Geometrical complexity of data approximators

There are many methods developed to approximate a cloud of vectors embedded in high-dimensional space by simpler objects: starting from principal points and linear manifolds to self-organizing maps, neural gas, elastic maps, various types of principal curves and principal trees, and so on. For each type of approximators the measure of the approximator complexity was developed too. These measures are necessary to find the balance between accuracy and complexity and to define the optimal approximations of a given type. We propose a measure of complexity (geometrical complexity) which is applicable to approximators of several types and which allows comparing data approximations of different types.Comment: 10 pages, 3 figures, minor correction and extensio

Models of multivariate regression for labor accidents in different production sectors: comparative study

The present article shows the results of an investigation carried out on the use of alternatives to carry out work accident studies in an objective manner in three production sectors that are of high risk: the electric power production sector, cement production and oil refining sector, so the main objective is focused on identifying the influential variables and the regression model that best explains the accident in each of these sectors and perform a comparative analysis between them. Among the techniques and tools used (data mining) are those related to multivariate statistics and generalized linear models and through the Akaike information criterion and Bayeciano criterion, it was possible to determine that the best regression model that explains the accident rate in two of the sectors studied is the negative binomial (cement and petroleum refining), while in the electric power sector, the best fit model resulted in Logistic Regression. In turn, for the three sectors in general, the variables that have the most significant impact are related to aspects such as: management commitment, occupational safety climate, safety training, psychosocial aspects and ergonomic sources, this result was corroborated by means of an accident analysis carried out in these three sectors

Credit Market Competition and the Nature of Firms

Empirical studies show that competition in the credit markets has important effects on the entry and growth of firms in nonfinancial industries. This paper explores the hypothesis that the availability of credit at the time of a firm's founding has a profound effect on that firm's nature. I conjecture that in times when financial capital is difficult to obtain, firms will need to be built as relatively solid organizations. However, in an environment of easily available financial capital, firms can be constituted with an intrinsically weaker structure. To test this conjecture, I use confidential data from the U.S. Census Bureau on the entire universe of business establishments in existence over a thirty-year period; I follow the life cycles of those same establishments through a period of regulatory reform during which U.S. states were allowed to remove barriers to entry in the banking industry, a development that resulted in significantly improved credit competition. The evidence confirms my conjecture. Firms constituted in post-reform years are intrinsically frailer than those founded in a more financially constrained environment, while firms of pre-reform vintage do not seem to adapt their nature to an easier credit environment. Credit market competition does lead to more entry and growth of firms, but also to complex dynamics experienced by the population of business organizations

HIV-1 infected monozygotic twins: a tale of two outcomes

<p>Abstract</p> <p>Background</p> <p>Replicate experiments are often difficult to find in evolutionary biology, as this field is inherently an historical science. However, viruses, bacteria and phages provide opportunities to study evolution in both natural and experimental contexts, due to their accelerated rates of evolution and short generation times. Here we investigate HIV-1 evolution by using a natural model represented by monozygotic twins infected synchronically at birth with an HIV-1 population from a shared blood transfusion source. We explore the evolutionary processes and population dynamics that shape viral diversity of HIV in these monozygotic twins.</p> <p>Results</p> <p>Despite the identical host genetic backdrop of monozygotic twins and the identical source and timing of the HIV-1 inoculation, the resulting HIV populations differed in genetic diversity, growth rate, recombination rate, and selection pressure between the two infected twins.</p> <p>Conclusions</p> <p>Our study shows that the outcome of evolution is strikingly different between these two "replicates" of viral evolution. Given the identical starting points at infection, our results support the impact of random epigenetic selection in early infection dynamics. Our data also emphasize the need for a better understanding of the impact of host-virus interactions in viral evolution.</p

Human Trafficking in Southeast Asia: Results from a Pilot Project in Vietnam

Human trafficking is one of the most widely spread and fastest growing crimes in the world. However, despite the scope of the problem, the important human rights issues at stake and the professed intent of governments around the world to put an end to "modern day slavery", there is very little that is actually known about the nature of human trafficking and those most at risk as potential victims. This is due in large part to the difficulty in collecting reliable and statistically useful data. In this paper we present the results of a pilot study run in rural Vietnam with the aim of overcoming these data issues. Rather than attempt to identify victims themselves, we rely on the form rural migration often takes in urbanizing developing countries to instead identify households that were sources of trafficking victims. This allows us to construct a viable sampling frame, on which we conduct a survey using novel techniques such as anchoring vignettes, indirect sampling, list randomization and social network analysis to construct a series of empirically valid estimates that can begin to shed light on the problem of human trafficking

High-Throughput Estimation of Yield for Individual Rice Plant Using Multi-angle RGB Imaging

International audienceModern breeding technologies are capable of producing hundreds of new varieties daily, so fast, simple and effective methods for screening valuable candidate plant materials are urgently needed. Final yield is a significant agricultural trait in rice breeding. In the screening and evaluation of the rice varieties, measuring and evaluating rice yield is essential. Conventional means of measuring rice yield mainly depend on manual determination, which is tedious, labor-intensive, subjective and error-prone, especially when large-scale plants were to be investigated. This paper presented an in vivo, automatic and high-throughput method to estimate the yield of individual pot-grown rice plant using multi-angle RGB imaging and image analysis. In this work, we demonstrated a new idea of estimating rice yield from projected panicle area, projected area of leaf and stem and fractal dimension. 5-fold cross validation showed that the predictive error was 7.45%. The constructed model achieved promising results on rice plants grown both in-door and out-door. The presented work has the potential of accelerating yield estimation and would be a promising impetus for plant phenomics