Suchergebnisse

This research attempts to seek changing patterns of raw data availability and their correlations with implementations of open mandate policies. With a list of 13,785 journal articles whose authors archived datasets in a popular biomedical data repository after these articles were published in journals, this research uses regression analysis to test the correlations between data contributions and mandate implementations. It finds that both funder-based and publisher-based mandates have a strong impact on scholars' likelihood to contribute to open data repositories. Evidence also suggests that like policies have changed the habit of authors in selecting publishing venues: open access journals have been apparently preferred by those authors whose projects are sponsored by the federal government agencies, and these journals are also highly ranked in the biomedical fields. Various stakeholders, particularly institutional administrators and open access professionals, may find the findings of this research helpful for adjusting data management policies to increase the number of quality free datasets and enhance data usability. The data-sharing example in biomedical studies provides a good case to show the importance of policy-making in the reshaping of scholarly communication.

Every year, large areas of savannas and woodlands burn due to natural conditions and land management practices. Given the relevant level of greenhouse gas emissions produced by biomass burning in tropical regions, it is becoming even more important to clearly define historic fire regimes so that prospective emission reduction management strategies can be well informed, and their results Measured, Reported, and Verified (MRV). Thus, developing tools for accurately, and periodically mapping burned areas, based on cost advantageous, expedite, and repeatable rigorous approaches, is important. The main objective of this study is to investigate the potential of novel Genetic Programming (GP) methodologies for classifying burned areas in satellite imagery over savannas and tropical woodlands and to assess if they can improve over the popular and currently applied methods of Maximum Likelihood classification and Classification and Regression Tree analysis. The tests are performed using three Landsat images from Brazil (South America), Guinea-Bissau (West Africa) and the Democratic Republic of Congo (Central Africa). Burned areas were digitized on-screen to produce mapped information serving as surrogate ground-truth. Validation results show that all methods provide an overestimation of burned area, but GP achieves higher accuracy values in two of the three cases. GP is the most versatile machine learning method available today, but still largely underused in remote sensing. This study shows that standard GP can produce better results than two classical methods, and illustrates its versatility and potential in becoming a mainstream method for more difficult tasks involving the large amounts of newly available data.

We discuss a new way of constructing pointwise confidence intervals for the distribution function in the current status model. The confidence intervals are based on the smoothed maximum likelihood estimator, using local smooth functional theory and normal limit distributions. Bootstrap methods for constructing these intervals are considered. Other methods to construct confidence intervals, using the non-standard limit distribution of the (restricted) maximum likelihood estimator, are compared with our approach via simulations and real data applications. ; We are very grateful to Cécile Durot for communicating her approach to the proof of lemma 2 to us. The research of the second author was supported by the Research Foundation Flanders (FWO) (grant number 11W7315N). Support from the IAP Research Network P7/06 of the Belgian State (Belgian Science Policy) is gratefully acknowledged. For the simulations, we used the infrastructure of the VSC – Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Government – department EWI.

An application of the empirical likelihood method to non-Gaussian locally stationary processes is presented. Based on the central limit theorem for locally stationary processes, we give the asymptotic distributions of the maximum empirical likelihood estimator and the empirical likelihood ratio statistics, respectively. It is shown that the empirical likelihood method enables us to make inferences on various important indices in a time series analysis. Furthermore, we give a numerical study and investigate a finite sample property.

Abstract
Intrinsic impediments, namely weak mechanical strength, low ionic conductivity, low electrochemical performance, and stability have largely inhibited beyond practical applications of hydrogels in electronic devices and remains as a significant challenge in the scientific world. Here, we report a biospecies-derived genomic DNA hybrid gel electrolyte with many synergistic effects, including robust mechanical properties (mechanical strength and elongation of 6.98 MPa and 997.42%, respectively) and ion migration channels, which consequently demonstrated high ionic conductivity (73.27 mS/cm) and superior electrochemical stability (1.64 V). Notably, when applied to a supercapacitor the hybrid gel-based devices exhibit a specific capacitance of 425 F/g. Furthermore, it maintained rapid charging/discharging with a capacitance retention rate of 93.8% after ∼200,000 cycles while exhibiting a maximum energy density of 35.07 Wh/kg and a maximum power density of 193.9 kW/kg. This represents the best value among the current supercapacitors and can be immediately applied to minicars, solar cells, and LED lightning. The widespread use of DNA gel electrolytes will revolutionize human efforts to industrialize high-performance green energy.

Abstract
Multiple-strain (polygenomic) infections are a ubiquitous feature of Plasmodium falciparum parasite population genetics. Under simple assumptions of superinfection, polygenomic infections are hypothesized to be the result of multiple infectious bites. As a result, polygenomic infections have been used as evidence of repeat exposure and used to derive genetic metrics associated with high transmission intensity. However, not all polygenomic infections are the result of multiple infectious bites. Some result from the transmission of multiple, genetically related strains during a single infectious bite (cotransmission). Superinfection and cotransmission represent two distinct transmission processes, and distinguishing between the two could improve inferences regarding parasite transmission intensity. Here, we describe a new metric, RH, that utilizes the correlation in allelic state (heterozygosity) within polygenomic infections to estimate the likelihood that the observed complexity resulted from either superinfection or cotransmission. RH is flexible and can be applied to any type of genetic data. As a proof of concept, we used RH to quantify polygenomic relatedness and estimate cotransmission and superinfection rates from a set of 1,758 malaria infections genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode. Contrary to expectation, we found that cotransmission was responsible for a significant fraction of 43% to 53% of the polygenomic infections collected in three distinct epidemiological regions in Senegal. The prediction that polygenomic infections frequently result from cotransmission stresses the need to incorporate estimates of relatedness within polygenomic infections to ensure the accuracy of genomic epidemiology surveillance data for informing public health activities.

Abstract Background The fungus Purpureocillium lilacinum is widely known as a biological control agent against plant parasitic nematodes. This research article consists of genomic annotation of the first draft of whole genome sequence of P. lilacinum . The study aims to decipher the putative genetic components of the fungus involved in nematode pathogenesis by performing comparative genomic analysis with nine closely related fungal species in Hypocreales. Results de novo genomic assembly was done and a total of 301 scaffolds were constructed for P. lilacinum genomic DNA. By employing structural genome prediction models, 13, 266 genes coding for proteins were predicted in the genome. Approximately 73 % of the predicted genes were functionally annotated using Blastp, InterProScan and Gene Ontology. A 14.7 % fraction of the predicted genes shared significant homology with genes in the Pathogen Host Interactions (PHI) database. The phylogenomic analysis carried out using maximum likelihood RAxML algorithm provided insight into the evolutionary relationship of P. lilacinum . In congruence with other closely related species in the Hypocreales namely, Metarhizium spp ., Pochonia chlamydosporia , Cordyceps militaris , Trichoderma reesei and Fusarium spp ., P. lilacinum has large gene sets coding for G-protein coupled receptors (GPCRs), proteases, glycoside hydrolases and carbohydrate esterases that are required for degradation of nematode-egg shell components. Screening of the genome by Antibiotics & Secondary Metabolite Analysis Shell (AntiSMASH) pipeline indicated that the genome potentially codes for a variety of secondary metabolites, possibly required for adaptation to heterogeneous lifestyles reported for P. lilacinum . Significant up-regulation of subtilisin-like serine protease genes in presence of nematode eggs in quantitative real-time analyses suggested potential role of serine proteases in nematode pathogenesis. Conclusions The data offer a better understanding of Purpureocillium lilacinum genome and will enhance our understanding on the molecular mechanism involved in nematophagy.

The detection of family relationships in genetic databases is of interest in various scientific disciplines such as genetic epidemiology, population and conservation genetics, forensic science, and genealogical research. Nowadays, screening genetic databases for related individuals forms an important aspect of standard quality control procedures. Relatedness research is usually based on an allele sharing analysis of identity by state (IBS) or identity by descent (IBD) alleles. Existing IBS/IBD methods mainly aim to identify first-degree relationships (parent–offspring or full siblings) and second degree (half-siblings, avuncular, or grandparent–grandchild) pairs. Little attention has been paid to the detection of in-between first and second-degree relationships such as three-quarter siblings (3/4S) who share fewer alleles than first-degree relationships but more alleles than second-degree relationships. With the progressively increasing sample sizes used in genetic research, it becomes more likely that such relationships are present in the database under study. In this paper, we extend existing likelihood ratio (LR) methodology to accurately infer the existence of 3/4S, distinguishing them from full siblings and second-degree relatives. We use bootstrap confidence intervals to express uncertainty in the LRs. Our proposal accounts for linkage disequilibrium (LD) by using marker pruning, and we validate our methodology with a pedigree-based simulation study accounting for both LD and recombination. An empirical genome-wide array data set from the GCAT Genomes for Life cohort project is used to illustrate the method. ; This work was partially supported by grants RTI2018-095518-B-C22 (JG), RTI2018-095518-B-C21 (IGF and CBV), and ADE 10/00026 (RdC) (MCIU/AEI/FEDER) of the Spanish Ministry of Science, Innovation and Universities and the European Regional Development Fund, by grants SGR1269 and 2017 SGR529 (RdC) of the Generalitat de Catalunya, by grant R01 GM075091 (JG) from the United States National Institutes of Health, by the Ramon y Cajal action RYC-2011-07822 (RdC), by Agency for Management of University and Research Grants (AGAUR) of the Catalan Government grant 2017SGR723 (VM), and by the Spanish Association Against Cancer (AECC) Scientific Foundation, grant GCTRA18022MORE (VM). ; Peer Reviewed ; Postprint (published version)

BACKGROUND: Over the past recent years, Vibrio cholerae has been associated with outbreaks in sub-Saharan Africa, notably in Democratic Republic of the Congo (DRC). This study aimed to determine the genetic relatedness of isolates responsible for cholera outbreaks in eastern DRC between 2014 and 2017, and their potential spread to bordering countries. METHODS/PRINCIPAL FINDINGS: Phenotypic analysis and whole genome sequencing (WGS) were carried out on 78 clinical isolates of V. cholerae associated with cholera in eastern provinces of DRC between 2014 and 2017. SNP-based phylogenomic data show that most isolates (73/78) were V. cholerae O1 biotype El Tor with CTX-3 type prophage. They fell within the third transmission wave of the current seventh pandemic El Tor (7PET) lineage and were contained in the introduction event (T)10 in East Africa. These isolates clustered in two sub-clades corresponding to Multiple Locus Sequence Types (MLST) profiles ST69 and the newly assigned ST515, the latter displaying a higher genetic diversity. Both sub-clades showed a distinct geographic clustering, with ST69 isolates mostly restricted to Lake Tanganyika basin and phylogenetically related to V. cholerae isolates associated with cholera outbreaks in western Tanzania, whereas ST515 isolates were disseminated along the Albertine Rift and closely related to isolates in South Sudan, Uganda, Tanzania and Zambia. Other V. cholerae isolates (5/78) were non-O1/non-O139 without any CTX prophage and no phylogenetic relationship with already characterized non-O1/non-O139 isolates. CONCLUSIONS/SIGNIFICANCE: Current data confirm the association of both DRC O1 7PET (T)10 sub-clades ST69 and ST515 with recurrent outbreaks in eastern DRC and at regional level over the past 10 years. Interestingly, while ST69 is predominantly a locally endemic sequence type, ST515 became adaptable enough to expand across DRC neighboring countries.

BACKGROUND: Over the past recent years, Vibrio cholerae has been associated with outbreaks in sub-Saharan Africa, notably in Democratic Republic of the Congo (DRC). This study aimed to determine the genetic relatedness of isolates responsible for cholera outbreaks in eastern DRC between 2014 and 2017, and their potential spread to bordering countries. METHODS/PRINCIPAL FINDINGS: Phenotypic analysis and whole genome sequencing (WGS) were carried out on 78 clinical isolates of V. cholerae associated with cholera in eastern provinces of DRC between 2014 and 2017. SNP-based phylogenomic data show that most isolates (73/78) were V. cholerae O1 biotype El Tor with CTX-3 type prophage. They fell within the third transmission wave of the current seventh pandemic El Tor (7PET) lineage and were contained in the introduction event (T)10 in East Africa. These isolates clustered in two sub-clades corresponding to Multiple Locus Sequence Types (MLST) profiles ST69 and the newly assigned ST515, the latter displaying a higher genetic diversity. Both sub-clades showed a distinct geographic clustering, with ST69 isolates mostly restricted to Lake Tanganyika basin and phylogenetically related to V. cholerae isolates associated with cholera outbreaks in western Tanzania, whereas ST515 isolates were disseminated along the Albertine Rift and closely related to isolates in South Sudan, Uganda, Tanzania and Zambia. Other V. cholerae isolates (5/78) were non-O1/non-O139 without any CTX prophage and no phylogenetic relationship with already characterized non-O1/non-O139 isolates. CONCLUSIONS/SIGNIFICANCE: Current data confirm the association of both DRC O1 7PET (T)10 sub-clades ST69 and ST515 with recurrent outbreaks in eastern DRC and at regional level over the past 10 years. Interestingly, while ST69 is predominantly a locally endemic sequence type, ST515 became adaptable enough to expand across DRC neighboring countries.

AbstractChen and Bhattacharyya [Exact confidence bounds for an exponential parameter under hybrid censoring, Commun Statist Theory Methods 17 (1988), 1857–1870] considered a hybrid censoring scheme and obtained the exact distribution of the maximum likelihood estimator of the mean of an exponential distribution along with an exact lower confidence bound. Childs et al. [Exact likelihood inference based on Type‐I and Type‐II hybrid censored samples from the exponential distribution, Ann Inst Statist Math 55 (2003), 319–330] recently derived an alternative simpler expression for the distribution of the MLE. These authors also proposed a new hybrid censoring scheme and derived similar results for the exponential model. In this paper, we propose two generalized hybrid censoring schemes which have some advantages over the hybrid censoring schemes already discussed in the literature. We then derive the exact distribution of the maximum likelihood estimator as well as exact confidence intervals for the mean of the exponential distribution under these generalized hybrid censoring schemes. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004

Risk is at the center of many policy decisions in companies, governments and other institutions. The risk of road fatalities concerns local governments in planning counter- measures, the risk and severity of counterparty default concerns bank risk managers on a daily basis and the risk of infection has actuarial and epidemiological consequences. However, risk can not be observed directly and it usually varies over time. Measuring risk is therefore an important exercise. In this paper we introduce a general multivariate framework for the time series analysis of risk that is modelled as a latent process. The latent risk time series model extends existing approaches by the simultaneous modelling of (i) the exposure to an event, (ii) the risk of that event occurring and (iii) the severity of the event. First, we discuss existing time series approaches for the analysis of risk which have been applied to road safety, actuarial and epidemiological problems. Seco! nd, we present a general model for the analysis of risk and discuss its statistical treatment based on linear state space methods. Third, we apply the methodology to time series of insurance claims, credit card purchases and road safety. It is shown that the general methodology can be effectively used in the assessment of risk.