Recurrence interval statistics of cellular automaton seismicity models

The recurrence interval statistics for regional seismicity follows a universal distribution function, independent of the tectonic setting or average rate of activity (Corral, 2004). The universal function is a modified gamma distribution with power-law scaling of recurrence intervals shorter than the average rate of activity and exponential decay for larger intervals. We employ the method of Corral (2004) to examine the recurrence statistics of a range of cellular automaton earthquake models. The majority of models has an exponential distribution of recurrence intervals, the same as that of a Poisson process. One model, the Olami-Feder-Christensen automaton, has recurrence statistics consistent with regional seismicity for a certain range of the conservation parameter of that model. For conservation parameters in this range, the event size statistics are also consistent with regional seismicity. Models whose dynamics are dominated by characteristic earthquakes do not appear to display universality of recurrence statistics.

Bulgarian Digital Mathematical Library BulDML and Czech Digital Mathematical Library DML-CZ as parts of the European Digital Mathematics Library EuDML

The paper presents in brief the Bulgarian Digital Mathematical Library BulDML and the Czech Digital Mathematical Library DML-CZ. Both libraries use the open source software DSpace and both are partners in the European Digital Mathematics Library EuDML. We describe their content and metadata schemas; outline the architecture system and overview the statistics of its use.

Using Statistics to Set Priorities

In November 2015-March 2016, I assigned my Graduate Assistant, David Durden, a project to compile usage statistics and trends for digitized collections between 2013-2015 from UMD Digital Collections and our contributions to the Internet Archive between 2008-2015. The original intent of the project was to provide usage metrics to assist the Digitization Initiatives Committee in prioritizing projects or content areas. The project also uncovered trends that should impact how we think about making digital collections discoverable and accessible. For example, if 50-60% of traffic into UMD Digital Collections comes from outside the University or College Park, MD, how will this impact the potential usage of content when access is restricted to campus due to licensing, copyright, or ownership restrictions? With a growing population using mobile browsers, how will a flash-based viewer restrict users’ access to content? How might we develop content or its discoverability for a growing social media user base? In this talk, I will briefly discuss the usage trends for the represented collections, how we may use these in prioritizing future projects, and issues I will discuss with collection managers as we develop project plans and the Manager of Digital Programs and Initiatives as we develop the digital collections repository.

Custom Analytics with Google Tag Manager: Assessing Usage Statistics on the MD-SOAR Platform

As usage metrics continue to attain an increasingly central role in library system assessment and analysis, librarians tasked with system selection, implementation, and support are driven to identify metric approaches that simultaneously require less technical complexity and greater levels of data granularity. Such approaches allow systems librarians to present evidence-based claims of platform usage behaviors while reducing the resources necessary to collect such information, thereby representing a novel approach to real-time user analysis as well as dual benefit in active and preventative cost reduction. As part of the DSpace implementation for the MD SOAR initiative, the Consortial Library Application Support (CLAS) division has begun test implementation of the Google Tag Manager analytic system in an attempt to collect custom analytical dimensions to track author- and university-specific download behaviors. Building on the work of Conrad , CLAS seeks to demonstrate that the GTM approach to custom analytics provides both granular metadata-based usage statistics in an approach that will prove extensible for additional statistical gathering in the future. This poster will discuss the methodology used to develop these custom tag approaches, the benefits of using the GTM model, and the risks and benefits associated with further implementation.

New Fefe-hydrogenase Genes Identified In A Metagenomic Fosmid Library From A Municipal Wastewater Treatment Plant As Revealed By High-throughput Sequencing.

A fosmid metagenomic library was constructed with total community DNA obtained from a municipal wastewater treatment plant (MWWTP), with the aim of identifying new FeFe-hydrogenase genes encoding the enzymes most important for hydrogen metabolism. The dataset generated by pyrosequencing of a fosmid library was mined to identify environmental gene tags (EGTs) assigned to FeFe-hydrogenase. The majority of EGTs representing FeFe-hydrogenase genes were affiliated with the class Clostridia, suggesting that this group is the main hydrogen producer in the MWWTP analyzed. Based on assembled sequences, three FeFe-hydrogenase genes were predicted based on detection of the L2 motif (MPCxxKxxE) in the encoded gene product, confirming true FeFe-hydrogenase sequences. These sequences were used to design specific primers to detect fosmids encoding FeFe-hydrogenase genes predicted from the dataset. Three identified fosmids were completely sequenced. The cloned genomic fragments within these fosmids are closely related to members of the Spirochaetaceae, Bacteroidales and Firmicutes, and their FeFe-hydrogenase sequences are characterized by the structure type M3, which is common to clostridial enzymes. FeFe-hydrogenase sequences found in this study represent hitherto undetected sequences, indicating the high genetic diversity regarding these enzymes in MWWTP. Results suggest that MWWTP have to be considered as reservoirs for new FeFe-hydrogenase genes.

A quantitative and qualitative evaluation of reports of clinical trials published in six Brazilian dental journals indexed in the Scientific Electronic Library Online (SciELO)

INTRODUCTION: Open access publishing is becoming increasingly popular within the biomedical sciences. SciELO, the Scientific Electronic Library Online, is a digital library covering a selected collection of Brazilian scientific journals many of which provide open access to full-text articles.This library includes a number of dental journals some of which may include reports of clinical trials in English, Portuguese and/or Spanish. Thus, SciELO could play an important role as a source of evidence for dental healthcare interventions especially if it yields a sizeable number of high quality reports. OBJECTIVE: The aim of this study was to identify reports of clinical trials by handsearching of dental journals that are accessible through SciELO, and to assess the overall quality of these reports. MATERIAL AND METHODS: Electronic versions of six Brazilian dental Journals indexed in SciELO were handsearched at www.scielo.br in September 2008. Reports of clinical trials were identified and classified as controlled clinical trials (CCTs - prospective, experimental studies comparing 2 or more healthcare interventions in human beings) or randomized controlled trials (RCTs - a random allocation method is clearly reported), according to Cochrane eligibility criteria. CRITERIA TO ASSESS METHODOLOGICAL QUALITY INCLUDED: method of randomization, concealment of treatment allocation, blinded outcome assessment, handling of withdrawals and losses and whether an intention-to-treat analysis had been carried out. RESULTS: The search retrieved 33 CCTs and 43 RCTs. A majority of the reports provided no description of either the method of randomization (75.3%) or concealment of the allocation sequence (84.2%). Participants and outcome assessors were reported as blinded in only 31.2% of the reports. Withdrawals and losses were only clearly described in 6.5% of the reports and none mentioned an intention-to-treat analysis or any similar procedure. CONCLUSIONS: The results of this study indicate that a substantial number of reports of trials and systematic reviews are available in the dental journals listed in SciELO, and that these could provide valuable evidence for clinical decision making. However, it is clear that the quality of a number of these reports is of some concern and that improvement in the conduct and reporting of these trials could be achieved if authors adhered to internationally accepted guidelines, e.g. the CONSORT statement.

An empirical evaluation of imputation accuracy for association statistics reveals increased type-I error rates in genome-wide associations

Background: Genome wide association studies (GWAS) are becoming the approach of choice to identify genetic determinants of complex phenotypes and common diseases. The astonishing amount of generated data and the use of distinct genotyping platforms with variable genomic coverage are still analytical challenges. Imputation algorithms combine directly genotyped markers information with haplotypic structure for the population of interest for the inference of a badly genotyped or missing marker and are considered a near zero cost approach to allow the comparison and combination of data generated in different studies. Several reports stated that imputed markers have an overall acceptable accuracy but no published report has performed a pair wise comparison of imputed and empiric association statistics of a complete set of GWAS markers. Results: In this report we identified a total of 73 imputed markers that yielded a nominally statistically significant association at P < 10(-5) for type 2 Diabetes Mellitus and compared them with results obtained based on empirical allelic frequencies. Interestingly, despite their overall high correlation, association statistics based on imputed frequencies were discordant in 35 of the 73 (47%) associated markers, considerably inflating the type I error rate of imputed markers. We comprehensively tested several quality thresholds, the haplotypic structure underlying imputed markers and the use of flanking markers as predictors of inaccurate association statistics derived from imputed markers. Conclusions: Our results suggest that association statistics from imputed markers showing specific MAF (Minor Allele Frequencies) range, located in weak linkage disequilibrium blocks or strongly deviating from local patterns of association are prone to have inflated false positive association signals. The present study highlights the potential of imputation procedures and proposes simple procedures for selecting the best imputed markers for follow-up genotyping studies.

Statistics of opinion domains of the majority-vote model on a square lattice

The existence of juxtaposed regions of distinct cultures in spite of the fact that people's beliefs have a tendency to become more similar to each other's as the individuals interact repeatedly is a puzzling phenomenon in the social sciences. Here we study an extreme version of the frequency-dependent bias model of social influence in which an individual adopts the opinion shared by the majority of the members of its extended neighborhood, which includes the individual itself. This is a variant of the majority-vote model in which the individual retains its opinion in case there is a tie among the neighbors' opinions. We assume that the individuals are fixed in the sites of a square lattice of linear size L and that they interact with their nearest neighbors only. Within a mean-field framework, we derive the equations of motion for the density of individuals adopting a particular opinion in the single-site and pair approximations. Although the single-site approximation predicts a single opinion domain that takes over the entire lattice, the pair approximation yields a qualitatively correct picture with the coexistence of different opinion domains and a strong dependence on the initial conditions. Extensive Monte Carlo simulations indicate the existence of a rich distribution of opinion domains or clusters, the number of which grows with L(2) whereas the size of the largest cluster grows with ln L(2). The analysis of the sizes of the opinion domains shows that they obey a power-law distribution for not too large sizes but that they are exponentially distributed in the limit of very large clusters. In addition, similarly to other well-known social influence model-Axelrod's model-we found that these opinion domains are unstable to the effect of a thermal-like noise.

New genes of Xanthomonas citri subsp citri involved in pathogenesis and adaptation revealed by a transposon-based mutant library

Background: Citrus canker is a disease caused by the phytopathogens Xanthomonas citri subsp. citri, Xanthomonas fuscans subsp. aurantifolli and Xanthomonas alfalfae subsp. citrumelonis. The first of the three species, which causes citrus bacterial canker type A, is the most widely spread and severe, attacking all citrus species. In Brazil, this species is the most important, being found in practically all areas where citrus canker has been detected. Like most phytobacterioses, there is no efficient way to control citrus canker. Considering the importance of the disease worldwide, investigation is needed to accurately detect which genes are related to the pathogen-host adaptation process and which are associated with pathogenesis. Results: Through transposon insertion mutagenesis, 10,000 mutants of Xanthomonas citri subsp. citri strain 306 (Xcc) were obtained, and 3,300 were inoculated in Rangpur lime (Citrus limonia) leaves. Their ability to cause citrus canker was analyzed every 3 days until 21 days after inoculation; a set of 44 mutants showed altered virulence, with 8 presenting a complete loss of causing citrus canker symptoms. Sequencing of the insertion site in all 44 mutants revealed that 35 different ORFs were hit, since some ORFs were hit in more than one mutant, with mutants for the same ORF presenting the same phenotype. An analysis of these ORFs showed that some encoded genes were previously known as related to pathogenicity in phytobacteria and, more interestingly, revealed new genes never implicated with Xanthomonas pathogenicity before, including hypothetical ORFs. Among the 8 mutants with no canker symptoms are the hrpB4 and hrpX genes, two genes that belong to type III secretion system (TTSS), two hypothetical ORFS and, surprisingly, the htrA gene, a gene reported as involved with the virulence process in animal-pathogenic bacteria but not described as involved in phytobacteria virulence. Nucleic acid hybridization using labeled cDNA probes showed that some of the mutated genes are differentially expressed when the bacterium is grown in citrus leaves. Finally, comparative genomic analysis revealed that 5 mutated ORFs are in new putative pathogenicity islands. Conclusion: The identification of these new genes related with Xcc infection and virulence is a great step towards the understanding of plant-pathogen interactions and could allow the development of strategies to control citrus canker.