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Found 6 result(s)
This interactive database provides complete access to statistics on seasonal cotton supply and use for each country and each region in the world, from 1920/21 to date. This project is part of ICAC’s efforts to improve the transparency of world cotton statistics.
We present the MUSE-Wide survey, a blind, 3D spectroscopic survey in the CANDELS/GOODS-S and CANDELS/COSMOS regions. Each MUSE-Wide pointing has a depth of 1 hour and hence targets more extreme and more luminous objects over 10 times the area of the MUSE-Deep fields (Bacon et al. 2017). The legacy value of MUSE-Wide lies in providing "spectroscopy of everything" without photometric pre-selection. We describe the data reduction, post-processing and PSF characterization of the first 44 CANDELS/GOODS-S MUSE-Wide pointings released with this publication. Using a 3D matched filtering approach we detected 1,602 emission line sources, including 479 Lyman-α (Lya) emitting galaxies with redshifts 2.9≲z≲6.3. We cross-match the emission line sources to existing photometric catalogs, finding almost complete agreement in redshifts and stellar masses for our low redshift (z < 1.5) emitters. At high redshift, we only find ~55% matches to photometric catalogs. We encounter a higher outlier rate and a systematic offset of Δz≃0.2 when comparing our MUSE redshifts with photometric redshifts. Cross-matching the emission line sources with X-ray catalogs from the Chandra Deep Field South, we find 127 matches, including 10 objects with no prior spectroscopic identification. Stacking X-ray images centered on our Lya emitters yielded no signal; the Lya population is not dominated by even low luminosity AGN. A total of 9,205 photometrically selected objects from the CANDELS survey lie in the MUSE-Wide footprint, which we provide optimally extracted 1D spectra of. We are able to determine the spectroscopic redshift of 98% of 772 photometrically selected galaxies brighter than 24th F775W magnitude. All the data in the first data release - datacubes, catalogs, extracted spectra, maps - are available at the website.
DBpedia is a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself.
The Analytical Geomagnetic Data Center of the Trans-Regional INTERMAGNET Segment is operated by the Geophysical Center of the Russian Academy of Sciences (GC RAS). Geomagnetic data are transmitted from observatories and stations located in Russia and near-abroad countries. The Center also provides access to spaceborne data products. The MAGNUS hardware-software system underlies the operation of the Center. Its particular feature is the automated real-time recognition of artificial (anthropogenic) disturbances in incoming data. Being based on fuzzy logic approach, this quality control service facilitates the preparation of the definitive magnetograms from preliminary records carried out by data experts manually. The MAGNUS system also performs on-the-fly multi-criteria estimation of geomagnetic activity using several indicators and provides online tools for modeling electromagnetic parameters in the near-Earth space. The collected geomagnetic data are stored using relational database management system. The geomagnetic database is intended for storing both 1-minute and 1-second data. The results of anthropogenic and natural disturbance recognition are also stored in the database.
Nuclear Data Services contains atomic, molecular and nuclear data sets for the development and maintenance of nuclear technologies. It includes energy-dependent reaction probabilities (cross sections), the energy and angular distributions of reaction products for many combinations of target and projectile, and the atomic and nuclear properties of excited states, and their radioactive decay data. Their main concern is providing data required to design a modern nuclear reactor for electricity production. Approximately 11.5 million nuclear data points have been measured and compiled into computerized form.
MalaCards is an integrated database of human maladies and their annotations, modeled on the architecture and richness of the popular GeneCards database of human genes. MalaCards mines and merges varied web data sources to generate a computerized web card for each human disease. Each MalaCard contains disease specific prioritized annotative information, as well as links between associated diseases, leveraging the GeneCards relational database, search engine, and GeneDecks set-distillation tool. As proofs of concept of the search/distill/infer pipeline we find expected elucidations, as well as potentially novel ones.