cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5576164
title: American Alcohol Photo Stimuli (AAPS): A standardized set of alcohol and matched non-alcohol images

description: <i>Background</i>: Photographic stimuli are commonly used to assess cue reactivity in the research and treatment of alcohol use disorder. The stimuli used are often non-standardized, not properly validated, and poorly controlled. There are no previously published, validated, American-relevant sets of alcohol images created in a standardized fashion. <i>Objectives</i>: We aimed to: 1) make available a standardized, matched set of photographic alcohol and non-alcohol beverage stimuli, 2) establish face validity, the extent to which the stimuli are subjectively viewed as what they are purported to be, and 3) establish construct validity, the degree to which a test measures what it claims to be measuring. <i>Methods</i>: We produced a standardized set of 36 images consisting of American alcohol and non-alcohol beverages matched for basic color, form, and complexity. A total of 178 participants (95 male, 82 female, 1 genderqueer) rated each image for appetitiveness. An arrow-probe task, in which matched pairs were categorized after being presented for 200 ms, assessed face validity. Criteria for construct validity were met if variation in AUDIT scores were associated with variation in performance on tasks during alcohol image presentation. <i>Results</i>: Overall, images were categorized with &gt;90% accuracy. Participants’ AUDIT scores correlated significantly with alcohol “want” and “like” ratings [<i>r</i>(176) = 0.27, <i>p</i> = &lt;0.001; <i>r</i>(176) = 0.36, <i>p</i> = &lt;0.001] and arrow-probe latency [<i>r</i>(176) = −0.22, <i>p</i> = 0.004], but not with non-alcohol outcomes. Furthermore, appetitive ratings and arrow-probe latency for alcohol, but not non-alcohol, differed significantly for heavy versus light drinkers. <i>Conclusion</i>: Our image set provides valid and reliable alcohol stimuli for both explicit and implicit tests of cue reactivity. The use of standardized, validated, reliable image sets may improve consistency across research and treatment paradigms.
DOI: 10.6084/m9.figshare.5576164.v1
title: American Alcohol Photo Stimuli (AAPS): A standardized set of alcohol and matched non-alcohol images

description: <i>Background</i>: Photographic stimuli are commonly used to assess cue reactivity in the research and treatment of alcohol use disorder. The stimuli used are often non-standardized, not properly validated, and poorly controlled. There are no previously published, validated, American-relevant sets of alcohol images created in a standardized fashion. <i>Objectives</i>: We aimed to: 1) make available a standardized, matched set of photographic alcohol and non-alcohol beverage stimuli, 2) establish face validity, the extent to which the stimuli are subjectively viewed as what they are purported to be, and 3) establish construct validity, the degree to which a test measures what it claims to be measuring. <i>Methods</i>: We produced a standardized set of 36 images consisting of American alcohol and non-alcohol beverages matched for basic color, form, and complexity. A total of 178 participants (95 male, 82 female, 1 genderqueer) rated each image for appetitiveness. An arrow-probe task, in which matched pairs were categorized after being presented for 200 ms, assessed face validity. Criteria for construct validity were met if variation in AUDIT scores were associated with variation in performance on tasks during alcohol image presentation. <i>Results</i>: Overall, images were categorized with &gt;90% accuracy. Participants’ AUDIT scores correlated significantly with alcohol “want” and “like” ratings [<i>r</i>(176) = 0.27, <i>p</i> = &lt;0.001; <i>r</i>(176) = 0.36, <i>p</i> = &lt;0.001] and arrow-probe latency [<i>r</i>(176) = −0.22, <i>p</i> = 0.004], but not with non-alcohol outcomes. Furthermore, appetitive ratings and arrow-probe latency for alcohol, but not non-alcohol, differed significantly for heavy versus light drinkers. <i>Conclusion</i>: Our image set provides valid and reliable alcohol stimuli for both explicit and implicit tests of cue reactivity. The use of standardized, validated, reliable image sets may improve consistency across research and treatment paradigms.
DOI: 10.22023/mdx.5573854
title: Coastal Vulnerability Indicator Library

description: The Resilience-Increasing Strategies for Coasts – Toolkit (RISC-KIT) FP7 EU project (2013-2017) aims to produce a set of three innovative and EU-coherent open-source and open-access methods, tools and management approaches (the RISC-KIT) in support of coastal managers, decision-makers and policy makers to reduce risk and increase resilience to low-frequency, high impact hydro-meteorological events. Risk is defined within this project as the product of the probability of a hazard, the exposure of receptors and their vulnerability. Representing the vulnerability and the potential role of DRR in their reduction is crucial for supporting the decision. As such a specific task of the RISC-KIT project (Task 2.2) is dedicated to developing a Library of Vulnerability Indicators to input in the RISC-KIT Toolkit and to test the tools on 11 case studies. The deliverable “Coastal Vulnerability Indicator Library” is composed of a Microsoft Excel database and a guidance document. The deliverable introduces the necessary concepts and methods, provides a review and a collection of existing indicators and proposes methodologies for developing new indicators. The Library has been constructed around four categories: Built Environment, Population, Ecosystem and Systems. The Library also identifies Disaster Reduction Measures influencing vulnerability and proposes methods to include within the assessment of vulnerability.
DOI: 10.6084/m9.figshare.5573560
title: Species pool distributions along functional trade-offs shape plant productivity–diversity relationships

description: Data and scripts needed to re-do the analysis of the article : "Species pool distributions along functional trade-offs shape plant productivity–diversity relationships"<br>
DOI: 10.6084/m9.figshare.5573647.v1
title: Template to provide grant data

description: Template to provide grant data to Europe PMC, notes on second sheet.
DOI: 10.6084/m9.figshare.5573560.v1
title: Species pool distributions along functional trade-offs shape plant productivity–diversity relationships

description: Data and scripts needed to re-do the analysis of the article : "Species pool distributions along functional trade-offs shape plant productivity–diversity relationships"<br>
DOI: 10.6084/m9.figshare.5573542
title: FRET Simulation Dataset

description: Datafiles contain over 3 million simulated noisy FRET spectra which can be used for validating FRET analysis approaches. The same data is formatted for both matlab and python. The matlab file can be read in with each of the components as a separate variable. The python numpy array can be read in and then converted to a dictionary containing each component using numpy.load(‘YourFilepath’).item().<br>Matlab Variable/Python Dictionary Entry:<br> ’Simulated Pixels’: These are simulated noisy spectra covering a range of SNR and FRET efficiencies, organized in the following manner: Simulated_Pixels[N,Power,Efficiency,Excitation,Emission], where N are repeat simulations to calculate statistics with (1000 simulations for every condition). Has an overall shape of (1000, 150, 11, 2, 32). ’sRET luxFRET Calibration Spectra’: These are noiseless calibration spectra organized in the following manner: sRET luxFRET Calibration Spectra[Power,Donor or Acceptor,Excitation,Emission], with an overall shape of (150, 2, 2, 32). These spectra can also be used to calculate the normalized emission spectra and gamma parameter needed for sensorFRET, but we also included those values separately for convenience. ’Power Vector’: The vector relating the indices in the 2nd dimension of ‘Simulated Pixels’ to the simulated power used ranging from 0.1-1000 (arbitrary units) in 150 logarithmic steps to change the SNR and provide normalized residuals in the approximate range of 0.001 to 0.1. ’Efficiency Vector’: The vector relating the indices in the 3rd dimension of ‘Simulated Pixels’ to the simulated FRET efficiency ranging from 0 to 1 in 11 linear steps. ’Excitation Wavelength Vector’: The vector relating the indices of the 4th dimension of ‘Simulated Pixels’ to the simulated Excitation wavelength, either 405 or 458. ’Emission Wavelength Vector’: The vector relating the indices of the 5th dimension of ‘Simulated Pixels’ to the simulated Emission Wavelengths, ranging from 416 to 718 in 32 linear steps to match the spectral resolution of our experiments. ’Normalized Emission Spectra’:An array containing the normalized emission shapes for the Cerulean and Venus fluorophores (shape of (2, 32)). ’Gamma’: the sensorFRET gamma parameter for the Cerulean/Venus-405/458 pairing, 0.0605 (from experiment) ’Qd’: the quantum efficiency of Cerulean, 0.62.<br> ’Qa’: the quantum efficiency of Venus, 0.57.
DOI: 10.6084/m9.figshare.5573509
title: Tensor-on-Tensor Regression

description: I propose a framework for the linear prediction of a multiway array (i.e., a tensor) from another multiway array of arbitrary dimension, using the contracted tensor product. This framework generalizes several existing approaches, including methods to predict a scalar outcome from a tensor, a matrix from a matrix, or a tensor from a scalar. I describe an approach that exploits the multiway structure of both the predictors and the outcomes by restricting the coefficients to have reduced PARAFAC/CANDECOMP rank. I propose a general and efficient algorithm for penalized least-squares estimation, which allows for a ridge (<i>L</i><sub>2</sub>) penalty on the coefficients. The objective is shown to give the mode of a Bayesian posterior, which motivates a Gibbs sampling algorithm for inference. I illustrate the approach with an application to facial image data. An R package is available at <i>https://github.com/lockEF/MultiwayRegression</i>.
DOI: 10.6084/m9.figshare.5573506
title: Confidence Intervals for Conditional Tail Risk Measures in ARMA–GARCH Models

description: ARMA–GARCH models are widely used to model the conditional mean and conditional variance dynamics of returns on risky assets. Empirical results suggest heavy-tailed innovations with positive extreme value index for these models. Hence, one may use extreme value theory to estimate extreme quantiles of residuals. Using weak convergence of the weighted sequential tail empirical process of the residuals, we derive the limiting distribution of extreme conditional Value-at-Risk (CVaR) and conditional expected shortfall (CES) estimates for a wide range of extreme value index estimators. To construct confidence intervals, we propose to use self-normalization. This leads to improved coverage vis-à-vis the normal approximation, while delivering slightly wider confidence intervals. A data-driven choice of the number of upper order statistics in the estimation is suggested and shown to work well in simulations. An application to stock index returns documents the improvements of CVaR and CES forecasts.
DOI: 10.6084/m9.figshare.5573506.v2
title: Confidence Intervals for Conditional Tail Risk Measures in ARMA–GARCH Models

description: ARMA–GARCH models are widely used to model the conditional mean and conditional variance dynamics of returns on risky assets. Empirical results suggest heavy-tailed innovations with positive extreme value index for these models. Hence, one may use extreme value theory to estimate extreme quantiles of residuals. Using weak convergence of the weighted sequential tail empirical process of the residuals, we derive the limiting distribution of extreme conditional Value-at-Risk (CVaR) and conditional expected shortfall (CES) estimates for a wide range of extreme value index estimators. To construct confidence intervals, we propose to use self-normalization. This leads to improved coverage vis-à-vis the normal approximation, while delivering slightly wider confidence intervals. A data-driven choice of the number of upper order statistics in the estimation is suggested and shown to work well in simulations. An application to stock index returns documents the improvements of CVaR and CES forecasts.
DOI: 10.6084/m9.figshare.5573509.v2
title: Tensor-on-Tensor Regression

description: I propose a framework for the linear prediction of a multiway array (i.e., a tensor) from another multiway array of arbitrary dimension, using the contracted tensor product. This framework generalizes several existing approaches, including methods to predict a scalar outcome from a tensor, a matrix from a matrix, or a tensor from a scalar. I describe an approach that exploits the multiway structure of both the predictors and the outcomes by restricting the coefficients to have reduced PARAFAC/CANDECOMP rank. I propose a general and efficient algorithm for penalized least-squares estimation, which allows for a ridge (<i>L</i><sub>2</sub>) penalty on the coefficients. The objective is shown to give the mode of a Bayesian posterior, which motivates a Gibbs sampling algorithm for inference. I illustrate the approach with an application to facial image data. An R package is available at <i>https://github.com/lockEF/MultiwayRegression</i>.
DOI: 10.6084/m9.figshare.5573506.v1
title: Confidence Intervals for Conditional Tail Risk Measures in ARMA-GARCH Models

description: ARMA-GARCH models are widely used to model the conditional mean and conditional variance dynamics of returns on risky assets. Empirical results suggest heavy-tailed innovations with positive extreme value index for these models. Hence, one may use extreme value theory to estimate extreme quantiles of residuals. Using weak convergence of the weighted sequential tail empirical process of the residuals, we derive the limiting distribution of extreme conditional Value-at-Risk (CVaR) and conditional Expected Shortfall (CES) estimates for a wide range of extreme value index estimators. To construct confidence intervals we propose to use self-normalization. This leads to improved coverage vis-à-vis the normal approximation, while delivering slightly wider confidence intervals. A data-driven choice of the number of upper order statistics in the estimation is suggested and shown to work well in simulations. An application to stock index returns documents the improvements of CVaR and CES forecasts.
DOI: 10.6084/m9.figshare.5573509.v1
title: Tensor-on-tensor regression

description: We propose a framework for the linear prediction of a multi-way array (i.e., a tensor) from another multi-way array of arbitrary dimension, using the contracted tensor product. This framework generalizes several existing approaches, including methods to predict a scalar outcome from a tensor, a matrix from a matrix, or a tensor from a scalar. We describe an approach that exploits the multiway structure of both the predictors and the outcomes by restricting the coefficients to have reduced CP-rank. We propose a general and efficient algorithm for penalized least-squares estimation, which allows for a ridge (<i>L</i><sub>2</sub>) penalty on the coefficients. The objective is shown to give the mode of a Bayesian posterior, which motivates a Gibbs sampling algorithm for inference. We illustrate the approach with an application to facial image data. An R package is available at https://github.com/lockEF/MultiwayRegression.
DOI: 10.6084/m9.figshare.5573284
title: Error-Calibrated ABC

description: This repository includes all of the code and results described in the following paper:<br>van der Vaart, E., Prangle, D. & Sibly, R.M. "Taking Error Into Account When Fitting Models with Approximate Bayesian Computation" (2018) Ecological Applications
DOI: 10.6084/m9.figshare.5573296
title: GRHL2

description: GRHL2 ChIP-Seq data
DOI: 10.6084/m9.figshare.5573284.v1
title: Error-Calibrated ABC

description: This repository includes all of the code and results described in the following paper:<br>van der Vaart, E., Prangle, D. & Sibly, R.M. "Taking Error Into Account When Fitting Models with Approximate Bayesian Computation" (2018) Ecological Applications
DOI: 10.6084/m9.figshare.5573224
title: Supplementary Material for: Lymphocyte Cell Ratios and Mortality among Incident Hemodialysis Patients

description: <b><i>Background:</i></b> Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been previously suggested as oncologic prognostication markers. These are associated with malnutrition and inflammation, and hence, may provide benefit in predicting mortality among hemodialysis patients. <b><i>Methods:</i></b> Among 108,548 incident hemodialysis patients in a large U.S. dialysis organization (2007–2011), we compared the mortality predictability of NLR and PLR with baseline and time-varying covariate Cox models using the receiver operating characteristic curve (AUROC), net reclassification index (NRI), and adjusted R<sup>2</sup>. <b><i>Results:</i></b> During the median follow-up period of 1.4 years, 28,618 patients died. Median (IQR) NLR and PLR at baseline were 3.64 (2.68–5.00) and 179 (136–248) respectively. NLR was associated with higher mortality, which appeared stronger in the time-varying versus baseline model. PLR exhibited a J-shaped association with mortality in both models. NLR provided better mortality prediction in addition to demographics, comorbidities, and serum albumin; ΔAUROC and NRI for 1-year mortality (95% CI) were 0.010 (0.009–0.012) and 6.4% (5.5–7.3%) respectively. Additionally, adjusted R<sup>2</sup> (95% CI) for the Cox model increased from 0.269 (0.262–0.276) to 0.283 (0.276–0.290) in the non-time-varying model and from 0.467 (0.461–0.472) to 0.505 (0.500–0.512) in the time-varying model. There was little to no benefit of adding PLR to predict mortality. <b><i>Conclusions:</i></b> High NLR in incident hemodialysis patients predicted mortality, especially in the short-term period. NLR, but not PLR, added modest benefit in predicting mortality along with demographics, comorbidities, and serum albumin, and should be included in prognostication approaches.
DOI: 10.6084/m9.figshare.5573224.v1
title: Supplementary Material for: Lymphocyte Cell Ratios and Mortality among Incident Hemodialysis Patients

description: <b><i>Background:</i></b> Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been previously suggested as oncologic prognostication markers. These are associated with malnutrition and inflammation, and hence, may provide benefit in predicting mortality among hemodialysis patients. <b><i>Methods:</i></b> Among 108,548 incident hemodialysis patients in a large U.S. dialysis organization (2007–2011), we compared the mortality predictability of NLR and PLR with baseline and time-varying covariate Cox models using the receiver operating characteristic curve (AUROC), net reclassification index (NRI), and adjusted R<sup>2</sup>. <b><i>Results:</i></b> During the median follow-up period of 1.4 years, 28,618 patients died. Median (IQR) NLR and PLR at baseline were 3.64 (2.68–5.00) and 179 (136–248) respectively. NLR was associated with higher mortality, which appeared stronger in the time-varying versus baseline model. PLR exhibited a J-shaped association with mortality in both models. NLR provided better mortality prediction in addition to demographics, comorbidities, and serum albumin; ΔAUROC and NRI for 1-year mortality (95% CI) were 0.010 (0.009–0.012) and 6.4% (5.5–7.3%) respectively. Additionally, adjusted R<sup>2</sup> (95% CI) for the Cox model increased from 0.269 (0.262–0.276) to 0.283 (0.276–0.290) in the non-time-varying model and from 0.467 (0.461–0.472) to 0.505 (0.500–0.512) in the time-varying model. There was little to no benefit of adding PLR to predict mortality. <b><i>Conclusions:</i></b> High NLR in incident hemodialysis patients predicted mortality, especially in the short-term period. NLR, but not PLR, added modest benefit in predicting mortality along with demographics, comorbidities, and serum albumin, and should be included in prognostication approaches.
DOI: 10.6084/m9.figshare.5573296.v2
title: GRHL2

description: GRHL2 ChIP-Seq data
DOI: 10.6084/m9.figshare.5573101
title: python script to demo pyphot

description: python script to demo pyphot
DOI: 10.6084/m9.figshare.5573095
title: jupyter notebook to demo pyphot

description: jupyter notebook to demo pyphot
DOI: 10.6084/m9.figshare.5573098
title: Oystercatcher foraging data

description: This .csv file contains data on successful foraging of limpets by Eurasian Oystercatchers. Attack time and handling time are given, along with limpet length estimated as a proportion of an average bill length (75mm) and this is then converted. Where the foraging occurred is also recorded. For details of the methods please contact the authors. The paper has just been submitted.
DOI: 10.6084/m9.figshare.5573092
title: Limpet measurements

description: This .csv file contains data on limpet dimensions, position, cover and head orientation. For full details on the methods please contact the authors. The paper has just been submitted for review.
DOI: 10.6084/m9.figshare.5573098.v1
title: Oystercatcher foraging data

description: This .csv file contains data on successful foraging of limpets by Eurasian Oystercatchers. Attack time and handling time are given, along with limpet length estimated as a proportion of an average bill length (75mm) and this is then converted. Where the foraging occurred is also recorded. For details of the methods please contact the authors. The paper has just been submitted.
DOI: 10.6084/m9.figshare.5573101.v2
title: python script to demo pyphot

description: python script to demo pyphot
DOI: 10.6084/m9.figshare.5573092.v1
title: Limpet measurements

description: This .csv file contains data on limpet dimensions, position, cover and head orientation. For full details on the methods please contact the authors. The paper has just been submitted for review.
DOI: 10.6084/m9.figshare.5573089
title: ISO-SWS spectrum for IRC+10216

description: ISO-SWS spectrum of IRC+10216
DOI: 10.6084/m9.figshare.5573089.v1
title: ISO-SWS spectrum for IRC+10216

description: ISO-SWS spectrum of IRC+10216
DOI: 10.6084/m9.figshare.5573095.v1
title: jupyter notebook to demo pyphot

description: jupyter notebook to demo pyphot
DOI: 10.6084/m9.figshare.5573029
title: Dataset for: NANDROLONE-INDUCED NUCLEAR ACCUMULATION OF MYOD PROTEIN IS MEDIATED BY NUMB, A NOTCH INHIBITOR, IN C2C12 MYOBLASTS

description: Signaling via the androgen receptor (AR) stimulates myogenic progenitor differentiation. In addition, myogenic differentiation factor D (MyoD) and Numb, a Notch inhibitor, play key roles in regulating myogenic differentiation. Nandrolone, an anabolic steroid, upregulates both MyoD and Numb expression in myogenic cells. However, the molecular mechanisms by which MyoD is upregulated by nandrolone are unclear. Moreover, the potential crosstalk between nandrolone, MyoD, and Numb is not well understood. With these considerations in mind, we examined the effects of nandrolone on the expression of MyoD mRNA and protein, and determined the interactions of MyoD and Numb in the presence or absence of nandrolone in differentiating C2C12 myoblasts. Nandrolone increased MyoD mRNA and protein expression and significantly enhanced nuclear translocation of MyoD protein. The later effect of nandrolone was blunted by siRNA against Numb. Immunoprecipitation studies confirmed that Numb forms complexes with MyoD. Chromatin immunoprecipitation revealed that in the presence of nandrolone, Numb is recruited to a region of the MyH7 promotor containing the E-box to which MyoD binds. These data indicate that nandrolone-regulated MyoD activation occurs mainly through a posttranslational mechanism which promotes MyoD nuclear accumulation, and suggest that this effect of nandrolone is, at least in part, mediated by Numb.