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863 results for “chemistry”
Google Scholar search record: ?start=0&q=crayfish+%22water+chemistry%22&hl=en&as_vis=0,5&as_sdt=0,5
File generated: Search date, time, timezone: 2022-04-15 17:50:45 (Europe/London) Search parameters: All these words: crayfish None of these words: This exact word or phrase: "water chemistry" Any these words: Language: en Between these years: and Number of pages exported: 1 Starting from page: 1 Citations included: TRUE Citations included: TRUE Search only in the title: FALSE Authors: Source: GS links generated: https://scholar.google.co.uk/scholar?start=0&q=crayfish+%22water+chemistry%22&hl=en&as_vis=0,5&as_sdt=0,5
Google Scholar search record: ?start=0&q=crayfish+%22water+chemistry%22&hl=en&as_vis=0,5&as_sdt=0,5
File generated: Search date, time, timezone: 2022-04-15 17:34:33 (Europe/London) Search parameters: All these words: crayfish None of these words: This exact word or phrase: "water chemistry" Any these words: Language: en Between these years: and Number of pages exported: 1 Starting from page: 1 Citations included: TRUE Citations included: TRUE Search only in the title: FALSE Authors: Source: GS links generated: https://scholar.google.co.uk/scholar?start=0&q=crayfish+%22water+chemistry%22&hl=en&as_vis=0,5&as_sdt=0,5
Conformation and structural features of diuron and irgarol: insights from quantum chemistry calculations.
<p>A set of conformational relevant structures of Diuron and Irgarol (two biocides) obtained from conformational analyses carried out using Density Functional Theory (DFT). The geometries are given in the mol2 format.</p>
Probing the Extent of Vertical Mixing in Brown Dwarf Atmospheres with Disequilibrium Chemistry
<p><strong>OVERVIEW</strong></p> <p>The substellar atmospheric models described in <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220814317M/abstract">Mukherjee et al. (2022)</a> are presented here. The grid of these 1D radiative-convective atmospheric models was computed using the newly released open-source climate code PICASO 3.0 (<a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220807836M/abstract">Mukherjee et al. (2022)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2019ApJ...878...70B/abstract">Batalha et al. (2019)</a>). The grid consists of four parameters – the effective temperature (T<sub>eff</sub>), gravity (log(g)), K<sub>zz</sub> in the radiative zones, and mixing length in the convective zones. Models with T<sub>eff </sub> between 400-1000 K with an increment of 25 K are included. log(g) has been varied from 4.5 to 5.5 with an increment of 0.25 dex. The K<sub>zz</sub> in the radiative zone has been varied between 1x, 0.01x, and 100x the parametrization presented in <a href="https://ui.adsabs.harvard.edu/abs/2022ExA....53..279M/abstract">Moses et al. (2021)</a>, whereas the convective mixing length has been between the atmospheric pressure scale height and 0.1x the scale height.</p> <p>There are three types of files released here – atmospheric composition files (TP_chemistry), thermal emission spectra files (spectra), and atmospheric Kzz profile files (TP_kz). </p> <p><strong>ATMOSPHERIC COMPOSITION</strong></p> <p>The atmospheric composition files are located in the folder TP_chemistry. These files have the temperature structure of the atmosphere as a function of pressure accompanied by the volume mixing ratio of 37 gases as a function of pressure. </p> <p>The TP_chemistry files are named following the format “profile_sc_qt_rz_[factor1]_cz_[factor2]_[Teff]_grav_[gravity]_mh_+0.0_sm_NA.dat", where [factor1] denotes the multiplier used for the radiative zone Kzz and can vary between ‘x0pt01’, ‘x1’, and ‘x100’. [factor2] denotes the multiplier for the mixing length and can vary between ‘1’ and ‘0pt1’. [Teff] and [gravity] denote the Teff and gravity of the models used. A simple code snippet to read and plot these files is presented below.</p> <p><strong>SPECTRA</strong></p> <p>The spectra files are located in the folder "spectra_highres_1", "spectra_highres_2", "spectra_highres_3", and "spectra_highres_4". These files have the thermal emission spectra between 0.3-30 microns calculated using the computed models. The native spectral resolution of these calculations is at an R = 500,000, but <strong>please be aware that these spectra should always be binned down to a resolution of R = 50,000 or less before usage</strong>. This means that these spectra should only be used to interpret datasets with a spectral resolution of 50,000 or less. Please contact the authors if higher resolution spectra are needed. The spectra have been uploaded in three different folders to make the file sizes manageable for transfer.</p> <p>The spectra files are also similarly named using the format “spectra_sc_qt_rz_[factor1]_cz_[factor2]_[Teff]_grav_[gravity]_mh_+0.0_sm_NA.tar.gz". These files can be directly read into a Python pandas dataframe using </p> <pre><code class="language-python">pd.read_csv(filename, compression='gzip')</code></pre> <p> The first column of the file is wavenumbers in cm<sup>-1, </sup>which can be converted to wavelength in microns by wavelength [microns] =10000/wavenumbers[cm<sup>-1</sup>]. The second column of the file is flux in erg/s/cm<sup>2</sup>/cm. Note that these fluxes need to be multiplied with R<sup>2</sup>/D<sup>2</sup> before comparing them with the typically observed flux of brown dwarfs/exoplanets. R is the radius of the object, and D is the distance here. A tutorial to convert these fluxes to other units is present in <a href="https://natashabatalha.github.io/picaso/notebooks/6_BrownDwarfs.html#Convert-to-F_\nu-Units-and-Regrid">this link</a>. A binned-down version (R=15,000) of these high-resolution spectra can also be found in the "spectra_lowres" folder. These can be used for datasets that have a maximum spectral resolution of 15,000.</p> <p><strong>K<sub>zz</sub> PROFILE</strong></p> <p>The K<sub>zz </sub>as a function of pressure for each model is presented in these files. The K<sub>zz</sub> is reported in cm<sup>2</sup>/s. These files are also similarly named using the format “kz_sc_qt_rz_[factor1]_cz_[factor2]_[Teff]_grav_[gravity]_mh_+0.0_sm_NA.dat". The columns of the files are pressure in bars, the temperature in K, and Kzz in cm<sup>2</sup>/s.</p> <p> </p> <p><strong>EXAMPLE PYTHON CODE TO READ AND PLOT COMPOSITION FILES</strong></p> <pre><code class="language-python">import numpy as np import pandas as pd import matplotlib.pyplot as plt grav = np.array([316,562,1000,1780,3160]) Teff=np.array([400,425,450,475,500,525,550,575,600,625,650,675,700,725,750,775,800,825,850,875,900,925,950,975,1000]) factor1 = np.array(['x0pt01','x1','x100']) factor2 = np.array(['1','0pt1']) file ="profile_sc_qt_rz_"+factor1[0]+"_cz_"+factor2[0]+"_"+str(Teff[14])+"_grav_"+str(grav[14])+"_mh_+0.0_sm_NA.dat" df = pd.read_csv(file, sep="\t") # Plot T(P) profile plt.ylim(100,1e-4) plt.semilogy(df['temperature'],df['pressure']) plt.show() # Plot H2O mixing ratio profile plt.ylim(100,1e-4) plt.loglog(df['H2O'],df['pressure']) plt.show()</code></pre> <p><strong>CREDITS</strong></p> <p>If you use these tables, please cite <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv220814317M/abstract">Mukherjee et al. (2022, Astrophysical Journal, in press.)</a></p> <p> </p>
Variability due to climate and chemistry in observations of oxygenated Earth-analogue exoplanets: Simulations and results
<p>The Great Oxidation Event was a period during which Earth's atmospheric oxygen (O<sub>2</sub>) concentrations increased from ~10<sup>−5</sup> times its present atmospheric level (PAL) to near modern levels, marking the start of the Proterozoic geological eon 2.4 billion years ago. Using WACCM6, an Earth System Model, we simulate the atmosphere of Earth-analogue exoplanets with O<sub>2</sub> mixing ratios between 0.1% and 150% PAL. Using these simulations, we calculate the reflection/emission spectra over multiple orbits using the Planetary Spectrum Generator. We highlight how observer angle, albedo, chemistry, and clouds affect the simulated observations. We show that inter-annual climate variations, as well as short-term variations due to clouds, can be observed in our simulated atmospheres with a telescope concept such as LUVOIR or HabEx. Annual variability and seasonal variability can change the planet's reflected flux (including the reflected flux of key spectral features such as O<sub>2</sub> and H<sub>2</sub>O) by up to factors of 5 and 20, respectively, for the same planetary phase. This variability is best observed with a high-throughput coronagraph. For example, HabEx (4 m) with a starshade performs up to a factor of two times better than a LUVOIR B (6 m) style telescope. The variability and signal-to-noise ratio of some spectral features depends non-linearly on atmospheric O<sub>2</sub> concentration. This is caused by temperature and chemical column depth variations, as well as generally increased liquid and ice cloud content for atmospheres with O<sub>2</sub> concentrations of <1% PAL.</p>
Quantum calculation results for "Butyl Acetate Pyrolysis and Combustion Chemistry: Mechanism Generation and Shock Tube Experiments"
<p>This repository contains the quantum calculation results associated with the paper "Butyl Acetate Pyrolysis and Combustion Chemistry: Mechanism Generation and Shock Tube Experiments" by Xiaorui Dong, Gianmaria Pio, Farhan Arafin, Andrew Laich, Jessica Baker, Erik Ninnemann, Subith S. Vasu, and William H. Green.</p> <p>In the BA_QM.zip, there are five subfolders:</p> <ul> <li>The "BA_Habs" folder has 18 entries related to the calculations of butyl acetate H abstraction reactions</li> <li>The "BA_Retroene" folder has 6 entries related to the calculations of butyl acetate retro-ene reactions</li> <li>The "Species" folder has 606 entries related to the calculations of non-TS species included in the kinetic mechanisms.</li> <li>The "TS_XYZ" and "XYZ" folders contain the XYZ files of the calculated TS and non-TS geometries, respectively.</li> </ul> <p>For each species and TS calculation, the CBS-QB3 optimization/single point energy calculation is stored in the "composite" folder, the frequency calculation is stored in the 'freq' folder, and scan jobs for torsional modes (if available) are stored in the 'scan_XXXX' folders. For reaction and TS entries, folders are named in a user-readable way. For species, folders are named according to their SMILES representation.</p>
Spectral and trait data for Rapid estimates of leaf litter chemistry using reflectance spectroscopy
<p>Measuring the chemical traits of leaf litter is important for understanding plants' roles in nutrient cycles, including through nutrient resorption and litter decomposition, but conventional leaf trait measurements are often destructive and labor-intensive. Here, we develop and evaluate the performance of partial least-squares regression (PLSR) models that use reflectance spectra of intact or ground leaves to estimate leaf litter traits, including carbon and nitrogen concentration, carbon fractions, and leaf mass per area (LMA). Our analyses included more than 300 samples of senesced foliage from 11 species of temperate trees, including needleleaf and broadleaf species. Across all samples, we could predict each trait with moderate-to-high accuracy from both intact-leaf litter spectra (validation <em>R<sup>2</sup></em> = 0.543-0.941; %RMSE = 7.49-18.5) and ground-leaf litter spectra (validation <em>R<sup>2</sup></em> = 0.491-0.946; %RMSE = 7.00-19.5). Notably, intact-leaf spectra yielded better predictions of LMA. Our results support the feasibility of building models to estimate multiple chemical traits from leaf litter of a range of species. In particular, the success of intact-leaf spectral models allows non-destructive trait estimation in a matter of seconds, which could enable researchers to measure the same leaves over time in studies of nutrient resorption.</p>
EnzChemRED, a rich enzyme chemistry relation extraction dataset
<h1>Abstract</h1> <p>Expert curation is essential to capture knowledge of enzyme functions from the scientific literature in FAIR open knowledgebases but cannot keep pace with the rate of new discoveries and new publications. In this work we present EnzChemRED, for Enzyme Chemistry Relation Extraction Dataset, a new training and benchmarking dataset to support the development of Natural Language Processing (NLP) methods such as (large) language models that can assist enzyme curation. EnzChemRED consists of 1,210 expert curated PubMed abstracts in which enzymes and the chemical reactions they catalyze are annotated using UniProtKB and ChEBI identifiers. We show that fine-tuning language models with EnzChemRED significantly boosts their ability to identify proteins and chemicals in text (86.30% F1 score) and to extract the chemical conversions in which they participate (86.66% F1 score), and the enzymes that catalyze those conversions (83.79% F1 score). We apply our methods to abstracts at PubMed scale to create a draft map of enzyme functions in literature to guide curation efforts in UniProtKB and the reaction knowledgebase Rhea.</p> <p><strong>Corresponding authors:</strong> Alan Bridge (alan.bridge@sib.swiss) and Zhiyong Lu (zhiyong.lu@nih.gov)</p> <h1>Content</h1> <p>This repository contains data to support the development of natural language processing (NLP) methods to mine biochemical reactions from text for Rhea and UniProt.</p>
Data set for "A Magnesium Binding Site And The Anomeric Effect Regulate The Abiotic Redox Chemistry Of Nicotinamide Nucleotides"
<p>Data associated with Sebastianelli L, Kaur H, Chen Z, Krishnamurthy R, Mansy SS (2024) A magnesium binding site and the anomeric effect regulate the abiotic redox chemistry of nicotinamide nucleotides. Chem Eur J. 30, e202400411. DOI: 10.1002/chem.202400411 [<a href="https://chemistry-europe.onlinelibrary.wiley.com/doi/abs/10.1002/chem.202400411">link</a>]</p>
The Pan-Canadian Chemical Library: A Mechanism to Open Academic Chemistry to High-Throughput Virtual Screening
<h1>Pan-Canadian Chemical Library</h1> <p>This Zenodo repository contains the cheap and druglike subset of the Pan-Canadian Chemical Library (PCCL) project. For more information, visit <a href="https://pccl.thesgc.org/" rel="nofollow">https://pccl.thesgc.org</a>.</p> <h2>PCCL library</h2> <p>The PCCL library is splitted by reaction, then by number of heavy atoms. Two types of files are available in zip archives:</p> <ul> <li>The SMILES format files, with the SMILES string and their product name,</li> <li>The CSV format file, with all the information generated during their enumeration: reagents, druglike properties, etc.</li> </ul> <p>Note: Purchasability is defined according to two integers: 1 for products only composed of BB-50 reagents, and 2 for products composed of BB-40 or BB-50 reagents. Read more about the meaning of these reagents groups in the article below.</p> <h2>Citation</h2> <p>If you find the PCCL useful or if you use it, please cite our paper:</p> <p>Bedart, C. <em>et al.</em> The Pan-Canadian Chemical Library: A mechanism to open academic chemistry to high-throughput virtual screening. Scientific Data 11, (2024).<br>doi: <a title="10.1038/s41597-024-03443-5" href="https://www.nature.com/articles/s41597-024-03443-5">10.1038/s41597-024-03443-5</a></p> <p> </p> <p> </p>
Age-resolved chemistry of red giants in the solar neighbourhood
<p>In our associated paper we find age-abundance trends for individual elements using a sample of solar-neighborhood stars observed with the SDSS-APOGEE instrument. Here we publish the likelihood functions from a Bayesian isochrone matching to determine the most probable age.</p>
Improvements to stratospheric chemistry scheme in the UM-UKCA (v10.7) model: solar cycle and heterogeneous reactions
<p>These are the data and the Python notebooks required to create the figures from the paper.</p> <p> </p> <p>Abstract:</p> <p>Improvements are made to two areas of the United Kingdom Chemistry and Aerosol (UKCA) module, which forms part of the Met Office Unified Model (UM) used for weather and climate applications. Firstly, a solar cycle is added to the photolysis scheme. The effect on total column ozone of this addition was found to be around 1-2% in mid-latitude and equatorial regions in phase with the solar cycle. Secondly, reactions occurring on the surfaces of polar stratospheric clouds and sulfate aerosol are updated and extended by modification of the uptake coefficients of five existing reactions and the addition of a further eight reactions involving bromine species. These modifications are shown to reduce the overabundance of modeled total-column ozone in the Arctic during October to February, southern mid-latitudes during August, and the Antarctic during September. Antarctic springtime ozone depletion is shown to be enhanced by 25 DU on average, which now causes the ozone hole to be somewhat too deep compared to observations. We show that this is in part due to a cold bias of the Antarctic polar vortex in the model.</p>
Nobel Prize winners in Physics, Chemistry and Medicine or Physiology 1994-2018
<p>The lists of Nobel Prize winners in Physics, Chemistry and Medicine or Physiology 1994-2018 + theirs Scopus ID's and theirs affiliations at the time of the award.</p>
Sensitivity Analysis of Gas-Phase Aromatic Chemistry in TMC-1
<p>This repository contains a number of files related to the gas-phase kinetic sensitivity analysis presented and described in Byrne et al. 2024 (in prep). The raw abundances as a function of time for all analyses are contained in 'Sensitivity_raw.hdf5.zip', while the sensitivities are located in 'Sensitivity_data.hdf5.zip'. 'Sens_Walkthrough.ipynb' is a jupyter notebook that explains how to examine this data using functions defined in 'ranking.py' and 'plotting.py'. This notebook also requires the two reactions.in files. Finally, the input files used to generate the data along with the NAUTILUS modeling code can be found in 'Model-Inputs.zip'. These inputs primarily come from the development branch of cixue/BATMAN with minor changes described in a README file.</p>
Fig. 1 in The prevalence of Leucocytozoon spp. in nestlings of three wild raptor species including implications on haematological and blood chemistry values
Fig. 1. Prevalence of Leucozytozoon spp. infection in nestlings of common buzzards (Buteo buteo), red kites (Milvus milvus) and northern goshawks (Accipiter gentilis). Asterisks refer to P-values ≤0.05, determined by GLMM. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in The prevalence of Leucocytozoon spp. in nestlings of three wild raptor species including implications on haematological and blood chemistry values
Fig. 3. Results of linear discriminant analysis (LDA) comparing 15 selected blood parameters between uninfected and infected raptor nestlings. a) Distribution of the LDA according to uninfected and infected nestlings. b) Correlation plot of the first axis of the 15 selected variables.
Fig. 2 in The prevalence of Leucocytozoon spp. in nestlings of three wild raptor species including implications on haematological and blood chemistry values
Fig. 2. Proportion of infected individuals of common buzzard (Buteo buteo), red kite (Milvus milvus) and northern goshawk (Accipiter gentilis) nestlings (n = 528) in relation to the proportion of the nestling period, determined by age and the species-specific average nestling duration. Calculated nestling periods were grouped into steps of ten percent (0.2–0.9). Each step represents the proportion of all individuals examined within this period. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
The role of catchment characteristics, discharge, and active layer thaw on seasonal stream chemistry across ten permafrost catchments
<p>Data used for the paper: The role of catchment characteristics, discharge, and active layer thaw on seasonal stream chemistry across ten permafrost catchments. Contains water quality and discharge data. See paper for more details.</p>
In situ synthesis within micron-sized soft chemical reactors created via programmable aerosol chemistry
<p>Dataset of microscope images to accompany our manuscript. Images are arranged in folder based on experiment number and each folder contains a file describing the images individually.</p>
Sonora Bobcat: cloud-free, substellar atmosphere models, spectra, photometry, evolution, and chemistry
<p><strong>OVERVIEW</strong></p> <p>Presented here are models for non-irradiated, substellar mass objects belonging to the Sonora model series, described in Marley et al. (2021). The files presented here are model temperature-pressure structures ("structure"), emergent spectra from the top of the atmosphere ("spectra"), thermal evolution and photometry ("evolution_and_photometry"), and rainout chemical equilibrium tables used to compute the models ("chemistry"). </p> <p>Atmospheric structure and spectra .tar file names specify metallicity [M/H] and carbon-to-oxygen ratio (C/O) relative to solar. For example, "structures+0.0_co1.5<a href="../api/files/2e9ce76a-67fc-4fd6-ae5c-f88f16c610ea/structures%2B0.0_co1.5.tar.gz">.</a>tar.gz" contains the set of radiative-convective equilibrium atmospheric structures for solar metallicity ("+0.0") with C/O=1.5 times the solar abundance. The _co*.* is omitted for solar C/O, or co_1.0. The individual file naming convention is described below. All stated abundances and ratios are relative to Lodders (2010) abundances, see Marley et al. (2021) for details and use caution when referring to other abundance tabulations.</p> <p>This particular set of model atmosphere structures and associated spectra, photometry, and evolution, which we name <strong>Sonora Bobcat</strong>, are for cloudless objects with 3.25 ≤ log g (cgs) ≤ 5.5 and 200 ≤ Teff ≤ 2400K. Steps in T<sub>eff</sub> vary from 25K to 1000K and steps in log g are 0.25 or 0.5. Some combinations of model grid parameters include additional values of the gravity. Models are provided for [M/H] = -0.5, 0.0, and +0.5 and "rainout" chemical equilibrium. A limited set of models with carbon-to-oxygen ratio of 0.5 and 1.5 times solar abundance are also included. For the convenience of having a rectangular table in (T<sub>eff</sub>, gravity) space, models are calculated in regimes that are not reached by the evolution, such as very high gravity and very low T<sub>eff</sub>. Refer to the companion evolution tables to identify combinations of T<sub>eff</sub> and log g outside the bounds covered by the evolution.</p> <p><strong>ATMOSPHERIC STRUCTURE</strong></p> <p>Atmospheric structure and spectra filenames specify Teff and gravity (in mks units) along with [M/H] and (C/O) relative to solar. "co1.5" in version and spectra header nomenclature refers to 1.5 times the solar C/O ratio. _co*.* is generally omitted for 1.0, the solar value. For example, the file t1000g316nc_m-0.5.dat contains the structure of a model with T<sub>eff</sub>=1000K, g=316m/s<sup>2</sup> (the exact value of the gravity is given<sup> </sup>in the first line of the file, see below) , [Fe/H]=-0.5, and C/O=1.0 times the solar value. </p> <p>Temperature structure and spectra files have a one line header giving "Teff, grav(MKS), Y, f_sed, kz_min, [Fe/H], C/O, f_hole". Teff and grav are the effective temperature (K) and gravity (MKS), Y is the He mass fraction. f_sed is a cloud parameterization which is not relevant for these cloudless models and is arbitrarily given as 0.0. Likewise kz_min relates to the atmospheric eddy diffusion coefficient, which is also not relevant for these chemical equilibrium models and is arbitrarily set equal to a placeholder value that is not used in these models. [Fe/H] and C/O are the metallicity and C/O ratios as described above. [Fe/H] is identical to [M/H]. f_hole is another cloud parameter for cloudy models, not relevant to these cloudless models.</p> <p>Columns in the atmosphere structure files describe the atmosphere at discrete levels. Columns give: level index, P(bar), T(K), internally used check parameter, adiabatic temperature gradient (d ln T / d ln P), local temperature gradient (d ln T / d ln P), atmospheric density (g / cm<sup>3</sup>).</p> <p><strong>EVOLUTION AND PHOTOMETRY</strong></p> <p>Evolution and Photometry tables are described in detail in a README file included in that tar file. Evolution files connect mass, effective temperature, radius, age, gravity, and moment of inertia for these model sets. Each set of model spectra is complemented with tables of fluxes and of absolute magnitudes in a number of photometric systems commonly used in brown dwarf and exoplanet research (MKO, Keck, 2MASS, SDSS, WISE, Spitzer IRAC, etc). Fluxes and magnitudes for the full set of JWST filters is also included in separate tables. Magnitudes are computed on the Vega system (using the Vega spectrum of Bohlin & Gilliland 2004) or on the AB system (e.g. for SDSS).</p> <p><strong>SPECTRA</strong></p> <p>The model spectra each contain close to 362000 wavelength points. The resolving power varies with wavelength and ranges from R=6000 to 200000 but is otherwise the same for all spectra. The first line gives the model parameters in the same format as the structure files described above. This is followed by the spectrum</p> <p>Column 1: wavelength in µm</p> <p>Column 2: <strong>Radiation flux <em>F<sub>ν</sub></em></strong><sub> </sub>= \(4\pi\) x Eddington flux <em>H</em><sub>ν</sub>, in erg/cm<sup>2</sup>/s/Hz (always exercise caution with factors of \(4\pi\) when comparing to the radiation and Eddington flux, e.g., see Section 3.3 of Hubeny & Mihalas, "Theory of Stellar Atmospheres")</p> <p>The spectral fluxes are given at the top of the atmosphere and are strictly monochromatic. The model spectrum provides no information in the wavelength range between two tabulated points. Unless a spectral line or feature is well resolved,<em> interpolation in wavelength is not advised</em>. For comparison with data, the model spectra need to be convolved and binned to the instrumental resolution and sampling. In our experience, a minimum of 10 wavelength points is necessary to obtain a reasonable average flux over a wavelength interval. This is a rule of thumb and caution is advised, especially when comparing with high resolution data. The flux received at Earth is that given in the table scaled by (R/D)<sup>2</sup> where R is the radius of the object (given in the companion evolution tables) and D its distance. </p> <p>The solar spectra and photometry are the same as those archived at https://zenodo.org/record/1309035#.YOyz4S1h2X0, which did not provide the T(P) profiles available here.</p> <p><strong>CHEMISTRY</strong></p> <p>We also separately include rainout chemical equilibrium tables for these same atmospheric bulk abundances. These chemistry files are described in detail by their own README file. Additional chemistry tables, beyond those used for the models presented here, are also included for completeness. Users interested in the chemical abundances of the structure models must interpolate within the matching chemistry file for the atmospheric species of interest.</p> <p><strong>CREDITS</strong></p> <p>If you use these tables in your research, please cite Marley et al. (2021, Astrophysical Journal, Volume 920, Issue 2, id.85.)</p> <p>16 Feb 2024: Error corrected in Column 2 heading. Column 2 is the Radiation flux, not the Eddington flux as previously stated. Citation updated.</p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.