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8,937 results for “Acidity”
Supplementary data (CC BY-NC-SA 4.0): A reactive neural network framework for water-loaded acidic zeolites
<p><strong>Content (Creative Commons Attribution Non Commercial Share Alike 4.0 International):</strong></p><p>This dataset provides supplementary data to "A reactive neural network framework for water-loaded acidic zeolites". It contains trained Neural Network Potentials (NNP and ΔNNP model), scripts, and all energy and force data used in this work at the (Δ)NNP, ReaxFF, and DFT (SCAN+D3(BJ) and ωB97X-D3(BJ)) level. Energy and forces are stored as ASE trajectory files (traj), readable by the <a href="https://wiki.fysik.dtu.dk/ase/index.html">Atomic Simulation Environment </a>(ASE). In addition, this repository contains the generated training database with DFT (SCAN+D3(BJ)) energies and forces as SchNetPack1.0 database (SiAlOH.db) file readable by ASE and <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>.</p><ol><li>"aimd_simulations.zip" - VASP INCAR file, XDATCAR and traj file for 10 ps AIMD run (Supplementary Figure 6) and NNP level (re-)calculated energies/forces ("aimd_nnp_recalc.traj")</li><li>"biased_dynamics.zip" - VASP/Plumed input and output files for DFT (SCAN+D3(BJ)) and NNP level biased dynamics including traj files (Supplementary Figure 12)</li><li>"database_input.zip" - structure (cif) files of the initial structures used for database generation (Supplementary Table 1)</li><li>"delta_nnp.zip" - (pytorch) ΔNNP model (compatible with <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>) together with example scripts </li><li>"error_stats.zip" - traj files of all generalization tests (Figure 1 and Supplementary Figure 4) storing energies/forces at the SCAN+D3(BJ), ReaxFF, and NNP level as well as traj files with ΔNNP and ωB97X-D3(BJ) energies/forces for a subset taken from biased dynamics runs (Supplementary Figure 11)</li><li>"md_simulations.zip" - NNP level MD trajectories of all generalization test (Figure 1 and Supplementary Figure 4) runs including an example script for an MD run</li><li>"neb_calculations.zip" - traj files and example scripts for NEB calculations at the (Δ)NNP along with the corresponding DFT energy/force data (SCAN+D3(BJ) and ωB97X-D3(BJ))</li><li>"nnps.zip" - (pytorch) NNP model files (compatible with <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>)</li><li>"silica_database.zip" - output files of the single-point (SP) and optimization test runs (Supplementary Figure 1) of pure silica structures together with an example structure optimization script </li><li>"SiAlOH.db" - DFT (SCAN+D3(BJ)) training database as SchNetPack1.0 database file readable by ASE and <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a></li></ol>
Dataset of "Liquid-Jet Photoemission Spectroscopy as a Structural Tool: Site-Specific Acid-Base Chemistry of Vitamin C"
<p>Liquid-jet photoemission spectroscopy (LJ-PES) directly probes the electronic structure of solutes<br>and solvents. It also emerges as a novel tool to explore chemical structure in aqueous solutions, yet<br>the scope of the approach has to be examined. Here, we present a pH-dependent liquid-jet photoelectron<br>spectroscopic investigation of ascorbic acid (vitamin C). We combine core-level photoelectron<br>spectroscopy and ab initio calculations, allowing us to site-specifically explore the acid-base chemistry<br>of the biomolecule. For the first time, we demonstrate the capability of the method to simultaneously<br>assign two deprotonation sites within the molecule. We show that a large change in chemical shift<br>appears even for atoms distant several bonds from the chemically modified group. Furthermore, we<br>present a highly efficient and accurate computational protocol based on a single structure using the<br>maximum overlap method for modeling core-level photoelectron spectra in aqueous environments.<br>This work poses a broader question: To what extent can LJ-PES complement established structural<br>techniques such as nuclear magnetic resonance? Answering this question is highly relevant in view<br>of the large number of incorrect molecular structures published.</p>
Concentration of gaseous iodic acid measured over the Southern Ocean in the austral summer of 2016/2017, during the Antarctic Circumnavigation Expedition (ACE).
<p>Measurements of iodic acid concentration in the gas phase obtained with a nitrate chemical ionization mass spectrometer (we used an APi-TOF mass spectrometer produced by Tofwerk AG coupled with a Chemical ionization inlet A70 produced by Airmodus). Iodic acid is detected in the mass spectrometer either as a deprotonated ion or as a cluster with the reagent ion (NO3-). The concentration is calculated as the area of these two peaks normalized to the concentration of the reagent ions (monomer, dimer and trimer) and multiplied by a calibration factor equal to 6.9E9 molecules cm<sup>-3</sup> that was experimentally derived at Paul Scherrer Institute in the summer 2017, after the campaign.</p> <p>Iodic acid can participate in both new particle formation and growth, affecting the Earth radiative balance and cloud properties. Iodic acid is produced from the iodine radical but the exact formation pathways is still unknown.</p> <p>Measurements were performed on the upper deck of the icebreaker Akademik Tryoshnikov along the track of the Antarctic Circumnavigation expedition. Temporal coverage is from January 22, 2017 to March 19, 2017. There are no data for the first leg of the expedition because the instrument was not on the ship. The instrument was operated during leg 4 but data has not been processed yet. Data were collected with one-second time resolution but integrated to five minutes to increase the signal to noise ratio. Concentrations are reported as molecules per cubic centimeter in five minutes averages. The lower limit of detection was estimated to be lower than 6E3 molecules cm<sup>-3</sup>. Data below the detection limit were replaced by the detection limit divided by the square root of 2.</p> <p>Pollution from the ship exhaust and other human activities (e.g. helicopter flights) was identified as described in Schmale et al. 2019 (<a href="https://doi.org/10.1175/BAMS-D-18-0187.1">https://doi.org/10.1175/BAMS-D-18-0187.1</a>) and a corresponding flag was associated to the data (with 1 meaning clean data and 2 polluted data). No direct influence of pollution on the iodic acid concentration was found.</p> <p>***** Dataset contents *****</p> <p>- 01_gas_iodic_acid_concentration_data.csv, data file, comma-separated values</p> <p>- 02_IodicAcid_file_header.txt, metadata, text format</p> <p>- 03_README.txt, metadata, text format</p> <p> </p>
Humic acid like concentration in seawater samples, collected from the trace metal rosettes in the Southern Ocean during the austral summer of 2016/2017, on board the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>Humic acid like concentration (abbreviated HA) measured with respect to the Suwannee River Fulvic acid standards (µmol SRFA equivalent per litre).</p> <p>Seawater samples were collected from trace metal rosette (TMR) deployments at different depths in the water column during the Antarctic Circumnavigation Expedition (ACE). Humic acid like data from legs 1 and 2, from TMR cast numbers 3 to 16, were analysed by electrochemistry following standard additions of Suwannee River Fulvic Acid (standard 1, IHSS). This data is to support iron ligands and iron bioavailability as well as hydrolysable saccharides (TPZT) data, also collected during ACE.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_humics_data.csv, data file, comma-separated values</li> <li>ace_humics_data_visual_summary.png, metadata, portable network graphics</li> <li>data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This humics dataset from ACE is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Data supporting the study "An organic crystalline state in ageing atmospheric aerosol proxies: spatially resolved structural changes in levitated fatty acid particles" by Milsom et al. (2021))
<p>Data supporting the figures and findings presented in the study <strong>"An organic crystalline state in ageing atmospheric aerosol proxies: spatially resolved structural changes in levitated fatty acid particles" by Milsom et al. (2021), <em>Atmos. Chem. Phys..</em></strong></p>
De Obaldia et al. Differential mosquito attraction to humans is associated with skin-derived carboxylic acid levels
<p>These supplementary files accompany the manuscript by De Obaldia et al. entitled "Differential mosquito attraction to humans is associated with skin-derived carboxylic acid levels." This includes all raw data in the paper, supplementary data, and instructions for the mosquito behavioral assays.</p> <p> </p> <p>On January 2, 2023 we added one new data file and a .readme to explain changes between the original pre-print and the published peer-reviewed version of the paper https://pubmed.ncbi.nlm.nih.gov/36261039/</p>
Adsorption free energies and potentials of mean-force for interactions between amino acids, lipid fragments, and nanoparticles
<p>This dataset contains tabulated potentials of mean force (PMFs) and associated adsorption (binding) free energies for interactions of amino acids side chain analogues and lipid fragments (LF) with a range of materials: titanium dioxide, iron oxide, amorphous silica, quartz, and a range of carbon-based materials including amorphous carbon, graphene and carbon nanotubes both in a pristine form and functionalized by certain chemical groups. All data were computed from atomistic molecular dynamics simulations as a part of the SmartNanoTox project 2016-2020. Version 2 of the dataset includes additional materials: zink oxide, zink sulfate in pristine and PMMA-coated forms computed within NanoSolveIt project (2019-2023). The data are intended to be used in coarse-grained models describing interactions of nanomaterials with nanoparticles, for the prediction of the binding affinity of proteins and lipids to nanoparticles, and as biological "fingerprints" of nanomaterials characterizing behavior of the nanomaterials in biological environments. </p>
Multiple biogeochemical variables were measured for organic and mineral soils on Arctic LTER experimental plots in moist acidic and non-acidic tundra, Arctic LTER Toolik Field Station, Alaska 2013.
Measures of soil nutrient content (available N and P, Extractable N and P, Total C, N and P), and microbial biomass and activity (exoenzyme activity) were measured for organic and mineral soils on Arctic LTER experimental plots at Toolik field station in moist acidic and non-acidic tundra (organic soils only).
Soil and canopy temperature data from the Arctic LTER Moist Acidic Tussock Experimental plots (MAT89) from 2012 to 2018, Toolik Field Station, North Slope, Alaska
Soil and canopy temperature data from the Arctic LTER 1989 Moist Acidic Tussock Experimental plots(MAT89). The station was established in 1990 in block 2 of a 4 block random block design. The plots are located on a hillside near Toolik Lake, Alaska (68 38' N, 149 36'W). Treatments include - control (CT), greenhouse (GH), greenhouse plus nitrogen and phosphorus (GHNP) shade (SH), shade plus nitrogen and phosphorus (SHNP) and nitrogen and phosphorus (NP). Profiles include above and within canopy, 10, 20 and 40 centimeter soil depths. Not all treatments have a complete profile. Meteorological data was also collected but are included in a separate data set.
Relative percent cover and leaf nutrients was measured for plant species on Arctic LTER experimental plots in moist acidic and non-acid tundra, Arctic LTER Toolik Field Station, Alaska 2015
Relative percent cover was measured for plant species on Arctic LTER experimental plots at Toolik field station in moist acidic and non-acidic tundra in greenhouse and control plots. Leaf percent carbon, percent nitrogen and percent phosphorus were collected from dominant species in greenhouse and control plots on Arctic LTER experimental plots at Toolik field station in moist acidic, non-acidic tundra, wet sedge and shrub tundra
Soil biogeochemical variables collected on the Arctic LTER experimental plots in moist acidic, moist non-acidic, wet shrub and shrub tundra, Arctic LTER Toolik Field Station, Alaska 2015
We investigated the effect of long-term warming on multiple soil and microbial carbon, nitrogen, and phosphorus pools, and microbial extracellular enzyme activities, with a particular focus on phosphorus, in Alaskan tundra plots underlain by permafrost
Tussock height and diameter in moist acidic tussock tundra at the site of the 2007 Anaktuvuk River fire scar, and nearby unburned tundra measured in 2016
This dataset consists of Eriophorum vaginatum tussock height and width (diameter) measurements, and was used to evaluate differences in physical strucutre of previously burned tundra (2007 Anaktuvuk River fire) and nearby unburned tundra. At each site, all tussocks that intersected four 100 meter transects were measured from soil surface to tussock top in four cardinal directions, and diameter was measured in two directions. These data were used to examine the impact of post-fire changes in plant community composition and structure on habitat suitability and rodent herbivore activity in response to a large, severe, and unprecedented fire in northern Alaska moist acidic tundra.
Tussock (Eriophorum vaginatum) density, mortality, and rodent-herbivore activity in moist acidic tussock tundra at the site of the 2007 Anaktuvuk River fire and nearby unburned tundra, measured in 2019
This dataset consists of tussock density, mortality rates and causes, and an assesment of rodent-herbivore activity levels in previously burned (2007 Anaktuvuk River fire) and unburned tussock tundra. Eriophourm vaginatum tussocks were counted every meter within a 1 square meter quadrat along three transects. Cause of tussock mortality, as well as level of rodent herbivory was assessed for each tussock, and rodent herbivore activity was assessed for each quadrat. The goal of the project was to examine the impact of post-fire changes in plant community composition and structure on habitat suitability and rodent herbivore activity in response to a large, severe, and unprecedented fire in northern Alaska moist acidic tundra.
Leaf area index (LAI) by plant functional group in moist acidic tussock tundra, at the 2007 Anaktuvuk River fire scar measured in 2017
This file contains leaf area index (LAI) based on biomass measurements from an aboveground pluck in the southern portion of the Anaktuvuk River fire scar, and a nearby unburned site in late July 2017. Vegetation was sampled randomly at 10-m intervals along two 100 meter transects at both the burned and unburned sites. Vegetation was sampled within a 10X40 cm quadrat to the mineral layer, and plant material was sorted into new and old aboveground leaf and woody biomass by species. All samples were dried and weighed, and subsampled leaf material was scanned to determine specific leaf area (centimeterSquaredPerGram biomass) per species, which was then used to transform leaf biomass (gramPerMeterSquared) into the leaf area index for each site.
Eriophorum tiller length in simulated herbivory experiment in moist acidic tundra experimental plots, Arctic LTER, Toolik Field Station, North Slope Alaska, from 2018 to 2021.
Tiller length of Eriophorum vaginatum subjected to fertilization and simulated herbivory from 2018 until 2021. Plants were part of a fertilization experiment begun in 2006 and included four levels of nutrient addition. For the simulated herbivory experiment, plants were not clipped, clipped once in 2018, or clipped every year of the experiment.
Biomass totals and root biomass (partitioned by percent of total leaf area) for species, tissue type, and functional group for the Arctic LTER experimental 1981 mesic acidic tussock tundra (MAT81) for the 2000 and 2015 harvests, Toolik Field Station, Alaska.
Whole plant biomass totals and root biomass (partitioned by percent of total leaf area) for species, tissue type, and functional group for the Arctic LTER experimental 1981 mesic acidic tussock tundra (MAT81) for the 2000 and 2015 harvests. Because most of the root biomass could not be identified to species in either 2000 or 2015, the calculation of root biomass and element content for roots not identified to species was estimated by the proportion of those species’ contributions to total leaf area. Specific Leaf Area (SLA = leaf area per gram leaf, centimeter squared per gram) values were available from several previous harvests of this experiment; in the present study, we used measurements from the 1995 harvest (Shaver et al. 2001).
Rapid root to leaf uptake of inorganic and amino acid nitrogen in three dryland plant species.
Our aim was to quantify inorganic and organic nitrogen (N) uptake and compare short-term nutrient acquisition patterns among three dryland plant species: Bouteloua eriopoda, Achnatherum hymenoides, and Gutierrezia sarothrae collected from a mixed grassland community in the Northern Chihuahuan Desert to better understand how asynchronous resource availability may influence biotic interactions and nutrient retention in these ecosystems. We collected living plants from two locations within the Sevilleta National Wildlife Refuge and transplanted them into pots maintained in the greenhouse with supplemental light and water for two months. We then conducted a greenhouse experiment using these species to compare nutrient uptake of 15N-labeled ammonium (NH4+), nitrate (NO3-), and glutamate (an amino acid) over 12 to 48 hours. Our study examined three main questions: (1) How rapidly do these dryland plants take up available soil N?, (2) Does leaf uptake differ among inorganic and amino acid N forms?, and (3) Do plant species differ in the speed or form of short-term N uptake?. In the greenhouse, we applied one of three isotopic 15N tracers directly to plant roots and quantified N uptake and recovery in leaves after 12, 24, and 48 hours. We found that plants took up inorganic and amino acid N to leaves as rapidly as 12 h following application, and N uptake more than doubled between 24 and 48 h. Inorganic N uptake was 3-4x higher than organic N uptake in all three species, and plants took up ammonium and nitrate at 2-3x faster rates than glutamate. On average, B. eriopoda had higher inorganic N recovery and uptake speeds, while G. sarothrae had the highest organic N uptake over time. A. hymenoides root to leaf uptake was ~50% lower than the other two species after 48 h. Plants showed similar patterns of short-term foliar uptake and recovery indicating a lack of niche partitioning by N form among the three dryland species measured. Our results suggest that soil inorganic N, par
Dataset - Characterization of Kazachstania humilis and Lactic Acid Bacteria interactions in French sourdoughs
<p>Here you can find the dataset and Rmarkdonw script associated to the scientific paper : Dataset - Characterization of Kazachstania humilis and Lactic Acid Bacteria interactions in French sourdoughs</p>
Supplementary data for the manuscript "Technical note: Estimating aqueous solubilities and activity coefficients of mono- and α,ω-dicarboxylic acids using COSMO-RS-DARE"
<p>.cosmo files (BP-TZVPD-FINE) of dicarboxylic acids (C2-C8), dimers and monohydrates of mono- (C1-C6) and dicarboxylic acids, and water dimer.</p>
Human TWIK-related Acid-Sensitive K+ Channel 1 (TASK1): A Target Enabling Package
<p>The TWIK related acid-sensitive K<sup>+</sup> channel 1 (<a href="https://www.ncbi.nlm.nih.gov/gene/3777">TASK-1</a>) belongs to the family of two-pore domain potassium (K<sub>2P</sub>) channels. It regulates resting membrane potential and is expressed in cardiomyocytes, neurons and vascular smooth muscle cells. Loss of function mutations in TASK-1 lead to primary pulmonary hypertension type 4 (PPH4) which is often fatal in mid-life (1). We have produced TASK-1 and determined structures of this protein alone and in complex with two highly potent inhibitors, BAY 1000493 and BAY 2341237, with EC<sub>50</sub> values of 9.5 nM and 7.6 nM, respectively. We have used a two-electrode voltage clamp assay to measure the effect of mutations in TASK-1 and the effect of inhibitors. The native structure of TASK-1 also allowed us to map the six known disease mutations leading to PPH4.</p>
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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.