cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4121/68679132-8c48-4633-9ad7-c6c8b9346b78
title: Transcriptions of semi-structured interviews underlying: Preliminary Higher Order Thinking Skills Framework for Interdisciplinary Scientific Reasoning and Problem Solving in Engineering Science Education

description: This dataset supports a study investigating higher order thinking skills (HOTS) within the context of interdisciplinary problem solving and scientific reasoning (IDPSSR) in engineering science higher education. The primary aim of the research was to develop a preliminary HOTS framework for IDPSSR by synthesizing insights from relevant literature and expert interviews.The dataset contains transcriptions from semi-structured interviews conducted with experienced scientists and educators involved in interdisciplinary teaching and research in engineering and science. These interviews were conducted to gather expert perspectives on HOTS in higher education for interdisciplinary contexts. <br><strong>Content:</strong> Transcriptions of semi-structured interviews with experts. This dataset is valuable for researchers and educators interested in (i) developing frameworks for teaching HOTS in interdisciplinary contexts, (ii) exploring methods for fostering scientific reasoning and problem-solving in higher education, a and (iii) informing curriculum design in engineering and science education.<br>The dataset includes expert insights, which are context-specific and may require careful interpretation when applying findings to other educational settings. Data confidentiality is maintained, with identifying details anonymized to protect participant privacy. Also, it may contain grammatical and spelling errors.
DOI: 10.4121/68679132-8c48-4633-9ad7-c6c8b9346b78.v1
title: Transcriptions of semi-structured interviews underlying: Preliminary Higher Order Thinking Skills Framework for Interdisciplinary Scientific Reasoning and Problem Solving in Engineering Science Education

description: This dataset supports a study investigating higher order thinking skills (HOTS) within the context of interdisciplinary problem solving and scientific reasoning (IDPSSR) in engineering science higher education. The primary aim of the research was to develop a preliminary HOTS framework for IDPSSR by synthesizing insights from relevant literature and expert interviews.The dataset contains transcriptions from semi-structured interviews conducted with experienced scientists and educators involved in interdisciplinary teaching and research in engineering and science. These interviews were conducted to gather expert perspectives on HOTS in higher education for interdisciplinary contexts. <br><strong>Content:</strong> Transcriptions of semi-structured interviews with experts. This dataset is valuable for researchers and educators interested in (i) developing frameworks for teaching HOTS in interdisciplinary contexts, (ii) exploring methods for fostering scientific reasoning and problem-solving in higher education, a and (iii) informing curriculum design in engineering and science education.<br>The dataset includes expert insights, which are context-specific and may require careful interpretation when applying findings to other educational settings. Data confidentiality is maintained, with identifying details anonymized to protect participant privacy. Also, it may contain grammatical and spelling errors.
DOI: 10.17192/fdr/63
title: Dataset: modeling with NetLogo in higher education

description: The dataset consists of: - final reports and according models produced by university students - codes for segments according to description in research paper - coded interview segments
DOI: 10.17192/fdr/154
title: Data for an integrated model to predict the intention to vaccinate against Covid-19
DOI: 10.17192/fdr/89
title: Modeling Reward Learning Under Placebo Expectancies: A Q-Learning Approach

description: This repository includes code and data necessary for reproducing the analyses presented in the attached pre-print of the paper "Augustat, N., Chuang, L.-C., Panitz, C., Stolz, C., Müller, E. M., Endres, D.: Modeling Reward Learning Under Placebo Expectancies: A Q-Learning Approach" to appear in the proceedings of CogSci 2022.
DOI: 10.17192/fdr/82
title: Validation of the performance of the random forest model for activity classification

description: We applied the trained random forest models to the 50% data withheld for testing to evaluate its performance in classifying bat activity. Similarly, we applied random forest models to the bird and human activity dataset after calculating the same predictor variables as for the bats. We first calculated the true positive rate (TPR) as the ratio of correctly identified incidents by comparing the observed data with the activity class attributed by the trained random forest models for all dataset types (i.e., human activity dataset, woodpecker, and bat video sequences). Next, we calculated the models’ F-score (F1) using the Caret package (Kuhn, 2008). Data and code are stored here.
DOI: 10.17192/fdr/99
title: Nodal lymphangiogenesis and immunophenotypic variations of sinus endothelium in sentinel and non-sentinel lymph nodes of invasive breast carcinoma

description: This repository contains the minimal dataset for the paper "Nodal lymphangiogenesis and immunophenotypic variations of sinus endothelium in sentinel and non-sentinel lymph nodes of invasive breast carcinoma", submitted to PLOS ONE for revision. The results listed in the paper can be reproduced with the data stored here. Data including calendary dates can additionally be requested via data_UMR or email at trafo@[1] or westhoff@[2] (upon reasonable request). [1]uni-marburg.de [2]med.uni-marburg.de
DOI: 10.17192/fdr/37
title: Metamorphic development of the olfactory system in the red flour beetle (Tribolium castaneum, HERBST) - Dataset Antennal OSNs

description: Each lif-file (Leica Image File) contains one or more confocal image stacks of the same specimen. At the time of submission, those files can be opened using Leicas LAS X software (Core Offline Version is sufficient), or any software using the open-source Bio-Formats library. The archives contain stereomicroscopic timelapse images and a descriptional textfile with the original image timestamps.
DOI: 10.25345/c5n873b6f
title: MassIVE MSV000096464 - Gnps stage 1 molecular network training
title: analyze the lc-ms raw data with molecular networking using gnps
DOI: 10.5281/zenodo.14184570
title: Predictive physiological anticipatory activity preceding seemingly unpredictable stimuli: An update of Mossbridge et al's meta-analysis

description: The research that created this data is described in:



Duggan M and Tressoldi P. Predictive physiological anticipatory activity preceding seemingly unpredictable stimuli: An update of Mossbridge et al’s meta-analysis [version 2; referees: 2 approved]. F1000Research 2018, 7:407 (https://doi.org/10.12688/f1000research.14330.2)


Two files are included:



MA_PPAA_Final.xlsx - Database

Code.pdf - Code
DOI: 10.5281/zenodo.14184571
title: Predictive physiological anticipatory activity preceding seemingly unpredictable stimuli: An update of Mossbridge et al's meta-analysis

description: The research that created this data is described in:



Duggan M and Tressoldi P. Predictive physiological anticipatory activity preceding seemingly unpredictable stimuli: An update of Mossbridge et al’s meta-analysis [version 2; referees: 2 approved]. F1000Research 2018, 7:407 (https://doi.org/10.12688/f1000research.14330.2)


Two files are included:



MA_PPAA_Final.xlsx - Database

Code.pdf - Code
DOI: 10.17192/fdr/76.3
title: Integration of optic flow into the sky compass network in the brain of the desert locust

description: Physiological and meta data, code for their analysis, and code underlying the computational model for the manuscript 'Integration of optic flow into the sky compass network in the brain of the desert locust'.
DOI: 10.17192/fdr/105
title: Substanz_Screening

description: Substanz Screening Mikroskopie Daten zugehörig zur Dissertation Stephan Ringshandl. Für erweiterte Informationen sei auf die in dieser Sammlung hinterlegte README Datei verwiesen. Jede Datei enthält Daten einer halben Mikrotiterplatte. Der 6-stellige Code im Titel bezeichnet die Mikrotiterplatte, wobei die Systematik in der in dieser Sammlung ebenfalls enthaltenen README Datei zu finden ist. nd2 Dateien enthalten die oben beschriebenen Kanäle und in seltenen Fällen auch eine Aufnahme im DIC (Differentialinterferenzkontrast) Kanal. Signalfarben entsprechen folgenden Objekten: rot wurde über CellMask Red gefärbt = differenzierte THP1 Zellen, blau würde über Höchst 33342 gefärbt = DNA (Zellkern der THP1 Zellen), grün ist durch Legionellen exprimiertes GFP = Legionella pneumophila Corby. Mikroskopie über Nikon Eclipse Ti2 Mikroskop mit folgenden Einstellungen. Jeweils Kanalfarbe/Anregungsfilter/Dichroitischer Spiegel/Emissionsfilter: blau/381,5 nm - 392,5 nm/409 nm/417 nm – 477 nm, grün/457 nm – 487nm/495 nm/502,5 nm - 537,5 nm, rot/542 nm – 582 nm/593 nm/604 nm - 644 nm.
DOI: 10.17192/fdr/210
title: A virtual library of small molecules mimicking dipeptides
title: Dipeptide-mimic library

description: Virtual combinatorial libraries are prevalent in drug discovery due to improvements in the prediction of synthetic reactions that can actually be performed. This has gone hand in hand with the development of virtual screening capabilities to effectively screen the large chemical spaces spanned by exhaustive enumeration of reaction products. In this study, we generated a small-molecule dipeptide mimic library to target proteins binding small peptides. The library was created based on the general idea of peptide synthesis, i.e. amino acid mimics were reacted in silico to form the dipeptide mimics. The data set contains of 400 sets of mimics for each of the 400 dipeptides that can be formed from the 20 proteinogenic amino acids.
DOI: 10.17192/fdr/176.3
title: Measuring Dysfunctional Interpersonal Beliefs: Validation of the Interpersonal Cognitive Distortions Scale among a German-speaking Sample

description: The dataset from the file "pooled sample_without outliers.csv" belongs to a clinical psychological study that has already been published as a preprint (https://psyarxiv.com/e5qyu/) and previously pre-registered (https://aspredicted.org/4i22q.pdf). The study was approved by the local ethics committee of the Philipps University of Marburg (reference number: 2022-29k). The doi of the preprint is 10.31234/osf.io/e5qyu. Additional material can be found at https://osf.io/ep2n8/. The dataset contains data from a mixed online sample (N=208) collected between August 5, 2022, and August 15, 2022, using the online research platform "Prolific" (https://www.prolific.co/). Outliers have already been excluded. Additional information about the variables included in the dataset can be found in the file "codebook.txt"
DOI: 10.17192/fdr/147
title: Reconciliation in Colombia – A Q-methodological Study

description: This is the data from a q-methodological research project on reconciliation in Colombia, which was conducted from May 2021 until August 2022 and funded by the Deutsche Stiftung Friedensforschung (DSF). Data was collected from October until mid-December 2021 online via Q Method Software (https://qmethodsoftware.com) and analyzed with Ken-Q Analysis (https://shawnbanasick.github.io/ken-q-analysis/). Research participants were asked to share their perspectives on reconciliation in Colombia by ranking images on a distribution scale from -4 (least representative images for reconciliation) to +4 (most representative images for reconciliation). The resulting distributions of images are referred to as Q sorts and factor analysis is used to find groups of similar Q sorts, i.e. perspectives on reconciliation. Since the scope of publications is always limited, we seek to provide a higher level of transparency to our research providing our research data in this repository.
DOI: 10.17192/fdr/168
title: Integration of optic flow into the sky compass network in the brain of the desert locust (Frontiers Version)

description: This repository accompanies the 2023 Frontiers manuscript 'Integration of optic flow into the sky compass network in the brain of the desert locust'. It contains physiological and meta data, code for their analysis, and code underlying the computational model and simulation.
DOI: 10.17192/fdr/89.6
title: Modeling Reward Learning Under Placebo Expectancies: A Q-Learning Approach

description: This repository includes code and data necessary for reproducing the analyses presented in the attached pre-print of the paper "Augustat, N., Chuang, L.-C., Panitz, C., Stolz, C., Müller, E. M., Endres, D.: Modeling Reward Learning Under Placebo Expectancies: A Q-Learning Approach" to appear in the proceedings of CogSci 2022.
DOI: 10.17192/fdr/200.4
title: Processing unexpected social feedback in depression

description: The data sets "study_data.csv" and "interrater_reliability.csv" are part of a clinical psychology study that investigates differences in the processing of social feedback in a heterogeneous online sample (N = 155) with varying degrees of depression. The study was registered at [Aspredicted.org](http://aspredicted.org/) (https://aspredicted.org/tj6tb.pdf) and published as a preprint at Psyarxiv (https://psyarxiv.com/tvebd/; doi: 10.31234/osf.io/tvebd).
DOI: 10.17192/fdr/192
title: Appendix-Demographic Mortality Measures as Indicators of Amenable or Avoidable Deaths in the 50 States of the United States of America. An Example of a Population-Based Health Care Quality Indicator - Applied to Chronic Obstructive Pulmonary Disease (COPD)

description: In this work, a novel approach to measuring amenable deaths is introduced. The lowest age-specific mortality rates in the USA have been isolated to create normative life tables. The concept of normative life tables was first described in the context of the Global Burden of Disease Study at the University of Washington in Seattle, for measuring the general burden of disease in specific populations. Normative life tables provide an ideal life table for the USA, and shed light on shortcomings in states with comparatively high mortality rates. The normative life table approach is applied for a chronic and frequent health condition in the USA, namely COPD (Chronic Obstructive Lung Disease). The lowest COPD mortality rates in the USA for 2016 have been isolated to create normative COPD life tables. These normative life tables show the best practice for COPD in the USA. Excess deaths in COPD across the states are regarded as amenable deaths, i.e., deaths that with timely and effective medical interventions and public health efforts could have been prevented. California has the lowest proportion of amenable deaths due to COPD. Texas has moderate mortality rates for COPD, while Kentucky has the highest COPD mortalities in the USA, and therefore the highest proportion of amenable deaths in COPD. These changes are also reflected in the life expectancy of individuals with COPD. California has the highest life expectancy for individuals with COPD. In 2016, 50- year-olds with COPD in California were expected to live for an additional 21.01 years, while in Texas they had an additional 17.82 years to live and in Kentucky, only 11.94 years. The normative life table approach adds to current efforts by providing a fair way of measuring health care performance. It acts as an indicator of health care quality by measuring the share of amenable deaths that, with timely and effective medical interventions and public health efforts, could have been avoided.
DOI: 10.17192/fdr/166.6
title: Multispectral analysis-ready satellite data for three East African mountain ecosystems

description: Our data provides a readme file and multiple Cloud Optimised Geotif (.tif) files and its associated metadata in .json format of Sentinel-2 analysis-ready satellite data for three East African mountain ecosystems namely: Bale Mountains (BM) in Ethiopia and Mounts Kilimanjaro and Meru (KM) in Tanzania. The .tif files include monthly and annual products including ten spectral images (red, green, blue, broad near-infrared, near-infrared, red edge 1-3, and shortwave-infrared 1-2) as well as 24 calculated spectral indices . For the full list of indices please refer to the readme file. Additionally, the workflow, parameters files and python script are attached, that were used to generate the analysis-ready data. The data can be read in an Geographic Information System (GIS) software or using programming languages like R or python.
DOI: 10.17192/fdr/232
title: QUICL Experiment Data

description: This repository contains all experiment results used in evaluating our Paper "QUICL: Disruption-tolerant Networking via a QUIC Convergence Layer," in which we present our novel, QUIC-based Convergence Layer for Bundle Protocol Version 7 compliant disruption-tolerant networks. Disruption-tolerant networks (DTNs) have a wide range of applications, including emergency situations where traditional communication infrastructure has been destroyed, remote rural deployments where communication infrastructure does not exist, and environmental monitoring in which animals are outfitted with sensors and transmit data whenever they come into contact with a base station. Using the de-facto DTN protocol standard, Bundle Protocol version 7 (BPv7), nodes communicate data using Convergence Layer Protocols (CLPs), which are broad abstractions for the underlying communication technology. BPv7 specifies two CLPs for DTNs: MTCP and TCPCL. However, they have distinct but equally undesirable flaws in functionality, complexity, performance, and reliability. QUICL is built on the QUIC transport protocol, which offers advantages over TCP-based protocols in a DTN setting. QUICL, in particular, improves congestion control, supports multiplexing, ensures reliable transmission, effectively manages unstable networks, and encrypts traffic by default. Our implementation, already merged upstream, is based on the free and open-source DTN7-go protocol suite and the QUIC-go library. Our experimental evaluation shows that even in tough situations, such as a bundle transmission over 63 hops with a packet loss of 30% on each hop, QUICL still delivers data, while most other DTN software/CLP combinations fail to transmit any data.
DOI: 10.17192/fdr/56
title: Data For LIBS Application

description: This folder contains all data mentioned in the paper "Identifying microplastic litter with Laser-Induced Breakdown Spectroscopy (LIBS): A first Approach". This includes the LIBS data of the reference plastics (PA6, PE, PP, PVC, PET, PC, and PS from the suppliers Vitasheet Group and BAM), the 14 natural materials, and the 45 microparticles. In addition to the LIBS data, the FTIR data of the 45 microparticles are included in the folder.
DOI: 10.17192/fdr/73
title: Machine Learning Classification of Trajectories from Molecular Dynamics Simulations of Chromosome Segregation

description: In contrast to the well characterized mitotic machinery in eukaryotes it seems as if there is no universal mechanism organizing chromosome segregation in all bacteria. Apparently, some bacteria even use combinations of different segregation mechanisms such as protein machines or rely on physical forces. The identification of the relevant mechanisms is a difficult task. Here, we introduce a new machine learning approach to this problem. It is based on the analysis of trajectories of individual loci in the course of chromosomal segregation obtained by fluorescence microscopy. While machine learning approaches have already been applied successfully to trajectory classification in other areas, so far it has not been possible to use them to discriminate segregation mechanisms in bacteria. A main obstacle for this is the large number of trajectories required to train machine learning algorithms that we overcome here by using trajectories obtained from molecular dynamics simulations. We used these trajectories to train four different machine learning algorithms, two linear models and two tree-based classifiers, to discriminate segregation mechanisms and possible combinations of them. The classification was performed once using the complete trajectories as high-dimensional input vectors as well as on a set of features which were used to transform the trajectories into low-dimensional input vectors for the classifiers. Finally, we tested our classifiers on shorter trajectories with duration times comparable (or even shorter) than typical experimental trajectories and on trajectories measured with varying temporal resolutions. Our results demonstrate that machine learning algorithms are indeed capable of discriminating different segregation mechanisms in bacteria and to even resolve combinations of the mechanisms on rather short time scales. In this repository, the trained machine learning models and the corresponding data sets are stored. The code for evaluating the models can be found in the GitHub repository https://github.com/DavidGeisel/ML_Classification_MD_Trajectories.
DOI: 10.17192/fdr/211
title: Identifying and Counting Avian Blood Cells in Whole Slide Images via Deep Learning

description: This dataset contains research data as presented in: Vogelbacher, M.; Strehmann, F.; Bellafkir, H.; Mühling, M.; Korfhage, N.; Schneider, D.; Rösner, S.; Schabo, D. G.; Farwig, N.; Freisleben, B. Identifying and Counting Avian Blood Cells in Whole Slide Images via Deep Learning. Submitted for publication. 2024. In this article, we present a novel approach to automatically quantify avian red and white blood cells in whole slide images. Our approach is based on two deep neural network models. The first model determines image regions that are suitable for counting blood cells, and the second model is an instance segmentation model that detects the cells in the determined image regions. The region selection model achieves up to 97.3% in terms of the F1 score, and the instance segmentation model achieves up to 90.7% in terms of mean average precision. Our approach helps ornithologists to acquire hematological data from avian blood smears more precisely and efficiently. The data published here include the raw annotated data as well as the trained models for the automated counting of blood cells in avian blood smears. Our code is publicly available at https://github.com/umr-ds/avibloodcount.
DOI: 10.17192/fdr/24
title: Experimentelles Schmerzparadigma Erwartungsveränderung (Studie II)

description: description: Daten aus einem experimentellen Paradigma mit drei Messzeitpunkten / Längsschnitt mit N = 73 ProbandInnen mit subklinischen Schmerzbildern - Hitzereizparadigma mit Applikation von Schmerzreizen - ProbandInnen wurden in zwei Bedingungen randomisiert und erhielten abhängig von ihrer Bedingung unterschiedliche Erwartungsinduktionen, sodass sie die darauffolgende Erfahrung im Experiment entweder als erwartungsbestätigend vs. erwartungsverletzend erlebten - primäres Outcome: Bewertung der Schmerzerfahrung; Generalisierung der Erfahrung auf Bewältigungseinschätzung mit anderen Schmerzen
DOI: 10.17192/fdr/176
title: Measuring Dysfunctional Interpersonal Beliefs: Validation of the Interpersonal Cognitive Distortions Scale among a German-speaking Sample

description: This repository contains data from a study in which nonclinical and clinical participants were recruited via an online research platform. They had to be at least 18 years old and fluent in German. The nonclinical and clinical samples were separated using pre-screening filters, and gender was counterbalanced within each sample. The order of questionnaires was randomized for each participant. The final sample consisted of 116 participants in the nonclinical sample and 100 participants in the clinical sample. The study was registered with AsPredicted (https://aspredicted.org/4i22q.pdf) and approved by our local ethics committee (reference number: 2022-29k).
DOI: 10.17192/fdr/229
title: Datenbank_Rassismus_in_rechten_Diskursen

description: Forschungsdaten zur Dissertation "Rassismus in rechten Diskursen" (DOI: 10.17192/z2024.0044)