995 resultados para Filters methods


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Polycyclic aromatic hydrocarbons, butyltins, polychlorinated biphenyls, DDT and metabolites, other chlorinated pesticides, trace and major elements, and a number of measures of contaminant effects are quantified in bivalves and sediments collected as part of the NOAA National Status and Trends (NS&T) Program. This document contains descriptions of some of the sampling and analytical protocols used by NS&T contract laboratories from 1993 through 1996. (PDF contains 257 pages)

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South Carolina’s oyster reefs are a major component of the coastal landscape. Eastern oysters Crassostrea virginica are an important economic resource to the state and serve many essential functions in the environment, including water filtration, creek bank stabilization and habitat for other plants and animals. Effective conservation and management of oyster reefs is dependent on an understanding of their abundance, distribution, condition, and change over time. In South Carolina, over 95% of the state’s oyster habitat is intertidal. The current intertidal oyster reef database for South Carolina was developed by field assessment over several years. This database was completed in the early 1980s and is in need of an update to assess resource/habitat status and trends across the state. Anthropogenic factors such as coastal development and associated waterway usage (e.g., boat wakes) are suspected of significantly altering the extent and health of the state’s oyster resources. In 2002 the NOAA Coastal Services Center’s (Center) Coastal Remote Sensing Program (CRS) worked with the Marine Resources Division of the South Carolina Department of Natural Resources (SCDNR) to develop methods for mapping intertidal oyster reefs along the South Carolina coast using remote sensing technology. The objective of this project was to provide SCDNR with potential methodologies and approaches for assessing oyster resources in a more efficiently than could be accomplished through field digitizing. The project focused on the utility of high-resolution aerial imagery and on documenting the effectiveness of various analysis techniques for accomplishing the update. (PDF contains 32 pages)

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Functional Electrical Stimulation (FES) is a technique that consists on applying electrical current pulses to artificially activate motor nerve fibers and produce muscle contractions to achieve functional movements. The main applications of FES are within the rehabilitation field, in which this technique is used to aid recovery or to restore lost motor functions. People that benefit of FES are usually patients with neurological disorders which result in motor dysfunctions; most common patients include stroke and spinal cord injury (SCI). Neuroprosthesis are devices that have their basis in FES technique, and their aim is to bridge interrupted or damaged neural paths between the brain and upper or lower limbs. One of the aims of neuroprosthesis is to artificially generate muscle contractions that produce functional movements, and therefore, assist impaired people by making them able to perform activities of daily living (ADL). FES applies current pulses and stimulates nerve fibers by means of electrodes, which can be either implanted or surface electrodes. Both of them have advantages and disadvantages. Implanted electrodes need open surgery to place them next to the nerve root, so these electrodes carry many disadvantages that are produced by the use of invasive techniques. In return, as the electrodes are attached to the nerve, they make it easier to achieve selective functional movements. On the contrary, surface electrodes are not invasive and are easily attached or detached on the skin. Main disadvantages of surface electrodes are the difficulty of selectively stimulating nerve fibers and uncomfortable feeling perceived by users due to sensory nerves located in the skin. Electrical stimulation surface electrode technology has improved significantly through the years and recently, multi-field electrodes have been suggested. This multi-field or matrix electrode approach brings many advantages to FES; among them it is the possibility of easily applying different stimulation methods and techniques. The main goal of this thesis is therefore, to test two stimulation methods, which are asynchronous and synchronous stimulation, in the upper limb with multi-field electrodes. To this end, a purpose-built wrist torque measuring system and a graphic user interface were developed to measure wrist torque produced with each of the methods and to efficiently carry out the experiments. Then, both methods were tested on 15 healthy subjects and sensitivity results were analyzed for different cases. Results show that there are significant differences between methods regarding sensation in some cases, which can affect effectiveness or success of FES.

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The successful application of techniques to enhance detection of age marks in biological specimens is of vital importance in fisheries research. This manual documents age determination techniques used by staff at the Woods Hole Laboratory, National Marine Fisheries Service. General information on procedures for preparing anatomical structures is described, together with criteria used to interpret growth patterns and assign ages. Annotated photographs of age structures are provided to illustrate criteria. Detailed procedures are given for the following species: Atlantic herring (Clupea harengus), haddock (Melanogrammus aeglefinus), Atlantic cod (Gadus morhua), pollock (Pollachius virens), silver hake (Merluccius bilinearis), red hake (Urophycis chuss), black sea bass (Centropristis striata), weakfish (Cynoscion regalis), Atlantic mackerel (Scomber scombrus), butterfish (Peprilus triacanthus), redfish (Sebastes fasciatus), summer flounder (Paralichthys dentatus), winter flounder (Pseudopleuronectes americanus), witch flounder (Glyptocephalus cynoglossus), American plaice (Hippoglossoides platessoides), yellowtail flounder (Limanda ferruginea), surf clam (Spisula solidissima), and ocean quahog (Arctica islandica). (PDF file contains 142 pages.)

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Accurate and fast decoding of speech imagery from electroencephalographic (EEG) data could serve as a basis for a new generation of brain computer interfaces (BCIs), more portable and easier to use. However, decoding of speech imagery from EEG is a hard problem due to many factors. In this paper we focus on the analysis of the classification step of speech imagery decoding for a three-class vowel speech imagery recognition problem. We empirically show that different classification subtasks may require different classifiers for accurately decoding and obtain a classification accuracy that improves the best results previously published. We further investigate the relationship between the classifiers and different sets of features selected by the common spatial patterns method. Our results indicate that further improvement on BCIs based on speech imagery could be achieved by carefully selecting an appropriate combination of classifiers for the subtasks involved.

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