrochemical area measurements using the [Ru(NH$_3$)$_6$]$^{3+}$/[Ru(NH$_3$)$_6$]$^{2+}$ redox couple, and topographic atomic force microscopy (AFM) imaging. These three methods were compared to each other for each composition separately and for the entire set of samples regardless of composition. Double-layer capacitance measurements were found to be positively correlated to the roughness factors determined by AFM topography. Electrochemical area measurements were found to be less correlated with measured roughness factors as well as applicable only to two of the three compositions studied. The results indicate that in situ double-layer capacitance measurements are a practical, versatile technique for estimating the accessible surface area of a metal sample.Comment: Accepted for publication in Nano Convergence, 6 figure

Impact of antibacterials on subsequent resistance and clinical outcomes in adult patients with viral pneumonia: An opportunity for stewardship

INTRODUCTION: Respiratory viruses are increasingly recognized as significant etiologies of pneumonia among hospitalized patients. Advanced technologies using multiplex molecular assays and polymerase-chain reaction increase the ability to identify viral pathogens and may ultimately impact antibacterial use. METHOD: This was a single-center retrospective cohort study to evaluate the impact of antibacterials in viral pneumonia on clinical outcomes and subsequent multidrug-resistant organism (MDRO) infections/colonization. Patients admitted from March 2013 to November 2014 with positive respiratory viral panels (RVP) and radiographic findings of pneumonia were included. Patients transferred from an outside hospital or not still hospitalized 72 hours after the RVP report date were excluded. Patients were categorized based on exposure to systemic antibacterials: less than 3 days representing short-course therapy and 3 to 10 days being long-course therapy. RESULTS: A total of 174 patients (long-course, n = 67; short-course, n = 28; mixed bacterial-viral infection, n = 79) were included with most being immunocompromised (56.3 %) with active malignancy the primary etiology (69.4 %). Rhinovirus/Enterovirus (23 %), Influenza (19 %), and Parainfluenza (15.5 %) were the viruses most commonly identified. A total of 13 different systemic antibacterials were used as empiric therapy in the 95 patients with pure viral infection for a total of 466 days-of-therapy. Vancomycin (50.7 %), cefepime (40.3 %), azithromycin (40.3 %), meropenem (23.9 %), and linezolid (20.9 %) were most frequently used. In-hospital mortality did not differ between patients with viral pneumonia in the short-course and long-course groups. Subsequent infection/colonization with a MDRO was more frequent in the long-course group compared to the short-course group (53.2 vs 21.1 %; P = 0.027). CONCLUSION: This study found that long-course antibacterial use in the setting of viral pneumonia had no impact on clinical outcomes but increased the incidence of subsequent MDRO infection/colonization

Epidemiology, co-infections, and outcomes of viral pneumonia in adults an observational cohort study

Advanced technologies using polymerase-chain reaction have allowed for increased recognition of viral respiratory infections including pneumonia. Co-infections have been described for several respiratory viruses, especially with influenza. Outcomes of viral pneumonia, including cases with co-infections, have not been well described. This was observational cohort study conducted to describe hospitalized patients with viral pneumonia including co-infections, clinical outcomes, and predictors of mortality. Patients admitted from March 2013 to November 2014 with a positive respiratory virus panel (RVP) and radiographic findings of pneumonia within 48 h of the index RVP were included. Co-respiratory infection (CRI) was defined as any organism identification from a respiratory specimen within 3 days of the index RVP. Predictors of in-hospital mortality on univariate analysis were evaluated in a multivariate model. Of 284 patients with viral pneumonia, a majority (51.8%) were immunocompromised. A total of 84 patients (29.6%) were found to have a CRI with 48 (57.6%) having a bacterial CRI. Viral CRI with HSV, CMV, or both occurred in 28 patients (33.3%). Fungal (16.7%) and other CRIs (7.1%) were less common. Many patients required mechanical ventilation (54%) and vasopressor support (36%). Overall in-hospital mortality was high (23.2%) and readmissions were common with several patients re-hospitalized within 30 (21.1%) and 90 days (36.7%) of discharge. Predictors of in-hospital mortality on multivariate regression included severity of illness factors, stem-cell transplant, and identification of multiple respiratory viruses. In conclusion, hospital mortality is high among adult patients with viral pneumonia and patients with multiple respiratory viruses identified may be at a higher risk

Text-mining of PubMed abstracts by natural language processing to create a public knowledge base on molecular mechanisms of bacterial enteropathogens

<p>Abstract</p> <p>Background</p> <p>The Enteropathogen Resource Integration Center (ERIC; <url>http://www.ericbrc.org</url>) has a goal of providing bioinformatics support for the scientific community researching enteropathogenic bacteria such as <it>Escherichia coli </it>and <it>Salmonella </it>spp. Rapid and accurate identification of experimental conclusions from the scientific literature is critical to support research in this field. Natural Language Processing (NLP), and in particular Information Extraction (IE) technology, can be a significant aid to this process.</p> <p>Description</p> <p>We have trained a powerful, state-of-the-art IE technology on a corpus of abstracts from the microbial literature in PubMed to automatically identify and categorize biologically relevant entities and predicative relations. These relations include: Genes/Gene Products and their Roles; Gene Mutations and the resulting Phenotypes; and Organisms and their associated Pathogenicity. Evaluations on blind datasets show an F-measure average of greater than 90% for entities (genes, operons, etc.) and over 70% for relations (gene/gene product to role, etc). This IE capability, combined with text indexing and relational database technologies, constitute the core of our recently deployed text mining application.</p> <p>Conclusion</p> <p>Our Text Mining application is available online on the ERIC website <url>http://www.ericbrc.org/portal/eric/articles</url>. The information retrieval interface displays a list of recently published enteropathogen literature abstracts, and also provides a search interface to execute custom queries by keyword, date range, etc. Upon selection, processed abstracts and the entities and relations extracted from them are retrieved from a relational database and marked up to highlight the entities and relations. The abstract also provides links from extracted genes and gene products to the ERIC Annotations database, thus providing access to comprehensive genomic annotations and adding value to both the text-mining and annotations systems.</p

The Tao of open science for ecology

The field of ecology is poised to take advantage of emerging technologies that facilitate the gathering, analyzing, and sharing of data, methods, and results. The concept of transparency at all stages of the research process, coupled with free and open access to data, code, and papers, constitutes “open science.” Despite the many benefits of an open approach to science, a number of barriers to entry exist that may prevent researchers from embracing openness in their own work. Here we describe several key shifts in mindset that underpin the transition to more open science. These shifts in mindset include thinking about data stewardship rather than data ownership, embracing transparency throughout the data life‐cycle and project duration, and accepting critique in public. Though foreign and perhaps frightening at first, these changes in thinking stand to benefit the field of ecology by fostering collegiality and broadening access to data and findings. We present an overview of tools and best practices that can enable these shifts in mindset at each stage of the research process, including tools to support data management planning and reproducible analyses, strategies for soliciting constructive feedback throughout the research process, and methods of broadening access to final research products

The SAMI Galaxy Survey : spatially resolving the main sequence of star formation

We present the ∼800 star formation rate maps for the Sydney-AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey based on H α emission maps, corrected for dust attenuation via the Balmer decrement, that are included in the SAMI Public Data Release 1. We mask out spaxels contaminated by non-stellar emission using the [O iii]/H β, [N ii]/H α, [S ii]/H α, and [O i]/H α line ratios. Using these maps, we examine the global and resolved star-forming main sequences of SAMI galaxies as a function of morphology, environmental density, and stellar mass. Galaxies further below the star-forming main sequence are more likely to have flatter star formation profiles. Early-type galaxies split into two populations with similar stellar masses and central stellar mass surface densities. The main-sequence population has centrally concentrated star formation similar to late-type galaxies, while galaxies >3σ below the main sequence show significantly reduced star formation most strikingly in the nuclear regions. The split populations support a two-step quenching mechanism, wherein halo mass first cuts off the gas supply and remaining gas continues to form stars until the local stellar mass surface density can stabilize the reduced remaining fuel against further star formation. Across all morphologies, galaxies in denser environments show a decreased specific star formation rate from the outside in, supporting an environmental cause for quenching, such as ram-pressure stripping or galaxy interactions.Publisher PDFPeer reviewe

Deep Sequencing the Transcriptome Reveals Seasonal Adaptive Mechanisms in a Hibernating Mammal

Mammalian hibernation is a complex phenotype involving metabolic rate reduction, bradycardia, profound hypothermia, and a reliance on stored fat that allows the animal to survive for months without food in a state of suspended animation. To determine the genes responsible for this phenotype in the thirteen-lined ground squirrel (Ictidomys tridecemlineatus) we used the Roche 454 platform to sequence mRNA isolated at six points throughout the year from three key tissues: heart, skeletal muscle, and white adipose tissue (WAT). Deep sequencing generated approximately 3.7 million cDNA reads from 18 samples (6 time points ×3 tissues) with a mean read length of 335 bases. Of these, 3,125,337 reads were assembled into 140,703 contigs. Approximately 90% of all sequences were matched to proteins in the human UniProt database. The total number of distinct human proteins matched by ground squirrel transcripts was 13,637 for heart, 12,496 for skeletal muscle, and 14,351 for WAT. Extensive mitochondrial RNA sequences enabled a novel approach of using the transcriptome to construct the complete mitochondrial genome for I. tridecemlineatus. Seasonal and activity-specific changes in mRNA levels that met our stringent false discovery rate cutoff (1.0×10−11) were used to identify patterns of gene expression involving various aspects of the hibernation phenotype. Among these patterns are differentially expressed genes encoding heart proteins AT1A1, NAC1 and RYR2 controlling ion transport required for contraction and relaxation at low body temperatures. Abundant RNAs in skeletal muscle coding ubiquitin pathway proteins ASB2, UBC and DDB1 peak in October, suggesting an increase in muscle proteolysis. Finally, genes in WAT that encode proteins involved in lipogenesis (ACOD, FABP4) are highly expressed in August, but gradually decline in expression during the seasonal transition to lipolysis