USGS: Building on leadership in mapping oceans and coasts

USGS Publications Warehouse

Myers, M.D.

2008-01-01

The US Geological Survey (USGS) offers continuously improving technologies for mapping oceans and coasts providing unique opportunity for characterizing the marine environment and to expand the understanding of coastal and ocean processes, resources, and hazards. USGS, which has been designated as a leader for mapping the Exclusive Economic Zone, has made an advanced strategic plan, Facing Tomorrow's Challenges- US Geological Survey Science in the Decade 2007 to 2017. This plan focuses on innovative and transformational themes that serve key clients and customers, expand partnerships, and have long-term national impact. The plan includes several key science directions, including Understanding Ecosystems and Predicting Ecosystem Change, Energy and Minerals for America's Future, and A National Hazards, Risk, and Resilience Assessment Program. USGS has also collaborated with diverse partners to incorporate mapping and monitoring within interdisciplinary research programs, addressing the system-scale response of coastal and marine ecosystems.

Bathymetry, acoustic backscatter, and seafloor character of Farallon Escarpment and Rittenburg Bank, northern California

USGS Publications Warehouse

Dartnell, Peter; Cochrane, Guy R.; Finlayson, David P.

2014-01-01

In 2011, scientists from the U.S. Geological Survey’s Coastal and Marine Geology Program acquired bathymetry and acoustic-backscatter data along the upper slope of the Farallon Escarpment and Rittenburg Bank within the Gulf of the Farallones National Marine Sanctuary offshore of the San Francisco Bay area. The surveys were funded by the National Oceanic and Atmospheric Administration’s Deep Sea Coral Research and Technology Program to identify potential deep sea coral habitat prior to planned sampling efforts. Bathymetry and acoustic-backscatter data can be used to map seafloor geology (rock, sand, mud), and slope of the sea floor, both of which are useful for the prediction of deep sea coral habitat. The data also can be used for the prediction of sediment and contaminant budgets and transport, and for the assessment of earthquake and tsunami hazards. The surveys were conducted aboard National Oceanic and Atmospheric Administration’s National Marine Sanctuary Program’s 67-foot-long research vessel Fulmar outfitted with a U.S. Geological Survey 100-kHz Reson 7111 multibeam-echosounder system. This report provides the bathymetry and backscatter data acquired during these surveys, interpretive seafloor character maps in several formats, a summary of the mapping mission, maps of bathymetry and backscatter, and Federal Geographic Data Committee metadata.

Landsat for practical forest type mapping - A test case

NASA Technical Reports Server (NTRS)

Bryant, E.; Dodge, A. G., Jr.; Warren, S. D.

1980-01-01

Computer classified Landsat maps are compared with a recent conventional inventory of forest lands in northern Maine. Over the 196,000 hectare area mapped, estimates of the areas of softwood, mixed wood and hardwood forest obtained by a supervised classification of the Landsat data and a standard inventory based on aerial photointerpretation, probability proportional to prediction, field sampling and a standard forest measurement program are found to agree to within 5%. The cost of the Landsat maps is estimated to be $0.065/hectare. It is concluded that satellite techniques are worth developing for forest inventories, although they are not yet refined enough to be incorporated into current practical inventories.

Predicting successful tactile mapping of virtual objects.

PubMed

Brayda, Luca; Campus, Claudio; Gori, Monica

2013-01-01

Improving spatial ability of blind and visually impaired people is the main target of orientation and mobility (O&M) programs. In this study, we use a minimalistic mouse-shaped haptic device to show a new approach aimed at evaluating devices providing tactile representations of virtual objects. We consider psychophysical, behavioral, and subjective parameters to clarify under which circumstances mental representations of spaces (cognitive maps) can be efficiently constructed with touch by blindfolded sighted subjects. We study two complementary processes that determine map construction: low-level perception (in a passive stimulation task) and high-level information integration (in an active exploration task). We show that jointly considering a behavioral measure of information acquisition and a subjective measure of cognitive load can give an accurate prediction and a practical interpretation of mapping performance. Our simple TActile MOuse (TAMO) uses haptics to assess spatial ability: this may help individuals who are blind or visually impaired to be better evaluated by O&M practitioners or to evaluate their own performance.

National Oceanic and Atmospheric Administration's Cetacean and Sound Mapping Effort: Continuing Forward with an Integrated Ocean Noise Strategy.

PubMed

Harrison, Jolie; Ferguson, Megan; Gedamke, Jason; Hatch, Leila; Southall, Brandon; Van Parijs, Sofie

2016-01-01

To help manage chronic and cumulative impacts of human activities on marine mammals, the National Oceanic and Atmospheric Administration (NOAA) convened two working groups, the Underwater Sound Field Mapping Working Group (SoundMap) and the Cetacean Density and Distribution Mapping Working Group (CetMap), with overarching effort of both groups referred to as CetSound, which (1) mapped the predicted contribution of human sound sources to ocean noise and (2) provided region/time/species-specific cetacean density and distribution maps. Mapping products were presented at a symposium where future priorities were identified, including institutionalization/integration of the CetSound effort within NOAA-wide goals and programs, creation of forums and mechanisms for external input and funding, and expanded outreach/education. NOAA is subsequently developing an ocean noise strategy to articulate noise conservation goals and further identify science and management actions needed to support them.

Spatial Patterns of High Aedes aegypti Oviposition Activity in Northwestern Argentina

PubMed Central

Estallo, Elizabet Lilia; Más, Guillermo; Vergara-Cid, Carolina; Lanfri, Mario Alberto; Ludueña-Almeida, Francisco; Scavuzzo, Carlos Marcelo; Introini, María Virginia; Zaidenberg, Mario; Almirón, Walter Ricardo

2013-01-01

Background In Argentina, dengue has affected mainly the Northern provinces, including Salta. The objective of this study was to analyze the spatial patterns of high Aedes aegypti oviposition activity in San Ramón de la Nueva Orán, northwestern Argentina. The location of clusters as hot spot areas should help control programs to identify priority areas and allocate their resources more effectively. Methodology Oviposition activity was detected in Orán City (Salta province) using ovitraps, weekly replaced (October 2005–2007). Spatial autocorrelation was measured with Moran’s Index and depicted through cluster maps to identify hot spots. Total egg numbers were spatially interpolated and a classified map with Ae. aegypti high oviposition activity areas was performed. Potential breeding and resting (PBR) sites were geo-referenced. A logistic regression analysis of interpolated egg numbers and PBR location was performed to generate a predictive mapping of mosquito oviposition activity. Principal Findings Both cluster maps and predictive map were consistent, identifying in central and southern areas of the city high Ae. aegypti oviposition activity. A logistic regression model was successfully developed to predict Ae. aegypti oviposition activity based on distance to PBR sites, with tire dumps having the strongest association with mosquito oviposition activity. A predictive map reflecting probability of oviposition activity was produced. The predictive map delimitated an area of maximum probability of Ae. aegypti oviposition activity in the south of Orán city where tire dumps predominate. The overall fit of the model was acceptable (ROC = 0.77), obtaining 99% of sensitivity and 75.29% of specificity. Conclusions Distance to tire dumps is inversely associated with high mosquito activity, allowing us to identify hot spots. These methodologies are useful for prevention, surveillance, and control of tropical vector borne diseases and might assist National Health Ministry to focus resources more effectively. PMID:23349813

Multi-Scale Mapping of Vegetation Biomass

NASA Astrophysics Data System (ADS)

Hudak, A. T.; Fekety, P.; Falkowski, M. J.; Kennedy, R. E.; Crookston, N.; Smith, A. M.; Mahoney, P.; Glenn, N. F.; Dong, J.; Kane, V. R.; Woodall, C. W.

2016-12-01

Vegetation biomass mapping at multiple scales is important for carbon inventory and monitoring, reporting, and verification (MRV). Project-level lidar collections allow biomass estimation with high confidence where associated with field plot measurements. Predictive models developed from such datasets are customarily used to generate landscape-scale biomass maps. We tested the feasibility of predicting biomass in landscapes surveyed with lidar but without field plots, by withholding plot datasets from a reduced model applied to the landscapes, and found support for a generalized model in the northern Idaho ecoregion. We are also upscaling a generalized model to all forested lands in Idaho. Our regional modeling approach is to sample the 30-m biomass predictions from the landscape-scale maps and use them to train a regional biomass model, using Landsat time series, topographic derivatives, and climate variables as predictors. Our regional map validation approach is to aggregate the regional, annual biomass predictions to the county level and compare them to annual county-level biomass summarized independently from systematic, field-based, annual inventories conducted by the US Forest Inventory and Analysis (FIA) Program nationally. A national-scale forest cover map generated independently from 2010 PALSAR data at 25-m resolution is being used to mask non-forest pixels from the aggregations. Effects of climate change on future regional biomass stores are also being explored, using biomass estimates projected from stand-level inventory data collected in the National Forests and comparing them to FIA plot data collected independently on public and private lands, projected under the same climate change scenarios, with disturbance trends extracted from the Landsat time series. Our ultimate goal is to demonstrate, focusing on the ecologically diverse Northwest region of the USA, a carbon monitoring system (CMS) that is accurate, objective, repeatable, and transparent.

MOCAT: A Metagenomics Assembly and Gene Prediction Toolkit

PubMed Central

Li, Junhua; Chen, Weineng; Chen, Hua; Mende, Daniel R.; Arumugam, Manimozhiyan; Pan, Qi; Liu, Binghang; Qin, Junjie; Wang, Jun; Bork, Peer

2012-01-01

MOCAT is a highly configurable, modular pipeline for fast, standardized processing of single or paired-end sequencing data generated by the Illumina platform. The pipeline uses state-of-the-art programs to quality control, map, and assemble reads from metagenomic samples sequenced at a depth of several billion base pairs, and predict protein-coding genes on assembled metagenomes. Mapping against reference databases allows for read extraction or removal, as well as abundance calculations. Relevant statistics for each processing step can be summarized into multi-sheet Excel documents and queryable SQL databases. MOCAT runs on UNIX machines and integrates seamlessly with the SGE and PBS queuing systems, commonly used to process large datasets. The open source code and modular architecture allow users to modify or exchange the programs that are utilized in the various processing steps. Individual processing steps and parameters were benchmarked and tested on artificial, real, and simulated metagenomes resulting in an improvement of selected quality metrics. MOCAT can be freely downloaded at http://www.bork.embl.de/mocat/. PMID:23082188

MOCAT: a metagenomics assembly and gene prediction toolkit.

PubMed

Kultima, Jens Roat; Sunagawa, Shinichi; Li, Junhua; Chen, Weineng; Chen, Hua; Mende, Daniel R; Arumugam, Manimozhiyan; Pan, Qi; Liu, Binghang; Qin, Junjie; Wang, Jun; Bork, Peer

2012-01-01

MOCAT is a highly configurable, modular pipeline for fast, standardized processing of single or paired-end sequencing data generated by the Illumina platform. The pipeline uses state-of-the-art programs to quality control, map, and assemble reads from metagenomic samples sequenced at a depth of several billion base pairs, and predict protein-coding genes on assembled metagenomes. Mapping against reference databases allows for read extraction or removal, as well as abundance calculations. Relevant statistics for each processing step can be summarized into multi-sheet Excel documents and queryable SQL databases. MOCAT runs on UNIX machines and integrates seamlessly with the SGE and PBS queuing systems, commonly used to process large datasets. The open source code and modular architecture allow users to modify or exchange the programs that are utilized in the various processing steps. Individual processing steps and parameters were benchmarked and tested on artificial, real, and simulated metagenomes resulting in an improvement of selected quality metrics. MOCAT can be freely downloaded at http://www.bork.embl.de/mocat/.

Satellite Capabilities Mapping - Utilizing Small Satellites

DTIC Science & Technology

2010-09-01

Metrics Definition…………………………..50 Figure 19. System and Requirements Decomposition…………………………………...59 Figure 20. TPS Fuctional Mapping Process...offered by small satellites. “The primary force in our corner of the universe is our sun. The sun is constantly radiating enormous amounts of...weather prediction models, a primary tool for forecasting weather” [19]. The NPOESS was a tri-agency program intended to develop and operate the next

Assess, Map and Predict the Integrity, Resilience, and ...

EPA Pesticide Factsheets

This project will provide knowledge and adaptive management techniques to both maintain healthy waters and to improve degraded systems. It will provide scientific support for the National Aquatic Resource Surveys. Results will provide a basis for informed decision making and tools applicable to EPA program office and regional needs at national regional, and local scales. The research products, tools, models, and maps produced will be an excellent means to communicate management options with stakeholders. To share information about SSWR research projects

Community-Based Mindfulness Program for Disease Prevention and Health Promotion: Targeting Stress Reduction.

PubMed

Galla, Brian M; O'Reilly, Gillian A; Kitil, M Jennifer; Smalley, Susan L; Black, David S

2015-01-01

Poorly managed stress leads to detrimental physical and psychological consequences that have implications for individual and community health. Evidence indicates that U.S. adults predominantly use unhealthy strategies for stress management. This study examines the impact of a community-based mindfulness training program on stress reduction. This study used a one-group pretest-posttest design. The study took place at the UCLA Mindful Awareness Research Center in urban Los Angeles. A sample of N = 127 community residents (84% Caucasian, 74% female) were included in the study. Participants received mindfulness training through the Mindful Awareness Practices (MAPs) for Daily Living I. Mindfulness, self-compassion, and perceived stress were measured at baseline and postintervention. Paired-sample t-tests were used to test for changes in outcome measures from baseline to postintervention. Hierarchical regression analysis was fit to examine whether change in self-reported mindfulness and self-compassion predicted postintervention perceived stress scores. There were statistically significant improvements in self-reported mindfulness (t = -10.67, p < .001, d = .90), self-compassion (t = -8.50, p < .001, d = .62), and perceived stress (t = 9.28, p < .001, d = -.78) at postintervention. Change in self-compassion predicted postintervention perceived stress (β = -.44, t = -5.06, p < .001), but change in mindfulness did not predict postintervention perceived stress (β = -.04, t = -.41, p = .68). These results indicate that a community-based mindfulness training program can lead to reduced levels of psychological stress. Mindfulness training programs such as MAPs may offer a promising approach for general public health promotion through improving stress management in the urban community.

Environmental Impact Research Program: Reservoir Bank Erosion and Cultural Resources: Experiments in Mapping and Predicting the Erosion of Archeological Sediments at Reservoirs Along the Middle Missouri River with Sequential Historical Aerial Photographs

DTIC Science & Technology

1989-08-01

points on both the photos and base map. Transects placed at 100-m intervals along the waterline, oriented perpendicular to the gradient or slope just...the identifica- tion of major factors influencing bank erosion, independent variables measured included gradient of the land at the intersection of...have a very steep gradient , approaching vertical in some cases, broken only by intermittent minor drainages which have dissected terrace margins. b

Colorado Lightning Mapping Array Collaborations through the GOES-R Visiting Scientist Program

NASA Technical Reports Server (NTRS)

Stano, Geoffrey T.; Szoke, Edward; Rydell, Nezette; Cox, Robert; Mazur, Rebecca

2014-01-01

For the past two years, the GOES-R Proving Ground has solicited proposals for its Visiting Scientist Program. NASA's Short-term Prediction Research and Transition (SPoRT) Center has used this opportunity to support the GOES-R Proving Ground by expanding SPoRT's total lightning collaborations. In 2012, this expanded the evaluation of SPoRT's pseudo-geostationary lightning mapper product to the Aviation Weather Center and Storm Prediction Center. This year, SPoRT has collaborated with the Colorado Lightning Mapping Array (COLMA) and potential end users. In particular, SPoRT is collaborating with the Cooperative Institute for Research in the Atmosphere (CIRA) and Colorado State University (CSU) to obtain these data in real-time. From there, SPoRT is supporting the transition of these data to the local forecast offices in Boulder, Colorado and Cheyenne, Wyoming as well as to Proving Ground projects (e.g., the Hazardous Weather Testbed's Spring Program and Aviation Weather Center's Summer Experiment). This presentation will focus on the results of this particular Visiting Scientist Program trip. In particular, the COLMA data are being provided to both forecast offices for initial familiarization. Additionally, several forecast issues have been highlighted as important uses for COLMA data in the operational environment. These include the utility of these data for fire weather situations, situational awareness for both severe weather and lightning safety, and formal evaluations to take place in the spring of 2014.

Fifty year canon of solar eclipses: 1986 - 2035

NASA Technical Reports Server (NTRS)

Espenak, Fred

1987-01-01

A complete catalog is presented, listing the general characteristics of every solar eclipse from 1901 through 2100. To complement this catalog, a detailed set of cylindrical projection world maps shows the umbral paths of every solar eclipse over the 200 year interval. Focusing in on the next 50 years, accurate geodetic path coordinates and local circumstances for the 71 central eclipses from 1987 through 2035 are tabulated. Finally, the geodetic paths of the umbral and penumbral shadows of all 109 solar eclipses in this period are plotted on orthographic projection maps of the Earth. Appendices are included which discuss eclipse geometry, eclipse frequency and occurrence, modern eclipse prediction and time determination. Finally, code for a simple Fortran program is given to predict the occurrence and characteristics of solar eclipses.

Characteristics of genomic signatures derived using univariate methods and mechanistically anchored functional descriptors for predicting drug- and xenobiotic-induced nephrotoxicity.

PubMed

Shi, Weiwei; Bugrim, Andrej; Nikolsky, Yuri; Nikolskya, Tatiana; Brennan, Richard J

2008-01-01

ABSTRACT The ideal toxicity biomarker is composed of the properties of prediction (is detected prior to traditional pathological signs of injury), accuracy (high sensitivity and specificity), and mechanistic relationships to the endpoint measured (biological relevance). Gene expression-based toxicity biomarkers ("signatures") have shown good predictive power and accuracy, but are difficult to interpret biologically. We have compared different statistical methods of feature selection with knowledge-based approaches, using GeneGo's database of canonical pathway maps, to generate gene sets for the classification of renal tubule toxicity. The gene set selection algorithms include four univariate analyses: t-statistics, fold-change, B-statistics, and RankProd, and their combination and overlap for the identification of differentially expressed probes. Enrichment analysis following the results of the four univariate analyses, Hotelling T-square test, and, finally out-of-bag selection, a variant of cross-validation, were used to identify canonical pathway maps-sets of genes coordinately involved in key biological processes-with classification power. Differentially expressed genes identified by the different statistical univariate analyses all generated reasonably performing classifiers of tubule toxicity. Maps identified by enrichment analysis or Hotelling T-square had lower classification power, but highlighted perturbed lipid homeostasis as a common discriminator of nephrotoxic treatments. The out-of-bag method yielded the best functionally integrated classifier. The map "ephrins signaling" performed comparably to a classifier derived using sparse linear programming, a machine learning algorithm, and represents a signaling network specifically involved in renal tubule development and integrity. Such functional descriptors of toxicity promise to better integrate predictive toxicogenomics with mechanistic analysis, facilitating the interpretation and risk assessment of predictive genomic investigations.

Objective rapid delineation of areas at risk from block-and-ash pyroclastic flows and surges

USGS Publications Warehouse

Widiwijayanti, C.; Voight, B.; Hidayat, D.; Schilling, S.P.

2009-01-01

Assessments of pyroclastic flow (PF) hazards are commonly based on mapping of PF and surge deposits and estimations of inundation limits, and/or computer models of varying degrees of sophistication. In volcanic crises a PF hazard map may be sorely needed, but limited time, exposures, or safety aspects may preclude fieldwork, and insufficient time or baseline data may be available for reliable dynamic simulations. We have developed a statistically constrained simulation model for block-and-ash type PFs to estimate potential areas of inundation by adapting methodology from Iverson et al. (Geol Soc America Bull 110:972-984, (1998) for lahars. The predictive equations for block-and-ash PFs are calibrated with data from several volcanoes and given by A = (0.05 to 0.1) V2/3, B = (35 to 40) V2/3, where A is cross-sectional area of inundation, B is planimetric area and V is deposit volume. The proportionality coefficients were obtained from regression analyses and comparison of simulations to mapped deposits. The method embeds the predictive equations in a GIS program coupled with DEM topography, using the LAHARZ program of Schilling (1998). Although the method is objective and reproducible, any PF hazard zone so computed should be considered as an approximate guide only, due to uncertainties on the coefficients applicable to individual PFs, the authenticity of DEM details, and the volume of future collapses. The statistical uncertainty of the predictive equations, which imply a factor of two or more in predicting A or B for a specified V, is superposed on the uncertainty of forecasting V for the next PF to descend a particular valley. Multiple inundation zones, produced by simulations using a selected range of volumes, partly accommodate these uncertainties. The resulting maps show graphically that PF inundation potentials are highest nearest volcano sources and along valley thalwegs, and diminish with distance from source and lateral distance from thalweg. The model does not explicitly consider dynamic behavior, which can be important. Ash-cloud surge impact limits must be extended beyond PF hazard zones and we provide several approaches to do this. The method has been used to supply PF and surge hazard maps in two crises: Merapi 2006; and Montserrat 2006-2007. ?? Springer-Verlag 2008.

Developing and Delivering National-Scale Gridded Phenology Data Products

NASA Astrophysics Data System (ADS)

Marsh, L.; Crimmins, M.; Crimmins, T. M.; Gerst, K.; Rosemartin, A.; Switzer, J.; Weltzin, J. F.

2016-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) is now producing and freely delivering daily maps and short-term forecasts of accumulated growing degree days and spring onset dates (based on the Extended Spring Indices) at fine spatial scale for the conterminous United States. These data products have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, determining planting dates, anticipating allergy outbreaks and planning agricultural harvest dates. Accumulated growing degree day (AGDD) maps were selected because accumulated temperature is a strong driver of phenological transitions in plants and animals, including leaf-out, flowering, fruit ripening and migration. The Extended Spring Indices (SI-x) are based on predictive climate models for lilac and honeysuckle leaf and bloom; they have been widely used to summarize changes in the timing of spring onset. The SI-x is used as a national indicator of climate change impacts by the US Global Change Research Program and the Environmental Protection Agency. The USA-NPN is a national-scale program that supports scientific advancement and decision-making by collecting, storing, and sharing phenology data and information. To best serve various audiences, the AGDD and SI-x gridded maps are available in various formats through a range of access tools, including the USA-NPN online visualization tool as well as industry standards compliant web services. We plan to expand the suite of gridded map products offered by the USA-NPN to include predictive maps of phenological transitions for additional plant and animal species at fine spatial and temporal resolution in the near future. USA-NPN invites you to use freely available daily and short-term forecast maps of accumulated growing degree days and spring onset dates at fine spatial scale for the conterminous United States.

Large-scale mapping and predictive modeling of submerged aquatic vegetation in a shallow eutrophic lake.

PubMed

Havens, Karl E; Harwell, Matthew C; Brady, Mark A; Sharfstein, Bruce; East, Therese L; Rodusky, Andrew J; Anson, Daniel; Maki, Ryan P

2002-04-09

A spatially intensive sampling program was developed for mapping the submerged aquatic vegetation (SAV) over an area of approximately 20,000 ha in a large, shallow lake in Florida, U.S. The sampling program integrates Geographic Information System (GIS) technology with traditional field sampling of SAV and has the capability of producing robust vegetation maps under a wide range of conditions, including high turbidity, variable depth (0 to 2 m), and variable sediment types. Based on sampling carried out in August-September 2000, we measured 1,050 to 4,300 ha of vascular SAV species and approximately 14,000 ha of the macroalga Chara spp. The results were similar to those reported in the early 1990s, when the last large-scale SAV sampling occurred. Occurrence of Chara was strongly associated with peat sediments, and maximal depths of occurrence varied between sediment types (mud, sand, rock, and peat). A simple model of Chara occurrence, based only on water depth, had an accuracy of 55%. It predicted occurrence of Chara over large areas where the plant actually was not found. A model based on sediment type and depth had an accuracy of 75% and produced a spatial map very similar to that based on observations. While this approach needs to be validated with independent data in order to test its general utility, we believe it may have application elsewhere. The simple modeling approach could serve as a coarse-scale tool for evaluating effects of water level management on Chara populations.

Evaluation and prediction of shrub cover in coastal Oregon forests (USA)

Treesearch

Becky K. Kerns; Janet L. Ohmann

2004-01-01

We used data from regional forest inventories and research programs, coupled with mapped climatic and topographic information, to explore relationships and develop multiple linear regression (MLR) and regression tree models for total and deciduous shrub cover in the Oregon coastal province. Results from both types of models indicate that forest structure variables were...

Rotary engine performance computer program (RCEMAP and RCEMAPPC): User's guide

NASA Technical Reports Server (NTRS)

Bartrand, Timothy A.; Willis, Edward A.

1993-01-01

This report is a user's guide for a computer code that simulates the performance of several rotary combustion engine configurations. It is intended to assist prospective users in getting started with RCEMAP and/or RCEMAPPC. RCEMAP (Rotary Combustion Engine performance MAP generating code) is the mainframe version, while RCEMAPPC is a simplified subset designed for the personal computer, or PC, environment. Both versions are based on an open, zero-dimensional combustion system model for the prediction of instantaneous pressures, temperature, chemical composition and other in-chamber thermodynamic properties. Both versions predict overall engine performance and thermal characteristics, including bmep, bsfc, exhaust gas temperature, average material temperatures, and turbocharger operating conditions. Required inputs include engine geometry, materials, constants for use in the combustion heat release model, and turbomachinery maps. Illustrative examples and sample input files for both versions are included.

Toward a national fuels mapping strategy: Lessons from selected mapping programs

USGS Publications Warehouse

Loveland, Thomas R.

2001-01-01

The establishment of a robust national fuels mapping program must be based on pertinent lessons from relevant national mapping programs. Many large-area mapping programs are under way in numerous Federal agencies. Each of these programs follows unique strategies to achieve mapping goals and objectives. Implementation approaches range from highly centralized programs that use tightly integrated standards and dedicated staff, to dispersed programs that permit considerable flexibility. One model facilitates national consistency, while the other allows accommodation of locally relevant conditions and issues. An examination of the programmatic strategies of four national vegetation and land cover mapping initiatives can identify the unique approaches, accomplishments, and lessons of each that should be considered in the design of a national fuel mapping program. The first three programs are the U.S. Geological Survey Gap Analysis Program, the U.S. Geological Survey National Land Cover Characterization Program, and the U.S. Fish and Wildlife Survey National Wetlands Inventory. A fourth program, the interagency Multiresolution Land Characterization Program, offers insights in the use of partnerships to accomplish mapping goals. Collectively, the programs provide lessons, guiding principles, and other basic concepts that can be used to design a successful national fuels mapping initiative.

Predicting a roadkill hotspots based on spatial distribution of Korean water deer (Hydropotes inermis argyropus) using Maxent model in South Korea Expressway : In Case of Cheongju-Sangju Expressway

NASA Astrophysics Data System (ADS)

Park, Hyomin; Lee, Sangdon

2016-04-01

Road construction has direct and indirect effects on ecosystems. Especially wildlife-vehicle conflicts (roadkills) caused by roads are a considerable threat for population of many species. This study aims to identify the effects of topographic characteristics and spatial distribution of Korean water deer (Hydropotes inermis). Korean water deer is indigenous and native species in Korea that listed LC (least concern) by IUCN redlist categories. Korean water deer population is growing every year occupying for most of roadkills (>70%) in Korean express highway. In order to predict a distribution of the Korean water deer, we selected factors that most affected water deer's habitat. Major habitats of waterdeer are known as agricultural area, forest area and water. Based on this result, eight factors were selected (land cover map, vegetation map, age class of forest, diameter class of tree, population, slope of study site, elevation of study site, distance of river), and made a thematic map by using GIS program (ESRI, Arc GIS 10.3.1 ver.). To analyze the affected factors of waterdeer distribution, GPS data and thematic map of study area were entered into Maxent model (Maxent 3.3.3.k.). Results of analysis were verified by the AUC (Area Unit Curve) of ROC (Receiver Operating Characteristic). The ROC curve used the sensitivity and specificity as a reference for determining the prediction efficiency of the model and AUC area of ROC curve was higher prediction efficiency closer to '1.' Selecting factors that affected the distribution of waterdeer were land cover map, diameter class of tree and elevation of study site. The value of AUC was 0.623. To predict the water deer's roadkills hot spot on Cheongju-Sangju Expressway, the thematic map was prepared based on GPS data of roadkill spots. As a result, the topographic factors that affected waterdeer roadkill were land cover map, actual vegetation map and age class of forest and the value of AUC was 0.854. Through this study, we could identify the site and hot spots that water deer frequently expected to use based on quantitative data on the spatial and topographic factors. Therefore, we can suggest ways to minimize roadkills by selecting the hot spots and by suggesting construction of eco-corridors. This study will significantly enhance human-wildlife conflicts by identifying key habitat areas for wild mammals.

Predictive mapping of seabirds, pinnipeds and cetaceans off the Pacific Coast of Washington

USGS Publications Warehouse

Menza, Charles; Leirness, Jeffery B.; White, Tim; Winship, Arliss; Kinlan, Brian P.; Kracker, Laura; Zamon, Jeannette E.; Ballance, Lisa; Becker, Elizabeth; Forney, Karin A.; Barlow, Jay; Adams, Josh; Pereksta, David; Pearson, Scott; Pierce, John; Jeffries, Steven J.; Calambokidis, John; Douglas, Annie; Hanson, Bradford C.; Benson, Scott R.; Antrim, Liam

2016-01-01

This research supports the National Oceanic and Atmospheric Administration (NOAA) Coastal Zone Management Program, a voluntary partnership between the federal government and U.S. coastal and Great Lakes states and territories authorized by the Coastal Zone Management Act (CZMA) of 1972 to address national coastal issues. The act provides the basis for protecting, restoring, and responsibly developing our nation’s diverse coastal communities and resources. To meet the goals of the CZMA, the national program takes a comprehensive approach to coastal resource management – balancing the often competing and occasionally conflicting demands of coastal resource use, economic development, and conservation. A wide range of issues are addressed through the program, including coastal development, water quality, public access, habitat protection, energy facility siting, ocean governance and planning, coastal hazards, and climate change. Accurate maps of seabird and marine mammal distributions are an important tool for making informed management decisions that affect all of these issues. 

MethPrimer: designing primers for methylation PCRs.

PubMed

Li, Long-Cheng; Dahiya, Rajvir

2002-11-01

DNA methylation is an epigenetic mechanism of gene regulation. Bisulfite- conversion-based PCR methods, such as bisulfite sequencing PCR (BSP) and methylation specific PCR (MSP), remain the most commonly used techniques for methylation mapping. Existing primer design programs developed for standard PCR cannot handle primer design for bisulfite-conversion-based PCRs due to changes in DNA sequence context caused by bisulfite treatment and many special constraints both on the primers and the region to be amplified for such experiments. Therefore, the present study was designed to develop a program for such applications. MethPrimer, based on Primer 3, is a program for designing PCR primers for methylation mapping. It first takes a DNA sequence as its input and searches the sequence for potential CpG islands. Primers are then picked around the predicted CpG islands or around regions specified by users. MethPrimer can design primers for BSP and MSP. Results of primer selection are delivered through a web browser in text and in graphic view.

Modeling and mapping abundance of American Woodcock across the Midwestern and Northeastern United States

USGS Publications Warehouse

Thogmartin, W.E.; Sauer, J.R.; Knutson, M.G.

2007-01-01

We used an over-dispersed Poisson regression with fixed and random effects, fitted by Markov chain Monte Carlo methods, to model population spatial patterns of relative abundance of American woodcock (Scolopax minor) across its breeding range in the United States. We predicted North American woodcock Singing Ground Survey counts with a log-linear function of explanatory variables describing habitat, year effects, and observer effects. The model also included a conditional autoregressive term representing potential correlation between adjacent route counts. Categories of explanatory habitat variables in the model included land-cover composition, climate, terrain heterogeneity, and human influence. Woodcock counts were higher in landscapes with more forest, especially aspen (Populus tremuloides) and birch (Betula spp.) forest, and in locations with a high degree of interspersion among forest, shrubs, and grasslands. Woodcock counts were lower in landscapes with a high degree of human development. The most noteworthy practical application of this spatial modeling approach was the ability to map predicted relative abundance. Based on a map of predicted relative abundance derived from the posterior parameter estimates, we identified major concentrations of woodcock abundance in east-central Minnesota, USA, the intersection of Vermont, USA, New York, USA, and Ontario, Canada, the upper peninsula of Michigan, USA, and St. Lawrence County, New York. The functional relations we elucidated for the American woodcock provide a basis for the development of management programs and the model and map may serve to focus management and monitoring on areas and habitat features important to American woodcock.

Artificial Intelligence Techniques for Predicting and Mapping Daily Pan Evaporation

NASA Astrophysics Data System (ADS)

Arunkumar, R.; Jothiprakash, V.; Sharma, Kirty

2017-09-01

In this study, Artificial Intelligence techniques such as Artificial Neural Network (ANN), Model Tree (MT) and Genetic Programming (GP) are used to develop daily pan evaporation time-series (TS) prediction and cause-effect (CE) mapping models. Ten years of observed daily meteorological data such as maximum temperature, minimum temperature, relative humidity, sunshine hours, dew point temperature and pan evaporation are used for developing the models. For each technique, several models are developed by changing the number of inputs and other model parameters. The performance of each model is evaluated using standard statistical measures such as Mean Square Error, Mean Absolute Error, Normalized Mean Square Error and correlation coefficient (R). The results showed that daily TS-GP (4) model predicted better with a correlation coefficient of 0.959 than other TS models. Among various CE models, CE-ANN (6-10-1) resulted better than MT and GP models with a correlation coefficient of 0.881. Because of the complex non-linear inter-relationship among various meteorological variables, CE mapping models could not achieve the performance of TS models. From this study, it was found that GP performs better for recognizing single pattern (time series modelling), whereas ANN is better for modelling multiple patterns (cause-effect modelling) in the data.

Mapping soil textural fractions across a large watershed in north-east Florida.

PubMed

Lamsal, S; Mishra, U

2010-08-01

Assessment of regional scale soil spatial variation and mapping their distribution is constrained by sparse data which are collected using field surveys that are labor intensive and cost prohibitive. We explored geostatistical (ordinary kriging-OK), regression (Regression Tree-RT), and hybrid methods (RT plus residual Sequential Gaussian Simulation-SGS) to map soil textural fractions across the Santa Fe River Watershed (3585 km(2)) in north-east Florida. Soil samples collected from four depths (L1: 0-30 cm, L2: 30-60 cm, L3: 60-120 cm, and L4: 120-180 cm) at 141 locations were analyzed for soil textural fractions (sand, silt and clay contents), and combined with textural data (15 profiles) assembled under the Florida Soil Characterization program. Textural fractions in L1 and L2 were autocorrelated, and spatially mapped across the watershed. OK performance was poor, which may be attributed to the sparse sampling. RT model structure varied among textural fractions, and the model explained variations ranged from 25% for L1 silt to 61% for L2 clay content. Regression residuals were simulated using SGS, and the average of simulated residuals were used to approximate regression residual distribution map, which were added to regression trend maps. Independent validation of the prediction maps showed that regression models performed slightly better than OK, and regression combined with average of simulated regression residuals improved predictions beyond the regression model. Sand content >90% in both 0-30 and 30-60 cm covered 80.6% of the watershed area. Copyright 2010 Elsevier Ltd. All rights reserved.

Mapping of ligand-binding cavities in proteins.

PubMed

Andersson, C David; Chen, Brian Y; Linusson, Anna

2010-05-01

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterize and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity, and charge). This approach can provide valuable information on the similarities and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterization and mapping of "orphan structures", selection of protein structures for docking studies in structure-based design, and identification of proteins for selectivity screens in drug design programs. 2009 Wiley-Liss, Inc.

Mapping of Ligand-Binding Cavities in Proteins

PubMed Central

Andersson, C. David; Chen, Brian Y.; Linusson, Anna

2010-01-01

The complex interactions between proteins and small organic molecules (ligands) are intensively studied because they play key roles in biological processes and drug activities. Here, we present a novel approach to characterise and map the ligand-binding cavities of proteins without direct geometric comparison of structures, based on Principal Component Analysis of cavity properties (related mainly to size, polarity and charge). This approach can provide valuable information on the similarities, and dissimilarities, of binding cavities due to mutations, between-species differences and flexibility upon ligand-binding. The presented results show that information on ligand-binding cavity variations can complement information on protein similarity obtained from sequence comparisons. The predictive aspect of the method is exemplified by successful predictions of serine proteases that were not included in the model construction. The presented strategy to compare ligand-binding cavities of related and unrelated proteins has many potential applications within protein and medicinal chemistry, for example in the characterisation and mapping of “orphan structures”, selection of protein structures for docking studies in structure-based design and identification of proteins for selectivity screens in drug design programs. PMID:20034113

VS30 – A site-characterization parameter for use in building Codes, simplified earthquake resistant design, GMPEs, and ShakeMaps

USGS Publications Warehouse

Borcherdt, Roger D.

2012-01-01

VS30, defined as the average seismic shear-wave velocity from the surface to a depth of 30 meters, has found wide-spread use as a parameter to characterize site response for simplified earthquake resistant design as implemented in building codes worldwide. VS30 , as initially introduced by the author for the US 1994 NEHRP Building Code, provides unambiguous definitions of site classes and site coefficients for site-dependent response spectra based on correlations derived from extensive borehole logging and comparative ground-motion measurement programs in California. Subsequent use of VS30 for development of strong ground motion prediction equations (GMPEs) and measurement of extensive sets of VS borehole data have confirmed the previous empirical correlations and established correlations of SVS30 with VSZ at other depths. These correlations provide closed form expressions to predict S30 V at a large number of additional sites and further justify S30 V as a parameter to characterize site response for simplified building codes, GMPEs, ShakeMap, and seismic hazard mapping.

Prediction of Low Community Sanitation Coverage Using Environmental and Sociodemographic Factors in Amhara Region, Ethiopia

PubMed Central

Oswald, William E.; Stewart, Aisha E. P.; Flanders, W. Dana; Kramer, Michael R.; Endeshaw, Tekola; Zerihun, Mulat; Melaku, Birhanu; Sata, Eshetu; Gessesse, Demelash; Teferi, Tesfaye; Tadesse, Zerihun; Guadie, Birhan; King, Jonathan D.; Emerson, Paul M.; Callahan, Elizabeth K.; Moe, Christine L.; Clasen, Thomas F.

2016-01-01

This study developed and validated a model for predicting the probability that communities in Amhara Region, Ethiopia, have low sanitation coverage, based on environmental and sociodemographic conditions. Community sanitation coverage was measured between 2011 and 2014 through trachoma control program evaluation surveys. Information on environmental and sociodemographic conditions was obtained from available data sources and linked with community data using a geographic information system. Logistic regression was used to identify predictors of low community sanitation coverage (< 20% versus ≥ 20%). The selected model was geographically and temporally validated. Model-predicted probabilities of low community sanitation coverage were mapped. Among 1,502 communities, 344 (22.90%) had coverage below 20%. The selected model included measures for high topsoil gravel content, an indicator for low-lying land, population density, altitude, and rainfall and had reasonable predictive discrimination (area under the curve = 0.75, 95% confidence interval = 0.72, 0.78). Measures of soil stability were strongly associated with low community sanitation coverage, controlling for community wealth, and other factors. A model using available environmental and sociodemographic data predicted low community sanitation coverage for areas across Amhara Region with fair discrimination. This approach could assist sanitation programs and trachoma control programs, scaling up or in hyperendemic areas, to target vulnerable areas with additional activities or alternate technologies. PMID:27430547

Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

PubMed

Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

2017-09-11

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Dynamic Optimization

NASA Technical Reports Server (NTRS)

Laird, Philip

1992-01-01

We distinguish static and dynamic optimization of programs: whereas static optimization modifies a program before runtime and is based only on its syntactical structure, dynamic optimization is based on the statistical properties of the input source and examples of program execution. Explanation-based generalization is a commonly used dynamic optimization method, but its effectiveness as a speedup-learning method is limited, in part because it fails to separate the learning process from the program transformation process. This paper describes a dynamic optimization technique called a learn-optimize cycle that first uses a learning element to uncover predictable patterns in the program execution and then uses an optimization algorithm to map these patterns into beneficial transformations. The technique has been used successfully for dynamic optimization of pure Prolog.

SIMPL: A Simplified Model-Based Program for the Analysis and Visualization of Groundwater Rebound in Abandoned Mines to Prevent Contamination of Water and Soils by Acid Mine Drainage

PubMed Central

Kim, Sung-Min

2018-01-01

Cessation of dewatering following underground mine closure typically results in groundwater rebound, because mine voids and surrounding strata undergo flooding up to the levels of the decant points, such as shafts and drifts. SIMPL (Simplified groundwater program In Mine workings using the Pipe equation and Lumped parameter model), a simplified lumped parameter model-based program for predicting groundwater levels in abandoned mines, is presented herein. The program comprises a simulation engine module, 3D visualization module, and graphical user interface, which aids data processing, analysis, and visualization of results. The 3D viewer facilitates effective visualization of the predicted groundwater level rebound phenomenon together with a topographic map, mine drift, goaf, and geological properties from borehole data. SIMPL is applied to data from the Dongwon coal mine and Dalsung copper mine in Korea, with strong similarities in simulated and observed results. By considering mine workings and interpond connections, SIMPL can thus be used to effectively analyze and visualize groundwater rebound. In addition, the predictions by SIMPL can be utilized to prevent the surrounding environment (water and soil) from being polluted by acid mine drainage. PMID:29747480

A Proposal for Phase 4 of the Forest Inventory and Analysis Program

Treesearch

Ronald E. McRoberts

2005-01-01

Maps of forest cover were constructed using observations from forest inventory plots, Landsat Thematic Mapper satellite imagery, and a logistic regression model. Estimates of mean proportion forest area and the variance of the mean were calculated for circular study areas with radii ranging from 1 km to 15 km. The spatial correlation among pixel predictions was...

A stem-map model for predicting tree canopy cover of Forest Inventory and Analysis (FIA) plots

Treesearch

Chris Toney; John D. Shaw; Mark D. Nelson

2009-01-01

Tree canopy cover is an important stand characteristic that affects understory light, fuel moisture, decomposition rates, wind speed, and wildlife habitat. Canopy cover also is a component of most definitions of forest land used by US and international agencies. The USDA Forest Service Forest Inventory and Analysis (FIA) Program currently does not provide a national...

Middle Atmosphere Program. Handbook for MAP, volume 20

NASA Technical Reports Server (NTRS)

Bowhill, S. A. (Editor); Edwards, B. (Editor)

1986-01-01

Various topics related to investigations of the middle atmosphere are discussed. Numerical weather prediction, performance characteristics of weather profiling radars, determination of gravity wave and turbulence parameters, case studies of gravity-wave propagation, turbulence and diffusion due to gravity waves, the climatology of gravity waves, mesosphere-stratosphere-troposphere radar, antenna arrays, and data management techniques are among the topics discussed.

Influence of Subjectivity in Geological Mapping on the Net Penetration Rate Prediction for a Hard Rock TBM

NASA Astrophysics Data System (ADS)

Seo, Yongbeom; Macias, Francisco Javier; Jakobsen, Pål Drevland; Bruland, Amund

2018-05-01

The net penetration rate of hard rock tunnel boring machines (TBM) is influenced by rock mass degree of fracturing. This influence is taken into account in the NTNU prediction model by the rock mass fracturing factor ( k s). k s is evaluated by geological mapping, the measurement of the orientation of fractures and the spacing of fractures and fracture type. Geological mapping is a subjective procedure. Mapping results can therefore contain considerable uncertainty. The mapping data of a tunnel mapped by three researchers were compared, and the influence of the variation in geological mapping was estimated to assess the influence of subjectivity in geological mapping. This study compares predicted net penetration rates and actual net penetration rates for TBM tunneling (from field data) and suggests mapping methods that can reduce the error related to subjectivity. The main findings of this paper are as follows: (1) variation of mapping data between individuals; (2) effect of observed variation on uncertainty in predicted net penetration rates; (3) influence of mapping methods on the difference between predicted and actual net penetration rate.

Semiautomated model building for RNA crystallography using a directed rotameric approach.

PubMed

Keating, Kevin S; Pyle, Anna Marie

2010-05-04

Structured RNA molecules play essential roles in a variety of cellular processes; however, crystallographic studies of such RNA molecules present a large number of challenges. One notable complication arises from the low resolutions typical of RNA crystallography, which results in electron density maps that are imprecise and difficult to interpret. This problem is exacerbated by the lack of computational tools for RNA modeling, as many of the techniques commonly used in protein crystallography have no equivalents for RNA structure. This leads to difficulty and errors in the model building process, particularly in modeling of the RNA backbone, which is highly error prone due to the large number of variable torsion angles per nucleotide. To address this, we have developed a method for accurately building the RNA backbone into maps of intermediate or low resolution. This method is semiautomated, as it requires a crystallographer to first locate phosphates and bases in the electron density map. After this initial trace of the molecule, however, an accurate backbone structure can be built without further user intervention. To accomplish this, backbone conformers are first predicted using RNA pseudotorsions and the base-phosphate perpendicular distance. Detailed backbone coordinates are then calculated to conform both to the predicted conformer and to the previously located phosphates and bases. This technique is shown to produce accurate backbone structure even when starting from imprecise phosphate and base coordinates. A program implementing this methodology is currently available, and a plugin for the Coot model building program is under development.

Interactive computer programs for the graphic analysis of nucleotide sequence data.

PubMed Central

Luckow, V A; Littlewood, R K; Rownd, R H

1984-01-01

A group of interactive computer programs have been developed which aid in the collection and graphical analysis of nucleotide and protein sequence data. The programs perform the following basic functions: a) enter, edit, list, and rearrange sequence data; b) permit automatic entry of nucleotide sequence data directly from an autoradiograph into the computer; c) search for restriction sites or other specified patterns and plot a linear or circular restriction map, or print their locations; d) plot base composition; e) analyze homology between sequences by plotting a two-dimensional graphic matrix; and f) aid in plotting predicted secondary structures of RNA molecules. PMID:6546437

Ensemble Learning of QTL Models Improves Prediction of Complex Traits

PubMed Central

Bian, Yang; Holland, James B.

2015-01-01

Quantitative trait locus (QTL) models can provide useful insights into trait genetic architecture because of their straightforward interpretability but are less useful for genetic prediction because of the difficulty in including the effects of numerous small effect loci without overfitting. Tight linkage between markers introduces near collinearity among marker genotypes, complicating the detection of QTL and estimation of QTL effects in linkage mapping, and this problem is exacerbated by very high density linkage maps. Here we developed a thinning and aggregating (TAGGING) method as a new ensemble learning approach to QTL mapping. TAGGING reduces collinearity problems by thinning dense linkage maps, maintains aspects of marker selection that characterize standard QTL mapping, and by ensembling, incorporates information from many more markers-trait associations than traditional QTL mapping. The objective of TAGGING was to improve prediction power compared with QTL mapping while also providing more specific insights into genetic architecture than genome-wide prediction models. TAGGING was compared with standard QTL mapping using cross validation of empirical data from the maize (Zea mays L.) nested association mapping population. TAGGING-assisted QTL mapping substantially improved prediction ability for both biparental and multifamily populations by reducing both the variance and bias in prediction. Furthermore, an ensemble model combining predictions from TAGGING-assisted QTL and infinitesimal models improved prediction abilities over the component models, indicating some complementarity between model assumptions and suggesting that some trait genetic architectures involve a mixture of a few major QTL and polygenic effects. PMID:26276383

Comparing National Water Model Inundation Predictions with Hydrodynamic Modeling

NASA Astrophysics Data System (ADS)

Egbert, R. J.; Shastry, A.; Aristizabal, F.; Luo, C.

2017-12-01

The National Water Model (NWM) simulates the hydrologic cycle and produces streamflow forecasts, runoff, and other variables for 2.7 million reaches along the National Hydrography Dataset for the continental United States. NWM applies Muskingum-Cunge channel routing which is based on the continuity equation. However, the momentum equation also needs to be considered to obtain better estimates of streamflow and stage in rivers especially for applications such as flood inundation mapping. Simulation Program for River NeTworks (SPRNT) is a fully dynamic model for large scale river networks that solves the full nonlinear Saint-Venant equations for 1D flow and stage height in river channel networks with non-uniform bathymetry. For the current work, the steady-state version of the SPRNT model was leveraged. An evaluation on SPRNT's and NWM's abilities to predict inundation was conducted for the record flood of Hurricane Matthew in October 2016 along the Neuse River in North Carolina. This event was known to have been influenced by backwater effects from the Hurricane's storm surge. Retrospective NWM discharge predictions were converted to stage using synthetic rating curves. The stages from both models were utilized to produce flood inundation maps using the Height Above Nearest Drainage (HAND) method which uses the local relative heights to provide a spatial representation of inundation depths. In order to validate the inundation produced by the models, Sentinel-1A synthetic aperture radar data in the VV and VH polarizations along with auxiliary data was used to produce a reference inundation map. A preliminary, binary comparison of the inundation maps to the reference, limited to the five HUC-12 areas of Goldsboro, NC, yielded that the flood inundation accuracies for NWM and SPRNT were 74.68% and 78.37%, respectively. The differences for all the relevant test statistics including accuracy, true positive rate, true negative rate, and positive predictive value were found to be statistically significant. Further research will include a larger segment of the Neuse River to make more confident conclusions on how SPRNT can improve on NWM predictions. An interactive Tethys web application was developed to display and compare the inundation maps.

Presurgical language fMRI: Clinical practices and patient outcomes in epilepsy surgical planning.

PubMed

Benjamin, Christopher F A; Li, Alexa X; Blumenfeld, Hal; Constable, R Todd; Alkawadri, Rafeed; Bickel, Stephan; Helmstaedter, Christoph; Meletti, Stefano; Bronen, Richard; Warfield, Simon K; Peters, Jurriaan M; Reutens, David; Połczyńska, Monika; Spencer, Dennis D; Hirsch, Lawrence J

2018-03-12

The goal of this study was to document current clinical practice and report patient outcomes in presurgical language functional MRI (fMRI) for epilepsy surgery. Epilepsy surgical programs worldwide were surveyed as to the utility, implementation, and efficacy of language fMRI in the clinic; 82 programs responded. Respondents were predominantly US (61%) academic programs (85%), and evaluated adults (44%), adults and children (40%), or children only (16%). Nearly all (96%) reported using language fMRI. Surprisingly, fMRI is used to guide surgical margins (44% of programs) as well as lateralize language (100%). Sites using fMRI for localization most often use a distance margin around activation of 10mm. While considered useful, 56% of programs reported at least one instance of disagreement with other measures. Direct brain stimulation typically confirmed fMRI findings (74%) when guiding margins, but instances of unpredicted decline were reported by 17% of programs and 54% reported unexpected preservation of function. Programs reporting unexpected decline did not clearly differ from those which did not. Clinicians using fMRI to guide surgical margins do not typically map known language-critical areas beyond Broca's and Wernicke's. This initial data shows many clinical teams are confident using fMRI not only for language lateralization but also to guide surgical margins. Reported cases of unexpected language preservation when fMRI activation is resected, and cases of language decline when it is not, emphasize a critical need for further validation. Comprehensive studies comparing commonly-used fMRI paradigms to predict stimulation mapping and post-surgical language decline remain of high importance. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Assessing gains in teacher knowledge and confidence in a long-duration climate literacy initiative

NASA Astrophysics Data System (ADS)

Haine, D. B.; Kendall, L.; Yelton, S.

2013-12-01

Climate Literacy: Integrating Modeling & Technology Experiences (CLIMATE) in NC Classrooms, an interdisciplinary, global climate change program for NC high school science teachers is administered by UNC Chapel Hill's Institute for the Environment (IE) with funding from NASA's Innovations in Climate Education (NICE) Program. Currently in its third year, this year-long program serves 24 teaching fellows annually and combines hands-on climate science investigations with experiential learning in fragile ecosystem environments to achieve the following program goals: increased teacher knowledge of climate change science and predicted impacts; increased teacher knowledge of modeling and technology resources, with an emphasis on those provided by NASA; and increased teacher confidence in using technology to address climate change education. A mixed-methods evaluation approach that includes external evaluation is providing quantitative and qualitative data about the extent to which program goals are being achieved. With regard to increases in teacher knowledge, teachers often self-report an increase in knowledge as a result of a program activity; this session will describe our strategies for assessing actual gains in teacher knowledge which include pre- and post-collaborative concept mapping and pre- and post-open response questionnaires. For each evaluation approach utilized, the process of analyzing these qualitative data will be discussed and results shared. For example, a collaborative concept mapping activity for assessment of learning as a result of the summer institute was utilized to assess gains in content knowledge. Working in small groups, teachers were asked to identify key vocabulary terms and show their relationship to one another via a concept map to answer these questions: What is global climate change? What is/are the: evidence? mechanisms? causes? consequences? Concept maps were constructed at the beginning (pre) and again at the end (post) of the Summer Institute. Concept map analysis revealed that post-maps included more key terms/concepts on average than pre-concept maps and that 6-9 NEW terms were present on post-maps; these NEW terms were directly related to science content addressed during the summer institute. In an effort to assess knowledge gained as a result of participating in an experiential weekend retreat, a pre- and post-open response questionnaire focused on the spruce-fir forest, an ecosystem prominently featured during programming, was administered. Post-learning assessments revealed learning gains for 100% of participants, all of whom were able to provide responses that referenced specific content covered during the retreat. To demonstrate increased teacher confidence in using technology to support climate science instruction, teachers are asked to develop and pilot a lesson that integrates at least one NASA resource. In collaboration with an external evaluator, a rubric was developed to evaluate submitted lessons in an effort to assess progress at achieving this program goal. The process of developing this rubric as well as the results from this analysis will be shared along with the challenges and insights that have been revealed from analyzing submitted lessons.

Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D

DOE PAGES

Preciat Gonzalez, German A.; El Assal, Lemmer R. P.; Noronha, Alberto; ...

2017-06-14

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, manymore » algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.« less

Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D

DOE Office of Scientific and Technical Information (OSTI.GOV)

Preciat Gonzalez, German A.; El Assal, Lemmer R. P.; Noronha, Alberto

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, manymore » algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.« less

Comparative evaluation of atom mapping algorithms for balanced metabolic reactions: application to Recon 3D.

PubMed

Preciat Gonzalez, German A; El Assal, Lemmer R P; Noronha, Alberto; Thiele, Ines; Haraldsdóttir, Hulda S; Fleming, Ronan M T

2017-06-14

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, many algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.

The evolving Alaska mapping program.

USGS Publications Warehouse

Brooks, P.D.; O'Brien, T. J.

1986-01-01

This paper describes the development of mapping in Alaska, the current status of the National Mapping Program, and future plans for expanding and improving the mapping coverage. Research projects with Landsat Multispectral Scanner and Return Vidicon imagery and real- and synthetic-aperture radar; image mapping programs; digital mapping; remote sensing projects; the Alaska National Interest Lands Conservation Act; and the Alaska High-Altitude Aerial Photography Program are also discussed.-from Authors

P-Hint-Hunt: a deep parallelized whole genome DNA methylation detection tool.

PubMed

Peng, Shaoliang; Yang, Shunyun; Gao, Ming; Liao, Xiangke; Liu, Jie; Yang, Canqun; Wu, Chengkun; Yu, Wenqiang

2017-03-14

The increasing studies have been conducted using whole genome DNA methylation detection as one of the most important part of epigenetics research to find the significant relationships among DNA methylation and several typical diseases, such as cancers and diabetes. In many of those studies, mapping the bisulfite treated sequence to the whole genome has been the main method to study DNA cytosine methylation. However, today's relative tools almost suffer from inaccuracies and time-consuming problems. In our study, we designed a new DNA methylation prediction tool ("Hint-Hunt") to solve the problem. By having an optimal complex alignment computation and Smith-Waterman matrix dynamic programming, Hint-Hunt could analyze and predict the DNA methylation status. But when Hint-Hunt tried to predict DNA methylation status with large-scale dataset, there are still slow speed and low temporal-spatial efficiency problems. In order to solve the problems of Smith-Waterman dynamic programming and low temporal-spatial efficiency, we further design a deep parallelized whole genome DNA methylation detection tool ("P-Hint-Hunt") on Tianhe-2 (TH-2) supercomputer. To the best of our knowledge, P-Hint-Hunt is the first parallel DNA methylation detection tool with a high speed-up to process large-scale dataset, and could run both on CPU and Intel Xeon Phi coprocessors. Moreover, we deploy and evaluate Hint-Hunt and P-Hint-Hunt on TH-2 supercomputer in different scales. The experimental results illuminate our tools eliminate the deviation caused by bisulfite treatment in mapping procedure and the multi-level parallel program yields a 48 times speed-up with 64 threads. P-Hint-Hunt gain a deep acceleration on CPU and Intel Xeon Phi heterogeneous platform, which gives full play of the advantages of multi-cores (CPU) and many-cores (Phi).

Repeatability in photo-interpretation of tree canopy cover and its effect on predictive mapping

Treesearch

Thomas A. Jackson; Gretchen G. Moisen; Paul L. Patterson; John Tipton

2012-01-01

In this study, we explore repeatability in photo-interpreted imagery from the National Agriculture Imagery Program that was sampled as part of the National Land Cover Database 2011 Tree Canopy Cover pilot project. Data were collected in 5 diverse pilot areas in the US, including one each in Oregon, Utah, Kansas, Michigan and Georgia. Repeatability metrics. The intra-...

The Probabilities of Unique Events

DTIC Science & Technology

2012-08-30

social justice and also participated in antinuclear demonstrations. The participants ranked the probability that Linda is a feminist bank teller as...investigated them. We propose a new theory (implemented in a computer program) in which such estimates depend on an intuitive non-numerical system capable only...of simple procedures, and a deliberative system that maps intuitions into numbers. The theory predicts that estimates of the probabilities of

The longitudinal effect of concept map teaching on critical thinking of nursing students.

PubMed

Lee, Weillie; Chiang, Chi-Hua; Liao, I-Chen; Lee, Mei-Li; Chen, Shiah-Lian; Liang, Tienli

2013-10-01

Concept map is a useful cognitive tool for enhancing a student's critical thinking by encouraging students to process information deeply for understanding. However, there is limited understanding of longitudinal effects of concept map teaching on students' critical thinking. The purpose of the study was to investigate the growth and the other factors influencing the development of critical thinking in response to concept map as an interventional strategy for nursing students in a two-year registered nurse baccalaureate program. The study was a quasi-experimental and longitudinal follow-up design. A convenience sample was drawn from a university in central Taiwan. Data were collected at different time points at the beginning of each semester using structured questionnaires including Critical Thinking Scale and Approaches to Learning and Studying. The intervention of concept map teaching was given at the second semester in the Medical-Surgical Nursing course. The results of the findings revealed student started with a mean critical thinking score of 41.32 and decreased at a rate of 0.42 over time, although not significant. After controlling for individual characteristics, the final model revealed that the experimental group gained a higher critical thinking score across time than the control group. The best predictive variables of initial status in critical thinking were without clinical experience and a higher pre-test score. The growth in critical thinking was predicted best by a lower pre-test score, and lower scores on surface approach and organized study. Our study suggested that concept map is a useful teaching strategy to enhance student critical thinking. Copyright © 2012 Elsevier Ltd. All rights reserved.

RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures

PubMed Central

Miao, Zhichao; Adamiak, Ryszard W.; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cheng, Clarence; Chojnowski, Grzegorz; Chou, Fang-Chieh; Cordero, Pablo; Cruz, José Almeida; Ferré-D'Amaré, Adrian R.; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Dunin-Horkawicz, Stanislaw; Kladwang, Wipapat; Krokhotin, Andrey; Lach, Grzegorz; Magnus, Marcin; Major, François; Mann, Thomas H.; Masquida, Benoît; Matelska, Dorota; Meyer, Mélanie; Peselis, Alla; Popenda, Mariusz; Purzycka, Katarzyna J.; Serganov, Alexander; Stasiewicz, Juliusz; Szachniuk, Marta; Tandon, Arpit; Tian, Siqi; Wang, Jian; Xiao, Yi; Xu, Xiaojun; Zhang, Jinwei; Zhao, Peinan; Zok, Tomasz; Westhof, Eric

2015-01-01

This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5–3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson–Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/. PMID:25883046

Enhancing programming logic thinking using analogy mapping

NASA Astrophysics Data System (ADS)

Sukamto, R. A.; Megasari, R.

2018-05-01

Programming logic thinking is the most important competence for computer science students. However, programming is one of the difficult subject in computer science program. This paper reports our work about enhancing students' programming logic thinking using Analogy Mapping for basic programming subject. Analogy Mapping is a computer application which converts source code into analogies images. This research used time series evaluation and the result showed that Analogy Mapping can enhance students' programming logic thinking.

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

NASA Astrophysics Data System (ADS)

Booth, N. L.; Everman, E.; Kuo, I.; Sprague, L.; Murphy, L.

2011-12-01

A new web-based decision support system has been developed as part of the U.S. Geological Survey (USGS) National Water Quality Assessment Program's (NAWQA) effort to provide ready access to Spatially Referenced Regressions On Watershed attributes (SPARROW) results of stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via an intuitive graphical user interface with a map-based display. The SPARROW Decision Support System (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions, distribution of nutrient sources, nutrient delivery to downstream waterbodies, and simulations of altered nutrient inputs including atmospheric and agricultural sources. The DSS offers other features for analysis including various background map layers, model output exports, and the ability to save and share prediction scenarios. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. The underlying modeling framework and server infrastructure illustrate innovations in the information technology and geosciences fields for delivering SPARROW model predictions over the web by performing intensive model computations and map visualizations of the predicted conditions within the stream network.

Local Integration of the National Atmospheric Release Advisory Center with Cities (LINC)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ermak, D L; Tull, J E; Mosley-Rovi, R

The objective of the ''Local Integration of the National Atmospheric Release Advisory Center with Cities'' (LINC) program is to demonstrate the capability for providing local government agencies with an advanced operational atmospheric plume prediction capability, which can be seamlessly integrated with appropriate federal agency support for homeland security applications. LINC is a Domestic Demonstration and Application Program (DDAP) funded by the Chemical and Biological National Security Program (CBNP), which is part of the Department of Energy's (DOE) National Nuclear Security Administration (NNSA). LINC will make use of capabilities that have been developed the CBNP, and integrated into the National Atmosphericmore » Release Advisory Center (NARAC) at Lawrence Livermore National Laboratory (LLNL). NARAC tools services will be provided to pilot study cities and counties to map plumes from terrorism threats. Support to these local agencies will include training and customized support for exercises, special events, and general emergencies. NARAC provides tools and services that map the probable spread of hazardous material which have been accidentally or intentionally released into the atmosphere. Primarily supported by the DOE, NARAC is a national support and resource center for planning, real-time assessment and detailed studies of incidents involving a wide variety of hazards, including radiological, chemical, or biological releases. NARAC is a distributed system, providing modeling and geographical information tools for use on an end user's computer system, as well as real-time access to global meteorological and geographical databases and advanced three-dimensional model predictions.« less

Lymphatic filariasis transmission risk map of India, based on a geo-environmental risk model.

PubMed

Sabesan, Shanmugavelu; Raju, Konuganti Hari Kishan; Subramanian, Swaminathan; Srivastava, Pradeep Kumar; Jambulingam, Purushothaman

2013-09-01

The strategy adopted by a global program to interrupt transmission of lymphatic filariasis (LF) is mass drug administration (MDA) using chemotherapy. India also followed this strategy by introducing MDA in the historically known endemic areas. All other areas, which remained unsurveyed, were presumed to be nonendemic and left without any intervention. Therefore, identification of LF transmission risk areas in the entire country has become essential so that they can be targeted for intervention. A geo-environmental risk model (GERM) developed earlier was used to create a filariasis transmission risk map for India. In this model, a Standardized Filariasis Transmission Risk Index (SFTRI, based on geo-environmental risk variables) was used as a predictor of transmission risk. The relationship between SFTRI and endemicity (historically known) of an area was quantified by logistic regression analysis. The quantified relationship was validated by assessing the filarial antigenemia status of children living in the unsurveyed areas through a ground truth study. A significant positive relationship was observed between SFTRI and the endemicity of an area. Overall, the model prediction of filarial endemic status of districts was found to be correct in 92.8% of the total observations. Thus, among the 190 districts hitherto unsurveyed, as many as 113 districts were predicted to be at risk, and the remaining at no risk. The GERM developed on geographic information system (GIS) platform is useful for LF spatial delimitation on a macrogeographic/regional scale. Furthermore, the risk map developed will be useful for the national LF elimination program by identifying areas at risk for intervention and for undertaking surveillance in no-risk areas.

Mariner Jupiter/Saturn LCSSE thruster/valve assembly and injection propulsion unit rocket engine assemblies: 0.2-lbf T/VA development and margin limit test report

NASA Technical Reports Server (NTRS)

Clark, E. C.

1975-01-01

Thruster valve assemblies (T/VA's) were subjected to the development test program for the combined JPL Low-Cost Standardized Spacecraft Equipment (LCSSE) and Mariner Jupiter/Saturn '77 spacecraft (MJS) programs. The development test program was designed to achieve the following program goals: (1) demonstrate T/VA design compliance with JPL Specifications, (2) to conduct a complete performance Cf map of the T/VA over the full operating range of environment, (3) demonstrate T/VA life capability and characteristics of life margin for steady-state limit cycle and momentum wheel desaturation duty cycles, (4) verification of structural design capability, and (5) generate a computerized performance model capable of predicting T/VA operation over pressures ranging from 420 to 70 psia, propellant temperatures ranging from 140 F to 40 F, pulse widths of 0.008 to steady-state operation with unlimited duty cycle capability, and finally predict the transient performance associated with reactor heatup during any given duty cycle, start temperature, feed pressure, and propellant temperature conditions.

Gstat: a program for geostatistical modelling, prediction and simulation

NASA Astrophysics Data System (ADS)

Pebesma, Edzer J.; Wesseling, Cees G.

1998-01-01

Gstat is a computer program for variogram modelling, and geostatistical prediction and simulation. It provides a generic implementation of the multivariable linear model with trends modelled as a linear function of coordinate polynomials or of user-defined base functions, and independent or dependent, geostatistically modelled, residuals. Simulation in gstat comprises conditional or unconditional (multi-) Gaussian sequential simulation of point values or block averages, or (multi-) indicator sequential simulation. Besides many of the popular options found in other geostatistical software packages, gstat offers the unique combination of (i) an interactive user interface for modelling variograms and generalized covariances (residual variograms), that uses the device-independent plotting program gnuplot for graphical display, (ii) support for several ascii and binary data and map file formats for input and output, (iii) a concise, intuitive and flexible command language, (iv) user customization of program defaults, (v) no built-in limits, and (vi) free, portable ANSI-C source code. This paper describes the class of problems gstat can solve, and addresses aspects of efficiency and implementation, managing geostatistical projects, and relevant technical details.

Demonstration and Validation of GTS Long-Term Monitoring Optimization Software at Military and Government Sites

DTIC Science & Technology

2011-02-01

Defense DoE Department of Energy DPT Direct push technology EPA Environmental Protection Agency ERPIMS Enviromental Restoration Program...and 3) assessing whether new wells should be added and where (i.e., network adequacy). • Predict allows import and comparison of new sampling...data against previously estimated trends and maps. Two options include trend flagging and plume flagging to identify potentially anomalous new values

Potential assessment of genome-wide association study and genomic selection in Japanese pear Pyrus pyrifolia

PubMed Central

Iwata, Hiroyoshi; Hayashi, Takeshi; Terakami, Shingo; Takada, Norio; Sawamura, Yutaka; Yamamoto, Toshiya

2013-01-01

Although the potential of marker-assisted selection (MAS) in fruit tree breeding has been reported, bi-parental QTL mapping before MAS has hindered the introduction of MAS to fruit tree breeding programs. Genome-wide association studies (GWAS) are an alternative to bi-parental QTL mapping in long-lived perennials. Selection based on genomic predictions of breeding values (genomic selection: GS) is another alternative for MAS. This study examined the potential of GWAS and GS in pear breeding with 76 Japanese pear cultivars to detect significant associations of 162 markers with nine agronomic traits. We applied multilocus Bayesian models accounting for ordinal categorical phenotypes for GWAS and GS model training. Significant associations were detected at harvest time, black spot resistance and the number of spurs and two of the associations were closely linked to known loci. Genome-wide predictions for GS were accurate at the highest level (0.75) in harvest time, at medium levels (0.38–0.61) in resistance to black spot, firmness of flesh, fruit shape in longitudinal section, fruit size, acid content and number of spurs and at low levels (<0.2) in all soluble solid content and vigor of tree. Results suggest the potential of GWAS and GS for use in future breeding programs in Japanese pear. PMID:23641189

Uncertainty indication in soil function maps - transparent and easy-to-use information to support sustainable use of soil resources

NASA Astrophysics Data System (ADS)

Greiner, Lucie; Nussbaum, Madlene; Papritz, Andreas; Zimmermann, Stephan; Gubler, Andreas; Grêt-Regamey, Adrienne; Keller, Armin

2018-05-01

Spatial information on soil function fulfillment (SFF) is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1) indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM) that are used for soil function assessment (SFA) and (2) showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil resources.

Middle Atmosphere Program. Handbook for MAP, volume 6

NASA Technical Reports Server (NTRS)

Sechrist, C. F., Jr. (Editor)

1982-01-01

A directory of scientists associated with the Middle Atmosphere Program (MAP) is presented. The MAP steering committee, the standing committees, MAP study groups, and MAP projects are mentioned along with the MAP secretariat and regional consultative group.

High-resolution linkage map and chromosome-scale genome assembly for cassava (Manihot esculenta Crantz) from 10 populations.

PubMed

2014-12-11

Cassava (Manihot esculenta Crantz) is a major staple crop in Africa, Asia, and South America, and its starchy roots provide nourishment for 800 million people worldwide. Although native to South America, cassava was brought to Africa 400-500 years ago and is now widely cultivated across sub-Saharan Africa, but it is subject to biotic and abiotic stresses. To assist in the rapid identification of markers for pathogen resistance and crop traits, and to accelerate breeding programs, we generated a framework map for M. esculenta Crantz from reduced representation sequencing [genotyping-by-sequencing (GBS)]. The composite 2412-cM map integrates 10 biparental maps (comprising 3480 meioses) and organizes 22,403 genetic markers on 18 chromosomes, in agreement with the observed karyotype. We used the map to anchor 71.9% of the draft genome assembly and 90.7% of the predicted protein-coding genes. The chromosome-anchored genome sequence will be useful for breeding improvement by assisting in the rapid identification of markers linked to important traits, and in providing a framework for genomic selection-enhanced breeding of this important crop. Copyright © 2015 International Cassava Genetic Map Consortium (ICGMC).

Engineering Feasibility and Trade Studies for the NASA/VSGC MicroMaps Space Mission

NASA Technical Reports Server (NTRS)

Abdelkhalik, Ossama O.; Nairouz, Bassem; Weaver, Timothy; Newman, Brett

2003-01-01

Knowledge of airborne CO concentrations is critical for accurate scientific prediction of global scale atmospheric behavior. MicroMaps is an existing NASA owned gas filter radiometer instrument designed for space-based measurement of atmospheric CO vertical profiles. Due to programmatic changes, the instrument does not have access to the space environment and is in storage. MicroMaps hardware has significant potential for filling a critical scientific need, thus motivating concept studies for new and innovative scientific spaceflight missions that would leverage the MicroMaps heritage and investment, and contribute to new CO distribution data. This report describes engineering feasibility and trade studies for the NASA/VSGC MicroMaps Space Mission. Conceptual studies encompass: 1) overall mission analysis and synthesis methodology, 2) major subsystem studies and detailed requirements development for an orbital platform option consisting of a small, single purpose spacecraft, 3) assessment of orbital platform option consisting of the International Space Station, and 4) survey of potential launch opportunities for gaining assess to orbit. Investigations are of a preliminary first-order nature. Results and recommendations from these activities are envisioned to support future MicroMaps Mission design decisions regarding program down select options leading to more advanced and mature phases.

Assessment of the national schistosomiasis control program in a typical region along the Yangtze River, China.

PubMed

Hu, Yi; Li, Si; Xia, Congcong; Chen, Yue; Lynn, Henry; Zhang, Tiejun; Xiong, Chenglong; Chen, Gengxin; He, Zonggui; Zhang, Zhijie

2017-01-01

Schistosomiasis remains a major public health problem in eastern China, particularly along the Yangtze River Basin. The latest national schistosomiasis control program (NSCP) was implemented in 2005 with the main goal of reducing the rate of infection to less than 5% by 2008 and 1% by 2015. To assess the progress, we applied a Bayesian spatio-temporal model to describe dynamics of schistosomiasis in Guichi, Anhui Province, China, using annual parasitological and environmental data collected within 41 sample villages for the period 2005-2011. Predictive maps of schistosomiasis showed that the disease prevalence remains constant and low. Results of uncertainty analysis, in the form of probability contour maps (PCMs), indicated that the first goal of "infection rate less than 5% by 2008" was fully achieved in the study area. More longitudinal data for schistosomiasis are needed for the assessment of the second goal of "infection rate less than 1% by 2015". Compared with the traditional way of mapping uncertainty (e.g., variance or mean-square error), our PCMs provide more realistic information for schistosomiasis control. Copyright © 2016 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

Maps for the nation: The current federal mapping establishment

USGS Publications Warehouse

North, G.W.

1983-01-01

The U.S. Government annually produces an estimated 53,000 new maps and charts and distributes about 160 million copies. A large number of these maps are produced under the national mapping program, a decentralized Federal/State cooperative approach to mapping the country at standard scales. Circular A-16, issued by the Office of Management and Budget in 1953 and revised in 1967, delegates the mapping responsibilities to various federal agencies. The U.S. Department of the Interior's Geological Survey is the principal federal agency responsible for implementing the national mapping program. Other major federal map producing agencies include the Departments of Agriculture, Commerce, Defense, Housing and Urban Development, and Transportation, and the Tennessee Valley Authority. To make maps and mapping information more readily available, the National Cartographic Information Center was established in 1974 and an expanded National Map Library Depository Program in 1981. The most recent of many technological advances made under the mapping program are in the areas of digital cartography and video disc and optical disc information storage systems. Future trends and changes in the federal mapping program will involve expanded information and customer service operations, further developments in the production and use of digital cartographic data, and consideration of a Federal Mapping Agency. ?? 1983.

Development of predictive mapping techniques for soil survey and salinity mapping

NASA Astrophysics Data System (ADS)

Elnaggar, Abdelhamid A.

Conventional soil maps represent a valuable source of information about soil characteristics, however they are subjective, very expensive, and time-consuming to prepare. Also, they do not include explicit information about the conceptual mental model used in developing them nor information about their accuracy, in addition to the error associated with them. Decision tree analysis (DTA) was successfully used in retrieving the expert knowledge embedded in old soil survey data. This knowledge was efficiently used in developing predictive soil maps for the study areas in Benton and Malheur Counties, Oregon and accessing their consistency. A retrieved soil-landscape model from a reference area in Harney County was extrapolated to develop a preliminary soil map for the neighboring unmapped part of Malheur County. The developed map had a low prediction accuracy and only a few soil map units (SMUs) were predicted with significant accuracy, mostly those shallow SMUs that have either a lithic contact with the bedrock or developed on a duripan. On the other hand, the developed soil map based on field data was predicted with very high accuracy (overall was about 97%). Salt-affected areas of the Malheur County study area are indicated by their high spectral reflectance and they are easily discriminated from the remote sensing data. However, remote sensing data fails to distinguish between the different classes of soil salinity. Using the DTA method, five classes of soil salinity were successfully predicted with an overall accuracy of about 99%. Moreover, the calculated area of salt-affected soil was overestimated when mapped using remote sensing data compared to that predicted by using DTA. Hence, DTA could be a very helpful approach in developing soil survey and soil salinity maps in more objective, effective, less-expensive and quicker ways based on field data.

Accuracy of CNV Detection from GWAS Data.

PubMed

Zhang, Dandan; Qian, Yudong; Akula, Nirmala; Alliey-Rodriguez, Ney; Tang, Jinsong; Gershon, Elliot S; Liu, Chunyu

2011-01-13

Several computer programs are available for detecting copy number variants (CNVs) using genome-wide SNP arrays. We evaluated the performance of four CNV detection software suites--Birdsuite, Partek, HelixTree, and PennCNV-Affy--in the identification of both rare and common CNVs. Each program's performance was assessed in two ways. The first was its recovery rate, i.e., its ability to call 893 CNVs previously identified in eight HapMap samples by paired-end sequencing of whole-genome fosmid clones, and 51,440 CNVs identified by array Comparative Genome Hybridization (aCGH) followed by validation procedures, in 90 HapMap CEU samples. The second evaluation was program performance calling rare and common CNVs in the Bipolar Genome Study (BiGS) data set (1001 bipolar cases and 1033 controls, all of European ancestry) as measured by the Affymetrix SNP 6.0 array. Accuracy in calling rare CNVs was assessed by positive predictive value, based on the proportion of rare CNVs validated by quantitative real-time PCR (qPCR), while accuracy in calling common CNVs was assessed by false positive/false negative rates based on qPCR validation results from a subset of common CNVs. Birdsuite recovered the highest percentages of known HapMap CNVs containing >20 markers in two reference CNV datasets. The recovery rate increased with decreased CNV frequency. In the tested rare CNV data, Birdsuite and Partek had higher positive predictive values than the other software suites. In a test of three common CNVs in the BiGS dataset, Birdsuite's call was 98.8% consistent with qPCR quantification in one CNV region, but the other two regions showed an unacceptable degree of accuracy. We found relatively poor consistency between the two "gold standards," the sequence data of Kidd et al., and aCGH data of Conrad et al. Algorithms for calling CNVs especially common ones need substantial improvement, and a "gold standard" for detection of CNVs remains to be established.

Use of regression‐based models to map sensitivity of aquatic resources to atmospheric deposition in Yosemite National Park, USA

USGS Publications Warehouse

Clow, David W.; Nanus, Leora; Huggett, Brian

2010-01-01

An abundance of exposed bedrock, sparse soil and vegetation, and fast hydrologic flushing rates make aquatic ecosystems in Yosemite National Park susceptible to nutrient enrichment and episodic acidification due to atmospheric deposition of nitrogen (N) and sulfur (S). In this study, multiple linear regression (MLR) models were created to estimate fall‐season nitrate and acid neutralizing capacity (ANC) in surface water in Yosemite wilderness. Input data included estimated winter N deposition, fall‐season surface‐water chemistry measurements at 52 sites, and basin characteristics derived from geographic information system layers of topography, geology, and vegetation. The MLR models accounted for 84% and 70% of the variance in surface‐water nitrate and ANC, respectively. Explanatory variables (and the sign of their coefficients) for nitrate included elevation (positive) and the abundance of neoglacial and talus deposits (positive), unvegetated terrain (positive), alluvium (negative), and riparian (negative) areas in the basins. Explanatory variables for ANC included basin area (positive) and the abundance of metamorphic rocks (positive), unvegetated terrain (negative), water (negative), and winter N deposition (negative) in the basins. The MLR equations were applied to 1407 stream reaches delineated in the National Hydrography Data Set for Yosemite, and maps of predicted surface‐water nitrate and ANC concentrations were created. Predicted surface‐water nitrate concentrations were highest in small, high‐elevation cirques, and concentrations declined downstream. Predicted ANC concentrations showed the opposite pattern, except in high‐elevation areas underlain by metamorphic rocks along the Sierran Crest, which had relatively high predicted ANC (>200 μeq L−1). Maps were created to show where basin characteristics predispose aquatic resources to nutrient enrichment and acidification effects from N and S deposition. The maps can be used to help guide development of water‐quality programs designed to monitor and protect natural resources in national parks.

Execution models for mapping programs onto distributed memory parallel computers

NASA Technical Reports Server (NTRS)

Sussman, Alan

1992-01-01

The problem of exploiting the parallelism available in a program to efficiently employ the resources of the target machine is addressed. The problem is discussed in the context of building a mapping compiler for a distributed memory parallel machine. The paper describes using execution models to drive the process of mapping a program in the most efficient way onto a particular machine. Through analysis of the execution models for several mapping techniques for one class of programs, we show that the selection of the best technique for a particular program instance can make a significant difference in performance. On the other hand, the results of benchmarks from an implementation of a mapping compiler show that our execution models are accurate enough to select the best mapping technique for a given program.

Mapping Applications Center, National Mapping Division, U.S. Geological Survey

USGS Publications Warehouse

,

1996-01-01

The Mapping Applications Center (MAC), National Mapping Division (NMD), is the eastern regional center for coordinating the production, distribution, and sale of maps and digital products of the U.S. Geological Survey (USGS). It is located in the John Wesley Powell Federal Building in Reston, Va. The MAC's major functions are to (1) establish and manage cooperative mapping programs with State and Federal agencies; (2) perform new research in preparing and applying geospatial information; (3) prepare digital cartographic data, special purpose maps, and standard maps from traditional and classified source materials; (4) maintain the domestic names program of the United States; (5) manage the National Aerial Photography Program (NAPP); (6) coordinate the NMD's publications and outreach programs; and (7) direct the USGS mapprinting operations.

Lunar Geologic Mapping Program: 2008 Update

NASA Technical Reports Server (NTRS)

Gaddis, L.; Tanaka, K.; Skinner, J.; Hawke, B. R.

2008-01-01

The NASA Lunar Geologic Mapping Program is underway and a mappers handbook is in preparation. This program for systematic, global lunar geologic mapping at 1:2.5M scale incorporates digital, multi-scale data from a wide variety of sources. Many of these datasets have been tied to the new Unified Lunar Control Network 2005 [1] and are available online. This presentation summarizes the current status of this mapping program, the datasets now available, and how they might be used for mapping on the Moon.

A Stochastic Simulation Framework for the Prediction of Strategic Noise Mapping and Occupational Noise Exposure Using the Random Walk Approach

PubMed Central

Haron, Zaiton; Bakar, Suhaimi Abu; Dimon, Mohamad Ngasri

2015-01-01

Strategic noise mapping provides important information for noise impact assessment and noise abatement. However, producing reliable strategic noise mapping in a dynamic, complex working environment is difficult. This study proposes the implementation of the random walk approach as a new stochastic technique to simulate noise mapping and to predict the noise exposure level in a workplace. A stochastic simulation framework and software, namely RW-eNMS, were developed to facilitate the random walk approach in noise mapping prediction. This framework considers the randomness and complexity of machinery operation and noise emission levels. Also, it assesses the impact of noise on the workers and the surrounding environment. For data validation, three case studies were conducted to check the accuracy of the prediction data and to determine the efficiency and effectiveness of this approach. The results showed high accuracy of prediction results together with a majority of absolute differences of less than 2 dBA; also, the predicted noise doses were mostly in the range of measurement. Therefore, the random walk approach was effective in dealing with environmental noises. It could predict strategic noise mapping to facilitate noise monitoring and noise control in the workplaces. PMID:25875019

Staff Recall Travel Time for ST Elevation Myocardial Infarction Impacted by Traffic Congestion and Distance: A Digitally Integrated Map Software Study.

PubMed

Cole, Justin; Beare, Richard; Phan, Thanh G; Srikanth, Velandai; MacIsaac, Andrew; Tan, Christianne; Tong, David; Yee, Susan; Ho, Jesslyn; Layland, Jamie

2017-01-01

Recent evidence suggests hospitals fail to meet guideline specified time to percutaneous coronary intervention (PCI) for a proportion of ST elevation myocardial infarction (STEMI) presentations. Implicit in achieving this time is the rapid assembly of crucial catheter laboratory staff. As a proof-of-concept, we set out to create regional maps that graphically show the impact of traffic congestion and distance to destination on staff recall travel times for STEMI, thereby producing a resource that could be used by staff to improve reperfusion time for STEMI. Travel times for staff recalled to one inner and one outer metropolitan hospital at midnight, 6 p.m., and 7 a.m. were estimated using Google Maps Application Programming Interface. Computer modeling predictions were overlaid on metropolitan maps showing color coded staff recall travel times for STEMI, occurring within non-peak and peak hour traffic congestion times. Inner metropolitan hospital staff recall travel times were more affected by traffic congestion compared with outer metropolitan times, and the latter was more affected by distance. The estimated mean travel times to hospital during peak hour were greater than midnight travel times by 13.4 min to the inner and 6.0 min to the outer metropolitan hospital at 6 p.m. ( p  < 0.001). At 7 a.m., the mean difference was 9.5 min to the inner and 3.6 min to the outer metropolitan hospital ( p  < 0.001). Only 45% of inner metropolitan staff were predicted to arrive within 30 min at 6 p.m. compared with 100% at midnight ( p  < 0.001), and 56% of outer metropolitan staff at 6 p.m. ( p  = 0.021). Our results show that integration of map software with traffic congestion data, distance to destination and travel time can predict optimal residence of staff when on-call for PCI.

Effects of habitat map generalization in biodiversity assessment

NASA Technical Reports Server (NTRS)

Stoms, David M.

1992-01-01

Species richness is being mapped as part of an inventory of biological diversity in California (i.e., gap analysis). Species distributions are modeled with a GIS on the basis of maps of each species' preferred habitats. Species richness is then tallied in equal-area sampling units. A GIS sensitivity analysis examined the effects of the level of generalization of the habitat map on the predicted distribution of species richness in the southern Sierra Nevada. As the habitat map was generalized, the number of habitat types mapped within grid cells tended to decrease with a corresponding decline in numbers of species predicted. Further, the ranking of grid cells in order of predicted numbers of species changed dramatically between levels of generalization. Areas predicted to be of greatest conservation value on the basis of species richness may therefore be sensitive to GIS data resolution.

Increasing the availability of national mapping products.

USGS Publications Warehouse

Roney, J.I.; Ogilvie, B.C.

1981-01-01

A discussion of the means employed by the US Geological Survey to facilitate map usage, covering aspects of project Map Accessibility Program including special rolled and folded map packaging, new market testing, parks and campgrounds program, expanded map dealer program, new booklet-type State sales index and catalog and new USGS map reference code. The USGS is seen as the producer of a tremendous nation-wide inventory of topographic and related map products available in unprecedented types, formats and scales, and as endeavouring to increase access to its products. The new USGS map reference code is appended. -J.C.Stone

Ground-water vulnerability to nitrate contamination in the mid-atlantic region

USGS Publications Warehouse

Greene, Earl A.; LaMotte, Andrew E.; Cullinan, Kerri-Ann; Smith, Elizabeth R.

2005-01-01

The U.S. Environmental Protection Agency?s (USEPA) Regional Vulnerability Assessment (ReVA) Program has developed a set of statistical tools to support regional-scale, integrated ecological risk-assessment studies. One of these tools, developed by the U.S. Geological Survey (USGS), is used with available water-quality data obtained from USGS National Water-Quality Assessment (NAWQA) and other studies in association with land cover, geology, soils, and other geographic data to develop logistic-regression equations that predict the vulnerability of ground water to nitrate concentrations exceeding specified thresholds in the Mid-Atlantic Region. The models were developed and applied to produce spatial probability maps showing the likelihood of elevated concentrations of nitrate in the region. These maps can be used to identify areas that currently are at risk and help identify areas where ground water has been affected by human activities. This information can be used by regional and local water managers to protect water supplies and identify land-use planning solutions and monitoring programs in these vulnerable areas.

Can next-generation soil data products improve soil moisture modelling at the continental scale? An assessment using a new microclimate package for the R programming environment

NASA Astrophysics Data System (ADS)

Kearney, Michael R.; Maino, James L.

2018-06-01

Accurate models of soil moisture are vital for solving core problems in meteorology, hydrology, agriculture and ecology. The capacity for soil moisture modelling is growing rapidly with the development of high-resolution, continent-scale gridded weather and soil data together with advances in modelling methods. In particular, the GlobalSoilMap.net initiative represents next-generation, depth-specific gridded soil products that may substantially increase soil moisture modelling capacity. Here we present an implementation of Campbell's infiltration and redistribution model within the NicheMapR microclimate modelling package for the R environment, and use it to assess the predictive power provided by the GlobalSoilMap.net product Soil and Landscape Grid of Australia (SLGA, ∼100 m) as well as the coarser resolution global product SoilGrids (SG, ∼250 m). Predictions were tested in detail against 3 years of root-zone (3-75 cm) soil moisture observation data from 35 monitoring sites within the OzNet project in Australia, with additional tests of the finalised modelling approach against cosmic-ray neutron (CosmOz, 0-50 cm, 9 sites from 2011 to 2017) and satellite (ASCAT, 0-2 cm, continent-wide from 2007 to 2009) observations. The model was forced by daily 0.05° (∼5 km) gridded meteorological data. The NicheMapR system predicted soil moisture to within experimental error for all data sets. Using the SLGA or the SG soil database, the OzNet soil moisture could be predicted with a root mean square error (rmse) of ∼0.075 m3 m-3 and a correlation coefficient (r) of 0.65 consistently through the soil profile without any parameter tuning. Soil moisture predictions based on the SLGA and SG datasets were ≈ 17% closer to the observations than when using a chloropleth-derived soil data set (Digital Atlas of Australian Soils), with the greatest improvements occurring for deeper layers. The CosmOz observations were predicted with similar accuracy (r = 0.76 and rmse of ∼0.085 m3 m-3). Comparisons at the continental scale to 0-2 cm satellite data (ASCAT) showed that the SLGA/SG datasets increased model fit over simulations using the DAAS soil properties (r ∼ 0.63 &rmse 15% vs. r 0.48 &rmse 18%, respectively). Overall, our results demonstrate the advantages of using GlobalSoilMap.net products in combination with gridded weather data for modelling soil moisture at fine spatial and temporal resolution at the continental scale.

Potential of EnMAP spaceborne imaging spectroscopy for the prediction of common surface soil properties and expected accuracy

NASA Astrophysics Data System (ADS)

Chabrillat, Sabine; Foerster, Saskia; Steinberg, Andreas; Stevens, Antoine; Segl, Karl

2016-04-01

There is a renewed awareness of the finite nature of the world's soil resources, growing concern about soil security, and significant uncertainties about the carrying capacity of the planet. As a consequence, soil scientists are being challenged to provide regular assessments of soil conditions from local through to global scales. However, only a few countries have the necessary survey and monitoring programs to meet these new needs and existing global data sets are out-of-date. A particular issue is the clear demand for a new area-wide regional to global coverage with accurate, up-to-date, and spatially referenced soil information as expressed by the modeling scientific community, farmers and land users, and policy and decision makers. Soil spectroscopy from remote sensing observations based on studies from the laboratory scale to the airborne scale has been shown to be a proven method for the quantitative prediction of key soil surface properties in local areas for exposed soils in appropriate surface conditions such as low vegetation cover and low water content. With the upcoming launch of the next generation of hyperspectral satellite sensors in the next 3 to 5 years (EnMAP, HISUI, PRISMA, SHALOM), a great potential for the global mapping and monitoring of soil properties is appearing. Nevertheless, the capabilities to extend the soil properties current spectral modeling from local to regional scales are still to be demonstrated using robust methods. In particular, three central questions are at the forefront of research nowadays: a) methodological developments toward improved algorithms and operational tools for the extraction of soil properties, b) up scaling from the laboratory into space domain, and c) demonstration of the potential of upcoming satellite systems and expected accuracy of soil maps. In this study, airborne imaging spectroscopy data from several test sites are used to simulate EnMAP satellite images at 30 m scale. Then, different soil algorithms are examined based on the analyses of chemical-physical features from the soil spectral reflectance and/or multivariate established techniques such as Partial-Least Squares PLS, Support-Vector Machine SVM, to determine common surface soil properties, in particular soil organic carbon (SOC), clay and iron oxide content. Results show that EnMAP is able to predict clay, free iron oxide, and SOC with an RV2 between 0.53 and 0.67 compared to airborne imagery with RV2 between 0.64 and 0.74. The correlation between EnMAP and airborne imagery prediction results is high (Pearson coefficients between 0.84 and 0.91). Furthermore, spatial distribution is coherent between the airborne mapping and simulated EnMAP mapping as shown with a spatial structure analysis. In general, this paper demonstrates the high potential of upcoming spaceborne hyperspectral missions for soil science studies but also shows the need for future adapted strategies to fulfill the entire potential of soil spectroscopy for orbital utilization.

Template‐based field map prediction for rapid whole brain B0 shimming

PubMed Central

Shi, Yuhang; Vannesjo, S. Johanna; Miller, Karla L.

2017-01-01

Purpose In typical MRI protocols, time is spent acquiring a field map to calculate the shim settings for best image quality. We propose a fast template‐based field map prediction method that yields near‐optimal shims without measuring the field. Methods The template‐based prediction method uses prior knowledge of the B0 distribution in the human brain, based on a large database of field maps acquired from different subjects, together with subject‐specific structural information from a quick localizer scan. The shimming performance of using the template‐based prediction is evaluated in comparison to a range of potential fast shimming methods. Results Static B0 shimming based on predicted field maps performed almost as well as shimming based on individually measured field maps. In experimental evaluations at 7 T, the proposed approach yielded a residual field standard deviation in the brain of on average 59 Hz, compared with 50 Hz using measured field maps and 176 Hz using no subject‐specific shim. Conclusions This work demonstrates that shimming based on predicted field maps is feasible. The field map prediction accuracy could potentially be further improved by generating the template from a subset of subjects, based on parameters such as head rotation and body mass index. Magn Reson Med 80:171–180, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. PMID:29193340

Middle Atmosphere Program. Handbook for MAP, Volume 17

NASA Technical Reports Server (NTRS)

Sechrist, C. F., Jr. (Editor)

1985-01-01

The Middle Atmosphere Program (MAP) handbook is divided into three parts. Part 1 consists of minutes of MAP steering committee meeting and MAP assembly. Part 2 consists of project and study group reports, such as: (1) Atmospheric Tides Middle Atmosphere Program (ATMAP), report of the Nov./Dec. 1981, and May 1982 observational campaigns; MAP/WINE experimenters meeting at Berlin, 1985; (3) MAP/WINE experimenters meeting at Loen, Norway, 1985; and (4) the penetration of ultraviolet solar radiation into the middle atmosphere. Part 3 consists of national reports.

NORTH AMERICAN DATUM 1983 IMPLEMENTATION IMPACTS ON THE USGS NATIONAL MAPPING PROGRAM.

USGS Publications Warehouse

Jones, William J.; Needham, Paul E.

1985-01-01

The U. S. Geological Survey has previously experienced the impacts on the National Mapping Program that are associated with implementing a readjustment of the horizontal datum. The impacts of these past readjustments were minimal compared to those of the current readjustment. The Geological Survey currently has produced and published over 60,000 different map products. The 7. 5-minute mapping program is nearing completion with over 85 percent of the conterminous States mapped. The intermediate-scale mapping program of the conterminous United States is scheduled for completion of planimetric editions by the end of 1986. It is apparent that until digital cartographic data are available, implementation of the North American Datum 1983 will primarily consist of cartographic adjustment of existing map products.

Climate Prediction Center - Expert Assessments Index

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Monitoring and Data > Global Climate Data & Maps > ; Global Regional Climate Maps Regional Climate Maps Banner The Monthly regional analyses products are

Bayesian geostatistics in health cartography: the perspective of malaria.

PubMed

Patil, Anand P; Gething, Peter W; Piel, Frédéric B; Hay, Simon I

2011-06-01

Maps of parasite prevalences and other aspects of infectious diseases that vary in space are widely used in parasitology. However, spatial parasitological datasets rarely, if ever, have sufficient coverage to allow exact determination of such maps. Bayesian geostatistics (BG) is a method for finding a large sample of maps that can explain a dataset, in which maps that do a better job of explaining the data are more likely to be represented. This sample represents the knowledge that the analyst has gained from the data about the unknown true map. BG provides a conceptually simple way to convert these samples to predictions of features of the unknown map, for example regional averages. These predictions account for each map in the sample, yielding an appropriate level of predictive precision.

Bayesian geostatistics in health cartography: the perspective of malaria

PubMed Central

Patil, Anand P.; Gething, Peter W.; Piel, Frédéric B.; Hay, Simon I.

2011-01-01

Maps of parasite prevalences and other aspects of infectious diseases that vary in space are widely used in parasitology. However, spatial parasitological datasets rarely, if ever, have sufficient coverage to allow exact determination of such maps. Bayesian geostatistics (BG) is a method for finding a large sample of maps that can explain a dataset, in which maps that do a better job of explaining the data are more likely to be represented. This sample represents the knowledge that the analyst has gained from the data about the unknown true map. BG provides a conceptually simple way to convert these samples to predictions of features of the unknown map, for example regional averages. These predictions account for each map in the sample, yielding an appropriate level of predictive precision. PMID:21420361

User's manual for University of Arizona APART program (Analysis Program - Arizona Radiation Trace)

NASA Technical Reports Server (NTRS)

Breault, R. P.

1975-01-01

A description and operating instructions for the Analysis Program Arizona Radiation Trace (APART) are given. This is a computer program that is able to efficiently and accurately predict the off-axis rejection characteristics of unwanted stray radiation for complex rotationally symmetric optical systems. The program first determines the critical objects or areas that scatter radiation to the image plane either directly or through imaging elements: this provides the opportunity to modify, if necessary, the design so that the number of critical areas seen by the image plane is reduced or the radiation to these critical areas is minimized. Next, the power distribution reaching the image plane and a sectional power map of all internal surfaces are computed. Angular information is also provided that relates the angle by which the radiation came into a surface to the angle by which the radiation is scattered out of the surface.

Benefits Mapping and Analysis Program (BenMAP)

EPA Pesticide Factsheets

This area summarizes the key features of the BenMAP-CE program and links to pages that provide more details regarding the program, the basic principles of air pollution benefits analysis and a link to download the software.

Discrimination of Active and Weakly Active Human BACE1 Inhibitors Using Self-Organizing Map and Support Vector Machine.

PubMed

Li, Hang; Wang, Maolin; Gong, Ya-Nan; Yan, Aixia

2016-01-01

β-secretase (BACE1) is an aspartyl protease, which is considered as a novel vital target in Alzheimer`s disease therapy. We collected a data set of 294 BACE1 inhibitors, and built six classification models to discriminate active and weakly active inhibitors using Kohonen's Self-Organizing Map (SOM) method and Support Vector Machine (SVM) method. Each molecular descriptor was calculated using the program ADRIANA.Code. We adopted two different methods: random method and Self-Organizing Map method, for training/test set split. The descriptors were selected by F-score and stepwise linear regression analysis. The best SVM model Model2C has a good prediction performance on test set with prediction accuracy, sensitivity (SE), specificity (SP) and Matthews correlation coefficient (MCC) of 89.02%, 90%, 88%, 0.78, respectively. Model 1A is the best SOM model, whose accuracy and MCC of the test set were 94.57% and 0.98, respectively. The lone pair electronegativity and polarizability related descriptors importantly contributed to bioactivity of BACE1 inhibitor. The Extended-Connectivity Finger-Prints_4 (ECFP_4) analysis found some vitally key substructural features, which could be helpful for further drug design research. The SOM and SVM models built in this study can be obtained from the authors by email or other contacts.

Computer-composite mapping for geologists

USGS Publications Warehouse

van Driel, J.N.

1980-01-01

A computer program for overlaying maps has been tested and evaluated as a means for producing geologic derivative maps. Four maps of the Sugar House Quadrangle, Utah, were combined, using the Multi-Scale Data Analysis and Mapping Program, in a single composite map that shows the relative stability of the land surface during earthquakes. Computer-composite mapping can provide geologists with a powerful analytical tool and a flexible graphic display technique. Digitized map units can be shown singly, grouped with different units from the same map, or combined with units from other source maps to produce composite maps. The mapping program permits the user to assign various values to the map units and to specify symbology for the final map. Because of its flexible storage, easy manipulation, and capabilities of graphic output, the composite-mapping technique can readily be applied to mapping projects in sedimentary and crystalline terranes, as well as to maps showing mineral resource potential. ?? 1980 Springer-Verlag New York Inc.

Contribution of physical modelling to climate-driven landslide hazard mapping: an alpine test site

NASA Astrophysics Data System (ADS)

Vandromme, R.; Desramaut, N.; Baills, A.; Hohmann, A.; Grandjean, G.; Sedan, O.; Mallet, J. P.

2012-04-01

The aim of this work is to develop a methodology for integrating climate change scenarios into quantitative hazard assessment and especially their precipitation component. The effects of climate change will be different depending on both the location of the site and the type of landslide considered. Indeed, mass movements can be triggered by different factors. This paper describes a methodology to address this issue and shows an application on an alpine test site. Mechanical approaches represent a solution for quantitative landslide susceptibility and hazard modeling. However, as the quantity and the quality of data are generally very heterogeneous at a regional scale, it is necessary to take into account the uncertainty in the analysis. In this perspective, a new hazard modeling method is developed and integrated in a program named ALICE. This program integrates mechanical stability analysis through a GIS software taking into account data uncertainty. This method proposes a quantitative classification of landslide hazard and offers a useful tool to gain time and efficiency in hazard mapping. However, an expertise approach is still necessary to finalize the maps. Indeed it is the only way to take into account some influent factors in slope stability such as heterogeneity of the geological formations or effects of anthropic interventions. To go further, the alpine test site (Barcelonnette area, France) is being used to integrate climate change scenarios into ALICE program, and especially their precipitation component with the help of a hydrological model (GARDENIA) and the regional climate model REMO (Jacob, 2001). From a DEM, land-cover map, geology, geotechnical data and so forth the program classifies hazard zones depending on geotechnics and different hydrological contexts varying in time. This communication, realized within the framework of Safeland project, is supported by the European Commission under the 7th Framework Programme for Research and Technological Development, Area "Environment", Activity 1.3.3.1 "Prediction of triggering and risk assessment for landslides".

The "neuro-mapping locator" software. A real-time intraoperative objective paraesthesia mapping tool to evaluate paraesthesia coverage of the painful zone in patients undergoing spinal cord stimulation lead implantation.

PubMed

Guetarni, F; Rigoard, P

2015-03-01

Conventional spinal cord stimulation (SCS) generates paraesthesia, as the efficacy of this technique is based on the relationship between the paraesthesia provided by SCS on the painful zone and an analgesic effect on the stimulated zone. Although this basic postulate is based on clinical evidence, it is clear that this relationship has never been formally demonstrated by scientific studies. There is a need for objective evaluation tools ("transducers") to transpose electrical signals to clinical effects and to guide therapeutic choices. We have developed a software at Poitiers University hospital allowing real-time objective mapping of the paraesthesia generated by SCS lead placement and programming during the implantation procedure itself, on a touch screen interface. The purpose of this article is to describe this intraoperative mapping software, in terms of its concept and technical aspects. The Neuro-Mapping Locator (NML) software is dedicated to patients with failed back surgery syndrome, candidates for SCS lead implantation, to actively participate in the implantation procedure. Real-time geographical localization of the paraesthesia generated by percutaneous or multicolumn surgical SCS lead implanted under awake anaesthesia allows intraoperative lead programming and possibly lead positioning to be modified with the patient's cooperation. Software updates should enable us to refine objectives related to the use of this tool and minimize observational biases. The ultimate goals of NML software should not be limited to optimize one specific device implantation in a patient but also allow to compare instantaneously various stimulation strategies, by characterizing new technical parameters as "coverage efficacy" and "device specificity" on selected subgroups of patients. Another longer-term objective would be to organize these predictive factors into computer science ontologies, which could constitute robust and helpful data for device selection and programming of tomorrow's neurostimulators. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Using Maps in Web Analytics to Evaluate the Impact of Web-Based Extension Programs

ERIC Educational Resources Information Center

Veregin, Howard

2015-01-01

Maps can be a valuable addition to the Web analytics toolbox for Extension programs that use the Web to disseminate information. Extension professionals use Web analytics tools to evaluate program impacts. Maps add a unique perspective through visualization and analysis of geographic patterns and their relationships to other variables. Maps can…

Risk of nitrate in groundwaters of the United States - A national perspective

USGS Publications Warehouse

Nolan, B.T.; Ruddy, B.C.; Hitt, K.J.; Helsel, D.R.

1997-01-01

Nitrate contamination of groundwater occurs in predictable patterns, based on findings of the U.S. Geological Survey's (USGS) National Water Quality Assessment (NAWQA) Program. The NAWQA Program was begun in 1991 to describe the quality of the Nation's water resources, using nationally consistent methods. Variables affecting nitrate concentration in groundwater were grouped as 'input' factors (population density end the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources) and 'aquifer vulnerability' factors (soil drainage characteristic and the ratio of woodland acres to cropland acres in agricultural areas) and compiled in a national map that shows patterns of risk for nitrate contamination of groundwater. Areas with high nitrogen input, well-drained soils, and low woodland to cropland ratio have the highest potential for contamination of shallow groundwater by nitrate. Groundwater nitrate data collected through 1992 from wells less than 100 ft deep generally verified the risk patterns shown on the national map. Median nitrate concentration was 0.2 mg/L in wells representing the low-risk group, and the maximum contaminant level (MCL) was exceeded in 3% of the wells. In contrast, median nitrate concentration was 4.8 mg/L in wells representing the high-risk group, and the MCL was exceeded in 25% of the wells.Nitrate contamination of groundwater occurs in predictable patterns, based on findings of the U.S. Geological Survey's (USGS) National Water Quality Assessment (NAWQA) Program. The NAWQA Program was begun in 1991 to describe the quality of the Nation's water resources, using nationally consistent methods. Variables affecting nitrate concentration in groundwater were grouped as `input' factors (population density and the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources) and `aquifer vulnerability' factors (soil drainage characteristic and the ratio of woodland acres to cropland acres in agricultural areas) and compiled in a national map that shows patterns of risk for nitrate contamination of groundwater. Areas with high nitrogen input, well-drained soils, and low woodland to cropland ratio have the highest potential for contamination of shallow groundwater by nitrate. Groundwater nitrate data collected through 1992 from wells less than 100 ft deep generally verified the risk patterns shown on the national map. Median nitrate concentration was 0.2 mg/L in wells representing the low-risk group, and the maximum contaminant level (MCL) was exceeded in 3% of the wells. In contrast, median nitrate concentration was 4.8 mg/L in wells representing the high-risk group, and the MCL was exceeded in 25% of the wells.

TU-G-BRA-03: Predicting Radiation Therapy Induced Ventilation Changes Using 4DCT Jacobian Calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patton, T; Du, K; Bayouth, J

2015-06-15

Purpose: Longitudinal changes in lung ventilation following radiation therapy can be mapped using four-dimensional computed tomography(4DCT) and image registration. This study aimed to predict ventilation changes caused by radiation therapy(RT) as a function of pre-RT ventilation and delivered dose. Methods: 4DCT images were acquired before and 3 months after radiation therapy for 13 subjects. Jacobian ventilation maps were calculated from the 4DCT images, warped to a common coordinate system, and a Jacobian ratio map was computed voxel-by-voxel as the ratio of post-RT to pre-RT Jacobian calculations. A leave-one-out method was used to build a response model for each subject: post-RTmore » to pre-RT Jacobian ratio data and dose distributions of 12 subjects were applied to the subject’s pre-RT Jacobian map to predict the post-RT Jacobian. The predicted Jacobian map was compared to the actual post-RT Jacobian map to evaluate efficacy. Within this cohort, 8 subjects had repeat pre-RT scans that were compared as a reference for no ventilation change. Maps were compared using gamma pass rate criteria of 2mm distance-to-agreement and 6% ventilation difference. Gamma pass rates were compared using paired t-tests to determine significant differences. Further analysis masked non-radiation induced changes by excluding voxels below specified dose thresholds. Results: Visual inspection demonstrates the predicted post-RT ventilation map is similar to the actual map in magnitude and distribution. Quantitatively, the percentage of voxels in agreement when excluding voxels receiving below specified doses are: 74%/20Gy, 73%/10Gy, 73%/5Gy, and 71%/0Gy. By comparison, repeat scans produced 73% of voxels within the 6%/2mm criteria. The agreement of the actual post-RT maps with the predicted maps was significantly better than agreement with pre-RT maps (p<0.02). Conclusion: This work validates that significant changes to ventilation post-RT can be predicted. The differences between the predicted and actual outcome are similar to differences between repeat scans with equivalent ventilation. This work was supported by NIH grant CA166703 and a Pilot Grant from University of Iowa Carver College of Medicine.« less

Can Mapping Algorithms Based on Raw Scores Overestimate QALYs Gained by Treatment? A Comparison of Mappings Between the Roland-Morris Disability Questionnaire and the EQ-5D-3L Based on Raw and Differenced Score Data.

PubMed

Madan, Jason; Khan, Kamran A; Petrou, Stavros; Lamb, Sarah E

2017-05-01

Mapping algorithms are increasingly being used to predict health-utility values based on responses or scores from non-preference-based measures, thereby informing economic evaluations. We explored whether predictions in the EuroQol 5-dimension 3-level instrument (EQ-5D-3L) health-utility gains from mapping algorithms might differ if estimated using differenced versus raw scores, using the Roland-Morris Disability Questionnaire (RMQ), a widely used health status measure for low back pain, as an example. We estimated algorithms mapping within-person changes in RMQ scores to changes in EQ-5D-3L health utilities using data from two clinical trials with repeated observations. We also used logistic regression models to estimate response mapping algorithms from these data to predict within-person changes in responses to each EQ-5D-3L dimension from changes in RMQ scores. Predicted health-utility gains from these mappings were compared with predictions based on raw RMQ data. Using differenced scores reduced the predicted health-utility gain from a unit decrease in RMQ score from 0.037 (standard error [SE] 0.001) to 0.020 (SE 0.002). Analysis of response mapping data suggests that the use of differenced data reduces the predicted impact of reducing RMQ scores across EQ-5D-3L dimensions and that patients can experience health-utility gains on the EQ-5D-3L 'usual activity' dimension independent from improvements captured by the RMQ. Mappings based on raw RMQ data overestimate the EQ-5D-3L health utility gains from interventions that reduce RMQ scores. Where possible, mapping algorithms should reflect within-person changes in health outcome and be estimated from datasets containing repeated observations if they are to be used to estimate incremental health-utility gains.

Mapping the EORTC QLQ-C30 onto the EQ-5D-3L: assessing the external validity of existing mapping algorithms.

PubMed

Doble, Brett; Lorgelly, Paula

2016-04-01

To determine the external validity of existing mapping algorithms for predicting EQ-5D-3L utility values from EORTC QLQ-C30 responses and to establish their generalizability in different types of cancer. A main analysis (pooled) sample of 3560 observations (1727 patients) and two disease severity patient samples (496 and 93 patients) with repeated observations over time from Cancer 2015 were used to validate the existing algorithms. Errors were calculated between observed and predicted EQ-5D-3L utility values using a single pooled sample and ten pooled tumour type-specific samples. Predictive accuracy was assessed using mean absolute error (MAE) and standardized root-mean-squared error (RMSE). The association between observed and predicted EQ-5D utility values and other covariates across the distribution was tested using quantile regression. Quality-adjusted life years (QALYs) were calculated using observed and predicted values to test responsiveness. Ten 'preferred' mapping algorithms were identified. Two algorithms estimated via response mapping and ordinary least-squares regression using dummy variables performed well on number of validation criteria, including accurate prediction of the best and worst QLQ-C30 health states, predicted values within the EQ-5D tariff range, relatively small MAEs and RMSEs, and minimal differences between estimated QALYs. Comparison of predictive accuracy across ten tumour type-specific samples highlighted that algorithms are relatively insensitive to grouping by tumour type and affected more by differences in disease severity. Two of the 'preferred' mapping algorithms suggest more accurate predictions, but limitations exist. We recommend extensive scenario analyses if mapped utilities are used in cost-utility analyses.

High-resolution linkage map and chromosome-scale genome assembly for cassava ( Manihot esculenta Crantz) from 10 populations

DOE PAGES

Lyons, Jessica

2014-12-11

Cassava Manihot esculenta Crantz) is a major staple crop in Africa, Asia, and South America, and its starchy roots provide nourishment for 800 million people worldwide. Although native to South America, cassava was brought to Africa 400–500 years ago and is now widely cultivated across sub-Saharan Africa, but it is subject to biotic and abiotic stresses. To assist in the rapid identification of markers for pathogen resistance and crop traits, and to accelerate breeding programs, we generated a framework map for M. esculent Crantz from reduced representation sequencing [genotyping-by-sequencing (GBS)]. The composite 2412-cM map integrates 10 biparental maps (comprising 3480more » meioses) and organizes 22,403 genetic markers on 18 chromosomes, in agreement with the observed karyotype. Here, we used the map to anchor 71.9% of the draft genome assembly and 90.7% of the predicted protein-coding genes. The chromosome-anchored genome sequence will be useful for breeding improvement by assisting in the rapid identification of markers linked to important traits, and in providing a framework for genomic selectionenhanced breeding of this important crop.« less

High-resolution linkage map and chromosome-scale genome assembly for cassava ( Manihot esculenta Crantz) from 10 populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lyons, Jessica

Cassava Manihot esculenta Crantz) is a major staple crop in Africa, Asia, and South America, and its starchy roots provide nourishment for 800 million people worldwide. Although native to South America, cassava was brought to Africa 400–500 years ago and is now widely cultivated across sub-Saharan Africa, but it is subject to biotic and abiotic stresses. To assist in the rapid identification of markers for pathogen resistance and crop traits, and to accelerate breeding programs, we generated a framework map for M. esculent Crantz from reduced representation sequencing [genotyping-by-sequencing (GBS)]. The composite 2412-cM map integrates 10 biparental maps (comprising 3480more » meioses) and organizes 22,403 genetic markers on 18 chromosomes, in agreement with the observed karyotype. Here, we used the map to anchor 71.9% of the draft genome assembly and 90.7% of the predicted protein-coding genes. The chromosome-anchored genome sequence will be useful for breeding improvement by assisting in the rapid identification of markers linked to important traits, and in providing a framework for genomic selectionenhanced breeding of this important crop.« less

Climate Prediction Center - Outlooks: Current UV Index Forecast Map

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A Self-Organizing Map Based Evaluation of the Antarctic Mesoscale Prediction System Using Observations from a 30-m Instrumented Tower on the Ross Ice Shelf, Antarctica

NASA Astrophysics Data System (ADS)

Nigro, M. A.; Cassano, J. J.; Wille, J.; Bromwich, D. H.; Lazzara, M. A.

2015-12-01

An accurate representation of the atmospheric boundary layer in numerical weather prediction models is important for predicting turbulence and energy exchange in the atmosphere. This study uses two years of observations from a 30-m automatic weather station (AWS) installed on the Ross Ice Shelf, Antarctica to evaluate forecasts from the Antarctic Mesoscale Prediction System (AMPS), a numerical weather prediction system based on the polar version of the Weather Research and Forecasting (Polar WRF) model that uses the MYJ planetary boundary layer scheme and that primarily supports the extensive aircraft operations of the U.S. Antarctic Program. The 30-m AWS has six levels of instrumentation, providing vertical profiles of temperature, wind speed, and wind direction. The observations show the atmospheric boundary layer over the Ross Ice Shelf is stable approximately 80% of the time, indicating the influence of the permanent ice surface in this region. The observations from the AWS are further analyzed using the method of self-organizing maps (SOM) to identify the range of potential temperature profiles that occur over the Ross Ice Shelf. The SOM analysis identified 30 patterns, which range from strong inversions to slightly unstable profiles. The corresponding AMPS forecasts were evaluated for each of the 30 patterns to understand the accuracy of the AMPS near surface layer under different atmospheric conditions. The results indicate that under stable conditions AMPS with MYJ under predicts the inversion strength by as much as 7.4 K over the 30-m depth of the tower and over predicts the near surface wind speed by as much as 3.8 m s-1. Conversely, under slightly unstable conditions, AMPS predicts both the inversion strength and near surface wind speeds with reasonable accuracy.

PARTS: Probabilistic Alignment for RNA joinT Secondary structure prediction

PubMed Central

Harmanci, Arif Ozgun; Sharma, Gaurav; Mathews, David H.

2008-01-01

A novel method is presented for joint prediction of alignment and common secondary structures of two RNA sequences. The joint consideration of common secondary structures and alignment is accomplished by structural alignment over a search space defined by the newly introduced motif called matched helical regions. The matched helical region formulation generalizes previously employed constraints for structural alignment and thereby better accommodates the structural variability within RNA families. A probabilistic model based on pseudo free energies obtained from precomputed base pairing and alignment probabilities is utilized for scoring structural alignments. Maximum a posteriori (MAP) common secondary structures, sequence alignment and joint posterior probabilities of base pairing are obtained from the model via a dynamic programming algorithm called PARTS. The advantage of the more general structural alignment of PARTS is seen in secondary structure predictions for the RNase P family. For this family, the PARTS MAP predictions of secondary structures and alignment perform significantly better than prior methods that utilize a more restrictive structural alignment model. For the tRNA and 5S rRNA families, the richer structural alignment model of PARTS does not offer a benefit and the method therefore performs comparably with existing alternatives. For all RNA families studied, the posterior probability estimates obtained from PARTS offer an improvement over posterior probability estimates from a single sequence prediction. When considering the base pairings predicted over a threshold value of confidence, the combination of sensitivity and positive predictive value is superior for PARTS than for the single sequence prediction. PARTS source code is available for download under the GNU public license at http://rna.urmc.rochester.edu. PMID:18304945

The GRAM-3 model

NASA Technical Reports Server (NTRS)

Justus, C. G.

1987-01-01

The Global Reference Atmosphere Model (GRAM) is under continuous development and improvement. GRAM data were compared with Middle Atmosphere Program (MAP) predictions and with shuttle data. An important note: Users should employ only step sizes in altitude that give vertical density gradients consistent with shuttle-derived density data. Using too small a vertical step size (finer then 1 km) will result in what appears to be unreasonably high values of density shears but what in reality is noise in the model.

Laharz_py: GIS tools for automated mapping of lahar inundation hazard zones

USGS Publications Warehouse

Schilling, Steve P.

2014-01-01

Laharz_py is written in the Python programming language as a suite of tools for use in ArcMap Geographic Information System (GIS). Primarily, Laharz_py is a computational model that uses statistical descriptions of areas inundated by past mass-flow events to forecast areas likely to be inundated by hypothetical future events. The forecasts use physically motivated and statistically calibrated power-law equations that each has a form A = cV2/3, relating mass-flow volume (V) to planimetric or cross-sectional areas (A) inundated by an average flow as it descends a given drainage. Calibration of the equations utilizes logarithmic transformation and linear regression to determine the best-fit values of c. The software uses values of V, an algorithm for idenitifying mass-flow source locations, and digital elevation models of topography to portray forecast hazard zones for lahars, debris flows, or rock avalanches on maps. Laharz_py offers two methods to construct areas of potential inundation for lahars: (1) Selection of a range of plausible V values results in a set of nested hazard zones showing areas likely to be inundated by a range of hypothetical flows; and (2) The user selects a single volume and a confidence interval for the prediction. In either case, Laharz_py calculates the mean expected A and B value from each user-selected value of V. However, for the second case, a single value of V yields two additional results representing the upper and lower values of the confidence interval of prediction. Calculation of these two bounding predictions require the statistically calibrated prediction equations, a user-specified level of confidence, and t-distribution statistics to calculate the standard error of regression, standard error of the mean, and standard error of prediction. The portrayal of results from these two methods on maps compares the range of inundation areas due to prediction uncertainties with uncertainties in selection of V values. The Open-File Report document contains an explanation of how to install and use the software. The Laharz_py software includes an example data set for Mount Rainier, Washington. The second part of the documentation describes how to use all of the Laharz_py tools in an example dataset at Mount Rainier, Washington.

Observing gas in Cosmic Web filaments to constrain simulations of cosmic structure formation

NASA Astrophysics Data System (ADS)

Wakker, Bart

2016-10-01

Cosmological simulations predict that dark matter and baryons condense into multi-Mpc filamentary structures, making up the Cosmic Web. This is outlined by dark matter halos, inside which 10% of baryons are concentrated to make stars in galaxies. The other 90% of the baryons remain gaseous, with about half located outside galaxy halos. They can be traced by Lyman alpha absorbers, whose HI column density is determined by a combination of gas density and the intensity of the extragalactic ionizing background (EGB). About 1000 HST orbits have been expended to map the 50% of baryons in galaxy halos. This contrasts with 37 orbits explicitly allocated to map the other 50% (our Cycle 18 program to observe 17 AGN projected onto a single filament at cz 3500 km/s). We propose a 68-orbit program to observe 40 AGN, creating a sample of 56 sightlines covering a second filament at cz 2500 km/s. Using this dataset we will do the following: (1) measure the intensity of the EGB to within about 50%; (2) confirm that the linewidth of Lya absorbers increases near the filament axis, suggesting increasing temperature or turbulence; (3) check our earlier finding that simulations predict a transverse density HI profile (which scales with the dark-matter profile) that is much broader than is indicated by the observations.

Predicting Anthropogenic Noise Contributions to US Waters.

PubMed

Gedamke, Jason; Ferguson, Megan; Harrison, Jolie; Hatch, Leila; Henderson, Laurel; Porter, Michael B; Southall, Brandon L; Van Parijs, Sofie

2016-01-01

To increase understanding of the potential effects of chronic underwater noise in US waters, the National Oceanic and Atmospheric Administration (NOAA) organized two working groups in 2011, collectively called "CetSound," to develop tools to map the density and distribution of cetaceans (CetMap) and predict the contribution of human activities to underwater noise (SoundMap). The SoundMap effort utilized data on density, distribution, acoustic signatures of dominant noise sources, and environmental descriptors to map estimated temporal, spatial, and spectral contributions to background noise. These predicted soundscapes are an initial step toward assessing chronic anthropogenic noise impacts on the ocean's varied acoustic habitats and the animals utilizing them.

SU-F-J-219: Predicting Ventilation Change Due to Radiation Therapy: Dependency On Pre-RT Ventilation and Effort Correction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patton, T; Du, K; Bayouth, J

Purpose: Ventilation change caused by radiation therapy (RT) can be predicted using four-dimensional computed tomography (4DCT) and image registration. This study tested the dependency of predicted post-RT ventilation on effort correction and pre-RT lung function. Methods: Pre-RT and 3 month post-RT 4DCT images were obtained for 13 patients. The 4DCT images were used to create ventilation maps using a deformable image registration based Jacobian expansion calculation. The post-RT ventilation maps were predicted in four different ways using the dose delivered, pre-RT ventilation, and effort correction. The pre-RT ventilation and effort correction were toggled to determine dependency. The four different predictedmore » ventilation maps were compared to the post-RT ventilation map calculated from image registration to establish the best prediction method. Gamma pass rates were used to compare the different maps with the criteria of 2mm distance-to-agreement and 6% ventilation difference. Paired t-tests of gamma pass rates were used to determine significant differences between the maps. Additional gamma pass rates were calculated using only voxels receiving over 20 Gy. Results: The predicted post-RT ventilation maps were in agreement with the actual post-RT maps in the following percentage of voxels averaged over all subjects: 71% with pre-RT ventilation and effort correction, 69% with no pre-RT ventilation and effort correction, 60% with pre-RT ventilation and no effort correction, and 58% with no pre-RT ventilation and no effort correction. When analyzing only voxels receiving over 20 Gy, the gamma pass rates were respectively 74%, 69%, 65%, and 55%. The prediction including both pre- RT ventilation and effort correction was the only prediction with significant improvement over using no prediction (p<0.02). Conclusion: Post-RT ventilation is best predicted using both pre-RT ventilation and effort correction. This is the only prediction that provided a significant improvement on agreement. Research support from NIH grants CA166119 and CA166703, a gift from Roger Koch, and a Pilot Grant from University of Iowa Carver College of Medicine.« less

Mapping proteins in the presence of paralogs using units of coevolution

PubMed Central

2013-01-01

Background We study the problem of mapping proteins between two protein families in the presence of paralogs. This problem occurs as a difficult subproblem in coevolution-based computational approaches for protein-protein interaction prediction. Results Similar to prior approaches, our method is based on the idea that coevolution implies equal rates of sequence evolution among the interacting proteins, and we provide a first attempt to quantify this notion in a formal statistical manner. We call the units that are central to this quantification scheme the units of coevolution. A unit consists of two mapped protein pairs and its score quantifies the coevolution of the pairs. This quantification allows us to provide a maximum likelihood formulation of the paralog mapping problem and to cast it into a binary quadratic programming formulation. Conclusion CUPID, our software tool based on a Lagrangian relaxation of this formulation, makes it, for the first time, possible to compute state-of-the-art quality pairings in a few minutes of runtime. In summary, we suggest a novel alternative to the earlier available approaches, which is statistically sound and computationally feasible. PMID:24564758

Cloudgene: A graphical execution platform for MapReduce programs on private and public clouds

PubMed Central

2012-01-01

Background The MapReduce framework enables a scalable processing and analyzing of large datasets by distributing the computational load on connected computer nodes, referred to as a cluster. In Bioinformatics, MapReduce has already been adopted to various case scenarios such as mapping next generation sequencing data to a reference genome, finding SNPs from short read data or matching strings in genotype files. Nevertheless, tasks like installing and maintaining MapReduce on a cluster system, importing data into its distributed file system or executing MapReduce programs require advanced knowledge in computer science and could thus prevent scientists from usage of currently available and useful software solutions. Results Here we present Cloudgene, a freely available platform to improve the usability of MapReduce programs in Bioinformatics by providing a graphical user interface for the execution, the import and export of data and the reproducibility of workflows on in-house (private clouds) and rented clusters (public clouds). The aim of Cloudgene is to build a standardized graphical execution environment for currently available and future MapReduce programs, which can all be integrated by using its plug-in interface. Since Cloudgene can be executed on private clusters, sensitive datasets can be kept in house at all time and data transfer times are therefore minimized. Conclusions Our results show that MapReduce programs can be integrated into Cloudgene with little effort and without adding any computational overhead to existing programs. This platform gives developers the opportunity to focus on the actual implementation task and provides scientists a platform with the aim to hide the complexity of MapReduce. In addition to MapReduce programs, Cloudgene can also be used to launch predefined systems (e.g. Cloud BioLinux, RStudio) in public clouds. Currently, five different bioinformatic programs using MapReduce and two systems are integrated and have been successfully deployed. Cloudgene is freely available at http://cloudgene.uibk.ac.at. PMID:22888776

Nasa's Planetary Geologic Mapping Program: Overview

NASA Astrophysics Data System (ADS)

Williams, D. A.

2016-06-01

NASA's Planetary Science Division supports the geologic mapping of planetary surfaces through a distinct organizational structure and a series of research and analysis (R&A) funding programs. Cartography and geologic mapping issues for NASA's planetary science programs are overseen by the Mapping and Planetary Spatial Infrastructure Team (MAPSIT), which is an assessment group for cartography similar to the Mars Exploration Program Assessment Group (MEPAG) for Mars exploration. MAPSIT's Steering Committee includes specialists in geological mapping, who make up the Geologic Mapping Subcommittee (GEMS). I am the GEMS Chair, and with a group of 3-4 community mappers we advise the U.S. Geological Survey Planetary Geologic Mapping Coordinator (Dr. James Skinner) and develop policy and procedures to aid the planetary geologic mapping community. GEMS meets twice a year, at the Annual Lunar and Planetary Science Conference in March, and at the Annual Planetary Mappers' Meeting in June (attendance is required by all NASA-funded geologic mappers). Funding programs under NASA's current R&A structure to propose geological mapping projects include Mars Data Analysis (Mars), Lunar Data Analysis (Moon), Discovery Data Analysis (Mercury, Vesta, Ceres), Cassini Data Analysis (Saturn moons), Solar System Workings (Venus or Jupiter moons), and the Planetary Data Archiving, Restoration, and Tools (PDART) program. Current NASA policy requires all funded geologic mapping projects to be done digitally using Geographic Information Systems (GIS) software. In this presentation we will discuss details on how geologic mapping is done consistent with current NASA policy and USGS guidelines.

A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1) for spatial prediction of floods

NASA Astrophysics Data System (ADS)

Tien Bui, Dieu; Hoang, Nhat-Duc

2017-09-01

In this study, a probabilistic model, named as BayGmmKda, is proposed for flood susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian framework constructed by a combination of a Gaussian mixture model (GMM), radial-basis-function Fisher discriminant analysis (RBFDA), and a geographic information system (GIS) database. In the Bayesian framework, GMM is used for modeling the data distribution of flood-influencing factors in the GIS database, whereas RBFDA is utilized to construct a latent variable that aims at enhancing the model performance. As a result, the posterior probabilistic output of the BayGmmKda model is used as flood susceptibility index. Experiment results showed that the proposed hybrid framework is superior to other benchmark models, including the adaptive neuro-fuzzy inference system and the support vector machine. To facilitate the model implementation, a software program of BayGmmKda has been developed in MATLAB. The BayGmmKda program can accurately establish a flood susceptibility map for the study region. Accordingly, local authorities can overlay this susceptibility map onto various land-use maps for the purpose of land-use planning or management.

An application of quantile random forests for predictive mapping of forest attributes

Treesearch

E.A. Freeman; G.G. Moisen

2015-01-01

Increasingly, random forest models are used in predictive mapping of forest attributes. Traditional random forests output the mean prediction from the random trees. Quantile regression forests (QRF) is an extension of random forests developed by Nicolai Meinshausen that provides non-parametric estimates of the median predicted value as well as prediction quantiles. It...

Role of post-mapping computed tomography in virtual-assisted lung mapping.

PubMed

Sato, Masaaki; Nagayama, Kazuhiro; Kuwano, Hideki; Nitadori, Jun-Ichi; Anraku, Masaki; Nakajima, Jun

2017-02-01

Background Virtual-assisted lung mapping is a novel bronchoscopic preoperative lung marking technique in which virtual bronchoscopy is used to predict the locations of multiple dye markings. Post-mapping computed tomography is performed to confirm the locations of the actual markings. This study aimed to examine the accuracy of marking locations predicted by virtual bronchoscopy and elucidate the role of post-mapping computed tomography. Methods Automated and manual virtual bronchoscopy was used to predict marking locations. After bronchoscopic dye marking under local anesthesia, computed tomography was performed to confirm the actual marking locations before surgery. Discrepancies between marking locations predicted by the different methods and the actual markings were examined on computed tomography images. Forty-three markings in 11 patients were analyzed. Results The average difference between the predicted and actual marking locations was 30 mm. There was no significant difference between the latest version of the automated virtual bronchoscopy system (30.7 ± 17.2 mm) and manual virtual bronchoscopy (29.8 ± 19.1 mm). The difference was significantly greater in the upper vs. lower lobes (37.1 ± 20.1 vs. 23.0 ± 6.8 mm, for automated virtual bronchoscopy; p < 0.01). Despite this discrepancy, all targeted lesions were successfully resected using 3-dimensional image guidance based on post-mapping computed tomography reflecting the actual marking locations. Conclusions Markings predicted by virtual bronchoscopy were dislocated from the actual markings by an average of 3 cm. However, surgery was accurately performed using post-mapping computed tomography guidance, demonstrating the indispensable role of post-mapping computed tomography in virtual-assisted lung mapping.

Shear-wave velocity characterization of the USGS Hawaiian strong-motion network on the Island of Hawaii and development of an NEHRP site-class map

USGS Publications Warehouse

Wong, Ivan G.; Stokoe, Kenneth; Cox, Brady R.; Yuan, Jiabei; Knudsen, Keith L.; Terra, Fabia; Okubo, Paul G.; Lin, Yin-Cheng

2011-01-01

To assess the level and nature of ground shaking in Hawaii for the purposes of earthquake hazard mitigation and seismic design, empirical ground-motion prediction models are desired. To develop such empirical relationships, knowledge of the subsurface site conditions beneath strong-motion stations is critical. Thus, as a first step to develop ground-motion prediction models for Hawaii, spectral-analysis-of-surface-waves (SASW) profiling was performed at the 22 free-field U.S. Geological Survey (USGS) strong-motion sites on the Big Island to obtain shear-wave velocity (VS) data. Nineteen of these stations recorded the 2006 Kiholo Bay moment magnitude (M) 6.7 earthquake, and 17 stations recorded the triggered M 6.0 Mahukona earthquake. VS profiling was performed to reach depths of more than 100 ft. Most of the USGS stations are situated on sites underlain by basalt, based on surficial geologic maps. However, the sites have varying degrees of weathering and soil development. The remaining strong-motion stations are located on alluvium or volcanic ash. VS30 (average VS in the top 30 m) values for the stations on basalt ranged from 906 to 1908 ft/s [National Earthquake Hazards Reduction Program (NEHRP) site classes C and D], because most sites were covered with soil of variable thickness. Based on these data, an NEHRP site-class map was developed for the Big Island. These new VS data will be a significant input into an update of the USGS statewide hazard maps and to the operation of ShakeMap on the island of Hawaii.

Facilitating the exploitation of ERTS imagery using snow enhancement techniques. [geological mapping of New England test area

NASA Technical Reports Server (NTRS)

Wobber, F. J.; Martin, K. R. (Principal Investigator); Amato, R. V.; Leshendok, T.

1974-01-01

The author has identified the following significant results. The procedure for conducting a regional geological mapping program utilizing snow-enhanced ERTS-1 imagery has been summarized. While it is recognized that mapping procedures in geological programs will vary from area to area and from geologist to geologist, it is believed that the procedure tested in this project is applicable over a wide range of mapping programs. The procedure is designed to maximize the utility and value of ERTS-1 imagery and aerial photography within the initial phase of geological mapping programs. Sample products which represent interim steps in the mapping formula (e.g. the ERTS Fracture-Lineament Map) have been prepared. A full account of these procedures and products will be included within the Snow Enhancement Users Manual.

Creating and validating cis-regulatory maps of tissue-specific gene expression regulation

PubMed Central

O'Connor, Timothy R.; Bailey, Timothy L.

2014-01-01

Predicting which genomic regions control the transcription of a given gene is a challenge. We present a novel computational approach for creating and validating maps that associate genomic regions (cis-regulatory modules–CRMs) with genes. The method infers regulatory relationships that explain gene expression observed in a test tissue using widely available genomic data for ‘other’ tissues. To predict the regulatory targets of a CRM, we use cross-tissue correlation between histone modifications present at the CRM and expression at genes within 1 Mbp of it. To validate cis-regulatory maps, we show that they yield more accurate models of gene expression than carefully constructed control maps. These gene expression models predict observed gene expression from transcription factor binding in the CRMs linked to that gene. We show that our maps are able to identify long-range regulatory interactions and improve substantially over maps linking genes and CRMs based on either the control maps or a ‘nearest neighbor’ heuristic. Our results also show that it is essential to include CRMs predicted in multiple tissues during map-building, that H3K27ac is the most informative histone modification, and that CAGE is the most informative measure of gene expression for creating cis-regulatory maps. PMID:25200088

Analysis of spatial distribution of land cover maps accuracy

NASA Astrophysics Data System (ADS)

Khatami, R.; Mountrakis, G.; Stehman, S. V.

2017-12-01

Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain yielded similar AUC; iv) for the larger sample size (i.e., very dense spatial sample) and per-class predictions, the spatial domain yielded larger AUC; v) increasing the sample size improved accuracy predictions with a greater benefit accruing to the spatial domain; and vi) the function used for interpolation had the smallest effect on AUC.

Active Fire Mapping Program

MedlinePlus

Active Fire Mapping Program Current Large Incidents (Home) New Large Incidents Fire Detection Maps MODIS Satellite Imagery VIIRS Satellite Imagery Fire Detection GIS Data Fire Data in Google Earth ...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Susandi, Armi, E-mail: armi@meteo.itb.ac.id; Tamamadin, Mamad, E-mail: mamadtama@meteo.itb.ac.id; Djamal, Erizal, E-mail: erizal-jamal@yahoo.com

This paper describes information system of rice planting calendar to help farmers in determining the time for rice planting. The information includes rainfall prediction in ten days (dasarian) scale overlaid to map of rice field to produce map of rice planting in village level. The rainfall prediction was produced by stochastic modeling using Fast Fourier Transform (FFT) and Non-Linier Least Squares methods to fit the curve of function to the rainfall data. In this research, the Fourier series has been modified become non-linear function to follow the recent characteristics of rainfall that is non stationary. The results have been alsomore » validated in 4 steps, including R-Square, RMSE, R-Skill, and comparison with field data. The development of information system (cyber extension) provides information such as rainfall prediction, prediction of the planting time, and interactive space for farmers to respond to the information submitted. Interfaces for interactive response will be critical to the improvement of prediction accuracy of information, both rainfall and planting time. The method used to get this information system includes mapping on rice planting prediction, converting the format file, developing database system, developing website, and posting website. Because of this map was overlaid with the Google map, the map files must be converted to the .kml file format.« less

Apparent diffusion coefficient mapping in medulloblastoma predicts non-infiltrative surgical planes.

PubMed

Marupudi, Neena I; Altinok, Deniz; Goncalves, Luis; Ham, Steven D; Sood, Sandeep

2016-11-01

An appropriate surgical approach for posterior fossa lesions is to start tumor removal from areas with a defined plane to where tumor is infiltrating the brainstem or peduncles. This surgical approach minimizes risk of damage to eloquent areas. Although magnetic resonance imaging (MRI) is the current standard preoperative imaging obtained for diagnosis and surgical planning of pediatric posterior fossa tumors, it offers limited information on the infiltrative planes between tumor and normal structures in patients with medulloblastomas. Because medulloblastomas demonstrate diffusion restriction on apparent diffusion coefficient map (ADC map) sequences, we investigated the role of ADC map in predicting infiltrative and non-infiltrative planes along the brain stem and/or cerebellar peduncles by medulloblastomas prior to surgery. Thirty-four pediatric patients with pathologically confirmed medulloblastomas underwent surgical resection at our facility from 2004 to 2012. An experienced pediatric neuroradiologist reviewed the brain MRIs/ADC map, assessing the planes between the tumor and cerebellar peduncles/brain stem. An independent evaluator documented surgical findings from operative reports for comparison to the radiographic findings. The radiographic findings were statistically compared to the documented intraoperative findings to determine predictive value of the test in identifying tumor infiltration of the brain stem cerebellar peduncles. Twenty-six patients had preoperative ADC mapping completed and thereby, met inclusion criteria. Mean age at time of surgery was 8.3 ± 4.6 years. Positive predictive value of ADC maps to predict tumor invasion of the brain stem and cerebellar peduncles ranged from 69 to 88 %; negative predictive values ranged from 70 to 89 %. Sensitivity approached 93 % while specificity approached 78 %. ADC maps are valuable in predicting the infiltrative and non-infiltrative planes along the tumor and brain stem interface in medulloblastomas. Inclusion and evaluation of ADC maps in preoperative evaluation can assist in surgical resection planning in patients with medulloblastoma.

Incorporation of satellite remote sensing pan-sharpened imagery into digital soil prediction and mapping models to characterize soil property variability in small agricultural fields

NASA Astrophysics Data System (ADS)

Xu, Yiming; Smith, Scot E.; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P.

2017-01-01

Soil prediction models based on spectral indices from some multispectral images are too coarse to characterize spatial pattern of soil properties in small and heterogeneous agricultural lands. Image pan-sharpening has seldom been utilized in Digital Soil Mapping research before. This research aimed to analyze the effects of pan-sharpened (PAN) remote sensing spectral indices on soil prediction models in smallholder farm settings. This research fused the panchromatic band and multispectral (MS) bands of WorldView-2, GeoEye-1, and Landsat 8 images in a village in Southern India by Brovey, Gram-Schmidt and Intensity-Hue-Saturation methods. Random Forest was utilized to develop soil total nitrogen (TN) and soil exchangeable potassium (Kex) prediction models by incorporating multiple spectral indices from the PAN and MS images. Overall, our results showed that PAN remote sensing spectral indices have similar spectral characteristics with soil TN and Kex as MS remote sensing spectral indices. There is no soil prediction model incorporating the specific type of pan-sharpened spectral indices always had the strongest prediction capability of soil TN and Kex. The incorporation of pan-sharpened remote sensing spectral data not only increased the spatial resolution of the soil prediction maps, but also enhanced the prediction accuracy of soil prediction models. Small farms with limited footprint, fragmented ownership and diverse crop cycle should benefit greatly from the pan-sharpened high spatial resolution imagery for soil property mapping. Our results show that multiple high and medium resolution images can be used to map soil properties suggesting the possibility of an improvement in the maps' update frequency. Additionally, the results should benefit the large agricultural community through the reduction of routine soil sampling cost and improved prediction accuracy.

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

PubMed Central

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-01-01

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides. PMID:27187430

A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

PubMed

Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

2016-05-11

In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

As-built design specification for segment map (Sgmap) program

NASA Technical Reports Server (NTRS)

Tompkins, M. A. (Principal Investigator)

1981-01-01

The segment map program (SGMAP), which is part of the CLASFYT package, is described in detail. This program is designed to output symbolic maps or numerical dumps from LANDSAT cluster/classification files or aircraft ground truth/processed ground truth files which are in 'universal' format.

Thread mapping using system-level model for shared memory multicores

NASA Astrophysics Data System (ADS)

Mitra, Reshmi

Exploring thread-to-core mapping options for a parallel application on a multicore architecture is computationally very expensive. For the same algorithm, the mapping strategy (MS) with the best response time may change with data size and thread counts. The primary challenge is to design a fast, accurate and automatic framework for exploring these MSs for large data-intensive applications. This is to ensure that the users can explore the design space within reasonable machine hours, without thorough understanding on how the code interacts with the platform. Response time is related to the cycles per instructions retired (CPI), taking into account both active and sleep states of the pipeline. This work establishes a hybrid approach, based on Markov Chain Model (MCM) and Model Tree (MT) for system-level steady state CPI prediction. It is designed for shared memory multicore processors with coarse-grained multithreading. The thread status is represented by the MCM states. The program characteristics are modeled as the transition probabilities, representing the system moving between active and suspended thread states. The MT model extrapolates these probabilities for the actual application size (AS) from the smaller AS performance. This aspect of the framework, along with, the use of mathematical expressions for the actual AS performance information, results in a tremendous reduction in the CPI prediction time. The framework is validated using an electromagnetics application. The average performance prediction error for steady state CPI results with 12 different MSs is less than 1%. The total run time of model is of the order of minutes, whereas the actual application execution time is in terms of days.

Improve EPA's AIRNow Air Quality Index Maps with NASA/NOAA Satellite Data

NASA Astrophysics Data System (ADS)

Pasch, A.; Zahn, P. H.; DeWinter, J. L.; Haderman, M. D.; White, J. E.; Dickerson, P.; Dye, T. S.; Martin, R. V.

2011-12-01

The U.S. Environmental Protection Agency's (EPA) AIRNow program provides maps of real-time hourly Air Quality Index (AQI) conditions and daily AQI forecasts nationwide (http://www.airnow.gov). The public uses these maps to make decisions concerning their respiratory health. The usefulness of the AIRNow air quality maps depends on the accuracy and spatial coverage of air quality measurements. Currently, the maps use only ground-based measurements, which have significant gaps in coverage in some parts of the United States. As a result, contoured AQI levels have high uncertainty in regions far from monitors. To improve the usefulness of air quality maps, scientists at EPA and Sonoma Technology, Inc. are working in collaboration with the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and university researchers on a project to incorporate additional measurements into the maps via the AIRNow Satellite Data Processor (ASDP). These measurements include estimated surface PM

A hadoop-based method to predict potential effective drug combination.

PubMed

Sun, Yifan; Xiong, Yi; Xu, Qian; Wei, Dongqing

2014-01-01

Combination drugs that impact multiple targets simultaneously are promising candidates for combating complex diseases due to their improved efficacy and reduced side effects. However, exhaustive screening of all possible drug combinations is extremely time-consuming and impractical. Here, we present a novel Hadoop-based approach to predict drug combinations by taking advantage of the MapReduce programming model, which leads to an improvement of scalability of the prediction algorithm. By integrating the gene expression data of multiple drugs, we constructed data preprocessing and the support vector machines and naïve Bayesian classifiers on Hadoop for prediction of drug combinations. The experimental results suggest that our Hadoop-based model achieves much higher efficiency in the big data processing steps with satisfactory performance. We believed that our proposed approach can help accelerate the prediction of potential effective drugs with the increasing of the combination number at an exponential rate in future. The source code and datasets are available upon request.

A Hadoop-Based Method to Predict Potential Effective Drug Combination

PubMed Central

Xiong, Yi; Xu, Qian; Wei, Dongqing

2014-01-01

Combination drugs that impact multiple targets simultaneously are promising candidates for combating complex diseases due to their improved efficacy and reduced side effects. However, exhaustive screening of all possible drug combinations is extremely time-consuming and impractical. Here, we present a novel Hadoop-based approach to predict drug combinations by taking advantage of the MapReduce programming model, which leads to an improvement of scalability of the prediction algorithm. By integrating the gene expression data of multiple drugs, we constructed data preprocessing and the support vector machines and naïve Bayesian classifiers on Hadoop for prediction of drug combinations. The experimental results suggest that our Hadoop-based model achieves much higher efficiency in the big data processing steps with satisfactory performance. We believed that our proposed approach can help accelerate the prediction of potential effective drugs with the increasing of the combination number at an exponential rate in future. The source code and datasets are available upon request. PMID:25147789

Analysis of factors influencing hydration site prediction based on molecular dynamics simulations.

PubMed

Yang, Ying; Hu, Bingjie; Lill, Markus A

2014-10-27

Water contributes significantly to the binding of small molecules to proteins in biochemical systems. Molecular dynamics (MD) simulation based programs such as WaterMap and WATsite have been used to probe the locations and thermodynamic properties of hydration sites at the surface or in the binding site of proteins generating important information for structure-based drug design. However, questions associated with the influence of the simulation protocol on hydration site analysis remain. In this study, we use WATsite to investigate the influence of factors such as simulation length and variations in initial protein conformations on hydration site prediction. We find that 4 ns MD simulation is appropriate to obtain a reliable prediction of the locations and thermodynamic properties of hydration sites. In addition, hydration site prediction can be largely affected by the initial protein conformations used for MD simulations. Here, we provide a first quantification of this effect and further indicate that similar conformations of binding site residues (RMSD < 0.5 Å) are required to obtain consistent hydration site predictions.

Special Focus

PubMed Central

Nawrocki, Eric P.; Burge, Sarah W.

2013-01-01

The development of RNA bioinformatic tools began more than 30 y ago with the description of the Nussinov and Zuker dynamic programming algorithms for single sequence RNA secondary structure prediction. Since then, many tools have been developed for various RNA sequence analysis problems such as homology search, multiple sequence alignment, de novo RNA discovery, read-mapping, and many more. In this issue, we have collected a sampling of reviews and original research that demonstrate some of the many ways bioinformatics is integrated with current RNA biology research. PMID:23948768

LLMapReduce: Multi-Lingual Map-Reduce for Supercomputing Environments

DTIC Science & Technology

2015-11-20

1990s. Popularized by Google [36] and Apache Hadoop [37], map-reduce has become a staple technology of the ever- growing big data community...Lexington, MA, U.S.A Abstract— The map-reduce parallel programming model has become extremely popular in the big data community. Many big data ...to big data users running on a supercomputer. LLMapReduce dramatically simplifies map-reduce programming by providing simple parallel programming

How well should probabilistic seismic hazard maps work?

NASA Astrophysics Data System (ADS)

Vanneste, K.; Stein, S.; Camelbeeck, T.; Vleminckx, B.

2016-12-01

Recent large earthquakes that gave rise to shaking much stronger than shown in earthquake hazard maps have stimulated discussion about how well these maps forecast future shaking. These discussions have brought home the fact that although the maps are designed to achieve certain goals, we know little about how well they actually perform. As for any other forecast, this question involves verification and validation. Verification involves assessing how well the algorithm used to produce hazard maps implements the conceptual PSHA model ("have we built the model right?"). Validation asks how well the model forecasts the shaking that actually occurs ("have we built the right model?"). We explore the verification issue by simulating the shaking history of an area with assumed distribution of earthquakes, frequency-magnitude relation, temporal occurrence model, and ground-motion prediction equation. We compare the "observed" shaking at many sites over time to that predicted by a hazard map generated for the same set of parameters. PSHA predicts that the fraction of sites at which shaking will exceed that mapped is p = 1 - exp(t/T), where t is the duration of observations and T is the map's return period. This implies that shaking in large earthquakes is typically greater than shown on hazard maps, as has occurred in a number of cases. A large number of simulated earthquake histories yield distributions of shaking consistent with this forecast, with a scatter about this value that decreases as t/T increases. The median results are somewhat lower than predicted for small values of t/T and approach the predicted value for larger values of t/T. Hence, the algorithm appears to be internally consistent and can be regarded as verified for this set of simulations. Validation is more complicated because a real observed earthquake history can yield a fractional exceedance significantly higher or lower than that predicted while still being consistent with the hazard map in question. As a result, given that in the real world we have only a single sample, it is hard to assess whether a misfit between a map and observations arises by chance or reflects a biased map.

Importance of Integrating High-Resoultion 2D Flood Hazard Maps in the Flood Disaster Management of Marikina City, Philippines

NASA Astrophysics Data System (ADS)

Tapales, Ben Joseph; Mendoza, Jerico; Uichanco, Christopher; Mahar Francisco Amante Lagmay, Alfredo; Moises, Mark Anthony; Delmendo, Patricia; Eneri Tingin, Neil

2015-04-01

Flooding has been a perennial problem in the city of Marikina. These incidences result in human and economic losses. In response to this, the city has been investing in their flood disaster mitigation program in the past years. As a result, flooding in Marikina was reduced by 31% from 1992 to 2004. [1] However, these measures need to be improved so as to mitigate the effects of floods with more than 100 year return period, such as the flooding brought by tropical storm Ketsana in 2009 which generated 455mm of rains over a 24-hour period. Heavy rainfall caused the streets to be completely submerged in water, leaving at least 70 people dead in the area. In 2012, the Southwest monsoon, enhanced by a typhoon, brought massive rains with an accumulated rainfall of 472mm for 22-hours, a number greater than that which was experienced during Ketsana. At this time, the local government units were much more prepared in mitigating the risk with the use of early warning and evacuation measures, resulting to zero casualty in the area. Their urban disaster management program, however, can be further improved through the integration of high-resolution 2D flood hazard maps in the city's flood disaster management. The use of these maps in flood disaster management is essential in reducing flood-related risks. This paper discusses the importance and advantages of integrating flood maps in structural and non-structural mitigation measures in the case of Marikina City. Flood hazard maps are essential tools in predicting the frequency and magnitude of floods in an area. An information that may be determined with the use of these maps is the locations of evacuation areas, which may be accurately positioned using high-resolution 2D flood hazard maps. Evacuation of people in areas that are not vulnerable of being inundated is one of the unnecessary measures that may be prevented and thus optimizing mitigation efforts by local government units. This paper also discusses proposals for a more efficient exchange of information, allowing for flood simulations to be utilized in local flood disaster management programs. The success of these systems relies heavily on the knowledge of the people involved. As environmental changes create more significant impacts, the need to adapt to these is vital for man's safety. [1] Pacific Disaster Center

Importance of Integrating High-Resoultion 2D Flood Hazard Maps in the Flood Disaster Management of Marikina City, Philippines

NASA Astrophysics Data System (ADS)

Tapales, B. J. M.; Mendoza, J.; Uichanco, C.; Lagmay, A. M. F. A.; Moises, M. A.; Delmendo, P.; Tingin, N. E.

2014-12-01

Flooding has been a perennial problem in the city of Marikina. These incidences result in human and economic losses. In response to this, the city has been investing in their flood disaster mitigation program in the past years. As a result, flooding in Marikina was reduced by 31% from 1992 to 2004. [1] However, these measures need to be improved so as to mitigate the effects of floods with more than 100 year return period, such as the flooding brought by tropical storm Ketsana in 2009 which generated 455mm of rains over a 24-hour period. Heavy rainfall caused the streets to be completely submerged in water, leaving at least 70 people dead in the area. In 2012, the Southwest monsoon, enhanced by a typhoon, brought massive rains with an accumulated rainfall of 472mm for 22-hours, a number greater than that which was experienced during Ketsana. At this time, the local government units were much more prepared in mitigating the risk with the use of early warning and evacuation measures, resulting to zero casualty in the area. Their urban disaster management program, however, can be further improved through the integration of high-resolution 2D flood hazard maps in the city's flood disaster management. The use of these maps in flood disaster management is essential in reducing flood-related risks. This paper discusses the importance and advantages of integrating flood maps in structural and non-structural mitigation measures in the case of Marikina City. Flood hazard maps are essential tools in predicting the frequency and magnitude of floods in an area. An information that may be determined with the use of these maps is the locations of evacuation areas, which may be accurately positioned using high-resolution 2D flood hazard maps. Evacuation of areas that are not vulnerable of being inundated is one of the unnecessary measures that may be prevented and thus optimizing mitigation efforts by local government units. This paper also discusses proposals for a more efficient exchange of information, allowing for flood simulations to be utilized in local flood disaster management programs. The success of these systems relies heavily on the knowledge of the people involved. As environmental changes create more significant impacts, the need to adapt to these is vital for man's safety. [1] Pacific Disaster Center

Alaska Interim Land Cover Mapping Program; final report

USGS Publications Warehouse

Fitzpatrick-Lins, Katherine; Doughty, E.F.; Shasby, Mark; Benjamin, Susan

1989-01-01

In 1985, the U.S. Geological Survey initiated a research project to develop an interim land cover data base for Alaska as an alternative to the nationwide Land Use and Land Cover Mapping Program. The Alaska Interim Land Cover Mapping Program was subsequently created to develop methods for producing a series of land cover maps that utilized the existing Landsat digital land cover classifications produced by and for the major land management agencies for mapping the vegetation of Alaska. The program was successful in producing digital land cover classifications and statistical summaries using a common statewide classification and in reformatting these data to produce l:250,000-scale quadrangle-based maps directly from the Scitex laser plotter. A Federal and State agency review of these products found considerable user support for the maps. Presently the Geological Survey is committed to digital processing of six to eight quadrangles each year.

The Impact of the Measures of Academic Progress (MAP) Program on Student Reading Achievement

ERIC Educational Resources Information Center

Cordray, David S.; Pion, Georgine M.; Brandt, Chris; Molefe, Ayrin

2013-01-01

One of the most widely used commercially available systems incorporating benchmark assessment and training in differentiated instruction is the Northwest Evaluation Association's (NWEA) Measures of Academic Progress (MAP) program. The MAP program involves two components: (1) computer-adaptive assessments administered to students three to four…

Application of Landsat imagery to problems of petroleum exploration in Qaidam Basin, China

USGS Publications Warehouse

Bailey, G.B.; Anderson, P.D.

1982-01-01

Tertiary and Quaternary nonmarine, petroleum-bearing sedimentary rocks have been extensively deformed by compressive forces. These forces created many folds which are current targets of Chinese exploration programs. Image-derived interpretations of folds, strike-slip faults, thrust faults, normal or reverse faults, and fractures compared very favorably, in terms of locations and numbers mapped, with Chinese data compiled from years of extensive field mapping. Many potential hydrocarbon trapping structures were precisely located. Orientations of major structural trends defined from Landsat imagery correlate well with those predicted for the area based on global tectonic theory. These correlations suggest that similar orientations exist in the eastern half of the basin where folded rocks are mostly obscured by unconsolidated surface sediments and where limited exploration has occurred.--Modified journal abstract.

Automated identification of RNA 3D modules with discriminative power in RNA structural alignments.

PubMed

Theis, Corinna; Höner Zu Siederdissen, Christian; Hofacker, Ivo L; Gorodkin, Jan

2013-12-01

Recent progress in predicting RNA structure is moving towards filling the 'gap' in 2D RNA structure prediction where, for example, predicted internal loops often form non-canonical base pairs. This is increasingly recognized with the steady increase of known RNA 3D modules. There is a general interest in matching structural modules known from one molecule to other molecules for which the 3D structure is not known yet. We have created a pipeline, metaRNAmodules, which completely automates extracting putative modules from the FR3D database and mapping of such modules to Rfam alignments to obtain comparative evidence. Subsequently, the modules, initially represented by a graph, are turned into models for the RMDetect program, which allows to test their discriminative power using real and randomized Rfam alignments. An initial extraction of 22 495 3D modules in all PDB files results in 977 internal loop and 17 hairpin modules with clear discriminatory power. Many of these modules describe only minor variants of each other. Indeed, mapping of the modules onto Rfam families results in 35 unique locations in 11 different families. The metaRNAmodules pipeline source for the internal loop modules is available at http://rth.dk/resources/mrm.

Regional mapping of soil parent material by machine learning based on point data

NASA Astrophysics Data System (ADS)

Lacoste, Marine; Lemercier, Blandine; Walter, Christian

2011-10-01

A machine learning system (MART) has been used to predict soil parent material (SPM) at the regional scale with a 50-m resolution. The use of point-specific soil observations as training data was tested as a replacement for the soil maps introduced in previous studies, with the aim of generating a more even distribution of training data over the study area and reducing information uncertainty. The 27,020-km 2 study area (Brittany, northwestern France) contains mainly metamorphic, igneous and sedimentary substrates. However, superficial deposits (aeolian loam, colluvial and alluvial deposits) very often represent the actual SPM and are typically under-represented in existing geological maps. In order to calibrate the predictive model, a total of 4920 point soil descriptions were used as training data along with 17 environmental predictors (terrain attributes derived from a 50-m DEM, as well as emissions of K, Th and U obtained by means of airborne gamma-ray spectrometry, geological variables at the 1:250,000 scale and land use maps obtained by remote sensing). Model predictions were then compared: i) during SPM model creation to point data not used in model calibration (internal validation), ii) to the entire point dataset (point validation), and iii) to existing detailed soil maps (external validation). The internal, point and external validation accuracy rates were 56%, 81% and 54%, respectively. Aeolian loam was one of the three most closely predicted substrates. Poor prediction results were associated with uncommon materials and areas with high geological complexity, i.e. areas where existing maps used for external validation were also imprecise. The resultant predictive map turned out to be more accurate than existing geological maps and moreover indicated surface deposits whose spatial coverage is consistent with actual knowledge of the area. This method proves quite useful in predicting SPM within areas where conventional mapping techniques might be too costly or lengthy or where soil maps are insufficient for use as training data. In addition, this method allows producing repeatable and interpretable results, whose accuracy can be assessed objectively.

Geostatistical Model-Based Estimates of Schistosomiasis Prevalence among Individuals Aged ≤20 Years in West Africa

PubMed Central

Schur, Nadine; Hürlimann, Eveline; Garba, Amadou; Traoré, Mamadou S.; Ndir, Omar; Ratard, Raoult C.; Tchuem Tchuenté, Louis-Albert; Kristensen, Thomas K.; Utzinger, Jürg; Vounatsou, Penelope

2011-01-01

Background Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps. Methodology We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging. Principal Findings Our models revealed that 50.8 million individuals aged ≤20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection. Conclusion/Significance We present the first empirical estimates for S. mansoni and S. haematobium prevalence at high spatial resolution throughout West Africa. Our prediction maps allow prioritizing of interventions in a spatially explicit manner, and will be useful for monitoring and evaluation of schistosomiasis control programs. PMID:21695107

USGS EDMAP Program-Training the Next Generation of Geologic Mappers

USGS Publications Warehouse

,

2010-01-01

EDMAP is an interactive and meaningful program for university students to gain experience and knowledge in geologic mapping while contributing to national efforts to map the geology of the United States. It is a matching-funds grant program with universities and is one of the three components of the congressionally mandated U.S. Geological Survey (USGS) National Cooperative Geologic Mapping Program. Geology professors whose specialty is geologic mapping request EDMAP funding to support upper-level undergraduate and graduate students at their colleges or universities in a 1-year mentor-guided geologic mapping project that focuses on a specific geographic area. Every Federal dollar that is awarded is matched with university funds.

Integrating genomics and proteomics data to predict drug effects using binary linear programming.

PubMed

Ji, Zhiwei; Su, Jing; Liu, Chenglin; Wang, Hongyan; Huang, Deshuang; Zhou, Xiaobo

2014-01-01

The Library of Integrated Network-Based Cellular Signatures (LINCS) project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound's effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound's effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin) according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors) inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational model can be used to elucidate potential mechanisms of a compound's efficacy.

Identification of residue pairing in interacting β-strands from a predicted residue contact map.

PubMed

Mao, Wenzhi; Wang, Tong; Zhang, Wenxuan; Gong, Haipeng

2018-04-19

Despite the rapid progress of protein residue contact prediction, predicted residue contact maps frequently contain many errors. However, information of residue pairing in β strands could be extracted from a noisy contact map, due to the presence of characteristic contact patterns in β-β interactions. This information may benefit the tertiary structure prediction of mainly β proteins. In this work, we propose a novel ridge-detection-based β-β contact predictor to identify residue pairing in β strands from any predicted residue contact map. Our algorithm RDb 2 C adopts ridge detection, a well-developed technique in computer image processing, to capture consecutive residue contacts, and then utilizes a novel multi-stage random forest framework to integrate the ridge information and additional features for prediction. Starting from the predicted contact map of CCMpred, RDb 2 C remarkably outperforms all state-of-the-art methods on two conventional test sets of β proteins (BetaSheet916 and BetaSheet1452), and achieves F1-scores of ~ 62% and ~ 76% at the residue level and strand level, respectively. Taking the prediction of the more advanced RaptorX-Contact as input, RDb 2 C achieves impressively higher performance, with F1-scores reaching ~ 76% and ~ 86% at the residue level and strand level, respectively. In a test of structural modeling using the top 1 L predicted contacts as constraints, for 61 mainly β proteins, the average TM-score achieves 0.442 when using the raw RaptorX-Contact prediction, but increases to 0.506 when using the improved prediction by RDb 2 C. Our method can significantly improve the prediction of β-β contacts from any predicted residue contact maps. Prediction results of our algorithm could be directly applied to effectively facilitate the practical structure prediction of mainly β proteins. All source data and codes are available at http://166.111.152.91/Downloads.html or the GitHub address of https://github.com/wzmao/RDb2C .

Group-regularized individual prediction: theory and application to pain.

PubMed

Lindquist, Martin A; Krishnan, Anjali; López-Solà, Marina; Jepma, Marieke; Woo, Choong-Wan; Koban, Leonie; Roy, Mathieu; Atlas, Lauren Y; Schmidt, Liane; Chang, Luke J; Reynolds Losin, Elizabeth A; Eisenbarth, Hedwig; Ashar, Yoni K; Delk, Elizabeth; Wager, Tor D

2017-01-15

Multivariate pattern analysis (MVPA) has become an important tool for identifying brain representations of psychological processes and clinical outcomes using fMRI and related methods. Such methods can be used to predict or 'decode' psychological states in individual subjects. Single-subject MVPA approaches, however, are limited by the amount and quality of individual-subject data. In spite of higher spatial resolution, predictive accuracy from single-subject data often does not exceed what can be accomplished using coarser, group-level maps, because single-subject patterns are trained on limited amounts of often-noisy data. Here, we present a method that combines population-level priors, in the form of biomarker patterns developed on prior samples, with single-subject MVPA maps to improve single-subject prediction. Theoretical results and simulations motivate a weighting based on the relative variances of biomarker-based prediction-based on population-level predictive maps from prior groups-and individual-subject, cross-validated prediction. Empirical results predicting pain using brain activity on a trial-by-trial basis (single-trial prediction) across 6 studies (N=180 participants) confirm the theoretical predictions. Regularization based on a population-level biomarker-in this case, the Neurologic Pain Signature (NPS)-improved single-subject prediction accuracy compared with idiographic maps based on the individuals' data alone. The regularization scheme that we propose, which we term group-regularized individual prediction (GRIP), can be applied broadly to within-person MVPA-based prediction. We also show how GRIP can be used to evaluate data quality and provide benchmarks for the appropriateness of population-level maps like the NPS for a given individual or study. Copyright © 2015 Elsevier Inc. All rights reserved.

Statistics of particle time-temperature histories.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hewson, John C.; Lignell, David O.; Sun, Guangyuan

2014-10-01

Particles in non - isothermal turbulent flow are subject to a stochastic environment tha t produces a distribution of particle time - temperature histories. This distribution is a function of the dispersion of the non - isothermal (continuous) gas phase and the distribution of particles relative to that gas phase. In this work we extend the one - dimensional turbulence (ODT) model to predict the joint dispersion of a dispersed particle phase and a continuous phase. The ODT model predicts the turbulent evolution of continuous scalar fields with a model for the cascade of fluctuations to smaller sc ales (themore » 'triplet map') at a rate that is a function of the fully resolved one - dimens ional velocity field . Stochastic triplet maps also drive Lagrangian particle dispersion with finite Stokes number s including inertial and eddy trajectory - crossing effect s included. Two distinct approaches to this coupling between triplet maps and particle dispersion are developed and implemented along with a hybrid approach. An 'instantaneous' particle displacement model matches the tracer particle limit and provide s an accurate description of particle dispersion. A 'continuous' particle displacement m odel translates triplet maps into a continuous velocity field to which particles respond. Particles can alter the turbulence, and modifications to the stochastic rate expr ession are developed for two - way coupling between particles and the continuous phase. Each aspect of model development is evaluated in canonical flows (homogeneous turbulence, free - shear flows and wall - bounded flows) for which quality measurements are ava ilable. ODT simulations of non - isothermal flows provide statistics for particle heating. These simulations show the significance of accurately predicting the joint statistics of particle and fluid dispersion . Inhomogeneous turbulence coupled with the in fluence of the mean flow fields on particles of varying properties alter s particle dispersion. The joint particle - temperature dispersion leads to a distribution of temperature histories predicted by the ODT . Predictions are shown for the lower moments an d the full distributions of the particle positions, particle - observed gas temperatures and particle temperatures. An analysis of the time scales affecting particle - temperature interactions covers Lagrangian integral time scales based on temperature autoco rrelations, rates of temperature change associated with particle motion relative to the temperature field and rates of diffusional change of temperatures. These latter two time scales have not been investigated previously; they are shown to be strongly in termittent having peaked distributions with long tails. The logarithm of the absolute value of these time scales exhibits a distribution closer to normal. A cknowledgements This work is supported by the Defense Threat Reduction Agency (DTRA) under their Counter - Weapons of Mass Destruction Basic Research Program in the area of Chemical and Biological Agent Defeat under award number HDTRA1 - 11 - 4503I to Sandia National Laboratories. The authors would like to express their appreciation for the guidance provi ded by Dr. Suhithi Peiris to this project and to the Science to Defeat Weapons of Mass Destruction program.« less

Building a base map with AutoCAD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flarity, S.J.

1989-12-01

The fundamental step in the exploration process is building a base map. Consequently, any serious computer exploration program should be capable of providing base maps. Data used in constructing base maps are available from commercial sources such as Tobin. and Petroleum Information. These data sets include line and well data, the line data being latitude longitude vectors, and the ell data any identifying text information for well and their locations. AutoCAD is a commercial program useful in building base maps. Its features include infinite zoom and pan capability, layering, block definition, text dialog boxes, and a command language, AutoLisp. AutoLispmore » provides more power by allowing the geologist to modify the way the program works. Three AutoLisp routines presented here allow geologists to construct a geologic base map from raw Tobin data. The first program, WELLS.LSP, sets up the map environment for the subsequent programs, WELLADD.LSP and LINEADD.LSP. Welladd.lisp reads the Tobin data and spots the well symbols and the identifying information. Lineadd.lsp performs the same task on line and textural information contained within the data set.« less

The Dokuchaev hypothesis as a basis for predictive digital soil mapping (on the 125th anniversary of its publication)

NASA Astrophysics Data System (ADS)

Florinsky, I. V.

2012-04-01

Predictive digital soil mapping is widely used in soil science. Its objective is the prediction of the spatial distribution of soil taxonomic units and quantitative soil properties via the analysis of spatially distributed quantitative characteristics of soil-forming factors. Western pedometrists stress the scientific priority and principal importance of Hans Jenny's book (1941) for the emergence and development of predictive soil mapping. In this paper, we demonstrate that Vasily Dokuchaev explicitly defined the central idea and statement of the problem of contemporary predictive soil mapping in the year 1886. Then, we reconstruct the history of the soil formation equation from 1899 to 1941. We argue that Jenny adopted the soil formation equation from Sergey Zakharov, who published it in a well-known fundamental textbook in 1927. It is encouraging that this issue was clarified in 2011, the anniversary year for publications of Dokuchaev and Jenny.

RECENT DEVELOPMENTS IN THE U. S. GEOLOGICAL SURVEY'S LANDSAT IMAGE MAPPING PROGRAM.

USGS Publications Warehouse

Brownworth, Frederick S.; Rohde, Wayne G.

1986-01-01

At the 1984 ASPRS-ACSM Convention in Washington, D. C. a paper on 'The Emerging U. S. Geological Survey Image Mapping Program' was presented that discussed recent satellite image mapping advancements and published products. Since then Landsat image mapping has become an integral part of the National Mapping Program. The Survey currently produces about 20 Landsat multispectral scanner (MSS) and Thematic Mapper (TM) image map products annually at 1:250,000 and 1:100,000 scales, respectively. These Landsat image maps provide users with a regional or synoptic view of an area. The resultant geographical presentation of the terrain and cultural features will help planners and managers make better decisions regarding the use of our national resources.

Migrant Action Program. Annual Report, 1972.

ERIC Educational Resources Information Center

Migrant Action Program, Mason City, IA.

The philosophy behind and the operations of the Iowa Migrant Action Program (MAP) are discussed in this 1972 annual report. In developing its programs, MAP emphasizes self-determination as a key factor in redirecting the migrant to a life style different from the one he has known. MAP's various projects are intended to economically upgrade the…

75 FR 42762 - Agency Information Collection Activities: Proposed Collection; Comment Request, OMB No. 1660-0015...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-22

... Amendments to National Flood Insurance Program Maps (Spanish). SUMMARY: The Federal Emergency Management... Insurance Program Maps (Spanish). Abstract: This collection of information allows owners of structures that... National Flood Insurance Program Maps (Spanish)/ FEMA Form 086-0-22A. Subtotal 18,775 18,775 22,530 659,228...

75 FR 24723 - Agency Information Collection Activities: Proposed Collection; Comment Request, 1660-0037...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-05

... Insurance Program Maps (Spanish). SUMMARY: The Federal Emergency Management Agency, as part of its... Flood Insurance Program Maps (Spanish). Abstract: FEMA Forms 086-0-22 and 086-0-22A are designed to...,389 Single Residential Lot or Structure Amendments to National Flood Insurance Program Maps (Spanish...

Mapping for prevention: GIS models for directing childhood lead poisoning prevention programs.

PubMed Central

Miranda, Marie Lynn; Dolinoy, Dana C; Overstreet, M Alicia

2002-01-01

Environmental threats to children's health--especially low-level lead exposure--are complex and multifaceted; consequently, mitigation of these threats has proven costly and insufficient and has produced economic and racial disparities in exposure among populations. Policy makers, public health officials, child advocates, and others currently lack the appropriate infrastructure to evaluate children's risk and exposure potential across a broad range of risks. Unable to identify where the highest risk of exposure occurs, children's environmental health programs remain mitigative instead of preventive. In this article we use geographic information system spatial analysis of data from blood lead screening, county tax assessors, and the U.S. Census to predict statistically based lead exposure risk levels mapped at the individual tax parcel unit in six counties in North Carolina. The resulting model uses weighted risk factors to spatially locate modeled exposure zones, thus highlighting critical areas for targeted intervention. The methods presented here hold promise for application and extension to the other 94 North Carolina counties and nationally, as well as to other environmental health risks. PMID:12204831

Community Resilience Informed by Science and Experience (C-RISE)

NASA Astrophysics Data System (ADS)

Young Morse, R.; Peake, L.; Bowness, G.

2017-12-01

The Gulf of Maine Research Institute is developing an interactive learning experience that engages participants in the interdependence of humans and the environment, the cycles of observation and experiment that advance science knowledge, and the changes we see now and that are predicted for sea level and storm frequency. These scientific concepts and principles will be brought to human scale through the connection to the challenge of city planning in our harbor communities. We are leveraging the ESRI Story Maps platform to build rich visualization-based narratives that feature NOAA maps, data and tools. Our program participants work in teams to navigate the content and participate in facilitated group discussions led by our educators. Based on the adult learning experience and in concert with new content being developed for the LabVenture program around the theme of Climate Change, we will develop a learning experience for 5th and 6th graders.Our goal is to immerse 1000+ adults from target communities in Greater Portland region as well as 8000+ middle school students from throughout the state in the experience.

Development of a Mapped Diabetes Community Program Guide for a Safety Net Population

PubMed Central

Zallman, Leah; Ibekwe, Lynn; Thompson, Jennifer W.; Ross-Degnan, Dennis; Oken, Emily

2014-01-01

Purpose Enhancing linkages between patients and community programs is increasingly recognized as a method for improving physical activity, nutrition and weight management. Although interactive mapped community program guides may be beneficial, there remains a dearth of articles that describe the processes and practicalities of creating such guides. This article describes the development of an interactive, web-based mapped community program guide at a safety net institution and the lessons learned from that process. Conclusions This project demonstrated the feasibility of creating two maps – a program guide and a population health map. It also revealed some key challenges and lessons for future work in this area, particularly within safety-net institutions. Our work underscores the need for developing partnerships outside of the health care system and the importance of employing community-based participatory methods. In addition to facilitating improvements in individual wellness, mapping community programs also has the potential to improve population health management by healthcare delivery systems such as hospitals, health centers, or public health systems, including city and state departments of health. PMID:24752180

Cortical Auditory Evoked Potentials Recorded From Nucleus Hybrid Cochlear Implant Users.

PubMed

Brown, Carolyn J; Jeon, Eun Kyung; Chiou, Li-Kuei; Kirby, Benjamin; Karsten, Sue A; Turner, Christopher W; Abbas, Paul J

2015-01-01

Nucleus Hybrid Cochlear Implant (CI) users hear low-frequency sounds via acoustic stimulation and high-frequency sounds via electrical stimulation. This within-subject study compares three different methods of coordinating programming of the acoustic and electrical components of the Hybrid device. Speech perception and cortical auditory evoked potentials (CAEP) were used to assess differences in outcome. The goals of this study were to determine whether (1) the evoked potential measures could predict which programming strategy resulted in better outcome on the speech perception task or was preferred by the listener, and (2) CAEPs could be used to predict which subjects benefitted most from having access to the electrical signal provided by the Hybrid implant. CAEPs were recorded from 10 Nucleus Hybrid CI users. Study participants were tested using three different experimental processor programs (MAPs) that differed in terms of how much overlap there was between the range of frequencies processed by the acoustic component of the Hybrid device and range of frequencies processed by the electrical component. The study design included allowing participants to acclimatize for a period of up to 4 weeks with each experimental program prior to speech perception and evoked potential testing. Performance using the experimental MAPs was assessed using both a closed-set consonant recognition task and an adaptive test that measured the signal-to-noise ratio that resulted in 50% correct identification of a set of 12 spondees presented in background noise. Long-duration, synthetic vowels were used to record both the cortical P1-N1-P2 "onset" response and the auditory "change" response (also known as the auditory change complex [ACC]). Correlations between the evoked potential measures and performance on the speech perception tasks are reported. Differences in performance using the three programming strategies were not large. Peak-to-peak amplitude of the ACC was not found to be sensitive enough to accurately predict the programming strategy that resulted in the best performance on either measure of speech perception. All 10 Hybrid CI users had residual low-frequency acoustic hearing. For all 10 subjects, allowing them to use both the acoustic and electrical signals provided by the implant improved performance on the consonant recognition task. For most subjects, it also resulted in slightly larger cortical change responses. However, the impact that listening mode had on the cortical change responses was small, and again, the correlation between the evoked potential and speech perception results was not significant. CAEPs can be successfully measured from Hybrid CI users. The responses that are recorded are similar to those recorded from normal-hearing listeners. The goal of this study was to see if CAEPs might play a role either in identifying the experimental program that resulted in best performance on a consonant recognition task or in documenting benefit from the use of the electrical signal provided by the Hybrid CI. At least for the stimuli and specific methods used in this study, no such predictive relationship was found.

Evaluating Gridded Spring Indices Using the USA National Phenology Network's Observational Phenology Data

NASA Astrophysics Data System (ADS)

Crimmins, T. M.; Gerst, K.

2017-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) produces and freely delivers daily and short-term forecast maps of spring onset dates at fine spatial scale for the conterminous United States and Alaska using the Spring Indices. These models, which represent the start of biological activity in the spring season, were developed using a long-term observational record of four species of lilacs and honeysuckles contributed by volunteer observers. Three of the four species continue to be tracked through the USA-NPN's phenology observation program, Nature's Notebook. The gridded Spring Index maps have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, anticipating allergy outbreaks and planning agricultural harvest dates. However, to date, there has not been a comprehensive assessment of how well the gridded Spring Index maps accurately reflect phenological activity in lilacs and honeysuckles or other species of plants. In this study, we used observational plant phenology data maintained by the USA-NPN to evaluate how well the gridded Spring Index maps match leaf and flowering onset dates in a) the lilac and honeysuckle species used to construct the models and b) in several species of deciduous trees. The Spring Index performed strongly at predicting the timing of leaf-out and flowering in lilacs and honeysuckles. The average error between predicted and observed date of onset ranged from 5.9 to 11.4 days. Flowering models performed slightly better than leaf-out models. The degree to which the Spring Indices predicted native deciduous tree leaf and flower phenology varied by year, species, and region. Generally, the models were better predictors of leaf and flowering onset dates in the Northeastern and Midwestern US. These results reveal when and where the Spring Indices are a meaningful proxy of phenological activity across the United States.

Bulk tank milk prevalence and production losses, spatial analysis, and predictive risk mapping of Ostertagia ostertagi infections in Mexican cattle herds.

PubMed

Villa-Mancera, Abel; Pastelín-Rojas, César; Olivares-Pérez, Jaime; Córdova-Izquierdo, Alejandro; Reynoso-Palomar, Alejandro

2018-05-01

This study investigated the prevalence, production losses, spatial clustering, and predictive risk mapping in different climate zones in five states of Mexico. The bulk tank milk samples obtained between January and April 2015 were analyzed for antibodies against Ostertagia ostertagi using the Svanovir ELISA. A total of 1204 farm owners or managers answered the questionnaire. The overall herd prevalence and mean optical density ratio (ODR) of parasite were 61.96% and 0.55, respectively. Overall, the production loss was approximately 0.542 kg of milk per parasited cow per day (mean ODR = 0.92, 142 farms, 11.79%). The spatial disease cluster analysis using SatScan software indicated that two high-risk clusters were observed. In the multivariable analysis, three models were tested for potential association with the ELISA results supported by climatic, environmental, and management factors. The final logistic regression model based on both climatic/environmental and management variables included the factors rainfall, elevation, land surface temperature (LST) day, and parasite control program that were significantly associated with an increased risk of infection. Geostatistical kriging was applied to generate a risk map for the presence of parasite in dairy cattle herds in Mexico. The results indicate that climatic and meteorological factors had a higher potential impact on the spatial distribution of O. ostertagi than the management factors.

Effects of urban microcellular environments on ray-tracing-based coverage predictions.

PubMed

Liu, Zhongyu; Guo, Lixin; Guan, Xiaowei; Sun, Jiejing

2016-09-01

The ray-tracing (RT) algorithm, which is based on geometrical optics and the uniform theory of diffraction, has become a typical deterministic approach of studying wave-propagation characteristics. Under urban microcellular environments, the RT method highly depends on detailed environmental information. The aim of this paper is to provide help in selecting the appropriate level of accuracy required in building databases to achieve good tradeoffs between database costs and prediction accuracy. After familiarization with the operating procedures of the RT-based prediction model, this study focuses on the effect of errors in environmental information on prediction results. The environmental information consists of two parts, namely, geometric and electrical parameters. The geometric information can be obtained from a digital map of a city. To study the effects of inaccuracies in geometry information (building layout) on RT-based coverage prediction, two different artificial erroneous maps are generated based on the original digital map, and systematic analysis is performed by comparing the predictions with the erroneous maps and measurements or the predictions with the original digital map. To make the conclusion more persuasive, the influence of random errors on RMS delay spread results is investigated. Furthermore, given the electrical parameters' effect on the accuracy of the predicted results of the RT model, the dielectric constant and conductivity of building materials are set with different values. The path loss and RMS delay spread under the same circumstances are simulated by the RT prediction model.

An Agent-based Model for Groundwater Allocation and Management at the Bakken Shale in Western North Dakota

NASA Astrophysics Data System (ADS)

Lin, T.; Lin, Z.; Lim, S.

2017-12-01

We present an integrated modeling framework to simulate groundwater level change under the dramatic increase of hydraulic fracturing water use in the Bakken Shale oil production area. The framework combines the agent-based model (ABM) with the Fox Hills-Hell Creek (FH-HC) groundwater model. In development of the ABM, institution theory is used to model the regulation policies from the North Dakota State Water Commission, while evolutionary programming and cognitive maps are used to model the social structure that emerges from the behavior of competing individual water businesses. Evolutionary programming allows individuals to select an appropriate strategy when annually applying for potential water use permits; whereas cognitive maps endow agent's ability and willingness to compete for more water sales. All agents have their own influence boundaries that inhibit their competitive behavior toward their neighbors but not to non-neighbors. The decision-making process is constructed and parameterized with both quantitative and qualitative information, i.e., empirical water use data and knowledge gained from surveys with stakeholders. By linking institution theory, evolutionary programming, and cognitive maps, our approach addresses a higher complexity of the real decision making process. Furthermore, this approach is a new exploration for modeling the dynamics of Coupled Human and Natural System. After integrating ABM with the FH-HC model, drought and limited water accessibility scenarios are simulated to predict FH-HC ground water level changes in the future. The integrated modeling framework of ABM and FH-HC model can be used to support making scientifically sound policies in water allocation and management.

Predicting chromosomal locations of genetically mapped loci in maize using the Morgan2McClintock Translator.

PubMed

Lawrence, Carolyn J; Seigfried, Trent E; Bass, Hank W; Anderson, Lorinda K

2006-03-01

The Morgan2McClintock Translator permits prediction of meiotic pachytene chromosome map positions from recombination-based linkage data using recombination nodule frequency distributions. Its outputs permit estimation of DNA content between mapped loci and help to create an integrated overview of the maize nuclear genome structure.

NASA Applied Sciences Disasters Program Support for the September 2017 Mexico Earthquakes

NASA Astrophysics Data System (ADS)

Glasscoe, M. T.; Kirschbaum, D.; Torres-Perez, J. L.; Yun, S. H.; Owen, S. E.; Hua, H.; Fielding, E. J.; Liang, C.; Bekaert, D. P.; Osmanoglu, B.; Amini, R.; Green, D. S.; Murray, J. J.; Stough, T.; Struve, J. C.; Seepersad, J.; Thompson, V.

2017-12-01

The 8 September M 8.1 Tehuantepec and 19 September M 7.1 Puebla earthquakes were among the largest earthquakes recorded in Mexico. These two events caused widespread damage, affecting several million people and causing numerous casualties. A team of event coordinators in the NASA Applied Sciences Program activated soon after these devastating earthquakes in order to support decision makers in Mexico, using NASA modeling and international remote sensing capabilities to generate decision support products to aid in response and recovery. The NASA Disasters Program promotes the use of Earth observations to improve the prediction of, preparation for, response to, and recovery from natural and technological disasters. For these two events, the Disasters Program worked with Mexico's space agency (Agencia Espacial Mexico, AEM) and the National Center for Prevention of Disasters (Centro Nacional de Prevención de Desastres, CENAPRED) to generate products to support response, decision-making, and recovery. Products were also provided to academic partners, technical institutions, and field responders to support response. In addition, the Program partnered with the US Geological Survey (USGS), Office of Foreign Disaster Assistance (OFDA), and other partners in order to provide information to federal and domestic agencies that were supporting event response. Leveraging the expertise of investigators at NASA Centers, products such as landslide susceptibility maps, precipitation models, and radar based damage assessments and surface deformation maps were generated and used by AEM, CENAPRED, and others during the event. These were used by AEM in collaboration with other government agencies in Mexico to make appropriate decisions for mapping damage, rescue and recovery, and informing the population regarding areas prone to potential risk. We will provide an overview of the response activities and data products generated in support of the earthquake response, partnerships with domestic and international partners, and preliminary feedback from end-user partners in Mexico during response efforts following these two earthquakes.

Topsoil organic carbon content of Europe, a new map based on a generalised additive model

NASA Astrophysics Data System (ADS)

de Brogniez, Delphine; Ballabio, Cristiano; Stevens, Antoine; Jones, Robert J. A.; Montanarella, Luca; van Wesemael, Bas

2014-05-01

There is an increasing demand for up-to-date spatially continuous organic carbon (OC) data for global environment and climatic modeling. Whilst the current map of topsoil organic carbon content for Europe (Jones et al., 2005) was produced by applying expert-knowledge based pedo-transfer rules on large soil mapping units, the aim of this study was to replace it by applying digital soil mapping techniques on the first European harmonised geo-referenced topsoil (0-20 cm) database, which arises from the LUCAS (land use/cover area frame statistical survey) survey. A generalized additive model (GAM) was calibrated on 85% of the dataset (ca. 17 000 soil samples) and a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as environmental covariates (500 m resolution). The validation of the model (applied on 15% of the dataset), gave an R2 of 0.27. We observed that most organic soils were under-predicted by the model and that soils of Scandinavia were also poorly predicted. The model showed an RMSE of 42 g kg-1 for mineral soils and of 287 g kg-1 for organic soils. The map of predicted OC content showed the lowest values in Mediterranean countries and in croplands across Europe, whereas highest OC content were predicted in wetlands, woodlands and in mountainous areas. The map of standard error of the OC model predictions showed high values in northern latitudes, wetlands, moors and heathlands, whereas low uncertainty was mostly found in croplands. A comparison of our results with the map of Jones et al. (2005) showed a general agreement on the prediction of mineral soils' OC content, most probably because the models use some common covariates, namely land cover and temperature. Our model however failed to predict values of OC content greater than 200 g kg-1, which we explain by the imposed unimodal distribution of our model, whose mean is tilted towards the majority of soils, which are mineral. Finally, average OC content predictions for each land cover class compared well between models, with our model always showing smaller standard deviations. We concluded that the chosen model and covariates are appropriate for the prediction of OC content in European mineral soils. We presented in this work the first map of topsoil OC content at European scale based on a harmonised soil dataset. The associated uncertainty map shall support the end-users in a careful use of the predictions.

Application of a GIS-/remote sensing-based approach for predicting groundwater potential zones using a multi-criteria data mining methodology.

PubMed

Mogaji, Kehinde Anthony; Lim, Hwee San

2017-07-01

This study integrates the application of Dempster-Shafer-driven evidential belief function (DS-EBF) methodology with remote sensing and geographic information system techniques to analyze surface and subsurface data sets for the spatial prediction of groundwater potential in Perak Province, Malaysia. The study used additional data obtained from the records of the groundwater yield rate of approximately 28 bore well locations. The processed surface and subsurface data produced sets of groundwater potential conditioning factors (GPCFs) from which multiple surface hydrologic and subsurface hydrogeologic parameter thematic maps were generated. The bore well location inventories were partitioned randomly into a ratio of 70% (19 wells) for model training to 30% (9 wells) for model testing. Application results of the DS-EBF relationship model algorithms of the surface- and subsurface-based GPCF thematic maps and the bore well locations produced two groundwater potential prediction (GPP) maps based on surface hydrologic and subsurface hydrogeologic characteristics which established that more than 60% of the study area falling within the moderate-high groundwater potential zones and less than 35% falling within the low potential zones. The estimated uncertainty values within the range of 0 to 17% for the predicted potential zones were quantified using the uncertainty algorithm of the model. The validation results of the GPP maps using relative operating characteristic curve method yielded 80 and 68% success rates and 89 and 53% prediction rates for the subsurface hydrogeologic factor (SUHF)- and surface hydrologic factor (SHF)-based GPP maps, respectively. The study results revealed that the SUHF-based GPP map accurately delineated groundwater potential zones better than the SHF-based GPP map. However, significant information on the low degree of uncertainty of the predicted potential zones established the suitability of the two GPP maps for future development of groundwater resources in the area. The overall results proved the efficacy of the data mining model and the geospatial technology in groundwater potential mapping.

Predictive model of outcome of targeted nodal assessment in colorectal cancer.

PubMed

Nissan, Aviram; Protic, Mladjan; Bilchik, Anton; Eberhardt, John; Peoples, George E; Stojadinovic, Alexander

2010-02-01

Improvement in staging accuracy is the principal aim of targeted nodal assessment in colorectal carcinoma. Technical factors independently predictive of false negative (FN) sentinel lymph node (SLN) mapping should be identified to facilitate operative decision making. To define independent predictors of FN SLN mapping and to develop a predictive model that could support surgical decisions. Data was analyzed from 2 completed prospective clinical trials involving 278 patients with colorectal carcinoma undergoing SLN mapping. Clinical outcome of interest was FN SLN(s), defined as one(s) with no apparent tumor cells in the presence of non-SLN metastases. To assess the independent predictive effect of a covariate for a nominal response (FN SLN), a logistic regression model was constructed and parameters estimated using maximum likelihood. A probabilistic Bayesian model was also trained and cross validated using 10-fold train-and-test sets to predict FN SLN mapping. Area under the curve (AUC) from receiver operating characteristics curves of these predictions was calculated to determine the predictive value of the model. Number of SLNs (<3; P = 0.03) and tumor-replaced nodes (P < 0.01) independently predicted FN SLN. Cross validation of the model created with Bayesian Network Analysis effectively predicted FN SLN (area under the curve = 0.84-0.86). The positive and negative predictive values of the model are 83% and 97%, respectively. This study supports a minimum threshold of 3 nodes for targeted nodal assessment in colorectal cancer, and establishes sufficient basis to conclude that SLN mapping and biopsy cannot be justified in the presence of clinically apparent tumor-replaced nodes.

Application of Data-Driven Evidential Belief Functions to Prospectivity Mapping for Aquamarine-Bearing Pegmatites, Lundazi District, Zambia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carranza, E. J. M., E-mail: carranza@itc.nl; Woldai, T.; Chikambwe, E. M.

A case application of data-driven estimation of evidential belief functions (EBFs) is demonstrated to prospectivity mapping in Lundazi district (eastern Zambia). Spatial data used to represent recognition criteria of prospectivity for aquamarine-bearing pegmatites include mapped granites, mapped faults/fractures, mapped shear zones, and radioelement concentration ratios derived from gridded airborne radiometric data. Data-driven estimates EBFs take into account not only (a) spatial association between an evidential map layer and target deposits but also (b) spatial relationships between classes of evidences in an evidential map layer. Data-driven estimates of EBFs can indicate which spatial data provide positive or negative evidence of prospectivity.more » Data-driven estimates of EBFs of only spatial data providing positive evidence of prospectivity were integrated according to Dempster's rule of combination. Map of integrated degrees of belief was used to delineate zones of relative degress of prospectivity for aquamarine-bearing pegmatites. The predictive map has at least 85% prediction rate and at least 79% success rate of delineating training and validation deposits, respectively. The results illustrate usefulness of data-driven estimation of EBFs in GIS-based predictive mapping of mineral prospectivity. The results also show usefulness of EBFs in managing uncertainties associated with evidential maps.« less

Curriculum Mapping: A Method to Assess and Refine Undergraduate Degree Programs

ERIC Educational Resources Information Center

Joyner-Melito, Helen S.

2016-01-01

Over the past several decades, there has been increasing interest in program- and university-level assessment and aligning learning outcomes to program content. Curriculum mapping is a tool that creates a visual map of all courses in the curriculum and how they relate to curriculum learning outcomes. Assessment tools/activities are often included…

Middle Atmosphere Program. Handbook for MAP, volume 11

NASA Technical Reports Server (NTRS)

Sechrist, C. F., Jr. (Editor)

1984-01-01

An overview is presented of the research activities and objectives of the middle atmosphere program (MAP). Status reports are presented of projects underway in the area of middle atmosphere climatology and atmospheric chemistry condensed minutes of MAP steering committee meetings are contained in this volume. Research recommendations for increased U.S. participation in the middle atmosphere program are given.

Development of an Intervention Map for a Parent Education Intervention to Prevent Violence Among Hispanic Middle School Students.

ERIC Educational Resources Information Center

Murray, Nancy; Kelder, Steve; Parcel, Guy; Orpinas, Pamela

1998-01-01

Describes development of an intervention program for Hispanic parents to reduce violence by increased monitoring of their middle school students. Program development used a five-step guided intervention mapping process. Student surveys and parent interviews provided data to inform program design. Intervention mapping ensured involvement with the…

Using Concept Mapping as as Tool for Program Theory Development

ERIC Educational Resources Information Center

Orsi, Rebecca

2011-01-01

The purpose of this methodological study is to explore how well a process called "concept mapping" (Trochim, 1989) can articulate the theory which underlies a social program. Articulation of a program's theory is a key step in completing a sound theory based evaluation (Weiss, 1997a). In this study, concept mapping is used to…

Crack Growth Prediction Methodology for Multi-Site Damage: Layered Analysis and Growth During Plasticity

NASA Technical Reports Server (NTRS)

James, Mark Anthony

1999-01-01

A finite element program has been developed to perform quasi-static, elastic-plastic crack growth simulations. The model provides a general framework for mixed-mode I/II elastic-plastic fracture analysis using small strain assumptions and plane stress, plane strain, and axisymmetric finite elements. Cracks are modeled explicitly in the mesh. As the cracks propagate, automatic remeshing algorithms delete the mesh local to the crack tip, extend the crack, and build a new mesh around the new tip. State variable mapping algorithms transfer stresses and displacements from the old mesh to the new mesh. The von Mises material model is implemented in the context of a non-linear Newton solution scheme. The fracture criterion is the critical crack tip opening displacement, and crack direction is predicted by the maximum tensile stress criterion at the crack tip. The implementation can accommodate multiple curving and interacting cracks. An additional fracture algorithm based on nodal release can be used to simulate fracture along a horizontal plane of symmetry. A core of plane strain elements can be used with the nodal release algorithm to simulate the triaxial state of stress near the crack tip. Verification and validation studies compare analysis results with experimental data and published three-dimensional analysis results. Fracture predictions using nodal release for compact tension, middle-crack tension, and multi-site damage test specimens produced accurate results for residual strength and link-up loads. Curving crack predictions using remeshing/mapping were compared with experimental data for an Arcan mixed-mode specimen. Loading angles from 0 degrees to 90 degrees were analyzed. The maximum tensile stress criterion was able to predict the crack direction and path for all loading angles in which the material failed in tension. Residual strength was also accurately predicted for these cases.

Wildland resource information system: user's guide

Treesearch

Robert M. Russell; David A. Sharpnack; Elliot L. Amidon

1975-01-01

This user's guide provides detailed information about how to use the computer programs of WRIS, a computer system for storing and manipulating data about land areas. Instructions explain how to prepare maps, digitize by automatic scanners or by hand, produce polygon maps, and combine map layers. Support programs plot maps, store them on tapes, produce summaries,...

USACE National Coastal Mapping Program Update

NASA Astrophysics Data System (ADS)

Sylvester, C.

2017-12-01

The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) formed in 1998 to support the coastal mapping and charting requirements of the USACE, NAVO, NOAA and USGS. This partnership fielded three generations of airborne lidar bathymeters, executed operational data collection programs within the U.S. and overseas, and advanced research and development in airborne lidar bathymetry and complementary technologies. JALBTCX executes a USACE Headquarters-funded National Coastal Mapping Program (NCMP). Initiated in 2004, the NCMP provides high-resolution, high-accuracy elevation and imagery data along the sandy shorelines of the U.S. on a recurring basis. NCMP mapping activities are coordinated with Federal mapping partners through the Interagency Working Group on Ocean and Coastal Mapping and the 3D Elevation Program. The NCMP, currently in it's third cycle, is performing operations along the East Coast in 2017, after having completed surveys along the Gulf Coast in 2016 and conducting emergency response operations in support of Hurricane Matthew. This presentation will provide an overview of JALBTCX, its history in furthering airborne lidar bathymetry technology to meet emerging mapping requirements, current NCMP operations and data products, and Federal mapping coordination activities.

Is there more valuable information in PWI datasets for a voxel-wise acute ischemic stroke tissue outcome prediction than what is represented by typical perfusion maps?

NASA Astrophysics Data System (ADS)

Forkert, Nils Daniel; Siemonsen, Susanne; Dalski, Michael; Verleger, Tobias; Kemmling, Andre; Fiehler, Jens

2014-03-01

The acute ischemic stroke is a leading cause for death and disability in the industry nations. In case of a present acute ischemic stroke, the prediction of the future tissue outcome is of high interest for the clinicians as it can be used to support therapy decision making. Within this context, it has already been shown that the voxel-wise multi-parametric tissue outcome prediction leads to more promising results compared to single channel perfusion map thresholding. Most previously published multi-parametric predictions employ information from perfusion maps derived from perfusion-weighted MRI together with other image sequences such as diffusion-weighted MRI. However, it remains unclear if the typically calculated perfusion maps used for this purpose really include all valuable information from the PWI dataset for an optimal tissue outcome prediction. To investigate this problem in more detail, two different methods to predict tissue outcome using a k-nearest-neighbor approach were developed in this work and evaluated based on 18 datasets of acute stroke patients with known tissue outcome. The first method integrates apparent diffusion coefficient and perfusion parameter (Tmax, MTT, CBV, CBF) information for the voxel-wise prediction, while the second method employs also apparent diffusion coefficient information but the complete perfusion information in terms of the voxel-wise residue functions instead of the perfusion parameter maps for the voxel-wise prediction. Overall, the comparison of the results of the two prediction methods for the 18 patients using a leave-one-out cross validation revealed no considerable differences. Quantitatively, the parameter-based prediction of tissue outcome led to a mean Dice coefficient of 0.474, while the prediction using the residue functions led to a mean Dice coefficient of 0.461. Thus, it may be concluded from the results of this study that the perfusion parameter maps typically derived from PWI datasets include all valuable perfusion information required for a voxel-based tissue outcome prediction, while the complete analysis of the residue functions does not add further benefits for the voxel-wise tissue outcome prediction and is also computationally more expensive.

A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2013-02-01

The purpose of the present study is to compare the prediction performances of three different approaches such as decision tree (DT), support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) for landslide susceptibility mapping at Penang Hill area, Malaysia. The necessary input parameters for the landslide susceptibility assessments were obtained from various sources. At first, landslide locations were identified by aerial photographs and field surveys and a total of 113 landslide locations were constructed. The study area contains 340,608 pixels while total 8403 pixels include landslides. The landslide inventory was randomly partitioned into two subsets: (1) part 1 that contains 50% (4000 landslide grid cells) was used in the training phase of the models; (2) part 2 is a validation dataset 50% (4000 landslide grid cells) for validation of three models and to confirm its accuracy. The digitally processed images of input parameters were combined in GIS. Finally, landslide susceptibility maps were produced, and the performances were assessed and discussed. Total fifteen landslide susceptibility maps were produced using DT, SVM and ANFIS based models, and the resultant maps were validated using the landslide locations. Prediction performances of these maps were checked by receiver operating characteristics (ROC) by using both success rate curve and prediction rate curve. The validation results showed that, area under the ROC curve for the fifteen models produced using DT, SVM and ANFIS varied from 0.8204 to 0.9421 for success rate curve and 0.7580 to 0.8307 for prediction rate curves, respectively. Moreover, the prediction curves revealed that model 5 of DT has slightly higher prediction performance (83.07), whereas the success rate showed that model 5 of ANFIS has better prediction (94.21) capability among all models. The results of this study showed that landslide susceptibility mapping in the Penang Hill area using the three approaches (e.g., DT, SVM and ANFIS) is viable. As far as the performance of the models are concerned, the results appeared to be quite satisfactory, i.e., the zones determined on the map being zones of relative susceptibility.

Comparing the Performance of Japan's Earthquake Hazard Maps to Uniform and Randomized Maps

NASA Astrophysics Data System (ADS)

Brooks, E. M.; Stein, S. A.; Spencer, B. D.

2015-12-01

The devastating 2011 magnitude 9.1 Tohoku earthquake and the resulting shaking and tsunami were much larger than anticipated in earthquake hazard maps. Because this and all other earthquakes that caused ten or more fatalities in Japan since 1979 occurred in places assigned a relatively low hazard, Geller (2011) argued that "all of Japan is at risk from earthquakes, and the present state of seismological science does not allow us to reliably differentiate the risk level in particular geographic areas," so a map showing uniform hazard would be preferable to the existing map. Defenders of the maps countered by arguing that these earthquakes are low-probability events allowed by the maps, which predict the levels of shaking that should expected with a certain probability over a given time. Although such maps are used worldwide in making costly policy decisions for earthquake-resistant construction, how well these maps actually perform is unknown. We explore this hotly-contested issue by comparing how well a 510-year-long record of earthquake shaking in Japan is described by the Japanese national hazard (JNH) maps, uniform maps, and randomized maps. Surprisingly, as measured by the metric implicit in the JNH maps, i.e. that during the chosen time interval the predicted ground motion should be exceeded only at a specific fraction of the sites, both uniform and randomized maps do better than the actual maps. However, using as a metric the squared misfit between maximum observed shaking and that predicted, the JNH maps do better than uniform or randomized maps. These results indicate that the JNH maps are not performing as well as expected, that what factors control map performance is complicated, and that learning more about how maps perform and why would be valuable in making more effective policy.

Predicting disease risk, identifying stakeholders, and informing control strategies: A case study of anthrax in Montana

PubMed Central

Morris, Lillian R.; Blackburn, Jason K.

2018-01-01

Infectious diseases that affect wildlife and livestock are challenging to manage, and can lead to large scale die offs, economic losses, and threats to human health. The management of infectious diseases in wildlife and livestock is made easier with knowledge of disease risk across space and identifying stakeholders associated with high risk landscapes. This study focuses on anthrax, caused by the bacterium Bacillus anthracis, risk to wildlife and livestock in Montana. There is a history of anthrax in Montana, but the spatial extent of disease risk and subsequent wildlife species at risk are not known. Our objective was to predict the potential geographic distribution of anthrax risk across Montana, identify wildlife species at risk and their distributions, and define stakeholders. We used an ecological niche model to predict the potential distribution of anthrax risk. We overlaid susceptible wildlife species distributions and land ownership delineations on our risk map. We found that there was an extensive region across Montana predicted as potential anthrax risk. These potentially risky landscapes overlapped the ranges of all 6 ungulate species considered in the analysis and livestock grazing allotments, and this overlap was on public and private land for all species. Our findings suggest that there is the potential for a multi species anthrax outbreak on multiple landscapes across Montana. Our potential anthrax risk map can be used to prioritize landscapes for surveillance and for implementing livestock vaccination programs. PMID:27169560

Predicting Disease Risk, Identifying Stakeholders, and Informing Control Strategies: A Case Study of Anthrax in Montana.

PubMed

Morris, Lillian R; Blackburn, Jason K

2016-06-01

Infectious diseases that affect wildlife and livestock are challenging to manage and can lead to large-scale die-offs, economic losses, and threats to human health. The management of infectious diseases in wildlife and livestock is made easier with knowledge of disease risk across space and identifying stakeholders associated with high-risk landscapes. This study focuses on anthrax, caused by the bacterium Bacillus anthracis, risk to wildlife and livestock in Montana. There is a history of anthrax in Montana, but the spatial extent of disease risk and subsequent wildlife species at risk are not known. Our objective was to predict the potential geographic distribution of anthrax risk across Montana, identify wildlife species at risk and their distributions, and define stakeholders. We used an ecological niche model to predict the potential distribution of anthrax risk. We overlaid susceptible wildlife species distributions and land ownership delineations on our risk map. We found that there was an extensive region across Montana predicted as potential anthrax risk. These potentially risky landscapes overlapped the ranges of all 6 ungulate species considered in the analysis and livestock grazing allotments, and this overlap was on public and private land for all species. Our findings suggest that there is the potential for a multi-species anthrax outbreak on multiple landscapes across Montana. Our potential anthrax risk map can be used to prioritize landscapes for surveillance and for implementing livestock vaccination programs.

Satellite freeze forecast system: Executive summary

NASA Technical Reports Server (NTRS)

Martsolf, J. D. (Principal Investigator)

1983-01-01

A satellite-based temperature monitoring and prediction system consisting of a computer controlled acquisition, processing, and display system and the ten automated weather stations called by that computer was developed and transferred to the national weather service. This satellite freeze forecasting system (SFFS) acquires satellite data from either one of two sources, surface data from 10 sites, displays the observed data in the form of color-coded thermal maps and in tables of automated weather station temperatures, computes predicted thermal maps when requested and displays such maps either automatically or manually, archives the data acquired, and makes comparisons with historical data. Except for the last function, SFFS handles these tasks in a highly automated fashion if the user so directs. The predicted thermal maps are the result of two models, one a physical energy budget of the soil and atmosphere interface and the other a statistical relationship between the sites at which the physical model predicts temperatures and each of the pixels of the satellite thermal map.

Insights into earthquake hazard map performance from shaking history simulations

NASA Astrophysics Data System (ADS)

Stein, S.; Vanneste, K.; Camelbeeck, T.; Vleminckx, B.

2017-12-01

Why recent large earthquakes caused shaking stronger than predicted by earthquake hazard maps is under debate. This issue has two parts. Verification involves how well maps implement probabilistic seismic hazard analysis (PSHA) ("have we built the map right?"). Validation asks how well maps forecast shaking ("have we built the right map?"). We explore how well a map can ideally perform by simulating an area's shaking history and comparing "observed" shaking to that predicted by a map generated for the same parameters. The simulations yield shaking distributions whose mean is consistent with the map, but individual shaking histories show large scatter. Infrequent large earthquakes cause shaking much stronger than mapped, as observed. Hence, PSHA seems internally consistent and can be regarded as verified. Validation is harder because an earthquake history can yield shaking higher or lower than that predicted while being consistent with the hazard map. The scatter decreases for longer observation times because the largest earthquakes and resulting shaking are increasingly likely to have occurred. For the same reason, scatter is much less for the more active plate boundary than for a continental interior. For a continental interior, where the mapped hazard is low, even an M4 event produces exceedances at some sites. Larger earthquakes produce exceedances at more sites. Thus many exceedances result from small earthquakes, but infrequent large ones may cause very large exceedances. However, for a plate boundary, an M6 event produces exceedance at only a few sites, and an M7 produces them in a larger, but still relatively small, portion of the study area. As reality gives only one history, and a real map involves assumptions about more complicated source geometries and occurrence rates, which are unlikely to be exactly correct and thus will contribute additional scatter, it is hard to assess whether misfit between actual shaking and a map — notably higher-than-mapped shaking — arises by chance or reflects biases in the map. Due to this problem, there are limits to how well we can expect hazard maps to predict future shaking, as well as to our ability to test the performance of a hazard map based on available observations.

Forest/non-forest mapping using inventory data and satellite imagery

Treesearch

Ronald E. McRoberts

2002-01-01

For two study areas in Minnesota, USA, one heavily forested and one sparsely forested, maps of predicted proportion forest area were created using Landsat Thematic Mapper imagery, forest inventory plot data, and two prediction techniques, logistic regression and a k-Nearest Neighbours technique. The maps were used to increase the precision of forest area estimates by...

Predicting Chromosomal Locations of Genetically Mapped Loci in Maize Using the Morgan2McClintock Translator

PubMed Central

Lawrence, Carolyn J.; Seigfried, Trent E.; Bass, Hank W.; Anderson, Lorinda K.

2006-01-01

The Morgan2McClintock Translator permits prediction of meiotic pachytene chromosome map positions from recombination-based linkage data using recombination nodule frequency distributions. Its outputs permit estimation of DNA content between mapped loci and help to create an integrated overview of the maize nuclear genome structure. PMID:16387866

Gender differences in the accuracy of time-dependent blood pressure indices for predicting coronary heart disease: A random-effects modeling approach.

PubMed

Brant, Larry J; Ferrucci, Luigi; Sheng, Shan L; Concin, Hans; Zonderman, Alan B; Kelleher, Cecily C; Longo, Dan L; Ulmer, Hanno; Strasak, Alexander M

2010-12-01

Previous studies on blood pressure (BP) indices as a predictor of coronary heart disease (CHD) have provided equivocal results and generally relied on Cox proportional hazards regression methodology, with age and sex accounting for most of the predictive capability of the model. The aim of the present study was to use serially collected BP measurements to examine age-and gender-related differences in BP indices for predicting CHD. The predictive accuracy of time-dependent BP indices for CHD was investigated using a method of risk prediction based on posterior probabilities calculated from mixed-effects regression to utilize intraindividual differences in serial BP measurements according to age changes within gender groups. Data were collected prospectively from 2 community-dwelling cohort studies in the United States (Baltimore Longitudinal Study of Aging [BLSA]) and Europe (Vorarlberg Health Monitoring and Promotion Program [VHM&PP]). The study comprised 152,633 participants (aged 30-74 years) and 610,061 BP measurements. During mean follow-up of 7.5 years, 2457 nonfatal and fatal CHD events were observed. In both study populations, pulse pressure (PP) and systolic blood pressure (SBP) performed best as individual predictors of CHD in women (area under the receiver operating characteristic curve [AUC(ROC)] was between 0.83 and 0.85 for PP, and between 0.77 and 0.81 for SBP). Mean arterial pressure (MAP) and diastolic blood pressure (DBP) performed better for men (AUC(ROC) = 0.67 and 0.65 for MAP and DBP, respectively, in the BLSA; AUC(ROC) = 0.77 and 0.75 in the VHM&PP) than for women (AUC(ROC) = 0.60 for both MAP and DBP in the BLSA; AUC(ROC) = 0.75 and 0.52, respectively, in the VHM&PP). The degree of discrimination in both populations was overall greater but more varied for all BP indices for women (AUC(ROC) estimates between 0.85 [PP in the VHM&PP] and 0.52 [DBP in the VHM&PP]) than for men (AUC(ROC) estimates between 0.78 [MAP + PP in the VHM&PP] and 0.63 [PP in the BLSA]). Our findings indicate differences in discrimination between women and men in the accuracy of longitudinally collected BP measurements for predicting CHD, implicating the usefulness of gender-specific BP indices to assess individual CHD risk. Copyright © 2010. Published by EM Inc USA.

Assessing Changes in High School Students' Conceptual Understanding through Concept Maps before and after the Computer-Based Predict-Observe-Explain (CB-POE) Tasks on Acid-Base Chemistry at the Secondary Level

ERIC Educational Resources Information Center

Yaman, Fatma; Ayas, Alipasa

2015-01-01

Although concept maps have been used as alternative assessment methods in education, there has been an ongoing debate on how to evaluate students' concept maps. This study discusses how to evaluate students' concept maps as an assessment tool before and after 15 computer-based Predict-Observe-Explain (CB-POE) tasks related to acid-base chemistry.…

Geovisualization in the HydroProg web map service

NASA Astrophysics Data System (ADS)

Spallek, Waldemar; Wieczorek, Malgorzata; Szymanowski, Mariusz; Niedzielski, Tomasz; Swierczynska, Malgorzata

2016-04-01

The HydroProg system, built at the University of Wroclaw (Poland) in frame of the research project no. 2011/01/D/ST10/04171 financed by the National Science Centre of Poland, has been designed for computing predictions of river stages in real time on a basis of multimodelling. This experimental system works on the upper Nysa Klodzka basin (SW Poland) above the gauge in the town of Bardo, with the catchment area of 1744 square kilometres. The system operates in association with the Local System for Flood Monitoring of Klodzko County (LSOP), and produces hydrograph prognoses as well as inundation predictions. For presenting the up-to-date predictions and their statistics in the online mode, the dedicated real-time web map service has been designed. Geovisualisation in the HydroProg map service concerns: interactive maps of study area, interactive spaghetti hydrograms of water level forecasts along with observed river stages, animated images of inundation. The LSOP network offers a high spatial and temporal resolution of observations, as the length of the sampling interval is equal to 15 minutes. The main environmental elements related to hydrological modelling are shown on the main map. This includes elevation data (hillshading and hypsometric tints), rivers and reservoirs as well as catchment boundaries. Furthermore, we added main towns, roads as well as political and administrative boundaries for better map understanding. The web map was designed as a multi-scale representation, with levels of detail and zooming according to scales: 1:100 000, 1:250 000 and 1:500 000. Observations of water level in LSOP are shown on interactive hydrographs for each gauge. Additionally, predictions and some of their statistical characteristics (like prediction errors and Nash-Sutcliffe efficiency) are shown for selected gauges. Finally, predictions of inundation are presented on animated maps which have been added for four experimental sites. The HydroProg system is a strictly scientific project, but the web map service has been designed for all web users. The main objective of the paper is to present the design process of the web map service, following the cartographic and graphic principles.

Lithium-Ion Batteries for Aerospace Applications

NASA Technical Reports Server (NTRS)

Surampudi, S.; Halpert, G.; Marsh, R. A.; James, R.

1999-01-01

This presentation reviews: (1) the goals and objectives, (2) the NASA and Airforce requirements, (3) the potential near term missions, (4) management approach, (5) the technical approach and (6) the program road map. The objectives of the program include: (1) develop high specific energy and long life lithium ion cells and smart batteries for aerospace and defense applications, (2) establish domestic production sources, and to demonstrate technological readiness for various missions. The management approach is to encourage the teaming of universities, R&D organizations, and battery manufacturing companies, to build on existing commercial and government technology, and to develop two sources for manufacturing cells and batteries. The technological approach includes: (1) develop advanced electrode materials and electrolytes to achieve improved low temperature performance and long cycle life, (2) optimize cell design to improve specific energy, cycle life and safety, (3) establish manufacturing processes to ensure predictable performance, (4) establish manufacturing processes to ensure predictable performance, (5) develop aerospace lithium ion cells in various AH sizes and voltages, (6) develop electronics for smart battery management, (7) develop a performance database required for various applications, and (8) demonstrate technology readiness for the various missions. Charts which review the requirements for the Li-ion battery development program are presented.

Hubble’s Global View of Jupiter During the Juno Mission

NASA Astrophysics Data System (ADS)

Simon, Amy A.; Wong, Michael H.; Orton, Glenn S.; Cosentino, Richard; Tollefson, Joshua; Johnson, Perianne

2017-10-01

With two observing programs designed for mapping clouds and hazes in Jupiter's atmosphere during the Juno mission, the Hubble Space Telescope is acquiring an unprecedented set of global maps for study. The Outer Planet Atmospheres Legacy program (OPAL, PI: Simon) and the Wide Field Coverage for Juno program (WFCJ, PI: Wong) are designed to enable frequent multi-wavelength global mapping of Jupiter, with many maps timed specifically for Juno’s perijove passes. Filters span wavelengths from 212 to 894 nm. Besides offering global views for Juno observation context, they also reveal a wealth of information about interesting atmospheric dynamical features. We will summarize the latest findings from these global mapping programs, including changes in the Great Red Spot, zonal wind profile analysis, and persistent cyclone-generated waves in the North Equatorial Belt.

Decoding the Formation of New Semantics: MVPA Investigation of Rapid Neocortical Plasticity during Associative Encoding through Fast Mapping.

PubMed

Atir-Sharon, Tali; Gilboa, Asaf; Hazan, Hananel; Koilis, Ester; Manevitz, Larry M

2015-01-01

Neocortical structures typically only support slow acquisition of declarative memory; however, learning through fast mapping may facilitate rapid learning-induced cortical plasticity and hippocampal-independent integration of novel associations into existing semantic networks. During fast mapping the meaning of new words and concepts is inferred, and durable novel associations are incidentally formed, a process thought to support early childhood's exuberant learning. The anterior temporal lobe, a cortical semantic memory hub, may critically support such learning. We investigated encoding of semantic associations through fast mapping using fMRI and multivoxel pattern analysis. Subsequent memory performance following fast mapping was more efficiently predicted using anterior temporal lobe than hippocampal voxels, while standard explicit encoding was best predicted by hippocampal activity. Searchlight algorithms revealed additional activity patterns that predicted successful fast mapping semantic learning located in lateral occipitotemporal and parietotemporal neocortex and ventrolateral prefrontal cortex. By contrast, successful explicit encoding could be classified by activity in medial and dorsolateral prefrontal and parahippocampal cortices. We propose that fast mapping promotes incidental rapid integration of new associations into existing neocortical semantic networks by activating related, nonoverlapping conceptual knowledge. In healthy adults, this is better captured by unique anterior and lateral temporal lobe activity patterns, while hippocampal involvement is less predictive of this kind of learning.

Corn rootworms (Coleoptera: Chrysomelidae) in space and time

NASA Astrophysics Data System (ADS)

Park, Yong-Lak

Spatial dispersion is a main characteristic of insect populations. Dispersion pattern provides useful information for developing effective sampling and scouting programs because it affects sampling accuracy, efficiency, and precision. Insect dispersion, however, is dynamic in space and time and largely dependent upon interactions among insect, plant and environmental factors. This study investigated the spatial and temporal dynamics of corn rootworm dispersion at different spatial scales by using the global positioning system, the geographic information system, and geostatistics. Egg dispersion pattern was random or uniform in 8-ha cornfields, but could be aggregated at a smaller scale. Larval dispersion pattern was aggregated regardless of spatial scales used in this study. Soil moisture positively affected corn rootworm egg and larval dispersions. Adult dispersion tended to be aggregated during peak population period and random or uniform early and late in the season and corn plant phenology was a major factor to determine dispersion patterns. The dispersion pattern of root injury by corn rootworm larval feeding was aggregated and the degree of aggregation increased as the root injury increased within the range of root injury observed in microscale study. Between-year relationships in dispersion among eggs, larvae, adult, and environment provided a strategy that could predict potential root damage the subsequent year. The best prediction map for the subsequent year's potential root damage was the dispersion maps of adults during population peaked in the cornfield. The prediction map was used to develop site-specific pest management that can reduce chemical input and increase control efficiency by controlling pests only where management is needed. This study demonstrated the spatio-temporal dynamics of insect population and spatial interactions among insects, plants, and environment.

Arterial spin labeling-based Z-maps have high specificity and positive predictive value for neurodegenerative dementia compared to FDG-PET.

PubMed

Fällmar, David; Haller, Sven; Lilja, Johan; Danfors, Torsten; Kilander, Lena; Tolboom, Nelleke; Egger, Karl; Kellner, Elias; Croon, Philip M; Verfaillie, Sander C J; van Berckel, Bart N M; Ossenkoppele, Rik; Barkhof, Frederik; Larsson, Elna-Marie

2017-10-01

Cerebral perfusion analysis based on arterial spin labeling (ASL) MRI has been proposed as an alternative to FDG-PET in patients with neurodegenerative disease. Z-maps show normal distribution values relating an image to a database of controls. They are routinely used for FDG-PET to demonstrate disease-specific patterns of hypometabolism at the individual level. This study aimed to compare the performance of Z-maps based on ASL to FDG-PET. Data were combined from two separate sites, each cohort consisting of patients with Alzheimer's disease (n = 18 + 7), frontotemporal dementia (n = 12 + 8) and controls (n = 9 + 29). Subjects underwent pseudocontinuous ASL and FDG-PET. Z-maps were created for each subject and modality. Four experienced physicians visually assessed the 166 Z-maps in random order, blinded to modality and diagnosis. Discrimination of patients versus controls using ASL-based Z-maps yielded high specificity (84%) and positive predictive value (80%), but significantly lower sensitivity compared to FDG-PET-based Z-maps (53% vs. 96%, p < 0.001). Among true-positive cases, correct diagnoses were made in 76% (ASL) and 84% (FDG-PET) (p = 0.168). ASL-based Z-maps can be used for visual assessment of neurodegenerative dementia with high specificity and positive predictive value, but with inferior sensitivity compared to FDG-PET. • ASL-based Z-maps yielded high specificity and positive predictive value in neurodegenerative dementia. • ASL-based Z-maps had significantly lower sensitivity compared to FDG-PET-based Z-maps. • FDG-PET might be reserved for ASL-negative cases where clinical suspicion persists. • Findings were similar at two study sites.

Using a detailed uncertainty analysis to adjust mapped rates of forest disturbance derived from Landsat time series data (Invited)

NASA Astrophysics Data System (ADS)

Cohen, W. B.; Yang, Z.; Stehman, S.; Huang, C.; Healey, S. P.

2013-12-01

Forest ecosystem process models require spatially and temporally detailed disturbance data to accurately predict fluxes of carbon or changes in biodiversity over time. A variety of new mapping algorithms using dense Landsat time series show great promise for providing disturbance characterizations at an annual time step. These algorithms provide unprecedented detail with respect to timing, magnitude, and duration of individual disturbance events, and causal agent. But all maps have error and disturbance maps in particular can have significant omission error because many disturbances are relatively subtle. Because disturbance, although ubiquitous, can be a relatively rare event spatially in any given year, omission errors can have a great impact on mapped rates. Using a high quality reference disturbance dataset, it is possible to not only characterize map errors but also to adjust mapped disturbance rates to provide unbiased rate estimates with confidence intervals. We present results from a national-level disturbance mapping project (the North American Forest Dynamics project) based on the Vegetation Change Tracker (VCT) with annual Landsat time series and uncertainty analyses that consist of three basic components: response design, statistical design, and analyses. The response design describes the reference data collection, in terms of the tool used (TimeSync), a formal description of interpretations, and the approach for data collection. The statistical design defines the selection of plot samples to be interpreted, whether stratification is used, and the sample size. Analyses involve derivation of standard agreement matrices between the map and the reference data, and use of inclusion probabilities and post-stratification to adjust mapped disturbance rates. Because for NAFD we use annual time series, both mapped and adjusted rates are provided at an annual time step from ~1985-present. Preliminary evaluations indicate that VCT captures most of the higher intensity disturbances, but that many of the lower intensity disturbances (thinnings, stress related to insects and disease, etc.) are missed. Because lower intensity disturbances are a large proportion of the total set of disturbances, adjusting mapped disturbance rates to include these can be important for inclusion in ecosystem process models. The described statistical disturbance rate adjustments are aspatial in nature, such that the basic underlying map is unchanged. For spatially explicit ecosystem modeling, such adjustments, although important, can be difficult to directly incorporate. One approach for improving the basic underlying map is an ensemble modeling approach that uses several different complementary maps, each derived from a different algorithm and having their own strengths and weaknesses relative to disturbance magnitude and causal agent of disturbance. We will present results from a pilot study associated with the Landscape Change Monitoring System (LCMS), an emerging national-level program that builds upon NAFD and the well-established Monitoring Trends in Burn Severity (MTBS) program.

MAP - a mapping and analysis program for harvest planning

Treesearch

Robert N. Eli; Chris B. LeDoux; Penn A. Peters

1984-01-01

The Northeastern Forest Experiment Station and the Department of Civil Engineering at West Virginia University are cooperating in the development of a Mapping and Analysis Program, to be named MAP. The goal of this computer software package is to significantly improve the planning and harvest efficiency of small to moderately sized harvest units located in mountainous...

Modeling Weather Impact on Ground Delay Programs

NASA Technical Reports Server (NTRS)

Wang, Yao; Kulkarni, Deepak

2011-01-01

Scheduled arriving aircraft demand may exceed airport arrival capacity when there is abnormal weather at an airport. In such situations, Federal Aviation Administration (FAA) institutes ground-delay programs (GDP) to delay flights before they depart from their originating airports. Efficient GDP planning depends on the accuracy of prediction of airport capacity and demand in the presence of uncertainties in weather forecast. This paper presents a study of the impact of dynamic airport surface weather on GDPs. Using the National Traffic Management Log, effect of weather conditions on the characteristics of GDP events at selected busy airports is investigated. Two machine learning methods are used to generate models that map the airport operational conditions and weather information to issued GDP parameters and results of validation tests are described.

An integrated approach to flood hazard assessment on alluvial fans using numerical modeling, field mapping, and remote sensing

USGS Publications Warehouse

Pelletier, J.D.; Mayer, L.; Pearthree, P.A.; House, P.K.; Demsey, K.A.; Klawon, J.K.; Vincent, K.R.

2005-01-01

Millions of people in the western United States live near the dynamic, distributary channel networks of alluvial fans where flood behavior is complex and poorly constrained. Here we test a new comprehensive approach to alluvial-fan flood hazard assessment that uses four complementary methods: two-dimensional raster-based hydraulic modeling, satellite-image change detection, fieldbased mapping of recent flood inundation, and surficial geologic mapping. Each of these methods provides spatial detail lacking in the standard method and each provides critical information for a comprehensive assessment. Our numerical model simultaneously solves the continuity equation and Manning's equation (Chow, 1959) using an implicit numerical method. It provides a robust numerical tool for predicting flood flows using the large, high-resolution Digital Elevation Models (DEMs) necessary to resolve the numerous small channels on the typical alluvial fan. Inundation extents and flow depths of historic floods can be reconstructed with the numerical model and validated against field- and satellite-based flood maps. A probabilistic flood hazard map can also be constructed by modeling multiple flood events with a range of specified discharges. This map can be used in conjunction with a surficial geologic map to further refine floodplain delineation on fans. To test the accuracy of the numerical model, we compared model predictions of flood inundation and flow depths against field- and satellite-based flood maps for two recent extreme events on the southern Tortolita and Harquahala piedmonts in Arizona. Model predictions match the field- and satellite-based maps closely. Probabilistic flood hazard maps based on the 10 yr, 100 yr, and maximum floods were also constructed for the study areas using stream gage records and paleoflood deposits. The resulting maps predict spatially complex flood hazards that strongly reflect small-scale topography and are consistent with surficial geology. In contrast, FEMA Flood Insurance Rate Maps (FIRMs) based on the FAN model predict uniformly high flood risk across the study areas without regard for small-scale topography and surficial geology. ?? 2005 Geological Society of America.

SU-E-J-92: Validating Dose Uncertainty Estimates Produced by AUTODIRECT, An Automated Program to Evaluate Deformable Image Registration Accuracy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, H; Chen, J; Pouliot, J

2015-06-15

Purpose: Deformable image registration (DIR) is a powerful tool with the potential to deformably map dose from one computed-tomography (CT) image to another. Errors in the DIR, however, will produce errors in the transferred dose distribution. We have proposed a software tool, called AUTODIRECT (automated DIR evaluation of confidence tool), which predicts voxel-specific dose mapping errors on a patient-by-patient basis. This work validates the effectiveness of AUTODIRECT to predict dose mapping errors with virtual and physical phantom datasets. Methods: AUTODIRECT requires 4 inputs: moving and fixed CT images and two noise scans of a water phantom (for noise characterization). Then,more » AUTODIRECT uses algorithms to generate test deformations and applies them to the moving and fixed images (along with processing) to digitally create sets of test images, with known ground-truth deformations that are similar to the actual one. The clinical DIR algorithm is then applied to these test image sets (currently 4) . From these tests, AUTODIRECT generates spatial and dose uncertainty estimates for each image voxel based on a Student’s t distribution. This work compares these uncertainty estimates to the actual errors made by the Velocity Deformable Multi Pass algorithm on 11 virtual and 1 physical phantom datasets. Results: For 11 of the 12 tests, the predicted dose error distributions from AUTODIRECT are well matched to the actual error distributions within 1–6% for 10 virtual phantoms, and 9% for the physical phantom. For one of the cases though, the predictions underestimated the errors in the tail of the distribution. Conclusion: Overall, the AUTODIRECT algorithm performed well on the 12 phantom cases for Velocity and was shown to generate accurate estimates of dose warping uncertainty. AUTODIRECT is able to automatically generate patient-, organ- , and voxel-specific DIR uncertainty estimates. This ability would be useful for patient-specific DIR quality assurance.« less

Applications systems verification and transfer project. Volume 8: Satellite snow mapping and runoff prediction handbook

NASA Technical Reports Server (NTRS)

Bowley, C. J.; Barnes, J. C.; Rango, A.

1981-01-01

The purpose of the handbook is to update the various snowcover interpretation techniques, document the snow mapping techniques used in the various ASVT study areas, and describe the ways snowcover data have been applied to runoff prediction. Through documentation in handbook form, the methodology developed in the Snow Mapping ASVT can be applied to other areas.

High-resolution mapping of forest carbon stocks in the Colombian Amazon

NASA Astrophysics Data System (ADS)

Asner, G. P.; Clark, J. K.; Mascaro, J.; Galindo García, G. A.; Chadwick, K. D.; Navarrete Encinales, D. A.; Paez-Acosta, G.; Cabrera Montenegro, E.; Kennedy-Bowdoin, T.; Duque, Á.; Balaji, A.; von Hildebrand, P.; Maatoug, L.; Bernal, J. F. Phillips; Yepes Quintero, A. P.; Knapp, D. E.; García Dávila, M. C.; Jacobson, J.; Ordóñez, M. F.

2012-07-01

High-resolution mapping of tropical forest carbon stocks can assist forest management and improve implementation of large-scale carbon retention and enhancement programs. Previous high-resolution approaches have relied on field plot and/or light detection and ranging (LiDAR) samples of aboveground carbon density, which are typically upscaled to larger geographic areas using stratification maps. Such efforts often rely on detailed vegetation maps to stratify the region for sampling, but existing tropical forest maps are often too coarse and field plots too sparse for high-resolution carbon assessments. We developed a top-down approach for high-resolution carbon mapping in a 16.5 million ha region (> 40%) of the Colombian Amazon - a remote landscape seldom documented. We report on three advances for large-scale carbon mapping: (i) employing a universal approach to airborne LiDAR-calibration with limited field data; (ii) quantifying environmental controls over carbon densities; and (iii) developing stratification- and regression-based approaches for scaling up to regions outside of LiDAR coverage. We found that carbon stocks are predicted by a combination of satellite-derived elevation, fractional canopy cover and terrain ruggedness, allowing upscaling of the LiDAR samples to the full 16.5 million ha region. LiDAR-derived carbon maps have 14% uncertainty at 1 ha resolution, and the regional map based on stratification has 28% uncertainty in any given hectare. High-resolution approaches with quantifiable pixel-scale uncertainties will provide the most confidence for monitoring changes in tropical forest carbon stocks. Improved confidence will allow resource managers and decision makers to more rapidly and effectively implement actions that better conserve and utilize forests in tropical regions.

High-resolution Mapping of Forest Carbon Stocks in the Colombian Amazon

NASA Astrophysics Data System (ADS)

Asner, G. P.; Clark, J. K.; Mascaro, J.; Galindo García, G. A.; Chadwick, K. D.; Navarrete Encinales, D. A.; Paez-Acosta, G.; Cabrera Montenegro, E.; Kennedy-Bowdoin, T.; Duque, Á.; Balaji, A.; von Hildebrand, P.; Maatoug, L.; Bernal, J. F. Phillips; Knapp, D. E.; García Dávila, M. C.; Jacobson, J.; Ordóñez, M. F.

2012-03-01

High-resolution mapping of tropical forest carbon stocks can assist forest management and improve implementation of large-scale carbon retention and enhancement programs. Previous high-resolution approaches have relied on field plot and/or Light Detection and Ranging (LiDAR) samples of aboveground carbon density, which are typically upscaled to larger geographic areas using stratification maps. Such efforts often rely on detailed vegetation maps to stratify the region for sampling, but existing tropical forest maps are often too coarse and field plots too sparse for high resolution carbon assessments. We developed a top-down approach for high-resolution carbon mapping in a 16.5 million ha region (>40 %) of the Colombian Amazon - a remote landscape seldom documented. We report on three advances for large-scale carbon mapping: (i) employing a universal approach to airborne LiDAR-calibration with limited field data; (ii) quantifying environmental controls over carbon densities; and (iii) developing stratification- and regression-based approaches for scaling up to regions outside of LiDAR coverage. We found that carbon stocks are predicted by a combination of satellite-derived elevation, fractional canopy cover and terrain ruggedness, allowing upscaling of the LiDAR samples to the full 16.5 million ha region. LiDAR-derived carbon mapping samples had 14.6 % uncertainty at 1 ha resolution, and regional maps based on stratification and regression approaches had 25.6 % and 29.6 % uncertainty, respectively, in any given hectare. High-resolution approaches with reported local-scale uncertainties will provide the most confidence for monitoring changes in tropical forest carbon stocks. Improved confidence will allow resource managers and decision-makers to more rapidly and effectively implement actions that better conserve and utilize forests in tropical regions.

What do we need to know to predict ENSO? Student-centered learning in a Master course in Climate Physics

NASA Astrophysics Data System (ADS)

Lübbecke, Joke; Glessmer, Mirjam

2017-04-01

An important learning outcome of a Master of Sciences program is to empower students to understand which information they need, how they can gain the required knowledge and skills, and how to apply those to solve a given scientific problem. In designing a class on the El-Nino-Southern-Oscillation (ENSO) for students in the Climate Physics program at Kiel University, Germany, we have implemented various active learning strategies to meet this goal. The course is guided by an overarching question, embedded in a short story: What would we need to know to successfully predict ENSO? The students identify desired learning outcomes and collaboratively construct a concept map which then serves as a structure for the 12 weeks of the course, where each individual topic is situated in the larger context of the students' own concept map. Each learning outcome of the course is therefore directly motivated by a need to know expressed by the students themselves. During each session, students are actively involved in the learning process. They work individually or in small groups, for example testing different index definitions, analyzing data sets, setting up simple numerical models and planning and constructing hands-on experiments to demonstrate physical processes involved in the formation of El Niño events. The instructor's role is to provide the necessary background information and guide the students where it is needed. Insights are shared between groups as students present their findings to each other and combine the information, for example by cooperatively constructing a world map displaying the impacts of ENSO or by exchanging experts on different ENSO oscillator theories between groups. Development of this course was supported by the PerLe Fonds for teaching innovations at Kiel University. A preliminary evaluation has been very positive with students in particular appreciating their active involvement in the class.

Mask Analysis Program (MAP) reference manual

NASA Technical Reports Server (NTRS)

Mitchell, C. L.

1976-01-01

A document intended to serve as a User's Manual and a Programmer's Manual for the Mask Analysis Program is presented. The first portion of the document is devoted to the user. It contains all of the information required to execute MAP. The remainder of the document describes the details of MAP software logic. Although the information in this portion is not required to run the program, it is recommended that every user review it to gain an appreciation for the program functions.

The psychological four-color mapping problem.

PubMed

Francis, Gregory; Bias, Keri; Shive, Joshua

2010-06-01

Mathematicians have proven that four colors are sufficient to color 2-D maps so that no neighboring regions share the same color. Here we consider the psychological 4-color problem: Identifying which 4 colors should be used to make a map easy to use. We build a model of visual search for this design task and demonstrate how to apply it to the task of identifying the optimal colors for a map. We parameterized the model with a set of 7 colors using a visual search experiment in which human participants found a target region on a small map. We then used the model to predict search times for new maps and identified the color assignments that minimize or maximize average search time. The differences between these maps were predicted to be substantial. The model was then tested with a larger set of 31 colors on a map of English counties under conditions in which participants might memorize some aspects of the map. Empirical tests of the model showed that an optimally best colored version of this map is searched 15% faster than the correspondingly worst colored map. Thus, the color assignment seems to affect search times in a way predicted by the model, and this effect persists even when participants might use other sources of knowledge about target location. PsycINFO Database Record (c) 2010 APA, all rights reserved.

In Silico Identification of Epitopes in Mycobacterium avium subsp. paratuberculosis Proteins That Were Upregulated under Stress Conditions

PubMed Central

Gurung, Ratna B.; Purdie, Auriol C.; Begg, Douglas J.

2012-01-01

Johne's disease in ruminants is caused by Mycobacterium avium subsp. paratuberculosis. Diagnosis of M. avium subsp. paratuberculosis infection is difficult, especially in the early stages. To date, ideal antigen candidates are not available for efficient immunization or immunodiagnosis. This study reports the in silico selection and subsequent analysis of epitopes of M. avium subsp. paratuberculosis proteins that were found to be upregulated under stress conditions as a means to identify immunogenic candidate proteins. Previous studies have reported differential regulation of proteins when M. avium subsp. paratuberculosis is exposed to stressors which induce a response similar to dormancy. Dormancy may be involved in evading host defense mechanisms, and the host may also mount an immune response against these proteins. Twenty-five M. avium subsp. paratuberculosis proteins that were previously identified as being upregulated under in vitro stress conditions were analyzed for B and T cell epitopes by use of the prediction tools at the Immune Epitope Database and Analysis Resource. Major histocompatibility complex class I T cell epitopes were predicted using an artificial neural network method, and class II T cell epitopes were predicted using the consensus method. Conformational B cell epitopes were predicted from the relevant three-dimensional structure template for each protein. Based on the greatest number of predicted epitopes, eight proteins (MAP2698c [encoded by desA2], MAP2312c [encoded by fadE19], MAP3651c [encoded by fadE3_2], MAP2872c [encoded by fabG5_2], MAP3523c [encoded by oxcA], MAP0187c [encoded by sodA], and the hypothetical proteins MAP3567 and MAP1168c) were identified as potential candidates for study of antibody- and cell-mediated immune responses within infected hosts. PMID:22496492

Neural networks for satellite remote sensing and robotic sensor interpretation

NASA Astrophysics Data System (ADS)

Martens, Siegfried

Remote sensing of forests and robotic sensor fusion can be viewed, in part, as supervised learning problems, mapping from sensory input to perceptual output. This dissertation develops ARTMAP neural networks for real-time category learning, pattern recognition, and prediction tailored to remote sensing and robotics applications. Three studies are presented. The first two use ARTMAP to create maps from remotely sensed data, while the third uses an ARTMAP system for sensor fusion on a mobile robot. The first study uses ARTMAP to predict vegetation mixtures in the Plumas National Forest based on spectral data from the Landsat Thematic Mapper satellite. While most previous ARTMAP systems have predicted discrete output classes, this project develops new capabilities for multi-valued prediction. On the mixture prediction task, the new network is shown to perform better than maximum likelihood and linear mixture models. The second remote sensing study uses an ARTMAP classification system to evaluate the relative importance of spectral and terrain data for map-making. This project has produced a large-scale map of remotely sensed vegetation in the Sierra National Forest. Network predictions are validated with ground truth data, and maps produced using the ARTMAP system are compared to a map produced by human experts. The ARTMAP Sierra map was generated in an afternoon, while the labor intensive expert method required nearly a year to perform the same task. The robotics research uses an ARTMAP system to integrate visual information and ultrasonic sensory information on a B14 mobile robot. The goal is to produce a more accurate measure of distance than is provided by the raw sensors. ARTMAP effectively combines sensory sources both within and between modalities. The improved distance percept is used to produce occupancy grid visualizations of the robot's environment. The maps produced point to specific problems of raw sensory information processing and demonstrate the benefits of using a neural network system for sensor fusion.

USGS standard quadrangle maps for emergency response

USGS Publications Warehouse

Moore, Laurence R.

2009-01-01

The 1:24,000-scale topographic quadrangle was the primary product of the U.S. Geological Survey's (USGS) National Mapping Program from 1947-1992. This map series includes about 54,000 map sheets for the conterminous United States, and is the only uniform map series ever produced that covers this area at such a large scale. This map series partially was revised under several programs, starting as early as 1968, but these programs were not adequate to keep the series current. Through the 1990s the emphasis of the USGS mapping program shifted away from topographic maps and toward more specialized digital data products. Topographic map revision dropped off rapidly after 1999, and stopped completely by 2004. Since 2001, emergency-response and homeland security requirement have revived the question of whether a standard national topographic series is needed. Emergencies such as Hurricane Katrina in 2005 and California wildfires in 2007-08 demonstrated that familiar maps are important to first responders. Maps that have a standard scale, extent, and grids help reduce confusion and save time in emergencies. Traditional maps are designed to allow the human brain to quickly process large amounts of information, and depend on artistic layout and design that cannot be fully automated. In spite of technical advances, creating a traditional, general-purpose topographic map is still expensive. Although the content and layout of traditional topographic maps probably is still desirable, the preferred packaging and delivery of maps has changed. Digital image files are now desired by most users, but to be useful to the emergency-response community, these files must be easy to view and easy to print without specialized geographic information system expertise or software.

Libraries, the MAP, and Student Achievement.

ERIC Educational Resources Information Center

Jones, Cherri; Singer, Marietta; Miller, David W.; Makemson, Carroll; Elliott, Kara; Litsch, Diana; Irwin, Barbara; Hoemann, Cheryl; Elmore, Jennifer; Roe, Patty; Gregg, Diane; Needham, Joyce; Stanley, Jerri; Reinert, John; Holtz, Judy; Jenkins, Sandra; Giles, Paula

2002-01-01

Includes 17 articles that discuss the Missouri Assessment Program (MAP) and the role of school library media centers. Highlights include improving student achievement; improving student scores on the MAP; graphic organizers; programs for volunteer student library workers; research process; research skills; reading initiatives; collaborative…

Risk maps for targeting exotic plant pest detection programs in the United States

Treesearch

R.D. Magarey; D.M. Borchert; J.S. Engle; M Garcia-Colunga; Frank H. Koch; et al

2011-01-01

In the United States, pest risk maps are used by the Cooperative Agricultural Pest Survey for spatial and temporal targeting of exotic plant pest detection programs. Methods are described to create standardized host distribution, climate and pathway risk maps for the top nationally ranked exotic pest targets. Two examples are provided to illustrate the risk mapping...

US Topo Maps 2014: Program updates and research

USGS Publications Warehouse

Fishburn, Kristin A.

2014-01-01

The U. S. Geological Survey (USGS) US Topo map program is now in year two of its second three-year update cycle. Since the program was launched in 2009, the product and the production system tools and processes have undergone enhancements that have made the US Topo maps a popular success story. Research and development continues with structural and content product enhancements, streamlined and more fully automated workflows, and the evaluation of a GIS-friendly US Topo GIS Packet. In addition, change detection methodologies are under evaluation to further streamline product maintenance and minimize resource expenditures for production in the future. The US Topo map program will continue to evolve in the years to come, providing traditional map users and Geographic Information System (GIS) analysts alike with a convenient, freely available product incorporating nationally consistent data that are quality assured to high standards.

Isolation and characterization of new highly polymorphic DNA markers from the Huntington disease region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weber, B.; Hedrick, A.; Andrew, S.

1992-02-01

The defect causing Huntington disease (HD) has been mapped to 4p16.3, distal to the DNA marker D4S10. Subsequently, additional polymorphic markers closer to the HD gene have been isolated, which has led to the establishment of predictive testing programs for individuals at risk for HD. Approximately 17% of persons presenting to the Canadian collaborative study for predictive testing for HD have not received any modification of risk, in part because of limited informativeness of currently available DNA markers. Therefore, more highly polymorphic DNA markers are needed, which well further increase the accuracy and availability of predictive testing, specifically for familiesmore » with complex or incomplete pedigree structures. In addition, new markers are urgently needed in order to refine the breakpoints in the few known recombinant HD chromosomes, which could allow a more accurate localization of the HD gene within 4p16.3 and, therefore, accelerate the cloning of the disease gene. In this study, the authors present the identification and characterization of nine new polymorphic DNA markers, including three markers which detect highly informative multiallelic VNTR-like polymorphisms with PIC values of up to .84. These markers have been isolated from a cloned region of DNA which has been previously mapped approximately 1,000 kb from the 4p telomere.« less

Analysis of Factors Influencing Hydration Site Prediction Based on Molecular Dynamics Simulations

PubMed Central

2015-01-01

Water contributes significantly to the binding of small molecules to proteins in biochemical systems. Molecular dynamics (MD) simulation based programs such as WaterMap and WATsite have been used to probe the locations and thermodynamic properties of hydration sites at the surface or in the binding site of proteins generating important information for structure-based drug design. However, questions associated with the influence of the simulation protocol on hydration site analysis remain. In this study, we use WATsite to investigate the influence of factors such as simulation length and variations in initial protein conformations on hydration site prediction. We find that 4 ns MD simulation is appropriate to obtain a reliable prediction of the locations and thermodynamic properties of hydration sites. In addition, hydration site prediction can be largely affected by the initial protein conformations used for MD simulations. Here, we provide a first quantification of this effect and further indicate that similar conformations of binding site residues (RMSD < 0.5 Å) are required to obtain consistent hydration site predictions. PMID:25252619

An integrated user-friendly ArcMAP tool for bivariate statistical modeling in geoscience applications

NASA Astrophysics Data System (ADS)

Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusof, Z.; Tehrany, M. S.

2014-10-01

Modeling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modeling. Bivariate statistical analysis (BSA) assists in hazard modeling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, BSM (bivariate statistical modeler), for BSA technique is proposed. Three popular BSA techniques such as frequency ratio, weights-of-evidence, and evidential belief function models are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and is created by a simple graphical user interface, which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.

An integrated user-friendly ArcMAP tool for bivariate statistical modelling in geoscience applications

NASA Astrophysics Data System (ADS)

Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusoff, Z. M.; Tehrany, M. S.

2015-03-01

Modelling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modelling. Bivariate statistical analysis (BSA) assists in hazard modelling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time-consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, bivariate statistical modeler (BSM), for BSA technique is proposed. Three popular BSA techniques, such as frequency ratio, weight-of-evidence (WoE), and evidential belief function (EBF) models, are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and created by a simple graphical user interface (GUI), which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve (AUC) is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.

Myocardial infarction size and location: a comparative study of epicardial isopotential mapping, thallium-201 scintigraphy, electrocardiography and vectorcardiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Toyama, S.; Suzuki, K.; Takahashi, T.

1987-07-01

Based on epicardial isopotential mapping (the Ep Map), which was calculated from body surface isopotential mapping (the Body Map) with Yamashita's method, using the finite element technique, we predicted the location and size of the abnormal depolarized area (the infarcted area) in 19 clinical cases of anterior and 18 cases of inferoposterior infarction. The prediction was done using Toyama's diagnostic method, previously reported. The accuracy of the prediction by the Ep Map was assessed by comparing it with findings from thallium-201 scintigraphy (SCG), electrocardiography (ECG) and vectorcardiography (VCG). In all cases of anterior infarction, the location of the abnormal depolarizedmore » areas determined on the Ep Map, which was localized at the anterior wall along the anterior intraventricular septum, agreed with the location of the abnormal findings obtained by SCG, ECG and VCG. For all inferoposterior infarction cases, the abnormal depolarized areas were localized at the posterior wall and the location also coincided with that of the abnormal findings obtained by SCG, ECG and VCG. Furthermore, we ranked and ordered the size of the abnormal depolarized areas, which were predicted by the Ep Map for both anterior and inferoposterior infarction cases. In the cases of anterior infarction, the order of the size of the abnormal depolarized area by the Ep Map was correlated to the size of the abnormal findings by SCG, as well as to the results from Selvester's QRS scoring system in ECG and to the angle of the maximum QRS vector in the horizontal plane in VCG.« less

Evaluation of prognostic and predictive value of microtubule associated protein tau in two independent cohorts.

PubMed

Baquero, Maria T; Lostritto, Karen; Gustavson, Mark D; Bassi, Kimberly A; Appia, Franck; Camp, Robert L; Molinaro, Annette M; Harris, Lyndsay N; Rimm, David L

2011-11-02

Microtubule associated proteins (MAPs) endogenously regulate microtubule stabilization and have been reported as prognostic and predictive markers for taxane response. The microtubule stabilizer, MAP-tau, has shown conflicting results. We quantitatively assessed MAP-tau expression in two independent breast cancer cohorts to determine prognostic and predictive value of this biomarker. MAP-tau expression was evaluated in the retrospective Yale University breast cancer cohort (n = 651) using tissue microarrays and also in the TAX 307 cohort, a clinical trial randomized for TAC versus FAC chemotherapy (n = 140), using conventional whole tissue sections. Expression was measured using the AQUA method for quantitative immunofluorescence. Scores were correlated with clinicopathologic variables, survival, and response to therapy. Assessment of the Yale cohort using Cox univariate analysis indicated an improved overall survival (OS) in tumors with a positive correlation between high MAP-tau expression and overall survival (OS) (HR = 0.691, 95% CI = 0.489-0.974; P = 0.004). Kaplan Meier analysis showed 10-year survival for 65% of patients with high MAP-tau expression compared to 52% with low expression (P = .006). In TAX 307, high expression was associated with significantly longer median time to tumor progression (TTP) regardless of treatment arm (33.0 versus 23.4 months, P = 0.010) with mean TTP of 31.2 months. Response rates did not differ by MAP-tau expression (P = 0.518) or by treatment arm (P = 0.584). Quantitative measurement of MAP-tau expression has prognostic value in both cohorts, with high expression associated with longer TTP and OS. Differences by treatment arm or response rate in low versus high MAP-tau groups were not observed, indicating that MAP-tau is not associated with response to taxanes and is not a useful predictive marker for taxane-based chemotherapy.

MaMR: High-performance MapReduce programming model for material cloud applications

NASA Astrophysics Data System (ADS)

Jing, Weipeng; Tong, Danyu; Wang, Yangang; Wang, Jingyuan; Liu, Yaqiu; Zhao, Peng

2017-02-01

With the increasing data size in materials science, existing programming models no longer satisfy the application requirements. MapReduce is a programming model that enables the easy development of scalable parallel applications to process big data on cloud computing systems. However, this model does not directly support the processing of multiple related data, and the processing performance does not reflect the advantages of cloud computing. To enhance the capability of workflow applications in material data processing, we defined a programming model for material cloud applications that supports multiple different Map and Reduce functions running concurrently based on hybrid share-memory BSP called MaMR. An optimized data sharing strategy to supply the shared data to the different Map and Reduce stages was also designed. We added a new merge phase to MapReduce that can efficiently merge data from the map and reduce modules. Experiments showed that the model and framework present effective performance improvements compared to previous work.

Lunar Geologic Mapping: A Preliminary Map of a Portion of the LQ-10 ("Marius") Quadrangle

NASA Technical Reports Server (NTRS)

Gregg, T. K. P.; Yingst, R. A.

2009-01-01

Since the first lunar mapping program ended in the 1970s, new topographical, multispectral, elemental and albedo imaging datasets have become available (e.g., Clementine, Lunar Prospector, Galileo). Lunar science has also advanced within the intervening time period. A new systematic lunar geologic mapping effort endeavors to build on the success of earlier mapping programs by fully integrating the many disparate datasets using GIS software and bringing to bear the most current understanding of lunar geologic history. As part of this program, we report on a 1:2,500,000-scale preliminary map of a subset of Lunar Quadrangle 10 ("LQ-10" or the "Marius Quadrangle," see Figures 1 and 2), and discuss the first-order science results. By generating a geologic map of this region, we can constrain the stratigraphic and geologic relationships between features, revealing information about the Moon s chemical and thermal evolution.

Representation of DNA sequences in genetic codon context with applications in exon and intron prediction.

PubMed

Yin, Changchuan

2015-04-01

To apply digital signal processing (DSP) methods to analyze DNA sequences, the sequences first must be specially mapped into numerical sequences. Thus, effective numerical mappings of DNA sequences play key roles in the effectiveness of DSP-based methods such as exon prediction. Despite numerous mappings of symbolic DNA sequences to numerical series, the existing mapping methods do not include the genetic coding features of DNA sequences. We present a novel numerical representation of DNA sequences using genetic codon context (GCC) in which the numerical values are optimized by simulation annealing to maximize the 3-periodicity signal to noise ratio (SNR). The optimized GCC representation is then applied in exon and intron prediction by Short-Time Fourier Transform (STFT) approach. The results show the GCC method enhances the SNR values of exon sequences and thus increases the accuracy of predicting protein coding regions in genomes compared with the commonly used 4D binary representation. In addition, this study offers a novel way to reveal specific features of DNA sequences by optimizing numerical mappings of symbolic DNA sequences.

76 FR 21325 - Notice of Funds Availability: Inviting Applications for the Market Access Program

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-15

... for the 2012 Market Access Program (MAP). The intended effect of this notice is to solicit... INFORMATION CONTACT: Entities wishing to apply for funding assistance should contact the Program Operations....gov/mos/programs/map.asp . SUPPLEMENTARY INFORMATION: I. Funding Opportunity Description Authority...

A Probabilistic Strategy for Understanding Action Selection

PubMed Central

Kim, Byounghoon; Basso, Michele A.

2010-01-01

Brain regions involved in transforming sensory signals into movement commands are the likely sites where decisions are formed. Once formed, a decision must be read-out from the activity of populations of neurons to produce a choice of action. How this occurs remains unresolved. We recorded from four superior colliculus (SC) neurons simultaneously while monkeys performed a target selection task. We implemented three models to gain insight into the computational principles underlying population coding of action selection. We compared the population vector average (PVA), winner-takes-all (WTA) and a Bayesian model, maximum a posteriori estimate (MAP) to determine which predicted choices most often. The probabilistic model predicted more trials correctly than both the WTA and the PVA. The MAP model predicted 81.88% whereas WTA predicted 71.11% and PVA/OLE predicted the least number of trials at 55.71 and 69.47%. Recovering MAP estimates using simulated, non-uniform priors that correlated with monkeys’ choice performance, improved the accuracy of the model by 2.88%. A dynamic analysis revealed that the MAP estimate evolved over time and the posterior probability of the saccade choice reached a maximum at the time of the saccade. MAP estimates also scaled with choice performance accuracy. Although there was overlap in the prediction abilities of all the models, we conclude that movement choice from populations of neurons may be best understood by considering frameworks based on probability. PMID:20147560

Large-scale structure prediction by improved contact predictions and model quality assessment.

PubMed

Michel, Mirco; Menéndez Hurtado, David; Uziela, Karolis; Elofsson, Arne

2017-07-15

Accurate contact predictions can be used for predicting the structure of proteins. Until recently these methods were limited to very big protein families, decreasing their utility. However, recent progress by combining direct coupling analysis with machine learning methods has made it possible to predict accurate contact maps for smaller families. To what extent these predictions can be used to produce accurate models of the families is not known. We present the PconsFold2 pipeline that uses contact predictions from PconsC3, the CONFOLD folding algorithm and model quality estimations to predict the structure of a protein. We show that the model quality estimation significantly increases the number of models that reliably can be identified. Finally, we apply PconsFold2 to 6379 Pfam families of unknown structure and find that PconsFold2 can, with an estimated 90% specificity, predict the structure of up to 558 Pfam families of unknown structure. Out of these, 415 have not been reported before. Datasets as well as models of all the 558 Pfam families are available at http://c3.pcons.net/ . All programs used here are freely available. arne@bioinfo.se. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Folding Digital Mapping into a Traditional Field Camp Program

NASA Astrophysics Data System (ADS)

Kelley, D. F.

2011-12-01

Louisiana State University runs a field camp with a permanent fixed-base which has continually operated since 1928 in the Front Range just to the south of Colorado Springs, CO. The field camp program which offers a 6-credit hour course in Field Geology follows a very traditional structure. The first week is spent collecting data for the construction of a detailed stratigraphic column of the local geology. The second week is spent learning the skills of geologic mapping, while the third applies these skills to a more geologically complicated mapping area. The final three weeks of the field camp program are spent studying and mapping igneous and metamorphic rocks as well as conducting a regional stratigraphic correlation exercise. Historically there has been a lack of technology involved in this program. All mapping has been done in the field without the use of any digital equipment and all products have been made in the office without the use of computers. In the summer of 2011 the use of GPS units, and GIS software were introduced to the program. The exercise that was chosen for this incorporation of technology was one in which metamorphic rocks are mapped within Golden Gate Canyon State Park in Colorado. This same mapping exercise was carried out during the 2010 field camp session with no GPS or GIS use. The students in both groups had the similar geologic backgrounds, similar grade point averages, and similar overall performances at field camp. However, the group that used digital mapping techniques mapped the field area more quickly and reportedly with greater ease. Additionally, the students who used GPS and GIS included more detailed rock descriptions with their final maps indicating that they spent less time in the field focusing on mapping contacts between units. The outcome was a better overall product. The use of GPS units also indirectly caused the students to produce better field maps. In addition to greater ease in mapping, the use of GIS software to create maps was rewarding to the students and gave them mapping experience that is in line with industry standards.

Integrating smart roadside initiative into the V2I component of the connected vehicle program : task 3.2.

DOT National Transportation Integrated Search

2015-01-01

This document details an analysis that maps the current Connected Vehicle development effort to the SRI efforts currently underway. The document provides a mapping of how SRI incorporates into the Connected Vehicle program. This mapping is performed ...

Two States Mapping Based Time Series Neural Network Model for Compensation Prediction Residual Error

NASA Astrophysics Data System (ADS)

Jung, Insung; Koo, Lockjo; Wang, Gi-Nam

2008-11-01

The objective of this paper was to design a model of human bio signal data prediction system for decreasing of prediction error using two states mapping based time series neural network BP (back-propagation) model. Normally, a lot of the industry has been applied neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has got a residual error between real value and prediction result. Therefore, we designed two states of neural network model for compensation residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We determined that most of the simulation cases were satisfied by the two states mapping based time series prediction model. In particular, small sample size of times series were more accurate than the standard MLP model.

Validation of a remote sensing model to identify Simulium damnosum s.l. breeding sites in Sub-Saharan Africa.

PubMed

Jacob, Benjamin G; Novak, Robert J; Toe, Laurent D; Sanfo, Moussa; Griffith, Daniel A; Lakwo, Thomson L; Habomugisha, Peace; Katabarwa, Moses N; Unnasch, Thomas R

2013-01-01

Recently, most onchocerciasis control programs have begun to focus on elimination. Developing an effective elimination strategy relies upon accurately mapping the extent of endemic foci. In areas of Africa that suffer from a lack of infrastructure and/or political instability, developing such accurate maps has been difficult. Onchocerciasis foci are localized near breeding sites for the black fly vectors of the infection. The goal of this study was to conduct ground validation studies to evaluate the sensitivity and specificity of a remote sensing model developed to predict S. damnosum s.l. breeding sites. Remote sensing images from Togo were analyzed to identify areas containing signature characteristics of S. damnosum s.l. breeding habitat. All 30 sites with the spectral signature were found to contain S. damnosum larvae, while 0/52 other sites judged as likely to contain larvae were found to contain larvae. The model was then used to predict breeding sites in Northern Uganda. This area is hyper-endemic for onchocerciasis, but political instability had precluded mass distribution of ivermectin until 2009. Ground validation revealed that 23/25 sites with the signature contained S. damnosum larvae, while 8/10 sites examined lacking the signature were larvae free. Sites predicted to have larvae contained significantly more larvae than those that lacked the signature. This study suggests that a signature extracted from remote sensing images may be used to predict the location of S. damnosum s.l. breeding sites with a high degree of accuracy. This method should be of assistance in predicting communities at risk for onchocerciasis in areas of Africa where ground-based epidemiological surveys are difficult to implement.

Validation of a Remote Sensing Model to Identify Simulium damnosum s.l. Breeding Sites in Sub-Saharan Africa

PubMed Central

Jacob, Benjamin G.; Novak, Robert J.; Toe, Laurent D.; Sanfo, Moussa; Griffith, Daniel A.; Lakwo, Thomson L.; Habomugisha, Peace; Katabarwa, Moses N.; Unnasch, Thomas R.

2013-01-01

Background Recently, most onchocerciasis control programs have begun to focus on elimination. Developing an effective elimination strategy relies upon accurately mapping the extent of endemic foci. In areas of Africa that suffer from a lack of infrastructure and/or political instability, developing such accurate maps has been difficult. Onchocerciasis foci are localized near breeding sites for the black fly vectors of the infection. The goal of this study was to conduct ground validation studies to evaluate the sensitivity and specificity of a remote sensing model developed to predict S. damnosum s.l. breeding sites. Methodology/Principal Findings Remote sensing images from Togo were analyzed to identify areas containing signature characteristics of S. damnosum s.l. breeding habitat. All 30 sites with the spectral signature were found to contain S. damnosum larvae, while 0/52 other sites judged as likely to contain larvae were found to contain larvae. The model was then used to predict breeding sites in Northern Uganda. This area is hyper-endemic for onchocerciasis, but political instability had precluded mass distribution of ivermectin until 2009. Ground validation revealed that 23/25 sites with the signature contained S. damnosum larvae, while 8/10 sites examined lacking the signature were larvae free. Sites predicted to have larvae contained significantly more larvae than those that lacked the signature. Conclusions/Significance This study suggests that a signature extracted from remote sensing images may be used to predict the location of S. damnosum s.l. breeding sites with a high degree of accuracy. This method should be of assistance in predicting communities at risk for onchocerciasis in areas of Africa where ground-based epidemiological surveys are difficult to implement. PMID:23936571

WGSSAT: A High-Throughput Computational Pipeline for Mining and Annotation of SSR Markers From Whole Genomes.

PubMed

Pandey, Manmohan; Kumar, Ravindra; Srivastava, Prachi; Agarwal, Suyash; Srivastava, Shreya; Nagpure, Naresh S; Jena, Joy K; Kushwaha, Basdeo

2018-03-16

Mining and characterization of Simple Sequence Repeat (SSR) markers from whole genomes provide valuable information about biological significance of SSR distribution and also facilitate development of markers for genetic analysis. Whole genome sequencing (WGS)-SSR Annotation Tool (WGSSAT) is a graphical user interface pipeline developed using Java Netbeans and Perl scripts which facilitates in simplifying the process of SSR mining and characterization. WGSSAT takes input in FASTA format and automates the prediction of genes, noncoding RNA (ncRNA), core genes, repeats and SSRs from whole genomes followed by mapping of the predicted SSRs onto a genome (classified according to genes, ncRNA, repeats, exonic, intronic, and core gene region) along with primer identification and mining of cross-species markers. The program also generates a detailed statistical report along with visualization of mapped SSRs, genes, core genes, and RNAs. The features of WGSSAT were demonstrated using Takifugu rubripes data. This yielded a total of 139 057 SSR, out of which 113 703 SSR primer pairs were uniquely amplified in silico onto a T. rubripes (fugu) genome. Out of 113 703 mined SSRs, 81 463 were from coding region (including 4286 exonic and 77 177 intronic), 7 from RNA, 267 from core genes of fugu, whereas 105 641 SSR and 601 SSR primer pairs were uniquely mapped onto the medaka genome. WGSSAT is tested under Ubuntu Linux. The source code, documentation, user manual, example dataset and scripts are available online at https://sourceforge.net/projects/wgssat-nbfgr.

The Probabilities of Unique Events

PubMed Central

Khemlani, Sangeet S.; Lotstein, Max; Johnson-Laird, Phil

2012-01-01

Many theorists argue that the probabilities of unique events, even real possibilities such as President Obama's re-election, are meaningless. As a consequence, psychologists have seldom investigated them. We propose a new theory (implemented in a computer program) in which such estimates depend on an intuitive non-numerical system capable only of simple procedures, and a deliberative system that maps intuitions into numbers. The theory predicts that estimates of the probabilities of conjunctions should often tend to split the difference between the probabilities of the two conjuncts. We report two experiments showing that individuals commit such violations of the probability calculus, and corroborating other predictions of the theory, e.g., individuals err in the same way even when they make non-numerical verbal estimates, such as that an event is highly improbable. PMID:23056224

An analytical analysis of the dispersion predictions for effluents from the Saturn 5 and Scout-Algol 3 rocket exhausts

NASA Technical Reports Server (NTRS)

Stephens, J. B.; Susko, M.; Kaufman, J. W.; Hill, C. K.

1973-01-01

Predictions of the spatial concentration mapping of the potentially toxic constituents of the exhaust effluents from a launch of a Saturn 5 and of a Scout-Algol 3 vehicle utilizing the NASA/MSFC Multilayer Diffusion Program are provided. In the case of the Saturn 5, special attention was given to the concentration fields of carbon monoxide with a correlation of carbon dioxide concentrations. The Scout-Algol 3 provided an example of the centerline concentrations of hydrogen chloride, carbon monoxide, and alumina under typical meteorological conditions. While these results define the specific environmental impact of these two launches under the meteorological conditions existing during launches, they also provide a basis for the empirical monitoring of the constituents of the exhaust effluents of these vehicles.

Mapping students' ideas to understand learning in a collaborative programming environment

NASA Astrophysics Data System (ADS)

Harlow, Danielle Boyd; Leak, Anne Emerson

2014-07-01

Recent studies in learning programming have largely focused on high school and college students; less is known about how young children learn to program. From video data of 20 students using a graphical programming interface, we identified ideas that were shared and evolved through an elementary school classroom. In mapping these ideas and their resulting changes in programs and outputs, we were able to identify the contextual features which contributed to how ideas moved through the classroom as students learned. We suggest this process of idea mapping in visual programming environments as a viable method for understanding collaborative, constructivist learning as well as a context under which experiences can be developed to improve student learning.

Arguing for a multi-hazard mapping program in Newfoundland and Labrador, Canada

NASA Astrophysics Data System (ADS)

Batterson, Martin; Neil, Stapleton

2010-05-01

This poster describes efforts to implement a Provincial multi-hazard mapping program, and will explore the challenges associated with this process. Newfoundland and Labrador is on the eastern edge of North America, has a large land area (405,212 km2) and a small population (510,000; 2009 estimate). The province currently has no legislative framework to control development in hazardous areas, but recent landslides in the communities of Daniel's Harbour and Trout River, both of which forced the relocation of residents, emphasize the need for action. There are two factors which confirm the need for a natural hazard mapping program: the documented history of natural disasters, and the future potential impacts of climate change. Despite being relatively far removed from the impacts of earthquake and volcanic activity, Newfoundland and Labrador has a long history of natural disasters. Rockfall, landslide, avalanche and flood events have killed at least 176 people over the past 225 years, many in their own homes. Some of the fatalities resulted from the adjacency of homes to places of employment, and of communities and roads to steep slopes. Others were likely the result of chance, and were thus unavoidable. Still others were the result of poor planning, albeit unwitting. Increasingly however, aesthetics have replaced pragmatism as a selection criterion for housing developments, with residential construction being contemplated for many coastal areas. The issue is exacerbated by the impacts of climate change, which while not a universal bane for the Province, will likely result in rising sea level and enhanced coastal erosion. Much of the Province's coastline is receding at up to 30 cm (and locally higher) per year. Sea level is anticipated to rise by 70cm to over 100 cm by 2099, based on IPCC predictions, plus the effects of enhanced ice sheet melting, plus (or minus) continued local isostatic adjustment. The history of geological disasters, coupled with pressures on development and the threat of rising sea levels, has prompted the initiation of a Provincial multi-hazard mapping program. Initial focus is on the north-east Avalon Peninsula, where the majority of the Province's residents are located and where most development is occurring. A regional land-use plan is being initiated for this area. While there are few, if any, standard protocols in literature for determining variables/data to be included in a hazard assessment, three important factors require consideration: the characteristics and detail of the study area, the availability of digital datasets, and the scale of data. For the north-east Avalon Peninsula hazard mapping will combine slope models generated from DEMs, bedrock/surficial geology mapping at 1:50,000 scale, Provincial flood risk mapping and municipal digital topographic data at 1:2500 scale, and historical research and field work, to produce a ‘traffic-light' designation of potentially hazardous areas. Data will be presented in an ArcGIS environment. Sea-level rise scenarios will also be incorporated into the mapping. Following the experience of flood risk mapping in the Province, which identified hazardous areas for development which nevertheless continued to experience urban expansion, subsequently ensuring the utilization of these maps in future land-use planning will likely require entrenchment in legislation.

Tile prediction schemes for wide area motion imagery maps in GIS

NASA Astrophysics Data System (ADS)

Michael, Chris J.; Lin, Bruce Y.

2017-11-01

Wide-area surveillance, traffic monitoring, and emergency management are just several of many applications benefiting from the incorporation of Wide-Area Motion Imagery (WAMI) maps into geographic information systems. Though the use of motion imagery as a GIS base map via the Web Map Service (WMS) standard is not a new concept, effectively streaming imagery is particularly challenging due to its large scale and the multidimensionally interactive nature of clients that use WMS. Ineffective streaming from a server to one or more clients can unnecessarily overwhelm network bandwidth and cause frustratingly large amounts of latency in visualization to the user. Seamlessly streaming WAMI through GIS requires good prediction to accurately guess the tiles of the video that will be traversed in the near future. In this study, we present an experimental framework for such prediction schemes by presenting a stochastic interaction model that represents a human user's interaction with a GIS video map. We then propose several algorithms by which the tiles of the stream may be predicted. Results collected both within the experimental framework and using human analyst trajectories show that, though each algorithm thrives under certain constraints, the novel Markovian algorithm yields the best results overall. Furthermore, we make the argument that the proposed experimental framework is sufficient for the study of these prediction schemes.

Efficient Swath Mapping Laser Altimetry Demonstration Instrument Incubator Program

NASA Technical Reports Server (NTRS)

Yu, Anthony W.; Krainak, Michael A,; Harding, David J.; Abshire, James B.; Sun, Xiaoli; Cavanaugh, John; Valett, Susan

2010-01-01

In this paper we will discuss our eighteen-month progress of a three-year Instrument Incubator Program (IIP) funded by NASA Earth Science Technology Office (ESTO) on swath mapping laser altimetry system. This paper will discuss the system approach, enabling technologies and instrument concept for the swath mapping laser altimetry.

Ripple Effect Mapping: A "Radiant" Way to Capture Program Impacts

ERIC Educational Resources Information Center

Kollock, Debra Hansen; Flage, Lynette; Chazdon, Scott; Paine, Nathan; Higgins, Lorie

2012-01-01

Learn more about a promising follow-up, participatory group process designed to document the results of Extension educational efforts within complex, real-life settings. The method, known as Ripple Effect Mapping, uses elements of Appreciative Inquiry, mind mapping, and qualitative data analysis to engage program participants and other community…

Approximating prediction uncertainty for random forest regression models

Treesearch

John W. Coulston; Christine E. Blinn; Valerie A. Thomas; Randolph H. Wynne

2016-01-01

Machine learning approaches such as random forest have increased for the spatial modeling and mapping of continuous variables. Random forest is a non-parametric ensemble approach, and unlike traditional regression approaches there is no direct quantification of prediction error. Understanding prediction uncertainty is important when using model-based continuous maps as...

Modeling and Prediction of Wildfire Hazard in Southern California, Integration of Models with Imaging Spectrometry

NASA Technical Reports Server (NTRS)

Roberts, Dar A.; Church, Richard; Ustin, Susan L.; Brass, James A. (Technical Monitor)

2001-01-01

Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated into standard fuel models accessible to the FARSITE fire spread simulator. The FARSITE model and BEHAVE are considered industry standards for fire behavior analysis. Anderson level fuels map, generated using a binary decision tree classifier are available for multiple dates in the Santa Monica Mountains and at least one date for Santa Barbara. Fuel maps that will fill in the areas between Santa Barbara and the Santa Monica Mountains study sites are in progress, as part of a NASA Regional Earth Science Application Center, the Southern California Wildfire Hazard Center. Species-level maps, were supplied to fire managing agencies (Los Angeles County Fire, California Department of Forestry). Research results were published extensively in the refereed and non-refereed literature. Educational outreach included funding of several graduate students, undergraduate intern training and an article featured in the California Alliance for Minorities Program (CAMP) Quarterly Journal.

United States Air Force Statistical Digest, Fiscal Year 1965, Twentieth Edition

DTIC Science & Technology

1965-09-30

prOVided by the USAF under Military Assistance Program . MAP EMPLOYEES - Category of civilian personnel engaged in activities reqUired in carrying out the...92 - USAF CIVIUAN EMPLOYEES IN SALARIED AND WAGE BOARD GROUPS EMPLOYED UNDER MILITARY ASSISTANCE PROGRAM (MAP), WORLO-WIDE, AT END OF QUARTER - FY...statistical material for tary Assistance Program (MAP), and re- the digest. AFCHO will furnish a chronology lated studies and historical events. of

Use of a ground-water flow model with particle tracking to evaluate ground-water vulnerability, Clark County, Washington

USGS Publications Warehouse

Snyder, D.T.; Wilkinson, J.M.; Orzol, L.L.

1996-01-01

A ground-water flow model was used in conjunction with particle tracking to evaluate ground-water vulnerability in Clark County, Washington. Using the particle-tracking program, particles were placed in every cell of the flow model (about 60,000 particles) and tracked backwards in time and space upgradient along flow paths to their recharge points. A new computer program was developed that interfaces the results from a particle-tracking program with a geographic information system (GIS). The GIS was used to display and analyze the particle-tracking results. Ground-water vulnerability was evaluated by selecting parts of the ground-water flow system and combining the results with ancillary information stored in the GIS to determine recharge areas, characteristics of recharge areas, downgradient impact of land use at recharge areas, and age of ground water. Maps of the recharge areas for each hydrogeologic unit illustrate the presence of local, intermediate, or regional ground-water flow systems and emphasize the three-dimensional nature of the ground-water flow system in Clark County. Maps of the recharge points for each hydrogeologic unit were overlaid with maps depicting aquifer sensitivity as determined by DRASTIC (a measure of the pollution potential of ground water, based on the intrinsic characteristics of the near-surface unsaturated and saturated zones) and recharge from on-site waste-disposal systems. A large number of recharge areas were identified, particularly in southern Clark County, that have a high aquifer sensitivity, coincide with areas of recharge from on-site waste-disposal systems, or both. Using the GIS, the characteristics of the recharge areas were related to the downgradient parts of the ground-water system that will eventually receive flow that has recharged through these areas. The aquifer sensitivity, as indicated by DRASTIC, of the recharge areas for downgradient parts of the flow system was mapped for each hydrogeologic unit. A number of public-supply wells in Clark County may be receiving a component of water that recharged in areas that are more conducive to contaminant entry. The aquifer sensitivity maps illustrate a critical deficiency in the DRASTIC methodology: the failure to account for the dynamics of the ground-water flow system. DRASTIC indices calculated for a particular location thus do not necessarily reflect the conditions of the ground-water resources at the recharge areas to that particular location. Each hydrogeologic unit was also mapped to highlight those areas that will eventually receive flow from recharge areas with on-site waste-disposal systems. Most public-supply wells in southern Clark County may eventually receive a component of water that was recharged from on-site waste-disposal systems.Traveltimes from particle tracking were used to estimate the minimum and maximum age of ground water within each model-grid cell. Chlorofluorocarbon (CFC)-age dating of ground water from 51 wells was used to calibrate effective porosity values used for the particle- tracking program by comparison of ground-water ages determined through the use of the CFC-age dating with those calculated by the particle- tracking program. There was a 76 percent agreement in predicting the presence of modern water in the 51 wells as determined using CFCs and calculated by the particle-tracking program. Maps showing the age of ground water were prepared for all the hydrogeologic units. Areas with the youngest ground-water ages are expected to be at greatest risk for contamination from anthropogenic sources. Comparison of these maps with maps of public- supply wells in Clark County indicates that most of these wells may withdraw ground water that is, in part, less than 100 years old, and in many instances less than 10 years old. Results of the analysis showed that a single particle-tracking analysis simulating advective transport can be used to evaluate ground-water vulnerability for any part of a ground-wate

BRCA-Monet: a breast cancer specific drug treatment mode-of-action network for treatment effective prediction using large scale microarray database.

PubMed

Ma, Chifeng; Chen, Hung-I; Flores, Mario; Huang, Yufei; Chen, Yidong

2013-01-01

Connectivity map (cMap) is a recent developed dataset and algorithm for uncovering and understanding the treatment effect of small molecules on different cancer cell lines. It is widely used but there are still remaining challenges for accurate predictions. Here, we propose BRCA-MoNet, a network of drug mode of action (MoA) specific to breast cancer, which is constructed based on the cMap dataset. A drug signature selection algorithm fitting the characteristic of cMap data, a quality control scheme as well as a novel query algorithm based on BRCA-MoNet are developed for more effective prediction of drug effects. BRCA-MoNet was applied to three independent data sets obtained from the GEO database: Estrodial treated MCF7 cell line, BMS-754807 treated MCF7 cell line, and a breast cancer patient microarray dataset. In the first case, BRCA-MoNet could identify drug MoAs likely to share same and reverse treatment effect. In the second case, the result demonstrated the potential of BRCA-MoNet to reposition drugs and predict treatment effects for drugs not in cMap data. In the third case, a possible procedure of personalized drug selection is showcased. The results clearly demonstrated that the proposed BRCA-MoNet approach can provide increased prediction power to cMap and thus will be useful for identification of new therapeutic candidates.

A revised ground-motion and intensity interpolation scheme for shakemap

USGS Publications Warehouse

Worden, C.B.; Wald, D.J.; Allen, T.I.; Lin, K.; Garcia, D.; Cua, G.

2010-01-01

We describe a weighted-average approach for incorporating various types of data (observed peak ground motions and intensities and estimates from groundmotion prediction equations) into the ShakeMap ground motion and intensity mapping framework. This approach represents a fundamental revision of our existing ShakeMap methodology. In addition, the increased availability of near-real-time macroseismic intensity data, the development of newrelationships between intensity and peak ground motions, and new relationships to directly predict intensity from earthquake source information have facilitated the inclusion of intensity measurements directly into ShakeMap computations. Our approach allows for the combination of (1) direct observations (ground-motion measurements or reported intensities), (2) observations converted from intensity to ground motion (or vice versa), and (3) estimated ground motions and intensities from prediction equations or numerical models. Critically, each of the aforementioned data types must include an estimate of its uncertainties, including those caused by scaling the influence of observations to surrounding grid points and those associated with estimates given an unknown fault geometry. The ShakeMap ground-motion and intensity estimates are an uncertainty-weighted combination of these various data and estimates. A natural by-product of this interpolation process is an estimate of total uncertainty at each point on the map, which can be vital for comprehensive inventory loss calculations. We perform a number of tests to validate this new methodology and find that it produces a substantial improvement in the accuracy of ground-motion predictions over empirical prediction equations alone.

RCrane: semi-automated RNA model building.

PubMed

Keating, Kevin S; Pyle, Anna Marie

2012-08-01

RNA crystals typically diffract to much lower resolutions than protein crystals. This low-resolution diffraction results in unclear density maps, which cause considerable difficulties during the model-building process. These difficulties are exacerbated by the lack of computational tools for RNA modeling. Here, RCrane, a tool for the partially automated building of RNA into electron-density maps of low or intermediate resolution, is presented. This tool works within Coot, a common program for macromolecular model building. RCrane helps crystallographers to place phosphates and bases into electron density and then automatically predicts and builds the detailed all-atom structure of the traced nucleotides. RCrane then allows the crystallographer to review the newly built structure and select alternative backbone conformations where desired. This tool can also be used to automatically correct the backbone structure of previously built nucleotides. These automated corrections can fix incorrect sugar puckers, steric clashes and other structural problems.

A genetic algorithm-based job scheduling model for big data analytics.

PubMed

Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

Using a combined computational-experimental approach to predict antibody-specific B cell epitopes.

PubMed

Sela-Culang, Inbal; Benhnia, Mohammed Rafii-El-Idrissi; Matho, Michael H; Kaever, Thomas; Maybeno, Matt; Schlossman, Andrew; Nimrod, Guy; Li, Sheng; Xiang, Yan; Zajonc, Dirk; Crotty, Shane; Ofran, Yanay; Peters, Bjoern

2014-04-08

Antibody epitope mapping is crucial for understanding B cell-mediated immunity and required for characterizing therapeutic antibodies. In contrast to T cell epitope mapping, no computational tools are in widespread use for prediction of B cell epitopes. Here, we show that, utilizing the sequence of an antibody, it is possible to identify discontinuous epitopes on its cognate antigen. The predictions are based on residue-pairing preferences and other interface characteristics. We combined these antibody-specific predictions with results of cross-blocking experiments that identify groups of antibodies with overlapping epitopes to improve the predictions. We validate the high performance of this approach by mapping the epitopes of a set of antibodies against the previously uncharacterized D8 antigen, using complementary techniques to reduce method-specific biases (X-ray crystallography, peptide ELISA, deuterium exchange, and site-directed mutagenesis). These results suggest that antibody-specific computational predictions and simple cross-blocking experiments allow for accurate prediction of residues in conformational B cell epitopes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Exploring discrepancies between quantitative validation results and the geomorphic plausibility of statistical landslide susceptibility maps

NASA Astrophysics Data System (ADS)

Steger, Stefan; Brenning, Alexander; Bell, Rainer; Petschko, Helene; Glade, Thomas

2016-06-01

Empirical models are frequently applied to produce landslide susceptibility maps for large areas. Subsequent quantitative validation results are routinely used as the primary criteria to infer the validity and applicability of the final maps or to select one of several models. This study hypothesizes that such direct deductions can be misleading. The main objective was to explore discrepancies between the predictive performance of a landslide susceptibility model and the geomorphic plausibility of subsequent landslide susceptibility maps while a particular emphasis was placed on the influence of incomplete landslide inventories on modelling and validation results. The study was conducted within the Flysch Zone of Lower Austria (1,354 km2) which is known to be highly susceptible to landslides of the slide-type movement. Sixteen susceptibility models were generated by applying two statistical classifiers (logistic regression and generalized additive model) and two machine learning techniques (random forest and support vector machine) separately for two landslide inventories of differing completeness and two predictor sets. The results were validated quantitatively by estimating the area under the receiver operating characteristic curve (AUROC) with single holdout and spatial cross-validation technique. The heuristic evaluation of the geomorphic plausibility of the final results was supported by findings of an exploratory data analysis, an estimation of odds ratios and an evaluation of the spatial structure of the final maps. The results showed that maps generated by different inventories, classifiers and predictors appeared differently while holdout validation revealed similar high predictive performances. Spatial cross-validation proved useful to expose spatially varying inconsistencies of the modelling results while additionally providing evidence for slightly overfitted machine learning-based models. However, the highest predictive performances were obtained for maps that explicitly expressed geomorphically implausible relationships indicating that the predictive performance of a model might be misleading in the case a predictor systematically relates to a spatially consistent bias of the inventory. Furthermore, we observed that random forest-based maps displayed spatial artifacts. The most plausible susceptibility map of the study area showed smooth prediction surfaces while the underlying model revealed a high predictive capability and was generated with an accurate landslide inventory and predictors that did not directly describe a bias. However, none of the presented models was found to be completely unbiased. This study showed that high predictive performances cannot be equated with a high plausibility and applicability of subsequent landslide susceptibility maps. We suggest that greater emphasis should be placed on identifying confounding factors and biases in landslide inventories. A joint discussion between modelers and decision makers of the spatial pattern of the final susceptibility maps in the field might increase their acceptance and applicability.

Functional materials discovery using energy-structure-function maps

NASA Astrophysics Data System (ADS)

Pulido, Angeles; Chen, Linjiang; Kaczorowski, Tomasz; Holden, Daniel; Little, Marc A.; Chong, Samantha Y.; Slater, Benjamin J.; McMahon, David P.; Bonillo, Baltasar; Stackhouse, Chloe J.; Stephenson, Andrew; Kane, Christopher M.; Clowes, Rob; Hasell, Tom; Cooper, Andrew I.; Day, Graeme M.

2017-03-01

Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy-structure-function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy-structure-function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.

Functional materials discovery using energy-structure-function maps.

PubMed

Pulido, Angeles; Chen, Linjiang; Kaczorowski, Tomasz; Holden, Daniel; Little, Marc A; Chong, Samantha Y; Slater, Benjamin J; McMahon, David P; Bonillo, Baltasar; Stackhouse, Chloe J; Stephenson, Andrew; Kane, Christopher M; Clowes, Rob; Hasell, Tom; Cooper, Andrew I; Day, Graeme M

2017-03-30

Molecular crystals cannot be designed in the same manner as macroscopic objects, because they do not assemble according to simple, intuitive rules. Their structures result from the balance of many weak interactions, rather than from the strong and predictable bonding patterns found in metal-organic frameworks and covalent organic frameworks. Hence, design strategies that assume a topology or other structural blueprint will often fail. Here we combine computational crystal structure prediction and property prediction to build energy-structure-function maps that describe the possible structures and properties that are available to a candidate molecule. Using these maps, we identify a highly porous solid, which has the lowest density reported for a molecular crystal so far. Both the structure of the crystal and its physical properties, such as methane storage capacity and guest-molecule selectivity, are predicted using the molecular structure as the only input. More generally, energy-structure-function maps could be used to guide the experimental discovery of materials with any target function that can be calculated from predicted crystal structures, such as electronic structure or mechanical properties.

GDAP: a web tool for genome-wide protein disulfide bond prediction.

PubMed

O'Connor, Brian D; Yeates, Todd O

2004-07-01

The Genomic Disulfide Analysis Program (GDAP) provides web access to computationally predicted protein disulfide bonds for over one hundred microbial genomes, including both bacterial and achaeal species. In the GDAP process, sequences of unknown structure are mapped, when possible, to known homologous Protein Data Bank (PDB) structures, after which specific distance criteria are applied to predict disulfide bonds. GDAP also accepts user-supplied protein sequences and subsequently queries the PDB sequence database for the best matches, scans for possible disulfide bonds and returns the results to the client. These predictions are useful for a variety of applications and have previously been used to show a dramatic preference in certain thermophilic archaea and bacteria for disulfide bonds within intracellular proteins. Given the central role these stabilizing, covalent bonds play in such organisms, the predictions available from GDAP provide a rich data source for designing site-directed mutants with more stable thermal profiles. The GDAP web application is a gateway to this information and can be used to understand the role disulfide bonds play in protein stability both in these unusual organisms and in sequences of interest to the individual researcher. The prediction server can be accessed at http://www.doe-mbi.ucla.edu/Services/GDAP.

Wave rotor demonstrator engine assessment

NASA Technical Reports Server (NTRS)

Snyder, Philip H.

1996-01-01

The objective of the program was to determine a wave rotor demonstrator engine concept using the Allison 250 series engine. The results of the NASA LERC wave rotor effort were used as a basis for the wave rotor design. A wave rotor topped gas turbine engine was identified which incorporates five basic requirements of a successful demonstrator engine. Predicted performance maps of the wave rotor cycle were used along with maps of existing gas turbine hardware in a design point study. The effects of wave rotor topping on the engine cycle and the subsequent need to rematch compressor and turbine sections in the topped engine were addressed. Comparison of performance of the resulting engine is made on the basis of wave rotor topped engine versus an appropriate baseline engine using common shaft compressor hardware. The topped engine design clearly demonstrates an impressive improvement in shaft horsepower (+11.4%) and SFC (-22%). Off design part power engine performance for the wave rotor topped engine was similarly improved including that at engine idle conditions. Operation of the engine at off design was closely examined with wave rotor operation at less than design burner outlet temperatures and rotor speeds. Challenges identified in the development of a demonstrator engine are discussed. A preliminary design was made of the demonstrator engine including wave rotor to engine transition ducts. Program cost and schedule for a wave rotor demonstrator engine fabrication and test program were developed.

Mapping Coastal Flood Zones for the National Flood Insurance Program

NASA Astrophysics Data System (ADS)

Carlton, D.; Cook, C. L.; Weber, J.

2004-12-01

The National Flood Insurance Program (NFIP) was created by Congress in 1968, and significantly amended in 1973 to reduce loss of life and property caused by flooding, reduce disaster relief costs caused by flooding and make Federally backed flood insurance available to property owners. These goals were to be achieved by requiring building to be built to resist flood damages, guide construction away from flood hazards, and transferring the cost of flood losses from taxpayers to policyholders. Areas subject to flood hazards were defined as those areas that have a probability greater than 1 percent of being inundated in any given year. Currently over 19,000 communities participate in the NFIP, many of them coastal communities subject to flooding from tides, storm surge, waves, or tsunamis. The mapping of coastal hazard areas began in the early 1970's and has been evolving ever since. At first only high tides and storm surge were considered in determining the hazardous areas. Then, after significant wave caused storm damage to structures outside of the mapped hazard areas wave hazards were also considered. For many years FEMA has had Guidelines and Specifications for mapping coastal hazards for the East Coast and the Gulf Coast. In September of 2003 a study was begun to develop similar Guidelines and Specifications for the Pacific Coast. Draft Guidelines and Specifications will be delivered to FEMA by September 30, 2004. During the study tsunamis were identified as a potential source of a 1 percent flood event on the West Coast. To better understand the analytical results, and develop adequate techniques to estimate the magnitude of a tsunami with a 1 percent probability of being equaled or exceeded in any year, a pilot study has begun at Seaside Oregon. Both the onshore velocity and the resulting wave runup are critical functions for FEMA to understand and potentially map. The pilot study is a cooperative venture between NOAA and USGS that is partially funded by both agencies and by FEMA. The results of the pilot study will help FEMA determine when tsunamis should be considered in mapping coastal hazards, how to predict their impact, how they should be mapped and possibly the construction standards for zones mapped as having a 1 percent or greater chance of suffering a tsunami.

Promoting Diversity in STEM through Active Recruiting and Mentoring: The Pre-Major in Astronomy Program (Pre-MAP) at the University of Washington

NASA Astrophysics Data System (ADS)

Schwieterman, Edward; Binder, Breanna; Tremmel, Michael; Garofali, Kristen; Agol, Eric; Meadows, Victoria

2015-11-01

The Pre-Major in Astronomy Program (Pre-MAP) is a research and mentoring program for underclassmen and transfer students offered by the University of Washington Astronomy Department since 2005. The primary goal of Pre-MAP is to recruit and retain students from groups traditionally underrepresented in science, technology, engineering, and mathematics (STEM) through early exposure to research. The Pre-MAP seminar is the core component of the program and offers instruction in computing skills, data manipulation, science writing, statistical analysis, and scientific speaking and presentation skills. Students choose research projects proposed by faculty, post-docs and graduate students in areas related to astrophysics, planetary science, and astrobiology. Pre-MAP has been successful in retaining underrepresented students in STEM fields relative to the broader UW population, and we've found these students are more likely to graduate and excel academically than their peers. As of spring 2015, more than one hundred students have taken the Pre-MAP seminar, and both internal and external evaluations have shown that all groups of participating students report an increased interest in astronomy and science careers at the end of the seminar. Several former Pre-MAP students have obtained or are pursuing doctoral and master’s degrees in STEM fields; many more work at NASA centers, teaching colleges, or as engineers or data analysts. Pre- MAP student research has produced dozens of publications in peer-reviewed research journals. This talk will provide an overview of the program: the structure of the seminar, examples of projects completed by students, cohort-building activities outside the seminar, funding sources, recruitment strategies, and the aggregate demographic and achievement data of our students. It is our hope that similar programs may be adopted successfully at other institutions.

Design and application of star map simulation system for star sensors

NASA Astrophysics Data System (ADS)

Wu, Feng; Shen, Weimin; Zhu, Xifang; Chen, Yuheng; Xu, Qinquan

2013-12-01

Modern star sensors are powerful to measure attitude automatically which assure a perfect performance of spacecrafts. They achieve very accurate attitudes by applying algorithms to process star maps obtained by the star camera mounted on them. Therefore, star maps play an important role in designing star cameras and developing procession algorithms. Furthermore, star maps supply significant supports to exam the performance of star sensors completely before their launch. However, it is not always convenient to supply abundant star maps by taking pictures of the sky. Thus, star map simulation with the aid of computer attracts a lot of interests by virtue of its low price and good convenience. A method to simulate star maps by programming and extending the function of the optical design program ZEMAX is proposed. The star map simulation system is established. Firstly, based on analyzing the working procedures of star sensors to measure attitudes and the basic method to design optical system by ZEMAX, the principle of simulating star sensor imaging is given out in detail. The theory about adding false stars and noises, and outputting maps is discussed and the corresponding approaches are proposed. Then, by external programming, the star map simulation program is designed and produced. Its user interference and operation are introduced. Applications of star map simulation method in evaluating optical system, star image extraction algorithm and star identification algorithm, and calibrating system errors are presented completely. It was proved that the proposed simulation method provides magnificent supports to the study on star sensors, and improves the performance of star sensors efficiently.

Computer Programs to Display and Modify Data in Geographic Coordinates and Methods to Transfer Positions to and from Maps, with Applications to Gravity Data Processing, Global Positioning Systems, and 30-Meter Digital Elevation Models

USGS Publications Warehouse

Plouff, Donald

1998-01-01

Computer programs were written in the Fortran language to process and display gravity data with locations expressed in geographic coordinates. The programs and associated processes have been tested for gravity data in an area of about 125,000 square kilometers in northwest Nevada, southeast Oregon, and northeast California. This report discusses the geographic aspects of data processing. Utilization of the programs begins with application of a template (printed in PostScript format) to transfer locations obtained with Global Positioning Systems to and from field maps and includes a 5-digit geographic-based map naming convention for field maps. Computer programs, with source codes that can be copied, are used to display data values (printed in PostScript format) and data coverage, insert data into files, extract data from files, shift locations, test for redundancy, and organize data by map quadrangles. It is suggested that 30-meter Digital Elevation Models needed for gravity terrain corrections and other applications should be accessed in a file search by using the USGS 7.5-minute map name as a file name, for example, file '40117_B8.DEM' contains elevation data for the map with a southeast corner at lat 40? 07' 30' N. and lon 117? 52' 30' W.

MSD-MAP: A Network-Based Systems Biology Platform for Predicting Disease-Metabolite Links.

PubMed

Wathieu, Henri; Issa, Naiem T; Mohandoss, Manisha; Byers, Stephen W; Dakshanamurthy, Sivanesan

2017-01-01

Cancer-associated metabolites result from cell-wide mechanisms of dysregulation. The field of metabolomics has sought to identify these aberrant metabolites as disease biomarkers, clues to understanding disease mechanisms, or even as therapeutic agents. This study was undertaken to reliably predict metabolites associated with colorectal, esophageal, and prostate cancers. Metabolite and disease biological action networks were compared in a computational platform called MSD-MAP (Multi Scale Disease-Metabolite Association Platform). Using differential gene expression analysis with patient-based RNAseq data from The Cancer Genome Atlas, genes up- or down-regulated in cancer compared to normal tissue were identified. Relational databases were used to map biological entities including pathways, functions, and interacting proteins, to those differential disease genes. Similar relational maps were built for metabolites, stemming from known and in silico predicted metabolite-protein associations. The hypergeometric test was used to find statistically significant relationships between disease and metabolite biological signatures at each tier, and metabolites were assessed for multi-scale association with each cancer. Metabolite networks were also directly associated with various other diseases using a disease functional perturbation database. Our platform recapitulated metabolite-disease links that have been empirically verified in the scientific literature, with network-based mapping of jointly-associated biological activity also matching known disease mechanisms. This was true for colorectal, esophageal, and prostate cancers, using metabolite action networks stemming from both predicted and known functional protein associations. By employing systems biology concepts, MSD-MAP reliably predicted known cancermetabolite links, and may serve as a predictive tool to streamline conventional metabolomic profiling methodologies. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Estimating the Health and Economic Impacts of Changes in Local Air Quality

PubMed Central

Carvour, Martha L.; Hughes, Amy E.; Fann, Neal

2018-01-01

Objectives. To demonstrate the benefits-mapping software Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE), which integrates local air quality data with previously published concentration–response and health–economic valuation functions to estimate the health effects of changes in air pollution levels and their economic consequences. Methods. We illustrate a local health impact assessment of ozone changes in the 10-county nonattainment area of the Dallas–Fort Worth region of Texas, estimating the short-term effects on mortality predicted by 2 scenarios for 3 years (2008, 2011, and 2013): an incremental rollback of the daily 8-hour maximum ozone levels of all area monitors by 10 parts per billion and a rollback-to-a-standard ambient level of 65 parts per billion at only monitors above that level. Results. Estimates of preventable premature deaths attributable to ozone air pollution obtained by the incremental rollback method varied little by year, whereas those obtained by the rollback-to-a-standard method varied by year and were sensitive to the choice of ordinality and the use of preloaded or imported data. Conclusions. BenMAP-CE allows local and regional public health analysts to generate timely, evidence-based estimates of the health impacts and economic consequences of potential policy options in their communities. PMID:29698094

SeqTU: A web server for identification of bacterial transcription units

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Xin; Chou, Wen -Chi; Ma, Qin

A transcription unit (TU) consists of K ≥ 1 consecutive genes on the same strand of a bacterial genome that are transcribed into a single mRNA molecule under certain conditions. Their identification is an essential step in elucidation of transcriptional regulatory networks. We have recently developed a machine-learning method to accurately identify TUs from RNA-seq data, based on two features of the assembled RNA reads: the continuity and stability of RNA-seq coverage across a genomic region. While good performance was achieved by the method on Escherichia coli and Clostridium thermocellum, substantial work is needed to make the program generally applicablemore » to all bacteria, knowing that the program requires organism specific information. A web server, named SeqTU, was developed to automatically identify TUs with given RNA-seq data of any bacterium using a machine-learning approach. The server consists of a number of utility tools, in addition to TU identification, such as data preparation, data quality check and RNA-read mapping. SeqTU provides a user-friendly interface and automated prediction of TUs from given RNA-seq data. Furthermore, the predicted TUs are displayed intuitively using HTML format along with a graphic visualization of the prediction.« less

SeqTU: A web server for identification of bacterial transcription units

DOE PAGES

Chen, Xin; Chou, Wen -Chi; Ma, Qin; ...

2017-03-07

A transcription unit (TU) consists of K ≥ 1 consecutive genes on the same strand of a bacterial genome that are transcribed into a single mRNA molecule under certain conditions. Their identification is an essential step in elucidation of transcriptional regulatory networks. We have recently developed a machine-learning method to accurately identify TUs from RNA-seq data, based on two features of the assembled RNA reads: the continuity and stability of RNA-seq coverage across a genomic region. While good performance was achieved by the method on Escherichia coli and Clostridium thermocellum, substantial work is needed to make the program generally applicablemore » to all bacteria, knowing that the program requires organism specific information. A web server, named SeqTU, was developed to automatically identify TUs with given RNA-seq data of any bacterium using a machine-learning approach. The server consists of a number of utility tools, in addition to TU identification, such as data preparation, data quality check and RNA-read mapping. SeqTU provides a user-friendly interface and automated prediction of TUs from given RNA-seq data. Furthermore, the predicted TUs are displayed intuitively using HTML format along with a graphic visualization of the prediction.« less

Computer Program for the Design and Off-Design Performance of Turbojet and Turbofan Engine Cycles

NASA Technical Reports Server (NTRS)

Morris, S. J.

1978-01-01

The rapid computer program is designed to be run in a stand-alone mode or operated within a larger program. The computation is based on a simplified one-dimensional gas turbine cycle. Each component in the engine is modeled thermo-dynamically. The component efficiencies used in the thermodynamic modeling are scaled for the off-design conditions from input design point values using empirical trends which are included in the computer code. The engine cycle program is capable of producing reasonable engine performance prediction with a minimum of computer execute time. The current computer execute time on the IBM 360/67 for one Mach number, one altitude, and one power setting is about 0.1 seconds. about 0.1 seconds. The principal assumption used in the calculation is that the compressor is operated along a line of maximum adiabatic efficiency on the compressor map. The fluid properties are computed for the combustion mixture, but dissociation is not included. The procedure included in the program is only for the combustion of JP-4, methane, or hydrogen.

Propeller performance and weight predictions appended to the Navy/NASA engine program

NASA Technical Reports Server (NTRS)

Plencner, R. M.; Senty, P.; Wickenheiser, T. J.

1983-01-01

The Navy/NASA Engine Performance (NNEP) is a general purpose computer program currently employed by government, industry and university personnel to simulate the thermodynamic cycles of turbine engines. NNEP is a modular program which has the ability to evaluate the performance of an arbitrary engine configuration defined by the user. In 1979, a program to calculate engine weight (WATE-2) was developed by Boeing's Military Division under NASA contract. This program uses a preliminary design approach to determine engine weights and dimensions. Because the thermodynamic and configuration information required by the weight code was available in NNEP, the weight code was appended to NNEP. Due to increased emphasis on fuel economy, a renewed interest has developed in propellers. This report describes the modifications developed by NASA to both NNEP and WATE-2 to determine the performance, weight and dimensions of propellers and the corresponding gearbox. The propeller performance model has three options, two of which are based on propeller map interpolation. Propeller and gearbox weights are obtained from empirical equations which may easily be modified by the user.

CPC - Monitoring & Data: Regional Climate Maps

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Information CPC Web Team HOME > Monitoring and Data > Global Climate Data & Maps > Global Regional Climate Maps Regional Climate Maps Banner The Monthly regional analyses products are usually

Fiscal Year 2013 Trails Management Program Mitigation Action Plan Annual Report, October 2013

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pava, Daniel S.

This Trails Management Program Mitigation Action Plan Annual Report (Trails MAPAR) has been prepared for the Department of Energy (DOE)/National Nuclear Security Administration (NNSA) as part of implementing the 2003 Final Environmental Assessment for the Proposed Los Alamos National Laboratory Trails Management Program (DOE 2003). The Trails Mitigation Action Plan (MAP) is now a part of the Site-Wide Environmental Impact Statement for the Continued Operation of Los Alamos National Laboratory (DOE/EIS 0380) Mitigation Action Plan (2008 SWEIS MAP) (DOE 2008). The MAP provides guidance for the continued implementation of the Trails Management Program at Los Alamos National Laboratory (LANL) andmore » integration of future mitigation actions into the 2008 SWEIS MAP to decrease impacts associated with recreational trails use at LANL. This eighth MAPAR includes a summary of Trails Management Program activities and actions during Fiscal Year (FY) 2013, from October 2012 through September 2013.« less

NOAA Office of Exploration and Research > About OER > Program Review

Science.gov Websites

Organization Guiding Documents Organizational Structure Map of Staff and Affiliate Locations Strategic Plan Media News Room OER Symposium Overview Organization Guiding Documents Organizational Structure Map of Program Review Home About OER Overview Organization Guiding Documents Organizational Structure Map of

The Map Corner.

ERIC Educational Resources Information Center

Cheyney, Arnold B.; Capone, Donald L.

This teaching resource is aimed at helping students develop the skills necessary to locate places on the earth. Designed as a collection of map skill exercises rather than a sequential program of study, this program expects that students have access to and some knowledge of how to use globes, maps, atlases, and encyclopedias. The volume contains 6…

The MAP program: building the digital terrain model.

Treesearch

R.H. Twito; R.W. Mifflin; R.J. McGaughey

1987-01-01

PLANS, a software package for integrated timber-harvest planning, uses digital terrain models to provide the topographic data needed to fit harvest and transportation designs to specific terrain. MAP, an integral program in the PLANS package, is used to construct the digital terrain models required by PLANS. MAP establishes digital terrain models using digitizer-traced...

A Developmental Mapping Program Integrating Geography and Mathematics.

ERIC Educational Resources Information Center

Muir, Sharon Pray; Cheek, Helen Neely

Presented and discussed is a model which can be used by educators who want to develop an interdisciplinary map skills program in geography and mathematics. The model assumes that most children in elementary schools perform cognitively at Piaget's concrete operational stage, that readiness for map skills can be assessed with Piagetian or…

Moraxella catarrhalis synthesizes an autotransporter that is an acid phosphatase.

PubMed

Hoopman, Todd C; Wang, Wei; Brautigam, Chad A; Sedillo, Jennifer L; Reilly, Thomas J; Hansen, Eric J

2008-02-01

Moraxella catarrhalis O35E was shown to synthesize a 105-kDa protein that has similarity to both acid phosphatases and autotransporters. The N-terminal portion of the M. catarrhalis acid phosphatase A (MapA) was most similar (the BLAST probability score was 10(-10)) to bacterial class A nonspecific acid phosphatases. The central region of the MapA protein had similarity to passenger domains of other autotransporter proteins, whereas the C-terminal portion of MapA resembled the translocation domain of conventional autotransporters. Cloning and expression of the M. catarrhalis mapA gene in Escherichia coli confirmed the presence of acid phosphatase activity in the MapA protein. The MapA protein was shown to be localized to the outer membrane of M. catarrhalis and was not detected either in the soluble cytoplasmic fraction from disrupted M. catarrhalis cells or in the spent culture supernatant fluid from M. catarrhalis. Use of the predicted MapA translocation domain in a fusion construct with the passenger domain from another predicted M. catarrhalis autotransporter confirmed the translocation ability of this MapA domain. Inactivation of the mapA gene in M. catarrhalis strain O35E reduced the acid phosphatase activity expressed by this organism, and this mutation could be complemented in trans with the wild-type mapA gene. Nucleotide sequence analysis of the mapA gene from six M. catarrhalis strains showed that this protein was highly conserved among strains of this pathogen. Site-directed mutagenesis of a critical histidine residue (H233A) in the predicted active site of the acid phosphatase domain in MapA eliminated acid phosphatase activity in the recombinant MapA protein. This is the first description of an autotransporter protein that expresses acid phosphatase activity.

Moraxella catarrhalis Synthesizes an Autotransporter That Is an Acid Phosphatase▿

PubMed Central

Hoopman, Todd C.; Wang, Wei; Brautigam, Chad A.; Sedillo, Jennifer L.; Reilly, Thomas J.; Hansen, Eric J.

2008-01-01

Moraxella catarrhalis O35E was shown to synthesize a 105-kDa protein that has similarity to both acid phosphatases and autotransporters. The N-terminal portion of the M. catarrhalis acid phosphatase A (MapA) was most similar (the BLAST probability score was 10−10) to bacterial class A nonspecific acid phosphatases. The central region of the MapA protein had similarity to passenger domains of other autotransporter proteins, whereas the C-terminal portion of MapA resembled the translocation domain of conventional autotransporters. Cloning and expression of the M. catarrhalis mapA gene in Escherichia coli confirmed the presence of acid phosphatase activity in the MapA protein. The MapA protein was shown to be localized to the outer membrane of M. catarrhalis and was not detected either in the soluble cytoplasmic fraction from disrupted M. catarrhalis cells or in the spent culture supernatant fluid from M. catarrhalis. Use of the predicted MapA translocation domain in a fusion construct with the passenger domain from another predicted M. catarrhalis autotransporter confirmed the translocation ability of this MapA domain. Inactivation of the mapA gene in M. catarrhalis strain O35E reduced the acid phosphatase activity expressed by this organism, and this mutation could be complemented in trans with the wild-type mapA gene. Nucleotide sequence analysis of the mapA gene from six M. catarrhalis strains showed that this protein was highly conserved among strains of this pathogen. Site-directed mutagenesis of a critical histidine residue (H233A) in the predicted active site of the acid phosphatase domain in MapA eliminated acid phosphatase activity in the recombinant MapA protein. This is the first description of an autotransporter protein that expresses acid phosphatase activity. PMID:18065547

78 FR 23893 - Notice of Funds Availability: Inviting Applications for the Market Access Program

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-23

... inviting proposals for the 2014 Market Access Program (MAP). The intended effect of this notice is to... Agricultural Service (FAS). The funding authority for MAP expires at the end of fiscal year 2013. This notice... program funding is reauthorized prior to that time. In the event this program is not reauthorized, or is...

Mapping Students' Ideas to Understand Learning in a Collaborative Programming Environment

ERIC Educational Resources Information Center

Harlow, Danielle Boyd; Leak, Anne Emerson

2014-01-01

Recent studies in learning programming have largely focused on high school and college students; less is known about how young children learn to program. From video data of 20 students using a graphical programming interface, we identified ideas that were shared and evolved through an elementary school classroom. In mapping these ideas and their…

Using remote sensing, ecological niche modeling, and Geographic Information Systems for Rift Valley fever risk assessment in the United States

NASA Astrophysics Data System (ADS)

Tedrow, Christine Atkins

The primary goal in this study was to explore remote sensing, ecological niche modeling, and Geographic Information Systems (GIS) as aids in predicting candidate Rift Valley fever (RVF) competent vector abundance and distribution in Virginia, and as means of estimating where risk of establishment in mosquitoes and risk of transmission to human populations would be greatest in Virginia. A second goal in this study was to determine whether the remotely-sensed Normalized Difference Vegetation Index (NDVI) can be used as a proxy variable of local conditions for the development of mosquitoes to predict mosquito species distribution and abundance in Virginia. As part of this study, a mosquito surveillance database was compiled to archive the historical patterns of mosquito species abundance in Virginia. In addition, linkages between mosquito density and local environmental and climatic patterns were spatially and temporally examined. The present study affirms the potential role of remote sensing imagery for species distribution prediction, and it demonstrates that ecological niche modeling is a valuable predictive tool to analyze the distributions of populations. The MaxEnt ecological niche modeling program was used to model predicted ranges for potential RVF competent vectors in Virginia. The MaxEnt model was shown to be robust, and the candidate RVF competent vector predicted distribution map is presented. The Normalized Difference Vegetation Index (NDVI) was found to be the most useful environmental-climatic variable to predict mosquito species distribution and abundance in Virginia. However, these results indicate that a more robust prediction is obtained by including other environmental-climatic factors correlated to mosquito densities (e.g., temperature, precipitation, elevation) with NDVI. The present study demonstrates that remote sensing and GIS can be used with ecological niche and risk modeling methods to estimate risk of virus establishment in mosquitoes and transmission to humans. Maps delineating the geographic areas in Virginia with highest risk for RVF establishment in mosquito populations and RVF disease transmission to human populations were generated in a GIS using human, domestic animal, and white-tailed deer population estimates and the MaxEnt potential RVF competent vector species distribution prediction. The candidate RVF competent vector predicted distribution and RVF risk maps presented in this study can help vector control agencies and public health officials focus Rift Valley fever surveillance efforts in geographic areas with large co-located populations of potential RVF competent vectors and human, domestic animal, and wildlife hosts. Keywords. Rift Valley fever, risk assessment, Ecological Niche Modeling, MaxEnt, Geographic Information System, remote sensing, Pearson's Product-Moment Correlation Coefficient, vectors, mosquito distribution, mosquito density, mosquito surveillance, United States, Virginia, domestic animals, white-tailed deer, ArcGIS

National Park Service vegetation inventory program: Mississippi National River and Recreation Area, Minnesota

USGS Publications Warehouse

Hop, Kevin D.; Drake, Jim; Strassman, Andrew C.; Hoy, Erin E.; Jakusz, Joseph; Menard, Shannon; Dieck, Jennifer

2015-01-01

The Mississippi National River and Recreation Area (MISS) vegetation mapping project is an initiative of the National Park Service (NPS) Vegetation Inventory Program (VIP) to classify and map vegetation types of MISS. (Note: “MISS” is also referred to as “park” throughout this report.) The goals of the project are to adequately describe and map vegetation types of the park and to provide the NPS Natural Resource Inventory and Monitoring (I&M) Program, resource managers, and biological researchers with useful baseline vegetation information.The MISS vegetation mapping project was officially started in spring 2012, with a scoping meeting wherein partners discussed project objectives, goals, and methods. Major collaborators at this meeting included staff from the NPS MISS, the NPS Great Lakes Network (GLKN), NatureServe, and the USGS Upper Midwest Environmental Sciences Center. The Minnesota Department of Natural Resources (DNR) was also in attendance. Common to all NPS VIP projects, the three main components of the MISS vegetation mapping project are as follows: (1) vegetation classification, (2) vegetation mapping, and (3) map accuracy assessment (AA). In this report, each of these fundamental components is discussed in detail.With the completion of the MISS vegetation mapping project, all nine park units within the NPS GLKN have received vegetation classification and mapping products from the NPS and USGS vegetation programs. Voyageurs National Park and Isle Royale National Park were completed during 1996–2001 (as program pilot projects) and another six park units were completed during 2004–11, including the Apostle Islands National Lakeshore, Grand Portage National Monument, Indiana Dunes National Lakeshore, Pictured Rocks National Lakeshore, Saint Croix National Scenic Riverway, and Sleeping Bear Dunes National Lakeshore.

Computational prediction of atomic structures of helical membrane proteins aided by EM maps.

PubMed

Kovacs, Julio A; Yeager, Mark; Abagyan, Ruben

2007-09-15

Integral membrane proteins pose a major challenge for protein-structure prediction because only approximately 100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane alpha-helices. However, when an intermediate-resolution electron microscopy (EM) map is available, it can be used to provide restraints which, in combination with a suitable computational protocol, make structure prediction feasible. In this work we present such a protocol, which proceeds in three stages: 1), generation of an ensemble of alpha-helices by flexible fitting into each of the density rods in the low-resolution EM map, spanning a range of rotational angles around the main helical axes and translational shifts along the density rods; 2), fast optimization of side chains and scoring of the resulting conformations; and 3), refinement of the lowest-scoring conformations with internal coordinate mechanics, by optimizing the van der Waals, electrostatics, hydrogen bonding, torsional, and solvation energy contributions. In addition, our method implements a penalty term through a so-called tethering map, derived from the EM map, which restrains the positions of the alpha-helices. The protocol was validated on three test cases: GpA, KcsA, and MscL.

Statistical mapping of count survey data

USGS Publications Warehouse

Royle, J. Andrew; Link, W.A.; Sauer, J.R.; Scott, J. Michael; Heglund, Patricia J.; Morrison, Michael L.; Haufler, Jonathan B.; Wall, William A.

2002-01-01

We apply a Poisson mixed model to the problem of mapping (or predicting) bird relative abundance from counts collected from the North American Breeding Bird Survey (BBS). The model expresses the logarithm of the Poisson mean as a sum of a fixed term (which may depend on habitat variables) and a random effect which accounts for remaining unexplained variation. The random effect is assumed to be spatially correlated, thus providing a more general model than the traditional Poisson regression approach. Consequently, the model is capable of improved prediction when data are autocorrelated. Moreover, formulation of the mapping problem in terms of a statistical model facilitates a wide variety of inference problems which are cumbersome or even impossible using standard methods of mapping. For example, assessment of prediction uncertainty, including the formal comparison of predictions at different locations, or through time, using the model-based prediction variance is straightforward under the Poisson model (not so with many nominally model-free methods). Also, ecologists may generally be interested in quantifying the response of a species to particular habitat covariates or other landscape attributes. Proper accounting for the uncertainty in these estimated effects is crucially dependent on specification of a meaningful statistical model. Finally, the model may be used to aid in sampling design, by modifying the existing sampling plan in a manner which minimizes some variance-based criterion. Model fitting under this model is carried out using a simulation technique known as Markov Chain Monte Carlo. Application of the model is illustrated using Mourning Dove (Zenaida macroura) counts from Pennsylvania BBS routes. We produce both a model-based map depicting relative abundance, and the corresponding map of prediction uncertainty. We briefly address the issue of spatial sampling design under this model. Finally, we close with some discussion of mapping in relation to habitat structure. Although our models were fit in the absence of habitat information, the resulting predictions show a strong inverse relation with a map of forest cover in the state, as expected. Consequently, the results suggest that the correlated random effect in the model is broadly representing ecological variation, and that BBS data may be generally useful for studying bird-habitat relationships, even in the presence of observer errors and other widely recognized deficiencies of the BBS.

First-trimester mean arterial blood pressure and the risk of preeclampsia: The Great Obstetrical Syndromes (GOS) study.

PubMed

Gasse, Cédric; Boutin, Amélie; Coté, Maxime; Chaillet, Nils; Bujold, Emmanuel; Demers, Suzanne

2018-04-01

To estimate the predictive value of first-trimester mean arterial pressure (MAP) for the hypertensive disorders of pregnancy (HDP). We performed a prospective cohort study of nulliparous women recruited at 11 0/7 -13 6/7  weeks. MAP was calculated from blood pressure measured on both arms simultaneously using an automated device taking a series of recordings until blood pressure stability was reached. MAP was reported as multiples of the median adjusted for gestational age. Participants were followed for development of gestational hypertension (GH), preeclampsia (PE), preterm PE (<37 weeks) and early-onset (EO) PE (<34 weeks). Receiver operating characteristic curves and the area under the curve (AUC) were used to estimate the predictive values of MAP. Multivariate logistic regressions were used to develop predictive models combining MAP and maternal characteristics. We obtained complete follow-up in 4700 (99%) out of 4749 eligible participants. GH without PE was observed in 250 (5.3%) participants, and PE in 241 (5.1%), including 33 (0.7%) preterm PE and 10 (0.2%) EO-PE. First-trimester MAP was associated with GH (AUC: 0.77; 95%CI: 0.74-0.80); term PE (0.73; 95%CI: 0.70-0.76), preterm PE (0.80; 95%CI: 0.73-0.87) and EO-PE (0.79; 95%CI: 0.62-0.96). At a 10% false-positive rate, first-trimester MAP could have predicted 39% of GH, 34% of term PE, 48% of preterm PE and 60% of EO-PE. The addition of maternal characteristics improved the predictive values (to 40%, 37%, 55% and 70%, respectively). First-trimester MAP is a strong predictor of GH and PE in nulliparous women. Copyright © 2017 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

Differences in Clinical Features of Methamphetamine Users with Persistent Psychosis and Patients with Schizophrenia.

PubMed

Wang, Liang-Jen; Lin, Shih-Ku; Chen, Yi-Chih; Huang, Ming-Chyi; Chen, Tzu-Ting; Ree, Shao-Chun; Chen, Chih-Ken

Methamphetamine exerts neurotoxic effects and elicits psychotic symptoms. This study attempted to compare clinical differences between methamphetamine users with persistent psychosis (MAP) and patients with schizophrenia. In addition, we examined the discrimination validity by using symptom clusters to differentiate between MAP and schizophrenia. We enrolled 53 MAP patients and 53 patients with schizophrenia. The psychopathology of participants was assessed using the Chinese version of the Diagnostic Interview for Genetic Studies and the 18-item Brief Psychiatric Rating Scale. Logistic regression was used to examine the predicted probability scores of different symptom combinations on discriminating between MAP and schizophrenia. The receiver operating characteristic (ROC) analyses and area under the curve (AUC) were further applied to examine the discrimination validity of the predicted probability scores on differentiating between MAP and schizophrenia. We found that MAP and schizophrenia demonstrated similar patterns of delusions. Compared to patients with schizophrenia, MAP experienced significantly higher proportions of visual hallucinations and of somatic or tactile hallucinations. However, MAP exhibited significantly lower severity in conceptual disorganization, mannerism/posturing, blunted affect, emotional withdrawal, and motor retardation compared to patients with schizophrenia. The ROC analysis showed that a predicted probability score combining the aforementioned 7 items of symptoms could significantly differentiate between MAP and schizophrenia (AUC = 0.77). Findings in the current study suggest that nuanced differences might exist in the clinical presentation of secondary psychosis (MAP) and primary psychosis (schizophrenia). Combining the symptoms as a whole may help with differential diagnosis for MAP and schizophrenia. © 2016 S. Karger AG, Basel.

COSMIC Payload in NCAR-NASPO GPS Satellite System for Severe Weather Prediction

NASA Astrophysics Data System (ADS)

Lai-Chen, C.

Severe weather, such as cyclones, heavy rainfall, outburst of cold air, etc., results in great disaster all the world. It is the mission for the scientists to design a warning system, to predict the severe weather systems and to reduce the damage of the society. In Taiwan, National Satellite Project Office (NSPO) initiated ROCSAT-3 program at 1997. She scheduled the Phase I conceptual design to determine the mission for observation weather system. Cooperating with National Center of Atmospheric Research (NCAR), NSPO involved an international cooperation research and operation program to build a 32 GPS satellites system. NCAR will offer 24 GPS satellites. The total expanse will be US 100 millions. NSPO also provide US 80 millions for launching and system engineering operation. And NCAR will be responsible for Payload Control Center and Fiducial Network. The cooperative program contract has been signed by Taiwan National Science Council, Taipei Economic Cultural Office of United States and American Institute in Taiwan. One of the payload is COSMIC, Constellation Observation System for Meteorology, Ionosphere and Climate. It is a GPS meteorology instrument system. The system will observe the weather information, e. g. electron density profiles, horizontal and vertical TEC and CFT scintillation and communication outage maps. The mission is to obtain the weather data such as vertical temperature profiles, water vapor distribution and pressure distribution over the world for global weather forecasting, especially during the severe weather period. The COSMIC Conference held on November, 1998. The export license was also issued by Department of Commerce of Unites States at November, 1998. Recently, NSPO begun to train their scientists to investigate the system. Scientists simulate the observation data to combine the existing routine satellite infrared cloud maps, radar echo and synoptic weather analysis for severe weather forecasting. It is hopeful to provide more accurate weather analysis for forecasting and decreasing the damage of the disasters over the area concerned.

Building addiction recovery capital through online participation in a recovery community.

PubMed

Bliuc, Ana-Maria; Best, David; Iqbal, Muhammad; Upton, Katie

2017-11-01

This study examines how online participation in a community of recovery contributes to personal journeys of recovery. It investigates whether recovery capital building - as indicated by increased levels and quality of online social interactions - and markers of positive identity development predict retention in a recovery program designed around fostering community involvement for early stage recovery addicts. It was predicted that online participation on the group's Facebook page and positive identity development are associated to retention in the program. To map how participants interact online, social network analysis (SNA) based on naturally occurring online data (N = 609) on the Facebook page of a recovery community was conducted. Computerised linguistic analyses evaluated sentiment of the textual data (capturing social identity markers). Linear regression analyses evaluated whether indicators of recovery capital predict program retention. To illustrate the findings in the context of the specific recovery community, presented are two case studies of key participants who moved from the periphery to the centre of the social network. By conducting in-depth interviews with these participants, personal experiences of engagement in the online community of group members who have undergone the most significant changes since joining the community are explored. Retention in the program was determined by a) the number of comment 'likes' and all 'likes' received on the Facebook page; b) position in the social network (degree of centrality); and c) linguistic content around group identity and achievement. Positive online interactions between members of recovery communities support the recovery process through helping participants to develop recovery capital that binds them to groups supportive of positive change. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reentry trajectories of a space glider, taking acceleration and heating constraints into account

NASA Astrophysics Data System (ADS)

Strauss, Adi

1988-03-01

Three-dimensional trajectories for aerodynamically controlled reentry of an unpowered Space Shuttle-type vehicle from equatorial orbit are investigated analytically, summarizing the results obtained in the author's thesis (Strauss, 1987). Computer programs constructed on the basis of the governing equations of Chern and Yang (1982) and Chern and Vinh (1980) in modified dimensionless Chapman variables are used to optimize the roll angle and lift coefficient of the trajectories. Typical results are presented in graphs and maps and shown to be in good agreement with AVION SPATIAL predictions for the ESA Hermes spacecraft.

Remotely piloted aircraft in the civil environment

NASA Technical Reports Server (NTRS)

Gregory, T. J.; Nelms, W. P.; Karmarkar, J. S.

1977-01-01

Improved remotely piloted aircraft (RPAs), i.e., incorporating reductions in size, weight, and cost, are becoming available for civilian applications. Existing RPA programs are described and predicted into the future. Attention is given to the NASA Mini-Sniffer, which will fly to altitudes of more than 20,000 m, sample the atmosphere behind supersonic cruise aircraft, and telemeter the data to ground stations. Design and operating parameters of the aircraft are given, especially the optical sensing systems, and civilian RPA uses are outlined, including airborne research, remote mapping, rescue, message relay, and transportation of need materials. Civil regulatory factors are also dealt with.

The prediction and mapping of geoidal undulations from GEOS-3 altimetry. [gravity anomalies

NASA Technical Reports Server (NTRS)

Kearsley, W.

1978-01-01

From the adjusted altimeter data an approximation to the geoid height in ocean areas is obtained. Methods are developed to produce geoid maps in these areas. Geoid heights are obtained for grid points in the region to be mapped, and two of the parameters critical to the production of an accurate map are investigated. These are the spacing of the grid, which must be related to the half-wavelength of the altimeter signal whose amplitude is the desired accuracy of the contour; and the method adopted to predict the grid values. Least squares collocation was used to find geoid undulations on a 1 deg grid in the mapping area. Twenty maps, with their associated precisions, were produced and are included. These maps cover the Indian Ocean, Southwestern and Northeastern portions of the Pacific Ocean, and Southwest Atlantic and the U.S. Calibration Area.

Testing mapping algorithms of the cancer-specific EORTC QLQ-C30 onto EQ-5D in malignant mesothelioma.

PubMed

Arnold, David T; Rowen, Donna; Versteegh, Matthijs M; Morley, Anna; Hooper, Clare E; Maskell, Nicholas A

2015-01-23

In order to estimate utilities for cancer studies where the EQ-5D was not used, the EORTC QLQ-C30 can be used to estimate EQ-5D using existing mapping algorithms. Several mapping algorithms exist for this transformation, however, algorithms tend to lose accuracy in patients in poor health states. The aim of this study was to test all existing mapping algorithms of QLQ-C30 onto EQ-5D, in a dataset of patients with malignant pleural mesothelioma, an invariably fatal malignancy where no previous mapping estimation has been published. Health related quality of life (HRQoL) data where both the EQ-5D and QLQ-C30 were used simultaneously was obtained from the UK-based prospective observational SWAMP (South West Area Mesothelioma and Pemetrexed) trial. In the original trial 73 patients with pleural mesothelioma were offered palliative chemotherapy and their HRQoL was assessed across five time points. This data was used to test the nine available mapping algorithms found in the literature, comparing predicted against observed EQ-5D values. The ability of algorithms to predict the mean, minimise error and detect clinically significant differences was assessed. The dataset had a total of 250 observations across 5 timepoints. The linear regression mapping algorithms tested generally performed poorly, over-estimating the predicted compared to observed EQ-5D values, especially when observed EQ-5D was below 0.5. The best performing algorithm used a response mapping method and predicted the mean EQ-5D with accuracy with an average root mean squared error of 0.17 (Standard Deviation; 0.22). This algorithm reliably discriminated between clinically distinct subgroups seen in the primary dataset. This study tested mapping algorithms in a population with poor health states, where they have been previously shown to perform poorly. Further research into EQ-5D estimation should be directed at response mapping methods given its superior performance in this study.

Evaluation of prognostic and predictive value of microtubule associated protein tau in two independent cohorts

PubMed Central

2011-01-01

Introduction Microtubule associated proteins (MAPs) endogenously regulate microtubule stabilization and have been reported as prognostic and predictive markers for taxane response. The microtubule stabilizer, MAP-tau, has shown conflicting results. We quantitatively assessed MAP-tau expression in two independent breast cancer cohorts to determine prognostic and predictive value of this biomarker. Methods MAP-tau expression was evaluated in the retrospective Yale University breast cancer cohort (n = 651) using tissue microarrays and also in the TAX 307 cohort, a clinical trial randomized for TAC versus FAC chemotherapy (n = 140), using conventional whole tissue sections. Expression was measured using the AQUA method for quantitative immunofluorescence. Scores were correlated with clinicopathologic variables, survival, and response to therapy. Results Assessment of the Yale cohort using Cox univariate analysis indicated an improved overall survival (OS) in tumors with a positive correlation between high MAP-tau expression and overall survival (OS) (HR = 0.691, 95% CI = 0.489-0.974; P = 0.004). Kaplan Meier analysis showed 10-year survival for 65% of patients with high MAP-tau expression compared to 52% with low expression (P = .006). In TAX 307, high expression was associated with significantly longer median time to tumor progression (TTP) regardless of treatment arm (33.0 versus 23.4 months, P = 0.010) with mean TTP of 31.2 months. Response rates did not differ by MAP-tau expression (P = 0.518) or by treatment arm (P = 0.584). Conclusions Quantitative measurement of MAP-tau expression has prognostic value in both cohorts, with high expression associated with longer TTP and OS. Differences by treatment arm or response rate in low versus high MAP-tau groups were not observed, indicating that MAP-tau is not associated with response to taxanes and is not a useful predictive marker for taxane-based chemotherapy. PMID:21888627

Historical Topographic Map Collection bookmark

USGS Publications Warehouse

Fishburn, Kristin A.; Allord, Gregory J.

2017-06-29

The U.S. Geological Survey (USGS) National Geospatial Program is scanning published USGS 1:250,000-scale and larger topographic maps printed between 1884, the inception of the topographic mapping program, and 2006. The goal of this project, which began publishing the historical scanned maps in 2011, is to provide a digital repository of USGS topographic maps, available to the public at no cost. For more than 125 years, USGS topographic maps have accurately portrayed the complex geography of the Nation. The USGS is the Nation’s largest producer of printed topographic maps, and prior to 2006, USGS topographic maps were created using traditional cartographic methods and printed using a lithographic printing process. As the USGS continues the release of a new generation of topographic maps (US Topo) in electronic form, the topographic map remains an indispensable tool for government, science, industry, land management planning, and leisure.

75 FR 75693 - National Cooperative Geologic Mapping Program (NCGMP) Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-06

... DEPARTMENT OF THE INTERIOR Geological Survey National Cooperative Geologic Mapping Program (NCGMP) Advisory Committee AGENCY: U.S. Geological Survey, Interior. ACTION: Notice of audio conference. [[Page 75694

Postprocessing classification images

NASA Technical Reports Server (NTRS)

Kan, E. P.

1979-01-01

Program cleans up remote-sensing maps. It can be used with existing image-processing software. Remapped images closely resemble familiar resource information maps and can replace or supplement classification images not postprocessed by this program.

BRCA-Monet: a breast cancer specific drug treatment mode-of-action network for treatment effective prediction using large scale microarray database

PubMed Central

2013-01-01

Background Connectivity map (cMap) is a recent developed dataset and algorithm for uncovering and understanding the treatment effect of small molecules on different cancer cell lines. It is widely used but there are still remaining challenges for accurate predictions. Method Here, we propose BRCA-MoNet, a network of drug mode of action (MoA) specific to breast cancer, which is constructed based on the cMap dataset. A drug signature selection algorithm fitting the characteristic of cMap data, a quality control scheme as well as a novel query algorithm based on BRCA-MoNet are developed for more effective prediction of drug effects. Result BRCA-MoNet was applied to three independent data sets obtained from the GEO database: Estrodial treated MCF7 cell line, BMS-754807 treated MCF7 cell line, and a breast cancer patient microarray dataset. In the first case, BRCA-MoNet could identify drug MoAs likely to share same and reverse treatment effect. In the second case, the result demonstrated the potential of BRCA-MoNet to reposition drugs and predict treatment effects for drugs not in cMap data. In the third case, a possible procedure of personalized drug selection is showcased. Conclusions The results clearly demonstrated that the proposed BRCA-MoNet approach can provide increased prediction power to cMap and thus will be useful for identification of new therapeutic candidates. Website: The web based application is developed and can be access through the following link http://compgenomics.utsa.edu/BRCAMoNet/ PMID:24564956

How do homeless adults change their lives after completing an intensive job-skills program? A prospective study.

PubMed

Gray, Heather M; Nelson, Sarah E; Shaffer, Howard J; Stebbins, Patricia; Farina, Andrea Ryan

2017-09-01

Among people experiencing homelessness, difficulty securing housing is often compounded by concurrent challenges including unemployment, chronic illness, criminal justice involvement, and victimization. The Moving Ahead Program (MAP) is a vocational rehabilitation program that seeks to help adults facing these challenges to secure competitive employment. We prospectively studied how MAP graduates (N = 97) changed from the beginning of MAP to about six months after graduation. We observed a variety of positive outcomes not just in employment and housing but also in health, substance use, and criminal justice involvement. However, these gains were not universal; for instance, participants were less likely to report positive outcomes at follow-up if they started MAP with a serious mental illness, made relatively small gains in work skills, or did not seek mental health treatment during the six months after they completed MAP. These findings might encourage program staff to devote additional resources toward supporting at-risk students.

Determining the Exchangeability of Concept Map and Problem-Solving Essay Scores

ERIC Educational Resources Information Center

Hollenbeck, Keith; Twyman, Todd; Tindal, Gerald

2006-01-01

This study investigated the score exchangeability of concept maps with problem-solving essays. Of interest was whether sixth-grade students' concept maps predicted their scores on essay responses that used concept map content. Concept maps were hypothesized to be alternatives to performance assessments for content-area domain knowledge in science.…

Mapping forest conditions: past, present, and future

Treesearch

Maggi Kelly

2017-01-01

Mapping and mapped data have always been critical to public land managers and researchers for identifying and characterizing wildlife habitat across scales, monitoring species and habitat change, and predicting and planning future scenarios. Maps and mapping protocols are often incorporated into wildlife and habitat management plans, as is the case with the California...

Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations.

PubMed

Wang, D; Salah El-Basyoni, I; Stephen Baenziger, P; Crossa, J; Eskridge, K M; Dweikat, I

2012-11-01

Though epistasis has long been postulated to have a critical role in genetic regulation of important pathways as well as provide a major source of variation in the process of speciation, the importance of epistasis for genomic selection in the context of plant breeding is still being debated. In this paper, we report the results on the prediction of genetic values with epistatic effects for 280 accessions in the Nebraska Wheat Breeding Program using adaptive mixed least absolute shrinkage and selection operator (LASSO). The development of adaptive mixed LASSO, originally designed for association mapping, for the context of genomic selection is reported. The results show that adaptive mixed LASSO can be successfully applied to the prediction of genetic values while incorporating both marker main effects and epistatic effects. Especially, the prediction accuracy is substantially improved by the inclusion of two-locus epistatic effects (more than onefold in some cases as measured by cross-validation correlation coefficient), which is observed for multiple traits and planting locations. This points to significant potential in using non-additive genetic effects for genomic selection in crop breeding practices.

Spatial distribution and deployment of community-based distributors implementing integrated community case management (iCCM): Geographic information system (GIS) mapping study in three South Sudan states.

PubMed

Pratt, Abigail; Dale, Martin; Olivi, Elena; Miller, Jane

2014-12-01

In late 2012 and in conjunction with South Sudan's Ministry of Health - National Malaria Control Program, PSI (Population Services International) conducted a comprehensive mapping exercise to assess geographical coverage of its integrated community case management (iCCM) program and consider scope for expansion. The operational research was designed to provide evidence and support for low-cost mapping and monitoring systems, demonstrating the use of technology to enhance the quality of programming and to allow for the improved allocation of resources through appropriate and need-based deployment of community-based distributors (CBDs). The survey took place over the course of three months and program staff gathered GPS (global positioning system) data, along with demographic data, for over 1200 CBDs and 111 CBD supervisors operating in six counties in South Sudan. Data was collated, cleaned and quality assured, input into an Excel database, and subsequently uploaded to geographic information system (GIS) for spatial analysis and map production. The mapping results showed that over three-quarters of CBDs were deployed within a five kilometer radius of a health facility or another CBD, contrary to program planning and design. Other characteristics of the CBD and CBD supervisor profiles (age, gender, literacy) were more closely matched with other regional programs. The results of this mapping exercise provided a valuable insight into the contradictions found between a program "deployment plan" and the realities observed during field implementation. It also highlighted an important need for program implementers and national-level strategy makers to consider the natural and community-driven diffusion of CBDs, and take into consideration the strength of the local health facilities when developing a deployment plan.

77 FR 24169 - Notice of Funds Availability: Inviting Applications for the Market Access Program

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-23

... for the 2013 Market Access Program (MAP). The intended effect of this notice is to solicit... not be considered. FOR FURTHER INFORMATION CONTACT: Entities wishing to apply for funding assistance... at http://www.fas.usda.gov/mos/programs/map.asp . SUPPLEMENTARY INFORMATION: I. Funding Opportunity...

Mathemagenic Activities Program: [Reports on Cognitive/Language Development].

ERIC Educational Resources Information Center

Smock, Charles D., Ed.

This set of 13 research reports, bulletins and papers is a product of the Mathemagenic Activities Program (MAP) for early childhood education of the University of Georgia Follow Through Program. Based on Piagetian theory, the MAP provides sequentially structured sets of curriculum materials and processes that are designed to continually challenge…

A MAP read-routine for IBM 7094 Fortran II binary tapes

Treesearch

Robert S. Helfman

1966-01-01

Two MAP (Macro Assembly Program) language routines are descrived. They permit Fortran IV programs to read binary tapes generated by Fortran II programs, on the IBM 7090 and 7094 computers. One routine is for use with 7040/44-IBSYS, the other for 7090/94-IBSYS.

Usability and Functional Enhancements to an Online Interface for Predicting Post Fire Erosion (WEPP-PEP)

NASA Astrophysics Data System (ADS)

Lew, Roger; Dobre, Mariana; Elliot, William; Robichaud, Pete; Brooks, Erin; Frankenberger, Jim

2017-04-01

There is an increased interest in the United States to use soil burn severity maps in watershed-scale hydrologic models to estimate post-fire sediment erosion from burned areas. This information is needed by stakeholders in order to concentrate their pre- or post-fire management efforts in ecologically sensitive areas to decrease the probability of post-fire sediment delivery. But these tools traditionally have been time consuming and difficult to use by managers because input datasets must be obtained and correctly processed for valid results. The Water Erosion Prediction Project (WEPP) has previously been developed as an online and easy-to-use interface to help land managers with running simulations without any knowledge of computer programming or hydrologic modeling. The interface automates the acquisition of DEM, climate, soils, and landcover data, and also automates channel and hillslope delineation for the users. The backend is built with Mapserver, GDAL, PHP, C++, Python while the front end uses OpenLayers, and, of course, JavaScript. The existing WEPP online interface was enhanced to provide better usability to stakeholders in United States (Forest Service, BLM, USDA) as well as to provide enhanced functionality for managing both pre-fire and post-fire treatments. Previously, only site administrators could add burn severity maps. The interface now allows users to create accounts to upload and share FlamMap prediction maps, differenced Normalized Burned Ratio (dNBR), or Burned Area Reflectance Classification (BARC) maps. All maps are loaded into a sortable catalog so users can quickly find their area of interest. Once loaded, the interface has been modified to support running comparisons between baseline condition with "no burn" and with a burn severity classification map. The interface has also been enhanced to allow users to conduct single storm analyses to examine, for example, how much soil loss would result after a 100-year storm. An OpenLayers map allows users to overlay the watershed hillslopes and channels, burn severity, and erosion. The interface provides flowpath results for each hillslope and at the outlet, as well as return period and frequency analysis reports. Once problematic areas have been identified, the interface allows users to export the watershed in a format that can be used by the Erosion Risk Management Tool (ERMiT) and Disturbed WEPP (post-disturbance modeling) for more detailed hillslope-level analyses. Numerous other changes were made to improve the overall usability of the interface: allow simulations in both SI and English units, added immovable pop-up dialogs to guide the users, and removed extraneous information from the interface. In upcoming months, a workshop will be conducted to demonstrate these new capabilities to stakeholders. Efforts are underway to use site-specific SSURGO soils to that are modified based on burn severity rather than using generic soil classes.

Large-extent digital soil mapping approaches for total soil depth

NASA Astrophysics Data System (ADS)

Mulder, Titia; Lacoste, Marine; Saby, Nicolas P. A.; Arrouays, Dominique

2015-04-01

Total soil depth (SDt) plays a key role in supporting various ecosystem services and properties, including plant growth, water availability and carbon stocks. Therefore, predictive mapping of SDt has been included as one of the deliverables within the GlobalSoilMap project. In this work SDt was predicted for France following the directions of GlobalSoilMap, which requires modelling at 90m resolution. This first method, further referred to as DM, consisted of modelling the deterministic trend in SDt using data mining, followed by a bias correction and ordinary kriging of the residuals. Considering the total surface area of France, being about 540K km2, employed methods may need to be able dealing with large data sets. Therefore, a second method, multi-resolution kriging (MrK) for large datasets, was implemented. This method consisted of modelling the deterministic trend by a linear model, followed by interpolation of the residuals. For the two methods, the general trend was assumed to be explained by the biotic and abiotic environmental conditions, as described by the Soil-Landscape paradigm. The mapping accuracy was evaluated by an internal validation and its concordance with previous soil maps. In addition, the prediction interval for DM and the confidence interval for MrK were determined. Finally, the opportunities and limitations of both approaches were evaluated. The results showed consistency in mapped spatial patterns and a good prediction of the mean values. DM was better capable in predicting extreme values due to the bias correction. Also, DM was more powerful in capturing the deterministic trend than the linear model of the MrK approach. However, MrK was found to be more straightforward and flexible in delivering spatial explicit uncertainty measures. The validation indicated that DM was more accurate than MrK. Improvements for DM may be expected by predicting soil depth classes. MrK shows potential for modelling beyond the country level, at high resolution. Large-extent digital soil mapping approaches for SDt may be improved by (1) taking into account SDt observations which are censored and (2) using high-resolution biotic and abiotic environmental data. The latter may improve modelling the soil-landscape interactions influencing soil pedogenesis. Concluding, this work provided a robust and reproducible method (DM) for high-resolution soil property modelling, in accordance with the GlobalSoilMap requirements and an efficient alternative for large-extent digital soil mapping (MrK).

Prospective evaluation of shape similarity based pose prediction method in D3R Grand Challenge 2015

NASA Astrophysics Data System (ADS)

Kumar, Ashutosh; Zhang, Kam Y. J.

2016-09-01

Evaluation of ligand three-dimensional (3D) shape similarity is one of the commonly used approaches to identify ligands similar to one or more known active compounds from a library of small molecules. Apart from using ligand shape similarity as a virtual screening tool, its role in pose prediction and pose scoring has also been reported. We have recently developed a method that utilizes ligand 3D shape similarity with known crystallographic ligands to predict binding poses of query ligands. Here, we report the prospective evaluation of our pose prediction method through the participation in drug design data resource (D3R) Grand Challenge 2015. Our pose prediction method was used to predict binding poses of heat shock protein 90 (HSP90) and mitogen activated protein kinase kinase kinase kinase (MAP4K4) ligands and it was able to predict the pose within 2 Å root mean square deviation (RMSD) either as the top pose or among the best of five poses in a majority of cases. Specifically for HSP90 protein, a median RMSD of 0.73 and 0.68 Å was obtained for the top and the best of five predictions respectively. For MAP4K4 target, although the median RMSD for our top prediction was only 2.87 Å but the median RMSD of 1.67 Å for the best of five predictions was well within the limit for successful prediction. Furthermore, the performance of our pose prediction method for HSP90 and MAP4K4 ligands was always among the top five groups. Particularly, for MAP4K4 protein our pose prediction method was ranked number one both in terms of mean and median RMSD when the best of five predictions were considered. Overall, our D3R Grand Challenge 2015 results demonstrated that ligand 3D shape similarity with the crystal ligand is sufficient to predict binding poses of new ligands with acceptable accuracy.

2010-2011 Performance of the AirNow Satellite Data Processor

NASA Astrophysics Data System (ADS)

Pasch, A. N.; DeWinter, J. L.; Haderman, M. D.; van Donkelaar, A.; Martin, R. V.; Szykman, J.; White, J. E.; Dickerson, P.; Zahn, P. H.; Dye, T. S.

2012-12-01

The U.S. Environmental Protection Agency's (EPA) AirNow program provides maps of real time hourly Air Quality Index (AQI) conditions and daily AQI forecasts nationwide (http://www.airnow.gov). The public uses these maps to make health-based decisions. The usefulness of the AirNow air quality maps depends on the accuracy and spatial coverage of air quality measurements. Currently, the maps use only ground-based measurements, which have significant gaps in coverage in some parts of the United States. As a result, contoured AQI levels have high uncertainty in regions far from monitors. To improve the usefulness of air quality maps, scientists at EPA, Dalhousie University, and Sonoma Technology, Inc. have been working in collaboration with the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA) to incorporate satellite-estimated surface PM2.5 concentrations into the maps via the AirNow Satellite Data Processor (ASDP). These satellite estimates are derived using NASA/NOAA satellite aerosol optical depth (AOD) retrievals and GEOS-Chem modeled ratios of surface PM2.5 concentrations to AOD. GEOS-Chem is a three-dimensional chemical transport model for atmospheric composition driven by meteorological input from the Goddard Earth Observing System (GOES). The ASDP can fuse multiple PM2.5 concentration data sets to generate AQI maps with improved spatial coverage. The goal of ASDP is to provide more detailed AQI information in monitor-sparse locations and augment monitor-dense locations with more information. We will present a statistical analysis for 2010-2011 of the ASDP predictions of PM2.5 focusing on performance at validation sites. In addition, we will present several case studies evaluating the ASDP's performance for multiple regions and seasons, focusing specifically on days when large spatial gradients in AQI and wildfire smoke impact were observed.

Remote Sensing Program

NASA Technical Reports Server (NTRS)

Philipson, W. R. (Principal Investigator); Liang, T.; Philpot, W. D.

1983-01-01

Field spectroradiometric and airborne multispectral scanner data were related to vineyard yield and other agronomic variables in an attempt to determine the optimum wavelengths for yield prediction modeling. Reflections between vine canopy reflectance and several management practices were also considered. Spectral analysis of test vines found that, although some correlations with vine yield were significant, they were inadequate for producing a yield prediction model. The findings also indicate that the vines examined through the field spectroradiometers were not truly representative. Geologic linears identified from aerial photographys, LANDSAT images, and maps were compared to gas well locations in three New York' counties. Correlations were found between the dominant trends in regional liners and gas field boundaries and trends. Other projects being conducted under the grant include determining vegetable acreage in mucklands, site selection for windmills, spectral effects of sulfur dioxide, and screening tomato seedlings for salt tolerance.

Developmental Levels of Processing in Metaphor Interpretation.

ERIC Educational Resources Information Center

Johnson, Janice; Pascual-Leone, Juan

1989-01-01

Outlines a theory of metaphor that posits varying levels of semantic processing and formalizes the levels in terms of kinds of semantic mapping operators. Predicted complexity of semantic mapping operators was tested using metaphor interpretations of 204 children aged 6-12 years and 24 adults. Processing score increased predictably with age. (SAK)

Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran

NASA Astrophysics Data System (ADS)

Zeraatpisheh, Mojtaba; Ayoubi, Shamsollah; Jafari, Azam; Finke, Peter

2017-05-01

The efficiency of different digital and conventional soil mapping approaches to produce categorical maps of soil types is determined by cost, sample size, accuracy and the selected taxonomic level. The efficiency of digital and conventional soil mapping approaches was examined in the semi-arid region of Borujen, central Iran. This research aimed to (i) compare two digital soil mapping approaches including Multinomial logistic regression and random forest, with the conventional soil mapping approach at four soil taxonomic levels (order, suborder, great group and subgroup levels), (ii) validate the predicted soil maps by the same validation data set to determine the best method for producing the soil maps, and (iii) select the best soil taxonomic level by different approaches at three sample sizes (100, 80, and 60 point observations), in two scenarios with and without a geomorphology map as a spatial covariate. In most predicted maps, using both digital soil mapping approaches, the best results were obtained using the combination of terrain attributes and the geomorphology map, although differences between the scenarios with and without the geomorphology map were not significant. Employing the geomorphology map increased map purity and the Kappa index, and led to a decrease in the 'noisiness' of soil maps. Multinomial logistic regression had better performance at higher taxonomic levels (order and suborder levels); however, random forest showed better performance at lower taxonomic levels (great group and subgroup levels). Multinomial logistic regression was less sensitive than random forest to a decrease in the number of training observations. The conventional soil mapping method produced a map with larger minimum polygon size because of traditional cartographic criteria used to make the geological map 1:100,000 (on which the conventional soil mapping map was largely based). Likewise, conventional soil mapping map had also a larger average polygon size that resulted in a lower level of detail. Multinomial logistic regression at the order level (map purity of 0.80), random forest at the suborder (map purity of 0.72) and great group level (map purity of 0.60), and conventional soil mapping at the subgroup level (map purity of 0.48) produced the most accurate maps in the study area. The multinomial logistic regression method was identified as the most effective approach based on a combined index of map purity, map information content, and map production cost. The combined index also showed that smaller sample size led to a preference for the order level, while a larger sample size led to a preference for the great group level.

The national land use data program of the US Geological Survey

NASA Technical Reports Server (NTRS)

Anderson, J. R.; Witmer, R. E.

1975-01-01

The Land Use Data and Analysis (LUDA) Program which provides a systematic and comprehensive collection and analysis of land use and land cover data on a nationwide basis is described. Maps are compiled at about 1:125,000 scale showing present land use/cover at Level II of a land use/cover classification system developed by the U.S. Geological Survey in conjunction with other Federal and state agencies and other users. For each of the land use/cover maps produced at 1:125,000 scale, overlays are also compiled showing Federal land ownership, river basins and subbasins, counties, and census county subdivisions. The program utilizes the advanced technology of the Special Mapping Center of the U.S. Geological Survey, high altitude NASA photographs, aerial photographs acquired for the USGS Topographic Division's mapping program, and LANDSAT data in complementary ways.

Project Mapping to Build Capacity and Demonstrate Impact in the Earth Sciences

NASA Astrophysics Data System (ADS)

Hemmings, S. N.; Searby, N. D.; Murphy, K. J.; Mataya, C. J.; Crepps, G.; Clayton, A.; Stevens, C. L.

2017-12-01

Diverse organizations are increasingly using project mapping to communicate location-based information about their activities. NASA's Earth Science Division (ESD), through the Earth Science Data Systems and Applied Sciences' Capacity Building Program (CBP), has created a geographic information system of all ESD projects to support internal program management for the agency. The CBP's NASA DEVELOP program has built an interactive mapping tool to support capacity building for the program's varied constituents. This presentation will explore the types of programmatic opportunities provided by a geographic approach to management, communication, and strategic planning. We will also discuss the various external benefits that mapping supports and that build capacity in the Earth sciences. These include activities such as project matching (location-focused synergies), portfolio planning, inter- and intra-organizational collaboration, science diplomacy, and basic impact analysis.

Use of Intervention Mapping to Enhance Health Care Professional Practice: A Systematic Review.

PubMed

Durks, Desire; Fernandez-Llimos, Fernando; Hossain, Lutfun N; Franco-Trigo, Lucia; Benrimoj, Shalom I; Sabater-Hernández, Daniel

2017-08-01

Intervention Mapping is a planning protocol for developing behavior change interventions, the first three steps of which are intended to establish the foundations and rationales of such interventions. This systematic review aimed to identify programs that used Intervention Mapping to plan changes in health care professional practice. Specifically, it provides an analysis of the information provided by the programs in the first three steps of the protocol to determine their foundations and rationales of change. A literature search was undertaken in PubMed, Scopus, SciELO, and DOAJ using "Intervention Mapping" as keyword. Key information was gathered, including theories used, determinants of practice, research methodologies, theory-based methods, and practical applications. Seventeen programs aimed at changing a range of health care practices were included. The social cognitive theory and the theory of planned behavior were the most frequently used frameworks in driving change within health care practices. Programs used a large variety of research methodologies to identify determinants of practice. Specific theory-based methods (e.g., modelling and active learning) and practical applications (e.g., health care professional training and facilitation) were reported to inform the development of practice change interventions and programs. In practice, Intervention Mapping delineates a three-step systematic, theory- and evidence-driven process for establishing the theoretical foundations and rationales underpinning change in health care professional practice. The use of Intervention Mapping can provide health care planners with useful guidelines for the theoretical development of practice change interventions and programs.

Concept mapping enhances learning of biochemistry.

PubMed

Surapaneni, Krishna M; Tekian, Ara

2013-03-05

Teaching basic science courses is challenging in undergraduate medical education because of the ubiquitous use of didactic lectures and reward for recall of factual information during examinations. The purpose of this study is to introduce concept maps with clinical cases (the innovative program) to improve learning of biochemistry course content. Participants were first year medical students (n=150) from Saveetha Medical College and Hospital (India); they were randomly divided into two groups of 75, one group attending the traditional program, the other the innovative program. Student performance was measured using three written knowledge tests (each with a maximum score of 20). The students also evaluated the relevance of the learning process using a 12-item questionnaire. Students in the innovative program using concept mapping outperformed those in the traditional didactic program (means of 7.13-8.28 vs. 12.33-13.93, p<0.001). The students gave high positive ratings for the innovative course (93-100% agreement). The new concept-mapping program resulted in higher academic performance compared to the traditional course and was perceived favorably by the students. They especially valued the use of concept mapping as learning tools to foster the relevance of biochemistry to clinical practice, and to enhance their reasoning and learning skills, as well as their deeper understanding for biochemistry.

Concept mapping enhances learning of biochemistry

PubMed Central

Surapaneni, Krishna M.; Tekian, Ara

2013-01-01

Background Teaching basic science courses is challenging in undergraduate medical education because of the ubiquitous use of didactic lectures and reward for recall of factual information during examinations. The purpose of this study is to introduce concept maps with clinical cases (the innovative program) to improve learning of biochemistry course content. Methods Participants were first year medical students (n=150) from Saveetha Medical College and Hospital (India); they were randomly divided into two groups of 75, one group attending the traditional program, the other the innovative program. Student performance was measured using three written knowledge tests (each with a maximum score of 20). The students also evaluated the relevance of the learning process using a 12-item questionnaire. Results Students in the innovative program using concept mapping outperformed those in the traditional didactic program (means of 7.13–8.28 vs. 12.33–13.93, p<0.001). The students gave high positive ratings for the innovative course (93–100% agreement). Conclusion The new concept-mapping program resulted in higher academic performance compared to the traditional course and was perceived favorably by the students. They especially valued the use of concept mapping as learning tools to foster the relevance of biochemistry to clinical practice, and to enhance their reasoning and learning skills, as well as their deeper understanding for biochemistry. PMID:23464600

Concept mapping enhances learning of biochemistry.

PubMed

Surapaneni, KrishnaM; Tekian, Ara

2013-01-01

Teaching basic science courses is challenging in undergraduate medical education because of the ubiquitous use of didactic lectures and reward for recall of factual information during examinations. The purpose of this study is to introduce concept maps with clinical cases (the innovative program) to improve learning of biochemistry course content. Participants were first year medical students (n=150) from Saveetha Medical College and Hospital (India); they were randomly divided into two groups of 75, one group attending the traditional program, the other the innovative program. Student performance was measured using three written knowledge tests (each with a maximum score of 20). The students also evaluated the relevance of the learning process using a 12-item questionnaire. Students in the innovative program using concept mapping outperformed those in the traditional didactic program (means of 7.13-8.28 vs. 12.33-13.93, p<0.001). The students gave high positive ratings for the innovative course (93-100% agreement). The new concept-mapping program resulted in higher academic performance compared to the traditional course and was perceived favorably by the students. They especially valued the use of concept mapping as learning tools to foster the relevance of biochemistry to clinical practice, and to enhance their reasoning and learning skills, as well as their deeper understanding for biochemistry.

Plasmid mapping computer program.

PubMed Central

Nolan, G P; Maina, C V; Szalay, A A

1984-01-01

Three new computer algorithms are described which rapidly order the restriction fragments of a plasmid DNA which has been cleaved with two restriction endonucleases in single and double digestions. Two of the algorithms are contained within a single computer program (called MPCIRC). The Rule-Oriented algorithm, constructs all logical circular map solutions within sixty seconds (14 double-digestion fragments) when used in conjunction with the Permutation method. The program is written in Apple Pascal and runs on an Apple II Plus Microcomputer with 64K of memory. A third algorithm is described which rapidly maps double digests and uses the above two algorithms as adducts. Modifications of the algorithms for linear mapping are also presented. PMID:6320105

National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project

USGS Publications Warehouse

Hop, Kevin D.; Strassman, Andrew C.; Hall, Mark; Menard, Shannon; Largay, Ery; Sattler, Stephanie; Hoy, Erin E.; Ruhser, Janis; Hlavacek, Enrika; Dieck, Jennifer

2017-01-01

The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program classifies, describes, and maps existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Northeast Temperate Network, and NPS Appalachian National Scenic Trail (APPA) have completed vegetation classification and mapping of APPA for the NPS VMI Program.Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of APPA and to determine how best to map the vegetation types by using aerial imagery. Analyses of data from 1,618 vegetation plots were used to describe USNVC associations of APPA. Data from 289 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Data from 269 validation sites were collected to assess vegetation mapping prior to submitting the vegetation map for accuracy assessment (AA). Data from 3,265 AA sites were collected, of which 3,204 were used to test accuracy of the vegetation map layer. The collective of these datasets affirmed 280 USNVC associations for the APPA vegetation mapping project.To map the vegetation and land cover of APPA, 169 map classes were developed. The 169 map classes consist of 150 that represent natural (including ruderal) vegetation types in the USNVC, 11 that represent cultural (agricultural and developed) vegetation types in the USNVC, 5 that represent natural landscapes with catastrophic disturbance or some other modification to natural vegetation preventing accurate classification in the USNVC, and 3 that represent nonvegetated water (non-USNVC). Features were interpreted from viewing 4-band digital aerial imagery using digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). (Digital aerial imagery was collected each fall during 2009–11 to capture leaf-phenology change of hardwood trees across the latitudinal range of APPA.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in GIS. Polygon units were mapped to either a 0.5-hectare (ha) or 0.25-ha minimum mapping unit, depending on vegetation type or scenario; however, polygon units were mapped to 0.1 ha for alpine vegetation.A geodatabase containing various feature-class layers and tables provide locations and support data to USNVC vegetation types (vegetation map layer), vegetation plots, verification sites, validation sites, AA sites, project boundary extent and zones, and aerial image centers and flight lines. The feature-class layer and related tables of the vegetation map layer provide 30,395 polygons of detailed attribute data covering 110,919.7 ha, with an average polygon size of 3.6 ha; the vegetation map coincides closely with the administrative boundary for APPA.Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 28,242 polygons (92.9% of polygons) and cover 106,413.0 ha (95.9%) of the map extent for APPA. The map layer indicates APPA to be 92.4% forest and woodland (102,480.8 ha), 1.7% shrubland (1866.3 ha), and 1.8% herbaceous cover (2,065.9 ha). Map classes representing park-special vegetation (undefined in the USNVC) apply to 58 polygons (0.2% of polygons) and cover 404.3 ha (0.4%) of the map extent. Map classes representing USNVC cultural types apply to 1,777 polygons (5.8% of polygons) and cover 2,516.3 ha (2.3%) of the map extent. Map classes representing nonvegetated water (non-USNVC) apply to 332 polygons (1.1% of polygons) and cover 1,586.2 ha (1.4%) of the map extent.

Storm Prediction Center Fire Weather Forecasts

Science.gov Websites

Archive NOAA Weather Radio Research Non-op. Products Forecast Tools Svr. Tstm. Events SPC Publications SPC Composite Maps Fire Weather Graphical Composite Maps Forecast and observational maps for various fire

Ecological Monitoring and Compliance Program 2007 Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hansen, Dennis; Anderson, David; Derek, Hall

2008-03-01

In accordance with U.S. Department of Energy (DOE) Order 450.1, 'Environmental Protection Program', the Office of the Assistant Manager for Environmental Management of the DOE, National Nuclear Security Administration Nevada Site Office (NNSA/NSO) requires ecological monitoring and biological compliance support for activities and programs conducted at the Nevada Test Site (NTS). National Security Technologies, LLC (NSTec), Ecological Services has implemented the Ecological Monitoring and Compliance (EMAC) Program to provide this support. EMAC is designed to ensure compliance with applicable laws and regulations, delineate and define NTS ecosystems, and provide ecological information that can be used to predict and evaluate themore » potential impacts of proposed projects and programs on those ecosystems. This report summarizes the EMAC activities conducted by NSTec during calendar year 2007. Monitoring tasks during 2007 included eight program areas: (a) biological surveys, (b) desert tortoise compliance, (c) ecosystem mapping and data management, (d) sensitive plant monitoring, (e) sensitive and protected/regulated animal monitoring, (f) habitat monitoring, (g) habitat restoration monitoring, and (h) biological monitoring at the Nonproliferation Test and Evaluation Complex (NPTEC). The following sections of this report describe work performed under these eight areas.« less

Longitudinal predictive ability of mapping models: examining post-intervention EQ-5D utilities derived from baseline MHAQ data in rheumatoid arthritis patients.

PubMed

Kontodimopoulos, Nick; Bozios, Panagiotis; Yfantopoulos, John; Niakas, Dimitris

2013-04-01

The purpose of this methodological study was to to provide insight into the under-addressed issue of the longitudinal predictive ability of mapping models. Post-intervention predicted and reported utilities were compared, and the effect of disease severity on the observed differences was examined. A cohort of 120 rheumatoid arthritis (RA) patients (60.0% female, mean age 59.0) embarking on therapy with biological agents completed the Modified Health Assessment Questionnaire (MHAQ) and the EQ-5D at baseline, and at 3, 6 and 12 months post-intervention. OLS regression produced a mapping equation to estimate post-intervention EQ-5D utilities from baseline MHAQ data. Predicted and reported utilities were compared with t test, and the prediction error was modeled, using fixed effects, in terms of covariates such as age, gender, time, disease duration, treatment, RF, DAS28 score, predicted and reported EQ-5D. The OLS model (RMSE = 0.207, R(2) = 45.2%) consistently underestimated future utilities, with a mean prediction error of 6.5%. Mean absolute differences between reported and predicted EQ-5D utilities at 3, 6 and 12 months exceeded the typically reported MID of the EQ-5D (0.03). According to the fixed-effects model, time, lower predicted EQ-5D and higher DAS28 scores had a significant impact on prediction errors, which appeared increasingly negative for lower reported EQ-5D scores, i.e., predicted utilities tended to be lower than reported ones in more severe health states. This study builds upon existing research having demonstrated the potential usefulness of mapping disease-specific instruments onto utility measures. The specific issue of longitudinal validity is addressed, as mapping models derived from baseline patients need to be validated on post-therapy samples. The underestimation of post-treatment utilities in the present study, at least in more severe patients, warrants further research before it is prudent to conduct cost-utility analyses in the context of RA by means of the MHAQ alone.

MAPS of Cancer

NASA Technical Reports Server (NTRS)

Gray, Lincoln

1998-01-01

Our goal was to produce an interactive visualization from a mathematical model that successfully predicts metastases from head and neck cancer. We met this goal early in the project. The visualization is available for the public to view. Our work appears to fill a need for more information about this deadly disease. The idea of this project was to make an easily interpretable visualization based on what we call "functional maps" of disease. A functional map is a graphic summary of medical data, where distances between parts of the body are determined by the probability of disease, not by anatomical distances. Functional maps often beat little resemblance to anatomical maps, but they can be used to predict the spread of disease. The idea of modeling the spread of disease in an abstract multidimensional space is difficult for many people. Our goal was to make the important predictions easy to see. NASA must face this problem frequently: how to help laypersons and professionals see important trends in abstract, complex data. We took advantage of concepts perfected in NASA's graphics libraries. As an analogy, consider a functional map of early America. Suppose we choose travel times, rather than miles, as our measures of inter-city distances. For Abraham Lincoln, travel times would have been the more meaningful measure of separation between cities. In such a map New Orleans would be close to Memphis because of the Mississippi River. St. Louis would be close to Portland because of the Oregon Trail. Oklahoma City would be far from Little Rock because of the Cheyenne. Such a map would look puzzling to those of us who have always seen physical maps, but the functional map would be more useful in predicting the probabilities of inter-site transit. Continuing the analogy, we could predict the spread of social diseases such as gambling along the rivers and cattle rustling along the trails. We could simply print the functional map of America, but it would be more interesting to show meaningful patterns of dispersal. We had previously published the functional map of the head and neck, but it was difficult to explain to either patients or surgeons because that view of our body did not resemble anatomy. This discrepancy between functional and physical maps is just a mathematical restatement of the well-known fact that some diseases, such as head and neck cancer, spread in complex patterns, not always to the next nearest site. We had discovered that a computer could re-arrange anatomy so that this particular disease spreads to the next nearest site. The functional map explains over 95% of the metastases in 1400 patients. In a sense, we had graphed what our body "looks like" to a tumor. The tumor readily travels between adjacent areas in the functional map. The functional map is a succinct visual display of trends that are not easily appreciated in tables of probabilities.

Can Probability Maps of Swept-Source Optical Coherence Tomography Predict Visual Field Changes in Preperimetric Glaucoma?

PubMed

Lee, Won June; Kim, Young Kook; Jeoung, Jin Wook; Park, Ki Ho

2017-12-01

To determine the usefulness of swept-source optical coherence tomography (SS-OCT) probability maps in detecting locations with significant reduction in visual field (VF) sensitivity or predicting future VF changes, in patients with classically defined preperimetric glaucoma (PPG). Of 43 PPG patients, 43 eyes were followed-up on every 6 months for at least 2 years were analyzed in this longitudinal study. The patients underwent wide-field SS-OCT scanning and standard automated perimetry (SAP) at the time of enrollment. With this wide-scan protocol, probability maps originating from the corresponding thickness map and overlapped with SAP VF test points could be generated. We evaluated the vulnerable VF points with SS-OCT probability maps as well as the prevalence of locations with significant VF reduction or subsequent VF changes observed in the corresponding damaged areas of the probability maps. The vulnerable VF points were shown in superior and inferior arcuate patterns near the central fixation. In 19 of 43 PPG eyes (44.2%), significant reduction in baseline VF was detected within the areas of structural change on the SS-OCT probability maps. In 16 of 43 PPG eyes (37.2%), subsequent VF changes within the areas of SS-OCT probability map change were observed over the course of the follow-up. Structural changes on SS-OCT probability maps could detect or predict VF changes using SAP, in a considerable number of PPG eyes. Careful comparison of probability maps with SAP results could be useful in diagnosing and monitoring PPG patients in the clinical setting.

Metallic Hydrogen

NASA Astrophysics Data System (ADS)

Silvera, Isaac; Zaghoo, Mohamed; Salamat, Ashkan

2015-03-01

Hydrogen is the simplest and most abundant element in the Universe. At high pressure it is predicted to transform to a metal with remarkable properties: room temperature superconductivity, a metastable metal at ambient conditions, and a revolutionary rocket propellant. Both theory and experiment have been challenged for almost 80 years to determine its condensed matter phase diagram, in particular the insulator-metal transition. Hydrogen is predicted to dissociate to a liquid atomic metal at multi-megabar pressures and T =0 K, or at megabar pressures and very high temperatures. Thus, its predicted phase diagram has a broad field of liquid metallic hydrogen at high pressure, with temperatures ranging from thousands of degrees to zero Kelvin. In a bench top experiment using static compression in a diamond anvil cell and pulsed laser heating, we have conducted measurements on dense hydrogen in the region of 1.1-1.7 Mbar and up to 2200 K. We observe a first-order phase transition in the liquid phase, as well as sharp changes in optical transmission and reflectivity when this phase is entered. The optical signature is that of a metal. The mapping of the phase line of this transition is in excellent agreement with recent theoretical predictions for the long-sought plasma phase transition to metallic hydrogen. Research supported by the NSF, Grant DMR-1308641, the DOE Stockpile Stewardship Academic Alliance Program, Grant DE-FG52-10NA29656, and NASA Earth and Space Science Fellowship Program, Award NNX14AP17H.

Impairment of speech production predicted by lesion load of the left arcuate fasciculus.

PubMed

Marchina, Sarah; Zhu, Lin L; Norton, Andrea; Zipse, Lauryn; Wan, Catherine Y; Schlaug, Gottfried

2011-08-01

Previous studies have suggested that patients' potential for poststroke language recovery is related to lesion size; however, lesion location may also be of importance, particularly when fiber tracts that are critical to the sensorimotor mapping of sounds for articulation (eg, the arcuate fasciculus) have been damaged. In this study, we tested the hypothesis that lesion loads of the arcuate fasciculus (ie, volume of arcuate fasciculus that is affected by a patient's lesion) and of 2 other tracts involved in language processing (the extreme capsule and the uncinate fasciculus) are inversely related to the severity of speech production impairments in patients with stroke with aphasia. Thirty patients with chronic stroke with residual impairments in speech production underwent high-resolution anatomic MRI and a battery of cognitive and language tests. Impairment was assessed using 3 functional measures of spontaneous speech (eg, rate, informativeness, and overall efficiency) as well as naming ability. To quantitatively analyze the relationship between impairment scores and lesion load along the 3 fiber tracts, we calculated tract-lesion overlap volumes for each patient using probabilistic maps of the tracts derived from diffusion tensor images of 10 age-matched healthy subjects. Regression analyses showed that arcuate fasciculus lesion load, but not extreme capsule or uncinate fasciculus lesion load or overall lesion size, significantly predicted rate, informativeness, and overall efficiency of speech as well as naming ability. A new variable, arcuate fasciculus lesion load, complements established voxel-based lesion mapping techniques and, in the future, may potentially be used to estimate impairment and recovery potential after stroke and refine inclusion criteria for experimental rehabilitation programs.

Scanning and georeferencing historical USGS quadrangles

USGS Publications Warehouse

Fishburn, Kristin A.; Davis, Larry R.; Allord, Gregory J.

2017-06-23

The U.S. Geological Survey (USGS) National Geospatial Program is scanning published USGS 1:250,000-scale and larger topographic maps printed between 1884, the inception of the topographic mapping program, and 2006. The goal of this project, which began publishing the Historical Topographic Map Collection in 2011, is to provide access to a digital repository of USGS topographic maps that is available to the public at no cost. For more than 125 years, USGS topographic maps have accurately portrayed the complex geography of the Nation. The USGS is the Nation’s largest producer of traditional topographic maps, and, prior to 2006, USGS topographic maps were created using traditional cartographic methods and printed using a lithographic process. The next generation of topographic maps, US Topo, is being released by the USGS in digital form, and newer technologies make it possible to also deliver historical maps in the same electronic format that is more publicly accessible.

Designing a workplace return-to-work program for occupational low back pain: an intervention mapping approach.

PubMed

Ammendolia, Carlo; Cassidy, David; Steensta, Ivan; Soklaridis, Sophie; Boyle, Eleanor; Eng, Stephanie; Howard, Hamer; Bhupinder, Bains; Côté, Pierre

2009-06-09

Despite over 2 decades of research, the ability to prevent work-related low back pain (LBP) and disability remains elusive. Recent research suggests that interventions that are focused at the workplace and incorporate the principals of participatory ergonomics and return-to-work (RTW) coordination can improve RTW and reduce disability following a work-related back injury. Workplace interventions or programs to improve RTW are difficult to design and implement given the various individuals and environments involved, each with their own unique circumstances. Intervention mapping provides a framework for designing and implementing complex interventions or programs. The objective of this study is to design a best evidence RTW program for occupational LBP tailored to the Ontario setting using an intervention mapping approach. We used a qualitative synthesis based on the intervention mapping methodology. Best evidence from systematic reviews, practice guidelines and key articles on the prognosis and management of LBP and improving RTW was combined with theoretical models for managing LBP and changing behaviour. This was then systematically operationalized into a RTW program using consensus among experts and stakeholders. The RTW Program was further refined following feedback from nine focus groups with various stakeholders. A detailed five step RTW program was developed. The key features of the program include; having trained personnel coordinate the RTW process, identifying and ranking barriers and solutions to RTW from the perspective of all important stakeholders, mediating practical solutions at the workplace and, empowering the injured worker in RTW decision-making. Intervention mapping provided a useful framework to develop a comprehensive RTW program tailored to the Ontario setting.

In Preparation of the Nationwide Dissemination of the School-Based Obesity Prevention Program DOiT: Stepwise Development Applying the Intervention Mapping Protocol

ERIC Educational Resources Information Center

van Nassau, Femke; Singh, Amika S.; van Mechelen, Willem; Brug, Johannes; Chin A. Paw, Mai J. M.

2014-01-01

Background: The school-based Dutch Obesity Intervention in Teenagers (DOiT) program is an evidence-based obesity prevention program. In preparation for dissemination throughout the Netherlands, this study aimed to adapt the initial program and to develop an implementation strategy and materials. Methods: We revisited the Intervention Mapping (IM)…

Kalman/Map filtering-aided fast normalized cross correlation-based Wi-Fi fingerprinting location sensing.

PubMed

Sun, Yongliang; Xu, Yubin; Li, Cheng; Ma, Lin

2013-11-13

A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF) that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results.

Kalman/Map Filtering-Aided Fast Normalized Cross Correlation-Based Wi-Fi Fingerprinting Location Sensing

PubMed Central

Sun, Yongliang; Xu, Yubin; Li, Cheng; Ma, Lin

2013-01-01

A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF) that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results. PMID:24233027

Achievement goals, competition appraisals, and the well- and ill-being of elite youth soccer players over two competitive seasons.

PubMed

Adie, James W; Duda, Joan L; Ntoumanis, Nikos

2010-08-01

Grounded in the 2 x 2 achievement goal framework (Elliot & McGregor, 2001), the purpose of this study was to investigate the temporal relationships between achievement goals, competition appraisals and indices of psychological and emotional welfare among elite adolescent soccer players. A subsidiary aim was to ascertain the mediational role of competition appraisals in explaining the potential achievement goal and well-/ill-being relationships. Ninety-one boys (mean age = 13.82 years) involved in an elite soccer program completed multisection questionnaires capturing the targeted variables. Measures were obtained on five occasions across two competitive seasons. Multilevel regression analyses revealed that MAp goals positively, and MAv goals negatively, predicted within-person changes in well-being over two seasons. PAp goal adoption was positively associated to within-person changes in negative affect. PAv goals corresponded negatively to between-person mean differences in positive affect. The results of the indirect effects showed challenge appraisals accounted for within-person associations between a MAp goal focus and well- and ill-being over time. The present findings provide only partial support for the utility of the 2 x 2 achievement goal framework in predicting young athletes' psychological and emotional functioning in an elite youth sport setting.

Use of Mapping and Spatial and Space-Time Modeling Approaches in Operational Control of Aedes aegypti and Dengue

PubMed Central

Eisen, Lars; Lozano-Fuentes, Saul

2009-01-01

The aims of this review paper are to 1) provide an overview of how mapping and spatial and space-time modeling approaches have been used to date to visualize and analyze mosquito vector and epidemiologic data for dengue; and 2) discuss the potential for these approaches to be included as routine activities in operational vector and dengue control programs. Geographical information system (GIS) software are becoming more user-friendly and now are complemented by free mapping software that provide access to satellite imagery and basic feature-making tools and have the capacity to generate static maps as well as dynamic time-series maps. Our challenge is now to move beyond the research arena by transferring mapping and GIS technologies and spatial statistical analysis techniques in user-friendly packages to operational vector and dengue control programs. This will enable control programs to, for example, generate risk maps for exposure to dengue virus, develop Priority Area Classifications for vector control, and explore socioeconomic associations with dengue risk. PMID:19399163

Cartographic standards to improve maps produced by the Forest Inventory and Analysis program

Treesearch

Charles H. (Hobie) Perry; Mark D. Nelson

2009-01-01

The Forest Service, U.S. Department of Agriculture's Forest Inventory and Analysis (FIA) program is incorporating an increasing number of cartographic products in reports, publications, and presentations. To create greater quality and consistency within the national FIA program, a Geospatial Standards team developed cartographic design standards for FIA map...

ECOREGIONAL GAP ANALYSIS OF THE SOUTHWESTERN UNITED STATES: THE SOUTHWEST REGIONAL GAP ANALYSIS PROJECT FINAL REPORT

EPA Science Inventory

The Gap Analysis Program is a national program with the mission of developing key datasets needed to assess biological diversity across the nation. The primary objectives of the Gap Analysis Program are: (1) Land Cover Mapping – to map the distributions of natural communities; (2...

Assessment of training needs and preferences for geographic information systems (GIS) mapping in state comprehensive cancer-control programs.

PubMed

Hopfer, Suellen; Chadwick, Amy E; Parrott, Roxanne L; Ghetian, Christie B; Lengerich, Eugene J

2009-10-01

Geographic information systems (GIS) mapping technologies have potential to advance public health promotion by mapping regional differences in attributes (e.g., disease burden, environmental exposures, access to health care services) to suggest priorities for public health interventions. Training in GIS for comprehensive cancer control (CCC) has been overlooked. State CCC programs' GIS training needs were assessed by interviewing 49 state CCC directors. A majority perceived a need for GIS training, slightly more than half of state CCC programs had access to geocoded data, and the majority of programs did not require continuing education credits of their staff. CCC directors perceived judging maps and realizing their limitations as important skills and identified epidemiologists, CCC staff, public health officials, policy makers, and cancer coalition members as training audiences. They preferred in-class training sessions that last a few hours to a day. Lessons learned are shared to develop training programs with translatable GIS skills for CCC.

Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions.

PubMed

Truong, Tuyet T A; Hardy, Giles E St J; Andrew, Margaret E

2017-01-01

Invasive weeds are a serious problem worldwide, threatening biodiversity and damaging economies. Modeling potential distributions of invasive weeds can prioritize locations for monitoring and control efforts, increasing management efficiency. Forecasts of invasion risk at regional to continental scales are enabled by readily available downscaled climate surfaces together with an increasing number of digitized and georeferenced species occurrence records and species distribution modeling techniques. However, predictions at a finer scale and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Contemporary remote sensing (RS) data can enhance predictions by providing a range of spatial environmental data products at fine scale beyond climatic variables only. In this study, we used the Global Biodiversity Information Facility (GBIF) and empirical maximum entropy (MaxEnt) models to model the potential distributions of 14 invasive plant species across Southeast Asia (SEA), selected from regional and Vietnam's lists of priority weeds. Spatial environmental variables used to map invasion risk included bioclimatic layers and recent representations of global land cover, vegetation productivity (GPP), and soil properties developed from Earth observation data. Results showed that combining climate and RS data reduced predicted areas of suitable habitat compared with models using climate or RS data only, with no loss in model accuracy. However, contributions of RS variables were relatively limited, in part due to uncertainties in the land cover data. We strongly encourage greater adoption of quantitative remotely sensed estimates of ecosystem structure and function for habitat suitability modeling. Through comprehensive maps of overall predicted area and diversity of invasive species, we found that among lifeforms (herb, shrub, and vine), shrub species have higher potential invasion risk in SEA. Native invasive species, which are often overlooked in weed risk assessment, may be as serious a problem as non-native invasive species. Awareness of invasive weeds and their environmental impacts is still nascent in SEA and information is scarce. Freely available global spatial datasets, not least those provided by Earth observation programs, and the results of studies such as this one provide critical information that enables strategic management of environmental threats such as invasive species.

SU-E-T-280: Reconstructed Rectal Wall Dose Map-Based Verification of Rectal Dose Sparing Effect According to Rectum Definition Methods and Dose Perturbation by Air Cavity in Endo-Rectal Balloon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, J; Research Institute of Biomedical Engineering, The Catholic University of Korea, Seoul; Park, H

Purpose: Dosimetric effect and discrepancy according to the rectum definition methods and dose perturbation by air cavity in an endo-rectal balloon (ERB) were verified using rectal-wall (Rwall) dose maps considering systematic errors in dose optimization and calculation accuracy in intensity-modulated radiation treatment (IMRT) for prostate cancer patients. Methods: When the inflated ERB having average diameter of 4.5 cm and air volume of 100 cc is used for patient, Rwall doses were predicted by pencil-beam convolution (PBC), anisotropic analytic algorithm (AAA), and AcurosXB (AXB) with material assignment function. The errors of dose optimization and calculation by separating air cavity from themore » whole rectum (Rwhole) were verified with measured rectal doses. The Rwall doses affected by the dose perturbation of air cavity were evaluated using a featured rectal phantom allowing insert of rolled-up gafchromic films and glass rod detectors placed along the rectum perimeter. Inner and outer Rwall doses were verified with reconstructed predicted rectal wall dose maps. Dose errors and extent at dose levels were evaluated with estimated rectal toxicity. Results: While AXB showed insignificant difference of target dose coverage, Rwall doses underestimated by up to 20% in dose optimization for the Rwhole than Rwall at all dose range except for the maximum dose. As dose optimization for Rwall was applied, the Rwall doses presented dose error less than 3% between dose calculation algorithm except for overestimation of maximum rectal dose up to 5% in PBC. Dose optimization for Rwhole caused dose difference of Rwall especially at intermediate doses. Conclusion: Dose optimization for Rwall could be suggested for more accurate prediction of rectal wall dose prediction and dose perturbation effect by air cavity in IMRT for prostate cancer. This research was supported by the Leading Foreign Research Institute Recruitment Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (MSIP) (Grant No. 200900420)« less

Contemporary Remotely Sensed Data Products Refine Invasive Plants Risk Mapping in Data Poor Regions

PubMed Central

Truong, Tuyet T. A.; Hardy, Giles E. St. J.; Andrew, Margaret E.

2017-01-01

Invasive weeds are a serious problem worldwide, threatening biodiversity and damaging economies. Modeling potential distributions of invasive weeds can prioritize locations for monitoring and control efforts, increasing management efficiency. Forecasts of invasion risk at regional to continental scales are enabled by readily available downscaled climate surfaces together with an increasing number of digitized and georeferenced species occurrence records and species distribution modeling techniques. However, predictions at a finer scale and in landscapes with less topographic variation may require predictors that capture biotic processes and local abiotic conditions. Contemporary remote sensing (RS) data can enhance predictions by providing a range of spatial environmental data products at fine scale beyond climatic variables only. In this study, we used the Global Biodiversity Information Facility (GBIF) and empirical maximum entropy (MaxEnt) models to model the potential distributions of 14 invasive plant species across Southeast Asia (SEA), selected from regional and Vietnam’s lists of priority weeds. Spatial environmental variables used to map invasion risk included bioclimatic layers and recent representations of global land cover, vegetation productivity (GPP), and soil properties developed from Earth observation data. Results showed that combining climate and RS data reduced predicted areas of suitable habitat compared with models using climate or RS data only, with no loss in model accuracy. However, contributions of RS variables were relatively limited, in part due to uncertainties in the land cover data. We strongly encourage greater adoption of quantitative remotely sensed estimates of ecosystem structure and function for habitat suitability modeling. Through comprehensive maps of overall predicted area and diversity of invasive species, we found that among lifeforms (herb, shrub, and vine), shrub species have higher potential invasion risk in SEA. Native invasive species, which are often overlooked in weed risk assessment, may be as serious a problem as non-native invasive species. Awareness of invasive weeds and their environmental impacts is still nascent in SEA and information is scarce. Freely available global spatial datasets, not least those provided by Earth observation programs, and the results of studies such as this one provide critical information that enables strategic management of environmental threats such as invasive species. PMID:28555147

History of greenness mapping at the EROS data center

USGS Publications Warehouse

Van Beek, Carolyn; Vandersnick, Richard

1993-01-01

In 1987, the U.S. Geological Survey's EROS Data Center (EDC)installed a system to acquire, process, and distribute advanced very high resolution radiometer (AVHRR) satellite image data collected over North America. Using this system, the EDC began an experimental greenness mapping program as part of the U.S. Agency for the International Development Famine Early Warning System. The program used the greenness information derived from AVHRR data to identify potential outbreaks of locusts and grasshoppers in the Sahelian region of Africa. In 1988, the EDC began greenness mapping projects in Africa and the northern Great Plains of the United States. In 1989, the system was augmented to acquire AVHRR information for the rest of the world. As a result, the greenness mapping program was able to collect data for fire danger assessment, agricultural assessment, and land characterization. Illustrations of each of the mapping projects trace the chronology of the greenness mapping program at the EDC. Displays represent the initial activity in Africa and the transition of the north Great Plains project to the current conterminous U.S. project. The program's expansion to include Alaska, Eurasia, a prototype North America data set, and ultimately, an experimental global land 1-km product is also shown. The poster describes major technical advances in data processing, the development of derivative products, the magnitude of the data volume of each level, and major applications.

Intervention mapping: a process for developing theory- and evidence-based health education programs.

PubMed

Bartholomew, L K; Parcel, G S; Kok, G

1998-10-01

The practice of health education involves three major program-planning activities: needs assessment, program development, and evaluation. Over the past 20 years, significant enhancements have been made to the conceptual base and practice of health education. Models that outline explicit procedures and detailed conceptualization of community assessment and evaluation have been developed. Other advancements include the application of theory to health education and promotion program development and implementation. However, there remains a need for more explicit specification of the processes by which one uses theory and empirical findings to develop interventions. This article presents the origins, purpose, and description of Intervention Mapping, a framework for health education intervention development. Intervention Mapping is composed of five steps: (1) creating a matrix of proximal program objectives, (2) selecting theory-based intervention methods and practical strategies, (3) designing and organizing a program, (4) specifying adoption and implementation plans, and (5) generating program evaluation plans.

First Steps in Initiating an Effective Maternal, Neonatal, and Child Health Program in Urban Slums: the BRAC Manoshi Project's Experience with Community Engagement, Social Mapping, and Census Taking in Bangladesh.

PubMed

Marcil, Lucy; Afsana, Kaosar; Perry, Henry B

2016-02-01

The processes for implementing effective programs at scale in low-income countries have not been well-documented in the peer-reviewed literature. This article describes the initial steps taken by one such program--the BRAC Manoshi Project, which now reaches a population of 6.9 million. The project has achieved notable increases in facility births and reductions in maternal and neonatal mortality. The focus of the paper is on the initial steps--community engagement, social mapping, and census taking. Community engagement began with (1) engaging local leaders, (2) creating Maternal, Neonatal, and Child Health Committees for populations of approximately 10,000 people, (3) responding to advice from the community, (4) social mapping of the community, and (5) census taking. Social mapping involved community members working with BRAC staff to map all important physical features that affect how the community carries out its daily functions--such as alleys, lanes and roads, schools, mosques, markets, pharmacies, health facilities, latrine sites, and ponds. As the social mapping progressed, it became possible to conduct household censuses with maps identifying every household and listing family members by household. Again, this was a process of collaboration between BRAC staff and community members. Thus, social mapping and census taking were also instrumental for advancing community engagement. These three processes-community engagement, social mapping, and census taking--can be valuable strategies for strengthening health programs in urban slum settings of low-income countries.

Carbon mapping of Argentine savannas: Using fractional tree cover to scale from field to region

NASA Astrophysics Data System (ADS)

González-Roglich, M.; Swenson, J. J.

2015-12-01

Programs which intend to maintain or enhance carbon (C) stocks in natural ecosystems are promising, but require detailed and spatially explicit C distribution models to monitor the effectiveness of management interventions. Savanna ecosystems are significant components of the global C cycle, covering about one fifth of the global land mass, but they have received less attention in C monitoring protocols. Our goal was to estimate C storage across a broad savanna ecosystem using field surveys and freely available satellite images. We first mapped tree canopies at 2.5 m resolution with a spatial subset of high resolution panchromatic images to then predict regional wall-to-wall tree percent cover using 30-m Landsat imagery and the Random Forests algorithms. We found that a model with summer and winter spectral indices from Landsat, climate and topography performed best. Using a linear relationship between C and % tree cover, we then predicted tree C stocks across the gradient of tree cover, explaining 87 % of the variability. The spatially explicit validation of the tree C model with field-measured C-stocks revealed an RMSE of 8.2 tC/ha which represented ~30% of the mean C stock for areas with tree cover, comparable to studies based on more advanced remote sensing methods, such as LiDAR and RADAR. Sample spatial distribution highly affected the performance of the RF models in predicting tree cover, raising concerns regarding the predictive capabilities of the model in areas for which training data is not present. The 50,000 km2 has ~41 Tg C, which could be released to the atmosphere if agricultural pressure intensifies in this semiarid savanna.

Mapping Global Potential Risk of Mango Sudden Decline Disease Caused by Ceratocystis fimbriata.

PubMed

Galdino, Tarcísio Visintin da Silva; Kumar, Sunil; Oliveira, Leonardo S S; Alfenas, Acelino C; Neven, Lisa G; Al-Sadi, Abdullah M; Picanço, Marcelo C

2016-01-01

The Mango Sudden Decline (MSD), also referred to as Mango Wilt, is an important disease of mango in Brazil, Oman and Pakistan. This fungus is mainly disseminated by the mango bark beetle, Hypocryphalus mangiferae (Stebbing), by infected plant material, and the infested soils where it is able to survive for long periods. The best way to avoid losses due to MSD is to prevent its establishment in mango production areas. Our objectives in this study were to: (1) predict the global potential distribution of MSD, (2) identify the mango growing areas that are under potential risk of MSD establishment, and (3) identify climatic factors associated with MSD distribution. Occurrence records were collected from Brazil, Oman and Pakistan where the disease is currently known to occur in mango. We used the correlative maximum entropy based model (MaxEnt) algorithm to assess the global potential distribution of MSD. The MaxEnt model predicted suitable areas in countries where the disease does not already occur in mango, but where mango is grown. Among these areas are the largest mango producers in the world including India, China, Thailand, Indonesia, and Mexico. The mean annual temperature, precipitation of coldest quarter, precipitation seasonality, and precipitation of driest month variables contributed most to the potential distribution of MSD disease. The mango bark beetle vector is known to occur beyond the locations where MSD currently exists and where the model predicted suitable areas, thus showing a high likelihood for disease establishment in areas predicted by our model. Our study is the first to map the potential risk of MSD establishment on a global scale. This information can be used in designing strategies to prevent introduction and establishment of MSD disease, and in preparation of efficient pest risk assessments and monitoring programs.

Mapping Global Potential Risk of Mango Sudden Decline Disease Caused by Ceratocystis fimbriata

PubMed Central

Oliveira, Leonardo S. S.; Alfenas, Acelino C.; Neven, Lisa G.; Al-Sadi, Abdullah M.

2016-01-01

The Mango Sudden Decline (MSD), also referred to as Mango Wilt, is an important disease of mango in Brazil, Oman and Pakistan. This fungus is mainly disseminated by the mango bark beetle, Hypocryphalus mangiferae (Stebbing), by infected plant material, and the infested soils where it is able to survive for long periods. The best way to avoid losses due to MSD is to prevent its establishment in mango production areas. Our objectives in this study were to: (1) predict the global potential distribution of MSD, (2) identify the mango growing areas that are under potential risk of MSD establishment, and (3) identify climatic factors associated with MSD distribution. Occurrence records were collected from Brazil, Oman and Pakistan where the disease is currently known to occur in mango. We used the correlative maximum entropy based model (MaxEnt) algorithm to assess the global potential distribution of MSD. The MaxEnt model predicted suitable areas in countries where the disease does not already occur in mango, but where mango is grown. Among these areas are the largest mango producers in the world including India, China, Thailand, Indonesia, and Mexico. The mean annual temperature, precipitation of coldest quarter, precipitation seasonality, and precipitation of driest month variables contributed most to the potential distribution of MSD disease. The mango bark beetle vector is known to occur beyond the locations where MSD currently exists and where the model predicted suitable areas, thus showing a high likelihood for disease establishment in areas predicted by our model. Our study is the first to map the potential risk of MSD establishment on a global scale. This information can be used in designing strategies to prevent introduction and establishment of MSD disease, and in preparation of efficient pest risk assessments and monitoring programs. PMID:27415625

Computational Prediction of Atomic Structures of Helical Membrane Proteins Aided by EM Maps

PubMed Central

Kovacs, Julio A.; Yeager, Mark; Abagyan, Ruben

2007-01-01

Integral membrane proteins pose a major challenge for protein-structure prediction because only ≈100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane α-helices. However, when an intermediate-resolution electron microscopy (EM) map is available, it can be used to provide restraints which, in combination with a suitable computational protocol, make structure prediction feasible. In this work we present such a protocol, which proceeds in three stages: 1), generation of an ensemble of α-helices by flexible fitting into each of the density rods in the low-resolution EM map, spanning a range of rotational angles around the main helical axes and translational shifts along the density rods; 2), fast optimization of side chains and scoring of the resulting conformations; and 3), refinement of the lowest-scoring conformations with internal coordinate mechanics, by optimizing the van der Waals, electrostatics, hydrogen bonding, torsional, and solvation energy contributions. In addition, our method implements a penalty term through a so-called tethering map, derived from the EM map, which restrains the positions of the α-helices. The protocol was validated on three test cases: GpA, KcsA, and MscL. PMID:17496035

HIV Pre-exposure Prophylaxis Program Implementation Using Intervention Mapping.

PubMed

Flash, Charlene A; Frost, Elizabeth L T; Giordano, Thomas P; Amico, K Rivet; Cully, Jeffrey A; Markham, Christine M

2018-04-01

HIV pre-exposure prophylaxis has been proven to be an effective tool in HIV prevention. However, numerous barriers still exist in pre-exposure prophylaxis implementation. The framework of Intervention Mapping was used from August 2016 to October 2017 to describe the process of adoption, implementation, and maintenance of an HIV prevention program from 2012 through 2017 in Houston, Texas, that is nested within a county health system HIV clinic. Using the tasks outlined in the Intervention Mapping framework, potential program implementers were identified, outcomes and performance objectives established, matrices of change objectives created, and methods and practical applications formed. Results include the formation of three matrices that document program outcomes, change agents involved in the process, and the determinants needed to facilitate program adoption, implementation, and maintenance. Key features that facilitated successful program adoption and implementation were obtaining leadership buy-in, leveraging existing resources, systematic evaluation of operations, ongoing education for both clinical and nonclinical staff, and attention to emergent issues during launch. The utilization of Intervention Mapping to delineate the program planning steps can provide a model for pre-exposure prophylaxis implementation in other settings. Copyright © 2018. Published by Elsevier Inc.

Assessment and Mapping of Forest Parcel Sizes

Treesearch

Brett J. Butler; Susan L. King

2005-01-01

A method for analyzing and mapping forest parcel sizes in the Northeastern United States is presented. A decision tree model was created that predicts forest parcel size from spatially explicit predictor variables: population density, State, percentage forest land cover, and road density. The model correctly predicted parcel size for 60 percent of the observations in a...

CPC - Monitoring & Data: Pacific Island Climate Data

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Monitoring and Data > Pacific Islands Climate Data & Maps island stations. NOAA/ National Weather Service NOAA Center for Weather and Climate Prediction Climate

Climate Prediction Center - Monitoring and Data

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News monthly data, time series, and maps for various climate parameters, such as precipitation, temperature Oscillations (ENSO) and other climate patterns such as the North Atlantic and Pacific Decadal Oscillations, and

A study of mapping exogenous knowledge representations into CONFIG

NASA Technical Reports Server (NTRS)

Mayfield, Blayne E.

1992-01-01

Qualitative reasoning is reasoning with a small set of qualitative values that is an abstraction of a larger and perhaps infinite set of quantitative values. The use of qualitative and quantitative reasoning together holds great promise for performance improvement in applications that suffer from large and/or imprecise knowledge domains. Included among these applications are the modeling, simulation, analysis, and fault diagnosis of physical systems. Several research groups continue to discover and experiment with new qualitative representations and reasoning techniques. However, due to the diversity of these techniques, it is difficult for the programs produced to exchange system models easily. The availability of mappings to transform knowledge from the form used by one of these programs to that used by another would open the doors for comparative analysis of these programs in areas such as completeness, correctness, and performance. A group at the Johnson Space Center (JSC) is working to develop CONFIG, a prototype qualitative modeling, simulation, and analysis tool for fault diagnosis applications in the U.S. space program. The availability of knowledge mappings from the programs produced by other research groups to CONFIG may provide savings in CONFIG's development costs and time, and may improve CONFIG's performance. The study of such mappings is the purpose of the research described in this paper. Two other research groups that have worked with the JSC group in the past are the Northwest University Group and the University of Texas at Austin Group. The former has produced a qualitative reasoning tool named SIMGEN, and the latter has produced one named QSIM. Another program produced by the Austin group is CC, a preprocessor that permits users to develop input for eventual use by QSIM, but in a more natural format. CONFIG and CC are both based on a component-connection ontology, so a mapping from CC's knowledge representation to CONFIG's knowledge representation was chosen as the focus of this study. A mapping from CC to CONFIG was developed. Due to differences between the two programs, however, the mapping transforms some of the CC knowledge to CONFIG as documentation rather than as knowledge in a form useful to computation. The study suggests that it may be worthwhile to pursue the mappings further. By implementing the mapping as a program, actual comparisons of computational efficiency and quality of results can be made between the QSIM and CONFIG programs. A secondary study may reveal that the results of the two programs augment one another, contradict one another, or differ only slightly. If the latter, the qualitative reasoning techniques may be compared in other areas, such as computational efficiency.

Meta-Analysis of Land Use / Land Cover Change Factors in the Conterminous US and Prediction of Potential Working Timberlands in the US South from FIA Inventory Plots and NLCD Cover Maps

NASA Astrophysics Data System (ADS)

Jeuck, James A.

This dissertation consists of research projects related to forest land use / land cover (LULC): (1) factors predicting LULC change and (2) methodology to predict particular forest use, or "potential working timberland" (PWT), from current forms of land data. The first project resulted in a published paper, a meta-analysis of 64 econometric models from 47 studies predicting forest land use changes. The response variables, representing some form of forest land change, were organized into four groups: forest conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified, from 21 F2A models, 21 F2D models, 12 F2NF models, and 10 U2D models. These variables were organized into a hierarchy of 119 independent variable groups, 15 categories, and 4 econometric drivers suitable for conducting simple vote count statistics. Vote counts were summarized at the independent variable group level and formed into ratios estimating the predictive success of each variable group. Two ratio estimates were developed based on (1) proportion of times independent variables successfully achieved statistical significance (p ≤0.10), and (2) proportion of times independent variables successfully met the original researchers'expectations. In F2D models, popular independent variables such as population, income, and urban proximity often achieved statistical significance. In F2A models, popular independent variables such as forest and agricultural rents and costs, governmental programs, and site quality often achieved statistical significance. In U2D models, successful independent variables included urban rents and costs, zoning issues concerning forestland loss, site quality, urban proximity, population, and income. F2NF models high success variables were found to be agricultural rents, site quality, population, and income. This meta-analysis provides insight into the general success of econometric independent variables for future forest use or cover change research. The second part of this dissertation developed a method for predicting area estimates and spatial distribution of PWT in the US South. This technique determined land use from USFS Forest Inventory and Analysis (FIA) and land cover from the National Land Cover Database (NLCD). Three dependent variable forms (DV Forms) were derived from the FIA data: DV Form 1, timberland, other; DV Form 2, short timberland, tall timberland, agriculture, other; and DV Form 3, short hardwood (HW) timberland, tall HW timberland, short softwood (SW) timberland, tall SW timberland, agriculture, other. The prediction accuracy of each DV Form was investigated using both random forest model and logistic regression model specifications and data optimization techniques. Model verification employing a "leave-group-out" Monte Carlo simulation determined the selection of a stratified version of the random forest model using one-year NLCD observations with an overall accuracy of 0.53-0.94. The lower accuracy side of the range was when predictions were made from an aggregated NLCD land cover class "grass_shrub". The selected model specification was run using 2011 NLCD and the other predictor variables to produce three levels of timberland prediction and probability maps for the US South. Spatial masks removed areas unlikely to be working forests (protected and urbanized lands) resulting in PWT maps. The area of the resulting maps compared well with USFS area estimates and masked PWT maps and had an 8-11% reduction of the USFS timberland estimate for the US South compared to the DV Form. Change analysis of the 2011 NLCD to PWT showed (1) the majority of the short timberland came from NLCD grass_shrub; (2) the majority of NLCD grass_shrub predicted into tall timberland, and (3) NLCD grass_shrub was more strongly associated with timberland in the Coastal Plain. Resulting map products provide practical analytical tools for those interested in studying the area and distribution of PWT in the US South.

Reachability Maps for In Situ Operations

NASA Technical Reports Server (NTRS)

Deen, Robert G.; Leger, Patrick C.; Robinson, Matthew L.; Bonitz, Robert G.

2013-01-01

This work covers two programs that accomplish the same goal: creation of a "reachability map" from stereo imagery that tells where operators of a robotic arm can reach or touch the surface, and with which instruments. The programs are "marsreach" (for MER) and "phxreach." These programs make use of the planetary image geometry (PIG) library. However, unlike the other programs, they are not multi-mission. Because of the complexity of arm kinematics, the programs are specific to each mission.

Scoping of Flood Hazard Mapping Needs for Androscoggin County, Maine

USGS Publications Warehouse

Schalk, Charles W.; Dudley, Robert W.

2007-01-01

Background The Federal Emergency Management Agency (FEMA) developed a plan in 1997 to modernize the FEMA flood mapping program. FEMA flood maps delineate flood hazard areas in support of the National Flood Insurance Program (NFIP). FEMA's plan outlined the steps necessary to update FEMA's flood maps for the nation to a seamless digital format and streamline FEMA's operations in raising public awareness of the importance of the maps and responding to requests to revise them. The modernization of flood maps involves conversion of existing information to digital format and integration of improved flood hazard data as needed and as funds allow. To determine flood mapping modernization needs, FEMA has established specific scoping activities to be done on a county-by-county basis for identifying and prioritizing requisite flood-mapping activities for map modernization. The U.S. Geological Survey (USGS), in cooperation with FEMA and the Maine Floodplain Management Program (MFMP) State Planning Office, began scoping work in 2006 for Androscoggin County. Scoping activities included assembling existing data and map needs information for communities in Androscoggin County, documentation of data, contacts, community meetings, and prioritized mapping needs in a final scoping report (this document), and updating the Mapping Needs Update Support System (MNUSS) Database with information gathered during the scoping process. The average age of the FEMA floodplain maps in Androscoggin County, Maine, is at least 17 years. Most studies were published in the early 1990s, and some towns have partial maps that are more recent than their study date. Since the studies were done, development has occurred in many of the watersheds and the characteristics of the watersheds have changed with time. Therefore, many of the older studies may not depict current conditions nor accurately estimate risk in terms of flood heights or flood mapping.

Scoping of Flood Hazard Mapping Needs for Lincoln County, Maine

USGS Publications Warehouse

Schalk, Charles W.; Dudley, Robert W.

2007-01-01

Background The Federal Emergency Management Agency (FEMA) developed a plan in 1997 to modernize the FEMA flood mapping program. FEMA flood maps delineate flood hazard areas in support of the National Flood Insurance Program (NFIP). FEMA's plan outlined the steps necessary to update FEMA's flood maps for the nation to a seamless digital format and streamline FEMA's operations in raising public awareness of the importance of the maps and responding to requests to revise them. The modernization of flood maps involves conversion of existing information to digital format and integration of improved flood hazard data as needed. To determine flood mapping modernization needs, FEMA has established specific scoping activities to be done on a county-by-county basis for identifying and prioritizing requisite flood-mapping activities for map modernization. The U.S. Geological Survey (USGS), in cooperation with FEMA and the Maine Floodplain Management Program (MFMP) State Planning Office, began scoping work in 2006 for Lincoln County. Scoping activities included assembling existing data and map needs information for communities in Lincoln County, documentation of data, contacts, community meetings, and prioritized mapping needs in a final scoping report (this document), and updating the Mapping Needs Update Support System (MNUSS) database with information gathered during the scoping process. The average age of the FEMA floodplain maps in Lincoln County, Maine is at least 17 years. Many of these studies were published in the mid- to late-1980s, and some towns have partial maps that are more recent than their study. However, in the ensuing 15-20 years, development has occurred in many of the watersheds, and the characteristics of the watersheds have changed with time. Therefore, many of the older studies may not depict current conditions nor accurately estimate risk in terms of flood heights or flood mapping.

The Pilot Lunar Geologic Mapping Project: Summary Results and Recommendations from the Copernicus Quadrangle

NASA Technical Reports Server (NTRS)

Skinner, J. A., Jr.; Gaddis, L. R.; Hagerty, J. J.

2010-01-01

The first systematic lunar geologic maps were completed at 1:1M scale for the lunar near side during the 1960s using telescopic and Lunar Orbiter (LO) photographs [1-3]. The program under which these maps were completed established precedents for map base, scale, projection, and boundaries in order to avoid widely discrepant products. A variety of geologic maps were subsequently produced for various purposes, including 1:5M scale global maps [4-9] and large scale maps of high scientific interest (including the Apollo landing sites) [10]. Since that time, lunar science has benefitted from an abundance of surface information, including high resolution images and diverse compositional data sets, which have yielded a host of topical planetary investigations. The existing suite of lunar geologic maps and topical studies provide exceptional context in which to unravel the geologic history of the Moon. However, there has been no systematic approach to lunar geologic mapping since the flight of post-Apollo scientific orbiters. Geologic maps provide a spatial and temporal framework wherein observations can be reliably benchmarked and compared. As such, a lack of a systematic mapping program means that modern (post- Apollo) data sets, their scientific ramifications, and the lunar scientists who investigate these data, are all marginalized in regard to geologic mapping. Marginalization weakens the overall understanding of the geologic evolution of the Moon and unnecessarily partitions lunar research. To bridge these deficiencies, we began a pilot geologic mapping project in 2005 as a means to assess the interest, relevance, and technical methods required for a renewed lunar geologic mapping program [11]. Herein, we provide a summary of the pilot geologic mapping project, which focused on the geologic materials and stratigraphic relationships within the Copernicus quadrangle (0-30degN, 0-45degW).

Can early host responses to mycobacterial infection predict eventual disease outcomes?

PubMed

de Silva, Kumudika; Begg, Douglas J; Plain, Karren M; Purdie, Auriol C; Kawaji, Satoko; Dhand, Navneet K; Whittington, Richard J

2013-11-01

Diagnostic tests used for Johne's disease in sheep either have poor sensitivity and specificity or only detect disease in later stages of infection. Predicting which of the infected sheep are likely to become infectious later in life is currently not feasible and continues to be a major hindrance in disease control. We conducted this longitudinal study to investigate if a suite of diagnostic tests conducted in Mycobacterium avium subspecies paratuberculosis (MAP) exposed lambs at 4 months post infection can accurately predict their clinical status at 12 months post infection. We tracked cellular and humoral responses and quantity of MAP shedding for up to 12 months post challenge in 20 controls and 37 exposed sheep. Infection was defined at necropsy by tissue culture and disease spectrum by lesion type. Data were analysed using univariable and multivariable logistic regression models and a subset of variables from the earliest period post inoculation (4 months) was selected for predicting disease outcomes later on (12 months). Sensitivity and specificity of tests and their combinations in series and parallel were determined. Early elevation in faecal MAP DNA quantity and a lower interferon gamma (IFNγ) response were significantly associated with sheep becoming infectious as well as progressing to severe disease. Conversely, early low faecal MAP DNA and higher interleukin-10 responses were significantly associated with an exposed animal developing protective immunity. Combination of early elevated faecal MAP DNA or lower IFNγ response had the highest sensitivity (75%) and specificity (81%) for identifying sheep that would become infectious. Collectively, these results highlight the potential for combined test interpretation to aid in the early prediction of sheep susceptibility to MAP infection. Copyright © 2013 Elsevier B.V. All rights reserved.

Decomposition Technique for Remaining Useful Life Prediction

NASA Technical Reports Server (NTRS)

Saha, Bhaskar (Inventor); Goebel, Kai F. (Inventor); Saxena, Abhinav (Inventor); Celaya, Jose R. (Inventor)

2014-01-01

The prognostic tool disclosed here decomposes the problem of estimating the remaining useful life (RUL) of a component or sub-system into two separate regression problems: the feature-to-damage mapping and the operational conditions-to-damage-rate mapping. These maps are initially generated in off-line mode. One or more regression algorithms are used to generate each of these maps from measurements (and features derived from these), operational conditions, and ground truth information. This decomposition technique allows for the explicit quantification and management of different sources of uncertainty present in the process. Next, the maps are used in an on-line mode where run-time data (sensor measurements and operational conditions) are used in conjunction with the maps generated in off-line mode to estimate both current damage state as well as future damage accumulation. Remaining life is computed by subtracting the instance when the extrapolated damage reaches the failure threshold from the instance when the prediction is made.

Creating Geologically Based Radon Potential Maps for Kentucky

NASA Astrophysics Data System (ADS)

Overfield, B.; Hahn, E.; Wiggins, A.; Andrews, W. M., Jr.

2017-12-01

Radon potential in the United States, Kentucky in particular, has historically been communicated using a single hazard level for each county; however, physical phenomena are not controlled by administrative boundaries, so single-value county maps do not reflect the significant variations in radon potential in each county. A more accurate approach uses bedrock geology as a predictive tool. A team of nurses, health educators, statisticians, and geologists partnered to create 120 county maps showing spatial variations in radon potential by intersecting residential radon test kit results (N = 60,000) with a statewide 1:24,000-scale bedrock geology coverage to determine statistically valid radon-potential estimates for each geologic unit. Maps using geology as a predictive tool for radon potential are inherently more detailed than single-value county maps. This mapping project revealed that areas in central and south-central Kentucky with the highest radon potential are underlain by shales and karstic limestones.

Intraspecific scaling of arterial blood pressure in the Burmese python.

PubMed

Enok, Sanne; Slay, Christopher; Abe, Augusto S; Hicks, James W; Wang, Tobias

2014-07-01

Interspecific allometric analyses indicate that mean arterial blood pressure (MAP) increases with body mass of snakes and mammals. In snakes, MAP increases in proportion to the increased distance between the heart and the head, when the heart-head vertical distance is expressed as ρgh (where ρ is the density of blood, G: is acceleration due to gravity and h is the vertical distance above the heart), and the rise in MAP is associated with a larger heart to normalize wall stress in the ventricular wall. Based on measurements of MAP in Burmese pythons ranging from 0.9 to 3.7 m in length (0.20-27 kg), we demonstrate that although MAP increases with body mass, the rise in MAP is merely half of that predicted by heart-head distance. Scaling relationships within individual species, therefore, may not be accurately predicted by existing interspecific analyses. © 2014. Published by The Company of Biologists Ltd.

Mapping intra-urban malaria risk using high resolution satellite imagery: a case study of Dar es Salaam.

PubMed

Kabaria, Caroline W; Molteni, Fabrizio; Mandike, Renata; Chacky, Frank; Noor, Abdisalan M; Snow, Robert W; Linard, Catherine

2016-07-30

With more than half of Africa's population expected to live in urban settlements by 2030, the burden of malaria among urban populations in Africa continues to rise with an increasing number of people at risk of infection. However, malaria intervention across Africa remains focused on rural, highly endemic communities with far fewer strategic policy directions for the control of malaria in rapidly growing African urban settlements. The complex and heterogeneous nature of urban malaria requires a better understanding of the spatial and temporal patterns of urban malaria risk in order to design effective urban malaria control programs. In this study, we use remotely sensed variables and other environmental covariates to examine the predictability of intra-urban variations of malaria infection risk across the rapidly growing city of Dar es Salaam, Tanzania between 2006 and 2014. High resolution SPOT satellite imagery was used to identify urban environmental factors associated malaria prevalence in Dar es Salaam. Supervised classification with a random forest classifier was used to develop high resolution land cover classes that were combined with malaria parasite prevalence data to identify environmental factors that influence localized heterogeneity of malaria transmission and develop a high resolution predictive malaria risk map of Dar es Salaam. Results indicate that the risk of malaria infection varied across the city. The risk of infection increased away from the city centre with lower parasite prevalence predicted in administrative units in the city centre compared to administrative units in the peri-urban suburbs. The variation in malaria risk within Dar es Salaam was shown to be influenced by varying environmental factors. Higher malaria risks were associated with proximity to dense vegetation, inland water and wet/swampy areas while lower risk of infection was predicted in densely built-up areas. The predictive maps produced can serve as valuable resources for municipal councils aiming to shrink the extents of malaria across cities, target resources for vector control or intensify mosquito and disease surveillance. The semi-automated modelling process developed can be replicated in other urban areas to identify factors that influence heterogeneity in malaria risk patterns and detect vulnerable zones. There is a definite need to expand research into the unique epidemiology of malaria transmission in urban areas for focal elimination and sustained control agendas.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PubMed

Kropat, Georg; Bochud, Francois; Jaboyedoff, Michel; Laedermann, Jean-Pascal; Murith, Christophe; Palacios Gruson, Martha; Baechler, Sébastien

2015-09-01

According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information. Copyright © 2015 Elsevier Ltd. All rights reserved.

Examining occupational therapy education through faculty engagement in curriculum mapping and pedagogical reflection.

PubMed

MacNeil, Cheryl; Hand, Theresa

2014-01-01

This article discusses a 1-yr evaluation study of a master of science in occupational therapy program to examine curriculum content and pedagogical practices as a way to gauge program preparedness to move to a clinical doctorate. Faculty members participated in a multitiered qualitative study that included curriculum mapping, semistructured individual interviewing, and iterative group analysis. Findings indicate that curriculum mapping and authentic dialogue helped the program formulate a more streamlined and integrated curriculum with increased faculty collaboration. Curriculum mapping and collaborative pedagogical reflection are valuable evaluation strategies for examining preparedness to offer a clinical doctorate, enhancing a self-study process, and providing information for ongoing formative curriculum review. Copyright © 2014 by the American Occupational Therapy Association, Inc.

Mapping soil texture classes and optimization of the result by accuracy assessment

NASA Astrophysics Data System (ADS)

Laborczi, Annamária; Takács, Katalin; Bakacsi, Zsófia; Szabó, József; Pásztor, László

2014-05-01

There are increasing demands nowadays on spatial soil information in order to support environmental related and land use management decisions. The GlobalSoilMap.net (GSM) project aims to make a new digital soil map of the world using state-of-the-art and emerging technologies for soil mapping and predicting soil properties at fine resolution. Sand, silt and clay are among the mandatory GSM soil properties. Furthermore, soil texture class information is input data of significant agro-meteorological and hydrological models. Our present work aims to compare and evaluate different digital soil mapping methods and variables for producing the most accurate spatial prediction of texture classes in Hungary. In addition to the Hungarian Soil Information and Monitoring System as our basic data, digital elevation model and its derived components, geological database, and physical property maps of the Digital Kreybig Soil Information System have been applied as auxiliary elements. Two approaches have been applied for the mapping process. At first the sand, silt and clay rasters have been computed independently using regression kriging (RK). From these rasters, according to the USDA categories, we have compiled the texture class map. Different combinations of reference and training soil data and auxiliary covariables have resulted several different maps. However, these results consequentially include the uncertainty factor of the three kriged rasters. Therefore we have suited data mining methods as the other approach of digital soil mapping. By working out of classification trees and random forests we have got directly the texture class maps. In this way the various results can be compared to the RK maps. The performance of the different methods and data has been examined by testing the accuracy of the geostatistically computed and the directly classified results. We have used the GSM methodology to assess the most predictive and accurate way for getting the best among the several result maps. Acknowledgement: Our work was supported by the Hungarian National Scientific Research Foundation (OTKA, Grant No. K105167).

Spatial Prediction of Soil Classes by Using Soil Weathering Parameters Derived from vis-NIR Spectroscopy

NASA Astrophysics Data System (ADS)

Ramirez-Lopez, Leonardo; Alexandre Dematte, Jose

2010-05-01

There is consensus in the scientific community about the great need of spatial soil information. Conventional mapping methods are time consuming and involve high costs. Digital soil mapping has emerged as an area in which the soil mapping is optimized by the application of mathematical and statistical approaches, as well as the application of expert knowledge in pedology. In this sense, the objective of the study was to develop a methodology for the spatial prediction of soil classes by using soil spectroscopy methodologies related with fieldwork, spectral data from satellite image and terrain attributes in simultaneous. The studied area is located in São Paulo State, and comprised an area of 473 ha, which was covered by a regular grid (100 x 100 m). In each grid node was collected soil samples at two depths (layers A and B). There were extracted 206 samples from transect sections and submitted to soil analysis (clay, Al2O3, Fe2O3, SiO2 TiO2, and weathering index). The first analog soil class map (ASC-N) contains only soil information regarding from orders to subgroups of the USDA Soil Taxonomy System. The second (ASC-H) map contains some additional information related to some soil attributes like color, ferric levels and base sum. For the elaboration of the digital soil maps the data was divided into three groups: i) Predicted soil attributes of the layer B (related to the soil weathering) which were obtained by using a local soil spectral library; ii) Spectral bands data extracted from a Landsat image; and iii) Terrain parameters. This information was summarized by a principal component analysis (PCA) in each group. Digital soil maps were generated by supervised classification using a maximum likelihood method. The trainee information for this classification was extracted from five toposequences based on the analog soil class maps. The spectral models of weathering soil attributes shown a high predictive performance with low error (R2 0.71 to 0.90). The spatial prediction of these attributes also showed a high performance (validations with R2> 0.78). These models allowed to increase spatial resolution of soil weathering information. On the other hand, the comparison between the analog and digital soil maps showed a global accuracy of 69% for the ASC-N map and 62% in the ASC-H map, with kappa indices of 0.52 and 0.45 respectively.

Evaluation of automated global mapping of Reference Soil Groups of WRB2015

NASA Astrophysics Data System (ADS)

Mantel, Stephan; Caspari, Thomas; Kempen, Bas; Schad, Peter; Eberhardt, Einar; Ruiperez Gonzalez, Maria

2017-04-01

SoilGrids is an automated system that provides global predictions for standard numeric soil properties at seven standard depths down to 200 cm, currently at spatial resolutions of 1km and 250m. In addition, the system provides predictions of depth to bedrock and distribution of soil classes based on WRB and USDA Soil Taxonomy (ST). In SoilGrids250m(1), soil classes (WRB, version 2006) consist of the RSG and the first prefix qualifier, whereas in SoilGrids1km(2), the soil class was assessed at RSG level. Automated mapping of World Reference Base (WRB) Reference Soil Groups (RSGs) at a global level has great advantages. Maps can be updated in a short time span with relatively little effort when new data become available. To translate soil names of older versions of FAO/WRB and national classification systems of the source data into names according to WRB 2006, correlation tables are used in SoilGrids. Soil properties and classes are predicted independently from each other. This means that the combinations of soil properties for the same cells or soil property-soil class combinations do not necessarily yield logical combinations when the map layers are studied jointly. The model prediction procedure is robust and probably has a low source of error in the prediction of RSGs. It seems that the quality of the original soil classification in the data and the use of correlation tables are the largest sources of error in mapping the RSG distribution patterns. Predicted patterns of dominant RSGs were evaluated in selected areas and sources of error were identified. Suggestions are made for improvement of WRB2015 RSG distribution predictions in SoilGrids. Keywords: Automated global mapping; World Reference Base for Soil Resources; Data evaluation; Data quality assurance References 1 Hengl T, de Jesus JM, Heuvelink GBM, Ruiperez Gonzalez M, Kilibarda M, et al. (2016) SoilGrids250m: global gridded soil information based on Machine Learning. Earth System Science Data (ESSD), in review. 2 Hengl T, de Jesus JM, MacMillan RA, Batjes NH, Heuvelink GBM, et al. (2014) SoilGrids1km — Global Soil Information Based on Automated Mapping. PLoS ONE 9(8): e105992. doi:10.1371/journal.pone.0105992

Predicting health-related quality of life (EQ-5D-5 L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP.

PubMed

Peak, Jasmine; Goranitis, Ilias; Day, Ed; Copello, Alex; Freemantle, Nick; Frew, Emma

2018-05-30

Economic evaluation normally requires information to be collected on outcome improvement using utility values. This is often not collected during the treatment of substance use disorders making cost-effectiveness evaluations of therapy difficult. One potential solution is the use of mapping to generate utility values from clinical measures. This study develops and evaluates mapping algorithms that could be used to predict the EuroQol-5D (EQ-5D-5 L) and the ICEpop CAPability measure for Adults (ICECAP-A) from the three commonly used clinical measures; the CORE-OM, the LDQ and the TOP measures. Models were estimated using pilot trial data of heroin users in opiate substitution treatment. In the trial the EQ-5D-5 L, ICECAP-A, CORE-OM, LDQ and TOP were administered at baseline, three and twelve month time intervals. Mapping was conducted using estimation and validation datasets. The normal estimation dataset, which comprised of baseline sample data, used ordinary least squares (OLS) and tobit regression methods. Data from the baseline and three month time periods were combined to create a pooled estimation dataset. Cluster and mixed regression methods were used to map from this dataset. Predictive accuracy of the models was assessed using the root mean square error (RMSE) and the mean absolute error (MAE). Algorithms were validated using sample data from the follow-up time periods. Mapping algorithms can be used to predict the ICECAP-A and the EQ-5D-5 L in the context of opiate dependence. Although both measures can be predicted, the ICECAP-A was better predicted by the clinical measures. There were no advantages of pooling the data. There were 6 chosen mapping algorithms, which had MAE scores ranging from 0.100 to 0.138 and RMSE scores ranging from 0.134 to 0.178. It is possible to predict the scores of the ICECAP-A and the EQ-5D-5 L with the use of mapping. In the context of opiate dependence, these algorithms provide the possibility of generating utility values from clinical measures and thus enabling economic evaluation of alternative therapy options. ISRCTN22608399 . Date of registration: 27/04/2012. Date of first randomisation: 14/08/2012.

Predictive landslide susceptibility mapping using spatial information in the Pechabun area of Thailand

NASA Astrophysics Data System (ADS)

Oh, Hyun-Joo; Lee, Saro; Chotikasathien, Wisut; Kim, Chang Hwan; Kwon, Ju Hyoung

2009-04-01

For predictive landslide susceptibility mapping, this study applied and verified probability model, the frequency ratio and statistical model, logistic regression at Pechabun, Thailand, using a geographic information system (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys, and maps of the topography, geology and land cover were constructed to spatial database. The factors that influence landslide occurrence, such as slope gradient, slope aspect and curvature of topography and distance from drainage were calculated from the topographic database. Lithology and distance from fault were extracted and calculated from the geology database. Land cover was classified from Landsat TM satellite image. The frequency ratio and logistic regression coefficient were overlaid for landslide susceptibility mapping as each factor’s ratings. Then the landslide susceptibility map was verified and compared using the existing landslide location. As the verification results, the frequency ratio model showed 76.39% and logistic regression model showed 70.42% in prediction accuracy. The method can be used to reduce hazards associated with landslides and to plan land cover.

National Park Service Vegetation Mapping Inventory Program: Natchez Trace Parkway vegetation mapping project report

USGS Publications Warehouse

Hop, Kevin D.; Strassman, Andrew C.; Nordman, Carl; Pyne, Milo; White, Rickie; Jakusz, Joseph; Hoy, Erin E.; Dieck, Jennifer

2016-01-01

The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Gulf Coast Network, and NPS Natchez Trace Parkway (NATR; also referred to as Parkway) have completed vegetation classification and mapping of NATR for the NPS VMI Program.Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of NATR and to determine how best to map them by using aerial imagery. Analyses of data from 589 vegetation plots had been used to describe an initial 99 USNVC associations in the Parkway; this classification work was completed prior to beginning this NATR vegetation mapping project. Data were collected during this project from another eight quick plots to support new vegetation types not previously identified at the Parkway. Data from 120 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Furthermore, data from 900 accuracy assessment (AA) sites were collected (of which 894 were used to test accuracy of the vegetation map layer). The collective of all these datasets resulted in affirming 122 USNVC associations at NATR.To map the vegetation and open water of NATR, 63 map classes were developed. including the following: 54 map classes represent natural (including ruderal) vegetation types in the USNVC, 5 map classes represent cultural (agricultural and developed) vegetation types in the USNVC, 3 map classes represent nonvegetation open-water bodies (non-USNVC), and 1 map class represents landscapes that had received tornado damage a few months prior to the time of aerial imagery collection. Features were interpreted from viewing 4-band digital aerial imagery by means of digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems. (The aerial imagery was collected during mid-October 2011 for the northern reach of the Parkway and mid-November 2011 for the southern reach of the Parkway to capture peak leaf-phenology of trees.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in geographic information systems. Polygon units were mapped to either a 0.5 hectare (ha) or 0.25 ha minimum mapping unit, depending on vegetation type or scenario.A geodatabase containing various feature-class layers and tables present the locations of USNVC vegetation types (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial image centers. The feature-class layer and related tables for the vegetation map provide 13,529 polygons of detailed attribute data covering 21,655.5 ha, with an average polygon size of 1.6 ha; the vegetation map coincides closely with the administrative boundary for NATR.Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 12,648 polygons (93.5% of polygons) and cover 18,542.7 ha (85.6%) of the map extent for NATR. The map layer indicates the Parkway to be 70.5% forest and woodland (15,258.7 ha), 0.3% shrubland (63.0 ha), and 14.9% herbaceous cover (3,221.0 ha). Map classes representing USNVC cultural types apply to 678 polygons (5.0% of polygons) and cover 2,413.9 ha (11.1%) of the map extent.

High-resolution mapping and modelling of surface albedo in Norwegian boreal forests: from remotely sensed data to predictions

NASA Astrophysics Data System (ADS)

Cherubini, Francesco; Hu, Xiangping; Vezhapparambu, Sajith; Stromman, Anders

2017-04-01

Surface albedo, a key parameter of the Earth's climate system, has high variability in space, time, and land cover and its parameterization is among the most important variables in climate models. The lack of extensive estimates for model improvement is one of the main limitations for accurately quantifying the influence of surface albedo changes on the planetary radiation balance. We use multi-year satellite retrievals of MODIS surface albedo (MCD43A3), high resolution land cover maps, and meteorological records to characterize albedo variations in Norway across latitude, seasons, land cover type, and topography. We then use this dataset to elaborate semi-empirical models to predict albedo values as a function of tree species, age, volume and climate variables like temperature and snow water equivalents (SWE). Given the complexity of the dataset and model formulation, we apply an innovative non-linear programming approach simultaneously coupled with linear un-mixing. The MODIS albedo products are at a resolution of about 500 m and 8 days. The land cover maps provide vegetation structure information on relative abundance of tree species, age, and biomass volumes at 16 m resolution (for both deciduous and coniferous species). Daily observations of meteorological information on air temperature and SWE are produced at 1 km resolution from interpolation of meteorological weather stations in Norway. These datasets have different resolution and projection, and are harmonized by identifying, for each MODIS pixel, the intersecting land cover polygons and the percentage area of the MODIS pixel represented by each land cover type. We then filter the subplots according to the following criteria: i) at least 96% of the total pixel area is covered by a single land cover class (either forest or cropland); ii) if forest area, at least 98% of the forest area is covered by spruce, deciduous or pine. Forested pixels are then categorized as spruce, deciduous, or pine dominant if the fraction of the respective tree species is greater than 75%. Results show averages of albedo estimates for forests and cropland depicting spatial (along a latitudinal gradient) and temporal (daily, monthly, and seasonal) variations across Norway. As the case study region is a country with heterogeneous topography, we also study the sensitivity of the albedo estimates to the slope and aspect of the terrain. The mathematical programming approach uses a variety of functional forms, constraints and variables, leading to many different model outputs. There are several models with relatively high performances, allowing for a flexibility in the model selection, with different model variants suitable for different situations. This approach produces albedo predictions at the same resolution of the land cover dataset (16 m, notably higher than the MODIS estimates), can incorporate changes in climate conditions, and is robust to cross-validation between different locations. By integrating satellite measurements and high-resolution vegetation maps, we can thus produce semi-empirical models that can predict albedo values for boreal forests using a variety of input variables representing climate and/or vegetation structure. Further research can explore the possible advantages of its implementation in land surface schemes over existing approaches.

Mapping the Rural Adolescent Girls' Participation in Residential Non-Formal Education Program--A Study in Lunkaransar Block, Rajasthan, India

ERIC Educational Resources Information Center

Sharma, Shilpa

2002-01-01

The present study, "Mapping Rural Adolescent Girl's Participation in Residential Non- Formal Education Program--A Study in Lunkaransar Block, Rajasthan", was an attempt to understand the dimensions of rural adolescent girls' participation in the "Balika Shivir" Program. It is a six month residential non-formal education program…

Curriculum Mapping: A Before-and-After Look at Faculty Perceptions of Their Courses and the Mapping Process

ERIC Educational Resources Information Center

Joyner, Helen S.

2016-01-01

The increased interest in program- and university-level assessment over the past few decades has led to increased faculty involvement in developing program learning outcomes and performing program assessment activities. Depending on the level of support and encouragement faculty receive from administration and other entities, they may support or…

Geologic mapping of Kentucky; a history and evaluation of the Kentucky Geological Survey--U.S. Geological Survey Mapping Program, 1960-1978

USGS Publications Warehouse

Cressman, Earle Rupert; Noger, Martin C.

1981-01-01

In 1960, the U.S. Geological Survey and the Kentucky Geological Survey began a program to map the State geologically at a scale of 1:24,000 and to publish the maps as 707 U.S. Geological Survey Geologic Quadrangle Maps. Fieldwork was completed by the spring of 1977, and all maps were published by December 1978. Geologic mapping of the State was proposed by the Kentucky Society of Professional Engineers in 1959. Wallace W. Hagan, Director and State Geologist of the Kentucky Geological Survey, and Preston McGrain, Assistant State Geologist, promoted support for the proposal among organizations such as Chambers of Commerce, industrial associations, professional societies, and among members of the State government. It was also arranged for the U.S. Geological Survey to supply mapping personnel and to publish the maps; the cost would be shared equally by the two organizations. Members of the U.S. Geological Survey assigned to the program were organized as the Branch of Kentucky Geology. Branch headquarters, including an editorial staff, was at Lexington, Ky., but actual mapping was conducted from 18 field offices distributed throughout the State. The Publications Division of the U.S. Geological Survey established a cartographic office at Lexington to prepare the maps for publication. About 260 people, including more than 200 professionals, were assigned to the Branch of Kentucky Geology by the U.S. Geological Survey at one time or another. The most geologists assigned any one year was 61. To complete the mapping and ancillary studies, 661 professional man-years were required, compared with an original estimate of 600 man-years. A wide variety of field methods were used, but most geologists relied on the surveying altimeter to obtain elevations. Surface data were supplemented by drill-hole records, and several dozen shallow diamond-drill holes were drilled to aid the mapping. Geologists generally scribed their own maps, with a consequent saving of publication costs. Paleontologists and stratigraphers of the U.S. Geological Survey cooperated closely with the program. Paleontologic studies were concentrated in the Ordovician of central Kentucky, the Pennsylvanian of eastern and western Kentucky, and the Mesozoic and Cenozoic of westernmost Kentucky. In addition to financial support, the Kentucky Geological Survey provided economic data, stratigraphic support, and drillhole records to the field offices. Geologists of the State Survey made subsurface structural interpretations, constructed bedrock topography maps, and mapped several quadrangles. Some of the problems encountered were the inadequacy of much of the existing stratigraphic nomenclature, the uneven quality of some of the mapping, and the effects of relative isolation on the professional development of some of the geologists. The program cost a total of $20,927,500. In terms of 1960 dollars, it cost $16,035,000; this compares with an original estimate of $12,000,000. Although it is difficult to place a monetary value on the geologic mapping, the program has contributed to newly discovered mineral wealth, jobs, and money saved by government and industry. The maps are used widely in the exploration for coal, oil and gas, fluorspar, limestone, and clay. The maps are also used in planning highways and locations of dams, in evaluating foundation and excavation conditions, in preparing environmental impact statements, and in land-use planning.

Land-Use Analysis and Simulated Effects of Land-Use Change and Aggregate Mining on Groundwater Flow in the South Platte River Valley, Brighton to Fort Lupton, Colorado

USGS Publications Warehouse

Arnold, L.R.; Mladinich, C.S.; Langer, W.H.; Daniels, J.S.

2010-01-01

Land use in the South Platte River valley between the cities of Brighton and Fort Lupton, Colo., is undergoing change as urban areas expand, and the extent of aggregate mining in the Brighton-Fort Lupton area is increasing as the demand for aggregate grows in response to urban development. To improve understanding of land-use change and the potential effects of land-use change and aggregate mining on groundwater flow, the U.S. Geological Survey, in cooperation with the cities of Brighton and Fort Lupton, analyzed socioeconomic and land-use trends and constructed a numerical groundwater flow model of the South Platte alluvial aquifer in the Brighton-Fort Lupton area. The numerical groundwater flow model was used to simulate (1) steady-state hydrologic effects of predicted land-use conditions in 2020 and 2040, (2) transient cumulative hydrologic effects of the potential extent of reclaimed aggregate pits in 2020 and 2040, (3) transient hydrologic effects of actively dewatered aggregate pits, and (4) effects of different hypothetical pit spacings and configurations on groundwater levels. The SLEUTH (Slope, Land cover, Exclusion, Urbanization, Transportation, and Hillshade) urban-growth modeling program was used to predict the extent of urban area in 2020 and 2040. Wetlands in the Brighton-Fort Lupton area were mapped as part of the study, and mapped wetland locations and areas of riparian herbaceous vegetation previously mapped by the Colorado Division of Wildlife were compared to simulation results to indicate areas where wetlands or riparian herbaceous vegetation might be affected by groundwater-level changes resulting from land-use change or aggregate mining. Analysis of land-use conditions in 1957, 1977, and 2000 indicated that the general distribution of irrigated land and non-irrigated land remained similar from 1957 to 2000, but both land uses decreased as urban area increased. Urban area increased about 165 percent from 1957 to 1977 and about 56 percent from 1977 to 2000 with most urban growth occurring east of Brighton and Fort Lupton and along major transportation corridors. Land-use conditions in 2020 and 2040 predicted by the SLEUTH modeling program indicated urban growth will continue to develop primarily east of Brighton and Fort Lupton and along major transportation routes, but substantial urban growth also is predicted south and west of Brighton. Steady-state simulations of the hydrologic effects of predicted land-use conditions in 2020 and 2040 indicated groundwater levels declined less than 2 feet relative to simulated groundwater levels in 2000. Groundwater levels declined most where irrigated land was converted to urban area and least where non-irrigated land was converted to urban area. Simulated groundwater-level declines resulting from land-use conditions in 2020 and 2040 are not predicted to substantially affect wetlands or riparian herbaceous vegetation in the study area because the declines are small and wetlands and riparian herbaceous vegetation generally are not located where simulated declines occur. See Report PDF for unabridged abstract.

Milestones: Critical Elements in Clinical Informatics Fellowship Programs

PubMed Central

Lehmann, Christoph U.; Munger, Benson

2016-01-01

Summary Background Milestones refer to points along a continuum of a competency from novice to expert. Resident and fellow assessment and program evaluation processes adopted by the ACGME include the mandate that programs report the educational progress of residents and fellows twice annually utilizing Milestones developed by a specialty specific ACGME working group of experts. Milestones in clinical training programs are largely unmapped to specific assessment tools. Residents and fellows are mainly assessed using locally derived assessment instruments. These assessments are then reviewed by the Clinical Competency Committee which assigns and reports trainee ratings using the specialty specific reporting Milestones. Methods and Results The challenge and opportunity facing the nascent specialty of Clinical Informatics is how to optimally utilize this framework across a growing number of accredited fellowships. The authors review how a mapped milestone framework, in which each required sub-competency is mapped to a single milestone assessment grid, can enable the use of milestones for multiple uses including individualized learning plans, fellow assessments, and program evaluation. Furthermore, such a mapped strategy will foster the ability to compare fellow progress within and between Clinical Informatics Fellowships in a structured and reliable fashion. Clinical Informatics currently has far less variability across programs and thus could easily utilize a more tightly defined set of milestones with a clear mapping to sub-competencies. This approach would enable greater standardization of assessment instruments and processes across programs while allowing for variability in how those sub-competencies are taught. Conclusions A mapped strategy for Milestones offers significant advantages for Clinical Informatics programs. PMID:27081414

Description of a user-oriented geographic information system - The resource analysis program

NASA Technical Reports Server (NTRS)

Tilmann, S. E.; Mokma, D. L.

1980-01-01

This paper describes the Resource Analysis Program, an applied geographic information system. Several applications are presented which utilized soil, and other natural resource data, to develop integrated maps and data analyses. These applications demonstrate the methods of analysis and the philosophy of approach used in the mapping system. The applications are evaluated in reference to four major needs of a functional mapping system: data capture, data libraries, data analysis, and mapping and data display. These four criteria are then used to describe an effort to develop the next generation of applied mapping systems. This approach uses inexpensive microcomputers for field applications and should prove to be a viable entry point for users heretofore unable or unwilling to venture into applied computer mapping.

Cartographic research 1977

USGS Publications Warehouse

,

1978-01-01

Two major subjects of the current research of the Topographic Division as reported here are related to policy decisions affecting the National Mapping Program of the Geological Survey. The adoption of a metric mapping policy has resulted in new cartographic products with associated changes in map design that require new looks in graphics and new equipment. The increasing use of digitized cartographic information has led to developments in data acquisition, processing, and storage and consequent changes in equipment and techniques. This report summarizes the activities in cartographic research and development for the 12-month period ending June 1977 and covers work done at the several facilities of the Topographic Division: the Western Mapping Center at Menlo Park, Calif., the Rocky Mountain Mapping Center at Denver, Colo., the Mid-Continent Mapping Center at Rolla, Mo., and the Eastern Mapping Center, the Special Mapping Center, the Office of Plans and Program Development, and the Office of Research and Technical Standards all at Reston, Va.

Status and future of extraterrestrial mapping programs

NASA Technical Reports Server (NTRS)

Batson, R. M.

1981-01-01

Extensive mapping programs have been completed for the Earth's Moon and for the planet Mercury. Mars, Venus, and the Galilean satellites of Jupiter (Io, Europa, Ganymede, and Callisto), are currently being mapped. The two Voyager spacecraft are expected to return data from which maps can be made of as many as six of the satellites of Saturn and two or more of the satellites of Uranus. The standard reconnaissance mapping scales used for the planets are 1:25,000,000 and 1:5,000,000; where resolution of data warrants, maps are compiled at the larger scales of 1:2,000,000, 1:1,000,000 and 1:250,000. Planimetric maps of a particular planet are compiled first. The first spacecraft to visit a planet is not designed to return data from which elevations can be determined. As exploration becomes more intensive, more sophisticated missions return photogrammetric and other data to permit compilation of contour maps.

An interactive program to display user-generated or file-based maps on a personal computer monitor

USGS Publications Warehouse

Langer, W.H.; Stephens, R.W.

1987-01-01

PC MAP-MAKER is an ADVANCED BASIC program written to provide users of IBM XT, IBM AT, and compatible computers with a straight-forward, flexible method to display geographical data on a color or monochrome PC (personal computer) monitor. Data can be political boundaries such as State and county boundaries; natural curvilinear features such as rivers, drainage areas, and geological contacts; and points such as well locations and mineral localities. Essentially any point defined by a latitude and longitude and any line defined by a series of latitude and longitude values can be displayed using the program. PC MAP MAKER allows users to view tabular data from U.S. Geological Survey files such as WATSTORE (National Water Data Storage and Retrieval System) in a map format in a time much shorter than required by sending the data to a line plotter. The screen image can be saved to disk for recall at a later date, and hard copies can be printed with a dot matrix printer. The program is user-friendly, using menus or prompts to guide user input. It is fully documented and structured to allow the user to tailor the program to the user 's specific needs. The documentation includes a tutorial designed to introduce users to the capabilities of the program using the State of Colorado as a demonstration map area. (Author 's abstract)

International Low-Earth-Orbit Spacecraft Materials Test Program Initiated for Better Prediction of Durability and Performance

NASA Technical Reports Server (NTRS)

Rutledge, Sharon K.

1999-01-01

Spacecraft in low Earth orbit (LEO) are subjected to many components of the environment, which can cause them to degrade much more rapidly than intended and greatly shorten their functional life. The atomic oxygen, ultraviolet radiation, and cross contamination present in LEO can affect sensitive surfaces such as thermal control paints, multilayer insulation, solar array surfaces, and optical surfaces. The LEO Spacecraft Materials Test (LEO-SMT) program is being conducted to assess the effects of simulated LEO exposure on current spacecraft materials to increase understanding of LEO degradation processes as well as to enable the prediction of in-space performance and durability. Using ground-based simulation facilities to test the durability of materials currently flying in LEO will allow researchers to compare the degradation evidenced in the ground-based facilities with that evidenced on orbit. This will allow refinement of ground laboratory test systems and the development of algorithms to predict the durability and performance of new materials in LEO from ground test results. Accurate predictions based on ground tests could reduce development costs and increase reliability. The wide variety of national and international materials being tested represent materials being functionally used on spacecraft in LEO. The more varied the types of materials tested, the greater the probability that researchers will develop and validate predictive models for spacecraft long-term performance and durability. Organizations that are currently participating in the program are ITT Research Institute (USA), Lockheed Martin (USA), MAP (France), SOREQ Nuclear Research Center (Israel), TNO Institute of Applied Physics (The Netherlands), and UBE Industries, Ltd. (Japan). These represent some of the major suppliers of thermal control and sensor materials currently flying in LEO. The participants provide materials that are exposed to selected levels of atomic oxygen, vacuum ultraviolet radiation, contamination, or synergistic combined environments at the NASA Lewis Research Center. Changes in characteristics that could affect mission performance or lifetime are then measured. These characteristics include changes in mass, solar absorptance, and thermal emittance. The durability of spacecraft materials from U.S. suppliers is then compared with those of materials from other participating countries. Lewis will develop and validate performance and durability prediction models using this ground data and available space data. NASA welcomes the opportunity to consider additional international participants in this program, which should greatly aid future spacecraft designers as they select materials for LEO missions.

Precambrian Field Camp at the University of Minnesota Duluth - Teaching Skills Applicable to Mapping Glaciated Terranes of the Canadian Shield

NASA Astrophysics Data System (ADS)

Miller, J. D.; Hudak, G. J.; Peterson, D.

2011-12-01

Since 2007, the central program of the Precambrian Research Center (PRC) at the University of Minnesota Duluth has been a six-week geology field camp focused on the Precambrian geology of the Canadian Shield. This field camp has two main purposes. First and foremost is to teach students specialized field skills and field mapping techniques that can be utilized to map and interpret Precambrian shield terranes characterized by sparse outcrop and abundant glacial cover. In addition to teaching basic outcrop mapping technique , students are introduced to geophysical surveying (gravity, magnetics), glacial drift prospecting, and drill core logging techniques in several of our geological mapping exercises. These mapping methodologies are particularly applicable to minerals exploration in shield terranes. The second and equally important goal of the PRC field camp is to teach students modern map-making and map production skills. During the fifth and sixth weeks of field camp, students conduct "capstone" mapping projects. These projects encompass one week of detailed bedrock mapping in remote regions of northern Minnesota that have not been mapped in detail (e.g. scales greater than 1:24,000) and a second week of map-making and map generation utilizing geographic information systems (currently ArcGIS10), graphics software packages (Adobe Illustrator CS4), and various imaging software for geophysical and topographic data. Over the past five years, PRC students and faculty have collaboratively published 21 geologic maps through the Precambrian Research Center Map Series. These maps are currently being utilized in a variety of ways by industry, academia, and government for mineral exploration programs, development of undergraduate, graduate, and faculty research projects, and for planning, archeological studies, and public education programs in Minnesota's state parks. Acquisition of specialized Precambrian geological mapping skills and geologic map-making proficiencies has enabled our students to be highly sought after for employment and/or subsequent graduate studies.

Cost-benefit analysis of vaccination against Mycobacterium avium ssp. paratuberculosis in dairy cattle, given its cross-reactivity with tuberculosis tests.

PubMed

Groenendaal, Huybert; Zagmutt, Francisco J; Patton, Elisabeth A; Wells, Scott J

2015-09-01

Johne's disease (JD), or paratuberculosis, is a chronic enteric disease of ruminants, caused by infection with Mycobacterium avium ssp. paratuberculosis (MAP). Johne's disease causes considerable economic losses to the US dairy industry, estimated to be over $200 million annually. Available control strategies include management measures to improve calf hygiene, test-and-cull strategies, and vaccination. Although the first 2 strategies have shown to reduce the prevalence of MAP, they require dedicated and long-term efforts from dairy producers, with often relatively slow progress. As a result, uptake of both strategies has not been as wide as expected given the economic benefits especially of improved hygiene. Vaccination has also been found to reduce the prevalence and economic losses of JD, but most economic estimates have been based on simulation of hypothetical vaccines. In addition, if an animal is vaccinated, cross-reactivity between MAP antibodies and bovine tuberculosis (BTB) antigens may occur, decreasing the specificity of BTB tests. Therefore, MAP vaccination would cause additional indirect costs to the BTB surveillance and control program. The objective of the present study was to use data from a MAP vaccine trial together with an epidemiologic and economic model to estimate the direct on-farm benefits of MAP vaccination and to estimate the indirect costs of MAP vaccination due to the cross-reactivity with BTB tests. Direct economic benefits of MAP vaccination were estimated at $8.03 (90% predictive interval: -$25.97 to $41.36) per adult animal per year, all accruing to the dairy producers. This estimate is likely an underestimation of the true direct benefits of MAP vaccination. In addition, indirect economic costs due to cross-reactivity were $2.14 per adult animal per year, making MAP vaccination economically attractive. Only in regions or states with a high frequency of BTB testing (because of, for example, Mycobacterium bovis outbreaks in a wild deer population) and areas where typically small groups of animals are BTB tested would MAP vaccination not be economically attractive. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Designing a workplace return-to-work program for occupational low back pain: an intervention mapping approach

PubMed Central

Ammendolia, Carlo; Cassidy, David; Steensta, Ivan; Soklaridis, Sophie; Boyle, Eleanor; Eng, Stephanie; Howard, Hamer; Bhupinder, Bains; Côté, Pierre

2009-01-01

Background Despite over 2 decades of research, the ability to prevent work-related low back pain (LBP) and disability remains elusive. Recent research suggests that interventions that are focused at the workplace and incorporate the principals of participatory ergonomics and return-to-work (RTW) coordination can improve RTW and reduce disability following a work-related back injury. Workplace interventions or programs to improve RTW are difficult to design and implement given the various individuals and environments involved, each with their own unique circumstances. Intervention mapping provides a framework for designing and implementing complex interventions or programs. The objective of this study is to design a best evidence RTW program for occupational LBP tailored to the Ontario setting using an intervention mapping approach. Methods We used a qualitative synthesis based on the intervention mapping methodology. Best evidence from systematic reviews, practice guidelines and key articles on the prognosis and management of LBP and improving RTW was combined with theoretical models for managing LBP and changing behaviour. This was then systematically operationalized into a RTW program using consensus among experts and stakeholders. The RTW Program was further refined following feedback from nine focus groups with various stakeholders. Results A detailed five step RTW program was developed. The key features of the program include; having trained personnel coordinate the RTW process, identifying and ranking barriers and solutions to RTW from the perspective of all important stakeholders, mediating practical solutions at the workplace and, empowering the injured worker in RTW decision-making. Conclusion Intervention mapping provided a useful framework to develop a comprehensive RTW program tailored to the Ontario setting. PMID:19508728

Application of Machine Learning to Arterial Spin Labeling in Mild Cognitive Impairment and Alzheimer Disease.

PubMed

Collij, Lyduine E; Heeman, Fiona; Kuijer, Joost P A; Ossenkoppele, Rik; Benedictus, Marije R; Möller, Christiane; Verfaillie, Sander C J; Sanz-Arigita, Ernesto J; van Berckel, Bart N M; van der Flier, Wiesje M; Scheltens, Philip; Barkhof, Frederik; Wink, Alle Meije

2016-12-01

Purpose To investigate whether multivariate pattern recognition analysis of arterial spin labeling (ASL) perfusion maps can be used for classification and single-subject prediction of patients with Alzheimer disease (AD) and mild cognitive impairment (MCI) and subjects with subjective cognitive decline (SCD) after using the W score method to remove confounding effects of sex and age. Materials and Methods Pseudocontinuous 3.0-T ASL images were acquired in 100 patients with probable AD; 60 patients with MCI, of whom 12 remained stable, 12 were converted to a diagnosis of AD, and 36 had no follow-up; 100 subjects with SCD; and 26 healthy control subjects. The AD, MCI, and SCD groups were divided into a sex- and age-matched training set (n = 130) and an independent prediction set (n = 130). Standardized perfusion scores adjusted for age and sex (W scores) were computed per voxel for each participant. Training of a support vector machine classifier was performed with diagnostic status and perfusion maps. Discrimination maps were extracted and used for single-subject classification in the prediction set. Prediction performance was assessed with receiver operating characteristic (ROC) analysis to generate an area under the ROC curve (AUC) and sensitivity and specificity distribution. Results Single-subject diagnosis in the prediction set by using the discrimination maps yielded excellent performance for AD versus SCD (AUC, 0.96; P < .01), good performance for AD versus MCI (AUC, 0.89; P < .01), and poor performance for MCI versus SCD (AUC, 0.63; P = .06). Application of the AD versus SCD discrimination map for prediction of MCI subgroups resulted in good performance for patients with MCI diagnosis converted to AD versus subjects with SCD (AUC, 0.84; P < .01) and fair performance for patients with MCI diagnosis converted to AD versus those with stable MCI (AUC, 0.71; P > .05). Conclusion With automated methods, age- and sex-adjusted ASL perfusion maps can be used to classify and predict diagnosis of AD, conversion of MCI to AD, stable MCI, and SCD with good to excellent accuracy and AUC values. © RSNA, 2016.

T2* Mapping Provides Information That Is Statistically Comparable to an Arthroscopic Evaluation of Acetabular Cartilage.

PubMed

Morgan, Patrick; Nissi, Mikko J; Hughes, John; Mortazavi, Shabnam; Ellerman, Jutta

2017-07-01

Objectives The purpose of this study was to validate T2* mapping as an objective, noninvasive method for the prediction of acetabular cartilage damage. Methods This is the second step in the validation of T2*. In a previous study, we established a quantitative predictive model for identifying and grading acetabular cartilage damage. In this study, the model was applied to a second cohort of 27 consecutive hips to validate the model. A clinical 3.0-T imaging protocol with T2* mapping was used. Acetabular regions of interest (ROI) were identified on magnetic resonance and graded using the previously established model. Each ROI was then graded in a blinded fashion by arthroscopy. Accurate surgical location of ROIs was facilitated with a 2-dimensional map projection of the acetabulum. A total of 459 ROIs were studied. Results When T2* mapping and arthroscopic assessment were compared, 82% of ROIs were within 1 Beck group (of a total 6 possible) and 32% of ROIs were classified identically. Disease prediction based on receiver operating characteristic curve analysis demonstrated a sensitivity of 0.713 and a specificity of 0.804. Model stability evaluation required no significant changes to the predictive model produced in the initial study. Conclusions These results validate that T2* mapping provides statistically comparable information regarding acetabular cartilage when compared to arthroscopy. In contrast to arthroscopy, T2* mapping is quantitative, noninvasive, and can be used in follow-up. Unlike research quantitative magnetic resonance protocols, T2* takes little time and does not require a contrast agent. This may facilitate its use in the clinical sphere.

Making Dynamic Digital Maps Cross-Platform and WWW Capable

NASA Astrophysics Data System (ADS)

Condit, C. D.

2001-05-01

High-quality color geologic maps are an invaluable information resource for educators, students and researchers. However, maps with large datasets that include images, or various types of movies, in addition to site locations where analytical data has been collected, are difficult to publish in a format that facilitates their easy access, distribution and use. The development of capable desktop computers and object oriented graphical programming environments has facilitated publication of such data sets in an encapsulated form. The original Dynamic Digital Map (DDM) programs, developed using the Macintosh based SuperCard programming environment, exemplified this approach, in which all data are included in a single package designed so that display and access to the data did not depend on proprietary programs. These DDMs were aimed for ease of use, and allowed data to be displayed by several methods, including point-and-click at icons pin-pointing sample (or image) locations on maps, and from clicklists of sample or site numbers. Each of these DDMs included an overview and automated tour explaining the content organization and program use. This SuperCard development culminated in a "DDM Template", which is a SuperCard shell into which SuperCard users could insert their own content and thus create their own DDMs, following instructions in an accompanying "DDM Cookbook" (URL http://www.geo.umass.edu/faculty/condit/condit2.html). These original SuperCard-based DDMs suffered two critical limitations: a single user platform (Macintosh) and, although they can be downloaded from the web, their use lacked an integration into the WWW. Over the last eight months I have been porting the DDM technology to MetaCard, which is aggressively cross-platform (11 UNIX dialects, WIN32 and Macintosh). The new MetaCard DDM is redesigned to make the maps and images accessible either from CD or the web, using the "LoadNGo" concept. LoadNGo allows the user to download the stand-alone DDM program using a standard browser, and then use the program independently to access images, maps and data with fast web connections. DDMs are intended to be a fast and inexpensive way to publish and make accessible, as an integrated product, high-quality color maps and data sets. They are not a substitute for the analytical capability of GIS; however maps produced using GIS and CAD programs can be easily integrated into DDMs. The preparation of any map product is a time consuming effort. To compliment that effort, the DDM Templates have build into them the capability to contain explanatory text at three different user levels (or perhaps in three different languages), thus one DDM may be used as both a research publication medium and an educational outreach product, with the user choosing which user mode to access the data.

Analogical Processes in Children's Understanding of Spatial Representations

ERIC Educational Resources Information Center

Yuan, Lei; Uttal, David; Gentner, Dedre

2017-01-01

We propose that map reading can be construed as a form of analogical mapping. We tested 2 predictions that follow from this claim: First, young children's patterns of performance in map reading tasks should parallel those found in analogical mapping tasks; and, second, children will benefit from guided alignment instructions that help them see the…

Prediction of enzymatic pathways by integrative pathway mapping

PubMed Central

Wichelecki, Daniel J; San Francisco, Brian; Zhao, Suwen; Rodionov, Dmitry A; Vetting, Matthew W; Al-Obaidi, Nawar F; Lin, Henry; O'Meara, Matthew J; Scott, David A; Morris, John H; Russel, Daniel; Almo, Steven C; Osterman, Andrei L

2018-01-01

The functions of most proteins are yet to be determined. The function of an enzyme is often defined by its interacting partners, including its substrate and product, and its role in larger metabolic networks. Here, we describe a computational method that predicts the functions of orphan enzymes by organizing them into a linear metabolic pathway. Given candidate enzyme and metabolite pathway members, this aim is achieved by finding those pathways that satisfy structural and network restraints implied by varied input information, including that from virtual screening, chemoinformatics, genomic context analysis, and ligand -binding experiments. We demonstrate this integrative pathway mapping method by predicting the L-gulonate catabolic pathway in Haemophilus influenzae Rd KW20. The prediction was subsequently validated experimentally by enzymology, crystallography, and metabolomics. Integrative pathway mapping by satisfaction of structural and network restraints is extensible to molecular networks in general and thus formally bridges the gap between structural biology and systems biology. PMID:29377793

MAP3K8/TPL-2/COT is a potential predictive marker for MEK inhibitor treatment in high-grade serous ovarian carcinomas.

PubMed

Gruosso, Tina; Garnier, Camille; Abelanet, Sophie; Kieffer, Yann; Lemesre, Vincent; Bellanger, Dorine; Bieche, Ivan; Marangoni, Elisabetta; Sastre-Garau, Xavier; Mieulet, Virginie; Mechta-Grigoriou, Fatima

2015-10-12

Ovarian cancer is a silent disease with a poor prognosis that urgently requires new therapeutic strategies. In low-grade ovarian tumours, mutations in the MAP3K BRAF gene constitutively activate the downstream kinase MEK. Here we demonstrate that an additional MAP3K, MAP3K8 (TPL-2/COT), accumulates in high-grade serous ovarian carcinomas (HGSCs) and is a potential prognostic marker for these tumours. By combining analyses on HGSC patient cohorts, ovarian cancer cells and patient-derived xenografts, we demonstrate that MAP3K8 controls cancer cell proliferation and migration by regulating key players in G1/S transition and adhesion dynamics. In addition, we show that the MEK pathway is the main pathway involved in mediating MAP3K8 function, and that MAP3K8 exhibits a reliable predictive value for the effectiveness of MEK inhibitor treatment. Our data highlight key roles for MAP3K8 in HGSC and indicate that MEK inhibitors could be a useful treatment strategy, in combination with conventional chemotherapy, for this disease.

Mapping ecological systems with a random foret model: tradeoffs between errors and bias

Treesearch

Emilie Grossmann; Janet Ohmann; James Kagan; Heather May; Matthew Gregory

2010-01-01

New methods for predictive vegetation mapping allow improved estimations of plant community composition across large regions. Random Forest (RF) models limit over-fitting problems of other methods, and are known for making accurate classification predictions from noisy, nonnormal data, but can be biased when plot samples are unbalanced. We developed two contrasting...

INTEGRATING EARTH OBSERVATION AND FIELD DATA INTO A LYME DISEASE MODEL TO MAP AND PREDICT RISKS TO BIODIVERSITY AND HUMAN HEALTH

EPA Science Inventory

DW-75-92243901
Title: Integrating Earth Observation and Field Data into a Lyme Disease Model to Map and Predict Risks to Biodiversity and Human HealthDurland Fish, Maria Diuk-Wasser, Joe Roman, Yongtao Guan, Brad Lobitz, Rama Nemani, Joe Piesman, Montira J. Pongsiri, F...

Mapping risk of Nipah virus transmission across Asia and across Bangladesh.

PubMed

Peterson, A Townsend

2015-03-01

Nipah virus is a highly pathogenic but poorly known paramyxovirus from South and Southeast Asia. In spite of the risks that it poses to human health, the geography and ecology of its occurrence remain little understood-the virus is basically known from Bangladesh and peninsular Malaysia, and little in between. In this contribution, I use documented occurrences of the virus to develop ecological niche-based maps summarizing its likely broader occurrence-although rangewide maps could not be developed that had significant predictive abilities, reflecting minimal sample sizes available, maps within Bangladesh were quite successful in identifying areas in which the virus is predictably present and likely transmitted. © 2013 APJPH.

Mapping Computation with No Memory

NASA Astrophysics Data System (ADS)

Burckel, Serge; Gioan, Emeric; Thomé, Emmanuel

We investigate the computation of mappings from a set S n to itself with in situ programs, that is using no extra variables than the input, and performing modifications of one component at a time. We consider several types of mappings and obtain effective computation and decomposition methods, together with upper bounds on the program length (number of assignments). Our technique is combinatorial and algebraic (graph coloration, partition ordering, modular arithmetics).

Middle Atmosphere Program. Handbook for MAP, volume 27

NASA Technical Reports Server (NTRS)

Edwards, Belva (Editor)

1989-01-01

The proceedings are presented from the MAP program of July 1988. It is intended to be a quick synopsis of the symposium. General topics include: New International Equatorial Observatory; Dynamics of the Middle Atmosphere in Winter (DYNAMICS); Global Budget of Stratospheric Trace Constituents (GLOBUS); Gravity Waves and Turbulence in the Middle Atmosphere Program (GRATMAP); Middle Atmosphere Electrodynamics (MAE); Winter in Northern Europe (WINE); Atmospheric Tides Middle Atmosphere Program (ATMAP); and many others.

GENENG: A program for calculating design and off-design performance for turbojet and turbofan engines

NASA Technical Reports Server (NTRS)

Koenig, R. W.; Fishbach, L. H.

1972-01-01

A computer program entitled GENENG employs component performance maps to perform analytical, steady state, engine cycle calculations. Through a scaling procedure, each of the component maps can be used to represent a family of maps (different design values of pressure ratios, efficiency, weight flow, etc.) Either convergent or convergent-divergent nozzles may be used. Included is a complete FORTRAN 4 listing of the program. Sample results and input explanations are shown for one-spool and two-spool turbojets and two-spool separate- and mixed-flow turbofans operating at design and off-design conditions.

Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data

USGS Publications Warehouse

Krizanich, Gary; Finn, Michael P.

2009-01-01

Water quality of Table Rock Lake in southwestern Missouri is assessed using Landsat Thematic Mapper satellite data. A pilot study uses multidate satellite image scenes in conjunction with physical measurements of secchi disk transparency collected by the Lakes of Missouri Volunteer Program to construct a regression model used to estimate water clarity. The natural log of secchi disk transparency is the dependent variable in the regression and the independent variables are Thematic Mapper band 1 (blue) reflectance and a ratio of the band 1 and band 3 (red) reflectance. The regression model can be used to reliably predict water clarity anywhere within the lake. A pixel-level lake map of predicted water clarity or computed trophic state can be produced from the model output. Information derived from this model can be used by water-resource managers to assess water quality and evaluate effects of changes in the watershed on water quality.

Sequence harmony: detecting functional specificity from alignments

PubMed Central

Feenstra, K. Anton; Pirovano, Walter; Krab, Klaas; Heringa, Jaap

2007-01-01

Multiple sequence alignments are often used for the identification of key specificity-determining residues within protein families. We present a web server implementation of the Sequence Harmony (SH) method previously introduced. SH accurately detects subfamily specific positions from a multiple alignment by scoring compositional differences between subfamilies, without imposing conservation. The SH web server allows a quick selection of subtype specific sites from a multiple alignment given a subfamily grouping. In addition, it allows the predicted sites to be directly mapped onto a protein structure and displayed. We demonstrate the use of the SH server using the family of plant mitochondrial alternative oxidases (AOX). In addition, we illustrate the usefulness of combining sequence and structural information by showing that the predicted sites are clustered into a few distinct regions in an AOX homology model. The SH web server can be accessed at www.ibi.vu.nl/programs/seqharmwww. PMID:17584793

Mapping the landscape of metabolic goals of a cell

DOE PAGES

Zhao, Qi; Stettner, Arion I.; Reznik, Ed; ...

2016-05-23

Here, genome-scale flux balance models of metabolism provide testable predictions of all metabolic rates in an organism, by assuming that the cell is optimizing a metabolic goal known as the objective function. We introduce an efficient inverse flux balance analysis (invFBA) approach, based on linear programming duality, to characterize the space of possible objective functions compatible with measured fluxes. After testing our algorithm on simulated E. coli data and time-dependent S. oneidensis fluxes inferred from gene expression, we apply our inverse approach to flux measurements in long-term evolved E. coli strains, revealing objective functions that provide insight into metabolic adaptationmore » trajectories.« less

Laser Signature Prediction Using The VALUE Computer Program

NASA Astrophysics Data System (ADS)

Akerman, Alexander; Hoffman, George A.; Patton, Ronald

1989-09-01

A variety of enhancements are being made to the 1976-vintage LASERX computer code. These include: - Surface characterization with BDRF tabular data - Specular reflection from transparent surfaces - Generation of glint direction maps - Generation of relative range imagery - Interface to the LOWTRAN atmospheric transmission code - Interface to the LEOPS laser sensor code - User friendly menu prompting for easy setup Versions of VALUE have been written for both VAX/VMS and PC/DOS computer environments. Outputs have also been revised to be user friendly and include tables, plots, and images for (1) intensity, (2) cross section,(3) reflectance, (4) relative range, (5) region type, and (6) silhouette.

The Pre-Major in Astronomy Program at the University of Washington: Increasing Diversity Through Research Experiences and Mentoring Since 2005

NASA Astrophysics Data System (ADS)

Rosenfield, Philip

2013-01-01

Graduate students in the astronomy department at the University of Washington began the Pre-Major in Astronomy Program (Pre-MAP) after recognizing that underrepresented students in STEM fields are not well retained after their transition from high school. Pre-MAP is a research and mentoring program that begins with a keystone seminar. First year students enroll in the Pre-MAP seminar to learn astronomical research techniques that they apply to research projects conducted in small groups. Students also receive one-on-one mentoring and peer support for the duration of the academic year and beyond. They are incorporated early into the department by attending Astronomy Department events and Pre-MAP field trips. Successful Pre-MAP students have declared astronomy and physics majors, expanded their research projects beyond the fall quarter, presented posters at the UW Undergraduate Research Symposium, and received research fellowships and summer internships. In this talk, we will discuss how we identified the issues that Pre-MAP was designed to address, what we've learned after six years of Pre-MAP, and share statistical results from a long-term quantitative comparison evaluation.

Combining automated peak tracking in SAR by NMR with structure-based backbone assignment from 15N-NOESY

PubMed Central

2012-01-01

Background Chemical shift mapping is an important technique in NMR-based drug screening for identifying the atoms of a target protein that potentially bind to a drug molecule upon the molecule's introduction in increasing concentrations. The goal is to obtain a mapping of peaks with known residue assignment from the reference spectrum of the unbound protein to peaks with unknown assignment in the target spectrum of the bound protein. Although a series of perturbed spectra help to trace a path from reference peaks to target peaks, a one-to-one mapping generally is not possible, especially for large proteins, due to errors, such as noise peaks, missing peaks, missing but then reappearing, overlapped, and new peaks not associated with any peaks in the reference. Due to these difficulties, the mapping is typically done manually or semi-automatically, which is not efficient for high-throughput drug screening. Results We present PeakWalker, a novel peak walking algorithm for fast-exchange systems that models the errors explicitly and performs many-to-one mapping. On the proteins: hBclXL, UbcH5B, and histone H1, it achieves an average accuracy of over 95% with less than 1.5 residues predicted per target peak. Given these mappings as input, we present PeakAssigner, a novel combined structure-based backbone resonance and NOE assignment algorithm that uses just 15N-NOESY, while avoiding TOCSY experiments and 13C-labeling, to resolve the ambiguities for a one-to-one mapping. On the three proteins, it achieves an average accuracy of 94% or better. Conclusions Our mathematical programming approach for modeling chemical shift mapping as a graph problem, while modeling the errors directly, is potentially a time- and cost-effective first step for high-throughput drug screening based on limited NMR data and homologous 3D structures. PMID:22536902

Mathemagenic Activities Program: [Reports from a Conference on New Perspectives in Developmental Assessment (1st, Athens, Georgia, November 15, 1972)].

ERIC Educational Resources Information Center

Smock, Charles D., Ed.; And Others

This set of four research reports is a product of the Mathemagenic Activities Program (MAP) for early childhood education of the University of Georgia Follow Through Program. Based on Piagetian theory, the MAP provides sequentially structured sets of curriculum materials and processes that are designed to continually challenge children in…

A Critical Review of Concept Mapping Research Literature: Informing Teaching and Learning Practices in GED Preparation Programs

ERIC Educational Resources Information Center

Martin, Larry G.; Martin, Fatima A.; Southworth, Erica

2015-01-01

Concept maps (Cmaps) are still underutilized in adult literacy programs and classes. The teaching and learning approaches that have been used historically in adult literacy programs to address the learning needs of these students have not kept pace with the literacy skill demands that have sprung from the increased pace of technological…

Whole-central nervous system functional imaging in larval Drosophila

PubMed Central

Lemon, William C.; Pulver, Stefan R.; Höckendorf, Burkhard; McDole, Katie; Branson, Kristin; Freeman, Jeremy; Keller, Philipp J.

2015-01-01

Understanding how the brain works in tight concert with the rest of the central nervous system (CNS) hinges upon knowledge of coordinated activity patterns across the whole CNS. We present a method for measuring activity in an entire, non-transparent CNS with high spatiotemporal resolution. We combine a light-sheet microscope capable of simultaneous multi-view imaging at volumetric speeds 25-fold faster than the state-of-the-art, a whole-CNS imaging assay for the isolated Drosophila larval CNS and a computational framework for analysing multi-view, whole-CNS calcium imaging data. We image both brain and ventral nerve cord, covering the entire CNS at 2 or 5 Hz with two- or one-photon excitation, respectively. By mapping network activity during fictive behaviours and quantitatively comparing high-resolution whole-CNS activity maps across individuals, we predict functional connections between CNS regions and reveal neurons in the brain that identify type and temporal state of motor programs executed in the ventral nerve cord. PMID:26263051

Evaluation of Ten Methods for Initializing a Land Surface Model

NASA Technical Reports Server (NTRS)

Rodell, M.; Houser, P. R.; Berg, A. A.; Famiglietti, J. S.

2005-01-01

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth"s water cycle and climate variability. NASA"s Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type).

A Neural Circuit Model of Flexible Sensori-motor Mapping: Learning and Forgetting on Multiple Timescales

PubMed Central

Fusi, Stefano; Asaad, Wael F.; Miller, Earl K.; Wang, Xiao-Jing

2007-01-01

Summary Volitional behavior relies on the brain’s ability to remap sensory flow to motor programs whenever demanded by a changed behavioral context. To investigate the circuit basis of such flexible behavior, we have developed a biophysically-based decision-making network model of spiking neurons for arbitrary sensorimotor mapping. The model quantitatively reproduces behavioral and prefrontal single-cell data from an experiment in which monkeys learn visuo-motor associations that are reversed unpredictably from time to time. We show that when synaptic modifications occur on multiple timescales, the model behavior becomes flexible only when needed: slow components of learning usually dominate the decision process. However, if behavioral contexts change frequently enough, fast components of plasticity take over, and the behavior exhibits a quick forget-and-learn pattern. This model prediction is confirmed by monkey data. Therefore, our work reveals a scenario for conditional associative learning that is distinct from instant switching between sets of well established sensorimotor associations. PMID:17442251

Citrus breeding, genetics and genomics in Japan

PubMed Central

Omura, Mitsuo; Shimada, Takehiko

2016-01-01

Citrus is one of the most cultivated fruits in the world, and satsuma mandarin (Citrus unshiu Marc.) is a major cultivated citrus in Japan. Many excellent cultivars derived from satsuma mandarin have been released through the improvement of mandarins using a conventional breeding method. The citrus breeding program is a lengthy process owing to the long juvenility, and it is predicted that marker-assisted selection (MAS) will overcome the obstacle and improve the efficiency of conventional breeding methods. To promote citrus molecular breeding in Japan, a genetic mapping was initiated in 1987, and the experimental tools and resources necessary for citrus functional genomics have been developed in relation to the physiological analysis of satsuma mandarin. In this paper, we review the progress of citrus breeding and genome researches in Japan and report the studies on genetic mapping, expression sequence tag cataloguing, and molecular characterization of breeding characteristics, mainly in terms of the metabolism of bio-functional substances as well as factors relating to, for example, fruit quality, disease resistance, polyembryony, and flowering. PMID:27069387

A neural circuit model of flexible sensorimotor mapping: learning and forgetting on multiple timescales.

PubMed

Fusi, Stefano; Asaad, Wael F; Miller, Earl K; Wang, Xiao-Jing

2007-04-19

Volitional behavior relies on the brain's ability to remap sensory flow to motor programs whenever demanded by a changed behavioral context. To investigate the circuit basis of such flexible behavior, we have developed a biophysically based decision-making network model of spiking neurons for arbitrary sensorimotor mapping. The model quantitatively reproduces behavioral and prefrontal single-cell data from an experiment in which monkeys learn visuomotor associations that are reversed unpredictably from time to time. We show that when synaptic modifications occur on multiple timescales, the model behavior becomes flexible only when needed: slow components of learning usually dominate the decision process. However, if behavioral contexts change frequently enough, fast components of plasticity take over, and the behavior exhibits a quick forget-and-learn pattern. This model prediction is confirmed by monkey data. Therefore, our work reveals a scenario for conditional associative learning that is distinct from instant switching between sets of well-established sensorimotor associations.

Decoding the Regulatory Network for Blood Development from Single-Cell Gene Expression Measurements

PubMed Central

Haghverdi, Laleh; Lilly, Andrew J.; Tanaka, Yosuke; Wilkinson, Adam C.; Buettner, Florian; Macaulay, Iain C.; Jawaid, Wajid; Diamanti, Evangelia; Nishikawa, Shin-Ichi; Piterman, Nir; Kouskoff, Valerie; Theis, Fabian J.; Fisher, Jasmin; Göttgens, Berthold

2015-01-01

Here we report the use of diffusion maps and network synthesis from state transition graphs to better understand developmental pathways from single cell gene expression profiling. We map the progression of mesoderm towards blood in the mouse by single-cell expression analysis of 3,934 cells, capturing cells with blood-forming potential at four sequential developmental stages. By adapting the diffusion plot methodology for dimensionality reduction to single-cell data, we reconstruct the developmental journey to blood at single-cell resolution. Using transitions between individual cellular states as input, we develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model that recapitulates blood development. Model predictions were validated by showing that Sox7 inhibits primitive erythropoiesis, and that Sox and Hox factors control early expression of Erg. We therefore demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that control organogenesis. PMID:25664528

GEMAS: prediction of solid-solution phase partitioning coefficients (Kd) for oxoanions and boric acid in soils using mid-infrared diffuse reflectance spectroscopy.

PubMed

Janik, Leslie J; Forrester, Sean T; Soriano-Disla, José M; Kirby, Jason K; McLaughlin, Michael J; Reimann, Clemens

2015-02-01

The authors' aim was to develop rapid and inexpensive regression models for the prediction of partitioning coefficients (Kd), defined as the ratio of the total or surface-bound metal/metalloid concentration of the solid phase to the total concentration in the solution phase. Values of Kd were measured for boric acid (B[OH]3(0)) and selected added soluble oxoanions: molybdate (MoO4(2-)), antimonate (Sb[OH](6-)), selenate (SeO4(2-)), tellurate (TeO4(2-)) and vanadate (VO4(3-)). Models were developed using approximately 500 spectrally representative soils of the Geochemical Mapping of Agricultural Soils of Europe (GEMAS) program. These calibration soils represented the major properties of the entire 4813 soils of the GEMAS project. Multiple linear regression (MLR) from soil properties, partial least-squares regression (PLSR) using mid-infrared diffuse reflectance Fourier-transformed (DRIFT) spectra, and models using DRIFT spectra plus analytical pH values (DRIFT + pH), were compared with predicted log K(d + 1) values. Apart from selenate (R(2)  = 0.43), the DRIFT + pH calibrations resulted in marginally better models to predict log K(d + 1) values (R(2)  = 0.62-0.79), compared with those from PSLR-DRIFT (R(2)  = 0.61-0.72) and MLR (R(2)  = 0.54-0.79). The DRIFT + pH calibrations were applied to the prediction of log K(d + 1) values in the remaining 4313 soils. An example map of predicted log K(d + 1) values for added soluble MoO4(2-) in soils across Europe is presented. The DRIFT + pH PLSR models provided a rapid and inexpensive tool to assess the risk of mobility and potential availability of boric acid and selected oxoanions in European soils. For these models to be used in the prediction of log K(d + 1) values in soils globally, additional research will be needed to determine if soil variability is accounted on the calibration. © 2014 SETAC.

TSEMA: interactive prediction of protein pairings between interacting families

PubMed Central

Izarzugaza, José M. G.; Juan, David; Pons, Carles; Ranea, Juan A. G.; Valencia, Alfonso; Pazos, Florencio

2006-01-01

An entire family of methodologies for predicting protein interactions is based on the observed fact that families of interacting proteins tend to have similar phylogenetic trees due to co-evolution. One application of this concept is the prediction of the mapping between the members of two interacting protein families (which protein within one family interacts with which protein within the other). The idea is that the real mapping would be the one maximizing the similarity between the trees. Since the exhaustive exploration of all possible mappings is not feasible for large families, current approaches use heuristic techniques which do not ensure the best solution to be found. This is why it is important to check the results proposed by heuristic techniques and to manually explore other solutions. Here we present TSEMA, the server for efficient mapping assessment. This system calculates an initial mapping between two families of proteins based on a Monte Carlo approach and allows the user to interactively modify it based on performance figures and/or specific biological knowledge. All the explored mappings are graphically shown over a representation of the phylogenetic trees. The system is freely available at . Standalone versions of the software behind the interface are available upon request from the authors. PMID:16845017

Production of high-resolution forest-ecosite maps based on model predictions of soil moisture and nutrient regimes over a large forested area.

PubMed

Yang, Qi; Meng, Fan-Rui; Bourque, Charles P-A; Zhao, Zhengyong

2017-09-08

Forest ecosite reflects the local site conditions that are meaningful to forest productivity as well as basic ecological functions. Field assessments of vegetation and soil types are often used to identify forest ecosites. However, the production of high-resolution ecosite maps for large areas from interpolating field data is difficult because of high spatial variation and associated costs and time requirements. Indices of soil moisture and nutrient regimes (i.e., SMR and SNR) introduced in this study reflect the combined effects of biogeochemical and topographic factors on forest growth. The objective of this research is to present a method for creating high-resolution forest ecosite maps based on computer-generated predictions of SMR and SNR for an area in Atlantic Canada covering about 4.3 × 10 6 hectares (ha) of forestland. Field data from 1,507 forest ecosystem classification plots were used to assess the accuracy of the ecosite maps produced. Using model predictions of SMR and SNR alone, ecosite maps were 61 and 59% correct in identifying 10 Acadian- and Maritime-Boreal-region ecosite types, respectively. This method provides an operational framework for the production of high-resolution maps of forest ecosites over large areas without the need for data from expensive, supplementary field surveys.

Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data.

PubMed

Dalponte, Michele; Coomes, David A

2016-10-01

Forests are a major component of the global carbon cycle, and accurate estimation of forest carbon stocks and fluxes is important in the context of anthropogenic global change. Airborne laser scanning (ALS) data sets are increasingly recognized as outstanding data sources for high-fidelity mapping of carbon stocks at regional scales.We develop a tree-centric approach to carbon mapping, based on identifying individual tree crowns (ITCs) and species from airborne remote sensing data, from which individual tree carbon stocks are calculated. We identify ITCs from the laser scanning point cloud using a region-growing algorithm and identifying species from airborne hyperspectral data by machine learning. For each detected tree, we predict stem diameter from its height and crown-width estimate. From that point on, we use well-established approaches developed for field-based inventories: above-ground biomasses of trees are estimated using published allometries and summed within plots to estimate carbon density.We show this approach is highly reliable: tests in the Italian Alps demonstrated a close relationship between field- and ALS-based estimates of carbon stocks ( r 2  = 0·98). Small trees are invisible from the air, and a correction factor is required to accommodate this effect.An advantage of the tree-centric approach over existing area-based methods is that it can produce maps at any scale and is fundamentally based on field-based inventory methods, making it intuitive and transparent. Airborne laser scanning, hyperspectral sensing and computational power are all advancing rapidly, making it increasingly feasible to use ITC approaches for effective mapping of forest carbon density also inside wider carbon mapping programs like REDD++.

Documenting Uncertainty and Error in Gridded Growing Degree Day and Spring Onset Maps Generated by the USA National Phenology Network

NASA Astrophysics Data System (ADS)

Crimmins, T. M.; Switzer, J.; Rosemartin, A.; Marsh, L.; Gerst, K.; Crimmins, M.; Weltzin, J. F.

2016-12-01

Since 2016 the USA National Phenology Network (USA-NPN; www.usanpn.org) has produced and delivered daily maps and short-term forecasts of accumulated growing degree days and spring onset dates at fine spatial scale for the conterminous United States. Because accumulated temperature is a strong driver of phenological transitions in plants and animals, including leaf-out, flowering, fruit ripening, and migration, these data products have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, determining planting dates, anticipating allergy outbreaks and planning agricultural harvest dates. The USA-NPN is a national-scale program that supports scientific advancement and decision-making by collecting, storing, and sharing phenology data and information. We will be expanding the suite of gridded map products offered by the USA-NPN to include predictive species-specific maps of phenological transitions in plants and animals at fine spatial and temporal resolution in the future. Data products, such as the gridded maps currently produced by the USA-NPN, inherently contain uncertainty and error arising from multiple sources, including error propagated forward from underlying climate data and from the models implemented. As providing high-quality, vetted data in a transparent way is central to the USA-NPN, we aim to identify and report the sources and magnitude of uncertainty and error in gridded maps and forecast products. At present, we compare our real-time gridded products to independent, trustworthy data sources, such as the Climate Reference Network, on a daily basis and report Mean Absolute Error and bias through an interactive online dashboard.

Satellite SAR applied in offhore wind resource mapping: possibilities and limitations

NASA Astrophysics Data System (ADS)

Hasager, C. B.

Satellite remote sensing of ocean wind fields from Synthetic Aperture Radar (SAR) observations is presented. The study is based on a series of more than 60 ERS-2 SAR satellite scenes from the Horns Rev in the North Sea. The wind climate from the coastline and 80 km offshore is mapped in detail with a resolution of 400 m by 400 m grid cells. Spatial variations in wind speed as a function of wind direction and fetch are observed and discussed. The satellite wind fields are compared to in-situ observations from a tall offshore meteorological mast at which wind speed at 4 levels are analysed. The mast is located 14 km offshore and the wind climate is observed continously since May 1999. For offshore wind resource mapping the SAR-based wind field maps can constitute an alternative to in-situ observations and a practical method is developed for applied use in WAsP (Wind Atlas Analysis and Application Program). The software is the de facto world standard tool used for prediction of wind climate and power production from wind turbines and wind farms. The possibilities and limitations on achieving offshore wind resource estimates using SAR-based wind fields in lieu of in-situ data are discussed. It includes a presentation of the footprint area-averaging techniques tailored for SAR-based wind field maps. Averaging techniques are relevant for the reduction of noise apparent in SAR wind speed maps. Acknowledgments: Danish Research Agency (SAT-WIND Sagsnr. 2058-03-0006) for funding, ESA (EO-1356, AO-153) for ERS-2 SAR scenes, and Elsam Engineering A/S for in-situ met-data.

The freetext matching algorithm: a computer program to extract diagnoses and causes of death from unstructured text in electronic health records

PubMed Central

2012-01-01

Background Electronic health records are invaluable for medical research, but much information is stored as free text rather than in a coded form. For example, in the UK General Practice Research Database (GPRD), causes of death and test results are sometimes recorded only in free text. Free text can be difficult to use for research if it requires time-consuming manual review. Our aim was to develop an automated method for extracting coded information from free text in electronic patient records. Methods We reviewed the electronic patient records in GPRD of a random sample of 3310 patients who died in 2001, to identify the cause of death. We developed a computer program called the Freetext Matching Algorithm (FMA) to map diagnoses in text to the Read Clinical Terminology. The program uses lookup tables of synonyms and phrase patterns to identify diagnoses, dates and selected test results. We tested it on two random samples of free text from GPRD (1000 texts associated with death in 2001, and 1000 general texts from cases and controls in a coronary artery disease study), comparing the output to the U.S. National Library of Medicine’s MetaMap program and the gold standard of manual review. Results Among 3310 patients registered in the GPRD who died in 2001, the cause of death was recorded in coded form in 38.1% of patients, and in the free text alone in 19.4%. On the 1000 texts associated with death, FMA coded 683 of the 735 positive diagnoses, with precision (positive predictive value) 98.4% (95% confidence interval (CI) 97.2, 99.2) and recall (sensitivity) 92.9% (95% CI 90.8, 94.7). On the general sample, FMA detected 346 of the 447 positive diagnoses, with precision 91.5% (95% CI 88.3, 94.1) and recall 77.4% (95% CI 73.2, 81.2), which was similar to MetaMap. Conclusions We have developed an algorithm to extract coded information from free text in GP records with good precision. It may facilitate research using free text in electronic patient records, particularly for extracting the cause of death. PMID:22870911

A Web-Based Interactive Mapping System of State Wide School Performance: Integrating Google Maps API Technology into Educational Achievement Data

ERIC Educational Resources Information Center

Wang, Kening; Mulvenon, Sean W.; Stegman, Charles; Anderson, Travis

2008-01-01

Google Maps API (Application Programming Interface), released in late June 2005 by Google, is an amazing technology that allows users to embed Google Maps in their own Web pages with JavaScript. Google Maps API has accelerated the development of new Google Maps based applications. This article reports a Web-based interactive mapping system…

An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms.

PubMed

Hua, Hong-Li; Zhang, Fa-Zhan; Labena, Abraham Alemayehu; Dong, Chuan; Jin, Yan-Ting; Guo, Feng-Biao

Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes. The predictions yielded the highest area under receiver operating characteristic (ROC) curve (AUC) of 0.9716 through tenfold cross-validation test. Proper features were utilized to construct models to make predictions in distantly related bacteria. The accuracy of predictions was evaluated via the consistency of predictions and known essential genes of target species. The highest AUC of 0.9552 and average AUC of 0.8314 were achieved when making predictions across organisms. An independent dataset from Synechococcus elongatus , which was released recently, was obtained for further assessment of the performance of our model. The AUC score of predictions is 0.7855, which is higher than other methods. This research presents that features obtained by homology mapping uniquely can achieve quite great or even better results than those integrated features. Meanwhile, the work indicates that machine learning-based method can assign more efficient weight coefficients than using empirical formula based on biological knowledge.

[Development of an analyzing system for soil parameters based on NIR spectroscopy].

PubMed

Zheng, Li-Hua; Li, Min-Zan; Sun, Hong

2009-10-01

A rapid estimation system for soil parameters based on spectral analysis was developed by using object-oriented (OO) technology. A class of SOIL was designed. The instance of the SOIL class is the object of the soil samples with the particular type, specific physical properties and spectral characteristics. Through extracting the effective information from the modeling spectral data of soil object, a map model was established between the soil parameters and its spectral data, while it was possible to save the mapping model parameters in the database of the model. When forecasting the content of any soil parameter, the corresponding prediction model of this parameter can be selected with the same soil type and the similar soil physical properties of objects. And after the object of target soil samples was carried into the prediction model and processed by the system, the accurate forecasting content of the target soil samples could be obtained. The system includes modules such as file operations, spectra pretreatment, sample analysis, calibrating and validating, and samples content forecasting. The system was designed to run out of equipment. The parameters and spectral data files (*.xls) of the known soil samples can be input into the system. Due to various data pretreatment being selected according to the concrete conditions, the results of predicting content will appear in the terminal and the forecasting model can be stored in the model database. The system reads the predicting models and their parameters are saved in the model database from the module interface, and then the data of the tested samples are transferred into the selected model. Finally the content of soil parameters can be predicted by the developed system. The system was programmed with Visual C++6.0 and Matlab 7.0. And the Access XP was used to create and manage the model database.

Updates to the zoonotic niche map of Ebola virus disease in Africa

PubMed Central

Pigott, David M; Millear, Anoushka I; Earl, Lucas; Morozoff, Chloe; Han, Barbara A; Shearer, Freya M; Weiss, Daniel J; Brady, Oliver J; Kraemer, Moritz UG; Moyes, Catherine L; Bhatt, Samir; Gething, Peter W; Golding, Nick; Hay, Simon I

2016-01-01

As the outbreak of Ebola virus disease (EVD) in West Africa is now contained, attention is turning from control to future outbreak prediction and prevention. Building on a previously published zoonotic niche map (Pigott et al., 2014), this study incorporates new human and animal occurrence data and expands upon the way in which potential bat EVD reservoir species are incorporated. This update demonstrates the potential for incorporating and updating data used to generate the predicted suitability map. A new data portal for sharing such maps is discussed. This output represents the most up-to-date estimate of the extent of EVD zoonotic risk in Africa. These maps can assist in strengthening surveillance and response capacity to contain viral haemorrhagic fevers. DOI: http://dx.doi.org/10.7554/eLife.16412.001 PMID:27414263

InMAP: a new model for air pollution interventions

NASA Astrophysics Data System (ADS)

Tessum, C. W.; Hill, J. D.; Marshall, J. D.

2015-10-01

Mechanistic air pollution models are essential tools in air quality management. Widespread use of such models is hindered, however, by the extensive expertise or computational resources needed to run most models. Here, we present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations - the air pollution outcome generally causing the largest monetized health damages - attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical information from the output of a state-of-the-science chemical transport model (WRF-Chem) within an Eulerian modeling framework, to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. InMAP uses a variable resolution grid that focuses on human exposures by employing higher spatial resolution in urban areas and lower spatial resolution in rural and remote locations and in the upper atmosphere; and by directly calculating steady-state, annual average concentrations. In comparisons run here, InMAP recreates WRF-Chem predictions of changes in total PM2.5 concentrations with population-weighted mean fractional error (MFE) and bias (MFB) < 10 % and population-weighted R2 ~ 0.99. Among individual PM2.5 species, the best predictive performance is for primary PM2.5 (MFE: 16 %; MFB: 13 %) and the worst predictive performance is for particulate nitrate (MFE: 119 %; MFB: 106 %). Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. Features planned for future model releases include a larger spatial domain, more temporal information, and the ability to predict ground-level ozone (O3) concentrations. The InMAP model source code and input data are freely available online.

Improvements on mapping soil liquefaction at a regional scale

NASA Astrophysics Data System (ADS)

Zhu, Jing

Earthquake induced soil liquefaction is an important secondary hazard during earthquakes and can lead to significant damage to infrastructure. Mapping liquefaction hazard is important in both planning for earthquake events and guiding relief efforts by positioning resources once the events have occurred. This dissertation addresses two aspects of liquefaction hazard mapping at a regional scale including 1) predictive liquefaction hazard mapping and 2) post-liquefaction cataloging. First, current predictive hazard liquefaction mapping relies on detailed geologic maps and geotechnical data, which are not always available in at-risk regions. This dissertation improves the predictive liquefaction hazard mapping by the development and validation of geospatial liquefaction models (Chapter 2 and 3) that predict liquefaction extent and are appropriate for global application. The geospatial liquefaction models are developed using logistic regression from a liquefaction database consisting of the data from 27 earthquake events from six countries. The model that performs best over the entire dataset includes peak ground velocity (PGV), VS30, distance to river, distance to coast, and precipitation. The model that performs best over the noncoastal dataset includes PGV, VS30, water table depth, distance to water body, and precipitation. Second, post-earthquake liquefaction cataloging historically relies on field investigation that is often limited by time and expense, and therefore results in limited and incomplete liquefaction inventories. This dissertation improves the post-earthquake cataloging by the development and validation of a remote sensing-based method that can be quickly applied over a broad region after an earthquake and provide a detailed map of liquefaction surface effects (Chapter 4). Our method uses the optical satellite images before and after an earthquake event from the WorldView-2 satellite with 2 m spatial resolution and eight spectral bands. Our method uses the changes of spectral variables that are sensitive to surface moisture and soil characteristics paired with a supervised classification.

Many-to-one form-to-function mapping weakens parallel morphological evolution.

PubMed

Thompson, Cole J; Ahmed, Newaz I; Veen, Thor; Peichel, Catherine L; Hendry, Andrew P; Bolnick, Daniel I; Stuart, Yoel E

2017-11-01

Evolutionary ecologists aim to explain and predict evolutionary change under different selective regimes. Theory suggests that such evolutionary prediction should be more difficult for biomechanical systems in which different trait combinations generate the same functional output: "many-to-one mapping." Many-to-one mapping of phenotype to function enables multiple morphological solutions to meet the same adaptive challenges. Therefore, many-to-one mapping should undermine parallel morphological evolution, and hence evolutionary predictability, even when selection pressures are shared among populations. Studying 16 replicate pairs of lake- and stream-adapted threespine stickleback (Gasterosteus aculeatus), we quantified three parts of the teleost feeding apparatus and used biomechanical models to calculate their expected functional outputs. The three feeding structures differed in their form-to-function relationship from one-to-one (lower jaw lever ratio) to increasingly many-to-one (buccal suction index, opercular 4-bar linkage). We tested for (1) weaker linear correlations between phenotype and calculated function, and (2) less parallel evolution across lake-stream pairs, in the many-to-one systems relative to the one-to-one system. We confirm both predictions, thus supporting the theoretical expectation that increasing many-to-one mapping undermines parallel evolution. Therefore, sole consideration of morphological variation within and among populations might not serve as a proxy for functional variation when multiple adaptive trait combinations exist. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

A Matlab Program for Textural Classification Using Neural Networks

NASA Astrophysics Data System (ADS)

Leite, E. P.; de Souza, C.

2008-12-01

A new MATLAB code that provides tools to perform classification of textural images for applications in the Geosciences is presented. The program, here coined TEXTNN, comprises the computation of variogram maps in the frequency domain for specific lag distances in the neighborhood of a pixel. The result is then converted back to spatial domain, where directional or ominidirectional semivariograms are extracted. Feature vectors are built with textural information composed of the semivariance values at these lag distances and, moreover, with histogram measures of mean, standard deviation and weighted fill-ratio. This procedure is applied to a selected group of pixels or to all pixels in an image using a moving window. A feed- forward back-propagation Neural Network can then be designed and trained on feature vectors of predefined classes (training set). The training phase minimizes the mean-squared error on the training set. Additionally, at each iteration, the mean-squared error for every validation is assessed and a test set is evaluated. The program also calculates contingency matrices, global accuracy and kappa coefficient for the three data sets, allowing a quantitative appraisal of the predictive power of the Neural Network models. The interpreter is able to select the best model obtained from a k-fold cross-validation or to use a unique split-sample data set for classification of all pixels in a given textural image. The code is opened to the geoscientific community and is very flexible, allowing the experienced user to modify it as necessary. The performance of the algorithms and the end-user program were tested using synthetic images, orbital SAR (RADARSAT) imagery for oil seepage detection, and airborne, multi-polarimetric SAR imagery for geologic mapping. The overall results proved very promising.

Integration of Ausubelian Learning Theory and Educational Computing.

ERIC Educational Resources Information Center

Heinze-Fry, Jane A.; And Others

1984-01-01

Examines possible benefits when Ausubelian learning approaches are integrated into computer-assisted instruction, presenting an example of this integration in a computer program dealing with introductory ecology concepts. The four program parts (tutorial, interactive concept mapping, simulations, and vee-mapping) are described. (JN)

Landscape prediction and mapping of game fish biomass, an ecosystem service of Michigan rivers

USGS Publications Warehouse

Esselman, Peter C.; Stevenson, R Jan; Lupi, Frank; Riseng, Catherine M.; Wiley, Michael J.

2015-01-01

The increased integration of ecosystem service concepts into natural resource management places renewed emphasis on prediction and mapping of fish biomass as a major provisioning service of rivers. The goals of this study were to predict and map patterns of fish biomass as a proxy for the availability of catchable fish for anglers in rivers and to identify the strongest landscape constraints on fish productivity. We examined hypotheses about fish responses to total phosphorus (TP), as TP is a growth-limiting nutrient known to cause increases (subsidy response) and/or decreases (stress response) in fish biomass depending on its concentration and the species being considered. Boosted regression trees were used to define nonlinear functions that predicted the standing crops of Brook Trout Salvelinus fontinalis, Brown Trout Salmo trutta, Smallmouth Bass Micropterus dolomieu, panfishes (seven centrarchid species), and Walleye Sander vitreus by using landscape and modeled local-scale predictors. Fitted models were highly significant and explained 22–56% of the variation in validation data sets. Nonlinear and threshold responses were apparent for numerous predictors, including TP concentration, which had significant effects on all except the Walleye fishery. Brook Trout and Smallmouth Bass exhibited both subsidy and stress responses, panfish biomass exhibited a subsidy response only, and Brown Trout exhibited a stress response. Maps of reach-specific standing crop predictions showed patterns of predicted fish biomass that corresponded to spatial patterns in catchment area, water temperature, land cover, and nutrient availability. Maps illustrated predictions of higher trout biomass in coldwater streams draining glacial till in northern Michigan, higher Smallmouth Bass and panfish biomasses in warmwater systems of southern Michigan, and high Walleye biomass in large main-stem rivers throughout the state. Our results allow fisheries managers to examine the biomass potential of streams, describe geographic patterns of fisheries, explore possible nutrient management targets, and identify habitats that are candidates for species management.

Habitat selection of Rocky Mountain elk in a nonforested environment

USGS Publications Warehouse

Sawyer, H.; Nielson, R.M.; Lindzey, F.G.; Keith, L.; Powell, J.H.; Abraham, A.A.

2007-01-01

Recent expansions by Rocky Mountain elk (Cervus elaphus) into nonforested habitats across the Intermountain West have required managers to reconsider the traditional paradigms of forage and cover as they relate to managing elk and their habitats. We examined seasonal habitat selection patterns of a hunted elk population in a nonforested high-desert region of southwestern Wyoming, USA. We used 35,246 global positioning system locations collected from 33 adult female elk to model probability of use as a function of 6 habitat variables: slope, aspect, elevation, habitat diversity, distance to shrub cover, and distance to road. We developed resource selection probability functions for individual elk, and then we averaged the coefficients to estimate population-level models for summer and winter periods. We used the population-level models to generate predictive maps by assigning pixels across the study area to 1 of 4 use categories (i.e., high, medium-high, medium-low, or low), based on quartiles of the predictions. Model coefficients and predictive maps indicated that elk selected for summer habitats characterized by higher elevations in areas of high vegetative diversity, close to shrub cover, northerly aspects, moderate slopes, and away from roads. Winter habitat selection patterns were similar, except elk shifted to areas with lower elevations and southerly aspects. We validated predictive maps by using 528 locations collected from an independent sample of radiomarked elk (n = 55) and calculating the proportion of locations that occurred in each of the 4 use categories. Together, the high- and medium-high use categories of the summer and winter predictive maps contained 92% and 74% of summer and winter elk locations, respectively. Our population-level models and associated predictive maps were successful in predicting winter and summer habitat use by elk in a nonforested environment. In the absence of forest cover, elk seemed to rely on a combination of shrubs, topography, and low human disturbance to meet their thermal and hiding cover requirements.

Complete Bouguer gravity anomaly map of the state of Colorado

USGS Publications Warehouse

Abrams, Gerda A.

1993-01-01

The Bouguer gravity anomaly map is part of a folio of maps of Colorado cosponsored by the National Mineral Resources Assessment Program (NAMRAP) and the National Geologic Mapping Program (COGEOMAP) and was produced to assist in studies of the mineral resource potential and tectonic setting of the State. Previous compilations of about 12,000 gravity stations by Behrendt and Bajwa (1974a,b) are updated by this map. The data was reduced at a 2.67 g/cm3 and the grid contoured at 3 mGal intervals. This map will aid in the mineral resource assessment by indicating buried intrusive complexes, volcanic fields, major faults and shear zones, and sedimentary basins; helping to identify concealed geologic units; and identifying localities that might be hydrothermically altered or mineralized.

LPmerge: an R package for merging genetic maps by linear programming.

PubMed

Endelman, Jeffrey B; Plomion, Christophe

2014-06-01

Consensus genetic maps constructed from multiple populations are an important resource for both basic and applied research, including genome-wide association analysis, genome sequence assembly and studies of evolution. The LPmerge software uses linear programming to efficiently minimize the mean absolute error between the consensus map and the linkage maps from each population. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts. LPmerge is on CRAN at http://cran.r-project.org/web/packages/LPmerge. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Scoping of Flood Hazard Mapping Needs for Penobscot County, Maine

USGS Publications Warehouse

Schalk, Charles W.; Dudley, Robert W.

2007-01-01

Background The Federal Emergency Management Agency (FEMA) developed a plan in 1997 to modernize the FEMA flood mapping program. FEMA flood maps delineate flood hazard areas in support of the National Flood Insurance Program (NFIP). FEMA's plan outlined the steps necessary to update FEMA's flood maps for the nation to a seamless digital format and streamline FEMA's operations in raising public awareness of the importance of the maps and responding to requests to revise them. The modernization of flood maps involves conversion of existing information to digital format and integration of improved flood hazard data as needed. To determine flood mapping modernization needs, FEMA has established specific scoping activities to be done on a county-by-county basis for identifying and prioritizing requisite flood-mapping activities for map modernization. The U.S. Geological Survey (USGS), in cooperation with FEMA and the Maine State Planning Office Floodplain Management Program (MFMP), began scoping work in 2006 for Penobscot County. Scoping activities included assembling existing data and map needs information for communities in Penobscot County, documentation of data, contacts, community meetings, and prioritized mapping needs in a final scoping report (this document), and updating the Mapping Needs Update Support System (MNUSS) Database with information gathered during the scoping process. As of 2007, the average age of the FEMA floodplain maps in Penobscot County, Maine, is 22 years, based on the most recent revisions to the maps. Because the revisions did not affect all the map panels in each town, however, the true average date probably is more than 22 years. Many of the studies were published in the mid-1980s. Since the studies were completed, development has occurred in many of the watersheds, and the characteristics of the watersheds have changed with time. Therefore, many of the older studies may not depict current conditions nor accurately estimate risk in terms of flood heights or flood mapping.

Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

NASA Astrophysics Data System (ADS)

Stephenson, D. B.

1997-10-01

The skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the variance of the correlation distribution can vary from unity up to the number of grid points depending on the choice of weighting metric. The (pseudo-) inverse of the sample covariance matrix acts as a special choice for the metric in that it gives a correlation distribution which has minimal kurtosis and maximum dimension. Minimal kurtosis suggests that the average predictive skill might be improved due to the rarer occurrence of troublesome outlier patterns far from the mean state. Maximum dimension has a disadvantage for analogue prediction schemes in that it gives the minimum number of analogue states. This metric also has an advantage in that it allows one to powerfully test the null hypothesis of multinormality by examining the second and third moments of the correlation coefficient which were introduced by Mardia as invariant measures of multivariate kurtosis and skewness. For these reasons, it is suggested that this metric could be usefully employed in the prediction of weather/climate and in fingerprinting anthropogenic climate change. The ideas are illustrated using the bivariate example of the observed monthly mean sea-level pressures at Darwin and Tahitifrom 1866 1995.

Impact of cell size on inventory and mapping errors in a cellular geographic information system

NASA Technical Reports Server (NTRS)

Wehde, M. E. (Principal Investigator)

1979-01-01

The author has identified the following significant results. The effect of grid position was found insignificant for maps but highly significant for isolated mapping units. A modelable relationship between mapping error and cell size was observed for the map segment analyzed. Map data structure was also analyzed with an interboundary distance distribution approach. Map data structure and the impact of cell size on that structure were observed. The existence of a model allowing prediction of mapping error based on map structure was hypothesized and two generations of models were tested under simplifying assumptions.

The genetic architecture of maize height.

PubMed

Peiffer, Jason A; Romay, Maria C; Gore, Michael A; Flint-Garcia, Sherry A; Zhang, Zhiwu; Millard, Mark J; Gardner, Candice A C; McMullen, Michael D; Holland, James B; Bradbury, Peter J; Buckler, Edward S

2014-04-01

Height is one of the most heritable and easily measured traits in maize (Zea mays L.). Given a pedigree or estimates of the genomic identity-by-state among related plants, height is also accurately predictable. But, mapping alleles explaining natural variation in maize height remains a formidable challenge. To address this challenge, we measured the plant height, ear height, flowering time, and node counts of plants grown in >64,500 plots across 13 environments. These plots contained >7300 inbreds representing most publically available maize inbreds in the United States and families of the maize Nested Association Mapping (NAM) panel. Joint-linkage mapping of quantitative trait loci (QTL), fine mapping in near isogenic lines (NILs), genome-wide association studies (GWAS), and genomic best linear unbiased prediction (GBLUP) were performed. The heritability of maize height was estimated to be >90%. Mapping NAM family-nested QTL revealed the largest explained 2.1 ± 0.9% of height variation. The effects of two tropical alleles at this QTL were independently validated by fine mapping in NIL families. Several significant associations found by GWAS colocalized with established height loci, including brassinosteroid-deficient dwarf1, dwarf plant1, and semi-dwarf2. GBLUP explained >80% of height variation in the panels and outperformed bootstrap aggregation of family-nested QTL models in evaluations of prediction accuracy. These results revealed maize height was under strong genetic control and had a highly polygenic genetic architecture. They also showed that multiple models of genetic architecture differing in polygenicity and effect sizes can plausibly explain a population's variation in maize height, but they may vary in predictive efficacy.

Family history of diabetes modifies the effect of blood pressure for incident diabetes in Middle Eastern women: Tehran Lipid and Glucose Study.

PubMed

Hatami, M; Hadaegh, F; Khalili, D; Sheikholeslami, F; Azizi, F

2012-02-01

Elevated blood pressure (BP) may lead to incident diabetes. However, data about the effect of different BP components on incident diabetes in Middle Eastern women is lacking. We evaluated systolic BP (SBP), diastolic BP (DBP), pulse pressure (PP) and mean arterial pressure (MAP) as independent predictors of diabetes in Iranian women. We performed a population-based prospective study among 3028 non-diabetic women, aged ≥20 years. Odds ratios (ORs) of diabetes were calculated for every 1 s.d. increase in SBP, DBP, PP and MAP. During ≈6 years of follow-up, 220 women developed diabetes. There were significant interactions between family history of diabetes and SBP, PP and MAP (P≤0.01) in predicting incident diabetes. In women without a family history of diabetes, all BP components were significantly associated with diabetes in the age-adjusted model; the risk factor-adjusted ORs were significant (P<0.05) for SBP, PP and MAP (1.30, 1.34 and 1.27, respectively) with similar predictive ability (area under the receiver operating characteristic curve ≈83%). In women with family history of diabetes, in the age-adjusted model, SBP, DBP and MAP were associated with diabetes; in multivariable model, they were not independent predictors of diabetes. In conclusion, in women without family history of diabetes, SBP, PP and MAP, were independent predictors of diabetes with almost similar predictive ability; hence, in the evaluation of the risk of BP components for prediction of diabetes, the presence of family history of diabetes should be considered.

Predictive Mapping of Forest Attributes on the Fishlake National Forest

Treesearch

Tracey S. Frescino; Gretchen G. Moisen

2005-01-01

Forest land managers increasingly need maps of forest characteristics to aid in planning and management. A set of 30-m resolution maps was prepared for the Fishlake National Forest by modeling FIA plot variables as nonparametric functions of ancillary digital data. The set includes maps of volume, biomass, growth, stand age, size, crown cover, and various aspen...

Soil property maps of Africa at 250 m resolution

NASA Astrophysics Data System (ADS)

Kempen, Bas; Hengl, Tomislav; Heuvelink, Gerard B. M.; Leenaars, Johan G. B.; Walsh, Markus G.; MacMillan, Robert A.; Mendes de Jesus, Jorge S.; Shepherd, Keith; Sila, Andrew; Desta, Lulseged T.; Tondoh, Jérôme E.

2015-04-01

Vast areas of arable land in sub-Saharan Africa suffer from low soil fertility and physical soil constraints, and significant amounts of nutrients are lost yearly due to unsustainable soil management practices. At the same time it is expected that agriculture in Africa must intensify to meet the growing demand for food and fiber the next decades. Protection and sustainable management of Africa's soil resources is crucial to achieve this. In this context, comprehensive, accurate and up-to-date soil information is an essential input to any agricultural or environmental management or policy and decision-making model. In Africa, detailed soil information has been fragmented and limited to specific zones of interest for decades. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. AfSIS builds on recent advances in digital soil mapping, infrared spectroscopy, remote sensing, (geo)statistics, and integrated soil fertility management to improve the way soils are evaluated, mapped, and monitored. Over the period 2008-2014, the AfSIS project has compiled two soil profile data sets (about 28,000 unique locations): the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site (new soil samples) database -- the two data sets represent the most comprehensive soil sample database of the African continent to date. In addition a large set of high-resolution environmental data layers (covariates) was assembled. The point data were used in the AfSIS project to generate a set of maps of key soil properties for the African continent at 250 m spatial resolution: sand, silt and clay fractions, bulk density, organic carbon, total nitrogen, pH, cation-exchange capacity, exchangeable bases (Ca, K, Mg, Na), exchangeable acidity, and Al content. These properties were mapped for six depth intervals up to 2 m: 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm. Random forests modelling was used to relate the soil profile observations to a set covariates, that included global soil class and property maps, MODIS imagery and a DEM, in a 3D mapping framework. The model residuals were interpolated by 3D kriging, after which the kriging predictions were added to the random forests predictions to obtain the soil property predictions. The model predictions were validated with 5-fold cross-validation. The random forests models explained between 37% (exch. Na) and 85% (Al content) of the variation in the data. Results also show that globally predicted soil classes help improve continental scale mapping of the soil nutrients and are often among the most important predictors. We conclude that the first mapping results look promising. We used an automated modelling framework that enables re-computing the maps as new data becomes arrives, hereby gradually improving the maps. We showed that global maps of soil classes and properties produced with models that were predominantly calibrated on areas with plentiful observations can be used to improve the accuracy of predictions in regions with less plentiful data, such as Africa.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Performance Measures for Adaptive Decisioning Systems

DTIC Science & Technology

1991-09-11

set to hypothesis space mapping best approximates the known map. Two assumptions, a sufficiently representative training set and the ability of the...successful prediction of LINEXT performance. The LINEXT algorithm above performs the decision space mapping on the training-set ele- ments exactly. For a

The Miller Assessment for Preschoolers: A Longitudinal and Predictive Study. Final Report.

ERIC Educational Resources Information Center

Foundation for Knowledge in Development, Littleton, CO.

The study reported here sought to establish the predictive validity of the Miller Assessment for Preschoolers (MAP), an instrument designed to identify preschool children at risk for school-related problems in the primary years. Children (N=338) in 11 states who were originally tested in 1980 as part of the MAP standardization project were given a…

Use of airborne hyperspectral imagery to map soil parameters in tilled agricultural fields

USGS Publications Warehouse

Hively, W. Dean; McCarty, Gregory W.; Reeves, James B.; Lang, Megan W.; Oesterling, Robert A.; Delwiche, Stephen R.

2011-01-01

Soil hyperspectral reflectance imagery was obtained for six tilled (soil) agricultural fields using an airborne imaging spectrometer (400–2450 nm, ~10 nm resolution, 2.5 m spatial resolution). Surface soil samples (n = 315) were analyzed for carbon content, particle size distribution, and 15 agronomically important elements (Mehlich-III extraction). When partial least squares (PLS) regression of imagery-derived reflectance spectra was used to predict analyte concentrations, 13 of the 19 analytes were predicted with R2 > 0.50, including carbon (0.65), aluminum (0.76), iron (0.75), and silt content (0.79). Comparison of 15 spectral math preprocessing treatments showed that a simple first derivative worked well for nearly all analytes. The resulting PLS factors were exported as a vector of coefficients and used to calculate predicted maps of soil properties for each field. Image smoothing with a 3 × 3 low-pass filter prior to spectral data extraction improved prediction accuracy. The resulting raster maps showed variation associated with topographic factors, indicating the effect of soil redistribution and moisture regime on in-field spatial variability. High-resolution maps of soil analyte concentrations can be used to improve precision environmental management of farmlands.

Urban Seismic Hazard Mapping for Memphis, Shelby County, Tennessee

USGS Publications Warehouse

Gomberg, Joan

2006-01-01

Earthquakes cannot be predicted, but scientists can forecast how strongly the ground is likely to shake as a result of an earthquake. Seismic hazard maps provide one way of conveying such forecasts. The U.S. Geological Survey (USGS), which produces seismic hazard maps for the Nation, is now engaged in developing more detailed maps for vulnerable urban areas. The first set of these maps is now available for Memphis, Tennessee.

Geological Mapping of the Debussy Quadrangle (H-14) Preliminary Results

NASA Astrophysics Data System (ADS)

Pegg, D. L.; Rothery, D. A.; Balme, M. R.; Conway, S. J.

2018-05-01

We present the current status of geological mapping of the Debussy quadrangle. Mapping underway as part of a program to map the entire planet at a scale of 1:3M using MESSENGER data in preparation for the BepiColombo mission.

Methods of analysis and resources available for genetic trait mapping.

PubMed

Ott, J

1999-01-01

Methods of genetic linkage analysis are reviewed and put in context with other mapping techniques. Sources of information are outlined (books, web sites, computer programs). Special consideration is given to statistical problems in canine genetic mapping (heterozygosity, inbreeding, marker maps).

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges.

PubMed

Zanin, Marina; Mangabeira Albernaz, Ana Luisa

2016-01-01

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map's coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions.

How to Display Hazards and other Scientific Data Using Google Maps

NASA Astrophysics Data System (ADS)

Venezky, D. Y.; Fee, J. M.

2007-12-01

The U.S. Geological Survey's (USGS) Volcano Hazard Program (VHP) is launching a map-based interface to display hazards information using the Google® Map API (Application Program Interface). Map-based interfaces provide a synoptic view of data, making patterns easier to detect and allowing users to quickly ascertain where hazards are in relation to major population and infrastructure centers. Several map-based interfaces are now simple to run on a web server, providing ideal platforms for sharing information with colleagues, emergency managers, and the public. There are three main steps to making data accessible on a map-based interface; formatting the input data, plotting the data on the map, and customizing the user interface. The presentation, "Creating Geospatial RSS and ATOM feeds for Map-based Interfaces" (Fee and Venezky, this session), reviews key features for map input data. Join us for this presentation on how to plot data in a geographic context and then format the display with images, custom markers, and links to external data. Examples will show how the VHP Volcano Status Map was created and how to plot a field trip with driving directions.

Accuracy of three-dimensional multislice view Doppler in diagnosis of morbid adherent placenta

PubMed Central

Abdel Moniem, Alaa M.; Ibrahim, Ahmed; Akl, Sherif A.; Aboul-Enen, Loay; Abdelazim, Ibrahim A.

2015-01-01

Objective To detect the accuracy of the three-dimensional multislice view (3D MSV) Doppler in the diagnosis of morbid adherent placenta (MAP). Material and Methods Fifty pregnant women at ≥28 weeks gestation with suspected MAP were included in this prospective study. Two dimensional (2D) trans-abdominal gray-scale ultrasound scan was performed for the subjects to confirm the gestational age, placental location, and findings suggestive of MAP, followed by the 3D power Doppler and then the 3D MSV Doppler to confirm the diagnosis of MAP. Intraoperative findings and histopathology results of removed uteri in cases managed by emergency hysterectomy were compared with preoperative sonographic findings to detect the accuracy of the 3D MSV Doppler in the diagnosis of MAP. Results The 3D MSV Doppler increased the accuracy and predictive values of the diagnostic criteria of MAP compared with the 3D power Doppler. The sensitivity and negative predictive value (NPV) (79.6% and 82.2%, respectively) of crowded vessels over the peripheral sub-placental zone to detect difficult placental separation and considerable intraoperative blood loss in cases of MAP using the 3D power Doppler was increased to 82.6% and 84%, respectively, using the 3D MSV Doppler. In addition, the sensitivity, specificity, and positive predictive value (PPV) (90.9%, 68.8%, and 47%, respectively) of the disruption of the uterine serosa-bladder interface for the detection of emergency hysterectomy in cases of MAP using the 3D power Doppler was increased to 100%, 71.8%, and 50%, respectively, using the 3D MSV Doppler. Conclusion The 3D MSV Doppler is a useful adjunctive tool to the 3D power Doppler or color Doppler to refine the diagnosis of MAP. PMID:26401104

GIM-TEC adaptive ionospheric weather assessment and forecast system

NASA Astrophysics Data System (ADS)

Gulyaeva, T. L.; Arikan, F.; Hernandez-Pajares, M.; Stanislawska, I.

2013-09-01

The Ionospheric Weather Assessment and Forecast (IWAF) system is a computer software package designed to assess and predict the world-wide representation of 3-D electron density profiles from the Global Ionospheric Maps of Total Electron Content (GIM-TEC). The unique system products include daily-hourly numerical global maps of the F2 layer critical frequency (foF2) and the peak height (hmF2) generated with the International Reference Ionosphere extended to the plasmasphere, IRI-Plas, upgraded by importing the daily-hourly GIM-TEC as a new model driving parameter. Since GIM-TEC maps are provided with 1- or 2-days latency, the global maps forecast for 1 day and 2 days ahead are derived using an harmonic analysis applied to the temporal changes of TEC, foF2 and hmF2 at 5112 grid points of a map encapsulated in IONEX format (-87.5°:2.5°:87.5°N in latitude, -180°:5°:180°E in longitude). The system provides online the ionospheric disturbance warnings in the global W-index map establishing categories of the ionospheric weather from the quiet state (W=±1) to intense storm (W=±4) according to the thresholds set for instant TEC perturbations regarding quiet reference median for the preceding 7 days. The accuracy of IWAF system predictions of TEC, foF2 and hmF2 maps is superior to the standard persistence model with prediction equal to the most recent ‘true’ map. The paper presents outcomes of the new service expressed by the global ionospheric foF2, hmF2 and W-index maps demonstrating the process of origin and propagation of positive and negative ionosphere disturbances in space and time and their forecast under different scenarios.

Analyzing multiple data sets by interconnecting RSAT programs via SOAP Web services: an example with ChIP-chip data.

PubMed

Sand, Olivier; Thomas-Chollier, Morgane; Vervisch, Eric; van Helden, Jacques

2008-01-01

This protocol shows how to access the Regulatory Sequence Analysis Tools (RSAT) via a programmatic interface in order to automate the analysis of multiple data sets. We describe the steps for writing a Perl client that connects to the RSAT Web services and implements a workflow to discover putative cis-acting elements in promoters of gene clusters. In the presented example, we apply this workflow to lists of transcription factor target genes resulting from ChIP-chip experiments. For each factor, the protocol predicts the binding motifs by detecting significantly overrepresented hexanucleotides in the target promoters and generates a feature map that displays the positions of putative binding sites along the promoter sequences. This protocol is addressed to bioinformaticians and biologists with programming skills (notions of Perl). Running time is approximately 6 min on the example data set.

Reactivity of young chars via energetic distribution measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calo, J.M.; Lilly, W.D.

1991-01-01

The current project is directed at developing related techniques for the characterization and prediction/correlation of the reactivity of young'' chars to steam and oxygen. Of particular interest is mapping of the reactivity behavior of the resultant chars, as revealed by the energetic heterogeneity of the complexes with char preparation conditions; i.e., heating rate and ultimate temperature. In this first quarterly technical progress report we present the background of the project and the research program for the proposed investigations. The following work was accomplished on the experimental apparatus: a new set of electronics for the UTi quadrupole mass spectrometer head wasmore » purchased and delivered. The Temperature Programmed Desorption (TPD) System was moved to another laboratory and interfaced with the mass spectrometer system. A Polycold{trademark} freon refrigeration system was repaired and interfaced with the vacuum system for the TPD apparatus. It will be used to cool the diffusion pump trap. 60 refs.« less

Ranking of Texas reservoirs for application of carbon dioxide miscible displacement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ham, J

Of the 431 reservoirs screened, 211 projected revenue that exceeded cost, ie, were profitable. Only the top 154 reservoirs, however, showed a profit greater than 30%. The top 10 reservoirs predicted a profit of at least 80%. Six of the top ten were Gulf Coast sandstones. The reservoirs are representative of the most productive discoveries in Texas; they account for about 72% of the recorded 52 billion barrels oil production in the State. Preliminary evaluation in this study implied that potential production from CO{sub 2}-EOR could be as much as 4 billion barrels. In order to enhance the chances ofmore » achieving this, DOE should consider a targeted outreach program to the specific independent operators controlling the leases. Development of ownership/technical potential maps and an outreach program should be initiated to aid this identification.« less

Cognitive ergonomics: the use of mind mapping tool in maintaining productive sector of a Brazilian paper company.

PubMed

Mattos, Diego; Mateus, José Roberto; Merino, Eugenio

2012-01-01

The use of mind maps as a method of building knowledge, planning, organizing activities and ideas can be seen in the literature related to ergonomics. The results of such use are relevant and its use in academic area found. However, regarding to its use in industrial environments, studies can't not be found. With this scenario, and based on the perception of the ergonomist about the importance of using methods such as mind maps in support of human cognition, it seems pertinent to its use in industry sectors whose cognitive demand requires. Given these assumptions, this study aimed to apply the method of Mind Maps in Productive Maintenance sector of a Brazilian paper. The Productive Maintenance sector in the Paper Industry has an important contribution to operational performance. With practical Predictive Maintenance, Preventive Maintenance and Corrective Maintenance, the industry advocates to make the machines to produce paper is not to stop producing when they are programmed to do so. Among the practices cited, the Preventive Maintenance is one that leads to pre-determined intervals in order to reduce the possibility of placing the equipment in a condition below the required level of acceptance. Therefore, this article aims to propose using the tool "mental maps" in order to collaborate in planning and implementation of preventive maintenance activities in the sector of mechanical maintenance of a pulp and paper industry in southern Brazil. The study investigated the maintenance sector through its employees, who went through training about the tool and then use it and ergonomists company.

Challenging the Myth of Right Nondominant Hemisphere: Lessons from Corticosubcortical Stimulation Mapping in Awake Surgery and Surgical Implications.

PubMed

Vilasboas, Tatiana; Herbet, Guillaume; Duffau, Hugues

2017-07-01

For many years, the right hemisphere (RH) was considered as nondominant, especially in right-handers. In neurosurgical practice, this dogma resulted in the selection of awake procedure with language mapping only for lesions of the left dominant hemisphere. Conversely, surgery under general anesthesia (possibly with motor mapping) was usually proposed for right lesions. However, when objective neuropsychological assessments were performed, they frequently showed cognitive and behavioral deficits after brain surgery, even in the RH. Therefore, to preserve an optimal quality of life, especially in patients with a long survival expectancy (as in low-grade gliomas), awake surgery with cortical and axonal electrostimulation mapping has recently been proposed for resection of right tumors. Here, we review new insights gained from intraoperative stimulation into the pivotal role of the RH in movement execution and control, visual processes and spatial cognition, language and nonverbal semantic processing, executive functions (e.g., attention), and social cognition (mentalizing and emotion recognition). These original findings, which break with the myth of a nondominant RH, may have important implications in cognitive neurosciences, by improving our knowledge of the functional connectivity of the RH, as well as for the clinical management of patients with a right lesion. In brain surgery, awake mapping should be considered more systematically in the RH. Moreover, neuropsychological examination must be achieved in a more systematic manner before and after surgery within the RH, to optimize care by predicting the likelihood of functional recovery and by elaborating specific programs of rehabilitation. Copyright © 2017 Elsevier Inc. All rights reserved.

Analogy Mapping Development for Learning Programming

NASA Astrophysics Data System (ADS)

Sukamto, R. A.; Prabawa, H. W.; Kurniawati, S.

2017-02-01

Programming skill is an important skill for computer science students, whereas nowadays, there many computer science students are lack of skills and information technology knowledges in Indonesia. This is contrary with the implementation of the ASEAN Economic Community (AEC) since the end of 2015 which is the qualified worker needed. This study provided an effort for nailing programming skills by mapping program code to visual analogies as learning media. The developed media was based on state machine and compiler principle and was implemented in C programming language. The state of every basic condition in programming were successful determined as analogy visualization.

Winter in Northern Europe (WINE) Project

NASA Technical Reports Server (NTRS)

Vonzahn, U.

1982-01-01

The scientific aims, work plan, and organization of the Middle Atmosphere Program winter in northern Europe (MAP/WINE) are described. Proposed contributions to the MAP/WINE program from various countries are enumerated. Specific atmospheric parameters to be examined are listed along with the corresponding measurement technique.

7 CFR 1485.18 - Advances.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AGRICULTURE EXPORT PROGRAMS COOPERATIVE AGREEMENTS FOR THE DEVELOPMENT OF FOREIGN MARKETS FOR AGRICULTURAL COMMODITIES Market Access Program § 1485.18 Advances. (a) Policy. In general, CCC operates MAP and EIP/MAP on... participant for generic promotion activities. Prior to making an advance, CCC may require the participant to...

Multifrequency Aperture-Synthesizing Microwave Radiometer System (MFASMR). Volume 2: Appendix

NASA Technical Reports Server (NTRS)

Wiley, C. A.; Chang, M. U.

1981-01-01

A number of topics supporting the systems analysis of a multifrequency aperture-synthesizing microwave radiometer system are discussed. Fellgett's (multiple) advantage, interferometer mapping behavior, mapping geometry, image processing programs, and sampling errors are among the topics discussed. A FORTRAN program code is given.

Intelligent seismic risk mitigation system on structure building

NASA Astrophysics Data System (ADS)

Suryanita, R.; Maizir, H.; Yuniorto, E.; Jingga, H.

2018-01-01

Indonesia located on the Pacific Ring of Fire, is one of the highest-risk seismic zone in the world. The strong ground motion might cause catastrophic collapse of the building which leads to casualties and property damages. Therefore, it is imperative to properly design the structural response of building against seismic hazard. Seismic-resistant building design process requires structural analysis to be performed to obtain the necessary building responses. However, the structural analysis could be very difficult and time consuming. This study aims to predict the structural response includes displacement, velocity, and acceleration of multi-storey building with the fixed floor plan using Artificial Neural Network (ANN) method based on the 2010 Indonesian seismic hazard map. By varying the building height, soil condition, and seismic location in 47 cities in Indonesia, 6345 data sets were obtained and fed into the ANN model for the learning process. The trained ANN can predict the displacement, velocity, and acceleration responses with up to 96% of predicted rate. The trained ANN architecture and weight factors were later used to build a simple tool in Visual Basic program which possesses the features for prediction of structural response as mentioned previously.

Towards Inferring Protein Interactions: Challenges and Solutions

NASA Astrophysics Data System (ADS)

Zhang, Ya; Zha, Hongyuan; Chu, Chao-Hsien; Ji, Xiang

2006-12-01

Discovering interacting proteins has been an essential part of functional genomics. However, existing experimental techniques only uncover a small portion of any interactome. Furthermore, these data often have a very high false rate. By conceptualizing the interactions at domain level, we provide a more abstract representation of interactome, which also facilitates the discovery of unobserved protein-protein interactions. Although several domain-based approaches have been proposed to predict protein-protein interactions, they usually assume that domain interactions are independent on each other for the convenience of computational modeling. A new framework to predict protein interactions is proposed in this paper, where no assumption is made about domain interactions. Protein interactions may be the result of multiple domain interactions which are dependent on each other. A conjunctive norm form representation is used to capture the relationships between protein interactions and domain interactions. The problem of interaction inference is then modeled as a constraint satisfiability problem and solved via linear programing. Experimental results on a combined yeast data set have demonstrated the robustness and the accuracy of the proposed algorithm. Moreover, we also map some predicted interacting domains to three-dimensional structures of protein complexes to show the validity of our predictions.

The U.S. Geological Survey's Earthquake Summary Posters: A GIS-based Education and Communication Product for Presenting Consolidated Post-Earthquake Information

NASA Astrophysics Data System (ADS)

Tarr, A.; Benz, H.; Earle, P.; Wald, D. J.

2003-12-01

Earthquake Summary Posters (ESP's), a new product of the U.S. Geological Survey's Earthquake Program, are produced at the National Earthquake Information Center (NEIC) in Golden. The posters consist of rapidly-generated, GIS-based maps made following significant earthquakes worldwide (typically M>7.0, or events of significant media/public interest). ESP's consolidate, in an attractive map format, a large-scale epicentral map, several auxiliary regional overviews (showing tectonic and geographical setting, seismic history, seismic hazard, and earthquake effects), depth sections (as appropriate), a table of regional earthquakes, and a summary of the reional seismic history and tectonics. The immediate availability of the latter text summaries has been facilitated by the availability of Rapid, Accurate Tectonic Summaries (RATS) produced at NEIC and posted on the web following significant events. The rapid production of ESP's has been facilitated by generating, during the past two years, regional templates for tectonic areas around the world by organizing the necessary spatially-referenced data for the map base and the thematic layers that overlay the base. These GIS databases enable scripted Arc Macro Language (AML) production of routine elements of the maps (for example background seismicity, tectonic features, and probabilistic hazard maps). However, other elements of the maps are earthquake-specific and are produced manually to reflect new data, earthquake effects, and special characteristics. By the end of this year, approximately 85% of the Earth's seismic zones will be covered for generating future ESP's. During the past year, 13 posters were completed, comparable to the yearly average expected for significant earthquakes. Each year, all ESPs will be published on a CD in PDF format as an Open-File Report. In addition, each is linked to the special event earthquake pages on the USGS Earthquake Program web site (http://earthquake.usgs.gov). Although three formats are generated, the poster-size format is the most popular for display, outreach, and use as a working map for project scientists (JPEG format for web; PDF for download, editing, and printing) whereas the other (smaller) formats are suitable for briefing packages. We will soon make both GIS and PDF files of individual elements of the posters available online. ESP's provide an unprecedented opportunity for college earth-science faculty to take advantage of current events for timely lessons in global tectonics. They are also invaluable to communicate with the media and with government officials. ESP's will be used as a vehicle to present other products now under development under the auspices of NEIC and the ANSS, including rapid finite-fault models, global predictive ShakeMaps, "Did You Feel It?", and Rapid Assessments of Global Earthquakes (RAGE, Earle and others, this meeting).

REQUIREMENT VERIFICATION AND SYSTEMS ENGINEERING TECHNICAL REVIEW (SETR) ON A COMMERCIAL DERIVATIVE AIRCRAFT (CDA) PROGRAM

DTIC Science & Technology

2017-09-01

the SETR entrance criteria of these events. Out of 30 evaluated SETR entrance criteria, 22 map to FAA elements. A case study of a military CDA...evaluated SETR entrance criteria, 22 map to FAA elements. A case study of a military CDA program, the Presidential Helicopter Replacement Program...3 C. SCOPE AND METHODOLOGY .................................................. 4 D. ORGANIZATION OF THESIS

Enhanced propagation modeling of directional aviation noise: A hybrid parabolic equation-fast field program method

NASA Astrophysics Data System (ADS)

Rosenbaum, Joyce E.

2011-12-01

Commercial air traffic is anticipated to increase rapidly in the coming years. The impact of aviation noise on communities surrounding airports is, therefore, a growing concern. Accurate prediction of noise can help to mitigate the impact on communities and foster smoother integration of aerospace engineering advances. The problem of accurate sound level prediction requires careful inclusion of all mechanisms that affect propagation, in addition to correct source characterization. Terrain, ground type, meteorological effects, and source directivity can have a substantial influence on the noise level. Because they are difficult to model, these effects are often included only by rough approximation. This dissertation presents a model designed for sound propagation over uneven terrain, with mixed ground type and realistic meteorological conditions. The model is a hybrid of two numerical techniques: the parabolic equation (PE) and fast field program (FFP) methods, which allow for physics-based inclusion of propagation effects and ensure the low frequency content, a factor in community impact, is predicted accurately. Extension of the hybrid model to a pseudo-three-dimensional representation allows it to produce aviation noise contour maps in the standard form. In order for the model to correctly characterize aviation noise sources, a method of representing arbitrary source directivity patterns was developed for the unique form of the parabolic equation starting field. With this advancement, the model can represent broadband, directional moving sound sources, traveling along user-specified paths. This work was prepared for possible use in the research version of the sound propagation module in the Federal Aviation Administration's new standard predictive tool.

Phenologically informed re-ordering of Landsat to account for inter-annual variability: a method to map Ash trees (Fraxinus spp.) using remotely sensed imagery

NASA Astrophysics Data System (ADS)

Isaacson, B. N.; Singh, A.; Serbin, S. P.; Townsend, P. A.

2009-12-01

Rapid ecosystem invasion by the emerald ash borer (Agrilus planipennis Fairemaire) is forcing resource managers to make decisions regarding how best to manage the pest, but a detailed map of abundance of the host, ash trees of the genus Fraxinus, does not exist, frustrating fully informed management decisions. We have developed methods to map ash tree abundance across a broad spatial extent in Wisconsin using their unique phenology (late leaf-out, early leaf-fall) and the rich dataset of Landsat imagery that can be used to characterize ash senescence with respect to other deciduous species. However, across environmental gradients in Wisconsin, senescence can vary by days or even weeks such that leaf-drop within one species can temporally vary even within a single Landsat footprint. To address this issue, we used phenology products from NASA’s MODIS for North American Carbon Program (NACP) coupled with vegetation indices derived from a time series of Landsat imagery across multiple years to determine the phenological position of each Landsat pixel within a single idealized growing season. Pixels within Landsat images collected in different years were re-arranged in a phenologically-informed time series that described autumn senescence. This characterization of leaf-drop was then related to the abundance of ash trees, producing a spatially-generalizable model of moderate resolution capable of predicting ash abundance across the state using multiple Landsat scenes. Empirical models predicting ash abundance for two Landsat footprints in Wisconsin indicate model fits for ash abundance of R^2=0.65 in north-central WI, and R^2>0.70 in southeastern WI.

Scoping of Flood Hazard Mapping Needs for Hancock County, Maine

USGS Publications Warehouse

Schalk, Charles W.; Dudley, Robert W.

2007-01-01

Background The Federal Emergency Management Agency (FEMA) developed a plan in 1997 to modernize the FEMA flood mapping program. FEMA flood maps delineate flood hazard areas in support of the National Flood Insurance Program (NFIP). FEMA's plan outlined the steps necessary to update FEMA's flood maps for the nation to a seamless digital format and streamline FEMA's operations in raising public awareness of the importance of the maps and responding to requests to revise them. The modernization of flood maps involves conversion of existing information to digital format and integration of improved flood hazard data as needed. To determine flood mapping modernization needs, FEMA has established specific scoping activities to be done on a county-by-county basis for identifying and prioritizing requisite flood-mapping activities for map modernization. The U.S. Geological Survey (USGS), in cooperation with FEMA and the Maine Floodplain Management Program (MFMP) State Planning Office, began scoping work in 2006 for Hancock County. Scoping activities included assembling existing data and map needs information for communities in Hancock County, documentation of data, contacts, community meetings, and prioritized mapping needs in a final scoping report (this document), and updating the Mapping Needs Update Support System (MNUSS) database with information gathered during the scoping process. The average age of the FEMA floodplain maps (all types) in Hancock County, Maine, is at least 19 years. Most of these studies were published in the late 1980s and early 1990s, and no study is more recent than 1992. Some towns have partial maps that are more recent than their study, indicating that the true average age of the data is probably more than 19 years. Since the studies were done, development has occurred in some of the watersheds and the characteristics of the watersheds have changed. Therefore, many of the older studies may not depict current conditions or accurately estimate risk in terms of flood heights or flood mapping.

OZONE MONITORING, MAPPING, AND PUBLIC OUTREACH ...

EPA Pesticide Factsheets

The U.S. EPA had developed a handbook to help state and local government officials implement ozone monitoring, mapping, and outreach programs. The handbook, called Ozone Monitoring, Mapping, and Public Outreach: Delivering Real-Time Ozone Information to Your Community, provides step-by-step instructions on how to: Design, site, operate, and maintain an ozone monitoring network. Install, configure, and operate the Automatic Data Transfer System Use MapGen software to create still-frame and animated ozone maps. Develop and outreach plan to communicate information about real-time ozone levels and their health effects to the public.This handbook was developed by EPA's EMPACT program. The program takes advantage of new technologies that make it possible to provide environmental information to the public in near real time. EMPACT is working with the 86 largest metropolitan areas of the country to help communities in these areas: Collect, manage and distribute time-relevant environmental information. Provide their residents with easy-to-understand information they can use in making informed, day-to-day decisions. Information

Link between orientation and retinotopic maps in primary visual cortex

PubMed Central

Paik, Se-Bum; Ringach, Dario L.

2012-01-01

Maps representing the preference of neurons for the location and orientation of a stimulus on the visual field are a hallmark of primary visual cortex. It is not yet known how these maps develop and what function they play in visual processing. One hypothesis postulates that orientation maps are initially seeded by the spatial interference of ON- and OFF-center retinal receptive field mosaics. Here we show that such a mechanism predicts a link between the layout of orientation preferences around singularities of different signs and the cardinal axes of the retinotopic map. Moreover, we confirm the predicted relationship holds in tree shrew primary visual cortex. These findings provide additional support for the notion that spatially structured input from the retina may provide a blueprint for the early development of cortical maps and receptive fields. More broadly, it raises the possibility that spatially structured input from the periphery may shape the organization of primary sensory cortex of other modalities as well. PMID:22509015

An Integrated Children Disease Prediction Tool within a Special Social Network.

PubMed

Apostolova Trpkovska, Marika; Yildirim Yayilgan, Sule; Besimi, Adrian

2016-01-01

This paper proposes a social network with an integrated children disease prediction system developed by the use of the specially designed Children General Disease Ontology (CGDO). This ontology consists of children diseases and their relationship with symptoms and Semantic Web Rule Language (SWRL rules) that are specially designed for predicting diseases. The prediction process starts by filling data about the appeared signs and symptoms by the user which are after that mapped with the CGDO ontology. Once the data are mapped, the prediction results are presented. The phase of prediction executes the rules which extract the predicted disease details based on the SWRL rule specified. The motivation behind the development of this system is to spread knowledge about the children diseases and their symptoms in a very simple way using the specialized social networking website www.emama.mk.

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Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Prediction Climate Prediction Center 5200 Auth Road Camp Springs, Maryland 20746 Climate Prediction Center

Opportunities for Environmental Noise Mapping in Saudi Arabia: A Case of Traffic Noise Annoyance in an Urban Area in Jeddah City.

PubMed

Zytoon, Mohamed A

2016-05-13

As the traffic and other environmental noise generating activities are growing in The Kingdom of Saudi Arabia (KSA), adverse health and other impacts are expected to develop. The management of such problem involves many actions, of which noise mapping has been proven to be a helpful approach. The objective of the current study was to test the adequacy of the available data in KSA municipalities for generating urban noise maps and to verify the applicability of available environmental noise mapping and noise annoyance models for KSA. Therefore, noise maps were produced for Al-Fayha District in Jeddah City, KSA using commercially available noise mapping software and applying the French national computation method "NMPB" for traffic noise. Most of the data required for traffic noise prediction and annoyance analysis were available, either in the Municipality GIS department or in other governmental authorities. The predicted noise levels during the three time periods, i.e., daytime, evening, and nighttime, were found higher than the maximum recommended levels established in KSA environmental noise standards. Annoyance analysis revealed that high percentages of the District inhabitants were highly annoyed, depending on the type of planning zone and period of interest. These results reflect the urgent need to consider environmental noise reduction in KSA national plans. The accuracy of the predicted noise levels and the availability of most of the necessary data should encourage further studies on the use of noise mapping as part of noise reduction plans.

Development of flood-inundation maps for the West Branch Susquehanna River near the Borough of Jersey Shore, Lycoming County, Pennsylvania

USGS Publications Warehouse

Roland, Mark A.; Hoffman, Scott A.

2011-01-01

Streamflow data, water-surface-elevation profiles derived from a Hydrologic Engineering Center River Analysis System hydraulic model, and geographical information system digital elevation models were used to develop a set of 18 flood-inundation maps for an approximately 5-mile reach of the West Branch Susquehanna River near the Borough of Jersey Shore, Pa. The inundation maps were created by the U.S. Geological Survey in cooperation with the Susquehanna River Basin Commission and Lycoming County as part of an ongoing effort by the National Oceanic and Atmospheric Administration's National Weather Service to focus on continued improvements to the flood forecasting and warning abilities in the Susquehanna River Basin and to modernize flood-forecasting methodologies. The maps, ranging from 23.0 to 40.0 feet in 1-foot increments, correspond to river stage at the U.S. Geological Survey streamgage 01549760 at Jersey Shore. The electronic files used to develop the maps were provided to the National Weather Service for incorporation into their Advanced Hydrologic Prediction Service website. The maps are displayed on this website, which serves as a web-based floodwarning system, and can be used to identify areas of predicted flood inundation associated with forecasted flood-peak stages. During times of flooding or predicted flooding, these maps can be used by emergency managers and the public to take proactive steps to protect life and reduce property damage caused by floods.

A Mapping of Drug Space from the Viewpoint of Small Molecule Metabolism

PubMed Central

Basuino, Li; Chambers, Henry F.; Lee, Deok-Sun; Wiest, Olaf G.; Babbitt, Patricia C.

2009-01-01

Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the “effect space” comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism. PMID:19701464

Genome-based prediction of test cross performance in two subsequent breeding cycles.

PubMed

Hofheinz, Nina; Borchardt, Dietrich; Weissleder, Knuth; Frisch, Matthias

2012-12-01

Genome-based prediction of genetic values is expected to overcome shortcomings that limit the application of QTL mapping and marker-assisted selection in plant breeding. Our goal was to study the genome-based prediction of test cross performance with genetic effects that were estimated using genotypes from the preceding breeding cycle. In particular, our objectives were to employ a ridge regression approach that approximates best linear unbiased prediction of genetic effects, compare cross validation with validation using genetic material of the subsequent breeding cycle, and investigate the prospects of genome-based prediction in sugar beet breeding. We focused on the traits sugar content and standard molasses loss (ML) and used a set of 310 sugar beet lines to estimate genetic effects at 384 SNP markers. In cross validation, correlations >0.8 between observed and predicted test cross performance were observed for both traits. However, in validation with 56 lines from the next breeding cycle, a correlation of 0.8 could only be observed for sugar content, for standard ML the correlation reduced to 0.4. We found that ridge regression based on preliminary estimates of the heritability provided a very good approximation of best linear unbiased prediction and was not accompanied with a loss in prediction accuracy. We conclude that prediction accuracy assessed with cross validation within one cycle of a breeding program can not be used as an indicator for the accuracy of predicting lines of the next cycle. Prediction of lines of the next cycle seems promising for traits with high heritabilities.

The Quantitative Evaluation of the Clinical and Translational Science Awards (CTSA) Program Based on Science Mapping and Scientometric Analysis

PubMed Central

Zhang, Yin; Wang, Lei

2013-01-01

Abstract The Clinical and Translational Science Awards (CTSA) program is one of the most important initiatives in translational medical funding. The quantitative evaluation of the efficiency and performance of the CTSA program has a significant referential meaning for the decision making of global translational medical funding. Using science mapping and scientometric analytic tools, this study quantitatively analyzed the scientific articles funded by the CTSA program. The results of the study showed that the quantitative productivities of the CTSA program had a stable increase since 2008. In addition, the emerging trends of the research funded by the CTSA program covered clinical and basic medical research fields. The academic benefits from the CTSA program were assisting its members to build a robust academic home for the Clinical and Translational Science and to attract other financial support. This study provided a quantitative evaluation of the CTSA program based on science mapping and scientometric analysis. Further research is required to compare and optimize other quantitative methods and to integrate various research results. PMID:24330689

The quantitative evaluation of the Clinical and Translational Science Awards (CTSA) program based on science mapping and scientometric analysis.

PubMed

Zhang, Yin; Wang, Lei; Diao, Tianxi

2013-12-01

The Clinical and Translational Science Awards (CTSA) program is one of the most important initiatives in translational medical funding. The quantitative evaluation of the efficiency and performance of the CTSA program has a significant referential meaning for the decision making of global translational medical funding. Using science mapping and scientometric analytic tools, this study quantitatively analyzed the scientific articles funded by the CTSA program. The results of the study showed that the quantitative productivities of the CTSA program had a stable increase since 2008. In addition, the emerging trends of the research funded by the CTSA program covered clinical and basic medical research fields. The academic benefits from the CTSA program were assisting its members to build a robust academic home for the Clinical and Translational Science and to attract other financial support. This study provided a quantitative evaluation of the CTSA program based on science mapping and scientometric analysis. Further research is required to compare and optimize other quantitative methods and to integrate various research results. © 2013 Wiley Periodicals, Inc.

The US Geological Survey's National Mapping Division programs, products, and services that can support wetlands mapping

USGS Publications Warehouse

Baxter, F.S.

1990-01-01

The US Geological Survey (USGS) programs can play an important role in support of President Bush's policy of no net loss of wetlands. A principal goal of USGS is to provide cartographic information that contributes to the wise management of the Nation's natural resources. This information consists of maps, cartographic data bases (graphic and digital), remotely sensed imagery, and information services. These products are used by Federal, State, and local governments, the private sector, and individual citizens in making decisions on the existence and use of land and water resources. I discuss the programs, products, and information services of the National Mapping Division, the tools available to determine where wetlands exist, and the capability of periodic measurement of wetlands to help in assessing compliance with the concept of no net loss of wetlands. -from Author

Simulation-Based Height of Burst Map for Asteroid Airburst Damage Prediction

NASA Technical Reports Server (NTRS)

Aftosmis, Michael J.; Mathias, Donovan L.; Tarano, Ana M.

2017-01-01

Entry and breakup models predict that airburst in the Earth's atmosphere is likely for asteroids up to approximately 200 meters in diameter. Objects of this size can deposit over 250 megatons of energy into the atmosphere. Fast-running ground damage prediction codes for such events rely heavily upon methods developed from nuclear weapons research to estimate the damage potential for an airburst at altitude. (Collins, 2005; Mathias, 2017; Hills and Goda, 1993). In particular, these tools rely upon the powerful yield scaling laws developed for point-source blasts that are used in conjunction with a Height of Burst (HOB) map to predict ground damage for an airburst of a specific energy at a given altitude. While this approach works extremely well for yields as large as tens of megatons, it becomes less accurate as yields increase to the hundreds of megatons potentially released by larger airburst events. This study revisits the assumptions underlying this approach and shows how atmospheric buoyancy becomes important as yield increases beyond a few megatons. We then use large-scale three-dimensional simulations to construct numerically generated height of burst maps that are appropriate at the higher energy levels associated with the entry of asteroids with diameters of hundreds of meters. These numerically generated HOB maps can then be incorporated into engineering methods for damage prediction, significantly improving their accuracy for asteroids with diameters greater than 80-100 m.

Integrating Map Algebra and Statistical Modeling for Spatio- Temporal Analysis of Monthly Mean Daily Incident Photosynthetically Active Radiation (PAR) over a Complex Terrain.

PubMed

Evrendilek, Fatih

2007-12-12

This study aims at quantifying spatio-temporal dynamics of monthly mean dailyincident photosynthetically active radiation (PAR) over a vast and complex terrain such asTurkey. The spatial interpolation method of universal kriging, and the combination ofmultiple linear regression (MLR) models and map algebra techniques were implemented togenerate surface maps of PAR with a grid resolution of 500 x 500 m as a function of fivegeographical and 14 climatic variables. Performance of the geostatistical and MLR modelswas compared using mean prediction error (MPE), root-mean-square prediction error(RMSPE), average standard prediction error (ASE), mean standardized prediction error(MSPE), root-mean-square standardized prediction error (RMSSPE), and adjustedcoefficient of determination (R² adj. ). The best-fit MLR- and universal kriging-generatedmodels of monthly mean daily PAR were validated against an independent 37-year observeddataset of 35 climate stations derived from 160 stations across Turkey by the Jackknifingmethod. The spatial variability patterns of monthly mean daily incident PAR were moreaccurately reflected in the surface maps created by the MLR-based models than in thosecreated by the universal kriging method, in particular, for spring (May) and autumn(November). The MLR-based spatial interpolation algorithms of PAR described in thisstudy indicated the significance of the multifactor approach to understanding and mappingspatio-temporal dynamics of PAR for a complex terrain over meso-scales.

Performance-based planning and programming in the context of MAP-21 : a TPCB workshop

DOT National Transportation Integrated Search

2015-01-01

This report highlights key recommendations and noteworthy practices identified at the workshop on Performance-based Planning and Programming in the Context of MAP-21 held on March 6-7, 2014 in New York City, New York and via video teleconferenc...

Exploring the Realized Niche: Simulated Ecological Mapping with a Microcomputer.

ERIC Educational Resources Information Center

Kent, J. W.

1983-01-01

Describes a computer program based upon field observations of littoral zonation modified by a small stream. The program employs user-defined color graphic characters to display simulated ecological maps representing the patterning of organisms in response to local values of niche limiting factors. (Author/JN)

Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery

NASA Astrophysics Data System (ADS)

Castillo, Jose Alan A.; Apan, Armando A.; Maraseni, Tek N.; Salmo, Severino G.

2017-12-01

The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82-0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8-28.5 Mg ha-1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement non-forest land uses, especially with the inclusion of elevation data. The study demonstrates encouraging results in biomass mapping of mangroves and other coastal land uses in the tropics using the freely accessible and relatively high-resolution Sentinel imagery.

Promoting Inclusivity in STEM through Active Recruiting and Mentoring: The Pre-Major in Astronomy Program (Pre-MAP) at the University of Washington

NASA Astrophysics Data System (ADS)

Schwieterman, Edward; Binder, Breanna A.; Pre-Major in Astronomy Program

2016-01-01

The Pre-Major in Astronomy Program (Pre-MAP) is a research and mentoring program for entering undergraduate students offered by the University of Washington Astronomy Department since 2005. The primary goal of Pre-MAP is to recruit and retain students from groups traditionally underrepresented in science, technology, engineering, and mathematics (STEM) through early exposure to guided research projects. The Pre-MAP seminar is the core component of the program and offers instruction in computing skills, data manipulation, science writing, statistical analysis, and scientific speaking and presentation skills. Students choose research projects proposed by faculty, post-docs and graduate students in areas related to astrophysics, planetary science, and astrobiology. Pre-MAP has been successful in retaining underrepresented students in STEM fields relative to the broader UW population, and we've found these students are more likely to graduate and excel academically than their peers. As of fall 2015, more than one hundred students have taken the Pre-MAP seminar, and both internal and external evaluations have shown that all groups of participating students report an increased interest in astronomy and science careers at the end of the seminar. This talk will provide an overview of the program and the structure of the core seminar. In particular, the talk will focus on additions and revisions to the seminar course over the last few years, such as the introduction of a public speaking coach, career and internship modules, and the formalization of external lab tours.

Comparison of the Effects of Episodic Mapping and Traditional Notetaking on the Recall of Historical Text.

ERIC Educational Resources Information Center

Denner, Peter R.

This study examined the effects of episodic-mapping, traditional notetaking, and rereading on eighth-grade students' recall of historical text. Episodic-maps are a kind of notetaking procedure that requires students to represent ideas from a text in the form of a graphic diagram. As predicted, both episodic-mapping and traditional notetaking…

[Response to treatment of patients abusing the "dappou drug" who participated in a group relapse prevention program: a comparison with patients abusing methamphetamine].

PubMed

Hikitsuchi, Emi; Matsumoto, Toshihiko; Wada, Kiyoshi; Tanibuchi, Yuko; Takano, Ayumi; Imamura, Fumi; Kawachi, Hiraku; Wakabayashi, Asako; Kato, Takashi

2014-12-01

In this study, we compared the efficacy of a group relapse prevention program using the cognitive behavioral therapy-based workbook, Serigaya Methamphetamine Relapse Prevention Program (SMARPP), between patients abusing the so-called "dappou drugs" (designer drug in Japan, and those abusing methamphetamine (MAP). Both groups participated in the SMARPP at the Center Hospital, National Center of Neurology and Psychiatry. Results showed that, no significant differences were found in the rates of participation in the program or self-reported frequency of drug or alcohol use between the patients abusing "dappou drugs" or MAP. However, patients using "dappou drugs" reported no significant increase in their confidence in their ability to resist the temptation to use drugs on the self- report drug abuse scales after the SMARPP intervention, while patients abusing MAP reported a significant positive difference in their ability to resist temptation. In addition, insight into substance abuse problems and motivation to participate in further treatment slightly declined in those using "dappou drugs," while there was a significant increase reported by the patients using MAP. These results suggested that the SMARPP might not be as effective for patients abusing "dappou drugs" as for those abusing MAP. The development of a relapse prevention program specifically designed for patients abusing "dappou drugs" is required.

BenMAP Downloads

EPA Pesticide Factsheets

Download the current and legacy versions of the BenMAP program. Download configuration and aggregation/pooling/valuation files to estimate benefits. BenMAP-CE is free and open source software, and the source code is available upon request.

Evaluating Predictive Models of Software Quality

NASA Astrophysics Data System (ADS)

Ciaschini, V.; Canaparo, M.; Ronchieri, E.; Salomoni, D.

2014-06-01

Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

Environmental benefits vs. costs of geologic mapping

USGS Publications Warehouse

Bhagwat, S.B.; Berg, R.C.

1992-01-01

Boone and Winnebago Counties, Illinois, U.S.A., were selected for this study, required by the Illinois State Senate, because mapping and environmental interpretations were completed there in 1981. Costs of geologic mapping in these counties in 1990 dollars were $290,000. Two estimates of costs of statewide mapping were made, one extrapolated from Boone and Winnebago Counties ($21 million), the other estimated on the basis of differences between the Boone/Winnebago program and proposed mapping program for the State of Illinois ($55 million). Benefits of geologic information come in the form of future avoided costs for environmental cleanup. Only the quantifiable data, available from a few sites, were included. Data collection, based on 55 personal interviews in Boone and Winnebago Counties, were grouped into four cumulative categories with increasing variability. Geologic maps alone cannot account for all avoided costs of future cleanup. Therefore, estimated benefits were reduced by 50, 75, and 90 percent in three scenarios. To account for delays in proper utilization of knowledge gained from a mapping program, a 10-yr delay in benefit realization was assumed. All benefits were converted to 1990 dollars. In benefit category 4, benefit-cost ratios for Boone/Winnebago Counties ranged between 5 and 55. Statewide projection of benefits was based on county areas and an aquifer contamination potential score for each county. Statewide benefit-cost ratio in benefit category 4 ranged from 1.2 to 14 ($21 million mapping costs) and from 0.5 to 5.4 ($55 million mapping costs). ?? 1992 Springer-Verlag New York Inc.

Multi-step-ahead Method for Wind Speed Prediction Correction Based on Numerical Weather Prediction and Historical Measurement Data

NASA Astrophysics Data System (ADS)

Wang, Han; Yan, Jie; Liu, Yongqian; Han, Shuang; Li, Li; Zhao, Jing

2017-11-01

Increasing the accuracy of wind speed prediction lays solid foundation to the reliability of wind power forecasting. Most traditional correction methods for wind speed prediction establish the mapping relationship between wind speed of the numerical weather prediction (NWP) and the historical measurement data (HMD) at the corresponding time slot, which is free of time-dependent impacts of wind speed time series. In this paper, a multi-step-ahead wind speed prediction correction method is proposed with consideration of the passing effects from wind speed at the previous time slot. To this end, the proposed method employs both NWP and HMD as model inputs and the training labels. First, the probabilistic analysis of the NWP deviation for different wind speed bins is calculated to illustrate the inadequacy of the traditional time-independent mapping strategy. Then, support vector machine (SVM) is utilized as example to implement the proposed mapping strategy and to establish the correction model for all the wind speed bins. One Chinese wind farm in northern part of China is taken as example to validate the proposed method. Three benchmark methods of wind speed prediction are used to compare the performance. The results show that the proposed model has the best performance under different time horizons.

Advances and Challenges in Genomic Selection for Disease Resistance.

PubMed

Poland, Jesse; Rutkoski, Jessica

2016-08-04

Breeding for disease resistance is a central focus of plant breeding programs, as any successful variety must have the complete package of high yield, disease resistance, agronomic performance, and end-use quality. With the need to accelerate the development of improved varieties, genomics-assisted breeding is becoming an important tool in breeding programs. With marker-assisted selection, there has been success in breeding for disease resistance; however, much of this work and research has focused on identifying, mapping, and selecting for major resistance genes that tend to be highly effective but vulnerable to breakdown with rapid changes in pathogen races. In contrast, breeding for minor-gene quantitative resistance tends to produce more durable varieties but is a more challenging breeding objective. As the genetic architecture of resistance shifts from single major R genes to a diffused architecture of many minor genes, the best approach for molecular breeding will shift from marker-assisted selection to genomic selection. Genomics-assisted breeding for quantitative resistance will therefore necessitate whole-genome prediction models and selection methodology as implemented for classical complex traits such as yield. Here, we examine multiple case studies testing whole-genome prediction models and genomic selection for disease resistance. In general, whole-genome models for disease resistance can produce prediction accuracy suitable for application in breeding. These models also largely outperform multiple linear regression as would be applied in marker-assisted selection. With the implementation of genomic selection for yield and other agronomic traits, whole-genome marker profiles will be available for the entire set of breeding lines, enabling genomic selection for disease at no additional direct cost. In this context, the scope of implementing genomics selection for disease resistance, and specifically for quantitative resistance and quarantined pathogens, becomes a tractable and powerful approach in breeding programs.

Landscape scale mapping of forest inventory data by nearest neighbor classification

Treesearch

Andrew Lister

2009-01-01

One of the goals of the Forest Service, U.S. Department of Agriculture's Forest Inventory and Analysis (FIA) program is large-area mapping. FIA scientists have tried many methods in the past, including geostatistical methods, linear modeling, nonlinear modeling, and simple choropleth and dot maps. Mapping methods that require individual model-based maps to be...

GlobalSoilMap France: High-resolution spatial modelling the soils of France up to two meter depth.

PubMed

Mulder, V L; Lacoste, M; Richer-de-Forges, A C; Arrouays, D

2016-12-15

This work presents the first GlobalSoilMap (GSM) products for France. We developed an automatic procedure for mapping the primary soil properties (clay, silt, sand, coarse elements, pH, soil organic carbon (SOC), cation exchange capacity (CEC) and soil depth). The procedure employed a data-mining technique and a straightforward method for estimating the 90% confidence intervals (CIs). The most accurate models were obtained for pH, sand and silt. Next, CEC, clay and SOC were found reasonably accurate predicted. Coarse elements and soil depth were the least accurate of all models. Overall, all models were considered robust; important indicators for this were 1) the small difference in model diagnostics between the calibration and cross-validation set, 2) the unbiased mean predictions, 3) the smaller spatial structure of the prediction residuals in comparison to the observations and 4) the similar performance compared to other developed GlobalSoilMap products. Nevertheless, the confidence intervals (CIs) were rather wide for all soil properties. The median predictions became less reliable with increasing depth, as indicated by the increase of CIs with depth. In addition, model accuracy and the corresponding CIs varied depending on the soil variable of interest, soil depth and geographic location. These findings indicated that the CIs are as informative as the model diagnostics. In conclusion, the presented method resulted in reasonably accurate predictions for the majority of the soil properties. End users can employ the products for different purposes, as was demonstrated with some practical examples. The mapping routine is flexible for cloud-computing and provides ample opportunity to be further developed when desired by its users. This allows regional and international GSM partners with fewer resources to develop their own products or, otherwise, to improve the current routine and work together towards a robust high-resolution digital soil map of the world. Copyright © 2016 Elsevier B.V. All rights reserved.

Climate Prediction Center - Monitoring & Data: La Niña Seasonal Maps and

Science.gov Websites

Statistics Skip Navigation Links www.nws.noaa.gov NOAA logo - Click to go to the NOAA home page National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Organization Search Go Search the CPC Go About Us Our Mission Who We Are Contact Us

Predictive mapping of forest composition and structure with direct gradient analysis and nearest neighbor imputation in coastal Oregon, U.S.A.

Treesearch

Janet L. Ohmann; Matthew J. Gregory

2002-01-01

Spatially explicit information on the species composition and structure of forest vegetation is needed at broad spatial scales for natural resource policy analysis and ecological research. We present a method for predictive vegetation mapping that applies direct gradient analysis and nearest-neighbor imputation to ascribe detailed ground attributes of vegetation to...

Neural networks for learning and prediction with applications to remote sensing and speech perception

NASA Astrophysics Data System (ADS)

Gjaja, Marin N.

1997-11-01

Neural networks for supervised and unsupervised learning are developed and applied to problems in remote sensing, continuous map learning, and speech perception. Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART networks synthesize fuzzy logic and neural networks, and supervised ARTMAP networks incorporate ART modules for prediction and classification. New ART and ARTMAP methods resulting from analyses of data structure, parameter specification, and category selection are developed. Architectural modifications providing flexibility for a variety of applications are also introduced and explored. A new methodology for automatic mapping from Landsat Thematic Mapper (TM) and terrain data, based on fuzzy ARTMAP, is developed. System capabilities are tested on a challenging remote sensing problem, prediction of vegetation classes in the Cleveland National Forest from spectral and terrain features. After training at the pixel level, performance is tested at the stand level, using sites not seen during training. Results are compared to those of maximum likelihood classifiers, back propagation neural networks, and K-nearest neighbor algorithms. Best performance is obtained using a hybrid system based on a convex combination of fuzzy ARTMAP and maximum likelihood predictions. This work forms the foundation for additional studies exploring fuzzy ARTMAP's capability to estimate class mixture composition for non-homogeneous sites. Exploratory simulations apply ARTMAP to the problem of learning continuous multidimensional mappings. A novel system architecture retains basic ARTMAP properties of incremental and fast learning in an on-line setting while adding components to solve this class of problems. The perceptual magnet effect is a language-specific phenomenon arising early in infant speech development that is characterized by a warping of speech sound perception. An unsupervised neural network model is proposed that embodies two principal hypotheses supported by experimental data--that sensory experience guides language-specific development of an auditory neural map and that a population vector can predict psychological phenomena based on map cell activities. Model simulations show how a nonuniform distribution of map cell firing preferences can develop from language-specific input and give rise to the magnet effect.

Recombination in diverse maize is stable, predictable, and associated with genetic load.

PubMed

Rodgers-Melnick, Eli; Bradbury, Peter J; Elshire, Robert J; Glaubitz, Jeffrey C; Acharya, Charlotte B; Mitchell, Sharon E; Li, Chunhui; Li, Yongxiang; Buckler, Edward S

2015-03-24

Among the fundamental evolutionary forces, recombination arguably has the largest impact on the practical work of plant breeders. Varying over 1,000-fold across the maize genome, the local meiotic recombination rate limits the resolving power of quantitative trait mapping and the precision of favorable allele introgression. The consequences of low recombination also theoretically extend to the species-wide scale by decreasing the power of selection relative to genetic drift, and thereby hindering the purging of deleterious mutations. In this study, we used genotyping-by-sequencing (GBS) to identify 136,000 recombination breakpoints at high resolution within US and Chinese maize nested association mapping populations. We find that the pattern of cross-overs is highly predictable on the broad scale, following the distribution of gene density and CpG methylation. Several large inversions also suppress recombination in distinct regions of several families. We also identify recombination hotspots ranging in size from 1 kb to 30 kb. We find these hotspots to be historically stable and, compared with similar regions with low recombination, to have strongly differentiated patterns of DNA methylation and GC content. We also provide evidence for the historical action of GC-biased gene conversion in recombination hotspots. Finally, using genomic evolutionary rate profiling (GERP) to identify putative deleterious polymorphisms, we find evidence for reduced genetic load in hotspot regions, a phenomenon that may have considerable practical importance for breeding programs worldwide.