WorldWideScience

Sample records for census hard-to-see sea

  1. Harding County 2000 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  2. Indonesia in the South China Sea Dispute: Humble-Hard Power

    OpenAIRE

    Robertua, Verdinand; Sinaga, Obsatar

    2018-01-01

    This research discussed the opportunities for Indonesia to act as humble-hard power in South China Sea dispute. Permanent Court of Arbitration’s decision in July 2016 to give South China Sea based on UNCLOS’s regulation has provoked China’s objection. This research question is on how to understand the conception of humble-hard power and the possibility for Indonesia to be humble-hard power in the South China Sea dispute? This article borrowed the concept of humble-hard power from Adam Nieves ...

  3. Water mass census in the Nordic seas using climatological and observational data sets

    International Nuclear Information System (INIS)

    Piacsek, S.; Allard, R.; McClean, J.

    2008-01-01

    We have compared and evaluated the water mass census in the Greenland-Iceland-Norwegian (Gin) Sea area from climatologies, observational data sets and model output. The four climatologies evaluated were: the 1998 and 2001 versions of the World Ocean Atlas (WOA98, WOA01), and the United States Navy's GDEM90 (Generalized Digital Environmental Model) and MODAS01 (Modular Ocean Data Assimilation System) climatologies. Three observational data sets were examined: the multidecadal (1965-1995) set contained on the National Oceano- graphic Data Centre's (NODC) WOD98 (World Ocean Data) Cd-Rom, and two seasonal data sets extracted from observations taken on six cruises by the SACLANT Research Center (SACLANTCEN) of NATO/Italy between 1986-1989. The model data is extracted from a global model run at 1/3 degree resolution for the years 1983-1997, using the Pop (Parallel Ocean Program) model of the Los Alamos National Laboratory. The census computations focused on the Norwegian Sea, in the southern part of the Gin Sea, between 10 0 W-10 0 E and 60 0 N-70 0 N, especially for comparisons with the hydro casts and the model. Cases of such evaluation computations included: (a) short term comparisons with quasi-synoptic CTD surveys carried out over a 4-year period in the southeastern Gin Sea; (b) climatological comparisons utilizing all available casts from the WOD98 Cd-Rom, with four climatologies; and (c) a comparison between the WOA01 climatology and the Pop model output ending in 1997. In this region in the spring, the fraction of ocean water that has salinity above 34.85 is ∼94%, and that has temperatures above 0 0 C is ∼33%. Three principal water masses dominated the census: the Atlantic water A W, the deep water D W and an intermediate water mass defined as Lower Arctic Intermediate Water (LAIW). Besides these classes, both the climatologies and the observations exhibited the significant presence of deep water masses with T-S characteristics that do not fall into the named

  4. Harding County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  5. Harding County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  6. Harding County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  7. California sea otter (Enhydra lutris nereis) census results, Spring 2017

    Science.gov (United States)

    Tinker, M. Tim; Hatfield, Brian B.

    2017-09-29

    The 2017 census of southern sea otters (Enhydra lutris nereis) was conducted between late April and early July along the mainland coast of central California and in April at San Nicolas Island in southern California. The 3-year average of combined counts from the mainland range and San Nicolas Island was 3,186, down by 86 sea otters from the previous year. This is the second year that the official index has exceeded 3,090, the Endangered Species Act delisting threshold identified in the U.S. Fish and Wildlife Service’s Southern Sea Otter Recovery Plan (the threshold would need to be exceeded for 3 consecutive years before delisting consideration). The 5-year average trend in abundance, including both the mainland range and San Nicolas Island populations, remains positive at 2.3 percent per year. Continuing lack of growth in the range peripheries likely explains the cessation of range expansion.

  8. A longitudinal study of Steller sea lion natality rates in the Gulf of Alaska with comparisons to census data.

    Directory of Open Access Journals (Sweden)

    John M Maniscalco

    Full Text Available Steller sea lion (Eumetopias jubatus numbers in the Western Distinct Population Segment are beginning to recover following the dramatic decline that began in the 1970s and ended around the turn of the century. Low female reproductive rates (natality may have contributed to the decline and remain an issue of concern for this population. During the 2000s we found high natality among Steller sea lions in the Gulf of Alaska indicating a healthy population. This study extends these previous estimates over an additional three years and tests for interannual variations and long-term trends. We further examine the proportions of pups to adult females observed on the rookery and nearby haulouts during the birthing season to assess whether census data can be used to estimate natality. Open robust design multistate models were built and tested using Program MARK to estimate survival, resighting, and state transition probabilities in addition to other parameters dependent on whether or not a female gave birth in the previous year. Natality was estimated at 70% with some evidence of interannual variation but a long-term increasing or decreasing trend was not supported by the data. Bootstrap and regression comparisons of census data with natality estimates revealed no correlation between the two methods suggesting that census data are not an appropriate proxy for natality in this species. Longitudinal studies of individual animals are an appropriate method for estimating vital rates in species with variable detection over time such as the Steller sea lion. This work indicates that natality remains high in this region and is consistent with a population in recovery.

  9. Census Blockgroups for the United States Virgin Islands

    Data.gov (United States)

    U.S. Environmental Protection Agency — A census block group (BG) is a cluster of census blocks having the same first digit of their four-digit identifying numbers within a census tract. (See also Census...

  10. Harding County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  11. California sea lion and northern fur seal censuses conducted at Channel Islands, California by Alaska Fisheries Science Center from 1969-07-31 to 2015-08-08 (NCEI Accession 0145165)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Marine Mammal Laboratories' California Current Ecosystem Program (AFSC/NOAA) initiated and maintains census programs for California sea lions (Zalophus...

  12. Harding County 2010 Census Voting District County-based (VTD)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  13. Using WICID (Web-based Interface to Census Interaction Data in the Classroom

    Directory of Open Access Journals (Sweden)

    John Stillwell

    2006-12-01

    Full Text Available The Census of Population is one of the key sources of data for social science research in the UK. Many census results appear in published reports, but most data are available directly from the Office of National Statistics or from web sites offering extraction services for registered users. Many Geography students use information from the census to undertake projects and to complete dissertations, frequently when studying small geographical areas. It is important that students learn the skills for downloading census data and understand what shortcomings are associated with the data as well as knowing how to incorporate the data into GIS and to analyse it effectively. This paper focuses on how students at the University of Leeds are taught to use one particular product of the census, the Origin-Destination Statistics, that are available from a web-based interface known as WICID. The paper briefly outlines the context and characteristics of the data before explaining the rudiments of building queries and extracting data. A typical class assignment is presented to demonstrate how a student learns how to build queries using WICID before analysing the results or mapping the data using an independent GIS. Experience indicates that students need to think hard about their requirements before using WICID for project work.

  14. Please mind the gap - Visual census and cryptic biodiversity assessment at central Red Sea coral reefs.

    Science.gov (United States)

    Pearman, John K; Anlauf, Holger; Irigoien, Xabier; Carvalho, Susana

    2016-07-01

    Coral reefs harbor the most diverse assemblages in the ocean, however, a large proportion of the diversity is cryptic and, therefore, undetected by standard visual census techniques. Cryptic and exposed communities differ considerably in species composition and ecological function. This study compares three different coral reef assessment protocols: i) visual benthic reef surveys: ii) visual census of Autonomous Reef Monitoring Structures (ARMS) plates; and iii) metabarcoding techniques of the ARMS (including sessile, 106-500 μm and 500-2000 μm size fractions), that target the cryptic and exposed communities of three reefs in the central Red Sea. Visual census showed a dominance of Cnidaria (Anthozoa) and Rhodophyta on the reef substrate, while Porifera, Bryozoa and Rhodophyta were the most abundant groups on the ARMS plates. Metabarcoding, targeting the 18S rRNA gene, significantly increased estimates of the species diversity (p < 0.001); revealing that Annelida were generally the dominant phyla (in terms of reads) of all fractions and reefs. Furthermore, metabarcoding detected microbial eukaryotic groups such as Syndiniophyceae, Mamiellophyceae and Bacillariophyceae as relevant components of the sessile fraction. ANOSIM analysis showed that the three reef sites showed no differences based on the visual census data. Metabarcoding showed a higher sensitivity for identifying differences between reef communities at smaller geographic scales than standard visual census techniques as significant differences in the assemblages were observed amongst the reefs. Comparison of the techniques showed no similar patterns for the visual techniques while the metabarcoding of the ARMS showed similar patterns amongst fractions. Establishing ARMS as a standard tool in reef monitoring will not only advance our understanding of local processes and ecological community response to environmental changes, as different faunal components will provide complementary information but

  15. AFSC/NMML/CCEP: Channel Islands Pinniped Census

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Marine Mammal Laboratories' California Current Ecosystem Program (AFSC/NOAA) initiated and maintains census programs for California sea lions (Zalophus...

  16. Please mind the gap – Visual census and cryptic biodiversity assessment at central Red Sea coral reefs

    KAUST Repository

    Pearman, John K.

    2016-04-26

    Coral reefs harbor the most diverse assemblages in the ocean, however, a large proportion of the diversity is cryptic and, therefore, undetected by standard visual census techniques. Cryptic and exposed communities differ considerably in species composition and ecological function. This study compares three different coral reef assessment protocols: i) visual benthic reef surveys: ii) visual census of Autonomous Reef Monitoring Structures (ARMS) plates; and iii) metabarcoding techniques of the ARMS (including sessile, 106–500 μm and 500–2000 μm size fractions), that target the cryptic and exposed communities of three reefs in the central Red Sea. Visual census showed a dominance of Cnidaria (Anthozoa) and Rhodophyta on the reef substrate, while Porifera, Bryozoa and Rhodophyta were the most abundant groups on the ARMS plates. Metabarcoding, targeting the 18S rRNA gene, significantly increased estimates of the species diversity (p < 0.001); revealing that Annelida were generally the dominant phyla (in terms of reads) of all fractions and reefs. Furthermore, metabarcoding detected microbial eukaryotic groups such as Syndiniophyceae, Mamiellophyceae and Bacillariophyceae as relevant components of the sessile fraction. ANOSIM analysis showed that the three reef sites showed no differences based on the visual census data. Metabarcoding showed a higher sensitivity for identifying differences between reef communities at smaller geographic scales than standard visual census techniques as significant differences in the assemblages were observed amongst the reefs. Comparison of the techniques showed no similar patterns for the visual techniques while the metabarcoding of the ARMS showed similar patterns amongst fractions. Establishing ARMS as a standard tool in reef monitoring will not only advance our understanding of local processes and ecological community response to environmental changes, as different faunal components will provide complementary information but

  17. Please mind the gap – Visual census and cryptic biodiversity assessment at central Red Sea coral reefs

    KAUST Repository

    Pearman, John K.; Anlauf, Holger; Irigoien, Xabier; Carvalho, Susana

    2016-01-01

    Coral reefs harbor the most diverse assemblages in the ocean, however, a large proportion of the diversity is cryptic and, therefore, undetected by standard visual census techniques. Cryptic and exposed communities differ considerably in species composition and ecological function. This study compares three different coral reef assessment protocols: i) visual benthic reef surveys: ii) visual census of Autonomous Reef Monitoring Structures (ARMS) plates; and iii) metabarcoding techniques of the ARMS (including sessile, 106–500 μm and 500–2000 μm size fractions), that target the cryptic and exposed communities of three reefs in the central Red Sea. Visual census showed a dominance of Cnidaria (Anthozoa) and Rhodophyta on the reef substrate, while Porifera, Bryozoa and Rhodophyta were the most abundant groups on the ARMS plates. Metabarcoding, targeting the 18S rRNA gene, significantly increased estimates of the species diversity (p < 0.001); revealing that Annelida were generally the dominant phyla (in terms of reads) of all fractions and reefs. Furthermore, metabarcoding detected microbial eukaryotic groups such as Syndiniophyceae, Mamiellophyceae and Bacillariophyceae as relevant components of the sessile fraction. ANOSIM analysis showed that the three reef sites showed no differences based on the visual census data. Metabarcoding showed a higher sensitivity for identifying differences between reef communities at smaller geographic scales than standard visual census techniques as significant differences in the assemblages were observed amongst the reefs. Comparison of the techniques showed no similar patterns for the visual techniques while the metabarcoding of the ARMS showed similar patterns amongst fractions. Establishing ARMS as a standard tool in reef monitoring will not only advance our understanding of local processes and ecological community response to environmental changes, as different faunal components will provide complementary information but

  18. PCR múltiple para la detección de los genes sea, seb, sec, sed y see de Staphylococcus aureus: Caracterización de aislamientos de origen alimentario Multiplex PCR for the detection of sea, seb, sec, sed and see genes of Staphylococcus aureus: Characterization of isolates from food

    Directory of Open Access Journals (Sweden)

    E. A. Manfredi

    2010-09-01

    Full Text Available La presencia de Staphylococcus aureus en los alimentos representa un riesgo potencial para la salud pública; sus enterotoxinas son el principal factor de virulencia. La detección de las enterotoxinas de S. aureus puede realizarse por ELISA, aunque sólo es posible detectar el pool de enterotoxinas SEA, SEB, SEC, SED y SEE. Los objetivos del presente trabajo fueron optimizar dos técnicas de PCR múltiple para la detección de los genes sea, seb, sec, sed y see de S. aureus y caracterizar un conjunto de 115 aislamientos de Staphylococcus spp. asociados a intoxicaciones alimentarias provenientes de diferentes provincias de Argentina. La caracterización se realizó por pruebas bioquímicas, ELISA y PCR. Sesenta y ocho aislamientos (59,1% fueron positivos por ELISA, mientras que 61 (53% fueron positivos por PCR. De los aislamientos positivos por PCR, 34 (55,7% portaron el gen sea, 9 (14,8% el gen seb, 5 (8,1% el gen see, 4 (6,5% el gen sec, 6 (9,9% los genes sea y seb, 2 (3,3% los genes sea y sec, y 1 (1,7% los genes sea y sed. Este es el primer estudio de caracterización genotípica de aislamientos de S. aureus asociados con brotes de intoxicación alimentaria registrados en distintas provincias argentinas.The presence of Staphylococcus aureus in food represents a potential risk to public health, being its enterotoxins the major virulence factor. Enterotoxin detection can be determined by ELISA, but only for the pool of enterotoxins SEA, SEB, SEC, SED and SEE. The main aims of this study were to optimize two PCR techniques for detection of S. aureus sea, seb, sec, sed and see, and to characterize Staphylococcus spp. isolates associated with food intoxication. Two PCR techniques were optimized and 115 Staphylococcus spp. isolates from Ciudad Autónoma de Buenos Aires, and Buenos Aires, Córdoba, and Neuquén provinces were characterized. The characterization was performed by biochemical tests, ELISA and PCR. Sixty-eight isolates (59.1% were

  19. County Economic Census for Harding County, New Mexico, 2006se TIGER

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The 2006 Second Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage...

  20. Community-level destruction of hard corals by the sea urchin Diadema setosum.

    Science.gov (United States)

    Qiu, Jian-Wen; Lau, Dickey C C; Cheang, Chi-chiu; Chow, Wing-kuen

    2014-08-30

    Sea urchins are common herbivores and bioeroders of coral ecosystems, but rarely have they been reported as corallivores. We determined the spatial pattern of hard coral damage due to corallivory and bioerosion by the sea urchin Diadema setosum Leske in Hong Kong waters. Coral damage was common at the northeastern sites, with 23.7 - 90.3% colonies being either collapsed or severely damaged with >25% tissue loss. Many genera of corals were impacted by the sea urchin but the damage was most obvious for the structure forming genus Platygyra. The percentage of severely damaged and collapsed coral had significant positive correlation with the abundance of D. setosum, which ranged from 0.01 to 5.2 individuals per coral head or 0.1 - 21.1 individuals m(-2) across the study sites. Remedial management actions such as sea urchin removal are urgently needed to save these fringing coral communities. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Potential Uses of Administrative Records for Triple System Modeling for Estimation of Census Coverage Error in 2020

    Directory of Open Access Journals (Sweden)

    Griffin Richard A.

    2014-06-01

    Full Text Available Heterogeneity in capture probabilities is known to produce bias in the dual system estimates that have been used to estimate census coverage in U.S. Censuses since 1980. Triple system estimation using an administrative records list as a third source along with the census and coverage measurement survey has the potential to produce estimates with less bias. This is particularly important for hard-to-reach populations.

  2. Economic Census Designated Places for Harding County, New Mexico, 2006se TIGER

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The 2006 Second Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage...

  3. 2000 Census Designated Places for Harding County, New Mexico, 2006se TIGER

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The 2006 Second Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage...

  4. Characterisation of hard-substrate habitats in the German Bight (SE North Sea) from video observation

    Science.gov (United States)

    Michaelis, Rune; Mielck, Finn; Papenmeier, Svenja; Sander, Lasse; Hass, H. Christian

    2017-04-01

    Accumulations of cobble- to boulder-sized material provide important habitat functions for many plant and animal species in the marine environment. These include nursery for fish, anchor point for sessile marine species and feeding ground for many different organisms. Detailed knowledge of such reef habitats and their properties is thus crucial for the determination of marine protected areas and consequently also for the management of the North Sea. As stones and boulders usually cannot be recovered from the seafloor to be investigated in the lab most analyses have to rely on non-invasive methods like e.g. underwater video- and diver-observation data. Due to these limitations these habitats are not well understood with regard to their spatial distribution, temporal development and ecology. Furthermore, there is no standardized way to assess the structure and cover of biological communities on such hard-substrates, which discourages comparison of data between different regions. We here present a standardized workflow to analyse underwater videos of hard-substrate habitats recorded in different areas of the North Sea. The idea is to combine these detailed information with an area-wide habitat classification based on sidescan sonar data. For image-based evaluation, the videos are transformed into single frames, extracted every five seconds of video running time and imported into a self-developed image analysis script. This script allows the user to select and count different descriptors in numerical categories. These include amongst others the different size classes of stones, the areal coverage of sessile marine organisms, the surrounding sediment properties or the presence of grazers. These semi-quantitative data are subsequently statistically analysed to produce a set of standardized characteristics of the hard-substrate habitats and the controlling factors of their current state and development. Preliminary results show that boulders in sandy environments are

  5. 2017 Census Test

    Science.gov (United States)

    /Programs Latest Information Are you in a Survey? 2020 Census 2018 Census Test 2010 Census American Information Surveys/Programs Main Are you in a Survey? 2020 Census 2018 Census Test If you have received a Census. Latest Information The 2018 Census Test will take place in Pierce County, Wash.; Providence

  6. 2000 Census Unified School Districts for Harding County, New Mexico, 2006se TIGER

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The 2006 Second Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage...

  7. 2020 Census

    Science.gov (United States)

    What We Do Our Research Business Opportunities Census Careers Field Jobs by State Regional Offices /Programs Respond, Survey Data Newsroom News, Blogs About Us Our Research Search Population Economy Business ., area. 2017 Census Test The 2017 Census Test provided the opportunity to research new methods and

  8. Census Model Transition: Contributions to its Implementation in Portugal

    Directory of Open Access Journals (Sweden)

    Dias Carlos A.

    2016-03-01

    Full Text Available Given the high cost and complexity of traditional censuses, some countries have started to change the census process. Following this trend, Portugal is also evaluating a new census model as an alternative to an exhaustive collection of all statistical units. The main motivations for the implementation of this census model transition in Portugal are related to the decrease in statistical burden on citizens, improvements in the frequency of outputs, and the reduction of collection costs associated with census operations. This article seeks to systematise and critically review all alternatives to the traditional census methodologies, presenting their advantages and disadvantages and the countries that use them. As a result of the comparison, we conclude that the methods that best meet these objectives are those that use administrative data, either in whole or in part. We also present and discuss the results of an inventory and evaluation of administrative registers in Portugal with the potential to produce statistical census information.

  9. Kosovo 2011 Census: Contested Census within a Contested State

    Directory of Open Access Journals (Sweden)

    Mehmet Musaj

    2015-12-01

    Full Text Available This paper analyzes the census in Kosovo in 2011 with specific focus on the political implications and ethnic minority rights. A key conclusion is that this census highly influences public policy-making, and with regard to minority rights, the census data, in comparison to previous estimates and Kosovo Constitutional provisions, is not favorable to ethnic minorities. Expressing a lower number of minorities in total terms, the 2011 census explicitly reduced the representation of minorities at the central and local institutions, and consequently affected budget allocations. However, we must be aware that to some extent, because of the full boycott in the North by local Serbs, and the partial boycott in the South by the Roma and Serb communities, comparisons are limited and the data needs to be analyzed with care.

  10. Qualified Census Tracts

    Data.gov (United States)

    Department of Housing and Urban Development — A Qualified Census Tract (QCT) is any census tract (or equivalent geographic area defined by the Census Bureau) in which at least 50% of households have an income...

  11. Census Data

    Data.gov (United States)

    Department of Housing and Urban Development — The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic...

  12. Census Videos

    Science.gov (United States)

    Employment and Payroll Survey of Business Owners Work from Home Our statistics highlight trends in household statistics from multiple surveys. Data Tools & Apps Main American FactFinder Census Business Builder My Classification Codes (i.e., NAICS) Economic Census Economic Indicators Economic Studies Industry Statistics

  13. Census Photos

    Science.gov (United States)

    Employment and Payroll Survey of Business Owners Work from Home Our statistics highlight trends in household statistics from multiple surveys. Data Tools & Apps Main American FactFinder Census Business Builder My Classification Codes (i.e., NAICS) Economic Census Economic Indicators Economic Studies Industry Statistics

  14. Census.gov

    Science.gov (United States)

    Employment and Payroll Survey of Business Owners Work from Home Our statistics highlight trends in household statistics from multiple surveys. Data Tools & Apps Main American FactFinder Census Business Builder My Classification Codes (i.e., NAICS) Economic Census Economic Indicators Economic Studies Industry Statistics

  15. Census Audio

    Science.gov (United States)

    Employment and Payroll Survey of Business Owners Work from Home Our statistics highlight trends in household statistics from multiple surveys. Data Tools & Apps Main American FactFinder Census Business Builder My Classification Codes (i.e., NAICS) Economic Census Economic Indicators Economic Studies Industry Statistics

  16. Region 9 Census Block 2010

    Science.gov (United States)

    Geography:The TIGER Line Files are feature classes and related database files (.) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census Blocks are statistical areas bounded on all sides by visible features, such as streets, roads, streams, and railroad tracks, and/or by non visible boundaries such as city, town, township, and county limits, and short line-of-sight extensions of streets and roads. Census blocks are relatively small in area; for example, a block in a city bounded by streets. However, census blocks in remote areas are often large and irregular and may even be many square miles in area. A common misunderstanding is that data users think census blocks are used geographically to build all other census geographic areas, rather all other census geographic areas are updated and then used as the primary constraints, along with roads and water features, to delineate the tabulation blocks. As a result, all 2010 Census blocks nest within every other 2010 Census geographic area, so that Census Bureau statistical data can be tabulated at the block level and aggregated up t

  17. In Brief: Ocean life census

    Science.gov (United States)

    Showstack, Randy

    2010-10-01

    The Census of Marine Life, an international effort to assess the diversity, distribution, and abundance of marine life, issued a report on 23 September summarizing the decade­long project that the organization calls “the most comprehensive inventory of known marine life ever compiled.” The census has involved more than 2700 scientists and 670 participating institutions from more than 80 nations and territories. In addition, three books were released on 23 September that provide an overview of census insights and their implications, a summary of findings and discoveries by the 17 census projects, and portraits of about 100 species. “The Census of Marine Life is the book of oceans' nature,” census cofounder Jesse Ausubel wrote in a forward to one of the books. Ausubel is vice president of programs for the Alfred P. Sloan Foundation, which contributed $75 million to the $650 million census. “This book reports the known, unknown, and unknowable of the first Census of Marine Life. This book is about the richness of 3.5 billion years.” For more information, visit http://www.coml.org.

  18. Dense Matching Comparison Between Census and a Convolutional Neural Network Algorithm for Plant Reconstruction

    Science.gov (United States)

    Xia, Y.; Tian, J.; d'Angelo, P.; Reinartz, P.

    2018-05-01

    3D reconstruction of plants is hard to implement, as the complex leaf distribution highly increases the difficulty level in dense matching. Semi-Global Matching has been successfully applied to recover the depth information of a scene, but may perform variably when different matching cost algorithms are used. In this paper two matching cost computation algorithms, Census transform and an algorithm using a convolutional neural network, are tested for plant reconstruction based on Semi-Global Matching. High resolution close-range photogrammetric images from a handheld camera are used for the experiment. The disparity maps generated based on the two selected matching cost methods are comparable with acceptable quality, which shows the good performance of Census and the potential of neural networks to improve the dense matching.

  19. Census Infographics & Visualizations

    Science.gov (United States)

    Employment and Payroll Survey of Business Owners Work from Home Our statistics highlight trends in household statistics from multiple surveys. Data Tools & Apps Main American FactFinder Census Business Builder My statistics that relate to current events, observances, holidays, and anniversaries. Census Business Builder

  20. 500 Cities: Census Tract Boundaries

    Data.gov (United States)

    U.S. Department of Health & Human Services — This census tract shapefile for the 500 Cities project was extracted from the Census 2010 Tiger/Line database and modified to remove portions of census tracts that...

  1. Hard scattering and a diffractive trigger

    International Nuclear Information System (INIS)

    Berger, E.L.; Collins, J.C.; Soper, D.E.; Sterman, G.

    1986-02-01

    Conclusions concerning the properties of hard scattering in diffractively produced systems are summarized. One motivation for studying diffractive hard scattering is to investigate the interface between Regge theory and perturbative QCD. Another is to see whether diffractive triggering can result in an improvement in the signal-to-background ratio of measurements of production of very heavy quarks. 5 refs

  2. The Aggregate Dutch Historical Censuses

    NARCIS (Netherlands)

    Ashkpour, Ashkan; Meroño-Peñuela, Albert; Mandemakers, Kees

    2015-01-01

    Historical censuses have an enormous potential for research. In order to fully use this potential, harmonization of these censuses is essential. During the last decades, enormous efforts have been undertaken in digitizing the published aggregated outcomes of the Dutch historical censuses

  3. The Aggregate Dutch Historical Censuses

    NARCIS (Netherlands)

    A. Ashkpour (Ashkan); A. Meronõ-Peñuela (Albert); C.A. Mandemakers (Kees)

    2015-01-01

    textabstractHistorical censuses have an enormous potential for research. In order to fully use this potential, harmonization of these censuses is essential. During the last decades, enormous efforts have been undertaken in digitizing the published aggregated outcomes of the Dutch historical censuses

  4. 2000 Census 3-Digit ZIP Code Tabulation Areas (ZCTAs) for Harding County, New Mexico, 2006se TIGER

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The 2006 Second Edition TIGER/Line files are an extract of selected geographic and cartographic information from the Census TIGER database. The geographic coverage...

  5. Environment and feeding change the ability of heart rate to predict metabolism in resting Steller sea lions (Eumetopias jubatus).

    Science.gov (United States)

    Young, Beth L; Rosen, David A S; Haulena, Martin; Hindle, Allyson G; Trites, Andrew W

    2011-01-01

    The ability to use heart rate (fh) to predict oxygen consumption rates ([Formula: see text]) in Steller sea lions and other pinnipeds has been investigated in fasting animals. However, it is unknown whether established fh:[Formula: see text] relationships hold under more complex physiological situations, such as when animals are feeding or digesting. We assessed whether fh could accurately predict [Formula: see text] in trained Steller sea lions while fasting and after being fed. Using linear mixed-effects models, we derived unique equations to describe the fh:[Formula: see text] relationship for fasted sea lions resting on land and in water. Feeding did not significantly change the fh:[Formula: see text] relationship on land. However, Steller sea lions in water displayed a different fh:[Formula: see text] relationship after consuming a 4-kg meal compared with the fasting condition. Incorporating comparable published fh:[Formula: see text] data from Steller sea lions showed a distinct effect of feeding after a 6-kg meal. Ultimately, our study illustrated that both feeding and physical environment are statistically relevant when deriving [Formula: see text] from telemetered fh, but that only environment affects the practical ability to predict metabolism from fh. Updating current bioenergetic models with data gathered using these predictive fh:[Formula: see text] equations will yield more accurate estimates of metabolic rates of free-ranging Steller sea lions under a variety of physiological, behavioral, and environmental states.

  6. DENSE MATCHING COMPARISON BETWEEN CENSUS AND A CONVOLUTIONAL NEURAL NETWORK ALGORITHM FOR PLANT RECONSTRUCTION

    Directory of Open Access Journals (Sweden)

    Y. Xia

    2018-05-01

    Full Text Available 3D reconstruction of plants is hard to implement, as the complex leaf distribution highly increases the difficulty level in dense matching. Semi-Global Matching has been successfully applied to recover the depth information of a scene, but may perform variably when different matching cost algorithms are used. In this paper two matching cost computation algorithms, Census transform and an algorithm using a convolutional neural network, are tested for plant reconstruction based on Semi-Global Matching. High resolution close-range photogrammetric images from a handheld camera are used for the experiment. The disparity maps generated based on the two selected matching cost methods are comparable with acceptable quality, which shows the good performance of Census and the potential of neural networks to improve the dense matching.

  7. Time Series Analysis for Forecasting Hospital Census: Application to the Neonatal Intensive Care Unit.

    Science.gov (United States)

    Capan, Muge; Hoover, Stephen; Jackson, Eric V; Paul, David; Locke, Robert

    2016-01-01

    Accurate prediction of future patient census in hospital units is essential for patient safety, health outcomes, and resource planning. Forecasting census in the Neonatal Intensive Care Unit (NICU) is particularly challenging due to limited ability to control the census and clinical trajectories. The fixed average census approach, using average census from previous year, is a forecasting alternative used in clinical practice, but has limitations due to census variations. Our objectives are to: (i) analyze the daily NICU census at a single health care facility and develop census forecasting models, (ii) explore models with and without patient data characteristics obtained at the time of admission, and (iii) evaluate accuracy of the models compared with the fixed average census approach. We used five years of retrospective daily NICU census data for model development (January 2008 - December 2012, N=1827 observations) and one year of data for validation (January - December 2013, N=365 observations). Best-fitting models of ARIMA and linear regression were applied to various 7-day prediction periods and compared using error statistics. The census showed a slightly increasing linear trend. Best fitting models included a non-seasonal model, ARIMA(1,0,0), seasonal ARIMA models, ARIMA(1,0,0)x(1,1,2)7 and ARIMA(2,1,4)x(1,1,2)14, as well as a seasonal linear regression model. Proposed forecasting models resulted on average in 36.49% improvement in forecasting accuracy compared with the fixed average census approach. Time series models provide higher prediction accuracy under different census conditions compared with the fixed average census approach. Presented methodology is easily applicable in clinical practice, can be generalized to other care settings, support short- and long-term census forecasting, and inform staff resource planning.

  8. [The need to develop demographic census systems for Latin America].

    Science.gov (United States)

    Silva, A

    1987-01-01

    The author presents the case for developing new software packages specifically designed to process population census information for Latin America. The focus is on the problems faced by developing countries in handling vast amounts of data in an efficient way. First, the basic methods of census data processing are discussed, then brief descriptions of some of the available software are included. Finally, ways in which data processing programs could be geared toward and utilized for improving the accuracy of Latin American censuses in the 1990s are proposed.

  9. Special Census Program

    Science.gov (United States)

    Employment and Payroll Survey of Business Owners Work from Home Our statistics highlight trends in household statistics from multiple surveys. Data Tools & Apps Main American FactFinder Census Business Builder My Classification Codes (i.e., NAICS) Economic Census Economic Indicators Economic Studies Industry Statistics

  10. Colfax County 2000 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  11. Otero County 2000 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  12. Socorro County 2000 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  13. Catron County 2000 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  14. Sierra County 2000 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  15. Curry County 2000 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  16. Bernalillo County 2000 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  17. Eddy County 2000 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  18. America's Churning Races: Race and Ethnicity Response Changes Between Census 2000 and the 2010 Census.

    Science.gov (United States)

    Liebler, Carolyn A; Porter, Sonya R; Fernandez, Leticia E; Noon, James M; Ennis, Sharon R

    2017-02-01

    A person's racial or ethnic self-identification can change over time and across contexts, which is a component of population change not usually considered in studies that use race and ethnicity as variables. To facilitate incorporation of this aspect of population change, we show patterns and directions of individual-level race and Hispanic response change throughout the United States and among all federally recognized race/ethnic groups. We use internal U.S. Census Bureau data from the 2000 and 2010 censuses in which responses have been linked at the individual level (N = 162 million). Approximately 9.8 million people (6.1 %) in our data have a different race and/or Hispanic-origin response in 2010 than they did in 2000. Race response change was especially common among those reported as American Indian, Alaska Native, Native Hawaiian, Other Pacific Islander, in a multiple-race response group, or Hispanic. People reported as non-Hispanic white, black, or Asian in 2000 usually had the same response in 2010 (3 %, 6 %, and 9 % of responses changed, respectively). Hispanic/non-Hispanic ethnicity responses were also usually consistent (13 % and 1 %, respectively, changed). We found a variety of response change patterns, which we detail. In many race/Hispanic response groups, we see population churn in the form of large countervailing flows of response changes that are hidden in cross-sectional data. We find that response changes happen across ages, sexes, regions, and response modes, with interesting variation across racial/ethnic categories. Researchers should address the implications of race and Hispanic-origin response change when designing analyses and interpreting results.

  19. Use of Proton SEE Data as a Proxy for Bounding Heavy-Ion SEE Susceptibility

    Science.gov (United States)

    Ladbury, Raymond L.; Lauenstein, Jean-Marie; Hayes, Kathryn P.

    2015-01-01

    Although heavy-ion single-event effects (SEE) pose serious threats to semiconductor devices in space, many missions face difficulties testing such devices at heavy-ion accelerators. Low-cost missions often find such testing too costly. Even well funded missions face issues testing commercial off the shelf (COTS) due to packaging and integration. Some missions wish to fly COTS systems with little insight into their components. Heavy-ion testing such parts and systems requires access to expensive and hard-to-access ultra-high energy ion accelerators, or significant system modification. To avoid these problems, some have proposed using recoil ions from high-energy protons as a proxy to bound heavy-ion SEE rates.

  20. Census County Subdivisions for the United States Virgin Islands (CENSUS.COUNTY_SUBDIV_USVI)

    Data.gov (United States)

    U.S. Environmental Protection Agency — County subdivisions are the primary divisions of counties and statistically equivalent entities for the reporting of decennial census data. They include census...

  1. 2015 Census Blocks Geodatabase

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The 2015 TIGER Geodatabases are extracts of selected nation based and state based geographic and cartographic information from the U.S. Census Bureau's Master...

  2. Challenges to the census: international trends and a need to consider public health benefits.

    Science.gov (United States)

    Wilson, R T; Hasanali, S H; Sheikh, M; Cramer, S; Weinberg, G; Firth, A; Weiss, S H; Soskolne, C L

    2017-10-01

    The Canadian government decision to cancel the mandatory long-form census in 2010 (subsequently restored in 2015), along with similar discussions in the United Kingdom (UK) and the United States of America (USA), have brought the purpose and use of census data into focus for epidemiologists and public health professionals. Policy decision-makers should be well-versed in the public health importance of accurate and reliable census data for emergency preparedness planning, controlling disease outbreaks, and for addressing health concerns among vulnerable populations including the elderly, low-income, racial/ethnic minorities, and special residential groups (e.g., nursing homes). Valid census information is critical to ensure that policy makers and public health practitioners have the evidence needed to: (1) establish incidence rates, mortality rates, and prevalence for the full characterization of emerging health issues; (2) address disparities in health care, prevention strategies and health outcomes among vulnerable populations; and (3) plan and effectively respond in times of disaster and emergency. At a time when budget and sample size cuts have been implemented in the UK, a voluntary census is being debated in the US. In Canada, elimination of the mandatory long-form census in 2011 resulted in unreliable population enumeration, as well as a substantial waste of money and resources for taxpayers, businesses and communities. The purpose of this article is to provide a brief overview of recent international trends and to review the foundational role of the census in public health management and planning using historical and current examples of environmental contamination, cancer clusters and emerging infections. Citing a general absence of public health applications of the census in cost-benefit analyses, we call on policy makers to consider its application to emergency preparedness, outbreak response, and chronic disease prevention efforts. At the same time, we

  3. Hard and Soft Governance: The Journey from Transnational Agencies to School Leadership

    Science.gov (United States)

    Moos, Lejf

    2009-01-01

    The governance and leadership at transnational, national and school level seem to be converging into a number of isomorphic forms as we see a tendency towards substituting "hard" forms of governance, that are legally binding, with "soft" forms based on persuasion and advice. This article analyses and discusses governance forms…

  4. Santa Fe County 2000 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  5. McKinley County 2000 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  6. Sandoval County 2000 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  7. Lea County 2000 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  8. Bernalillo County 2000 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  9. Taos County 2000 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  10. 2000 Census Urban Areas and Clusters

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  11. San Miguel County 2000 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  12. Catron County 2000 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  13. Santa Fe County 2000 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  14. Los Alamos County 2000 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  15. Otero County 2000 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  16. Census Business Builder (CBB)

    Science.gov (United States)

    Employment and Payroll Survey of Business Owners Work from Home Our statistics highlight trends in household statistics from multiple surveys. Data Tools & Apps Main American FactFinder Census Business Builder My Classification Codes (i.e., NAICS) Economic Census Economic Indicators Economic Studies Industry Statistics

  17. Use of aerial photograph to enhance dog population census in Ilorin ...

    African Journals Online (AJOL)

    The ground survey method for dog population census is considered to be prone to error in enumeration. As a result, use of aerial photography has been suggested as capable of enhancing ground survey methods for more accurate results. Dog population census was carried out within llorin city in October 2010 using direct ...

  18. Radiation hardness of undoped BGO crystals

    International Nuclear Information System (INIS)

    Sahu, S.K.; Peng, K.C.; Huang, H.C.; Wang, C.H.; Chang, Y.H.; Hou, W.S.; Ueno, K.; Chou, F.I.; Wei, Y.Y.

    1997-01-01

    We measured the radiation hardness of undoped BGO crystals from two different manufacturers. Such crystals are proposed to be used in a small-angle calorimeter of the BELLE detector of the KEK B-factory. Transparency and scintillation light output of the crystals were monitored to see the effect of radiation damage. The crystals show considerable radiation hardness up to 10.2 Mrad equivalent dose, which is much higher than the maximum expected dosage of 500 krad per year of running at BELLE. (orig.)

  19. CDC WONDER: Population (from Census)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Population online databases contain data from the US Census Bureau. The Census Estimates online database contains contains county-level population counts for...

  20. CDC WONDER: Population (from Census)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Population online databases contain data from the US Census Bureau. The Census Estimates online database contains county-level population counts for years 1970 -...

  1. 77 FR 50082 - Notice of Opportunity To Submit Content Request for the 2013 Census of Aquaculture

    Science.gov (United States)

    2012-08-20

    ... Content Request for the 2013 Census of Aquaculture AGENCY: National Agricultural Statistics Service... requests for the 2013 Census of Aquaculture. This census is required by law under the ``Census of... results of the 2005 Census of Aquaculture were released in October 2006. For more information, visit...

  2. New Mexico, 2010 Census Census Tract State-based

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  3. Ethnicity in censuses: Changeable and inconstant category

    Directory of Open Access Journals (Sweden)

    Mrđen Snježana

    2002-01-01

    Full Text Available The issue of ethnicity was set in all censuses of SFRY, as well as in the first censuses in countries that were created after its disintegration. When analyzing the censuses it can be concluded that it is a changeable category. Not only was the manner of forming the question in censuses changing, but also the number of categories of nationality and their order in published census' results. It depended on state policy and the political situation preceding the censuses. Since the answer on the issues of ethnicity is a subjective criterion, and it was written down according to the freely declared statement of the residents, guaranteed by the Constitution. It has often happened that same individuals have declared themselves differently from one census to another, and also some categories of ethnicity have vanished and some others were created. Although in SFRY nations and ethnicities were equal, still indirectly in published results, existence of these two categories was indicated. But, in newly created countries, the manner of forming the question of ethnicity was changed, their number and order were also changed and the notion of 'minority' was again introduced, indicating, beyond doubt, a different status of nationality (except the majority from the one in the former Yugoslavia.

  4. De Baca County 2000 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  5. Rio Arriba County 2000 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  6. Is there a see-saw over an ice-free Arctic Ocean?

    Science.gov (United States)

    Stendel, Martin; Yang, Shuting; Langen, Peter; Rodehacke, Christian; Mottram, Ruth; Hesselbjerg Christensen, Jens

    2017-04-01

    The "see-saw" in winter temperatures between western Greenland and the Canadian Arctic on one side and northern Europe on the other has been described by Loewe already in 1937, but actually this behaviour was at least known since the Danish colonization of Greenland in the early 18th century. The see-saw is associated with pressure anomalies not only near the region of interest, but as remote as the Mediterranean and the North Pacific. Recent research has pointed out the role of sea ice in maintaining the see-saw in either its warm or its cold phase over extended periods, which strongly affects European winter temperatures. What would happen to the seesaw if Arctic sea ice were to disappear suddenly? In the framework of the FP7-funded project ice2ice, we try to answer this and related questions. We have conducted a very long global simulation with a global climate model interactively coupled to a Greenland ice sheet component, covering the period 1850-3250 at a horizontal resolution of approximately 125 km. Up to 2005, the forcing is from observed greenhouse gas concentrations, and from 2006 onward it follows the extended RCP8.5 scenario, in which greenhouse gas concentrations continue to increase and eventually level out around 2250. With such a strong forcing, all Arctic sea ice has completely disappeared by roughly the same time, and the surface mass balance of the Greenland Ice Sheet becomes strongly negative. We investigate how the see-saw behaves in such an ice-free world and which implications circulation changes have in the Arctic and over Europe. To further elucidate the role of sea ice distribution on the atmospheric flow and the role of surface fluxes in maintaining the Greenland-European see-saw, we intend at a later time to expand our analysis to include a contrasting simulation with both western Greenland and northern Europe covered by ice during the Last Glacier Maximum.

  7. 77 FR 39678 - Census Bureau

    Science.gov (United States)

    2012-07-05

    ... and small businesses. While these Exchanges are still in development and states have broad flexibility... DEPARTMENT OF COMMERCE Census Bureau Proposed Information Collection; Comment Request; 2013 Current Population Survey Annual Social and Economic Supplement Content Test AGENCY: U.S. Census Bureau...

  8. Using Remotely Sensed Data to Automate and Improve Census Bureau Update Activities

    Science.gov (United States)

    Desch, A., IV

    2017-12-01

    Location of established and new housing structures is fundamental in the Census Bureau's planning and execution of each decennial census. Past Census address list compilation and update programs have involved sending more than 100,000 workers into the field to find and verify housing units. The 2020 Census program has introduced an imagery based In-Office Address Canvassing Interactive Review (IOAC-IR) program in an attempt to reduce the in-field workload. The human analyst driven, aerial image based IOAC-IR operation has proven to be a cost effective and accurate substitute for a large portion of the expensive in-field address canvassing operations. However, the IOAC-IR still required more than a year to complete and over 100 full-time dedicated employees. Much of the basic image analysis work done in IOAC-IR can be handled with established remote sensing and computer vision techniques. The experience gained from the Interactive Review phase of In-Office Address Canvassing has led to the development of a prototype geo-processing tool to automate much of this process for future and ongoing Address Canvassing operations. This prototype utilizes high-resolution aerial imagery and LiDAR to identify structures and compare their location to existing Census geographic information. In this presentation, we report on the comparison of this exploratory system's results to the human based IOAC-IR. The experimental image and LiDAR based change detection approach has itself led to very promising follow-on experiments utilizing very current, high repeat datasets and scalable cloud computing. We will discuss how these new techniques can be used to both aid the US Census Bureau meet its goals of identify all the housing units in the US as well as aid developing countries better identify where there population is currently distributed.

  9. Comparison of 2010 Census Nonresponse Follow-Up Proxy Responses with Administrative Records Using Census Coverage Measurement Results

    Directory of Open Access Journals (Sweden)

    Mulry Mary H.

    2017-06-01

    Full Text Available The U.S. Census Bureau is currently conducting research on ways to use administrative records to reduce the cost and improve the quality of the 2020 Census Nonresponse Followup (NRFU at addresses that do not self-respond electronically or by mail. Previously, when a NRFU enumerator was unable to contact residents at an address, he/she found a knowledgeable person, such as a neighbor or apartment manager, who could provide the census information for the residents. This was called a proxy response. The Census Bureau’s recent advances in merging federal and third-party databases raise the question: Are proxy responses for NRFU addresses more accurate than the administrative records available for the housing unit? Our study attempts to answer this question by comparing the quality of proxy responses and the administrative records for those housing units in the same timeframe using the results of 2010 Census Coverage Measurement (CCM Program. The assessment of the quality of the proxy responses and the administrative records in the CCM sample of block clusters takes advantage of the extensive fieldwork, processing, and clerical matching conducted for the CCM.

  10. Results of the January 2017 waterbird census in Slovenia

    Directory of Open Access Journals (Sweden)

    Božič Luka

    2017-12-01

    Full Text Available In 2017, the International Waterbird Census (IWC was carried out in Slovenia on January 14 and 15. Waterbirds were counted on all larger rivers, along the entire Slovenian Coastland and on most of the major standing waters in the country. During the census, in which 235 observers took part, 413 sections of the rivers and coastal sea with a total length of 1,427 km and 200 other localities (164 standing waters and 36 streams were surveyed. The census was characterized by harsh winter conditions and high proportion of frozen water bodies. Altogether, 51,790 waterbirds of 61 species were counted. Thus, the number of waterbirds and the number of species recorded were close to the 21-year average. The highest numbers of waterbirds were counted in the Drava count area, i.e. 20,064 individuals (38.7% of all waterbirds in Slovenia. By far the most numerous species was Mallard Anas platyrhynchos (46.1% of all waterbirds, followed by Coot Fulica atra (6.8% of all waterbirds, Cormorant Phalacrocorax carbo (5.9% of all waterbirds, Black-headed Gull Chroicocephalus ridibundus (5.7% of all waterbirds and Mute Swan Cygnus olor (3.9% of all waterbirds. The number of 1,000 counted individuals was also surpassed by Yellow-legged Gull Larus michahellis, Teal An. crecca, Tufted Duck Aythya fuligula, White-fronted Goose Anser albifrons, Pygmy Cormorant P. pygmeus and Grey Heron Ardea cinerea. Among the rarer recorded species, the Red-breasted Goose Branta ruficollis (registered for the first time during the January Waterbird Censuses and only for the third time ever in Slovenia and Barnacle Goose Branta leucopsis (the first probable A category individual for IWC and Slovenia deserve special mention. Numbers of the following species were the highest so far recorded during the IWC: Mandarin Duck Aix galericulata (together with 2006 and 2012, Pintail An. acuta, Ferruginous Duck Ay. nyroca, Long-tailed Duck Clangula hyemalis (together with 2003, Goosander Mergus

  11. Countermeasure Study on Deep-sea Oil Exploitation in the South China Sea——A Comparison between Deep-sea Oil Exploitation in the South China Sea and the Gulf of Mexico

    Science.gov (United States)

    Zhao, Hui; Qiu, Weiting; Qu, Weilu

    2018-02-01

    The unpromising situation of terrestrial oil resources makes the deep-sea oil industry become an important development strategy. The South China Sea has a vast sea area with a wide distribution of oil and gas resources, but there is a phenomenon that exploration and census rates and oil exploitation are low. In order to solve the above problems, this article analyzes the geology, oil and gas exploration and exploration equipment in the South China Sea and the Gulf of Mexico. Comparing the political environment of China and the United States energy industry and the economic environment of oil companies, this article points out China’s deep-sea oil exploration and mining problems that may exist. Finally, the feasibility of oil exploration and exploitation in the South China Sea is put forward, which will provide reference to improve the conditions of oil exploration in the South China Sea and promoting the stable development of China’s oil industry.

  12. The distribution patterns of Red Sea Chaetodontid assemblages

    NARCIS (Netherlands)

    Zekeria, ZA; Afeworki, Y; Videler, JJ; Zekeria, A.

    2005-01-01

    1. The occurrence and abundance of butterflyfishes were investigated in northern, central and southern areas of the Eritrean Red Sea coast. Visual census was used to estimate the presence and abundance of the species along 100-metre long transects. 2. The assemblages of buttertlyfishes from the

  13. Census Careers

    Science.gov (United States)

    Indicators Economic Studies Industry Statistics Portal Other Economic Programs Business is a large part of Classification Codes (i.e., NAICS) Economic Census Economic Indicators Economic Studies Industry Statistics Portal Other Economic Programs Business Latest Information Business Characteristics Classification Codes

  14. 39th annual Reed rig census

    International Nuclear Information System (INIS)

    Crowhurst, M.E.; Fitts, R.L.

    1991-01-01

    This paper reports on cutbacks in U.S. exploration and development drilling during the first half of 1991 which squeezed most of the optimism out of the drilling industry. Just how rough the year has been is underscored by the results of this year's rig census. The number of rotary rigs available for U.S. drilling declined by only 69 units (3%) during the past 12 months. But despite those withdrawals from competition, only 66% of the remaining rigs were working at the time the census was taken. Results of the 1991 census contrasted sharply with the stability and optimism that seemed apparent a year ago when 72% of the available rig fleet met the census definition of active. At that time, the mini-boom in horizontal drilling coupled with tax-credit- driven gas drilling led to a relatively high rig utilization rate and suggested that rig supply and demand might be close to an economically acceptable balance. However, it quickly became apparent in early 1991 that industry optimism was unjustified. Horizontal drilling began to drop and the lowest natural gas prices in 12 years triggered rapid declines in gas drilling. Although oil prices have been relatively stable and above $18 per bbl since January 1989, most major operators have concluded that a better return on investment can be had outside the U.S. and have drastically cut their domestic drilling budgets. These factors, combined with softened energy demand from the worldwide recession, further slowed U.S. drilling. The long awaited balance between rig supply and demand has seemingly slipped away. The 1991 Reed rig census describes an industry facing several more rough years. Details of this year's census include: The available U.S. fleet now stands at 2,251 rigs, down by 69 from the 2,320-unit total in 1990, and the lowest since 1976. Rigs meeting the census definition of active numbered 1,485, down 192 (11.4%) from the 1,677 active rigs counted a year earlier

  15. Structural qualia: a solution to the hard problem of consciousness.

    Science.gov (United States)

    Loorits, Kristjan

    2014-01-01

    The hard problem of consciousness has been often claimed to be unsolvable by the methods of traditional empirical sciences. It has been argued that all the objects of empirical sciences can be fully analyzed in structural terms but that consciousness is (or has) something over and above its structure. However, modern neuroscience has introduced a theoretical framework in which also the apparently non-structural aspects of consciousness, namely the so called qualia or qualitative properties, can be analyzed in structural terms. That framework allows us to see qualia as something compositional with internal structures that fully determine their qualitative nature. Moreover, those internal structures can be identified which certain neural patterns. Thus consciousness as a whole can be seen as a complex neural pattern that misperceives some of its own highly complex structural properties as monadic and qualitative. Such neural pattern is analyzable in fully structural terms and thereby the hard problem is solved.

  16. Structural qualia: a solution to the hard problem of consciousness

    Directory of Open Access Journals (Sweden)

    Kristjan eLoorits

    2014-03-01

    Full Text Available The hard problem of consciousness has been often claimed to be unsolvable by the methods of traditional empirical sciences. It has been argued that all the objects of empirical sciences can be fully analyzed in structural terms but that consciousness is (or has something over and above its structure. However, modern neuroscience has introduced a theoretical framework in which also the apparently non-structural aspects of consciousness, namely the so called qualia or qualitative properties, can be analyzed in structural terms. That framework allows us to see qualia as something compositional with internal structures that fully determine their qualitative nature. Moreover, those internal structures can be identified which certain neural patterns. Thus consciousness as a whole can be seen as a complex neural pattern that misperceives some of its own highly complex structural properties as monadic and qualitative. Such neural pattern is analyzable in fully structural terms and thereby the hard problem is solved.

  17. South China sea off Viet Nam to see more exploration

    International Nuclear Information System (INIS)

    Anon.

    1992-01-01

    British and Japanese operators are posed for exploration campaigns off southern Viet Nam. This paper reports that a 50-50 partnership of Lasmo International Ltd., London, and C. Itoh Exploration Co. of Japan signed a heads of agreement covering Block 04-2, and AEDC Vietnam Oil Development Co. and Teikoku Oil Co. acquired Block 05-3 under a production sharing contract. AEDC is a unit of AOC Energy Development Co., a subsidiary of Arabian Oil Co. (AOC) of Japan. Both tracts are in the Con Son basin in the South China Sea. Site is 15 km north of 500 million bbl Dai Hung (Big Bear) oil field for which state owned Petrovietnam is evaluating bids to place on production. A unit of the Royal Dutch/shell Group acquired a west offset, Block 10, early this year. The Lasmo-C. Itoh acreage is among five blocks offered in Vietnam's second round of offshore licensing. All are in the area that once was reserved entirely for Vietsovpetro, a partnership of Petrovietnam and the former Soviet Union

  18. The use of census migration data to approximate human movement patterns across temporal scales.

    Science.gov (United States)

    Wesolowski, Amy; Buckee, Caroline O; Pindolia, Deepa K; Eagle, Nathan; Smith, David L; Garcia, Andres J; Tatem, Andrew J

    2013-01-01

    Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data.

  19. Census 2000 Places (cen00pl02)

    Data.gov (United States)

    California Natural Resource Agency — Census 2000 Place Names provides a seamless statewide GIS layer of places, including census designated places (CDP), consolidated cities, and incorporated places,...

  20. 75 FR 17835 - Census Day, 2010

    Science.gov (United States)

    2010-04-07

    ... Since our Nation's earliest days, the census has played an important role in identifying where resources... receive adequate funding for schools, hospitals, senior centers, and other public works projects. The 2010 Census will also aid employers in selecting locations for new factories and businesses as our economy...

  1. Standard hardness conversion tables for metals relationship among brinell hardness, vickers hardness, rockwell hardness, superficial hardness, knoop hardness, and scleroscope hardness

    CERN Document Server

    American Society for Testing and Materials. Philadelphia

    2007-01-01

    1.1 Conversion Table 1 presents data in the Rockwell C hardness range on the relationship among Brinell hardness, Vickers hardness, Rockwell hardness, Rockwell superficial hardness, Knoop hardness, and Scleroscope hardness of non-austenitic steels including carbon, alloy, and tool steels in the as-forged, annealed, normalized, and quenched and tempered conditions provided that they are homogeneous. 1.2 Conversion Table 2 presents data in the Rockwell B hardness range on the relationship among Brinell hardness, Vickers hardness, Rockwell hardness, Rockwell superficial hardness, Knoop hardness, and Scleroscope hardness of non-austenitic steels including carbon, alloy, and tool steels in the as-forged, annealed, normalized, and quenched and tempered conditions provided that they are homogeneous. 1.3 Conversion Table 3 presents data on the relationship among Brinell hardness, Vickers hardness, Rockwell hardness, Rockwell superficial hardness, and Knoop hardness of nickel and high-nickel alloys (nickel content o...

  2. The use of census migration data to approximate human movement patterns across temporal scales.

    Directory of Open Access Journals (Sweden)

    Amy Wesolowski

    Full Text Available Human movement plays a key role in economies and development, the delivery of services, and the spread of infectious diseases. However, it remains poorly quantified partly because reliable data are often lacking, particularly for low-income countries. The most widely available are migration data from human population censuses, which provide valuable information on relatively long timescale relocations across countries, but do not capture the shorter-scale patterns, trips less than a year, that make up the bulk of human movement. Census-derived migration data may provide valuable proxies for shorter-term movements however, as substantial migration between regions can be indicative of well connected places exhibiting high levels of movement at finer time scales, but this has never been examined in detail. Here, an extensive mobile phone usage data set for Kenya was processed to extract movements between counties in 2009 on weekly, monthly, and annual time scales and compared to data on change in residence from the national census conducted during the same time period. We find that the relative ordering across Kenyan counties for incoming, outgoing and between-county movements shows strong correlations. Moreover, the distributions of trip durations from both sources of data are similar, and a spatial interaction model fit to the data reveals the relationships of different parameters over a range of movement time scales. Significant relationships between census migration data and fine temporal scale movement patterns exist, and results suggest that census data can be used to approximate certain features of movement patterns across multiple temporal scales, extending the utility of census-derived migration data.

  3. Hard-bottom bathyal habitats and keystone epibenthic species on Le Danois Bank (Cantabrian Sea)

    Science.gov (United States)

    Sánchez, F.; Rodríguez Basalo, A.; García-Alegre, A.; Gómez-Ballesteros, M.

    2017-12-01

    "El Cachucho" Marine Protected Area (MPA), which comprises Le Danois Bank and its intraslope basin, was included during 2008 in the Nature 2000 network mainly because of the presence of the habitat "1170 Reefs" according to the EU Habitat Directive. To review the effectiveness of existing management measures, several activities aimed at characterizing the most structurally complex hard-bottom habitats were planned and carried out during the ESMAREC 0514 survey. For identification of these habitats, several transects using the photogrammetric towed sled Politolana were carried out on Le Danois Bank, in the depth range between 427 and 1379 m, searching for the sea beds with higher values of slope and backscatter. Photogrammetric techniques were used for image scaling, so we could determine the surface areas of different substrata types (facies) and their species densities. A total area of 28,762 m2 was analyzed in the still images of 23 transects, verifying that 85% of the substrata of our study area are occupied by 4 different facies: Bedrock, bedrock with mixed sediments, mixed sediments with pebbles and boulders, and mixed sediments. Acoustic data and ground-truth visual data were combined to evaluate distinctive benthic scenarios. The relative abundances of the 123 epibenthic species identified by image analyses show that the most abundant are sponges (29%), cnidarians (26%), crustaceans (26%) and echinoderms (14%), i.e. mostly sessile species or those with low mobility. The keystone species of the "1170 Reefs" habitat are 3 cnidarians: Callogorgia verticillata, Paramuricea cf. placomus and Dendrophyllia cornigera, and 3 sponges, Asconema setubalense, Geodia msp.1 and Phakellia robusta. Eight new habitats (biotopes) have been identified on Le Danois Bank, six of which occur on the hard bottoms, with depth, substratum, BPI (Bathymetric Position Index) and slope as determining environmental variables that explain their spatial distributions.

  4. Census in North Vietnam

    National Research Council Canada - National Science Library

    1960-01-01

    This population census decree aims at collecting the most fundamental and accurate data on the population situation of North Vietnam to lay the foundation for all plans and public administration policies...

  5. New Mexico Census Tracts, Total Population (2010)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article...

  6. Deep-sea disposal: Protecting fish and man

    International Nuclear Information System (INIS)

    Hagen, A.

    1988-01-01

    The definition of radioactive waste unsuitable for dumping at sea is based on the protection of man. See IAEA Safety Series No. 78. The development of criteria for assessing the impact on deep sea marine organisms at the population level has been attempted in a report recently published by the IAEA. See IAEA Technical Reports Series, No. 228 (1988). The report indicates that certain radionuclides may give rise to high dose rates to marine organisms if dumping is carried out with the assumptions of instantaneous release at the sea floor and dumping over long periods of time. In the report, a hypothetical dose rate to molluscs from zinc-65, which poses no significant harm to man, has the potential for giving high doses to bottom-dwelling molluscs

  7. 15 CFR 50.10 - Fee structure for special population censuses.

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Fee structure for special population... § 50.10 Fee structure for special population censuses. The Bureau of the Census is authorized to conduct special population censuses at the request of and at the expense of the community concerned. To...

  8. Crab Nebula Variations in Hard X-rays

    Science.gov (United States)

    Wilson-Hodge, Colleen A.

    2012-01-01

    The Crab Nebula was surprisingly variable from 2001-2010, with less variability before 2001 and since mid-2010. We presented evidence for spectral softening from RXTE, Swift/BAT, and Fermi GBM during the mid-2008-2010 flux decline. We see no clear connections between the hard X-ray variations and the GeV flares

  9. Providing Access to Census-based Interaction Data in the UK: That's WICID!

    Directory of Open Access Journals (Sweden)

    John Stillwell

    2006-08-01

    Full Text Available The Census Interaction Data Service (CIDS is funded by the Economic and Social Research Council in the UK to provide access for social science researchers and students to the detailed migration and journey-to-work statistics that are collected by the national statistical agencies. These interaction data sets are known collectively as the Special Migration Statistics (SMS and the Special Workplace Statistics (SWS. This paper outlines how problems of user access to these data have been tackled through the development of a web-based system known as WICID (Web-based Interface to Census Interaction Data. The paper illustrates various interface features including some of the query building facilities that enable users to extract counts of flows of particular groups of individuals between selected origin and destination areas. New tools are outlined for assisting area selection using digital maps of census geographies, for planning output and for adding value to the data through analysis. Mapping of flows of migrants between London boroughs and the rest of the UK demonstrates the value of the data. The paper begins with a summary of the data sets that are contained within the system and an outline of the system architecture.

  10. 15 CFR 917.11 - Guidelines for Sea Grant Fellowships.

    Science.gov (United States)

    2010-01-01

    ... percent matching funds from non-Federal sources to which all Matched Funding Program projects are subject... NATIONAL SEA GRANT PROGRAM FUNDING REGULATIONS Sea Grant Matched Funding Program § 917.11 Guidelines for... applications for Sea Grant Fellowship funding. (b) Funding will be made to eligible entities (see § 917.10 of...

  11. Decennial Censuses: Historical Data on Enumerator Productivity Are Limited

    National Research Council Canada - National Science Library

    2001-01-01

    ... it. These factors-used to calculate productivity-are some of the largest drivers of census costs, and the Bureau developed its budget for the 2000 Census using a model that contained key assumptions...

  12. Food Desert Census Tract Polygons, Region 9, 2000, US EPA Region 9

    Data.gov (United States)

    U.S. Environmental Protection Agency — Census Tract Data - Census 2000 This data layer represents Census 2000 demographic data derived from the PL94-171 redistricting files and SF3. Census geographic...

  13. Deep-sea pennatulaceans (sea pens) - recent discoveries, morphological adaptations, and responses to benthic oceanographic parameters

    Science.gov (United States)

    Williams, G. C.

    2015-12-01

    Pennatulaceans are sessile, benthic marine organisms that are bathymetrically wide-ranging, from the intertidal to approximately 6300 m in depth, and are conspicuous constituents of deep-sea environments. The vast majority of species are adapted for anchoring in soft sediments by the cylindrical peduncle - a muscular hydrostatic skeleton. However, in the past decade a few species ("Rockpens") have been discovered and described that can attach to hard substratum such as exposed rocky outcrops at depths between 669 and 1969 m, by a plunger-like adaptation of the base of the peduncle. Of the thirty-six known genera, eleven (or 30%) have been recorded from depths greater than 1000 m. The pennatulacean depth record holders are an unidentified species of Umbellula from 6260 m in the Peru-Chile Trench and a recently-discovered and described genus and species, Porcupinella profunda, from 5300 m the Porcupine Abyssal Plain of the northeastern Atlantic. A morphologically-differentiated type of polyp (acrozooid) have recently been discovered and described in two genera of shallow-water coral reef sea pens. Acrozooids apparently represent asexual buds and presumably can detach from the adult to start clonal colonies through asexual budding. Acrozooids are to be expected in deep-sea pennatulaceans, but so far have not been observed below 24 m in depth. Morphological responses at depths greater than 1000 m in deep-sea pennatulaceas include: fewer polyps, larger polyps, elongated stalks, and clustering of polyps along the rachis. Responses to deep-ocean physical parameters and anthropogenic changes that could affect the abundance and distribution of deep-sea pennatulaceans include changes in bottom current flow and food availability, changes in seawater temperature and pH, habitat destruction by fish trawling, and sunken refuse pollution. No evidence of the effects of ocean acidification or other effects of anthropogenic climate change in sea pens of the deep-sea has been

  14. Pediatric emergency department census during major sporting events.

    Science.gov (United States)

    Kim, Tommy Y; Barcega, Besh B; Denmark, T Kent

    2012-11-01

    Our study attempted to evaluate the effects of major sporting events on the census of a pediatric emergency department (ED) in the United States specifically related to the National Football League Super Bowl, National Basketball Association (NBA) Finals, and Major League Baseball World Series. We performed a retrospective data analysis of our pediatric ED census on the number of visits during major sporting events over a 5-year period. Data during the same period 1 week after the major sporting event were collected for comparison as the control. We evaluated the medians of 2-hour increments around the event start time. Subgroup analysis was performed for games involving the local sporting teams. Our results showed no significant difference in ED census during the sporting events, except in the post 6 to 8 hours of the NBA finals. Subgroup analysis of the Los Angeles Lakers showed the same significant findings in the post 6 to 8 hours of the NBA finals. No major difference in pediatric ED census is observed during the most major sporting events in the United States.

  15. Local censuses in the 18th century.

    Science.gov (United States)

    Law, C M

    1969-03-01

    Abstract Recent work on the population problems of the eighteenth century has been mainly based on the use of parish records. Another source, and one which, surprisingly, has received little attention is the local census. These are more numerous than is generally realised; and can be of great use in demographic studies. This paper examines 125 local censuses mainly taken in urban areas. They are discussed in terms of how they come to be taken, their reliability, extant manuscript material and their contents. Whilst most of the censuses confine themselves to the basic facts such as total population, number of houses and number of families, some give details of sex, age, marital status and occupation. Generally the information is given for the parish or local administrative unit, but in a few instances it is available by streets.

  16. New Mexico Census Tracts, Households by Type (2010)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article...

  17. New Mexico Census Tracts, Housing Vacancy Status (2010)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article...

  18. 40th annual Reed rig census

    International Nuclear Information System (INIS)

    Fitts, R.L.; Stokes, T.A.

    1992-01-01

    This paper reports that declines characterize the 1992 rig census-in the number of available drilling rigs, in the number of active rigs, in rig utilization rate, in the number of rig owners and in industry optimism. The number of rotary rigs available for U.S. drilling fell by 255 units (11.3%) during the past 12 months, an attrition rate almost four times greater than in 1991. But despite the high attrition, only 59.7% of remaining rigs were working during the time the census was taken. Results of the 1992 census bring emphasis to an industry trend that became apparent in early 1991. The major oil companies, and many independents, continued their exodus form the U.S., and the remaining independents, which were hurt by low natural gas prices and unfavorable tax treatment of intangible drilling costs, were not able to pick u the drilling slack. Consequently, the past year has been disastrous for many U.S. drilling contractors, and the outlook for this industry segment remains bleak

  19. The Register-based Census in Germany: Historical Context and Relevance for Population Research

    Directory of Open Access Journals (Sweden)

    Rembrandt Scholz

    2016-08-01

    Full Text Available In 2011, Germany carried out its first census after a 20-year break. In light of the United Nations’ recommendations that countries initiate a population census at least every 10 years, the census was long overdue. Moreover, demographers had for some time been demanding a new enumeration that would enable them to place the calculation of demographic indicators on a reliable basis. With the 2011 census, Germany not only met the demand for a current population census, but also broke new ground by using a register-based approach. Unlike the Scandinavian countries, which have a long tradition of performing register-based data analyses, the linking of administrative data in Germany is restricted by the country’s legal framework. Thus, the 2011 census was an ambitious project. After contextualising the 2011 census historically, we discuss in this contribution the census’ relevance for generating central demographic data. Specifically, we compare the updated population estimates of the 1987 census to the results of the 2011 census in order to identify possible systematic sources of error that distort demographic indicators and analyses.

  20. Seeing Objects as Faces Enhances Object Detection.

    Science.gov (United States)

    Takahashi, Kohske; Watanabe, Katsumi

    2015-10-01

    The face is a special visual stimulus. Both bottom-up processes for low-level facial features and top-down modulation by face expectations contribute to the advantages of face perception. However, it is hard to dissociate the top-down factors from the bottom-up processes, since facial stimuli mandatorily lead to face awareness. In the present study, using the face pareidolia phenomenon, we demonstrated that face awareness, namely seeing an object as a face, enhances object detection performance. In face pareidolia, some people see a visual stimulus, for example, three dots arranged in V shape, as a face, while others do not. This phenomenon allows us to investigate the effect of face awareness leaving the stimulus per se unchanged. Participants were asked to detect a face target or a triangle target. While target per se was identical between the two tasks, the detection sensitivity was higher when the participants recognized the target as a face. This was the case irrespective of the stimulus eccentricity or the vertical orientation of the stimulus. These results demonstrate that seeing an object as a face facilitates object detection via top-down modulation. The advantages of face perception are, therefore, at least partly, due to face awareness.

  1. Seeing Objects as Faces Enhances Object Detection

    Directory of Open Access Journals (Sweden)

    Kohske Takahashi

    2015-09-01

    Full Text Available The face is a special visual stimulus. Both bottom-up processes for low-level facial features and top-down modulation by face expectations contribute to the advantages of face perception. However, it is hard to dissociate the top-down factors from the bottom-up processes, since facial stimuli mandatorily lead to face awareness. In the present study, using the face pareidolia phenomenon, we demonstrated that face awareness, namely seeing an object as a face, enhances object detection performance. In face pareidolia, some people see a visual stimulus, for example, three dots arranged in V shape, as a face, while others do not. This phenomenon allows us to investigate the effect of face awareness leaving the stimulus per se unchanged. Participants were asked to detect a face target or a triangle target. While target per se was identical between the two tasks, the detection sensitivity was higher when the participants recognized the target as a face. This was the case irrespective of the stimulus eccentricity or the vertical orientation of the stimulus. These results demonstrate that seeing an object as a face facilitates object detection via top-down modulation. The advantages of face perception are, therefore, at least partly, due to face awareness.

  2. Marine fauna of hard substrata of the Cleaver bank and Dogger bank

    NARCIS (Netherlands)

    Schrieken, N.; Gittenberger, A.; Coolen, J.W.P.; Lengkeek, W.

    2013-01-01

    As most of the sea bottom in the Dutch part of the North Sea consists of sand, marine fauna that live in association with hard substrates are rarely monitored. We report here on the results of a species inventory in June 2011 done by scuba-diving while focusing on a wreck on the Dogger Bank and on

  3. Marine fauna of hard substrata of the Cleaver Bank and Dogger Bank

    NARCIS (Netherlands)

    Schrieken, N.; Gittenberger, A.; Coolen, J.W.P.; Lengkeek, W.

    2013-01-01

    As most of the sea bottom in the Dutch part of the North Sea consists of sand, marine fauna that live in association with hard substrates are rarely monitored. We report here on the results of a species inventory in June 2011 done by scuba-diving while focusing on a wreck on the Dogger Bank and on

  4. Seabird species vary in behavioural response to drone census.

    Science.gov (United States)

    Brisson-Curadeau, Émile; Bird, David; Burke, Chantelle; Fifield, David A; Pace, Paul; Sherley, Richard B; Elliott, Kyle H

    2017-12-20

    Unmanned aerial vehicles (UAVs) provide an opportunity to rapidly census wildlife in remote areas while removing some of the hazards. However, wildlife may respond negatively to the UAVs, thereby skewing counts. We surveyed four species of Arctic cliff-nesting seabirds (glaucous gull Larus hyperboreus, Iceland gull Larus glaucoides, common murre Uria aalge and thick-billed murre Uria lomvia) using a UAV and compared censusing techniques to ground photography. An average of 8.5% of murres flew off in response to the UAV, but >99% of those birds were non-breeders. We were unable to detect any impact of the UAV on breeding success of murres, except at a site where aerial predators were abundant and several birds lost their eggs to predators following UAV flights. Furthermore, we found little evidence for habituation by murres to the UAV. Most gulls flew off in response to the UAV, but returned to the nest within five minutes. Counts of gull nests and adults were similar between UAV and ground photography, however the UAV detected up to 52.4% more chicks because chicks were camouflaged and invisible to ground observers. UAVs provide a less hazardous and potentially more accurate method for surveying wildlife. We provide some simple recommendations for their use.

  5. Historical measures of social context in life course studies: retrospective linkage of addresses to decennial censuses

    Directory of Open Access Journals (Sweden)

    Whitsel Eric A

    2004-11-01

    Full Text Available Abstract Background There is evidence of a contribution of early life socioeconomic exposures to the risk of chronic diseases in adulthood. However, extant studies investigating the impact of the neighborhood social environment on health tend to characterize only the current social environment. This in part may be due to complexities involved in obtaining and geocoding historical addresses. The Life Course Socioeconomic Status, Social Context, and Cardiovascular Disease Study collected information on childhood (1930–1950 and early adulthood (1960–1980 place of residence from 12,681 black and white middle-aged and older men and women from four U.S. communities to link participants with census-based socioeconomic indicators over the life course. Results Most (99% participants were linked to 1930–50 county level socioeconomic census data (the smallest level of aggregation universally available during this time period corresponding to childhood place of residence. Linkage did not vary by race, gender, birth cohort, or level of educational attainment. A commercial geocoding vendor processed participants' self-reported street addresses for ages 30, 40, and 50. For 1970 and 1980 censuses, spatial coordinates were overlaid onto shape files containing census tract boundaries; for 1960 no shape files existed and comparability files were used. Several methods were tested for accuracy and to increase linkage. Successful linkage to historical census tracts varied by census (66% for 1960, 76% for 1970, 85% for 1980. This compares to linkage rates of 94% for current addresses provided by participants over the course of the ARIC examinations. Conclusion There are complexities and limitations in characterizing the past social context. However, our results suggest that it is feasible to characterize the earlier social environment with known levels of measurement error and that such an approach should be considered in future studies.

  6. 1980 Census Tracts (TIGER)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This data set is a vector polygon digital data structure taken from Census Bureau's TIGER/Line Files, 1994, for New Mexico. The source software used was ARC/INFO...

  7. [The use of census data to estimate levels of urbanization].

    Science.gov (United States)

    Darwin, M; Tukiran

    1991-01-01

    Problems concerning changes in the definition of urbanization for demographic analysis are examined. "This article attempts to examine the problem by clarifying the definition of the concept and indicators of urban and urbanization and by making a longitudinal analysis of urbanization using the Indonesian 1920-1990 Census data." (SUMMARY IN ENG) excerpt

  8. The 1941 villages census – an important source for studying local history

    Directory of Open Access Journals (Sweden)

    Sergiu Tabuncic

    2014-12-01

    Full Text Available The 1941 census is an important source for studying the history of the settlements from the present-time districts of Soldanesti and Rezina in the Republic of Moldova. In 1941, those localities were part of Bessarabia’s Orhei County. The materials of that census are stored at the National Archives of the Republic of Moldova, the fund No 2069, inventory 1, part 1, file 450-a. Villages Census 1941 – this is the title of the questionnaire used to collect data. The census was conducted under the auspices of the Central Institute of Statistics subordinate to the Council of Ministers of Romania. The census questionnaire contained 28 sections, each containing questions aimed to clarify the status of settlements in terms of administrative, social, economic, ethnographic, cultural, medical and religious aspects. Many questions pertained to the duration and continuity of the population’s residing in villages listed in the census and villages’ foundation years, to description of rural settlements, permanent and temporary dwellings. Also, the census results show some elements of relations between Romanians and Roma people. The 1941 census is the most significant and representative component of local history, substantially enriching the sources of this domain of research.

  9. Awkward Questions: Language Issues in the 2011 Census in England

    Science.gov (United States)

    Sebba, Mark

    2018-01-01

    The 2011 Census in England broke new ground, as a question about language had never previously been asked. After stakeholder consultations and a series of trials, the census authority decided on two questions based on earlier censuses in the USA: one about the respondent's "main language" and another about proficiency in English. This…

  10. Counting nurses: the power of historical census data.

    Science.gov (United States)

    D'Antonio, Patricia; Whelan, Jean C

    2009-10-01

    This study used census data to construct a demographic profile of early 20th century nurses in the United States. Census data are recognised as a rich source of quantitative information on long-term changes. However, difficulties in retrieving census data dissuade researchers from exploiting this source. Integrated Public Use Microdata Series, a standardised and digitialised version of census data, enables greater ease in retrieving and analysing data. A sample of respondents identifying as 'professional nurses' for the years 1900-1950 was extracted from Integrated Public Use Microdata Series categorised by the variables of race, sex and marital status. The resulting data were analysed for simple frequency statistics using SPSS software. Results revealed a tremendous increase in the number of nurses over the five decades under study. Nurses were increasingly young, female, single and white until 1930. After 1930, white and African-American women nurses began to reflect trends towards more diversity. This study is the first systematic attempt to trace the demographic trajectory of professional nurses in the United States in the early 20th century. It also demonstrates the possibilities of using digital technologies to restructure the asking and answering of historical questions. The use of quantitative methods of social history has trans-national applications which can facilitate global investigations into the demographic composition of the nursing occupation. RELEVANCE TO POLICY: This way of using digitalisation of census data provides a way to examine historical trans-national workforce trends. Such trends provide a firmer base upon which to construct workforce and practice strategies for a future global workforce.

  11. Archive of Census Related Products (ACRP): 1992 Boundary Files

    Data.gov (United States)

    National Aeronautics and Space Administration — The 1992 Boundary Files portion of the Archive of Census Related Products (ACRP) consists of 1992 boundary data from the U.S. Census Bureau's Topologically...

  12. Census 2000 Urbanized Areas (CEN00UA02_2)

    Data.gov (United States)

    California Natural Resource Agency — For Census 2000, the Census Bureau classifies as 'urban' all territory, population, and housing units located within an urbanized area (UA) or an urban cluster (UC)....

  13. Census Tracts & Block Groups, 2004, East Baton Rouge, Louisiana

    Data.gov (United States)

    Louisiana Geographic Information Center — This is a graphical polygon dataset depicting the polygon boundaries of 107 semi-permanent census tracts and the census blocks within the Parish of East Baton Rouge....

  14. Preventive Intra Oral Treatment of Sea Cucumber Ameliorate OVA-Induced Allergic Airway Inflammation.

    Science.gov (United States)

    Lee, Da-In; Park, Mi-Kyung; Kang, Shin Ae; Choi, Jun-Ho; Kang, Seok-Jung; Lee, Jeong-Yeol; Yu, Hak Sun

    2016-01-01

    Sea cucumber extracts have potent biological effects, including anti-viral, anti-cancer, antibacterial, anti-oxidant, and anti-inflammation effects. To understand their anti-asthma effects, we induced allergic airway inflammation in mice after 7 oral administrations of the extract. The hyper-responsiveness value in mice with ovalbumin (OVA)-alum-induced asthma after oral injection of sea cucumber extracts was significantly lower than that in the OVA-alum-induced asthma group. In addition, the number of eosinophils in the lungs of asthma-induced mice pre-treated with sea cucumber extract was significantly decreased compared to that of PBS pre-treated mice. Additionally, CD4[Formula: see text]CD25[Formula: see text]Foxp3[Formula: see text]T (regulatory T; Treg) cells significantly increased in mesenteric lymph nodes after 7 administrations of the extract. These results suggest that sea cucumber extract can ameliorate allergic airway inflammation via Treg cell activation and recruitment to the lung.

  15. Use of aerial photograph to enhance dog population census in Ilorin ...

    African Journals Online (AJOL)

    HP USER

    rabies control programme among dogs in the city. Keywords:Aerial .... define coverage area by harmonized boundaries. Census ... concerned with management of dogs and cases of dog bite. .... associated with clinical human rabies in a.

  16. Why is the North Sea West of Us?

    DEFF Research Database (Denmark)

    Gammeltoft, Peder

    2016-01-01

    . Occurrences of sea names such as the North Sea are examined and analysed to see how they spread from an original one-language form to exist in multiple languages, and analyses them from a linguistic, geographic and nautical perspective. It is found that Seas or bodies of water in stretches of sea are named......This article focuses on the motivations behind sea-naming, by means of examples from Europe but also elsewhere. Why do certain sea names become dominant while others retract into local forms or simply die out? The article takes us back in time to the early days of map-making and, indeed, earlier...

  17. Micro Structure and Hardness Analysis of Brass Metal Welded

    Science.gov (United States)

    Lukman Faris, N.; Muljadi; Djuhana

    2018-01-01

    Brass metals are widely used for plumbing fittings. High tensile brasses are more highly alloyed and find uses in marine engineering. The welding of brass metal has been done by using electrical weld machine (SMAW). The microstructure of brass metal welded was observed by optical microscope. The result can see that the microstructure has been changed due to heat from welding. The microstructure of original brass metal is seen a fine laminar stucture, but the microstructure at HAZ appears bigger grains and some area at HAZ is seen coarser microstructure. The microstructure at weld zone can be seen that it was found some of agglomeration of materials from reaction between brass metal and electrode coating wire. According the hardness measurement, it is found highest hardness value about 301.92 HV at weld zone, and hardness value at base metal is 177.84 HV

  18. Colonization of habitat islands in the deep sea: recruitment to glass sponge stalks

    Science.gov (United States)

    Beaulieu, Stace E.

    2001-04-01

    Biogenic structures in the deep sea often act as hard substratum 'islands' for the attachment of encrusting fauna. At an abyssal station in the NE Pacific, stalks of hexactinellid sponges in the genus Hyalonema are habitat islands for species-rich epifaunal communities. An experimental study was conducted to (1) determine the colonization rates of artificial Hyalonema stalks, (2) compare the species composition and diversity of recruits to newly available substrata to that of the natural communities, and (3) examine the vertical distribution of recruits. Four sets of six artificial sponge stalks, constructed of Hyalonema spicules, were deployed at 4100 m depth for 3- to 5-month periods. There was no difference in net colonization or immigration rate among the four deployments. Colonization rates were similar to those reported for other deep-sea, hard substratum recruitment experiments. The taxa that recruited to the artificial stalks were a subset of the taxa found in natural communities. However, several taxa important in structuring natural communities did not recruit to the artificial stalks. The two taxa with the highest invasion rates, a calcareous foraminiferan ( Cibicides lobatulus) and a serpulid polychaete ( Bathyvermilia sp.), also were the two taxa with greatest relative abundance in natural communities. Vertical distributions of Cibicides and an agglutinated foraminiferan ( Telammina sp.) were skewed towards the top of the artificial stalks, potentially because of active habitat selection. These results have several implications for natural Hyalonema stalk communities. Most importantly, species composition and abundance of individuals in the stalk communities appear to be maintained by frequent recruitment of a few common taxa and infrequent recruitment of many rare taxa. An argument is presented for temporal-mosaic maintenance of diversity in these deep-sea, hard substratum communities.

  19. 75 FR 52173 - Proposed Urban Area Criteria for the 2010 Census

    Science.gov (United States)

    2010-08-24

    ... avoid confusion with the Census Bureau's official urban- rural classifications. I. History Over the... been possible previously. Rather than delineating urban areas in an interactive and manual fashion, the... consistent fashion. For example, the Census Bureau split large agglomerations for Census 2000 by using...

  20. Sea Surface Temperature and Ocean Color Variability in the South China Sea

    Science.gov (United States)

    Conaty, A. P.

    2001-12-01

    The South China Sea is a marginal sea in the Southeast Asian region whose surface circulation is driven by monsoons and whose surface currents have complex seasonal patterns. Its rich natural resources and strategic location have made its small islands areas of political dispute among the neighboring nations. This study aims to show the seasonal and interannual variability of sea surface temperature and ocean color in South China Sea. It makes use of NOAA's Advanced Very High Resolution Radiometer (AVHRR) satellite data sets on sea surface temperature for the period 1981-2000 and NASA's Nimbus-7 Coastal Zone Color Scanner (CZCS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite data sets on pigment concentration (ocean color) for the period 1981-1996 and 1997-2000, respectively. Transect lines were drawn along several potential hotspot areas to show the variability in sea surface temperature and pigment concentration through time. In-situ data on sea surface temperature along South China Sea were likewise plotted to see the variability with time. Higher seasonal variability in sea surface temperature was seen at higher latitudes. Interannual variability was within 1-3 Kelvin. In most areas, pigment concentration was higher during northern hemisphere winter and autumn, after the monsoon rains, with a maximum of 30 milligrams per cubic meter.

  1. Work Hard / Play Hard

    OpenAIRE

    Burrows, J.; Johnson, V.; Henckel, D.

    2016-01-01

    Work Hard / Play Hard was a participatory performance/workshop or CPD experience hosted by interdisciplinary arts atelier WeAreCodeX, in association with AntiUniversity.org. As a socially/economically engaged arts practice, Work Hard / Play Hard challenged employees/players to get playful, or go to work. 'The game changes you, you never change the game'. Employee PLAYER A 'The faster the better.' Employer PLAYER B

  2. [Automated processing of data from the 1985 population and housing census].

    Science.gov (United States)

    Cholakov, S

    1987-01-01

    The author describes the method of automated data processing used in the 1985 census of Bulgaria. He notes that the computerization of the census involves decentralization and the use of regional computing centers as well as data processing at the Central Statistical Office's National Information Computer Center. Special attention is given to problems concerning the projection and programming of census data. (SUMMARY IN ENG AND RUS)

  3. To See and To Be Seen

    DEFF Research Database (Denmark)

    Nielsen, Kirsten

    2013-01-01

    autoritært gudsbillede, der kan medføre vold i Guds navn, går fejl af Gen 22's centrale budskab: afvisningen af menneskeofringer er udtryk for Guds omsorg. The aim of this article is to demonstrate: 1) that the root ראה plays a crucial role in Gen 16 and 22, where Hagar and Abraham see and acknowledge Yahweh......, and Yahweh sees and shows solicitude; 2) that there is a close connection between Yahweh as ‘he who sees and he who is seen’, i.e. between his solicitude and his appearance, as expressed in the names for God and places in Gen 16:13-14 and Gen 22:14; 3) that there is a link between Yahweh’s appearance, his...... holy places, and his double promise; 4) that Gen 16 and 22 are variants of the same narrative with the same theological point, namely: Yahweh’s solicitude; and 5) that the theological criticism of God in Gen 22 as an authoritarian being whose will may lead to violence being committed in his name...

  4. Hard tissue deposition in dental pulp canal by {alpha}-tricalcium phosphate cement

    Energy Technology Data Exchange (ETDEWEB)

    Yoshikawa, M.; Toda, T. [Osaka Dental Univ. (Japan). Dept. of Endodontics; Mandai, Y. [Bio-Chemical Lab. of Nitta Gelatin Inc., Yao (Japan); Oonishi, H. [Osaka Minami National Hospital, Kawachi (Japan). Dept. of Orthopaedic Surgery

    2001-07-01

    Canal closure by hard tissue proliferation in the pulp canal and/or apical foramen is the most ideal healing after pulp removal. Generally, Ca(OH){sub 2} may induce secondary dentine or dentine-bridge on the amputated pulp surface. However, Ca(OH){sub 2} shows strong alkalinity and may cause severe inflammatory responses in the residual pulp. Moreover, completely formed dentine-bridge at the orifice will disturb further treatment of residual pulp because of the difficulty in localizing the pathway. The purpose of this study was to see hard tissue induction using newly developed {alpha}-tricalcium phosphate cement and to recognize the morphological difference of hard tissue from that of Ca(OH){sub 2}. (orig.)

  5. New Mexico Census Tracts, Race and Hispanic Ethnicity (2010)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article...

  6. New Mexico Census Tracts, Median Age by Sex (2010)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article...

  7. Results of the 2000 census of wild reindeer on the Taimyr Peninsula

    Directory of Open Access Journals (Sweden)

    Leonid A. Kolpashchikov

    2003-04-01

    Full Text Available We conducted a census of wild reindeer (Rangifer tarandus on the Taimyr Peninsula during 21-25 July 2000. This was the eighteenth aerial population census of wild reindeer on the Taimyr since counts began in 1959. Prior to the census, we conducted reconnaissance flights to identify areas of reindeer concentration. After the reindeer became aggregated, we estimated group size both visually and by photographing the larger groups. Unusually hot and dry weather (temperatures of 25-30 °C and a high density of mosquitoes during the census likely forced the reindeer to group into unusually large concentrations. In late July most of the reindeer in the Taimyr population were distributed in two groupings that contained at least 450 000 animals, and one area that contained about 110 000. Smaller groups found during the census and the estimated 43 000 resident wild reindeer that were not counted during the census brought the total minimum population estimate to about 1 040 000. The maximum number of wild reindeer present could have been as high as about 1 100 000.

  8. Alien seas oceans in space

    CERN Document Server

    Lopes, Rosaly

    2013-01-01

    In the early days of planetary observation, oceans were thought to exist in all corners of the Solar System. Carbonated seas percolated beneath the clouds of Venus. Features on the Moon's surface were given names such as "the Bay of Rainbows” and the "Ocean of Storms." With the advent of modern telescopes and spacecraft exploration these ancient concepts of planetary seas have been replaced by the reality of something even more exotic. Alien Seas serves up the current research, past beliefs, and new theories to offer a rich array of the "seas" on other worlds. It is organized by location and by the material composing the oceans under discussion, with expert authors penning chapters on their  specialty. Each chapter features new original art depicting alien seas, as well as the latest ground-based and spacecraft images. With the contributors as guides, readers can explore the wild seas of Jupiter's watery satellite Europa, believed similar in composition to battery acid. Saturn's planet-sized moon Titan see...

  9. Census Bureau Regional Office Boundaries : New Structure as of January 2013

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The Census Bureau has six regional offices to facilitate data collection, data dissemination and geographic operations within their boundary. The surveys these...

  10. Who is Hmong? Questions and Evidence from the U.S. Census

    Directory of Open Access Journals (Sweden)

    Victoria Udalova

    2006-01-01

    Full Text Available This paper explores the boundaries of the Hmong community as measured by different categories in 2000 U.S. census data. Following careful assessment of detailed Census data, the authors conclude that theusual criterion used to identify a person in the data as Hmong is too narrow, and that a broader, more inclusive definition more accurately delineates the Hmong ethnic group. The authors propose that anyonewho reported in the Census that his or her race, ancestry, or language was Hmong should be included in the Hmong community. This more inclusive method provides evidence that the Hmong populationenumerated by the 2000 U.S. census was about 18% larger than the figure that is usually reported.

  11. Tortugas Reef Fish Census (CRCP)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This is a long term data set collecting visual census transect data on reef fishes at staions located at Rileys Hump, Tortugas South Ecological Reservee.

  12. Detection of Small Sea-Surface Targets with a Search Lidar

    NARCIS (Netherlands)

    Heuvel, J.C. van den; Bekman, H.H.P.T.; Putten, F.J.M.; Cohen, L.A.

    2007-01-01

    Naval operations in the littoral have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and low velocity, which makes them hard to detect by radar in the presence of sea clutter. Typical threats include periscopes, jet skies, FIAC’s, and speedboats.

  13. Mora County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  14. Bernalillo County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  15. Chaves County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  16. Lea County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  17. Guadalupe County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  18. Lincoln County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  19. Bernalillo County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  20. Torrance County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  1. Sierra County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  2. Grant County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  3. Luna County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  4. New Mexico, 2010 Census Place

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  5. Otero County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  6. Quay County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  7. Union County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  8. Sandoval County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  9. Socorro County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  10. Valencia County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  11. Taos County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  12. Sandoval County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  13. Eddy County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  14. Socorro County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  15. Grant County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  16. Roosevelt County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  17. Cibola County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  18. Lincoln County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  19. Lincoln County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  20. Union County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  1. Taos County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  2. Guadalupe County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  3. Luna County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  4. Catron County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  5. Hidalgo County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  6. Otero County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  7. Curry County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  8. Chaves County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  9. Sierra County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  10. Chaves County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  11. Union County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  12. Lea County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  13. Otero County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  14. Valencia County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  15. Curry County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  16. Quay County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  17. Quay County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  18. Luna County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  19. Union County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  20. Bernalillo County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  1. Guadalupe County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  2. Catron County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  3. Cibola County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  4. Sandoval County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  5. Colfax County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  6. Roosevelt County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  7. Grant County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  8. Sierra County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  9. Otero County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  10. Lea County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  11. Lincoln County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  12. Curry County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  13. Eddy County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  14. Valencia County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  15. Hidalgo County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  16. Mora County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  17. Socorro County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  18. Quay County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  19. Luna County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  20. Chaves County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  1. Taos County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  2. Torrance County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  3. Taos County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  4. Hidalgo County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  5. Mora County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  6. Torrance County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  7. Colfax County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  8. Bernalillo County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  9. Torrance County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  10. Socorro County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  11. Sierra County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  12. Lea County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  13. Cibola County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  14. Roosevelt County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  15. Sandoval County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  16. Hidalgo County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  17. Valencia County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  18. Grant County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  19. Eddy County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  20. Colfax County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  1. Mora County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  2. Catron County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  3. Hard electronics; Hard electronics

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    Hard material technologies were surveyed to establish the hard electronic technology which offers superior characteristics under hard operational or environmental conditions as compared with conventional Si devices. The following technologies were separately surveyed: (1) The device and integration technologies of wide gap hard semiconductors such as SiC, diamond and nitride, (2) The technology of hard semiconductor devices for vacuum micro- electronics technology, and (3) The technology of hard new material devices for oxides. The formation technology of oxide thin films made remarkable progress after discovery of oxide superconductor materials, resulting in development of an atomic layer growth method and mist deposition method. This leading research is expected to solve such issues difficult to be easily realized by current Si technology as high-power, high-frequency and low-loss devices in power electronics, high temperature-proof and radiation-proof devices in ultimate electronics, and high-speed and dense- integrated devices in information electronics. 432 refs., 136 figs., 15 tabs.

  4. [Statement of the board of directors of the German Sociological Society on the population census].

    Science.gov (United States)

    1983-10-01

    This statement concerning population censuses has been prepared at the request of the board of directors of the German Sociological Society in light of the controversy surrounding the 1983 census in the Federal Republic of Germany. It is suggested that sample surveys cannot replace a census, a census is indispensable as a data source for regional analyses and studies of small population groups, a census must be carried out in a way that preserves the confidentiality of data, and census data must be accessible to scientific research.

  5. Boreal earliest Triassic biotas elucidate globally depauperate hard substrate communities after the end-Permian mass extinction.

    Science.gov (United States)

    Zatoń, Michał; Niedźwiedzki, Grzegorz; Blom, Henning; Kear, Benjamin P

    2016-11-08

    The end-Permian mass extinction constituted the most devastating biotic crisis of the Phanerozoic. Its aftermath was characterized by harsh marine conditions incorporating volcanically induced oceanic warming, widespread anoxia and acidification. Bio-productivity accordingly experienced marked fluctuations. In particular, low palaeolatitude hard substrate communities from shallow seas fringing Western Pangaea and the Tethyan Realm were extremely impoverished, being dominated by monogeneric colonies of filter-feeding microconchid tubeworms. Here we present the first equivalent field data for Boreal hard substrate assemblages from the earliest Triassic (Induan) of East Greenland. This region bordered a discrete bio-realm situated at mid-high palaeolatitude (>30°N). Nevertheless, hard substrate biotas were compositionally identical to those from elsewhere, with microconchids encrusting Claraia bivalves and algal buildups on the sea floor. Biostratigraphical correlation further shows that Boreal microconchids underwent progressive tube modification and unique taxic diversification concordant with changing habitats over time. We interpret this as a post-extinction recovery and adaptive radiation sequence that mirrored coeval subequatorial faunas, and thus confirms hard substrate ecosystem depletion as a hallmark of the earliest Triassic interval globally.

  6. Archive of Census Related Products (ACRP): 1990 Standard Extract Files

    Data.gov (United States)

    National Aeronautics and Space Administration — The 1990 Standard Extract Files portion of the Archive of Census Related Products (ACRP) contains population and housing data derived from the U.S. Census Bureau's...

  7. see Gupta VK 433 Andreev V see Porcellato AM 963 Antony J see ...

    Indian Academy of Sciences (India)

    Cryogenic, superconducting and rf results of the SRFQ2 of PIAVE. 963. Prakash P N. Superconducting linear accelerator system for. NSC. 849 see Ghosh S. 881. Prakash S see Sharma Hitesh. 497. Prasad J see Chopra S. 753. Prasad Moonooku see Pande S A. 859. Prasad R L. CO2 laser photoacoustic spectra and vibra-.

  8. Bernalillo County Transportation Analysis Zones, Census 2000 from TIGER 2008

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Shapefiles are an extract of selected geographic and cartographic information from the Census MAF/TIGER database. The Census MAF/TIGER database...

  9. 1,001 Celestial Wonders to See Before You Die The Best Sky Objects for Star Gazers

    CERN Document Server

    Bakich, Michael E

    2010-01-01

    Many deep-sky objects that can appear quite wonderful in photographs can be hard to observe in the telescope. This book is your guide to the more interesting nebulae, star clusters, and galaxies, objects that will bring gasps when you see them through a telescope. Author Michael E. Bakich shows you how to spot constellations you’ve heard of but haven’t been able to find. He gives you lists of bright deep-sky objects to target on clear nights. And he guides your search for the famous named splendors you’ve heard of — and perhaps seen a picture of — and would like to see through your own telescope. Bakich, an observer since he was in third grade, knows the sky better than most. In his current position as senior editor and also photo editor for the highly regarded Astronomy magazine, he has the technical expertise and finely honed communication skills to help you easily locate the best sites in the sky. His more than 250 astroimages help you identify the detail in these sky wonders. Bakich organizes hi...

  10. Production of [Formula: see text] and [Formula: see text] in p-Pb collisions at [Formula: see text] TeV.

    Science.gov (United States)

    Adamová, D; Aggarwal, M M; Aglieri Rinella, G; Agnello, M; Agrawal, N; Ahammed, Z; Ahmad, S; Ahn, S U; Aiola, S; Akindinov, A; Alam, S N; Albuquerque, D S D; Aleksandrov, D; Alessandro, B; Alexandre, D; Alfaro Molina, R; Alici, A; Alkin, A; Alme, J; Alt, T; Altinpinar, S; Altsybeev, I; Alves Garcia Prado, C; An, M; Andrei, C; Andrews, H A; Andronic, A; Anguelov, V; Anson, C; Antičić, T; Antinori, F; Antonioli, P; Anwar, R; Aphecetche, L; Appelshäuser, H; Arcelli, S; Arnaldi, R; Arnold, O W; Arsene, I C; Arslandok, M; Audurier, B; Augustinus, A; Averbeck, R; Azmi, M D; Badalà, A; Baek, Y W; Bagnasco, S; Bailhache, R; Bala, R; Baldisseri, A; Ball, M; Baral, R C; Barbano, A M; Barbera, R; Barile, F; Barioglio, L; Barnaföldi, G G; Barnby, L S; Barret, V; Bartalini, P; Barth, K; Bartke, J; Bartsch, E; Basile, M; Bastid, N; Basu, S; Bathen, B; Batigne, G; Batista Camejo, A; Batyunya, B; Batzing, P C; Bearden, I G; Beck, H; Bedda, C; Behera, N K; Belikov, I; Bellini, F; Bello Martinez, H; Bellwied, R; Beltran, L G E; Belyaev, V; Bencedi, G; Beole, S; Bercuci, A; Berdnikov, Y; Berenyi, D; Bertens, R A; Berzano, D; Betev, L; Bhasin, A; Bhat, I R; Bhati, A K; Bhattacharjee, B; Bhom, J; Bianchi, L; Bianchi, N; Bianchin, C; Bielčík, J; Bielčíková, J; Bilandzic, A; Biro, G; Biswas, R; Biswas, S; Blair, J T; Blau, D; Blume, C; Boca, G; Bock, F; Bogdanov, A; Boldizsár, L; Bombara, M; Bonomi, G; Bonora, M; Book, J; Borel, H; Borissov, A; Borri, M; Botta, E; Bourjau, C; Braun-Munzinger, P; Bregant, M; Broker, T A; Browning, T A; Broz, M; Brucken, E J; Bruna, E; Bruno, G E; Budnikov, D; Buesching, H; Bufalino, S; Buhler, P; Buitron, S A I; Buncic, P; Busch, O; Buthelezi, Z; Butt, J B; Buxton, J T; Cabala, J; Caffarri, D; Caines, H; Caliva, A; Calvo Villar, E; Camerini, P; Capon, A A; Carena, F; Carena, W; Carnesecchi, F; Castillo Castellanos, J; Castro, A J; Casula, E A R; Ceballos Sanchez, C; Cerello, P; Chang, B; Chapeland, S; Chartier, M; Charvet, J L; Chattopadhyay, S; Chattopadhyay, S; Chauvin, A; Cherney, M; Cheshkov, C; Cheynis, B; Chibante Barroso, V; Chinellato, D D; Cho, S; Chochula, P; Choi, K; Chojnacki, M; Choudhury, S; Christakoglou, P; Christensen, C H; Christiansen, P; Chujo, T; Chung, S U; Cicalo, C; Cifarelli, L; Cindolo, F; Cleymans, J; Colamaria, F; Colella, D; Collu, A; Colocci, M; Conesa Balbastre, G; Conesa Del Valle, Z; Connors, M E; Contreras, J G; Cormier, T M; Corrales Morales, Y; Cortés Maldonado, I; Cortese, P; Cosentino, M R; Costa, F; Costanza, S; Crkovská, J; Crochet, P; Cuautle, E; Cunqueiro, L; Dahms, T; Dainese, A; Danisch, M C; Danu, A; Das, D; Das, I; Das, S; Dash, A; Dash, S; De, S; De Caro, A; de Cataldo, G; de Conti, C; de Cuveland, J; De Falco, A; De Gruttola, D; De Marco, N; De Pasquale, S; De Souza, R D; Degenhardt, H F; Deisting, A; Deloff, A; Deplano, C; Dhankher, P; Di Bari, D; Di Mauro, A; Di Nezza, P; Di Ruzza, B; Diaz Corchero, M A; Dietel, T; Dillenseger, P; Divià, R; Djuvsland, Ø; Dobrin, A; Domenicis Gimenez, D; Dönigus, B; Dordic, O; Drozhzhova, T; Dubey, A K; Dubla, A; Ducroux, L; Duggal, A K; Dupieux, P; Ehlers, R J; Elia, D; Endress, E; Engel, H; Epple, E; Erazmus, B; Erhardt, F; Espagnon, B; Esumi, S; Eulisse, G; Eum, J; Evans, D; Evdokimov, S; Fabbietti, L; Fabris, D; Faivre, J; Fantoni, A; Fasel, M; Feldkamp, L; Feliciello, A; Feofilov, G; Ferencei, J; Fernández Téllez, A; Ferreiro, E G; Ferretti, A; Festanti, A; Feuillard, V J G; Figiel, J; Figueredo, M A S; Filchagin, S; Finogeev, D; Fionda, F M; Fiore, E M; Floris, M; Foertsch, S; Foka, P; Fokin, S; Fragiacomo, E; Francescon, A; Francisco, A; Frankenfeld, U; Fronze, G G; Fuchs, U; Furget, C; Furs, A; Fusco Girard, M; Gaardhøje, J J; Gagliardi, M; Gago, A M; Gajdosova, K; Gallio, M; Galvan, C D; Gangadharan, D R; Ganoti, P; Gao, C; Garabatos, C; Garcia-Solis, E; Garg, K; Garg, P; Gargiulo, C; Gasik, P; Gauger, E F; Gay Ducati, M B; Germain, M; Ghosh, P; Ghosh, S K; Gianotti, P; Giubellino, P; Giubilato, P; Gladysz-Dziadus, E; Glässel, P; Goméz Coral, D M; Gomez Ramirez, A; Gonzalez, A S; Gonzalez, V; González-Zamora, P; Gorbunov, S; Görlich, L; Gotovac, S; Grabski, V; Graczykowski, L K; Graham, K L; Greiner, L; Grelli, A; Grigoras, C; Grigoriev, V; Grigoryan, A; Grigoryan, S; Grion, N; Gronefeld, J M; Grosa, F; Grosse-Oetringhaus, J F; Grosso, R; Gruber, L; Grull, F R; Guber, F; Guernane, R; Guerzoni, B; Gulbrandsen, K; Gunji, T; Gupta, A; Gupta, R; Guzman, I B; Haake, R; Hadjidakis, C; Hamagaki, H; Hamar, G; Hamon, J C; Harris, J W; Harton, A; Hatzifotiadou, D; Hayashi, S; Heckel, S T; Hellbär, E; Helstrup, H; Herghelegiu, A; Herrera Corral, G; Herrmann, F; Hess, B A; Hetland, K F; Hillemanns, H; Hippolyte, B; Hladky, J; Horak, D; Hosokawa, R; Hristov, P; Hughes, C; Humanic, T J; Hussain, N; Hussain, T; Hutter, D; Hwang, D S; Ilkaev, R; Inaba, M; Ippolitov, M; Irfan, M; Isakov, V; Islam, M S; Ivanov, M; Ivanov, V; Izucheev, V; Jacak, B; Jacazio, N; Jacobs, P M; Jadhav, M B; Jadlovska, S; Jadlovsky, J; Jahnke, C; Jakubowska, M J; Janik, M A; Jayarathna, P H S Y; Jena, C; Jena, S; Jercic, M; Jimenez Bustamante, R T; Jones, P G; Jusko, A; Kalinak, P; Kalweit, A; Kang, J H; Kaplin, V; Kar, S; Karasu Uysal, A; Karavichev, O; Karavicheva, T; Karayan, L; Karpechev, E; Kebschull, U; Keidel, R; Keijdener, D L D; Keil, M; Ketzer, B; Mohisin Khan, M; Khan, P; Khan, S A; Khanzadeev, A; Kharlov, Y; Khatun, A; Khuntia, A; Kielbowicz, M M; Kileng, B; Kim, D W; Kim, D J; Kim, D; Kim, H; Kim, J S; Kim, J; Kim, M; Kim, M; Kim, S; Kim, T; Kirsch, S; Kisel, I; Kiselev, S; Kisiel, A; Kiss, G; Klay, J L; Klein, C; Klein, J; Klein-Bösing, C; Klewin, S; Kluge, A; Knichel, M L; Knospe, A G; Kobdaj, C; Kofarago, M; Kollegger, T; Kolojvari, A; Kondratiev, V; Kondratyeva, N; Kondratyuk, E; Konevskikh, A; Kopcik, M; Kour, M; Kouzinopoulos, C; Kovalenko, O; Kovalenko, V; Kowalski, M; Koyithatta Meethaleveedu, G; Králik, I; Kravčáková, A; Krivda, M; Krizek, F; Kryshen, E; Krzewicki, M; Kubera, A M; Kučera, V; Kuhn, C; Kuijer, P G; Kumar, A; Kumar, J; Kumar, L; Kumar, S; Kundu, S; Kurashvili, P; Kurepin, A; Kurepin, A B; Kuryakin, A; Kushpil, S; Kweon, M J; Kwon, Y; La Pointe, S L; La Rocca, P; Lagana Fernandes, C; Lakomov, I; Langoy, R; Lapidus, K; Lara, C; Lardeux, A; Lattuca, A; Laudi, E; Lavicka, R; Lazaridis, L; Lea, R; Leardini, L; Lee, S; Lehas, F; Lehner, S; Lehrbach, J; Lemmon, R C; Lenti, V; Leogrande, E; León Monzón, I; Lévai, P; Li, S; Li, X; Lien, J; Lietava, R; Lindal, S; Lindenstruth, V; Lippmann, C; Lisa, M A; Litichevskyi, V; Ljunggren, H M; Llope, W J; Lodato, D F; Loenne, P I; Loginov, V; Loizides, C; Loncar, P; Lopez, X; López Torres, E; Lowe, A; Luettig, P; Lunardon, M; Luparello, G; Lupi, M; Lutz, T H; Maevskaya, A; Mager, M; Mahajan, S; Mahmood, S M; Maire, A; Majka, R D; Malaev, M; Maldonado Cervantes, I; Malinina, L; Mal'Kevich, D; Malzacher, P; Mamonov, A; Manko, V; Manso, F; Manzari, V; Mao, Y; Marchisone, M; Mareš, J; Margagliotti, G V; Margotti, A; Margutti, J; Marín, A; Markert, C; Marquard, M; Martin, N A; Martinengo, P; Martinez, J A L; Martínez, M I; Martínez García, G; Martinez Pedreira, M; Mas, A; Masciocchi, S; Masera, M; Masoni, A; Mastroserio, A; Mathis, A M; Matyja, A; Mayer, C; Mazer, J; Mazzilli, M; Mazzoni, M A; Meddi, F; Melikyan, Y; Menchaca-Rocha, A; Meninno, E; Mercado Pérez, J; Meres, M; Mhlanga, S; Miake, Y; Mieskolainen, M M; Mihaylov, D; Mikhaylov, K; Milano, L; Milosevic, J; Mischke, A; Mishra, A N; Miśkowiec, D; Mitra, J; Mitu, C M; Mohammadi, N; Mohanty, B; Montes, E; Moreira De Godoy, D A; Moreno, L A P; Moretto, S; Morreale, A; Morsch, A; Muccifora, V; Mudnic, E; Mühlheim, D; Muhuri, S; Mukherjee, M; Mulligan, J D; Munhoz, M G; Münning, K; Munzer, R H; Murakami, H; Murray, S; Musa, L; Musinsky, J; Myers, C J; Naik, B; Nair, R; Nandi, B K; Nania, R; Nappi, E; Naru, M U; Natal da Luz, H; Nattrass, C; Navarro, S R; Nayak, K; Nayak, R; Nayak, T K; Nazarenko, S; Nedosekin, A; Negrao De Oliveira, R A; Nellen, L; Nesbo, S V; Ng, F; Nicassio, M; Niculescu, M; Niedziela, J; Nielsen, B S; Nikolaev, S; Nikulin, S; Nikulin, V; Noferini, F; Nomokonov, P; Nooren, G; Noris, J C C; Norman, J; Nyanin, A; Nystrand, J; Oeschler, H; Oh, S; Ohlson, A; Okubo, T; Olah, L; Oleniacz, J; Oliveira Da Silva, A C; Oliver, M H; Onderwaater, J; Oppedisano, C; Orava, R; Oravec, M; Ortiz Velasquez, A; Oskarsson, A; Otwinowski, J; Oyama, K; Ozdemir, M; Pachmayer, Y; Pacik, V; Pagano, D; Pagano, P; Paić, G; Pal, S K; Palni, P; Pan, J; Pandey, A K; Panebianco, S; Papikyan, V; Pappalardo, G S; Pareek, P; Park, J; Park, W J; Parmar, S; Passfeld, A; Pathak, S P; Paticchio, V; Patra, R N; Paul, B; Pei, H; Peitzmann, T; Peng, X; Pereira, L G; Pereira Da Costa, H; Peresunko, D; Perez Lezama, E; Peskov, V; Pestov, Y; Petráček, V; Petrov, V; Petrovici, M; Petta, C; Pezzi, R P; Piano, S; Pikna, M; Pillot, P; Pimentel, L O D L; Pinazza, O; Pinsky, L; Piyarathna, D B; Płoskoń, M; Planinic, M; Pluta, J; Pochybova, S; Podesta-Lerma, P L M; Poghosyan, M G; Polichtchouk, B; Poljak, N; Poonsawat, W; Pop, A; Poppenborg, H; Porteboeuf-Houssais, S; Porter, J; Pospisil, J; Pozdniakov, V; Prasad, S K; Preghenella, R; Prino, F; Pruneau, C A; Pshenichnov, I; Puccio, M; Puddu, G; Pujahari, P; Punin, V; Putschke, J; Qvigstad, H; Rachevski, A; Raha, S; Rajput, S; Rak, J; Rakotozafindrabe, A; Ramello, L; Rami, F; Rana, D B; Raniwala, R; Raniwala, S; Räsänen, S S; Rascanu, B T; Rathee, D; Ratza, V; Ravasenga, I; Read, K F; Redlich, K; Rehman, A; Reichelt, P; Reidt, F; Ren, X; Renfordt, R; Reolon, A R; Reshetin, A; Reygers, K; Riabov, V; Ricci, R A; Richert, T; Richter, M; Riedler, P; Riegler, W; Riggi, F; Ristea, C; Rodríguez Cahuantzi, M; Røed, K; Rogochaya, E; Rohr, D; Röhrich, D; Rokita, P S; Ronchetti, F; Ronflette, L; Rosnet, P; Rossi, A; Rotondi, A; Roukoutakis, F; Roy, A; Roy, C; Roy, P; Rubio Montero, A J; Rui, R; Russo, R; Rustamov, A; Ryabinkin, E; Ryabov, Y; Rybicki, A; Saarinen, S; Sadhu, S; Sadovsky, S; Šafařík, K; Saha, S K; Sahlmuller, B; Sahoo, B; Sahoo, P; Sahoo, R; Sahoo, S; Sahu, P K; Saini, J; Sakai, S; Saleh, M A; Salzwedel, J; Sambyal, S; Samsonov, V; Sandoval, A; Sarkar, D; Sarkar, N; Sarma, P; Sas, M H P; Scapparone, E; Scarlassara, F; Scharenberg, R P; Scheid, H S; Schiaua, C; Schicker, R; Schmidt, C; Schmidt, H R; Schmidt, M O; Schmidt, M; Schukraft, J; Schutz, Y; Schwarz, K; Schweda, K; Scioli, G; Scomparin, E; Scott, R; Šefčík, M; Seger, J E; Sekiguchi, Y; Sekihata, D; Selyuzhenkov, I; Senosi, K; Senyukov, S; Serradilla, E; Sett, P; Sevcenco, A; Shabanov, A; Shabetai, A; Shadura, O; Shahoyan, R; Shangaraev, A; Sharma, A; Sharma, A; Sharma, M; Sharma, M; Sharma, N; Sheikh, A I; Shigaki, K; Shou, Q; Shtejer, K; Sibiriak, Y; Siddhanta, S; Sielewicz, K M; Siemiarczuk, T; Silvermyr, D; Silvestre, C; Simatovic, G; Simonetti, G; Singaraju, R; Singh, R; Singhal, V; Sinha, T; Sitar, B; Sitta, M; Skaali, T B; Slupecki, M; Smirnov, N; Snellings, R J M; Snellman, T W; Song, J; Song, M; Soramel, F; Sorensen, S; Sozzi, F; Spiriti, E; Sputowska, I; Srivastava, B K; Stachel, J; Stan, I; Stankus, P; Stenlund, E; Stiller, J H; Stocco, D; Strmen, P; Suaide, A A P; Sugitate, T; Suire, C; Suleymanov, M; Suljic, M; Sultanov, R; Šumbera, M; Sumowidagdo, S; Suzuki, K; Swain, S; Szabo, A; Szarka, I; Szczepankiewicz, A; Szymanski, M; Tabassam, U; Takahashi, J; Tambave, G J; Tanaka, N; Tarhini, M; Tariq, M; Tarzila, M G; Tauro, A; Tejeda Muñoz, G; Telesca, A; Terasaki, K; Terrevoli, C; Teyssier, B; Thakur, D; Thakur, S; Thomas, D; Tieulent, R; Tikhonov, A; Timmins, A R; Toia, A; Tripathy, S; Trogolo, S; Trombetta, G; Trubnikov, V; Trzaska, W H; Trzeciak, B A; Tsuji, T; Tumkin, A; Turrisi, R; Tveter, T S; Ullaland, K; Umaka, E N; Uras, A; Usai, G L; Utrobicic, A; Vala, M; Van Der Maarel, J; Van Hoorne, J W; van Leeuwen, M; Vanat, T; Vande Vyvre, P; Varga, D; Vargas, A; Vargyas, M; Varma, R; Vasileiou, M; Vasiliev, A; Vauthier, A; Vázquez Doce, O; Vechernin, V; Veen, A M; Velure, A; Vercellin, E; Vergara Limón, S; Vernet, R; Vértesi, R; Vickovic, L; Vigolo, S; Viinikainen, J; Vilakazi, Z; Villalobos Baillie, O; Villatoro Tello, A; Vinogradov, A; Vinogradov, L; Virgili, T; Vislavicius, V; Vodopyanov, A; Völkl, M A; Voloshin, K; Voloshin, S A; Volpe, G; von Haller, B; Vorobyev, I; Voscek, D; Vranic, D; Vrláková, J; Wagner, B; Wagner, J; Wang, H; Wang, M; Watanabe, D; Watanabe, Y; Weber, M; Weber, S G; Weiser, D F; Wessels, J P; Westerhoff, U; Whitehead, A M; Wiechula, J; Wikne, J; Wilk, G; Wilkinson, J; Willems, G A; Williams, M C S; Windelband, B; Witt, W E; Yalcin, S; Yang, P; Yano, S; Yin, Z; Yokoyama, H; Yoo, I-K; Yoon, J H; Yurchenko, V; Zaccolo, V; Zaman, A; Zampolli, C; Zanoli, H J C; Zaporozhets, S; Zardoshti, N; Zarochentsev, A; Závada, P; Zaviyalov, N; Zbroszczyk, H; Zhalov, M; Zhang, H; Zhang, X; Zhang, Y; Zhang, C; Zhang, Z; Zhao, C; Zhigareva, N; Zhou, D; Zhou, Y; Zhou, Z; Zhu, H; Zhu, J; Zhu, X; Zichichi, A; Zimmermann, A; Zimmermann, M B; Zimmermann, S; Zinovjev, G; Zmeskal, J

    2017-01-01

    The transverse momentum distributions of the strange and double-strange hyperon resonances ([Formula: see text], [Formula: see text]) produced in p-Pb collisions at [Formula: see text] TeV were measured in the rapidity range [Formula: see text] for event classes corresponding to different charged-particle multiplicity densities, [Formula: see text]d[Formula: see text]/d[Formula: see text]. The mean transverse momentum values are presented as a function of [Formula: see text]d[Formula: see text]/d[Formula: see text], as well as a function of the particle masses and compared with previous results on hyperon production. The integrated yield ratios of excited to ground-state hyperons are constant as a function of [Formula: see text]d[Formula: see text]/d[Formula: see text]. The equivalent ratios to pions exhibit an increase with [Formula: see text]d[Formula: see text]/d[Formula: see text], depending on their strangeness content.

  11. The importance of North Sea gas to European energy supply

    International Nuclear Information System (INIS)

    Probert, R.

    1992-01-01

    Natural gas can, of course, be transported over very long distances but, because of the economics of gas transmission, its impact is most often local. This has certainly been the case with North Sea gas, which has clearly contributed significantly to European energy supply and will continue to do so for some time to come. The historical importance of the discovery of gas in the North Sea has been that it has enabled natural gas industries to grow rapidly in North West Europe. Without North Sea gas and Dutch gas it is difficult to see how town gas would have been replaced in North West Europe. Certainly, a much smaller natural gas industry would have emerged. North Sea gas has inevitably had the greatest impact on gas markets in the countries of the European Community and this will remain the case in future. Nevertheless, it is inevitable that gas will, in future, flow across more national boundaries than in the past, and that North Sea gas will have an important part to play in meeting the Central European demand for competitively priced, secure supplies. This paper discusses the United Kingdom market for gas and future demand both in the United Kingdom and more widely in Europe. An examination of the availability of gas supplies from the North Sea suggests that it is unlikely that there will be a surplus of gas for export from the United Kingdom continental shelf. Norway will remain the main source of exports, with the Netherlands also in a strong position. Transportation and political aspects are also considered. (author)

  12. A Global Perspective on Drinking-Water and Sanitation Classification: An Evaluation of Census Content.

    Science.gov (United States)

    Yu, Weiyu; Wardrop, Nicola A; Bain, Robert E S; Lin, Yanzhao; Zhang, Ce; Wright, Jim A

    2016-01-01

    Following the recent expiry of the United Nations' 2015 Millennium Development Goals (MDGs), new international development agenda covering 2030 water, sanitation and hygiene (WASH) targets have been proposed, which imply new demands on data sources for monitoring relevant progress. This study evaluates drinking-water and sanitation classification systems from national census questionnaire content, based upon the most recent international policy changes, to examine national population census's ability to capture drinking-water and sanitation availability, safety, accessibility, and sustainability. In total, 247 censuses from 83 low income and lower-middle income countries were assessed using a scoring system, intended to assess harmonised water supply and sanitation classification systems for each census relative to the typology needed to monitor the proposed post-2015 indicators of WASH targets. The results signal a lack of international harmonisation and standardisation in census categorisation systems, especially concerning safety, accessibility, and sustainability of services in current census content. This suggests further refinements and harmonisation of future census content may be necessary to reflect ambitions for post-2015 monitoring.

  13. A Global Perspective on Drinking-Water and Sanitation Classification: An Evaluation of Census Content.

    Directory of Open Access Journals (Sweden)

    Weiyu Yu

    Full Text Available Following the recent expiry of the United Nations' 2015 Millennium Development Goals (MDGs, new international development agenda covering 2030 water, sanitation and hygiene (WASH targets have been proposed, which imply new demands on data sources for monitoring relevant progress. This study evaluates drinking-water and sanitation classification systems from national census questionnaire content, based upon the most recent international policy changes, to examine national population census's ability to capture drinking-water and sanitation availability, safety, accessibility, and sustainability. In total, 247 censuses from 83 low income and lower-middle income countries were assessed using a scoring system, intended to assess harmonised water supply and sanitation classification systems for each census relative to the typology needed to monitor the proposed post-2015 indicators of WASH targets. The results signal a lack of international harmonisation and standardisation in census categorisation systems, especially concerning safety, accessibility, and sustainability of services in current census content. This suggests further refinements and harmonisation of future census content may be necessary to reflect ambitions for post-2015 monitoring.

  14. Hard time to be parents? Sea urchin fishery shifts potential reproductive contribution of population onto the shoulders of the young adults.

    Science.gov (United States)

    Loi, Barbara; Guala, Ivan; Pires da Silva, Rodrigo; Brundu, Gianni; Baroli, Maura; Farina, Simone

    2017-01-01

    In Sardinia, as in other regions of the Mediterranean Sea, sustainable fisheries of the sea urchin Paracentrotus lividus have become a necessity. At harvesting sites, the systematic removal of large individuals (diameter ≥ 50 mm) seriously compromises the biological and ecological functions of sea urchin populations. Specifically, in this study, we compared the reproductive potential of the populations from Mediterranean coastal areas which have different levels of sea urchin fishing pressure. The areas were located at Su Pallosu Bay, where pressure is high and Tavolara-Punta Coda Cavallo, a marine protected area where sea urchin harvesting is low. Reproductive potential was estimated by calculating the gonadosomatic index (GSI) from June 2013 to May 2014 both for individuals of commercial size (diameter without spines, TD ≥ 50 mm) and the undersized ones with gonads (30 ≤ TD sea urchins than on their size. However, since population survival in the high-pressure zone is supported by the high density of undersized sea urchins between 30 and 50 mm, management measures should be addressed to maintain these sizes and to shed light on the source of the larval supply.

  15. Production of K[Formula: see text](892)[Formula: see text] and [Formula: see text](1020) in p-Pb collisions at [Formula: see text] = 5.02 TeV.

    Science.gov (United States)

    Adam, J; Adamová, D; Aggarwal, M M; Aglieri Rinella, G; Agnello, M; Agrawal, N; Ahammed, Z; Ahmad, S; Ahn, S U; Aiola, S; Akindinov, A; Alam, S N; Aleksandrov, D; Alessandro, B; Alexandre, D; Alfaro Molina, R; Alici, A; Alkin, A; Almaraz, J R M; Alme, J; Alt, T; Altinpinar, S; Altsybeev, I; Alves Garcia Prado, C; Andrei, C; Andronic, A; Anguelov, V; Antičić, T; Antinori, F; Antonioli, P; Aphecetche, L; Appelshäuser, H; Arcelli, S; Arnaldi, R; Arnold, O W; Arsene, I C; Arslandok, M; Audurier, B; Augustinus, A; Averbeck, R; Azmi, M D; Badalà, A; Baek, Y W; Bagnasco, S; Bailhache, R; Bala, R; Balasubramanian, S; Baldisseri, A; Baral, R C; Barbano, A M; Barbera, R; Barile, F; Barnaföldi, G G; Barnby, L S; Barret, V; Bartalini, P; Barth, K; Bartke, J; Bartsch, E; Basile, M; Bastid, N; Basu, S; Bathen, B; Batigne, G; Batista Camejo, A; Batyunya, B; Batzing, P C; Bearden, I G; Beck, H; Bedda, C; Behera, N K; Belikov, I; Bellini, F; Bello Martinez, H; Bellwied, R; Belmont, R; Belmont-Moreno, E; Belyaev, V; Benacek, P; Bencedi, G; Beole, S; Berceanu, I; Bercuci, A; Berdnikov, Y; Berenyi, D; Bertens, R A; Berzano, D; Betev, L; Bhasin, A; Bhat, I R; Bhati, A K; Bhattacharjee, B; Bhom, J; Bianchi, L; Bianchi, N; Bianchin, C; Bielčík, J; Bielčíková, J; Bilandzic, A; Biro, G; Biswas, R; Biswas, S; Bjelogrlic, S; Blair, J T; Blau, D; Blume, C; Bock, F; Bogdanov, A; Bøggild, H; Boldizsár, L; Bombara, M; Book, J; Borel, H; Borissov, A; Borri, M; Bossú, F; Botta, E; Bourjau, C; Braun-Munzinger, P; Bregant, M; Breitner, T; Broker, T A; Browning, T A; Broz, M; Brucken, E J; Bruna, E; Bruno, G E; Budnikov, D; Buesching, H; Bufalino, S; Buncic, P; Busch, O; Buthelezi, Z; Butt, J B; Buxton, J T; Caffarri, D; Cai, X; Caines, H; Calero Diaz, L; Caliva, A; Calvo Villar, E; Camerini, P; Carena, F; Carena, W; Carnesecchi, F; Castillo Castellanos, J; Castro, A J; Casula, E A R; Ceballos Sanchez, C; Cerello, P; Cerkala, J; Chang, B; Chapeland, S; Chartier, M; Charvet, J L; Chattopadhyay, S; Chattopadhyay, S; Chauvin, A; Chelnokov, V; Cherney, M; Cheshkov, C; Cheynis, B; Chibante Barroso, V; Chinellato, D D; Cho, S; Chochula, P; Choi, K; Chojnacki, M; Choudhury, S; Christakoglou, P; Christensen, C H; Christiansen, P; Chujo, T; Chung, S U; Cicalo, C; Cifarelli, L; Cindolo, F; Cleymans, J; Colamaria, F; Colella, D; Collu, A; Colocci, M; Conesa Balbastre, G; Conesa Del Valle, Z; Connors, M E; Contreras, J G; Cormier, T M; Corrales Morales, Y; Cortés Maldonado, I; Cortese, P; Cosentino, M R; Costa, F; Crochet, P; Cruz Albino, R; Cuautle, E; Cunqueiro, L; Dahms, T; Dainese, A; Danisch, M C; Danu, A; Das, D; Das, I; Das, S; Dash, A; Dash, S; De, S; De Caro, A; de Cataldo, G; de Conti, C; de Cuveland, J; De Falco, A; De Gruttola, D; De Marco, N; De Pasquale, S; Deisting, A; Deloff, A; Dénes, E; Deplano, C; Dhankher, P; Di Bari, D; Di Mauro, A; Di Nezza, P; Diaz Corchero, M A; Dietel, T; Dillenseger, P; Divià, R; Djuvsland, Ø; Dobrin, A; Domenicis Gimenez, D; Dönigus, B; Dordic, O; Drozhzhova, T; Dubey, A K; Dubla, A; Ducroux, L; Dupieux, P; Ehlers, R J; Elia, D; Endress, E; Engel, H; Epple, E; Erazmus, B; Erdemir, I; Erhardt, F; Espagnon, B; Estienne, M; Esumi, S; Eum, J; Evans, D; Evdokimov, S; Eyyubova, G; Fabbietti, L; Fabris, D; Faivre, J; Fantoni, A; Fasel, M; Feldkamp, L; Feliciello, A; Feofilov, G; Ferencei, J; Fernández Téllez, A; Ferreiro, E G; Ferretti, A; Festanti, A; Feuillard, V J G; Figiel, J; Figueredo, M A S; Filchagin, S; Finogeev, D; Fionda, F M; Fiore, E M; Fleck, M G; Floris, M; Foertsch, S; Foka, P; Fokin, S; Fragiacomo, E; Francescon, A; Frankenfeld, U; Fronze, G G; Fuchs, U; Furget, C; Furs, A; Fusco Girard, M; Gaardhøje, J J; Gagliardi, M; Gago, A M; Gallio, M; Gangadharan, D R; Ganoti, P; Gao, C; Garabatos, C; Garcia-Solis, E; Gargiulo, C; Gasik, P; Gauger, E F; Germain, M; Gheata, A; Gheata, M; Ghosh, P; Ghosh, S K; Gianotti, P; Giubellino, P; Giubilato, P; Gladysz-Dziadus, E; Glässel, P; Goméz Coral, D M; Gomez Ramirez, A; Gonzalez, V; González-Zamora, P; Gorbunov, S; Görlich, L; Gotovac, S; Grabski, V; Grachov, O A; Graczykowski, L K; Graham, K L; Grelli, A; Grigoras, A; Grigoras, C; Grigoriev, V; Grigoryan, A; Grigoryan, S; Grinyov, B; Grion, N; Gronefeld, J M; Grosse-Oetringhaus, J F; Grossiord, J-Y; Grosso, R; Guber, F; Guernane, R; Guerzoni, B; Gulbrandsen, K; Gunji, T; Gupta, A; Gupta, R; Haake, R; Haaland, Ø; Hadjidakis, C; Haiduc, M; Hamagaki, H; Hamar, G; Hamon, J C; Harris, J W; Harton, A; Hatzifotiadou, D; Hayashi, S; Heckel, S T; Hellbär, E; Helstrup, H; Herghelegiu, A; Herrera Corral, G; Hess, B A; Hetland, K F; Hillemanns, H; Hippolyte, B; Horak, D; Hosokawa, R; Hristov, P; Huang, M; Humanic, T J; Hussain, N; Hussain, T; Hutter, D; Hwang, D S; Ilkaev, R; Inaba, M; Incani, E; Ippolitov, M; Irfan, M; Ivanov, M; Ivanov, V; Izucheev, V; Jacazio, N; Jacobs, P M; Jadhav, M B; Jadlovska, S; Jadlovsky, J; Jahnke, C; Jakubowska, M J; Jang, H J; Janik, M A; Jayarathna, P H S Y; Jena, C; Jena, S; Jimenez Bustamante, R T; Jones, P G; Jusko, A; Kalinak, P; Kalweit, A; Kamin, J; Kang, J H; Kaplin, V; Kar, S; Karasu Uysal, A; Karavichev, O; Karavicheva, T; Karayan, L; Karpechev, E; Kebschull, U; Keidel, R; Keijdener, D L D; Keil, M; Mohisin Khan, M; Khan, P; Khan, S A; Khanzadeev, A; Kharlov, Y; Kileng, B; Kim, D W; Kim, D J; Kim, D; Kim, H; Kim, J S; Kim, M; Kim, M; Kim, S; Kim, T; Kirsch, S; Kisel, I; Kiselev, S; Kisiel, A; Kiss, G; Klay, J L; Klein, C; Klein, J; Klein-Bösing, C; Klewin, S; Kluge, A; Knichel, M L; Knospe, A G; Kobdaj, C; Kofarago, M; Kollegger, T; Kolojvari, A; Kondratiev, V; Kondratyeva, N; Kondratyuk, E; Konevskikh, A; Kopcik, M; Kostarakis, P; Kour, M; Kouzinopoulos, C; Kovalenko, O; Kovalenko, V; Kowalski, M; Koyithatta Meethaleveedu, G; Králik, I; Kravčáková, A; Kretz, M; Krivda, M; Krizek, F; Kryshen, E; Krzewicki, M; Kubera, A M; Kučera, V; Kuhn, C; Kuijer, P G; Kumar, A; Kumar, J; Kumar, L; Kumar, S; Kurashvili, P; Kurepin, A; Kurepin, A B; Kuryakin, A; Kweon, M J; Kwon, Y; La Pointe, S L; La Rocca, P; Ladron de Guevara, P; Lagana Fernandes, C; Lakomov, I; Langoy, R; Lara, C; Lardeux, A; Lattuca, A; Laudi, E; Lea, R; Leardini, L; Lee, G R; Lee, S; Lehas, F; Lemmon, R C; Lenti, V; Leogrande, E; León Monzón, I; León Vargas, H; Leoncino, M; Lévai, P; Li, S; Li, X; Lien, J; Lietava, R; Lindal, S; Lindenstruth, V; Lippmann, C; Lisa, M A; Ljunggren, H M; Lodato, D F; Loenne, P I; Loginov, V; Loizides, C; Lopez, X; López Torres, E; Lowe, A; Luettig, P; Lunardon, M; Luparello, G; Lutz, T H; Maevskaya, A; Mager, M; Mahajan, S; Mahmood, S M; Maire, A; Majka, R D; Malaev, M; Maldonado Cervantes, I; Malinina, L; Mal'Kevich, D; Malzacher, P; Mamonov, A; Manko, V; Manso, F; Manzari, V; Marchisone, M; Mareš, J; Margagliotti, G V; Margotti, A; Margutti, J; Marín, A; Markert, C; Marquard, M; Martin, N A; Martin Blanco, J; Martinengo, P; Martínez, M I; Martínez García, G; Martinez Pedreira, M; Mas, A; Masciocchi, S; Masera, M; Masoni, A; Massacrier, L; Mastroserio, A; Matyja, A; Mayer, C; Mazer, J; Mazzoni, M A; Mcdonald, D; Meddi, F; Melikyan, Y; Menchaca-Rocha, A; Meninno, E; Mercado Pérez, J; Meres, M; Miake, Y; Mieskolainen, M M; Mikhaylov, K; Milano, L; Milosevic, J; Minervini, L M; Mischke, A; Mishra, A N; Miśkowiec, D; Mitra, J; Mitu, C M; Mohammadi, N; Mohanty, B; Molnar, L; Montaño Zetina, L; Montes, E; Moreira De Godoy, D A; Moreno, L A P; Moretto, S; Morreale, A; Morsch, A; Muccifora, V; Mudnic, E; Mühlheim, D; Muhuri, S; Mukherjee, M; Mulligan, J D; Munhoz, M G; Munzer, R H; Murakami, H; Murray, S; Musa, L; Musinsky, J; Naik, B; Nair, R; Nandi, B K; Nania, R; Nappi, E; Naru, M U; Natal da Luz, H; Nattrass, C; Navarro, S R; Nayak, K; Nayak, R; Nayak, T K; Nazarenko, S; Nedosekin, A; Nellen, L; Ng, F; Nicassio, M; Niculescu, M; Niedziela, J; Nielsen, B S; Nikolaev, S; Nikulin, S; Nikulin, V; Noferini, F; Nomokonov, P; Nooren, G; Noris, J C C; Norman, J; Nyanin, A; Nystrand, J; Oeschler, H; Oh, S; Oh, S K; Ohlson, A; Okatan, A; Okubo, T; Olah, L; Oleniacz, J; Oliveira Da Silva, A C; Oliver, M H; Onderwaater, J; Oppedisano, C; Orava, R; Ortiz Velasquez, A; Oskarsson, A; Otwinowski, J; Oyama, K; Ozdemir, M; Pachmayer, Y; Pagano, P; Paić, G; Pal, S K; Pan, J; Pandey, A K; Papikyan, V; Pappalardo, G S; Pareek, P; Park, W J; Parmar, S; Passfeld, A; Paticchio, V; Patra, R N; Paul, B; Pei, H; Peitzmann, T; Pereira Da Costa, H; Peresunko, D; Pérez Lara, C E; Perez Lezama, E; Peskov, V; Pestov, Y; Petráček, V; Petrov, V; Petrovici, M; Petta, C; Piano, S; Pikna, M; Pillot, P; Pimentel, L O D L; Pinazza, O; Pinsky, L; Piyarathna, D B; Płoskoń, M; Planinic, M; Pluta, J; Pochybova, S; Podesta-Lerma, P L M; Poghosyan, M G; Polichtchouk, B; Poljak, N; Poonsawat, W; Pop, A; Porteboeuf-Houssais, S; Porter, J; Pospisil, J; Prasad, S K; Preghenella, R; Prino, F; Pruneau, C A; Pshenichnov, I; Puccio, M; Puddu, G; Pujahari, P; Punin, V; Putschke, J; Qvigstad, H; Rachevski, A; Raha, S; Rajput, S; Rak, J; Rakotozafindrabe, A; Ramello, L; Rami, F; Raniwala, R; Raniwala, S; Räsänen, S S; Rascanu, B T; Rathee, D; Read, K F; Redlich, K; Reed, R J; Rehman, A; Reichelt, P; Reidt, F; Ren, X; Renfordt, R; Reolon, A R; Reshetin, A; Revol, J-P; Reygers, K; Riabov, V; Ricci, R A; Richert, T; Richter, M; Riedler, P; Riegler, W; Riggi, F; Ristea, C; Rocco, E; Rodríguez Cahuantzi, M; Rodriguez Manso, A; Røed, K; Rogochaya, E; Rohr, D; Röhrich, D; Romita, R; Ronchetti, F; Ronflette, L; Rosnet, P; Rossi, A; Roukoutakis, F; Roy, A; Roy, C; Roy, P; Rubio Montero, A J; Rui, R; Russo, R; Ryabinkin, E; Ryabov, Y; Rybicki, A; Sadovsky, S; Šafařík, K; Sahlmuller, B; Sahoo, P; Sahoo, R; Sahoo, S; Sahu, P K; Saini, J; Sakai, S; Saleh, M A; Salzwedel, J; Sambyal, S; Samsonov, V; Šándor, L; Sandoval, A; Sano, M; Sarkar, D; Sarma, P; Scapparone, E; Scarlassara, F; Schiaua, C; Schicker, R; Schmidt, C; Schmidt, H R; Schuchmann, S; Schukraft, J; Schulc, M; Schuster, T; Schutz, Y; Schwarz, K; Schweda, K; Scioli, G; Scomparin, E; Scott, R; Šefčík, M; Seger, J E; Sekiguchi, Y; Sekihata, D; Selyuzhenkov, I; Senosi, K; Senyukov, S; Serradilla, E; Sevcenco, A; Shabanov, A; Shabetai, A; Shadura, O; Shahoyan, R; Shangaraev, A; Sharma, A; Sharma, M; Sharma, M; Sharma, N; Shigaki, K; Shtejer, K; Sibiriak, Y; Siddhanta, S; Sielewicz, K M; Siemiarczuk, T; Silvermyr, D; Silvestre, C; Simatovic, G; Simonetti, G; Singaraju, R; Singh, R; Singha, S; Singhal, V; Sinha, B C; Sinha, T; Sitar, B; Sitta, M; Skaali, T B; Slupecki, M; Smirnov, N; Snellings, R J M; Snellman, T W; Søgaard, C; Song, J; Song, M; Song, Z; Soramel, F; Sorensen, S; Souza, R D de; Sozzi, F; Spacek, M; Spiriti, E; Sputowska, I; Spyropoulou-Stassinaki, M; Stachel, J; Stan, I; Stankus, P; Stefanek, G; Stenlund, E; Steyn, G; Stiller, J H; Stocco, D; Strmen, P; Suaide, A A P; Sugitate, T; Suire, C; Suleymanov, M; Suljic, M; Sultanov, R; Šumbera, M; Szabo, A; Szanto de Toledo, A; Szarka, I; Szczepankiewicz, A; Szymanski, M; Tabassam, U; Takahashi, J; Tambave, G J; Tanaka, N; Tangaro, M A; Tarhini, M; Tariq, M; Tarzila, M G; Tauro, A; Tejeda Muñoz, G; Telesca, A; Terasaki, K; Terrevoli, C; Teyssier, B; Thäder, J; Thomas, D; Tieulent, R; Timmins, A R; Toia, A; Trogolo, S; Trombetta, G; Trubnikov, V; Trzaska, W H; Tsuji, T; Tumkin, A; Turrisi, R; Tveter, T S; Ullaland, K; Uras, A; Usai, G L; Utrobicic, A; Vajzer, M; Vala, M; Valencia Palomo, L; Vallero, S; Van Der Maarel, J; Van Hoorne, J W; van Leeuwen, M; Vanat, T; Vande Vyvre, P; Varga, D; Vargas, A; Vargyas, M; Varma, R; Vasileiou, M; Vasiliev, A; Vauthier, A; Vechernin, V; Veen, A M; Veldhoen, M; Velure, A; Venaruzzo, M; Vercellin, E; Vergara Limón, S; Vernet, R; Verweij, M; Vickovic, L; Viesti, G; Viinikainen, J; Vilakazi, Z; Villalobos Baillie, O; Villatoro Tello, A; Vinogradov, A; Vinogradov, L; Vinogradov, Y; Virgili, T; Vislavicius, V; Viyogi, Y P; Vodopyanov, A; Völkl, M A; Voloshin, K; Voloshin, S A; Volpe, G; von Haller, B; Vorobyev, I; Vranic, D; Vrláková, J; Vulpescu, B; Wagner, B; Wagner, J; Wang, H; Wang, M; Watanabe, D; Watanabe, Y; Weber, M; Weber, S G; Weiser, D F; Wessels, J P; Westerhoff, U; Whitehead, A M; Wiechula, J; Wikne, J; Wilk, G; Wilkinson, J; Williams, M C S; Windelband, B; Winn, M; Yang, H; Yang, P; Yano, S; Yasar, C; Yin, Z; Yokoyama, H; Yoo, I-K; Yoon, J H; Yurchenko, V; Yushmanov, I; Zaborowska, A; Zaccolo, V; Zaman, A; Zampolli, C; Zanoli, H J C; Zaporozhets, S; Zardoshti, N; Zarochentsev, A; Závada, P; Zaviyalov, N; Zbroszczyk, H; Zgura, I S; Zhalov, M; Zhang, H; Zhang, X; Zhang, Y; Zhang, C; Zhang, Z; Zhao, C; Zhigareva, N; Zhou, D; Zhou, Y; Zhou, Z; Zhu, H; Zhu, J; Zichichi, A; Zimmermann, A; Zimmermann, M B; Zinovjev, G; Zyzak, M

    The production of K[Formula: see text](892)[Formula: see text] and [Formula: see text](1020) mesons has been measured in p-Pb collisions at [Formula: see text][Formula: see text] 5.02 TeV. K[Formula: see text] and [Formula: see text] are reconstructed via their decay into charged hadrons with the ALICE detector in the rapidity range [Formula: see text]. The transverse momentum spectra, measured as a function of the multiplicity, have a p[Formula: see text] range from 0 to 15 GeV/ c for K[Formula: see text] and from 0.3 to 21 GeV/ c for [Formula: see text]. Integrated yields, mean transverse momenta and particle ratios are reported and compared with results in pp collisions at [Formula: see text][Formula: see text] 7 TeV and Pb-Pb collisions at [Formula: see text][Formula: see text] 2.76 TeV. In Pb-Pb and p-Pb collisions, K[Formula: see text] and [Formula: see text] probe the hadronic phase of the system and contribute to the study of particle formation mechanisms by comparison with other identified hadrons. For this purpose, the mean transverse momenta and the differential proton-to-[Formula: see text] ratio are discussed as a function of the multiplicity of the event. The short-lived K[Formula: see text] is measured to investigate re-scattering effects, believed to be related to the size of the system and to the lifetime of the hadronic phase.

  16. Allegheny County Jail Daily Census

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — A daily census of the inmates at the Allegheny County Jail (ACJ). Includes gender, race, age at booking, and current age. The records for each month contain a...

  17. 76 FR 13980 - Proposed Information Collection; Comment Request; 2012 Economic Census Covering the Information...

    Science.gov (United States)

    2011-03-15

    ... essential information for government, business, and the general public. Economic data are the Census Bureau... Economic Census Covering the Information, etc. AGENCY: U.S. Census Bureau, Commerce. ACTION: Notice... ). SUPPLEMENTARY INFORMATION: I. Abstract The economic census, conducted under authority of Title 13, United States...

  18. Short-term acute hypercapnia affects cellular responses to trace metals in the hard clams Mercenaria mercenaria.

    Science.gov (United States)

    Ivanina, Anna V; Beniash, Elia; Etzkorn, Markus; Meyers, Tiffany B; Ringwood, Amy H; Sokolova, Inna M

    2013-09-15

    Estuarine and coastal habitats experience large fluctuations of environmental factors such as temperature, salinity, partial pressure of CO2 ( [Formula: see text] ) and pH; they also serve as the natural sinks for trace metals. Benthic filter-feeding organisms such as bivalves are exposed to the elevated concentrations of metals in estuarine water and sediments that can strongly affect their physiology. The effects of metals on estuarine organisms may be exacerbated by other environmental factors. Thus, a decrease in pH caused by high [Formula: see text] (hypercapnia) can modulate the effects of trace metals by affecting metal bioavailability, accumulation or binding. To better understand the cellular mechanisms of interactions between [Formula: see text] and trace metals in marine bivalves, we exposed isolated mantle cells of the hard clams (Mercenaria mercenaria) to different levels of [Formula: see text] (0.05, 1.52 and 3.01 kPa) and two major trace metal pollutants - cadmium (Cd) and copper (Cu). Elevated [Formula: see text] resulted in a decrease in intracellular pH (pHi) of the isolated mantle cells from 7.8 to 7.4. Elevated [Formula: see text] significantly but differently affected the trace metal accumulation by the cells. Cd uptake was suppressed at elevated [Formula: see text] levels while Cu accumulation has greatly accelerated under hypercapnic conditions. Interestingly, at higher extracellular Cd levels, labile intracellular Cd(2+) concentration remained the same, while intracellular levels of free Zn(2+) increased suggesting that Cd(2+) substitutes bound Zn(2+) in these cells. In contrast, Cu exposure did not affect intracellular Zn(2+) but led to a profound increase in the intracellular levels of labile Cu(2+) and Fe(2+). An increase in the extracellular concentrations of Cd and Cu led to the elevated production of reactive oxygen species under the normocapnic conditions (0.05 kPa [Formula: see text] ); surprisingly, this effect was mitigated in

  19. International and internal migration measured from the School Census in England.

    Science.gov (United States)

    Simpson, Ludi; Marquis, Naomi; Jivraj, Stephen

    2010-01-01

    The School Census is the only regularly updated dataset covering almost all of the population of a specific age, which records changes of address along with ethnicity and some family economic circumstances. It can be used to measure internal and international family migration as shown in this report. The School Census is suited to identify and quantify new local migration streams between censuses, successfully identifying the local distribution of Eastern European immigration in the decade since 2000. The measures do not provide a complete measure of migration, either internally or internationally. The exclusion of those outside the state school system means that internal migration is under-estimated, and international migration is approximately measured. The advantages of the School Census are its frequent updates, its fine geographical information, and its indicators of ethnicity and low family income, which powerfully complement other sources.

  20. China Dimensions Data Collection: China County-Level Data on Population (Census) and Agriculture, Keyed to 1:1M GIS Map

    Data.gov (United States)

    National Aeronautics and Space Administration — China County-Level Data on Population (Census) and Agriculture, Keyed To 1:1M GIS Map consists of census, agricultural economic, and boundary data for the...

  1. New approaches for air-sea fluxes in the Southern Ocean

    CSIR Research Space (South Africa)

    Gille, S

    2016-05-01

    Full Text Available Air-sea exchanges in the Southern Ocean of momentum, heat, freshwater, carbon dioxide, and other gases are not well documented because fluxes are sparsely sampled (see Figure 1) and because high winds, high sea state, and lack of calibration...

  2. Observation of [Formula: see text] and [Formula: see text] decays.

    Science.gov (United States)

    Aaij, R; Adeva, B; Adinolfi, M; Ajaltouni, Z; Akar, S; Albrecht, J; Alessio, F; Alexander, M; Ali, S; Alkhazov, G; Alvarez Cartelle, P; Alves, A A; Amato, S; Amerio, S; Amhis, Y; An, L; Anderlini, L; Andreassi, G; Andreotti, M; Andrews, J E; Appleby, R B; Archilli, F; d'Argent, P; Arnau Romeu, J; Artamonov, A; Artuso, M; Aslanides, E; Auriemma, G; Baalouch, M; Babuschkin, I; Bachmann, S; Back, J J; Badalov, A; Baesso, C; Baker, S; Baldini, W; Barlow, R J; Barschel, C; Barsuk, S; Barter, W; Baszczyk, M; Batozskaya, V; Batsukh, B; Battista, V; Bay, A; Beaucourt, L; Beddow, J; Bedeschi, F; Bediaga, I; Bel, L J; Bellee, V; Belloli, N; Belous, K; Belyaev, I; Ben-Haim, E; Bencivenni, G; Benson, S; Benton, J; Berezhnoy, A; Bernet, R; Bertolin, A; Betancourt, C; Betti, F; Bettler, M-O; van Beuzekom, M; Bezshyiko, Ia; Bifani, S; Billoir, P; Bird, T; Birnkraut, A; Bitadze, A; Bizzeti, A; Blake, T; Blanc, F; Blouw, J; Blusk, S; Bocci, V; Boettcher, T; Bondar, A; Bondar, N; Bonivento, W; Bordyuzhin, I; Borgheresi, A; Borghi, S; Borisyak, M; Borsato, M; Bossu, F; Boubdir, M; Bowcock, T J V; Bowen, E; Bozzi, C; Braun, S; Britsch, M; Britton, T; Brodzicka, J; Buchanan, E; Burr, C; Bursche, A; Buytaert, J; Cadeddu, S; Calabrese, R; Calvi, M; Calvo Gomez, M; Camboni, A; Campana, P; Campora Perez, D H; Capriotti, L; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carniti, P; Carson, L; Carvalho Akiba, K; Casse, G; Cassina, L; Castillo Garcia, L; Cattaneo, M; Cauet, Ch; Cavallero, G; Cenci, R; Charles, M; Charpentier, Ph; Chatzikonstantinidis, G; Chefdeville, M; Chen, S; Cheung, S-F; Chobanova, V; Chrzaszcz, M; Cid Vidal, X; Ciezarek, G; Clarke, P E L; Clemencic, M; Cliff, H V; Closier, J; Coco, V; Cogan, J; Cogneras, E; Cogoni, V; Cojocariu, L; Collazuol, G; Collins, P; Comerma-Montells, A; Contu, A; Cook, A; Coombs, G; Coquereau, S; Corti, G; Corvo, M; Costa Sobral, C M; Couturier, B; Cowan, G A; Craik, D C; Crocombe, A; Cruz Torres, M; Cunliffe, S; Currie, R; D'Ambrosio, C; Da Cunha Marinho, F; Dall'Occo, E; Dalseno, J; David, P N Y; Davis, A; De Aguiar Francisco, O; De Bruyn, K; De Capua, S; De Cian, M; De Miranda, J M; De Paula, L; De Serio, M; De Simone, P; Dean, C-T; Decamp, D; Deckenhoff, M; Del Buono, L; Demmer, M; Dendek, A; Derkach, D; Deschamps, O; Dettori, F; Dey, B; Di Canto, A; Dijkstra, H; Dordei, F; Dorigo, M; Dosil Suárez, A; Dovbnya, A; Dreimanis, K; Dufour, L; Dujany, G; Dungs, K; Durante, P; Dzhelyadin, R; Dziurda, A; Dzyuba, A; Déléage, N; Easo, S; Ebert, M; Egede, U; Egorychev, V; Eidelman, S; Eisenhardt, S; Eitschberger, U; Ekelhof, R; Eklund, L; Ely, S; Esen, S; Evans, H M; Evans, T; Falabella, A; Farley, N; Farry, S; Fay, R; Fazzini, D; Ferguson, D; Fernandez Prieto, A; Ferrari, F; Ferreira Rodrigues, F; Ferro-Luzzi, M; Filippov, S; Fini, R A; Fiore, M; Fiorini, M; Firlej, M; Fitzpatrick, C; Fiutowski, T; Fleuret, F; Fohl, K; Fontana, M; Fontanelli, F; Forshaw, D C; Forty, R; Franco Lima, V; Frank, M; Frei, C; Fu, J; Furfaro, E; Färber, C; Gallas Torreira, A; Galli, D; Gallorini, S; Gambetta, S; Gandelman, M; Gandini, P; Gao, Y; Garcia Martin, L M; García Pardiñas, J; Garra Tico, J; Garrido, L; Garsed, P J; Gascon, D; Gaspar, C; Gavardi, L; Gazzoni, G; Gerick, D; Gersabeck, E; Gersabeck, M; Gershon, T; Ghez, Ph; Gianì, S; Gibson, V; Girard, O G; Giubega, L; Gizdov, K; Gligorov, V V; Golubkov, D; Golutvin, A; Gomes, A; Gorelov, I V; Gotti, C; Govorkova, E; Grabalosa Gándara, M; Graciani Diaz, R; Granado Cardoso, L A; Graugés, E; Graverini, E; Graziani, G; Grecu, A; Griffith, P; Grillo, L; Gruberg Cazon, B R; Grünberg, O; Gushchin, E; Guz, Yu; Gys, T; Göbel, C; Hadavizadeh, T; Hadjivasiliou, C; Haefeli, G; Haen, C; Haines, S C; Hall, S; Hamilton, B; Han, X; Hansmann-Menzemer, S; Harnew, N; Harnew, S T; Harrison, J; Hatch, M; He, J; Head, T; Heister, A; Hennessy, K; Henrard, P; Henry, L; Hernando Morata, J A; van Herwijnen, E; Heß, M; Hicheur, A; Hill, D; Hombach, C; Hopchev, H; Hulsbergen, W; Humair, T; Hushchyn, M; Hussain, N; Hutchcroft, D; Idzik, M; Ilten, P; Jacobsson, R; Jaeger, A; Jalocha, J; Jans, E; Jawahery, A; Jiang, F; John, M; Johnson, D; Jones, C R; Joram, C; Jost, B; Jurik, N; Kandybei, S; Kanso, W; Karacson, M; Kariuki, J M; Karodia, S; Kecke, M; Kelsey, M; Kenyon, I R; Kenzie, M; Ketel, T; Khairullin, E; Khanji, B; Khurewathanakul, C; Kirn, T; Klaver, S; Klimaszewski, K; Koliiev, S; Kolpin, M; Komarov, I; Koopman, R F; Koppenburg, P; Kosmyntseva, A; Kozachuk, A; Kozeiha, M; Kravchuk, L; Kreplin, K; Kreps, M; Krokovny, P; Kruse, F; Krzemien, W; Kucewicz, W; Kucharczyk, M; Kudryavtsev, V; Kuonen, A K; Kurek, K; Kvaratskheliya, T; Lacarrere, D; Lafferty, G; Lai, A; Lanfranchi, G; Langenbruch, C; Latham, T; Lazzeroni, C; Le Gac, R; van Leerdam, J; Lees, J-P; Leflat, A; Lefrançois, J; Lefèvre, R; Lemaitre, F; Lemos Cid, E; Leroy, O; Lesiak, T; Leverington, B; Li, Y; Likhomanenko, T; Lindner, R; Linn, C; Lionetto, F; Liu, B; Liu, X; Loh, D; Longstaff, I; Lopes, J H; Lucchesi, D; Lucio Martinez, M; Luo, H; Lupato, A; Luppi, E; Lupton, O; Lusiani, A; Lyu, X; Machefert, F; Maciuc, F; Maev, O; Maguire, K; Malde, S; Malinin, A; Maltsev, T; Manca, G; Mancinelli, G; Manning, P; Maratas, J; Marchand, J F; Marconi, U; Marin Benito, C; Marino, P; Marks, J; Martellotti, G; Martin, M; Martinelli, M; Martinez Santos, D; Martinez Vidal, F; Martins Tostes, D; Massacrier, L M; Massafferri, A; Matev, R; Mathad, A; Mathe, Z; Matteuzzi, C; Mauri, A; Maurin, B; Mazurov, A; McCann, M; McCarthy, J; McNab, A; McNulty, R; Meadows, B; Meier, F; Meissner, M; Melnychuk, D; Merk, M; Merli, A; Michielin, E; Milanes, D A; Minard, M-N; Mitzel, D S; Mogini, A; Molina Rodriguez, J; Monroy, I A; Monteil, S; Morandin, M; Morawski, P; Mordà, A; Morello, M J; Moron, J; Morris, A B; Mountain, R; Muheim, F; Mulder, M; Mussini, M; Müller, D; Müller, J; Müller, K; Müller, V; Naik, P; Nakada, T; Nandakumar, R; Nandi, A; Nasteva, I; Needham, M; Neri, N; Neubert, S; Neufeld, N; Neuner, M; Nguyen, A D; Nguyen, T D; Nguyen-Mau, C; Nieswand, S; Niet, R; Nikitin, N; Nikodem, T; Novoselov, A; O'Hanlon, D P; Oblakowska-Mucha, A; Obraztsov, V; Ogilvy, S; Oldeman, R; Onderwater, C J G; Otalora Goicochea, J M; Otto, A; Owen, P; Oyanguren, A; Pais, P R; Palano, A; Palombo, F; Palutan, M; Panman, J; Papanestis, A; Pappagallo, M; Pappalardo, L L; Parker, W; Parkes, C; Passaleva, G; Pastore, A; Patel, G D; Patel, M; Patrignani, C; Pearce, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perret, P; Pescatore, L; Petridis, K; Petrolini, A; Petrov, A; Petruzzo, M; Picatoste Olloqui, E; Pietrzyk, B; Pikies, M; Pinci, D; Pistone, A; Piucci, A; Playfer, S; Plo Casasus, M; Poikela, T; Polci, F; Poluektov, A; Polyakov, I; Polycarpo, E; Pomery, G J; Popov, A; Popov, D; Popovici, B; Poslavskii, S; Potterat, C; Price, E; Price, J D; Prisciandaro, J; Pritchard, A; Prouve, C; Pugatch, V; Puig Navarro, A; Punzi, G; Qian, W; Quagliani, R; Rachwal, B; Rademacker, J H; Rama, M; Ramos Pernas, M; Rangel, M S; Raniuk, I; Ratnikov, F; Raven, G; Redi, F; Reichert, S; Dos Reis, A C; Remon Alepuz, C; Renaudin, V; Ricciardi, S; Richards, S; Rihl, M; Rinnert, K; Rives Molina, V; Robbe, P; Rodrigues, A B; Rodrigues, E; Rodriguez Lopez, J A; Rodriguez Perez, P; Rogozhnikov, A; Roiser, S; Rollings, A; Romanovskiy, V; Romero Vidal, A; Ronayne, J W; Rotondo, M; Rudolph, M S; Ruf, T; Ruiz Valls, P; Saborido Silva, J J; Sadykhov, E; Sagidova, N; Saitta, B; Salustino Guimaraes, V; Sanchez Mayordomo, C; Sanmartin Sedes, B; Santacesaria, R; Santamarina Rios, C; Santimaria, M; Santovetti, E; Sarti, A; Satriano, C; Satta, A; Saunders, D M; Savrina, D; Schael, S; Schellenberg, M; Schiller, M; Schindler, H; Schlupp, M; Schmelling, M; Schmelzer, T; Schmidt, B; Schneider, O; Schopper, A; Schubert, K; Schubiger, M; Schune, M-H; Schwemmer, R; Sciascia, B; Sciubba, A; Semennikov, A; Sergi, A; Serra, N; Serrano, J; Sestini, L; Seyfert, P; Shapkin, M; Shapoval, I; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, V; Siddi, B G; Silva Coutinho, R; Silva de Oliveira, L; Simi, G; Simone, S; Sirendi, M; Skidmore, N; Skwarnicki, T; Smith, E; Smith, I T; Smith, J; Smith, M; Snoek, H; Sokoloff, M D; Soler, F J P; Souza De Paula, B; Spaan, B; Spradlin, P; Sridharan, S; Stagni, F; Stahl, M; Stahl, S; Stefko, P; Stefkova, S; Steinkamp, O; Stemmle, S; Stenyakin, O; Stevenson, S; Stoica, S; Stone, S; Storaci, B; Stracka, S; Straticiuc, M; Straumann, U; Sun, L; Sutcliffe, W; Swientek, K; Syropoulos, V; Szczekowski, M; Szumlak, T; T'Jampens, S; Tayduganov, A; Tekampe, T; Tellarini, G; Teubert, F; Thomas, E; van Tilburg, J; Tilley, M J; Tisserand, V; Tobin, M; Tolk, S; Tomassetti, L; Tonelli, D; Topp-Joergensen, S; Toriello, F; Tournefier, E; Tourneur, S; Trabelsi, K; Traill, M; Tran, M T; Tresch, M; Trisovic, A; Tsaregorodtsev, A; Tsopelas, P; Tully, A; Tuning, N; Ukleja, A; Ustyuzhanin, A; Uwer, U; Vacca, C; Vagnoni, V; Valassi, A; Valat, S; Valenti, G; Vallier, A; Vazquez Gomez, R; Vazquez Regueiro, P; Vecchi, S; van Veghel, M; Velthuis, J J; Veltri, M; Veneziano, G; Venkateswaran, A; Vernet, M; Vesterinen, M; Viaud, B; Vieira, D; Vieites Diaz, M; Viemann, H; Vilasis-Cardona, X; Vitti, M; Volkov, V; Vollhardt, A; Voneki, B; Vorobyev, A; Vorobyev, V; Voß, C; de Vries, J A; Vázquez Sierra, C; Waldi, R; Wallace, C; Wallace, R; Walsh, J; Wang, J; Ward, D R; Wark, H M; Watson, N K; Websdale, D; Weiden, A; Whitehead, M; Wicht, J; Wilkinson, G; Wilkinson, M; Williams, M; Williams, M P; Williams, M; Williams, T; Wilson, F F; Wimberley, J; Wishahi, J; Wislicki, W; Witek, M; Wormser, G; Wotton, S A; Wraight, K; Wyllie, K; Xie, Y; Xing, Z; Xu, Z; Yang, Z; Yin, H; Yu, J; Yuan, X; Yushchenko, O; Zarebski, K A; Zavertyaev, M; Zhang, L; Zhang, Y; Zhang, Y; Zhelezov, A; Zheng, Y; Zhokhov, A; Zhu, X; Zhukov, V; Zucchelli, S

    2017-01-01

    The decays [Formula: see text] and [Formula: see text] are observed for the first time using a data sample corresponding to an integrated luminosity of 3.0 fb[Formula: see text], collected by the LHCb experiment in proton-proton collisions at the centre-of-mass energies of 7 and 8[Formula: see text]. The branching fractions relative to that of [Formula: see text] are measured to be [Formula: see text]where the first uncertainties are statistical and the second are systematic.

  3. Simbol-X: Imaging The Hard X-ray Sky with Unprecedented Spatial Resolution and Sensitivity

    Science.gov (United States)

    Tagliaferri, Gianpiero; Simbol-X Joint Scientific Mission Group

    2009-01-01

    Simbol-X is a hard X-ray mission, with imaging capability in the 0.5-80 keV range. It is based on a collaboration between the French and Italian space agencies with participation of German laboratories. The launch is foreseen in late 2014. It relies on a formation flight concept, with two satellites carrying one the mirror module and the other one the focal plane detectors. The mirrors will have a 20 m focal length, while the two focal plane detectors will be put one on top of the other one. This combination will provide over two orders of magnitude improvement in angular resolution and sensitivity in the hard X-ray range with respect to non-focusing techniques. The Simbol-X revolutionary instrumental capabilities will allow us to elucidate outstanding questions in high energy astrophysics such as those related to black-holes accretion physics and census, and to particle acceleration mechanisms. We will give an overall description of the mission characteristics, performances and scientific objectives.

  4. Measurement of [Formula: see text] polarisation in [Formula: see text] collisions at [Formula: see text] = 7 TeV.

    Science.gov (United States)

    Aaij, R; Adeva, B; Adinolfi, M; Affolder, A; Ajaltouni, Z; Albrecht, J; Alessio, F; Alexander, M; Ali, S; Alkhazov, G; Alvarez Cartelle, P; Alves, A A; Amato, S; Amerio, S; Amhis, Y; An, L; Anderlini, L; Anderson, J; Andreassen, R; Andreotti, M; Andrews, J E; Appleby, R B; Aquines Gutierrez, O; Archilli, F; Artamonov, A; Artuso, M; Aslanides, E; Auriemma, G; Baalouch, M; Bachmann, S; Back, J J; Badalov, A; Balagura, V; Baldini, W; Barlow, R J; Barschel, C; Barsuk, S; Barter, W; Batozskaya, V; Bauer, Th; Bay, A; Beddow, J; Bedeschi, F; Bediaga, I; Belogurov, S; Belous, K; Belyaev, I; Ben-Haim, E; Bencivenni, G; Benson, S; Benton, J; Berezhnoy, A; Bernet, R; Bettler, M-O; van Beuzekom, M; Bien, A; Bifani, S; Bird, T; Bizzeti, A; Bjørnstad, P M; Blake, T; Blanc, F; Blouw, J; Blusk, S; Bocci, V; Bondar, A; Bondar, N; Bonivento, W; Borghi, S; Borgia, A; Borsato, M; Bowcock, T J V; Bowen, E; Bozzi, C; Brambach, T; van den Brand, J; Bressieux, J; Brett, D; Britsch, M; Britton, T; Brook, N H; Brown, H; Bursche, A; Busetto, G; Buytaert, J; Cadeddu, S; Calabrese, R; Callot, O; Calvi, M; Calvo Gomez, M; Camboni, A; Campana, P; Campora Perez, D; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carranza-Mejia, H; Carson, L; Carvalho Akiba, K; Casse, G; Cassina, L; Castillo Garcia, L; Cattaneo, M; Cauet, Ch; Cenci, R; Charles, M; Charpentier, Ph; Cheung, S-F; Chiapolini, N; Chrzaszcz, M; Ciba, K; Cid Vidal, X; Ciezarek, G; Clarke, P E L; Clemencic, M; Cliff, H V; Closier, J; Coca, C; Coco, V; Cogan, J; Cogneras, E; Collins, P; Comerma-Montells, A; Contu, A; Cook, A; Coombes, M; Coquereau, S; Corti, G; Corvo, M; Counts, I; Couturier, B; Cowan, G A; Craik, D C; Cruz Torres, M; Cunliffe, S; Currie, R; D'Ambrosio, C; Dalseno, J; David, P; David, P N Y; Davis, A; De Bruyn, K; De Capua, S; De Cian, M; De Miranda, J M; De Paula, L; De Silva, W; De Simone, P; Decamp, D; Deckenhoff, M; Del Buono, L; Déléage, N; Derkach, D; Deschamps, O; Dettori, F; Di Canto, A; Dijkstra, H; Donleavy, S; Dordei, F; Dorigo, M; Dosil Suárez, A; Dossett, D; Dovbnya, A; Dupertuis, F; Durante, P; Dzhelyadin, R; Dziurda, A; Dzyuba, A; Easo, S; Egede, U; Egorychev, V; Eidelman, S; Eisenhardt, S; Eitschberger, U; Ekelhof, R; Eklund, L; El Rifai, I; Elsasser, Ch; Esen, S; Evans, T; Falabella, A; Färber, C; Farinelli, C; Farry, S; Ferguson, D; Fernandez Albor, V; Ferreira Rodrigues, F; Ferro-Luzzi, M; Filippov, S; Fiore, M; Fiorini, M; Firlej, M; Fitzpatrick, C; Fiutowski, T; Fontana, M; Fontanelli, F; Forty, R; Francisco, O; Frank, M; Frei, C; Frosini, M; Fu, J; Furfaro, E; Gallas Torreira, A; Galli, D; Gandelman, M; Gandini, P; Gao, Y; Garofoli, J; Garra Tico, J; Garrido, L; Gaspar, C; Gauld, R; Gavardi, L; Gersabeck, E; Gersabeck, M; Gershon, T; Ghez, Ph; Gianelle, A; Giani, S; Gibson, V; Giubega, L; Gligorov, V V; Göbel, C; Golubkov, D; Golutvin, A; Gomes, A; Gordon, H; Gotti, C; Grabalosa Gándara, M; Graciani Diaz, R; Granado Cardoso, L A; Graugés, E; Graziani, G; Grecu, A; Greening, E; Gregson, S; Griffith, P; Grillo, L; Grünberg, O; Gui, B; Gushchin, E; Guz, Yu; Gys, T; Hadjivasiliou, C; Haefeli, G; Haen, C; Haines, S C; Hall, S; Hamilton, B; Hampson, T; Han, X; Hansmann-Menzemer, S; Harnew, N; Harnew, S T; Harrison, J; Hartmann, T; He, J; Head, T; Heijne, V; Hennessy, K; Henrard, P; Henry, L; Hernando Morata, J A; van Herwijnen, E; Heß, M; Hicheur, A; Hill, D; Hoballah, M; Hombach, C; Hulsbergen, W; Hunt, P; Hussain, N; Hutchcroft, D; Hynds, D; Iakovenko, V; Idzik, M; Ilten, P; Jacobsson, R; Jaeger, A; Jalocha, J; Jans, E; Jaton, P; Jawahery, A; Jezabek, M; Jing, F; John, M; Johnson, D; Jones, C R; Joram, C; Jost, B; Jurik, N; Kaballo, M; Kandybei, S; Kanso, W; Karacson, M; Karbach, T M; Kelsey, M; Kenyon, I R; Ketel, T; Khanji, B; Khurewathanakul, C; Klaver, S; Kochebina, O; Kolpin, M; Komarov, I; Koopman, R F; Koppenburg, P; Korolev, M; Kozlinskiy, A; Kravchuk, L; Kreplin, K; Kreps, M; Krocker, G; Krokovny, P; Kruse, F; Kucharczyk, M; Kudryavtsev, V; Kurek, K; Kvaratskheliya, T; La Thi, V N; Lacarrere, D; Lafferty, G; Lai, A; Lambert, D; Lambert, R W; Lanciotti, E; Lanfranchi, G; Langenbruch, C; Latham, T; Lazzeroni, C; Le Gac, R; van Leerdam, J; Lees, J-P; Lefèvre, R; Leflat, A; Lefrançois, J; Leo, S; Leroy, O; Lesiak, T; Leverington, B; Li, Y; Liles, M; Lindner, R; Linn, C; Lionetto, F; Liu, B; Liu, G; Lohn, S; Longstaff, I; Longstaff, I; Lopes, J H; Lopez-March, N; Lowdon, P; Lu, H; Lucchesi, D; Luisier, J; Luo, H; Lupato, A; Luppi, E; Lupton, O; Machefert, F; Machikhiliyan, I V; Maciuc, F; Maev, O; Malde, S; Manca, G; Mancinelli, G; Manzali, M; Maratas, J; Marchand, J F; Marconi, U; Marino, P; Märki, R; Marks, J; Martellotti, G; Martens, A; Martín Sánchez, A; Martinelli, M; Martinez Santos, D; Martinez Vidal, F; Martins Tostes, D; Massafferri, A; Matev, R; Mathe, Z; Matteuzzi, C; Mazurov, A; McCann, M; McCarthy, J; McNab, A; McNulty, R; McSkelly, B; Meadows, B; Meier, F; Meissner, M; Merk, M; Milanes, D A; Minard, M-N; Molina Rodriguez, J; Monteil, S; Moran, D; Morandin, M; Morawski, P; Mordà, A; Morello, M J; Moron, J; Mountain, R; Muheim, F; Müller, K; Muresan, R; Muster, B; Naik, P; Nakada, T; Nandakumar, R; Nasteva, I; Needham, M; Neri, N; Neubert, S; Neufeld, N; Neuner, M; Nguyen, A D; Nguyen, T D; Nguyen-Mau, C; Nicol, M; Niess, V; Niet, R; Nikitin, N; Nikodem, T; Novoselov, A; Oblakowska-Mucha, A; Obraztsov, V; Oggero, S; Ogilvy, S; Okhrimenko, O; Oldeman, R; Onderwater, G; Orlandea, M; Otalora Goicochea, J M; Owen, P; Oyanguren, A; Pal, B K; Palano, A; Palombo, F; Palutan, M; Panman, J; Papanestis, A; Pappagallo, M; Parkes, C; Parkinson, C J; Passaleva, G; Patel, G D; Patel, M; Patrignani, C; Pazos Alvarez, A; Pearce, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perez Trigo, E; Perret, P; Perrin-Terrin, M; Pescatore, L; Pesen, E; Petridis, K; Petrolini, A; Picatoste Olloqui, E; Pietrzyk, B; Pilař, T; Pinci, D; Pistone, A; Playfer, S; Plo Casasus, M; Polci, F; Polok, G; Poluektov, A; Polycarpo, E; Popov, A; Popov, D; Popovici, B; Potterat, C; Powell, A; Prisciandaro, J; Pritchard, A; Prouve, C; Pugatch, V; Puig Navarro, A; Punzi, G; Qian, W; Rachwal, B; Rademacker, J H; Rakotomiaramanana, B; Rama, M; Rangel, M S; Raniuk, I; Rauschmayr, N; Raven, G; Redford, S; Reichert, S; Reid, M M; Dos Reis, A C; Ricciardi, S; Richards, A; Rinnert, K; Rives Molina, V; Roa Romero, D A; Robbe, P; Rodrigues, A B; Rodrigues, E; Rodriguez Perez, P; Roiser, S; Romanovsky, V; Romero Vidal, A; Rotondo, M; Rouvinet, J; Ruf, T; Ruffini, F; Ruiz, H; Ruiz Valls, P; Sabatino, G; Saborido Silva, J J; Sagidova, N; Sail, P; Saitta, B; Salustino Guimaraes, V; Sanchez Mayordomo, C; Sanmartin Sedes, B; Santacesaria, R; Santamarina Rios, C; Santovetti, E; Sapunov, M; Sarti, A; Satriano, C; Satta, A; Savrie, M; Savrina, D; Schiller, M; Schindler, H; Schlupp, M; Schmelling, M; Schmidt, B; Schneider, O; Schopper, A; Schune, M-H; Schwemmer, R; Sciascia, B; Sciubba, A; Seco, M; Semennikov, A; Senderowska, K; Sepp, I; Serra, N; Serrano, J; Sestini, L; Seyfert, P; Shapkin, M; Shapoval, I; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, V; Shires, A; Silva Coutinho, R; Simi, G; Sirendi, M; Skidmore, N; Skwarnicki, T; Smith, N A; Smith, E; Smith, E; Smith, J; Smith, M; Snoek, H; Sokoloff, M D; Soler, F J P; Soomro, F; Souza, D; Souza De Paula, B; Spaan, B; Sparkes, A; Spinella, F; Spradlin, P; Stagni, F; Stahl, S; Steinkamp, O; Stenyakin, O; Stevenson, S; Stoica, S; Stone, S; Storaci, B; Stracka, S; Straticiuc, M; Straumann, U; Stroili, R; Subbiah, V K; Sun, L; Sutcliffe, W; Swientek, K; Swientek, S; Syropoulos, V; Szczekowski, M; Szczypka, P; Szilard, D; Szumlak, T; T'Jampens, S; Teklishyn, M; Tellarini, G; Teodorescu, E; Teubert, F; Thomas, C; Thomas, E; van Tilburg, J; Tisserand, V; Tobin, M; Tolk, S; Tomassetti, L; Tonelli, D; Topp-Joergensen, S; Torr, N; Tournefier, E; Tourneur, S; Tran, M T; Tresch, M; Tsaregorodtsev, A; Tsopelas, P; Tuning, N; Ubeda Garcia, M; Ukleja, A; Ustyuzhanin, A; Uwer, U; Vagnoni, V; Valenti, G; Vallier, A; Vazquez Gomez, R; Vazquez Regueiro, P; Vázquez Sierra, C; Vecchi, S; Velthuis, J J; Veltri, M; Veneziano, G; Vesterinen, M; Viaud, B; Vieira, D; Vieites Diaz, M; Vilasis-Cardona, X; Vollhardt, A; Volyanskyy, D; Voong, D; Vorobyev, A; Vorobyev, V; Voß, C; Voss, H; de Vries, J A; Waldi, R; Wallace, C; Wallace, R; Walsh, J; Wandernoth, S; Wang, J; Ward, D R; Watson, N K; Webber, A D; Websdale, D; Whitehead, M; Wicht, J; Wiedner, D; Wiggers, L; Wilkinson, G; Williams, M P; Williams, M; Wilson, F F; Wimberley, J; Wishahi, J; Wislicki, W; Witek, M; Wormser, G; Wotton, S A; Wright, S; Wu, S; Wyllie, K; Xie, Y; Xing, Z; Xu, Z; Yang, Z; Yuan, X; Yushchenko, O; Zangoli, M; Zavertyaev, M; Zhang, F; Zhang, L; Zhang, W C; Zhang, Y; Zhelezov, A; Zhokhov, A; Zhong, L; Zvyagin, A

    The polarisation of prompt [Formula: see text] mesons is measured by performing an angular analysis of [Formula: see text] decays using proton-proton collision data, corresponding to an integrated luminosity of 1.0[Formula: see text], collected by the LHCb detector at a centre-of-mass energy of 7 TeV. The polarisation is measured in bins of transverse momentum [Formula: see text] and rapidity [Formula: see text] in the kinematic region [Formula: see text] and [Formula: see text], and is compared to theoretical models. No significant polarisation is observed.

  5. 75 FR 29508 - The 2010 Census Count Question Resolution Program

    Science.gov (United States)

    2010-05-26

    ... hundreds of square miles. Census blocs are the smallest geographic entities for which the Census Bureau... information on total population, sex, age, race, Hispanic or Latino origin, household relationship, group... housing units. This information includes age, sex, race, Hispanic or Latino origin, household relationship...

  6. Towards a census of supercompact massive galaxies in the Kilo Degree Survey

    Science.gov (United States)

    Tortora, C.; La Barbera, F.; Napolitano, N. R.; Roy, N.; Radovich, M.; Cavuoti, S.; Brescia, M.; Longo, G.; Getman, F.; Capaccioli, M.; Grado, A.; Kuijken, K. H.; de Jong, J. T. A.; McFarland, J. P.; Puddu, E.

    2016-04-01

    The abundance of compact, massive, early-type galaxies (ETGs) provides important constraints to galaxy formation scenarios. Thanks to the area covered, depth, excellent spatial resolution and seeing, the ESO Public optical Kilo Degree Survey (KiDS), carried out with the VLT Survey Telescope, offers a unique opportunity to conduct a complete census of the most compact galaxies in the Universe. This paper presents a first census of such systems from the first 156 deg2 of KiDS. Our analysis relies on g-, r- and I-band effective radii (Re), derived by fitting galaxy images with point spread function (PSF)-convolved Sérsic models, high-quality photometric redshifts, zphot, estimated from machine learning techniques, and stellar masses, M⋆, calculated from KiDS aperture photometry. After massiveness ({M_{⋆}}≳ 8 × 10^{10} M_{⊙}) and compactness ({R_e}≲ 1.5 kpc in g, r and I bands) criteria are applied, a visual inspection of the candidates plus near-infrared photometry from VIKING-DR1 are used to refine our sample. The final catalogue, to be spectroscopically confirmed, consists of 92 systems in the redshift range z ˜ 0.2-0.7. This sample, which we expect to increase by a factor of 10 over the total survey area, represents the first attempt to select massive supercompact ETGs (MSCGs) in KiDS. We investigate the impact of redshift systematics in the selection, finding that this seems to be a major source of contamination in our sample. A preliminary analysis shows that MSCGs exhibit negative internal colour gradients, consistent with a passive evolution of these systems. We find that the number density of MSCGs is only mildly consistent with predictions from simulations at z > 0.2, while no such system is found at z < 0.2.

  7. History of census in the Czech Republic and in France (or in Germany, in the USA)

    OpenAIRE

    Šťastný, Jan

    2016-01-01

    Principal objective of this bachelor thesis is comparing census in the Czech Republic, in France and in the USA. In introductory section concerns on history of census in particular countries, mainly on detailed describe of census during 20th century. This is followed by chapters which attend to methodology and last census in selected countries where illustrated different access in variable parts of the world is. The last part is concerned about following census and perspective to the future, ...

  8. Studying Hardness Meter Spring Strength to Understand Hardness Distribution on Body Surfaces.

    Science.gov (United States)

    Arima, Yoshitaka

    2017-10-01

    For developing a hardness multipoint measurement system for understanding hardness distribution on biological body surfaces, we investigated the spring strength of the contact portion main axis of a biological tissue hardness meter (product name: PEK). We measured the hardness of three-layered sheets of six types of gel sheets (90 mm × 60 mm × 6 mm) constituting the acupuncture practice pads, with PEK measurements of 1.96 N, 2.94 N, 3.92 N, 4.90 N, 5.88 N, 6.86 N, 7.84 N, 8.82 N, and 9.81 N of the main axis spring strength. We obtained measurements 10 times for the gel sheets and simultaneously measured the load using a digital scale. We measured the hardness distribution of induration embedded and breast cancer palpation models, with a main axis with 1.96 N, 4.90 N, and 9.81 N spring strengths, to create a two-dimensional Contour Fill Chart. Using 4.90 N spring strength, we could obtain measurement loads of ≤3.0 N, and the mean hardness was 5.14 mm. This was close to the median of the total measurement range 0.0-10.0 mm, making the measurement range the largest for this spring strength. We could image the induration of the induration-embedded model regardless of the spring strength. Overall, 4.90 N spring strength was best suited for imaging cancer in the breast cancer palpation model. Copyright © 2017. Published by Elsevier B.V.

  9. Harding County TIGER 2000 Hydrography and Nodes

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — TIGER, TIGER/Line, and Census TIGER are registered trademarks of the Bureau of the Census. The Redistricting Census 2000 TIGER/Line files are an extract of selected...

  10. Provincial migration in China : Preliminary insights from the 2010 population census

    NARCIS (Netherlands)

    A.M. Fischer (Andrew Martín)

    2012-01-01

    textabstractIn anticipation of the forthcoming release of the 2010 national population census of China, this paper compares the limited population data that have been released so far with annual data on natural population increase since the 2000 census in order to construct a rough but robust

  11. Using Random Forest to Improve the Downscaling of Global Livestock Census Data

    Science.gov (United States)

    Nicolas, Gaëlle; Robinson, Timothy P.; Wint, G. R. William; Conchedda, Giulia; Cinardi, Giuseppina; Gilbert, Marius

    2016-01-01

    Large scale, high-resolution global data on farm animal distributions are essential for spatially explicit assessments of the epidemiological, environmental and socio-economic impacts of the livestock sector. This has been the major motivation behind the development of the Gridded Livestock of the World (GLW) database, which has been extensively used since its first publication in 2007. The database relies on a downscaling methodology whereby census counts of animals in sub-national administrative units are redistributed at the level of grid cells as a function of a series of spatial covariates. The recent upgrade of GLW1 to GLW2 involved automating the processing, improvement of input data, and downscaling at a spatial resolution of 1 km per cell (5 km per cell in the earlier version). The underlying statistical methodology, however, remained unchanged. In this paper, we evaluate new methods to downscale census data with a higher accuracy and increased processing efficiency. Two main factors were evaluated, based on sample census datasets of cattle in Africa and chickens in Asia. First, we implemented and evaluated Random Forest models (RF) instead of stratified regressions. Second, we investigated whether models that predicted the number of animals per rural person (per capita) could provide better downscaled estimates than the previous approach that predicted absolute densities (animals per km2). RF models consistently provided better predictions than the stratified regressions for both continents and species. The benefit of per capita over absolute density models varied according to the species and continent. In addition, different technical options were evaluated to reduce the processing time while maintaining their predictive power. Future GLW runs (GLW 3.0) will apply the new RF methodology with optimized modelling options. The potential benefit of per capita models will need to be further investigated with a better distinction between rural and agricultural

  12. Using Random Forest to Improve the Downscaling of Global Livestock Census Data.

    Directory of Open Access Journals (Sweden)

    Gaëlle Nicolas

    Full Text Available Large scale, high-resolution global data on farm animal distributions are essential for spatially explicit assessments of the epidemiological, environmental and socio-economic impacts of the livestock sector. This has been the major motivation behind the development of the Gridded Livestock of the World (GLW database, which has been extensively used since its first publication in 2007. The database relies on a downscaling methodology whereby census counts of animals in sub-national administrative units are redistributed at the level of grid cells as a function of a series of spatial covariates. The recent upgrade of GLW1 to GLW2 involved automating the processing, improvement of input data, and downscaling at a spatial resolution of 1 km per cell (5 km per cell in the earlier version. The underlying statistical methodology, however, remained unchanged. In this paper, we evaluate new methods to downscale census data with a higher accuracy and increased processing efficiency. Two main factors were evaluated, based on sample census datasets of cattle in Africa and chickens in Asia. First, we implemented and evaluated Random Forest models (RF instead of stratified regressions. Second, we investigated whether models that predicted the number of animals per rural person (per capita could provide better downscaled estimates than the previous approach that predicted absolute densities (animals per km2. RF models consistently provided better predictions than the stratified regressions for both continents and species. The benefit of per capita over absolute density models varied according to the species and continent. In addition, different technical options were evaluated to reduce the processing time while maintaining their predictive power. Future GLW runs (GLW 3.0 will apply the new RF methodology with optimized modelling options. The potential benefit of per capita models will need to be further investigated with a better distinction between rural

  13. Dasymetric high resolution population distribution estimates for improved decision making, with a case study of sea-level rise vulnerability in Boca Raton, Florida

    Science.gov (United States)

    Ziegler, Hannes Moritz

    Planners and managers often rely on coarse population distribution data from the census for addressing various social, economic, and environmental problems. In the analysis of physical vulnerabilities to sea-level rise, census units such as blocks or block groups are coarse relative to the required decision-making application. This study explores the benefits offered from integrating image classification and dasymetric mapping at the household level to provide detailed small area population estimates at the scale of residential buildings. In a case study of Boca Raton, FL, a sea-level rise inundation grid based on mapping methods by NOAA is overlaid on the highly detailed population distribution data to identify vulnerable residences and estimate population displacement. The enhanced spatial detail offered through this method has the potential to better guide targeted strategies for future development, mitigation, and adaptation efforts.

  14. Radioactivity contamination of the Russian Arctic Seas

    Energy Technology Data Exchange (ETDEWEB)

    Rissanen, K. [STUK Radiation and Nuclear Safety Authority, Rovaniemi (Finland); Ikaeheimonen, T.K. [STUK Radiation and Nuclear Safety Authority, Helsinki (Finland); Matishov, D.; Matishov, G.G. [Murmansk Marine Biological Inst., Murmansk (Russian Federation)

    2001-04-01

    The levels of the anthropogenic radionuclides in the Russian Arctic Seas are low compared to the potential sources of pollution and originata mainly from the global fallout, Chernobyl fallout and from the western nuclear fuel reprocessing plants. Fresh release of radioactivity was noticed in this study only in the Kola Bay and in two sampling locations in the White Sea. The increased {sup 137}Cs concentrations measured in the estuaries of River Dvina and River Yenisey are caused by the riverine transport from the large catchment area. The sediments of the Russian Arctic Seas are hard. Good and enough long cores for sedimentation rate determination were obtained only in two locations in the White Sea. All the cores from river estuaries were badly mixed. (EHS)

  15. Using MODIS spectral information to classify sea ice scenes for CERES radiance-to-flux inversion

    Science.gov (United States)

    Corbett, J.; Su, W.; Liang, L.; Eitzen, Z.

    2013-12-01

    The Clouds and Earth's Radiant Energy System (CERES) instruments on NASA's Terra and Aqua satellites measure the shortwave (SW) radiance reflected from the Earth. In order to provide an estimate of the top-of-atmosphere reflected SW flux we need to know the anisotropy of the radiance reflected from the scene. Sea Ice scenes are particularly complex due to the wide range of surface conditions that comprise sea ice. For example, the anisotropy of snow-covered sea ice is quite different to that of sea ice with melt-ponds. To attempt to provide a consistent scene classification we have developed the Sea Ice Brightness Index (SIBI). The SIBI is defined as one minus the normalized difference between reflectances from the 0.469 micron and 0.858 micron bands from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. For brighter snow-covered sea ice scenes the SIBI value is close to 1.0. As the surface changes to bare ice, melt ponds, etc. the SIBI decreases. For open water the SIBI value is around 0.2-0.3. The SIBI exhibits no dependence on viewing zenith or solar zenith angle, allowing for consistent scene identification. To use the SIBI we classify clear-sky CERES field-of-views over sea ice into 3 groups; SIBI≥0.935, 0.935>SIBI≥0.85 and SIBISIBI based ADMs. Using the second metric, we see a reduction in the latitude/longitude binned mean RMS error between the ADM predicted radiance and the measured radiance from 8% to 7% in May and from 17% to 12% in July. These improvements suggest that using the SIBI to account for changes in the sea ice surface will lead to improved CERES flux retrievals.

  16. A Simple Model Framework to Explore the Deeply Uncertain, Local Sea Level Response to Climate Change. A Case Study on New Orleans, Louisiana

    Science.gov (United States)

    Bakker, Alexander; Louchard, Domitille; Keller, Klaus

    2016-04-01

    Sea-level rise threatens many coastal areas around the world. The integrated assessment of potential adaptation and mitigation strategies requires a sound understanding of the upper tails and the major drivers of the uncertainties. Global warming causes sea-level to rise, primarily due to thermal expansion of the oceans and mass loss of the major ice sheets, smaller ice caps and glaciers. These components show distinctly different responses to temperature changes with respect to response time, threshold behavior, and local fingerprints. Projections of these different components are deeply uncertain. Projected uncertainty ranges strongly depend on (necessary) pragmatic choices and assumptions; e.g. on the applied climate scenarios, which processes to include and how to parameterize them, and on error structure of the observations. Competing assumptions are very hard to objectively weigh. Hence, uncertainties of sea-level response are hard to grasp in a single distribution function. The deep uncertainty can be better understood by making clear the key assumptions. Here we demonstrate this approach using a relatively simple model framework. We present a mechanistically motivated, but simple model framework that is intended to efficiently explore the deeply uncertain sea-level response to anthropogenic climate change. The model consists of 'building blocks' that represent the major components of sea-level response and its uncertainties, including threshold behavior. The framework's simplicity enables the simulation of large ensembles allowing for an efficient exploration of parameter uncertainty and for the simulation of multiple combined adaptation and mitigation strategies. The model framework can skilfully reproduce earlier major sea level assessments, but due to the modular setup it can also be easily utilized to explore high-end scenarios and the effect of competing assumptions and parameterizations.

  17. Auxiliary midwives in hard to reach rural areas of Myanmar: filling MCH gaps.

    Science.gov (United States)

    Wangmo, Sangay; Suphanchaimat, Rapeepong; Htun, Wai Mar Mar; Tun Aung, Tin; Khitdee, Chiraporn; Patcharanarumol, Walaiporn; Htoon, Pe Thet; Tangcharoensathien, Viroj

    2016-09-01

    Auxiliary Midwives (AMWs) are community health volunteers supporting the work of midwives, especially maternal and child health services in hard to-reach areas in Myanmar. This paper assessed the contributions of AMW to maternal and child health services, factors influencing their productivity and their willingness to serve the community. The study applied quantitative cross-sectional survey using census method. Total of 1,185 AMWs belonging to three batches: trained prior to 2000, between 2000 and 2011, and in 2012, from 21 townships of 17 states and regions in Myanmar participated in the study. Multiple logit regression was used to examine the impact of age, marital status, education, domicile, recruitment pattern and 'batch of training', on AMW's confidence level in providing care, and their intention to serve the community more than 5 years. All AMWs were able to provide essential maternal and child health services including antenatal care, normal delivery and post-natal care. They could identify and refer high-risk pregnancies to larger health facilities for proper management. On average, 9 deliveries, 11 antenatal and 9 postnatal cases were performed by an AMW during the six months prior to this study. AMWs had a comparative advantage for longer service in hard-to-reach villages where they lived, spoke the same dialect as the locals, understood the socio-cultural dimensions, and were well accepted by the community. Despite these contributions, 90 % of the respondents expressed receiving no adequate supervision, refresher training, replenishment of the AMW kits and transportation cost. AMWs in the elder age group are significantly more confident in taking care of the patients than those in the younger groups. Over 90 % of the respondents intended to stay more than five years in the community. The confidence in catering services appeared to have significant association with a longer period of stay in AMW jobs as evidenced by the odds ratio of 3.5, compared

  18. Auxiliary midwives in hard to reach rural areas of Myanmar: filling MCH gaps

    Directory of Open Access Journals (Sweden)

    Sangay Wangmo

    2016-09-01

    Full Text Available Abstract Background Auxiliary Midwives (AMWs are community health volunteers supporting the work of midwives, especially maternal and child health services in hard to-reach areas in Myanmar. This paper assessed the contributions of AMW to maternal and child health services, factors influencing their productivity and their willingness to serve the community. Method The study applied quantitative cross-sectional survey using census method. Total of 1,185 AMWs belonging to three batches: trained prior to 2000, between 2000 and 2011, and in 2012, from 21 townships of 17 states and regions in Myanmar participated in the study. Multiple logit regression was used to examine the impact of age, marital status, education, domicile, recruitment pattern and ‘batch of training’, on AMW’s confidence level in providing care, and their intention to serve the community more than 5 years. Results All AMWs were able to provide essential maternal and child health services including antenatal care, normal delivery and post-natal care. They could identify and refer high-risk pregnancies to larger health facilities for proper management. On average, 9 deliveries, 11 antenatal and 9 postnatal cases were performed by an AMW during the six months prior to this study. AMWs had a comparative advantage for longer service in hard-to-reach villages where they lived, spoke the same dialect as the locals, understood the socio-cultural dimensions, and were well accepted by the community. Despite these contributions, 90 % of the respondents expressed receiving no adequate supervision, refresher training, replenishment of the AMW kits and transportation cost. AMWs in the elder age group are significantly more confident in taking care of the patients than those in the younger groups. Over 90 % of the respondents intended to stay more than five years in the community. The confidence in catering services appeared to have significant association with a longer period of stay

  19. Variability in abundance of temperate reef fishes estimated by visual census.

    Directory of Open Access Journals (Sweden)

    Alejo J Irigoyen

    Full Text Available Identifying sources of sampling variation and quantifying their magnitude is critical to the interpretation of ecological field data. Yet, most monitoring programs of reef fish populations based on underwater visual censuses (UVC consider only a few of the factors that may influence fish counts, such as the diver or census methodology. Recent studies, however, have drawn attention to a broader range of processes that introduce variability at different temporal scales. This study analyzes the magnitude of different sources of variation in UVCs of temperate reef fishes off Patagonia (Argentina. The variability associated with time-of-day, tidal state, and time elapsed between censuses (minutes, days, weeks and months was quantified for censuses conducted on the five most conspicuous and common species: Pinguipes brasilianus, Pseudopercis semifasciata, Sebastes oculatus, Acanthistius patachonicus and Nemadactylus bergi. Variance components corresponding to spatial heterogeneity and to the different temporal scales were estimated using nested random models. The levels of variability estimated for the different species were related to their life history attributes and behavior. Neither time-of-day nor tidal state had a significant effect on counts, except for the influence of tide on P. brasilianus. Spatial heterogeneity was the dominant source of variance in all but one species. Among the temporal scales, the intra-annual variation was the highest component for most species due to marked seasonal fluctuations in abundance, followed by the weekly and the instantaneous variation; the daily component was not significant. The variability between censuses conducted at different tidal levels and time-of-day was similar in magnitude to the instantaneous variation, reinforcing the conclusion that stochastic variation at very short time scales is non-negligible and should be taken into account in the design of monitoring programs and experiments. The present

  20. New Mexico County Boundaries (2010 Census)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  1. Dona Ana County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  2. Santa Fe County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  3. Curry County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  4. Union County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  5. Rio Arriba County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  6. Dona Ana County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  7. Los Alamos County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  8. San Miguel County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  9. San Juan County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  10. Rio Arriba County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  11. Valencia County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  12. Socorro County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  13. Sandoval County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  14. Eddy County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  15. Dona Ana County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  16. Los Alamos County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  17. McKinley County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  18. San Juan County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  19. McKinley County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  20. Los Alamos County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  1. San Miguel County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  2. De Baca County 2010 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  3. McKinley County 2010 Census Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  4. De Baca County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  5. Dona Ana County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  6. Los Alamos County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  7. San Juan County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  8. Santa Fe County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  9. McKinley County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  10. Rio Arriba County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  11. San Miguel County 2010 Census Blocks

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  12. Mora County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  13. Otero County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  14. Torrance County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  15. Catron County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  16. San Juan County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  17. Santa Fe County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  18. San Miguel County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  19. De Baca County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  20. Rio Arriba County 2010 Census Edges

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  1. Bernalillo County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  2. Taos County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  3. Grant County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  4. New Mexico, 2010 Census American Indian

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  5. Extreme Longevity in Proteinaceous Deep-Sea Corals

    Energy Technology Data Exchange (ETDEWEB)

    Roark, E B; Guilderson, T P; Dunbar, R B; Fallon, S J; Mucciarone, D A

    2009-02-09

    Deep-sea corals are found on hard substrates on seamounts and continental margins world-wide at depths of 300 to {approx}3000 meters. Deep-sea coral communities are hotspots of deep ocean biomass and biodiversity, providing critical habitat for fish and invertebrates. Newly applied radiocarbon age date from the deep water proteinaceous corals Gerardia sp. and Leiopathes glaberrima show that radial growth rates are as low as 4 to 35 {micro}m yr{sup -1} and that individual colony longevities are on the order of thousands of years. The management and conservation of deep sea coral communities is challenged by their commercial harvest for the jewelry trade and damage caused by deep water fishing practices. In light of their unusual longevity, a better understanding of deep sea coral ecology and their interrelationships with associated benthic communities is needed to inform coherent international conservation strategies for these important deep-sea ecosystems.

  6. [The impact of technological change on census taking: some thoughts on implications for the 1990 round of censuses and on the statistical use of administrative records].

    Science.gov (United States)

    Brackstone, G J

    1984-01-01

    The author presents some general thoughts on the implications of technological change for the 1990 round of censuses and for the statistical use of administrative records. Consideration is also given to alternative methods of obtaining the type of data traditionally collected in a population census, by using these new technologies in association with administrative record systems.

  7. [The measurement of data quality in censuses of population and housing].

    Science.gov (United States)

    1980-01-01

    The determination of data quality in population and housing censuses is discussed. Principal types of errors commonly found in census data are reviewed, and the parameters used to evaluate data quality are described. Various methods for measuring data quality are outlined and possible applications of the methods are illustrated using Canadian examples

  8. Negotiating Race and Ethnicity: exploring the implications of the 1991 Census

    OpenAIRE

    Ballard, Roger

    1996-01-01

    This paper explores the way in which the concepts of 'Ethnic group' and 'Race' were operationalised in the 1991 Census of the UK, and explores the far-reaching impact which these conceptualization have had on the character of published Census data.

  9. Rezultati januarskega štetja vodnih ptic leta 2014 v Sloveniji / Results of the January 2014 waterbird census in Slovenia

    Directory of Open Access Journals (Sweden)

    Božič Luka

    2014-11-01

    Full Text Available In 2014, the International Waterbird Census (IWC was carried out in Slovenia on 18 and 19 Jan. Waterbirds were counted on all larger rivers, along the entire Slovenian Coastland and on most of the major standing waters in the country. During the census, in which 268 observers took part, 413 sections of the rivers and coastal sea with a total length of 1395.1 km and 226 other localities (178 standing waters and 48 streams were surveyed. Altogether, 45,346 waterbirds of 62 species were counted. This is the lowest number of waterbirds recorded after the 1997 and 1998 censuses. The greatest numbers of waterbirds were counted in the Drava count area, i.e. 20,217 individuals (44.6% of all waterbirds in Slovenia. By far the most numerous species was Mallard Anas platyrhynchos (43.0% of all waterbirds, followed by Black-headed Gull Chroicocephalus ridibundus (10.1% of all waterbirds, Coot Fulica atra (7.9% of all waterbirds, Yellow-legged Gull Larus michahellis (6.0% of all waterbirds and Cormorant Phalacrocorax carbo (4.6% of all waterbirds. The number of 1,000 counted individuals was also surpassed by Mute Swan Cygnus olor, Pochard Aythya ferina, Tufted Duck Ay. fuligula and Teal An. crecca. Among the rarer recorded species, the Black Stork Ciconia nigra (registered for the first time during the January Waterbird Censuses; only the second winter record in Slovenia, Cattle Egret Bubulcus ibis and Flamingo Phoenicopterus roseus (both registered only for the second time during the IWC should be given a special mention. Numbers of the following species were the highest so far recorded during the IWC: Shelduck Tadorna tadorna, Muscovy Duck Cairina moschata, Shoveler An. clypeata, Redthroated Loon Gavia stellata and Pygmy Cormorant Phalacrocorax pygmeus. Also, the total number of C and E category species/taxa was the highest to date, although still quite low with 70 individuals. Numbers of the following species were the lowest so far recorded during the IWC

  10. 76 FR 321 - Proposed Information Collection; Comment Request; 2012 Economic Census Covering the Utilities...

    Science.gov (United States)

    2011-01-04

    ... Economic Census Covering the Utilities, Transportation and Warehousing, Finance and Insurance, and Real... nondecennial census years. The 2012 Economic Census covering Utilities, Transportation and Warehousing, Finance... basic statistics by kind of business on the number of establishments, revenue, payroll, and employment...

  11. Hard bottom substrate monitoring Horns Rev offshore wind farm. Annual status report 2003

    Energy Technology Data Exchange (ETDEWEB)

    Leonhard, S.B.; Pedersen, John

    2004-05-15

    Elsam and Eltra built the offshore demonstration wind farm at Horns Rev in the North Sea. Elsam is the owner and is responsible for the operation of the wind farm. Eltra is responsible for the connection of the wind farm to the national onshore grid. In the summer months of 2002, Elsam constructed the world's largest offshore wind farm off the Danish west coast. The wind farm is sited 14-20 km into the North Sea, west of Blaevands Huk. The first wind turbine was erected in May 2002 and the last wind turbine tower of a total of 80 was in place by August 2002. The construction work was completed with the last connecting cables sluiced down in September 2002. All the wind turbines were in production by December 2002. The expected impact of the wind farm will primarily be an alternation of habitats due to the introduction of hard bottom substrates as wind turbine towers and scour protections. A continuous development in the epifouling communities will be expected together with an introduction of new or alien species in the area. The indigenous benthic community in the area of Horns Rev can be characterised by infauna species belonging to the Goniadella-Spisula community. This community is typical of sandbanks in the North Sea area, although communities in such areas are very variable and site-specific. Character species used as indicators for environmental changes in the Horns Rev area are the bristle worms Goniadella bobretzkii, Ophelia borealis, Psione remota and Orbinia sertulata and the mussels Goodallia triangularis and Spisula solida. In connection with the implementation of the monitoring programme concerning the ecological impact of the introduction of hard substrate related to the Horns Rev Wind Farm, surveys on hard bottom substrate was conducted in March 2003 and in September 2003. This report describes the first year results of surveys on hard substrate after the completion of the offshore wind farm at Horns Rev. (au)

  12. Hard bottom substrate monitoring Horns Rev offshore wind farm. Annual status report. 2004

    Energy Technology Data Exchange (ETDEWEB)

    Leonhard, S.B.; Pedersen, John

    2005-05-15

    Elsam and Eltra have built the offshore demonstration wind farm at Horns Rev in the North Sea. Elsam is the owner and is responsible for the operation of the wind farm. Eltra is responsible for the connection of the wind farm to the national onshore grid. In the summer months of 2002, Elsam constructed the world's largest offshore wind farm at the Danish west coast. The wind farm is located 14-20 km into the North Sea, west of Blaevands Huk. The first wind turbine foundation was in place in March 2002 and the last mono-pile was in place in August 2002 for a total of 80. The construction work was completed with the last connecting cables sluiced down in September 2002. All the wind turbines were in production in December 2002. The expected impact from the wind farm will primarily be an alternation of habitats due to the introduction of hard bottom substrates as wind mono-piles and scour protections. A continuous development in the epifouling communities will be expected together with an introduction of new or alien species in the area. The indigenous benthic community in the area of Horn Rev can be characterised by infauna species belonging to the Goniadella-Spisula community. This community is typical of sandbanks in the North Sea area, although communities in such areas are very variable and site specific. Character species used as indicators for environmental changes in the Horns Rev area are the bristle worms Goniadella bobretzkii, Ophelia borealis, Psione remota and Orbinia sertulata and the mussels Goodallia triangularis and Spisula solida. In connection with the implementation of the monitoring programme concerning the ecological impact of the introduction of hard substrate related to the Horns Rev Wind Farm, surveys on hard bottom substrates were initialised in March 2003 with monitoring conducted in September 2003 and March and September 2004. This report describes the results from surveys on hard substrates in 2004. (au)

  13. Hard bottom substrate monitoring Horns Rev offshore wind farm. Annual status report. 2004

    Energy Technology Data Exchange (ETDEWEB)

    Leonhard, S B; Pedersen, John

    2005-05-15

    Elsam and Eltra have built the offshore demonstration wind farm at Horns Rev in the North Sea. Elsam is the owner and is responsible for the operation of the wind farm. Eltra is responsible for the connection of the wind farm to the national onshore grid. In the summer months of 2002, Elsam constructed the world's largest offshore wind farm at the Danish west coast. The wind farm is located 14-20 km into the North Sea, west of Blaevands Huk. The first wind turbine foundation was in place in March 2002 and the last mono-pile was in place in August 2002 for a total of 80. The construction work was completed with the last connecting cables sluiced down in September 2002. All the wind turbines were in production in December 2002. The expected impact from the wind farm will primarily be an alternation of habitats due to the introduction of hard bottom substrates as wind mono-piles and scour protections. A continuous development in the epifouling communities will be expected together with an introduction of new or alien species in the area. The indigenous benthic community in the area of Horn Rev can be characterised by infauna species belonging to the Goniadella-Spisula community. This community is typical of sandbanks in the North Sea area, although communities in such areas are very variable and site specific. Character species used as indicators for environmental changes in the Horns Rev area are the bristle worms Goniadella bobretzkii, Ophelia borealis, Psione remota and Orbinia sertulata and the mussels Goodallia triangularis and Spisula solida. In connection with the implementation of the monitoring programme concerning the ecological impact of the introduction of hard substrate related to the Horns Rev Wind Farm, surveys on hard bottom substrates were initialised in March 2003 with monitoring conducted in September 2003 and March and September 2004. This report describes the results from surveys on hard substrates in 2004. (au)

  14. Production of [Formula: see text] and [Formula: see text] in proton-proton collisions at [Formula: see text] 7 TeV.

    Science.gov (United States)

    Abelev, B; Adam, J; Adamová, D; Aggarwal, M M; Rinella, G Aglieri; Agnello, M; Agostinelli, A; Agrawal, N; Ahammed, Z; Ahmad, N; Ahmed, I; Ahn, S U; Ahn, S A; Aimo, I; Aiola, S; Ajaz, M; Akindinov, A; Alam, S N; Aleksandrov, D; Alessandro, B; Alexandre, D; Alici, A; Alkin, A; Alme, J; Alt, T; Altinpinar, S; Altsybeev, I; Alves Garcia Prado, C; Andrei, C; Andronic, A; Anguelov, V; Anielski, J; Antičić, T; Antinori, F; Antonioli, P; Aphecetche, L; Appelshäuser, H; Arcelli, S; Armesto, N; Arnaldi, R; Aronsson, T; Arsene, I C; Arslandok, M; Augustinus, A; Averbeck, R; Awes, T C; Azmi, M D; Bach, M; Badalà, A; Baek, Y W; Bagnasco, S; Bailhache, R; Bala, R; Baldisseri, A; Baltasar Dos Santos Pedrosa, F; Baral, R C; Barbera, R; Barile, F; Barnaföldi, G G; Barnby, L S; Barret, V; Bartke, J; Basile, M; Bastid, N; Basu, S; Bathen, B; Batigne, G; Batista Camejo, A; Batyunya, B; Batzing, P C; Baumann, C; Bearden, I G; Beck, H; Bedda, C; Behera, N K; Belikov, I; Bellini, F; Bellwied, R; Belmont-Moreno, E; Belmont, R; Belyaev, V; Bencedi, G; Beole, S; Berceanu, I; Bercuci, A; Berdnikov, Y; Berenyi, D; Berger, M E; Bertens, R A; Berzano, D; Betev, L; Bhasin, A; Bhat, I R; Bhati, A K; Bhattacharjee, B; Bhom, J; Bianchi, L; Bianchi, N; Bianchin, C; Bielčík, J; Bielčíková, J; Bilandzic, A; Bjelogrlic, S; Blanco, F; Blau, D; Blume, C; Bock, F; Bogdanov, A; Bøggild, H; Bogolyubsky, M; Böhmer, F V; Boldizsár, L; Bombara, M; Book, J; Borel, H; Borissov, A; Bossú, F; Botje, M; Botta, E; Böttger, S; Braun-Munzinger, P; Bregant, M; Breitner, T; Broker, T A; Browning, T A; Broz, M; Bruna, E; Bruno, G E; Budnikov, D; Buesching, H; Bufalino, S; Buncic, P; Busch, O; Buthelezi, Z; Caffarri, D; Cai, X; Caines, H; Calero Diaz, L; Caliva, A; Calvo Villar, E; Camerini, P; Carena, F; Carena, W; Castillo Castellanos, J; Casula, E A R; Catanescu, V; Cavicchioli, C; Ceballos Sanchez, C; Cepila, J; Cerello, P; Chang, B; Chapeland, S; Charvet, J L; Chattopadhyay, S; Chattopadhyay, S; Chelnokov, V; Cherney, M; Cheshkov, C; Cheynis, B; Chibante Barroso, V; Chinellato, D D; Chochula, P; Chojnacki, M; Choudhury, S; Christakoglou, P; Christensen, C H; Christiansen, P; Chujo, T; Chung, S U; Cicalo, C; Cifarelli, L; Cindolo, F; Cleymans, J; Colamaria, F; Colella, D; Collu, A; Colocci, M; Conesa Balbastre, G; Conesa Del Valle, Z; Connors, M E; Contreras, J G; Cormier, T M; Corrales Morales, Y; Cortese, P; Cortés Maldonado, I; Cosentino, M R; Costa, F; Crochet, P; Cruz Albino, R; Cuautle, E; Cunqueiro, L; Dainese, A; Dang, R; Danu, A; Das, D; Das, I; Das, K; Das, S; Dash, A; Dash, S; De, S; Delagrange, H; Deloff, A; Dénes, E; D'Erasmo, G; De Caro, A; de Cataldo, G; de Cuveland, J; De Falco, A; De Gruttola, D; De Marco, N; De Pasquale, S; de Rooij, R; Diaz Corchero, M A; Dietel, T; Dillenseger, P; Divià, R; Di Bari, D; Di Liberto, S; Di Mauro, A; Di Nezza, P; Djuvsland, Ø; Dobrin, A; Dobrowolski, T; Domenicis Gimenez, D; Dönigus, B; Dordic, O; Dørheim, S; Dubey, A K; Dubla, A; Ducroux, L; Dupieux, P; Dutta Majumdar, A K; Hilden, T E; Ehlers, R J; Elia, D; Engel, H; Erazmus, B; Erdal, H A; Eschweiler, D; Espagnon, B; Esposito, M; Estienne, M; Esumi, S; Evans, D; Evdokimov, S; Fabris, D; Faivre, J; Falchieri, D; Fantoni, A; Fasel, M; Fehlker, D; Feldkamp, L; Felea, D; Feliciello, A; Feofilov, G; Ferencei, J; Fernández Téllez, A; Ferreiro, E G; Ferretti, A; Festanti, A; Figiel, J; Figueredo, M A S; Filchagin, S; Finogeev, D; Fionda, F M; Fiore, E M; Floratos, E; Floris, M; Foertsch, S; Foka, P; Fokin, S; Fragiacomo, E; Francescon, A; Frankenfeld, U; Fuchs, U; Furget, C; Furs, A; Fusco Girard, M; Gaardhøje, J J; Gagliardi, M; Gago, A M; Gallio, M; Gangadharan, D R; Ganoti, P; Gao, C; Garabatos, C; Garcia-Solis, E; Gargiulo, C; Garishvili, I; Gerhard, J; Germain, M; Gheata, A; Gheata, M; Ghidini, B; Ghosh, P; Ghosh, S K; Gianotti, P; Giubellino, P; Gladysz-Dziadus, E; Glässel, P; Gomez Ramirez, A; González-Zamora, P; Gorbunov, S; Görlich, L; Gotovac, S; Graczykowski, L K; Grelli, A; Grigoras, A; Grigoras, C; Grigoriev, V; Grigoryan, A; Grigoryan, S; Grinyov, B; Grion, N; Grosse-Oetringhaus, J F; Grossiord, J-Y; Grosso, R; Guber, F; Guernane, R; Guerzoni, B; Guilbaud, M; Gulbrandsen, K; Gulkanyan, H; Gumbo, M; Gunji, T; Gupta, A; Gupta, R; Khan, K H; Haake, R; Haaland, Ø; Hadjidakis, C; Haiduc, M; Hamagaki, H; Hamar, G; Hanratty, L D; Hansen, A; Harris, J W; Hartmann, H; Harton, A; Hatzifotiadou, D; Hayashi, S; Heckel, S T; Heide, M; Helstrup, H; Herghelegiu, A; Herrera Corral, G; Hess, B A; Hetland, K F; Hippolyte, B; Hladky, J; Hristov, P; Huang, M; Humanic, T J; Hussain, N; Hussain, T; Hutter, D; Hwang, D S; Ilkaev, R; Ilkiv, I; Inaba, M; Innocenti, G M; Ionita, C; Ippolitov, M; Irfan, M; Ivanov, M; Ivanov, V; Jachołkowski, A; Jacobs, P M; Jahnke, C; Jang, H J; Janik, M A; Jayarathna, P H S Y; Jena, C; Jena, S; Jimenez Bustamante, R T; Jones, P G; Jung, H; Jusko, A; Kadyshevskiy, V; Kalinak, P; Kalweit, A; Kamin, J; Kang, J H; Kaplin, V; Kar, S; Karasu Uysal, A; Karavichev, O; Karavicheva, T; Karpechev, E; Kebschull, U; Keidel, R; Keijdener, D L D; Svn, M Keil; Khan, M M; Khan, P; Khan, S A; Khanzadeev, A; Kharlov, Y; Kileng, B; Kim, B; Kim, D W; Kim, D J; Kim, J S; Kim, M; Kim, M; Kim, S; Kim, T; Kirsch, S; Kisel, I; Kiselev, S; Kisiel, A; Kiss, G; Klay, J L; Klein, J; Klein-Bösing, C; Kluge, A; Knichel, M L; Knospe, A G; Kobdaj, C; Kofarago, M; Köhler, M K; Kollegger, T; Kolojvari, A; Kondratiev, V; Kondratyeva, N; Konevskikh, A; Kovalenko, V; Kowalski, M; Kox, S; Koyithatta Meethaleveedu, G; Kral, J; Králik, I; Kravčáková, A; Krelina, M; Kretz, M; Krivda, M; Krizek, F; Kryshen, E; Krzewicki, M; Kučera, V; Kucheriaev, Y; Kugathasan, T; Kuhn, C; Kuijer, P G; Kulakov, I; Kumar, J; Kurashvili, P; Kurepin, A; Kurepin, A B; Kuryakin, A; Kushpil, S; Kweon, M J; Kwon, Y; Ladron de Guevara, P; Lagana Fernandes, C; Lakomov, I; Langoy, R; Lara, C; Lardeux, A; Lattuca, A; La Pointe, S L; La Rocca, P; Lea, R; Leardini, L; Lee, G R; Legrand, I; Lehnert, J; Lemmon, R C; Lenti, V; Leogrande, E; Leoncino, M; León Monzón, I; Lévai, P; Li, S; Lien, J; Lietava, R; Lindal, S; Lindenstruth, V; Lippmann, C; Lisa, M A; Ljunggren, H M; Lodato, D F; Loenne, P I; Loggins, V R; Loginov, V; Lohner, D; Loizides, C; Lopez, X; López Torres, E; Lu, X-G; Luettig, P; Lunardon, M; Luparello, G; Ma, R; Maevskaya, A; Mager, M; Mahapatra, D P; Mahmood, S M; Maire, A; Majka, R D; Malaev, M; Maldonado Cervantes, I; Malinina, L; Mal'Kevich, D; Malzacher, P; Mamonov, A; Manceau, L; Manko, V; Manso, F; Manzari, V; Marchisone, M; Mareš, J; Margagliotti, G V; Margotti, A; Marín, A; Markert, C; Marquard, M; Martashvili, I; Martin, N A; Martinengo, P; Martínez, M I; Martínez García, G; Martin Blanco, J; Martynov, Y; Mas, A; Masciocchi, S; Masera, M; Masoni, A; Massacrier, L; Mastroserio, A; Matyja, A; Mayer, C; Mazer, J; Mazzoni, M A; Meddi, F; Menchaca-Rocha, A; Meninno, E; Mercado Pérez, J; Meres, M; Miake, Y; Mikhaylov, K; Milano, L; Milosevic, J; Mischke, A; Mishra, A N; Miśkowiec, D; Mitra, J; Mitu, C M; Mlynarz, J; Mohammadi, N; Mohanty, B; Molnar, L; Montaño Zetina, L; Montes, E; Morando, M; Moreira De Godoy, D A; Moretto, S; Morreale, A; Morsch, A; Muccifora, V; Mudnic, E; Mühlheim, D; Muhuri, S; Mukherjee, M; Müller, H; Munhoz, M G; Murray, S; Musa, L; Musinsky, J; Nandi, B K; Nania, R; Nappi, E; Nattrass, C; Nayak, K; Nayak, T K; Nazarenko, S; Nedosekin, A; Nicassio, M; Niculescu, M; Niedziela, J; Nielsen, B S; Nikolaev, S; Nikulin, S; Nikulin, V; Nilsen, B S; Noferini, F; Nomokonov, P; Nooren, G; Norman, J; Nyanin, A; Nystrand, J; Oeschler, H; Oh, S; Oh, S K; Okatan, A; Okubo, T; Olah, L; Oleniacz, J; Oliveira Da Silva, A C; Onderwaater, J; Oppedisano, C; Ortiz Velasquez, A; Oskarsson, A; Otwinowski, J; Oyama, K; Ozdemir, M; Sahoo, P; Pachmayer, Y; Pachr, M; Pagano, P; Paić, G; Pajares, C; Pal, S K; Palmeri, A; Pant, D; Papikyan, V; Pappalardo, G S; Pareek, P; Park, W J; Parmar, S; Passfeld, A; Patalakha, D I; Paticchio, V; Paul, B; Pawlak, T; Peitzmann, T; Pereira Da Costa, H; Pereira De Oliveira Filho, E; Peresunko, D; Pérez Lara, C E; Pesci, A; Peskov, V; Pestov, Y; Petráček, V; Petran, M; Petris, M; Petrovici, M; Petta, C; Piano, S; Pikna, M; Pillot, P; Pinazza, O; Pinsky, L; Piyarathna, D B; Płoskoń, M; Planinic, M; Pluta, J; Pochybova, S; Podesta-Lerma, P L M; Poghosyan, M G; Pohjoisaho, E H O; Polichtchouk, B; Poljak, N; Pop, A; Porteboeuf-Houssais, S; Porter, J; Potukuchi, B; Prasad, S K; Preghenella, R; Prino, F; Pruneau, C A; Pshenichnov, I; Puccio, M; Puddu, G; Pujahari, P; Punin, V; Putschke, J; Qvigstad, H; Rachevski, A; Raha, S; Rajput, S; Rak, J; Rakotozafindrabe, A; Ramello, L; Raniwala, R; Raniwala, S; Räsänen, S S; Rascanu, B T; Rathee, D; Rauf, A W; Razazi, V; Read, K F; Real, J S; Redlich, K; Reed, R J; Rehman, A; Reichelt, P; Reicher, M; Reidt, F; Renfordt, R; Reolon, A R; Reshetin, A; Rettig, F; Revol, J-P; Reygers, K; Riabov, V; Ricci, R A; Richert, T; Richter, M; Riedler, P; Riegler, W; Riggi, F; Rivetti, A; Rocco, E; Rodríguez Cahuantzi, M; Rodriguez Manso, A; Røed, K; Rogochaya, E; Rohni, S; Rohr, D; Röhrich, D; Romita, R; Ronchetti, F; Ronflette, L; Rosnet, P; Rossi, A; Roukoutakis, F; Roy, A; Roy, C; Roy, P; Rubio Montero, A J; Rui, R; Russo, R; Ryabinkin, E; Ryabov, Y; Rybicki, A; Sadovsky, S; Šafařík, K; Sahlmuller, B; Sahoo, R; Sahu, P K; Saini, J; Sakai, S; Salgado, C A; Salzwedel, J; Sambyal, S; Samsonov, V; Sanchez Castro, X; Sánchez Rodríguez, F J; Šándor, L; Sandoval, A; Sano, M; Santagati, G; Sarkar, D; Scapparone, E; Scarlassara, F; Scharenberg, R P; Schiaua, C; Schicker, R; Schmidt, C; Schmidt, H R; Schuchmann, S; Schukraft, J; Schulc, M; Schuster, T; Schutz, Y; Schwarz, K; Schweda, K; Scioli, G; Scomparin, E; Scott, R; Segato, G; Seger, J E; Sekiguchi, Y; Selyuzhenkov, I; Senosi, K; Seo, J; Serradilla, E; Sevcenco, A; Shabetai, A; Shabratova, G; Shahoyan, R; Shangaraev, A; Sharma, A; Sharma, N; Sharma, S; Shigaki, K; Shtejer, K; Sibiriak, Y; Siddhanta, S; Siemiarczuk, T; Silvermyr, D; Silvestre, C; Simatovic, G; Singaraju, R; Singh, R; Singha, S; Singhal, V; Sinha, B C; Sinha, T; Sitar, B; Sitta, M; Skaali, T B; Skjerdal, K; Slupecki, M; Smirnov, N; Snellings, R J M; Søgaard, C; Soltz, R; Song, J; Song, M; Soramel, F; Sorensen, S; Spacek, M; Spiriti, E; Sputowska, I; Spyropoulou-Stassinaki, M; Srivastava, B K; Stachel, J; Stan, I; Stefanek, G; Steinpreis, M; Stenlund, E; Steyn, G; Stiller, J H; Stocco, D; Stolpovskiy, M; Strmen, P; Suaide, A A P; Sugitate, T; Suire, C; Suleymanov, M; Sultanov, R; Šumbera, M; Symons, T J M; Szabo, A; Szanto de Toledo, A; Szarka, I; Szczepankiewicz, A; Szymanski, M; Takahashi, J; Tangaro, M A; Tapia Takaki, J D; Tarantola Peloni, A; Tarazona Martinez, A; Tariq, M; Tarzila, M G; Tauro, A; Tejeda Muñoz, G; Telesca, A; Terasaki, K; Terrevoli, C; Thäder, J; Thomas, D; Tieulent, R; Timmins, A R; Toia, A; Trubnikov, V; Trzaska, W H; Tsuji, T; Tumkin, A; Turrisi, R; Tveter, T S; Ullaland, K; Uras, A; Usai, G L; Vajzer, M; Vala, M; Valencia Palomo, L; Vallero, S; Vande Vyvre, P; Van Der Maarel, J; Van Hoorne, J W; van Leeuwen, M; Vargas, A; Vargyas, M; Varma, R; Vasileiou, M; Vasiliev, A; Vechernin, V; Veldhoen, M; Velure, A; Venaruzzo, M; Vercellin, E; Vergara Limón, S; Vernet, R; Verweij, M; Vickovic, L; Viesti, G; Viinikainen, J; Vilakazi, Z; Villalobos Baillie, O; Vinogradov, A; Vinogradov, L; Vinogradov, Y; Virgili, T; Vislavicius, V; Viyogi, Y P; Vodopyanov, A; Völkl, M A; Voloshin, K; Voloshin, S A; Volpe, G; von Haller, B; Vorobyev, I; Vranic, D; Vrláková, J; Vulpescu, B; Vyushin, A; Wagner, B; Wagner, J; Wagner, V; Wang, M; Wang, Y; Watanabe, D; Weber, M; Weber, S G; Wessels, J P; Westerhoff, U; Wiechula, J; Wikne, J; Wilde, M; Wilk, G; Wilkinson, J; Williams, M C S; Windelband, B; Winn, M; Yaldo, C G; Yamaguchi, Y; Yang, H; Yang, P; Yang, S; Yano, S; Yasnopolskiy, S; Yi, J; Yin, Z; Yoo, I-K; Yushmanov, I; Zaccolo, V; Zach, C; Zaman, A; Zampolli, C; Zaporozhets, S; Zarochentsev, A; Závada, P; Zaviyalov, N; Zbroszczyk, H; Zgura, I S; Zhalov, M; Zhang, H; Zhang, X; Zhang, Y; Zhao, C; Zhigareva, N; Zhou, D; Zhou, F; Zhou, Y; Zhuo, Zhou; Zhu, H; Zhu, J; Zhu, X; Zichichi, A; Zimmermann, A; Zimmermann, M B; Zinovjev, G; Zoccarato, Y; Zyzak, M

    The production of the strange and double-strange baryon resonances ([Formula: see text], [Formula: see text]) has been measured at mid-rapidity ([Formula: see text][Formula: see text]) in proton-proton collisions at [Formula: see text] [Formula: see text] 7 TeV with the ALICE detector at the LHC. Transverse momentum spectra for inelastic collisions are compared to QCD-inspired models, which in general underpredict the data. A search for the [Formula: see text] pentaquark, decaying in the [Formula: see text] channel, has been carried out but no evidence is seen.

  15. Los Alamos County 1990 Census Tracts

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This data set is a vector polygon digital data structure taken from the Census Bureau's TIGER/Line Files, 1994, for New Mexico. The source software used was ARC/INFO...

  16. Interoperable and accessible census and survey data from IPUMS.

    Science.gov (United States)

    Kugler, Tracy A; Fitch, Catherine A

    2018-02-27

    The first version of the Integrated Public Use Microdata Series (IPUMS) was released to users in 1993, and since that time IPUMS has come to stand for interoperable and accessible census and survey data. Initially created to harmonize U.S. census microdata over time, IPUMS now includes microdata from the U.S. and international censuses and from surveys on health, employment, and other topics. IPUMS also provides geo-spatial data, aggregate population data, and environmental data. IPUMS supports ten data products, each disseminating an integrated data collection with a set of tools that make complex data easy to find, access, and use. Key features are record-level integration to create interoperable datasets, user-friendly interfaces, and comprehensive metadata and documentation. The IPUMS philosophy aligns closely with the FAIR principles of findability, accessibility, interoperability, and re-usability. IPUMS data have catalyzed knowledge generation across a wide range of social science and other disciplines, as evidenced by the large volume of publications and other products created by the vast IPUMS user community.

  17. Measurement of the forward energy flow in pp collisions at [Formula: see text].

    Science.gov (United States)

    Aaij, R; Abellan Beteta, C; Adametz, A; Adeva, B; Adinolfi, M; Adrover, C; Affolder, A; Ajaltouni, Z; Albrecht, J; Alessio, F; Alexander, M; Ali, S; Alkhazov, G; Alvarez Cartelle, P; Alves, A A; Amato, S; Amhis, Y; Anderlini, L; Anderson, J; Appleby, R B; Aquines Gutierrez, O; Archilli, F; Artamonov, A; Artuso, M; Aslanides, E; Auriemma, G; Bachmann, S; Back, J J; Baesso, C; Balagura, V; Baldini, W; Barlow, R J; Barschel, C; Barsuk, S; Barter, W; Bates, A; Bauer, Th; Bay, A; Beddow, J; Bediaga, I; Belogurov, S; Belous, K; Belyaev, I; Ben-Haim, E; Benayoun, M; Bencivenni, G; Benson, S; Benton, J; Berezhnoy, A; Bernet, R; Bettler, M-O; van Beuzekom, M; Bien, A; Bifani, S; Bird, T; Bizzeti, A; Bjørnstad, P M; Blake, T; Blanc, F; Blanks, C; Blouw, J; Blusk, S; Bobrov, A; Bocci, V; Bondar, A; Bondar, N; Bonivento, W; Borghi, S; Borgia, A; Bowcock, T J V; Bozzi, C; Brambach, T; van den Brand, J; Bressieux, J; Brett, D; Britsch, M; Britton, T; Brook, N H; Brown, H; Büchler-Germann, A; Burducea, I; Bursche, A; Buytaert, J; Cadeddu, S; Callot, O; Calvi, M; Calvo Gomez, M; Camboni, A; Campana, P; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carranza-Mejia, H; Carson, L; Carvalho Akiba, K; Casse, G; Cattaneo, M; Cauet, Ch; Charles, M; Charpentier, Ph; Chen, P; Chiapolini, N; Chrzaszcz, M; Ciba, K; Cid Vidal, X; Ciezarek, G; Clarke, P E L; Clemencic, M; Cliff, H V; Closier, J; Coca, C; Coco, V; Cogan, J; Cogneras, E; Collins, P; Comerma-Montells, A; Contu, A; Cook, A; Coombes, M; Corti, G; Couturier, B; Cowan, G A; Craik, D C; Cunliffe, S; Currie, R; D'Ambrosio, C; David, P; David, P N Y; De Bonis, I; De Bruyn, K; De Capua, S; De Cian, M; De Miranda, J M; De Paula, L; De Simone, P; Decamp, D; Deckenhoff, M; Degaudenzi, H; Del Buono, L; Deplano, C; Derkach, D; Deschamps, O; Dettori, F; Di Canto, A; Dickens, J; Dijkstra, H; Diniz Batista, P; Dogaru, M; Domingo Bonal, F; Donleavy, S; Dordei, F; Dosil Suárez, A; Dossett, D; Dovbnya, A; Dupertuis, F; Dzhelyadin, R; Dziurda, A; Dzyuba, A; Easo, S; Egede, U; Egorychev, V; Eidelman, S; van Eijk, D; Eisenhardt, S; Eitschberger, U; Ekelhof, R; Eklund, L; El Rifai, I; Elsasser, Ch; Elsby, D; Falabella, A; Färber, C; Fardell, G; Farinelli, C; Farry, S; Fave, V; Ferguson, D; Fernandez Albor, V; Ferreira Rodrigues, F; Ferro-Luzzi, M; Filippov, S; Fiore, M; Fitzpatrick, C; Fontana, M; Fontanelli, F; Forty, R; Francisco, O; Frank, M; Frei, C; Frosini, M; Furcas, S; Gallas Torreira, A; Galli, D; Gandelman, M; Gandini, P; Gao, Y; Garnier, J-C; Garofoli, J; Garosi, P; Garra Tico, J; Garrido, L; Gaspar, C; Gauld, R; Gersabeck, E; Gersabeck, M; Gershon, T; Ghez, Ph; Gibson, V; Gligorov, V V; Göbel, C; Golubkov, D; Golutvin, A; Gomes, A; Gordon, H; Grabalosa Gándara, M; Graciani Diaz, R; Granado Cardoso, L A; Graugés, E; Graziani, G; Grecu, A; Greening, E; Gregson, S; Grünberg, O; Gui, B; Gushchin, E; Guz, Yu; Gys, T; Hadjivasiliou, C; Haefeli, G; Haen, C; Haines, S C; Hall, S; Hampson, T; Hansmann-Menzemer, S; Harnew, N; Harnew, S T; Harrison, J; Harrison, P F; Hartmann, T; He, J; Heijne, V; Hennessy, K; Henrard, P; Hernando Morata, J A; van Herwijnen, E; Hicks, E; Hill, D; Hoballah, M; Hopchev, P; Hulsbergen, W; Hunt, P; Huse, T; Hussain, N; Hutchcroft, D; Hynds, D; Iakovenko, V; Ilten, P; Imong, J; Jacobsson, R; Jaeger, A; Jahjah Hussein, M; Jans, E; Jansen, F; Jaton, P; Jean-Marie, B; Jing, F; John, M; Johnson, D; Jones, C R; Jost, B; Kaballo, M; Kandybei, S; Karacson, M; Karbach, T M; Kenyon, I R; Kerzel, U; Ketel, T; Keune, A; Khanji, B; Kim, Y M; Kochebina, O; Komarov, I; Koopman, R F; Koppenburg, P; Korolev, M; Kozlinskiy, A; Kravchuk, L; Kreplin, K; Kreps, M; Krocker, G; Krokovny, P; Kruse, F; Kucharczyk, M; Kudryavtsev, V; Kvaratskheliya, T; La Thi, V N; Lacarrere, D; Lafferty, G; Lai, A; Lambert, D; Lambert, R W; Lanciotti, E; Lanfranchi, G; Langenbruch, C; Latham, T; Lazzeroni, C; Le Gac, R; van Leerdam, J; Lees, J-P; Lefèvre, R; Leflat, A; Lefrançois, J; Leroy, O; Li, Y; Li Gioi, L; Liles, M; Lindner, R; Linn, C; Liu, B; Liu, G; von Loeben, J; Lopes, J H; Lopez Asamar, E; Lopez-March, N; Lu, H; Luisier, J; Luo, H; Mac Raighne, A; Machefert, F; Machikhiliyan, I V; Maciuc, F; Maev, O; Malde, S; Manca, G; Mancinelli, G; Mangiafave, N; Marconi, U; Märki, R; Marks, J; Martellotti, G; Martens, A; Martin, L; Martín Sánchez, A; Martinelli, M; Martinez Santos, D; Martins Tostes, D; Massafferri, A; Matev, R; Mathe, Z; Matteuzzi, C; Matveev, M; Maurice, E; Mazurov, A; McCarthy, J; McGregor, G; McNulty, R; Meier, F; Meissner, M; Merk, M; Merkel, J; Milanes, D A; Minard, M-N; Molina Rodriguez, J; Monteil, S; Moran, D; Morawski, P; Mountain, R; Mous, I; Muheim, F; Müller, K; Muresan, R; Muryn, B; Muster, B; Mylroie-Smith, J; Naik, P; Nakada, T; Nandakumar, R; Nasteva, I; Needham, M; Neufeld, N; Nguyen, A D; Nguyen, T D; Nguyen-Mau, C; Nicol, M; Niess, V; Niet, R; Nikitin, N; Nikodem, T; Nomerotski, A; Novoselov, A; Oblakowska-Mucha, A; Obraztsov, V; Oggero, S; Ogilvy, S; Okhrimenko, O; Oldeman, R; Orlandea, M; Otalora Goicochea, J M; Owen, P; Pal, B K; Palano, A; Palutan, M; Panman, J; Papanestis, A; Pappagallo, M; Parkes, C; Parkinson, C J; Passaleva, G; Patel, G D; Patel, M; Patrick, G N; Patrignani, C; Pavel-Nicorescu, C; Pazos Alvarez, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perego, D L; Perez Trigo, E; Pérez-Calero Yzquierdo, A; Perret, P; Perrin-Terrin, M; Pessina, G; Petridis, K; Petrolini, A; Phan, A; Picatoste Olloqui, E; Pie Valls, B; Pietrzyk, B; Pilař, T; Pinci, D; Playfer, S; Plo Casasus, M; Polci, F; Polok, G; Poluektov, A; Polycarpo, E; Popov, D; Popovici, B; Potterat, C; Powell, A; Prisciandaro, J; Pugatch, V; Puig Navarro, A; Qian, W; Rademacker, J H; Rakotomiaramanana, B; Rangel, M S; Raniuk, I; Rauschmayr, N; Raven, G; Redford, S; Reid, M M; Dos Reis, A C; Ricciardi, S; Richards, A; Rinnert, K; Rives Molina, V; Roa Romero, D A; Robbe, P; Rodrigues, E; Rodriguez Perez, P; Rogers, G J; Roiser, S; Romanovsky, V; Romero Vidal, A; Rouvinet, J; Ruf, T; Ruiz, H; Sabatino, G; Saborido Silva, J J; Sagidova, N; Sail, P; Saitta, B; Salzmann, C; Sanmartin Sedes, B; Sannino, M; Santacesaria, R; Santamarina Rios, C; Santinelli, R; Santovetti, E; Sapunov, M; Sarti, A; Satriano, C; Satta, A; Savrie, M; Savrina, D; Schaack, P; Schiller, M; Schindler, H; Schleich, S; Schlupp, M; Schmelling, M; Schmidt, B; Schneider, O; Schopper, A; Schune, M-H; Schwemmer, R; Sciascia, B; Sciubba, A; Seco, M; Semennikov, A; Senderowska, K; Sepp, I; Serra, N; Serrano, J; Seyfert, P; Shapkin, M; Shapoval, I; Shatalov, P; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, O; Shevchenko, V; Shires, A; Silva Coutinho, R; Skwarnicki, T; Smith, N A; Smith, E; Smith, M; Sobczak, K; Soler, F J P; Soomro, F; Souza, D; Souza De Paula, B; Spaan, B; Sparkes, A; Spradlin, P; Stagni, F; Stahl, S; Steinkamp, O; Stoica, S; Stone, S; Storaci, B; Straticiuc, M; Straumann, U; Subbiah, V K; Swientek, S; Syropoulos, V; Szczekowski, M; Szczypka, P; Szumlak, T; T'Jampens, S; Teklishyn, M; Teodorescu, E; Teubert, F; Thomas, C; Thomas, E; van Tilburg, J; Tisserand, V; Tobin, M; Tolk, S; Tonelli, D; Topp-Joergensen, S; Torr, N; Tournefier, E; Tourneur, S; Tran, M T; Tresch, M; Tsaregorodtsev, A; Tsopelas, P; Tuning, N; Ubeda Garcia, M; Ukleja, A; Urner, D; Uwer, U; Vagnoni, V; Valenti, G; Vazquez Gomez, R; Vazquez Regueiro, P; Vecchi, S; Velthuis, J J; Veltri, M; Veneziano, G; Vesterinen, M; Viaud, B; Videau, I; Vieira, D; Vilasis-Cardona, X; Visniakov, J; Vollhardt, A; Volyanskyy, D; Voong, D; Vorobyev, A; Vorobyev, V; Voß, C; Voss, H; Waldi, R; Wallace, R; Wandernoth, S; Wang, J; Ward, D R; Watson, N K; Webber, A D; Websdale, D; Whitehead, M; Wicht, J; Wiedner, D; Wiggers, L; Wilkinson, G; Williams, M P; Williams, M; Wilson, F F; Wishahi, J; Witek, M; Witzeling, W; Wotton, S A; Wright, S; Wu, S; Wyllie, K; Xie, Y; Xing, F; Xing, Z; Yang, Z; Young, R; Yuan, X; Yushchenko, O; Zangoli, M; Zavertyaev, M; Zhang, F; Zhang, L; Zhang, W C; Zhang, Y; Zhelezov, A; Zhokhov, A; Zhong, L; Zvyagin, A

    The energy flow created in pp collisions at [Formula: see text] is studied within the pseudorapidity range 1.9< η <4.9 with data collected by the LHCb experiment. The measurements are performed for inclusive minimum-bias interactions, hard scattering processes and events with an enhanced or suppressed diffractive contribution. The results are compared to predictions given by Pythia-based and cosmic-ray event generators, which provide different models of soft hadronic interactions.

  18. Social Vulnerability Index (SoVI) for Delaware based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Delaware census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  19. Social Vulnerability Index (SoVI) for Alabama based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Alabama census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  20. Social Vulnerability Index (SoVI) for Washington based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Washington census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  1. Social Vulnerability Index (SoVI) for Hawaii based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Hawaii census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  2. Social Vulnerability Index (SoVI) for Mississippi based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Mississippi census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  3. Social Vulnerability Index (SoVI) for Louisiana based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Louisiana census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  4. Social Vulnerability Index (SoVI) for Wisconsin based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Wisconsin census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  5. Social Vulnerability Index (SoVI) for Georgia based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Georgia census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  6. Social Vulnerability Index (SoVI) for Michigan based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Michigan census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  7. Social Vulnerability Index (SoVI) for Virginia based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Virginia census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  8. Social Vulnerability Index (SoVI) for Maryland based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Maryland census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  9. Social Vulnerability Index (SoVI) for Maine based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Maine census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  10. Social Vulnerability Index (SoVI) for Alaska based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Alaska census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  11. Social Vulnerability Index (SoVI) for Illinois based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Illinois census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  12. Social Vulnerability Index (SoVI) for Ohio based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Ohio census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  13. Social Vulnerability Index (SoVI) for Pennsylvania based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Pennsylvania census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  14. Social Vulnerability Index (SoVI) for Connecticut based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Connecticut census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  15. Social Vulnerability Index (SoVI) for Massachusetts based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Massachusetts census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  16. Social Vulnerability Index (SoVI) for Texas based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Texas census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  17. Social Vulnerability Index (SoVI) for Indiana based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Indiana census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  18. Social Vulnerability Index (SoVI) for Oregon based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Oregon census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  19. « To see beyond the horizon of mere selfishness » : l’horizon moral dans les romans de George Eliot

    OpenAIRE

    Toussaint, Benjamine

    2015-01-01

    In spite of her apostasy, George Eliot still believed in the moral and spiritual values of Christianity and it is hardly surprising she should have used the metaphor of the horizon to refer to this ideal notion of the essence of Christianity since the horizon is both unreachable and yet always visible, showing the direction one ought to follow. Her characters’ moral odyssey is about learning to see beyond the limits of their own self-centered experience; however, as Lydgate underlines in Midd...

  20. A global census of marine microbes

    Digital Repository Service at National Institute of Oceanography (India)

    Amaral-Zettler, L.; Artigas, L.F.; Baross, J.; LokaBharathi, P.A; Boetius, A; Chandramohan, D.; Herndl, G.; Kogure, K.; Neal, P.; Pedros-Alio, C.; Ramette, A; Schouten, S.; Stal, L.; Thessen, A; De Leeuw, J.; Sogin, M.

    In this chapter we provide a brief history of what is known about marine microbial diversity, summarize our achievements in performing a global census of marine microbes, and reflect on the questions and priorities for the future of the marine...

  1. Demographic Data - TIGER/Line Shapefile, 2010, 2010 county, Miami-Dade County, FL, 2010 Census Census Tract County-based

    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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  4. TIGER/Line Shapefile, 2016, nation, U.S., Current Tribal Census Tract National

    Data.gov (United States)

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  5. In Brief: Deep-sea observatory

    Science.gov (United States)

    Showstack, Randy

    2008-11-01

    The first deep-sea ocean observatory offshore of the continental United States has begun operating in the waters off central California. The remotely operated Monterey Accelerated Research System (MARS) will allow scientists to monitor the deep sea continuously. Among the first devices to be hooked up to the observatory are instruments to monitor earthquakes, videotape deep-sea animals, and study the effects of acidification on seafloor animals. ``Some day we may look back at the first packets of data streaming in from the MARS observatory as the equivalent of those first words spoken by Alexander Graham Bell: `Watson, come here, I need you!','' commented Marcia McNutt, president and CEO of the Monterey Bay Aquarium Research Institute, which coordinated construction of the observatory. For more information, see http://www.mbari.org/news/news_releases/2008/mars-live/mars-live.html.

  6. 76 FR 13981 - Proposed Information Collection; Comment Request; 2012 Economic Census Covering the Construction...

    Science.gov (United States)

    2011-03-15

    ... essential information for government, business and the general public. The 2012 Economic Census covering the... Economic Census Covering the Construction Sector AGENCY: U.S. Census Bureau. ACTION: Notice. SUMMARY: The... provider of timely, relevant and quality data about the people and economy of the United States. Economic...

  7. 76 FR 13978 - Proposed Information Collection; Comment Request; 2012 Economic Census Covering the Manufacturing...

    Science.gov (United States)

    2011-03-15

    ... essential information for government, business and the general public. The 2012 Economic Census covering the... Economic Census Covering the Manufacturing Sector AGENCY: U.S. Census Bureau. ACTION: Notice. SUMMARY: The... provider of timely, relevant and quality data about the people and economy of the United States. Economic...

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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  7. TIGER/Line Shapefile, 2010, 2010 state, Wisconsin, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  8. TIGER/Line Shapefile, 2010, 2010 state, Missouri, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  9. TIGER/Line Shapefile, 2010, 2010 state, Illinois, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  10. TIGER/Line Shapefile, 2010, 2010 state, Alabama, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  11. TIGER/Line Shapefile, 2010, 2010 state, Minnesota, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  12. TIGER/Line Shapefile, 2010, 2010 state, Connecticut, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  13. TIGER/Line Shapefile, 2010, 2010 state, Wyoming, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  14. TIGER/Line Shapefile, 2010, 2010 state, Vermont, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  15. DEMOGRAPHICS OF THE PROVINCE OF CEBELIBEREKET ACCORDING TO 1927 POPULATION CENSUS

    OpenAIRE

    ÇANAK, Erdem

    2016-01-01

    The Republic of Turkey, has been established after a long time struggle for independence. In the meantime, thousands of citizens have lost their lives or became disabled. In addition new generations had grown up deprived of many things. Therefore Republican administration want to conduct census for develope sound policies for the future and learn about the quality and number of the population which is the main source of wealth of the country. In this direction, firstly The Statistics Departme...

  16. A multifaceted approach to understanding dynamic urban processes: satellites, surveys, and censuses.

    Science.gov (United States)

    Jones, B.; Balk, D.; Montgomery, M.; Liu, Z.

    2014-12-01

    Urbanization will arguably be the most significant demographic trend of the 21st century, particularly in fast-growing regions of the developing world. Characterizing urbanization in a spatial context, however, is a difficult task given only the moderate resolution data provided by traditional sources of demographic data (i.e., censuses and surveys). Using a sample of five world "mega-cities" we demonstrate how new satellite data products and new analysis of existing satellite data, when combined with new applications of census and survey microdata, can reveal more about cities and urbanization in combination than either data type can by itself. In addition to the partially modelled Global Urban-Rural Mapping Project (GRUMP) urban extents we consider four sources of remotely sensed data that can be used to estimate urban extents; the NOAA Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) intercallibrated nighttime lights time series data, the newer NOAA Visible Infrared Imager Radiometer Suite (VIIRS) nighttime lights data, the German Aerospace Center (DLR) radar satellite data, and Dense Sampling Method (DSM) analysis of the NASA scatterometer data. Demographic data come from national censuses and/or georeferenced survey data from the Demographic & Health Survey (DHS) program. We overlay demographic and remotely sensed data (e.g., Figs 1, 2) to address two questions; (1) how well do satellite derived measures of urban intensity correlate with demographic measures, and (2) how well are temporal changes in the data correlated. Using spatial regression techniques, we then estimate statistical relationships (controlling for influences such as elevation, coastal proximity, and economic development) between the remotely sensed and demographic data and test the ability of each to predict the other. Satellite derived imagery help us to better understand the evolution of the built environment and urban form, while the underlying demographic

  17. EnviroAtlas - Commute Time to Work by Census Block Group for the Conterminous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas dataset portrays the commute time of workers to their workplace for each Census Block Group (CBG) during 2008-2012. Data were compiled from the...

  18. Sea-Shore Interface Robotic Design

    Science.gov (United States)

    2014-06-01

    for various beachfront terrains. Robotics , Robot , Amphibious Vehicles, Mobility, Surf-Zone, Autonomous, Wheg, exoskeleton Unclassified Unclassified...controllers and to showcase the benefits of a modular construction. The result was an exoskeleton design with modular components, see Figure 2.1. Figure 2.1...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS SEA-SHORE INTERFACE ROBOTIC DESIGN by Timothy L. Bell June 2014 Thesis Advisor: Richard Harkins

  19. Living alone in South and Southeast Asia: An analysis of census data

    Directory of Open Access Journals (Sweden)

    Chai Podhisita

    2015-06-01

    Full Text Available Background: Living alone (in a one-person household has reached very high levels in some parts of the world. Across Asia the phenomenon is common in parts of East Asia, but has rarely been examined in South or Southeast Asia. Objective: The authors seek to establish from the evidence of censuses the main contours of living alone in South and Southeast Asia, and in doing so address issues of definition and measurement, particularly issues arising due to differences in the census handling of the 'group quarters' type of household. Methods: The paper examines 10 national censuses in the IPUMS archive of census micro-files. The data are explored for age profiles of living alone by sex, classified by urban versus rural residence and marital status. Results: The censuses reveal a combination of underlying commonalities among the countries and dates as well as distinct national features. There are distinct age profiles for males and females, and profiles typical of urban and rural sectors across countries. Living alone in group quarters is most common among young adults. Tabulation by marital status shows considerable variation among single young adults and elderly widowed or divorced/separated persons. It is also found that the proportions of the population not living with core family who are living alone vary widely by age and sex and across countries and years. Conclusions: Studies of living alone with national censuses must take note of whether conventional households and group quarters are included and how these are defined. Group quarters residence makes up a significant proportion of living alone among the young.

  20. CENSUS OF THE POPULATION, BUILDINGS AND HOUSING IN SWITZERLAND

    CERN Multimedia

    Relation with the Host States Service; Tel. 72848

    2000-01-01

    A census of the population, buildings and housing is to be conducted on the whole territory of the Swiss Confederation on 5 December 2000. For this purpose, those residing in Switzerland will receive a personal questionnaire at their place of residence plus a questionnaire on buildings and housing if they own real estate in Switzerland. The Swiss Permanent Mission to the International Organizations in Geneva has requested CERN to invite members of its personnel to complete these questionnaires and either to hand them to the census agents when they call at their places of residence on 5 December 2000 or to post them to the address indicated on the questionnaire.

  1. Horns Rev offshore wind farm. Introducing hard bottom substrate sea bottom and marine biology. Data report 2001

    International Nuclear Information System (INIS)

    Leonhard, S.B.; Pedersen, John

    2002-08-01

    The Ministry of Environment and Energy requested ELSAM and ELTRA to establish an offshore wind farm with an output of 150 MW in the waters of Horns Rev, approximately 15 km off Blaevandshuk, which is the most westerly point of Denmark. The first phase of construction of the wind farm have started in spring 2002. Before the construction activities take place, a baseline description of the benthos has been conducted as a part of an environmental monitoring programme for the introduction of hard bottom substrates in the North Sea. The establishment of a monitoring programme is required according to some environmental guidelines for offshore wind farms prepared by the Danish Energy Agency. The monitoring programme established for the benthic infauna was performed in spring 2001. In addition to a proposed fish investigation programme concerning the stomach contents of fish a comparative programme on benthos was established as part of the monitoring programme. The benthos sampling in connection with the fish programme was conducted in autumn 2001. This benthic survey includes sampling in a proposed reference area for the fish surveys north east of the wind farm. This report presents the data of the baseline environmental survey of the seabed in the wind farm site and in the proposed reference site and a brief description of the weather conditions at the time of sampling. (au)

  2. Federal census of the population in Switzerland

    CERN Multimedia

    DG Unit

    2011-01-01

    A federal census of the 2010 population has been underway since January 2011. The objective is to provide important insights into the composition of the resident population, households and families in Switzerland and identify trends. The census methods have been modernised so that it covers only information that is not already contained in Federal, Cantonal and municipal registries of persons; the information will be gathered via questionnaires issued to approximately 3% of the population residing in Switzerland. In order to obtain representative information about the local population, the Canton of Geneva has requested that questionnaires be issued to international civil servants and members of their families aged 15 and over who live in the Canton. They will be invited to respond to the questionnaire on a strictly voluntary basis. If they choose not to respond to the questionnaire, they will not be contacted again. The Permanent Swiss Mission to the International Organizations in Geneva wishes in advance t...

  3. 75 FR 81965 - Proposed Information Collection; Comment Request; Census Barriers, Attitudes, and Motivators...

    Science.gov (United States)

    2010-12-29

    ... communications activities for the 2010 Census, combining advertising, partnerships, public relations, Census in..., invites the general public and other Federal agencies to take this opportunity to comment on proposed and/or continuing information collections, as required by the Paperwork Reduction Act of 1995, Public Law...

  4. Production of [Formula: see text] and [Formula: see text] mesons up to high transverse momentum in pp collisions at 2.76 TeV.

    Science.gov (United States)

    Acharya, S; Adamová, D; Aggarwal, M M; Rinella, G Aglieri; Agnello, M; Agrawal, N; Ahammed, Z; Ahmad, N; Ahn, S U; Aiola, S; Akindinov, A; Alam, S N; Albuquerque, D S D; Aleksandrov, D; Alessandro, B; Alexandre, D; Molina, R Alfaro; Alici, A; Alkin, A; Alme, J; Alt, T; Altsybeev, I; Prado, C Alves Garcia; An, M; Andrei, C; Andrews, H A; Andronic, A; Anguelov, V; Anson, C; Antičić, T; Antinori, F; Antonioli, P; Anwar, R; Aphecetche, L; Appelshäuser, H; Arcelli, S; Arnaldi, R; Arnold, O W; Arsene, I C; Arslandok, M; Audurier, B; Augustinus, A; Averbeck, R; Awes, T; Azmi, M D; Badalà, A; Baek, Y W; Bagnasco, S; Bailhache, R; Bala, R; Baldisseri, A; Ball, M; Baral, R C; Barbano, A M; Barbera, R; Barile, F; Barioglio, L; Barnaföldi, G G; Barnby, L S; Barret, V; Bartalini, P; Barth, K; Bartke, J; Bartsch, E; Basile, M; Bastid, N; Basu, S; Bathen, B; Batigne, G; Camejo, A Batista; Batyunya, B; Batzing, P C; Bearden, I G; Beck, H; Bedda, C; Behera, N K; Belikov, I; Bellini, F; Martinez, H Bello; Bellwied, R; Beltran, L G E; Belyaev, V; Bencedi, G; Beole, S; Bercuci, A; Berdnikov, Y; Berenyi, D; Bertens, R A; Berzano, D; Betev, L; Bhasin, A; Bhat, I R; Bhati, A K; Bhattacharjee, B; Bhom, J; Bianchi, L; Bianchi, N; Bianchin, C; Bielčík, J; Bielčíková, J; Bilandzic, A; Biro, G; Biswas, R; Biswas, S; Blair, J T; Blau, D; Blume, C; Boca, G; Bock, F; Bogdanov, A; Boldizsár, L; Bombara, M; Bonomi, G; Bonora, M; Book, J; Borel, H; Borissov, A; Borri, M; Botta, E; Bourjau, C; Braun-Munzinger, P; Bregant, M; Broker, T A; Browning, T A; Broz, M; Brucken, E J; Bruna, E; Bruno, G E; Budnikov, D; Buesching, H; Bufalino, S; Buhler, P; Buitron, S A I; Buncic, P; Busch, O; Buthelezi, Z; Butt, J B; Buxton, J T; Cabala, J; Caffarri, D; Caines, H; Caliva, A; Villar, E Calvo; Camerini, P; Capon, A A; Carena, F; Carena, W; Carnesecchi, F; Castellanos, J Castillo; Castro, A J; Casula, E A R; Sanchez, C Ceballos; Cerello, P; Chang, B; Chapeland, S; Chartier, M; Charvet, J L; Chattopadhyay, S; Chattopadhyay, S; Chauvin, A; Cherney, M; Cheshkov, C; Cheynis, B; Barroso, V Chibante; Chinellato, D D; Cho, S; Chochula, P; Choi, K; Chojnacki, M; Choudhury, S; Christakoglou, P; Christensen, C H; Christiansen, P; Chujo, T; Chung, S U; Cicalo, C; Cifarelli, L; Cindolo, F; Cleymans, J; Colamaria, F; Colella, D; Collu, A; Colocci, M; Concas, M; Balbastre, G Conesa; Valle, Z Conesa Del; Connors, M E; Contreras, J G; Cormier, T M; Morales, Y Corrales; Maldonado, I Cortés; Cortese, P; Cosentino, M R; Costa, F; Costanza, S; Crkovská, J; Crochet, P; Cuautle, E; Cunqueiro, L; Dahms, T; Dainese, A; Danisch, M C; Danu, A; Das, D; Das, I; Das, S; Dash, A; Dash, S; De, S; De Caro, A; de Cataldo, G; de Conti, C; de Cuveland, J; De Falco, A; De Gruttola, D; De Marco, N; De Pasquale, S; De Souza, R D; Degenhardt, H F; Deisting, A; Deloff, A; Deplano, C; Dhankher, P; Di Bari, D; Di Mauro, A; Di Nezza, P; Di Ruzza, B; Corchero, M A Diaz; Dietel, T; Dillenseger, P; Divià, R; Djuvsland, Ø; Dobrin, A; Gimenez, D Domenicis; Dönigus, B; Dordic, O; Drozhzhova, T; Dubey, A K; Dubla, A; Ducroux, L; Duggal, A K; Dupieux, P; Ehlers, R J; Elia, D; Endress, E; Engel, H; Epple, E; Erazmus, B; Erhardt, F; Espagnon, B; Esumi, S; Eulisse, G; Eum, J; Evans, D; Evdokimov, S; Fabbietti, L; Faivre, J; Fantoni, A; Fasel, M; Feldkamp, L; Feliciello, A; Feofilov, G; Ferencei, J; Téllez, A Fernández; Ferreiro, E G; Ferretti, A; Festanti, A; Feuillard, V J G; Figiel, J; Figueredo, M A S; Filchagin, S; Finogeev, D; Fionda, F M; Fiore, E M; Floris, M; Foertsch, S; Foka, P; Fokin, S; Fragiacomo, E; Francescon, A; Francisco, A; Frankenfeld, U; Fronze, G G; Fuchs, U; Furget, C; Furs, A; Girard, M Fusco; Gaardhøje, J J; Gagliardi, M; Gago, A M; Gajdosova, K; Gallio, M; Galvan, C D; Ganoti, P; Gao, C; Garabatos, C; Garcia-Solis, E; Garg, K; Garg, P; Gargiulo, C; Gasik, P; Gauger, E F; Ducati, M B Gay; Germain, M; Ghosh, P; Ghosh, S K; Gianotti, P; Giubellino, P; Giubilato, P; Gladysz-Dziadus, E; Glässel, P; Coral, D M Goméz; Ramirez, A Gomez; Gonzalez, A S; Gonzalez, V; González-Zamora, P; Gorbunov, S; Görlich, L; Gotovac, S; Grabski, V; Graczykowski, L K; Graham, K L; Greiner, L; Grelli, A; Grigoras, C; Grigoriev, V; Grigoryan, A; Grigoryan, S; Grion, N; Gronefeld, J M; Grosa, F; Grosse-Oetringhaus, J F; Grosso, R; Gruber, L; Grull, F R; Guber, F; Guernane, R; Guerzoni, B; Gulbrandsen, K; Gunji, T; Gupta, A; Gupta, R; Guzman, I B; Haake, R; Hadjidakis, C; Hamagaki, H; Hamar, G; Hamon, J C; Harris, J W; Harton, A; Hatzifotiadou, D; Hayashi, S; Heckel, S T; Hellbär, E; Helstrup, H; Herghelegiu, A; Corral, G Herrera; Herrmann, F; Hess, B A; Hetland, K F; Hillemanns, H; Hippolyte, B; Hladky, J; Hohlweger, B; Horak, D; Hornung, S; Hosokawa, R; Hristov, P; Hughes, C; Humanic, T J; Hussain, N; Hussain, T; Hutter, D; Hwang, D S; Ilkaev, R; Inaba, M; Ippolitov, M; Irfan, M; Isakov, V; Ivanov, M; Ivanov, V; Izucheev, V; Jacak, B; Jacazio, N; Jacobs, P M; Jadhav, M B; Jadlovska, S; Jadlovsky, J; Jaelani, S; Jahnke, C; Jakubowska, M J; Janik, M A; Jayarathna, P H S Y; Jena, C; Jena, S; Jercic, M; Bustamante, R T Jimenez; Jones, P G; Jusko, A; Kalinak, P; Kalweit, A; Kamin, J; Kang, J H; Kaplin, V; Kar, S; Uysal, A Karasu; Karavichev, O; Karavicheva, T; Karayan, L; Karpechev, E; Kebschull, U; Keidel, R; Keijdener, D L D; Keil, M; Ketzer, B; Khan, P; Khan, S A; Khanzadeev, A; Kharlov, Y; Khatun, A; Khuntia, A; Kielbowicz, M M; Kileng, B; Kim, D; Kim, D W; Kim, D J; Kim, H; Kim, J S; Kim, J; Kim, M; Kim, M; Kim, S; Kim, T; Kirsch, S; Kisel, I; Kiselev, S; Kisiel, A; Kiss, G; Klay, J L; Klein, C; Klein, J; Klein-Bösing, C; Klewin, S; Kluge, A; Knichel, M L; Knospe, A G; Kobdaj, C; Kofarago, M; Kollegger, T; Kolojvari, A; Kondratiev, V; Kondratyeva, N; Kondratyuk, E; Konevskikh, A; Kopcik, M; Kour, M; Kouzinopoulos, C; Kovalenko, O; Kovalenko, V; Kowalski, M; Meethaleveedu, G Koyithatta; Králik, I; Kravčáková, A; Krivda, M; Krizek, F; Kryshen, E; Krzewicki, M; Kubera, A M; Kučera, V; Kuhn, C; Kuijer, P G; Kumar, A; Kumar, J; Kumar, L; Kumar, S; Kundu, S; Kurashvili, P; Kurepin, A; Kurepin, A B; Kuryakin, A; Kushpil, S; Kweon, M J; Kwon, Y; La Pointe, S L; La Rocca, P; Fernandes, C Lagana; Lakomov, I; Langoy, R; Lapidus, K; Lara, C; Lardeux, A; Lattuca, A; Laudi, E; Lavicka, R; Lazaridis, L; Lea, R; Leardini, L; Lee, S; Lehas, F; Lehner, S; Lehrbach, J; Lemmon, R C; Lenti, V; Leogrande, E; Monzón, I León; Lévai, P; Li, S; Li, X; Lien, J; Lietava, R; Lindal, S; Lindenstruth, V; Lippmann, C; Lisa, M A; Litichevskyi, V; Ljunggren, H M; Llope, W J; Lodato, D F; Loenne, P I; Loginov, V; Loizides, C; Loncar, P; Lopez, X; Torres, E López; Lowe, A; Luettig, P; Lunardon, M; Luparello, G; Lupi, M; Lutz, T H; Maevskaya, A; Mager, M; Mahajan, S; Mahmood, S M; Maire, A; Majka, R D; Malaev, M; Cervantes, I Maldonado; Malinina, L; Mal'Kevich, D; Malzacher, P; Mamonov, A; Manko, V; Manso, F; Manzari, V; Mao, Y; Marchisone, M; Mareš, J; Margagliotti, G V; Margotti, A; Margutti, J; Marín, A; Markert, C; Marquard, M; Martin, N A; Martinengo, P; Martinez, J A L; Martínez, M I; García, G Martínez; Pedreira, M Martinez; Mas, A; Masciocchi, S; Masera, M; Masoni, A; Mastroserio, A; Mathis, A M; Matyja, A; Mayer, C; Mazer, J; Mazzilli, M; Mazzoni, M A; Meddi, F; Melikyan, Y; Menchaca-Rocha, A; Meninno, E; Pérez, J Mercado; Meres, M; Mhlanga, S; Miake, Y; Mieskolainen, M M; Mihaylov, D L; Mikhaylov, K; Milano, L; Milosevic, J; Mischke, A; Mishra, A N; Miśkowiec, D; Mitra, J; Mitu, C M; Mohammadi, N; Mohanty, B; Khan, M Mohisin; Montes, E; De Godoy, D A Moreira; Moreno, L A P; Moretto, S; Morreale, A; Morsch, A; Muccifora, V; Mudnic, E; Mühlheim, D; Muhuri, S; Mukherjee, M; Mulligan, J D; Munhoz, M G; Münning, K; Munzer, R H; Murakami, H; Murray, S; Musa, L; Musinsky, J; Myers, C J; Naik, B; Nair, R; Nandi, B K; Nania, R; Nappi, E; Narayan, A; Naru, M U; da Luz, H Natal; Nattrass, C; Navarro, S R; Nayak, K; Nayak, R; Nayak, T K; Nazarenko, S; Nedosekin, A; De Oliveira, R A Negrao; Nellen, L; Nesbo, S V; Ng, F; Nicassio, M; Niculescu, M; Niedziela, J; Nielsen, B S; Nikolaev, S; Nikulin, S; Nikulin, V; Noferini, F; Nomokonov, P; Nooren, G; Noris, J C C; Norman, J; Nyanin, A; Nystrand, J; Oeschler, H; Oh, S; Ohlson, A; Okubo, T; Olah, L; Oleniacz, J; Da Silva, A C Oliveira; Oliver, M H; Onderwaater, J; Oppedisano, C; Orava, R; Oravec, M; Velasquez, A Ortiz; Oskarsson, A; Otwinowski, J; Oyama, K; Pachmayer, Y; Pacik, V; Pagano, D; Pagano, P; Paić, G; Palni, P; Pan, J; Pandey, A K; Panebianco, S; Papikyan, V; Pappalardo, G S; Pareek, P; Park, J; Park, W J; Parmar, S; Passfeld, A; Pathak, S P; Paticchio, V; Patra, R N; Paul, B; Pei, H; Peitzmann, T; Peng, X; Pereira, L G; Da Costa, H Pereira; Peresunko, D; Lezama, E Perez; Peskov, V; Pestov, Y; Petráček, V; Petrov, V; Petrovici, M; Petta, C; Pezzi, R P; Piano, S; Pikna, M; Pillot, P; Pimentel, L O D L; Pinazza, O; Pinsky, L; Piyarathna, D B; Oskoń, M Pł; Planinic, M; Pluta, J; Pochybova, S; Podesta-Lerma, P L M; Poghosyan, M G; Polichtchouk, B; Poljak, N; Poonsawat, W; Pop, A; Poppenborg, H; Porteboeuf-Houssais, S; Porter, J; Pospisil, J; Pozdniakov, V; Prasad, S K; Preghenella, R; Prino, F; Pruneau, C A; Pshenichnov, I; Puccio, M; Puddu, G; Pujahari, P; Punin, V; Putschke, J; Qvigstad, H; Rachevski, A; Raha, S; Rajput, S; Rak, J; Rakotozafindrabe, A; Ramello, L; Rami, F; Rana, D B; Raniwala, R; Raniwala, S; Räsänen, S S; Rascanu, B T; Rathee, D; Ratza, V; Ravasenga, I; Read, K F; Redlich, K; Rehman, A; Reichelt, P; Reidt, F; Ren, X; Renfordt, R; Reolon, A R; Reshetin, A; Reygers, K; Riabov, V; Ricci, R A; Richert, T; Richter, M; Riedler, P; Riegler, W; Riggi, F; Ristea, C; Cahuantzi, M Rodríguez; Røed, K; Rogochaya, E; Rohr, D; Röhrich, D; Rokita, P S; Ronchetti, F; Ronflette, L; Rosnet, P; Rossi, A; Rotondi, A; Roukoutakis, F; Roy, A; Roy, C; Roy, P; Montero, A J Rubio; Rueda, O V; Rui, R; Russo, R; Rustamov, A; Ryabinkin, E; Ryabov, Y; Rybicki, A; Saarinen, S; Sadhu, S; Sadovsky, S; Šafařík, K; Saha, S K; Sahlmuller, B; Sahoo, B; Sahoo, P; Sahoo, R; Sahoo, S; Sahu, P K; Saini, J; Sakai, S; Saleh, M A; Salzwedel, J; Sambyal, S; Samsonov, V; Sandoval, A; Sarkar, D; Sarkar, N; Sarma, P; Sas, M H P; Scapparone, E; Scarlassara, F; Scharenberg, R P; Scheid, H S; Schiaua, C; Schicker, R; Schmidt, C; Schmidt, H R; Schmidt, M O; Schmidt, M; Schuchmann, S; Schukraft, J; Schutz, Y; Schwarz, K; Schweda, K; Scioli, G; Scomparin, E; Scott, R; Šefčík, M; Seger, J E; Sekiguchi, Y; Sekihata, D; Selyuzhenkov, I; Senosi, K; Senyukov, S; Serradilla, E; Sett, P; Sevcenco, A; Shabanov, A; Shabetai, A; Shadura, O; Shahoyan, R; Shangaraev, A; Sharma, A; Sharma, A; Sharma, M; Sharma, M; Sharma, N; Sheikh, A I; Shigaki, K; Shou, Q; Shtejer, K; Sibiriak, Y; Siddhanta, S; Sielewicz, K M; Siemiarczuk, T; Silvermyr, D; Silvestre, C; Simatovic, G; Simonetti, G; Singaraju, R; Singh, R; Singhal, V; Sinha, T; Sitar, B; Sitta, M; Skaali, T B; Slupecki, M; Smirnov, N; Snellings, R J M; Snellman, T W; Song, J; Song, M; Soramel, F; Sorensen, S; Sozzi, F; Spiriti, E; Sputowska, I; Srivastava, B K; Stachel, J; Stan, I; Stankus, P; Stenlund, E; Stiller, J H; Stocco, D; Strmen, P; Suaide, A A P; Sugitate, T; Suire, C; Suleymanov, M; Suljic, M; Sultanov, R; Šumbera, M; Sumowidagdo, S; Suzuki, K; Swain, S; Szabo, A; Szarka, I; Szczepankiewicz, A; Szymanski, M; Tabassam, U; Takahashi, J; Tambave, G J; Tanaka, N; Tarhini, M; Tariq, M; Tarzila, M G; Tauro, A; Muñoz, G Tejeda; Telesca, A; Terasaki, K; Terrevoli, C; Teyssier, B; Thakur, D; Thakur, S; Thomas, D; Tieulent, R; Tikhonov, A; Timmins, A R; Toia, A; Tripathy, S; Trogolo, S; Trombetta, G; Trubnikov, V; Trzaska, W H; Trzeciak, B A; Tsuji, T; Tumkin, A; Turrisi, R; Tveter, T S; Ullaland, K; Umaka, E N; Uras, A; Usai, G L; Utrobicic, A; Vala, M; Van Der Maarel, J; Van Hoorne, J W; van Leeuwen, M; Vanat, T; Vyvre, P Vande; Varga, D; Vargas, A; Vargyas, M; Varma, R; Vasileiou, M; Vasiliev, A; Vauthier, A; Doce, O Vázquez; Vechernin, V; Veen, A M; Velure, A; Vercellin, E; Limón, S Vergara; Vernet, R; Vértesi, R; Vickovic, L; Vigolo, S; Viinikainen, J; Vilakazi, Z; Baillie, O Villalobos; Tello, A Villatoro; Vinogradov, A; Vinogradov, L; Virgili, T; Vislavicius, V; Vodopyanov, A; Völkl, M A; Voloshin, K; Voloshin, S A; Volpe, G; von Haller, B; Vorobyev, I; Voscek, D; Vranic, D; Vrláková, J; Wagner, B; Wagner, J; Wang, H; Wang, M; Watanabe, D; Watanabe, Y; Weber, M; Weber, S G; Weiser, D F; Wessels, J P; Westerhoff, U; Whitehead, A M; Wiechula, J; Wikne, J; Wilk, G; Wilkinson, J; Willems, G A; Williams, M C S; Windelband, B; Witt, W E; Yalcin, S; Yang, P; Yano, S; Yin, Z; Yokoyama, H; Yoo, I-K; Yoon, J H; Yurchenko, V; Zaccolo, V; Zaman, A; Zampolli, C; Zanoli, H J C; Zardoshti, N; Zarochentsev, A; Závada, P; Zaviyalov, N; Zbroszczyk, H; Zhalov, M; Zhang, H; Zhang, X; Zhang, Y; Zhang, C; Zhang, Z; Zhao, C; Zhigareva, N; Zhou, D; Zhou, Y; Zhou, Z; Zhu, H; Zhu, J; Zhu, X; Zichichi, A; Zimmermann, A; Zimmermann, M B; Zimmermann, S; Zinovjev, G; Zmeskal, J

    2017-01-01

    The invariant differential cross sections for inclusive [Formula: see text] and [Formula: see text] mesons at midrapidity were measured in pp collisions at [Formula: see text] TeV for transverse momenta [Formula: see text] GeV/ c and [Formula: see text] GeV/ c , respectively, using the ALICE detector. This large range in [Formula: see text] was achieved by combining various analysis techniques and different triggers involving the electromagnetic calorimeter (EMCal). In particular, a new single-cluster, shower-shape based method was developed for the identification of high-[Formula: see text] neutral pions, which exploits that the showers originating from their decay photons overlap in the EMCal. Above 4 GeV/[Formula: see text], the measured cross sections are found to exhibit a similar power-law behavior with an exponent of about 6.3. Next-to-leading-order perturbative QCD calculations differ from the measured cross sections by about 30% for the [Formula: see text], and between 30-50% for the [Formula: see text] meson, while generator-level simulations with PYTHIA 8.2 describe the data to better than 10-30%, except at [Formula: see text] GeV/[Formula: see text]. The new data can therefore be used to further improve the theoretical description of [Formula: see text] and [Formula: see text] meson production.

  5. "Mis on see luuletaja luule..." : [luuletused] / Juhan Viiding

    Index Scriptorium Estoniae

    Viiding, Juhan, 1948-1995

    2001-01-01

    Tekst eesti ja inglise k. J. Viidingu lühibiograafia eesti ja inglise k. lk. 151. Sisu: "Mis on see luuletaja luule..." = "So what is a poet's poetry then..." ; Eluküsimus = A question of life ; "sügisemees..." = "the autumn man..." ; "Lamades, seistes ja istudes..." = "Lying, standing or sitting..." ; "öö käest pannakse päeva käele..." = "from the hand of night to the hand of day..." ; "sa karjatad pikalt ja valuga..." = "you scream long and hard..." ; Tee = The road ; "tuisk on kolmandat päeva..." = "its's day three of the blizzard..." ; Latern = Street lamp ; "Eluaeg olen tahtnud õue..." = "All my life, I've wanted out..." ; "su südamepuuris on vaikus..." = "In the cage of your heart there is silence..."

  6. Mass-induced [|#8#|]Sea Level Variations in the Red Sea from Satellite Altimetry and GRACE

    Science.gov (United States)

    Feng, W.; Lemoine, J.; Zhong, M.; Hsu, H.

    2011-12-01

    We have analyzed mass-induced sea level variations (SLVs) in the Red Sea from steric-corrected altimetry and GRACE between January 2003 and December 2010. The steric component of SLVs in the Red Sea calculated from climatological temperature and salinity data is relatively small and anti-phase with the mass-induced SLV. The total SLV in the Red Sea is mainly driven by the mass-induced SLV, which increases in winter when the Red Sea gains the water mass from the Gulf of Aden and vice versa in summer. Spatial and temporal patterns of mass-induced SLVs in the Red Sea from steric-corrected altimetry agree very well with GRACE observations. Both of two independent observations show high annual amplitude in the central Red Sea (>20cm). Total mass-induced SLVs in the Red Sea from two independent observations have similar annual amplitude and phase. One main purpose of our work is to see whether GRGS's ten-day GRACE results can observe intra-seasonal mass change in the Red Sea. The wavelet coherence analysis indicates that GRGS's results show the high correlation with the steric-corrected SLVs on intra-seasonal time scale. The agreement is excellent for all the time-span until 1/3 year period and is patchy between 1/3 and 1/16 year period. Furthermore, water flux estimates from current-meter arrays and moorings show mass gain in winter and mass loss in summer, which is also consistent with altimetry and GRACE.

  7. Sequence spaces [Formula: see text] and [Formula: see text] with application in clustering.

    Science.gov (United States)

    Khan, Mohd Shoaib; Alamri, Badriah As; Mursaleen, M; Lohani, Qm Danish

    2017-01-01

    Distance measures play a central role in evolving the clustering technique. Due to the rich mathematical background and natural implementation of [Formula: see text] distance measures, researchers were motivated to use them in almost every clustering process. Beside [Formula: see text] distance measures, there exist several distance measures. Sargent introduced a special type of distance measures [Formula: see text] and [Formula: see text] which is closely related to [Formula: see text]. In this paper, we generalized the Sargent sequence spaces through introduction of [Formula: see text] and [Formula: see text] sequence spaces. Moreover, it is shown that both spaces are BK -spaces, and one is a dual of another. Further, we have clustered the two-moon dataset by using an induced [Formula: see text]-distance measure (induced by the Sargent sequence space [Formula: see text]) in the k-means clustering algorithm. The clustering result established the efficacy of replacing the Euclidean distance measure by the [Formula: see text]-distance measure in the k-means algorithm.

  8. Rio Arriba County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  9. McKinley County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  10. San Miguel County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  11. De Baca County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  12. San Juan County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  13. New Mexico, 2010 Census Block State-based

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  14. Santa Fe County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  15. Los Alamos County 2010 Census Block Groups

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  16. VT 2010 Census Block Group Boundaries and Statistics

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) BLCKGR2010 contains a subset of attributes from Summary File 1 of the 2010 Decennial Census. The TIGER/Line Files are shapefiles and related...

  17. Racial measurement and statistical field in Brazilian census (1872-1940: a convergent approach

    Directory of Open Access Journals (Sweden)

    Alexandre de Paiva Rio Camargo

    2009-12-01

    Full Text Available This paper investigates the meanings given by the racial classification in several Brazilian census. It proposes a convergent analysis of the social-political conventions established for the research (1872, 1890, 1940 or omission (1920 of the racial item of the surveys in different historical moments and the emergency of the technical community of statisticians in the midst of changing in paradigm census. As a method, it assumes a circularity between the social system of racial classification, the interpretations chapters on national identity hired to introduce the census – “O povo brasileiro e sua evolução” by Oliveira Vianna (1920, and “A cultura brasileira” by Fernando de Azevedo (1940 – and the role played by the technical requirements in the taken positions of the statisticians. The article analyzes the reports written by the census committees and organizers at the verbal level, in order to compare the arguments presented to the informations and crossings obtained in the matrix level. It takes the 1940 census as a turning point in the statistical activity because it reveals the structural conflict between the policy function primarily reserved for statistics and the consecration of the technical competence. Accordingly, this paper addresses the gradual release of statistical ideology from the political propaganda on the color.

  18. Social Vulnerability Index (SoVI) for Coastal States based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of coastal states census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  19. Social Vulnerability Index (SoVI) for Rhode Island based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of Rhode Island census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  20. Social Vulnerability Index (SoVI) for New Hampshire based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of New Hampshire census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  1. Social Vulnerability Index (SoVI) for New Jersey based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of New Jersey census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  2. Social Vulnerability Index (SoVI) for New York based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of New York census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  3. Social Vulnerability Index (SoVI) for South Carolina based on 2000 Census Block Groups

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data depicts the social vulnerability of South Carolina census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

  4. Competing probabilistic models for catch-effort relationships in wildlife censuses

    Energy Technology Data Exchange (ETDEWEB)

    Skalski, J.R.; Robson, D.S.; Matsuzaki, C.L.

    1983-01-01

    Two probabilistic models are presented for describing the chance that an animal is captured during a wildlife census, as a function of trapping effort. The models in turn are used to propose relationships between sampling intensity and catch-per-unit-effort (C.P.U.E.) that were field tested on small mammal populations. Capture data suggests a model of diminshing C.P.U.E. with increasing levels of trapping intensity. The catch-effort model is used to illustrate optimization procedures in the design of mark-recapture experiments for censusing wild populations. 14 references, 2 tables.

  5. Harding County Blocks, Total Population (2010)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article...

  6. 76 FR 14647 - Proposed Information Collection; Comment Request; 2012 Economic Census Covering the Mining Sector

    Science.gov (United States)

    2011-03-17

    ... essential information for government, business and the general public. The 2012 Economic Census covering the... Economic Census Covering the Mining Sector AGENCY: U.S. Census Bureau. ACTION: Notice. SUMMARY: The... provider of timely, relevant and quality data about the people and economy of the United States. Economic...

  7. Revisiting the definition of local hardness and hardness kernel.

    Science.gov (United States)

    Polanco-Ramírez, Carlos A; Franco-Pérez, Marco; Carmona-Espíndola, Javier; Gázquez, José L; Ayers, Paul W

    2017-05-17

    An analysis of the hardness kernel and local hardness is performed to propose new definitions for these quantities that follow a similar pattern to the one that characterizes the quantities associated with softness, that is, we have derived new definitions for which the integral of the hardness kernel over the whole space of one of the variables leads to local hardness, and the integral of local hardness over the whole space leads to global hardness. A basic aspect of the present approach is that global hardness keeps its identity as the second derivative of energy with respect to the number of electrons. Local hardness thus obtained depends on the first and second derivatives of energy and electron density with respect to the number of electrons. When these derivatives are approximated by a smooth quadratic interpolation of energy, the expression for local hardness reduces to the one intuitively proposed by Meneses, Tiznado, Contreras and Fuentealba. However, when one combines the first directional derivatives with smooth second derivatives one finds additional terms that allow one to differentiate local hardness for electrophilic attack from the one for nucleophilic attack. Numerical results related to electrophilic attacks on substituted pyridines, substituted benzenes and substituted ethenes are presented to show the overall performance of the new definition.

  8. TIGER/Line Shapefile, 2016, 2010 nation, U.S., 2010 Census Urban Area National

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master...

  9. TIGER/Line Shapefile, 2015, nation, U.S., Current Tribal Census Tract National Shapefile

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master...

  10. TIGER/Line Shapefile, 2017, 2010 nation, U.S., 2010 Census Urban Area National

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master...

  11. TIGER/Line Shapefile, 2015, 2010 nation, U.S., 2010 Census Urban Area National

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master...

  12. Census Bureau Reports at Least 350 Languages Spoken in U.S. Homes

    Science.gov (United States)

    Employment and Payroll Survey of Business Owners Work from Home Our statistics highlight trends in household statistics from multiple surveys. Data Tools & Apps Main American FactFinder Census Business Builder My Classification Codes (i.e., NAICS) Economic Census Economic Indicators Economic Studies Industry Statistics

  13. Playing Moderately Hard to Get

    Directory of Open Access Journals (Sweden)

    Stephen Reysen

    2013-12-01

    Full Text Available In two studies, we examined the effect of different degrees of attraction reciprocation on ratings of attraction toward a potential romantic partner. Undergraduate college student participants imagined a potential romantic partner who reciprocated a low (reciprocating attraction one day a week, moderate (reciprocating attraction three days a week, high (reciprocating attraction five days a week, or unspecified degree of attraction (no mention of reciprocation. Participants then rated their degree of attraction toward the potential partner. The results of Study 1 provided only partial support for Brehm’s emotion intensity theory. However, after revising the high reciprocation condition vignette in Study 2, supporting Brehm’s emotion intensity theory, results show that a potential partners’ display of reciprocation of attraction acted as a deterrent to participants’ intensity of experienced attraction to the potential partner. The results support the notion that playing moderately hard to get elicits more intense feelings of attraction from potential suitors than playing too easy or too hard to get. Discussion of previous research examining playing hard to get is also re-examined through an emotion intensity theory theoretical lens.

  14. 77 FR 18790 - Proposed Information Collection; Comment Request; Generic Clearance for the 2020 Census Field Tests

    Science.gov (United States)

    2012-03-28

    ... should be directed to Erin Love, Census Bureau, HQ-3H468E, Washington, DC 20233; (301) 763-2034 (or via the Internet at erin.s.love@census.gov ). SUPPLEMENTARY INFORMATION: I. Abstract The U.S. Census... telephone interviews. III. Data OMB Control Number: None. Form Number: Not yet determined. Type of Review...

  15. TIGER/Line Shapefile, 2010, 2010 state, New York, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  16. TIGER/Line Shapefile, 2010, 2010 state, South Dakota, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  17. TIGER/Line Shapefile, 2010, 2010 state, West Virginia, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  18. TIGER/Line Shapefile, 2010, 2010 state, Rhode Island, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  19. TIGER/Line Shapefile, 2010, 2010 state, North Carolina, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  20. TIGER/Line Shapefile, 2010, 2010 state, North Dakota, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  1. TIGER/Line Shapefile, 2010, 2010 state, New Hampshire, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  2. TIGER/Line Shapefile, 2010, 2010 state, South Carolina, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  3. TIGER/Line Shapefile, 2010, 2010 state, New Jersey, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  4. American Indian Areas Located in Region 2 (CENSUS.AM_INDIAN_AREAS_R2)

    Data.gov (United States)

    U.S. Environmental Protection Agency — There are both legal and statistical American Indian, Alaska Native, and native Hawaiian entities for which the U.S. Census Bureau provides data for Census 2000. The...

  5. Hard and Soft Governance

    DEFF Research Database (Denmark)

    Moos, Lejf

    2009-01-01

    of Denmark, and finally the third layer: the leadership used in Danish schools. The use of 'soft governance' is shifting the focus of governance and leadership from decisions towards influence and power and thus shifting the focus of the processes from the decision-making itself towards more focus......The governance and leadership at transnational, national and school level seem to be converging into a number of isomorphic forms as we see a tendency towards substituting 'hard' forms of governance, that are legally binding, with 'soft' forms based on persuasion and advice. This article analyses...... and discusses governance forms at several levels. The first layer is the global: the methods of 'soft governance' that are being utilised by transnational agencies. The second layer is the national and local: the shift in national and local governance seen in many countries, but here demonstrated in the case...

  6. Why Are Drugs So Hard to Quit?

    Medline Plus

    Full Text Available ... Quitting drugs is hard because addiction is a brain disease. Your brain is like a control tower that sends out ... and choices. Addiction changes the signals in your brain and makes it hard to feel OK without ...

  7. ASSESSMENT OF EFFICIENCY OF APPLICATION OF TOOLS OF CARRYING OUT THE ALL-RUSSIAN POPULATION CENSUS OF 2020

    Directory of Open Access Journals (Sweden)

    Oleg V. Manzhula

    2014-01-01

    Full Text Available At a stage of preparation for the All-Russian population census of 2020 it is necessary to develop methodical and technological support of processes of carrying out census for increase of reliability of data collection and quality of information processing of population census of the Russian Federation with use of modern information and communication technologies, and also a technique of an assessment of efficiency of application of tools of carrying out census

  8. Visual Census of the Reef Fishes in the Natural Reserve of the ...

    African Journals Online (AJOL)

    Keywords: visual census, reef fishes, natural reserve, Glorieuses Islands, western Indian Ocean This paper constitutes the first qualitative study of coral reef fish populations in the archipelago of the Glorieuses Islands (northern Mozambique Channel). Sampling by visual census techniques, at depths between 0 and 15 ...

  9. Population: Census Bureau Total Estimates (2010-2012)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — Total population estimates are estimates of the total number of residents living in an area on July 1 of each year. The Census Bureau’s Population Division produces...

  10. Towards validation of the Internet Census 2012

    NARCIS (Netherlands)

    Maan, Dirk; Cardoso de Santanna, José Jair; Sperotto, Anna; de Boer, Pieter-Tjerk; Kermarrec, Yvon

    2014-01-01

    The reliability of the ``Internet Census 2012'' (IC), an anonymously published scan of the entire IPv4 address space, is not a priori clear. As a step towards validation of this dataset, we compare it to logged reference data on a /16 network, and present an approach to systematically handle

  11. Santa Fe County 1990 Census Subcounty Areas

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — This dataset is a vector digital data structure taken from the Census Bureau's TIGER/Line Files, 1994, for New Mexico. The source software used was ARC/INFO 7.0.3

  12. Smoking prevalence among doctors and nurses-2013 New Zealand census data.

    Science.gov (United States)

    Edwards, Richard; Tu, Danny; Stanley, James; Martin, Greg; Gifford, Heather; Newcombe, Rhiannon

    2018-03-09

    To examine recent smoking trends among doctors and nurses in New Zealand. Analysis of smoking prevalence in the 2013 New Zealand Census and comparison with previous census data. The 2013 census included 7,065 male and 5,619 female doctors, and 2,988 male and 36,138 female nurses. Non-response to smoking questions was less than 3%. In 2013, 2% of male and female doctors and 9% of male and 8% of female nurses were regular cigarette smokers. This compared with 4% male and 3% female doctors, and 20% male and 13% female nurses in 2006. Psychiatric nurses had the highest smoking prevalence (15% male, 18% female). More Māori doctors (6.8%) and nurses (19.3%) smoked. Around 96% of young (New Zealand doctors had achieved the Smokefree 2025 goal of minimal (workplace smoking cessation support may be an efficient means to reduce smoking among key occupational groups, and may help reduce population smoking prevalence.

  13. Use of laser rhinoscopy to treat a nasal obstruction in a captive California sea lion (Zalophus californianus).

    Science.gov (United States)

    Sherrill, Johanna; Peavy, George M; Kopit, Mark J; Garner, Michael M; Gardiner, Chris H; Adams, Lance M

    2004-06-01

    Laser rhinoscopy was used to treat a nasal obstruction in a captive California sea lion (Zalophus californianus). The rehabilitated, adult, female sea lion developed mucopurulent, intermittent, bilateral nasal discharge and functional nasal obstruction 20 mo after acquisition by the Aquarium of the Pacific in Long Beach, California. A 3-mm-thick soft tissue structure spanning the region between the soft and hard palates, a deviated nasal septum, and several nasopharyngeal polyps were identified. Biopsies and cultures of the obstructive web showed ulcerative granulation tissue with suppurative inflammation, bacterial infection, and a partial section of an arthropod larva (not speciated). Laser rhinoscopy was performed to relieve the caudal nasopharyngeal obstruction and ablate the polyps. The sea lion appeared to breathe through the nares with lessened nasal discharge for a period of 6 wk after laser therapy, but within 8 wk the mucopurulent nasal discharge returned, the obstruction had reformed, and the sea lion was euthanized. Postmortem examination confirmed antemortem diagnoses of caudal nasopharyngeal obstruction secondary to inflammatory tissue; however, no additional sections of arthropod parasites were located microscopically.

  14. Sea otter dental enamel is highly resistant to chipping due to its microstructure.

    Science.gov (United States)

    Ziscovici, Charles; Lucas, Peter W; Constantino, Paul J; Bromage, Timothy G; van Casteren, Adam

    2014-10-01

    Dental enamel is prone to damage by chipping with large hard objects at forces that depend on chip size and enamel toughness. Experiments on modern human teeth have suggested that some ante-mortem chips on fossil hominin enamel were produced by bite forces near physiological maxima. Here, we show that equivalent chips in sea otter enamel require even higher forces than human enamel. Increased fracture resistance correlates with more intense enamel prism decussation, often seen also in some fossil hominins. It is possible therefore that enamel chips in such hominins may have formed at even greater forces than currently envisaged. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  15. The future for the Global Sea Level Observing System (GLOSS) Sea Level Data Rescue

    Science.gov (United States)

    Bradshaw, Elizabeth; Matthews, Andrew; Rickards, Lesley; Aarup, Thorkild

    2016-04-01

    Historical sea level data are rare and unrepeatable measurements with a number of applications in climate studies (sea level rise), oceanography (ocean currents, tides, surges), geodesy (national datum), geophysics and geology (coastal land movements) and other disciplines. However, long-term time series are concentrated in the northern hemisphere and there are no records at the Permanent Service for Mean Sea Level (PSMSL) global data bank longer than 100 years in the Arctic, Africa, South America or Antarctica. Data archaeology activities will help fill in the gaps in the global dataset and improve global sea level reconstruction. The Global Sea Level Observing System (GLOSS) is an international programme conducted under the auspices of the WMO-IOC Joint Technical Commission for Oceanography and Marine Meteorology. It was set up in 1985 to collect long-term tide gauge observations and to develop systems and standards "for ocean monitoring and flood warning purposes". At the GLOSS-GE-XIV Meeting in 2015, GLOSS agreed on a number of action items to be developed in the next two years. These were: 1. To explore mareogram digitisation applications, including NUNIEAU (more information available at: http://www.mediterranee.cerema.fr/logiciel-de-numerisation-des-enregistrements-r57.html) and other recent developments in scanning/digitisation software, such as IEDRO's Weather Wizards program, to see if they could be used via a browser. 2. To publicise sea level data archaeology and rescue by: • maintaining and regularly updating the Sea Level Data Archaeology page on the GLOSS website • strengthening links to the GLOSS data centres and data rescue organisations e.g. linking to IEDRO, ACRE, RDA • restarting the sea level data rescue blog with monthly posts. 3. Investigate sources of funding for data archaeology and rescue projects. 4. Propose "Guidelines" for rescuing sea level data. These action items will aid the discovery, scanning, digitising and quality control

  16. Eliciting and Defining Requirements Based on Metaevaluation: the Case of the CRAS 2008 Census

    Directory of Open Access Journals (Sweden)

    Edilson Ferneda

    2014-10-01

    Full Text Available The Brazilian Ministry of Social Development and Fight against Hunger (MDS regularly promotes the evaluation of its social programs, such as those developed in the Reference Centers for Social Assistance (CRAS. Such evaluations make use of a web system that supports the collection and processing of information as well as the dissemination of its results to local, regional and central government officials through the so-called CRAS Census. A meta-evaluation of the CRAS 2008 Census was carried out based on criteria specified by the Joint Committee (1994, from which we elicited requirements that enabled improvements of the web system. The article reports new requirements elicited from the meta-evaluation of the CRAS 2008 Census, held in the period 2009-2010. The approach of meta-evaluation as an alternative source of requirements elicitation took into consideration results from evaluations of social programs in order to identify system problems without the usual need of intense interaction with users. This approach revealed opportunities for improvements in the evaluation process that led to the elicitation of requirements for the computerized system. Some of the elicited features were incorporated into the Census 2010 and others may be incorporated in future censuses.

  17. Hard time to be parents? Sea urchin fishery shifts potential reproductive contribution of population onto the shoulders of the young adults

    Directory of Open Access Journals (Sweden)

    Barbara Loi

    2017-03-01

    Full Text Available Background In Sardinia, as in other regions of the Mediterranean Sea, sustainable fisheries of the sea urchin Paracentrotus lividus have become a necessity. At harvesting sites, the systematic removal of large individuals (diameter ≥ 50 mm seriously compromises the biological and ecological functions of sea urchin populations. Specifically, in this study, we compared the reproductive potential of the populations from Mediterranean coastal areas which have different levels of sea urchin fishing pressure. The areas were located at Su Pallosu Bay, where pressure is high and Tavolara-Punta Coda Cavallo, a marine protected area where sea urchin harvesting is low. Methods Reproductive potential was estimated by calculating the gonadosomatic index (GSI from June 2013 to May 2014 both for individuals of commercial size (diameter without spines, TD ≥ 50 mm and the undersized ones with gonads (30 ≤ TD < 40 mm and 40 ≤ TD < 50 mm. Gamete output was calculated for the commercial-size class and the undersized individuals with fertile gonads (40 ≤ TD < 50 mm in relation to their natural density (gamete output per m2. Results The reproductive potential of populations was slightly different at the beginning of the sampling period but it progressed at different rates with an early spring spawning event in the high-pressure zone and two gamete depositions in early and late spring in the low-pressure zone. For each fertile size class, GSI values changed significantly during the year of our study and between the two zones. Although the multiple spawning events determined a two-fold higher total gamete output of population (popTGO in the low-pressure zone, the population mean gamete output (popMGO was similar in the two zones. In the high-pressure zone, the commercial-sized individuals represented approximatively 5% of the population, with almost all the individuals smaller than 60 mm producing an amount of gametes nearly three times lower than the

  18. An Earth System Science Program for the Baltic Sea Region

    Science.gov (United States)

    Meier, H. E. M.; Rutgersson, A.; Reckermann, M.

    2014-04-01

    From Russia in the east to Sweden, Denmark, and Germany in the west, reaching south to the tips of the Czech Republic, Slovakia, and Ukraine, the Baltic Sea watershed drains nearly 20% of Europe (see Figure 1). In the highly populated south, the temperate climate hosts intensive agriculture and industry. In the north, the landscape is boreal and rural. In the Baltic Sea itself, complex bathymetry and stratification patterns as well as extended hypoxic and anoxic deep waters add to the diversity. Yet in recent history, the differences across the Baltic Sea region have been more than physical: In the mid-20th century, the watershed was split in two.

  19. Public census data on CD-ROM at Lawrence Berkeley Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Merrill, D.W.

    1992-07-02

    In connection with the Comprehensive Epidemiologic Data Resource (CEDR) and Populations at Risk to Environmental Pollution (PAREP) projects, of the Information and Computing Sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), are using public socioeconomic and geographic data files which are available to CEDR and PAREP collaborators via LBL's computing network. At this time 67 CD-ROM diskettes (approximately 35 gigabytes) are on line via the Unix file server cedrcd.lbl.gov. Most of the files are from the US Bureau of the Census, and most pertain to the 1990 Census of Population and Housing. This paper contains a list of the CD-ROMs available.

  20. The Barbados Sea Level Record

    Science.gov (United States)

    Fairbanks, R. G.; Mortlock, R. A.; Abdul, N. A.; Wright, J. D.; Cao, L.; Mey, J. L.

    2013-12-01

    Additional offshore drill cores, nearly 100 new radiometric dates, and more than 1000 kilometers of Multibeam mapping greatly enhance the Barbados Sea Level record. Extensive Multibeam mapping around the entire island covers approximately 2650 km2 of the sea bottom and now integrates the offshore reef topography and Barbados Sea Level Record with the unparalleled onshore core collection, digital elevation maps, and Pleistocene sea level record spanning the past one million years. The reef crest coral, Acropora palmata, remains the stalwart indicator of sea level for many reasons that are validated by our redundant sea level records and redundant dating via Th/U and Pa/U analyses. Microanalysis and densitometry studies better explain why Acropora palmata is so well preserved in the Pleistocene reef records and therefore why it is the species of choice for sea level reconstructions and radiometric dating. New drill cores into reefs that formed during Marine Isotope Stage 3 lead us to a model of diagenesis that allows us to better prospect for unaltered coral samples in older reefs that may be suitable for Th/U dating. Equally important, our diagenesis model reinforces our rigorous sample quality criteria in a more quantitative manner. The Barbados Sea Level record has a sampling resolution of better than 100 years throughout much of the last deglaciation showing unprecedented detail in redundant drill cores. The Melt Water Pulses (MWP1A and MWP1B) are well resolved and the intervening interval that includes the Younger Dryas reveals sea level changes in new detail that are consistent with the terrestrial records of ice margins (see Abdul et al., this section). More than 100 paired Th/U and radiocarbon ages place the Barbados Sea Level Record unambiguously on the radiocarbon time scale for direct comparisons with the terrestrial records of ice margin changes.

  1. The Holy See.

    Science.gov (United States)

    1987-03-01

    Focus in this discussion of the Holy See is on geography, the people, history, government and institutions, foreign relations, and relations with the US and the Holy See. Vatican City occupies 0.439 square kilometers (109 acres). Some 1000 individuals live within the Vatican's walls, most of whom are Italian or Swiss by nationality. Vatican citizenship usually is accorded only to those who reside in Vatican City by reason of office or employment and, with certain restrictions, to their families. The Pope delegates the internal administration of Vatican City to the Pontifical Commission for the State of the Vatican City, headed by the Cardinal Secretary of State. The legal system is based on canon law or the laws of the city of Rome. On February 11, 1929, the Holy See and the Italian government signed 3 agreements regulating a dispute since 1871 about the Law of Guarantees, law which sought to assure the Pope's spiritual freedom, an income, and special status for the Vatican area. The agreements include: a treaty recognizing the independence and sovereignty of the Holy See and creating the State of the Vatican City; a concordat fixing the relations between the government and the church within Italy; and a financial convention providing the Holy See with compensation for its losses in 1870. The Pope, at this time John Paul II, exercises supreme legislative, executive, and judicial power over the Holy See and within the State of the Vatican City. The Pope rules the Holy See through the Roman Curia and Papal Civil Service, which staffs it. The Holy See, which carries on an active diplomacy of considerable scope and variety, is particularly active diplomatically in international organizations. The US maintained consular relations with the Papal States from 1797-1870 and diplomatic relations with the Pope in his capacity as head of the Papal States. These relations lapsed with the final loss of all papal territories in 1870. In 1984, the US and the Holy See announced the

  2. TIGER/Line Shapefile, 2016, Series Information for the Current Census Tract State-based Shapefile

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master...

  3. Measurement of the [Formula: see text] and [Formula: see text] production cross sections in multilepton final states using 3.2 fb[Formula: see text] of [Formula: see text] collisions at [Formula: see text] = 13 TeV with the ATLAS detector.

    Science.gov (United States)

    Aaboud, M; Aad, G; Abbott, B; Abdallah, J; Abdinov, O; Abeloos, B; Aben, R; AbouZeid, O S; Abraham, N L; Abramowicz, H; Abreu, H; Abreu, R; Abulaiti, Y; Acharya, B S; Adamczyk, L; Adams, D L; Adelman, J; Adomeit, S; Adye, T; Affolder, A A; Agatonovic-Jovin, T; Agricola, J; Aguilar-Saavedra, J A; Ahlen, S P; Ahmadov, F; Aielli, G; Akerstedt, H; Åkesson, T P A; Akimov, A V; Alberghi, G L; Albert, J; Albrand, S; Alconada Verzini, M J; Aleksa, M; Aleksandrov, I N; Alexa, C; Alexander, G; Alexopoulos, T; Alhroob, M; Ali, B; Aliev, M; Alimonti, G; Alison, J; Alkire, S P; Allbrooke, B M M; Allen, B W; Allport, P P; Aloisio, A; Alonso, A; Alonso, F; Alpigiani, C; Alstaty, M; Alvarez Gonzalez, B; Álvarez Piqueras, D; Alviggi, M G; Amadio, B T; Amako, K; Amaral Coutinho, Y; Amelung, C; Amidei, D; Amor Dos Santos, S P; Amorim, A; Amoroso, S; Amundsen, G; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anders, J K; Anderson, K J; Andreazza, A; Andrei, V; Angelidakis, S; Angelozzi, I; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A V; Anjos, N; Annovi, A; Antel, C; Antonelli, M; Antonov, A; Anulli, F; Aoki, M; Aperio Bella, L; Arabidze, G; Arai, Y; Araque, J P; Arce, A T H; Arduh, F A; Arguin, J-F; Argyropoulos, S; Arik, M; Armbruster, A J; Armitage, L J; Arnaez, O; Arnold, H; Arratia, M; Arslan, O; Artamonov, A; Artoni, G; Artz, S; Asai, S; Asbah, N; Ashkenazi, A; Åsman, B; Asquith, L; Assamagan, K; Astalos, R; Atkinson, M; Atlay, N B; Augsten, K; Avolio, G; Axen, B; Ayoub, M K; Azuelos, G; Baak, M A; Baas, A E; Baca, M J; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Bagiacchi, P; Bagnaia, P; Bai, Y; Baines, J T; Baker, O K; Baldin, E M; Balek, P; Balestri, T; Balli, F; Balunas, W K; Banas, E; Banerjee, Sw; Bannoura, A A E; Barak, L; Barberio, E L; Barberis, D; Barbero, M; Barillari, T; Barklow, T; Barlow, N; Barnes, S L; Barnett, B M; Barnett, R M; Barnovska-Blenessy, Z; Baroncelli, A; Barone, G; Barr, A J; Barranco Navarro, L; Barreiro, F; Barreiro Guimarães da Costa, J; Bartoldus, R; Barton, A E; Bartos, P; Basalaev, A; Bassalat, A; Bates, R L; Batista, S J; Batley, J R; Battaglia, M; Bauce, M; Bauer, F; Bawa, H S; Beacham, J B; Beattie, M D; Beau, T; Beauchemin, P H; Bechtle, P; Beck, H P; Becker, K; Becker, M; Beckingham, M; Becot, C; Beddall, A J; Beddall, A; Bednyakov, V A; Bedognetti, M; Bee, C P; Beemster, L J; Beermann, T A; Begel, M; Behr, J K; Belanger-Champagne, C; Bell, A S; Bella, G; Bellagamba, L; Bellerive, A; Bellomo, M; Belotskiy, K; Beltramello, O; Belyaev, N L; Benary, O; Benchekroun, D; Bender, M; Bendtz, K; Benekos, N; Benhammou, Y; Benhar Noccioli, E; Benitez, J; Benjamin, D P; Bensinger, J R; Bentvelsen, S; Beresford, L; Beretta, M; Berge, D; Bergeaas Kuutmann, E; Berger, N; Beringer, J; Berlendis, S; Bernard, N R; Bernius, C; Bernlochner, F U; Berry, T; Berta, P; Bertella, C; Bertoli, G; Bertolucci, F; Bertram, I A; Bertsche, C; Bertsche, D; Besjes, G J; Bessidskaia Bylund, O; Bessner, M; Besson, N; Betancourt, C; Bethke, S; Bevan, A J; Bhimji, W; Bianchi, R M; Bianchini, L; Bianco, M; Biebel, O; Biedermann, D; Bielski, R; Biesuz, N V; Biglietti, M; De Mendizabal, J Bilbao; Bilokon, H; Bindi, M; Binet, S; Bingul, A; Bini, C; Biondi, S; Bjergaard, D M; Black, C W; Black, J E; Black, K M; Blackburn, D; Blair, R E; Blanchard, J-B; Blanco, J E; Blazek, T; Bloch, I; Blocker, C; Blum, W; Blumenschein, U; Blunier, S; Bobbink, G J; Bobrovnikov, V S; Bocchetta, S S; Bocci, A; Bock, C; Boehler, M; Boerner, D; Bogaerts, J A; Bogavac, D; Bogdanchikov, A G; Bohm, C; Boisvert, V; Bokan, P; Bold, T; Boldyrev, A S; Bomben, M; Bona, M; Boonekamp, M; Borisov, A; Borissov, G; Bortfeldt, J; Bortoletto, D; Bortolotto, V; Bos, K; Boscherini, D; Bosman, M; Bossio Sola, J D; Boudreau, J; Bouffard, J; Bouhova-Thacker, E V; Boumediene, D; Bourdarios, C; Boutle, S K; Boveia, A; Boyd, J; Boyko, I R; Bracinik, J; Brandt, A; Brandt, G; Brandt, O; Bratzler, U; Brau, B; Brau, J E; Braun, H M; Breaden Madden, W D; Brendlinger, K; Brennan, A J; Brenner, L; Brenner, R; Bressler, S; Bristow, T M; Britton, D; Britzger, D; Brochu, F M; Brock, I; Brock, R; Brooijmans, G; Brooks, T; Brooks, W K; Brosamer, J; Brost, E; Broughton, J H; de Renstrom, P A Bruckman; Bruncko, D; Bruneliere, R; Bruni, A; Bruni, G; Bruni, L S; Brunt, B H; Bruschi, M; Bruscino, N; Bryant, P; Bryngemark, L; Buanes, T; Buat, Q; Buchholz, P; Buckley, A G; Budagov, I A; Buehrer, F; Bugge, M K; Bulekov, O; Bullock, D; Burckhart, H; Burdin, S; Burgard, C D; Burghgrave, B; Burka, K; Burke, S; Burmeister, I; Burr, J T P; Busato, E; Büscher, D; Büscher, V; Bussey, P; Butler, J M; Buttar, C M; Butterworth, J M; Butti, P; Buttinger, W; Buzatu, A; Buzykaev, A R; Cabrera Urbán, S; Caforio, D; Cairo, V M; Cakir, O; Calace, N; Calafiura, P; Calandri, A; Calderini, G; Calfayan, P; Caloba, L P; Lopez, S Calvente; Calvet, D; Calvet, S; Calvet, T P; Toro, R Camacho; Camarda, S; Camarri, P; Cameron, D; Caminal Armadans, R; Camincher, C; Campana, S; Campanelli, M; Camplani, A; Campoverde, A; Canale, V; Canepa, A; Cano Bret, M; Cantero, J; Cantrill, R; Cao, T; Capeans Garrido, M D M; Caprini, I; Caprini, M; Capua, M; Caputo, R; Carbone, R M; Cardarelli, R; Cardillo, F; Carli, I; Carli, T; Carlino, G; Carminati, L; Caron, S; Carquin, E; Carrillo-Montoya, G D; Carter, J R; Carvalho, J; Casadei, D; Casado, M P; Casolino, M; Casper, D W; Castaneda-Miranda, E; Castelijn, R; Castelli, A; Gimenez, V Castillo; Castro, N F; Catinaccio, A; Catmore, J R; Cattai, A; Caudron, J; Cavaliere, V; Cavallaro, E; Cavalli, D; Cavalli-Sforza, M; Cavasinni, V; Ceradini, F; Cerda Alberich, L; Cerio, B C; Cerqueira, A S; Cerri, A; Cerrito, L; Cerutti, F; Cerv, M; Cervelli, A; Cetin, S A; Chafaq, A; Chakraborty, D; Chan, S K; Chan, Y L; Chang, P; Chapman, J D; Charlton, D G; Chatterjee, A; Chau, C C; Chavez Barajas, C A; Che, S; Cheatham, S; Chegwidden, A; Chekanov, S; Chekulaev, S V; Chelkov, G A; Chelstowska, M A; Chen, C; Chen, H; Chen, K; Chen, S; Chen, S; Chen, X; Chen, Y; Cheng, H C; Cheng, H J; Cheng, Y; Cheplakov, A; Cheremushkina, E; Moursli, R Cherkaoui El; Chernyatin, V; Cheu, E; Chevalier, L; Chiarella, V; Chiarelli, G; Chiodini, G; Chisholm, A S; Chitan, A; Chizhov, M V; Choi, K; Chomont, A R; Chouridou, S; Chow, B K B; Christodoulou, V; Chromek-Burckhart, D; Chudoba, J; Chuinard, A J; Chwastowski, J J; Chytka, L; Ciapetti, G; Ciftci, A K; Cinca, D; Cindro, V; Cioara, I A; Ciocca, C; Ciocio, A; Cirotto, F; Citron, Z H; Citterio, M; Ciubancan, M; Clark, A; Clark, B L; Clark, M R; Clark, P J; Clarke, R N; Clement, C; Coadou, Y; Cobal, M; Coccaro, A; Cochran, J; Coffey, L; Colasurdo, L; Cole, B; Colijn, A P; Collot, J; Colombo, T; Compostella, G; Conde Muiño, P; Coniavitis, E; Connell, S H; Connelly, I A; Consorti, V; Constantinescu, S; Conti, G; Conventi, F; Cooke, M; Cooper, B D; Cooper-Sarkar, A M; Cormier, K J R; Cornelissen, T; Corradi, M; Corriveau, F; Corso-Radu, A; Cortes-Gonzalez, A; Cortiana, G; Costa, G; Costa, M J; Costanzo, D; Cottin, G; Cowan, G; Cox, B E; Cranmer, K; Crawley, S J; Cree, G; Crépé-Renaudin, S; Crescioli, F; Cribbs, W A; Crispin Ortuzar, M; Cristinziani, M; Croft, V; Crosetti, G; Cuhadar Donszelmann, T; Cummings, J; Curatolo, M; Cúth, J; Cuthbert, C; Czirr, H; Czodrowski, P; D'amen, G; D'Auria, S; D'Onofrio, M; De Sousa, M J Da Cunha Sargedas; Da Via, C; Dabrowski, W; Dado, T; Dai, T; Dale, O; Dallaire, F; Dallapiccola, C; Dam, M; Dandoy, J R; Dang, N P; Daniells, A C; Dann, N S; Danninger, M; Dano Hoffmann, M; Dao, V; Darbo, G; Darmora, S; Dassoulas, J; Dattagupta, A; Davey, W; David, C; Davidek, T; Davies, M; Davison, P; Dawe, E; Dawson, I; Daya-Ishmukhametova, R K; De, K; de Asmundis, R; De Benedetti, A; De Castro, S; De Cecco, S; De Groot, N; de Jong, P; De la Torre, H; De Lorenzi, F; De Maria, A; De Pedis, D; De Salvo, A; De Sanctis, U; De Santo, A; De Regie, J B De Vivie; Dearnaley, W J; Debbe, R; Debenedetti, C; Dedovich, D V; Dehghanian, N; Deigaard, I; Del Gaudio, M; Del Peso, J; Del Prete, T; Delgove, D; Deliot, F; Delitzsch, C M; Deliyergiyev, M; Dell'Acqua, A; Dell'Asta, L; Dell'Orso, M; Della Pietra, M; Della Volpe, D; Delmastro, M; Delsart, P A; DeMarco, D A; Demers, S; Demichev, M; Demilly, A; Denisov, S P; Denysiuk, D; Derendarz, D; Derkaoui, J E; Derue, F; Dervan, P; Desch, K; Deterre, C; Dette, K; Deviveiros, P O; Dewhurst, A; Dhaliwal, S; Di Ciaccio, A; Di Ciaccio, L; Di Clemente, W K; Di Donato, C; Di Girolamo, A; Di Girolamo, B; Di Micco, B; Di Nardo, R; Di Simone, A; Di Sipio, R; Di Valentino, D; Diaconu, C; Diamond, M; Dias, F A; Diaz, M A; Diehl, E B; Dietrich, J; Diglio, S; Dimitrievska, A; Dingfelder, J; Dita, P; Dita, S; Dittus, F; Djama, F; Djobava, T; Djuvsland, J I; do Vale, M A B; Dobos, D; Dobre, M; Doglioni, C; Dohmae, T; Dolejsi, J; Dolezal, Z; Dolgoshein, B A; Donadelli, M; Donati, S; Dondero, P; Donini, J; Dopke, J; Doria, A; Dova, M T; Doyle, A T; Drechsler, E; Dris, M; Du, Y; Duarte-Campderros, J; Duchovni, E; Duckeck, G; Ducu, O A; Duda, D; Dudarev, A; Duffield, E M; Duflot, L; Duguid, L; Dührssen, M; Dumancic, M; Dunford, M; Duran Yildiz, H; Düren, M; Durglishvili, A; Duschinger, D; Dutta, B; Dyndal, M; Eckardt, C; Ecker, K M; Edgar, R C; Edwards, N C; Eifert, T; Eigen, G; Einsweiler, K; Ekelof, T; El Kacimi, M; Ellajosyula, V; Ellert, M; Elles, S; Ellinghaus, F; Elliot, A A; Ellis, N; Elmsheuser, J; Elsing, M; Emeliyanov, D; Enari, Y; Endner, O C; Endo, M; Ennis, J S; Erdmann, J; Ereditato, A; Ernis, G; Ernst, J; Ernst, M; Errede, S; Ertel, E; Escalier, M; Esch, H; Escobar, C; Esposito, B; Etienvre, A I; Etzion, E; Evans, H; Ezhilov, A; Fabbri, F; Fabbri, L; Facini, G; Fakhrutdinov, R M; Falciano, S; Falla, R J; Faltova, J; Fang, Y; Fanti, M; Farbin, A; Farilla, A; Farina, C; Farina, E M; Farooque, T; Farrell, S; Farrington, S M; Farthouat, P; Fassi, F; Fassnacht, P; Fassouliotis, D; Faucci Giannelli, M; Favareto, A; Fawcett, W J; Fayard, L; Fedin, O L; Fedorko, W; Feigl, S; Feligioni, L; Feng, C; Feng, E J; Feng, H; Fenyuk, A B; Feremenga, L; Fernandez Martinez, P; Fernandez Perez, S; Ferrando, J; Ferrari, A; Ferrari, P; Ferrari, R; de Lima, D E Ferreira; Ferrer, A; Ferrere, D; Ferretti, C; Ferretto Parodi, A; Fiedler, F; Filipčič, A; Filipuzzi, M; Filthaut, F; Fincke-Keeler, M; Finelli, K D; Fiolhais, M C N; Fiorini, L; Firan, A; Fischer, A; Fischer, C; Fischer, J; Fisher, W C; Flaschel, N; Fleck, I; Fleischmann, P; Fletcher, G T; Fletcher, R R M; Flick, T; Floderus, A; Flores Castillo, L R; Flowerdew, M J; Forcolin, G T; Formica, A; Forti, A; Foster, A G; Fournier, D; Fox, H; Fracchia, S; Francavilla, P; Franchini, M; Francis, D; Franconi, L; Franklin, M; Frate, M; Fraternali, M; Freeborn, D; Fressard-Batraneanu, S M; Friedrich, F; Froidevaux, D; Frost, J A; Fukunaga, C; Fullana Torregrosa, E; Fusayasu, T; Fuster, J; Gabaldon, C; Gabizon, O; Gabrielli, A; Gabrielli, A; Gach, G P; Gadatsch, S; Gadomski, S; Gagliardi, G; Gagnon, L G; Gagnon, P; Galea, C; Galhardo, B; Gallas, E J; Gallop, B J; Gallus, P; Galster, G; Gan, K K; Gao, J; Gao, Y; Gao, Y S; Garay Walls, F M; García, C; García Navarro, J E; Garcia-Sciveres, M; Gardner, R W; Garelli, N; Garonne, V; Gascon Bravo, A; Gatti, C; Gaudiello, A; Gaudio, G; Gaur, B; Gauthier, L; Gavrilenko, I L; Gay, C; Gaycken, G; Gazis, E N; Gecse, Z; Gee, C N P; Geich-Gimbel, Ch; Geisen, M; Geisler, M P; Gemme, C; Genest, M H; Geng, C; Gentile, S; George, S; Gerbaudo, D; Gershon, A; Ghasemi, S; Ghazlane, H; Ghneimat, M; Giacobbe, B; Giagu, S; Giannetti, P; Gibbard, B; Gibson, S M; Gignac, M; Gilchriese, M; Gillam, T P S; Gillberg, D; Gilles, G; Gingrich, D M; Giokaris, N; Giordani, M P; Giorgi, F M; Giorgi, F M; Giraud, P F; Giromini, P; Giugni, D; Giuli, F; Giuliani, C; Giulini, M; Gjelsten, B K; Gkaitatzis, S; Gkialas, I; Gkougkousis, E L; Gladilin, L K; Glasman, C; Glatzer, J; Glaysher, P C F; Glazov, A; Goblirsch-Kolb, M; Godlewski, J; Goldfarb, S; Golling, T; Golubkov, D; Gomes, A; Gonçalo, R; Costa, J Goncalves Pinto Firmino Da; Gonella, G; Gonella, L; Gongadze, A; de la Hoz, S González; Gonzalez Parra, G; Gonzalez-Sevilla, S; Goossens, L; Gorbounov, P A; Gordon, H A; Gorelov, I; Gorini, B; Gorini, E; Gorišek, A; Gornicki, E; Goshaw, A T; Gössling, C; Gostkin, M I; Goudet, C R; Goujdami, D; Goussiou, A G; Govender, N; Gozani, E; Graber, L; Grabowska-Bold, I; Gradin, P O J; Grafström, P; Gramling, J; Gramstad, E; Grancagnolo, S; Gratchev, V; Gravila, P M; Gray, H M; Graziani, E; Greenwood, Z D; Grefe, C; Gregersen, K; Gregor, I M; Grenier, P; Grevtsov, K; Griffiths, J; Grillo, A A; Grimm, K; Grinstein, S; Gris, Ph; Grivaz, J-F; Groh, S; Grohs, J P; Gross, E; Grosse-Knetter, J; Grossi, G C; Grout, Z J; Guan, L; Guan, W; Guenther, J; Guescini, F; Guest, D; Gueta, O; Guido, E; Guillemin, T; Guindon, S; Gul, U; Gumpert, C; Guo, J; Guo, Y; Gupta, S; Gustavino, G; Gutierrez, P; Gutierrez Ortiz, N G; Gutschow, C; Guyot, C; Gwenlan, C; Gwilliam, C B; Haas, A; Haber, C; Hadavand, H K; Haddad, N; Hadef, A; Haefner, P; Hageböck, S; Hajduk, Z; Hakobyan, H; Haleem, M; Haley, J; Halladjian, G; Hallewell, G D; Hamacher, K; Hamal, P; Hamano, K; Hamilton, A; Hamity, G N; Hamnett, P G; Han, L; Hanagaki, K; Hanawa, K; Hance, M; Haney, B; Hanke, P; Hanna, R; Hansen, J B; Hansen, J D; Hansen, M C; Hansen, P H; Hara, K; Hard, A S; Harenberg, T; Hariri, F; Harkusha, S; Harrington, R D; Harrison, P F; Hartjes, F; Hartmann, N M; Hasegawa, M; Hasegawa, Y; Hasib, A; Hassani, S; Haug, S; Hauser, R; Hauswald, L; Havranek, M; Hawkes, C M; Hawkings, R J; Hayden, D; Hays, C P; Hays, J M; Hayward, H S; Haywood, S J; Head, S J; Heck, T; Hedberg, V; Heelan, L; Heim, S; Heim, T; Heinemann, B; Heinrich, J J; Heinrich, L; Heinz, C; Hejbal, J; Helary, L; Hellman, S; Helsens, C; Henderson, J; Henderson, R C W; Heng, Y; Henkelmann, S; Henriques Correia, A M; Henrot-Versille, S; Herbert, G H; Hernández Jiménez, Y; Herten, G; Hertenberger, R; Hervas, L; Hesketh, G G; Hessey, N P; Hetherly, J W; Hickling, R; Higón-Rodriguez, E; Hill, E; Hill, J C; Hiller, K H; Hillier, S J; Hinchliffe, I; Hines, E; Hinman, R R; Hirose, M; Hirschbuehl, D; Hobbs, J; Hod, N; Hodgkinson, M C; Hodgson, P; Hoecker, A; Hoeferkamp, M R; Hoenig, F; Hohn, D; Holmes, T R; Homann, M; Hong, T M; Hooberman, B H; Hopkins, W H; Horii, Y; Horton, A J; Hostachy, J-Y; Hou, S; Hoummada, A; Howarth, J; Hrabovsky, M; Hristova, I; Hrivnac, J; Hryn'ova, T; Hrynevich, A; Hsu, C; Hsu, P J; Hsu, S-C; Hu, D; Hu, Q; Huang, Y; Hubacek, Z; Hubaut, F; Huegging, F; Huffman, T B; Hughes, E W; Hughes, G; Huhtinen, M; Huo, P; Huseynov, N; Huston, J; Huth, J; Iacobucci, G; Iakovidis, G; Ibragimov, I; Iconomidou-Fayard, L; Ideal, E; Idrissi, Z; Iengo, P; Igonkina, O; Iizawa, T; Ikegami, Y; Ikeno, M; Ilchenko, Y; Iliadis, D; Ilic, N; Ince, T; Introzzi, G; Ioannou, P; Iodice, M; Iordanidou, K; Ippolito, V; Ishijima, N; Ishino, M; Ishitsuka, M; Ishmukhametov, R; Issever, C; Istin, S; Ito, F; Iturbe Ponce, J M; Iuppa, R; Iwanski, W; Iwasaki, H; Izen, J M; Izzo, V; Jabbar, S; Jackson, B; Jackson, M; Jackson, P; Jain, V; Jakobi, K B; Jakobs, K; Jakobsen, S; Jakoubek, T; Jamin, D O; Jana, D K; Jansen, E; Jansky, R; Janssen, J; Janus, M; Jarlskog, G; Javadov, N; Javůrek, T; Jeanneau, F; Jeanty, L; Jeng, G-Y; Jennens, D; Jenni, P; Jentzsch, J; Jeske, C; Jézéquel, S; Ji, H; Jia, J; Jiang, H; Jiang, Y; Jiggins, S; Jimenez Pena, J; Jin, S; Jinaru, A; Jinnouchi, O; Johansson, P; Johns, K A; Johnson, W J; Jon-And, K; Jones, G; Jones, R W L; Jones, S; Jones, T J; Jongmanns, J; Jorge, P M; Jovicevic, J; Ju, X; Juste Rozas, A; Köhler, M K; Kaczmarska, A; Kado, M; Kagan, H; Kagan, M; Kahn, S J; Kajomovitz, E; Kalderon, C W; Kaluza, A; Kama, S; Kamenshchikov, A; Kanaya, N; Kaneti, S; Kanjir, L; Kantserov, V A; Kanzaki, J; Kaplan, B; Kaplan, L S; Kapliy, A; Kar, D; Karakostas, K; Karamaoun, A; Karastathis, N; Kareem, M J; Karentzos, E; Karnevskiy, M; Karpov, S N; Karpova, Z M; Karthik, K; Kartvelishvili, V; Karyukhin, A N; Kasahara, K; Kashif, L; Kass, R D; Kastanas, A; Kataoka, Y; Kato, C; Katre, A; Katzy, J; Kawade, K; Kawagoe, K; Kawamoto, T; Kawamura, G; Kazama, S; Kazanin, V F; Keeler, R; Kehoe, R; Keller, J S; Kempster, J J; Keoshkerian, H; Kepka, O; Kerševan, B P; Kersten, S; Keyes, R A; Khader, M; Khalil-Zada, F; Khanov, A; Kharlamov, A G; Khoo, T J; Khovanskiy, V; Khramov, E; Khubua, J; Kido, S; Kim, H Y; Kim, S H; Kim, Y K; Kimura, N; Kind, O M; King, B T; King, M; King, S B; Kirk, J; Kiryunin, A E; Kishimoto, T; Kisielewska, D; Kiss, F; Kiuchi, K; Kivernyk, O; Kladiva, E; Klein, M H; Klein, M; Klein, U; Kleinknecht, K; Klimek, P; Klimentov, A; Klingenberg, R; Klinger, J A; Klioutchnikova, T; Kluge, E-E; Kluit, P; Kluth, S; Knapik, J; Kneringer, E; Knoops, E B F G; Knue, A; Kobayashi, A; Kobayashi, D; Kobayashi, T; Kobel, M; Kocian, M; Kodys, P; Koffas, T; Koffeman, E; Koi, T; Kolanoski, H; Kolb, M; Koletsou, I; Komar, A A; Komori, Y; Kondo, T; Kondrashova, N; Köneke, K; König, A C; Kono, T; Konoplich, R; Konstantinidis, N; Kopeliansky, R; Koperny, S; Köpke, L; Kopp, A K; Korcyl, K; Kordas, K; Korn, A; Korol, A A; Korolkov, I; Korolkova, E V; Kortner, O; Kortner, S; Kosek, T; Kostyukhin, V V; Kotwal, A; Kourkoumeli-Charalampidi, A; Kourkoumelis, C; Kouskoura, V; Kowalewska, A B; Kowalewski, R; Kowalski, T Z; Kozakai, C; Kozanecki, W; Kozhin, A S; Kramarenko, V A; Kramberger, G; Krasnopevtsev, D; Krasny, M W; Krasznahorkay, A; Kraus, J K; Kravchenko, A; Kretz, M; Kretzschmar, J; Kreutzfeldt, K; Krieger, P; Krizka, K; Kroeninger, K; Kroha, H; Kroll, J; Kroseberg, J; Krstic, J; Kruchonak, U; Krüger, H; Krumnack, N; Kruse, A; Kruse, M C; Kruskal, M; Kubota, T; Kucuk, H; Kuday, S; Kuechler, J T; Kuehn, S; Kugel, A; Kuger, F; Kuhl, A; Kuhl, T; Kukhtin, V; Kukla, R; Kulchitsky, Y; Kuleshov, S; Kuna, M; Kunigo, T; Kupco, A; Kurashige, H; Kurochkin, Y A; Kus, V; Kuwertz, E S; Kuze, M; Kvita, J; Kwan, T; Kyriazopoulos, D; La Rosa, A; La Rosa Navarro, J L; La Rotonda, L; Lacasta, C; Lacava, F; Lacey, J; Lacker, H; Lacour, D; Lacuesta, V R; Ladygin, E; Lafaye, R; Laforge, B; Lagouri, T; Lai, S; Lammers, S; Lampl, W; Lançon, E; Landgraf, U; Landon, M P J; Lang, V S; Lange, J C; Lankford, A J; Lanni, F; Lantzsch, K; Lanza, A; Laplace, S; Lapoire, C; Laporte, J F; Lari, T; Lasagni Manghi, F; Lassnig, M; Laurelli, P; Lavrijsen, W; Law, A T; Laycock, P; Lazovich, T; Lazzaroni, M; Le, B; Le Dortz, O; Le Guirriec, E; Quilleuc, E P Le; LeBlanc, M; LeCompte, T; Ledroit-Guillon, F; Lee, C A; Lee, S C; Lee, L; Lefebvre, G; Lefebvre, M; Legger, F; Leggett, C; Lehan, A; Lehmann Miotto, G; Lei, X; Leight, W A; Leisos, A; Leister, A G; Leite, M A L; Leitner, R; Lellouch, D; Lemmer, B; Leney, K J C; Lenz, T; Lenzi, B; Leone, R; Leone, S; Leonidopoulos, C; Leontsinis, S; Lerner, G; Leroy, C; Lesage, A A J; Lester, C G; Levchenko, M; Levêque, J; Levin, D; Levinson, L J; Levy, M; Lewis, D; Leyko, A M; Leyton, M; Li, B; Li, H; Li, H L; Li, L; Li, L; Li, Q; Li, S; Li, X; Li, Y; Liang, Z; Liberti, B; Liblong, A; Lichard, P; Lie, K; Liebal, J; Liebig, W; Limosani, A; Lin, S C; Lin, T H; Lindquist, B E; Lionti, A E; Lipeles, E; Lipniacka, A; Lisovyi, M; Liss, T M; Lister, A; Litke, A M; Liu, B; Liu, D; Liu, H; Liu, H; Liu, J; Liu, J B; Liu, K; Liu, L; Liu, M; Liu, M; Liu, Y L; Liu, Y; Livan, M; Lleres, A; Llorente Merino, J; Lloyd, S L; Lo Sterzo, F; Lobodzinska, E M; Loch, P; Lockman, W S; Loebinger, F K; Loevschall-Jensen, A E; Loew, K M; Loginov, A; Lohse, T; Lohwasser, K; Lokajicek, M; Long, B A; Long, J D; Long, R E; Longo, L; Looper, K A; Lopes, L; Lopez Mateos, D; Lopez Paredes, B; Lopez Paz, I; Lopez Solis, A; Lorenz, J; Lorenzo Martinez, N; Losada, M; Lösel, P J; Lou, X; Lounis, A; Love, J; Love, P A; Lu, H; Lu, N; Lubatti, H J; Luci, C; Lucotte, A; Luedtke, C; Luehring, F; Lukas, W; Luminari, L; Lundberg, O; Lund-Jensen, B; Luzi, P M; Lynn, D; Lysak, R; Lytken, E; Lyubushkin, V; Ma, H; Ma, L L; Ma, Y; Maccarrone, G; Macchiolo, A; Macdonald, C M; Maček, B; Machado Miguens, J; Madaffari, D; Madar, R; Maddocks, H J; Mader, W F; Madsen, A; Maeda, J; Maeland, S; Maeno, T; Maevskiy, A; Magradze, E; Mahlstedt, J; Maiani, C; Maidantchik, C; Maier, A A; Maier, T; Maio, A; Majewski, S; Makida, Y; Makovec, N; Malaescu, B; Malecki, Pa; Maleev, V P; Malek, F; Mallik, U; Malon, D; Malone, C; Maltezos, S; Malyukov, S; Mamuzic, J; Mancini, G; Mandelli, B; Mandelli, L; Mandić, I; Maneira, J; Filho, L Manhaes de Andrade; Manjarres Ramos, J; Mann, A; Manousos, A; Mansoulie, B; Mansour, J D; Mantifel, R; Mantoani, M; Manzoni, S; Mapelli, L; Marceca, G; March, L; Marchiori, G; Marcisovsky, M; Marjanovic, M; Marley, D E; Marroquim, F; Marsden, S P; Marshall, Z; Marti-Garcia, S; Martin, B; Martin, T A; Martin, V J; Latour, B Martin Dit; Martinez, M; Martinez Outschoorn, V I; Martin-Haugh, S; Martoiu, V S; Martyniuk, A C; Marx, M; Marzin, A; Masetti, L; Mashimo, T; Mashinistov, R; Masik, J; Maslennikov, A L; Massa, I; Massa, L; Mastrandrea, P; Mastroberardino, A; Masubuchi, T; Mättig, P; Mattmann, J; Maurer, J; Maxfield, S J; Maximov, D A; Mazini, R; Mazza, S M; Mc Fadden, N C; Goldrick, G Mc; Mc Kee, S P; McCarn, A; McCarthy, R L; McCarthy, T G; McClymont, L I; McDonald, E F; McFarlane, K W; Mcfayden, J A; Mchedlidze, G; McMahon, S J; McPherson, R A; Medinnis, M; Meehan, S; Mehlhase, S; Mehta, A; Meier, K; Meineck, C; Meirose, B; Melini, D; Mellado Garcia, B R; Melo, M; Meloni, F; Mengarelli, A; Menke, S; Meoni, E; Mergelmeyer, S; Mermod, P; Merola, L; Meroni, C; Merritt, F S; Messina, A; Metcalfe, J; Mete, A S; Meyer, C; Meyer, C; Meyer, J-P; Meyer, J; Meyer Zu Theenhausen, H; Miano, F; Middleton, R P; Miglioranzi, S; Mijović, L; Mikenberg, G; Mikestikova, M; Mikuž, M; Milesi, M; Milic, A; Miller, D W; Mills, C; Milov, A; Milstead, D A; Minaenko, A A; Minami, Y; Minashvili, I A; Mincer, A I; Mindur, B; Mineev, M; Ming, Y; Mir, L M; Mistry, K P; Mitani, T; Mitrevski, J; Mitsou, V A; Miucci, A; Miyagawa, P S; Mjörnmark, J U; Moa, T; Mochizuki, K; Mohapatra, S; Molander, S; Moles-Valls, R; Monden, R; Mondragon, M C; Mönig, K; Monk, J; Monnier, E; Montalbano, A; Montejo Berlingen, J; Monticelli, F; Monzani, S; Moore, R W; Morange, N; Moreno, D; Moreno Llácer, M; Morettini, P; Morgenstern, S; Mori, D; Mori, T; Morii, M; Morinaga, M; Morisbak, V; Moritz, S; Morley, A K; Mornacchi, G; Morris, J D; Mortensen, S S; Morvaj, L; Mosidze, M; Moss, J; Motohashi, K; Mount, R; Mountricha, E; Mouraviev, S V; Moyse, E J W; Muanza, S; Mudd, R D; Mueller, F; Mueller, J; Mueller, R S P; Mueller, T; Muenstermann, D; Mullen, P; Mullier, G A; Munoz Sanchez, F J; Murillo Quijada, J A; Murray, W J; Musheghyan, H; Muškinja, M; Myagkov, A G; Myska, M; Nachman, B P; Nackenhorst, O; Nagai, K; Nagai, R; Nagano, K; Nagasaka, Y; Nagata, K; Nagel, M; Nagy, E; Nairz, A M; Nakahama, Y; Nakamura, K; Nakamura, T; Nakano, I; Namasivayam, H; Naranjo Garcia, R F; Narayan, R; Narrias Villar, D I; Naryshkin, I; Naumann, T; Navarro, G; Nayyar, R; Neal, H A; Nechaeva, P Yu; Neep, T J; Nef, P D; Negri, A; Negrini, M; Nektarijevic, S; Nellist, C; Nelson, A; Nemecek, S; Nemethy, P; Nepomuceno, A A; Nessi, M; Neubauer, M S; Neumann, M; Neves, R M; Nevski, P; Newman, P R; Nguyen, D H; Manh, T Nguyen; Nickerson, R B; Nicolaidou, R; Nielsen, J; Nikiforov, A; Nikolaenko, V; Nikolic-Audit, I; Nikolopoulos, K; Nilsen, J K; Nilsson, P; Ninomiya, Y; Nisati, A; Nisius, R; Nobe, T; Nodulman, L; Nomachi, M; Nomidis, I; Nooney, T; Norberg, S; Nordberg, M; Norjoharuddeen, N; Novgorodova, O; Nowak, S; Nozaki, M; Nozka, L; Ntekas, K; Nurse, E; Nuti, F; O'grady, F; O'Neil, D C; O'Rourke, A A; O'Shea, V; Oakham, F G; Oberlack, H; Obermann, T; Ocariz, J; Ochi, A; Ochoa, I; Ochoa-Ricoux, J P; Oda, S; Odaka, S; Ogren, H; Oh, A; Oh, S H; Ohm, C C; Ohman, H; Oide, H; Okawa, H; Okumura, Y; Okuyama, T; Olariu, A; Oleiro Seabra, L F; Olivares Pino, S A; Oliveira Damazio, D; Olszewski, A; Olszowska, J; Onofre, A; Onogi, K; Onyisi, P U E; Oreglia, M J; Oren, Y; Orestano, D; Orlando, N; Orr, R S; Osculati, B; Ospanov, R; Garzon, G Otero Y; Otono, H; Ouchrif, M; Ould-Saada, F; Ouraou, A; Oussoren, K P; Ouyang, Q; Owen, M; Owen, R E; Ozcan, V E; Ozturk, N; Pachal, K; Pacheco Pages, A; Pacheco Rodriguez, L; Padilla Aranda, C; Pagáčová, M; Pagan Griso, S; Paige, F; Pais, P; Pajchel, K; Palacino, G; Palazzo, S; Palestini, S; Palka, M; Pallin, D; Palma, A; St Panagiotopoulou, E; Pandini, C E; Panduro Vazquez, J G; Pani, P; Panitkin, S; Pantea, D; Paolozzi, L; Papadopoulou, Th D; Papageorgiou, K; Paramonov, A; Paredes Hernandez, D; Parker, A J; Parker, M A; Parker, K A; Parodi, F; Parsons, J A; Parzefall, U; Pascuzzi, V R; Pasqualucci, E; Passaggio, S; Pastore, Fr; Pásztor, G; Pataraia, S; Pater, J R; Pauly, T; Pearce, J; Pearson, B; Pedersen, L E; Pedersen, M; Lopez, S Pedraza; Pedro, R; Peleganchuk, S V; Pelikan, D; Penc, O; Peng, C; Peng, H; Penwell, J; Peralva, B S; Perego, M M; Perepelitsa, D V; Perez Codina, E; Perini, L; Pernegger, H; Perrella, S; Peschke, R; Peshekhonov, V D; Peters, K; Peters, R F Y; Petersen, B A; Petersen, T C; Petit, E; Petridis, A; Petridou, C; Petroff, P; Petrolo, E; Petrov, M; Petrucci, F; Pettersson, N E; Peyaud, A; Pezoa, R; Phillips, P W; Piacquadio, G; Pianori, E; Picazio, A; Piccaro, E; Piccinini, M; Pickering, M A; Piegaia, R; Pilcher, J E; Pilkington, A D; Pin, A W J; Pinamonti, M; Pinfold, J L; Pingel, A; Pires, S; Pirumov, H; Pitt, M; Plazak, L; Pleier, M-A; Pleskot, V; Plotnikova, E; Plucinski, P; Pluth, D; Poettgen, R; Poggioli, L; Pohl, D; Polesello, G; Poley, A; Policicchio, A; Polifka, R; Polini, A; Pollard, C S; Polychronakos, V; Pommès, K; Pontecorvo, L; Pope, B G; Popeneciu, G A; Popovic, D S; Poppleton, A; Pospisil, S; Potamianos, K; Potrap, I N; Potter, C J; Potter, C T; Poulard, G; Poveda, J; Pozdnyakov, V; Pozo Astigarraga, M E; Pralavorio, P; Pranko, A; Prell, S; Price, D; Price, L E; Primavera, M; Prince, S; Proissl, M; Prokofiev, K; Prokoshin, F; Protopopescu, S; Proudfoot, J; Przybycien, M; Puddu, D; Purohit, M; Puzo, P; Qian, J; Qin, G; Qin, Y; Quadt, A; Quayle, W B; Queitsch-Maitland, M; Quilty, D; Raddum, S; Radeka, V; Radescu, V; Radhakrishnan, S K; Radloff, P; Rados, P; Ragusa, F; Rahal, G; Raine, J A; Rajagopalan, S; Rammensee, M; Rangel-Smith, C; Ratti, M G; Rauscher, F; Rave, S; Ravenscroft, T; Ravinovich, I; Raymond, M; Read, A L; Readioff, N P; Reale, M; Rebuzzi, D M; Redelbach, A; Redlinger, G; Reece, R; Reeves, K; Rehnisch, L; Reichert, J; Reisin, H; Rembser, C; Ren, H; Rescigno, M; Resconi, S; Rezanova, O L; Reznicek, P; Rezvani, R; Richter, R; Richter, S; Richter-Was, E; Ricken, O; Ridel, M; Rieck, P; Riegel, C J; Rieger, J; Rifki, O; Rijssenbeek, M; Rimoldi, A; Rimoldi, M; Rinaldi, L; Ristić, B; Ritsch, E; Riu, I; Rizatdinova, F; Rizvi, E; Rizzi, C; Robertson, S H; Robichaud-Veronneau, A; Robinson, D; Robinson, J E M; Robson, A; Roda, C; Rodina, Y; Rodriguez Perez, A; Rodriguez Rodriguez, D; Roe, S; Rogan, C S; Røhne, O; Romaniouk, A; Romano, M; Romano Saez, S M; Romero Adam, E; Rompotis, N; Ronzani, M; Roos, L; Ros, E; Rosati, S; Rosbach, K; Rose, P; Rosenthal, O; Rosien, N-A; Rossetti, V; Rossi, E; Rossi, L P; Rosten, J H N; Rosten, R; Rotaru, M; Roth, I; Rothberg, J; Rousseau, D; Royon, C R; Rozanov, A; Rozen, Y; Ruan, X; Rubbo, F; Rudolph, M S; Rühr, F; Ruiz-Martinez, A; Rurikova, Z; Rusakovich, N A; Ruschke, A; Russell, H L; Rutherfoord, J P; Ruthmann, N; Ryabov, Y F; Rybar, M; Rybkin, G; Ryu, S; Ryzhov, A; Rzehorz, G F; Saavedra, A F; Sabato, G; Sacerdoti, S; Sadrozinski, H F-W; Sadykov, R; Safai Tehrani, F; Saha, P; Sahinsoy, M; Saimpert, M; Saito, T; Sakamoto, H; Sakurai, Y; Salamanna, G; Salamon, A; Loyola, J E Salazar; Salek, D; De Bruin, P H Sales; Salihagic, D; Salnikov, A; Salt, J; Salvatore, D; Salvatore, F; Salvucci, A; Salzburger, A; Sammel, D; Sampsonidis, D; Sanchez, A; Sánchez, J; Sanchez Martinez, V; Sandaker, H; Sandbach, R L; Sander, H G; Sandhoff, M; Sandoval, C; Sandstroem, R; Sankey, D P C; Sannino, M; Sansoni, A; Santoni, C; Santonico, R; Santos, H; Santoyo Castillo, I; Sapp, K; Sapronov, A; Saraiva, J G; Sarrazin, B; Sasaki, O; Sasaki, Y; Sato, K; Sauvage, G; Sauvan, E; Savage, G; Savard, P; Sawyer, C; Sawyer, L; Saxon, J; Sbarra, C; Sbrizzi, A; Scanlon, T; Scannicchio, D A; Scarcella, M; Scarfone, V; Schaarschmidt, J; Schacht, P; Schachtner, B M; Schaefer, D; Schaefer, R; Schaeffer, J; Schaepe, S; Schaetzel, S; Schäfer, U; Schaffer, A C; Schaile, D; Schamberger, R D; Scharf, V; Schegelsky, V A; Scheirich, D; Schernau, M; Schiavi, C; Schier, S; Schillo, C; Schioppa, M; Schlenker, S; Schmidt-Sommerfeld, K R; Schmieden, K; Schmitt, C; Schmitt, S; Schmitz, S; Schneider, B; Schnoor, U; Schoeffel, L; Schoening, A; Schoenrock, B D; Schopf, E; Schott, M; Schovancova, J; Schramm, S; Schreyer, M; Schuh, N; Schulte, A; Schultens, M J; Schultz-Coulon, H-C; Schulz, H; Schumacher, M; Schumm, B A; Schune, Ph; Schwartzman, A; Schwarz, T A; Schwegler, Ph; Schweiger, H; Schwemling, Ph; Schwienhorst, R; Schwindling, J; Schwindt, T; Sciolla, G; Scuri, F; Scutti, F; Searcy, J; Seema, P; Seidel, S C; Seiden, A; Seifert, F; Seixas, J M; Sekhniaidze, G; Sekhon, K; Sekula, S J; Seliverstov, D M; Semprini-Cesari, N; Serfon, C; Serin, L; Serkin, L; Sessa, M; Seuster, R; Severini, H; Sfiligoj, T; Sforza, F; Sfyrla, A; Shabalina, E; Shaikh, N W; Shan, L Y; Shang, R; Shank, J T; Shapiro, M; Shatalov, P B; Shaw, K; Shaw, S M; Shcherbakova, A; Shehu, C Y; Sherwood, P; Shi, L; Shimizu, S; Shimmin, C O; Shimojima, M; Shiyakova, M; Shmeleva, A; Shoaleh Saadi, D; Shochet, M J; Shojaii, S; Shrestha, S; Shulga, E; Shupe, M A; Sicho, P; Sickles, A M; Sidebo, P E; Sidiropoulou, O; Sidorov, D; Sidoti, A; Siegert, F; Sijacki, Dj; Silva, J; Silverstein, S B; Simak, V; Simard, O; Simic, Lj; Simion, S; Simioni, E; Simmons, B; Simon, D; Simon, M; Sinervo, P; Sinev, N B; Sioli, M; Siragusa, G; Sivoklokov, S Yu; Sjölin, J; Skinner, M B; Skottowe, H P; Skubic, P; Slater, M; Slavicek, T; Slawinska, M; Sliwa, K; Slovak, R; Smakhtin, V; Smart, B H; Smestad, L; Smiesko, J; Smirnov, S Yu; Smirnov, Y; Smirnova, L N; Smirnova, O; Smith, M N K; Smith, R W; Smizanska, M; Smolek, K; Snesarev, A A; Snyder, S; Sobie, R; Socher, F; Soffer, A; Soh, D A; Sokhrannyi, G; Sanchez, C A Solans; Solar, M; Soldatov, E Yu; Soldevila, U; Solodkov, A A; Soloshenko, A; Solovyanov, O V; Solovyev, V; Sommer, P; Son, H; Song, H Y; Sood, A; Sopczak, A; Sopko, V; Sorin, V; Sosa, D; Sotiropoulou, C L; Soualah, R; Soukharev, A M; South, D; Sowden, B C; Spagnolo, S; Spalla, M; Spangenberg, M; Spanò, F; Sperlich, D; Spettel, F; Spighi, R; Spigo, G; Spiller, L A; Spousta, M; Denis, R D St; Stabile, A; Stamen, R; Stamm, S; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stanitzki, M M; Stapnes, S; Starchenko, E A; Stark, G H; Stark, J; Staroba, P; Starovoitov, P; Stärz, S; Staszewski, R; Steinberg, P; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stewart, G A; Stillings, J A; Stockton, M C; Stoebe, M; Stoicea, G; Stolte, P; Stonjek, S; Stradling, A R; Straessner, A; Stramaglia, M E; Strandberg, J; Strandberg, S; Strandlie, A; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Stroynowski, R; Strubig, A; Stucci, S A; Stugu, B; Styles, N A; Su, D; Su, J; Subramaniam, R; Suchek, S; Sugaya, Y; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, S; Sun, X; Sundermann, J E; Suruliz, K; Susinno, G; Sutton, M R; Suzuki, S; Svatos, M; Swiatlowski, M; Sykora, I; Sykora, T; Ta, D; Taccini, C; Tackmann, K; Taenzer, J; Taffard, A; Tafirout, R; Taiblum, N; Takai, H; Takashima, R; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A A; Tan, K G; Tanaka, J; Tanaka, R; Tanaka, S; Tannenwald, B B; Araya, S Tapia; Tapprogge, S; Tarem, S; Tartarelli, G F; Tas, P; Tasevsky, M; Tashiro, T; Tassi, E; Tavares Delgado, A; Tayalati, Y; Taylor, A C; Taylor, G N; Taylor, P T E; Taylor, W; Teischinger, F A; Teixeira-Dias, P; Temming, K K; Temple, D; Ten Kate, H; Teng, P K; Teoh, J J; Tepel, F; Terada, S; Terashi, K; Terron, J; Terzo, S; Testa, M; Teuscher, R J; Theveneaux-Pelzer, T; Thomas, J P; Thomas-Wilsker, J; Thompson, E N; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Tibbetts, M J; Ticse Torres, R E; Tikhomirov, V O; Tikhonov, Yu A; Timoshenko, S; Tipton, P; Tisserant, S; Todome, K; Todorov, T; Todorova-Nova, S; Tojo, J; Tokár, S; Tokushuku, K; Tolley, E; Tomlinson, L; Tomoto, M; Tompkins, L; Toms, K; Tong, B; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Trischuk, W; Trocmé, B; Trofymov, A; Troncon, C; Trottier-McDonald, M; Trovatelli, M; Truong, L; Trzebinski, M; Trzupek, A; Tseng, J C-L; Tsiareshka, P V; Tsipolitis, G; Tsirintanis, N; Tsiskaridze, S; Tsiskaridze, V; Tskhadadze, E G; Tsui, K M; Tsukerman, I I; Tsulaia, V; Tsuno, S; Tsybychev, D; Tudorache, A; Tudorache, V; Tuna, A N; Tupputi, S A; Turchikhin, S; Turecek, D; Turgeman, D; Turra, R; Turvey, A J; Tuts, P M; Tyndel, M; Ucchielli, G; Ueda, I; Ughetto, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Ungaro, F C; Unno, Y; Unverdorben, C; Urban, J; Urquijo, P; Urrejola, P; Usai, G; Usanova, A; Vacavant, L; Vacek, V; Vachon, B; Valderanis, C; Valdes Santurio, E; Valencic, N; Valentinetti, S; Valero, A; Valery, L; Valkar, S; Vallecorsa, S; Valls Ferrer, J A; Van Den Wollenberg, W; Van Der Deijl, P C; van der Geer, R; van der Graaf, H; van Eldik, N; van Gemmeren, P; Van Nieuwkoop, J; van Vulpen, I; van Woerden, M C; Vanadia, M; Vandelli, W; Vanguri, R; Vaniachine, A; Vankov, P; Vardanyan, G; Vari, R; Varnes, E W; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vasquez, J G; Vazeille, F; Vazquez Schroeder, T; Veatch, J; Veloce, L M; Veloso, F; Veneziano, S; Ventura, A; Venturi, M; Venturi, N; Venturini, A; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Viazlo, O; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Vigani, L; Vigne, R; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinogradov, V B; Vittori, C; Vivarelli, I; Vlachos, S; Vlasak, M; Vogel, M; Vokac, P; Volpi, G; Volpi, M; von der Schmitt, H; von Toerne, E; Vorobel, V; Vorobev, K; Vos, M; Voss, R; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vuillermet, R; Vukotic, I; Vykydal, Z; Wagner, P; Wagner, W; Wahlberg, H; Wahrmund, S; Wakabayashi, J; Walder, J; Walker, R; Walkowiak, W; Wallangen, V; Wang, C; Wang, C; Wang, F; Wang, H; Wang, H; Wang, J; Wang, J; Wang, K; Wang, R; Wang, S M; Wang, T; Wang, T; Wang, W; Wang, X; Wanotayaroj, C; Warburton, A; Ward, C P; Wardrope, D R; Washbrook, A; Watkins, P M; Watson, A T; Watson, M F; Watts, G; Watts, S; Waugh, B M; Webb, S; Weber, M S; Weber, S W; Webster, J S; Weidberg, A R; Weinert, B; Weingarten, J; Weiser, C; Weits, H; Wells, P S; Wenaus, T; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, M D; Werner, P; Wessels, M; Wetter, J; Whalen, K; Whallon, N L; Wharton, A M; White, A; White, M J; White, R; Whiteson, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wildauer, A; Wilk, F; Wilkens, H G; Williams, H H; Williams, S; Willis, C; Willocq, S; Wilson, J A; Wingerter-Seez, I; Winklmeier, F; Winston, O J; Winter, B T; Wittgen, M; Wittkowski, J; Wolter, M W; Wolters, H; Worm, S D; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wu, M; Wu, M; Wu, S L; Wu, X; Wu, Y; Wyatt, T R; Wynne, B M; Xella, S; Xu, D; Xu, L; Yabsley, B; Yacoob, S; Yakabe, R; Yamaguchi, D; Yamaguchi, Y; Yamamoto, A; Yamamoto, S; Yamanaka, T; Yamauchi, K; Yamazaki, Y; Yan, Z; Yang, H; Yang, H; Yang, Y; Yang, Z; Yao, W-M; Yap, Y C; Yasu, Y; Yatsenko, E; Wong, K H Yau; Ye, J; Ye, S; Yeletskikh, I; Yen, A L; Yildirim, E; Yorita, K; Yoshida, R; Yoshihara, K; Young, C; Young, C J S; Youssef, S; Yu, D R; Yu, J; Yu, J M; Yu, J; Yuan, L; Yuen, S P Y; Yusuff, I; Zabinski, B; Zaidan, R; Zaitsev, A M; Zakharchuk, N; Zalieckas, J; Zaman, A; Zambito, S; Zanello, L; Zanzi, D; Zeitnitz, C; Zeman, M; Zemla, A; Zeng, J C; Zeng, Q; Zengel, K; Zenin, O; Ženiš, T; Zerwas, D; Zhang, D; Zhang, F; Zhang, G; Zhang, H; Zhang, J; Zhang, L; Zhang, R; Zhang, R; Zhang, X; Zhang, Z; Zhao, X; Zhao, Y; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, C; Zhou, L; Zhou, L; Zhou, M; Zhou, N; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhukov, K; Zibell, A; Zieminska, D; Zimine, N I; Zimmermann, C; Zimmermann, S; Zinonos, Z; Zinser, M; Ziolkowski, M; Živković, L; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zwalinski, L

    2017-01-01

    A measurement of the [Formula: see text] and [Formula: see text] production cross sections in final states with either two same-charge muons, or three or four leptons (electrons or muons) is presented. The analysis uses a data sample of proton-proton collisions at [Formula: see text] TeV recorded with the ATLAS detector at the Large Hadron Collider in 2015, corresponding to a total integrated luminosity of 3.2 fb[Formula: see text]. The inclusive cross sections are extracted using likelihood fits to signal and control regions, resulting in [Formula: see text] pb and [Formula: see text] pb, in agreement with the Standard Model predictions.

  4. Cloud Response to Arctic Sea Ice Loss and Implications for Feedbacks in the CESM1 Climate Model

    Science.gov (United States)

    Morrison, A.; Kay, J. E.; Chepfer, H.; Guzman, R.; Bonazzola, M.

    2017-12-01

    Clouds have the potential to accelerate or slow the rate of Arctic sea ice loss through their radiative influence on the surface. Cloud feedbacks can therefore play into Arctic warming as clouds respond to changes in sea ice cover. As the Arctic moves toward an ice-free state, understanding how cloud - sea ice relationships change in response to sea ice loss is critical for predicting the future climate trajectory. From satellite observations we know the effect of present-day sea ice cover on clouds, but how will clouds respond to sea ice loss as the Arctic transitions to a seasonally open water state? In this study we use a lidar simulator to first evaluate cloud - sea ice relationships in the Community Earth System Model (CESM1) against present-day observations (2006-2015). In the current climate, the cloud response to sea ice is well-represented in CESM1: we see no summer cloud response to changes in sea ice cover, but more fall clouds over open water than over sea ice. Since CESM1 is credible for the current Arctic climate, we next assess if our process-based understanding of Arctic cloud feedbacks related to sea ice loss is relevant for understanding future Arctic clouds. In the future Arctic, summer cloud structure continues to be insensitive to surface conditions. As the Arctic warms in the fall, however, the boundary layer deepens and cloud fraction increases over open ocean during each consecutive decade from 2020 - 2100. This study will also explore seasonal changes in cloud properties such as opacity and liquid water path. Results thus far suggest that a positive fall cloud - sea ice feedback exists in the present-day and future Arctic climate.

  5. Measurement of the [Formula: see text] meson lifetime using [Formula: see text] decays.

    Science.gov (United States)

    Aaij, R; Adeva, B; Adinolfi, M; Affolder, A; Ajaltouni, Z; Albrecht, J; Alessio, F; Alexander, M; Ali, S; Alkhazov, G; Cartelle, P Alvarez; Alves, A A; Amato, S; Amerio, S; Amhis, Y; Anderlini, L; Anderson, J; Andreassen, R; Andreotti, M; Andrews, J E; Appleby, R B; Gutierrez, O Aquines; Archilli, F; Artamonov, A; Artuso, M; Aslanides, E; Auriemma, G; Baalouch, M; Bachmann, S; Back, J J; Badalov, A; Balagura, V; Baldini, W; Barlow, R J; Barschel, C; Barsuk, S; Barter, W; Batozskaya, V; Bauer, Th; Bay, A; Beddow, J; Bedeschi, F; Bediaga, I; Belogurov, S; Belous, K; Belyaev, I; Ben-Haim, E; Bencivenni, G; Benson, S; Benton, J; Berezhnoy, A; Bernet, R; Bettler, M-O; van Beuzekom, M; Bien, A; Bifani, S; Bird, T; Bizzeti, A; Bjørnstad, P M; Blake, T; Blanc, F; Blouw, J; Blusk, S; Bocci, V; Bondar, A; Bondar, N; Bonivento, W; Borghi, S; Borgia, A; Borsato, M; Bowcock, T J V; Bowen, E; Bozzi, C; Brambach, T; van den Brand, J; Bressieux, J; Brett, D; Britsch, M; Britton, T; Brook, N H; Brown, H; Bursche, A; Busetto, G; Buytaert, J; Cadeddu, S; Calabrese, R; Callot, O; Calvi, M; Calvo Gomez, M; Camboni, A; Campana, P; Campora Perez, D; Carbone, A; Carboni, G; Cardinale, R; Cardini, A; Carranza-Mejia, H; Carson, L; Carvalho Akiba, K; Casse, G; Castillo Garcia, L; Cattaneo, M; Cauet, Ch; Cenci, R; Charles, M; Charpentier, Ph; Cheung, S-F; Chiapolini, N; Chrzaszcz, M; Ciba, K; Cid Vidal, X; Ciezarek, G; Clarke, P E L; Clemencic, M; Cliff, H V; Closier, J; Coca, C; Coco, V; Cogan, J; Cogneras, E; Collins, P; Comerma-Montells, A; Contu, A; Cook, A; Coombes, M; Coquereau, S; Corti, G; Counts, I; Couturier, B; Cowan, G A; Craik, D C; Cruz Torres, M; Cunliffe, S; Currie, R; D'Ambrosio, C; Dalseno, J; David, P; David, P N Y; Davis, A; De Bonis, I; De Bruyn, K; De Capua, S; De Cian, M; De Miranda, J M; De Paula, L; De Silva, W; De Simone, P; Decamp, D; Deckenhoff, M; Del Buono, L; Déléage, N; Derkach, D; Deschamps, O; Dettori, F; Di Canto, A; Dijkstra, H; Donleavy, S; Dordei, F; Dorigo, M; Dorosz, P; Dosil Suárez, A; Dossett, D; Dovbnya, A; Dupertuis, F; Durante, P; Dzhelyadin, R; Dziurda, A; Dzyuba, A; Easo, S; Egede, U; Egorychev, V; Eidelman, S; Eisenhardt, S; Eitschberger, U; Ekelhof, R; Eklund, L; El Rifai, I; Elsasser, Ch; Falabella, A; Färber, C; Farinelli, C; Farry, S; Ferguson, D; Fernandez Albor, V; Ferreira Rodrigues, F; Ferro-Luzzi, M; Filippov, S; Fiore, M; Fiorini, M; Fitzpatrick, C; Fontana, M; Fontanelli, F; Forty, R; Francisco, O; Frank, M; Frei, C; Frosini, M; Furfaro, E; Gallas Torreira, A; Galli, D; Gandelman, M; Gandini, P; Gao, Y; Garofoli, J; Garra Tico, J; Garrido, L; Gaspar, C; Gauld, R; Gersabeck, E; Gersabeck, M; Gershon, T; Ghez, Ph; Gianelle, A; Gibson, V; Giubega, L; Gligorov, V V; Göbel, C; Golubkov, D; Golutvin, A; Gomes, A; Gordon, H; Grabalosa Gándara, M; Graciani Diaz, R; Granado Cardoso, L A; Graugés, E; Graziani, G; Grecu, A; Greening, E; Gregson, S; Griffith, P; Grillo, L; Grünberg, O; Gui, B; Gushchin, E; Guz, Yu; Gys, T; Hadjivasiliou, C; Haefeli, G; Haen, C; Hafkenscheid, T W; Haines, S C; Hall, S; Hamilton, B; Hampson, T; Hansmann-Menzemer, S; Harnew, N; Harnew, S T; Harrison, J; Hartmann, T; He, J; Head, T; Heijne, V; Hennessy, K; Henrard, P; Hernando Morata, J A; van Herwijnen, E; Heß, M; Hicheur, A; Hill, D; Hoballah, M; Hombach, C; Hulsbergen, W; Hunt, P; Huse, T; Hussain, N; Hutchcroft, D; Hynds, D; Iakovenko, V; Idzik, M; Ilten, P; Jacobsson, R; Jaeger, A; Jans, E; Jaton, P; Jawahery, A; Jing, F; John, M; Johnson, D; Jones, C R; Joram, C; Jost, B; Jurik, N; Kaballo, M; Kandybei, S; Kanso, W; Karacson, M; Karbach, T M; Kenyon, I R; Ketel, T; Khanji, B; Khurewathanakul, C; Klaver, S; Kochebina, O; Komarov, I; Koopman, R F; Koppenburg, P; Korolev, M; Kozlinskiy, A; Kravchuk, L; Kreplin, K; Kreps, M; Krocker, G; Krokovny, P; Kruse, F; Kucharczyk, M; Kudryavtsev, V; Kurek, K; Kvaratskheliya, T; La Thi, V N; Lacarrere, D; Lafferty, G; Lai, A; Lambert, D; Lambert, R W; Lanciotti, E; Lanfranchi, G; Langenbruch, C; Latham, T; Lazzeroni, C; Le Gac, R; van Leerdam, J; Lees, J-P; Lefèvre, R; Leflat, A; Lefrançois, J; Leo, S; Leroy, O; Lesiak, T; Leverington, B; Li, Y; Liles, M; Lindner, R; Linn, C; Lionetto, F; Liu, B; Liu, G; Lohn, S; Longstaff, I; Lopes, J H; Lopez-March, N; Lowdon, P; Lu, H; Lucchesi, D; Luisier, J; Luo, H; Luppi, E; Lupton, O; Machefert, F; Machikhiliyan, I V; Maciuc, F; Maev, O; Malde, S; Manca, G; Mancinelli, G; Manzali, M; Maratas, J; Marconi, U; Marino, P; Märki, R; Marks, J; Martellotti, G; Martens, A; Martín Sánchez, A; Martinelli, M; Martinez Santos, D; Martins Tostes, D; Massafferri, A; Matev, R; Mathe, Z; Matteuzzi, C; Mazurov, A; McCann, M; McCarthy, J; McNab, A; McNulty, R; McSkelly, B; Meadows, B; Meier, F; Meissner, M; Merk, M; Milanes, D A; Minard, M-N; Molina Rodriguez, J; Monteil, S; Moran, D; Morandin, M; Morawski, P; Mordà, A; Morello, M J; Mountain, R; Mous, I; Muheim, F; Müller, K; Muresan, R; Muryn, B; Muster, B; Naik, P; Nakada, T; Nandakumar, R; Nasteva, I; Needham, M; Neubert, S; Neufeld, N; Nguyen, A D; Nguyen, T D; Nguyen-Mau, C; Nicol, M; Niess, V; Niet, R; Nikitin, N; Nikodem, T; Novoselov, A; Oblakowska-Mucha, A; Obraztsov, V; Oggero, S; Ogilvy, S; Okhrimenko, O; Oldeman, R; Onderwater, G; Orlandea, M; Otalora Goicochea, J M; Owen, P; Oyanguren, A; Pal, B K; Palano, A; Palutan, M; Panman, J; Papanestis, A; Pappagallo, M; Pappalardo, L; Parkes, C; Parkinson, C J; Passaleva, G; Patel, G D; Patel, M; Patrignani, C; Pavel-Nicorescu, C; Pazos Alvarez, A; Pearce, A; Pellegrino, A; Penso, G; Pepe Altarelli, M; Perazzini, S; Perez Trigo, E; Perret, P; Perrin-Terrin, M; Pescatore, L; Pesen, E; Pessina, G; Petridis, K; Petrolini, A; Picatoste Olloqui, E; Pietrzyk, B; Pilař, T; Pinci, D; Pistone, A; Playfer, S; Plo Casasus, M; Polci, F; Polok, G; Poluektov, A; Polycarpo, E; Popov, A; Popov, D; Popovici, B; Potterat, C; Powell, A; Prisciandaro, J; Pritchard, A; Prouve, C; Pugatch, V; Puig Navarro, A; Punzi, G; Qian, W; Rachwal, B; Rademacker, J H; Rakotomiaramanana, B; Rama, M; Rangel, M S; Raniuk, I; Rauschmayr, N; Raven, G; Redford, S; Reichert, S; Reid, M M; Dos Reis, A C; Ricciardi, S; Richards, A; Rinnert, K; Rives Molina, V; Roa Romero, D A; Robbe, P; Roberts, D A; Rodrigues, A B; Rodrigues, E; Rodriguez Perez, P; Roiser, S; Romanovsky, V; Romero Vidal, A; Rotondo, M; Rouvinet, J; Ruf, T; Ruffini, F; Ruiz, H; Ruiz Valls, P; Sabatino, G; Saborido Silva, J J; Sagidova, N; Sail, P; Saitta, B; Salustino Guimaraes, V; Sanmartin Sedes, B; Santacesaria, R; Santamarina Rios, C; Santovetti, E; Sapunov, M; Sarti, A; Satriano, C; Satta, A; Savrie, M; Savrina, D; Schiller, M; Schindler, H; Schlupp, M; Schmelling, M; Schmidt, B; Schneider, O; Schopper, A; Schune, M-H; Schwemmer, R; Sciascia, B; Sciubba, A; Seco, M; Semennikov, A; Senderowska, K; Sepp, I; Serra, N; Serrano, J; Seyfert, P; Shapkin, M; Shapoval, I; Shcheglov, Y; Shears, T; Shekhtman, L; Shevchenko, O; Shevchenko, V; Shires, A; Silva Coutinho, R; Simi, G; Sirendi, M; Skidmore, N; Skwarnicki, T; Smith, N A; Smith, E; Smith, E; Smith, J; Smith, M; Snoek, H; Sokoloff, M D; Soler, F J P; Soomro, F; Souza, D; Souza De Paula, B; Spaan, B; Sparkes, A; Spinella, F; Spradlin, P; Stagni, F; Stahl, S; Steinkamp, O; Stevenson, S; Stoica, S; Stone, S; Storaci, B; Stracka, S; Straticiuc, M; Straumann, U; Stroili, R; Subbiah, V K; Sun, L; Sutcliffe, W; Swientek, S; Syropoulos, V; Szczekowski, M; Szczypka, P; Szilard, D; Szumlak, T; T'Jampens, S; Teklishyn, M; Tellarini, G; Teodorescu, E; Teubert, F; Thomas, C; Thomas, E; van Tilburg, J; Tisserand, V; Tobin, M; Tolk, S; Tomassetti, L; Tonelli, D; Topp-Joergensen, S; Torr, N; Tournefier, E; Tourneur, S; Tran, M T; Tresch, M; Tsaregorodtsev, A; Tsopelas, P; Tuning, N; Ubeda Garcia, M; Ukleja, A; Ustyuzhanin, A; Uwer, U; Vagnoni, V; Valenti, G; Vallier, A; Vazquez Gomez, R; Vazquez Regueiro, P; Vázquez Sierra, C; Vecchi, S; Velthuis, J J; Veltri, M; Veneziano, G; Vesterinen, M; Viaud, B; Vieira, D; Vilasis-Cardona, X; Vollhardt, A; Volyanskyy, D; Voong, D; Vorobyev, A; Vorobyev, V; Voß, C; Voss, H; de Vries, J A; Waldi, R; Wallace, C; Wallace, R; Wandernoth, S; Wang, J; Ward, D R; Watson, N K; Webber, A D; Websdale, D; Whitehead, M; Wicht, J; Wiechczynski, J; Wiedner, D; Wiggers, L; Wilkinson, G; Williams, M P; Williams, M; Wilson, F F; Wimberley, J; Wishahi, J; Wislicki, W; Witek, M; Wormser, G; Wotton, S A; Wright, S; Wu, S; Wyllie, K; Xie, Y; Xing, Z; Yang, Z; Yuan, X; Yushchenko, O; Zangoli, M; Zavertyaev, M; Zhang, F; Zhang, L; Zhang, W C; Zhang, Y; Zhelezov, A; Zhokhov, A; Zhong, L; Zvyagin, A

    The lifetime of the [Formula: see text] meson is measured using semileptonic decays having a [Formula: see text] meson and a muon in the final state. The data, corresponding to an integrated luminosity of [Formula: see text], are collected by the LHCb detector in [Formula: see text] collisions at a centre-of-mass energy of 8 TeV. The measured lifetime is [Formula: see text]where the first uncertainty is statistical and the second is systematic.

  6. TIGER/Line Shapefile, 2010, 2010 state, District of Columbia, 2010 Census Block State-based

    Data.gov (United States)

    US Census Bureau, Department of Commerce — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  7. [The Italian deprivation index at census block level: definition, description and association with general mortality].

    Science.gov (United States)

    Caranci, Nicola; Biggeri, Annibale; Grisotto, Laura; Pacelli, Barbara; Spadea, Teresa; Costa, Giuseppe

    2010-01-01

    the study is aimed at developing a nationwide deprivation index at municipality and census block level, based on the 2001 Census data, and meeting epidemiological needs. The study uses data drawn from the 2001 General Census of Population and Housing. From the 280 variables defined at census block level (352,605 census tracts with average number of inhabitants 169, standard deviation 225; and average area 0.6 km², sd 2.4 km²) five traits that operationally combine to represent the multidimensionality of the social and material deprivation concept have been selected; these are: low level of education, unemployment, non-home ownership, one parent family and overcrowding. The index is calculated by summing standardized indicators and it is also available as categorical by quintiles of population. The same procedure is applied to aggregate frequency data at municipality level. The correlation between mortality and deprivation has been evaluated using 2000-2004 general mortality. considering national data, a strong north-south gradient in deprivation was observed. The municipality deprivation index 2001 is highly correlated to the index likewise calculated on the basis of the previous 1991 Census (r=0.91). General mortality was positively correlated to the index (in particular in population up to 64 years and in larger size municipalities). the pattern described by the deprivation index was coherent with what is already known about geographic distribution of poverty and its impact on mortality. Such outcome bears out the index use for epidemiological purposes.

  8. Hard paths, soft paths or no paths? Cross-cultural perceptions of water solutions

    Science.gov (United States)

    Wutich, A.; White, A. C.; White, D. D.; Larson, K. L.; Brewis, A.; Roberts, C.

    2014-01-01

    In this study, we examine how development status and water scarcity shape people's perceptions of "hard path" and "soft path" water solutions. Based on ethnographic research conducted in four semi-rural/peri-urban sites (in Bolivia, Fiji, New Zealand, and the US), we use content analysis to conduct statistical and thematic comparisons of interview data. Our results indicate clear differences associated with development status and, to a lesser extent, water scarcity. People in the two less developed sites were more likely to suggest hard path solutions, less likely to suggest soft path solutions, and more likely to see no path to solutions than people in the more developed sites. Thematically, people in the two less developed sites envisioned solutions that involve small-scale water infrastructure and decentralized, community-based solutions, while people in the more developed sites envisioned solutions that involve large-scale infrastructure and centralized, regulatory water solutions. People in the two water-scarce sites were less likely to suggest soft path solutions and more likely to see no path to solutions (but no more likely to suggest hard path solutions) than people in the water-rich sites. Thematically, people in the two water-rich sites seemed to perceive a wider array of unrealized potential soft path solutions than those in the water-scarce sites. On balance, our findings are encouraging in that they indicate that people are receptive to soft path solutions in a range of sites, even those with limited financial or water resources. Our research points to the need for more studies that investigate the social feasibility of soft path water solutions, particularly in sites with significant financial and natural resource constraints.

  9. Harding County Blocks, Housing Occupancy Status (2010)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article...

  10. Harding County Blocks, Households by Type (2010)

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The once-a-decade decennial census was conducted in April 2010 by the U.S. Census Bureau. This count of every resident in the United States was mandated by Article...

  11. Impact of coastal defence structures (tetrapods) on a demersal hard-bottom fish community in the southern North Sea.

    Science.gov (United States)

    Wehkamp, Stephanie; Fischer, Philipp

    2013-02-01

    In the coming decades, artificial defence structures will increase in importance worldwide for the protection of coasts against the impacts of global warming. However, the ecological effects of such structures on the natural surroundings remain unclear. We investigated the impact of experimentally introduced tetrapod fields on the demersal fish community in a hard-bottom area in the southern North Sea. The results indicated a significant decrease in fish abundance in the surrounding area caused by migration effects towards the artificial structures. Diversity (HB) and evenness (E) values exhibited greater variation after the introduction of the tetrapods. Additionally, a distinct increase in young-of-the-year (YOY) fish was observed near the structures within the second year after introduction. We suggest that the availability of adequate refuges in combination with additional food resources provided by the artificial structures has a highly species-specific attraction effect. However, these findings also demonstrate that our knowledge regarding the impact of artificial structures on temperate fish communities is still too limited to truly understand the ecological processes that are initiated by the introduction of artificial structures. Long-term investigations and additional experimental in situ work worldwide will be indispensable for a full understanding of the mechanisms by which coastal defence structures interact with the coastal environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Looked-but-failed-to-see-errors in traffic

    DEFF Research Database (Denmark)

    Herslund, Mai-Britt; Jørgensen, N O

    2003-01-01

    Danish studies of traffic accidents at priority intersections have shown a particular type of accidents. In these accidents a car driver supposed to give way has collided with a bicycle rider on the priority road. Often the involved car drivers have maintained that they did not see the bicycle...... looking in the direction where the other parties were but have not seen (i.e. perceived the presence of) the other road user. This paper describes two studies approaching this problem.One study is based on 10 self-reported near accidents. It does show that "looked-but-failed-to-see" events do occur...... until immediately before the collision even though the bicycle must have been clearly visible.Similar types of accidents have been the subject of studies elsewhere. In literature they are labelled "looked-but-failed-to-see", because it seems clear that in many cases the car drivers have actually been...

  13. [Application of image recognition technology in census of national traditional Chinese medicine resources].

    Science.gov (United States)

    Zhang, Xiao-Bo; Ge, Xiao-Guang; Jin, Yan; Shi, Ting-Ting; Wang, Hui; Li, Meng; Jing, Zhi-Xian; Guo, Lan-Ping; Huang, Lu-Qi

    2017-11-01

    With the development of computer and image processing technology, image recognition technology has been applied to the national medicine resources census work at all stages.Among them: ①In the preparatory work, in order to establish a unified library of traditional Chinese medicine resources, using text recognition technology based on paper materials, be the assistant in the digitalization of various categories related to Chinese medicine resources; to determine the representative area and plots of the survey from each census team, based on the satellite remote sensing image and vegetation map and other basic data, using remote sensing image classification and other technical methods to assist in determining the key investigation area. ②In the process of field investigation, to obtain the planting area of Chinese herbal medicine was accurately, we use the decision tree model, spectral feature and object-oriented method were used to assist the regional identification and area estimation of Chinese medicinal materials.③In the process of finishing in the industry, in order to be able to relatively accurately determine the type of Chinese medicine resources in the region, based on the individual photos of the plant, the specimens and the name of the use of image recognition techniques, to assist the statistical summary of the types of traditional Chinese medicine resources. ④In the application of the results of transformation, based on the pharmaceutical resources and individual samples of medicinal herbs, the development of Chinese medicine resources to identify APP and authentic herbs 3D display system, assisted the identification of Chinese medicine resources and herbs identification characteristics. The introduction of image recognition technology in the census of Chinese medicine resources, assisting census personnel to carry out related work, not only can reduce the workload of the artificial, improve work efficiency, but also improve the census results

  14. The effect of acidulated phosphate fluoride application on dental enamel surfaces hardness

    Directory of Open Access Journals (Sweden)

    Edhie Arief P

    2007-09-01

    Full Text Available Enamel demineralization by acid is the first step of caries process. It has recently been shown that acidulated phosphate fluoride (APF can maintain the hardness of enamel surface. The aim of this study was examine the effect of APF application in the hardest of enamel surface. Fifty extracted teeth were cut at their crown, 40 teeth were taken randomly then divided into 4 groups, group 1 as the control, group 2 was treated with APF for 1 minute, group 3 for 4 minutes and group 4 for 7 minutes, then all the samples were washed with demineralized water. To see the effect of APF, all of the samples were soaked in lactic acid demineralization solution with pH 4,5 for 72 hours., the hardness of the surfaces of those samples before and after the treatment was measured by Micro Vickers Hardness Tester. The data were analyzed using One-Way ANOVA and LSD tests. In conclusion, 1.23% APF gel can reduce higher enamel demineralization.

  15. New Mexico, 2010 Census, Primary and Secondary Roads

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  16. New Mexico, 2010 Census Unified School District Shapefile

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  17. Guadalupe County 2010 Census County Subdivision County-based

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  18. Bernalillo County 2010 Census County Subdivision County-based

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  19. New Mexico, 2010 Census County Subdivision State-based

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  20. New Mexico, 2010 Census Block Group State-based

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  1. Eddy County 2010 Census County Subdivision County-based

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census...

  2. A CDT-Based Heuristic Zone Design Approach for Economic Census Investigators

    Directory of Open Access Journals (Sweden)

    Changixu Cheng

    2015-01-01

    Full Text Available This paper addresses a special zone design problem for economic census investigators that is motivated by a real-world application. This paper presented a heuristic multikernel growth approach via Constrained Delaunay Triangulation (CDT. This approach not only solved the barriers problem but also dealt with the polygon data in zoning procedure. In addition, it uses a new heuristic method to speed up the zoning process greatly on the premise of the required quality of zoning. At last, two special instances for economic census were performed, highlighting the performance of this approach.

  3. Comparing relative abundance, lengths, and habitat of temperate reef fishes using simultaneous underwater visual census, video, and trap sampling

    KAUST Repository

    Bacheler, NM

    2017-04-28

    Unbiased counts of individuals or species are often impossible given the prevalence of cryptic or mobile species. We used 77 simultaneous multi-gear deployments to make inferences about relative abundance, diversity, length composition, and habitat of the reef fish community along the southeastern US Atlantic coast. In total, 117 taxa were observed by underwater visual census (UVC), stationary video, and chevron fish traps, with more taxa being observed by UVC (100) than video (82) or traps (20). Frequency of occurrence of focal species was similar among all sampling approaches for tomtate Haemulon aurolineatum and black sea bass Centropristis striata, higher for UVC and video compared to traps for red snapper Lutjanus campechanus, vermilion snapper Rhomboplites aurorubens, and gray triggerfish Balistes capriscus, and higher for UVC compared to video or traps for gray snapper L. griseus and lionfish Pterois spp. For 6 of 7 focal species, correlations of relative abundance among gears were strongest between UVC and video, but there was substantial variability among species. The number of recorded species between UVC and video was correlated (ρ = 0.59), but relationships between traps and the other 2 methods were weaker. Lengths of fish visually estimated by UVC were similar to lengths of fish caught in traps, as were habitat characterizations from UVC and video. No gear provided a complete census for any species in our study, suggesting that analytical methods accounting for imperfect detection are necessary to make unbiased inferences about fish abundance.

  4. Maternal mortality in South Africa in 2001: From demographic census to epidemiological investigation

    Directory of Open Access Journals (Sweden)

    McCaa Robert

    2008-08-01

    Full Text Available Abstract Background Maternal mortality remains poorly researched in Africa, and is likely to worsen dramatically as a consequence of HIV/AIDS. Methods The 2001 census of South Africa included a question on deaths in the previous 12 months, and two questions on external causes and maternal mortality, defined as "pregnancy-related deaths". A microdata sample from the census permits researchers to assess levels and differentials in maternal mortality, in a country severely affected by high death rates from HIV/AIDS and from external causes. Results After correcting for several minor biases, our estimate of the Maternal Mortality Ratio (MMR in 2001 was 542 per 100,000 live births. This level is much higher than previous estimates dating from pre-HIV/AIDS times. This high level occurred despite a relatively low proportion of maternal deaths (6.4% among deaths of women aged 15–49 years, and was due to the astonishingly high level of adult mortality, some 4.7 times higher than expected from mortality below age 15 or above age 50. The main reasons for these excessive levels were HIV/AIDS and external causes of deaths. Our regional estimates of MMR were found to be consistent with other findings in the Cape Town area, and with the Agincourt DSS. The differentials in MMR were considerable: 1 to 9.2 for population groups (race, 1 to 3.2 for provinces, and 1 to 2.4 for levels of education. Relationship with income and wealth were complex, with highest values for middle income and middle wealth index. The effect of urbanization was small, and reversed in a multivariate analysis. Higher risks in provinces were not necessarily associated with lower income, lower education or higher proportions of home delivery, but correlated primarily with the prevalence of HIV/AIDS. Conclusion Demographic census microdata offer the opportunity to conduct an epidemiologic analysis of maternal mortality. In the case of South Africa, the level of MMR increased dramatically

  5. Unveiling the Biodiversity of Deep-Sea Nematodes through Metabarcoding: Are We Ready to Bypass the Classical Taxonomy?

    Science.gov (United States)

    Dell'Anno, Antonio; Carugati, Laura; Corinaldesi, Cinzia; Riccioni, Giulia; Danovaro, Roberto

    2015-01-01

    Nematodes inhabiting benthic deep-sea ecosystems account for >90% of the total metazoan abundances and they have been hypothesised to be hyper-diverse, but their biodiversity is still largely unknown. Metabarcoding could facilitate the census of biodiversity, especially for those tiny metazoans for which morphological identification is difficult. We compared, for the first time, different DNA extraction procedures based on the use of two commercial kits and a previously published laboratory protocol and tested their suitability for sequencing analyses of 18S rDNA of marine nematodes. We also investigated the reliability of Roche 454 sequencing analyses for assessing the biodiversity of deep-sea nematode assemblages previously morphologically identified. Finally, intra-genomic variation in 18S rRNA gene repeats was investigated by Illumina MiSeq in different deep-sea nematode morphospecies to assess the influence of polymorphisms on nematode biodiversity estimates. Our results indicate that the two commercial kits should be preferred for the molecular analysis of biodiversity of deep-sea nematodes since they consistently provide amplifiable DNA suitable for sequencing. We report that the morphological identification of deep-sea nematodes matches the results obtained by metabarcoding analysis only at the order-family level and that a large portion of Operational Clustered Taxonomic Units (OCTUs) was not assigned. We also show that independently from the cut-off criteria and bioinformatic pipelines used, the number of OCTUs largely exceeds the number of individuals and that 18S rRNA gene of different morpho-species of nematodes displayed intra-genomic polymorphisms. Our results indicate that metabarcoding is an important tool to explore the diversity of deep-sea nematodes, but still fails in identifying most of the species due to limited number of sequences deposited in the public databases, and in providing quantitative data on the species encountered. These aspects

  6. Vulnerability of marginal seas to sea level rise

    Science.gov (United States)

    Gomis, Damia; Jordà, Gabriel

    2017-04-01

    Sea level rise (SLR) is a serious thread for coastal areas and has a potential negative impact on society and economy. SLR can lead for instance to land loss, beach reduction, increase of the damage of marine storms on coastal infrastructures and to the salinization of underground water streams. It is well acknowledged that future SLR will be inhomogeneous across the globe, with regional differences of up to 100% with respect to global mean sea level (GMSL). Several studies have addressed the projections of SLR at regional scale, but most of them are based on global climate models (GCMs) that have a relatively coarse spatial resolution (>1°). In marginal seas this has proven to be a strong limitation, as their particular configurations require spatial resolutions that are not reachable by present GCMs. A paradigmatic case is the Mediterranean Sea, connected to the global ocean through the Strait of Gibraltar, a narrow passage of 14 km width. The functioning of the Mediterranean Sea involves a variety of processes including an overturning circulation, small-scale convection and a rich mesoscale field. Moreover, the long-term evolution of Mediterranean sea level has been significantly different from the global mean during the last decades. The observations of present climate and the projections for the next decades have lead some authors to hypothesize that the particular characteristics of the basin could allow Mediterranean mean sea level to evolve differently from the global mean. Assessing this point is essential to undertake proper adaptation strategies for the largely populated Mediterranean coastal areas. In this work we apply a new approach that combines regional and global projections to analyse future SLR. In a first step we focus on the quantification of the expected departures of future Mediterranean sea level from GMSL evolution and on the contribution of different processes to these departures. As a result we find that, in spite of its particularities

  7. Public census data on CD-ROM at Lawrence Berkeley Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Merrill, D.W.

    1992-10-01

    The Comprehensive Epidemiologic Data Resource (CEDR) and Populations at Risk to Environmental Pollution (PAREP) projects, of the Information and Computing Sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), are using public socio-economic and geographic data files which are available to CEDR and PAREP collaborators via LBL's computing network. At this time 70 CD-ROM diskettes (approximately 36 gigabytes) are on line via the Unix file server cedrcd. lbl. gov. Most of the files are from the US Bureau of the Census, and most pertain to the 1990 Census of Population and Housing. All the CD-ROM diskettes contain documentation in the form of ASCII text files. Printed documentation for most files is available for inspection at University of California Data and Technical Assistance (UC DATA), or the UC Documents Library. Many of the CD-ROM diskettes distributed by the Census Bureau contain software for PC compatible computers, for easily accessing the data. Shared access to the data is maintained through a collaboration among the CEDR and PAREP projects at LBL, and UC DATA, and the UC Documents Library. Via the Sun Network File System (NFS), these data can be exported to Internet computers for direct access by the user's application program(s).

  8. Public census data on CD-ROM at Lawrence Berkeley Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Merrill, D.W.

    1992-10-01

    The Comprehensive Epidemiologic Data Resource (CEDR) and Populations at Risk to Environmental Pollution (PAREP) projects, of the Information and Computing Sciences Division (ICSD) at Lawrence Berkeley Laboratory (LBL), are using public socio-economic and geographic data files which are available to CEDR and PAREP collaborators via LBL`s computing network. At this time 70 CD-ROM diskettes (approximately 36 gigabytes) are on line via the Unix file server cedrcd. lbl. gov. Most of the files are from the US Bureau of the Census, and most pertain to the 1990 Census of Population and Housing. All the CD-ROM diskettes contain documentation in the form of ASCII text files. Printed documentation for most files is available for inspection at University of California Data and Technical Assistance (UC DATA), or the UC Documents Library. Many of the CD-ROM diskettes distributed by the Census Bureau contain software for PC compatible computers, for easily accessing the data. Shared access to the data is maintained through a collaboration among the CEDR and PAREP projects at LBL, and UC DATA, and the UC Documents Library. Via the Sun Network File System (NFS), these data can be exported to Internet computers for direct access by the user`s application program(s).

  9. [Location information acquisition and sharing application design in national census of Chinese medicine resources].

    Science.gov (United States)

    Zhang, Xiao-Bo; Li, Meng; Wang, Hui; Guo, Lan-Ping; Huang, Lu-Qi

    2017-11-01

    In literature, there are many information on the distribution of Chinese herbal medicine. Limited by the technical methods, the origin of Chinese herbal medicine or distribution of information in ancient literature were described roughly. It is one of the main objectives of the national census of Chinese medicine resources, which is the background information of the types and distribution of Chinese medicine resources in the region. According to the national Chinese medicine resource census technical specifications and pilot work experience, census team with "3S" technology, computer network technology, digital camera technology and other modern technology methods, can effectively collect the location information of traditional Chinese medicine resources. Detailed and specific location information, such as regional differences in resource endowment and similarity, biological characteristics and spatial distribution, the Chinese medicine resource census data access to the accuracy and objectivity evaluation work, provide technical support and data support. With the support of spatial information technology, based on location information, statistical summary and sharing of multi-source census data can be realized. The integration of traditional Chinese medicine resources and related basic data can be a spatial integration, aggregation and management of massive data, which can help for the scientific rules data mining of traditional Chinese medicine resources from the overall level and fully reveal its scientific connotation. Copyright© by the Chinese Pharmaceutical Association.

  10. 15 CFR 50.40 - Fee structure for statistics for city blocks in the 1980 Census of Population and Housing.

    Science.gov (United States)

    2010-01-01

    ... blocks in the 1980 Census of Population and Housing. 50.40 Section 50.40 Commerce and Foreign Trade... the 1980 Census of Population and Housing. (a) As part of the regular program of the 1980 census, the Census Bureau will publish printed reports containing certain summary population and housing statistics...

  11. Temporal and Spatial Scales of Labrador Sea Water Formation

    Science.gov (United States)

    Clarke, R. A.

    1984-01-01

    Labrador Sea Water is an intermediate water found at the same density and depth range in the North Atlantic as the Mediterranean water. It is formed by convection from the sea surface to depths greather than 2 km in winter in the Western Labrador Sea. The processes leading to deep convection begin with the formation of a 200 km scale cyclonic circulation about denser than average upper layer water in the Western Labrador Sea. This circulation pattern is hypothesized to be driven by an ocean/atmosphere heat exchange that has its maximum in this region. By early March, if deep convection is taking place, one sees that this body of denser upper waters penetrates to the top of the deep temperature/salinity maximum marking the core of the North Atlantic Deep Water. We note that the horizontal scale of this body is still 100-200 km normal to the coastline.

  12. Hardness of enamel exposed to Coca-Cola and artificial saliva.

    Science.gov (United States)

    Devlin, H; Bassiouny, M A; Boston, D

    2006-01-01

    The purpose of this study was to determine the rate of change in indentation hardness of enamel in permanent teeth exposed to Coca-Cola. In a further experiment, the ability of a commercially available artificial saliva to remineralize enamel treated with Coca-Cola was tested. Ten enamel specimens were randomly chosen to be treated with Coca-Cola (experimental groups) and seven with water (control group). The fluids were applied for 1, 2, 3 h and overnight (15 h), washed off with a few drops of water and the moist enamel indentation hardness tested after each interval. With Coca-Cola treatment, the mean enamel hardness was 92.6% (s.d. = 7.9) of the original baseline hardness after 1 h, 93.25% (s.d. = 10.15) after 2 h, 85.7% (s.d. = 12.03) after 3 h and 80.3% after 15 h. The mean indentation hardness of control specimens treated with water was 108.7% (s.d. = 16.09) of the original hardness after 1 h, 99.09% (s.d. = 18.98) after 2 h, 98.97% (s.d. =11.24) after 3 h and 98.42% (s.d. = 22.78) after 15 h. In a separate experiment, the hardness of 9 enamel specimens was tested, as previously described, before and after treatment with Coca-Cola overnight and again after application of artificial saliva for 3 min. Coca-Cola reduced the mean indentation hardness of enamel in the teeth, but the hardness was partially restored with artificial saliva (Salivart) and increased by 18% from the demineralized enamel hardness.

  13. Nordic children’s ideas about living things in the sea

    DEFF Research Database (Denmark)

    Stougaard, Birgitte

    The aim of the study is to explores what kind of ideas eight years old children in the Nordic countries have about life in the sea according to their drawings. It aim is also to see if there is a difference between their ideas and if so, what kind of difference. The children were asked to draw...... everything they knew that lives in the sea. Each child was asked to explain their drawing. A special scale was used to analyse the drawings. Oral presentation at ASE Annual Conference, University of Reading 6-8 January 2011...

  14. Comparison of farmers in the agricultural health study to the 1992 and the 1997 censuses of agriculture.

    Science.gov (United States)

    Lynch, Charles F; Sprince, Nancy L; Heywood, Ellen; Pierce, Joy; Logsden-Sackett, Nyla; Pennybacker, Margaret; Alavanja, Michael C R

    2005-01-01

    The Agricultural Health Study (AHS) is a large, prospective cohort study in the states of Iowa and North Carolina that has been developed to better understand how pesticides and other agricultural exposures relate to the occurrence of cancer and other diseases. This report compares the characteristics of AHS farmers to the Census of Agriculture to evaluate the generalizability of AHS findings. We restricted the AHS to private pesticide applicators who enrolled in Iowa (n = 31,065) and in North Carolina (n = 17,239) between 1993 and 1997, and who identified themselves as living or working on a farm. We compared their self-reported data with data from the 1992 and 1997 Censuses of Agriculture. AHS farmers in Iowa are younger; live or work on larger farms; more frequently apply herbicides, insecticides, and fungicides; and are more likely to raise beef cattle and swine, and grow corn, soybeans, hay, and oats. AHS farmers in North Carolina are also younger, live or work on larger farms, more frequently reported growing crops commonly seen in the state, and are more frequent pesticide users. However, animals raised are similar to those in the North Carolina Census of Agriculture. AHS farmers likely represent the higher end of pesticide usage in both states in part because AHS farmers have larger farms. Since the health effects of pesticides are best ascertained among pesticide users with the greatest exposure, the AHS cohort should prove to be a valuable resource for health effects research.

  15. Collective modes in simple melts: Transition from soft spheres to the hard sphere limit.

    Science.gov (United States)

    Khrapak, Sergey; Klumov, Boris; Couëdel, Lénaïc

    2017-08-11

    We study collective modes in a classical system of particles with repulsive inverse-power-law (IPL) interactions in the fluid phase, near the fluid-solid coexistence (IPL melts). The IPL exponent is varied from n = 10 to n = 100 to mimic the transition from moderately soft to hard-sphere-like interactions. We compare the longitudinal dispersion relations obtained using molecular dynamic (MD) simulations with those calculated using the quasi-crystalline approximation (QCA) and find that this simple theoretical approach becomes grossly inaccurate for [Formula: see text]. Similarly, conventional expressions for high-frequency (instantaneous) elastic moduli, predicting their divergence as n increases, are meaningless in this regime. Relations of the longitudinal and transverse elastic velocities of the QCA model to the adiabatic sound velocity, measured in MD simulations, are discussed for the regime where QCA is applicable. Two potentially useful freezing indicators for classical particle systems with steep repulsive interactions are discussed.

  16. Search-Lidar Demonstrator for Detection of Small Sea-Surface Targets

    NARCIS (Netherlands)

    Heuvel, J.C. van den; Bekman, H.H.P.T.; Putten, F.J.M. van; Cohen, L.H.; Schleijpen, H.M.A.

    2008-01-01

    Coastal surveillance and naval operations in the littoral both have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and a low velocity that makes them hard to detect by radar. Typical threats include jet skis, FIAC’s, and speedboats. Lidar

  17. Educational Planning: The Census Bureau Can Help.

    Science.gov (United States)

    Whitson, Dorothy W.

    The author states that projection of future populations is not feasible because the chief factor in the computations, the birth rate, cannot be predicted with certainty. The paper discusses some national implications, and also suggests that census data by school district can be useful in improving formulas for distribution of federal and State…

  18. [Symbol: see text]2 Optimized predictive image coding with [Symbol: see text]∞ bound.

    Science.gov (United States)

    Chuah, Sceuchin; Dumitrescu, Sorina; Wu, Xiaolin

    2013-12-01

    In many scientific, medical, and defense applications of image/video compression, an [Symbol: see text]∞ error bound is required. However, pure[Symbol: see text]∞-optimized image coding, colloquially known as near-lossless image coding, is prone to structured errors such as contours and speckles if the bit rate is not sufficiently high; moreover, most of the previous [Symbol: see text]∞-based image coding methods suffer from poor rate control. In contrast, the [Symbol: see text]2 error metric aims for average fidelity and hence preserves the subtlety of smooth waveforms better than the ∞ error metric and it offers fine granularity in rate control, but pure [Symbol: see text]2-based image coding methods (e.g., JPEG 2000) cannot bound individual errors as the [Symbol: see text]∞-based methods can. This paper presents a new compression approach to retain the benefits and circumvent the pitfalls of the two error metrics. A common approach of near-lossless image coding is to embed into a DPCM prediction loop a uniform scalar quantizer of residual errors. The said uniform scalar quantizer is replaced, in the proposed new approach, by a set of context-based [Symbol: see text]2-optimized quantizers. The optimization criterion is to minimize a weighted sum of the [Symbol: see text]2 distortion and the entropy while maintaining a strict [Symbol: see text]∞ error bound. The resulting method obtains good rate-distortion performance in both [Symbol: see text]2 and [Symbol: see text]∞ metrics and also increases the rate granularity. Compared with JPEG 2000, the new method not only guarantees lower [Symbol: see text]∞ error for all bit rates, but also it achieves higher PSNR for relatively high bit rates.

  19. 78 FR 67103 - Request for Nominations of Members To Serve on the Census Scientific Advisory Committee

    Science.gov (United States)

    2013-11-08

    ... the Census Bureau on the uses of scientific developments in statistical data collection, statistical analysis, survey methodology, geospatial analysis, econometrics, cognitive psychology, and computer science... following disciplines: demography, economics, geography, psychology, statistics, survey methodology, social...

  20. 77 FR 1454 - Request for Nominations of Members To Serve on the Census Scientific Advisory Committee

    Science.gov (United States)

    2012-01-10

    ... the U.S. Census Bureau on the uses of scientific developments in statistical data collection, statistical analysis, survey methodology, geospatial analysis, econometrics, cognitive psychology, and... following disciplines: Demography, economics, geography, psychology, statistics, survey methodology, social...