Ecoregions of the conterminous United States: evolution of a hierarchical spatial framework
Omernik, James M.; Griffith, Glenn E.
2014-01-01
A map of ecological regions of the conterminous United States, first published in 1987, has been greatly refined and expanded into a hierarchical spatial framework in response to user needs, particularly by state resource management agencies. In collaboration with scientists and resource managers from numerous agencies and institutions in the United States, Mexico, and Canada, the framework has been expanded to cover North America, and the original ecoregions (now termed Level III) have been refined, subdivided, and aggregated to identify coarser as well as more detailed spatial units. The most generalized units (Level I) define 10 ecoregions in the conterminous U.S., while the finest-scale units (Level IV) identify 967 ecoregions. In this paper, we explain the logic underpinning the approach, discuss the evolution of the regional mapping process, and provide examples of how the ecoregions were distinguished at each hierarchical level. The variety of applications of the ecoregion framework illustrates its utility in resource assessment and management.
Ecoregions of the Conterminous United States: Evolution of a Hierarchical Spatial Framework
NASA Astrophysics Data System (ADS)
Omernik, James M.; Griffith, Glenn E.
2014-12-01
A map of ecological regions of the conterminous United States, first published in 1987, has been greatly refined and expanded into a hierarchical spatial framework in response to user needs, particularly by state resource management agencies. In collaboration with scientists and resource managers from numerous agencies and institutions in the United States, Mexico, and Canada, the framework has been expanded to cover North America, and the original ecoregions (now termed Level III) have been refined, subdivided, and aggregated to identify coarser as well as more detailed spatial units. The most generalized units (Level I) define 10 ecoregions in the conterminous U.S., while the finest-scale units (Level IV) identify 967 ecoregions. In this paper, we explain the logic underpinning the approach, discuss the evolution of the regional mapping process, and provide examples of how the ecoregions were distinguished at each hierarchical level. The variety of applications of the ecoregion framework illustrates its utility in resource assessment and management.
A hierarchical typology of intermodal air-rail connections at large airports in the United States.
DOT National Transportation Integrated Search
2010-01-01
In July 2005, the United States Government Accountability Office (GAO) issued a report discussing : intermodal transportation strategies in developing airport intermodal capabilities (USGAO 2005). In this : report, the GAO identified those airports t...
Ecological subregion codes by county, coterminous United States
Victor A. Rudis
1999-01-01
This publication presents the National Hierarchical Framework of Ecological Units (ECOMAP 1993) by county for the coterminous United States. Assignment of the framework to individual counties is based on the predominant area by province and section to facilitate integration of county-referenced information with areas of uniform ecological potential. Included are maps...
Hierarchical model analysis of the Atlantic Flyway Breeding Waterfowl Survey
Sauer, John R.; Zimmerman, Guthrie S.; Klimstra, Jon D.; Link, William A.
2014-01-01
We used log-linear hierarchical models to analyze data from the Atlantic Flyway Breeding Waterfowl Survey. The survey has been conducted by state biologists each year since 1989 in the northeastern United States from Virginia north to New Hampshire and Vermont. Although yearly population estimates from the survey are used by the United States Fish and Wildlife Service for estimating regional waterfowl population status for mallards (Anas platyrhynchos), black ducks (Anas rubripes), wood ducks (Aix sponsa), and Canada geese (Branta canadensis), they are not routinely adjusted to control for time of day effects and other survey design issues. The hierarchical model analysis permits estimation of year effects and population change while accommodating the repeated sampling of plots and controlling for time of day effects in counting. We compared population estimates from the current stratified random sample analysis to population estimates from hierarchical models with alternative model structures that describe year to year changes as random year effects, a trend with random year effects, or year effects modeled as 1-year differences. Patterns of population change from the hierarchical model results generally were similar to the patterns described by stratified random sample estimates, but significant visibility differences occurred between twilight to midday counts in all species. Controlling for the effects of time of day resulted in larger population estimates for all species in the hierarchical model analysis relative to the stratified random sample analysis. The hierarchical models also provided a convenient means of estimating population trend as derived statistics from the analysis. We detected significant declines in mallard and American black ducks and significant increases in wood ducks and Canada geese, a trend that had not been significant for 3 of these 4 species in the prior analysis. We recommend using hierarchical models for analysis of the Atlantic Flyway Breeding Waterfowl Survey.
Hierarchical Bayesian Model (HBM) - Derived Estimates of Air Quality for 2007: Annual Report
This report describes EPA's Hierarchical Bayesian model generated (HBM) estimates of ozone (O3) and fine particulate matter (PM2.5 particles with aerodynamic diameter < 2.5 microns)concentrations throughout the continental United States during the 2007 calen...
Hierarchical group testing for multiple infections.
Hou, Peijie; Tebbs, Joshua M; Bilder, Christopher R; McMahan, Christopher S
2017-06-01
Group testing, where individuals are tested initially in pools, is widely used to screen a large number of individuals for rare diseases. Triggered by the recent development of assays that detect multiple infections at once, screening programs now involve testing individuals in pools for multiple infections simultaneously. Tebbs, McMahan, and Bilder (2013, Biometrics) recently evaluated the performance of a two-stage hierarchical algorithm used to screen for chlamydia and gonorrhea as part of the Infertility Prevention Project in the United States. In this article, we generalize this work to accommodate a larger number of stages. To derive the operating characteristics of higher-stage hierarchical algorithms with more than one infection, we view the pool decoding process as a time-inhomogeneous, finite-state Markov chain. Taking this conceptualization enables us to derive closed-form expressions for the expected number of tests and classification accuracy rates in terms of transition probability matrices. When applied to chlamydia and gonorrhea testing data from four states (Region X of the United States Department of Health and Human Services), higher-stage hierarchical algorithms provide, on average, an estimated 11% reduction in the number of tests when compared to two-stage algorithms. For applications with rarer infections, we show theoretically that this percentage reduction can be much larger. © 2016, The International Biometric Society.
Hierarchical group testing for multiple infections
Hou, Peijie; Tebbs, Joshua M.; Bilder, Christopher R.; McMahan, Christopher S.
2016-01-01
Summary Group testing, where individuals are tested initially in pools, is widely used to screen a large number of individuals for rare diseases. Triggered by the recent development of assays that detect multiple infections at once, screening programs now involve testing individuals in pools for multiple infections simultaneously. Tebbs, McMahan, and Bilder (2013, Biometrics) recently evaluated the performance of a two-stage hierarchical algorithm used to screen for chlamydia and gonorrhea as part of the Infertility Prevention Project in the United States. In this article, we generalize this work to accommodate a larger number of stages. To derive the operating characteristics of higher-stage hierarchical algorithms with more than one infection, we view the pool decoding process as a time-inhomogeneous, finite-state Markov chain. Taking this conceptualization enables us to derive closed-form expressions for the expected number of tests and classification accuracy rates in terms of transition probability matrices. When applied to chlamydia and gonorrhea testing data from four states (Region X of the United States Department of Health and Human Services), higher-stage hierarchical algorithms provide, on average, an estimated 11 percent reduction in the number of tests when compared to two-stage algorithms. For applications with rarer infections, we show theoretically that this percentage reduction can be much larger. PMID:27657666
Hierarchical Bayesian Model (HBM)-Derived Estimates of Air Quality for 2004 - Annual Report
This report describes EPA's Hierarchical Bayesian model-generated (HBM) estimates of O3 and PM2.5 concentrations throughout the continental United States during the 2004 calendar year. HBM estimates provide the spatial and temporal variance of O3 ...
Hierarchical Bayesian Model (HBM) - Derived Estimates of Air Quality for 2008: Annual Report
This report describes EPA’s Hierarchical Bayesian model generated (HBM) estimates of ozone (O3) and fine particulate matter (PM2.5, particles with aerodynamic diameter < 2.5 microns) concentrations throughout the continental United States during the 2007 ca...
Hierarchical Trust Management of COI in Heterogeneous Mobile Networks
2017-08-01
PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 5c. PROGRAM ELEMENT NUMBER 5b. GRANT NUMBER 5a. CONTRACT NUMBER Form Approved OMB NO. 0704...Report: Hierarchical Trust Management of COI in Heterogeneous Mobile Networks The views, opinions and/or findings contained in this report are those of...Institute & State University Title: Hierarchical Trust Management of COI in Heterogeneous Mobile Networks Report Term: 0-Other Email: irchen@vt.edu
Ecological Subregions: Sections and Subsections for the conterminous United States
D.T. Cleland; J.A. Freeouf; J.E. Keys; G.J. Nowacki; C.A. Carpenter; W.H. McNab
2007-01-01
This map and accompanying descriptions were developed through participation with numerous individuals from federal and state agencies and non-governmental organizations using criteria defined in the National Hierarchical Framework of Ecological Units. Delineation generally involved the âtop-down approachâ of subdividing section level units. A âbottom-up approachâ was...
ERIC Educational Resources Information Center
Escobar-Ortloff, Luz Marina; Ortloff, Warren G.
This paper shares reflections from a doctoral dissertation that investigated differences in hierarchical values (social and moral) that existed between preservice teacher education students and professors of education in the United States and Colombia. The study used the Rokeach Value Survey instrument to determine students' and faculty members'…
Supporting Novice Teachers through Mentoring and Induction in the United States
ERIC Educational Resources Information Center
Zembytska, Maryna
2015-01-01
The study focuses on the U.S. system of novice teacher support. The study highlights the evolution of mentoring from a traditional, isolated, hierarchical one-to-one relationship to multiple interactions which comprise a collaborative developmental network. The findings suggest that mentoring and induction support in the United States are…
Forest ecosystems of a Lower Gulf Coastal Plainlandscape: multifactor classification and analysis
P. Charles Goebel; Brian J. Palik; L. Katherine Kirkman; Mark B. Drew; Larry West; Dee C. Pederson
2001-01-01
The most common forestland classification techniques applied in the southeastern United States are vegetation-based. While not completely ignored, the application of multifactor, hierarchical ecosystem classifications are limited despite their widespread use in other regions of the eastern United States. We present one of the few truly integrated ecosystem...
Mark A. Rumble; R. Scott Gamo
2011-01-01
Timber management is the most prominent land management activity in the Black Hills National Forest in the northcentral United States. Management units are stands 4-32 ha in size and are described using a hierarchal vegetative description including vegetation type, size class (age), and overstory canopy cover. For the most part, these stands are relatively homogeneous...
ERIC Educational Resources Information Center
Wu, Yin
2016-01-01
This study intends to compare and contrast student and school factors that are associated with students' mathematics self-efficacy in the United States and China. Using hierarchical linear regressions to analyze the Programme for International Student Assessment (PISA) 2012 data, this study compares math self-efficacy, achievement, and variables…
Spatial scaling of non-native fish richness across the United States
Qinfeng Guo; Julian D. Olden
2014-01-01
A major goal and challenge of invasion ecology is to describe and interpret spatial and temporal patterns of species invasions. Here, we examined fish invasion patterns at four spatially structured and hierarchically nested scales across the contiguous United States (i.e., from large to small: region, basin, watershed, and sub-watershed). All spatial relationships in...
Delineation, peer review, and refinement of subregions of the conterminous United States
J.E. Keys; D.T. Cleland; W.H. McNab
2007-01-01
This paper briefly describes the background of the U.S. Department of Agriculture (USDA) Forest Service National Hierarchical Framework of Ecological Units and the methods used for delineating map units at the subregion planning and analysis scale. The process for scientific review and continuous refinement of ecological units and associated data of subregions is also...
ERIC Educational Resources Information Center
Ying, Yu-Wen; Han, Meekyung
2008-01-01
The study examined variation in the prediction of adjustment in Taiwanese students by ethnic density. A total of 155 Taiwanese students were assessed via survey pre-departure and three times post-arrival in the United States. Hierarchical regression analysis showed students on campuses with fewer other Taiwanese peers formed more friendships with…
ERIC Educational Resources Information Center
Lee, Gang; Kim, Yanghee
2016-01-01
To identify ways that national culture, school characteristics, and individual attributes impact the victimization of students in Grade 8, data from the United States and three East Asian countries (i.e., Japan, S. Korea, and Taiwan) were compared using the 2011 Trends in International Mathematics and Science Study (TIMSS) and Hierarchical Liner…
Reversing Patterns of Control in Australia: Can Schools Be Self-Governing?
ERIC Educational Resources Information Center
Smart, Don
Historically, in sharp contrast with the United States, the Australian state systems of public education have always been extremely centralized and hierarchical in structure. While these highly centralized systems served the sparsely populated Australian states well during the early years of this century in providing universal free education and…
DOT National Transportation Integrated Search
1995-08-01
Bridge design engineers and local highway officials make bridge replacement decisions across the : United States. The Analytical Hierarchy Process was used to characterize the bridge material selection : decision of these individuals. State Departmen...
Delineation of climate regions in the Northeastern United States
Arthur T. DeGaetano
1996-01-01
Climate is a primary criterion for the development, description and validation of subregional levels of the National Hierarchical Framework of Ecological Units. However, climate information is not currently available in the form or level of detail required for integration with other biophysical factors at the section or subsection levels. In this study, historical...
ERIC Educational Resources Information Center
Nunez, Anne-Marie; Kim, Dongbin
2012-01-01
Latinos' college enrollment rates, particularly in four-year institutions, have not kept pace with their population growth in the United States. Using three-level hierarchical generalized linear modeling, this study analyzes data from the Educational Longitudinal Study (ELS) to examine the influence of high school and state contexts, in addition…
Kashuba, Roxolana; Cha, YoonKyung; Alameddine, Ibrahim; Lee, Boknam; Cuffney, Thomas F.
2010-01-01
Multilevel hierarchical modeling methodology has been developed for use in ecological data analysis. The effect of urbanization on stream macroinvertebrate communities was measured across a gradient of basins in each of nine metropolitan regions across the conterminous United States. The hierarchical nature of this dataset was harnessed in a multi-tiered model structure, predicting both invertebrate response at the basin scale and differences in invertebrate response at the region scale. Ordination site scores, total taxa richness, Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa richness, and richness-weighted mean tolerance of organisms at a site were used to describe invertebrate responses. Percentage of urban land cover was used as a basin-level predictor variable. Regional mean precipitation, air temperature, and antecedent agriculture were used as region-level predictor variables. Multilevel hierarchical models were fit to both levels of data simultaneously, borrowing statistical strength from the complete dataset to reduce uncertainty in regional coefficient estimates. Additionally, whereas non-hierarchical regressions were only able to show differing relations between invertebrate responses and urban intensity separately for each region, the multilevel hierarchical regressions were able to explain and quantify those differences within a single model. In this way, this modeling approach directly establishes the importance of antecedent agricultural conditions in masking the response of invertebrates to urbanization in metropolitan regions such as Milwaukee-Green Bay, Wisconsin; Denver, Colorado; and Dallas-Fort Worth, Texas. Also, these models show that regions with high precipitation, such as Atlanta, Georgia; Birmingham, Alabama; and Portland, Oregon, start out with better regional background conditions of invertebrates prior to urbanization but experience faster negative rates of change with urbanization. Ultimately, this urbanization-invertebrate response example is used to detail the multilevel hierarchical construction methodology, showing how the result is a set of models that are both statistically more rigorous and ecologically more interpretable than simple linear regression models.
A Hierarchical Model and Analysis of Factors Affecting the Adoption of Timber as a Bridge
Robert L. Smith; Robert J. Bush; Daniel L. Schmoldt
1995-01-01
The Analytical Hierarchy Process was used to characterize the bridge material selection decisions of highway engineers and local highway officials across the United States. State Department of Transportation engineers, private consulting engineers, and local highway officials were personally interviewed in Mississippi, Virginia, Washington, and Wisconsin to identify...
Level III Ecoregions of Alaska
Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. The ecoregions of Alaska are a framework for organizing and interpreting environmental data for State, national, and international level inventory, monitoring, and research efforts. The map and descriptions for 20 ecological regions were derived by synthesizing information on the geographic distribution of environmental factors such as climate, physiography, geology, permafrost, soils, and vegetation. A qualitative assessment was used to interpret the distributional patterns and relative importance of these factors from place to place (Gallant and others, 1995). Numeric identifiers assigned to the ecoregions are coordinated with those used on the map of Ecoregions of the Conterminous United States (Omernik 1987, U.S. EPA 2010) as a continuation of efforts to map ecoregions for the United States. Additionally, the ecoregions for Alaska and the conterminous United States, along with ecological regions for Canada (Wiken 1986) and Mexico, have been combined for maps at three hierarchical levels for North America (Omernik 1995, Commission for Environmental Cooperation, 1997, 2006). A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions. At Level III, there are currently 182
M.D. Bryant; B.E. Wright; B.J. Davies
1992-01-01
A hierarchical classification system separating stream habitat into habitat units defined by stream morphology and hydrology was used in a pre-enhancement stream survey. The system separates habitat units into macrounits, mesounits, and micro- units and includes a separate evaluation of instream cover that also uses the hierarchical scheme. This paper presents an...
Robert L. Smith; Robert J. Bush; Daniel L. Schmoldt
1995-01-01
Bridge design engineers and local highway officials make bridge replacement decisions across the United States. The Analytical Hierarchy Process was used to characterize the bridge material selection decision of these individuals. State Department of Transportation engineers, private consulting engineers, and local highway officials were personally interviewed in...
Virulence differences in blumeria graminis f. sp. tritici from the central and eastern United States
USDA-ARS?s Scientific Manuscript database
Wheat powdery mildew is a disease of international importance that occurs across a wide geographic area in the USA. A virulence survey of Blumeria graminis f. sp. tritici, the causal agent, was conducted by sampling 36 wheat fields in 15 U.S. states in the years 2013 and 2014. Using a hierarchical...
Improving Water Quality Assessments through a HierarchicalBayesian Analysis of Variability
Water quality measurement error and variability, while well-documented in laboratory-scale studies, is rarely acknowledged or explicitly resolved in most water body assessments, including those conducted in compliance with the United States Environmental Protection Agency (USEPA)...
Badre, David
2012-01-01
Growing evidence suggests that the prefrontal cortex (PFC) is organized hierarchically, with more anterior regions having increasingly abstract representations. How does this organization support hierarchical cognitive control and the rapid discovery of abstract action rules? We present computational models at different levels of description. A neural circuit model simulates interacting corticostriatal circuits organized hierarchically. In each circuit, the basal ganglia gate frontal actions, with some striatal units gating the inputs to PFC and others gating the outputs to influence response selection. Learning at all of these levels is accomplished via dopaminergic reward prediction error signals in each corticostriatal circuit. This functionality allows the system to exhibit conditional if–then hypothesis testing and to learn rapidly in environments with hierarchical structure. We also develop a hybrid Bayesian-reinforcement learning mixture of experts (MoE) model, which can estimate the most likely hypothesis state of individual participants based on their observed sequence of choices and rewards. This model yields accurate probabilistic estimates about which hypotheses are attended by manipulating attentional states in the generative neural model and recovering them with the MoE model. This 2-pronged modeling approach leads to multiple quantitative predictions that are tested with functional magnetic resonance imaging in the companion paper. PMID:21693490
The consequences of consensus: American health policy in the twentieth century.
Fox, D M
1986-01-01
For most of the twentieth century the central theme in the history of health policy in the United States was the elaboration and implementation of a consensus that health services should be organized in regional hierarchies. This consensus was based on shared beliefs about how medical advances were made and disseminated. Hierarchical regionalism became national health policy in several stages that culminated in the 1960s. Since the 1970s, however, the national policy of hierarchical regionalism has been eroded by the unexpected consequences of its success.
Bagdasarov, Zhanna; Edmondson, Christine B
2013-01-01
We investigated the role of anger expression and cultural framework in predicting Russian immigrant women's physical and psychological health status. One hundred Russian immigrant women between the ages of 30 and 65 completed questionnaires assessing anger expression, cultural framework, and health status. All research questions were addressed using hierarchical regression procedures. The results are discussed in terms of implications for understanding immigration experiences of Russian women who migrate from countries that are more collectivistic and less individualistic than the United States.
Glendon W. Smalley; Carlie McCowan; S. David Todd; Phillip M. Morrissey; J. Andrew McBride
2013-01-01
This paper summarizes the application of a land classification system developed by the senior author to the Standing Stone State Forest and State Park (SSSF&SP) on the Eastern Highland Rim. Landtypes are the most detailed level in the hierarchical system and represent distinct units of the landscape (mapped at a scale of 1:24,000) as defined by climate, geology,...
Violated expectations and acculturative stress among U.S. Hispanic immigrants.
Negy, Charles; Schwartz, Shari; Reig-Ferrer, Abilio
2009-07-01
Expectancy violation theory (EVT) was tested with 112 Hispanic immigrants living in the United States by determining whether discrepancies between their retrospectively recalled pre-migration expectations about life in the United States and their post-migration (actual) experiences in the United States would predict their levels of acculturative stress. Discrepancies were assessed in 4 domains (ability to communicate with English speakers, perceiving their communities and the United States as safe, obtaining adequate employment, and experiencing racism). Overall, the results indicated that discrepancies between pre-migration expectations and post-migration experiences were associated significantly with acculturative stress, although some of the findings were counter to EVT. Also, on the basis of a hierarchical regression analysis, the discrepancies significantly, albeit modestly, contributed to the prediction of acculturative stress beyond the predictive ability of general demographic variables and post-migration experiences. Implications for clinical interventions and research opportunities with EVT and Hispanic immigrants are discussed.
Gu, Weidong; Medalla, Felicita; Hoekstra, Robert M
2018-02-01
The National Antimicrobial Resistance Monitoring System (NARMS) at the Centers for Disease Control and Prevention tracks resistance among Salmonella infections. The annual number of Salmonella isolates of a particular serotype from states may be small, making direct estimation of resistance proportions unreliable. We developed a Bayesian hierarchical model to improve estimation by borrowing strength from relevant sampling units. We illustrate the models with different specifications of spatio-temporal interaction using 2004-2013 NARMS data for ceftriaxone-resistant Salmonella serotype Heidelberg. Our results show that Bayesian estimates of resistance proportions were smoother than observed values, and the difference between predicted and observed proportions was inversely related to the number of submitted isolates. The model with interaction allowed for tracking of annual changes in resistance proportions at the state level. We demonstrated that Bayesian hierarchical models provide a useful tool to examine spatio-temporal patterns of small sample size such as those found in NARMS. Published by Elsevier Ltd.
United States Marine Corps Cost Reduction and the Joint Battle Command Platform
2013-09-01
2013) ...................... 20 Figure 4. Hierarchical multi- level representation of the JBC-P FoS capability areas and metrics (After Han et...Technician FY Fiscal Year GAO Government Accountability Office GCE Ground Combat Element GOTS Government off the Shelf HMMWV High...widely dispersed units across the battlefield (HQMC, 2013). This control is desired to be extended down to the company level and below. The vision
Cohen, Mitchell J; Grossman, Adam D; Morabito, Diane; Knudson, M Margaret; Butte, Atul J; Manley, Geoffrey T
2010-01-01
Advances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome. Multivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality. We identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters. Here we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients.
A hierarchical framework of aquatic ecological units in North America (Nearctic Zone).
James R. Maxwell; Clayton J. Edwards; Mark E. Jensen; Steven J. Paustian; Harry Parrott; Donley M. Hill
1995-01-01
Proposes a framework for classifying and mapping aquatic systems at various scales using ecologically significant physical and biological criteria. Classification and mapping concepts follow tenets of hierarchical theory, pattern recognition, and driving variables. Criteria are provided for the hierarchical classification and mapping of aquatic ecological units of...
Building hierarchical models of avian distributions for the State of Georgia
Howell, J.E.; Peterson, J.T.; Conroy, M.J.
2008-01-01
To predict the distributions of breeding birds in the state of Georgia, USA, we built hierarchical models consisting of 4 levels of nested mapping units of decreasing area: 90,000 ha, 3,600 ha, 144 ha, and 5.76 ha. We used the Partners in Flight database of point counts to generate presence and absence data at locations across the state of Georgia for 9 avian species: Acadian flycatcher (Empidonax virescens), brownheaded nuthatch (Sitta pusilla), Carolina wren (Thryothorus ludovicianus), indigo bunting (Passerina cyanea), northern cardinal (Cardinalis cardinalis), prairie warbler (Dendroica discolor), yellow-billed cuckoo (Coccyxus americanus), white-eyed vireo (Vireo griseus), and wood thrush (Hylocichla mustelina). At each location, we estimated hierarchical-level-specific habitat measurements using the Georgia GAP Analysis18 class land cover and other Geographic Information System sources. We created candidate, species-specific occupancy models based on previously reported relationships, and fit these using Markov chain Monte Carlo procedures implemented in OpenBugs. We then created a confidence model set for each species based on Akaike's Information Criterion. We found hierarchical habitat relationships for all species. Three-fold cross-validation estimates of model accuracy indicated an average overall correct classification rate of 60.5%. Comparisons with existing Georgia GAP Analysis models indicated that our models were more accurate overall. Our results provide guidance to wildlife scientists and managers seeking predict avian occurrence as a function of local and landscape-level habitat attributes.
Sasaki, Hatoko; Yonemoto, Naohiro; Mori, Rintaro; Nishida, Toshihiko; Kusuda, Satoshi; Nakayama, Takeo
2017-01-01
Abstract Objective To assess organizational culture in neonatal intensive care units (NICUs) in Japan. Design Cross-sectional survey of organizational culture. Setting Forty NICUs across Japan. Participants Physicians and nurses who worked in NICUs (n = 2006). Main Outcome Measures The Competing Values Framework (CVF) was used to assess the organizational culture of the study population. The 20-item CVF was divided into four culture archetypes: Group, Developmental, Hierarchical and Rational. We calculated geometric means (gmean) and 95% bootstrap confidence intervals of the individual dimensions by unit and occupation. The median number of staff, beds, physicians’ work hours and work engagement were also calculated to examine the differences by culture archetypes. Results Group (gmean = 34.6) and Hierarchical (gmean = 31.7) culture archetypes were higher than Developmental (gmean = 16.3) and Rational (gmean = 17.4) among physicians as a whole. Hierarchical (gmean = 36.3) was the highest followed by Group (gmean = 25.8), Developmental (gmean = 16.3) and Rational (gmean = 21.7) among nurses as a whole. Units with dominant Hierarchical culture had a slightly higher number of physicians (median = 7) than dominant Group culture (median = 6). Units with dominant Group culture had a higher number of beds (median = 12) than dominant Hierarchical culture (median = 9) among physicians. Nurses from units with a dominant Group culture (median = 2.8) had slightly higher work engagement compared with those in units with a dominant Hierarchical culture (median = 2.6). Conclusions Our findings revealed that organizational culture in NICUs varies depending on occupation and group size. Group and Hierarchical cultures predominated in Japanese NICUs. Assessing organizational culture will provide insights into the perceptions of unit values to improve quality of care. PMID:28371865
Sasaki, Hatoko; Yonemoto, Naohiro; Mori, Rintaro; Nishida, Toshihiko; Kusuda, Satoshi; Nakayama, Takeo
2017-06-01
To assess organizational culture in neonatal intensive care units (NICUs) in Japan. Cross-sectional survey of organizational culture. Forty NICUs across Japan. Physicians and nurses who worked in NICUs (n = 2006). The Competing Values Framework (CVF) was used to assess the organizational culture of the study population. The 20-item CVF was divided into four culture archetypes: Group, Developmental, Hierarchical and Rational. We calculated geometric means (gmean) and 95% bootstrap confidence intervals of the individual dimensions by unit and occupation. The median number of staff, beds, physicians' work hours and work engagement were also calculated to examine the differences by culture archetypes. Group (gmean = 34.6) and Hierarchical (gmean = 31.7) culture archetypes were higher than Developmental (gmean = 16.3) and Rational (gmean = 17.4) among physicians as a whole. Hierarchical (gmean = 36.3) was the highest followed by Group (gmean = 25.8), Developmental (gmean = 16.3) and Rational (gmean = 21.7) among nurses as a whole. Units with dominant Hierarchical culture had a slightly higher number of physicians (median = 7) than dominant Group culture (median = 6). Units with dominant Group culture had a higher number of beds (median = 12) than dominant Hierarchical culture (median = 9) among physicians. Nurses from units with a dominant Group culture (median = 2.8) had slightly higher work engagement compared with those in units with a dominant Hierarchical culture (median = 2.6). Our findings revealed that organizational culture in NICUs varies depending on occupation and group size. Group and Hierarchical cultures predominated in Japanese NICUs. Assessing organizational culture will provide insights into the perceptions of unit values to improve quality of care. © The Author 2017. Published by Oxford University Press in association with the International Society for Quality in Health Care
Re-Envisioning Nurse Faculty Mentoring: Developmental Network Connections That Count
ERIC Educational Resources Information Center
Kennedy, Margaret Babb
2012-01-01
Fears surrounding the nurse faculty shortage in the United States have prompted significant emphasis on supporting novice educators and those in transition to new roles within academia through mentoring. Yet a continued focus on traditionally held notions of a hierarchical dyad limits possibilities for facilitating rich, diverse, mentoring…
ERIC Educational Resources Information Center
Lester, Regan; Petrie, Trent A.
1995-01-01
Examined the relationship of personality and physical variables to bulimic symptoms. Hierarchical regression analysis of a sample of Mexican American female students revealed that body mass and endorsement of United States societal values concerning attractiveness were related positively to bulimic symptomatology; age, body satisfaction, and…
Implementation of a Matrix Organizational Structure: A Case Study.
ERIC Educational Resources Information Center
Whorton, David M.
The implementation of a matrix structure as an alternative to the traditional collegial/bureaucratic form at a college of education in a medium-size state university is described. Matrix organizational structures are differentiated from hierarchical bureaucratic structures by dividing the organization's tasks into functional units across which an…
Background/Question/Methods Many environmental factors influence human mortality simultaneously. However, assessing their cumulative effects remains a challenging task. In this study we used the Environmental Quality Index (EQI), developed by the U.S. EPA, as a measure of overall...
ERIC Educational Resources Information Center
Kennedy, Sheryl Y.; Smith, Julia B.
2013-01-01
This study used Hierarchical Linear Modeling to analyze the relationship between school organizational behaviors and practices (at the school level) on teachers' reports of internal and external physiological sources of efficacy. Six hundred sixty-one teachers from 42 schools in the United States were surveyed to measure both individual sources of…
Janssen, Terry
2000-01-01
A system and method for facilitating decision-making comprising a computer program causing linkage of data representing a plurality of argument structure units into a hierarchical argument structure. Each argument structure unit comprises data corresponding to a hypothesis and its corresponding counter-hypothesis, data corresponding to grounds that provide a basis for inference of the hypothesis or its corresponding counter-hypothesis, data corresponding to a warrant linking the grounds to the hypothesis or its corresponding counter-hypothesis, and data corresponding to backing that certifies the warrant. The hierarchical argument structure comprises a top level argument structure unit and a plurality of subordinate level argument structure units. Each of the plurality of subordinate argument structure units comprises at least a portion of the grounds of the argument structure unit to which it is subordinate. Program code located on each of a plurality of remote computers accepts input from one of a plurality of contributors. Each input comprises data corresponding to an argument structure unit in the hierarchical argument structure and supports the hypothesis or its corresponding counter-hypothesis. A second programming code is adapted to combine the inputs into a single hierarchical argument structure. A third computer program code is responsive to the second computer program code and is adapted to represent a degree of support for the hypothesis and its corresponding counter-hypothesis in the single hierarchical argument structure.
Forested plant associations of the Colville National Forest.
Clinton K. Williams; Brian F. Kelley; Bradley G. Smith; Terry R. Lillybridge
1995-01-01
A classification of forest vegetation is presented for the Colville National Forest in northeastern Washington State. It is based on potential vegetation with the plant association as the basic unit. The classification is based on a sample of approximately 229 intensive plots and 282 reconnaissance plots distributed across the forest from 1980 to 1983. The hierarchical...
2016-04-06
used against Sri Lanka’s Tamil Tigers and UNITAS will likely bring an end to the Lord’s Resistance Army. Because the leader of the LRA, Joseph Kony... Tamil Tigers and Angola’s UNITAS. The level of violence between the three organizations is comparable. The lone or hierarchical organization may be
USDA-ARS?s Scientific Manuscript database
Venturia effusa is the most important pathogen of pecan in the southeastern USA. Little information exists on the population biology and genetic diversity of the pathogen. A hierarchical sampling of a total of 784 isolates from 63 trees in 11 pecan orchards in the southeastern USA were screened agai...
ERIC Educational Resources Information Center
Huang, Haigen; Zhu, Hao
2017-01-01
The purpose of this study was to examine whether school disciplinary climate and grit predicted low socioeconomic status (SES) students being high achievers in mathematics and science with a representative sample of 15-year-old students in the United States. Our analysis, using a two-level logistic hierarchical linear model (HLM), indicated both…
ERIC Educational Resources Information Center
Neseth, Hans; Savage, Todd A.; Navarro, Rachel
2009-01-01
The current migration of Latino/as into the United States has many schools struggling to meet the unique academic needs of this particular group of students. Previous research suggests level of acculturation and perceived social support impact mathematics achievement amongst Latino/a students. The current study employed hierarchical and…
ERIC Educational Resources Information Center
Shiovitz-Ezra, Sharon; Leitsch, Sara A.
2010-01-01
The authors explore associations between objective and subjective social network characteristics and loneliness in later life, using data from the National Social Life, Health, and Aging Project, a nationally representative sample of individuals ages 57 to 85 in the United States. Hierarchical linear regression was used to examine the associations…
USDA-ARS?s Scientific Manuscript database
Rift Valley fever (RVF) is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease...
NASA Astrophysics Data System (ADS)
Sahai, Swupnil
This thesis includes three parts. The overarching theme is how to analyze structured hierarchical data, with applications to astronomy and sociology. The first part discusses how expectation propagation can be used to parallelize the computation when fitting big hierarchical bayesian models. This methodology is then used to fit a novel, nonlinear mixture model to ultraviolet radiation from various regions of the observable universe. The second part discusses how the Stan probabilistic programming language can be used to numerically integrate terms in a hierarchical bayesian model. This technique is demonstrated on supernovae data to significantly speed up convergence to the posterior distribution compared to a previous study that used a Gibbs-type sampler. The third part builds a formal latent kernel representation for aggregate relational data as a way to more robustly estimate the mixing characteristics of agents in a network. In particular, the framework is applied to sociology surveys to estimate, as a function of ego age, the age and sex composition of the personal networks of individuals in the United States.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shorikov, A. F., E-mail: afshorikov@mail.ru
This article discusses a discrete-time dynamical system consisting of a set a controllable objects (region and forming it municipalities). The dynamics each of these is described by the corresponding vector nonlinear discrete-time recurrent vector equations and its control system consist from two levels: basic (control level I) that is dominating and subordinate level (control level II). Both levels have different criterions of functioning and united a priori by determined informational and control connections defined in advance. In this paper we study the problem of optimization of guaranteed result for program control by the final state of regional social and economicmore » system in the presence of risks. For this problem we proposed in this work an economical and mathematical model of two-level hierarchical minimax program control the final state of regional social and economic system in the presence of risks and the general scheme for its solving.« less
NASA Astrophysics Data System (ADS)
Shorikov, A. F.
2016-12-01
In this article we consider a discrete-time dynamical system consisting of a set a controllable objects (region and forming it municipalities). The dynamics each of these is described by the corresponding linear or nonlinear discrete-time recurrent vector relations and its control system consist from two levels: basic level (control level I) that is dominating level and auxiliary level (control level II) that is subordinate level. Both levels have different criterions of functioning and united by information and control connections which defined in advance. In this article we study the problem of optimization of guaranteed result for program control by the final state of regional social and economic system in the presence of risks vectors. For this problem we propose a mathematical model in the form of two-level hierarchical minimax program control problem of the final states of this system with incomplete information and the general scheme for its solving.
ERIC Educational Resources Information Center
Torney-Purta, Judith; Barber, Carolyn H.; Wilkenfeld, Britt
2007-01-01
Many studies have reported gaps between Latino and non-Latino adolescents in academic and political outcomes. The current study presents possible explanations for such gaps, both at the individual and school level. Hierarchical linear modeling is employed to examine data from 2,811 American ninth graders (approximately 14 years of age) who had…
Hong S. He; Daniel C. Dey; Xiuli Fan; Mevin B. Hooten; John M. Kabrick; Christopher K. Wikle; Zhaofei. Fan
2007-01-01
In the Midwestern United States, the GeneralLandOffice (GLO) survey records provide the only reasonably accurate data source of forest composition and tree species distribution at the time of pre-European settlement (circa late 1800 to early 1850). However, GLO data have two fundamental limitations: coarse spatial resolutions (the square mile section and half mile...
Early Reading Achievement of Children in Immigrant Families: Is There an Immigrant Paradox?
ERIC Educational Resources Information Center
Palacios, Natalia; Guttmanova, Katarina; Chase-Lansdale, P. Lindsay
2008-01-01
This article examines whether longitudinal reading trajectories vary by the generational status of immigrant children as they begin formal schooling through the 3rd grade. The results of the hierarchical linear model indicated that 1st and 2nd generation children (i.e., those born in a foreign country and those born in the United States to…
The United States Army Functional Concept for Intelligence, 2016-2028
2010-10-13
Intelligence improvement strategies historically addressed the changing operational environment by creating sensors and analytical systems designed to locate...hierarchical centrally- directed combat formations and predict their actions in high-intensity conflict. These strategies assumed that intelligence...4) U.S. operations can be derailed over time through a strategy of exhaustion. (5) U.S. forces distributed over wide areas can be
Brian J. Clough; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall
2016-01-01
Accurate uncertainty assessments of plot-level live tree biomass stocks are an important precursor to estimating uncertainty in annual national greenhouse gas inventories (NGHGIs) developed from forest inventory data. However, current approaches employed within the United Statesâ NGHGI do not specifically incorporate methods to address error in tree-scale biomass...
ERIC Educational Resources Information Center
Sebastian, James; Moon, Jeong-Mi
2017-01-01
The purpose of this study was to examine whether female principals have a more participatory style compared to their male counterparts by examining principals' daily time allocation patterns. The study analyzed data from End of Day (EOD) survey logs from principals in an urban school district in the United States. Results from hierarchical linear…
ERIC Educational Resources Information Center
Kandiko, C. B.
2008-01-01
To compare college and university student engagement in two countries with different responses to global forces, Canada and the United States (US), a series of hierarchical linear regression (HLM) models were developed to analyse data from the 2006 administration of the National Survey of Student Engagement (NSSE). Overall, students in the U.S.…
Regional forest resource assessment in an ecological framework: the Southern United States
Victor A. Rudis
1998-01-01
Information about forest resources grouped by ecologically homogeneous area can be used to discern relationships between those resources and ecological processes. The author used forest resource data from 0.4-ha plots, and data on population and land area (by county), together with a global-to-local hierarchical framework of land areas with similar ecological potential...
Wireless communication and spectrum sharing for public safety in the United States.
Kapucu, Naim; Haupt, Brittany; Yuksel, Murat
2016-01-01
With the vast number of fragmented, independent public safety wireless communication systems, the United States is encountering major challenges with enhancing interoperability and effectively managing costs while sharing limited availability of critical spectrum. The traditional hierarchical approach of emergency management does not always allow for needed flexibility and is not a mandate. A national system would reduce equipment needs, increase effectiveness, and enrich quality and coordination of response; however, it is dependent on integrating the commercial market. This article discusses components of an ideal national wireless public safety system consists along with key policies in regulating wireless communication and spectrum sharing for public safety and challenges for implementation.
Hao, Yongping; Balluz, Lina; Strosnider, Heather; Wen, Xiao Jun; Li, Chaoyang; Qualters, Judith R
2015-08-01
Short-term effects of air pollution exposure on respiratory disease mortality are well established. However, few studies have examined the effects of long-term exposure, and among those that have, results are inconsistent. To evaluate long-term association between ambient ozone, fine particulate matter (PM2.5, particles with an aerodynamic diameter of 2.5 μm or less), and chronic lower respiratory disease (CLRD) mortality in the contiguous United States. We fit Bayesian hierarchical spatial Poisson models, adjusting for five county-level covariates (percentage of adults aged ≥65 years, poverty, lifetime smoking, obesity, and temperature), with random effects at state and county levels to account for spatial heterogeneity and spatial dependence. We derived county-level average daily concentration levels for ambient ozone and PM2.5 for 2001-2008 from the U.S. Environmental Protection Agency's down-scaled estimates and obtained 2007-2008 CLRD deaths from the National Center for Health Statistics. Exposure to ambient ozone was associated with an increased rate of CLRD deaths, with a rate ratio of 1.05 (95% credible interval, 1.01-1.09) per 5-ppb increase in ozone; the association between ambient PM2.5 and CLRD mortality was positive but statistically insignificant (rate ratio, 1.07; 95% credible interval, 0.99-1.14). This study links air pollution exposure data with CLRD mortality for all 3,109 contiguous U.S. counties. Ambient ozone may be associated with an increased rate of death from CLRD in the contiguous United States. Although we adjusted for selected county-level covariates and unobserved influences through Bayesian hierarchical spatial modeling, the possibility of ecologic bias remains.
Genetic structure of Culex erraticus populations across the Americas.
Mendenhall, Ian H; Bahl, Justin; Blum, Michael J; Wesson, Dawn M
2012-05-01
Culex erraticus (Dyar & Knab) is a potential competent vector for several arboviruses such as Eastern and Venezuelan equine encephalitis viruses and West Nile virus. It therefore may play a role in the maintenance and spread of viral populations in areas of concern, including the United States where it occurs in >33 states. However, little information is available on potential barriers to movement across the species' distribution. Here, we analyze genetic variation among Cx. erraticus collected from Colombia, Guatemala, and nine locations in the United States to better understand population structure and connectivity. Comparative sequence analysis of the second internal transcribed spacer and mitochondrial NADH dehydrogenase genes identified two major lineages of sampled populations. One lineage represented the central and eastern United States, whereas the other corresponded to Central America, South America, and the western United States. Hierarchical analysis of genetic variation provided further evidence of regional population structure, although the majority of genetic variation was found to reside within populations, suggestive of large population sizes. Although significant physical barriers such as the Chihuahuan Desert probably constrain the spread of Cx. erraticus, large population sizes and connectivity within regions remain important risk factors that probably contribute to the movement of arboviruses within and between these regions.
ERIC Educational Resources Information Center
Glasser, Howard M.
2012-01-01
Although middle school is a critical time in adolescents' development, little is known about how that development is affected by public single-sex classes even though recent federal policy decisions have led more schools to provide these offerings. This case study used ethnographic methods to explore ways teachers, students, and courses in one…
ERIC Educational Resources Information Center
Siordia, Carlos; Diaz, Maria E.
2012-01-01
In this study, we investigate individual-level language shift in a population of Mexican origin Latinos/as aged 65 and up. By using data from the Hispanic Established Populations for the Epidemiologic Study of the Elderly, we investigate their English language use as the dependent variable in a hierarchical linear model. The microlevel independent…
NASA Astrophysics Data System (ADS)
Bao, Cheng; Cai, Ningsheng; Croiset, Eric
2011-10-01
Following our integrated hierarchical modeling framework of natural gas internal reforming solid oxide fuel cell (IRSOFC), this paper firstly introduces the model libraries of main balancing units, including some state-of-the-art achievements and our specific work. Based on gPROMS programming code, flexible configuration and modular design are fully realized by specifying graphically all unit models in each level. Via comparison with the steady-state experimental data of Siemens-Westinghouse demonstration system, the in-house multi-level SOFC-gas turbine (GT) simulation platform is validated to be more accurate than the advanced power system analysis tool (APSAT). Moreover, some units of the demonstration system are designed reversely for analysis of a typically part-load transient process. The framework of distributed and dynamic modeling in most of units is significant for the development of control strategies in the future.
Link, W.A.; Sauer, J.R.; Niven, D.K.
2006-01-01
Analysis of Christmas Bird Count (CBC) data is complicated by the need to account for variation in effort on counts and to provide summaries over large geographic regions. We describe a hierarchical model for analysis of population change using CBC data that addresses these needs. The effect of effort is modeled parametrically, with parameter values varying among strata as identically distributed random effects. Year and site effects are modeled hierarchically, accommodating large regional variation in number of samples and precision of estimates. The resulting model is complex, but a Bayesian analysis can be conducted using Markov chain Monte Carlo techniques. We analyze CBC data for American Black Ducks (Anas rubripes), a species of considerable management interest that has historically been monitored using winter surveys. Over the interval 1966-2003, Black Duck populations showed distinct regional patterns of population change. The patterns shown by CBC data are similar to those shown by the Midwinter Waterfowl Inventory for the United States.
Visual question answering using hierarchical dynamic memory networks
NASA Astrophysics Data System (ADS)
Shang, Jiayu; Li, Shiren; Duan, Zhikui; Huang, Junwei
2018-04-01
Visual Question Answering (VQA) is one of the most popular research fields in machine learning which aims to let the computer learn to answer natural language questions with images. In this paper, we propose a new method called hierarchical dynamic memory networks (HDMN), which takes both question attention and visual attention into consideration impressed by Co-Attention method, which is the best (or among the best) algorithm for now. Additionally, we use bi-directional LSTMs, which have a better capability to remain more information from the question and image, to replace the old unit so that we can capture information from both past and future sentences to be used. Then we rebuild the hierarchical architecture for not only question attention but also visual attention. What's more, we accelerate the algorithm via a new technic called Batch Normalization which helps the network converge more quickly than other algorithms. The experimental result shows that our model improves the state of the art on the large COCO-QA dataset, compared with other methods.
Tackett, Jennifer L; Slobodskaya, Helena R; Mar, Raymond A; Deal, James; Halverson, Charles F; Baker, Spencer R; Pavlopoulos, Vassilis; Besevegis, Elias
2012-08-01
Childhood personality is a rapidly growing area of investigation within individual differences research. One understudied topic is the universality of the hierarchical structure of childhood personality. In the present investigation, parents rated the personality characteristics of 3,751 children from 5 countries and 4 age groups. The hierarchical structure of childhood personality was examined for 1-, 2-, 3-, 4-, and 5-factor models across country (Canada, China, Greece, Russia, and the United States) and age group (3-5, 6-8, 9-11, and 12-14 years of age). Many similarities were noted across both country and age. The Five-Factor Model was salient beginning in early childhood (ages 3-5). Deviations across groups and from adult findings are noted, including the prominent role of antagonism in childhood personality and the high covariation between Conscientiousness and intellect. Future directions, including the need for more explicit attempts to merge temperament and personality models, are discussed. © 2011 The Authors. Journal of Personality © 2011, Wiley Periodicals, Inc.
ERIC Educational Resources Information Center
Raykov, Tenko
2011-01-01
Interval estimation of intraclass correlation coefficients in hierarchical designs is discussed within a latent variable modeling framework. A method accomplishing this aim is outlined, which is applicable in two-level studies where participants (or generally lower-order units) are clustered within higher-order units. The procedure can also be…
The sociology of health in the United States: recent theoretical contributions.
Cockerham, William C
2014-04-01
This paper examines recent trends in theory in health sociology in the United States and finds that the use of theory is flourishing. The central thesis is that the field has reached a mature state and is in the early stage of a paradigm shift away from a past focus on methodological individualism (in which the individual is the primary unit of analysis) toward a growing utilization of theories with a structural orientation This outcome is materially aided by research methods (e.g. hierarchal linear modeling, biomarkers) providing measures of structural effects on the health of the individual that were often absent or underdeveloped in the past. Structure needs to be accounted for in any social endeavor and contemporary medical sociology appears to be doing precisely that as part of the next stage of its evolution. The recent contributions to theory in the sociology of health discussed in this paper are fundamental cause, medicalization, social capital, neighborhood disadvantage, and health lifestyle theories.
2016-05-24
common feature of the depressive and anxiety disorders: a test of the revised integrative hierarchical model in a national sample. J Abnorm Psychol...proliferation of this unique form of warfare, concerns have been raised regarding the psychological impact such operations have on RPA operators directly...and clinical interviews utilizing the Clinician Administered Psychological Survey to determine the nature of the respondents’ stressful military
Song, Geoboo
2014-03-01
In the face of a growing public health concern accompanying the reemerging threat of preventable diseases, this research seeks mainly to explain variations in the perceived benefits and risks of vaccinations among the general public in the United States. As Mary Douglas and Aaron Wildavsky's grid-group cultural theory of risk perception claims, the analytical results based upon original data from a nationwide Internet survey of 1,213 American adults conducted in 2010 suggest that individuals' cultural predispositions contribute to the formation of their perceptions pertaining to vaccine benefits and risks at both societal and individual levels, in conjunction with other factors suggested by previous risk perception literature, such as perceived prevalence of diseases, trust, knowledge level, and demographic characteristics. Those with a strong hierarch orientation tend to envision greater benefits and lesser risks and conceive of a relatively high ratio of benefit to risk when compared to other cultural types. By contrast, those with a strong fatalist tendency are inclined to emphasize risks and downplay benefits while conceiving of a low vaccination benefit-risk ratio. Situated between hierarchs and fatalists, strong egalitarians are prone to perceive greater benefits, smaller risks, and a more positive benefit-risk ratio than strong individualists. © 2013 Society for Risk Analysis.
Krieg, Alexander; Ma, Li; Robinson, Patricia
2018-02-17
Impression management has important implications for success at work. This study explores differences in impression management in the East and West by examining the use of self-promotion, ingratiation, and exemplification directed towards three targets: supervisors, peers, and subordinates among 945 company employees from Japan, Korea, and the United States. Our results show that Korean employees used all three strategies most frequently, followed by United States, and then Japanese employees. Japanese and Korean employees used impression management strategies differentially across the three targets, and U.S. employees used impression management equally across targets. This elucidates how cultural trends in hierarchical relationships impact social behavior within the workplace. A follow-up mediation analysis found that relational or labor mobility fully mediated country differences in impression management, suggesting that culture is also reflected in larger social ecological trends in employee's ability and likelihood to change jobs, which also account for impression management strategy usage. Theoretical and practical implications for international business are discussed. This research may be useful in aligning strategies foreign employees might employ for using impression management when in Japan, Korea, and the United States.
O'Connor, R.J.; Jones, M.T.; White, D.; Hunsaker, C.; Loveland, Tom; Jones, Bruce; Preston, E.
1996-01-01
Classification and regression tree (CART) analysis was used to create hierarchically organized models of the distribution of bird species richness across the conterminous United States. Species richness data were taken from the Breeding Bird Survey and were related to climatic and land use data. We used a systematic spatial grid of approximately 12,500 hexagons, each approximately 640 square kilometres in area. Within each hexagon land use was characterized by the Loveland et al. land cover classification based on Advanced Very High Resolution Radiometer (AVHRR) data from NOAA polar orbiting meteorological satellites. These data were aggregated to yield fourteen land classes equivalent to an Anderson level II coverage; urban areas were added from the Digital Chart of the World. Each hexagon was characterized by climate data and landscape pattern metrics calculated from the land cover. A CART model then related the variation in species richness across the 1162 hexagons for which bird species richness data were available to the independent variables, yielding an R2-type goodness of fit metric of 47.5% deviance explained. The resulting model recognized eleven groups of hexagons, with species richness within each group determined by unique sequences of hierarchically constrained independent variables. Within the hierarchy, climate data accounted for more variability in the bird data, followed by land cover proportion, and then pattern metrics. The model was then used to predict species richness in all 12,500 hexagons of the conterminous United States yielding a map of the distribution of these eleven classes of bird species richness as determined by the environmental correlates. The potential for using this technique to interface biogeographic theory with the hierarchy theory of ecology is discussed. ?? 1996 Blackwell Science Ltd.
Brely, Lucas; Bosia, Federico; Pugno, Nicola M
2018-06-20
Contact unit size reduction is a widely studied mechanism as a means to improve adhesion in natural fibrillar systems, such as those observed in beetles or geckos. However, these animals also display complex structural features in the way the contact is subdivided in a hierarchical manner. Here, we study the influence of hierarchical fibrillar architectures on the load distribution over the contact elements of the adhesive system, and the corresponding delamination behaviour. We present an analytical model to derive the load distribution in a fibrillar system loaded in shear, including hierarchical splitting of contacts, i.e. a "hierarchical shear-lag" model that generalizes the well-known shear-lag model used in mechanics. The influence on the detachment process is investigated introducing a numerical procedure that allows the derivation of the maximum delamination force as a function of the considered geometry, including statistical variability of local adhesive energy. Our study suggests that contact splitting generates improved adhesion only in the ideal case of extremely compliant contacts. In real cases, to produce efficient adhesive performance, contact splitting needs to be coupled with hierarchical architectures to counterbalance high load concentrations resulting from contact unit size reduction, generating multiple delamination fronts and helping to avoid detrimental non-uniform load distributions. We show that these results can be summarized in a generalized adhesion scaling scheme for hierarchical structures, proving the beneficial effect of multiple hierarchical levels. The model can thus be used to predict the adhesive performance of hierarchical adhesive structures, as well as the mechanical behaviour of composite materials with hierarchical reinforcements.
Power laws, discontinuities and regional city size distributions
Garmestani, A.S.; Allen, Craig R.; Gallagher, C.M.
2008-01-01
Urban systems are manifestations of human adaptation to the natural environment. City size distributions are the expression of hierarchical processes acting upon urban systems. In this paper, we test the entire city size distributions for the southeastern and southwestern United States (1990), as well as the size classes in these regions for power law behavior. We interpret the differences in the size of the regional city size distributions as the manifestation of variable growth dynamics dependent upon city size. Size classes in the city size distributions are snapshots of stable states within urban systems in flux.
ERIC Educational Resources Information Center
Rocconi, Louis M.
2011-01-01
Hierarchical linear models (HLM) solve the problems associated with the unit of analysis problem such as misestimated standard errors, heterogeneity of regression and aggregation bias by modeling all levels of interest simultaneously. Hierarchical linear modeling resolves the problem of misestimated standard errors by incorporating a unique random…
Yamaguchi, Motonori; Logan, Gordon D
2016-12-01
Hierarchical control of skilled performance depends on the ability of higher level control to process several lower level units as a single chunk. The present study investigated the development of hierarchical control of skilled typewriting, focusing on the process of memory chunking. In the first 3 experiments, skilled typists typed words or nonwords under concurrent memory load. Memory chunks developed and consolidated into long-term memory when the same typing materials were repeated in 6 consecutive trials, but chunks did not develop when repetitions were spaced. However, when concurrent memory load was removed during training, memory chunks developed more efficiently with longer lags between repetitions than shorter lags. From these results, it is proposed that memory chunking requires 2 representations of the same letter string to be maintained simultaneously in short-term memory: 1 representation from the current trial, and the other from an earlier trial that is either retained from the immediately preceding trial or retrieved from long-term memory (i.e., study state retrieval). (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Raghavan, Ram K.; Goodin, Douglas G.; Neises, Daniel; Anderson, Gary A.; Ganta, Roman R.
2016-01-01
This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF) prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio–economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio–temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio–economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main–effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35°C) in the region, and the relevance of these factors in the context of climate–change impacts on tick–borne diseases are discussed. PMID:26942604
Raghavan, Ram K; Goodin, Douglas G; Neises, Daniel; Anderson, Gary A; Ganta, Roman R
2016-01-01
This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF) prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socio-economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio-temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio-economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main-effects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35°C) in the region, and the relevance of these factors in the context of climate-change impacts on tick-borne diseases are discussed.
NASA Astrophysics Data System (ADS)
Kasatkin, D. V.; Yanchuk, S.; Schöll, E.; Nekorkin, V. I.
2017-12-01
We report the phenomenon of self-organized emergence of hierarchical multilayered structures and chimera states in dynamical networks with adaptive couplings. This process is characterized by a sequential formation of subnetworks (layers) of densely coupled elements, the size of which is ordered in a hierarchical way, and which are weakly coupled between each other. We show that the hierarchical structure causes the decoupling of the subnetworks. Each layer can exhibit either a two-cluster state, a periodic traveling wave, or an incoherent state, and these states can coexist on different scales of subnetwork sizes.
ERIC Educational Resources Information Center
Yamaguchi, Motonori; Logan, Gordon D.
2016-01-01
Hierarchical control of skilled performance depends on the ability of higher level control to process several lower level units as a single chunk. The present study investigated the development of hierarchical control of skilled typewriting, focusing on the process of memory chunking. In the first 3 experiments, skilled typists typed words or…
Rigorous Free-Fermion Entanglement Renormalization from Wavelet Theory
NASA Astrophysics Data System (ADS)
Haegeman, Jutho; Swingle, Brian; Walter, Michael; Cotler, Jordan; Evenbly, Glen; Scholz, Volkher B.
2018-01-01
We construct entanglement renormalization schemes that provably approximate the ground states of noninteracting-fermion nearest-neighbor hopping Hamiltonians on the one-dimensional discrete line and the two-dimensional square lattice. These schemes give hierarchical quantum circuits that build up the states from unentangled degrees of freedom. The circuits are based on pairs of discrete wavelet transforms, which are approximately related by a "half-shift": translation by half a unit cell. The presence of the Fermi surface in the two-dimensional model requires a special kind of circuit architecture to properly capture the entanglement in the ground state. We show how the error in the approximation can be controlled without ever performing a variational optimization.
White Hughto, Jaclyn M; Murchison, Gabriel R; Clark, Kirsty; Pachankis, John E; Reisner, Sari L
2016-12-01
To identify geographic and individual-level factors associated with healthcare access among transgender people in the United States. Multilevel analyses were conducted to investigate lifetime healthcare refusal using national data from 5831 U.S. transgender adults. Hierarchical generalized linear models examined associations between individual (age, gender, race, income, insurance, and healthcare avoidance) and state-level factors (percent voting Republican, percent same-sex couple households, income inequality, and transgender protective laws) and lifetime refusal of care. Results show that individual-level factors (being older; trans feminine; Native American, multiracial, or other racial/ethnic minority; having low income; and avoiding care due to discrimination) are positively associated with care refusal (all P-values <0.05). Adjusting for individual-level factors, variation was observed across U.S. states, with a greater proportion of states in the Southern and Western United States with transgender residents at increased odds of experiencing care refusal, relative to other regions of the United States. When adjusting for state-level factors, the percentage of the state population voting Republican was positively associated with care refusal among the transgender adults sampled (P < 0.01). Transgender adults surveyed reported differential access to healthcare by geographic region. Identifying geographic and individual-level factors associated with healthcare barriers allows for the development of targeted educational and policy interventions to improve healthcare access for transgender people most in need of services.
A hierarchical-multiobjective framework for risk management
NASA Technical Reports Server (NTRS)
Haimes, Yacov Y.; Li, Duan
1991-01-01
A broad hierarchical-multiobjective framework is established and utilized to methodologically address the management of risk. United into the framework are the hierarchical character of decision-making, the multiple decision-makers at separate levels within the hierarchy, the multiobjective character of large-scale systems, the quantitative/empirical aspects, and the qualitative/normative/judgmental aspects. The methodological components essentially consist of hierarchical-multiobjective coordination, risk of extreme events, and impact analysis. Examples of applications of the framework are presented. It is concluded that complex and interrelated forces require an analysis of trade-offs between engineering analysis and societal preferences, as in the hierarchical-multiobjective framework, to successfully address inherent risk.
2011-10-01
Richiardi, J., Eryilmaz, H., Schwartz, S ., Vuilleumier, P., Van De Ville, D.,1499 2010. Decoding brain states from fmri connectivity graphs. Neuroimage1500...Differences Related to Sex and Kinship 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) 5d. PROJECT NUMBER 5e. TASK NUMBER...5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) University of Minnesota,Institute for Mathematics and Its Applications,207
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kuperman, R.G.
1995-12-31
Despite the expansion of environmental toxicology studies over the past decade, soil ecosystems have largely been ignored in ecotoxicological studies in the United States. The objective of this project was to develop and test the efficacy of a comprehensive methodology for assessing ecological impacts of soil contamination. A hierarchical approach that integrates biotic parameters and ecosystem processes was used to give insight into the mechanisms that lead to alterations in the structure and function of soil ecosystems in contaminated areas. This approach involved (1) a thorough survey of the soil biota to determine community structure, (2) laboratory and field testsmore » on critical ecosystem processes, (3) toxicity trials, and (4) the use of spatial analyses to provide input to the decision-making, process. This methodology appears to, offer an efficient and potentially cost-saving tool for remedial investigations of contaminated sites.« less
Woodward, Albert; Das, Abhik; Raskin, Ira E; Morgan-Lopez, Antonio A
2006-11-01
Data from the Alcohol and Drug Services Study (ADSS) are used to analyze the structure and operation of the substance abuse treatment industry in the United States. Published literature contains little systematic empirical analysis of the interaction between organizational characteristics and treatment outcomes. This paper addresses that deficit. It develops and tests a hierarchical linear model (HLM) to address questions about the empirical relationship between treatment inputs (industry costs, types and use of counseling and medical personnel, diagnosis mix, patient demographics, and the nature and level of services used in substance abuse treatment), and patient outcomes (retention and treatment completion rates). The paper adds to the literature by demonstrating a direct and statistically significant link between treatment completion and the organizational and staffing structure of the treatment setting. Related reimbursement issues, questions for future analysis, and limitations of the ADSS for this analysis are discussed.
Chimera states in networks of logistic maps with hierarchical connectivities
NASA Astrophysics Data System (ADS)
zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard
2018-04-01
Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.
Hierarchical Formation of Fibrillar and Lamellar Self-Assemblies from Guanosine-Based Motifs
Neviani, Paolo; Sarazin, Dominique; Schmutz, Marc; Blanck, Christian; Giuseppone, Nicolas; Spada, Gian Piero
2010-01-01
Here we investigate the supramolecular polymerizations of two lipophilic guanosine derivatives in chloroform by light scattering technique and TEM experiments. The obtained data reveal the presence of several levels of organization due to the hierarchical self-assembly of the guanosine units in ribbons that in turn aggregate in fibrillar or lamellar soft structures. The elucidation of these structures furnishes an explanation to the physical behaviour of guanosine units which display organogelator properties. PMID:20798860
Muths, Erin; Jung, Robin E.; Bailey, Larissa L.; Adams, Michael J.; Corn, P. Stephen; Dodd, C. Kenneth; Fellers, Gary M.; Sadinski, Walter J.; Schwalbe, Cecil R.; Walls, Susan C.; Fisher, Robert N.; Gallant, Alisa L.; Battaglin, William A.; Green, D. Earl
2005-01-01
Most research to assess amphibian declines has focused on local-scale projects on one or a few species. The Amphibian Research and Monitoring Initiative (ARMI) is a national program in the United States mandated by congressional directive and implemented by the U.S. Department of the Interior (specifically the U.S. Geological Survey, USGS). Program goals are to monitor changes in populations of amphibians across U.S. Department of the Interior lands and to address research questions related to amphibian declines using a hierarchical framework of base-, mid- and apex-level monitoring sites. ARMI is currently monitoring 83 amphibian species (29% of species in the U.S.) at mid- and apex-level areas. We chart the progress of this 5-year-old program and provide an example of mid-level monitoring from 1 of the 7 ARMI regions.
Glassy nature of hierarchical organizations.
Zamani, Maryam; Vicsek, Tamas
2017-05-03
The question of why and how animal and human groups form temporarily stable hierarchical organizations has long been a great challenge from the point of quantitative interpretations. The prevailing observation/consensus is that a hierarchical social or technological structure is optimal considering a variety of aspects. Here we introduce a simple quantitative interpretation of this situation using a statistical mechanics-type approach. We look for the optimum of the efficiency function [Formula: see text] with J ij denoting the nature of the interaction between the units i and j and a i standing for the ability of member i to contribute to the efficiency of the system. Notably, this expression for E eff has a similar structure to that of the energy as defined for spin-glasses. Unconventionally, we assume that J ij -s can have the values 0 (no interaction), +1 and -1; furthermore, a direction is associated with each edge. The essential and novel feature of our approach is that instead of optimizing the state of the nodes of a pre-defined network, we search for extrema for given a i -s in the complex efficiency landscape by finding locally optimal network topologies for a given number of edges of the subgraphs considered.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Hongwei; Cao, Ranran; Yu, Shixin
Single-layer catalysis sparks huge interests and gains widespread attention owing to its high activity. Simultaneously, three-dimensional (3D) hierarchical structure can afford large surface area and abundant reactive sites, contributing to high efficiency. Herein, we report an absorbing single-unit-cell layer established Bi2WO6 3D hierarchical architecture fabricated by a sodium dodecyl benzene sulfonate (SDBS)-assisted assembled strategy. The DBS- long chains can adsorb on the (Bi2O2)2+ layers and hence impede stacking of the layers, resulting in the single-unit-cell layer. We also uncovered that SDS with a shorter chain is less effective than SDBS. Due to the sufficient exposure of surface O atoms, single-unit-cellmore » layer 3D Bi2WO6 shows strong selectivity for adsorption on multiform organic dyes with different charges. Remarkably, the single-unit-cell layer 3D Bi2WO6 casts profoundly enhanced photodegradation activity and especially a superior photocatalytic H2 evolution rate, which is 14-fold increase in contrast to the bulk Bi2WO6. Systematic photoelectrochemical characterizations disclose that the substantially elevated carrier density and charge separation efficiency take responsibility for the strengthened photocatalytic performance. Additionally, the possibility of single-unit-cell layer 3D Bi2WO6 as dye-sensitized solar cells (DSSC) has also been attempted and it was manifested to be a promising dye-sensitized photoanode for oxygen evolution reaction (ORR). Our work not only furnish an insight into designing single-layer assembled 3D hierarchical architecture, but also offer a multi-functional material for environmental and energy applications.« less
HIV Trends in the United States: Diagnoses and Estimated Incidence
Song, Ruiguang; Tang, Tian; An, Qian; Prejean, Joseph; Dietz, Patricia; Hernandez, Angela L; Green, Timothy; Harris, Norma; McCray, Eugene; Mermin, Jonathan
2017-01-01
Background The best indicator of the impact of human immunodeficiency virus (HIV) prevention programs is the incidence of infection; however, HIV is a chronic infection and HIV diagnoses may include infections that occurred years before diagnosis. Alternative methods to estimate incidence use diagnoses, stage of disease, and laboratory assays of infection recency. Using a consistent, accurate method would allow for timely interpretation of HIV trends. Objective The objective of our study was to assess the recent progress toward reducing HIV infections in the United States overall and among selected population segments with available incidence estimation methods. Methods Data on cases of HIV infection reported to national surveillance for 2008-2013 were used to compare trends in HIV diagnoses, unadjusted and adjusted for reporting delay, and model-based incidence for the US population aged ≥13 years. Incidence was estimated using a biomarker for recency of infection (stratified extrapolation approach) and 2 back-calculation models (CD4 and Bayesian hierarchical models). HIV testing trends were determined from behavioral surveys for persons aged ≥18 years. Analyses were stratified by sex, race or ethnicity (black, Hispanic or Latino, and white), and transmission category (men who have sex with men, MSM). Results On average, HIV diagnoses decreased 4.0% per year from 48,309 in 2008 to 39,270 in 2013 (P<.001). Adjusting for reporting delays, diagnoses decreased 3.1% per year (P<.001). The CD4 model estimated an annual decrease in incidence of 4.6% (P<.001) and the Bayesian hierarchical model 2.6% (P<.001); the stratified extrapolation approach estimated a stable incidence. During these years, overall, the percentage of persons who ever had received an HIV test or had had a test within the past year remained stable; among MSM testing increased. For women, all 3 incidence models corroborated the decreasing trend in HIV diagnoses, and HIV diagnoses and 2 incidence models indicated decreases among blacks and whites. The CD4 and Bayesian hierarchical models, but not the stratified extrapolation approach, indicated decreases in incidence among MSM. Conclusions HIV diagnoses and CD4 and Bayesian hierarchical model estimates indicated decreases in HIV incidence overall, among both sexes and all race or ethnicity groups. Further progress depends on effectively reducing HIV incidence among MSM, among whom the majority of new infections occur. PMID:28159730
Murchison, Gabriel R.; Clark, Kirsty; Pachankis, John E.; Reisner, Sari L.
2016-01-01
Abstract Purpose: To identify geographic and individual-level factors associated with healthcare access among transgender people in the United States. Methods: Multilevel analyses were conducted to investigate lifetime healthcare refusal using national data from 5831 U.S. transgender adults. Hierarchical generalized linear models examined associations between individual (age, gender, race, income, insurance, and healthcare avoidance) and state-level factors (percent voting Republican, percent same-sex couple households, income inequality, and transgender protective laws) and lifetime refusal of care. Results: Results show that individual-level factors (being older; trans feminine; Native American, multiracial, or other racial/ethnic minority; having low income; and avoiding care due to discrimination) are positively associated with care refusal (all P-values <0.05). Adjusting for individual-level factors, variation was observed across U.S. states, with a greater proportion of states in the Southern and Western United States with transgender residents at increased odds of experiencing care refusal, relative to other regions of the United States. When adjusting for state-level factors, the percentage of the state population voting Republican was positively associated with care refusal among the transgender adults sampled (P < 0.01). Conclusion: Transgender adults surveyed reported differential access to healthcare by geographic region. Identifying geographic and individual-level factors associated with healthcare barriers allows for the development of targeted educational and policy interventions to improve healthcare access for transgender people most in need of services. PMID:27636030
2012-01-01
Background Evidence-based practices have not been routinely adopted in community mental health organizations despite the support of scientific evidence and in some cases even legislative or regulatory action. We examined the association of clinician attitudes toward evidence-based practice with organizational culture, climate, and other characteristics in a nationally representative sample of mental health organizations in the United States. Methods In-person, group-administered surveys were conducted with a sample of 1,112 mental health service providers in a nationwide sample of 100 mental health service institutions in 26 states in the United States. The study examines these associations with a two-level Hierarchical Linear Modeling (HLM) analysis of responses to the Evidence-Based Practice Attitude Scale (EBPAS) at the individual clinician level as a function of the Organizational Social Context (OSC) measure at the organizational level, controlling for other organization and clinician characteristics. Results We found that more proficient organizational cultures and more engaged and less stressful organizational climates were associated with positive clinician attitudes toward adopting evidence-based practice. Conclusions The findings suggest that organizational intervention strategies for improving the organizational social context of mental health services may contribute to the success of evidence-based practice dissemination and implementation efforts by influencing clinician attitudes. PMID:22726759
Level IV Ecoregions of the Conterminous United States
Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level III ecoregions. Methods used to define the ecoregions are explained in Omernik (
Control of discrete event systems modeled as hierarchical state machines
NASA Technical Reports Server (NTRS)
Brave, Y.; Heymann, M.
1991-01-01
The authors examine a class of discrete event systems (DESs) modeled as asynchronous hierarchical state machines (AHSMs). For this class of DESs, they provide an efficient method for testing reachability, which is an essential step in many control synthesis procedures. This method utilizes the asynchronous nature and hierarchical structure of AHSMs, thereby illustrating the advantage of the AHSM representation as compared with its equivalent (flat) state machine representation. An application of the method is presented where an online minimally restrictive solution is proposed for the problem of maintaining a controlled AHSM within prescribed legal bounds.
Application of a hierarchical structure stochastic learning automation
NASA Technical Reports Server (NTRS)
Neville, R. G.; Chrystall, M. S.; Mars, P.
1979-01-01
A hierarchical structure automaton was developed using a two state stochastic learning automato (SLA) in a time shared model. Application of the hierarchical SLA to systems with multidimensional, multimodal performance criteria is described. Results of experiments performed with the hierarchical SLA using a performance index with a superimposed noise component of ? or - delta distributed uniformly over the surface are discussed.
Aligning interprofessional education collaborative sub-competencies to a progression of learning.
Patel Gunaldo, Tina; Brisolara, Kari Fitzmorris; Davis, Alison H; Moore, Robert
2017-05-01
In the United States, the Interprofessional Education Collaborative (IPEC) developed four core competencies for interprofessional collaborative practice. Even though the IPEC competencies and respective sub-competencies were not created in a hierarchal manner, one might reflect upon a logical progression of learning as well as learners accruing skills allowing them to master one level of learning and building on the aggregate of skills before advancing to the next level. The Louisiana State University Health-New Orleans Center for Interprofessional Education and Collaborative Practice (CIPECP) determined the need to align the sub-competencies with the level of behavioural expectations in order to simplify the process of developing an interprofessional education experience targeted to specific learning levels. In order to determine the most effective alignment, CIPECP discussions revolved around current programmatic expectations across the institution. Faculty recognised the need to align sub-competencies with student learning objectives. Simultaneously, a progression of learning existing within each of the four IPEC domains was noted. Ultimately, the faculty and staff team agreed upon categorising the sub-competencies in a hierarchical manner for the four domains into either a "basic, intermediate, or advanced" level of competency.
HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.
Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B
2017-07-01
This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lai, Canhai; Xu, Zhijie; Pan, Wenxiao
2016-01-01
To quantify the predictive confidence of a solid sorbent-based carbon capture design, a hierarchical validation methodology—consisting of basic unit problems with increasing physical complexity coupled with filtered model-based geometric upscaling has been developed and implemented. This paper describes the computational fluid dynamics (CFD) multi-phase reactive flow simulations and the associated data flows among different unit problems performed within the said hierarchical validation approach. The bench-top experiments used in this calibration and validation effort were carefully designed to follow the desired simple-to-complex unit problem hierarchy, with corresponding data acquisition to support model parameters calibrations at each unit problem level. A Bayesianmore » calibration procedure is employed and the posterior model parameter distributions obtained at one unit-problem level are used as prior distributions for the same parameters in the next-tier simulations. Overall, the results have demonstrated that the multiphase reactive flow models within MFIX can be used to capture the bed pressure, temperature, CO2 capture capacity, and kinetics with quantitative accuracy. The CFD modeling methodology and associated uncertainty quantification techniques presented herein offer a solid framework for estimating the predictive confidence in the virtual scale up of a larger carbon capture device.« less
How misapplication of the hydrologic unit framework diminishes the meaning of watersheds
Omernik, James M.; Griffith, Glenn E.; Hughes, Robert M.; Glover, James B.; Weber, Marc H.
2017-01-01
Hydrologic units provide a convenient but problematic nationwide set of geographic polygons based on subjectively determined subdivisions of land surface areas at several hierarchical levels. The problem is that it is impossible to map watersheds, basins, or catchments of relatively equal size and cover the whole country. The hydrologic unit framework is in fact composed mostly of watersheds and pieces of watersheds. The pieces include units that drain to segments of streams, remnant areas, noncontributing areas, and coastal or frontal units that can include multiple watersheds draining to an ocean or large lake. Hence, half or more of the hydrologic units are not watersheds as the name of the framework “Watershed Boundary Dataset” implies. Nonetheless, hydrologic units and watersheds are commonly treated as synonymous, and this misapplication and misunderstanding can have some serious scientific and management consequences. We discuss some of the strengths and limitations of watersheds and hydrologic units as spatial frameworks. Using examples from the Northwest and Southeast United States, we explain how the misapplication of the hydrologic unit framework has altered the meaning of watersheds and can impair understanding associations between spatial geographic characteristics and surface water conditions.
Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems
2004-11-01
Systems Murat Yasar, Devendra Tolani, and Asok Ray The Pennsylvania State University, University Park, Pennsylvania Neerav Shah Glenn Research Center...Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems Murat Yasar, Devendra Tolani, and Asok Ray The Pennsylvania State University...Systems Murat Yasar, Devendra Tolani, and Asok Ray The Pennsylvania State University University Park, Pennsylvania 16802 Neerav Shah National
Hierarchical models of animal abundance and occurrence
Royle, J. Andrew; Dorazio, R.M.
2006-01-01
Much of animal ecology is devoted to studies of abundance and occurrence of species, based on surveys of spatially referenced sample units. These surveys frequently yield sparse counts that are contaminated by imperfect detection, making direct inference about abundance or occurrence based on observational data infeasible. This article describes a flexible hierarchical modeling framework for estimation and inference about animal abundance and occurrence from survey data that are subject to imperfect detection. Within this framework, we specify models of abundance and detectability of animals at the level of the local populations defined by the sample units. Information at the level of the local population is aggregated by specifying models that describe variation in abundance and detection among sites. We describe likelihood-based and Bayesian methods for estimation and inference under the resulting hierarchical model. We provide two examples of the application of hierarchical models to animal survey data, the first based on removal counts of stream fish and the second based on avian quadrat counts. For both examples, we provide a Bayesian analysis of the models using the software WinBUGS.
Chen, Tian; Mueller, Jochen; Shea, Kristina
2017-03-31
Multi-material 3D printing has created new opportunities for fabricating deployable structures. We design reversible, deployable structures that are fabricated flat, have defined load bearing capacity, and multiple, predictable activated geometries. These structures are designed with a hierarchical framework where the proposed bistable actuator serves as the base building block. The actuator is designed to maximise its stroke length, with the expansion ratio approaching one when serially connected. The activation force of the actuator is parameterised through its joint material and joint length. Simulation and experimental results show that the bistability triggering force can be tuned between 0.5 and 5.0 N. Incorporating this bistable actuator, the first group of hierarchical designs demonstrate the deployment of space frame structures with a tetrahedron module consisting of three active edges, each containing four serially connected actuators. The second group shows the design of flat structures that assume either positive or negative Gaussian curvature once activated. By flipping the initial configuration of the unit actuators, structures such as a dome and an enclosure are demonstrated. A modified Dynamic Relaxation method is used to simulate all possible geometries of the hierarchical structures. Measured geometries differ by less than 5% compared to simulation results.
Chen, Tian; Mueller, Jochen; Shea, Kristina
2017-01-01
Multi-material 3D printing has created new opportunities for fabricating deployable structures. We design reversible, deployable structures that are fabricated flat, have defined load bearing capacity, and multiple, predictable activated geometries. These structures are designed with a hierarchical framework where the proposed bistable actuator serves as the base building block. The actuator is designed to maximise its stroke length, with the expansion ratio approaching one when serially connected. The activation force of the actuator is parameterised through its joint material and joint length. Simulation and experimental results show that the bistability triggering force can be tuned between 0.5 and 5.0 N. Incorporating this bistable actuator, the first group of hierarchical designs demonstrate the deployment of space frame structures with a tetrahedron module consisting of three active edges, each containing four serially connected actuators. The second group shows the design of flat structures that assume either positive or negative Gaussian curvature once activated. By flipping the initial configuration of the unit actuators, structures such as a dome and an enclosure are demonstrated. A modified Dynamic Relaxation method is used to simulate all possible geometries of the hierarchical structures. Measured geometries differ by less than 5% compared to simulation results. PMID:28361891
Ecological units of the Northern Region: Subsections
John A. Nesser; Gary L. Ford; C. Lee Maynard; Debbie Dumroese
1997-01-01
Ecological units are described at the subsection level of the Forest Service National Hierarchical Framework of Ecological Units. A total of 91 subsections are delineated on the 1996 map "Ecological Units of the Northern Region: Subsections," based on physical and biological criteria. This document consists of descriptions of the climate, geomorphology,...
Hierarchical modeling of molecular energies using a deep neural network
NASA Astrophysics Data System (ADS)
Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton
2018-06-01
We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.
Directing folding pathways for multi-component DNA origami nanostructures with complex topology
NASA Astrophysics Data System (ADS)
Marras, A. E.; Zhou, L.; Kolliopoulos, V.; Su, H.-J.; Castro, C. E.
2016-05-01
Molecular self-assembly has become a well-established technique to design complex nanostructures and hierarchical mesoscale assemblies. The typical approach is to design binding complementarity into nucleotide or amino acid sequences to achieve the desired final geometry. However, with an increasing interest in dynamic nanodevices, the need to design structures with motion has necessitated the development of multi-component structures. While this has been achieved through hierarchical assembly of similar structural units, here we focus on the assembly of topologically complex structures, specifically with concentric components, where post-folding assembly is not feasible. We exploit the ability to direct folding pathways to program the sequence of assembly and present a novel approach of designing the strand topology of intermediate folding states to program the topology of the final structure, in this case a DNA origami slider structure that functions much like a piston-cylinder assembly in an engine. The ability to program the sequence and control orientation and topology of multi-component DNA origami nanostructures provides a foundation for a new class of structures with internal and external moving parts and complex scaffold topology. Furthermore, this work provides critical insight to guide the design of intermediate states along a DNA origami folding pathway and to further understand the details of DNA origami self-assembly to more broadly control folding states and landscapes.
A Hierarchical Framework for State-Space Matrix Inference and Clustering.
Zuo, Chandler; Chen, Kailei; Hewitt, Kyle J; Bresnick, Emery H; Keleş, Sündüz
2016-09-01
In recent years, a large number of genomic and epigenomic studies have been focusing on the integrative analysis of multiple experimental datasets measured over a large number of observational units. The objectives of such studies include not only inferring a hidden state of activity for each unit over individual experiments, but also detecting highly associated clusters of units based on their inferred states. Although there are a number of methods tailored for specific datasets, there is currently no state-of-the-art modeling framework for this general class of problems. In this paper, we develop the MBASIC ( M atrix B ased A nalysis for S tate-space I nference and C lustering) framework. MBASIC consists of two parts: state-space mapping and state-space clustering. In state-space mapping, it maps observations onto a finite state-space, representing the activation states of units across conditions. In state-space clustering, MBASIC incorporates a finite mixture model to cluster the units based on their inferred state-space profiles across all conditions. Both the state-space mapping and clustering can be simultaneously estimated through an Expectation-Maximization algorithm. MBASIC flexibly adapts to a large number of parametric distributions for the observed data, as well as the heterogeneity in replicate experiments. It allows for imposing structural assumptions on each cluster, and enables model selection using information criterion. In our data-driven simulation studies, MBASIC showed significant accuracy in recovering both the underlying state-space variables and clustering structures. We applied MBASIC to two genome research problems using large numbers of datasets from the ENCODE project. The first application grouped genes based on transcription factor occupancy profiles of their promoter regions in two different cell types. The second application focused on identifying groups of loci that are similar to a GATA2 binding site that is functional at its endogenous locus by utilizing transcription factor occupancy data and illustrated applicability of MBASIC in a wide variety of problems. In both studies, MBASIC showed higher levels of raw data fidelity than analyzing these data with a two-step approach using ENCODE results on transcription factor occupancy data.
Level III Ecoregions of Kentucky
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Michigan
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Arkansas
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Mississippi
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Connecticut
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Georgia
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Colorado
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Wisconsin
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Oregon
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Arkansas
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Florida
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Nevada
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Virginia
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Illinois
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Virginia
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Delaware
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Wyoming
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Alabama
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Alabama
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Nebraska
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Delaware
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Kansas
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Louisiana
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Michigan
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Arizona
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Georgia
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Montana
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Nebraska
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Vermont
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Wisconsin
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Tennessee
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Colorado
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Oklahoma
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Maryland
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Wyoming
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Connecticut
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Missouri
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Washington
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Minnesota
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Massachusetts
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Tennessee
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Washington
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Maryland
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Mississippi
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Vermont
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Kentucky
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Illinois
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Indiana
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Louisiana
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Oklahoma
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Massachusetts
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Montana
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of California
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Pennsylvania
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Florida
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of California
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of Minnesota
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Arizona
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Pennsylvania
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Indiana
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of Missouri
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
A hierarchical transition state search algorithm
NASA Astrophysics Data System (ADS)
del Campo, Jorge M.; Köster, Andreas M.
2008-07-01
A hierarchical transition state search algorithm is developed and its implementation in the density functional theory program deMon2k is described. This search algorithm combines the double ended saddle interpolation method with local uphill trust region optimization. A new formalism for the incorporation of the distance constrain in the saddle interpolation method is derived. The similarities between the constrained optimizations in the local trust region method and the saddle interpolation are highlighted. The saddle interpolation and local uphill trust region optimizations are validated on a test set of 28 representative reactions. The hierarchical transition state search algorithm is applied to an intramolecular Diels-Alder reaction with several internal rotors, which makes automatic transition state search rather challenging. The obtained reaction mechanism is discussed in the context of the experimentally observed product distribution.
Medalla, Felicita; Gu, Weidong; Mahon, Barbara E; Judd, Michael; Folster, Jason; Griffin, Patricia M; Hoekstra, Robert M
2016-01-01
Salmonella infections are a major cause of illness in the United States. The antimicrobial agents used to treat severe infections include ceftriaxone, ciprofloxacin, and ampicillin. Antimicrobial drug resistance has been associated with adverse clinical outcomes. To estimate the incidence of resistant culture-confirmed nontyphoidal Salmonella infections, we used Bayesian hierarchical models of 2004-2012 data from the Centers for Disease Control and Prevention National Antimicrobial Resistance Monitoring System and Laboratory-based Enteric Disease Surveillance. We based 3 mutually exclusive resistance categories on susceptibility testing: ceftriaxone and ampicillin resistant, ciprofloxacin nonsusceptible but ceftriaxone susceptible, and ampicillin resistant but ceftriaxone and ciprofloxacin susceptible. We estimated the overall incidence of resistant infections as 1.07/100,000 person-years for ampicillin-only resistance, 0.51/100,000 person-years for ceftriaxone and ampicillin resistance, and 0.35/100,000 person-years for ciprofloxacin nonsusceptibility, or ≈6,200 resistant culture-confirmed infections annually. These national estimates help define the magnitude of the resistance problem so that control measures can be appropriately targeted.
Building the United States National Vegetation Classification
Franklin, S.B.; Faber-Langendoen, D.; Jennings, M.; Keeler-Wolf, T.; Loucks, O.; Peet, R.; Roberts, D.; McKerrow, A.
2012-01-01
The Federal Geographic Data Committee (FGDC) Vegetation Subcommittee, the Ecological Society of America Panel on Vegetation Classification, and NatureServe have worked together to develop the United States National Vegetation Classification (USNVC). The current standard was accepted in 2008 and fosters consistency across Federal agencies and non-federal partners for the description of each vegetation concept and its hierarchical classification. The USNVC is structured as a dynamic standard, where changes to types at any level may be proposed at any time as new information comes in. But, because much information already exists from previous work, the NVC partners first established methods for screening existing types to determine their acceptability with respect to the 2008 standard. Current efforts include a screening process to assign confidence to Association and Group level descriptions, and a review of the upper three levels of the classification. For the upper levels especially, the expectation is that the review process includes international scientists. Immediate future efforts include the review of remaining levels and the development of a proposal review process.
Choi, Sunha H
2012-04-01
This study tested a healthy immigrant effect (HIE) and postimmigration health status changes among late life immigrants. Using three waves of the Second Longitudinal Study of Aging (1994-2000) and the linked mortality file through 2006, this study compared (a) chronic health conditions, (b) longitudinal trajectories of self-rated health, (c) longitudinal trajectories of functional impairments, and (d) mortality between three groups (age 70+): (i) late life immigrants with less than 15 years in the United States (n = 133), (ii) longer term immigrants (n = 672), and (iii) U.S.-born individuals (n = 8,642). Logistic and Poisson regression, hierarchical generalized linear modeling, and survival analyses were conducted. Late life immigrants were less likely to suffer from cancer, had lower numbers of chronic conditions at baseline, and displayed lower hazards of mortality during the 12-year follow-up. However, their self-rated health and functional status were worse than those of their counterparts over time. A HIE was only partially supported among older adults.
Physical Activity Levels and Well-Being in Older Adults.
Bae, Wonyul; Ik Suh, Young; Ryu, Jungsu; Heo, Jinmoo
2017-04-01
The objective of this study was to identify the interconnectedness of different intensity levels of physical activity and psychological (life satisfaction and positive affect) and physical (physical health) well-being. Participants were from the National Study of Midlife in the United States with assessments in 2004 and aged 25 to 74 living in the United States were included in the analyses. We conducted bivariate correlations to examine significant relationships among the study variables. In addition, after multicollinearity among the independent variable was checked, a series of hierarchical regression analyses with physical health, positive affect, and life satisfaction as criterion variables were conducted. The results showed that light physical activities were positively associated with physical health and life satisfaction in summer, whereas light physical activities and all dependent variables were positively correlated in winter. Furthermore, engaging in moderate physical activities was positively related only with physical health. Meanwhile, vigorous physical activities were not associated with life satisfaction, physical health, and positive affect in summer and winter.
Leadership styles across hierarchical levels in nursing departments.
Stordeur, S; Vandenberghe, C; D'hoore, W
2000-01-01
Some researchers have reported on the cascading effect of transformational leadership across hierarchical levels. One study examined this effect in nursing, but it was limited to a single hospital. To examine the cascading effect of leadership styles across hierarchical levels in a sample of nursing departments and to investigate the effect of hierarchical level on the relationships between leadership styles and various work outcomes. Based on a sample of eight hospitals, the cascading effect was tested using correlation analysis. The main sources of variation among leadership scores were determined with analyses of variance (ANOVA), and the interaction effect of hierarchical level and leadership styles on criterion variables was tested with moderated regression analysis. No support was found for a cascading effect of leadership across hierarchical levels. Rather, the variation of leadership scores was explained primarily by the organizational context. Transformational leadership had a stronger impact on criterion variables than transactional leadership. Interaction effects between leadership styles and hierarchical level were observed only for perceived unit effectiveness. The hospital's structure and culture are major determinants of leadership styles.
HIV Trends in the United States: Diagnoses and Estimated Incidence.
Hall, H Irene; Song, Ruiguang; Tang, Tian; An, Qian; Prejean, Joseph; Dietz, Patricia; Hernandez, Angela L; Green, Timothy; Harris, Norma; McCray, Eugene; Mermin, Jonathan
2017-02-03
The best indicator of the impact of human immunodeficiency virus (HIV) prevention programs is the incidence of infection; however, HIV is a chronic infection and HIV diagnoses may include infections that occurred years before diagnosis. Alternative methods to estimate incidence use diagnoses, stage of disease, and laboratory assays of infection recency. Using a consistent, accurate method would allow for timely interpretation of HIV trends. The objective of our study was to assess the recent progress toward reducing HIV infections in the United States overall and among selected population segments with available incidence estimation methods. Data on cases of HIV infection reported to national surveillance for 2008-2013 were used to compare trends in HIV diagnoses, unadjusted and adjusted for reporting delay, and model-based incidence for the US population aged ≥13 years. Incidence was estimated using a biomarker for recency of infection (stratified extrapolation approach) and 2 back-calculation models (CD4 and Bayesian hierarchical models). HIV testing trends were determined from behavioral surveys for persons aged ≥18 years. Analyses were stratified by sex, race or ethnicity (black, Hispanic or Latino, and white), and transmission category (men who have sex with men, MSM). On average, HIV diagnoses decreased 4.0% per year from 48,309 in 2008 to 39,270 in 2013 (P<.001). Adjusting for reporting delays, diagnoses decreased 3.1% per year (P<.001). The CD4 model estimated an annual decrease in incidence of 4.6% (P<.001) and the Bayesian hierarchical model 2.6% (P<.001); the stratified extrapolation approach estimated a stable incidence. During these years, overall, the percentage of persons who ever had received an HIV test or had had a test within the past year remained stable; among MSM testing increased. For women, all 3 incidence models corroborated the decreasing trend in HIV diagnoses, and HIV diagnoses and 2 incidence models indicated decreases among blacks and whites. The CD4 and Bayesian hierarchical models, but not the stratified extrapolation approach, indicated decreases in incidence among MSM. HIV diagnoses and CD4 and Bayesian hierarchical model estimates indicated decreases in HIV incidence overall, among both sexes and all race or ethnicity groups. Further progress depends on effectively reducing HIV incidence among MSM, among whom the majority of new infections occur. ©H Irene Hall, Ruiguang Song, Tian Tang, Qian An, Joseph Prejean, Patricia Dietz, Angela L Hernandez, Timothy Green, Norma Harris, Eugene McCray, Jonathan Mermin. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 03.02.2017.
Impact of work pressure, work stress and work-family conflict on firefighter burnout.
Smith, Todd D; DeJoy, David M; Dyal, Mari-Amanda Aimee; Huang, Gaojian
2017-10-25
Little research has explored burnout and its causes in the American fire service. Data were collected from career firefighters in the southeastern United States (n = 208) to explore these relationships. A hierarchical regression model was tested to examine predictors of burnout including sociodemographic characteristics (model 1), work pressure (model 2), work stress and work-family conflict (model 3) and interaction terms (model 4). The main findings suggest that perceived work stress and work-family conflict emerged as the significant predictors of burnout (both p < .001). Interventions and programs aimed at these predictors could potentially curtail burnout among firefighters.
The Normative Environment for Drug Use: Comparisons among American Indian and White Adolescents
Dieterich, Sara E.; Swaim, Randall C.; Beauvais, Fred
2013-01-01
The present study examined the influence of descriptive norms, injunctive norms, perceived outcome expectancies, and ethnicity on marijuana and inhalant use among 2334 American Indian and white high school students who lived on or near reservations in the United States. Hierarchical multiple regression analyses were conducted with survey data collected during the 2009-2010 and 2010-2011 school years. Results suggest differences between ethnicities in the influence of the normative environment and outcome expectancies on both marijuana and inhalant use. Study limitations are noted, and future research is suggested. PMID:23768429
ENEL power generation and transmission control (PGTC) system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Galli, F.; Schiavi
1986-08-01
The ENEL (Italian State Power Board) PGTC System has a multi-level architecture which consists of a National Control Center (NCC), eight Area Control Centers (ACC), and Remote Terminal Units (RTU). Remote Control Centers (RCC), representing the third hierarchical level of the control system, will be integrated into the system beginning in 1987. This paper describes the structure of the PGTC system from the remote stations up to the NCC and the main control functions. The method of implementation, the organizational and managerial problems that were faced in the development of the project are also described.
NASA Astrophysics Data System (ADS)
Hoffmann, Leif Soren Birger Per Ove Holm
In my dissertation I argue that because the European Union and the United States of America have been largely treated as unique or at least special cases, both the literature on American-state building and that on European market integration have missed how close comparison alters both our descriptive views and social-scientific explanations of the shape of each polity. In particular, scholars have not sufficiently recognized that the European Union has gone further than the United States in many elements of the creation of a centralized, liberalized single market, nor have they produced explanations that account well for this development. This study challenges the dominant assumption that the United States is generally more hierarchical and centralized than the European Union and more of a single free market in the sense of fewer allowable trade barriers. By analyzing the rules of market integration in services (over 70% of GDP), public procurement (15 -- 20% GDP) and the regulated goods markets (goods like elevators with their own regulatory regimes), I demonstrate that in all these major cases the European Union has adopted rules that open exchange to competition more than the United States. While the actual integration of flows on the ground is still generally less across European states than American ones, the political rules are more - and more liberally - integrated in Europe. I offer an institutional and ideational argument to explain these differences, with two main parts. First, there is no American parallel to the institution of the European Commission, which is mandated to continually push liberalization forward. My research shows that Commission leadership has been critical to each of the examined cases. Second, broader norms of legitimate governance favor centralized authority - including liberalizing central authority - more in the European Union than in the United States. Despite all the criticism we hear of the European Union, the basic notion of federal governance of market integration is far more strongly accepted across Europe at both elite and mass levels than in the United States. As interview evidence in this study displays, many Americans consistently object to any role for the federal government.
ERIC Educational Resources Information Center
Nimon, Kim
2012-01-01
Using state achievement data that are openly accessible, this paper demonstrates the application of hierarchical linear modeling within the context of career technical education research. Three prominent approaches to analyzing clustered data (i.e., modeling aggregated data, modeling disaggregated data, modeling hierarchical data) are discussed…
Li, Xiao-Yun; Chen, Li-Hua; Rooke, Joanna Claire; Deng, Zhao; Hu, Zhi-Yi; Wang, Shao-Zhuan; Wang, Li; Li, Yu; Krief, Alain; Su, Bao-Lian
2013-03-15
Mesoporous TiO(2) with a hierarchically 3D dendrimeric nanostructure comprised of nanoribbon building units has been synthesized via a spontaneous self-formation process from various titanium alkoxides. These hierarchically 3D dendrimeric architectures can be obtained by a very facile, template-free method, by simply dropping a titanium butoxide precursor into methanol solution. The novel configuration of the mesoporous TiO(2) nanostructure in nanoribbon building units yields a high surface area. The calcined samples show significantly enhanced photocatalytic activity and degradation rates owing to the mesoporosity and their improved crystallinity after calcination. Furthermore, the 3D dendrimeric architectures can be preserved after phase transformation from amorphous TiO(2) to anatase or rutile, which occurs during calcination. In addition, the spontaneous self-formation process of mesoporous TiO(2) with hierarchically 3D dendrimeric architectures from the hydrolysis and condensation reaction of titanium butoxide in methanol has been followed by in situ optical microscopy (OM), revealing the secret on the formation of hierarchically 3D dendrimeric nanostructures. Moreover, mesoporous TiO(2) nanostructures with similar hierarchically 3D dendrimeric architectures can also be obtained using other titanium alkoxides. The porosities and nanostructures of the resultant products were characterized by SEM, TEM, XRD, and N(2) adsorption-desorption measurements. The present work provides a facile and reproducible method for the synthesis of novel mesoporous TiO(2) nanoarchitectures, which in turn could herald the fabrication of more efficient photocatalysts. Copyright © 2012 Elsevier Inc. All rights reserved.
A management-oriented classification of pinyon-juniper woodlands of the Great Basin
Neil E. West; Robin J. Tausch; Paul T. Tueller
1998-01-01
A hierarchical framework for the classification of Great Basin pinyon-juniper woodlands was based on a systematic sample of 426 stands from a random selection of 66 of the 110 mountain ranges in the region. That is, mountain ranges were randomly selected, but stands were systematically located on mountain ranges. The National Hierarchical Framework of Ecological Units...
How Misapplication of the Hydrologic Unit Framework Diminishes the Meaning of Watersheds
Hydrologic units provide a convenient nationwide set of geographic polygons based on an arbitrary subdivision of the drainage of land surface areas at several hierarchical levels. Half or more of these units, however, are not true watersheds as the official name of the framework,...
On the origin of biological construction, with a focus on multicellularity.
van Gestel, Jordi; Tarnita, Corina E
2017-10-17
Biology is marked by a hierarchical organization: all life consists of cells; in some cases, these cells assemble into groups, such as endosymbionts or multicellular organisms; in turn, multicellular organisms sometimes assemble into yet other groups, such as primate societies or ant colonies. The construction of new organizational layers results from hierarchical evolutionary transitions, in which biological units (e.g., cells) form groups that evolve into new units of biological organization (e.g., multicellular organisms). Despite considerable advances, there is no bottom-up, dynamical account of how, starting from the solitary ancestor, the first groups originate and subsequently evolve the organizing principles that qualify them as new units. Guided by six central questions, we propose an integrative bottom-up approach for studying the dynamics underlying hierarchical evolutionary transitions, which builds on and synthesizes existing knowledge. This approach highlights the crucial role of the ecology and development of the solitary ancestor in the emergence and subsequent evolution of groups, and it stresses the paramount importance of the life cycle: only by evaluating groups in the context of their life cycle can we unravel the evolutionary trajectory of hierarchical transitions. These insights also provide a starting point for understanding the types of subsequent organizational complexity. The central research questions outlined here naturally link existing research programs on biological construction (e.g., on cooperation, multilevel selection, self-organization, and development) and thereby help integrate knowledge stemming from diverse fields of biology.
Organization of excitable dynamics in hierarchical biological networks.
Müller-Linow, Mark; Hilgetag, Claus C; Hütt, Marc-Thorsten
2008-09-26
This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks. Representatives of different types of hierarchical networks as well as two biological neural networks are explored with a three-state model of node activation for systematically varying levels of random background network stimulation. The results demonstrate that two principal topological aspects of hierarchical networks, node centrality and network modularity, correlate with the network activity patterns at different levels of spontaneous network activation. The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal network of Caenorhabditis elegans is strongly influenced by hub nodes. These findings indicate the interaction of multiple topological features and dynamic states in the function of complex biological networks.
Wang, Xianfu; Liu, Bin; Wang, Qiufan; Song, Weifeng; Hou, Xiaojuan; Chen, Di; Cheng, Yi-bing; Shen, Guozhen
2013-03-13
Highly flexible stacked and in-plane all-solid-state supercapacitors are fabricated on 3D hierarchical GeSe2 nanostructures with high performance, and, when configured as a self-powered photodetector nanosystem, can be used to power CdSe nanowire photodetectors. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Matthews, Luke J.; Tehrani, Jamie J.; Jordan, Fiona M.; Collard, Mark; Nunn, Charles L.
2011-01-01
Background Archaeologists and anthropologists have long recognized that different cultural complexes may have distinct descent histories, but they have lacked analytical techniques capable of easily identifying such incongruence. Here, we show how Bayesian phylogenetic analysis can be used to identify incongruent cultural histories. We employ the approach to investigate Iranian tribal textile traditions. Methods We used Bayes factor comparisons in a phylogenetic framework to test two models of cultural evolution: the hierarchically integrated system hypothesis and the multiple coherent units hypothesis. In the hierarchically integrated system hypothesis, a core tradition of characters evolves through descent with modification and characters peripheral to the core are exchanged among contemporaneous populations. In the multiple coherent units hypothesis, a core tradition does not exist. Rather, there are several cultural units consisting of sets of characters that have different histories of descent. Results For the Iranian textiles, the Bayesian phylogenetic analyses supported the multiple coherent units hypothesis over the hierarchically integrated system hypothesis. Our analyses suggest that pile-weave designs represent a distinct cultural unit that has a different phylogenetic history compared to other textile characters. Conclusions The results from the Iranian textiles are consistent with the available ethnographic evidence, which suggests that the commercial rug market has influenced pile-rug designs but not the techniques or designs incorporated in the other textiles produced by the tribes. We anticipate that Bayesian phylogenetic tests for inferring cultural units will be of great value for researchers interested in studying the evolution of cultural traits including language, behavior, and material culture. PMID:21559083
Perception of hierarchical boundaries in music and its modulation by expertise.
Zhang, Jingjing; Jiang, Cunmei; Zhou, Linshu; Yang, Yufang
2016-10-01
Hierarchical structure with units of different timescales is a key feature of music. For the perception of such structures, the detection of each boundary is crucial. Here, using electroencephalography (EEG), we explore the perception of hierarchical boundaries in music, and test whether musical expertise modifies such processing. Musicians and non-musicians were presented with musical excerpts containing boundaries at three hierarchical levels, including section, phrase and period boundaries. Non-boundary was chosen as a baseline condition. Recordings from musicians showed CPS (closure positive shift) was evoked at all the three boundaries, and their amplitude increased as the hierarchical level became higher, which suggest that musicians could represent music events at different timescales in a hierarchical way. For non-musicians, the CPS was only elicited at the period boundary and undistinguishable negativities were induced at all the three boundaries. The results indicate that a different and less clear way was used by non-musicians in boundary perception. Our findings reveal, for the first time, an ERP correlate of perceiving hierarchical boundaries in music, and show that the phrasing ability could be enhanced by musical expertise. Copyright © 2016 Elsevier Ltd. All rights reserved.
Jiao, Y.; Lapointe, N.W.R.; Angermeier, P.L.; Murphy, B.R.
2009-01-01
Models of species' demographic features are commonly used to understand population dynamics and inform management tactics. Hierarchical demographic models are ideal for the assessment of non-indigenous species because our knowledge of non-indigenous populations is usually limited, data on demographic traits often come from a species' native range, these traits vary among populations, and traits are likely to vary considerably over time as species adapt to new environments. Hierarchical models readily incorporate this spatiotemporal variation in species' demographic traits by representing demographic parameters as multi-level hierarchies. As is done for traditional non-hierarchical matrix models, sensitivity and elasticity analyses are used to evaluate the contributions of different life stages and parameters to estimates of population growth rate. We applied a hierarchical model to northern snakehead (Channa argus), a fish currently invading the eastern United States. We used a Monte Carlo approach to simulate uncertainties in the sensitivity and elasticity analyses and to project future population persistence under selected management tactics. We gathered key biological information on northern snakehead natural mortality, maturity and recruitment in its native Asian environment. We compared the model performance with and without hierarchy of parameters. Our results suggest that ignoring the hierarchy of parameters in demographic models may result in poor estimates of population size and growth and may lead to erroneous management advice. In our case, the hierarchy used multi-level distributions to simulate the heterogeneity of demographic parameters across different locations or situations. The probability that the northern snakehead population will increase and harm the native fauna is considerable. Our elasticity and prognostic analyses showed that intensive control efforts immediately prior to spawning and/or juvenile-dispersal periods would be more effective (and probably require less effort) than year-round control efforts. Our study demonstrates the importance of considering the hierarchy of parameters in estimating population growth rate and evaluating different management strategies for non-indigenous invasive species. ?? 2009 Elsevier B.V.
An Adaptive Complex Network Model for Brain Functional Networks
Gomez Portillo, Ignacio J.; Gleiser, Pablo M.
2009-01-01
Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902
Antibiotic resistance shaping multi-level population biology of bacteria
Baquero, Fernando; Tedim, Ana P.; Coque, Teresa M.
2013-01-01
Antibiotics have natural functions, mostly involving cell-to-cell signaling networks. The anthropogenic production of antibiotics, and its release in the microbiosphere results in a disturbance of these networks, antibiotic resistance tending to preserve its integrity. The cost of such adaptation is the emergence and dissemination of antibiotic resistance genes, and of all genetic and cellular vehicles in which these genes are located. Selection of the combinations of the different evolutionary units (genes, integrons, transposons, plasmids, cells, communities and microbiomes, hosts) is highly asymmetrical. Each unit of selection is a self-interested entity, exploiting the higher hierarchical unit for its own benefit, but in doing so the higher hierarchical unit might acquire critical traits for its spread because of the exploitation of the lower hierarchical unit. This interactive trade-off shapes the population biology of antibiotic resistance, a composed-complex array of the independent “population biologies.” Antibiotics modify the abundance and the interactive field of each of these units. Antibiotics increase the number and evolvability of “clinical” antibiotic resistance genes, but probably also many other genes with different primary functions but with a resistance phenotype present in the environmental resistome. Antibiotics influence the abundance, modularity, and spread of integrons, transposons, and plasmids, mostly acting on structures present before the antibiotic era. Antibiotics enrich particular bacterial lineages and clones and contribute to local clonalization processes. Antibiotics amplify particular genetic exchange communities sharing antibiotic resistance genes and platforms within microbiomes. In particular human or animal hosts, the microbiomic composition might facilitate the interactions between evolutionary units involved in antibiotic resistance. The understanding of antibiotic resistance implies expanding our knowledge on multi-level population biology of bacteria. PMID:23508522
Antibiotic resistance shaping multi-level population biology of bacteria.
Baquero, Fernando; Tedim, Ana P; Coque, Teresa M
2013-01-01
Antibiotics have natural functions, mostly involving cell-to-cell signaling networks. The anthropogenic production of antibiotics, and its release in the microbiosphere results in a disturbance of these networks, antibiotic resistance tending to preserve its integrity. The cost of such adaptation is the emergence and dissemination of antibiotic resistance genes, and of all genetic and cellular vehicles in which these genes are located. Selection of the combinations of the different evolutionary units (genes, integrons, transposons, plasmids, cells, communities and microbiomes, hosts) is highly asymmetrical. Each unit of selection is a self-interested entity, exploiting the higher hierarchical unit for its own benefit, but in doing so the higher hierarchical unit might acquire critical traits for its spread because of the exploitation of the lower hierarchical unit. This interactive trade-off shapes the population biology of antibiotic resistance, a composed-complex array of the independent "population biologies." Antibiotics modify the abundance and the interactive field of each of these units. Antibiotics increase the number and evolvability of "clinical" antibiotic resistance genes, but probably also many other genes with different primary functions but with a resistance phenotype present in the environmental resistome. Antibiotics influence the abundance, modularity, and spread of integrons, transposons, and plasmids, mostly acting on structures present before the antibiotic era. Antibiotics enrich particular bacterial lineages and clones and contribute to local clonalization processes. Antibiotics amplify particular genetic exchange communities sharing antibiotic resistance genes and platforms within microbiomes. In particular human or animal hosts, the microbiomic composition might facilitate the interactions between evolutionary units involved in antibiotic resistance. The understanding of antibiotic resistance implies expanding our knowledge on multi-level population biology of bacteria.
Liu, Bin; Tan, Dongsheng; Wang, Xianfu; Chen, Di; Shen, Guozhen
2013-06-10
Flexible and highly efficient energy storage units act as one of the key components in portable electronics. In this work, by planar-integrated assembly of hierarchical ZnCo₂O₄ nanowire arrays/carbon fibers electrodes, a new class of flexible all-solid-state planar-integrated fiber supercapacitors are designed and produced via a low-cost and facile method. The as-fabricated flexible devices exhibit high-efficiency, enhanced capacity, long cycle life, and excellent electrical stability. An enhanced distributed-capacitance effect is experimentally observed for the device. This strategy enables highly flexible new structured supercapacitors with maximum functionality and minimized size, thus making it possible to be readily applied in flexible/portable photoelectronic devices. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Tao, Jiayou; Liu, Nishuang; Li, Luying; Su, Jun; Gao, Yihua
2014-03-07
A solid-state high performance flexible asymmetric supercapacitor (ASC) was fabricated. Its anode is based on organic-inorganic materials, where polypyrrole (PPy) is uniformly wrapped on MnO2 nanoflowers grown on carbon cloth (CC), and its cathode is made of activated carbon (AC) on CC. The ASC has an areal capacitance of 1.41 F cm(-2) and an energy density of 0.63 mW h cm(-2) at a power density of 0.9 mW cm(-2). An energy storage unit fabricated using multiple ASCs can drive a light-emitting diode (LED) segment display, a mini motor and even a toy car after full charging. The high-performance ASCs have significant potential applications in flexible electronics and electrical vehicles.
Heo, Jinmoo; Lee, Youngkhill; Pedersen, Paul M; McCormick, Bryan P
2010-09-01
This study examined how serious leisure, individual differences, social context, and location contribute to older adults' experiences of flow - an intense psychological state - in their daily lives. The Experience Sampling Method was used with 19 older adults in a Midwestern city in the United States. Experience of flow was the outcome measure, and the data were analyzed using hierarchical linear modeling. Results indicated that location and employment status influenced the subjects' flow experience. Furthermore, the findings revealed that retirement was negatively related to experiencing flow, and there was a significant association between home and the flow experience. The results of this study enhance the understanding of flow experiences in the everyday lives of older adults.
Synchrony, Waves, and Spatial Hierarchies in the Spread of Influenza
NASA Astrophysics Data System (ADS)
Viboud, Cécile; Bjørnstad, Ottar N.; Smith, David L.; Simonsen, Lone; Miller, Mark A.; Grenfell, Bryan T.
2006-04-01
Quantifying long-range dissemination of infectious diseases is a key issue in their dynamics and control. Here, we use influenza-related mortality data to analyze the between-state progression of interpandemic influenza in the United States over the past 30 years. Outbreaks show hierarchical spatial spread evidenced by higher pairwise synchrony between more populous states. Seasons with higher influenza mortality are associated with higher disease transmission and more rapid spread than are mild ones. The regional spread of infection correlates more closely with rates of movement of people to and from their workplaces (workflows) than with geographical distance. Workflows are described in turn by a gravity model, with a rapid decay of commuting up to around 100 km and a long tail of rare longer range flow. A simple epidemiological model, based on the gravity formulation, captures the observed increase of influenza spatial synchrony with transmissibility; high transmission allows influenza to spread rapidly beyond local spatial constraints.
Menachemi, Nir; Yeager, Valerie A; Duncan, W Jack; Katholi, Charles R; Ginter, Peter M
2012-01-01
State public health preparedness units (SPHPUs) were developed in response to federal funding to improve response to disasters: a responsibility that had not traditionally been within the purview of public health. The SPHPUs were created within the existing public health organizational structure, and their placement may have implications for how the unit functions, how communication takes place, and ultimately how well the key responsibilities are performed. This study empirically identifies a taxonomy of similarly structured SPHPUs and examines whether this structure is associated with state geographic, demographic, and threat-vulnerability characteristics. Data representing each SPHPU were extracted from publically available sources, including organizational charts and emergency preparedness plans for 2009. A cross-sectional segmentation analysis was conducted of variables representing structural attributes. Fifty state public health departments. Variables representing "span of control" and "hierarchal levels" were extracted from organizational charts. Structural "complexity" and "centralization" were extracted from state emergency preparedness documents and other secondary sources. On average, 6.6 people report to the same manager as the SPHPU director; 2.1 levels separate the SPHPU director from the state health officer; and a mean of 13.5 agencies collaborate with SPHPU during a disaster. Despite considerable variability in how SPHPUs had been structured, results of the cluster and principal component analysis identified 7 similarly structured groups. Neither the taxonomic groups nor the individual variables representing structure were found to be associated with state characteristics, including threat vulnerabilities. Our finding supports the hypothesis that SPHPUs are seemingly inadvertently (eg, not strategically) organized. This taxonomy provides the basis for which future research can examine how SPHPU structure relates to performance measures and preparedness strategies.
Level IV Ecoregions of New Jersey
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of New Mexico
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level IV Ecoregions of North Carolina
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of South Carolina
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Level III Ecoregions of New Hampshire
Ecoregions by state were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 105 regions whereas the conterminous United States has 85 (U.S. Environmental Protection Agency, 2011). Level IV ecoregions are further subdivisions of Level III eco
Zigler, Corwin M; Choirat, Christine; Dominici, Francesca
2018-03-01
Despite dramatic air quality improvement in the United States over the past decades, recent years have brought renewed scrutiny and uncertainty surrounding the effectiveness of specific regulatory programs for continuing to improve air quality and public health outcomes. We employ causal inference methods and a spatial hierarchical regression model to characterize the extent to which a designation of "nonattainment" with the 1997 National Ambient Air Quality Standard for ambient fine particulate matter (PM2.5) in 2005 causally affected ambient PM2.5 and health outcomes among over 10 million Medicare beneficiaries in the Eastern United States in 2009-2012. We found that, on average across all retained study locations, reductions in ambient PM2.5 and Medicare health outcomes could not be conclusively attributed to the nonattainment designations against the backdrop of other regional strategies that impacted the entire Eastern United States. A more targeted principal stratification analysis indicates substantial health impacts of the nonattainment designations among the subset of areas where the designations are estimated to have actually reduced ambient PM2.5 beyond levels achieved by regional measures, with noteworthy reductions in all-cause mortality, chronic obstructive pulmonary disorder, heart failure, ischemic heart disease, and respiratory tract infections. These findings provide targeted evidence of the effectiveness of local control measures after nonattainment designations for the 1997 PM2.5 air quality standard.
A reward optimization method based on action subrewards in hierarchical reinforcement learning.
Fu, Yuchen; Liu, Quan; Ling, Xionghong; Cui, Zhiming
2014-01-01
Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are "trial and error" and "related reward." A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of "curse of dimensionality," which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The "curse of dimensionality" problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well.
NASA Astrophysics Data System (ADS)
Yang, Can; Ma, Cheng; Hu, Linxi; He, Guangqiang
2018-06-01
We present a hierarchical modulation coherent communication protocol, which simultaneously achieves classical optical communication and continuous-variable quantum key distribution. Our hierarchical modulation scheme consists of a quadrature phase-shifting keying modulation for classical communication and a four-state discrete modulation for continuous-variable quantum key distribution. The simulation results based on practical parameters show that it is feasible to transmit both quantum information and classical information on a single carrier. We obtained a secure key rate of 10^{-3} bits/pulse to 10^{-1} bits/pulse within 40 kilometers, and in the meantime the maximum bit error rate for classical information is about 10^{-7}. Because continuous-variable quantum key distribution protocol is compatible with standard telecommunication technology, we think our hierarchical modulation scheme can be used to upgrade the digital communication systems to extend system function in the future.
Arling, Greg; Kane, Robert L; Mueller, Christine; Lewis, Teresa
2007-04-01
To explain variation in direct care resource use (RU) of nursing home residents based on the Resource Utilization Groups III (RUG-III) classification system and other resident- and unit-level explanatory variables. Primary data were collected on 5,314 nursing home residents in 156 nursing units in 105 facilities from four states (CO, IN, MN, MS) from 1998 to 2004. Study Design. Nurses and other direct care staff recorded resident-specific and other time caring for all residents on sampled nursing units. Care time was linked to resident data from the Minimum Data Set assessment instrument. Major variables were: RUG-III group (34-group), other health and functional conditions, licensed and other professional minutes per day, unlicensed minutes per day, and direct care RU (wage-weighted minutes). Resident- and unit-level relationships were examined through hierarchical linear modeling. Time study data were recorded with hand-held computers, verified for accuracy by project staff at the data collection sites and then merged into resident and unit-level data sets. Resident care time and RU varied between and within nursing units. RUG-III group was related to RU; variables such as length of stay and unit percentage of high acuity residents also were significantly related. Case-mix indices (CMIs) constructed from study data displayed much less variation across RUG-III groups than CMIs from earlier time studies. Results from earlier time studies may not be representative of care patterns of Medicaid and private pay residents. New RUG-III CMIs should be developed to better reflect the relative costs of caring for these residents.
Hierarchical flexural strength of enamel: transition from brittle to damage-tolerant behaviour
Bechtle, Sabine; Özcoban, Hüseyin; Lilleodden, Erica T.; Huber, Norbert; Schreyer, Andreas; Swain, Michael V.; Schneider, Gerold A.
2012-01-01
Hard, biological materials are generally hierarchically structured from the nano- to the macro-scale in a somewhat self-similar manner consisting of mineral units surrounded by a soft protein shell. Considerable efforts are underway to mimic such materials because of their structurally optimized mechanical functionality of being hard and stiff as well as damage-tolerant. However, it is unclear how different hierarchical levels interact to achieve this performance. In this study, we consider dental enamel as a representative, biological hierarchical structure and determine its flexural strength and elastic modulus at three levels of hierarchy using focused ion beam (FIB) prepared cantilevers of micrometre size. The results are compared and analysed using a theoretical model proposed by Jäger and Fratzl and developed by Gao and co-workers. Both properties decrease with increasing hierarchical dimension along with a switch in mechanical behaviour from linear-elastic to elastic-inelastic. We found Gao's model matched the results very well. PMID:22031729
Population influences on tornado reports in the United States
Anderson, C.J.; Wikle, C.K.; Zhou, Q.; Royle, J. Andrew
2007-01-01
The number of tornadoes reported in the United States is believed to be less than the actual incidence of tornadoes, especially prior to the 1990s, because tornadoes may be undetectable by human witnesses in sparsely populated areas and areas in which obstructions limit the line of sight. A hierarchical Bayesian model is used to simultaneously correct for population-based sampling bias and estimate tornado density using historical tornado report data. The expected result is that F2-F5 compared with F0-F1 tornado reports would vary less with population density. The results agree with this hypothesis for the following population centers: Atlanta, Georgia; Champaign, Illinois; and Des Moines, Iowa. However, the results indicated just the opposite in Oklahoma. It is hypothesized that the result is explained by the misclassification of tornadoes that were worthy of F2-F5 rating but were classified as F0-F1 tornadoes, thereby artificially decreasing the number of F2-F5 and increasing the number of F0-F1 reports in rural Oklahoma.
Gu, Weidong; Mahon, Barbara E.; Judd, Michael; Folster, Jason; Griffin, Patricia M.; Hoekstra, Robert M.
2017-01-01
Salmonella infections are a major cause of illness in the United States. The antimicrobial agents used to treat severe infections include ceftriaxone, ciprofloxacin, and ampicillin. Antimicrobial drug resistance has been associated with adverse clinical outcomes. To estimate the incidence of resistant culture-confirmed nontyphoidal Salmonella infections, we used Bayesian hierarchical models of 2004–2012 data from the Centers for Disease Control and Prevention National Antimicrobial Resistance Monitoring System and Laboratory-based Enteric Disease Surveillance. We based 3 mutually exclusive resistance categories on susceptibility testing: ceftriaxone and ampicillin resistant, ciprofloxacin nonsusceptible but ceftriaxone susceptible, and ampicillin resistant but ceftriaxone and ciprofloxacin susceptible. We estimated the overall incidence of resistant infections as 1.07/100,000 person-years for ampicillin-only resistance, 0.51/100,000 person-years for ceftriaxone and ampicillin resistance, and 0.35/100,000 person-years for ciprofloxacin nonsusceptibility, or ≈6,200 resistant culture-confirmed infections annually. These national estimates help define the magnitude of the resistance problem so that control measures can be appropriately targeted. PMID:27983506
Diwan, Sadhna; Jonnalagadda, Satya S; Balaswamy, Shantha
2004-10-01
Using the life stress model of psychological well-being, in this study we examined risks and resources predicting the occurrence of both positive and negative affect among older Asian Indian immigrants who experienced stressful life events. We collected data through a telephone survey of 226 respondents (aged 50 years and older) in the Southeastern United States. We used hierarchical, negative binomial regression analyses to examine correlates of positive and negative affect. Different coping resources influenced positive and negative affect when stressful life events were controlled for. Being female was a common risk factor for poorer positive and increased negative affect. Satisfaction with friendships and a cultural or ethnic identity that is either bicultural or more American were predictive of greater positive affect. Greater religiosity and increased mastery were resources predicting less negative affect. Cognitive and structural interventions that increase opportunities for social integration, increasing mastery, and addressing spiritual concerns are discussed as ways of coping with stress to improve the well-being of individuals in this immigrant community.
New insight in magnetic saturation behavior of nickel hierarchical structures
NASA Astrophysics Data System (ADS)
Ma, Ji; Zhang, Jianxing; Liu, Chunting; Chen, Kezheng
2017-09-01
It is unanimously accepted that non-ferromagnetic inclusions in a ferromagnetic system will lower down total saturation magnetization in unit of emu/g. In this study, ;lattice strain; was found to be another key factor to have critical impact on magnetic saturation behavior of the system. The lattice strain determined assembling patterns of primary nanoparticles in hierarchical structures and was intimately related with the formation process of these architectures. Therefore, flower-necklace-like and cauliflower-like nickel hierarchical structures were used as prototype systems to evidence the relationship between assembling patterns of primary nanoparticles and magnetic saturation behaviors of these architectures. It was found that the influence of lattice strain on saturation magnetization outperformed that of non-ferromagnetic inclusions in these hierarchical structures. This will enable new insights into fundamental understanding of related magnetic effects.
Local variations in spatial synchrony of influenza epidemics.
Stark, James H; Cummings, Derek A T; Ermentrout, Bard; Ostroff, Stephen; Sharma, Ravi; Stebbins, Samuel; Burke, Donald S; Wisniewski, Stephen R
2012-01-01
Understanding the mechanism of influenza spread across multiple geographic scales is not complete. While the mechanism of dissemination across regions and states of the United States has been described, understanding the determinants of dissemination between counties has not been elucidated. The paucity of high resolution spatial-temporal influenza incidence data to evaluate disease structure is often not available. We report on the underlying relationship between the spread of influenza and human movement between counties of one state. Significant synchrony in the timing of epidemics exists across the entire state and decay with distance (regional correlation=62%). Synchrony as a function of population size display evidence of hierarchical spread with more synchronized epidemics occurring among the most populated counties. A gravity model describing movement between two populations is a stronger predictor of influenza spread than adult movement to and from workplaces suggesting that non-routine and leisure travel drive local epidemics. These findings highlight the complex nature of influenza spread across multiple geographic scales.
Local Variations in Spatial Synchrony of Influenza Epidemics
Stark, James H.; Cummings, Derek A. T.; Ermentrout, Bard; Ostroff, Stephen; Sharma, Ravi; Stebbins, Samuel; Burke, Donald S.; Wisniewski, Stephen R.
2012-01-01
Background Understanding the mechanism of influenza spread across multiple geographic scales is not complete. While the mechanism of dissemination across regions and states of the United States has been described, understanding the determinants of dissemination between counties has not been elucidated. The paucity of high resolution spatial-temporal influenza incidence data to evaluate disease structure is often not available. Methodology and Findings We report on the underlying relationship between the spread of influenza and human movement between counties of one state. Significant synchrony in the timing of epidemics exists across the entire state and decay with distance (regional correlation = 62%). Synchrony as a function of population size display evidence of hierarchical spread with more synchronized epidemics occurring among the most populated counties. A gravity model describing movement between two populations is a stronger predictor of influenza spread than adult movement to and from workplaces suggesting that non-routine and leisure travel drive local epidemics. Conclusions These findings highlight the complex nature of influenza spread across multiple geographic scales. PMID:22916274
Cunningham, James K; Maxwell, Jane Carlisle; Campollo, Octavio; Cunningham, Kathryn I; Liu, Lon-Mu; Lin, Hui-Lin
2010-10-01
Although illicit drug purity is a widely discussed health risk, research explaining its geographic variation within a country is rare. This study examines whether proximity to the US-Mexico border, the United States' primary drug import portal, is associated with geographic variation in US methamphetamine, heroin and cocaine purity. Distances (proximity) between the US-Mexico border and locations of methamphetamine, cocaine and heroin seizures/acquisitions (n = 239,070) recorded in STRIDE (System to Retrieve Information from Drug Evidence) were calculated for the period of 1990-2004. The association of drug purity with these distances and other variables, including time and seizure/acquisition size, was examined using hierarchical multivariate linear modeling (HMLM). Coterminous United States. Methamphetamine, cocaine and heroin purity generally decreased with distance from the US-Mexico border. Heroin purity, however, after initially declining with distance, turned upwards-a U-shaped association. During 2000-04, methamphetamine purity also had a U-shaped association with distance. For each of the three drugs, temporal changes in the purity of small acquisitions (<10 g) were typically more dynamic in areas closer to the US-Mexico border. Geographic variance in methamphetamine, cocaine and heroin purity throughout the coterminous United States was associated with US-Mexico border proximity. The U-shaped associations between border-distance and purity for heroin and methamphetamine may be due to imports of those drugs via the eastern United States and southeast Canada, respectively. That said, areas closer to the US-Mexico border generally had relatively high illicit drug purity, as well as more dynamic change in the purity of small ('retail level') drug amounts. © 2010 The Authors, Addiction © 2010 Society for the Study of Addiction.
Advancing Methods for Estimating Cropland Area
NASA Astrophysics Data System (ADS)
King, L.; Hansen, M.; Stehman, S. V.; Adusei, B.; Potapov, P.; Krylov, A.
2014-12-01
Measurement and monitoring of complex and dynamic agricultural land systems is essential with increasing demands on food, feed, fuel and fiber production from growing human populations, rising consumption per capita, the expansion of crops oils in industrial products, and the encouraged emphasis on crop biofuels as an alternative energy source. Soybean is an important global commodity crop, and the area of land cultivated for soybean has risen dramatically over the past 60 years, occupying more than 5% of all global croplands (Monfreda et al 2008). Escalating demands for soy over the next twenty years are anticipated to be met by an increase of 1.5 times the current global production, resulting in expansion of soybean cultivated land area by nearly the same amount (Masuda and Goldsmith 2009). Soybean cropland area is estimated with the use of a sampling strategy and supervised non-linear hierarchical decision tree classification for the United States, Argentina and Brazil as the prototype in development of a new methodology for crop specific agricultural area estimation. Comparison of our 30 m2 Landsat soy classification with the National Agricultural Statistical Services Cropland Data Layer (CDL) soy map shows a strong agreement in the United States for 2011, 2012, and 2013. RapidEye 5m2 imagery was also classified for soy presence and absence and used at the field scale for validation and accuracy assessment of the Landsat soy maps, describing a nearly 1 to 1 relationship in the United States, Argentina and Brazil. The strong correlation found between all products suggests high accuracy and precision of the prototype and has proven to be a successful and efficient way to assess soybean cultivated area at the sub-national and national scale for the United States with great potential for application elsewhere.
Scaling properties of European research units
Jamtveit, Bjørn; Jettestuen, Espen; Mathiesen, Joachim
2009-01-01
A quantitative characterization of the scale-dependent features of research units may provide important insight into how such units are organized and how they grow. The relative importance of top-down versus bottom-up controls on their growth may be revealed by their scaling properties. Here we show that the number of support staff in Scandinavian research units, ranging in size from 20 to 7,800 staff members, is related to the number of academic staff by a power law. The scaling exponent of ≈1.30 is broadly consistent with a simple hierarchical model of the university organization. Similar scaling behavior between small and large research units with a wide range of ambitions and strategies argues against top-down control of the growth. Top-down effects, and externally imposed effects from changing political environments, can be observed as fluctuations around the main trend. The observed scaling law implies that cost-benefit arguments for merging research institutions into larger and larger units may have limited validity unless the productivity per academic staff and/or the quality of the products are considerably higher in larger institutions. Despite the hierarchical structure of most large-scale research units in Europe, the network structures represented by the academic component of such units are strongly antihierarchical and suboptimal for efficient communication within individual units. PMID:19625626
Ranking the Difficulty Level of the Knowledge Units Based on Learning Dependency
ERIC Educational Resources Information Center
Liu, Jun; Sha, Sha; Zheng, Qinghua; Zhang, Wei
2012-01-01
Assigning difficulty level indicators to the knowledge units helps the learners plan their learning activities more efficiently. This paper focuses on how to use the topology of a knowledge map to compute and rank the difficulty levels of knowledge units. Firstly, the authors present the hierarchical structure and properties of the knowledge map.…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Volkoff, T. J., E-mail: adidasty@gmail.com
We motivate and introduce a class of “hierarchical” quantum superposition states of N coupled quantum oscillators. Unlike other well-known multimode photonic Schrödinger-cat states such as entangled coherent states, the hierarchical superposition states are characterized as two-branch superpositions of tensor products of single-mode Schrödinger-cat states. In addition to analyzing the photon statistics and quasiprobability distributions of prominent examples of these nonclassical states, we consider their usefulness for highprecision quantum metrology of nonlinear optical Hamiltonians and quantify their mode entanglement. We propose two methods for generating hierarchical superpositions in N = 2 coupled microwave cavities, exploiting currently existing quantum optical technology formore » generating entanglement between spatially separated electromagnetic field modes.« less
Relationship Between State Malpractice Environment and Quality of Health Care in the United States.
Bilimoria, Karl Y; Chung, Jeanette W; Minami, Christina A; Sohn, Min-Woong; Pavey, Emily S; Holl, Jane L; Mello, Michelle M
2017-05-01
One major intent of the medical malpractice system in the United States is to deter negligent care and to create incentives for delivering high-quality health care. A study was conducted to assess whether state-level measures of malpractice risk were associated with hospital quality and patient safety. In an observational study of short-term, acute-care general hospitals in the United States that publicly reported in the Centers for Medicaid & Medicare Services Hospital Compare in 2011, hierarchical regression models were used to estimate associations between state-specific malpractice environment measures (rates of paid claims, average Medicare Malpractice Geographic Practice Cost Index [MGPCI], absence of tort reform laws, and a composite measure) and measures of hospital quality (processes of care, imaging utilization, 30-day mortality and readmission, Agency for Healthcare Research and Quality Patient Safety Indicators, and patient experience from the Hospital Consumer Assessment of Healthcare Providers and Systems [HCAHPS]). No consistent association between malpractice environment and hospital process-of-care measures was found. Hospitals in areas with a higher MGPCI were associated with lower adjusted odds of magnetic resonance imaging overutilization for lower back pain but greater adjusted odds of overutilization of cardiac stress testing and brain/sinus computed tomography (CT) scans. The MGPCI was negatively associated with 30-day mortality measures but positively associated with 30-day readmission measures. Measures of malpractice risk were also negatively associated with HCAHPS measures of patient experience. Overall, little evidence was found that greater malpractice risk improves adherence to recommended clinical standards of care, but some evidence was found that malpractice risk may encourage defensive medicine. Copyright © 2017 The Joint Commission. Published by Elsevier Inc. All rights reserved.
Evaluating multi-level models to test occupancy state responses of Plethodontid salamanders
Kroll, Andrew J.; Garcia, Tiffany S.; Jones, Jay E.; Dugger, Catherine; Murden, Blake; Johnson, Josh; Peerman, Summer; Brintz, Ben; Rochelle, Michael
2015-01-01
Plethodontid salamanders are diverse and widely distributed taxa and play critical roles in ecosystem processes. Due to salamander use of structurally complex habitats, and because only a portion of a population is available for sampling, evaluation of sampling designs and estimators is critical to provide strong inference about Plethodontid ecology and responses to conservation and management activities. We conducted a simulation study to evaluate the effectiveness of multi-scale and hierarchical single-scale occupancy models in the context of a Before-After Control-Impact (BACI) experimental design with multiple levels of sampling. Also, we fit the hierarchical single-scale model to empirical data collected for Oregon slender and Ensatina salamanders across two years on 66 forest stands in the Cascade Range, Oregon, USA. All models were fit within a Bayesian framework. Estimator precision in both models improved with increasing numbers of primary and secondary sampling units, underscoring the potential gains accrued when adding secondary sampling units. Both models showed evidence of estimator bias at low detection probabilities and low sample sizes; this problem was particularly acute for the multi-scale model. Our results suggested that sufficient sample sizes at both the primary and secondary sampling levels could ameliorate this issue. Empirical data indicated Oregon slender salamander occupancy was associated strongly with the amount of coarse woody debris (posterior mean = 0.74; SD = 0.24); Ensatina occupancy was not associated with amount of coarse woody debris (posterior mean = -0.01; SD = 0.29). Our simulation results indicate that either model is suitable for use in an experimental study of Plethodontid salamanders provided that sample sizes are sufficiently large. However, hierarchical single-scale and multi-scale models describe different processes and estimate different parameters. As a result, we recommend careful consideration of study questions and objectives prior to sampling data and fitting models.
Hayek, Samah; Dietz, Patricia M; Van Handel, Michelle; Zhang, Jun; Shrestha, Ram K; Huang, Ya-Lin A; Wan, Choi; Mermin, Jonathan
2015-01-01
To assess the association between state per capita allocations of Centers for Disease Control and Prevention (CDC) funding for HIV testing and the percentage of persons tested for HIV. We examined data from 2 sources: 2011 Behavioral Risk Factor Surveillance System and 2010-2011 State HIV Budget Allocations Reports. Behavioral Risk Factor Surveillance System data were used to estimate the percentage of persons aged 18 to 64 years who had reported testing for HIV in the last 2 years in the United States by state. State HIV Budget Allocations Reports were used to calculate the state mean annual per capita allocations for CDC-funded HIV testing reported by state and local health departments in the United States. The association between the state fixed-effect per capita allocations for CDC-funded HIV testing and self-reported HIV testing in the last 2 years among persons aged 18 to 64 years was assessed with a hierarchical logistic regression model adjusting for individual-level characteristics. The percentage of persons tested for HIV in the last 2 years. In 2011, 18.7% (95% confidence interval = 18.4-19.0) of persons reported being tested for HIV in last 2 years (state range, 9.7%-28.2%). During 2010-2011, the state mean annual per capita allocation for CDC-funded HIV testing was $0.34 (state range, $0.04-$1.04). A $0.30 increase in per capita allocation for CDC-funded HIV testing was associated with an increase of 2.4 percentage points (14.0% vs 16.4%) in the percentage of persons tested for HIV per state. Providing HIV testing resources to health departments was associated with an increased percentage of state residents tested for HIV.
Hierarchical modeling of cluster size in wildlife surveys
Royle, J. Andrew
2008-01-01
Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).
Semantic Image Segmentation with Contextual Hierarchical Models.
Seyedhosseini, Mojtaba; Tasdizen, Tolga
2016-05-01
Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).
Metastability on the hierarchical lattice
NASA Astrophysics Data System (ADS)
den Hollander, Frank; Jovanovski, Oliver
2017-07-01
We study metastability for Glauber spin-flip dynamics on the N-dimensional hierarchical lattice with n hierarchical levels. Each vertex carries an Ising spin that can take the values -1 or +1 . Spins interact with an external magnetic field h>0 . Pairs of spins interact with each other according to a ferromagnetic pair potential J=\\{J_i\\}i=1n , where J_i>0 is the strength of the interaction between spins at hierarchical distance i. Spins flip according to a Metropolis dynamics at inverse temperature β. In the limit as β\\to∞ , we analyse the crossover time from the metastable state \\boxminus (all spins -1 ) to the stable state \\boxplus (all spins +1 ). Under the assumption that J is non-increasing, we identify the mean transition time up to a multiplicative factor 1+o_β(1) . On the scale of its mean, the transition time is exponentially distributed. We also identify the set of configurations representing the gate for the transition. For the special case where Ji = \\tilde{J}/Ni , 1 ≤slant i ≤slant n , with \\tilde{J}>0 the relevant formulas simplify considerably. Also the hierarchical mean-field limit N\\to∞ can be analysed in detail.
Hierarchical Controlled Remote State Preparation by Using a Four-Qubit Cluster State
NASA Astrophysics Data System (ADS)
Ma, Peng-Cheng; Chen, Gui-Bin; Li, Xiao-Wei; Zhan, You-Bang
2018-06-01
We propose a scheme for hierarchical controlled remote preparation of an arbitrary single-qubit state via a four-qubit cluster state as the quantum channel. In this scheme, a sender wishes to help three agents to remotely prepare a quantum state, respectively. The three agents are divided into two grades, that is, an agent is in the upper grade and other two agents are in the lower grade. In this process of remote state preparation, the agent of the upper grade only needs the assistance of any one of the other two agents for recovering the sender's original state, while an agent of the lower grade needs the collaboration of all the other two agents. In other words, the agents of two grades have different authorities to reconstruct sender's original state.
Mapping brucellosis increases relative to elk density using hierarchical Bayesian models
Cross, Paul C.; Heisey, Dennis M.; Scurlock, Brandon M.; Edwards, William H.; Brennan, Angela; Ebinger, Michael R.
2010-01-01
The relationship between host density and parasite transmission is central to the effectiveness of many disease management strategies. Few studies, however, have empirically estimated this relationship particularly in large mammals. We applied hierarchical Bayesian methods to a 19-year dataset of over 6400 brucellosis tests of adult female elk (Cervus elaphus) in northwestern Wyoming. Management captures that occurred from January to March were over two times more likely to be seropositive than hunted elk that were killed in September to December, while accounting for site and year effects. Areas with supplemental feeding grounds for elk had higher seroprevalence in 1991 than other regions, but by 2009 many areas distant from the feeding grounds were of comparable seroprevalence. The increases in brucellosis seroprevalence were correlated with elk densities at the elk management unit, or hunt area, scale (mean 2070 km2; range = [95–10237]). The data, however, could not differentiate among linear and non-linear effects of host density. Therefore, control efforts that focus on reducing elk densities at a broad spatial scale were only weakly supported. Additional research on how a few, large groups within a region may be driving disease dynamics is needed for more targeted and effective management interventions. Brucellosis appears to be expanding its range into new regions and elk populations, which is likely to further complicate the United States brucellosis eradication program. This study is an example of how the dynamics of host populations can affect their ability to serve as disease reservoirs.
Hierarchical Traces for Reduced NSM Memory Requirements
NASA Astrophysics Data System (ADS)
Dahl, Torbjørn S.
This paper presents work on using hierarchical long term memory to reduce the memory requirements of nearest sequence memory (NSM) learning, a previously published, instance-based reinforcement learning algorithm. A hierarchical memory representation reduces the memory requirements by allowing traces to share common sub-sequences. We present moderated mechanisms for estimating discounted future rewards and for dealing with hidden state using hierarchical memory. We also present an experimental analysis of how the sub-sequence length affects the memory compression achieved and show that the reduced memory requirements do not effect the speed of learning. Finally, we analyse and discuss the persistence of the sub-sequences independent of specific trace instances.
Kitsos, Christine M; Bhamidipati, Phani; Melnikova, Irena; Cash, Ethan P; McNulty, Chris; Furman, Julia; Cima, Michael J; Levinson, Douglas
2007-01-01
This study examined whether hierarchical clustering could be used to detect cell states induced by treatment combinations that were generated through automation and high-throughput (HT) technology. Data-mining techniques were used to analyze the large experimental data sets to determine whether nonlinear, non-obvious responses could be extracted from the data. Unary, binary, and ternary combinations of pharmacological factors (examples of stimuli) were used to induce differentiation of HL-60 cells using a HT automated approach. Cell profiles were analyzed by incorporating hierarchical clustering methods on data collected by flow cytometry. Data-mining techniques were used to explore the combinatorial space for nonlinear, unexpected events. Additional small-scale, follow-up experiments were performed on cellular profiles of interest. Multiple, distinct cellular profiles were detected using hierarchical clustering of expressed cell-surface antigens. Data-mining of this large, complex data set retrieved cases of both factor dominance and cooperativity, as well as atypical cellular profiles. Follow-up experiments found that treatment combinations producing "atypical cell types" made those cells more susceptible to apoptosis. CONCLUSIONS Hierarchical clustering and other data-mining techniques were applied to analyze large data sets from HT flow cytometry. From each sample, the data set was filtered and used to define discrete, usable states that were then related back to their original formulations. Analysis of resultant cell populations induced by a multitude of treatments identified unexpected phenotypes and nonlinear response profiles.
NASA Astrophysics Data System (ADS)
Kramer, Tobias; Kreisbeck, Christoph; Rodriguez, Mirta; Hein, Birgit
2011-03-01
We study the efficiency of the energy transfer in the Fenna-Matthews-Olson complex solving the non-Markovian hierarchical equations (HE) proposed by Ishizaki and Fleming in 2009, which include properly the reorganization process. We compare it to the Markovian approach and find that the Markovian dynamics overestimates the thermalization rate, yielding higher efficiencies than the HE. Using the high-performance of graphics processing units (GPU) we cover a large range of reorganization energies and temperatures and find that initial quantum beatings are important for the energy distribution, but of limited influence to the efficiency. Our efficient GPU implementation of the HE allows us to calculate nonlinear spectra of the FMO complex. References see www.quantumdynamics.de
Bayesian state space models for dynamic genetic network construction across multiple tissues.
Liang, Yulan; Kelemen, Arpad
2016-08-01
Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.
Becoming Reactive by Concretization
NASA Technical Reports Server (NTRS)
Prieditis, Armand; Janakiraman, Bhaskar
1992-01-01
One way to build a reactive system is to construct an action table indexed by the current situation or stimulus. The action table describes what course of action to pursue for each situation or stimulus. This paper describes an incremental approach to constructing the action table through achieving goals with a hierarchical search system. These hierarchies are generated with transformations called concretizations, which add constraints to a problem and which can reduce the search space. The basic idea is that an action for a state is looked up in the action table and executed whenever the action table has an entry for that state; otherwise, a path is found to the nearest (cost-wise in a graph with costweighted arcs) state that has a mappring from a state in the next highest hierarchy. For each state along the solution path, the successor state in the path is cached in the action table entry for that state. Without caching, the hierarchical search system can logarithmically reduce search. When the table is complete the system no longer searches: it simply reacts by proceeding to the state listed in the table for each state. Since the cached information is specific only to the nearest state in the next highest hierarchy and not the goal, inter-goal transfer of reactivity is possible. To illustrate our approach, we show how an implemented hierarchical search system can completely reactive.
Arling, Greg; Kane, Robert L; Mueller, Christine; Lewis, Teresa
2007-01-01
Objective To explain variation in direct care resource use (RU) of nursing home residents based on the Resource Utilization Groups III (RUG-III) classification system and other resident- and unit-level explanatory variables. Data Sources/Study Setting Primary data were collected on 5,314 nursing home residents in 156 nursing units in 105 facilities from four states (CO, IN, MN, MS) from 1998 to 2004. Study Design Nurses and other direct care staff recorded resident-specific and other time caring for all residents on sampled nursing units. Care time was linked to resident data from the Minimum Data Set assessment instrument. Major variables were: RUG-III group (34-group), other health and functional conditions, licensed and other professional minutes per day, unlicensed minutes per day, and direct care RU (wage-weighted minutes). Resident- and unit-level relationships were examined through hierarchical linear modeling. Data Collection/Extraction Methods Time study data were recorded with hand-held computers, verified for accuracy by project staff at the data collection sites and then merged into resident and unit-level data sets. Principal Findings Resident care time and RU varied between and within nursing units. RUG-III group was related to RU; variables such as length of stay and unit percentage of high acuity residents also were significantly related. Case-mix indices (CMIs) constructed from study data displayed much less variation across RUG-III groups than CMIs from earlier time studies. Conclusions Results from earlier time studies may not be representative of care patterns of Medicaid and private pay residents. New RUG-III CMIs should be developed to better reflect the relative costs of caring for these residents. PMID:17362220
Modular, Hierarchical Learning By Artificial Neural Networks
NASA Technical Reports Server (NTRS)
Baldi, Pierre F.; Toomarian, Nikzad
1996-01-01
Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.
U.S. congressional district cancer death rates.
Hao, Yongping; Ward, Elizabeth M; Jemal, Ahmedin; Pickle, Linda W; Thun, Michael J
2006-06-23
Geographic patterns of cancer death rates in the U.S. have customarily been presented by county or aggregated into state economic or health service areas. Herein, we present the geographic patterns of cancer death rates in the U.S. by congressional district. Many congressional districts do not follow state or county boundaries. However, counties are the smallest geographical units for which death rates are available. Thus, a method based on the hierarchical relationship of census geographic units was developed to estimate age-adjusted death rates for congressional districts using data obtained at county level. These rates may be useful in communicating to legislators and policy makers about the cancer burden and potential impact of cancer control in their jurisdictions. Mortality data were obtained from the National Center for Health Statistics (NCHS) for 1990-2001 for 50 states, the District of Columbia, and all counties. We computed annual average age-adjusted death rates for all cancer sites combined, the four major cancers (lung and bronchus, prostate, female breast, and colorectal cancer) and cervical cancer. Cancer death rates varied widely across congressional districts for all cancer sites combined, for the four major cancers, and for cervical cancer. When examined at the national level, broad patterns of mortality by sex, race and region were generally similar with those previously observed based on county and state economic area. We developed a method to generate cancer death rates by congressional district using county-level mortality data. Characterizing the cancer burden by congressional district may be useful in promoting cancer control and prevention programs, and persuading legislators to enact new cancer control programs and/or strengthening existing ones. The method can be applied to state legislative districts and other analyses that involve data aggregation from different geographic units.
U.S. congressional district cancer death rates
Hao, Yongping; Ward, Elizabeth M; Jemal, Ahmedin; Pickle, Linda W; Thun, Michael J
2006-01-01
Background Geographic patterns of cancer death rates in the U.S. have customarily been presented by county or aggregated into state economic or health service areas. Herein, we present the geographic patterns of cancer death rates in the U.S. by congressional district. Many congressional districts do not follow state or county boundaries. However, counties are the smallest geographical units for which death rates are available. Thus, a method based on the hierarchical relationship of census geographic units was developed to estimate age-adjusted death rates for congressional districts using data obtained at county level. These rates may be useful in communicating to legislators and policy makers about the cancer burden and potential impact of cancer control in their jurisdictions. Results Mortality data were obtained from the National Center for Health Statistics (NCHS) for 1990–2001 for 50 states, the District of Columbia, and all counties. We computed annual average age-adjusted death rates for all cancer sites combined, the four major cancers (lung and bronchus, prostate, female breast, and colorectal cancer) and cervical cancer. Cancer death rates varied widely across congressional districts for all cancer sites combined, for the four major cancers, and for cervical cancer. When examined at the national level, broad patterns of mortality by sex, race and region were generally similar with those previously observed based on county and state economic area. Conclusion We developed a method to generate cancer death rates by congressional district using county-level mortality data. Characterizing the cancer burden by congressional district may be useful in promoting cancer control and prevention programs, and persuading legislators to enact new cancer control programs and/or strengthening existing ones. The method can be applied to state legislative districts and other analyses that involve data aggregation from different geographic units. PMID:16796732
Use Hierarchical Storage and Analysis to Exploit Intrinsic Parallelism
NASA Astrophysics Data System (ADS)
Zender, C. S.; Wang, W.; Vicente, P.
2013-12-01
Big Data is an ugly name for the scientific opportunities and challenges created by the growing wealth of geoscience data. How to weave large, disparate datasets together to best reveal their underlying properties, to exploit their strengths and minimize their weaknesses, to continually aggregate more information than the world knew yesterday and less than we will learn tomorrow? Data analytics techniques (statistics, data mining, machine learning, etc.) can accelerate pattern recognition and discovery. However, often researchers must, prior to analysis, organize multiple related datasets into a coherent framework. Hierarchical organization permits entire dataset to be stored in nested groups that reflect their intrinsic relationships and similarities. Hierarchical data can be simpler and faster to analyze by coding operators to automatically parallelize processes over isomorphic storage units, i.e., groups. The newest generation of netCDF Operators (NCO) embody this hierarchical approach, while still supporting traditional analysis approaches. We will use NCO to demonstrate the trade-offs involved in processing a prototypical Big Data application (analysis of CMIP5 datasets) using hierarchical and traditional analysis approaches.
Distributed Decision Making Environment.
1982-12-01
Findeisen , F. N. Bailey, M. Brdys, K. Malinowski, P. Tatjewoki and A. Wozniak, Control and Coordination in Hierarchical Systems, New York, NY: Wiley...1977. [99] W. Findeisen et al., "On-line hierarchical control for steady-state systems," IEEE Trans. Automat. Conts., vol. AC-23, no. 2, pp. 189-209
Hierarchical control of motor units in voluntary contractions.
De Luca, Carlo J; Contessa, Paola
2012-01-01
For the past five decades there has been wide acceptance of a relationship between the firing rate of motor units and the afterhyperpolarization of motoneurons. It has been promulgated that the higher-threshold, larger-soma, motoneurons fire faster than the lower-threshold, smaller-soma, motor units. This relationship was based on studies on anesthetized cats with electrically stimulated motoneurons. We questioned its applicability to motor unit control during voluntary contractions in humans. We found that during linearly force-increasing contractions, firing rates increased as exponential functions. At any time and force level, including at recruitment, the firing rate values were inversely related to the recruitment threshold of the motor unit. The time constants of the exponential functions were directly related to the recruitment threshold. From the Henneman size principle it follows that the characteristics of the firing rates are also related to the size of the soma. The "firing rate spectrum" presents a beautifully simple control scheme in which, at any given time or force, the firing rate value of earlier-recruited motor units is greater than that of later-recruited motor units. This hierarchical control scheme describes a mechanism that provides an effective economy of force generation for the earlier-recruited lower force-twitch motor units, and reduces the fatigue of later-recruited higher force-twitch motor units-both characteristics being well suited for generating and sustaining force during the fight-or-flight response.
Level III Ecoregions of EPA Region 7
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level IV Ecoregions of EPA Region 7
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level IV Ecoregions of EPA Region 1
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level IV Ecoregions of EPA Region 10
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level IV Ecoregions of EPA Region 3
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level III Ecoregions of EPA Region 10
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level IV Ecoregions of EPA Region 2
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level III Ecoregions of EPA Region 2
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level III Ecoregions of EPA Region 5
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level IV Ecoregions of EPA Region 5
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level III Ecoregions of EPA Region 1
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level IV Ecoregions of EPA Region 6
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level III Ecoregions of EPA Region 3
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level III Ecoregions of EPA Region 6
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level IV Ecoregions of EPA Region 4
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Level III Ecoregions of EPA Region 4
Ecoregions by EPA region were extracted from the seamless national shapefile. Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of patterns of biotic and abiotic phenomena, including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another. A Roman numeral hierarchical scheme has been adopted for different levels for ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 52 regions (Commission for Environmental Cooperation Working Group, 1997). At Level III, the continental United States contains 104 regions whereas the conterminous United States has 84 (U.S. Environmental Protection Agency, 2005). Level IV ecoregions are further subdivisions of Level I
Tsuchimoto, Masashi; Tanimura, Yoshitaka
2015-08-11
A system with many energy states coupled to a harmonic oscillator bath is considered. To study quantum non-Markovian system-bath dynamics numerically rigorously and nonperturbatively, we developed a computer code for the reduced hierarchy equations of motion (HEOM) for a graphics processor unit (GPU) that can treat the system as large as 4096 energy states. The code employs a Padé spectrum decomposition (PSD) for a construction of HEOM and the exponential integrators. Dynamics of a quantum spin glass system are studied by calculating the free induction decay signal for the cases of 3 × 2 to 3 × 4 triangular lattices with antiferromagnetic interactions. We found that spins relax faster at lower temperature due to transitions through a quantum coherent state, as represented by the off-diagonal elements of the reduced density matrix, while it has been known that the spins relax slower due to suppression of thermal activation in a classical case. The decay of the spins are qualitatively similar regardless of the lattice sizes. The pathway of spin relaxation is analyzed under a sudden temperature drop condition. The Compute Unified Device Architecture (CUDA) based source code used in the present calculations is provided as Supporting Information .
Valle, M; Witt, L A
2001-06-01
By using regression analyses on data from 355 full-time employees of a customer-service organization in the eastern United States, the authors tested the hypothesis that perceptions of organizational politics are more strongly related to job dissatisfaction among individuals who perceive low levels of teamwork importance than among those who perceive high levels of teamwork importance. Hierarchical moderated regression analysis of the data revealed that the moderating effect of teamwork importance was most relevant at average-to-high levels of perceived politics. That finding supports the assertion that one way to address the negative impact of organizational politics is to try to ensure that employees value teamwork.
Spatio-temporal Eigenvector Filtering: Application on Bioenergy Crop Impacts
NASA Astrophysics Data System (ADS)
Wang, M.; Kamarianakis, Y.; Georgescu, M.
2017-12-01
A suite of 10-year ensemble-based simulations was conducted to investigate the hydroclimatic impacts due to large-scale deployment of perennial bioenergy crops across the continental United States. Given the large size of the simulated dataset (about 60Tb), traditional hierarchical spatio-temporal statistical modelling cannot be implemented for the evaluation of physics parameterizations and biofuel impacts. In this work, we propose a filtering algorithm that takes into account the spatio-temporal autocorrelation structure of the data while avoiding spatial confounding. This method is used to quantify the robustness of simulated hydroclimatic impacts associated with bioenergy crops to alternative physics parameterizations and observational datasets. Results are evaluated against those obtained from three alternative Bayesian spatio-temporal specifications.
Sandilos, Lia E; Cycyk, Lauren M; Hammer, Carol Scheffner; Sawyer, Brook E; López, Lisa; Blair, Clancy
This study investigated the relationship of preschool teachers' self-reported depressive symptomatology, perception of classroom control, and perception of school climate to classroom quality as measured by the Classroom Assessment Scoring System Pre-K. The sample consisted of 59 urban preschool classrooms serving low-income and linguistically diverse students in the northeastern and southeastern United States. Results of hierarchical linear modeling revealed that teachers' individual reports of depressive symptomatology were significantly and negatively predictive of the observed quality of their instructional support and classroom organization. The findings of this study have implications for increasing access to mental health supports for teachers in an effort to minimize depressive symptoms and potentially improve classroom quality.
Im, Eun-Ok; Ko, Young; Chee, Eunice; Chee, Wonshik
The purpose of this study was to explore the associations of immigration transition to cardiovascular symptoms among 4 major racial/ethnic groups of 1054 midlife women in the United States. This was a secondary analysis of the data from 2 large national survey studies. The instruments included questions on background characteristics and immigration transition and the Cardiovascular Symptom Index for Midlife Women. The data were analyzed using inferential statistics including hierarchical multiple regressions. Immigrants reported fewer numbers (t = 5.268, P < .01) and lower severity scores (t = 5.493, P < .01) of cardiovascular symptoms compared with nonimmigrants. Self-reported racial/ethnic identify was a significant factor influencing cardiovascular symptoms (P < .01).
NASA Astrophysics Data System (ADS)
Shorikov, A. F.
2017-10-01
In this paper we study the problem of optimization of guaranteed result for program control by the final state of regional social and economic system in the presence of risks. For this problem we propose a mathematical model in the form of two-level hierarchical minimax program control problem of the final state of this process with incomplete information. For solving of its problem we constructed the common algorithm that has a form of a recurrent procedure of solving a linear programming and a finite optimization problems.
ERIC Educational Resources Information Center
Smith, Herbert A.
This study involved examining an instructional unit with regard to its concept content and appropriateness for its target audience. The study attempted to determine (1) what concepts are treated explicitly or implicitly, (2) whether there is a hierarchical conceptual structure within the unit, (3) what level of sophistication is required to…
DOT National Transportation Integrated Search
1995-08-01
Bridge design engineers and local highway officials make bridge replacement decsions across the U.S. The Analytical Hierarchical Process was used to characterize the bridge material selection decisions of these individuals. State Departments of Trans...
Automatic Abstraction in Planning
NASA Technical Reports Server (NTRS)
Christensen, J.
1991-01-01
Traditionally, abstraction in planning has been accomplished by either state abstraction or operator abstraction, neither of which has been fully automatic. We present a new method, predicate relaxation, for automatically performing state abstraction. PABLO, a nonlinear hierarchical planner, implements predicate relaxation. Theoretical, as well as empirical results are presented which demonstrate the potential advantages of using predicate relaxation in planning. We also present a new definition of hierarchical operators that allows us to guarantee a limited form of completeness. This new definition is shown to be, in some ways, more flexible than previous definitions of hierarchical operators. Finally, a Classical Truth Criterion is presented that is proven to be sound and complete for a planning formalism that is general enough to include most classical planning formalisms that are based on the STRIPS assumption.
Griffith, Glenn E.; Omernik, James M.; Smith, David W.; Cook, Terry D.; Tallyn, Ed; Moseley, Kendra; Johnson, Colleen B.
2016-02-23
Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources. They are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance (Bryce and others, 1999). These general purpose regions are critical for structuring and implementing ecosystem management strategies across Federal agencies, State agencies, and nongovernment organizations that are responsible for different types of resources in the same geographical areas (Omernik and others, 2000).The approach used to compile this map is based on the premise that ecological regions are hierarchical and can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity (Wiken, 1986; Omernik, 1987, 1995). These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions (Commission for Environmental Cooperation Working Group, 1997, map revised 2006). At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions (U.S. Environmental Protection Agency, 2013). Level IV, depicted here for California, is a further refinement of level III ecoregions. Explanations of the methods used to define these ecoregions are given in Omernik (1995), Omernik and others (2000), and Omernik and Griffith (2014).California has great ecological and biological diversity. The State contains offshore islands and coastal lowlands, large alluvial valleys, forested mountain ranges, deserts, and various aquatic habitats. There are 13 level III ecoregions and 177 level IV ecoregions in California and most continue into ecologically similar parts of adjacent States of the United States or Mexico (Bryce and others, 2003; Thorson and others, 2003; Griffith and others, 2014).The California ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale (Omernik, 1987; U.S. Environmental Protection Agency, 2013). This poster is the result of a collaborative project primarily between U.S. Environmental Protection Agency (USEPA) Region IX, USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), California Department of Fish and Wildlife (DFW), U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), U.S. Department of the Interior–Geological Survey (USGS), and other State of California agencies and universities.The project is associated with interagency efforts to develop a common framework of ecological regions (McMahon and others, 2001). Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service (Bailey and others, 1994; Miles and Goudy, 1997; Cleland and others, 2007), the USEPA (Omernik 1987, 1995), and the NRCS (U.S. Department of Agriculture–Soil Conservation Service, 1981; U.S. Department of Agriculture–Natural Resources Conservation Service, 2006). As each of these frameworks is further refined, their differences are becoming less discernible. Regional collaborative projects such as this one in California, where some agreement has been reached among multiple resource-management agencies, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.
Modeling Bivariate Longitudinal Hormone Profiles by Hierarchical State Space Models
Liu, Ziyue; Cappola, Anne R.; Crofford, Leslie J.; Guo, Wensheng
2013-01-01
The hypothalamic-pituitary-adrenal (HPA) axis is crucial in coping with stress and maintaining homeostasis. Hormones produced by the HPA axis exhibit both complex univariate longitudinal profiles and complex relationships among different hormones. Consequently, modeling these multivariate longitudinal hormone profiles is a challenging task. In this paper, we propose a bivariate hierarchical state space model, in which each hormone profile is modeled by a hierarchical state space model, with both population-average and subject-specific components. The bivariate model is constructed by concatenating the univariate models based on the hypothesized relationship. Because of the flexible framework of state space form, the resultant models not only can handle complex individual profiles, but also can incorporate complex relationships between two hormones, including both concurrent and feedback relationship. Estimation and inference are based on marginal likelihood and posterior means and variances. Computationally efficient Kalman filtering and smoothing algorithms are used for implementation. Application of the proposed method to a study of chronic fatigue syndrome and fibromyalgia reveals that the relationships between adrenocorticotropic hormone and cortisol in the patient group are weaker than in healthy controls. PMID:24729646
Modeling Bivariate Longitudinal Hormone Profiles by Hierarchical State Space Models.
Liu, Ziyue; Cappola, Anne R; Crofford, Leslie J; Guo, Wensheng
2014-01-01
The hypothalamic-pituitary-adrenal (HPA) axis is crucial in coping with stress and maintaining homeostasis. Hormones produced by the HPA axis exhibit both complex univariate longitudinal profiles and complex relationships among different hormones. Consequently, modeling these multivariate longitudinal hormone profiles is a challenging task. In this paper, we propose a bivariate hierarchical state space model, in which each hormone profile is modeled by a hierarchical state space model, with both population-average and subject-specific components. The bivariate model is constructed by concatenating the univariate models based on the hypothesized relationship. Because of the flexible framework of state space form, the resultant models not only can handle complex individual profiles, but also can incorporate complex relationships between two hormones, including both concurrent and feedback relationship. Estimation and inference are based on marginal likelihood and posterior means and variances. Computationally efficient Kalman filtering and smoothing algorithms are used for implementation. Application of the proposed method to a study of chronic fatigue syndrome and fibromyalgia reveals that the relationships between adrenocorticotropic hormone and cortisol in the patient group are weaker than in healthy controls.
Fractal-like hierarchical organization of bone begins at the nanoscale
NASA Astrophysics Data System (ADS)
Reznikov, Natalie; Bilton, Matthew; Lari, Leonardo; Stevens, Molly M.; Kröger, Roland
2018-05-01
The components of bone assemble hierarchically to provide stiffness and toughness. However, the organization and relationship between bone’s principal components—mineral and collagen—has not been clearly elucidated. Using three-dimensional electron tomography imaging and high-resolution two-dimensional electron microscopy, we demonstrate that bone mineral is hierarchically assembled beginning at the nanoscale: Needle-shaped mineral units merge laterally to form platelets, and these are further organized into stacks of roughly parallel platelets. These stacks coalesce into aggregates that exceed the lateral dimensions of the collagen fibrils and span adjacent fibrils as continuous, cross-fibrillar mineralization. On the basis of these observations, we present a structural model of hierarchy and continuity for the mineral phase, which contributes to the structural integrity of bone.
Hierarchical SAPO‐34 Architectures with Tailored Acid Sites using Sustainable Sugar Templates
Miletto, Ivana; Ivaldi, Chiara; Paul, Geo; Chapman, Stephanie; Marchese, Leonardo; Raja, Robert
2018-01-01
Abstract In a distinct, bottom‐up synthetic methodology, monosaccharides (fructose and glucose) and disaccharides (sucrose) have been used as mesoporogens to template hierarchical SAPO‐34 catalysts. Detailed materials characterization, which includes solid‐state magic angle spinning NMR and probe‐based FTIR, reveals that, although the mesopore dimensions are modified by the identity of the sugar template, the desirable acid characteristics of the microporous framework are retained. When the activity of the hierarchical SAPO‐34 catalysts was evaluated in the industrially relevant Beckmann rearrangement, under liquid‐phase conditions, the enhanced mass‐transport properties of sucrose‐templated hierarchical SAPO‐34 were found to deliver a superior yield of ϵ‐caprolactam. PMID:29686961
The Stability of Tidal Equilibrium for Hierarchical Star-Planet-Moon Systems
NASA Astrophysics Data System (ADS)
Adams, Fred C.
2018-04-01
Motivated by the current search for exomoons, this talk considers the stability of tidal equilibrium for hierarchical three-body systems containing a star, a planet, and a moon. In this treatment, the energy and angular momentum budgets include contributions from the planetary orbit, lunar orbit, stellar spin, planetary spin, and lunar spin. The goal is to determine the optimized energy state of the system subject to the constraint of constant angular momentum. Due to the lack of a closed form solution for the full three-body problem, however, we must use use an approximate description of the orbits. We first consider the Keplerian limit and find that the critical energy states are saddle points, rather than minima, so that these hierarchical systems have no stable tidal equilibrium states. We then generalize the calculation so that the lunar orbit is described by a time-averaged version of the circular restricted three-body problem. In this latter case, the critical energy state is a shallow minimum, so that a tidal equilibrium state exists. In both cases, however, the lunar orbit for the critical point lies outside the boundary (roughly half the Hill radius) where (previous) numerical simulations indicate dynamical instability.
Hierarchical auto-configuration addressing in mobile ad hoc networks (HAAM)
NASA Astrophysics Data System (ADS)
Ram Srikumar, P.; Sumathy, S.
2017-11-01
Addressing plays a vital role in networking to identify devices uniquely. A device must be assigned with a unique address in order to participate in the data communication in any network. Different protocols defining different types of addressing are proposed in literature. Address auto-configuration is a key requirement for self organizing networks. Existing auto-configuration based addressing protocols require broadcasting probes to all the nodes in the network before assigning a proper address to a new node. This needs further broadcasts to reflect the status of the acquired address in the network. Such methods incur high communication overheads due to repetitive flooding. To address this overhead, a new partially stateful address allocation scheme, namely Hierarchical Auto-configuration Addressing (HAAM) scheme is extended and proposed. Hierarchical addressing basically reduces latency and overhead caused during address configuration. Partially stateful addressing algorithm assigns addresses without the need for flooding and global state awareness, which in turn reduces the communication overhead and space complexity respectively. Nodes are assigned addresses hierarchically to maintain the graph of the network as a spanning tree which helps in effectively avoiding the broadcast storm problem. Proposed algorithm for HAAM handles network splits and merges efficiently in large scale mobile ad hoc networks incurring low communication overheads.
Kim, Cheolho; Moon, Jun Hyuk
2018-06-13
Micro-supercapacitors (MSCs) are attractive for applications in next-generation mobile and wearable devices and have the potential to complement or even replace lithium batteries. However, many previous MSCs have often exhibited a low volumetric energy density with high-loading electrodes because of the nonuniform pore structure of the electrodes. To address this issue, we introduced a uniform-pore carbon electrode fabricated by 3D interference lithography. Furthermore, a hierarchical pore-patterned carbon (hPC) electrode was formed by introducing a micropore by chemical etching into the macropore carbon skeleton. The hPC electrodes were applied to solid-state MSCs. We achieved a constant volumetric capacitance and a corresponding volumetric energy density for electrodes of various thicknesses. The hPC MSC reached a volumetric energy density of approximately 1.43 mW h/cm 3 . The power density of the hPC MSC was 1.69 W/cm 3 . We could control the capacitance and voltage additionally by connecting the unit MSC cells in series or parallel, and we confirmed the operation of a light-emitting diode. We believe that our pore-patterned electrodes will provide a new platform for compact but high-performance energy storage devices.
Combined algorithmic and GPU acceleration for ultra-fast circular conebeam backprojection
NASA Astrophysics Data System (ADS)
Brokish, Jeffrey; Sack, Paul; Bresler, Yoram
2010-04-01
In this paper, we describe the first implementation and performance of a fast O(N3logN) hierarchical backprojection algorithm for cone beam CT with a circular trajectory1,developed on a modern Graphics Processing Unit (GPU). The resulting tomographic backprojection system for 3D cone beam geometry combines speedup through algorithmic improvements provided by the hierarchical backprojection algorithm with speedup from a massively parallel hardware accelerator. For data parameters typical in diagnostic CT and using a mid-range GPU card, we report reconstruction speeds of up to 360 frames per second, and relative speedup of almost 6x compared to conventional backprojection on the same hardware. The significance of these results is twofold. First, they demonstrate that the reduction in operation counts demonstrated previously for the FHBP algorithm can be translated to a comparable run-time improvement in a massively parallel hardware implementation, while preserving stringent diagnostic image quality. Second, the dramatic speedup and throughput numbers achieved indicate the feasibility of systems based on this technology, which achieve real-time 3D reconstruction for state-of-the art diagnostic CT scanners with small footprint, high-reliability, and affordable cost.
Hierarchical spatiotemporal matrix models for characterizing invasions
Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew
2007-01-01
The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing.
Hierarchical spatiotemporal matrix models for characterizing invasions
Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew
2007-01-01
The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing. ?? 2006, The International Biometric Society.
Federal standards and procedures for the National Watershed Boundary Dataset (WBD)
,; ,; ,
2013-01-01
The Watershed Boundary Dataset (WBD) is a comprehensive aggregated collection of hydrologic unit data consistent with the national criteria for delineation and resolution. This document establishes Federal standards and procedures for creating the WBD as seamless and hierarchical hydrologic unit data, based on topographic and hydrologic features at a 1:24,000 scale in the United States, except for Alaska at 1:63,360 scale, and 1:25,000 scale in the Caribbean. The data within the WBD have been reviewed for certification through the 12-digit hydrologic unit for compliance with the criteria outlined in this document. Any edits to certified data will be reviewed against this standard prior to inclusion. Although not required as part of the framework WBD, the guidelines contain details for compiling and delineating the boundaries of two additional levels, the 14- and 16-digit hydrologic units, as well as the use of higher resolution base information to improve delineations. The guidelines presented herein are designed to enable local, regional, and national partners to delineate hydrologic units consistently and accurately. Such consistency improves watershed management through efficient sharing of information and resources and by ensuring that digital geographic data are usable with other related Geographic Information System (GIS) data.Terminology, definitions, and procedural information are provided to ensure uniformity in hydrologic unit boundaries, names, and numerical codes. Detailed standards and specifications for data are included. The document also includes discussion of objectives, communications required for revising the data resolution in the United States and the Caribbean, as well as final review and data-quality criteria. Instances of unusual landforms or artificial features that affect the hydrologic units are described with metadata standards. Up-to-date information and availability of the hydrologic units are listed at http:// www.nrcs.usda.gov/wps/portal/nrcs/detail/national/technical/ nra/dma/?&cid=nrcs143_021630/.
Federal standards and procedures for the National Watershed Boundary Dataset (WBD)
U.S. Geological Survey and U.S. Department of Agriculture, Natural Resources Conservation Service
2012-01-01
The Watershed Boundary Dataset (WBD) is a comprehensive aggregated collection of hydrologic unit data consistent with the national criteria for delineation and resolution. This document establishes Federal standards and procedures for creating the WBD as seamless and hierarchical hydrologic unit data, based on topographic and hydrologic features at a 1:24,000 scale in the United States, except for Alaska at 1:63,360 scale, and 1:25,000 scale in the Caribbean. The data within the WBD have been reviewed for certification through the 12-digit hydrologic unit for compliance with the criteria outlined in this document. Any edits to certified data will be reviewed against this standard prior to inclusion. Although not required as part of the framework WBD, the guidelines contain details for compiling and delineating the boundaries of two additional levels, the 14- and 16-digit hydrologic units, as well as the use of higher resolution base information to improve delineations. The guidelines presented herein are designed to enable local, regional, and national partners to delineate hydrologic units consistently and accurately. Such consistency improves watershed management through efficient sharing of information and resources and by ensuring that digital geographic data are usable with other related Geographic Information System (GIS) data. Terminology, definitions, and procedural information are provided to ensure uniformity in hydrologic unit boundaries, names, and numerical codes. Detailed standards and specifications for data are included. The document also includes discussion of objectives, communications required for revising the data resolution in the United States and the Caribbean, as well as final review and data-quality criteria. Instances of unusual landforms or artificial features that affect the hydrologic units are described with metadata standards. Up-to-date information and availability of the hydrologic units are listed at http://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/water/watersheds/?cid=nrcs143_021630/.
Hierarchical control of motor units in voluntary contractions
Contessa, Paola
2012-01-01
For the past five decades there has been wide acceptance of a relationship between the firing rate of motor units and the afterhyperpolarization of motoneurons. It has been promulgated that the higher-threshold, larger-soma, motoneurons fire faster than the lower-threshold, smaller-soma, motor units. This relationship was based on studies on anesthetized cats with electrically stimulated motoneurons. We questioned its applicability to motor unit control during voluntary contractions in humans. We found that during linearly force-increasing contractions, firing rates increased as exponential functions. At any time and force level, including at recruitment, the firing rate values were inversely related to the recruitment threshold of the motor unit. The time constants of the exponential functions were directly related to the recruitment threshold. From the Henneman size principle it follows that the characteristics of the firing rates are also related to the size of the soma. The “firing rate spectrum” presents a beautifully simple control scheme in which, at any given time or force, the firing rate value of earlier-recruited motor units is greater than that of later-recruited motor units. This hierarchical control scheme describes a mechanism that provides an effective economy of force generation for the earlier-recruited lower force-twitch motor units, and reduces the fatigue of later-recruited higher force-twitch motor units—both characteristics being well suited for generating and sustaining force during the fight-or-flight response. PMID:21975447
Midwives' experiences of facilitating normal birth in an obstetric-led unit: a feminist perspective.
Keating, Annette; Fleming, Valerie E M
2009-10-01
to explore midwives' experiences of facilitating normal birth in an obstetric-led unit. a feminist approach using semi-structured interviews focusing on midwives' perceptions of normal birth and their ability to facilitate this birth option in an obstetric-led unit. Ireland. a purposeful sample of 10 midwives with 6-30 years of midwifery experience. All participants had worked for a minimum of 6 years in a labour ward setting, and had been in their current setting for the previous 2 years. the midwives' narratives related to the following four concepts of patriarchy: 'hierarchical thinking', 'power and prestige', 'a logic of domination' and 'either/or thinking' (dualisms). Two themes, 'hierarchical thinking' and 'either/or thinking', (dualisms) along with their subthemes are presented in this paper. this study identified some of the reasons why midwives find it difficult to facilitate normal birth in an obstetric unit setting, and identified a need for further research in this area. Midwifery education and supportive management structures are required if midwives are to become confident practitioners of normal birth.
NASA Astrophysics Data System (ADS)
Ma, Peng-Cheng; Chen, Gui-Bin; Li, Xiao-Wei; Zhan, You-Bang
2018-05-01
In this paper, we present a scheme for Hierarchically controlled remote preparation of an arbitrary single-qubit state via a four-qubit |χ > state as the quantum channel. In this scheme, a sender wishes to help three agents to remotely prepare a quantum state, respectively. The three agents are divided into two grades, that is, an agent is in the upper grade and other two agents are in the lower grade. It is shown that the agent of the upper grade only needs the assistance of any one of the other two agents for recovering the sender's original state, while an agent of the lower grade needs the collaboration of all the other two agents. In other words, the agents of two grades have different authorities to recover sender's original state.
Miller, David A.W.; Grant, Evan H. Campbell
2015-01-01
Regional monitoring strategies frequently employ a nested sampling design where a finite set of study areas from throughout a region are selected within which intensive sub-sampling occurs. This sampling protocol naturally lends itself to a hierarchical analysis to account for dependence among sub-samples. Implementing such an analysis within a classic likelihood framework is computationally prohibitive with species occurrence data when accounting for detection probabilities. Bayesian methods offer an alternative framework to make this analysis feasible. We demonstrate a general approach for estimating occupancy when data come from a nested sampling design. Using data from a regional monitoring program of wood frogs (Lithobates sylvaticus) and spotted salamanders (Ambystoma maculatum) in vernal pools, we analyzed data using static and dynamic occupancy frameworks. We analyzed observations from 2004-2013collected within 14 protected areas located throughout the northeast United States . We use the data set to estimate trends in occupancy at both the regional and individual protected area level. We show that occupancy at the regional level was relatively stable for both species. Much more variation occurred within individual study areas, with some populations declining and some increasing for both species. We found some evidence for a latitudinal gradient in trends among protected areas. However, support for this pattern is overestimated when the hierarchical nature of the data collection is not controlled for in the analysis. For both species, occupancy appeared to be declining in the most southern areas, while occupancy was stable or increasing in more northern areas. These results shed light on the range-level population status of these pond-breeding amphibians and our approach provides a framework that can be used to examine drivers of change including among-year and among-site variation in occurrence dynamics, while properly accounting for nested structure of data collection.
Building Regional Threat-Based Networks for Estuaries in the Western United States
Merrifield, Matthew S.; Hines, Ellen; Liu, Xiaohang; Beck, Michael W.
2011-01-01
Estuaries are ecologically and economically valuable and have been highly degraded from both land and sea. Estuarine habitats in the coastal zone are under pressure from a range of human activities. In the United States and elsewhere, very few conservation plans focused on estuaries are regional in scope; fewer still address threats to estuary long term viability.We have compiled basic information about the spatial extent of threats to identify commonalities. To do this we classify estuaries into hierarchical networks that share similar threat characteristics using a spatial database (geodatabase) of threats to estuaries from land and sea in the western U.S.Our results show that very few estuaries in this region (16%) have no or minimal stresses from anthropogenic activity. Additionally, one quarter (25%) of all estuaries in this study have moderate levels of all threats. The small number of un-threatened estuaries is likely not representative of the ecological variability in the region and will require working to abate threats at others. We think the identification of these estuary groups can foster sharing best practices and coordination of conservation activities amongst estuaries in any geography. PMID:21387006
Maguire-Jack, Kathryn; Lanier, Paul; Johnson-Motoyama, Michelle; Welch, Hannah; Dineen, Michael
2015-09-01
There are documented disparities in the rates at which black children come into contact with the child welfare system in the United States compared to white children. A great deal of research has proliferated aimed at understanding whether systematic biases or differential rates of risk among different groups drive these disparities (Drake et al., 2011). In the current study, county rates of maltreatment disparity are compared across the United States and examined in relation to rates of poverty disparity as well as population density. Specifically, using hierarchical linear modeling with a spatially lagged dependent variable, the current study examined data from the National Child Abuse and Neglect Data System (NCANDS) and found that poverty disparities were associated with rates of maltreatment disparities, and densely populated metropolitan counties tended to have the greatest levels of maltreatment disparity for both black and Hispanic children. A significant curvilinear relationship was also observed between these variables, such that in addition to the most densely populated counties, the most sparsely populated counties also tended to have higher rates of maltreatment disparity for black and Hispanic children. Copyright © 2015 Elsevier Ltd. All rights reserved.
Exploring the Dynamics of Dyadic Interactions via Hierarchical Segmentation
ERIC Educational Resources Information Center
Hsieh, Fushing; Ferrer, Emilio; Chen, Shu-Chun; Chow, Sy-Miin
2010-01-01
In this article we present an exploratory tool for extracting systematic patterns from multivariate data. The technique, hierarchical segmentation (HS), can be used to group multivariate time series into segments with similar discrete-state recurrence patterns and it is not restricted by the stationarity assumption. We use a simulation study to…
Mannes, Zachary L; Burrell, Larry E; Dunne, Eugene M; Hearn, Lauren E; Whitehead, Nicole Ennis
We examined the influence of age on associations between affective states, social support, and alcohol use by age cohorts. We recruited 96 older Black adults living with HIV from the southeastern United States in 2013 and 2014. Participants completed questionnaires assessing demographics, psychological function, and substance use. Hierarchical regression analyses assessed the relationship between psychosocial factors and alcohol use in a 50- to 59-year-old group, and a 60-years-and-older age group. After controlling for covariates, trait anger, state anger, and life stress were positively associated with alcohol consumption in the younger group, while social support was negatively associated with alcohol consumption in the older group. Interventions should target negative affective states in 50- to 59-year-old adults with HIV, and preserve social support for adults with HIV as they age, as such interventions will likely have an impact on these individuals' alcohol consumption and longstanding quality of life. Copyright © 2016 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.
Predicting summer residential electricity demand across the U.S.A using climate information
NASA Astrophysics Data System (ADS)
Sun, X.; Wang, S.; Lall, U.
2017-12-01
We developed a Bayesian Hierarchical model to predict monthly residential per capita electricity consumption at the state level across the USA using climate information. The summer period was selected since cooling requirements may be directly associated with electricity use, while for winter a mix of energy sources may be used to meet heating needs. Historical monthly electricity consumption data from 1990 to 2013 were used to build a predictive model with a set of corresponding climate and non-climate covariates. A clustering analysis was performed first to identify groups of states that had similar temporal patterns for the cooling degree days of each state. Then, a partial pooling model was applied to each cluster to assess the sensitivity of monthly per capita residential electricity demand to each predictor (including cooling-degree-days, gross domestic product (GDP) per capita, per capita electricity demand of previous month and previous year, and the residential electricity price). The sensitivity of residential electricity to cooling-degree-days has an identifiable geographic distribution with higher values in northeastern United States.
Utley, J M; Affuso, O; Rucks, A C
2016-10-01
Multilevel/hierarchical obesity studies analyze adolescent and family, neighbourhood and social settings' characteristics to generate data needed to design prevention interventions. This scoping study summarizes such studies' characteristics and key findings to provide information to decision makers, which allows them to quickly grasp the state of the evidence and potential policy implications for adolescent obesity prevention. PubMed, CINAHLplus, PsychINFO and Sociological Abstracts were searched for peer-reviewed studies spanning 1 January 2000-31 August 2014. Inclusion criteria included (i) outcome weight status, physical activity and weight status, or physical activity alone if the aim was obesity prevention; (ii) 12- to 19-year-old participants in a cross-sectional study, a separate analysis in a cross-sectional study or a longitudinal follow-up. Nineteen studies were published in the United States of America; four in Canada; two in Spain, China and Vietnam, respectively; and one in Germany. Self-efficacy, parental physical activity support, perceived neighbourhood support, social cohesion and access to recreational facilities were associated with increased activity levels; neighbourhood physical disorder and perceived lack of safety associated with reduced physical activity levels. Overweight or obesity was associated with sugar-sweetened beverage intake and household availability thereof; reduced odds were reported with fruit and vegetable intake and household availability of these, daily breakfast and family meal frequency. Potential adolescent obesity risk regulators may be found at the individual, family or social contextual levels. © 2016 World Obesity.
Hierarchical CaCO3 chromatography: a stationary phase based on biominerals.
Sato, Kosuke; Oaki, Yuya; Takahashi, Daisuke; Toshima, Kazunobu; Imai, Hiroaki
2015-03-23
In biomineralization, acidic macromolecules play important roles for the growth control of crystals through a specific interaction. Inspired by this interaction, we report on an application of the hierarchical structures in CaCO3 biominerals to a stationary phase of chromatography. The separation and purification of acidic small organic molecules are achieved by thin-layer chromatography and flash chromatography using the powder of biominerals as the stationary phase. The unit nanocrystals and their oriented assembly, the hierarchical structure, are suitable for the adsorption site of the target organic molecules and the flow path of the elution solvents, respectively. The separation mode is ascribed to the specific adsorption of the acidic molecules on the crystal face and the coordination of the functional groups to the calcium ions. The results imply that a new family of stationary phase of chromatography can be developed by the fine tuning of hierarchical structures in CaCO3 materials. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Not all stars form in clusters - measuring the kinematics of OB associations with Gaia
NASA Astrophysics Data System (ADS)
Ward, Jacob L.; Kruijssen, J. M. Diederik
2018-04-01
It is often stated that star clusters are the fundamental units of star formation and that most (if not all) stars form in dense stellar clusters. In this monolithic formation scenario, low-density OB associations are formed from the expansion of gravitationally bound clusters following gas expulsion due to stellar feedback. N-body simulations of this process show that OB associations formed this way retain signs of expansion and elevated radial anisotropy over tens of Myr. However, recent theoretical and observational studies suggest that star formation is a hierarchical process, following the fractal nature of natal molecular clouds and allowing the formation of large-scale associations in situ. We distinguish between these two scenarios by characterizing the kinematics of OB associations using the Tycho-Gaia Astrometric Solution catalogue. To this end, we quantify four key kinematic diagnostics: the number ratio of stars with positive radial velocities to those with negative radial velocities, the median radial velocity, the median radial velocity normalized by the tangential velocity, and the radial anisotropy parameter. Each quantity presents a useful diagnostic of whether the association was more compact in the past. We compare these diagnostics to models representing random motion and the expanding products of monolithic cluster formation. None of these diagnostics show evidence of expansion, either from a single cluster or multiple clusters, and the observed kinematics are better represented by a random velocity distribution. This result favours the hierarchical star formation model in which a minority of stars forms in bound clusters and large-scale, hierarchically structured associations are formed in situ.
Posttraumatic Stress in U.S. Marines: The Role of Unit Cohesion and Combat Exposure
ERIC Educational Resources Information Center
Armistead-Jehle, Patrick; Johnston, Scott L.; Wade, Nathaniel G.; Ecklund, Christofer J.
2011-01-01
Combat exposure is a consistent predictor of posttraumatic stress (PTS). Understanding factors that might buffer the effects of combat exposure is crucial for helping service members weather the stress of war. In a study of U.S. Marines returning from Iraq, hierarchical multiple regression analyses revealed that unit cohesion and combat exposure…
Valley segments, stream reaches, and channel units [Chapter 2
Peter A. Bisson; David R. Montgomery; John M. Buffington
2006-01-01
Valley segments, stream reaches, and channel units are three hierarchically nested subdivisions of the drainage network (Frissell et al. 1986), falling in size between landscapes and watersheds (see Chapter 1) and individual point measurements made along the stream network (Table 2.1; also see Chapters 3 and 4). These three subdivisions compose the habitat for large,...
ERIC Educational Resources Information Center
Yamaguchi, Motonori; Randle, James M.; Wilson, Thomas L.; Logan, Gordon D.
2017-01-01
Hierarchical control of skilled performance depends on chunking of several lower-level units into a single higher-level unit. The present study examined the relationship between chunking and recognition of trained materials in the context of typewriting. In 3 experiments, participants were trained with typing nonwords and were later tested on…
Sato, Naoyuki; Yamaguchi, Yoko
2009-06-01
The human cognitive map is known to be hierarchically organized consisting of a set of perceptually clustered landmarks. Patient studies have demonstrated that these cognitive maps are maintained by the hippocampus, while the neural dynamics are still poorly understood. The authors have shown that the neural dynamic "theta phase precession" observed in the rodent hippocampus may be capable of forming hierarchical cognitive maps in humans. In the model, a visual input sequence consisting of object and scene features in the central and peripheral visual fields, respectively, results in the formation of a hierarchical cognitive map for object-place associations. Surprisingly, it is possible for such a complex memory structure to be formed in a few seconds. In this paper, we evaluate the memory retrieval of object-place associations in the hierarchical network formed by theta phase precession. The results show that multiple object-place associations can be retrieved with the initial cue of a scene input. Importantly, according to the wide-to-narrow unidirectional connections among scene units, the spatial area for object-place retrieval can be controlled by the spatial area of the initial cue input. These results indicate that the hierarchical cognitive maps have computational advantages on a spatial-area selective retrieval of multiple object-place associations. Theta phase precession dynamics is suggested as a fundamental neural mechanism of the human cognitive map.
Sandilos, Lia E.; Cycyk, Lauren M.; Hammer, Carol Scheffner; Sawyer, Brook E.; López, Lisa; Blair, Clancy
2015-01-01
Research Findings This study investigated the relationship of preschool teachers' self-reported depressive symptomatology, perception of classroom control, and perception of school climate to classroom quality as measured by the Classroom Assessment Scoring System Pre-K. The sample consisted of 59 urban preschool classrooms serving low-income and linguistically diverse students in the northeastern and southeastern United States. Results of hierarchical linear modeling revealed that teachers' individual reports of depressive symptomatology were significantly and negatively predictive of the observed quality of their instructional support and classroom organization. Practice or Policy The findings of this study have implications for increasing access to mental health supports for teachers in an effort to minimize depressive symptoms and potentially improve classroom quality. PMID:26924914
Silk, Kami J; Weiner, Judith; Parrott, Roxanne L
2005-12-01
Genetically modified (GM) foods are currently a controversial topic about which the lay public in the United States knows little. Formative research has demonstrated that the lay public is uncertain and concerned about GM foods. This study (N = 858) extends focus group research by using the Theory of Reasoned Action (TRA) to examine attitudes and subjective norms related to GM foods as a theoretical strategy for audience segmentation. A hierarchical cluster analysis revealed four unique audiences based on their attitude and subjective norm toward GM foods (ambivalent-biotech, antibiotech, biotech-normer, and biotech individual). Results are discussed in terms of the theoretical and practical significance for audience segmentation.
Hierarchical rank and women's organizational mobility: glass ceilings in corporate law firms.
Gorman, Elizabeth H; Kmec, Julie A
2009-03-01
This article revives the debate over whether women's upward mobility prospects decline as they climb organizational hierarchies. Although this proposition is a core element of the "glass ceiling" metaphor, it has failed to gain strong support in previous research. The article establishes a firm theoretical foundation for expecting an increasing female disadvantage, with an eye toward defining the scope conditions and extending the model to upper-level external hires. The approach is illustrated in an empirical setting that meets the proposed scope conditions: corporate law firms in the United States. Results confirm that in this setting, the female mobility disadvantage is greater at higher organizational levels in the case of internal promotions, but not in the case of external hires.
Effects of post-migration factors on PTSD outcomes among immigrant survivors of political violence.
Chu, Tracy; Keller, Allen S; Rasmussen, Andrew
2013-10-01
This study examined the predictors of posttraumatic stress disorder (PTSD) in a clinical sample of 875 immigrant survivors of political violence resettled in the United States, with a specific aim of comparing the relative predictive power of pre-migration and post-migration experiences. Results from a hierarchical OLS regression indicated that pre-migration experiences such as rape/sexual assault were significantly associated with worse PTSD outcomes, as were post-migration factors such as measures of financial and legal insecurity. Post-migration variables, which included immigration status in the US, explained significantly more variance in PTSD outcomes than premigration variables alone. Discussion focused on the importance of looking at postmigration living conditions when treating trauma in this population.
Mirjankar, Nikhil S; Fraga, Carlos G; Carman, April J; Moran, James J
2016-02-02
Chemical attribution signatures (CAS) for chemical threat agents (CTAs), such as cyanides, are being investigated to provide an evidentiary link between CTAs and specific sources to support criminal investigations and prosecutions. Herein, stocks of KCN and NaCN were analyzed for trace anions by high performance ion chromatography (HPIC), carbon stable isotope ratio (δ(13)C) by isotope ratio mass spectrometry (IRMS), and trace elements by inductively coupled plasma optical emission spectroscopy (ICP-OES). The collected analytical data were evaluated using hierarchical cluster analysis (HCA), Fisher-ratio (F-ratio), interval partial least-squares (iPLS), genetic algorithm-based partial least-squares (GAPLS), partial least-squares discriminant analysis (PLSDA), K nearest neighbors (KNN), and support vector machines discriminant analysis (SVMDA). HCA of anion impurity profiles from multiple cyanide stocks from six reported countries of origin resulted in cyanide samples clustering into three groups, independent of the associated alkali metal (K or Na). The three groups were independently corroborated by HCA of cyanide elemental profiles and corresponded to countries each having one known solid cyanide factory: Czech Republic, Germany, and United States. Carbon stable isotope measurements resulted in two clusters: Germany and United States (the single Czech stock grouped with United States stocks). Classification errors for two validation studies using anion impurity profiles collected over five years on different instruments were as low as zero for KNN and SVMDA, demonstrating the excellent reliability associated with using anion impurities for matching a cyanide sample to its factory using our current cyanide stocks. Variable selection methods reduced errors for those classification methods having errors greater than zero; iPLS-forward selection and F-ratio typically provided the lowest errors. Finally, using anion profiles to classify cyanides to a specific stock or stock group for a subset of United States stocks resulted in cross-validation errors ranging from 0 to 5.3%.
Van Gosen, Bradley S.; Ellefsen, Karl J.
2018-04-16
This study examined titanium distribution in the Atlantic Coastal Plain of the southeastern United States; the titanium is found in heavy-mineral sands that include the minerals ilmenite (Fe2+TiO3), rutile (TiO2), or leucoxene (an alteration product of ilmenite). Deposits of heavy-mineral sands in ancient and modern coastal plains are a significant feedstock source for the titanium dioxide pigments industry. Currently, two heavy-mineral sands mining and processing operations are active in the southeast United States producing concentrates of ilmenite-leucoxene, rutile, and zircon. The results of this study indicate the potential for similar deposits in many areas of the Atlantic Coastal Plain.This study used the titanium analyses of 3,457 stream sediment samples that were analyzed as part of the U.S. Geological Survey’s National Geochemical Survey program. This data set was analyzed by an integrated spatial modeling technique known as Bayesian hierarchical modeling to map the regional-scale, spatial distribution of titanium concentrations. In particular, clusters of anomalous concentrations of titanium occur: (1) along the Fall Zone, from Virginia to Alabama, where metamorphic and igneous rocks of the Piedmont region contact younger sediments of the Coastal Plain; (2) a paleovalley near the South Carolina and North Carolina border; (3) the upper and middle Atlantic Coastal Plain of North Carolina; (4) the majority of the Atlantic Coastal Plain of Virginia; and (5) barrier islands and stretches of the modern shoreline from South Carolina to northeast Florida. The areas mapped by this study could help mining companies delimit areas for exploration.
Abstract Linguistic Structure Correlates with Temporal Activity during Naturalistic Comprehension
Brennan, Jonathan R.; Stabler, Edward P.; Van Wagenen, Sarah E.; Luh, Wen-Ming; Hale, John T.
2016-01-01
Neurolinguistic accounts of sentence comprehension identify a network of relevant brain regions, but do not detail the information flowing through them. We investigate syntactic information. Does brain activity implicate a computation over hierarchical grammars or does it simply reflect linear order, as in a Markov chain? To address this question, we quantify the cognitive states implied by alternative parsing models. We compare processing-complexity predictions from these states against fMRI timecourses from regions that have been implicated in sentence comprehension. We find that hierarchical grammars independently predict timecourses from left anterior and posterior temporal lobe. Markov models are predictive in these regions and across a broader network that includes the inferior frontal gyrus. These results suggest that while linear effects are wide-spread across the language network, certain areas in the left temporal lobe deal with abstract, hierarchical syntactic representations. PMID:27208858
Stability of glassy hierarchical networks
NASA Astrophysics Data System (ADS)
Zamani, M.; Camargo-Forero, L.; Vicsek, T.
2018-02-01
The structure of interactions in most animal and human societies can be best represented by complex hierarchical networks. In order to maintain close-to-optimal function both stability and adaptability are necessary. Here we investigate the stability of hierarchical networks that emerge from the simulations of an organization type with an efficiency function reminiscent of the Hamiltonian of spin glasses. Using this quantitative approach we find a number of expected (from everyday observations) and highly non-trivial results for the obtained locally optimal networks, including, for example: (i) stability increases with growing efficiency and level of hierarchy; (ii) the same perturbation results in a larger change for more efficient states; (iii) networks with a lower level of hierarchy become more efficient after perturbation; (iv) due to the huge number of possible optimal states only a small fraction of them exhibit resilience and, finally, (v) ‘attacks’ targeting the nodes selectively (regarding their position in the hierarchy) can result in paradoxical outcomes.
Hierarchical Hopping through Localized States in a Random Potential
NASA Astrophysics Data System (ADS)
Rajan, Harihar; Srivastava, Vipin
2003-03-01
Generalisation of Mott's idea on (low - temperature, large-time), Variable-range-hopping is considered to include hopping at some what higher temperature(that do not kill localization). These transitions complement the variable- range-hopping in that they do not conserve energy and occur at relatively lower time scales. The hopper picks the next state in a hierarchical fashion in accordance with certain conditions. The results are found to tie up nicely with an interesting property pertaining to the energy dependence of localized states. Acknowlwdgements: One of us(VS) would like to thank Association of Commonwealth Universities and Leverhulme Trust for financial help and to Sir Sam Edwards for hospitality at Cavendish Laboratory,Cambridge CB3 0HE.
A hierarchical approach to reliability modeling of fault-tolerant systems. M.S. Thesis
NASA Technical Reports Server (NTRS)
Gossman, W. E.
1986-01-01
A methodology for performing fault tolerant system reliability analysis is presented. The method decomposes a system into its subsystems, evaluates vent rates derived from the subsystem's conditional state probability vector and incorporates those results into a hierarchical Markov model of the system. This is done in a manner that addresses failure sequence dependence associated with the system's redundancy management strategy. The method is derived for application to a specific system definition. Results are presented that compare the hierarchical model's unreliability prediction to that of a more complicated tandard Markov model of the system. The results for the example given indicate that the hierarchical method predicts system unreliability to a desirable level of accuracy while achieving significant computational savings relative to component level Markov model of the system.
McCaughey, Deirdre; DelliFraine, Jami; Erwin, Cathleen O
2015-01-01
Hospitals in North America consistently have employee injury rates ranking among the highest of all industries. Organizations that mandate workplace safety training and emphasize safety compliance tend to have lower injury rates and better employee safety perceptions. However, it is unclear if the work environment in different national health care systems (United States vs. Canada) is associated with different employee safety perceptions or injury rates. This study examines occupational safety and workplace satisfaction in two different countries with employees working for the same organization. Survey data were collected from environmental services employees (n = 148) at three matched hospitals (two in Canada and one in the United States). The relationships that were examined included: (1) safety leadership and safety training with individual/unit safety perceptions; (2) supervisor and coworker support with individual job satisfaction and turnover intention; and (3) unit turnover, labor usage, and injury rates. Hierarchical regression analysis and ANO VA found safety leadership and safety training to be positively related to individual safety perceptions, and unit safety grade and effects were similar across all hospitals. Supervisor and coworker support were found to be related to individual and organizational outcomes and significant differences were found across the hospitals. Significant differences were found in injury rates, days missed, and turnover across the hospitals. This study offers support for occupational safety training as a viable mechanism to reduce employee injury rates and that a codified training program translates across national borders. Significant differences were found.between the hospitals with respect to employee and organizational outcomes (e.g., turnover). These findings suggest that work environment differences are reflective of the immediate work group and environment, and may reflect national health care system differences.
2015-01-01
Microsupercapacitors (MSCs) are promising energy storage devices to power miniaturized portable electronics and microelectromechanical systems. With the increasing attention on all-solid-state flexible supercapacitors, new strategies for high-performance flexible MSCs are highly desired. Here, we demonstrate all-solid-state, flexible micropseudocapacitors via direct laser patterning on crack-free, flexible WO3/polyvinylidene fluoride (PVDF)/multiwalled carbon nanotubes (MWCNTs) composites containing high levels of porous hierarchically structured WO3 nanomaterials (up to 50 wt %) and limited binder (PVDF, <25 wt %). The work leads to an areal capacitance of 62.4 mF·cm–2 and a volumetric capacitance of 10.4 F·cm–3, exceeding that of graphene based flexible MSCs by a factor of 26 and 3, respectively. As a noncarbon based flexible MSC, hierarchically nanostructured WO3 in the narrow finger electrode is essential to such enhancement in energy density due to its pseudocapacitive property. The effects of WO3/PVDF/MWCNTs composite composition and the dimensions of interdigital structure on the performance of the flexible MSCs are investigated. PMID:26618406
A Hierarchical Bayesian Model for Crowd Emotions
Urizar, Oscar J.; Baig, Mirza S.; Barakova, Emilia I.; Regazzoni, Carlo S.; Marcenaro, Lucio; Rauterberg, Matthias
2016-01-01
Estimation of emotions is an essential aspect in developing intelligent systems intended for crowded environments. However, emotion estimation in crowds remains a challenging problem due to the complexity in which human emotions are manifested and the capability of a system to perceive them in such conditions. This paper proposes a hierarchical Bayesian model to learn in unsupervised manner the behavior of individuals and of the crowd as a single entity, and explore the relation between behavior and emotions to infer emotional states. Information about the motion patterns of individuals are described using a self-organizing map, and a hierarchical Bayesian network builds probabilistic models to identify behaviors and infer the emotional state of individuals and the crowd. This model is trained and tested using data produced from simulated scenarios that resemble real-life environments. The conducted experiments tested the efficiency of our method to learn, detect and associate behaviors with emotional states yielding accuracy levels of 74% for individuals and 81% for the crowd, similar in performance with existing methods for pedestrian behavior detection but with novel concepts regarding the analysis of crowds. PMID:27458366
Huang, Xuezhen; Liu, Hewei; Zhang, Xi; Jiang, Hongrui
2015-12-23
Microsupercapacitors (MSCs) are promising energy storage devices to power miniaturized portable electronics and microelectromechanical systems. With the increasing attention on all-solid-state flexible supercapacitors, new strategies for high-performance flexible MSCs are highly desired. Here, we demonstrate all-solid-state, flexible micropseudocapacitors via direct laser patterning on crack-free, flexible WO3/polyvinylidene fluoride (PVDF)/multiwalled carbon nanotubes (MWCNTs) composites containing high levels of porous hierarchically structured WO3 nanomaterials (up to 50 wt %) and limited binder (PVDF, <25 wt %). The work leads to an areal capacitance of 62.4 mF·cm(-2) and a volumetric capacitance of 10.4 F·cm(-3), exceeding that of graphene based flexible MSCs by a factor of 26 and 3, respectively. As a noncarbon based flexible MSC, hierarchically nanostructured WO3 in the narrow finger electrode is essential to such enhancement in energy density due to its pseudocapacitive property. The effects of WO3/PVDF/MWCNTs composite composition and the dimensions of interdigital structure on the performance of the flexible MSCs are investigated.
Khoshnood, B; Pryde, P; Blondel, B; Lee, K S
2003-12-01
Previous studies have shown socioeconomic disparities in the use of prenatal diagnosis in several countries, including France and the United States. Few studies however, have examined the impact of socioeconomic differences in prenatal testing on disparities in the live birth prevalence of congenital anomalies. In this article, we first review and further discuss some of the results of our previously published work that assesses: i) socioeconomic differences in the use of amniocentesis in the United States using data from national birth cohorts; and ii) impact of socioeconomic differences in prenatal diagnosis on the live birth prevalence of Down's syndrome (trisomy 21). We then present the results of a study that explores the potential effects of public policies regarding abortion on state-level differences in the live birth prevalence of Down's syndrome. We used birth data from the National Center for Health Statistics for the years 1989 to 1991 as well as data from the National Abortion and Reproductive Rights Action League (NARAL) state-by-state review of abortion rights. The main individual-level socioeconomic variables in the analyses were maternal ethnicity and education; the analyses of the interaction effects between maternal age and ethnicity are presented here. Interaction effects were assessed using logistic regression models with likelihood ratio tests. We used hierarchical logistic regression models for analyses of state-level effects while controlling for individual-level socioeconomic factors. We found substantial age-specific socioeconomic differences in the use of amniocentesis and in the rates of age-related increase in the live birth prevalence of Down's syndrome. In particular, African Americans and Mexican Americans were found to have lower odds of amniocentesis use and higher odds of Down's syndrome at birth. In addition, after controlling for maternal age, socioeconomic factors and prenatal care, we found that states which allowed public financing of abortion services for all or most circumstances had lower odds of Down's syndrome at birth. Unless socioeconomic differences in prenatal testing are addressed, the increasing use of prenatal testing might result in widening socioeconomic disparities in the live birth prevalence of Down's syndrome and other major congenital anomalies in future years.
NASA Astrophysics Data System (ADS)
Kashim, Rosmaini; Kasim, Maznah Mat; Rahman, Rosshairy Abd
2015-12-01
Measuring university performance is essential for efficient allocation and utilization of educational resources. In most of the previous studies, performance measurement in universities emphasized the operational efficiency and resource utilization without investigating the university's ability to fulfill the needs of its stakeholders and society. Therefore, assessment of the performance of university should be separated into two stages namely efficiency and effectiveness. In conventional DEA analysis, a decision making unit (DMU) or in this context, a university is generally treated as a black-box which ignores the operation and interdependence of the internal processes. When this happens, the results obtained would be misleading. Thus, this paper suggest an alternative framework for measuring the overall performance of a university by incorporating both efficiency and effectiveness and applies network DEA model. The network DEA models are recommended because this approach takes into account the interrelationship between the processes of efficiency and effectiveness in the system. This framework also focuses on the university structure which is expanded from the hierarchical to form a series of horizontal relationship between subordinate units by assuming both intermediate unit and its subordinate units can generate output(s). Three conceptual models are proposed to evaluate the performance of a university. An efficiency model is developed at the first stage by using hierarchical network model. It is followed by an effectiveness model which take output(s) from the hierarchical structure at the first stage as a input(s) at the second stage. As a result, a new overall performance model is proposed by combining both efficiency and effectiveness models. Thus, once this overall model is realized and utilized, the university's top management can determine the overall performance of each unit more accurately and systematically. Besides that, the result from the network DEA model can give a superior benchmarking power over the conventional models.
Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M
2018-05-07
A Bayesian model for sparse, hierarchical, inver-covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fMRI, MEG and EEG data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in MEG beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.
Hierarchical graphs for rule-based modeling of biochemical systems
2011-01-01
Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal) of an edge represents a class of association (dissociation) reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR) complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for specifying rule-based models, such as the BioNetGen language (BNGL). Thus, the proposed use of hierarchical graphs should promote clarity and better understanding of rule-based models. PMID:21288338
A hierarchical clustering methodology for the estimation of toxicity.
Martin, Todd M; Harten, Paul; Venkatapathy, Raghuraman; Das, Shashikala; Young, Douglas M
2008-01-01
ABSTRACT A quantitative structure-activity relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural similarity is defined in terms of 2-D physicochemical descriptors (such as connectivity and E-state indices). A genetic algorithm-based technique is used to generate statistically valid QSAR models for each cluster (using the pool of descriptors described above). The toxicity for a given query compound is estimated using the weighted average of the predictions from the closest cluster from each step in the hierarchical clustering assuming that the compound is within the domain of applicability of the cluster. The hierarchical clustering methodology was tested using a Tetrahymena pyriformis acute toxicity data set containing 644 chemicals in the training set and with two prediction sets containing 339 and 110 chemicals. The results from the hierarchical clustering methodology were compared to the results from several different QSAR methodologies.
Multi-scale chromatin state annotation using a hierarchical hidden Markov model
NASA Astrophysics Data System (ADS)
Marco, Eugenio; Meuleman, Wouter; Huang, Jialiang; Glass, Kimberly; Pinello, Luca; Wang, Jianrong; Kellis, Manolis; Yuan, Guo-Cheng
2017-04-01
Chromatin-state analysis is widely applied in the studies of development and diseases. However, existing methods operate at a single length scale, and therefore cannot distinguish large domains from isolated elements of the same type. To overcome this limitation, we present a hierarchical hidden Markov model, diHMM, to systematically annotate chromatin states at multiple length scales. We apply diHMM to analyse a public ChIP-seq data set. diHMM not only accurately captures nucleosome-level information, but identifies domain-level states that vary in nucleosome-level state composition, spatial distribution and functionality. The domain-level states recapitulate known patterns such as super-enhancers, bivalent promoters and Polycomb repressed regions, and identify additional patterns whose biological functions are not yet characterized. By integrating chromatin-state information with gene expression and Hi-C data, we identify context-dependent functions of nucleosome-level states. Thus, diHMM provides a powerful tool for investigating the role of higher-order chromatin structure in gene regulation.
The physics origin of the hierarchy of bodies in space
NASA Astrophysics Data System (ADS)
Bejan, A.; Wagstaff, R. W.
2016-03-01
Here we show that bodies of the same size suspended uniformly in space constitute a system (a "suspension") in a state of uniform volumetric tension because of mass-to-mass forces of attraction. The system "snaps" hierarchically, and evolves faster to a state of reduced tension when the bodies coalesce spontaneously nonuniformly, i.e., hierarchically, into few large and many small bodies suspended in the same space. Hierarchy, not uniformity, is the design that emerges, and it is in accord with the constructal law. The implications of this principle of physics in natural organization and evolution are discussed.
Efficient propagation of the hierarchical equations of motion using the matrix product state method
NASA Astrophysics Data System (ADS)
Shi, Qiang; Xu, Yang; Yan, Yaming; Xu, Meng
2018-05-01
We apply the matrix product state (MPS) method to propagate the hierarchical equations of motion (HEOM). It is shown that the MPS approximation works well in different type of problems, including boson and fermion baths. The MPS method based on the time-dependent variational principle is also found to be applicable to HEOM with over one thousand effective modes. Combining the flexibility of the HEOM in defining the effective modes and the efficiency of the MPS method thus may provide a promising tool in simulating quantum dynamics in condensed phases.
Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong
2010-01-01
Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information processing. PMID:21852971
NASA Astrophysics Data System (ADS)
Zhang, Yifu; Jiang, Hanmei; Wang, Qiushi; Zheng, Jiqi; Meng, Changgong
2018-07-01
Three-dimensional (3D) porous N, O-doped carbon with hierarchical structures composed of micropores, mesopores and macropores were synthesized by the direct carbonization of kelp with a "self-activation" process. The as-obtained 3D N, O-doped carbon remained abundant N and O functional groups and the BET specific surface area measured 656 m2 g-1. 3D hierarchical porous structures with the pore size ranged from several nanometers to hundred nanometers and lots of pores were attributed to mesopores with the average pore size of about 5.4 nm. Electrochemical properties of the 3D hierarchical porous N, O-doped carbon as a supercapactior (SC) electrode were investigated and it delivered excellent capacitance of 669 mF cm-2 at 1 mA cm-2 due to its 3D hierarchical porous structures with high specific surface area which is beneficial for improving ionic storage and transportation in electrodes. This kelp-derived carbon exhibited excellent cyclic performance with the retention of 104% after 10,000 cycles. A flexible solid-state symmetric SC (SSC) device was fabricated using the 3D hierarchical porous N, O-doped carbon and delivered an excellent capacitance of 412 mF cm-2 at 2 mA cm-2 and satisfying cyclic stability with the retention of 85% after 10,000 cycles. The areal energy density of the SSC device reach up to 0.146 mWh cm-2 at the power density of 0.8 mW cm-2. This facile route for low-cost carbonaceous materials with novel architecture and functionality can be as a promising alternative to synthesize biomass carbon for practical SC application.
Drivers of Variability in Public-Supply Water Use Across the Contiguous United States
NASA Astrophysics Data System (ADS)
Worland, Scott C.; Steinschneider, Scott; Hornberger, George M.
2018-03-01
This study explores the relationship between municipal water use and an array of climate, economic, behavioral, and policy variables across the contiguous U.S. The relationship is explored using Bayesian-hierarchical regression models for over 2,500 counties, 18 covariates, and three higher-level grouping variables. Additionally, a second analysis is included for 83 cities where water price and water conservation policy information is available. A hierarchical model using the nine climate regions (product of National Oceanic and Atmospheric Administration) as the higher-level groups results in the best out-of-sample performance, as estimated by the Widely Available Information Criterion, compared to counties grouped by urban continuum classification or primary economic activity. The regression coefficients indicate that the controls on water use are not uniform across the nation: e.g., counties in the Northeast and Northwest climate regions are more sensitive to social variables, whereas counties in the Southwest and East North Central climate regions are more sensitive to environmental variables. For the national city-level model, it appears that arid cities with a high cost of living and relatively low water bills sell more water per customer, but as with the county-level model, the effect of each variable depends heavily on where a city is located.
Hierarchical information fusion for global displacement estimation in microsensor motion capture.
Meng, Xiaoli; Zhang, Zhi-Qiang; Wu, Jian-Kang; Wong, Wai-Choong
2013-07-01
This paper presents a novel hierarchical information fusion algorithm to obtain human global displacement for different gait patterns, including walking, running, and hopping based on seven body-worn inertial and magnetic measurement units. In the first-level sensor fusion, the orientation for each segment is achieved by a complementary Kalman filter (CKF) which compensates for the orientation error of the inertial navigation system solution through its error state vector. For each foot segment, the displacement is also estimated by the CKF, and zero velocity update is included for the drift reduction in foot displacement estimation. Based on the segment orientations and left/right foot locations, two global displacement estimates can be acquired from left/right lower limb separately using a linked biomechanical model. In the second-level geometric fusion, another Kalman filter is deployed to compensate for the difference between the two estimates from the sensor fusion and get more accurate overall global displacement estimation. The updated global displacement will be transmitted to left/right foot based on the human lower biomechanical model to restrict the drifts in both feet displacements. The experimental results have shown that our proposed method can accurately estimate human locomotion for the three different gait patterns with regard to the optical motion tracker.
Optimal control in microgrid using multi-agent reinforcement learning.
Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin
2012-11-01
This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Matsumoto, Monica M. S.; Beig, Niha G.; Udupa, Jayaram K.; Archer, Steven; Torigian, Drew A.
2014-03-01
Lung cancer is associated with the highest cancer mortality rates among men and women in the United States. The accurate and precise identification of the lymph node stations on computed tomography (CT) images is important for staging disease and potentially for prognosticating outcome in patients with lung cancer, as well as for pretreatment planning and response assessment purposes. To facilitate a standard means of referring to lymph nodes, the International Association for the Study of Lung Cancer (IASLC) has recently proposed a definition of the different lymph node stations and zones in the thorax. However, nodal station identification is typically performed manually by visual assessment in clinical radiology. This approach leaves room for error due to the subjective and potentially ambiguous nature of visual interpretation, and is labor intensive. We present a method of automatically recognizing the mediastinal IASLC-defined lymph node stations by modifying a hierarchical fuzzy modeling approach previously developed for body-wide automatic anatomy recognition (AAR) in medical imagery. Our AAR-lymph node (AAR-LN) system follows the AAR methodology and consists of two steps. In the first step, the various lymph node stations are manually delineated on a set of CT images following the IASLC definitions. These delineations are then used to build a fuzzy hierarchical model of the nodal stations which are considered as 3D objects. In the second step, the stations are automatically located on any given CT image of the thorax by using the hierarchical fuzzy model and object recognition algorithms. Based on 23 data sets used for model building, 22 independent data sets for testing, and 10 lymph node stations, a mean localization accuracy of within 1-6 voxels has been achieved by the AAR-LN system.
NASA Astrophysics Data System (ADS)
Middlebrook, A. M.; Marcolli, C.; Canagaratna, M. R.; Worsnop, D. R.; Bahreini, R.; de Gouw, J. A.; Warneke, C.; Goldan, P. D.; Kuster, W. C.; Williams, E. J.; Lerner, B. M.; Roberts, J. M.; Meagher, J. F.; Fehsenfeld, F. C.; Marchewka, M. L.; Bertman, S. B.
2006-12-01
We applied hierarchical cluster analysis to an Aerodyne aerosol mass spectrometer (AMS) bulk mass spectral dataset collected aboard the NOAA research vessel Ronald H. Brown during the 2002 New England Air Quality Study off the east coast of the United States. Emphasizing the organic peaks, the cluster analysis yielded a series of categories that are distinguishable with respect to their mass spectra and their occurrence as a function of time. The differences between the categories mainly arise from relative intensity changes rather than from the presence or absence of specific peaks. The most frequent category exhibits a strong signal at m/z 44 and represents oxidized organic matter probably originating from both anthropogenic as well as biogenic sources. On the basis of spectral and trace gas correlations, the second most common category with strong signals at m/z 29, 43, and 44 contains contributions from isoprene oxidation products. The third through the fifth most common categories have peak patterns characteristic of monoterpene oxidation products and were most frequently observed when air masses from monoterpene rich regions were sampled. Taken together, the second through the fifth most common categories represent on average 17% of the total organic mass that stems likely from biogenic sources during the ship's cruise. These numbers have to be viewed as lower limits since the most common category was attributed to anthropogenic sources for this calculation. The cluster analysis was also very effective in identifying a few contaminated mass spectra that were not removed during pre-processing. This study demonstrates that hierarchical clustering is a useful tool to analyze the complex patterns of the organic peaks in bulk aerosol mass spectra from a field study.
Fast Low-Rank Bayesian Matrix Completion With Hierarchical Gaussian Prior Models
NASA Astrophysics Data System (ADS)
Yang, Linxiao; Fang, Jun; Duan, Huiping; Li, Hongbin; Zeng, Bing
2018-06-01
The problem of low rank matrix completion is considered in this paper. To exploit the underlying low-rank structure of the data matrix, we propose a hierarchical Gaussian prior model, where columns of the low-rank matrix are assumed to follow a Gaussian distribution with zero mean and a common precision matrix, and a Wishart distribution is specified as a hyperprior over the precision matrix. We show that such a hierarchical Gaussian prior has the potential to encourage a low-rank solution. Based on the proposed hierarchical prior model, a variational Bayesian method is developed for matrix completion, where the generalized approximate massage passing (GAMP) technique is embedded into the variational Bayesian inference in order to circumvent cumbersome matrix inverse operations. Simulation results show that our proposed method demonstrates superiority over existing state-of-the-art matrix completion methods.
Wei Wu; James Clark; James Vose
2010-01-01
Hierarchical Bayesian (HB) modeling allows for multiple sources of uncertainty by factoring complex relationships into conditional distributions that can be used to draw inference and make predictions. We applied an HB model to estimate the parameters and state variables of a parsimonious hydrological model â GR4J â by coherently assimilating the uncertainties from the...
The problem of gestalt in neurobiology.
Sokolov, E N
1997-01-01
The question of gestalts is discussed within the framework of its neuronal mechanisms. Two basic hypotheses are considered: 1) that of gestalts as a result of the hierarchical organization of neurons (gnostic units), and 2) that of gestalts as a result of the synchronization of neurons of a given level. Analysis of published data led to the conclusion that gestalts result from vector coding in the hierarchical organization of neurons. High-frequency oscillations in the gamma range (40-200 Hz) are of endogenous origin, and their function is to reinforce the synaptic inputs to those neurons which are involved in the synthesis of a gestalt.
Convoys of Social Relations in Cross-National Context.
Ajrouch, Kristine J; Fuller, Heather R; Akiyama, Hiroko; Antonucci, Toni C
2018-05-08
This study examines national variations in social networks among older adults across 4 countries in diverse regions of the world: Japan, Lebanon, Mexico, and the United States. The aim is to provide insights into universal as well as unique attributes of social networks in later life. The analyses examine convoy characteristics among adults aged 50+ in metropolitan areas of Japan (N = 557), Lebanon (N = 284), Mexico (N = 556), and the United States (N = 583). Data were collected using the hierarchical mapping technique on representative samples in each locale. Multilevel models were conducted by nation to examine whether convoy characteristics vary by age and closeness. Network size and geographic proximity were dimensions of social networks sensitive to national context. By contrast, how age and feelings of closeness varied with contact frequency and the presence of children in networks revealed universal patterns. Furthermore, feelings of closeness varied by age with regard to size and contact frequency in Lebanon, proximity in Japan, and composition in Mexico. Identifying universal and unique characteristics of social networks in later life provide a preliminary empirical basis upon which to advance a global perspective on convoys of social relations and how they inform policies that can facilitate health and well-being among middle-aged and older people around the world.
Chow, Angela; Eccles, Jacquelynne S; Salmela-Aro, Katariina
2012-11-01
Two independent studies were conducted to extend previous research by examining the associations between task value priority patterns across school subjects and aspirations toward the physical and information technology- (IT-) related sciences. Study 1 measured task values of a sample of 10th graders in the United States (N = 249) across (a) physics and chemistry, (b) math, and (c) English. Study 2 measured task values of a sample of students in the second year of high school in Finland (N = 351) across (a) math and science, (b) Finnish, and (c) the arts and physical education. In both studies, students were classified into groups according to how they ranked math and science in relation to the other subjects. Regression analyses indicated that task value group membership significantly predicted subsequent aspirations toward physical and IT-related sciences measured 1-2 years later. The task value groups who placed the highest priority on math and science were significantly more likely to aspire to physical and IT-related sciences than were the other groups. These findings provide support for the theoretical assumption regarding the predictive role of intraindividual hierarchical patterns of task values for subsequent preferences and choices suggested by the Eccles [Parsons] (1983) expectancy-value model.
Ding, Yew Yoong; Abisheganaden, John; Chong, Wai Fung; Heng, Bee Hoon; Lim, Tow Keang
2013-01-01
We sought to compare the effectiveness of acute geriatric units with usual medical care in reducing short-term mortality among seniors hospitalized for pneumonia in the real world. In a retrospective cohort study, we merged chart and administrative data of seniors aged 65 years and older admitted to acute geriatric units and other medical units for pneumonia at three hospitals over 1 year. The outcome was 30-day mortality. Hierarchical logistic regression modeling was carried out to estimate the treatment effect of acute geriatric units for all seniors, those aged 80 years and older, and those with premorbid ambulation impairment, after adjusting for demographic and clinical characteristics, and accounting for clustering around hospitals. Among 2721 seniors, 30-day mortality was 25.5%. For those admitted to acute geriatric and other medical units, this was 24.2% and 25.8%, respectively. Using hierarchical logistic regression modeling, treatment in acute geriatric units was not associated with significant mortality reduction among all seniors (OR 0.72, 95% CI 0.52-1.00). However, significant mortality reduction was observed in the subgroups of those aged 80 years and older (OR 0.73, 95% CI 0.54-0.99), and with premorbid ambulation impairment (OR 0.65, 95% CI 0.46-0.93). Acute geriatric units reduced short-term mortality among seniors hospitalized for pneumonia who were aged 80 years and older or had premorbid ambulation impairment. Further research is required to determine if this beneficial effect extends to seniors hospitalized for other acute medical disorders. © 2012 Japan Geriatrics Society.
Coevolution of dynamical states and interactions in dynamic networks
NASA Astrophysics Data System (ADS)
Zimmermann, Martín G.; Eguíluz, Víctor M.; San Miguel, Maxi
2004-06-01
We explore the coupled dynamics of the internal states of a set of interacting elements and the network of interactions among them. Interactions are modeled by a spatial game and the network of interaction links evolves adapting to the outcome of the game. As an example, we consider a model of cooperation in which the adaptation is shown to facilitate the formation of a hierarchical interaction network that sustains a highly cooperative stationary state. The resulting network has the characteristics of a small world network when a mechanism of local neighbor selection is introduced in the adaptive network dynamics. The highly connected nodes in the hierarchical structure of the network play a leading role in the stability of the network. Perturbations acting on the state of these special nodes trigger global avalanches leading to complete network reorganization.
Hwang, Wei-Chin; Ting, Julia Y
2008-04-01
This study examines the impact of level of acculturation and acculturative stress on the mental health of Asian American college students. Hierarchical regression analyses were used to clarify the relation between level of acculturation, acculturative stress, and mental health outcomes (psychological distress and clinical depression). Being less identified with mainstream United States culture was associated with higher psychological distress and clinical depression, but lost significance when acculturative stress was introduced into the model. Retention or relinquishing of identification with one's heritage culture was not associated with mental health outcomes. Although understanding level of acculturation can help us identify those at risk, findings suggest that acculturative stress is a more proximal risk factor and increases risk for mental health problems independently of global perceptions of stress.
Hamann, Darla J
2014-08-01
This research examines how the empowerment of residents' family members and nursing home employees in managerial decision making is related to service quality. The study was conducted using data from 33 nursing homes in the United States. Surveys were administered to more than 1,000 employees on-site and mailed to the primary-contact family member of each resident. The resulting multilevel data were analyzed using hierarchical linear modeling. The empowerment of families in decision making was positively associated with their perceptions of service quality. The empowerment of nursing staff in decision making was more strongly related to service quality than the empowerment of nonnursing staff. Among nursing staff, the empowerment of nursing assistants improved service quality more than the empowerment of nurses. © The Author(s) 2013.
When West meets East: a short-term immersion experience in South Korea.
Wallace, Linda S
2007-01-01
The purpose of this study was to explore American student perceptions of caring for Korean patients during a 2 week exchange program. Perceptions of Korea/Koreans focused on five areas: respect, hospitality and gift giving, ability to speak English, hierarchical relationships, and being protective. Their perceptions of personal change focused in four areas: valuing personal cultural experiences, increasing cultural awareness and compassion, seeing people from other ethnic groups as individuals and developing interest in oriental medicine. Four areas of importance identified when caring for Korean patients included showing respect, importance of family, food, and care for post-partum mothers. Differences were experienced between an individualistic, low-context society (United States) and a collectivist, high context society (Korea) where the influence of Confucianism is pervasive.
Guidelines for developing effective health education service in a national health agency.
Ochor, J O
1983-01-01
The constraints facing health education include: the fragmentation and dispersal of health-educational services among different agencies and personnel; lack of policy guidelines; ineffectively organized and inefficiently managed health education systems; poor hierarchical status and inadequacy of resources. To resolve these constraints, national health education systems in health agencies should be developed on the basis of stipulated guidelines that could ensure their viability, efficiency and effectiveness. A study at the African Regional Health Education Centre, Ibadan, Nigeria, has yielded thirty synthesized guidelines. The "guidelines" were empirically tested as an evaluation tool by assessing the operational and organizational status of Oyo State Health Education Unit, Ibadan, Nigeria. These guidelines are adaptable to local conditions to enhance the re-organization, re-orientation and consolidation of health education in national health agencies.
Khan, Diba; Rossen, Lauren M; Hamilton, Brady E; He, Yulei; Wei, Rong; Dienes, Erin
2017-06-01
Teen birth rates have evidenced a significant decline in the United States over the past few decades. Most of the states in the US have mirrored this national decline, though some reports have illustrated substantial variation in the magnitude of these decreases across the U.S. Importantly, geographic variation at the county level has largely not been explored. We used National Vital Statistics Births data and Hierarchical Bayesian space-time interaction models to produce smoothed estimates of teen birth rates at the county level from 2003-2012. Results indicate that teen birth rates show evidence of clustering, where hot and cold spots occur, and identify spatial outliers. Findings from this analysis may help inform efforts targeting the prevention efforts by illustrating how geographic patterns of teen birth rates have changed over the past decade and where clusters of high or low teen birth rates are evident. Published by Elsevier Ltd.
Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003–2012
Khan, Diba; Rossen, Lauren M.; Hamilton, Brady E.; He, Yulei; Wei, Rong; Dienes, Erin
2017-01-01
Teen birth rates have evidenced a significant decline in the United States over the past few decades. Most of the states in the US have mirrored this national decline, though some reports have illustrated substantial variation in the magnitude of these decreases across the U.S. Importantly, geographic variation at the county level has largely not been explored. We used National Vital Statistics Births data and Hierarchical Bayesian space-time interaction models to produce smoothed estimates of teen birth rates at the county level from 2003–2012. Results indicate that teen birth rates show evidence of clustering, where hot and cold spots occur, and identify spatial outliers. Findings from this analysis may help inform efforts targeting the prevention efforts by illustrating how geographic patterns of teen birth rates have changed over the past decade and where clusters of high or low teen birth rates are evident. PMID:28552189
Completing the land resource hierarchy
USDA-ARS?s Scientific Manuscript database
The Land Resource Hierarchy of the NRCS is a hierarchal landscape classification consisting of resource areas which represent both conceptual and spatially discrete landscape units stratifying agency programs and practices. The Land Resource Hierarchy (LRH) scales from discrete points (soil pedon an...
Hierarchical process memory: memory as an integral component of information processing
Hasson, Uri; Chen, Janice; Honey, Christopher J.
2015-01-01
Models of working memory commonly focus on how information is encoded into and retrieved from storage at specific moments. However, in the majority of real-life processes, past information is used continuously to process incoming information across multiple timescales. Considering single unit, electrocorticography, and functional imaging data, we argue that (i) virtually all cortical circuits can accumulate information over time, and (ii) the timescales of accumulation vary hierarchically, from early sensory areas with short processing timescales (tens to hundreds of milliseconds) to higher-order areas with long processing timescales (many seconds to minutes). In this hierarchical systems perspective, memory is not restricted to a few localized stores, but is intrinsic to information processing that unfolds throughout the brain on multiple timescales. “The present contains nothing more than the past, and what is found in the effect was already in the cause.”Henri L Bergson PMID:25980649
Bio-inspired Murray materials for mass transfer and activity
NASA Astrophysics Data System (ADS)
Zheng, Xianfeng; Shen, Guofang; Wang, Chao; Li, Yu; Dunphy, Darren; Hasan, Tawfique; Brinker, C. Jeffrey; Su, Bao-Lian
2017-04-01
Both plants and animals possess analogous tissues containing hierarchical networks of pores, with pore size ratios that have evolved to maximize mass transport and rates of reactions. The underlying physical principles of this optimized hierarchical design are embodied in Murray's law. However, we are yet to realize the benefit of mimicking nature's Murray networks in synthetic materials due to the challenges in fabricating vascularized structures. Here we emulate optimum natural systems following Murray's law using a bottom-up approach. Such bio-inspired materials, whose pore sizes decrease across multiple scales and finally terminate in size-invariant units like plant stems, leaf veins and vascular and respiratory systems provide hierarchical branching and precise diameter ratios for connecting multi-scale pores from macro to micro levels. Our Murray material mimics enable highly enhanced mass exchange and transfer in liquid-solid, gas-solid and electrochemical reactions and exhibit enhanced performance in photocatalysis, gas sensing and as Li-ion battery electrodes.
Luo, Huabin; Yu, Gary; Wu, Bei
2018-01-11
The primary objectives of this study were 1) to examine trends of self-reported cognitive impairment among 5 major racial/ethnic groups during 1997-2015 in the United States and 2) to examine differences in the trends across these groups. Data were from the National Health Interview Survey (NHIS). The sample consisted of 155,682 people aged 60 or older. Respondents were asked to report whether any family member was "limited in any way because of difficulty remembering or because of experiencing periods of confusion." Race/ethnicity categories were non-Hispanic white, non-Hispanic black, Native American, Hispanic, and Asian. We applied hierarchical age-period-cohort cross-classified random-effects models for the trend analysis. All analyses accounted for the complex survey design of NHIS. The overall rate of self-reported cognitive impairment increased from 5.7% in 1997 to 6.7% in 2015 (P for trend <.001). Among non-Hispanic white respondents, the rate increased from 5.2% in 1997 to 6.1% in 2015 (slope = 0.14, P for trend <.001). We observed no significant trend in rate of cognitive impairment in other groups. After we controlled for covariates, we found that Asian (B = 0.31), non-Hispanic black (B = 0.37), Hispanic (B = 0.25), and Native American (B = 0.87) respondents were more likely than non-Hispanic white respondents to report cognitive impairment (P <.001 for all). We found an increased rate of self-reported cognitive impairment in older adults of 5 major racial/ethnic groups from 1997 through 2015 in the United States. However, the rate of self-reported cognitive impairment was low, which may suggest underreporting. There is a need to further promote awareness of the disease among individuals, family members, and health care providers.
A hierarchical model for estimating change in American Woodcock populations
Sauer, J.R.; Link, W.A.; Kendall, W.L.; Kelley, J.R.; Niven, D.K.
2008-01-01
The Singing-Ground Survey (SGS) is a primary source of information on population change for American woodcock (Scolopax minor). We analyzed the SGS using a hierarchical log-linear model and compared the estimates of change and annual indices of abundance to a route regression analysis of SGS data. We also grouped SGS routes into Bird Conservation Regions (BCRs) and estimated population change and annual indices using BCRs within states and provinces as strata. Based on the hierarchical model?based estimates, we concluded that woodcock populations were declining in North America between 1968 and 2006 (trend = -0.9%/yr, 95% credible interval: -1.2, -0.5). Singing-Ground Survey results are generally similar between analytical approaches, but the hierarchical model has several important advantages over the route regression. Hierarchical models better accommodate changes in survey efficiency over time and space by treating strata, years, and observers as random effects in the context of a log-linear model, providing trend estimates that are derived directly from the annual indices. We also conducted a hierarchical model analysis of woodcock data from the Christmas Bird Count and the North American Breeding Bird Survey. All surveys showed general consistency in patterns of population change, but the SGS had the shortest credible intervals. We suggest that population management and conservation planning for woodcock involving interpretation of the SGS use estimates provided by the hierarchical model.
Scholes, Edwin
2008-01-01
Ethology is rooted in the idea that behavior is composed of discrete units and sub-units that can be compared among taxa in a phylogenetic framework. This means that behavior, like morphology and genes, is inherently modular. Yet, the concept of modularity is not well integrated into how we envision the behavioral components of phenotype. Understanding ethological modularity, and its implications for animal phenotype organization and evolution, requires that we construct interpretive schemes that permit us to examine it. In this study, I describe the structure and composition of a complex part of the behavioral phenotype of Parotia lawesii Ramsay, 1885--a bird of paradise (Aves: Paradisaeidae) from the forests of eastern New Guinea. I use archived voucher video clips, photographic ethograms, and phenotype ontology diagrams to describe the modular units comprising courtship at various levels of integration. Results show P. lawesii to have 15 courtship and mating behaviors (11 males, 4 females) hierarchically arranged within a complex seven-level structure. At the finest level examined, male displays are comprised of 49 modular sub-units (elements) differentially employed to form more complex modular units (phases and versions) at higher-levels of integration. With its emphasis on hierarchical modularity, this study provides an important conceptual framework for understanding courtship-related phenotypic complexity and provides a solid basis for comparative study of the genus Parotia.
Cable deformation simulation and a hierarchical framework for Nb3Sn Rutherford cables
DOE Office of Scientific and Technical Information (OSTI.GOV)
Arbelaez, D.; Prestemon, S. O.; Ferracin, P.
2009-09-13
Knowledge of the three-dimensional strain state induced in the superconducting filaments due to loads on Rutherford cables is essential to analyze the performance of Nb{sub 3}Sn magnets. Due to the large range of length scales involved, we develop a hierarchical computational scheme that includes models at both the cable and strand levels. At the Rutherford cable level, where the strands are treated as a homogeneous medium, a three-dimensional computational model is developed to determine the deformed shape of the cable that can subsequently be used to determine the strain state under specified loading conditions, which may be of thermal, magnetic,more » and mechanical origins. The results can then be transferred to the model at the strand/macro-filament level for rod restack process (RRP) strands, where the geometric details of the strand are included. This hierarchical scheme can be used to estimate the three-dimensional strain state in the conductor as well as to determine the effective properties of the strands and cables from the properties of individual components. Examples of the modeling results obtained for the orthotropic mechanical properties of the Rutherford cables are presented.« less
Multimodal emotional state recognition using sequence-dependent deep hierarchical features.
Barros, Pablo; Jirak, Doreen; Weber, Cornelius; Wermter, Stefan
2015-12-01
Emotional state recognition has become an important topic for human-robot interaction in the past years. By determining emotion expressions, robots can identify important variables of human behavior and use these to communicate in a more human-like fashion and thereby extend the interaction possibilities. Human emotions are multimodal and spontaneous, which makes them hard to be recognized by robots. Each modality has its own restrictions and constraints which, together with the non-structured behavior of spontaneous expressions, create several difficulties for the approaches present in the literature, which are based on several explicit feature extraction techniques and manual modality fusion. Our model uses a hierarchical feature representation to deal with spontaneous emotions, and learns how to integrate multiple modalities for non-verbal emotion recognition, making it suitable to be used in an HRI scenario. Our experiments show that a significant improvement of recognition accuracy is achieved when we use hierarchical features and multimodal information, and our model improves the accuracy of state-of-the-art approaches from 82.5% reported in the literature to 91.3% for a benchmark dataset on spontaneous emotion expressions. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
The default-mode, ego-functions and free-energy: a neurobiological account of Freudian ideas
Friston, K. J.
2010-01-01
This article explores the notion that Freudian constructs may have neurobiological substrates. Specifically, we propose that Freud’s descriptions of the primary and secondary processes are consistent with self-organized activity in hierarchical cortical systems and that his descriptions of the ego are consistent with the functions of the default-mode and its reciprocal exchanges with subordinate brain systems. This neurobiological account rests on a view of the brain as a hierarchical inference or Helmholtz machine. In this view, large-scale intrinsic networks occupy supraordinate levels of hierarchical brain systems that try to optimize their representation of the sensorium. This optimization has been formulated as minimizing a free-energy; a process that is formally similar to the treatment of energy in Freudian formulations. We substantiate this synthesis by showing that Freud’s descriptions of the primary process are consistent with the phenomenology and neurophysiology of rapid eye movement sleep, the early and acute psychotic state, the aura of temporal lobe epilepsy and hallucinogenic drug states. PMID:20194141
Chang, Xiao; Liu, Shuai; Yu, Yong-Tao; Li, Yi-Xue; Li, Yuan-Yuan
2010-08-12
The Saccharopolyspora erythraea genome sequence was released in 2007. In order to look at the gene regulations at whole transcriptome level, an expression microarray was specifically designed on the S. erythraea strain NRRL 2338 genome sequence. Based on these data, we set out to investigate the potential transcriptional regulatory networks and their organization. In view of the hierarchical structure of bacterial transcriptional regulation, we constructed a hierarchical coexpression network at whole transcriptome level. A total of 27 modules were identified from 1255 differentially expressed transcript units (TUs) across time course, which were further classified in to four groups. Functional enrichment analysis indicated the biological significance of our hierarchical network. It was indicated that primary metabolism is activated in the first rapid growth phase (phase A), and secondary metabolism is induced when the growth is slowed down (phase B). Among the 27 modules, two are highly correlated to erythromycin production. One contains all genes in the erythromycin-biosynthetic (ery) gene cluster and the other seems to be associated with erythromycin production by sharing common intermediate metabolites. Non-concomitant correlation between production and expression regulation was observed. Especially, by calculating the partial correlation coefficients and building the network based on Gaussian graphical model, intrinsic associations between modules were found, and the association between those two erythromycin production-correlated modules was included as expected. This work created a hierarchical model clustering transcriptome data into coordinated modules, and modules into groups across the time course, giving insight into the concerted transcriptional regulations especially the regulation corresponding to erythromycin production of S. erythraea. This strategy may be extendable to studies on other prokaryotic microorganisms.
NASA Technical Reports Server (NTRS)
Tanaka, K. L.; Dohm, J. M.; Irwin, R.; Kolb, E. J.; Skinner, J. A., Jr.; Hare, T. M.
2010-01-01
We are in the fourth year of a fiveyear effort to map the global geology of Mars at 1:20M scale using mainly Mars Global Surveyor, Mars Express, and Mars Odyssey image and altimetry datasets. Previously, we reported on details of project management, mapping datasets (local and regional), initial and anticipated mapping approaches, and tactics of map unit delineation and description [1-2]. Last year, we described mapping and unit delineation results thus far, a new unit identified in the northern plains, and remaining steps to complete the map [3].
Deep hierarchical attention network for video description
NASA Astrophysics Data System (ADS)
Li, Shuohao; Tang, Min; Zhang, Jun
2018-03-01
Pairing video to natural language description remains a challenge in computer vision and machine translation. Inspired by image description, which uses an encoder-decoder model for reducing visual scene into a single sentence, we propose a deep hierarchical attention network for video description. The proposed model uses convolutional neural network (CNN) and bidirectional LSTM network as encoders while a hierarchical attention network is used as the decoder. Compared to encoder-decoder models used in video description, the bidirectional LSTM network can capture the temporal structure among video frames. Moreover, the hierarchical attention network has an advantage over single-layer attention network on global context modeling. To make a fair comparison with other methods, we evaluate the proposed architecture with different types of CNN structures and decoders. Experimental results on the standard datasets show that our model has a more superior performance than the state-of-the-art techniques.
Mee, Jonathan A; Bernatchez, Louis; Reist, Jim D; Rogers, Sean M; Taylor, Eric B
2015-01-01
The concept of the designatable unit (DU) affords a practical approach to identifying diversity below the species level for conservation prioritization. However, its suitability for defining conservation units in ecologically diverse, geographically widespread and taxonomically challenging species complexes has not been broadly evaluated. The lake whitefish species complex (Coregonus spp.) is geographically widespread in the Northern Hemisphere, and it contains a great deal of variability in ecology and evolutionary legacy within and among populations, as well as a great deal of taxonomic ambiguity. Here, we employ a set of hierarchical criteria to identify DUs within the Canadian distribution of the lake whitefish species complex. We identified 36 DUs based on (i) reproductive isolation, (ii) phylogeographic groupings, (iii) local adaptation and (iv) biogeographic regions. The identification of DUs is required for clear discussion regarding the conservation prioritization of lake whitefish populations. We suggest conservation priorities among lake whitefish DUs based on biological consequences of extinction, risk of extinction and distinctiveness. Our results exemplify the need for extensive genetic and biogeographic analyses for any species with broad geographic distributions and the need for detailed evaluation of evolutionary history and adaptive ecological divergence when defining intraspecific conservation units. PMID:26029257
Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)
NASA Astrophysics Data System (ADS)
Raskovic, Dejan
Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.
Testing the apparent resistance of three dominant plants to chronic drought on the Colorado Plateau
Hoover, David L.; Duniway, Michael C.; Belnap, Jayne
2016-01-01
Many drylands, including the south-western United States, are projected to become more water-limited as these regions become warmer and drier with climate change. Such chronic drought may push individual species or plant functional types beyond key thresholds leading to reduced growth or even mortality. Indeed, recent observational and experimental evidence from the Colorado Plateau suggests that C3 grasses are the most vulnerable to chronic drought, while C4 grasses and C3 shrubs appear to have greater resistance.The effects of chronic, or press-drought are predicted to begin at the physiological level and translate up to higher hierarchical levels. To date, the drought resistance of C4grasses and C3 shrubs in this region has been only evaluated at the community level and thus we lack information on whether there are sensitivities to drought at lower hierarchical levels. In this study, we tested the apparent drought resistance of three dominant species (Pleuraphis jamesii, a C4 rhizomatous grass; Coleogyne ramosissima, a C3 drought-deciduous shrub; and Ephedra viridis, a C3 evergreen shrub) to an ongoing experimental press-drought (-35% precipitation) by comparing individual-level responses (ecophysiology and growth dynamics) to community-level responses (plant cover).For all three species, we observed consistent responses across all hierarchical levels:P. jamesii was sensitive to drought across all measured variables, while the shrubsC. ramosissima and E. viridis had little to no responses to the experimental press-drought at any given level.Synthesis. Our findings suggest that the apparent drought resistance at higher hierarchical levels, such as cover, may serve as good proxies for lower-level responses. Furthermore, it appears the shrubs are avoiding drought, possibly by utilizing moisture at deeper soil layers, while the grasses are limited to shallower layers and must endure the drought conditions. Give this differential sensitivity to drought, a future with less precipitation and higher temperatures may increase the dominance of shrubs on the Colorado Plateau, as grasses succumb to chronic water stress.
DeWalt, R. Edward; Cao, Yong; Tweddale, Tari; Grubbs, Scott A.; Hinz, Leon; Pessino, Massimo; Robinson, Jason L.
2012-01-01
Abstract Ohio is an eastern USA state that historically was >70% covered in upland and mixed coniferous forest; about 60% of it glaciated by the Wisconsinan glacial episode. Its stonefly fauna has been studied in piecemeal fashion until now. The assemblage of Ohio stoneflies was assessed from over 4,000 records accumulated from 18 institutions, new collections, and trusted literature sources. Species richness totaled 102 with estimators Chao2 and ICE Mean predicting 105.6 and 106.4, respectively. Singletons and doubletons totaled 18 species. All North American families were represented with Perlidae accounted for the highest number of species at 34. The family Peltoperlidae contributed a single species. Most species had univoltine–fast life cycles with the vast majority emerging in summer, although there was a significant component of winter stoneflies. Nine United States Geological Survey hierarchical drainage units level 6 (HUC6) were used to stratify specimen data. Species richness was significantly related to the number of unique HUC6 locations, but there was no relationship with HUC6 drainage area. A nonparametric multidimensional scaling analysis found that larger HUC6s in the western part of the state had similar assemblages with lower species richness that were found to align with more savanna and wetland habitat. Other drainages having richer assemblages were aligned with upland deciduous and mixed coniferous forests of the east and south where slopes were higher. The Ohio assemblage was most similar to the well–studied fauna of Indiana (88 spp.) and Kentucky (108 spp.), two neighboring states. Many rare species and several high quality stream reaches should be considered for greater protection. PMID:22539876
ERIC Educational Resources Information Center
Reeve, Charlie L.; Basalik, Debra
2011-01-01
The current study examines the degree to which state intellectual capital, state religiosity and reproductive health form a meaningful nexus of ecological relations. Though the specific magnitude of effects vary across outcomes, results from hierarchical regression analyses were consistent with the hypothesized path model indicating that a state's…
Bled, F.; Royle, J. Andrew; Cam, E.
2011-01-01
Invasive species are regularly claimed as the second threat to biodiversity. To apply a relevant response to the potential consequences associated with invasions (e.g., emphasize management efforts to prevent new colonization or to eradicate the species in places where it has already settled), it is essential to understand invasion mechanisms and dynamics. Quantifying and understanding what influences rates of spatial spread is a key research area for invasion theory. In this paper, we develop a model to account for occupancy dynamics of an invasive species. Our model extends existing models to accommodate several elements of invasive processes; we chose the framework of hierarchical modeling to assess site occupancy status during an invasion. First, we explicitly accounted for spatial structure and how distance among sites and position relative to one another affect the invasion spread. In particular, we accounted for the possibility of directional propagation and provided a way of estimating the direction of this possible spread. Second, we considered the influence of local density on site occupancy. Third, we decided to split the colonization process into two subprocesses, initial colonization and recolonization, which may be ground-breaking because these subprocesses may exhibit different relationships with environmental variations (such as density variation) or colonization history (e.g., initial colonization might facilitate further colonization events). Finally, our model incorporates imperfection in detection, which might be a source of substantial bias in estimating population parameters. We focused on the case of the Eurasian Collared-Dove (Streptopelia decaocto) and its invasion of the United States since its introduction in the early 1980s, using data from the North American BBS (Breeding Bird Survey). The Eurasian Collared-Dove is one of the most successful invasive species, at least among terrestrial vertebrates. Our model provided estimation of the spread direction consistent with empirical observations. Site persistence probability exhibits a quadratic response to density. We also succeeded at detecting differences in the relationship between density and initial colonization vs. recolonization probabilities. We provide a map of sites that may be colonized in the future as an example of possible practical application of our work. ?? 2011 by the Ecological Society of America.
Hierarchical graphs for better annotations of rule-based models of biochemical systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hu, Bin; Hlavacek, William
2009-01-01
In the graph-based formalism of the BioNetGen language (BNGL), graphs are used to represent molecules, with a colored vertex representing a component of a molecule, a vertex label representing the internal state of a component, and an edge representing a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions, with a rule that specifies addition (removal) of an edge representing a class of association (dissociation) reactions and with a rule that specifies a change of vertex label representing a class of reactions that affect the internal state of amore » molecular component. A set of rules comprises a mathematical/computational model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Here, for purposes of model annotation, we propose an extension of BNGL that involves the use of hierarchical graphs to represent (1) relationships among components and subcomponents of molecules and (2) relationships among classes of reactions defined by rules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR)/CD3 complex. Likewise, we illustrate how hierarchical graphs can be used to document the similarity of two related rules for kinase-catalyzed phosphorylation of a protein substrate. We also demonstrate how a hierarchical graph representing a protein can be encoded in an XML-based format.« less
Advances in Applications of Hierarchical Bayesian Methods with Hydrological Models
NASA Astrophysics Data System (ADS)
Alexander, R. B.; Schwarz, G. E.; Boyer, E. W.
2017-12-01
Mechanistic and empirical watershed models are increasingly used to inform water resource decisions. Growing access to historical stream measurements and data from in-situ sensor technologies has increased the need for improved techniques for coupling models with hydrological measurements. Techniques that account for the intrinsic uncertainties of both models and measurements are especially needed. Hierarchical Bayesian methods provide an efficient modeling tool for quantifying model and prediction uncertainties, including those associated with measurements. Hierarchical methods can also be used to explore spatial and temporal variations in model parameters and uncertainties that are informed by hydrological measurements. We used hierarchical Bayesian methods to develop a hybrid (statistical-mechanistic) SPARROW (SPAtially Referenced Regression On Watershed attributes) model of long-term mean annual streamflow across diverse environmental and climatic drainages in 18 U.S. hydrological regions. Our application illustrates the use of a new generation of Bayesian methods that offer more advanced computational efficiencies than the prior generation. Evaluations of the effects of hierarchical (regional) variations in model coefficients and uncertainties on model accuracy indicates improved prediction accuracies (median of 10-50%) but primarily in humid eastern regions, where model uncertainties are one-third of those in arid western regions. Generally moderate regional variability is observed for most hierarchical coefficients. Accounting for measurement and structural uncertainties, using hierarchical state-space techniques, revealed the effects of spatially-heterogeneous, latent hydrological processes in the "localized" drainages between calibration sites; this improved model precision, with only minor changes in regional coefficients. Our study can inform advances in the use of hierarchical methods with hydrological models to improve their integration with stream measurements.
Efficient steady-state solver for hierarchical quantum master equations
NASA Astrophysics Data System (ADS)
Zhang, Hou-Dao; Qiao, Qin; Xu, Rui-Xue; Zheng, Xiao; Yan, YiJing
2017-07-01
Steady states play pivotal roles in many equilibrium and non-equilibrium open system studies. Their accurate evaluations call for exact theories with rigorous treatment of system-bath interactions. Therein, the hierarchical equations-of-motion (HEOM) formalism is a nonperturbative and non-Markovian quantum dissipation theory, which can faithfully describe the dissipative dynamics and nonlinear response of open systems. Nevertheless, solving the steady states of open quantum systems via HEOM is often a challenging task, due to the vast number of dynamical quantities involved. In this work, we propose a self-consistent iteration approach that quickly solves the HEOM steady states. We demonstrate its high efficiency with accurate and fast evaluations of low-temperature thermal equilibrium of a model Fenna-Matthews-Olson pigment-protein complex. Numerically exact evaluation of thermal equilibrium Rényi entropies and stationary emission line shapes is presented with detailed discussion.
Bayesian X-ray computed tomography using a three-level hierarchical prior model
NASA Astrophysics Data System (ADS)
Wang, Li; Mohammad-Djafari, Ali; Gac, Nicolas
2017-06-01
In recent decades X-ray Computed Tomography (CT) image reconstruction has been largely developed in both medical and industrial domain. In this paper, we propose using the Bayesian inference approach with a new hierarchical prior model. In the proposed model, a generalised Student-t distribution is used to enforce the Haar transformation of images to be sparse. Comparisons with some state of the art methods are presented. It is shown that by using the proposed model, the sparsity of sparse representation of images is enforced, so that edges of images are preserved. Simulation results are also provided to demonstrate the effectiveness of the new hierarchical model for reconstruction with fewer projections.
Hierarchical structure of biological systems
Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M
2014-01-01
A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961
Hierarchical structure of biological systems: a bioengineering approach.
Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M
2014-01-01
A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems.
A Graph-Embedding Approach to Hierarchical Visual Word Mergence.
Wang, Lei; Liu, Lingqiao; Zhou, Luping
2017-02-01
Appropriately merging visual words are an effective dimension reduction method for the bag-of-visual-words model in image classification. The approach of hierarchically merging visual words has been extensively employed, because it gives a fully determined merging hierarchy. Existing supervised hierarchical merging methods take different approaches and realize the merging process with various formulations. In this paper, we propose a unified hierarchical merging approach built upon the graph-embedding framework. Our approach is able to merge visual words for any scenario, where a preferred structure and an undesired structure are defined, and, therefore, can effectively attend to all kinds of requirements for the word-merging process. In terms of computational efficiency, we show that our algorithm can seamlessly integrate a fast search strategy developed in our previous work and, thus, well maintain the state-of-the-art merging speed. To the best of our survey, the proposed approach is the first one that addresses the hierarchical visual word mergence in such a flexible and unified manner. As demonstrated, it can maintain excellent image classification performance even after a significant dimension reduction, and outperform all the existing comparable visual word-merging methods. In a broad sense, our work provides an open platform for applying, evaluating, and developing new criteria for hierarchical word-merging tasks.
Statistical label fusion with hierarchical performance models
Asman, Andrew J.; Dagley, Alexander S.; Landman, Bennett A.
2014-01-01
Label fusion is a critical step in many image segmentation frameworks (e.g., multi-atlas segmentation) as it provides a mechanism for generalizing a collection of labeled examples into a single estimate of the underlying segmentation. In the multi-label case, typical label fusion algorithms treat all labels equally – fully neglecting the known, yet complex, anatomical relationships exhibited in the data. To address this problem, we propose a generalized statistical fusion framework using hierarchical models of rater performance. Building on the seminal work in statistical fusion, we reformulate the traditional rater performance model from a multi-tiered hierarchical perspective. This new approach provides a natural framework for leveraging known anatomical relationships and accurately modeling the types of errors that raters (or atlases) make within a hierarchically consistent formulation. Herein, we describe several contributions. First, we derive a theoretical advancement to the statistical fusion framework that enables the simultaneous estimation of multiple (hierarchical) performance models within the statistical fusion context. Second, we demonstrate that the proposed hierarchical formulation is highly amenable to the state-of-the-art advancements that have been made to the statistical fusion framework. Lastly, in an empirical whole-brain segmentation task we demonstrate substantial qualitative and significant quantitative improvement in overall segmentation accuracy. PMID:24817809
NASA Technical Reports Server (NTRS)
Schmidt, Phillip; Garg, Sanjay
1991-01-01
A framework for a decentralized hierarchical controller partitioning structure is developed. This structure allows for the design of separate airframe and propulsion controllers which, when assembled, will meet the overall design criterion for the integrated airframe/propulsion system. An algorithm based on parameter optimization of the state-space representation for the subsystem controllers is described. The algorithm is currently being applied to an integrated flight propulsion control design example.
Nurses' perspectives on the intersection of safety and informed decision making in maternity care.
Jacobson, Carrie H; Zlatnik, Marya G; Kennedy, Holly Powell; Lyndon, Audrey
2013-01-01
To explore maternity nurses' perceptions of women's informed decision making during labor and birth to better understand how interdisciplinary communication challenges might affect patient safety. Constructivist grounded theory. Four hospitals in the western United States. Forty-six (46) nurses and physicians practicing in maternity units. Data collection strategies included individual interviews and participant observation. Data were analyzed using the constant comparative method, dimensional analysis, and situational analysis (Charmaz, 2006; Clarke, 2005; Schatzman, 1991). The nurses' central action of holding off harm encompassed three communication strategies: persuading agreement, managing information, and coaching of mothers and physicians. These strategies were executed in a complex, hierarchical context characterized by varied practice patterns and relationships. Nurses' priorities and patient safety goals were sometimes misaligned with those of physicians, resulting in potentially unsafe communication. The communication strategies nurses employed resulted in intended and unintended consequences with safety implications for mothers and providers and had the potential to trap women in the middle of interprofessional conflicts and differences of opinion. © 2013 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses.
Hierarchal Genetic Stratigraphy: A Framework for Paleoceanography
NASA Astrophysics Data System (ADS)
Busch, R. M.; West, R. R.
1987-04-01
A detailed, genetic stratigraphic framework for paleoceanographic studies can be derived by describing, correlating, interpreting, and predicting stratigraphic sequences relative to a hierarchy of their constituent time-stratigraphic transgressive-regressive units ("T-R units"). T-R unit hierarchies are defined and correlated using lithostratigraphic and paleoecologic data, but correlations can be enhanced or "checked" (tested to confirm or deny) with objective biostratigraphic, magnetostratigraphic, or chemostratigraphic data. Such chronostratigraphies can then be bracketed by radiometric ages, so that average periodicities for T-R units can be calculated and a hierarchal geochronology derived. T-R units are inferred to be the net depositional result of eustatic cycles of sea level change and can be differentiated from autocyclic deepening-shallowing units because the latter are noncorrelative intrabasinally. Boundaries between T-R units are conformable or unconformable "genetic surfaces" of two types: transgressive surfaces and "climate change surfaces". The latter are useful for correlating minor transgressive phases through nonmarine intervals, thereby deriving information linking paleoclimatic and paleoceanographic processes. Permo-Carboniferous sequences can be analyzed relative to a hierarchy of six scales of genetic T-R units having periodicities of 225-300 m.y. (first order), 20-90 m.y. (second order), 7-13 m.y. (third-order), 0.6-3.6 m.y. (fourth order), 300-500 × 10³ years (fifth order), and 50-130 × 10³ years or less (sixth-order). Paleogeographic maps for the time of maximum transgression ("transgressive apex") of successive fifth-order T-R units (5-25 m thick) in the Glenshaw Formation (Upper Pennsylvanian, Northern Appalachian Basin) delineate delta lobes, embayments, islands, and linear seaways. Relative extent of marine inundation on the fifth-order maps was used to delineate fourth-order T-R units, and the fourth-order T-R units constitute the transgressive half of a third-order T-R unit. This third-, fourth-, and fifth-order hierarchy is correlated more than 1200 km (750 miles) to the Western Interior "Basin," and is confirmed with limited objective biostratigraphy.
State-Level Predictors of Food Insecurity among Households with Children
ERIC Educational Resources Information Center
Bartfeld, Judi; Dunifon, Rachel
2006-01-01
This article examines interstate variation in household food security. Using hierarchical modeling, we identify several kinds of state characteristics that appear linked to household food security: the availability and accessibility of federal nutrition assistance programs, policies affecting economic wellbeing of low income families, and states'…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Chao; Xu, Zhijie; Lai, Canhai
A hierarchical model calibration and validation is proposed for quantifying the confidence level of mass transfer prediction using a computational fluid dynamics (CFD) model, where the solvent-based carbon dioxide (CO2) capture is simulated and simulation results are compared to the parallel bench-scale experimental data. Two unit problems with increasing level of complexity are proposed to breakdown the complex physical/chemical processes of solvent-based CO2 capture into relatively simpler problems to separate the effects of physical transport and chemical reaction. This paper focuses on the calibration and validation of the first unit problem, i.e. the CO2 mass transfer across a falling ethanolaminemore » (MEA) film in absence of chemical reaction. This problem is investigated both experimentally and numerically using nitrous oxide (N2O) as a surrogate for CO2. To capture the motion of gas-liquid interface, a volume of fluid method is employed together with a one-fluid formulation to compute the mass transfer between the two phases. Bench-scale parallel experiments are designed and conducted to validate and calibrate the CFD models using a general Bayesian calibration. Two important transport parameters, e.g. Henry’s constant and gas diffusivity, are calibrated to produce the posterior distributions, which will be used as the input for the second unit problem to address the chemical adsorption of CO2 across the MEA falling film, where both mass transfer and chemical reaction are involved.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stewart, Robert N; Piburn, Jesse O; Sorokine, Alexandre
The application of spatiotemporal (ST) analytics to integrated data from major sources such as the World Bank, United Nations, and dozens of others holds tremendous potential for shedding new light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. Realizing this potential first requires an ST data model that addresses challenges in properly merging data from multiple authors, with evolving ontological perspectives, semantical differences, and changing attributes, as well as content that is textual, numeric, categorical, and hierarchical. Equally challenging is the development of analytical and visualization approaches that provide a serious exploration of thismore » integrated data while remaining accessible to practitioners with varied backgrounds. The WSTAMP project at Oak Ridge National Laboratory has yielded two major results in addressing these challenges: 1) development of the WSTAMP database, a significant advance in ST data modeling that integrates 10,000+ attributes covering over 200 nation states spanning over 50 years from over 30 major sources and 2) a novel online ST exploratory and analysis tool providing an array of modern statistical and visualization techniques for analyzing these data temporally, spatially, and spatiotemporally under a standard analytic workflow. We discuss the status of this work and report on major findings. Acknowledgment Prepared by Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, Tennessee 37831-6285, managed by UT-Battelle, LLC for the U. S. Department of Energy under contract no. DEAC05-00OR22725. Copyright This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.« less
Zhang, Dechao; Zhang, Long; Yang, Kun; Wang, Hongqiang; Yu, Chuang; Xu, Di; Xu, Bo; Wang, Li-Min
2017-10-25
Exploration of advanced solid electrolytes with good interfacial stability toward electrodes is a highly relevant research topic for all-solid-state batteries. Here, we report PCL/SN blends integrating with PAN-skeleton as solid polymer electrolyte prepared by a facile method. This polymer electrolyte with hierarchical architectures exhibits high ionic conductivity, large electrochemical windows, high degree flexibility, good flame-retardance ability, and thermal stability (workable at 80 °C). Additionally, it demonstrates superior compatibility and electrochemical stability toward metallic Li as well as LiFePO 4 cathode. The electrolyte/electrode interfaces are very stable even subjected to 4.5 V at charging state for long time. The LiFePO 4 /Li all-solid-state cells based on this electrolyte deliver high capacity, outstanding cycling stability, and superior rate capability better than those based on liquid electrolyte. This solid polymer electrolyte is eligible for next generation high energy density all-solid-state batteries.
NASA Astrophysics Data System (ADS)
Ramanathan, Ramya; Guin, Arijit; Ritzi, Robert W.; Dominic, David F.; Freedman, Vicky L.; Scheibe, Timothy D.; Lunt, Ian A.
2010-04-01
A geometric-based simulation methodology was developed and incorporated into a computer code to model the hierarchical stratal architecture, and the corresponding spatial distribution of permeability, in braided channel belt deposits. The code creates digital models of these deposits as a three-dimensional cubic lattice, which can be used directly in numerical aquifer or reservoir models for fluid flow. The digital models have stratal units defined from the kilometer scale to the centimeter scale. These synthetic deposits are intended to be used as high-resolution base cases in various areas of computational research on multiscale flow and transport processes, including the testing of upscaling theories. The input parameters are primarily univariate statistics. These include the mean and variance for characteristic lengths of sedimentary unit types at each hierarchical level, and the mean and variance of log-permeability for unit types defined at only the lowest level (smallest scale) of the hierarchy. The code has been written for both serial and parallel execution. The methodology is described in part 1 of this paper. In part 2 (Guin et al., 2010), models generated by the code are presented and evaluated.
Modular evolution of the Cetacean vertebral column.
Buchholtz, Emily A
2007-01-01
Modular theory predicts that hierarchical developmental processes generate hierarchical phenotypic units that are capable of independent modification. The vertebral column is an overtly modular structure, and its rapid phenotypic transformation in cetacean evolution provides a case study for modularity. Terrestrial mammals have five morphologically discrete vertebral series that are now known to be coincident with Hox gene expression patterns. Here, I present the hypothesis that in living Carnivora and Artiodactyla, and by inference in the terrestrial ancestors of whales, the series are themselves components of larger precaudal and caudal modular units. Column morphology in a series of fossil and living whales is used to predict the type and sequence of developmental changes responsible for modification of that ancestral pattern. Developmental innovations inferred include independent meristic additions to the precaudal column in basal archaeocetes and basilosaurids, stepwise homeotic reduction of the sacral series in protocetids, and dissociation of the caudal series into anterior tail and fluke subunits in basilosaurids. The most dramatic change was the novel association of lumbar and anterior caudal vertebrae in a module that crosses the precaudal/caudal boundary. This large unit is defined by shared patterns of vertebral morphology, count, and size in all living whales (Neoceti).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ramanathan, Ramya; Guin, Arijit; Ritzi, Robert W.
A geometric-based simulation methodology was developed and incorporated into a computer code to model the hierarchical stratal architecture, and the corresponding spatial distribution of permeability, in braided channel belt deposits. The code creates digital models of these deposits as a three-dimensional cubic lattice, which can be used directly in numerical aquifer or reservoir models for fluid flow. The digital models have stratal units defined from the km scale to the cm scale. These synthetic deposits are intended to be used as high-resolution base cases in various areas of computational research on multiscale flow and transport processes, including the testing ofmore » upscaling theories. The input parameters are primarily univariate statistics. These include the mean and variance for characteristic lengths of sedimentary unit types at each hierarchical level, and the mean and variance of log-permeability for unit types defined at only the lowest level (smallest scale) of the hierarchy. The code has been written for both serial and parallel execution. The methodology is described in Part 1 of this series. In Part 2, models generated by the code are presented and evaluated.« less
Ecoregions of Arizona (poster)
Griffith, Glenn E.; Omernik, James M.; Johnson, Colleen Burch; Turner, Dale S.
2014-01-01
Ecoregions denote areas of general similarity in ecosystems and in the type, quality, and quantity of environmental resources; they are designed to serve as a spatial framework for the research, assessment, management, and monitoring of ecosystems and ecosystem components. By recognizing the spatial differences in the capacities and potentials of ecosystems, ecoregions stratify the environment by its probable response to disturbance. These general purpose regions are critical for structuring and implementing ecosystem management strategies across federal agencies, state agencies, and nongovernment organizations that are responsible for different types of resources within the same geographical areas. The Arizona ecoregion map was compiled at a scale of 1:250,000. It revises and subdivides an earlier national ecoregion map that was originally compiled at a smaller scale. The approach used to compile this map is based on the premise that ecological regions can be identified through the analysis of the spatial patterns and the composition of biotic and abiotic phenomena that affect or reflect differences in ecosystem quality and integrity. These phenomena include geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The relative importance of each characteristic varies from one ecological region to another regardless of the hierarchical level. A Roman numeral hierarchical scheme has been adopted for different levels of ecological regions. Level I is the coarsest level, dividing North America into 15 ecological regions. Level II divides the continent into 50 regions. At level III, the continental United States contains 105 ecoregions and the conterminous United States has 85 ecoregions. Level IV is a further subdivision of level III ecoregions. Arizona contains arid deserts and canyonlands, semiarid shrub- and grass-covered plains, woodland- and shrubland-covered hills, lava fields and volcanic plateaus, forested mountains, glaciated peaks, and river alluvial floodplains. Ecological diversity is remarkably high. There are 7 level III ecoregions and 52 level IV ecoregions in Arizona and many continue into ecologically similar parts of adjacent states. This poster is part of a collaborative project primarily between the U.S. Geological Survey (USGS), USEPA National Health and Environmental Effects Research Laboratory (Corvallis, Oregon), USEPA Region IX, U.S. Department of Agriculture (USDA)–Natural Resources Conservation Service (NRCS), The Nature Conservancy, and several Arizona state agencies. The project is associated with an interagency effort to develop a common national framework of ecological regions. Reaching that objective requires recognition of the differences in the conceptual approaches and mapping methodologies applied to develop the most common ecoregion-type frameworks, including those developed by the USDA–Forest Service, the USEPA, and the NRCS. As each of these frameworks is further refined, their differences are becoming less discernible. Collaborative ecoregion projects, such as this one in Arizona, are a step toward attaining consensus and consistency in ecoregion frameworks for the entire nation.
A Comprehensive System of Energy Intensity Indicators for the U.S.: Methods, Data and Key Trends
DOE Office of Scientific and Technical Information (OSTI.GOV)
Belzer, D. B.
2014-08-01
This report describes a comprehensive system of energy intensity indicators for the United States that has been developed for the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) over the past decade. This system of indicators is hierarchical in nature, beginning with detailed indexes of energy intensity for various sectors of the economy, which are ultimately aggregated to an overall energy intensity index for the economy as a whole. The aggregation of energy intensity indexes to higher levels in the hierarchy is performed with a version of the Log Mean Divisia index (LMDI) method. Based upon themore » data and methods in the system of indicators, the economy-wide energy intensity index shows a decline of about 14% in 2011 relative to a 1985 base year.« less
Literacy Gaps by Educational Attainment: A Cross-National Analysis.
Park, Hyunjoon; Kyei, Pearl
2011-03-01
Existing cross-national research on educational attainment does not fully address whether the same level of educational attainment generates the same level of literacy skills in different countries. We analyze literacy skills data for young adults from 19 countries in the 1994-1998 International Adult Literacy Survey and find that in all countries, individuals with a higher level of educational attainment tend to have greater literacy skills. However, there is substantial variation across countries in the size of literacy gaps by levels of educational attainment. In particular, young adults in the United States show the largest literacy gaps. Using two-level hierarchical linear models, we find that cross-national differences in the literacy gap between more- and less-educated individuals are systematically linked to the degree of between-school inequality in school resources (instructional materials, class size, teachers' experience and certification).
Hierarchical functional modularity in the resting-state human brain.
Ferrarini, Luca; Veer, Ilya M; Baerends, Evelinda; van Tol, Marie-José; Renken, Remco J; van der Wee, Nic J A; Veltman, Dirk J; Aleman, André; Zitman, Frans G; Penninx, Brenda W J H; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, Julien
2009-07-01
Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain. Copyright 2009 Wiley-Liss, Inc
Hao, Pin; Zhao, Zhenhuan; Tian, Jian; Li, Haidong; Sang, Yuanhua; Yu, Guangwei; Cai, Huaqiang; Liu, Hong; Wong, C P; Umar, Ahmad
2014-10-21
Renewable, cost-effective and eco-friendly electrode materials have attracted much attention in the energy conversion and storage fields. Bagasse, the waste product from sugarcane that mainly contains cellulose derivatives, can be a promising candidate to manufacture supercapacitor electrode materials. This study demonstrates the fabrication and characterization of highly porous carbon aerogels by using bagasse as a raw material. Macro and mesoporous carbon was first prepared by carbonizing the freeze-dried bagasse aerogel; consequently, microporous structure was created on the walls of the mesoporous carbon by chemical activation. Interestingly, it was observed that the specific surface area, the pore size and distribution of the hierarchical porous carbon were affected by the activation temperature. In order to evaluate the ability of the hierarchical porous carbon towards the supercapacitor electrode performance, solid state symmetric supercapacitors were assembled, and a comparable high specific capacitance of 142.1 F g(-1) at a discharge current density of 0.5 A g(-1) was demonstrated. The fabricated solid state supercapacitor displayed excellent capacitance retention of 93.9% over 5000 cycles. The high energy storage ability of the hierarchical porous carbon was attributed to the specially designed pore structures, i.e., co-existence of the micropores and mesopores. This research has demonstrated that utilization of sustainable biopolymers as the raw materials for high performance supercapacitor electrode materials is an effective way to fabricate low-cost energy storage devices.
Hierarchical relaxation dynamics in a tilted two-band Bose-Hubbard model
NASA Astrophysics Data System (ADS)
Cosme, Jayson G.
2018-04-01
We numerically examine slow and hierarchical relaxation dynamics of interacting bosons described by a tilted two-band Bose-Hubbard model. The system is found to exhibit signatures of quantum chaos within the spectrum and the validity of the eigenstate thermalization hypothesis for relevant physical observables is demonstrated for certain parameter regimes. Using the truncated Wigner representation in the semiclassical limit of the system, dynamics of relevant observables reveal hierarchical relaxation and the appearance of prethermalized states is studied from the perspective of statistics of the underlying mean-field trajectories. The observed prethermalization scenario can be attributed to different stages of glassy dynamics in the mode-time configuration space due to dynamical phase transition between ergodic and nonergodic trajectories.
Hyperbranched quasi-1D nanostructures for solid-state dye-sensitized solar cells.
Passoni, Luca; Ghods, Farbod; Docampo, Pablo; Abrusci, Agnese; Martí-Rujas, Javier; Ghidelli, Matteo; Divitini, Giorgio; Ducati, Caterina; Binda, Maddalena; Guarnera, Simone; Li Bassi, Andrea; Casari, Carlo Spartaco; Snaith, Henry J; Petrozza, Annamaria; Di Fonzo, Fabio
2013-11-26
In this work we demonstrate hyperbranched nanostructures, grown by pulsed laser deposition, composed of one-dimensional anatase single crystals assembled in arrays of high aspect ratio hierarchical mesostructures. The proposed growth mechanism relies on a two-step process: self-assembly from the gas phase of amorphous TiO2 clusters in a forest of tree-shaped hierarchical mesostructures with high aspect ratio; oriented crystallization of the branches upon thermal treatment. Structural and morphological characteristics can be optimized to achieve both high specific surface area for optimal dye uptake and broadband light scattering thanks to the microscopic feature size. Solid-state dye sensitized solar cells fabricated with arrays of hyperbranched TiO2 nanostructures on FTO-glass sensitized with D102 dye showed a significant 66% increase in efficiency with respect to a reference mesoporous photoanode and reached a maximum efficiency of 3.96% (among the highest reported for this system). This result was achieved mainly thanks to an increase in photogenerated current directly resulting from improved light harvesting efficiency of the hierarchical photoanode. The proposed photoanode overcomes typical limitations of 1D TiO2 nanostructures applied to ss-DSC and emerges as a promising foundation for next-generation high-efficiency solid-state devices comprosed of dyes, polymers, or quantum dots as sensitizers.
Walkey, Allan J; Weinberg, Janice; Wiener, Renda Soylemez; Cooke, Colin R; Lindenauer, Peter K
2018-06-01
To determine between-hospital variation in interventions provided to patients with do not resuscitate (DNR) orders. United States Agency of Healthcare Research and Quality, Healthcare Cost and Utilization Project, California State Inpatient Database. Retrospective cohort study including hospitalized patients aged 40 and older with potential indications for invasive treatments: in-hospital cardiac arrest (indication for CPR), acute respiratory failure (mechanical ventilation), acute renal failure (hemodialysis), septic shock (central venous catheterization), and palliative care. Hierarchical logistic regression to determine associations of hospital "early" DNR rates (DNR order placed within 24 hours of admission) with utilization of invasive interventions. California State Inpatient Database, year 2011. Patients with DNR orders at high-DNR-rate hospitals were less likely to receive invasive mechanical ventilation for acute respiratory failure or hemodialysis for acute renal failure, but more likely to receive palliative care than DNR patients at low-DNR-rate hospitals. Patients without DNR orders experienced similar rates of invasive interventions regardless of hospital DNR rates. Hospitals vary widely in the scope of invasive or organ-supporting treatments provided to patients with DNR orders. © Health Research and Educational Trust.
Global-Local Interactions Modulate Tropical Moisture Exports to the Ohio River Basin
NASA Astrophysics Data System (ADS)
Doss-Gollin, J.; Farnham, D. J.; Lall, U.
2016-12-01
Regional-scale extreme rainfall and flooding are temporally and spatially associated with the occurrence of tropical moisture exports (TMEs) in the Ohio River Basin (ORB). TMEs are related to but not synonymous with atmospheric rivers, which refer to specific filiamentary organizational processes. TMEs to the ORB may be driven by strong, persistent ridging over the Eastern United States and troughing over the Central United States, creating favorable conditions for southerly flow and moisture transport from the Gulf of Mexico and Caribbean Sea. However, the strong inter-annual variation in TME activity over the ORB suggests dependence on global-scale features of the atmospheric circulation. We suggest that this synoptic dipole pattern may be viewed as the passage of one or more high-wavenumber, transient Rossby waves. We build a multi-level hierarchical Bayesian model in which the probability distribution of TME entering the ORB is a function of the phase and amplitude of the traveling waves. In turn, the joint distribution of the phase and amplitude of this wave is modulated by hemispheric-scale features of the atmospheric and oceanic circulation, and the amplitude and synchronization of quasi-stationary Rossby waves with wavenumber 1-4. Our approach bridges information about different features of the atmospheric circulation which inform the predictability of TME at multiple time scales and develops existing understanding of the atmospheric drivers of TMEs beyond existing composite and EOF studies.
The structure and large-scale organization of extreme cold waves over the conterminous United States
NASA Astrophysics Data System (ADS)
Xie, Zuowei; Black, Robert X.; Deng, Yi
2017-12-01
Extreme cold waves (ECWs) occurring over the conterminous United States (US) are studied through a systematic identification and documentation of their local synoptic structures, associated large-scale meteorological patterns (LMPs), and forcing mechanisms external to the US. Focusing on the boreal cool season (November-March) for 1950‒2005, a hierarchical cluster analysis identifies three ECW patterns, respectively characterized by cold surface air temperature anomalies over the upper midwest (UM), northwestern (NW), and southeastern (SE) US. Locally, ECWs are synoptically organized by anomalous high pressure and northerly flow. At larger scales, the UM LMP features a zonal dipole in the mid-tropospheric height field over North America, while the NW and SE LMPs each include a zonal wave train extending from the North Pacific across North America into the North Atlantic. The Community Climate System Model version 4 (CCSM4) in general simulates the three ECW patterns quite well and successfully reproduces the observed enhancements in the frequency of their associated LMPs. La Niña and the cool phase of the Pacific Decadal Oscillation (PDO) favor the occurrence of NW ECWs, while the warm PDO phase, low Arctic sea ice extent and high Eurasian snow cover extent (SCE) are associated with elevated SE-ECW frequency. Additionally, high Eurasian SCE is linked to increases in the occurrence likelihood of UM ECWs.
Haley, Danielle F; Haardörfer, Regine; Kramer, Michael R; Adimora, Adaora A; Wingood, Gina M; Goswami, Neela D; Rubtsova, Anna; Ludema, Christina; Hickson, DeMarc A; Ramirez, Catalina; Ross, Zev; Bolivar, Hector; Cooper, Hannah L F
2017-04-01
Neighborhood characteristics shape sexual risk in HIV-uninfected adults in the United States (US). We assess relationships between census tract characteristics and sexual risk behaviors in a predominantly HIV-infected cohort of women living in the Southern US. This cross-sectional multilevel analysis included data from 737 HIV-infected and HIV-uninfected women enrolled in the Women's Interagency HIV Study. Administrative data captured characteristics of census tracts where women lived; participant-level data were gathered via survey. We used principal components analysis to condense tract-level variables into components: social disorder (e.g., violent crime rate), and social disadvantage (e.g., alcohol outlet density). We used hierarchical generalized linear models to assess relationships between tract-level characteristics and condomless vaginal intercourse, anal intercourse, and condomless anal intercourse. Greater social disorder was associated with less anal intercourse (OR = 0.63, 95% CI = 0.43-0.94) and condomless anal intercourse (OR = 0.49, 95% CI = 0.30-0.80), regardless of HIV status. There were no statistically significant additive or multiplicative interactions between tract characteristics and HIV status. Neighborhood characteristics are associated with sexual risk behaviors among women living in the Southern US, these relationships do not vary by HIV status. Future studies should establish temporality and explore the causal pathways through which neighborhoods influence sexual risk. Copyright © 2017 Elsevier Inc. All rights reserved.
Haley, Danielle F.; Haardörfer, Regine; Kramer, Michael R.; Adimora, Adaora A.; Wingood, Gina M.; Goswami, Neela D.; Rubtsova, Anna; Ludema, Christina; Hickson, DeMarc A.; Ramirez, Catalina; Ross, Zev; Bolivar, Hector; Cooper, Hannah LF
2017-01-01
Introduction Neighborhood characteristics shape sexual risk in HIV-uninfected adults in the United States (US). We assess relationships between census tract characteristics and sexual risk behaviors in a predominantly HIV-infected cohort of women living in the Southern US. Methods This cross-sectional multilevel analysis included data from 737 HIV-infected and HIV-uninfected women enrolled in the Women’s Interagency HIV Study. Administrative data captured characteristics of census tracts where women lived; participant-level data were gathered via survey. We used principal components analysis to condense tract-level variables into components: social disorder (e.g., violent crime rate) and social disadvantage (e.g., alcohol outlet density). We used hierarchical generalized linear models to assess relationships between tract-level characteristics and condomless vaginal intercourse (CVI), anal intercourse (AI), and condomless anal intercourse (CAI). Results Greater social disorder was associated with less AI (OR=0.63, 95% CI=0.43, 0.94) and CAI (OR=0.49, 95% CI=0.30, 0.80), regardless of HIV status. There were no statistically significant additive or multiplicative interactions between tract characteristics and HIV status. Conclusion Neighborhood characteristics are associated with sexual risk behaviors among women living in the Southern US, these relationships do not vary by HIV status. Future studies should establish temporality and explore the causal pathways through which neighborhoods influence sexual risk. PMID:28476327
Convex Clustering: An Attractive Alternative to Hierarchical Clustering
Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth
2015-01-01
The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340
Jo, Young-Moo; Kim, Tae-Hyung; Lee, Chul-Soon; Lim, Kyeorei; Na, Chan Woong; Abdel-Hady, Faissal; Wazzan, Abdulaziz A; Lee, Jong-Heun
2018-03-14
Nearly monodisperse hollow hierarchical Co 3 O 4 nanocages of four different sizes (∼0.3, 1.0, 2.0, and 4.0 μm) consisting of nanosheets were prepared by controlled precipitation of zeolitic imidazolate framework-67 (ZIF-67) rhombic dodecahedra, followed by solvothermal synthesis of Co 3 O 4 nanocages using ZIF-67 self-sacrificial templates, and subsequent heat treatment for the development of high-performance methylbenzene sensors. The sensor based on hollow hierarchical Co 3 O 4 nanocages with the size of ∼1.0 μm exhibited not only ultrahigh responses (resistance ratios) to 5 ppm p-xylene (78.6) and toluene (43.8) but also a remarkably high selectivity to methylbenzene over the interference of ubiquitous ethanol at 225 °C. The unprecedented and high response and selectivity to methylbenzenes are attributed to the highly gas-accessible hollow hierarchical morphology with thin shells, abundant mesopores, and high surface area per unit volume as well as the high catalytic activity of Co 3 O 4 . Moreover, the size, shell thickness, mesopores, and hollow/hierarchical morphology of the nanocages, the key parameters determining the gas response and selectivity, could be well-controlled by tuning the precipitation of ZIF-67 rhombic dodecahedra and solvothermal reaction. This method can pave a new pathway for the design of high-performance methylbenzene sensors for monitoring the quality of indoor air.
Zhang, Lei; Huang, Youju; Wang, Jingyun; Rong, Yun; Lai, Weihua; Zhang, Jiawei; Chen, Tao
2015-05-19
Gold nanoparticles (AuNPs) labeled lateral-flow test strip immunoassay (LFTS) has been widely used in biomedical, feed/food, and environmental analysis fields. Conventional ILFS assay usually uses spherical AuNPs as labeled probes and shows low detection sensitivity, which further limits its widespread practical application. Unlike spherical AuNP used as labeled probe in conventional ILFS, in our present study, a hierarchical flowerlike AuNP specific probe was designed for LFTS and further used to detect Escherichia coli O157:H7 (E. coli O157:H7). Three types of hierarchical flowerlike AuNPs, such as tipped flowerlike, popcornlike, and large-sized flowerlike AuNPs were synthesized in a one-step method. Compared with other two kinds of Au particles, tipped flowerlike AuNPs probes for LFTS particularly exhibited highly sensitive detection of E. coli O157:H7. The remarkable improvement of detection sensitivity of tipped flowerlike AuNPs probes can be achieved even as low as 10(3) colony-forming units (CFU)/mL by taking advantages of its appropriate size and hierarchical structures, which is superior over the detection performance of conventional LFTS. Using this novel tipped flower AuNPs probes, quantitative detection of E. coli O157:H7 can be obtained partially in a wide concentration range with good repeatability. This hierarchical tipped flower-shaped AuNPs probe for LFTS is promising for the practical applications in widespread analysis fields.
Convex clustering: an attractive alternative to hierarchical clustering.
Chen, Gary K; Chi, Eric C; Ranola, John Michael O; Lange, Kenneth
2015-05-01
The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/.
NASA Technical Reports Server (NTRS)
Caines, P. E.
1999-01-01
The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.
Discriminative Hierarchical K-Means Tree for Large-Scale Image Classification.
Chen, Shizhi; Yang, Xiaodong; Tian, Yingli
2015-09-01
A key challenge in large-scale image classification is how to achieve efficiency in terms of both computation and memory without compromising classification accuracy. The learning-based classifiers achieve the state-of-the-art accuracies, but have been criticized for the computational complexity that grows linearly with the number of classes. The nonparametric nearest neighbor (NN)-based classifiers naturally handle large numbers of categories, but incur prohibitively expensive computation and memory costs. In this brief, we present a novel classification scheme, i.e., discriminative hierarchical K-means tree (D-HKTree), which combines the advantages of both learning-based and NN-based classifiers. The complexity of the D-HKTree only grows sublinearly with the number of categories, which is much better than the recent hierarchical support vector machines-based methods. The memory requirement is the order of magnitude less than the recent Naïve Bayesian NN-based approaches. The proposed D-HKTree classification scheme is evaluated on several challenging benchmark databases and achieves the state-of-the-art accuracies, while with significantly lower computation cost and memory requirement.
NASA Astrophysics Data System (ADS)
Jiang, Yu; Suvanto, Mika; Pakkanen, Tapani A.
2016-01-01
Extensive studies have been performed with the aim of fabricating hierarchical surface structures inspired by nature. However, synthetic hierarchical structures have to sacrifice mechanical resistance to functionality by introducing finer scaled structures. Therefore, surfaces are less durable. Surface micro-micro hierarchy has been proven to be effective in replacing micro-nano hierarchy in the sense of superhydrophobicity. However, less attention has been paid to the combined micro-micro hierarchies with surface pillars and pits incorporated together. The fabrication of this type of hierarchy may be less straightforward, with the possibility of being a complicated multi-step process. In this study, we present a simple yet mass producible fabrication method for hierarchical structures with different combinations of surface pillars and pits. The fabrication was based on only one aluminum (Al) mold with sequential mountings. The fabricated structures exhibit high mechanical durability and structural stabilities with a normal load up to 100 kg. In addition, the theoretical estimation of the wetting state shows a promising way of stabilizing a water droplet on the surface pit structures with a more stable Cassie-Baxter state.
A neural network with modular hierarchical learning
NASA Technical Reports Server (NTRS)
Baldi, Pierre F. (Inventor); Toomarian, Nikzad (Inventor)
1994-01-01
This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.
Bio-inspired Murray materials for mass transfer and activity
Zheng, Xianfeng; Shen, Guofang; Wang, Chao; Li, Yu; Dunphy, Darren; Hasan, Tawfique; Brinker, C. Jeffrey; Su, Bao-Lian
2017-01-01
Both plants and animals possess analogous tissues containing hierarchical networks of pores, with pore size ratios that have evolved to maximize mass transport and rates of reactions. The underlying physical principles of this optimized hierarchical design are embodied in Murray's law. However, we are yet to realize the benefit of mimicking nature's Murray networks in synthetic materials due to the challenges in fabricating vascularized structures. Here we emulate optimum natural systems following Murray's law using a bottom-up approach. Such bio-inspired materials, whose pore sizes decrease across multiple scales and finally terminate in size-invariant units like plant stems, leaf veins and vascular and respiratory systems provide hierarchical branching and precise diameter ratios for connecting multi-scale pores from macro to micro levels. Our Murray material mimics enable highly enhanced mass exchange and transfer in liquid–solid, gas–solid and electrochemical reactions and exhibit enhanced performance in photocatalysis, gas sensing and as Li-ion battery electrodes. PMID:28382972
Lunn, David J.; Gould, Oliver E. C.; Whittell, George R.; Armstrong, Daniel P.; Mineart, Kenneth P.; Winnik, Mitchell A.; Spontak, Richard J.; Pringle, Paul G.; Manners, Ian
2016-01-01
Anisotropic nanoparticles prepared from block copolymers are of growing importance as building blocks for the creation of synthetic hierarchical materials. However, the assembly of these structural units is generally limited to the use of amphiphilic interactions. Here we report a simple, reversible coordination-driven hierarchical self-assembly strategy for the preparation of micron-scale fibres and macroscopic films based on monodisperse cylindrical block copolymer micelles. Coordination of Pd(0) metal centres to phosphine ligands immobilized within the soluble coronas of block copolymer micelles is found to induce intermicelle crosslinking, affording stable linear fibres comprised of micelle subunits in a staggered arrangement. The mean length of the fibres can be varied by altering the micelle concentration, reaction stoichiometry or aspect ratio of the micelle building blocks. Furthermore, the fibres aggregate on drying to form robust, self-supporting macroscopic micelle-based thin films with useful mechanical properties that are analogous to crosslinked polymer networks, but on a longer length scale. PMID:27538877
Notes sur les mouvements recursifs (Notes on Regressive Moves).
ERIC Educational Resources Information Center
Auchlin, Antoine; And Others
1981-01-01
Examines the phenomenon of regressive moves (retro-interpretation) in the light of a hypothesis according to which the formation of complex and hierarchically organized conversation units is subordinated to the linearity of discourse. Analyzes a transactional exchange, describing the interplay of integration, anticipation, and retro-interpretation…
Shedding a Tier: Flattening Organisational Structures and Employee Empowerment.
ERIC Educational Resources Information Center
Powell, Loraine
2002-01-01
Surveyed United Kingdom business people and secondary school educators working in organizations with a flatter structure about organizational climate, job meaningfulness, communications, work intensity, and personal motivation. Found that old hierarchical attitudes persist and that an investment in changing the culture is required in order to…
Action detection by double hierarchical multi-structure space-time statistical matching model
NASA Astrophysics Data System (ADS)
Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang
2018-03-01
Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.
Superhydrophobicity of hierarchical nanostructure of candle soot films
NASA Astrophysics Data System (ADS)
Hankhuntond, A.; Singjai, P.; Sakulsermsuk, S.
2017-09-01
Candle soot containing carbon nanoparticles can form hierarchical structure films. We prepared soot films by using glass slides blocking candle flame in the middle of the flame. The hierarchical nanostructures of the carbon nanoparticles films were confirmed by scanning electron microscopy and transmission electron microscopy. Carbon nanoparticle size was 49.2 ± 9.0 nm from SEM, which agrees to 37.9 ± 8.5 nm from TEM. The contact angles of water droplets on these films are more than 150°, indicating superhydrophobic surface. Decrease contact angles of water droplets were observed with an increase deposition time. The decrease of contact angle was saturated at about 150° when the deposition time reaches 180 s. Cassie-Baxter state was attributed to describe superhydrophobicity of carbon nanoparticles films because the hierarchical nanostructures of the surface provide a large fraction of hollows on the surface. We proposed that the contact angle dependence on deposition time was governed by the increase of the distance between nanopillars in carbon nanoparticles films.
Hierarchical Shared Control of Cane-Type Walking-Aid Robot
Tao, Chunjing
2017-01-01
A hierarchical shared-control method of the walking-aid robot for both human motion intention recognition and the obstacle emergency-avoidance method based on artificial potential field (APF) is proposed in this paper. The human motion intention is obtained from the interaction force measurements of the sensory system composed of 4 force-sensing registers (FSR) and a torque sensor. Meanwhile, a laser-range finder (LRF) forward is applied to detect the obstacles and try to guide the operator based on the repulsion force calculated by artificial potential field. An obstacle emergency-avoidance method which comprises different control strategies is also assumed according to the different states of obstacles or emergency cases. To ensure the user's safety, the hierarchical shared-control method combines the intention recognition method with the obstacle emergency-avoidance method based on the distance between the walking-aid robot and the obstacles. At last, experiments validate the effectiveness of the proposed hierarchical shared-control method. PMID:29093805
The Analysis of Image Segmentation Hierarchies with a Graph-based Knowledge Discovery System
NASA Technical Reports Server (NTRS)
Tilton, James C.; Cooke, diane J.; Ketkar, Nikhil; Aksoy, Selim
2008-01-01
Currently available pixel-based analysis techniques do not effectively extract the information content from the increasingly available high spatial resolution remotely sensed imagery data. A general consensus is that object-based image analysis (OBIA) is required to effectively analyze this type of data. OBIA is usually a two-stage process; image segmentation followed by an analysis of the segmented objects. We are exploring an approach to OBIA in which hierarchical image segmentations provided by the Recursive Hierarchical Segmentation (RHSEG) software developed at NASA GSFC are analyzed by the Subdue graph-based knowledge discovery system developed by a team at Washington State University. In this paper we discuss out initial approach to representing the RHSEG-produced hierarchical image segmentations in a graphical form understandable by Subdue, and provide results on real and simulated data. We also discuss planned improvements designed to more effectively and completely convey the hierarchical segmentation information to Subdue and to improve processing efficiency.
Hierarchical VOOH hollow spheres for symmetrical and asymmetrical supercapacitor devices.
Jing, Xuyang; Wang, Cong; Feng, Wenjing; Xing, Na; Jiang, Hanmei; Lu, Xiangyu; Zhang, Yifu; Meng, Changgong
2018-01-01
Hierarchical VOOH hollow spheres with low crystallinity composed of nanoparticles were prepared by a facile and template-free method, which involved a precipitation of precursor microspheres in aqueous solution at room temperature and subsequent hydrothermal reaction. Quasi-solid-state symmetric and asymmetric supercapacitor (SSC and ASC) devices were fabricated using hierarchical VOOH hollow spheres as the electrodes, and the electrochemical properties of the VOOH//VOOH SSC device and the VOOH//AC ASC device were studied by cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS). Results demonstrated that the electrochemical performance of the VOOH//AC ASC device was better than that of the VOOH//VOOH SSC device. After 3000 cycles, the specific capacitance of the VOOH//AC ASC device retains 83% of the initial capacitance, while the VOOH//VOOH SSC device retains only 7.7%. Findings in this work proved that hierarchical VOOH hollow spheres could be a promising candidate as an ideal electrode material for supercapacitor devices.
Hierarchical VOOH hollow spheres for symmetrical and asymmetrical supercapacitor devices
NASA Astrophysics Data System (ADS)
Jing, Xuyang; Wang, Cong; Feng, Wenjing; Xing, Na; Jiang, Hanmei; Lu, Xiangyu; Zhang, Yifu; Meng, Changgong
2018-01-01
Hierarchical VOOH hollow spheres with low crystallinity composed of nanoparticles were prepared by a facile and template-free method, which involved a precipitation of precursor microspheres in aqueous solution at room temperature and subsequent hydrothermal reaction. Quasi-solid-state symmetric and asymmetric supercapacitor (SSC and ASC) devices were fabricated using hierarchical VOOH hollow spheres as the electrodes, and the electrochemical properties of the VOOH//VOOH SSC device and the VOOH//AC ASC device were studied by cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS). Results demonstrated that the electrochemical performance of the VOOH//AC ASC device was better than that of the VOOH//VOOH SSC device. After 3000 cycles, the specific capacitance of the VOOH//AC ASC device retains 83% of the initial capacitance, while the VOOH//VOOH SSC device retains only 7.7%. Findings in this work proved that hierarchical VOOH hollow spheres could be a promising candidate as an ideal electrode material for supercapacitor devices.
Action detection by double hierarchical multi-structure space–time statistical matching model
NASA Astrophysics Data System (ADS)
Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang
2018-06-01
Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.
Morton, Lindsay M.; Linet, Martha S.; Clarke, Christina A.; Kadin, Marshall E.; Vajdic, Claire M.; Monnereau, Alain; Maynadié, Marc; Chiu, Brian C.-H.; Marcos-Gragera, Rafael; Costantini, Adele Seniori; Cerhan, James R.; Weisenburger, Dennis D.
2010-01-01
After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and “in situ” lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications. PMID:20699439
Turner, Jennifer J; Morton, Lindsay M; Linet, Martha S; Clarke, Christina A; Kadin, Marshall E; Vajdic, Claire M; Monnereau, Alain; Maynadié, Marc; Chiu, Brian C-H; Marcos-Gragera, Rafael; Costantini, Adele Seniori; Cerhan, James R; Weisenburger, Dennis D
2010-11-18
After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and "in situ" lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications.
The Neural Correlates of Hierarchical Predictions for Perceptual Decisions.
Weilnhammer, Veith A; Stuke, Heiner; Sterzer, Philipp; Schmack, Katharina
2018-05-23
Sensory information is inherently noisy, sparse, and ambiguous. In contrast, visual experience is usually clear, detailed, and stable. Bayesian theories of perception resolve this discrepancy by assuming that prior knowledge about the causes underlying sensory stimulation actively shapes perceptual decisions. The CNS is believed to entertain a generative model aligned to dynamic changes in the hierarchical states of our volatile sensory environment. Here, we used model-based fMRI to study the neural correlates of the dynamic updating of hierarchically structured predictions in male and female human observers. We devised a crossmodal associative learning task with covertly interspersed ambiguous trials in which participants engaged in hierarchical learning based on changing contingencies between auditory cues and visual targets. By inverting a Bayesian model of perceptual inference, we estimated individual hierarchical predictions, which significantly biased perceptual decisions under ambiguity. Although "high-level" predictions about the cue-target contingency correlated with activity in supramodal regions such as orbitofrontal cortex and hippocampus, dynamic "low-level" predictions about the conditional target probabilities were associated with activity in retinotopic visual cortex. Our results suggest that our CNS updates distinct representations of hierarchical predictions that continuously affect perceptual decisions in a dynamically changing environment. SIGNIFICANCE STATEMENT Bayesian theories posit that our brain entertains a generative model to provide hierarchical predictions regarding the causes of sensory information. Here, we use behavioral modeling and fMRI to study the neural underpinnings of such hierarchical predictions. We show that "high-level" predictions about the strength of dynamic cue-target contingencies during crossmodal associative learning correlate with activity in orbitofrontal cortex and the hippocampus, whereas "low-level" conditional target probabilities were reflected in retinotopic visual cortex. Our findings empirically corroborate theorizations on the role of hierarchical predictions in visual perception and contribute substantially to a longstanding debate on the link between sensory predictions and orbitofrontal or hippocampal activity. Our work fundamentally advances the mechanistic understanding of perceptual inference in the human brain. Copyright © 2018 the authors 0270-6474/18/385008-14$15.00/0.
Mathematical structure of unit systems
NASA Astrophysics Data System (ADS)
Kitano, Masao
2013-05-01
We investigate the mathematical structure of unit systems and the relations between them. Looking over the entire set of unit systems, we can find a mathematical structure that is called preorder (or quasi-order). For some pair of unit systems, there exists a relation of preorder such that one unit system is transferable to the other unit system. The transfer (or conversion) is possible only when all of the quantities distinguishable in the latter system are always distinguishable in the former system. By utilizing this structure, we can systematically compare the representations in different unit systems. Especially, the equivalence class of unit systems (EUS) plays an important role because the representations of physical quantities and equations are of the same form in unit systems belonging to an EUS. The dimension of quantities is uniquely defined in each EUS. The EUS's form a partially ordered set. Using these mathematical structures, unit systems and EUS's are systematically classified and organized as a hierarchical tree.
Formal verification of a set of memory management units
NASA Technical Reports Server (NTRS)
Schubert, E. Thomas; Levitt, K.; Cohen, Gerald C.
1992-01-01
This document describes the verification of a set of memory management units (MMU). The verification effort demonstrates the use of hierarchical decomposition and abstract theories. The MMUs can be organized into a complexity hierarchy. Each new level in the hierarchy adds a few significant features or modifications to the lower level MMU. The units described include: (1) a page check translation look-aside module (TLM); (2) a page check TLM with supervisor line; (3) a base bounds MMU; (4) a virtual address translation MMU; and (5) a virtual address translation MMU with memory resident segment table.
A method of transition conflict resolving in hierarchical control
NASA Astrophysics Data System (ADS)
Łabiak, Grzegorz
2016-09-01
The paper concerns the problem of automatic solving of transition conflicts in hierarchical concurrent state machines (also known as UML state machine). Preparing by the designer a formal specification of a behaviour free from conflicts can be very complex. In this paper, it is proposed a method for solving conflicts through transition predicates modification. Partially specified predicates in the nondeterministic diagram are transformed into a symbolic Boolean space, whose points of the space code all possible valuations of transition predicates. Next, all valuations under partial specifications are logically multiplied by a function which represents all possible orthogonal predicate valuations. The result of this operation contains all possible collections of predicates, which under given partial specification make that the original diagram is conflict free and deterministic.
One grain, one nation: rice genetics and the corporate state in early Francoist Spain (1939–1952.
Camprubi, Lino
2010-01-01
This paper aims to show the links between rice genetics and the corporatist political economy of early Francoism. After investigating the transition from prewar rice producers' associations to a new federation embedded in a vertical union, I identify three main novelties of the new organization: its national scope, its need to address lack of supply rather than overproduction, and its hierarchical functioning. I then focus on the one state-owned agricultural station devoted to rice research, showing how its agricultural scientists shaped, and relied on, the state-controlled unions, both for producing and distributing new varieties of rice and for controlling the seeds farmers used. Finally, I explore how this relationship made it possible for the scientists to test, multiply, and distribute throughout the Spanish landscape the seeds they produced at the laboratory, thus putting hierarchical unity and autarky to work and demonstrating the role of scientists as active agents of state formation and landscape transformation within a corporatist political economy.
A hierarchical model for spatial capture-recapture data
Royle, J. Andrew; Young, K.V.
2008-01-01
Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.
Effects of Course Type on Freshman Learning.
ERIC Educational Resources Information Center
Bohr, Louise
This study considers the effects of course types on reading, mathematics, and critical thinking skill gains for college freshmen. Course groups, arranged hierarchically in three tiers from large groupings down to individual courses, are used as units for analysis. Both Hard Applied and Hard Pure Biglan-paradigm course groups contributed to…
Perspective Taking Promotes Action Understanding and Learning
ERIC Educational Resources Information Center
Lozano, Sandra C.; Martin Hard, Bridgette; Tversky, Barbara
2006-01-01
People often learn actions by watching others. The authors propose and test the hypothesis that perspective taking promotes encoding a hierarchical representation of an actor's goals and subgoals-a key process for observational learning. Observers segmented videos of an object assembly task into coarse and fine action units. They described what…
Dealing with Dependence (Part II): A Gentle Introduction to Hierarchical Linear Modeling
ERIC Educational Resources Information Center
McCoach, D. Betsy
2010-01-01
In education, most naturally occurring data are clustered within contexts. Students are clustered within classrooms, classrooms are clustered within schools, and schools are clustered within districts. When people are clustered within naturally occurring organizational units such as schools, classrooms, or districts, the responses of people from…
Group Coordination Support in Networked Multimedia Systems
1999-12-01
GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S...51 2.3.3 Aggregation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 2.4 Discussion...Hierarchical aggregation of concurrent sessions and corresponding session graph. 23 2.4 User attributes
The North American Breeding Bird Survey 1966–2011: Summary analysis and species accounts
Sauer, John R.; Link, William A.; Fallon, Jane E.; Pardieck, Keith L.; Ziolkowski, David J.
2013-01-01
The North American Breeding Bird Survey is a roadside, count-based survey conducted by volunteer observers. Begun in 1966, it now is a primary source of information on spatial and temporal patterns of population change for North American birds. We analyze population change for states, provinces, Bird Conservation Regions, and the entire survey within the contiguous United States and southern Canada for 426 species using a hierarchical log-linear model that controls for observer effects in counting. We also map relative abundance and population change for each species using a spatial smoothing of data at the scale of survey routes. We present results in accounts that describe major breeding habitats, migratory status, conservation status, and population trends for each species at several geographic scales. We also present composite results for groups of species categorized by habitats and migratory status. The survey varies greatly among species in percentage of species' range covered and precision of results, but consistent patterns of decline occur among eastern forest, grassland, and aridland obligate birds while generalist bird species are increasing.
Preparation and properties of ZnS superhydrophobic surface with hierarchical structure
NASA Astrophysics Data System (ADS)
Yao, Lujun; Zheng, Maojun; He, Shuanghu; Ma, Li; Li, Mei; Shen, Wenzhong
2011-01-01
A novel ZnS hierarchical structure composed of nanorod arrays with branched nanosheets and nanowires grown on their upside walls, was synthesized over Au-coated silicon substrate via chemical vapor deposition technique. Contact angle and sliding angle of this hierarchical film with no surface modification were measured to be about 153.8° and 9.1° for 5 μl water droplets. Self-cleaning behavior and dynamic water-repelling performance were clearly demonstrated. In addition, electrowetting transition phenomenon from superhydrophobic to hydrophilic state happened when a critical bias ∼7.0 V was applied. Below this threshold voltage, the contact angle change is little. This work for the first time reports the creation of ZnS superhydrophobic surface and could enrich its research field as surface functional materials.
Reinforcement Learning for Weakly-Coupled MDPs and an Application to Planetary Rover Control
NASA Technical Reports Server (NTRS)
Bernstein, Daniel S.; Zilberstein, Shlomo
2003-01-01
Weakly-coupled Markov decision processes can be decomposed into subprocesses that interact only through a small set of bottleneck states. We study a hierarchical reinforcement learning algorithm designed to take advantage of this particular type of decomposability. To test our algorithm, we use a decision-making problem faced by autonomous planetary rovers. In this problem, a Mars rover must decide which activities to perform and when to traverse between science sites in order to make the best use of its limited resources. In our experiments, the hierarchical algorithm performs better than Q-learning in the early stages of learning, but unlike Q-learning it converges to a suboptimal policy. This suggests that it may be advantageous to use the hierarchical algorithm when training time is limited.
Prohibiting juvenile access to tobacco: Violation rates, cigarette sales, and youth smoking.
Spivak, Andrew L; Monnat, Shannon M
2015-09-01
Scholars who examine the efficacy of juvenile tobacco sales restrictions, especially the 1992 "Synar Amendment" that led all of fifty U.S. states to enact prohibitions on tobacco sales to minors, are notably divided as to impact on youth smoking. Some researchers claim that such policies have failed and ought to be abandoned (Craig & Boris, 2007; Etter, 2006; Glantz, 2002), while others insist that enforcement has indeed led to reduced tobacco use (DiFranza, 2011b; SAMHSA, 2011). The present study is the first to combine data on Synar violation rates from all states and years available since the amendment's implementation, assessing the connection to national rates of cigarette sales and youth smoking behavior. Using national data from the United States Substance Abuse and Mental Health Services Administration, the Tobacco Institute, and the Centers for Disease Control's Youth Risk Behavior Surveillance System across all U.S. states between 1996 and 2007, we employ hierarchical linear modeling to examine the connection between retailer Synar violations and youth smoking. Controlling for state-level demographic variables, results indicate that retailer violation rates are significantly associated with greater youth smoking prevalence, as well as higher overall cigarette sales. While critiques of Synar policies are substantive and should be addressed, laws prohibiting the sale of tobacco to juveniles appear to have had some degree of success. Copyright © 2015 Elsevier B.V. All rights reserved.
Handel, Colleen M.; Sauer, John
2017-01-01
Management interest in North American birds has increasingly focused on species that breed in Alaska, USA, and Canada, where habitats are changing rapidly in response to climatic and anthropogenic factors. We used a series of hierarchical models to estimate rates of population change in 2 forested Bird Conservation Regions (BCRs) in Alaska based on data from the roadside North American Breeding Bird Survey (BBS) and the Alaska Landbird Monitoring Survey, which samples off-road areas on public resource lands. We estimated long-term (1993–2015) population trends for 84 bird species from the BBS and short-term (2003–2015) trends for 31 species from both surveys. Among the 84 species with long-term estimates, 11 had positive trends and 17 had negative trends in 1 or both BCRs; negative trends were primarily found among aerial insectivores and wetland-associated species, confirming range-wide negative continental trends for many of these birds. Three species with negative trends in the contiguous United States and southern Canada had positive trends in Alaska, suggesting different population dynamics at the northern edges of their ranges. Regional population trends within Alaska differed for several species, particularly those represented by different subspecies in the 2 BCRs, which are separated by rugged, glaciated mountain ranges. Analysis of the roadside and off-road data in a joint hierarchical model with shared parameters resulted in improved precision of trend estimates and suggested a roadside-related difference in underlying population trends for several species, particularly within the Northwestern Interior Forest BCR. The combined analysis highlights the importance of considering population structure, physiographic barriers, and spatial heterogeneity in habitat change when assessing patterns of population change across a landscape as broad as Alaska. Combined analysis of roadside and off-road survey data in a hierarchical framework may be particularly useful for evaluating patterns of population change in relatively undeveloped regions with sparse roadside BBS coverage.
Crimmins, Shawn M.; Walleser, Liza R.; Hertel, Dan R.; McKann, Patrick C.; Rohweder, Jason J.; Thogmartin, Wayne E.
2016-01-01
There is growing need to develop models of spatial patterns in animal abundance, yet comparatively few examples of such models exist. This is especially true in situations where the abundance of one species may inhibit that of another, such as the intensively-farmed landscape of the Prairie Pothole Region (PPR) of the central United States, where waterfowl production is largely constrained by mesocarnivore nest predation. We used a hierarchical Bayesian approach to relate the distribution of various land-cover types to the relative abundances of four mesocarnivores in the PPR: coyote Canis latrans, raccoon Procyon lotor, red fox Vulpes vulpes, and striped skunk Mephitis mephitis. We developed models for each species at multiple spatial resolutions (41.4 km2, 10.4 km2, and 2.6 km2) to address different ecological and management-related questions. Model results for each species were similar irrespective of resolution. We found that the amount of row-crop agriculture was nearly ubiquitous in our best models, exhibiting a positive relationship with relative abundance for each species. The amount of native grassland land-cover was positively associated with coyote and raccoon relative abundance, but generally absent from models for red fox and skunk. Red fox and skunk were positively associated with each other, suggesting potential niche overlap. We found no evidence that coyote abundance limited that of other mesocarnivore species, as might be expected under a hypothesis of mesopredator release. The relationships between relative abundance and land-cover types were similar across spatial resolutions. Our results indicated that mesocarnivores in the PPR are most likely to occur in portions of the landscape with large amounts of agricultural land-cover. Further, our results indicated that track-survey data can be used in a hierarchical framework to gain inferences regarding spatial patterns in animal relative abundance.
HiVy automated translation of stateflow designs for model checking verification
NASA Technical Reports Server (NTRS)
Pingree, Paula
2003-01-01
tool set enables model checking of finite state machines designs. This is acheived by translating state-chart specifications into the input language of the Spin model checker. An abstract syntax of hierarchical sequential automata (HSA) is provided as an intermediate format tool set.
Sparsey™: event recognition via deep hierarchical sparse distributed codes
Rinkus, Gerard J.
2014-01-01
The visual cortex's hierarchical, multi-level organization is captured in many biologically inspired computational vision models, the general idea being that progressively larger scale (spatially/temporally) and more complex visual features are represented in progressively higher areas. However, most earlier models use localist representations (codes) in each representational field (which we equate with the cortical macrocolumn, “mac”), at each level. In localism, each represented feature/concept/event (hereinafter “item”) is coded by a single unit. The model we describe, Sparsey, is hierarchical as well but crucially, it uses sparse distributed coding (SDC) in every mac in all levels. In SDC, each represented item is coded by a small subset of the mac's units. The SDCs of different items can overlap and the size of overlap between items can be used to represent their similarity. The difference between localism and SDC is crucial because SDC allows the two essential operations of associative memory, storing a new item and retrieving the best-matching stored item, to be done in fixed time for the life of the model. Since the model's core algorithm, which does both storage and retrieval (inference), makes a single pass over all macs on each time step, the overall model's storage/retrieval operation is also fixed-time, a criterion we consider essential for scalability to the huge (“Big Data”) problems. A 2010 paper described a nonhierarchical version of this model in the context of purely spatial pattern processing. Here, we elaborate a fully hierarchical model (arbitrary numbers of levels and macs per level), describing novel model principles like progressive critical periods, dynamic modulation of principal cells' activation functions based on a mac-level familiarity measure, representation of multiple simultaneously active hypotheses, a novel method of time warp invariant recognition, and we report results showing learning/recognition of spatiotemporal patterns. PMID:25566046
On the Structure of Earth Science Data Collections
NASA Astrophysics Data System (ADS)
Barkstrom, B. R.
2009-12-01
While there has been substantial work in the IT community regarding metadata and file identifier schemas, there appears to be relatively little work on the organization of the file collections that constitute the preponderance of Earth science data. One symptom of this difficulty appears in nomenclature describing collections: the terms `Data Product,' `Data Set,' and `Version' are overlaid with multiple meanings between communities. A particularly important aspect of this lack of standardization appears when the community attempts to developa schema for data file identifiers. There are four candidate families of identifiers: ● Randomly assigned identifiers, such as GUIDs or UUIDs, ● Segmented numerical identifiers, such as OIDs or the prefixes for DOIs, ● Extensible URL-based identifiers, such as URNs, PURL, ARK, and similar schemas, ● Text-based identifiers based on citations for papers and books, such as those suggested for the International Polar Year (IPY) citations. Unfortunately, these schema families appear to be devoid of content based on the actual structures of Earth science data collections. In this paper, we consider an organization based on an industrial production paradigm that appears to provide the preponderance of Earth science data from satellites and in situ observations. This paradigm produces a hierarchical collection structure, similar to one discussed in Barkstrom [2003: Lecture Notes in Computer Science, 2649, pp. 118-133]. In this organization, three key collection types are ● a Data Product, which is a collection of files that have similar key parameters and included data time interval, ● a Data Set, which is a collection of files within a Data Product that comes from a specified set of Data Sources, ● a Data Set Version, which is a collection of files within a Data Set for which the data producer has attempted to ensure error homogeneity. Within a Data Set Version, files appear as a time series of instances that may be identified by the starting time of the data in the file. For data intended for climate uses, it seems appropriate to state this time in terms of Astronomical Julian Date, which is a long-standing international standard that provides continuity between current observations and paleo-climatic observations. Because this collection structure is hierarchical, it could be used by either of the two hierarchical identifier schema families, although it is probably easier to use with the OID/DOI family. This hierarchical collection structure fits into the hierarchical structure of Archival Information Packages (AIPs) identified in the Open Archival Information Systems (OAIS) Reference Model. In that model, AIPs are subdivided into Archival Information Units (AIUs), which describe individual files, or Archival Information Collections (AICs). The latter can be hierarchically nested, leading to an OAIS RM-consistent collection structure that does not appear clearly in other metadata standards. This paper will also discuss the connection between these collection categories and other metadata, as well as the possible need for other organizational schemas to capture the full range of Earth science data collection structures.
McCarty-Caplan, David
2018-01-01
This study examined the relationship between master of social work programs' (MSW) support of lesbian, gay, bisexual, and transgender people (LGBT-competence) and the sexual minority competence (LGB-competence) of social work students. Data were gathered from a sample of MSW program directors, faculty members, and students (N = 1385) within 34 MSW programs in the United States. A series of hierarchical linear models tested if a MSW program's LGBT-competence was associated with the LGB-competence of its students. Results showed a significant relationship between organizational LGBT-competence and individual LGB-competence within schools of social work, and that programs with greater LGBT-competence also had students who felt more competent to work with sexual minorities. These findings suggest schools of social work can take substantive action at an organizational level to improve the professional LGB-competence of future social workers. Implications for social work education are discussed.
Shaping attitudes about homosexuality: the role of religion and cultural context.
Adamczyk, Amy; Pitt, Cassady
2009-06-01
Across the globe, the debate over homosexuality continues, with great variation in public opinion about the acceptability of homosexuality, laws regulating same-sex unions and penalties for homosexual sex behaviors. Religion is often seen as an important predictor of attitudes about homosexuality. However, cross-national differences in cultural orientations suggest that the role religion has in explaining homosexual attitudes may depend on a nation's cultural context. In this study, we merge ideas from cultural sociology and religious contextual effects to explain cross-national variation in public opinion about homosexuality. Using data from the fourth wave of the World Values Survey and Hierarchical Modeling techniques, we find support for the micro and macro effects of religion and a survival vs. self-expressive cultural orientation. Moreover, we find that personal religious beliefs have a greater effect on attitudes about homosexuality in countries like the United States, which have a strong self-expressive cultural orientation.
Nature and transformation of dissolved organic matter in treatment wetlands
Barber, L.B.; Leenheer, J.A.; Noyes, T.I.; Stiles, E.A.
2001-01-01
This investigation into the occurrence, character, and transformation of dissolved organic matter (DOM) in treatment wetlands in the western United States shows that (i) the nature of DOM in the source water has a major influence on transformations that occur during treatment, (ii) the climate factors have a secondary effect on transformations, (iii) the wetlands receiving treated wastewater can produce a net increase in DOM, and (iv) the hierarchical analytical approach used in this study can measure the subtle DOM transformations that occur. As wastewater treatment plant effluent passes through treatment wetlands, the DOM undergoes transformation to become more aromatic and oxygenated. Autochthonous sources are contributed to the DOM, the nature of which is governed by the developmental stage of the wetland system as well as vegetation patterns. Concentrations of specific wastewaterderived organic contaminants such as linear alkylbenzene sulfonate, caffeine, and ethylenediaminetetraacetic acid were significantly attenuated by wetland treatment and were not contributed by internal loading.
Exploring Indigenous Identities of Urban American Indian Youth of the Southwest
Kulis, Stephen; Wagaman, M. Alex; Tso, Crescentia; Brown, Eddie F.
2013-01-01
This study examined the indigenous identities of urban American Indian youth using measures related to three theoretical dimensions of Markstrom's identity model: identification (tribal and ethnic heritage), connection (reservation ties), and involvement in traditional cultural practices and spirituality. Data came from self-administered questionnaires completed by 142 urban American Indian middle school students in a southwestern metropolitan area with the largest urban American Indian population in the United States. Using both quantitative and qualitative measures, descriptive statistics showed most youth were connected to all three dimensions of indigenous identity. Hierarchical regression analyses showed that youth with the strongest sense of American Indian ethnic identity had native fathers and were heavily involved in traditional cultural practices and spirituality. Although urban American Indians may face challenges in maintaining their tribal identities, the youth in this study appeared strongly moored to their native indigenous heritage. Implications for future research are discussed. PMID:23766553
Developmental Relations Among Motor and Cognitive Processes and Mathematics Skills.
Kim, Helyn; Duran, Chelsea A K; Cameron, Claire E; Grissmer, David
2018-03-01
This study explored transactional associations among visuomotor integration, attention, fine motor coordination, and mathematics skills in a diverse sample of one hundred thirty-five 5-year-olds (kindergarteners) and one hundred nineteen 6-year-olds (first graders) in the United States who were followed over the course of 2 school years. Associations were dynamic, with more reciprocal transactions occurring in kindergarten than in the later grades. Specifically, visuomotor integration and mathematics exhibited ongoing reciprocity in kindergarten and first grade, attention contributed to mathematics in kindergarten and first grade, mathematics contributed to attention across the kindergarten year only, and fine motor coordination contributed to mathematics indirectly, through visuomotor integration, across kindergarten and first grade. Implications of examining the hierarchical interrelations among processes underlying the development of children's mathematics skills are discussed. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.
Factors of empowerment for women in recovery from substance use.
Hunter, Bronwyn A; Jason, Leonard A; Keys, Christopher B
2013-03-01
Empowerment is an interdisciplinary construct heavily grounded in the theories of community psychology. Although empowerment has a strong theoretical foundation, few context-specific quantitative measures have been designed to evaluate empowerment for specific populations. The present study explored the factor structure of a modified empowerment scale with a cross-sectional sample of 296 women in recovery from substance use who lived in recovery homes located throughout the United States. Results from an exploratory factor analysis identified three factors of psychological empowerment which were closely related to previous conceptualizations of psychological empowerment: self-perception, resource knowledge and participation. Further analyses demonstrated a hierarchical relationship among the three factors, with resource knowledge predicting participation when controlling for self-perception. Finally, a correlational analysis demonstrated the initial construct validity of each factor, as each factor of empowerment was significantly and positively related to self-esteem. Implications for the application of psychological empowerment theory and research are discussed.
Age at Immigration and Kidney Function among Self-Identified Healthy Africans in the United States.
Ali, Mana; Mwendwa, Denée T; Sims, Regina; Ricks, Madia; Sumner, Anne E
2016-02-01
Kidney disease disparately affects those of African descent. Age trends have generally been established for kidney function in the overall US population, but the contribution of age at the time of immigration for African immigrants is unknown. To examine the independent and joint effects of age and age at the time of immigration, and kidney function. Estimated glomerular filtration rate (eGFR) was calculated for 93 African immigrants (60 % male; mean age = 33.5). Hierarchical regression and post hoc analyses revealed a significant age × age at the time of immigration interaction after accounting for traditional risk factors among those who immigrated at age ≤21. Younger age at the time of immigration to the US may exacerbate an inverse relationship between age and kidney function in a self-identified healthy African immigrant sample. Investigation of biopsychosocial factors associated with kidney health among African immigrants is warranted.
Factors of Empowerment for Women in Recovery from Substance Use
Hunter, Bronwyn A.; Jason, Leonard A.; Keys, Christopher B.
2014-01-01
Empowerment is an interdisciplinary construct heavily grounded in the theories of community psychology. Although empowerment has a strong theoretical foundation, few context-specific quantitative measures have been designed to evaluate empowerment for specific populations. The present study explored the factor structure of a modified empowerment scale with a cross-sectional sample of 296 women in recovery from substance use who lived in recovery homes located throughout the United States. Results from an exploratory factor analysis identified three factors of psychological empowerment which were closely related to previous conceptualizations of psychological empowerment: self perception, resource knowledge and participation. Further analyses demonstrated a hierarchical relationship among the three factors, with resource knowledge predicting participation when controlling for self-perception. Finally, a correlational analysis demonstrated the initial construct validity of each factor, as each factor of empowerment was significantly and positively related to self-esteem. Implications for the application of psychological empowerment theory and research are discussed. PMID:22392193
Literacy Gaps by Educational Attainment: A Cross-National Analysis
Park, Hyunjoon; Kyei, Pearl
2011-01-01
Existing cross-national research on educational attainment does not fully address whether the same level of educational attainment generates the same level of literacy skills in different countries. We analyze literacy skills data for young adults from 19 countries in the 1994–1998 International Adult Literacy Survey and find that in all countries, individuals with a higher level of educational attainment tend to have greater literacy skills. However, there is substantial variation across countries in the size of literacy gaps by levels of educational attainment. In particular, young adults in the United States show the largest literacy gaps. Using two-level hierarchical linear models, we find that cross-national differences in the literacy gap between more- and less-educated individuals are systematically linked to the degree of between-school inequality in school resources (instructional materials, class size, teachers’ experience and certification). PMID:21818163
Understanding neighbourhoods, communities and environments: new approaches for social work research.
Holland, Sally; Burgess, Stephen; Grogan-Kaylor, Andy; Delva, Jorge
2010-06-01
This article discusses some new ways in which social work research can explore the interaction between neighbourhoods and child and adult wellbeing. The authors note that social work practices are often criticised for taking an individualistic approach and paying too little attention to the service user's environment. The article uses examples of research projects from Chile, the United States of America and Wales, to discuss the use of spatially oriented research methods for understanding neighbourhood factors. Quantitative, qualitative and mixed methods approaches that are particularly appropriate for investigating social work relevant topics are discussed in turn, including quantitative and qualitative uses for geographical information systems (GIS), hierarchical linear modelling (HLM) for analysing spatially clustered data and qualitative mobile interviews. The article continues with a discussion of the strengths and limitations of using spatially orientated research designs in social work research settings and concludes optimistically with suggestions for future directions in this area.
Hierarchical folding free energy landscape of HP35 revealed by most probable path clustering.
Jain, Abhinav; Stock, Gerhard
2014-07-17
Adopting extensive molecular dynamics simulations of villin headpiece protein (HP35) by Shaw and co-workers, a detailed theoretical analysis of the folding of HP35 is presented. The approach is based on the recently proposed most probable path algorithm which identifies the metastable states of the system, combined with dynamical coring of these states in order to obtain a consistent Markov state model. The method facilitates the construction of a dendrogram associated with the folding free-energy landscape of HP35, which reveals a hierarchical funnel structure and shows that the native state is rather a kinetic trap than a network hub. The energy landscape of HP35 consists of the entropic unfolded basin U, where the prestructuring of the protein takes place, the intermediate basin I, which is connected to U via the rate-limiting U → I transition state reflecting the formation of helix-1, and the native basin N, containing a state close to the NMR structure and a native-like state that exhibits enhanced fluctuations of helix-3. The model is in line with recent experimental observations that the intermediate and native states differ mostly in their dynamics (locked vs unlocked states). Employing dihedral angle principal component analysis, subdiffusive motion on a multidimensional free-energy surface is found.
Van Bogaert, Peter; Adriaenssens, Jef; Dilles, Tinne; Martens, Daisy; Van Rompaey, Bart; Timmermans, Olaf
2014-11-01
To study the impact of role, job- and organizational characteristics on nurse managers' work related stress and well-being such as feelings of emotional exhaustion, work engagement, job satisfaction and turnover intention. Various studies investigated role-, job- and organizational characteristics influencing nurse-related work environments. Research on nurse managers' related work environments define influencing factors, but, a clear understanding of the impact of nurse-managers' work-environment characteristics on their work related stress and well-being is limited. A cross-sectional design with a survey. A cross-sectional survey (N = 365) was carried out between December 2011-March 2012. The questionnaire was based on various validated measurement instruments identified by expert meetings (e.g. staff nurses, nurse managers and executives and physicians). Hierarchical regression analyses were performed using emotional exhaustion, work engagement, job satisfaction and turnover intentions as outcome variables. Study results showed one out of six nursing unit managers have high to very high feelings of emotional exhaustion and two out of three respondents have high to very high work engagement. Hierarchical regression models showed that role conflict and role meaningfulness were strong predictors of nursing unit managers' work related stress and well-being, alongside with job- and organizational characteristics. Several risk factors and stimulating factors influencing nurse unit managers' work related stress and well-being were identified. Further challenges will be to develop proper interventions and strategies to support nursing unit managers and their team in daily practice to deliver the best and safest patient care. © 2014 John Wiley & Sons Ltd.
Subramanian, S V; Kawachi, Ichiro
2006-06-01
The empirical relationship between income inequality and health has been much debated and discussed. Recent reviews suggest that the current evidence is mixed, with the relationship between state income inequality and health in the United States (US) being perhaps the most robust. In this paper, we examine the multilevel interactions between state income inequality, individual poor self-rated health, and a range of individual demographic and socioeconomic markers in the US. We use the pooled data from the 1995 and 1997 Current Population Surveys, and the data on state income inequality (represented using Gini coefficient) from the 1990, 1980, and 1970 US Censuses. Utilizing a cross-sectional multilevel design of 201,221 adults nested within 50 US states we calibrated two-level binomial hierarchical mixed models (with states specified as a random effect). Our analyses suggest that for a 0.05 change in the state income inequality, the odds ratio (OR) of reporting poor health was 1.30 (95% CI: 1.17-1.45) in a conditional model that included individual age, sex, race, marital status, education, income, and health insurance coverage as well as state median income. With few exceptions, we did not find strong statistical support for differential effects of state income inequality across different population groups. For instance, the relationship between state income inequality and poor health was steeper for whites compared to blacks (OR=1.34; 95% CI: 1.20-1.48) and for individuals with incomes greater than $75,000 compared to less affluent individuals (OR=1.65; 95% CI: 1.26-2.15). Our findings, however, primarily suggests an overall (as opposed to differential) contextual effect of state income inequality on individual self-rated poor health. To the extent that contemporaneous state income inequality differentially affects population sub-groups, our analyses suggest that the adverse impact of inequality is somewhat stronger for the relatively advantaged socioeconomic groups. This pattern was found to be consistent regardless of whether we consider contemporaneous or lagged effects of state income inequality on health. At the same time, the contemporaneous main effect of state income inequality remained statistically significant even when conditioned for past levels of income inequality and median income of states.
Hierarchical FeTiO3-TiO2 hollow spheres for efficient simulated sunlight-driven water oxidation.
Han, Taoran; Chen, Yajie; Tian, Guohui; Wang, Jian-Qiang; Ren, Zhiyu; Zhou, Wei; Fu, Honggang
2015-10-14
Oxygen generation is the key step for the photocatalytic overall water splitting and considered to be kinetically more challenging than hydrogen generation. Here, an effective water oxidation catalyst of hierarchical FeTiO3-TiO2 hollow spheres are prepared via a two-step sequential solvothermal processes and followed by thermal treatment. The existence of an effective heterointerface and built-in electric field in the surface space charge region in FeTiO3-TiO2 hollow spheres plays a positive role in promoting the separation of photoinduced electron-hole pairs. Surface photovoltage, transient-state photovoltage, fluorescence and electrochemical characterization are used to investigate the transfer process of photoinduced charge carriers. The photogenerated charge carriers in the hierarchical FeTiO3-TiO2 hollow spheres with a proper molar ratio display much higher separation efficiency and longer lifetime than those in the FeTiO3 alone. Moreover, it is suggested that the hierarchical porous hollow structure can contribute to the enhancement of light utilization, surface active sites and material transportation through the framework walls. This specific synergy significantly contributes to the remarkable improvement of the photocatalytic water oxidation activity of the hierarchical FeTiO3-TiO2 hollow spheres under simulated sunlight (AM1.5).
Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods.
Notaro, Marco; Schubach, Max; Robinson, Peter N; Valentini, Giorgio
2017-10-12
The prediction of human gene-abnormal phenotype associations is a fundamental step toward the discovery of novel genes associated with human disorders, especially when no genes are known to be associated with a specific disease. In this context the Human Phenotype Ontology (HPO) provides a standard categorization of the abnormalities associated with human diseases. While the problem of the prediction of gene-disease associations has been widely investigated, the related problem of gene-phenotypic feature (i.e., HPO term) associations has been largely overlooked, even if for most human genes no HPO term associations are known and despite the increasing application of the HPO to relevant medical problems. Moreover most of the methods proposed in literature are not able to capture the hierarchical relationships between HPO terms, thus resulting in inconsistent and relatively inaccurate predictions. We present two hierarchical ensemble methods that we formally prove to provide biologically consistent predictions according to the hierarchical structure of the HPO. The modular structure of the proposed methods, that consists in a "flat" learning first step and a hierarchical combination of the predictions in the second step, allows the predictions of virtually any flat learning method to be enhanced. The experimental results show that hierarchical ensemble methods are able to predict novel associations between genes and abnormal phenotypes with results that are competitive with state-of-the-art algorithms and with a significant reduction of the computational complexity. Hierarchical ensembles are efficient computational methods that guarantee biologically meaningful predictions that obey the true path rule, and can be used as a tool to improve and make consistent the HPO terms predictions starting from virtually any flat learning method. The implementation of the proposed methods is available as an R package from the CRAN repository.
Swartz, Michael D; Cai, Yi; Chan, Wenyaw; Symanski, Elaine; Mitchell, Laura E; Danysh, Heather E; Langlois, Peter H; Lupo, Philip J
2015-02-09
While there is evidence that maternal exposure to benzene is associated with spina bifida in offspring, to our knowledge there have been no assessments to evaluate the role of multiple hazardous air pollutants (HAPs) simultaneously on the risk of this relatively common birth defect. In the current study, we evaluated the association between maternal exposure to HAPs identified by the United States Environmental Protection Agency (U.S. EPA) and spina bifida in offspring using hierarchical Bayesian modeling that includes Stochastic Search Variable Selection (SSVS). The Texas Birth Defects Registry provided data on spina bifida cases delivered between 1999 and 2004. The control group was a random sample of unaffected live births, frequency matched to cases on year of birth. Census tract-level estimates of annual HAP levels were obtained from the U.S. EPA's 1999 Assessment System for Population Exposure Nationwide. Using the distribution among controls, exposure was categorized as high exposure (>95(th) percentile), medium exposure (5(th)-95(th) percentile), and low exposure (<5(th) percentile, reference). We used hierarchical Bayesian logistic regression models with SSVS to evaluate the association between HAPs and spina bifida by computing an odds ratio (OR) for each HAP using the posterior mean, and a 95% credible interval (CI) using the 2.5(th) and 97.5(th) quantiles of the posterior samples. Based on previous assessments, any pollutant with a Bayes factor greater than 1 was selected for inclusion in a final model. Twenty-five HAPs were selected in the final analysis to represent "bins" of highly correlated HAPs (ρ > 0.80). We identified two out of 25 HAPs with a Bayes factor greater than 1: quinoline (ORhigh = 2.06, 95% CI: 1.11-3.87, Bayes factor = 1.01) and trichloroethylene (ORmedium = 2.00, 95% CI: 1.14-3.61, Bayes factor = 3.79). Overall there is evidence that quinoline and trichloroethylene may be significant contributors to the risk of spina bifida. Additionally, the use of Bayesian hierarchical models with SSVS is an alternative approach in the evaluation of multiple environmental pollutants on disease risk. This approach can be easily extended to environmental exposures, where novel approaches are needed in the context of multi-pollutant modeling.
Examining Elementary Social Studies Marginalization: A Multilevel Model
ERIC Educational Resources Information Center
Fitchett, Paul G.; Heafner, Tina L.; Lambert, Richard G.
2014-01-01
Utilizing data from the National Center for Education Statistics Schools and Staffing Survey (SASS), a multilevel model (Hierarchical Linear Model) was developed to examine the association of teacher/classroom and state level indicators on reported elementary social studies instructional time. Findings indicated that state testing policy was a…
Mapping integration of midwives across the United States: Impact on access, equity, and outcomes
Stoll, Kathrin; MacDorman, Marian; Declercq, Eugene; Cramer, Renee; Cheyney, Melissa; Fisher, Timothy; Butt, Emma; Yang, Y. Tony; Powell Kennedy, Holly
2018-01-01
Poor coordination of care across providers and birth settings has been associated with adverse maternal-newborn outcomes. Research suggests that integration of midwives into regional health systems is a key determinant of optimal maternal-newborn outcomes, yet, to date, the characteristics of an integrated system have not been described, nor linked to health disparities. Methods Our multidisciplinary team examined published regulatory data to inform a 50-state database describing the environment for midwifery practice and interprofessional collaboration. Items (110) detailed differences across jurisdictions in scope of practice, autonomy, governance, and prescriptive authority; as well as restrictions that can affect patient safety, quality, and access to maternity providers across birth settings. A nationwide survey of state regulatory experts (n = 92) verified the ‘on the ground’ relevance, importance, and realities of local interpretation of these state laws. Using a modified Delphi process, we selected 50/110 key items to include in a weighted, composite Midwifery Integration Scoring (MISS) system. Higher scores indicate greater integration of midwives across all settings. We ranked states by MISS scores; and, using reliable indicators in the CDC-Vital Statistics Database, we calculated correlation coefficients between MISS scores and maternal-newborn outcomes by state, as well as state density of midwives and place of birth. We conducted hierarchical linear regression analysis to control for confounding effects of race. Results MISS scores ranged from lowest at 17 (North Carolina) to highest at 61 (Washington), out of 100 points. Higher MISS scores were associated with significantly higher rates of spontaneous vaginal delivery, vaginal birth after cesarean, and breastfeeding, and significantly lower rates of cesarean, preterm birth, low birth weight infants, and neonatal death. MISS scores also correlated with density of midwives and access to care across birth settings. Significant differences in newborn outcomes accounted for by MISS scores persisted after controlling for proportion of African American births in each state. Conclusion The MISS scoring system assesses the level of integration of midwives and evaluates regional access to high quality maternity care. In the United States, higher MISS Scores were associated with significantly higher rates of physiologic birth, less obstetric interventions, and fewer adverse neonatal outcomes. PMID:29466389
Hierarchical Synthesis of Coastal Ecosystem Health Indicators at Karimunjawa National Marine Park
NASA Astrophysics Data System (ADS)
Danu Prasetya, Johan; Ambariyanto; Supriharyono; Purwanti, Frida
2018-02-01
The coastal ecosystem of Karimunjawa National Marine Park (KNMP) is facing various pressures, including from human activity. Monitoring the health condition of coastal ecosystems periodically is needed as an evaluation of the ecosystem condition. Systematic and consistent indicators are needed in monitoring of coastal ecosystem health. This paper presents hierarchical synthesis of coastal ecosystem health indicators using Analytic Hierarchy Process (AHP) method. Hierarchical synthesis is obtained from process of weighting by paired comparison based on expert judgments. The variables of coastal ecosystem health indicators in this synthesis consist of 3 level of variable, i.e. main variable, sub-variable and operational variable. As a result of assessment, coastal ecosystem health indicators consist of 3 main variables, i.e. State of Ecosystem, Pressure and Management. Main variables State of Ecosystem and Management obtain the same value i.e. 0.400, while Pressure value was 0.200. Each main variable consist of several sub-variable, i.e. coral reef, reef fish, mangrove and seagrass for State of Ecosystem; fisheries and marine tourism activity for Pressure; planning and regulation, institutional and also infrastructure and financing for Management. The highest value of sub-variable of main variable State of Ecosystem, Pressure and Management were coral reef (0.186); marine tourism pressure (0.133) and institutional (0.171), respectively. The highest value of operational variable of main variable State of Ecosystem, Pressure and Management were percent of coral cover (0.058), marine tourism pressure (0.133) and presence of zonation plan, regulation also socialization of monitoring program (0.53), respectively. Potential pressure from marine tourism activity is the variable that most affect the health of the ecosystem. The results of this research suggest that there is a need to develop stronger conservation strategies to facing with pressures from marine tourism activities.
NASA Astrophysics Data System (ADS)
Pagán, Brianna; Ashfaq, Moetasim; Nayak, Munir; Rastogi, Deeksha; Margulis, Steven; Pal, Jeremy
2017-04-01
The Western United States shares limited snowmelt driven water supplies amongst millions of people, a multi-billion dollar agriculture industry and fragile ecosystems. The climatology of the region is highly variable, characterized by the frequent occurrences of both flood and drought conditions that cause increasingly challenging water management issues. Although variable year to year, up to half of California's total precipitation can be linked to atmospheric rivers (ARs). Most notably, ARs have been connected to nearly every major historic flood in the region, establishing its critical role to water supply. Numerous prior studies have considered potential climate change impacts over the Western United States and have generally concluded that warmer temperatures will reduce snowpack and shift runoff timing, causing reductions to water supply. Here we examine the role of ARs as one mechanism for explaining projected increases in flood and drought frequency and intensity under climate change scenarios, vital information for water resource managers. A hierarchical modeling framework to downscale 11 coupled global climate models from CMIP5 is used to form an ensemble of high-resolution dynamically downscaled regional climate model (via RegCM4) simulations at 18-km and hydrological (via VIC) simulations at a 4-km resolution for baseline (1965-2005) and future (2010-2050) periods under RCP 8.5. Each ensemble member's ability to capture observational AR climatology over the baseline period is evaluated. Baseline to future period changes to AR size, duration, seasonal timing, trajectory, magnitude and frequency are presented. These changes to the characterizations of ARs in the region are used to determine if any links exist to changes in snowpack volume, runoff timing, and the occurrence of daily and annual cumulative extreme precipitation and runoff events. Shifts in extreme AR frequency and magnitude are expected to increase flood risks, which without adequate multi-year reservoir storage solutions could further strain water supply resources.
Hardware Acceleration of Sparse Cognitive Algorithms
2016-05-01
Processor in Memory (PiM) extensions and a 65 nm ASIC version. They were compared against a 28 nm GPU baseline using the KTH video action recognition...30 Table 17. Memory Requirement of Proposed ASIC...for improvement of performance per unit of power for customized implementations of the Sparsey and Numenta Hierarchical Temporal Memory (HTM
Elapsed Time: Why Is It So Difficult to Teach?
ERIC Educational Resources Information Center
Kamii, Constance; Russell, Kelly A.
2012-01-01
Based on Piaget's theory of logico-mathematical knowledge, 126 students in grades 2-5 were asked 6 questions about elapsed time. The main reason found for difficulty with elapsed time is children's inability to coordinate hierarchical units (hours and minutes). The educational implications drawn are that students must be encouraged to think about…
ERIC Educational Resources Information Center
Darwish, Naif A.; Qasim, Muhammad
2016-01-01
In academia, smooth progression of students significantly depends on the way curricula are developed and organized. Curricula or study plans with high degree of interconnectivity between courses, multiple prerequisites, and hierarchically structured courses tend to complicate the smooth progress of the enrolled students. In this work, a rigorous…
ERIC Educational Resources Information Center
Botvinick, Matthew; Plaut, David C.
2004-01-01
In everyday tasks, selecting actions in the proper sequence requires a continuously updated representation of temporal context. Previous models have addressed this problem by positing a hierarchy of processing units, mirroring the roughly hierarchical structure of naturalistic tasks themselves. The present study considers an alternative framework,…
Using an Ecological Land Hierarchy to Predict Seasonal-Wetland Abundance in Upland Forests
Brian J. Palik; Richard Buech; Leanne Egeland
2003-01-01
Hierarchy theory, when applied to landscapes, predicts that broader-scale ecosystems constrain the development of finer-scale, nested ecosystems. This prediction finds application in hierarchical land classifications. Such classifications typically apply to physiognomically similar ecosystems, or ecological land units, e.g., a set of multi-scale forest ecosystems. We...
Mahl, Sukhy; Lee, Shoo K; Baker, G Ross; Cronin, Catherine M G; Stevens, Bonnie; Ye, Xiang Y
2015-01-01
Studies of adult patient populations suggest that organizational culture is associated with quality improvement (QI) implementation, as well as patient outcomes. However, very little research on organizational culture has been performed in neonatal patient populations. This combined cross-sectional survey and retrospective cohort study assessed employee perceptions of organizational culture and QI implementation within 18 Canadian neonatal intensive care units. The associations between these data and neonatal outcomes in extremely preterm infants (born at < 29 weeks' gestation) were then assessed using multivariable analyses. Perceptions of unit culture and QI implementation varied according to occupation and age. Higher hierarchical culture was associated with increased survival without major morbidities (odds ratio, 1.04; 95% confidence interval, 1.01-1.06), as were higher QI implementation scores (odds ratio range, 1.20-1.36 by culture type). Our data suggest that organizational culture, particularly hierarchical culture, and level of QI implementation may play a role in neonatal outcomes. Copyright © 2015 National Association of Pediatric Nurse Practitioners. Published by Elsevier Inc. All rights reserved.
A Hierarchical MFI Zeolite with a Two-Dimensional Square Mesostructure.
Shen, Xuefeng; Mao, Wenting; Ma, Yanhang; Xu, Dongdong; Wu, Peng; Terasaki, Osamu; Han, Lu; Che, Shunai
2018-01-15
A conceptual design and synthesis of ordered mesoporous zeolites is a challenging research subject in material science. Several seminal articles report that one-dimensional (1D) mesostructured lamellar zeolites are possibly directed by sheet-assembly of surfactants, which collapse after removal of intercalated surfactants. However, except for one example of two-dimensional (2D) hexagonal mesoporous zeolite, no other zeolites with ordered 2D or three-dimensional (3D) mesostructures have been reported. An ordered 2D mesoporous zeolite can be templated by a cylindrical assembly unit with specific interactions in the hydrophobic part. A template molecule with azobenzene in the hydrophobic tail and diquaternary ammonium in the hydrophilic head group directs hierarchical MFI zeolite with a 2D square mesostructure. The material has an elongated octahedral morphology, and quaternary, ordered, straight, square channels framed by MFI thin sheets expanded along the a-c planes and joined with 90° rotations. The structural matching between the cylindrical assembly unit and zeolite framework is crucial for mesostructure construction. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Hierarchical Solution of the Traveling Salesman Problem with Random Dyadic Tilings
NASA Astrophysics Data System (ADS)
Kalmár-Nagy, Tamás; Bak, Bendegúz Dezső
We propose a hierarchical heuristic approach for solving the Traveling Salesman Problem (TSP) in the unit square. The points are partitioned with a random dyadic tiling and clusters are formed by the points located in the same tile. Each cluster is represented by its geometrical barycenter and a “coarse” TSP solution is calculated for these barycenters. Midpoints are placed at the middle of each edge in the coarse solution. Near-optimal (or optimal) minimum tours are computed for each cluster. The tours are concatenated using the midpoints yielding a solution for the original TSP. The method is tested on random TSPs (independent, identically distributed points in the unit square) up to 10,000 points as well as on a popular benchmark problem (att532 — coordinates of 532 American cities). Our solutions are 8-13% longer than the optimal ones. We also present an optimization algorithm for the partitioning to improve our solutions. This algorithm further reduces the solution errors (by several percent using 1000 iteration steps). The numerical experiments demonstrate the viability of the approach.
Modeling abundance using hierarchical distance sampling
Royle, Andy; Kery, Marc
2016-01-01
In this chapter, we provide an introduction to classical distance sampling ideas for point and line transect data, and for continuous and binned distance data. We introduce the conditional and the full likelihood, and we discuss Bayesian analysis of these models in BUGS using the idea of data augmentation, which we discussed in Chapter 7. We then extend the basic ideas to the problem of hierarchical distance sampling (HDS), where we have multiple point or transect sample units in space (or possibly in time). The benefit of HDS in practice is that it allows us to directly model spatial variation in population size among these sample units. This is a preeminent concern of most field studies that use distance sampling methods, but it is not a problem that has received much attention in the literature. We show how to analyze HDS models in both the unmarked package and in the BUGS language for point and line transects, and for continuous and binned distance data. We provide a case study of HDS applied to a survey of the island scrub-jay on Santa Cruz Island, California.
Minimax terminal approach problem in two-level hierarchical nonlinear discrete-time dynamical system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shorikov, A. F., E-mail: afshorikov@mail.ru
We consider a discrete–time dynamical system consisting of three controllable objects. The motions of all objects are given by the corresponding vector nonlinear or linear discrete–time recurrent vector relations, and control system for its has two levels: basic (first or I level) that is dominating and subordinate level (second or II level) and both have different criterions of functioning and united a priori by determined informational and control connections defined in advance. For the dynamical system in question, we propose a mathematical formalization in the form of solving a multistep problem of two-level hierarchical minimax program control over the terminalmore » approach process with incomplete information and give a general scheme for its solving.« less
Arab, Ali; Holan, Scott H.; Wikle, Christopher K.; Wildhaber, Mark L.
2012-01-01
Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.
Developing human capital: what is the impact on nurse turnover?
Rondeau, Kent V; Williams, Eric S; Wagar, Terry H
2009-09-01
To investigate the impact that increasing human capital through staff training makes on the voluntary turnover of registered nurses. Healthcare organizations in Canada, the United Kingdom, the United States, and Australia are experiencing turbulent nursing labour markets characterized by extreme staff shortages and high levels of turnover. Organizations that invest in the development of their nursing human resources may be able to mitigate high turnover through the creation of conditions that more effectively develop and utilize their existing human capital. A questionnaire was sent to the chief nursing officers of 2208 hospitals and long-term care facilities in every province and territory of Canada yielding a response rate of 32.3%. The analysis featured a three-step hierarchical regression with two sets of control variables. After controlling for establishment demographics and local labour market conditions, perceptions of nursing human capital and the level of staff training provided were modestly associated with lower levels of establishment turnover. and implications for Nursing Management The results suggest that healthcare organizations that have made greater investments in their nursing human capital are more likely to demonstrate lower levels of turnover of their registered nursing personnel.
Accelerated decomposition techniques for large discounted Markov decision processes
NASA Astrophysics Data System (ADS)
Larach, Abdelhadi; Chafik, S.; Daoui, C.
2017-12-01
Many hierarchical techniques to solve large Markov decision processes (MDPs) are based on the partition of the state space into strongly connected components (SCCs) that can be classified into some levels. In each level, smaller problems named restricted MDPs are solved, and then these partial solutions are combined to obtain the global solution. In this paper, we first propose a novel algorithm, which is a variant of Tarjan's algorithm that simultaneously finds the SCCs and their belonging levels. Second, a new definition of the restricted MDPs is presented to ameliorate some hierarchical solutions in discounted MDPs using value iteration (VI) algorithm based on a list of state-action successors. Finally, a robotic motion-planning example and the experiment results are presented to illustrate the benefit of the proposed decomposition algorithms.
Time-series analyses of air pollution and mortality in the United States: a subsampling approach.
Moolgavkar, Suresh H; McClellan, Roger O; Dewanji, Anup; Turim, Jay; Luebeck, E Georg; Edwards, Melanie
2013-01-01
Hierarchical Bayesian methods have been used in previous papers to estimate national mean effects of air pollutants on daily deaths in time-series analyses. We obtained maximum likelihood estimates of the common national effects of the criteria pollutants on mortality based on time-series data from ≤ 108 metropolitan areas in the United States. We used a subsampling bootstrap procedure to obtain the maximum likelihood estimates and confidence bounds for common national effects of the criteria pollutants, as measured by the percentage increase in daily mortality associated with a unit increase in daily 24-hr mean pollutant concentration on the previous day, while controlling for weather and temporal trends. We considered five pollutants [PM10, ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), and sulfur dioxide (SO2)] in single- and multipollutant analyses. Flexible ambient concentration-response models for the pollutant effects were considered as well. We performed limited sensitivity analyses with different degrees of freedom for time trends. In single-pollutant models, we observed significant associations of daily deaths with all pollutants. The O3 coefficient was highly sensitive to the degree of smoothing of time trends. Among the gases, SO2 and NO2 were most strongly associated with mortality. The flexible ambient concentration-response curve for O3 showed evidence of nonlinearity and a threshold at about 30 ppb. Differences between the results of our analyses and those reported from using the Bayesian approach suggest that estimates of the quantitative impact of pollutants depend on the choice of statistical approach, although results are not directly comparable because they are based on different data. In addition, the estimate of the O3-mortality coefficient depends on the amount of smoothing of time trends.
Facile synthesis of hierarchical porous VOx@carbon composites for supercapacitors.
Zhao, Chunxia; Cao, Jinqiao; Yang, Yunxia; Chen, Wen; Li, Junshen
2014-08-01
Hierarchical or micro-nano structured porous VOx@carbon composites were synthesized by a one-step method using phenolic resin as the carbon precursor and ammonium metavanadate as the source of vanadium oxides. The effects of the vanadium source loading on the microstructure and electrochemical properties of the composites were investigated. X-ray diffraction results showed that as the vanadium oxides source loading increased, vanadium oxides in the composites changed oxidation states from V2O3 to mixed states of V2O3 and VO2. Electrochemical test results indicated that the micro-nano porous structure of the composites could facilitate the ion diffusion in the rich porous structure and then promote the electrochemical reaction. More importantly, we found that vanadium oxides greatly enhanced the electrochemical performance of the materials, due to the faradic capacitance generated from vanadium oxide nanoparticles. A maximum specific capacitance of 171 F/g was obtained from VOx@carbon composite with vanadium loading of ∼44 wt%. Further increasing the VOx loading over this fraction was not beneficial. Our results suggested that hierarchical porous VOx@carbon composites were promising candidates for supercapacitor applications. Copyright © 2013 Elsevier Inc. All rights reserved.
Compression of 3D Point Clouds Using a Region-Adaptive Hierarchical Transform.
De Queiroz, Ricardo; Chou, Philip A
2016-06-01
In free-viewpoint video, there is a recent trend to represent scene objects as solids rather than using multiple depth maps. Point clouds have been used in computer graphics for a long time and with the recent possibility of real time capturing and rendering, point clouds have been favored over meshes in order to save computation. Each point in the cloud is associated with its 3D position and its color. We devise a method to compress the colors in point clouds which is based on a hierarchical transform and arithmetic coding. The transform is a hierarchical sub-band transform that resembles an adaptive variation of a Haar wavelet. The arithmetic encoding of the coefficients assumes Laplace distributions, one per sub-band. The Laplace parameter for each distribution is transmitted to the decoder using a custom method. The geometry of the point cloud is encoded using the well-established octtree scanning. Results show that the proposed solution performs comparably to the current state-of-the-art, in many occasions outperforming it, while being much more computationally efficient. We believe this work represents the state-of-the-art in intra-frame compression of point clouds for real-time 3D video.
Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation.
Sun, Rui; Zhang, Guanghai; Yan, Xiaoxing; Gao, Jun
2016-08-16
Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.
Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation
Sun, Rui; Zhang, Guanghai; Yan, Xiaoxing; Gao, Jun
2016-01-01
Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods. PMID:27537888
Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.
Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano
2016-08-18
This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.
Hierarchical organization of functional connectivity in the mouse brain: a complex network approach
NASA Astrophysics Data System (ADS)
Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano
2016-08-01
This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.
Anatomy of exotic Higgs decays in 2HDM
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kling, Felix; No, Jose Miguel; Su, Shufang
Large mass splittings between new scalars in two-Higgs-doublet models (2HDM) open a key avenue to search for these new states via exotic heavy Higgs decays. We discuss in detail the different search channels for these new scalars at the LHC in the presence of a sizable mass splitting, i.e. a hierarchical 2HDM scenario, taking into account the theoretical and experimental constraints. Here, we provide benchmark planes to exploit the complementarity among these searches, analyzing their potential to probe the hierarchical 2HDM parameter space during LHC Run 2.
Anatomy of exotic Higgs decays in 2HDM
NASA Astrophysics Data System (ADS)
Kling, Felix; No, Jose Miguel; Su, Shufang
2016-09-01
Large mass splittings between new scalars in two-Higgs-doublet models (2HDM) open a key avenue to search for these new states via exotic heavy Higgs decays. We discuss in detail the different search channels for these new scalars at the LHC in the presence of a sizable mass splitting, i.e. a hierarchical 2HDM scenario, taking into account the theoretical and experimental constraints. We provide benchmark planes to exploit the complementarity among these searches, analyzing their potential to probe the hierarchical 2HDM parameter space during LHC Run 2.
Anatomy of exotic Higgs decays in 2HDM
Kling, Felix; No, Jose Miguel; Su, Shufang
2016-09-16
Large mass splittings between new scalars in two-Higgs-doublet models (2HDM) open a key avenue to search for these new states via exotic heavy Higgs decays. We discuss in detail the different search channels for these new scalars at the LHC in the presence of a sizable mass splitting, i.e. a hierarchical 2HDM scenario, taking into account the theoretical and experimental constraints. Here, we provide benchmark planes to exploit the complementarity among these searches, analyzing their potential to probe the hierarchical 2HDM parameter space during LHC Run 2.
Differences in school climate and student engagement in China and the United States.
Bear, George G; Yang, Chunyan; Chen, Dandan; He, Xianyou; Xie, Jia-Shu; Huang, Xishan
2018-06-01
The purpose of this study was to examine differences between American and Chinese students in their perceptions of school climate and engagement in school, and in the relation between school climate and engagement. Confirmatory factor analyses were used to support the factor structure and measurement invariance of the two measures administered: The Delaware School Climate Survey-Student and the Delaware Student Engagement Scale. Differences in latent means were tested, and differences in relations between variables were examined using multilevel hierarchical linear modeling. Participants consisted of 3,176 Chinese and 4,085 American students, Grades 3-5, 7-8, and 10-12. Chinese students perceived school climate more favorably than American students, particularly beyond elementary school. Findings were more complex for student engagement. In elementary school, American students reported greater cognitive-behavioral and emotional engagement, and especially the former. In middle school and high school, Chinese students reported greater emotional engagement; however, no significant differences were found for cognitive-behavioral engagement. Most intriguing were results of multilevel hierarchical modeling that examined associations between school climate and student engagement: They were significant in American schools but not Chinese schools. Chinese students, compared with American students, perceived the climate of their schools more favorably, especially after elementary school. However, among Chinese students, their perceptions of school climate were unrelated to their self-reported engagement in school-school climate did not seem to matter as much. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Hierarchical organization in the temporal structure of infant-direct speech and song.
Falk, Simone; Kello, Christopher T
2017-06-01
Caregivers alter the temporal structure of their utterances when talking and singing to infants compared with adult communication. The present study tested whether temporal variability in infant-directed registers serves to emphasize the hierarchical temporal structure of speech. Fifteen German-speaking mothers sang a play song and told a story to their 6-months-old infants, or to an adult. Recordings were analyzed using a recently developed method that determines the degree of nested clustering of temporal events in speech. Events were defined as peaks in the amplitude envelope, and clusters of various sizes related to periods of acoustic speech energy at varying timescales. Infant-directed speech and song clearly showed greater event clustering compared with adult-directed registers, at multiple timescales of hundreds of milliseconds to tens of seconds. We discuss the relation of this newly discovered acoustic property to temporal variability in linguistic units and its potential implications for parent-infant communication and infants learning the hierarchical structures of speech and language. Copyright © 2017 Elsevier B.V. All rights reserved.
Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.
Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong
Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.
NASA Astrophysics Data System (ADS)
Hachay, Olga; Khachay, Andrey
2015-04-01
The last decades are characterized by active development of Earth's sciences. The modern research methods and technologies give the opportunity to obtain new data about the Earth's structure and processes, which occur in its interior. The conception development about the nonlinear geodynamics practically coincides with research of nonlinear processes in different parts of physics. In geology soliton and auto wave conceptions are developed, principles of synergetic and self organization become be used, in geodynamics the macro quantum behavior of large mass matter, which are in critical state, in geophysics the auto wave nature of geophysical fields is researched in a frame of a new structural model with hierarchical inclusions. It is very significant to define the time of reaction lagging, in spite of the influence on the massif can be assumed as elastic. The unique model which can explain that effect is a model of the massif with a hierarchic structure. We developed a mathematical algorithm using integral and integral-differential equations for 2-D model for two problems in a frequency domain: diffraction a sound wave and linear polarized transverse wave through a arbitrary hierarchy rank inclusion plunged in an N-layered medium. That algorithm differs from the fractal model approach by a freer selecting of heterogeneities position of each rank. And the second, the problem is solved in the dynamical approach. The higher the amount of the hierarchic ranks the more is the degree of nonlinearity of the massive response and the longer can be the time of massive reaction lag of the influence. For research of hierarchic medium we had developed an iterative algorithm for electromagnetic and seismic fields in the problem setting similar to analyze higher for layered-block models with homogeneous inclusions. We had developed an iterative algorithm of inverse problem solution for the same models, using the approach of three stage interpretation. For that we had developed a new integral differential equation for the theoretical inverse problem of 2-D electromagnetic field in a hierarchic inclusion, embedded in the N-layered medium. References: Hachay O.A. et al.(2008 a) Modeling of seismic and electromagnetic field in the hierarchic heterogeneous media. Proceedings of International conference. Ekaterinburg: IGF UB RAS Hachay O.A. et al. (2008 b).Complex electromagnetic and seismic method of research of the crust and Earth's mantle structure. Proceedings of International conference. Ekaterinburg: IGF UB RAS Hachay O.A. et al. (2013) Modeling of electromagnetic and seismic fields in hierarchic heterogeneous media. Bulletin of South Ural State University. Series:"Computational mathematics and Software Engineering". 2: 48-55.
Assari, Shervin
2013-02-01
To test if social support and ethnicity mediate/moderate the association between religion involvement and subjective health in the United States. This is a secondary analysis of National Survey of American Life, 2003. Hierarchical regression was fit to a national household probability sample of adult African Americans (n = 3570), Caribbean Blacks (n = 1621), and Whites (n = 891). Frequency of church attendance, positive/negative church-based social support, ethnicity, and subjective health (overall life satisfaction and self-rated mental health) were considered as predictor, mediator, moderator and outcome, respectively. Frequency of church attendance had a significant and positive association with mental health and life satisfaction among all ethnic groups. Frequency of church attendance was also correlated with positive and negative social support among all ethnic groups. Church-based social support fully mediated the association between frequency of church attendance and overall life satisfaction among African Americans but not among Caribbean Blacks, or Whites. Church-based social support, however, partially mediated the association between frequency of church attendance and overall mental health among African Americans but not among Caribbean Blacks or Whites. Ethnicity shapes how church-based social support mediates the association between religious involvement and subjective health. Our results showed a moderating mediation effect of ethnicity and social support on the religious involvement-subjective health linkage, in a way that it is only among African Americans that social support is a pathway for the beneficial health effect of religious involvement.
Chambers, Brittany D; Erausquin, Jennifer Toller; Tanner, Amanda E; Nichols, Tracy R; Brown-Jeffy, Shelly
2017-12-07
Despite decreases in infants born premature and at low birth weight in the United States (U.S.), racial disparities between Black and White women continue. In response, the purpose of this analysis was to examine associations between both traditional and novel indicators of county-level structural racism and birth outcomes among Black and White women. We merged individual-level data from the California Birth Statistical Master Files 2009-2013 with county-level data from the United States (U.S.) Census American Community Survey. We used hierarchical linear modeling to examine Black-White differences among 531,170 primiparous women across 33 California counties. Traditional (e.g., dissimilarity index) and novel indicators (e.g., Black to White ratio in elected office) were associated with earlier gestational age and lower birth weight among Black and White women. A traditional indicator was more strongly associated with earlier gestational age for Black women than for White women. This was the first study to empirically demonstrate that structural racism, measured by both traditional and novel indicators, is associated with poor health and wellbeing of infants born to Black and White women. However, findings indicate traditional indicators of structural racism, rather than novel indicators, better explain racial disparities in birth outcomes. Results also suggest the need to develop more innovative approaches to: (1) measure structural racism at the county-level and (2) reform public policies to increase integration and access to resources.
Mental Health Correlates of Cigarette Use in LGBT Individuals in the Southeastern United States.
Drescher, Christopher F; Lopez, Eliot J; Griffin, James A; Toomey, Thomas M; Eldridge, Elizabeth D; Stepleman, Lara M
2018-05-12
Smoking prevalence for lesbian, gay, bisexual, and transgender (LGBT) individuals is higher than for heterosexual, cisgender individuals. Elevated smoking rates have been linked to psychiatric comorbidities, substance use, poverty, low education levels, and stress. This study examined mental health (MH) correlates of cigarette use in LGBT individuals residing in a metropolitan area in the southeastern United States. Participants were 335 individuals from an LGBT health needs assessment (mean age 34.7; SD = 13.5; 63% gay/lesbian; 66% Caucasian; 81% cisgender). Demographics, current/past psychiatric diagnoses, number of poor MH days in the last 30, the Patient Health Questionnaire (PHQ) 2 depression screener, the Three-Item Loneliness Scale, and frequency of cigarette use were included. Analyses included bivariate correlations, analysis of variance (ANOVA), and regression. Multiple demographic and MH factors were associated with smoker status and frequency of smoking. A logistic regression indicated that lower education and bipolar disorder were most strongly associated with being a smoker. For smokers, a hierarchical regression model including demographic and MH variables accounted for 17.6% of the variance in frequency of cigarette use. Only education, bipolar disorder, and the number of poor MH days were significant contributors in the overall model. Conclusions/Importance: Less education, bipolar disorder, and recurrent poor MH increase LGBT vulnerability to cigarette use. Access to LGBT-competent MH providers who can address culturally specific factors in tobacco cessation is crucial to reducing this health disparities.