Search results for "TW"
showing 10 items of 16860 documents
Thompson Sampling Based Active Learning in Probabilistic Programs with Application to Travel Time Estimation
2019
The pertinent problem of Traveling Time Estimation (TTE) is to estimate the travel time, given a start location and a destination, solely based on the coordinates of the points under consideration. This is typically solved by fitting a function based on a sequence of observations. However, it can be expensive or slow to obtain labeled data or measurements to calibrate the estimation function. Active Learning tries to alleviate this problem by actively selecting samples that minimize the total number of samples needed to do accurate inference. Probabilistic Programming Languages (PPL) give us the opportunities to apply powerful Bayesian inference to model problems that involve uncertainties.…
Modularity as a source of new morphological variation in the mandible of hybrid mice.
2012
Abstract Background Hybridization is often seen as a process dampening phenotypic differences accumulated between diverging evolutionary units. For a complex trait comprising several relatively independent modules, hybridization may however simply generate new phenotypes, by combining into a new mosaic modules inherited from each parental groups and parts intermediate with respect to the parental groups. We tested this hypothesis by studying mandible size and shape in a set of first and second generation hybrids resulting from inbred wild-derived laboratory strains documenting two subspecies of house mice, Musmusculus domesticus and Musmusculus musculus. Phenotypic variation of the mandible…
Temperate Fish Detection and Classification: a Deep Learning based Approach
2021
A wide range of applications in marine ecology extensively uses underwater cameras. Still, to efficiently process the vast amount of data generated, we need to develop tools that can automatically detect and recognize species captured on film. Classifying fish species from videos and images in natural environments can be challenging because of noise and variation in illumination and the surrounding habitat. In this paper, we propose a two-step deep learning approach for the detection and classification of temperate fishes without pre-filtering. The first step is to detect each single fish in an image, independent of species and sex. For this purpose, we employ the You Only Look Once (YOLO) …
Comparative biogeography of echinoids, bivalves and gastropods from the Southern Ocean.
2013
ABSTRACTAim Biogeographical patterns within three classes, the Echinoidea, Bivalvia andGastropoda, were investigated in Antarctic, sub-Antarctic and cold-temperateareas based on species occurrence data. Faunal similarities among regions wereanalysed to: (1) test the robustness of the biogeographical patterns previouslyidentified in bivalves and gastropods; (2) compare them with the biogeographi-cal patterns identified for echinoids; and (3) evaluate the reliability of the bio-geographical provinces previously proposed, depending on the taxa andtaxonomic levels analysed.Location The Southern Ocean, sub-Antarctic islands and cold-temperate areassouth of 45° S latitude at depths of < 1000 m.Meth…
Condition-dependent skipped spawning in anadromous brown trout (Salmo trutta)
2018
Repeat spawners of anadromous salmonids may contribute significantly to population resilience by providing multiple cohorts to both seawater and freshwater life stages. In this study, winter survival of sea trout (Salmo trutta Linnaeus, 1758) post spawners (kelts) was 89%. Sea survival increased linearly with female length with a return probability between 30% and 50%, whereas males attained a maximum return probability of 60% at 520 mm. Of the returning sea trout, 40% skipped spawning and they had significantly lower condition factor as kelts compared with those who returned after one summer. These results suggest that sex-specific differences in individual post-spawning growth–survival t…
Facebook groups as citizen science tools for plant species monitoring
2021
I social network sono canali di comunicazione utilizzati per condividere enormi quantità di dati, che possono essere utilizzati per la ricerca scientifica, anche nel campo della biodiversità. Per sapere quanto i dati ricavati dai social network possono integrare quelli raccolti per scopi scientifici, è necessario individuarne i bias. Utilizzando i dati estratti da un gruppo Facebook specializzato nella flora vascolare siciliana, abbiamo analizzato quali sono i caratteri che aumentano la probabilità che una pianta spontanea venga fotografata e postata su un social network. A tal fine, abbiamo confrontato frequenze e attributi delle specie fotografate dai membri del gruppo Facebook con quelli…
Functional genomics of arbuscular mycorrhiza : decoding the symbiotic cell programme
2004
More extensive insight into plant genes involved in the symbiotic programme of arbuscular mycorrhiza is presently being achieved by global approaches that aim to discover novel genes or subsets of genes that are essential to cell programmes in the different steps of plantfungal interactions. The strategy of functional genomics based on large-scale differential RNA expression analyses (differential-display reverse transcriptase - PCR), electronic Northerns, suppressive subtractive hybridization, DNA chips) is presented, with a focus on arbuscular mycorrhiza in Pisum sativum and Medicago truncatula. The most recent knowledge about gene networks that are modulated in roots during arbuscular …
Machine learning predictions of trophic status indicators and plankton dynamic in coastal lagoons
2018
Abstract Multivariate trophic indices provide an efficient way to assess and classify the eutrophication level and ecological status of a given water body, but their computation requires the availability of experimental information on many parameters, including biological data, that might not always be available. Here we show that machine learning techniques – once trained against a full data set – can be used to infer plankton biomass information from chemical and physical parameter only, so that trophic index can then be computed without using additional biological data. More specifically, we reconstruct plankton information from chemical and physical data, and this information together w…
Distance decay 2.0 – a global synthesis of taxonomic and functional turnover in ecological communities
2021
AbstractUnderstanding the variation in community composition and species abundances, i.e., β-diversity, is at the heart of community ecology. A common approach to examine β-diversity is to evaluate directional turnover in community composition by measuring the decay in the similarity among pairs of communities along spatial or environmental distances. We provide the first global synthesis of taxonomic and functional distance decay along spatial and environmental distance by analysing 149 datasets comprising different types of organisms and environments. We modelled an exponential distance decay for each dataset using generalized linear models and extracted r2 and slope to analyse the streng…
Genome reduction and potential metabolic complementation of the dual endosymbionts in the whitefly Bemisia tabaci
2015
Background The whitefly Bemisia tabaci is an important agricultural pest with global distribution. This phloem-sap feeder harbors a primary symbiont, “Candidatus Portiera aleyrodidarum”, which compensates for the deficient nutritional composition of its food sources, and a variety of secondary symbionts. Interestingly, all of these secondary symbionts are found in co-localization with the primary symbiont within the same bacteriocytes, which should favor the evolution of strong interactions between symbionts. Results In this paper, we analyzed the genome sequences of the primary symbiont Portiera and of the secondary symbiont Hamiltonella in the B. tabaci Mediterranean (MED) species in orde…