cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15139/s3/wzooxx
title: Replication Data for: Schoolhouse Rocked: Pandemic Politics and the Nationalization of School Board Elections

description: We examine the influence of national politics and changing racial demographics on school board elections. We identify the districts where candidates campaigned on Critical Race Theory (CRT), COVID response, or parent control/transparency (what we call “conflict elections”) and examine two related questions. First, what characteristics define school districts that had elections involving these issues? Second, in the places that had conflict elections, how frequently did “conflict candidates” win, and what factors influenced their odds of winning? Utilizing a unique dataset of all school board elections in Wisconsin in 2022, we find that Republican presidential vote share is positively related to both the probability that a school district had a conflict election and that a conflict candidate won. We also find that in communities where the white population declined between 2010 and 2020, there was a higher likelihood that a conflict candidate won compared to communities where the size of the white population grew. Overall, our analysis confirms that school board elections are increasingly mirroring nationalized trends in other elections.
DOI: 10.3886/e157861v1-143096
title: MUSIC Model of Motivation in 30 College Courses - 2022

description: Student evaluations of teaching (SETs) are important at most colleges and universities. One purpose of this study was to determine the extent to which motivational climate was associated with SETs. Another purpose was to determine whether course ease was associated with SETs. Participants included 2,949 undergraduate students from 30 courses at a large public university. Using hierarchical linear modeling, we examined the extent to which students’ motivation-related course perceptions (empowerment/autonomy, usefulness, success expectancies, situational interest, and caring) related to SETs at the student and class level. SETs were highly associated with motivational climate. Furthermore, easier courses were rated lower by students when controlling for motivational climate and the demographical composition of the class. These findings highlight the association between the motivational climate and SETs and suggest that one way to improve SETs may be for instructors to focus on improving the motivational climate rather than making the course easier. For more details, see this article: Jones, B. D., Miyazaki, Y., Li, M., & Biscotte, S. (2022). Motivational climate predicts student evaluations of teaching: Relationships between students’ course perceptions, ease of course, and evaluations of teaching. AERA Open. Jones, B. D., Miyazaki, Y., Li, M., & Biscotte, S. (2022). Motivational climate predicts student evaluations of teaching: Relationships between students’ course perceptions, ease of course, and evaluations of teaching. AERA Open.
description: n/a
description: Response Rates: see Jones, B. D., Miyazaki, Y., Li, M., & Biscotte, S. (2022). Motivational climate predicts student evaluations of teaching: Relationships between students’ course perceptions, ease of course, and evaluations of teaching. AERA Open.
description: Presence of Common Scales: MUSIC® Model of Academic Motivation Inventory (Jones, 2012/2020)<br>Instructor rating (Jones, 2010)<br>Course rating (Jones, 2010)<br>Ease of Course scale (Jones et al., 2021)<br><br>References<br>Jones, B. D. (2010). An examination of motivation model components in face-to-face and online instruction. Electronic Journal of Research in Educational Psychology, 8(3), 915-944. <br> Jones, B. D. (2012/2020). User guide for assessing the components of the MUSIC® Model of Motivation. http://www.theMUSICmodel.com <br> Jones, B. D., Krost, K., & Jones, M. W. (2021). Relationships between students’ course perceptions, effort, and achievement in an online course. Computers and Education Open, 2, Article 100051. https://doi.org/10.1016/j.caeo.2021.100051
description: see Jones, B. D., Miyazaki, Y., Li, M., & Biscotte, S. (2022). Motivational climate predicts student evaluations of teaching: Relationships between students’ course perceptions, ease of course, and evaluations of teaching. AERA Open.
description: web-based survey;
DOI: 10.6073/pasta/0887954770a8ae5b15438c4f2181cfd3
title: Daily climate summary: Meterologic Measurements at Cedar Creek Natural History Area

description: Meteorological measurements include air temperature, precipitation, wind speed and direction, soil temperature, and relative humidity. These measurements are taken on an hourly basis.
DOI: 10.5281/zenodo.8414474
title: Laypeople in Fire Protection: Their Motivation, Their Emotions, Their Value

description: This online supplement contains datasets (raw data) and study material collected in a study by the University of Münster, Germany. The study is part of a larger research project (https://www.brawa.ovgu.de/en/) and examined the motivation, emotions, and behavior of laypeople in fire protection. Fire events, a specific type of emergency situation, occur regularly and often cost people’s lives. Early fire detection and involvement of (trained) laypeople in very early stages is essential, especially in fire-prone historical buildings. In an interview study (N = 25) and a quantification study (N = 238), we examined laypeople’s motivation to help, their emotions, and their value – especially regarding behaviors – during fires. In Study 1, based on in-depth interviews using the critical incident technique, we inductively developed three category systems: 1) Key motivators included one’s emotional bond to the object, altruism, self-protection, and self-efficacy. 2) Laypeople’s emotions, such as shock at first but also calmness, were categorized. 3) We also found that laypeople’s primary value during fire incidents was their ability to provide support, e.g., knowledge of the building. In Study 2, we found quantitative support for the findings derived from Study 1. Additionally, we compared laypeople’s and experts’ assessments and compared reactions depending on fire size. Thus, our research shifts the focus from evacuation to active – and safe – involvement of laypeople. Our results are helpful for executives in emergency management, as they may find value in including laypeople when coping with emergencies. The ethics committee of the Faculty of Psychology and Sports Science of the University of Münster approved the studies (under ID 2021-30-MT and ID 2021-14-MT) and we preregistered them with aspredicted.org (available at https://aspredicted.org/blind.php?x=6yk694 and https://aspredicted.org/CN7_1QL). The studies were supported by the German Federal Ministry of Education and Research (grant numbers 13N15416 and 13N15419). <strong>This online supplement includes:</strong> An online supplement (online appendix) containing additional material and results for Study 1 and Study 2 One codebook describing all instructions and items in Study 2 (quantification study) Raw (anonymized) data set and analysis script for Study 2 (Note: The raw data contains only the information of persons who were included in the analysis and who gave their informed consent. Some demographic information was deleted to ensure anonymity.)
DOI: 10.6084/m9.figshare.24568231.v1
title: Lisinopril is superior to Hydralazine in reducing the proteinuria in G1/G1 mice

description: To ascertain if the protective effect of lisinopril on renal disease in G1/G1 mice was mediated solely by its anti-hypertensive effects, we compared the effects of hydralazine, a pure vasodilator without specific effects on afferent or efferent arterioles or on intraglomerular pressure, with those of lisinopril. Mice were randomized to one of three experimental groups, one treated with lisinopril (75 mg/L in drinking water), one treated with hydralazine (200 mg/L in drinking water), and a control untreated group. Mice were randomized to treatment or no treatment at day 7 post-injection after confirming presence of proteinuria. Albuminuria was similar among groups at days 4 and 7. Reduced proteinuria is evident in the lisinopril group starting at day 14 (7 days after start of treatment), and reduced further thereafter. One of the values was excluded from the Control group (day 18/marked with *) because the creatinine was undetected, therefore this is unlikely to be urine but likely some other biologic fluid. The mouse was almost moribund at that time and likely anuric. This mouse was sacrificed and blood/tissue were harvested.
DOI: 10.6084/m9.figshare.24568231
title: Lisinopril is superior to Hydralazine in reducing the proteinuria in G1/G1 mice

description: To ascertain if the protective effect of lisinopril on renal disease in G1/G1 mice was mediated solely by its anti-hypertensive effects, we compared the effects of hydralazine, a pure vasodilator without specific effects on afferent or efferent arterioles or on intraglomerular pressure, with those of lisinopril. Mice were randomized to one of three experimental groups, one treated with lisinopril (75 mg/L in drinking water), one treated with hydralazine (200 mg/L in drinking water), and a control untreated group. Mice were randomized to treatment or no treatment at day 7 post-injection after confirming presence of proteinuria. Albuminuria was similar among groups at days 4 and 7. Reduced proteinuria is evident in the lisinopril group starting at day 14 (7 days after start of treatment), and reduced further thereafter. One of the values was excluded from the Control group (day 18/marked with *) because the creatinine was undetected, therefore this is unlikely to be urine but likely some other biologic fluid. The mouse was almost moribund at that time and likely anuric. This mouse was sacrificed and blood/tissue were harvested.
DOI: 10.5281/zenodo.10119287
title: Running a Red Light: An Investigation into Why Software Engineers (Occasionally) Ignore Coverage Checks --- Appendix

description: This online appendix contains the anonymised responses to our survey, which we have analysed in our report. In addition, it also includes the mapping of axial coding codes to larger groups, and (if not self-evident) a further explanation of these groups.
DOI: 10.5281/zenodo.10119288
title: Running a Red Light: An Investigation into Why Software Engineers (Occasionally) Ignore Coverage Checks --- Appendix

description: This online appendix contains the anonymised responses to our survey, which we have analysed in our report. In addition, it also includes the mapping of axial coding codes to larger groups, and (if not self-evident) a further explanation of these groups.
DOI: 10.6084/m9.figshare.24050802
title: Genetic control of MRI contrast using the manganese transporter Zip14

description: These are the primary data described in our paper titled "Genetic control of MRI contrast using the manganese transporter Zip14". The MRI data are organized into the following file hierarchy:Injected virus. The filename is structured: 'Capsid'-'Promoter'-Zip14-'Tag'_Injection-'BrainArea' Animal. 'M' denotes sex male and 'F' denotes sex female, followed by a numerical identifier. Timepoint. Imaging was performed over the course of weeks 'W' after injection. Images. <br><br>We strongly suggest using MIPAV to view the NIfTI format images. 'image_input' is the reconstructed MPRAGE image at each timepoint. Other files that may be included in each folder include output from ANTs registration of the Allen Institute Mouse Brain Atlas template and corresponding CCFv3 labels to the image and T1 mapping protocol-required images. Immunohistology data are included in the corresponding 'Animal' folder. We suggest using Fiji to view these .lsm, .czi, .nd2, and .tif images. Please contact us if you have any questions.
DOI: 10.5281/zenodo.10138625
title: OPENCV LIBRARY IN PAYTON AND COMPARATIVE ANALYSIS OF THE METHODOLOGY OF USE IN COMPUTER VISION
DOI: 10.5281/zenodo.10138624
title: OPENCV LIBRARY IN PAYTON AND COMPARATIVE ANALYSIS OF THE METHODOLOGY OF USE IN COMPUTER VISION
DOI: 10.5281/zenodo.10138499
title: Laypeople in Fire Protection: Their Motivation, Their Emotions, Their Value

description: This online supplement contains a dataset (raw data) collected in a study by the University of Münster, Germany, as well as supplementary study materials, and the online appendix of our paper including additional results. The study is part of a larger research project (https://www.brawa.ovgu.de/en/) and examined the motivation, emotions, and behavior of laypeople in fire protection.
Fire events, a specific type of emergency situation, occur regularly and often cost people's lives. Early fire detection and involvement of (trained) laypeople in very early stages is essential, especially in fire-prone historical buildings. In an interview study (N = 25) and a quantification study (N = 238), we examined laypeople's motivation to help, their emotions, and their value – especially regarding behaviors – during fires. In Study 1, based on in-depth interviews using the critical incident technique, we inductively developed three category systems: 1) Key motivators included one's emotional bond to the object, altruism, self-protection, and self-efficacy. 2) Laypeople's emotions, such as stress at first but also calmness, were categorized. 3) We also found that laypeople's primary value during fire incidents was their ability to provide support, e.g., knowledge of the building. In Study 2, we found quantitative support for the findings derived from Study 1. Additionally, we compared laypeople's and experts' assessments and compared reactions depending on fire size. Thus, our research shifts the focus from evacuation to active – and safe – involvement of laypeople. Our results are helpful for executives in emergency management, as they may find value in including laypeople when coping with emergencies.
The ethics committee of the Faculty of Psychology and Sports Science of the University of Münster approved the studies (under ID 2021-30-MT and ID 2021-14-MT) and we preregistered them with aspredicted.org (available at https://aspredicted.org/dd2p8.pdf and https://aspredicted.org/m6zh5.pdf). The studies were supported by the German Federal Ministry of Education and Research (grant number 13N15416).
This online supplement includes:

An online supplement (online appendix) containing additional material and results for Study 1 and Study 2
One codebook describing all instructions and items in Study 2 (quantification study)
Raw (anonymized) data set and analysis script for Study 2 (Note: The raw data contains only the information of persons who were included in the analysis and who gave their informed consent. Some demographic information was deleted to ensure anonymity.)
DOI: 10.5281/zenodo.8414473
title: Laypeople in Fire Protection: Their Motivation, Their Emotions, Their Value

description: This online supplement contains a dataset (raw data) collected in a study by the University of Münster, Germany, as well as supplementary study materials, and the online appendix of our paper including additional results. The study is part of a larger research project (https://www.brawa.ovgu.de/en/) and examined the motivation, emotions, and behavior of laypeople in fire protection.
Fire events, a specific type of emergency situation, occur regularly and often cost people's lives. Early fire detection and involvement of (trained) laypeople in very early stages is essential, especially in fire-prone historical buildings. In an interview study (N = 25) and a quantification study (N = 238), we examined laypeople's motivation to help, their emotions, and their value – especially regarding behaviors – during fires. In Study 1, based on in-depth interviews using the critical incident technique, we inductively developed three category systems: 1) Key motivators included one's emotional bond to the object, altruism, self-protection, and self-efficacy. 2) Laypeople's emotions, such as stress at first but also calmness, were categorized. 3) We also found that laypeople's primary value during fire incidents was their ability to provide support, e.g., knowledge of the building. In Study 2, we found quantitative support for the findings derived from Study 1. Additionally, we compared laypeople's and experts' assessments and compared reactions depending on fire size. Thus, our research shifts the focus from evacuation to active – and safe – involvement of laypeople. Our results are helpful for executives in emergency management, as they may find value in including laypeople when coping with emergencies.
The ethics committee of the Faculty of Psychology and Sports Science of the University of Münster approved the studies (under ID 2021-30-MT and ID 2021-14-MT) and we preregistered them with aspredicted.org (available at https://aspredicted.org/dd2p8.pdf and https://aspredicted.org/m6zh5.pdf). The studies were supported by the German Federal Ministry of Education and Research (grant number 13N15416).
This online supplement includes:

An online supplement (online appendix) containing additional material and results for Study 1 and Study 2
One codebook describing all instructions and items in Study 2 (quantification study)
Raw (anonymized) data set and analysis script for Study 2 (Note: The raw data contains only the information of persons who were included in the analysis and who gave their informed consent. Some demographic information was deleted to ensure anonymity.)
DOI: 10.5281/zenodo.10138648
title: TERMINOLOGIYA FANI VA UNING RIVOJLANISHI, TERMINOLOGIYANING BOSHQA FANLAR BILAN ALOQASI, TERMINLAR VA ULARNI O'RGANISH MASALALARI.
DOI: 10.5281/zenodo.10138649
title: TERMINOLOGIYA FANI VA UNING RIVOJLANISHI, TERMINOLOGIYANING BOSHQA FANLAR BILAN ALOQASI, TERMINLAR VA ULARNI O'RGANISH MASALALARI.
DOI: 10.5281/zenodo.10010428
title: Estimación de uso de suelo del Sistema Urbano Nacional en nivel manzana 2020

description: Estimación del uso de suelo del Sistema Urbano Nacional 2020.
Los valores existentes son:
- Habitacional de Alta Densidad (H-a)
- Habitacional de Media Densidad (H-m)
- Habitacional de Baja Densidad (H-b)
- Habitacional Mixto de Alta Densidad M-a (HM-a)
- Habitacional Mixto de Media Densidad (HM-m)
- Mixto Especializado (M)
- Equipamiento (E)
- Comercio y Servicios (CS)
- Industria (I)
- Deporte, Recreación y Áreas Verdes (AV)
description: Se utilizan los datos censales del Instituto Nacional de Estadística y Geografía y se expresa a través de las manzanas urbanas censales del año 2020 a nivel nacional. En particular, se utiliza el Marco Geoestadístico Nacional a nivel de manzana para la identificación del uso habitacional y la definición de la densidad. Para la identificación de los destinos del suelo (equipamiento, instalaciones diversas e infraestructura), se utilizan los datos geográficos puntuales contenidos en el Sistema para la Consulta de Información Censal SCINCE (en particular del Sistema de Infraestructura Pública, SIP) y se complementan con los puntos derivados del Directorio Estadístico Nacional de Unidades Económicas DENUE. Las principales actividades económicas se localizan a partir del DENUE, y su tamaño se define a partir del personal ocupado. Esto hizo posible identificar la mezcla de usos y calcular la densidad.
Los usos del suelo se obtienen a partir de la combinación de datos presentes en cada manzana, cumpliendo con los siguientes criterios:
Manzanas en las que no hay presencia de actividad económica (puntos DENUE) se consideran como habitacional. El grupo de manzanas con vivienda y con presencia considerable de Unidades Económicas (UE) se clasificaron como habitacional mixto. Manzanas con predominio de UE de gran tamaño (promedio superior a 50 personas ocupadas), se clasificaron como comercio-servicios, industria y mixto especializado (este último, se expresa en manzanas que combinan usos predominantes diferentes al habitacional). Las manzanas con ausencia de vivienda, se clasificaron como equipamiento, comercio, industria y área verde, de acuerdo con los datos puntuales del SIP.
Para calcular la densidad en las categorías estimadas habitacional y habitacional mixto, se definieron y aplicaron los criterios: habitacional de alta densidad con más de 150 viv/ha, de media entre 150 y más de 99 viv/ha, y baja menor que 100 viv/ha. Para el caso del habitacional mixto de alta densidad mayor a 2, y media de 1 hasta 2. Valores obtenidos del cociente del número de unidades económicas entre el número de viviendas por manzana.
DOI: 10.5281/zenodo.7626566
title: Estimación de uso de suelo del Sistema Urbano Nacional en nivel manzana 2020

description: Estimación del uso de suelo del Sistema Urbano Nacional 2020.<br> Los valores existentes son:<br> - Habitacional de Alta Densidad (H-a)<br> - Habitacional de Media Densidad (H-m)<br> - Habitacional de Baja Densidad (H-b)<br> - Habitacional Mixto de Alta Densidad M-a (HM-a)<br> - Habitacional Mixto de Media Densidad (HM-m)<br> - Mixto Especializado (M)<br> - Equipamiento (E)<br> - Comercio y Servicios (CS)<br> - Industria (I)<br> - Deporte, Recreación y Áreas Verdes (AV)
description: Se utilizan los datos censales del Instituto Nacional de Estadística y Geografía y se expresa a través de las manzanas urbanas censales del año 2020 a nivel nacional. En particular, se utiliza el Marco Geoestadístico Nacional a nivel de manzana para la identificación del uso habitacional y la definición de la densidad. Para la identificación de los destinos del suelo (equipamiento, instalaciones diversas e infraestructura), se utilizan los datos geográficos puntuales contenidos en el Sistema para la Consulta de Información Censal SCINCE (en particular del Sistema de Infraestructura Pública, SIP) y se complementan con los puntos derivados del Directorio Estadístico Nacional de Unidades Económicas DENUE. Las principales actividades económicas se localizan a partir del DENUE, y su tamaño se define a partir del personal ocupado. Esto hizo posible identificar la mezcla de usos y calcular la densidad. Los usos del suelo se obtienen a partir de la combinación de datos presentes en cada manzana, cumpliendo con los siguientes criterios: Manzanas en las que no hay presencia de actividad económica (puntos DENUE) se consideran como habitacional. El grupo de manzanas con vivienda y con presencia considerable de Unidades Económicas (UE) se clasificaron como habitacional mixto. Manzanas con predominio de UE de gran tamaño (promedio superior a 50 personas ocupadas), se clasificaron como comercio-servicios, industria y mixto especializado (este último, se expresa en manzanas que combinan usos predominantes diferentes al habitacional). Las manzanas con ausencia de vivienda, se clasificaron como equipamiento, comercio, industria y área verde, de acuerdo con los datos puntuales del SIP. Para calcular la densidad en las categorías estimadas habitacional y habitacional mixto, se definieron y aplicaron los criterios: habitacional de alta densidad con más de 150 viv/ha, de media entre 150 y más de 99 viv/ha, y baja menor que 100 viv/ha. Para el caso del habitacional mixto de alta densidad mayor a 2, y media de 1 hasta 2. Valores obtenidos del cociente del número de unidades económicas entre el número de viviendas por manzana.
description: {"references": ["http://rtm22.centrogeo.edu.mx/uso-de-suelo/"]}