Transferring 2001 National Household Travel Survey

Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle Atlantic, and Pacific), MSA size, and the availability of rail. Extrapolating NHTS data within small geographic areas could risk developing and subsequently using unreliable estimates. For example, if a planning agency in City X of State Y estimates travel rates and other travel characteristics based on survey data collected from NHTS sample households that were located in City X of State Y, then the agency could risk developing and using unreliable estimates for their planning process. Typically, this limitation significantly increases as the size of an area decreases. That said, the NHTS contains a wealth of information that could allow statistical inferences about small geographic areas, with a pre-determined level of statistical certainty. The question then becomes whether a method can be developed that integrates the NHTS data and other data to estimate key travel characteristics for small geographic areas such as Census tract and transportation analysis zone, and whether this method can outperform other, competing methods

Arthroscopic decompression and notchplasty for long-standing anterior cruciate ligament impingement in a patient with multiple epiphyseal dysplasia: a case report

<p>Abstract</p> <p>Introduction</p> <p>Multiple epiphyseal dysplasia is a genetically and clinically heterogeneous osteochondroplasia with symmetrical involvement. It is characterized by joint pain in childhood and early adulthood with early onset of osteoarthritis, mainly affecting the hips.</p> <p>Case presentation</p> <p>We report the case of a 20-year-old man of Asian origin with multiple epiphyseal dysplasia presenting with bilateral knee pain, stiffness and instability found to be caused by bilateral anterior cruciate ligament impingement on abnormal medial femoral condyles. Bilateral staged arthroscopic notchplasty was performed successfully, resulting in subjective relief of pain, and improved range of movement and stability.</p> <p>Conclusion</p> <p>Care should be taken not to exclude a diagnosis of multiple epiphyseal dysplasia when few of the characteristic radiographic features are evident but clinical suspicion is high. This case highlights the scope for subjective symptomatic improvement following a minimum of surgical intervention. We recommend limiting early intervention to managing symptomatic features rather than radiographic abnormalities alone.</p

Conserved synteny at the protein family level reveals genes underlying Shewanella species’ cold tolerance and predicts their novel phenotypes

© The Authors 2009. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License. The definitive version was published in Functional & Integrative Genomics 10 (2010): 97-110, doi:10.1007/s10142-009-0142-y.Bacteria of the genus Shewanella can thrive in different environments and demonstrate significant variability in their metabolic and ecophysiological capabilities including cold and salt tolerance. Genomic characteristics underlying this variability across species are largely unknown. In this study, we address the problem by a comparison of the physiological, metabolic, and genomic characteristics of 19 sequenced Shewanella species. We have employed two novel approaches based on association of a phenotypic trait with the number of the trait-specific protein families (Pfam domains) and on the conservation of synteny (order in the genome) of the trait-related genes. Our first approach is top-down and involves experimental evaluation and quantification of the species’ cold tolerance followed by identification of the correlated Pfam domains and genes with a conserved synteny. The second, a bottom-up approach, predicts novel phenotypes of the species by calculating profiles of each Pfam domain among their genomes and following pair-wise correlation of the profiles and their network clustering. Using the first approach, we find a link between cold and salt tolerance of the species and the presence in the genome of a Na+/H+ antiporter gene cluster. Other cold-tolerance-related genes include peptidases, chemotaxis sensory transducer proteins, a cysteine exporter, and helicases. Using the bottom-up approach, we found several novel phenotypes in the newly sequenced Shewanella species, including degradation of aromatic compounds by an aerobic hybrid pathway in Shewanella woodyi, degradation of ethanolamine by Shewanella benthica, and propanediol degradation by Shewanella putrefaciens CN32 and Shewanella sp. W3-18-1.This research was supported by the U.S. Department of Energy (DOE) Office of Biological and Environmental Research under the Genomics: GTL Program via the Shewanella Federation consortium

The Global Historical Climatology Network: A preview of Version 2

Instruments that could reliably measure temperature, precipitation, and pressure were developed by the late 17th and early 18th centuries. It has been estimated that weather records have been collected at one to two hundred thousand locations since those first instruments were placed in the field. Numerous applications, from global change studies to climate impact assessments to general circulation models, make use of such historical records. Given their importance, it is unfortunate that one cannot approach a single researcher or data center to acquire all of the records for all of the stations, or even a large portion of them. In 1990, the Carbon Dioxide Information Analysis Center (CDIAC), the National Climatic Data Center (NCDC), and the World Meteorological Organization (WMO) undertook a collaborative effort aimed at solving this problem. The initiative completed its first data product, known as the Global Historical Climatology Network (GHCN) version 1.0, in 1992. This data base contains quality-controlled monthly climatic time series from 6,039 temperature, 7,533 precipitation, 1,883 sea level pressure, and 1,873 station pressure stations located on global land areas. This paper describes the data and methods being used to compile GHCN version 2.0, an expanded and improved version of its predecessor. Planned for distribution in early 1995, its enhancements will include (1) data for additional stations--perhaps three times as many as in version 1.0, plus maximum/minimum temperature measurements; (2) detailed assessments of data quality, including nearest-neighbor checks; and (3) adjustments for nonclimatic inhomogeneities, such as station relocations and land use changes