cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4104390
title: The Daily Life of Software Engineers during the COVID-19 Pandemic -- Replication Package

description: Following the onset of the COVID-19 pandemic and subsequent lockdowns, software engineers' daily life was disrupted and abruptly forced into remote working from home. This change deeply impacted typical working routines, affecting both well-being and productivity. Moreover, this pandemic will have long-lasting effects in the software industry, with several tech companies allowing their employees to work from home indefinitely if they wish to do so. Therefore, it is crucial to analyze and understand how a typical working day looks like when working from home and how individual activities affect software developers' well-being and productivity. We performed a two-wave longitudinal study involving almost 200 globally carefully selected software professionals, inferring daily activities with perceived well-being, productivity, and other relevant psychological and social variables. Results suggest that the time software engineers spent doing specific activities from home was similar when working in the office. (e.g., coding &gt; emails &gt; code review &gt; networking). However, we also found some meaningful mean differences. The amount of time developers spent on each activity was unrelated to their well-being, perceived productivity, and other variables. We conclude that working remotely is not per se a challenge for organizations or developers.
DOI: 10.5281/zenodo.4104389
title: The Daily Life of Software Engineers during the COVID-19 Pandemic -- Replication Package

description: Following the onset of the COVID-19 pandemic and subsequent lockdowns, software engineers' daily life was disrupted and abruptly forced into remote working from home. This change deeply impacted typical working routines, affecting both well-being and productivity. Moreover, this pandemic will have long-lasting effects in the software industry, with several tech companies allowing their employees to work from home indefinitely if they wish to do so. Therefore, it is crucial to analyze and understand how a typical working day looks like when working from home and how individual activities affect software developers' well-being and productivity. We performed a two-wave longitudinal study involving almost 200 globally carefully selected software professionals, inferring daily activities with perceived well-being, productivity, and other relevant psychological and social variables. Results suggest that the time software engineers spent doing specific activities from home was similar when working in the office. (e.g., coding &gt; emails &gt; code review &gt; networking). However, we also found some meaningful mean differences. The amount of time developers spent on each activity was unrelated to their well-being, perceived productivity, and other variables. We conclude that working remotely is not per se a challenge for organizations or developers.
DOI: 10.7298/p9wj-nk83
title: Data From: Ammonia volatilization from composting with oxidized biochar
DOI: 10.25909/mnt4-g127
title: Combined effects of climate change and the herbicide diuron on the coral Acropora millepora (NESP 2.1.6 and NESP TWQ 5.2, AIMS)
DOI: 10.25910/tp1y-2k41
title: Concordance to link IUCN Red List Threats to CPC economic sectors

description: This concordance was used to connect IUCN Red List Threat data to economic sectors, classified according to the UN Statistics Division's Central Product Classification.
description: This item was populated manually using Excel. Key assumptions are included in the header rows.
DOI: 10.6084/m9.figshare.12993071.v1
title: Agronomy_938990_master_file.csv

description: Dateset for Agronomy paper "Warming reduces net carbon gain and productivity in Medicago sativa and Festuca arundinacea"
DOI: 10.6084/m9.figshare.12993071.v2
title: Agronomy_938990_Data

description: Dateset for Agronomy paper "Warming reduces net carbon gain and productivity in Medicago sativa and Festuca arundinacea"
DOI: 10.1285/i25327518v4i1p37
title: Training Teachers as Health Promoters

description: In the context of the global changes that affect families and communities, including the current COVID-19 pandemic, today's young people face new threats to their health and most of them lack adequate nutrition, healthcare services and education. As children and adolescents spend a significant amount of their time at school (or remotely connected with teachers, as occurred in these last months of health emergency), educators have the great opportunity to positively contribute to their global growth, fostering physical, mental and social wellbeing, which has also a significant impact on students' academic achievements. Nowadays, training teachers as "health promoters" allows educational system to deal more effectively with health needs of the students, helping them in the prevention of risky behaviours (cigarette smoking, binge drinking, drug use etc). According to the recommendations provided by the World Health Organization and UNESCO, we highlight the need for pre-service and in-service teacher training on the major topics concerning young people health, as well as COVID-19 safety issues. Moreover, teachers should be trained on the most participatory and pro-active methodologies to effectively convey health-related contents in school setting, in order to trigger a personal interiorization of the knowledge acquired by the students, and to engage them in practical actions about healthy lifestyles (i.e. balanced nutrition and physical exercise, no smoking, no alcohol, no drugs). Teacher training on health topics enables educators to develop a new professional identity based on a health-centered vision, in the perspective of reducing social/health inequalities that still concern most disadvantaged children. Medical professionals and pedagogists could be appointed as available consultants respectively for training teachers on health contents and about the most effective didactic strategies useful for displaying educational interventions in school setting aimed at preventing unhealthy habits among young people. Health education should be included in scholastic curricula within scientific disciplines or treated as separate subject in extracurricular activities under direct responsibility of school staff.
DOI: 10.6084/m9.figshare.12993071
title: Vinod_Jacob_Agronomy_938990_Data

description: Dateset for Agronomy paper "Warming reduces net carbon gain and productivity in Medicago sativa and Festuca arundinacea"
DOI: 10.6084/m9.figshare.12993071.v4
title: Vinod_Jacob_Agronomy_938990_Data

description: Dateset for Agronomy paper "Warming reduces net carbon gain and productivity in Medicago sativa and Festuca arundinacea"
DOI: 10.6084/m9.figshare.12993071.v3
title: Vinod_Jacob_Agronomy_938990_Data

description: Dateset for Agronomy paper "Warming reduces net carbon gain and productivity in Medicago sativa and Festuca arundinacea"
DOI: 10.6084/m9.figshare.13109486
title: Raw data of Cr2O3 and proximate composition of diets

description: Data of Cr2O3 and composition of diets<br>
DOI: 10.6084/m9.figshare.13109486.v1
title: Raw data of Cr2O3 and proximate composition of diets

description: Data of Cr2O3 and composition of diets<br>
DOI: 10.6084/m9.figshare.13109495
title: Raw data of enzyme activity

description: enzyme activity<br>
DOI: 10.6084/m9.figshare.13109501
title: Raw data of feed and nutrient digestibility

description: feed and nutrient digestibility<br>
DOI: 10.21227/kq45-ce47
title: DeepWiPHY: Synthetic and real-world IEEE 802.11ax OFDM symbol dataset

description: This dataset is associated with the paper entitled "DeepWiPHY: Deep Learning-based Receiver Design and Dataset for IEEE 802.11ax Systems", accepted by IEEE Transactions on Wireless Communications. It has synthetic and real-word IEEE 802.11ax OFDM symbols. The synthetic dataset has around 110 million OFDM symbols and the real-world dataset has more than 14 million OFDM symbols. Our comprehensive synthetic dataset has specifically considered typical indoor channel models and RF impairments. The real-world dataset was collected under a wide range of signal-to-noise ratio (SNR) levels and at various locations in a large office. To create this real-world dataset, we built a passive sniffing-based data collection testbed with a commercial AP, a Samsung mobile phone and two USRPs.
DOI: 10.6084/m9.figshare.13109492.v1
title: Pinus sylvestris assembly (Trinity_guided) gene level information

description: Gene level data of transcriptomes assemblies of Pinus sylvestris (Trinity_guided.fa and Trinity_Lace.fa). <br>
DOI: 10.6084/m9.figshare.13102925
title: OD9 dataset part 17/28

description: 435 032 nwchem logfiles calculated thanks to the quchempedia BOINC project.DFT calculations (B3LYP / 321G)The first 184 158 molecules corresond to the recalculation of QM9 and PC9. The others are newly generated molecules with the EvoMol software.Beware the concaneted tar file is 141GB of compressed files.<br>
DOI: 10.6084/m9.figshare.13102925.v1
title: OD9 dataset part 17/28

description: 435 032 nwchem logfiles calculated thanks to the quchempedia BOINC project.DFT calculations (B3LYP / 321G)The first 184 158 molecules corresond to the recalculation of QM9 and PC9. The others are newly generated molecules with the EvoMol software.Beware the concaneted tar file is 141GB of compressed files.<br>
DOI: 10.6084/m9.figshare.13102916
title: OD9 dataset part 16/28

description: 435 032 nwchem logfiles calculated thanks to the quchempedia BOINC project.DFT calculations (B3LYP / 321G)The first 184 158 molecules corresond to the recalculation of QM9 and PC9. The others are newly generated molecules with the EvoMol software.Beware the concaneted tar file is 141GB of compressed files.<br>
DOI: 10.6084/m9.figshare.13102916.v1
title: OD9 dataset part 16/28

description: 435 032 nwchem logfiles calculated thanks to the quchempedia BOINC project.DFT calculations (B3LYP / 321G)The first 184 158 molecules corresond to the recalculation of QM9 and PC9. The others are newly generated molecules with the EvoMol software.Beware the concaneted tar file is 141GB of compressed files.<br>
DOI: 10.6084/m9.figshare.13109507
title: Supplementary Material for: The Acute Effect of Meal Timing on the Gut Microbiome and the Cardiometabolic Health of the Host: A Crossover Randomized Control Trial

description: <b><i>Purpose:</i></b> The interaction of diet with gut microbiome has been implicated in the onset of cardiovascular disease. The gut microbiome displays diurnal rhythms, which may be influenced by meal timing. <b><i>Objective:</i></b> This study aimed to investigate the effect of the timing of main meal consumption on the microbiome and cardiometabolic biomarkers of the host. <b><i>Methods:</i></b> Seventeen healthy adults randomly consumed an isocaloric diet for 7 days, twice, by alternating lunch with dinner meals, and with a 2-week washout in-between. Sixty percent of the participants’ daily energy requirements was consumed either as lunch or dinner, respectively. Meals were provided free to the participants. All fecal samples produced the last 3 days of each intervention were collected and analyzed for microbial profiling (16S rRNA gene amplicon sequencing), quantitative estimation of representative bacterial groups (qPCR) of the gut microbiome, and the output of short-chain fatty acids (SCFA) in feces. Fasted blood samples were analyzed for low-grade inflammatory biomarkers, blood lipids, insulin, and glucose levels. Cumulative energy loss in feces was measured over the collection period using bomb calorimetry. <b><i>Results:</i></b> Meal timing had no significant effects on fecal SCFA output, energy loss in feces, microbial community profiling, and bacterial species relative abundance. The absolute concentration of <i>Escherichia coli</i> was significantly higher after the large lunch intervention (<i>p</i> = 0.02). No effects on blood biomarkers of cardiometabolic health were observed. <b><i>Conclusions:</i></b> In a well-controlled study, main meal timing displayed minimal acute effects on the gut microbiome composition, its diet-related function, and blood biomarkers of cardiometabolic health.
DOI: 10.6084/m9.figshare.13109507.v1
title: Supplementary Material for: The Acute Effect of Meal Timing on the Gut Microbiome and the Cardiometabolic Health of the Host: A Crossover Randomized Control Trial

description: <b><i>Purpose:</i></b> The interaction of diet with gut microbiome has been implicated in the onset of cardiovascular disease. The gut microbiome displays diurnal rhythms, which may be influenced by meal timing. <b><i>Objective:</i></b> This study aimed to investigate the effect of the timing of main meal consumption on the microbiome and cardiometabolic biomarkers of the host. <b><i>Methods:</i></b> Seventeen healthy adults randomly consumed an isocaloric diet for 7 days, twice, by alternating lunch with dinner meals, and with a 2-week washout in-between. Sixty percent of the participants’ daily energy requirements was consumed either as lunch or dinner, respectively. Meals were provided free to the participants. All fecal samples produced the last 3 days of each intervention were collected and analyzed for microbial profiling (16S rRNA gene amplicon sequencing), quantitative estimation of representative bacterial groups (qPCR) of the gut microbiome, and the output of short-chain fatty acids (SCFA) in feces. Fasted blood samples were analyzed for low-grade inflammatory biomarkers, blood lipids, insulin, and glucose levels. Cumulative energy loss in feces was measured over the collection period using bomb calorimetry. <b><i>Results:</i></b> Meal timing had no significant effects on fecal SCFA output, energy loss in feces, microbial community profiling, and bacterial species relative abundance. The absolute concentration of <i>Escherichia coli</i> was significantly higher after the large lunch intervention (<i>p</i> = 0.02). No effects on blood biomarkers of cardiometabolic health were observed. <b><i>Conclusions:</i></b> In a well-controlled study, main meal timing displayed minimal acute effects on the gut microbiome composition, its diet-related function, and blood biomarkers of cardiometabolic health.
DOI: 10.24378/exe.2723
title: Drain blocking has limited short-term effects on greenhouse gas fluxes in a Molinia caerulea dominated shallow peatland (dataset)

description: This is the dataset used for the Gatis et al. (2020) article "Drain blocking has limited short-term effects on greenhouse gas fluxes in a Molinia caerulea dominated shallow peatland" published in Ecological Engineering.
description: Data collected and analysed in the production of the manuscript Gatis et al (2020) Drain blocking has limited short-term effects on greenhouse gas fluxes in a Molinia caerulea dominated shallow peatland Ecological Engineering. It includes net ecosystem exchange, methane, below-ground soil respiration and vegetation composition data for a pre-post, control-restored paired experiment of a restored drained Molinia caerulea dominated peatland. Requires Microsoft Excel to open.
description: The article associated with this dataset is available in ORE at http://hdl.handle.net/10871/123252
DOI: 10.24378/exe.2663
title: Calcium-Stannous Oxide Solid Solutions for Solar Devices (dataset)

description: This is the dataset used for the Taylor et al. (2020) article "Calcium-Stannous Oxide Solid Solutions for Solar Devices" published in Applied Physics Letters.
description: Database containing the relaxed atomic structure files relating to the structures modelled in the article. These atomic structure files are compatible with the VASP DFT simulation package, but can be transformed into formats usable by other first principles or empirical software packages through use of freely available converters online.
description: The article associated with this dataset is located in ORE at: http://hdl.handle.net/10871/123189
DOI: 10.6084/m9.figshare.13107953.v1
title: MAP Trial Mouth Pictures

description: Composite pictures from the two study groups of the MAP Trial.<br>(1st file) MAP Occlusal Treatment Group Mouth Pictures: Central images corresponds to jaw closure in maximal intercuspal position; lateral pictures correspond to lateral jaw motion towards each side. Upper panels correspond to the initial condition; lower pictures shows the result.Placebo group file <br> All pictures of 39 patients before and after occlusal grinding and, in selected cases, composite-resin addition.Therapy was performed in two main steps:1. Adjustment of jaw closure in centric position2. Adjustment of lateral jaw motion<br>(2nd file) MAP Placebo Group Mouth Pictures: <br>Central images corresponds to jaw closure in maximal intercuspal position; lateral pictures correspond to lateral jaw motion towards each side. As placebo therapy, occlusion was not altered.<br>
DOI: 10.6084/m9.figshare.13107953
title: MAP Trial Mouth Pictures

description: Composite pictures from the two study groups of the MAP Trial.<br>(1st file) MAP Occlusal Treatment Group Mouth Pictures: Central images corresponds to jaw closure in maximal intercuspal position; lateral pictures correspond to lateral jaw motion towards each side. Upper panels correspond to the initial condition; lower pictures shows the result.Placebo group file <br> All pictures of 39 patients before and after occlusal grinding and, in selected cases, composite-resin addition.Therapy was performed in two main steps:1. Adjustment of jaw closure in centric position2. Adjustment of lateral jaw motion<br>(2nd file) MAP Placebo Group Mouth Pictures: <br>Central images corresponds to jaw closure in maximal intercuspal position; lateral pictures correspond to lateral jaw motion towards each side. As placebo therapy, occlusion was not altered.<br>
DOI: 10.5281/zenodo.4079198
title: Study of terminological subsystems of modern school textbooks in Russian with the help of word embedding models Word2Vec and neural networks

description: The aim of the project is to analyse the inventory and functioning of scientific terms and special lexemes in textbooks for secondary schools of the Russian Federation with the help of modern methods of natural language processing and deep learning. The number of terms from different fields of knowledge that a pupil should learn during secondary school studies has never been evaluated. According to the preliminary evaluations made on the basis of the Model Basic Curriculum for General and Secondary Education in 2015 only the subject "Russian language" presupposes that a pupil finishing the 11th grade of secondary school should be able to understand, recognise and use about 1000 terms and terminological combinations. Thus, taking into account the number of school subjects, the total number of special vocabulary units studied in general education schools is measured in thousands. At the same time, the comparative characteristics of the inventory and functioning of terms in textbooks for different school subjects are not studied and remain unknown. The correlation between the terminological density of the text in school textbooks for different subjects and the place occupied by these subjects in the curriculum is not clear. The traditional way of compiling lists of scientific terms is simply by gleaning them from special texts and writing down manually. If this method is reliable in terms of intellectualisation of selection principles, it cannot be applied to large data sets and does not reflect either the frequency of use of terms, or the specificity of their syntagmatic connections, or the systemic relationship between terms. The current project is aimed at filling this gap by means of 1) creating a full-text corpus of school textbooks for 5–11 classes included in the Federal List compiled by the Ministry of Education, 2) automatic extraction, stratification, and mapping of terms with the help of distribution semantics algorithms, 3) creation and training of a deep neural network capable of predicting the subject, level of education and educational topic given a group of vector representations of terms as input. The results of the research can be of fundamental interest in the perspective of terminology science development and also have practical applications in the creation of different types of educational literature. <em>Funding: The reported study was funded by RFBR, project number 19-29-14032</em>
DOI: 10.5281/zenodo.4079197
title: Study of terminological subsystems of modern school textbooks in Russian with the help of word embedding models Word2Vec and neural networks

description: The aim of the project is to analyse the inventory and functioning of scientific terms and special lexemes in textbooks for secondary schools of the Russian Federation with the help of modern methods of natural language processing and deep learning. The number of terms from different fields of knowledge that a pupil should learn during secondary school studies has never been evaluated. According to the preliminary evaluations made on the basis of the Model Basic Curriculum for General and Secondary Education in 2015 only the subject "Russian language" presupposes that a pupil finishing the 11th grade of secondary school should be able to understand, recognise and use about 1000 terms and terminological combinations. Thus, taking into account the number of school subjects, the total number of special vocabulary units studied in general education schools is measured in thousands. At the same time, the comparative characteristics of the inventory and functioning of terms in textbooks for different school subjects are not studied and remain unknown. The correlation between the terminological density of the text in school textbooks for different subjects and the place occupied by these subjects in the curriculum is not clear. The traditional way of compiling lists of scientific terms is simply by gleaning them from special texts and writing down manually. If this method is reliable in terms of intellectualisation of selection principles, it cannot be applied to large data sets and does not reflect either the frequency of use of terms, or the specificity of their syntagmatic connections, or the systemic relationship between terms. The current project is aimed at filling this gap by means of 1) creating a full-text corpus of school textbooks for 5–11 classes included in the Federal List compiled by the Ministry of Education, 2) automatic extraction, stratification, and mapping of terms with the help of distribution semantics algorithms, 3) creation and training of a deep neural network capable of predicting the subject, level of education and educational topic given a group of vector representations of terms as input. The results of the research can be of fundamental interest in the perspective of terminology science development and also have practical applications in the creation of different types of educational literature. <em>Funding: The reported study was funded by RFBR, project number 19-29-14032</em>
DOI: 10.34644/laudatio-dev-nek37xmbbn_-vhllti3h
title: TuNiZ_17-18