Search results for "Mach"
showing 10 items of 3360 documents
Novel simple templates for reproducible positioning of skin applicators in brachytherapy.
2016
Purpose : Esteya and Valencia surface applicators are designed to treat skin tumors using brachytherapy. In clinical practice, in order to avoid errors that may affect the treatment outcome, there are two issues that need to be carefully addressed. First, the selected applicator for the treatment should provide adequate margin for the target, and second, the applicator has to be precisely positioned before each treatment fraction. In this work, we describe the development and use of a new acrylic templates named Template La Fe-ITIC. They have been designed specifically to help the clinical user in the selection of the correct applicator, and to assist the medical staff in reproducing the po…
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.…
A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data
2018
This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then a…
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) …
Notulae to the Italian native vascular flora: 5
2018
In this contribution, new data concerning the distribution of native vascular flora in Italy are presented. It includes new records and confirmations to the Italian administrative regions for taxa in the genera Allium, Arabis, Campanula, Centaurea, Chaerophyllum, Crocus, Dactylis, Dianthus, Festuca, Galanthus, Helianthemum, Lysimachia, Milium, Pteris, and Quercus. Nomenclature and distribution updates, published elsewhere, and corrections are provided as supplementary material.
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…
Unsupervised Classification of Acoustic Echoes from Two Krill Species in the Southern Ocean (Ross Sea)
2021
This work presents a computational methodology able to automatically classify the echoes of two krill species recorded in the Ross sea employing scientific echo-sounder at three different frequencies (38, 120 and 200 kHz). The goal of classifying the gregarious species represents a time-consuming task and is accomplished by using differences and/or thresholds estimated on the energy features of the insonified targets. Conversely, our methodology takes into account energy, morphological and depth features of echo data, acquired at different frequencies. Internal validation indices of clustering were used to verify the ability of the clustering in recognizing the correct number of species. Th…
Diet and trophic niche of the invasive signal crayfish in the first invaded Italian stream ecosystem.
2021
The occurrence of the signal crayfsh Pacifastacus leniusculus in the Valla Stream was the frst established population of this invasive species recorded in an Italian stream ecosystem. We evaluated the seasonality of diet and trophic niche of invasive signal crayfsh in order to estimate the ecological role and efects on native communities of the stream ecosystem. We studied the diferences in food source use between sexes, life stages and seasons using carbon and nitrogen stable isotope analyses. To supplement stable isotope analyses, we evaluated food source usage using traditional stomach content analysis. We tested the hypothesis that juveniles have a diferent diet, showing diferent trophi…
Consumption of pelagic tunicates by cetaceans calves in the Mediterranean Sea
2018
Gelatinous zooplankton, including jellyfish, ctenophores and pelagic tunicates, constitutes fragile marine animals that live in the water column, and represent an important resource for marine food webs through their seasonal pulses. Although there is scarce evidence on the occurrence of gelatinous zooplankton in stomach contents of apex, endothermic predators such as cetaceans, the ecological significance of such observations requires consideration. In this study, we report on the occurrence of pelagic tunicates in the stomach of three individual calves of two cetacean species from the western Mediterranean, and collate all previous reports of gelatinous zooplankton in cetacean diets. We t…
Helminth communities of loggerhead turtles (Caretta caretta) from Central and Western Mediterranean Sea: the importance of host's ontogeny.
2009
We investigated the factors providing structure to the helminth communities of 182 loggerhead sea turtles, Caretta caretta, collected in 6 localities from Central and Western Mediterranean. Fifteen helminth taxa (10 digeneans, 4 nematodes and 1 acanthocephalan) were identified, of which 12 were specialist to marine turtles; very low numbers of immature individuals of 3 species typical from fish or cetaceans were also found. These observations confirm the hypothesis that phylogenetic factors restrict community composition to helminth species specific to marine turtles. There were significant community dissimilarities between turtles from different localities, the overall pattern being compat…