6,958 research outputs found
Efficient Evaluation of the Number of False Alarm Criterion
This paper proposes a method for computing efficiently the significance of a
parametric pattern inside a binary image. On the one hand, a-contrario
strategies avoid the user involvement for tuning detection thresholds, and
allow one to account fairly for different pattern sizes. On the other hand,
a-contrario criteria become intractable when the pattern complexity in terms of
parametrization increases. In this work, we introduce a strategy which relies
on the use of a cumulative space of reduced dimensionality, derived from the
coupling of a classic (Hough) cumulative space with an integral histogram
trick. This space allows us to store partial computations which are required by
the a-contrario criterion, and to evaluate the significance with a lower
computational cost than by following a straightforward approach. The method is
illustrated on synthetic examples on patterns with various parametrizations up
to five dimensions. In order to demonstrate how to apply this generic concept
in a real scenario, we consider a difficult crack detection task in still
images, which has been addressed in the literature with various local and
global detection strategies. We model cracks as bounded segments, detected by
the proposed a-contrario criterion, which allow us to introduce additional
spatial constraints based on their relative alignment. On this application, the
proposed strategy yields state-of the-art results, and underlines its potential
for handling complex pattern detection tasks
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Characterization of ecosystem services associated with deep-sea habitats and natural stormwater treatment systems and their incorporation into environmental management
We, as a society, are notoriously bad at finding balance between extraction of natural resources and environmental protection. The concept of ecosystem services, the direct and indirect benefits derived from the environment, attempts to ameliorate these failures by linking natural processes to human well-being. The goal of this dissertation was to explore approaches for characterizing ecosystem services and to identify how they can be incorporated into environmental management. To do this, I used two groups of systems subject to human impact, deep-sea habitats and natural stormwater treatment systems (NTS), that provided a suite of characteristics with which to compare and contrast (e.g. marine versus terrestrial, level of human impact, ease of access). While deep-sea habitats and NTS provide some of the same ecosystem services, the structures and functions that support them can differ. Mechanisms for incorporating this information into environmental decision-making differ among systems as well. As interest in deep-sea natural resources continues to grow, environmental decision-makers have the novel opportunity to employ an ecosystem services approach, prior to commercial exploitation in cases such as mining. In comparing molecular and morphology-based methods for assessment and monitoring of deep-sea biodiversity, I examined scientific and economic tradeoffs between the two to suggest a combined approach as most cost-effective when considering future environmental requirements. I also leveraged existing deep-sea imagery and biological trait analysis to evaluate fisheries services and climate-regulating services related to carbon at methane seeps off southern California, identifying the Del Mar seep as the largest contributor to ecosystem services. In contrast to the seemingly untouched deep sea, NTS are human-designed to mimic physical and biological processes, which can generate ecosystem services such as climate-regulating services related to carbon. I found that, although urban greenspaces are not carbon sinks, NTS and natural areas are more carbon-efficient than grass lawns and horticultural gardens. NTS present a unique opportunity to manipulate natural structures and functions for targeted benefits, such as carbon sequestration and storage. Together, this body of work serves to operationalize ecosystem services in a multitude of contexts with practical applications
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Resource guide for speech-language practitioners : side effects of seizure medications
textSide effects of seizure medications in individuals with intellectual disabilities (ID) may affect speech and language development for this population. Research information about these effects may be useful for speech-language pathologist practitioners, since they will most likely work in environments that involve assessing and treating individuals with ID. In this meta-analysis, a total of 19 articles were reviewed to examine the side effects of AEDs in individuals with ID and seizure disorders. Side effects from AEDs were found; however, research regarding how AEDs and seizure disorders affected speech and language development was not available. Based on the findings, participants on AEDs regimens experienced a variety of side effects that included behavioral side effects, adverse cognitive side effects, and non-behavioral side effects. However, information regarding AEDs side effects and speech and language development was nonexistent. Based on the findings, further research in this is much needed for practicing speech-language pathologists in this topic.Communication Sciences and Disorder
Consequences of cell-to-cell P-glycoprotein transfer on acquired multidrug resistance in breast cancer: a cell population dynamics model
Cancer is a proliferation disease affecting a genetically unstable cell
population, in which molecular alterations can be somatically inherited by
genetic, epigenetic or extragenetic transmission processes, leading to a
cooperation of neoplastic cells within tumoral tissue. The efflux protein
P-glycoprotein (P gp) is overexpressed in many cancer cells and has known
capacity to confer multidrug resistance to cytotoxic therapies. Recently,
cell-to-cell P-gp transfers have been shown. Herein, we combine experimental
evidence and a mathematical model to examine the consequences of an
intercellular P-gp trafficking in the extragenetic transfer of multidrug
resistance from resistant to sensitive cell subpopulations. We report
cell-to-cell transfers of functional P-gp in co-cultures of a P-gp
overexpressing human breast cancer MCF-7 cell variant, selected for its
resistance towards doxorubicin, with the parental sensitive cell line. We found
that P-gp as well as efflux activity distribution are progressively reorganized
over time in co-cultures analyzed by flow cytometry. A mathematical model based
on a Boltzmann type integro-partial differential equation structured by a
continuum variable corresponding to P-gp activity describes the cell
populations in co-culture. The mathematical model elucidates the population
elements in the experimental data, specifically, the initial proportions, the
proliferative growth rates, and the transfer rates of P-gp in the sensitive and
resistant subpopulations. We confirmed cell-to-cell transfer of functional
P-gp. The transfer process depends on the gradient of P-gp expression in the
donor-recipient cell interactions, as they evolve over time. Extragenetically
acquired drug resistance is an additional aptitude of neoplastic cells which
has implications in the diagnostic value of P-gp expression and in the design
of chemotherapy regimensComment: 13 pages, 8 figures, 1 tabl
Supervised machine learning based multi-task artificial intelligence classification of retinopathies
Artificial intelligence (AI) classification holds promise as a novel and
affordable screening tool for clinical management of ocular diseases. Rural and
underserved areas, which suffer from lack of access to experienced
ophthalmologists may particularly benefit from this technology. Quantitative
optical coherence tomography angiography (OCTA) imaging provides excellent
capability to identify subtle vascular distortions, which are useful for
classifying retinovascular diseases. However, application of AI for
differentiation and classification of multiple eye diseases is not yet
established. In this study, we demonstrate supervised machine learning based
multi-task OCTA classification. We sought 1) to differentiate normal from
diseased ocular conditions, 2) to differentiate different ocular disease
conditions from each other, and 3) to stage the severity of each ocular
condition. Quantitative OCTA features, including blood vessel tortuosity (BVT),
blood vascular caliber (BVC), vessel perimeter index (VPI), blood vessel
density (BVD), foveal avascular zone (FAZ) area (FAZ-A), and FAZ contour
irregularity (FAZ-CI) were fully automatically extracted from the OCTA images.
A stepwise backward elimination approach was employed to identify sensitive
OCTA features and optimal-feature-combinations for the multi-task
classification. For proof-of-concept demonstration, diabetic retinopathy (DR)
and sickle cell retinopathy (SCR) were used to validate the supervised machine
leaning classifier. The presented AI classification methodology is applicable
and can be readily extended to other ocular diseases, holding promise to enable
a mass-screening platform for clinical deployment and telemedicine.Comment: Supplemental material attached at the en
DCU-Paris13 systems for the SANCL 2012 shared task
The DCU-Paris13 team submitted three systems to the SANCL 2012 shared task on parsing English web text. The first submission, the highest ranked constituency parsing system, uses a combination of PCFG-LA product grammar parsing and self-training. In the second submission, also a constituency parsing system, the n-best lists of various parsing models are combined using an approximate sentence-level product model. The third system, the highest ranked system in the dependency parsing track, uses voting over dependency arcs to combine the output of three constituency parsing systems which have been converted to dependency trees. All systems make use of a data-normalisation component, a parser accuracy predictor and a genre classifier
Involvement of small-scale dairy farms in an industrial supply chain: When production standards meet farm diversity
In certain contexts, dairy firms are supplied by small-scale family farms. Firms provide a set of technical and economic recommendations meant to help farmers meet their requirements in terms of the quantity and quality of milk collected. This study analyzes how such recommendations may be adopted by studying six farms in Brazil. All farms are beneficiaries of the country's agrarian reforms, but they differ in terms of how they developed their activities, their resources and their milk collection objectives. First, we built a technical and economic benchmark farm based on recommendations from a dairy firm and farmer advisory institutions. Our analysis of the farms' practices and technical and economic results show that none of the farms in the sample apply all of the benchmark recommendations; however, all farms specialized in dairy production observe the main underlying principles with regard to feeding systems and breeding. The decisive factors in whether the benchmark is adopted and successfully implemented are (i) access to the supply chain when a farmer establishes his activity, (ii) a grasp of reproduction and forage production techniques and (iii) an understanding of dairy cattle feed dietary rationing principles. The technical problems observed in some cases impact the farms' dairy performance and cash position; this can lead to a process of disinvestment. This dynamic of farms facing production standards suggests that the diversity of specialized livestock farmers should be taken into account more effectively through advisory approaches that combine basic zootechnical training with assistance in planning farm activities over the short and medium term. (Résumé d'auteur
Handling unknown words in statistical latent-variable parsing models for Arabic, English and French
This paper presents a study of the impact of using simple and complex morphological clues to improve the classification of rare and unknown words for parsing. We compare this approach to a language-independent technique
often used in parsers which is based solely on word frequencies. This study is applied to three languages that exhibit different levels of morphological expressiveness: Arabic, French and English. We integrate information
about Arabic affixes and morphotactics into a PCFG-LA parser and obtain stateof-the-art accuracy. We also show that these morphological clues can be learnt automatically
from an annotated corpus
From news to comment: Resources and benchmarks for parsing the language of web 2.0
We investigate the problem of parsing the noisy language of social media. We evaluate four all-Street-Journal-trained statistical parsers (Berkeley, Brown, Malt and MST) on a new dataset containing 1,000 phrase structure trees for sentences from microblogs (tweets) and discussion forum posts. We compare the four parsers on their ability to produce Stanford dependencies for these Web 2.0 sentences. We find that the parsers have a particular problem with tweets and that a substantial part of this problem is related to POS tagging accuracy. We attempt three retraining experiments involving Malt, Brown and an in-house Berkeley-style parser and obtain a statistically significant improvement for all three parsers
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