A Study of Memory Effects in a Chess Database

PubMed Central

Schaigorodsky, Ana L.; Perotti, Juan I.; Billoni, Orlando V.

2016-01-01

A series of recent works studying a database of chronologically sorted chess games–containing 1.4 million games played by humans between 1998 and 2007– have shown that the popularity distribution of chess game-lines follows a Zipf’s law, and that time series inferred from the sequences of those game-lines exhibit long-range memory effects. The presence of Zipf’s law together with long-range memory effects was observed in several systems, however, the simultaneous emergence of these two phenomena were always studied separately up to now. In this work, by making use of a variant of the Yule-Simon preferential growth model, introduced by Cattuto et al., we provide an explanation for the simultaneous emergence of Zipf’s law and long-range correlations memory effects in a chess database. We find that Cattuto’s Model (CM) is able to reproduce both, Zipf’s law and the long-range correlations, including size-dependent scaling of the Hurst exponent for the corresponding time series. CM allows an explanation for the simultaneous emergence of these two phenomena via a preferential growth dynamics, including a memory kernel, in the popularity distribution of chess game-lines. This mechanism results in an aging process in the chess game-line choice as the database grows. Moreover, we find burstiness in the activity of subsets of the most active players, although the aggregated activity of the pool of players displays inter-event times without burstiness. We show that CM is not able to produce time series with bursty behavior providing evidence that burstiness is not required for the explanation of the long-range correlation effects in the chess database. Our results provide further evidence favoring the hypothesis that long-range correlations effects are a consequence of the aging of game-lines and not burstiness, and shed light on the mechanism that operates in the simultaneous emergence of Zipf’s law and long-range correlations in a community of chess players. PMID:28005922

Atrial fibrillation detection using an iPhone 4S.

PubMed

Lee, Jinseok; Reyes, Bersain A; McManus, David D; Maitas, Oscar; Mathias, Oscar; Chon, Ki H

2013-01-01

Atrial fibrillation (AF) affects three to five million Americans and is associated with significant morbidity and mortality. Existing methods to diagnose this paroxysmal arrhythmia are cumbersome and/or expensive. We hypothesized that an iPhone 4S can be used to detect AF based on its ability to record a pulsatile photoplethysmogram signal from a fingertip using the built-in camera lens. To investigate the capability of the iPhone 4S for AF detection, we first used two databases, the MIT-BIH AF and normal sinus rhythm (NSR) to derive discriminatory threshold values between two rhythms. Both databases include RR time series originating from 250 Hz sampled ECG recordings. We rescaled the RR time series to 30 Hz so that the RR time series resolution is 1/30 (s) which is equivalent to the resolution from an iPhone 4S. We investigated three statistical methods consisting of the root mean square of successive differences (RMSSD), the Shannon entropy (ShE) and the sample entropy (SampE), which have been proved to be useful tools for AF assessment. Using 64-beat segments from the MIT-BIH databases, we found the beat-to-beat accuracy value of 0.9405, 0.9300, and 0.9614 for RMSSD, ShE, and SampE, respectively. Using an iPhone 4S, we collected 2-min pulsatile time series from 25 prospectively recruited subjects with AF pre- and postelectrical cardioversion. Using derived threshold values of RMSSD, ShE and SampE from the MIT-BIH databases, we found the beat-to-beat accuracy of 0.9844, 0.8494, and 0.9522, respectively. It should be recognized that for clinical applications, the most relevant objective is to detect the presence of AF in the data. Using this criterion, we achieved an accuracy of 100% for both the MIT-BIH AF and iPhone 4S databases.

Cluster analysis of word frequency dynamics

NASA Astrophysics Data System (ADS)

Maslennikova, Yu S.; Bochkarev, V. V.; Belashova, I. A.

2015-01-01

This paper describes the analysis and modelling of word usage frequency time series. During one of previous studies, an assumption was put forward that all word usage frequencies have uniform dynamics approaching the shape of a Gaussian function. This assumption can be checked using the frequency dictionaries of the Google Books Ngram database. This database includes 5.2 million books published between 1500 and 2008. The corpus contains over 500 billion words in American English, British English, French, German, Spanish, Russian, Hebrew, and Chinese. We clustered time series of word usage frequencies using a Kohonen neural network. The similarity between input vectors was estimated using several algorithms. As a result of the neural network training procedure, more than ten different forms of time series were found. They describe the dynamics of word usage frequencies from birth to death of individual words. Different groups of word forms were found to have different dynamics of word usage frequency variations.

AQUAdexIM: highly efficient in-memory indexing and querying of astronomy time series images

NASA Astrophysics Data System (ADS)

Hong, Zhi; Yu, Ce; Wang, Jie; Xiao, Jian; Cui, Chenzhou; Sun, Jizhou

2016-12-01

Astronomy has always been, and will continue to be, a data-based science, and astronomers nowadays are faced with increasingly massive datasets, one key problem of which is to efficiently retrieve the desired cup of data from the ocean. AQUAdexIM, an innovative spatial indexing and querying method, performs highly efficient on-the-fly queries under users' request to search for Time Series Images from existing observation data on the server side and only return the desired FITS images to users, so users no longer need to download entire datasets to their local machines, which will only become more and more impractical as the data size keeps increasing. Moreover, AQUAdexIM manages to keep a very low storage space overhead and its specially designed in-memory index structure enables it to search for Time Series Images of a given area of the sky 10 times faster than using Redis, a state-of-the-art in-memory database.

Supporting Building Portfolio Investment and Policy Decision Making through an Integrated Building Utility Data Platform

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

Aziz, Azizan; Lasternas, Bertrand; Alschuler, Elena

The American Recovery and Reinvestment Act stimulus funding of 2009 for smart grid projects resulted in the tripling of smart meters deployment. In 2012, the Green Button initiative provided utility customers with access to their real-time1 energy usage. The availability of finely granular data provides an enormous potential for energy data analytics and energy benchmarking. The sheer volume of time-series utility data from a large number of buildings also poses challenges in data collection, quality control, and database management for rigorous and meaningful analyses. In this paper, we will describe a building portfolio-level data analytics tool for operational optimization, businessmore » investment and policy assessment using 15-minute to monthly intervals utility data. The analytics tool is developed on top of the U.S. Department of Energy’s Standard Energy Efficiency Data (SEED) platform, an open source software application that manages energy performance data of large groups of buildings. To support the significantly large volume of granular interval data, we integrated a parallel time-series database to the existing relational database. The time-series database improves on the current utility data input, focusing on real-time data collection, storage, analytics and data quality control. The fully integrated data platform supports APIs for utility apps development by third party software developers. These apps will provide actionable intelligence for building owners and facilities managers. Unlike a commercial system, this platform is an open source platform funded by the U.S. Government, accessible to the public, researchers and other developers, to support initiatives in reducing building energy consumption.« less

The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts

Treesearch

L.N. Hudson; T. Newbold; S. Contu

2014-01-01

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that...

Estimation of time-delayed mutual information and bias for irregularly and sparsely sampled time-series

PubMed Central

Albers, D. J.; Hripcsak, George

2012-01-01

A method to estimate the time-dependent correlation via an empirical bias estimate of the time-delayed mutual information for a time-series is proposed. In particular, the bias of the time-delayed mutual information is shown to often be equivalent to the mutual information between two distributions of points from the same system separated by infinite time. Thus intuitively, estimation of the bias is reduced to estimation of the mutual information between distributions of data points separated by large time intervals. The proposed bias estimation techniques are shown to work for Lorenz equations data and glucose time series data of three patients from the Columbia University Medical Center database. PMID:22536009

Nonlinear analysis of the occurrence of hurricanes in the Gulf of Mexico and the Caribbean Sea

NASA Astrophysics Data System (ADS)

Rojo-Garibaldi, Berenice; Salas-de-León, David Alberto; Adela Monreal-Gómez, María; Sánchez-Santillán, Norma Leticia; Salas-Monreal, David

2018-04-01

Hurricanes are complex systems that carry large amounts of energy. Their impact often produces natural disasters involving the loss of human lives and materials, such as infrastructure, valued at billions of US dollars. However, not everything about hurricanes is negative, as hurricanes are the main source of rainwater for the regions where they develop. This study shows a nonlinear analysis of the time series of the occurrence of hurricanes in the Gulf of Mexico and the Caribbean Sea obtained from 1749 to 2012. The construction of the hurricane time series was carried out based on the hurricane database of the North Atlantic basin hurricane database (HURDAT) and the published historical information. The hurricane time series provides a unique historical record on information about ocean-atmosphere interactions. The Lyapunov exponent indicated that the system presented chaotic dynamics, and the spectral analysis and nonlinear analyses of the time series of the hurricanes showed chaotic edge behavior. One possible explanation for this chaotic edge is the individual chaotic behavior of hurricanes, either by category or individually regardless of their category and their behavior on a regular basis.

An Extended IEEE 118-Bus Test System With High Renewable Penetration

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

Pena, Ivonne; Martinez-Anido, Carlo Brancucci; Hodge, Bri-Mathias

This article describes a new publicly available version of the IEEE 118-bus test system, named NREL-118. The database is based on the transmission representation (buses and lines) of the IEEE 118-bus test system, with a reconfigured generation representation using three regions of the US Western Interconnection from the latest Western Electricity Coordination Council (WECC) 2024 Common Case [1]. Time-synchronous hourly load, wind, and solar time series are provided for over one year (8784 hours). The public database presented and described in this manuscript will allow researchers to model a test power system using detailed transmission, generation, load, wind, and solarmore » data. This database includes key additional features that add to the current IEEE 118-bus test model, such as: the inclusion of 10 generation technologies with different heat rate functions, minimum stable levels and ramping rates, GHG emissions rates, regulation and contingency reserves, and hourly time series data for one full year for load, wind and solar generation.« less

The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface.

PubMed

Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B; Almon, Richard R; DuBois, Debra C; Jusko, William J; Hoffman, Eric P

2004-01-01

Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp).

The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface

PubMed Central

Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B.; Almon, Richard R.; DuBois, Debra C.; Jusko, William J.; Hoffman, Eric P.

2004-01-01

Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp). PMID:14681485

A data mining framework for time series estimation.

PubMed

Hu, Xiao; Xu, Peng; Wu, Shaozhi; Asgari, Shadnaz; Bergsneider, Marvin

2010-04-01

Time series estimation techniques are usually employed in biomedical research to derive variables less accessible from a set of related and more accessible variables. These techniques are traditionally built from systems modeling approaches including simulation, blind decovolution, and state estimation. In this work, we define target time series (TTS) and its related time series (RTS) as the output and input of a time series estimation process, respectively. We then propose a novel data mining framework for time series estimation when TTS and RTS represent different sets of observed variables from the same dynamic system. This is made possible by mining a database of instances of TTS, its simultaneously recorded RTS, and the input/output dynamic models between them. The key mining strategy is to formulate a mapping function for each TTS-RTS pair in the database that translates a feature vector extracted from RTS to the dissimilarity between true TTS and its estimate from the dynamic model associated with the same TTS-RTS pair. At run time, a feature vector is extracted from an inquiry RTS and supplied to the mapping function associated with each TTS-RTS pair to calculate a dissimilarity measure. An optimal TTS-RTS pair is then selected by analyzing these dissimilarity measures. The associated input/output model of the selected TTS-RTS pair is then used to simulate the TTS given the inquiry RTS as an input. An exemplary implementation was built to address a biomedical problem of noninvasive intracranial pressure assessment. The performance of the proposed method was superior to that of a simple training-free approach of finding the optimal TTS-RTS pair by a conventional similarity-based search on RTS features. 2009 Elsevier Inc. All rights reserved.

feets: feATURE eXTRACTOR for tIME sERIES

NASA Astrophysics Data System (ADS)

Cabral, Juan; Sanchez, Bruno; Ramos, Felipe; Gurovich, Sebastián; Granitto, Pablo; VanderPlas, Jake

2018-06-01

feets characterizes and analyzes light-curves from astronomical photometric databases for modelling, classification, data cleaning, outlier detection and data analysis. It uses machine learning algorithms to determine the numerical descriptors that characterize and distinguish the different variability classes of light-curves; these range from basic statistical measures such as the mean or standard deviation to complex time-series characteristics such as the autocorrelation function. The library is not restricted to the astronomical field and could also be applied to any kind of time series. This project is a derivative work of FATS (ascl:1711.017).

The Global Streamflow Indices and Metadata Archive (GSIM) - Part 1: The production of a daily streamflow archive and metadata

NASA Astrophysics Data System (ADS)

Do, Hong Xuan; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth

2018-04-01

This is the first part of a two-paper series presenting the Global Streamflow Indices and Metadata archive (GSIM), a worldwide collection of metadata and indices derived from more than 35 000 daily streamflow time series. This paper focuses on the compilation of the daily streamflow time series based on 12 free-to-access streamflow databases (seven national databases and five international collections). It also describes the development of three metadata products (freely available at https://doi.pangaea.de/10.1594/PANGAEA.887477): (1) a GSIM catalogue collating basic metadata associated with each time series, (2) catchment boundaries for the contributing area of each gauge, and (3) catchment metadata extracted from 12 gridded global data products representing essential properties such as land cover type, soil type, and climate and topographic characteristics. The quality of the delineated catchment boundary is also made available and should be consulted in GSIM application. The second paper in the series then explores production and analysis of streamflow indices. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.

Weighted combination of LOD values oa splitted into frequency windows

NASA Astrophysics Data System (ADS)

Fernandez, L. I.; Gambis, D.; Arias, E. F.

In this analysis a one-day combined time series of LOD(length-of-day) estimates is presented. We use individual data series derived by 7 GPS and 3 SLR analysis centers, which routinely contribute to the IERS database over a recent 27-month period (Jul 1996 - Oct 1998). The result is compared to the multi-technique combined series C04 produced by the Central Bureau of the IERS that is commonly used as a reference for the study of the phenomena of Earth rotation variations. The Frequency Windows Combined Series procedure brings out a time series, which is close to C04 but shows an amplitude difference that might explain the evident periodic behavior present in the differences of these two combined series. This method could be useful to generate a new time series to be used as a reference in the high frequency variations of the Earth rotation studies.

Memory and long-range correlations in chess games

NASA Astrophysics Data System (ADS)

Schaigorodsky, Ana L.; Perotti, Juan I.; Billoni, Orlando V.

2014-01-01

In this paper we report the existence of long-range memory in the opening moves of a chronologically ordered set of chess games using an extensive chess database. We used two mapping rules to build discrete time series and analyzed them using two methods for detecting long-range correlations; rescaled range analysis and detrended fluctuation analysis. We found that long-range memory is related to the level of the players. When the database is filtered according to player levels we found differences in the persistence of the different subsets. For high level players, correlations are stronger at long time scales; whereas in intermediate and low level players they reach the maximum value at shorter time scales. This can be interpreted as a signature of the different strategies used by players with different levels of expertise. These results are robust against the assignation rules and the method employed in the analysis of the time series.

Prediction of flow dynamics using point processes

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Stemler, Thomas; Eroglu, Deniz; Marwan, Norbert

2018-01-01

Describing a time series parsimoniously is the first step to study the underlying dynamics. For a time-discrete system, a generating partition provides a compact description such that a time series and a symbolic sequence are one-to-one. But, for a time-continuous system, such a compact description does not have a solid basis. Here, we propose to describe a time-continuous time series using a local cross section and the times when the orbit crosses the local cross section. We show that if such a series of crossing times and some past observations are given, we can predict the system's dynamics with fine accuracy. This reconstructability neither depends strongly on the size nor the placement of the local cross section if we have a sufficiently long database. We demonstrate the proposed method using the Lorenz model as well as the actual measurement of wind speed.

Documentation of the U.S. Geological Survey Oceanographic Time-Series Measurement Database

USGS Publications Warehouse

Montgomery, Ellyn T.; Martini, Marinna A.; Lightsom, Frances L.; Butman, Bradford

2008-01-02

This report describes the instrumentation and platforms used to make the measurements; the methods used to process, apply quality-control criteria, and archive the data; the data storage format, and how the data are released and distributed. The report also includes instructions on how to access the data from the online database at http://stellwagen.er.usgs.gov/. As of 2016, the database contains about 5,000 files, which may include observations of current velocity, wave statistics, ocean temperature, conductivity, pressure, and light transmission at one or more depths over some duration of time.

On an Allan variance approach to classify VLBI radio-sources on the basis of their astrometric stability

NASA Astrophysics Data System (ADS)

Gattano, C.; Lambert, S.; Bizouard, C.

2017-12-01

In the context of selecting sources defining the celestial reference frame, we compute astrometric time series of all VLBI radio-sources from observations in the International VLBI Service database. The time series are then analyzed with Allan variance in order to estimate the astrometric stability. From results, we establish a new classification that takes into account the whole multi-time scales information. The algorithm is flexible on the definition of ``stable source" through an adjustable threshold.

Alternative method to validate the seasonal land cover regions of the conterminous United States

Treesearch

Zhiliang Zhu; Donald O. Ohlen; Raymond L. Czaplewski; Robert E. Burgan

1996-01-01

An accuracy assessment method involving double sampling and the multivariate composite estimator has been used to validate the prototype seasonal land cover characteristics database of the conterminous United States. The database consists of 159 land cover classes, classified using time series of 1990 1-km satellite data and augmented with ancillary data including...

Digital database of channel cross-section surveys, Mount St. Helens, Washington

USGS Publications Warehouse

Mosbrucker, Adam R.; Spicer, Kurt R.; Major, Jon J.; Saunders, Dennis R.; Christianson, Tami S.; Kingsbury, Cole G.

2015-08-06

Stream-channel cross-section survey data are a fundamental component to studies of fluvial geomorphology. Such data provide important parameters required by many open-channel flow models, sediment-transport equations, sediment-budget computations, and flood-hazard assessments. At Mount St. Helens, Washington, the long-term response of channels to the May 18, 1980, eruption, which dramatically altered the hydrogeomorphic regime of several drainages, is documented by an exceptional time series of repeat stream-channel cross-section surveys. More than 300 cross sections, most established shortly following the eruption, represent more than 100 kilometers of surveyed topography. Although selected cross sections have been published previously in print form, we present a comprehensive digital database that includes geospatial and tabular data. Furthermore, survey data are referenced to a common geographic projection and to common datums. Database design, maintenance, and data dissemination are accomplished through a geographic information system (GIS) platform, which integrates survey data acquired with theodolite, total station, and global navigation satellite system (GNSS) instrumentation. Users can interactively perform advanced queries and geospatial time-series analysis. An accuracy assessment provides users the ability to quantify uncertainty within these data. At the time of publication, this project is ongoing. Regular database updates are expected; users are advised to confirm they are using the latest version.

Compression technique for large statistical data bases

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

Eggers, S.J.; Olken, F.; Shoshani, A.

1981-03-01

The compression of large statistical databases is explored and are proposed for organizing the compressed data, such that the time required to access the data is logarithmic. The techniques exploit special characteristics of statistical databases, namely, variation in the space required for the natural encoding of integer attributes, a prevalence of a few repeating values or constants, and the clustering of both data of the same length and constants in long, separate series. The techniques are variations of run-length encoding, in which modified run-lengths for the series are extracted from the data stream and stored in a header, which ismore » used to form the base level of a B-tree index into the database. The run-lengths are cumulative, and therefore the access time of the data is logarithmic in the size of the header. The details of the compression scheme and its implementation are discussed, several special cases are presented, and an analysis is given of the relative performance of the various versions.« less

A non linear analysis of human gait time series based on multifractal analysis and cross correlations

NASA Astrophysics Data System (ADS)

Muñoz-Diosdado, A.

2005-01-01

We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems.

Efficient hemodynamic event detection utilizing relational databases and wavelet analysis

NASA Technical Reports Server (NTRS)

Saeed, M.; Mark, R. G.

2001-01-01

Development of a temporal query framework for time-oriented medical databases has hitherto been a challenging problem. We describe a novel method for the detection of hemodynamic events in multiparameter trends utilizing wavelet coefficients in a MySQL relational database. Storage of the wavelet coefficients allowed for a compact representation of the trends, and provided robust descriptors for the dynamics of the parameter time series. A data model was developed to allow for simplified queries along several dimensions and time scales. Of particular importance, the data model and wavelet framework allowed for queries to be processed with minimal table-join operations. A web-based search engine was developed to allow for user-defined queries. Typical queries required between 0.01 and 0.02 seconds, with at least two orders of magnitude improvement in speed over conventional queries. This powerful and innovative structure will facilitate research on large-scale time-oriented medical databases.

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

Global gridded crop specific agricultural areas from 1961-2014

NASA Astrophysics Data System (ADS)

Konar, M.; Jackson, N. D.

2017-12-01

Current global cropland datasets are limited in crop specificity and temporal resolution. Time series maps of crop specific agricultural areas would enable us to better understand the global agricultural geography of the 20th century. To this end, we develop a global gridded dataset of crop specific agricultural areas from 1961-2014. To do this, we downscale national cropland information using a probabilistic approach. Our method relies upon gridded Global Agro-Ecological Zones (GAEZ) maps, the History Database of the Global Environment (HYDE), and crop calendars from Sacks et al. (2010). We estimate crop-specific agricultural areas for a 0.25 degree spatial grid and annual time scale for all major crops. We validate our global estimates for the year 2000 with Monfreda et al. (2008) and our time series estimates within the United States using government data. This database will contribute to our understanding of global agricultural change of the past century.

Fossil-Fuel C02 Emissions Database and Exploration System

NASA Astrophysics Data System (ADS)

Krassovski, M.; Boden, T.

2012-04-01

Fossil-Fuel C02 Emissions Database and Exploration System Misha Krassovski and Tom Boden Carbon Dioxide Information Analysis Center Oak Ridge National Laboratory The Carbon Dioxide Information Analysis Center (CDIAC) at Oak Ridge National Laboratory (ORNL) quantifies the release of carbon from fossil-fuel use and cement production each year at global, regional, and national spatial scales. These estimates are vital to climate change research given the strong evidence suggesting fossil-fuel emissions are responsible for unprecedented levels of carbon dioxide (CO2) in the atmosphere. The CDIAC fossil-fuel emissions time series are based largely on annual energy statistics published for all nations by the United Nations (UN). Publications containing historical energy statistics make it possible to estimate fossil-fuel CO2 emissions back to 1751 before the Industrial Revolution. From these core fossil-fuel CO2 emission time series, CDIAC has developed a number of additional data products to satisfy modeling needs and to address other questions aimed at improving our understanding of the global carbon cycle budget. For example, CDIAC also produces a time series of gridded fossil-fuel CO2 emission estimates and isotopic (e.g., C13) emissions estimates. The gridded data are generated using the methodology described in Andres et al. (2011) and provide monthly and annual estimates for 1751-2008 at 1° latitude by 1° longitude resolution. These gridded emission estimates are being used in the latest IPCC Scientific Assessment (AR4). Isotopic estimates are possible thanks to detailed information for individual nations regarding the carbon content of select fuels (e.g., the carbon signature of natural gas from Russia). CDIAC has recently developed a relational database to house these baseline emissions estimates and associated derived products and a web-based interface to help users worldwide query these data holdings. Users can identify, explore and download desired CDIAC fossil-fuel CO2 emissions data. This presentation introduces the architecture and design of the new relational database and web interface, summarizes the present state and functionality of the Fossil-Fuel CO2 Emissions Database and Exploration System, and highlights future plans for expansion of the relational database and interface.

Neutron monitors and muon detectors for solar modulation studies: 2. ϕ time series

NASA Astrophysics Data System (ADS)

Ghelfi, A.; Maurin, D.; Cheminet, A.; Derome, L.; Hubert, G.; Melot, F.

2017-08-01

The level of solar modulation at different times (related to the solar activity) is a central question of solar and galactic cosmic-ray physics. In the first paper of this series, we have established a correspondence between the uncertainties on ground-based detectors count rates and the parameter ϕ (modulation level in the force-field approximation) reconstructed from these count rates. In this second paper, we detail a procedure to obtain a reference ϕ time series from neutron monitor data. We show that we can have an unbiased and accurate ϕ reconstruction (Δϕ / ϕ ≃ 10 %). We also discuss the potential of Bonner spheres spectrometers and muon detectors to provide ϕ time series. Two by-products of this calculation are updated ϕ values for the cosmic-ray database and a web interface to retrieve and plot ϕ from the 50's to today (http://lpsc.in2p3.fr/crdb).

Web-based access to near real-time and archived high-density time-series data: cyber infrastructure challenges & developments in the open-source Waveform Server

NASA Astrophysics Data System (ADS)

Reyes, J. C.; Vernon, F. L.; Newman, R. L.; Steidl, J. H.

2010-12-01

The Waveform Server is an interactive web-based interface to multi-station, multi-sensor and multi-channel high-density time-series data stored in Center for Seismic Studies (CSS) 3.0 schema relational databases (Newman et al., 2009). In the last twelve months, based on expanded specifications and current user feedback, both the server-side infrastructure and client-side interface have been extensively rewritten. The Python Twisted server-side code-base has been fundamentally modified to now present waveform data stored in cluster-based databases using a multi-threaded architecture, in addition to supporting the pre-existing single database model. This allows interactive web-based access to high-density (broadband @ 40Hz to strong motion @ 200Hz) waveform data that can span multiple years; the common lifetime of broadband seismic networks. The client-side interface expands on it's use of simple JSON-based AJAX queries to now incorporate a variety of User Interface (UI) improvements including standardized calendars for defining time ranges, applying on-the-fly data calibration to display SI-unit data, and increased rendering speed. This presentation will outline the various cyber infrastructure challenges we have faced while developing this application, the use-cases currently in existence, and the limitations of web-based application development.

Fast and Flexible Multivariate Time Series Subsequence Search

NASA Technical Reports Server (NTRS)

Bhaduri, Kanishka; Oza, Nikunj C.; Zhu, Qiang; Srivastava, Ashok N.

2010-01-01

Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which often contain several gigabytes of data. Surprisingly, research on MTS search is very limited. Most of the existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two algorithms to solve this problem (1) a List Based Search (LBS) algorithm which uses sorted lists for indexing, and (2) a R*-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences. Both algorithms guarantee that all matching patterns within the specified thresholds will be returned (no false dismissals). The very few false alarms can be removed by a post-processing step. Since our framework is also capable of Univariate Time-Series (UTS) subsequence search, we first demonstrate the efficiency of our algorithms on several UTS datasets previously used in the literature. We follow this up with experiments using two large MTS databases from the aviation domain, each containing several millions of observations. Both these tests show that our algorithms have very high prune rates (>99%) thus needing actual disk access for only less than 1% of the observations. To the best of our knowledge, MTS subsequence search has never been attempted on datasets of the size we have used in this paper.

Engaging with Families in Out-of-School Time Learning. Out-of-School Time Evaluation Snapshot. Number 4

ERIC Educational Resources Information Center

Harvard University Harvard Family Research Project, 2004

2004-01-01

Harvard Family Research Project's series of Out-of-School Time Evaluation Snapshots distills the wealth of information compiled in our Out-of-School Time Program Evaluation Database into a single report. Each Snapshot examines a specific aspect of out-of-school time (OST) evaluation. This Snapshot provides an overview of how researchers are…

A Newly Updated Database of Elevation-changes of the Greenand Ice Sheet to Study Surface Processes and Ice Dynamics

NASA Astrophysics Data System (ADS)

Schenk, A. F.; Csatho, B. M.; van den Broeke, M.; Kuipers Munneke, P.

2015-12-01

This paper reports about important upgrades of the Greenland Ice Sheet (GrIS) surface elevation and elevation-change database obtained with our Surface Elevation And Change detection (SERAC) software suite. We have developed SERAC to derive information from laser altimetry data, particularly time series of elevation changes and their partitioning into changes caused by ice dynamics. This allows direct investigation of ice dynamic processes that is much needed for improving the predictive power of ice sheet models. SERAC is different from most other change detection methods. It is based on detecting changes of surface patches, about 1 km by 1 km in size, rather than deriving elevation changes from individual laser points. The current database consists of ~100,000 time series with satellite laser altimetry data from ICESat, airborne laser observations obtained by NASA's Airborne Topographic Mapper (ATM) and the Land, Vegetation and Ice Sensor (LVIS). The upgrade is significant, because not only new observations from 2013 and 2014 have been added but also a number of improvements lead to a more comprehensive and consistent record of elevation-changes. First, we used the model that gives in addition to ice sheet also information about ice caps and glaciers (Rastner et al., 2012) for deciding if a laser point is on the ice sheet or ice cap. Then we added small gaps that exist in the ICESat GLA12 data set because the ice sheet mask is not wide enough. The new database is now more complete and will facilitate more accurate comparisons of mass balance studies obtained from the Gravity Recovery and Climate Experiment system (GRACE). For determining the part of a time series caused by ice dynamics we used the new firn compaction model and Surface Mass Balance (SMB) estimates from RACMO2.3. The new database spans the time period from 1993 to 2014. Adding new observations amounts to a spatial densification of the old record and at the same time extends the time domain by two years. Our presentation will show the improvement of the reconstruction of the total changes, those caused by SMB and ice dynamic during the ICESat mission (2003-2009). Moreover we will review changes on scales from individual outlet glaciers to drainage basins and the entire ice sheet.

Databases for multilevel biophysiology research available at Physiome.jp.

PubMed

Asai, Yoshiyuki; Abe, Takeshi; Li, Li; Oka, Hideki; Nomura, Taishin; Kitano, Hiroaki

2015-01-01

Physiome.jp (http://physiome.jp) is a portal site inaugurated in 2007 to support model-based research in physiome and systems biology. At Physiome.jp, several tools and databases are available to support construction of physiological, multi-hierarchical, large-scale models. There are three databases in Physiome.jp, housing mathematical models, morphological data, and time-series data. In late 2013, the site was fully renovated, and in May 2015, new functions were implemented to provide information infrastructure to support collaborative activities for developing models and performing simulations within the database framework. This article describes updates to the databases implemented since 2013, including cooperation among the three databases, interactive model browsing, user management, version management of models, management of parameter sets, and interoperability with applications.

Incorporating Retention Time to Refine Models Predicting Thermal Regimes of Stream Networks Across New England

EPA Science Inventory

Thermal regimes are a critical factor in models predicting effects of watershed management activities on fish habitat suitability. We have assembled a database of lotic temperature time series across New England (> 7000 station-year combinations) from state and Federal data s...

SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data.

PubMed

Salehi, Ali; Jimenez-Berni, Jose; Deery, David M; Palmer, Doug; Holland, Edward; Rozas-Larraondo, Pablo; Chapman, Scott C; Georgakopoulos, Dimitrios; Furbank, Robert T

2015-01-01

To our knowledge, there is no software or database solution that supports large volumes of biological time series sensor data efficiently and enables data visualization and analysis in real time. Existing solutions for managing data typically use unstructured file systems or relational databases. These systems are not designed to provide instantaneous response to user queries. Furthermore, they do not support rapid data analysis and visualization to enable interactive experiments. In large scale experiments, this behaviour slows research discovery, discourages the widespread sharing and reuse of data that could otherwise inform critical decisions in a timely manner and encourage effective collaboration between groups. In this paper we present SensorDB, a web based virtual laboratory that can manage large volumes of biological time series sensor data while supporting rapid data queries and real-time user interaction. SensorDB is sensor agnostic and uses web-based, state-of-the-art cloud and storage technologies to efficiently gather, analyse and visualize data. Collaboration and data sharing between different agencies and groups is thereby facilitated. SensorDB is available online at http://sensordb.csiro.au.

A hierarchical spatial framework and database for the national river fish habitat condition assessment

USGS Publications Warehouse

Wang, L.; Infante, D.; Esselman, P.; Cooper, A.; Wu, D.; Taylor, W.; Beard, D.; Whelan, G.; Ostroff, A.

2011-01-01

Fisheries management programs, such as the National Fish Habitat Action Plan (NFHAP), urgently need a nationwide spatial framework and database for health assessment and policy development to protect and improve riverine systems. To meet this need, we developed a spatial framework and database using National Hydrography Dataset Plus (I-.100,000-scale); http://www.horizon-systems.com/nhdplus). This framework uses interconfluence river reaches and their local and network catchments as fundamental spatial river units and a series of ecological and political spatial descriptors as hierarchy structures to allow users to extract or analyze information at spatial scales that they define. This database consists of variables describing channel characteristics, network position/connectivity, climate, elevation, gradient, and size. It contains a series of catchment-natural and human-induced factors that are known to influence river characteristics. Our framework and database assembles all river reaches and their descriptors in one place for the first time for the conterminous United States. This framework and database provides users with the capability of adding data, conducting analyses, developing management scenarios and regulation, and tracking management progresses at a variety of spatial scales. This database provides the essential data needs for achieving the objectives of NFHAP and other management programs. The downloadable beta version database is available at http://ec2-184-73-40-15.compute-1.amazonaws.com/nfhap/main/.

Development and analysis of a meteorological database, Argonne National Laboratory, Illinois

USGS Publications Warehouse

Over, Thomas M.; Price, Thomas H.; Ishii, Audrey L.

2010-01-01

A database of hourly values of air temperature, dewpoint temperature, wind speed, and solar radiation from January 1, 1948, to September 30, 2003, primarily using data collected at the Argonne National Laboratory station, was developed for use in continuous-time hydrologic modeling in northeastern Illinois. Missing and apparently erroneous data values were replaced with adjusted values from nearby stations used as 'backup'. Temporal variations in the statistical properties of the data resulting from changes in measurement and data-storage methodologies were adjusted to match the statistical properties resulting from the data-collection procedures that have been in place since January 1, 1989. The adjustments were computed based on the regressions between the primary data series from Argonne National Laboratory and the backup series using data obtained during common periods; the statistical properties of the regressions were used to assign estimated standard errors to values that were adjusted or filled from other series. Each hourly value was assigned a corresponding data-source flag that indicates the source of the value and its transformations. An analysis of the data-source flags indicates that all the series in the database except dewpoint have a similar fraction of Argonne National Laboratory data, with about 89 percent for the entire period, about 86 percent from 1949 through 1988, and about 98 percent from 1989 through 2003. The dewpoint series, for which observations at Argonne National Laboratory did not begin until 1958, has only about 71 percent Argonne National Laboratory data for the entire period, about 63 percent from 1948 through 1988, and about 93 percent from 1989 through 2003, indicating a lower reliability of the dewpoint sensor. A basic statistical analysis of the filled and adjusted data series in the database, and a series of potential evapotranspiration computed from them using the computer program LXPET (Lamoreux Potential Evapotranspiration) also was carried out. This analysis indicates annual cycles in solar radiation and potential evapotranspiration that follow the annual cycle of extraterrestrial solar radiation, whereas temperature and dewpoint annual cycles are lagged by about 1 month relative to the solar cycle. The annual cycle of wind has a late summer minimum, and spring and fall maximums. At the annual time scale, the filled and adjusted data series and computed potential evapotranspiration have significant serial correlation and possibly have significant temporal trends. The inter-annual fluctuations of temperature and dewpoint are weakest, whereas those of wind and potential evapotranspiration are strongest.

A novel encoding Lempel-Ziv complexity algorithm for quantifying the irregularity of physiological time series.

PubMed

Zhang, Yatao; Wei, Shoushui; Liu, Hai; Zhao, Lina; Liu, Chengyu

2016-09-01

The Lempel-Ziv (LZ) complexity and its variants have been extensively used to analyze the irregularity of physiological time series. To date, these measures cannot explicitly discern between the irregularity and the chaotic characteristics of physiological time series. Our study compared the performance of an encoding LZ (ELZ) complexity algorithm, a novel variant of the LZ complexity algorithm, with those of the classic LZ (CLZ) and multistate LZ (MLZ) complexity algorithms. Simulation experiments on Gaussian noise, logistic chaotic, and periodic time series showed that only the ELZ algorithm monotonically declined with the reduction in irregularity in time series, whereas the CLZ and MLZ approaches yielded overlapped values for chaotic time series and time series mixed with Gaussian noise, demonstrating the accuracy of the proposed ELZ algorithm in capturing the irregularity, rather than the complexity, of physiological time series. In addition, the effect of sequence length on the ELZ algorithm was more stable compared with those on CLZ and MLZ, especially when the sequence length was longer than 300. A sensitivity analysis for all three LZ algorithms revealed that both the MLZ and the ELZ algorithms could respond to the change in time sequences, whereas the CLZ approach could not. Cardiac interbeat (RR) interval time series from the MIT-BIH database were also evaluated, and the results showed that the ELZ algorithm could accurately measure the inherent irregularity of the RR interval time series, as indicated by lower LZ values yielded from a congestive heart failure group versus those yielded from a normal sinus rhythm group (p < 0.01). Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The GOLM-database standard- a framework for time-series data management based on free software

NASA Astrophysics Data System (ADS)

Eichler, M.; Francke, T.; Kneis, D.; Reusser, D.

2009-04-01

Monitoring and modelling projects usually involve time series data originating from different sources. Often, file formats, temporal resolution and meta-data documentation rarely adhere to a common standard. As a result, much effort is spent on converting, harmonizing, merging, checking, resampling and reformatting these data. Moreover, in work groups or during the course of time, these tasks tend to be carried out redundantly and repeatedly, especially when new data becomes available. The resulting duplication of data in various formats strains additional ressources. We propose a database structure and complementary scripts for facilitating these tasks. The GOLM- (General Observation and Location Management) framework allows for import and storage of time series data of different type while assisting in meta-data documentation, plausibility checking and harmonization. The imported data can be visually inspected and its coverage among locations and variables may be visualized. Supplementing scripts provide options for data export for selected stations and variables and resampling of the data to the desired temporal resolution. These tools can, for example, be used for generating model input files or reports. Since GOLM fully supports network access, the system can be used efficiently by distributed working groups accessing the same data over the internet. GOLM's database structure and the complementary scripts can easily be customized to specific needs. Any involved software such as MySQL, R, PHP, OpenOffice as well as the scripts for building and using the data base, including documentation, are free for download. GOLM was developed out of the practical requirements of the OPAQUE-project. It has been tested and further refined in the ERANET-CRUE and SESAM projects, all of which used GOLM to manage meteorological, hydrological and/or water quality data.

RECENT DEVELOPMENTS IN HYDROWEB DATABASE Water level time series on lakes and reservoirs (Invited)

NASA Astrophysics Data System (ADS)

Cretaux, J.; Arsen, A.; Calmant, S.

2013-12-01

We present the current state of the Hydroweb database as well as developments in progress. It provides offline water level time series on rivers, reservoirs and lakes based on altimetry data from several satellites (Topex/Poseidon, ERS, Jason-1&2, GFO and ENVISAT). The major developments in Hydroweb concerns the development of an operational data centre with automatic acquisition and processing of IGDR data for updating time series in near real time (both for lakes & rivers) and also use of additional remote sensing data, like satellite imagery allowing the calculation of lake's surfaces. A lake data centre is under development at the Legos in coordination with Hydrolare Project leaded by SHI (State Hydrological Institute of the Russian Academy of Science). It will provide the level-surface-volume variations of about 230 lakes and reservoirs, calculated through combination of various satellite images (Modis, Asar, Landsat, Cbers) and radar altimetry (Topex / Poseidon, Jason-1 & 2, GFO, Envisat, ERS2, AltiKa). The final objective is to propose a data centre fully based on remote sensing technique and controlled by in situ infrastructure for the Global Terrestrial Network for Lakes (GTN-L) under the supervision of WMO and GCOS. In a longer perspective, the Hydroweb database will integrate data from future missions (Jason-3, Jason-CS, Sentinel-3A/B) and finally will serve for the design of the SWOT mission. The products of hydroweb will be used as input data for simulation of the SWOT products (water height and surface variations of lakes and rivers). In the future, the SWOT mission will allow to monitor on a sub-monthly basis the worldwide lakes and reservoirs bigger than 250 * 250 m and Hydroweb will host water level and extent products from this

Shortened acquisition protocols for the quantitative assessment of the 2-tissue-compartment model using dynamic PET/CT 18F-FDG studies.

PubMed

Strauss, Ludwig G; Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2011-03-01

(18)F-FDG kinetics are quantified by a 2-tissue-compartment model. The routine use of dynamic PET is limited because of this modality's 1-h acquisition time. We evaluated shortened acquisition protocols up to 0-30 min regarding the accuracy for data analysis with the 2-tissue-compartment model. Full dynamic series for 0-60 min were analyzed using a 2-tissue-compartment model. The time-activity curves and the resulting parameters for the model were stored in a database. Shortened acquisition data were generated from the database using the following time intervals: 0-10, 0-16, 0-20, 0-25, and 0-30 min. Furthermore, the impact of adding a 60-min uptake value to the dynamic series was evaluated. The datasets were analyzed using dedicated software to predict the results of the full dynamic series. The software is based on a modified support vector machines (SVM) algorithm and predicts the compartment parameters of the full dynamic series. The SVM-based software provides user-independent results and was accurate at predicting the compartment parameters of the full dynamic series. If a squared correlation coefficient of 0.8 (corresponding to 80% explained variance of the data) was used as a limit, a shortened acquisition of 0-16 min was accurate at predicting the 60-min 2-tissue-compartment parameters. If a limit of 0.9 (90% explained variance) was used, a dynamic series of at least 0-20 min together with the 60-min uptake values is required. Shortened acquisition protocols can be used to predict the parameters of the 2-tissue-compartment model. Either a dynamic PET series of 0-16 min or a combination of a dynamic PET/CT series of 0-20 min and a 60-min uptake value is accurate for analysis with a 2-tissue-compartment model.

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process.

PubMed

Moran, John L; Solomon, Patricia J

2013-05-24

Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. Monthly mean raw mortality (at hospital discharge) time series, 1995-2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) "in-control" status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag40 and 35% had autocorrelation through to lag40; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.

Historical Space Climate Data from Finland: Compilation and Analysis

NASA Astrophysics Data System (ADS)

Nevanlinna, Heikki

2004-10-01

We have compiled archived geomagnetic observations from the Helsinki magnetic observatory as well as visual sightings of auroral occurrence in Finland. The magnetic database comprises about 2 000 000 observations of H- and D-components measured during 1844-1909 with time resolution of 10 min to 1 h. In addition, magnetic observations carried out in the First and Second Polar Years in Finland have been recompiled. Magnetic activity indices (three-hour K-and daily Ak-figures) have been derived from the magnetic observations. Comparisons between the Finnish indices and simultaneous global aa-index (starting in 1868) show a good mutual correlation. The Helsinki activity index series can be used as a (pseudo) extension of the aa-index series for about two solar cycles 1844d -1868. On the annual level the correlation coefficient is about 0.9 during the overlapped time interval 1868-1897. The auroral database consists of about 20 000 single observations observed in Finland since the year 1748. The database of visual auroras has been completed by auroral occurrence (AO) index data derived from the Finnish all-sky camera recordings during 1973 -1997 at several sites in Lapland. The AO-index reveals both spatial and temporal variations of auroras from diurnal to solar cycle time scales in different space weather conditions.

Automatic location of L/H transition times for physical studies with a large statistical basis

NASA Astrophysics Data System (ADS)

González, S.; Vega, J.; Murari, A.; Pereira, A.; Dormido-Canto, S.; Ramírez, J. M.; contributors, JET-EFDA

2012-06-01

Completely automatic techniques to estimate and validate L/H transition times can be essential in L/H transition analyses. The generation of databases with hundreds of transition times and without human intervention is an important step to accomplish (a) L/H transition physics analysis, (b) validation of L/H theoretical models and (c) creation of L/H scaling laws. An entirely unattended methodology is presented in this paper to build large databases of transition times in JET using time series. The proposed technique has been applied to a dataset of 551 JET discharges between campaigns C21 and C26. A prediction with discharges that show a clear signature in time series is made through the locating properties of the wavelet transform. It is an accurate prediction and the uncertainty interval is ±3.2 ms. The discharges with a non-clear pattern in the time series use an L/H mode classifier based on discharges with a clear signature. In this case, the estimation error shows a distribution with mean and standard deviation of 27.9 ms and 37.62 ms, respectively. Two different regression methods have been applied to the measurements acquired at the transition times identified by the automatic system. The obtained scaling laws for the threshold power are not significantly different from those obtained using the data at the transition times determined manually by the experts. The automatic methods allow performing physical studies with a large number of discharges, showing, for example, that there are statistically different types of transitions characterized by different scaling laws.

Characterizing rainfall in the Tenerife island

NASA Astrophysics Data System (ADS)

Díez-Sierra, Javier; del Jesus, Manuel; Losada Rodriguez, Inigo

2017-04-01

In many locations, rainfall data are collected through networks of meteorological stations. The data collection process is nowadays automated in many places, leading to the development of big databases of rainfall data covering extensive areas of territory. However, managers, decision makers and engineering consultants tend not to extract most of the information contained in these databases due to the lack of specific software tools for their exploitation. Here we present the modeling and development effort put in place in the Tenerife island in order to develop MENSEI-L, a software tool capable of automatically analyzing a complete rainfall database to simplify the extraction of information from observations. MENSEI-L makes use of weather type information derived from atmospheric conditions to separate the complete time series into homogeneous groups where statistical distributions are fitted. Normal and extreme regimes are obtained in this manner. MENSEI-L is also able to complete missing data in the time series and to generate synthetic stations by using Kriging techniques. These techniques also serve to generate the spatial regimes of precipitation, both normal and extreme ones. MENSEI-L makes use of weather type information to also provide a stochastic three-day probability forecast for rainfall.

Oral lichen planus in childhood: a case series.

PubMed

Cascone, Marco; Celentano, Antonio; Adamo, Daniela; Leuci, Stefania; Ruoppo, Elvira; Mignogna, Michele D

2017-06-01

Although the exact incidence of pediatric oral lichen planus (OLP) is unknown, the oral mucosa seems to be less commonly involved, and the clinical presentation is often atypical. The aim of the study is to present a case series of OLP in childhood. From our database, we retrospectively selected and analyzed the clinical data of OLP patients under the age of 18 where the diagnosis had been confirmed by histopathological analysis. The case series from our database shows eight patients, four males and four females. The mean (±SD) age at the time of diagnosis of the disease was 13.5 (±2.73) years, ranging in age from 9 to 17. Clinically, a reticular pattern was present in six patients (75%), and the tongue was the most commonly involved oral site (six cases, 75%). We also report the first case of OLP in a 9-year-old girl affected by autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy. We report the largest case series of pediatric OLP published in literature thus far. Differences in the disease between adults and pediatric patients have been detected, but further investigation and a larger case series are needed to establish any detailed differences in clinical outcomes. © 2017 The International Society of Dermatology.

Identifying arsenic trioxide (ATO) functions in leukemia cells by using time series gene expression profiles.

PubMed

Yang, Hong; Lin, Shan; Cui, Jingru

2014-02-10

Arsenic trioxide (ATO) is presently the most active single agent in the treatment of acute promyelocytic leukemia (APL). In order to explore the molecular mechanism of ATO in leukemia cells with time series, we adopted bioinformatics strategy to analyze expression changing patterns and changes in transcription regulation modules of time series genes filtered from Gene Expression Omnibus database (GSE24946). We totally screened out 1847 time series genes for subsequent analysis. The KEGG (Kyoto encyclopedia of genes and genomes) pathways enrichment analysis of these genes showed that oxidative phosphorylation and ribosome were the top 2 significantly enriched pathways. STEM software was employed to compare changing patterns of gene expression with assigned 50 expression patterns. We screened out 7 significantly enriched patterns and 4 tendency charts of time series genes. The result of Gene Ontology showed that functions of times series genes mainly distributed in profiles 41, 40, 39 and 38. Seven genes with positive regulation of cell adhesion function were enriched in profile 40, and presented the same first increased model then decreased model as profile 40. The transcription module analysis showed that they mainly involved in oxidative phosphorylation pathway and ribosome pathway. Overall, our data summarized the gene expression changes in ATO treated K562-r cell lines with time and suggested that time series genes mainly regulated cell adhesive. Furthermore, our result may provide theoretical basis of molecular biology in treating acute promyelocytic leukemia. Copyright © 2013 Elsevier B.V. All rights reserved.

MRNIDX - Marine Data Index: Database Description, Operation, Retrieval, and Display

USGS Publications Warehouse

Paskevich, Valerie F.

1982-01-01

A database referencing the location and content of data stored on magnetic medium was designed to assist in the indexing of time-series and spatially dependent marine geophysical data collected or processed by the U. S. Geological Survey. The database was designed and created for input to the Geologic Retrieval and Synopsis Program (GRASP) to allow selective retrievals of information pertaining to location of data, data format, cruise, geographical bounds and collection dates of data. This information is then used to locate the stored data for administrative purposes or further processing. Database utilization is divided into three distinct operations. The first is the inventorying of the data and the updating of the database, the second is the retrieval of information from the database, and the third is the graphic display of the geographical boundaries to which the retrieved information pertains.

Exploring total cardiac variability in healthy and pathophysiological subjects using improved refined multiscale entropy.

PubMed

Marwaha, Puneeta; Sunkaria, Ramesh Kumar

2017-02-01

Multiscale entropy (MSE) and refined multiscale entropy (RMSE) techniques are being widely used to evaluate the complexity of a time series across multiple time scales 't'. Both these techniques, at certain time scales (sometimes for the entire time scales, in the case of RMSE), assign higher entropy to the HRV time series of certain pathologies than that of healthy subjects, and to their corresponding randomized surrogate time series. This incorrect assessment of signal complexity may be due to the fact that these techniques suffer from the following limitations: (1) threshold value 'r' is updated as a function of long-term standard deviation and hence unable to explore the short-term variability as well as substantial variability inherited in beat-to-beat fluctuations of long-term HRV time series. (2) In RMSE, entropy values assigned to different filtered scaled time series are the result of changes in variance, but do not completely reflect the real structural organization inherited in original time series. In the present work, we propose an improved RMSE (I-RMSE) technique by introducing a new procedure to set the threshold value by taking into account the period-to-period variability inherited in a signal and evaluated it on simulated and real HRV database. The proposed I-RMSE assigns higher entropy to the age-matched healthy subjects than that of patients suffering from atrial fibrillation, congestive heart failure, sudden cardiac death and diabetes mellitus, for the entire time scales. The results strongly support the reduction in complexity of HRV time series in female group, old-aged, patients suffering from severe cardiovascular and non-cardiovascular diseases, and in their corresponding surrogate time series.

Inference of sigma factor controlled networks by using numerical modeling applied to microarray time series data of the germinating prokaryote.

PubMed

Strakova, Eva; Zikova, Alice; Vohradsky, Jiri

2014-01-01

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

Network-based Prediction of Lotic Thermal Regimes Across New England

EPA Science Inventory

Thermal regimes are a critical factor in models predicting effects of watershed management activities on fish habitat suitability. We have assembled a database of lotic temperature time series across New England (> 7000 station-year combinations) from state and Federal data sour...

A database of 10 min average measurements of solar radiation and meteorological variables in Ostrava, Czech Republic

NASA Astrophysics Data System (ADS)

Opálková, Marie; Navrátil, Martin; Špunda, Vladimír; Blanc, Philippe; Wald, Lucien

2018-04-01

A database containing 10 min means of solar irradiance measured on a horizontal plane in several ultraviolet and visible bands from July 2014 to December 2016 at three stations in the area of the city of Ostrava (Czech Republic) is presented. The database contains time series of 10 min average irradiances or photosynthetic photon flux densities measured in the following spectral bands: 280-315 nm (UVB); 315-380 nm (UVA); and 400-700 nm (photosynthetically active radiation, PAR); 510-700 nm; 600-700 nm; 610-680 nm; 690-780 nm; 400-1100 nm. A series of meteorological variables including relative air humidity and air temperature at surface is also provided at the same 10 min time step at all three stations, and precipitation is provided for two stations. Air pressure, wind speed, wind direction, and concentrations of air pollutants PM10, SO2, NOx, NO, NO2 were measured at the 1 h time step at the fourth station owned by the Public Health Institute of Ostrava. The details of the experimental sites and instruments used for the measurements are given. Special attention is given to the data quality, and the original approach to the data quality which was established is described in detail. About 130 000 records for each of the three stations are available in the database. This database offers a unique ensemble of variables having a high temporal resolution and it is a reliable source for radiation in relation to environment and vegetation in highly polluted areas of industrial cities in the of northern mid-latitudes. The database has been placed on the PANGAEA repository (https://doi.org/10.1594/PANGAEA.879722) and contains individual data files for each station.

MetaRNA-Seq: An Interactive Tool to Browse and Annotate Metadata from RNA-Seq Studies.

PubMed

Kumar, Pankaj; Halama, Anna; Hayat, Shahina; Billing, Anja M; Gupta, Manish; Yousri, Noha A; Smith, Gregory M; Suhre, Karsten

2015-01-01

The number of RNA-Seq studies has grown in recent years. The design of RNA-Seq studies varies from very simple (e.g., two-condition case-control) to very complicated (e.g., time series involving multiple samples at each time point with separate drug treatments). Most of these publically available RNA-Seq studies are deposited in NCBI databases, but their metadata are scattered throughout four different databases: Sequence Read Archive (SRA), Biosample, Bioprojects, and Gene Expression Omnibus (GEO). Although the NCBI web interface is able to provide all of the metadata information, it often requires significant effort to retrieve study- or project-level information by traversing through multiple hyperlinks and going to another page. Moreover, project- and study-level metadata lack manual or automatic curation by categories, such as disease type, time series, case-control, or replicate type, which are vital to comprehending any RNA-Seq study. Here we describe "MetaRNA-Seq," a new tool for interactively browsing, searching, and annotating RNA-Seq metadata with the capability of semiautomatic curation at the study level.

A Comparative Study of Frequent and Maximal Periodic Pattern Mining Algorithms in Spatiotemporal Databases

NASA Astrophysics Data System (ADS)

Obulesu, O.; Rama Mohan Reddy, A., Dr; Mahendra, M.

2017-08-01

Detecting regular and efficient cyclic models is the demanding activity for data analysts due to unstructured, vigorous and enormous raw information produced from web. Many existing approaches generate large candidate patterns in the occurrence of huge and complex databases. In this work, two novel algorithms are proposed and a comparative examination is performed by considering scalability and performance parameters. The first algorithm is, EFPMA (Extended Regular Model Detection Algorithm) used to find frequent sequential patterns from the spatiotemporal dataset and the second one is, ETMA (Enhanced Tree-based Mining Algorithm) for detecting effective cyclic models with symbolic database representation. EFPMA is an algorithm grows models from both ends (prefixes and suffixes) of detected patterns, which results in faster pattern growth because of less levels of database projection compared to existing approaches such as Prefixspan and SPADE. ETMA uses distinct notions to store and manage transactions data horizontally such as segment, sequence and individual symbols. ETMA exploits a partition-and-conquer method to find maximal patterns by using symbolic notations. Using this algorithm, we can mine cyclic models in full-series sequential patterns including subsection series also. ETMA reduces the memory consumption and makes use of the efficient symbolic operation. Furthermore, ETMA only records time-series instances dynamically, in terms of character, series and section approaches respectively. The extent of the pattern and proving efficiency of the reducing and retrieval techniques from synthetic and actual datasets is a really open & challenging mining problem. These techniques are useful in data streams, traffic risk analysis, medical diagnosis, DNA sequence Mining, Earthquake prediction applications. Extensive investigational outcomes illustrates that the algorithms outperforms well towards efficiency and scalability than ECLAT, STNR and MAFIA approaches.

Wind Speed Dependence of Acoustic Ambient Vertical Directional Spectra at High Frequency

DTIC Science & Technology

1989-05-26

the measurements, which is 8 to 32 kHz, is sufficiently high that the propagation is adequately modeled using the Eikonal equation approximation. 4 TD...level spectra were calculated from the resulting time series. Spectral levels at 8, 16, and 32 kHz were recorded in a database along with the wind...indications of biological or industrial contaminations were removed. The resulting database seen here contained 215 samples. 10 * TD 8565 0z 00 a.I. cn

A Dashboard for the Italian Computing in ALICE

NASA Astrophysics Data System (ADS)

Elia, D.; Vino, G.; Bagnasco, S.; Crescente, A.; Donvito, G.; Franco, A.; Lusso, S.; Mura, D.; Piano, S.; Platania, G.; ALICE Collaboration

2017-10-01

A dashboard devoted to the computing in the Italian sites for the ALICE experiment at the LHC has been deployed. A combination of different complementary monitoring tools is typically used in most of the Tier-2 sites: this makes somewhat difficult to figure out at a glance the status of the site and to compare information extracted from different sources for debugging purposes. To overcome these limitations a dedicated ALICE dashboard has been designed and implemented in each of the ALICE Tier-2 sites in Italy: in particular, it provides a single, interactive and easily customizable graphical interface where heterogeneous data are presented. The dashboard is based on two main ingredients: an open source time-series database and a dashboard builder tool for visualizing time-series metrics. Various sensors, able to collect data from the multiple data sources, have been also written. A first version of a national computing dashboard has been implemented using a specific instance of the builder to gather data from all the local databases.

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process

PubMed Central

2013-01-01

Background Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. Methods Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. Results The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag40 and 35% had autocorrelation through to lag40; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. Conclusions The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues. PMID:23705957

Online learning algorithm for time series forecasting suitable for low cost wireless sensor networks nodes.

PubMed

Pardo, Juan; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma

2015-04-21

Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.

Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes

PubMed Central

Pardo, Juan; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma

2015-01-01

Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources. PMID:25905698

Predicting Thermal Regimes of Stream Networks Across New England: Natural and Anthropogenic Influences

EPA Science Inventory

Thermal regime is a critical factor in models predicting joint effects of watershed management activities and climate change on habitat suitability for fish. We used a database of lotic temperature time series across New England (> 7000 station-year combinations) from state a...

County Business Patterns: United States, 2002.

ERIC Educational Resources Information Center

US Department of Commerce, 2004

2004-01-01

In this report, subnational economic data by industry, including Educational Services, is provided. County Business Patterns is useful for studying the economic activity of small areas; analyzing economic changes over time; and as a benchmark for statistical series, surveys, and databases between economic censuses. The number of establishments,…

A Deep Machine Learning Method for Classifying Cyclic Time Series of Biological Signals Using Time-Growing Neural Network.

PubMed

Gharehbaghi, Arash; Linden, Maria

2017-10-12

This paper presents a novel method for learning the cyclic contents of stochastic time series: the deep time-growing neural network (DTGNN). The DTGNN combines supervised and unsupervised methods in different levels of learning for an enhanced performance. It is employed by a multiscale learning structure to classify cyclic time series (CTS), in which the dynamic contents of the time series are preserved in an efficient manner. This paper suggests a systematic procedure for finding the design parameter of the classification method for a one-versus-multiple class application. A novel validation method is also suggested for evaluating the structural risk, both in a quantitative and a qualitative manner. The effect of the DTGNN on the performance of the classifier is statistically validated through the repeated random subsampling using different sets of CTS, from different medical applications. The validation involves four medical databases, comprised of 108 recordings of the electroencephalogram signal, 90 recordings of the electromyogram signal, 130 recordings of the heart sound signal, and 50 recordings of the respiratory sound signal. Results of the statistical validations show that the DTGNN significantly improves the performance of the classification and also exhibits an optimal structural risk.

Using pad‐stripped acausally filtered strong‐motion data

USGS Publications Warehouse

Boore, David; Sisi, Aida Azari; Akkar, Sinan

2012-01-01

Most strong‐motion data processing involves acausal low‐cut filtering, which requires the addition of sometimes lengthy zero pads to the data. These padded sections are commonly removed by organizations supplying data, but this can lead to incompatibilities in measures of ground motion derived in the usual way from the padded and the pad‐stripped data. One way around this is to use the correct initial conditions in the pad‐stripped time series when computing displacements, velocities, and linear oscillator response. Another way of ensuring compatibility is to use postprocessing of the pad‐stripped acceleration time series. Using 4071 horizontal and vertical acceleration time series from the Turkish strong‐motion database, we show that the procedures used by two organizations—ITACA (ITalian ACcelerometric Archive) and PEER NGA (Pacific Earthquake Engineering Research Center–Next Generation Attenuation)—lead to little bias and distortion of derived seismic‐intensity measures.

High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets

NASA Astrophysics Data System (ADS)

Chen, Tai-Liang; Cheng, Ching-Hsue; Teoh, Hia-Jong

2008-02-01

Stock investors usually make their short-term investment decisions according to recent stock information such as the late market news, technical analysis reports, and price fluctuations. To reflect these short-term factors which impact stock price, this paper proposes a comprehensive fuzzy time-series, which factors linear relationships between recent periods of stock prices and fuzzy logical relationships (nonlinear relationships) mined from time-series into forecasting processes. In empirical analysis, the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) and HSI (Heng Seng Index) are employed as experimental datasets, and four recent fuzzy time-series models, Chen’s (1996), Yu’s (2005), Cheng’s (2006) and Chen’s (2007), are used as comparison models. Besides, to compare with conventional statistic method, the method of least squares is utilized to estimate the auto-regressive models of the testing periods within the databases. From analysis results, the performance comparisons indicate that the multi-period adaptation model, proposed in this paper, can effectively improve the forecasting performance of conventional fuzzy time-series models which only factor fuzzy logical relationships in forecasting processes. From the empirical study, the traditional statistic method and the proposed model both reveal that stock price patterns in the Taiwan stock and Hong Kong stock markets are short-term.

Ensemble Deep Learning for Biomedical Time Series Classification

PubMed Central

2016-01-01

Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost. PMID:27725828

Normative Databases for Imaging Instrumentation.

PubMed

Realini, Tony; Zangwill, Linda M; Flanagan, John G; Garway-Heath, David; Patella, Vincent M; Johnson, Chris A; Artes, Paul H; Gaddie, Ian B; Fingeret, Murray

2015-08-01

To describe the process by which imaging devices undergo reference database development and regulatory clearance. The limitations and potential improvements of reference (normative) data sets for ophthalmic imaging devices will be discussed. A symposium was held in July 2013 in which a series of speakers discussed issues related to the development of reference databases for imaging devices. Automated imaging has become widely accepted and used in glaucoma management. The ability of such instruments to discriminate healthy from glaucomatous optic nerves, and to detect glaucomatous progression over time is limited by the quality of reference databases associated with the available commercial devices. In the absence of standardized rules governing the development of reference databases, each manufacturer's database differs in size, eligibility criteria, and ethnic make-up, among other key features. The process for development of imaging reference databases may be improved by standardizing eligibility requirements and data collection protocols. Such standardization may also improve the degree to which results may be compared between commercial instruments.

Normative Databases for Imaging Instrumentation

PubMed Central

Realini, Tony; Zangwill, Linda; Flanagan, John; Garway-Heath, David; Patella, Vincent Michael; Johnson, Chris; Artes, Paul; Ben Gaddie, I.; Fingeret, Murray

2015-01-01

Purpose To describe the process by which imaging devices undergo reference database development and regulatory clearance. The limitations and potential improvements of reference (normative) data sets for ophthalmic imaging devices will be discussed. Methods A symposium was held in July 2013 in which a series of speakers discussed issues related to the development of reference databases for imaging devices. Results Automated imaging has become widely accepted and used in glaucoma management. The ability of such instruments to discriminate healthy from glaucomatous optic nerves, and to detect glaucomatous progression over time is limited by the quality of reference databases associated with the available commercial devices. In the absence of standardized rules governing the development of reference databases, each manufacturer’s database differs in size, eligibility criteria, and ethnic make-up, among other key features. Conclusions The process for development of imaging reference databases may be improved by standardizing eligibility requirements and data collection protocols. Such standardization may also improve the degree to which results may be compared between commercial instruments. PMID:25265003

Preliminary Integrated Geologic Map Databases for the United States: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, Rhode Island and Vermont

USGS Publications Warehouse

Nicholson, Suzanne W.; Dicken, Connie L.; Horton, John D.; Foose, Michael P.; Mueller, Julia A.L.; Hon, Rudi

2006-01-01

The rapid growth in the use of Geographic Information Systems (GIS) has highlighted the need for regional and national scale digital geologic maps that have standardized information about geologic age and lithology. Such maps can be conveniently used to generate derivative maps for manifold special purposes such as mineral-resource assessment, metallogenic studies, tectonic studies, and environmental research. Although two digital geologic maps (Schruben and others, 1994; Reed and Bush, 2004) of the United States currently exist, their scales (1:2,500,000 and 1:5,000,000) are too general for many regional applications. Most states have digital geologic maps at scales of about 1:500,000, but the databases are not comparably structured and, thus, it is difficult to use the digital database for more than one state at a time. This report describes the result for a seven state region of an effort by the U.S. Geological Survey to produce a series of integrated and standardized state geologic map databases that cover the entire United States. In 1997, the United States Geological Survey's Mineral Resources Program initiated the National Surveys and Analysis (NSA) Project to develop national digital databases. One primary activity of this project was to compile a national digital geologic map database, utilizing state geologic maps, to support studies in the range of 1:250,000- to 1:1,000,000-scale. To accomplish this, state databases were prepared using a common standard for the database structure, fields, attribution, and data dictionaries. For Alaska and Hawaii new state maps are being prepared and the preliminary work for Alaska is being released as a series of 1:250,000 scale quadrangle reports. This document provides background information and documentation for the integrated geologic map databases of this report. This report is one of a series of such reports releasing preliminary standardized geologic map databases for the United States. The data products of the project consist of two main parts, the spatial databases and a set of supplemental tables relating to geologic map units. The datasets serve as a data resource to generate a variety of stratigraphic, age, and lithologic maps. This documentation is divided into four main sections: (1) description of the set of data files provided in this report, (2) specifications of the spatial databases, (3) specifications of the supplemental tables, and (4) an appendix containing the data dictionaries used to populate some fields of the spatial database and supplemental tables.

Predicting thermal regimes of stream networks across the Chesapeake Bay Watershed: Natural and anthropogenic influences

EPA Science Inventory

Thermal regimes are a critical factor in models predicting joint effects of watershed management activities and climate change on fish habitat suitability. We have compiled a database of lotic temperature time series across the Chesapeake Bay Watershed (725 station-year combinat...

Analysis of Patent Activity in the Field of Quantum Information Processing

NASA Astrophysics Data System (ADS)

Winiarczyk, Ryszard; Gawron, Piotr; Miszczak, Jarosław Adam; Pawela, Łukasz; Puchała, Zbigniew

2013-03-01

This paper provides an analysis of patent activity in the field of quantum information processing. Data from the PatentScope database from the years 1993-2011 was used. In order to predict the future trends in the number of filed patents time series models were used.

Field Experiments in Manpower Issues.

ERIC Educational Resources Information Center

Mobilization for Youth, Inc., New York, NY. Experimental Manpower Lab.

The first three reports in this series describe the data-based results of systematic experimentation and survey research concerned with the following timely manpower issues: (1) The Effects of Monetary Incentives on the Learning of Remedial English by Disadvantaged Trainees, (2) The Reward Preferences of Neighborhood Youth Corps Trainees, and (3)…

CRETACEOUS CLIMATE SENSITIVITY STUDY USING DINOSAUR & PLANT PALEOBIOGEOGRAPHY

NASA Astrophysics Data System (ADS)

Goswami, A.; Main, D. J.; Noto, C. R.; Moore, T. L.; Scotese, C.

2009-12-01

The Early Cretaceous was characterized by cool poles and moderate global temperatures (~16° C). During the mid and late Cretaceous, long-term global warming (~20° - 22° C) was driven by increasing levels of CO2, rising sea level (lowering albedo) and the continuing breakup of Pangea. Paleoclimatic reconstructions for four time intervals during the Cretaceous: Middle Campanian (80 Ma), Cenomanian/Turonian (90 Ma), Early Albian (110 Ma) and Barremian-Hauterivian (130Ma) are presented here. These paleoclimate simulations were prepared using the Fast Ocean and Atmosphere Model (FOAM). The simulated results show the pattern of the pole-to-Equator temperature gradients, rainfall, surface run-off, the location of major rivers and deltas. In order to investigate the effect of potential dispersal routes on paleobiogeographic patterns, a time-slice series of maps from Early - Late Cretaceous were produced showing plots of dinosaur and plant fossil distributions. These Maps were created utilizing: 1) plant fossil localities from the GEON and Paleobiology (PBDB) databases; and 2) dinosaur fossil localities from an updated version of the Dinosauria (Weishampel, 2004) database. These results are compared to two different types of datasets, 1) Paleotemperature database for the Cretaceous and 2) locality data obtained from GEON, PBDB and Dinosauria database. Global latitudinal mean temperatures from both the model and the paelotemperature database were plotted on a series of latitudinal graphs along with the distributions of fossil plants and dinosaurs. It was found that most dinosaur localities through the Cretaceous tend to cluster within specific climate belts, or envelopes. Also, these Cretaceous maps show variance in biogeographic zonation of both plants and dinosaurs that is commensurate with reconstructed climate patterns and geography. These data are particularly useful for understanding the response of late Mesozoic ecosystems to geographic and climatic conditions that differed markedly from the present. Studies of past biotas and their changes may elucidate the role of climatic and geographic factors in driving changes in species distributions, ecosystem organization, and evolutionary dynamics over time.

Use of a prototype pulse oximeter for time series analysis of heart rate variability

NASA Astrophysics Data System (ADS)

González, Erika; López, Jehú; Hautefeuille, Mathieu; Velázquez, Víctor; Del Moral, Jésica

2015-05-01

This work presents the development of a low cost pulse oximeter prototype consisting of pulsed red and infrared commercial LEDs and a broad spectral photodetector used to register time series of heart rate and oxygen saturation of blood. This platform, besides providing these values, like any other pulse oximeter, processes the signals to compute a power spectrum analysis of the patient heart rate variability in real time and, additionally, the device allows access to all raw and analyzed data if databases construction is required or another kind of further analysis is desired. Since the prototype is capable of acquiring data for long periods of time, it is suitable for collecting data in real life activities, enabling the development of future wearable applications.

Methods and apparatus for constructing and implementing a universal extension module for processing objects in a database

NASA Technical Reports Server (NTRS)

Li, Chung-Sheng (Inventor); Smith, John R. (Inventor); Chang, Yuan-Chi (Inventor); Jhingran, Anant D. (Inventor); Padmanabhan, Sriram K. (Inventor); Hsiao, Hui-I (Inventor); Choy, David Mun-Hien (Inventor); Lin, Jy-Jine James (Inventor); Fuh, Gene Y. C. (Inventor); Williams, Robin (Inventor)

2004-01-01

Methods and apparatus for providing a multi-tier object-relational database architecture are disclosed. In one illustrative embodiment of the present invention, a multi-tier database architecture comprises an object-relational database engine as a top tier, one or more domain-specific extension modules as a bottom tier, and one or more universal extension modules as a middle tier. The individual extension modules of the bottom tier operationally connect with the one or more universal extension modules which, themselves, operationally connect with the database engine. The domain-specific extension modules preferably provide such functions as search, index, and retrieval services of images, video, audio, time series, web pages, text, XML, spatial data, etc. The domain-specific extension modules may include one or more IBM DB2 extenders, Oracle data cartridges and/or Informix datablades, although other domain-specific extension modules may be used.

Label free cell-tracking and division detection based on 2D time-lapse images for lineage analysis of early embryo development.

PubMed

Cicconet, Marcelo; Gutwein, Michelle; Gunsalus, Kristin C; Geiger, Davi

2014-08-01

In this paper we report a database and a series of techniques related to the problem of tracking cells, and detecting their divisions, in time-lapse movies of mammalian embryos. Our contributions are (1) a method for counting embryos in a well, and cropping each individual embryo across frames, to create individual movies for cell tracking; (2) a semi-automated method for cell tracking that works up to the 8-cell stage, along with a software implementation available to the public (this software was used to build the reported database); (3) an algorithm for automatic tracking up to the 4-cell stage, based on histograms of mirror symmetry coefficients captured using wavelets; (4) a cell-tracking database containing 100 annotated examples of mammalian embryos up to the 8-cell stage; and (5) statistical analysis of various timing distributions obtained from those examples. Copyright © 2014 Elsevier Ltd. All rights reserved.

Self-rated health: patterns in the journeys of patients with multi-morbidity and frailty.

PubMed

Martin, Carmel Mary

2014-12-01

Self-rated health (SRH) is a single measure predictor of hospital utilization and health outcomes in epidemiological studies. There have been few studies of SRH in patient journeys in clinical settings. Reduced resilience to stressors, reflected by SRH, exposes older people (complex systems) to the risk of hospitalization. It is proposed that SRH reflects rather than predicts deteriorations and hospital use; with low SRH autocorrelation in time series. The aim was to investigate SRH fluctuations in regular outbound telephone calls (average biweekly) to patients by Care Guides. Descriptive case study using quantitative autoregressive techniques and qualitative case analysis on SRH time series. Fourteen participants were randomly selected from the Patient Journey Record System (PaJR) database. The PaJR database recorded 198 consecutively sampled older multi-morbid patients journeys in three primary care settings. Analysis consisted of triangulation of SRH (0 very poor - 6 excellent) patterns from three analyses: SRH graduations associations with service utilization; time series modelling (autocorrelation, and step ahead forecast); and qualitative categorization of deteriorations. Fourteen patients reported mean SRH 2.84 (poor-fair) in 818 calls over 13 ± 6.4 months of follow-up. In 24% calls, SRH was poor-fair and significantly associated with hospital use. SRH autocorrelation was low in 14 time series (-0.11 to 0.26) with little difference (χ(2)  = 6.46, P = 0.91) among them. Fluctuations between better and worse health were very common and poor health was associated with hospital use. It is not clear why some patients continued on a downward trajectory, whereas others who destabilized appeared to completely recover, and even improved over time. SRH reflects an individual's complex health trajectory, but as a single measure does not predict when and how deteriorations will occur in this study. Individual patients appear to behave as complex adaptive systems. The dynamics of SRH and its influences in destabilizations warrant further research. © 2014 John Wiley & Sons, Ltd.

Information mining over heterogeneous and high-dimensional time-series data in clinical trials databases.

PubMed

Altiparmak, Fatih; Ferhatosmanoglu, Hakan; Erdal, Selnur; Trost, Donald C

2006-04-01

An effective analysis of clinical trials data involves analyzing different types of data such as heterogeneous and high dimensional time series data. The current time series analysis methods generally assume that the series at hand have sufficient length to apply statistical techniques to them. Other ideal case assumptions are that data are collected in equal length intervals, and while comparing time series, the lengths are usually expected to be equal to each other. However, these assumptions are not valid for many real data sets, especially for the clinical trials data sets. An addition, the data sources are different from each other, the data are heterogeneous, and the sensitivity of the experiments varies by the source. Approaches for mining time series data need to be revisited, keeping the wide range of requirements in mind. In this paper, we propose a novel approach for information mining that involves two major steps: applying a data mining algorithm over homogeneous subsets of data, and identifying common or distinct patterns over the information gathered in the first step. Our approach is implemented specifically for heterogeneous and high dimensional time series clinical trials data. Using this framework, we propose a new way of utilizing frequent itemset mining, as well as clustering and declustering techniques with novel distance metrics for measuring similarity between time series data. By clustering the data, we find groups of analytes (substances in blood) that are most strongly correlated. Most of these relationships already known are verified by the clinical panels, and, in addition, we identify novel groups that need further biomedical analysis. A slight modification to our algorithm results an effective declustering of high dimensional time series data, which is then used for "feature selection." Using industry-sponsored clinical trials data sets, we are able to identify a small set of analytes that effectively models the state of normal health.

[Design and implementation of online statistical analysis function in information system of air pollution and health impact monitoring].

PubMed

Lü, Yiran; Hao, Shuxin; Zhang, Guoqing; Liu, Jie; Liu, Yue; Xu, Dongqun

2018-01-01

To implement the online statistical analysis function in information system of air pollution and health impact monitoring, and obtain the data analysis information real-time. Using the descriptive statistical method as well as time-series analysis and multivariate regression analysis, SQL language and visual tools to implement online statistical analysis based on database software. Generate basic statistical tables and summary tables of air pollution exposure and health impact data online; Generate tendency charts of each data part online and proceed interaction connecting to database; Generate butting sheets which can lead to R, SAS and SPSS directly online. The information system air pollution and health impact monitoring implements the statistical analysis function online, which can provide real-time analysis result to its users.

Semantic Segmentation and Difference Extraction via Time Series Aerial Video Camera and its Application

NASA Astrophysics Data System (ADS)

Amit, S. N. K.; Saito, S.; Sasaki, S.; Kiyoki, Y.; Aoki, Y.

2015-04-01

Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts's road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

Methods for removal of unwanted signals from gravity time-series: Comparison using linear techniques complemented with analysis of system dynamics

NASA Astrophysics Data System (ADS)

Valencio, Arthur; Grebogi, Celso; Baptista, Murilo S.

2017-10-01

The presence of undesirable dominating signals in geophysical experimental data is a challenge in many subfields. One remarkable example is surface gravimetry, where frequencies from Earth tides correspond to time-series fluctuations up to a thousand times larger than the phenomena of major interest, such as hydrological gravity effects or co-seismic gravity changes. This work discusses general methods for the removal of unwanted dominating signals by applying them to 8 long-period gravity time-series of the International Geodynamics and Earth Tides Service, equivalent to the acquisition from 8 instruments in 5 locations representative of the network. We compare three different conceptual approaches for tide removal: frequency filtering, physical modelling, and data-based modelling. Each approach reveals a different limitation to be considered depending on the intended application. Vestiges of tides remain in the residues for the modelling procedures, whereas the signal was distorted in different ways by the filtering and data-based procedures. The linear techniques employed were power spectral density, spectrogram, cross-correlation, and classical harmonics decomposition, while the system dynamics was analysed by state-space reconstruction and estimation of the largest Lyapunov exponent. Although the tides could not be completely eliminated, they were sufficiently reduced to allow observation of geophysical events of interest above the 10 nm s-2 level, exemplified by a hydrology-related event of 60 nm s-2. The implementations adopted for each conceptual approach are general, so that their principles could be applied to other kinds of data affected by undesired signals composed mainly by periodic or quasi-periodic components.

Production and Uses of Multi-Decade Geodetic Earth Science Data Records

NASA Astrophysics Data System (ADS)

Bock, Y.; Kedar, S.; Moore, A. W.; Fang, P.; Liu, Z.; Sullivan, A.; Argus, D. F.; Jiang, S.; Marshall, S. T.

2017-12-01

The Solid Earth Science ESDR System (SESES) project funded under the NASA MEaSUREs program produces and disseminates mature, long-term, calibrated and validated, GNSS based Earth Science Data Records (ESDRs) that encompass multiple diverse areas of interest in Earth Science, such as tectonic motion, transient slip and earthquake dynamics, as well as meteorology, climate, and hydrology. The ESDRs now span twenty-five years for the earliest stations and today are available for thousands of global and regional stations. Using a unified metadata database and a combination of GNSS solutions generated by two independent analysis centers, the project currently produces four long-term ESDR's: Geodetic Displacement Time Series: Daily, combined, cleaned and filtered, GIPSY and GAMIT long-term time series of continuous GPS station positions (global and regional) in the latest version of ITRF, automatically updated weekly. Geodetic Velocities: Weekly updated velocity field + velocity field histories in various reference frames; compendium of all model parameters including earthquake catalog, coseismic offsets, and postseismic model parameters (exponential or logarithmic). Troposphere Delay Time Series: Long-term time series of troposphere delay (30-min resolution) at geodetic stations, necessarily estimated during position time series production and automatically updated weekly. Seismogeodetic records for historic earthquakes: High-rate broadband displacement and seismic velocity time series combining 1 Hz GPS displacements and 100 Hz accelerometer data for select large earthquakes and collocated cGPS and seismic instruments from regional networks. We present several recent notable examples of the ESDR's usage: A transient slip study that uses the combined position time series to unravel "tremor-less" slow tectonic transient events. Fault geometry determination from geodetic slip rates. Changes in water resources across California's physiographic provinces at a spatial resolution of 75 km. Retrospective study of a southern California summer monsoon event.

Noise/spike detection in phonocardiogram signal as a cyclic random process with non-stationary period interval.

PubMed

Naseri, H; Homaeinezhad, M R; Pourkhajeh, H

2013-09-01

The major aim of this study is to describe a unified procedure for detecting noisy segments and spikes in transduced signals with a cyclic but non-stationary periodic nature. According to this procedure, the cycles of the signal (onset and offset locations) are detected. Then, the cycles are clustered into a finite number of groups based on appropriate geometrical- and frequency-based time series. Next, the median template of each time series of each cluster is calculated. Afterwards, a correlation-based technique is devised for making a comparison between a test cycle feature and the associated time series of each cluster. Finally, by applying a suitably chosen threshold for the calculated correlation values, a segment is prescribed to be either clean or noisy. As a key merit of this research, the procedure can introduce a decision support for choosing accurately orthogonal-expansion-based filtering or to remove noisy segments. In this paper, the application procedure of the proposed method is comprehensively described by applying it to phonocardiogram (PCG) signals for finding noisy cycles. The database consists of 126 records from several patients of a domestic research station acquired by a 3M Littmann(®) 3200, 4KHz sampling frequency electronic stethoscope. By implementing the noisy segments detection algorithm with this database, a sensitivity of Se=91.41% and a positive predictive value, PPV=92.86% were obtained based on physicians assessments. Copyright © 2013 Elsevier Ltd. All rights reserved.

Interchangeability of counts of cases and hours of cases for quantifying a hospital's change in workload among four-week periods of 1 year.

PubMed

Dexter, Franklin; Epstein, Richard H; Ledolter, Johannes; Wanderer, Jonathan P

2018-05-16

Recent studies have made longitudinal assessments of case counts using State (e.g., United States) and Provincial (e.g., Canada) databases. Such databases rarely include either operating room (OR) or anesthesia times and, even when duration data are available, there are major statistical limitations to their use. We evaluated how to forecast short-term changes in OR caseload and workload (hours) and how to decide whether changes are outliers (e.g., significant, abrupt decline in anesthetics). Observational cohort study. Large teaching hospital. 35 years of annual anesthesia caseload data. Annual data were used without regard to where or when in the year each case was performed, thereby matching public use files. Changes in caseload or hours among four-week periods were examined within individual year-long periods using 159 consecutive four-week periods from the same hospital. Series of 12 four-week periods of the hours of cases performed on workdays lacked trend or correlation among periods for 49 of 50 series and followed normal distributions for 50 of 50 series. These criteria also were satisfied for 50 of 50 series based on counts of cases. The Pearson r = 0.999 between hours of anesthetics and cases. For purposes of time series analysis of total workload at a hospital within 1-year, hours of cases and counts of cases are interchangeable. Simple control chart methods of detecting sudden changes in workload or caseload, based simply on the sample mean and standard deviation from the preceding year, are appropriate. Copyright © 2018 Elsevier Inc. All rights reserved.

Applying data mining techniques to medical time series: an empirical case study in electroencephalography and stabilometry.

PubMed

Anguera, A; Barreiro, J M; Lara, J A; Lizcano, D

2016-01-01

One of the major challenges in the medical domain today is how to exploit the huge amount of data that this field generates. To do this, approaches are required that are capable of discovering knowledge that is useful for decision making in the medical field. Time series are data types that are common in the medical domain and require specialized analysis techniques and tools, especially if the information of interest to specialists is concentrated within particular time series regions, known as events. This research followed the steps specified by the so-called knowledge discovery in databases (KDD) process to discover knowledge from medical time series derived from stabilometric (396 series) and electroencephalographic (200) patient electronic health records (EHR). The view offered in the paper is based on the experience gathered as part of the VIIP project. Knowledge discovery in medical time series has a number of difficulties and implications that are highlighted by illustrating the application of several techniques that cover the entire KDD process through two case studies. This paper illustrates the application of different knowledge discovery techniques for the purposes of classification within the above domains. The accuracy of this application for the two classes considered in each case is 99.86% and 98.11% for epilepsy diagnosis in the electroencephalography (EEG) domain and 99.4% and 99.1% for early-age sports talent classification in the stabilometry domain. The KDD techniques achieve better results than other traditional neural network-based classification techniques.

Time-series analysis in imatinib-resistant chronic myeloid leukemia K562-cells under different drug treatments.

PubMed

Zhao, Yan-Hong; Zhang, Xue-Fang; Zhao, Yan-Qiu; Bai, Fan; Qin, Fan; Sun, Jing; Dong, Ying

2017-08-01

Chronic myeloid leukemia (CML) is characterized by the accumulation of active BCR-ABL protein. Imatinib is the first-line treatment of CML; however, many patients are resistant to this drug. In this study, we aimed to compare the differences in expression patterns and functions of time-series genes in imatinib-resistant CML cells under different drug treatments. GSE24946 was downloaded from the GEO database, which included 17 samples of K562-r cells with (n=12) or without drug administration (n=5). Three drug treatment groups were considered for this study: arsenic trioxide (ATO), AMN107, and ATO+AMN107. Each group had one sample at each time point (3, 12, 24, and 48 h). Time-series genes with a ratio of standard deviation/average (coefficient of variation) >0.15 were screened, and their expression patterns were revealed based on Short Time-series Expression Miner (STEM). Then, the functional enrichment analysis of time-series genes in each group was performed using DAVID, and the genes enriched in the top ten functional categories were extracted to detect their expression patterns. Different time-series genes were identified in the three groups, and most of them were enriched in the ribosome and oxidative phosphorylation pathways. Time-series genes in the three treatment groups had different expression patterns and functions. Time-series genes in the ATO group (e.g. CCNA2 and DAB2) were significantly associated with cell adhesion, those in the AMN107 group were related to cellular carbohydrate metabolic process, while those in the ATO+AMN107 group (e.g. AP2M1) were significantly related to cell proliferation and antigen processing. In imatinib-resistant CML cells, ATO could influence genes related to cell adhesion, AMN107 might affect genes involved in cellular carbohydrate metabolism, and the combination therapy might regulate genes involved in cell proliferation.

Phenological classification of the United States: A geographic framework for extending multi-sensor time-series data

USGS Publications Warehouse

Gu, Yingxin; Brown, Jesslyn F.; Miura, Tomoaki; van Leeuwen, Willem J.D.; Reed, Bradley C.

2010-01-01

This study introduces a new geographic framework, phenological classification, for the conterminous United States based on Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time-series data and a digital elevation model. The resulting pheno-class map is comprised of 40 pheno-classes, each having unique phenological and topographic characteristics. Cross-comparison of the pheno-classes with the 2001 National Land Cover Database indicates that the new map contains additional phenological and climate information. The pheno-class framework may be a suitable basis for the development of an Advanced Very High Resolution Radiometer (AVHRR)-MODIS NDVI translation algorithm and for various biogeographic studies.

An ab initio electronic transport database for inorganic materials.

PubMed

Ricci, Francesco; Chen, Wei; Aydemir, Umut; Snyder, G Jeffrey; Rignanese, Gian-Marco; Jain, Anubhav; Hautier, Geoffroy

2017-07-04

Electronic transport in materials is governed by a series of tensorial properties such as conductivity, Seebeck coefficient, and effective mass. These quantities are paramount to the understanding of materials in many fields from thermoelectrics to electronics and photovoltaics. Transport properties can be calculated from a material's band structure using the Boltzmann transport theory framework. We present here the largest computational database of electronic transport properties based on a large set of 48,000 materials originating from the Materials Project database. Our results were obtained through the interpolation approach developed in the BoltzTraP software, assuming a constant relaxation time. We present the workflow to generate the data, the data validation procedure, and the database structure. Our aim is to target the large community of scientists developing materials selection strategies and performing studies involving transport properties.

A comprehensive view of the web-resources related to sericulture

PubMed Central

Singh, Deepika; Chetia, Hasnahana; Kabiraj, Debajyoti; Sharma, Swagata; Kumar, Anil; Sharma, Pragya; Deka, Manab; Bora, Utpal

2016-01-01

Recent progress in the field of sequencing and analysis has led to a tremendous spike in data and the development of data science tools. One of the outcomes of this scientific progress is development of numerous databases which are gaining popularity in all disciplines of biology including sericulture. As economically important organism, silkworms are studied extensively for their numerous applications in the field of textiles, biomaterials, biomimetics, etc. Similarly, host plants, pests, pathogens, etc. are also being probed to understand the seri-resources more efficiently. These studies have led to the generation of numerous seri-related databases which are extremely helpful for the scientific community. In this article, we have reviewed all the available online resources on silkworm and its related organisms, including databases as well as informative websites. We have studied their basic features and impact on research through citation count analysis, finally discussing the role of emerging sequencing and analysis technologies in the field of seri-data science. As an outcome of this review, a web portal named SeriPort, has been created which will act as an index for the various sericulture-related databases and web resources available in cyberspace. Database URL: http://www.seriport.in/ PMID:27307138

Interactive Learning Modules: Enabling Near Real-Time Oceanographic Data Use In Undergraduate Education

NASA Astrophysics Data System (ADS)

Kilb, D. L.; Fundis, A. T.; Risien, C. M.

2012-12-01

The focus of the Education and Public Engagement (EPE) component of the NSF's Ocean Observatories Initiative (OOI) is to provide a new layer of cyber-interactivity for undergraduate educators to bring near real-time data from the global ocean into learning environments. To accomplish this, we are designing six online services including: 1) visualization tools, 2) a lesson builder, 3) a concept map builder, 4) educational web services (middleware), 5) collaboration tools and 6) an educational resource database. Here, we report on our Fall 2012 release that includes the first four of these services: 1) Interactive visualization tools allow users to interactively select data of interest, display the data in various views (e.g., maps, time-series and scatter plots) and obtain statistical measures such as mean, standard deviation and a regression line fit to select data. Specific visualization tools include a tool to compare different months of data, a time series explorer tool to investigate the temporal evolution of select data parameters (e.g., sea water temperature or salinity), a glider profile tool that displays ocean glider tracks and associated transects, and a data comparison tool that allows users to view the data either in scatter plot view comparing one parameter with another, or in time series view. 2) Our interactive lesson builder tool allows users to develop a library of online lesson units, which are collaboratively editable and sharable and provides starter templates designed from learning theory knowledge. 3) Our interactive concept map tool allows the user to build and use concept maps, a graphical interface to map the connection between concepts and ideas. This tool also provides semantic-based recommendations, and allows for embedding of associated resources such as movies, images and blogs. 4) Education web services (middleware) will provide an educational resource database API.

Research on PM2.5 time series characteristics based on data mining technology

NASA Astrophysics Data System (ADS)

Zhao, Lifang; Jia, Jin

2018-02-01

With the development of data mining technology and the establishment of environmental air quality database, it is necessary to discover the potential correlations and rules by digging the massive environmental air quality information and analyzing the air pollution process. In this paper, we have presented a sequential pattern mining method based on the air quality data and pattern association technology to analyze the PM2.5 time series characteristics. Utilizing the real-time monitoring data of urban air quality in China, the time series rule and variation properties of PM2.5 under different pollution levels are extracted and analyzed. The analysis results show that the time sequence features of the PM2.5 concentration is directly affected by the alteration of the pollution degree. The longest time that PM2.5 remained stable is about 24 hours. As the pollution degree gets severer, the instability time and step ascending time gradually changes from 12-24 hours to 3 hours. The presented method is helpful for the controlling and forecasting of the air quality while saving the measuring costs, which is of great significance for the government regulation and public prevention of the air pollution.

Condensing Massive Satellite Datasets For Rapid Interactive Analysis

NASA Astrophysics Data System (ADS)

Grant, G.; Gallaher, D. W.; Lv, Q.; Campbell, G. G.; Fowler, C.; LIU, Q.; Chen, C.; Klucik, R.; McAllister, R. A.

2015-12-01

Our goal is to enable users to interactively analyze massive satellite datasets, identifying anomalous data or values that fall outside of thresholds. To achieve this, the project seeks to create a derived database containing only the most relevant information, accelerating the analysis process. The database is designed to be an ancillary tool for the researcher, not an archival database to replace the original data. This approach is aimed at improving performance by reducing the overall size by way of condensing the data. The primary challenges of the project include: - The nature of the research question(s) may not be known ahead of time. - The thresholds for determining anomalies may be uncertain. - Problems associated with processing cloudy, missing, or noisy satellite imagery. - The contents and method of creation of the condensed dataset must be easily explainable to users. The architecture of the database will reorganize spatially-oriented satellite imagery into temporally-oriented columns of data (a.k.a., "data rods") to facilitate time-series analysis. The database itself is an open-source parallel database, designed to make full use of clustered server technologies. A demonstration of the system capabilities will be shown. Applications for this technology include quick-look views of the data, as well as the potential for on-board satellite processing of essential information, with the goal of reducing data latency.

Mathematical models for exploring different aspects of genotoxicity and carcinogenicity databases.

PubMed

Benigni, R; Giuliani, A

1991-12-01

One great obstacle to understanding and using the information contained in the genotoxicity and carcinogenicity databases is the very size of such databases. Their vastness makes them difficult to read; this leads to inadequate exploitation of the information, which becomes costly in terms of time, labor, and money. In its search for adequate approaches to the problem, the scientific community has, curiously, almost entirely neglected an existent series of very powerful methods of data analysis: the multivariate data analysis techniques. These methods were specifically designed for exploring large data sets. This paper presents the multivariate techniques and reports a number of applications to genotoxicity problems. These studies show how biology and mathematical modeling can be combined and how successful this combination is.

Creating Your Own Database.

ERIC Educational Resources Information Center

Blair, John C., Jr.

1982-01-01

Outlines the important factors to be considered in selecting a database management system for use with a microcomputer and presents a series of guidelines for developing a database. General procedures, report generation, data manipulation, information storage, word processing, data entry, database indexes, and relational databases are among the…

Time-series oligonucleotide count to assign antiviral siRNAs with long utility fit in the big data era.

PubMed

Wada, K; Wada, Y; Iwasaki, Y; Ikemura, T

2017-10-01

Oligonucleotides are key elements of nucleic acid therapeutics such as small interfering RNAs (siRNAs). Influenza and Ebolaviruses are zoonotic RNA viruses mutating very rapidly, and their sequence changes must be characterized intensively to design therapeutic oligonucleotides with long utility. Focusing on a total of 182 experimentally validated siRNAs for influenza A, B and Ebolaviruses compiled by the siRNA database, we conducted time-series analyses of occurrences of siRNA targets in these viral genomes. Reflecting their high mutation rates, occurrences of target oligonucleotides evidently fluctuate in viral populations and often disappear. Time-series analysis of the one-base changed sequences derived from each original target identified the oligonucleotide that shows a compensatory increase and will potentially become the 'awaiting-type oligonucleotide'; the combined use of this oligonucleotide with the original can provide therapeutics with long utility. This strategy is also useful for assigning diagnostic reverse transcription-PCR primers with long utility.

Visibility graph analysis of heart rate time series and bio-marker of congestive heart failure

NASA Astrophysics Data System (ADS)

Bhaduri, Anirban; Bhaduri, Susmita; Ghosh, Dipak

2017-09-01

Study of RR interval time series for Congestive Heart Failure had been an area of study with different methods including non-linear methods. In this article the cardiac dynamics of heart beat are explored in the light of complex network analysis, viz. visibility graph method. Heart beat (RR Interval) time series data taken from Physionet database [46, 47] belonging to two groups of subjects, diseased (congestive heart failure) (29 in number) and normal (54 in number) are analyzed with the technique. The overall results show that a quantitative parameter can significantly differentiate between the diseased subjects and the normal subjects as well as different stages of the disease. Further, the data when split into periods of around 1 hour each and analyzed separately, also shows the same consistent differences. This quantitative parameter obtained using the visibility graph analysis thereby can be used as a potential bio-marker as well as a subsequent alarm generation mechanism for predicting the onset of Congestive Heart Failure.

Time-series oligonucleotide count to assign antiviral siRNAs with long utility fit in the big data era

PubMed Central

Wada, K; Wada, Y; Iwasaki, Y; Ikemura, T

2017-01-01

Oligonucleotides are key elements of nucleic acid therapeutics such as small interfering RNAs (siRNAs). Influenza and Ebolaviruses are zoonotic RNA viruses mutating very rapidly, and their sequence changes must be characterized intensively to design therapeutic oligonucleotides with long utility. Focusing on a total of 182 experimentally validated siRNAs for influenza A, B and Ebolaviruses compiled by the siRNA database, we conducted time-series analyses of occurrences of siRNA targets in these viral genomes. Reflecting their high mutation rates, occurrences of target oligonucleotides evidently fluctuate in viral populations and often disappear. Time-series analysis of the one-base changed sequences derived from each original target identified the oligonucleotide that shows a compensatory increase and will potentially become the ‘awaiting-type oligonucleotide’ the combined use of this oligonucleotide with the original can provide therapeutics with long utility. This strategy is also useful for assigning diagnostic reverse transcription-PCR primers with long utility. PMID:28905886

Evaluating the Impact of Database Heterogeneity on Observational Study Results

PubMed Central

Madigan, David; Ryan, Patrick B.; Schuemie, Martijn; Stang, Paul E.; Overhage, J. Marc; Hartzema, Abraham G.; Suchard, Marc A.; DuMouchel, William; Berlin, Jesse A.

2013-01-01

Clinical studies that use observational databases to evaluate the effects of medical products have become commonplace. Such studies begin by selecting a particular database, a decision that published papers invariably report but do not discuss. Studies of the same issue in different databases, however, can and do generate different results, sometimes with strikingly different clinical implications. In this paper, we systematically study heterogeneity among databases, holding other study methods constant, by exploring relative risk estimates for 53 drug-outcome pairs and 2 widely used study designs (cohort studies and self-controlled case series) across 10 observational databases. When holding the study design constant, our analysis shows that estimated relative risks range from a statistically significant decreased risk to a statistically significant increased risk in 11 of 53 (21%) of drug-outcome pairs that use a cohort design and 19 of 53 (36%) of drug-outcome pairs that use a self-controlled case series design. This exceeds the proportion of pairs that were consistent across databases in both direction and statistical significance, which was 9 of 53 (17%) for cohort studies and 5 of 53 (9%) for self-controlled case series. Our findings show that clinical studies that use observational databases can be sensitive to the choice of database. More attention is needed to consider how the choice of data source may be affecting results. PMID:23648805

Long-term cycles in the history of life: periodic biodiversity in the paleobiology database.

PubMed

Melott, Adrian L

2008-01-01

Time series analysis of fossil biodiversity of marine invertebrates in the Paleobiology Database (PBDB) shows a significant periodicity at approximately 63 My, in agreement with previous analyses based on the Sepkoski database. I discuss how this result did not appear in a previous analysis of the PBDB. The existence of the 63 My periodicity, despite very different treatment of systematic error in both PBDB and Sepkoski databases strongly argues for consideration of its reality in the fossil record. Cross-spectral analysis of the two datasets finds that a 62 My periodicity coincides in phase by 1.6 My, equivalent to better than the errors in either measurement. Consequently, the two data sets not only contain the same strong periodicity, but its peaks and valleys closely correspond in time. Two other spectral peaks appear in the PBDB analysis, but appear to be artifacts associated with detrending and with the increased interval length. Sampling-standardization procedures implemented by the PBDB collaboration suggest that the signal is not an artifact of sampling bias. Further work should focus on finding the cause of the 62 My periodicity.

Finite element techniques in computational time series analysis of turbulent flows

NASA Astrophysics Data System (ADS)

Horenko, I.

2009-04-01

In recent years there has been considerable increase of interest in the mathematical modeling and analysis of complex systems that undergo transitions between several phases or regimes. Such systems can be found, e.g., in weather forecast (transitions between weather conditions), climate research (ice and warm ages), computational drug design (conformational transitions) and in econometrics (e.g., transitions between different phases of the market). In all cases, the accumulation of sufficiently detailed time series has led to the formation of huge databases, containing enormous but still undiscovered treasures of information. However, the extraction of essential dynamics and identification of the phases is usually hindered by the multidimensional nature of the signal, i.e., the information is "hidden" in the time series. The standard filtering approaches (like f.~e. wavelets-based spectral methods) have in general unfeasible numerical complexity in high-dimensions, other standard methods (like f.~e. Kalman-filter, MVAR, ARCH/GARCH etc.) impose some strong assumptions about the type of the underlying dynamics. Approach based on optimization of the specially constructed regularized functional (describing the quality of data description in terms of the certain amount of specified models) will be introduced. Based on this approach, several new adaptive mathematical methods for simultaneous EOF/SSA-like data-based dimension reduction and identification of hidden phases in high-dimensional time series will be presented. The methods exploit the topological structure of the analysed data an do not impose severe assumptions on the underlying dynamics. Special emphasis will be done on the mathematical assumptions and numerical cost of the constructed methods. The application of the presented methods will be first demonstrated on a toy example and the results will be compared with the ones obtained by standard approaches. The importance of accounting for the mathematical assumptions used in the analysis will be pointed up in this example. Finally, applications to analysis of meteorological and climate data will be presented.

Quantifying faculty teaching time in a department of obstetrics and gynecology.

PubMed

Emmons, S

1998-10-01

The goal of this project was to develop a reproducible system that measures quantity and quality of teaching in unduplicated hours, such that comparisons of teaching activities could be drawn within and across departments. Such a system could be used for allocating teaching monies and for assessing teaching as part of the promotion and tenure process. Various teaching activities, including time spent in clinic, rounds, and doing procedures, were enumerated. The faculty were surveyed about their opinions on the proportion of clinical time spent in teaching. The literature also was reviewed. Based on analysis of the faculty survey and the literature, a series of calculations were developed to divide clinical time among resident teaching, medical student teaching, and patient care. The only input needed was total time spent in the various clinical activities, time spent in didactic activities, and the resident procedure database. This article describes a simple and fair database system to calculate time spent teaching from activities such as clinic, ward rounds, labor and delivery, and surgery. The teaching portfolio database calculates teaching as a proportion of the faculty member's total activities. The end product is a report that provides a reproducible yearly summary of faculty teaching time per activity and per type of learner.

An ab initio electronic transport database for inorganic materials

DOE PAGES

Ricci, Francesco; Chen, Wei; Aydemir, Umut; ...

2017-07-04

Electronic transport in materials is governed by a series of tensorial properties such as conductivity, Seebeck coefficient, and effective mass. These quantities are paramount to the understanding of materials in many fields from thermoelectrics to electronics and photovoltaics. Transport properties can be calculated from a material’s band structure using the Boltzmann transport theory framework. We present here the largest computational database of electronic transport properties based on a large set of 48,000 materials originating from the Materials Project database. Our results were obtained through the interpolation approach developed in the BoltzTraP software, assuming a constant relaxation time. We present themore » workflow to generate the data, the data validation procedure, and the database structure. In conclusion, our aim is to target the large community of scientists developing materials selection strategies and performing studies involving transport properties.« less

An ab initio electronic transport database for inorganic materials

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

Ricci, Francesco; Chen, Wei; Aydemir, Umut

Electronic transport in materials is governed by a series of tensorial properties such as conductivity, Seebeck coefficient, and effective mass. These quantities are paramount to the understanding of materials in many fields from thermoelectrics to electronics and photovoltaics. Transport properties can be calculated from a material’s band structure using the Boltzmann transport theory framework. We present here the largest computational database of electronic transport properties based on a large set of 48,000 materials originating from the Materials Project database. Our results were obtained through the interpolation approach developed in the BoltzTraP software, assuming a constant relaxation time. We present themore » workflow to generate the data, the data validation procedure, and the database structure. In conclusion, our aim is to target the large community of scientists developing materials selection strategies and performing studies involving transport properties.« less

Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases

PubMed Central

2005-01-01

Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB. PMID:16046824

Identification of Development-Related Genes in the Ovaries of Adult Harmonia axyridis (Pallas) Lady Beetles Using a Time- Series Analysis by RNA-seq.

PubMed

Du, Wenxiao; Zeng, Fanrong

2016-12-14

Adults of the lady beetle species Harmonia axyridis (Pallas) are bred artificially en masse for classic biological control, which requires egg-laying by the H. axyridis ovary. Development-related genes may impact the growth of the H. axyridis adult ovary but have not been reported. Here, we used integrative time-series RNA-seq analysis of the ovary in H. axyridis adults to detect development-related genes. A total of 28,558 unigenes were functionally annotated using seven types of databases to obtain an annotated unigene database for ovaries in H. axyridis adults. We also analysed differentially expressed genes (DEGs) between samples. Based on a combination of the results of this bioinformatics analysis with literature reports and gene expression level changes in four different stages, we focused on the development of oocyte reproductive stem cell and yolk formation process and identified 26 genes with high similarity to development-related genes. 20 DEGs were randomly chosen for quantitative real-time PCR (qRT-PCR) to validate the accuracy of the RNA-seq results. This study establishes a robust pipeline for the discovery of key genes using high-throughput sequencing and the identification of a class of development-related genes for characterization.

Transportation-markings database : composite categories, classification & index. Part I 5, Volume 3, additional studies

DOT National Transportation Integrated Search

2006-01-01

The Transportation-Markings Database project (within the T-M Monograph Series) began in 1997 with the publishing of the initial component, Transportation-Markings Database: Marine. That study was joined by T-M Database: Traffic Control Devices (1998)...

Time-series animation techniques for visualizing urban growth

USGS Publications Warehouse

Acevedo, W.; Masuoka, P.

1997-01-01

Time-series animation is a visually intuitive way to display urban growth. Animations of landuse change for the Baltimore-Washington region were generated by showing a series of images one after the other in sequential order. Before creating an animation, various issues which will affect the appearance of the animation should be considered, including the number of original data frames to use, the optimal animation display speed, the number of intermediate frames to create between the known frames, and the output media on which the animations will be displayed. To create new frames between the known years of data, the change in each theme (i.e. urban development, water bodies, transportation routes) must be characterized and an algorithm developed to create the in-between frames. Example time-series animations were created using a temporal GIS database of the Baltimore-Washington area. Creating the animations involved generating raster images of the urban development, water bodies, and principal transportation routes; overlaying the raster images on a background image; and importing the frames to a movie file. Three-dimensional perspective animations were created by draping each image over digital elevation data prior to importing the frames to a movie file. ?? 1997 Elsevier Science Ltd.

Database Search Strategies & Tips. Reprints from the Best of "ONLINE" [and]"DATABASE."

ERIC Educational Resources Information Center

Online, Inc., Weston, CT.

Reprints of 17 articles presenting strategies and tips for searching databases online appear in this collection, which is one in a series of volumes of reprints from "ONLINE" and "DATABASE" magazines. Edited for information professionals who use electronically distributed databases, these articles address such topics as: (1)…

Detecting and characterizing high-frequency oscillations in epilepsy: a case study of big data analysis

NASA Astrophysics Data System (ADS)

Huang, Liang; Ni, Xuan; Ditto, William L.; Spano, Mark; Carney, Paul R.; Lai, Ying-Cheng

2017-01-01

We develop a framework to uncover and analyse dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive datasets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert transform paradigm to obtain the fundamental components embedded in the time series at distinct time scales, and statistical/scaling analysis of the components. As a case study, we apply our framework to detecting and characterizing high-frequency oscillations (HFOs) from a big database of rat electroencephalogram recordings. We find a striking phenomenon: HFOs exhibit on-off intermittency that can be quantified by algebraic scaling laws. Our framework can be generalized to big data-related problems in other fields such as large-scale sensor data and seismic data analysis.

Transient deformation from daily GPS displacement time series: postseismic deformation, ETS and evolving strain rates

NASA Astrophysics Data System (ADS)

Bock, Y.; Fang, P.; Moore, A. W.; Kedar, S.; Liu, Z.; Owen, S. E.; Glasscoe, M. T.

2016-12-01

Detection of time-dependent crustal deformation relies on the availability of accurate surface displacements, proper time series analysis to correct for secular motion, coseismic and non-tectonic instrument offsets, periodic signatures at different frequencies, and a realistic estimate of uncertainties for the parameters of interest. As part of the NASA Solid Earth Science ESDR System (SESES) project, daily displacement time series are estimated for about 2500 stations, focused on tectonic plate boundaries and having a global distribution for accessing the terrestrial reference frame. The "combined" time series are optimally estimated from independent JPL GIPSY and SIO GAMIT solutions, using a consistent set of input epoch-date coordinates and metadata. The longest time series began in 1992; more than 30% of the stations have experienced one or more of 35 major earthquakes with significant postseismic deformation. Here we present three examples of time-dependent deformation that have been detected in the SESES displacement time series. (1) Postseismic deformation is a fundamental time-dependent signal that indicates a viscoelastic response of the crust/mantle lithosphere, afterslip, or poroelastic effects at different spatial and temporal scales. It is critical to identify and estimate the extent of postseismic deformation in both space and time not only for insight into the crustal deformation and earthquake cycles and their underlying physical processes, but also to reveal other time-dependent signals. We report on our database of characterized postseismic motions using a principal component analysis to isolate different postseismic processes. (2) Starting with the SESES combined time series and applying a time-dependent Kalman filter, we examine episodic tremor and slow slip (ETS) in the Cascadia subduction zone. We report on subtle slip details, allowing investigation of the spatiotemporal relationship between slow slip transients and tremor and their underlying physical mechanisms. (3) We present evolving strain dilatation and shear rates based on the SESES velocities for regional subnetworks as a metric for assigning earthquake probabilities and detection of possible time-dependent deformation related to underlying physical processes.

Quantitative Assessment of Arrhythmia Using Non-linear Approach: A Non-invasive Prognostic Tool

NASA Astrophysics Data System (ADS)

Chakraborty, Monisha; Ghosh, Dipak

2017-12-01

Accurate prognostic tool to identify severity of Arrhythmia is yet to be investigated, owing to the complexity of the ECG signal. In this paper, we have shown that quantitative assessment of Arrhythmia is possible using non-linear technique based on "Hurst Rescaled Range Analysis". Although the concept of applying "non-linearity" for studying various cardiac dysfunctions is not entirely new, the novel objective of this paper is to identify the severity of the disease, monitoring of different medicine and their dose, and also to assess the efficiency of different medicine. The approach presented in this work is simple which in turn will help doctors in efficient disease management. In this work, Arrhythmia ECG time series are collected from MIT-BIH database. Normal ECG time series are acquired using POLYPARA system. Both time series are analyzed in thelight of non-linear approach following the method "Rescaled Range Analysis". The quantitative parameter, "Fractal Dimension" (D) is obtained from both types of time series. The major finding is that Arrhythmia ECG poses lower values of D as compared to normal. Further, this information can be used to access the severity of Arrhythmia quantitatively, which is a new direction of prognosis as well as adequate software may be developed for the use of medical practice.

Quantitative Assessment of Arrhythmia Using Non-linear Approach: A Non-invasive Prognostic Tool

NASA Astrophysics Data System (ADS)

Chakraborty, Monisha; Ghosh, Dipak

2018-04-01

Accurate prognostic tool to identify severity of Arrhythmia is yet to be investigated, owing to the complexity of the ECG signal. In this paper, we have shown that quantitative assessment of Arrhythmia is possible using non-linear technique based on "Hurst Rescaled Range Analysis". Although the concept of applying "non-linearity" for studying various cardiac dysfunctions is not entirely new, the novel objective of this paper is to identify the severity of the disease, monitoring of different medicine and their dose, and also to assess the efficiency of different medicine. The approach presented in this work is simple which in turn will help doctors in efficient disease management. In this work, Arrhythmia ECG time series are collected from MIT-BIH database. Normal ECG time series are acquired using POLYPARA system. Both time series are analyzed in thelight of non-linear approach following the method "Rescaled Range Analysis". The quantitative parameter, "Fractal Dimension" (D) is obtained from both types of time series. The major finding is that Arrhythmia ECG poses lower values of D as compared to normal. Further, this information can be used to access the severity of Arrhythmia quantitatively, which is a new direction of prognosis as well as adequate software may be developed for the use of medical practice.

A Method to Assess Seasonality of Urinary Tract Infections Based on Medication Sales and Google Trends

PubMed Central

Lambert, Bruno; Flahault, Antoine; Chartier-Kastler, Emmanuel; Hanslik, Thomas

2013-01-01

Background Despite the fact that urinary tract infection (UTI) is a very frequent disease, little is known about its seasonality in the community. Methods and Findings To estimate seasonality of UTI using multiple time series constructed with available proxies of UTI. Eight time series based on two databases were used: sales of urinary antibacterial medications reported by a panel of pharmacy stores in France between 2000 and 2012, and search trends on the Google search engine for UTI-related terms between 2004 and 2012 in France, Germany, Italy, the USA, China, Australia and Brazil. Differences between summers and winters were statistically assessed with the Mann-Whitney test. We evaluated seasonality by applying the Harmonics Product Spectrum on Fast Fourier Transform. Seven time series out of eight displayed a significant increase in medication sales or web searches in the summer compared to the winter, ranging from 8% to 20%. The eight time series displayed a periodicity of one year. Annual increases were seen in the summer for UTI drug sales in France and Google searches in France, the USA, Germany, Italy, and China. Increases occurred in the austral summer for Google searches in Brazil and Australia. Conclusions An annual seasonality of UTIs was evidenced in seven different countries, with peaks during the summer. PMID:24204587

A combined solar and geomagnetic index for thermospheric climate

PubMed Central

Mlynczak, Martin G; Hunt, Linda A; Marshall, B Thomas; Russell, James M; Mertens, Christopher J; Thompson, R Earl; Gordley, Larry L

2015-01-01

Infrared radiation from nitric oxide (NO) at 5.3 µm is a primary mechanism by which the thermosphere cools to space. The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the NASA Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics satellite has been measuring thermospheric cooling by NO for over 13 years. In this letter we show that the SABER time series of globally integrated infrared power (watts) radiated by NO can be replicated accurately by a multiple linear regression fit using the F10.7, Ap, and Dst indices. This allows reconstruction of the NO power time series back nearly 70 years with extant databases of these indices. The relative roles of solar ultraviolet and geomagnetic processes in determining the NO cooling are derived and shown to vary significantly over the solar cycle. The NO power is a fundamental integral constraint on the thermospheric climate, and the time series presented here can be used to test upper atmosphere models over seven different solar cycles. Key Points F10.7, Ap, and Dst replicate time series of radiative cooling by nitric oxide Quantified relative roles of solar irradiance, geomagnetism in radiative cooling Establish a new index and extend record of thermospheric cooling back 70 years PMID:26709319

A combined solar and geomagnetic index for thermospheric climate.

PubMed

Mlynczak, Martin G; Hunt, Linda A; Marshall, B Thomas; Russell, James M; Mertens, Christopher J; Thompson, R Earl; Gordley, Larry L

2015-05-28

Infrared radiation from nitric oxide (NO) at 5.3 µm is a primary mechanism by which the thermosphere cools to space. The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on the NASA Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics satellite has been measuring thermospheric cooling by NO for over 13 years. In this letter we show that the SABER time series of globally integrated infrared power (watts) radiated by NO can be replicated accurately by a multiple linear regression fit using the F 10.7 , Ap , and Dst indices. This allows reconstruction of the NO power time series back nearly 70 years with extant databases of these indices. The relative roles of solar ultraviolet and geomagnetic processes in determining the NO cooling are derived and shown to vary significantly over the solar cycle. The NO power is a fundamental integral constraint on the thermospheric climate, and the time series presented here can be used to test upper atmosphere models over seven different solar cycles. F 10.7 , Ap , and Dst replicate time series of radiative cooling by nitric oxide Quantified relative roles of solar irradiance, geomagnetism in radiative cooling Establish a new index and extend record of thermospheric cooling back 70 years.

NOAA Propagation Database Value in Tsunami Forecast Guidance

NASA Astrophysics Data System (ADS)

Eble, M. C.; Wright, L. M.

2016-02-01

The National Oceanic and Atmospheric Administration (NOAA) Center for Tsunami Research (NCTR) has developed a tsunami forecasting capability that combines a graphical user interface with data ingestion and numerical models to produce estimates of tsunami wave arrival times, amplitudes, current or water flow rates, and flooding at specific coastal communities. The capability integrates several key components: deep-ocean observations of tsunamis in real-time, a basin-wide pre-computed propagation database of water level and flow velocities based on potential pre-defined seismic unit sources, an inversion or fitting algorithm to refine the tsunami source based on the observations during an event, and tsunami forecast models. As tsunami waves propagate across the ocean, observations from the deep ocean are automatically ingested into the application in real-time to better define the source of the tsunami itself. Since passage of tsunami waves over a deep ocean reporting site is not immediate, we explore the value of the NOAA propagation database in providing placeholder forecasts in advance of deep ocean observations. The propagation database consists of water elevations and flow velocities pre-computed for 50 x 100 [km] unit sources in a continuous series along all known ocean subduction zones. The 2011 Japan Tohoku tsunami is presented as the case study

The Global Streamflow Indices and Metadata archive (G-SIM): A compilation of global streamflow time series indices and meta-data

NASA Astrophysics Data System (ADS)

Do, Hong; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth; Senerivatne, Sonia

2017-04-01

In-situ observations of daily streamflow with global coverage are a crucial asset for understanding large-scale freshwater resources which are an essential component of the Earth system and a prerequisite for societal development. Here we present the Global Streamflow Indices and Metadata archive (G-SIM), a collection indices derived from more than 20,000 daily streamflow time series across the globe. These indices are designed to support global assessments of change in wet and dry extremes, and have been compiled from 12 free-to-access online databases (seven national databases and five international collections). The G-SIM archive also includes significant metadata to help support detailed understanding of streamflow dynamics, with the inclusion of drainage area shapefile and many essential catchment properties such as land cover type, soil and topographic characteristics. The automated procedure in data handling and quality control of the project makes G-SIM a reproducible, extendible archive and can be utilised for many purposes in large-scale hydrology. Some potential applications include the identification of observational trends in hydrological extremes, the assessment of climate change impacts on streamflow regimes, and the validation of global hydrological models.

Reduction of the dimension of neural network models in problems of pattern recognition and forecasting

NASA Astrophysics Data System (ADS)

Nasertdinova, A. D.; Bochkarev, V. V.

2017-11-01

Deep neural networks with a large number of parameters are a powerful tool for solving problems of pattern recognition, prediction and classification. Nevertheless, overfitting remains a serious problem in the use of such networks. A method of solving the problem of overfitting is proposed in this article. This method is based on reducing the number of independent parameters of a neural network model using the principal component analysis, and can be implemented using existing libraries of neural computing. The algorithm was tested on the problem of recognition of handwritten symbols from the MNIST database, as well as on the task of predicting time series (rows of the average monthly number of sunspots and series of the Lorentz system were used). It is shown that the application of the principal component analysis enables reducing the number of parameters of the neural network model when the results are good. The average error rate for the recognition of handwritten figures from the MNIST database was 1.12% (which is comparable to the results obtained using the "Deep training" methods), while the number of parameters of the neural network can be reduced to 130 times.

Trends in solar radiation in NCEP/NCAR database and measurements in northeastern Brazil

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

Silva, Vicente de Paulo Rodrigues da; Silva, Roberta Araujo e; Cavalcanti, Enilson Palmeira

2010-10-15

The database from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis project available for the period from 1948 to 2009 was used for obtaining long-term solar radiation for northeastern Brazil. Measurements of global solar radiation (R{sub s}) from data collection platform (DCP) for four climatic zones of northeastern Brazil were compared to the re-analysis data. Applying cluster analysis to R{sub s} from database, homogeneous sub-regions in northeastern Brazil were determined. Long times series of R{sub s} and sunshine duration measurements data for two sites, Petrolina (09 09'S, 40 22'W) and Juazeiro (09 24'S, 40 26'W), exceedingmore » 30 years, were analyzed. In order to exclude the decadal variations which are linked to the Pacific Decadal Oscillation, high-frequency cycles in the solar radiation and sunshine duration time series were eliminated by using a 14-year moving average, and the Mann-Kendall test was employed to assess the long-term variability of re-analysis and measured solar radiation. This study provides an overview of the decrease in solar radiation in a large area, which can be attributed to the global dimming effect. The global solar radiation obtained from the NCEP/NCAR re-analysis data overestimate that obtained from DCP measurements by 1.6% to 18.6%. Results show that there is a notable symmetry between R{sub s} from the re-analysis data and sunshine duration measurements. (author)« less

A Combined Solar and Geomagnetic Index for Thermospheric Climate

NASA Technical Reports Server (NTRS)

Hunt, Linda; Mlynczak, Marty

2015-01-01

Infrared radiation from nitric oxide (NO) at 5.3 Â is a primary mechanism by which the thermosphere cools to space. The SABER instrument on the NASA TIMED satellite has been measuring thermospheric cooling by NO for over 13 years. Physically, changes in NO emission are due to changes in temperature, atomic oxygen, and the NO density. These physical changes however are driven by changes in solar irradiance and changes in geomagnetic conditions. We show that the SABER time series of globally integrated infrared power (Watts) radiated by NO can be replicated accurately by a multiple linear regression fit using the F10.7, Ap, and Dst indices. This fit enables several fundamental properties of NO cooling to be determined as well as their variability with time, permitting reconstruction of the NO power time series back nearly 70 years with extant databases of these indices. The relative roles of solar ultraviolet and geomagnetic processes in determining the NO cooling are derived and shown to be solar cycle dependent. This reconstruction provides a long-term time series of an integral radiative constraint on thermospheric climate that can be used to test climate models.

Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition

PubMed Central

Munoz-Organero, Mario; Ruiz-Blazquez, Ramona

2017-01-01

Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates (F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware. PMID:28208736

Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition.

PubMed

Munoz-Organero, Mario; Ruiz-Blazquez, Ramona

2017-02-08

Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates ( F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware.

A Physiological Time Series Dynamics-Based Approach to Patient Monitoring and Outcome Prediction

PubMed Central

Lehman, Li-Wei H.; Adams, Ryan P.; Mayaud, Louis; Moody, George B.; Malhotra, Atul; Mark, Roger G.; Nemati, Shamim

2015-01-01

Cardiovascular variables such as heart rate (HR) and blood pressure (BP) are regulated by an underlying control system, and therefore, the time series of these vital signs exhibit rich dynamical patterns of interaction in response to external perturbations (e.g., drug administration), as well as pathological states (e.g., onset of sepsis and hypotension). A question of interest is whether “similar” dynamical patterns can be identified across a heterogeneous patient cohort, and be used for prognosis of patients’ health and progress. In this paper, we used a switching vector autoregressive framework to systematically learn and identify a collection of vital sign time series dynamics, which are possibly recurrent within the same patient and may be shared across the entire cohort. We show that these dynamical behaviors can be used to characterize the physiological “state” of a patient. We validate our technique using simulated time series of the cardiovascular system, and human recordings of HR and BP time series from an orthostatic stress study with known postural states. Using the HR and BP dynamics of an intensive care unit (ICU) cohort of over 450 patients from the MIMIC II database, we demonstrate that the discovered cardiovascular dynamics are significantly associated with hospital mortality (dynamic modes 3 and 9, p = 0.001, p = 0.006 from logistic regression after adjusting for the APACHE scores). Combining the dynamics of BP time series and SAPS-I or APACHE-III provided a more accurate assessment of patient survival/mortality in the hospital than using SAPS-I and APACHE-III alone (p = 0.005 and p = 0.045). Our results suggest that the discovered dynamics of vital sign time series may contain additional prognostic value beyond that of the baseline acuity measures, and can potentially be used as an independent predictor of outcomes in the ICU. PMID:25014976

A High Temperature Cyclic Oxidation Data Base for Selected Materials Tested at NASA Glenn Research Center

NASA Technical Reports Server (NTRS)

Barrett, Charles A.

2003-01-01

The cyclic oxidation test results for some 1000 high temperature commercial and experimental alloys have been collected in an EXCEL database. This database represents over thirty years of research at NASA Glenn Research Center in Cleveland, Ohio. The data is in the form of a series of runs of specific weight change versus time values for a set of samples tested at a given temperature, cycle time, and exposure time. Included on each run is a set of embedded plots of the critical data. The nature of the data is discussed along with analysis of the cyclic oxidation process. In addition examples are given as to how a set of results can be analyzed. The data is assembled on a read-only compact disk which is available on request from Materials Durability Branch, NASA Glenn Research Center, Cleveland, Ohio.

Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

NASA Astrophysics Data System (ADS)

Peltoniemi, Mikko; Aurela, Mika; Böttcher, Kristin; Kolari, Pasi; Loehr, John; Karhu, Jouni; Linkosalmi, Maiju; Melih Tanis, Cemal; Tuovinen, Juha-Pekka; Nadir Arslan, Ali

2018-01-01

In recent years, monitoring of the status of ecosystems using low-cost web (IP) or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1-3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/). Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862). Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

Dynamic Forecasting Conditional Probability of Bombing Attacks Based on Time-Series and Intervention Analysis.

PubMed

Li, Shuying; Zhuang, Jun; Shen, Shifei

2017-07-01

In recent years, various types of terrorist attacks occurred, causing worldwide catastrophes. According to the Global Terrorism Database (GTD), among all attack tactics, bombing attacks happened most frequently, followed by armed assaults. In this article, a model for analyzing and forecasting the conditional probability of bombing attacks (CPBAs) based on time-series methods is developed. In addition, intervention analysis is used to analyze the sudden increase in the time-series process. The results show that the CPBA increased dramatically at the end of 2011. During that time, the CPBA increased by 16.0% in a two-month period to reach the peak value, but still stays 9.0% greater than the predicted level after the temporary effect gradually decays. By contrast, no significant fluctuation can be found in the conditional probability process of armed assault. It can be inferred that some social unrest, such as America's troop withdrawal from Afghanistan and Iraq, could have led to the increase of the CPBA in Afghanistan, Iraq, and Pakistan. The integrated time-series and intervention model is used to forecast the monthly CPBA in 2014 and through 2064. The average relative error compared with the real data in 2014 is 3.5%. The model is also applied to the total number of attacks recorded by the GTD between 2004 and 2014. © 2016 Society for Risk Analysis.

Alaska Geochemical Database - Mineral Exploration Tool for the 21st Century - PDF of presentation

USGS Publications Warehouse

Granitto, Matthew; Schmidt, Jeanine M.; Labay, Keith A.; Shew, Nora B.; Gamble, Bruce M.

2012-01-01

The U.S. Geological Survey has created a geochemical database of geologic material samples collected in Alaska. This database is readily accessible to anyone with access to the Internet. Designed as a tool for mineral or environmental assessment, land management, or mineral exploration, the initial version of the Alaska Geochemical Database - U.S. Geological Survey Data Series 637 - contains geochemical, geologic, and geospatial data for 264,158 samples collected from 1962-2009: 108,909 rock samples; 92,701 sediment samples; 48,209 heavy-mineral-concentrate samples; 6,869 soil samples; and 7,470 mineral samples. In addition, the Alaska Geochemical Database contains mineralogic data for 18,138 nonmagnetic-fraction heavy mineral concentrates, making it the first U.S. Geological Survey database of this scope that contains both geochemical and mineralogic data. Examples from the Alaska Range will illustrate potential uses of the Alaska Geochemical Database in mineral exploration. Data from the Alaska Geochemical Database have been extensively checked for accuracy of sample media description, sample site location, and analytical method using U.S. Geological Survey sample-submittal archives and U.S. Geological Survey publications (plus field notebooks and sample site compilation base maps from the Alaska Technical Data Unit in Anchorage, Alaska). The database is also the repository for nearly all previously released U.S. Geological Survey Alaska geochemical datasets. Although the Alaska Geochemical Database is a fully relational database in Microsoft® Access 2003 and 2010 formats, these same data are also provided as a series of spreadsheet files in Microsoft® Excel 2003 and 2010 formats, and as ASCII text files. A DVD version of the Alaska Geochemical Database was released in October 2011, as U.S. Geological Survey Data Series 637, and data downloads are available at http://pubs.usgs.gov/ds/637/. Also, all Alaska Geochemical Database data have been incorporated into the interactive U.S. Geological Survey Mineral Resource Data web portal, available at http://mrdata.usgs.gov/.

Five hydrologic and landscape databases for selected National Wildlife Refuges in the Southeastern United States

USGS Publications Warehouse

Buell, Gary R.; Gurley, Laura N.; Calhoun, Daniel L.; Hunt, Alexandria M.

2017-06-12

This report serves as metadata and a user guide for five out of six hydrologic and landscape databases developed by the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, to describe data-collection, data-reduction, and data-analysis methods used to construct the databases and provides statistical and graphical descriptions of the databases. Six hydrologic and landscape databases were developed: (1) the Cache River and White River National Wildlife Refuges (NWRs) and contributing watersheds in Arkansas, Missouri, and Oklahoma, (2) the Cahaba River NWR and contributing watersheds in Alabama, (3) the Caloosahatchee and J.N. “Ding” Darling NWRs and contributing watersheds in Florida, (4) the Clarks River NWR and contributing watersheds in Kentucky, Tennessee, and Mississippi, (5) the Lower Suwannee NWR and contributing watersheds in Georgia and Florida, and (6) the Okefenokee NWR and contributing watersheds in Georgia and Florida. Each database is composed of a set of ASCII files, Microsoft Access files, and Microsoft Excel files. The databases were developed as an assessment and evaluation tool for use in examining NWR-specific hydrologic patterns and trends as related to water availability and water quality for NWR ecosystems, habitats, and target species. The databases include hydrologic time-series data, summary statistics on landscape and hydrologic time-series data, and hydroecological metrics that can be used to assess NWR hydrologic conditions and the availability of aquatic and riparian habitat. Landscape data that describe the NWR physiographic setting and the locations of hydrologic data-collection stations were compiled and mapped. Categories of landscape data include land cover, soil hydrologic characteristics, physiographic features, geographic and hydrographic boundaries, hydrographic features, and regional runoff estimates. The geographic extent of each database covers an area within which human activities, climatic variation, and hydrologic processes can potentially affect the hydrologic regime of the NWRs and adjacent areas. The hydrologic and landscape database for the Cache and White River NWRs and contributing watersheds in Arkansas, Missouri, and Oklahoma has been described and documented in detail (Buell and others, 2012). This report serves as a companion to the Buell and others (2012) report to describe and document the five subsequent hydrologic and landscape databases that were developed: Chapter A—the Cahaba River NWR and contributing watersheds in Alabama, Chapter B—the Caloosahatchee and J.N. “Ding” Darling NWRs and contributing watersheds in Florida, Chapter C—the Clarks River NWR and contributing watersheds in Kentucky, Tennessee, and Mississippi, Chapter D—the Lower Suwannee NWR and contributing watersheds in Georgia and Florida, and Chapter E—the Okefenokee NWR and contributing watersheds in Georgia and Florida.

The Effects of Armed Conflict on Schooling in Sub-Saharan Africa

ERIC Educational Resources Information Center

Poirier, Thomas

2012-01-01

In the past decades, most of the countries in Sub-Saharan Africa have been affected by armed conflicts. By means of a time-series cross-sectional (TSCS) database, we attempt to measure the impact of war on a sample of 43 countries in Africa from 1950 to 2010. These conflicts, and especially civil wars, are shown to have a strong negative effect on…

Computers in the Cop Car: Impact of the Mobile Digital Terminal Technology on Motor Vehicle Theft Clearance and Recovery Rates in a Texas City.

ERIC Educational Resources Information Center

Nunn, Samuel

1993-01-01

Assessed the impact of the Mobile Digital Terminal technology (computers used to communicate with remote crime databases) on motor vehicle theft clearance (arresting a perpetrator) and recovery rates in Fort Worth (Texas), using a time series analysis. Impact has been ambiguous, with little evidence of improved clearance or recovery. (SLD)

Clinical Characteristics of Malignant Melanoma in Southwest China: A Single-Center Series of 82 Consecutive Cases and a Meta-Analysis of 958 Reported Cases

PubMed Central

Huang, Hui; Zhai, Zhifang; Shen, Zhu; Lin, Hui

2016-01-01

Purpose The present study determined the clinical characteristics and prognostic factors in patients with malignant melanoma based on a series of 82 cases from January 2009 to December 2014 in Southwest Hospital and a meta-analysis (including 12 articles) involving 958 patients in China. Materials and methods The database elements included basic demographic data and prognosticators which were extracted from medical records. Statistical analyses of survival, and multivariate analyses of factors associated with survival were performed using the Kaplan—Meier method, and the Cox proportional hazard model, respectively. Literatures were identified through systematic searches in PubMed, Embase, the Cochrane Library, China National Knowledge Infrastructure (CNKI) and Weipu database (VIP) database for the period from inception to December 2015. The meta-analysis was conducted using R 3.1.1 meta-analysis software Results In this series of 82 cases, the median age of the patients was 57.50 years. Melanoma was located in the foot in 79% of patients. Sixty-one patients (74.4%) were classified as stage II-III. Thirty-two patients (39.0%) had acral malignant melanoma, and 31 patients (37.8%) had nodular malignant melanoma. The clinical characteristics of melanoma were similar to those in areas outside southwest China (from results of the meta-analysis). The median survival time was 29.50 months. The 1-year, 3-year, and 5-year survival rates were 84.1%, 39.0% and 10.9%, respectively. COX regression following multi-factor analysis showed that ulcer, tumor boundary and lymph node metastasis were associated with prognosis. Conclusions The clinical characteristics of melanoma in Chinese were different from those in Caucasians. Ulcer, tumor margins, and lymph node metastasis were significantly associated with prognosis. Immune therapy may prolong the median survival time of patients with acral melanoma, nodular melanoma, or stage I-III disease, although these differences were not statistically significant. PMID:27861496

NEW SUNS IN THE COSMOS. III. MULTIFRACTAL SIGNATURE ANALYSIS

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

Freitas, D. B. de; Nepomuceno, M. M. F.; Junior, P. R. V. de Moraes

2016-11-01

In the present paper, we investigate the multifractality signatures in hourly time series extracted from the CoRoT spacecraft database. Our analysis is intended to highlight the possibility that astrophysical time series can be members of a particular class of complex and dynamic processes, which require several photometric variability diagnostics to characterize their structural and topological properties. To achieve this goal, we search for contributions due to a nonlinear temporal correlation and effects caused by heavier tails than the Gaussian distribution, using a detrending moving average algorithm for one-dimensional multifractal signals (MFDMA). We observe that the correlation structure is the mainmore » source of multifractality, while heavy-tailed distribution plays a minor role in generating the multifractal effects. Our work also reveals that the rotation period of stars is inherently scaled by the degree of multifractality. As a result, analyzing the multifractal degree of the referred series, we uncover an evolution of multifractality from shorter to larger periods.« less

Multiple Solutions of Real-time Tsunami Forecasting Using Short-term Inundation Forecasting for Tsunamis Tool

NASA Astrophysics Data System (ADS)

Gica, E.

2016-12-01

The Short-term Inundation Forecasting for Tsunamis (SIFT) tool, developed by NOAA Center for Tsunami Research (NCTR) at the Pacific Marine Environmental Laboratory (PMEL), is used in forecast operations at the Tsunami Warning Centers in Alaska and Hawaii. The SIFT tool relies on a pre-computed tsunami propagation database, real-time DART buoy data, and an inversion algorithm to define the tsunami source. The tsunami propagation database is composed of 50×100km unit sources, simulated basin-wide for at least 24 hours. Different combinations of unit sources, DART buoys, and length of real-time DART buoy data can generate a wide range of results within the defined tsunami source. For an inexperienced SIFT user, the primary challenge is to determine which solution, among multiple solutions for a single tsunami event, would provide the best forecast in real time. This study investigates how the use of different tsunami sources affects simulated tsunamis at tide gauge locations. Using the tide gauge at Hilo, Hawaii, a total of 50 possible solutions for the 2011 Tohoku tsunami are considered. Maximum tsunami wave amplitude and root mean square error results are used to compare tide gauge data and the simulated tsunami time series. Results of this study will facilitate SIFT users' efforts to determine if the simulated tide gauge tsunami time series from a specific tsunami source solution would be within the range of possible solutions. This study will serve as the basis for investigating more historical tsunami events and tide gauge locations.

Fast Demand Forecast of Electric Vehicle Charging Stations for Cell Phone Application

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

Majidpour, Mostafa; Qiu, Charlie; Chung, Ching-Yen

This paper describes the core cellphone application algorithm which has been implemented for the prediction of energy consumption at Electric Vehicle (EV) Charging Stations at UCLA. For this interactive user application, the total time of accessing database, processing the data and making the prediction, needs to be within a few seconds. We analyze four relatively fast Machine Learning based time series prediction algorithms for our prediction engine: Historical Average, kNearest Neighbor, Weighted k-Nearest Neighbor, and Lazy Learning. The Nearest Neighbor algorithm (k Nearest Neighbor with k=1) shows better performance and is selected to be the prediction algorithm implemented for themore » cellphone application. Two applications have been designed on top of the prediction algorithm: one predicts the expected available energy at the station and the other one predicts the expected charging finishing time. The total time, including accessing the database, data processing, and prediction is about one second for both applications.« less

Fisher information framework for time series modeling

NASA Astrophysics Data System (ADS)

Venkatesan, R. C.; Plastino, A.

2017-08-01

A robust prediction model invoking the Takens embedding theorem, whose working hypothesis is obtained via an inference procedure based on the minimum Fisher information principle, is presented. The coefficients of the ansatz, central to the working hypothesis satisfy a time independent Schrödinger-like equation in a vector setting. The inference of (i) the probability density function of the coefficients of the working hypothesis and (ii) the establishing of constraint driven pseudo-inverse condition for the modeling phase of the prediction scheme, is made, for the case of normal distributions, with the aid of the quantum mechanical virial theorem. The well-known reciprocity relations and the associated Legendre transform structure for the Fisher information measure (FIM, hereafter)-based model in a vector setting (with least square constraints) are self-consistently derived. These relations are demonstrated to yield an intriguing form of the FIM for the modeling phase, which defines the working hypothesis, solely in terms of the observed data. Cases for prediction employing time series' obtained from the: (i) the Mackey-Glass delay-differential equation, (ii) one ECG signal from the MIT-Beth Israel Deaconess Hospital (MIT-BIH) cardiac arrhythmia database, and (iii) one ECG signal from the Creighton University ventricular tachyarrhythmia database. The ECG samples were obtained from the Physionet online repository. These examples demonstrate the efficiency of the prediction model. Numerical examples for exemplary cases are provided.

Fast Multivariate Search on Large Aviation Datasets

NASA Technical Reports Server (NTRS)

Bhaduri, Kanishka; Zhu, Qiang; Oza, Nikunj C.; Srivastava, Ashok N.

2010-01-01

Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which can contain up to several gigabytes of data. Surprisingly, research on MTS search is very limited. Most existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two provably correct algorithms to solve this problem (1) an R-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences, and (2) a List Based Search (LBS) algorithm which uses sorted lists for indexing. We demonstrate the performance of these algorithms using two large MTS databases from the aviation domain, each containing several millions of observations Both these tests show that our algorithms have very high prune rates (>95%) thus needing actual

Intercomparison of Satellite Derived Gravity Time Series with Inferred Gravity Time Series from TOPEX/POSEIDON Sea Surface Heights and Climatological Model Output

NASA Technical Reports Server (NTRS)

Cox, C.; Au, A.; Klosko, S.; Chao, B.; Smith, David E. (Technical Monitor)

2001-01-01

The upcoming GRACE mission promises to open a window on details of the global mass budget that will have remarkable clarity, but it will not directly answer the question of what the state of the Earth's mass budget is over the critical last quarter of the 20th century. To address that problem we must draw upon existing technologies such as SLR, DORIS, and GPS, and climate modeling runs in order to improve our understanding. Analysis of long-period geopotential changes based on SLR and DORIS tracking has shown that addition of post 1996 satellite tracking data has a significant impact on the recovered zonal rates and long-period tides. Interannual effects such as those causing the post 1996 anomalies must be better characterized before refined estimates of the decadal period changes in the geopotential can be derived from the historical database of satellite tracking. A possible cause of this anomaly is variations in ocean mass distribution, perhaps associated with the recent large El Nino/La Nina. In this study, a low-degree spherical harmonic gravity time series derived from satellite tracking is compared with a TOPEX/POSEIDON-derived sea surface height time series. Corrections for atmospheric mass effects, continental hydrology, snowfall accumulation, and ocean steric model predictions will be considered.

Use of national clinical databases for informing and for evaluating health care policies.

PubMed

Black, Nick; Tan, Stefanie

2013-02-01

Policy-makers and analysts could make use of national clinical databases either to inform or to evaluate meso-level (organisation and delivery of health care) and macro-level (national) policies. Reviewing the use of 15 of the best established databases in England, we identify and describe four published examples of each use. These show that policy-makers can either make use of the data itself or of research based on the database. For evaluating policies, the major advantages are the huge sample sizes available, the generalisability of the data, its immediate availability and historic information. The principal methodological challenges involve the need for risk adjustment and time-series analysis. Given their usefulness in the policy arena, there are several reasons why national clinical databases have not been used more, some due to a lack of 'push' by their custodians and some to the lack of 'pull' by policy-makers. Greater exploitation of these valuable resources would be facilitated by policy-makers' and custodians' increased awareness, minimisation of legal restrictions on data use, improvements in the quality of databases and a library of examples of applications to policy. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

MOnthly TEmperature DAtabase of Spain 1951-2010: MOTEDAS. (1) Quality control

NASA Astrophysics Data System (ADS)

Peña-Angulo, Dhais; Cortesi, Nicola; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; González-Hidalgo, José Carlos

2014-05-01

The HIDROCAES project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is focused on the high resolution in the Spanish continental land of the warming processes during the 1951-2010. To do that the Department of Geography (University of Zaragoza, Spain), the Hydrometeorological Service (Brno Division, Chezck Republic) and the ISAC-CNR (Bologna, Italy) are developing the new dataset MOTEDAS (MOnthly TEmperature DAtabase of Spain), from which we present a collection of poster to show (1) the general structure of dataset and quality control; (2) the analyses of spatial correlation of monthly mean values of maximum (Tmax) and minimum (Tmin temperature; (3) the reconstruction processes of series and high resolution grid developing; (4) the first initial results of trend analyses of annual, seasonal and monthly range mean values. MOTEDAS has been created after exhaustive analyses and quality control of the original digitalized data of the Spanish National Meteorological Agency (Agencia Estatal de Meteorología, AEMET). Quality control was applied without any prior reconstruction, i.e. on original series. Then, from the total amount of series stored at AEMet archives (more than 4680) we selected only those series with at least 10 years of data (i.e. 120 months, 3066 series) to apply a quality control and reconstruction processes (see Poster MOTEDAS 3). Length of series was Tmin, upper and lower thresholds of absolute data, etc), and by comparison with reference series (see Poster MOTEDAS 3, about reconstruction). Anomalous data were considered when difference between Candidate and Reference series were higher than three times the interquartile distance. The total amount of monthly suspicious data recognized and discarded at the end of this analyses was 7832 data for Tmin, and 8063 for Tmax data; they represent less than 0,8% of original total monthly data, for both Tmax and Tmin. No spatial pattern was detected in the suspicious data; month by month Tmin shows maximum detection in summer months, while Tmax does not show any monthly pattern. Secondly, the homogeneity analyses was performed on the list of series free of anomalous data by using an arrays of test (SNHT, Bivariate, T de Student and Pettit) after new reference series calculated with data free of anomalous. The tests were applied at monthly, seasonal and annual scale (i.e. 17 times per method). Statistical inhomogeneity detections were accepted as follows: Three annual detections (monthly, seasonal, annual) must be found in SNHT or Bivariate test. The total amount of detections by the four tests was greater than 5% of the total possible detection per year. Before any correction we examined the Candidate and reference series chart. Proclim and Anclim software were used during all the processes The total amount of series affected by inhomogeneities was 1013 (Tmax) and 1011 (Tmin), i.e. 1/3 of original series was considered as inhomogeneous. We notice that identified inhomogeneous series in Tmax and Tmin usually do not coincide. This apparently small amount of series compared with previous work could be originated because of the mean length of series is around 15-20 years. References. Stepánek P. 2008a. AnClim - software for time series analysis (for Windows 95/NT). Department of Geography, Faculty of Natural Sciences, MU, Brno, 1.47 B. Stepánek P.. 2008b. ProClimDB - Software for Processing Climatological Datasets. CHMI, Regional office, Brno.

A new edition of the Mars 1:5,000,000 map series

NASA Technical Reports Server (NTRS)

Batson, R. M.; Mcewen, Alfred S.; Wu, Sherman S. C.

1991-01-01

A new edition of the Mars 1:5,000,000 scale map series is in preparation. Two sheets will be made for each quadrangle. Sheet one will show shaded relief, contours, and nomenclature. Sheet 2 will be a full-color photomosaic prepared on the Mars digital image model (MDIM) base co-registered with the Mars low-resolution color database. The latter will have an abbreviated graticule (latitude/longitude ticks only) and no other line overprint. The four major databases used to assemble this series are now virtually complete. These are: (1) Viking-revised shaded relief maps at 1:5,000,000 scale; (2) contour maps at 1:2,000,000 scale; (3) the Mars digital image model; and (4) a color image mosaic of Mars. Together, these databases form the most complete planetwide cartographic definition of Mars that can be compiled with existing data. The new edition will supersede the published Mars 1:5,000,000 scale maps, including the original shaded relief and topographic maps made primarily with Mariner 9 data and the Viking-revised shaded relief and controlled photomosaic series. Publication of the new series will begin in late 1991 or early 1992, and it should be completed in two years.

sunstardb: A Database for the Study of Stellar Magnetism and the Solar-stellar Connection

NASA Astrophysics Data System (ADS)

Egeland, Ricky

2018-05-01

The “solar-stellar connection” began as a relatively small field of research focused on understanding the processes that generate magnetic fields in stars and sometimes lead to a cyclic pattern of long-term variability in activity, as demonstrated by our Sun. This area of study has recently become more broadly pertinent to questions of exoplanet habitability and exo-space weather, as well as stellar evolution. In contrast to other areas of stellar research, individual stars in the solar-stellar connection often have a distinct identity and character in the literature, due primarily to the rarity of the decades-long time-series that are necessary for studying stellar activity cycles. Furthermore, the underlying stellar dynamo is not well understood theoretically, and is thought to be sensitive to several stellar properties, e.g., luminosity, differential rotation, and the depth of the convection zone, which in turn are often parameterized by other more readily available properties. Relevant observations are scattered throughout the literature and existing stellar databases, and consolidating information for new studies is a tedious and laborious exercise. To accelerate research in this area I developed sunstardb, a relational database of stellar properties and magnetic activity proxy time-series keyed by individual named stars. The organization of the data eliminates the need for the problematic catalog cross-matching operations inherent when building an analysis data set from heterogeneous sources. In this article I describe the principles behind sunstardb, the data structures and programming interfaces, as well as use cases from solar-stellar connection research.

Probabilistic seismic hazard assessment for northern Southeast Asia

NASA Astrophysics Data System (ADS)

Chan, C. H.; Wang, Y.; Kosuwan, S.; Nguyen, M. L.; Shi, X.; Sieh, K.

2016-12-01

We assess seismic hazard for northern Southeast Asia through constructing an earthquake and fault database, conducting a series of ground-shaking scenarios and proposing regional seismic hazard maps. Our earthquake database contains earthquake parameters from global and local seismic catalogues, including the ISC, ISC-GEM, the global ANSS Comprehensive Catalogues, Seismological Bureau, Thai Meteorological Department, Thailand, and Institute of Geophysics Vietnam Academy of Science and Technology, Vietnam. To harmonize the earthquake parameters from various catalogue sources, we remove duplicate events and unify magnitudes into the same scale. Our active fault database include active fault data from previous studies, e.g. the active fault parameters determined by Wang et al. (2014), Department of Mineral Resources, Thailand, and Institute of Geophysics, Vietnam Academy of Science and Technology, Vietnam. Based on the parameters from analysis of the databases (i.e., the Gutenberg-Richter relationship, slip rate, maximum magnitude and time elapsed of last events), we determined the earthquake recurrence models of seismogenic sources. To evaluate the ground shaking behaviours in different tectonic regimes, we conducted a series of tests by matching the felt intensities of historical earthquakes to the modelled ground motions using ground motion prediction equations (GMPEs). By incorporating the best-fitting GMPEs and site conditions, we utilized site effect and assessed probabilistic seismic hazard. The highest seismic hazard is in the region close to the Sagaing Fault, which cuts through some major cities in central Myanmar. The northern segment of Sunda megathrust, which could potentially cause M8-class earthquake, brings significant hazard along the Western Coast of Myanmar and eastern Bangladesh. Besides, we conclude a notable hazard level in northern Vietnam and the boundary between Myanmar, Thailand and Laos, due to a series of strike-slip faults, which could potentially cause moderate-large earthquakes. Note that although much of the region has a low probability of damaging shaking, low-probability events have resulted in much destruction recently in SE Asia (e.g. 2008 Wenchuan, 2015 Sabah earthquakes).

Development of web tools to disseminate space geodesy data-related products

NASA Astrophysics Data System (ADS)

Soudarin, Laurent; Ferrage, Pascale; Mezerette, Adrien

2015-04-01

In order to promote the products of the DORIS system, the French Space Agency CNES has developed and implemented on the web site of the International DORIS Service (IDS) a set of plot tools to interactively build and display time series of site positions, orbit residuals and terrestrial parameters (scale, geocenter). An interactive global map is also available to select sites, and to get access to their information. Besides the products provided by the CNES Orbitography Team and the IDS components, these tools allow comparing time evolutions of coordinates for collocated DORIS and GNSS stations, thanks to the collaboration with the Terrestrial Frame Combination Center of the International GNSS Service (IGS). A database was created to improve robustness and efficiency of the tools, with the objective to propose a complete web service to foster data exchange with the other geodetic services of the International Association of Geodesy (IAG). The possibility to visualize and compare position time series of the four main space geodetic techniques DORIS, GNSS, SLR and VLBI is already under way at the French level. A dedicated version of these web tools has been developed for the French Space Geodesy Research Group (GRGS). It will give access to position time series provided by the GRGS Analysis Centers involved in DORIS, GNSS, SLR and VLBI data processing for the realization of the International Terrestrial Reference Frame. In this presentation, we will describe the functionalities of these tools, and we will address some aspects of the time series (content, format).

EMAP and EMAGE: a framework for understanding spatially organized data.

PubMed

Baldock, Richard A; Bard, Jonathan B L; Burger, Albert; Burton, Nicolas; Christiansen, Jeff; Feng, Guanjie; Hill, Bill; Houghton, Derek; Kaufman, Matthew; Rao, Jianguo; Sharpe, James; Ross, Allyson; Stevenson, Peter; Venkataraman, Shanmugasundaram; Waterhouse, Andrew; Yang, Yiya; Davidson, Duncan R

2003-01-01

The Edinburgh MouseAtlas Project (EMAP) is a time-series of mouse-embryo volumetric models. The models provide a context-free spatial framework onto which structural interpretations and experimental data can be mapped. This enables collation, comparison, and query of complex spatial patterns with respect to each other and with respect to known or hypothesized structure. The atlas also includes a time-dependent anatomical ontology and mapping between the ontology and the spatial models in the form of delineated anatomical regions or tissues. The models provide a natural, graphical context for browsing and visualizing complex data. The Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) is one of the first applications of the EMAP framework and provides a spatially mapped gene-expression database with associated tools for data mapping, submission, and query. In this article, we describe the underlying principles of the Atlas and the gene-expression database, and provide a practical introduction to the use of the EMAP and EMAGE tools, including use of new techniques for whole body gene-expression data capture and mapping.

Massive parallelization of serial inference algorithms for a complex generalized linear model

PubMed Central

Suchard, Marc A.; Simpson, Shawn E.; Zorych, Ivan; Ryan, Patrick; Madigan, David

2014-01-01

Following a series of high-profile drug safety disasters in recent years, many countries are redoubling their efforts to ensure the safety of licensed medical products. Large-scale observational databases such as claims databases or electronic health record systems are attracting particular attention in this regard, but present significant methodological and computational concerns. In this paper we show how high-performance statistical computation, including graphics processing units, relatively inexpensive highly parallel computing devices, can enable complex methods in large databases. We focus on optimization and massive parallelization of cyclic coordinate descent approaches to fit a conditioned generalized linear model involving tens of millions of observations and thousands of predictors in a Bayesian context. We find orders-of-magnitude improvement in overall run-time. Coordinate descent approaches are ubiquitous in high-dimensional statistics and the algorithms we propose open up exciting new methodological possibilities with the potential to significantly improve drug safety. PMID:25328363

Environment Online: The Greening of Databases. Part 2. Scientific and Technical Databases.

ERIC Educational Resources Information Center

Alston, Patricia Gayle

1991-01-01

This second in a series of articles about online sources of environmental information describes scientific and technical databases that are useful for searching environmental data. Topics covered include chemicals and hazardous substances; agriculture; pesticides; water; forestry, oil, and energy resources; air; environmental and occupational…

3DView: Space physics data visualizer

NASA Astrophysics Data System (ADS)

Génot, V.; Beigbeder, L.; Popescu, D.; Dufourg, N.; Gangloff, M.; Bouchemit, M.; Caussarieu, S.; Toniutti, J.-P.; Durand, J.; Modolo, R.; André, N.; Cecconi, B.; Jacquey, C.; Pitout, F.; Rouillard, A.; Pinto, R.; Erard, S.; Jourdane, N.; Leclercq, L.; Hess, S.; Khodachenko, M.; Al-Ubaidi, T.; Scherf, M.; Budnik, E.

2018-04-01

3DView creates visualizations of space physics data in their original 3D context. Time series, vectors, dynamic spectra, celestial body maps, magnetic field or flow lines, and 2D cuts in simulation cubes are among the variety of data representation enabled by 3DView. It offers direct connections to several large databases and uses VO standards; it also allows the user to upload data. 3DView's versatility covers a wide range of space physics contexts.

Teaching Three-Dimensional Structural Chemistry Using Crystal Structure Databases. 4. Examples of Discovery-Based Learning Using the Complete Cambridge Structural Database

ERIC Educational Resources Information Center

Battle, Gary M.; Allen, Frank H.; Ferrence, Gregory M.

2011-01-01

Parts 1 and 2 of this series described the educational value of experimental three-dimensional (3D) chemical structures determined by X-ray crystallography and retrieved from the crystallographic databases. In part 1, we described the information content of the Cambridge Structural Database (CSD) and discussed a representative teaching subset of…

Teaching Three-Dimensional Structural Chemistry Using Crystal Structure Databases. 3. The Cambridge Structural Database System: Information Content and Access Software in Educational Applications

ERIC Educational Resources Information Center

Battle, Gary M.; Allen, Frank H.; Ferrence, Gregory M.

2011-01-01

Parts 1 and 2 of this series described the educational value of experimental three-dimensional (3D) chemical structures determined by X-ray crystallography and retrieved from the crystallographic databases. In part 1, we described the information content of the Cambridge Structural Database (CSD) and discussed a representative teaching subset of…

Monitoring performance of a highly distributed and complex computing infrastructure in LHCb

NASA Astrophysics Data System (ADS)

Mathe, Z.; Haen, C.; Stagni, F.

2017-10-01

In order to ensure an optimal performance of the LHCb Distributed Computing, based on LHCbDIRAC, it is necessary to be able to inspect the behavior over time of many components: firstly the agents and services on which the infrastructure is built, but also all the computing tasks and data transfers that are managed by this infrastructure. This consists of recording and then analyzing time series of a large number of observables, for which the usage of SQL relational databases is far from optimal. Therefore within DIRAC we have been studying novel possibilities based on NoSQL databases (ElasticSearch, OpenTSDB and InfluxDB) as a result of this study we developed a new monitoring system based on ElasticSearch. It has been deployed on the LHCb Distributed Computing infrastructure for which it collects data from all the components (agents, services, jobs) and allows creating reports through Kibana and a web user interface, which is based on the DIRAC web framework. In this paper we describe this new implementation of the DIRAC monitoring system. We give details on the ElasticSearch implementation within the DIRAC general framework, as well as an overview of the advantages of the pipeline aggregation used for creating a dynamic bucketing of the time series. We present the advantages of using the ElasticSearch DSL high-level library for creating and running queries. Finally we shall present the performances of that system.

Causal strength induction from time series data.

PubMed

Soo, Kevin W; Rottman, Benjamin M

2018-04-01

One challenge when inferring the strength of cause-effect relations from time series data is that the cause and/or effect can exhibit temporal trends. If temporal trends are not accounted for, a learner could infer that a causal relation exists when it does not, or even infer that there is a positive causal relation when the relation is negative, or vice versa. We propose that learners use a simple heuristic to control for temporal trends-that they focus not on the states of the cause and effect at a given instant, but on how the cause and effect change from one observation to the next, which we call transitions. Six experiments were conducted to understand how people infer causal strength from time series data. We found that participants indeed use transitions in addition to states, which helps them to reach more accurate causal judgments (Experiments 1A and 1B). Participants use transitions more when the stimuli are presented in a naturalistic visual format than a numerical format (Experiment 2), and the effect of transitions is not driven by primacy or recency effects (Experiment 3). Finally, we found that participants primarily use the direction in which variables change rather than the magnitude of the change for estimating causal strength (Experiments 4 and 5). Collectively, these studies provide evidence that people often use a simple yet effective heuristic for inferring causal strength from time series data. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Library Micro-Computing, Vol. 2. Reprints from the Best of "ONLINE" [and]"DATABASE."

ERIC Educational Resources Information Center

Online, Inc., Weston, CT.

Reprints of 19 articles pertaining to library microcomputing appear in this collection, the second of two volumes on this topic in a series of volumes of reprints from "ONLINE" and "DATABASE" magazines. Edited for information professionals who use electronically distributed databases, these articles address such topics as: (1)…

Chickenpox and Risk of Stroke: A Self-controlled Case Series Analysis

PubMed Central

Thomas, Sara L.; Minassian, Caroline; Ganesan, Vijeya; Langan, Sinéad M.; Smeeth, Liam

2014-01-01

Background. There is good evidence that respiratory and other infections that cause systemic inflammation can trigger strokes; however, the role of specific infections is unclear. Case reports have highlighted chickenpox as a possible risk factor for arterial ischemic stroke, particularly in children, but rigorous studies are needed to determine and quantify any increased risk. Methods. We used anonymized electronic health records totaling >100 million person-years of observation from 4 UK primary care databases to identify individuals who had documented clinical chickenpox and a stroke or transient ischemic attack (TIA). Self-controlled case series methods were used to quantify any increased risk of first stroke or TIA in the 0–6 and 7–12 months following chickenpox compared to other observed time periods. We analyzed data within each database, and performed meta-analyses to obtain summary age-adjusted incidence ratios (IRs) separately for adults and children. Results. Five hundred sixty eligible individuals (including 60 children) were identified who experienced chickenpox and a stroke or TIA during follow-up. Among children, there was a 4-fold increased risk of stroke in the 0–6 months after chickenpox (summary IR = 4.07; 95% confidence interval [CI], 1.96–8.45; I2 = 0%). Among adults, there was a less marked increased risk with moderate between-database heterogeneity (random-effects summary IR = 2.13; 95% CI, 1.05–4.36; I2 = 51%). There was no significant increased risk of stroke in the 7–12 months after chickenpox in children or adults, nor was there evidence of increased risk of TIA in either time period. Conclusions. Our study provides new evidence that children who experience chickenpox are at increased risk of stroke in the subsequent 6 months. PMID:24092802

Chickenpox and risk of stroke: a self-controlled case series analysis.

PubMed

Thomas, Sara L; Minassian, Caroline; Ganesan, Vijeya; Langan, Sinéad M; Smeeth, Liam

2014-01-01

There is good evidence that respiratory and other infections that cause systemic inflammation can trigger strokes; however, the role of specific infections is unclear. Case reports have highlighted chickenpox as a possible risk factor for arterial ischemic stroke, particularly in children, but rigorous studies are needed to determine and quantify any increased risk. We used anonymized electronic health records totaling >100 million person-years of observation from 4 UK primary care databases to identify individuals who had documented clinical chickenpox and a stroke or transient ischemic attack (TIA). Self-controlled case series methods were used to quantify any increased risk of first stroke or TIA in the 0-6 and 7-12 months following chickenpox compared to other observed time periods. We analyzed data within each database, and performed meta-analyses to obtain summary age-adjusted incidence ratios (IRs) separately for adults and children. Five hundred sixty eligible individuals (including 60 children) were identified who experienced chickenpox and a stroke or TIA during follow-up. Among children, there was a 4-fold increased risk of stroke in the 0-6 months after chickenpox (summary IR = 4.07; 95% confidence interval [CI], 1.96-8.45; I(2) = 0%). Among adults, there was a less marked increased risk with moderate between-database heterogeneity (random-effects summary IR = 2.13; 95% CI, 1.05-4.36; I(2) = 51%). There was no significant increased risk of stroke in the 7-12 months after chickenpox in children or adults, nor was there evidence of increased risk of TIA in either time period. Our study provides new evidence that children who experience chickenpox are at increased risk of stroke in the subsequent 6 months.

Performance of vegetation indices from Landsat time series in deforestation monitoring

NASA Astrophysics Data System (ADS)

Schultz, Michael; Clevers, Jan G. P. W.; Carter, Sarah; Verbesselt, Jan; Avitabile, Valerio; Quang, Hien Vu; Herold, Martin

2016-10-01

The performance of Landsat time series (LTS) of eight vegetation indices (VIs) was assessed for monitoring deforestation across the tropics. Three sites were selected based on differing remote sensing observation frequencies, deforestation drivers and environmental factors. The LTS of each VI was analysed using the Breaks For Additive Season and Trend (BFAST) Monitor method to identify deforestation. A robust reference database was used to evaluate the performance regarding spatial accuracy, sensitivity to observation frequency and combined use of multiple VIs. The canopy cover sensitive Normalized Difference Fraction Index (NDFI) was the most accurate. Among those tested, wetness related VIs (Normalized Difference Moisture Index (NDMI) and the Tasselled Cap wetness (TCw)) were spatially more accurate than greenness related VIs (Normalized Difference Vegetation Index (NDVI) and Tasselled Cap greenness (TCg)). When VIs were fused on feature level, spatial accuracy was improved and overestimation of change reduced. NDVI and NDFI produced the most robust results when observation frequency varies.

Development of web tools to disseminate space geodesy data-related products

NASA Astrophysics Data System (ADS)

Soudarin, L.; Ferrage, P.; Mezerette, A.

2014-12-01

In order to promote the products of the DORIS system, the French Space Agency CNES has developed and implemented on the web site of the International DORIS Service (IDS) a set of plot tools to interactively build and display time series of site positions, orbit residuals and terrestrial parameters (scale, geocenter). An interactive global map is also available to select sites, and to get access to their information. Besides the products provided by the CNES Orbitography Team and the IDS components, these tools allow comparing time evolutions of coordinates for collocated DORIS and GNSS stations, thanks to the collaboration with the Terrestrial Frame Combination Center of the International GNSS Service (IGS). The next step currently in progress is the creation of a database to improve robustness and efficiency of the tools, with the objective to propose a complete web service to foster data exchange with the other geodetic services of the International Association of Geodesy (IAG). The possibility to visualize and compare position time series of the four main space geodetic techniques DORIS, GNSS, SLR and VLBI is already under way at the French level. A dedicated version of these web tools has been developed for the French Space Geodesy Research Group (GRGS). It will give access to position time series provided by the GRGS Analysis Centers involved in DORIS, GNSS, SLR and VLBI data processing for the realization of the International Terrestrial Reference Frame. In this presentation, we will describe the functionalities of these tools, and we will address some aspects of the time series (content, format).

A global multiproxy database for temperature reconstructions of the Common Era.

PubMed

2017-07-11

Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850-2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.

A global multiproxy database for temperature reconstructions of the Common Era

USGS Publications Warehouse

Emile-Geay, Julian; McKay, Nicholas P.; Kaufman, Darrell S.; von Gunten, Lucien; Wang, Jianghao; Anchukaitis, Kevin J.; Abram, Nerilie J.; Addison, Jason A.; Curran, Mark A.J.; Evans, Michael N.; Henley, Benjamin J.; Hao, Zhixin; Martrat, Belen; McGregor, Helen V.; Neukom, Raphael; Pederson, Gregory T.; Stenni, Barbara; Thirumalai, Kaustubh; Werner, Johannes P.; Xu, Chenxi; Divine, Dmitry V.; Dixon, Bronwyn C.; Gergis, Joelle; Mundo, Ignacio A.; Nakatsuka, T.; Phipps, Steven J.; Routson, Cody C.; Steig, Eric J.; Tierney, Jessica E.; Tyler, Jonathan J.; Allen, Kathryn J.; Bertler, Nancy A. N.; Bjorklund, Jesper; Chase, Brian M.; Chen, Min-Te; Cook, Ed; de Jong, Rixt; DeLong, Kristine L.; Dixon, Daniel A.; Ekaykin, Alexey A.; Ersek, Vasile; Filipsson, Helena L.; Francus, Pierre; Freund, Mandy B.; Frezzotti, M.; Gaire, Narayan P.; Gajewski, Konrad; Ge, Quansheng; Goosse, Hugues; Gornostaeva, Anastasia; Grosjean, Martin; Horiuchi, Kazuho; Hormes, Anne; Husum, Katrine; Isaksson, Elisabeth; Kandasamy, Selvaraj; Kawamura, Kenji; Koc, Nalan; Leduc, Guillaume; Linderholm, Hans W.; Lorrey, Andrew M.; Mikhalenko, Vladimir; Mortyn, P. Graham; Motoyama, Hideaki; Moy, Andrew D.; Mulvaney, Robert; Munz, Philipp M.; Nash, David J.; Oerter, Hans; Opel, Thomas; Orsi, Anais J.; Ovchinnikov, Dmitriy V.; Porter, Trevor J.; Roop, Heidi; Saenger, Casey; Sano, Masaki; Sauchyn, David; Saunders, K.M.; Seidenkrantz, Marit-Solveig; Severi, Mirko; Shao, X.; Sicre, Marie-Alexandrine; Sigl, Michael; Sinclair, Kate; St. George, Scott; St. Jacques, Jeannine-Marie; Thamban, Meloth; Thapa, Udya Kuwar; Thomas, E.; Turney, Chris; Uemura, Ryu; Viau, A.E.; Vladimirova, Diana O.; Wahl, Eugene; White, James W. C.; Yu, Z.; Zinke, Jens

2017-01-01

Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.

A global multiproxy database for temperature reconstructions of the Common Era

PubMed Central

Emile-Geay, Julien; McKay, Nicholas P.; Kaufman, Darrell S.; von Gunten, Lucien; Wang, Jianghao; Anchukaitis, Kevin J.; Abram, Nerilie J.; Addison, Jason A.; Curran, Mark A.J.; Evans, Michael N.; Henley, Benjamin J.; Hao, Zhixin; Martrat, Belen; McGregor, Helen V.; Neukom, Raphael; Pederson, Gregory T.; Stenni, Barbara; Thirumalai, Kaustubh; Werner, Johannes P.; Xu, Chenxi; Divine, Dmitry V.; Dixon, Bronwyn C.; Gergis, Joelle; Mundo, Ignacio A.; Nakatsuka, Takeshi; Phipps, Steven J.; Routson, Cody C.; Steig, Eric J.; Tierney, Jessica E.; Tyler, Jonathan J.; Allen, Kathryn J.; Bertler, Nancy A.N.; Björklund, Jesper; Chase, Brian M.; Chen, Min-Te; Cook, Ed; de Jong, Rixt; DeLong, Kristine L.; Dixon, Daniel A.; Ekaykin, Alexey A.; Ersek, Vasile; Filipsson, Helena L.; Francus, Pierre; Freund, Mandy B.; Frezzotti, Massimo; Gaire, Narayan P.; Gajewski, Konrad; Ge, Quansheng; Goosse, Hugues; Gornostaeva, Anastasia; Grosjean, Martin; Horiuchi, Kazuho; Hormes, Anne; Husum, Katrine; Isaksson, Elisabeth; Kandasamy, Selvaraj; Kawamura, Kenji; Kilbourne, K. Halimeda; Koç, Nalan; Leduc, Guillaume; Linderholm, Hans W.; Lorrey, Andrew M.; Mikhalenko, Vladimir; Mortyn, P. Graham; Motoyama, Hideaki; Moy, Andrew D.; Mulvaney, Robert; Munz, Philipp M.; Nash, David J.; Oerter, Hans; Opel, Thomas; Orsi, Anais J.; Ovchinnikov, Dmitriy V.; Porter, Trevor J.; Roop, Heidi A.; Saenger, Casey; Sano, Masaki; Sauchyn, David; Saunders, Krystyna M.; Seidenkrantz, Marit-Solveig; Severi, Mirko; Shao, Xuemei; Sicre, Marie-Alexandrine; Sigl, Michael; Sinclair, Kate; St. George, Scott; St. Jacques, Jeannine-Marie; Thamban, Meloth; Kuwar Thapa, Udya; Thomas, Elizabeth R.; Turney, Chris; Uemura, Ryu; Viau, Andre E.; Vladimirova, Diana O.; Wahl, Eugene R.; White, James W.C.; Yu, Zicheng; Zinke, Jens

2017-01-01

Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python. PMID:28696409

The intermediate polar GK Persei: An unstable relation of the X-ray and the optical intensities in a series of outbursts

NASA Astrophysics Data System (ADS)

Šimon, V.

2015-03-01

Context. GK Per is an intermediate polar that has been displaying dwarf nova outbursts since the middle of the twentieth century. Aims: I analyzed a series of such outbursts in the optical and X-ray bands. I pay attention to the relation of intensities of the optical and X-ray emissions, and its reproducibility in a series of these consecutive outbursts. Methods: This analysis uses the data from the BAT/Swift, ASM/RXTE, AAVSO, and AFOEV databases. It investigates the relation of the time evolution of the profiles of outbursts in the individual bands (hard X-ray, medium/hard X-ray, and optical). Results: This analysis shows that the X-ray intensity steeply rises only in the start of the optical outburst and steeply declines only when the optical outburst comes to its end. However, the 1.5-50 keV band intensity saturates and balances on a plateau during the outburst. (The longer the outburst, the longer its plateau.) The peak X-ray intensities of this series display a significantly narrower range than the optical ones (a factor of about two versus a factor of about eight). This implies a discrepancy between the mass flow through the disk and the production of the X-ray emission via bremsstrahlung at the polar caps of the white dwarf. This discrepancy is the largest in the time of the peak optical intensity when the whole disk (or at least its inner part) is in the hot state and the flow of matter through the disk is the greatest. This study shows that a series of outbursts constitutes more general properties of this discrepancy. I argue that the saturation of the X-ray luminosity in outburst cannot be caused by a dominant increase in X-ray absorption. In the interpretation, large structural changes of the accreting regions at the magnetic poles of the white dwarf occur during the outburst. A buried shock proposed by some authors for polars is also promising for explaining the X-ray light curves of outbursts of GK Per. This research made use of the BAT/Swift, ASM/RXTE, AAVSO, and AFOEV databases.

Towards a Dynamic Digital Observatory: Synthesizing Community Data and Model Development in the Susquehanna River Basin and Chesapeake Bay

NASA Astrophysics Data System (ADS)

Dressler, K. A.; Piasecki, M.; Bhatt, G.; Duffy, C. J.; Reed, P. M.

2007-12-01

Physically-based fully-distributed hydrologic models simulate hydrologic state variables spatiotemporally using information on forcing (climate) and landscape (topography, land use, hydrogeology) heterogeneities. Incorporating physical data layers in the hydrologic model requires intensive data development. Traditionally, GIS has been used for data management, data analysis and visualization; however, proprietary data structures, platform dependence, isolated data model and non-dynamic data-interaction with pluggable software components of existing GIS frameworks, makes it restrictive to perform sophisticated numerical modeling. In this effort we present a "tightly-coupled" GIS interface to Penn State Integrated Hydrologic Model (PIHM; www.pihm.psu.edu) called PIHMgis which is open source, platform independent and extensible. The tight coupling between GIS and the model is achieved by developing a shared data-model and hydrologic-model data structure. Domain discretization is fundamental to the approach and an unstructured triangular irregular network (e.g. Delaunay triangles) is generated with both geometric and parametric constraints. A local prismatic control volume is formed by vertical projection of the Delaunay triangles forming each layer of the model. Given a set of constraints (e.g. river network support, watershed boundary, altitude zones, ecological regions, hydraulic properties, climate zones, etc), an "optimal" mesh is generated. Time variant forcing for the model is typically derived from time series data available at points that are transferred onto a grid. Therefore, the modeling environment can use the Observations Database model developed by the Hydrologic Information Systems group of the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI). As part of a initial testbed series the database has been implemented in support for the Susquehanna and Chesapeake Bay watersheds and is now being populated by national (USGS-NWIS; EPA- STORET), regional (Chesapeake Information Management System, CIMS; National Air Deposition Program, NADP), and local (RTH-Net, Burd Run) datasets. The data can be searched side by side in a one-stop-querying- center, www.hydroseek.org , another application developed as part of the CUAHSI HIS effort. The ultimate goal is to populate the observations database with as many catalogues (i.e. collections of information on what data sources contain) as possible including the build out of the local data sources, i.e. the Susquehanna River Basin Hydrologic Observatory System (SRBHOS) time series server.

Initiation & completion rates of hepatitis A vaccination among US pediatric populations born between 2005 and 2009.

PubMed

Weiss, Thomas; Zhang, Dongmu; Borse, Nagesh N; Walter, Emmanuel B

2015-11-27

To estimate hepatitis A vaccine series initiation and completion rates, assess time to vaccination, identify missed opportunities for the hepatitis A vaccine series, and examine factors associated with hepatitis A vaccine series initiation and completion. We conducted a retrospective, observational study using three healthcare claims databases separately. The study population was comprised of children born between years 2005 and 2009 that were continuously enrolled for at least three and a half years from the date of birth. Every child was followed from date of birth for three and a half years for hepatitis A vaccination. There were 93,735 eligible children from Clinformatics Data Mart, 202,513 from MarketScan Commercial, and 207,545 from MarketScan Medicaid. The overall hepatitis A vaccine series initiation rate was 63.8-79.4% and completion rate was 45.1-66.8% across the three databases. About 62.8-90.1% of the children who never initiated hepatitis A vaccine had at least one well visit from 1 year to three and a half years old. Children were more likely to initiate and complete the hepatitis A vaccine series if they were from more recent birth cohorts, from states with a hepatitis A vaccination recommendation prior to the ACIP universal recommendation, from states with daycare/school entry requirements, were enrolled in an HMO health plan, had pediatricians as primary providers, had more doctor's office/well visits and received MMR/Varicella vaccines. In this study, approximately one in every three to five children remained unvaccinated against hepatitis A. Although the hepatitis A vaccine series initiation and completion improved from 2005 to 2009, vaccine coverage has stabilized in recent years. It is important for providers to identify every opportunity for hepatitis A vaccination and to assure that children get protection from this vaccine-preventable disease. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

In search of functional association from time-series microarray data based on the change trend and level of gene expression

PubMed Central

He, Feng; Zeng, An-Ping

2006-01-01

Background The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional linkages between genes from expression data are mainly based on a point-to-point comparison. Change trends between consecutive time points in time-series data have been so far not well explored. Results In this work we present a new method based on extracting main features of the change trend and level of gene expression between consecutive time points. The method, termed as trend correlation (TC), includes two major steps: 1, calculating a maximal local alignment of change trend score by dynamic programming and a change trend correlation coefficient between the maximal matched change levels of each gene pair; 2, inferring relationships of gene pairs based on two statistical extraction procedures. The new method considers time shifts and inverted relationships in a similar way as the local clustering (LC) method but the latter is merely based on a point-to-point comparison. The TC method is demonstrated with data from yeast cell cycle and compared with the LC method and the widely used Pearson correlation coefficient (PCC) based clustering method. The biological significance of the gene pairs is examined with several large-scale yeast databases. Although the TC method predicts an overall lower number of gene pairs than the other two methods at a same p-value threshold, the additional number of gene pairs inferred by the TC method is considerable: e.g. 20.5% compared with the LC method and 49.6% with the PCC method for a p-value threshold of 2.7E-3. Moreover, the percentage of the inferred gene pairs consistent with databases by our method is generally higher than the LC method and similar to the PCC method. A significant number of the gene pairs only inferred by the TC method are process-identity or function-similarity pairs or have well-documented biological interactions, including 443 known protein interactions and some known cell cycle related regulatory interactions. It should be emphasized that the overlapping of gene pairs detected by the three methods is normally not very high, indicating a necessity of combining the different methods in search of functional association of genes from time-series data. For a p-value threshold of 1E-5 the percentage of process-identity and function-similarity gene pairs among the shared part of the three methods reaches 60.2% and 55.6% respectively, building a good basis for further experimental and functional study. Furthermore, the combined use of methods is important to infer more complete regulatory circuits and network as exemplified in this study. Conclusion The TC method can significantly augment the current major methods to infer functional linkages and biological network and is well suitable for exploring temporal relationships of gene expression in time-series data. PMID:16478547

Data-based information gain on the response behaviour of hydrological models at catchment scale

NASA Astrophysics Data System (ADS)

Willems, Patrick

2013-04-01

A data-based approach is presented to analyse the response behaviour of hydrological models at the catchment scale. The approach starts with a number of sequential time series processing steps, applied to available rainfall, ETo and river flow observation series. These include separation of the high frequency (e.g., hourly, daily) river flow series into subflows, split of the series in nearly independent quick and slow flow hydrograph periods, and the extraction of nearly independent peak and low flows. Quick-, inter- and slow-subflow recession behaviour, sub-responses to rainfall and soil water storage are derived from the time series data. This data-based information on the catchment response behaviour can be applied on the basis of: - Model-structure identification and case-specific construction of lumped conceptual models for gauged catchments; or diagnostic evaluation of existing model structures; - Intercomparison of runoff responses for gauged catchments in a river basin, in order to identify similarity or significant differences between stations or between time periods, and relate these differences to spatial differences or temporal changes in catchment characteristics; - (based on the evaluation of the temporal changes in previous point:) Detection of temporal changes/trends and identification of its causes: climate trends, or land use changes; - Identification of asymptotic properties of the rainfall-runoff behaviour towards extreme peak or low flow conditions (for a given catchment) or towards extreme catchment conditions (for regionalization, ungauged basin prediction purposes); hence evaluating the performance of the model in making extrapolations beyond the range of available stations' data; - (based on the evaluation in previous point:) Evaluation of the usefulness of the model for making extrapolations to more extreme climate conditions projected by for instance climate models. Examples are provided for river basins in Belgium, Ethiopia, Kenya, Ecuador, Bolivia and China. References: Van Steenbergen, N., Willems, P. (2012), 'Method for testing the accuracy of rainfall-runoff models in predicting peak flow changes due to rainfall changes, in a climate changing context', Journal of Hydrology, 414-415, 425-434, doi:10.1016/j.jhydrol.2011.11.017 Mora, D., Willems, P. (2012), 'Decadal oscillations in rainfall and air temperature in the Paute River Basin - Southern Andes of Ecuador', Theoretical and Applied Climatology, 108(1), 267-282, doi:0.1007/s00704-011-0527-4 Taye, M.T., Willems, P. (2011). 'Influence of climate variability on representative QDF predictions of the upper Blue Nile Basin', Journal of Hydrology, 411, 355-365, doi:10.1016/j.jhydrol.2011.10.019 Taye, M.T., Willems, P. (2012). 'Temporal variability of hydro-climatic extremes in the Blue Nile basin', Water Resources Research, 48, W03513, 13p. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Willems, P., De Smedt, F., Batelaan, O. (in press), 'Climate change impact on river flows and catchment hydrology: a comparison of two spatially distributed models', Hydrological Processes; doi: 10.1002/hyp.9480 [in press

The investigation of Martian dune fields using very high resolution photogrammetric measurements and time series analysis

NASA Astrophysics Data System (ADS)

Kim, J.; Park, M.; Baik, H. S.; Choi, Y.

2016-12-01

At the present time, arguments continue regarding the migration speeds of Martian dune fields and their correlation with atmospheric circulation. However, precisely measuring the spatial translation of Martian dunes has rarely conducted only a very few times Therefore, we developed a generic procedure to precisely measure the migration of dune fields with recently introduced 25-cm resolution High Resolution Imaging Science Experimen (HIRISE) employing a high-accuracy photogrammetric processor and sub-pixel image correlator. The processor was designed to trace estimated dune migration, albeit slight, over the Martian surface by 1) the introduction of very high resolution ortho images and stereo analysis based on hierarchical geodetic control for better initial point settings; 2) positioning error removal throughout the sensor model refinement with a non-rigorous bundle block adjustment, which makes possible the co-alignment of all images in a time series; and 3) improved sub-pixel co-registration algorithms using optical flow with a refinement stage conducted on a pyramidal grid processor and a blunder classifier. Moreover, volumetric changes of Martian dunes were additionally traced by means of stereo analysis and photoclinometry. The established algorithms have been tested using high-resolution HIRISE images over a large number of Martian dune fields covering whole Mars Global Dune Database. Migrations over well-known crater dune fields appeared to be almost static for the considerable temporal periods and were weakly correlated with wind directions estimated by the Mars Climate Database (Millour et al. 2015). Only over a few Martian dune fields, such as Kaiser crater, meaningful migration speeds (>1m/year) compared to phtotogrammetric error residual have been measured. Currently a technical improved processor to compensate error residual using time series observation is under developing and expected to produce the long term migration speed over Martian dune fields where constant HIRISE image acquisitions are available. ACKNOWLEDGEMENTS: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under iMars grant agreement Nr. 607379.

Using Monte Carlo Simulation to Prioritize Key Maritime Environmental Impacts of Port Infrastructure

NASA Astrophysics Data System (ADS)

Perez Lespier, L. M.; Long, S.; Shoberg, T.

2016-12-01

This study creates a Monte Carlo simulation model to prioritize key indicators of environmental impacts resulting from maritime port infrastructure. Data inputs are derived from LandSat imagery, government databases, and industry reports to create the simulation. Results are validated using subject matter experts and compared with those returned from time-series regression to determine goodness of fit. The Port of Prince Rupert, Canada is used as the location for the study.

Development of a Genome-Proxy Microarray for Profiling Marine Microbial Communities and its Application to a Time Series in Monterey Bay, California

DTIC Science & Technology

2008-09-01

community representation. 12 survey a complex microbial community. Community DNA or rRNA extracted from a sample may require amplification before...restricted to cultivated clades, since not only do many clades have sufficient database representation due to 16S environmental surveys , but such...well developed for standard and comprehensive surveys . Depending on the population being targeted and the identification method, FCM can be a

Slushie World: An In-Class Access Database Tutorial

ERIC Educational Resources Information Center

Wynn, Donald E., Jr.; Pratt, Renée M. E.

2015-01-01

The Slushie World case study is designed to teach the basics of Microsoft Access and database management over a series of three 75-minute class sessions. Students are asked to build a basic database to track sales and inventory for a small business. Skills to be learned include table creation, data entry and importing, form and report design,…

Library Micro-Computing, Vol. 1. Reprints from the Best of "ONLINE" [and]"DATABASE."

ERIC Educational Resources Information Center

Online, Inc., Weston, CT.

Reprints of 18 articles pertaining to library microcomputing appear in this collection, the first of two volumes on this topic in a series of volumes of reprints from "ONLINE" and "DATABASE" magazines. Edited for information professionals who use electronically distributed databases, these articles address such topics as: (1) an integrated library…

Community Organizing for Database Trial Buy-In by Patrons

ERIC Educational Resources Information Center

Pionke, J. J.

2015-01-01

Database trials do not often garner a lot of feedback. Using community-organizing techniques can not only potentially increase the amount of feedback received but also deepen the relationship between the librarian and his or her constituent group. This is a case study of the use of community-organizing techniques in a series of database trials for…

Single-grain 40Ar-39Ar ages of glauconies: implications for the geologic time scale and global sea level variations

PubMed

Smith; Evensen; York; Odin

1998-03-06

The mineral series glaucony supplies 40% of the absolute-age database for the geologic time scale of the last 250 million years. However, glauconies have long been suspected of giving young potassium-argon ages on bulk samples. Laser-probe argon-argon dating shows that glaucony populations comprise grains with a wide range of ages, suggesting a period of genesis several times longer ( approximately 5 million years) than previously thought. An estimate of the age of their enclosing sediments (and therefore of time scale boundaries) is given by the oldest nonrelict grains in the glaucony populations, whereas the formation times of the younger grains appear to be modulated by global sea level.

Educational and Scientific Applications of the \\itTime Navigator}

NASA Astrophysics Data System (ADS)

Cole, M.; Snow, J. T.; Slatt, R. M.

2001-05-01

Several recent conferences have noted the need to focus on the evolving interface between research and education at all levels of science, mathematics, engineering, and technology education. This interface, which is a distinguishing feature of graduate education in the U.S., is increasingly in demand at the undergraduate and K-12 levels, particularly in the earth sciences. In this talk, we present a new database for earth systems science and will explore applications to K-12 and undergraduate education, as well as the scientific and graduate role. The University of Oklahoma, College of Geosciences is in the process of acquiring the \\itTime Navigator}, a multi-disciplinary, multimedia database, which will form the core asset of the Center for Earth Systems Science. The Center, whose mission is to further the understanding of the dynamic Earth within both the academic and the general public communities, will serve as a portal for research, information, and education for scientists and educators. \\itTime Navigator} was developed over a period of some twenty years by the noted British geoscience author, Ron Redfern, in connection with the recently published, \\itOrigins, the evolution of continents, oceans and life}, the third in a series of books for the educated layperson. Over the years \\itTime Navigator} has evolved into an interactive, multimedia database displaying much of the significant geological, paleontological, climatological, and tectonic events from the latest Proterozoic (750 MYA) through to the present. The focus is mainly on the Western Hemisphere and events associated with the coalescence and breakup of Pangea and the evolution of the earth into its present form. \\itOrigins} will be available as early as Fall 2001 as an interactive electronic book for the general, scientifically-literate public. While electronic books are unlikely to replace traditional print books, the format does allow non-linear exploration of content. We believe that the electronic version of \\itOrigins} can be a demonstration project for delivering multimedia content to a variety of audiences. In the first half of this presentation, we give a brief overview of \\itTime Navigator}, including a demonstration of the content and sophistication of the database, We will focus on layered, multimedia features, ease of use, and interactivity. The second half of the presentation will feature undergraduate and 9-12 applications which are built around a series of "research projects" emphasizing application of the Scientific Method, analyzing scientific data, and how scientists achieve consensus on theories.

The Massachusetts Sustainable-Yield Estimator: A decision-support tool to assess water availability at ungaged stream locations in Massachusetts

USGS Publications Warehouse

Archfield, Stacey A.; Vogel, Richard M.; Steeves, Peter A.; Brandt, Sara L.; Weiskel, Peter K.; Garabedian, Stephen P.

2010-01-01

Federal, State and local water-resource managers require a variety of data and modeling tools to better understand water resources. The U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, has developed a statewide, interactive decision-support tool to meet this need. The decision-support tool, referred to as the Massachusetts Sustainable-Yield Estimator (MA SYE) provides screening-level estimates of the sustainable yield of a basin, defined as the difference between the unregulated streamflow and some user-specified quantity of water that must remain in the stream to support such functions as recreational activities or aquatic habitat. The MA SYE tool was designed, in part, because the quantity of surface water available in a basin is a time-varying quantity subject to competing demands for water. To compute sustainable yield, the MA SYE tool estimates a daily time series of unregulated, daily mean streamflow for a 44-year period of record spanning October 1, 1960, through September 30, 2004. Selected streamflow quantiles from an unregulated, daily flow-duration curve are estimated by solving six regression equations that are a function of physical and climate basin characteristics at an ungaged site on a stream of interest. Streamflow is then interpolated between the estimated quantiles to obtain a continuous daily flow-duration curve. A time series of unregulated daily streamflow subsequently is created by transferring the timing of the daily streamflow at a reference streamgage to the ungaged site by equating exceedence probabilities of contemporaneous flow at the two locations. One of 66 reference streamgages is selected by kriging, a geostatistical method, which is used to map the spatial relation among correlations between the time series of the logarithm of daily streamflows at each reference streamgage and the ungaged site. Estimated unregulated, daily mean streamflows show good agreement with observed unregulated, daily mean streamflow at 18 streamgages located across southern New England. Nash-Sutcliffe efficiency goodness-of-fit values are between 0.69 and 0.98, and percent root-mean-square-error values are between 19 and 283 percent. The MA SYE tool provides an estimate of streamflow adjusted for current (2000-04) water withdrawals and discharges using a spatially referenced database of permitted groundwater and surface-water withdrawal and discharge volumes. For a user-selected basin, the database is queried to obtain the locations of water withdrawal or discharge volumes within the basin. Groundwater and surface-water withdrawals and discharges are subtracted and added, respectively, from the unregulated, daily streamflow at an ungaged site to obtain a streamflow time series that includes the effects of these withdrawals and discharges. Users also have the option of applying an analytical solution to the time-varying, groundwater withdrawal and discharge volumes that take into account the effects of the aquifer properties on the timing and magnitude of streamflow alteration. For the MA SYE tool, it is assumed that groundwater and surface-water divides are coincident. For areas of southeastern Massachusetts and Cape Cod where this assumption is known to be violated, groundwater-flow models are used to estimate average monthly streamflows at fixed locations. There are several limitations to the quality and quantity of the spatially referenced database of groundwater and surface-water withdrawals and discharges. The adjusted streamflow values do not account for the effects on streamflow of climate change, septic-system discharge, impervious area, non-public water-supply withdrawals less than 100,000 gallons per day, and impounded surface-water bodies.

Annual Corn Yield Estimation through Multi-temporal MODIS Data

NASA Astrophysics Data System (ADS)

Shao, Y.; Zheng, B.; Campbell, J. B.

2013-12-01

This research employed 13 years of the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate annual corn yield for the Midwest of the United States. The overall objective of this study was to examine if annual corn yield could be accurately predicted using MODIS time-series NDVI (Normalized Difference Vegetation Index) and ancillary data such monthly precipitation and temperature. MODIS-NDVI 16-Day composite images were acquired from the USGS EROS Data Center for calendar years 2000 to 2012. For the same time-period, county level corn yield statistics were obtained from the National Agricultural Statistics Service (NASS). The monthly precipitation and temperature measures were derived from Precipitation-Elevation Regressions on Independent Slopes Model (PRISM) climate data. A cropland mask was derived using 2006 National Land Cover Database. For each county and within the cropland mask, the MODIS-NDVI time-series data and PRISM climate data were spatially averaged, at their respective time steps. We developed a random forest predictive model with the MODIS-NDVI and climate data as predictors and corn yield as response. To assess the model accuracy, we used twelve years of data as training and the remaining year as hold-out testing set. The training and testing procedures were repeated 13 times. The R2 ranged from 0.72 to 0.83 for testing years. It was also found that the inclusion of climate data did not improve the model predictive performance. MODIS-NDVI time-series data alone might provide sufficient information for county level corn yield prediction.

A geo-spatial data management system for potentially active volcanoes—GEOWARN project

NASA Astrophysics Data System (ADS)

Gogu, Radu C.; Dietrich, Volker J.; Jenny, Bernhard; Schwandner, Florian M.; Hurni, Lorenz

2006-02-01

Integrated studies of active volcanic systems for the purpose of long-term monitoring and forecast and short-term eruption prediction require large numbers of data-sets from various disciplines. A modern database concept has been developed for managing and analyzing multi-disciplinary volcanological data-sets. The GEOWARN project (choosing the "Kos-Yali-Nisyros-Tilos volcanic field, Greece" and the "Campi Flegrei, Italy" as test sites) is oriented toward potentially active volcanoes situated in regions of high geodynamic unrest. This article describes the volcanological database of the spatial and temporal data acquired within the GEOWARN project. As a first step, a spatial database embedded in a Geographic Information System (GIS) environment was created. Digital data of different spatial resolution, and time-series data collected at different intervals or periods, were unified in a common, four-dimensional representation of space and time. The database scheme comprises various information layers containing geographic data (e.g. seafloor and land digital elevation model, satellite imagery, anthropogenic structures, land-use), geophysical data (e.g. from active and passive seismicity, gravity, tomography, SAR interferometry, thermal imagery, differential GPS), geological data (e.g. lithology, structural geology, oceanography), and geochemical data (e.g. from hydrothermal fluid chemistry and diffuse degassing features). As a second step based on the presented database, spatial data analysis has been performed using custom-programmed interfaces that execute query scripts resulting in a graphical visualization of data. These query tools were designed and compiled following scenarios of known "behavior" patterns of dormant volcanoes and first candidate signs of potential unrest. The spatial database and query approach is intended to facilitate scientific research on volcanic processes and phenomena, and volcanic surveillance.

Preliminary Results on Design and Implementation of a Solar Radiation Monitoring System

PubMed Central

Balan, Mugur C.; Damian, Mihai; Jäntschi, Lorentz

2008-01-01

The paper presents a solar radiation monitoring system, using two scientific pyranometers and an on-line computer home-made data acquisition system. The first pyranometer measures the global solar radiation and the other one, which is shaded, measure the diffuse radiation. The values of total and diffuse solar radiation are continuously stored into a database on a server. Original software was created for data acquisition and interrogation of the created system. The server application acquires the data from pyranometers and stores it into a database with a baud rate of one record at 50 seconds. The client-server application queries the database and provides descriptive statistics. A web interface allow to any user to define the including criteria and to obtain the results. In terms of results, the system is able to provide direct, diffuse and total radiation intensities as time series. Our client-server application computes also derivate heats. The ability of the system to evaluate the local solar energy potential is highlighted. PMID:27879746

Building a Massive Volcano Archive and the Development of a Tool for the Science Community

NASA Technical Reports Server (NTRS)

Linick, Justin

2012-01-01

The Jet Propulsion Laboratory has traditionally housed one of the world's largest databases of volcanic satellite imagery, the ASTER Volcano Archive (10Tb), making these data accessible online for public and scientific use. However, a series of changes in how satellite imagery is housed by the Earth Observing System (EOS) Data Information System has meant that JPL has been unable to systematically maintain its database for the last several years. We have provided a fast, transparent, machine-to-machine client that has updated JPL's database and will keep it current in near real-time. The development of this client has also given us the capability to retrieve any data provided by NASA's Earth Observing System Clearinghouse (ECHO) that covers a volcanic event reported by U.S. Air Force Weather Agency (AFWA). We will also provide a publicly available tool that interfaces with ECHO that can provide functionality not available in any of ECHO's Earth science discovery tools.

Distributing Variable Star Data to the Virtual Observatory

NASA Astrophysics Data System (ADS)

Kinne, Richard C.; Templeton, M. R.; Henden, A. A.; Zografou, P.; Harbo, P.; Evans, J.; Rots, A. H.; LAZIO, J.

2013-01-01

Effective distribution of data is a core element of effective astronomy today. The AAVSO is the home of several different unique databases. The AAVSO International Database (AID) contains over a century of photometric and time-series data on thousands of individual variable stars comprising over 22 million observations. The AAVSO Photometric All-Sky Survey (APASS) is a new photometric catalog containing calibrated photometry in Johnson B, V and Sloan g', r' and i' filters for stars with magnitudes of 10 < V < 17. The AAVSO is partnering with researchers and technologists at the Virtual Astronomical Observatory (VAO) to solve the data distribution problem for these datasets by making them available via various VO tools. We give specific examples of how these data can be accessed through Virtual Observatory (VO) toolsets and utilized for astronomical research.

Using kittens to unlock photo-sharing website datasets for environmental applications

NASA Astrophysics Data System (ADS)

Gascoin, Simon

2016-04-01

Mining photo-sharing websites is a promising approach to complement in situ and satellite observations of the environment, however a challenge is to deal with the large degree of noise inherent to online social datasets. Here I explored the value of the Flickr image hosting website database to monitor the snow cover in the Pyrenees. Using the Flickr application programming interface (API) I queried all the public images metadata tagged at least with one of the following words: "snow", "neige", "nieve", "neu" (snow in French, Spanish and Catalan languages). The search was limited to the geo-tagged pictures taken in the Pyrenees area. However, the number of public pictures available in the Flickr database for a given time interval depends on several factors, including the Flickr website popularity and the development of digital photography. Thus, I also searched for all Flickr images tagged with "chat", "gat" or "gato" (cat in French, Spanish and Catalan languages). The tag "cat" was not considered in order to exclude the results from North America where Flickr got popular earlier than in Europe. The number of "cat" images per month was used to fit a model of the number of images uploaded in Flickr with time. This model was used to remove this trend in the numbers of snow-tagged photographs. The resulting time series was compared to a time series of the snow cover area derived from the MODIS satellite over the same region. Both datasets are well correlated; in particular they exhibit the same seasonal evolution, although the inter-annual variabilities are less similar. I will also discuss which other factors may explain the main discrepancies in order to further decrease the noise in the Flickr dataset.

Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC): Towards a New Adjusted Radiosonde Dataset

NASA Astrophysics Data System (ADS)

Free, M. P.; Angell, J. K.; Durre, I.; Klein, S.; Lanzante, J.; Lawrimore, J.; Peterson, T.; Seidel, D.

2002-05-01

The objective of NOAA's RATPAC project is to develop climate-quality global, hemispheric and zonal upper-air temperature time series from the NCDC radiosonde database. Lanzante, Klein and Seidel (LKS) have produced an 87-station adjusted radiosonde dataset using a multifactor expert decision approach. Our goal is to extend this dataset spatially and temporally and to provide a method to update it routinely at NCDC. Since the LKS adjustment method is too labor-intensive for these purposes, we are investigating a first-difference method (Peterson et al., 1998) and an automated version of the LKS method. The first difference method (FD) can be used to combine large numbers of time series into spatial means, but also introduces a random error in the resulting large-scale averages. If the portions of the time series with suspect continuity are withheld from the calculations, it has the potential to reconstruct the real variability without the effects of the discontinuities. However, tests of FD on unadjusted radiosonde data and on reanalysis temperature data suggest that it must be used with caution when the number of stations is low and the number of data gaps is high. Because of these problems with the first difference approach, we are also considering an automated version of the LKS adjustment method using statistical change points, day-night temperature difference series, relationships between changes in adjacent atmospheric levels, and station histories to identify inhomogeneities in the temperature data.

Coastal Change Processes Project data report for observations near Fire Island, New York, January to April 2012

USGS Publications Warehouse

Armstrong, Brandy N.; Warner, John C.; List, Jeffrey H.; Martini, Marinna A.; Montgomery, Ellyn T.; Voulgaris, George; Traykovski, Peter A.

2015-01-01

An oceanographic field study during January through April 2012 investigated processes that control the sediment-transport dynamics near Fire Island, New York. This report describes the project background, field program, instrumentation configuration, and locations of the sensors deploymed. The data collected and supporting meteorological observations are presented as time series plots for data visualization. Additionally, individual, links to the database containing digital data files are available as part of this report.

Coastal Change Processes Project data report for oceanographic observations near Fire Island, New York, February through May 2014

USGS Publications Warehouse

Armstrong, Brandy N.; Warner, John C.; List, Jeffrey H.; Martini, Marinna A.; Montgomery, Ellyn T.; Traykovski, Peter A.; Voulgaris, George

2015-01-01

An oceanographic field study during February through May 2014 investigated processes that control the sediment-transport dynamics along the western part of Fire Island, New York. This report describes the project background, field program, instrumentation configuration, and locations of the sensors deployed. The data collected, including meteorological observations, are presented as time-series plots for data visualization. Additionally, individual links to the database containing digital data files are available as part of this report.

Automated Data Aggregation for Time-Series Analysis: Study Case on Anaesthesia Data Warehouse.

PubMed

Lamer, Antoine; Jeanne, Mathieu; Ficheur, Grégoire; Marcilly, Romaric

2016-01-01

Data stored in operational databases are not reusable directly. Aggregation modules are necessary to facilitate secondary use. They decrease volume of data while increasing the number of available information. In this paper, we present four automated engines of aggregation, integrated into an anaesthesia data warehouse. Four instances of clinical questions illustrate the use of those engines for various improvements of quality of care: duration of procedure, drug administration, assessment of hypotension and its related treatment.

Analysis of Rhythms in Experimental Signals

NASA Astrophysics Data System (ADS)

Desherevskii, A. V.; Zhuravlev, V. I.; Nikolsky, A. N.; Sidorin, A. Ya.

2017-12-01

We compare algorithms designed to extract quasiperiodic components of a signal and estimate the amplitude, phase, stability, and other characteristics of a rhythm in a sliding window in the presence of data gaps. Each algorithm relies on its own rhythm model; therefore, it is necessary to use different algorithms depending on the research objectives. The described set of algorithms and methods is implemented in the WinABD software package, which includes a time-series database management system, a powerful research complex, and an interactive data-visualization environment.

Interdisciplinary Investigations in Support of Project DI-MOD

NASA Technical Reports Server (NTRS)

Starks, Scott A. (Principal Investigator)

1996-01-01

Various concepts from time series analysis are used as the basis for the development of algorithms to assist in the analysis and interpretation of remote sensed imagery. An approach to trend detection that is based upon the fractal analysis of power spectrum estimates is presented. Additionally, research was conducted toward the development of a software architecture to support processing tasks associated with databases housing a variety of data. An algorithmic approach which provides for the automation of the state monitoring process is presented.

Using Amazon Web Services (AWS) to enable real-time, remote sensing of biophysical and anthropogenic conditions in green infrastructure systems in Philadelphia, an ultra-urban application of the Internet of Things (IoT)

NASA Astrophysics Data System (ADS)

Montalto, F. A.; Yu, Z.; Soldner, K.; Israel, A.; Fritch, M.; Kim, Y.; White, S.

2017-12-01

Urban stormwater utilities are increasingly using decentralized "green" infrastructure (GI) systems to capture stormwater and achieve compliance with regulations. Because environmental conditions, and design varies by GSI facility, monitoring of GSI systems under a range of conditions is essential. Conventional monitoring efforts can be costly because in-field data logging requires intense data transmission rates. The Internet of Things (IoT) can be used to more cost-effectively collect, store, and publish GSI monitoring data. Using 3G mobile networks, a cloud-based database was built on an Amazon Web Services (AWS) EC2 virtual machine to store and publish data collected with environmental sensors deployed in the field. This database can store multi-dimensional time series data, as well as photos and other observations logged by citizen scientists through a public engagement mobile app through a new Application Programming Interface (API). Also on the AWS EC2 virtual machine, a real-time QAQC flagging algorithm was developed to validate the sensor data streams.

Modern representation of databases on the example of the Catalog of Solar Proton Events in the 23rd Cycle of Solar Activity

NASA Astrophysics Data System (ADS)

Ishkov, V. N.; Zabarinskaya, L. P.; Sergeeva, N. A.

2017-11-01

The development of studies of solar sources and their effects on the state of the near-Earth space required systematization of the corresponding information in the form of databases and catalogs for the entire time of observation of any geoeffective phenomenon that includes, if possible at the time of creation, all of the characteristics of the phenomena themselves and the sources of these phenomena on the Sun. A uniform presentation of information in the form of a series of similar catalogs that cover long time intervals is of particular importance. The large amount of information collected in such catalogs makes it necessary to use modern methods of its organization and presentation that allow a transition between individual parts of the catalog and a quick search for necessary events and their characteristics, which is implemented in the presented Catalog of Solar Proton Events in the 23rd Cycle of Solar Activity of the sequence of catalogs (six separate issues) that cover the period from 1970 to 2009 (20th-23rd solar cycles).

Hospital Visits Due to Domestic Violence from 1994 to 2011 in the Solomon Islands: A Descriptive Case Series

PubMed Central

Negin, Joel; Houasia, Patrick; Munamua, Alex B; Leon, David P; Rimon, Mia; Martiniuk, Alexandra LC

2014-01-01

The Solomon Islands has one of the highest rates of domestic violence in the world. This paper is a descriptive case series of all cases of domestic violence presenting to the Solomon Islands National Referral Hospital (NRH) over 18 years. Data were routinely collected from a database of all patients who were treated by NRH general surgery and orthopedic clinicians between 1994 and 2011, inclusive. The total number of cases in the injury database as a result of domestic violence was 387. The average number of cases in the database per year from 1994 to 2011 was 20. There were 6% more female patients (205 of 387; 53%) than male (182 of 387; 47%). Of the cases in which the perpetrator of the violence against a female patient was specified (111 of 205 female cases), 74% (82 of 111) were the patient's husband. Only 5% (5 of 111) of cases in females were inflicted by another female. This analysis provides the best available information on domestic violence cases requiring a visit to a tertiary hospital in a Pacific Island in the specified time period and is undoubtedly an under-estimate of the total cases of domestic violence. Preventing and treating domestic violence in the Solomon Islands and in the Pacific is an important challenge and there is a significant role for secondary and tertiary health services in screening for and preventing domestic violence. PMID:25285254

Results of Russian geomagnetic observatories in the 19th century: magnetic activity, 1841-1862

NASA Astrophysics Data System (ADS)

Nevanlinna, H.; Häkkinen, L.

2010-04-01

Hourly (spot readings) magnetic data (H- and D-components) were digitized from Russian yearbook tables for the years 1850-1862 from four observatories. The pdf pictures for digitization were taken by a normal digital camera. The database obtained consists of about 900 000 single data points. The time series of hourly magnetic values reveal slow secular variations (declination only) as well as transient and regular geomagnetic variations of external origin. The quality and homogeneity of the data is satisfactory. Daily Ak-indices were calculated using the index algorithm that has been earlier applied to 19th century data from Helsinki (Finland) as well as modern magnetic observatory recordings. The activity index series derived from the Russian data is consistent with earlier activity index series for 1850-1862. The digitized index data series derived in this study was extended back to 1841 by including magnetic C9 activity index data available from a Russian observatory (St. Petersburg). Magnetic data rescued here is well suitable for various reconstructions for studies of the long-term variation of the space weather in the 19th century.

Integrating forensic information in a crime intelligence database.

PubMed

Rossy, Quentin; Ioset, Sylvain; Dessimoz, Damien; Ribaux, Olivier

2013-07-10

Since 2008, intelligence units of six states of the western part of Switzerland have been sharing a common database for the analysis of high volume crimes. On a daily basis, events reported to the police are analysed, filtered and classified to detect crime repetitions and interpret the crime environment. Several forensic outcomes are integrated in the system such as matches of traces with persons, and links between scenes detected by the comparison of forensic case data. Systematic procedures have been settled to integrate links assumed mainly through DNA profiles, shoemarks patterns and images. A statistical outlook on a retrospective dataset of series from 2009 to 2011 of the database informs for instance on the number of repetition detected or confirmed and increased by forensic case data. Time needed to obtain forensic intelligence in regard with the type of marks treated, is seen as a critical issue. Furthermore, the underlying integration process of forensic intelligence into the crime intelligence database raised several difficulties in regards of the acquisition of data and the models used in the forensic databases. Solutions found and adopted operational procedures are described and discussed. This process form the basis to many other researches aimed at developing forensic intelligence models. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

WEB-GIS Decision Support System for CO2 storage

NASA Astrophysics Data System (ADS)

Gaitanaru, Dragos; Leonard, Anghel; Radu Gogu, Constantin; Le Guen, Yvi; Scradeanu, Daniel; Pagnejer, Mihaela

2013-04-01

Environmental decision support systems (DSS) paradigm evolves and changes as more knowledge and technology become available to the environmental community. Geographic Information Systems (GIS) can be used to extract, assess and disseminate some types of information, which are otherwise difficult to access by traditional methods. In the same time, with the help of the Internet and accompanying tools, creating and publishing online interactive maps has become easier and rich with options. The Decision Support System (MDSS) developed for the MUSTANG (A MUltiple Space and Time scale Approach for the quaNtification of deep saline formations for CO2 storaGe) project is a user friendly web based application that uses the GIS capabilities. MDSS can be exploited by the experts for CO2 injection and storage in deep saline aquifers. The main objective of the MDSS is to help the experts to take decisions based large structured types of data and information. In order to achieve this objective the MDSS has a geospatial objected-orientated database structure for a wide variety of data and information. The entire application is based on several principles leading to a series of capabilities and specific characteristics: (i) Open-Source - the entire platform (MDSS) is based on open-source technologies - (1) database engine, (2) application server, (3) geospatial server, (4) user interfaces, (5) add-ons, etc. (ii) Multiple database connections - MDSS is capable to connect to different databases that are located on different server machines. (iii)Desktop user experience - MDSS architecture and design follows the structure of a desktop software. (iv)Communication - the server side and the desktop are bound together by series functions that allows the user to upload, use, modify and download data within the application. The architecture of the system involves one database and a modular application composed by: (1) a visualization module, (2) an analysis module, (3) a guidelines module, and (4) a risk assessment module. The Database component is build by using the PostgreSQL and PostGIS open source technology. The visualization module allows the user to view data of CO2 injection sites in different ways: (1) geospatial visualization, (2) table view, (3) 3D visualization. The analysis module will allow the user to perform certain analysis like Injectivity, Containment and Capacity analysis. The Risk Assessment module focus on the site risk matrix approach. The Guidelines module contains the methodologies of CO2 injection and storage into deep saline aquifers guidelines.

Missing "Links" in Bioinformatics Education: Expanding Students' Conceptions of Bioinformatics Using a Biodiversity Database of Living and Fossil Reef Corals

ERIC Educational Resources Information Center

Nehm, Ross H.; Budd, Ann F.

2006-01-01

NMITA is a reef coral biodiversity database that we use to introduce students to the expansive realm of bioinformatics beyond genetics. We introduce a series of lessons that have students use this database, thereby accessing real data that can be used to test hypotheses about biodiversity and evolution while targeting the "National Science …

The Starlite Project

DTIC Science & Technology

1990-09-01

conflicts. The current prototyping tool also provides a multiversion data object control mechanism. From a series of experiments, we found that the...performance of a multiversion distributed database system is quite sensitive to the size of read-sets and write-sets of transactions. A multiversion database...510-512. (18) Son, S. H. and N. Haghighi, "Performance Evaluation of Multiversion Database Systems," Sixth IEEE International Conference on Data

Cassini Tour Atlas Automated Generation

NASA Technical Reports Server (NTRS)

Grazier, Kevin R.; Roumeliotis, Chris; Lange, Robert D.

2011-01-01

During the Cassini spacecraft s cruise phase and nominal mission, the Cassini Science Planning Team developed and maintained an online database of geometric and timing information called the Cassini Tour Atlas. The Tour Atlas consisted of several hundreds of megabytes of EVENTS mission planning software outputs, tables, plots, and images used by mission scientists for observation planning. Each time the nominal mission trajectory was altered or tweaked, a new Tour Atlas had to be regenerated manually. In the early phases of Cassini s Equinox Mission planning, an a priori estimate suggested that mission tour designers would develop approximately 30 candidate tours within a short period of time. So that Cassini scientists could properly analyze the science opportunities in each candidate tour quickly and thoroughly so that the optimal series of orbits for science return could be selected, a separate Tour Atlas was required for each trajectory. The task of manually generating the number of trajectory analyses in the allotted time would have been impossible, so the entire task was automated using code written in five different programming languages. This software automates the generation of the Cassini Tour Atlas database. It performs with one UNIX command what previously took a day or two of human labor.

The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts

PubMed Central

Hudson, Lawrence N; Newbold, Tim; Contu, Sara; Hill, Samantha L L; Lysenko, Igor; De Palma, Adriana; Phillips, Helen R P; Senior, Rebecca A; Bennett, Dominic J; Booth, Hollie; Choimes, Argyrios; Correia, David L P; Day, Julie; Echeverría-Londoño, Susy; Garon, Morgan; Harrison, Michelle L K; Ingram, Daniel J; Jung, Martin; Kemp, Victoria; Kirkpatrick, Lucinda; Martin, Callum D; Pan, Yuan; White, Hannah J; Aben, Job; Abrahamczyk, Stefan; Adum, Gilbert B; Aguilar-Barquero, Virginia; Aizen, Marcelo A; Ancrenaz, Marc; Arbeláez-Cortés, Enrique; Armbrecht, Inge; Azhar, Badrul; Azpiroz, Adrián B; Baeten, Lander; Báldi, András; Banks, John E; Barlow, Jos; Batáry, Péter; Bates, Adam J; Bayne, Erin M; Beja, Pedro; Berg, Åke; Berry, Nicholas J; Bicknell, Jake E; Bihn, Jochen H; Böhning-Gaese, Katrin; Boekhout, Teun; Boutin, Céline; Bouyer, Jérémy; Brearley, Francis Q; Brito, Isabel; Brunet, Jörg; Buczkowski, Grzegorz; Buscardo, Erika; Cabra-García, Jimmy; Calviño-Cancela, María; Cameron, Sydney A; Cancello, Eliana M; Carrijo, Tiago F; Carvalho, Anelena L; Castro, Helena; Castro-Luna, Alejandro A; Cerda, Rolando; Cerezo, Alexis; Chauvat, Matthieu; Clarke, Frank M; Cleary, Daniel F R; Connop, Stuart P; D'Aniello, Biagio; da Silva, Pedro Giovâni; Darvill, Ben; Dauber, Jens; Dejean, Alain; Diekötter, Tim; Dominguez-Haydar, Yamileth; Dormann, Carsten F; Dumont, Bertrand; Dures, Simon G; Dynesius, Mats; Edenius, Lars; Elek, Zoltán; Entling, Martin H; Farwig, Nina; Fayle, Tom M; Felicioli, Antonio; Felton, Annika M; Ficetola, Gentile F; Filgueiras, Bruno K C; Fonte, Steven J; Fraser, Lauchlan H; Fukuda, Daisuke; Furlani, Dario; Ganzhorn, Jörg U; Garden, Jenni G; Gheler-Costa, Carla; Giordani, Paolo; Giordano, Simonetta; Gottschalk, Marco S; Goulson, Dave; Gove, Aaron D; Grogan, James; Hanley, Mick E; Hanson, Thor; Hashim, Nor R; Hawes, Joseph E; Hébert, Christian; Helden, Alvin J; Henden, John-André; Hernández, Lionel; Herzog, Felix; Higuera-Diaz, Diego; Hilje, Branko; Horgan, Finbarr G; Horváth, Roland; Hylander, Kristoffer; Isaacs-Cubides, Paola; Ishitani, Masahiro; Jacobs, Carmen T; Jaramillo, Víctor J; Jauker, Birgit; Jonsell, Mats; Jung, Thomas S; Kapoor, Vena; Kati, Vassiliki; Katovai, Eric; Kessler, Michael; Knop, Eva; Kolb, Annette; Kőrösi, Ádám; Lachat, Thibault; Lantschner, Victoria; Le Féon, Violette; LeBuhn, Gretchen; Légaré, Jean-Philippe; Letcher, Susan G; Littlewood, Nick A; López-Quintero, Carlos A; Louhaichi, Mounir; Lövei, Gabor L; Lucas-Borja, Manuel Esteban; Luja, Victor H; Maeto, Kaoru; Magura, Tibor; Mallari, Neil Aldrin; Marin-Spiotta, Erika; Marshall, E J P; Martínez, Eliana; Mayfield, Margaret M; Mikusinski, Grzegorz; Milder, Jeffrey C; Miller, James R; Morales, Carolina L; Muchane, Mary N; Muchane, Muchai; Naidoo, Robin; Nakamura, Akihiro; Naoe, Shoji; Nates-Parra, Guiomar; Navarrete Gutierrez, Dario A; Neuschulz, Eike L; Noreika, Norbertas; Norfolk, Olivia; Noriega, Jorge Ari; Nöske, Nicole M; O'Dea, Niall; Oduro, William; Ofori-Boateng, Caleb; Oke, Chris O; Osgathorpe, Lynne M; Paritsis, Juan; Parra-H, Alejandro; Pelegrin, Nicolás; Peres, Carlos A; Persson, Anna S; Petanidou, Theodora; Phalan, Ben; Philips, T Keith; Poveda, Katja; Power, Eileen F; Presley, Steven J; Proença, Vânia; Quaranta, Marino; Quintero, Carolina; Redpath-Downing, Nicola A; Reid, J Leighton; Reis, Yana T; Ribeiro, Danilo B; Richardson, Barbara A; Richardson, Michael J; Robles, Carolina A; Römbke, Jörg; Romero-Duque, Luz Piedad; Rosselli, Loreta; Rossiter, Stephen J; Roulston, T'ai H; Rousseau, Laurent; Sadler, Jonathan P; Sáfián, Szabolcs; Saldaña-Vázquez, Romeo A; Samnegård, Ulrika; Schüepp, Christof; Schweiger, Oliver; Sedlock, Jodi L; Shahabuddin, Ghazala; Sheil, Douglas; Silva, Fernando A B; Slade, Eleanor M; Smith-Pardo, Allan H; Sodhi, Navjot S; Somarriba, Eduardo J; Sosa, Ramón A; Stout, Jane C; Struebig, Matthew J; Sung, Yik-Hei; Threlfall, Caragh G; Tonietto, Rebecca; Tóthmérész, Béla; Tscharntke, Teja; Turner, Edgar C; Tylianakis, Jason M; Vanbergen, Adam J; Vassilev, Kiril; Verboven, Hans A F; Vergara, Carlos H; Vergara, Pablo M; Verhulst, Jort; Walker, Tony R; Wang, Yanping; Watling, James I; Wells, Konstans; Williams, Christopher D; Willig, Michael R; Woinarski, John C Z; Wolf, Jan H D; Woodcock, Ben A; Yu, Douglas W; Zaitsev, Andrey S; Collen, Ben; Ewers, Rob M; Mace, Georgina M; Purves, Drew W; Scharlemann, Jörn P W; Purvis, Andy

2014-01-01

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – http://www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015. PMID:25558364

The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts.

PubMed

Hudson, Lawrence N; Newbold, Tim; Contu, Sara; Hill, Samantha L L; Lysenko, Igor; De Palma, Adriana; Phillips, Helen R P; Senior, Rebecca A; Bennett, Dominic J; Booth, Hollie; Choimes, Argyrios; Correia, David L P; Day, Julie; Echeverría-Londoño, Susy; Garon, Morgan; Harrison, Michelle L K; Ingram, Daniel J; Jung, Martin; Kemp, Victoria; Kirkpatrick, Lucinda; Martin, Callum D; Pan, Yuan; White, Hannah J; Aben, Job; Abrahamczyk, Stefan; Adum, Gilbert B; Aguilar-Barquero, Virginia; Aizen, Marcelo A; Ancrenaz, Marc; Arbeláez-Cortés, Enrique; Armbrecht, Inge; Azhar, Badrul; Azpiroz, Adrián B; Baeten, Lander; Báldi, András; Banks, John E; Barlow, Jos; Batáry, Péter; Bates, Adam J; Bayne, Erin M; Beja, Pedro; Berg, Åke; Berry, Nicholas J; Bicknell, Jake E; Bihn, Jochen H; Böhning-Gaese, Katrin; Boekhout, Teun; Boutin, Céline; Bouyer, Jérémy; Brearley, Francis Q; Brito, Isabel; Brunet, Jörg; Buczkowski, Grzegorz; Buscardo, Erika; Cabra-García, Jimmy; Calviño-Cancela, María; Cameron, Sydney A; Cancello, Eliana M; Carrijo, Tiago F; Carvalho, Anelena L; Castro, Helena; Castro-Luna, Alejandro A; Cerda, Rolando; Cerezo, Alexis; Chauvat, Matthieu; Clarke, Frank M; Cleary, Daniel F R; Connop, Stuart P; D'Aniello, Biagio; da Silva, Pedro Giovâni; Darvill, Ben; Dauber, Jens; Dejean, Alain; Diekötter, Tim; Dominguez-Haydar, Yamileth; Dormann, Carsten F; Dumont, Bertrand; Dures, Simon G; Dynesius, Mats; Edenius, Lars; Elek, Zoltán; Entling, Martin H; Farwig, Nina; Fayle, Tom M; Felicioli, Antonio; Felton, Annika M; Ficetola, Gentile F; Filgueiras, Bruno K C; Fonte, Steven J; Fraser, Lauchlan H; Fukuda, Daisuke; Furlani, Dario; Ganzhorn, Jörg U; Garden, Jenni G; Gheler-Costa, Carla; Giordani, Paolo; Giordano, Simonetta; Gottschalk, Marco S; Goulson, Dave; Gove, Aaron D; Grogan, James; Hanley, Mick E; Hanson, Thor; Hashim, Nor R; Hawes, Joseph E; Hébert, Christian; Helden, Alvin J; Henden, John-André; Hernández, Lionel; Herzog, Felix; Higuera-Diaz, Diego; Hilje, Branko; Horgan, Finbarr G; Horváth, Roland; Hylander, Kristoffer; Isaacs-Cubides, Paola; Ishitani, Masahiro; Jacobs, Carmen T; Jaramillo, Víctor J; Jauker, Birgit; Jonsell, Mats; Jung, Thomas S; Kapoor, Vena; Kati, Vassiliki; Katovai, Eric; Kessler, Michael; Knop, Eva; Kolb, Annette; Kőrösi, Ádám; Lachat, Thibault; Lantschner, Victoria; Le Féon, Violette; LeBuhn, Gretchen; Légaré, Jean-Philippe; Letcher, Susan G; Littlewood, Nick A; López-Quintero, Carlos A; Louhaichi, Mounir; Lövei, Gabor L; Lucas-Borja, Manuel Esteban; Luja, Victor H; Maeto, Kaoru; Magura, Tibor; Mallari, Neil Aldrin; Marin-Spiotta, Erika; Marshall, E J P; Martínez, Eliana; Mayfield, Margaret M; Mikusinski, Grzegorz; Milder, Jeffrey C; Miller, James R; Morales, Carolina L; Muchane, Mary N; Muchane, Muchai; Naidoo, Robin; Nakamura, Akihiro; Naoe, Shoji; Nates-Parra, Guiomar; Navarrete Gutierrez, Dario A; Neuschulz, Eike L; Noreika, Norbertas; Norfolk, Olivia; Noriega, Jorge Ari; Nöske, Nicole M; O'Dea, Niall; Oduro, William; Ofori-Boateng, Caleb; Oke, Chris O; Osgathorpe, Lynne M; Paritsis, Juan; Parra-H, Alejandro; Pelegrin, Nicolás; Peres, Carlos A; Persson, Anna S; Petanidou, Theodora; Phalan, Ben; Philips, T Keith; Poveda, Katja; Power, Eileen F; Presley, Steven J; Proença, Vânia; Quaranta, Marino; Quintero, Carolina; Redpath-Downing, Nicola A; Reid, J Leighton; Reis, Yana T; Ribeiro, Danilo B; Richardson, Barbara A; Richardson, Michael J; Robles, Carolina A; Römbke, Jörg; Romero-Duque, Luz Piedad; Rosselli, Loreta; Rossiter, Stephen J; Roulston, T'ai H; Rousseau, Laurent; Sadler, Jonathan P; Sáfián, Szabolcs; Saldaña-Vázquez, Romeo A; Samnegård, Ulrika; Schüepp, Christof; Schweiger, Oliver; Sedlock, Jodi L; Shahabuddin, Ghazala; Sheil, Douglas; Silva, Fernando A B; Slade, Eleanor M; Smith-Pardo, Allan H; Sodhi, Navjot S; Somarriba, Eduardo J; Sosa, Ramón A; Stout, Jane C; Struebig, Matthew J; Sung, Yik-Hei; Threlfall, Caragh G; Tonietto, Rebecca; Tóthmérész, Béla; Tscharntke, Teja; Turner, Edgar C; Tylianakis, Jason M; Vanbergen, Adam J; Vassilev, Kiril; Verboven, Hans A F; Vergara, Carlos H; Vergara, Pablo M; Verhulst, Jort; Walker, Tony R; Wang, Yanping; Watling, James I; Wells, Konstans; Williams, Christopher D; Willig, Michael R; Woinarski, John C Z; Wolf, Jan H D; Woodcock, Ben A; Yu, Douglas W; Zaitsev, Andrey S; Collen, Ben; Ewers, Rob M; Mace, Georgina M; Purves, Drew W; Scharlemann, Jörn P W; Purvis, Andy

2014-12-01

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - http://www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.

Optimizing a Query by Transformation and Expansion.

PubMed

Glocker, Katrin; Knurr, Alexander; Dieter, Julia; Dominick, Friederike; Forche, Melanie; Koch, Christian; Pascoe Pérez, Analie; Roth, Benjamin; Ückert, Frank

2017-01-01

In the biomedical sector not only the amount of information produced and uploaded into the web is enormous, but also the number of sources where these data can be found. Clinicians and researchers spend huge amounts of time on trying to access this information and to filter the most important answers to a given question. As the formulation of these queries is crucial, automated query expansion is an effective tool to optimize a query and receive the best possible results. In this paper we introduce the concept of a workflow for an optimization of queries in the medical and biological sector by using a series of tools for expansion and transformation of the query. After the definition of attributes by the user, the query string is compared to previous queries in order to add semantic co-occurring terms to the query. Additionally, the query is enlarged by an inclusion of synonyms. The translation into database specific ontologies ensures the optimal query formulation for the chosen database(s). As this process can be performed in various databases at once, the results are ranked and normalized in order to achieve a comparable list of answers for a question.

Transportation-markings database : traffic control devices. Part I 2, Volume 3, additional studies

DOT National Transportation Integrated Search

1998-01-01

The Database (Part I 1, 2, 3, 4) of transportation-markings: a study in communication monograph series draws together the several varios dimensions of T-M. it shares this drawing togther function with the General Classification (Part H). But, paradox...

Transportation-markings database : aeronautical navigation aids. Part I 4, Volume 3, additional studies

DOT National Transportation Integrated Search

2001-01-01

The Database (Parts I 1, 2, 3, 4 of TRANSPORTATION-MARKINGS: A STUDY IN COMMUNICATION MONOGRAPH SERIES) draws together the several dimensions of T-M. It shares this drawmg together function with the General Classification (Part H). But, paradoxically...

Trends in Total Cloud Amount Over China (1951 - 1994)

DOE Data Explorer

Kaiser, Dale P. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States).

1999-01-01

These total cloud amount time series for China are derived from the work of Kaiser (1998). The cloud data were extracted from a database of 6-hourly weather observations provided by the National Climate Center of the China Meteorological Administration (CMA) to the U.S. Department of Energy's Carbon Dioxide Information Analysis Center (CDIAC) through a bilateral research agreement. Surface-observed (visual) six-hourly observations [0200, 0800, 1400, and 2000 Beijing Time (BT)] of cloud amount (0-10 tenths of sky cover) were available from 196 Chinese stations covering the period 1954-94. Data from 1951-1953 were also available; however, they only included 0800, 1400, and 2000 BT observations.

HYPE: a WFD tool for the identification of significant and sustained upward trends in groundwater time series

NASA Astrophysics Data System (ADS)

Lopez, Benjamin; Croiset, Nolwenn; Laurence, Gourcy

2014-05-01

The Water Framework Directive 2006/11/CE (WFD) on the protection of groundwater against pollution and deterioration asks Member States to identify significant and sustained upward trends in all bodies or groups of bodies of groundwater that are characterised as being at risk in accordance with Annex II to Directive 2000/60/EC. The Directive indicates that the procedure for the identification of significant and sustained upward trends must be based on a statistical method. Moreover, for significant increases of concentrations of pollutants, trend reversals are identified as being necessary. This means to be able to identify significant trend reversals. A specific tool, named HYPE, has been developed in order to help stakeholders working on groundwater trend assessment. The R encoded tool HYPE provides statistical analysis of groundwater time series. It follows several studies on the relevancy of the use of statistical tests on groundwater data series (Lopez et al., 2011) and other case studies on the thematic (Bourgine et al., 2012). It integrates the most powerful and robust statistical tests for hydrogeological applications. HYPE is linked to the French national database on groundwater data (ADES). So monitoring data gathered by the Water Agencies can be directly processed. HYPE has two main modules: - a characterisation module, which allows to visualize time series. HYPE calculates the main statistical characteristics and provides graphical representations; - a trend module, which identifies significant breaks, trends and trend reversals in time series, providing result table and graphical representation (cf figure). Additional modules are also implemented to identify regional and seasonal trends and to sample time series in a relevant way. HYPE has been used successfully in 2012 by the French Water Agencies to satisfy requirements of the WFD, concerning characterization of groundwater bodies' qualitative status and evaluation of the risk of non-achievement of good status. Bourgine B. et al. 2012, Ninth International Geostatistics Congress, Oslo, Norway June 11 - 15. Lopez B. et al. 2011, Final Report BRGM/RP-59515-FR. 166p.

Systematic review of the efficacy of fat grafting and platelet-rich plasma for wound healing.

PubMed

Smith, Oliver J; Kanapathy, Muholan; Khajuria, Ankur; Prokopenko, Max; Hachach-Haram, Nadine; Mann, Haroon; Mosahebi, Ash

2018-05-09

Adipose-derived stem cells found in fat grafts may have significant healing properties. When fat is combined with autologous platelet-rich plasma (PRP), there may be enhanced healing effects due to the pro-angiogenic and anti-inflammatory effects of PRP. This study aimed to evaluate the current evidence on fat grafting in combination with PRP for wound healing to establish the efficacy of this technique. A comprehensive search in the MEDLINE, EMBASE, CENTRAL, Science Citation Index, and Google Scholar databases (to March 2017) was conducted to identify studies on fat grafting and PRP for wound healing. Case series of less than 3 cases and studies only describing harvest technique were excluded. The database identified 571 articles, of which 3 articles that used a combination of fat and PRP for wound healing (1 RCT and 2 case series) were included in this review. A total of 69 wounds in 64 patients were treated with an average wound size of 36.32cm 2 . Of these, 67% of wounds achieved complete healing. When reported, the mean time to healing was 7.5 weeks for those who underwent a single treatment. There were no significant complications in any patients. The combination of fat grafting and PRP may achieve adequate wound healing with relatively quick wound healing time compared with standard wound management options. However, evidence is extremely limited, and further studies are required to evaluate its efficacy for wound healing. © 2018 Medicalhelplines.com Inc and John Wiley & Sons Ltd.

Molecular Modeling and Experimental Investigations of Nonlinear Optical Compounds Monosubstituted Derivatives of Dicyanovinylbenzene

NASA Technical Reports Server (NTRS)

Timofeeva, Tatiana V.; Nesterov, Vladimir N.; Antipin, Mikhail Yu.; Clark, Ronald D.; Sanghadasa, Mohan; Cardelino, Beatriz H.; Moore, Craig E.; Frazier, Donald O.

1999-01-01

A search for potential nonlinear optical compounds was performed using the Cambridge Structure Database and molecular modeling. We investigated a series of monosubstituted derivatives of dicyanovinylbenzene, since the nonlinear optical (NLO) properties of such derivatives (o-methoxy-dicyanovinylbenzene, DIVA) were studied earlier. The molecular geometry of these compounds was investigated with x-ray analysis and discussed along with the results of molecular mechanics and ab initio quantum chemical calculations. The influence of crystal packing on the planarity of the molecules of this series has been revealed. Two new compounds from the series studied, ortho-F and para-Cl-dicyanovinylbenzene, according to powder measurements, were found to be NLO compounds in the crystal state about 10 times more active than urea. The peculiarities of crystal structure formation in the framework of balance between van der Waals and electrostatic interactions have been discussed. The crystal shape of DIVA and two new NLO compounds have been calculated on the basis of the known crystal structure.

The evolution of monitoring system: the INFN-CNAF case study

NASA Astrophysics Data System (ADS)

Bovina, Stefano; Michelotto, Diego

2017-10-01

Over the past two years, the operations at CNAF, the ICT center of the Italian Institute for Nuclear Physics, have undergone significant changes. The adoption of configuration management tools, such as Puppet, and the constant increase of dynamic and cloud infrastructures have led us to investigate a new monitoring approach. The present work deals with the centralization of the monitoring service at CNAF through a scalable and highly configurable monitoring infrastructure. The selection of tools has been made taking into account the following requirements given by users: (I) adaptability to dynamic infrastructures, (II) ease of configuration and maintenance, capability to provide more flexibility, (III) compatibility with existing monitoring system, (IV) re-usability and ease of access to information and data. In the paper, the CNAF monitoring infrastructure and its related components are hereafter described: Sensu as monitoring router, InfluxDB as time series database to store data gathered from sensors, Uchiwa as monitoring dashboard and Grafana as a tool to create dashboards and to visualize time series metrics.

Teaching Three-Dimensional Structural Chemistry Using Crystal Structure Databases. 2. Teaching Units that Utilize an Interactive Web-Accessible Subset of the Cambridge Structural Database

ERIC Educational Resources Information Center

Battle, Gary M.; Allen, Frank H.; Ferrence, Gregory M.

2010-01-01

A series of online interactive teaching units have been developed that illustrate the use of experimentally measured three-dimensional (3D) structures to teach fundamental chemistry concepts. The units integrate a 500-structure subset of the Cambridge Structural Database specially chosen for their pedagogical value. The units span a number of key…

CEBS: a comprehensive annotated database of toxicological data

PubMed Central

Lea, Isabel A.; Gong, Hui; Paleja, Anand; Rashid, Asif; Fostel, Jennifer

2017-01-01

The Chemical Effects in Biological Systems database (CEBS) is a comprehensive and unique toxicology resource that compiles individual and summary animal data from the National Toxicology Program (NTP) testing program and other depositors into a single electronic repository. CEBS has undergone significant updates in recent years and currently contains over 11 000 test articles (exposure agents) and over 8000 studies including all available NTP carcinogenicity, short-term toxicity and genetic toxicity studies. Study data provided to CEBS are manually curated, accessioned and subject to quality assurance review prior to release to ensure high quality. The CEBS database has two main components: data collection and data delivery. To accommodate the breadth of data produced by NTP, the CEBS data collection component is an integrated relational design that allows the flexibility to capture any type of electronic data (to date). The data delivery component of the database comprises a series of dedicated user interface tables containing pre-processed data that support each component of the user interface. The user interface has been updated to include a series of nine Guided Search tools that allow access to NTP summary and conclusion data and larger non-NTP datasets. The CEBS database can be accessed online at http://www.niehs.nih.gov/research/resources/databases/cebs/. PMID:27899660

Organizing research data.

PubMed

Sestoft, Peter

2011-01-01

Research relies on ever larger amounts of data from experiments, automated production equipment, questionnaries, times series such as weather records, and so on. A major task in science is to combine, process and analyse such data to obtain evidence of patterns and correlations.Most research data are on digital form, which in principle ensures easy processing and analysis, easy long-term preservation, and easy reuse in future research, perhaps in entirely unanticipated ways. However, in practice, obstacles such as incompatible or undocumented data formats, poor data quality and lack of familiarity with current technology prevent researchers from making full use of available data.This paper argues that relational databases are excellent tools for veterinary research and animal production; provides a small example to introduce basic database concepts; and points out some concerns that must be addressed when organizing data for research purposes.

Structural Pattern Recognition Techniques for Data Retrieval in Massive Fusion Databases

NASA Astrophysics Data System (ADS)

Vega, J.; Murari, A.; Rattá, G. A.; Castro, P.; Pereira, A.; Portas, A.

2008-03-01

Diagnostics of present day reactor class fusion experiments, like the Joint European Torus (JET), generate thousands of signals (time series and video images) in each discharge. There is a direct correspondence between the physical phenomena taking place in the plasma and the set of structural shapes (patterns) that they form in the signals: bumps, unexpected amplitude changes, abrupt peaks, periodic components, high intensity zones or specific edge contours. A major difficulty related to data analysis is the identification, in a rapid and automated way, of a set of discharges with comparable behavior, i.e. discharges with "similar" patterns. Pattern recognition techniques are efficient tools to search for similar structural forms within the database in a fast an intelligent way. To this end, classification systems must be developed to be used as indexation methods to directly fetch the more similar patterns.

A series of PDB related databases for everyday needs.

PubMed

Joosten, Robbie P; te Beek, Tim A H; Krieger, Elmar; Hekkelman, Maarten L; Hooft, Rob W W; Schneider, Reinhard; Sander, Chris; Vriend, Gert

2011-01-01

The Protein Data Bank (PDB) is the world-wide repository of macromolecular structure information. We present a series of databases that run parallel to the PDB. Each database holds one entry, if possible, for each PDB entry. DSSP holds the secondary structure of the proteins. PDBREPORT holds reports on the structure quality and lists errors. HSSP holds a multiple sequence alignment for all proteins. The PDBFINDER holds easy to parse summaries of the PDB file content, augmented with essentials from the other systems. PDB_REDO holds re-refined, and often improved, copies of all structures solved by X-ray. WHY_NOT summarizes why certain files could not be produced. All these systems are updated weekly. The data sets can be used for the analysis of properties of protein structures in areas ranging from structural genomics, to cancer biology and protein design.

Forecasting ESKAPE infections through a time-varying auto-adaptive algorithm using laboratory-based surveillance data.

PubMed

Ballarin, Antonio; Posteraro, Brunella; Demartis, Giuseppe; Gervasi, Simona; Panzarella, Fabrizio; Torelli, Riccardo; Paroni Sterbini, Francesco; Morandotti, Grazia; Posteraro, Patrizia; Ricciardi, Walter; Gervasi Vidal, Kristian A; Sanguinetti, Maurizio

2014-12-06

Mathematical or statistical tools are capable to provide a valid help to improve surveillance systems for healthcare and non-healthcare-associated bacterial infections. The aim of this work is to evaluate the time-varying auto-adaptive (TVA) algorithm-based use of clinical microbiology laboratory database to forecast medically important drug-resistant bacterial infections. Using TVA algorithm, six distinct time series were modelled, each one representing the number of episodes per single 'ESKAPE' (E nterococcus faecium, S taphylococcus aureus, K lebsiella pneumoniae, A cinetobacter baumannii, P seudomonas aeruginosa and E nterobacter species) infecting pathogen, that had occurred monthly between 2002 and 2011 calendar years at the Università Cattolica del Sacro Cuore general hospital. Monthly moving averaged numbers of observed and forecasted ESKAPE infectious episodes were found to show a complete overlapping of their respective smoothed time series curves. Overall good forecast accuracy was observed, with percentages ranging from 82.14% for E. faecium infections to 90.36% for S. aureus infections. Our approach may regularly provide physicians with forecasted bacterial infection rates to alert them about the spread of antibiotic-resistant bacterial species, especially when clinical microbiological results of patients' specimens are delayed.

Comparing temperature of subauroral mesopause over Yakutia with SABER radiometer data for 2002-2014

NASA Astrophysics Data System (ADS)

Ammosova, Anastasiya; Gavrilyeva, Galina; Ammosov, Petr; Koltovskoi, Igor

2017-06-01

We present the temperature database for the mesopause region, which was collected from spectral measurements of bands O2(0-1) and OH(6-2) with the infrared spectrograph SP-50 at the Maimaga station (63° N; 129.5° E) in 2002-2014. The temperature time series covers 11-year solar cycle. It is compared with the temperature obtained with the Sounding of the Atmosphere using Broadband Emission Radiometry instrument (SABER, v.1.07 and v.2.0), installed onboard the TIMED satellite. We compare temperatures measured during satellite passes at distances under 500 km from the intersection of the spectrograph sighting line with the hydroxyl emitting layer (~87 km) and oxygen emitting layer (~95 km). The time criterion is 30 min. We observe that there is a seasonal dependence of the difference between the ground-based and satellite measurements. The data obtained using SABER v2.0 show good agreement with the temperatures measured with the infrared digital spectrograph. The analysis we carried out allows us to conclude that a series of rotational temperatures obtained at the Maimaga station can be used to study temperature variations on different time scales including long-term trends at the mesopause height.

GPS data exploration for seismologists and geodesists

NASA Astrophysics Data System (ADS)

Webb, F.; Bock, Y.; Kedar, S.; Dong, D.; Jamason, P.; Chang, R.; Prawirodirdjo, L.; MacLeod, I.; Wadsworth, G.

2007-12-01

Over the past decade, GPS and seismic networks spanning the western US plate boundaries have produced vast amounts of data that need to be made accessible to both the geodesy and seismology communities. Unlike seismic data, raw geodetic data requires significant processing before geophysical interpretations can be made. This requires the generation of data-products (time series, velocities and strain maps) and dissemination strategies to bridge these differences and assure efficient use of data across traditionally separate communities. "GPS DATA PRODUCTS FOR SOLID EARTH SCIENCE" (GDPSES) is a multi-year NASA funded project, designed to produce and deliver high quality GPS time series, velocities, and strain fields, derived from multiple GPS networks along the western US plate boundary, and to make these products easily accessible to geophysicists. Our GPS product dissemination is through modern web-based IT methodology. Product browsing is facilitated through a web tool known as GPS Explorer and continuous streams of GPS time series are provided using web services to the seismic archive, where it can be accessed by seismologists using traditional seismic data viewing and manipulation tools. GPS-Explorer enables users to efficiently browse several layers of data products from raw data through time series, velocities and strain by providing the user with a web interface, which seamlessly interacts with a continuously updated database of these data products through the use of web-services. The current archive contains GDPSES data products beginning in 1995, and includes observations from GPS stations in EarthScope's Plate Boundary Observatory (PBO), as well as from real-time real-time CGPS stations. The generic, standards-based approach used in this project enables GDPSES to seamlessly expand indefinitely to include other space-time-dependent data products from additional GPS networks. The prototype GPS-Explorer provides users with a personalized working environment in which the user may zoom in and access subsets of the data via web services. It provides users with a variety of interactive web tools interconnected in a portlet environment to explore and save datasets of interest to return to at a later date. At the same time the GPS time series are also made available through the seismic data archive, where the GPS networks are treated as regular seismic networks, whose data is made available in data formats used by seismic utilities such as SEED readers and SAC. A key challenge, stemming from the fundamental differences between seismic and geodetic time series, is the representation of reprocessed of GPS data in the seismic archive. As GPS processing algorithms evolve and their accuracy increases, a periodic complete recreation of the the GPS time series archive is necessary.

Prolog as a Teaching Tool for Relational Database Interrogation.

ERIC Educational Resources Information Center

Collier, P. A.; Samson, W. B.

1982-01-01

The use of the Prolog programing language is promoted as the language to use by anyone teaching a course in relational databases. A short introduction to Prolog is followed by a series of examples of queries. Several references are noted for anyone wishing to gain a deeper understanding. (MP)

Administrative Information Systems: The 1980 Profile. CAUSE Monograph Series.

ERIC Educational Resources Information Center

Thomas, Charles R.

The first summaries of the CAUSE National Database, which was established in 1980, are presented. The database is updated annually to provide members with baseline reference information on the status of administrative information systems in colleges and universities. Information is based on responses from 350 CAUSE member campuses, which are…

76 FR 12617 - Airworthiness Directives; The Boeing Company Model 777-200 and -300 Series Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-08

... installing new operational software for the electrical load management system and configuration database... the electrical load management system operational software and configuration database software, in... Management, P.O. Box 3707, MC 2H-65, Seattle, Washington 98124-2207; telephone 206- 544-5000, extension 1...

Comparative analysis of death by suicide in Brazil and in the United States: descriptive, cross-sectional time series study.

PubMed

Abuabara, Alexander; Abuabara, Allan; Tonchuk, Carin Albino Luçolli

2017-01-01

The World Health Organization recognizes suicide as a public health priority. Increased knowledge of suicide risk factors is needed in order to be able to adopt effective prevention strategies. The aim of this study was to analyze and compare the association between the Gini coefficient (which is used to measure inequality) and suicide death rates over a 14-year period (2000-2013) in Brazil and in the United States (US). The hypothesis put forward was that reduction of income inequality is accompanied by reduction of suicide rates. Descriptive cross-sectional time-series study in Brazil and in the US. Population, death and suicide death data were extracted from the DATASUS database in Brazil and from the National Center for Health Statistics in the US. Gini coefficient data were obtained from the World Development Indicators. Time series analysis was performed on Brazilian and American official data regarding the number of deaths caused by suicide between 2000 and 2013 and the Gini coefficients of the two countries. The suicide trends were examined and compared. Brazil and the US present converging Gini coefficients, mainly due to reduction of inequality in Brazil over the last decade. However, suicide rates are not converging as hypothesized, but are in fact rising in both countries. The hypothesis that reduction of income inequality is accompanied by reduction of suicide rates was not verified.

125 years of glacier survey of the Austrian Alpine Club: results and future challenges

NASA Astrophysics Data System (ADS)

Fischer, Andrea

2016-04-01

One of the aims of the German and Austrian Alpine Club was the scientific investigation of the Alps. In 1891, several years after Swiss initiatives, Richter put out a call to contribute to regular glacier length surveys in the Eastern Alps. Since then more than 100 glaciers have been surveyed on a first biannual and later annual basis. The database includes measured data showing a general glacier retreat since 1891, with two periods of glacier advances in the 1920s and 1980s. Less well known are the sketches and reports which illustrate, for instance, changes in surface texture. The interpretation of length change data requires a larger sample of data for a reasonable interpretation on a regional scale. Nearly every time series in the long history of investigation includes gaps, e.g. in cases of problematic snout positions on steep rock walls or in lakes, or of debris-covered tongues. Current climate change adds the problem of glaciers splitting up into several smaller glaciers which behave differently. Several basic questions need to be addressed to arrive at a most accurate prolongated time series: How should measurements on disintegrating or debris-covered (and thus more or less stagnating) glaciers be documented, and how can we homogenize length change time series? Despite of uncertainties, length change data are amongst the longest available records, bridging the gap to moraine datings of the early holocene.

Global-scale analysis of satellite-derived time series of naturally inundated areas as a basis for floodplain modeling

NASA Astrophysics Data System (ADS)

Adam, L.; Döll, P.; Prigent, C.; Papa, F.

2010-08-01

Floodplains play an important role in the terrestrial water cycle and are very important for biodiversity. Therefore, an improved representation of the dynamics of floodplain water flows and storage in global hydrological and land surface models is required. To support model validation, we combined monthly time series of satellite-derived inundation areas (Papa et al., 2010) with data on irrigated rice areas (Portmann et al., 2010). In this way, we obtained global-scale time series of naturally inundated areas (NIA), with monthly values of inundation extent during 1993-2004 and a spatial resolution of 0.5°. For most grid cells (0.5°×0.5°), the mean annual maximum of NIA agrees well with the static open water extent of the Global Lakes and Wetlands database (GLWD) (Lehner and Döll, 2004), but in 16% of the cells NIA is larger than GLWD. In some regions, like Northwestern Europe, NIA clearly overestimates inundated areas, probably because of confounding very wet soils with inundated areas. In other areas, such as South Asia, it is likely that NIA can help to enhance GLWD. NIA data will be very useful for developing and validating a floodplain modeling algorithm for the global hydrological model WGHM. For example, we found that monthly NIAs correlate with observed river discharges.

Statistical Downscaling in Multi-dimensional Wave Climate Forecast

NASA Astrophysics Data System (ADS)

Camus, P.; Méndez, F. J.; Medina, R.; Losada, I. J.; Cofiño, A. S.; Gutiérrez, J. M.

2009-04-01

Wave climate at a particular site is defined by the statistical distribution of sea state parameters, such as significant wave height, mean wave period, mean wave direction, wind velocity, wind direction and storm surge. Nowadays, long-term time series of these parameters are available from reanalysis databases obtained by numerical models. The Self-Organizing Map (SOM) technique is applied to characterize multi-dimensional wave climate, obtaining the relevant "wave types" spanning the historical variability. This technique summarizes multi-dimension of wave climate in terms of a set of clusters projected in low-dimensional lattice with a spatial organization, providing Probability Density Functions (PDFs) on the lattice. On the other hand, wind and storm surge depend on instantaneous local large-scale sea level pressure (SLP) fields while waves depend on the recent history of these fields (say, 1 to 5 days). Thus, these variables are associated with large-scale atmospheric circulation patterns. In this work, a nearest-neighbors analog method is used to predict monthly multi-dimensional wave climate. This method establishes relationships between the large-scale atmospheric circulation patterns from numerical models (SLP fields as predictors) with local wave databases of observations (monthly wave climate SOM PDFs as predictand) to set up statistical models. A wave reanalysis database, developed by Puertos del Estado (Ministerio de Fomento), is considered as historical time series of local variables. The simultaneous SLP fields calculated by NCEP atmospheric reanalysis are used as predictors. Several applications with different size of sea level pressure grid and with different temporal domain resolution are compared to obtain the optimal statistical model that better represents the monthly wave climate at a particular site. In this work we examine the potential skill of this downscaling approach considering perfect-model conditions, but we will also analyze the suitability of this methodology to be used for seasonal forecast and for long-term climate change scenario projection of wave climate.

AnClim and ProClimDB software for data quality control and homogenization of time series

NASA Astrophysics Data System (ADS)

Stepanek, Petr

2015-04-01

During the last decade, a software package consisting of AnClim, ProClimDB and LoadData for processing (mainly climatological) data has been created. This software offers a complex solution for processing of climatological time series, starting from loading the data from a central database (e.g. Oracle, software LoadData), through data duality control and homogenization to time series analysis, extreme value evaluations and RCM outputs verification and correction (ProClimDB and AnClim software). The detection of inhomogeneities is carried out on a monthly scale through the application of AnClim, or newly by R functions called from ProClimDB, while quality control, the preparation of reference series and the correction of found breaks is carried out by the ProClimDB software. The software combines many statistical tests, types of reference series and time scales (monthly, seasonal and annual, daily and sub-daily ones). These can be used to create an "ensemble" of solutions, which may be more reliable than any single method. AnClim software is suitable for educational purposes: e.g. for students getting acquainted with methods used in climatology. Built-in graphical tools and comparison of various statistical tests help in better understanding of a given method. ProClimDB is, on the contrary, tool aimed for processing of large climatological datasets. Recently, functions from R may be used within the software making it more efficient in data processing and capable of easy inclusion of new methods (when available under R). An example of usage is easy comparison of methods for correction of inhomogeneities in daily data (HOM of Paul Della-Marta, SPLIDHOM method of Olivier Mestre, DAP - own method, QM of Xiaolan Wang and others). The software is available together with further information on www.climahom.eu . Acknowledgement: this work was partially funded by the project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248.

An open-database of Grape Harvest dates for climate research: data description and quality assessment

NASA Astrophysics Data System (ADS)

Daux, V.; Garcia de Cortazar-Atauri, I.; Yiou, P.; Chuine, I.; Garnier, E.; Ladurie, E. Le Roy; Mestre, O.; Tardaguila, J.

2011-11-01

We present a dataset of grape harvest dates (GHD) series that has been compiled from international and non-translated French and Spanish literature and from unpublished documentary sources from public organizations and from wine-growers. As of June 2011, this GHD dataset comprises 378 series mainly from France (93% of the data) as well as series from Switzerland, Italy, Spain and Luxembourg. The series have variable length and contain gaps of variable sizes. The longest and most complete ones are from Burgundy, Switzerland, Southern Rhône valley, Jura and Ile-de-France. The GHD series were grouped into 27 regions according to their location, to geomorphological and geological criteria, and to past and present grape varieties. The GHD regional composite series (GHD-RCS) were calculated and compared pairwise to assess the quality of the series. Significant (p-value < 0.001) and strong correlations exist between most of them. As expected, the correlations tended to be higher when the vineyards are closer, the highest correlation (R = 0.91) being obtained between the High Loire Valley and the Ile-de-France GHD-RCS. The strong dependence of vine cycle on temperature and, therefore, the strong link between GHD and the temperature of the growing season was also used to test the quality of the GHD series. The strongest correlations are obtained between the GHD-RCS and the temperature series of the nearest weather stations. Moreover, the GHD-RCS/temperature correlation maps show spatial patterns similar to temperature correlation maps. The stability of the correlations over time is explored. The most striking feature is their generalized deterioration at the late 19th-early 20th turning point. The possible effects on the GHD of the phylloxera crisis, which took place at this time, are discussed. The median of the standardized GHD-RCS was calculated. The distribution of the extreme years of this general synthetic series is not homogenous. Extremely late years all occur during a two-century long time-window from the early 17th to the early 19th century, while extremely early years are frequent during the 16th and since the mid-19th century. The dataset is made accessible for climate research through the Internet. It should allow a variety of climate studies, including reconstructions of atmospheric circulation over Western Europe.

Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database.

PubMed

Wu, Mike; Ghassemi, Marzyeh; Feng, Mengling; Celi, Leo A; Szolovits, Peter; Doshi-Velez, Finale

2017-05-01

The widespread adoption of electronic health records allows us to ask evidence-based questions about the need for and benefits of specific clinical interventions in critical-care settings across large populations. We investigated the prediction of vasopressor administration and weaning in the intensive care unit. Vasopressors are commonly used to control hypotension, and changes in timing and dosage can have a large impact on patient outcomes. We considered a cohort of 15 695 intensive care unit patients without orders for reduced care who were alive 30 days post-discharge. A switching-state autoregressive model (SSAM) was trained to predict the multidimensional physiological time series of patients before, during, and after vasopressor administration. The latent states from the SSAM were used as predictors of vasopressor administration and weaning. The unsupervised SSAM features were able to predict patient vasopressor administration and successful patient weaning. Features derived from the SSAM achieved areas under the receiver operating curve of 0.92, 0.88, and 0.71 for predicting ungapped vasopressor administration, gapped vasopressor administration, and vasopressor weaning, respectively. We also demonstrated many cases where our model predicted weaning well in advance of a successful wean. Models that used SSAM features increased performance on both predictive tasks. These improvements may reflect an underlying, and ultimately predictive, latent state detectable from the physiological time series. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Potential assessment of the "support vector machine" method in forecasting ambient air pollutant trends.

PubMed

Lu, Wei-Zhen; Wang, Wen-Jian

2005-04-01

Monitoring and forecasting of air quality parameters are popular and important topics of atmospheric and environmental research today due to the health impact caused by exposing to air pollutants existing in urban air. The accurate models for air pollutant prediction are needed because such models would allow forecasting and diagnosing potential compliance or non-compliance in both short- and long-term aspects. Artificial neural networks (ANN) are regarded as reliable and cost-effective method to achieve such tasks and have produced some promising results to date. Although ANN has addressed more attentions to environmental researchers, its inherent drawbacks, e.g., local minima, over-fitting training, poor generalization performance, determination of the appropriate network architecture, etc., impede the practical application of ANN. Support vector machine (SVM), a novel type of learning machine based on statistical learning theory, can be used for regression and time series prediction and have been reported to perform well by some promising results. The work presented in this paper aims to examine the feasibility of applying SVM to predict air pollutant levels in advancing time series based on the monitored air pollutant database in Hong Kong downtown area. At the same time, the functional characteristics of SVM are investigated in the study. The experimental comparisons between the SVM model and the classical radial basis function (RBF) network demonstrate that the SVM is superior to the conventional RBF network in predicting air quality parameters with different time series and of better generalization performance than the RBF model.

SUVI Thematic Maps: A new tool for space weather forecasting

NASA Astrophysics Data System (ADS)

Hughes, J. M.; Seaton, D. B.; Darnel, J.

2017-12-01

The new Solar Ultraviolet Imager (SUVI) instruments aboard NOAA's GOES-R series satellites collect continuous, high-quality imagery of the Sun in six wavelengths. SUVI imagers produce at least one image every 10 seconds, or 8,640 images per day, considerably more data than observers can digest in real time. Over the projected 20-year lifetime of the four GOES-R series spacecraft, SUVI will provide critical imagery for space weather forecasters and produce an extensive but unwieldy archive. In order to condense the database into a dynamic and searchable form we have developed solar thematic maps, maps of the Sun with key features, such as coronal holes, flares, bright regions, quiet corona, and filaments, identified. Thematic maps will be used in NOAA's Space Weather Prediction Center to improve forecaster response time to solar events and generate several derivative products. Likewise, scientists use thematic maps to find observations of interest more easily. Using an expert-trained, naive Bayesian classifier to label each pixel, we create thematic maps in real-time. We created software to collect expert classifications of solar features based on SUVI images. Using this software, we compiled a database of expert classifications, from which we could characterize the distribution of pixels associated with each theme. Given new images, the classifier assigns each pixel the most appropriate label according to the trained distribution. Here we describe the software to collect expert training and the successes and limitations of the classifier. The algorithm excellently identifies coronal holes but fails to consistently detect filaments and prominences. We compare the Bayesian classifier to an artificial neural network, one of our attempts to overcome the aforementioned limitations. These results are very promising and encourage future research into an ensemble classification approach.

Multivariate statistical analysis of wildfires in Portugal

NASA Astrophysics Data System (ADS)

Costa, Ricardo; Caramelo, Liliana; Pereira, Mário

2013-04-01

Several studies demonstrate that wildfires in Portugal present high temporal and spatial variability as well as cluster behavior (Pereira et al., 2005, 2011). This study aims to contribute to the characterization of the fire regime in Portugal with the multivariate statistical analysis of the time series of number of fires and area burned in Portugal during the 1980 - 2009 period. The data used in the analysis is an extended version of the Rural Fire Portuguese Database (PRFD) (Pereira et al, 2011), provided by the National Forest Authority (Autoridade Florestal Nacional, AFN), the Portuguese Forest Service, which includes information for more than 500,000 fire records. There are many multiple advanced techniques for examining the relationships among multiple time series at the same time (e.g., canonical correlation analysis, principal components analysis, factor analysis, path analysis, multiple analyses of variance, clustering systems). This study compares and discusses the results obtained with these different techniques. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005: "Synoptic patterns associated with large summer forest fires in Portugal". Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692, the project FLAIR (PTDC/AAC-AMB/104702/2008) and the EU 7th Framework Program through FUME (contract number 243888).

Reliability of the Defense Commissary Agency Personnel Property Database.

DTIC Science & Technology

2000-02-18

Departments’ personal property databases. The tests were designed to validate the personal property databases. This report is the second in a series of...with the completeness of its data , and key data elements were not reliable for estimating the historical costs of real property for the Military...values of greater than $100,000. However, some of the Military Departments had problems with the completeness of its data , and key data elements

Design considerations, architecture, and use of the Mini-Sentinel distributed data system.

PubMed

Curtis, Lesley H; Weiner, Mark G; Boudreau, Denise M; Cooper, William O; Daniel, Gregory W; Nair, Vinit P; Raebel, Marsha A; Beaulieu, Nicolas U; Rosofsky, Robert; Woodworth, Tiffany S; Brown, Jeffrey S

2012-01-01

We describe the design, implementation, and use of a large, multiorganizational distributed database developed to support the Mini-Sentinel Pilot Program of the US Food and Drug Administration (FDA). As envisioned by the US FDA, this implementation will inform and facilitate the development of an active surveillance system for monitoring the safety of medical products (drugs, biologics, and devices) in the USA. A common data model was designed to address the priorities of the Mini-Sentinel Pilot and to leverage the experience and data of participating organizations and data partners. A review of existing common data models informed the process. Each participating organization designed a process to extract, transform, and load its source data, applying the common data model to create the Mini-Sentinel Distributed Database. Transformed data were characterized and evaluated using a series of programs developed centrally and executed locally by participating organizations. A secure communications portal was designed to facilitate queries of the Mini-Sentinel Distributed Database and transfer of confidential data, analytic tools were developed to facilitate rapid response to common questions, and distributed querying software was implemented to facilitate rapid querying of summary data. As of July 2011, information on 99,260,976 health plan members was included in the Mini-Sentinel Distributed Database. The database includes 316,009,067 person-years of observation time, with members contributing, on average, 27.0 months of observation time. All data partners have successfully executed distributed code and returned findings to the Mini-Sentinel Operations Center. This work demonstrates the feasibility of building a large, multiorganizational distributed data system in which organizations retain possession of their data that are used in an active surveillance system. Copyright © 2012 John Wiley & Sons, Ltd.

AT_CHLORO, a comprehensive chloroplast proteome database with subplastidial localization and curated information on envelope proteins.

PubMed

Ferro, Myriam; Brugière, Sabine; Salvi, Daniel; Seigneurin-Berny, Daphné; Court, Magali; Moyet, Lucas; Ramus, Claire; Miras, Stéphane; Mellal, Mourad; Le Gall, Sophie; Kieffer-Jaquinod, Sylvie; Bruley, Christophe; Garin, Jérôme; Joyard, Jacques; Masselon, Christophe; Rolland, Norbert

2010-06-01

Recent advances in the proteomics field have allowed a series of high throughput experiments to be conducted on chloroplast samples, and the data are available in several public databases. However, the accurate localization of many chloroplast proteins often remains hypothetical. This is especially true for envelope proteins. We went a step further into the knowledge of the chloroplast proteome by focusing, in the same set of experiments, on the localization of proteins in the stroma, the thylakoids, and envelope membranes. LC-MS/MS-based analyses first allowed building the AT_CHLORO database (http://www.grenoble.prabi.fr/protehome/grenoble-plant-proteomics/), a comprehensive repertoire of the 1323 proteins, identified by 10,654 unique peptide sequences, present in highly purified chloroplasts and their subfractions prepared from Arabidopsis thaliana leaves. This database also provides extensive proteomics information (peptide sequences and molecular weight, chromatographic retention times, MS/MS spectra, and spectral count) for a unique chloroplast protein accurate mass and time tag database gathering identified peptides with their respective and precise analytical coordinates, molecular weight, and retention time. We assessed the partitioning of each protein in the three chloroplast compartments by using a semiquantitative proteomics approach (spectral count). These data together with an in-depth investigation of the literature were compiled to provide accurate subplastidial localization of previously known and newly identified proteins. A unique knowledge base containing extensive information on the proteins identified in envelope fractions was thus obtained, allowing new insights into this membrane system to be revealed. Altogether, the data we obtained provide unexpected information about plastidial or subplastidial localization of some proteins that were not suspected to be associated to this membrane system. The spectral counting-based strategy was further validated as the compartmentation of well known pathways (for instance, photosynthesis and amino acid, fatty acid, or glycerolipid biosynthesis) within chloroplasts could be dissected. It also allowed revisiting the compartmentation of the chloroplast metabolism and functions.

Hydrologic and landscape database for the Cache and White River National Wildlife Refuges and contributing watersheds in Arkansas, Missouri, and Oklahoma

USGS Publications Warehouse

Buell, Gary R.; Wehmeyer, Loren L.; Calhoun, Daniel L.

2012-01-01

A hydrologic and landscape database was developed by the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, for the Cache River and White River National Wildlife Refuges and their contributing watersheds in Arkansas, Missouri, and Oklahoma. The database is composed of a set of ASCII files, Microsoft Access® files, Microsoft Excel® files, an Environmental Systems Research Institute (ESRI) ArcGIS® geodatabase, ESRI ArcGRID® raster datasets, and an ESRI ArcReader® published map. The database was developed as an assessment and evaluation tool to use in examining refuge-specific hydrologic patterns and trends as related to water availability for refuge ecosystems, habitats, and target species; and includes hydrologic time-series data, statistics, and hydroecological metrics that can be used to assess refuge hydrologic conditions and the availability of aquatic and riparian habitat. Landscape data that describe the refuge physiographic setting and the locations of hydrologic-data collection stations are also included in the database. Categories of landscape data include land cover, soil hydrologic characteristics, physiographic features, geographic and hydrographic boundaries, hydrographic features, regional runoff estimates, and gaging-station locations. The database geographic extent covers three hydrologic subregions—the Lower Mississippi–St Francis (0802), the Upper White (1101), and the Lower Arkansas (1111)—within which human activities, climatic variation, and hydrologic processes can potentially affect the hydrologic regime of the refuges and adjacent areas. Database construction has been automated to facilitate periodic updates with new data. The database report (1) serves as a user guide for the database, (2) describes the data-collection, data-reduction, and data-analysis methods used to construct the database, (3) provides a statistical and graphical description of the database, and (4) provides detailed information on the development of analytical techniques designed to assess water availability for ecological needs.

CDM analysis

NASA Technical Reports Server (NTRS)

Larson, Robert E.; Mcentire, Paul L.; Oreilly, John G.

1993-01-01

The C Data Manager (CDM) is an advanced tool for creating an object-oriented database and for processing queries related to objects stored in that database. The CDM source code was purchased and will be modified over the course of the Arachnid project. In this report, the modified CDM is referred to as MCDM. Using MCDM, a detailed series of experiments was designed and conducted on a Sun Sparcstation. The primary results and analysis of the CDM experiment are provided in this report. The experiments involved creating the Long-form Faint Source Catalog (LFSC) database and then analyzing it with respect to following: (1) the relationships between the volume of data and the time required to create a database; (2) the storage requirements of the database files; and (3) the properties of query algorithms. The effort focused on defining, implementing, and analyzing seven experimental scenarios: (1) find all sources by right ascension--RA; (2) find all sources by declination--DEC; (3) find all sources in the right ascension interval--RA1, RA2; (4) find all sources in the declination interval--DEC1, DEC2; (5) find all sources in the rectangle defined by--RA1, RA2, DEC1, DEC2; (6) find all sources that meet certain compound conditions; and (7) analyze a variety of query algorithms. Throughout this document, the numerical results obtained from these scenarios are reported; conclusions are presented at the end of the document.

Impact of missing data on the efficiency of homogenisation: experiments with ACMANTv3

NASA Astrophysics Data System (ADS)

Domonkos, Peter; Coll, John

2018-04-01

The impact of missing data on the efficiency of homogenisation with ACMANTv3 is examined with simulated monthly surface air temperature test datasets. The homogeneous database is derived from an earlier benchmarking of daily temperature data in the USA, and then outliers and inhomogeneities (IHs) are randomly inserted into the time series. Three inhomogeneous datasets are generated and used, one with relatively few and small IHs, another one with IHs of medium frequency and size, and a third one with large and frequent IHs. All of the inserted IHs are changes to the means. Most of the IHs are single sudden shifts or pair of shifts resulting in platform-shaped biases. Each test dataset consists of 158 time series of 100 years length, and their mean spatial correlation is 0.68-0.88. For examining the impacts of missing data, seven experiments are performed, in which 18 series are left complete, while variable quantities (10-70%) of the data of the other 140 series are removed. The results show that data gaps have a greater impact on the monthly root mean squared error (RMSE) than the annual RMSE and trend bias. When data with a large ratio of gaps is homogenised, the reduction of the upper 5% of the monthly RMSE is the least successful, but even there, the efficiency remains positive. In terms of reducing the annual RMSE and trend bias, the efficiency is 54-91%. The inclusion of short and incomplete series with sufficient spatial correlation in all cases improves the efficiency of homogenisation with ACMANTv3.

Time-series panel analysis (TSPA): multivariate modeling of temporal associations in psychotherapy process.

PubMed

Ramseyer, Fabian; Kupper, Zeno; Caspar, Franz; Znoj, Hansjörg; Tschacher, Wolfgang

2014-10-01

Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Archiving and Near Real Time Visualization of USGS Instantaneous Data

NASA Astrophysics Data System (ADS)

Zaslavsky, I.; Ryan, D.; Whitenack, T.; Valentine, D. W.; Rodriguez, M.

2009-12-01

The CUAHSI Hydrologic Information System project has been developing databases, services and online and desktop software applications supporting standards-based publication and access to large volumes of hydrologic data from US federal agencies and academic partners. In particular, the CUAHSI WaterML 1.x schema specification for exchanging hydrologic time series, earlier published as an OGC Discussion Paper (2007), has been adopted by the United States Geological Survey to provide web service access to USGS daily values and instantaneous data. The latter service, making available raw measurements of discharge, gage height and several other parameters for over 10,000 USGS real time measurement points, was announced by USGS, as an experimental WaterML-compliant service, at the end of July 2009. We demonstrate an online application that leverages the new service for nearly continuous harvesting of USGS real time data, and simultaneous visualization and analysis of the data streams. To make this possible, we integrate service components of the CUAHSI software stack with Open Source Data Turbine (OSDT) system, an NSF-supported software environment for robust and scalable assimilation of multimedia data streams (e.g. from sensors), and interfacing with a variety of viewers, databases, archival systems and client applications. Our application continuously queries USGS Instantaneous water data service (which provides access to 15-min measurements updated at USGS every 4 hours), and maps the results for each station-variable combination to a separate "channel", which is used by OSDT to quickly access and manipulate the time series. About 15,000 channels are used, which makes it by far the largest deployment of OSDT. Using RealTime Data Viewer, users can now select one or more stations of interest (e.g. from upstream or downstream from each other), and observe and annotate simultaneous dynamics in the respective discharge and gage height values, using fast forward or backward modes, real-time mode, etc. Memory management, scheduling service-based retrieval from USGS web services, and organizing access to 7,330 selected stations, turned out to be the major challenges in this project. To allow station navigation, they are grouped by state and county in the user interface. Memory footprint has been monitored under different Java VM settings, to find the correct regime. These and other solutions are discussed in the paper, and accompanied with a series of examples of simultaneous visualization of discharge from multiple stations as a component of hydrologic analysis.

True Brachial Artery Aneurysm after Arteriovenous Fistula for Hemodialysis: Five Cases and Literature Review.

PubMed

Fendri, Jihene; Palcau, Laura; Cameliere, Lucie; Coffin, Olivier; Felisaz, Aurelien; Gouicem, Djelloul; Dufranc, Julie; Laneelle, Damien; Berger, Ludovic

2017-02-01

The donor artery after a long-standing arteriovenous fistula (AVF) for hemodialysis usually evolves exceptionally toward a true aneurysmal degeneration (AD). The purpose of this article was to describe true brachial artery AD in end-stage renal disease patients after AVF creation, as well as its influencing factors and treatment strategies. We present a retrospective, observational, single-center study realized in Caen University Hospital's Vascular Surgery Department from May 1996 to November 2015. The inclusion criteria were true AD of the brachial artery after a vascular access for hemodialysis. A literature research, using the same criteria, was performed on the articles published between 1994 and 2015. The used databases included MEDLINE (via PubMed), EMBASE via OVID, Cochrane Library Database, and ResearchGate. Our series includes 5 patients. Twenty-one articles were found in the literature: 17 case reports, 3 series, and 1 review. The same triggering factors for AD (high flow and immunosuppressive treatment) were found. The mean age at the time of AVF creation, first renal transplantation, and AD's diagnosis were respectively 26 (range 15-49), 29.2, and 48.6 years (range 37-76) in our series versus 34 (range 27-39), 40.4 (range 28-55), and 55.5 years (range 35-75) in cases found in the literature. The time spread after AVF creation and aneurysmal diagnosis was about 20.6 years (range 18-25) in our study versus 20.5 years (range 9-29) in the case reports. Our surgical attitude corresponds principally to that described in the literature. Nevertheless, we describe for the first time one case of arterial transposition to exclude the brachial aneurysm using superficial femoral artery. Arterial aneurysm is a rare, but significant complication after a long-term creation of hemodialysis access. High flow and immunosuppression may accelerate this process. Young age of the patients may act as a benefic factor and delay the AD. Arterial transposition could be an option in the absence of any venous conduit, if anatomy does not permit the use of prosthetic grafts. Copyright © 2016 Elsevier Inc. All rights reserved.

The Problem with the Delta Cost Project Database

ERIC Educational Resources Information Center

Jaquette, Ozan; Parra, Edna

2016-01-01

The Integrated Postsecondary Education System (IPEDS) collects data on Title IV institutions. The Delta Cost Project (DCP) integrated data from multiple IPEDS survey components into a public-use longitudinal dataset. The DCP Database was the basis for dozens of journal articles and a series of influential policy reports. Unfortunately, a flaw in…

76 FR 5503 - Airworthiness Directives; The Boeing Company Model 777-200 Series Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-01

... software, as applicable; and making a change to the cabin services system (CSS) configuration database and... software, as applicable; and make a change to the cabin services system (CSS) configuration database and... 5 p.m., Monday through Friday, except Federal holidays. For service information identified in this...

The Fossil Calibration Database-A New Resource for Divergence Dating.

PubMed

Ksepka, Daniel T; Parham, James F; Allman, James F; Benton, Michael J; Carrano, Matthew T; Cranston, Karen A; Donoghue, Philip C J; Head, Jason J; Hermsen, Elizabeth J; Irmis, Randall B; Joyce, Walter G; Kohli, Manpreet; Lamm, Kristin D; Leehr, Dan; Patané, Josés L; Polly, P David; Phillips, Matthew J; Smith, N Adam; Smith, Nathan D; Van Tuinen, Marcel; Ware, Jessica L; Warnock, Rachel C M

2015-09-01

Fossils provide the principal basis for temporal calibrations, which are critical to the accuracy of divergence dating analyses. Translating fossil data into minimum and maximum bounds for calibrations is the most important-often least appreciated-step of divergence dating. Properly justified calibrations require the synthesis of phylogenetic, paleontological, and geological evidence and can be difficult for nonspecialists to formulate. The dynamic nature of the fossil record (e.g., new discoveries, taxonomic revisions, updates of global or local stratigraphy) requires that calibration data be updated continually lest they become obsolete. Here, we announce the Fossil Calibration Database (http://fossilcalibrations.org), a new open-access resource providing vetted fossil calibrations to the scientific community. Calibrations accessioned into this database are based on individual fossil specimens and follow best practices for phylogenetic justification and geochronological constraint. The associated Fossil Calibration Series, a calibration-themed publication series at Palaeontologia Electronica, will serve as a key pipeline for peer-reviewed calibrations to enter the database. © The Author(s) 2015. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Challenges in the automated classification of variable stars in large databases

NASA Astrophysics Data System (ADS)

Graham, Matthew; Drake, Andrew; Djorgovski, S. G.; Mahabal, Ashish; Donalek, Ciro

2017-09-01

With ever-increasing numbers of astrophysical transient surveys, new facilities and archives of astronomical time series, time domain astronomy is emerging as a mainstream discipline. However, the sheer volume of data alone - hundreds of observations for hundreds of millions of sources - necessitates advanced statistical and machine learning methodologies for scientific discovery: characterization, categorization, and classification. Whilst these techniques are slowly entering the astronomer's toolkit, their application to astronomical problems is not without its issues. In this paper, we will review some of the challenges posed by trying to identify variable stars in large data collections, including appropriate feature representations, dealing with uncertainties, establishing ground truths, and simple discrete classes.

Database on veterinary clinical research in homeopathy.

PubMed

Clausen, Jürgen; Albrecht, Henning

2010-07-01

The aim of the present report is to provide an overview of the first database on clinical research in veterinary homeopathy. Detailed searches in the database 'Veterinary Clinical Research-Database in Homeopathy' (http://www.carstens-stiftung.de/clinresvet/index.php). The database contains about 200 entries of randomised clinical trials, non-randomised clinical trials, observational studies, drug provings, case reports and case series. Twenty-two clinical fields are covered and eight different groups of species are included. The database is free of charge and open to all interested veterinarians and researchers. The database enables researchers and veterinarians, sceptics and supporters to get a quick overview of the status of veterinary clinical research in homeopathy and alleviates the preparation of systematical reviews or may stimulate reproductions or even new studies. 2010 Elsevier Ltd. All rights reserved.

A data mining method to facilitate SAR transfer.

PubMed

Wassermann, Anne Mai; Bajorath, Jürgen

2011-08-22

A challenging practical problem in medicinal chemistry is the transfer of SAR information from one chemical series to another. Currently, there are no computational methods available to rationalize or support this process. Herein, we present a data mining approach that enables the identification of alternative analog series with different core structures, corresponding substitution patterns, and comparable potency progression. Scaffolds can be exchanged between these series and new analogs suggested that incorporate preferred R-groups. The methodology can be applied to search for alternative analog series if one series is known or, alternatively, to systematically assess SAR transfer potential in compound databases.

POLARIS: A 30-meter probabilistic soil series map of the contiguous United States

USGS Publications Warehouse

Chaney, Nathaniel W; Wood, Eric F; McBratney, Alexander B; Hempel, Jonathan W; Nauman, Travis; Brungard, Colby W.; Odgers, Nathan P

2016-01-01

A new complete map of soil series probabilities has been produced for the contiguous United States at a 30 m spatial resolution. This innovative database, named POLARIS, is constructed using available high-resolution geospatial environmental data and a state-of-the-art machine learning algorithm (DSMART-HPC) to remap the Soil Survey Geographic (SSURGO) database. This 9 billion grid cell database is possible using available high performance computing resources. POLARIS provides a spatially continuous, internally consistent, quantitative prediction of soil series. It offers potential solutions to the primary weaknesses in SSURGO: 1) unmapped areas are gap-filled using survey data from the surrounding regions, 2) the artificial discontinuities at political boundaries are removed, and 3) the use of high resolution environmental covariate data leads to a spatial disaggregation of the coarse polygons. The geospatial environmental covariates that have the largest role in assembling POLARIS over the contiguous United States (CONUS) are fine-scale (30 m) elevation data and coarse-scale (~ 2 km) estimates of the geographic distribution of uranium, thorium, and potassium. A preliminary validation of POLARIS using the NRCS National Soil Information System (NASIS) database shows variable performance over CONUS. In general, the best performance is obtained at grid cells where DSMART-HPC is most able to reduce the chance of misclassification. The important role of environmental covariates in limiting prediction uncertainty suggests including additional covariates is pivotal to improving POLARIS' accuracy. This database has the potential to improve the modeling of biogeochemical, water, and energy cycles in environmental models; enhance availability of data for precision agriculture; and assist hydrologic monitoring and forecasting to ensure food and water security.

The urological complications of renal transplantation: a series of 1535 patients.

PubMed

Streeter, E H; Little, D M; Cranston, D W; Morris, P J

2002-11-01

To determine the incidence of urological complications of renal transplantation at one institution, and relate this to donor and recipient factors. A consecutive series of 1535 renal transplants were audited, and a database of donor and recipient characteristics created for risk-factor analysis. An unstented Leadbetter-Politano anastomosis was the preferred method of ureteric reimplantation. There were 45 urinary leaks, 54 primary ureteric obstructions, nine cases of ureteric calculi, three bladder stones and 19 cases of bladder outlet obstruction at some time after transplantation. The overall incidence of urological complications was 9.2%, with that for urinary leak or primary ureteric obstruction being 6.5%. One graft was lost because of complications, and there were three deaths associated directly or indirectly with urological complications. There was no association with recipient age, cadaveric vs living-donor transplants, or cold ischaemic times before organ reimplantation, although the donor age was slightly higher in cases of urinary leak. There was no association with kidneys imported via the UK national organ-sharing scheme vs the use of local kidneys. The management of these complications is discussed. The incidence of urological complications in this series has remained essentially unchanged for 20 years. The causes of these complications and techniques for their prevention are discussed.

Laptop Computer - Based Facial Recognition System Assessment

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

R. A. Cain; G. B. Singleton

2001-03-01

The objective of this project was to assess the performance of the leading commercial-off-the-shelf (COTS) facial recognition software package when used as a laptop application. We performed the assessment to determine the system's usefulness for enrolling facial images in a database from remote locations and conducting real-time searches against a database of previously enrolled images. The assessment involved creating a database of 40 images and conducting 2 series of tests to determine the product's ability to recognize and match subject faces under varying conditions. This report describes the test results and includes a description of the factors affecting the results.more » After an extensive market survey, we selected Visionics' FaceIt{reg_sign} software package for evaluation and a review of the Facial Recognition Vendor Test 2000 (FRVT 2000). This test was co-sponsored by the US Department of Defense (DOD) Counterdrug Technology Development Program Office, the National Institute of Justice, and the Defense Advanced Research Projects Agency (DARPA). Administered in May-June 2000, the FRVT 2000 assessed the capabilities of facial recognition systems that were currently available for purchase on the US market. Our selection of this Visionics product does not indicate that it is the ''best'' facial recognition software package for all uses. It was the most appropriate package based on the specific applications and requirements for this specific application. In this assessment, the system configuration was evaluated for effectiveness in identifying individuals by searching for facial images captured from video displays against those stored in a facial image database. An additional criterion was that the system be capable of operating discretely. For this application, an operational facial recognition system would consist of one central computer hosting the master image database with multiple standalone systems configured with duplicates of the master operating in remote locations. Remote users could perform real-time searches where network connectivity is not available. As images are enrolled at the remote locations, periodic database synchronization is necessary.« less

Has upwelling strengthened along worldwide coasts over 1982-2010?

NASA Astrophysics Data System (ADS)

Varela, R.; Álvarez, I.; Santos, F.; Decastro, M.; Gómez-Gesteira, M.

2015-05-01

Changes in coastal upwelling strength have been widely studied since 1990 when Bakun proposed that global warming can induce the intensification of upwelling in coastal areas. Whether present wind trends support this hypothesis remains controversial, as results of previous studies seem to depend on the study area, the length of the time series, the season, and even the database used. In this study, temporal and spatial trends in the coastal upwelling regime worldwide were investigated during upwelling seasons from 1982 to 2010 using a single wind database (Climate Forecast System Reanalysis) with high spatial resolution (0.3°). Of the major upwelling systems, increasing trends were only observed in the coastal areas of Benguela, Peru, Canary, and northern California. A tendency for an increase in upwelling-favourable winds was also identified along several less studied regions, such as the western Australian and southern Caribbean coasts.

CELL5M: A geospatial database of agricultural indicators for Africa South of the Sahara.

PubMed

Koo, Jawoo; Cox, Cindy M; Bacou, Melanie; Azzarri, Carlo; Guo, Zhe; Wood-Sichra, Ulrike; Gong, Queenie; You, Liangzhi

2016-01-01

Recent progress in large-scale georeferenced data collection is widening opportunities for combining multi-disciplinary datasets from biophysical to socioeconomic domains, advancing our analytical and modeling capacity. Granular spatial datasets provide critical information necessary for decision makers to identify target areas, assess baseline conditions, prioritize investment options, set goals and targets and monitor impacts. However, key challenges in reconciling data across themes, scales and borders restrict our capacity to produce global and regional maps and time series. This paper provides overview, structure and coverage of CELL5M-an open-access database of geospatial indicators at 5 arc-minute grid resolution-and introduces a range of analytical applications and case-uses. CELL5M covers a wide set of agriculture-relevant domains for all countries in Africa South of the Sahara and supports our understanding of multi-dimensional spatial variability inherent in farming landscapes throughout the region.

Has upwelling strengthened along worldwide coasts over 1982-2010?

PubMed Central

Varela, R.; Álvarez, I.; Santos, F.;  deCastro, M.; Gómez-Gesteira, M.

2015-01-01

Changes in coastal upwelling strength have been widely studied since 1990 when Bakun proposed that global warming can induce the intensification of upwelling in coastal areas. Whether present wind trends support this hypothesis remains controversial, as results of previous studies seem to depend on the study area, the length of the time series, the season, and even the database used. In this study, temporal and spatial trends in the coastal upwelling regime worldwide were investigated during upwelling seasons from 1982 to 2010 using a single wind database (Climate Forecast System Reanalysis) with high spatial resolution (0.3°). Of the major upwelling systems, increasing trends were only observed in the coastal areas of Benguela, Peru, Canary, and northern California. A tendency for an increase in upwelling-favourable winds was also identified along several less studied regions, such as the western Australian and southern Caribbean coasts. PMID:25952477

Rainfall statistics, stationarity, and climate change.

PubMed

Sun, Fubao; Roderick, Michael L; Farquhar, Graham D

2018-03-06

There is a growing research interest in the detection of changes in hydrologic and climatic time series. Stationarity can be assessed using the autocorrelation function, but this is not yet common practice in hydrology and climate. Here, we use a global land-based gridded annual precipitation (hereafter P ) database (1940-2009) and find that the lag 1 autocorrelation coefficient is statistically significant at around 14% of the global land surface, implying nonstationary behavior (90% confidence). In contrast, around 76% of the global land surface shows little or no change, implying stationary behavior. We use these results to assess change in the observed P over the most recent decade of the database. We find that the changes for most (84%) grid boxes are within the plausible bounds of no significant change at the 90% CI. The results emphasize the importance of adequately accounting for natural variability when assessing change. Copyright © 2018 the Author(s). Published by PNAS.

Rainfall statistics, stationarity, and climate change

NASA Astrophysics Data System (ADS)

Sun, Fubao; Roderick, Michael L.; Farquhar, Graham D.

2018-03-01

There is a growing research interest in the detection of changes in hydrologic and climatic time series. Stationarity can be assessed using the autocorrelation function, but this is not yet common practice in hydrology and climate. Here, we use a global land-based gridded annual precipitation (hereafter P) database (1940–2009) and find that the lag 1 autocorrelation coefficient is statistically significant at around 14% of the global land surface, implying nonstationary behavior (90% confidence). In contrast, around 76% of the global land surface shows little or no change, implying stationary behavior. We use these results to assess change in the observed P over the most recent decade of the database. We find that the changes for most (84%) grid boxes are within the plausible bounds of no significant change at the 90% CI. The results emphasize the importance of adequately accounting for natural variability when assessing change.

Depth-area-duration characteristics of storm rainfall in Texas using Multi-Sensor Precipitation Estimates

NASA Astrophysics Data System (ADS)

McEnery, J. A.; Jitkajornwanich, K.

2012-12-01

This presentation will describe the methodology and overall system development by which a benchmark dataset of precipitation information has been used to characterize the depth-area-duration relations in heavy rain storms occurring over regions of Texas. Over the past two years project investigators along with the National Weather Service (NWS) West Gulf River Forecast Center (WGRFC) have developed and operated a gateway data system to ingest, store, and disseminate NWS multi-sensor precipitation estimates (MPE). As a pilot project of the Integrated Water Resources Science and Services (IWRSS) initiative, this testbed uses a Standard Query Language (SQL) server to maintain a full archive of current and historic MPE values within the WGRFC service area. These time series values are made available for public access as web services in the standard WaterML format. Having this volume of information maintained in a comprehensive database now allows the use of relational analysis capabilities within SQL to leverage these multi-sensor precipitation values and produce a valuable derivative product. The area of focus for this study is North Texas and will utilize values that originated from the West Gulf River Forecast Center (WGRFC); one of three River Forecast Centers currently represented in the holdings of this data system. Over the past two decades, NEXRAD radar has dramatically improved the ability to record rainfall. The resulting hourly MPE values, distributed over an approximate 4 km by 4 km grid, are considered by the NWS to be the "best estimate" of rainfall. The data server provides an accepted standard interface for internet access to the largest time-series dataset of NEXRAD based MPE values ever assembled. An automated script has been written to search and extract storms over the 18 year period of record from the contents of this massive historical precipitation database. Not only can it extract site-specific storms, but also duration-specific storms and storms separated by user defined inter-event periods. A separate storm database has been created to store the selected output. By storing output within tables in a separate database, we can make use of powerful SQL capabilities to perform flexible pattern analysis. Previous efforts have made use of historic data from limited clusters of irregularly spaced physical gauges. Spatial extent of the observational network has been a limiting factor. The relatively dense distribution of MPE provides a virtual mesh of observations stretched over the landscape. This work combines a unique hydrologic data resource with programming and database analysis to characterize storm depth-area-duration relationships.

The IVTANTHERMO-Online database for thermodynamic properties of individual substances with web interface

NASA Astrophysics Data System (ADS)

Belov, G. V.; Dyachkov, S. A.; Levashov, P. R.; Lomonosov, I. V.; Minakov, D. V.; Morozov, I. V.; Sineva, M. A.; Smirnov, V. N.

2018-01-01

The database structure, main features and user interface of an IVTANTHERMO-Online system are reviewed. This system continues the series of the IVTANTHERMO packages developed in JIHT RAS. It includes the database for thermodynamic properties of individual substances and related software for analysis of experimental results, data fitting, calculation and estimation of thermodynamical functions and thermochemistry quantities. In contrast to the previous IVTANTHERMO versions it has a new extensible database design, the client-server architecture, a user-friendly web interface with a number of new features for online and offline data processing.

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

Grahn, D.; Wright, B.J.; Carnes, B.A.

A research reactor for exclusive use in experimental radiobiology was designed and built at Argonne National Laboratory in the 1960`s. It was located in a special addition to Building 202, which housed the Division of Biological and Medical Research. Its location assured easy access for all users to the animal facilities, and it was also near the existing gamma-irradiation facilities. The water-cooled, heterogeneous 200-kW(th) reactor, named JANUS, became the focal point for a range of radiobiological studies gathered under the rubic of {open_quotes}the JANUS program{close_quotes}. The program ran from about 1969 to 1992 and included research at all levels ofmore » biological organization, from subcellular to organism. More than a dozen moderate- to large-scale studies with the B6CF{sub 1} mouse were carried out; these focused on the late effects of whole-body exposure to gamma rays or fission neutrons, in matching exposure regimes. In broad terms, these studies collected data on survival and on the pathology observed at death. A deliberate effort was made to establish the cause of death. This archieve describes these late-effects studies and their general findings. The database includes exposure parameters, time of death, and the gross pathology and histopathology in codified form. A series of appendices describes all pathology procedures and codes, treatment or irradiation codes, and the manner in which the data can be accessed in the ORACLE database management system. A series of tables also presents summaries of the individual experiments in terms of radiation quality, sample sizes at entry, mean survival times by sex, and number of gross pathology and histopathology records.« less

Death following partner bereavement: A self-controlled case series analysis.

PubMed

King, Michael; Lodwick, Rebecca; Jones, Rebecca; Whitaker, Heather; Petersen, Irene

2017-01-01

There is mixed evidence that older people bereaved of a spouse or partner are at risk of adverse outcomes. The main difficulty is to take account of other explanatory factors. We tested for an association between a patient's death and the timing of any bereavement of a cohabitee. Self-controlled case series study in which each case serves as his or her own control and which thereby accounts for all fixed measurable and unmeasurable confounders. We used the Health Improvement Network (THIN) primary care database to identify patients who died aged 50-99 years during the period 2003 to 2014. We used the household identifier in the database to determine whether they had an opposite sex cohabitee at the start of the observation period. 38,773 men and 23,396 women who had died and who had a cohabitee at the start of the observation period, were identified and included in male and female cohorts respectively. A higher risk of death was found in the 24 months after the death of the cohabitee than in the time classified as unexposed. The greatest risk was during the first 3 months after the death of the cohabitee (age-adjusted incidence rate ratio [IRR] 1.63, 95% CI 1.45-1.83 in the male cohort, and IRR 1.70, 95% CI 1.52-1.90 in the female cohort). Risk of death in men or women was significantly higher after the death of a cohabitee and this was greatest in the first three months of bereavement. We need more evidence on the effectiveness of interventions to reduce this increased mortality.

NutriSonic web expert system for meal management and nutrition counseling with nutrient time-series analysis, e-food exchange and easy data transition.

PubMed

Hong, Soon-Myung; Cho, Jee-Ye; Lee, Jin-Hee; Kim, Gon; Kim, Min-Chan

2008-01-01

This study was conducted to develop the NutriSonic Web Expert System for Meal Management and Nutrition Counseling with Analysis of User's Nutritive Changes of selected days and food exchange information with easy data transition. This program manipulates a food, menu and meal and search database that has been developed. Also, the system provides a function to check the user's nutritive change of selected days. Users can select a recommended general and therapeutic menu using this system. NutriSonic can analyze nutrients and e-food exchange ("e" means the food exchange data base calculated by a computer program) in menus and meals. The expert can insert and store a meal database and generate the synthetic information of age, sex and therapeutic purpose of disease. With investigation and analysis of the user's needs, the meal planning program on the internet has been continuously developed. Users are able to follow up their nutritive changes with nutrient information and ratio of 3 major energy nutrients. Also, users can download another data format like Excel files (.xls) for analysis and verify their nutrient time-series analysis. The results of analysis are presented quickly and accurately. Therefore it can be used by not only usual people, but also by dietitians and nutritionists who take charge of making a menu and experts in the field of food and nutrition. It is expected that the NutriSonic Web Expert System can be useful for nutrition education, nutrition counseling and expert meal management.

Rapid sample classification using an open port sampling interface coupled with liquid introduction atmospheric pressure ionization mass spectrometry

DOE PAGES

Van Berkel, Gary J.; Kertesz, Vilmos

2016-11-15

An “Open Access”-like mass spectrometric platform to fully utilize the simplicity of the manual open port sampling interface for rapid characterization of unprocessed samples by liquid introduction atmospheric pressure ionization mass spectrometry has been lacking. The in-house developed integrated software with a simple, small and relatively low-cost mass spectrometry system introduced here fills this void. Software was developed to operate the mass spectrometer, to collect and process mass spectrometric data files, to build a database and to classify samples using such a database. These tasks were accomplished via the vendorprovided software libraries. Sample classification based on spectral comparison utilized themore » spectral contrast angle method. As a result, using the developed software platform near real-time sample classification is exemplified using a series of commercially available blue ink rollerball pens and vegetable oils. In the case of the inks, full scan positive and negative ion ESI mass spectra were both used for database generation and sample classification. For the vegetable oils, full scan positive ion mode APCI mass spectra were recorded. The overall accuracy of the employed spectral contrast angle statistical model was 95.3% and 98% in case of the inks and oils, respectively, using leave-one-out cross-validation. In conclusion, this work illustrates that an open port sampling interface/mass spectrometer combination, with appropriate instrument control and data processing software, is a viable direct liquid extraction sampling and analysis system suitable for the non-expert user and near real-time sample classification via database matching.« less

Rapid sample classification using an open port sampling interface coupled with liquid introduction atmospheric pressure ionization mass spectrometry

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

Van Berkel, Gary J.; Kertesz, Vilmos

An “Open Access”-like mass spectrometric platform to fully utilize the simplicity of the manual open port sampling interface for rapid characterization of unprocessed samples by liquid introduction atmospheric pressure ionization mass spectrometry has been lacking. The in-house developed integrated software with a simple, small and relatively low-cost mass spectrometry system introduced here fills this void. Software was developed to operate the mass spectrometer, to collect and process mass spectrometric data files, to build a database and to classify samples using such a database. These tasks were accomplished via the vendorprovided software libraries. Sample classification based on spectral comparison utilized themore » spectral contrast angle method. As a result, using the developed software platform near real-time sample classification is exemplified using a series of commercially available blue ink rollerball pens and vegetable oils. In the case of the inks, full scan positive and negative ion ESI mass spectra were both used for database generation and sample classification. For the vegetable oils, full scan positive ion mode APCI mass spectra were recorded. The overall accuracy of the employed spectral contrast angle statistical model was 95.3% and 98% in case of the inks and oils, respectively, using leave-one-out cross-validation. In conclusion, this work illustrates that an open port sampling interface/mass spectrometer combination, with appropriate instrument control and data processing software, is a viable direct liquid extraction sampling and analysis system suitable for the non-expert user and near real-time sample classification via database matching.« less

Impacts of ENSO on global hydrology

NASA Astrophysics Data System (ADS)

Ward, P. J.; Eisner, S.; Flörke, M.; Kummu, M.

2012-04-01

The economic consequences of flooding are huge, as exemplified by recent major floods in Thailand, Pakistan, and Australia. Moreover, research shows that economic losses due to flooding have increased dramatically in recent decades. Whilst much research is being carried out to assess how this may be related to socioeconomic development (increased exposure to floods) or climate change (increased hazard), the role of interannual climate variability is poorly understood at the global scale. We provide the first global assessment of the sensitivity of extreme global river discharge to the El Niño Southern Oscillation (ENSO). Past studies have either: (a) assessed this at the local scale; or (b) assessed only global correlations between ENSO and mean river discharge. Firstly, we used a daily observed discharge dataset for 622 gauging stations (from the GRDC database), and assessed and mapped correlations and sensitivities between these time-series and several indices of ENSO. We found that, on average, for the stations studied ENSO has a greater impact on annual high-flow events than on mean annual discharge, especially in the extra-tropics. However, the geographical coverage of the dataset is poor in some regions, and is highly skewed towards certain areas (e.g. North America, Europe, and eastern Australia). This renders a truly global assessment of ENSO impacts impossible based on these observed time-series. Hence, we are also using a modelling approach to estimate correlations and sensitivities in all basins, gauged and ungauged. For this, we are using a gridded time-series of modelled daily discharge from the EU-WATCH project, and analysing relationships between these time-series (per grid-cell) and indices of ENSO. This allows for the first truly global assessment of the impact of ENSO variability on river discharge; these analyses are ongoing. Of course, this approach entails its own problems; the use of global hydrological models to derive daily discharge time-series introduces its own uncertainties. Hence, the results derived from the modelling exercise will be validated against the results derived from the observed data. The quantification of ENSO impacts provides relevant information for water management, allowing the identification of problem areas and providing a basis for risk assessments.

Changes in the NDVI of Boreal Forests over the period 1984 to 2003 measured using time series of Landsat TM/ETM+ surface reflectance and the GIMMS AVHRR NDVI record.

NASA Astrophysics Data System (ADS)

McMillan, A. M.; Rocha, A. V.; Goulden, M. L.

2006-12-01

There is a prevailing opinion that the boreal landscape is undergoing change as a result of warming temperatures leading to earlier springs, greater forest fire frequency and possibly CO2 fertilization. One widely- used line of evidence is the GIMMS AVHRR NDVI record. Several studies suggest increasing rates of photosynthesis in boreal forests from 1982 to 1991 (based on NDVI increases) while others suggest declining photosynthesis from 1996 to 2003. We suspect that a portion of these changes are due to the successional stage of the forests. We compiled a time-series of atmospherically-corrected Landsat TM/ETM+ images spanning the period 1984 to 2003 over the BOREAS Northern Study Area and compared spatial and temporal patterns of NDVI between the two records. The Landsat time series is higher resolution and, together with the Canadian Fire Service Large Fire Database, provides stand-age information. We then (1) analyzed the agreement between the Landsat and GIMMS AVHRR time series; (2) determined how the stage of forest succession affected NDVI; (3) assessed how the calculation method of annual averages of NDVI affects decadal-scale trends. The agreement between the Landsat and the AVHRR was reasonable although the depression of NDVI associated with the aerosols from the Pinatubo volcano was greater in the GIMMS time series. Pixels containing high proportions of stands burned within a decade of the observation period showed very high gains in NDVI while the more mature stands were constant. While NDVI appears to exhibit a large sensitivity to the presence of snow, the choice of a May to September averaging period for NDVI over a June to August averaging period did not affect the interannual patterns in NDVI at this location because the snow pack was seldom present in either of these periods. Knowledge of the spatial and temporal patterns of wild fire will prove useful in interpreting trends of remotely-sensed proxies of photosynthesis.

An open-access database of grape harvest dates for climate research: data description and quality assessment

NASA Astrophysics Data System (ADS)

Daux, V.; Garcia de Cortazar-Atauri, I.; Yiou, P.; Chuine, I.; Garnier, E.; Ladurie, E. Le Roy; Mestre, O.; Tardaguila, J.

2012-09-01

We present an open-access dataset of grape harvest dates (GHD) series that has been compiled from international, French and Spanish literature and from unpublished documentary sources from public organizations and from wine-growers. As of June 2011, this GHD dataset comprises 380 series mainly from France (93% of the data) as well as series from Switzerland, Italy, Spain and Luxemburg. The series have variable length (from 1 to 479 data, mean length of 45 data) and contain gaps of variable sizes (mean ratio of observations/series length of 0.74). The longest and most complete ones are from Burgundy, Switzerland, Southern Rhône valley, Jura and Ile-de-France. The most ancient harvest date of the dataset is in 1354 in Burgundy. The GHD series were grouped into 27 regions according to their location, to geomorphological and geological criteria, and to past and present grape varieties. The GHD regional composite series (GHD-RCS) were calculated and compared pairwise to assess their reliability assuming that series close to one another are highly correlated. Most of the pairwise correlations are significant (p-value < 0.001) and strong (mean pairwise correlation coefficient of 0.58). As expected, the correlations tend to be higher when the vineyards are closer. The highest correlation (R = 0.91) is obtained between the High Loire Valley and the Ile-de-France GHD-RCS. The strong dependence of the vine cycle on temperature and, therefore, the strong link between the harvest dates and the temperature of the growing season was also used to test the quality of the GHD series. The strongest correlations are obtained between the GHD-RCS and the temperature series of the nearest weather stations. Moreover, the GHD-RCS/temperature correlation maps show spatial patterns similar to temperature correlation maps. The stability of the correlations over time is explored. The most striking feature is their generalised deterioration at the late 19th-early 20th century. The possible effects on GHD of the phylloxera crisis, which took place at this time, are discussed. The median of all the standardized GHD-RCS was calculated. The distribution of the extreme years of this general series is not homogenous. Extremely late years all occur during a two-century long time window from the early 17th to the early 19th century, while extremely early years are frequent during the 16th and since the mid-19th century.

Existing and Emerging Technologies in Education: A Descriptive Overview. CREATE Monograph Series.

ERIC Educational Resources Information Center

Bakke, Thomas W.

Second in a series of six monographs on the use of new technologies in the instruction of learning disabled students, the paper offers a descriptive overview of new technologies. Topics addressed include the following: (1) techniques for sharing computer resources (including aspects of networking, sharing information through databases, and the use…

Global Autocorrelation Scales of the Partial Pressure of Oceanic CO2

NASA Technical Reports Server (NTRS)

Li, Zhen; Adamec, David; Takahashi, Taro; Sutherland, Stewart C.

2004-01-01

A global database of approximately 1.7 million observations of the partial pressure of carbon dioxide in surface ocean waters (pCO2) collected between 1970 and 2003 is used to estimate its spatial autocorrelation structure. The patterns of the lag distance where the autocorrelation exceeds 0.8 is similar to patterns in the spatial distribution of the first baroclinic Rossby radius of deformation indicating that ocean circulation processes play a significant role in determining the spatial variability of pCO2. For example, the global maximum of the distance at which autocorrelations exceed 0.8 averages about 140 km in the equatorial Pacific. Also, the lag distance at which the autocorrelation exceed 0.8 is greater in the vicinity of the Gulf Stream than it is near the Kuroshio, approximately 50 km near the Gulf Stream as opposed to 20 km near the Kuroshio. Separate calculations for times when the sun is north and south of the equator revealed no obvious seasonal dependence of the spatial autocorrelation scales. The pCO2 measurements at Ocean Weather Station (OWS) 'P', in the eastern subarctic Pacific (50 N, 145 W) is the only fixed location where an uninterrupted time series of sufficient length exists to calculate a meaningful temporal autocorrelation function for lags greater than a few days. The estimated temporal autocorrelation function at OWS 'P', is highly variable. A spectral analysis of the longest four pCO2 time series indicates a high level of variability occurring over periods from the atmospheric synoptic to the maximum length of the time series, in this case 42 days. It is likely that a relative peak in variability with a period of 3-6 days is related to atmospheric synoptic period variability and ocean mixing events due to wind stirring. However, the short length of available time series makes identifying temporal relationships between pCO2 and atmospheric or ocean processes problematic.

National Geomagnetism Program: Current Status & Five-Year Plan, 2006-2010

USGS Publications Warehouse

Love, Jeffrey J.

2006-01-01

Executive Summary: The U.S. Geological Survey's Geomagnetism Program serves the scientific community and the broader public by collecting and distributing magnetometer data from an array of ground-based observatories and by conducting scientific analysis on those data. Preliminary, variational time-series can be collected and distributed in near-real time, while fully calibrated, absolute time-series are distributed after processing. The data are used by the civilian and military parts of the Federal Government, by private industry, and by academia, for a wide variety of purposes of both immediately practical importance and long-term scientific interest, including space-weather diagnosis and related hazard mitigation, mapping of the magnetic field and measurement of its activity, and research on the nature of the Earth's interior and the near-Earth space environment. This document reviews the current status of the Program, in terms of its situation within the Government and within the scientific community; summarizes the Program's operations, its staffing situation, and its facilities; describes the diversity of uses of Program magnetometer data; and presents a plan for the next 5 years for enhancing the Program's data-based services, developing products, and conducting scientific research.

On the Analysis of the Climatology of Cloudiness of the Arabian Peninsula

NASA Astrophysics Data System (ADS)

Yousef, L. A.; Temimi, M.

2015-12-01

This study aims to determine the climatology of cloudiness over the Arabian Peninsula. The determined climatology will assist solar energy resource assessment in the region. The seasonality of cloudiness and its spatial variability will also help guide several cloud seeding operational experiments in the region. Cloud properties from the International Satellite Cloud Climatology Project (ISCCP) database covering the time period from 1983 through 2009 are analyzed. Time series of low, medium, high, and total cloud amounts are investigated, in addition to cloud optical depth and total column water vapor. Initial results show significant decreasing trends in the total and middle cloud amounts, both annually and seasonally, at a 95% confidence interval. The relationship between cloud amounts and climate oscillations known to affect the region is explored. Climate indices exhibiting significant correlations with the total cloud amounts include the Pacific Decadal Oscillation (PDO) index. The study also includes a focus on the United Arab Emirates (UAE), comparing the inferred cloudiness data to in situ rainfall measurements taken from rain gauges across the UAE. To assess the impact of cloudiness on solar power resources in the country, time series of cloud amounts and Direct Normal Irradiance (DNI), obtained from the UAE Solar Atlas, are compared.

Solubility Database

National Institute of Standards and Technology Data Gateway

SRD 106 IUPAC-NIST Solubility Database (Web, free access)   These solubilities are compiled from 18 volumes (Click here for List) of the International Union for Pure and Applied Chemistry(IUPAC)-NIST Solubility Data Series. The database includes liquid-liquid, solid-liquid, and gas-liquid systems. Typical solvents and solutes include water, seawater, heavy water, inorganic compounds, and a variety of organic compounds such as hydrocarbons, halogenated hydrocarbons, alcohols, acids, esters and nitrogen compounds. There are over 67,500 solubility measurements and over 1800 references.

Recent NASA Wake-Vortex Flight Tests, Flow-Physics Database and Wake-Development Analysis

NASA Technical Reports Server (NTRS)

Vicroy, Dan D.; Vijgen, Paul M.; Reimer, Heidi M.; Gallegos, Joey L.; Spalart, Philippe R.

1998-01-01

A series of flight tests over the ocean of a four engine turboprop airplane in the cruise configuration have provided a data set for improved understanding of wake vortex physics and atmospheric interaction. An integrated database has been compiled for wake characterization and validation of wake-vortex computational models. This paper describes the wake-vortex flight tests, the data processing, the database development and access, and results obtained from preliminary wake-characterization analysis using the data sets.

Database Management System

NASA Technical Reports Server (NTRS)

1990-01-01

In 1981 Wayne Erickson founded Microrim, Inc, a company originally focused on marketing a microcomputer version of RIM (Relational Information Manager). Dennis Comfort joined the firm and is now vice president, development. The team developed an advanced spinoff from the NASA system they had originally created, a microcomputer database management system known as R:BASE 4000. Microrim added many enhancements and developed a series of R:BASE products for various environments. R:BASE is now the second largest selling line of microcomputer database management software in the world.

Improving prehospital trauma care in Rwanda through continuous quality improvement: an interrupted time series analysis.

PubMed

Scott, John W; Nyinawankusi, Jeanne D'Arc; Enumah, Samuel; Maine, Rebecca; Uwitonze, Eric; Hu, Yihan; Kabagema, Ignace; Byiringiro, Jean Claude; Riviello, Robert; Jayaraman, Sudha

2017-07-01

Injury is a major cause of premature death and disability in East Africa, and high-quality pre-hospital care is essential for optimal trauma outcomes. The Rwandan pre-hospital emergency care service (SAMU) uses an electronic database to evaluate and optimize pre-hospital care through a continuous quality improvement programme (CQIP), beginning March 2014. The SAMU database was used to assess pre-hospital quality metrics including supplementary oxygen for hypoxia (O2), intravenous fluids for hypotension (IVF), cervical collar placement for head injuries (c-collar), and either splinting (splint) or administration of pain medications (pain) for long bone fractures. Targets of >90% were set for each metric and daily team meetings and monthly feedback sessions were implemented to address opportunities for improvement. These five pre-hospital quality metrics were assessed monthly before and after implementation of the CQIP. Met and unmet needs for O2, IVF, and c-collar were combined into a summative monthly SAMU Trauma Quality Scores (STQ score). An interrupted time series linear regression model compared the STQ score during 14 months before the CQIP implementation to the first 14 months after. During the 29-month study period 3,822 patients met study criteria. 1,028 patients needed one or more of the five studied interventions during the study period. All five endpoints had a significant increase between the pre-CQI and post-CQI periods (p<0.05 for all), and all five achieved a post-CQI average of at least 90% completion. The monthly composite STQ scores ranged from 76.5 to 97.9 pre-CQI, but tightened to 86.1-98.7 during the post-CQI period. Interrupted time series analysis of the STQ score showed that CQI programme led to both an immediate improvement of +6.1% (p=0.017) and sustained monthly improvements in care delivery-improving at a rate of 0.7% per month (p=0.028). The SAMU experience demonstrates the utility of a responsive, data-driven quality improvement programme to yield significant immediate and sustained improvements in pre-hospital care for trauma in Rwanda. This programme may be used as an example for additional efforts engaging frontline staff with real-time data feedback in order to rapidly translate data collection efforts into improved care for the injured in a resource-limited setting. Copyright © 2017 Elsevier Ltd. All rights reserved.

MTF Database: A Repository of Students' Academic Performance Measurements for the Development of Techniques for Evaluating Team Functioning

ERIC Educational Resources Information Center

Hsiung, Chin-Min; Zheng, Xiang-Xiang

2015-01-01

The Measurements for Team Functioning (MTF) database contains a series of student academic performance measurements obtained at a national university in Taiwan. The measurements are acquired from unit tests and homework tests performed during a core mechanical engineering course, and provide an objective means of assessing the functioning of…

Improving Child Outcomes with Data-Based Decision Making: Interpreting and Using Data

ERIC Educational Resources Information Center

Gischlar, Karen L.; Hojnoski, Robin L.; Missall, Kristen N.

2009-01-01

This article is the third in a series describing the steps in using data-based decision making to inform intervention and, ultimately, improve outcomes for children. Whereas the first two articles describe identifying and measuring important behaviors to target for intervention, the purpose of this article is to describe basic considerations in…

Dimensions of clinical nurse specialist work in the UK.

PubMed

Leary, Alison; Crouch, Heather; Lezard, Anthony; Rawcliffe, Chris; Boden, Louise; Richardson, Alison

To model the work of clinical nurse specialists (CNSs) in the UK. This article examines data mined as part of a national project. The Pandora database was initially collected on a Microsoft Office Access database and subsequently, a Structured Query Language database in several iterations from June 2006 to September 2008. Pandora recorded CNS activity as a series of events with eight dimensions to each event. Data from this were mined to examine the complexity of CNS work. This study represents the work of 463 CNSs over 2,778 days in England, Scotland and Wales. Clinical work, including physical assessment, referral, symptom control and 'rescue' work, accounted for a large part of the CNS's role. Administration was the second highest workload, with about half of these administrative tasks identified as being suitable for secretarial staff to undertake. Research, education and consultation accounted for less time. A significant proportion of the nurses' clinical work is undertaken by telephone. CNSs in this study spent much of their time doing complex clinical work. Payment by Results (Department of Health 2006) should recognise the work undertaken by CNSs, particularly that done on the telephone. Complex clinical work by CNSs takes place in many different contexts using a wide range of interventions. The role of the CNS is complex and diverse, making comparisons of it difficult. More research needs to be done in relation to quality, safety and efficiency.

The new IAGOS Database Portal

NASA Astrophysics Data System (ADS)

Boulanger, Damien; Gautron, Benoit; Thouret, Valérie; Fontaine, Alain

2016-04-01

IAGOS (In-service Aircraft for a Global Observing System) is a European Research Infrastructure which aims at the provision of long-term, regular and spatially resolved in situ observations of the atmospheric composition. IAGOS observation systems are deployed on a fleet of commercial aircraft. The IAGOS database is an essential part of the global atmospheric monitoring network. It contains IAGOS-core data and IAGOS-CARIBIC (Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container) data. The IAGOS Database Portal (http://www.iagos.fr, damien.boulanger@obs-mip.fr) is part of the French atmospheric chemistry data center AERIS (http://www.aeris-data.fr). The new IAGOS Database Portal has been released in December 2015. The main improvement is the interoperability implementation with international portals or other databases in order to improve IAGOS data discovery. In the frame of the IGAS project (IAGOS for the Copernicus Atmospheric Service), a data network has been setup. It is composed of three data centers: the IAGOS database in Toulouse; the HALO research aircraft database at DLR (https://halo-db.pa.op.dlr.de); and the CAMS data center in Jülich (http://join.iek.fz-juelich.de). The CAMS (Copernicus Atmospheric Monitoring Service) project is a prominent user of the IGAS data network. The new portal provides improved and new services such as the download in NetCDF or NASA Ames formats, plotting tools (maps, time series, vertical profiles, etc.) and user management. Added value products are available on the portal: back trajectories, origin of air masses, co-location with satellite data, etc. The link with the CAMS data center, through JOIN (Jülich OWS Interface), allows to combine model outputs with IAGOS data for inter-comparison. Finally IAGOS metadata has been standardized (ISO 19115) and now provides complete information about data traceability and quality.

Mining Claim Activity on Federal Land for the Period 1976 through 2003

USGS Publications Warehouse

Causey, J. Douglas

2005-01-01

Previous reports on mining claim records provided information and statistics (number of claims) using data from the U.S. Bureau of Land Management's (BLM) Mining Claim Recordation System. Since that time, BLM converted their mining claim data to the Legacy Repost 2000 system (LR2000). This report describes a process to extract similar statistical data about mining claims from LR2000 data using different software and procedures than were used in the earlier work. A major difference between this process and the previous work is that every section that has a mining claim record is assigned a value. This is done by proportioning a claim between each section in which it is recorded. Also, the mining claim data in this report includes all BLM records, not just the western states. LR2000 mining claim database tables for the United States were provided by BLM in text format and imported into a Microsoft? Access2000 database in January, 2004. Data from two tables in the BLM LR2000 database were summarized through a series of database queries to determine a number that represents active mining claims in each Public Land Survey (PLS) section for each of the years from 1976 to 2002. For most of the area, spatial databases are also provided. The spatial databases are only configured to work with the statistics provided in the non-spatial data files. They are suitable for geographic information system (GIS)-based regional assessments at a scale of 1:100,000 or smaller (for example, 1:250,000).

Molecular Modeling and Experimental Study of Nonlinear Optical Compounds: Mono-Substituted Derivatives of Dicyanovinylbenzene

NASA Technical Reports Server (NTRS)

Timofeeva, Tatyana V.; Nesterov, Vladimir N.; Antipin, Mikhael Y.; Clark, R. D.; Sanghadasa, M.; Cardelino, B. H.; Moore, C. E.; Frazier, Donald O.

2000-01-01

A search for potential nonlinear optical (NLO) compounds has been performed using the Cambridge Structural Database and molecular modeling. We have studied a series of mono-substituted derivatives of dicyanovinylbenzene as the NLO properties of one of its derivatives (o-methoxy-dicyanovinylbenzene, DIVA) were described earlier. The molecular geometry in the series of the compounds studied was investigated with an X- ray analysis and discussed along with results of molecular mechanics and ab initio quantum chemical calculations. The influence of crystal packing on the molecular planarity has been revealed. Two new compounds from the series studied were found to be active for second harmonic generation (SHG) in the powder. The measurements of SHG efficiency have shown that the o-F- and p-Cl-derivatives of dicyanovinylbenzene are about 10 and 20- times more active than urea, respectively. The peculiarities of crystal structure formation in the framework of balance between the van der Waals and electrostatic interactions have been discussed. The crystal morphology of DIVA and two new SHG-active compounds have been calculated on the basis of their known crystal structures.

Molecular surface representation using 3D Zernike descriptors for protein shape comparison and docking.

PubMed

Kihara, Daisuke; Sael, Lee; Chikhi, Rayan; Esquivel-Rodriguez, Juan

2011-09-01

The tertiary structures of proteins have been solved in an increasing pace in recent years. To capitalize the enormous efforts paid for accumulating the structure data, efficient and effective computational methods need to be developed for comparing, searching, and investigating interactions of protein structures. We introduce the 3D Zernike descriptor (3DZD), an emerging technique to describe molecular surfaces. The 3DZD is a series expansion of mathematical three-dimensional function, and thus a tertiary structure is represented compactly by a vector of coefficients of terms in the series. A strong advantage of the 3DZD is that it is invariant to rotation of target object to be represented. These two characteristics of the 3DZD allow rapid comparison of surface shapes, which is sufficient for real-time structure database screening. In this article, we review various applications of the 3DZD, which have been recently proposed.

Applications of functional data analysis: A systematic review.

PubMed

Ullah, Shahid; Finch, Caroline F

2013-03-19

Functional data analysis (FDA) is increasingly being used to better analyze, model and predict time series data. Key aspects of FDA include the choice of smoothing technique, data reduction, adjustment for clustering, functional linear modeling and forecasting methods. A systematic review using 11 electronic databases was conducted to identify FDA application studies published in the peer-review literature during 1995-2010. Papers reporting methodological considerations only were excluded, as were non-English articles. In total, 84 FDA application articles were identified; 75.0% of the reviewed articles have been published since 2005. Application of FDA has appeared in a large number of publications across various fields of sciences; the majority is related to biomedicine applications (21.4%). Overall, 72 studies (85.7%) provided information about the type of smoothing techniques used, with B-spline smoothing (29.8%) being the most popular. Functional principal component analysis (FPCA) for extracting information from functional data was reported in 51 (60.7%) studies. One-quarter (25.0%) of the published studies used functional linear models to describe relationships between explanatory and outcome variables and only 8.3% used FDA for forecasting time series data. Despite its clear benefits for analyzing time series data, full appreciation of the key features and value of FDA have been limited to date, though the applications show its relevance to many public health and biomedical problems. Wider application of FDA to all studies involving correlated measurements should allow better modeling of, and predictions from, such data in the future especially as FDA makes no a priori age and time effects assumptions.

Applications of functional data analysis: A systematic review

PubMed Central

2013-01-01

Background Functional data analysis (FDA) is increasingly being used to better analyze, model and predict time series data. Key aspects of FDA include the choice of smoothing technique, data reduction, adjustment for clustering, functional linear modeling and forecasting methods. Methods A systematic review using 11 electronic databases was conducted to identify FDA application studies published in the peer-review literature during 1995–2010. Papers reporting methodological considerations only were excluded, as were non-English articles. Results In total, 84 FDA application articles were identified; 75.0% of the reviewed articles have been published since 2005. Application of FDA has appeared in a large number of publications across various fields of sciences; the majority is related to biomedicine applications (21.4%). Overall, 72 studies (85.7%) provided information about the type of smoothing techniques used, with B-spline smoothing (29.8%) being the most popular. Functional principal component analysis (FPCA) for extracting information from functional data was reported in 51 (60.7%) studies. One-quarter (25.0%) of the published studies used functional linear models to describe relationships between explanatory and outcome variables and only 8.3% used FDA for forecasting time series data. Conclusions Despite its clear benefits for analyzing time series data, full appreciation of the key features and value of FDA have been limited to date, though the applications show its relevance to many public health and biomedical problems. Wider application of FDA to all studies involving correlated measurements should allow better modeling of, and predictions from, such data in the future especially as FDA makes no a priori age and time effects assumptions. PMID:23510439

Visualization and Time-Series Analysis of Ground-Water Data for C-Area, Savannah River Site, South Carolina, 1984-2004

USGS Publications Warehouse

Conrads, Paul; Roehl, Edwin A.; Daamen, Ruby C.; Chapelle, Francis H.; Lowery, Mark A.; Mundry, Uwe H.

2007-01-01

In 2004, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, initiated a study of historical ground-water data of C-Area on the Savannah River Site in South Carolina. The soils and ground water at C-Area are contaminated with high concentrations of trichloroethylene and lesser amounts of tetrachloroethylene. The objectives of the investigation were (1) to analyze the historical data to determine if data-mining techniques could be applied to the historical database to ascertain whether natural attenuation of recalcitrant contaminants, such as volatile organic compounds, is occurring and (2) to determine whether inferential (surrogate) analytes could be used for more cost-effective monitoring. Twenty-one years of data (1984-2004) were collected from 396 wells in the study area and converted from record data to time-series data for analysis. A Ground-Water Data Viewer was developed to allow users to spatially and temporally visualize the analyte data. Overall, because the data were temporally and spatially sparse, data analysis was limited to only qualitative descriptions.

Spatial Pyramid Covariance based Compact Video Code for Robust Face Retrieval in TV-series.

PubMed

Li, Yan; Wang, Ruiping; Cui, Zhen; Shan, Shiguang; Chen, Xilin

2016-10-10

We address the problem of face video retrieval in TV-series which searches video clips based on the presence of specific character, given one face track of his/her. This is tremendously challenging because on one hand, faces in TV-series are captured in largely uncontrolled conditions with complex appearance variations, and on the other hand retrieval task typically needs efficient representation with low time and space complexity. To handle this problem, we propose a compact and discriminative representation for the huge body of video data, named Compact Video Code (CVC). Our method first models the face track by its sample (i.e., frame) covariance matrix to capture the video data variations in a statistical manner. To incorporate discriminative information and obtain more compact video signature suitable for retrieval, the high-dimensional covariance representation is further encoded as a much lower-dimensional binary vector, which finally yields the proposed CVC. Specifically, each bit of the code, i.e., each dimension of the binary vector, is produced via supervised learning in a max margin framework, which aims to make a balance between the discriminability and stability of the code. Besides, we further extend the descriptive granularity of covariance matrix from traditional pixel-level to more general patchlevel, and proceed to propose a novel hierarchical video representation named Spatial Pyramid Covariance (SPC) along with a fast calculation method. Face retrieval experiments on two challenging TV-series video databases, i.e., the Big Bang Theory and Prison Break, demonstrate the competitiveness of the proposed CVC over state-of-the-art retrieval methods. In addition, as a general video matching algorithm, CVC is also evaluated in traditional video face recognition task on a standard Internet database, i.e., YouTube Celebrities, showing its quite promising performance by using an extremely compact code with only 128 bits.

Time domain nonlinear SMA damper force identification approach and its numerical validation

NASA Astrophysics Data System (ADS)

Xin, Lulu; Xu, Bin; He, Jia

2012-04-01

Most of the currently available vibration-based identification approaches for structural damage detection are based on eigenvalues and/or eigenvectors extracted from vibration measurements and, strictly speaking, are only suitable for linear system. However, the initiation and development of damage in engineering structures under severe dynamic loadings are typical nonlinear procedure. Studies on the identification of restoring force which is a direct indicator of the extent of the nonlinearity have received increasing attention in recent years. In this study, a date-based time domain identification approach for general nonlinear system was developed. The applied excitation and the corresponding response time series of the structure were used for identification by means of standard least-square techniques and a power series polynomial model (PSPM) which was utilized to model the nonlinear restoring force (NRF). The feasibility and robustness of the proposed approach was verified by a 2 degree-of-freedoms (DOFs) lumped mass numerical model equipped with a shape memory ally (SMA) damper mimicking nonlinear behavior. The results show that the proposed data-based time domain method is capable of identifying the NRF in engineering structures without any assumptions on the mass distribution and the topology of the structure, and provides a promising way for damage detection in the presence of structural nonlinearities.

Long-term Trend of Satellite-observed Chlorophyll-a Concentration Variations in the East/Japan Sea

NASA Astrophysics Data System (ADS)

Park, J. E.; PARK, K. A.

2016-02-01

Long-term time-series of satellite ocean color data enable us to analyze the effects of climate change on ocean ecosystem through chlorophyll-a concentration as a proxy for phytoplankton biomass. In this study, we constructed a 17 year-long time-series dataset (1998-2014) of chlorophyll-a concentration by combining SeaWiFS (Obrview-2, 1997-2010) and MODIS (Aqua, 2002-present) data in the East Sea (Japan Sea). Several types of errors such as anonymously high values (a speckle error), stripe-like patterns, discrepancy originating from time gap between the two satellites were eliminated to enhance the accuracy of chlorophyll-a concentration data. The composited chlorophyll-a concentration maps, passing through the post-processing of the speckle errors, were improved significantly, by 14% of abnormal variability in maximum. Using the database, we investigated spatial and temporal variability of chlorophyll-a concentration in the East Sea. Spatial distribution of long-term trend of chlorophyll-a concentration indicated obvious distinction between northern and southern regions of the subpolar front. It revealed predominant seasonal variabilities as well as long-term changes in the timings of spring bloom. This study addresses the important role of local climate change on fast changing ecosystem of the East Sea as one of miniature oceans.

Practical analysis of tide gauges records from Antarctica

NASA Astrophysics Data System (ADS)

Galassi, Gaia; Spada, Giorgio

2015-04-01

We have collected and analyzed in a basic way the currently available time series from tide gauges deployed along the coasts of Antarctica. The database of the Permanent Service for Mean Sea Level (PSMSL) holds relative sea level information for 17 stations, which are mostly concentrated in the Antarctic Peninsula (8 out of 17). For 7 of the PSMSL stations, Revised Local Reference (RLR) monthly and yearly observations are available, spanning from year 1957.79 (Almirante Brown) to 2013.95 (Argentine Islands). For the remaining 11 stations, only metric monthly data can be obtained during the time window 1957-2013. The record length of the available time series is not generally exceeding 20 years. Remarkable exceptions are the RLR station of Argentine Island, located in the Antarctic Peninsula (AP) (time span: 1958-2013, record length: 54 years, completeness=98%), and the metric station of Syowa in East Antarctica (1975-2012, 37 years, 92%). The general quality (geographical coverage and length of record) of the time series hinders a coherent geophysical interpretation of the relative sea-level data along the coasts of Antarctica. However, in an attempt to characterize the relative sea level signals available, we have stacked (i.e., averaged) the RLR time series for the AP and for the whole Antarctica. The so obtained time series have been analyzed using simple regression in order to estimate a trend and a possible sea-level acceleration. For the AP, the the trend is 1.8 ± 0.2 mm/yr and for the whole Antarctica it is 2.1 ± 0.1 mm/yr (both during 1957-2013). The modeled values of Glacial Isostatic Adjustment (GIA) obtained with ICE-5G(VM2) using program SELEN, range between -0.7 and -1.6 mm/yr, showing that the sea-level trend recorded by tide gauges is strongly influenced by GIA. Subtracting the average GIA contribution (-1.1 mm/yr) to observed sea-level trend from the two stacks, we obtain 3.2 and 2.9 mm/yr for Antarctica and AP respectively, which are interpreted as the effect of current ice melting and steric ocean contributions. By the Ensemble Empirical Mode Decomposition method, we have detected different oscillations embedded in the sea-level signals for Antarctica and AP. This confirms previously recognized connections between the sea-level variations in Antarctica and ocean modes like the ENSO.

Time series modelling to forecast prehospital EMS demand for diabetic emergencies.

PubMed

Villani, Melanie; Earnest, Arul; Nanayakkara, Natalie; Smith, Karen; de Courten, Barbora; Zoungas, Sophia

2017-05-05

Acute diabetic emergencies are often managed by prehospital Emergency Medical Services (EMS). The projected growth in prevalence of diabetes is likely to result in rising demand for prehospital EMS that are already under pressure. The aims of this study were to model the temporal trends and provide forecasts of prehospital attendances for diabetic emergencies. A time series analysis on monthly cases of hypoglycemia and hyperglycemia was conducted using data from the Ambulance Victoria (AV) electronic database between 2009 and 2015. Using the seasonal autoregressive integrated moving average (SARIMA) modelling process, different models were evaluated. The most parsimonious model with the highest accuracy was selected. Forty-one thousand four hundred fifty-four prehospital diabetic emergencies were attended over a seven-year period with an increase in the annual median monthly caseload between 2009 (484.5) and 2015 (549.5). Hypoglycemia (70%) and people with type 1 diabetes (48%) accounted for most attendances. The SARIMA (0,1,0,12) model provided the best fit, with a MAPE of 4.2% and predicts a monthly caseload of approximately 740 by the end of 2017. Prehospital EMS demand for diabetic emergencies is increasing. SARIMA time series models are a valuable tool to allow forecasting of future caseload with high accuracy and predict increasing cases of prehospital diabetic emergencies into the future. The model generated by this study may be used by service providers to allow appropriate planning and resource allocation of EMS for diabetic emergencies.

BGFit: management and automated fitting of biological growth curves.

PubMed

Veríssimo, André; Paixão, Laura; Neves, Ana Rute; Vinga, Susana

2013-09-25

Existing tools to model cell growth curves do not offer a flexible integrative approach to manage large datasets and automatically estimate parameters. Due to the increase of experimental time-series from microbiology and oncology, the need for a software that allows researchers to easily organize experimental data and simultaneously extract relevant parameters in an efficient way is crucial. BGFit provides a web-based unified platform, where a rich set of dynamic models can be fitted to experimental time-series data, further allowing to efficiently manage the results in a structured and hierarchical way. The data managing system allows to organize projects, experiments and measurements data and also to define teams with different editing and viewing permission. Several dynamic and algebraic models are already implemented, such as polynomial regression, Gompertz, Baranyi, Logistic and Live Cell Fraction models and the user can add easily new models thus expanding current ones. BGFit allows users to easily manage their data and models in an integrated way, even if they are not familiar with databases or existing computational tools for parameter estimation. BGFit is designed with a flexible architecture that focus on extensibility and leverages free software with existing tools and methods, allowing to compare and evaluate different data modeling techniques. The application is described in the context of bacterial and tumor cells growth data fitting, but it is also applicable to any type of two-dimensional data, e.g. physical chemistry and macroeconomic time series, being fully scalable to high number of projects, data and model complexity.

Assessing the quality of rainfall data when aiming to achieve flood resilience

NASA Astrophysics Data System (ADS)

Hoang, C. T.; Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.

2012-04-01

A new EU Floods Directive entered into force five years ago. This Directive requires Member States to coordinate adequate measures to reduce flood risk. European flood management systems require reliable rainfall statistics, e.g. the Intensity-duration-Frequency curves for shorter and shorter durations and for a larger and larger range of return periods. Preliminary studies showed that the number of floods was lower when using low time resolution data of high intensity rainfall events, compared to estimates obtained with the help of higher time resolution data. These facts suggest that a particular attention should be paid to the rainfall data quality in order to adequately investigate flood risk aiming to achieve flood resilience. The potential consequences of changes in measuring and recording techniques have been somewhat discussed in the literature with respect to a possible introduction of artificial inhomogeneities in time series. In this paper, we discuss how to detect another artificiality: most of the rainfall time series have a lower recording frequency than that is assumed, furthermore the effective high-frequency limit often depends on the recording year due to algorithm changes. This question is particularly important for operational hydrology, because an error on the effective recording high frequency introduces biases in the corresponding statistics. In this direction, we developed a first version of a SERQUAL procedure to automatically detect the effective time resolution of highly mixed data. Being applied to the 166 rainfall time series in France, the SERQUAL procedure has detected that most of them have an effective hourly resolution, rather than a 5 minutes resolution. Furthermore, series having an overall 5 minute resolution do not have it for all years. These results raise serious concerns on how to benchmark stochastic rainfall models at a sub-hourly resolution, which are particularly desirable for operational hydrology. Therefore, database quality must be checked before use. Due to the fact that the multiple scales and possible scaling behaviour of hydrological data are particularly important for many applications, including flood resilience research, this paper first investigates the sensitivity of the scaling estimates and methods to the deficit of short duration rainfall data, and consequently propose a few simple criteria for a reliable evaluation of the data quality. Then we showed that our procedure SERQUAL enable us to extract high quality sub-series from longer time series that will be much more reliable to calibrate and/or validate short duration quantiles and hydrological models.

Rapid on-site defibrillation versus community program.

PubMed

Fedoruk, J C; Paterson, D; Hlynka, M; Fung, K Y; Gobet, Michael; Currie, Wayne

2002-01-01

For patients who suffer out-of-hospital cardiac arrest, the time from collapse to initial defibrillation is the single most important factor that affects survival to hospital discharge. The purpose of this study was to compare the survival rates of cardiac arrest victims within an institution that has a rapid defibrillation program with those of its own urban community, tiered EMS system. A logistic regression analysis of a retrospective data series (n = 23) and comparative analysis to a second retrospective data series (n = 724) were gathered for the study period September 1994 to September 1999. The first data series included all persons at Casino Windsor who suffered a cardiac arrest. Data collected included: age, gender, death/survival (neurologically intact discharge), presenting rhythm (ventricular fibrillation (VF), ventricular tachycardia (VT), or other), time of collapse, time to arrival of security personnel, time to initiation of cardiopulmonary resuscitation (CPR) prior to defibrillation (when applicable), time to arrival of staff nurse, time to initial defibrillation, and time to return of spontaneous circulation (if any). Significantly, all arrests within this series were witnessed by the surveillance camera systems, allowing time of collapse to be accurately determined rather than estimated. These data were compared to those of similar events, times, and intervals for all patients in the greater Windsor area who suffered cardiac arrest. This second series was based upon the Ontario Prehospital Advanced Life Support (OPALS) Study database, as coordinated by the Clinical Epidemiology Unit of the Ottawa Hospital, University of Ottawa. The Casino Windsor had 23 cases of cardiac arrests. Of the cases, 13 (56.5%) were male and 10 (43.5%) were female. All cases (100%) were witnessed. The average of the ages was 61.1 years, of the time to initial defibrillation was 7.7 minutes, and of the time for EMS to reach the patient was 13.3 minutes. The presenting rhythm was VF/VT in 91% of the case. Fifteen patients were discharged alive from hospital for a 65% survival rate. The Greater Windsor Study area included 668 cases of out-of-hospital cardiac arrest: Of these, 410 (61.4%) were male and 258 (38.6%) were female, 365 (54.6%) were witnessed, and 303 (45.4%) were not witnessed. The initial rhythm was VF/VT was in 34.3%. Thirty-seven (5.5%) were discharged alive from the hospital. This study provides further evidence that PAD Programs may enhance cardiac arrest survival rates and should be considered for any venue with large numbers of adults as well as areas with difficult medical access.

IDCDACS: IDC's Distributed Application Control System

NASA Astrophysics Data System (ADS)

Ertl, Martin; Boresch, Alexander; Kianička, Ján; Sudakov, Alexander; Tomuta, Elena

2015-04-01

The Preparatory Commission for the CTBTO is an international organization based in Vienna, Austria. Its mission is to establish a global verification regime to monitor compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT), which bans all nuclear explosions. For this purpose time series data from a global network of seismic, hydro-acoustic and infrasound (SHI) sensors are transmitted to the International Data Centre (IDC) in Vienna in near-real-time, where it is processed to locate events that may be nuclear explosions. We newly designed the distributed application control system that glues together the various components of the automatic waveform data processing system at the IDC (IDCDACS). Our highly-scalable solution preserves the existing architecture of the IDC processing system that proved successful over many years of operational use, but replaces proprietary components with open-source solutions and custom developed software. Existing code was refactored and extended to obtain a reusable software framework that is flexibly adaptable to different types of processing workflows. Automatic data processing is organized in series of self-contained processing steps, each series being referred to as a processing pipeline. Pipelines process data by time intervals, i.e. the time-series data received from monitoring stations is organized in segments based on the time when the data was recorded. So-called data monitor applications queue the data for processing in each pipeline based on specific conditions, e.g. data availability, elapsed time or completion states of preceding processing pipelines. IDCDACS consists of a configurable number of distributed monitoring and controlling processes, a message broker and a relational database. All processes communicate through message queues hosted on the message broker. Persistent state information is stored in the database. A configurable processing controller instantiates and monitors all data processing applications. Due to decoupling by message queues the system is highly versatile and failure tolerant. The implementation utilizes the RabbitMQ open-source messaging platform that is based upon the Advanced Message Queuing Protocol (AMQP), an on-the-wire protocol (like HTML) and open industry standard. IDCDACS uses high availability capabilities provided by RabbitMQ and is equipped with failure recovery features to survive network and server outages. It is implemented in C and Python and is operated in a Linux environment at the IDC. Although IDCDACS was specifically designed for the existing IDC processing system its architecture is generic and reusable for different automatic processing workflows, e.g. similar to those described in (Olivieri et al. 2012, Kværna et al. 2012). Major advantages are its independence of the specific data processing applications used and the possibility to reconfigure IDCDACS for different types of processing, data and trigger logic. A possible future development would be to use the IDCDACS framework for different scientific domains, e.g. for processing of Earth observation satellite data extending the one-dimensional time-series intervals to spatio-temporal data cubes. REFERENCES Olivieri M., J. Clinton (2012) An almost fair comparison between Earthworm and SeisComp3, Seismological Research Letters, 83(4), 720-727. Kværna, T., S. J. Gibbons, D. B. Harris, D. A. Dodge (2012) Adapting pipeline architectures to track developing aftershock sequences and recurrent explosions, Proceedings of the 2012 Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies, 776-785.

It's time for a crisper image of the Face of the Earth: Landsat and climate time series for massive land cover & climate change mapping at detailed resolution.

NASA Astrophysics Data System (ADS)

Pons, Xavier; Miquel, Ninyerola; Oscar, González-Guerrero; Cristina, Cea; Pere, Serra; Alaitz, Zabala; Lluís, Pesquer; Ivette, Serral; Joan, Masó; Cristina, Domingo; Maria, Serra Josep; Jordi, Cristóbal; Chris, Hain; Martha, Anderson; Juanjo, Vidal

2014-05-01

Combining climate dynamics and land cover at a relative coarse resolution allows a very interesting approach to global studies, because in many cases these studies are based on a quite high temporal resolution, but they may be limited in large areas like the Mediterranean. However, the current availability of long time series of Landsat imagery and spatially detailed surface climate models allow thinking on global databases improving the results of mapping in areas with a complex history of landscape dynamics, characterized by fragmentation, or areas where relief creates intricate climate patterns that can be hardly monitored or modeled at coarse spatial resolutions. DinaCliVe (supported by the Spanish Government and ERDF, and by the Catalan Government, under grants CGL2012-33927 and SGR2009-1511) is the name of the project that aims analyzing land cover and land use dynamics as well as vegetation stress, with a particular emphasis on droughts, and the role that climate variation may have had in such phenomena. To meet this objective is proposed to design a massive database from long time series of Landsat land cover products (grouped in quinquennia) and monthly climate records (in situ climate data) for the Iberian Peninsula (582,000 km2). The whole area encompasses 47 Landsat WRS2 scenes (Landsat 4 to 8 missions, from path 197 to 202 and from rows 30 to 34), and 52 Landsat WRS1 scenes (for the previous Landsat missions, 212 to 221 and 30 to 34). Therefore, a mean of 49.5 Landsat scenes, 8 quinquennia per scene and a about 6 dates per quinquennium , from 1975 to present, produces around 2376 sets resulting in 30 m x 30 m spatial resolution maps. Each set is composed by highly coherent geometric and radiometric multispectral and multitemporal (to account for phenology) imagery as well as vegetation and wetness indexes, and several derived topographic information (about 10 Tbyte of data). Furthermore, on the basis on a previous work: the Digital Climatic Atlas of the Iberian Peninsula, spatio-temporal surface climate data has been generated with a monthly resolution (from January 1950 to December 2010) through a multiple regression model and residuals spatial interpolation using geographic variables (altitude, latitude and continentality) and solar radiation (only in the case of temperatures). This database includes precipitation, mean minimum and mean maximum air temperature and mean air temperature, improving the previous one by using the ASTER GDEM at 30 m spatial resolution, by deepening to a monthly resolution and by increasing the number of meteorological stations used, representing a total amount of 0.7 Tbyte of data. An initial validation shows accuracies higher than 85 % for land cover maps and an RMS of 1.2 ºC, 1.6 ºC and 22 mm for mean and extreme temperatures, and for precipitation, respectively. This amount of new detailed data for the Iberian Peninsula framework will be used to study the spatial direction, velocity and acceleration of the tendencies related to climate change, land cover and tree line dynamics. A global analysis using all these datasets will try to discriminate the climatic signal when interpreted together with anthropogenic driving forces. Ultimately, getting ready for massive database computation and analysis will improve predictions for global models that will require of the growing high-resolution information available.

Quasars Probing Quasars. X. The Quasar Pair Spectral Database

NASA Astrophysics Data System (ADS)

Findlay, Joseph R.; Prochaska, J. Xavier; Hennawi, Joseph F.; Fumagalli, Michele; Myers, Adam D.; Bartle, Stephanie; Chehade, Ben; DiPompeo, Michael A.; Shanks, Tom; Lau, Marie Wingyee; Rubin, Kate H. R.

2018-06-01

The rare close projection of two quasars on the sky provides the opportunity to study the host galaxy environment of a foreground quasar in absorption against the continuum emission of a background quasar. For over a decade the “Quasars probing quasars” series has utilized this technique to further the understanding of galaxy formation and evolution in the presence of a quasar at z > 2, resolving scales as small as a galactic disk and from bound gas in the circumgalactic medium to the diffuse environs of intergalactic space. Presented here is the public release of the quasar pair spectral database utilized in these studies. In addition to projected pairs at z > 2, the database also includes quasar pair members at z < 2, gravitational lens candidates, and quasars closely separated in redshift that are useful for small-scale clustering studies. In total, the database catalogs 5627 distinct objects, with 4083 lying within 5‧ of at least one other source. A spectral library contains 3582 optical and near-infrared spectra for 3028 of the cataloged sources. As well as reporting on 54 newly discovered quasar pairs, we outline the key contributions made by this series over the last 10 years, summarize the imaging and spectroscopic data used for target selection, discuss the target selection methodologies, describe the database content, and explore some avenues for future work. Full documentation for the spectral database, including download instructions, is supplied at http://specdb.readthedocs.io/en/latest/.

RESIS-II: An Updated Version of the Original Reservoir Sedimentation Survey Information System (RESIS) Database

USGS Publications Warehouse

Ackerman, Katherine V.; Mixon, David M.; Sundquist, Eric T.; Stallard, Robert F.; Schwarz, Gregory E.; Stewart, David W.

2009-01-01

The Reservoir Sedimentation Survey Information System (RESIS) database, originally compiled by the Soil Conservation Service (now the Natural Resources Conservation Service) in collaboration with the Texas Agricultural Experiment Station, is the most comprehensive compilation of data from reservoir sedimentation surveys throughout the conterminous United States (U.S.). The database is a cumulative historical archive that includes data from as early as 1755 and as late as 1993. The 1,823 reservoirs included in the database range in size from farm ponds to the largest U.S. reservoirs (such as Lake Mead). Results from 6,617 bathymetric surveys are available in the database. This Data Series provides an improved version of the original RESIS database, termed RESIS-II, and a report describing RESIS-II. The RESIS-II relational database is stored in Microsoft Access and includes more precise location coordinates for most of the reservoirs than the original database but excludes information on reservoir ownership. RESIS-II is anticipated to be a template for further improvements in the database.

Between a Map and a Data Rod

NASA Technical Reports Server (NTRS)

Teng, William; Rui, Hualan; Strub, Richard; Vollmer, Bruce

2015-01-01

A Digital Divide has long stood between how NASA and other satellite-derived data are typically archived (time-step arrays or maps) and how hydrology and other point-time series oriented communities prefer to access those data. In essence, the desired method of data access is orthogonal to the way the data are archived. Our approach to bridging the Divide is part of a larger NASA-supported data rods project to enhance access to and use of NASA and other data by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS) and the larger hydrology community. Our main objective was to determine a way to reorganize data that is optimal for these communities. Two related objectives were to optimally reorganize data in a way that (1) is operational and fits in and leverages the existing Goddard Earth Sciences Data and Information Services Center (GES DISC) operational environment and (2) addresses the scaling up of data sets available as time series from those archived at the GES DISC to potentially include those from other Earth Observing System Data and Information System (EOSDIS) data archives. Through several prototype efforts and lessons learned, we arrived at a non-database solution that satisfied our objectivesconstraints. We describe, in this presentation, how we implemented the operational production of pre-generated data rods and, considering the tradeoffs between length of time series (or number of time steps), resources needed, and performance, how we implemented the operational production of on-the-fly (virtual) data rods. For the virtual data rods, we leveraged a number of existing resources, including the NASA Giovanni Cache and NetCDF Operators (NCO) and used data cubes processed in parallel. Our current benchmark performance for virtual generation of data rods is about a years worth of time series for hourly data (9,000 time steps) in 90 seconds. Our approach is a specific implementation of the general optimal strategy of reorganizing data to match the desired means of access. Results from our project have already significantly extended NASA data to the large and important hydrology user community that has been, heretofore, mostly unable to easily access and use NASA data.

Between a Map and a Data Rod

NASA Astrophysics Data System (ADS)

Teng, W. L.; Rui, H.; Strub, R. F.; Vollmer, B.

2015-12-01

A "Digital Divide" has long stood between how NASA and other satellite-derived data are typically archived (time-step arrays or "maps") and how hydrology and other point-time series oriented communities prefer to access those data. In essence, the desired method of data access is orthogonal to the way the data are archived. Our approach to bridging the Divide is part of a larger NASA-supported "data rods" project to enhance access to and use of NASA and other data by the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS) and the larger hydrology community. Our main objective was to determine a way to reorganize data that is optimal for these communities. Two related objectives were to optimally reorganize data in a way that (1) is operational and fits in and leverages the existing Goddard Earth Sciences Data and Information Services Center (GES DISC) operational environment and (2) addresses the scaling up of data sets available as time series from those archived at the GES DISC to potentially include those from other Earth Observing System Data and Information System (EOSDIS) data archives. Through several prototype efforts and lessons learned, we arrived at a non-database solution that satisfied our objectives/constraints. We describe, in this presentation, how we implemented the operational production of pre-generated data rods and, considering the tradeoffs between length of time series (or number of time steps), resources needed, and performance, how we implemented the operational production of on-the-fly ("virtual") data rods. For the virtual data rods, we leveraged a number of existing resources, including the NASA Giovanni Cache and NetCDF Operators (NCO) and used data cubes processed in parallel. Our current benchmark performance for virtual generation of data rods is about a year's worth of time series for hourly data (~9,000 time steps) in ~90 seconds. Our approach is a specific implementation of the general optimal strategy of reorganizing data to match the desired means of access. Results from our project have already significantly extended NASA data to the large and important hydrology user community that has been, heretofore, mostly unable to easily access and use NASA data.

A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

NASA Astrophysics Data System (ADS)

Duveiller, G.; Donatelli, M.; Fumagalli, D.; Zucchini, A.; Nelson, R.; Baruth, B.

2017-02-01

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

Software Classifications: Trends in Literacy Software Publication and Marketing.

ERIC Educational Resources Information Center

Balajthy, Ernest

First in a continuing series of reports on trends in marketing and publication of software for literacy education, a study explored the development of a database to track the trends and reported on trends seen in 1995. The final version of the 1995 database consisted of 1011 software titles, 165 of which had been published in 1995 and 846…

A High School Student's Bill of Rights. Teaching Resources in the ERIC Database (TRIED) Series.

ERIC Educational Resources Information Center

Gottlieb, Stephen S.

Designed to tap the rich collection of instructional techniques in the ERIC database, this compilation of lesson plans focuses on teaching high school students their Constitutional rights and responsibilities. The 40 lesson plans in the book cover the courts and basic rights, the rights of criminal suspects, the rights of minors and education law,…

Digital map databases in support of avionic display systems

NASA Astrophysics Data System (ADS)

Trenchard, Michael E.; Lohrenz, Maura C.; Rosche, Henry, III; Wischow, Perry B.

1991-08-01

The emergence of computerized mission planning systems (MPS) and airborne digital moving map systems (DMS) has necessitated the development of a global database of raster aeronautical chart data specifically designed for input to these systems. The Naval Oceanographic and Atmospheric Research Laboratory''s (NOARL) Map Data Formatting Facility (MDFF) is presently dedicated to supporting these avionic display systems with the development of the Compressed Aeronautical Chart (CAC) database on Compact Disk Read Only Memory (CDROM) optical discs. The MDFF is also developing a series of aircraft-specific Write-Once Read Many (WORM) optical discs. NOARL has initiated a comprehensive research program aimed at improving the pilots'' moving map displays current research efforts include the development of an alternate image compression technique and generation of a standard set of color palettes. The CAC database will provide digital aeronautical chart data in six different scales. CAC is derived from the Defense Mapping Agency''s (DMA) Equal Arc-second (ARC) Digitized Raster Graphics (ADRG) a series of scanned aeronautical charts. NOARL processes ADRG to tailor the chart image resolution to that of the DMS display while reducing storage requirements through image compression techniques. CAC is being distributed by DMA as a library of CDROMs.

Quantifying solid waste and recycling employment in Florida, USA: Trends in public and private sectors.

PubMed

Park, Sunjoo; Yi, Hongtao; Feiock, Richard C

2015-12-01

Measuring and tracking the numbers of jobs in solid waste management and recycling industries over time provide basic data to inform decision makers about the important role played by this sector in a state or region's 'green economy'. This study estimates the number of people employed in the solid waste and recycling industry from 1989 through 2011 in the state of Florida (USA), applying a classification scheme based on the Standard Industrial Code (SIC) and utilizing the National Establishment Time Series (NETS) database. The results indicate that solid waste and recycling jobs in the private sector steadily increased from 1989 to 2011, whereas government employment for solid waste management fluctuated over the same period. © The Author(s) 2015.

Enhancements of Bayesian Blocks; Application to Large Light Curve Databases

NASA Technical Reports Server (NTRS)

Scargle, Jeff

2015-01-01

Bayesian Blocks are optimal piecewise linear representations (step function fits) of light-curves. The simple algorithm implementing this idea, using dynamic programming, has been extended to include more data modes and fitness metrics, multivariate analysis, and data on the circle (Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations, Scargle, Norris, Jackson and Chiang 2013, ApJ, 764, 167), as well as new results on background subtraction and refinement of the procedure for precise timing of transient events in sparse data. Example demonstrations will include exploratory analysis of the Kepler light curve archive in a search for "star-tickling" signals from extraterrestrial civilizations. (The Cepheid Galactic Internet, Learned, Kudritzki, Pakvasa1, and Zee, 2008, arXiv: 0809.0339; Walkowicz et al., in progress).

The Effect of Share 35 on Biliary Complications: an Interrupted Time Series Analysis.

PubMed

Fleming, J N; Taber, D J; Axelrod, D; Chavin, K D

2018-05-16

The purpose of the Share 35 allocation policy was to improve liver transplant waitlist mortality, targeting high MELD waitlisted patients. However, policy changes may also have unintended consequences that must be balanced with the primary desired outcome. We performed an interrupted time series assessing the impact of Share 35 on biliary complications in a select national liver transplant population using the Vizient CDB/RM ™ database. Liver transplants that occurred between October 2012 and September 2015 were included. There was a significant change in the incident-rate of biliary complications between Pre-Share 35 (n=3,018) and Post-Share 35 (n=9,984) cohorts over time (p=0.023, r2=0.44). As a control, a subanalysis was performed throughout the same time period in Region 9 transplant centers, where a broad sharing agreement had previously been implemented. In the subanalysis, there was no change in the incident-rate of biliary complications between the two time periods. Length of stay and mean direct cost demonstrated a change after implementation of Share 35, although they did not meet statistical difference. While the target of improved waitlist mortality is of utmost importance for the equitable allocation of organs, unintended consequences of policy changes should be studied for a full assessment of a policy's impact. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

A solar radiation database for Chile.

PubMed

Molina, Alejandra; Falvey, Mark; Rondanelli, Roberto

2017-11-01

Chile hosts some of the sunniest places on earth, which has led to a growing solar energy industry in recent years. However, the lack of high resolution measurements of solar irradiance becomes a critical obstacle for both financing and design of solar installations. Besides the Atacama Desert, Chile displays a large array of "solar climates" due to large latitude and altitude variations, and so provides a useful testbed for the development of solar irradiance maps. Here a new public database for surface solar irradiance over Chile is presented. This database includes hourly irradiance from 2004 to 2016 at 90 m horizontal resolution over continental Chile. Our results are based on global reanalysis data to force a radiative transfer model for clear sky solar irradiance and an empirical model based on geostationary satellite data for cloudy conditions. The results have been validated using 140 surface solar irradiance stations throughout the country. Model mean percentage error in hourly time series of global horizontal irradiance is only 0.73%, considering both clear and cloudy days. The simplicity and accuracy of the model over a wide range of solar conditions provides confidence that the model can be easily generalized to other regions of the world.

A Bayesian Multivariate Receptor Model for Estimating Source Contributions to Particulate Matter Pollution using National Databases.

PubMed

Hackstadt, Amber J; Peng, Roger D

2014-11-01

Time series studies have suggested that air pollution can negatively impact health. These studies have typically focused on the total mass of fine particulate matter air pollution or the individual chemical constituents that contribute to it, and not source-specific contributions to air pollution. Source-specific contribution estimates are useful from a regulatory standpoint by allowing regulators to focus limited resources on reducing emissions from sources that are major contributors to air pollution and are also desired when estimating source-specific health effects. However, researchers often lack direct observations of the emissions at the source level. We propose a Bayesian multivariate receptor model to infer information about source contributions from ambient air pollution measurements. The proposed model incorporates information from national databases containing data on both the composition of source emissions and the amount of emissions from known sources of air pollution. The proposed model is used to perform source apportionment analyses for two distinct locations in the United States (Boston, Massachusetts and Phoenix, Arizona). Our results mirror previous source apportionment analyses that did not utilize the information from national databases and provide additional information about uncertainty that is relevant to the estimation of health effects.

Impact of the mass media on calls to the CDC National AIDS Hotline.

PubMed

Fan, D P

1996-06-01

This paper considers new computer methodologies for assessing the impact of different types of public health information. The example used public service announcements (PSAs) and mass media news to predict the volume of attempts to call the CDC National AIDS Hotline from December 1992 through to the end of 1993. The analysis relied solely on data from electronic databases. Newspaper stories and television news transcripts were obtained from the NEXIS electronic database and were scored by machine for AIDS coverage. The PSA database was generated by computer monitoring of advertising distributed by the Centers for Disease Control and Prevention (CDC) and by others. The volume of call attempts was collected automatically by the public branch exchange (PBX) of the Hotline telephone system. The call attempts, the PSAs and the news story data were related to each other using both a standard time series method and the statistical model of ideodynamics. The analysis indicated that the only significant explanatory variable for the call attempts was PSAs produced by the CDC. One possible explanation was that these commercials all included the Hotline telephone number while the other information sources did not.

Dynamic publication model for neurophysiology databases.

PubMed

Gardner, D; Abato, M; Knuth, K H; DeBellis, R; Erde, S M

2001-08-29

We have implemented a pair of database projects, one serving cortical electrophysiology and the other invertebrate neurones and recordings. The design for each combines aspects of two proven schemes for information interchange. The journal article metaphor determined the type, scope, organization and quantity of data to comprise each submission. Sequence databases encouraged intuitive tools for data viewing, capture, and direct submission by authors. Neurophysiology required transcending these models with new datatypes. Time-series, histogram and bivariate datatypes, including illustration-like wrappers, were selected by their utility to the community of investigators. As interpretation of neurophysiological recordings depends on context supplied by metadata attributes, searches are via visual interfaces to sets of controlled-vocabulary metadata trees. Neurones, for example, can be specified by metadata describing functional and anatomical characteristics. Permanence is advanced by data model and data formats largely independent of contemporary technology or implementation, including Java and the XML standard. All user tools, including dynamic data viewers that serve as a virtual oscilloscope, are Java-based, free, multiplatform, and distributed by our application servers to any contemporary networked computer. Copyright is retained by submitters; viewer displays are dynamic and do not violate copyright of related journal figures. Panels of neurophysiologists view and test schemas and tools, enhancing community support.

Homogenisation of minimum and maximum air temperature in northern Portugal

NASA Astrophysics Data System (ADS)

Freitas, L.; Pereira, M. G.; Caramelo, L.; Mendes, L.; Amorim, L.; Nunes, L.

2012-04-01

Homogenization of minimum and maximum air temperature has been carried out for northern Portugal for the period 1941-2010. The database corresponds to the values of the monthly arithmetic averages calculated from daily values observed at stations within the network of stations managed by the national Institute of Meteorology (IM). Some of the weather stations of IM's network are collecting data for more than a century; however, during the entire observing period, some factors have affected the climate series and have to be considered such as, changes in the station surroundings and changes related to replacement of manually operated instruments. Besides these typical changes, it is of particular interest the station relocation to rural areas or to the urban-rural interface and the installation of automatic weather stations in the vicinity of the principal or synoptic stations with the aim of replacing them. The information from these relocated and new stations was merged to produce just one but representative time series of that site. This process starts at the end 90's and the information of the time series fusion process constitutes the set of metadata used. Two basic procedures were performed: (i) preliminary statistical and quality control analysis; and, (ii) detection and correction of problems of homogeneity. In the first case, was developed and used software for quality control, specifically dedicated for the detection of outliers, based on the quartile values of the time series itself. The analysis of homogeneity was performed using the MASH (Multiple Analysis of Series for Homogenisation) and HOMER, which is a software application developed and recently made available within the COST Action ES0601 (COST-ES0601, 2012). Both methods provide a fast quality control of the original data and were developed for automatic processing, analyzing, homogeneity testing and adjusting of climatological data, but manual usage is also possible. Obtained results with both methods will be presented, compared and discussed along with the results of the sensitivity tests performed with both methods. COST-ES0601, 2012: "ACTION COST-ES0601 - Advances in homogenisation methods of climate series: an integrated approach HOME". Available at http://www.homogenisation.org/v_02_15/ [accessed 3 January 2012].

Complexity matching in dyadic conversation.

PubMed

Abney, Drew H; Paxton, Alexandra; Dale, Rick; Kello, Christopher T

2014-12-01

Recent studies of dyadic interaction have examined phenomena of synchronization, entrainment, alignment, and convergence. All these forms of behavioral matching have been hypothesized to play a supportive role in establishing coordination and common ground between interlocutors. In the present study, evidence is found for a new kind of coordination termed complexity matching. Temporal dynamics in conversational speech signals were analyzed through time series of acoustic onset events. Timing in periods of acoustic energy was found to exhibit behavioral matching that reflects complementary timing in turn-taking. In addition, acoustic onset times were found to exhibit power law clustering across a range of timescales, and these power law functions were found to exhibit complexity matching that is distinct from behavioral matching. Complexity matching is discussed in terms of interactive alignment and other theoretical principles that lead to new hypotheses about information exchange in dyadic conversation and interaction in general. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Indoor air quality analysis based on Hadoop

NASA Astrophysics Data System (ADS)

Tuo, Wang; Yunhua, Sun; Song, Tian; Liang, Yu; Weihong, Cui

2014-03-01

The air of the office environment is our research object. The data of temperature, humidity, concentrations of carbon dioxide, carbon monoxide and ammonia are collected peer one to eight seconds by the sensor monitoring system. And all the data are stored in the Hbase database of Hadoop platform. With the help of HBase feature of column-oriented store and versioned (automatically add the time column), the time-series data sets are bulit based on the primary key Row-key and timestamp. The parallel computing programming model MapReduce is used to process millions of data collected by sensors. By analysing the changing trend of parameters' value at different time of the same day and at the same time of various dates, the impact of human factor and other factors on the room microenvironment is achieved according to the liquidity of the office staff. Moreover, the effective way to improve indoor air quality is proposed in the end of this paper.

Aerodynamic Tests of the Space Launch System for Database Development

NASA Technical Reports Server (NTRS)

Pritchett, Victor E.; Mayle, Melody N.; Blevins, John A.; Crosby, William A.; Purinton, David C.

2014-01-01

The Aerosciences Branch (EV33) at the George C. Marshall Space Flight Center (MSFC) has been responsible for a series of wind tunnel tests on the National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) vehicles. The primary purpose of these tests was to obtain aerodynamic data during the ascent phase and establish databases that can be used by the Guidance, Navigation, and Mission Analysis Branch (EV42) for trajectory simulations. The paper describes the test particulars regarding models and measurements and the facilities used, as well as database preparations.

Simulating the complex output of rainfall and hydrological processes using the information contained in large data sets: the Direct Sampling approach.

NASA Astrophysics Data System (ADS)

Oriani, Fabio

2017-04-01

The unpredictable nature of rainfall makes its estimation as much difficult as it is essential to hydrological applications. Stochastic simulation is often considered a convenient approach to asses the uncertainty of rainfall processes, but preserving their irregular behavior and variability at multiple scales is a challenge even for the most advanced techniques. In this presentation, an overview on the Direct Sampling technique [1] and its recent application to rainfall and hydrological data simulation [2, 3] is given. The algorithm, having its roots in multiple-point statistics, makes use of a training data set to simulate the outcome of a process without inferring any explicit probability measure: the data are simulated in time or space by sampling the training data set where a sufficiently similar group of neighbor data exists. This approach allows preserving complex statistical dependencies at different scales with a good approximation, while reducing the parameterization to the minimum. The straights and weaknesses of the Direct Sampling approach are shown through a series of applications to rainfall and hydrological data: from time-series simulation to spatial rainfall fields conditioned by elevation or a climate scenario. In the era of vast databases, is this data-driven approach a valid alternative to parametric simulation techniques? [1] Mariethoz G., Renard P., and Straubhaar J. (2010), The Direct Sampling method to perform multiple-point geostatistical simulations, Water. Rerous. Res., 46(11), http://dx.doi.org/10.1029/2008WR007621 [2] Oriani F., Straubhaar J., Renard P., and Mariethoz G. (2014), Simulation of rainfall time series from different climatic regions using the direct sampling technique, Hydrol. Earth Syst. Sci., 18, 3015-3031, http://dx.doi.org/10.5194/hess-18-3015-2014 [3] Oriani F., Borghi A., Straubhaar J., Mariethoz G., Renard P. (2016), Missing data simulation inside flow rate time-series using multiple-point statistics, Environ. Model. Softw., vol. 86, pp. 264 - 276, http://dx.doi.org/10.1016/j.envsoft.2016.10.002

Evolutionary cost analysis of valsartan initiation among patients with hypertension: a time series approach.

PubMed

Sun, Peter; Chang, Joanne; Zhang, Jie; Kahler, Kristijan H

2012-01-01

This study examines the evolutionary impact of valsartan initiation on medical costs. A retrospective time series study design was used with a large, US national commercial claims database for the period of 2004-2008. Hypertensive patients who initiated valsartan between the ages of 18 and 63, and had continuous enrollment for 24-month pre-initiation period and 24-month post-initiation period were selected. Patients' monthly medical costs were calculated based on individual claims. A novel time series model was devised with monthly medical costs as its dependent variables, autoregressive integrated moving average (ARIMA) as its stochastic components, and four indicative variables as its decomposed interventional components. The number of post-initiation months before a cost-offset point was also assessed. Patients (n = 18,269) had mean age of 53 at the initiation date, and 53% of them were female. The most common co-morbid conditions were dyslipidemia (52%), diabetes (24%), and hypertensive complications (17%). The time series model suggests that medical costs were increasing by approximately $10 per month (p < 0.01) before the initiation, and decreasing by approximately $6 per month (p < 0.01) after the initiation. After the 4th post-initiation month, medical costs for patients with the initiation were statistically significantly lower (p < 0.01) than forecasted medical costs for the same patients without the initiation. The study has its limitations in data representativeness, ability to collect unrecorded clinical conditions, treatments, and costs, as well as its generalizability to patients with different characteristics. Commercially insured hypertensive patients experienced monthly medical cost increase before valsartan initiation. Based on our model, the evolutionary impact of the initiation on medical costs included a temporary cost surge, a gradual, consistent, and statistically significant cost decrease, and a cost-offset point around the 4th post-initiation month.

Spatiotemporal dynamics of human settlement patterns in the Southeast U.S. from DMSP/OLS nightlight time series, 1992-2013

NASA Astrophysics Data System (ADS)

Wang, C.; Lu, L.

2015-12-01

The Southeast U.S. is listed one of the fastest growing regions by the Census Bureau, covering two of the eleven megaregions of the United States (Florida and Piedmont Atlantic). The Defense Meteorological Satellite Program (DMSP)'s Operational Line-scan System (OLS) nighttime light (NTL) imagery offers a good opportunity for characterizing the extent and dynamics of urban development at global and regional scales. However, the commonly used thresholding technique for NTL-based urban land mapping often underestimates the suburban and rural areas and overestimates urban extents. In this study we developed a novel approach to estimating impervious surface area (ISA) by integrating the NTL and optical reflectance data. A geographically weighted regression model was built to extract ISA from the Vegetation-Adjusted NTL Urban Index (VANUI). The ISA was estimated each year from 1992 to 2013 to generate the ISA time series for the U.S. Southeast region. Using the National Land Cover Database (NLCD) products of percent imperviousness (2001, 2006, and 2010) as our reference data, accuracy assessment indicated that our approach made considerable improvement of the ISA estimation, especially in suburban areas. With the ISA time series, a nonparametric Mann-Kendall trend analysis was performed to detect hotspots of human settlement expansion, followed by the exploration of decennial U.S. census data to link these patterns to migration flows in these hotspots. Our results provided significant insights to human settlement of the U.S. Southeast in the past decades. The proposed approach has great potential for mapping ISA at broad scales with nightlight data such as DMSP/OLS and the new-generation VIIRS products. The ISA time series generated in this study can be used to assess the anthropogenic impacts on regional climate, environment and ecosystem services in the U.S. Southeast.

Identification of AR(I)MA processes for modelling temporal correlations of GPS observations

NASA Astrophysics Data System (ADS)

Luo, X.; Mayer, M.; Heck, B.

2009-04-01

In many geodetic applications observations of the Global Positioning System (GPS) are routinely processed by means of the least-squares method. However, this algorithm delivers reliable estimates of unknown parameters und realistic accuracy measures only if both the functional and stochastic models are appropriately defined within GPS data processing. One deficiency of the stochastic model used in many GPS software products consists in neglecting temporal correlations of GPS observations. In practice the knowledge of the temporal stochastic behaviour of GPS observations can be improved by analysing time series of residuals resulting from the least-squares evaluation. This paper presents an approach based on the theory of autoregressive (integrated) moving average (AR(I)MA) processes to model temporal correlations of GPS observations using time series of observation residuals. A practicable integration of AR(I)MA models in GPS data processing requires the determination of the order parameters of AR(I)MA processes at first. In case of GPS, the identification of AR(I)MA processes could be affected by various factors impacting GPS positioning results, e.g. baseline length, multipath effects, observation weighting, or weather variations. The influences of these factors on AR(I)MA identification are empirically analysed based on a large amount of representative residual time series resulting from differential GPS post-processing using 1-Hz observation data collected within the permanent SAPOS® (Satellite Positioning Service of the German State Survey) network. Both short and long time series are modelled by means of AR(I)MA processes. The final order parameters are determined based on the whole residual database; the corresponding empirical distribution functions illustrate that multipath and weather variations seem to affect the identification of AR(I)MA processes much more significantly than baseline length and observation weighting. Additionally, the modelling results of temporal correlations using high-order AR(I)MA processes are compared with those by means of first order autoregressive (AR(1)) processes and empirically estimated autocorrelation functions.

Standardized Access and Processing of Multi-Source Earth Observation Time-Series Data within a Regional Data Middleware

NASA Astrophysics Data System (ADS)

Eberle, J.; Schmullius, C.

2017-12-01

Increasing archives of global satellite data present a new challenge to handle multi-source satellite data in a user-friendly way. Any user is confronted with different data formats and data access services. In addition the handling of time-series data is complex as an automated processing and execution of data processing steps is needed to supply the user with the desired product for a specific area of interest. In order to simplify the access to data archives of various satellite missions and to facilitate the subsequent processing, a regional data and processing middleware has been developed. The aim of this system is to provide standardized and web-based interfaces to multi-source time-series data for individual regions on Earth. For further use and analysis uniform data formats and data access services are provided. Interfaces to data archives of the sensor MODIS (NASA) as well as the satellites Landsat (USGS) and Sentinel (ESA) have been integrated in the middleware. Various scientific algorithms, such as the calculation of trends and breakpoints of time-series data, can be carried out on the preprocessed data on the basis of uniform data management. Jupyter Notebooks are linked to the data and further processing can be conducted directly on the server using Python and the statistical language R. In addition to accessing EO data, the middleware is also used as an intermediary between the user and external databases (e.g., Flickr, YouTube). Standardized web services as specified by OGC are provided for all tools of the middleware. Currently, the use of cloud services is being researched to bring algorithms to the data. As a thematic example, an operational monitoring of vegetation phenology is being implemented on the basis of various optical satellite data and validation data from the German Weather Service. Other examples demonstrate the monitoring of wetlands focusing on automated discovery and access of Landsat and Sentinel data for local areas.

Temporal and spatial distribution of isotopes in river water in Central Europe: 50 years experience with the Austrian network of isotopes in rivers.

PubMed

Rank, Dieter; Wyhlidal, Stefan; Schott, Katharina; Weigand, Silvia; Oblin, Armin

2018-05-01

The Austrian network of isotopes in rivers comprises about 15 sampling locations and has been operated since 1976. The Danube isotope time series goes back to 1963. The isotopic composition of river water in Central Europe is mainly governed by the isotopic composition of precipitation in the catchment area; evaporation effects play only a minor role. Short-term and long-term isotope signals in precipitation are thus transmitted through the whole catchment. The influence of climatic changes has become observable in the long-term stable isotope time series of precipitation and surface waters. Environmental 3 H values were around 8 TU in 2015, short-term 3 H pulses up to about 80 TU in the rivers Danube and March were a consequence of releases from nuclear power plants. The complete isotope data series of this network will be included in the Global Network of Isotopes in Rivers database of the International Atomic Energy Agency (IAEA) in 2017. This article comprises a review of 50 years isotope monitoring on rivers and is also intended to provide base information on the (isotope-)hydrological conditions in Central Europe specifically for the end-users of these data, e.g. for modelling hydrological processes. Furthermore, this paper includes the 2006-2015 supplement adding to the Danube isotope set published earlier.

Introducing stochastics into the simulation of convective precipitation events

NASA Astrophysics Data System (ADS)

Pistotnik, Georg

2010-05-01

In a joint project, the Central Institute for Meteorology and Geodynamics (ZAMG) and the Vienna University of Technology aimed to characterize strong precipitation events and their impact in the Bucklige Welt region in Eastern Austria. Both the region's hydrological and meteorological characteristics, namely its composition of virtually countless small catchments with short response times and a high frequency of summertime convective storms, cause the occurrence of flooding to be strictly tied to convective rainfall events, which is why this study has been focused on this type of precipitation. The meteorological database consists of the ZAMG's high-resolution analysis and nowcasting system INCA ("Integrated Nowcasting through Comprehensive Analysis"), which provides a set of precipitation analyses generated by a statistically optimized combination of rain gauge measurements and radar data with a temporal resolution of 15 minutes and a spatial resolution of 1 kilometre. An intensity threshold of 3.8mm/15min has been used to classify any observed precipitation as a convective one, thus extracting 245 convection days with a total number of almost 1600 individual storm events over the project region out of the 5-year data set from 2003 to 2007. Consecutive analyses were used to compute the motion of these storms, a complex process that could not be completely automatized; due to the repeated occurrence of storm splits or coalescences, a manual control of the automatically provided "suggestion" of movement had to be performed in order to merge two or more precipitation maxima to a single storm if necessary, thus yielding the smoothest and most plausible storm tracks and ensuring a high quality of the database. In the first part of the project, distributions for all characteristic parameters have been derived, including the number of storms per day, their place and time of initiation, their motion, lifetime, maximum intensity and maximum "cell volume" (i.e. overall precipitation per time step). Both components of the mean motion as well as of its deviations could be approximated by normal distributions, whereas the number of storms per day, their lifetime, maximum intensity and maximum cell volume roughly followed exponential distributions. The shapes of the convective cells were approximated by Gaussian bells with the peak intensity and the cell volume as boundary conditions. The temporal courses of the peak intensities and cell volumes were assumed to follow parabolas which are symmetric with respect to the half of the lifetime. In the second part of the project, these distributions were used to drive a random generator that allows simulating an arbitrary number of convection days in order to obtain pseudo time series of convective precipitation for each grid point. An algorithm to create correlated samples of random numbers enabled to also account for the observed correlation between some of the parameters, i.e. lifetime and maximum intensity or maximum cell volume. The spatial structures of the return periods of simulated convective precipitation events may provide valuable additional information when being assimilated to the time series measured by the (unfortunately rather sparse) rain gauges in this region. Thus, further studies have to investigate to what extent the "convection simulator" is able to reproduce these time series. Some iterative fine-tuning of the parameters' distributions as well as an extension of the database to a longer time span may further improve the results and enable to simulate realistic spatio-temporal convection scenarios ("design storms") that have the potential to feed hydrological models and, together with vegetation and soil characteristics, hopefully enable to better assess and regionalize the torrent hazard over the project region.

Rapid sample classification using an open port sampling interface coupled with liquid introduction atmospheric pressure ionization mass spectrometry.

PubMed

Van Berkel, Gary J; Kertesz, Vilmos

2017-02-15

An "Open Access"-like mass spectrometric platform to fully utilize the simplicity of the manual open port sampling interface for rapid characterization of unprocessed samples by liquid introduction atmospheric pressure ionization mass spectrometry has been lacking. The in-house developed integrated software with a simple, small and relatively low-cost mass spectrometry system introduced here fills this void. Software was developed to operate the mass spectrometer, to collect and process mass spectrometric data files, to build a database and to classify samples using such a database. These tasks were accomplished via the vendor-provided software libraries. Sample classification based on spectral comparison utilized the spectral contrast angle method. Using the developed software platform near real-time sample classification is exemplified using a series of commercially available blue ink rollerball pens and vegetable oils. In the case of the inks, full scan positive and negative ion ESI mass spectra were both used for database generation and sample classification. For the vegetable oils, full scan positive ion mode APCI mass spectra were recorded. The overall accuracy of the employed spectral contrast angle statistical model was 95.3% and 98% in case of the inks and oils, respectively, using leave-one-out cross-validation. This work illustrates that an open port sampling interface/mass spectrometer combination, with appropriate instrument control and data processing software, is a viable direct liquid extraction sampling and analysis system suitable for the non-expert user and near real-time sample classification via database matching. Published in 2016. This article is a U.S. Government work and is in the public domain in the USA. Published in 2016. This article is a U.S. Government work and is in the public domain in the USA.

Compilation of reinforced carbon-carbon transatlantic abort landing arc jet test results

NASA Technical Reports Server (NTRS)

Milhoan, James D.; Pham, Vuong T.; Yuen, Eric H.

1993-01-01

This document consists of the entire test database generated to support the Reinforced Carbon-Carbon Transatlantic Abort Landing Study. RCC components used for orbiter nose cap and wing leading edge thermal protection were originally designed to have a multi-mission entry capability of 2800 F. Increased orbiter range capability required a predicted increase in excess of 3300 F. Three test series were conducted. Test series #1 used ENKA-based RCC specimens coated with silicon carbide, treated with tetraethyl orthosilicate, sealed with Type A surface enhancement, and tested at 3000-3400 F with surface pressure of 60-101 psf. Series #2 used ENKA- or AVTEX-based RCC, with and without silicon carbide, Type A or double Type AA surface enhancement, all impregnated with TEOS, and at temperatures from 1440-3350 F with pressures from 100-350 psf. Series #3 tested ENKA-based RCC, with and without silicon carbide coating. No specimens were treated with TEOS or sealed with Type A. Surface temperatures ranged from 2690-3440 F and pressures ranged from 313-400 psf. These combined test results provided the database for establishing RCC material single-mission-limit temperature and developing surface recession correlations used to predict mass loss for abort conditions.

Deregulation of sale of over-the-counter drugs outside of pharmacies in the Republic of Korea: interrupted-time-series analysis of outpatient visits before and after the policy.

PubMed

Chun, Sung-Youn; Park, Hye-Ki; Han, Kyu-Tae; Kim, Woorim; Lee, Hyo-Jung; Park, Eun-Cheol

2017-07-12

We evaluated the effectiveness of a policy allowing for the sale of over-the-counter drugs outside of pharmacies by examining its effect on number of monthly outpatient visits for acute upper respiratory infections, dyspepsia, and migraine. We used medical claims data extracted from the Korean National Health Insurance Cohort Database from 2009 to 2013. The Korean National Health Insurance Cohort Database comprises a nationally representative sample of claims - about 2% of the entire population - obtained from the medical record data held by the Korean National Health Insurance Corporation (which has data on the entire nation). The analysis included26,284,706 person-months of 1,042,728 individuals. An interrupted-time series analysis was performed. Outcome measures were monthly outpatient visits for acute upper respiratory infections, dyspepsia, and migraine. To investigate the effect of the policy, we compared the number of monthly visits before and after the policy's implementation in 2012. For acute upper respiratory infections, monthly outpatient visits showed a decreasing trend before the policy (ß = -0.0003);after it, a prompt change and increasing trend in monthly outpatient visits were observed, but these were non-significant. For dyspepsia, the trend was increasing before implementation (ß = -0.0101), but this reversed after implementation(ß = -0.007). For migraine, an increasing trend was observed before the policy (ß = 0.0057). After it, we observed a significant prompt change (ß = -0.0314) but no significant trend. Deregulation of selling over-the-counter medication outside of pharmacies reduced monthly outpatient visits for dyspepsia and migraine symptoms, but not acute upper respiratory infections.

[The 'Beijing clinical database' on severe acute respiratory syndrome patients: its design, process, quality control and evaluation].

PubMed

2004-04-01

To develop a large database on clinical presentation, treatment and prognosis of all clinical diagnosed severe acute respiratory syndrome (SARS) cases in Beijing during the 2003 "crisis", in order to conduct further clinical studies. The database was designed by specialists, under the organization of the Beijing Commanding Center for SARS Treatment and Cure, including 686 data items in six sub-databases: primary medical-care seeking, vital signs, common symptoms and signs, treatment, laboratory and auxiliary test, and cost. All hospitals having received SARS inpatients were involved in the project. Clinical data was transferred and coded by trained doctors and data entry was carried out by trained nurses, according to a uniformed protocol. A series of procedures had been taken before the database was finally established which included programmed logic checking, digit-by-digit check on 5% random sample, data linkage for transferred cases, coding of characterized information, database structure standardization, case reviewe by computer program according to SARS Clinical Diagnosis Criteria issued by the Ministry of Health, and exclusion of unqualified patients. The database involved 2148 probable SARS cases in accordant with the clinical diagnosis criteria, including 1291 with complete records. All cases and record-complete cases showed an almost identical distribution in sex, age, occupation, residence areas and time of onset. The completion rate of data was not significantly different between the two groups except for some items on primary medical-care seeking. Specifically, the data completion rate was 73% - 100% in primary medical-care seeking, 90% in common symptoms and signs, 100% for treatment, 98% for temperature, 90% for pulse, 100% for outcomes and 98% for costs in hospital. The number of cases collected in the Beijing Clinical Database of SARS Patients was fairly complete. Cases with complete records showed that they could serve as excellent representatives of all cases. The completeness of data was quite satisfactory with primary clinical items which allowed for further clinical studies.

An Evaluator's Guide to Using DB MASTER: A Microcomputer Based File Management Program. Research on Evaluation Program, Paper and Report Series No. 91.

ERIC Educational Resources Information Center

Gray, Peter J.

Ways a microcomputer can be used to establish and maintain an evaluation database and types of data management features possible on a microcomputer are described in this report, which contains step-by-step procedures and numerous examples for establishing a database, manipulating data, and designing and printing reports. Following a brief…

Assessing co-regulation of directly linked genes in biological networks using microarray time series analysis.

PubMed

Del Sorbo, Maria Rosaria; Balzano, Walter; Donato, Michele; Draghici, Sorin

2013-11-01

Differential expression of genes detected with the analysis of high throughput genomic experiments is a commonly used intermediate step for the identification of signaling pathways involved in the response to different biological conditions. The impact analysis was the first approach for the analysis of signaling pathways involved in a certain biological process that was able to take into account not only the magnitude of the expression change of the genes but also the topology of signaling pathways including the type of each interactions between the genes. In the impact analysis, signaling pathways are represented as weighted directed graphs with genes as nodes and the interactions between genes as edges. Edges weights are represented by a β factor, the regulatory efficiency, which is assumed to be equal to 1 in inductive interactions between genes and equal to -1 in repressive interactions. This study presents a similarity analysis between gene expression time series aimed to find correspondences with the regulatory efficiency, i.e. the β factor as found in a widely used pathway database. Here, we focused on correlations among genes directly connected in signaling pathways, assuming that the expression variations of upstream genes impact immediately downstream genes in a short time interval and without significant influences by the interactions with other genes. Time series were processed using three different similarity metrics. The first metric is based on the bit string matching; the second one is a specific application of the Dynamic Time Warping to detect similarities even in presence of stretching and delays; the third one is a quantitative comparative analysis resulting by an evaluation of frequency domain representation of time series: the similarity metric is the correlation between dominant spectral components. These three approaches are tested on real data and pathways, and a comparison is performed using Information Retrieval benchmark tools, indicating the frequency approach as the best similarity metric among the three, for its ability to detect the correlation based on the correspondence of the most significant frequency components. Copyright © 2013. Published by Elsevier Ireland Ltd.

Forecasting changes in amphibian biodiversity: aiming at a moving target

PubMed Central

Collins, James P; Halliday, Tim

2005-01-01

Amphibian population declines and sudden species' extinctions began to be noted at the beginning of the 1980s. Understanding the causes of the losses is hampered by our poor knowledge of the amphibian fauna in many parts of the world. Amphibian taxa are still being described at a high rate, especially in the tropics, which means that even quantifying species lost as a percentage of the current fauna can be a misleading statistic in some parts of the globe. The number of species that have gone missing is only one measure of the loss of biodiversity. Long-term studies of single-species populations are needed, but this approach has its limits. Amphibian populations often show great annual variation in population size making it difficult, if not impossible, to use short-term studies as a basis for deciding if a population is increasing or decreasing in the long term. Aggregating single studies into databases and searching for patterns of variation is a way of overcoming this limitation. Several databases on species and population time series are available or in development. These records show that declines are continuing worldwide with some species and populations, especially in the tropics and at higher elevations, at greater risk of extinction than others. Unfortunately, amphibian databases with population time series have much less information for the tropics compared to the temperate zone, and less for Africa and Asia compared with Europe and North America. Focusing limited resources using comprehensive statistical designs is a way to maximize the efficiency and effectiveness of monitoring efforts. It is clear that, in the first decades of the twenty-first century, the regions of the globe with the highest diversity of amphibian species will experience the greatest rates of decrease of forests and increase in human population size, fertilizer use, agricultural production, creation of new croplands and irrigation. Many of these changes are likely negatively to affect amphibian species diversity, and their influence must be understood before concluding, at least for amphibians, that the 2010 millennium assessment goal of significantly reversing the rate of loss of Earth's biodiversity can be met. PMID:15856554

Forecasting changes in amphibian biodiversity: aiming at a moving target.

PubMed

Collins, James P; Halliday, Tim

2005-02-28

Amphibian population declines and sudden species' extinctions began to be noted at the beginning of the 1980s. Understanding the causes of the losses is hampered by our poor knowledge of the amphibian fauna in many parts of the world. Amphibian taxa are still being described at a high rate, especially in the tropics, which means that even quantifying species lost as a percentage of the current fauna can be a misleading statistic in some parts of the globe. The number of species that have gone missing is only one measure of the loss of biodiversity. Long-term studies of single-species populations are needed, but this approach has its limits. Amphibian populations often show great annual variation in population size making it difficult, if not impossible, to use short-term studies as a basis for deciding if a population is increasing or decreasing in the long term. Aggregating single studies into databases and searching for patterns of variation is a way of overcoming this limitation. Several databases on species and population time series are available or in development. These records show that declines are continuing worldwide with some species and populations, especially in the tropics and at higher elevations, at greater risk of extinction than others. Unfortunately, amphibian databases with population time series have much less information for the tropics compared to the temperate zone, and less for Africa and Asia compared with Europe and North America. Focusing limited resources using comprehensive statistical designs is a way to maximize the efficiency and effectiveness of monitoring efforts. It is clear that, in the first decades of the twenty-first century, the regions of the globe with the highest diversity of amphibian species will experience the greatest rates of decrease of forests and increase in human population size, fertilizer use, agricultural production, creation of new croplands and irrigation. Many of these changes are likely negatively to affect amphibian species diversity, and their influence must be understood before concluding, at least for amphibians, that the 2010 millennium assessment goal of significantly reversing the rate of loss of Earth's biodiversity can be met.

Using 50 years of soil radiocarbon data to identify optimal approaches for estimating soil carbon residence times

NASA Astrophysics Data System (ADS)

Baisden, W. T.; Canessa, S.

2013-01-01

In 1959, Athol Rafter began a substantial programme of systematically monitoring the flow of 14C produced by atmospheric thermonuclear tests through organic matter in New Zealand soils under stable land use. A database of ∼500 soil radiocarbon measurements spanning 50 years has now been compiled, and is used here to identify optimal approaches for soil C-cycle studies. Our results confirm the potential of 14C to determine residence times, by estimating the amount of ‘bomb 14C’ incorporated. High-resolution time series confirm this approach is appropriate, and emphasise that residence times can be calculated routinely with two or more time points as little as 10 years apart. This approach is generally robust to the key assumptions that can create large errors when single time-point 14C measurements are modelled. The three most critical assumptions relate to: (1) the distribution of turnover times, and particularly the proportion of old C (‘passive fraction’), (2) the lag time between photosynthesis and C entering the modelled pool, (3) changes in the rates of C input. When carrying out approaches using robust assumptions on time-series samples, multiple soil layers can be aggregated using a mixing equation. Where good archived samples are available, AMS measurements can develop useful understanding for calibrating models of the soil C cycle at regional to continental scales with sample numbers on the order of hundreds rather than thousands. Sample preparation laboratories and AMS facilities can play an important role in coordinating the efficient delivery of robust calculated residence times for soil carbon.

The Eruption Forecasting Information System: Volcanic Eruption Forecasting Using Databases

NASA Astrophysics Data System (ADS)

Ogburn, S. E.; Harpel, C. J.; Pesicek, J. D.; Wellik, J.

2016-12-01

Forecasting eruptions, including the onset size, duration, location, and impacts, is vital for hazard assessment and risk mitigation. The Eruption Forecasting Information System (EFIS) project is a new initiative of the US Geological Survey-USAID Volcano Disaster Assistance Program (VDAP) and will advance VDAP's ability to forecast the outcome of volcanic unrest. The project supports probability estimation for eruption forecasting by creating databases useful for pattern recognition, identifying monitoring data thresholds beyond which eruptive probabilities increase, and for answering common forecasting questions. A major component of the project is a global relational database, which contains multiple modules designed to aid in the construction of probabilistic event trees and to answer common questions that arise during volcanic crises. The primary module contains chronologies of volcanic unrest. This module allows us to query eruption chronologies, monitoring data, descriptive information, operational data, and eruptive phases alongside other global databases, such as WOVOdat and the Global Volcanism Program. The EFIS database is in the early stages of development and population; thus, this contribution also is a request for feedback from the community. Preliminary data are already benefitting several research areas. For example, VDAP provided a forecast of the likely remaining eruption duration for Sinabung volcano, Indonesia, using global data taken from similar volcanoes in the DomeHaz database module, in combination with local monitoring time-series data. In addition, EFIS seismologists used a beta-statistic test and empirically-derived thresholds to identify distal volcano-tectonic earthquake anomalies preceding Alaska volcanic eruptions during 1990-2015 to retrospectively evaluate Alaska Volcano Observatory eruption precursors. This has identified important considerations for selecting analog volcanoes for global data analysis, such as differences between closed and open system volcanoes.

Thoracolumbar spine fractures in frontal impact crashes.

PubMed

Pintar, Frank A; Yoganandan, Narayan; Maiman, Dennis J; Scarboro, Mark; Rudd, Rodney W

2012-01-01

There is currently no injury assessment for thoracic or lumbar spine fractures in the motor vehicle crash standards throughout the world. Compression-related thoracolumbar fractures are occurring in frontal impacts and yet the mechanism of injury is poorly understood. The objective of this investigation was to characterize these injuries using real world crash data from the US-DOT-NHTSA NASS-CDS and CIREN databases. Thoracic and lumbar AIS vertebral body fracture codes were searched for in the two databases. The NASS database was used to characterize population trends as a function of crash year and vehicle model year. The CIREN database was used to examine a case series in more detail. From the NASS database there were 2000-4000 occupants in frontal impacts with thoracic and lumbar vertebral body fractures per crash year. There was an increasing trend in incidence rate of thoracolumbar fractures in frontal impact crashes as a function of vehicle model year from 1986 to 2008; this was not the case for other crash types. From the CIREN database, the thoracolumbar spine was most commonly fractured at either the T12 or L1 level. Major, burst type fractures occurred predominantly at T12, L1 or L5; wedge fractures were most common at L1. Most CIREN occupants were belted; there were slightly more females involved; they were almost all in bucket seats; impact location occurred approximately half the time on the road and half off the road. The type of object struck also seemed to have some influence on fractured spine level, suggesting that the crash deceleration pulse may be influential in the type of compression vector that migrates up the spinal column. Future biomechanical studies are required to define mechanistically how these fractures are influenced by these many factors.

Verification and Validation of NASA-Supported Enhancements to PECAD's Decision Support Tools

NASA Technical Reports Server (NTRS)

McKellipo, Rodney; Ross, Kenton W.

2006-01-01

The NASA Applied Sciences Directorate (ASD), part of the Earth-Sun System Division of NASA's Science Mission Directorate, has partnered with the U.S. Department of Agriculture (USDA) to enhance decision support in the area of agricultural efficiency-an application of national importance. The ASD integrated the results of NASA Earth science research into USDA decision support tools employed by the USDA Foreign Agricultural Service (FAS) Production Estimates and Crop Assessment Division (PECAD), which supports national decision making by gathering, analyzing, and disseminating global crop intelligence. Verification and validation of the following enhancements are summarized: 1) Near-real-time Moderate Resolution Imaging Spectroradiometer (MODIS) products through PECAD's MODIS Image Gallery; 2) MODIS Normalized Difference Vegetation Index (NDVI) time series data through the USDA-FAS MODIS NDVI Database; and 3) Jason-1 and TOPEX/Poseidon lake level estimates through PECAD's Global Reservoir and Lake Monitor. Where possible, each enhanced product was characterized for accuracy, timeliness, and coverage, and the characterized performance was compared to PECAD operational requirements. The MODIS Image Gallery and the GRLM are more mature and have achieved a semi-operational status, whereas the USDA-FAS MODIS NDVI Database is still evolving and should be considered

Three-dimensional object recognition based on planar images

NASA Astrophysics Data System (ADS)

Mital, Dinesh P.; Teoh, Eam-Khwang; Au, K. C.; Chng, E. K.

1993-01-01

This paper presents the development and realization of a robotic vision system for the recognition of 3-dimensional (3-D) objects. The system can recognize a single object from among a group of known regular convex polyhedron objects that is constrained to lie on a calibrated flat platform. The approach adopted comprises a series of image processing operations on a single 2-dimensional (2-D) intensity image to derive an image line drawing. Subsequently, a feature matching technique is employed to determine 2-D spatial correspondences of the image line drawing with the model in the database. Besides its identification ability, the system can also provide important position and orientation information of the recognized object. The system was implemented on an IBM-PC AT machine executing at 8 MHz without the 80287 Maths Co-processor. In our overall performance evaluation based on a 600 recognition cycles test, the system demonstrated an accuracy of above 80% with recognition time well within 10 seconds. The recognition time is, however, indirectly dependent on the number of models in the database. The reliability of the system is also affected by illumination conditions which must be clinically controlled as in any industrial robotic vision system.

An online database of nuclear electromagnetic moments

NASA Astrophysics Data System (ADS)

Mertzimekis, T. J.; Stamou, K.; Psaltis, A.

2016-01-01

Measurements of nuclear magnetic dipole and electric quadrupole moments are considered quite important for the understanding of nuclear structure both near and far from the valley of stability. The recent advent of radioactive beams has resulted in a plethora of new, continuously flowing, experimental data on nuclear structure - including nuclear moments - which hinders the information management. A new, dedicated, public and user friendly online database (http://magneticmoments.info) has been created comprising experimental data of nuclear electromagnetic moments. The present database supersedes existing printed compilations, including also non-evaluated series of data and relevant meta-data, while putting strong emphasis on bimonthly updates. The scope, features and extensions of the database are reported.

BioBenchmark Toyama 2012: an evaluation of the performance of triple stores on biological data

PubMed Central

2014-01-01

Background Biological databases vary enormously in size and data complexity, from small databases that contain a few million Resource Description Framework (RDF) triples to large databases that contain billions of triples. In this paper, we evaluate whether RDF native stores can be used to meet the needs of a biological database provider. Prior evaluations have used synthetic data with a limited database size. For example, the largest BSBM benchmark uses 1 billion synthetic e-commerce knowledge RDF triples on a single node. However, real world biological data differs from the simple synthetic data much. It is difficult to determine whether the synthetic e-commerce data is efficient enough to represent biological databases. Therefore, for this evaluation, we used five real data sets from biological databases. Results We evaluated five triple stores, 4store, Bigdata, Mulgara, Virtuoso, and OWLIM-SE, with five biological data sets, Cell Cycle Ontology, Allie, PDBj, UniProt, and DDBJ, ranging in size from approximately 10 million to 8 billion triples. For each database, we loaded all the data into our single node and prepared the database for use in a classical data warehouse scenario. Then, we ran a series of SPARQL queries against each endpoint and recorded the execution time and the accuracy of the query response. Conclusions Our paper shows that with appropriate configuration Virtuoso and OWLIM-SE can satisfy the basic requirements to load and query biological data less than 8 billion or so on a single node, for the simultaneous access of 64 clients. OWLIM-SE performs best for databases with approximately 11 million triples; For data sets that contain 94 million and 590 million triples, OWLIM-SE and Virtuoso perform best. They do not show overwhelming advantage over each other; For data over 4 billion Virtuoso works best. 4store performs well on small data sets with limited features when the number of triples is less than 100 million, and our test shows its scalability is poor; Bigdata demonstrates average performance and is a good open source triple store for middle-sized (500 million or so) data set; Mulgara shows a little of fragility. PMID:25089180

Database for the degradation risk assessment of groundwater resources (Southern Italy)

NASA Astrophysics Data System (ADS)

Polemio, M.; Dragone, V.; Mitolo, D.

2003-04-01

The risk characterisation of quality degradation and availability lowering of groundwater resources has been pursued for a wide coastal plain (Basilicata region, Southern Italy), an area covering 40 km along the Ionian Sea and 10 km inland. The quality degradation is due two phenomena: pollution due to discharge of waste water (coming from urban areas) and due to salt pollution, related to seawater intrusion but not only. The availability lowering is due to overexploitation but also due to drought effects. To this purpose the historical data of 1,130 wells have been collected. Wells, homogenously distributed in the area, were the source of geological, stratigraphical, hydrogeological, geochemical data. In order to manage space-related information via a GIS, a database system has been devised to encompass all the surveyed wells and the body of information available per well. Geo-databases were designed to comprise the four types of data collected: a database including geometrical, geological and hydrogeological data on wells (WDB), a database devoted to chemical and physical data on groundwater (CDB), a database including the geotechnical parameters (GDB), a database concering piezometric and hydrological (rainfall, air temperature, river discharge) data (HDB). The record pertaining to each well is identified in these databases by the progressive number of the well itself. Every database is designed as follows: a) the HDB contains 1,158 records, 28 of and 31 fields, mainly describing the geometry of the well and of the stratigraphy; b) the CDB encompasses data about 157 wells, based on which the chemical and physical analyses of groundwater have been carried out. More than one record has been associated with these 157 wells, due to periodic monitoring and analysis; c) the GDB covers 61 wells to which the geotechnical parameters obtained by soil samples taken at various depths; the HDB is designed to permit the analysis of long time series (from 1918) of piezometric data, monitored by more than 60 wells, temperature, rainfall and river discharge data. Based on geo-databases, the geostatistical processing of data has permitted to characterise the degradation risk of groundwater resources of a wide coastal aquifer.

BioBenchmark Toyama 2012: an evaluation of the performance of triple stores on biological data.

PubMed

Wu, Hongyan; Fujiwara, Toyofumi; Yamamoto, Yasunori; Bolleman, Jerven; Yamaguchi, Atsuko

2014-01-01

Biological databases vary enormously in size and data complexity, from small databases that contain a few million Resource Description Framework (RDF) triples to large databases that contain billions of triples. In this paper, we evaluate whether RDF native stores can be used to meet the needs of a biological database provider. Prior evaluations have used synthetic data with a limited database size. For example, the largest BSBM benchmark uses 1 billion synthetic e-commerce knowledge RDF triples on a single node. However, real world biological data differs from the simple synthetic data much. It is difficult to determine whether the synthetic e-commerce data is efficient enough to represent biological databases. Therefore, for this evaluation, we used five real data sets from biological databases. We evaluated five triple stores, 4store, Bigdata, Mulgara, Virtuoso, and OWLIM-SE, with five biological data sets, Cell Cycle Ontology, Allie, PDBj, UniProt, and DDBJ, ranging in size from approximately 10 million to 8 billion triples. For each database, we loaded all the data into our single node and prepared the database for use in a classical data warehouse scenario. Then, we ran a series of SPARQL queries against each endpoint and recorded the execution time and the accuracy of the query response. Our paper shows that with appropriate configuration Virtuoso and OWLIM-SE can satisfy the basic requirements to load and query biological data less than 8 billion or so on a single node, for the simultaneous access of 64 clients. OWLIM-SE performs best for databases with approximately 11 million triples; For data sets that contain 94 million and 590 million triples, OWLIM-SE and Virtuoso perform best. They do not show overwhelming advantage over each other; For data over 4 billion Virtuoso works best. 4store performs well on small data sets with limited features when the number of triples is less than 100 million, and our test shows its scalability is poor; Bigdata demonstrates average performance and is a good open source triple store for middle-sized (500 million or so) data set; Mulgara shows a little of fragility.

Detection of time delays and directional interactions based on time series from complex dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

2017-07-01

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

Use of interrupted time series analysis in evaluating health care quality improvements.

PubMed

Penfold, Robert B; Zhang, Fang

2013-01-01

Interrupted time series (ITS) analysis is arguably the strongest quasi-experimental research design. ITS is particularly useful when a randomized trial is infeasible or unethical. The approach usually involves constructing a time series of population-level rates for a particular quality improvement focus (eg, rates of attention-deficit/hyperactivity disorder [ADHD] medication initiation) and testing statistically for a change in the outcome rate in the time periods before and time periods after implementation of a policy/program designed to change the outcome. In parallel, investigators often analyze rates of negative outcomes that might be (unintentionally) affected by the policy/program. We discuss why ITS is a useful tool for quality improvement. Strengths of ITS include the ability to control for secular trends in the data (unlike a 2-period before-and-after t test), ability to evaluate outcomes using population-level data, clear graphical presentation of results, ease of conducting stratified analyses, and ability to evaluate both intended and unintended consequences of interventions. Limitations of ITS include the need for a minimum of 8 time periods before and 8 after an intervention to evaluate changes statistically, difficulty in analyzing the independent impact of separate components of a program that are implemented close together in time, and existence of a suitable control population. Investigators must also be careful not to make individual-level inferences when population-level rates are used to evaluate interventions (though ITS can be used with individual-level data). A brief description of ITS is provided, including a fully implemented (but hypothetical) study of the impact of a program to reduce ADHD medication initiation in children younger than 5 years old and insured by Medicaid in Washington State. An example of the database needed to conduct an ITS is provided, as well as SAS code to implement a difference-in-differences model using preschool-age children in California as a comparison group. Copyright © 2013 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

The investigation of active Martian dune fields using very high resolution photogrammetric measurements

NASA Astrophysics Data System (ADS)

Kim, Jungrack; Kim, Younghwi; Park, Minseong

2016-10-01

At the present time, arguments continue regarding the migration speeds of Martian dune fields and their correlation with atmospheric circulation. However, precisely measuring the spatial translation of Martian dunes has succeeded only a very few times—for example, in the Nili Patera study (Bridges et al. 2012) using change-detection algorithms and orbital imagery. Therefore, in this study, we developed a generic procedure to precisely measure the migration of dune fields with recently introduced 25-cm resolution orbital imagery specifically using a high-accuracy photogrammetric processor. The processor was designed to trace estimated dune migration, albeit slight, over the Martian surface by 1) the introduction of very high resolution ortho images and stereo analysis based on hierarchical geodetic control for better initial point settings; 2) positioning error removal throughout the sensor model refinement with a non-rigorous bundle block adjustment, which makes possible the co-alignment of all images in a time series; and 3) improved sub-pixel co-registration algorithms using optical flow with a refinement stage conducted on a pyramidal grid processor and a blunder classifier. Moreover, volumetric changes of Martian dunes were additionally traced by means of stereo analysis and photoclinometry. The established algorithms have been tested using high-resolution HIRISE time-series images over several Martian dune fields. Dune migrations were iteratively processed both spatially and volumetrically, and the results were integrated to be compared to the Martian climate model. Migrations over well-known crater dune fields appeared to be almost static for the considerable temporal periods and were weakly correlated with wind directions estimated by the Mars Climate Database (Millour et al. 2015). As a result, a number of measurements over dune fields in the Mars Global Dune Database (Hayward et al. 2014) covering polar areas and mid-latitude will be demonstrated. Acknowledgements:The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under iMars grant agreement Nr. 607379.

Visualization Component of Vehicle Health Decision Support System

NASA Technical Reports Server (NTRS)

Jacob, Joseph; Turmon, Michael; Stough, Timothy; Siegel, Herbert; Walter, patrick; Kurt, Cindy

2008-01-01

The visualization front-end of a Decision Support System (DSS) also includes an analysis engine linked to vehicle telemetry, and a database of learned models for known behaviors. Because the display is graphical rather than text-based, the summarization it provides has a greater information density on one screen for evaluation by a flight controller.This tool provides a system-level visualization of the state of a vehicle, and drill-down capability for more details and interfaces to separate analysis algorithms and sensor data streams. The system-level view is a 3D rendering of the vehicle, with sensors represented as icons, tied to appropriate positions within the vehicle body and colored to indicate sensor state (e.g., normal, warning, anomalous state, etc.). The sensor data is received via an Information Sharing Protocol (ISP) client that connects to an external server for real-time telemetry. Users can interactively pan, zoom, and rotate this 3D view, as well as select sensors for a detail plot of the associated time series data. Subsets of the plotted data can be selected and sent to an external analysis engine to either search for a similar time series in an historical database, or to detect anomalous events. The system overview and plotting capabilities are completely general in that they can be applied to any vehicle instrumented with a collection of sensors. This visualization component can interface with the ISP for data streams used by NASA s Mission Control Center at Johnson Space Center. In addition, it can connect to, and display results from, separate analysis engine components that identify anomalies or that search for past instances of similar behavior. This software supports NASA's Software, Intelligent Systems, and Modeling element in the Exploration Systems Research and Technology Program by augmenting the capability of human flight controllers to make correct decisions, thus increasing safety and reliability. It was designed specifically as a tool for NASA's flight controllers to monitor the International Space Station and a future Crew Exploration Vehicle.

Regression analysis of radial artery pulse palpation as a potential tool for traditional Chinese medicine training education.

PubMed

Huang, Po-Yu; Lin, Wen-Chen; Chiu, Bill Yuan-Chi; Chang, Hen-Hong; Lin, Kang-Ping

2013-12-01

Pulse palpation was an important part of the traditional Chinese medicine (TCM) vascular examination. It is challenging for new physicians to learn to differentiate between palpations of various pulse types, due to limited comparative learning time with established masters, and so normally it takes many years to master the art. The purpose of this study was to introduce an offline TCM skill evaluation and comparison system that makes available learning of palpation without the master's presence. We record patient's radial artery pulse using an existing pressure-based pulse acquisition system, then annotate it with teachers' evaluation when palpating the same patient, assigned as likelihood of it being each pulse type, e.g. wiry, slippery, hesitant. These training data were separated into per-doctor and per-skill databases for evaluation and comparison purposes, using the following novel procedure: each database was used as training data to a panel of time-series data-mining algorithms, driven by two validation tests, with the created training models evaluated in mean-squared-error. Each validation of the panel and training data yielded an array of error terms, and we chose one to quantitatively evaluate palpation techniques, giving way to compute self consistency and mutual-similarity across different practitioners and techniques. Our experiment of two practitioners and 396 per-processing samples yielded the following: one of the physicians has much higher value of self-consistency for all tested pulse types. Also, the two physicians have high similarity in how they palpate the slipper pulse (P) type, but very dissimilar for hesitant (H) type. This system of skill comparisons may be more broadly applied in places where supervised learning algorithms can detect and use meaningful features in the data; we chose a panel of algorithms previously shown to be effective for many time-series types, but specialized algorithms may be added to improve feature-specific aspect of evaluation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Trend analysis of air temperature and precipitation time series over Greece: 1955-2010

NASA Astrophysics Data System (ADS)

Marougianni, G.; Melas, D.; Kioutsioukis, I.; Feidas, H.; Zanis, P.; Anandranistakis, E.

2012-04-01

In this study, a database of air temperature and precipitation time series from the network of Hellenic National Meteorological Service has been developed in the framework of the project GEOCLIMA, co-financed by the European Union and Greek national funds through the Operational Program "Competitiveness and Entrepreneurship" of the Research Funding Program COOPERATION 2009. Initially, a quality test was applied to the raw data and then missing observations have been imputed with a regularized, spatial-temporal expectation - maximization algorithm to complete the climatic record. Next, a quantile - matching algorithm was applied in order to verify the homogeneity of the data. The processed time series were used for the calculation of temporal annual and seasonal trends of air temperature and precipitation. Monthly maximum and minimum surface air temperature and precipitation means at all available stations in Greece were analyzed for temporal trends and spatial variation patterns for the longest common time period of homogenous data (1955 - 2010), applying the Mann-Kendall test. The majority of the examined stations showed a significant increase in the summer maximum and minimum temperatures; this could be possibly physically linked to the Etesian winds, because of the less frequent expansion of the low over the southeastern Mediterranean. Summer minimum temperatures have been increasing at a faster rate than that of summer maximum temperatures, reflecting an asymmetric change of extreme temperature distributions. Total annual precipitation has been significantly decreased at the stations located in western Greece, as well as in the southeast, while the remaining areas exhibit a non-significant negative trend. This reduction is very likely linked to the positive phase of the NAO that resulted in an increase in the frequency and persistence of anticyclones over the Mediterranean.

Prediction of Safety Stock Using Fuzzy Time Series (FTS) and Technology of Radio Frequency Identification (RFID) for Stock Control at Vendor Managed Inventory (VMI)

NASA Astrophysics Data System (ADS)

Mashuri, Chamdan; Suryono; Suseno, Jatmiko Endro

2018-02-01

This research was conducted by prediction of safety stock using Fuzzy Time Series (FTS) and technology of Radio Frequency Identification (RFID) for stock control at Vendor Managed Inventory (VMI). Well-controlled stock influenced company revenue and minimized cost. It discussed about information system of safety stock prediction developed through programming language of PHP. Input data consisted of demand got from automatic, online and real time acquisition using technology of RFID, then, sent to server and stored at online database. Furthermore, data of acquisition result was predicted by using algorithm of FTS applying universe of discourse defining and fuzzy sets determination. Fuzzy set result was continued to division process of universe of discourse in order to be to final step. Prediction result was displayed at information system dashboard developed. By using 60 data from demand data, prediction score was 450.331 and safety stock was 135.535. Prediction result was done by error deviation validation using Mean Square Percent Error of 15%. It proved that FTS was good enough in predicting demand and safety stock for stock control. For deeper analysis, researchers used data of demand and universe of discourse U varying at FTS to get various result based on test data used.

[Spanish doctoral theses in emergency medicine (1978-2013)].

PubMed

Fernández-Guerrero, Inés María

2015-01-01

To quantitatively analyze the production of Spanish doctoral theses in emergency medicine. Quantitative synthesis of productivity indicators for 214 doctoral theses in emergency medicine found in the database (TESEO) for Spanish universities from 1978 to 2013. We processed the data in 3 ways as follows: compilation of descriptive statistics, regression analysis (correlation coefficients of determination), and modeling of linear trend (time-series analysis). Most of the thesis supervisors (84.1%) only oversaw a single project. No major supervisor of 10 or more theses was identified. Analysis of cosupervision indicated there were 1.6 supervisors per thesis. The theses were defended in 67 departments (both general and specialist departments) because no emergency medicine departments had been established. The most productive universities were 2 large ones (Universitat de Barcelona and Universidad Complutense de Madrid) and 3 medium-sized ones (Universidad de Granada, Universitat Autónoma de Barcelona, and Universidad de La Laguna). Productivity over time analyzed as the trend for 2-year periods in the time-series was expressed as a polynomial function with a correlation coefficient of determination of R2 = 0.80. Spanish doctoral research in emergency medicine has grown markedly. Work has been done in various university departments in different disciplines and specialties. The findings confirm that emergency medicine is a disciplinary field.

Interventions to reduce waiting times for elective procedures.

PubMed

Ballini, Luciana; Negro, Antonella; Maltoni, Susanna; Vignatelli, Luca; Flodgren, Gerd; Simera, Iveta; Holmes, Jane; Grilli, Roberto

2015-02-23

Long waiting times for elective healthcare procedures may cause distress among patients, may have adverse health consequences and may be perceived as inappropriate delivery and planning of health care. To assess the effectiveness of interventions aimed at reducing waiting times for elective care, both diagnostic and therapeutic. We searched the following electronic databases: Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (1946-), EMBASE (1947-), the Cumulative Index to Nursing and Allied Health Literature (CINAHL), ABI Inform, the Canadian Research Index, the Science, Social Sciences and Humanities Citation Indexes, a series of databases via Proquest: Dissertations & Theses (including UK & Ireland), EconLit, PAIS (Public Affairs International), Political Science Collection, Nursing Collection, Sociological Abstracts, Social Services Abstracts and Worldwide Political Science Abstracts. We sought related reviews by searching the Cochrane Database of Systematic Reviews and the Database of Abstracts of Reviews of Effectiveness (DARE). We searched trial registries, as well as grey literature sites and reference lists of relevant articles. We considered randomised controlled trials (RCTs), controlled before-after studies (CBAs) and interrupted time series (ITS) designs that met EPOC minimum criteria and evaluated the effectiveness of any intervention aimed at reducing waiting times for any type of elective procedure. We considered studies reporting one or more of the following outcomes: number or proportion of participants whose waiting times were above or below a specific time threshold, or participants' mean or median waiting times. Comparators could include any type of active intervention or standard practice. Two review authors independently extracted data from, and assessed risk of bias of, each included study, using a standardised form and the EPOC 'Risk of bias' tool. They classified interventions as follows: interventions aimed at (1) rationing and/or prioritising demand, (2) expanding capacity, or (3) restructuring the intake assessment/referral process.For RCTs when available, we reported preintervention and postintervention values of outcome for intervention and control groups, and we calculated the absolute change from baseline or the effect size with 95% confidence interval (CI). We reanalysed ITS studies that had been inappropriately analysed using segmented time-series regression, and obtained estimates for regression coefficients corresponding to two standardised effect sizes: change in level and change in slope. Eight studies met our inclusion criteria: three RCTs and five ITS studies involving a total of 135 general practices/primary care clinics, seven hospitals and one outpatient clinic. The studies were heterogeneous in terms of types of interventions, elective procedures and clinical conditions; this made meta-analysis unfeasible.One ITS study evaluating prioritisation of demand through a system for streamlining elective surgery services reduced the number of semi-urgent participants waiting longer than the recommended time (< 90 days) by 28 participants/mo, while no effects were found for urgent (< 30 days) versus non-urgent participants (< 365 days).Interventions aimed at restructuring the intake assessment/referral process were evaluated in seven studies. Four studies (two RCTs and two ITSs) evaluated open access, or direct booking/referral: One RCT, which showed that open access to laparoscopic sterilisation reduced waiting times, had very high attrition (87%); the other RCT showed that open access to investigative services reduced waiting times (30%) for participants with lower urinary tract syndrome (LUTS) but had no effect on waiting times for participants with microscopic haematuria. In one ITS study, same-day scheduling for paediatric health clinic appointments reduced waiting times (direct reduction of 25.2 days, and thereafter a decrease of 3.03 days per month), while another ITS study showed no effect of a direct booking system on proportions of participants receiving a colposcopy appointment within the recommended time. One RCT and one ITS showed no effect of distant consultancy (instant photography for dermatological conditions and telemedicine for ear nose throat (ENT) conditions) on waiting times; another ITS study showed no effect of a pooled waiting list on the number of participants waiting for uncomplicated spinal surgery.Overall quality of the evidence for all outcomes, assessed using the GRADE (Grades of Recommendation, Assessment, Development and Evaluation) tool, ranged from low to very low.We found no studies evaluating interventions to increase capacity or to ration demand. As only a handful of low-quality studies are presently available, we cannot draw any firm conclusions about the effectiveness of the evaluated interventions in reducing waiting times. However, interventions involving the provision of more accessible services (open access or direct booking/referral) show some promise.

Applications of Sentinel-2 data for agriculture and forest monitoring using the absolute difference (ZABUD) index derived from the AgroEye software (ESA)

NASA Astrophysics Data System (ADS)

de Kok, R.; WeŻyk, P.; PapieŻ, M.; Migo, L.

2017-10-01

To convince new users of the advantages of the Sentinel_2 sensor, a simplification of classic remote sensing tools allows to create a platform of communication among domain specialists of agricultural analysis, visual image interpreters and remote sensing programmers. An index value, known in the remote sensing user domain as "Zabud" was selected to represent, in color, the essentials of a time series analysis. The color index used in a color atlas offers a working platform for an agricultural field control. This creates a database of test and training areas that enables rapid anomaly detection in the agricultural domain. The use cases and simplifications now function as an introduction to Sentinel_2 based remote sensing, in an area that before relies on VHR imagery and aerial data, to serve mainly the visual interpretation. The database extension with detected anomalies allows developers of open source software to design solutions for further agricultural control with remote sensing.

Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing.

PubMed

Hasson, Uri; Skipper, Jeremy I; Wilde, Michael J; Nusbaum, Howard C; Small, Steven L

2008-01-15

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data.

Improving the Analysis, Storage and Sharing of Neuroimaging Data using Relational Databases and Distributed Computing

PubMed Central

Hasson, Uri; Skipper, Jeremy I.; Wilde, Michael J.; Nusbaum, Howard C.; Small, Steven L.

2007-01-01

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data. PMID:17964812

High Resolution Spatiotemporal Climate Reconstruction and Variability in East Asia during Little Ice Age

NASA Astrophysics Data System (ADS)

Lin, K. H. E.; Wang, P. K.; Lee, S. Y.; Liao, Y. C.; Fan, I. C.; Liao, H. M.

2017-12-01

The Little ice Age (LIA) is one of the most prominent epochs in paleoclimate reconstruction of the Common Era. While the signals of LIA were generally discovered across hemispheres, wide arrays of regional variability were found, and the reconstructed anomalies were sometimes inconsistent across studies by using various proxy data or historical records. This inconsistency is mainly attributed to limited data coverage at fine resolution that can assist high-resolution climate reconstruction in the continuous spatiotemporal trends. Qing dynasty (1644-1911 CE) of China existed in the coldest period of LIA. Owing to a long-standing tradition that acquired local officials to record odds and social or meteorological events, thousands of local chronicles were left. Zhang eds. (2004) took two decades to compile all these meteorological records in a compendium, for which we then digitized and coded all records into our REACHS database system for reconstructing climate. There were in total 1,435 points (sites) in our database for over 80,000 events in the period of time. After implementing two-rounds coding check for data quality control (accuracy rate 87.2%), multiple indexes were retrieved for reconstructing annually and seasonally resolved temperature and precipitation series for North, Central, and South China. The reconstruction methods include frequency count and grading, with usage of multiple regression models to test sensitivity and to calculate correlations among several reconstructed series. Validation was also conducted through comparison with instrumental data and with other reconstructed series in previous studies. Major research results reveal interannual (3-5 years), decadal (8-12 years), and interdecadal (≈30 years) variabilities with strong regional expressions across East China. Cooling effect was not homogenously distributed in space and time. Flood and drought conditions frequently repeated but the spatiotemporal pattern was variant, indicating likely different climate regimes that can be linked to the dynamism of large atmospheric circulation and East Asian monsoon. Spatiotemporal analysis of extreme events such as typhoons and extreme droughts also indicated similar patterns. More detailed analysis are undertaken to explain the physical mechanisms that can drive these changes.

M-52 spray booth qualification test

NASA Technical Reports Server (NTRS)

1990-01-01

The procedures, performance, and results obtained from the M-52 spray booth qualification test are documented. The test was conducted at Thiokol Corporation, Space Operations, M-52 Inert Parts Preparation facility. The purpose of this testing sequence was to ensure the spray booth would produce flight qualified hardware. The testing sequence was conducted in two series. The first series was conducted under CTP-0142, Revision 1. The second series was conducted in accordance with CTP-0142, Revision 2. The test sequence started with CTP-0142, Revision 1. The series consisted of the contamination removal test and the performance test. The contamination removal test was used to assess the Teflon level in the spray booth. The performance test consisted of painting and Chemloking a forward dome inside the spray booth per flight procedures. During the performance test, two sets of witness panels (case/insulation and steel/epoxy/steel) were prepared and pull tested. The CTP-0142, Revision 2, series of testing consisted of re-testing the steel/epoxy/steel witness panels. The pull tests analysis indicates the results of the tensile tests were comparable to the systems tunnel witness panel database. The exposed panel set and the control panel set average tensile values were above the 1-basis lower limits established on the systems tunnel witness panel database. It is recommended that the M-52 spray booth be qualified for producing flight hardware.

Investigation of methods for hydroclimatic data homogenization

NASA Astrophysics Data System (ADS)

Steirou, E.; Koutsoyiannis, D.

2012-04-01

We investigate the methods used for the adjustment of inhomogeneities of temperature time series covering the last 100 years. Based on a systematic study of scientific literature, we classify and evaluate the observed inhomogeneities in historical and modern time series, as well as their adjustment methods. It turns out that these methods are mainly statistical, not well justified by experiments and are rarely supported by metadata. In many of the cases studied the proposed corrections are not even statistically significant. From the global database GHCN-Monthly Version 2, we examine all stations containing both raw and adjusted data that satisfy certain criteria of continuity and distribution over the globe. In the United States of America, because of the large number of available stations, stations were chosen after a suitable sampling. In total we analyzed 181 stations globally. For these stations we calculated the differences between the adjusted and non-adjusted linear 100-year trends. It was found that in the two thirds of the cases, the homogenization procedure increased the positive or decreased the negative temperature trends. One of the most common homogenization methods, 'SNHT for single shifts', was applied to synthetic time series with selected statistical characteristics, occasionally with offsets. The method was satisfactory when applied to independent data normally distributed, but not in data with long-term persistence. The above results cast some doubts in the use of homogenization procedures and tend to indicate that the global temperature increase during the last century is between 0.4°C and 0.7°C, where these two values are the estimates derived from raw and adjusted data, respectively.

Evaluation of the impact of fetal fibronectin test implementation on hospital admissions for preterm labour in Ontario: a multiple baseline time-series design.

PubMed

Fell, D B; Sprague, A E; Grimshaw, J M; Yasseen, A S; Coyle, D; Dunn, S I; Perkins, S L; Peterson, W E; Johnson, M; Bunting, P S; Walker, M C

2014-03-01

To determine the impact of a health system-wide fetal fibronectin (fFN) testing programme on the rates of hospital admission for preterm labour (PTL). Multiple baseline time-series design. Canadian province of Ontario. A retrospective population-based cohort of antepartum and delivered obstetrical admissions in all Ontario hospitals between 1 April 2002 and 31 March 2010. International Classification of Diseases codes in a health system-wide hospital administrative database were used to identify the study population and define the outcome measure. An aggregate time series of monthly rates of hospital admissions for PTL was analysed using segmented regression models after aligning the fFN test implementation date for each institution. Rate of obstetrical hospital admission for PTL. Estimated rates of hospital admission for PTL following fFN implementation were lower than predicted had pre-implementation trends prevailed. The reduction in the rate was modest, but statistically significant, when estimated at 12 months following fFN implementation (-0.96 hospital admissions for PTL per 100 preterm births; 95% confidence interval [CI], -1.02 to -0.90, P = 0.04). The statistically significant reduction was sustained at 24 and 36 months following implementation. Using a robust quasi-experimental study design to overcome confounding as a result of underlying secular trends or concurrent interventions, we found evidence of a small but statistically significant reduction in the health system-level rate of hospital admissions for PTL following implementation of fFN testing in a large Canadian province. © 2013 Royal College of Obstetricians and Gynaecologists.

The association between ambient inhalable particulate matter and the disease burden of respiratory disease: An ecological study based on ten-year time series data in Tianjin, China.

PubMed

Zeng, Qiang; Wu, Ziting; Jiang, Guohong; Wu, Xiaoyin; Li, Pei; Ni, Yang; Xiong, Xiuqin; Wang, Xinyan; Parasat; Li, Guoxing; Pan, Xiaochuan

2017-08-01

There is limited evidence available worldwide about the quantitative relationship between particulate matter with an aerodynamic diameter of less than 10µm (PM 10 ) and years of life lost (YLL) caused by respiratory diseases (RD), especially regarding long-term time series data. We investigated the quantitative exposure-response association between PM 10 and the disease burden of RD. We obtained the daily concentration of ambient pollutants (PM 10 , nitrogen dioxide and sulphur dioxide), temperature and relative humidity data, as well as the death monitoring data from 2001 to 2010 in Tianjin. Then, a time series database was built after the daily YLL of RD was calculated. We applied a generalized additive model (GAM) to estimate the burden of PM 10 on daily YLL of RD and to determine the effect (the increase of daily YLL) of every 10μg/m 3 increase in PM 10 on health. We found that every 10μg/m 3 increase in PM 10 was associated with the greatest increase in YLL of 0.84 (95% CI: 0.45, 1.23) years at a 2-day (current day and previous day, lag01) moving average PM 10 concentration for RD. The association between PM 10 and YLL was stronger in females and the elderly (≥65 years of age). The association between PM 10 and YLL of RD differed according to district. These findings also provide new epidemiological evidence for respiratory disease prevention. Copyright © 2017 Elsevier Inc. All rights reserved.

Rice Crop Monitoring and Yield Assessment with MODIS 250m Gridded Vegetation Products: A Case Study of Sa Kaeo Province, Thailand

NASA Astrophysics Data System (ADS)

Wijesingha, J. S. J.; Deshapriya, N. L.; Samarakoon, L.

2015-04-01

Billions of people in the world depend on rice as a staple food and as an income-generating crop. Asia is the leader in rice cultivation and it is necessary to maintain an up-to-date rice-related database to ensure food security as well as economic development. This study investigates general applicability of high temporal resolution Moderate Resolution Imaging Spectroradiometer (MODIS) 250m gridded vegetation product for monitoring rice crop growth, mapping rice crop acreage and analyzing crop yield, at the province-level. The MODIS 250m Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) time series data, field data and crop calendar information were utilized in this research in Sa Kaeo Province, Thailand. The following methodology was used: (1) data pre-processing and rice plant growth analysis using Vegetation Indices (VI) (2) extraction of rice acreage and start-of-season dates from VI time series data (3) accuracy assessment, and (4) yield analysis with MODIS VI. The results show a direct relationship between rice plant height and MODIS VI. The crop calendar information and the smoothed NDVI time series with Whittaker Smoother gave high rice acreage estimation (with 86% area accuracy and 75% classification accuracy). Point level yield analysis showed that the MODIS EVI is highly correlated with rice yield and yield prediction using maximum EVI in the rice cycle predicted yield with an average prediction error 4.2%. This study shows the immense potential of MODIS gridded vegetation product for keeping an up-to-date Geographic Information System of rice cultivation.

The IEO Data Center Management System: Tools for quality control, analysis and access marine data

NASA Astrophysics Data System (ADS)

Casas, Antonia; Garcia, Maria Jesus; Nikouline, Andrei

2010-05-01

Since 1994 the Data Centre of the Spanish Oceanographic Institute develops system for archiving and quality control of oceanographic data. The work started in the frame of the European Marine Science & Technology Programme (MAST) when a consortium of several Mediterranean Data Centres began to work on the MEDATLAS project. Along the years, old software modules for MS DOS were rewritten, improved and migrated to Windows environment. Oceanographic data quality control includes now not only vertical profiles (mainly CTD and bottles observations) but also time series of currents and sea level observations. New powerful routines for analysis and for graphic visualization were added. Data presented originally in ASCII format were organized recently in an open source MySQL database. Nowadays, the IEO, as part of SeaDataNet Infrastructure, has designed and developed a new information system, consistent with the ISO 19115 and SeaDataNet standards, in order to manage the large and diverse marine data and information originated in Spain by different sources, and to interoperate with SeaDataNet. The system works with data stored in ASCII files (MEDATLAS, ODV) as well as data stored within the relational database. The components of the system are: 1.MEDATLAS Format and Quality Control - QCDAMAR: Quality Control of Marine Data. Main set of tools for working with data presented as text files. Includes extended quality control (searching for duplicated cruises and profiles, checking date, position, ship velocity, constant profiles, spikes, density inversion, sounding, acceptable data, impossible regional values,...) and input/output filters. - QCMareas: A set of procedures for the quality control of tide gauge data according to standard international Sea Level Observing System. These procedures include checking for unexpected anomalies in the time series, interpolation, filtering, computation of basic statistics and residuals. 2. DAMAR: A relational data base (MySql) designed to manage the wide variety of marine information as common vocabularies, Catalogues (CSR & EDIOS), Data and Metadata. 3.Other tools for analysis and data management - Import_DB: Script to import data and metadata from the Medatlas ASCII files into the database. - SelDamar/Selavi: interface with the database for local and web access. Allows selective retrievals applying the criteria introduced by the user, as geographical bounds, data responsible, cruises, platform, time periods, etc. Includes also statistical reference values calculation, plotting of original and mean profiles together with vertical interpolation. - ExtractDAMAR: Script to extract data when they are archived in ASCII files that meet the criteria upon an user request through SelDamar interface and export them in ODV format, making also a unit conversion.

User’s guide to the North Pacific Pelagic Seabird Database 2.0

USGS Publications Warehouse

Drew, Gary S.; Piatt, John F.; Renner, Martin

2015-07-13

The North Pacific Pelagic Seabird Database (NPPSD) was created in 2005 to consolidate data on the oceanic distribution of marine bird species in the North Pacific. Most of these data were collected on surveys by counting species within defined areas and at known locations (that is, on strip transects). The NPPSD also contains observations of other bird species and marine mammals. The original NPPSD combined data from 465 surveys conducted between 1973 and 2002, primarily in waters adjacent to Alaska. These surveys included 61,195 sample transects with location, environment, and metadata information, and the data were organized in a flat-file format. In developing NPPSD 2.0, our goals were to add new datasets, to make significant improvements to database functionality and to provide the database online. NPPSD 2.0 includes data from a broader geographic range within the North Pacific, including new observations made offshore of the Russian Federation, Japan, Korea, British Columbia (Canada), Oregon, and California. These data were imported into a relational database, proofed, and structured in a common format. NPPSD 2.0 contains 351,674 samples (transects) collected between 1973 and 2012, representing a total sampled area of 270,259 square kilometers, and extends the time series of samples in some areas—notably the Bering Sea—to four decades. It contains observations of 16,988,138 birds and 235,545 marine mammals and is available on the NPPSD Web site. Supplementary materials include an updated set of standardized taxonomic codes, reference maps that show the spatial and temporal distribution of the survey efforts and a downloadable query tool.

Historical hydrology and database on flood events (Apulia, southern Italy)

NASA Astrophysics Data System (ADS)

Lonigro, Teresa; Basso, Alessia; Gentile, Francesco; Polemio, Maurizio

2014-05-01

Historical data about floods represent an important tool for the comprehension of the hydrological processes, the estimation of hazard scenarios as a basis for Civil Protection purposes, as a basis of the rational land use management, especially in karstic areas, where time series of river flows are not available and the river drainage is rare. The research shows the importance of the improvement of existing flood database with an historical approach, finalized to collect past or historical floods event, in order to better assess the occurrence trend of floods, in the case for the Apulian region (south Italy). The main source of records of flood events for Apulia was the AVI (the acronym means Italian damaged areas) database, an existing Italian database that collects data concerning damaging floods from 1918 to 1996. The database was expanded consulting newspapers, publications, and technical reports from 1996 to 2006. In order to expand the temporal range further data were collected searching in the archives of regional libraries. About 700 useful news from 17 different local newspapers were found from 1876 to 1951. From a critical analysis of the 700 news collected since 1876 to 1952 only 437 were useful for the implementation of the Apulia database. The screening of these news showed the occurrence of about 122 flood events in the entire region. The district of Bari, the regional main town, represents the area in which the great number of events occurred; the historical analysis confirms this area as flood-prone. There is an overlapping period (from 1918 to 1952) between old AVI database and new historical dataset obtained by newspapers. With regard to this period, the historical research has highlighted new flood events not reported in the existing AVI database and it also allowed to add more details to the events already recorded. This study shows that the database is a dynamic instrument, which allows a continuous implementation of data, even in real time. More details on previous results of this research activity were recently published (Polemio, 2010; Basso et al., 2012; Lonigro et al., 2013) References Basso A., Lonigro T. and Polemio M. (2012) "The improvement of historical database on damaging hydrogeological events in the case of Apulia (Southern Italy)". Rendiconti online della Società Geologica Italiana, 21: 379-380; Lonigro T., Basso A. and Polemio M. (2013) "Historical database on damaging hydrogeological events in Apulia region (Southern Italy)". Rendiconti online della Società Geologica Italiana, 24: 196-198; Polemio M. (2010) "Historical floods and a recent extreme rainfall event in the Murgia karstic environment (Southern Italy)". Zeitschrift für Geomorphologie, 54(2): 195-219.

Trends in Education Access and Financing during the Transition in Central And Eastern Europe. Social Challenges of Transition Series.

ERIC Educational Resources Information Center

Laporte, Bruno; Ringold, Dena

This paper is one in a series of reports based upon data from the "Social Challenges of Transition (SCT)" database. This cross-country study examines empirical trends in access to and financing of education in nine Central and East European countries. The study substantially improves the understanding of the impact of transition on…

An Experimental Database for Conventional and Alternate Control Concepts on the HSR 1.675% Reference H Model

NASA Technical Reports Server (NTRS)

McMillin, Naomi; Allen, Jerry; Erickson, Gary; Campbell, Jim; Mann, Mike; Kubiatko, Paul; Yingling, David; Mason, Charlie

1999-01-01

The objective was to experimentally evaluate the longitudinal and lateral-directional stability and control characteristics of the Reference H configuration at supersonic and transonic speeds. A series of conventional and alternate control devices were also evaluated at supersonic and transonic speeds. A database on the conventional and alternate control devices was to be created for use in the HSR program.

Homeostasis and Gauss statistics: barriers to understanding natural variability.

PubMed

West, Bruce J

2010-06-01

In this paper, the concept of knowledge is argued to be the top of a three-tiered system of science. The first tier is that of measurement and data, followed by information consisting of the patterns within the data, and ending with theory that interprets the patterns and yields knowledge. Thus, when a scientific theory ceases to be consistent with the database the knowledge based on that theory must be re-examined and potentially modified. Consequently, all knowledge, like glory, is transient. Herein we focus on the non-normal statistics of physiologic time series and conclude that the empirical inverse power-law statistics and long-time correlations are inconsistent with the theoretical notion of homeostasis. We suggest replacing the notion of homeostasis with that of Fractal Physiology.

Assessing air quality in Aksaray with time series analysis

NASA Astrophysics Data System (ADS)

Kadilar, Gamze Özel; Kadilar, Cem

2017-04-01

Sulphur dioxide (SO2) is a major air pollutant caused by the dominant usage of diesel, petrol and fuels by vehicles and industries. One of the most air-polluted city in Turkey is Aksaray. Hence, in this study, the level of SO2 is analyzed in Aksaray based on the database monitored at air quality monitoring station of Turkey. Seasonal Autoregressive Integrated Moving Average (SARIMA) approach is used to forecast the level of SO2 air quality parameter. The results indicate that the seasonal ARIMA model provides reliable and satisfactory predictions for the air quality parameters and expected to be an alternative tool for practical assessment and justification.

Has the aetiology of ischaemic stroke changed in the past decades? Analysis and comparison of data from current and historical stroke databases.

PubMed

Sánchez-Larsen, Á; García-García, J; Ayo-Martín, O; Hernández-Fernández, F; Díaz-Maroto, I; Fernández-Díaz, E; Monteagudo, M; Segura, T

2016-09-16

We aimed to determine whether the aetiology of ischaemic stroke has changed in recent years and, if so, to ascertain the possible reasons for these changes. We analysed the epidemiological history and vascular risk factors of all patients diagnosed with ischaemic stroke at Complejo Hospitalario Universitario de Albacete (CHUA) from 2009 to 2014. Ischaemic stroke subtypes were established using the TOAST criteria. Our results were compared to data from the classic Stroke Data Bank (SDB); in addition, both series were compared to those of other hospital databases covering the period between the two. We analysed 1664 patients (58% were men) with a mean age of 74 years. Stroke aetiology in both series (CHUA, SDB) was as follows: atherosclerosis (12%, 9%), small-vessel occlusion (13%, 25%), cardioembolism (32%, 19%), stroke of other determined aetiology (3%, 4%), and stroke of undetermined aetiology (40%, 44%). Sixty-three percent of the patients from the CHUA and 42% of the patients from the SDB were older than 70 years. Cardioembolic strokes were more prevalent in patients older than 70 years in both series. Untreated hypertension was more frequent in the SDB (SDB = 31% vs CHUA = 10%). The analysis of other databases shows that the prevalence of cardioembolic stroke is increasing worldwide. Our data show that the prevalence of lacunar strokes is decreasing worldwide whereas cardioembolic strokes are increasingly more frequent in both our hospital and other series compared to the SDB. These differences may be explained by population ageing and the improvements in management of hypertension and detection of cardioembolic arrhythmias in stroke units. Copyright © 2016 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

A mapping review of the literature on UK-focused health and social care databases.

PubMed

Cooper, Chris; Rogers, Morwenna; Bethel, Alison; Briscoe, Simon; Lowe, Jenny

2015-03-01

Bibliographic databases are a day-to-day tool of the researcher: they offer the researcher easy and organised access to knowledge, but how much is actually known about the databases on offer? The focus of this paper is UK health and social care databases. These databases are often small, specialised by topic, and provide a complementary literature to the large, international databases. There is, however, good evidence that these databases are overlooked in systematic reviews, perhaps because little is known about what they can offer. To systematically locate and map, published and unpublished literature on the key UK health and social care bibliographic databases. Systematic searching and mapping. Two hundred and forty-two items were identified which specifically related to the 24 of the 34 databases under review. There is little published or unpublished literature specifically analysing the key UK health and social care databases. Since several UK databases have closed, others are at risk, and some are overlooked in reviews, better information is required to enhance our knowledge. Further research on UK health and social care databases is required. This paper suggests the need to develop the evidence base through a series of case studies on each of the databases. © 2014 The authors. Health Information and Libraries Journal © 2014 Health Libraries Journal.

Urinary bladder cancer treated with radical cystectomy: perioperative parameters and early complications prospectively registered in a national population-based database.

PubMed

Jerlström, Tomas; Gårdmark, Truls; Carringer, Malcolm; Holmäng, Sten; Liedberg, Fredrik; Hosseini, Abolfazl; Malmström, Per-Uno; Ljungberg, Börje; Hagberg, Oskar; Jahnson, Staffan

2014-08-01

Cystectomy combined with pelvic lymph-node dissection and urinary diversion entails high morbidity and mortality. Improvements are needed, and a first step is to collect information on the current situation. In 2011, this group took the initiative to start a population-based database in Sweden (population 9.5 million in 2011) with prospective registration of patients and complications until 90 days after cystectomy. This article reports findings from the first year of registration. Participation was voluntary, and data were reported by local urologists or research nurses. Perioperative parameters and early complications classified according to the modified Clavien system were registered, and selected variables of possible importance for complications were analysed by univariate and multivariate logistic regression. During 2011, 285 (65%) of 435 cystectomies performed in Sweden were registered in the database, the majority reported by the seven academic centres. Median blood loss was 1000 ml, operating time 318 min, and length of hospital stay 15 days. Any complications were registered for 103 patients (36%). Clavien grades 1-2 and 3-5 were noted in 19% and 15%, respectively. Thirty-seven patients (13%) were reoperated on at least once. In logistic regression analysis elevated risk of complications was significantly associated with operating time exceeding 318 min in both univariate and multivariate analysis, and with age 76-89 years only in multivariate analysis. It was feasible to start a national population-based registry of radical cystectomies for bladder cancer. The evaluation of the first year shows an increased risk of complications in patients with longer operating time and higher age. The results agree with some previously published series but should be interpreted with caution considering the relatively low coverage, which is expected to be higher in the future.

Operational Monitoring of GOME-2 and IASI Level 1 Product Processing at EUMETSAT

NASA Astrophysics Data System (ADS)

Livschitz, Yakov; Munro, Rosemary; Lang, Rüdiger; Fiedler, Lars; Dyer, Richard; Eisinger, Michael

2010-05-01

The growing complexity of operational level 1 radiance products from Low Earth Orbiting (LEO) platforms like EUMETSATs Metop series makes near-real-time monitoring of product quality a challenging task. The main challenge is to provide a monitoring system which is flexible and robust enough to identify and to react to anomalies which may be previously unknown to the system, as well as to provide all means and parameters necessary in order to support efficient ad-hoc analysis of the incident. The operational monitoring system developed at EUMETSAT for monitoring of GOME-2 and IASI level 1 data allows to perform near-real-time monitoring of operational products and instrument's health in a robust and flexible fashion. For effective information management, the system is based on a relational database (Oracle). An Extract, Transform, Load (ETL) process transforms products in EUMETSAT Polar System (EPS) format into relational data structures. The identification of commonalities between products and instruments allows for a database structure design in such a way that different data can be analyzed using the same business intelligence functionality. An interactive analysis software implementing modern data mining techniques is also provided for a detailed look into the data. The system is effectively used for day-to-day monitoring, long-term reporting, instrument's degradation analysis as well as for ad-hoc queries in case of an unexpected instrument or processing behaviour. Having data from different sources on a single instrument and even from different instruments, platforms or numerical weather prediction within the same database allows effective cross-comparison and looking for correlated parameters. Automatic alarms raised by checking for deviation of certain parameters, for data losses and other events significantly reduce time, necessary to monitor the processing on a day-to-day basis.

Operational Monitoring of GOME-2 and IASI Level 1 Product Processing at EUMETSAT

NASA Astrophysics Data System (ADS)

Livschitz, Y.; Munro, R.; Lang, R.; Fiedler, L.; Dyer, R.; Eisinger, M.

2009-12-01

The growing complexity of operational level 1 radiance products from Low Earth Orbiting (LEO) platforms like EUMETSATs Metop series makes near-real-time monitoring of product quality a challenging task. The main challenge is to provide a monitoring system which is flexible and robust enough to identify and to react to anomalies which may be previously unknown to the system, as well as to provide all means and parameters necessary in order to support efficient ad-hoc analysis of the incident. The operational monitoring system developed at EUMETSAT for monitoring of GOME-2 and IASI level 1 data allows to perform near-real-time monitoring of operational products and instrument’s health in a robust and flexible fashion. For effective information management, the system is based on a relational database (Oracle). An Extract, Transform, Load (ETL) process transforms products in EUMETSAT Polar System (EPS) format into relational data structures. The identification of commonalities between products and instruments allows for a database structure design in such a way that different data can be analyzed using the same business intelligence functionality. An interactive analysis software implementing modern data mining techniques is also provided for a detailed look into the data. The system is effectively used for day-to-day monitoring, long-term reporting, instrument’s degradation analysis as well as for ad-hoc queries in case of an unexpected instrument or processing behaviour. Having data from different sources on a single instrument and even from different instruments, platforms or numerical weather prediction within the same database allows effective cross-comparison and looking for correlated parameters. Automatic alarms raised by checking for deviation of certain parameters, for data losses and other events significantly reduce time, necessary to monitor the processing on a day-to-day basis.

Waveform Fingerprinting for Efficient Seismic Signal Detection

NASA Astrophysics Data System (ADS)

Yoon, C. E.; OReilly, O. J.; Beroza, G. C.

2013-12-01

Cross-correlating an earthquake waveform template with continuous waveform data has proven a powerful approach for detecting events missing from earthquake catalogs. If templates do not exist, it is possible to divide the waveform data into short overlapping time windows, then identify window pairs with similar waveforms. Applying these approaches to earthquake monitoring in seismic networks has tremendous potential to improve the completeness of earthquake catalogs, but because effort scales quadratically with time, it rapidly becomes computationally infeasible. We develop a fingerprinting technique to identify similar waveforms, using only a few compact features of the original data. The concept is similar to human fingerprints, which utilize key diagnostic features to identify people uniquely. Analogous audio-fingerprinting approaches have accurately and efficiently found similar audio clips within large databases; example applications include identifying songs and finding copyrighted content within YouTube videos. In order to fingerprint waveforms, we compute a spectrogram of the time series, and segment it into multiple overlapping windows (spectral images). For each spectral image, we apply a wavelet transform, and retain only the sign of the maximum magnitude wavelet coefficients. This procedure retains just the large-scale structure of the data, providing both robustness to noise and significant dimensionality reduction. Each fingerprint is a high-dimensional, sparse, binary data object that can be stored in a database without significant storage costs. Similar fingerprints within the database are efficiently searched using locality-sensitive hashing. We test this technique on waveform data from the Northern California Seismic Network that contains events not detected in the catalog. We show that this algorithm successfully identifies similar waveforms and detects uncataloged low magnitude events in addition to cataloged events, while running to completion faster than a comparison waveform autocorrelation code.

Spatio-temporal analysis of recent groundwater-level trends in the Red River Delta, Vietnam

NASA Astrophysics Data System (ADS)

Bui, Duong Du; Kawamura, Akira; Tong, Thanh Ngoc; Amaguchi, Hideo; Nakagawa, Naoko

2012-12-01

A groundwater-monitoring network has been in operation in the Red River Delta, Vietnam, since 1995. Trends in groundwater level (1995-2009) in 57 wells in the Holocene unconfined aquifer and 63 wells in the Pleistocene confined aquifer were determined by applying the non-parametric Mann-Kendall trend test and Sen's slope estimator. At each well, 17 time series (e.g. annual, seasonal, monthly), computed from the original data, were analyzed. Analysis of the annual groundwater-level means revealed that 35 % of the wells in the unconfined aquifer showed downward trends, while about 21 % showed upward trends. On the other hand, confined-aquifer groundwater levels experienced downward trends in almost all locations. Spatial distributions of trends indicated that the strongly declining trends (>0.3 m/year) were mainly found in urban areas around Hanoi where there is intensive abstraction of groundwater. Although the trend results for most of the 17 time series at a given well were quite similar, different trend patterns were detected in several. The findings reflect unsustainable groundwater development and the importance of maintaining groundwater monitoring and a database in the Delta, particularly in urban areas.

Seasonal dynamics of bacterial meningitis: a time-series analysis.

PubMed

Paireau, Juliette; Chen, Angelica; Broutin, Helene; Grenfell, Bryan; Basta, Nicole E

2016-06-01

Bacterial meningitis, which is caused mainly by Neisseria meningitidis, Haemophilus influenzae, and Streptococcus pneumoniae, inflicts a substantial burden of disease worldwide. Yet, the temporal dynamics of this disease are poorly characterised and many questions remain about the ecology of the disease. We aimed to comprehensively assess seasonal trends in bacterial meningitis on a global scale. We developed the first bacterial meningitis global database by compiling monthly incidence data as reported by country-level surveillance systems. Using country-level wavelet analysis, we identified whether a 12 month periodic component (annual seasonality) was detected in time-series that had at least 5 years of data with at least 40 cases reported per year. We estimated the mean timing of disease activity by computing the centre of gravity of the distribution of cases and investigated whether synchrony exists between the three pathogens responsible for most cases of bacterial meningitis. We used country-level data from 66 countries, including from 47 countries outside the meningitis belt in sub-Saharan Africa. A persistent seasonality was detected in 49 (96%) of the 51 time-series from 38 countries eligible for inclusion in the wavelet analyses. The mean timing of disease activity had a latitudinal trend, with bacterial meningitis seasons peaking during the winter months in countries in both the northern and southern hemispheres. The three pathogens shared similar seasonality, but time-shifts differed slightly by country. Our findings provide key insight into the seasonal dynamics of bacterial meningitis and add to knowledge about the global epidemiology of meningitis and the host, environment, and pathogen characteristics driving these patterns. Comprehensive understanding of global seasonal trends in meningitis could be used to design more effective prevention and control strategies. Princeton University Health Grand Challenge, US National Institutes of Health (NIH), NIH Fogarty International Center Research and Policy for Infectious Disease Dynamics programme (RAPIDD), Bill & Melinda Gates Foundation. Copyright © 2016 Paireau et al. Open Access article distributed under the terms of CC BY NC-ND. Published by Elsevier Ltd.. All rights reserved.

Seasonal dynamics of bacterial meningitis: a time-series analysis

PubMed Central

Paireau, Juliette; Chen, Angelica; Broutin, Helene; Grenfell, Bryan; Basta, Nicole E

2017-01-01

Summary Background Bacterial meningitis, which is caused mainly by Neisseria meningitidis, Haemophilus influenzae, and Streptococcus pneumoniae, inflicts a substantial burden of disease worldwide. Yet, the temporal dynamics of this disease are poorly characterised and many questions remain about the ecology of the disease. We aimed to comprehensively assess seasonal trends in bacterial meningitis on a global scale. Methods We developed the first bacterial meningitis global database by compiling monthly incidence data as reported by country-level surveillance systems. Using country-level wavelet analysis, we identified whether a 12 month periodic component (annual seasonality) was detected in time-series that had at least 5 years of data with at least 40 cases reported per year. We estimated the mean timing of disease activity by computing the centre of gravity of the distribution of cases and investigated whether synchrony exists between the three pathogens responsible for most cases of bacterial meningitis. Findings We used country-level data from 66 countries, including from 47 countries outside the meningitis belt in sub-Saharan Africa. A persistent seasonality was detected in 49 (96%) of the 51 time-series from 38 countries eligible for inclusion in the wavelet analyses. The mean timing of disease activity had a latitudinal trend, with bacterial meningitis seasons peaking during the winter months in countries in both the northern and southern hemispheres. The three pathogens shared similar seasonality, but time-shifts differed slightly by country. Interpretation Our findings provide key insight into the seasonal dynamics of bacterial meningitis and add to knowledge about the global epidemiology of meningitis and the host, environment, and pathogen characteristics driving these patterns. Comprehensive understanding of global seasonal trends in meningitis could be used to design more effective prevention and control strategies. Funding Princeton University Health Grand Challenge, US National Institutes of Health (NIH), NIH Fogarty International Center Research and Policy for Infectious Disease Dynamics programme (RAPIDD), Bill & Melinda Gates Foundation. PMID:27198841

Development and application of basis database for materials life cycle assessment in china

NASA Astrophysics Data System (ADS)

Li, Xiaoqing; Gong, Xianzheng; Liu, Yu

2017-03-01

As the data intensive method, high quality environmental burden data is an important premise of carrying out materials life cycle assessment (MLCA), and the reliability of data directly influences the reliability of the assessment results and its application performance. Therefore, building Chinese MLCA database is the basic data needs and technical supports for carrying out and improving LCA practice. Firstly, some new progress on database which related to materials life cycle assessment research and development are introduced. Secondly, according to requirement of ISO 14040 series standards, the database framework and main datasets of the materials life cycle assessment are studied. Thirdly, MLCA data platform based on big data is developed. Finally, the future research works were proposed and discussed.

BIOFRAG – a new database for analyzing BIOdiversity responses to forest FRAGmentation

PubMed Central

Pfeifer, Marion; Lefebvre, Veronique; Gardner, Toby A; Arroyo-Rodriguez, Victor; Baeten, Lander; Banks-Leite, Cristina; Barlow, Jos; Betts, Matthew G; Brunet, Joerg; Cerezo, Alexis; Cisneros, Laura M; Collard, Stuart; D'Cruze, Neil; da Silva Motta, Catarina; Duguay, Stephanie; Eggermont, Hilde; Eigenbrod, Felix; Hadley, Adam S; Hanson, Thor R; Hawes, Joseph E; Heartsill Scalley, Tamara; Klingbeil, Brian T; Kolb, Annette; Kormann, Urs; Kumar, Sunil; Lachat, Thibault; Lakeman Fraser, Poppy; Lantschner, Victoria; Laurance, William F; Leal, Inara R; Lens, Luc; Marsh, Charles J; Medina-Rangel, Guido F; Melles, Stephanie; Mezger, Dirk; Oldekop, Johan A; Overal, William L; Owen, Charlotte; Peres, Carlos A; Phalan, Ben; Pidgeon, Anna M; Pilia, Oriana; Possingham, Hugh P; Possingham, Max L; Raheem, Dinarzarde C; Ribeiro, Danilo B; Ribeiro Neto, Jose D; Douglas Robinson, W; Robinson, Richard; Rytwinski, Trina; Scherber, Christoph; Slade, Eleanor M; Somarriba, Eduardo; Stouffer, Philip C; Struebig, Matthew J; Tylianakis, Jason M; Tscharntke, Teja; Tyre, Andrew J; Urbina Cardona, Jose N; Vasconcelos, Heraldo L; Wearn, Oliver; Wells, Konstans; Willig, Michael R; Wood, Eric; Young, Richard P; Bradley, Andrew V; Ewers, Robert M

2014-01-01

Habitat fragmentation studies have produced complex results that are challenging to synthesize. Inconsistencies among studies may result from variation in the choice of landscape metrics and response variables, which is often compounded by a lack of key statistical or methodological information. Collating primary datasets on biodiversity responses to fragmentation in a consistent and flexible database permits simple data retrieval for subsequent analyses. We present a relational database that links such field data to taxonomic nomenclature, spatial and temporal plot attributes, and environmental characteristics. Field assessments include measurements of the response(s) (e.g., presence, abundance, ground cover) of one or more species linked to plots in fragments within a partially forested landscape. The database currently holds 9830 unique species recorded in plots of 58 unique landscapes in six of eight realms: mammals 315, birds 1286, herptiles 460, insects 4521, spiders 204, other arthropods 85, gastropods 70, annelids 8, platyhelminthes 4, Onychophora 2, vascular plants 2112, nonvascular plants and lichens 320, and fungi 449. Three landscapes were sampled as long-term time series (>10 years). Seven hundred and eleven species are found in two or more landscapes. Consolidating the substantial amount of primary data available on biodiversity responses to fragmentation in the context of land-use change and natural disturbances is an essential part of understanding the effects of increasing anthropogenic pressures on land. The consistent format of this database facilitates testing of generalizations concerning biologic responses to fragmentation across diverse systems and taxa. It also allows the re-examination of existing datasets with alternative landscape metrics and robust statistical methods, for example, helping to address pseudo-replication problems. The database can thus help researchers in producing broad syntheses of the effects of land use. The database is dynamic and inclusive, and contributions from individual and large-scale data-collection efforts are welcome. PMID:24967073

Qualitative and Quantitative Pedigree Analysis: Graph Theory, Computer Software, and Case Studies.

ERIC Educational Resources Information Center

Jungck, John R.; Soderberg, Patti

1995-01-01

Presents a series of elementary mathematical tools for re-representing pedigrees, pedigree generators, pedigree-driven database management systems, and case studies for exploring genetic relationships. (MKR)

Elective change of surgeon during the OR day has an operationally negligible impact on turnover time.

PubMed

Austin, Thomas M; Lam, Humphrey V; Shin, Naomi S; Daily, Bethany J; Dunn, Peter F; Sandberg, Warren S

2014-08-01

To compare turnover times for a series of elective cases with surgeons following themselves with turnover times for a series of previously scheduled elective procedures for which the succeeding surgeon differed from the preceding surgeon. Retrospective cohort study. University-affiliated teaching hospital. The operating room (OR) statistical database was accessed to gather 32 months of turnover data from a large academic institution. Turnover time data for the same-surgeon and surgeon-swap groups were batched by month to minimize autocorrelation and achieve data normalization. Two-way analysis of variance (ANOVA) using the monthly batched data was performed with surgeon swapping and changes in procedure category as variables of turnover time. Similar analyses were performed using individual surgical services, hourly time intervals during the surgical day, and turnover frequency per OR as additional covariates to surgeon swapping. The mean (95% confidence interval [CI]) same-surgeon turnover time was 43.6 (43.2 - 44.0) minutes versus 51.0 (50.5 - 51.6) minutes for a planned surgeon swap (P < 0.0001). This resulted in a difference (95% CI) of 7.4 (6.8 - 8.1) minutes. The exact increase in turnover time was dependent on surgical service, change in subsequent procedure type, time of day when the turnover occurred, and turnover frequency. The investigated institution averages 2.5 cases per OR per day. The cumulative additional turnover time (far less than one hour per OR per day) for switching surgeons definitely does not allow the addition of another elective procedure if the difference could be eliminated. A flexible scheduling policy allowing surgeon swapping rather than requiring full blocks incurs minimal additional staffed time during the OR day while allowing the schedule to be filled with available elective cases. Copyright © 2014 Elsevier Inc. All rights reserved.

[Scimitar syndrome: a case series].

PubMed

Jaramillo González, Carlos; Karam Bechara, José; Sáenz Gómez, Jessica; Siegert Olivares, Augusto; Jamaica Balderas, Lourdes

Scimitar syndrome is a rare and complex congenital anomaly of the lung with multiple variables and is named for its resemblance to the classical radiological crooked sword. Its defining feature is the anomalous pulmonary drainage. It is associated with various cardiothoracic malformations and a wide spectrum of clinical manifestations. Nine patients diagnosed with scimitar syndrome found in the database of Hospital Infantil de México between 2009 and 2013 were reviewed. Demographic records, clinical status and hemodynamic parameters reported were collected. This case series called attention to certain differences between our group of patients and those reported in the international literature. Patients were predominantly female and were diagnosed between 1 and 20 months of life. All were asymptomatic at the time of the study. Half of the patients had a history of respiratory disease and all patients had with pulmonary hypertension. Surgical management was required in on-third of the patient group. Copyright © 2014 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

Scaling of seismic memory with earthquake size

NASA Astrophysics Data System (ADS)

Zheng, Zeyu; Yamasaki, Kazuko; Tenenbaum, Joel; Podobnik, Boris; Tamura, Yoshiyasu; Stanley, H. Eugene

2012-07-01

It has been observed that discrete earthquake events possess memory, i.e., that events occurring in a particular location are dependent on the history of that location. We conduct an analysis to see whether continuous real-time data also display a similar memory and, if so, whether such autocorrelations depend on the size of earthquakes within close spatiotemporal proximity. We analyze the seismic wave form database recorded by 64 stations in Japan, including the 2011 “Great East Japan Earthquake,” one of the five most powerful earthquakes ever recorded, which resulted in a tsunami and devastating nuclear accidents. We explore the question of seismic memory through use of mean conditional intervals and detrended fluctuation analysis (DFA). We find that the wave form sign series show power-law anticorrelations while the interval series show power-law correlations. We find size dependence in earthquake autocorrelations: as the earthquake size increases, both of these correlation behaviors strengthen. We also find that the DFA scaling exponent α has no dependence on the earthquake hypocenter depth or epicentral distance.

Changing pattern of natural hazards due to extreme hydro-meteorological conditions (Apulia, southern Italy)

NASA Astrophysics Data System (ADS)

Polemio, Maurizio; Lonigro, Teresa

2013-04-01

Recent international researches have underlined the evidences of climate changes throughout the world. Among the consequences of climate change, there is the increase in the frequency and magnitude of natural disasters, such as droughts, windstorms, heat waves, landslides, floods and secondary floods (i.e. rapid accumulation or pounding of surface water with very low flow velocity). The Damaging Hydrogeological Events (DHEs) can be defined as the occurrence of one or more simultaneous aforementioned phenomena causing damages. They represent a serious problem, especially in DHE-prone areas with growing urbanisation. In these areas the increasing frequency of extreme hydrological events could be related to climate variations and/or urban development. The historical analysis of DHEs can support decision making and land-use planning, ultimately reducing natural risks. The paper proposes a methodology, based on both historical and time series approaches, used for describing the influence of climatic variability on the number of phenomena observed. The historical approach is finalised to collect phenomenon historical data. The historical flood and landslide data are important for the comprehension of the evolution of a study area and for the estimation of risk scenarios as a basis for civil protection purposes. Phenomenon historical data is useful for expanding the historical period of investigation in order to assess the occurrence trend of DHEs. The time series approach includes the collection and the statistical analysis of climatic and rainfall data (monthly rainfall, wet days, rainfall intensity, and temperature data together with the annual maximum of short-duration rainfall data, from 1 hour to 5 days), which are also used as a proxy for floods and landslides. The climatic and rainfall data are useful to characterise the climate variations and trends and to roughly assess the effects of these trends on river discharge and on the triggering of landslides. The time series approach is completed by tools to analyse simultaneously all data types. The methodology was tested considering a selected Italian region (Apulia, southern Italy). The data were collected in two databases: a damaging hydrogeological event database (1186 landslides and floods since 1918) and a climate database (from 1877; short-duration rainfall from 1921). A statistically significant decreasing trend of rainfall intensity and an increasing trend of temperature, landslides, and DHEs were observed. A generalised decreasing trend of short-duration rainfall was observed. If there is not an evident relationship between climate variability and the variability of DHE occurrences, the role of anthropogenic modifications (increasing use or misuse of flood- and landslide-prone areas) could be hypothesized to justify the increasing occurrences of floods and landslides.. This study identifies the advantages of a simplifying approach to reduce the intrinsic complexities of the spatial-temporal analysis of climate variability, permitting the simultaneous analysis of the modification of flood and landslide occurrences.

Ventriculoperitoneal shunt insertion for hydrocephalus in human immunodeficiency virus-infected adults: a systematic review and meta-analysis protocol.

PubMed

Loan, James J M; Mankahla, Ncedile; Meintjes, Graeme; Fieggen, A Graham

2017-10-16

Hydrocephalus is a recognised complication of human immunodeficiency virus (HIV)-related opportunistic infections. Symptomatic raised cerebrospinal fluid pressure can be treated with ventriculoperitoneal shunt insertion (VPS). In HIV-infected patients however, there is a concern that VPS might be associated with unacceptably high rates of mortality. We aim to systematically review and appraise published literature to determine reported outcomes and identify predictors of outcome following VPS in relevant subgroups of HIV-infected adults. The following electronic databases will be searched: The Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (PubMed), EMBASE, CINAHL (EBSCOhost), LILACS (BIREME), Research Registry ( www.researchregistry.com ), the metaRegister of Controlled Trials (mRCT) ( www.controlled-trials.com ), ClinicalTrials.gov ( www.clinicaltrials.gov ) and OpenSIGLE database. Any randomised studies, cohort studies, case-control studies, interrupted time series or sequential case series reporting survival following VPS in HIV-infected individuals will be included. If high-quality homogenous studies exist, meta-analysis will be conducted to determine 1-, 6- and 12-month mortality with comparison made between underlying aetiologies of hydrocephalus. This study will generate a comprehensive review of VPS in HIV-infected patients for publication. The primary outcome of meta-analysis is 12-month survival. If only low-quality, heterogeneous studies are available, this study will demonstrate this deficiency and will be of value in justifying and aiding the design of future studies. PROSPERO CRD42016052239.

Empirical performance of the self-controlled case series design: lessons for developing a risk identification and analysis system.

PubMed

Suchard, Marc A; Zorych, Ivan; Simpson, Shawn E; Schuemie, Martijn J; Ryan, Patrick B; Madigan, David

2013-10-01

The self-controlled case series (SCCS) offers potential as an statistical method for risk identification involving medical products from large-scale observational healthcare data. However, analytic design choices remain in encoding the longitudinal health records into the SCCS framework and its risk identification performance across real-world databases is unknown. To evaluate the performance of SCCS and its design choices as a tool for risk identification in observational healthcare data. We examined the risk identification performance of SCCS across five design choices using 399 drug-health outcome pairs in five real observational databases (four administrative claims and one electronic health records). In these databases, the pairs involve 165 positive controls and 234 negative controls. We also consider several synthetic databases with known relative risks between drug-outcome pairs. We evaluate risk identification performance through estimating the area under the receiver-operator characteristics curve (AUC) and bias and coverage probability in the synthetic examples. The SCCS achieves strong predictive performance. Twelve of the twenty health outcome-database scenarios return AUCs >0.75 across all drugs. Including all adverse events instead of just the first per patient and applying a multivariate adjustment for concomitant drug use are the most important design choices. However, the SCCS as applied here returns relative risk point-estimates biased towards the null value of 1 with low coverage probability. The SCCS recently extended to apply a multivariate adjustment for concomitant drug use offers promise as a statistical tool for risk identification in large-scale observational healthcare databases. Poor estimator calibration dampens enthusiasm, but on-going work should correct this short-coming.

Exploration of ToxCast/Tox21 bioassays as candidate bioanalytical tools for measuring groups of chemicals in water.

PubMed

Louisse, Jochem; Dingemans, Milou M L; Baken, Kirsten A; van Wezel, Annemarie P; Schriks, Merijn

2018-06-14

The present study explores the ToxCast/Tox21 database to select candidate bioassays as bioanalytical tools for measuring groups of chemicals in water. To this aim, the ToxCast/Tox21 database was explored for bioassays that detect polycyclic aromatic hydrocarbons (PAHs), aromatic amines (AAs), (chloro)phenols ((C)Ps) and halogenated aliphatic hydrocarbons (HAliHs), which are included in the European and/or Dutch Drinking Water Directives. Based on the analysis of the availability and performance of bioassays included in the database, we concluded that several bioassays are suitable as bioanalytical tools for assessing the presence of PAHs and (C)Ps in drinking water sources. No bioassays were identified for AAs and HAliHs, due to the limited activity of these chemicals and/or the limited amount of data on these chemicals in the database. A series of bioassays was selected that measure molecular or cellular effects that are covered by bioassays currently in use for chemical water quality monitoring. Interestingly, also bioassays were selected that represent molecular or cellular effects that are not covered by bioassays currently applied. The usefulness of these newly identified bioassays as bioanalytical tools should be further evaluated in follow-up studies. Altogether, this study shows how exploration of the ToxCast/Tox21 database provides a series of candidate bioassays as bioanalytical tools for measuring groups of chemicals in water. This assessment can be performed for any group of chemicals of interest (if represented in the database), and may provide candidate bioassays that can be used to complement the currently applied bioassays for chemical water quality assessment. Copyright © 2018. Published by Elsevier Ltd.

Long-term follow-up for keystone design perforator island flap for closure of myelomeningocele.

PubMed

Donaldson, Christopher; Murday, Hamsaveni K M; Gutman, Matthew J; Maher, Rory; Goldschlager, Tony; Xenos, Chris; Danks, R Andrew

2018-04-01

We have previously reported a small series on the closure of large myelomeningocele (MMC) defects with a keystone design perforator island flap (KDPIF) in a paediatric neurosurgical centre in Australia. We are now presenting an updated longer term follow-up of an expanded series demonstrating longer term durability of this vascularized flap for large myelomeningocele defects. The prospective data from the Monash Neurosurgical Database were used to select all cases of MMC between December 2008 and September 2016. Retrospective analysis of the neurosurgical database revealed an additional three patients who underwent KDPIF closure at the Monash Medical Centre for MMC repair at birth. Wound healing was satisfactory in all six cases. With delayed follow-up, there was no associated skin flap separation, skin flap dehiscence, skin flap necrosis, cerebro-spinal fluid leak, however two infections were encountered, both resolved with conservative management including antibiotics and simple washout. In this expanded case series with increased longevity of follow-up, the keystone design perforator island flap remains a robust alternative for closure of large myelomeningocele defects.

New reconstruction of the sunspot group numbers since 1739 using direct calibration and "backbone" methods

NASA Astrophysics Data System (ADS)

Chatzistergos, Theodosios; Usoskin, Ilya G.; Kovaltsov, Gennady A.; Krivova, Natalie A.; Solanki, Sami K.

2017-06-01

Context. The group sunspot number (GSN) series constitute the longest instrumental astronomical database providing information on solar activity. This database is a compilation of observations by many individual observers, and their inter-calibration has usually been performed using linear rescaling. There are multiple published series that show different long-term trends for solar activity. Aims: We aim at producing a GSN series, with a non-linear non-parametric calibration. The only underlying assumptions are that the differences between the various series are due to different acuity thresholds of the observers, and that the threshold of each observer remains constant throughout the observing period. Methods: We used a daisy chain process with backbone (BB) observers and calibrated all overlapping observers to them. We performed the calibration of each individual observer with a probability distribution function (PDF) matrix constructed considering all daily values for the overlapping period with the BB. The calibration of the BBs was carried out in a similar manner. The final series was constructed by merging different BB series. We modelled the propagation of errors straightforwardly with Monte Carlo simulations. A potential bias due to the selection of BBs was investigated and the effect was shown to lie within the 1σ interval of the produced series. The exact selection of the reference period was shown to have a rather small effect on our calibration as well. Results: The final series extends back to 1739 and includes data from 314 observers. This series suggests moderate activity during the 18th and 19th century, which is significantly lower than the high level of solar activity predicted by other recent reconstructions applying linear regressions. Conclusions: The new series provides a robust reconstruction, based on modern and non-parametric methods, of sunspot group numbers since 1739, and it confirms the existence of the modern grand maximum of solar activity in the second half of the 20th century. Values of the group sunspot number series are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/602/A69

Spatial downscaling and correction of precipitation and temperature time series to high resolution hydrological response units in the Canadian Rocky Mountains

NASA Astrophysics Data System (ADS)

Kienzle, Stefan

2015-04-01

Precipitation is the central driving force of most hydrological processes, and is also the most variable element of the hydrological cycle. As the precipitation to runoff ratio is non-linear, errors in precipitation estimations are amplified in streamflow simulations. Therefore, the accurate estimate of areal precipitation is essential for watershed models and relevant impacts studies. A procedure is presented to demonstrate the spatial distribution of daily precipitation and temperature estimates across the Rocky Mountains within the framework of the ACRU agro-hydrological modelling system (ACRU). ACRU (Schulze, 1995) is a physical-conceptual, semi-distributed hydrological modelling system designed to be responsive to changes in land use and climate. The model has been updated to include specific high-mountain and cold climate routines and is applied to simulate impacts of land cover and climate change on the hydrological behaviour of numerous Rocky Mountain watersheds in Alberta, Canada. Both air temperature and precipitation time series need to be downscaled to hydrological response units (HRUs), as they are the spatial modelling units for the model. The estimation of accurate daily air temperatures is critical for the separation of rain and snow. The precipitation estimation procedure integrates a spatially distributed daily precipitation database for the period 1950 to 2010 at a scale of 10 by 10 km with a 1971-2000 climate normal database available at 2 by 2 km (PRISM). Resulting daily precipitation time series are further downscaled to the spatial resolution of hydrological response units, defined by 100 m elevation bands, land cover, and solar radiation, which have an average size of about 15 km2. As snow measurements are known to have a potential under-catch of up to 40%, further adjustment of snowfall may need to be increased using a procedure by Richter (1995). Finally, precipitation input to HRUs with slopes steeper than 10% need to be further corrected, because the true, sloped area, has a larger area than the planimetric area derived from a GIS. The omission of correcting for sloped areas would result in incorrect calculations of interception volumes, soil moisture storages, groundwater recharge rates, actual evapotranspiration volumes, and runoff coefficients. Daily minimum and maximum air temperatures are estimated for each HRU by downscaling the 10km time series to the HRUs by (a) applying monthly mean lapse rates, estimated either from surrounding climate stations or from the PRISM climate normal dataset in combination with a digital elevation model, (b) adjusting further for aspect of the HRU based on monthly mean incoming solar radiation, and (c) adjusting for canopy cover using the monthly mean leaf area indices. Precipitation estimates can be verified using independent snow water equivalent measurements derived from snow pillow or snow course observations, while temperature estimates are verified against either independent temperature measurements from climate stations, or from fire observation towers.

Comparative Transcriptional Analysis of Loquat Fruit Identifies Major Signal Networks Involved in Fruit Development and Ripening Process.

PubMed

Song, Huwei; Zhao, Xiangxiang; Hu, Weicheng; Wang, Xinfeng; Shen, Ting; Yang, Liming

2016-11-04

Loquat ( Eriobotrya japonica Lindl.) is an important non-climacteric fruit and rich in essential nutrients such as minerals and carotenoids. During fruit development and ripening, thousands of the differentially expressed genes (DEGs) from various metabolic pathways cause a series of physiological and biochemical changes. To better understand the underlying mechanism of fruit development, the Solexa/Illumina RNA-seq high-throughput sequencing was used to evaluate the global changes of gene transcription levels. More than 51,610,234 high quality reads from ten runs of fruit development were sequenced and assembled into 48,838 unigenes. Among 3256 DEGs, 2304 unigenes could be annotated to the Gene Ontology database. These DEGs were distributed into 119 pathways described in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. A large number of DEGs were involved in carbohydrate metabolism, hormone signaling, and cell-wall degradation. The real-time reverse transcription (qRT)-PCR analyses revealed that several genes related to cell expansion, auxin signaling and ethylene response were differentially expressed during fruit development. Other members of transcription factor families were also identified. There were 952 DEGs considered as novel genes with no annotation in any databases. These unigenes will serve as an invaluable genetic resource for loquat molecular breeding and postharvest storage.

Using Landsat imagery to detect, monitor, and project net landscape change

USGS Publications Warehouse

Reker, Ryan R.; Sohl, Terry L.; Gallant, Alisa L.

2015-01-01

Detailed landscape information is a necessary component to bird habitat conservation planning. The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center has been providing information on the Earth’s surface for over 40 years via the continuous series of Landsat satellites. In addition to operating, processing, and disseminating satellite images, EROS is the home to nationwide and global landscape mapping, monitoring, and projection products, including:National Land Cover Database (NLCD) – the definitive land cover dataset for the U.S., with updates occurring at five-year intervals;Global Land Cover Monitoring – producing 30m resolution global land cover;LANDFIRE – Landscape Fire and Resource Management Planning Tools–EROS is a partner in this joint program between U.S. Department of Agriculture and Department of Interior that produces consistent, comprehensive, geospatial data and databases that describe vegetation, wildland fuel, and fire regimes across the U.S.;Land Cover Trends – a landscape monitoring and assessment effort to understand the rates, trends, causes, and consequences of contemporary U.S. land use and land cover change; andLand Use and Land Cover (LULC) Modeling – a project extending contemporary databases of landscape change forward and backward in time through moderate-resolution land cover projections.

Access to Emissions Distributions and Related Ancillary Data through the ECCAD database

NASA Astrophysics Data System (ADS)

Darras, Sabine; Granier, Claire; Liousse, Catherine; De Graaf, Erica; Enriquez, Edgar; Boulanger, Damien; Brissebrat, Guillaume

2017-04-01

The ECCAD database (Emissions of atmospheric Compounds and Compilation of Ancillary Data) provides a user-friendly access to global and regional surface emissions for a large set of chemical compounds and ancillary data (land use, active fires, burned areas, population,etc). The emissions inventories are time series gridded data at spatial resolution from 1x1 to 0.1x0.1 degrees. ECCAD is the emissions database of the GEIA (Global Emissions InitiAtive) project and a sub-project of the French Atmospheric Data Center AERIS (http://www.aeris-data.fr). ECCAD has currently more than 2200 users originating from more than 80 countries. The project benefits from this large international community of users to expand the number of emission datasets made available. ECCAD provides detailed metadata for each of the datasets and various tools for data visualization, for computing global and regional totals and for interactive spatial and temporal analysis. The data can be downloaded as interoperable NetCDF CF-compliant files, i.e. the data are compatible with many other client interfaces. The presentation will provide information on the datasets available within ECCAD, as well as examples of the analysis work that can be done online through the website: http://eccad.aeris-data.fr.

Access to Emissions Distributions and Related Ancillary Data through the ECCAD database

NASA Astrophysics Data System (ADS)

Darras, Sabine; Enriquez, Edgar; Granier, Claire; Liousse, Catherine; Boulanger, Damien; Fontaine, Alain

2016-04-01

The ECCAD database (Emissions of atmospheric Compounds and Compilation of Ancillary Data) provides a user-friendly access to global and regional surface emissions for a large set of chemical compounds and ancillary data (land use, active fires, burned areas, population,etc). The emissions inventories are time series gridded data at spatial resolution from 1x1 to 0.1x0.1 degrees. ECCAD is the emissions database of the GEIA (Global Emissions InitiAtive) project and a sub-project of the French Atmospheric Data Center AERIS (http://www.aeris-data.fr). ECCAD has currently more than 2200 users originating from more than 80 countries. The project benefits from this large international community of users to expand the number of emission datasets made available. ECCAD provides detailed metadata for each of the datasets and various tools for data visualization, for computing global and regional totals and for interactive spatial and temporal analysis. The data can be downloaded as interoperable NetCDF CF-compliant files, i.e. the data are compatible with many other client interfaces. The presentation will provide information on the datasets available within ECCAD, as well as examples of the analysis work that can be done online through the website: http://eccad.aeris-data.fr.

A flatfile of ground motion intensity measurements from induced earthquakes in Oklahoma and Kansas

USGS Publications Warehouse

Rennolet, Steven B.; Moschetti, Morgan P.; Thompson, Eric M.; Yeck, William

2018-01-01

We have produced a uniformly processed database of orientation-independent (RotD50, RotD100) ground motion intensity measurements containing peak horizontal ground motions (accelerations and velocities) and 5-percent-damped pseudospectral accelerations (0.1–10 s) from more than 3,800 M ≥ 3 earthquakes in Oklahoma and Kansas that occurred between January 2009 and December 2016. Ground motion time series were collected from regional, national, and temporary seismic arrays out to 500 km. We relocated the majority of the earthquake hypocenters using a multiple-event relocation algorithm to produce a set of near-uniformly processed hypocentral locations. Ground motion processing followed standard methods, with the primary objective of reducing the effects of noise on the measurements. Regional wave-propagation features and the high seismicity rate required careful selection of signal windows to ensure that we captured the entire ground motion record and that contaminating signals from extraneous earthquakes did not contribute to the database. Processing was carried out with an automated scheme and resulted in a database comprising more than 174,000 records (https://dx.doi.org/10.5066/F73B5X8N). We anticipate that these results will be useful for improved understanding of earthquake ground motions and for seismic hazard applications.

Multifractality and autoregressive processes of dry spell lengths in Europe: an approach to their complexity and predictability

NASA Astrophysics Data System (ADS)

Lana, X.; Burgueño, A.; Serra, C.; Martínez, M. D.

2017-01-01

Dry spell lengths, DSL, defined as the number of consecutive days with daily rain amounts below a given threshold, may provide relevant information about drought regimes. Taking advantage of a daily pluviometric database covering a great extension of Europe, a detailed analysis of the multifractality of the dry spell regimes is achieved. At the same time, an autoregressive process is applied with the aim of predicting DSL. A set of parameters, namely Hurst exponent, H, estimated from multifractal spectrum, f( α), critical Hölder exponent, α 0, for which f( α) reaches its maximum value, spectral width, W, and spectral asymmetry, B, permits a first clustering of European rain gauges in terms of the complexity of their DSL series. This set of parameters also allows distinguishing between time series describing fine- or smooth-structure of the DSL regime by using the complexity index, CI. Results of previous monofractal analyses also permits establishing comparisons between smooth-structures, relatively low correlation dimensions, notable predictive instability and anti-persistence of DSL for European areas, sometimes submitted to long droughts. Relationships are also found between the CI and the mean absolute deviation, MAD, and the optimum autoregressive order, OAO, of an ARIMA( p, d,0) autoregressive process applied to the DSL series. The detailed analysis of the discrepancies between empiric and predicted DSL underlines the uncertainty over predictability of long DSL, particularly for the Mediterranean region.

The U.S. Geological Survey mapping and cartographic database activities, 2006-2010

USGS Publications Warehouse

Craun, Kari J.; Donnelly, John P.; Allord, Gregory J.

2011-01-01

The U.S. Geological Survey (USGS) began systematic topographic mapping of the United States in the 1880s, beginning with scales of 1:250,000 and 1:125,000 in support of geological mapping. Responding to the need for higher resolution and more detail, the 1:62,500-scale, 15-minute, topographic map series was begun in the beginning of the 20th century. Finally, in the 1950s the USGS adopted the 1:24,000-scale, 7.5-minute topographic map series to portray even more detail, completing the coverage of the conterminous 48 states of the United States with this series in 1992. In 2001, the USGS developed the vision and concept of The National Map, a topographic database for the 21st century and the source for a new generation of topographic maps (http://nationalmap.gov/). In 2008, the initial production of those maps began with a 1:24,000-scale digital product. In a separate, but related project, the USGS began scanning the existing inventory of historical topographic maps at all scales to accompany the new topographic maps. The USGS also had developed a digital database of The National Atlas of the United States. The digital version of Atlas is now Web-available and supports a mapping engine for small scale maps of the United States and North America. These three efforts define topographic mapping activities of the USGS during the last few years and are discussed below.

Tsunami early warning in the Mediterranean: role, structure and tricks of pre-computed tsunami simulation databases and matching/forecasting algorithms

NASA Astrophysics Data System (ADS)

Armigliato, Alberto; Pagnoni, Gianluca; Tinti, Stefano

2014-05-01

The general idea that pre-computed simulated scenario databases can play a key role in conceiving tsunami early warning systems is commonly accepted by now. But it was only in the last decade that it started to be applied to the Mediterranean region, taking special impulse from initiatives like the GDACS and from recently concluded EU-funded projects such as TRIDEC and NearToWarn. With reference to these two projects and with the possibility of further developing this research line in the frame of the FP7 ASTARTE project, we discuss some results we obtained regarding two major topics, namely the strategies applicable to the tsunami scenario database building and the design and performance assessment of a timely and "reliable" elementary-scenario combination algorithm to be run in real-time. As for the first theme, we take advantage of the experience gained in the test areas of Western Iberia, Rhodes (Greece) and Cyprus to illustrate the criteria with which a "Matching Scenario Database" (MSDB) can be built. These involve 1) the choice of the main tectonic tsunamigenic sources (or areas), 2) their tessellation with matrices of elementary faults whose dimension heavily depend on the particular studied area and must be a compromise between the needs to represent the tsunamigenic area in sufficient detail and of limiting the number of scenarios to be simulated, 3) the computation of the scenarios themselves, 4) the choice of the relevant simulation outputs and the standardisation of their formats. Regarding the matching/forecast algorithm, we want it to select and combine the MSDB elements based on the initial earthquake magnitude and location estimate, and to produce a forecast of (at least) the tsunami arrival time, amplitude and period at the closest tide-level sensors and in all needed forecast points. We discuss the performance of the algorithm in terms of the time needed to produce the forecast after the earthquake is detected. In particular, we analyse the different contributions of a number of factors such as the efficient code development and availability of cutting-edge hardware to run the code itself, the wise selection of the MSDB outputs to be combined, the choice of the forecast points where water elevation time series must be taken into account, and few others.

Analysis and Exchange of Multimedia Laboratory Data Using the Brain Database

PubMed Central

Wertheim, Steven L.

1990-01-01

Two principal goals of the Brain Database are: 1) to support laboratory data collection and analysis of multimedia information about the nervous system and 2) to support exchange of these data among researchers and clinicians who may be physically distant. This has been achieved by an implementation of experimental and clinical records within a relational database. An Image Series Editor has been created that provides a graphical interface to these data for the purposes of annotation, quantification and other analyses. Cooperating laboratories each maintain their own copies of the Brain Database to which they may add private data. Although the data in a given experimental or patient record will be distributed among many tables and external image files, the user can treat each record as a unit that can be extracted from the local database and sent to a distant colleague.

Space Station Freedom environmental database system (FEDS) for MSFC testing

NASA Technical Reports Server (NTRS)

Story, Gail S.; Williams, Wendy; Chiu, Charles

1991-01-01

The Water Recovery Test (WRT) at Marshall Space Flight Center (MSFC) is the first demonstration of integrated water recovery systems for potable and hygiene water reuse as envisioned for Space Station Freedom (SSF). In order to satisfy the safety and health requirements placed on the SSF program and facilitate test data assessment, an extensive laboratory analysis database was established to provide a central archive and data retrieval function. The database is required to store analysis results for physical, chemical, and microbial parameters measured from water, air and surface samples collected at various locations throughout the test facility. The Oracle Relational Database Management System (RDBMS) was utilized to implement a secured on-line information system with the ECLSS WRT program as the foundation for this system. The database is supported on a VAX/VMS 8810 series mainframe and is accessible from the Marshall Information Network System (MINS). This paper summarizes the database requirements, system design, interfaces, and future enhancements.

Similarity analysis of spectra obtained via reflectance spectrometry in legal medicine.

PubMed

Belenki, Liudmila; Sterzik, Vera; Bohnert, Michael

2014-02-01

In the present study, a series of reflectance spectra of postmortem lividity, pallor, and putrefaction-affected skin for 195 investigated cases in the course of cooling down the corpse has been collected. The reflectance spectrometric measurements were stored together with their respective metadata in a MySQL database. The latter has been managed via a scientific information repository. We propose similarity measures and a criterion of similarity that capture similar spectra recorded at corpse skin. We systematically clustered reflectance spectra from the database as well as their metadata, such as case number, age, sex, skin temperature, duration of cooling, and postmortem time, with respect to the given criterion of similarity. Altogether, more than 500 reflectance spectra have been pairwisely compared. The measures that have been used to compare a pair of reflectance curve samples include the Euclidean distance between curves and the Euclidean distance between derivatives of the functions represented by the reflectance curves at the same wavelengths in the spectral range of visible light between 380 and 750 nm. For each case, using the recorded reflectance curves and the similarity criterion, the postmortem time interval during which a characteristic change in the shape of reflectance spectrum takes place is estimated. The latter is carried out via a software package composed of Java, Python, and MatLab scripts that query the MySQL database. We show that in legal medicine, matching and clustering of reflectance curves obtained by means of reflectance spectrometry with respect to a given criterion of similarity can be used to estimate the postmortem interval.

Internationally coordinated glacier monitoring: strategy and datasets

NASA Astrophysics Data System (ADS)

Hoelzle, Martin; Armstrong, Richard; Fetterer, Florence; Gärtner-Roer, Isabelle; Haeberli, Wilfried; Kääb, Andreas; Kargel, Jeff; Nussbaumer, Samuel; Paul, Frank; Raup, Bruce; Zemp, Michael

2014-05-01

Internationally coordinated monitoring of long-term glacier changes provide key indicator data about global climate change and began in the year 1894 as an internationally coordinated effort to establish standardized observations. Today, world-wide monitoring of glaciers and ice caps is embedded within the Global Climate Observing System (GCOS) in support of the United Nations Framework Convention on Climate Change (UNFCCC) as an important Essential Climate Variable (ECV). The Global Terrestrial Network for Glaciers (GTN-G) was established in 1999 with the task of coordinating measurements and to ensure the continuous development and adaptation of the international strategies to the long-term needs of users in science and policy. The basic monitoring principles must be relevant, feasible, comprehensive and understandable to a wider scientific community as well as to policy makers and the general public. Data access has to be free and unrestricted, the quality of the standardized and calibrated data must be high and a combination of detailed process studies at selected field sites with global coverage by satellite remote sensing is envisaged. Recently a GTN-G Steering Committee was established to guide and advise the operational bodies responsible for the international glacier monitoring, which are the World Glacier Monitoring Service (WGMS), the US National Snow and Ice Data Center (NSIDC), and the Global Land Ice Measurements from Space (GLIMS) initiative. Several online databases containing a wealth of diverse data types having different levels of detail and global coverage provide fast access to continuously updated information on glacier fluctuation and inventory data. For world-wide inventories, data are now available through (a) the World Glacier Inventory containing tabular information of about 130,000 glaciers covering an area of around 240,000 km2, (b) the GLIMS-database containing digital outlines of around 118,000 glaciers with different time stamps and (c) the Randolph Glacier Inventory (RGI), a new and globally complete digital dataset of outlines from about 180,000 glaciers with some meta-information, which has been used for many applications relating to the IPCC AR5 report. Concerning glacier changes, a database (Fluctuations of Glaciers) exists containing information about mass balance, front variations including past reconstructed time series, geodetic changes and special events. Annual mass balance reporting contains information for about 125 glaciers with a subset of 37 glaciers with continuous observational series since 1980 or earlier. Front variation observations of around 1800 glaciers are available from most of the mountain ranges world-wide. This database was recently updated with 26 glaciers having an unprecedented dataset of length changes from from reconstructions of well-dated historical evidence going back as far as the 16th century. Geodetic observations of about 430 glaciers are available. The database is completed by a dataset containing information on special events including glacier surges, glacier lake outbursts, ice avalanches, eruptions of ice-clad volcanoes, etc. related to about 200 glaciers. A special database of glacier photographs contains 13,000 pictures from around 500 glaciers, some of them dating back to the 19th century. A key challenge is to combine and extend the traditional observations with fast evolving datasets from new technologies.

Development and validation of a set of six adaptable prognosis prediction (SAP) models based on time-series real-world big data analysis for patients with cancer receiving chemotherapy: A multicenter case crossover study

PubMed Central

Kanai, Masashi; Okamoto, Kazuya; Yamamoto, Yosuke; Yoshioka, Akira; Hiramoto, Shuji; Nozaki, Akira; Nishikawa, Yoshitaka; Yamaguchi, Daisuke; Tomono, Teruko; Nakatsui, Masahiko; Baba, Mika; Morita, Tatsuya; Matsumoto, Shigemi; Kuroda, Tomohiro; Okuno, Yasushi; Muto, Manabu

2017-01-01

Background We aimed to develop an adaptable prognosis prediction model that could be applied at any time point during the treatment course for patients with cancer receiving chemotherapy, by applying time-series real-world big data. Methods Between April 2004 and September 2014, 4,997 patients with cancer who had received systemic chemotherapy were registered in a prospective cohort database at the Kyoto University Hospital. Of these, 2,693 patients with a death record were eligible for inclusion and divided into training (n = 1,341) and test (n = 1,352) cohorts. In total, 3,471,521 laboratory data at 115,738 time points, representing 40 laboratory items [e.g., white blood cell counts and albumin (Alb) levels] that were monitored for 1 year before the death event were applied for constructing prognosis prediction models. All possible prediction models comprising three different items from 40 laboratory items (40C3 = 9,880) were generated in the training cohort, and the model selection was performed in the test cohort. The fitness of the selected models was externally validated in the validation cohort from three independent settings. Results A prognosis prediction model utilizing Alb, lactate dehydrogenase, and neutrophils was selected based on a strong ability to predict death events within 1–6 months and a set of six prediction models corresponding to 1,2, 3, 4, 5, and 6 months was developed. The area under the curve (AUC) ranged from 0.852 for the 1 month model to 0.713 for the 6 month model. External validation supported the performance of these models. Conclusion By applying time-series real-world big data, we successfully developed a set of six adaptable prognosis prediction models for patients with cancer receiving chemotherapy. PMID:28837592

Visual Analytics of integrated Data Systems for Space Weather Purposes

NASA Astrophysics Data System (ADS)

Rosa, Reinaldo; Veronese, Thalita; Giovani, Paulo

Analysis of information from multiple data sources obtained through high resolution instrumental measurements has become a fundamental task in all scientific areas. The development of expert methods able to treat such multi-source data systems, with both large variability and measurement extension, is a key for studying complex scientific phenomena, especially those related to systemic analysis in space and environmental sciences. In this talk, we present a time series generalization introducing the concept of generalized numerical lattice, which represents a discrete sequence of temporal measures for a given variable. In this novel representation approach each generalized numerical lattice brings post-analytical data information. We define a generalized numerical lattice as a set of three parameters representing the following data properties: dimensionality, size and post-analytical measure (e.g., the autocorrelation, Hurst exponent, etc)[1]. From this representation generalization, any multi-source database can be reduced to a closed set of classified time series in spatiotemporal generalized dimensions. As a case study, we show a preliminary application in space science data, highlighting the possibility of a real time analysis expert system. In this particular application, we have selected and analyzed, using detrended fluctuation analysis (DFA), several decimetric solar bursts associated to X flare-classes. The association with geomagnetic activity is also reported. DFA method is performed in the framework of a radio burst automatic monitoring system. Our results may characterize the variability pattern evolution, computing the DFA scaling exponent, scanning the time series by a short windowing before the extreme event [2]. For the first time, the application of systematic fluctuation analysis for space weather purposes is presented. The prototype for visual analytics is implemented in a Compute Unified Device Architecture (CUDA) by using the K20 Nvidia graphics processing units (GPUs) to reduce the integrated analysis runtime. [1] Veronese et al. doi: 10.6062/jcis.2009.01.02.0021, 2010. [2] Veronese et al. doi:http://dx.doi.org/10.1016/j.jastp.2010.09.030, 2011.

An application of HOMER and ACMANT for homogenising monthly precipitation records in Ireland

NASA Astrophysics Data System (ADS)

Coll, John; Curley, Mary; Domonkos, Peter; Aguilar, Enric; Walsh, Seamus; Sweeney, John

2015-04-01

Climate change studies based only on raw long-term data are potentially flawed due to the many breaks introduced from non-climatic sources. Consequently, accurate climate data is an essential prerequisite for basing climate related decision making on; and quality controlled, homogenised climate data are becoming integral to European Union Member State efforts to deliver climate services. Ireland has a good repository of monthly precipitation data at approximately 1900 locations stored in the Met Éireann database. The record length at individual precipitation stations varies greatly. However, an audit of the data established the continuous record length at each station and the number of missing months, and based on this two initial subsets of station series (n = 88 and n = 110) were identified for preliminary homogenisation efforts. The HOMER joint detection algorithm was applied to the combined network of these 198 longer station series on an Ireland-wide basis where contiguous intact monthly records ranged from ~40 to 71 years (1941 - 2010). HOMER detected 91 breaks in total in the country-wide series analysis distributed across 63 (~32%) of the 71 year series records analysed. In a separate approach, four sub-series clusters (n = 38 - 61) for the 1950 - 2010 period were used in a parallel analysis applying both ACMANT and HOMER to a regionalised split of the 198 series. By comparison ACMANT detected a considerably higher number of breaks across the four regional series clusters, 238 distributed across 123 (~62%) of the 61 year series records analysed. These preliminary results indicate a relatively high proportion of detected breaks in the series, a situation not generally reflected in observed later 20th century precipitation records across Europe (Domonkos, 2014). However, this elevated ratio of series with detected breaks (~32% in HOMER and ~62% in ACMANT) parallels the break detection rate in a recent analysis of series in the Netherlands (Buishand et al 2013). In the case of Ireland, the climate is even more markedly maritime than that of the Netherlands and the spatial correlations between the Irish series are high (>0.8). Therefore it is likely that both HOMER and ACMANT are detecting relatively small breaks in the series; e.g. the overall range of correction amplitudes derived by HOMER were small and only applied to sections of the corrected series. As Ireland has a relatively dense network of highly correlated station series, we anticipate continued high detection rates as the analysis is extended to incorporate a greater number of station series, and that the ongoing work will quantify the extent of any breaks in Ireland's monthly precipitation series. KEY WORDS: Ireland, precipitation, time series, homogenisation, HOMER, ACMANT. References Buishand, T.A., DeMartino, G., Spreeuw, J.N., Brandsma, T. (2013). Homogeneity of precipitation series in the Netherlands and their trends in the past century. International Journal of Climatology. 33:815-833 Domonkos, P. (2014). Homogenisation of precipitation time series with ACMANT. Theoretical and Applied Climatology. 118:1-2. DOI 10.1007/s00704-014-1298-5.

Pan Air Geometry Management System (PAGMS): A data-base management system for PAN AIR geometry data

NASA Technical Reports Server (NTRS)

Hall, J. F.

1981-01-01

A data-base management system called PAGMS was developed to facilitate the data transfer in applications computer programs that create, modify, plot or otherwise manipulate PAN AIR type geometry data in preparation for input to the PAN AIR system of computer programs. PAGMS is composed of a series of FORTRAN callable subroutines which can be accessed directly from applications programs. Currently only a NOS version of PAGMS has been developed.

A knowledge based application of the extended aircraft interrogation and display system

NASA Technical Reports Server (NTRS)

Glover, Richard D.; Larson, Richard R.

1991-01-01

A family of multiple-processor ground support test equipment was used to test digital flight-control systems on high-performance research aircraft. A unit recently built for the F-18 high alpha research vehicle project is the latest model in a series called the extended aircraft interrogation and display system. The primary feature emphasized monitors the aircraft MIL-STD-1553B data buses and provides real-time engineering units displays of flight-control parameters. A customized software package was developed to provide real-time data interpretation based on rules embodied in a highly structured knowledge database. The configuration of this extended aircraft interrogation and display system is briefly described, and the evolution of the rule based package and its application to failure modes and effects testing on the F-18 high alpha research vehicle is discussed.

VizieR Online Data Catalog: Spitzer photometric time series of HD 97658 (Van Grootel+, 2014)

NASA Astrophysics Data System (ADS)

Van Grootel, V.; Gillon, M.; Valencia, D.; Madhusudhan, N.; Dragomir, D.; Howe, A. R.; Burrows, A. S.; Demory, B.-O.; Deming, D.; Ehrenreich, D.; Lovis, C.; Mayor, M.; Pepe, F.; Queloz, D.; Scuflaire, R.; Seager, S.; Segransan, D.; Udry, S.

2017-07-01

We monitored HD 97658 with Spitzer's IRAC camera on 2013 August 10 from 13:01:00 to 18:27:00 UT, corresponding to a transit window as computed from the MOST transit ephemeris (Dragomir et al. 2013, J/ApJ/772/L2). These Spitzer data were acquired in the context of the Cycle 9 program 90072 (PI: M. Gillon) dedicated to the search for the transits of RV-detected low-mass planets. They consist of 2320 sets of 64 individual subarray images obtained at 4.5 μm with an integration time of 0.08 s. They are available on the Spitzer Heritage Archive database under the form of 2320 Basic Calibrated Data files calibrated by the standard Spitzer reduction pipeline (version S19.1.0). (1 data file).

Milliarcsecond Astronomy with the CHARA Array

NASA Astrophysics Data System (ADS)

Schaefer, Gail; ten Brummelaar, Theo; Gies, Douglas; Jones, Jeremy; Farrington, Christopher

2018-01-01

The Center for High Angular Resolution Astronomy offers 50 nights per year of open access time at the CHARA Array. The Array consists of six telescopes linked together as an interferometer, providing sub-milliarcsecond resolution in the optical and near-infrared. The Array enables a variety of scientific studies, including measuring stellar angular diameters, imaging stellar shapes and surface features, mapping the orbits of close binary companions, and resolving circumstellar environments. The open access time is part of an NSF/MSIP funded program to open the CHARA Array to the broader astronomical community. As part of the program, we will build a searchable database for the CHARA data archive and run a series of one-day community workshops at different locations across the country to expand the user base for stellar interferometry and encourage new scientific investigations with the CHARA Array.

Evaluating nitrogen removal by vegetation uptake using satellite image time series in riparian catchments.

PubMed

Wang, Xuelei; Wang, Qiao; Yang, Shengtian; Zheng, Donghai; Wu, Chuanqing; Mannaerts, C M

2011-06-01

Nitrogen (N) removal by vegetation uptake is one of the most important functions of riparian buffer zones in preventing non-point source pollution (NSP), and many studies about N uptake at the river reach scale have proven the effectiveness of plants in controlling nutrient pollution. However, at the watershed level, the riparian zones form dendritic networks and, as such, may be the predominant spatially structured feature in catchments and landscapes. Thus, assessing the functions of riparian system at the basin scale is important. In this study, a new method coupling remote sensing and ecological models was used to assess the N removal by riparian vegetation on a large spatial scale. The study site is located around the Guanting reservoir in Beijing, China, which was abandoned as the source water system for Beijing due to serious NSP in 1997. SPOT 5 data was used to map the land cover, and Landsat-5 TM time series images were used to retrieve land surface parameters. A modified forest nutrient cycling and biomass model (ForNBM) was used to simulate N removal, and the modified net primary productivity (NPP) module was driven by remote sensing image time series. Besides the remote sensing data, the necessary database included meteorological data, soil chemical and physical data and plant nutrient data. Pot and plot experiments were used to calibrate and validate the simulations. Our study has proven that, by coupling remote sensing data and parameters retrieval techniques to plant growth process models, catchment scale estimations of nitrogen uptake rates can be improved by spatial pixel-based modelling. Copyright © 2011 Elsevier B.V. All rights reserved.

A longitudinal model for functional connectivity networks using resting-state fMRI.

PubMed

Hart, Brian; Cribben, Ivor; Fiecas, Mark

2018-06-04

Many neuroimaging studies collect functional magnetic resonance imaging (fMRI) data in a longitudinal manner. However, the current fMRI literature lacks a general framework for analyzing functional connectivity (FC) networks in fMRI data obtained from a longitudinal study. In this work, we build a novel longitudinal FC model using a variance components approach. First, for all subjects' visits, we account for the autocorrelation inherent in the fMRI time series data using a non-parametric technique. Second, we use a generalized least squares approach to estimate 1) the within-subject variance component shared across the population, 2) the baseline FC strength, and 3) the FC's longitudinal trend. Our novel method for longitudinal FC networks seeks to account for the within-subject dependence across multiple visits, the variability due to the subjects being sampled from a population, and the autocorrelation present in fMRI time series data, while restricting the number of parameters in order to make the method computationally feasible and stable. We develop a permutation testing procedure to draw valid inference on group differences in the baseline FC network and change in FC over longitudinal time between a set of patients and a comparable set of controls. To examine performance, we run a series of simulations and apply the model to longitudinal fMRI data collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Overall, we found no difference in the global FC network between Alzheimer's disease patients and healthy controls, but did find differing local aging patterns in the FC between the left hippocampus and the posterior cingulate cortex. Copyright © 2018 Elsevier Inc. All rights reserved.

Using time-series intervention analysis to understand U.S. Medicaid expenditures on antidepressant agents.

PubMed

Ferrand, Yann; Kelton, Christina M L; Guo, Jeff J; Levy, Martin S; Yu, Yan

2011-03-01

Medicaid programs' spending on antidepressants increased from $159 million in 1991 to $2 billion in 2005. The National Institute for Health Care Management attributed this expenditure growth to increases in drug utilization, entry of newer higher-priced antidepressants, and greater prescription drug insurance coverage. Rising enrollment in Medicaid has also contributed to this expenditure growth. This research examines the impact of specific events, including branded-drug and generic entry, a black box warning, direct-to-consumer advertising (DTCA), and new indication approval, on Medicaid spending on antidepressants. Using quarterly expenditure data for 1991-2005 from the national Medicaid pharmacy claims database maintained by the Centers for Medicare and Medicaid Services, a time-series autoregressive integrated moving average (ARIMA) intervention analysis was performed on 6 specific antidepressant drugs and on overall antidepressant spending. Twenty-nine potentially relevant interventions and their dates of occurrence were identified from the literature. Each was tested for an impact on the time series. Forecasts from the models were compared with a holdout sample of actual expenditure data. Interventions with significant impacts on Medicaid expenditures included the patent expiration of Prozac® (P<0.01) and the entry of generic paroxetine producers (P=0.04), which reduced expenditures on Prozac® and Paxil®, respectively, and the 1997 increase in DTCA (P=0.05), which increased spending on Wellbutrin®. Except for Paxil®, the ARIMA models had low prediction errors. Generic entry at the aggregate level did not lead to a reduction in overall expenditures (P>0.05), implying that the expanding market for antidepressants overwhelmed the effect of generic competition. Copyright © 2011 Elsevier Inc. All rights reserved.

A time-series analysis of the relation between unemployment rate and hospital admission for acute myocardial infarction and stroke in Brazil over more than a decade.

PubMed

Katz, Marcelo; Bosworth, Hayden B; Lopes, Renato D; Dupre, Matthew E; Morita, Fernando; Pereira, Carolina; Franco, Fabio G M; Prado, Rogerio R; Pesaro, Antonio E; Wajngarten, Mauricio

2016-12-01

The effect of socioeconomic stressors on the incidence of cardiovascular disease (CVD) is currently open to debate. Using time-series analysis, our study aimed to evaluate the relationship between unemployment rate and hospital admission for acute myocardial infarction (AMI) and stroke in Brazil over a recent 11-year span. Data on monthly hospital admissions for AMI and stroke from March 2002 to December 2013 were extracted from the Brazilian Public Health System Database. The monthly unemployment rate was obtained from the Brazilian Institute for Applied Economic Research, during the same period. The autoregressive integrated moving average (ARIMA) model was used to test the association of temporal series. Statistical significance was set at p<0.05. From March 2002 to December 2013, 778,263 admissions for AMI and 1,581,675 for stroke were recorded. During this time period, the unemployment rate decreased from 12.9% in 2002 to 4.3% in 2013, while admissions due to AMI and stroke increased. However, the adjusted ARIMA model showed a positive association between the unemployment rate and admissions for AMI but not for stroke (estimate coefficient=2.81±0.93; p=0.003 and estimate coefficient=2.40±4.34; p=0.58, respectively). From 2002 to 2013, hospital admissions for AMI and stroke increased, whereas the unemployment rate decreased. However, the adjusted ARIMA model showed a positive association between unemployment rate and admissions due to AMI but not for stroke. Further studies are warranted to validate our findings and to better explore the mechanisms by which socioeconomic stressors, such as unemployment, might impact on the incidence of CVD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Ophthalmology and vision science research: part 5: surfing or sieving--using literature databases wisely.

PubMed

Sherwin, Trevor; Gilhotra, Amardeep K

2006-02-01

Literature databases are an ever-expanding resource available to the field of medical sciences. Understanding how to use such databases efficiently is critical for those involved in research. However, for the uninitiated, getting started is a major hurdle to overcome and for the occasional user, the finer points of database searching remain an unacquired skill. In the fifth and final article in this series aimed at those embarking on ophthalmology and vision science research, we look at how the beginning researcher can start to use literature databases and, by using a stepwise approach, how they can optimize their use. This instructional paper gives a hypothetical example of a researcher writing a review article and how he or she acquires the necessary scientific literature for the article. A prototype search of the Medline database is used to illustrate how even a novice might swiftly acquire the skills required for a medium-level search. It provides examples and key tips that can increase the proficiency of the occasional user. Pitfalls of database searching are discussed, as are the limitations of which the user should be aware.

SIMS: addressing the problem of heterogeneity in databases

NASA Astrophysics Data System (ADS)

Arens, Yigal

1997-02-01

The heterogeneity of remotely accessible databases -- with respect to contents, query language, semantics, organization, etc. -- presents serious obstacles to convenient querying. The SIMS (single interface to multiple sources) system addresses this global integration problem. It does so by defining a single language for describing the domain about which information is stored in the databases and using this language as the query language. Each database to which SIMS is to provide access is modeled using this language. The model describes a database's contents, organization, and other relevant features. SIMS uses these models, together with a planning system drawing on techniques from artificial intelligence, to decompose a given user's high-level query into a series of queries against the databases and other data manipulation steps. The retrieval plan is constructed so as to minimize data movement over the network and maximize parallelism to increase execution speed. SIMS can recover from network failures during plan execution by obtaining data from alternate sources, when possible. SIMS has been demonstrated in the domains of medical informatics and logistics, using real databases.

Fast protein tertiary structure retrieval based on global surface shape similarity.

PubMed

Sael, Lee; Li, Bin; La, David; Fang, Yi; Ramani, Karthik; Rustamov, Raif; Kihara, Daisuke

2008-09-01

Characterization and identification of similar tertiary structure of proteins provides rich information for investigating function and evolution. The importance of structure similarity searches is increasing as structure databases continue to expand, partly due to the structural genomics projects. A crucial drawback of conventional protein structure comparison methods, which compare structures by their main-chain orientation or the spatial arrangement of secondary structure, is that a database search is too slow to be done in real-time. Here we introduce a global surface shape representation by three-dimensional (3D) Zernike descriptors, which represent a protein structure compactly as a series expansion of 3D functions. With this simplified representation, the search speed against a few thousand structures takes less than a minute. To investigate the agreement between surface representation defined by 3D Zernike descriptor and conventional main-chain based representation, a benchmark was performed against a protein classification generated by the combinatorial extension algorithm. Despite the different representation, 3D Zernike descriptor retrieved proteins of the same conformation defined by combinatorial extension in 89.6% of the cases within the top five closest structures. The real-time protein structure search by 3D Zernike descriptor will open up new possibility of large-scale global and local protein surface shape comparison. 2008 Wiley-Liss, Inc.

Periodic and Aperiodic Variability in the Molecular Cloud ρ Ophiuchus

NASA Astrophysics Data System (ADS)

Parks, J. Robert; Plavchan, Peter; White, Russel J.; Gee, Alan H.

2014-03-01

Presented are the results of a near-IR photometric survey of 1678 stars in the direction of the ρ Ophiuchus (ρ Oph) star forming region using data from the 2MASS Calibration Database. For each target in this sample, up to 1584 individual J-, H-, and Ks -band photometric measurements with a cadence of ~1 day are obtained over three observing seasons spanning ~2.5 yr it is the most intensive survey of stars in this region to date. This survey identifies 101 variable stars with ΔKs -band amplitudes from 0.044 to 2.31 mag and Δ(J - Ks ) color amplitudes ranging from 0.053 to 1.47 mag. Of the 72 young ρ Oph star cluster members included in this survey, 79% are variable; in addition, 22 variable stars are identified as candidate members. Based on the temporal behavior of the Ks time-series, the variability is distinguished as either periodic, long time-scale or irregular. This temporal behavior coupled with the behavior of stellar colors is used to assign a dominant variability mechanism. A new period-searching algorithm finds periodic signals in 32 variable stars with periods between 0.49 to 92 days. The chief mechanism driving the periodic variability for 18 stars is rotational modulation of cool starspots while 3 periodically vary due to accretion-induced hot spots. The time-series for six variable stars contains discrete periodic "eclipse-like" features with periods ranging from 3 to 8 days. These features may be asymmetries in the circumstellar disk, potentially sustained or driven by a proto-planet at or near the co-rotation radius. Aperiodic, long time-scale variations in stellar flux are identified in the time-series for 31 variable stars with time-scales ranging from 64 to 790 days. The chief mechanism driving long time-scale variability is variable extinction or mass accretion rates. The majority of the variable stars (40) exhibit sporadic, aperiodic variability over no discernable time-scale. No chief variability mechanism could be identified for these variable stars.

A storage scheme for the real-time database supporting the on-line commitment

NASA Astrophysics Data System (ADS)

Dai, Hong-bin; Jing, Yu-jian; Wang, Hui

2013-07-01

The modern SCADA (Supervisory Control and Data acquisition) systems have been applied to various aspects of everyday life. As the time goes on, the requirements of the applications of the systems vary. Thus the data structure of the real-time database, which is the core of a SCADA system, often needs modification. As a result, the commitment consisting of a sequence of configuration operations modifying the data structure of the real-time database is performed from time to time. Though it is simple to perform the off-line commitment by first stopping and then restarting the system, during which all the data in the real-time database are reconstructed. It is much more preferred or in some cases even necessary to perform the on-line commitment, during which the real-time database can still provide real-time service and the system continues working normally. In this paper, a storage scheme of the data in the real-time database is proposed. It helps the real-time database support its on-line commitment, during which real-time service is still available.

Exercising privacy rights in medical science.

PubMed

Hillmer, Michael; Redelmeier, Donald A

2007-12-04

Privacy laws are intended to preserve human well-being and improve medical outcomes. We used the Sportstats website, a repository of competitive athletic data, to test how easily these laws can be circumvented. We designed a haphazard, unrepresentative case-series analysis and applied unscientific methods based on an Internet connection and idle time. We found it both feasible and titillating to breach anonymity, stockpile personal information and generate misquotations. We extended our methods to snoop on celebrities, link to outside databases and uncover refusal to participate. Throughout our study, we evaded capture and public humiliation despite violating these 6 privacy fundamentals. We suggest that the legitimate principle of safeguarding personal privacy is undermined by the natural human tendency toward showing off.

Analysis of hydraulic fracturing flowback and produced waters using accurate mass: identification of ethoxylated surfactants.

PubMed

Thurman, E Michael; Ferrer, Imma; Blotevogel, Jens; Borch, Thomas

2014-10-07

Two series of ethylene oxide (EO) surfactants, polyethylene glycols (PEGs from EO3 to EO33) and linear alkyl ethoxylates (LAEs C-9 to C-15 with EO3-EO28), were identified in hydraulic fracturing flowback and produced water using a new application of the Kendrick mass defect and liquid chromatography/quadrupole-time-of-flight mass spectrometry. The Kendrick mass defect differentiates the proton, ammonium, and sodium adducts in both singly and doubly charged forms. A structural model of adduct formation is presented, and binding constants are calculated, which is based on a spherical cagelike conformation, where the central cation (NH4(+) or Na(+)) is coordinated with ether oxygens. A major purpose of the study was the identification of the ethylene oxide (EO) surfactants and the construction of a database with accurate masses and retention times in order to unravel the mass spectral complexity of surfactant mixtures used in hydraulic fracturing fluids. For example, over 500 accurate mass assignments are made in a few seconds of computer time, which then is used as a fingerprint chromatogram of the water samples. This technique is applied to a series of flowback and produced water samples to illustrate the usefulness of ethoxylate "fingerprinting", in a first application to monitor water quality that results from fluids used in hydraulic fracturing.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2010)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, NC (USA)

2010-01-01

The 2010 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2007. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2007 were published earlier (Boden et al. 2010). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2013)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, NC (USA)

2013-01-01

The 2013 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2010. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2010 were published earlier (Boden et al. 2013). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2015)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, NC (USA)

2015-01-01

The 2015 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2011. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2011 were published earlier (Boden et al. 2015). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2011)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA)

2011-01-01

The 2011 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2008. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2008 were published earlier (Boden et al. 2011). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2012)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Appalachian State University, Boone, NC (USA)

2012-01-01

The 2012 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2009. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2009 were published earlier (Boden et al. 2012). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (1751-2006) (NDP-058.2009)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Marland, G. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA)

2009-01-01

The 2009 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2006. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2006 were published earlier (Boden et al. 2009). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

Annual Fossil-Fuel CO2 Emissions: Mass of Emissions Gridded by One Degree Latitude by One Degree Longitude (NDP-058.2016)

DOE Data Explorer

Andres, R. J. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Boden, T. A. [Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA)

2016-01-01

The 2016 version of this database presents a time series recording 1° latitude by 1° longitude CO2 emissions in units of million metric tons of carbon per year from anthropogenic sources for 1751-2013. Detailed geographic information on CO2 emissions can be critical in understanding the pattern of the atmospheric and biospheric response to these emissions. Global, regional, and national annual estimates for 1751 through 2013 were published earlier (Boden et al. 2016). Those national, annual CO2 emission estimates were based on statistics about fossil-fuel burning, cement manufacturing and gas flaring in oil fields as well as energy production, consumption, and trade data, using the methods of Marland and Rotty (1984). The national annual estimates were combined with gridded 1° data on political units and 1984 human populations to create the new gridded CO2 emission time series. The same population distribution was used for each of the years as proxy for the emission distribution within each country. The implied assumption for that procedure was that per capita energy use and fuel mixes are uniform over a political unit. The consequence of this first-order procedure is that the spatial changes observed over time are solely due to changes in national energy consumption and nation-based fuel mix. Increases in fossil-fuel CO2 emissions over time are apparent for most areas.

An innovative procedure to assess multi-scale temporal trends in groundwater quality: Example of the nitrate in the Seine-Normandy basin, France

NASA Astrophysics Data System (ADS)

Lopez, Benjamin; Baran, Nicole; Bourgine, Bernard

2015-03-01

The European Water Framework Directive (WFD) asks Member States to identify trends in contaminant concentrations in groundwater and to take measures to reach a good chemical status by 2015. In this study, carried out in a large hydrological basin (95,300 km2), an innovative procedure is described for the assessment of recent trends in groundwater nitrate concentrations both at sampling point and regional scales. Temporal variograms of piezometric and nitrate concentration time series are automatically calculated and fitted in order to classify groundwater according to their temporal pattern. These results are then coupled with aquifer lithology to map spatial units within which the modes of diffuse transport of contaminants towards groundwater are assumed to be the same at all points. These spatial units are suitable for evaluating regional trends. The stability over time of the time series is tested based on the cumulative sum principle, to determine the time period during which the trend should be sought. The Mann-Kendall and Regional-Kendall nonparametric tests for monotonic trends, coupled with the Sen-slope test, are applied to the periods following the point breaks thus determined at both the sampling point or regional scales. This novel procedure is robust and enables rapid processing of large databases of raw data. It would therefore be useful for managing groundwater quality in compliance with the aims of the WFD.

The ego-moving metaphor of time relies on visual experience: No representation of time along the sagittal space in the blind.

PubMed

Rinaldi, Luca; Vecchi, Tomaso; Fantino, Micaela; Merabet, Lotfi B; Cattaneo, Zaira

2018-03-01

In many cultures, humans conceptualize the past as behind the body and the future as in front. Whether this spatial mapping of time depends on visual experience is still not known. Here, we addressed this issue by testing early-blind participants in a space-time motor congruity task requiring them to classify a series of words as referring to the past or the future by moving their hand backward or forward. Sighted participants showed a preferential mapping between forward movements and future-words and backward movements and past-words. Critically, blind participants did not show any such preferential time-space mapping. Furthermore, in a questionnaire requiring participants to think about past and future events, blind participants did not appear to perceive the future as psychologically closer than the past, as it is the case of sighted individuals. These findings suggest that normal visual development is crucial for representing time along the sagittal space. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Extending Glacier Monitoring into the Little Ice Age and Beyond

NASA Astrophysics Data System (ADS)

Nussbaumer, S. U.; Gärtner-Roer, I.; Zemp, M.; Zumbühl, H. J.; Masiokas, M. H.; Espizua, L. E.; Pitte, P.

2011-12-01

Glaciers are among the best natural proxies of climatic changes and, as such, a key variable within the international climate observing system. The worldwide monitoring of glacier distribution and fluctuations has been internationally coordinated for more than a century. Direct measurements of seasonal and annual glacier mass balance are available for the past six decades. Regular observations of glacier front variations have been carried out since the late 19th century. Information on glacier fluctuations before the onset of regular in situ measurements have to be reconstructed from moraines, historical evidence, and a wide range of dating methods. The majority of corresponding data is not available to the scientific community which challenges the reproducibility and direct comparison of the results. Here, we present a first approach towards the standardization of reconstructed Holocene glacier front variations as well as the integration of the corresponding data series into the database of the World Glacier Monitoring Service (www.wgms.ch), within the framework of the Global Terrestrial Network for Glaciers (www.gtn-g.org). The concept for the integration of these reconstructed front variations into the relational glacier database of the WGMS was jointly elaborated and tested by experts of both fields (natural and historical sciences), based on reconstruction series of 15 glaciers in Europe (western/central Alps and southern Norway) and 9 in southern South America. The reconstructed front variation series extend the direct measurements of the 20th century by two centuries in Norway and by four in the Alps and in South America. The storage of the records within the international glacier databases guarantees the long-term availability of the data series and increases the visibility of the scientific research which - in historical glaciology - is often the work of a lifetime. The standardized collection of reconstructed glacier front variations from southern Norway, the western Alps and the southern Andes allows a direct comparison between different glaciers. It is a first step towards a worldwide compilation and free dissemination of Holocene glacier fluctuation series within the internationally coordinated glacier monitoring.

The development of a new database of gas emissions: MAGA, a collaborative web environment for collecting data

NASA Astrophysics Data System (ADS)

Cardellini, C.; Chiodini, G.; Frigeri, A.; Bagnato, E.; Aiuppa, A.; McCormick, B.

2013-12-01

The data on volcanic and non-volcanic gas emissions available online are, as today, incomplete and most importantly, fragmentary. Hence, there is need for common frameworks to aggregate available data, in order to characterize and quantify the phenomena at various spatial and temporal scales. Building on the Googas experience we are now extending its capability, particularly on the user side, by developing a new web environment for collecting and publishing data. We have started to create a new and detailed web database (MAGA: MApping GAs emissions) for the deep carbon degassing in the Mediterranean area. This project is part of the Deep Earth Carbon Degassing (DECADE) research initiative, lunched in 2012 by the Deep Carbon Observatory (DCO) to improve the global budget of endogenous carbon from volcanoes. MAGA database is planned to complement and integrate the work in progress within DECADE in developing CARD (Carbon Degassing) database. MAGA database will allow researchers to insert data interactively and dynamically into a spatially referred relational database management system, as well as to extract data. MAGA kicked-off with the database set up and a complete literature survey on publications on volcanic gas fluxes, by including data on active craters degassing, diffuse soil degassing and fumaroles both from dormant closed-conduit volcanoes (e.g., Vulcano, Phlegrean Fields, Santorini, Nysiros, Teide, etc.) and open-vent volcanoes (e.g., Etna, Stromboli, etc.) in the Mediterranean area and Azores. For each geo-located gas emission site, the database holds images and description of the site and of the emission type (e.g., diffuse emission, plume, fumarole, etc.), gas chemical-isotopic composition (when available), gas temperature and gases fluxes magnitude. Gas sampling, analysis and flux measurement methods are also reported together with references and contacts to researchers expert of the site. Data can be accessed on the network from a web interface or as a data-driven web service, where software clients can request data directly from the database. This way Geographical Information Systems (GIS) and Virtual Globes (e.g., Google Earth) can easily access the database, and data can be exchanged with other database. In details the database now includes: i) more than 1000 flux data about volcanic plume degassing from Etna (4 summit craters and bulk degassing) and Stromboli volcanoes, with time averaged CO2 fluxes of ~ 18000 and 766 t/d, respectively; ii) data from ~ 30 sites of diffuse soil degassing from Napoletan volcanoes, Azores, Canary, Etna, Stromboli, and Vulcano Island, with a wide range of CO2 fluxes (from les than 1 to 1500 t/d) and iii) several data on fumarolic emissions (~ 7 sites) with CO2 fluxes up to 1340 t/day (i.e., Stromboli). When available, time series of compositional data have been archived in the database (e.g., for Campi Flegrei fumaroles). We believe MAGA data-base is an important starting point to develop a large scale, expandable data-base aimed to excite, inspire, and encourage participation among researchers. In addition, the possibility to archive location and qualitative information for gas emission/sites not yet investigated, could stimulate the scientific community for future researches and will provide an indication on the current uncertainty on deep carbon fluxes global estimates.

A web-based tool for groundwater mapping and drought analysis

NASA Astrophysics Data System (ADS)

Christensen, S.; Burns, M.; Jones, N.; Strassberg, G.

2012-12-01

In 2011-2012, the state of Texas saw the worst one-year drought on record. Fluctuations in gravity measured by GRACE satellites indicate that as much as 100 cubic kilometers of water was lost during this period. Much of this came from reservoirs and shallow soil moisture, but a significant amount came from aquifers. In response to this crisis, a Texas Drought Technology Steering Committee (TDTSC) consisting of academics and water managers was formed to develop new tools and strategies to assist the state in monitoring, predicting, and responding to drought events. In this presentation, we describe one of the tools that was developed as part of this effort. When analyzing the impact of drought on groundwater levels, it is fairly common to examine time series data at selected monitoring wells. However, accurately assessing impacts and trends requires both spatial and temporal analysis involving the development of detailed water level maps at various scales. Creating such maps in a flexible and rapid fashion is critical for effective drought analysis, but can be challenging due to the massive amounts of data involved and the processing required to generate such maps. Furthermore, wells are typically not sampled at the same points in time, and so developing a water table map for a particular date requires both spatial and temporal interpolation of water elevations. To address this challenge, a Cloud-based water level mapping system was developed for the state of Texas. The system is based on the Texas Water Development Board (TWDB) groundwater database, but can be adapted to use other databases as well. The system involves a set of ArcGIS workflows running on a server with a web-based front end and a Google Earth plug-in. A temporal interpolation geoprocessing tool was developed to estimate the piezometric heads for all wells in a given region at a specific date using a regression analysis. This interpolation tool is coupled with other geoprocessing tools to filter data and interpolate point elevations spatially to produce water level, drawdown, and depth to groundwater maps. The web interface allows for users to generate these maps at locations and times of interest. A sequence of maps can be generated over a period of time and animated to visualize how water levels are changing. The time series regression analysis can also be used to do short-term predictions of future water levels.

High-Level Data-Abstraction System

NASA Technical Reports Server (NTRS)

Fishwick, P. A.

1986-01-01

Communication with data-base processor flexible and efficient. High Level Data Abstraction (HILDA) system is three-layer system supporting data-abstraction features of Intel data-base processor (DBP). Purpose of HILDA establishment of flexible method of efficiently communicating with DBP. Power of HILDA lies in its extensibility with regard to syntax and semantic changes. HILDA's high-level query language readily modified. Offers powerful potential to computer sites where DBP attached to DEC VAX-series computer. HILDA system written in Pascal and FORTRAN 77 for interactive execution.

DFACS - DATABASE, FORMS AND APPLICATIONS FOR CABLING AND SYSTEMS, VERSION 3.30

NASA Technical Reports Server (NTRS)

Billitti, J. W.

1994-01-01

DFACS is an interactive multi-user computer-aided engineering tool for system level electrical integration and cabling engineering. The purpose of the program is to provide the engineering community with a centralized database for entering and accessing system functional definitions, subsystem and instrument-end circuit pinout details, and harnessing data. The primary objective is to provide an instantaneous single point of information interchange, thus avoiding error-prone, time-consuming, and costly multiple-path data shuttling. The DFACS program, which is centered around a single database, has built-in menus that provide easy data input and access for all involved system, subsystem, and cabling personnel. The DFACS program allows parallel design of circuit data sheets and harness drawings. It also recombines raw information to automatically generate various project documents and drawings including the Circuit Data Sheet Index, the Electrical Interface Circuits List, Assembly and Equipment Lists, Electrical Ground Tree, Connector List, Cable Tree, Cabling Electrical Interface and Harness Drawings, Circuit Data Sheets, and ECR List of Affected Interfaces/Assemblies. Real time automatic production of harness drawings and circuit data sheets from the same data reservoir ensures instant system and cabling engineering design harmony. DFACS also contains automatic wire routing procedures and extensive error checking routines designed to minimize the possibility of engineering error. DFACS is designed to run on DEC VAX series computers under VMS using Version 6.3/01 of INGRES QUEL/OSL, a relational database system which is available through Relational Technology, Inc. The program is available in VAX BACKUP format on a 1600 BPI 9-track magnetic tape (standard media) or a TK50 tape cartridge. DFACS was developed in 1987 and last updated in 1990. DFACS is a copyrighted work with all copyright vested in NASA. DEC, VAX and VMS are trademarks of Digital Equipment Corporation. INGRES QUEL/OSL is a trademark of Relational Technology, Inc.

Examining the social determinants of children's developmental health: protocol for building a pan-Canadian population-based monitoring system for early childhood development

PubMed Central

Guhn, Martin; Janus, Magdalena; Enns, Jennifer; Brownell, Marni; Forer, Barry; Duku, Eric; Muhajarine, Nazeem; Raos, Rob

2016-01-01

Introduction Early childhood is a key period to establish policies and practices that optimise children's health and development, but Canada lacks nationally representative data on social indicators of children's well-being. To address this gap, the Early Development Instrument (EDI), a teacher-administered questionnaire completed for kindergarten-age children, has been implemented across most Canadian provinces over the past 10 years. The purpose of this protocol is to describe the Canadian Neighbourhoods and Early Child Development (CanNECD) Study, the aims of which are to create a pan-Canadian EDI database to monitor trends over time in children's developmental health and to advance research examining the social determinants of health. Methods and analysis Canada-wide EDI records from 2004 to 2014 (representing over 700 000 children) will be linked to Canada Census and Income Taxfiler data. Variables of socioeconomic status derived from these databases will be used to predict neighbourhood-level EDI vulnerability rates by conducting a series of regression analyses and latent variable models at provincial/territorial and national levels. Where data are available, we will measure the neighbourhood-level change in developmental vulnerability rates over time and model the socioeconomic factors associated with those trends. Ethics and dissemination Ethics approval for this study was granted by the Behavioural Research Ethics Board at the University of British Columbia. Study findings will be disseminated to key partners, including provincial and federal ministries, schools and school districts, collaborative community groups and the early childhood development research community. The database created as part of this longitudinal population-level monitoring system will allow researchers to associate practices, programmes and policies at school and community levels with trends in developmental health outcomes. The CanNECD Study will guide future early childhood development action and policies, using the database as a tool for formative programme and policy evaluation. PMID:27130168

Database for the Geologic Map of Upper Eocene to Holocene Volcanic and Related Rocks of the Cascade Range, Oregon

USGS Publications Warehouse

Nimz, Kathryn; Ramsey, David W.; Sherrod, David R.; Smith, James G.

2008-01-01

Since 1979, Earth scientists of the Geothermal Research Program of the U.S. Geological Survey have carried out multidisciplinary research in the Cascade Range. The goal of this research is to understand the geology, tectonics, and hydrology of the Cascades in order to characterize and quantify geothermal resource potential. A major goal of the program is compilation of a comprehensive geologic map of the entire Cascade Range that incorporates modern field studies and that has a unified and internally consistent explanation. This map is one of three in a series that shows Cascade Range geology by fitting published and unpublished mapping into a province-wide scheme of rock units distinguished by composition and age; map sheets of the Cascade Range in Washington (Smith, 1993) and California will complete the series. The complete series forms a guide to exploration and evaluation of the geothermal resources of the Cascade Range and will be useful for studies of volcano hazards, volcanology, and tectonics. This digital release contains all the information used to produce the geologic map published as U.S. Geological Survey Geologic Investigations Series I-2569 (Sherrod and Smith, 2000). The main component of this digital release is a geologic map database prepared using ArcInfo GIS. This release also contains files to view or print the geologic map and accompanying descriptive pamphlet from I-2569.

Architecture and prototypical implementation of a semantic querying system for big Earth observation image bases

PubMed Central

Tiede, Dirk; Baraldi, Andrea; Sudmanns, Martin; Belgiu, Mariana; Lang, Stefan

2017-01-01

ABSTRACT Spatiotemporal analytics of multi-source Earth observation (EO) big data is a pre-condition for semantic content-based image retrieval (SCBIR). As a proof of concept, an innovative EO semantic querying (EO-SQ) subsystem was designed and prototypically implemented in series with an EO image understanding (EO-IU) subsystem. The EO-IU subsystem is automatically generating ESA Level 2 products (scene classification map, up to basic land cover units) from optical satellite data. The EO-SQ subsystem comprises a graphical user interface (GUI) and an array database embedded in a client server model. In the array database, all EO images are stored as a space-time data cube together with their Level 2 products generated by the EO-IU subsystem. The GUI allows users to (a) develop a conceptual world model based on a graphically supported query pipeline as a combination of spatial and temporal operators and/or standard algorithms and (b) create, save and share within the client-server architecture complex semantic queries/decision rules, suitable for SCBIR and/or spatiotemporal EO image analytics, consistent with the conceptual world model. PMID:29098143

CMGTooL user's manual

USGS Publications Warehouse

Xu, Jingping; Lightsom, Fran; Noble, Marlene A.; Denham, Charles

2002-01-01

During the past several years, the sediment transport group in the Coastal and Marine Geology Program (CMGP) of the U. S. Geological Survey has made major revisions to its methodology of processing, analyzing, and maintaining the variety of oceanographic time-series data. First, CMGP completed the transition of the its oceanographic time-series database to a self-documenting NetCDF (Rew et al., 1997) data format. Second, CMGP’s oceanographic data variety and complexity have been greatly expanded from traditional 2-dimensional, single-point time-series measurements (e.g., Electro-magnetic current meters, transmissometers) to more advanced 3-dimensional and profiling time-series measurements due to many new acquisitions of modern instruments such as Acoustic Doppler Current Profiler (RDI, 1996), Acoustic Doppler Velocitimeter, Pulse-Coherence Acoustic Doppler Profiler (SonTek, 2001), Acoustic Bacscatter Sensor (Aquatec, 1001001001001001001). In order to accommodate the NetCDF format of data from the new instruments, a software package of processing, analyzing, and visualizing time-series oceanographic data was developed. It is named CMGTooL. The CMGTooL package contains two basic components: a user-friendly GUI for NetCDF file analysis, processing and manipulation; and a data analyzing program library. Most of the routines in the library are stand-alone programs suitable for batch processing. CMGTooL is written in MATLAB computing language (The Mathworks, 1997), therefore users must have MATLAB installed on their computer in order to use this software package. In addition, MATLAB’s Signal Processing Toolbox is also required by some CMGTooL’s routines. Like most MATLAB programs, all CMGTooL codes are compatible with different computing platforms including PC, MAC, and UNIX machines (Note: CMGTooL has been tested on different platforms that run MATLAB 5.2 (Release 10) or lower versions. Some of the commands related to MAC may not be compatible with later releases of MATLAB). The GUI and some of the library routines call low-level NetCDF file I/O, variable and attribute functions. These NetCDF exclusive functions are supported by a MATLAB toolbox named NetCDF, created by Dr. Charles Denham . This toolbox has to be installed in order to use the CMGTooL GUI. The CMGTooL GUI calls several routines that were initially developed by others. The authors would like to acknowledge the following scientists for their ideas and codes: Dr. Rich Signell (USGS), Dr. Chris Sherwood (USGS), and Dr. Bob Beardsley (WHOI). Many special terms that carry special meanings in either MATLAB or the NetCDF Toolbox are used in this manual. Users are encouraged to read the documents of MATLAB and NetCDF for references.

Why didn't Box-Jenkins win (again)

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

Pack, D.J.; Downing, D.J.

This paper focuses on the forecasting performance of the Box-Jenkins methodology applied to the 111 time series of the Makridakis competition. It considers the influence of the following factors: (1) time series length, (2) time-series information (autocorrelation) content, (3) time-series outliers or structural changes, (4) averaging results over time series, and (5) forecast time origin choice. It is found that the 111 time series contain substantial numbers of very short series, series with obvious structural change, and series whose histories are relatively uninformative. If these series are typical of those that one must face in practice, the real message ofmore » the competition is that univariate time series extrapolations will frequently fail regardless of the methodology employed to produce them.« less

Multifractal analysis of visibility graph-based Ito-related connectivity time series.

PubMed

Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano

2016-02-01

In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.

Empirical STORM-E Model. [I. Theoretical and Observational Basis

NASA Technical Reports Server (NTRS)

Mertens, Christopher J.; Xu, Xiaojing; Bilitza, Dieter; Mlynczak, Martin G.; Russell, James M., III

2013-01-01

Auroral nighttime infrared emission observed by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument onboard the Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics (TIMED) satellite is used to develop an empirical model of geomagnetic storm enhancements to E-region peak electron densities. The empirical model is called STORM-E and will be incorporated into the 2012 release of the International Reference Ionosphere (IRI). The proxy for characterizing the E-region response to geomagnetic forcing is NO+(v) volume emission rates (VER) derived from the TIMED/SABER 4.3 lm channel limb radiance measurements. The storm-time response of the NO+(v) 4.3 lm VER is sensitive to auroral particle precipitation. A statistical database of storm-time to climatological quiet-time ratios of SABER-observed NO+(v) 4.3 lm VER are fit to widely available geomagnetic indices using the theoretical framework of linear impulse-response theory. The STORM-E model provides a dynamic storm-time correction factor to adjust a known quiescent E-region electron density peak concentration for geomagnetic enhancements due to auroral particle precipitation. Part II of this series describes the explicit development of the empirical storm-time correction factor for E-region peak electron densities, and shows comparisons of E-region electron densities between STORM-E predictions and incoherent scatter radar measurements. In this paper, Part I of the series, the efficacy of using SABER-derived NO+(v) VER as a proxy for the E-region response to solar-geomagnetic disturbances is presented. Furthermore, a detailed description of the algorithms and methodologies used to derive NO+(v) VER from SABER 4.3 lm limb emission measurements is given. Finally, an assessment of key uncertainties in retrieving NO+(v) VER is presented

Operational use of open satellite data for marine water quality monitoring

NASA Astrophysics Data System (ADS)

Symeonidis, Panagiotis; Vakkas, Theodoros

2017-09-01

The purpose of this study was to develop an operational platform for marine water quality monitoring using near real time satellite data. The developed platform utilizes free and open satellite data available from different data sources like COPERNICUS, the European Earth Observation Initiative, or NASA, from different satellites and instruments. The quality of the marine environment is operationally evaluated using parameters like chlorophyll-a concentration, water color and Sea Surface Temperature (SST). For each parameter, there are more than one dataset available, from different data sources or satellites, to allow users to select the most appropriate dataset for their area or time of interest. The above datasets are automatically downloaded from the data provider's services and ingested to the central, spatial engine. The spatial data platform uses the Postgresql database with the PostGIS extension for spatial data storage and Geoserver for the provision of the spatial data services. The system provides daily, 10 days and monthly maps and time series of the above parameters. The information is provided using a web client which is based on the GET SDI PORTAL, an easy to use and feature rich geospatial visualization and analysis platform. The users can examine the temporal variation of the parameters using a simple time animation tool. In addition, with just one click on the map, the system provides an interactive time series chart for any of the parameters of the available datasets. The platform can be offered as Software as a Service (SaaS) to any area in the Mediterranean region.

The World Database for Pediatric and Congenital Heart Surgery: Update.

PubMed

Louis, James St; Kirklin, James

2018-05-01

Following several years of planning and design, the World Database for Pediatric and Congenital Heart Surgery (WDPCHS) went live on January 1, 2017. The first operational year of this valuable database has proven very successful. As of February 28, 2018, more than 4,500 patients have been submitted from 39 centers; participation currently spans 19 countries over 6 continents, with 120 more centers in the enrollment pipeline. This update, the first in a series, is intended to provide World Society for Pediatric and Congenital Heart Surgery members and others who care for children with congenital heart disease with a broad overview of current progress and ongoing activities surrounding the WDPCHS.

Flood risk changes in Northeastern part of Iberian Peninsula: from impact data to flow data

NASA Astrophysics Data System (ADS)

Llasat, Maria-Carmen; Gilabert, Joan; Llasat-Botija, Montserrat; Marcos, Raül; Quintana-Seguí, Pere; Turco, Marco

2014-05-01

The analysis of the temporal evolution of historical floods usually is based on proxy data obtained collecting flooding information from continuous records in municipal, ecclesiastic and private documentary sources. This kind of documentary series usually provide details of the damage caused by the flooding, with the exact date and duration, and in some occasions, some details on the behaviour of the rising water (duration, magnitude, indirect measurements), further details about the precipitation episode that gave rise to it, and the characteristics and dimensions of the riverbeds and the infrastructure associated with the watercourse (dams, bridges, mills, dykes). Based on this information, the first step is to estimate the flood impacts and, usually, in order to build flood data series, the event is classified following some criteria (i.e. catastrophic, extraordinary, ordinary). Exceptionally, some events are reconstructed and the maximum flow or level of the inundation is estimated. However, there are not so many studies that compare flow series and flood series obtained from proxy data. The interest of doing it is, not only to check the quality of the information and to compare the trend of both kind of series, but also to identify the role of other variables and their potential change in the flood risk evolution. Besides this, a potential relationship between the flood classification criteria and the flood frequency distribution obtained from flow data could be done. The contribution departs from the INUNGAMA database that contains 372 flood events recorded in Northeastern of Iberian Peninsula from 1900 to 2010 (Barnolas and Llasat, 2007; Llasat et al, 2013); the PRESSGAMA database that includes more than 15,000 news related to natural hazards and climate change published between 1981 and 2010 and with detailed information for each flood event (Llasat et al, 2009) and the historical flood database with data since the 14th century for the rivers Ter, Llobregat and Segre (Llasat et al, 2005). Daily flow data for the rivers Muga (1971-2013), Ter (1912-2013) and Llobregat (1912-2013) has also been obtained from the Catalan Water Agency. Precipitation and temperature daily data has been provided by Spain-02 (Herrera et al 2012) for the period 1950-2008. First of all, the quality of all the series has been checked and a consistency analysis between them has been done. The correlation between rainfall and flow series has been studied for some specific catchments. Then, trend analysis of different series has been made by applying the Mann-Kendall method and a resampling method (Turco and Llasat, 2011), in order to identify decadal changes. Finally, a flood event has been selected as case study to illustrate the different factors that can be involved. This contribution has been supported by the DRIHM project.

Fugitive emission source characterization using a gradient-based optimization scheme and scalar transport adjoint

NASA Astrophysics Data System (ADS)

Brereton, Carol A.; Joynes, Ian M.; Campbell, Lucy J.; Johnson, Matthew R.

2018-05-01

Fugitive emissions are important sources of greenhouse gases and lost product in the energy sector that can be difficult to detect, but are often easily mitigated once they are known, located, and quantified. In this paper, a scalar transport adjoint-based optimization method is presented to locate and quantify unknown emission sources from downstream measurements. This emission characterization approach correctly predicted locations to within 5 m and magnitudes to within 13% of experimental release data from Project Prairie Grass. The method was further demonstrated on simulated simultaneous releases in a complex 3-D geometry based on an Alberta gas plant. Reconstructions were performed using both the complex 3-D transient wind field used to generate the simulated release data and using a sequential series of steady-state RANS wind simulations (SSWS) representing 30 s intervals of physical time. Both the detailed transient and the simplified wind field series could be used to correctly locate major sources and predict their emission rates within 10%, while predicting total emission rates from all sources within 24%. This SSWS case would be much easier to implement in a real-world application, and gives rise to the possibility of developing pre-computed databases of both wind and scalar transport adjoints to reduce computational time.

Spurious One-Month and One-Year Periods in Visual Observations of Variable Stars

NASA Astrophysics Data System (ADS)

Percy, J. R.

2015-12-01

Visual observations of variable stars, when time-series analyzed with some algorithms such as DC-DFT in vstar, show spurious periods at or close to one synodic month (29.5306 days), and also at about a year, with an amplitude of typically a few hundredths of a magnitude. The one-year periods have been attributed to the Ceraski effect, which was believed to be a physiological effect of the visual observing process. This paper reports on time-series analysis, using DC-DFT in vstar, of visual observations (and in some cases, V observations) of a large number of stars in the AAVSO International Database, initially to investigate the one-month periods. The results suggest that both the one-month and one-year periods are actually due to aliasing of the stars' very low-frequency variations, though they do not rule out very low-amplitude signals (typically 0.01 to 0.02 magnitude) which may be due to a different process, such as a physiological one. Most or all of these aliasing effects may be avoided by using a different algorithm, which takes explicit account of the window function of the data, and/or by being fully aware of the possible presence of and aliasing by very low-frequency variations.

Comparative study of methods for recognition of an unknown person's action from a video sequence

NASA Astrophysics Data System (ADS)

Hori, Takayuki; Ohya, Jun; Kurumisawa, Jun

2009-02-01

This paper proposes a Tensor Decomposition Based method that can recognize an unknown person's action from a video sequence, where the unknown person is not included in the database (tensor) used for the recognition. The tensor consists of persons, actions and time-series image features. For the observed unknown person's action, one of the actions stored in the tensor is assumed. Using the motion signature obtained from the assumption, the unknown person's actions are synthesized. The actions of one of the persons in the tensor are replaced by the synthesized actions. Then, the core tensor for the replaced tensor is computed. This process is repeated for the actions and persons. For each iteration, the difference between the replaced and original core tensors is computed. The assumption that gives the minimal difference is the action recognition result. For the time-series image features to be stored in the tensor and to be extracted from the observed video sequence, the human body silhouette's contour shape based feature is used. To show the validity of our proposed method, our proposed method is experimentally compared with Nearest Neighbor rule and Principal Component analysis based method. Experiments using 33 persons' seven kinds of action show that our proposed method achieves better recognition accuracies for the seven actions than the other methods.

Presentations to Emergency Departments for COPD: A Time Series Analysis.

PubMed

Rosychuk, Rhonda J; Youngson, Erik; Rowe, Brian H

2016-01-01

Background. Chronic obstructive pulmonary disease (COPD) is a common respiratory condition characterized by progressive dyspnea and acute exacerbations which may result in emergency department (ED) presentations. This study examines monthly rates of presentations to EDs in one Canadian province. Methods. Presentations for COPD made by individuals aged ≥55 years during April 1999 to March 2011 were extracted from provincial databases. Data included age, sex, and health zone of residence (North, Central, South, and urban). Crude rates were calculated. Seasonal autoregressive integrated moving average (SARIMA) time series models were developed. Results. ED presentations for COPD totalled 188,824 and the monthly rate of presentation remained relatively stable (from 197.7 to 232.6 per 100,000). Males and seniors (≥65 years) comprised 52.2% and 73.7% of presentations, respectively. The ARIMA(1,0, 0) × (1,0, 1)12 model was appropriate for the overall rate of presentations and for each sex and seniors. Zone specific models showed relatively stable or decreasing rates; the North zone had an increasing trend. Conclusions. ED presentation rates for COPD have been relatively stable in Alberta during the past decade. However, their increases in northern regions deserve further exploration. The SARIMA models quantified the temporal patterns and can help planning future health care service needs.

Outburst of the recurrent nova V745 Sco

NASA Astrophysics Data System (ADS)

Waagen, Elizabeth O.

2014-02-01

The outburst of the recurrent nova V745 Sco (Nova Sco 1937) by Rod Stubbings (Tetoora Road, VIC, Australia) at visual magnitude 9.0 on 2014 February 6.694 UT is reported. This recurrent nova is fading quickly. Follow-up observations of all types (visual, CCD, DSLR) are strongly encouraged, as is spectroscopy; fast time-series of this nova may be useful to detect possible flaring activity as was observed during the outburst of U Scorpii in 2010. Coincident time-series by multiple observers would be most useful for such a study, with a V-filter being preferred. Observations reported to the AAVSO International Database show V745 Sco at visual mag. 10.2 on 2014 Feb. 07.85833 UT (A. Pearce, Nedlands, W. Australia). Finder charts with sequence may be created using the AAVSO Variable Star Plotter (http://www.aavso.org/vsp). Observations should be submitted to the AAVSO International Database. Previous outbursts occurred in 1937 and 1989. The 1937 outburst was detected in 1958 (in decline at magnitude 11.0 on 1937 May 11.1 UT; outburst had occurred within the previous 19 days) by Lukas Plaut on plates taken by Hendrik van Gent at the Leiden Observatory; the object was announced as Nova Sco 1937 and later assigned the GCVS name V745 Sco. The 1989 outburst was detected on 1989 August 1.55 UT by Mati Morel (MMAT, Thornton, NSW, Australia) at visual magnitude 10.4 and in decline. Dr. Bradley Schaefer (Louisiana State University) reports (2010ApJS..187..275S) in his comprehensive analysis of the 10 known galactic recurrent novae (including V745 Sco) that the median interval between recurrent novae outbursts is 24 years. The interval since the 1989 outburst of V745 Sco is 24.10 years. See the Alert Notice for additional visual and multicolor photometry and for more details.

Utilizing Temperature and Resistivity Data as a Way to Characterize Water and Solute Movement and Groundwater-Surface Water Interaction in Variably Saturated Porous Media

NASA Astrophysics Data System (ADS)

Scotch, C.; Murgulet, D.; Hay, R.

2012-12-01

This study utilizes a multidisciplinary approach to better analyze the extent to which groundwater and surface water interact in the Oso Creek water shed of South Texas using temperature data, electrical resistivity and numerical modeling methods. The three primary objectives of this study are to: (1) identify primary areas of streambed groundwater-surface water interaction using temperature time series and resistivity soundings; (2) improve understanding of solute flow and groundwater, surface water, and sediment interaction in a semiarid, urban coastal area; (3) improve our understanding of groundwater contribution to contaminant transport and discharge to the bays and estuaries and ultimately the Gulf of Mexico. Temperature data was acquired over a one year period, using temperature loggers, from June 11, 2009 to May 18, 2010 at 15-minute intervals from 17 monitoring sites along Oso Creek and its tributaries. Each monitoring site consisted of 4 temperature loggers equally vertically spaced from the stream surface down to a depth of one meter. Furthermore, groundwater temperatures and water levels were collected from wells adjacent to the temperature monitoring sites. In order to fulfill the objectives of this study, existing hydrogeologic, stratigraphic, and other ancillary data are being integrated into a finite difference model developed using the USGS VS2DT software for the Oso Creek Watershed. The model will be calibrated using existing temperature and water level data and a resistivity component will also be added to assure accuracy of the model and temperature data by helping to identify varying lithologies and water conductivities. Compiling a time-series of temperature data and incorporating available hydrostratigraphic, geomorphologic and water level data will enable the development of a comprehensive database. This database is necessary to develop the detailed flow model that will enable an understanding of the extent of groundwater surface water interaction and their associated flow regimes.

Regenerating time series from ordinal networks.

PubMed

McCullough, Michael; Sakellariou, Konstantinos; Stemler, Thomas; Small, Michael

2017-03-01

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches. First, we use recurrence quantification analysis on traditional recurrence plots and order recurrence plots to compare the temporal structure of the original time series with random walk surrogate time series. Second, we estimate the largest Lyapunov exponent from the original time series and investigate the extent to which this invariant measure can be estimated from the surrogate time series. Finally, estimates of correlation dimension are computed to compare the topological properties of the original and surrogate time series dynamics. Our findings show that ordinal networks constructed from univariate time series data constitute stochastic models which approximate important dynamical properties of the original systems.

Regenerating time series from ordinal networks

NASA Astrophysics Data System (ADS)

McCullough, Michael; Sakellariou, Konstantinos; Stemler, Thomas; Small, Michael

2017-03-01

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches. First, we use recurrence quantification analysis on traditional recurrence plots and order recurrence plots to compare the temporal structure of the original time series with random walk surrogate time series. Second, we estimate the largest Lyapunov exponent from the original time series and investigate the extent to which this invariant measure can be estimated from the surrogate time series. Finally, estimates of correlation dimension are computed to compare the topological properties of the original and surrogate time series dynamics. Our findings show that ordinal networks constructed from univariate time series data constitute stochastic models which approximate important dynamical properties of the original systems.

How to Handle the Avalanche of Online Documentation.

ERIC Educational Resources Information Center

Nolan, Maureen P.

1981-01-01

The method of handling the printed documentation associated with online information retrieval, which is described, involves the use of a series of separate but related files: database files, system files, network files, index sheets, and equipment files. (FM)

GPS Position Time Series @ JPL

NASA Technical Reports Server (NTRS)

Owen, Susan; Moore, Angelyn; Kedar, Sharon; Liu, Zhen; Webb, Frank; Heflin, Mike; Desai, Shailen

2013-01-01

Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined Time Series/Velocities - crustal deformation for tectonic, volcanic, ground water studies center dot ARIA Time Series/Coseismic Data Products - Hazard monitoring and response focused center dot ARIA data system designed to integrate GPS and InSAR - GPS tropospheric delay used for correcting InSAR - Caltech's GIANT time series analysis uses GPS to correct orbital errors in InSAR - Zhen Liu's talking tomorrow on InSAR Time Series analysis

HIST-EU - a dataset of European relevance, a database to enable long-term climate variability studies on regional scale

NASA Astrophysics Data System (ADS)

Auer, I.; Böhm, R.; Ganekind, M.; Schöner, W.; Nemec, J.; Chimani, B.

2010-09-01

Instrumental time series of different climate elements are an important requisite for climate and climate impact studies. Long-term time series can improve our understanding of climate change during the instrumental period. During recent decades a number of national and international initiatives in European countries have significantly increased the number of existing long-term instrumental series; however a publically available data base covering Europe has not been created so far. For the "Greater Alpine Region" (4-19 deg E, 43-49 deg N, 0-3500m asl) the HISTALP data base has been established consisting of monthly homogenised temperature, pressure, precipitation, sunshine and cloudiness records. The data set may be described as follows: Long-term (fully exploiting the potential of systematically measured data). dense (network density adequate in respect to the spatial coherence of the given climate element) quality improved (outliers removed, gaps filled) homogenised (earlier sections adjusted to the recent state of the measuring site) multiple (covering more than one climate element) user friendly (well described and kept in different modes for different applications) HIST-EU is inteded to be a data set of European relevance allowing studying climate variability on regional scale. It focuses on data collection, data recovery and rescue, and homogenizing. HIST-EU will use the infrastructure of HISTALP (www.zamg.ac.at/histalp) and will allow free or restricted data access due to the regulations of data providers. HIST-EU will be carried out under the umbrella of ECSN/EUMETNET.

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.

GloboLakes: A global observatory of lake responses to environmental change.

NASA Astrophysics Data System (ADS)

Groom, Steve; Tyler, Andrew; Hunter, Peter; Spyrakos, Evangelos; Martinez-Vicente, Victor; Merchant, Chris; Cutler, Mark; Rowan, John; Dawson, Terry; Maberly, Stephen; Cavalho, Laurence; Elliot, Alex; Thackery, Stephen; Miller, Claire; Scott, Marian

2014-05-01

The world's freshwater ecosystems are vital components of the global biosphere, yet are vulnerable to climate and other human-induced change. There is increasing recognition that lakes play an important role in global biogeochemical cycling and provide key ecosystem services. However, our understanding of how lakes respond to environmental change at a global scale, and how this impacts on their status and function, is hampered by limited information on their chemical, physical and ecological condition. There are estimated to be over 300 million lakes globally, of which over 17,000 are greater than 10 km2 in surface area. These numbers have limited the systematic study of lake ecosystems. GloboLakes is a five-year UK research programme investigating the state of lakes and their response to climatic and other environmental drivers of change. It will establish a satellite-based observatory with archive and near-real time data processing to produce a time series of observed biogeochemical parameters and lake temperature for over 1000 lakes globally. This will be supported by linked ancillary data on climate and catchment land-use. The ability to monitor a large number of lakes consistently at high frequency and globally will facilitate a paradigm shift in our understanding of how lakes respond to environmental change at different spatial and temporal scales. A key requirement is to validate satellite retrieval algorithms and test the time-series of resulting lake properties such as chlorophyll-a by comparison with in situ data. To support the former extensive bio-optical and constituent data were taken in year 1 of the project in a number of UK lakes with a variety of trophic states. Furthermore, for wider validation activities GloboLakes has established the LIMNADES initiative to create a centralised database of ground bio-optical measurements of worldwide lakes through voluntary cooperation across the international scientific community. This presentation will introduce the GloboLakes project including its scientific ambitions for the next 4 years, present initial results, focussing on in-water optical data and describe the LIMNADES database.

Evaluation of Robustness to Setup and Range Uncertainties for Head and Neck Patients Treated With Pencil Beam Scanning Proton Therapy

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

Malyapa, Robert; Lowe, Matthew; Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester

Purpose: To evaluate the robustness of head and neck plans for treatment with intensity modulated proton therapy to range and setup errors, and to establish robustness parameters for the planning of future head and neck treatments. Methods and Materials: Ten patients previously treated were evaluated in terms of robustness to range and setup errors. Error bar dose distributions were generated for each plan, from which several metrics were extracted and used to define a robustness database of acceptable parameters over all analyzed plans. The patients were treated in sequentially delivered series, and plans were evaluated for both the first seriesmore » and for the combined error over the whole treatment. To demonstrate the application of such a database in the head and neck, for 1 patient, an alternative treatment plan was generated using a simultaneous integrated boost (SIB) approach and plans of differing numbers of fields. Results: The robustness database for the treatment of head and neck patients is presented. In an example case, comparison of single and multiple field plans against the database show clear improvements in robustness by using multiple fields. A comparison of sequentially delivered series and an SIB approach for this patient show both to be of comparable robustness, although the SIB approach shows a slightly greater sensitivity to uncertainties. Conclusions: A robustness database was created for the treatment of head and neck patients with intensity modulated proton therapy based on previous clinical experience. This will allow the identification of future plans that may benefit from alternative planning approaches to improve robustness.« less

The iMars WebGIS - Spatio-Temporal Data Queries and Single Image Map Web Services

NASA Astrophysics Data System (ADS)

Walter, Sebastian; Steikert, Ralf; Schreiner, Bjoern; Muller, Jan-Peter; van Gasselt, Stephan; Sidiropoulos, Panagiotis; Lanz-Kroechert, Julia

2017-04-01

Introduction: Web-based planetary image dissemination platforms usually show outline coverages of the data and offer querying for metadata as well as preview and download, e.g. the HRSC Mapserver (Walter & van Gasselt, 2014). Here we introduce a new approach for a system dedicated to change detection by simultanous visualisation of single-image time series in a multi-temporal context. While the usual form of presenting multi-orbit datasets is the merge of the data into a larger mosaic, we want to stay with the single image as an important snapshot of the planetary surface at a specific time. In the context of the EU FP-7 iMars project we process and ingest vast amounts of automatically co-registered (ACRO) images. The base of the co-registration are the high precision HRSC multi-orbit quadrangle image mosaics, which are based on bundle-block-adjusted multi-orbit HRSC DTMs. Additionally we make use of the existing bundle-adjusted HRSC single images available at the PDS archives. A prototype demonstrating the presented features is available at http://imars.planet.fu-berlin.de. Multi-temporal database: In order to locate multiple coverage of images and select images based on spatio-temporal queries, we converge available coverage catalogs for various NASA imaging missions into a relational database management system with geometry support. We harvest available metadata entries during our processing pipeline using the Integrated Software for Imagers and Spectrometers (ISIS) software. Currently, this database contains image outlines from the MGS/MOC, MRO/CTX and the MO/THEMIS instruments with imaging dates ranging from 1996 to the present. For the MEx/HRSC data, we already maintain a database which we automatically update with custom software based on the VICAR environment. Web Map Service with time support: The MapServer software is connected to the database and provides Web Map Services (WMS) with time support based on the START_TIME image attribute. It allows temporal WMS GetMap requests by setting additional TIME parameter values in the request. The values for the parameter represent an interval defined by its lower and upper bounds. As the WMS time standard only supports one time variable, only the start times of the images are considered. If no time values are submitted with the request, the full time range of all images is assumed as the default. Dynamic single image WMS: To compare images from different acquisition times at sites of multiple coverage, we have to load every image as a single WMS layer. Due to the vast amount of single images we need a way to set up the layers in a dynamic way - the map server does not know the images to be served beforehand. We use the MapScript interface to dynamically access MapServer's objects and configure the file name and path of the requested image in the map configuration. The layers are created on-the-fly each representing only one single image. On the frontend side, the vendor-specific WMS request parameter (PRODUCTID) has to be appended to the regular set of WMS parameters. The request is then passed on to the MapScript instance. Web Map Tile Cache: In order to speed up access of the WMS requests, a MapCache instance has been integrated in the pipeline. As it is not aware of the available PDS product IDs which will be queried, the PRODUCTID parameter is configured as an additional dimension of the cache. The WMS request is received by the Apache webserver configured with the MapCache module. If the tile is available in the tile cache, it is immediately commited to the client. If not available, the tile request is forwarded to Apache and the MapScript module. The Python script intercepts the WMS request and extracts the product ID from the parameter chain. It loads the layer object from the map file and appends the file name and path of the inquired image. After some possible further image processing inside the script (stretching, color matching), the request is submitted to the MapServer backend which in turn delivers the response back to the MapCache instance. Web frontend: We have implemented a web-GIS frontend based on various OpenLayers components. The basemap is a global color-hillshaded HRSC bundle-adjusted DTM mosaic with a resolution of 50 m per pixel. The new bundle-block-adjusted qudrangle mosaics of the MC-11 quadrangle, both image and DTM, are included with opacity slider options. The layer user interface has been adapted on the base of the ol3-layerswitcher and extended by foldable and switchable groups, layer sorting (by resolution, by time and alphabeticallly) and reordering (drag-and-drop). A collapsible time panel accomodates a time slider interface where the user can filter the visible data by a range of Mars or Earth dates and/or by solar longitudes. The visualisation of time-series of single images is controlled by a specific toolbar enabling the workflow of image selection (by point or bounding box), dynamic image loading and playback of single images in a video player-like environment. During a stress-test campaign we could demonstrate that the system is capable of serving up to 10 simultaneous users on its current lightweight development hardware. It is planned to relocate the software to more powerful hardware by the time of this conference. Conclusions/Outlook: The iMars webGIS is an expert tool for the detection and visualization of surface changes. We demonstrate a technique to dynamically retrieve and display single images based on the time-series structure of the data. Together with the multi-temporal database and its MapServer/MapCache backend it provides a stable and high performance environment for the dissemination of the various iMars products. Acknowledgements: This research has received funding from the EU's FP7 Programme under iMars 607379 and by the German Space Agency (DLR Bonn), grant 50 QM 1301 (HRSC on Mars Express).

A general framework for time series data mining based on event analysis: application to the medical domains of electroencephalography and stabilometry.

PubMed

Lara, Juan A; Lizcano, David; Pérez, Aurora; Valente, Juan P

2014-10-01

There are now domains where information is recorded over a period of time, leading to sequences of data known as time series. In many domains, like medicine, time series analysis requires to focus on certain regions of interest, known as events, rather than analyzing the whole time series. In this paper, we propose a framework for knowledge discovery in both one-dimensional and multidimensional time series containing events. We show how our approach can be used to classify medical time series by means of a process that identifies events in time series, generates time series reference models of representative events and compares two time series by analyzing the events they have in common. We have applied our framework on time series generated in the areas of electroencephalography (EEG) and stabilometry. Framework performance was evaluated in terms of classification accuracy, and the results confirmed that the proposed schema has potential for classifying EEG and stabilometric signals. The proposed framework is useful for discovering knowledge from medical time series containing events, such as stabilometric and electroencephalographic time series. These results would be equally applicable to other medical domains generating iconographic time series, such as, for example, electrocardiography (ECG). Copyright © 2014 Elsevier Inc. All rights reserved.

Multiple elastic scattering of electrons in condensed matter

NASA Astrophysics Data System (ADS)

Jablonski, A.

2017-01-01

Since the 1940s, much attention has been devoted to the problem of accurate theoretical description of electron transport in condensed matter. The needed information for describing different aspects of the electron transport is the angular distribution of electron directions after multiple elastic collisions. This distribution can be expanded into a series of Legendre polynomials with coefficients, Al. In the present work, a database of these coefficients for all elements up to uranium (Z=92) and a dense grid of electron energies varying from 50 to 5000 eV has been created. The database makes possible the following applications: (i) accurate interpolation of coefficients Al for any element and any energy from the above range, (ii) fast calculations of the differential and total elastic-scattering cross sections, (iii) determination of the angular distribution of directions after multiple collisions, (iv) calculations of the probability of elastic backscattering from solids, and (v) calculations of the calibration curves for determination of the inelastic mean free paths of electrons. The last two applications provide data with comparable accuracy to Monte Carlo simulations, yet the running time is decreased by several orders of magnitude. All of the above applications are implemented in the Fortran program MULTI_SCATT. Numerous illustrative runs of this program are described. Despite a relatively large volume of the database of coefficients Al, the program MULTI_SCATT can be readily run on personal computers.

Experiments with a novel content-based image retrieval software: can we eliminate classification systems in adolescent idiopathic scoliosis?

PubMed

Menon, K Venugopal; Kumar, Dinesh; Thomas, Tessamma

2014-02-01

Study Design Preliminary evaluation of new tool. Objective To ascertain whether the newly developed content-based image retrieval (CBIR) software can be used successfully to retrieve images of similar cases of adolescent idiopathic scoliosis (AIS) from a database to help plan treatment without adhering to a classification scheme. Methods Sixty-two operated cases of AIS were entered into the newly developed CBIR database. Five new cases of different curve patterns were used as query images. The images were fed into the CBIR database that retrieved similar images from the existing cases. These were analyzed by a senior surgeon for conformity to the query image. Results Within the limits of variability set for the query system, all the resultant images conformed to the query image. One case had no similar match in the series. The other four retrieved several images that were matching with the query. No matching case was left out in the series. The postoperative images were then analyzed to check for surgical strategies. Broad guidelines for treatment could be derived from the results. More precise query settings, inclusion of bending films, and a larger database will enhance accurate retrieval and better decision making. Conclusion The CBIR system is an effective tool for accurate documentation and retrieval of scoliosis images. Broad guidelines for surgical strategies can be made from the postoperative images of the existing cases without adhering to any classification scheme.

Measures of dependence for multivariate Lévy distributions

NASA Astrophysics Data System (ADS)

Boland, J.; Hurd, T. R.; Pivato, M.; Seco, L.

2001-02-01

Recent statistical analysis of a number of financial databases is summarized. Increasing agreement is found that logarithmic equity returns show a certain type of asymptotic behavior of the largest events, namely that the probability density functions have power law tails with an exponent α≈3.0. This behavior does not vary much over different stock exchanges or over time, despite large variations in trading environments. The present paper proposes a class of multivariate distributions which generalizes the observed qualities of univariate time series. A new consequence of the proposed class is the "spectral measure" which completely characterizes the multivariate dependences of the extreme tails of the distribution. This measure on the unit sphere in M-dimensions, in principle completely general, can be determined empirically by looking at extreme events. If it can be observed and determined, it will prove to be of importance for scenario generation in portfolio risk management.

Using All-Sky Imaging to Improve Telescope Scheduling (Abstract)

NASA Astrophysics Data System (ADS)

Cole, G. M.

2017-12-01

(Abstract only) Automated scheduling makes it possible for a small telescope to observe a large number of targets in a single night. But when used in areas which have less-than-perfect sky conditions such automation can lead to large numbers of observations of clouds and haze. This paper describes the development of a "sky-aware" telescope automation system that integrates the data flow from an SBIG AllSky340c camera with an enhanced dispatch scheduler to make optimum use of the available observing conditions for two highly instrumented backyard telescopes. Using the minute-by-minute time series image stream and a self-maintained reference database, the software maintains a file of sky brightness, transparency, stability, and forecasted visibility at several hundred grid positions. The scheduling software uses this information in real time to exclude targets obscured by clouds and select the best observing task, taking into account the requirements and limits of each instrument.

Predicting adverse hemodynamic events in critically ill patients.

PubMed

Yoon, Joo H; Pinsky, Michael R

2018-06-01

The art of predicting future hemodynamic instability in the critically ill has rapidly become a science with the advent of advanced analytical processed based on computer-driven machine learning techniques. How these methods have progressed beyond severity scoring systems to interface with decision-support is summarized. Data mining of large multidimensional clinical time-series databases using a variety of machine learning tools has led to our ability to identify alert artifact and filter it from bedside alarms, display real-time risk stratification at the bedside to aid in clinical decision-making and predict the subsequent development of cardiorespiratory insufficiency hours before these events occur. This fast evolving filed is primarily limited by linkage of high-quality granular to physiologic rationale across heterogeneous clinical care domains. Using advanced analytic tools to glean knowledge from clinical data streams is rapidly becoming a reality whose clinical impact potential is great.

Time Series Proteome Profiling

PubMed Central

Formolo, Catherine A.; Mintz, Michelle; Takanohashi, Asako; Brown, Kristy J.; Vanderver, Adeline; Halligan, Brian; Hathout, Yetrib

2014-01-01

This chapter provides a detailed description of a method used to study temporal changes in the endoplasmic reticulum (ER) proteome of fibroblast cells exposed to ER stress agents (tunicamycin and thapsigargin). Differential stable isotope labeling by amino acids in cell culture (SILAC) is used in combination with crude ER fractionation, SDS–PAGE and LC-MS/MS to define altered protein expression in tunicamycin or thapsigargin treated cells versus untreated cells. Treated and untreated cells are harvested at different time points, mixed at a 1:1 ratio and processed for ER fractionation. Samples containing labeled and unlabeled proteins are separated by SDS–PAGE, bands are digested with trypsin and the resulting peptides analyzed by LC-MS/MS. Proteins are identified using Bioworks software and the Swiss-Prot data-base, whereas ratios of protein expression between treated and untreated cells are quantified using ZoomQuant software. Data visualization is facilitated by GeneSpring software. proteomics PMID:21082445

Spatial Indexing for Data Searching in Mobile Sensing Environments.

PubMed

Zhou, Yuchao; De, Suparna; Wang, Wei; Moessner, Klaus; Palaniswami, Marimuthu S

2017-06-18

Data searching and retrieval is one of the fundamental functionalities in many Web of Things applications, which need to collect, process and analyze huge amounts of sensor stream data. The problem in fact has been well studied for data generated by sensors that are installed at fixed locations; however, challenges emerge along with the popularity of opportunistic sensing applications in which mobile sensors keep reporting observation and measurement data at variable intervals and changing geographical locations. To address these challenges, we develop the Geohash-Grid Tree, a spatial indexing technique specially designed for searching data integrated from heterogeneous sources in a mobile sensing environment. Results of the experiments on a real-world dataset collected from the SmartSantander smart city testbed show that the index structure allows efficient search based on spatial distance, range and time windows in a large time series database.

Spatial Indexing for Data Searching in Mobile Sensing Environments

PubMed Central

Zhou, Yuchao; De, Suparna; Wang, Wei; Moessner, Klaus; Palaniswami, Marimuthu S.

2017-01-01

Data searching and retrieval is one of the fundamental functionalities in many Web of Things applications, which need to collect, process and analyze huge amounts of sensor stream data. The problem in fact has been well studied for data generated by sensors that are installed at fixed locations; however, challenges emerge along with the popularity of opportunistic sensing applications in which mobile sensors keep reporting observation and measurement data at variable intervals and changing geographical locations. To address these challenges, we develop the Geohash-Grid Tree, a spatial indexing technique specially designed for searching data integrated from heterogeneous sources in a mobile sensing environment. Results of the experiments on a real-world dataset collected from the SmartSantander smart city testbed show that the index structure allows efficient search based on spatial distance, range and time windows in a large time series database. PMID:28629156

The Evolution of Your Success Lies at the Centre of Your Co-Authorship Network

PubMed Central

Servia-Rodríguez, Sandra; Noulas, Anastasios; Mascolo, Cecilia; Fernández-Vilas, Ana; Díaz-Redondo, Rebeca P.

2015-01-01

Collaboration among scholars and institutions is progressively becoming essential to the success of research grant procurement and to allow the emergence and evolution of scientific disciplines. Our work focuses on analysing if the volume of collaborations of one author together with the relevance of his collaborators is somewhat related to his research performance over time. In order to prove this relation we collected the temporal distributions of scholars’ publications and citations from the Google Scholar platform and the co-authorship network (of Computer Scientists) underlying the well-known DBLP bibliographic database. By the application of time series clustering, social network analysis and non-parametric statistics, we observe that scholars with similar publications (citations) patterns also tend to have a similar centrality in the co-authorship network. To our knowledge, this is the first work that considers success evolution with respect to co-authorship. PMID:25760732

Modeling Geomagnetic Variations using a Machine Learning Framework

NASA Astrophysics Data System (ADS)

Cheung, C. M. M.; Handmer, C.; Kosar, B.; Gerules, G.; Poduval, B.; Mackintosh, G.; Munoz-Jaramillo, A.; Bobra, M.; Hernandez, T.; McGranaghan, R. M.

2017-12-01

We present a framework for data-driven modeling of Heliophysics time series data. The Solar Terrestrial Interaction Neural net Generator (STING) is an open source python module built on top of state-of-the-art statistical learning frameworks (traditional machine learning methods as well as deep learning). To showcase the capability of STING, we deploy it for the problem of predicting the temporal variation of geomagnetic fields. The data used includes solar wind measurements from the OMNI database and geomagnetic field data taken by magnetometers at US Geological Survey observatories. We examine the predictive capability of different machine learning techniques (recurrent neural networks, support vector machines) for a range of forecasting times (minutes to 12 hours). STING is designed to be extensible to other types of data. We show how STING can be used on large sets of data from different sensors/observatories and adapted to tackle other problems in Heliophysics.

Lognormal Behavior of the Size Distributions of Animation Characters

NASA Astrophysics Data System (ADS)

Yamamoto, Ken

This study investigates the statistical property of the character sizes of animation, superhero series, and video game. By using online databases of Pokémon (video game) and Power Rangers (superhero series), the height and weight distributions are constructed, and we find that the weight distributions of Pokémon and Zords (robots in Power Rangers) follow the lognormal distribution in common. For the theoretical mechanism of this lognormal behavior, the combination of the normal distribution and the Weber-Fechner law is proposed.

Modernization and multiscale databases at the U.S. geological survey

USGS Publications Warehouse

Morrison, J.L.

1992-01-01

The U.S. Geological Survey (USGS) has begun a digital cartographic modernization program. Keys to that program are the creation of a multiscale database, a feature-based file structure that is derived from a spatial data model, and a series of "templates" or rules that specify the relationships between instances of entities in reality and features in the database. The database will initially hold data collected from the USGS standard map products at scales of 1:24,000, 1:100,000, and 1:2,000,000. The spatial data model is called the digital line graph-enhanced model, and the comprehensive rule set consists of collection rules, product generation rules, and conflict resolution rules. This modernization program will affect the USGS mapmaking process because both digital and graphic products will be created from the database. In addition, non-USGS map users will have more flexibility in uses of the databases. These remarks are those of the session discussant made in response to the six papers and the keynote address given in the session. ?? 1992.

Construction of crystal structure prototype database: methods and applications.

PubMed

Su, Chuanxun; Lv, Jian; Li, Quan; Wang, Hui; Zhang, Lijun; Wang, Yanchao; Ma, Yanming

2017-04-26

Crystal structure prototype data have become a useful source of information for materials discovery in the fields of crystallography, chemistry, physics, and materials science. This work reports the development of a robust and efficient method for assessing the similarity of structures on the basis of their interatomic distances. Using this method, we proposed a simple and unambiguous definition of crystal structure prototype based on hierarchical clustering theory, and constructed the crystal structure prototype database (CSPD) by filtering the known crystallographic structures in a database. With similar method, a program structure prototype analysis package (SPAP) was developed to remove similar structures in CALYPSO prediction results and extract predicted low energy structures for a separate theoretical structure database. A series of statistics describing the distribution of crystal structure prototypes in the CSPD was compiled to provide an important insight for structure prediction and high-throughput calculations. Illustrative examples of the application of the proposed database are given, including the generation of initial structures for structure prediction and determination of the prototype structure in databases. These examples demonstrate the CSPD to be a generally applicable and useful tool for materials discovery.

Construction of crystal structure prototype database: methods and applications

NASA Astrophysics Data System (ADS)

Su, Chuanxun; Lv, Jian; Li, Quan; Wang, Hui; Zhang, Lijun; Wang, Yanchao; Ma, Yanming

2017-04-01

Crystal structure prototype data have become a useful source of information for materials discovery in the fields of crystallography, chemistry, physics, and materials science. This work reports the development of a robust and efficient method for assessing the similarity of structures on the basis of their interatomic distances. Using this method, we proposed a simple and unambiguous definition of crystal structure prototype based on hierarchical clustering theory, and constructed the crystal structure prototype database (CSPD) by filtering the known crystallographic structures in a database. With similar method, a program structure prototype analysis package (SPAP) was developed to remove similar structures in CALYPSO prediction results and extract predicted low energy structures for a separate theoretical structure database. A series of statistics describing the distribution of crystal structure prototypes in the CSPD was compiled to provide an important insight for structure prediction and high-throughput calculations. Illustrative examples of the application of the proposed database are given, including the generation of initial structures for structure prediction and determination of the prototype structure in databases. These examples demonstrate the CSPD to be a generally applicable and useful tool for materials discovery.

A seabird monitoring program for the North Pacific

USGS Publications Warehouse

Hatcher, S.A.; Kaiser, G.W.; Kondratyev, Alexander V.; Byrd, G.V.

1994-01-01

Seabird monitoring is the accumulation of time series data on any aspect of seabird distribution, abundance, demography, or behavior. Typical studies include annual or less frequent measures of numbers or productivity; less commonly, the focus is on marine habitat use, phenology, food habits, or survival. The key requirement is that observations are replicated over time and made with sufficient precision and accuracy to permit the meaningful analysis of variability and trends. Along the Pacific coast of North America, seabird monitoring has consumed substantial amounts of public funding since the early 1970s. The effort has been largely uncoordinated among the many entities involved, including provincial, state, and federal agencies, some private organizations, university faculty, and students. We reaffirm the rationale for monitoring seabirds, review briefly the nature and accomplishments of the existing effort, and suggest actions needed to improve the effectiveness of seabird monitoring in the Pacific. In particular, we propose and describe a comprehensive Seabird Monitoring Database designed specifically to work with observations on seabird population parameters that are replicated over time.

A retrospective clinical study of incidence of root canal instrument separation in an endodontics graduate program: a PennEndo database study.

PubMed

Iqbal, Mian K; Kohli, Meetu R; Kim, Jessica S

2006-11-01

This study investigated the incidence of hand and rotary instrument separation (IS) in the endodontics graduate program at the University of Pennsylvania between 2000 and 2004. In 4,865 endodontic resident cases the incidence of hand and rotary IS was 0.25% and 1.68%, respectively. The odds for rotary IS were seven times more than for hand IS. The probability of separating a file in apical third was 33, and 6 times more likely when compared to coronal and middle thirds of the canals. The highest percentage of IS occurred in mandibular (55.5%) and maxillary (33.3%) molars. Furthermore, the odds of separating a file in molars were 2.9 times greater than premolars. Among the ProFile series 29 rotary instruments, the .06 taper # 5 and # 6 files separated the most. There was no significant difference in IS between the use of torque controlled versus nontorque controlled handpieces, nor between first and second year residency.

Detection of a sudden change of the field time series based on the Lorenz system.

PubMed

Da, ChaoJiu; Li, Fang; Shen, BingLu; Yan, PengCheng; Song, Jian; Ma, DeShan

2017-01-01

We conducted an exploratory study of the detection of a sudden change of the field time series based on the numerical solution of the Lorenz system. First, the time when the Lorenz path jumped between the regions on the left and right of the equilibrium point of the Lorenz system was quantitatively marked and the sudden change time of the Lorenz system was obtained. Second, the numerical solution of the Lorenz system was regarded as a vector; thus, this solution could be considered as a vector time series. We transformed the vector time series into a time series using the vector inner product, considering the geometric and topological features of the Lorenz system path. Third, the sudden change of the resulting time series was detected using the sliding t-test method. Comparing the test results with the quantitatively marked time indicated that the method could detect every sudden change of the Lorenz path, thus the method is effective. Finally, we used the method to detect the sudden change of the pressure field time series and temperature field time series, and obtained good results for both series, which indicates that the method can apply to high-dimension vector time series. Mathematically, there is no essential difference between the field time series and vector time series; thus, we provide a new method for the detection of the sudden change of the field time series.

Estimated incidence of pertussis in people aged <50 years in the United States

PubMed Central

Chen, Chi-Chang; Balderston McGuiness, Catherine; Krishnarajah, Girishanthy; Blanchette, Christopher M.; Wang, Yuanyuan; Sun, Kainan; Buck, Philip O.

2016-01-01

ABSTRACT The introduction of pertussis vaccination in the United States (US) in the 1940s has greatly reduced its burden. However, the incidence of pertussis is difficult to quantify, as many cases are not laboratory-confirmed or reported, particularly in adults. This study estimated pertussis incidence in a commercially insured US population aged <50 years. Data were extracted from IMS' PharMetrics Plus claims database for patients with a diagnosis of pertussis or cough illness using International Classification of Diseases (ICD-9) codes, a commercial outpatient laboratory database for patients with a pertussis laboratory test, and the Centers for Disease Control influenza surveillance database. US national pertussis incidence was projected using 3 methods: (1) diagnosed pertussis, defined as a claim for pertussis (ICD-9 033.0, 033.9, 484.3) during 2008–2013; (2) based on proxy pertussis predictive logistic regression models; (3) using the fraction of cough illness (ICD-9 033.0, 033.9, 484.3, 786.2, 466.0, 466.1, 487.1) attributed to laboratory-confirmed pertussis, estimated by time series linear regression models. Method 1 gave a projected annual incidence of diagnosed pertussis of 9/100,000, which was highest in those aged <1 year. Method 2 gave an average annual projected incidence of 21/100,000. Method 3 gave an overall regression-estimated weighted annual incidence of pertussis of 649/100,000, approximately 58–93 times higher than method 1 depending on the year. These estimations, which are consistent with considerable underreporting of pertussis in people aged <50 years and provide further evidence that the majority of cases go undetected, especially with increasing age, may aid in the development of public health programs to reduce pertussis burden. PMID:27246119

Freight transportation in Oklahoma : selected data from federal sources

DOT National Transportation Integrated Search

1996-10-01

Welcome to the State Freight Transportation Profile. This report presents information on freight transportation in Oklahoma and is part of a series of reports covering all 50 States. The purpose of the report is to present the major Federal databases...

Freight transportation in Illinois : selected data from federal sources

DOT National Transportation Integrated Search

1996-10-01

Welcome to the State Freight Transportation Profile. This report presents information on freight transportation in Illinois and is part of a series of reports covering all 50 States. The purpose of the report is to present the major Federal databases...

Freight transportation in Wisconsin : selected data from federal sources

DOT National Transportation Integrated Search

1996-10-01

Welcome to the State Freight Transportation Profile. This report presents information on freight transportation in Wisconsin and is part of a series of reports covering all 50 States. The purpose of the report is to present the major Federal database...

Freight transportation in Missouri : selected data from federal sources

DOT National Transportation Integrated Search

1996-10-01

Welcome to the State Freight Transportation Profile. This report presents information on freight transportation in Missouri and is part of a series of reports covering all 50 States. The purpose of the report is to present the major Federal databases...

Freight transportation in Michigan : selected data from federal sources

DOT National Transportation Integrated Search

1996-10-01

Welcome to the State Freight Transportation Profile. This report presents information on freight transportation in Michigan and is part of a series of reports covering all 50 States. The purpose of the report is to present the major Federal databases...

Freight transportation in Wyoming : selected data from federal sources

DOT National Transportation Integrated Search

1996-10-01

Welcome to the State Freight Transportation Profile. This report presents information on freight transportation in Wyoming and is part of a series of reports covering all 50 States. The purpose of the report is to present the major Federal databases ...

Freight transportation in Indiana : selected data from federal sources

DOT National Transportation Integrated Search

1996-10-01

Welcome to the State Freight Transportation Profile. This report presents information on freight transportation in Indiana and is part of a series of reports covering all 50 States. The purpose of the report is to present the major Federal databases ...

Freight transportation in Vermont : selected data from federal sources

DOT National Transportation Integrated Search

1996-10-01

Welcome to the State Freight Transportation Profile. This report presents information on freight transportation in Vermont and is part of a series of reports covering all 50 States. The purpose of the report is to present the major Federal databases ...

Freight transportation in Colorado : selected data from federal sources

DOT National Transportation Integrated Search

1996-10-01

Welcome to the State Freight Transportation Profile. This report presents information on freight transportation in Colorado and is part of a series of reports covering all 50 States. The purpose of the report is to present the major Federal databases...

Freight transportation in Minnesota : selected data from federal sources

DOT National Transportation Integrated Search

1996-10-01

Welcome to the State Freight Transportation Profile. This report presents information on freight transportation in Minnesota and is part of a series of reports covering all 50 States. The purpose of the report is to present the major Federal database...

Volatility of linear and nonlinear time series

NASA Astrophysics Data System (ADS)

Kalisky, Tomer; Ashkenazy, Yosef; Havlin, Shlomo

2005-07-01

Previous studies indicated that nonlinear properties of Gaussian distributed time series with long-range correlations, ui , can be detected and quantified by studying the correlations in the magnitude series ∣ui∣ , the “volatility.” However, the origin for this empirical observation still remains unclear and the exact relation between the correlations in ui and the correlations in ∣ui∣ is still unknown. Here we develop analytical relations between the scaling exponent of linear series ui and its magnitude series ∣ui∣ . Moreover, we find that nonlinear time series exhibit stronger (or the same) correlations in the magnitude time series compared with linear time series with the same two-point correlations. Based on these results we propose a simple model that generates multifractal time series by explicitly inserting long range correlations in the magnitude series; the nonlinear multifractal time series is generated by multiplying a long-range correlated time series (that represents the magnitude series) with uncorrelated time series [that represents the sign series sgn(ui) ]. We apply our techniques on daily deep ocean temperature records from the equatorial Pacific, the region of the El-Ninõ phenomenon, and find: (i) long-range correlations from several days to several years with 1/f power spectrum, (ii) significant nonlinear behavior as expressed by long-range correlations of the volatility series, and (iii) broad multifractal spectrum.

An interactive toolkit to extract phenological time series data from digital repeat photography

NASA Astrophysics Data System (ADS)

Seyednasrollah, B.; Milliman, T. E.; Hufkens, K.; Kosmala, M.; Richardson, A. D.

2017-12-01

Near-surface remote sensing and in situ photography are powerful tools to study how climate change and climate variability influence vegetation phenology and the associated seasonal rhythms of green-up and senescence. The rapidly-growing PhenoCam network has been using in situ digital repeat photography to study phenology in almost 500 locations around the world, with an emphasis on North America. However, extracting time series data from multiple years of half-hourly imagery - while each set of images may contain several regions of interest (ROI's), corresponding to different species or vegetation types - is not always straightforward. Large volumes of data require substantial processing time, and changes (either intentional or accidental) in camera field of view requires adjustment of ROI masks. Here, we introduce and present "DrawROI" as an interactive web-based application for imagery from PhenoCam. DrawROI can also be used offline, as a fully independent toolkit that significantly facilitates extraction of phenological data from any stack of digital repeat photography images. DrawROI provides a responsive environment for phenological scientists to interactively a) delineate ROIs, b) handle field of view (FOV) shifts, and c) extract and export time series data characterizing image color (i.e. red, green and blue channel digital numbers for the defined ROI). The application utilizes artificial intelligence and advanced machine learning techniques and gives user the opportunity to redraw new ROIs every time an FOV shift occurs. DrawROI also offers a quality control flag to indicate noisy data and images with low quality due to presence of foggy weather or snow conditions. The web-based application significantly accelerates the process of creating new ROIs and modifying pre-existing ROI in the PhenoCam database. The offline toolkit is presented as an open source R-package that can be used with similar datasets with time-lapse photography to obtain more data for studying phenology for a large community of ecologists. We will illustrate the use of the toolkit using imagery from a selection of sites within the National Ecological Observatory Network (NEON).

Duality between Time Series and Networks

PubMed Central

Campanharo, Andriana S. L. O.; Sirer, M. Irmak; Malmgren, R. Dean; Ramos, Fernando M.; Amaral, Luís A. Nunes.

2011-01-01

Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways. PMID:21858093

A framework for cross-observatory volcanological database management

NASA Astrophysics Data System (ADS)

Aliotta, Marco Antonio; Amore, Mauro; Cannavò, Flavio; Cassisi, Carmelo; D'Agostino, Marcello; Dolce, Mario; Mastrolia, Andrea; Mangiagli, Salvatore; Messina, Giuseppe; Montalto, Placido; Fabio Pisciotta, Antonino; Prestifilippo, Michele; Rossi, Massimo; Scarpato, Giovanni; Torrisi, Orazio

2017-04-01

In the last years, it has been clearly shown how the multiparametric approach is the winning strategy to investigate the complex dynamics of the volcanic systems. This involves the use of different sensor networks, each one dedicated to the acquisition of particular data useful for research and monitoring. The increasing interest devoted to the study of volcanological phenomena led the constitution of different research organizations or observatories, also relative to the same volcanoes, which acquire large amounts of data from sensor networks for the multiparametric monitoring. At INGV we developed a framework, hereinafter called TSDSystem (Time Series Database System), which allows to acquire data streams from several geophysical and geochemical permanent sensor networks (also represented by different data sources such as ASCII, ODBC, URL etc.), located on the main volcanic areas of Southern Italy, and relate them within a relational database management system. Furthermore, spatial data related to different dataset are managed using a GIS module for sharing and visualization purpose. The standardization provides the ability to perform operations, such as query and visualization, of many measures synchronizing them using a common space and time scale. In order to share data between INGV observatories, and also with Civil Protection, whose activity is related on the same volcanic districts, we designed a "Master View" system that, starting from the implementation of a number of instances of the TSDSystem framework (one for each observatory), makes possible the joint interrogation of data, both temporal and spatial, on instances located in different observatories, through the use of web services technology (RESTful, SOAP). Similarly, it provides metadata for equipment using standard schemas (such as FDSN StationXML). The "Master View" is also responsible for managing the data policy through a "who owns what" system, which allows you to associate viewing/download of spatial or time intervals to particular users or groups.

Exercising privacy rights in medical science

PubMed Central

Hillmer, Michael; Redelmeier, Donald A.

2007-01-01

Privacy laws are intended to preserve human well-being and improve medical outcomes. We used the Sportstats website, a repository of competitive athletic data, to test how easily these laws can be circumvented. We designed a haphazard, unrepresentative case-series analysis and applied unscientific methods based on an Internet connection and idle time. We found it both feasible and titillating to breach anonymity, stockpile personal information and generate misquotations. We extended our methods to snoop on celebrities, link to outside databases and uncover refusal to participate. Throughout our study, we evaded capture and public humiliation despite violating these 6 privacy fundamentals. We suggest that the legitimate principle of safeguarding personal privacy is undermined by the natural human tendency toward showing off. PMID:18056619

Observations of V694 Mon (MWC 560) requested for Chandra campaign

NASA Astrophysics Data System (ADS)

Waagen, Elizabeth O.

2016-02-01

Dr. Jeno Sokoloski (Columbia University) and Mr. Adrian Lucy (graduate student, Columbia University) have requested AAVSO observations of the jet-driving symbiotic star V694 Mon (MWC 560), which is in outburst, in support of upcoming Chandra observations to investigate the state of the inner accretion disk during this outburst. Beginning now and continuing through April 2016, Sokoloski writes, "multi-band photometry (UBVRI, but especially UBV), spectroscopy, and minute-time-resolution light curves of the optical flickering are requested. Series of exposures in B or V will be very interesting." Finder charts with sequence may be created using the AAVSO Variable Star Plotter (https://www.aavso.org/vsp). Observations should be submitted to the AAVSO International Database. See full Alert Notice for more details.