On representation of temporal variability in electricity capacity planning models

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

Merrick, James H.

This study systematically investigates how to represent intra-annual temporal variability in models of optimum electricity capacity investment. Inappropriate aggregation of temporal resolution can introduce substantial error into model outputs and associated economic insight. The mechanisms underlying the introduction of this error are shown. How many representative periods are needed to fully capture the variability is then investigated. For a sample dataset, a scenario-robust aggregation of hourly (8760) resolution is possible in the order of 10 representative hours when electricity demand is the only source of variability. The inclusion of wind and solar supply variability increases the resolution of the robustmore » aggregation to the order of 1000. A similar scale of expansion is shown for representative days and weeks. These concepts can be applied to any such temporal dataset, providing, at the least, a benchmark that any other aggregation method can aim to emulate. Finally, how prior information about peak pricing hours can potentially reduce resolution further is also discussed.« less

Annotating spatio-temporal datasets for meaningful analysis in the Web

NASA Astrophysics Data System (ADS)

Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

2014-05-01

More and more environmental datasets that vary in space and time are available in the Web. This comes along with an advantage of using the data for other purposes than originally foreseen, but also with the danger that users may apply inappropriate analysis procedures due to lack of important assumptions made during the data collection process. In order to guide towards a meaningful (statistical) analysis of spatio-temporal datasets available in the Web, we have developed a Higher-Order-Logic formalism that captures some relevant assumptions in our previous work [1]. It allows to proof on meaningful spatial prediction and aggregation in a semi-automated fashion. In this poster presentation, we will present a concept for annotating spatio-temporal datasets available in the Web with concepts defined in our formalism. Therefore, we have defined a subset of the formalism as a Web Ontology Language (OWL) pattern. It allows capturing the distinction between the different spatio-temporal variable types, i.e. point patterns, fields, lattices and trajectories, that in turn determine whether a particular dataset can be interpolated or aggregated in a meaningful way using a certain procedure. The actual annotations that link spatio-temporal datasets with the concepts in the ontology pattern are provided as Linked Data. In order to allow data producers to add the annotations to their datasets, we have implemented a Web portal that uses a triple store at the backend to store the annotations and to make them available in the Linked Data cloud. Furthermore, we have implemented functions in the statistical environment R to retrieve the RDF annotations and, based on these annotations, to support a stronger typing of spatio-temporal datatypes guiding towards a meaningful analysis in R. [1] Stasch, C., Scheider, S., Pebesma, E., Kuhn, W. (2014): "Meaningful spatial prediction and aggregation", Environmental Modelling & Software, 51, 149-165.

A Re-Evaluation of the Size of the White Shark (Carcharodon carcharias) Population off California, USA

PubMed Central

Burgess, George H.; Bruce, Barry D.; Cailliet, Gregor M.; Goldman, Kenneth J.; Grubbs, R. Dean; Lowe, Christopher G.; MacNeil, M. Aaron; Mollet, Henry F.; Weng, Kevin C.; O'Sullivan, John B.

2014-01-01

White sharks are highly migratory and segregate by sex, age and size. Unlike marine mammals, they neither surface to breathe nor frequent haul-out sites, hindering generation of abundance data required to estimate population size. A recent tag-recapture study used photographic identifications of white sharks at two aggregation sites to estimate abundance in “central California” at 219 mature and sub-adult individuals. They concluded this represented approximately one-half of the total abundance of mature and sub-adult sharks in the entire eastern North Pacific Ocean (ENP). This low estimate generated great concern within the conservation community, prompting petitions for governmental endangered species designations. We critically examine that study and find violations of model assumptions that, when considered in total, lead to population underestimates. We also use a Bayesian mixture model to demonstrate that the inclusion of transient sharks, characteristic of white shark aggregation sites, would substantially increase abundance estimates for the adults and sub-adults in the surveyed sub-population. Using a dataset obtained from the same sampling locations and widely accepted demographic methodology, our analysis indicates a minimum all-life stages population size of >2000 individuals in the California subpopulation is required to account for the number and size range of individual sharks observed at the two sampled sites. Even accounting for methodological and conceptual biases, an extrapolation of these data to estimate the white shark population size throughout the ENP is inappropriate. The true ENP white shark population size is likely several-fold greater as both our study and the original published estimate exclude non-aggregating sharks and those that independently aggregate at other important ENP sites. Accurately estimating the central California and ENP white shark population size requires methodologies that account for biases introduced by sampling a limited number of sites and that account for all life history stages across the species' range of habitats. PMID:24932483

A re-evaluation of the size of the white shark (Carcharodon carcharias) population off California, USA.

PubMed

Burgess, George H; Bruce, Barry D; Cailliet, Gregor M; Goldman, Kenneth J; Grubbs, R Dean; Lowe, Christopher G; MacNeil, M Aaron; Mollet, Henry F; Weng, Kevin C; O'Sullivan, John B

2014-01-01

White sharks are highly migratory and segregate by sex, age and size. Unlike marine mammals, they neither surface to breathe nor frequent haul-out sites, hindering generation of abundance data required to estimate population size. A recent tag-recapture study used photographic identifications of white sharks at two aggregation sites to estimate abundance in "central California" at 219 mature and sub-adult individuals. They concluded this represented approximately one-half of the total abundance of mature and sub-adult sharks in the entire eastern North Pacific Ocean (ENP). This low estimate generated great concern within the conservation community, prompting petitions for governmental endangered species designations. We critically examine that study and find violations of model assumptions that, when considered in total, lead to population underestimates. We also use a Bayesian mixture model to demonstrate that the inclusion of transient sharks, characteristic of white shark aggregation sites, would substantially increase abundance estimates for the adults and sub-adults in the surveyed sub-population. Using a dataset obtained from the same sampling locations and widely accepted demographic methodology, our analysis indicates a minimum all-life stages population size of >2000 individuals in the California subpopulation is required to account for the number and size range of individual sharks observed at the two sampled sites. Even accounting for methodological and conceptual biases, an extrapolation of these data to estimate the white shark population size throughout the ENP is inappropriate. The true ENP white shark population size is likely several-fold greater as both our study and the original published estimate exclude non-aggregating sharks and those that independently aggregate at other important ENP sites. Accurately estimating the central California and ENP white shark population size requires methodologies that account for biases introduced by sampling a limited number of sites and that account for all life history stages across the species' range of habitats.

The asymmetric evolution of the Colombian Eastern Cordillera. Tectonic inheritance or climatic forcing? New evidence from thermochronology and sedimentology

NASA Astrophysics Data System (ADS)

Ramirez-Arias, Juan Carlos; Mora, Andrés; Rubiano, Jorge; Duddy, Ian; Parra, Mauricio; Moreno, Nestor; Stockli, Daniel; Casallas, Wilson

2012-11-01

New thermochronological data, facies, paleocurrents and provenance allow us to refine the chronology of deformation in the central segment of the Colombian Eastern Cordillera. Based on a new extensive AFT dataset, we document the spatial evolution of active deformation, from the axial zone of the Eastern Cordillera at about 50 Ma in to active growth of the frontal thin skinned structures in Late Miocene time. Paleocurrents allow us to push backwards into the Middle to Early Late-Miocene the emergence of the easternmost frontal thrust; whereas careful assessment of exposure gates tied to AFT data enable to refine the unroofing history for Eocene to Miocene times. Based on that, we produced a kinematically restored cross section with higher resolution than previous assessments. Using these datasets, we compare the evolution of the central segment of the Eastern Cordillera in this region with the evolution of adjacent areas in the context of climatic forcing of orogenic evolution. We find that in this region and, in the Eastern Cordillera in general, tectonic inheritance and transpression exert an initial dominant control on the initial orogen asymmetry, which is later enhanced due to an orographically-focused erosion. We therefore suggest that it is not climate alone the factor controlling orogenic asymmetry in the Eastern Cordillera of Colombia.

Nanocubes for real-time exploration of spatiotemporal datasets.

PubMed

Lins, Lauro; Klosowski, James T; Scheidegger, Carlos

2013-12-01

Consider real-time exploration of large multidimensional spatiotemporal datasets with billions of entries, each defined by a location, a time, and other attributes. Are certain attributes correlated spatially or temporally? Are there trends or outliers in the data? Answering these questions requires aggregation over arbitrary regions of the domain and attributes of the data. Many relational databases implement the well-known data cube aggregation operation, which in a sense precomputes every possible aggregate query over the database. Data cubes are sometimes assumed to take a prohibitively large amount of space, and to consequently require disk storage. In contrast, we show how to construct a data cube that fits in a modern laptop's main memory, even for billions of entries; we call this data structure a nanocube. We present algorithms to compute and query a nanocube, and show how it can be used to generate well-known visual encodings such as heatmaps, histograms, and parallel coordinate plots. When compared to exact visualizations created by scanning an entire dataset, nanocube plots have bounded screen error across a variety of scales, thanks to a hierarchical structure in space and time. We demonstrate the effectiveness of our technique on a variety of real-world datasets, and present memory, timing, and network bandwidth measurements. We find that the timings for the queries in our examples are dominated by network and user-interaction latencies.

Areal Feature Matching Based on Similarity Using Critic Method

NASA Astrophysics Data System (ADS)

Kim, J.; Yu, K.

2015-10-01

In this paper, we propose an areal feature matching method that can be applied for many-to-many matching, which involves matching a simple entity with an aggregate of several polygons or two aggregates of several polygons with fewer user intervention. To this end, an affine transformation is applied to two datasets by using polygon pairs for which the building name is the same. Then, two datasets are overlaid with intersected polygon pairs that are selected as candidate matching pairs. If many polygons intersect at this time, we calculate the inclusion function between such polygons. When the value is more than 0.4, many of the polygons are aggregated as single polygons by using a convex hull. Finally, the shape similarity is calculated between the candidate pairs according to the linear sum of the weights computed in CRITIC method and the position similarity, shape ratio similarity, and overlap similarity. The candidate pairs for which the value of the shape similarity is more than 0.7 are determined as matching pairs. We applied the method to two geospatial datasets: the digital topographic map and the KAIS map in South Korea. As a result, the visual evaluation showed two polygons that had been well detected by using the proposed method. The statistical evaluation indicates that the proposed method is accurate when using our test dataset with a high F-measure of 0.91.

A modern plant-climate research dataset for modelling eastern North American plant taxa.

NASA Astrophysics Data System (ADS)

Gonzales, L. M.; Grimm, E. C.; Williams, J. W.; Nordheim, E. V.

2008-12-01

Continental-scale modern pollen-climate data repositories are a primary data source for paleoclimate reconstructions. However, these repositories can contain artifacts, such as records from different depositional environment and replicate records, that can influence the observed pollen-climate relationships as well as the paleoclimate reconstructions derived from these relationships. In this paper, we address the issues related to these artifacts as we define the methods used to create a research dataset from the North American Modern Pollen Database (Whitmore et al., 2005). Additionally, we define the methods used to select the environmental variables that are best for modeling regional pollen-climate relationships from the research dataset. Because the depositional environment determines the relative strengths of the local and regional pollen signals, combining data from different depositional environments results in pollen abundances that can be influenced by the local pollen signal. Replicate records in pollen-climate datasets can skew pollen-climate relationships by causing an over- or under- representation of pollen abundances in climate space. When these two artifacts are combined, the errors introduced into pollen-climate relationship modeling are compounded. The research dataset we present consists of 2,613 records in eastern North America, of which 70.9% are lacustrine sites. We demonstrate that this new research database improves upon the modeling of regional pollen-climate relationships for eastern North American taxa. The research dataset encompasses the majority of the temperature and mean summer precipitation ranges of the NAMPD's climatic range and 40% of its mean winter precipitation range. NAMPD sites with higher winter precipitation are located along the northwestern coast of North America where a rainshadow effect produces abundant winter precipitation. We present our analysis of the research dataset for use in paleoclimate reconstructions, and recommend that mean winter and summer temperature and precipitation variables be used for pollen-climate relationship modeling.

Interoperable Solar Data and Metadata via LISIRD 3

NASA Astrophysics Data System (ADS)

Wilson, A.; Lindholm, D. M.; Pankratz, C. K.; Snow, M. A.; Woods, T. N.

2015-12-01

LISIRD 3 is a major upgrade of the LASP Interactive Solar Irradiance Data Center (LISIRD), which serves several dozen space based solar irradiance and related data products to the public. Through interactive plots, LISIRD 3 provides data browsing supported by data subsetting and aggregation. Incorporating a semantically enabled metadata repository, LISIRD 3 users see current, vetted, consistent information about the datasets offered. Users can now also search for datasets based on metadata fields such as dataset type and/or spectral or temporal range. This semantic database enables metadata browsing, so users can discover the relationships between datasets, instruments, spacecraft, mission and PI. The database also enables creation and publication of metadata records in a variety of formats, such as SPASE or ISO, making these datasets more discoverable. The database also enables the possibility of a public SPARQL endpoint, making the metadata browsable in an automated fashion. LISIRD 3's data access middleware, LaTiS, provides dynamic, on demand reformatting of data and timestamps, subsetting and aggregation, and other server side functionality via a RESTful OPeNDAP compliant API, enabling interoperability between LASP datasets and many common tools. LISIRD 3's templated front end design, coupled with the uniform data interface offered by LaTiS, allows easy integration of new datasets. Consequently the number and variety of datasets offered by LISIRD has grown to encompass several dozen, with many more to come. This poster will discuss design and implementation of LISIRD 3, including tools used, capabilities enabled, and issues encountered.

Glycemic Control Indices and Their Aggregation in the Prediction of Nocturnal Hypoglycemia From Intermittent Blood Glucose Measurements.

PubMed

Sampath, Sivananthan; Tkachenko, Pavlo; Renard, Eric; Pereverzev, Sergei V

2016-11-01

Despite the risk associated with nocturnal hypoglycemia (NH) there are only a few methods aiming at the prediction of such events based on intermittent blood glucose monitoring data. One of the first methods that potentially can be used for NH prediction is based on the low blood glucose index (LBGI) and suggested, for example, in Accu-Chek® Connect as a hypoglycemia risk indicator. On the other hand, nowadays there are other glucose control indices (GCI), which could be used for NH prediction in the same spirit as LBGI. In the present study we propose a general approach of combining NH predictors constructed from different GCI. The approach is based on a recently developed strategy for aggregating ranking algorithms in machine learning. NH predictors have been calibrated and tested on data extracted from clinical trials, performed in EU FP7-funded project DIAdvisor. Then, to show a portability of the method we have tested it on another dataset that was received from EU Horizon 2020-funded project AMMODIT. We exemplify the proposed approach by aggregating NH predictors that have been constructed based on 4 GCI associated with hypoglycemia. Even though these predictors have been preliminary optimized to exhibit better performance on the considered dataset, our aggregation approach allows a further performance improvement. On the dataset, where a portability of the proposed approach has been demonstrated, the aggregating predictor has exhibited the following performance: sensitivity 77%, specificity 83.4%, positive predictive value 80.2%, negative predictive value 80.6%, which is higher than conventionally considered as acceptable. The proposed approach shows potential to be used in telemedicine systems for NH prediction. © 2016 Diabetes Technology Society.

End-member modelling as a tool for climate reconstruction-An Eastern Mediterranean case study.

PubMed

Beuscher, Sarah; Krüger, Stefan; Ehrmann, Werner; Schmiedl, Gerhard; Milker, Yvonne; Arz, Helge; Schulz, Hartmut

2017-01-01

The Eastern Mediterranean Sea is a sink for terrigenous sediments from North Africa, Europe and Asia Minor. Its sediments therefore provide valuable information on the climate dynamics in the source areas and the associated transport processes. We present a high-resolution dataset of sediment core M40/4_SL71, which was collected SW of Crete and spans the last ca. 180 kyr. We analysed the clay mineral composition, the grain size distribution within the silt fraction, and the abundance of major and trace elements. We tested the potential of end-member modelling on these sedimentological datasets as a tool for reconstructing the climate variability in the source regions and the associated detrital input. For each dataset, we modelled three end members. All end members were assigned to a specific provenance and sedimentary process. In total, three end members were related to the Saharan dust input, and five were related to the fluvial sediment input. One end member was strongly associated with the sapropel layers. The Saharan dust end members of the grain size and clay mineral datasets generally suggest enhanced dust export into the Eastern Mediterranean Sea during the dry phases with short-term increases during Heinrich events. During the African Humid Periods, dust export was reduced but may not have completely ceased. The loading patterns of two fluvial end members show a strong relationship with the Northern Hemisphere insolation, and all fluvial end members document enhanced input during the African Humid Periods. The sapropel end member most likely reflects the fixation of redox-sensitive elements within the anoxic sapropel layers. Our results exemplify that end-member modelling is a valuable tool for interpreting extensive and multidisciplinary datasets.

End-member modelling as a tool for climate reconstruction—An Eastern Mediterranean case study

PubMed Central

Krüger, Stefan; Ehrmann, Werner; Schmiedl, Gerhard; Milker, Yvonne; Arz, Helge; Schulz, Hartmut

2017-01-01

The Eastern Mediterranean Sea is a sink for terrigenous sediments from North Africa, Europe and Asia Minor. Its sediments therefore provide valuable information on the climate dynamics in the source areas and the associated transport processes. We present a high-resolution dataset of sediment core M40/4_SL71, which was collected SW of Crete and spans the last ca. 180 kyr. We analysed the clay mineral composition, the grain size distribution within the silt fraction, and the abundance of major and trace elements. We tested the potential of end-member modelling on these sedimentological datasets as a tool for reconstructing the climate variability in the source regions and the associated detrital input. For each dataset, we modelled three end members. All end members were assigned to a specific provenance and sedimentary process. In total, three end members were related to the Saharan dust input, and five were related to the fluvial sediment input. One end member was strongly associated with the sapropel layers. The Saharan dust end members of the grain size and clay mineral datasets generally suggest enhanced dust export into the Eastern Mediterranean Sea during the dry phases with short-term increases during Heinrich events. During the African Humid Periods, dust export was reduced but may not have completely ceased. The loading patterns of two fluvial end members show a strong relationship with the Northern Hemisphere insolation, and all fluvial end members document enhanced input during the African Humid Periods. The sapropel end member most likely reflects the fixation of redox-sensitive elements within the anoxic sapropel layers. Our results exemplify that end-member modelling is a valuable tool for interpreting extensive and multidisciplinary datasets. PMID:28934332

Trends and characteristics of animal-vehicle collisions in the United States.

PubMed

Sullivan, John M

2011-02-01

Since 1990, fatal animal-vehicle collisions (AVCs) in the United States have more than doubled. This paper examines annual AVC trends in the United States over a 19-year period, seasonal and diurnal patterns of AVC risk, the geographic distribution of crash risk by state, and the association between posted speed limit and AVC crash risk in darkness. AVCs were compiled from the Fatality Analysis Reporting System (FARS) and the General Estimates System (GES) for the years 1990-2008 to examine annual crash trends for fatal and nonfatal crashes. Seasonal trends for fatal AVCs were examined with the aggregated FARS dataset; seasonal trends for fatal and nonfatal AVCs were also examined by aggregating four years of Michigan crash data. State-by-state distributions of fatal AVCs were also described with the aggregated FARS dataset. Finally, the relationship between posted speed limit and the odds that a fatal or nonfatal AVC occurred in darkness were examined with logistic regressions using the aggregated FARS and Michigan datasets. Between 1990 and 2008, fatal AVCs increased by 104% and by 1.3 crashes per trillion vehicle miles travelled per year. Although not all AVCs involve deer, daily and seasonal AVC crash trends follow the general activity pattern of deer populations, consistent with prior reports. The odds that a fatal AVC occurred in darkness were also found to increase by 2.3% for each mile-per-hour increase in speed; a similar, albeit smaller, effect was also observed in the aggregated Michigan dataset, among nonfatal crashes. AVCs represent a small but increasing share of crashes in the United States. Seasonal and daily variation in the pattern of AVCs seem to follow variation in deer exposure and ambient light level. Finally, the relative risk that a fatal and nonfatal AVC occurred in darkness is influenced by posted speed limit, suggesting that a driver's limited forward vision at night plays a role in AVCs, as it does in pedestrian collisions. The association between speed limit and crash risk in darkness suggests that AVC risk might be reduced with countermeasures that improve a driver's forward view of the road. Copyright © 2010 Elsevier Ltd. All rights reserved.

Aggregating todays data for tomorrows science: a geological use case

NASA Astrophysics Data System (ADS)

Glaves, H.; Kingdon, A.; Nayembil, M.; Baker, G.

2016-12-01

Geoscience data is made up of diverse and complex smaller datasets that, when aggregated together, build towards what is recognised as `big data'. The British Geological Survey (BGS), which acts as a repository for all subsurface data from the United Kingdom, has been collating these disparate small datasets that have been accumulated from the activities of a large number of geoscientists over many years. Recently this picture has been further complicated by the addition of new data sources such as near real-time sensor data, and industry or community data that is increasingly delivered via automatic donations. Many of these datasets have been aggregated in relational databases to form larger ones that are used to address a variety of issues ranging from development of national infrastructure to disaster response. These complex domain-specific SQL databases deliver effective data management using normalised subject-based database designs in a secure environment. However, the isolated subject-oriented design of these systems inhibits efficient cross-domain querying of the datasets. Additionally, the tools provided often do not enable effective data discovery as they have problems resolving the complex underlying normalised structures. Recent requirements to understand sub-surface geology in three dimensions have led BGS to develop new data systems. One such solution is PropBase which delivers a generic denormalised data structure within an RDBMS to store geological property data. Propbase facilitates rapid and standardised data discovery and access, incorporating 2D and 3D physical and chemical property data, including associated metadata. It also provides a dedicated web interface to deliver complex multiple data sets from a single database in standardised common output formats (e.g. CSV, GIS shape files) without the need for complex data conditioning. PropBase facilitates new scientific research, previously considered impractical, by enabling property data searches across multiple databases. Using the Propbase exemplar this presentation will seek to illustrate how BGS has developed systems for aggregating `small datasets' to create the `big data' necessary for the data analytics, mining, processing and visualisation needed for future geoscientific research.

Web-based access, aggregation, and visualization of future climate projections with emphasis on agricultural assessments

NASA Astrophysics Data System (ADS)

Villoria, Nelson B.; Elliott, Joshua; Müller, Christoph; Shin, Jaewoo; Zhao, Lan; Song, Carol

2018-01-01

Access to climate and spatial datasets by non-specialists is restricted by technical barriers involving hardware, software and data formats. We discuss an open-source online tool that facilitates downloading the climate data from the global circulation models used by the Inter-Sectoral Impacts Model Intercomparison Project. The tool also offers temporal and spatial aggregation capabilities for incorporating future climate scenarios in applications where spatial aggregation is important. We hope that streamlined access to these data facilitates analysis of climate related issues while considering the uncertainties derived from future climate projections and temporal aggregation choices.

Toward global crop type mapping using a hybrid machine learning approach and multi-sensor imagery

NASA Astrophysics Data System (ADS)

Wang, S.; Le Bras, S.; Azzari, G.; Lobell, D. B.

2017-12-01

Current global scale datasets on agricultural land use do not have sufficient spatial or temporal resolution to meet the needs of many applications. The recent rapid increase in public availability of fine- to moderate-resolution satellite imagery from Landsat OLI and Copernicus Sentinel-2 provides a unique opportunity to improve agricultural land use datasets. This project leverages these new satellite data streams, existing census data, and a novel training approach to develop global, annual maps that indicate the presence of (i) cropland and (ii) specific crops at a 20m resolution. Our machine learning methodology consists of two steps. The first is a supervised classifier trained with explicitly labelled data to distinguish between crop and non-crop pixels, creating a binary mask. For ground truth, we use labels collected by previous mapping efforts (e.g. IIASA's crowdsourced data (Fritz et al. 2015) and AFSIS's geosurvey data) in combination with new data collected manually. The crop pixels output by the binary mask are input to the second step: a semi-supervised clustering algorithm to resolve different crop types and generate a crop type map. We do not use field-level information on crop type to train the algorithm, making this approach scalable spatially and temporally. We instead incorporate size constraints on clusters based on aggregated agricultural land use statistics and other, more generalizable domain knowledge. We employ field-level data from the U.S., Southern Europe, and Eastern Africa to validate crop-to-cluster assignments.

Impacts of long-term no-tillage and conventional tillage management of spring wheat-lentil cropping systems in dryland Eastern Montana, USA, on fungi associated to soil aggregation

USDA-ARS?s Scientific Manuscript database

Lentil (Lens culinaris Medikus CV. Indianhead) used to replace fallow in spring-wheat (Triticum aestivum) rotation in the semi-arid Eastern Montana USA, may improve soil quality. We evaluate the 14 years influence of continuous wheat under no-tillage (WNT), fallow-wheat under conventional tillage (F...

Tillage practices in the conterminous United States, 1989-2004-Datasets Aggregated by Watershed

USGS Publications Warehouse

Baker, Nancy T.

2011-01-01

This report documents the methods used to aggregate county-level tillage practices to the 8-digit hydrologic unit (HU) watershed. The original county-level data were collected by the Conservation Technology Information Center (CTIC). The CTIC collects tillage data by conducting surveys about tillage systems for all counties in the United States. Tillage systems include three types of conservation tillage (no-till, ridge-till, and mulch-till), reduced tillage, and intensive tillage. Total planted acreage for each tillage practice for each crop grown is reported to the CTIC. The dataset includes total planted acreage by tillage type for selected crops (corn, cotton, grain sorghum, soybeans, fallow, forage, newly established permanent pasture, spring and fall seeded small grains, and 'other' crops) for 1989-2004. Two tabular datasets, based on the 1992 enhanced and 2001 National Land Cover Data (NLCD), are provided as part of this report and include the land-cover area-weighted interpolation and aggregation of acreage for each tillage practice in each 8-digit HU watershed in the conterminous United States for each crop. Watershed aggregations were done by overlying the 8-digit HU polygons with a raster of county boundaries and a raster of either the enhanced 1992 or the 2001 NLCD for cultivated land to derive a county/land-cover area weighting factor. The weighting factor then was applied to the county-level tillage data for the counties within each 8-digit HU and summed to yield the total acreage of each tillage type within each 8-digit HU watershed.

An indicator of tree migration in forests of the eastern United States

Treesearch

C.W. Woodall; C.M. Oswalt; J.A. Westfall; C.H. Perry; M.D. Nelson; A.O. Finley

2009-01-01

Changes in tree species distributions are a potential impact of climate change on forest ecosystems. The examination of tree species shifts in forests of the eastern United States largely has been limited to simulation activities due to a lack of consistent, long-term forest inventory datasets. The goal of this study was to compare current geographic distributions of...

Soviet and East European energy crisis: its dimensions and implications for East--West trade

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

Hewett, E.A.

The world energy crisis has placed tremendous pressure on Soviet planners to divert oil destined for Eastern Europe to hard currency markets (or in some cases to charge Eastern Europe hard currency for the oil); and this pressure would have come irrespective of developments in Soviet energy-production costs. The Soviet-East European energy crisis is also political in nature because the increase balance-of-payments problems for Eastern Europe, which will cause austerity measures in the East European countries, measures which the population seems likely to resist. Thus, the Soviet-East European energy crisis is both related and unrelated to the energy crisis wemore » face in the United States. The purpose of this paper is to project to 1980 the aggregate energy balance in Eastern Europe and the USSR, and to explore the implications of that projection for East--West trade. The year 1980 the aggregate energy balance in Eastern Europe and the USSR, and to explore the implications of that projection for East--West trade. The year 1980 is not very far away; it would be prefereble if the projection could go farther. But the technique used here is simple extrapolation with some educated guesses concerning growth rates. Such techniques tend to work quite well for the near future; over the longer term the only hope is to actually model the processes involved and their interconnections. 18 references and footnotes.« less

Open University Learning Analytics dataset.

PubMed

Kuzilek, Jakub; Hlosta, Martin; Zdrahal, Zdenek

2017-11-28

Learning Analytics focuses on the collection and analysis of learners' data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students' interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license.

Open University Learning Analytics dataset

PubMed Central

Kuzilek, Jakub; Hlosta, Martin; Zdrahal, Zdenek

2017-01-01

Learning Analytics focuses on the collection and analysis of learners’ data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students’ interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license. PMID:29182599

A modern pollen-climate dataset from the Darjeeling area, eastern Himalaya: Assessing its potential for past climate reconstruction

NASA Astrophysics Data System (ADS)

Ghosh, Ruby; Bruch, Angela A.; Portmann, Felix; Bera, Subir; Paruya, Dipak Kumar; Morthekai, P.; Ali, Sheikh Nawaz

2017-10-01

Relying on the ability of pollen assemblages to differentiate among elevationally stratified vegetation zones, we assess the potential of a modern pollen-climate dataset from the Darjeeling area, eastern Himalaya, in past climate reconstructions. The dataset includes 73 surface samples from 25 sites collected from a c. 130-3600 m a.s.l. elevation gradient along a horizontal distance of c. 150 km and 124 terrestrial pollen taxa, which are analysed with respect to various climatic and environmental variables such as mean annual temperature (MAT), mean annual precipitation (MAP), mean temperature of coldest quarter (MTCQ), mean temperature of warmest quarter (MTWQ), mean precipitation of driest quarter (MPDQ), mean precipitation of wettest quarter (MPWQ), AET (actual evapotranspiration) and MI (moisture index). To check the reliability of the modern pollen-climate relationships different ordination methods are employed and subsequently tested with Huisman-Olff-Fresco (HOF) models. A series of pollen-climate parameter transfer functions using weighted-averaging regression and calibration partial least squares (WA-PLS) models are developed to reconstruct past climate changes from modern pollen data, and have been cross-validated. Results indicate that three of the environmental variables i.e., MTCQ, MPDQ and MI have strong potential for past climate reconstruction based on the available surface pollen dataset. The potential of the present modern pollen-climate relationship for regional quantitative paleoclimate reconstruction is further tested on a Late Quaternary fossil pollen profile from the Darjeeling foothill region with previously reconstructed and quantified climate. The good agreement with existing data allows for new insights in the hydroclimatic conditions during the Last glacial maxima (LGM) with (winter) temperature being the dominant controlling factor for glacial changes during the LGM in the eastern Himalaya.

The added value of convection permitting simulations of extreme precipitation events over the eastern Mediterranean

NASA Astrophysics Data System (ADS)

Zittis, G.; Bruggeman, A.; Camera, C.; Hadjinicolaou, P.; Lelieveld, J.

2017-07-01

Climate change is expected to substantially influence precipitation amounts and distribution. To improve simulations of extreme rainfall events, we analyzed the performance of different convection and microphysics parameterizations of the WRF (Weather Research and Forecasting) model at very high horizontal resolutions (12, 4 and 1 km). Our study focused on the eastern Mediterranean climate change hot-spot. Five extreme rainfall events over Cyprus were identified from observations and were dynamically downscaled from the ERA-Interim (EI) dataset with WRF. We applied an objective ranking scheme, using a 1-km gridded observational dataset over Cyprus and six different performance metrics, to investigate the skill of the WRF configurations. We evaluated the rainfall timing and amounts for the different resolutions, and discussed the observational uncertainty over the particular extreme events by comparing three gridded precipitation datasets (E-OBS, APHRODITE and CHIRPS). Simulations with WRF capture rainfall over the eastern Mediterranean reasonably well for three of the five selected extreme events. For these three cases, the WRF simulations improved the ERA-Interim data, which strongly underestimate the rainfall extremes over Cyprus. The best model performance is obtained for the January 1989 event, simulated with an average bias of 4% and a modified Nash-Sutcliff of 0.72 for the 5-member ensemble of the 1-km simulations. We found overall added value for the convection-permitting simulations, especially over regions of high-elevation. Interestingly, for some cases the intermediate 4-km nest was found to outperform the 1-km simulations for low-elevation coastal parts of Cyprus. Finally, we identified significant and inconsistent discrepancies between the three, state of the art, gridded precipitation datasets for the tested events, highlighting the observational uncertainty in the region.

Natural aggregates of the conterminous United States

USGS Publications Warehouse

Langer, William H.

1988-01-01

Crushed stone and sand and gravel are the two main sources of natural aggregates. These materials are commonly used construction materials and frequently can be interchanged with one another. They are widely used throughout the United States, with every State except two producing crushed stone. Together they amount to about half the mining volume in the United States. Approximately 96 percent of sand and gravel and 77 percent of the crushed stone produced in the United States are used in the construction industry. Natural aggregates are widely distributed throughout the United States in a variety of geologic environments. Sand and gravel deposits commonly are the results of the weathering of bedrock and subsequent transportation and deposition of the material by water or ice (glaciers). As such, they commonly occur as river or stream deposits or in glaciated areas as glaciofluvial and other deposits. Crushed stone aggregates are derived from a wide variety of parent bedrock materials. Limestone and other carbonates account for approximately three quarters of the rocks used for crushed stone, with granite and other igneous rocks making up the bulk of the remainder. Limestone deposits are widespread throughout the Central and Eastern United States and are scattered in the West. Granites are widely distributed in the Eastern and Western United States, with few exposures in the Midwest. Igneous rocks (excluding granites) are largely concentrated in the Western United States and in a few isolated localities in the East. Even though natural aggregates are widely distributed throughout the United States, they are not universally available for consumptive use. Some areas are devoid of sand and gravel, and potential sources of crushed stone may be covered with sufficient unconsolidated material to make surface mining impractical. In some areas many aggregates do not meet the physical property requirements for certain uses, or they may contain mineral constituents that react adversely when used as concrete aggregate. In areas where suitable natural aggregate is not available or accessible, it may become necessary to improve the quality of existing aggregate, to import aggregate from outside the area, or to substitute artificial aggregate for natural aggregate. In most cases, all of these alternatives add substantially to the cost of the final product. Even though an area may be blessed with an abundance of aggregate suitable for the intended purpose, existing land uses, zoning, or regulations may preclude commercial exploitation of the aggregate. This report also discusses the aggregate industry in general terms, including exploration, mining, and processing, as well as aggregate production rates. Proper long-range planning based on an understanding of the aggregate industry can help assure adequate supplies of aggregate.

Grid Connected Functionality

DOE Data Explorer

Baker, Kyri; Jin, Xin; Vaidynathan, Deepthi; Jones, Wesley; Christensen, Dane; Sparn, Bethany; Woods, Jason; Sorensen, Harry; Lunacek, Monte

2016-08-04

Dataset demonstrating the potential benefits that residential buildings can provide for frequency regulation services in the electric power grid. In a hardware-in-the-loop (HIL) implementation, simulated homes along with a physical laboratory home are coordinated via a grid aggregator, and it is shown that their aggregate response has the potential to follow the regulation signal on a timescale of seconds. Connected (communication-enabled), devices in the National Renewable Energy Laboratory's (NREL's) Energy Systems Integration Facility (ESIF) received demand response (DR) requests from a grid aggregator, and the devices responded accordingly to meet the signal while satisfying user comfort bounds and physical hardware limitations.

Application of an assessment protocol to extensive species and total basal area per acre datasets for the eastern coterminous United States

Treesearch

Rachel Riemann; Ty Wilson; Andrew Lister

2012-01-01

We recently developed an assessment protocol that provides information on the magnitude, location, frequency and type of error in geospatial datasets of continuous variables (Riemann et al. 2010). The protocol consists of a suite of assessment metrics which include an examination of data distributions and areas estimates, at several scales, examining each in the form...

Corrigendum to "Three climatic cycles recorded in a loess-palaeosol sequence at Semlac (Romania)-Implications for dust accumulation in south-eastern Europe" [Quat. Sci. Rev. 154C (2016) 130-142

NASA Astrophysics Data System (ADS)

Zeeden, C.; Kels, H.; Hambach, U.; Schulte, P.; Protze, J.; Eckmeier, E.; Marković, S. B.; Klasen, N.; Lehmkuhl, F.

2018-05-01

In the article 'Three climatic cycles recorded in a loess-palaeosol sequence at Semlac (Romania)-Implications for dust accumulation in south-eastern Europe' (Zeeden et al., 2016) we employed rock magnetic and grain size proxy data in combination with OSL- and correlative age models. The data and dating is combined to discuss glacial-interglacial paleoclimate variability in an Eurasian context. This dataset was also interpreted regarding the dust source in the eastern Carpathian (Middle Danube) Basin.

Inflammatory bowel disease in children of middle eastern descent.

PubMed

Naidoo, Christina Mai Ying; Leach, Steven T; Day, Andrew S; Lemberg, Daniel A

2014-01-01

Increasing rates of inflammatory bowel disease (IBD) are now seen in populations where it was once uncommon. The pattern of IBD in children of Middle Eastern descent in Australia has never been reported. This study aimed to investigate the burden of IBD in children of Middle Eastern descent at the Sydney Children's Hospital, Randwick (SCHR). The SCHR IBD database was used to identify patients of self-reported Middle Eastern ethnicity diagnosed between 1987 and 2011. Demographic, diagnosis, and management data was collected for all Middle Eastern children and an age and gender matched non-Middle Eastern IBD control group. Twenty-four patients of Middle Eastern descent were identified. Middle Eastern Crohn's disease patients had higher disease activity at diagnosis, higher use of thiopurines, and less restricted colonic disease than controls. Although there were limitations with this dataset, we estimated a higher prevalence of IBD in Middle Eastern children and they had a different disease phenotype and behavior compared to the control group, with less disease restricted to the colon and likely a more active disease course.

Inflammatory Bowel Disease in Children of Middle Eastern Descent

PubMed Central

Naidoo, Christina Mai Ying; Leach, Steven T.; Day, Andrew S.; Lemberg, Daniel A.

2014-01-01

Increasing rates of inflammatory bowel disease (IBD) are now seen in populations where it was once uncommon. The pattern of IBD in children of Middle Eastern descent in Australia has never been reported. This study aimed to investigate the burden of IBD in children of Middle Eastern descent at the Sydney Children's Hospital, Randwick (SCHR). The SCHR IBD database was used to identify patients of self-reported Middle Eastern ethnicity diagnosed between 1987 and 2011. Demographic, diagnosis, and management data was collected for all Middle Eastern children and an age and gender matched non-Middle Eastern IBD control group. Twenty-four patients of Middle Eastern descent were identified. Middle Eastern Crohn's disease patients had higher disease activity at diagnosis, higher use of thiopurines, and less restricted colonic disease than controls. Although there were limitations with this dataset, we estimated a higher prevalence of IBD in Middle Eastern children and they had a different disease phenotype and behavior compared to the control group, with less disease restricted to the colon and likely a more active disease course. PMID:24987422

Seasonal Variations of Oceanographic Variables and Eastern Little Tuna (Euthynnus affinis) Catches in the North Indramayu Waters Java Sea

NASA Astrophysics Data System (ADS)

Syamsuddin, Mega; Sunarto; Yuliadi, Lintang

2018-02-01

The remotely derived oceanographic variables included sea surface temperature (SST), chlorophyll-a (Chl-a) and Eastern Little Tuna (Euthynnus affinis) catches are used as a combined dataset to understand the seasonal variation of oceanographic variables and Eastern Little Tuna catches in the north Indramayu waters, Java Sea. The fish catches and remotely sensed data were analysed for the 5 years datasets from 2010-2014. This study has shown the effect of monsoon inducing oceanographic condition in the study area. Seasonal change features were dominant for all the selected oceanographic parameters of SST and Chl-a, and also Eastern Little Tuna catches, respectively. The Eastern Little Tuna catch rates have the peak season from September to December (700 to 1000) ton that corresponded with the value of SST ranging from 29 °C to 30 °C following the decreasing of Chl-a concentrations in September to November (0.4 to 0.5) mg m-3. The monsoonal system plays a great role in determining the variability of oceanographic conditions and catch in the north Indramayu waters, Java Sea. The catches seemed higher during the northwest monsoon than in the southeast monsoon for all year observations except in 2010. The wavelet spectrum analysis results confirmed that Eastern Little Tuna catches had seasonal and inter-annual variations during 2012-2014. The SST had seasonal variations during 2010-2014. The Chl-a also showed seasonal variations during 2010-2011 and interannual variations during 2011-2014. Our results would benefit the fishermen and policy makers to have better management for sustainable catch in the study area.

Floating Ice-Algal Aggregates below Melting Arctic Sea Ice

PubMed Central

Assmy, Philipp; Ehn, Jens K.; Fernández-Méndez, Mar; Hop, Haakon; Katlein, Christian; Sundfjord, Arild; Bluhm, Katrin; Daase, Malin; Engel, Anja; Fransson, Agneta; Granskog, Mats A.; Hudson, Stephen R.; Kristiansen, Svein; Nicolaus, Marcel; Peeken, Ilka; Renner, Angelika H. H.; Spreen, Gunnar; Tatarek, Agnieszka; Wiktor, Jozef

2013-01-01

During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting ice floes of first-year pack ice. The macroscopic (1-15 cm in diameter) aggregates had a mucous consistency and were dominated by typical ice-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layers. We were able, for the first time, to obtain quantitative abundance and biomass estimates of these aggregates. Although their biomass and production on a square metre basis was small compared to ice-algal blooms, the floating ice-algal aggregates supported high levels of biological activity on the scale of the individual aggregate. In addition they constituted a food source for the ice-associated fauna as revealed by pigments indicative of zooplankton grazing, high abundance of naked ciliates, and ice amphipods associated with them. During the Arctic melt season, these floating aggregates likely play an important ecological role in an otherwise impoverished near-surface sea ice environment. Our findings provide important observations and measurements of a unique aggregate-based habitat during the 2012 record sea ice minimum year. PMID:24204642

Floating ice-algal aggregates below melting arctic sea ice.

PubMed

Assmy, Philipp; Ehn, Jens K; Fernández-Méndez, Mar; Hop, Haakon; Katlein, Christian; Sundfjord, Arild; Bluhm, Katrin; Daase, Malin; Engel, Anja; Fransson, Agneta; Granskog, Mats A; Hudson, Stephen R; Kristiansen, Svein; Nicolaus, Marcel; Peeken, Ilka; Renner, Angelika H H; Spreen, Gunnar; Tatarek, Agnieszka; Wiktor, Jozef

2013-01-01

During two consecutive cruises to the Eastern Central Arctic in late summer 2012, we observed floating algal aggregates in the melt-water layer below and between melting ice floes of first-year pack ice. The macroscopic (1-15 cm in diameter) aggregates had a mucous consistency and were dominated by typical ice-associated pennate diatoms embedded within the mucous matrix. Aggregates maintained buoyancy and accumulated just above a strong pycnocline that separated meltwater and seawater layers. We were able, for the first time, to obtain quantitative abundance and biomass estimates of these aggregates. Although their biomass and production on a square metre basis was small compared to ice-algal blooms, the floating ice-algal aggregates supported high levels of biological activity on the scale of the individual aggregate. In addition they constituted a food source for the ice-associated fauna as revealed by pigments indicative of zooplankton grazing, high abundance of naked ciliates, and ice amphipods associated with them. During the Arctic melt season, these floating aggregates likely play an important ecological role in an otherwise impoverished near-surface sea ice environment. Our findings provide important observations and measurements of a unique aggregate-based habitat during the 2012 record sea ice minimum year.

2001 Bhuj, India, earthquake engineering seismoscope recordings and Eastern North America ground-motion attenuation relations

USGS Publications Warehouse

Cramer, C.H.; Kumar, A.

2003-01-01

Engineering seismoscope data collected at distances less than 300 km for the M 7.7 Bhuj, India, mainshock are compatible with ground-motion attenuation in eastern North America (ENA). The mainshock ground-motion data have been corrected to a common geological site condition using the factors of Joyner and Boore (2000) and a classification scheme of Quaternary or Tertiary sediments or rock. We then compare these data to ENA ground-motion attenuation relations. Despite uncertainties in recording method, geological site corrections, common tectonic setting, and the amount of regional seismic attenuation, the corrected Bhuj dataset agrees with the collective predictions by ENA ground-motion attenuation relations within a factor of 2. This level of agreement is within the dataset uncertainties and the normal variance for recorded earthquake ground motions.

Filtering Raw Terrestrial Laser Scanning Data for Efficient and Accurate Use in Geomorphologic Modeling

NASA Astrophysics Data System (ADS)

Gleason, M. J.; Pitlick, J.; Buttenfield, B. P.

2011-12-01

Terrestrial laser scanning (TLS) represents a new and particularly effective remote sensing technique for investigating geomorphologic processes. Unfortunately, TLS data are commonly characterized by extremely large volume, heterogeneous point distribution, and erroneous measurements, raising challenges for applied researchers. To facilitate efficient and accurate use of TLS in geomorphology, and to improve accessibility for TLS processing in commercial software environments, we are developing a filtering method for raw TLS data to: eliminate data redundancy; produce a more uniformly spaced dataset; remove erroneous measurements; and maintain the ability of the TLS dataset to accurately model terrain. Our method conducts local aggregation of raw TLS data using a 3-D search algorithm based on the geometrical expression of expected random errors in the data. This approach accounts for the estimated accuracy and precision limitations of the instruments and procedures used in data collection, thereby allowing for identification and removal of potential erroneous measurements prior to data aggregation. Initial tests of the proposed technique on a sample TLS point cloud required a modest processing time of approximately 100 minutes to reduce dataset volume over 90 percent (from 12,380,074 to 1,145,705 points). Preliminary analysis of the filtered point cloud revealed substantial improvement in homogeneity of point distribution and minimal degradation of derived terrain models. We will test the method on two independent TLS datasets collected in consecutive years along a non-vegetated reach of the North Fork Toutle River in Washington. We will evaluate the tool using various quantitative, qualitative, and statistical methods. The crux of this evaluation will include a bootstrapping analysis to test the ability of the filtered datasets to model the terrain at roughly the same accuracy as the raw datasets.

Facilitating NCAR Data Discovery by Connecting Related Resources

NASA Astrophysics Data System (ADS)

Rosati, A.

2012-12-01

Linking datasets, creators, and users by employing the proper standards helps to increase the impact of funded research. In order for users to find a dataset, it must first be named. Data citations play the important role of giving datasets a persistent presence by assigning a formal "name" and location. This project focuses on the next step of the "name-find-use" sequence: enhancing discoverability of NCAR data by connecting related resources on the web. By examining metadata schemas that document datasets, I examined how Semantic Web approaches can help to ensure the widest possible range of data users. The focus was to move from search engine optimization (SEO) to information connectivity. Two main markup types are very visible in the Semantic Web and applicable to scientific dataset discovery: The Open Archives Initiative-Object Reuse and Exchange (OAI-ORE - www.openarchives.org) and Microdata (HTML5 and www.schema.org). My project creates pilot aggregations of related resources using both markup types for three case studies: The North American Regional Climate Change Assessment Program (NARCCAP) dataset and related publications, the Palmer Drought Severity Index (PSDI) animation and image files from NCAR's Visualization Lab (VisLab), and the multidisciplinary data types and formats from the Advanced Cooperative Arctic Data and Information Service (ACADIS). This project documents the differences between these markups and how each creates connectedness on the web. My recommendations point toward the most efficient and effective markup schema for aggregating resources within the three case studies based on the following assessment criteria: ease of use, current state of support and adoption of technology, integration with typical web tools, available vocabularies and geoinformatic standards, interoperability with current repositories and access portals (e.g. ESG, Java), and relation to data citation tools and methods.

Improving Large-Scale Image Retrieval Through Robust Aggregation of Local Descriptors.

PubMed

Husain, Syed Sameed; Bober, Miroslaw

2017-09-01

Visual search and image retrieval underpin numerous applications, however the task is still challenging predominantly due to the variability of object appearance and ever increasing size of the databases, often exceeding billions of images. Prior art methods rely on aggregation of local scale-invariant descriptors, such as SIFT, via mechanisms including Bag of Visual Words (BoW), Vector of Locally Aggregated Descriptors (VLAD) and Fisher Vectors (FV). However, their performance is still short of what is required. This paper presents a novel method for deriving a compact and distinctive representation of image content called Robust Visual Descriptor with Whitening (RVD-W). It significantly advances the state of the art and delivers world-class performance. In our approach local descriptors are rank-assigned to multiple clusters. Residual vectors are then computed in each cluster, normalized using a direction-preserving normalization function and aggregated based on the neighborhood rank. Importantly, the residual vectors are de-correlated and whitened in each cluster before aggregation, leading to a balanced energy distribution in each dimension and significantly improved performance. We also propose a new post-PCA normalization approach which improves separability between the matching and non-matching global descriptors. This new normalization benefits not only our RVD-W descriptor but also improves existing approaches based on FV and VLAD aggregation. Furthermore, we show that the aggregation framework developed using hand-crafted SIFT features also performs exceptionally well with Convolutional Neural Network (CNN) based features. The RVD-W pipeline outperforms state-of-the-art global descriptors on both the Holidays and Oxford datasets. On the large scale datasets, Holidays1M and Oxford1M, SIFT-based RVD-W representation obtains a mAP of 45.1 and 35.1 percent, while CNN-based RVD-W achieve a mAP of 63.5 and 44.8 percent, all yielding superior performance to the state-of-the-art.

Mantle P wave travel time tomography of Eastern and Southern Africa: New images of mantle upwellings

NASA Astrophysics Data System (ADS)

Benoit, M. H.; Li, C.; van der Hilst, R.

2006-12-01

Much of Eastern Africa, including Ethiopia, Kenya, and Tanzania, has undergone extensive tectonism, including rifting, uplift, and volcanism during the Cenozoic. The cause of this tectonism is often attributed to the presence of one or more mantle upwellings, including starting thermal plumes and superplumes. Previous regional seismic studies and global tomographic models show conflicting results regarding the spatial and thermal characteristics of these upwellings. Additionally, there are questions concerning the extent to which the Archean and Proterozoic lithosphere has been altered by possible thermal upwellings in the mantle. To further constrain the mantle structure beneath Southern and Eastern Africa and to investigate the origin of the tectonism in Eastern Africa, we present preliminary results of a large-scale P wave travel time tomographic study of the region. We invert travel time measurements from the EHB database with travel time measurements taken from regional PASSCAL datasets including the Ethiopia Broadband Seismic Experiment (2000-2002); Kenya Broadband Seismic Experiment (2000-2002); Southern Africa Seismic Experiment (1997- 1999); Tanzania Broadband Seismic Experiment (1995-1997), and the Saudi Arabia PASSCAL Experiment (1995-1997). The tomographic inversion uses 3-D sensitivity kernels to combine different datasets and is parameterized with an irregular grid so that high spatial resolution can be obtained in areas of dense data coverage. It uses an adaptive least-squares context using the LSQR method with norm and gradient damping.

Trust-aware recommendation for improving aggregate diversity

NASA Astrophysics Data System (ADS)

Liu, Haifeng; Bai, Xiaomei; Yang, Zhuo; Tolba, Amr; Xia, Feng

2015-10-01

Recommender systems are becoming increasingly important and prevalent because of the ability of solving information overload. In recent years, researchers are paying increasing attention to aggregate diversity as a key metric beyond accuracy, because improving aggregate recommendation diversity may increase long tails and sales diversity. Trust is often used to improve recommendation accuracy. However, how to utilize trust to improve aggregate recommendation diversity is unexplored. In this paper, we focus on solving this problem and propose a novel trust-aware recommendation method by incorporating time factor into similarity computation. The rationale underlying the proposed method is that, trustees with later creation time of trust relation can bring more diverse items to recommend to their trustors than other trustees with earlier creation time of trust relation. Through relevant experiments on publicly available dataset, we demonstrate that the proposed method outperforms the baseline method in terms of aggregate diversity while maintaining almost the same recall.

Aggregated Indexing of Biomedical Time Series Data

PubMed Central

Woodbridge, Jonathan; Mortazavi, Bobak; Sarrafzadeh, Majid; Bui, Alex A.T.

2016-01-01

Remote and wearable medical sensing has the potential to create very large and high dimensional datasets. Medical time series databases must be able to efficiently store, index, and mine these datasets to enable medical professionals to effectively analyze data collected from their patients. Conventional high dimensional indexing methods are a two stage process. First, a superset of the true matches is efficiently extracted from the database. Second, supersets are pruned by comparing each of their objects to the query object and rejecting any objects falling outside a predetermined radius. This pruning stage heavily dominates the computational complexity of most conventional search algorithms. Therefore, indexing algorithms can be significantly improved by reducing the amount of pruning. This paper presents an online algorithm to aggregate biomedical times series data to significantly reduce the search space (index size) without compromising the quality of search results. This algorithm is built on the observation that biomedical time series signals are composed of cyclical and often similar patterns. This algorithm takes in a stream of segments and groups them to highly concentrated collections. Locality Sensitive Hashing (LSH) is used to reduce the overall complexity of the algorithm, allowing it to run online. The output of this aggregation is used to populate an index. The proposed algorithm yields logarithmic growth of the index (with respect to the total number of objects) while keeping sensitivity and specificity simultaneously above 98%. Both memory and runtime complexities of time series search are improved when using aggregated indexes. In addition, data mining tasks, such as clustering, exhibit runtimes that are orders of magnitudes faster when run on aggregated indexes. PMID:27617298

A global wind resource atlas including high-resolution terrain effects

NASA Astrophysics Data System (ADS)

Hahmann, Andrea; Badger, Jake; Olsen, Bjarke; Davis, Neil; Larsen, Xiaoli; Badger, Merete

2015-04-01

Currently no accurate global wind resource dataset is available to fill the needs of policy makers and strategic energy planners. Evaluating wind resources directly from coarse resolution reanalysis datasets underestimate the true wind energy resource, as the small-scale spatial variability of winds is missing. This missing variability can account for a large part of the local wind resource. Crucially, it is the windiest sites that suffer the largest wind resource errors: in simple terrain the windiest sites may be underestimated by 25%, in complex terrain the underestimate can be as large as 100%. The small-scale spatial variability of winds can be modelled using novel statistical methods and by application of established microscale models within WAsP developed at DTU Wind Energy. We present the framework for a single global methodology, which is relative fast and economical to complete. The method employs reanalysis datasets, which are downscaled to high-resolution wind resource datasets via a so-called generalization step, and microscale modelling using WAsP. This method will create the first global wind atlas (GWA) that covers all land areas (except Antarctica) and 30 km coastal zone over water. Verification of the GWA estimates will be done at carefully selected test regions, against verified estimates from mesoscale modelling and satellite synthetic aperture radar (SAR). This verification exercise will also help in the estimation of the uncertainty of the new wind climate dataset. Uncertainty will be assessed as a function of spatial aggregation. It is expected that the uncertainty at verification sites will be larger than that of dedicated assessments, but the uncertainty will be reduced at levels of aggregation appropriate for energy planning, and importantly much improved relative to what is used today. In this presentation we discuss the methodology used, which includes the generalization of wind climatologies, and the differences in local and spatially aggregated wind resources that result from using different reanalyses in the various verification regions. A prototype web interface for the public access to the data will also be showcased.

Scientific Datasets: Discovery and Aggregation for Semantic Interpretation.

NASA Astrophysics Data System (ADS)

Lopez, L. A.; Scott, S.; Khalsa, S. J. S.; Duerr, R.

2015-12-01

One of the biggest challenges that interdisciplinary researchers face is finding suitable datasets in order to advance their science; this problem remains consistent across multiple disciplines. A surprising number of scientists, when asked what tool they use for data discovery, reply "Google", which is an acceptable solution in some cases but not even Google can find -or cares to compile- all the data that's relevant for science and particularly geo sciences. If a dataset is not discoverable through a well known search provider it will remain dark data to the scientific world.For the past year, BCube, an EarthCube Building Block project, has been developing, testing and deploying a technology stack capable of data discovery at web-scale using the ultimate dataset: The Internet. This stack has 2 principal components, a web-scale crawling infrastructure and a semantic aggregator. The web-crawler is a modified version of Apache Nutch (the originator of Hadoop and other big data technologies) that has been improved and tailored for data and data service discovery. The second component is semantic aggregation, carried out by a python-based workflow that extracts valuable metadata and stores it in the form of triples through the use semantic technologies.While implementing the BCube stack we have run into several challenges such as a) scaling the project to cover big portions of the Internet at a reasonable cost, b) making sense of very diverse and non-homogeneous data, and lastly, c) extracting facts about these datasets using semantic technologies in order to make them usable for the geosciences community. Despite all these challenges we have proven that we can discover and characterize data that otherwise would have remained in the dark corners of the Internet. Having all this data indexed and 'triplelized' will enable scientists to access a trove of information relevant to their work in a more natural way. An important characteristic of the BCube stack is that all the code we have developed is open sourced and available to anyone who wants to experiment and collaborate with the project at: http://github.com/b-cube/

Defect Categorization: Making Use of a Decade of Widely Varying Historical Data

NASA Technical Reports Server (NTRS)

Shull, Forrest; Seaman, Carolyn; Godfrey, Sara H.; Guo, Yuepu

2008-01-01

This paper describes our experience in aggregating a number of historical datasets containing inspection defect data using different categorizing schemes. Our goal was to make use of the historical data by creating models to guide future development projects. We describe our approach to reconciling the different choices used in the historical datasets to categorize defects, and the challenges we faced. We also present a set of recommendations for others involved in classifying defects.

Increasing consistency of disease biomarker prediction across datasets.

PubMed

Chikina, Maria D; Sealfon, Stuart C

2014-01-01

Microarray studies with human subjects often have limited sample sizes which hampers the ability to detect reliable biomarkers associated with disease and motivates the need to aggregate data across studies. However, human gene expression measurements may be influenced by many non-random factors such as genetics, sample preparations, and tissue heterogeneity. These factors can contribute to a lack of agreement among related studies, limiting the utility of their aggregation. We show that it is feasible to carry out an automatic correction of individual datasets to reduce the effect of such 'latent variables' (without prior knowledge of the variables) in such a way that datasets addressing the same condition show better agreement once each is corrected. We build our approach on the method of surrogate variable analysis but we demonstrate that the original algorithm is unsuitable for the analysis of human tissue samples that are mixtures of different cell types. We propose a modification to SVA that is crucial to obtaining the improvement in agreement that we observe. We develop our method on a compendium of multiple sclerosis data and verify it on an independent compendium of Parkinson's disease datasets. In both cases, we show that our method is able to improve agreement across varying study designs, platforms, and tissues. This approach has the potential for wide applicability to any field where lack of inter-study agreement has been a concern.

Associations between land use and Perkinsus marinus infection of eastern oysters in a high salinity, partially urbanized estuary

USGS Publications Warehouse

Gray, Brian R.; Bushek, David; Drane, J. Wanzer; Porter, Dwayne

2009-01-01

Infection levels of eastern oysters by the unicellular pathogen Perkinsus marinus have been associated with anthropogenic influences in laboratory studies. However, these relationships have been difficult to investigate in the field because anthropogenic inputs are often associated with natural influences such as freshwater inflow, which can also affect infection levels. We addressed P. marinus-land use associations using field-collected data from Murrells Inlet, South Carolina, USA, a developed, coastal estuary with relatively minor freshwater inputs. Ten oysters from each of 30 reefs were sampled quarterly in each of 2 years. Distances to nearest urbanized land class and to nearest stormwater outfall were measured via both tidal creeks and an elaboration of Euclidean distance. As the forms of any associations between oyster infection and distance to urbanization were unknown a priori, we used data from the first and second years of the study as exploratory and confirmatory datasets, respectively. With one exception, quarterly land use associations identified using the exploratory dataset were not confirmed using the confirmatory dataset. The exception was an association between the prevalence of moderate to high infection levels in winter and decreasing distance to nearest urban land use. Given that the study design appeared adequate to detect effects inferred from the exploratory dataset, these results suggest that effects of land use gradients were largely insubstantial or were ephemeral with duration less than 3 months.

Comparison of pelletized lime with other antistripping additives.

DOT National Transportation Integrated Search

2014-05-01

Stripping is a common problem in HMA pavements in Oregon, especially in Eastern Oregon. : Stripping is the degradation of the bond between the aggregate and the asphalt binder due to the : presence of water this mechanism of degradation can lead ...

Partitioning-based mechanisms under personalized differential privacy.

PubMed

Li, Haoran; Xiong, Li; Ji, Zhanglong; Jiang, Xiaoqian

2017-05-01

Differential privacy has recently emerged in private statistical aggregate analysis as one of the strongest privacy guarantees. A limitation of the model is that it provides the same privacy protection for all individuals in the database. However, it is common that data owners may have different privacy preferences for their data. Consequently, a global differential privacy parameter may provide excessive privacy protection for some users, while insufficient for others. In this paper, we propose two partitioning-based mechanisms, privacy-aware and utility-based partitioning, to handle personalized differential privacy parameters for each individual in a dataset while maximizing utility of the differentially private computation. The privacy-aware partitioning is to minimize the privacy budget waste, while utility-based partitioning is to maximize the utility for a given aggregate analysis. We also develop a t -round partitioning to take full advantage of remaining privacy budgets. Extensive experiments using real datasets show the effectiveness of our partitioning mechanisms.

Will higher traffic flow lead to more traffic conflicts? A crash surrogate metric based analysis

PubMed Central

Kuang, Yan; Yan, Yadan

2017-01-01

In this paper, we aim to examine the relationship between traffic flow and potential conflict risks by using crash surrogate metrics. It has been widely recognized that one traffic flow corresponds to two distinct traffic states with different speeds and densities. In view of this, instead of simply aggregating traffic conditions with the same traffic volume, we represent potential conflict risks at a traffic flow fundamental diagram. Two crash surrogate metrics, namely, Aggregated Crash Index and Time to Collision, are used in this study to represent the potential conflict risks with respect to different traffic conditions. Furthermore, Beijing North Ring III and Next Generation SIMulation Interstate 80 datasets are utilized to carry out case studies. By using the proposed procedure, both datasets generate similar trends, which demonstrate the applicability of the proposed methodology and the transferability of our conclusions. PMID:28787022

Partitioning-based mechanisms under personalized differential privacy

PubMed Central

Li, Haoran; Xiong, Li; Ji, Zhanglong; Jiang, Xiaoqian

2017-01-01

Differential privacy has recently emerged in private statistical aggregate analysis as one of the strongest privacy guarantees. A limitation of the model is that it provides the same privacy protection for all individuals in the database. However, it is common that data owners may have different privacy preferences for their data. Consequently, a global differential privacy parameter may provide excessive privacy protection for some users, while insufficient for others. In this paper, we propose two partitioning-based mechanisms, privacy-aware and utility-based partitioning, to handle personalized differential privacy parameters for each individual in a dataset while maximizing utility of the differentially private computation. The privacy-aware partitioning is to minimize the privacy budget waste, while utility-based partitioning is to maximize the utility for a given aggregate analysis. We also develop a t-round partitioning to take full advantage of remaining privacy budgets. Extensive experiments using real datasets show the effectiveness of our partitioning mechanisms. PMID:28932827

Will higher traffic flow lead to more traffic conflicts? A crash surrogate metric based analysis.

PubMed

Kuang, Yan; Qu, Xiaobo; Yan, Yadan

2017-01-01

In this paper, we aim to examine the relationship between traffic flow and potential conflict risks by using crash surrogate metrics. It has been widely recognized that one traffic flow corresponds to two distinct traffic states with different speeds and densities. In view of this, instead of simply aggregating traffic conditions with the same traffic volume, we represent potential conflict risks at a traffic flow fundamental diagram. Two crash surrogate metrics, namely, Aggregated Crash Index and Time to Collision, are used in this study to represent the potential conflict risks with respect to different traffic conditions. Furthermore, Beijing North Ring III and Next Generation SIMulation Interstate 80 datasets are utilized to carry out case studies. By using the proposed procedure, both datasets generate similar trends, which demonstrate the applicability of the proposed methodology and the transferability of our conclusions.

Effects of Agaricus lilaceps fairy rings on soil aggregation and microbial community structure in relation to growth stimulation of western wheatgrass (Pascopyrum smithii) in Eastern Montana rangeland.

PubMed

Caesar-Tonthat, The Can; Espeland, Erin; Caesar, Anthony J; Sainju, Upendra M; Lartey, Robert T; Gaskin, John F

2013-07-01

Stimulation of plant productivity caused by Agaricus fairy rings has been reported, but little is known about the effects of these fungi on soil aggregation and the microbial community structure, particularly the communities that can bind soil particles. We studied three concentric zones of Agaricus lilaceps fairy rings in Eastern Montana that stimulate western wheatgrass (Pascopyrum smithii): outside the ring (OUT), inside the ring (IN), and stimulated zone adjacent to the fungal fruiting bodies (SZ) to determine (1) soil aggregate proportion and stability, (2) the microbial community composition and the N-acetyl-β-D-glucosaminidase activity associated with bulk soil at 0-15 cm depth, (3) the predominant culturable bacterial communities that can bind to soil adhering to wheatgrass roots, and (4) the stimulation of wheatgrass production. In bulk soil, macroaggregates (4.75-2.00 and 2.00-0.25 mm) and aggregate stability increased in SZ compared to IN and OUT. The high ratio of fungal to bacteria (fatty acid methyl ester) and N-acetyl-β-D-glucosaminidase activity in SZ compared to IN and OUT suggest high fungal biomass. A soil sedimentation assay performed on the predominant isolates from root-adhering soil indicated more soil-binding bacteria in SZ than IN and OUT; Pseudomonas fluorescens and Stenotrophomonas maltophilia isolates predominated in SZ, whereas Bacillus spp. isolates predominated in IN and OUT. This study suggests that growth stimulation of wheatgrass in A. lilaceps fairy rings may be attributed to the activity of the fungus by enhancing soil aggregation of bulk soil at 0-15 cm depth and influencing the amount and functionality of specific predominant microbial communities in the wheatgrass root-adhering soil.

Multiple distant origins for green sea turtles aggregating off Gorgona Island in the Colombian eastern Pacific.

PubMed

Amorocho, Diego F; Abreu-Grobois, F Alberto; Dutton, Peter H; Reina, Richard D

2012-01-01

Mitochondrial DNA analyses have been useful for resolving maternal lineages and migratory behavior to foraging grounds (FG) in sea turtles. However, little is known about source rookeries and haplotype composition of foraging green turtle aggregations in the southeastern Pacific. We used mitochondrial DNA control region sequences to identify the haplotype composition of 55 green turtles, Chelonia mydas, captured in foraging grounds of Gorgona National Park in the Colombian Pacific. Amplified fragments of the control region (457 bp) revealed the presence of seven haplotypes, with haplotype (h) and nucleotide (π) diversities of h = 0.300±0.080 and π = 0.009±0.005 respectively. The most common haplotype was CMP4 observed in 83% of individuals, followed by CMP22 (5%). The genetic composition of the Gorgona foraging population primarily comprised haplotypes that have been found at eastern Pacific rookeries including Mexico and the Galapagos, as well as haplotypes of unknown stock origin that likely originated from more distant western Pacific rookeries. Mixed stock analysis suggests that the Gorgona FG population is comprised mostly of animals from the Galapagos rookery (80%). Lagrangian drifter data showed that movement of turtles along the eastern Pacific coast and eastward from distant western and central Pacific sites was possible through passive drift. Our results highlight the importance of this protected area for conservation management of green turtles recruited from distant sites along the eastern Pacific Ocean.

Multiple Distant Origins for Green Sea Turtles Aggregating off Gorgona Island in the Colombian Eastern Pacific

PubMed Central

Amorocho, Diego F.; Abreu-Grobois, F. Alberto; Dutton, Peter H.; Reina, Richard D.

2012-01-01

Mitochondrial DNA analyses have been useful for resolving maternal lineages and migratory behavior to foraging grounds (FG) in sea turtles. However, little is known about source rookeries and haplotype composition of foraging green turtle aggregations in the southeastern Pacific. We used mitochondrial DNA control region sequences to identify the haplotype composition of 55 green turtles, Chelonia mydas, captured in foraging grounds of Gorgona National Park in the Colombian Pacific. Amplified fragments of the control region (457 bp) revealed the presence of seven haplotypes, with haplotype (h) and nucleotide (π) diversities of h = 0.300±0.080 and π = 0.009±0.005 respectively. The most common haplotype was CMP4 observed in 83% of individuals, followed by CMP22 (5%). The genetic composition of the Gorgona foraging population primarily comprised haplotypes that have been found at eastern Pacific rookeries including Mexico and the Galapagos, as well as haplotypes of unknown stock origin that likely originated from more distant western Pacific rookeries. Mixed stock analysis suggests that the Gorgona FG population is comprised mostly of animals from the Galapagos rookery (80%). Lagrangian drifter data showed that movement of turtles along the eastern Pacific coast and eastward from distant western and central Pacific sites was possible through passive drift. Our results highlight the importance of this protected area for conservation management of green turtles recruited from distant sites along the eastern Pacific Ocean. PMID:22319635

';Best' Practices for Aggregating Subset Results from Archived Datasets

NASA Astrophysics Data System (ADS)

Baskin, W. E.; Perez, J.

2013-12-01

In response to the exponential growth in science data analysis and visualization capabilities Data Centers have been developing new delivery mechanisms to package and deliver large volumes of aggregated subsets of archived data. New standards are evolving to help data providers and application programmers deal with growing needs of the science community. These standards evolve from the best practices gleaned from new products and capabilities. The NASA Atmospheric Sciences Data Center (ASDC) has developed and deployed production provider-specific search and subset web applications for the CALIPSO, CERES, TES, and MOPITT missions. This presentation explores several use cases that leverage aggregated subset results and examines the standards and formats ASDC developers applied to the delivered files as well as the implementation strategies for subsetting and processing the aggregated products. The following topics will be addressed: - Applications of NetCDF CF conventions to aggregated level 2 satellite subsets - Data-Provider-Specific format requirements vs. generalized standards - Organization of the file structure of aggregated NetCDF subset output - Global Attributes of individual subsetted files vs. aggregated results - Specific applications and framework used for subsetting and delivering derivative data files

Residential load and rooftop PV generation: an Australian distribution network dataset

NASA Astrophysics Data System (ADS)

Ratnam, Elizabeth L.; Weller, Steven R.; Kellett, Christopher M.; Murray, Alan T.

2017-09-01

Despite the rapid uptake of small-scale solar photovoltaic (PV) systems in recent years, public availability of generation and load data at the household level remains very limited. Moreover, such data are typically measured using bi-directional meters recording only PV generation in excess of residential load rather than recording generation and load separately. In this paper, we report a publicly available dataset consisting of load and rooftop PV generation for 300 de-identified residential customers in an Australian distribution network, with load centres covering metropolitan Sydney and surrounding regional areas. The dataset spans a 3-year period, with separately reported measurements of load and PV generation at 30-min intervals. Following a detailed description of the dataset, we identify several means by which anomalous records (e.g. due to inverter failure) are identified and excised. With the resulting 'clean' dataset, we identify key customer-specific and aggregated characteristics of rooftop PV generation and residential load.

Long-term ice phenology records from eastern-central Europe

NASA Astrophysics Data System (ADS)

Takács, Katalin; Kern, Zoltán; Pásztor, László

2018-03-01

A dataset of annual freshwater ice phenology was compiled for the largest river (Danube) and the largest lake (Lake Balaton) in eastern-central Europe, extending regular river and lake ice monitoring data through the use of historical observations and documentary records dating back to AD 1774 and AD 1885, respectively. What becomes clear is that the dates of the first appearance of ice and freeze-up have shifted, arriving 12-30 and 4-13 days later, respectively, per 100 years. Break-up and ice-off have shifted to earlier dates by 7-13 and 9-27 days/100 years, except on Lake Balaton, where the date of break-up has not changed significantly. The datasets represent a resource for (paleo)climatological research thanks to the strong, physically determined link between water and air temperature and the occurrence of freshwater ice phenomena. The derived centennial records of freshwater cryophenology for the Danube and Balaton are readily available for detailed analysis of the temporal trends, large-scale spatial comparison, or other climatological purposes. The derived dataset is publicly available via PANGAEA at https://doi.org/10.1594/PANGAEA.881056.

Stability of Spatial Distributions of Stink Bugs, Boll Injury, and NDVI in Cotton.

PubMed

Reay-Jones, Francis P F; Greene, Jeremy K; Bauer, Philip J

2016-10-01

A 3-yr study was conducted to determine the degree of aggregation of stink bugs and boll injury in cotton, Gossypium hirsutum L., and their spatial association with a multispectral vegetation index (normalized difference vegetation index [NDVI]). Using the spatial analysis by distance indices analyses, stink bugs were less frequently aggregated (17% for adults and 4% for nymphs) than boll injury (36%). NDVI values were also significantly aggregated within fields in 19 of 48 analyses (40%), with the majority of significant indices occurring in July and August. Paired NDVI datasets from different sampling dates were frequently associated (86.5% for weekly intervals among datasets). Spatial distributions of both stink bugs and boll injury were less stable than for NDVI, with positive associations varying from 12.5 to 25% for adult stink bugs for weekly intervals, depending on species. Spatial distributions of boll injury from stink bug feeding were more stable than stink bugs, with 46% positive associations among paired datasets with weekly intervals. NDVI values were positively associated with boll injury from stink bug feeding in 11 out of 22 analyses, with no significant negative associations. This indicates that NDVI has potential as a component of site-specific management. Future work should continue to examine the value of remote sensing for insect management in cotton, with an aim to develop tools such as risk assessment maps that will help growers to reduce insecticide inputs. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A model of Fe speciation and biogeochemistry at the Tropical Eastern North Atlantic Time-Series Observatory site

NASA Astrophysics Data System (ADS)

Ye, Y.; Völker, C.; Wolf-Gladrow, D. A.

2009-10-01

A one-dimensional model of Fe speciation and biogeochemistry, coupled with the General Ocean Turbulence Model (GOTM) and a NPZD-type ecosystem model, is applied for the Tropical Eastern North Atlantic Time-Series Observatory (TENATSO) site. Among diverse processes affecting Fe speciation, this study is focusing on investigating the role of dust particles in removing dissolved iron (DFe) by a more complex description of particle aggregation and sinking, and explaining the abundance of organic Fe-binding ligands by modelling their origin and fate. The vertical distribution of different particle classes in the model shows high sensitivity to changing aggregation rates. Using the aggregation rates from the sensitivity study in this work, modelled particle fluxes are close to observations, with dust particles dominating near the surface and aggregates deeper in the water column. POC export at 1000 m is a little higher than regional sediment trap measurements, suggesting further improvement of modelling particle aggregation, sinking or remineralisation. Modelled strong ligands have a high abundance near the surface and decline rapidly below the deep chlorophyll maximum, showing qualitative similarity to observations. Without production of strong ligands, phytoplankton concentration falls to 0 within the first 2 years in the model integration, caused by strong Fe-limitation. A nudging of total weak ligands towards a constant value is required for reproducing the observed nutrient-like profiles, assuming a decay time of 7 years for weak ligands. This indicates that weak ligands have a longer decay time and therefore cannot be modelled adequately in a one-dimensional model. The modelled DFe profile is strongly influenced by particle concentration and vertical distribution, because the most important removal of DFe in deeper waters is colloid formation and aggregation. Redissolution of particulate iron is required to reproduce an observed DFe profile at TENATSO site. Assuming colloidal iron is mainly composed of inorganic colloids, the modelled colloidal to soluble iron ratio is lower that observations, indicating the importance of organic colloids.

Installation report : experimental mix using foamed asphalt.

DOT National Transportation Integrated Search

1982-01-01

This report describes the first foam asphalt mix produced and used in a highway pavement in Virginia. The aggregate used was a local Eastern Shore sand modified with 5% fly ash to improve the gradation. A foam asphalt chamber on a portable pug-mixer ...

Quantifying spatial and temporal patterns of flow intermittency using spatially contiguous runoff data

NASA Astrophysics Data System (ADS)

Yu (于松延), Songyan; Bond, Nick R.; Bunn, Stuart E.; Xu, Zongxue; Kennard, Mark J.

2018-04-01

River channel drying caused by intermittent stream flow is a widely-recognized factor shaping stream ecosystems. There is a strong need to quantify the distribution of intermittent streams across catchments to inform management. However, observational gauge networks provide only point estimates of streamflow variation. Increasingly, this limitation is being overcome through the use of spatially contiguous estimates of the terrestrial water-balance, which can also assist in estimating runoff and streamflow at large-spatial scales. Here we proposed an approach to quantifying spatial and temporal variation in monthly flow intermittency throughout river networks in eastern Australia. We aggregated gridded (5 × 5 km) monthly water-balance data with a hierarchically nested catchment dataset to simulate catchment runoff accumulation throughout river networks from 1900 to 2016. We also predicted zero flow duration for the entire river network by developing a robust predictive model relating measured zero flow duration (% months) to environmental predictor variables (based on 43 stream gauges). We then combined these datasets by using the predicted zero flow duration from the regression model to determine appropriate 'zero' flow thresholds for the modelled discharge data, which varied spatially across the catchments examined. Finally, based on modelled discharge data and identified actual zero flow thresholds, we derived summary metrics describing flow intermittency across the catchment (mean flow duration and coefficient-of-variation in flow permanence from 1900 to 2016). We also classified the relative degree of flow intermittency annually to characterise temporal variation in flow intermittency. Results showed that the degree of flow intermittency varied substantially across streams in eastern Australia, ranging from perennial streams flowing permanently (11-12 months) to strongly intermittent streams flowing 4 months or less of year. Results also showed that the temporal extent of flow intermittency varied dramatically inter-annually from 1900 to 2016, with the proportion of intermittent (weakly and strongly intermittent) streams ranging in length from 3% to nearly 100% of the river network, but there was no evidence of an increasing trend towards flow intermittency over this period. Our approach to generating spatially explicit and catchment-wide estimates of streamflow intermittency can facilitate improved ecological understanding and management of intermittent streams in Australia and around the world.

Understanding the Spatio-Temporal Pattern of Fire Disturbance in the Eastern Mongolia Using Modis Product

NASA Astrophysics Data System (ADS)

Wurihan; Zhang, H.; Zhang, Z.; Guo, X.; Zhao, J.; Duwala; Shan, Y.; Hongying

2018-04-01

Fire disturbance plays an important role in maintaining ecological balance, biodiversity and self-renewal. In this paper, the spatio-temporal pattern of fire disturbances in eastern Mongolia are studied by using the ArcGIS spatial analysis method, using the MCD45A1 data of MODIS fire products with long time series. It provides scientific basis and reference for the regional ecological environment security construction and international ecological security. Research indicates: (1) The fire disturbance in eastern Mongolia has obvious high and low peak interleaving phenomenon in the year, and the seasonal change is obvious. (2) The distribution pattern of fire disturbance in eastern Mongolia is aggregated, which indicates that the fire disturbance is not random and it is caused by certain influence. (3) Fire disturbance is mainly distributed in the eastern province of Mongolia, the border between China and Mongolia and the northern forest area of Sukhbaatar province. (4) The fire disturbance in the eastern part of the study area is strong and the southwest is weaker. The spreading regularity of fire disturbances in eastern Mongolia is closer to the natural level of ecosystem.

The nematode community in the Atlantic rainforest lizard Enyalius perditus Jackson, from south-eastern Brazil.

PubMed

Barreto-Lima, A F; Toledo, G M; Anjos, L A

2012-12-01

Studies focusing on communities of helminths from Brazilian lizards are increasing, but there are many blanks in the knowledge of parasitic fauna of wild fauna. This lack of knowledge hampers understanding of ecological and parasitological aspects of involved species. Moreover, the majority of research has focused on parasitic fauna of lizards from families Tropiduridae and Scincidae. Only a few studies have looked at lizards from the family Leiosauridae, including some species of Enyalius. This study presents data on the gastrointestinal parasite fauna of Enyalius perditus and their relationships with ecological aspects of hosts in a disturbed Atlantic rainforest area in the state of Minas Gerais, south-eastern Brazil. Two nematode species, Oswaldocruzia burseyi [(Molineidae) and Strongyluris oscari (Heterakidae) were found. Nematode species showed an aggregated distribution in this host population, with O. burseyi being more aggregated than S. oscari. The present study extends the range of occurrence of O. burseyi to the Brazilian continental area.

GIS - based decision and outreach tools for aggregate source management.

DOT National Transportation Integrated Search

2008-09-01

This research project combined various datasets, existing and created for this project, into an Interactive : Mapping Service (IMS) for use by Iowa DOT personnel, county planning and zoning departments and the : public in order to make more informed ...

Styles and Timing of Volatile-driven Activity in the Eastern Hellas Region of Mars

NASA Astrophysics Data System (ADS)

Crown, D. A.; Bleamaster, L. F., III; Mest, S. C.; Teneva, L. T.

2005-03-01

Current research integrates geologic studies of the basin floor and east rim using Viking Orbiter, Mars Global Surveyor, and Mars Odyssey datasets to provide a synthesis of the history of volatiles in the region.

An audit of some processing effects in aggregated occurrence records.

PubMed

Mesibov, Robert

2018-01-01

A total of ca 800,000 occurrence records from the Australian Museum (AM), Museums Victoria (MV) and the New Zealand Arthropod Collection (NZAC) were audited for changes in selected Darwin Core fields after processing by the Atlas of Living Australia (ALA; for AM and MV records) and the Global Biodiversity Information Facility (GBIF; for AM, MV and NZAC records). Formal taxon names in the genus- and species-groups were changed in 13-21% of AM and MV records, depending on dataset and aggregator. There was little agreement between the two aggregators on processed names, with names changed in two to three times as many records by one aggregator alone compared to records with names changed by both aggregators. The type status of specimen records did not change with name changes, resulting in confusion as to the name with which a type was associated. Data losses of up to 100% were found after processing in some fields, apparently due to programming errors. The taxonomic usefulness of occurrence records could be improved if aggregators included both original and the processed taxonomic data items for each record. It is recommended that end-users check original and processed records for data loss and name replacements after processing by aggregators.

The Gulf of Mexico Coastal Ocean Observing System: A Decade of Data Aggregation and Services.

NASA Astrophysics Data System (ADS)

Howard, M.; Gayanilo, F.; Kobara, S.; Baum, S. K.; Currier, R. D.; Stoessel, M. M.

2016-02-01

The Gulf of Mexico Coastal Ocean Observing System Regional Association (GCOOS-RA) celebrated its 10-year anniversary in 2015. GCOOS-RA is one of 11 RAs organized under the NOAA-led U.S. Integrated Ocean Observing System (IOOS) Program Office to aggregate regional data and make these data publicly-available in preferred forms and formats via standards-based web services. Initial development of GCOOS focused on building elements of the IOOS Data Management and Communications Plan which is a framework for end-to-end interoperability. These elements included: data discovery, catalog, metadata, online-browse, data access and transport. Initial data types aggregated included near real-time physical oceanographic, marine meteorological and satellite data. Our focus in the middle of the past decade was on the production of basic products such as maps of current oceanographic conditions and quasi-static datasets such as bathymetry and climatologies. In the latter part of the decade we incorporated historical physical oceanographic datasets and historical coastal and offshore water quality data into our holdings and added our first biological dataset. We also developed web environments and products to support Citizen Scientists and stakeholder groups such as recreational boaters. Current efforts are directed towards applying data quality assurance (testing and flagging) to non-federal data, data archiving at national repositories, serving and visualizing numerical model output, providing data services for glider operators, and supporting marine biodiversity observing networks. GCOOS Data Management works closely with the Gulf of Mexico Research Initiative Information and Data Cooperative and various groups involved with Gulf Restoration. GCOOS-RA has influenced attitudes and behaviors associated with good data stewardship and data management practices across the Gulf and will to continue to do so into the next decade.

GWIPS-viz: 2018 update

PubMed Central

Michel, Audrey M; Kiniry, Stephen J; O’Connor, Patrick B F; Mullan, James P

2018-01-01

Abstract The GWIPS-viz browser (http://gwips.ucc.ie/) is an on-line genome browser which is tailored for exploring ribosome profiling (Ribo-seq) data. Since its publication in 2014, GWIPS-viz provides Ribo-seq data for an additional 14 genomes bringing the current total to 23. The integration of new Ribo-seq data has been automated thereby increasing the number of available tracks to 1792, a 10-fold increase in the last three years. The increase is particularly substantial for data derived from human sources. Following user requests, we added the functionality to download these tracks in bigWig format. We also incorporated new types of data (e.g. TCP-seq) as well as auxiliary tracks from other sources that help with the interpretation of Ribo-seq data. Improvements in the visualization of the data have been carried out particularly for bacterial genomes where the Ribo-seq data are now shown in a strand specific manner. For higher eukaryotic datasets, we provide characteristics of individual datasets using the RUST program which includes the triplet periodicity, sequencing biases and relative inferred A-site dwell times. This information can be used for assessing the quality of Ribo-seq datasets. To improve the power of the signal, we aggregate Ribo-seq data from several studies into Global aggregate tracks for each genome. PMID:28977460

Gas Hydrate Characterization from a 3D Seismic Dataset in the Eastern Deepwater Gulf of Mexico

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

McConnell, Dan

The presence of a gas hydrate petroleum system and seismic attributes derived from 3D seismic data are used for the identification and characterization of gas hydrate deposits in the deepwater eastern Gulf of Mexico. In the central deepwater Gulf of Mexico (GoM), logging while drilling (LWD) data provided insight to the amplitude response of gas hydrate saturation in sands, which could be used to characterize complex gas hydrate deposits in other sandy deposits. In this study, a large 3D seismic data set from equivalent and distal Plio-Pleistocene sandy channel deposits in the deepwater eastern Gulf of Mexico is screened formore » direct hydrocarbon indicators for gas hydrate saturated sands.« less

D-cracking field performance of Portland cement concrete pavements containing limestone in Kansas : phase 1 report.

DOT National Transportation Integrated Search

2012-05-01

Premature deterioration of concrete pavement due to D-Cracking has been a problem in Kansas since the 1930s. : Limestone is the major source of coarse aggregate in eastern Kansas where the majority of the concrete pavements are : constructed. D-Crack...

12. Close up view of construction on the downstream face. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

12. Close up view of construction on the downstream face. Track at lower center conveyed aggregate from the stream bed to the mixing plant. Photographer unknown, October 15, 1924. Source: Salt River Project. - Mormon Flat Dam, On Salt River, Eastern Maricopa County, east of Phoenix, Phoenix, Maricopa County, AZ

Development of a Zooplankton Assemblage Indicator for the 2012 National Lakes Assessment: Performance in the Western U.S.

EPA Science Inventory

We used zooplankton count data collected as part of the 2012 National Lakes Assessment (NLA) to develop candidate metrics and multimetric indices (MMIs) for five aggregated ecoregions of the conterminous USA (Coastal Plains, Eastern Highlands, Plains, Upper Midwest, and Western M...

Development of a Multimetric Indicator of Pelagic Zooplankton Assemblage Condition for the 2012 National Lakes Assessment

EPA Science Inventory

We used zooplankton data collected for the 2012 National Lakes Assessment (NLA) to develop multimetric indices (MMIs) for five aggregated ecoregions of the conterminous USA (Coastal Plains, Eastern Highlands, Plains, Upper Midwest, and Western Mountains and Xeric [“West&rsq...

D-cracking field performance of portland cement concrete pavements containing limestone in Kansas : phase 1 report : technical summary.

DOT National Transportation Integrated Search

2012-05-01

Introduction: Premature deterioration of concrete pavement due to D-cracking has been a problem in Kansas since the 1930s. Limestone is the major source of coarse aggregate in eastern Kansas where the majority of the concrete pavements are constructe...

An extensive dataset of eye movements during viewing of complex images.

PubMed

Wilming, Niklas; Onat, Selim; Ossandón, José P; Açık, Alper; Kietzmann, Tim C; Kaspar, Kai; Gameiro, Ricardo R; Vormberg, Alexandra; König, Peter

2017-01-31

We present a dataset of free-viewing eye-movement recordings that contains more than 2.7 million fixation locations from 949 observers on more than 1000 images from different categories. This dataset aggregates and harmonizes data from 23 different studies conducted at the Institute of Cognitive Science at Osnabrück University and the University Medical Center in Hamburg-Eppendorf. Trained personnel recorded all studies under standard conditions with homogeneous equipment and parameter settings. All studies allowed for free eye-movements, and differed in the age range of participants (~7-80 years), stimulus sizes, stimulus modifications (phase scrambled, spatial filtering, mirrored), and stimuli categories (natural and urban scenes, web sites, fractal, pink-noise, and ambiguous artistic figures). The size and variability of viewing behavior within this dataset presents a strong opportunity for evaluating and comparing computational models of overt attention, and furthermore, for thoroughly quantifying strategies of viewing behavior. This also makes the dataset a good starting point for investigating whether viewing strategies change in patient groups.

Chemistry Data for Geothermometry Mapping of Deep Hydrothermal Reservoirs in Southeastern Idaho

DOE Data Explorer

Earl Mattson

2016-01-18

This dataset includes chemistry of geothermal water samples of the Eastern Snake River Plain and surrounding area. The samples included in this dataset were collected during the springs and summers of 2014 and 2015. All chemical analysis of the samples were conducted in the Analytical Laboratory at the Center of Advanced Energy Studies in Idaho Falls, Idaho. This data set supersedes #425 submission and is the final submission for AOP 3.1.2.1 for INL. Isotopic data collected by Mark Conrad will be submitted in a separate file.

The LANDFIRE Refresh strategy: updating the national dataset

USGS Publications Warehouse

Nelson, Kurtis J.; Connot, Joel A.; Peterson, Birgit E.; Martin, Charley

2013-01-01

The LANDFIRE Program provides comprehensive vegetation and fuel datasets for the entire United States. As with many large-scale ecological datasets, vegetation and landscape conditions must be updated periodically to account for disturbances, growth, and natural succession. The LANDFIRE Refresh effort was the first attempt to consistently update these products nationwide. It incorporated a combination of specific systematic improvements to the original LANDFIRE National data, remote sensing based disturbance detection methods, field collected disturbance information, vegetation growth and succession modeling, and vegetation transition processes. This resulted in the creation of two complete datasets for all 50 states: LANDFIRE Refresh 2001, which includes the systematic improvements, and LANDFIRE Refresh 2008, which includes the disturbance and succession updates to the vegetation and fuel data. The new datasets are comparable for studying landscape changes in vegetation type and structure over a decadal period, and provide the most recent characterization of fuel conditions across the country. The applicability of the new layers is discussed and the effects of using the new fuel datasets are demonstrated through a fire behavior modeling exercise using the 2011 Wallow Fire in eastern Arizona as an example.

Dataset on predictive compressive strength model for self-compacting concrete.

PubMed

Ofuyatan, O M; Edeki, S O

2018-04-01

The determination of compressive strength is affected by many variables such as the water cement (WC) ratio, the superplasticizer (SP), the aggregate combination, and the binder combination. In this dataset article, 7, 28, and 90-day compressive strength models are derived using statistical analysis. The response surface methodology is used toinvestigate the effect of the parameters: Varying percentages of ash, cement, WC, and SP on hardened properties-compressive strengthat 7,28 and 90 days. Thelevels of independent parameters are determinedbased on preliminary experiments. The experimental values for compressive strengthat 7, 28 and 90 days and modulus of elasticity underdifferent treatment conditions are also discussed and presented.These dataset can effectively be used for modelling and prediction in concrete production settings.

Geologic and societal factors affecting the international oceanic transport of aggregate

USGS Publications Warehouse

Langer, W.H.

1995-01-01

Crushed stone and sand and gravel are the two main sources of natural aggregate, and together comprise approximately half the volume and tonnage of mined material in the United States. Natural aggregate is a bulky, heavy material without special or unique properties, and it is commonly used near its source of production to minimize haulage cost. However, remoteness is no longer an absolute disqualifier for the production of aggregate. Today interstate aggregate routinely is shipped hundreds of kilometers by rail and barge. In addition, during 1992, the United States imported 1,317,000 metric tons of aggregate from Canada and 1,531,000 metric tons from Mexico. A number of ports on the Atlantic Coast and Gulf Coast of the United States receive imports of crushed stone from foreign sources for transport to various parts of the eastern United States. These areas either lack adequate supplies of aggregate or are augmenting their supplies because they have difficulties meeting current demand. These difficulties may include poor stone quality, environmental permitting problems, or transportation. Certain societal and geologic conditions of New York City and Philadelphia along the Atlantic Coast, and Tampa and New Orleans along the Gulf Coast, are discussed to demonstrate the different combinations of issues that contribute to the economic viability of importing crushed stone. ?? 1995 Oxford University Press.

Controls on architecture of Argentine limestone and associated strata in northeastern Kansas. A firstcut method for evaluating limestone aggregate durability using spectral scintillometry

DOT National Transportation Integrated Search

2006-10-01

Missourian strata were studied in eastern Kansas to evaluate the build-and-fill controls on strata deposited in association with high-amplitude glacioeustatic sea-level fluctuations. Results from this study show that creation of relief in high-freque...

Aggregate R-R-V Analysis

EPA Pesticide Factsheets

The excel file contains time series data of flow rates, concentrations of alachlor , atrazine, ammonia, total phosphorus, and total suspended solids observed in two watersheds in Indiana from 2002 to 2007. The aggregate time series data corresponding or representative to all these parameters was obtained using a specialized, data-driven technique. The aggregate data is hypothesized in the published paper to represent the overall health of both watersheds with respect to various potential water quality impairments. The time series data for each of the individual water quality parameters were used to compute corresponding risk measures (Rel, Res, and Vul) that are reported in Table 4 and 5. The aggregation of the risk measures, which is computed from the aggregate time series and water quality standards in Table 1, is also reported in Table 4 and 5 of the published paper. Values under column heading uncertainty reports uncertainties associated with reconstruction of missing records of the water quality parameters. Long-term records of the water quality parameters were reconstructed in order to estimate the (R-R-V) and corresponding aggregate risk measures. This dataset is associated with the following publication:Hoque, Y., S. Tripathi, M. Hantush , and R. Govindaraju. Aggregate Measures of Watershed Health from Reconstructed Water Quality Data with Uncertainty. Ed Gregorich JOURNAL OF ENVIRONMENTAL QUALITY. American Society of Agronomy, MADISON, WI,

Gas hydrate characterization from a 3D seismic dataset in the deepwater eastern Gulf of Mexico

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

McConnell, Daniel; Haneberg, William C.

Principal component analysis of spectral decomposition results combined with amplitude and frequency seismic attributes derived from 3D seismic data are used for the identification and characterization of gas hydrate deposits in the deepwater eastern Gulf of Mexico. In the central deepwater Gulf of Mexico (GoM), logging while drilling LWD data provided insight to the amplitude response of gas hydrate saturation in sands, which could be used to characterize complex gas hydrate deposits in other sandy deposits. In this study, a large 3D seismic data set from equivalent and distal Plio Pleistocene sandy channel deposits in the deepwater eastern Gulf ofmore » Mexico is screened for direct hydrocarbon indicators for gas hydrate saturated sands.« less

Marine Mammal Acoustic Monitoring and Habitat Investigation, Southern California Offshore Region

DTIC Science & Technology

2007-11-01

odontocete calls to allow rapid analysis of these large acoustic datasets. The calls of many baleen whale species are stereotyped and well known...common dolphins ( genus Delphinus) from the eastern North Pacific. Pages 1-35 Contributions in Science. Natural History Museum, L.A. County. HUANG, X

A novel weight determination method for time series data aggregation

NASA Astrophysics Data System (ADS)

Xu, Paiheng; Zhang, Rong; Deng, Yong

2017-09-01

Aggregation in time series is of great importance in time series smoothing, predicting and other time series analysis process, which makes it crucial to address the weights in times series correctly and reasonably. In this paper, a novel method to obtain the weights in time series is proposed, in which we adopt induced ordered weighted aggregation (IOWA) operator and visibility graph averaging (VGA) operator and linearly combine the weights separately generated by the two operator. The IOWA operator is introduced to the weight determination of time series, through which the time decay factor is taken into consideration. The VGA operator is able to generate weights with respect to the degree distribution in the visibility graph constructed from the corresponding time series, which reflects the relative importance of vertices in time series. The proposed method is applied to two practical datasets to illustrate its merits. The aggregation of Construction Cost Index (CCI) demonstrates the ability of proposed method to smooth time series, while the aggregation of The Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) illustrate how proposed method maintain the variation tendency of original data.

Composition, buoyancy regulation and fate of ice algal aggregates in the Central Arctic Ocean.

PubMed

Fernández-Méndez, Mar; Wenzhöfer, Frank; Peeken, Ilka; Sørensen, Heidi L; Glud, Ronnie N; Boetius, Antje

2014-01-01

Sea-ice diatoms are known to accumulate in large aggregates in and under sea ice and in melt ponds. There is recent evidence from the Arctic that such aggregates can contribute substantially to particle export when sinking from the ice. The role and regulation of microbial aggregation in the highly seasonal, nutrient- and light-limited Arctic sea-ice ecosystem is not well understood. To elucidate the mechanisms controlling the formation and export of algal aggregates from sea ice, we investigated samples taken in late summer 2011 and 2012, during two cruises to the Eurasian Basin of the Central Arctic Ocean. Spherical aggregates densely packed with pennate diatoms, as well as filamentous aggregates formed by Melosira arctica showed sign of different stages of degradation and physiological stoichiometries, with carbon to chlorophyll a ratios ranging from 110 to 66700, and carbon to nitrogen molar ratios of 8-35 and 9-40, respectively. Sub-ice algal aggregate densities ranged between 1 and 17 aggregates m(-2), maintaining an estimated net primary production of 0.4-40 mg C m(-2) d(-1), and accounted for 3-80% of total phototrophic biomass and up to 94% of local net primary production. A potential factor controlling the buoyancy of the aggregates was light intensity, regulating photosynthetic oxygen production and the amount of gas bubbles trapped within the mucous matrix, even at low ambient nutrient concentrations. Our data-set was used to evaluate the distribution and importance of Arctic algal aggregates as carbon source for pelagic and benthic communities.

Composition, Buoyancy Regulation and Fate of Ice Algal Aggregates in the Central Arctic Ocean

PubMed Central

Fernández-Méndez, Mar; Wenzhöfer, Frank; Peeken, Ilka; Sørensen, Heidi L.; Glud, Ronnie N.; Boetius, Antje

2014-01-01

Sea-ice diatoms are known to accumulate in large aggregates in and under sea ice and in melt ponds. There is recent evidence from the Arctic that such aggregates can contribute substantially to particle export when sinking from the ice. The role and regulation of microbial aggregation in the highly seasonal, nutrient- and light-limited Arctic sea-ice ecosystem is not well understood. To elucidate the mechanisms controlling the formation and export of algal aggregates from sea ice, we investigated samples taken in late summer 2011 and 2012, during two cruises to the Eurasian Basin of the Central Arctic Ocean. Spherical aggregates densely packed with pennate diatoms, as well as filamentous aggregates formed by Melosira arctica showed sign of different stages of degradation and physiological stoichiometries, with carbon to chlorophyll a ratios ranging from 110 to 66700, and carbon to nitrogen molar ratios of 8–35 and 9–40, respectively. Sub-ice algal aggregate densities ranged between 1 and 17 aggregates m−2, maintaining an estimated net primary production of 0.4–40 mg C m−2 d−1, and accounted for 3–80% of total phototrophic biomass and up to 94% of local net primary production. A potential factor controlling the buoyancy of the aggregates was light intensity, regulating photosynthetic oxygen production and the amount of gas bubbles trapped within the mucous matrix, even at low ambient nutrient concentrations. Our data-set was used to evaluate the distribution and importance of Arctic algal aggregates as carbon source for pelagic and benthic communities. PMID:25208058

Circumscription and Taxonomic Arrangement of Nigroboletus roseonigrescens Gen. Et Sp. Nov., a New Member of Boletaceae from Tropical South–Eastern China

PubMed Central

Gelardi, Matteo; Vizzini, Alfredo; Ercole, Enrico; Horak, Egon; Ming, Zhang; Li, Tai–Hui

2015-01-01

Nigroboletus is proposed as a novel genus in family Boletaceae, subfamily Boletoideae, to include N. roseonigrescens, a new boletoid species from tropical environment in south–eastern China. Detailed morphological description, color pictures of both fresh basidiomes in habitat and dried material along with photomicrographs and line drawings of the main anatomical features are provided, supported by a comprehensive phylogeny based on multigene molecular analysis (nrITS, nrLSU, rpb1, rpb2 and tef1-α datasets). Taxonomic placement and evolutionary relationships of Nigroboletus are investigated. PMID:26263180

Anomalous soil radon fluctuations - signal of earthquakes in Nepal and eastern India regions

NASA Astrophysics Data System (ADS)

Deb, Argha; Gazi, Mahasin; Barman, Chiranjib

2016-12-01

The present paper deals with pre-seismic soil radon-222 recorded at two different locations 200 m apart, at Jadavpur University main campus, Kolkata, India. Solid state nuclear track detector method is used for detection of the radioactive radon gas. Two simultaneous 4-month long time series data have been analysed. Anomalous fluctuations in the radon datasets have been observed prior to recent earthquakes in Nepal and eastern India during the monitoring period, mainly, the massive 25th April 7.8 M Nepal earthquake. The simultaneous measurements assist in identifying seismogenic radon precursor efficiently.

Eastern Tropical Pacific Precipitation Response to Zonal SPCZ events

NASA Astrophysics Data System (ADS)

Durán-Quesada, A. M.; Lintner, B. R.

2014-12-01

Extreme El Niño events and warming conditions in the eastern tropical Pacific have been linked to pronounced spatial displacements of the South Pacific Convergence Zone known as "zonal SPCZ" events.. Using a global dataset of Lagrangian back trajectories computed with the FLEXPART model for the period 1980-2013, comprehensive analysis of the 3D circulation characteristics associated with the SPCZ is undertaken. Ten days history of along-trajectory specific humidity, potential vorticity and temperature are reconstructed for zonal SPCZ events as well as other states,, with differences related to El Niño intensity and development stage as well as the state of the Western Hemisphere Warm Pool. How zonal events influence precipitation over the Eastern Tropical Pacific is examined using back trajectories, reanalysis, TRMM precipitation, and additional satellite derived cloud information. It is found that SPCZ displacements are associated with enhanced convection over the Eastern Tropical Pacific in good agreement with prior work. The connection between intensification of precipitation over the eastern Tropical Pacific during zonal events and suppression of rainfall over the Maritime continent is also described.

Genetic dating indicates that the Asian–Papuan admixture through Eastern Indonesia corresponds to the Austronesian expansion

PubMed Central

Xu, Shuhua; Pugach, Irina; Stoneking, Mark; Kayser, Manfred; Jin, Li

2012-01-01

Although the Austronesian expansion had a major impact on the languages of Island Southeast Asia, controversy still exists over the genetic impact of this expansion. The coexistence of both Asian and Papuan genetic ancestry in Eastern Indonesia provides a unique opportunity to address this issue. Here, we estimate recombination breakpoints in admixed genomes based on genome-wide SNP data and date the genetic admixture between populations of Asian vs. Papuan ancestry in Eastern Indonesia. Analyses of two genome-wide datasets indicate an eastward progression of the Asian admixture signal in Eastern Indonesia beginning about 4,000–3,000 y ago, which is in excellent agreement with inferences based on Austronesian languages. The average rate of spread of Asian genes in Eastern Indonesia was about 0.9 km/y. Our results indicate that the Austronesian expansion had a strong genetic as well as linguistic impact on Island Southeast Asia, and they significantly advance our understanding of the biological origins of human populations in the Asia–Pacific region. PMID:22396590

Velocity Field of the McMurdo Shear Zone from Annual Three-Dimensional Ground Penetrating Radar Imaging and Crevasse Matching

NASA Astrophysics Data System (ADS)

Ray, L.; Jordan, M.; Arcone, S. A.; Kaluzienski, L. M.; Koons, P. O.; Lever, J.; Walker, B.; Hamilton, G. S.

2017-12-01

The McMurdo Shear Zone (MSZ) is a narrow, intensely crevassed strip tens of km long separating the Ross and McMurdo ice shelves (RIS and MIS) and an important pinning feature for the RIS. We derive local velocity fields within the MSZ from two consecutive annual ground penetrating radar (GPR) datasets that reveal complex firn and marine ice crevassing; no englacial features are evident. The datasets were acquired in 2014 and 2015 using robot-towed 400 MHz and 200 MHz GPR over a 5 km x 5.7 km grid. 100 west-to-east transects at 50 m spacing provide three-dimensional maps that reveal the length of many firn crevasses, and their year-to-year structural evolution. Hand labeling of crevasse cross sections near the MSZ western and eastern boundaries reveal matching firn and marine ice crevasses, and more complex and chaotic features between these boundaries. By matching crevasse features from year to year both on the eastern and western boundaries and within the chaotic region, marine ice crevasses along the western and eastern boundaries are shown to align directly with firn crevasses, and the local velocity field is estimated and compared with data from strain rate surveys and remote sensing. While remote sensing provides global velocity fields, crevasse matching indicates greater local complexity attributed to faulting, folding, and rotation.

Epidaurus: aggregation and integration analysis of prostate cancer epigenome.

PubMed

Wang, Liguo; Huang, Haojie; Dougherty, Gregory; Zhao, Yu; Hossain, Asif; Kocher, Jean-Pierre A

2015-01-01

Integrative analyses of epigenetic data promise a deeper understanding of the epigenome. Epidaurus is a bioinformatics tool used to effectively reveal inter-dataset relevance and differences through data aggregation, integration and visualization. In this study, we demonstrated the utility of Epidaurus in validating hypotheses and generating novel biological insights. In particular, we described the use of Epidaurus to (i) integrate epigenetic data from prostate cancer cell lines to validate the activation function of EZH2 in castration-resistant prostate cancer and to (ii) study the mechanism of androgen receptor (AR) binding deregulation induced by the knockdown of FOXA1. We found that EZH2's noncanonical activation function was reaffirmed by its association with active histone markers and the lack of association with repressive markers. More importantly, we revealed that the binding of AR was selectively reprogramed to promoter regions, leading to the up-regulation of hundreds of cancer-associated genes including EGFR. The prebuilt epigenetic dataset from commonly used cell lines (LNCaP, VCaP, LNCaP-Abl, MCF7, GM12878, K562, HeLa-S3, A549, HePG2) makes Epidaurus a useful online resource for epigenetic research. As standalone software, Epidaurus is specifically designed to process user customized datasets with both efficiency and convenience. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Pantheon 1.0, a manually verified dataset of globally famous biographies.

PubMed

Yu, Amy Zhao; Ronen, Shahar; Hu, Kevin; Lu, Tiffany; Hidalgo, César A

2016-01-05

We present the Pantheon 1.0 dataset: a manually verified dataset of individuals that have transcended linguistic, temporal, and geographic boundaries. The Pantheon 1.0 dataset includes the 11,341 biographies present in more than 25 languages in Wikipedia and is enriched with: (i) manually verified demographic information (place and date of birth, gender) (ii) a taxonomy of occupations classifying each biography at three levels of aggregation and (iii) two measures of global popularity including the number of languages in which a biography is present in Wikipedia (L), and the Historical Popularity Index (HPI) a metric that combines information on L, time since birth, and page-views (2008-2013). We compare the Pantheon 1.0 dataset to data from the 2003 book, Human Accomplishments, and also to external measures of accomplishment in individual games and sports: Tennis, Swimming, Car Racing, and Chess. In all of these cases we find that measures of popularity (L and HPI) correlate highly with individual accomplishment, suggesting that measures of global popularity proxy the historical impact of individuals.

Pantheon 1.0, a manually verified dataset of globally famous biographies

PubMed Central

Yu, Amy Zhao; Ronen, Shahar; Hu, Kevin; Lu, Tiffany; Hidalgo, César A.

2016-01-01

We present the Pantheon 1.0 dataset: a manually verified dataset of individuals that have transcended linguistic, temporal, and geographic boundaries. The Pantheon 1.0 dataset includes the 11,341 biographies present in more than 25 languages in Wikipedia and is enriched with: (i) manually verified demographic information (place and date of birth, gender) (ii) a taxonomy of occupations classifying each biography at three levels of aggregation and (iii) two measures of global popularity including the number of languages in which a biography is present in Wikipedia (L), and the Historical Popularity Index (HPI) a metric that combines information on L, time since birth, and page-views (2008–2013). We compare the Pantheon 1.0 dataset to data from the 2003 book, Human Accomplishments, and also to external measures of accomplishment in individual games and sports: Tennis, Swimming, Car Racing, and Chess. In all of these cases we find that measures of popularity (L and HPI) correlate highly with individual accomplishment, suggesting that measures of global popularity proxy the historical impact of individuals. PMID:26731133

Enhancing studies of the connectome in autism using the autism brain imaging data exchange II

PubMed Central

Di Martino, Adriana; O’Connor, David; Chen, Bosi; Alaerts, Kaat; Anderson, Jeffrey S.; Assaf, Michal; Balsters, Joshua H.; Baxter, Leslie; Beggiato, Anita; Bernaerts, Sylvie; Blanken, Laura M. E.; Bookheimer, Susan Y.; Braden, B. Blair; Byrge, Lisa; Castellanos, F. Xavier; Dapretto, Mirella; Delorme, Richard; Fair, Damien A.; Fishman, Inna; Fitzgerald, Jacqueline; Gallagher, Louise; Keehn, R. Joanne Jao; Kennedy, Daniel P.; Lainhart, Janet E.; Luna, Beatriz; Mostofsky, Stewart H.; Müller, Ralph-Axel; Nebel, Mary Beth; Nigg, Joel T.; O’Hearn, Kirsten; Solomon, Marjorie; Toro, Roberto; Vaidya, Chandan J.; Wenderoth, Nicole; White, Tonya; Craddock, R. Cameron; Lord, Catherine; Leventhal, Bennett; Milham, Michael P.

2017-01-01

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity. PMID:28291247

The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes.

PubMed

Kelly, Jack; Knottenbelt, William

2015-01-01

Many countries are rolling out smart electricity meters. These measure a home's total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with itemised, appliance-by-appliance consumption information. Energy disaggregation is a computational technique for estimating appliance-by-appliance energy consumption from a whole-house meter signal. To conduct research on disaggregation algorithms, researchers require data describing not just the aggregate demand per building but also the 'ground truth' demand of individual appliances. In this context, we present UK-DALE: an open-access dataset from the UK recording Domestic Appliance-Level Electricity at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual appliances. This is the first open access UK dataset at this temporal resolution. We recorded from five houses, one of which was recorded for 655 days, the longest duration we are aware of for any energy dataset at this sample rate. We also describe the low-cost, open-source, wireless system we built for collecting our dataset.

OpenSHS: Open Smart Home Simulator.

PubMed

Alshammari, Nasser; Alshammari, Talal; Sedky, Mohamed; Champion, Justin; Bauer, Carolin

2017-05-02

This paper develops a new hybrid, open-source, cross-platform 3D smart home simulator, OpenSHS, for dataset generation. OpenSHS offers an opportunity for researchers in the field of the Internet of Things (IoT) and machine learning to test and evaluate their models. Following a hybrid approach, OpenSHS combines advantages from both interactive and model-based approaches. This approach reduces the time and efforts required to generate simulated smart home datasets. We have designed a replication algorithm for extending and expanding a dataset. A small sample dataset produced, by OpenSHS, can be extended without affecting the logical order of the events. The replication provides a solution for generating large representative smart home datasets. We have built an extensible library of smart devices that facilitates the simulation of current and future smart home environments. Our tool divides the dataset generation process into three distinct phases: first design: the researcher designs the initial virtual environment by building the home, importing smart devices and creating contexts; second, simulation: the participant simulates his/her context-specific events; and third, aggregation: the researcher applies the replication algorithm to generate the final dataset. We conducted a study to assess the ease of use of our tool on the System Usability Scale (SUS).

OpenSHS: Open Smart Home Simulator

PubMed Central

Alshammari, Nasser; Alshammari, Talal; Sedky, Mohamed; Champion, Justin; Bauer, Carolin

2017-01-01

This paper develops a new hybrid, open-source, cross-platform 3D smart home simulator, OpenSHS, for dataset generation. OpenSHS offers an opportunity for researchers in the field of the Internet of Things (IoT) and machine learning to test and evaluate their models. Following a hybrid approach, OpenSHS combines advantages from both interactive and model-based approaches. This approach reduces the time and efforts required to generate simulated smart home datasets. We have designed a replication algorithm for extending and expanding a dataset. A small sample dataset produced, by OpenSHS, can be extended without affecting the logical order of the events. The replication provides a solution for generating large representative smart home datasets. We have built an extensible library of smart devices that facilitates the simulation of current and future smart home environments. Our tool divides the dataset generation process into three distinct phases: first design: the researcher designs the initial virtual environment by building the home, importing smart devices and creating contexts; second, simulation: the participant simulates his/her context-specific events; and third, aggregation: the researcher applies the replication algorithm to generate the final dataset. We conducted a study to assess the ease of use of our tool on the System Usability Scale (SUS). PMID:28468330

Exploring the Impact of Chronic Tic Disorders on Youth: Results from the Tourette Syndrome Impact Survey

ERIC Educational Resources Information Center

Conelea, Christine A.; Woods, Douglas W.; Zinner, Samuel H.; Budman, Cathy; Murphy, Tanya; Scahill, Lawrence D.; Compton, Scott N.; Walkup, John

2011-01-01

Prior research has demonstrated that chronic tic disorders (CTD) are associated with functional impairment across several domains. However, methodological limitations, such as data acquired by parental report, datasets aggregated across child and adult samples, and small treatment-seeking samples, curtail interpretation. The current study explored…

Data regarding hydraulic fracturing distributions and treatment fluids, additives, proppants, and water volumes applied to wells drilled in the United States from 1947 through 2010

USGS Publications Warehouse

Gallegos, Tanya J.; Varela, Brian A.

2015-01-01

Comprehensive, published, and publicly available data regarding the extent, location, and character of hydraulic fracturing in the United States are scarce. The objective of this data series is to publish data related to hydraulic fracturing in the public domain. The spreadsheets released with this data series contain derivative datasets aggregated temporally and spatially from the commercial and proprietary IHS database of U.S. oil and gas production and well data (IHS Energy, 2011). These datasets, served in 21 spreadsheets in Microsoft Excel (.xlsx) format, outline the geographical distributions of hydraulic fracturing treatments and associated wells (including well drill-hole directions) as well as water volumes, proppants, treatment fluids, and additives used in hydraulic fracturing treatments in the United States from 1947 through 2010. This report also describes the data—extraction/aggregation processing steps, field names and descriptions, field types and sources. An associated scientific investigation report (Gallegos and Varela, 2014) provides a detailed analysis of the data presented in this data series and comparisons of the data and trends to the literature.

Interactions between commercial fishing and walleye pollock aggregations

NASA Astrophysics Data System (ADS)

Stienessen, Sarah; Wilson, Chris D.; Hallowed, Anne B.

2002-05-01

Scientists with the Alaska Fisheries Science Center are conducting a multiyear field experiment off the eastern side of Kodiak Island in the Gulf of Alaska to determine whether commercial fishing activities significantly affect the distribution and abundance of walleye pollock (Theragra chalcogramma), an important prey species of endangered Steller sea lions (Eumetopias jubatus). In support of this activity, spatio-temporal patterns were described for pollock aggregations. Acoustic-trawl surveys were conducted in two adjacent submarine troughs in August 2001. One trough served as a control site where fishing was prohibited and the other as a treatment site where fishing was allowed. Software, which included patch recognition algorithms, was used to extract acoustic data and generate patch size and shape-related variables to analyze fish aggregations. Important patch related descriptors included skewness, kurtosis, length, height, and density. Estimates of patch fractal dimensions, which relate school perimeter to school area, were less for juvenile than for adult aggregations, indicating a more complex school shape for adults. Comparisons of other patch descriptors were made between troughs and in the presence and absence of the fishery to determine whether trends in pollock aggregation dynamics were a result of the fishery or of naturally occurring events.

Geostatistical Characterization of Cereal Leaf Beetle (Coleoptera: Chrysomelidae) Distributions in Wheat.

PubMed

Reay-Jones, Francis P F

2017-08-01

A 3-yr study was conducted in wheat, Triticum aestivum L., in South Carolina to characterize the spatial distribution of Oulema melanopus (L.) adults, eggs, and larvae using semivariograms, which provides a measure of spatial dependence among sampling data. Moran's I coefficients for peak densities of each life stage indicated significant positive autocorrelation for seven (two for eggs, one for larvae, and four for adults) of the 16 datasets. Aggregation was detected in 13 of these 16 datasets when analyzed by semivariogram modeling, with spherical, Gaussian, and exponential models best fitting for eight, four, and one dataset, respectively, and with models for two datasets having only one parameter (nugget) significantly different from zero. The nugget-to-sill ratios ranged from 0.043 to 0.774, and indicated strong spatial dependence in six models (three for adults, two for eggs, and one for larvae), moderate spatial dependence in six models (three for adults and six for eggs), and weak spatial dependence in one model (adults). Range values varied from 39.1 m to 234.1 m, with an average of 120.1 ± 14.0 m. Average range values were 104.9, 135.2, and 161.2 m for adults, eggs, and larvae, respectively. Because the majority of semivariogram models in our study indicated aggregated distributions, spatial sampling will provide more information than nonspatial random sampling. Developing our understanding of spatial dependence of crop pests is needed to optimize sampling plans and can provide a basis for exploring site-specific management tactics. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Enhancing access and usage of earth observations to support environmental decision making in Eastern and Southern Africa

NASA Astrophysics Data System (ADS)

Shukla, S.; Husak, G. J.; Macharia, D.; Peterson, P.; Landsfeld, M. F.; Funk, C.; Flores, A.

2017-12-01

Remote sensing, reanalysis and model based earth observations (EOs) are crucial for environmental decision making, particularly in a region like Eastern and Southern Africa, where ground-based observations are sparse. NASA and the Famine Early Warning System Network (FEWS NET) provide several EOs relevant for monitoring, providing early warning of agroclimatic conditions. Nonetheless, real-time application of those EOs for decision making in the region is still limited. This presentation reports on an ongoing SERVIR-supported Applied Science Team (AST) project that aims to fill that gap by working in close collaboration with Regional Centre for Mapping of Resources for Development (RCMRD), the NASA SERVIR regional hub. The three main avenues being taken to enhance access and usage of EOs in the region are: (1) Transition and implementation of web-based tools to RCMRD to allow easy processing and visualization of EOs (2) Capacity building of personnel from regional and national agroclimate service agencies in using EOs, through training using targeted case studies, and (3) Development of new datasets to meet the specific needs of RCMRD and regional stakeholders. The presentation will report on the initial success, lessons learned, and feedback thus far in this project regarding the implementation of web-based tool and capacity building efforts. It will also briefly describe three new datasets, currently in development, to improve agroclimate monitoring in the region, which are: (1) Satellite infrared and stations based temperature maximum dataset (CHIRTS) (2) NASA's GEOS5 and NCEP's CFSv2 based seasonal scale reference evapotranspiration forecasts and (3) NCEP's GEFS based medium range weather forecasts which are bias-corrected to USGS and UCSB's rainfall monitoring dataset (CHIRPS).

SPICE: exploration and analysis of post-cytometric complex multivariate datasets.

PubMed

Roederer, Mario; Nozzi, Joshua L; Nason, Martha C

2011-02-01

Polychromatic flow cytometry results in complex, multivariate datasets. To date, tools for the aggregate analysis of these datasets across multiple specimens grouped by different categorical variables, such as demographic information, have not been optimized. Often, the exploration of such datasets is accomplished by visualization of patterns with pie charts or bar charts, without easy access to statistical comparisons of measurements that comprise multiple components. Here we report on algorithms and a graphical interface we developed for these purposes. In particular, we discuss thresholding necessary for accurate representation of data in pie charts, the implications for display and comparison of normalized versus unnormalized data, and the effects of averaging when samples with significant background noise are present. Finally, we define a statistic for the nonparametric comparison of complex distributions to test for difference between groups of samples based on multi-component measurements. While originally developed to support the analysis of T cell functional profiles, these techniques are amenable to a broad range of datatypes. Published 2011 Wiley-Liss, Inc.

Projected entrainment of fish resulting from aggregate dredging.

PubMed

Drabble, Ray

2012-02-01

Previous research to assess impacts from aggregate dredging has focussed on infaunal species with few studies made of fish entrainment. Entrainment evidence from hydraulic dredging studies is reviewed to develop a sensitivity index for benthic fish. Environmental monitoring attendant with the granting of new licences in the Eastern Channel Region (ECR) in 2006 offers a unique opportunity to assess the effects of dredging upon fish. Projected theoretical fish entrainment rates are calculated based upon: abundance data from 4m beam trawl sampling of fish species over the period 2005-2008; sensitivity data; and dredging activity and footprint derived from Electronic monitoring System (EMS) data. Results have been compared with actual entrainment rates and also against summary results from independent analysis of the changes in fish population over the period 2005-2008 (Drabble, 2012). The case is made for entrainment surveys to form part of impact monitoring for marine aggregate dredging. Copyright © 2011 Elsevier Ltd. All rights reserved.

Drought Variability in Eastern Part of Romania and its Connection with Large-Scale Air Circulation

NASA Astrophysics Data System (ADS)

Barbu, Nicu; Stefan, Sabina; Georgescu, Florinela

2014-05-01

Drought is a phenomenon that appears due to precipitation deficit and it is intensified by strong winds, high temperatures, low relative humidity and high insolation; in fact, all these factors lead to increasing of evapotranspiration processes that contribute to soil water deficit. The Standardized Precipitation Evapotranspiration Index (SPEI) take into account all this factors listed above. The temporal variability of the drought in Eastern part of Romania for 50 years, during the period 1961-2010, is investigated. This study is focused on the drought variability related to large scale air circulation. The gridded dataset with spatial resolution of 0.5º lat/lon of SPEI, (https://digital.csic.es/handle/10261/72264) were used to analyze drought periods in connection with large scale air circulation determinate from the two catalogues (GWT - GrossWetter-Typen and WLK - WetterLargenKlassifikation) defined in COST733Action. The GWT catalogue uses at input dataset the sea level pressure and the WLK catalogue uses as input dataset the geopotential field at 925 hPa and 500 hPa, wind at 700 hPa and total water content for entire atmospheric column. In this study we use the GWT catalogue with 18 circulation types and the WLK catalogue with 40 circulation types. The analysis for Barlad Hydrological Basin indicated that the negative values (that means water deficit - drought period) of SPEI are associated with prevailing anticyclonic regime and positive values (that means water excess - rainy period) of SPEI are associated with prevailing cyclonic regime as was expected. In last decade was observed an increase of dry period associated with an increase of anticyclonic activity over Romania. Using GWT18 catalogue the drought are associated with the north-eastern anticyclonic circulation type (NE-A). According to the WLK40 catalogue, the dominant circulation type associated with the drought is north-west-anticyclonic-dry anticyclonic (NW-AAD) type. keywords: drought, SPEI, large-scale atmospheric circulation

Damage and protection cost curves for coastal floods within the 600 largest European cities

NASA Astrophysics Data System (ADS)

Prahl, Boris F.; Boettle, Markus; Costa, Luís; Kropp, Jürgen P.; Rybski, Diego

2018-03-01

The economic assessment of the impacts of storm surges and sea-level rise in coastal cities requires high-level information on the damage and protection costs associated with varying flood heights. We provide a systematically and consistently calculated dataset of macroscale damage and protection cost curves for the 600 largest European coastal cities opening the perspective for a wide range of applications. Offering the first comprehensive dataset to include the costs of dike protection, we provide the underpinning information to run comparative assessments of costs and benefits of coastal adaptation. Aggregate cost curves for coastal flooding at the city-level are commonly regarded as by-products of impact assessments and are generally not published as a standalone dataset. Hence, our work also aims at initiating a more critical discussion on the availability and derivation of cost curves.

Damage and protection cost curves for coastal floods within the 600 largest European cities.

PubMed

Prahl, Boris F; Boettle, Markus; Costa, Luís; Kropp, Jürgen P; Rybski, Diego

2018-03-20

The economic assessment of the impacts of storm surges and sea-level rise in coastal cities requires high-level information on the damage and protection costs associated with varying flood heights. We provide a systematically and consistently calculated dataset of macroscale damage and protection cost curves for the 600 largest European coastal cities opening the perspective for a wide range of applications. Offering the first comprehensive dataset to include the costs of dike protection, we provide the underpinning information to run comparative assessments of costs and benefits of coastal adaptation. Aggregate cost curves for coastal flooding at the city-level are commonly regarded as by-products of impact assessments and are generally not published as a standalone dataset. Hence, our work also aims at initiating a more critical discussion on the availability and derivation of cost curves.

Tripartite community structure in social bookmarking data

NASA Astrophysics Data System (ADS)

Neubauer, Nicolas; Obermayer, Klaus

2011-12-01

Community detection is a branch of network analysis concerned with identifying strongly connected subnetworks. Social bookmarking sites aggregate datasets of often hundreds of millions of triples (document, user, and tag), which, when interpreted as edges of a graph, give rise to special networks called 3-partite, 3-uniform hypergraphs. We identify challenges and opportunities of generalizing community detection and in particular modularity optimization to these structures. Two methods for community detection are introduced that preserve the hypergraph's special structure to different degrees. Their performance is compared on synthetic datasets, showing the benefits of structure preservation. Furthermore, a tool for interactive exploration of the community detection results is introduced and applied to examples from real datasets. We find additional evidence for the importance of structure preservation and, more generally, demonstrate how tripartite community detection can help understand the structure of social bookmarking data.

A comparison of NLCD 2011 and LANDFIRE EVT 2010: Regional and national summaries.

USGS Publications Warehouse

McKerrow, Alexa; Dewitz, Jon; Long, Donald G.; Nelson, Kurtis; Connot, Joel A.; Smith, Jim

2016-01-01

In order to provide the land cover user community a summary of the similarity and differences between the 2011 National Land Cover Dataset (NLCD) and the Landscape Fire and Resource Management Planning Tools Program Existing Vegetation 2010 Data (LANDFIRE EVT), the two datasets were compared at a national (conterminous U.S.) and regional (Eastern, Midwestern, and Western) extents (Figure 1). The comparisons were done by generalizing the LANDFIRE data to be consistent with mapped land cover classes in the NLCD (i.e., crosswalked). Summaries of the comparisons were based on areal extent including 1) the total extent of each land cover class, and 2) land cover classes in corresponding 900-m2 areas. The results from the comparisons provide the user community information regarding the utility of both datasets relative to their intended uses.

Landscape risk factors for Lyme disease in the eastern broadleaf forest province of the Hudson River valley and the effect of explanatory data classification resolution.

PubMed

Messier, Kyle P; Jackson, Laura E; White, Jennifer L; Hilborn, Elizabeth D

2015-01-01

This study assessed how landcover classification affects associations between landscape characteristics and Lyme disease rate. Landscape variables were derived from the National Land Cover Database (NLCD), including native classes (e.g., deciduous forest, developed low intensity) and aggregate classes (e.g., forest, developed). Percent of each landcover type, median income, and centroid coordinates were calculated by census tract. Regression results from individual and aggregate variable models were compared with the dispersion parameter-based R(2) (Rα(2)) and AIC. The maximum Rα(2) was 0.82 and 0.83 for the best aggregate and individual model, respectively. The AICs for the best models differed by less than 0.5%. The aggregate model variables included forest, developed, agriculture, agriculture-squared, y-coordinate, y-coordinate-squared, income and income-squared. The individual model variables included deciduous forest, deciduous forest-squared, developed low intensity, pasture, y-coordinate, y-coordinate-squared, income, and income-squared. Results indicate that regional landscape models for Lyme disease rate are robust to NLCD landcover classification resolution. Published by Elsevier Ltd.

Reconstructing Druze population history.

PubMed

Marshall, Scarlett; Das, Ranajit; Pirooznia, Mehdi; Elhaik, Eran

2016-11-16

The Druze are an aggregate of communities in the Levant and Near East living almost exclusively in the mountains of Syria, Lebanon and Israel whose ~1000 year old religion formally opposes mixed marriages and conversions. Despite increasing interest in genetics of the population structure of the Druze, their population history remains unknown. We investigated the genetic relationships between Israeli Druze and both modern and ancient populations. We evaluated our findings in light of three hypotheses purporting to explain Druze history that posit Arabian, Persian or mixed Near Eastern-Levantine roots. The biogeographical analysis localised proto-Druze to the mountainous regions of southeastern Turkey, northern Iraq and southeast Syria and their descendants clustered along a trajectory between these two regions. The mixed Near Eastern-Middle Eastern localisation of the Druze, shown using both modern and ancient DNA data, is distinct from that of neighbouring Syrians, Palestinians and most of the Lebanese, who exhibit a high affinity to the Levant. Druze biogeographic affinity, migration patterns, time of emergence and genetic similarity to Near Eastern populations are highly suggestive of Armenian-Turkish ancestries for the proto-Druze.

Electronic Journals in Aggregated Collections: Providing Access through the Catalog and a Cold Fusion Database

ERIC Educational Resources Information Center

Anderson, Sue

2005-01-01

Patrons in academic libraries want convenient 24-hour access to full-text journals in a rapid, convenient manner. They want "anytime, anywhere" access to information and they do not want to enter a library to obtain it. This article describes how Eastern Washington University Libraries provide access to full-text journals through several…

Graphical display of histopathology data from toxicology studies for drug discovery and development: An industry perspective.

PubMed

Brown, Alan P; Drew, Philip; Knight, Brian; Marc, Philippe; Troth, Sean; Wuersch, Kuno; Zandee, Joyce

2016-12-01

Histopathology data comprise a critical component of pharmaceutical toxicology studies and are typically presented as finding incidence counts and severity scores per organ, and tabulated on multiple pages which can be challenging for review and aggregation of results. However, the SEND (Standard for Exchange of Nonclinical Data) standard provides a means for collecting and managing histopathology data in a uniform fashion which can allow informatics systems to archive, display and analyze data in novel ways. Various software applications have become available to convert histopathology data into graphical displays for analyses. A subgroup of the FDA-PhUSE Nonclinical Working Group conducted intra-industry surveys regarding the use of graphical displays of histopathology data. Visual cues, use-cases, the value of cross-domain and cross-study visualizations, and limitations were topics for discussion in the context of the surveys. The subgroup came to the following conclusions. Graphical displays appear advantageous as a communication tool to both pathologists and non-pathologists, and provide an efficient means for communicating pathology findings to project teams. Graphics can support hypothesis-generation which could include cross-domain interactive visualizations and/-or aggregating large datasets from multiple studies to observe and/or display patterns and trends. Incorporation of the SEND standard will provide a platform by which visualization tools will be able to aggregate, select and display information from complex and disparate datasets. Copyright © 2016 Elsevier Inc. All rights reserved.

Co-Infestation and Spatial Distribution of Bactrocera carambolae and Anastrepha spp. (Diptera: Tephritidae) in Common Guava in the Eastern Amazon

PubMed Central

Deus, E. G.; Godoy, W. A. C.; Sousa, M. S. M.; Lopes, G. N.; Jesus-Barros, C. R.; Silva, J. G.; Adaime, R.

2016-01-01

Field infestation and spatial distribution of introduced Bactrocera carambolae Drew and Hancock and native species of Anastrepha in common guavas [Psidium guajava (L.)] were investigated in the eastern Amazon. Fruit sampling was carried out in the municipalities of Calçoene and Oiapoque in the state of Amapá, Brazil. The frequency distribution of larvae in fruit was fitted to the negative binomial distribution. Anastrepha striata was more abundant in both sampled areas in comparison to Anastrepha fraterculus (Wiedemann) and B. carambolae. The frequency distribution analysis of adults revealed an aggregated pattern for B. carambolae as well as for A. fraterculus and Anastrepha striata Schiner, described by the negative binomial distribution. Although the populations of Anastrepha spp. may have suffered some impact due to the presence of B. carambolae, the results are still not robust enough to indicate effective reduction in the abundance of Anastrepha spp. caused by B. carambolae in a general sense. The high degree of aggregation observed for both species suggests interspecific co-occurrence with the simultaneous presence of both species in the analysed fruit. Moreover, a significant fraction of uninfested guavas also indicated absence of competitive displacement. PMID:27638949

A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring

USGS Publications Warehouse

Metzger, Marc J.; Bunce, Robert G.H.; Jongman, Rob H.G.; Sayre, Roger G.; Trabucco, Antonio; Zomer, Robert

2013-01-01

Main conclusions: The GEnS provides a robust spatial analytical framework for the aggregation of local observations, identification of gaps in current monitoring efforts and systematic design of complementary and new monitoring and research. The dataset is available for non-commercial use through the GEO portal (http://www.geoportal.org).

Educational Choices and the Selection Process: Before and after Compulsory Schooling

ERIC Educational Resources Information Center

Mocetti, Sauro

2012-01-01

The aim of this paper is to analyze the selection process at work before and after compulsory schooling by assessing the determinants of school failures, dropouts, and upper secondary school decisions of young Italians. The data-set is built combining individual data by the Labor Force Survey and aggregate data on local labor markets and school…

Dataset of aggregate producers in New Mexico

USGS Publications Warehouse

Orris, Greta J.

2000-01-01

This report presents data, including latitude and longitude, for aggregate sites in New Mexico that were believed to be active in the period 1997-1999. The data are presented in paper form in Part A of this report and as Microsoft Excel 97 and Data Interchange Format (DIF) files in Part B. The work was undertaken as part of the effort to update information for the National Atlas. This compilation includes data from: the files of U.S. Geological Survey (USGS); company contacts; the New Mexico Bureau of Mines and Mineral Resources, New Mexico Bureau of Mine Inspection, and the Mining and Minerals Division of the New Mexico Energy, Minerals and Natural Resources Department (Hatton and others, 1998); the Bureau of Land Management Information; and direct communications with some of the aggregate operators. Additional information on most of the sites is available in Hatton and others (1998).

Decision Making Based on Fuzzy Aggregation Operators for Medical Diagnosis from Dental X-ray images.

PubMed

Ngan, Tran Thi; Tuan, Tran Manh; Son, Le Hoang; Minh, Nguyen Hai; Dey, Nilanjan

2016-12-01

Medical diagnosis is considered as an important step in dentistry treatment which assists clinicians to give their decision about diseases of a patient. It has been affirmed that the accuracy of medical diagnosis, which is much influenced by the clinicians' experience and knowledge, plays an important role to effective treatment therapies. In this paper, we propose a novel decision making method based on fuzzy aggregation operators for medical diagnosis from dental X-Ray images. It firstly divides a dental X-Ray image into some segments and identified equivalent diseases by a classification method called Affinity Propagation Clustering (APC+). Lastly, the most potential disease is found using fuzzy aggregation operators. The experimental validation on real dental datasets of Hanoi Medical University Hospital, Vietnam showed the superiority of the proposed method against the relevant ones in terms of accuracy.

The African Crane Database (1978-2014): Records of three threatened crane species (Family: Gruidae) from southern and eastern Africa.

PubMed

Smith, Tanya; Page-Nicholson, Samantha; Morrison, Kerryn; Gibbons, Bradley; Jones, M Genevieve W; van Niekerk, Mark; Botha, Bronwyn; Oliver, Kirsten; McCann, Kevin; Roxburgh, Lizanne

2016-01-01

The International Crane Foundation (ICF) / Endangered Wildlife Trust's (EWT) African Crane Conservation Programme has recorded 26 403 crane sightings in its database from 1978 to 2014. This sightings collection is currently ongoing and records are continuously added to the database by the EWT field staff, ICF/EWT Partnership staff, various partner organizations and private individuals. The dataset has two peak collection periods: 1994-1996 and 2008-2012. The dataset collection spans five African countries: Kenya, Rwanda, South Africa, Uganda and Zambia; 98% of the data were collected in South Africa. Georeferencing of the dataset was verified before publication of the data. The dataset contains data on three African crane species: Blue Crane Anthropoides paradiseus , Grey Crowned Crane Balearica regulorum and Wattled Crane Bugeranus carunculatus . The Blue and Wattled Cranes are classified by the IUCN Red List of Threatened Species as Vulnerable and the Grey Crowned Crane as Endangered. This is the single most comprehensive dataset published on African Crane species that adds new information about the distribution of these three threatened species. We hope this will further aid conservation authorities to monitor and protect these species. The dataset continues to grow and especially to expand in geographic coverage into new countries in Africa and new sites within countries. The dataset can be freely accessed through the Global Biodiversity Information Facility data portal.

The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes

PubMed Central

Kelly, Jack; Knottenbelt, William

2015-01-01

Many countries are rolling out smart electricity meters. These measure a home’s total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with itemised, appliance-by-appliance consumption information. Energy disaggregation is a computational technique for estimating appliance-by-appliance energy consumption from a whole-house meter signal. To conduct research on disaggregation algorithms, researchers require data describing not just the aggregate demand per building but also the ‘ground truth’ demand of individual appliances. In this context, we present UK-DALE: an open-access dataset from the UK recording Domestic Appliance-Level Electricity at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual appliances. This is the first open access UK dataset at this temporal resolution. We recorded from five houses, one of which was recorded for 655 days, the longest duration we are aware of for any energy dataset at this sample rate. We also describe the low-cost, open-source, wireless system we built for collecting our dataset. PMID:25984347

The UK-DALE dataset, domestic appliance-level electricity demand and whole-house demand from five UK homes

NASA Astrophysics Data System (ADS)

Kelly, Jack; Knottenbelt, William

2015-03-01

Many countries are rolling out smart electricity meters. These measure a home’s total power demand. However, research into consumer behaviour suggests that consumers are best able to improve their energy efficiency when provided with itemised, appliance-by-appliance consumption information. Energy disaggregation is a computational technique for estimating appliance-by-appliance energy consumption from a whole-house meter signal. To conduct research on disaggregation algorithms, researchers require data describing not just the aggregate demand per building but also the ‘ground truth’ demand of individual appliances. In this context, we present UK-DALE: an open-access dataset from the UK recording Domestic Appliance-Level Electricity at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual appliances. This is the first open access UK dataset at this temporal resolution. We recorded from five houses, one of which was recorded for 655 days, the longest duration we are aware of for any energy dataset at this sample rate. We also describe the low-cost, open-source, wireless system we built for collecting our dataset.

Example MODIS Global Cloud Optical and Microphysical Properties: Comparisons between Terra and Aqua

NASA Technical Reports Server (NTRS)

Hubanks, P. A.; Platnick, S.; King, M. D.; Ackerman, S. A.; Frey, R. A.

2003-01-01

MODIS observations from the NASA EOS Terra spacecraft (launched in December 1999, 1030 local time equatorial crossing) have provided a unique data set of Earth observations. With the launch of the NASA Aqua spacecraft in May 2002 (1330 local time), two MODIS daytime (sunlit) and nighttime observations are now available in a 24 hour period, allowing for some measure of diurnal variability. We report on an initial analysis of several operational global (Level-3) cloud products from the two platforms. The MODIS atmosphere Level-3 products, which include clear-sky and aerosol products in addition to cloud products, are available as three separate files providing daily, eight-day, and monthly aggregations; each temporal aggregation is spatially aggregated to a 1 degree grid. The files contain approximately 600 statisitical datasets (from simple means and standard deviations to 1 - and 2-dimensional histograms). Operational cloud products include detection (cloud fraction), cloud-top properties, and daytimeonly cloud optical thickness and particle effective radius for both water and ice clouds. We will compare example global Terra and Aqua cloud fraction, optical thickness, and effective radius aggregations.

Ensemble of sparse classifiers for high-dimensional biological data.

PubMed

Kim, Sunghan; Scalzo, Fabien; Telesca, Donatello; Hu, Xiao

2015-01-01

Biological data are often high in dimension while the number of samples is small. In such cases, the performance of classification can be improved by reducing the dimension of data, which is referred to as feature selection. Recently, a novel feature selection method has been proposed utilising the sparsity of high-dimensional biological data where a small subset of features accounts for most variance of the dataset. In this study we propose a new classification method for high-dimensional biological data, which performs both feature selection and classification within a single framework. Our proposed method utilises a sparse linear solution technique and the bootstrap aggregating algorithm. We tested its performance on four public mass spectrometry cancer datasets along with two other conventional classification techniques such as Support Vector Machines and Adaptive Boosting. The results demonstrate that our proposed method performs more accurate classification across various cancer datasets than those conventional classification techniques.

Damage and protection cost curves for coastal floods within the 600 largest European cities

PubMed Central

Prahl, Boris F.; Boettle, Markus; Costa, Luís; Kropp, Jürgen P.; Rybski, Diego

2018-01-01

The economic assessment of the impacts of storm surges and sea-level rise in coastal cities requires high-level information on the damage and protection costs associated with varying flood heights. We provide a systematically and consistently calculated dataset of macroscale damage and protection cost curves for the 600 largest European coastal cities opening the perspective for a wide range of applications. Offering the first comprehensive dataset to include the costs of dike protection, we provide the underpinning information to run comparative assessments of costs and benefits of coastal adaptation. Aggregate cost curves for coastal flooding at the city-level are commonly regarded as by-products of impact assessments and are generally not published as a standalone dataset. Hence, our work also aims at initiating a more critical discussion on the availability and derivation of cost curves. PMID:29557944

Congo Basin rainfall climatology: can we believe the climate models?

PubMed

Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M; Moufouma-Okia, Wilfran

2013-01-01

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models.

Environmental siting suitability analysis for commercial scale ocean renewable energy: A southeast Florida case study

NASA Astrophysics Data System (ADS)

Mulcan, Amanda

This thesis aims to facilitate the siting and implementation of Florida Atlantic University Southeast National Marine Renewable Energy Center (FAU SNMREC) ocean current energy (OCE) projects offshore southeastern Florida through the analysis of benthic anchoring conditions. Specifically, a suitability analysis considering all presently available biologic and geologic datasets within the legal framework of OCE policy and regulation was done. OCE related literature sources were consulted to assign suitability levels to each dataset, ArcGIS interpolations generated seafloor substrate maps, and existing submarine cable pathways were considered for OCE power cables. The finalized suitability map highlights the eastern study area as most suitable for OCE siting due to its abundance of sand/sediment substrate, existing underwater cable route access, and minimal biologic presence. Higher resolution datasets are necessary to locate specific OCE development locales, better understand their benthic conditions, and minimize potentially negative OCE environmental impacts.

UpSet: Visualization of Intersecting Sets

PubMed Central

Lex, Alexander; Gehlenborg, Nils; Strobelt, Hendrik; Vuillemot, Romain; Pfister, Hanspeter

2016-01-01

Understanding relationships between sets is an important analysis task that has received widespread attention in the visualization community. The major challenge in this context is the combinatorial explosion of the number of set intersections if the number of sets exceeds a trivial threshold. In this paper we introduce UpSet, a novel visualization technique for the quantitative analysis of sets, their intersections, and aggregates of intersections. UpSet is focused on creating task-driven aggregates, communicating the size and properties of aggregates and intersections, and a duality between the visualization of the elements in a dataset and their set membership. UpSet visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes. Sorting according to various measures enables a task-driven analysis of relevant intersections and aggregates. The elements represented in the sets and their associated attributes are visualized in a separate view. Queries based on containment in specific intersections, aggregates or driven by attribute filters are propagated between both views. We also introduce several advanced visual encodings and interaction methods to overcome the problems of varying scales and to address scalability. UpSet is web-based and open source. We demonstrate its general utility in multiple use cases from various domains. PMID:26356912

Ecological patterns, distribution and population structure of Prionace glauca (Chondrichthyes: Carcharhinidae) in the tropical-subtropical transition zone of the north-eastern Pacific.

PubMed

Vögler, Rodolfo; Beier, Emilio; Ortega-García, Sofía; Santana-Hernández, Heriberto; Valdez-Flores, J Javier

2012-02-01

Regional ecological patterns, distribution and population structure of Prionace glauca were analyzed based on samples collected on-board two long-line fleets operating in oceanic waters (1994-96/2000-02) and in coastal oceanic waters (2003-2009) of the eastern tropical Pacific off México. Generalized additive models were applied to catch per unit of effort data to evaluate the effect of spatial, temporal and environmental factors on the horizontal distribution of the life stages (juvenile, adult) and the sexes at the estimated depth of catch. The presence of breeding areas was explored. The population structure was characterized by the presence of juveniles' aggregations and pregnant females towards coastal waters and the presence of adult males' aggregations towards oceanic waters. The species exhibited horizontal segregation by sex-size and vertical segregation by sex. Distribution of the sex-size groups at oceanic waters was seasonally affected by the latitude; however, at coastal oceanic waters mainly females were influenced by the longitude. Latitudinal changes on the horizontal distribution were coupled to the seasonal forward and backward of water masses through the study area. Adult males showed positive relationship with high temperatures and high-salinities waters (17.0°-20.0 °C; 34.2-34.4) although they were also detected in low-salinities waters. The distribution of juvenile males mainly occurred beyond low temperatures and low-salinities waters (14.0°-15.0 °C; 33.6-34.1), suggesting a wide tolerance of adult males to explore subartic and subtropical waters. At oceanic areas, adult females were aggregated towards latitudes <25.0°N, mainly associated to subtropical waters during summer. The distribution of juvenile females indicated its preference by lower temperatures and more saline waters. Presence of pregnant females suggests that the eastern tropical Pacific off México represents an ecological key region to the reproductive cycle of P. glauca. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modeling of depth to base of Last Glacial Maximum and seafloor sediment thickness for the California State Waters Map Series, eastern Santa Barbara Channel, California

USGS Publications Warehouse

Wong, Florence L.; Phillips, Eleyne L.; Johnson, Samuel Y.; Sliter, Ray W.

2012-01-01

Models of the depth to the base of Last Glacial Maximum and sediment thickness over the base of Last Glacial Maximum for the eastern Santa Barbara Channel are a key part of the maps of shallow subsurface geology and structure for offshore Refugio to Hueneme Canyon, California, in the California State Waters Map Series. A satisfactory interpolation of the two datasets that accounted for regional geologic structure was developed using geographic information systems modeling and graphics software tools. Regional sediment volumes were determined from the model. Source data files suitable for geographic information systems mapping applications are provided.

A quality assured surface wind database in Eastern Canada

NASA Astrophysics Data System (ADS)

Lucio-Eceiza, E. E.; González-Rouco, J. F.; Navarro, J.; Beltrami, H.; Jiménez, P. A.; García-Bustamante, E.; Hidalgo, A.

2012-04-01

This work summarizes the results of a Quality Assurance (QA) procedure applied to wind data centred over a wide area in Eastern Canada. The region includes the provinces of Quebec, Prince Edward Island, New Brunswick, Nova Scotia, Newfoundland, Labrador and parts of the north-eastern U.S. (Maine, New Hampshire, Massachusetts, New York and Vermont). The data set consists of 527 stations compiled from three different sources: 344 land sites from Environment Canada (EC; 1940-2009), 40 buoys distributed over the East Coast and the Canadian Great Lakes provided by the Department of Fisheries and Oceans (DFO; 1988-2008), and 143 land sites over both eastern Canada and north-eastern U.S. provided by the National Center of Atmospheric Research (NCAR; 1975-2007). The complexity of the QA process is enhanced in this case by the variety of institutional observational protocols that lead to different temporal resolutions (hourly, 3-h and 6-h), unit systems (km/h in EC; m/s in DFO and knots in NCAR), time references (e.g. UTC, UTC+1, UTC-5, UTC-4), etc. Initial corrections comprised the establishment of common reference systems for time (UTC) and units (MKS). The QA applied on the resulting dataset is structured in three steps that involve the detection and correction of: manipulation errors (i.e. repetitions); unrealistic values and ranges in wind module and direction; abnormally low (e.g. long constant periods) and high variations (e.g. extreme values and inhomogeneities). Results from the first step indicate 22 sites (8 EC; 14 DFO) showing temporal patterns that are unrealistically repeated along the stations. After the QA is applied, the dataset will be subject to statistical and dynamical downscaling studies. The statistical approaches will allow for an understanding of the wind field variability related to changes in the large scale atmospheric circulation as well as their dependence on local/regional features like topography, land-sea contrasts, snow/ice presence, etc. The dynamical downscaling will allow for process understanding assessments by performing high spatial resolution simulations with the WRF model. Finally, model validation will be targeted through the comparison with observations.

Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

NASA Astrophysics Data System (ADS)

Lee, Jongpil; Nam, Juhan

2017-08-01

Music auto-tagging is often handled in a similar manner to image classification by regarding the 2D audio spectrogram as image data. However, music auto-tagging is distinguished from image classification in that the tags are highly diverse and have different levels of abstractions. Considering this issue, we propose a convolutional neural networks (CNN)-based architecture that embraces multi-level and multi-scaled features. The architecture is trained in three steps. First, we conduct supervised feature learning to capture local audio features using a set of CNNs with different input sizes. Second, we extract audio features from each layer of the pre-trained convolutional networks separately and aggregate them altogether given a long audio clip. Finally, we put them into fully-connected networks and make final predictions of the tags. Our experiments show that using the combination of multi-level and multi-scale features is highly effective in music auto-tagging and the proposed method outperforms previous state-of-the-arts on the MagnaTagATune dataset and the Million Song Dataset. We further show that the proposed architecture is useful in transfer learning.

Developing the role of big data and analytics in health professional education.

PubMed

Ellaway, Rachel H; Pusic, Martin V; Galbraith, Robert M; Cameron, Terri

2014-03-01

As we capture more and more data about learners, their learning, and the organization of their learning, our ability to identify emerging patterns and to extract meaning grows exponentially. The insights gained from the analyses of these large amounts of data are only helpful to the extent that they can be the basis for positive action such as knowledge discovery, improved capacity for prediction, and anomaly detection. Big Data involves the aggregation and melding of large and heterogeneous datasets while education analytics involves looking for patterns in educational practice or performance in single or aggregate datasets. Although it seems likely that the use of education analytics and Big Data techniques will have a transformative impact on health professional education, there is much yet to be done before they can become part of mainstream health professional education practice. If health professional education is to be accountable for its programs run and are developed, then health professional educators will need to be ready to deal with the complex and compelling dynamics of analytics and Big Data. This article provides an overview of these emerging techniques in the context of health professional education.

Tree migration detection through comparisons of historic and current forest inventories

Treesearch

Christopher W. Woodall; Christopher M. Oswalt; James A. Westfall; Charles H. Perry; Mark N. Nelson

2009-01-01

Changes in tree species distributions are a potential impact of climate change on forest ecosystems. The examination of tree species shifts in forests of the eastern United States largely has been limited to modeling activities with little empirical analysis of long-term forest inventory datasets. The goal of this study was to compare historic and current spatial...

Development of Regional Wind Resource and Wind Plant Output Datasets for the Hawaiian Islands

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

Manobianco, J.; Alonge, C.; Frank, J.

In March 2009, AWS Truepower was engaged by the National Renewable Energy Laboratory (NREL) to develop a set of wind resource and plant output data for the Hawaiian Islands. The objective of this project was to expand the methods and techniques employed in the Eastern Wind Integration and Transmission Study (EWITS) to include the state of Hawaii.

A training course on tropical cyclones over the eastern Pacific Ocean

NASA Astrophysics Data System (ADS)

Farfan, L. M.; Pozo, D.; Raga, G.; Romero, R.; Zavala, J.

2008-05-01

As part of a research project funded by the Inter-American Institute for Global Change Research (IAI), we are performing a short course based on the current understanding of tropical cyclones in the eastern Pacific basin. In particular, we are focused in discussing the formation and intensification off the Mexican coast. Our main goal is to train students from higher-education institutions from selected countries in Latin America. Our approach includes the review of climatological features derived from the best-track dataset issued by the National Hurricane Center. Using this dataset, we built a climatology of relevant positions and storm tracks for the base period 1970-2006. Additionally, we designed hands-on sessions in which students analyze satellite imagery from several platforms (GOES, QuikSCATT and TRMM) along with mesoscale model simulations from the WRF model. Case studies that resulted in landfall over northwestern Mexico are used; this includes Hurricanes John, Lane and Paul all of which developed during the season of 2006. So far, the course has been taught in the Atmospheric Sciences Department at the University of Buenos Aires, Argentina, and in La Paz, Mexico, with students from Mexico, Chile, Brazil, Costa Rica and Cuba.

Assessing the Spatiotemporal Variation and Impact Factors of Net Primary Productivity in China

NASA Astrophysics Data System (ADS)

Wang, Xue; Tan, Kun; Chen, Baozhang; Du, Peijun

2017-03-01

In this study, the net primary productivity (NPP) in China from 2001 to 2012 was estimated based on the Carnegie-Ames-Stanford Approach (CASA) model using Moderate Resolution Imaging Spectroradiometer (MODIS) and meteorological datasets, and the accuracy was verified by a ChinaFLUX dataset. It was found that the spatiotemporal variations in NPP present a downward trend with the increase of latitude and longitude. Moreover, the influence of climate change on the evolution of NPP shows that NPP has had different impact factors in different regions and periods over the 12 years. The eastern region has shown the largest increase in gross regional product (GRP) and a significant fluctuation in NPP over the 12 years. Meanwhile, NPP in the eastern and central regions is significantly positively correlated with annual solar radiation, while NPP in these two regions is significantly negatively correlated with the growth rate of GRP. It is concluded that both the development of the economy and climate change have influenced NPP evolution in China. In addition, NPP has shown a steadily rising trend over the 12 years as a result of the great importance attributed to ecological issues when developing the economy.

Use Hierarchical Storage and Analysis to Exploit Intrinsic Parallelism

NASA Astrophysics Data System (ADS)

Zender, C. S.; Wang, W.; Vicente, P.

2013-12-01

Big Data is an ugly name for the scientific opportunities and challenges created by the growing wealth of geoscience data. How to weave large, disparate datasets together to best reveal their underlying properties, to exploit their strengths and minimize their weaknesses, to continually aggregate more information than the world knew yesterday and less than we will learn tomorrow? Data analytics techniques (statistics, data mining, machine learning, etc.) can accelerate pattern recognition and discovery. However, often researchers must, prior to analysis, organize multiple related datasets into a coherent framework. Hierarchical organization permits entire dataset to be stored in nested groups that reflect their intrinsic relationships and similarities. Hierarchical data can be simpler and faster to analyze by coding operators to automatically parallelize processes over isomorphic storage units, i.e., groups. The newest generation of netCDF Operators (NCO) embody this hierarchical approach, while still supporting traditional analysis approaches. We will use NCO to demonstrate the trade-offs involved in processing a prototypical Big Data application (analysis of CMIP5 datasets) using hierarchical and traditional analysis approaches.

Xray: N-dimensional, labeled arrays for analyzing physical datasets in Python

NASA Astrophysics Data System (ADS)

Hoyer, S.

2015-12-01

Efficient analysis of geophysical datasets requires tools that both preserve and utilize metadata, and that transparently scale to process large datas. Xray is such a tool, in the form of an open source Python library for analyzing the labeled, multi-dimensional array (tensor) datasets that are ubiquitous in the Earth sciences. Xray's approach pairs Python data structures based on the data model of the netCDF file format with the proven design and user interface of pandas, the popular Python data analysis library for labeled tabular data. On top of the NumPy array, xray adds labeled dimensions (e.g., "time") and coordinate values (e.g., "2015-04-10"), which it uses to enable a host of operations powered by these labels: selection, aggregation, alignment, broadcasting, split-apply-combine, interoperability with pandas and serialization to netCDF/HDF5. Many of these operations are enabled by xray's tight integration with pandas. Finally, to allow for easy parallelism and to enable its labeled data operations to scale to datasets that does not fit into memory, xray integrates with the parallel processing library dask.

An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study

PubMed Central

Murray, David; Stankovic, Lina; Stankovic, Vladimir

2017-01-01

Smart meter roll-outs provide easy access to granular meter measurements, enabling advanced energy services, ranging from demand response measures, tailored energy feedback and smart home/building automation. To design such services, train and validate models, access to data that resembles what is expected of smart meters, collected in a real-world setting, is necessary. The REFIT electrical load measurements dataset described in this paper includes whole house aggregate loads and nine individual appliance measurements at 8-second intervals per house, collected continuously over a period of two years from 20 houses. During monitoring, the occupants were conducting their usual routines. At the time of publishing, the dataset has the largest number of houses monitored in the United Kingdom at less than 1-minute intervals over a period greater than one year. The dataset comprises 1,194,958,790 readings, that represent over 250,000 monitored appliance uses. The data is accessible in an easy-to-use comma-separated format, is time-stamped and cleaned to remove invalid measurements, correctly label appliance data and fill in small gaps of missing data. PMID:28055033

An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study

NASA Astrophysics Data System (ADS)

Murray, David; Stankovic, Lina; Stankovic, Vladimir

2017-01-01

Smart meter roll-outs provide easy access to granular meter measurements, enabling advanced energy services, ranging from demand response measures, tailored energy feedback and smart home/building automation. To design such services, train and validate models, access to data that resembles what is expected of smart meters, collected in a real-world setting, is necessary. The REFIT electrical load measurements dataset described in this paper includes whole house aggregate loads and nine individual appliance measurements at 8-second intervals per house, collected continuously over a period of two years from 20 houses. During monitoring, the occupants were conducting their usual routines. At the time of publishing, the dataset has the largest number of houses monitored in the United Kingdom at less than 1-minute intervals over a period greater than one year. The dataset comprises 1,194,958,790 readings, that represent over 250,000 monitored appliance uses. The data is accessible in an easy-to-use comma-separated format, is time-stamped and cleaned to remove invalid measurements, correctly label appliance data and fill in small gaps of missing data.

An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study.

PubMed

Murray, David; Stankovic, Lina; Stankovic, Vladimir

2017-01-05

Smart meter roll-outs provide easy access to granular meter measurements, enabling advanced energy services, ranging from demand response measures, tailored energy feedback and smart home/building automation. To design such services, train and validate models, access to data that resembles what is expected of smart meters, collected in a real-world setting, is necessary. The REFIT electrical load measurements dataset described in this paper includes whole house aggregate loads and nine individual appliance measurements at 8-second intervals per house, collected continuously over a period of two years from 20 houses. During monitoring, the occupants were conducting their usual routines. At the time of publishing, the dataset has the largest number of houses monitored in the United Kingdom at less than 1-minute intervals over a period greater than one year. The dataset comprises 1,194,958,790 readings, that represent over 250,000 monitored appliance uses. The data is accessible in an easy-to-use comma-separated format, is time-stamped and cleaned to remove invalid measurements, correctly label appliance data and fill in small gaps of missing data.

Multi-gas and multi-source comparisons of six land use emission datasets and AFOLU estimates in the Fifth Assessment Report, for the tropics for 2000-2005

NASA Astrophysics Data System (ADS)

Roman-Cuesta, Rosa Maria; Herold, Martin; Rufino, Mariana C.; Rosenstock, Todd S.; Houghton, Richard A.; Rossi, Simone; Butterbach-Bahl, Klaus; Ogle, Stephen; Poulter, Benjamin; Verchot, Louis; Martius, Christopher; de Bruin, Sytze

2016-10-01

The Agriculture, Forestry and Other Land Use (AFOLU) sector contributes with ca. 20-25 % of global anthropogenic emissions (2010), making it a key component of any climate change mitigation strategy. AFOLU estimates, however, remain highly uncertain, jeopardizing the mitigation effectiveness of this sector. Comparisons of global AFOLU emissions have shown divergences of up to 25 %, urging for improved understanding of the reasons behind these differences. Here we compare a variety of AFOLU emission datasets and estimates given in the Fifth Assessment Report for the tropics (2000-2005) to identify plausible explanations for the differences in (i) aggregated gross AFOLU emissions, and (ii) disaggregated emissions by sources and gases (CO2, CH4, N2O). We also aim to (iii) identify countries with low agreement among AFOLU datasets to navigate research efforts. The datasets are FAOSTAT (Food and Agriculture Organization of the United Nations, Statistics Division), EDGAR (Emissions Database for Global Atmospheric Research), the newly developed AFOLU "Hotspots", "Houghton", "Baccini", and EPA (US Environmental Protection Agency) datasets. Aggregated gross emissions were similar for all databases for the AFOLU sector: 8.2 (5.5-12.2), 8.4, and 8.0 Pg CO2 eq. yr-1 (for Hotspots, FAOSTAT, and EDGAR respectively), forests reached 6.0 (3.8-10), 5.9, 5.9, and 5.4 Pg CO2 eq. yr-1 (Hotspots, FAOSTAT, EDGAR, and Houghton), and agricultural sectors were with 1.9 (1.5-2.5), 2.5, 2.1, and 2.0 Pg CO2 eq. yr-1 (Hotspots, FAOSTAT, EDGAR, and EPA). However, this agreement was lost when disaggregating the emissions by sources, continents, and gases, particularly for the forest sector, with fire leading the differences. Agricultural emissions were more homogeneous, especially from livestock, while those from croplands were the most diverse. CO2 showed the largest differences among the datasets. Cropland soils and enteric fermentation led to the smaller N2O and CH4 differences. Disagreements are explained by differences in conceptual frameworks (carbon-only vs. multi-gas assessments, definitions, land use vs. land cover, etc.), in methods (tiers, scales, compliance with Intergovernmental Panel on Climate Change (IPCC) guidelines, legacies, etc.) and in assumptions (carbon neutrality of certain emissions, instantaneous emissions release, etc.) which call for more complete and transparent documentation for all the available datasets. An enhanced dialogue between the carbon (CO2) and the AFOLU (multi-gas) communities is needed to reduce discrepancies of land use estimates.

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

Porwollik, Vera; Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Iizumi, Toshichika; Ray, Deepak K.; Ruane, Alex C.; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe;

[Developing forensic reference database by 18 autosomal STR for DNA identification in Republic of Belarus].

PubMed

Tsybovskii, I S; Veremeichik, V M; Kotova, S A; Kritskaya, S V; Evmenenko, S A; Udina, I G

2017-02-01

For the Republic of Belarus, development of a forensic reference database on the basis of 18 autosomal microsatellites (STR) using a population dataset (N = 1040), “familial” genotypic dataset (N = 2550) obtained from expertise performance of paternity testing, and a dataset of genotypes from a criminal registration database (N = 8756) is described. Population samples studied consist of 80% ethnic Belarusians and 20% individuals of other nationality or of mixed origin (by questionnaire data). Genotypes of 12346 inhabitants of the Republic of Belarus from 118 regional samples studied by 18 autosomal microsatellites are included in the sample: 16 tetranucleotide STR (D2S1338, TPOX, D3S1358, CSF1PO, D5S818, D8S1179, D7S820, THO1, vWA, D13S317, D16S539, D18S51, D19S433, D21S11, F13B, and FGA) and two pentanucleotide STR (Penta D and Penta E). The samples studied are in Hardy–Weinberg equilibrium according to distribution of genotypes by 18 STR. Significant differences were not detected between discrete populations or between samples from various historical ethnographic regions of the Republic of Belarus (Western and Eastern Polesie, Podneprovye, Ponemanye, Poozerye, and Center), which indicates the absence of prominent genetic differentiation. Statistically significant differences between the studied genotypic datasets also were not detected, which made it possible to combine the datasets and consider the total sample as a unified forensic reference database for 18 “criminalistic” STR loci. Differences between reference database of the Republic of Belarus and Russians and Ukrainians by the distribution of the range of autosomal STR also were not detected, corresponding to a close genetic relationship of the three Eastern Slavic nations mediated by common origin and intense mutual migrations. Significant differences by separate STR loci between the reference database of Republic of Belarus and populations of Southern and Western Slavs were observed. The necessity of using original reference database for support of forensic expertise practice in the Republic of Belarus was demonstrated.

Who Delivers without Water? A Multi Country Analysis of Water and Sanitation in the Childbirth Environment.

PubMed

Gon, Giorgia; Restrepo-Méndez, María Clara; Campbell, Oona M R; Barros, Aluísio J D; Woodd, Susannah; Benova, Lenka; Graham, Wendy J

2016-01-01

Hygiene during childbirth is essential to the health of mothers and newborns, irrespective of where birth takes place. This paper investigates the status of water and sanitation in both the home and facility childbirth environments, and for whom and where this is a more significant problem. We used three datasets: a global dataset, with information on the home environment from 58 countries, and two datasets for each of four countries in Eastern Africa: a healthcare facility dataset, and a dataset that incorporated information on facilities and the home environment to create a comprehensive description of birth environments in those countries. We constructed indices of improved water, and improved water and sanitation combined (WATSAN), for the home and healthcare facilities. The Joint Monitoring Program was used to construct indices for household; we tailored them to the facility context-household and facility indices include different components. We described what proportion of women delivered in an environment with improved WATSAN. For those women who delivered at home, we calculated what proportion had improved WATSAN by socio-economic status, education and rural-urban status. Among women delivering at home (58 countries), coverage of improved WATSAN by region varied from 9% to 53%. Fewer than 15% of women who delivered at home in Sub-Saharan Africa, had access to water and sanitation infrastructure (range 0.1% to 37%). This was worse among the poorest, the less educated and those living in rural areas. In Eastern Africa, where we looked at both the home and facility childbirth environment, a third of women delivered in an environment with improved water in Uganda and Rwanda; whereas, 18% of women in Kenya and 7% in Tanzania delivered with improved water and sanitation. Across the four countries, less than half of the facility deliveries had improved water, or improved water and sanitation in the childbirth environment. Access to water and sanitation during childbirth is poor across low and middle-income countries. Even when women travel to health facilities for childbirth, they are not guaranteed access to basic WATSAN infrastructure. These indicators should be measured routinely in order to inform improvements.

Magnetic Resonance Characterization of Hepatic Storage Iron in Transfusional Iron Overload

PubMed Central

Tang, Haiying; Jensen, Jens H.; Sammet, Christina L.; Sheth, Sujit; Swaminathan, Srirama V.; Hultman, Kristi; Kim, Daniel; Wu, Ed X.; Brown, Truman R.; Brittenham, Gary M.

2013-01-01

Purpose To quantify the two principal forms of hepatic storage iron, diffuse, soluble iron (primarily ferritin), and aggregated, insoluble iron (primarily hemosiderin) using a new MRI method in patients with transfusional iron overload. Materials and Methods Six healthy volunteers and twenty patients with transfusion-dependent thalassemia syndromes and iron overload were examined. Ferritin- and hemosiderin-like iron were determined based on the measurement of two distinct relaxation parameters: the “reduced” transverse relaxation rate, RR2 and the “aggregation index,” A, using three sets of Carr-Purcell-Meiboom-Gill (CPMG) datasets with different interecho spacings. Agarose phantoms, simulating the relaxation and susceptibility properties of tissue with different concentrations of dispersed (ferritin-like) and aggregated (hemosiderin-like) iron, were employed for validation. Results Both phantom and in vivo human data confirmed that transverse relaxation components associated with the dispersed and aggregated iron could be separated using the two-parameter (RR2, A) method. The MRI-determined total hepatic storage iron was highly correlated (r = 0.95) with measurements derived from biopsy or biosusceptometry. As total hepatic storage iron increased, the proportion stored as aggregated iron became greater. Conclusion This method provides a new means for non-invasive MRI determination of the partition of hepatic storage iron between ferritin and hemosiderin in iron overload disorders. PMID:23720394

MR characterization of hepatic storage iron in transfusional iron overload.

PubMed

Tang, Haiying; Jensen, Jens H; Sammet, Christina L; Sheth, Sujit; Swaminathan, Srirama V; Hultman, Kristi; Kim, Daniel; Wu, Ed X; Brown, Truman R; Brittenham, Gary M

2014-02-01

To quantify the two principal forms of hepatic storage iron, diffuse, soluble iron (primarily ferritin), and aggregated, insoluble iron (primarily hemosiderin) using a new MRI method in patients with transfusional iron overload. Six healthy volunteers and 20 patients with transfusion-dependent thalassemia syndromes and iron overload were examined. Ferritin- and hemosiderin-like iron were determined based on the measurement of two distinct relaxation parameters: the "reduced" transverse relaxation rate, RR2 , and the "aggregation index," A, using three sets of Carr-Purcell-Meiboom-Gill (CPMG) datasets with different interecho spacings. Agarose phantoms, simulating the relaxation and susceptibility properties of tissue with different concentrations of dispersed (ferritin-like) and aggregated (hemosiderin-like) iron, were used for validation. Both phantom and in vivo human data confirmed that transverse relaxation components associated with the dispersed and aggregated iron could be separated using the two-parameter (RR2 , A) method. The MRI-determined total hepatic storage iron was highly correlated (r = 0.95) with measurements derived from biopsy or biosusceptometry. As total hepatic storage iron increased, the proportion stored as aggregated iron became greater. This method provides a new means for noninvasive MRI determination of the partition of hepatic storage iron between ferritin and hemosiderin in iron overload disorders. Copyright © 2013 Wiley Periodicals, Inc.

The African Crane Database (1978-2014): Records of three threatened crane species (Family: Gruidae) from southern and eastern Africa

PubMed Central

Smith, Tanya; Page-Nicholson, Samantha; Gibbons, Bradley; Jones, M. Genevieve W.; van Niekerk, Mark; Botha, Bronwyn; Oliver, Kirsten; McCann, Kevin

2016-01-01

Abstract Background The International Crane Foundation (ICF) / Endangered Wildlife Trust’s (EWT) African Crane Conservation Programme has recorded 26 403 crane sightings in its database from 1978 to 2014. This sightings collection is currently ongoing and records are continuously added to the database by the EWT field staff, ICF/EWT Partnership staff, various partner organizations and private individuals. The dataset has two peak collection periods: 1994-1996 and 2008-2012. The dataset collection spans five African countries: Kenya, Rwanda, South Africa, Uganda and Zambia; 98% of the data were collected in South Africa. Georeferencing of the dataset was verified before publication of the data. The dataset contains data on three African crane species: Blue Crane Anthropoides paradiseus, Grey Crowned Crane Balearica regulorum and Wattled Crane Bugeranus carunculatus. The Blue and Wattled Cranes are classified by the IUCN Red List of Threatened Species as Vulnerable and the Grey Crowned Crane as Endangered. New information This is the single most comprehensive dataset published on African Crane species that adds new information about the distribution of these three threatened species. We hope this will further aid conservation authorities to monitor and protect these species. The dataset continues to grow and especially to expand in geographic coverage into new countries in Africa and new sites within countries. The dataset can be freely accessed through the Global Biodiversity Information Facility data portal. PMID:27956850

Integrating fine-scale soil data into species distribution models: preparing Soil Survey Geographic (SSURGO) data from multiple counties

Treesearch

Matthew P. Peters; Louis R. Iverson; Anantha M. Prasad; Steve N. Matthews

2013-01-01

Fine-scale soil (SSURGO) data were processed at the county level for 37 states within the eastern United States, initially for use as predictor variables in a species distribution model called DISTRIB II. Values from county polygon files converted into a continuous 30-m raster grid were aggregated to 4-km cells and integrated with other environmental and site condition...

Intensity-Duration-Frequency curves from remote sensing datasets: direct comparison of weather radar and CMORPH over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Morin, Efrat; Marra, Francesco; Peleg, Nadav; Mei, Yiwen; Anagnostou, Emmanouil N.

2017-04-01

Rainfall frequency analysis is used to quantify the probability of occurrence of extreme rainfall and is traditionally based on rain gauge records. The limited spatial coverage of rain gauges is insufficient to sample the spatiotemporal variability of extreme rainfall and to provide the areal information required by management and design applications. Conversely, remote sensing instruments, even if quantitative uncertain, offer coverage and spatiotemporal detail that allow overcoming these issues. In recent years, remote sensing datasets began to be used for frequency analyses, taking advantage of increased record lengths and quantitative adjustments of the data. However, the studies so far made use of concepts and techniques developed for rain gauge (i.e. point or multiple-point) data and have been validated by comparison with gauge-derived analyses. These procedures add further sources of uncertainty and prevent from isolating between data and methodological uncertainties and from fully exploiting the available information. In this study, we step out of the gauge-centered concept presenting a direct comparison between at-site Intensity-Duration-Frequency (IDF) curves derived from different remote sensing datasets on corresponding spatial scales, temporal resolutions and records. We analyzed 16 years of homogeneously corrected and gauge-adjusted C-Band weather radar estimates, high-resolution CMORPH and gauge-adjusted high-resolution CMORPH over the Eastern Mediterranean. Results of this study include: (a) good spatial correlation between radar and satellite IDFs ( 0.7 for 2-5 years return period); (b) consistent correlation and dispersion in the raw and gauge adjusted CMORPH; (c) bias is almost uniform with return period for 12-24 h durations; (d) radar identifies thicker tail distributions than CMORPH and the tail of the distributions depends on the spatial and temporal scales. These results demonstrate the potential of remote sensing datasets for rainfall frequency analysis for management (e.g. warning and early-warning systems) and design (e.g. sewer design, large scale drainage planning)

Crowdsourcing Physical Network Topology Mapping With Net.Tagger

DTIC Science & Technology

2016-03-01

backend server infrastructure . This in- cludes a full security audit, better web services handling, and integration with the OSM stack and dataset to...a novel approach to network infrastructure mapping that combines smartphone apps with crowdsourced collection to gather data for offline aggregation...and analysis. The project aims to build a map of physical network infrastructure such as fiber-optic cables, facilities, and access points. The

An in-silico method for identifying aggregation rate enhancer and mitigator mutations in proteins.

PubMed

Rawat, Puneet; Kumar, Sandeep; Michael Gromiha, M

2018-06-24

Newly synthesized polypeptides must pass stringent quality controls in cells to ensure appropriate folding and function. However, mutations, environmental stresses and aging can reduce efficiencies of these controls, leading to accumulation of protein aggregates, amyloid fibrils and plaques. In-vitro experiments have shown that even single amino acid substitutions can drastically enhance or mitigate protein aggregation kinetics. In this work, we have collected a dataset of 220 unique mutations in 25 proteins and classified them as enhancers or mitigators on the basis of their effect on protein aggregation rate. The data were analyzed via machine learning to identify features capable of distinguishing between aggregation rate enhancers and mitigators. Our initial Support Vector Machine (SVM) model separated such mutations with an overall accuracy of 69%. When local secondary structures at the mutation sites were considered, the accuracies further improved by 13-15%. The machine-learnt features are distinct for each secondary structure class at mutation sites. Protein stability and flexibility changes are important features for mutations in α-helices. β-strand propensity, polarity and charge become important when mutations occur in β-strands and ability to form secondary structure, helical tendency and aggregation propensity are important for mutations lying in coils. These results have been incorporated into a sequence-based algorithm (available at http://www.iitm.ac.in/bioinfo/aggrerate-disc/) capable of predicting whether a mutation will enhance or mitigate a protein's aggregation rate. This algorithm will find several applications towards understanding protein aggregation in human diseases, enable in-silico optimization of biopharmaceuticals and enzymes for improved biophysical attributes and de novo design of bio-nanomaterials. Copyright © 2018. Published by Elsevier B.V.

Comparison of charcoal and tree-ring records of recent fires in the eastern Klamath Mountains, California, USA

Treesearch

Cathy Whitlock; Carl N. Skinner; Patrick J. Bartlein; Thomas Minckley; Jerry A. Mohr

2004-01-01

Fire-history reconstructions are based on tree-ring records that span the last few centuries and charcoal data from lake-sediment cores that extend back several thousand years. The two approaches have unique strengths and weaknesses in their ability to depict past fire events and fire regimes, and most comparisons of these datasets in western conifer forests have...

Anti-thrombosis Repertoire of Blood-feeding Horsefly Salivary Glands*

PubMed Central

Ma, Dongying; Wang, Yipeng; Yang, Hailong; Wu, Jing; An, Shu; Gao, Li; Xu, Xueqing; Lai, Ren

2009-01-01

Blood-feeding arthropods rely heavily on the pharmacological properties of their saliva to get a blood meal and suppress immune reactions of hosts. Little information is available on antihemostatic substances in horsefly salivary glands although their saliva has been thought to contain wide range of physiologically active molecules. In traditional Eastern medicine, horseflies are used as anti-thrombosis material for hundreds of years. By proteomics coupling transcriptome analysis with pharmacological testing, several families of proteins or peptides, which exert mainly on anti-thrombosis functions, were identified and characterized from 60,000 pairs of salivary glands of the horsefly Tabanus yao Macquart (Diptera, Tabanidae). They are: (I) ten fibrin(ogen)olytic enzymes, which hydrolyze specially alpha chain of fibrin(ogen) and are the first family of fibrin(ogen)olytic enzymes purified and characterized from arthropods; (II) another fibrin(ogen)olytic enzyme, which hydrolyzes both alpha and beta chain of fibrin(ogen); (III) ten Arg-Gly-Asp-motif containing proteins acting as platelet aggregation inhibitors; (IV) five thrombin inhibitor peptides; (V) three vasodilator peptides; (VI) one apyrase acting as platelet aggregation inhibitor; (VII) one peroxidase with both platelet aggregation inhibitory and vasodilator activities. The first three families are belonging to antigen five proteins, which show obvious similarity with insect allergens. They are the first members of the antigen 5 family found in salivary glands of blood sucking arthropods to have anti-thromobosis function. The current results imply a possible evolution from allergens of blood-sucking insects to anti-thrombosis agents. The extreme diversity of horsefly anti-thrombosis components also reveals the anti-thrombosis molecular mechanisms of the traditional Eastern medicine insect material. PMID:19531497

Evaluation of Global Observations-Based Evapotranspiration Datasets and IPCC AR4 Simulations

NASA Technical Reports Server (NTRS)

Mueller, B.; Seneviratne, S. I.; Jimenez, C.; Corti, T.; Hirschi, M.; Balsamo, G.; Ciais, P.; Dirmeyer, P.; Fisher, J. B.; Guo, Z.;

Individual laboratory-measured discount rates predict field behavior

PubMed Central

Chabris, Christopher F.; Laibson, David; Morris, Carrie L.; Schuldt, Jonathon P.; Taubinsky, Dmitry

2009-01-01

We estimate discount rates of 555 subjects using a laboratory task and find that these individual discount rates predict inter-individual variation in field behaviors (e.g., exercise, BMI, smoking). The correlation between the discount rate and each field behavior is small: none exceeds 0.28 and many are near 0. However, the discount rate has at least as much predictive power as any variable in our dataset (e.g., sex, age, education). The correlation between the discount rate and field behavior rises when field behaviors are aggregated: these correlations range from 0.09-0.38. We present a model that explains why specific intertemporal choice behaviors are only weakly correlated with discount rates, even though discount rates robustly predict aggregates of intertemporal decisions. PMID:19412359

Individual laboratory-measured discount rates predict field behavior.

PubMed

Chabris, Christopher F; Laibson, David; Morris, Carrie L; Schuldt, Jonathon P; Taubinsky, Dmitry

2008-12-01

We estimate discount rates of 555 subjects using a laboratory task and find that these individual discount rates predict inter-individual variation in field behaviors (e.g., exercise, BMI, smoking). The correlation between the discount rate and each field behavior is small: none exceeds 0.28 and many are near 0. However, the discount rate has at least as much predictive power as any variable in our dataset (e.g., sex, age, education). The correlation between the discount rate and field behavior rises when field behaviors are aggregated: these correlations range from 0.09-0.38. We present a model that explains why specific intertemporal choice behaviors are only weakly correlated with discount rates, even though discount rates robustly predict aggregates of intertemporal decisions.

The influence of El Niño-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario

NASA Astrophysics Data System (ADS)

Fer, Istem; Tietjen, Britta; Jeltsch, Florian; Wolff, Christian

2017-09-01

The El Niño-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.

Constructing compact and effective graphs for recommender systems via node and edge aggregations

DOE PAGES

Lee, Sangkeun; Kahng, Minsuk; Lee, Sang-goo

2014-12-10

Exploiting graphs for recommender systems has great potential to flexibly incorporate heterogeneous information for producing better recommendation results. As our baseline approach, we first introduce a naive graph-based recommendation method, which operates with a heterogeneous log-metadata graph constructed from user log and content metadata databases. Although the na ve graph-based recommendation method is simple, it allows us to take advantages of heterogeneous information and shows promising flexibility and recommendation accuracy. However, it often leads to extensive processing time due to the sheer size of the graphs constructed from entire user log and content metadata databases. In this paper, we proposemore » node and edge aggregation approaches to constructing compact and e ective graphs called Factor-Item bipartite graphs by aggregating nodes and edges of a log-metadata graph. Furthermore, experimental results using real world datasets indicate that our approach can significantly reduce the size of graphs exploited for recommender systems without sacrificing the recommendation quality.« less

Validation of individual and aggregate global flood hazard models for two major floods in Africa.

NASA Astrophysics Data System (ADS)

Trigg, M.; Bernhofen, M.; Whyman, C.

2017-12-01

A recent intercomparison of global flood hazard models undertaken by the Global Flood Partnership shows that there is an urgent requirement to undertake more validation of the models against flood observations. As part of the intercomparison, the aggregated model dataset resulting from the project was provided as open access data. We compare the individual and aggregated flood extent output from the six global models and test these against two major floods in the African Continent within the last decade, namely severe flooding on the Niger River in Nigeria in 2012, and on the Zambezi River in Mozambique in 2007. We test if aggregating different number and combination of models increases model fit to the observations compared with the individual model outputs. We present results that illustrate some of the challenges of comparing imperfect models with imperfect observations and also that of defining the probability of a real event in order to test standard model output probabilities. Finally, we propose a collective set of open access validation flood events, with associated observational data and descriptions that provide a standard set of tests across different climates and hydraulic conditions.

The upper mantle shear wave velocity structure of East Africa derived from Rayleigh wave tomography

NASA Astrophysics Data System (ADS)

O'Donnell, J.; Nyblade, A.; Adams, A. N.; Weeraratne, D. S.; Mulibo, G.; Tugume, F.

2012-12-01

An expanded model of the three-dimensional shear wave velocity structure of the upper mantle beneath East Africa has been developed using data from the latest phases of the AfricaArray East African Seismic Experiment in conjunction with data from preceding studies. The combined dataset consists of 331 events recorded on a total of 95 seismic stations spanning Kenya, Uganda, Tanzania, Zambia and Malawi. In this latest study, 149 events were used to determine fundamental mode Rayleigh wave phase velocities at periods ranging from 20 to 182 seconds using the two-plane-wave method. These were subsequently combined with the similarly processed published measurements and inverted for an updated upper mantle three-dimensional shear wave velocity model. Newly imaged features include a substantial fast anomaly in eastern Zambia that may have exerted a controlling influence on the evolution of the Western Rift Branch. Furthermore, there is a suggestion that the Eastern Rift Branch trends southeastward offshore eastern Tanzania.

AMP: Assembly Matching Pursuit.

PubMed

Biswas, S; Jojic, V

2013-01-01

Metagenomics, the study of the total genetic material isolated from a biological host, promises to reveal host-microbe or microbe-microbe interactions that may help to personalize medicine or improve agronomic practice. We introduce a method that discovers metagenomic units (MGUs) relevant for phenotype prediction through sequence-based dictionary learning. The method aggregates patient-specific dictionaries and estimates MGU abundances in order to summarize a whole population and yield universally predictive biomarkers. We analyze the impact of Gaussian, Poisson, and Negative Binomial read count models in guiding dictionary construction by examining classification efficiency on a number of synthetic datasets and a real dataset from Ref. 1. Each outperforms standard methods of dictionary composition, such as random projection and orthogonal matching pursuit. Additionally, the predictive MGUs they recover are biologically relevant.

NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference.

PubMed

Bellot, Pau; Olsen, Catharina; Salembier, Philippe; Oliveras-Vergés, Albert; Meyer, Patrick E

2015-09-29

In the last decade, a great number of methods for reconstructing gene regulatory networks from expression data have been proposed. However, very few tools and datasets allow to evaluate accurately and reproducibly those methods. Hence, we propose here a new tool, able to perform a systematic, yet fully reproducible, evaluation of transcriptional network inference methods. Our open-source and freely available Bioconductor package aggregates a large set of tools to assess the robustness of network inference algorithms against different simulators, topologies, sample sizes and noise intensities. The benchmarking framework that uses various datasets highlights the specialization of some methods toward network types and data. As a result, it is possible to identify the techniques that have broad overall performances.

Nematode infection in the lizard Bogertia lutzae (Loveridge, 1941) from the Atlantic Forest in north-eastern Brazil.

PubMed

Avila, R W; Anjos, L A; Gonçalves, U; Freire, E M X; Almeida, W O; da Silva, R J

2010-06-01

Endoparasites associated with the small bromelicolous lizard Bogertia lutzae, a poorly studied phyllodactylid inhabitant of north-eastern Brazil, were studied. Fifty-seven specimens collected from the Atlantic Forest of Alagoas state were dissected. Only one species of parasite, the nematode Spauligodon oxkutzcabiensis, was found, with a prevalence of 22.8%. The intensity of infection was 2.62 +/- 1.19, and neither the prevalence nor mean intensity differed between the sexes. There was no correlation between lizard body size and intensity of infection. An aggregated pattern of distribution (D = 0.813) of S. oxkutzcabiensis was found in this lizard host population. Bogertia lutzae represents a new host recorded for S. oxkutzcabiensis, a parasite reported for the first time for Brazil.

SchizConnect: Mediating Neuroimaging Databases on Schizophrenia and Related Disorders for Large-Scale Integration

PubMed Central

Wang, Lei; Alpert, Kathryn I.; Calhoun, Vince D.; Cobia, Derin J.; Keator, David B.; King, Margaret D.; Kogan, Alexandr; Landis, Drew; Tallis, Marcelo; Turner, Matthew D.; Potkin, Steven G.; Turner, Jessica A.; Ambite, Jose Luis

2015-01-01

SchizConnect (www.schizconnect.org) is built to address the issues of multiple data repositories in schizophrenia neuroimaging studies. It includes a level of mediation—translating across data sources—so that the user can place one query, e.g. for diffusion images from male individuals with schizophrenia, and find out from across participating data sources how many datasets there are, as well as downloading the imaging and related data. The current version handles the Data Usage Agreements across different studies, as well as interpreting database-specific terminologies into a common framework. New data repositories can also be mediated to bring immediate access to existing datasets. Compared with centralized, upload data sharing models, SchizConnect is a unique, virtual database with a focus on schizophrenia and related disorders that can mediate live data as information are being updated at each data source. It is our hope that SchizConnect can facilitate testing new hypotheses through aggregated datasets, promoting discovery related to the mechanisms underlying schizophrenic dysfunction. PMID:26142271

FACETS: using open data to measure community social determinants of health.

PubMed

Cantor, Michael N; Chandras, Rajan; Pulgarin, Claudia

2018-04-01

To develop a dataset based on open data sources reflective of community-level social determinants of health (SDH). We created FACETS (Factors Affecting Communities and Enabling Targeted Services), an architecture that incorporates open data related to SDH into a single dataset mapped at the census-tract level for New York City. FACETS (https://github.com/mcantor2/FACETS) can be easily used to map individual addresses to their census-tract-level SDH. This dataset facilitates analysis across different determinants that are often not easily accessible. Wider access to open data from government agencies at the local, state, and national level would facilitate the aggregation and analysis of community-level determinants. Timeliness of updates to federal non-census data sources may limit their usefulness. FACETS is an important first step in standardizing and compiling SDH-related data in an open architecture that can give context to a patient's condition and enable better decision-making when developing a plan of care.

An interactive web application for the dissemination of human systems immunology data.

PubMed

Speake, Cate; Presnell, Scott; Domico, Kelly; Zeitner, Brad; Bjork, Anna; Anderson, David; Mason, Michael J; Whalen, Elizabeth; Vargas, Olivia; Popov, Dimitry; Rinchai, Darawan; Jourde-Chiche, Noemie; Chiche, Laurent; Quinn, Charlie; Chaussabel, Damien

2015-06-19

Systems immunology approaches have proven invaluable in translational research settings. The current rate at which large-scale datasets are generated presents unique challenges and opportunities. Mining aggregates of these datasets could accelerate the pace of discovery, but new solutions are needed to integrate the heterogeneous data types with the contextual information that is necessary for interpretation. In addition, enabling tools and technologies facilitating investigators' interaction with large-scale datasets must be developed in order to promote insight and foster knowledge discovery. State of the art application programming was employed to develop an interactive web application for browsing and visualizing large and complex datasets. A collection of human immune transcriptome datasets were loaded alongside contextual information about the samples. We provide a resource enabling interactive query and navigation of transcriptome datasets relevant to human immunology research. Detailed information about studies and samples are displayed dynamically; if desired the associated data can be downloaded. Custom interactive visualizations of the data can be shared via email or social media. This application can be used to browse context-rich systems-scale data within and across systems immunology studies. This resource is publicly available online at [Gene Expression Browser Landing Page ( https://gxb.benaroyaresearch.org/dm3/landing.gsp )]. The source code is also available openly [Gene Expression Browser Source Code ( https://github.com/BenaroyaResearch/gxbrowser )]. We have developed a data browsing and visualization application capable of navigating increasingly large and complex datasets generated in the context of immunological studies. This intuitive tool ensures that, whether taken individually or as a whole, such datasets generated at great effort and expense remain interpretable and a ready source of insight for years to come.

Congo Basin rainfall climatology: can we believe the climate models?

PubMed Central

Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M.; Moufouma-Okia, Wilfran

2013-01-01

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models. PMID:23878328

Quantifying scaling effects on satellite-derived forest area estimates for the conterminous USA

Treesearch

Daolan Zheng; L.S. Heath; M.J. Ducey; J.E. Smith

2009-01-01

We quantified the scaling effects on forest area estimates for the conterminous USA using regression analysis and the National Land Cover Dataset 30m satellite-derived maps in 2001 and 1992. The original data were aggregated to: (1) broad cover types (forest vs. non-forest); and (2) coarser resolutions (1km and 10 km). Standard errors of the model estimates were 2.3%...

Argonne Geothermal Geochemical Database v2.0

DOE Data Explorer

Harto, Christopher

2013-05-22

A database of geochemical data from potential geothermal sources aggregated from multiple sources as of March 2010. The database contains fields for the location, depth, temperature, pH, total dissolved solids concentration, chemical composition, and date of sampling. A separate tab contains data on non-condensible gas compositions. The database contains records for over 50,000 wells, although many entries are incomplete. Current versions of source documentation are listed in the dataset.

Basin Assessment Spatial Planning Platform

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

The tool is intended to facilitate hydropower development and water resource planning by improving synthesis and interpretation of disparate spatial datasets that are considered in development actions (e.g., hydrological characteristics, environmentally and culturally sensitive areas, existing or proposed water power resources, climate-informed forecasts). The tool enables this capability by providing a unique framework for assimilating, relating, summarizing, and visualizing disparate spatial data through the use of spatial aggregation techniques, relational geodatabase platforms, and an interactive web-based Geographic Information Systems (GIS). Data are aggregated and related based on shared intersections with a common spatial unit; in this case, industry-standard hydrologic drainagemore » areas for the U.S. (National Hydrography Dataset) are used as the spatial unit to associate planning data. This process is performed using all available scalar delineations of drainage areas (i.e., region, sub-region, basin, sub-basin, watershed, sub-watershed, catchment) to create spatially hierarchical relationships among planning data and drainages. These entity-relationships are stored in a relational geodatabase that provides back-end structure to the web GIS and its widgets. The full technology stack was built using all open-source software in modern programming languages. Interactive widgets that function within the viewport are also compatible with all modern browsers.« less

Innovations in user-defined analysis: dynamic grouping and customized user datasets in VistaPHw.

PubMed

Solet, David; Glusker, Ann; Laurent, Amy; Yu, Tianji

2006-01-01

Flexible, ready access to community health assessment data is a feature of innovative Web-based data query systems. An example is VistaPHw, which provides access to Washington state data and statistics used in community health assessment. Because of its flexible analysis options, VistaPHw customizes local, population-based results to be relevant to public health decision-making. The advantages of two innovations, dynamic grouping and the Custom Data Module, are described. Dynamic grouping permits the creation of user-defined aggregations of geographic areas, age groups, race categories, and years. Standard VistaPHw measures such as rates, confidence intervals, and other statistics may then be calculated for the new groups. Dynamic grouping has provided data for major, successful grant proposals, building partnerships with local governments and organizations, and informing program planning for community organizations. The Custom Data Module allows users to prepare virtually any dataset so it may be analyzed in VistaPHw. Uses for this module may include datasets too sensitive to be placed on a Web server or datasets that are not standardized across the state. Limitations and other system needs are also discussed.

Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

NASA Astrophysics Data System (ADS)

Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

2011-06-01

For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario.

PubMed

Alvarado-Uribe, Joanna; Gómez-Oliva, Andrea; Barrera-Animas, Ari Yair; Molina, Germán; Gonzalez-Mendoza, Miguel; Parra-Meroño, María Concepción; Jara, Antonio J

2018-03-17

Nowadays, Physical Web together with the increase in the use of mobile devices, Global Positioning System (GPS), and Social Networking Sites (SNS) have caused users to share enriched information on the Web such as their tourist experiences. Therefore, an area that has been significantly improved by using the contextual information provided by these technologies is tourism. In this way, the main goals of this work are to propose and develop an algorithm focused on the recommendation of Smart Point of Interaction (Smart POI) for a specific user according to his/her preferences and the Smart POIs' context. Hence, a novel Hybrid Recommendation Algorithm (HyRA) is presented by incorporating an aggregation operator into the user-based Collaborative Filtering (CF) algorithm as well as including the Smart POIs' categories and geographical information. For the experimental phase, two real-world datasets have been collected and preprocessed. In addition, one Smart POIs' categories dataset was built. As a result, a dataset composed of 16 Smart POIs, another constituted by the explicit preferences of 200 respondents, and the last dataset integrated by 13 Smart POIs' categories are provided. The experimental results show that the recommendations suggested by HyRA are promising.

HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario

PubMed Central

Gómez-Oliva, Andrea; Molina, Germán

2018-01-01

Nowadays, Physical Web together with the increase in the use of mobile devices, Global Positioning System (GPS), and Social Networking Sites (SNS) have caused users to share enriched information on the Web such as their tourist experiences. Therefore, an area that has been significantly improved by using the contextual information provided by these technologies is tourism. In this way, the main goals of this work are to propose and develop an algorithm focused on the recommendation of Smart Point of Interaction (Smart POI) for a specific user according to his/her preferences and the Smart POIs’ context. Hence, a novel Hybrid Recommendation Algorithm (HyRA) is presented by incorporating an aggregation operator into the user-based Collaborative Filtering (CF) algorithm as well as including the Smart POIs’ categories and geographical information. For the experimental phase, two real-world datasets have been collected and preprocessed. In addition, one Smart POIs’ categories dataset was built. As a result, a dataset composed of 16 Smart POIs, another constituted by the explicit preferences of 200 respondents, and the last dataset integrated by 13 Smart POIs’ categories are provided. The experimental results show that the recommendations suggested by HyRA are promising. PMID:29562590

Population specific biomarkers of human aging: a big data study using South Korean, Canadian and Eastern European patient populations.

PubMed

Mamoshina, Polina; Kochetov, Kirill; Putin, Evgeny; Cortese, Franco; Aliper, Alexander; Lee, Won-Suk; Ahn, Sung-Min; Uhn, Lee; Skjodt, Neil; Kovalchuk, Olga; Scheibye-Knudsen, Morten; Zhavoronkov, Alex

2018-01-11

Accurate and physiologically meaningful biomarkers for human aging are key to assessing anti-aging therapies. Given ethnic differences in health, diet, lifestyle, behaviour, environmental exposures and even average rate of biological aging, it stands to reason that aging clocks trained on datasets obtained from specific ethnic populations are more likely to account for these potential confounding factors, resulting in an enhanced capacity to predict chronological age and quantify biological age. Here we present a deep learning-based hematological aging clock modeled using the large combined dataset of Canadian, South Korean and Eastern European population blood samples that show increased predictive accuracy in individual populations compared to population-specific hematologic aging clocks. The performance of models was also evaluated on publicly-available samples of the American population from the National Health and Nutrition Examination Survey (NHANES). In addition, we explored the association between age predicted by both population-specific and combined hematological clocks and all-cause mortality. Overall, this study suggests a) the population-specificity of aging patterns and b) hematologic clocks predicts all-cause mortality. Proposed models added to the freely available Aging.AI system allowing improved ability to assess human aging. © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America.

Defining the natural fracture network in a shale gas play and its cover succession: The case of the Utica Shale in eastern Canada

NASA Astrophysics Data System (ADS)

Ladevèze, P.; Séjourné, S.; Rivard, C.; Lavoie, D.; Lefebvre, R.; Rouleau, A.

2018-03-01

In the St. Lawrence sedimentary platform (eastern Canada), very little data are available between shallow fresh water aquifers and deep geological hydrocarbon reservoir units (here referred to as the intermediate zone). Characterization of this intermediate zone is crucial, as the latter controls aquifer vulnerability to operations carried out at depth. In this paper, the natural fracture networks in shallow aquifers and in the Utica shale gas reservoir are documented in an attempt to indirectly characterize the intermediate zone. This study used structural data from outcrops, shallow observation well logs and deep shale gas well logs to propose a conceptual model of the natural fracture network. Shallow and deep fractures were categorized into three sets of steeply-dipping fractures and into a set of bedding-parallel fractures. Some lithological and structural controls on fracture distribution were identified. The regional geologic history and similarities between the shallow and deep fracture datasets allowed the extrapolation of the fracture network characterization to the intermediate zone. This study thus highlights the benefits of using both datasets simultaneously, while they are generally interpreted separately. Recommendations are also proposed for future environmental assessment studies in which the existence of preferential flow pathways and potential upward fluid migration toward shallow aquifers need to be identified.

Long-term study of aerosol-cloud-precipitation interaction over the eastern part of India using satellite observations during pre-monsoon season

NASA Astrophysics Data System (ADS)

Kant, Sunny; Panda, Jagabandhu; Pani, Shantanu Kumar; Wang, Pao K.

2018-05-01

This study attempts to analyze possible aerosol-cloud-precipitation interaction over the eastern part of India including Bhubaneswar city and the whole Odisha region primarily using a long-term satellite-based dataset from 2000 to 2016 during pre-monsoon period. Relationship between aerosol optical depth (AOD), rainfall, and cloud properties is examined by taking convectively driven rain events. The two-sample student's t test is used to compute "p" value of datasets that are statically significant. Role of aerosols in governing cloud properties is analyzed through the variation of COD (cloud optical depth) and CER (cloud effective radius) in the AOD ranges 0.2-0.8. A relatively stronger and affirmative AOD-CER relationship is observed over Bhubaneswar city compared to Odisha region though the aerosols still play an appreciable role for the later too. The AOD-COD relationship is weak over both the regions. For Odisha, relationships between aerosol and cloud parameters are insignificant irrespective of rainfall regimes. Fostering of heavy rainfall over these regions takes place due to invigoration and microphysical effect during pre-monsoon months, depending upon meteorological conditions. Liquid water content and presence of a mixed-phase zone, both seem to be quite important in the convectively driven precipitation over Odisha region including Bhubaneswar city.

Can Simple Transmission Chains Foster Collective Intelligence in Binary-Choice Tasks?

PubMed

Moussaïd, Mehdi; Seyed Yahosseini, Kyanoush

2016-01-01

In many social systems, groups of individuals can find remarkably efficient solutions to complex cognitive problems, sometimes even outperforming a single expert. The success of the group, however, crucially depends on how the judgments of the group members are aggregated to produce the collective answer. A large variety of such aggregation methods have been described in the literature, such as averaging the independent judgments, relying on the majority or setting up a group discussion. In the present work, we introduce a novel approach for aggregating judgments-the transmission chain-which has not yet been consistently evaluated in the context of collective intelligence. In a transmission chain, all group members have access to a unique collective solution and can improve it sequentially. Over repeated improvements, the collective solution that emerges reflects the judgments of every group members. We address the question of whether such a transmission chain can foster collective intelligence for binary-choice problems. In a series of numerical simulations, we explore the impact of various factors on the performance of the transmission chain, such as the group size, the model parameters, and the structure of the population. The performance of this method is compared to those of the majority rule and the confidence-weighted majority. Finally, we rely on two existing datasets of individuals performing a series of binary decisions to evaluate the expected performances of the three methods empirically. We find that the parameter space where the transmission chain has the best performance rarely appears in real datasets. We conclude that the transmission chain is best suited for other types of problems, such as those that have cumulative properties.

Can Simple Transmission Chains Foster Collective Intelligence in Binary-Choice Tasks?

PubMed Central

Moussaïd, Mehdi; Seyed Yahosseini, Kyanoush

2016-01-01

In many social systems, groups of individuals can find remarkably efficient solutions to complex cognitive problems, sometimes even outperforming a single expert. The success of the group, however, crucially depends on how the judgments of the group members are aggregated to produce the collective answer. A large variety of such aggregation methods have been described in the literature, such as averaging the independent judgments, relying on the majority or setting up a group discussion. In the present work, we introduce a novel approach for aggregating judgments—the transmission chain—which has not yet been consistently evaluated in the context of collective intelligence. In a transmission chain, all group members have access to a unique collective solution and can improve it sequentially. Over repeated improvements, the collective solution that emerges reflects the judgments of every group members. We address the question of whether such a transmission chain can foster collective intelligence for binary-choice problems. In a series of numerical simulations, we explore the impact of various factors on the performance of the transmission chain, such as the group size, the model parameters, and the structure of the population. The performance of this method is compared to those of the majority rule and the confidence-weighted majority. Finally, we rely on two existing datasets of individuals performing a series of binary decisions to evaluate the expected performances of the three methods empirically. We find that the parameter space where the transmission chain has the best performance rarely appears in real datasets. We conclude that the transmission chain is best suited for other types of problems, such as those that have cumulative properties. PMID:27880825

Turkish Cypriot paternal lineages bear an autochthonous character and closest resemblance to those from neighbouring Near Eastern populations.

PubMed

Gurkan, Cemal; Sevay, Huseyin; Demirdov, Damla Kanliada; Hossoz, Sinem; Ceker, Deren; Teralı, Kerem; Erol, Ayla Sevim

2017-03-01

Cyprus is an island in the Eastern Mediterranean Sea with a documented history of human settlements dating back over 10,000 years. To investigate the paternal lineages of a representative population from Cyprus in the context of the larger Near Eastern/Southeastern European genetic landscape. Three hundred and eighty samples from the second most populous ethnic group in Cyprus (Turkish Cypriots) were analysed at 17 Y-chromosomal short tandem repeat (Y-STR) loci. A haplotype diversity of 0.9991 was observed, along with a number of allelic variants, multi-allelic patterns and a most frequent haplotype that have not previously been reported elsewhere. Pairwise genetic distance comparisons of the Turkish Cypriot Y-STR dataset and Y-chromosomal haplogroup distribution with those from Near East/Southeastern Europe both suggested a closer genetic connection with the Near Eastern populations. Median-joining network analyses of the most frequent haplogroups also revealed some evidence towards in situ radiation. Turkish Cypriot paternal lineages seem to bear an autochthonous character and closest genetic connection with the neighbouring Near Eastern populations. These observations are further underscored by the fact that the haplogroups associated with the spread of Neolithic Agricultural Revolution from the Fertile Crescent (E1b1b/J1/J2/G2a) dominate (>70%) the Turkish Cypriot haplogroup distribution.

Development of a global historic monthly mean precipitation dataset

NASA Astrophysics Data System (ADS)

Yang, Su; Xu, Wenhui; Xu, Yan; Li, Qingxiang

2016-04-01

Global historic precipitation dataset is the base for climate and water cycle research. There have been several global historic land surface precipitation datasets developed by international data centers such as the US National Climatic Data Center (NCDC), European Climate Assessment & Dataset project team, Met Office, etc., but so far there are no such datasets developed by any research institute in China. In addition, each dataset has its own focus of study region, and the existing global precipitation datasets only contain sparse observational stations over China, which may result in uncertainties in East Asian precipitation studies. In order to take into account comprehensive historic information, users might need to employ two or more datasets. However, the non-uniform data formats, data units, station IDs, and so on add extra difficulties for users to exploit these datasets. For this reason, a complete historic precipitation dataset that takes advantages of various datasets has been developed and produced in the National Meteorological Information Center of China. Precipitation observations from 12 sources are aggregated, and the data formats, data units, and station IDs are unified. Duplicated stations with the same ID are identified, with duplicated observations removed. Consistency test, correlation coefficient test, significance t-test at the 95% confidence level, and significance F-test at the 95% confidence level are conducted first to ensure the data reliability. Only those datasets that satisfy all the above four criteria are integrated to produce the China Meteorological Administration global precipitation (CGP) historic precipitation dataset version 1.0. It contains observations at 31 thousand stations with 1.87 × 107 data records, among which 4152 time series of precipitation are longer than 100 yr. This dataset plays a critical role in climate research due to its advantages in large data volume and high density of station network, compared to other datasets. Using the Penalized Maximal t-test method, significant inhomogeneity has been detected in historic precipitation datasets at 340 stations. The ratio method is then employed to effectively remove these remarkable change points. Global precipitation analysis based on CGP v1.0 shows that rainfall has been increasing during 1901-2013 with an increasing rate of 3.52 ± 0.5 mm (10 yr)-1, slightly higher than that in the NCDC data. Analysis also reveals distinguished long-term changing trends at different latitude zones.

Spatially-explicit estimation of geographical representation in large-scale species distribution datasets.

PubMed

Kalwij, Jesse M; Robertson, Mark P; Ronk, Argo; Zobel, Martin; Pärtel, Meelis

2014-01-01

Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution dataset mergers, such as the one exemplified here, can serve as a baseline towards comprehensive species distribution datasets.

Comparing apples and oranges: the Community Intercomparison Suite

NASA Astrophysics Data System (ADS)

Schutgens, Nick; Stier, Philip; Pascoe, Stephen

2014-05-01

Visual representation and comparison of geoscientific datasets presents a huge challenge due to the large variety of file formats and spatio-temporal sampling of data (be they observations or simulations). The Community Intercomparison Suite attempts to greatly simplify these tasks for users by offering an intelligent but simple command line tool for visualisation and colocation of diverse datasets. In addition, CIS can subset and aggregate large datasets into smaller more manageable datasets. Our philosophy is to remove as much as possible the need for specialist knowledge by the user of the structure of a dataset. The colocation of observations with model data is as simple as: "cis col ::" which will resample the simulation data to the spatio-temporal sampling of the observations, contingent on a few user-defined options that specify a resampling kernel. CIS can deal with both gridded and ungridded datasets of 2, 3 or 4 spatio-temporal dimensions. It can handle different spatial coordinates (e.g. longitude or distance, altitude or pressure level). CIS supports both HDF, netCDF and ASCII file formats. The suite is written in Python with entirely publicly available open source dependencies. Plug-ins allow a high degree of user-moddability. A web-based developer hub includes a manual and simple examples. CIS is developed as open source code by a specialist IT company under supervision of scientists from the University of Oxford as part of investment in the JASMIN superdatacluster facility at the Centre of Environmental Data Archival.

Benthic bioindicators from the lakes of Northern Yakutia (Siberia, Russia) in paleoclimatic research

NASA Astrophysics Data System (ADS)

Tumanov, O. N.; Nazarova, L. B.; Frolova, L. A.; Pestryakova, L. A.

2012-04-01

High latitude regions are particularly affected by global climate change. Aquatic ecosystems are known to respond quickly and sensitively to such changes (Carpenter et al., 1992; Findlay et al. 2001; Smol et al., 2005). This effect is especially dramatic in regions with continental climates such as Northern and Eastern Siberia. In 2008, Russian-German expedition investigated 33 lakes of Kolyma river basin, North-Eastern Yakutia. The region of investigation is located in the mouth of Kolyma river between approximately 68°2' and 69°4' N and between 159°8' and 161°9' E. It's a most north-eastern region of Yakutia, so it's suitable for paleolimnological investigations. The investigated lakes are situated along the 200 km transect crossing 3 vegetation zones: polygonal tundra, forest tundra and northern taiga. The main aims were establishing a calibration dataset for paleoenvironmental reconstructions by using aquatic organisms, investigation of limnological variables and the influence of the environmental conditions on distribution of aquatic organisms in Yakutian lakes. The modern benthic fauna of the lakes is represented by 89 taxa from 14 taxonomic groups. The most abundant group was Mollusca. The most taxonomically diverse group was Chironomidae. A unique for this region species were discovered, such as Cincinna kamchatica, Physa jarochnovitschae, Colymbetes dolabratus, Ilybius wasastjernae, Xestochironomus sp., Agrypnia sp. etc. Cluster analysis of taxonomical composition of the benthic fauna of these lakes showed high dependency to vegetation zones. The highest levels of hydrobiological indexes (Shannon, Evenness, species richness) were registered in forest tundra. CCA analysis showed that the most influential factors in species distribution were climate-dependant factors, such as mean Tair of July, pH and water depth. Data from taxonomical analysis of Chironomidae group were used for establishing a calibration dataset for paleoenvironmental reconstructions.

Synchrony between reanalysis-driven RCM simulations and observations: variation with time scale

NASA Astrophysics Data System (ADS)

de Elía, Ramón; Laprise, René; Biner, Sébastien; Merleau, James

2017-04-01

Unlike coupled global climate models (CGCMs) that run in a stand-alone mode, nested regional climate models (RCMs) are driven by either a CGCM or a reanalysis dataset. This feature makes high correlations between the RCM simulation and its driver possible. When the driving dataset is a reanalysis, time correlations between RCM output and observations are also common and to be expected. In certain situations time correlation between driver and driven RCM is of particular interest and techniques have been developed to increase it (e.g. large-scale spectral nudging). For such cases, a question that remains open is whether aggregating in time increases the correlation between RCM output and observations. That is, although the RCM may be unable to reproduce a given daily event, whether it will still be able to satisfactorily simulate an anomaly on a monthly or annual basis. This is a preconception that the authors of this work and others in the community have held, perhaps as a natural extension of the properties of upscaling or aggregating other statistics such as the mean squared error. Here we explore analytically four particular cases that help us partially answer this question. In addition, we use observations datasets and RCM-simulated data to illustrate our findings. Results indicate that time upscaling does not necessarily increase time correlations, and that those interested in achieving high monthly or annual time correlations between RCM output and observations may have to do so by increasing correlation as much as possible at the shortest time scale. This may indicate that even when only concerned with time correlations at large temporal scale, large-scale spectral nudging acting at the time-step level may have to be used.

Aerosol direct and indirect radiative effect over Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Georgoulias, Aristeidis; Alexandri, Georgia; Zanis, Prodromos; Ntogras, Christos; Poeschl, Ulrich; Kourtidis, Kostas

In this work, we present results from the QUADIEEMS project which is focused on the aerosol-cloud relations and the aerosol direct and indirect radiative effect over the region of Eastern Mediterranean. First, a gridded dataset at a resolution of 0.1x0.1 degrees (~10km) with aerosol and cloud related parameters was compiled, using level-2 satellite observations from MODIS TERRA (3/2000-12/2012) and AQUA (7/2002-12/2012). The aerosol gridded dataset has been validated against sunphotometric measurements from 12 AERONET ground stations, showing that generally MODIS overestimates aerosol optical depth (AOD550). Then, the AOD550 and fine mode ratio (FMR550) data from MODIS were combined with aerosol index (AI) data from the Earth Probe TOMS and OMI satellite sensors, wind field data from the ERA-interim reanalysis and AOD550 data for various aerosol types from the GOCART model and the MACC reanalysis to quantify the relative contribution of different aerosol types (marine, dust, anthropogenic, fine-mode natural) to the total AOD550. The aerosol-cloud relations over the region were investigated with the use of the joint high resolution aerosol-cloud gridded dataset. Specifically, we focused on the seasonal relations between the cloud droplet number concentration (CDNC) and AOD550. The aerosol direct and first indirect radiative effect was then calculated for each aerosol type separately making use of the aerosol relative contribution to the total AOD550, the CDND-AOD550 relations and satellite-based parameterizations. The direct radiative effect was also quantified using simulations from a regional climate model (REGCM4), simulations with a radiative transfer model (SBDART) and the three methods were finally intervalidated.

Equine grass sickness in Scotland: A case-control study of environmental geochemical risk factors.

PubMed

Wylie, C E; Shaw, D J; Fordyce, F M; Lilly, A; Pirie, R S; McGorum, B C

2016-11-01

We hypothesised that the apparent geographical distribution of equine grass sickness (EGS) is partly attributable to suboptimal levels of soil macro- and trace elements in fields where EGS occurs. If proven, altering levels of particular elements could be used to reduce the risk of EGS. To determine whether the geographical distribution of EGS cases in eastern Scotland is associated with the presence or absence of particular environmental chemical elements. Retrospective time-matched case-control study. This study used data for 455 geo-referenced EGS cases and 910 time-matched controls in eastern Scotland, and geo-referenced environmental geochemical data from the British Geological Survey Geochemical Baseline Survey of the Environment stream sediment (G-BASE) and the James Hutton Institute, National Soil Inventory of Scotland (NSIS) datasets. Multivariable statistical analyses identified clusters of three main elements associated with cases from (i) the G-BASE dataset - higher environmental Ti and lower Zn, and (ii) the NSIS dataset - higher environmental Ti and lower Cr. There was also some evidence from univariable analyses for lower Al, Cd, Cu, Ni and Pb and higher Ca, K, Mo, Na and Se environmental concentrations being associated with a case. Results were complicated by a high degree of correlation between most geochemical elements. The work presented here would appear to reflect soil- not horse-level risk factors for EGS, but due to the complexity of the correlations between elements, further work is required to determine whether these associations reflect causality, and consequently whether interventions to alter concentrations of particular elements in soil, or in grazing horses, could potentially reduce the risk of EGS. The effect of chemical elements on the growth of those soil microorganisms implicated in EGS aetiology also warrants further study. © 2015 The The Authors Equine Veterinary Journal © 2015 EVJ Ltd.

Genomic timetree and historical biogeography of Caribbean island ameiva lizards (Pholidoscelis: Teiidae).

PubMed

Tucker, Derek B; Hedges, Stephen Blair; Colli, Guarino R; Pyron, Robert Alexander; Sites, Jack W

2017-09-01

The phylogenetic relationships and biogeographic history of Caribbean island ameivas ( Pholidoscelis ) are not well-known because of incomplete sampling, conflicting datasets, and poor support for many clades. Here, we use phylogenomic and mitochondrial DNA datasets to reconstruct a well-supported phylogeny and assess historical colonization patterns in the group. We obtained sequence data from 316 nuclear loci and one mitochondrial marker for 16 of 19 extant species of the Caribbean endemic genus Pholidoscelis . Phylogenetic analyses were carried out using both concatenation and species tree approaches. To estimate divergence times, we used fossil teiids to calibrate a timetree which was used to elucidate the historical biogeography of these lizards. All phylogenetic analyses recovered four well-supported species groups (clades) recognized previously and supported novel relationships of those groups, including a ( P. auberi + P. lineolatus ) clade (western + central Caribbean), and a ( P. exsul + P. plei ) clade (eastern Caribbean). Divergence between Pholidoscelis and its sister clade was estimated to have occurred ~25 Ma, with subsequent diversification on Caribbean islands occurring over the last 11 Myr. Of the six models compared in the biogeographic analyses, the scenario which considered the distance among islands and allowed dispersal in all directions best fit the data. These reconstructions suggest that the ancestor of this group colonized either Hispaniola or Puerto Rico from Middle America. We provide a well-supported phylogeny of Pholidoscelis with novel relationships not reported in previous studies that were based on significantly smaller datasets. We propose that Pholidoscelis colonized the eastern Greater Antilles from Middle America based on our biogeographic analysis, phylogeny, and divergence time estimates. The closing of the Central American Seaway and subsequent formation of the modern Atlantic meridional overturning circulation may have promoted dispersal in this group.

The isolation of the temperature effect on branched GDGT distribution in an elevation transect of the Eastern Cordillera, Colombia

NASA Astrophysics Data System (ADS)

Anderson, V. J.; Shanahan, T. M.; Saylor, J.; Horton, B. K.

2012-12-01

Recently, the distribution of branched GDGT's (glycerol dialkyl glycerol tetraethers) has been proposed as a proxy for temperature and pH in soils via the MBT/CBT index, and has been used to reconstruct past temperature variations in a number of settings ranging from marine sediments to loess deposits and paleosols. However, empirical calibrations of the MBT/CBT index against temperature show significant scatter, leading to uncertainties as large as ±2 degrees C . In this study we seek to add to and improve upon the existing soil calibration using a new set of samples spanning a large elevation (and temperature) gradient in the Eastern Cordillera of Colombia. At each site we buried temperature loggers to constrain the diurnal and seasonal temperature experienced by each soil sample. Located only 5 degrees north of the equator, our sites experience a very small seasonal temperature variation - most sites display an annual range of less than 4 degrees C. In addition, the pH of all of the soils is almost invariant across the transect, with the vast majority of samples having pH's between 4 and 5. This dataset represents a "best-case" scenario - small variations in seasonal temperature, pH, and well-constrained instrumental data - which allow us to examine the brGDGT-temperature relationship in the absence of major confounding factors such as seasonality and soil chemistry. Interestingly, the relationship between temperature and the MBT/CBT index is not improved using this dataset, suggesting that these factors are not the cause of the anomalous scatter in the calibration dataset. However, we find that using other parameterizations for the regression equation instead of the MBT and CBT indices, the errors in our temperature estimates are significantly reduced.

Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest.

PubMed

Fraimout, Antoine; Debat, Vincent; Fellous, Simon; Hufbauer, Ruth A; Foucaud, Julien; Pudlo, Pierre; Marin, Jean-Michel; Price, Donald K; Cattel, Julien; Chen, Xiao; Deprá, Marindia; François Duyck, Pierre; Guedot, Christelle; Kenis, Marc; Kimura, Masahito T; Loeb, Gregory; Loiseau, Anne; Martinez-Sañudo, Isabel; Pascual, Marta; Polihronakis Richmond, Maxi; Shearer, Peter; Singh, Nadia; Tamura, Koichiro; Xuéreb, Anne; Zhang, Jinping; Estoup, Arnaud

2017-04-01

Deciphering invasion routes from molecular data is crucial to understanding biological invasions, including identifying bottlenecks in population size and admixture among distinct populations. Here, we unravel the invasion routes of the invasive pest Drosophila suzukii using a multi-locus microsatellite dataset (25 loci on 23 worldwide sampling locations). To do this, we use approximate Bayesian computation (ABC), which has improved the reconstruction of invasion routes, but can be computationally expensive. We use our study to illustrate the use of a new, more efficient, ABC method, ABC random forest (ABC-RF) and compare it to a standard ABC method (ABC-LDA). We find that Japan emerges as the most probable source of the earliest recorded invasion into Hawaii. Southeast China and Hawaii together are the most probable sources of populations in western North America, which then in turn served as sources for those in eastern North America. European populations are genetically more homogeneous than North American populations, and their most probable source is northeast China, with evidence of limited gene flow from the eastern US as well. All introduced populations passed through bottlenecks, and analyses reveal five distinct admixture events. These findings can inform hypotheses concerning how this species evolved between different and independent source and invasive populations. Methodological comparisons indicate that ABC-RF and ABC-LDA show concordant results if ABC-LDA is based on a large number of simulated datasets but that ABC-RF out-performs ABC-LDA when using a comparable and more manageable number of simulated datasets, especially when analyzing complex introduction scenarios. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Joint innversion of seismic and magnetotelluric data in the Parkfield Region of California using the normalized cross-gradient constraint

USGS Publications Warehouse

Bennington, Ninfa L.; Zhang, Haijiang; Thurber, Cliff; Bedrosian, Paul A.

2015-01-01

We present jointly inverted models of P-wave velocity (Vp) and electrical resistivity for a two-dimensional profile centered on the San Andreas Fault Observatory at Depth (SAFOD). Significant structural similarity between main features of the separately inverted Vp and resistivity models is exploited by carrying out a joint inversion of the two datasets using the normalized cross-gradient constraint. This constraint favors structurally similar Vp and resistivity images that adequately fit the seismic and magnetotelluric (MT) datasets. The new inversion code, tomoDDMT, merges the seismic inversion code tomoDD and the forward modeling and sensitivity kernel subroutines of the MT inversion code OCCAM2DMT. TomoDDMT is tested on a synthetic dataset and demonstrates the code’s ability to more accurately resolve features of the input synthetic structure relative to the separately inverted resistivity and velocity models. Using tomoDDMT, we are able to resolve a number of key issues raised during drilling at SAFOD. We are able to infer the distribution of several geologic units including the Salinian granitoids, the Great Valley sequence, and the Franciscan Formation. The distribution and transport of fluids at both shallow and great depths is also examined. Low values of velocity/resistivity attributed to a feature known as the Eastern Conductor (EC) can be explained in two ways: the EC is a brine-filled, high porosity region, or this region is composed largely of clay-rich shales of the Franciscan. The Eastern Wall, which lies immediately adjacent to the EC, is unlikely to be a fluid pathway into the San Andreas Fault’s seismogenic zone due to its observed higher resistivity and velocity values.

A study of possible ``reef effects'' caused by a long-term time-lapse camera in the deep North Pacific

NASA Astrophysics Data System (ADS)

Vardaro, M. F.; Parmley, D.; Smith, K. L.

2007-08-01

The aggregation response of fish populations following the addition of artificial structures to seafloor habitats has been well documented in shallow-water reefs and at deeper structures such as oil extraction platforms. A long-term time-lapse camera was deployed for 27 four-month deployment periods at 4100 m in the eastern North Pacific to study abyssal megafauna activity and surface-benthos connections. The unique time-series data set provided by this research presented an opportunity to examine how deep-sea benthopelagic fish and epibenthic megafauna populations were affected by an isolated artificial structure and whether animal surveys at this site were biased by aggregation behavior. Counts were taken of benthopelagic grenadiers, Coryphaenoides spp., observed per week as well as numbers of the epibenthic echinoid Echinocrepis rostrata. No significant correlation ( rs=-0.39; p=0.11) was found between the duration of deployment (in weeks) and the average number of Coryphaenoides observed at the site. There was also no evidence of associative behavior around the time-lapse camera by E. rostrata ( rs=-0.32; p=0.19). The results of our study suggest that abyssal fish and epibenthic megafauna do not aggregate around artificial structures and that long-term time-lapse camera studies should not be impacted by aggregation response behaviors.

Synoptic regimes associated with the eastern Mediterranean wet season cyclone tracks

NASA Astrophysics Data System (ADS)

Almazroui, Mansour; Awad, Adel M.

2016-11-01

The main synoptic patterns associated with the wet season (October-May) eastern Mediterranean cyclones have been analyzed and described using NCEP/NCAR reanalysis datasets for the period 1958-2013. The cyclone tracks detected in the eastern Mediterranean are classified into two types based on their positions: the local tracks and the long tracks. The local tracks are either stationary or short tracks. The long tracks distinguished into eleven very closed and highly correlated clusters, which are presented into three regimes namely the northern, the southern and the eastern border Mediterranean regimes. Among the 940 (44.78% of a total of 2099) long tracks, the northern, southern, and eastern border regime contributes respectively about 53.62%, 41.81% and 5% of the long tracks. In addition, the distribution of the long tracks reveals that a larger proportion of the cyclones are generated at the northern coast during November and spring months, while few cyclones are developed over the eastern Mediterranean border in warm months (April and May). Further, their synoptic features show that the regimes are associated with the extension of Azores high, specifically for each regime, the cyclogenesis areas of its clusters are controlled by the intersection of low level (850 hPa) trough and the position of the upper level (250 hPa) maximum wind. Furthermore, the orientations of clusters are controlled by the extension of Siberian high and the shape of cyclonic trough at 850 hPa. In addition, the synoptic study shows that most of the southern cyclones generated externally by African and Red Sea troughs, while most of the northern and eastern border cyclones are generated internally.

Personality in 100,000 Words: A large-scale analysis of personality and word use among bloggers

PubMed Central

Yarkoni, Tal

2010-01-01

Previous studies have found systematic associations between personality and individual differences in word use. Such studies have typically focused on broad associations between major personality domains and aggregate word categories, potentially masking more specific associations. Here I report the results of a large-scale analysis of personality and word use in a large sample of blogs (N=694). The size of the dataset enabled pervasive correlations with personality to be identified for a broad range of lexical variables, including both aggregate word categories and individual English words. The results replicated category-level findings from previous offline studies, identified numerous novel associations at both a categorical and single-word level, and underscored the value of complementary approaches to the study of personality and word use. PMID:20563301

Reconstructing Druze population history

PubMed Central

Marshall, Scarlett; Das, Ranajit; Pirooznia, Mehdi; Elhaik, Eran

2016-01-01

The Druze are an aggregate of communities in the Levant and Near East living almost exclusively in the mountains of Syria, Lebanon and Israel whose ~1000 year old religion formally opposes mixed marriages and conversions. Despite increasing interest in genetics of the population structure of the Druze, their population history remains unknown. We investigated the genetic relationships between Israeli Druze and both modern and ancient populations. We evaluated our findings in light of three hypotheses purporting to explain Druze history that posit Arabian, Persian or mixed Near Eastern-Levantine roots. The biogeographical analysis localised proto-Druze to the mountainous regions of southeastern Turkey, northern Iraq and southeast Syria and their descendants clustered along a trajectory between these two regions. The mixed Near Eastern–Middle Eastern localisation of the Druze, shown using both modern and ancient DNA data, is distinct from that of neighbouring Syrians, Palestinians and most of the Lebanese, who exhibit a high affinity to the Levant. Druze biogeographic affinity, migration patterns, time of emergence and genetic similarity to Near Eastern populations are highly suggestive of Armenian-Turkish ancestries for the proto-Druze. PMID:27848937

Estimating economic value of agricultural water under changing conditions and the effects of spatial aggregation.

PubMed

Medellín-Azuara, Josué; Harou, Julien J; Howitt, Richard E

2010-11-01

Given the high proportion of water used for agriculture in certain regions, the economic value of agricultural water can be an important tool for water management and policy development. This value is quantified using economic demand curves for irrigation water. Such demand functions show the incremental contribution of water to agricultural production. Water demand curves are estimated using econometric or optimisation techniques. Calibrated agricultural optimisation models allow the derivation of demand curves using smaller datasets than econometric models. This paper introduces these subject areas then explores the effect of spatial aggregation (upscaling) on the valuation of water for irrigated agriculture. A case study from the Rio Grande-Rio Bravo Basin in North Mexico investigates differences in valuation at farm and regional aggregated levels under four scenarios: technological change, warm-dry climate change, changes in agricultural commodity prices, and water costs for agriculture. The scenarios consider changes due to external shocks or new policies. Positive mathematical programming (PMP), a calibrated optimisation method, is the deductive valuation method used. An exponential cost function is compared to the quadratic cost functions typically used in PMP. Results indicate that the economic value of water at the farm level and the regionally aggregated level are similar, but that the variability and distributional effects of each scenario are affected by aggregation. Moderately aggregated agricultural production models are effective at capturing average-farm adaptation to policy changes and external shocks. Farm-level models best reveal the distribution of scenario impacts. Copyright © 2009 Elsevier B.V. All rights reserved.

Dataset of timberland variables used to assess forest conditions in two Southeastern United States' fuelsheds

DOE PAGES

Parish, Esther S.; Dale, Virginia H.; Tobin, Emma; ...

2017-05-27

The data presented in this article are related to the research article entitled “How is wood-based pellet production affecting forest conditions in the southeastern United States?” (Dale et al., 2017). This article describes how United States Forest Service (USFS) Forest Inventory and Analysis (FIA) data from multiple state inventories were aggregated and used to extract ten annual timberland variables for trend analysis in two case study bioenergy fuelshed areas. This dataset is made publically available to enable critical or extended analyses of changes in forest conditions, either for the fuelshed areas supplying the ports of Savannah, Georgia and Chesapeake, Virginia,more » or for other southeastern US forested areas contributing biomass to the export wood pellet industry.« less

Dataset of timberland variables used to assess forest conditions in two Southeastern United States' fuelsheds

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

Parish, Esther S.; Dale, Virginia H.; Tobin, Emma

The data presented in this article are related to the research article entitled “How is wood-based pellet production affecting forest conditions in the southeastern United States?” (Dale et al., 2017). This article describes how United States Forest Service (USFS) Forest Inventory and Analysis (FIA) data from multiple state inventories were aggregated and used to extract ten annual timberland variables for trend analysis in two case study bioenergy fuelshed areas. This dataset is made publically available to enable critical or extended analyses of changes in forest conditions, either for the fuelshed areas supplying the ports of Savannah, Georgia and Chesapeake, Virginia,more » or for other southeastern US forested areas contributing biomass to the export wood pellet industry.« less

Visualizing Big Data Outliers through Distributed Aggregation.

PubMed

Wilkinson, Leland

2017-08-29

Visualizing outliers in massive datasets requires statistical pre-processing in order to reduce the scale of the problem to a size amenable to rendering systems like D3, Plotly or analytic systems like R or SAS. This paper presents a new algorithm, called hdoutliers, for detecting multidimensional outliers. It is unique for a) dealing with a mixture of categorical and continuous variables, b) dealing with big-p (many columns of data), c) dealing with big-n (many rows of data), d) dealing with outliers that mask other outliers, and e) dealing consistently with unidimensional and multidimensional datasets. Unlike ad hoc methods found in many machine learning papers, hdoutliers is based on a distributional model that allows outliers to be tagged with a probability. This critical feature reduces the likelihood of false discoveries.

Comparing apples and oranges: the Community Intercomparison Suite

NASA Astrophysics Data System (ADS)

Schutgens, Nick; Stier, Philip; Kershaw, Philip; Pascoe, Stephen

2015-04-01

Visual representation and comparison of geoscientific datasets presents a huge challenge due to the large variety of file formats and spatio-temporal sampling of data (be they observations or simulations). The Community Intercomparison Suite attempts to greatly simplify these tasks for users by offering an intelligent but simple command line tool for visualisation and colocation of diverse datasets. In addition, CIS can subset and aggregate large datasets into smaller more manageable datasets. Our philosophy is to remove as much as possible the need for specialist knowledge by the user of the structure of a dataset. The colocation of observations with model data is as simple as: "cis col ::" which will resample the simulation data to the spatio-temporal sampling of the observations, contingent on a few user-defined options that specify a resampling kernel. As an example, we apply CIS to a case study of biomass burning aerosol from the Congo. Remote sensing observations, in-situe observations and model data are shown in various plots, with the purpose of either comparing different datasets or integrating them into a single comprehensive picture. CIS can deal with both gridded and ungridded datasets of 2, 3 or 4 spatio-temporal dimensions. It can handle different spatial coordinates (e.g. longitude or distance, altitude or pressure level). CIS supports both HDF, netCDF and ASCII file formats. The suite is written in Python with entirely publicly available open source dependencies. Plug-ins allow a high degree of user-moddability. A web-based developer hub includes a manual and simple examples. CIS is developed as open source code by a specialist IT company under supervision of scientists from the University of Oxford and the Centre of Environmental Data Archival as part of investment in the JASMIN superdatacluster facility.

Eastern Denali Fault surface trace map, eastern Alaska and Yukon, Canada

USGS Publications Warehouse

Bender, Adrian M.; Haeussler, Peter J.

2017-05-04

We map the 385-kilometer (km) long surface trace of the right-lateral, strike-slip Denali Fault between the Totschunda-Denali Fault intersection in Alaska, United States and the village of Haines Junction, Yukon, Canada. In Alaska, digital elevation models based on light detection and ranging and interferometric synthetic aperture radar data enabled our fault mapping at scales of 1:2,000 and 1:10,000, respectively. Lacking such resources in Yukon, we developed new structure-from-motion digital photogrammetry products from legacy aerial photos to map the fault surface trace at a scale of 1:10,000 east of the international border. The section of the fault that we map, referred to as the Eastern Denali Fault, did not rupture during the 2002 Denali Fault earthquake (moment magnitude 7.9). Seismologic, geodetic, and geomorphic evidence, along with a paleoseismic record of past ground-rupturing earthquakes, demonstrate Holocene and contemporary activity on the fault, however. This map of the Eastern Denali Fault surface trace complements other data sets by providing an openly accessible digital interpretation of the location, length, and continuity of the fault’s surface trace based on the accompanying digital topography dataset. Additionally, the digitized fault trace may provide geometric constraints useful for modeling earthquake scenarios and related seismic hazard.

Rainfall-induced soil aggregate breakdown in field experiments at different rainfall intensities and initial soil moisture conditions

NASA Astrophysics Data System (ADS)

Shi, Pu; Thorlacius, Sigurdur; Keller, Thomas; Keller, Martin; Schulin, Rainer

2017-04-01

Soil aggregate breakdown under rainfall impact is an important process in interrill erosion, but is not represented explicitly in water erosion models. Aggregate breakdown not only reduces infiltration through surface sealing during rainfall, but also determines the size distribution of the disintegrated fragments and thus their availability for size-selective sediment transport and re-deposition. An adequate representation of the temporal evolution of fragment mass size distribution (FSD) during rainfall events and the dependence of this dynamics on factors such as rainfall intensity and soil moisture content may help improve mechanistic erosion models. Yet, little is known about the role of those factors in the dynamics of aggregate breakdown under field conditions. In this study, we conducted a series of artificial rainfall experiments on a field silt loam soil to investigate aggregate breakdown dynamics at different rainfall intensity (RI) and initial soil water content (IWC). We found that the evolution of FSD in the course of a rainfall event followed a consistent two-stage pattern in all treatments. The fragment mean weight diameter (MWD) drastically decreased in an approximately exponential way at the beginning of a rainfall event, followed by a further slow linear decrease in the second stage. We proposed an empirical model that describes this temporal pattern of MWD decrease during a rainfall event and accounts for the effects of RI and IWC on the rate parameters. The model was successfully tested using an independent dataset, showing its potential to be used in erosion models for the prediction of aggregate breakdown. The FSD at the end of the experimental rainfall events differed significantly among treatments, indicating that different aggregate breakdown mechanisms responded differently to the variation in initial soil moisture and rainfall intensity. These results provide evidence that aggregate breakdown dynamics needs to be considered in a case-specific manner in modelling sediment mobilization and transport during water erosion events.

An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman filter

NASA Astrophysics Data System (ADS)

Gorsevski, Pece V.; Jankowski, Piotr

2010-08-01

The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve optimal system performances. This paper explores the use of the Kalman filter to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find optimal solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in a case study in the Clearwater National Forest in central Idaho, using existing landslide datasets from roaded and roadless areas and terrain attributes. In this approach, fuzzy membership functions were used to standardize terrain attributes and develop criteria, while the aggregation of the criteria was achieved by the use of a Kalman filter. The approach presented here offers advantages over the classical MCE theory because the final solution includes both the aggregated solution and the areas of uncertainty expressed in terms of standard deviation. A comparison of this methodology with similar approaches suggested that this approach is promising for predicting landslide susceptibility and further application as a spatial decision support system.

Data Albums: An Event Driven Search, Aggregation and Curation Tool for Earth Science

NASA Technical Reports Server (NTRS)

Ramachandran, Rahul; Kulkarni, Ajinkya; Maskey, Manil; Bakare, Rohan; Basyal, Sabin; Li, Xiang; Flynn, Shannon

2014-01-01

Approaches used in Earth science research such as case study analysis and climatology studies involve discovering and gathering diverse data sets and information to support the research goals. To gather relevant data and information for case studies and climatology analysis is both tedious and time consuming. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. In cases where researchers are interested in studying a significant event, they have to manually assemble a variety of datasets relevant to it by searching the different distributed data systems. This paper presents a specialized search, aggregation and curation tool for Earth science to address these challenges. The search rool automatically creates curated 'Data Albums', aggregated collections of information related to a specific event, containing links to relevant data files [granules] from different instruments, tools and services for visualization and analysis, and information about the event contained in news reports, images or videos to supplement research analysis. Curation in the tool is driven via an ontology based relevancy ranking algorithm to filter out non relevant information and data.

The congruence between matrilineal genetic (mtDNA) and geographic diversity of Iranians and the territorial populations

PubMed Central

Bahmanimehr, Ardeshir; Eskandari, Ghafar; Nikmanesh, Fatemeh

2015-01-01

Objective(s): From the ancient era, emergence of Agriculture in the connecting region of Mesopotamia and the Iranian plateau at the foothills of the Zagros Mountains, made Iranian gene pool as an important source of populating the region. It has differentiated the population spread and different language groups. In order to trace the maternal genetic affinity between Iranians and other populations of the area and to establish the place of Iranians in a broad framework of ethnically and linguistically diverse groups of Middle Eastern and South Asian populations, a comparative study of territorial groups was designed and used in the population statistical analysis. Materials and Methods: Mix of 616 samples was sequenced for complete mtDNA or hyper variable regions in this study. A published dataset of neighboring populations was used as a comparison in the Iranian matrilineal lineage study based on mtDNA haplogroups. Results: Statistical analyses data, demonstrate a close genetic structure of all Iranian populations, thus suggesting their origin from a common maternal ancestral gene pool and show that the diverse maternal genetic structure does not reflect population differentiation in the region in their language. Conclusion: In the aggregate of the eastward spreads of proto-Elamo-Dravidian language from the Southwest region of Iran, the Elam province, a reasonable degree of homogeneity has been observed among Iranians in this study. The approach will facilitate our perception of the more detailed relationship of the ethnic groups living in Iran with the other ancient peoples of the area, testing linguistic hypothesis and population movements. PMID:25810873

Redefining climate regions in the United States of America using satellite remote sensing and machine learning for public health applications.

PubMed

Liss, Alexander; Koch, Magaly; Naumova, Elena N

2014-12-01

Existing climate classification has not been designed for an efficient handling of public health scenarios. This work aims to design an objective spatial climate regionalization method for assessing health risks in response to extreme weather. Specific climate regions for the conterminous United States of America (USA) were defined using satellite remote sensing (RS) data and compared with the conventional Köppen-Geiger (KG) divisions. Using the nationwide database of hospitalisations among the elderly (≥65 year olds), we examined the utility of a RS-based climate regionalization to assess public health risk due to extreme weather, by comparing the rate of hospitalisations in response to thermal extremes across climatic regions. Satellite image composites from 2002-2012 were aggregated, masked and compiled into a multi-dimensional dataset. The conterminous USA was classified into 8 distinct regions using a stepwise regionalization approach to limit noise and collinearity (LKN), which exhibited a high degree of consistency with the KG regions and a well-defined regional delineation by annual and seasonal temperature and precipitation values. The most populous was a temperate wet region (10.9 million), while the highest rate of hospitalisations due to exposure to heat and cold (9.6 and 17.7 cases per 100,000 persons at risk, respectively) was observed in the relatively warm and humid south-eastern region. RS-based regionalization demonstrates strong potential for assessing the adverse effects of severe weather on human health and for decision support. Its utility in forecasting and mitigating these effects has to be further explored.

The HBsAg Prevalence Among Blood Donors From Eastern Mediterranean and Middle Eastern Countries: A Systematic Review and Meta-Analysis.

PubMed

Babanejad, Mehran; Izadi, Neda; Najafi, Farid; Alavian, Seyed Moayed

2016-03-01

The world health organization (WHO) recommends that all blood donations should be screened for evidence of infections, such as hepatitis B. The present study aimed to determine the prevalence of hepatitis B surface antigen (HBsAg) in blood donors at the eastern Mediterranean region office (EMRO) of the WHO and middle eastern countries. A meta-analysis was carried out based on the results of an electronic literature search of PubMed, Ovid, Scopus, and Google Scholar for articles published from January 1, 2000, to August 31, 2015. In accordance with a significant homogeneity test and a large value of I2, the random effects model was used to aggregate data from the studies and produce the pooled estimates using the "Metan" command. We included 66 eligible studies. The pooled prevalence of HBsAg in blood donors of both EMRO and middle eastern (E and M) countries was 2.03% (95% confidence interval [CI]: 1.79 - 2.26). In addition, the prevalence rates in the EMRO countries was 1.99% (95% CI: 1.84 - 2.14) and 1.62% in the Middle Eastern countries (95% CI: 1.36 - 1.88). The prevalence among blood donors with more than one study was 1.58% in Egypt, 0.58% in Iran, 0.67% in Iraq, 2.84% in Pakistan, 3.02% in Saudi Arabia, 1.68% in Turkey, and 5.05% in Yemen. Based on the WHO classification of hepatitis B virus (HBV) prevalence, the prevalence of HBsAg in blood donors from E and M countries reached an intermediate level. However, there were low prevalence levels in some E and M countries.

Sea-floor geology and topography offshore in Eastern Long Island Sound

USGS Publications Warehouse

Poppe, L.J.; McMullen, K.Y.; Ackerman, S.D.; Blackwood, D.S.; Schaer, J.D.; Forrest, M.R.; Ostapenko, A.J.; Doran, E.F.

2011-01-01

A gridded multibeam bathymetric dataset covers approximately 133.7 square kilometers of sea floor offshore in eastern Long Island Sound. Although originally collected for charting purposes during National Oceanic and Atmospheric Administration hydrographic survey H11997, these acoustic data, and the sea-floor sampling and photography stations subsequently occupied to verify them during USGS cruise 2010-015-FA, are part of an expanding series of studies that provide a fundamental framework for research and resource management (for example, cables, pipelines, and dredging) activities in this major East Coast estuary. Results show the composition and terrain of the seabed and provide information on sediment transport and benthic habitat. Bedrock outcrops, erosional outliers, lag deposits of boulders, scour depressions, and extensive gravel pavements are common in the eastern part of the study area. These features, which result from the near-constant exposure to strong tidal currents, indicate sedimentary environments dominated by processes associated with erosion. Large fields of transverse and barchanoid sand waves in the western part of the study area reflect slightly lower energy levels and sedimentary environments where processes associated with coarse bedload transport prevail.

Characterization of mesoscale convective systems over the eastern Pacific during boreal summer

NASA Astrophysics Data System (ADS)

Berthet, Sarah; Rouquié, Bastien; Roca, Rémy

2015-04-01

The eastern Pacific Ocean is one of the most active tropical disturbances formation regions on earth. This preliminary study is part of a broader project that aims to investigate how mesoscale convective systems (MCS) may be related to these synoptic disturbances with emphasis on local initiation of tropical depressions. As a first step, the main characteristics of the MCS over the eastern Pacific are documented with the help of the recently developed TOOCAN tracking algorithm (Fiolleau and Roca, 2013) applied to the infrared satellite imagery data from GOES-W and -E for the period JJAS 2012-2014. More specifically, the spatial distribution of the MCS population, the statistics of their spatial extensions and durations, as well as their trajectories and propagation speeds are summarized. In addition the environment of the MCS will be investigated using various Global Precipitation Mission datasets and the Megha-Tropiques/SAPHIR humidity microwave sounder derived products. Reference: Fiolleau T. and R. Roca, (2013), An Algorithm For The Detection And Tracking Of Tropical Mesoscale Convective Systems Using Infrared Images From Geostationary Satellite, Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2012.2227762.

Integrating Federal and State data records to report progress in establishing agricultural conservation practices on Chesapeake Bay farms

USGS Publications Warehouse

Hively, W. Dean; Devereux, Olivia H.; Claggett, Peter

2013-01-01

In response to the Executive Order for Chesapeake Bay Protection and Restoration (E.O. #13508, May 12, 2009), the U.S. Geological Survey (USGS) took on the task of acquiring and assessing agricultural conservation practice data records for U.S. Department of Agriculture (USDA) programs, and transferred those datasets in aggregated format to State jurisdictional agencies for use in reporting conservation progress to the Chesapeake Bay Program Partnership (CBP Partnership). Under the guidelines and regulations that have been developed to protect and restore water-quality in the Chesapeake Bay, the six State jurisdictions that fall within the Chesapeake Bay watershed are required to report their progress in promoting agricultural conservation practices to the CBP Partnership on an annual basis. The installation and adoption of agricultural best management practices is supported by technical and financial assistance from both Federal and State conservation programs. The farm enrollment data for USDA conservation programs are confidential, but agencies can obtain access to the privacy-protected data if they are established as USDA Conservation Cooperators. The datasets can also be released to the public if they are first aggregated to protect farmer privacy. In 2012, the USGS used its Conservation Cooperator status to obtain implementation data for conservation programs sponsored by the USDA Natural Resources Conservation Service (NRCS) and the USDA Farm Service Agency (FSA) for farms within the Chesapeake Bay watershed. Three jurisdictions (Delaware, Pennsylvania, and West Virginia) used the USGS-provided aggregated dataset to report conservation progress in 2012, whereas the remaining three jurisdictions (Maryland, New York, and Virginia) used jurisdictional Conservation Cooperator Agreements to obtain privacy-protected data directly from the USDA. This report reviews the status of conservation data sharing between the USDA and the various jurisdictions, discusses the methods that were used by the USGS in 2012 to collect and process USDA agricultural conservation data, and also documents methods that were used by the jurisdictions to integrate Federal and State data records, reduce double counting, and provide an accurate reporting of conservation practices to the CBP Partnership’s Annual Progress Review. A similar tracking, reporting, and assessment will occur in future years, as State and Federal governments and nongovernmental organizations continue to work with farmers and conservation districts to reduce the impacts of agriculture on water-quality.

Estimating irrigation water use in the humid eastern United States

USGS Publications Warehouse

Levin, Sara B.; Zarriello, Phillip J.

2013-01-01

Accurate accounting of irrigation water use is an important part of the U.S. Geological Survey National Water-Use Information Program and the WaterSMART initiative to help maintain sustainable water resources in the Nation. Irrigation water use in the humid eastern United States is not well characterized because of inadequate reporting and wide variability associated with climate, soils, crops, and farming practices. To better understand irrigation water use in the eastern United States, two types of predictive models were developed and compared by using metered irrigation water-use data for corn, cotton, peanut, and soybean crops in Georgia and turf farms in Rhode Island. Reliable metered irrigation data were limited to these areas. The first predictive model that was developed uses logistic regression to predict the occurrence of irrigation on the basis of antecedent climate conditions. Logistic regression equations were developed for corn, cotton, peanut, and soybean crops by using weekly irrigation water-use data from 36 metered sites in Georgia in 2009 and 2010 and turf farms in Rhode Island from 2000 to 2004. For the weeks when irrigation was predicted to take place, the irrigation water-use volume was estimated by multiplying the average metered irrigation application rate by the irrigated acreage for a given crop. The second predictive model that was developed is a crop-water-demand model that uses a daily soil water balance to estimate the water needs of a crop on a given day based on climate, soil, and plant properties. Crop-water-demand models were developed independently of reported irrigation water-use practices and relied on knowledge of plant properties that are available in the literature. Both modeling approaches require accurate accounting of irrigated area and crop type to estimate total irrigation water use. Water-use estimates from both modeling methods were compared to the metered irrigation data from Rhode Island and Georgia that were used to develop the models as well as two independent validation datasets from Georgia and Virginia that were not used in model development. Irrigation water-use estimates from the logistic regression method more closely matched mean reported irrigation rates than estimates from the crop-water-demand model when compared to the irrigation data used to develop the equations. The root mean squared errors (RMSEs) for the logistic regression estimates of mean annual irrigation ranged from 0.3 to 2.0 inches (in.) for the five crop types; RMSEs for the crop-water-demand models ranged from 1.4 to 3.9 in. However, when the models were applied and compared to the independent validation datasets from southwest Georgia from 2010, and from Virginia from 1999 to 2007, the crop-water-demand model estimates were as good as or better at predicting the mean irrigation volume than the logistic regression models for most crop types. RMSEs for logistic regression estimates of mean annual irrigation ranged from 1.0 to 7.0 in. for validation data from Georgia and from 1.8 to 4.9 in. for validation data from Virginia; RMSEs for crop-water-demand model estimates ranged from 2.1 to 5.8 in. for Georgia data and from 2.0 to 3.9 in. for Virginia data. In general, regression-based models performed better in areas that had quality daily or weekly irrigation data from which the regression equations were developed; however, the regression models were less reliable than the crop-water-demand models when applied outside the area for which they were developed. In most eastern coastal states that do not have quality irrigation data, the crop-water-demand model can be used more reliably. The development of predictive models of irrigation water use in this study was hindered by a lack of quality irrigation data. Many mid-Atlantic and New England states do not require irrigation water use to be reported. A survey of irrigation data from 14 eastern coastal states from Maine to Georgia indicated that, with the exception of the data in Georgia, irrigation data in the states that do require reporting commonly did not contain requisite ancillary information such as irrigated area or crop type, lacked precision, or were at an aggregated temporal scale making them unsuitable for use in the development of predictive models. Confidence in the reliability of either modeling method is affected by uncertainty in the reported data from which the models were developed or validated. Only through additional collection of quality data and further study can the accuracy and uncertainty of irrigation water-use estimates be improved in the humid eastern United States.

SHARE: system design and case studies for statistical health information release

PubMed Central

Gardner, James; Xiong, Li; Xiao, Yonghui; Gao, Jingjing; Post, Andrew R; Jiang, Xiaoqian; Ohno-Machado, Lucila

2013-01-01

Objectives We present SHARE, a new system for statistical health information release with differential privacy. We present two case studies that evaluate the software on real medical datasets and demonstrate the feasibility and utility of applying the differential privacy framework on biomedical data. Materials and Methods SHARE releases statistical information in electronic health records with differential privacy, a strong privacy framework for statistical data release. It includes a number of state-of-the-art methods for releasing multidimensional histograms and longitudinal patterns. We performed a variety of experiments on two real datasets, the surveillance, epidemiology and end results (SEER) breast cancer dataset and the Emory electronic medical record (EeMR) dataset, to demonstrate the feasibility and utility of SHARE. Results Experimental results indicate that SHARE can deal with heterogeneous data present in medical data, and that the released statistics are useful. The Kullback–Leibler divergence between the released multidimensional histograms and the original data distribution is below 0.5 and 0.01 for seven-dimensional and three-dimensional data cubes generated from the SEER dataset, respectively. The relative error for longitudinal pattern queries on the EeMR dataset varies between 0 and 0.3. While the results are promising, they also suggest that challenges remain in applying statistical data release using the differential privacy framework for higher dimensional data. Conclusions SHARE is one of the first systems to provide a mechanism for custodians to release differentially private aggregate statistics for a variety of use cases in the medical domain. This proof-of-concept system is intended to be applied to large-scale medical data warehouses. PMID:23059729

Evaluation, Calibration and Comparison of the Precipitation-Runoff Modeling System (PRMS) National Hydrologic Model (NHM) Using Moderate Resolution Imaging Spectroradiometer (MODIS) and Snow Data Assimilation System (SNODAS) Gridded Datasets

NASA Astrophysics Data System (ADS)

Norton, P. A., II; Haj, A. E., Jr.

2014-12-01

The United States Geological Survey is currently developing a National Hydrologic Model (NHM) to support and facilitate coordinated and consistent hydrologic modeling efforts at the scale of the continental United States. As part of this effort, the Geospatial Fabric (GF) for the NHM was created. The GF is a database that contains parameters derived from datasets that characterize the physical features of watersheds. The GF was used to aggregate catchments and flowlines defined in the National Hydrography Dataset Plus dataset for more than 100,000 hydrologic response units (HRUs), and to establish initial parameter values for input to the Precipitation-Runoff Modeling System (PRMS). Many parameter values are adjusted in PRMS using an automated calibration process. Using these adjusted parameter values, the PRMS model estimated variables such as evapotranspiration (ET), potential evapotranspiration (PET), snow-covered area (SCA), and snow water equivalent (SWE). In order to evaluate the effectiveness of parameter calibration, and model performance in general, several satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) and Snow Data Assimilation System (SNODAS) gridded datasets including ET, PET, SCA, and SWE were compared to PRMS-simulated values. The MODIS and SNODAS data were spatially averaged for each HRU, and compared to PRMS-simulated ET, PET, SCA, and SWE values for each HRU in the Upper Missouri River watershed. Default initial GF parameter values and PRMS calibration ranges were evaluated. Evaluation results, and the use of MODIS and SNODAS datasets to update GF parameter values and PRMS calibration ranges, are presented and discussed.

Long-term records of global radiation, carbon and water fluxes derived from multi-satellite data and a process-based model

NASA Astrophysics Data System (ADS)

Ryu, Youngryel; Jiang, Chongya

2016-04-01

To gain insights about the underlying impacts of global climate change on terrestrial ecosystem fluxes, we present a long-term (1982-2015) global radiation, carbon and water fluxes products by integrating multi-satellite data with a process-based model, the Breathing Earth System Simulator (BESS). BESS is a coupled processed model that integrates radiative transfer in the atmosphere and canopy, photosynthesis (GPP), and evapotranspiration (ET). BESS was designed most sensitive to the variables that can be quantified reliably, fully taking advantages of remote sensing atmospheric and land products. Originally, BESS entirely relied on MODIS as input variables to produce global GPP and ET during the MODIS era. This study extends the work to provide a series of long-term products from 1982 to 2015 by incorporating AVHRR data. In addition to GPP and ET, more land surface processes related datasets are mapped to facilitate the discovery of the ecological variations and changes. The CLARA-A1 cloud property datasets, the TOMS aerosol datasets, along with the GLASS land surface albedo datasets, were input to a look-up table derived from an atmospheric radiative transfer model to produce direct and diffuse components of visible and near infrared radiation datasets. Theses radiation components together with the LAI3g datasets and the GLASS land surface albedo datasets, were used to calculate absorbed radiation through a clumping corrected two-stream canopy radiative transfer model. ECMWF ERA interim air temperature data were downscaled by using ALP-II land surface temperature dataset and a region-dependent regression model. The spatial and seasonal variations of CO2 concentration were accounted by OCO-2 datasets, whereas NOAA's global CO2 growth rates data were used to describe interannual variations. All these remote sensing based datasets are used to run the BESS. Daily fluxes in 1/12 degree were computed and then aggregated to half-month interval to match with the spatial-temporal resolution of LAI3g dataset. The BESS GPP and ET products were compared to other independent datasets including MPI-BGC and CLM. Overall, the BESS products show good agreement with the other two datasets, indicating a compelling potential for bridging remote sensing and land surface models.

Solar Irradiance Data Products at the LASP Interactive Solar IRradiance Datacenter (LISIRD)

NASA Astrophysics Data System (ADS)

Lindholm, D. M.; Ware DeWolfe, A.; Wilson, A.; Pankratz, C. K.; Snow, M. A.; Woods, T. N.

2011-12-01

The Laboratory for Atmospheric and Space Physics (LASP) has developed the LASP Interactive Solar IRradiance Datacenter (LISIRD, http://lasp.colorado.edu/lisird/) web site to provide access to a comprehensive set of solar irradiance measurements and related datasets. Current data holdings include products from NASA missions SORCE, UARS, SME, and TIMED-SEE. The data provided covers a wavelength range from soft X-ray (XUV) at 0.1 nm up to the near infrared (NIR) at 2400 nm, as well as Total Solar Irradiance (TSI). Other datasets include solar indices, spectral and flare models, solar images, and more. The LISIRD web site features updated plotting, browsing, and download capabilities enabled by dygraphs, JavaScript, and Ajax calls to the LASP Time Series Server (LaTiS). In addition to the web browser interface, most of the LISIRD datasets can be accessed via the LaTiS web service interface that supports the OPeNDAP standard. OPeNDAP clients and other programming APIs are available for making requests that subset, aggregate, or filter data on the server before it is transported to the user. This poster provides an overview of the LISIRD system, summarizes the datasets currently available, and provides details on how to access solar irradiance data products through LISIRD's interfaces.

Providing Access to a Diverse Set of Global Reanalysis Dataset Collections

NASA Astrophysics Data System (ADS)

Schuster, D.; Worley, S. J.

2015-12-01

The National Center for Atmospheric Research (NCAR) Research Data Archive (RDA, http://rda.ucar.edu) provides open access to a variety of global reanalysis dataset collections to support atmospheric and related sciences research worldwide. These include products from the European Centre for Medium-Range Weather Forecasts (ECMWF), Japan Meteorological Agency (JMA), National Centers for Environmental Prediction (NCEP), National Oceanic and Atmospheric Administration (NOAA), and NCAR.All RDA hosted reanalysis collections are freely accessible to registered users through a variety of methods. Standard access methods include traditional browser and scripted HTTP file download. Enhanced downloads are available through the Globus GridFTP "fire and forget" data transfer service, which provides an efficient, reliable, and preferred alternative to traditional HTTP-based methods. For those that favor interoperable access using compatible tools, the Unidata THREDDS Data server provides remote access to complete reanalysis collections by virtual dataset aggregation "files". Finally, users can request data subsets and format conversions to be prepared for them through web interface form requests or web service API batch requests. This approach uses NCAR HPC and central file systems to effectively prepare products from the high-resolution and very large reanalyses archives. The presentation will include a detailed inventory of all RDA reanalysis dataset collection holdings, and highlight access capabilities to these collections through use case examples.

Model specification and bootstrapping for multiply imputed data: An application to count models for the frequency of alcohol use

PubMed Central

Comulada, W. Scott

2015-01-01

Stata’s mi commands provide powerful tools to conduct multiple imputation in the presence of ignorable missing data. In this article, I present Stata code to extend the capabilities of the mi commands to address two areas of statistical inference where results are not easily aggregated across imputed datasets. First, mi commands are restricted to covariate selection. I show how to address model fit to correctly specify a model. Second, the mi commands readily aggregate model-based standard errors. I show how standard errors can be bootstrapped for situations where model assumptions may not be met. I illustrate model specification and bootstrapping on frequency counts for the number of times that alcohol was consumed in data with missing observations from a behavioral intervention. PMID:26973439

Self Calibrated Wireless Distributed Environmental Sensory Networks

PubMed Central

Fishbain, Barak; Moreno-Centeno, Erick

2016-01-01

Recent advances in sensory and communication technologies have made Wireless Distributed Environmental Sensory Networks (WDESN) technically and economically feasible. WDESNs present an unprecedented tool for studying many environmental processes in a new way. However, the WDESNs’ calibration process is a major obstacle in them becoming the common practice. Here, we present a new, robust and efficient method for aggregating measurements acquired by an uncalibrated WDESN, and producing accurate estimates of the observed environmental variable’s true levels rendering the network as self-calibrated. The suggested method presents novelty both in group-decision-making and in environmental sensing as it offers a most valuable tool for distributed environmental monitoring data aggregation. Applying the method on an extensive real-life air-pollution dataset showed markedly more accurate results than the common practice and the state-of-the-art. PMID:27098279

Examining the impacts of oil price changes on economic indicators: A panel approach

NASA Astrophysics Data System (ADS)

Lim, Kah Boon; Sek, Siok Kun

2017-04-01

The impact of oil price on global economy is evident from many studies and research findings. In this study, we extend the research on examining the impact of oil price changes on economic indicators in terms of economic growth and inflation by comparing different groups of economies (high income versus low income countries and oil importing versus oil exporting countries). Our main objective is to reveal if such impact varies across country income level/ development and oil dependency. In addition, we also seek to compare the impacts of oil price relative to the other factors indicators (money supply, foreign direct investment, exchange rate, government expenditure, inflation and gross domestic product) on economy. For the purpose of this study, the co-integration regression (DOLS and FMOLS) techniques are applied to the panel dataset of four groups of economies which contain 10 countries in each panel dataset. The analysis results show that oil price is not the main determinant although it can have a significant impact on inflation and economic growth across all groups of economies. The three main determinants of economic growth are exchange rate, aggregate demand and government expenditure while the determinants of inflation are aggregate supply and exchange rate. Furthermore, our result also concludes that oil price has a positive impact in oil exporting economies but it shows a negative impact in oil importing economies due to the oil dependency factor.

Prediction of nocturnal hypoglycemia by an aggregation of previously known prediction approaches: proof of concept for clinical application.

PubMed

Tkachenko, Pavlo; Kriukova, Galyna; Aleksandrova, Marharyta; Chertov, Oleg; Renard, Eric; Pereverzyev, Sergei V

2016-10-01

Nocturnal hypoglycemia (NH) is common in patients with insulin-treated diabetes. Despite the risk associated with NH, there are only a few methods aiming at the prediction of such events based on intermittent blood glucose monitoring data and none has been validated for clinical use. Here we propose a method of combining several predictors into a new one that will perform at the level of the best involved one, or even outperform all individual candidates. The idea of the method is to use a recently developed strategy for aggregating ranking algorithms. The method has been calibrated and tested on data extracted from clinical trials, performed in the European FP7-funded project DIAdvisor. Then we have tested the proposed approach on other datasets to show the portability of the method. This feature of the method allows its simple implementation in the form of a diabetic smartphone app. On the considered datasets the proposed approach exhibits good performance in terms of sensitivity, specificity and predictive values. Moreover, the resulting predictor automatically performs at the level of the best involved method or even outperforms it. We propose a strategy for a combination of NH predictors that leads to a method exhibiting a reliable performance and the potential for everyday use by any patient who performs self-monitoring of blood glucose. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

SchizConnect: Mediating neuroimaging databases on schizophrenia and related disorders for large-scale integration.

PubMed

Wang, Lei; Alpert, Kathryn I; Calhoun, Vince D; Cobia, Derin J; Keator, David B; King, Margaret D; Kogan, Alexandr; Landis, Drew; Tallis, Marcelo; Turner, Matthew D; Potkin, Steven G; Turner, Jessica A; Ambite, Jose Luis

2016-01-01

SchizConnect (www.schizconnect.org) is built to address the issues of multiple data repositories in schizophrenia neuroimaging studies. It includes a level of mediation--translating across data sources--so that the user can place one query, e.g. for diffusion images from male individuals with schizophrenia, and find out from across participating data sources how many datasets there are, as well as downloading the imaging and related data. The current version handles the Data Usage Agreements across different studies, as well as interpreting database-specific terminologies into a common framework. New data repositories can also be mediated to bring immediate access to existing datasets. Compared with centralized, upload data sharing models, SchizConnect is a unique, virtual database with a focus on schizophrenia and related disorders that can mediate live data as information is being updated at each data source. It is our hope that SchizConnect can facilitate testing new hypotheses through aggregated datasets, promoting discovery related to the mechanisms underlying schizophrenic dysfunction. Copyright © 2015 Elsevier Inc. All rights reserved.

Global distribution of clay-size minerals on land surface for biogeochemical and climatological studies

PubMed Central

Ito, Akihiko; Wagai, Rota

2017-01-01

Clay-size minerals play important roles in terrestrial biogeochemistry and atmospheric physics, but their data have been only partially compiled at global scale. We present a global dataset of clay-size minerals in the topsoil and subsoil at different spatial resolutions. The data of soil clay and its mineralogical composition were gathered through a literature survey and aggregated by soil orders of the Soil Taxonomy for each of the ten groups: gibbsite, kaolinite, illite/mica, smectite, vermiculite, chlorite, iron oxide, quartz, non-crystalline, and others. Using a global soil map, a global dataset of soil clay-size mineral distribution was developed at resolutions of 2' to 2° grid cells. The data uncertainty associated with data variability and assumption was evaluated using a Monte Carlo method, and validity of the clay-size mineral distribution obtained in this study was examined by comparing with other datasets. The global soil clay data offer spatially explicit studies on terrestrial biogeochemical cycles, dust emission to the atmosphere, and other interdisciplinary earth sciences. PMID:28829435

Using high-resolution variant frequencies to empower clinical genome interpretation.

PubMed

Whiffin, Nicola; Minikel, Eric; Walsh, Roddy; O'Donnell-Luria, Anne H; Karczewski, Konrad; Ing, Alexander Y; Barton, Paul J R; Funke, Birgit; Cook, Stuart A; MacArthur, Daniel; Ware, James S

2017-10-01

PurposeWhole-exome and whole-genome sequencing have transformed the discovery of genetic variants that cause human Mendelian disease, but discriminating pathogenic from benign variants remains a daunting challenge. Rarity is recognized as a necessary, although not sufficient, criterion for pathogenicity, but frequency cutoffs used in Mendelian analysis are often arbitrary and overly lenient. Recent very large reference datasets, such as the Exome Aggregation Consortium (ExAC), provide an unprecedented opportunity to obtain robust frequency estimates even for very rare variants.MethodsWe present a statistical framework for the frequency-based filtering of candidate disease-causing variants, accounting for disease prevalence, genetic and allelic heterogeneity, inheritance mode, penetrance, and sampling variance in reference datasets.ResultsUsing the example of cardiomyopathy, we show that our approach reduces by two-thirds the number of candidate variants under consideration in the average exome, without removing true pathogenic variants (false-positive rate<0.001).ConclusionWe outline a statistically robust framework for assessing whether a variant is "too common" to be causative for a Mendelian disorder of interest. We present precomputed allele frequency cutoffs for all variants in the ExAC dataset.

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

PubMed

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

Re-Organizing Earth Observation Data Storage to Support Temporal Analysis of Big Data

NASA Technical Reports Server (NTRS)

Lynnes, Christopher

2017-01-01

The Earth Observing System Data and Information System archives many datasets that are critical to understanding long-term variations in Earth science properties. Thus, some of these are large, multi-decadal datasets. Yet the challenge in long time series analysis comes less from the sheer volume than the data organization, which is typically one (or a small number of) time steps per file. The overhead of opening and inventorying complex, API-driven data formats such as Hierarchical Data Format introduces a small latency at each time step, which nonetheless adds up for datasets with O(10^6) single-timestep files. Several approaches to reorganizing the data can mitigate this overhead by an order of magnitude: pre-aggregating data along the time axis (time-chunking); storing the data in a highly distributed file system; or storing data in distributed columnar databases. Storing a second copy of the data incurs extra costs, so some selection criteria must be employed, which would be driven by expected or actual usage by the end user community, balanced against the extra cost.

Re-organizing Earth Observation Data Storage to Support Temporal Analysis of Big Data

NASA Astrophysics Data System (ADS)

Lynnes, C.

2017-12-01

The Earth Observing System Data and Information System archives many datasets that are critical to understanding long-term variations in Earth science properties. Thus, some of these are large, multi-decadal datasets. Yet the challenge in long time series analysis comes less from the sheer volume than the data organization, which is typically one (or a small number of) time steps per file. The overhead of opening and inventorying complex, API-driven data formats such as Hierarchical Data Format introduces a small latency at each time step, which nonetheless adds up for datasets with O(10^6) single-timestep files. Several approaches to reorganizing the data can mitigate this overhead by an order of magnitude: pre-aggregating data along the time axis (time-chunking); storing the data in a highly distributed file system; or storing data in distributed columnar databases. Storing a second copy of the data incurs extra costs, so some selection criteria must be employed, which would be driven by expected or actual usage by the end user community, balanced against the extra cost.

Insights into the abundance and diversity of abyssal megafauna in a polymetallic-nodule region in the eastern Clarion-Clipperton Zone

PubMed Central

Amon, Diva J.; Ziegler, Amanda F.; Dahlgren, Thomas G.; Glover, Adrian G.; Goineau, Aurélie; Gooday, Andrew J.; Wiklund, Helena; Smith, Craig R.

2016-01-01

There is growing interest in mining polymetallic nodules in the abyssal Clarion-Clipperton Zone (CCZ) in the Pacific. Nonetheless, benthic communities in this region remain poorly known. The ABYSSLINE Project is conducting benthic biological baseline surveys for the UK Seabed Resources Ltd. exploration contract area (UK-1) in the CCZ. Using a Remotely Operated Vehicle, we surveyed megafauna at four sites within a 900 km2 stratum in the UK-1 contract area, and at a site ~250 km east of the UK-1 area, allowing us to make the first estimates of abundance and diversity. We distinguished 170 morphotypes within the UK-1 contract area but species-richness estimators suggest this could be as high as 229. Megafaunal abundance averaged 1.48 ind. m−2. Seven of 12 collected metazoan species were new to science, and four belonged to new genera. Approximately half of the morphotypes occurred only on polymetallic nodules. There were weak, but statistically significant, positive correlations between megafaunal and nodule abundance. Eastern-CCZ megafaunal diversity is high relative to two abyssal datasets from other regions, however comparisons with CCZ and DISCOL datasets are problematic given the lack of standardised methods and taxonomy. We postulate that CCZ megafaunal diversity is driven in part by habitat heterogeneity. PMID:27470484

The version 3 OMI NO2 standard product

NASA Astrophysics Data System (ADS)

Krotkov, Nickolay A.; Lamsal, Lok N.; Celarier, Edward A.; Swartz, William H.; Marchenko, Sergey V.; Bucsela, Eric J.; Chan, Ka Lok; Wenig, Mark; Zara, Marina

2017-09-01

We describe the new version 3.0 NASA Ozone Monitoring Instrument (OMI) standard nitrogen dioxide (NO2) products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major improvements include (1) a new spectral fitting algorithm for NO2 slant column density (SCD) retrieval and (2) higher-resolution (1° latitude and 1.25° longitude) a priori NO2 and temperature profiles from the Global Modeling Initiative (GMI) chemistry-transport model with yearly varying emissions to calculate air mass factors (AMFs) required to convert SCDs into vertical column densities (VCDs). The new SCDs are systematically lower (by ˜ 10-40 %) than previous, version 2, estimates. Most of this reduction in SCDs is propagated into stratospheric VCDs. Tropospheric NO2 VCDs are also reduced over polluted areas, especially over western Europe, the eastern US, and eastern China. Initial evaluation over unpolluted areas shows that the new SPv3 products agree better with independent satellite- and ground-based Fourier transform infrared (FTIR) measurements. However, further evaluation of tropospheric VCDs is needed over polluted areas, where the increased spatial resolution and more refined AMF estimates may lead to better characterization of pollution hot spots.

Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics

USGS Publications Warehouse

Pervez, Md Shahriar; Brown, Jesslyn F.

2010-01-01

Accurate geospatial information on the extent of irrigated land improves our understanding of agricultural water use, local land surface processes, conservation or depletion of water resources, and components of the hydrologic budget. We have developed a method in a geospatial modeling framework that assimilates irrigation statistics with remotely sensed parameters describing vegetation growth conditions in areas with agricultural land cover to spatially identify irrigated lands at 250-m cell size across the conterminous United States for 2002. The geospatial model result, known as the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset (MIrAD-US), identified irrigated lands with reasonable accuracy in California and semiarid Great Plains states with overall accuracies of 92% and 75% and kappa statistics of 0.75 and 0.51, respectively. A quantitative accuracy assessment of MIrAD-US for the eastern region has not yet been conducted, and qualitative assessment shows that model improvements are needed for the humid eastern regions where the distinction in annual peak NDVI between irrigated and non-irrigated crops is minimal and county sizes are relatively small. This modeling approach enables consistent mapping of irrigated lands based upon USDA irrigation statistics and should lead to better understanding of spatial trends in irrigated lands across the conterminous United States. An improved version of the model with revised datasets is planned and will employ 2007 USDA irrigation statistics.

Towards Calibration of Sentinel 3 Data: Validation of Satellite-Derived SST Against In Situ Coastal Observations of the Portuguese Marine Waters

NASA Astrophysics Data System (ADS)

Vicente, Ricardo; Esteves, Rita; Lamas, Luisa; Pinto, Jose Paulo; Almeida, Sara; de Azevedo, Eduardo; Correia, Cecilia; Reis, Francisco

2016-08-01

Validation of future Sentinel-3 SLSTR data in the Eastern Atlantic Ocean was analysed here through a comparison of satellite-derived STT against in situ mooring buoys observations.SSTskin retrieved from IR satellite radiometers on- board ERS 1-2, Envisat, and Aqua, and concurrent SSTbulk measured with 14 buoy thermistors located at 1m depth were used to assess the statistical relationships between these datasets, with 20038 match- ups spanning from 1996 to 2015.As expected, results showed consistency between SSTskin and SSTbulk, exhibiting a correlation coefficient on the order of 98 %. Biases of both (A)ATSR and MODIS for day-time suggest a warmer satellite skin retrieval of + 0.15o and + 0.06o, respectively. For the night-time dataset, biases of - 0.25o and - 0.17o for (A)A TSR and MODIS, respectively, indicate cooler skin retrievals and reveal an inversion of the upper ocean thermic gradient. The RMSE ´s found were 0.53o for (A)ATSR and 0.41o for MODIS datasets.

On the Role of Aggregation Prone Regions in Protein Evolution, Stability, and Enzymatic Catalysis: Insights from Diverse Analyses

PubMed Central

Buck, Patrick M.; Kumar, Sandeep; Singh, Satish K.

2013-01-01

The various roles that aggregation prone regions (APRs) are capable of playing in proteins are investigated here via comprehensive analyses of multiple non-redundant datasets containing randomly generated amino acid sequences, monomeric proteins, intrinsically disordered proteins (IDPs) and catalytic residues. Results from this study indicate that the aggregation propensities of monomeric protein sequences have been minimized compared to random sequences with uniform and natural amino acid compositions, as observed by a lower average aggregation propensity and fewer APRs that are shorter in length and more often punctuated by gate-keeper residues. However, evidence for evolutionary selective pressure to disrupt these sequence regions among homologous proteins is inconsistent. APRs are less conserved than average sequence identity among closely related homologues (≥80% sequence identity with a parent) but APRs are more conserved than average sequence identity among homologues that have at least 50% sequence identity with a parent. Structural analyses of APRs indicate that APRs are three times more likely to contain ordered versus disordered residues and that APRs frequently contribute more towards stabilizing proteins than equal length segments from the same protein. Catalytic residues and APRs were also found to be in structural contact significantly more often than expected by random chance. Our findings suggest that proteins have evolved by optimizing their risk of aggregation for cellular environments by both minimizing aggregation prone regions and by conserving those that are important for folding and function. In many cases, these sequence optimizations are insufficient to develop recombinant proteins into commercial products. Rational design strategies aimed at improving protein solubility for biotechnological purposes should carefully evaluate the contributions made by candidate APRs, targeted for disruption, towards protein structure and activity. PMID:24146608

BEANS - a software package for distributed Big Data analysis

NASA Astrophysics Data System (ADS)

Hypki, Arkadiusz

2018-03-01

BEANS software is a web based, easy to install and maintain, new tool to store and analyse in a distributed way a massive amount of data. It provides a clear interface for querying, filtering, aggregating, and plotting data from an arbitrary number of datasets. Its main purpose is to simplify the process of storing, examining and finding new relations in huge datasets. The software is an answer to a growing need of the astronomical community to have a versatile tool to store, analyse and compare the complex astrophysical numerical simulations with observations (e.g. simulations of the Galaxy or star clusters with the Gaia archive). However, this software was built in a general form and it is ready to use in any other research field. It can be used as a building block for other open source software too.

Variability of hydrological droughts in the conterminous United States, 1951 through 2014

USGS Publications Warehouse

Austin, Samuel H.; Wolock, David M.; Nelms, David L.

2018-02-22

Spatial and temporal variability in the frequency, duration, and severity of hydrological droughts across the conterminous United States (CONUS) was examined using monthly mean streamflow measured at 872 sites from 1951 through 2014. Hydrological drought is identified as starting when streamflow falls below the 20th percentile streamflow value for 3 consecutive months and ending when streamflow remains above the 20th percentile streamflow value for 3 consecutive months. Mean drought frequency for all aggregated ecoregions in CONUS is 16 droughts per 100 years. Mean drought duration is 5 months, and mean drought severity is 39 percent on a scale ranging from 0 percent to 100 percent (with 100% being the most severe). Hydrological drought frequency is highest in the Western Mountains aggregated ecoregion and lowest in the Eastern Highlands, Northeast, and Southeast Plains aggregated ecoregions. Hydrological drought frequencies of 17 or more droughts per 100 years were found for the Central Plains, Southeast Coastal Plains, Western Mountains, and Western Xeric aggregated ecoregions. Drought duration and severity indicate spatial variability among the sites, but unlike drought frequency, do not show coherent spatial patterns. A comparison of an older period (1951–82) with a recent period (1983–2014) indicates few sites have statistically significant changes in drought frequency, drought duration, or drought severity at a 95-percent confidence level.

Statistically-Estimated Tree Composition for the Northeastern United States at Euro-American Settlement.

PubMed

Paciorek, Christopher J; Goring, Simon J; Thurman, Andrew L; Cogbill, Charles V; Williams, John W; Mladenoff, David J; Peters, Jody A; Zhu, Jun; McLachlan, Jason S

2016-01-01

We present a gridded 8 km-resolution data product of the estimated composition of tree taxa at the time of Euro-American settlement of the northeastern United States and the statistical methodology used to produce the product from trees recorded by land surveyors. Composition is defined as the proportion of stems larger than approximately 20 cm diameter at breast height for 22 tree taxa, generally at the genus level. The data come from settlement-era public survey records that are transcribed and then aggregated spatially, giving count data. The domain is divided into two regions, eastern (Maine to Ohio) and midwestern (Indiana to Minnesota). Public Land Survey point data in the midwestern region (ca. 0.8-km resolution) are aggregated to a regular 8 km grid, while data in the eastern region, from Town Proprietor Surveys, are aggregated at the township level in irregularly-shaped local administrative units. The product is based on a Bayesian statistical model fit to the count data that estimates composition on the 8 km grid across the entire domain. The statistical model is designed to handle data from both the regular grid and the irregularly-shaped townships and allows us to estimate composition at locations with no data and to smooth over noise caused by limited counts in locations with data. Critically, the model also allows us to quantify uncertainty in our composition estimates, making the product suitable for applications employing data assimilation. We expect this data product to be useful for understanding the state of vegetation in the northeastern United States prior to large-scale Euro-American settlement. In addition to specific regional questions, the data product can also serve as a baseline against which to investigate how forests and ecosystems change after intensive settlement. The data product is being made available at the NIS data portal as version 1.0.

Temporal and spatial variability of pelagic wild fish assemblages around Atlantic bluefin tuna Thunnus thynnus farms in the eastern Adriatic Sea.

PubMed

Segvić Bubić, T; Grubišić, L; Tičina, V; Katavić, I

2011-01-01

The abundance and size structure of wild fishes aggregated around the sea-cages of two commercial Thunnus thynnus farms, including control locations, were assessed and compared over a 1 year period. The T. thynnus farms were located in the eastern Adriatic Sea, offshore of the islands of Ugljan and Brač. Fish assemblages were evaluated through visual census using scuba at 2 month intervals at two sites within each farm. The data suggest that wild fish assemblages at the study sites differed greatly; 20 species occurred at the Ugljan farm and 17 at the Brač farm, while only seven species were observed at the control locations. The abundance and diversity of wild fish assemblages were greater at the farms in comparison to control locations. The most abundant families were Sparidae and Belonidae (>80% of aggregated fishes). At both farms, the abundance and diversity of wild fishes were highest during summer, while diversity was lowest in winter and was mainly characterized by schools of bogue Boops boops and garfish Belone belone. Variability was also detected in spatial assemblages between farms; B. boops and B. belone were the most abundant species for the overall study at the Brač farm, while B. belone and saddled bream Oblada melanura were the most abundant at the Ugljan farm. The settlement also played a significant role in farm-associated fish assemblages, as both juveniles and advanced juveniles were common residents at farms. The majority of species which settled at the farms belonged to the sparids. Results indicate that aggregations of wild fishes at T. thynnus farms are persistent year-round, though the assemblage compositions and size structures of dominant species vary in respect to location and season. © 2011 The Authors. Journal of Fish Biology © 2011 The Fisheries Society of the British Isles.

An autumn aggregation of fin (Balaenoptera physalus) and blue whales (B. musculus) in the Porcupine Seabight, southwest of Ireland

NASA Astrophysics Data System (ADS)

Baines, Mick; Reichelt, Maren; Griffin, Donal

2017-07-01

During a 16 week geophysical survey over the Porcupine Seabight (PSB) southwest of Ireland in July to October 2013, marine mammal observers logged 9382 km of effort. Balaenopterid whales comprised some 60% of a total of 373 cetacean sighting events (s), with a cumulative count (n) of 392 whales. Fin whales (Balaenoptera physalus) were especially abundant (s=111, n=209) and the number of blue whales (B. musculus) seen (s=12, n=16) exceeded the total previously reported from Irish waters, but 43% of balaenopterid sightings (s=98, n=172) were not identified to species level. Data for all balaenopterid whales were pooled and generalised additive models applied to identify environmental variables that predicted whale density and to estimate abundance and the spatial distribution of density. Depth range and chlorophyll-a concentration were significant predictors of whale presence, and depth and sea floor rugosity were significant predictors of group size. There appeared to be an influx of whales in September and October and the predicted abundance peaked in October with an estimate of 138 (95% CI 121-151) whales. Analysis of the direction of movement of whales showed no significant bias in any one direction. Feeding behaviour was observed in both whale species and circumstantial evidence suggested that they were aggregating to exploit seasonally abundant northern krill (Meganyctiphanes norvegica). Chasing behaviour observed among fin whales was interpreted as evidence that this aggregation also provided opportunities for social interaction related to their reproductive cycle. The PSB may provide a link between the high latitude summer feeding habitats of krill-feeding whales and a chain of highly productive habitats in the Eastern Boundary Upwelling Ecosystems and we suggest that whales may migrate southwards in autumn along this eastern route to the northwest African upwelling zones, where productivity peaks in winter.

Identifying the location and population served by domestic wells in California

USGS Publications Warehouse

Johnson, Tyler D.; Belitz, Kenneth

2015-01-01

Aggregating the results indicates that three hydrogeologic provinces contain nearly 80% of all domestic wells and also have the highest density of domestic well users: Central Valley (31.6%), Sierra Nevada (31.5%), and Northern Coast Ranges (16.6%). Results were also aggregated into groundwater basins and highland areas, collectively called Groundwater Units (GUs). Twenty-eight of the 938 GUs contain more than 50% of the total population served by domestic wells, 70 GUs contain more than 75%, and 150 GUs contain 90%. The 28 GUs are mostly located in the eastern and southern San Joaquin Valley (11), the Sacramento Valley (7), and the western foothills of the Sierra Nevada province (5). Using the information presented in this research along with other information about domestic-well use, the US Geological Survey has begun sampling high-use GUs for the Shallow Aquifer Assessment component of the Groundwater Ambient Assessment (GAMA) program.

Improving average ranking precision in user searches for biomedical research datasets

PubMed Central

Gobeill, Julien; Gaudinat, Arnaud; Vachon, Thérèse; Ruch, Patrick

2017-01-01

Abstract Availability of research datasets is keystone for health and life science study reproducibility and scientific progress. Due to the heterogeneity and complexity of these data, a main challenge to be overcome by research data management systems is to provide users with the best answers for their search queries. In the context of the 2016 bioCADDIE Dataset Retrieval Challenge, we investigate a novel ranking pipeline to improve the search of datasets used in biomedical experiments. Our system comprises a query expansion model based on word embeddings, a similarity measure algorithm that takes into consideration the relevance of the query terms, and a dataset categorization method that boosts the rank of datasets matching query constraints. The system was evaluated using a corpus with 800k datasets and 21 annotated user queries, and provided competitive results when compared to the other challenge participants. In the official run, it achieved the highest infAP, being +22.3% higher than the median infAP of the participant’s best submissions. Overall, it is ranked at top 2 if an aggregated metric using the best official measures per participant is considered. The query expansion method showed positive impact on the system’s performance increasing our baseline up to +5.0% and +3.4% for the infAP and infNDCG metrics, respectively. The similarity measure algorithm showed robust performance in different training conditions, with small performance variations compared to the Divergence from Randomness framework. Finally, the result categorization did not have significant impact on the system’s performance. We believe that our solution could be used to enhance biomedical dataset management systems. The use of data driven expansion methods, such as those based on word embeddings, could be an alternative to the complexity of biomedical terminologies. Nevertheless, due to the limited size of the assessment set, further experiments need to be performed to draw conclusive results. Database URL: https://biocaddie.org/benchmark-data PMID:29220475

DeepPap: Deep Convolutional Networks for Cervical Cell Classification.

PubMed

Zhang, Ling; Le Lu; Nogues, Isabella; Summers, Ronald M; Liu, Shaoxiong; Yao, Jianhua

2017-11-01

Automation-assisted cervical screening via Pap smear or liquid-based cytology (LBC) is a highly effective cell imaging based cancer detection tool, where cells are partitioned into "abnormal" and "normal" categories. However, the success of most traditional classification methods relies on the presence of accurate cell segmentations. Despite sixty years of research in this field, accurate segmentation remains a challenge in the presence of cell clusters and pathologies. Moreover, previous classification methods are only built upon the extraction of hand-crafted features, such as morphology and texture. This paper addresses these limitations by proposing a method to directly classify cervical cells-without prior segmentation-based on deep features, using convolutional neural networks (ConvNets). First, the ConvNet is pretrained on a natural image dataset. It is subsequently fine-tuned on a cervical cell dataset consisting of adaptively resampled image patches coarsely centered on the nuclei. In the testing phase, aggregation is used to average the prediction scores of a similar set of image patches. The proposed method is evaluated on both Pap smear and LBC datasets. Results show that our method outperforms previous algorithms in classification accuracy (98.3%), area under the curve (0.99) values, and especially specificity (98.3%), when applied to the Herlev benchmark Pap smear dataset and evaluated using five-fold cross validation. Similar superior performances are also achieved on the HEMLBC (H&E stained manual LBC) dataset. Our method is promising for the development of automation-assisted reading systems in primary cervical screening.

Effects of life-history traits on parasitism in a monogamous mammal, the eastern rock sengi ( Elephantulus myurus)

NASA Astrophysics Data System (ADS)

Lutermann, Heike; Medger, Katarina; Horak, Ivan G.

2012-02-01

The distribution of parasites is often characterised by substantial aggregation with a small proportion of hosts harbouring the majority of parasites. This pattern can be generated by abiotic and biotic factors that affect hosts and determine host exposure and susceptibility to parasites. Climate factors can change a host's investment in life-history traits (e.g. growth, reproduction) generating temporal patterns of parasite aggregation. Similarly, host age may affect such investment. Furthermore, sex-biased parasitism is common among vertebrates and has been linked to sexual dimorphism in morphology, behaviour and physiology. Studies exploring sex-biased parasitism have been almost exclusively conducted on polygynous species where dimorphic traits are often correlated. We investigated the effects of season and life-history traits on tick loads of the monogamous eastern rock sengi ( Elephantulus myurus). We found larger tick burdens during the non-breeding season possibly as a result of energetic constraints and/or climate effects on the tick. Reproductive investment resulted in increased larval abundance for females but not males and may be linked to sex-specific life-history strategies. The costs of reproduction could also explain the observed age effect with yearling individuals harbouring lower larval burdens than adults. Although adult males had the greatest larval tick loads, host sex appears to play a minor role in generating the observed parasite heterogeneities. Our study suggests that reproductive investment plays a major role for parasite patterns in the study species.

Effect of land management on soil properties in flood irrigated citrus orchards in Eastern Spain

NASA Astrophysics Data System (ADS)

Morugán-Coronado, A.; García-Orenes, F.; Cerdà, A.

2015-01-01

Agricultural land management greatly affects soil properties. Microbial soil communities are the most sensitive and rapid indicators of perturbations in land use and soil enzyme activities are sensitive biological indicators of the effects of soil management practices. Citrus orchards frequently have degraded soils and this paper evaluates how land management in citrus orchards can improve soil quality. A field experiment was performed in an orchard of orange trees (Citrus Sinensis) in the Alcoleja Experimental Station (Eastern Spain) with clay-loam agricultural soils to assess the long-term effects of herbicides with inorganic fertilizers (H), intensive ploughing and inorganic fertilizers (P) and organic farming (O) on the soil microbial properties, and to study the relationship between them. Nine soil samples were taken from each agricultural management plot. In all the samples the basal soil respiration, soil microbial biomass carbon, water holding capacity, electrical conductivity, soil organic matter, total nitrogen, available phosphorus, available potassium, aggregate stability, cation exchange capacity, pH, texture, macronutrients (Na, Ca and Mg), micronutrients (Fe, Mn, Zn and Cu), calcium carbonate equivalent, calcium carbonate content of limestone and enzimatic activities (urease, dehydrogenase, β-glucosidase and acid phosphatase) were determined. The results showed a substantial level of differentiation in the microbial properties, which were highly associated with soil organic matter content. The management practices including herbicides and intensive ploughing had similar results on microbial soil properties. O management contributed to an increase in the soil biology quality, aggregate stability and organic matter content.

Addressing data privacy in matched studies via virtual pooling.

PubMed

Saha-Chaudhuri, P; Weinberg, C R

2017-09-07

Data confidentiality and shared use of research data are two desirable but sometimes conflicting goals in research with multi-center studies and distributed data. While ideal for straightforward analysis, confidentiality restrictions forbid creation of a single dataset that includes covariate information of all participants. Current approaches such as aggregate data sharing, distributed regression, meta-analysis and score-based methods can have important limitations. We propose a novel application of an existing epidemiologic tool, specimen pooling, to enable confidentiality-preserving analysis of data arising from a matched case-control, multi-center design. Instead of pooling specimens prior to assay, we apply the methodology to virtually pool (aggregate) covariates within nodes. Such virtual pooling retains most of the information used in an analysis with individual data and since individual participant data is not shared externally, within-node virtual pooling preserves data confidentiality. We show that aggregated covariate levels can be used in a conditional logistic regression model to estimate individual-level odds ratios of interest. The parameter estimates from the standard conditional logistic regression are compared to the estimates based on a conditional logistic regression model with aggregated data. The parameter estimates are shown to be similar to those without pooling and to have comparable standard errors and confidence interval coverage. Virtual data pooling can be used to maintain confidentiality of data from multi-center study and can be particularly useful in research with large-scale distributed data.

MJO Signals in Latent Heating: Results from TRMM Retrievals

NASA Technical Reports Server (NTRS)

Zhang, Chidong; Ling, Jian; Hagos, Samson; Tao, Wei-Kuo; Lang, Steve; Takayabu, Yukari N.; Shige, Shoichi; Katsumata, Masaki; Olson, William S.; L'Ecuyer, Tristan

2010-01-01

The Madden-Julian Oscillation (MJO) is the dominant intraseasonal signal in the global tropical atmosphere. Almost all numerical climate models have difficulty to simulate realistic MJO. Four TRMM datasets of latent heating were diagnosed for signals in the MJO. In all four datasets, vertical structures of latent heating are dominated by two components, one deep with its peak above the melting level and one shallow with its peak below. Profiles of the two components are nearly ubiquitous in longitude, allowing a separation of the vertical and zonal/temporal variations when the latitudinal dependence is not considered. All four datasets exhibit robust MJO spectral signals in the deep component as eastward propagating spectral peaks centered at period of 50 days and zonal wavenumber 1, well distinguished from lower- and higher-frequency power and much stronger than the corresponding westward power. The shallow component shows similar but slightly less robust MJO spectral peaks. MJO signals were further extracted from a combination of band-pass (30 - 90 day) filtered deep and shallow components. Largest amplitudes of both deep and shallow components of the MJO are confined to the Indian and western Pacific Oceans. There is a local minimum in the deep components over the Maritime Continent. The shallow components of the MJO differ substantially among the four TRMM datasets in their detailed zonal distributions in the eastern hemisphere. In composites of the heating evolution through the life cycle of the MJO, the shallow components lead the deep ones in some datasets and at certain longitudes. In many respects, the four TRMM datasets agree well in their deep components, but not in their shallow components and the phase relations between the deep and shallow components. These results indicate that caution must be exercised in applications of these latent heating data.

The relationships between income inequality, welfare regimes and aggregate health: a systematic review.

PubMed

Kim, Ki-Tae

2017-06-01

: When analysing the relationships between income inequality, welfare regimes and aggregate health at the cross-national level, previous primary articles and systematic reviews reach inconsistent conclusions. Contrary to theoretical expectations, equal societies or the Social Democratic welfare regime do not always have the best aggregate health when compared with those of other relatively unequal societies or other welfare regimes. This article will shed light on the controversial subjects with a new decomposition systematic review method. The decomposition systematic review method breaks down an individual empirical article, if necessary, into multiple findings based on an article's use of the following four components: independent variable, dependent variable, method and dataset. This decomposition method extracts 107 findings from the selected 48 articles, demonstrating the dynamics between the four components. 'The age threshold effect' is recognized over which the hypothesized relations between income inequality, welfare regimes and aggregate health reverse. The hypothesis is supported mainly for younger infant and child health indicators, but not for adult health or general health indicators such as life expectancy. Further three threshold effects (income, gender and period) have also been put forward. The negative relationship between income inequality and aggregate health, often termed as the Wilkinson Hypothesis, was not generally observed in all health indicators except for infant and child mortality. The Scandinavian welfare regime reveals worse-than-expected outcomes in all health indicators except infant and child mortality. © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Normalized distance aggregation of discriminative features for person reidentification

NASA Astrophysics Data System (ADS)

Hou, Li; Han, Kang; Wan, Wanggen; Hwang, Jenq-Neng; Yao, Haiyan

2018-03-01

We propose an effective person reidentification method based on normalized distance aggregation of discriminative features. Our framework is built on the integration of three high-performance discriminative feature extraction models, including local maximal occurrence (LOMO), feature fusion net (FFN), and a concatenation of LOMO and FFN called LOMO-FFN, through two fast and discriminant metric learning models, i.e., cross-view quadratic discriminant analysis (XQDA) and large-scale similarity learning (LSSL). More specifically, we first represent all the cross-view person images using LOMO, FFN, and LOMO-FFN, respectively, and then apply each extracted feature representation to train XQDA and LSSL, respectively, to obtain the optimized individual cross-view distance metric. Finally, the cross-view person matching is computed as the sum of the optimized individual cross-view distance metric through the min-max normalization. Experimental results have shown the effectiveness of the proposed algorithm on three challenging datasets (VIPeR, PRID450s, and CUHK01).

Cultural Consensus Theory: Aggregating Continuous Responses in a Finite Interval

NASA Astrophysics Data System (ADS)

Batchelder, William H.; Strashny, Alex; Romney, A. Kimball

Cultural consensus theory (CCT) consists of cognitive models for aggregating responses of "informants" to test items about some domain of their shared cultural knowledge. This paper develops a CCT model for items requiring bounded numerical responses, e.g. probability estimates, confidence judgments, or similarity judgments. The model assumes that each item generates a latent random representation in each informant, with mean equal to the consensus answer and variance depending jointly on the informant and the location of the consensus answer. The manifest responses may reflect biases of the informants. Markov Chain Monte Carlo (MCMC) methods were used to estimate the model, and simulation studies validated the approach. The model was applied to an existing cross-cultural dataset involving native Japanese and English speakers judging the similarity of emotion terms. The results sharpened earlier studies that showed that both cultures appear to have very similar cognitive representations of emotion terms.

Non-Cooperative Facial Recognition Video Dataset Collection Plan

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

Kimura, Marcia L.; Erikson, Rebecca L.; Lombardo, Nicholas J.

The Pacific Northwest National Laboratory (PNNL) will produce a non-cooperative (i.e. not posing for the camera) facial recognition video data set for research purposes to evaluate and enhance facial recognition systems technology. The aggregate data set consists of 1) videos capturing PNNL role players and public volunteers in three key operational settings, 2) photographs of the role players for enrolling in an evaluation database, and 3) ground truth data that documents when the role player is within various camera fields of view. PNNL will deliver the aggregate data set to DHS who may then choose to make it available tomore » other government agencies interested in evaluating and enhancing facial recognition systems. The three operational settings that will be the focus of the video collection effort include: 1) unidirectional crowd flow 2) bi-directional crowd flow, and 3) linear and/or serpentine queues.« less

Local Hotspots In The Gulf Of Maine: Spatial Overlap Between Dynamic Aggregations Of Primary Productivity And Fish Abundance

NASA Astrophysics Data System (ADS)

Ribera, M.

2016-02-01

Identification of biological hotspots may be a necessary step toward ecosystem-based management goals, as these often signal underlying processes that aggregate or stimulate resources in a particular location. However, previously used metrics to locate these hotspots are not easily adapted to local marine datasets, in part due to the high spatial and temporal variability of phytoplankton populations. While most fish species in temperate regions are well adapted to the seasonal variability of phytoplankton abundance, it is the variability beyond this predictable pattern (i.e. anomalies) that may heavily impact the abundance and spatial distribution of organisms higher up the food chain. The objective of this study was to identify local-scale biological hotspots in a region in the western side of the Gulf of Maine using remote sensing chlorophyll-a data (from MERIS sensor), and to study the spatial overlap between these hotspots and high concentrations of fish abundance (derived from VTR dataset). For this reason, we defined a new hotspot metric that identified as a hotspot any area that consistently exhibited high-magnitude anomalies through time, a sign of highly dynamic communities. We improved on previous indices by minimizing the effect that different means and variances across space may have on the results, a situation that often occurs when comparing coastal and offshore systems. Results show a significant spatial correlation between pelagic fish abundance and aggregations of primary productivity. Spatial correlations were also significant between benthic fish abundance and primary productivity hotspots, but only during spring months. We argue that this new hotspot index compliments existing global measures as it helps managers understand the dynamic characteristics of a complex marine system. It also provides a unique metric that is easily compared across space and between different trophic levels, which may facilitate future ecosystem-wide studies.

Local Hotspots In The Gulf Of Maine: Spatial Overlap Between Dynamic Aggregations Of Primary Productivity And Fish Abundance

NASA Astrophysics Data System (ADS)

Ribera, M.

2016-12-01

Identification of biological hotspots may be a necessary step toward ecosystem-based management goals, as these often signal underlying processes that aggregate or stimulate resources in a particular location. However, previously used metrics to locate these hotspots are not easily adapted to local marine datasets, in part due to the high spatial and temporal variability of phytoplankton populations. While most fish species in temperate regions are well adapted to the seasonal variability of phytoplankton abundance, it is the variability beyond this predictable pattern (i.e. anomalies) that may heavily impact the abundance and spatial distribution of organisms higher up the food chain. The objective of this study was to identify local-scale biological hotspots in a region in the western side of the Gulf of Maine using remote sensing chlorophyll-a data (from MERIS sensor), and to study the spatial overlap between these hotspots and high concentrations of fish abundance (derived from VTR dataset). For this reason, we defined a new hotspot metric that identified as a hotspot any area that consistently exhibited high-magnitude anomalies through time, a sign of highly dynamic communities. We improved on previous indices by minimizing the effect that different means and variances across space may have on the results, a situation that often occurs when comparing coastal and offshore systems. Results show a significant spatial correlation between pelagic fish abundance and aggregations of primary productivity. Spatial correlations were also significant between benthic fish abundance and primary productivity hotspots, but only during spring months. We argue that this new hotspot index compliments existing global measures as it helps managers understand the dynamic characteristics of a complex marine system. It also provides a unique metric that is easily compared across space and between different trophic levels, which may facilitate future ecosystem-wide studies.

Historical extension of operational NDVI products for livestock insurance in Kenya

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Meroni, Michele; Shee, Apurba; Mude, Andrew G.; Woodard, Joshua; de Bie, C. A. J. M. (Kees); Rembold, Felix

2014-05-01

Droughts induce livestock losses that severely affect Kenyan pastoralists. Recent index insurance schemes have the potential of being a viable tool for insuring pastoralists against drought-related risk. Such schemes require as input a forage scarcity (or drought) index that can be reliably updated in near real-time, and that strongly relates to livestock mortality. Generally, a long record (>25 years) of the index is needed to correctly estimate mortality risk and calculate the related insurance premium. Data from current operational satellites used for large-scale vegetation monitoring span over a maximum of 15 years, a time period that is considered insufficient for accurate premium computation. This study examines how operational NDVI datasets compare to, and could be combined with the non-operational recently constructed 30-year GIMMS AVHRR record (1981-2011) to provide a near-real time drought index with a long term archive for the arid lands of Kenya. We compared six freely available, near-real time NDVI products: five from MODIS and one from SPOT-VEGETATION. Prior to comparison, all datasets were averaged in time for the two vegetative seasons in Kenya, and aggregated spatially at the administrative division level at which the insurance is offered. The feasibility of extending the resulting aggregated drought indices back in time was assessed using jackknifed R2 statistics (leave-one-year-out) for the overlapping period 2002-2011. We found that division-specific models were more effective than a global model for linking the division-level temporal variability of the index between NDVI products. Based on our results, good scope exists for historically extending the aggregated drought index, thus providing a longer operational record for insurance purposes. We showed that this extension may have large effects on the calculated insurance premium. Finally, we discuss several possible improvements to the drought index.

The Database for Aggregate Analysis of ClinicalTrials.gov (AACT) and Subsequent Regrouping by Clinical Specialty

PubMed Central

Tasneem, Asba; Aberle, Laura; Ananth, Hari; Chakraborty, Swati; Chiswell, Karen; McCourt, Brian J.; Pietrobon, Ricardo

2012-01-01

Background The ClinicalTrials.gov registry provides information regarding characteristics of past, current, and planned clinical studies to patients, clinicians, and researchers; in addition, registry data are available for bulk download. However, issues related to data structure, nomenclature, and changes in data collection over time present challenges to the aggregate analysis and interpretation of these data in general and to the analysis of trials according to clinical specialty in particular. Improving usability of these data could enhance the utility of ClinicalTrials.gov as a research resource. Methods/Principal Results The purpose of our project was twofold. First, we sought to extend the usability of ClinicalTrials.gov for research purposes by developing a database for aggregate analysis of ClinicalTrials.gov (AACT) that contains data from the 96,346 clinical trials registered as of September 27, 2010. Second, we developed and validated a methodology for annotating studies by clinical specialty, using a custom taxonomy employing Medical Subject Heading (MeSH) terms applied by an NLM algorithm, as well as MeSH terms and other disease condition terms provided by study sponsors. Clinical specialists reviewed and annotated MeSH and non-MeSH disease condition terms, and an algorithm was created to classify studies into clinical specialties based on both MeSH and non-MeSH annotations. False positives and false negatives were evaluated by comparing algorithmic classification with manual classification for three specialties. Conclusions/Significance The resulting AACT database features study design attributes parsed into discrete fields, integrated metadata, and an integrated MeSH thesaurus, and is available for download as Oracle extracts (.dmp file and text format). This publicly-accessible dataset will facilitate analysis of studies and permit detailed characterization and analysis of the U.S. clinical trials enterprise as a whole. In addition, the methodology we present for creating specialty datasets may facilitate other efforts to analyze studies by specialty groups. PMID:22438982

The database for aggregate analysis of ClinicalTrials.gov (AACT) and subsequent regrouping by clinical specialty.

PubMed

Tasneem, Asba; Aberle, Laura; Ananth, Hari; Chakraborty, Swati; Chiswell, Karen; McCourt, Brian J; Pietrobon, Ricardo

2012-01-01

The ClinicalTrials.gov registry provides information regarding characteristics of past, current, and planned clinical studies to patients, clinicians, and researchers; in addition, registry data are available for bulk download. However, issues related to data structure, nomenclature, and changes in data collection over time present challenges to the aggregate analysis and interpretation of these data in general and to the analysis of trials according to clinical specialty in particular. Improving usability of these data could enhance the utility of ClinicalTrials.gov as a research resource. The purpose of our project was twofold. First, we sought to extend the usability of ClinicalTrials.gov for research purposes by developing a database for aggregate analysis of ClinicalTrials.gov (AACT) that contains data from the 96,346 clinical trials registered as of September 27, 2010. Second, we developed and validated a methodology for annotating studies by clinical specialty, using a custom taxonomy employing Medical Subject Heading (MeSH) terms applied by an NLM algorithm, as well as MeSH terms and other disease condition terms provided by study sponsors. Clinical specialists reviewed and annotated MeSH and non-MeSH disease condition terms, and an algorithm was created to classify studies into clinical specialties based on both MeSH and non-MeSH annotations. False positives and false negatives were evaluated by comparing algorithmic classification with manual classification for three specialties. The resulting AACT database features study design attributes parsed into discrete fields, integrated metadata, and an integrated MeSH thesaurus, and is available for download as Oracle extracts (.dmp file and text format). This publicly-accessible dataset will facilitate analysis of studies and permit detailed characterization and analysis of the U.S. clinical trials enterprise as a whole. In addition, the methodology we present for creating specialty datasets may facilitate other efforts to analyze studies by specialty groups.

Ancestry and demography and descendants of Iron Age nomads of the Eurasian Steppe

NASA Astrophysics Data System (ADS)

Unterländer, Martina; Palstra, Friso; Lazaridis, Iosif; Pilipenko, Aleksandr; Hofmanová, Zuzana; Groß, Melanie; Sell, Christian; Blöcher, Jens; Kirsanow, Karola; Rohland, Nadin; Rieger, Benjamin; Kaiser, Elke; Schier, Wolfram; Pozdniakov, Dimitri; Khokhlov, Aleksandr; Georges, Myriam; Wilde, Sandra; Powell, Adam; Heyer, Evelyne; Currat, Mathias; Reich, David; Samashev, Zainolla; Parzinger, Hermann; Molodin, Vyacheslav I.; Burger, Joachim

2017-03-01

During the 1st millennium before the Common Era (BCE), nomadic tribes associated with the Iron Age Scythian culture spread over the Eurasian Steppe, covering a territory of more than 3,500 km in breadth. To understand the demographic processes behind the spread of the Scythian culture, we analysed genomic data from eight individuals and a mitochondrial dataset of 96 individuals originating in eastern and western parts of the Eurasian Steppe. Genomic inference reveals that Scythians in the east and the west of the steppe zone can best be described as a mixture of Yamnaya-related ancestry and an East Asian component. Demographic modelling suggests independent origins for eastern and western groups with ongoing gene-flow between them, plausibly explaining the striking uniformity of their material culture. We also find evidence that significant gene-flow from east to west Eurasia must have occurred early during the Iron Age.

An Intercomparison of Large-Extent Tree Canopy Cover Geospatial Datasets

NASA Astrophysics Data System (ADS)

Bender, S.; Liknes, G.; Ruefenacht, B.; Reynolds, J.; Miller, W. P.

2017-12-01

As a member of the Multi-Resolution Land Characteristics Consortium (MRLC), the U.S. Forest Service (USFS) is responsible for producing and maintaining the tree canopy cover (TCC) component of the National Land Cover Database (NLCD). The NLCD-TCC data are available for the conterminous United States (CONUS), coastal Alaska, Hawai'i, Puerto Rico, and the U.S. Virgin Islands. The most recent official version of the NLCD-TCC data is based primarily on reference data from 2010-2011 and is part of the multi-component 2011 version of the NLCD. NLCD data are updated on a five-year cycle. The USFS is currently producing the next official version (2016) of the NLCD-TCC data for the United States, and it will be made publicly-available in early 2018. In this presentation, we describe the model inputs, modeling methods, and tools used to produce the 30-m NLCD-TCC data. Several tree cover datasets at 30-m, as well as datasets at finer resolution, have become available in recent years due to advancements in earth observation data and their availability, computing, and sensors. We compare multiple tree cover datasets that have similar resolution to the NLCD-TCC data. We also aggregate the tree class from fine-resolution land cover datasets to a percent canopy value on a 30-m pixel, in order to compare the fine-resolution datasets to the datasets created directly from 30-m Landsat data. The extent of the tree canopy cover datasets included in the study ranges from global and national to the state level. Preliminary investigation of multiple tree cover datasets over the CONUS indicates a high amount of spatial variability. For example, in a comparison of the NLCD-TCC and the Global Land Cover Facility's Landsat Tree Cover Continuous Fields (2010) data by MRLC mapping zones, the zone-level root mean-square deviation ranges from 2% to 39% (mean=17%, median=15%). The analysis outcomes are expected to inform USFS decisions with regard to the next cycle (2021) of NLCD-TCC production.

Spatiotemporal variability and contribution of different aerosol types to the Aerosol Optical Depth over the Eastern Mediterranean

PubMed Central

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Pöschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2018-01-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the Aerosol Optical Depth (AOD) over the Eastern Mediterranean as derived from MODIS Terra (3/2000–12/2012) and Aqua (7/2002–12/2012) satellite instruments. For this purpose, a 0.1° × 0.1° gridded MODIS dataset was compiled and validated against sunphotometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium sized cities, industrial zones, and power plant complexes, seasonal variabilities, and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is ~ 0.22 ± 0.19 with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in Central and Eastern Europe, and transport of dust from the Sahara Desert and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine mode natural aerosols account for ~ 51 %, ~ 34 % and ~ 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account ~ 40 %, ~ 34 % and ~ 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations. PMID:29755508

Forest transitions in Eastern Europe and their effects on carbon budgets.

PubMed

Kuemmerle, Tobias; Kaplan, Jed O; Prishchepov, Alexander V; Rylsky, Ilya; Chaskovskyy, Oleh; Tikunov, Vladimir S; Müller, Daniel

2015-08-01

Forests often rebound from deforestation following industrialization and urbanization, but for many regions our understanding of where and when forest transitions happened, and how they affected carbon budgets remains poor. One such region is Eastern Europe, where political and socio-economic conditions changed drastically over the last three centuries, but forest trends have not yet been analyzed in detail. We present a new assessment of historical forest change in the European part of the former Soviet Union and the legacies of these changes on contemporary carbon stocks. To reconstruct forest area, we homogenized statistics at the provincial level for ad 1700-2010 to identify forest transition years and forest trends. We contrast our reconstruction with the KK11 and HYDE 3.1 land change scenarios, and use all three datasets to drive the LPJ dynamic global vegetation model to calculate carbon stock dynamics. Our results revealed that forest transitions in Eastern Europe occurred predominantly in the early 20th century, substantially later than in Western Europe. We also found marked geographic variation in forest transitions, with some areas characterized by relatively stable or continuously declining forest area. Our data suggest extensive deforestation in European Russia already prior to ad 1700, and even greater deforestation in the 18th and 19th centuries than in the KK11 and HYDE scenarios. Based on our reconstruction, cumulative carbon emissions from deforestation were greater before 1700 (60 Pg C) than thereafter (29 Pg C). Summed over our entire study area, forest transitions led to a modest uptake in carbon over recent decades, with our dataset showing the smallest effect (<5.5 Pg C) and a more heterogeneous pattern of source and sink regions. This suggests substantial sequestration potential in regrowing forests of the region, a trend that may be amplified through ongoing land abandonment, climate change, and CO2 fertilization. © 2015 John Wiley & Sons Ltd.

Spatiotemporal variability and contribution of different aerosol types to the aerosol optical depth over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Pöschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-11-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the aerosol optical depth (AOD) over the Eastern Mediterranean as derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra (March 2000-December 2012) and Aqua (July 2002-December 2012) satellite instruments. For this purpose, a 0.1° × 0.1° gridded MODIS dataset was compiled and validated against sun photometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium-sized cities, industrial zones and power plant complexes, seasonal variabilities and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is ˜ 0.22 ± 0.19, with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in central and eastern Europe and transport of dust from the Sahara and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine-mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine-mode natural aerosols account for ˜ 51, ˜ 34 and ˜ 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account ˜ 40, ˜ 34 and ˜ 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations.

Spatiotemporal Variability and Contribution of Different Aerosol Types to the Aerosol Optical Depth over the Eastern Mediterranean

NASA Technical Reports Server (NTRS)

Georgoulias, Aristeidis K.; Alexandri, Georgia; Kourtidis, Konstantinos A.; Lelieveld, Jos; Zanis, Prodromos; Poeschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-01-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the aerosol optical depth (AOD) over the Eastern Mediterranean as derived from MODIS (Moderate Resolution Imaging Spectroradiometer) Terra (March 2000-December 2012) and Aqua (July 2002-December 2012) satellite instruments. For this purpose, a 0.1deg × 0.1deg gridded MODIS dataset was compiled and validated against sun photometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium-sized cities, industrial zones and power plant complexes, seasonal variabilities and decadal averages. The average AOD at 550 nm (AOD550) for the entire region is approx. 0.22 +/- 0.19, with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in central and eastern Europe and transport of dust from the Sahara and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD550. The spatial and temporal variability of anthropogenic, dust and fine-mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine-mode natural aerosols account for approx. 51, approx. 34 and approx. 15 % of the total AOD550 over land, while, anthropogenic aerosols, dust and marine aerosols account approx. 40, approx. 34 and approx. 26 % of the total AOD550 over the sea, based on MODIS Terra and Aqua observations.

Spatiotemporal variability and contribution of different aerosol types to the Aerosol Optical Depth over the Eastern Mediterranean.

PubMed

Georgoulias, Aristeidis K; Alexandri, Georgia; Kourtidis, Konstantinos A; Lelieveld, Jos; Zanis, Prodromos; Pöschl, Ulrich; Levy, Robert; Amiridis, Vassilis; Marinou, Eleni; Tsikerdekis, Athanasios

2016-01-01

This study characterizes the spatiotemporal variability and relative contribution of different types of aerosols to the Aerosol Optical Depth (AOD) over the Eastern Mediterranean as derived from MODIS Terra (3/2000-12/2012) and Aqua (7/2002-12/2012) satellite instruments. For this purpose, a 0.1° × 0.1° gridded MODIS dataset was compiled and validated against sunphotometric observations from the AErosol RObotic NETwork (AERONET). The high spatial resolution and long temporal coverage of the dataset allows for the determination of local hot spots like megacities, medium sized cities, industrial zones, and power plant complexes, seasonal variabilities, and decadal averages. The average AOD at 550 nm (AOD 550 ) for the entire region is ~ 0.22 ± 0.19 with maximum values in summer and seasonal variabilities that can be attributed to precipitation, photochemical production of secondary organic aerosols, transport of pollution and smoke from biomass burning in Central and Eastern Europe, and transport of dust from the Sahara Desert and the Middle East. The MODIS data were analyzed together with data from other satellite sensors, reanalysis projects and a chemistry-aerosol-transport model using an optimized algorithm tailored for the region and capable of estimating the contribution of different aerosol types to the total AOD 550 . The spatial and temporal variability of anthropogenic, dust and fine mode natural aerosols over land and anthropogenic, dust and marine aerosols over the sea is examined. The relative contribution of the different aerosol types to the total AOD 550 exhibits a low/high seasonal variability over land/sea areas, respectively. Overall, anthropogenic aerosols, dust and fine mode natural aerosols account for ~ 51 %, ~ 34 % and ~ 15 % of the total AOD 550 over land, while, anthropogenic aerosols, dust and marine aerosols account ~ 40 %, ~ 34 % and ~ 26 % of the total AOD 550 over the sea, based on MODIS Terra and Aqua observations.

Effects of spatial resolution and landscape structure on land cover characterization

NASA Astrophysics Data System (ADS)

Yang, Wenli

This dissertation addressed problems in scaling, problems that are among the main challenges in remote sensing. The principal objective of the research was to investigate the effects of changing spatial scale on the representation of land cover. A second objective was to determine the relationship between such effects, characteristics of landscape structure and scaling procedures. Four research issues related to spatial scaling were examined. They included: (1) the upscaling of Normalized Difference Vegetation Index (NDVI); (2) the effects of spatial scale on indices of landscape structure; (3) the representation of land cover databases at different spatial scales; and (4) the relationships between landscape indices and land cover area estimations. The overall bias resulting from non-linearity of NDVI in relation to spatial resolution is generally insignificant as compared to other factors such as influences of aerosols and water vapor. The bias is, however, related to land surface characteristics. Significant errors may be introduced in heterogeneous areas where different land cover types exhibit strong spectral contrast. Spatially upscaled SPOT and TM NDVIs have information content comparable with the AVHRR-derived NDVI. Indices of landscape structure and spatial resolution are generally related, but the exact forms of the relationships are subject to changes in other factors including the basic patch unit constituting a landscape and the proportional area of foreground land cover under consideration. The extent of agreement between spatially aggregated coarse resolution land cover datasets and full resolution datasets changes with the properties of the original datasets, including the pixel size and class definition. There are close relationships between landscape structure and class areas estimated from spatially aggregated land cover databases. The relationships, however, do not permit extension from one area to another. Inversion calibration across different geographic/ecological areas is, therefore, not feasible. Different rules govern the land cover area changes across resolutions when different upscaling methods are used. Special attention should be given to comparison between land cover maps derived using different methods.

ENSO-cave drip water hydrochemical relationship: a 7-year dataset from south-eastern Australia

NASA Astrophysics Data System (ADS)

Tadros, Carol V.; Treble, Pauline C.; Baker, Andy; Fairchild, Ian; Hankin, Stuart; Roach, Regina; Markowska, Monika; McDonald, Janece

2016-11-01

Speleothems (cave deposits), used for palaeoenvironmental reconstructions, are deposited from cave drip water. Differentiating climate and karst processes within a drip-water signal is fundamental for the correct identification of palaeoenvironmental proxies and ultimately their interpretation within speleothem records. We investigate the potential use of trace element and stable oxygen-isotope (δ18O) variations in cave drip water as palaeorainfall proxies in an Australian alpine karst site. This paper presents the first extensive hydrochemical and δ18O dataset from Harrie Wood Cave, in the Snowy Mountains, south-eastern (SE) Australia. Using a 7-year long rainfall δ18O and drip-water Ca, Cl, Mg / Ca, Sr / Ca and δ18O datasets from three drip sites, we determined that the processes of mixing, dilution, flow path change, carbonate mineral dissolution and prior calcite precipitation (PCP) accounted for the observed variations in the drip-water geochemical composition. We identify that the three monitored drip sites are fed by fracture flow from a well-mixed epikarst storage reservoir, supplied by variable concentrations of dissolved ions from soil and bedrock dissolution. We constrained the influence of multiple processes and controls on drip-water composition in a region dominated by El Niño-Southern Oscillation (ENSO). During the El Niño and dry periods, enhanced PCP, a flow path change and dissolution due to increased soil CO2 production occurred in response to warmer than average temperatures in contrast to the La Niña phase, where dilution dominated and reduced PCP were observed. We present a conceptual model, illustrating the key processes impacting the drip-water chemistry. We identified a robust relationship between ENSO and drip-water trace element concentrations and propose that variations in speleothem Mg / Ca and Sr / Ca ratios may be interpreted to reflect palaeorainfall conditions. These findings inform palaeorainfall reconstruction from speleothems regionally and provide a basis for palaeoclimate studies globally, in regions where there is intermittent recharge variability.

Analysis of clouds and precipitation during Baiu period over the East China Sea with cloud database CTOP and precipitation database GSMaP

NASA Astrophysics Data System (ADS)

Nishi, N.; Hamada, A.; Hirose, H.; Hotta, S.; Suzuki, J.

2016-12-01

We have made a quantitative research of the clouds and precipitation during Baiu: the rainy season within the East Asia, using recent satellite observation datasets. As the precipitation dataset, we utilized the Global Satellite Mapping of Precipitation (GSMaP), whose primary source is passive microwave observations. As the cloud dataset, we used our original database CTOP, in which the cloud top height and optical depth are estimated only with the infrared split-window channels of the geostationary satellites. Lookup tables are made by training the infrared observations with the direct cloud observation by CloudSat and CALIPSO. This technique was originally developed only for the tropics but we extended it to the mid-latitude by estimating temperature at the cloud top instead of the height. We analyzed the properties of northward shift of the Baiu precipitation zone over the East China Sea. Abrupt northward shift in mid-June has already been reported. We showed here that the abrupt shift is limited to the western half of the East China Sea. We also analyzed the zonal difference of the precipitation amount in the East China Sea. In the central latitudinal range (30-33N), the amount is larger in the eastern part of the sea. There is no significant zonal contrast in both the activity of the low pressure and the front, while the sea surface temperature in the eastern part is slightly larger than in the western part. The zonal gradient is much smaller than that in the southern region near the Kuroshio Current, but may possibly affect the zonal contrast of the precipitation. By using CTOP cloud top data, we also calculated the occurrence ratio of the cloud with various thresholds of the top height. The ratio of clouds with the tops higher than 12 km in the East China Sea is clearly lower than those over the Continental area and the main Japanese islands.

Federated Tensor Factorization for Computational Phenotyping

PubMed Central

Kim, Yejin; Sun, Jimeng; Yu, Hwanjo; Jiang, Xiaoqian

2017-01-01

Tensor factorization models offer an effective approach to convert massive electronic health records into meaningful clinical concepts (phenotypes) for data analysis. These models need a large amount of diverse samples to avoid population bias. An open challenge is how to derive phenotypes jointly across multiple hospitals, in which direct patient-level data sharing is not possible (e.g., due to institutional policies). In this paper, we developed a novel solution to enable federated tensor factorization for computational phenotyping without sharing patient-level data. We developed secure data harmonization and federated computation procedures based on alternating direction method of multipliers (ADMM). Using this method, the multiple hospitals iteratively update tensors and transfer secure summarized information to a central server, and the server aggregates the information to generate phenotypes. We demonstrated with real medical datasets that our method resembles the centralized training model (based on combined datasets) in terms of accuracy and phenotypes discovery while respecting privacy. PMID:29071165

Biotea: semantics for Pubmed Central.

PubMed

Garcia, Alexander; Lopez, Federico; Garcia, Leyla; Giraldo, Olga; Bucheli, Victor; Dumontier, Michel

2018-01-01

A significant portion of biomedical literature is represented in a manner that makes it difficult for consumers to find or aggregate content through a computational query. One approach to facilitate reuse of the scientific literature is to structure this information as linked data using standardized web technologies. In this paper we present the second version of Biotea, a semantic, linked data version of the open-access subset of PubMed Central that has been enhanced with specialized annotation pipelines that uses existing infrastructure from the National Center for Biomedical Ontology. We expose our models, services, software and datasets. Our infrastructure enables manual and semi-automatic annotation, resulting data are represented as RDF-based linked data and can be readily queried using the SPARQL query language. We illustrate the utility of our system with several use cases. Our datasets, methods and techniques are available at http://biotea.github.io.

Information Theory and Voting Based Consensus Clustering for Combining Multiple Clusterings of Chemical Structures.

PubMed

Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2013-07-01

Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Hybrid Knowledge-Based and Data-Driven Approach to Identifying Semantically Similar Concepts

PubMed Central

Pivovarov, Rimma; Elhadad, Noémie

2012-01-01

An open research question when leveraging ontological knowledge is when to treat different concepts separately from each other and when to aggregate them. For instance, concepts for the terms "paroxysmal cough" and "nocturnal cough" might be aggregated in a kidney disease study, but should be left separate in a pneumonia study. Determining whether two concepts are similar enough to be aggregated can help build better datasets for data mining purposes and avoid signal dilution. Quantifying the similarity among concepts is a difficult task, however, in part because such similarity is context-dependent. We propose a comprehensive method, which computes a similarity score for a concept pair by combining data-driven and ontology-driven knowledge. We demonstrate our method on concepts from SNOMED-CT and on a corpus of clinical notes of patients with chronic kidney disease. By combining information from usage patterns in clinical notes and from ontological structure, the method can prune out concepts that are simply related from those which are semantically similar. When evaluated against a list of concept pairs annotated for similarity, our method reaches an AUC (area under the curve) of 92%. PMID:22289420

A suite of global, cross-scale topographic variables for environmental and biodiversity modeling

NASA Astrophysics Data System (ADS)

Amatulli, Giuseppe; Domisch, Sami; Tuanmu, Mao-Ning; Parmentier, Benoit; Ranipeta, Ajay; Malczyk, Jeremy; Jetz, Walter

2018-03-01

Topographic variation underpins a myriad of patterns and processes in hydrology, climatology, geography and ecology and is key to understanding the variation of life on the planet. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications, however to date, such datasets are unavailable. Here we used the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches. While a cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at Data Citation 1 and for download and visualization at http://www.earthenv.org/topography.

Global and continental changes of arid areas using the FAO Aridity Index over the periods 1951-1980 and 1981-2010

NASA Astrophysics Data System (ADS)

Spinoni, Jonathan; Micale, Fabio; Carrao, Hugo; Naumann, Gustavo; Barbosa, Paulo; Vogt, Jürgen

2013-04-01

An increase in arid areas and progressing land degradation are two of the main consequences of global climate change. In the 2nd edition of the World Atlas of Desertification (WAD), published by the United Nation Environment Program (UNEP) in 1997, a global aridity map was presented. This map was based on the Food and Agriculture Organization (FAO) Aridity Index (AI) that takes into account the annual ratio between precipitation (RR) and Potential Evapo-Transpiration (PET). According to the long-term mean value of this ratio, climate is therefore classified in hyper-arid (<0.05), arid (0.05-0.2), semi-arid (0.2-0.5), dry sub-humid (0.5-0.65), and humid (>0.65); a special case are cold climates, which occur if the mean annual PET is below 400 mm. In the framework of the 3rd edition of the WAD, we computed new global aridity maps to improve and update the old version that was based on a single dataset (CRU dataset, Climate Research Unit of University of East Anglia) related to the 1951-80 period only. We computed the AI on two different time intervals (1951-80 and 1981-2010) in order to account for shifts in classes between the two periods and we used two different datasets: PET from CRU (version 3.2), and precipitation from the global 0.5˚x0.5˚ gridded monthly precipitation of the Global Precipitation Climatology Center (GPCC) of the Deutscher Wetterdienst (DWD). We used the GPCC Full Data Reanalysis Version 6.0, which showed a high reliability during many quality checks and is based on more stations than the CRU's precipitation counterpart. The results show that the "arid areas" (i.e. AI <0.5) globally increased from 28.4% to 29.6% and in Northern Hemisphere the cold climate areas decreased from 26.6% to 25.4%. Comparing the aridity maps of the two periods, the areas which most remarkably moved to lower AI values ("more arid" conditions) are: Canada, Brazil, the Mediterranean Region, Eastern Europe, almost all of Africa, the Middle East, Eastern China, Borneo, and Australia. At regional or country level, a shift of one class towards a "more arid" class can be found in Alaska (U.S.), Alberta (Canada), Patagonia (Argentina), Pernambuco (Brazil), Western Peru, Spain, the Southern Sahara and North-Eastern Kalahari deserts, Rajasthan and Madhya Pradesh (India), Mongolia, the Yang-Tze Basin (China), and the North-Eastern and South-Western Australian coasts. On the other hand, Central U.S., Paraguay and Northern Argentina, Scandinavia, Northern Australia, and Western China moved to a wetter climate in the last period. Due to the low data availability, we assumed that no changes took place in Antarctica, which is meant to be under a permanent ice cap, excluding the northernmost Graham Land.

Search for the 700,000-year-old source crater of the Australasian tektite strewn field

NASA Technical Reports Server (NTRS)

Schnetzler, C. C.; Garvin, J. B.

1992-01-01

Many tektite investigations have hypothesized that the impact crater that was the source of the extensive Australasian strewn field lies somewhere in or near Indochina. This is due to variations in abundance and size of tektites across the strewn field, variation of thickness of microtektite layers in ocean cores, nature and ablation characteristics across the field, and, above all, the occurrence of the large, blocky, layered Muong Nong-type tektites in Indochina. A recent study of the location and chemistry of Muong Nong-type and splash-form tektites suggests that the source region can be further narrowed to a limited area in eastern Thailand and southern Loas. Satellite multispectral imagery, a digital elevation dataset, and maps showing drainage patterns were used to search within this area for possible anomalous features that may be large degraded impact craters. Four interesting structures were identified from these datasets, and they are presented.

Direct Measurements of the Convective Recycling of the Upper Troposphere

NASA Technical Reports Server (NTRS)

Bertram, Timothy H.; Perring, Anne E.; Wooldridge, Paul J.; Crounse, John D.; Kwan, Alan J.; Wennberg, Paul O.; Scheuer, Eric; Dibb, Jack; Avery, Melody; Sachse, Glen;

Authigenic kaolinite and associated pyrite in chalk of the Cretaceous Niobrara Formation, Eastern Colorado.

USGS Publications Warehouse

Pollastro, R.M.

1981-01-01

Cores from the Smoky Hill Chalk Member of the Cretaceous Niobrara Formation have several zones containing authigenic kaolinite as spherical, moldic, polycrystalline aggregates that occur within single or multichambered foraminiferal tests and are commonly associated with framboidal pyrite. Such kaolinite is inferred to result from volcanic ash deposited during chalk sedimentation. Shortly after burial, a colloidal aluminous gel or solution formed from the unstable ash and moved into organic-rich foraminiferal tests, where sulfate-reducing bacteria created a favorable microenvironment for the simultaneous crystallization of kaolinite and pyrite. -Author

Beluga whale (Delphinapterus leucas) vocalizations and call classification from the eastern Beaufort Sea population.

PubMed

Garland, Ellen C; Castellote, Manuel; Berchok, Catherine L

2015-06-01

Beluga whales, Delphinapterus leucas, have a graded call system; call types exist on a continuum making classification challenging. A description of vocalizations from the eastern Beaufort Sea beluga population during its spring migration are presented here, using both a non-parametric classification tree analysis (CART), and a Random Forest analysis. Twelve frequency and duration measurements were made on 1019 calls recorded over 14 days off Icy Cape, Alaska, resulting in 34 identifiable call types with 83% agreement in classification for both CART and Random Forest analyses. This high level of agreement in classification, with an initial subjective classification of calls into 36 categories, demonstrates that the methods applied here provide a quantitative analysis of a graded call dataset. Further, as calls cannot be attributed to individuals using single sensor passive acoustic monitoring efforts, these methods provide a comprehensive analysis of data where the influence of pseudo-replication of calls from individuals is unknown. This study is the first to describe the vocal repertoire of a beluga population using a robust and repeatable methodology. A baseline eastern Beaufort Sea beluga population repertoire is presented here, against which the call repertoire of other seasonally sympatric Alaskan beluga populations can be compared.

Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits

PubMed Central

Vesk, Peter A.

2017-01-01

Plant functional traits are increasingly used to generalize across species, however few examples exist of predictions from trait-based models being evaluated in new species or new places. Can we use functional traits to predict growth of unknown species in different areas? We used three independently collected datasets, each containing data on heights of individuals from non-resprouting species over a chronosquence of time-since-fire sites from three ecosystems in south-eastern Australia. We examined the influence of specific leaf area, woody density, seed size and leaf nitrogen content on three aspects of plant growth; maximum relative growth rate, age at maximum growth and asymptotic height. We tested our capacity to perform out-of-sample prediction of growth trajectories between ecosystems using species functional traits. We found strong trait-growth relationships in one of the datasets; whereby species with low SLA achieved the greatest asymptotic heights, species with high leaf-nitrogen content achieved relatively fast growth rates, and species with low seed mass reached their time of maximum growth early. However these same growth-trait relationships did not hold across the two other datasets, making accurate prediction from one dataset to another unachievable. We believe there is evidence to suggest that growth trajectories themselves may be fundamentally different between ecosystems and that trait-height-growth relationships may change over environmental gradients. PMID:28486535

Density-Aware Clustering Based on Aggregated Heat Kernel and Its Transformation

DOE PAGES

Huang, Hao; Yoo, Shinjae; Yu, Dantong; ...

2015-06-01

Current spectral clustering algorithms suffer from the sensitivity to existing noise, and parameter scaling, and may not be aware of different density distributions across clusters. If these problems are left untreated, the consequent clustering results cannot accurately represent true data patterns, in particular, for complex real world datasets with heterogeneous densities. This paper aims to solve these problems by proposing a diffusion-based Aggregated Heat Kernel (AHK) to improve the clustering stability, and a Local Density Affinity Transformation (LDAT) to correct the bias originating from different cluster densities. AHK statistically\\ models the heat diffusion traces along the entire time scale, somore » it ensures robustness during clustering process, while LDAT probabilistically reveals local density of each instance and suppresses the local density bias in the affinity matrix. Our proposed framework integrates these two techniques systematically. As a result, not only does it provide an advanced noise-resisting and density-aware spectral mapping to the original dataset, but also demonstrates the stability during the processing of tuning the scaling parameter (which usually controls the range of neighborhood). Furthermore, our framework works well with the majority of similarity kernels, which ensures its applicability to many types of data and problem domains. The systematic experiments on different applications show that our proposed algorithms outperform state-of-the-art clustering algorithms for the data with heterogeneous density distributions, and achieve robust clustering performance with respect to tuning the scaling parameter and handling various levels and types of noise.« less

A method to derive vegetation distribution maps for pollen dispersion models using birch as an example

NASA Astrophysics Data System (ADS)

Pauling, A.; Rotach, M. W.; Gehrig, R.; Clot, B.

2012-09-01

Detailed knowledge of the spatial distribution of sources is a crucial prerequisite for the application of pollen dispersion models such as, for example, COSMO-ART (COnsortium for Small-scale MOdeling - Aerosols and Reactive Trace gases). However, this input is not available for the allergy-relevant species such as hazel, alder, birch, grass or ragweed. Hence, plant distribution datasets need to be derived from suitable sources. We present an approach to produce such a dataset from existing sources using birch as an example. The basic idea is to construct a birch dataset using a region with good data coverage for calibration and then to extrapolate this relationship to a larger area by using land use classes. We use the Swiss forest inventory (1 km resolution) in combination with a 74-category land use dataset that covers the non-forested areas of Switzerland as well (resolution 100 m). Then we assign birch density categories of 0%, 0.1%, 0.5% and 2.5% to each of the 74 land use categories. The combination of this derived dataset with the birch distribution from the forest inventory yields a fairly accurate birch distribution encompassing entire Switzerland. The land use categories of the Global Land Cover 2000 (GLC2000; Global Land Cover 2000 database, 2003, European Commission, Joint Research Centre; resolution 1 km) are then calibrated with the Swiss dataset in order to derive a Europe-wide birch distribution dataset and aggregated onto the 7 km COSMO-ART grid. This procedure thus assumes that a certain GLC2000 land use category has the same birch density wherever it may occur in Europe. In order to reduce the strict application of this crucial assumption, the birch density distribution as obtained from the previous steps is weighted using the mean Seasonal Pollen Index (SPI; yearly sums of daily pollen concentrations). For future improvement, region-specific birch densities for the GLC2000 categories could be integrated into the mapping procedure.

Asymmetric variations in the tropical ascending branches of Hadley circulations and the associated mechanisms and effects

NASA Astrophysics Data System (ADS)

Sun, Bo

2018-03-01

This study investigates the variations in the tropical ascending branches (TABs) of Hadley circulations (HCs) during past decades, using a variety of reanalysis datasets. The northern tropical ascending branch (NTAB) and the southern tropical ascending branch (STAB), which are defined as the ascending branches of the Northern Hemisphere HC and Southern Hemisphere HC, respectively, are identified and analyzed regarding their trends and variability. The reanalysis datasets consistently show a persistent increase in STAB during past decades, whereas they show less consistency in NTAB regarding its decadalto multidecadal variability, which generally features a decreasing trend. These asymmetric trends in STAB and NTAB are attributed to asymmetric trends in the tropical SSTs. The relationship between STAB/NTAB and tropical SSTs is further examined regarding their interannual and decadal- to multidecadal variability. On the interannual time scale, the STAB and NTAB are essentially modulated by the eastern-Pacific type of ENSO, with a strengthened (weakened) STAB (NTAB) under an El Niño condition. On the decadal- to multidecadal time scale, the variability of STAB and NTAB is closely related to the southern tropical SSTs and the meridional asymmetry of global tropical SSTs, respectively. The tropical eastern Pacific SSTs (southern tropical SSTs) dominate the tropical SST-NTAB/STAB relationship on the interannual (decadal- to multidecadal) scale, whereas the NTAB is a passive factor in this relationship. Moreover, a cross-hemispheric relationship between the NTAB/STAB and the HC upper-level meridional winds is revealed.

Research Resource: A Reference Transcriptome for Constitutive Androstane Receptor and Pregnane X Receptor Xenobiotic Signaling

PubMed Central

Ochsner, Scott A.; Tsimelzon, Anna; Dong, Jianrong; Coarfa, Cristian

2016-01-01

The pregnane X receptor (PXR) (PXR/NR1I3) and constitutive androstane receptor (CAR) (CAR/NR1I2) members of the nuclear receptor (NR) superfamily of ligand-regulated transcription factors are well-characterized mediators of xenobiotic and endocrine-disrupting chemical signaling. The Nuclear Receptor Signaling Atlas maintains a growing library of transcriptomic datasets involving perturbations of NR signaling pathways, many of which involve perturbations relevant to PXR and CAR xenobiotic signaling. Here, we generated a reference transcriptome based on the frequency of differential expression of genes across 159 experiments compiled from 22 datasets involving perturbations of CAR and PXR signaling pathways. In addition to the anticipated overrepresentation in the reference transcriptome of genes encoding components of the xenobiotic stress response, the ranking of genes involved in carbohydrate metabolism and gonadotropin action sheds mechanistic light on the suspected role of xenobiotics in metabolic syndrome and reproductive disorders. Gene Set Enrichment Analysis showed that although acetaminophen, chlorpromazine, and phenobarbital impacted many similar gene sets, differences in direction of regulation were evident in a variety of processes. Strikingly, gene sets representing genes linked to Parkinson's, Huntington's, and Alzheimer's diseases were enriched in all 3 transcriptomes. The reference xenobiotic transcriptome will be supplemented with additional future datasets to provide the community with a continually updated reference transcriptomic dataset for CAR- and PXR-mediated xenobiotic signaling. Our study demonstrates how aggregating and annotating transcriptomic datasets, and making them available for routine data mining, facilitates research into the mechanisms by which xenobiotics and endocrine-disrupting chemicals subvert conventional NR signaling modalities. PMID:27409825

Research Resource: A Reference Transcriptome for Constitutive Androstane Receptor and Pregnane X Receptor Xenobiotic Signaling.

PubMed

Ochsner, Scott A; Tsimelzon, Anna; Dong, Jianrong; Coarfa, Cristian; McKenna, Neil J

2016-08-01

The pregnane X receptor (PXR) (PXR/NR1I3) and constitutive androstane receptor (CAR) (CAR/NR1I2) members of the nuclear receptor (NR) superfamily of ligand-regulated transcription factors are well-characterized mediators of xenobiotic and endocrine-disrupting chemical signaling. The Nuclear Receptor Signaling Atlas maintains a growing library of transcriptomic datasets involving perturbations of NR signaling pathways, many of which involve perturbations relevant to PXR and CAR xenobiotic signaling. Here, we generated a reference transcriptome based on the frequency of differential expression of genes across 159 experiments compiled from 22 datasets involving perturbations of CAR and PXR signaling pathways. In addition to the anticipated overrepresentation in the reference transcriptome of genes encoding components of the xenobiotic stress response, the ranking of genes involved in carbohydrate metabolism and gonadotropin action sheds mechanistic light on the suspected role of xenobiotics in metabolic syndrome and reproductive disorders. Gene Set Enrichment Analysis showed that although acetaminophen, chlorpromazine, and phenobarbital impacted many similar gene sets, differences in direction of regulation were evident in a variety of processes. Strikingly, gene sets representing genes linked to Parkinson's, Huntington's, and Alzheimer's diseases were enriched in all 3 transcriptomes. The reference xenobiotic transcriptome will be supplemented with additional future datasets to provide the community with a continually updated reference transcriptomic dataset for CAR- and PXR-mediated xenobiotic signaling. Our study demonstrates how aggregating and annotating transcriptomic datasets, and making them available for routine data mining, facilitates research into the mechanisms by which xenobiotics and endocrine-disrupting chemicals subvert conventional NR signaling modalities.

Soil aggregate stability and wind erodible fraction in a semi-arid environment of White Nile State, Sudan

NASA Astrophysics Data System (ADS)

Elhaja, Mohamed Eltom; Ibrahim, Ibrahim Saeed; Adam, Hassan Elnour; Csaplovics, Elmar

2014-11-01

One of the most important recent issues facing White Nile State, Sudan, as well as Sub Saharan Africa, is the threat of continued land degradation and desertification as a result of climatic factors and human activities. Remote sensing and satellites imageries with multi-temporal and spectral and GIS capability, plays a major role in developing a global and local operational capability for monitoring land degradation and desertification in dry lands, as well as in White Nile State. The process of desertification in form of sand encroachment in White Nile State has increased rapidly, and much effort has been devoted to define and study its causes and impacts. This study depicts the capability afforded by remote sensing and GIS to analyze and map the aggregate stability as indicator for the ability of soil to wind erosion process in White Nile State by using Geo-statistical techniques. Cloud-free subset Landsat; Enhance Thematic Mapper plus (ETM +) scenes covering the study area dated 2008 was selected in order to identify the different features covering the study area as well as to make the soil sampling map. Wet-sieving method was applied to determine the aggregate stability. The geo-statistical methods in EARDAS 9.1 software was used for mapping the aggregate stability. The results showed that the percentage of aggregate stability ranged from (0 to 61%) in the study area, which emphasized the phenomena of sand encroachment from the western part (North Kordofan) to the eastern part (White Nile State), following the wind direction. The study comes out with some valuable recommendations and comments, which could contribute positively in reducing sand encroachments

Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs: Application to the North-Eastern Mediterranean.

PubMed

Messina, Francesco; Finocchio, Andrea; Akar, Nejat; Loutradis, Aphrodite; Michalodimitrakis, Emmanuel I; Brdicka, Radim; Jodice, Carla; Novelletto, Andrea

2016-01-01

Human forensic STRs used for individual identification have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries crucial to the understanding of discontinuities at the European/Asian junction and the genetic legacy of ancient migrations, but seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long- to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. Several aspects of our results are confirmed on external STR datasets and replicate those of genome-wide SNP typings. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising from a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools.

A crab swarm at an ecological hotspot: patchiness and population density from AUV observations at a coastal, tropical seamount.

PubMed

Pineda, Jesús; Cho, Walter; Starczak, Victoria; Govindarajan, Annette F; Guzman, Héctor M; Girdhar, Yogesh; Holleman, Rusty C; Churchill, James; Singh, Hanumant; Ralston, David K

2016-01-01

A research cruise to Hannibal Bank, a seamount and an ecological hotspot in the coastal eastern tropical Pacific Ocean off Panama, explored the zonation, biodiversity, and the ecological processes that contribute to the seamount's elevated biomass. Here we describe the spatial structure of a benthic anomuran red crab population, using submarine video and autonomous underwater vehicle (AUV) photographs. High density aggregations and a swarm of red crabs were associated with a dense turbid layer 4-10 m above the bottom. The high density aggregations were constrained to 355-385 m water depth over the Northwest flank of the seamount, although the crabs also occurred at lower densities in shallower waters (∼280 m) and in another location of the seamount. The crab aggregations occurred in hypoxic water, with oxygen levels of 0.04 ml/l. Barcoding of Hannibal red crabs, and pelagic red crabs sampled in a mass stranding event in 2015 at a beach in San Diego, California, USA, revealed that the Panamanian and the Californian crabs are likely the same species, Pleuroncodes planipes, and these findings represent an extension of the southern endrange of this species. Measurements along a 1.6 km transect revealed three high density aggregations, with the highest density up to 78 crabs/m(2), and that the crabs were patchily distributed. Crab density peaked in the middle of the patch, a density structure similar to that of swarming insects.

A crab swarm at an ecological hotspot: patchiness and population density from AUV observations at a coastal, tropical seamount

PubMed Central

Cho, Walter; Starczak, Victoria; Govindarajan, Annette F.; Guzman, Héctor M.; Girdhar, Yogesh; Holleman, Rusty C.; Churchill, James; Singh, Hanumant; Ralston, David K.

2016-01-01

A research cruise to Hannibal Bank, a seamount and an ecological hotspot in the coastal eastern tropical Pacific Ocean off Panama, explored the zonation, biodiversity, and the ecological processes that contribute to the seamount’s elevated biomass. Here we describe the spatial structure of a benthic anomuran red crab population, using submarine video and autonomous underwater vehicle (AUV) photographs. High density aggregations and a swarm of red crabs were associated with a dense turbid layer 4–10 m above the bottom. The high density aggregations were constrained to 355–385 m water depth over the Northwest flank of the seamount, although the crabs also occurred at lower densities in shallower waters (∼280 m) and in another location of the seamount. The crab aggregations occurred in hypoxic water, with oxygen levels of 0.04 ml/l. Barcoding of Hannibal red crabs, and pelagic red crabs sampled in a mass stranding event in 2015 at a beach in San Diego, California, USA, revealed that the Panamanian and the Californian crabs are likely the same species, Pleuroncodes planipes, and these findings represent an extension of the southern endrange of this species. Measurements along a 1.6 km transect revealed three high density aggregations, with the highest density up to 78 crabs/m2, and that the crabs were patchily distributed. Crab density peaked in the middle of the patch, a density structure similar to that of swarming insects. PMID:27114859

Spatial distribution and occurrence probability of regional new particle formation events in eastern China

NASA Astrophysics Data System (ADS)

Shen, Xiaojing; Sun, Junying; Kivekäs, Niku; Kristensson, Adam; Zhang, Xiaoye; Zhang, Yangmei; Zhang, Lu; Fan, Ruxia; Qi, Xuefei; Ma, Qianli; Zhou, Huaigang

2018-01-01

In this work, the spatial extent of new particle formation (NPF) events and the relative probability of observing particles originating from different spatial origins around three rural sites in eastern China were investigated using the NanoMap method, using particle number size distribution (PNSD) data and air mass back trajectories. The length of the datasets used were 7, 1.5, and 3 years at rural sites Shangdianzi (SDZ) in the North China Plain (NCP), Mt. Tai (TS) in central eastern China, and Lin'an (LAN) in the Yangtze River Delta region in eastern China, respectively. Regional NPF events were observed to occur with the horizontal extent larger than 500 km at SDZ and TS, favoured by the fast transport of northwesterly air masses. At LAN, however, the spatial footprint of NPF events was mostly observed around the site within 100-200 km. Difference in the horizontal spatial distribution of new particle source areas at different sites was connected to typical meteorological conditions at the sites. Consecutive large-scale regional NPF events were observed at SDZ and TS simultaneously and were associated with a high surface pressure system dominating over this area. Simultaneous NPF events at SDZ and LAN were seldom observed. At SDZ the polluted air masses arriving over the NCP were associated with higher particle growth rate (GR) and new particle formation rate (J) than air masses from Inner Mongolia (IM). At TS the same phenomenon was observed for J, but GR was somewhat lower in air masses arriving over the NCP compared to those arriving from IM. The capability of NanoMap to capture the NPF occurrence probability depends on the length of the dataset of PNSD measurement but also on topography around the measurement site and typical air mass advection speed during NPF events. Thus the long-term measurements of PNSD in the planetary boundary layer are necessary in the further study of spatial extent and the probability of NPF events. The spatial extent, relative probability of occurrence, and typical evolution of PNSD during NPF events presented in this study provide valuable information to further understand the climate and air quality effects of new particle formation.

Automatic localization of the left ventricular blood pool centroid in short axis cardiac cine MR images.

PubMed

Tan, Li Kuo; Liew, Yih Miin; Lim, Einly; Abdul Aziz, Yang Faridah; Chee, Kok Han; McLaughlin, Robert A

2018-06-01

In this paper, we develop and validate an open source, fully automatic algorithm to localize the left ventricular (LV) blood pool centroid in short axis cardiac cine MR images, enabling follow-on automated LV segmentation algorithms. The algorithm comprises four steps: (i) quantify motion to determine an initial region of interest surrounding the heart, (ii) identify potential 2D objects of interest using an intensity-based segmentation, (iii) assess contraction/expansion, circularity, and proximity to lung tissue to score all objects of interest in terms of their likelihood of constituting part of the LV, and (iv) aggregate the objects into connected groups and construct the final LV blood pool volume and centroid. This algorithm was tested against 1140 datasets from the Kaggle Second Annual Data Science Bowl, as well as 45 datasets from the STACOM 2009 Cardiac MR Left Ventricle Segmentation Challenge. Correct LV localization was confirmed in 97.3% of the datasets. The mean absolute error between the gold standard and localization centroids was 2.8 to 4.7 mm, or 12 to 22% of the average endocardial radius. Graphical abstract Fully automated localization of the left ventricular blood pool in short axis cardiac cine MR images.

S-CNN: Subcategory-aware convolutional networks for object detection.

PubMed

Chen, Tao; Lu, Shijian; Fan, Jiayuan

2017-09-26

The marriage between the deep convolutional neural network (CNN) and region proposals has made breakthroughs for object detection in recent years. While the discriminative object features are learned via a deep CNN for classification, the large intra-class variation and deformation still limit the performance of the CNN based object detection. We propose a subcategory-aware CNN (S-CNN) to solve the object intra-class variation problem. In the proposed technique, the training samples are first grouped into multiple subcategories automatically through a novel instance sharing maximum margin clustering process. A multi-component Aggregated Channel Feature (ACF) detector is then trained to produce more latent training samples, where each ACF component corresponds to one clustered subcategory. The produced latent samples together with their subcategory labels are further fed into a CNN classifier to filter out false proposals for object detection. An iterative learning algorithm is designed for the joint optimization of image subcategorization, multi-component ACF detector, and subcategory-aware CNN classifier. Experiments on INRIA Person dataset, Pascal VOC 2007 dataset and MS COCO dataset show that the proposed technique clearly outperforms the state-of-the-art methods for generic object detection.

International trends in solid-state lighting : analyses of the article and patent literature.

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

Tsao, Jeffrey Yeenien; Huey, Mark C.; Boyack, Kevin W.

We present an analysis of the literature of solid-state lighting, based on a comprehensive dataset of 35,851 English-language articles and 12,420 U.S. patents published or issued during the years 1977-2004 in the foundational knowledge domain of electroluminescent materials and phenomena. The dataset was created using a complex, iteratively developed search string. The records in the dataset were then partitioned according to: whether they are articles or patents, their publication or issue date, their national or continental origin, whether the active electroluminescent material was inorganic or organic, and which of a number of emergent knowledge sub-domains they aggregate into on themore » basis of bibliographic coupling. From these partitionings, we performed a number of analyses, including: identification of knowledge sub-domains of historical and recent importance, and trends over time of the contributions of various nations and continents to the knowledge domain and its sub-domains. Among the key results: (1) The knowledge domain as a whole has been growing quickly: the average growth rates of the inorganic and organic knowledge sub-domains have been 8%/yr and 25%/yr, respectively, compared to average growth rates less than 5%/yr for English-language articles and U.S. patents in other knowledge domains. The growth rate of the organic knowledge sub-domain is so high that its historical dominance by the inorganic knowledge sub-domain will, at current trajectories, be reversed in the coming decade. (2) Amongst nations, the U.S. is the largest contributor to the overall knowledge domain, but Japan is on a trajectory to become the largest contributor within the coming half-decade. Amongst continents, Asia became the largest contributor during the past half-decade, overwhelmingly so for the organic knowledge sub-domain. (3) The relative contributions to the article and patent datasets differ for the major continents: North America contributing relatively more patents, Europe contributing relatively more articles, and Asia contributing in a more balanced fashion. (4) For the article dataset, the nations that contribute most in quantity also contribute most in breadth, while the nations that contribute less in quantity concentrate their contributions in particular knowledge sub-domains. For the patent dataset, North America and Europe tend to contribute improvements in end-use applications (e.g., in sensing, phototherapy and communications), while Asia tends to contribute improvements at the materials and chip levels. (5) The knowledge sub-domains that emerge from aggregations based on bibliographic coupling are roughly organized, for articles, by the degree of localization of electrons and holes in the material or phenomenon of interest, and for patents, according to both their emphasis on chips, systems or applications, and their emphasis on organic or inorganic materials. (6) The six 'hottest' topics in the article dataset are: spintronics, AlGaN UV LEDs, nanowires, nanophosphors, polyfluorenes and electrophosphorescence. The nine 'hottest' topics in the patent dataset are: OLED encapsulation, active-matrix displays, multicolor OLEDs, thermal transfer for OLED fabrication, ink-jet printed OLEDs, phosphor-converted LEDs, ornamental LED packages, photocuring and phototherapy, and LED retrofitting lamps. A significant caution in interpreting these results is that they are based on English-language articles and U.S. patents, and hence will tend to over-represent the strength of English-speaking nations (particularly the U.S.), and under-represent the strength of non-English-speaking nations (particularly China).« less

Thermal Structure and Dynamics of Saturn's Northern Springtime Disturbance

NASA Technical Reports Server (NTRS)

Fletcher, Leigh N.; Hesman, Brigette E.; Irwin, Patrick G.; Baines, Kevin H.; Momary, Thomas W.; SanchezLavega, Agustin; Flasar, F. Michael; Read, Peter L.; Orton, Glenn S.; SimonMiller, Amy;

Preliminary interpretation of high resolution 3D seismic data from offshore Mt. Etna, Italy

NASA Astrophysics Data System (ADS)

Gross, F.; Krastel, S.; Chiocci, F. L.; Ridente, D.; Cukur, D.; Bialas, J.; Papenberg, C. A.; Crutchley, G.; Koch, S.

2013-12-01

In order to gain knowledge about subsurface structures and its correlation to seafloor expressions, a hydro-acoustic dataset was collected during RV Meteor Cruise M86/2 (December 2011/January 2012) in Messina Straits and offshore Mt. Etna. Especially offshore Mt. Etna, the data reveals an obvious connection between subsurface structures and previously known morphological features at the sea floor. Therefore a high resolution 3D seismic dataset was acquired between Riposto Ridge and Catania Canyon close to the shore of eastern Sicily. The study area is characterized by a major structural high, which hosts several ridge-like features at the seafloor. These features are connected to a SW-NE trending fault system. The ridges are bended in their NE-SW direction and host major escarpments at the seafloor. Furthermore they are located directly next to a massive amphitheater structure offshore Mt. Etna with slope gradients of up to 35°, which is interpreted as remnants of a massive submarine mass wasting event off Sicily. The new 3D seismic dataset allows an in depth analysis of the ongoing deformation of the east flank of Mt. Etna.

Lithological properties of sedimentary environments in the shallow subsurface of the Northern Netherlands

NASA Astrophysics Data System (ADS)

Harting, Ronald; Bosch, Aleid; Gunnink, Jan

2014-05-01

Society has an increasing demand from the subsurface, which in the Dutch shallow subsurface (upper 30 to 40 meters) mainly focuses on natural aggregate resources, groundwater, infrastructure and dike safety. This stimulates the demand for knowledge about the composition and heterogeneity of the subsurface and its physical and chemical properties, including the uncertainties involved. Physical and chemical properties of sediments in the subsurface have been under investigation for decades; however, the usefulness of this data for applied research and the understanding of these properties is limited. This is due to several factors: studies consist mainly of separately collected datasets, targeted at a limited amount of parameters, focused on a small number of geological units, distributed unevenly with depth and usually collected from clustered drillings with limited spatial extent or are analysed with different techniques and methods, often on disturbed samples. These factors result in a heterogeneous and biased dataset not suitable to function as a reference dataset or to statistically determine regional characteristics of geological units. To overcome these shortcomings, the Geological Survey of the Netherlands is establishing a nation-wide reference dataset for physical and chemical properties. In 2006, a drilling campaign was started using cone penetration tests, cored drillings and geophysical well logs, choosing the sites for a good geographical distribution. The lithological properties of the undisturbed cores are visually described and interpreted for lithostratigraphy and inferred sedimentary environment based on lithofacies. The location of the samples in the cores are chosen based on this description and interpretation, resulting in an evenly distributed dataset of in situ samples with respect to geological units as well as an adequate number of samples suitable for statistical analysis. Analyses are uniformly performed for grain size distribution, permeability (both high and low permeable lithologies) and geochemical methods (X-Ray Fluorescence, Thermo-Gravimetric Analysis, Total Carbon, Total Sulphur and Total Organic Carbon). These analyses result in a large number of lithological, hydrological and geochemical parameters, i.e. clay content, sand median, vertical and horizontal permeability and CaCO3-content. We present the results from the analysis of lithological properties for the Northern Netherlands. Besides geology, these properties can be applied directly in studies concerning (amongst others) groundwater, natural aggregates and dike safety. We demonstrate the use of sedimentary environments based on lithofacies as a useful tool for comparison between lithostratigraphic units and lithofacies. These lithofacies match distinct parts of the marine, fluvial, glacial, eolian or organogenic environment, i.e. tidal channel sand, floodbasin clay and subglacial till. This results in lithological properties illustrating the heterogeneity within a geological unit and between equal depositional environments in different lithostratigraphic units. The acquired data have so far been used in several applied studies, i.e. improving parameterisation of 3D models leading to increased accuracy in groundwater models and dike safety studies concerning dike failure due to undermining. Recently, grain size distributions measured with different methods were recalibrated into a homogeneous dataset using this reference set, which greatly enlarged the dataset to be incorporated in the parameterisation of a 3D voxel model.

Does mycorrhizal inoculation benefit plant survival, plant development and small-scale soil fixation? Results from a perennial eco-engineering field experiment in the Swiss Alps.

NASA Astrophysics Data System (ADS)

Bast, Alexander; Grimm, Maria; Graf, Frank; Baumhauer, Roland; Gärtner, Holger

2015-04-01

In mountain environments superficial slope failures on coarse grained, vegetation-free slopes are common processes and entail a certain risk for humans and socio-economic structures. Eco-engineering measures can be applied to mitigate slope instabilities. In this regard, limited plant survival and growth can be supported by mycorrhizal inoculation, which was successfully tested in laboratory studies. However, related studies on a field scale are lacking. Furthermore, mycorrhizae are known to enhance soil aggregation, which is linked to soil physics such as shear strength, and hence it is a useful indicator for near-surface soil/slope stability. The overall objective of our contribution was to test whether mycorrhizal inoculation can be used to promote eco-engineering measures in steep alpine environments based on a five-year field experiment. We hypothesized that mycorrhizal inoculation (i) enhances soil aggregation, (ii) stimulate plant survival and fine root development, (iii) effects plant performance, (iv) the stimulated root development in turn influences aggregate stability, and (v) that climatic variations play a major role in fine-root development. We established mycorrhizal and non-mycorrhizal treated eco-engineered research plots (hedge layers mainly consisting of Alnus spp. and Salix spp.) on a field experimental scale. The experimental site is in the eastern Swiss Alps at an erosion-prone slope where many environmental conditions can be seen as homogeneous. Soil aggregation, fine root development and plant survival was quantified at the end of four growing seasons (2010, '11, '12, '14). Additionally, growth properties of Alnus spp. and Salix spp. were measured and their biomass estimated. Meteorological conditions, soil temperature and soil water content were recorded. (i) The introduced eco-engineering measures enhanced aggregate stability significantly. In contrast to published greenhouse and laboratory studies, mycorrhizal inoculation delayed soil aggregate stabilization relative to the non-inoculated site but resulted in a significantly higher aggregate stability compared to the control and the non-inoculated site at the end of the third growing season. (ii) Plant survival was significantly improved by the inoculation. Fine-root development was stimulated but not immediately. At the end of the third growing season, root length density tended to be higher and mean root diameter was significantly increased at the mycorrhizal treated site. (iii) Analyses on plant performance of Alnus and Salix demonstrated that the inoculated saplings achieved significantly higher survival rates. There was no treatment effect on plant growth properties except in 2010, where plant height and main stem diameter of Alnus was increased at the mycorrhizal treated site. The estimated total biomass of Alnus and Salix was higher at the mycorrhizal treated site. (iv) There was a positive correlation between root length density and aggregate stability, whereas roots < 0.5 mm were most influential on aggregate stability. (v) Interannual climatic variations seem to have a crucial influence on root development and, hence, on slope stability. There is a temporal offset of two growing seasons between inoculation effects tested in greenhouse/laboratory and the presented field experiment. However, the application of a commercial mycorrhizal inoculum in eco-engineering measures is a beneficial promoter to mitigate slope instability and surface erosion but needs to be tested at other sites. The contribution is mainly based on Bast (2014) and was funded by the Wolfermann Nägeli Stiftung Zürich and the Swiss Federal Office for Environment (BAFU No.: 09.0027.PJ/I211-3446). Bast, A. (2014): Mycorrhizal inoculation as a promoter for sustainable eco-engineering measures in steep alpine environments? Results of a three-year field experiment in the Arieschbach catchment, Fideris, eastern Swiss Alps. PhD Thesis. University of Berne: 149pp.

How much do different global GPP products agree in distribution and magnitude of GPP extremes?

NASA Astrophysics Data System (ADS)

Kim, S.; Ryu, Y.; Jiang, C.

2016-12-01

To evaluate uncertainty of global Gross Primary Productivity (GPP) extremes, we compare three global GPP datasets derived from different data processing methods (e.g. MPI-BGC: machine-learning, MODIS GPP (MOD17): semi-empirical, Breathing Earth System Simulator (BESS): process based). We preprocess the datasets following the method from Zscheischler et al., (2012) to detect GPP extremes which occur in less than 1% of the number of whole pixels, and to identify 3D-connected spatiotemporal GPP extremes. We firstly analyze global patterns and the magnitude of GPP extremes with MPI-BGC, MOD17, and BESS over 2001-2011. For consistent analysis in the three products, spatial and temporal resolution were set at 50 km and a monthly scale, respectively. Our results indicated that the global patterns of GPP extremes derived from MPI-BGC and BESS agreed with each other by showing hotspots in Northeastern Brazil and Eastern Texas. However, the extreme events detected from MOD17 were concentrated in tropical forests (e.g. Southeast Asia and South America). The amount of GPP reduction caused by climate extremes considerably differed across the products. For example, Russian heatwave in 2010 led to 100 Tg C uncertainty (198.7 Tg C in MPI-BGC, 305.6 Tg C in MOD17, and 237.8 Tg C in BESS). Moreover, the duration of extreme events differ among the three GPP datasets for the Russian heatwave (MPI-BGC: May-Sep, MOD17: Jun-Aug, and BESS: May-Aug). To test whether Sun induced Fluorescence (SiF), a proxy of GPP, can capture GPP extremes, we investigate global distribution of GPP extreme events in BESS, MOD17 and GOME-2 SiF between 2008 and 2014 when SiF data is available. We found that extreme GPP events in GOME-2 SiF and MOD17 appear in tropical forests whereas those in BESS emerged in Northeastern Brazil and Eastern Texas. The GPP extremes by severe 2011 US drought were detected by BESS and MODIS, but not by SiF. Our findings highlight that different GPP datasets could result in varying duration and intensity of GPP extremes and distribution of hotspots, and this study could contribute to quantifying uncertainties in GPP extremes.

Spatial patterns of the frog Oophaga pumilio in a plantation system are consistent with conspecific attraction.

PubMed

Folt, Brian; Donnelly, Maureen A; Guyer, Craig

2018-03-01

The conspecific attraction hypothesis predicts that individuals are attracted to conspecifics because conspecifics may be cues to quality habitat and/or colonists may benefit from living in aggregations. Poison frogs (Dendrobatidae) are aposematic, territorial, and visually oriented-three characteristics which make dendrobatids an appropriate model to test for conspecific attraction. In this study, we tested this hypothesis using an extensive mark-recapture dataset of the strawberry poison frog ( Oophaga pumilio ) from La Selva Biological Station, Costa Rica. Data were collected from replicate populations in a relatively homogenous Theobroma cacao plantation, which provided a unique opportunity to test how conspecifics influence the spatial ecology of migrants in a controlled habitat with homogenous structure. We predicted that (1) individuals entering a population would aggregate with resident adults, (2) migrants would share sites with residents at a greater frequency than expected by chance, and (3) migrant home ranges would have shorter nearest-neighbor distances (NND) to residents than expected by chance. The results were consistent with these three predictions: Relative to random simulations, we observed significant aggregation, home-range overlap, and NND distribution functions in four, five, and six, respectively, of the six migrant-resident groups analyzed. Conspecific attraction may benefit migrant O. pumilio by providing cues to suitable home sites and/or increasing the potential for social interactions with conspecifics; if true, these benefits should outweigh the negative effects of other factors associated with aggregation. The observed aggregation between migrant and resident O. pumilio is consistent with conspecific attraction in dendrobatid frogs, and our study provides rare support from a field setting that conspecific attraction may be a relevant mechanism for models of anuran spatial ecology.

Is the public sector of your country a diffusion borrower? Empirical evidence from Brazil

PubMed Central

Rocha, Leno S.; Rocha, Frederico S. A.; Souza, Thársis T. P.

2017-01-01

We propose a diffusion process to describe the global dynamic evolution of credit operations at a national level given observed operations at a subnational level in a sovereign country. Empirical analysis with a unique dataset from Brazilian federate constituents supports the conclusions. Despite the heterogeneity observed in credit operations at a subnational level, the aggregated dynamics at a national level were accurately described by the proposed model. Results may guide management of public finances, particularly debt manager authorities in charge of reaching surplus targets. PMID:28981532

A possible recovery of the near-surface wind speed in Eastern China during winter after 2000 and the potential causes

NASA Astrophysics Data System (ADS)

Zha, Jinlin; Wu, Jian; Zhao, Deming; Tang, Jianping

2018-04-01

A lasting decrease in the near-surface wind speed (SWS) in China has been revealed, but a following short-term strengthening in the SWS was rarely noted. In this paper, the daily mean SWS observed datasets from 328 measurement stations in Eastern China during the period 1981-2011 were used to investigate the facts and causes of the observed short-term strengthening in winter SWS in recent decades. The major results are summarized as follows: the SWS showed a significant decrease in the last 30 years, but a short-term strengthening in SWS was observed during the winter since 2000 in Eastern China. The SWS in Eastern China showed a significant decrease of - 0.11 m s-1 decade-1 from 1981 to 1999, followed by a weak increase of 0.0008 m s-1 decade-1 from 2000 to 2011. The short-term strengthening in the SWS since 2000 was mainly induced by the changes of the pressure-gradient force (PGF), which could be attributed to the changes of the sea-level pressure (SLP) in the region (51°-69.75° N, 51.75°-111.75° E). Furthermore, the changes of the PGF during the two periods of 1981-1999 and 2000-2011 were consistent with those of the SLP in the region (51°-69.75° N, 51.75°-111.75° E). The correlation coefficient between PGF and SLP was 0.32 and 0.66 during the period 1981-1999 and 2000-2011, respectively. Therefore, the effects of the changes in SLP over the region (51°-69.75° N, 51.75°-111.75° E) on changes of SWS in the Eastern China should be significant.

Reevaluation of a classic phylogeographic barrier: new techniques reveal the influence of microgeographic climate variation on population divergence

PubMed Central

Soto-Centeno, J Angel; Barrow, Lisa N; Allen, Julie M; Reed, David L

2013-01-01

We evaluated the mtDNA divergence and relationships within Geomys pinetis to assess the status of formerly recognized Geomys taxa. Additionally, we integrated new hypothesis-based tests in ecological niche models (ENM) to provide greater insight into causes for divergence and potential barriers to gene flow in Southeastern United States (Alabama, Florida, and Georgia). Our DNA sequence dataset confirmed and strongly supported two distinct lineages within G. pinetis occurring east and west of the ARD. Divergence date estimates showed that eastern and western lineages diverged about 1.37 Ma (1.9 Ma–830 ka). Predicted distributions from ENMs were consistent with molecular data and defined each population east and west of the ARD with little overlap. Niche identity and background similarity tests were statistically significant suggesting that ENMs from eastern and western lineages are not identical or more similar than expected based on random localities drawn from the environmental background. ENMs also support the hypothesis that the ARD represents a ribbon of unsuitable climate between more suitable areas where these populations are distributed. The estimated age of divergence between eastern and western lineages of G. pinetis suggests that the divergence was driven by climatic conditions during Pleistocene glacial–interglacial cycles. The ARD at the contact zone of eastern and western lineages of G. pinetis forms a significant barrier promoting microgeographic isolation that helps maintain ecological and genetic divergence. PMID:23789071

Evaluating the utility of detrital thermochronometric studies: detrital laser ablation (U-Th)/He dating and conventional bedrock zircon (U-Th)/He analyses from the eastern Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Horne, A.; Hodges, K. V.; Van Soest, M. C.

2016-12-01

Recent applications of the newly developed `laser ablation double dating' (LADD) technique, an integrated laser microprobe U/Pb and (U-Th)/He dating method, have showcased the potential utility of LADD for detrital thermochronologic studies. However, detrital thermochronologic techniques rely on confidence that detrital data adequately represent the full range of bedrock cooling ages within a catchment. To test this primary assumption, we compare (U-Th)/He zircon ages from age-elevation transects to LADD (U-Th)/He zircon ages from modern fluvial detritus collected at the range front in the eastern Sierra Nevada, California. Terminated by a normal fault escarpment, the small, steep catchments along the eastern side of the Sierra Nevada batholith are apropos locations for comparing the ability of detrital data to deduce the exhumation history of a source terrain with standard age-elevation transects. Additionally, the exhumation of the Sierra Nevada batholith is also intriguing, as past evaluations of the post-emplacement exhumation history of the range have yielded discrepant results. Thus far, analyses from the southern extent of the eastern Sierra Nevada show narrow ranges of cooling ages consistent with simple, relatively rapid exhumation. Ongoing analyses will expand the dataset such that we can fully compare bedrock and detrital age ranges as well as characterize the exhumation history of the range with a thermochronometer that has not been used to date the batholith.

Evidence of the Atlantic Multidecadal Oscillation driving multi-decadal variability of summertime surface air quality in the eastern United States: Implications for air quality management in the coming decades

NASA Astrophysics Data System (ADS)

Shen, L.; Mickley, L. J.

2016-12-01

Atlantic sea surface temperatures have a significant influence on the summertime meteorology and air quality in the eastern United States. In this study, we investigate the effect of the Atlantic Multidecadal Oscillation (AMO) on two key air pollutants, surface ozone and PM2.5, over the eastern United States. The shift of AMO from cold to warm phase increases surface air temperatures by 0.5 K across the East and reduces precipitation, resulting in a warmer and drier summer. By applying observed, present-day relationships between these pollutants and meteorological variables to a variety of observations and historical reanalysis datasets, we calculate the impacts of AMO on U.S. air quality. Our study reveals a multidecadal variability in mean summertime (JJA) maximum daily 8-hour (MDA8) ozone and surface PM2.5 concentrations in the eastern United States. In one-half cycle ( 30 years) of the AMO from negative to positive phase with constant anthropogenic emissions, JJA MDA8 ozone concentrations increase by 1-3 ppbv in the Northeast and 2-5 ppbv in the Great Plains; JJA PM2.5 concentrations increase by 0.8-1.2 μg m-3 in the Northeast and Southeast. The resulting impact on mortality rates is 4000 excess deaths per half cycle of AMO. We suggest that a complete picture of air quality management in coming decades requires consideration of the AMO influence.

Political regimes, political ideology, and self-rated health in Europe: a multilevel analysis.

PubMed

Huijts, Tim; Perkins, Jessica M; Subramanian, S V

2010-07-22

Studies on political ideology and health have found associations between individual ideology and health as well as between ecological measures of political ideology and health. Individual ideology and aggregate measures such as political regimes, however, were never examined simultaneously. Using adjusted logistic multilevel models to analyze data on individuals from 29 European countries and Israel, we found that individual ideology and political regime are independently associated with self-rated health. Individuals with rightwing ideologies report better health than leftwing individuals. Respondents from Eastern Europe and former Soviet republics report poorer health than individuals from social democratic, liberal, Christian conservative, and former Mediterranean dictatorship countries. In contrast to individual ideology and political regimes, country level aggregations of individual ideology are not related to reporting poor health. This study shows that although both individual political ideology and contextual political regime are independently associated with individuals' self-rated health, individual political ideology appears to be more strongly associated with self-rated health than political regime.

Political Regimes, Political Ideology, and Self-Rated Health in Europe: A Multilevel Analysis

PubMed Central

Huijts, Tim; Perkins, Jessica M.; Subramanian, S. V.

2010-01-01

Background Studies on political ideology and health have found associations between individual ideology and health as well as between ecological measures of political ideology and health. Individual ideology and aggregate measures such as political regimes, however, were never examined simultaneously. Methodology/Principal Findings Using adjusted logistic multilevel models to analyze data on individuals from 29 European countries and Israel, we found that individual ideology and political regime are independently associated with self-rated health. Individuals with rightwing ideologies report better health than leftwing individuals. Respondents from Eastern Europe and former Soviet republics report poorer health than individuals from social democratic, liberal, Christian conservative, and former Mediterranean dictatorship countries. In contrast to individual ideology and political regimes, country level aggregations of individual ideology are not related to reporting poor health. Conclusions/Significance This study shows that although both individual political ideology and contextual political regime are independently associated with individuals' self-rated health, individual political ideology appears to be more strongly associated with self-rated health than political regime. PMID:20661433

A World at Risk: Aggregating Development Trends to Forecast Global Habitat Conversion

PubMed Central

Oakleaf, James R.; Kennedy, Christina M.; Baruch-Mordo, Sharon; West, Paul C.; Gerber, James S.; Jarvis, Larissa; Kiesecker, Joseph

2015-01-01

A growing and more affluent human population is expected to increase the demand for resources and to accelerate habitat modification, but by how much and where remains unknown. Here we project and aggregate global spatial patterns of expected urban and agricultural expansion, conventional and unconventional oil and gas, coal, solar, wind, biofuels and mining development. Cumulatively, these threats place at risk 20% of the remaining global natural lands (19.68 million km2) and could result in half of the world’s biomes becoming >50% converted while doubling and tripling the extent of land converted in South America and Africa, respectively. Regionally, substantial shifts in land conversion could occur in Southern and Western South America, Central and Eastern Africa, and the Central Rocky Mountains of North America. With only 5% of the Earth’s at-risk natural lands under strict legal protection, estimating and proactively mitigating multi-sector development risk is critical for curtailing the further substantial loss of nature. PMID:26445282

A preindustrial to present record of SST from Darwin Island, Galápagos: constraining Eastern Pacific decadal variability

NASA Astrophysics Data System (ADS)

Jimenez, G.; Cole, J. E.; Vetter, L.; Thompson, D. M.; Tudhope, A. W.

2017-12-01

Climate reconstructions from sub-seasonally resolved corals have greatly enhanced our understanding of climate variability related to the El Niño-Southern Oscillation (ENSO). However, few such records exist from the Eastern Pacific, which experiences the greatest ENSO-related variance in sea surface temperature (SST). Therefore, climate patterns and mechanisms in the region remain unclear, particularly on decadal to multidecadal timescales. Here, we present a new, bimonthly-resolved δ18O-SST reconstruction from a Darwin Island coral, in the northern Galápagos archipelago. Comparison with Sr/Ca data from the same coral demonstrates that δ18O values in the core dominantly track SST, as is expected in areas with low-magnitude sea surface salinity changes such as the Galápagos. Spanning 2015 to approximately 1800 CE, our record thus represents the longest sub-seasonally resolved SST reconstruction bridging the pre-industrial era to the present day in the Eastern Pacific. This time span and resolution is ideal for identifying climatic processes on a range of timescales: the presence of modern data allows us to calibrate the record using satellite datasets, while several decades of data preceding the onset of greenhouse warming enables comparison between natural and anthropogenic climate forcings. Together with other reconstructions from the region, we use the record to establish a baseline of (ENSO-related) Eastern Pacific interannual and decadal variability and assess evidence for climate emergence and trends. Preliminary evidence suggests increased decadal variability during the latter half of the twentieth century, as well as a secular warming trend of approximately 0.1°C/decade, in agreement with other Eastern Pacific coral records. Finally, we explore the applications of coral δ13C values in reconstructing regional upwelling. Our record contributes to constraining the pre- to post-industrial climate history of the Eastern Pacific and provides insight into natural versus forced climate variability in the region.

Xenoliths in Eocene lavas from Central Tibet record carbonated metasomatism of the lithosphere

NASA Astrophysics Data System (ADS)

Goussin, Fanny; Cordier, Carole; Boulvais, Philippe; Guillot, Stéphane; Roperch, Pierrick; Replumaz, Anne

2017-04-01

Cenozoic post-collisional volcanism of the Tibetan Plateau, emplaced on an accreted continental margin under compression, could bring important information regarding the edification of the Plateau. In this study, we combined petrography, whole rock geochemistry, stable isotopes and in situ mineral analysis to decipher the genesis of Eocene-Oligocene magmatic rocks from the Nangqian basin (35-38 Ma, [Spurlin et al., 2005; Xu et al., 2016]), located at the hinge between Central Tibet and the Eastern Indo-Asia Collision Zone. Our dataset includes potassic trachyandesites; amphibole-bearing potassic trachytes; and rare ultrapotassic (K2O/Na2O ≥ 4) mafic syenites. All samples have high REE abundances (La = 100 - 500 x primitive mantle). Fractionation of heavy REE (Gd/YbN > 3) indicates melting in the garnet stability field, and relative depletion in high-field strength elements (Nb, Ta) indicates a selective enrichment of the source by metasomatic fluids. This metasomatism event is also evidenced by the occurrence of re-equilibrated mantle xenocrysts of phlogopite (Mg# = 88 - 90 and Cr2O3 content = 0.9 - 1.82 wt%) in mafic syenites. Potassic trachyandesites have specific composition, with negative Zr-Hf anomaly and low Hf/Sm (0.2 - 0.4). Indeed, they include xenocrystic aggregates, composed of magmatic clinopyroxene, apatite and subordinate biotite and feldspar, with interstitial calcite and dolomite. δ18OV -SMOW (9.2 - 11.0 ) and δ13CV -PDB (-6.1 - -4.0 ) of these rocks indicate the presence of primary, mantle-derived carbonates. In situ analysis of the major and trace element compositions of the carbonates, clinopyroxenes and apatites further suggest that these aggregates represent cumulates of a carbonate-bearing magma. These xenoliths thus show that the lithospheric mantle was also metasomatized by CO2-rich fluids. Cenozoic carbonatites in China have been identified in Maoniuping in Western Sichuan (31.7 Ma), Lixian in the Western Qinlin (22-23 Ma), and Nanjagbarwa in the Tethyan Himalayas (3.6-5.5 Ma) [Yang and Woolley, 2006]. Considering as such the Nangqian xenocrystic cumulates, Eocene carbonatites preferentially occurred on the three edges of the Songpan-Ganze block, and we propose that their mantellic sources were all affected by an input of subducted carbonates during the Triassic closure of the Songpan-Ganze ocean. Ages and local field relationships furthermore indicate that melting occurred during Eocene-Oligocene compressive events that propagated outward from the Songpan-Ganze block, suggesting renewed subduction of the block margins following the onset of the India-Asia collision. References: Spurlin, M. S., Yin, A., Horton, B. K., Zhou, J., & Wang, J. (2005). Structural evolution of the Yushu-Nangqian region and its relationship to syncollisional igneous activity, east-central Tibet. Geological Society of America Bulletin, 117(9-10), 1293-1317. Xu, Y., Bi, X. W., Hu, R. Z., Chen, Y. W., Liu, H. Q., & Xu, L. L. (2016). Geochronology and geochemistry of Eocene potassic felsic intrusions in the Nangqian basin, eastern Tibet: Tectonic and metallogenic implications. Lithos, 246, 212-227. Yang, Z., & Woolley, A. (2006). Carbonatites in China: a review. Journal of Asian Earth Sciences, 27(5), 559-575.

Distribution of diffuse flow megafauna in two sites on the Eastern Lau Spreading Center, Tonga

NASA Astrophysics Data System (ADS)

Podowski, Elizabeth L.; Moore, Tom S.; Zelnio, Kevin A.; Luther, George W., III; Fisher, Charles R.

2009-11-01

Hydrothermal vent environments are characterized by large gradients of toxic chemicals and high temperatures, which play a significant role in defining species' distributions. We used high-resolution imagery and spatially explicit in-situ physico-chemical measurements analyzed within a Geographic Information System (GIS) in order to characterize the spatial relations among different groups of megafauna, temperature, and chemistry within two discrete vent communities (40 and 50 m 2) on the Eastern Lau Spreading Center (ELSC). Chemical (sulfide and O 2 concentrations) and temperature data were obtained from approximately 75 different locations within each community using in-situ instruments. All data were integrated into a GIS, which served as a visualization tool and enabled the data to be analyzed in a spatial context. Our results confirm the importance of abiotic variables in defining the distributions of some fauna and elucidate several biological associations that are consistent between the two communities. The provannid snail, Alviniconcha spp., appears to actively avoid temperatures above 32-46 °C and/or sulfide concentrations exceeding approximately 260 μM. Slightly higher average sulfide concentrations and temperatures were measured among aggregations of Ifremeria nautilei compared to aggregations of the mussel Bathymodiolus brevior; however, the presence of mixed aggregations of the two species indicates an overlap in requirements. The brachyuran crab, Austinograea spp., was consistently observed directly on symbiont-containing species, particularly Alviniconcha spp. The solitary snail, Eosipho desbruyeresi, was rarely observed on biological substrata, but was often (60% of its population at the most active site) within 5 cm of symbiont-containing fauna, indicating a tolerance and preference for proximity to areas of high productivity. Densities and coverage of species differed substantially between the two communities despite high species overlap. Symbiont-containing species covered much larger areas at the more hydrothermally active site, ABE1, while shrimp and anemones occurred in relatively higher densities within the less-active site, TM1. This is the first study to thoroughly characterize realized distributions of megafauna at vent sites along the ELSC.

A computationally efficient Bayesian sequential simulation approach for the assimilation of vast and diverse hydrogeophysical datasets

NASA Astrophysics Data System (ADS)

Nussbaumer, Raphaël; Gloaguen, Erwan; Mariéthoz, Grégoire; Holliger, Klaus

2016-04-01

Bayesian sequential simulation (BSS) is a powerful geostatistical technique, which notably has shown significant potential for the assimilation of datasets that are diverse with regard to the spatial resolution and their relationship. However, these types of applications of BSS require a large number of realizations to adequately explore the solution space and to assess the corresponding uncertainties. Moreover, such simulations generally need to be performed on very fine grids in order to adequately exploit the technique's potential for characterizing heterogeneous environments. Correspondingly, the computational cost of BSS algorithms in their classical form is very high, which so far has limited an effective application of this method to large models and/or vast datasets. In this context, it is also important to note that the inherent assumption regarding the independence of the considered datasets is generally regarded as being too strong in the context of sequential simulation. To alleviate these problems, we have revisited the classical implementation of BSS and incorporated two key features to increase the computational efficiency. The first feature is a combined quadrant spiral - superblock search, which targets run-time savings on large grids and adds flexibility with regard to the selection of neighboring points using equal directional sampling and treating hard data and previously simulated points separately. The second feature is a constant path of simulation, which enhances the efficiency for multiple realizations. We have also modified the aggregation operator to be more flexible with regard to the assumption of independence of the considered datasets. This is achieved through log-linear pooling, which essentially allows for attributing weights to the various data components. Finally, a multi-grid simulating path was created to enforce large-scale variance and to allow for adapting parameters, such as, for example, the log-linear weights or the type of simulation path at various scales. The newly implemented search method for kriging reduces the computational cost from an exponential dependence with regard to the grid size in the original algorithm to a linear relationship, as each neighboring search becomes independent from the grid size. For the considered examples, our results show a sevenfold reduction in run time for each additional realization when a constant simulation path is used. The traditional criticism that constant path techniques introduce a bias to the simulations was explored and our findings do indeed reveal a minor reduction in the diversity of the simulations. This bias can, however, be largely eliminated by changing the path type at different scales through the use of the multi-grid approach. Finally, we show that adapting the aggregation weight at each scale considered in our multi-grid approach allows for reproducing both the variogram and histogram, and the spatial trend of the underlying data.

Project Roadkill: Linking European Hare vehicle collisions with landscape-structure using datasets from citizen scientists and professionals

NASA Astrophysics Data System (ADS)

Stretz, Carina; Heigl, Florian; Steiner, Wolfgang; Bauer, Thomas; Suppan, Franz; Zaller, Johann G.

2015-04-01

Road networks can implicate lots of negative effects for wildlife. One of the most important indication for strong landscape fragmentation are roadkills, i.e. collisions between motorised vehicles and wild animals. A species that is often involved in roadkills is the European hare (Lepus europaeus). European hare populations are in decline throughout Europe since the 1960s and classified as "potentially endangered" in the Red Data Book of Austria. Therefore, it is striking that in the hunting year 2013/14, 19,343 hares were killed on Austrian roads translating to 53 hare roadkills each day, or rather about two per hour. We hypothesized, that (I) hare-vehicle-collisions occur as an aggregation of events (hotspot), (II) the surrounding landscape influences the number of roadkilled hares and (III) roadkill data from citizen science projects and data from professionals (e.g. hunters, police) are convergent. Investigations on the surrounding landscape of the scenes of accidents will be carried out using land cover data derived from Landsat satellite images. Information on road kills are based on datasets from two different sources. One dataset stems from the citizen science project "Roadkill" (www.citizen-science.at/roadkill) where participants report roadkill findings via a web application. The second dataset is from a project where roadkill data were collected by the police and by hunters. Besides answering our research questions, findings of this project also allow the location of dangerous roadkill hotspots for animals and could be implemented in nature conservation actions.

Soil Bulk Density by Soil Type, Land Use and Data Source: Putting the Error in SOC Estimates

NASA Astrophysics Data System (ADS)

Wills, S. A.; Rossi, A.; Loecke, T.; Ramcharan, A. M.; Roecker, S.; Mishra, U.; Waltman, S.; Nave, L. E.; Williams, C. O.; Beaudette, D.; Libohova, Z.; Vasilas, L.

2017-12-01

An important part of SOC stock and pool assessment is the assessment, estimation, and application of bulk density estimates. The concept of bulk density is relatively simple (the mass of soil in a given volume), the specifics Bulk density can be difficult to measure in soils due to logistical and methodological constraints. While many estimates of SOC pools use legacy data in their estimates, few concerted efforts have been made to assess the process used to convert laboratory carbon concentration measurements and bulk density collection into volumetrically based SOC estimates. The methodologies used are particularly sensitive in wetlands and organic soils with high amounts of carbon and very low bulk densities. We will present an analysis across four database measurements: NCSS - the National Cooperative Soil Survey Characterization dataset, RaCA - the Rapid Carbon Assessment sample dataset, NWCA - the National Wetland Condition Assessment, and ISCN - the International soil Carbon Network. The relationship between bulk density and soil organic carbon will be evaluated by dataset and land use/land cover information. Prediction methods (both regression and machine learning) will be compared and contrasted across datasets and available input information. The assessment and application of bulk density, including modeling, aggregation and error propagation will be evaluated. Finally, recommendations will be made about both the use of new data in soil survey products (such as SSURGO) and the use of that information as legacy data in SOC pool estimates.

Recommended GIS Analysis Methods for Global Gridded Population Data

NASA Astrophysics Data System (ADS)

Frye, C. E.; Sorichetta, A.; Rose, A.

2017-12-01

When using geographic information systems (GIS) to analyze gridded, i.e., raster, population data, analysts need a detailed understanding of several factors that affect raster data processing, and thus, the accuracy of the results. Global raster data is most often provided in an unprojected state, usually in the WGS 1984 geographic coordinate system. Most GIS functions and tools evaluate data based on overlay relationships (area) or proximity (distance). Area and distance for global raster data can be either calculated directly using the various earth ellipsoids or after transforming the data to equal-area/equidistant projected coordinate systems to analyze all locations equally. However, unlike when projecting vector data, not all projected coordinate systems can support such analyses equally, and the process of transforming raster data from one coordinate space to another often results unmanaged loss of data through a process called resampling. Resampling determines which values to use in the result dataset given an imperfect locational match in the input dataset(s). Cell size or resolution, registration, resampling method, statistical type, and whether the raster represents continuous or discreet information potentially influence the quality of the result. Gridded population data represent estimates of population in each raster cell, and this presentation will provide guidelines for accurately transforming population rasters for analysis in GIS. Resampling impacts the display of high resolution global gridded population data, and we will discuss how to properly handle pyramid creation using the Aggregate tool with the sum option to create overviews for mosaic datasets.

Towards a quantitative, measurement-based estimate of the uncertainty in photon mass attenuation coefficients at radiation therapy energies

NASA Astrophysics Data System (ADS)

Ali, E. S. M.; Spencer, B.; McEwen, M. R.; Rogers, D. W. O.

2015-02-01

In this study, a quantitative estimate is derived for the uncertainty in the XCOM photon mass attenuation coefficients in the energy range of interest to external beam radiation therapy—i.e. 100 keV (orthovoltage) to 25 MeV—using direct comparisons of experimental data against Monte Carlo models and theoretical XCOM data. Two independent datasets are used. The first dataset is from our recent transmission measurements and the corresponding EGSnrc calculations (Ali et al 2012 Med. Phys. 39 5990-6003) for 10-30 MV photon beams from the research linac at the National Research Council Canada. The attenuators are graphite and lead, with a total of 140 data points and an experimental uncertainty of ˜0.5% (k = 1). An optimum energy-independent cross section scaling factor that minimizes the discrepancies between measurements and calculations is used to deduce cross section uncertainty. The second dataset is from the aggregate of cross section measurements in the literature for graphite and lead (49 experiments, 288 data points). The dataset is compared to the sum of the XCOM data plus the IAEA photonuclear data. Again, an optimum energy-independent cross section scaling factor is used to deduce the cross section uncertainty. Using the average result from the two datasets, the energy-independent cross section uncertainty estimate is 0.5% (68% confidence) and 0.7% (95% confidence). The potential for energy-dependent errors is discussed. Photon cross section uncertainty is shown to be smaller than the current qualitative ‘envelope of uncertainty’ of the order of 1-2%, as given by Hubbell (1999 Phys. Med. Biol 44 R1-22).

Status update: is smoke on your mind? Using social media to assess smoke exposure

NASA Astrophysics Data System (ADS)

Ford, Bonne; Burke, Moira; Lassman, William; Pfister, Gabriele; Pierce, Jeffrey R.

2017-06-01

Exposure to wildland fire smoke is associated with negative effects on human health. However, these effects are poorly quantified. Accurately attributing health endpoints to wildland fire smoke requires determining the locations, concentrations, and durations of smoke events. Most current methods for assessing these smoke events (ground-based measurements, satellite observations, and chemical transport modeling) are limited temporally, spatially, and/or by their level of accuracy. In this work, we explore using daily social media posts from Facebook regarding smoke, haze, and air quality to assess population-level exposure for the summer of 2015 in the western US. We compare this de-identified, aggregated Facebook dataset to several other datasets that are commonly used for estimating exposure, such as satellite observations (MODIS aerosol optical depth and Hazard Mapping System smoke plumes), daily (24 h) average surface particulate matter measurements, and model-simulated (WRF-Chem) surface concentrations. After adding population-weighted spatial smoothing to the Facebook data, this dataset is well correlated (R2 generally above 0.5) with the other methods in smoke-impacted regions. The Facebook dataset is better correlated with surface measurements of PM2. 5 at a majority of monitoring sites (163 of 293 sites) than the satellite observations and our model simulation. We also present an example case for Washington state in 2015, for which we combine this Facebook dataset with MODIS observations and WRF-Chem-simulated PM2. 5 in a regression model. We show that the addition of the Facebook data improves the regression model's ability to predict surface concentrations. This high correlation of the Facebook data with surface monitors and our Washington state example suggests that this social-media-based proxy can be used to estimate smoke exposure in locations without direct ground-based particulate matter measurements.

Mapping and Visualization of Storm-Surge Dynamics for Hurricane Katrina and Hurricane Rita

USGS Publications Warehouse

Gesch, Dean B.

2009-01-01

The damages caused by the storm surges from Hurricane Katrina and Hurricane Rita were significant and occurred over broad areas. Storm-surge maps are among the most useful geospatial datasets for hurricane recovery, impact assessments, and mitigation planning for future storms. Surveyed high-water marks were used to generate a maximum storm-surge surface for Hurricane Katrina extending from eastern Louisiana to Mobile Bay, Alabama. The interpolated surface was intersected with high-resolution lidar elevation data covering the study area to produce a highly detailed digital storm-surge inundation map. The storm-surge dataset and related data are available for display and query in a Web-based viewer application. A unique water-level dataset from a network of portable pressure sensors deployed in the days just prior to Hurricane Rita's landfall captured the hurricane's storm surge. The recorded sensor data provided water-level measurements with a very high temporal resolution at surveyed point locations. The resulting dataset was used to generate a time series of storm-surge surfaces that documents the surge dynamics in a new, spatially explicit way. The temporal information contained in the multiple storm-surge surfaces can be visualized in a number of ways to portray how the surge interacted with and was affected by land surface features. Spatially explicit storm-surge products can be useful for a variety of hurricane impact assessments, especially studies of wetland and land changes where knowledge of the extent and magnitude of storm-surge flooding is critical.

Relationships between palaeogeography and opal occurrence in Australia: A data-mining approach

NASA Astrophysics Data System (ADS)

Landgrebe, T. C. W.; Merdith, A.; Dutkiewicz, A.; Müller, R. D.

2013-07-01

Age-coded multi-layered geological datasets are becoming increasingly prevalent with the surge in open-access geodata, yet there are few methodologies for extracting geological information and knowledge from these data. We present a novel methodology, based on the open-source GPlates software in which age-coded digital palaeogeographic maps are used to “data-mine” spatio-temporal patterns related to the occurrence of Australian opal. Our aim is to test the concept that only a particular sequence of depositional/erosional environments may lead to conditions suitable for the formation of gem quality sedimentary opal. Time-varying geographic environment properties are extracted from a digital palaeogeographic dataset of the eastern Australian Great Artesian Basin (GAB) at 1036 opal localities. We obtain a total of 52 independent ordinal sequences sampling 19 time slices from the Early Cretaceous to the present-day. We find that 95% of the known opal deposits are tied to only 27 sequences all comprising fluvial and shallow marine depositional sequences followed by a prolonged phase of erosion. We then map the total area of the GAB that matches these 27 opal-specific sequences, resulting in an opal-prospective region of only about 10% of the total area of the basin. The key patterns underlying this association involve only a small number of key environmental transitions. We demonstrate that these key associations are generally absent at arbitrary locations in the basin. This new methodology allows for the simplification of a complex time-varying geological dataset into a single map view, enabling straightforward application for opal exploration and for future co-assessment with other datasets/geological criteria. This approach may help unravel the poorly understood opal formation process using an empirical spatio-temporal data-mining methodology and readily available datasets to aid hypothesis testing.

Mortality patterns and detection bias from carcass data: An example from wolf recovery in Wisconsin

USGS Publications Warehouse

Stenglein, Jennifer L.; Van Deelen, Timothy R.; Wydeven, Adrian P.; Mladenoff, David J.; Wiedenhoft, Jane E.; Businga, Nancy K.; Langenberg, Julia A.; Thomas, Nancy J.; Heisey, Dennis M.

2015-01-01

We developed models and provide computer code to make carcass recovery data more useful to wildlife managers. With these tools, wildlife managers can understand the spatial, temporal (e.g., across time periods, seasons), and demographic patterns in mortality causes from carcass recovery datasets. From datasets of radio-collared and non-collared carcasses, managers can calculate the detection bias by mortality cause in a non-collared carcass dataset compared to a collared carcass dataset. As a first step, we provide a standard procedure to assign mortality causes to carcasses. We provide an example of these methods for radio-collared wolves (n = 208) and non-collared wolves (n = 668) found dead in Wisconsin (1979–2012). We analyzed differences in mortality cause relative to season, age and sex classes, wolf harvest zones, and recovery phase (1979–1995: initial recovery, 1996–2002: early growth, 2003–2012: late growth). Seasonally, illegal kills and natural deaths were proportionally higher in winter (Oct–Mar) than summer (Apr–Sep) for collared wolves, whereas vehicle strikes and legal kills were higher in summer than winter. Spatially, more illegally killed collared wolves occurred in eastern wolf harvest zones where wolves reestablished more slowly and in the central forest region where optimal habitat is isolated by agriculture. Natural mortalities of collared wolves (e.g., disease, intraspecific strife, or starvation) were highest in western wolf harvest zones where wolves established earlier and existed at higher densities. Calculating detection bias in the non-collared dataset revealed that more than half of the non-collared carcasses on the landscape are not found. The lowest detection probabilities for non-collared carcasses (0.113–0.176) occurred in winter for natural, illegal, and unknown mortality causes.

Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs: Application to the North-Eastern Mediterranean

PubMed Central

Messina, Francesco; Finocchio, Andrea; Akar, Nejat; Loutradis, Aphrodite; Michalodimitrakis, Emmanuel I.; Brdicka, Radim; Jodice, Carla

2016-01-01

Human forensic STRs used for individual identification have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries crucial to the understanding of discontinuities at the European/Asian junction and the genetic legacy of ancient migrations, but seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long- to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. Several aspects of our results are confirmed on external STR datasets and replicate those of genome-wide SNP typings. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising from a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools. PMID:27898725

The influence of data characteristics on detecting wetland/stream surface-water connections in the Delmarva Peninsula, Maryland and Delaware

USGS Publications Warehouse

Vanderhoof, Melanie; Distler, Hayley; Lang, Megan W.; Alexander, Laurie C.

2018-01-01

The dependence of downstream waters on upstream ecosystems necessitates an improved understanding of watershed-scale hydrological interactions including connections between wetlands and streams. An evaluation of such connections is challenging when, (1) accurate and complete datasets of wetland and stream locations are often not available and (2) natural variability in surface-water extent influences the frequency and duration of wetland/stream connectivity. The Upper Choptank River watershed on the Delmarva Peninsula in eastern Maryland and Delaware is dominated by a high density of small, forested wetlands. In this analysis, wetland/stream surface water connections were quantified using multiple wetland and stream datasets, including headwater streams and depressions mapped from a lidar-derived digital elevation model. Surface-water extent was mapped across the watershed for spring 2015 using Landsat-8, Radarsat-2 and Worldview-3 imagery. The frequency of wetland/stream connections increased as a more complete and accurate stream dataset was used and surface-water extent was included, in particular when the spatial resolution of the imagery was finer (i.e., <10 m). Depending on the datasets used, 12–60% of wetlands by count (21–93% of wetlands by area) experienced surface-water interactions with streams during spring 2015. This translated into a range of 50–94% of the watershed contributing direct surface water runoff to streamflow. This finding suggests that our interpretation of the frequency and duration of wetland/stream connections will be influenced not only by the spatial and temporal characteristics of wetlands, streams and potential flowpaths, but also by the completeness, accuracy and resolution of input datasets.

Evaluating North American Electric Grid Reliability Using the Barabasi-Albert Network Model

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

Chassin, David P.; Posse, Christian

2005-09-15

The reliability of electric transmission systems is examined using a scale-free model of network topology and failure propagation. The topologies of the North American eastern and western electric grids are analyzed to estimate their reliability based on the Barabási-Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using other methods and they suggest that scale-free network models are usable to estimate aggregate electric grid reliability.

Evaluating North American Electric Grid Reliability Using the Barabasi-Albert Network Model

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

Chassin, David P.; Posse, Christian

2005-09-15

The reliability of electric transmission systems is examined using a scale-free model of network topology and failure propagation. The topologies of the North American eastern and western electric grids are analyzed to estimate their reliability based on the Barabasi-Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using standard power engineering methods, and they suggest that scale-free network models are usable to estimate aggregate electric grid reliability.

Combining individual participant and aggregated data in a meta-analysis with correlational studies.

PubMed

Pigott, Terri; Williams, Ryan; Polanin, Joshua

2012-12-01

This paper presents methods for combining individual participant data (IPD) with aggregated study level data (AD) in a meta-analysis of correlational studies. Although medical researchers have employed IPD in a wide range of studies, only a single example exists in the social sciences. New policies at the National Science Foundation requiring grantees to submit data archiving plans may increase social scientists' access to individual level data that could be combined with traditional meta-analysis. The methods presented here extend prior work on IPD to meta-analyses using correlational studies. The examples presented illustrate the synthesis of publicly available national datasets in education with aggregated study data from a meta-analysis examining the correlation of socioeconomic status measures and academic achievement. The major benefit of the inclusion of the individual level is that both within-study and between-study interactions among moderators of effect size can be estimated. Given the potential growth in data archives in the social sciences, we should see a corresponding increase in the ability to synthesize IPD and AD in a single meta-analysis, leading to a more complete understanding of how within-study and between-study moderators relate to effect size. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Advancing global marine biogeography research with open-source GIS software and cloud-computing

USGS Publications Warehouse

Fujioka, Ei; Vanden Berghe, Edward; Donnelly, Ben; Castillo, Julio; Cleary, Jesse; Holmes, Chris; McKnight, Sean; Halpin, patrick

2012-01-01

Across many scientific domains, the ability to aggregate disparate datasets enables more meaningful global analyses. Within marine biology, the Census of Marine Life served as the catalyst for such a global data aggregation effort. Under the Census framework, the Ocean Biogeographic Information System was established to coordinate an unprecedented aggregation of global marine biogeography data. The OBIS data system now contains 31.3 million observations, freely accessible through a geospatial portal. The challenges of storing, querying, disseminating, and mapping a global data collection of this complexity and magnitude are significant. In the face of declining performance and expanding feature requests, a redevelopment of the OBIS data system was undertaken. Following an Open Source philosophy, the OBIS technology stack was rebuilt using PostgreSQL, PostGIS, GeoServer and OpenLayers. This approach has markedly improved the performance and online user experience while maintaining a standards-compliant and interoperable framework. Due to the distributed nature of the project and increasing needs for storage, scalability and deployment flexibility, the entire hardware and software stack was built on a Cloud Computing environment. The flexibility of the platform, combined with the power of the application stack, enabled rapid re-development of the OBIS infrastructure, and ensured complete standards-compliance.

CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets

PubMed Central

Nowicka, Malgorzata; Krieg, Carsten; Weber, Lukas M.; Hartmann, Felix J.; Guglietta, Silvia; Becher, Burkhard; Levesque, Mitchell P.; Robinson, Mark D.

2017-01-01

High dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high throughput interrogation and characterization of cell populations.Here, we present an R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signaling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g. multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g. plots of aggregated signals). PMID:28663787

Noesis: Ontology based Scoped Search Engine and Resource Aggregator for Atmospheric Science

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Movva, S.; Li, X.; Cherukuri, P.; Graves, S.

2006-12-01

The goal for search engines is to return results that are both accurate and complete. The search engines should find only what you really want and find everything you really want. Search engines (even meta search engines) lack semantics. The basis for search is simply based on string matching between the user's query term and the resource database and the semantics associated with the search string is not captured. For example, if an atmospheric scientist is searching for "pressure" related web resources, most search engines return inaccurate results such as web resources related to blood pressure. In this presentation Noesis, which is a meta-search engine and a resource aggregator that uses domain ontologies to provide scoped search capabilities will be described. Noesis uses domain ontologies to help the user scope the search query to ensure that the search results are both accurate and complete. The domain ontologies guide the user to refine their search query and thereby reduce the user's burden of experimenting with different search strings. Semantics are captured by refining the query terms to cover synonyms, specializations, generalizations and related concepts. Noesis also serves as a resource aggregator. It categorizes the search results from different online resources such as education materials, publications, datasets, web search engines that might be of interest to the user.

Integrating ethnobiological knowledge into biodiversity conservation in the Eastern Himalayas.

PubMed

O'Neill, Alexander R; Badola, Hemant K; Dhyani, Pitamber P; Rana, Santosh K

2017-03-29

Biocultural knowledge provides valuable insight into ecological processes, and can guide conservation practitioners in local contexts. In many regions, however, such knowledge is underutilized due to its often-fragmented record in disparate sources. In this article, we review and apply ethnobiological knowledge to biodiversity conservation in the Eastern Himalayas. Using Sikkim, India as a case study, we: (i) traced the history and trends of ethnobiological documentation; (ii) identified priority species and habitat types; and, (iii) analyzed within and among community differences pertaining to species use and management. Our results revealed that Sikkim is a biocultural hotspot, where six ethnic communities and 1128 species engage in biocultural relationships. Since the mid-1800s, the number of ethnobiological publications from Sikkim has exponentially increased; however, our results also indicate that much of this knowledge is both unwritten and partitioned within an aging, gendered, and caste or ethnic group-specific stratum of society. Reviewed species were primarily wild or wild cultivated, native to subtropical and temperate forests, and pend IUCN Red List of Threatened Species assessment. Our results demonstrate the value of engaging local knowledge holders as active participants in conservation, and suggest the need for further ethnobiological research in the Eastern Himalayas. Our interdisciplinary approach, which included rank indices and geospatial modelling, can help integrate diverse datasets into evidence-based policy.

Reconstructing Asian faunal introductions to eastern Africa from multi-proxy biomolecular and archaeological datasets

PubMed Central

Buckley, Michael; Crowther, Alison; Frantz, Laurent; Eager, Heidi; Lebrasseur, Ophélie; Hutterer, Rainer; Hulme-Beaman, Ardern; Van Neer, Wim; Douka, Katerina; Veall, Margaret-Ashley; Quintana Morales, Eriéndira M.; Schuenemann, Verena J.; Reiter, Ella; Allen, Richard; Dimopoulos, Evangelos A.; Helm, Richard M.; Shipton, Ceri; Mwebi, Ogeto; Denys, Christiane; Horton, Mark; Wynne-Jones, Stephanie; Fleisher, Jeffrey; Radimilahy, Chantal; Wright, Henry; Searle, Jeremy B.; Krause, Johannes; Larson, Greger; Boivin, Nicole L.

2017-01-01

Human-mediated biological exchange has had global social and ecological impacts. In sub-Saharan Africa, several domestic and commensal animals were introduced from Asia in the pre-modern period; however, the timing and nature of these introductions remain contentious. One model supports introduction to the eastern African coast after the mid-first millennium CE, while another posits introduction dating back to 3000 BCE. These distinct scenarios have implications for understanding the emergence of long-distance maritime connectivity, and the ecological and economic impacts of introduced species. Resolution of this longstanding debate requires new efforts, given the lack of well-dated fauna from high-precision excavations, and ambiguous osteomorphological identifications. We analysed faunal remains from 22 eastern African sites spanning a wide geographic and chronological range, and applied biomolecular techniques to confirm identifications of two Asian taxa: domestic chicken (Gallus gallus) and black rat (Rattus rattus). Our approach included ancient DNA (aDNA) analysis aided by BLAST-based bioinformatics, Zooarchaeology by Mass Spectrometry (ZooMS) collagen fingerprinting, and direct AMS (accelerator mass spectrometry) radiocarbon dating. Our results support a late, mid-first millennium CE introduction of these species. We discuss the implications of our findings for models of biological exchange, and emphasize the applicability of our approach to tropical areas with poor bone preservation. PMID:28817590

Distribution and Abundance of Hopanoid Producers in Low-Oxygen Environments of the Eastern Pacific Ocean.

PubMed

Kharbush, Jenan J; Kejriwal, Kanchi; Aluwihare, Lihini I

2016-02-01

Hopanoids are bacterial membrane lipid biomarker molecules that feature prominently in the molecular fossil record. In the modern marine water column, recent reports implicate bacteria inhabiting low-oxygen environments as important sources of hopanoids to marine sediments. However, the preliminary biogeography reported by recent studies and the environmental conditions governing such distributions can only be confirmed when the numerical abundance of these organisms is known with more certainty. In this study, we employ two different approaches to examine the quantitative significance of phylogenetically distinct hopanoid producers in low-oxygen environments. First, we develop a novel quantitative PCR (qPCR) assay for the squalene hopene cyclase (sqhC) gene, targeting a subset of hopanoid producers previously identified to be important in the eastern North Pacific Ocean. The results represent the first quantitative gene abundance data of any kind for hopanoid producers in the marine water column and show that these putative alphaproteobacterial hopanoid producers are rare, comprising at most 0.2 % of the total bacterial community in our samples. Second, a complementary analysis of existing low-oxygen metagenomic datasets further examined the generality of the qPCR observation. We find that the dominant sqhC sequences in these metagenomic datasets are associated with phyla such as Nitrospinae rather than Proteobacteria, consistent with the qPCR finding that alphaproteobacterial hopanoid producers are not very abundant in low-oxygen environments. In fact, positive correlations between sqhC gene abundance and environmental parameters in these samples identify nitrite availability as a potentially important factor in the ecology of hopanoid producers that dominate low-oxygen environments.

Unequal views of inequality: Cross-national support for redistribution 1985-2011.

PubMed

VanHeuvelen, Tom

2017-05-01

This research examines public views on government responsibility to reduce income inequality, support for redistribution. While individual-level correlates of support for redistribution are relatively well understood, many questions remain at the country-level. Therefore, I examine how country-level characteristics affect aggregate support for redistribution. I test explanations of aggregate support using a unique dataset combining 18 waves of the International Social Survey Programme and European Social Survey. Results from mixed-effects logistic regression and fixed-effects linear regression models show two primary and contrasting effects. States that reduce inequality through bundles of tax and transfer policies are rewarded with more supportive publics. In contrast, economic development has a seemingly equivalent and dampening effect on public support. Importantly, the effect of economic development grows at higher levels of development, potentially overwhelming the amplifying effect of state redistribution. My results therefore suggest a fundamental challenge to proponents of egalitarian politics. Copyright © 2016 Elsevier Inc. All rights reserved.

An IDS Alerts Aggregation Algorithm Based on Rough Set Theory

NASA Astrophysics Data System (ADS)

Zhang, Ru; Guo, Tao; Liu, Jianyi

2018-03-01

Within a system in which has been deployed several IDS, a great number of alerts can be triggered by a single security event, making real alerts harder to be found. To deal with redundant alerts, we propose a scheme based on rough set theory. In combination with basic concepts in rough set theory, the importance of attributes in alerts was calculated firstly. With the result of attributes importance, we could compute the similarity of two alerts, which will be compared with a pre-defined threshold to determine whether these two alerts can be aggregated or not. Also, time interval should be taken into consideration. Allowed time interval for different types of alerts is computed individually, since different types of alerts may have different time gap between two alerts. In the end of this paper, we apply proposed scheme on DAPRA98 dataset and the results of experiment show that our scheme can efficiently reduce the redundancy of alerts so that administrators of security system could avoid wasting time on useless alerts.

Buckets: Aggregative, Intelligent Agents for Publishing

NASA Technical Reports Server (NTRS)

Nelson, Michael L.; Maly, Kurt; Shen, Stewart N. T.; Zubair, Mohammad

1998-01-01

Buckets are an aggregative, intelligent construct for publishing in digital libraries. The goal of research projects is to produce information. This information is often instantiated in several forms, differentiated by semantic types (report, software, video, datasets, etc.). A given semantic type can be further differentiated by syntactic representations as well (PostScript version, PDF version, Word version, etc.). Although the information was created together and subtle relationships can exist between them, different semantic instantiations are generally segregated along currently obsolete media boundaries. Reports are placed in report archives, software might go into a software archive, but most of the data and supporting materials are likely to be kept in informal personal archives or discarded altogether. Buckets provide an archive-independent container construct in which all related semantic and syntactic data types and objects can be logically grouped together, archived, and manipulated as a single object. Furthermore, buckets are active archival objects and can communicate with each other, people, or arbitrary network services.

Social Media Visual Analytics for Events

NASA Astrophysics Data System (ADS)

Diakopoulos, Nicholas; Naaman, Mor; Yazdani, Tayebeh; Kivran-Swaine, Funda

For large-scale multimedia events such as televised debates and speeches, the amount of content on social media channels such as Facebook or Twitter can easily become overwhelming, yet still contain information that may aid and augment understanding of the multimedia content via individual social media items, or aggregate information from the crowd's response. In this work we discuss this opportunity in the context of a social media visual analytic tool, Vox Civitas, designed to help journalists, media professionals, or other researchers make sense of large-scale aggregations of social media content around multimedia broadcast events. We discuss the design of the tool, present and evaluate the text analysis techniques used to enable the presentation, and detail the visual and interaction design. We provide an exploratory evaluation based on a user study in which journalists interacted with the system to analyze and report on a dataset of over one 100 000 Twitter messages collected during the broadcast of the U.S. State of the Union presidential address in 2010.

Comparison of Four Precipitation Forcing Datasets in Land Information System Simulations over the Continental U.S.

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Kuligowski, Robert J.; Langston, Carrie

2013-01-01

The NASA Short ]term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real ]time configuration of the NASA Land Information System (LIS) with the Noah land surface model (LSM). Output from the SPoRT ]LIS run is used to initialize land surface variables for local modeling applications at select National Weather Service (NWS) partner offices, and can be displayed in decision support systems for situational awareness and drought monitoring. The SPoRT ]LIS is run over a domain covering the southern and eastern United States, fully nested within the National Centers for Environmental Prediction Stage IV precipitation analysis grid, which provides precipitation forcing to the offline LIS ]Noah runs. The SPoRT Center seeks to expand the real ]time LIS domain to the entire Continental U.S. (CONUS); however, geographical limitations with the Stage IV analysis product have inhibited this expansion. Therefore, a goal of this study is to test alternative precipitation forcing datasets that can enable the LIS expansion by improving upon the current geographical limitations of the Stage IV product. The four precipitation forcing datasets that are inter ]compared on a 4 ]km resolution CONUS domain include the Stage IV, an experimental GOES quantitative precipitation estimate (QPE) from NESDIS/STAR, the National Mosaic and QPE (NMQ) product from the National Severe Storms Laboratory, and the North American Land Data Assimilation System phase 2 (NLDAS ]2) analyses. The NLDAS ]2 dataset is used as the control run, with each of the other three datasets considered experimental runs compared against the control. The regional strengths, weaknesses, and biases of each precipitation analysis are identified relative to the NLDAS ]2 control in terms of accumulated precipitation pattern and amount, and the impacts on the subsequent LSM spin ]up simulations. The ultimate goal is to identify an alternative precipitation forcing dataset that can best support an expansion of the real ]time SPoRT ]LIS to a domain covering the entire CONUS.

Vp and Vs seismic velocity models of the Sicilian-Tyrrhenian region using local earthquake data. Assessment tests to obtain reliable velocity models

NASA Astrophysics Data System (ADS)

Parisi, L.; Calo, M.; Luzio, D.; Sulli, A.

2011-12-01

In this work we present Vp and Vs velocity models of the crust and uppermost mantle beneath the Sicilian-Tyrrhenian region (Southern Italy). We applied the double-difference tomography of Zhang and Thurber (2003) further optimized by the post-processing Weighted Average Model method (Calò et al., 2009; Calò, 2009). The tomographic method was applied to three datasets. The first dataset contains 31270 P- and 13588 S- absolute data and 73022 P- and 27893 S- differential times regarding earthquakes occurred from 1981 to 2005 and recorded by 192 stations. The second dataset is composed by 27668 P- and 11183 S- absolute data and 63296 P- and 29683 S- differential times of earthquakes occurred between January 2006 and December 2009 and recorded by 140 stations. The third dataset results as a merging of the two datasets above described. After an assessment of the results obtained after the inversion of the three datasets, we constructed the final Vp and Vs models as syntheses of all results using the WAM method. Checkerboard tests indicate that horizontal resolution allow to recovery velocity structures 20 km wide in the southern Tyrrhenian Sea and north-eastern Sicily area whereas anomalies of from 40 to 70 km are restored in the southern part of Sicily, Ionian Sea and Sicily Channel. Vertical resolution is 3 km in the shallower parts of the models (down to about 20 km) and 8 -10 km in the deeper ones (down to 50 km). Furthermore, a Vp- Vs correlation analysis was performed in order to assess the minimum threshold of DWS (Toomey and Foulger, 1986) that ensures a sufficient reliability of the seismic velocity distributions. These preliminary results show highly resolved Vp and Vs models and provide new constrains on the lithospheric structures of the study area.

Transitioning Enhanced Land Surface Initialization and Model Verification Capabilities to the Kenya Meteorological Department (KMD)

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Mungai, John; Sakwa, Vincent; Zavodsky, Bradley T.; Srikishen, Jayanthi; Limaye, Ashutosh; Blankenship, Clay B.

2016-01-01

Flooding, severe weather, and drought are key forecasting challenges for the Kenya Meteorological Department (KMD), based in Nairobi, Kenya. Atmospheric processes leading to convection, excessive precipitation and/or prolonged drought can be strongly influenced by land cover, vegetation, and soil moisture content, especially during anomalous conditions and dry/wet seasonal transitions. It is thus important to represent accurately land surface state variables (green vegetation fraction, soil moisture, and soil temperature) in Numerical Weather Prediction (NWP) models. The NASA SERVIR and the Short-term Prediction Research and Transition (SPoRT) programs in Huntsville, AL have established a working partnership with KMD to enhance its regional modeling capabilities. SPoRT and SERVIR are providing experimental land surface initialization datasets and model verification capabilities for capacity building at KMD. To support its forecasting operations, KMD is running experimental configurations of the Weather Research and Forecasting (WRF; Skamarock et al. 2008) model on a 12-km/4-km nested regional domain over eastern Africa, incorporating the land surface datasets provided by NASA SPoRT and SERVIR. SPoRT, SERVIR, and KMD participated in two training sessions in March 2014 and June 2015 to foster the collaboration and use of unique land surface datasets and model verification capabilities. Enhanced regional modeling capabilities have the potential to improve guidance in support of daily operations and high-impact weather and climate outlooks over Eastern Africa. For enhanced land-surface initialization, the NASA Land Information System (LIS) is run over Eastern Africa at 3-km resolution, providing real-time land surface initialization data in place of interpolated global model soil moisture and temperature data available at coarser resolutions. Additionally, real-time green vegetation fraction (GVF) composites from the Suomi-NPP VIIRS instrument is being incorporated into the KMD-WRF runs, using the product generated by NOAA/NESDIS. Model verification capabilities are also being transitioned to KMD using NCAR's Model *Corresponding author address: Jonathan Case, ENSCO, Inc., 320 Sparkman Dr., Room 3008, Huntsville, AL, 35805. Email: Jonathan.Case-1@nasa.gov Evaluation Tools (MET; Brown et al. 2009) software in conjunction with a SPoRT-developed scripting package, in order to quantify and compare errors in simulated temperature, moisture and precipitation in the experimental WRF model simulations. This extended abstract and accompanying presentation summarizes the efforts and training done to date to support this unique regional modeling initiative at KMD. To honor the memory of Dr. Peter J. Lamb and his extensive efforts in bolstering weather and climate science and capacity-building in Africa, we offer this contribution to the special Peter J. Lamb symposium. The remainder of this extended abstract is organized as follows. The collaborating international organizations involved in the project are presented in Section 2. Background information on the unique land surface input datasets is presented in Section 3. The hands-on training sessions from March 2014 and June 2015 are described in Section 4. Sample experimental WRF output and verification from the June 2015 training are given in Section 5. A summary is given in Section 6, followed by Acknowledgements and References.

Water Masses in the Eastern Mediterranean Sea: An Analysis of Measured Isotopic Oxygen

NASA Astrophysics Data System (ADS)

de Ruggiero, Paola; Zanchettin, Davide; Bensi, Manuel; Hainbucher, Dagmar; Stenni, Barbara; Pierini, Stefano; Rubino, Angelo

2018-04-01

We investigate aspects of the water mass structure of the Adriatic and Ionian basins (Eastern Mediterranean Sea) and their interdecadal variability through statistical analyses focused on δ18Ο measurements carried out in 1985, 1990, and 2011. In particular, the more recent δ18Ο measurements extend throughout the entire water column and constitute, to the best of our knowledge, the largest synoptic dataset encompassing different sub-basins of the Mediterranean Sea. We study the statistical linkages between temperature, salinity, dissolved oxygen and δ18Ο. We find that δ18Ο is largely independent from the other parameters, and it can be used to trace major water masses that are typically found in the basins, including the Adriatic Dense Water, the Levantine Intermediate Water, and the Cretan Intermediate and Dense Waters. Finally, we explore the possibility of using δ18Ο concentration as a proxy for dominant modes of large-scale oceanic variability in the Mediterranean Sea.

Characterization of PTO and Idle Behavior for Utility Vehicles

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

Duran, Adam W.; Konan, Arnaud M.; Miller, Eric S.

This report presents the results of analyses performed on utility vehicle data composed primarily of aerial lift bucket trucks sampled from the National Renewable Energy Laboratory's Fleet DNA database to characterize power takeoff (PTO) and idle operating behavior for utility trucks. Two major data sources were examined in this study: a 75-vehicle sample of Odyne electric PTO (ePTO)-equipped vehicles drawn from multiple fleets spread across the United States and 10 conventional PTO-equipped Pacific Gas and Electric fleet vehicles operating in California. Novel data mining approaches were developed to identify PTO and idle operating states for each of the datasets usingmore » telematics and controller area network/onboard diagnostics data channels. These methods were applied to the individual datasets and aggregated to develop utilization curves and distributions describing PTO and idle behavior in both absolute and relative operating terms. This report also includes background information on the source vehicles, development of the analysis methodology, and conclusions regarding the study's findings.« less

BagMOOV: A novel ensemble for heart disease prediction bootstrap aggregation with multi-objective optimized voting.

PubMed

Bashir, Saba; Qamar, Usman; Khan, Farhan Hassan

2015-06-01

Conventional clinical decision support systems are based on individual classifiers or simple combination of these classifiers which tend to show moderate performance. This research paper presents a novel classifier ensemble framework based on enhanced bagging approach with multi-objective weighted voting scheme for prediction and analysis of heart disease. The proposed model overcomes the limitations of conventional performance by utilizing an ensemble of five heterogeneous classifiers: Naïve Bayes, linear regression, quadratic discriminant analysis, instance based learner and support vector machines. Five different datasets are used for experimentation, evaluation and validation. The datasets are obtained from publicly available data repositories. Effectiveness of the proposed ensemble is investigated by comparison of results with several classifiers. Prediction results of the proposed ensemble model are assessed by ten fold cross validation and ANOVA statistics. The experimental evaluation shows that the proposed framework deals with all type of attributes and achieved high diagnosis accuracy of 84.16 %, 93.29 % sensitivity, 96.70 % specificity, and 82.15 % f-measure. The f-ratio higher than f-critical and p value less than 0.05 for 95 % confidence interval indicate that the results are extremely statistically significant for most of the datasets.

Simulation and spatiotemporal pattern of air temperature and precipitation in Eastern Central Asia using RegCM.

PubMed

Meng, Xianyong; Long, Aihua; Wu, Yiping; Yin, Gang; Wang, Hao; Ji, Xiaonan

2018-02-26

Central Asia is a region that has a large land mass, yet meteorological stations in this area are relatively scarce. To address this data issues, in this study, we selected two reanalysis datasets (the ERA40 and NCEP/NCAR) and downscaled them to 40 × 40 km using RegCM. Then three gridded datasets (the CRU, APHRO, and WM) that were extrapolated from the observations of Central Asian meteorological stations to evaluate the performance of RegCM and analyze the spatiotemporal distribution of precipitation and air temperature. We found that since the 1960s, the air temperature in Xinjiang shows an increasing trend and the distribution of precipitation in the Tianshan area is quite complex. The precipitation is increasing in the south of the Tianshan Mountains (Southern Xinjiang, SX) and decreasing in the mountainous areas. The CRU and WM data indicate that precipitation in the north of the Tianshan Mountains (Northern Xinjiang, NX) is increasing, while the APHRO data show an opposite trend. The downscaled results from RegCM are generally consistent with the extrapolated gridded datasets in terms of the spatiotemporal patterns. We believe that our results can provide useful information in developing a regional climate model in Central Asia where meteorological stations are scarce.

A comparison of spatial interpolation methods for soil temperature over a complex topographical region

NASA Astrophysics Data System (ADS)

Wu, Wei; Tang, Xiao-Ping; Ma, Xue-Qing; Liu, Hong-Bin

2016-08-01

Soil temperature variability data provide valuable information on understanding land-surface ecosystem processes and climate change. This study developed and analyzed a spatial dataset of monthly mean soil temperature at a depth of 10 cm over a complex topographical region in southwestern China. The records were measured at 83 stations during the period of 1961-2000. Nine approaches were compared for interpolating soil temperature. The accuracy indicators were root mean square error (RMSE), modelling efficiency (ME), and coefficient of residual mass (CRM). The results indicated that thin plate spline with latitude, longitude, and elevation gave the best performance with RMSE varying between 0.425 and 0.592 °C, ME between 0.895 and 0.947, and CRM between -0.007 and 0.001. A spatial database was developed based on the best model. The dataset showed that larger seasonal changes of soil temperature were from autumn to winter over the region. The northern and eastern areas with hilly and low-middle mountains experienced larger seasonal changes.

A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: using point and gridded FLUXNET and water balance ET

USGS Publications Warehouse

Velpuri, Naga M.; Senay, Gabriel B.; Singh, Ramesh K.; Bohms, Stefanie; Verdin, James P.

2013-01-01

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. Extensive evaluation of such large scale estimates is necessary before they can be used in various applications. In this study, two monthly MODIS 1 km ET products, MODIS global ET (MOD16) and Operational Simplified Surface Energy Balance (SSEBop) ET, are validated over the conterminous United States at both point and basin scales. Point scale validation was performed using eddy covariance FLUXNET ET (FLET) data (2001–2007) aggregated by year, land cover, elevation and climate zone. Basin scale validation was performed using annual gridded FLUXNET ET (GFET) and annual basin water balance ET (WBET) data aggregated by various hydrologic unit code (HUC) levels. Point scale validation using monthly data aggregated by years revealed that the MOD16 ET and SSEBop ET products showed overall comparable annual accuracies. For most land cover types, both ET products showed comparable results. However, SSEBop showed higher performance for Grassland and Forest classes; MOD16 showed improved performance in the Woody Savanna class. Accuracy of both the ET products was also found to be comparable over different climate zones. However, SSEBop data showed higher skill score across the climate zones covering the western United States. Validation results at different HUC levels over 2000–2011 using GFET as a reference indicate higher accuracies for MOD16 ET data. MOD16, SSEBop and GFET data were validated against WBET (2000–2009), and results indicate that both MOD16 and SSEBop ET matched the accuracies of the global GFET dataset at different HUC levels. Our results indicate that both MODIS ET products effectively reproduced basin scale ET response (up to 25% uncertainty) compared to CONUS-wide point-based ET response (up to 50–60% uncertainty) illustrating the reliability of MODIS ET products for basin-scale ET estimation. Results from this research would guide the additional parameter refinement required for the MOD16 and SSEBop algorithms in order to further improve their accuracy and performance for agro-hydrologic applications.

Reforecasting the ENSO Events in the Past Fifty-Seven Years (1958-2014)

NASA Astrophysics Data System (ADS)

Huang, B.; Shin, C. S.; Shukla, J.; Marx, L.; Balmaseda, M.; Halder, S.; Dirmeyer, P.; Kinter, J. L.

2016-12-01

A set of ensemble seasonal reforecasts for 1958-2014 is conducted using the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), initialized with observation-based ocean, atmosphere, land and sea ice reanalyses, including the Eu­ropean Centre for Medium-Range Weather Forecasts (ECMWF) global ocean reanalysis version 4, the ERA-40 atmospheric reanalysis, the NCEP CFS Reanalysis for atmosphere, land and sea ice, and the NASA Global Land Data Assimilation System reanalysis version 2.0 for land. The purpose is to examine a long and continuous seasonal reforecast dataset from a modern seasonal forecast system to be used by the research community. In comparison with other current reforecasts, this dataset allows us to evaluate the degree to which El Niño and Southern Oscillation (ENSO) events can be predicted, using a larger sample of events. Furthermore, we can directly compare the predictability of the ENSO events in 1960s-70s with the more widely studied ENSO events occurring since the 1980s to examine the state-of-the-art seasonal forecast system's capability at different phases of global climate change and multidecadal variability. A major concern is whether the seasonal reforecasts before 1979 have useful skill when there were fewer ocean observations. Our preliminary examination of the reforecasts shows that, although the reforecasts have lower skill in predicting the SST anomalies in the North Pacific and North Atlantic before 1979, the prediction skill of the ENSO onset and development for 1958-1978 is comparable to that for 1979-2014. The skill of the earlier predictions declines faster in the ENSO decaying phase because the reforecasts initialized after the summer season persistently predict lingering wind and SST anomalies in the eastern equatorial Pacific during the decaying phase of several major ENSO events in the 1960s-70s. Since the 1980s, the reforecasts initialized in fall overestimate the peak SST anomalies in strong El Niño events. Both facts imply that the model air-sea feedback is overly active in the eastern Pacific before ENSO termination, likely induced by the model warm bias in the eastern Pacific during boreal winter and spring.

The Continued Demise of Columbia Glacier: Insights On Dynamic Change

NASA Astrophysics Data System (ADS)

Enderlin, E. M.; Hamilton, G. S.; O'Neel, S.; Bartholomaus, T. C.

2016-12-01

Columbia Glacier, Alaska, has served as the archetype for the retreat phase of the tidewater glacier cycle for the past three decades. Since the mid-1980s, the terminus has retreated 16 kilometers and the two major tributaries have thinned by > 400 m. This retreat and thinning led to separation of the tributaries in the late 2000s. Since their separation, the tributaries have exhibited strikingly different dynamic behaviors over seasonal to inter-annual time scales as they continue to adjust to the long-term changes in glacier geometry. Here we use a combination of ground, airborne, and satellite remote sensing datasets to characterize the dynamic behavior of the Columbia Glacier system. We focus on the time period following tributary separation, when the observational record is most abundant, but also investigate longer-term changes in dynamics such as the reorganization of ice flow in the eastern tributary (Figure 1). From the mid 2000s through 2012, the tributaries thinned at comparable rates ( 25 m/yr) based on repeat DEM differencing. Their behavior diverged in 2012, when the eastern tributary appeared to stabilize but the western tributary continued its sustained thinning trend. Thinning resumed along the eastern tributary in late 2013, and was accompanied by modest terminus retreat and acceleration. In contrast, the rate of thinning dramatically increased along the western tributary as it began to rapidly retreat in late 2013. These changes coincided with the three-fold increase in flow speed and pronounced increase in iceberg discharge from the western tributary. Although variations in the timing and magnitude of the recent dynamic changes can be at least partially explained by differences in the geometries of the tributaries, the dynamic behavior of Columbia Glacier's major tributaries is unlikely to be totally independent of environmental perturbations (i.e., entirely driven by the long-term dynamic adjustment). To assess the influence of environmental perturbations on the dynamic behavior of the glacier, we compare weekly to multi-year changes in glacier dynamics constructed from our airborne and satellite remotely-sensed datasets to time series of frontal ablation (i.e., submarine melting and iceberg calving) and surface mass balance compiled from ground-based observations.

Present-day trends of vertical ground motion along the coast lines

NASA Astrophysics Data System (ADS)

Ostanciaux, Émilie; Husson, Laurent; Choblet, Gaël; Robin, Cécile; Pedoja, Kevin

2012-01-01

Vertical ground motion (VGM) rates stand as crucial information, either for predicting the impact of the actual sea level rise along low-lying coasts or refining geodynamic problems. Because present day VGM rates have a magnitude smaller than 10 mm/yr, they remain challenging to quantify and often elusive. We focus on the quantification of global-scale VGM rates in order to identify global or regional trends. We computed VGM rates by combining tide gauges records and local satellite altimetry, which yield a new dataset of 634 VGM rates. We further compare this database to previous studies that use geodetic techniques and tide gauges records in order to evaluate the consistency of both our results and previous ones. The magnitudes differ by less than 5 mm/yr, and similar subsidence and uplift general tendencies appear. Even if the asset of our database stands in the greater number of sites, the combination of all studies, each with different pros and cons, yields a hybrid dataset that makes our attempt to extract VGM trends more robust than any other, independent study. Fennoscandia, the West coast of North America, and the eastern coast of Australia are uplifting, while the eastern coast of North America, the British Isles and Western Europe, the eastern Mediterranean Sea, Japan, and the western coast of Australia are subsiding. Glacial Isostatic Adjustment (GIA) is expected to provide a major contribution to the present-day signal. Aside from Fennoscandia, observed VGM often depart from the GIA model predictions of Peltier (2004). This either results from an underestimate of the model predictions or from the influence of other processes: indeed, the influence of the geodynamic setting appears in particular along the coasts of western North America or Japan, where the alternation of transform faults and subduction zones makes it possible to assign contrasted behaviours to the local geodynamic context. Local mechanisms like anthropogenic processes or sediment compaction, also contribute to VGM. This remains true for the critical cases of Venice, the Gulf of Mexico, the Ganges delta, and the Maldives, which are particularly exposed to the current sea level rise.

Estimating health benefits and cost-savings for achieving the Healthy People 2020 objective of reducing invasive colorectal cancer.

PubMed

Hung, Mei-Chuan; Ekwueme, Donatus U; White, Arica; Rim, Sun Hee; King, Jessica B; Wang, Jung-Der; Chang, Su-Hsin

2018-01-01

This study aims to quantify the aggregate potential life-years (LYs) saved and healthcare cost-savings if the Healthy People 2020 objective were met to reduce invasive colorectal cancer (CRC) incidence by 15%. We identified patients (n=886,380) diagnosed with invasive CRC between 2001 and 2011 from a nationally representative cancer dataset. We stratified these patients by sex, race/ethnicity, and age. Using these data and data from the 2001-2011 U.S. life tables, we estimated a survival function for each CRC group and the corresponding reference group and computed per-person LYs saved. We estimated per-person annual healthcare cost-savings using the 2008-2012 Medical Expenditure Panel Survey. We calculated aggregate LYs saved and cost-savings by multiplying the reduced number of CRC patients by the per-person LYs saved and lifetime healthcare cost-savings, respectively. We estimated an aggregate of 84,569 and 64,924 LYs saved for men and women, respectively, accounting for healthcare cost-savings of $329.3 and $294.2 million (in 2013$), respectively. Per person, we estimated 6.3 potential LYs saved related to those who developed CRC for both men and women, and healthcare cost-savings of $24,000 for men and $28,000 for women. Non-Hispanic whites and those aged 60-64 had the highest aggregate potential LYs saved and cost-savings. Achieving the HP2020 objective of reducing invasive CRC incidence by 15% by year 2020 would potentially save nearly 150,000 life-years and $624 million on healthcare costs. Copyright © 2017. Published by Elsevier Inc.

In situ camera observations reveal major role of zooplankton in modulating marine snow formation during an upwelling-induced plankton bloom

NASA Astrophysics Data System (ADS)

Taucher, Jan; Stange, Paul; Algueró-Muñiz, María; Bach, Lennart T.; Nauendorf, Alice; Kolzenburg, Regina; Büdenbender, Jan; Riebesell, Ulf

2018-05-01

Particle aggregation and the consequent formation of marine snow alter important properties of biogenic particles (size, sinking rate, degradability), thus playing a key role in controlling the vertical flux of organic matter to the deep ocean. However, there are still large uncertainties about rates and mechanisms of particle aggregation, as well as the role of plankton community structure in modifying biomass transfer from small particles to large fast-sinking aggregates. Here we present data from a high-resolution underwater camera system that we used to observe particle size distributions and formation of marine snow (aggregates >0.5 mm) over the course of a 9-week in situ mesocosm experiment in the Eastern Subtropical North Atlantic. After an oligotrophic phase of almost 4 weeks, addition of nutrient-rich deep water (650 m) initiated the development of a pronounced diatom bloom and the subsequent formation of large marine snow aggregates in all 8 mesocosms. We observed a substantial time lag between the peaks of chlorophyll a and marine snow biovolume of 9-12 days, which is much longer than previously reported and indicates a marked temporal decoupling of phytoplankton growth and marine snow formation during our study. Despite this time lag, our observations revealed substantial transfer of biomass from small particle sizes (single phytoplankton cells and chains) to marine snow aggregates of up to 2.5 mm diameter (ESD), with most of the biovolume being contained in the 0.5-1 mm size range. Notably, the abundance and community composition of mesozooplankton had a substantial influence on the temporal development of particle size spectra and formation of marine snow aggregates: While higher copepod abundances were related to reduced aggregate formation and biomass transfer towards larger particle sizes, the presence of appendicularia and doliolids enhanced formation of large marine snow. Furthermore, we combined in situ particle size distributions with measurements of particle sinking velocity to compute instantaneous (potential) vertical mass flux. However, somewhat surprisingly, we did not find a coherent relationship between our computed flux and measured vertical mass flux (collected by sediment traps in 15 m depth). Although the onset of measured vertical flux roughly coincided with the emergence of marine snow, we found substantial variability in mass flux among mesocosms that was not related to marine snow numbers, and was instead presumably driven by zooplankton-mediated alteration of sinking biomass and export of small particles (fecal pellets). Altogether, our findings highlight the role of zooplankton community composition and feeding interactions on particle size spectra and formation of marine snow aggregates, with important implications for our understanding of particle aggregation and vertical flux of organic matter in the ocean.

Assessing Applications of GPM and IMERG Passive Microwave Rain Rates in Modeling and Operational Forecasting

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Le Roy, A.; Smith, M. R.; Case, J.

2016-12-01

In support of NASA's recently launched GPM `core' satellite, the NASA-SPoRT project is leveraging experience in research-to-operations transitions and training to provide feedback on the operational utility of GPM products. Thus far, SPoRT has focused on evaluating the Level 2 GPROF passive microwave and IMERG rain rate estimates. Formal evaluations with end-users have occurred, as well as internal evaluations of the datasets. One set of end users for these products is National Weather Service Forecast Offices (WFOs) and National Weather Service River Forecast Centers (RFCs), comprising forecasters and hydrologists. SPoRT has hosted a series of formal assessments to determine uses and utility of these datasets for NWS operations at specific offices. Forecasters primarily have used Level 2 swath rain rates to observe rainfall in otherwise data-void regions and to confirm model QPF for their nowcasting or short-term forecasting. Hydrologists have been evaluating both the Level 2 rain rates and the IMERG rain rates, including rain rate accumulations derived from IMERG; hydrologists have used these data to supplement gauge data for post-event analysis as well as for longer-term forecasting. Results from specific evaluations will be presented. Another evaluation of the GPM passive microwave rain rates has been in using the data within other products that are currently transitioned to end-users, rather than as stand-alone observations. For example, IMERG Early data is being used as a forcing mechanism in the NASA Land Information System (LIS) for real-time soil moisture product over eastern Africa. IMERG is providing valuable precipitation information to LIS in an otherwise data-void region. Results and caveats will briefly be discussed. A third application of GPM data is using the IMERG Late and Final products for model verification in remote regions where high-quality gridded precipitation fields are not readily available. These datasets can now be used to verify NWP model forecasts over Eastern Africa using the SPoRT-MET scripts verification package, a wrapper around the NCAR Model Evaluation Toolkit (MET) verification software.

Population regulation in Gyrodactylus salaris - Atlantic salmon (Salmo salar L.) interactions: testing the paradigm.

PubMed

Ramírez, Raúl; Bakke, Tor A; Harris, Philip D

2015-07-25

Gyrodactylus salaris is a directly transmitted ectoparasite that reproduces in situ on its fish host. Wild Norwegian (East Atlantic) salmon stocks are thought to be especially susceptible to the parasite due to lack of co-adaptation, contrary to Baltic salmon stocks. This study i) identifies whether time- and density-dependent mechanisms in gyrodactylid population growth exist in G. salaris-Atlantic salmon interactions and ii) based on differences between Norwegian and Baltic stocks, determines whether the 'Atlantic susceptible, Baltic resistant' paradigm holds as an example of local adaptation. A total of 18 datasets of G. salaris population growth on individually isolated Atlantic salmon (12 different stocks) infected with three parasite strains were re-analysed using a Bayesian approach. Datasets included over 2000 observations of 388 individual fish. The best fitting model of population growth was time-limited; parasite population growth rate declined consistently from the beginning of infection. We found no evidence of exponential population growth in any dataset. In some stocks, a density dependence in the size of the initial inoculum limited the maximum rate of parasite population growth. There is no evidence to support the hypothesis that all Norwegian and Scottish Atlantic salmon stocks are equally susceptible to G. salaris, while Baltic stocks control and limit infections due to co-evolution. Northern and Western Norwegian as well as the Scottish Shin stocks, support higher initial parasite population growth rates than Baltic, South-eastern Norwegian, or the Scottish Conon stocks, and several Norwegian stocks tested (Akerselva, Altaelva, Lierelva, Numedalslågen), and the Scottish stocks (i.e. Conon, Shin), were able to limit infections after 40-50 days. No significant differences in performance of the three parasite strains (Batnfjordselva, Figga, and Lierelva), or the two parasite mitochondrial haplotypes (A and F) were observed. Our study shows a spectrum of growth rates, with some fish of the South-eastern Norwegian stocks sustaining parasite population growth rates overlapping those seen on Baltic Neva and Indalsälv stocks. This observation is inconsistent with the 'Baltic-resistant, Atlantic-susceptible' hypothesis, but suggests heterogeneity, perhaps linked to other host resistance genes driven by selection for local disease syndromes.

Collaborating to Compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium.

PubMed

Grossman, R L; Abel, B; Angiuoli, S; Barrett, J C; Bassett, D; Bramlett, K; Blumenthal, G M; Carlsson, A; Cortese, R; DiGiovanna, J; Davis-Dusenbery, B; Dittamore, R; Eberhard, D A; Febbo, P; Fitzsimons, M; Flamig, Z; Godsey, J; Goswami, J; Gruen, A; Ortuño, F; Han, J; Hayes, D; Hicks, J; Holloway, D; Hovelson, D; Johnson, J; Juhl, H; Kalamegham, R; Kamal, R; Kang, Q; Kelloff, G J; Klozenbuecher, M; Kolatkar, A; Kuhn, P; Langone, K; Leary, R; Loverso, P; Manmathan, H; Martin, A-M; Martini, J; Miller, D; Mitchell, M; Morgan, T; Mulpuri, R; Nguyen, T; Otto, G; Pathak, A; Peters, E; Philip, R; Posadas, E; Reese, D; Reese, M G; Robinson, D; Dei Rossi, A; Sakul, H; Schageman, J; Singh, S; Scher, H I; Schmitt, K; Silvestro, A; Simmons, J; Simmons, T; Sislow, J; Talasaz, A; Tang, P; Tewari, M; Tomlins, S; Toukhy, H; Tseng, H R; Tuck, M; Tzou, A; Vinson, J; Wang, Y; Wells, W; Welsh, A; Wilbanks, J; Wolf, J; Young, L; Lee, Jsh; Leiman, L C

2017-05-01

The cancer community understands the value of blood profiling measurements in assessing and monitoring cancer. We describe an effort among academic, government, biotechnology, diagnostic, and pharmaceutical companies called the Blood Profiling Atlas in Cancer (BloodPAC) Project. BloodPAC will aggregate, make freely available, and harmonize for further analyses, raw datasets, relevant associated clinical data (e.g., clinical diagnosis, treatment history, and outcomes), and sample preparation and handling protocols to accelerate the development of blood profiling assays. © 2017 Authors Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

ReOBS: a new approach to synthesize long-term multi-variable dataset and application to the SIRTA supersite

NASA Astrophysics Data System (ADS)

Chiriaco, Marjolaine; Dupont, Jean-Charles; Bastin, Sophie; Badosa, Jordi; Lopez, Julio; Haeffelin, Martial; Chepfer, Helene; Guzman, Rodrigo

2018-05-01

A scientific approach is presented to aggregate and harmonize a set of 60 geophysical variables at hourly timescale over a decade, and to allow multiannual and multi-variable studies combining atmospheric dynamics and thermodynamics, radiation, clouds and aerosols from ground-based observations. Many datasets from ground-based observations are currently in use worldwide. They are very valuable because they contain complete and precise information due to their spatio-temporal co-localization over more than a decade. These datasets, in particular the synergy between different type of observations, are under-used because of their complexity and diversity due to calibration, quality control, treatment, format, temporal averaging, metadata, etc. Two main results are presented in this article: (1) a set of methods available for the community to robustly and reliably process ground-based data at an hourly timescale over a decade is described and (2) a single netCDF file is provided based on the SIRTA supersite observations. This file contains approximately 60 geophysical variables (atmospheric and in ground) hourly averaged over a decade for the longest variables. The netCDF file is available and easy to use for the community. In this article, observations are re-analyzed. The prefix re refers to six main steps: calibration, quality control, treatment, hourly averaging, homogenization of the formats and associated metadata, as well as expertise on more than a decade of observations. In contrast, previous studies (i) took only some of these six steps into account for each variable, (ii) did not aggregate all variables together in a single file and (iii) did not offer an hourly resolution for about 60 variables over a decade (for the longest variables). The approach described in this article can be applied to different supersites and to additional variables. The main implication of this work is that complex atmospheric observations are made readily available for scientists who are non-experts in measurements. The dataset from SIRTA observations can be downloaded at http://sirta.ipsl.fr/reobs.html (last access: April 2017) (Downloads tab, no password required) under https://doi.org/10.14768/4F63BAD4-E6AF-4101-AD5A-61D4A34620DE.

NERIES: Seismic Data Gateways and User Composed Datasets Metadata Management

NASA Astrophysics Data System (ADS)

Spinuso, Alessandro; Trani, Luca; Kamb, Linus; Frobert, Laurent

2010-05-01

One of the NERIES EC project main objectives is to establish and improve the networking of seismic waveform data exchange and access among four main data centers in Europe: INGV, GFZ, ORFEUS and IPGP. Besides the implementation of the data backbone, several investigations and developments have been conducted in order to offer to the users the data available from this network, either programmatically or interactively. One of the challenges is to understand how to enable users` activities such as discovering, aggregating, describing and sharing datasets to obtain a decrease in the replication of similar data queries towards the network, exempting the data centers to guess and create useful pre-packed products. We`ve started to transfer this task more and more towards the users community, where the users` composed data products could be extensively re-used. The main link to the data is represented by a centralized webservice (SeismoLink) acting like a single access point to the whole data network. Users can download either waveform data or seismic station inventories directly from their own software routines by connecting to this webservice, which routes the request to the data centers. The provenance of the data is maintained and transferred to the users in the form of URIs, that identify the dataset and implicitly refer to the data provider. SeismoLink, combined with other webservices (eg EMSC-QuakeML earthquakes catalog service), is used from a community gateway such as the NERIES web portal (http://www.seismicportal.eu). Here the user interacts with a map based portlet which allows the dynamic composition of a data product, binding seismic event`s parameters with a set of seismic stations. The requested data is collected by the back-end processes of the portal, preserved and offered to the user in a personal data cart, where metadata can be generated interactively on-demand. The metadata, expressed in RDF, can also be remotely ingested. They offer rating, provenance and user annotation properties. Once generated they are included into a proprietary taxonomy, used by the overall architecture of the web portal. The metadata are made available through a SPARQL endpoint, thus allowing the datasets to be aggregated and shared among users in a meaningful way, enabling at the same time the development of third party visualization tools beyond the portal infrastructure. The SEE-GRID-SCI and the JISC-funded RapidSeis projects investigate the usage of this framework to enable the waveform data processing over the Grid.

Heterogeneities of the shear wave attenuation field in the lithosphere of East Tien Shan and their relationship with seismicity

NASA Astrophysics Data System (ADS)

Kopnichev, Yu. F.; Sokolova, I. N.

2012-02-01

The shear wave attenuation field in the lithosphere of Eastern Tien Shan has been mapped. The method based on analysis of the ratio between amplitudes of Sn and Pn waves was used. On aggregate, about 120 seismograms made at the Makanchi station (MKAR), mainly in the period of 2003-2009, at epicentral distances of about 350-1200 km were analyzed. It was found that shear wave attenuation in the lithosphere of Eastern Tien Shan is weaker than that in the region of Central Tien Shan. This agrees with the fact that the rate of deformation of the Earth's crust in Eastern Tien Shan is lower (based on GPS data), as is the seismicity level, in comparison to Central Tien Shan. The zones of high attenuation, where strong earthquakes with M > 7.0 have not occurred for the last 200 years, have been identified: first of all, these are the area west of Urumqi and that of the Lop Nur test site. It is suggested that in the first zone, where an annular seismicity structure has formed over the last 30 years, a strong earthquake may be being prepared. The second zone is most probably related to the uplift of mantle fluids resulting from a long-term intensive technogenic effect, analogous to what has occurred in areas of other nuclear test sites (Nevada and Semipalatinsk).

Publishing NASA Metadata as Linked Open Data for Semantic Mashups

NASA Astrophysics Data System (ADS)

Wilson, Brian; Manipon, Gerald; Hua, Hook

2014-05-01

Data providers are now publishing more metadata in more interoperable forms, e.g. Atom or RSS 'casts', as Linked Open Data (LOD), or as ISO Metadata records. A major effort on the part of the NASA's Earth Science Data and Information System (ESDIS) project is the aggregation of metadata that enables greater data interoperability among scientific data sets regardless of source or application. Both the Earth Observing System (EOS) ClearingHOuse (ECHO) and the Global Change Master Directory (GCMD) repositories contain metadata records for NASA (and other) datasets and provided services. These records contain typical fields for each dataset (or software service) such as the source, creation date, cognizant institution, related access URL's, and domain and variable keywords to enable discovery. Under a NASA ACCESS grant, we demonstrated how to publish the ECHO and GCMD dataset and services metadata as LOD in the RDF format. Both sets of metadata are now queryable at SPARQL endpoints and available for integration into "semantic mashups" in the browser. It is straightforward to reformat sets of XML metadata, including ISO, into simple RDF and then later refine and improve the RDF predicates by reusing known namespaces such as Dublin core, georss, etc. All scientific metadata should be part of the LOD world. In addition, we developed an "instant" drill-down and browse interface that provides faceted navigation so that the user can discover and explore the 25,000 datasets and 3000 services. The available facets and the free-text search box appear in the left panel, and the instantly updated results for the dataset search appear in the right panel. The user can constrain the value of a metadata facet simply by clicking on a word (or phrase) in the "word cloud" of values for each facet. The display section for each dataset includes the important metadata fields, a full description of the dataset, potentially some related URL's, and a "search" button that points to an OpenSearch GUI that is pre-configured to search for granules within the dataset. We will present our experiences with converting NASA metadata into LOD, discuss the challenges, illustrate some of the enabled mashups, and demonstrate the latest version of the "instant browse" interface for navigating multiple metadata collections.

Eastern Andean environmental and climate synthesis for the last 2000 years BP from terrestrial pollen and charcoal records of Patagonia

NASA Astrophysics Data System (ADS)

Sottile, G. D.; Echeverria, M. E.; Mancini, M. V.; Bianchi, M. M.; Marcos, M. A.; Bamonte, F. P.

2015-06-01

The Southern Hemisphere Westerly Winds (SWW) constitute an important zonal circulation system that dominates the dynamics of Southern Hemisphere mid-latitude climate. Little is known about climatic changes in the Southern South America in comparison to the Northern Hemisphere due to the low density of proxy records, and adequate chronology and sampling resolution to address environmental changes of the last 2000 years. Since 2009, new pollen and charcoal records from bog and lakes in northern and southern Patagonia at the east side of the Andes have been published with an adequate calibration of pollen assemblages related to modern vegetation and ecological behaviour. In this work we improve the chronological control of some eastern Andean previously published sequences and integrate pollen and charcoal dataset available east of the Andes to interpret possible environmental and SWW variability at centennial time scales. Through the analysis of modern and past hydric balance dynamics we compare these scenarios with other western Andean SWW sensitive proxy records for the last 2000 years. Due to the distinct precipitation regimes that exist between Northern (40-45° S) and Southern Patagonia (48-52° S) pollen sites locations, shifts on latitudinal and strength of the SWW results in large changes on hydric availability on forest and steppe communities. Therefore, we can interpret fossil pollen dataset as changes on paleohydric balance at every single site by the construction of paleohydric indices and comparison to charcoal records during the last 2000 cal yrs BP. Our composite pollen-based Northern and Southern Patagonia indices can be interpreted as changes in latitudinal variation and intensity of the SWW respectively. Dataset integration suggest poleward SWW between 2000 and 750 cal yrs BP and northward-weaker SWW during the Little Ice Age (750-200 cal yrs BP). These SWW variations are synchronous to Patagonian fire activity major shifts. We found an in phase fire regime (in terms of timing of biomass burning) between northern Patagonia Monte shrubland and Southern Patagonia steppe environments. Conversely, there is an antiphase fire regime between Northern and Southern Patagonia forest and forest-steppe ecotone environments. SWW variability may be associated to ENSO variability especially during the last millennia. For the last 200 cal yrs BP we can concluded that the SWW belt were more intense and poleward than the previous interval. Our composite pollen-based SWW indices show the potential of pollen dataset integration to improve the understanding of paleohydric variability especially for the last 2000 millennial in Patagonia.

Comparison and Evaluation of Annual NDVI Time Series in China Derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 Products

PubMed Central

Guo, Xiaoyi; Zhang, Hongyan; Wu, Zhengfang; Zhao, Jianjun; Zhang, Zhengxiang

2017-01-01

Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets (MOD13C1) are compared and evaluated for the period from 2001 to 2014 in China. The spatial patterns of the NDVI generally match between the LTDR V4 and MOD13C1 datasets. The transitional zone between high and low NDVI values generally matches the boundary of semi-arid and sub-humid regions. A significant and high coefficient of determination is found between the two datasets according to a pixel-based correlation analysis. The spatially averaged NDVI of LTDR V4 is characterized by a much weaker positive regression slope relative to that of the spatially averaged NDVI of the MOD13C1 dataset because of changes in NOAA AVHRR sensors between 2005 and 2006. The measured NDVI values of LTDR V4 were always higher than that of MOD13C1 in western China due to the relatively lower atmospheric water vapor content in western China, and opposite observation appeared in eastern China. In total, 18.54% of the LTDR V4 NDVI pixels exhibit significant trends, whereas 35.79% of the MOD13C1 NDVI pixels show significant trends. Good agreement is observed between the significant trends of the two datasets in the Northeast Plain, Bohai Economic Rim, Loess Plateau, and Yangtze River Delta. By contrast, the datasets contrasted in northwestern desert regions and southern China. A trend analysis of the regression slope values according to the vegetation type shows good agreement between the LTDR V4 and MOD13C1 datasets. This study demonstrates the spatial and temporal consistencies and discrepancies between the AVHRR LTDR and MODIS MOD13C1 NDVI products in China, which could provide useful information for the choice of NDVI products in subsequent studies of vegetation dynamics. PMID:28587266

Comparison and Evaluation of Annual NDVI Time Series in China Derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 Products.

PubMed

Guo, Xiaoyi; Zhang, Hongyan; Wu, Zhengfang; Zhao, Jianjun; Zhang, Zhengxiang

2017-06-06

Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets (MOD13C1) are compared and evaluated for the period from 2001 to 2014 in China. The spatial patterns of the NDVI generally match between the LTDR V4 and MOD13C1 datasets. The transitional zone between high and low NDVI values generally matches the boundary of semi-arid and sub-humid regions. A significant and high coefficient of determination is found between the two datasets according to a pixel-based correlation analysis. The spatially averaged NDVI of LTDR V4 is characterized by a much weaker positive regression slope relative to that of the spatially averaged NDVI of the MOD13C1 dataset because of changes in NOAA AVHRR sensors between 2005 and 2006. The measured NDVI values of LTDR V4 were always higher than that of MOD13C1 in western China due to the relatively lower atmospheric water vapor content in western China, and opposite observation appeared in eastern China. In total, 18.54% of the LTDR V4 NDVI pixels exhibit significant trends, whereas 35.79% of the MOD13C1 NDVI pixels show significant trends. Good agreement is observed between the significant trends of the two datasets in the Northeast Plain, Bohai Economic Rim, Loess Plateau, and Yangtze River Delta. By contrast, the datasets contrasted in northwestern desert regions and southern China. A trend analysis of the regression slope values according to the vegetation type shows good agreement between the LTDR V4 and MOD13C1 datasets. This study demonstrates the spatial and temporal consistencies and discrepancies between the AVHRR LTDR and MODIS MOD13C1 NDVI products in China, which could provide useful information for the choice of NDVI products in subsequent studies of vegetation dynamics.

The aggregation efficiency of very fine volcanic ash

NASA Astrophysics Data System (ADS)

Del Bello, E.; Taddeucci, J.; Scarlato, P.

2013-12-01

Explosive volcanic eruptions can discharge large amounts of very small sized pyroclasts (under 0.090 mm) into the atmosphere that may cause problems to people, infrastructures and environment. The transport and deposition of fine ash are ruled by aggregation that causes premature settling of fine ash and, as consequence, significantly reduces the concentration of airborne material over long distances. Parameterizing the aggregation potential of fine ash is then needed to provide accurate modelling of ash transport and deposition from volcanic plumes. Here we present the first results of laboratory experiments investigating the aggregation efficiency of very fine volcanic particles. Previous laboratory experiments have shown that collision kinetic and relative humidity provide the strongest effect on aggregation behaviour but were only limited to particles with size > 0.125 mm. In our work, we focus on natural volcanic ash at ambient humidity with particles size < 0.090 mm, by taking into account the effect of grain size distribution on aggregation potential. Two types of ash were used in our experiments: fresh ash, collected during fall-out from a recent plume-forming eruption at Sakurajima (Japan -July 2013) and old ash, collected from fall-out tephra deposits at Campi Flegrei (Italy, ca. 10 ka), to account for the different chemical composition and morphoscopic effects of altered ash on aggregation efficiency. Total samples were hand sieved to obtain three classes with unimodal grain size distributions (<0.090 mm, <0.063 mm, <0.032 mm). Bimodal grain size distributions were also obtained by mixing the three classes in different proportions. During each experiments, particles were sieved from the top of a transparent tank where a fan, placed at the bottom, allows turbulent dispersion of particles. Collision and sticking of particles on a vertical glass slide were filmed with a high speed cameras at 6000 fps. Our lenses arrangement provide high image resolution allowing to capture particles down to 0.005 mm in diameter. Video sequences of particles motion and collision were then processed with image analysis and particle tracking tools to determine i) the particle number density and ii) the grain size distribution of particles in the turbulent dispersion, and iii) the number of adhered particles as a function of time. Optical laser granulometry provided constrains on grain size distribution of ash particles effectively adhered to the glass slide at the end of each run. Results obtained from our data-set allowed to provide a relationship for determining aggregation rate as a function of particle number density across a range of particle size distributions. This empirical model can be used to determine the aggregation fraction starting from a given total grain size distribution, thus providing fundamental parameters to incorporate aggregation into numerical models of ash dispersal and deposition.

A correlation comparison between Altmetric Attention Scores and citations for six PLOS journals.

PubMed

Huang, Wenya; Wang, Peiling; Wu, Qiang

2018-01-01

This study considered all articles published in six Public Library of Science (PLOS) journals in 2012 and Web of Science citations for these articles as of May 2015. A total of 2,406 articles were analyzed to examine the relationships between Altmetric Attention Scores (AAS) and Web of Science citations. The AAS for an article, provided by Altmetric aggregates activities surrounding research outputs in social media (news outlet mentions, tweets, blogs, Wikipedia, etc.). Spearman correlation testing was done on all articles and articles with AAS. Further analysis compared the stratified datasets based on percentile ranks of AAS: top 50%, top 25%, top 10%, and top 1%. Comparisons across the six journals provided additional insights. The results show significant positive correlations between AAS and citations with varied strength for all articles and articles with AAS (or social media mentions), as well as for normalized AAS in the top 50%, top 25%, top 10%, and top 1% datasets. Four of the six PLOS journals, Genetics, Pathogens, Computational Biology, and Neglected Tropical Diseases, show significant positive correlations across all datasets. However, for the two journals with high impact factors, PLOS Biology and Medicine, the results are unexpected: the Medicine articles showed no significant correlations but the Biology articles tested positive for correlations with the whole dataset and the set with AAS. Both journals published substantially fewer articles than the other four journals. Further research to validate the AAS algorithm, adjust the weighting scheme, and include appropriate social media sources is needed to understand the potential uses and meaning of AAS in different contexts and its relationship to other metrics.

Nuclear Receptor Signaling Atlas: Opening Access to the Biology of Nuclear Receptor Signaling Pathways.

PubMed

Becnel, Lauren B; Darlington, Yolanda F; Ochsner, Scott A; Easton-Marks, Jeremy R; Watkins, Christopher M; McOwiti, Apollo; Kankanamge, Wasula H; Wise, Michael W; DeHart, Michael; Margolis, Ronald N; McKenna, Neil J

2015-01-01

Signaling pathways involving nuclear receptors (NRs), their ligands and coregulators, regulate tissue-specific transcriptomes in diverse processes, including development, metabolism, reproduction, the immune response and neuronal function, as well as in their associated pathologies. The Nuclear Receptor Signaling Atlas (NURSA) is a Consortium focused around a Hub website (www.nursa.org) that annotates and integrates diverse 'omics datasets originating from the published literature and NURSA-funded Data Source Projects (NDSPs). These datasets are then exposed to the scientific community on an Open Access basis through user-friendly data browsing and search interfaces. Here, we describe the redesign of the Hub, version 3.0, to deploy "Web 2.0" technologies and add richer, more diverse content. The Molecule Pages, which aggregate information relevant to NR signaling pathways from myriad external databases, have been enhanced to include resources for basic scientists, such as post-translational modification sites and targeting miRNAs, and for clinicians, such as clinical trials. A portal to NURSA's Open Access, PubMed-indexed journal Nuclear Receptor Signaling has been added to facilitate manuscript submissions. Datasets and information on reagents generated by NDSPs are available, as is information concerning periodic new NDSP funding solicitations. Finally, the new website integrates the Transcriptomine analysis tool, which allows for mining of millions of richly annotated public transcriptomic data points in the field, providing an environment for dataset re-use and citation, bench data validation and hypothesis generation. We anticipate that this new release of the NURSA database will have tangible, long term benefits for both basic and clinical research in this field.

Trends in ice sheet mass balance, 1992 to 2017

NASA Astrophysics Data System (ADS)

Shepherd, A.; Ivins, E. R.; Smith, B.; Velicogna, I.; Whitehouse, P. L.; Rignot, E. J.; van den Broeke, M. R.; Briggs, K.; Hogg, A.; Krinner, G.; Joughin, I. R.; Nowicki, S.; Payne, A. J.; Scambos, T.; Schlegel, N.; Moyano, G.; Konrad, H.

2017-12-01

The Ice Sheet Mass Balance Inter-Comparison Exercise (IMBIE) is a community effort, jointly supported by ESA and NASA, that aims to provide a consensus estimate of ice sheet mass balance from satellite gravimetry, altimetry and mass budget assessments, on an annual basis. The project has five experiment groups, one for each of the satellite techniques and two others to analyse surface mass balance (SMB) and glacial isostatic adjustment (GIA). The basic premise for the exercise is that individual ice sheet mass balance datasets are generated by project participants using common spatial and temporal domains to allow meaningful inter-comparison, and this controlled comparison in turn supports aggregation of the individual datasets over their full period. Participation is open to the full community, and the quality and consistency of submissions is regulated through a series of data standards and documentation requirements. The second phase of IMBIE commenced in 2015, with participant data submitted in 2016 and a combined estimate due for public release in 2017. Data from 48 participant groups were submitted to one of the three satellite mass balance technique groups or to the ancillary dataset groups. The individual mass balance estimates and ancillary datasets have been compared and combined within the respective groups. Following this, estimates of ice sheet mass balance derived from the individual techniques were then compared and combined. The result is single estimates of ice sheet mass balance for Greenland, East Antarctica, West Antarctica, and the Antarctic Peninsula. The participants, methodology and results of the exercise will be presented in this paper.

Potential mineral resources, Payette National Forest, Idaho: description and probabilistic estimation

USGS Publications Warehouse

Bookstrom, Arthur A.; Johnson, Bruce R.; Cookro, Theresa M.; Lund, Karen; Watts, Kenneth C.; King, Harley D.; Kleinkopf, Merlin D.; Pitkin, James A.; Sanchez, J. David; Causey, J. Douglas

1998-01-01

The Payette National Forest (PNF), in west-central Idaho, is geologically diverse and contains a wide variety of mineral resources. Mineral deposit types are grouped into locatable, leasable, and salable categories. The PNF has substantial past production and identified resources of locatable commodities, including gold, silver, copper, zinc, tungsten, antimony, mercury, and opal. Minor lignitic coal is the only leasable mineral resource known to be present in the PNF. Resources of salable commodities in the PNF include sand-and-gravel, basalt for crushed-rock aggregate, and minor gypsum. Locatable mineral resources are geographically divided between eastern and western parts of the PNF. The western PNF lies west of the Riggins-to-Cascade highway (US 95 - Idaho 55), and the eastern PNF is east of that highway. The western and eastern parts of the PNF are geologically distinctive and have different types of locatable mineral deposits, so their locatable mineral resources are described separately. Within the western and eastern parts of the PNF, locatable deposit types generally are described in order of decreasing geologic age. An expert panel delineated tracts considered geologically permissive and (or) favorable for the occurrence of undiscovered mineral deposits of types that are known to be present within or near the PNF. The panel also estimated probabilities for undiscovered deposits, and used numerical simulation, based on tonnage-grade distribution models, to derive estimates of in-situ metals contained. These estimates are summarized in terms of mean and median measures of central tendency. Most grade and tonnage distributions appear to be log-normal, with the median lower than the mean. Inasmuch as the mean is influenced by the largest deposits in the model tonnage-grade distribution, the median provides a lower measure of central tendency and a more conservative estimation of undiscovered resources.

The novel use of pop-off satellite tags (PSATs) to investigate the migratory behaviour of European sea bass Dicentrarchus labrax.

PubMed

O'Neill, R; Ó Maoiléidigh, N; McGinnity, P; Bond, N; Culloty, S

2018-05-01

A total of 12 adult European sea bass Dicentrarchus labrax were tagged with pop-off satellite archival tags (PSAT) in Irish coastal waters and in offshore waters in the north-east Celtic Sea between 2015 and 2016. Archived data were successfully recovered from five of the 12 tags deployed, three from fish released in inshore Irish waters and two from fish released offshore in the eastern Celtic Sea. All three fish tagged in inshore waters were found to undertake migrations into the open ocean coinciding with the spawning period. These fish also exhibited fidelity to inshore sites post-migration, returning to the same general location (within c. 73 km, which is roughly the predicted mean accuracy of the method) of their original release site. Although the number of tracks obtained here was limited, some degree of aggregation between inshore and offshore tagged fish in the eastern Celtic Sea was noted during the expected spawning period suggesting PSATs can provide new information on specific spawning locations of European sea bass. © 2018 The Fisheries Society of the British Isles.

The Eastern Gas Shales Project (EGSP) Data System: A case study in data base design, development, and application

USGS Publications Warehouse

Dyman, T.S.; Wilcox, L.A.

1983-01-01

The U.S. Geological Survey and Petroleum Information Corporation in Denver, Colorado, developed the Eastern Gas Shale Project (EGSP)Data System for the U.S. Department of Energy, Morgantown, West Virginia. Geological, geochemical, geophysical, and engineering data from Devonian shale samples from more than 5800 wells and outcrops in the Appalachian basin were edited and converted to a Petroleum Information Corporation data base. Well and sample data may be retrieved from this data system to produce (1)production-test summaries by formation and well location; (2)contoured isopach, structure, and trendsurface maps of Devonian shale units; (3)sample summary reports for samples by location, well, contractor, and sample number; (4)cross sections displaying digitized log traces, geochemical, and lithologic data by depth for wells; and (5)frequency distributions and bivariate plots. Although part of the EGSP Data System is proprietary, and distribution of complete well histories is prohibited by contract, maps and aggregated well-data listings are being made available to the public through published reports. ?? 1983 Plenum Publishing Corporation.

Demonstrating the robustness of population surveillance data: implications of error rates on demographic and mortality estimates.

PubMed

Fottrell, Edward; Byass, Peter; Berhane, Yemane

2008-03-25

As in any measurement process, a certain amount of error may be expected in routine population surveillance operations such as those in demographic surveillance sites (DSSs). Vital events are likely to be missed and errors made no matter what method of data capture is used or what quality control procedures are in place. The extent to which random errors in large, longitudinal datasets affect overall health and demographic profiles has important implications for the role of DSSs as platforms for public health research and clinical trials. Such knowledge is also of particular importance if the outputs of DSSs are to be extrapolated and aggregated with realistic margins of error and validity. This study uses the first 10-year dataset from the Butajira Rural Health Project (BRHP) DSS, Ethiopia, covering approximately 336,000 person-years of data. Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset. Key parameters of sex, age, death, literacy and roof material (an indicator of poverty) were selected for the introduction of errors based on their obvious importance in demographic and health surveillance and their established significant associations with mortality. Defining the original 10-year dataset as the 'gold standard' for the purposes of this investigation, population, age and sex compositions and Poisson regression models of mortality rate ratios were compared between each of the intentionally erroneous datasets and the original 'gold standard' 10-year data. The composition of the Butajira population was well represented despite introducing random errors, and differences between population pyramids based on the derived datasets were subtle. Regression analyses of well-established mortality risk factors were largely unaffected even by relatively high levels of random errors in the data. The low sensitivity of parameter estimates and regression analyses to significant amounts of randomly introduced errors indicates a high level of robustness of the dataset. This apparent inertia of population parameter estimates to simulated errors is largely due to the size of the dataset. Tolerable margins of random error in DSS data may exceed 20%. While this is not an argument in favour of poor quality data, reducing the time and valuable resources spent on detecting and correcting random errors in routine DSS operations may be justifiable as the returns from such procedures diminish with increasing overall accuracy. The money and effort currently spent on endlessly correcting DSS datasets would perhaps be better spent on increasing the surveillance population size and geographic spread of DSSs and analysing and disseminating research findings.

Effects of different regional climate model resolution and forcing scales on projected hydrologic changes

NASA Astrophysics Data System (ADS)

Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji

2016-10-01

We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.

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.

On Spatially Explicit Models of Epidemic and Endemic Cholera: The Haiti and Lake Kivu Case Studies.

NASA Astrophysics Data System (ADS)

Rinaldo, A.; Bertuzzo, E.; Mari, L.; Finger, F.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.

2014-12-01

The first part of the Lecture deals with the predictive ability of mechanistic models for the Haitian cholera epidemic. Predictive models of epidemic cholera need to resolve at suitable aggregation levels spatial data pertaining to local communities, epidemiological records, hydrologic drivers, waterways, patterns of human mobility and proxies of exposure rates. A formal model comparison framework provides a quantitative assessment of the explanatory and predictive abilities of various model settings with different spatial aggregation levels. Intensive computations and objective model comparisons show that parsimonious spatially explicit models accounting for spatial connections have superior explanatory power than spatially disconnected ones for short-to intermediate calibration windows. In general, spatially connected models show better predictive ability than disconnected ones. We suggest limits and validity of the various approaches and discuss the pathway towards the development of case-specific predictive tools in the context of emergency management. The second part deals with approaches suitable to describe patterns of endemic cholera. Cholera outbreaks have been reported in the Democratic Republic of the Congo since the 1970s. Here we employ a spatially explicit, inhomogeneous Markov chain model to describe cholera incidence in eight health zones on the shore of lake Kivu. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers in addition to baseline seasonality. The effect of human mobility is also modelled mechanistically. We test several models on a multi-year dataset of reported cholera cases. Fourteen models, accounting for different environmental drivers, are selected in calibration. Among these, the one accounting for seasonality, El Nino Southern Oscillation, precipitation and human mobility outperforms the others in cross-validation.

The Gulf of Mexico Coastal Ocean Observing System: Building an MBON for the Florida Keys.

NASA Astrophysics Data System (ADS)

Howard, M.; Stoessel, M. M.; Currier, R. D.

2016-02-01

The Gulf of Mexico Coastal Ocean Observing System Regional Association (GCOOS-RA) Data Portal was designed to aggregate regional data and to serve it to the public through standards-based services in useful and desirable forms. These standards are established and sanctioned for use by the U.S. Integrated Ocean Observing System (IOOS) Program Office with inputs from experts on the Integrated Ocean Observation Committee and the RA informatics community. In 2012, with considerable input from staff from Ocean Biogeographical Information System USA (OBIS-USA), IOOS began to develop and adopt standards for serving biological datasets. GCOOS-RA applied these standards the following year and began serving fisheries independent data through an GCOOS ERDDAP server. In late 2014, GCOOS-RA partnered with the University of South Florida in a 5-year Marine Biodiversity Observing Network (MBON) Project sponsored by NOAA, NASA and BOEM. Work began in 2015. GCOOS' primary role is to aggregate, organize and serve data that are useful to an MBON for the Florida Keys National Marine Sanctuary. GCOOS, in collaboration with Axiom Data Science, will produce a decision support system (DSS) for stakeholders such as NOAA National Marine Sanctuaries Program managers. The datasets to be managed include environmental observations from: field surveys, fixed platforms, and satellites; GIS layers of: bathymetry, shoreline, sanctuary boundaries, living marine resources and habitats; outputs from ocean circulation models and ecosystem models (e.g., Ecopath/Ecosim) and Environmental DNA. Additionally, the DSS may be called upon to perform analyses, compute indices of biodiversity and present results in tabular, graphic and fused forms in an interactive setting. This presentation will discuss our progress to date for this challenging work in data integration.

Scaling Up Scientific Discovery in Sleep Medicine: The National Sleep Research Resource.

PubMed

Dean, Dennis A; Goldberger, Ary L; Mueller, Remo; Kim, Matthew; Rueschman, Michael; Mobley, Daniel; Sahoo, Satya S; Jayapandian, Catherine P; Cui, Licong; Morrical, Michael G; Surovec, Susan; Zhang, Guo-Qiang; Redline, Susan

2016-05-01

Professional sleep societies have identified a need for strategic research in multiple areas that may benefit from access to and aggregation of large, multidimensional datasets. Technological advances provide opportunities to extract and analyze physiological signals and other biomedical information from datasets of unprecedented size, heterogeneity, and complexity. The National Institutes of Health has implemented a Big Data to Knowledge (BD2K) initiative that aims to develop and disseminate state of the art big data access tools and analytical methods. The National Sleep Research Resource (NSRR) is a new National Heart, Lung, and Blood Institute resource designed to provide big data resources to the sleep research community. The NSRR is a web-based data portal that aggregates, harmonizes, and organizes sleep and clinical data from thousands of individuals studied as part of cohort studies or clinical trials and provides the user a suite of tools to facilitate data exploration and data visualization. Each deidentified study record minimally includes the summary results of an overnight sleep study; annotation files with scored events; the raw physiological signals from the sleep record; and available clinical and physiological data. NSRR is designed to be interoperable with other public data resources such as the Biologic Specimen and Data Repository Information Coordinating Center Demographics (BioLINCC) data and analyzed with methods provided by the Research Resource for Complex Physiological Signals (PhysioNet). This article reviews the key objectives, challenges and operational solutions to addressing big data opportunities for sleep research in the context of the national sleep research agenda. It provides information to facilitate further interactions of the user community with NSRR, a community resource. © 2016 Associated Professional Sleep Societies, LLC.

OpenAQ: A Platform to Aggregate and Freely Share Global Air Quality Data

NASA Astrophysics Data System (ADS)

Hasenkopf, C. A.; Flasher, J. C.; Veerman, O.; DeWitt, H. L.

2015-12-01

Thousands of ground-based air quality monitors around the world publicly publish real-time air quality data; however, researchers and the public do not have access to this information in the ways most useful to them. Often, air quality data are posted on obscure websites showing only current values, are programmatically inaccessible, and/or are in inconsistent data formats across sites. Yet, historical and programmatic access to such a global dataset would be transformative to several scientific fields, from epidemiology to low-cost sensor technologies to estimates of ground-level aerosol by satellite retrievals. To increase accessibility and standardize this disparate dataset, we have built OpenAQ, an innovative, open platform created by a group of scientists and open data programmers. The source code for the platform is viewable at github.com/openaq. Currently, we are aggregating, storing, and making publicly available real-time air quality data (PM2.5, PM10, SO2, NO2, and O3) via an Application Program Interface (API). We will present the OpenAQ platform, which currently has the following specific capabilities: A continuous ingest mechanism for some of the most polluted cities, generalizable to more sources An API providing data-querying, including ability to filter by location, measurement type and value and date, as well as custom sort options A generalized, chart-based visualization tool to explore data accessible via the API At this stage, we are seeking wider participation and input from multiple research communities in expanding our data retrieval sites, standardizing our protocols, receiving feedback on quality issues, and creating tools that can be built on top of this open platform.

Quaternary Structure Heterogeneity of Oligomeric Proteins: A SAXS and SANS Study of the Dissociation Products of Octopus vulgaris Hemocyanin

PubMed Central

Spinozzi, Francesco; Mariani, Paolo; Mičetić, Ivan; Ferrero, Claudio; Pontoni, Diego; Beltramini, Mariano

2012-01-01

Octopus vulgaris hemocyanin shows a particular self-assembling pattern, characterized by a hierarchical organization of monomers. The highest molecular weight aggregate is a decamer, the stability of which in solution depends on several parameters. Different pH values, buffer compositions, H2O/D2O ratios and Hofmeister’s salts result in modifications of the aggregation state of Octopus vulgaris hemocyanin. The new QUAFIT method, recently applied to derive the structure of the decameric and the monomeric assembly from small-angle scattering data, is used here to model the polydisperse system that results from changing the solution conditions. A dataset of small-angle X-rays and neutron scattering curves is analysed by QUAFIT to derive structure, composition and concentration of different assemblies present in solution. According to the hierarchy of the association/dissociation processes and the possible number of different aggregation products in solution, each sample has been considered as a heterogeneous mixture composed of the entire decamer, the dissociated “loose” monomer and all the intermediate dissociation products. Scattering curves corresponding to given experimental conditions are well fitted by using a linear combination of single particle form factors. QUAFIT has proved to be a method of general validity to describe solutions of proteins that, even after purification processes, result to be intrinsically heterogeneous. PMID:23166737

Bayesian multinomial probit modeling of daily windows of ...

EPA Pesticide Factsheets

Past epidemiologic studies suggest maternal ambient air pollution exposure during critical periods of the pregnancy is associated with fetal development. We introduce a multinomial probit model that allows for the joint identification of susceptible daily periods during the pregnancy for 12 individual types of CHDs with respect to maternal PM2.5 exposure. We apply the model to a dataset of mothers from the National Birth Defect Prevention Study where daily PM2.5 exposures from weeks 2-8 of pregnancy are assigned (specific to each location and pregnancy date) using predictions from the downscaler pollution model. Results are compared to an aggregated exposure model which defines exposure as the average value over pregnancy weeks 2-8. Increased PM2.5 exposure during pregnancy days 53 and 50-51 for pulmonary valve stenosis and tetralogy of Fallot, respectively, are associated with an increased probability of development of each CHD. The largest estimated effect is seen for atrioventricular septal defects on pregnancy day 14. The aggregated exposure model fails to identify any significant windows of susceptibility during pregnancy weeks 2-8 for the considered CHDs. Considering daily PM2.5 exposures in a new modeling framework revealed positive associations for defects that the standard aggregated exposure model was unable to identify. Disclaimer: The views expressed in this manuscript are those of the authors and do not necessarily represent the views or policie

Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.

2017-12-01

Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.

Land cover mapping for development planning in Eastern and Southern Africa

NASA Astrophysics Data System (ADS)

Oduor, P.; Flores Cordova, A. I.; Wakhayanga, J. A.; Kiema, J.; Farah, H.; Mugo, R. M.; Wahome, A.; Limaye, A. S.; Irwin, D.

2016-12-01

Africa continues to experience intensification of land use, driven by competition for resources and a growing population. Land cover maps are some of the fundamental datasets required by numerous stakeholders to inform a number of development decisions. For instance, they can be integrated with other datasets to create value added products such as vulnerability impact assessment maps, and natural capital accounting products. In addition, land cover maps are used as inputs into Greenhouse Gas (GHG) inventories to inform the Agriculture, Forestry and other Land Use (AFOLU) sector. However, the processes and methodologies of creating land cover maps consistent with international and national land cover classification schemes can be challenging, especially in developing countries where skills, hardware and software resources can be limiting. To meet this need, SERVIR Eastern and Southern Africa developed methodologies and stakeholder engagement processes that led to a successful initiative in which land cover maps for 9 countries (Malawi, Rwanda, Namibia, Botswana, Lesotho, Ethiopia, Uganda, Zambia and Tanzania) were developed, using 2 major classification schemes. The first sets of maps were developed based on an internationally acceptable classification system, while the second sets of maps were based on a nationally defined classification system. The mapping process benefited from reviews from national experts and also from technical advisory groups. The maps have found diverse uses, among them the definition of the Forest Reference Levels in Zambia. In Ethiopia, the maps have been endorsed by the national mapping agency as part of national data. The data for Rwanda is being used to inform the Natural Capital Accounting process, through the WAVES program, a World Bank Initiative. This work illustrates the methodologies and stakeholder engagement processes that brought success to this land cover mapping initiative.

ATM Coastal Topography-Florida 2001: Eastern Panhandle

USGS Publications Warehouse

Yates, Xan; Nayegandhi, Amar; Brock, John C.; Sallenger, A.H.; Bonisteel, Jamie M.; Klipp, Emily S.; Wright, C. Wayne

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the eastern Florida panhandle coastline, acquired October 2, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography.

Chemical speciation and source apportionment of Non-Methane Volatile Organic Compounds (NMVOCs) in a Middle Eastern country

NASA Astrophysics Data System (ADS)

Salameh, Therese; Sauvage, Stéphane; Afif, Charbel; Borbon, Agnès; Locoge, Nadine

2014-05-01

NMVOCs, emitted from various sources, are of particular interest since they contribute to the formation of tropospheric ozone, PAN and secondary organic aerosols resulting in negative impacts on human health, climate and on the environment. To identify abatement measures, a profound knowledge of emission sources and their composition is a prerequisite. Air pollution in the Middle East region remains difficult to assess and understand because of a lack of ground-based measurements and the limited information on NMVOC chemical speciation and source apportionment. Based on a large database of NMVOC observations obtained in Beirut, the capital of Lebanon (a developing country in the Middle East region, located in Western Asia on the eastern shore of the Mediterranean Sea), the overall objective of this work is to apportion the sources of NMVOCs encountered in Lebanon. First, source profiles were determined with field measurements close to the main potential emitters namely the road transport, gasoline vapour, power generation and solvent uses. The results obtained are compared to other studies held in other regions and are used to assess the emission inventory developed for Lebanon. Secondly, two intensive field campaigns were held in a receptor site in Beirut during summer 2011 and winter 2012 in order to obtain a large time resolved dataset. The PMF analysis of this dataset was applied to apportion anthropogenic sources in this area. In both seasons, combustion (road transport and power generation) and gasoline evaporation, especially in winter, were the main sources contributing to the NMVOCs in Beirut. The results will support model implementation especially by completing the emission inventory established for the year 2010 by Waked et al. 2012 according to the EEA/EMEP guidelines because of the lack of Lebanon-specific emission factor.

Regional regression models of watershed suspended-sediment discharge for the eastern United States

NASA Astrophysics Data System (ADS)

Roman, David C.; Vogel, Richard M.; Schwarz, Gregory E.

2012-11-01

SummaryEstimates of mean annual watershed sediment discharge, derived from long-term measurements of suspended-sediment concentration and streamflow, often are not available at locations of interest. The goal of this study was to develop multivariate regression models to enable prediction of mean annual suspended-sediment discharge from available basin characteristics useful for most ungaged river locations in the eastern United States. The models are based on long-term mean sediment discharge estimates and explanatory variables obtained from a combined dataset of 1201 US Geological Survey (USGS) stations derived from a SPAtially Referenced Regression on Watershed attributes (SPARROW) study and the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES) database. The resulting regional regression models summarized for major US water resources regions 1-8, exhibited prediction R2 values ranging from 76.9% to 92.7% and corresponding average model prediction errors ranging from 56.5% to 124.3%. Results from cross-validation experiments suggest that a majority of the models will perform similarly to calibration runs. The 36-parameter regional regression models also outperformed a 16-parameter national SPARROW model of suspended-sediment discharge and indicate that mean annual sediment loads in the eastern United States generally correlates with a combination of basin area, land use patterns, seasonal precipitation, soil composition, hydrologic modification, and to a lesser extent, topography.

Regional regression models of watershed suspended-sediment discharge for the eastern United States

USGS Publications Warehouse

Roman, David C.; Vogel, Richard M.; Schwarz, Gregory E.

2012-01-01

Estimates of mean annual watershed sediment discharge, derived from long-term measurements of suspended-sediment concentration and streamflow, often are not available at locations of interest. The goal of this study was to develop multivariate regression models to enable prediction of mean annual suspended-sediment discharge from available basin characteristics useful for most ungaged river locations in the eastern United States. The models are based on long-term mean sediment discharge estimates and explanatory variables obtained from a combined dataset of 1201 US Geological Survey (USGS) stations derived from a SPAtially Referenced Regression on Watershed attributes (SPARROW) study and the Geospatial Attributes of Gages for Evaluating Streamflow (GAGES) database. The resulting regional regression models summarized for major US water resources regions 1–8, exhibited prediction R2 values ranging from 76.9% to 92.7% and corresponding average model prediction errors ranging from 56.5% to 124.3%. Results from cross-validation experiments suggest that a majority of the models will perform similarly to calibration runs. The 36-parameter regional regression models also outperformed a 16-parameter national SPARROW model of suspended-sediment discharge and indicate that mean annual sediment loads in the eastern United States generally correlates with a combination of basin area, land use patterns, seasonal precipitation, soil composition, hydrologic modification, and to a lesser extent, topography.

Differential exhumation at eastern margin of the Tibetan Plateau, from apatite fission-track thermochronology

NASA Astrophysics Data System (ADS)

Deng, Bin; Liu, Shu-gen; Li, Zhi-wu; Jansa, Luba F.; Liu, Shun; Wang, Guo-zhi; Sun, Wei

2013-04-01

New apatite fission-track (AFT) ages from Mesozoic sediments in the Sichuan basin, combined with previous fission-track data, demonstrate differential uplift and exhumation across the basin. Particularly significant change in exhumation (at least ~ 2000 m) was found across the Huaying Mts. Modeled temperature-time histories and the Boomerang plot of AFT dataset across the basin suggest rapid cooling and exhumation events during 120-80 Ma and at 20-10 Ma. They reflect the start of the basin-scale differential uplift and exhumation which effected the eastern growth of Tibetan Plateau. In particular, nested old-age center separated by Huaying Mts. was found in the center-to-northwest part of the Sichuan basin. A simplified one-dimensional, steady-state solution model was developed to calculate the mean exhumation rate, which is 0.05-0.2 mm/yr in most parts of the basin. It suggests a slow exhumation across much of the basin. The regional pattern of AFT age, length and erosion rate supports a progressive change from the nested old-age center towards the southwest. This pattern supports the idea of a prolonged, steady-state uplift and exhumation process across the basin, controlled by cratonic basin structure. The eastern growth of the Tibetan Plateau has exerted a significant effect on the rapid exhumation of the southwestern part of the Sichuan basin, but not on all of the basin during the Late Cenozoic.

The limits of seaward spreading and slope instability at the continental margin offshore Mt Etna, imaged by high-resolution 2D seismic data

NASA Astrophysics Data System (ADS)

Gross, Felix; Krastel, Sebastian; Geersen, Jacob; Behrmann, Jan Hinrich; Ridente, Domenico; Chiocci, Francesco Latino; Bialas, Jörg; Papenberg, Cord; Cukur, Deniz; Urlaub, Morelia; Micallef, Aaron

2016-01-01

Mount Etna is the largest active volcano in Europe. Instability of its eastern flank is well documented onshore, and continuously monitored by geodetic and InSAR measurements. Little is known, however, about the offshore extension of the eastern volcano flank, defining a serious shortcoming in stability models. In order to better constrain the active tectonics of the continental margin offshore the eastern flank of the volcano, we acquired a new high-resolution 2D reflection seismic dataset. The data provide new insights into the heterogeneous geology and tectonics at the continental margin offshore Mt Etna. The submarine realm is characterized by different blocks, which are controlled by local- and regional tectonics. A compressional regime is found at the toe of the continental margin, which is bound to a complex basin system. Both, the clear link between on- and offshore tectonic structures as well as the compressional regime at the easternmost flank edge, indicate a continental margin gravitational collapse as well as spreading to be present at Mt Etna. Moreover, we find evidence for the offshore southern boundary of the moving flank, which is identified as a right lateral oblique fault north of Catania Canyon. Our findings suggest a coupled volcano edifice/continental margin instability at Mt Etna, demonstrating first order linkage between on- and offshore tectonic processes.

Crystallographic Orientation Relationships (CORs) between rutile inclusions and garnet hosts: towards using COR frequencies as a petrogenetic indicator

NASA Astrophysics Data System (ADS)

Griffiths, Thomas; Habler, Gerlinde; Schantl, Philip; Abart, Rainer

2017-04-01

Crystallographic orientation relationships (CORs) between crystalline inclusions and their hosts are commonly used to support particular inclusion origins, but often interpretations are based on a small fraction of all inclusions in a system. The electron backscatter diffraction (EBSD) method allows collection of large COR datasets more quickly than other methods while maintaining high spatial resolution. Large datasets allow analysis of the relative frequencies of different CORs, and identification of 'statistical CORs', where certain limited degrees of freedom exist in the orientation relationship between two neighbour crystals (Griffiths et al. 2016). Statistical CORs exist in addition to completely fixed 'specific' CORs (previously the only type of COR considered). We present a comparison of three EBSD single point datasets (all N > 200 inclusions) of rutile inclusions in garnet hosts, covering three rock systems, each with a different geological history: 1) magmatic garnet in pegmatite from the Koralpe complex, Eastern Alps, formed at temperatures > 600°C and low pressures; 2) granulite facies garnet rims on ultra-high-pressure garnets from the Kimi complex, Rhodope Massif; and 3) a Moldanubian granulite from the southeastern Bohemian Massif, equilibrated at peak conditions of 1050°C and 1.6 GPa. The present study is unique because all datasets have been analysed using the same catalogue of potential CORs, therefore relative frequencies and other COR properties can be meaningfully compared. In every dataset > 94% of the inclusions analysed exhibit one of the CORs tested for. Certain CORs are consistently among the most common in all datasets. However, the relative abundances of these common CORs show large variations between datasets (varying from 8 to 42 % relative abundance in one case). Other CORs are consistently uncommon but nonetheless present in every dataset. Lastly, there are some CORs that are common in one of the datasets and rare in the remainder. These patterns suggest competing influences on relative COR frequencies. Certain CORs seem consistently favourable, perhaps pointing to very stable low energy configurations, whereas some CORs are favoured in only one system, perhaps due to particulars of the formation mechanism, kinetics or conditions. Variations in COR frequencies between datasets seem to correlate with the conditions of host-inclusion system evolution. The two datasets from granulite-facies metamorphic samples show more similarities to each other than to the pegmatite dataset, and the sample inferred to have experienced the highest temperatures (Moldanubian granulite) shows the lowest diversity of CORs, low frequencies of statistical CORs and the highest frequency of specific CORs. These results provide evidence that petrological information is being encoded in COR distributions. They make a strong case for further studies of the factors influencing COR development and for measurements of COR distributions in other systems and between different phases. Griffiths, T.A., Habler, G., Abart, R. (2016): Crystallographic orientation relationships in host-inclusion systems: New insights from large EBSD data sets. Amer. Miner., 101, 690-705.

A novel method for soil aggregate stability measurement by laser granulometry with sonication

NASA Astrophysics Data System (ADS)

Rawlins, B. G.; Lark, R. M.; Wragg, J.

2012-04-01

Regulatory authorities need to establish rapid, cost-effective methods to measure soil physical indicators - such as aggregate stability - which can be applied to large numbers of soil samples to detect changes of soil quality through monitoring. Limitations of sieve-based methods to measure the stability of soil macro-aggregates include: i) the mass of stable aggregates is measured, only for a few, discrete sieve/size fractions, ii) no account is taken of the fundamental particle size distribution of the sub-sampled material, and iii) they are labour intensive. These limitations could be overcome by measurements with a Laser Granulometer (LG) instrument, but this technology has not been widely applied to the quantification of aggregate stability of soils. We present a novel method to quantify macro-aggregate (1-2 mm) stability. We measure the difference between the mean weight diameter (MWD; μm) of aggregates that are stable in circulating water of low ionic strength, and the MWD of the fundamental particles of the soil to which these aggregates are reduced by sonication. The suspension is circulated rapidly through a LG analytical cell from a connected vessel for ten seconds; during this period hydrodynamic forces associated with the circulating water lead to the destruction of unstable aggregates. The MWD of stable aggregates is then measured by LG. In the next step, the aggregates - which are kept in the vessel at a minimal water circulation speed - are subject to sonication (18W for ten minutes) so the vast majority of the sample is broken down into its fundamental particles. The suspension is then recirculated rapidly through the LG and the MWD measured again. We refer to the difference between these two measurements as disaggregation reduction (DR) - the reduction in MWD on disaggregation by sonication. Soil types with more stable aggregates have larger values of DR. The stable aggregates - which are resistant to both slaking and mechanical breakdown by the hydrodynamic forces during circulation - are disrupted only by sonication. We used this method to compare macro-aggregate (1-2 mm) stability of air-dried agricultural topsoils under conventional tillage developed from two contrasting parent material types and compared the results with an alternative sieve-based technique. The first soil from the Midlands of England (developed from sedimentary mudstone; mean soil organic carbon (SOC) 2.5%) contained a substantially larger amount of illite/smectite (I/S) minerals compared to the second from the Wensum catchment in eastern England (developed from sands and glacial deposits; mean SOC=1.7%). The latter soils are prone to large erosive losses of fine sediment. Both sets of samples had been stored air-dried for 6 months prior to aggregate analyses. The mean values of DR (n=10 repeated subsample analyses) for the Midlands soil was 178μm; mean DR (n=10 repeat subsample analyses) for the Wensum soil was 30μm. The large difference in DR is most likely due to differences in soil mineralogy. The coefficient of variation of mean DR for duplicate analyses of sub-samples from the two topsoil types is around 10%. The majority of this variation is likely to be related to the difference in composition of the sub-samples. A standard, aggregated material could be included in further analyses to determine the relative magnitude of sub-sampling and analytical variance for this measurement technique. We then used the technique to investigate whether - as previously observed - variations (range 1000 - 4000 mg kg-1) in the quantity of amorphous (oxalate extractable) iron oxyhydroxides in a variety of soil samples (n=30) from the Wensum area (range SOC 1 - 2%) could account for differences in aggregate stability of these samples.

Application of the WRF-Chem model for the simulation of air quality over Cyprus

NASA Astrophysics Data System (ADS)

Kushta, Jonilda; Proestos, Yiannis; Georgiou, George; Christoudias, Theodoros; Lelieveld, Jos

2017-04-01

The fully coupled WRF-Chem (Weather Research and Forecasting with Chemistry) model is used to simulate air quality over Cyprus. Cyprus is an island country with complex topography, located in the eastern corner of East Mediterranean region, affected year-long by local, regional and long range transported pollution. An extensive sensitivity analysis of the model performance has been performed over the area of interest with three domains of respective grid spacing of 40, 8 and 2 km. Different configurations have been deployed regarding horizontal resolution, simulation timestep, boundary conditions, NOx emissions and speciation method of emitted NMVOCs (Non Methane Volatile Organic Compounds). The WRF-Chem model simulated hourly concentrations of air pollutants for a month-long period (July 2014) during which measurements are available over 13 stations (4 of which background stations, 1 industrial and 8 urban/traffic stations). The model was initialized with meteorological initial and boundary conditions (ICBC) using NCAR-NCEP's F Global Forecast System output (GFS) at a 1o x1o spatial resolution. The ICBC for the chemical species are derived from the MOZART global model results (2.5o x 2.5o). Both ICBCs datasets are updated every 6 hours. The emission inventory used in the study is the EDGAR-HTAP v2 dataset with a horizontal grid resolution of 0.1o × 0.1o, while an additional dataset with speciated NMVOCs (instead of summed volatile species) is also tested. The diurnal cycle of the atmospheric concentrations of ozone averaged over the island, exhibits a maximum of 114 μg/m3 when the boundary conditions are derived from MOZART and 94 μg/m3 when the boundary conditions are not included (local background and production), suggesting a constant inflow of ozone from long range transport of about 20 μg/m3. The contribution of pollution from regional sources is more pronounced at the western border due to the characteristic summer time north-northeasterly etesian flow that brings southward the pollution produced or accumulated over Eastern Europe, the Black sea and major upwind megacities (Istanbul, Athens etc). Ozone concentrations are overestimated in all stations indicating a possible overestimation of ozone from the global model (MOZART) that has also been discussed in other studies over neighbouring countries, or an excess of ozone production in the parent domain that includes all Eastern Mediterranean. Model results are influenced by the speciation of NMVOCs with the pre-speciated emission dataset resulting in lower ozone values by an average of 5 μg/m3. Lowering NOx emission brings ozone levels closer to observations; however this does not account for the overestimation of ozone since the respective comparison of NOx levels reveals strong underestimation of NOx (both NO and NO2) even before reducing them. Horizontal, vertical and temporal resolutions show smaller impact on changing the modelled patterns of ozone concentrations. The discrepancies between modelled and observed ozone over the main Cypriot urban areas point at the need for more detailed emission inventories, either in terms of spatial resolution and/or validation of absolute emitted values, and adjustments in the use of boundary conditions from global models.

ARK: Aggregation of Reads by K-Means for Estimation of Bacterial Community Composition.

PubMed

Koslicki, David; Chatterjee, Saikat; Shahrivar, Damon; Walker, Alan W; Francis, Suzanna C; Fraser, Louise J; Vehkaperä, Mikko; Lan, Yueheng; Corander, Jukka

2015-01-01

Estimation of bacterial community composition from high-throughput sequenced 16S rRNA gene amplicons is a key task in microbial ecology. Since the sequence data from each sample typically consist of a large number of reads and are adversely impacted by different levels of biological and technical noise, accurate analysis of such large datasets is challenging. There has been a recent surge of interest in using compressed sensing inspired and convex-optimization based methods to solve the estimation problem for bacterial community composition. These methods typically rely on summarizing the sequence data by frequencies of low-order k-mers and matching this information statistically with a taxonomically structured database. Here we show that the accuracy of the resulting community composition estimates can be substantially improved by aggregating the reads from a sample with an unsupervised machine learning approach prior to the estimation phase. The aggregation of reads is a pre-processing approach where we use a standard K-means clustering algorithm that partitions a large set of reads into subsets with reasonable computational cost to provide several vectors of first order statistics instead of only single statistical summarization in terms of k-mer frequencies. The output of the clustering is then processed further to obtain the final estimate for each sample. The resulting method is called Aggregation of Reads by K-means (ARK), and it is based on a statistical argument via mixture density formulation. ARK is found to improve the fidelity and robustness of several recently introduced methods, with only a modest increase in computational complexity. An open source, platform-independent implementation of the method in the Julia programming language is freely available at https://github.com/dkoslicki/ARK. A Matlab implementation is available at http://www.ee.kth.se/ctsoftware.

Potential for using regional and global datasets for national scale ecosystem service modelling

NASA Astrophysics Data System (ADS)

Maxwell, Deborah; Jackson, Bethanna

2016-04-01

Ecosystem service models are increasingly being used by planners and policy makers to inform policy development and decisions about national-level resource management. Such models allow ecosystem services to be mapped and quantified, and subsequent changes to these services to be identified and monitored. In some cases, the impact of small scale changes can be modelled at a national scale, providing more detailed information to decision makers about where to best focus investment and management interventions that could address these issues, while moving toward national goals and/or targets. National scale modelling often uses national (or local) data (for example, soils, landcover and topographical information) as input. However, there are some places where fine resolution and/or high quality national datasets cannot be easily obtained, or do not even exist. In the absence of such detailed information, regional or global datasets could be used as input to such models. There are questions, however, about the usefulness of these coarser resolution datasets and the extent to which inaccuracies in this data may degrade predictions of existing and potential ecosystem service provision and subsequent decision making. Using LUCI (the Land Utilisation and Capability Indicator) as an example predictive model, we examine how the reliability of predictions change when national datasets of soil, landcover and topography are substituted with coarser scale regional and global datasets. We specifically look at how LUCI's predictions of where water services, such as flood risk, flood mitigation, erosion and water quality, change when national data inputs are replaced by regional and global datasets. Using the Conwy catchment, Wales, as a case study, the land cover products compared are the UK's Land Cover Map (2007), the European CORINE land cover map and the ESA global land cover map. Soils products include the National Soil Map of England and Wales (NatMap) and the European Soils Database. NEXTmap elevation data, which covers the UK and parts of continental Europe, are compared to global AsterDEM and SRTM30 topographical products. While the regional and global datasets can be used to fill gaps in data requirements, the coarser resolution of these datasets means that there is greater aggregation of information over larger areas. This loss of detail impacts on the reliability of model output, particularly where significant discrepancies between datasets exist. The implications of this loss of detail in terms of spatial planning and decision making is discussed. Finally, in the context of broader development the need for better nationally and globally available data to allow LUCI and other ecosystem models to become more globally applicable is highlighted.

HCP: A Flexible CNN Framework for Multi-label Image Classification.

PubMed

Wei, Yunchao; Xia, Wei; Lin, Min; Huang, Junshi; Ni, Bingbing; Dong, Jian; Zhao, Yao; Yan, Shuicheng

2015-10-26

Convolutional Neural Network (CNN) has demonstrated promising performance in single-label image classification tasks. However, how CNN best copes with multi-label images still remains an open problem, mainly due to the complex underlying object layouts and insufficient multi-label training images. In this work, we propose a flexible deep CNN infrastructure, called Hypotheses-CNN-Pooling (HCP), where an arbitrary number of object segment hypotheses are taken as the inputs, then a shared CNN is connected with each hypothesis, and finally the CNN output results from different hypotheses are aggregated with max pooling to produce the ultimate multi-label predictions. Some unique characteristics of this flexible deep CNN infrastructure include: 1) no ground-truth bounding box information is required for training; 2) the whole HCP infrastructure is robust to possibly noisy and/or redundant hypotheses; 3) the shared CNN is flexible and can be well pre-trained with a large-scale single-label image dataset, e.g., ImageNet; and 4) it may naturally output multi-label prediction results. Experimental results on Pascal VOC 2007 and VOC 2012 multi-label image datasets well demonstrate the superiority of the proposed HCP infrastructure over other state-of-the-arts. In particular, the mAP reaches 90.5% by HCP only and 93.2% after the fusion with our complementary result in [44] based on hand-crafted features on the VOC 2012 dataset.

A comparison of three federal datasets for thermoelectric water withdrawals in the United States for 2010

USGS Publications Warehouse

Harris, Melissa A.; Diehl, Timothy H.

2017-01-01

Historically, thermoelectric water withdrawal has been estimated by the Energy Information Administration (EIA) and the U.S. Geological Survey's (USGS) water-use compilations. Recently, the USGS developed models for estimating withdrawal at thermoelectric plants to provide estimates independent from plant operator-reported withdrawal data. This article compares three federal datasets of thermoelectric withdrawals for the United States in 2010: one based on the USGS water-use compilation, another based on EIA data, and the third based on USGS model-estimated data. The withdrawal data varied widely. Many plants had three different withdrawal values, and for approximately 54% of the plants the largest withdrawal value was twice the smallest, or larger. The causes of discrepancies among withdrawal estimates included definitional differences, definitional noise, and various nondefinitional causes. The uncertainty in national totals can be characterized by the range among the three datasets, from 5,640 m3/s (129 billion gallons per day [bgd]) to 6,954 m3/s (158 bgd), or by the aggregate difference between the smallest and largest values at each plant, from 4,014 m3/s (92 bgd) to 8,590 m3/s (196 bgd). When used to assess the accuracy of reported values, the USGS model estimates identify plants that need to be reviewed.

USGS approach to real-time estimation of earthquake-triggered ground failure - Results of 2015 workshop

USGS Publications Warehouse

Allstadt, Kate E.; Thompson, Eric M.; Wald, David J.; Hamburger, Michael W.; Godt, Jonathan W.; Knudsen, Keith L.; Jibson, Randall W.; Jessee, M. Anna; Zhu, Jing; Hearne, Michael; Baise, Laurie G.; Tanyas, Hakan; Marano, Kristin D.

2016-03-30

The U.S. Geological Survey (USGS) Earthquake Hazards and Landslide Hazards Programs are developing plans to add quantitative hazard assessments of earthquake-triggered landsliding and liquefaction to existing real-time earthquake products (ShakeMap, ShakeCast, PAGER) using open and readily available methodologies and products. To date, prototype global statistical models have been developed and are being refined, improved, and tested. These models are a good foundation, but much work remains to achieve robust and defensible models that meet the needs of end users. In order to establish an implementation plan and identify research priorities, the USGS convened a workshop in Golden, Colorado, in October 2015. This document summarizes current (as of early 2016) capabilities, research and operational priorities, and plans for further studies that were established at this workshop. Specific priorities established during the meeting include (1) developing a suite of alternative models; (2) making use of higher resolution and higher quality data where possible; (3) incorporating newer global and regional datasets and inventories; (4) reducing barriers to accessing inventory datasets; (5) developing methods for using inconsistent or incomplete datasets in aggregate; (6) developing standardized model testing and evaluation methods; (7) improving ShakeMap shaking estimates, particularly as relevant to ground failure, such as including topographic amplification and accounting for spatial variability; and (8) developing vulnerability functions for loss estimates.

American mastodon extirpation in the Arctic and Subarctic predates human colonization and terminal Pleistocene climate change.

PubMed

Zazula, Grant D; MacPhee, Ross D E; Metcalfe, Jessica Z; Reyes, Alberto V; Brock, Fiona; Druckenmiller, Patrick S; Groves, Pamela; Harington, C Richard; Hodgins, Gregory W L; Kunz, Michael L; Longstaffe, Fred J; Mann, Daniel H; McDonald, H Gregory; Nalawade-Chavan, Shweta; Southon, John R

2014-12-30

Existing radiocarbon ((14)C) dates on American mastodon (Mammut americanum) fossils from eastern Beringia (Alaska and Yukon) have been interpreted as evidence they inhabited the Arctic and Subarctic during Pleistocene full-glacial times (∼ 18,000 (14)C years B.P.). However, this chronology is inconsistent with inferred habitat preferences of mastodons and correlative paleoecological evidence. To establish a last appearance date (LAD) for M. americanum regionally, we obtained 53 new (14)C dates on 36 fossils, including specimens with previously published dates. Using collagen ultrafiltration and single amino acid (hydroxyproline) methods, these specimens consistently date to beyond or near the ∼ 50,000 y B.P. limit of (14)C dating. Some erroneously "young" (14)C dates are due to contamination by exogenous carbon from natural sources and conservation treatments used in museums. We suggest mastodons inhabited the high latitudes only during warm intervals, particularly the Last Interglacial [Marine Isotope Stage (MIS) 5] when boreal forests existed regionally. Our (14)C dataset suggests that mastodons were extirpated from eastern Beringia during the MIS 4 glacial interval (∼ 75,000 y ago), following the ecological shift from boreal forest to steppe tundra. Mastodons thereafter became restricted to areas south of the continental ice sheets, where they suffered complete extinction ∼ 10,000 (14)C years B.P. Mastodons were already absent from eastern Beringia several tens of millennia before the first humans crossed the Bering Isthmus or the onset of climate changes during the terminal Pleistocene. Local extirpations of mastodons and other megafaunal populations in eastern Beringia were asynchrononous and independent of their final extinction south of the continental ice sheets.

American mastodon extirpation in the Arctic and Subarctic predates human colonization and terminal Pleistocene climate change

PubMed Central

Zazula, Grant D.; MacPhee, Ross D. E.; Metcalfe, Jessica Z.; Reyes, Alberto V.; Brock, Fiona; Druckenmiller, Patrick S.; Groves, Pamela; Harington, C. Richard; Hodgins, Gregory W. L.; Kunz, Michael L.; Longstaffe, Fred J.; Mann, Daniel H.; McDonald, H. Gregory; Nalawade-Chavan, Shweta; Southon, John R.

2014-01-01

Existing radiocarbon (14C) dates on American mastodon (Mammut americanum) fossils from eastern Beringia (Alaska and Yukon) have been interpreted as evidence they inhabited the Arctic and Subarctic during Pleistocene full-glacial times (∼18,000 14C years B.P.). However, this chronology is inconsistent with inferred habitat preferences of mastodons and correlative paleoecological evidence. To establish a last appearance date (LAD) for M. americanum regionally, we obtained 53 new 14C dates on 36 fossils, including specimens with previously published dates. Using collagen ultrafiltration and single amino acid (hydroxyproline) methods, these specimens consistently date to beyond or near the ∼50,000 y B.P. limit of 14C dating. Some erroneously “young” 14C dates are due to contamination by exogenous carbon from natural sources and conservation treatments used in museums. We suggest mastodons inhabited the high latitudes only during warm intervals, particularly the Last Interglacial [Marine Isotope Stage (MIS) 5] when boreal forests existed regionally. Our 14C dataset suggests that mastodons were extirpated from eastern Beringia during the MIS 4 glacial interval (∼75,000 y ago), following the ecological shift from boreal forest to steppe tundra. Mastodons thereafter became restricted to areas south of the continental ice sheets, where they suffered complete extinction ∼10,000 14C years B.P. Mastodons were already absent from eastern Beringia several tens of millennia before the first humans crossed the Bering Isthmus or the onset of climate changes during the terminal Pleistocene. Local extirpations of mastodons and other megafaunal populations in eastern Beringia were asynchrononous and independent of their final extinction south of the continental ice sheets. PMID:25453065

Spreading and slope instability at the continental margin offshore Mt Etna, imaged by high-resolution 2D seismic data

NASA Astrophysics Data System (ADS)

Gross, Felix; Krastel, Sebastian; Behrmann, Jan-Hinrich; Papenberg, Cord; Geersen, Jacob; Ridente, Domenico; Latino Chiocci, Francesco; Urlaub, Morelia; Bialas, Jörg; Micallef, Aaron

2015-04-01

Mount Etna is the largest active volcano in Europe. Its volcano edifice is located on top of continental crust close to the Ionian shore in east Sicily. Instability of the eastern flank of the volcano edifice is well documented onshore. The continental margin is supposed to deform as well. Little, however, is known about the offshore extension of the eastern volcano flank and its adjacent continental margin, which is a serious shortcoming in stability models. In order to better constrain the active tectonics of the continental margin offshore the eastern flank of the volcano, we acquired and processed a new marine high-resolution seismic and hydro-acoustic dataset. The data provide new detailed insights into the heterogeneous geology and tectonics of shallow continental margin structures offshore Mt Etna. In a similiar manner as observed onshore, the submarine realm is characterized by different blocks, which are controlled by local- and regional tectonics. We image a compressional regime at the toe of the continental margin, which is bound to an asymmetric basin system confining the eastward movement of the flank. In addition, we constrain the proposed southern boundary of the moving flank, which is identified as a right lateral oblique fault movement north of Catania Canyon. From our findings, we consider a major coupled volcano edifice instability and continental margin gravitational collapse and spreading to be present at Mt Etna, as we see a clear link between on- and offshore tectonic structures across the entire eastern flank. The new findings will help to evaluate hazards and risks accompanied by Mt Etna's slope- and continental margin instability and will be used as a base for future investigations in this region.

Middle Permian paleomagnetism of the Sydney Basin, Eastern Gondwana: Testing Pangea models and the timing of the end of the Kiaman Reverse Superchron

NASA Astrophysics Data System (ADS)

Belica, M. E.; Tohver, E.; Pisarevsky, S. A.; Jourdan, F.; Denyszyn, S.; George, A. D.

2017-03-01

Paleomagnetic and geochronologic data from the eastern margin of Gondwana have been obtained from the Gerringong Volcanics in the southern Sydney Basin, Australia. The corresponding paleomagnetic pole at 56.9°S, 154.8°E (N = 131; A95 = 9.1°) has a 40Ar/39Ar plagioclase plateau age of 265.05 ± 0.35 [0.46] Ma from the Bumbo Latite, and overlaps with recent radio-isotopic and paleomagnetic results published from Western Gondwana. The long-documented inconsistency between Middle Permian Eastern and Western Gondwanan paleomagnetic datasets is most likely an artefact of a lack of reliable paleomagnetic data from Eastern Gondwana for this period. A number of well-dated and recently published ca. 265 Ma paleomagnetic results from Gondwana and Laurussia are shown to be consistent with the Wegenerian Pangea A configuration, with a loose N-S fit of the continents for the Middle Permian. The lack of crustal overlap negates the need for a Pangea B configuration, which if valid must have been assembled to Pangea A by ca. 265 Ma. The reverse polarity Bumbo Latite was sampled from the Kiaman type-section located in the southern Sydney Basin. Three cases of normal polarity were detected in the overlying Saddleback, Dapto, and Berkeley Latites, previously assigned to the Kiaman Reverse Superchron (KRS). We review KRS-aged magnetostratigraphic data and propose that an age assignment of 265 Ma most likely represents the termination of the non-reversing field, with longer stable intervals of normal polarity recorded and able to be correlated globally.

Development of a risk index for prediction of abnormal pap test results in Serbia.

PubMed

Vukovic, Dejana; Antic, Ljiljana; Vasiljevic, Mladenko; Antic, Dragan; Matejic, Bojana

2015-01-01

Serbia is one of the countries with highest incidence and mortality rates for cervical cancer in Central and South Eastern Europe. Introducing a risk index could provide a powerful means for targeting groups at high likelihood of having an abnormal cervical smear and increase efficiency of screening. The aim of the present study was to create and assess validity ofa index for prediction of an abnormal Pap test result. The study population was drawn from patients attending Departments for Women's Health in two primary health care centers in Serbia. Out of 525 respondents 350 were randomly selected and data obtained from them were used as the index creation dataset. Data obtained from the remaining 175 were used as an index validation data set. Age at first intercourse under 18, more than 4 sexual partners, history of STD and multiparity were attributed statistical weights 16, 15, 14 and 13, respectively. The distribution of index scores in index-creation data set showed that most respondents had a score 0 (54.9%). In the index-creation dataset mean index score was 10.3 (SD-13.8), and in the validation dataset the mean was 9.1 (SD=13.2). The advantage of such scoring system is that it is simple, consisting of only four elements, so it could be applied to identify women with high risk for cervical cancer that would be referred for further examination.

Learning analytics: Dataset for empirical evaluation of entry requirements into engineering undergraduate programs in a Nigerian university.

PubMed

Odukoya, Jonathan A; Popoola, Segun I; Atayero, Aderemi A; Omole, David O; Badejo, Joke A; John, Temitope M; Olowo, Olalekan O

2018-04-01

In Nigerian universities, enrolment into any engineering undergraduate program requires that the minimum entry criteria established by the National Universities Commission (NUC) must be satisfied. Candidates seeking admission to study engineering discipline must have reached a predetermined entry age and met the cut-off marks set for Senior School Certificate Examination (SSCE), Unified Tertiary Matriculation Examination (UTME), and the post-UTME screening. However, limited effort has been made to show that these entry requirements eventually guarantee successful academic performance in engineering programs because the data required for such validation are not readily available. In this data article, a comprehensive dataset for empirical evaluation of entry requirements into engineering undergraduate programs in a Nigerian university is presented and carefully analyzed. A total sample of 1445 undergraduates that were admitted between 2005 and 2009 to study Chemical Engineering (CHE), Civil Engineering (CVE), Computer Engineering (CEN), Electrical and Electronics Engineering (EEE), Information and Communication Engineering (ICE), Mechanical Engineering (MEE), and Petroleum Engineering (PET) at Covenant University, Nigeria were randomly selected. Entry age, SSCE aggregate, UTME score, Covenant University Scholastic Aptitude Screening (CUSAS) score, and the Cumulative Grade Point Average (CGPA) of the undergraduates were obtained from the Student Records and Academic Affairs unit. In order to facilitate evidence-based evaluation, the robust dataset is made publicly available in a Microsoft Excel spreadsheet file. On yearly basis, first-order descriptive statistics of the dataset are presented in tables. Box plot representations, frequency distribution plots, and scatter plots of the dataset are provided to enrich its value. Furthermore, correlation and linear regression analyses are performed to understand the relationship between the entry requirements and the corresponding academic performance in engineering programs. The data provided in this article will help Nigerian universities, the NUC, engineering regulatory bodies, and relevant stakeholders to objectively evaluate and subsequently improve the quality of engineering education in the country.

Economic development, flow of funds, and the equilibrium interaction of financial frictions.

PubMed

Moll, Benjamin; Townsend, Robert M; Zhorin, Victor

2017-06-13

We use a variety of different datasets from Thailand to study not only the extremes of micro and macro variables but also within-country flow of funds and labor migration. We develop a general equilibrium model that encompasses regional variation in the type of financial friction and calibrate it to measured variation in regional aggregates. The model predicts substantial capital and labor flows from rural to urban areas even though these differ only in the underlying financial regime. Predictions for micro variables not used directly provide a model validation. Finally, we estimate the impact of a policy of counterfactual, regional isolationism.

WebGLORE: a web service for Grid LOgistic REgression.

PubMed

Jiang, Wenchao; Li, Pinghao; Wang, Shuang; Wu, Yuan; Xue, Meng; Ohno-Machado, Lucila; Jiang, Xiaoqian

2013-12-15

WebGLORE is a free web service that enables privacy-preserving construction of a global logistic regression model from distributed datasets that are sensitive. It only transfers aggregated local statistics (from participants) through Hypertext Transfer Protocol Secure to a trusted server, where the global model is synthesized. WebGLORE seamlessly integrates AJAX, JAVA Applet/Servlet and PHP technologies to provide an easy-to-use web service for biomedical researchers to break down policy barriers during information exchange. http://dbmi-engine.ucsd.edu/webglore3/. WebGLORE can be used under the terms of GNU general public license as published by the Free Software Foundation.

MIRA: An R package for DNA methylation-based inference of regulatory activity.

PubMed

Lawson, John T; Tomazou, Eleni M; Bock, Christoph; Sheffield, Nathan C

2018-03-01

DNA methylation contains information about the regulatory state of the cell. MIRA aggregates genome-scale DNA methylation data into a DNA methylation profile for independent region sets with shared biological annotation. Using this profile, MIRA infers and scores the collective regulatory activity for each region set. MIRA facilitates regulatory analysis in situations where classical regulatory assays would be difficult and allows public sources of open chromatin and protein binding regions to be leveraged for novel insight into the regulatory state of DNA methylation datasets. R package available on Bioconductor: http://bioconductor.org/packages/release/bioc/html/MIRA.html. nsheffield@virginia.edu.

The pension incentive to retire: empirical evidence for West Germany.

PubMed

Siddiqui, S

1997-01-01

"In this paper, the impact of the West German pension system on the retirement decisions of elderly citizens is analyzed within the framework of a discrete-time hazard rate model deduced from a micro-economic decision rule. The model is estimated using a panel dataset of elderly West German citizens. In order to improve the precision of the estimates obtained, the data from the sample are combined with aggregate-level information on the labour force participation behaviour of the elderly. Policy simulations based on the estimates reveal that the probability of early retirement can be reduced significantly by appropriate changes in the pension system." excerpt

Economic development, flow of funds, and the equilibrium interaction of financial frictions

PubMed Central

Moll, Benjamin; Townsend, Robert M.; Zhorin, Victor

2017-01-01

We use a variety of different datasets from Thailand to study not only the extremes of micro and macro variables but also within-country flow of funds and labor migration. We develop a general equilibrium model that encompasses regional variation in the type of financial friction and calibrate it to measured variation in regional aggregates. The model predicts substantial capital and labor flows from rural to urban areas even though these differ only in the underlying financial regime. Predictions for micro variables not used directly provide a model validation. Finally, we estimate the impact of a policy of counterfactual, regional isolationism. PMID:28592655

Pacific Northwest (PNW) Hydrologic Landscape (HL) polygons and HL code

EPA Pesticide Factsheets

A five-letter hydrologic landscape code representing five indices of hydrologic form that are related to hydrologic function: climate, seasonality, aquifer permeability, terrain, and soil permeability. Each hydrologic assessment unit is classified by one of the 81 different five-letter codes representing these indices. Polygon features in this dataset were created by aggregating (dissolving boundaries between) adjacent, similarly-coded hydrologic assessment units. Climate Classes: V-Very wet, W-Wet, M-Moist, D-Dry, S-Semiarid, A-Arid. Seasonality Sub-Classes: w-Fall or winter, s-Spring. Aquifer Permeability Classes: H-High, L-Low. Terrain Classes: M-Mountain, T-Transitional, F-Flat. Soil Permeability Classes: H-High, L-Low.

An integrated pan-tropical biomass map using multiple reference datasets.

PubMed

Avitabile, Valerio; Herold, Martin; Heuvelink, Gerard B M; Lewis, Simon L; Phillips, Oliver L; Asner, Gregory P; Armston, John; Ashton, Peter S; Banin, Lindsay; Bayol, Nicolas; Berry, Nicholas J; Boeckx, Pascal; de Jong, Bernardus H J; DeVries, Ben; Girardin, Cecile A J; Kearsley, Elizabeth; Lindsell, Jeremy A; Lopez-Gonzalez, Gabriela; Lucas, Richard; Malhi, Yadvinder; Morel, Alexandra; Mitchard, Edward T A; Nagy, Laszlo; Qie, Lan; Quinones, Marcela J; Ryan, Casey M; Ferry, Slik J W; Sunderland, Terry; Laurin, Gaia Vaglio; Gatti, Roberto Cazzolla; Valentini, Riccardo; Verbeeck, Hans; Wijaya, Arief; Willcock, Simon

2016-04-01

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets. © 2015 John Wiley & Sons Ltd.

The rise of agrarian capitalism and the decline of family farming in England.

PubMed

Shaw-Taylor, Leigh

2012-01-01

Historians have documented rising farm sizes throughout the period 1450–1850. Existing studies have revealed much about the mechanisms underlying the development of agrarian capitalism. However, we currently lack any consensus as to when the critical developments occurred. This is largely due to the absence of sufficiently large and geographically wide-ranging datasets but is also attributable to conceptual weaknesses in much of the literature. This article develops a new approach to the problem and argues that agrarian capitalism was dominant in southern and eastern England by 1700 but that in northern England the critical developments came later.

Contribution of Road Grade to the Energy Use of Modern Automobiles Across Large Datasets of Real-World Drive Cycles: Preprint

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

Wood, E.; Burton, E.; Duran, A.

Understanding the real-world power demand of modern automobiles is of critical importance to engineers using modeling and simulation to inform the intelligent design of increasingly efficient powertrains. Increased use of global positioning system (GPS) devices has made large scale data collection of vehicle speed (and associated power demand) a reality. While the availability of real-world GPS data has improved the industry's understanding of in-use vehicle power demand, relatively little attention has been paid to the incremental power requirements imposed by road grade. This analysis quantifies the incremental efficiency impacts of real-world road grade by appending high fidelity elevation profiles tomore » GPS speed traces and performing a large simulation study. Employing a large real-world dataset from the National Renewable Energy Laboratory's Transportation Secure Data Center, vehicle powertrain simulations are performed with and without road grade under five vehicle models. Aggregate results of this study suggest that road grade could be responsible for 1% to 3% of fuel use in light-duty automobiles.« less

Exploratory spatial data analysis of global MODIS active fire data

NASA Astrophysics Data System (ADS)

Oom, D.; Pereira, J. M. C.

2013-04-01

We performed an exploratory spatial data analysis (ESDA) of autocorrelation patterns in the NASA MODIS MCD14ML Collection 5 active fire dataset, for the period 2001-2009, at the global scale. The dataset was screened, resulting in an annual rate of false alarms and non-vegetation fires ranging from a minimum of 3.1% in 2003 to a maximum of 4.4% in 2001. Hot bare soils and gas flares were the major sources of false alarms and non-vegetation fires. The data were aggregated at 0.5° resolution for the global and local spatial autocorrelation Fire counts were found to be positively correlated up to distances of around 200 km, and negatively for larger distances. A value of 0.80 (p = 0.001, α = 0.05) for Moran's I indicates strong spatial autocorrelation between fires at global scale, with 60% of all cells displaying significant positive or negative spatial correlation. Different types of spatial autocorrelation were mapped and regression diagnostics allowed for the identification of spatial outlier cells, with fire counts much higher or lower than expected, considering their spatial context.

Portfolio optimization for seed selection in diverse weather scenarios.

PubMed

Marko, Oskar; Brdar, Sanja; Panić, Marko; Šašić, Isidora; Despotović, Danica; Knežević, Milivoje; Crnojević, Vladimir

2017-01-01

The aim of this work was to develop a method for selection of optimal soybean varieties for the American Midwest using data analytics. We extracted the knowledge about 174 varieties from the dataset, which contained information about weather, soil, yield and regional statistical parameters. Next, we predicted the yield of each variety in each of 6,490 observed subregions of the Midwest. Furthermore, yield was predicted for all the possible weather scenarios approximated by 15 historical weather instances contained in the dataset. Using predicted yields and covariance between varieties through different weather scenarios, we performed portfolio optimisation. In this way, for each subregion, we obtained a selection of varieties, that proved superior to others in terms of the amount and stability of yield. According to the rules of Syngenta Crop Challenge, for which this research was conducted, we aggregated the results across all subregions and selected up to five soybean varieties that should be distributed across the network of seed retailers. The work presented in this paper was the winning solution for Syngenta Crop Challenge 2017.

Social relations or social capital? Individual and community health effects of bonding social capital.

PubMed

Poortinga, Wouter

2006-07-01

Social capital has become one of the most popular topics in public health research in recent years. However, even after a decade of conceptual and empirical work on this subject, there is still considerable disagreement about whether bonding social capital is a collective resource that benefits communities or societies, or whether its health benefits are associated with people, their personal networks and support. Using data from the 2000 and 2002 Health Survey for England this study found that, in line with earlier research, personal levels of social support contribute to a better self-reported health status. The study also suggests that social capital is additionally important for people's health. In both datasets the aggregate social trust variable was significantly related to self-rated health before and after controlling for differences in socio-demographics and/or individual levels of social support. The results were corroborated in the second dataset with an alternative indicator of social capital. These results show that bonding social capital collectively contributes to people's self-rated health over and above the beneficial effects of personal social networks and support.

Cloud-based Predictive Modeling System and its Application to Asthma Readmission Prediction

PubMed Central

Chen, Robert; Su, Hang; Khalilia, Mohammed; Lin, Sizhe; Peng, Yue; Davis, Tod; Hirsh, Daniel A; Searles, Elizabeth; Tejedor-Sojo, Javier; Thompson, Michael; Sun, Jimeng

2015-01-01

The predictive modeling process is time consuming and requires clinical researchers to handle complex electronic health record (EHR) data in restricted computational environments. To address this problem, we implemented a cloud-based predictive modeling system via a hybrid setup combining a secure private server with the Amazon Web Services (AWS) Elastic MapReduce platform. EHR data is preprocessed on a private server and the resulting de-identified event sequences are hosted on AWS. Based on user-specified modeling configurations, an on-demand web service launches a cluster of Elastic Compute 2 (EC2) instances on AWS to perform feature selection and classification algorithms in a distributed fashion. Afterwards, the secure private server aggregates results and displays them via interactive visualization. We tested the system on a pediatric asthma readmission task on a de-identified EHR dataset of 2,967 patients. We conduct a larger scale experiment on the CMS Linkable 2008–2010 Medicare Data Entrepreneurs’ Synthetic Public Use File dataset of 2 million patients, which achieves over 25-fold speedup compared to sequential execution. PMID:26958172

Portrayed emotions in the movie "Forrest Gump"

PubMed Central

Boennen, Manuel; Mareike, Gehrke; Golz, Madleen; Hartigs, Benita; Hoffmann, Nico; Keil, Sebastian; Perlow, Malú; Peukmann, Anne Katrin; Rabe, Lea Noell; von Sobbe, Franca-Rosa; Hanke, Michael

2015-01-01

Here we present a dataset with a description of portrayed emotions in the movie ”Forrest Gump”. A total of 12 observers independently annotated emotional episodes regarding their temporal location and duration. The nature of an emotion was characterized with basic attributes, such as arousal and valence, as well as explicit emotion category labels. In addition, annotations include a record of the perceptual evidence for the presence of an emotion. Two variants of the movie were annotated separately: 1) an audio-movie version of Forrest Gump that has been used as a stimulus for the acquisition of a large public functional brain imaging dataset, and 2) the original audio-visual movie. We present reliability and consistency estimates that suggest that both stimuli can be used to study visual and auditory emotion cue processing in real-life like situations. Raw annotations from all observers are publicly released in full in order to maximize their utility for a wide range of applications and possible future extensions. In addition, aggregate time series of inter-observer agreement with respect to particular attributes of portrayed emotions are provided to facilitate adoption of these data. PMID:25977755

An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

NASA Astrophysics Data System (ADS)

Song, M.; Li, W.; Zhou, X.

2014-12-01

In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.

A fusion network for semantic segmentation using RGB-D data

NASA Astrophysics Data System (ADS)

Yuan, Jiahui; Zhang, Kun; Xia, Yifan; Qi, Lin; Dong, Junyu

2018-04-01

Semantic scene parsing is considerable in many intelligent field, including perceptual robotics. For the past few years, pixel-wise prediction tasks like semantic segmentation with RGB images has been extensively studied and has reached very remarkable parsing levels, thanks to convolutional neural networks (CNNs) and large scene datasets. With the development of stereo cameras and RGBD sensors, it is expected that additional depth information will help improving accuracy. In this paper, we propose a semantic segmentation framework incorporating RGB and complementary depth information. Motivated by the success of fully convolutional networks (FCN) in semantic segmentation field, we design a fully convolutional networks consists of two branches which extract features from both RGB and depth data simultaneously and fuse them as the network goes deeper. Instead of aggregating multiple model, our goal is to utilize RGB data and depth data more effectively in a single model. We evaluate our approach on the NYU-Depth V2 dataset, which consists of 1449 cluttered indoor scenes, and achieve competitive results with the state-of-the-art methods.

Portfolio optimization for seed selection in diverse weather scenarios

PubMed Central

Brdar, Sanja; Panić, Marko; Šašić, Isidora; Despotović, Danica; Knežević, Milivoje; Crnojević, Vladimir

2017-01-01

The aim of this work was to develop a method for selection of optimal soybean varieties for the American Midwest using data analytics. We extracted the knowledge about 174 varieties from the dataset, which contained information about weather, soil, yield and regional statistical parameters. Next, we predicted the yield of each variety in each of 6,490 observed subregions of the Midwest. Furthermore, yield was predicted for all the possible weather scenarios approximated by 15 historical weather instances contained in the dataset. Using predicted yields and covariance between varieties through different weather scenarios, we performed portfolio optimisation. In this way, for each subregion, we obtained a selection of varieties, that proved superior to others in terms of the amount and stability of yield. According to the rules of Syngenta Crop Challenge, for which this research was conducted, we aggregated the results across all subregions and selected up to five soybean varieties that should be distributed across the network of seed retailers. The work presented in this paper was the winning solution for Syngenta Crop Challenge 2017. PMID:28863173

Worldwide Distribution of Cytochrome P450 Alleles: A Meta-analysis of Population-scale Sequencing Projects.

PubMed

Zhou, Y; Ingelman-Sundberg, M; Lauschke, V M

2017-10-01

Genetic polymorphisms in cytochrome P450 (CYP) genes can result in altered metabolic activity toward a plethora of clinically important medications. Thus, single nucleotide variants and copy number variations in CYP genes are major determinants of drug pharmacokinetics and toxicity and constitute pharmacogenetic biomarkers for drug dosing, efficacy, and safety. Strikingly, the distribution of CYP alleles differs considerably between populations with important implications for personalized drug therapy and healthcare programs. To provide a global distribution map of CYP alleles with clinical importance, we integrated whole-genome and exome sequencing data from 56,945 unrelated individuals of five major human populations. By combining this dataset with population-specific linkage information, we derive the frequencies of 176 CYP haplotypes, providing an extensive resource for major genetic determinants of drug metabolism. Furthermore, we aggregated this dataset into spectra of predicted functional variability in the respective populations and discuss the implications for population-adjusted pharmacological treatment strategies. © 2017 The Authors Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Evaluation of bulk heat fluxes from atmospheric datasets

NASA Astrophysics Data System (ADS)

Farmer, Benton

Heat fluxes at the air-sea interface are an important component of the Earth's heat budget. In addition, they are an integral factor in determining the sea surface temperature (SST) evolution of the oceans. Different representations of these fluxes are used in both the atmospheric and oceanic communities for the purpose of heat budget studies and, in particular, for forcing oceanic models. It is currently difficult to quantify the potential impact varying heat flux representations have on the ocean response. In this study, a diagnostic tool is presented that allows for a straightforward comparison of surface heat flux formulations and atmospheric data sets. Two variables, relaxation time (RT) and the apparent temperature (T*), are derived from the linearization of the bulk formulas. They are then calculated to compare three bulk formulae and five atmospheric datasets. Additionally, the linearization is expanded to the second order to compare the amount of residual flux present. It is found that the use of a bulk formula employing a constant heat transfer coefficient produces longer relaxation times and contains a greater amount of residual flux in the higher order terms of the linearization. Depending on the temperature difference, the residual flux remaining in the second order and above terms can reach as much as 40--50% of the total residual on a monthly time scale. This is certainly a non-negligible residual flux. In contrast, a bulk formula using a stability and wind dependent transfer coefficient retains much of the total flux in the first order term, as only a few percent remain in the residual flux. Most of the difference displayed among the bulk formulas stems from the sensitivity to wind speed and the choice of a constant or spatially varying transfer coefficient. Comparing the representation of RT and T* provides insight into the differences among various atmospheric datasets. In particular, the representations of the western boundary current, upwelling, and the Indian monsoon regions of the oceans have distinct characteristics within each dataset. Localized regions, such as the eastern Mexican and Central American coasts, are also shown to have variability among the datasets. The use of this technique for the evaluation of bulk formulae and datasets is an efficient method for identifying the unique characteristics of each. Furthermore, insight into the heat fluxes produced by particular bulk formula or dataset can be gained.

Where did Roman masons get their material from? A preliminary DRIFTS/PCA investigation on mortar aggregates from X Regio buildings in the Veneto area (NE Italy) and their potential sources.

PubMed

De Lorenzi Pezzolo, Alessandra; Colombi, Michela; Mazzocchin, Gian Antonio

2018-05-22

In this work, preliminary results are presented of an ongoing investigation aiming to identify the possible material sources employed by ancient Romans in their building activity in the X Regio, the European region corresponding to present north-eastern Italy and Istria (Croatia and Slovenia). The 63-420 μm fraction of the aggregate component recovered from eleven mortar fragments of buildings located in the Veneto area (in or close to Lio Piccolo, Vicenza, and Padua) is studied by diffuse reflection infrared Fourier transform spectroscopy and compared through principal component analysis to samples collected from local potential sources of raw materials. In this regard, the investigated samples from Lio Piccolo present a distinctive complexity, being this site located within the Venice lagoon, an area that has since been undergoing dramatic changes both due to natural and anthropic causes. The Vicenza and Padua sites were considered for comparison sake because they are or were located close to two rivers, the Bacchiglione and the Brenta, that in ancient times flowed into the Venice lagoon. As expected, from the exploratory investigation reported here, no firm conclusions can be obtained for the mortar samples collected in Lio Piccolo, whereas the likely provenance of the aggregate component of the samples from Vicenza and Padova from the Bacchiglione and the Brenta riverbeds, respectively, is confirmed.

Smap Soil Moisture Data Assimilation for the Continental United States and Eastern Africa

NASA Astrophysics Data System (ADS)

Blankenship, C. B.; Case, J.; Zavodsky, B.; Crosson, W. L.

2016-12-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center manages near-real-time runs of the Noah Land Surface Model within the NASA Land Information System (LIS) over Continental U.S. (CONUS) and Eastern Africa domains. Soil moisture products from the CONUS model run are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. The baseline LIS configuration is the Noah model driven by atmospheric and combined radar/gauge precipitation analyses, and input satellite-derived real-time green vegetation fraction on a 3-km grid for the CONUS. This configuration is being enhanced by adding the assimilation of Level 2 Soil Moisture Active/Passive (SMAP) soil moisture retrievals in a parallel run beginning on 1 April 2015. Our implementation of SMAP assimilation includes a cumulative distribution function (CDF) matching approach that aggregates points with similar soil types. This method allows creation of robust CDFs with a short data record, and also permits the correction of local anomalies that may arise from poor forcing data (e.g., quality-control problems with rain gauges). Validation results using in situ soil monitoring networks in the CONUS are shown, with comparisons to the baseline SPoRT-LIS run. Initial results are also presented from a modeling run in eastern Africa, forced by Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation data. Strategies for spatial downscaling and for dealing with effective depth of the retrieval product are also discussed.

Land area change analysis following hurricane impacts in Delacroix, Louisiana, 2004--2009

USGS Publications Warehouse

Palaseanu-Lovejoy, Monica; Kranenburg, Christine J.; Brock, John C.

2012-01-01

The purpose of this project is to provide improved estimates of Louisiana wetland land loss due to hurricane impacts between 2004 and 2009 based upon a change detection mapping analysis that incorporates pre- and post-landfall (Hurricanes Katrina, Rita, Gustav, and Ike) fractional water classification of a combination of high resolution (QuickBird, IKONOS and Geoeye-1) and medium resolution (Landsat) satellite imagery. This second dataset focuses on Hurricanes Katrina and Gustav, which made landfall on August 29, 2005, and September 1, 2008, respectively. The study area is an approximately 1208-square-kilometer region surrounding Delacroix, Louisiana, in the eastern Delta Plain. Overall, 77 percent of the area remained unchanged between 2004 and 2009, and over 11 percent of the area was changed permanently by Hurricane Katrina (including both land gain and loss). Less than 3 percent was affected, either temporarily or permanently, by Hurricane Gustav. A related dataset (SIM 3141) focused on Hurricane Rita, which made landfall on the Louisiana/Texas border on September 24, 2005, as a Category 3 hurricane.

Reported Historic Asbestos Mines, Historic Asbestos Prospects, and Other Natural Occurrences of Asbestos in Oregon and Washington

USGS Publications Warehouse

Van Gosen, Bradley S.

2010-01-01

This map and its accompanying dataset provide information for 51 natural occurrences of asbestos in Washington and Oregon, using descriptions found in the geologic literature. Data on location, mineralogy, geology, and relevant literature for each asbestos site are provided. Using the map and digital data in this report, the user can examine the distribution of previously reported asbestos occurrences and their geological characteristics in the Pacific Northwest States of Washington and Oregon. This report is part of an ongoing study by the U.S. Geological Survey to identify and map reported natural asbestos occurrences in the United States, which thus far includes similar maps and datasets of natural asbestos occurrences within the Eastern United States (http://pubs.usgs.gov/of/2005/1189/), the Central United States (http://pubs.usgs.gov/of/2006/1211/), the Rocky Mountain States (http://pubs.usgs.gov/of/2007/1182/), and the Southwestern United States (http://pubs.usgs.gov/of/2008/1095/). These reports are intended to provide State and local government agencies and other stakeholders with geologic information on natural occurrences of asbestos in the United States.

Reported Historic Asbestos Mines, Historic Asbestos Prospects, and Natural Asbestos Occurrences in the Southwestern United States (Arizona, Nevada, and Utah)

USGS Publications Warehouse

Van Gosen, Bradley S.

2008-01-01

This map and its accompanying dataset provide information for 113 natural asbestos occurrences in the Southwestern United States (U.S.), using descriptions found in the geologic literature. Data on location, mineralogy, geology, and relevant literature for each asbestos site are provided. Using the map and digital data in this report, the user can examine the distribution of previously reported asbestos occurrences and their geological characteristics in the Southwestern U.S., which includes sites in Arizona, Nevada, and Utah. This report is part of an ongoing study by the U.S. Geological Survey to identify and map reported natural asbestos occurrences in the U.S., which thus far includes similar maps and datasets of natural asbestos occurrences within the Eastern U.S. (http://pubs.usgs.gov/of/2005/1189/), the Central U.S. (http://pubs.usgs.gov/of/2006/1211/), and the Rocky Mountain States (http://pubs.usgs.gov/of/2007/1182/. These reports are intended to provide State and local government agencies and other stakeholders with geologic information on natural occurrences of asbestos in the U.S.

Reported Historic Asbestos Mines, Historic Asbestos Prospects, and Natural Asbestos Occurrences in the Rocky Mountain States of the United States (Colorado, Idaho, Montana, New Mexico, and Wyoming)

USGS Publications Warehouse

Van Gosen, Bradley S.

2007-01-01

This map and its accompanying dataset provide information for 48 natural asbestos occurrences in the Rocky Mountain States of the United States (U.S.), using descriptions found in the geologic literature. Data on location, mineralogy, geology, and relevant literature for each asbestos site are provided. Using the map and digital data in this report, the user can examine the distribution of previously reported asbestos occurrences and their geological characteristics in the Rocky Mountain States. This report is part of an ongoing study by the U.S. Geological Survey to identify and map reported natural asbestos occurrences in the U.S., which thus far includes similar maps and datasets of natural asbestos occurrences within the Eastern U.S. (http://pubs.usgs.gov/of/2005/1189/) and the Central U.S. (http://pubs.usgs.gov/of/2006/1211/). These reports are intended to provide State and local government agencies and other stakeholders with geologic information on natural occurrences of asbestos in the U.S.

Inner Core Tomography Under Africa

NASA Astrophysics Data System (ADS)

Irving, J. C. E.

2014-12-01

Hemispherical structure in the inner core has been observed using both normal mode and body wave data, but the more regional scale properties of the inner core are still the subject of ongoing debate. The nature of the vertical boundary regions between the eastern and western hemispheres will be an important constraint on dynamical processes at work in the inner core. With limited data available, earlier inner core studies defined each boundary using one line of longitude, but this may not be a sufficient description for what could be one of the inner core's most heterogeneous regions. Here, I present a large, hand-picked dataset of PKPbc-PKPdf differential travel times which sample the inner core under Africa, where the proposed position of one hemisphere boundary is located. The dataset contains polar, intermediate and equatorial rays through the inner core, and the presence of crossing raypaths makes regional-scale tomography of the inner core feasible. I invert the data to find regional variations in inner core anisotropy under different parts of Africa, and present both anisotropy and voigt isotropic velocity variations of this important portion of the inner core.

A correlation comparison between Altmetric Attention Scores and citations for six PLOS journals

PubMed Central

Huang, Wenya; Wang, Peiling

2018-01-01

This study considered all articles published in six Public Library of Science (PLOS) journals in 2012 and Web of Science citations for these articles as of May 2015. A total of 2,406 articles were analyzed to examine the relationships between Altmetric Attention Scores (AAS) and Web of Science citations. The AAS for an article, provided by Altmetric aggregates activities surrounding research outputs in social media (news outlet mentions, tweets, blogs, Wikipedia, etc.). Spearman correlation testing was done on all articles and articles with AAS. Further analysis compared the stratified datasets based on percentile ranks of AAS: top 50%, top 25%, top 10%, and top 1%. Comparisons across the six journals provided additional insights. The results show significant positive correlations between AAS and citations with varied strength for all articles and articles with AAS (or social media mentions), as well as for normalized AAS in the top 50%, top 25%, top 10%, and top 1% datasets. Four of the six PLOS journals, Genetics, Pathogens, Computational Biology, and Neglected Tropical Diseases, show significant positive correlations across all datasets. However, for the two journals with high impact factors, PLOS Biology and Medicine, the results are unexpected: the Medicine articles showed no significant correlations but the Biology articles tested positive for correlations with the whole dataset and the set with AAS. Both journals published substantially fewer articles than the other four journals. Further research to validate the AAS algorithm, adjust the weighting scheme, and include appropriate social media sources is needed to understand the potential uses and meaning of AAS in different contexts and its relationship to other metrics. PMID:29621253

High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms

PubMed Central

Teodoro, George; Pan, Tony; Kurc, Tahsin M.; Kong, Jun; Cooper, Lee A. D.; Podhorszki, Norbert; Klasky, Scott; Saltz, Joel H.

2014-01-01

Analysis of large pathology image datasets offers significant opportunities for the investigation of disease morphology, but the resource requirements of analysis pipelines limit the scale of such studies. Motivated by a brain cancer study, we propose and evaluate a parallel image analysis application pipeline for high throughput computation of large datasets of high resolution pathology tissue images on distributed CPU-GPU platforms. To achieve efficient execution on these hybrid systems, we have built runtime support that allows us to express the cancer image analysis application as a hierarchical data processing pipeline. The application is implemented as a coarse-grain pipeline of stages, where each stage may be further partitioned into another pipeline of fine-grain operations. The fine-grain operations are efficiently managed and scheduled for computation on CPUs and GPUs using performance aware scheduling techniques along with several optimizations, including architecture aware process placement, data locality conscious task assignment, data prefetching, and asynchronous data copy. These optimizations are employed to maximize the utilization of the aggregate computing power of CPUs and GPUs and minimize data copy overheads. Our experimental evaluation shows that the cooperative use of CPUs and GPUs achieves significant improvements on top of GPU-only versions (up to 1.6×) and that the execution of the application as a set of fine-grain operations provides more opportunities for runtime optimizations and attains better performance than coarser-grain, monolithic implementations used in other works. An implementation of the cancer image analysis pipeline using the runtime support was able to process an image dataset consisting of 36,848 4Kx4K-pixel image tiles (about 1.8TB uncompressed) in less than 4 minutes (150 tiles/second) on 100 nodes of a state-of-the-art hybrid cluster system. PMID:25419546

Nuclear Receptor Signaling Atlas: Opening Access to the Biology of Nuclear Receptor Signaling Pathways

PubMed Central

Becnel, Lauren B.; Darlington, Yolanda F.; Ochsner, Scott A.; Easton-Marks, Jeremy R.; Watkins, Christopher M.; McOwiti, Apollo; Kankanamge, Wasula H.; Wise, Michael W.; DeHart, Michael; Margolis, Ronald N.; McKenna, Neil J.

2015-01-01

Signaling pathways involving nuclear receptors (NRs), their ligands and coregulators, regulate tissue-specific transcriptomes in diverse processes, including development, metabolism, reproduction, the immune response and neuronal function, as well as in their associated pathologies. The Nuclear Receptor Signaling Atlas (NURSA) is a Consortium focused around a Hub website (www.nursa.org) that annotates and integrates diverse ‘omics datasets originating from the published literature and NURSA-funded Data Source Projects (NDSPs). These datasets are then exposed to the scientific community on an Open Access basis through user-friendly data browsing and search interfaces. Here, we describe the redesign of the Hub, version 3.0, to deploy “Web 2.0” technologies and add richer, more diverse content. The Molecule Pages, which aggregate information relevant to NR signaling pathways from myriad external databases, have been enhanced to include resources for basic scientists, such as post-translational modification sites and targeting miRNAs, and for clinicians, such as clinical trials. A portal to NURSA’s Open Access, PubMed-indexed journal Nuclear Receptor Signaling has been added to facilitate manuscript submissions. Datasets and information on reagents generated by NDSPs are available, as is information concerning periodic new NDSP funding solicitations. Finally, the new website integrates the Transcriptomine analysis tool, which allows for mining of millions of richly annotated public transcriptomic data points in the field, providing an environment for dataset re-use and citation, bench data validation and hypothesis generation. We anticipate that this new release of the NURSA database will have tangible, long term benefits for both basic and clinical research in this field. PMID:26325041

Neodymium in the oceans: a global database, a regional comparison and implications for palaeoceanographic research

PubMed Central

Griffiths, Alexander M.; Lambelet, Myriam; Little, Susan H.; Stichel, Torben; Wilson, David J.

2016-01-01

The neodymium (Nd) isotopic composition of seawater has been used extensively to reconstruct ocean circulation on a variety of time scales. However, dissolved neodymium concentrations and isotopes do not always behave conservatively, and quantitative deconvolution of this non-conservative component can be used to detect trace metal inputs and isotopic exchange at ocean–sediment interfaces. In order to facilitate such comparisons for historical datasets, we here provide an extended global database for Nd isotopes and concentrations in the context of hydrography and nutrients. Since 2010, combined datasets for a large range of trace elements and isotopes are collected on international GEOTRACES section cruises, alongside classical nutrient and hydrography measurements. Here, we take a first step towards exploiting these datasets by comparing high-resolution Nd sections for the western and eastern North Atlantic in the context of hydrography, nutrients and aluminium (Al) concentrations. Evaluating those data in tracer–tracer space reveals that North Atlantic seawater Nd isotopes and concentrations generally follow the patterns of advection, as do Al concentrations. Deviations from water mass mixing are observed locally, associated with the addition or removal of trace metals in benthic nepheloid layers, exchange with ocean margins (i.e. boundary exchange) and/or exchange with particulate phases (i.e. reversible scavenging). We emphasize that the complexity of some of the new datasets cautions against a quantitative interpretation of individual palaeo Nd isotope records, and indicates the importance of spatial reconstructions for a more balanced approach to deciphering past ocean changes. This article is part of the themed issue ‘Biological and climatic impacts of ocean trace element chemistry’. PMID:29035258

Basin-fill Aquifer Modeling with Terrestrial Gravity: Assessing Static Offsets in Bulk Datasets using MATLAB; Case Study of Bridgeport, CA

NASA Astrophysics Data System (ADS)

Mlawsky, E. T.; Louie, J. N.; Pohll, G.; Carlson, C. W.; Blakely, R. J.

2015-12-01

Understanding the potential availability of water resources in Eastern California aquifers is of critical importance to making water management policy decisions and determining best-use practices for California, as well as for downstream use in Nevada. Hydrologic well log data can provide valuable information on aquifer capacity, but is often proprietarily inaccessible or economically unfeasible to obtain in sufficient quantity. In the case of basin-fill aquifers, it is possible to make estimates of aquifer geometry and volume using geophysical surveys of gravity, constrained by additional geophysical and geological observations. We use terrestrial gravity data to model depth-to-basement about the Bridgeport, CA basin for application in preserving the Walker Lake biome. In constructing the model, we assess several hundred gravity observations, existing and newly collected. We regard these datasets as "bulk," as the data are compiled from multiple sources. Inconsistencies among datasets can result in "static offsets," or artificial bull's-eye contours, within the gradient. Amending suspect offsets requires the attention of the modeler; picking these offsets by hand can be a time-consuming process when modeling large-scale basin features. We develop a MATLAB script for interpolating the residual Bouguer anomaly about the basin using sparse observation points, and leveling offset points with a user-defined sensitivity. The script is also capable of plotting gravity profiles between any two endpoints within the map extent. The resulting anomaly map provides an efficient means of locating and removing static offsets in the data, while also providing a fast visual representation of a bulk dataset. Additionally, we obtain gridded basin gravity models with an open-source alternative to proprietary modeling tools.

Climatic warming in China during 1901–2015 based on an extended dataset of instrumental temperature records

DOE PAGES

Cao, Lijuan; Yan, Zhongwei; Zhao, Ping; ...

2017-05-26

Monthly mean instrumental surface air temperature (SAT) observations back to the nineteenth century in China are synthesized from different sources via specific quality-control, interpolation, and homogenization. Compared with the first homogenized long-term SAT dataset for China which contained 18 stations mainly located in the middle and eastern part of China, the present dataset includes homogenized monthly SAT series at 32 stations, with an extended coverage especially towards western China. Missing values are interpolated by using observations at nearby stations, including those from neighboring countries. Cross validation shows that the mean bias error (MBE) is generally small and falls between 0.45more » °C and –0.35 °C. Multiple homogenization methods and available metadata are applied to assess the consistency of the time series and to adjust inhomogeneity biases. The homogenized annual mean SAT series shows a range of trends between 1.1 °C and 4.0 °C/century in northeastern China, between 0.4 °C and 1.9 °C/century in southeastern China, and between 1.4 °C and 3.7 °C/century in western China to the west of 105 E (from the initial years of the stations to 2015). The unadjusted data include unusually warm records during the 1940s and hence tend to underestimate the warming trends at a number of stations. As a result, the mean SAT series for China based on the climate anomaly method shows a warming trend of 1.56 °C/century during 1901–2015, larger than those based on other currently available datasets.« less

Climatic warming in China during 1901–2015 based on an extended dataset of instrumental temperature records

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

Cao, Lijuan; Yan, Zhongwei; Zhao, Ping

Monthly mean instrumental surface air temperature (SAT) observations back to the nineteenth century in China are synthesized from different sources via specific quality-control, interpolation, and homogenization. Compared with the first homogenized long-term SAT dataset for China which contained 18 stations mainly located in the middle and eastern part of China, the present dataset includes homogenized monthly SAT series at 32 stations, with an extended coverage especially towards western China. Missing values are interpolated by using observations at nearby stations, including those from neighboring countries. Cross validation shows that the mean bias error (MBE) is generally small and falls between 0.45more » °C and –0.35 °C. Multiple homogenization methods and available metadata are applied to assess the consistency of the time series and to adjust inhomogeneity biases. The homogenized annual mean SAT series shows a range of trends between 1.1 °C and 4.0 °C/century in northeastern China, between 0.4 °C and 1.9 °C/century in southeastern China, and between 1.4 °C and 3.7 °C/century in western China to the west of 105 E (from the initial years of the stations to 2015). The unadjusted data include unusually warm records during the 1940s and hence tend to underestimate the warming trends at a number of stations. As a result, the mean SAT series for China based on the climate anomaly method shows a warming trend of 1.56 °C/century during 1901–2015, larger than those based on other currently available datasets.« less

Urban emissions hotspots: Quantifying vehicle congestion and air pollution using mobile phone GPS data.

PubMed

Gately, Conor K; Hutyra, Lucy R; Peterson, Scott; Sue Wing, Ian

2017-10-01

On-road emissions vary widely on time scales as short as minutes and length scales as short as tens of meters. Detailed data on emissions at these scales are a prerequisite to accurately quantifying ambient pollution concentrations and identifying hotspots of human exposure within urban areas. We construct a highly resolved inventory of hourly fluxes of CO, NO 2 , NO x , PM 2.5 and CO 2 from road vehicles on 280,000 road segments in eastern Massachusetts for the year 2012. Our inventory integrates a large database of hourly vehicle speeds derived from mobile phone and vehicle GPS data with multiple regional datasets of vehicle flows, fleet characteristics, and local meteorology. We quantify the 'excess' emissions from traffic congestion, finding modest congestion enhancement (3-6%) at regional scales, but hundreds of local hotspots with highly elevated annual emissions (up to 75% for individual roadways in key corridors). Congestion-driven reductions in vehicle fuel economy necessitated 'excess' consumption of 113 million gallons of motor fuel, worth ∼ $415M, but this accounted for only 3.5% of the total fuel consumed in Massachusetts, as over 80% of vehicle travel occurs in uncongested conditions. Across our study domain, emissions are highly spatially concentrated, with 70% of pollution originating from only 10% of the roads. The 2011 EPA National Emissions Inventory (NEI) understates our aggregate emissions of NO x , PM 2.5 , and CO 2 by 46%, 38%, and 18%, respectively. However, CO emissions agree within 5% for the two inventories, suggesting that the large biases in NO x and PM 2.5 emissions arise from differences in estimates of diesel vehicle activity. By providing fine-scale information on local emission hotspots and regional emissions patterns, our inventory framework supports targeted traffic interventions, transparent benchmarking, and improvements in overall urban air quality. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial clustering of fatal, and non-fatal, suicide in new South Wales, Australia: implications for evidence-based prevention.

PubMed

Torok, Michelle; Konings, Paul; Batterham, Philip J; Christensen, Helen

2017-10-06

Rates of suicide appear to be increasing, indicating a critical need for more effective prevention initiatives. To increase the efficacy of future prevention initiatives, we examined the spatial distribution of suicide deaths and suicide attempts in New South Wales (NSW), Australia, to identify where high incidence 'suicide clusters' were occurring. Such clusters represent candidate regions where intervention is critically needed, and likely to have the greatest impact, thus providing an evidence-base for the targeted prioritisation of resources. Analysis is based on official suicide mortality statistics for NSW, provided by the Australian Bureau of Statistics, and hospital separations for non-fatal intentional self-harm, provided through the NSW Health Admitted Patient Data Collection at a Statistical Area 2 (SA2) geography. Geographical Information System (GIS) techniques were applied to detect suicide clusters occurring between 2005 and 2013 (aggregated), for persons aged over 5 years. The final dataset contained 5466 mortality and 86,017 non-fatal intentional self-harm cases. In total, 25 Local Government Areas were identified as primary or secondary likely candidate regions for intervention. Together, these regions contained approximately 200 SA2 level suicide clusters, which represented 46% (n = 39,869) of hospital separations and 43% (n = 2330) of suicide deaths between 2005 and 2013. These clusters primarily converged on the Eastern coastal fringe of NSW. Crude rates of suicide deaths and intentional self-harm differed at the Local Government Areas (LGA) level in NSW. There was a tendency for primary suicide clusters to occur within metropolitan and coastal regions, rather than rural areas. The findings demonstrate the importance of taking geographical variation of suicidal behaviour into account, prior to development and implementation of prevention initiatives, so that such initiatives can target key problem areas where they are likely to have maximal impact.

Reconstructed Historical Land Cover and Biophysical Parameters for Studies of Land-Atmosphere Interactions within the Eastern United States

NASA Technical Reports Server (NTRS)

Steyaert, Louis T.; Knox, Robert G.

2007-01-01

The local environment where we live within the Earth's biosphere is often taken for granted. This environment can vary depending on whether the land cover is a forest, grassland, wetland, water body, bare soil, pastureland, agricultural field, village, residential suburb, or an urban complex with concrete, asphalt, and large buildings. In general, the type and characteristics of land cover influence surface temperatures, sunlight exposure and duration, relative humidity, wind speed and direction, soil moisture amount, plant life, birds, and other wildlife in our backyards. The physical and biological properties (biophysical characteristics) of land cover help to determine our surface environment because they directly affect surface radiation, heat, and soil moisture processes, and also feedback to regional weather and climate. Depending on the spatial scale and land use intensity, land cover changes can have profound impacts on our local and regional environment. Over the past 350 years, the eastern half of the United States, an area extending from the grassland prairies of the Great Plains to the Gulf and Atlantic coasts, has experienced extensive land cover and land use changes that began with land clearing in the 1600s, led to extensive deforestation and intensive land use practices by 1920, and then evolved to the present-day landscape. Determining the consequences of such land cover changes on regional and global climate is a major research issue. Such research requires detailed historical land cover data and modeling experiments simulating historical climates. Given the need to understand the effects of historical land cover changes in the eastern United States, some questions include: - What were the most important land cover transformations and how did they alter biophysical characteristics of the land cover at key points in time since the mid-1600s? - How have land cover and land use changes over the past 350 years affected the land surface environment including surface weather, hydrologic, and climatic variability? - How do the potential effects of regional human-induced land cover change on the environment compare to similar changes that are caused by the natural variations of the Earth's climate system? To help answer these questions, we reconstructed a fractional land cover and biophysical parameter dataset for the eastern United States at 1650, 1850, 1920, and 1992 time-slices. Each land cover fraction is associated with a biophysical parameter class, a suite of parameters defining the biophysical characteristics of that kind of land cover. This new dataset is designed for use in computer models of land-atmosphere interactions, to understand and quantify the effects of historical land cover changes on the water, energy, and carbon cycles

OVERFLOW ROADLESS AREA, GEORGIA AND NORTH CAROLINA.

USGS Publications Warehouse

Koeppen, Robert P.; Davis, Michael P.

1984-01-01

The Overflow Roadless Area in the Blue Ridge Mountains of Georgia and North Carolina is underlain by complexly folded schist and gneiss of Proterozoic age. A mineral-resource survey found little likelihood for the occurrence of mineral or energy resources in the area. Minor isolated localities of mica pegmatite and amethyst gemstone occur in the area. Gneiss and schist suitable for rock aggregate are present in large quantities, but similar rocks abound outside the area. Natural gas may possibly be present at great depth beneath the overthrust of the Blue Ridge. Further seismic studies and exploratory drilling are needed to evaluate the natural gas potential of this part of the Eastern Overthrust Belt.

Application of Coastal Remote Sensing to Rhincodon Typus Habitat Monitoring Northeast of the Yucatán Peninsula

NASA Astrophysics Data System (ADS)

Leben, R. R.; Shannon, M. R.

2013-05-01

Whale sharks, Rhincodon Typus, congregate annually in the coastal waters northeast of the Yucatán Peninsula from May through mid-September, with peak abundance in occurring between late July and the middle of August. This coincides with seasonal upwelling along the northern Yucatán coast and the eastern margin of the Yucatán shelf. Remote sensing data, including ocean color, sea surface temperature, ocean vector winds, and satellite altimetry, are used to characterize the physical environment supporting this unique coastal ecology, which also has important economic ramifications for the region because of increasing ecotourism activities focused on whale shark aggregations.

Discovery of dense aggregations of stalked crinoids in Izu-Ogasawara trench, Japan.

PubMed

Oji, Tatsuo; Ogawa, Yujiro; Hunter, Aaron W; Kitazawa, Kota

2009-06-01

Stalked crinoids are recognized as living fossils that typically inhabit modern deep-water environments exceeding 100 m. Previous records of stalked crinoids from hadal depths (exceeding 6000 m) are extremely rare, and no in-situ information has been available. We show here that stalked crinoids live densely on rocky substrates at depths over 9000 m in the Izu-Ogasawara Trench off the eastern coast of Japan, evidenced by underwater photos and videos taken by a remotely operated vehicle. This is the deepest in-situ observation of stalked crinoids and demonstrates that crinoid meadows can exist at hadal depths close to the deepest ocean floor, in a fashion quite similar to populations observed in shallower depths.

Data Albums: An Event Driven Search, Aggregation and Curation Tool for Earth Science

NASA Technical Reports Server (NTRS)

Ramachandran, Rahul; Kulkarni, Ajinkya; Maskey, Manil; Bakare, Rohan; Basyal, Sabin; Li, Xiang; Flynn, Shannon

2014-01-01

One of the largest continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available. Approaches used in Earth science research such as case study analysis and climatology studies involve gathering discovering and gathering diverse data sets and information to support the research goals. Research based on case studies involves a detailed description of specific weather events using data from different sources, to characterize physical processes in play for a specific event. Climatology-based research tends to focus on the representativeness of a given event, by studying the characteristics and distribution of a large number of events. This allows researchers to generalize characteristics such as spatio-temporal distribution, intensity, annual cycle, duration, etc. To gather relevant data and information for case studies and climatology analysis is both tedious and time consuming. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the datasets of interest can obtain the specific files they need using these systems. However, in cases where researchers are interested in studying a significant event, they have to manually assemble a variety of datasets relevant to it by searching the different distributed data systems. In these cases, a search process needs to be organized around the event rather than observing instruments. In addition, the existing data systems assume users have sufficient knowledge regarding the domain vocabulary to be able to effectively utilize their catalogs. These systems do not support new or interdisciplinary researchers who may be unfamiliar with the domain terminology. This paper presents a specialized search, aggregation and curation tool for Earth science to address these existing challenges. The search tool automatically creates curated "Data Albums", aggregated collections of information related to a specific science topic or event, containing links to relevant data files (granules) from different instruments; tools and services for visualization and analysis; and information about the event contained in news reports, images or videos to supplement research analysis. Curation in the tool is driven via an ontology based relevancy ranking algorithm to filter out non-relevant information and data.

Non-Trivial Feature Derivation for Intensifying Feature Detection Using LIDAR Datasets Through Allometric Aggregation Data Analysis Applying Diffused Hierarchical Clustering for Discriminating Agricultural Land Cover in Portions of Northern Mindanao, Philippines

NASA Astrophysics Data System (ADS)

Villar, Ricardo G.; Pelayo, Jigg L.; Mozo, Ray Mari N.; Salig, James B., Jr.; Bantugan, Jojemar

2016-06-01

Leaning on the derived results conducted by Central Mindanao University Phil-LiDAR 2.B.11 Image Processing Component, the paper attempts to provides the application of the Light Detection and Ranging (LiDAR) derived products in arriving quality Landcover classification considering the theoretical approach of data analysis principles to minimize the common problems in image classification. These are misclassification of objects and the non-distinguishable interpretation of pixelated features that results to confusion of class objects due to their closely-related spectral resemblance, unbalance saturation of RGB information is a challenged at the same time. Only low density LiDAR point cloud data is exploited in the research denotes as 2 pts/m2 of accuracy which bring forth essential derived information such as textures and matrices (number of returns, intensity textures, nDSM, etc.) in the intention of pursuing the conditions for selection characteristic. A novel approach that takes gain of the idea of object-based image analysis and the principle of allometric relation of two or more observables which are aggregated for each acquisition of datasets for establishing a proportionality function for data-partioning. In separating two or more data sets in distinct regions in a feature space of distributions, non-trivial computations for fitting distribution were employed to formulate the ideal hyperplane. Achieving the distribution computations, allometric relations were evaluated and match with the necessary rotation, scaling and transformation techniques to find applicable border conditions. Thus, a customized hybrid feature was developed and embedded in every object class feature to be used as classifier with employed hierarchical clustering strategy for cross-examining and filtering features. This features are boost using machine learning algorithms as trainable sets of information for a more competent feature detection. The product classification in this investigation was compared to a classification based on conventional object-oriented approach promoting straight-forward functionalities of the software eCognition. A compelling rise of efficiency in the overall accuracy (74.4% to 93.4%) and kappa index of agreement (70.5% to 91.7%) is noticeable based on the initial process. Nevertheless, having low-dense LiDAR dataset could be enough in generating exponential increase of performance in accuracy.

Regional polyphase deformation of the Eastern Sierras Pampeanas (Argentina Andean foreland): strengths and weaknesses of paleostress inversion

NASA Astrophysics Data System (ADS)

Traforti, Anna; Zampieri, Dario; Massironi, Matteo; Viola, Giulio; Alvarado, Patricia; Di Toro, Giulio

2016-04-01

The Eastern Sierras Pampeanas of central Argentina are composed of a series of basement-cored ranges, located in the Andean foreland c. 600 km east of the Andean Cordillera. Although uplift of the ranges is partly attributed to the regional Neogene evolution (Ramos et al. 2002), many questions remain as to the timing and style of deformation. In fact, the Eastern Sierras Pampeanas show compelling evidence of a long lasting brittle history (spanning the Early Carboniferous to Present time), characterised by several deformation events reflecting different tectonic regimes. Each deformation phase resulted in further strain increments accommodated by reactivation of inherited structures and rheological anisotropies (Martino 2003). In the framework of such a polyphase brittle tectonic evolution affecting highly anisotropic basement rocks, the application of paleostress inversion methods, though powerful, suffers from some shortcomings, such as the likely heterogeneous character of fault slip datasets and the possible reactivation of even highly misoriented structures, and thus requires careful analysis. The challenge is to gather sufficient fault-slip data, to develop a proper understanding of the regional evolution. This is done by the identification of internally consistent fault and fracture subsets (associated to distinct stress states on the basis of their geometric and kinematic compatibility) in order to generate a chronologically-constrained evolutionary conceptual model. Based on large fault-slip datasets collected in the Sierras de Cordoba (Eastern Sierras Pampeanas), reduced stress tensors have been generated and interpreted as part of an evolutionary model by considering the obtained results against: (i) existing K-Ar illite ages of fault gouges in the study area (Bense et al. 2013), (ii) the nature and orientation of pre-existing anisotropies and (iii) the present-day stress field due to the convergence of the Nazca and South America plates (main shortening oriented WSW-ENE). Although remarkable differences in reactivation mechanisms have been observed for the various studied lithological domains (schist, gneiss and granitic rocks), the brittle regional polyphase deformation of the Eastern Sierras Pampeanas appears to be dominated by two extensional episodes (σ3 oriented NE/ENE and WNW, respectively), which can be associated with Middle-Late Permian to Early Cretaceous tectonism, followed by a compressional paleostress (σ1 oriented ENE), which is compatible with the present day Andean convergence. Paleostress inversion techniques, despite all uncertainties involved, represent a robust approach to disentangle complex polyphase deformation histories both in term of reactivation mechanisms and strain partitioning. References: Bense, F. A., Wemmer, K., Löbens, S., & Siegesmund, S. (2013). Fault gouge analyses: K-Ar illite dating, clay mineralogy and tectonic significance-a study from the Sierras Pampeanas, Argentina. International Journal of Earth Sciences, 103, 189-218. Martino, R. D. (2003). Las fajas de deformación dúctil de las Sierras Pampeanas de Córdoba : Una reseña general. Revista de La Asociación Geológica Argentina, 58(4), 549-571. Ramos, V. A., Cristallini, E. O., & Perez, D. J. (2002). The Pampean flat-slab of the Central Andes. Journal of South American Earth Sciences, 15, 59-78.

Current and future distribution of Aedes aegypti and Aedes albopictus (Diptera: Culicidae) in WHO Eastern Mediterranean Region.

PubMed

Ducheyne, Els; Tran Minh, Nhu Nguyen; Haddad, Nabil; Bryssinckx, Ward; Buliva, Evans; Simard, Frédéric; Malik, Mamunur Rahman; Charlier, Johannes; De Waele, Valérie; Mahmoud, Osama; Mukhtar, Muhammad; Bouattour, Ali; Hussain, Abdulhafid; Hendrickx, Guy; Roiz, David

2018-02-14

Aedes-borne diseases as dengue, zika, chikungunya and yellow fever are an emerging problem worldwide, being transmitted by Aedes aegypti and Aedes albopictus. Lack of up to date information about the distribution of Aedes species hampers surveillance and control. Global databases have been compiled but these did not capture data in the WHO Eastern Mediterranean Region (EMR), and any models built using these datasets fail to identify highly suitable areas where one or both species may occur. The first objective of this study was therefore to update the existing Ae. aegypti (Linnaeus, 1762) and Ae. albopictus (Skuse, 1895) compendia and the second objective was to generate species distribution models targeted to the EMR. A final objective was to engage the WHO points of contacts within the region to provide feedback and hence validate all model outputs. The Ae. aegypti and Ae. albopictus compendia provided by Kraemer et al. (Sci Data 2:150035, 2015; Dryad Digit Repos, 2015) were used as starting points. These datasets were extended with more recent species and disease data. In the next step, these sets were filtered using the Köppen-Geiger classification and the Mahalanobis distance. The occurrence data were supplemented with pseudo-absence data as input to Random Forests. The resulting suitability and maximum risk of establishment maps were combined into hard-classified maps per country for expert validation. The EMR datasets consisted of 1995 presence locations for Ae. aegypti and 2868 presence locations for Ae. albopictus. The resulting suitability maps indicated that there exist areas with high suitability and/or maximum risk of establishment for these disease vectors in contrast with previous model output. Precipitation and host availability, expressed as population density and night-time lights, were the most important variables for Ae. aegypti. Host availability was the most important predictor in case of Ae. albopictus. Internal validation was assessed geographically. External validation showed high agreement between the predicted maps and the experts' extensive knowledge of the terrain. Maps of distribution and maximum risk of establishment were created for Ae. aegypti and Ae. albopictus for the WHO EMR. These region-specific maps highlighted data gaps and these gaps will be filled using targeted monitoring and surveillance. This will increase the awareness and preparedness of the different countries for Aedes borne diseases.

AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images.

PubMed

Albarqouni, Shadi; Baur, Christoph; Achilles, Felix; Belagiannis, Vasileios; Demirci, Stefanie; Navab, Nassir

2016-05-01

The lack of publicly available ground-truth data has been identified as the major challenge for transferring recent developments in deep learning to the biomedical imaging domain. Though crowdsourcing has enabled annotation of large scale databases for real world images, its application for biomedical purposes requires a deeper understanding and hence, more precise definition of the actual annotation task. The fact that expert tasks are being outsourced to non-expert users may lead to noisy annotations introducing disagreement between users. Despite being a valuable resource for learning annotation models from crowdsourcing, conventional machine-learning methods may have difficulties dealing with noisy annotations during training. In this manuscript, we present a new concept for learning from crowds that handle data aggregation directly as part of the learning process of the convolutional neural network (CNN) via additional crowdsourcing layer (AggNet). Besides, we present an experimental study on learning from crowds designed to answer the following questions. 1) Can deep CNN be trained with data collected from crowdsourcing? 2) How to adapt the CNN to train on multiple types of annotation datasets (ground truth and crowd-based)? 3) How does the choice of annotation and aggregation affect the accuracy? Our experimental setup involved Annot8, a self-implemented web-platform based on Crowdflower API realizing image annotation tasks for a publicly available biomedical image database. Our results give valuable insights into the functionality of deep CNN learning from crowd annotations and prove the necessity of data aggregation integration.

Improving sand and gravel utilization and land-use planning. - 3D-modelling gravel resources with geospatial data.

NASA Astrophysics Data System (ADS)

Rolstad Libach, Lars; Wolden, Knut; Dagestad, Atle; Eskil Larsen, Bjørn

2017-04-01

The Norwegian aggregate industry produces approximately 14 million tons of sand and gravel aggregates annually to a value of approximately 100 million Euros. Utilization of aggregates are often linked to land-use conflicts and complex environmental impacts at the extraction site. These topics are managed on a local municipal level in Norway. The Geological Survey of Norway has a database and a web map service with information about sand and gravel deposits with considerable volumes and an importance evaluation. Some of the deposits covers large areas where the land-use conflicts are high. To ease and improve land-use planning, safeguard other important resources like groundwater and sustainable utilization of sand and gravel resources - there is a need for more detailed information of already mapped important resources. Detailed 3D-models of gravel deposits is a tool for a better land-use- and resource management. By combining seismic, GPR and resistivity geophysical profile data, borehole data, quaternary maps and lidar surface data, it has been possible to make 3D-models of deposits and to further research the possibilities for distinguishing different qualities and volumes. Good datasets and a detailed resource map is a prerequisite to assess geological resources for planners, extractors and neighbours. Future challenges lies in use of, often old, geophysical data, and combining these. What kind of information is it possible to grasp from depth-data that actually argues for a more detailed delineation of resources?

Observing the atmosphere in moisture space

NASA Astrophysics Data System (ADS)

Schulz, Hauke; Stevens, Bjorn

2017-04-01

Processes behind convective aggregation have mostly been analysed and identified on the basis of relatively idealized cloud resolving model studies. Relatively little effort has been spent on using observations to test or quantify the findings coming from the models. In 2010 the Barbados Cloud Observatory (BCO) was established on Barbados, which is on the edge of the ITCZ, in part to test hypotheses such as those emerging form the analysis of cloud resolving models. To better test ideas related to the driving forces of convective aggregation, we analyse BCO measurements to identify the processes changing the moist static energy flux, in moisture space, i.e., as a function of rank column water vapour. Similar approaches are used to analyse cloud resolving models. We composite five years of cloud- and water-vapor profiles, from a cloud radar, and Raman water vapour lidar to construct the structure of the observed atmosphere in moisture space. The data show both agreement and disagreement with the models: radiative transfer calculations of the cross-section reveal a strong anomalous radiative cooling in the boundary layer at the dry end of the moisture space. We show that the radiation, mainly in the long-wave, implies a shallow circulation. This circulation agrees generally with supplementary used reanalysis datasets, but the strength and extent vary more markedly across the analyses. Consistent with the modelling, the implied radiative driven circulation supports the aggregation process by importing net moist static energy into the moist regimes.

Natural and Anthropogenic Aerosol Trends from Satellite and Surface Observations and Model Simulations over the North Atlantic Ocean from 2002 to 2012

NASA Technical Reports Server (NTRS)

Jongeward, Andrew R.; Li, Zhanqing; He, Hao; Xiong, Xiaoxiong

2016-01-01

Aerosols contribute to Earths radiative budget both directly and indirectly, and large uncertainties remain in quantifying aerosol effects on climate. Variability in aerosol distribution and properties, as might result from changing emissions and transport processes, must be characterized. In this study, variations in aerosol loading across the eastern seaboard of theUnited States and theNorthAtlanticOcean during 2002 to 2012 are analyzed to examine the impacts of anthropogenic emission control measures using monthly mean data from MODIS, AERONET, and IMPROVE observations and Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulation.MODIS observes a statistically significant negative trend in aerosol optical depth (AOD) over the midlatitudes (-0.030 decade(sup-1)). Correlation analyses with surface AOD from AERONET sites in the upwind region combined with trend analysis from GOCART component AOD confirm that the observed decrease in the midlatitudes is chiefly associated with anthropogenic aerosols that exhibit significant negative trends from the eastern U.S. coast extending over the western North Atlantic. Additional analysis of IMPROVE surface PM(sub 2.5) observations demonstrates statistically significant negative trends in the anthropogenic components with decreasing mass concentrations over the eastern United States. Finally, a seasonal analysis of observational datasets is performed. The negative trend seen by MODIS is strongest during spring (MAM) and summer (JJA) months. This is supported by AERONET seasonal trends and is identified from IMPROVE seasonal trends as resulting from ammonium sulfate decreases during these seasons.

Training on Eastern Pacific tropical cyclones for Latin American students

NASA Astrophysics Data System (ADS)

Farfán, L. M.; Raga, G. B.

2009-05-01

Tropical cyclones are one of the most impressive atmospheric phenomena and their development in the Atlantic and Eastern Pacific basins has potential to affect several Latin-American and Caribbean countries, where human resources are limited. As part of an international research project, we are offering short courses based on the current understanding of tropical cyclones in the Eastern Pacific basin. Our main goal is to train students from higher-education institutions from various countries in Latin America. Key aspects are tropical cyclone formation and evolution, with particular emphasis on their development off the west coast of Mexico. Our approach includes lectures on tropical cyclone climatology and formation, dynamic and thermodynamic models, air-sea interaction and oceanic response, ocean waves and coastal impacts as well as variability and climate-related predictions. In particular, we use a best-track dataset issued by the United States National Hurricane Center and satellite observations to analyze convective patterns for the period 1970-2006. Case studies that resulted in landfall over northwestern Mexico are analyzed in more detail; this includes systems that developed during the 2006, 2007 and 2008 seasons. Additionally, we have organized a human-dimensions symposium to discuss socio-economic issues that are associated with the landfall of tropical cyclones. This includes coastal zone impact and flooding, the link between cyclones and water resources, the flow of weather and climate information from scientists to policy- makers, the role of emergency managers and decision makers, impact over health issues and the viewpoint of the insurance industry.

Cyanobacterial distributions along a physico-chemical gradient in the Northeastern Pacific Ocean.

PubMed

Sudek, Sebastian; Everroad, R Craig; Gehman, Alyssa-Lois M; Smith, Jason M; Poirier, Camille L; Chavez, Francisco P; Worden, Alexandra Z

2015-10-01

The cyanobacteria Prochlorococcus and Synechococcus are important marine primary producers. We explored their distributions and covariance along a physico-chemical gradient from coastal to open ocean waters in the Northeastern Pacific Ocean. An inter-annual pattern was delineated in the dynamic transition zone where upwelled and eastern boundary current waters mix, and two new Synechococcus clades, Eastern Pacific Clade (EPC) 1 and EPC2, were identified. By applying state-of-the-art phylogenetic analysis tools to bar-coded 16S amplicon datasets, we observed higher abundance of Prochlorococcus high-light I (HLI) and low-light I (LLI) in years when more oligotrophic water intruded farther inshore, while under stronger upwelling Synechococcus I and IV dominated. However, contributions of some cyanobacterial clades were proportionally relatively constant, e.g. Synechococcus EPC2. In addition to supporting observations that Prochlorococcus LLI thrive at higher irradiances than other LL taxa, the results suggest LLI tolerate lower temperatures than previously reported. The phylogenetic precision of our 16S rRNA gene analytical approach and depth of bar-coded sequencing also facilitated detection of clades at low abundance in unexpected places. These include Prochlorococcus at the coast and Cyanobium-related sequences offshore, although it remains unclear whether these came from resident or potentially advected cells. Our study enhances understanding of cyanobacterial distributions in an ecologically important eastern boundary system. © 2014 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.

Genetic tracking of the raccoon variant of rabies virus in eastern North America.

PubMed

Szanto, Annamaria G; Nadin-Davis, Susan A; Rosatte, Richard C; White, Bradley N

2011-06-01

To gain insight into the incursion of the raccoon variant of rabies into the raccoon population in three Canadian provinces, a collection of 192 isolates of the raccoon rabies virus (RRV) strain was acquired from across its North American range and was genetically characterized. A 516-nucleotide segment of the non-coding region between the G and L protein open reading frames, corresponding to the most variable region of the rabies virus genome, was sequenced. This analysis identified 119 different sequences, and phylogenetic analysis of the dataset supports the documented history of RRV spread. Three distinct geographically restricted RRV lineages were identified. Lineage 1 was found in Florida, Alabama and Georgia and appears to form the ancestral lineage of the raccoon variant of rabies. Lineage 2, represented by just two isolates, was found only in Florida, while the third lineage appears broadly distributed throughout the rest of the eastern United States and eastern Canada. In New York State, two distinct spatially segregated variants were identified; the one occupying the western and northern portions of the state was responsible for an incursion of raccoon rabies into the Canadian province of Ontario. Isolates from New Brunswick and Quebec form distinct, separate clusters, consistent with their independent origins from neighboring areas of the United States. The data are consistent with localized northward incursion into these three separate areas with no evidence of east-west viral movement between the three Canadian provinces. Copyright © 2011 Elsevier B.V. All rights reserved.

Surface circulation and upwelling patterns around Sri Lanka

NASA Astrophysics Data System (ADS)

de Vos, A.; Pattiaratchi, C. B.; Wijeratne, E. M. S.

2014-10-01

Sri Lanka occupies a unique location within the equatorial belt in the northern Indian Ocean, with the Arabian Sea on its western side and the Bay of Bengal on its eastern side, and experiences bi-annually reversing monsoon winds. Aggregations of blue whale (Balaenoptera musculus) have been observed along the southern coast of Sri Lanka during the northeast (NE) monsoon, when satellite imagery indicates lower productivity in the surface waters. This study explored elements of the dynamics of the surface circulation and coastal upwelling in the waters around Sri Lanka using satellite imagery and numerical simulations using the Regional Ocean Modelling System (ROMS). The model was run for 3 years to examine the seasonal and shorter-term (~10 days) variability. The results reproduced correctly the reversing current system, between the Equator and Sri Lanka, in response to the changing wind field: the eastward flowing Southwest Monsoon Current (SMC) during the southwest (SW) monsoon transporting 11.5 Sv (mean over 2010-2012) and the westward flowing Northeast Monsoon Current (NMC) transporting 9.6 Sv during the NE monsoon, respectively. A recirculation feature located to the east of Sri Lanka during the SW monsoon, the Sri Lanka Dome, is shown to result from the interaction between the SMC and the island of Sri Lanka. Along the eastern and western coasts, during both monsoon periods, flow is southward converging along the southern coast. During the SW monsoon, the island deflects the eastward flowing SMC southward, whilst along the eastern coast, the southward flow results from the Sri Lanka Dome recirculation. The major upwelling region, during both monsoon periods, is located along the southern coast, resulting from southward flow converging along the southern coast and subsequent divergence associated with the offshore transport of water. Higher surface chlorophyll concentrations were observed during the SW monsoon. The location of the flow convergence and hence the upwelling centre was dependent on the relative strengths of wind-driven flow along the eastern and western coasts: during the SW (NE) monsoon, the flow along the western (eastern) coast was stronger, migrating the upwelling centre to the east (west).

Using the Landsat data archive to assess long-term regional forest dynamics assessment in Eastern Europe, 1985-2012

NASA Astrophysics Data System (ADS)

Turubanova, S.; Potapov, P.; Krylov, A.; Tyukavina, A.; McCarty, J. L.; Radeloff, V. C.; Hansen, M. C.

2015-04-01

Dramatic political and economic changes in Eastern European countries following the dissolution of the "Eastern Bloc" and the collapse of the Soviet Union greatly affected land-cover and land-use trends. In particular, changes in forest cover dynamics may be attributed to the collapse of the planned economy, agricultural land abandonment, economy liberalization, and market conditions. However, changes in forest cover are hard to quantify given inconsistent forest statistics collected by different countries over the last 30 years. The objective of our research was to consistently quantify forest cover change across Eastern Europe from 1985 until 2012 using the complete Landsat data archive. We developed an algorithm for processing imagery from different Landsat platforms and sensors (TM and ETM+), aggregating these images into a common set of multi-temporal metrics, and mapping annual gross forest cover loss and decadal gross forest cover gain. Our results show that forest cover area increased from 1985 to 2012 by 4.7% across the region. Average annual gross forest cover loss was 0.41% of total forest cover area, with a statistically significant increase from 1985 to 2012. Most forest disturbance recovered fast, with only 12% of the areas of forest loss prior to 1995 not being recovered by 2012. Timber harvesting was the main cause of forest loss. Logging area declined after the collapse of socialism in the late 1980s, increased in the early 2000s, and decreased in most countries after 2007 due to the global economic crisis. By 2012, Central and Baltic Eastern European countries showed higher logging rates compared to their Western neighbours. Comparing our results with official forest cover and change estimates showed agreement in total forest area for year 2010, but with substantial disagreement between Landsat-based and official net forest cover area change. Landsat-based logging areas exhibit strong relationship with reported roundwood production at national scale. Our results allow national and sub-national level analysis of forest cover extent, change, and logging intensity and are available on-line as a baseline for further analyses of forest dynamics and its drivers.

Routine data for disease surveillance in the undeveloped region of the OR Tambo district of the Eastern Cape Province.

PubMed

Kabuya, Chrispin; Wright, Graham; Odama, Anthony; O'Mahoney, Don

2014-01-01

The research team needed to upsize the solution previously tested so that it could expand the routine data collected via tablet computers. The research team identified the general flow of data within clinics. Data was mainly collected from registers, which were later converted to electronic form and checked for duplication. A database was designed for the collection of demographic data (Patient Master Index), which was aimed at eliminating duplication of patients' data in several registers. Open Data Kit (ODK) Collect was setup on Android tablets for collecting disease related routine data, while ODK Aggregate as the storage and aggregates of data captured by ODK Collect and the Patient Master Index for demographic data, were setup on an Apple Mini Mac server. Data collection is in progress. The expected results include improved data quality, reliability and quick access to summary data. Secondly, instant retrieval of patient demographic details and clinic numbers are included. Thirdly, ability to form standard reporting from the SQL database and lastly exporting data into the TIER.net and DHIS systems via CVS files thus eliminating the need for data capturers are shown.

Massive Sorghum Collection Genotyped with SSR Markers to Enhance Use of Global Genetic Resources

PubMed Central

Bouchet, Sophie; Chantereau, Jacques; Deu, Monique; Gardes, Laetitia; Noyer, Jean-Louis; Rami, Jean-François; Rivallan, Ronan; Li, Yu; Lu, Ping; Wang, Tianyu; Folkertsma, Rolf T.; Arnaud, Elizabeth; Upadhyaya, Hari D.; Glaszmann, Jean-Christophe; Hash, C. Thomas

2013-01-01

Large ex situ collections require approaches for sampling manageable amounts of germplasm for in-depth characterization and use. We present here a large diversity survey in sorghum with 3367 accessions and 41 reference nuclear SSR markers. Of 19 alleles on average per locus, the largest numbers of alleles were concentrated in central and eastern Africa. Cultivated sorghum appeared structured according to geographic regions and race within region. A total of 13 groups of variable size were distinguished. The peripheral groups in western Africa, southern Africa and eastern Asia were the most homogeneous and clearly differentiated. Except for Kafir, there was little correspondence between races and marker-based groups. Bicolor, Caudatum, Durra and Guinea types were each dispersed in three groups or more. Races should therefore better be referred to as morphotypes. Wild and weedy accessions were very diverse and scattered among cultivated samples, reinforcing the idea that large gene-flow exists between the different compartments. Our study provides an entry to global sorghum germplasm collections. Our reference marker kit can serve to aggregate additional studies and enhance international collaboration. We propose a core reference set in order to facilitate integrated phenotyping experiments towards refined functional understanding of sorghum diversity. PMID:23565161

Polyploidisation and Geographic Differentiation Drive Diversification in a European High Mountain Plant Group (Doronicum clusii Aggregate, Asteraceae)

PubMed Central

Pachschwöll, Clemens; Escobar García, Pedro; Winkler, Manuela; Schneeweiss, Gerald M.; Schönswetter, Peter

2015-01-01

Range shifts (especially during the Pleistocene), polyploidisation and hybridization are major factors affecting high-mountain biodiversity. A good system to study their role in the European high mountains is the Doronicum clusii aggregate (Asteraceae), whose four taxa (D. clusii s.s., D. stiriacum, D. glaciale subsp. glaciale and D. glaciale subsp. calcareum) are differentiated geographically, ecologically (basiphilous versus silicicolous) and/or via their ploidy levels (diploid versus tetraploid). Here, we use DNA sequences (three plastid and one nuclear spacer) and AFLP fingerprinting data generated for 58 populations to infer phylogenetic relationships, origin of polyploids—whose ploidy level was confirmed by chromosomally calibrated DNA ploidy level estimates—and phylogeographic history. Taxonomic conclusions were informed, among others, by a Gaussian clustering method for species delimitation using dominant multilocus data. Based on molecular data we identified three lineages: (i) silicicolous diploid D. clusii s.s. in the Alps, (ii) silicicolous tetraploid D. stiriacum in the eastern Alps (outside the range of D. clusii s.s.) and the Carpathians and (iii) the basiphilous diploids D. glaciale subsp. glaciale (eastern Alps) and D. glaciale subsp. calcareum (northeastern Alps); each taxon was identified as distinct by the Gaussian clustering, but the separation of D. glaciale subsp. calcareum and D. glaciale subsp. glaciale was not stable, supporting their taxonomic treatment as subspecies. Carpathian and Alpine populations of D. stiriacum were genetically differentiated suggesting phases of vicariance, probably during the Pleistocene. The origin (autopolyploid versus allopolyploid) of D. stiriacum remained unclear. Doronicum glaciale subsp. calcareum was genetically and morphologically weakly separated from D. glaciale subsp. glaciale but exhibited significantly higher genetic diversity and rarity. This suggests that the more widespread D. glaciale subsp. glaciale originated from D. glaciale subsp. calcareum, which is restricted to a prominent Pleistocene refugium previously identified in other alpine plant species. PMID:25749621

Relationship of orogen-parallel exhumation in the Tauern and Rechnitz Windows to eastward lateral escape of the Eastern Alps

NASA Astrophysics Data System (ADS)

Favaro, Silvia; Schuster, Ralf; Scharf, Andrea; Handy, Mark R.

2013-04-01

Neogene orogen-parallel extensional in the Tauern and Rechnitz Windows and eastward lateral extrusion of the Eastern Alps are manifested, respectively, by exhumation and cooling and by subsidence of pull-apart basins. These events overlap in time, giving rise to the question of their relationship. The Tauern Window exposes relics of the European continental margin (Subpenninic units) and Alpine Tethys Ocean (Penninic units) beneath units derived from the Adriatic microplate (Austroalpine nappes). In the eastern part of the Tauern Window, the Subpenninic and Penninic nappes are deformed by two domes (Sonnblick and Hochalm domes) and the intervening tight Mallnitz synform. Reddy et al. (1996) proposed that the Sonnblick dome cooled first based on a trend of decreasing Rb-Sr and Ar-Ar white mica and biotite ages from the northwestern part of the Sonnblick Dome to the southeastern part of the Hochalm dome. When combined with this existing dataset, new Rb/Sr biotite ages point to simultaneous cooling of the domes to below the closure temperature of this isotopic system. Rb-Sr muscovite ages decrease from 26-30 Ma in the northwest to 20-25 Ma in the southeast. Rb-Sr biotite ages young in the same direction from 20-23 Ma to 16-19 Ma. The biotite ages do not vary in a transect of the Mallnitz synform and are therefore inferred to post-date this structure. Apatite fission track data follow this same NW to SE trend. A SE increase in intensity of mylinitic shearing along strike of the Mallnitz synform is interpreted to be a manifestation of stretch faulting related to normal faulting along the central part of the Katschberg Shear Zone system at the eastern end of the Tauern Window (Scharf et al., submitted). We attribute the SE decrease of the biotite cooling ages to an increased component of tectonic unroofing towards the eastern margin of the Tauern Window. Three new Rb-Sr biotite ages in the range of 16-26 Ma from the lowermost Austroalpine units (Wechsel and Semmering nappes) immediately above the Rechnitz Window are also interpreted to reflect cooling during extensional exhumation. This age range overlaps with that of rapid subsidence and sedimentation in pull-apart basins of the Eastern Alps (17-12 Ma) and opening of the Pannonian Basin (21-15 Ma) behind the retreating Carpathian subduction orogen. This suggests that exhumation in the Rechnitz Window and lateral escape of the Eastern Alps were broadly coeval with both Adriatic indentation and Carpathian rollback subduction.

The comparative phylogeography of fruit bats of the tribe Scotonycterini (Chiroptera, Pteropodidae) reveals cryptic species diversity related to African Pleistocene forest refugia.

PubMed

Hassanin, Alexandre; Khouider, Souraya; Gembu, Guy-Crispin; Goodman, Steven M; Kadjo, Blaise; Nesi, Nicolas; Pourrut, Xavier; Nakouné, Emmanuel; Bonillo, Céline

2015-03-01

The hypothesis of Pleistocene forest refugia was tested using comparative phylogeography of Scotonycterini, a fruit bat tribe endemic to Africa containing four species: Scotonycteris zenkeri, Casinycteris argynnis, C. campomaanensis, and C. ophiodon. Patterns of genetic structure were assessed using 105 Scotonycterini (including material from three holotypes) collected at 37 localities, and DNA sequences from the mitochondrial cytochrome b gene (1140 nt) and 12 nuclear introns (9641 nt). Phylogenetic trees and molecular dating were inferred by Bayesian methods. Multilocus analyses were performed using supermatrix, SuperTRI, and *BEAST approaches. Mitochondrial analyses reveal strong phylogeographical structure in Scotonycteris, with four divergent haplogroups (4.9-8.7%), from Upper Guinea, Cameroon, western Equatorial Africa, and eastern Democratic Republic of the Congo (DRC). In C. argynnis, we identify two mtDNA haplogroups corresponding to western and eastern Equatorial Africa (1.4-2.1%). In C. ophiodon, the mtDNA haplotypes from Cameroon and Ivory Coast differ by only 1.3%. Nuclear analyses confirm the validity of the recently described C. campomaanensis and indicate that western and eastern populations of C. argynnis are not fully isolated. All mtDNA clusters detected in Scotonycteris are found to be monophyletic based on the nuclear dataset, except in eastern DRC. In the nuclear tree, the clade from western Equatorial Africa is closely related to individuals from eastern DRC, whereas in the mitochondrial tree it appears to be the sister-group of the Cameroon clade. Migrate-n analyses support gene flow from western Equatorial Africa to eastern DRC. Molecular dating indicates that Pleistocene forest refugia have played an important role in shaping the evolution of Scotonycterini, with two phases of allopatric speciation at approximately 2.7 and 1.6 Mya, resulting from isolation in three main forest areas corresponding to Upper Guinea, Cameroon, and Equatorial Africa. Two cryptic species and two subspecies are described herein in the genus Scotonycteris. Female philopatry and male biased dispersal are supported for the smallest taxa, i.e., the three species of Scotonycteris and C. argynnis. The Congo, Ntem, and Sanaga rivers are identified as biogeographic barriers to the dispersal of Scotonycteris during interglacial periods. A greater capacity for long-distance dispersal is inferred for the largest species, C. ophiodon. Copyright © 2014 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Contribution of tropical cyclones to global rainfall

NASA Astrophysics Data System (ADS)

Khouakhi, Abdou; Villarini, Gabriele; Vecchi, Gabriel; Smith, James

2016-04-01

Rainfall associated with tropical cyclones (TCs) can have both devastating and beneficial impacts in different parts of the world. In this work, daily precipitation and historical six-hour best track TC datasets are used to quantify the contribution of TCs to global rainfall. We select 18607 rain gauge stations with at least 25 complete (at least 330 measurements per year) years between 1970 and 2014. We consider rainfall associated with TCs if the center of circulation of the storm passed within a given distance from the rain gauge and within a given time window. Spatial and temporal sensitivity analyses are performed with varying time windows (same day, ±1 day) and buffer radii (400 km and 500 km) around each rain gauge. Results highlight regional differences in TC-induced rainfall. The highest TC-induced precipitation totals (400 to 600+ mm/year) are prevalent along eastern Asia, western and northeastern Australia, and in the western Pacific islands. Stations along the southeast of the U.S. coast and surrounding the Gulf of Mexico receive up to 200 mm/year of TC rainfall. The highest annual fractional contributions of TCs to total rainfall (from 35 to 50%) are recorded in stations located in northwestern Australia, southeastern China, the northern Philippines and the southern Mexico peninsula. Seasonally, the highest proportions (40 to 50%) are recorded along eastern Australia and Mauritius in winter, and in eastern Asia and Mexico in summer and autumn. Analyses of the relative contribution of TCs to extreme rainfall using annual maximum (AM) and peaks-over-threshold (POT) approaches indicate notable differences among regions. The highest TC-AM rainfall proportions (45 to 60%) are found in stations located in Japan, eastern China, the Philippines, eastern and western Australia. Substantial contributions (25 to 40% of extreme rainfall) are also recorded in stations located along the U.S. East Coast, the Gulf of Mexico, and the Mexico peninsula. We find similar patterns using the POT approach to identify extremes. The fractional contributions decrease as we move inland from the coast. Moreover, the relationship between TC-induced extreme rainfall and the El Niño-Southern Oscillation is also examined using logistic and Poisson regression. Results indicate that TC-induced extreme rainfall tends to occur more frequently in Australia and along the U.S. East Coast during La Niña, and along eastern Asia and northwestern Pacific islands during El Niño.

Downscaling global land-use/land-cover projections for use in region-level state-and-transition simulation modeling

USGS Publications Warehouse

Sherba, Jason T.; Sleeter, Benjamin M.; Davis, Adam W.; Parker, Owen P.

2015-01-01

Global land-use/land-cover (LULC) change projections and historical datasets are typically available at coarse grid resolutions and are often incompatible with modeling applications at local to regional scales. The difficulty of downscaling and reapportioning global gridded LULC change projections to regional boundaries is a barrier to the use of these datasets in a state-and-transition simulation model (STSM) framework. Here we compare three downscaling techniques to transform gridded LULC transitions into spatial scales and thematic LULC classes appropriate for use in a regional STSM. For each downscaling approach, Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) LULC projections, at the 0.5 × 0.5 cell resolution, were downscaled to seven Level III ecoregions in the Pacific Northwest, United States. RCP transition values at each cell were downscaled based on the proportional distribution between ecoregions of (1) cell area, (2) land-cover composition derived from remotely-sensed imagery, and (3) historic LULC transition values from a LULC history database. Resulting downscaled LULC transition values were aggregated according to their bounding ecoregion and “cross-walked” to relevant LULC classes. Ecoregion-level LULC transition values were applied in a STSM projecting LULC change between 2005 and 2100. While each downscaling methods had advantages and disadvantages, downscaling using the historical land-use history dataset consistently apportioned RCP LULC transitions in agreement with historical observations. Regardless of the downscaling method, some LULC projections remain improbable and require further investigation.

Influence of uncertain identification of triggering rainfall on the assessment of landslide early warning thresholds

NASA Astrophysics Data System (ADS)

Peres, David J.; Cancelliere, Antonino; Greco, Roberto; Bogaard, Thom A.

2018-03-01

Uncertainty in rainfall datasets and landslide inventories is known to have negative impacts on the assessment of landslide-triggering thresholds. In this paper, we perform a quantitative analysis of the impacts of uncertain knowledge of landslide initiation instants on the assessment of rainfall intensity-duration landslide early warning thresholds. The analysis is based on a synthetic database of rainfall and landslide information, generated by coupling a stochastic rainfall generator and a physically based hydrological and slope stability model, and is therefore error-free in terms of knowledge of triggering instants. This dataset is then perturbed according to hypothetical reporting scenarios that allow simulation of possible errors in landslide-triggering instants as retrieved from historical archives. The impact of these errors is analysed jointly using different criteria to single out rainfall events from a continuous series and two typical temporal aggregations of rainfall (hourly and daily). The analysis shows that the impacts of the above uncertainty sources can be significant, especially when errors exceed 1 day or the actual instants follow the erroneous ones. Errors generally lead to underestimated thresholds, i.e. lower than those that would be obtained from an error-free dataset. Potentially, the amount of the underestimation can be enough to induce an excessive number of false positives, hence limiting possible landslide mitigation benefits. Moreover, the uncertain knowledge of triggering rainfall limits the possibility to set up links between thresholds and physio-geographical factors.

Addressing the identification problem in age-period-cohort analysis: a tutorial on the use of partial least squares and principal components analysis.

PubMed

Tu, Yu-Kang; Krämer, Nicole; Lee, Wen-Chung

2012-07-01

In the analysis of trends in health outcomes, an ongoing issue is how to separate and estimate the effects of age, period, and cohort. As these 3 variables are perfectly collinear by definition, regression coefficients in a general linear model are not unique. In this tutorial, we review why identification is a problem, and how this problem may be tackled using partial least squares and principal components regression analyses. Both methods produce regression coefficients that fulfill the same collinearity constraint as the variables age, period, and cohort. We show that, because the constraint imposed by partial least squares and principal components regression is inherent in the mathematical relation among the 3 variables, this leads to more interpretable results. We use one dataset from a Taiwanese health-screening program to illustrate how to use partial least squares regression to analyze the trends in body heights with 3 continuous variables for age, period, and cohort. We then use another dataset of hepatocellular carcinoma mortality rates for Taiwanese men to illustrate how to use partial least squares regression to analyze tables with aggregated data. We use the second dataset to show the relation between the intrinsic estimator, a recently proposed method for the age-period-cohort analysis, and partial least squares regression. We also show that the inclusion of all indicator variables provides a more consistent approach. R code for our analyses is provided in the eAppendix.

WebGLORE: a Web service for Grid LOgistic REgression

PubMed Central

Jiang, Wenchao; Li, Pinghao; Wang, Shuang; Wu, Yuan; Xue, Meng; Ohno-Machado, Lucila; Jiang, Xiaoqian

2013-01-01

WebGLORE is a free web service that enables privacy-preserving construction of a global logistic regression model from distributed datasets that are sensitive. It only transfers aggregated local statistics (from participants) through Hypertext Transfer Protocol Secure to a trusted server, where the global model is synthesized. WebGLORE seamlessly integrates AJAX, JAVA Applet/Servlet and PHP technologies to provide an easy-to-use web service for biomedical researchers to break down policy barriers during information exchange. Availability and implementation: http://dbmi-engine.ucsd.edu/webglore3/. WebGLORE can be used under the terms of GNU general public license as published by the Free Software Foundation. Contact: x1jiang@ucsd.edu PMID:24072732

Local Table Condensation in Rough Set Approach for Jumping Emerging Pattern Induction

NASA Astrophysics Data System (ADS)

Terlecki, Pawel; Walczak, Krzysztof

This paper extends the rough set approach for JEP induction based on the notion of a condensed decision table. The original transaction database is transformed to a relational form and patterns are induced by means of local reducts. The transformation employs an item aggregation obtained by coloring a graph that re0ects con0icts among items. For e±ciency reasons we propose to perform this preprocessing locally, i.e. at the transaction level, to achieve a higher dimensionality gain. Special maintenance strategy is also used to avoid graph rebuilds. Both global and local approach have been tested and discussed for dense and synthetically generated sparse datasets.

Do changes in the labour market take families out of poverty? Determinants of exiting poverty in Brazilian metropolitan regions.

PubMed

Machado, Ana Flavia; Ribas, Rafael Perez Ribas

2010-01-01

Using survival models, we test whether short-term changes in the labour market affect poverty duration. Data are from the Brazilian Monthly Employment Survey. Such a monthly dataset permits more accurate estimations of events than using annual data, but its panel follows households for a short period. Then methods that control for both right- and left-censoring should be used. The results are as follows: households with zero income are not those with the lowest chances of exiting; changes in aggregate unemployment do not affect poverty duration; and increasing wages in the informal sector has a negative effect on poverty duration.

A graph algebra for scalable visual analytics.

PubMed

Shaverdian, Anna A; Zhou, Hao; Michailidis, George; Jagadish, Hosagrahar V

2012-01-01

Visual analytics (VA), which combines analytical techniques with advanced visualization features, is fast becoming a standard tool for extracting information from graph data. Researchers have developed many tools for this purpose, suggesting a need for formal methods to guide these tools' creation. Increased data demands on computing requires redesigning VA tools to consider performance and reliability in the context of analysis of exascale datasets. Furthermore, visual analysts need a way to document their analyses for reuse and results justification. A VA graph framework encapsulated in a graph algebra helps address these needs. Its atomic operators include selection and aggregation. The framework employs a visual operator and supports dynamic attributes of data to enable scalable visual exploration of data.

Increasing Juniperus virginiana L. pollen in the Tulsa atmosphere: long-term trends, variability, and influence of meteorological conditions

NASA Astrophysics Data System (ADS)

Flonard, Michaela; Lo, Esther; Levetin, Estelle

2018-02-01

In the Tulsa area, the Cupressaceae is largely represented by eastern red cedar ( Juniperus virginiana L.). The encroachment of this species into the grasslands of Oklahoma has been well documented, and it is believed this trend will continue. The pollen is known to be allergenic and is a major component of the Tulsa atmosphere in February and March. This study examined airborne Cupressaceae pollen data from 1987 to 2016 to determine long-term trends, pollen seasonal variability, and influence of meteorological variables on airborne pollen concentrations. Pollen was collected through means of a Burkard sampler and analyzed with microscopy. Daily pollen concentrations and yearly pollen metrics showed a high degree of variability. In addition, there were significant increases over time in the seasonal pollen index and in peak concentrations. These increases parallel the increasing population of J. virginiana in the region. Pollen data were split into pre- and post-peak categories for statistical analyses, which revealed significant differences in correlations of the two datasets when analyzed with meteorological conditions. While temperature and dew point, among others were significant in both datasets, other factors, like relative humidity, were significant only in one dataset. Analyses using wind direction showed that southerly and southwestern winds contributed to increased pollen concentrations. This study confirms that J. virginiana pollen has become an increasing risk for individuals sensitive to this pollen and emphasizes the need for long-term aerobiological monitoring in other areas.

The Long Valley Caldera GIS database

USGS Publications Warehouse

Battaglia, Maurizio; Williams, M.J.; Venezky, D.Y.; Hill, D.P.; Langbein, J.O.; Farrar, C.D.; Howle, J.F.; Sneed, M.; Segall, P.

2003-01-01

This database provides an overview of the studies being conducted by the Long Valley Observatory in eastern California from 1975 to 2001. The database includes geologic, monitoring, and topographic datasets related to Long Valley caldera. The CD-ROM contains a scan of the original geologic map of the Long Valley region by R. Bailey. Real-time data of the current activity of the caldera (including earthquakes, ground deformation and the release of volcanic gas), information about volcanic hazards and the USGS response plan are available online at the Long Valley observatory web page (http://lvo.wr.usgs.gov). If you have any comments or questions about this database, please contact the Scientist in Charge of the Long Valley observatory.

SIFlore, a dataset of geographical distribution of vascular plants covering five centuries of knowledge in France: Results of a collaborative project coordinated by the Federation of the National Botanical Conservatories.

PubMed

Just, Anaïs; Gourvil, Johan; Millet, Jérôme; Boullet, Vincent; Milon, Thomas; Mandon, Isabelle; Dutrève, Bruno

2015-01-01

More than 20 years ago, the French Muséum National d'Histoire Naturelle (MNHN, Secretariat of the Fauna and Flora) published the first part of an atlas of the flora of France at a 20km spatial resolution, accounting for 645 taxa (Dupont 1990). Since then, at the national level, there has not been any work on this scale relating to flora distribution, despite the obvious need for a better understanding. In 2011, in response to this need, the Federation des Conservatoires Botaniques Nationaux (FCBN, http://www.fcbn.fr) launched an ambitious collaborative project involving eleven national botanical conservatories of France. The project aims to establish a formal procedure and standardized system for data hosting, aggregation and publication for four areas: flora, fungi, vegetation and habitats. In 2014, the first phase of the project led to the development of the national flora dataset: SIFlore. As it includes about 21 million records of flora occurrences, this is currently the most comprehensive dataset on the distribution of vascular plants (Tracheophyta) in the French territory. SIFlore contains information for about 15'454 plant taxa occurrences (indigenous and alien taxa) in metropolitan France and Reunion Island, from 1545 until 2014. The data records were originally collated from inventories, checklists, literature and herbarium records. SIFlore was developed by assembling flora datasets from the regional to the national level. At the regional level, source records are managed by the national botanical conservatories that are responsible for flora data collection and validation. In order to present our results, a geoportal was developed by the Fédération des conservatoires botaniques nationaux that allows the SIFlore dataset to be publically viewed. This portal is available at: http://siflore.fcbn.fr. As the FCBN belongs to the Information System for Nature and Landscapes' (SINP), a governmental program, the dataset is also accessible through the websites of the National Inventory of Natural Heritage (http://www.inpn.fr) and the Global Biodiversity Information Facility (http://www.gbif.fr). SIFlore is regularly updated with additional data records. It is also planned to expand the scope of the dataset to include information about taxon biology, phenology, ecology, chorology, frequency, conservation status and seed banks. A map showing an estimation of the dataset completeness (based on Jackknife 1 estimator) is presented and included as a numerical appendix. SIFlore aims to make the data of the flora of France available at the national level for conservation, policy management and scientific research. Such a dataset will provide enough information to allow for macro-ecological reviews of species distribution patterns and, coupled with climatic or topographic datasets, the identification of determinants of these patterns. This dataset can be considered as the primary indicator of the current state of knowledge of flora distribution across France. At a policy level, and in the context of global warming, this should promote the adoption of new measures aiming to improve and intensify flora conservation and surveys.

SIFlore, a dataset of geographical distribution of vascular plants covering five centuries of knowledge in France: Results of a collaborative project coordinated by the Federation of the National Botanical Conservatories

PubMed Central

Just, Anaïs; Gourvil, Johan; Millet, Jérôme; Boullet, Vincent; Milon, Thomas; Mandon, Isabelle; Dutrève, Bruno

2015-01-01

Abstract More than 20 years ago, the French Muséum National d’Histoire Naturelle1 (MNHN, Secretariat of the Fauna and Flora) published the first part of an atlas of the flora of France at a 20km spatial resolution, accounting for 645 taxa (Dupont 1990). Since then, at the national level, there has not been any work on this scale relating to flora distribution, despite the obvious need for a better understanding. In 2011, in response to this need, the Federation des Conservatoires Botaniques Nationaux2 (FCBN, http://www.fcbn.fr) launched an ambitious collaborative project involving eleven national botanical conservatories of France. The project aims to establish a formal procedure and standardized system for data hosting, aggregation and publication for four areas: flora, fungi, vegetation and habitats. In 2014, the first phase of the project led to the development of the national flora dataset: SIFlore. As it includes about 21 million records of flora occurrences, this is currently the most comprehensive dataset on the distribution of vascular plants (Tracheophyta) in the French territory. SIFlore contains information for about 15'454 plant taxa occurrences (indigenous and alien taxa) in metropolitan France and Reunion Island, from 1545 until 2014. The data records were originally collated from inventories, checklists, literature and herbarium records. SIFlore was developed by assembling flora datasets from the regional to the national level. At the regional level, source records are managed by the national botanical conservatories that are responsible for flora data collection and validation. In order to present our results, a geoportal was developed by the Fédération des conservatoires botaniques nationaux that allows the SIFlore dataset to be publically viewed. This portal is available at: http://siflore.fcbn.fr. As the FCBN belongs to the Information System for Nature and Landscapes’ (SINP), a governmental program, the dataset is also accessible through the websites of the National Inventory of Natural Heritage (http://www.inpn.fr) and the Global Biodiversity Information Facility (http://www.gbif.fr). SIFlore is regularly updated with additional data records. It is also planned to expand the scope of the dataset to include information about taxon biology, phenology, ecology, chorology, frequency, conservation status and seed banks. A map showing an estimation of the dataset completeness (based on Jackknife 1 estimator) is presented and included as a numerical appendix. Purpose: SIFlore aims to make the data of the flora of France available at the national level for conservation, policy management and scientific research. Such a dataset will provide enough information to allow for macro-ecological reviews of species distribution patterns and, coupled with climatic or topographic datasets, the identification of determinants of these patterns. This dataset can be considered as the primary indicator of the current state of knowledge of flora distribution across France. At a policy level, and in the context of global warming, this should promote the adoption of new measures aiming to improve and intensify flora conservation and surveys. PMID:26491386

Integrating spatial modeling, climate change scenarios, invasive species risk, and public perceptions to inform sustainable management in mixed hemlock-hardwood forests in Maine

NASA Astrophysics Data System (ADS)

Dunckel, Kathleen Lois

Introduced invasive pests and climate change are perhaps the most important and persistent catalyst for changes in forest composition. Infestation and outbreak of the hemlock woolly adelgid (HWA, Adelges tsugae) along the eastern coast of the USA, has led to widespread loss of hemlock (Tsuga canadensis (L.) Carr.), and a shift in tree species composition towards hardwood stands. Maine's forest dominated landscape and position at the leading edge of the HWA invasion provides an excellent opportunity to inform sustainable forest management (SFM) practices by using spatially explicit models to predict current tree species distribution, future range shifts, and solicit broad based feedback from Maine residents about forest management goals and preferences. This paper describes an interdisciplinary study of the ecological and social implications of changes in mixed northern hardwood forests due to disturbance. A two stage mapping approach was used where presence/absence of eastern hemlock is predicted with an overall accuracy of 85% and the continuous distribution (% basal area) was predicted with an accuracy of 83%. Given the importance of climate variables in predicting eastern hemlock, forecasts of future range shifts are possible using data generated through climate scenarios. The NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) dataset was used to model future shifts in the geographic range of eastern hemlock throughout the state of Maine. The results clearly describe a significant shift in eastern hemlock range with gains in total geographic area that is suitable habitat. Sustaining forest systems across the landscape requires not only ecological knowledge, but also the integration of multiple socio-economic criteria as well, including data obtained through broad-based public participation approaches. Here, 3000 Maine residents were surveyed and asked how they: (1) value local forests; (2) view forest management goals and threats to forest ecosystems; and (3) evaluate alternative treatment options for the control of invasive species - in this case, HWA. Results suggest that despite Maine's historic dependence on forest products, resident values regarding forests are complex and display agreement with both psycho-spiritual and anthropocentric motivations.

Cetacean distribution and abundance in relation to oceanographic domains on the eastern Bering Sea shelf: 1999-2004

NASA Astrophysics Data System (ADS)

Friday, Nancy A.; Waite, Janice M.; Zerbini, Alexandre N.; Moore, Sue E.

2012-06-01

Visual line transect surveys for cetaceans were conducted on the eastern Bering Sea shelf in association with pollock stock assessment surveys aboard the NOAA ship Miller Freeman in June and July of 1999, 2000, 2002, and 2004. Transect survey effort ranged from 1188 km in 1999 to 3761 km in 2002. Fin whales (Balaenoptera physalus) were the most common large whale in all years except 2004 when humpback whales (Megaptera novaeangliae) were more abundant. Dall's porpoise (Phocoenoides dalli) were the most common small cetacean in all years. Abundance estimates were calculated by year for each oceanographic domain: coastal, middle, and outer/slope. The middle and outer/slope domains were divided into two strata ("north" and "south") because of variable survey effort. The distribution and abundance of baleen whales changed between the earlier (colder) and later (warmer) survey years. Fin whales consistently occupied the outer shelf and secondarily the middle shelf, and their abundance was an order of magnitude greater in cold compared to warm years. Humpback whales "lived on the margin" of the northern Alaska Peninsula, eastern Aleutian Islands and Bristol Bay; their preferred habitat is possibly associated with areas of high prey availability due to nutrient upwelling and aggregation mechanisms. Minke whales (Balaenoptera acutorostrata) occur shoreward of fin whales in the outer and middle shelf and in coastal habitats along the Alaska Peninsula. The highest abundance for this species was observed in a cold (1999) year. No clear relationship emerged for odontocetes with regard to warm and cold years. Dall's porpoise occupied both outer and middle domains and harbor porpoise (Phocoena phocoena) were more common in middle and coastal domains. This study provided a unique, broad-scale assessment of cetacean distribution and abundance on the eastern Bering Sea shelf and a baseline for future comparisons.

The shallow-water fish assemblage of Isla del Coco National Park, Costa Rica: Structure and patterns in an isolated, predator-dominated ecosystem

USGS Publications Warehouse

Friedlander, Alan M.; Zgliczynski, Brian J.; Ballesteros, Enric; Aburto-Oropeza, Octavio; Bolaños, Allan; Sala, Enric

2012-01-01

Fishes at Isla del Coco National Park, Costa Rica, were surveyed as part of a larger scientific expedition to the area in September 2009. The average total biomass of nearshore fishes was 7.8 tonnes per ha, among the largest observed in the tropics, with apex predators such as sharks, jacks, and groupers accounting for nearly 40% of the total biomass. The abundance of reef and pelagic sharks, particularly large aggregations of threatened species such as the scalloped hammerhead shark (up to 42 hammerheads ha-1) and large schools of jacks and snappers show the capacity for high biomass in unfished ecosystems in the Eastern Tropical Pacific. However, the abundance of hammerhead and reef whitetip sharks appears to have been declining since the late 1990s, and likely causes may include increasing fishing pressure on sharks in the region and illegal fishing inside the Park. One Galapagos shark tagged on September 20, 2009 in the Isla del Coco National Park moved 255km southeast towards Malpelo Island in Colombia, when it stopped transmitting. These results contribute to the evidence that sharks conduct large-scale movements between marine protected areas (Isla del Coco, Malpelo, Galápagos) in the Eastern tropical Pacific and emphasize the need for regional-scale management. More than half of the species and 90% of the individuals observed were endemic to the tropical eastern Pacific. These high biomass and endemicity values highlight the uniqueness of the fish assemblage at Isla del Coco and its importance as a global biodiversity hotspot.

Early-to-middle Holocene sea-level fluctuations, coastal progradation and the Neolithic occupations in Yaojiang valley of southern Hangzhou bay, eastern China

NASA Astrophysics Data System (ADS)

Liu, Y.; Sun, Q.; Fan, D.; Chen, Z.

2017-12-01

The formation of Holocene coast in eastern China provided material base for the development of Neolithic civilizations. The coastal Yaojiang valley of south Hangzhou bay was one of the examples where the well-known Neolithic Hemudu Culture (HC) of Eastern China initiated. Here, we studied the early-to-middle Holocene environment changes in relation to sea-level fluctuations on the basis of a serial of sediment cores based on a set of new Accelerator Mass Spectrometry radiocarbon (AMS 14C) chronology. The result indicated that relative sea-level rose rapidly in the Yaojiang valley at the early Holocene, reaching its maximum at ca. 8000-7800 cal yr BP and then decelerated at ca. 7800-7500 cal yr BP. The alluvial plain in Yaojiang valley began to form at the foothills first and then grew towards the valley center accompanying with the sea-level stabilization after ca. 7500 cal yr BP. This progressive progradation of alluvial plain would attract the early arrivals of foragers to dwell at the foothills to engaging in rice farming after ca.7000 cal yr BP and starting the epic Hemudu Culture. The HC people then move down to the valley center as more land became available thanks to sediment aggregation and progradation. The rise and development of HC were closely associated with the sea-level induced landscape changes in Yaojiang valley at the early-middle Holocene, and the unstable hydraulic condition in the valley after 5000 cal yr BP could be accountable for the cultural termination.

European emissions of halogenated greenhouse gases inferred from atmospheric measurements.

PubMed

Keller, Christoph A; Hill, Matthias; Vollmer, Martin K; Henne, Stephan; Brunner, Dominik; Reimann, Stefan; O'Doherty, Simon; Arduini, Jgor; Maione, Michela; Ferenczi, Zita; Haszpra, Laszlo; Manning, Alistair J; Peter, Thomas

2012-01-03

European emissions of nine representative halocarbons (CFC-11, CFC-12, Halon 1211, HCFC-141b, HCFC-142b, HCFC-22, HFC-125, HFC-134a, HFC-152a) are derived for the year 2009 by combining long-term observations in Switzerland, Italy, and Ireland with campaign measurements from Hungary. For the first time, halocarbon emissions over Eastern Europe are assessed by top-down methods, and these results are compared to Western European emissions. The employed inversion method builds on least-squares optimization linking atmospheric observations with calculations from the Lagrangian particle dispersion model FLEXPART. The aggregated halocarbon emissions over the study area are estimated at 125 (106-150) Tg of CO(2) equiv/y, of which the hydrofluorocarbons (HFCs) make up the most important fraction with 41% (31-52%). We find that chlorofluorocarbon (CFC) emissions from banks are still significant and account for 35% (27-43%) of total halocarbon emissions in Europe. The regional differences in per capita emissions are only small for the HFCs, while emissions of CFCs and hydrochlorofluorocarbons (HCFCs) tend to be higher in Western Europe compared to Eastern Europe. In total, the inferred per capita emissions are similar to estimates for China, but 3.5 (2.3-4.5) times lower than for the United States. Our study demonstrates the large benefits of adding a strategically well placed measurement site to the existing European observation network of halocarbons, as it extends the coverage of the inversion domain toward Eastern Europe and helps to better constrain the emissions over Central Europe.

Implementation of a deidentified federated data network for population-based cohort discovery

PubMed Central

Abend, Aaron; Mandel, Aaron; Geraghty, Estella; Gabriel, Davera; Wynden, Rob; Kamerick, Michael; Anderson, Kent; Rainwater, Julie; Tarczy-Hornoch, Peter

2011-01-01

Objective The Cross-Institutional Clinical Translational Research project explored a federated query tool and looked at how this tool can facilitate clinical trial cohort discovery by managing access to aggregate patient data located within unaffiliated academic medical centers. Methods The project adapted software from the Informatics for Integrating Biology and the Bedside (i2b2) program to connect three Clinical Translational Research Award sites: University of Washington, Seattle, University of California, Davis, and University of California, San Francisco. The project developed an iterative spiral software development model to support the implementation and coordination of this multisite data resource. Results By standardizing technical infrastructures, policies, and semantics, the project enabled federated querying of deidentified clinical datasets stored in separate institutional environments and identified barriers to engaging users for measuring utility. Discussion The authors discuss the iterative development and evaluation phases of the project and highlight the challenges identified and the lessons learned. Conclusion The common system architecture and translational processes provide high-level (aggregate) deidentified access to a large patient population (>5 million patients), and represent a novel and extensible resource. Enhancing the network for more focused disease areas will require research-driven partnerships represented across all partner sites. PMID:21873473

The impact of the dimensions of environmental performance on firm performance in travel and tourism industry.

PubMed

Tan, Siow-Hooi; Habibullah, Muzafar Shah; Tan, Siow-Kian; Choon, Shay-Wei

2017-12-01

This study investigates the impact of the aggregate and individual dimensions of environmental performance (EP) on financial performance (FP), based on a dataset covering the travel and tourism industry (airlines, casinos, hotels, and restaurants) across different economic regions over the period 2003-2014. The results reveal that EP positively affects the FP in the hotel industry when aggregate EP is used. When individual dimensions of EP are considered, resource reduction is found to positively (negatively) affect the performance in the hotel (airline) industry, while product innovation positively affects the performance in the restaurant industry. Hence, the trade-off effect seems to be dominant in the airline industry, and the 'heterogeneous resources and reputation-building' hypothesis is evident in both the hotel and restaurant industries. In addition, in general, the findings support the positive moderating effect of slack resources on the relationship between the individual dimensions of EP and FP in the travel and tourism industry, and, hence, are supportive of the slack resources hypothesis. These effects, however, vary depending on the travel and tourism industry under investigation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Implementation of a deidentified federated data network for population-based cohort discovery.

PubMed

Anderson, Nicholas; Abend, Aaron; Mandel, Aaron; Geraghty, Estella; Gabriel, Davera; Wynden, Rob; Kamerick, Michael; Anderson, Kent; Rainwater, Julie; Tarczy-Hornoch, Peter

2012-06-01

The Cross-Institutional Clinical Translational Research project explored a federated query tool and looked at how this tool can facilitate clinical trial cohort discovery by managing access to aggregate patient data located within unaffiliated academic medical centers. The project adapted software from the Informatics for Integrating Biology and the Bedside (i2b2) program to connect three Clinical Translational Research Award sites: University of Washington, Seattle, University of California, Davis, and University of California, San Francisco. The project developed an iterative spiral software development model to support the implementation and coordination of this multisite data resource. By standardizing technical infrastructures, policies, and semantics, the project enabled federated querying of deidentified clinical datasets stored in separate institutional environments and identified barriers to engaging users for measuring utility. The authors discuss the iterative development and evaluation phases of the project and highlight the challenges identified and the lessons learned. The common system architecture and translational processes provide high-level (aggregate) deidentified access to a large patient population (>5 million patients), and represent a novel and extensible resource. Enhancing the network for more focused disease areas will require research-driven partnerships represented across all partner sites.

Application Of Empirical Phase Diagrams For Multidimensional Data Visualization Of High Throughput Microbatch Crystallization Experiments.

PubMed

Klijn, Marieke E; Hubbuch, Jürgen

2018-04-27

Protein phase diagrams are a tool to investigate cause and consequence of solution conditions on protein phase behavior. The effects are scored according to aggregation morphologies such as crystals or amorphous precipitates. Solution conditions affect morphological features, such as crystal size, as well as kinetic features, such as crystal growth time. Common used data visualization techniques include individual line graphs or symbols-based phase diagrams. These techniques have limitations in terms of handling large datasets, comprehensiveness or completeness. To eliminate these limitations, morphological and kinetic features obtained from crystallization images generated with high throughput microbatch experiments have been visualized with radar charts in combination with the empirical phase diagram (EPD) method. Morphological features (crystal size, shape, and number, as well as precipitate size) and kinetic features (crystal and precipitate onset and growth time) are extracted for 768 solutions with varying chicken egg white lysozyme concentration, salt type, ionic strength and pH. Image-based aggregation morphology and kinetic features were compiled into a single and easily interpretable figure, thereby showing that the EPD method can support high throughput crystallization experiments in its data amount as well as its data complexity. Copyright © 2018. Published by Elsevier Inc.

Modelling of 67P cometary grains dynamic in the vicinity of the Rosetta spacecraft

NASA Astrophysics Data System (ADS)

Cipriani, F.; Altobelli, N.; Taylor, M.; Fulle, M.; Della Corte, V.; Rotundi, A.

2017-09-01

The interpretation of a number of Rosetta datasets (e.g. GIADA, COSIMA, MIDAS...), relies on the description of cometary grains dynamic in the close vicinity of the spacecraft. In particular the charged grains behaviour in the 3D spacecraft sheath open to the instrument entrances is complex and has not been described at such scales. The existence of a warm electrons population (a few 10eVs energy) in the cometary plasma as revealed during the Rendez-vous phase has been driving the spacecraft potential to negative values typically in the range -1 to -20V as inferred from RPC measurements [1]. Observation of cometary grains in the 10μm to mm range by GIADA and COSIMA[2] allowed to distinguish so called 'compact' grains of processed materials from the solar nebula from 'fluffy' aggregates of more primitive origin. When detected such grains have been observed to reach the instruments at m/s or less velocities. On particular it was inferred that fluffy aggregates are disrupted by electrostatic forces in the vicinity of the spacecraft due to the effects of local plasma hence resulting in particle showers observed by the instruments.

LOST CREEK ROADLESS AREA, CALIFORNIA.

USGS Publications Warehouse

Muffler, L.J. Patrick; Campbell, Harry W.

1984-01-01

Geologic and mineral-resource investigations identified no mineral-resource potential in the Lost Creek Roadless Area, California. Sand and gravel have been mined from alluvial flood-plain deposits less than 1 mi outside the roadless area; these deposits are likely to extend into the roadless area beneath a Holocene basalt flow that may be as much as 40 ft thick. An oil and gas lease application which includes the eastern portion of the roadless area is pending. Abundant basalt in the area can be crushed and used as aggregate, but similar deposits of volcanic cinders or sand and gravel in more favorable locations are available outside the roadless area closer to major markets. No indication of coal or geothermal energy resources was identified.

Global invasion network of the brown marmorated stink bug, Halyomorpha halys.

PubMed

Valentin, Rafael E; Nielsen, Anne L; Wiman, Nik G; Lee, Doo-Hyung; Fonseca, Dina M

2017-08-29

Human mediated transportation into novel habitats is a prerequisite for the establishment of non-native species that become invasive, so knowledge of common sources may allow prevention. The brown marmorated stink bug (BMSB, Halyomorpha halys) is an East Asian species now established across North America and Europe, that in the Eastern United States of America (US) and Italy is causing significant economic losses to agriculture. After US populations were shown to originate from Northern China, others have tried to source BMSB populations now in Canada, Switzerland, Italy, France, Greece, and Hungary. Due to selection of different molecular markers, however, integrating all the datasets to obtain a broader picture of BMSB's expansion has been difficult. To address this limitation we focused on a single locus, the barcode region in the cytochrome oxidase I mitochondrial gene, and analyzed representative BMSB samples from across its current global range using an Approximate Bayesian Computation approach. We found that China is the likely source of most non-native populations, with at least four separate introductions in North America and three in Europe. Additionally, we found evidence of one bridgehead event: a likely Eastern US source for the central Italy populations that interestingly share enhanced pest status.

Application of a degree-day model of West Nile virus transmission risk to the East Coast of the United States of America.

PubMed

Konrad, Sarah K; Miller, Scott N

2012-11-01

A geographical information systems model that identifies regions of the United States of America (USA) susceptible to West Nile virus (WNV) transmission risk is presented. This system has previously been calibrated and tested in the western USA; in this paper we use datasets of WNV-killed birds from South Carolina and Connecticut to test the model in the eastern USA. Because their response to WNV infection is highly predictable, American crows were chosen as the primary source for model calibration and testing. Where crow data are absent, other birds are shown to be an effective substitute. Model results show that the same calibrated model demonstrated to work in the western USA has the same predictive ability in the eastern USA, allowing for a continental-scale evaluation of the transmission risk of WNV at a daily time step. The calibrated model is independent of mosquito species and requires inputs of only local maximum and minimum temperatures. Of benefit to the general public and vector control districts, the model predicts the onset of seasonal transmission risk, although it is less effective at identifying the end of the transmission risk season.

Insights into crustal structure of the Eastern North American Margin from community multichannel seismic and potential field data

NASA Astrophysics Data System (ADS)

Davis, J. K.; Becel, A.; Shillington, D. J.; Buck, W. R.

2017-12-01

In the fall of 2014, the R/V Marcus Langseth collected gravity, magnetic, and reflection seismic data as part of the Eastern North American Margin Community Seismic Experiment. The dataset covers a 500 km wide section of the Mid-Atlantic passive margin offshore North Carolina, which formed after the Mesozoic breakup of the supercontinent Pangaea. Using these seismic and potential field data, we present observations and interpretations along two cross margin and one along-margin profiles. Analyses and interpretations are conducted using pre-stack depth migrated reflection seismic profiles in conjunction with forward modeling of shipboard gravity and magnetic anomalies. Preliminary interpretations of the data reveal variations in basement character and structure across the entire transition between continental and oceanic domains. These interpretations help provide insight into the origin and nature of the prominent East Coast and Blake Spur magnetic anomalies, as well as the Inner Magnetic Quiet Zone which occupies the domain between the anomalies. Collectively, these observations can aid in deciphering the rift-to-drift transition during the breakup of North America and West Africa and formation of the Central Atlantic.

Partitioning Evapotranspiration into Green and Blue Water Sources in the Conterminous United States.

PubMed

Velpuri, Naga Manohar; Senay, Gabriel B

2017-07-21

In this study, we combined two 1 km actual evapotranspiration datasets (ET), one obtained from a root zone water balance model and another from an energy balance model, to partition annual ET into green (rainfall-based) and blue (surface water/groundwater) sources. Time series maps of green water ET (GWET) and blue water ET (BWET) are produced for the conterminous United States (CONUS) over 2001-2015. Our results indicate that average green and blue water for all land cover types in CONUS accounts for nearly 70% and 30% of the total ET, respectively. The ET in the eastern US arises mostly from GWET, and in the western US, it is mostly BWET. Analysis of the BWET in the 16 irrigated areas in CONUS revealed interesting results. While the magnitude of the BWET gradually showed a decline from west to east, the increase in coefficient of variation from west to east confirmed greater use of supplemental irrigation in the central and eastern US. We also established relationships between different hydro-climatology zones and their blue water requirements. This study provides insights on the relative contributions and the spatiotemporal dynamics of GWET and BWET, which could lead to improved water resources management.

Gas hydrate characterization from a 3D seismic dataset in the deepwater eastern Gulf of Mexico

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

McConnell, Daniel; Haneberg, William C.

Seismic stratigraphic features are delineated using principal component analysis of the band limited data at potential gas hydrate sands, and compared and calibrated with spectral decomposition thickness to constrain thickness in the absence of well control. Layers in the abyssal fan sediments are thinner than can be resolved with 50 Hz seismic and thus comprise composite thin-bed reflections. Amplitude vs frequency analysis are used to indicate gas and gas hydrate reflections. Synthetic seismic wedge models show that with 50Hz seismic data, a 40% saturation of a Plio Pleistocene GoM sand in the hydrate stability zone with no subjacent gas canmore » produce a phase change (negative to positive) with a strong correlation between amplitude and hydrate saturation. The synthetic seismic response is more complicated if the gas hydrate filled sediments overlie gassy sediments. Hydrate (or gas) saturation in thin beds enhances the amplitude response and can be used to estimate saturation. Gas hydrate saturation from rock physics, amplitude, and frequency analysis is compared to saturation derived from inversion at several interpreted gas hydrate accumulations in the eastern Gulf of Mexico.« less

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

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

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

Interactive Visualization and Analysis of Geospatial Data Sets - TrikeND-iGlobe

NASA Astrophysics Data System (ADS)

Rosebrock, Uwe; Hogan, Patrick; Chandola, Varun

2013-04-01

The visualization of scientific datasets is becoming an ever-increasing challenge as advances in computing technologies have enabled scientists to build high resolution climate models that have produced petabytes of climate data. To interrogate and analyze these large datasets in real-time is a task that pushes the boundaries of computing hardware and software. But integration of climate datasets with geospatial data requires considerable amount of effort and close familiarity of various data formats and projection systems, which has prevented widespread utilization outside of climate community. TrikeND-iGlobe is a sophisticated software tool that bridges this gap, allows easy integration of climate datasets with geospatial datasets and provides sophisticated visualization and analysis capabilities. The objective for TrikeND-iGlobe is the continued building of an open source 4D virtual globe application using NASA World Wind technology that integrates analysis of climate model outputs with remote sensing observations as well as demographic and environmental data sets. This will facilitate a better understanding of global and regional phenomenon, and the impact analysis of climate extreme events. The critical aim is real-time interactive interrogation. At the data centric level the primary aim is to enable the user to interact with the data in real-time for the purpose of analysis - locally or remotely. TrikeND-iGlobe provides the basis for the incorporation of modular tools that provide extended interactions with the data, including sub-setting, aggregation, re-shaping, time series analysis methods and animation to produce publication-quality imagery. TrikeND-iGlobe may be run locally or can be accessed via a web interface supported by high-performance visualization compute nodes placed close to the data. It supports visualizing heterogeneous data formats: traditional geospatial datasets along with scientific data sets with geographic coordinates (NetCDF, HDF, etc.). It also supports multiple data access mechanisms, including HTTP, FTP, WMS, WCS, and Thredds Data Server (for NetCDF data and for scientific data, TrikeND-iGlobe supports various visualization capabilities, including animations, vector field visualization, etc. TrikeND-iGlobe is a collaborative open-source project, contributors include NASA (ARC-PX), ORNL (Oakridge National Laboratories), Unidata, Kansas University, CSIRO CMAR Australia and Geoscience Australia.

Web-based interactive access, analysis and comparison of remotely sensed and in situ measured temperature data

NASA Astrophysics Data System (ADS)

Eberle, Jonas; Urban, Marcel; Hüttich, Christian; Schmullius, Christiane

2014-05-01

Numerous datasets providing temperature information from meteorological stations or remote sensing satellites are available. However, the challenging issue is to search in the archives and process the time series information for further analysis. These steps can be automated for each individual product, if the pre-conditions are complied, e.g. data access through web services (HTTP, FTP) or legal rights to redistribute the datasets. Therefore a python-based package was developed to provide data access and data processing tools for MODIS Land Surface Temperature (LST) data, which is provided by NASA Land Processed Distributed Active Archive Center (LPDAAC), as well as the Global Surface Summary of the Day (GSOD) and the Global Historical Climatology Network (GHCN) daily datasets provided by NOAA National Climatic Data Center (NCDC). The package to access and process the information is available as web services used by an interactive web portal for simple data access and analysis. Tools for time series analysis were linked to the system, e.g. time series plotting, decomposition, aggregation (monthly, seasonal, etc.), trend analyses, and breakpoint detection. Especially for temperature data a plot was integrated for the comparison of two temperature datasets based on the work by Urban et al. (2013). As a first result, a kernel density plot compares daily MODIS LST from satellites Aqua and Terra with daily means from GSOD and GHCN datasets. Without any data download and data processing, the users can analyze different time series datasets in an easy-to-use web portal. As a first use case, we built up this complimentary system with remotely sensed MODIS data and in situ measurements from meteorological stations for Siberia within the Siberian Earth System Science Cluster (www.sibessc.uni-jena.de). References: Urban, Marcel; Eberle, Jonas; Hüttich, Christian; Schmullius, Christiane; Herold, Martin. 2013. "Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale." Remote Sens. 5, no. 5: 2348-2367. Further materials: Eberle, Jonas; Clausnitzer, Siegfried; Hüttich, Christian; Schmullius, Christiane. 2013. "Multi-Source Data Processing Middleware for Land Monitoring within a Web-Based Spatial Data Infrastructure for Siberia." ISPRS Int. J. Geo-Inf. 2, no. 3: 553-576.

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

DOE PAGES

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith; ...

2017-11-06

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

Snow observations in Mount Lebanon (2011-2016)

NASA Astrophysics Data System (ADS)

Fayad, Abbas; Gascoin, Simon; Faour, Ghaleb; Fanise, Pascal; Drapeau, Laurent; Somma, Janine; Fadel, Ali; Bitar, Ahmad Al; Escadafal, Richard

2017-08-01

We present a unique meteorological and snow observational dataset in Mount Lebanon, a mountainous region with a Mediterranean climate, where snowmelt is an essential water resource. The study region covers the recharge area of three karstic river basins (total area of 1092 km2 and an elevation up to 3088 m). The dataset consists of (1) continuous meteorological and snow height observations, (2) snowpack field measurements, and (3) medium-resolution satellite snow cover data. The continuous meteorological measurements at three automatic weather stations (MZA, 2296 m; LAQ, 1840 m; and CED, 2834 m a.s.l.) include surface air temperature and humidity, precipitation, wind speed and direction, incoming and reflected shortwave irradiance, and snow height, at 30 min intervals for the snow seasons (November-June) between 2011 and 2016 for MZA and between 2014 and 2016 for CED and LAQ. Precipitation data were filtered and corrected for Geonor undercatch. Observations of snow height (HS), snow water equivalent, and snow density were collected at 30 snow courses located at elevations between 1300 and 2900 m a.s.l. during the two snow seasons of 2014-2016 with an average revisit time of 11 days. Daily gap-free snow cover extent (SCA) and snow cover duration (SCD) maps derived from MODIS snow products are provided for the same period (2011-2016). We used the dataset to characterize mean snow height, snow water equivalent (SWE), and density for the first time in Mount Lebanon. Snow seasonal variability was characterized with high HS and SWE variance and a relatively high snow density mean equal to 467 kg m-3. We find that the relationship between snow depth and snow density is specific to the Mediterranean climate. The current model explained 34 % of the variability in the entire dataset (all regions between 1300 and 2900 m a.s.l.) and 62 % for high mountain regions (elevation 2200-2900 m a.s.l.). The dataset is suitable for the investigation of snow dynamics and for the forcing and validation of energy balance models. Therefore, this dataset bears the potential to greatly improve the quantification of snowmelt and mountain hydrometeorological processes in this data-scarce region of the eastern Mediterranean. The DOI for the data is https://doi.org/10.5281/zenodo.583733.