Subjectivism as an unavoidable feature of ecological statistics

© 2014 Museu de Ciències Naturals de Barcelona. Subjectivism as an unavoidable feature of ecological statistics.— We approach here the handling of previous information when performing statistical inference in ecology, both when dealing with model specification and selection, and when dealing with parameter estimation. We compare the perspectives of this problem from the frequentist and Bayesian schools, including objective and subjective Bayesians. We show that the issue of making use of previous information and making a priori decisions is not only a reality for Bayesians but also for frequentists. However, the latter tend to overlook this because of the common difficulty of having previous information available on the magnitude of the effect that is thought to be biologically relevant. This prior information should be fed into a priori power tests when looking for the necessary sample sizes to couple statistical and biological significances. Ecologists should make a greater effort to make use of available prior information because this is their most legitimate contribution to the inferential process. Parameter estimation and model selection would benefit if this was done, allowing a more reliable accumulation of knowledge, and hence progress, in the biological sciences.Peer Reviewe

Multivariate regression smoothing through the 'fallling net'.

We consider multivariate regression smoothing through a conditional mean shift procedure. By computing local conditional means iteratively over a set or grid of target points, at each iteration a `net' is formed which gently drifts towards the data cloud, until it settles at the conditional modes of the response distribution. The method is edge-preserving and allows for multi-valued response

Exploring Bayesian models to evaluate control procedures for plant disease

Tigernut tubers are the main ingredient in the production of orxata in Valencia, a white soft sweet popular drink. In recent years, the appearance of black spots in the skin of tigernuts has led to important economic losses in orxata production because severely diseased tubers must be discarded. In this paper, we discuss three complementary statistical models to assess the disease incidence of harvested tubers from selected or treated seeds, and propose a measure of effectiveness for different treatments against the disease based on the probability of germination and the incidence of the disease. Statistical methods for these studies are approached from Bayesian reasoning and include mixed-effects models, Dirichlet-multinomial inferential processes and mixed-effects logistic regression models. Statistical analyses provide relevant information to carry out measures to palliate the black spot disease and achieve a high-quality production. For instance, the study shows that avoiding affected seeds increases the probability of harvesting asymptomatic tubers. It is also revealed that the best chemical treatment, when prioritizing germination, is disinfection with hydrochloric acid while sodium hypochlorite performs better if the priority is to have a reduced disease incidence. The reduction of the incidence of the black spots syndrome by disinfection with chemical agents supports the hypothesis that the causal agent is a pathogenic organism

Short and Long-Term Trainability in Older Adults: Training and Detraining Following Two Years of Multicomponent Cognitive-Physical Exercise Training

Despite the benefits of multicomponent physical–cognitive training programs (MCCogTPs), lower training intensities in the concurrent approach, and bigger heterogeneity with aging, suggest the need for long-term analyses, with special attention to training and detraining in older adults. The present study aims to examine these training/detraining effects in a two year MCCogTP, looking for specific dynamics in the trainability of their physical and cognitive capacities. The intervention was divided into four periods: T1, T2 (8 months of training each), and D1, D2 (3.5 months of detraining plus 0.5 of testing each). Twenty-five healthy seniors (70.82 ± 5.18 years) comprised the final sample and were assessed for cardiovascular fitness (6-minutes walking test), lower-limbs strength (30-seconds chair-stand test) and agility (8-feet timed up-and-go test). Inhibition (Stroop test) was considered for executive function. Physical and cognitive status improved significantly (p < 0.05) throughout the two years, with larger enhancements for physical function (mainly strength and agility). Strength and cardiovascular fitness were more sensitive to detraining, whilst agility proved to have larger training retentions. Inhibition followed an initial similar trend, but it was the only variable to improve along D2 (d = 0.52), and changes were not significant within periods. Notwithstanding aging, and the exercise cessation in D2, physical and cognitive status remained enhanced two years later compared to baseline, except for lower-limb strength. According to these results, basic physical capacities are very sensitive to training/detraining, deserving continuous attention (especially strength). Both reducing detraining periods and complementary resistance training should be considered. Additionally, physical enhancements following MCcogTPs may help cognition maintenance during detraining

Variable selection in the analysis of energy consumption-growth nexus

There is abundant empirical literature that focuses on whether energy consumption is a critical driver of economic growth. The evolution of this literature has largely consisted of attempts to solve the problems and answer the criticisms arising from earlier studies. One of the most common criticisms is that previous work concentrates on the bivariate relationship, energy consumption–economic growth. Many authors try to overcome this critique using control variables. However, the choice of these variables has been ad hoc, made according to the subjective economic rationale of the authors. Our contribution to this literature is to apply a robust probabilistic model to select the explanatory variables from a large set of potential candidates in the case of the US from 1949 to 2010, not only for an aggregate analysis but also for a sector analysis. The results highlight the critical role of public spending and energy intensity in the explanation of growth. Furthermore, since the study reveals different explanatory variables for each sector, it indicates the importance of policy decisions specifically aimed at different sectors.Generalitat Valenciana project PROMETEOII/2014/053, MINECO project ECO2014-58991-C3-2-R UJI project P1-1B2014-17 Spanish Ministry of Economy and Competitiveness project: MTM2013- 42323-

Multivariate regression smoothing through the 'fallling net'

We consider multivariate regression smoothing through a conditional mean shift procedure. By computing local conditional means iteratively over a set or grid of target points, at each iteration a `net' is formed which gently drifts towards the data cloud, until it settles at the conditional modes of the response distribution. The method is edge-preserving and allows for multi-valued response

A trans‐omics comparison reveals common gene expression strategies in four model organisms and exposes similarities and differences between them

The ultimate goal of gene expression regulation is on the protein level. However, because the amounts of mRNAs and proteins are controlled by their synthesis and degradation rates, the cellular amount of a given protein can be attained by following different strategies. By studying omics data for six expression variables (mRNA and protein amounts, plus their synthesis and decay rates), we previously demonstrated the existence of common expression strategies (CESs) for functionally related genes in the yeast Saccharomyces cerevisiae. Here we extend that study to two other eukaryotes: the yeast Schizosaccharomyces pombe and cultured human HeLa cells. We also use genomic data from the model prokaryote Escherichia coli as an external reference. We show that six-variable profiles (6VPs) can be constructed for every gene and that these 6VPs are similar for genes with similar functions in all the studied organisms. The differences in 6VPs between organisms can be used to establish their phylogenetic relationships. The analysis of the correlations among the six variables supports the hypothesis that most gene expression control occurs in actively growing organisms at the transcription rate level, and that translation plays a minor role. We propose that living organisms use CESs for the genes acting on the same physi-ological pathways, especially for those belonging to stable macromolecular complexes, but CESs have been modeled by evolution to adapt to the specific life circumstances of each organism

Towards breaking the Gender Gap in Science, Technology, Engineering and Mathematics

The gender gap in Science, Technology, Engineering and Mathematics (STEM) has drawn the attention of research and academic communities due to its impact in the Digital Society, targeting the fourth and fifth 2030 sustainable development goals of achieving quality education and gender equality. Recent studies show that women are enrolling STEM studies in smaller proportion than men and that they have a larger probability to renounce to their jobs or to take leaves. In this scenario, the involvement of educational institutions is seminal to change this trend. The School of Engineering of the University of Valencia (ETSE-UV), Spain, launched in 2011 a pilot program to promote STEM careers, focusing on increasing and retaining the number of female students choosing these studies. Building from this experience, the Girls4STEM project has been launched in 2019 with the aim of reaching female students from 6 to 18 years old, their families and teachers. In this paper, we present and motivate the project's objectives and main activities, framing them in current state of the art's literature. Preliminary results of the pilot program actions are presented, demonstrating the statistically significant impact on the percentage of enrolled female students and motivating the subsequent Girls4STEM project