Biomimetic Space-Variant Sampling in a Vision Prosthesis Improves the User's Skill in a Localization Task

In this experiment, we test the hypothesis of whether a 'retina-like' space variant sampling pattern can improve the efficiency of a visual prosthesis. Subjects wearing a visuo-auditory substitution system were tested for their ability to point at visual targets. The test group (space-variant sampling), performed significantly better than the control group (uniform sampling). The pointing accuracy was enhanced, as was the speed to find the target. Surprisingly, the time spanned to complete the training was also reduced, suggesting that this space-variant sampling scheme facilitates the mastering of sensorimotor contingencies

Efficient Parallel Statistical Model Checking of Biochemical Networks

We consider the problem of verifying stochastic models of biochemical networks against behavioral properties expressed in temporal logic terms. Exact probabilistic verification approaches such as, for example, CSL/PCTL model checking, are undermined by a huge computational demand which rule them out for most real case studies. Less demanding approaches, such as statistical model checking, estimate the likelihood that a property is satisfied by sampling executions out of the stochastic model. We propose a methodology for efficiently estimating the likelihood that a LTL property P holds of a stochastic model of a biochemical network. As with other statistical verification techniques, the methodology we propose uses a stochastic simulation algorithm for generating execution samples, however there are three key aspects that improve the efficiency: first, the sample generation is driven by on-the-fly verification of P which results in optimal overall simulation time. Second, the confidence interval estimation for the probability of P to hold is based on an efficient variant of the Wilson method which ensures a faster convergence. Third, the whole methodology is designed according to a parallel fashion and a prototype software tool has been implemented that performs the sampling/verification process in parallel over an HPC architecture

A whole-plant functional scheme predicting the early growth of tropical tree species: evidence from 15 tree species in Central Africa

Key message: This study highlighted the consistency of a functional scheme integrating leaf, stem and root traits, biomass allocation and stem anatomy for 15 tropical tree species at the seedling stage. This functional scheme was shaped by the trade-offs for resource use and the hydraulics of the plants and was found to determine seedling growth. Abstract: Functional traits determine plant functioning, performance and response to the environment and define species functional strategy. The functional strategy of 15 African tree species was assessed by (1) highlighting the structure of traits covariance and the underlying functional trade-offs, (2) inferring a whole-plant functional scheme and (3) testing the correlation of the functional scheme with plant performance for two early developmental stages (seedlings and saplings). We selected 10 seedlings for each of the 15 species studied from a nursery in south-eastern Cameroon and measured 18 functional traits, including leaf, stem and root traits, biomass allocation and stem anatomy. We assessed the height and diameter growth of the seedlings and the DBH growth and survival for the saplings of nearby plantations. Multivariate analyses highlighted the covariations among the functional traits of the leaf/stem/root, biomass allocation ratios and stem anatomy. The major trait covariation axes were driven by two trade-offs, first between resource acquisition and conservation and second between hydraulic safety and efficiency. The axes were integrated into a Bayesian network inferring a functional scheme at the whole-plant scale, which was found to predict the growth of the seedlings but not the performance of the saplings. The functional strategies of the seedlings were determined by an integrated whole-plant scheme reflecting the trade-offs for resource use and plant hydraulics. The scheme predicted the growth of the seedlings through mechanistic pathways from the wood stem to all the plant traits, but it appeared to shift at the stage of the saplings. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature

Aneuploidy screening of embryonic stem cell clones by metaphase karyotyping and droplet digital polymerase chain reaction

DNA input in ddPCR reaction. The figure shows copy number of Chr 8 (crosses) and Y (squares) measured by ddPCR with various input quantities of genomic DNA template. Vertical bars are Standard Errors. The experiment demonstrates linearity across the range of concentrations relevant to the DNA preparations assayed. This is a key point for the robustness of the screen, as gDNA preparations are challenging to standardize due to the disparity of growth rates between ES cell clones. (PDF 26 kb

Sequential schemes for frequentist estimation of properties in statistical model checking

National Research Foundation (NRF) Singapor

Lightweight Statistical Model Checking in Nondeterministic Continuous Time

Lightweight scheduler sampling brings statistical model checking to nondeterministic formalisms with undiscounted properties, in constant memory. Its direct application to continuous-time models is rendered ineffective by their dense concrete state spaces and the need to consider continuous input for optimal decisions. In this paper we describe the challenges and state of the art in applying lightweight scheduler sampling to three continuous-time formalisms: After a review of recent work on exploiting discrete abstractions for probabilistic timed automata, we discuss scheduler sampling for Markov automata and apply it on two case studies. We provide further insights into the tradeoffs between scheduler classes for stochastic automata. Throughout, we present extended experiments and new visualisations of the distribution of schedulers.</p

Rapid tree carbon stock recovery in managed Amazonian forests.

While around 20% of the Amazonian forest has been cleared for pastures and agriculture, one fourth of the remaining forest is dedicated to wood production [1] . Most of these production forests have been or will be selectively harvested for commercial timber, but recent studies show that even soon after logging, harvested stands retain much of their tree-biomass carbon and biodiversity [2,3] . Comparing species richness of various animal taxa among logged and unlogged forests across the tropics, Burivalova et al.[4] found that despite some variability among taxa, biodiversity loss was generally explained by logging intensity (the number of trees extracted). Here, we use a network of 79 permanent sample plots (376 ha total) located at 10 sites across the Amazon Basin [5] to assess the main drivers of time-to-recovery of post-logging tree carbon ( Table S1 ). Recovery time is of direct relevance to policies governing management practices (i.e., allowable volumes cut and cutting cycle lengths), and indirectly to forest-based climate change mitigation interventions

Nut production in Bertholletia excelsa across a logged forest mosaic: implications for multiple forest use

Although many examples of multiple-use forest management may be found in tropical smallholder systems, few studies provide empirical support for the integration of selective timber harvesting with non-timber forest product (NTFP) extraction. Brazil nut (Bertholletia excelsa, Lecythidaceae) is one of the world’s most economically-important NTFP species extracted almost entirely from natural forests across the Amazon Basin. An obligate out-crosser, Brazil nut flowers are pollinated by large-bodied bees, a process resulting in a hard round fruit that takes up to 14 months to mature. As many smallholders turn to the financial security provided by timber, Brazil nut fruits are increasingly being harvested in logged forests. We tested the influence of tree and stand-level covariates (distance to nearest cut stump and local logging intensity) on total nut production at the individual tree level in five recently logged Brazil nut concessions covering about 4000 ha of forest in Madre de Dios, Peru. Our field team accompanied Brazil nut harvesters during the traditional harvest period (January-April 2012 and January-April 2013) in order to collect data on fruit production. Three hundred and ninety-nine (approximately 80%) of the 499 trees included in this study were at least 100 m from the nearest cut stump, suggesting that concessionaires avoid logging near adult Brazil nut trees. Yet even for those trees on the edge of logging gaps, distance to nearest cut stump and local logging intensity did not have a statistically significant influence on Brazil nut production at the applied logging intensities (typically 1–2 timber trees removed per ha). In one concession where at least 4 trees ha-1 were removed, however, the logging intensity covariate resulted in a marginally significant (0.09) P value, highlighting a potential risk for a drop in nut production at higher intensities. While we do not suggest that logging activities should be completely avoided in Brazil nut rich forests, when a buffer zone cannot be observed, low logging intensities should be implemented. The sustainability of this integrated management system will ultimately depend on a complex series of socioeconomic and ecological interactions. Yet we submit that our study provides an important initial step in understanding the compatibility of timber harvesting with a high value NTFP, potentially allowing for diversification of forest use strategies in Amazonian Perù