997 resultados para Perth Amboy Region (N.J.)--Maps.
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Without knowledge of basic seafloor characteristics, the ability to address any number of critical marine and/or coastal management issues is diminished. For example, management and conservation of essential fish habitat (EFH), a requirement mandated by federally guided fishery management plans (FMPs), requires among other things a description of habitats for federally managed species. Although the list of attributes important to habitat are numerous, the ability to efficiently and effectively describe many, and especially at the scales required, does not exist with the tools currently available. However, several characteristics of seafloor morphology are readily obtainable at multiple scales and can serve as useful descriptors of habitat. Recent advancements in acoustic technology, such as multibeam echosounding (MBES), can provide remote indication of surficial sediment properties such as texture, hardness, or roughness, and further permit highly detailed renderings of seafloor morphology. With acoustic-based surveys providing a relatively efficient method for data acquisition, there exists a need for efficient and reproducible automated segmentation routines to process the data. Using MBES data collected by the Olympic Coast National Marine Sanctuary (OCNMS), and through a contracted seafloor survey, we expanded on the techniques of Cutter et al. (2003) to describe an objective repeatable process that uses parameterized local Fourier histogram (LFH) texture features to automate segmentation of surficial sediments from acoustic imagery using a maximum likelihood decision rule. Sonar signatures and classification performance were evaluated using video imagery obtained from a towed camera sled. Segmented raster images were converted to polygon features and attributed using a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999) for use in a geographical information system (GIS). (PDF contains 41 pages.)
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Table of Contents
1 | Introduction | 1 |
1.1 | What is an Adiabatic Shear Band? | 1 |
1.2 | The Importance of Adiabatic Shear Bands | 6 |
1.3 | Where Adiabatic Shear Bands Occur | 10 |
1.4 | Historical Aspects of Shear Bands | 11 |
1.5 | Adiabatic Shear Bands and Fracture Maps | 14 |
1.6 | Scope of the Book | 20 |
2 | Characteristic Aspects of Adiabatic Shear Bands | 24 |
2.1 | General Features | 24 |
2.2 | Deformed Bands | 27 |
2.3 | Transformed Bands | 28 |
2.4 | Variables Relevant to Adiabatic Shear Banding | 35 |
2.5 | Adiabatic Shear Bands in Non-Metals | 44 |
3 | Fracture and Damage Related to Adiabatic Shear Bands | 54 |
3.1 | Adiabatic Shear Band Induced Fracture | 54 |
3.2 | Microscopic Damage in Adiabatic Shear Bands | 57 |
3.3 | Metallurgical Implications | 69 |
3.4 | Effects of Stress State | 73 |
4 | Testing Methods | 76 |
4.1 | General Requirements and Remarks | 76 |
4.2 | Dynamic Torsion Tests | 80 |
4.3 | Dynamic Compression Tests | 91 |
4.4 | Contained Cylinder Tests | 95 |
4.5 | Transient Measurements | 98 |
5 | Constitutive Equations | 104 |
5.1 | Effect of Strain Rate on Stress-Strain Behaviour | 104 |
5.2 | Strain-Rate History Effects | 110 |
5.3 | Effect of Temperature on Stress-Strain Behaviour | 114 |
5.4 | Constitutive Equations for Non-Metals | 124 |
6 | Occurrence of Adiabatic Shear Bands | 125 |
6.1 | Empirical Criteria | 125 |
6.2 | One-Dimensional Equations and Linear Instability Analysis | 134 |
6.3 | Localization Analysis | 140 |
6.4 | Experimental Verification | 146 |
7 | Formation and Evolution of Shear Bands | 155 |
7.1 | Post-Instability Phenomena | 156 |
7.2 | Scaling and Approximations | 162 |
7.3 | Wave Trapping and Viscous Dissipation | 167 |
7.4 | The Intermediate Stage and the Formation of Adiabatic Shear Bands | 171 |
7.5 | Late Stage Behaviour and Post-Mortem Morphology | 179 |
7.6 | Adiabatic Shear Bands in Multi-Dimensional Stress States | 187 |
8 | Numerical Studies of Adiabatic Shear Bands | 194 |
8.1 | Objects, Problems and Techniques Involved in Numerical Simulations | 194 |
8.2 | One-Dimensional Simulation of Adiabatic Shear Banding | 199 |
8.3 | Simulation with Adaptive Finite Element Methods | 213 |
8.4 | Adiabatic Shear Bands in the Plane Strain Stress State | 218 |
9 | Selected Topics in Impact Dynamics | 229 |
9.1 | Planar Impact | 230 |
9.2 | Fragmentation | 237 |
9.3 | Penetration | 244 |
9.4 | Erosion | 255 |
9.5 | Ignition of Explosives | 261 |
9.6 | Explosive Welding | 268 |
10 | Selected Topics in Metalworking | 273 |
10.1 | Classification of Processes | 273 |
10.2 | Upsetting | 276 |
10.3 | Metalcutting | 286 |
10.4 | Blanking | 293 |
Appendices | 297 | |
A | Quick Reference | 298 |
B | Specific Heat and Thermal Conductivity | 301 |
C | Thermal Softening and Related Temperature Dependence | 312 |
D | Materials Showing Adiabatic Shear Bands | 335 |
E | Specification of Selected Materials Showing Adiabatic Shear Bands | 341 |
F | Conversion Factors | 357 |
References | 358 | |
Author Index | 369 | |
Subject Index | 375 |
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EXECUTIVE SUMMARY: The Coastal Change Analysis Programl (C-CAP) is developing a nationally standardized database on landcover and habitat change in the coastal regions of the United States. C-CAP is part of the Estuarine Habitat Program (EHP) of NOAA's Coastal Ocean Program (COP). C-CAP inventories coastal submersed habitats, wetland habitats, and adjacent uplands and monitors changes in these habitats on a one- to five-year cycle. This type of information and frequency of detection are required to improve scientific understanding of the linkages of coastal and submersed wetland habitats with adjacent uplands and with the distribution, abundance, and health of living marine resources. The monitoring cycle will vary according to the rate and magnitude of change in each geographic region. Satellite imagery (primarily Landsat Thematic Mapper), aerial photography, and field data are interpreted, classified, analyzed, and integrated with other digital data in a geographic information system (GIS). The resulting landcover change databases are disseminated in digital form for use by anyone wishing to conduct geographic analysis in the completed regions. C-CAP spatial information on coastal change will be input to EHP conceptual and predictive models to support coastal resource policy planning and analysis. CCAP products will include 1) spatially registered digital databases and images, 2) tabular summaries by state, county, and hydrologic unit, and 3) documentation. Aggregations to larger areas (representing habitats, wildlife refuges, or management districts) will be provided on a case-by-case basis. Ongoing C-CAP research will continue to explore techniques for remote determination of biomass, productivity, and functional status of wetlands and will evaluate new technologies (e.g. remote sensor systems, global positioning systems, image processing algorithms) as they become available. Selected hardcopy land-cover change maps will be produced at local (1:24,000) to regional scales (1:500,000) for distribution. Digital land-cover change data will be provided to users for the cost of reproduction. Much of the guidance contained in this document was developed through a series of professional workshops and interagency meetings that focused on a) coastal wetlands and uplands; b) coastal submersed habitat including aquatic beds; c) user needs; d) regional issues; e) classification schemes; f) change detection techniques; and g) data quality. Invited participants included technical and regional experts and representatives of key State and Federal organizations. Coastal habitat managers and researchers were given an opportunity for review and comment. This document summarizes C-CAP protocols and procedures that are to be used by scientists throughout the United States to develop consistent and reliable coastal change information for input to the C-CAP nationwide database. It also provides useful guidelines for contributors working on related projects. It is considered a working document subject to periodic review and revision.(PDF file contains 104 pages.)
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Greenland turbot (Reinhardtius hippoglossoides) is a commercially important flounder in both the North Atlantic and North Pacific Oceans. In the latter, its center of abundance is in the eastern Bering Sea and along the Aleutian Islands chain where its population is managed as a single stock. Harvest levels in this region of the North Pacific during the period 1970-81 were comparable with those in the northwest and northeast Atlantic, with annual average catches of 53,000 metric tons (t). However, the catch in 1984 dropped sharply to 23,100 t, in part because of reduced quotas arising from concern over continued poor recruitment and declining catch-per-unit-effort. Recruitment failure was manifested in 1) the sharp decline in the catch rate of young flsh in annual research trawl surveys on the continental shelf of the eastern Bering Sea and 2) an increasing proportion of older and larger fish in the commercial catch from the continental slope of both the eastern Bering Sea and Aleutian Islands. The cause ofthe decline in recruitment could not be clearly identifled. Greenland turbot of the Bering Sea-Aleutian Islands share certain distributional features with the North Atlantic form. There is an apparent bathymetric change in the size and age of fish, with younger animals occupying continental shelf depths and the older individuals residing at depths of the continental slope. At shallow depths the young are exposed to temperature fluctuations, whereas older animals along the slope are exposed to relatively stable temperatures. A hypothesis is proposed for describing the temporal and spatial paths by which young animals reach the mature or spawning portion of the population. (PDF file contains 38 pages.)
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222 p. : il.
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ENGLISH: A study has been made of the distributions of the 28 species of Chaetognatha in the waters off Peru and southern Ecuador, based primarily on data from oceanographic surveys carried out between 1958 and 1961 by the Inter-American Tropical Tuna Commission, Scripps Institution of Oceanography, and the Institute of Marine Resources Research and Consejo de Investigaciones Hidrobiologicas of Peru. Data from expeditions previous to 1958 also were used to aid in the interpretation of these materials. SPANISH: Se ha realizado un estudio de la distribución de las 28 especies de quetognatos en las aguas frente al Perú y al Ecuador meridional, basado principalmente sobre datos de los reconocimientos oceanográficos efectuados entre 1958 y 1961 por la Comisión Interamericana del Atún Tropical, la Institución Scripps de Oceanografía, y por el Instituto de Investigación de los Recursos Marinos y el Consejo de Investigaciones Hidrobiológicas del Perú. También se emplearon datos de las expediciones anteriores a 1958 para ayudar a la interpretación de este material. (PDF contains 102 pages)
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Many diseases are believed to be related to abnormal protein folding. In the first step of such pathogenic structural changes, misfolding occurs in regions important for the stability of the native structure. This destabilizes the normal protein conformation, while exposing the previously hidden aggregation-prone regions, leading to subsequent errors in the folding pathway. Sites involved in this first stage can be deemed switch regions of the protein, and can represent perfect binding targets for drugs to block the abnormal folding pathway and prevent pathogenic conformational changes. In this study, a prediction algorithm for the switch regions responsible for the start of pathogenic structural changes is introduced. With an accuracy of 94%, this algorithm can successfully find short segments covering sites significant in triggering conformational diseases (CDs) and is the first that can predict switch regions for various CDs. To illustrate its effectiveness in dealing with urgent public health problems, the reason of the increased pathogenicity of H5N1 influenza virus is analyzed; the mechanisms of the pandemic swine-origin 2009 A(H1N1) influenza virus in overcoming species barriers and in infecting large number of potential patients are also suggested. It is shown that the algorithm is a potential tool useful in the study of the pathology of CDs because: (1) it can identify the origin of pathogenic structural conversion with high sensitivity and specificity, and (2) it provides an ideal target for clinical treatment.