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A method is proposed for formulating a tool database with reference to the machine tools and recommended operating conditions at a specific plant. The database may be used to program machining operations in a CAM system.
To address the need for a centralized root trait database, we are compiling the Fine-Root Ecology Database (FRED) from published literature and unpublished data. FRED Version 1 (FRED 1.0) currently houses more than 70,000 observations of root traits and their associated site, vegetation, edaphic, and climatic conditions from across the globe (see image below, which shows the more than 1000 distinct locations associated with observations in FRED 1.0). Data collection is ongoing and will continue for the foreseeable future. The more than 300 root traits currently housed in FRED 1.0 are described in detail here. FRED is focused on fine roots (less than 2 mm), as coarse roots are studied using different methodology, often at very different scales, and have different traits and trait interpretations.
Crystallographic phasing recovers the phase information that is lost during a diffraction experiment. Molecular replacement is a commonly used phasing method for crystal structures in the protein data bank. In one form it uses a protein sequence to search a structure database to find suitable templates for phasing. However, sequence information is not always available, such as when proteins are crystallized with unknown binding partner proteins or when the crystal is of a contaminant. The recent development of AlphaFold published the predicted protein structures for every protein from twenty distinct species. In this work, we tested whether AlphaFold-predicted E. coli protein structures were accurate enough to enable sequence-independent phasing of diffraction data from two crystallization contaminants of unknown sequence. Using each of more than 4000 predicted structures as a search model, robust molecular replacement solutions were obtained, which allowed the identification and structure determination of YncE and YadF. Our results demonstrate the general utility of the AlphaFold-predicted structure database with respect to sequence-independent crystallographic phasing.
As large language models (LLMs) continue to evolve, their capacity to replace humans as their surrogates is also improving. As increasing numbers of intelligent tutoring systems (ITSs) are embracing the integration of LLMs for digital tutoring, questions are arising as to how effective they are and if their hallucinatory behaviors diminish their perceived advantages. One critical question that is seldom asked if the availability, plurality, and relative weaknesses in the reasoning process of LLMs are contributing to the much discussed digital divide and equity and fairness in online learning. In this paper, we present an experiment with database design theory assignments and demonstrate that while their capacity to reason logically is improving, LLMs are still prone to serious errors. We demonstrate that in online learning and in the absence of a human instructor, LLMs could introduce inequity in the form of “wrongful” tutoring that could be devastatingly harmful for learners, which we call ignorant bias, in increasingly popular digital learning. We also show that significant challenges remain for STEM subjects, especially for subjects for which sound and free online tutoring systems exist. Based on the set of use cases, we formulate a possible direction for an effective ITS for online database learning classes of the future.
Space radiation has recently been considered a risk factor for astronauts’ cardiac health. As an example, for the case of how to query and identify datasets within NASA’s GeneLab database and demonstrate the database utility, we used an unbiased systems biology method for identifying key genes/drivers for the contribution of space radiation on the cardiovascular system. This knowledge can contribute to designing appropriate experiments targeting these specific pathways. Microarray data from cardiomyocytes of male C57BL/6 mice followed-up for 28 days after exposure to 900 mGy of 1 GeV proton or 150 mGy of 1 GeV/n 56 Fe were compared to human endothelial cells (HUVECs) cultured for 7 days on the International Space Station (ISS). We observed common molecular pathways between simulated space radiation and HUVECs flown on the ISS. The analysis suggests FYN is the central driver/hub for the cardiovascular response to space radiation: the known oxidative stress induced immediately following radiation would only be transient and would upregulate FYN, which in turn would reduce reactive oxygen species (ROS) levels, protecting the cardiovascular system. The transcriptomic signature of exposure to protons was also much closer to the spaceflight signature than 56 Fe’s signature. To our knowledge, this is the first time GeneLab datasets were utilized to provide potential biological indications that the majority of ions on the ISS are protons, clearly illustrating the power of omics analysis. More generally, this work also demonstrates how to combine animal radiation studies done on the ground and spaceflight studies to evaluate human risk in space.
We created a large database of physical parameters and variability indicators by fully reducing and analyzing the large number of spectra taken to complement the asteroseismic observations of the COnvection, ROtation and planetary Transits (CoRoT) satellite. 7103 spectra of 261 stars obtained with the ESO echelle spectrograph HARPS have been stored in the VO-compliant database Spectroscopic Indicators in a SeisMic Archive (SISMA), along with the CoRoT photometric data of the 72 CoRoT asteroseismic targets. The remaining stars belong to the same variable classes of the CoRoT targets and were observed to better characterize the properties of such classes. Several useful variability indicators (mean line profiles, indices of differential rotation, activity and emission lines) together with vsin i and radial-velocity measurements have been extracted from the spectra. The atmospheric parameters T{sub eff},logg, and [Fe/H] have been computed following a homogeneous procedure. As a result, we fully characterize a sample of new and known variable stars by computing several spectroscopic indicators, also providing some cases of simultaneous photometry and spectroscopy.
With the advent of more sensitive all-sky instruments, the transient universe is being probed in greater depth than ever before. Taking advantage of available resources, we have established a comprehensive database of black hole (and black hole candidate) X-ray binary (BHXB) activity between 1996 and 2015 as revealed by all-sky instruments, scanning surveys, and select narrow-field X-ray instruments on board the INTErnational Gamma-Ray Astrophysics Laboratory, Monitor of All-Sky X-ray Image, Rossi X-ray Timing Explorer, and Swift telescopes; the Whole-sky Alberta Time-resolved Comprehensive black-Hole Database Of the Galaxy or WATCHDOG. Over the past two decades, we have detected 132 transient outbursts, tracked and classified behavior occurring in 47 transient and 10 persistently accreting BHs, and performed a statistical study on a number of outburst properties across the Galactic population. We find that outbursts undergone by BHXBs that do not reach the thermally dominant accretion state make up a substantial fraction (∼40%) of the Galactic transient BHXB outburst sample over the past ∼20 years. Our findings suggest that this “hard-only” behavior, observed in transient and persistently accreting BHXBs, is neither a rare nor recent phenomenon and may be indicative of an underlying physical process, relatively common among binary BHs, involving the mass-transfer rate onto the BH remaining at a low level rather than increasing as the outburst evolves. We discuss how the larger number of these “hard-only” outbursts and detected outbursts in general have significant implications for both the luminosity function and mass-transfer history of the Galactic BHXB population.
We present a coherent database of spectroscopic observations of far-IR fine-structure lines from the Herschel/Photoconductor Array Camera and Spectrometer archive for a sample of 170 local active galactic nuclei (AGNs), plus a comparison sample of 20 starburst galaxies and 43 dwarf galaxies. Published Spitzer/IRS and Herschel/SPIRE line fluxes are included to extend our database to the full 10–600 μm spectral range. The observations are compared to a set of Cloudy photoionization models to estimate the above physical quantities through different diagnostic diagrams. We confirm the presence of a stratification of gas density in the emission regions of the galaxies, which increases with the ionization potential of the emission lines. The new [O iv]{sub 25.9μm}/[O iii]{sub 88μm} versus [Ne iii]{sub 15.6μm}/[Ne ii]{sub 12.8μm} diagram is proposed as the best diagnostic to separate (1) AGN activity from any kind of star formation and (2) low-metallicity dwarf galaxies from starburst galaxies. Current stellar atmosphere models fail to reproduce the observed [O iv]{sub 25.9μm}/[O iii]{sub 88μm} ratios, which are much higher when compared to the predicted values. Finally, the ([Ne iii]{sub 15.6μm} + [Ne ii]{sub 12.8μm})/([S iv]{sub 10.5μm} +[S iii]{sub 18.7μm}) ratio is proposed as a promising metallicity tracer to be used in obscured objects, where optical lines fail to accurately measure the metallicity. The diagnostic power of mid- to far-infrared spectroscopy shown here for local galaxies will be of crucial importance to study galaxy evolution during the dust-obscured phase at the peak of the star formation and black hole accretion activity (1<z<4). This study will be addressed by future deep spectroscopic surveys with present and forthcoming facilities such as the James Webb Space Telescope, the Atacama Large Millimeter/submillimeter Array, and the Space Infrared telescope for Cosmology and Astrophysics.
Estimates of galaxy distances based on indicators that are independent of cosmological redshift are fundamental to astrophysics. Researchers use them to establish the extragalactic distance scale, to underpin estimates of the Hubble constant, and to study peculiar velocities induced by gravitational attractions that perturb the motions of galaxies with respect to the “Hubble flow” of universal expansion. In 2006 the NASA/IPAC Extragalactic Database (NED) began making available a comprehensive compilation of redshift-independent extragalactic distance estimates. A decade later, this compendium of distances (NED-D) now contains more than 100,000 individual estimates based on primary and secondary indicators, available for more than 28,000 galaxies, and compiled from over 2000 references in the refereed astronomical literature. This paper describes the methodology, content, and use of NED-D, and addresses challenges to be overcome in compiling such distances. Currently, 75 different distance indicators are in use. We include a figure that facilitates comparison of the indicators with significant numbers of estimates in terms of the minimum, 25th percentile, median, 75th percentile, and maximum distances spanned. Brief descriptions of the indicators, including examples of their use in the database, are given in an appendix.
Solar flares are complicated physical phenomena that are observable in a broad range of the electromagnetic spectrum, from radio waves to γ -rays. For a more comprehensive understanding of flares, it is necessary to perform a combined multi-wavelength analysis using observations from many satellites and ground-based observatories. For an efficient data search, integration of different flare lists, and representation of observational data, we have developed the Interactive Multi-Instrument Database of Solar Flares (IMIDSF, https://solarflare.njit.edu/). The web-accessible database is fully functional and allows the user to search for uniquely identified flare events based on their physical descriptors and the availability of observations by a particular set of instruments. Currently, the data from three primary flare lists ( Geostationary Operational Environmental Satellites , RHESSI , and HEK) and a variety of other event catalogs ( Hinode , Fermi GBM, Konus- W IND, the OVSA flare catalogs, the CACTus CME catalog, the Filament eruption catalog) and observing logs ( IRIS and Nobeyama coverage) are integrated, and an additional set of physical descriptors (temperature and emission measure) is provided along with an observing summary, data links, and multi-wavelength light curves for each flare event since 2002 January. We envision that this new tool will allow researchers to significantly speed up the search of events of interest for statistical and case studies.
Abstract. Measurements of dissolved organic carbon (DOC), nitrogen (DON), and phosphorus (DOP) concentrations are used to characterize the dissolved organic matter (DOM) pool and are important components of biogeochemical cycling in the coastal ocean. Here, we present the first edition of a global database (CoastDOM v1; available at https://doi.org/10.1594/PANGAEA.964012, Lønborg et al., 2023) compiling previously published and unpublished measurements of DOC, DON, and DOP in coastal waters. These data are complemented by hydrographic data such as temperature and salinity and, to the extent possible, other biogeochemical variables (e.g. chlorophyll a, inorganic nutrients) and the inorganic carbon system (e.g. dissolved inorganic carbon and total alkalinity). Overall, CoastDOM v1 includes observations of concentrations from all continents. However, most data were collected in the Northern Hemisphere, with a clear gap in DOM measurements from the Southern Hemisphere. The data included were collected from 1978 to 2022 and consist of 62 338 data points for DOC, 20 356 for DON, and 13 533 for DOP. The number of measurements decreases progressively in the sequence DOC > DON > DOP, reflecting both differences in the maturity of the analytical methods and the greater focus on carbon cycling by the aquatic science community. The global database shows that the average DOC concentration in coastal waters (average ± standard deviation (SD): 182±314 µmol C L−1; median: 103 µmol C L−1) is 13-fold higher than the average coastal DON concentration (13.6±30.4 µmol N L−1; median: 8.0 µmol N L−1), which is itself 39-fold higher than the average coastal DOP concentration (0.34±1.11 µmol P L−1; median: 0.18 µmol P L−1). This dataset will be useful for identifying global spatial and temporal patterns in DOM and will help facilitate the reuse of DOC, DON, and DOP data in studies aimed at better characterizing local biogeochemical processes; closing nutrient budgets; estimating carbon, nitrogen, and phosphorous pools; and establishing a baseline for modelling future changes in coastal waters.
Ponds and lakes are abundant in Arctic permafrost lowlands. They play an important role in Arctic wetland ecosystems by regulating carbon, water, and energy fluxes and providing freshwater habitats. However, ponds, i.e., waterbodies with surface areas smaller than 1.0 × 10 4 m 2 , have not been inventoried on global and regional scales. The Permafrost Region Pond and Lake (PeRL) database presents the results of a circum-Arctic effort to map ponds and lakes from modern (2002–2013) high-resolution aerial and satellite imagery with a resolution of 5 m or better. The database also includes historical imagery from 1948 to 1965 with a resolution of 6 m or better. PeRL includes 69 maps covering a wide range of environmental conditions from tundra to boreal regions and from continuous to discontinuous permafrost zones. Waterbody maps are linked to regional permafrost landscape maps which provide information on permafrost extent, ground ice volume, geology, and lithology. This paper describes waterbody classification and accuracy, and presents statistics of waterbody distribution for each site. Maps of permafrost landscapes in Alaska, Canada, and Russia are used to extrapolate waterbody statistics from the site level to regional landscape units. PeRL presents pond and lake estimates for a total area of 1.4 × 10 6 km 2 across the Arctic, about 17 % of the Arctic lowland ( < 300 m a.s.l.) land surface area. PeRL waterbodies with sizes of 1.0 ×10 6 m 2 down to 1.0 ×10 2 m 2 contributed up to 21 % to the total water fraction. Waterbody density ranged from 1.0 ×10 to 9.4 × 10 1 km –2 . Ponds are the dominant waterbody type by number in all landscapes representing 45–99 % of the total waterbody number. In conclusion, the implementation of PeRL size distributions in land surface models will greatly improve the investigation and projection of surface inundation and carbon fluxes in permafrost lowlands.
The convective cell tracking database V1 using the ARM CSAPR2 radar data set at the Sierras de Córdoba (COR) AMF site in Argentina consists of individually tracked convective cells during the entire CACTI field campaign from 15 October 2018 to 3 March 2019. The cell tracking database is produced by applying an updated version of the FLEXible object TRaKeR (FLEXTRKR) (Feng et al. 2022) to the Cartesian gridded CSAPR2 PPI data set produced by the Taranis radar processing package (Hardin et al. 2020).
This document describes a global database of inter-basin hydrological transfers that has been used by the University of New Hampshire Water Balance Model for several years. The database has focussed primarily on large scale water transfers that are built, under-construction, or proposed.
This database represents a list of community solar projects identified through various sources as of Spring 2018. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the souces e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to Eric O'Shaughnessy at eric.oshaughnessy@nlr.gov.
A multi-device database of disruption characteristics has been developed under the auspices of the International Tokamak Physics Activity magneto-hydrodynamics topical group. The purpose of this ITPA disruption database (IDDB) is to find the commonalities between the disruption and disruption mitigation characteristics in a wide variety of tokamaks in order to elucidate the physics underlying tokamak disruptions and to extrapolate toward much larger devices, such as ITER and future burning plasma devices. In contrast to previous smaller disruption data collation efforts, the IDDB aims to provide significant context for each shot provided, allowing exploration of a wide array of relationships between pre-disruption and disruption parameters. The IDDB presently includes contributions from nine tokamaks, including both conventional aspect ratio and spherical tokamaks. An initial parametric analysis of the available data is presented. This analysis includes current quench rates, halo current fraction and peaking, and the effectiveness of massive impurity injection. The IDDB is publicly available, with instruction for access provided herein.
A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.
A method identifies electric load types of a plurality of different electric loads. The method includes providing a load feature database of a plurality of different electric load types, each of the different electric load types including a first load feature vector having at least four different load features; sensing a voltage signal and a current signal for each of the different electric loads; determining a second load feature vector comprising at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the different electric loads; and identifying by a processor one of the different electric load types by determining a minimum distance of the second load feature vector to the first load feature vector of the different electric load types of the load feature database.