A geographic opportunistic forwarding strategy for vehicular named data networking

Studies in Computational Intelligence, 616

Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate

The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.g. death or alive) of an individual is not a fixed characteristic, and it varies along the study. In such cases, when evaluating the performance of the biomarker, several issues should be taken into account: first, the time-dependent nature of the disease status; and second, the presence of incomplete data (e.g. censored data typically present in survival studies). Accordingly, to assess the discrimination power of continuous biomarkers for time-dependent disease outcomes, time-dependent extensions of true positive rate, false positive rate, and ROC curve have been recently proposed. In this work, we present new nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker. The proposed estimators can accommodate right-censored data, as well as covariate-dependent censoring. The behavior of the estimators proposed in this study will be explored through simulations and illustrated using data from a cohort of patients who suffered from acute coronary syndrome.

Data quality in biofilm high-throughput routine analysis: intralaboratory protocol adaptation and experiment reproducibility

Biofilm research is growing more diverse and dependent on high-throughput technologies and the large-scale production of results aggravates data substantiation. In particular, it is often the case that experimental protocols are adapted to meet the needs of a particular laboratory and no statistical validation of the modified method is provided. This paper discusses the impact of intra-laboratory adaptation and non-rigorous documentation of experimental protocols on biofilm data interchange and validation. The case study is a non-standard, but widely used, workflow for Pseudomonas aeruginosa biofilm development, considering three analysis assays: the crystal violet (CV) assay for biomass quantification, the XTT assay for respiratory activity assessment, and the colony forming units (CFU) assay for determination of cell viability. The ruggedness of the protocol was assessed by introducing small changes in the biofilm growth conditions, which simulate minor protocol adaptations and non-rigorous protocol documentation. Results show that even minor variations in the biofilm growth conditions may affect the results considerably, and that the biofilm analysis assays lack repeatability. Intra-laboratory validation of non-standard protocols is found critical to ensure data quality and enable the comparison of results within and among laboratories.

Firm innovation and co-location in Portugal

This paper investigates the geographical distribution and concentration of firms’ innovation persistence and innovation type (product and process) based on three waves of the Portuguese Community Innovation Survey data covering the period 1998–2006. The main findings are: 1) both innovation persistence and innovation type are asymmetrically distributed across Portuguese regions, 2) the degree of correlation between geographical location and innovative output varies with the innovation type, and 3) the correlation between geographical unit and innovation increases when the spatial unit of analysis is narrower. The results suggest that the firms’ choices of geographical location have a long-lasting effect, engendering no equal probabilities of being persistently innovative.

Implementation and validation of a strain rate dependent anisotropic continuum model for masonry

A newly developed strain rate dependent anisotropic continuum model is proposed for impact and blast applications in masonry. The present model adopted the usual approach of considering different yield criteria in tension and compression. The analysis of unreinforced block work masonry walls subjected to impact is carried out to validate the capability of the model. Comparison of the numerical predictions and test data revealed good agreement. Next, a parametric study is conducted to evaluate the influence of the tensile strengths along the three orthogonal directions and of the wall thickness on the global behavior of masonry walls.

Estimation of statistical cure from cancer using population-based data

Dissertação de mestrado em Estatística