cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/ckp459gbbz.1
title: Genre-Based Approach: Its Integration To Teach English Grammar In Constructing Sentences

description: This study aims to discuss how teaching and learning activities were carried out by using Genre-based in teaching English grammar in constructing sentences at SMA Negeri 1 Kota Ternate. This study was conducted to the 27 students of class XI language and culture. The research was designed into a qualitative approach by using the phenomenological method. To collect data, the researcher used the students' results of the test. Research findings reveal that more than 70% of the students were successful in identifying the language features of constructing sentences. The implementation of a genre-based approach to teaching English grammar gives a good contribution to the improvement of the students' proficiency in constructing sentences.
DOI: 10.17632/kxcvx66s6g.1
title: Efficacy of repetitive transcranial magnetic stimulation for post-stroke depression: a systematic review and meta-analysis of randomized clinical trials.

description: This is the protocol for this meta-analysis
DOI: 10.21227/1zpf-s269
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains the IDs of geo-tagged tweets. The tweets were captured by an on-going project deployed at https://live.rlamsal.com.np. The geolocation data was extracted from the tweets which mentioned anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page).Note: I started sharing the IDs of the tweets that contained the exact location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs (above 150+ million tweets) shared in the Coronavirus (COVID-19) Tweets Dataset.If you need the geolocation-based data starting March 20, 2020, then use the Coronavirus (COVID-19) Tweets Dataset and hydrate the IDs while adding the following condition:data = json.loads(data)if data["coordinates"]: longitude, latitude = data["coordinates"]["coordinates"]The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-april29.* will contain tweet ID and sentiment data of the tweets that were tweeted between April 28, 2020, and April 29, 2020.Why are only tweet IDs being shared? It is Twitter's content redistribution policy that restricts the sharing of tweet information other than tweet IDs and/or user IDs. Twitter wants researchers to always pull fresh data using their API. Why? Here's my opinion. Maybe, some user might want to delete a particular tweet after a couple of minute(s)/hour(s)/day(s), and if the same tweet has already been pulled and is shared on a public domain, then it might make the user/community vulnerable to many inferences coming out of the shared data.
DOI: 10.17632/wvtx8ps724.1
title: Analyzing Construction Safety Training Methods and Evaluation Approaches to Improve Workers’ Risk Perception: A Literature Review

description: The construction industry is a large sector of the global economy and provides many jobs. Due to the nature of the industry, the workers are at a high-risk for an injury or a fatality. Construction safety training can teach workers how to avoid hazards and increase their risk perception, but current instruction methods do not seem to be lowering the rate of incident with fatality rates staying consistent throughout the years with the main cause of incident being human error. To improve current training methods and increase overall risk perception in construction workers, this paper aims to investigate different methods of conventional safety training and various techniques for measuring the effectiveness of safety training and propose approaches to improve typical construction safety training modules. The application of Virtual and Augmented reality in construction safety training is explored in this paper as well as the current methods used to train construction workers about safety. In this paper information was gathered in order to address different feedback as indicators of a worker’s risk perception.
DOI: 10.17632/y8gybd7ky4.1
title: Oyster thesis

description: Oyster thesis
DOI: 10.3886/e119702v2
title: Teachers’ Emotions during Video-based Video-based Teacher Professional Development

description: These files contain the anonymized data used to create the tables and figures found in "Exploring Teachers’ Emotions via Nonverbal Behavior during Video-based Teacher Professional Development". <br><br>Please refer to the abstract for the paper below: <br><br> Increasing research on teacher professional development (TPD) has found teachers’ self-reflection to be key for improving teaching effectiveness. Although video methodology, as often used in TPD, provides crucial insight concerning situated learning, teachers are often reticent to participate in TPD protocols due to discomfort over being videotaped. This longitudinal study explored emotion-related behaviors by assessing the nonverbal expressions exhibited by teachers during a 1-year video-based TPD program highlighting salient contributors to productive classroom dialogue. Six teachers were observed regarding bodily motion, facial expression, and eye contact, with results obtained across four workshops coded according to five types of emotions. The emotions of shame, defensiveness, and distraction appeared more often than did laughter and surprise, with the negative emotions found to decrease over time. This study highlights the importance of longitudinally evaluating teachers’ emotional expressions during video-based TPD activities and continued efforts to encourage teacher participation in these pedagogical training opportunities.
DOI: 10.5281/zenodo.3874571
title: Dataset: On the Aggregation and Nucleation Mechanism of the Monoclonal Antibody Anti-CD20 Near Liquid- Liquid Phase Separation (LLPS)

description: Dataset related to the paper: Pantuso et al., On the Aggregation and Nucleation Mechanism of the Monoclonal Antibody Anti-CD20 Near Liquid-Liquid Phase Separation (LLPS), Scientific Reports (2020) 10:8902.
DOI: 10.6073/pasta/0399bb0a55c2b9dad78fd0b23c45492c
title: Jornada Basin LTER: Wireless meteorological station at NPP P-SMAL site: 1-hour summary data: 2013 - ongoing

description: Hourly summary data at NPP P-SMAL met station. Average/maximum/minimum air temperature; average relative humidity and wind direction; average/maximum wind speed. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP P-SMAL site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.5281/zenodo.3874570
title: Dataset: On the Aggregation and Nucleation Mechanism of the Monoclonal Antibody Anti-CD20 Near Liquid- Liquid Phase Separation (LLPS)

description: Dataset related to the paper: Pantuso et al., On the Aggregation and Nucleation Mechanism of the Monoclonal Antibody Anti-CD20 Near Liquid-Liquid Phase Separation (LLPS), Scientific Reports (2020) 10:8902.
DOI: 10.6073/pasta/03db8a5991f494973062838643ae1b7b
title: Jornada Basin LTER: Wireless meteorological station at NPP P-SMAL site: 1-second summary precipitation data: 2013 - ongoing

description: 1-second summary precipitation data at NPP P-SMAL met station. Total precipitation per second is recorded only if there is measurable precipitation. This is recorded at an automated meteorological station installed at Jornada LTER NPP P-SMAL site.. This climate station is operated by the Jornada LTER Program. IMPORTANT: Rainfall is only recorded when a bucket tip occurs on the tipping bucket rain gauge. If there is missing data due to equipment or other problems, there will be no indication of this within this dataset. The user needs to review precipitation values in the 30 minute or hourly summary datasets to determine if there are missing data in this 1 second detailed precipitation dataset. Reference the package i.d.'s knb-lter-jrn.210437026, knb-lter-jrn.210437041, and knb-lter-jrn.210437056 for the NPP P-SMAL met station 30 minute, hourly, and daily summary datasets, respectively. This is an ONGOING dataset.
DOI: 10.6073/pasta/227933ea50d712c76b828ada5297d2e8
title: Jornada Basin LTER: Wireless meteorological station at NPP P-SMAL site: Daily summary data: 2013 - ongoing

description: Daily summary data at NPP P-SMAL met station. Average/maximum/minimum air temperature; average/maximum relative humidity and wind speed and average wind direction. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP P-SMAL site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.6073/pasta/8d41b61fc4927eca454f75c4042eae9d
title: Jornada Basin LTER: Wireless meteorological station at NPP P-SMAL site: 30-minute summary data: 2013 - ongoing

description: 30-minute summary data at NPP P-SMAL met station. Average air temperature, relative humidity, wind speed and wind direction are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP P-SMAL site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.6073/pasta/f9c10672962ae061ca4ec9ba72ce49dd
title: Jornada Basin LTER: Wireless meteorological station at NPP P-SMAL site: 5-minute summary wind and air temperature data: 2013 - ongoing

description: 5-minute summary data at NPP P-SMAL met station. Average air temperature, wind speed and wind direction are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP P-SMAL site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.3886/e119702v3
title: Teachers’ Emotions during Video-based Teacher Professional Development

description: These files contain the anonymized data used to create the tables and figures found in "Exploring Teachers’ Emotions via Nonverbal Behavior during Video-based Teacher Professional Development". <br><br>Please refer to the abstract for the paper below: <br><br> Increasing research on teacher professional development (TPD) has found teachers’ self-reflection to be key for improving teaching effectiveness. Although video methodology, as often used in TPD, provides crucial insight concerning situated learning, teachers are often reticent to participate in TPD protocols due to discomfort over being videotaped. This longitudinal study explored emotion-related behaviors by assessing the nonverbal expressions exhibited by teachers during a 1-year video-based TPD program highlighting salient contributors to productive classroom dialogue. Six teachers were observed regarding bodily motion, facial expression, and eye contact, with results obtained across four workshops coded according to five types of emotions. The emotions of shame, defensiveness, and distraction appeared more often than did laughter and surprise, with the negative emotions found to decrease over time. This study highlights the importance of longitudinally evaluating teachers’ emotional expressions during video-based TPD activities and continued efforts to encourage teacher participation in these pedagogical training opportunities.
DOI: 10.5281/zenodo.3873029
title: CMIP6_BiasCorrectedData_PrecipTMaxTMin_Countrywise

description: Here we have put the bias-corrected data of precipitation, maximum temperature, and minimum temperature data in country wise format. Each zipped country file contains 13 models, and each model includes five scenarios (historical, ssp126, ssp245, ssp370, and ssp585). Inside a scenario folder, a file named PrecipData can be read as the first three columns from the 3rd row contain year month and day numbers. 1st two rows from the 3rd column represent the longitude and latitude.
DOI: 10.6073/pasta/0456e47a28809e6228b5ca4b7eaaf6a1
title: Jornada Basin LTER: Wireless meteorological station at NPP P-SMAL site: Daily average soil volumetric water content data: 2013 - ongoing

description: Daily average of 30-minute Volumetric Water Content at NPP P-SMAL met station. Collection of soil volumetric water content data at Jornada LTER NPP sites, New Mexico, supports the environmental monitoring objectives of the Jornada LTER monitoring program that look at plant-soil water dynamics. Volumetric water content, bulk electrical conductivity, soil temperature, and bulk dielectric permittivity are measured and calculated at an automated meteorological station installed at Jornada LTER NPP P-SMAL site. The daily average at 3 soil depths is calculated from measurements made every 30 minutes at 10 cm, 20 cm, and 30 cm. This is an ONGOING dataset.
DOI: 10.6073/pasta/518483e8d2328a2be7affeb55e9c9cac
title: Jornada Basin LTER: Wireless meteorological station at NPP P-SMAL site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data at NPP P-SMAL met station. Collection of soil volumetric water content data at Jornada LTER NPP sites, New Mexico, supports the environmental monitoring objectives of the Jornada LTER monitoring program that look at plant-soil water dynamics. Volumetric water content, bulk electrical conductivity, soil temperature, and bulk dielectric permittivity are measured every 30 minutes at an automated meteorological station installed at Jornada LTER NPP P-SMAL site. Measurements are made every 30 minutes at 10 cm, 20 cm, and 30 cm soil depths. This is an ONGOING dataset.
DOI: 10.21227/n573-kq73
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains the IDs of geo-tagged tweets. The tweets were captured by an on-going project deployed at https://live.rlamsal.com.np. The geolocation data was extracted from the tweets which mentioned anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location. Please note that this dataset should be solely used for non-commercial research purposes (ignore every other LICENSE category given on this page).Note: I started sharing the IDs of the tweets that contained the exact location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs (above 150+ million tweets) shared in the Coronavirus (COVID-19) Tweets Dataset.If you need the geolocation-based data starting March 20, 2020, then use the Coronavirus (COVID-19) Tweets Dataset and hydrate the IDs while adding the following condition:data = json.loads(data)if data["coordinates"]: longitude, latitude = data["coordinates"]["coordinates"]The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-april29.* will contain tweet ID and sentiment data of the tweets that were tweeted between April 28, 2020, and April 29, 2020.Why are only tweet IDs being shared? It is Twitter's content redistribution policy that restricts the sharing of tweet information other than tweet IDs and/or user IDs. Twitter wants researchers to always pull fresh data using their API. Why? Here's my opinion. Maybe, some user might want to delete a particular tweet after a couple of minute(s)/hour(s)/day(s), and if the same tweet has already been pulled and is shared on a public domain, then it might make the user/community vulnerable to many inferences coming out of the shared data.
DOI: 10.6073/pasta/7154f788c894bc6399814ed325a078f9
title: Jornada Basin LTER: Wireless meteorological station at NPP P-TOBO site: 1-hour summary data: 2013 - ongoing

description: Hourly summary data at NPP P-TOBO met station. Average/maximum/minimum air temperature; average relative humidity and wind direction; average/maximum wind speed; solar radiation; albedo. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP P-TOBO site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Solar radiation is measured at 3m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.5281/zenodo.3874306
title: Data Set Primary Studies for Agent-Based Software Testing: A Systematic Mapping Study

description: This document contains the final set of primary studies used in our systematic mapping study that has been conducted with a set of 41 selected papers regarding agent-based systems in software testing.
DOI: 10.5281/zenodo.3874307
title: Data Set Primary Studies for Agent-Based Software Testing: A Systematic Mapping Study

description: This document contains the final set of primary studies used in our systematic mapping study that has been conducted with a set of 41 selected papers regarding agent-based systems in software testing.
DOI: 10.6073/pasta/0c276080d8b3a823d744b7f96adec47c
title: Jornada Basin LTER: Wireless meteorological station at NPP P-TOBO site: 1-second summary precipitation data: 2013 - ongoing

description: 1-second summary precipitation data at NPP P-TOBO met station. Total precipitation per second is recorded only if there is measurable precipitation. This is recorded at an automated meteorological station installed at Jornada LTER NPP P-TOBO site.. This climate station is operated by the Jornada LTER Program. IMPORTANT: Rainfall is only recorded when a bucket tip occurs on the tipping bucket rain gauge. If there is missing data due to equipment or other problems, there will be no indication of this within this dataset. The user needs to review precipitation values in the 30 minute or hourly summary datasets to determine if there are missing data in this 1 second detailed precipitation dataset. Reference the package i.d.'s knb-lter-jrn.210437027, knb-lter-jrn.210437042, and knb-lter-jrn.210437057 for the NPP P-TOBO met station 30 minute, hourly, and daily summary datasets, respectively. This is an ONGOING dataset.
DOI: 10.6073/pasta/6127a199bb43e43398adad876dd5592d
title: Jornada Basin LTER: Wireless meteorological station at NPP T-EAST site: 30-minute summary data: 2013 - ongoing

description: 30-minute summary data at NPP P-TOBO met station. Average air temperature, relative humidity, wind speed, wind direction, and solar radiation are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP P-TOBO site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Solar radiation is measured at 3m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.6073/pasta/ce7c373d0b87b8945cb4476f5efc57c8
title: Jornada Basin LTER: Wireless meteorological station at NPP P-TOBO site: Daily summary data: 2013 - ongoing

description: Daily summary data at NPP P-TOBO met station. Average/maximum/minimum air temperature; average/maximum relative humidity and wind speed and average wind direction; solar radiation; albedo. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP P-TOBO site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Solar radiation is measured at 3m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.5281/zenodo.3873542
title: An index of morphological and orthographic variation at the lexical level in the Hebrew Bible and the larger Dead Sea Scrolls: Version 1

description: An index of morphological and orthographic variation at the lexical level in the Hebrew Bible and the larger Dead Sea Scrolls. Please cite the following article when referring to this dataset: Johan de Joode. 2020. "Digital Masorah: Toward an Index of Orthographic and Morphological Variation at the Lexical Level". Journal for Semitics VOL (ISSUE). https://doi.org/10.25159/2663-6573/6632. This data is also accessible on Github: https://github.com/jdejoode/orthomorphindex-JSEM
DOI: 10.5281/zenodo.3873543
title: An index of morphological and orthographic variation at the lexical level in the Hebrew Bible and the larger Dead Sea Scrolls: Version 1

description: An index of morphological and orthographic variation at the lexical level in the Hebrew Bible and the larger Dead Sea Scrolls. Please cite the following article when referring to this dataset: Johan de Joode. 2020. "Digital Masorah: Toward an Index of Orthographic and Morphological Variation at the Lexical Level". Journal for Semitics VOL (ISSUE). https://doi.org/10.25159/2663-6573/6632. This data is also accessible on Github: https://github.com/jdejoode/orthomorphindex-JSEM
DOI: 10.6073/pasta/13b4ba5c802b7205762d0579625e4027
title: Jornada Basin LTER: Wireless meteorological station at NPP P-TOBO site: Daily average soil volumetric water content data: 2013 - ongoing

description: Daily average of 30-minute Volumetric Water Content at NPP P-TOBO met station. Collection of soil volumetric water content data at Jornada LTER NPP sites, New Mexico, supports the environmental monitoring objectives of the Jornada LTER monitoring program that look at plant-soil water dynamics. Volumetric water content, bulk electrical conductivity, soil temperature, and bulk dielectric permittivity are measured and calculated at an automated meteorological station installed at Jornada LTER NPP P-TOBO site. The daily average at 3 soil depths is calculated from measurements made every 30 minutes at 10 cm, 20 cm, and 30 cm. This is an ONGOING dataset.
DOI: 10.6073/pasta/817c2c78fcbe7bda07445bb6ea120169
title: Jornada Basin LTER: Wireless meteorological station at NPP P-TOBO site: 5-minute summary wind and air temperature data: 2013 - ongoing

description: 5-minute summary data at NPP P-TOBO met station. Average air temperature, wind speed and wind direction are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP P-TOBO site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.