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BackgroundTreatment of patients presenting with possible acute myocardial infarction (AMI) is based on timely diagnosis and proper risk stratification aided by biomarkers. We aimed at evaluating the predictive value of GDF-15 in patients presenting with symptoms suggestive of AMI.MethodsConsecutive patients presenting with suspected AMI were enrolled in three study centers. Cardiovascular events were assessed during a follow-up period of 6 months with a combined endpoint of death or MI.ResultsFrom the 1818 enrolled patients (m/f = 1208/610), 413 (22.7%) had an acute MI and 63 patients reached the combined endpoint. Patients with MI and patients with adverse outcome had higher GDF-15 levels compared with non-MI patients (967.1pg/mL vs. 692.2 pg/L, p<0.001) and with event-free patients (1660 pg/mL vs. 756.6 pg/L, p<0.001). GDF-15 levels were lower in patients with SYNTAX score ≤ 22 (797.3 pg/mL vs. 947.2 pg/L, p = 0.036). Increased GDF-15 levels on admission were associated with a hazard ratio of 2.1 for death or MI (95%CI: 1.67–2.65, p<0.001) in a model adjusted for age and sex and of 1.57 (1.13–2.19, p = 0.008) adjusted for the GRACE score variables. GDF-15 showed a relevant reclassification with regards to the GRACE score with an overall net reclassification index (NRI) of 12.5% and an integrated discrimination improvement (IDI) of 14.56% (p = 0.006).ConclusionGDF-15 is an independent predictor of future cardiovascular events in patients presenting with suspected MI. GDF-15 levels correlate with the severity of CAD and can identify and risk-stratify patients who need coronary revascularization.

Data obtained from computational DFT calculations on Cubic GdF is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files.

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Context

WorlWorld Development Indicators sheet is collected to understand various countries and their development score.

Content

I have collected this data from the world data bank by selecting specific countries.

World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially recognized international sources. It presents the most current and accurate global development data available and includes national, regional, and g and global estimates. [Note: Even though Global Development Finance (GDF) is no longer listed in the WDI database name, all external debt and financial flows data continue to be included in WDI. The GDF publication has been renamed International Debt Statistics (IDS) and has its own separate database, as well.

Acknowledgements

Thanks to the World Data Bank for the dataset.

Inspiration

You can work on finding which country is having the highest innovation score or social development score.

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A 20 year, 20,000 person, open longitudinal epidemiological study of a cohort town. GAZEL was not constructed to answer a specific question rather it was designed to help analyze a wide range of scientific problems and is accessible to the community of researchers specializing in epidemiology. Translation is not available for all pages. The GAZEL cohort, set up in 1989 by Inserm Unit 88 (subsequently Unit 687), in cooperation with several departments of ��lectricit�� de France-Gaz de France (EDF-GDF), was a public utility firm in France involved in production, transmission and distribution of energy. GAZEL initially included 20 624 volunteers working at EDF-GDF (15 010 men and 5614 women), aged from 35 to 50 years. In accordance with its purpose as a scientific research platform, the GAZEL cohort is permanently open to epidemiologic research teams. Today, more than 50 projects on very diversified themes have been set up in GAZEL by some 20 teams, French, belonging to different bodies, and foreign (Germany, Belgium, Canada, Great Britain, Sweden, Finland, and USA).

The simulated synthetic aperture sonar (SAS) data presented here was generated using PoSSM [Johnson and Brown 2018]. The data is suitable for bistatic, coherent signal processing and will form acoustic seafloor imagery. Included in this data package is simulated sonar data in Generic Data Format (GDF) files, a description of the GDF file contents, example SAS imagery, and supporting information about the simulated scenes. In total, there are eleven 60 m x 90 m scenes, labeled scene00 through scene10, with scene00 provided with the scatterers in isolation, i.e. no seafloor texture. This is provided for beamformer testing purposes and should result in an image similar to the one labeled "PoSSM-scene00-scene00-starboard-0.tif" in the Related Data Sets tab. The ten other scenes have varying degrees of model variation as described in "Description_of_Simulated_SAS_Data_Package.pdf". A description of the data and the model is found in the associated document called "Description_of_Simulated_SAS_Data_Package.pdf" and a description of the format in which the raw binary data is stored is found in the related document "PSU_GDF_Format_20240612.pdf". The format description also includes MATLAB code that will effectively parse the data to aid in signal processing and image reconstruction. It is left to the researcher to develop a beamforming algorithm suitable for coherent signal and image processing. Each 60 m x 90 m scene is represented by 4 raw (not beamformed) GDF files, labeled sceneXX-STARBOARD-000000 through 000003. It is possible to beamform smaller scenes from any one of these 4 files, i.e. the four files are combined sequentially to form a 60 m x 90 m image. Also included are comma separated value spreadsheets describing the locations of scatterers and objects of interest within each scene. In addition to the binary GDF data, a beamformed GeoTIFF image and a single-look complex (SLC, science file) data of each scene is provided. The SLC data (science) is stored in the Hierarchical Data Format 5 (https://www.hdfgroup.org/), and appended with ".hdf5" to indicate the HDF5 format. The data are stored as 32-bit real and 32-bit complex values. A viewer is available that provides basic graphing, image display, and directory navigation functions (https://www.hdfgroup.org/downloads/hdfview/). The HDF file contains all the information necessary to reconstruct a synthetic aperture sonar image. All major and contemporary programming languages have library support for encoding/decoding the HDF5 format. Supporting documentation that outlines positions of the seafloor scatterers is included in "Scatterer_Locations_Scene00.csv", while the locations of the objects of interest for scene01-scene10 are included in "Object_Locations_All_Scenes.csv". Portable Network Graphic (PNG) images that plot the location of objects of all the objects of interest in each scene in Along-Track and Cross-Track notation are provided.

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Data obtained from computational DFT calculations on Tetragonal GdF is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files.

The Interstellar Boundary Explorer, IBEX, has operated in space since 2008 updating our knowledge of the outer heliosphere and its interaction with the local interstellar medium. Start-time: 2008-12-25. There are currently 15 releases of IBEX-HI and/or IBEX-LO data covering the years from 2009 to 2018. This data set is derived from the Release 14 three-year IBEX-Hi map data with two-year overlaps of adjacent maps, 2009-2011, 2010-2012, and so forth through 2015-2017 from ram-direction fluxes with corrections for spacecraft motion, cg: Compton-Getting, but with no corrections, sp, for Energetic Neutral Atom, ENA, survival probability between 1 and 100 AU. The data set parameters include line-of-sight, LOS, integrated pressures computed separately from the Global Distributed Flux, GDF, the Ribbon Flux, and the Total Flux from summing GDF and Ribbon LOS pressures. Additionally there are signal to noise ratios for the GDF, Ribbon, and Total LOS pressures. Finally, there are power law slope values for the GDF differential flux and signal to noise ratios of the slope. The IBEX Release 14 data are archived as fully citable data. Please consult IBEX team publications and personnel for further details on production, processing, and usage of these data. The data consist of ram-direction sky maps in Solar Ecliptic Longitude, east and west, and Latitude angles for the above parameters. Details of the data and enabled science from Release 14 are given in the following journal publication: Schwadron, N. A., et al. 2018, Time Dependence of the IBEX Ribbon and the Globally Distributed Energetic Neutral Atom Flux Using the First 9 Years of Observations, DOI: 10.3847/1538-4365/aae48e. The following codes are used to define data set types in the multiple IBEX data releases: +-----------------------------------------------------------------------------------------------------------------------------------------------------------------+ Code Code definition --------- ------------------------------------------------------------------------------------------------------------------------------------------------------- cg Compton-Getting corrections have been applied to the data to account for the speed of the spacecraft relative to the direction of arrival of the ENAs nocg no Compton-Getting corrections --------- ------------------------------------------------------------------------------------------------------------------------------------------------------- sp survival probability corrections have been applied to the data to account for the loss of ENAs due to radiation pressure, photoionization and ionization via charge exchange with solar wind protons as they stream through the heliosphere. This correction scales the data out from IBEX at 1 AU to approximately 100 AU. In the original data this mode is denoted as Tabular. noSP no survival probability corrections have been applied to the data --------- ------------------------------------------------------------------------------------------------------------------------------------------------------- omni data from all directions ram data was collected when the spacecraft was ramming into the incoming ENAs antiram data was collected when the spacecraft was moving away from the incoming ENAs +-----------------------------------------------------------------------------------------------------------------------------------------------------------------+ This particular data set denoted in the original ASCII files as: +------------------------------------------------------------------------------------------------------------------------------------------------------------+ Directory Name File Content Description +---------------- -------------------------------------------------------------------------------------------------------------------------------------------+ GDFPressure Globally Distributed Flux Line-of-Sight Integrated Pressure in pdyne-au/cm^2 GDFSlope Power Law Slope of the differential flux spectrum for the Globally Distributed Flux GDFSlopeSN Signal/Noise ratio of the GDF differential flux power law slope where noise represents uncertainty GDFSN Globally Distributed Flux Signal/Noise, where Noise is defined as the uncertainty and the Signal is GDF Line-of-Sight integrated pressure RibbonPressure Ribbon Line-of-Sight Integrated Pressure in pdyne-au/cm^2 RibbonSN Ribbon Signal/Noise, where Noise is defined as the uncertainty and the Signal is GDF Line-of-Sight integrated pressure TotPressure Total Pressure in ENA maps including both the GDF and Ribbon. Line-of-Sight Integrated Pressure in pdyne-au/cm^2 TotSN Total Pressure Signal-to-Noise where noise represents uncertainty and signal represents the Total LOS integrated pressure +------------------------------------------------------------------------------------------------------------------------------------------------------------+

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World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates. [Note: Even though Global Development Finance (GDF) is no longer listed in the WDI database name, all external debt and financial flows data continue to be included in WDI. The GDF publication has been renamed International Debt Statistics (IDS), and has its own separate database, as well.

Last Updated:01/28/2025

Data contains Following 20 Countries 'Argentina', 'Australia', 'Brazil', 'China', 'France', 'Germany', 'India', 'Indonesia', 'Italy', 'Japan', 'Korea, Rep.', 'Mexico', 'Netherlands', 'Russian Federation', 'Saudi Arabia', 'Spain', 'Switzerland', 'Turkiye', 'United Kingdom', 'United States'

Dataset contains below Development Indicators 'Adolescent fertility rate (births per 1,000 women ages 15-19)', 'Agriculture, forestry, and fishing, value added (% of GDP)', 'Annual freshwater withdrawals, total (% of internal resources)', 'Births attended by skilled health staff (% of total)', 'Contraceptive prevalence, any method (% of married women ages 15-49)', 'Domestic credit provided by financial sector (% of GDP)', 'Electric power consumption (kWh per capita)', 'Energy use (kg of oil equivalent per capita)', 'Exports of goods and services (% of GDP)', 'External debt stocks, total (DOD, current US$)', 'Fertility rate, total (births per woman)', 'Foreign direct investment, net inflows (BoP, current US$)', 'Forest area (sq. km)', 'GDP (current US$)', 'GDP growth (annual %)', 'GNI per capita, Atlas method (current US$)', 'GNI per capita, PPP (current international $)', 'GNI, Atlas method (current US$)', 'GNI, PPP (current international $)', 'Gross capital formation (% of GDP)', 'High-technology exports (% of manufactured exports)', 'Immunization, measles (% of children ages 12-23 months)', 'Imports of goods and services (% of GDP)', 'Income share held by lowest 20%', 'Industry (including construction), value added (% of GDP)', 'Inflation, GDP deflator (annual %)', 'Life expectancy at birth, total (years)', 'Merchandise trade (% of GDP)', 'Military expenditure (% of GDP)', 'Mobile cellular subscriptions (per 100 people)', 'Mortality rate, under-5 (per 1,000 live births)', 'Net barter terms of trade index (2015 = 100)', 'Net migration', 'Net official development assistance and official aid received (current US$)', 'Personal remittances, received (current US$)', 'Population density (people per sq. km of land area)', 'Population growth (annual %)', 'Population, total', 'Poverty headcount ratio at $2.15 a day (2017 PPP) (% of population)', 'Poverty headcount ratio at national poverty lines (% of population)', 'Prevalence of HIV, total (% of population ages 15-49)', 'Prevalence of underweight, weight for age (% of children under 5)', 'Primary completion rate, total (% of relevant age group)', 'Revenue, excluding grants (% of GDP)', 'School enrollment, primary (% gross)', 'School enrollment, primary and secondary (gross), gender parity index (GPI)', 'School enrollment, secondary (% gross)', 'Surface area (sq. km)', 'Tax revenue (% of GDP)', 'Terrestrial and marine protected areas (% of total territorial area)', 'Time required to start a business (days)', 'Total debt service (% of exports of goods, services and primary income)', 'Urban population growth (annual %)

A method and composition are provided for inducing or enhancing chondrogenesis in vivo or in vitro. The method is performed by exposing the cells in vitro or in vivo to an extracellular matrix comprising of type I collagen, type II collagen or a mixture of type I collagen or type II collagen and hyaluronate and further containing GDF-5.

Description This dataset provides the raw data from observations made with the Whipple 10-meter imaging atmospheric Cherenkov telescope at the Fred Lawrence Whipple Observatory (FLWO) on Mt. Hopkins, Arizona between September 1994 and July 2011. The data are stored in a proprietary format, based on the CERN FZ framework, for which we have developed a pure Python reader/decoder with which you can extract the images and metadata for display or analysis. The observation logsheets which describe the data taking are also available for the majority of nights. Unfortunately a substantial fraction of the observations has been lost to the passage of time, so the dataset here is not complete. It is difficult to estimate the total quantity of data lost. The observations were generally made in 28-minute long runs with the telescope tracking a source in the sky during dark, moonless nights. These observations are organized into darkruns between the full-moon periods when no data-taking could be made, and into seasons around the Summer monsoon period in Arizona when the camera was disconnected to protect it from damage from lightning storms. The imaging camera used on the Whipple 10m telescope evolved during the time from 1994 to 2011, with this evolution being described in detail by Kildea et al., Astroparticle Physics, 28, 2, 182-195, (2007). Raw data files: raw10/dYYYYMMDD/gtNNNNNN.fz.xz Data recorded during each observation run are stored in a single data file in the Granite data format (GDF). These files contain multiple records of different types, as described in some detail in the readme page for the Python reader/decoder. The following record types are available and are supported by the reader: Run header: Nominal start time of the run, comments entered by the observer, and other miscellaneous information. 10m event: The data recorded for each event, including time, digitized image, trigger type, etc. 10m frame: Data recorded for special calibration events in early Whipple data. Phased out in GDF version 80 (starting on 1997-10-29), after which the calibration data appears in the 10m event records, flagged by a specific trigger bit. Tracking status: Target name and coordinates, and position of telescope (azimuth and elevation angles) read out periodically from the tracking computer, if available. HV status: Measured voltages and currents on each PMT, read out periodically from the high-voltage system, if available. Here the data files are grouped into tar archives for each season, e.g. raw10_1998_1999.tar, which will yield data files with the following hierarchy when unpacked: raw10/dYYYYMMDD/gtNNNNNN.fz.xz, where YYYYMMDD is the UTC date of the observations and NNNNNN is a zero-padded run number of the observation. The data files are compressed using the standard LZMA compression format, which can be read directly by the Python reader (there is no need to decompress the files manually). Users can download the full dataset (tar files) from this repository, unpack them and operate on them locally. Alternatively, the Python reader can download individual runs from the repository on-the-fly, which allows the data to be explored without downloading in advance. The raw data repository comprises: 22,805 observation runs, taken on 1,827 nights of observation, where 620,331,605 events were recorded during 24,633,108 seconds of observation (6,842.5 hours). Log sheet files: log10/dYYYYMMDD.log_10 The observations for each night are described by a plain-text (ASCII) log sheet, written by the observers that operated the telescope each night. These log sheets are also available in the repository, grouped into a tar archive, log10.tar, which unpacks into a set of files with the following hierarchy: log10/dYYYYMMDD.log_10. The logs have been anonymized to remove references to the names of the observers and support staff. The logs describe the observations made, problems encountered, weather conditions, modifications to the hardware, and give the results of a "quicklook" analysis of the data files (significance of any detection and rate of gamma rays detected). The logsheet archive comprises 2,582 logsheets describing the observations made on individual nights. Run database: raw10_run_summary.csv.xz Two summary databases are also available in CSV form. The file raw10_run_summary.csv.xz contains one entry for each data file in the archive, obtained by scanning the data file and processing the various records. Each record contains the following entries: filename: filename in the archive in the form raw10/dYYYYMMDD/gtNNNNNN.fz.xz (string) run_number: run number, extracted from the filename (integer) gdf_version: version number of the Granite data format (integer, between 21 and 83) nheader: number of GDF header records in the file (integer) nevent: number of GDF event records in the file (integer) nframe: number of GDF frame records in the file (integer) ntracking: number of GDF tracking records in the file (integer)...

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Data obtained from computational DFT calculations on Hexagonal GdF is provided. Available data include crystal structure, bandgap energy, stability, density of states, and calculation input/output files.

This composition appears in the F-Gd region of phase space. It's relative stability is shown in the F-Gd phase diagram (left). The relative stability of all other phases at this composition (and the combination of other stable phases, if no compound at this composition is stable) is shown in the relative stability plot (right)