Search results for "HMS"
showing 10 items of 1766 documents
Reverse-engineering the Arabidopsis thaliana transcriptional network under changing environmental conditions
2009
46 pages, 4 tables, 6 figures, 3 additinoal files.
Discrimination of fish populations using parasites: Random Forests on a ‘predictable’ host-parasite system
2010
SUMMARYWe address the effect of spatial scale and temporal variation on model generality when forming predictive models for fish assignment using a new data mining approach, Random Forests (RF), to variable biological markers (parasite community data). Models were implemented for a fish host-parasite system sampled along the Mediterranean and Atlantic coasts of Spain and were validated using independent datasets. We considered 2 basic classification problems in evaluating the importance of variations in parasite infracommunities for assignment of individual fish to their populations of origin: multiclass (2–5 population models, using 2 seasonal replicates from each of the populations) and 2…
Efficient estimation of generalized linear latent variable models.
2019
Generalized linear latent variable models (GLLVM) are popular tools for modeling multivariate, correlated responses. Such data are often encountered, for instance, in ecological studies, where presence-absences, counts, or biomass of interacting species are collected from a set of sites. Until very recently, the main challenge in fitting GLLVMs has been the lack of computationally efficient estimation methods. For likelihood based estimation, several closed form approximations for the marginal likelihood of GLLVMs have been proposed, but their efficient implementations have been lacking in the literature. To fill this gap, we show in this paper how to obtain computationally convenient estim…
Spatiotemporal Structure of Host‐Pathogen Interactions in a Metapopulation
2009
International audience; The ecological and evolutionary dynamics of species are influenced by spatiotemporal variation in population size. Unfortunately, we are usually limited in our ability to investigate the numerical dynamics of natural populations across large spatial scales and over long periods of time. Here we combine mechanistic and statistical approaches to reconstruct continuous-time infection dynamics of an obligate fungal pathogen on the basis of discrete-time occurrence data. The pathogen, Podosphaera plantaginis, infects its host plant, Plantago lanceolata, in a metapopulation setting where the presence of the pathogen has been recorded annually for 6 years in similar to 4,00…
A Network Model for the Correlation between Epistasis and Genomic Complexity
2008
The study of genetic interactions (epistasis) is central to the understanding of genome organization and evolution. A general correlation between epistasis and genomic complexity has been recently shown, such that in simpler genomes epistasis is antagonistic on average (mutational effects tend to cancel each other out), whereas a transition towards synergistic epistasis occurs in more complex genomes (mutational effects strengthen each other). Here, we use a simple network model to identify basic features explaining this correlation. We show that, in small networks with multifunctional nodes, lack of redundancy, and absence of alternative pathways, epistasis is antagonistic on average. In c…
Vector activity of Hyalesthes obsoletus living on nettles and transmitting a stolbur phytoplasma to grapevines: a case study
2007
International audience; We report a case study on the vector activity of a Hyalesthes obsoletus (Hemiptera: Cixiidae) population living on nettle plants (Urtica dioica) and transmitting a stolbur phytoplasma (Sp) to grapevines (Vitis vinifera). The research was conducted in a site that included a vineyard bordered with a large fallow area where nettles were the predominant plant species together with sparse old grapevines. Nettles hosted a high population of H. obsoletus. By using transparent sticky traps to sample adults, we observed that the daily flight activity of males and females to grapevines in the fallow was unimodal peaking between 15 and 21 h in the day. Adults were unable of gre…
Patterns of movement of released female brown bears in the Cantabrian Mountains, northwestern Spain
2017
Between 2008 and 2013, 3 female brown bears (Ursus arctos; 2 cubs-of-the-year and 1 2-yr-old) were rescued, rehabilitated in captivity, radiotagged, and released back to the Cantabrian Mountains, northwestern Spain. We characterized their daily and seasonal movements post-release to gain insights into their movement strategies and the viability of bears released in human-dominated environments. The bears exhibited marked diurnal activity and were active throughout winter. Two bears demonstrated behaviors similar to those reported for wild bears, whereas one cub-of-the-year was recaptured after 21 days because she developed signs of habituation to humans.
Online Scheduling of Task Graphs on Hybrid Platforms
2018
Modern computing platforms commonly include accelerators. We target the problem of scheduling applications modeled as task graphs on hybrid platforms made of two types of resources, such as CPUs and GPUs. We consider that task graphs are uncovered dynamically, and that the scheduler has information only on the available tasks, i.e., tasks whose predecessors have all been completed. Each task can be processed by either a CPU or a GPU, and the corresponding processing times are known. Our study extends a previous \(4\sqrt{m/k}\)-competitive online algorithm [2], where m is the number of CPUs and k the number of GPUs (\(m\ge k\)). We prove that no online algorithm can have a competitive ratio …
Ant Colony Optimisation-Based Classification Using Two-Dimensional Polygons
2016
The application of Ant Colony Optimization to the field of classification has mostly been limited to hybrid approaches which attempt at boosting the performance of existing classifiers (such as Decision Trees and Support Vector Machines (SVM)) — often through guided feature reductions or parameter optimizations.
Machine Learning Approaches for Activity Recognition and/or Activity Prediction in Locomotion Assistive Devices—A Systematic Review
2020
Locomotion assistive devices equipped with a microprocessor can potentially automatically adapt their behavior when the user is transitioning from one locomotion mode to another. Many developments in the field have come from machine learning driven controllers on locomotion assistive devices that recognize/predict the current locomotion mode or the upcoming one. This review synthesizes the machine learning algorithms designed to recognize or to predict a locomotion mode in order to automatically adapt the behavior of a locomotion assistive device. A systematic review was conducted on the Web of Science and MEDLINE databases (as well as in the retrieved papers) to identify articles published…