Search results for " processing"
showing 10 items of 7549 documents
Ephaptic coupling of myelinated nerve fibers
2001
Numerical predictions of a simple myelinated nerve fiber model are compared with theoretical results in the continuum and discrete limits, clarifying the nature of the conduction process on an isolated nerve axon. Since myelinated nerve fibers are often arranged in bundles, this model is used to study ephaptic (nonsynaptic) interactions between impulses on parallel fibers, which may play a functional role in neural processing.
POSS Grafting on Polyethylene and Maleic Anhydride-Grafted Polyethylene by One-Step Reactive Melt Mixing
2018
This study reports the one-step reactive melt mixing preparation of organic-inorganic hybrid based on maleic anhydride-grafted polyethylene and 3-(2-aminoethyl)aminopropyl-heptaisobutyl substituted polyhedral oligomeric silsesquioxane, (NPOSS), as well as on low-density polyethylene and allyl-heptaisobutyl-POSS (1POSS) in dicumyl peroxide presence, which is believed to activate the unsaturation of the reactive functional group of POSS itself. The successful grafting of POSS molecules onto polymeric backbones was probed through rheological and spectroscopic analysis. Grafting of POSS molecules enhances their dispersion in the polymeric matrix as shown by morphological analysis. Moreover, the…
Textureless macula swelling detection with multiple retinal fundus images
2011
Retinal fundus images acquired with nonmydriatic digital fundus cameras are versatile tools for the diagnosis of various retinal diseases. Because of the ease of use of newer camera models and their relatively low cost, these cameras can be employed by operators with limited training for telemedicine or point-of-care (PoC) applications. We propose a novel technique that uses uncalibrated multiple-view fundus images to analyze the swelling of the macula. This innovation enables the detection and quantitative measurement of swollen areas by remote ophthalmologists. This capability is not available with a single image and prone to error with stereo fundus cameras. We also present automatic alg…
Mitigation of enniatins in edible fish tissues by thermal processes and identification of degradation products.
2017
Emerging mycotoxins, such as enniatins and beauvericin, are common contaminants in vegetal matrices, but recently, the occurrence of mycotoxins in foodstuffs from animal origin has been also reported as they can be present in edible tissues of animals fed with contaminated feedstuffs. Sea bass, sea bream, Atlantic salmon and rainbow trout from aquaculture analyzed in the present survey showed contamination by emerging Fusarium mycotoxins enniatins (ENs). ENs were extracted from raw and cooked fish with acetonitrile and analyzed by Liquid Chromatography coupled to Mass Spectrometry. In this study, the stability of ENs was evaluated during food processing by the application of different cooki…
Occurrence, toxicity, bioaccessibility and mitigation strategies of beauvericin, a minor Fusarium mycotoxin.
2017
Emerging Fusarium mycotoxins include the toxic secondary metabolites fusaproliferin, enniatins, beauvericin (BEA), and moniliform. BEA is produced by some entomo- and phytopathogenic Fusarium species and occurs naturally on corn and corn-based foods and feeds infected by Fusarium spp. BEA has shown various biological activities (antibacterial, antifungal, and insecticidal) and possesses toxic activity, including the induction of apoptosis, increase cytoplasmic calcium concentration and lead to DNA fragmentation in mammalian cell lines. Cereals food processing has an important effect on mycotoxin stability, leading to less-contaminated food compared to the raw materials. Different industrial…
A study on the effect of contact pressure during physical activity on photoplethysmographic heart rate measurements
2020
Heart rate (HR) as an important physiological indicator could properly describe global subject&rsquo
An integrated fuzzy cells-classifier
2007
This paper introduces a genetic algorithm able to combine different classifiers based on different distance functions. The use of a genetic algorithm is motivated by the fact that the combination phase is based on the optimization of a vote strategy. The method has been applied to the classification of four types of biological cells, results show an improvement of the recognition rate using the genetic algorithm combination strategy compared with the recognition rate of each single classifier.
A genetic integrated fuzzy classifier
2005
This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells. The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.
A Combined Fuzzy and Probabilistic Data Descriptor for Distributed CBIR
2009
With the wide diffusion of digital image acquisition devices, the cost of managing hundreds of digital images is quickly increasing. Currently, the main way to search digital image libraries is by keywords given by the user. However, users usually add ambiguos keywords for large set of images. A content-based system intended to automatically find a query image, or similar images, within the whole collection is needed. In our work we address the scenario where medical image collections, which nowadays are rapidly expanding in quantity and heterogeneity, are shared in a distributed system to support diagnostic and preventive medicine. Our goal is to produce an efficient content-based descript…
Scalable Clustering by Iterative Partitioning and Point Attractor Representation
2016
Clustering very large datasets while preserving cluster quality remains a challenging data-mining task to date. In this paper, we propose an effective scalable clustering algorithm for large datasets that builds upon the concept of synchronization. Inherited from the powerful concept of synchronization, the proposed algorithm, CIPA (Clustering by Iterative Partitioning and Point Attractor Representations), is capable of handling very large datasets by iteratively partitioning them into thousands of subsets and clustering each subset separately. Using dynamic clustering by synchronization, each subset is then represented by a set of point attractors and outliers. Finally, CIPA identifies the…