cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5457442.v5
title: Datasets and R.code: "Sickness behaviors in vampire bats (Desmodus rotundus)"

description: Fileset contains datasets as well as R. code supporting "sickness behavior reduces allogrooming in vampire bats". R- code "dyadic_social_grooming_analysis" contains simple model of how sickness induced changes in allogrooming given to other individuals, could affect disease transmission.<br>Detailed description of individual datasets:<br>(1) "physiology_data" and R-code "physiology_analysis"group = Group the individual was housed in (1-7)experiment = Week, experiment 1 = week 1, experiment 2 = week 2individual = injected individualtreatment = treatment (LPS or PBS)bm.postmpre = bodymass post injection minus bodymass pre-injection (grams)WBC.postmpre = white blood cell concentration (cells/ml) post-injection minus pre-injectionNL.postmpre = NL ratio post-injection minus NL ratio pre-injection<br>(2) "individual_behaviors_means" and R-code "individual_behavior_analysis"focal.bat: focal bat of behavior scoring after injectiontreatment: treatment (LPS or PBS)activity: mean activity rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2sleep.rate: mean sleep rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2grooming.rate: mean self-grooming rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2ml.rate: mean mouthlicking rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2socgroom.rate: mean social grooming rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2moving.rate: mean moving rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2group: group the focal bat was housed in (from 1-7)groupsize: groupsize of the group the focal bat was housed in (2 or 4)<br>(3) "dyadic_social_grooming_dataset" and R-code "dyadic.social.grooming.analysis"focal.bat: focal bat of observationpartner: partner bat the focal bat was interacting withpair: description of two interacting bats as a pairgroup: group the focal bat was housed in (groups 1-7)groupsize: groupsize of the group the focal bat was housed in (2 or 4)day.in.exp: Day on the experimental timeline (see figure S1)week: Week in the experiment (week 1 or 2)duration.rec: duration in seconds the focal bat received grooming from partnerduration.act: duration in seconds the focal bat gave grooming to partnerhours.rec: hours recorded (always 2 h except for nights 5 and 13 due to technical problems)dir.dyad: unique description of a pair of two bats. Directional dyad, e.g focal bat is A and partner is B so directional dyad is B-&gt;Atreatment: treatment during the experimental week 1 or 2injection: injection = "no" for baseline nights and "yes" for nights when the focal bat was injected with either LPS or PBS
DOI: 10.6084/m9.figshare.5457412.v2
title: A Bayesian Phase I/II Trial Design for Immunotherapy

description: Immunotherapy is an innovative treatment approach that stimulates a patient’s immune system to fight cancer. It demonstrates characteristics distinct from conventional chemotherapy and stands to revolutionize cancer treatment. We propose a Bayesian phase I/II dose-finding design that incorporates the unique features of immunotherapy by simultaneously considering three outcomes: immune response, toxicity, and efficacy. The objective is to identify the biologically optimal dose, defined as the dose with the highest desirability in the risk–benefit tradeoff. An Emax model is utilized to describe the marginal distribution of the immune response. Conditional on the immune response, we jointly model toxicity and efficacy using a latent variable approach. Using the accumulating data, we adaptively randomize patients to experimental doses based on the continuously updated model estimates. A simulation study shows that our proposed design has good operating characteristics in terms of selecting the target dose and allocating patients to the target dose. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
DOI: 10.6084/m9.figshare.5457442.v4
title: Datasets and R.code: "Sickness behaviors in vampire bats (Desmodus rotundus)"

description: Fileset contains datasets as well as R. code supporting "sickness behavior reduces allogrooming in vampire bats". R- code "dyadic_social_grooming_analysis" contains simple model of how sickness induced changes in allogrooming given to other individuals, could affect disease transmission.<br>Detailed description of individual datasets:<br>(1) "physiology_data" and R-code "physiology_analysis"group = Group the individual was housed in (1-7)experiment = Week, experiment 1 = week 1, experiment 2 = week 2individual = injected individualtreatment = treatment (LPS or PBS)bm.postmpre = bodymass post injection minus bodymass pre-injection (grams)WBC.postmpre = white blood cell concentration (cells/ml) post-injection minus pre-injectionNL.postmpre = NL ratio post-injection minus NL ratio pre-injection<br>(2) "individual_behaviors_means" and R-code "individual_behavior_analysis"focal.bat: focal bat of behavior scoring after injectiontreatment: treatment (LPS or PBS)activity: mean activity rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2sleep.rate: mean sleep rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2grooming.rate: mean self-grooming rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2ml.rate: mean mouthlicking rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2socgroom.rate: mean social grooming rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2moving.rate: mean moving rate of 2 hours observation ((counts hour 1 / onscreen counts) + (counts hour 2 / onscreen counts)) / 2group: group the focal bat was housed in (from 1-7)groupsize: groupsize of the group the focal bat was housed in (2 or 4)<br>(3) "dyadic_social_grooming_dataset" and R-code "dyadic.social.grooming.analysis"focal.bat: focal bat of observationpartner: partner bat the focal bat was interacting withpair: description of two interacting bats as a pairgroup: group the focal bat was housed in (groups 1-7)groupsize: groupsize of the group the focal bat was housed in (2 or 4)day.in.exp: Day on the experimental timeline (see figure S1)week: Week in the experiment (week 1 or 2)duration.rec: duration in seconds the focal bat received grooming from partnerduration.act: duration in seconds the focal bat gave grooming to partnerhours.rec: hours recorded (always 2 h except for nights 5 and 13 due to technical problems)dir.dyad: unique description of a pair of two bats. Directional dyad, e.g focal bat is A and partner is B so directional dyad is B-&gt;Atreatment: treatment during the experimental week 1 or 2injection: injection = "no" for baseline nights and "yes" for nights when the focal bat was injected with either LPS or PBS
DOI: 10.6084/m9.figshare.5457412.v1
title: A Bayesian Phase I/II Trial Design for Immunotherapy

description: Immunotherapy is an innovative treatment approach that stimulates a patient's immune system to fight cancer. It demonstrates characteristics distinct from conventional chemotherapy and stands to revolutionize cancer treatment. We propose a Bayesian phase I/II dose-finding design that incorporates the unique features of immunotherapy by simultaneously considering three outcomes: immune response, toxicity and efficacy. The objective is to identify the biologically optimal dose, defined as the dose with the highest desirability in the risk-benefit tradeoff. An Emax model is utilized to describe the marginal distribution of the immune response. Conditional on the immune response, we jointly model toxicity and efficacy using a latent variable approach. Using the accumulating data, we adaptively randomize patients to experimental doses based on the continuously updated model estimates. A simulation study shows that our proposed design has good operating characteristics in terms of selecting the target dose and allocating patients to the target dose.
DOI: 10.6084/m9.figshare.5457409.v2
title: Sparsity Oriented Importance Learning for High-Dimensional Linear Regression

description: With now well-recognized nonnegligible model selection uncertainty, data analysts should no longer be satisfied with the output of a single final model from a model selection process, regardless of its sophistication. To improve reliability and reproducibility in model choice, one constructive approach is to make good use of a sound variable importance measure. Although interesting importance measures are available and increasingly used in data analysis, little theoretical justification has been done. In this article, we propose a new variable importance measure, sparsity oriented importance learning (SOIL), for high-dimensional regression from a sparse linear modeling perspective by taking into account the variable selection uncertainty via the use of a sensible model weighting. The SOIL method is theoretically shown to have the inclusion/exclusion property: When the model weights are properly around the true model, the SOIL importance can well separate the variables in the true model from the rest. In particular, even if the signal is weak, SOIL rarely gives variables not in the true model significantly higher important values than those in the true model. Extensive simulations in several illustrative settings and real-data examples with guided simulations show desirable properties of the SOIL importance in contrast to other importance measures. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.5457400
title: Placebo Response as a Latent Characteristic: Application to Analysis of Sequential Parallel Comparison Design Studies

description: In clinical trials, placebo response can affect the inference about efficacy of the studied treatment. It is important to have a robust way to classify trial subjects with respect to their response to placebo. Simple, criterion-based classification may lead to classification error and bias the inference. The uncertainty about placebo response characteristic has to be factored into the treatment effect estimation. We propose a novel approach that views the placebo response as a latent characteristic and the study sample as an unlabeled mixture of “placebo responders” and “placebo nonresponders.” The likelihood-based methodology is used to estimate the treatment effect corrected for placebo response as defined within sequential parallel comparison design.
DOI: 10.6084/m9.figshare.5457409.v1
title: Sparsity Oriented Importance Learning for High-dimensional Linear Regression

description: With now well-recognized non-negligible model selection uncertainty, data analysts should no longer be satisfied with the output of a single final model from a model selection process, regardless of its sophistication. To improve reliability and reproducibility in model choice, one constructive approach is to make good use of a sound variable importance measure. Although interesting importance measures are available and increasingly used in data analysis, little theoretical justification has been done. In this paper, we propose a new variable importance measure, <b>s</b>parsity <b>o</b>riented <b>i</b>mportance <b>l</b>earning (SOIL), for high-dimensional regression from a sparse linear modeling perspective by taking into account the variable selection uncertainty via the use of a sensible model weighting. The SOIL method is theoretically shown to have the inclusion/exclusion property: When the model weights are properly around the true model, the SOIL importance can well separate the variables in the true model from the rest. In particular, even if the signal is weak, SOIL rarely gives variables not in the true model significantly higher important values than those in the true model. Extensive simulations in several illustrative settings and real data examples with guided simulations show desirable properties of the SOIL importance in contrast to other importance measures.
DOI: 10.6084/m9.figshare.5457400.v1
title: Placebo Response as a Latent Characteristic: Application to Analysis of Sequential Parallel Comparison Design Studies

description: In clinical trials, placebo response can affect the inference about efficacy of the studied treatment. It is important to have a robust way to classify trial subjects with respect to their response to placebo. Simple, criterion-based classification may lead to classification error and bias the inference. The uncertainty about placebo response characteristic has to be factored into the treatment effect estimation. We propose a novel approach that views the placebo response as a latent characteristic and the study sample as an unlabeled mixture of “placebo responders” and “placebo nonresponders.” The likelihood-based methodology is used to estimate the treatment effect corrected for placebo response as defined within sequential parallel comparison design.
DOI: 10.6084/m9.figshare.5457346
title: Earth Analytics R Course Data: SOAP Lidar Remote Sensing Uncertainty data | Earth Lab CU Boulder

description: The new "week 04" data contains this subset. This repo is thus deprecated however it's going to stay live until the live R course is updated accordingly! <br><br>OLD: Data set to use for the homework assignment for week 05 of the earth analytics course. This is a fileset as next year i may include the week 4 data used in this week - in this dataset rather than in week 4. <br>
DOI: 10.6084/m9.figshare.5457292
title: HPC_Ala.zip

description: The climate to drive a hydrological model<br>
DOI: 10.6084/m9.figshare.5457292.v1
title: HPC_Ala.zip

description: The climate to drive a hydrological model<br>
DOI: 10.6084/m9.figshare.5457346.v1
title: earth analytics course lidar uncertainty data

description: Data set to use for the homework assignment for week 05 of the earth analytics course. This is a fileset as next year i may include the week 4 data used in this week - in this dataset rather than in week 4. <br>
DOI: 10.6084/m9.figshare.5457268.v2
title: Coding valence in touchscreen interactions: Hand dominance and lateral movement influence valence appraisals of emotional pictures

description: The Body-Specificity Hypothesis postulates that the space surrounding the dominant hand is perceived as positive due to the motor fluency of this hand, whereas the space surrounding the non-dominant hand is perceived as negative. Experimental studies based on this theoretical framework also revealed associations between affective valence and hand dominance (i.e., dominant hand—positive; non-dominant hand—negative), or lateral movements of the hands (i.e., right hand toward the right space—positive; left hand toward the left space—positive). Interestingly, these associations have not been examined with regard to how lateral actions of the hands may influence affective experiences as, for example, in valence appraisals of affective objects that have been manipulated. The study presented here has considered this question in light of the emerging interest of embodied cognition approaches to interactive technologies, particularly in affective experiences with touchscreen interfaces. Accordingly, right-handed participants evaluated the valence of positive and negative emotional pictures after interacting with them either with the dominant right or with the non-dominant left hand. Specifically, they moved the pictures either from left to right or from right to left sides of a touchscreen monitor. The results indicated that a valence matching between the hand used for the interactions, the picture’s valence category, and the movement’s starting side reinforced the valence appraisals of the pictures (i.e., positive/negative pictures were more positively/negatively evaluated). The findings are discussed against the background of the Theory of Event Coding, which accounts for both the affective properties of the stimuli and the affective connotation of the related action.
DOI: 10.6084/m9.figshare.5457346.v3
title: Earth Analytics Course Data: SOAP Lidar Remote Sensing Uncertainty data | Earth Lab CU Boulder

description: The new "week 04" data contains this subset. This repo is thus deprecated however it's going to stay live until the live R course is updated accordingly! <br><br>OLD: Data set to use for the homework assignment for week 05 of the earth analytics course. This is a fileset as next year i may include the week 4 data used in this week - in this dataset rather than in week 4. <br>
DOI: 10.6084/m9.figshare.5457346.v2
title: Earth Analytics Teaching Dataset: Lidar Remote Sensing Uncertainty data | Earth Lab CU Boulder

description: Data set to use for the homework assignment for week 05 of the earth analytics course. This is a fileset as next year i may include the week 4 data used in this week - in this dataset rather than in week 4. <br>
DOI: 10.6084/m9.figshare.5457268.v1
title: Coding valence in touchscreen interactions: Hand dominance and lateral movement influence valence appraisals of emotional pictures (submitted study)

description: Research on embodied cognition revealed that hand dominance and lateral arm movements are associated with affective valence. The study presented here examined those findings with regard to interactions of the hands in a touchscreen environment. Particularly, it was investigated whether using the non-/dominant hand or performing a lateral movement would influence valence appraisals of emotional pictures presented on a touchscreen monitor. The results suggest that a match between the interacting hand, the positive or negative picture and the movement' starting side (i.e. right or left), reinforced the appraisals upon the pictures i.e. positive (negative) pictures were more positively (negatively) evaluated.
DOI: 10.6084/m9.figshare.5457037
title: isotope.xlsx

description: trfewrb fewf we<br>
DOI: 10.6084/m9.figshare.5455789
title: Repositories of OER: data and indicators of reuse and educational aspects

description: Data from a population of 110 repositories of Open Educational Resources in Higher Education and its incidence of educational and reuse indicators.<br>The research resulting has been published in: <br>SANTOS-HERMOSA, Gema; FERRAN-FERRER, Núria; ABADAL, Ernest. <b>Repositories of Open Educational Resources: An Assessment of Reuse and Educational Aspects</b>. <i>The International Review of Research in Open and Distributed Learning, [S.l.], v. 18, n. 5, aug. 2017. ISSN 1492-3831. Available</i> at: Doi:http://dx.doi.org/10.19173/irrodl.v18i5.3063.<br>
DOI: 10.6084/m9.figshare.5457037.v1
title: isotope.xlsx

description: trfewrb fewf we<br>
DOI: 10.6084/m9.figshare.5455789.v1
title: Repositories of OER: data and indicators of reuse and educational aspects

description: Data from a population of 110 repositories of Open Educational Resources in Higher Education and its incidence of educational and reuse indicators.<br>The research resulting has been published in: <br>SANTOS-HERMOSA, Gema; FERRAN-FERRER, Núria; ABADAL, Ernest. <b>Repositories of Open Educational Resources: An Assessment of Reuse and Educational Aspects</b>. <i>The International Review of Research in Open and Distributed Learning, [S.l.], v. 18, n. 5, aug. 2017. ISSN 1492-3831. Available</i> at: Doi:http://dx.doi.org/10.19173/irrodl.v18i5.3063.<br>
DOI: 10.6084/m9.figshare.5455747
title: ORIOLE Survey 2013 (Spanish)

description: Data from the ORIOLE Survey 2013 (Spanish version) about the reuse of OER in learning and teaching. This research is part of the "Open Resources: Influences on Learners and Educators" project (ORIOLE): http://orioleproject.blogspot.com.es/<br>Some results of the ORIOLE Research have been published in:SANTOS-HERMOSA, Gema. <b>ORIOLE, in the Search for Evidence of OER in Teaching. Experiences in the Use, Re-use and the Sharing and Influence of Repositories</b>. <i>Qualitative Research in Education</i>, [S.l.], v. 3, n. 2, p. 232-268, june 2014. ISSN 2014-6418. Doi:http://dx.doi.org/10.4471/qre.2014.46.
DOI: 10.6084/m9.figshare.5455750
title: ORIOLE Survey 2013 (English)

description: Data from the ORIOLE Survey 2013 (English version) about the reuse of OER in learning and teaching. This research is part of the "Open Resources: Influences on Learners and Educators" project (ORIOLE): http://orioleproject.blogspot.com.es/<br>Some results of the ORIOLE Research have been published in: SANTOS-HERMOSA, Gema. <b>ORIOLE, in the Search for Evidence of OER in Teaching. Experiences in the Use, Re-use and the Sharing and Influence of Repositories</b>. <i>Qualitative Research in Education</i>, [S.l.], v. 3, n. 2, p. 232-268, june 2014. ISSN 2014-6418. Doi:http://dx.doi.org/10.4471/qre.2014.46.<br>
DOI: 10.6084/m9.figshare.5455747.v1
title: ORIOLE Survey 2013 (Spanish)

description: Data from the ORIOLE Survey 2013 (Spanish version) about the reuse of OER in learning and teaching. This research is part of the "Open Resources: Influences on Learners and Educators" project (ORIOLE): http://orioleproject.blogspot.com.es/<br>Some results of the ORIOLE Research have been published in:SANTOS-HERMOSA, Gema. <b>ORIOLE, in the Search for Evidence of OER in Teaching. Experiences in the Use, Re-use and the Sharing and Influence of Repositories</b>. <i>Qualitative Research in Education</i>, [S.l.], v. 3, n. 2, p. 232-268, june 2014. ISSN 2014-6418. Doi:http://dx.doi.org/10.4471/qre.2014.46.
DOI: 10.6084/m9.figshare.5455702
title: ActiveBandPassFilter

description: Active bandpass filter with 4 times amplification. It has a high-pass 3-pole butterworth circuit (-3 dB at 1 Hz, -30 dB at 0.3 Hz), and a low-pass 3-pole butterworth cirtuit (-3 dB at 20 Hz, -30 dB at 50 Hz).<br>References<br>Scherz P, Monk S (2016) Practical Electronics for Inventors, 4th edn. Edition: McGraw-Hill Education TAB.<br><br><br>
DOI: 10.6084/m9.figshare.5455750.v1
title: ORIOLE Survey 2013 (English)

description: Data from the ORIOLE Survey 2013 about the reuse of OER in learning and teaching. This research is part of the "Open Resources: Influences on Learners and Educators" project (ORIOLE); http://orioleproject.blogspot.com.es/<br>Some results of the ORIOLE Research have been published in: SANTOS-HERMOSA, Gema. <b>ORIOLE, in the Search for Evidence of OER in Teaching. Experiences in the Use, Re-use and the Sharing and Influence of Repositories</b>. <i>Qualitative Research in Education</i>, [S.l.], v. 3, n. 2, p. 232-268, june 2014. ISSN 2014-6418. Doi:http://dx.doi.org/10.4471/qre.2014.46.<br>
DOI: 10.6084/m9.figshare.5455495
title: GELS_FIN_GAR_ILLUMINA.zip

description: Genotyping of Finnish gelsolin amyloidosis families using an Illumina CoreExome SNP array. Included are full genotypes from all markers inside founder haplotype area overlapping the disease variant site plus a flanking megabase on both sides. Data is in plink format, applicable for haplotype analysis.
DOI: 10.6084/m9.figshare.5455480
title: MarcioFialho_PTASE_results_2017.zip

description: Outputs from program PTASE, used in Marcio Fialho's doctorate thesis.<br><br>Reference:<br>FIALHO, M. A. A. Improved star identification techniques for monochrome and color star trackers. 2017. 246p. Doctorate Thesis - Instituto Nacional de Pesquisas Espaciais, Sao Jose dos Campos, 2017.<br>
DOI: 10.6084/m9.figshare.5455447
title: Motion_coherence_thresholds

description: For both experiments, the motion coherence threshold for each observer across conditions.
DOI: 10.6084/m9.figshare.5455495.v1
title: GELS_FIN_GAR_ILLUMINA.zip

description: Genotyping of Finnish gelsolin amyloidosis families using an Illumina CoreExome SNP array. Included are full genotypes from all markers inside founder haplotype area overlapping the disease variant site plus a flanking megabase on both sides. Data is in plink format, applicable for haplotype analysis.