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33 results for “density of states”
Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter: Neutron star equation of state posterior samples
<p>Equation of state posterior samples associated with Legred et al., "Impact of the PSR J0740+6620 radius constraint on the properties of high-density matter," Phys. Rev. D 104, 063003 (2021); doi:10.1103/PhysRevD.104.063003</p> <p> </p> <p>Three sets of 1e4 samples from the posterior distribution over equations of state are provided. These sets are drawn from the posterior conditioned on different combinations of radio pulsar observations, gravitational wave data, and NICER x-ray measurements. The data release contains the equation of state table and the corresponding table of neutron star observables for each sample. The posterior distributions one can generate from these samples approximate those plotted in Figs. 1-6 of the accompanying paper.</p> <p> </p> <p>Refer to the readme for usage information.</p>
Buoyancy and Brownian motion of plastics in aqueous media: Predictions and implications for density separation and aerosol internal mixing state (Data Underlying Figures)
<p>Data underlying figures in A. Bain 'Buoyancy and Brownian motion of plastics in aqueous media: Predictions and implications for density separation and aerosol internal mixing state' RSC Environmental Science: Nano, 2022. </p> <p>CA = citric acid<br> NaCl = sodium chloride<br> AS = ammonium sulfate</p> <p>rho = difference in density (g/cm^3)<br> Rh = % relative humidity<br> radius is in micrometers<br> Pe0 are the calculated dimensionless Peclet numbers<br> </p>
Resting-State High-Density EEG using EGI GES 300 with 256 Channels of Healthy Elders, People with Subjective and Mild Cognitive Impairment and Alzheimer's Disease
<p>This repository contains Matlab files including 4 samples of resting-state EEG recording for Alzheimer's Disease (AD), Mild Cognitive Impairment (MCI), Subjective Cognitive Decline (SCD), and Healthy Controls (HC) using the HD-EEG EGI GES 300.</p> <p><strong>[AD: i108, MCI: i100, SCD: i090, HC: s055]</strong></p> <p> </p> <p><strong>Participants & Settings</strong></p> <p>In total 230 participants have been recruited from the memory and dementia clinic of the Greek Association of Alzheimer’s Disease and Related Disorders (GAADRD) and the 1st Department of Neurology, U.H. AHEPA, Aristotle University of Thessaloniki, Greece.</p> <p>The full dataset includes:</p> <p><strong>Healthy Controls Elders (60+ years old)</strong>: 33 participants</p> <p><strong>Subjective Cognitive Decline:</strong> 34 participants</p> <p><strong>Mild Cognitive Impairment</strong>: 79 participants</p> <p><strong>Alzheimer's Disease</strong>: 48 participants</p> <p><strong>Healthy Young (25-40 years old):</strong> 36 participants</p> <p>The study was carried out in accordance with the Declaration of Helsinki and received approval by the Scientific and Ethics Committee of GAADRD (No56_27/11/2016), and written informed consent was obtained from all participants prior to their participation in the study. The diagnosis of AD was conducted by a neuropsychiatrist according to their medical history, neuropsychological performance, structural magnetic resonance imaging (MRI), and clinical and neurological examinations.</p> <p>Participants with AD fulfilled the National Institute of Neurological and Communication Disorders and Stroke/Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) criteria for probable AD, as well as the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) criteria for dementia of Alzheimer’s type (American Psychological Association, 1994). On the other hand, the MCI participants fulfilled the Petersen criteria, while the SCD group met International Working Group-2 guidelines and the recent National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease (NI-AA), as well as the SCD-I Working Group instructions. </p> <p><strong>Resting-State EEG Recording</strong></p> <p>Fifteen-minute resting EEG activity was recorded for all the participants. For the whole duration of the resting state EEG recording, participants were advised to keep themselves relaxed as much as possible, close their eyes and open them after the researcher’s demand, sit still, minimize blinking or mouth movements and let their mind wander. The experimental procedure was monitored by a research assistant aiming to identify cases of horizontal eye movements, continued blinking, or excessive movement by visually inspecting the EEG traces during the experiment. More specifically, an EEG was registered for both resting conditions (eyes open, EO and eyes closed, EC) for at least 2–3 min for each period.</p> <p><strong>EEG Data Acquisition</strong></p> <p>The EEG data were collected by using the EGI 300 Geodesic EEG system (GES 300, CERTH-ITI, Thessaloniki, Greece) with a 256-channel HydroCel Geodesic Sensor Net (HCGSN) and a sampling rate of 250 Hz (EGI Eugene, OR). Moreover, the researcher placed the electrodes in accordance with the 256 HCGSN adult 1.0 montage system, while the signals were recorded relative to a vertex reference electrode (Cz), with AFz as the ground electrode with the electrodes’ impedance below 50 kΩ throughout the experimental procedure, as recommended for the high-input impedance amplifier. In detail, the HD-EEG data were analyzed offline in order to detect any artifact, as well as to conduct pre-processing (filtering, segmentation, bad channel replacement) using Net Station 4.3 software (EGI). HD-EEG data were initially filtered with a 5th-order bandpass Butterworth IIR filter of 0.3–30 Hz. Once the segmentation was completed, the detection of artifacts was performed by using the Net Station artifact detection tool for the automatic detection of excessive eye blinking and movement. Afterward, the signals were baseline corrected using 200 msec before the start of the experiment period and average re-referenced to transform them into reference-independent values.</p> <p> </p> <p><strong>Full Dataset Access</strong></p> <p>More information about the sample dataset and access to the full dataset can be available after request via e-mail:</p> <p><strong>Ioulietta Lazarou</strong> BSc, MSc, PhD candidate</p> <p>Neuropsychologist - Clinical Research Associate </p> <p>Centre for Research and Technology Hellas (CERTH), Information Technologies Institute (ITI)</p> <p>6th km Charilaou-Thermi Road, P.O. Box 60361, 57001 Thermi-Thessaloniki, Greece</p> <p>E-mail: <a href="mailto:iouliettalaz@iti.gr">iouliettalaz@iti.gr</a></p>
Dataset package for the Manuscript "Absence of bulk charge density wave order in the normal state of UTe2"
<p>The attached dataset contains raw data, normalized to the respective attenuater, reported in the manusript: </p> <p>"Absence of bulk charge density wave order in the normal state of UTe2".</p> <p>The files "Figure4a.dat", "Figure4b.dat", and "Figure4c.dat" contain data that were presented in Figure 4a, Figure4b, and Figure4c of the manuscript. The first columns contain the x-axis values, the second columns the intensities, and the third column the errorbars.</p> <p>The files "Figure3_N.dat" present the data in Figure 3 c. Here, N labels the (K,L)-coordinates. These are orivuded in "Figure3_KL.dat", where for a number N the N-th row presents the K and L values in the first and second column, respectively.</p> <p>The files "Fig2a.dat" and "Fig2b.dat" contain the datapoints presented in Figure 2a and Figure 2b, where the first column corresponds to the x-axis coordinate and the second column to the recorded intensity.</p>
Dataset from "Power Spectral Density-Based Resting-State EEG Classification of First-Episode Psychosis"
<p>Denoised and Preprocessed data from <em>EEG: First Episode Psychosis vs. Control Resting Task 1</em> as described in <em>Power Spectral Density-Based Resting-State EEG Classification of First-Episode Psychosis.</em></p> <p>Original dataset: <a href="https://doi.org/10.18112/openneuro.ds003944.v1.0.1">doi:10.18112/openneuro.ds003944.v1.0.1</a></p>
Density of states and Crystal Orbital Hamilton Population Analysis of CO adsorbed on Co
<p>This dataset pertains to an extensive study of the electronic structure of CO adsorbed on various active site topologies on cobalt. The following cobalt active site configurations were explored:</p> <ul> <li>Co(0001) (fcc)</li> <li>Co(0001) (hcp)</li> <li>Co(11-21) 3f</li> <li>Co(11-21) B5</li> <li>Co(100)</li> <li>Co(110)</li> <li>Co55/Al2O3 (top)</li> <li>Co55/Al2O3 (interfacial site)</li> <li>Co52/Al2O3 (defect site)</li> <li>Co84/Al2O3 (nanorod)</li> <li>Co54/TiO2 (cluster)</li> <li>Co81/TiO2 (nanorod)</li> </ul> <p>For each adsorption site, a density of states and crystal orbital hamilton population analysis was performed by means of the <a href="http://www.cohp.de/">Lobster</a> program. The original electronic structure calculations are performed using <a href="https://www.vasp.at/">VASP</a>. The input and output files for all calculations as well as the Python scripts how these files were parsed are found in this repository.</p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh outward facing state (OFS) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh outward facing state (OFS) conformation at apo condition, imaged from the cytoplasmic side, in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state closed (IFSclosed) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state closed (IFSclosed) conformation at apo condition, imaged from the cytoplasmic side, in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open (IFSopen) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open (IFSopen) conformation at apo condition, imaged from the cytoplasmic side , in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open, kinetically locked, (IFSopen-1) conformation at apo condition, imaged from the cytoplasmic side
<p>3D localization AFM (3D-LAFM) density map of glutamate transporter GltPh inward facing state open, kinetically locked, (IFSopen-1) conformation at apo condition, imaged from the cytoplasmic side , in <code>.afm</code> format and in <code>.mrc</code> format.</p> <p>Note: The <code>.afm</code> file encodes details for constructing 3D-LAFM density maps and includes experimental conditions in its header. Using <code>.afm</code> files requires the additional installation of the AFM file encoder (available from <a href="https://github.com/rafaeljiang23/3D-LAFM/tree/main/ChimeraX-AfmFormat_v2">GitHub</a>). Once the relevant installation is complete, <code>.afm</code> files can be opened in ChimeraX via drag-and-drop. In contrast, <code>.mrc</code> files, which encode only the density values equivalent to <code>.afm</code> files, can be directly opened in ChimeraX without requiring additional software installation.</p> <p>The deposited <code>.afm</code> file follows the 'AFM1' (metacode) format standard.</p>
Data for 'Normalization procedure for obtaining the local density of states from high-bias scanning tunneling spectroscopy'
<p>This folder contains all the raw data needed to generate the figures in the paper '<em>Normalization procedure for obtaining the local density of states from high-bias scanning tunneling spectroscopy.</em>' The data are seperated by the figures in which they appear, with a text folder in each folder that contains any relevant additional information. </p>
Dominant controls on coastal saline groundwater across North America: groundwater head and density interface at the stable state
<p>Resulting datasets described and evaluated in "Dominant controls on coastal saline groundwater across North America". </p> <p>The CSV's data is organized in columns.</p> <p>They contain the columns "spatID", "lat", "lon" and "head 492" / "zeta1 492", respectively. </p> <p>The columns "spatID" may be used to merge the two datasets.</p>
First-order phase transitions in Yang-Mills theories and the density of state method---data and analysis code release
<p>Data release for paper: Lucini, B., Mason, D., Piai, M., Rinaldi, E., & Vadacchino, D. (2023). First-order phase transitions in Yang-Mills theories and the density of state method. arXiv preprint arXiv:2305.07463.</p> <p>This data release comprises of:</p> <p>Importance sampling results: Input and output files for PureGauge file of HiRep (https://github.com/claudiopica/HiRep) and csv files contains analysis of results.</p> <p>LLR results: Input files for LLR_HB for a modified version of HiRep for the heat bath LLR algorthim with umbrella sampling (https://github.com/dave452/Hirep-LLR-SU) and some csv files containing analysis of output.</p> <p>Analysis code within the LLRAnalysis.zip, it contains the code and the conda environment.</p>
Dataset for the manuscript 'Orbital-optimized Density Functional Calculations of Molecular Rydberg Excited States with Real Space Grid Representation and Self-Interaction Correction'
<p>Dataset for the manuscript 'Orbital-optimized Density Functional Calculations of Molecular Rydberg Excited States with Real Space Grid Representation and Self-Interaction Correction'</p>
Distribution. Brazilian Amazon, S of the Rio Amazonas, between the Tapajos/Juruena system and the Tocantins/Araguaia river system to the E, in the Brazilian states of Para and Mato Grosso; the exact S limit ofits distribution is unclear, but it seems likely that it coincides with the transition between the Amazon rainforest and the cerrado savannas of C Brazil; this ecotone encompasses headwaters of the Xingu and Tapajos river systems in N Mato Grosso. Vieira's Titi (C. vieirai) is also known to occur in this region, but there are too few records to confirm whether their distributions intergrade, or in fact where the exact limits of their distributions are. One recent study also found that the Red-bellied Titi may be absent from or present at extremely low densities in large areas of the Tocantins-Xingu interfluvium. Given the overall lack of records, while it is clear that the Red-bellied Titi occurs over a vast area of the SE Amazon Basin, the exact limits of its distribution within this area remain unclear. in Phitheciidae
Distribution. Brazilian Amazon, S of the Rio Amazonas, between the Tapajos/Juruena system and the Tocantins/Araguaia river system to the E, in the Brazilian states of Para and Mato Grosso; the exact S limit ofits distribution is unclear, but it seems likely that it coincides with the transition between the Amazon rainforest and the cerrado savannas of C Brazil; this ecotone encompasses headwaters of the Xingu and Tapajos river systems in N Mato Grosso. Vieira's Titi (C. vieirai) is also known to occur in this region, but there are too few records to confirm whether their distributions intergrade, or in fact where the exact limits of their distributions are. One recent study also found that the Red-bellied Titi may be absent from or present at extremely low densities in large areas of the Tocantins-Xingu interfluvium. Given the overall lack of records, while it is clear that the Red-bellied Titi occurs over a vast area of the SE Amazon Basin, the exact limits of its distribution within this area remain unclear.
Data derived state probabilities for Z. noltei monitoring study. Observed variables were shoot density at four sites in this study
<p>1. In general, it is not feasible to collect enough empirical data to capture the entire range of processes that define a complex system, either intrinsically or when viewing the system from a different geographical or temporal perspective. In this context, an alternative approach is to consider model transferability, which is the act of translating a model built for one environment to another less well-known situation. Model transferability and adaptability may be extremely beneficial - approaches that aid in the reuse and adaption of models, particularly for sites with limited data, would benefit from widespread model uptake. Besides the reduced effort required to develop a model, data collection can be simplified when transferring a model to a different application context.</p> <p>2. The research presented in this paper focused on a case study to identify and implement guidelines for model adaptation. Our study adapted a general Dynamic Bayesian Networks (DBN) of a seagrass ecosystem to a new location where nodes were similar, but the conditional probability tables varied. We focused on two species of seagrass (Zostera noltei and Zostera marina) located in Arcachon Bay, France. Expert knowledge was used to complement peer-reviewed literature to identify which components needed adjustment including parameterisation and quantification of the model, and desired outcomes. We adopted both linguistic labels and scenario-based elicitation to elicit from experts the conditional probabilities used to quantify the DBN.</p> <p>3. Following the proposed guidelines, the model structure of the general DBN was retained, but the conditional probability tables were adapted for nodes that characterised the growth dynamics in Zostera spp. population located in Arcachon Bay, as well as the seasonal variation on their reproduction. Particular attention was paid to the light variable as it is a crucial driver of growth and physiology for seagrasses.</p> <p>4. Our guidelines provide a way to adapt a general DBN to specific ecosystems to maximise model reuse and minimise re-development effort. Especially important from a transferability perspective are guidelines for ecosystems with limited data, and how simulation and prior predictive approaches can be used in these contexts.</p>
Dataset for: "Spectrally Resolving the Phase and Amplitude of Coherent Phonons in the Charge Density Wave State of 1T-TaSe2"
Open the record for dataset details and reuse information.
FIGURE 5 in Using an Asteraceae checklist to understand collection history, species density and conservation implications: a case study in the state of Alagoas, Northeastern Brazil
FIGURE 5. Continental Protected Areas in the state of Alagoas. 1. Natural Monument of the São Francisco. 2. Wildlife Refuge of Morros do Craunã and Padre. 3. Ecological Station Curral do Meio. 4. Ecological Park Pedra do Sino. 5. Biological Reserve Pedra Talhada. 6. Environmental Protection Area Marituba do Peixe. 7. Environmental Protection Area of Piaçabuçu. 8. Extractive Reserve Jequiá. 9. Ecological Mangrove Reserve of Lagoa do Roteiro. 10. Ecological Reserve Saco da Pedra. 11. Environmental Protection Area of Santa Rita. 12. Environmental Protection Area of Catolé e Fernão Velho. 13. Municipal Park of Maceió. 14. Environmental Protection Area Patangy. 15. Environmental Protection Area of Murici. 16. Ecological Station of Murici. *RPPN
FIGURE 3 in Using an Asteraceae checklist to understand collection history, species density and conservation implications: a case study in the state of Alagoas, Northeastern Brazil
FIGURE 3. Results of the species richness (a) and collection density (b) analyses, and correlation between these two variables (c).
Getting to an Improved Understanding of Low-Density Lipoprotein Cholesterol and Dyslipidemia Management (GOULD) a Registry of High Cardiovascular Risk Subjects in the United States
ClinicalTrials.gov study NCT02993120. IPD Sharing: YES. Countries: 1. Publications: 8.
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