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This dataset is a bibliographical database associated to the journal article "Twenty Years of Distributed Port-Hamiltonian Systems: A Literature Review" by R. Rashad, F. Califano, A.J. van der Schaft, and S. Stramigioli. In this article we review the research studies carried out in the past twenty years in the field of Distributed Port-Hamiltonian systems. The dataset includes the papers reviewed in this article, classified in their respective groups, which are over 150 studies. In addition, the dataset has an extra of 80 more studies that were not cited in the review paper, but are related to the field. All journal articles and the majority of the conference proceedings have their DOI included in the dataset. The main .bib file is named "Reference_List_Review". We hope this could guide new researchers in the field and accelerate the research and development of this powerful paradigm.
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Raw data of HIGD2A-BioID2 experiment. Total spectrum count for 3 independent experiments for HIGD2A-BioID2 and 3 independent experiments for the control BioID targeted to the mitochondria (MTS-BioID2).
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1H-NMR spectroscopy data from 24-hr urine samples from Diets 1 and 4, Dietary Metabotype Score (DMS), blood glucose measurement and urinary calorific value. Data contains quantified values for identified metabolites (in mmol/ml) of 24-hr urine samples for 19 volunteers for the two reference diets in Excel format. For each sample, the DMS, area-under-the-curve (AUC) glucose and calorific value (in J/g) are also given. This data accompanies Garcia-Perez et al. (2020) "Dietary metabotype modelling predicts individual responses to dietary interventions: A feasibility study" Nature Food (submitted, ref.: NATFOOD-19060125C)
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The Excel File and Mat File contain the raw and transformed data that we used in our paper 'Financial Wealth, Investment and Sentiment in a Bayesian DSGE Model'.
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Data and code files for manuscript submitted to the Journal of Theoretical Biology.
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  • Other
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Hardware design for build a Step Width System Capture
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  • Other
  • Software/Code
  • Geospatial Data
  • Image
  • Sequencing Data
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  • Document
  • Text
  • File Set
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Open data and R analysis scripts for the paper as submitted for publication: "Poppelaars, E. S., Klackl, J., Scheepers, DT, Mühlberger, C., & Jonas, E. (2019). Reflecting on existential threats elicits self-reported negative affect but no physiological arousal." A dataset of 171 undergraduate students were randomly allocated to one of four existential threat conditions: mortality salience, freedom restriction, uncontrollability, and uncertainty; or to the non-existential threat condition: social-evaluative threat; or to a control condition (TV salience). Three facets of arousal were measured: positive and negative affect before and after reflection, subjective arousal during baseline and reflection, and physiological activation during baseline and reflection (electrodermal, cardiovascular, and respiratory), as well as personality traits (e.g. trait avoidance and approach, self-esteem). Description of files: - File 'README.txt' contains the description of the files (metadata). - File '20191024_IJMData_brief.sav' contains the raw data. - Files 'EXI.outl.del.RData' contains the complete dataset with missing values, with extra variables calculated, and with outliers deleted. - File 'Codebook_EXI.outl.del.csv' contains a description of all variables in the 'EXI.outl.del.RData' file (metadata). - Files 'EXI.outl.del.imp.RData' and 'EXI.outl.del.imp.extra.RData' contain multiple imputed datasets (without missing values) that can be used to reproduce results from the paper. - File '01_CalculationOfData.R' is an R analysis script that imports the raw data, calculates new variables, and imputes missing data via multiple imputation using the 'predictorMatrixAdj.xlsx' file. - File '02_AnalysisOfImputedData.R' is an R analysis script that calculates descriptive statistics, creates plots, and tests hypotheses using t-tests, Bayesian statistics, and multiple lineair regressions. Also uses the custom functions: 'BF.evidence.R', 'cohen.d.magnitude.R' and 'p.value.sig.R'.
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COVID-19 reported cases and deaths through 3/31/2020 world wide, excluding China and South Korea
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Different human linker histone (H1) variants are expected to have distinct binding modes to the nucleosome. The position and orientation of a number of different H1 globular domains on the nucleosome were investigated through molecular docking using MGLTools and HADDOCK. The nucleosome core and linker DNA in the GH5-chromatosome structure (PDB: 4QLC) were used as a docking template. GH5 (in PDB: 4QLC) was re-docked to this template to test the docking algorithm. Docked and re-docked GH5 compared well. The docking algorithm was further tested by docking the NMR solution structure of the globular domain of chicken H1 (GH1, PDB: 1GHC) to the nucleosome template. The position of docked GH1 on the nucleosome agreed with literature. 
The N-terminal - and globular domain H1x hybrid (NGH1x) was studied using solution NMR in both low (20 mM sodium phosphate, pH 7.0) and high (20 mM sodium phosphate, 1 M sodium perchlorate, pH 7.0) ionic strength conditions (de Wit, H., Vallet, A., Brutscher, B. et al. Biomol NMR Assign (2019) 13: 249. https://doi.org/10.1007/s12104-019-09886-x). These low and high ionic strength structures were docked to the nucleosome template. 
Homology (MODELLER) and ab initio modeling (CS-ROSETTA) were employed to model structures for other human H1 globular domains: GH1.0, GH1.4, GH1oo, and GH1t. The modeled structures were also docked to the nucleosome template.
 All the docking procedures listed above produced 100 models of different energies. In each case, the lowest energy docked model was chosen. The structures of all the H1 globular domains that were docked to the template are given as PDB files (1GHC_lowest_energy.pdb; 2LSO_lowest_energy.pdb; GH5_re-docked_position.pdb; NGH1x_high_salt_NTD.pdb; NGH1x_low_salt_NTD.pdb; modeled_GH1_0_lowest_energy.pdb; modeled_GH1_4_lowest_energy.pdb; modeled_GH1oo_lowest_energy.pdb; modelled_GH1t_lowest_energy.pdb) in the data file. The nucleosome template structure is also given in PDB file format (4QLC_nucleosome_without_GH5.pdb). Finally, the docked models are also given (GH5-chromatosome.pdb; 1GHC-chromatosome.pdb; 2LSO-chromatosome.pdb; GH1_0-chromatosome.pdb; GH1_4-chromatosome.pdb; GH1oo-chromatosome.pdb; GH1t-chromatosome.pdb; NGH1x_no_salt-chromatosome.pdb; NGH1x_salt-chromatosome.pdb). The files are compatible with most molecular graphics software. The file Dockings_modelling_test_and_results.pdf provides the modeling and docking results in figures and tables. A short description of each figure and table is given within the PDF file.
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  • Sequencing Data
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Even though partisan cues are widely recognized as a primary force shaping voter behavior in a referendum, their effect on a decision whether to attend or abstain from voting has not yet been carefully studied. Our analysis of the pre-referendum survey data gathered before the 2015 citizen-initiated referendum in Slovakia leads to two important conclusions: First, parties’ recommendations whether to attend or abstain from voting influence voters’ behavior in a similar fashion as their suggestions for which side to vote for. Moreover, in certain institutional settings, the partisan cues related to mobilization have an even stronger impact on voters than endorsements for who or what to vote for. Second, the provided party recommendations must be unambiguous and clear. Lower clarity cues are reflected in voters’ behavior to a lesser extent. Note: Data is originally collected by the FOCUS Agency (in Slovakia) on demand of the Daily SME. All the essential information could be found in the .xlsx file.
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  • Software/Code
  • Tabular Data
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