cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.4643797
title: calculated rovib spectral data for cis and trans HOCO at 296 K - J Phys Chem A Paper The Rovibrational Spectra of trans- and cis- HOCO, Calculated by MULTIMODE with ab initio Potential Energy and Dipole Moment Surfaces Stuart Carter, Yimin Wang and Joel M. Bowman∗

description: The Rovibrational Spectra of trans- and cis- HOCO, Calculated by MULTIMODE with ab initio Potential Energy and Dipole Moment Surfaces Stuart Carter, Yimin Wang and Joel M. Bowman∗ Supporting Information Description The two files ‘trans296’ and cis296” are all spectral line intensities, as described in the paper, for trans and cis-HOCO, respectively at 296 K as a function of increasing transition energy, as shown in Figures 1 and 2 of the paper. Each record in the files has a header with labels J" (N1,N2,N3,N4,N5,N6)" Ka" Kc" S E" J' (N1,N2,N3,N4,N5,N6)' Ka' Kc' E' E'-E" R^2(AU) R^2(DEBYE^2) S(1/ATM/CM2) S(CM/MOLE) (P,Q,R?) followed by the corresponding data. Each record is separated by ************************************************** All quantities denoted with “ are for the initial state and those denoted with ‘ are for the final state. All energies, E” or E’ are in cm<sup>-1</sup>. J K<sub>a</sub> K<sub>c</sub> are standard rotation quantum numbers, N1, etc. are labels for vibrational states corresponding to the normal modes in order of increasing energy, WITH THE EXCEPTION OF N6. This is a label for the delocalized torsion mode. Here is the convention. N6 = 0 is the ground torsion state of trans, N6=1 is the first excited torsion state of trans then for trans the sequence continues at N6=3, 5, 7, 9 etc for the first overtone, second overtone etc of trans. N6=2 denotes the ground torsion state of cis. (This is what is shown below). Then N6=4,6,8, 10… denote excited cis torsions. At some value of N6 we start to see delocalized states. (See Wang, Y.; Carter, S.; Bowman, J. M. Variational Calculations Of Vibrational Energies and IR Spectra of trans- and cis-HOCO Using New ab initio Potential Energy and Dipole Moment Surfaces. J. Phys. Chem. A 2013, 117, 9343–9352. for a discussion of these.) All data refer to the ground vibrational of cis or trans-HOCO for a range of J from 0 to 9 inclusive. Note the quantum assignments (N1,N2,N3,N4,N5,N6)' for final states is just a rough guide. In the example below 0 0 0 0 0 2 represents the ground vibrational state of cis-HOCO S is a symmetry label which here is always 1 and so can be basically ignored. The third line is the transition energy, E’-E”, R^2 and S in two sets of units. These are directly from eq. (1) of the paper, E” corresponds to E<sub>r</sub> and E’-E” to <i>n</i><sub>i</sub> of that equation. Finally a label for the type of rotational branch is given. *************************************************************** 1 0 0 0 0 0 2 0 1 1 552.4591791570921 1 0 0 0 0 0 2 1 0 556.8613154782342 4.402136321142166 0.3578071515953164 2.311301415783682 0.151578443037134 6.1136425631820724E-021 Q
DOI: 10.6084/m9.figshare.4643854
title: dmLT_Fig. 3. Recovery of dmLT after incubation at pH 3–7

description: Double mutant heat labile (dmLT) adjuvant is being proposed for oral vaccine formulation. Given the loss of dmLT observed with the HCl and simulated gastric fluid in Table 2 this experiment was conducted to determine the pH stability of dmLT. This work was conducted in two separate experiments. In the first experiment dmLT was diluted in pH buffers ranging from pH 3-7 and incubated at 4˚C and 37˚C. Samples were taken at the specified time points, neutralized and measured by ELISA. After determining dmLT was stable between the pH range of 4-5 a second experiment was conducted to look at finer pH intervals between 4 and 5. Again dmLT was diluted in pH buffers (4, 4.2, 4.4, 4.6, 4.8, 5), incubated at 4˚C and 37˚C. Samples were taken at the appropriate time points, neutralized and measured by dmLT ELISA.
DOI: 10.6084/m9.figshare.4643797.v1
title: calculated rovib spectral data for cis and trans HOCO at 296 K - J Phys Chem A Paper The Rovibrational Spectra of trans- and cis- HOCO, Calculated by MULTIMODE with ab initio Potential Energy and Dipole Moment Surfaces Stuart Carter, Yimin Wang and Joel M. Bowman∗

description: The Rovibrational Spectra of trans- and cis- HOCO, Calculated by MULTIMODE with ab initio Potential Energy and Dipole Moment Surfaces Stuart Carter, Yimin Wang and Joel M. Bowman∗ Supporting Information Description The two files ‘trans296’ and cis296” are all spectral line intensities, as described in the paper, for trans and cis-HOCO, respectively at 296 K as a function of increasing transition energy, as shown in Figures 1 and 2 of the paper. Each record in the files has a header with labels J" (N1,N2,N3,N4,N5,N6)" Ka" Kc" S E" J' (N1,N2,N3,N4,N5,N6)' Ka' Kc' E' E'-E" R^2(AU) R^2(DEBYE^2) S(1/ATM/CM2) S(CM/MOLE) (P,Q,R?) followed by the corresponding data. Each record is separated by ************************************************** All quantities denoted with “ are for the initial state and those denoted with ‘ are for the final state. All energies, E” or E’ are in cm<sup>-1</sup>. J K<sub>a</sub> K<sub>c</sub> are standard rotation quantum numbers, N1, etc. are labels for vibrational states corresponding to the normal modes in order of increasing energy, WITH THE EXCEPTION OF N6. This is a label for the delocalized torsion mode. Here is the convention. N6 = 0 is the ground torsion state of trans, N6=1 is the first excited torsion state of trans then for trans the sequence continues at N6=3, 5, 7, 9 etc for the first overtone, second overtone etc of trans. N6=2 denotes the ground torsion state of cis. (This is what is shown below). Then N6=4,6,8, 10… denote excited cis torsions. At some value of N6 we start to see delocalized states. (See Wang, Y.; Carter, S.; Bowman, J. M. Variational Calculations Of Vibrational Energies and IR Spectra of trans- and cis-HOCO Using New ab initio Potential Energy and Dipole Moment Surfaces. J. Phys. Chem. A 2013, 117, 9343–9352. for a discussion of these.) All data refer to the ground vibrational of cis or trans-HOCO for a range of J from 0 to 9 inclusive. Note the quantum assignments (N1,N2,N3,N4,N5,N6)' for final states is just a rough guide. In the example below 0 0 0 0 0 2 represents the ground vibrational state of cis-HOCO S is a symmetry label which here is always 1 and so can be basically ignored. The third line is the transition energy, E’-E”, R^2 and S in two sets of units. These are directly from eq. (1) of the paper, E” corresponds to E<sub>r</sub> and E’-E” to <i>n</i><sub>i</sub> of that equation. Finally a label for the type of rotational branch is given. *************************************************************** 1 0 0 0 0 0 2 0 1 1 552.4591791570921 1 0 0 0 0 0 2 1 0 556.8613154782342 4.402136321142166 0.3578071515953164 2.311301415783682 0.151578443037134 6.1136425631820724E-021 Q
DOI: 10.6084/m9.figshare.4641229
title: base cronicas gasto variables.zip

description: Dataset (.dta format for Stata) with health expenditures and identification of households with individuals with diabetes and/or hypertension, as well as relevant variables for the analysys in the paper Mexico´s Household Health Expenditures on Diabetes and Hypertension: What is the Additional Financial Burden? These data extract the relevant variables from the set of datasets from the Mexican National Health & Nutrition Survey 2012 (ENSANUT 2012).
DOI: 10.6084/m9.figshare.4641229.v1
title: base cronicas gasto variables.zip

description: Dataset (.dta format for Stata) with health expenditures and identification of households with individuals with diabetes and/or hypertension, as well as relevant variables for the analysys in the paper Mexico´s Household Health Expenditures on Diabetes and Hypertension: What is the Additional Financial Burden? These data extract the relevant variables from the set of datasets from the Mexican National Health & Nutrition Survey 2012 (ENSANUT 2012).
DOI: 10.6084/m9.figshare.4643641.v1
title: Survey of biologist's computational needs

description: Figures and survey data from forthcoming pre-print: In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principle investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work—including high performance computing (HPC), bioinformatics support, multi-step workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the U.S. and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC – acknowledging that data science skills will be required to build a deeper understanding of life.
DOI: 10.6084/m9.figshare.4643641.v3
title: Survey of biologist's computational needs

description: Figures and survey data from forthcoming pre-print: In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principle investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work—including high performance computing (HPC), bioinformatics support, multi-step workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the U.S. and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC – acknowledging that data science skills will be required to build a deeper understanding of life.
DOI: 10.6084/m9.figshare.4641157
title: Discrete Approximation of a Mixture Distribution via Restricted Divergence

description: Mixture distributions arise in many application areas, for example, as marginal distributions or convolutions of distributions. We present a method of constructing an easily tractable discrete mixture distribution as an approximation to a mixture distribution with a large to infinite number, discrete or continuous, of components. The proposed DIRECT (divergence restricting conditional tesselation) algorithm is set up such that a prespecified precision, defined in terms of Kullback–Leibler divergence between true distribution and approximation, is guaranteed. Application of the algorithm is demonstrated in two examples. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.4641157.v2
title: Discrete Approximation of a Mixture Distribution via Restricted Divergence

description: Mixture distributions arise in many application areas, for example, as marginal distributions or convolutions of distributions. We present a method of constructing an easily tractable discrete mixture distribution as an approximation to a mixture distribution with a large to infinite number, discrete or continuous, of components. The proposed DIRECT (divergence restricting conditional tesselation) algorithm is set up such that a prespecified precision, defined in terms of Kullback–Leibler divergence between true distribution and approximation, is guaranteed. Application of the algorithm is demonstrated in two examples. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.4641073
title: Salt marsh grazing meta-analysis: dataset

description: Underlying dataset for the manuscript:<b>Livestock grazing alters multiple ecosystem properties and services in salt marshes: a meta-analysis. </b><br>by Davidson, K.E., Fowler, M.S., Skov, M.W., Doerr, S., Beaumont, N. & Griffin, J.N. Accepted for publication in <i>Journal of Applied Ecology </i>(2017).
DOI: 10.6084/m9.figshare.4641157.v1
title: Discrete approximation of a mixture distribution via restricted divergence

description: Mixture distributions arise in many application areas, for example as marginal distributions or convolutions of distributions. We present a method of constructing an easily tractable discrete mixture distribution as an approximation to a mixture distribution with a large to infinite number, discrete or continuous, of components. The proposed direct (Divergence Restricting Conditional Tesselation) algorithm is set up such that a pre-specified precision, defined in terms of Kullback-Leibler divergence between true distribution and approximation, is guaranteed. Application of the algorithm is demonstrated in two examples.
DOI: 10.6084/m9.figshare.4641037
title: Experiment Data

description: This is the data repository for our manuscript in European Journal of Neuroscience. As this is our first attempt to share experiment data with others there could be some mistakes. Please feel free to contact me to improve this data repository if you are interested. <br>The full data set used in the study, including the multi unit activity (MUA), the single unit activity (SUA), the excitatory post synaptic currents (EPSC) and inhibitory post synaptic currents (IPSC). <br>for Bayesian Adaptive Regression Splines (BARS), please visit http://www.stat.cmu.edu/~kass/bars/bars.html <br>for Matlab based scripts to find local peaks and vally, please visit https://www.mathworks.com/matlabcentral/fileexchange/25500-peakfinder-x0--sel--thresh--extrema--includeendpoints--interpolate-<br>
DOI: 10.6084/m9.figshare.4641019
title: Gnutella_IP.zip

description: In the OSU data set, we obtained the IP addresses of the Gnutella peers used in the following reference.<br>Ren S, Guo L, Zhang X. ASAP: an AS-Aware Peer-Relay Protocol for High Quality VoIP with Low Overhead. In: IEEE ICDCS. Lisboa, Portugal; 2006. p.70-79.
DOI: 10.6084/m9.figshare.4641019.v1
title: Gnutella_IP.zip

description: In the OSU data set, we obtained the IP addresses of the Gnutella peers used in the following reference.<br>Ren S, Guo L, Zhang X. ASAP: an AS-Aware Peer-Relay Protocol for High Quality VoIP with Low Overhead. In: IEEE ICDCS. Lisboa, Portugal; 2006. p.70-79.
DOI: 10.6084/m9.figshare.4641037.v1
title: Experiment Data

description: This is the data repository for our manuscript in European Journal of Neuroscience. As this is our first attempt to share experiment data with others there could be some mistakes. Please feel free to contact me to improve this data repository if you are interested. <br>The full data set used in the study, including the multi unit activity (MUA), the single unit activity (SUA), the excitatory post synaptic currents (EPSC) and inhibitory post synaptic currents (IPSC). <br>for Bayesian Adaptive Regression Splines (BARS), please visit http://www.stat.cmu.edu/~kass/bars/bars.html <br>for Matlab based scripts to find local peaks and vally, please visit https://www.mathworks.com/matlabcentral/fileexchange/25500-peakfinder-x0--sel--thresh--extrema--includeendpoints--interpolate-<br>
DOI: 10.6084/m9.figshare.4641001
title: default_2014Apr15-100445_STM-STM_Spectroscopy--33_1.Z_flat

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DOI: 10.6084/m9.figshare.4641004
title: default_2014Apr15-100445_STM-STM_Spectroscopy--34_1.Z_flat

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DOI: 10.6084/m9.figshare.4640998
title: default_2014Apr15-100445_STM-STM_Spectroscopy--32_1.Z_flat

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DOI: 10.6084/m9.figshare.4641001.v1
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DOI: 10.6084/m9.figshare.4641004.v1
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DOI: 10.6084/m9.figshare.4640992
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DOI: 10.6084/m9.figshare.4640995
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DOI: 10.6084/m9.figshare.4640992.v1
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DOI: 10.6084/m9.figshare.4640998.v1
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DOI: 10.6084/m9.figshare.4640986
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DOI: 10.6084/m9.figshare.4640989
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DOI: 10.6084/m9.figshare.4640995.v1
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DOI: 10.6084/m9.figshare.4640980
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DOI: 10.6084/m9.figshare.4640983
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DOI: 10.6084/m9.figshare.4640986.v1
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DOI: 10.6084/m9.figshare.4640980.v1
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DOI: 10.6084/m9.figshare.4640989.v1
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DOI: 10.6084/m9.figshare.4640974
title: default_2014Mar05-122906_STM-STM_Spectroscopy--10_4.I(V)_flat

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DOI: 10.6084/m9.figshare.4640977
title: default_2014Mar05-122906_STM-STM_Spectroscopy--10_5.I(V)_flat

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DOI: 10.6084/m9.figshare.4640983.v1
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DOI: 10.6084/m9.figshare.4640968
title: default_2014Mar05-122906_STM-STM_Spectroscopy--10_2.I(V)_flat

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DOI: 10.6084/m9.figshare.4640971
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DOI: 10.6084/m9.figshare.4640974.v1
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DOI: 10.6084/m9.figshare.4640971.v1
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DOI: 10.6084/m9.figshare.4640977.v1
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DOI: 10.6084/m9.figshare.4640962
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DOI: 10.6084/m9.figshare.4640968.v1
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DOI: 10.6084/m9.figshare.4640959
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DOI: 10.6084/m9.figshare.4640965
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DOI: 10.6084/m9.figshare.4640956
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DOI: 10.6084/m9.figshare.4640959.v1
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DOI: 10.6084/m9.figshare.4640953
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DOI: 10.6084/m9.figshare.4640965.v1
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DOI: 10.6084/m9.figshare.4640953.v1
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DOI: 10.6084/m9.figshare.4640944
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DOI: 10.6084/m9.figshare.4640947
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DOI: 10.6084/m9.figshare.4640950
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DOI: 10.6084/m9.figshare.4640956.v1
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DOI: 10.6084/m9.figshare.4640941
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DOI: 10.6084/m9.figshare.4640944.v1
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DOI: 10.6084/m9.figshare.4640935
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DOI: 10.6084/m9.figshare.4640938
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DOI: 10.6084/m9.figshare.4640932
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DOI: 10.6084/m9.figshare.4640929
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DOI: 10.6084/m9.figshare.4640926
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DOI: 10.6084/m9.figshare.4640923
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DOI: 10.6084/m9.figshare.4640920
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