cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.21710717.v1
title: Towards Innovation Measurement in the Software Industry

description: Supplement materials for "Towards Innovation Measurement in the Software Industry". The main article can be accessed at https://doi.org/10.1016/j.jss.2013.01.013.
DOI: 10.17638/datacat.liverpool.ac.uk/1977
title: Towards Understanding of the Li Ion Migration Pathways in the Lithium Aluminium Sulphides Li3AlS3 and Li4.3AlS3.3Cl0.7 via 6,7Li Solid-State Nuclear Magnetic Resonance Spectroscopy

description: Li-containing materials providing fast ion transport pathways are fundamental in Li solid electrolytes and the future of all-solid-state batteries. Understanding these pathways, which usually benefit from structural disorder and cation/anion substitution, is paramount for further developments in next-generation Li solid electrolytes. Here, we exploit a range of variable temperature 6Li and 7Li nuclear magnetic resonance approaches to determine Li ion mobility path-ways, quantify Li ion jump rates and subsequently identify the limiting factors for Li ion diffusion in Li3AlS3 and chlorine doped analogue Li4.3AlS3.3Cl0.7. Static 7Li NMR line narrowing spectra of Li3AlS3 show the existence of both mobile and immobile Li ions, the latter limiting long-range translational ion diffusion, while in Li4.3AlS3.3Cl0.7, a single type of fast-moving ion is present and responsible for the higher conductivity of this phase. 6Li-6Li exchange spectroscopy spectra of Li3AlS3 reveal that the slower moving ions hop between non-equivalent Li positions in different structural layers. The absence of the immobile ions in Li4.3AlS3.3Cl0.7, as revealed from 7Li line narrowing experiments, suggests an increased rate of ion exchange between the layers in this phase compared with Li3AlS3. Detailed analysis of spin-lattice relaxation data allows extraction of Li ion jump rates that are significantly increased for the doped material and identify Li mobility pathways in both materials to be three-dimensional. The identification of factors limiting long range translational Li diffusion and understanding the effects of structural modification (such as anion substitution) on Li ion mobility provide a framework for the further development of more highly conductive Li solid electrolytes.
DOI: 10.5281/zenodo.7423877
title: Supplementary files for the article entitled: PIEZO2 promotes cell proliferation and metastasis in colon carcinoma through the SLIT2/ROBO1/VEGFC pathway

description: All results were analyzed using the Statistical Package for the Social Sciences version 20.0 (IBM Corporation, Armonk, NY, USA). The results of Schoenfeld residuals method were analyzed using the R 4.2.2 software and survminer package.
DOI: 10.5281/zenodo.7423876
title: Supplementary files for the article entitled: PIEZO2 promotes cell proliferation and metastasis in colon carcinoma through the SLIT2/ROBO1/VEGFC pathway

description: All results were analyzed using the Statistical Package for the Social Sciences version 20.0 (IBM Corporation, Armonk, NY, USA). The results of Schoenfeld residuals method were analyzed using the R 4.2.2 software and survminer package.
DOI: 10.5281/zenodo.7428254
title: Supplementary files for the article entitled: PIEZO2 promotes cell proliferation and metastasis in colon carcinoma through the SLIT2/ROBO1/VEGFC pathway

description: All results were analyzed using the Statistical Package for the Social Sciences version 20.0 (IBM Corporation, Armonk, NY, USA). The results of Schoenfeld residuals method were analyzed using the R 4.2.2 software and survminer package.
DOI: 10.25403/upresearchdata.21360429
title: Teacher's challenges in executing alternatives to corporal punishment in secondary public schools

description: The purpose of this study was to explore the challenges faced by teachers in implementing alternatives to corporal punishment (ATCP) using two public secondary schools, in the Gauteng province, as sources of data. <br> My data set consists of verbatim transcriptions of the interviews conducted with 7 educators and 2 principals to explore the challenges they experience in the implementation of alternatives to corporal punishment. <br> This is a qualitative study, I used semi structured interviews to collect data. Thematic analysis were used to analyse data. The data was coded and themes were finally developed.
DOI: 10.5281/zenodo.7428231
title: Supplemental information Table S10, S11 and S 17 for 'The impact of differential temperatures (30°C versus 45°C) on the methanogenic community in Philippine rice field soil'

description: Supplemental information Table S10, S11, and S17 for Xin Li's PhD thesis-'The impact of differential temperatures (30°C versus 45°C) on the methanogenic community in Philippine rice field soil'
DOI: 10.5281/zenodo.7428230
title: Supplemental information Table S10, S11 and S 17 for 'The impact of differential temperatures (30°C versus 45°C) on the methanogenic community in Philippine rice field soil'

description: Supplemental information Table S10, S11, and S17 for Xin Li's PhD thesis-'The impact of differential temperatures (30°C versus 45°C) on the methanogenic community in Philippine rice field soil'
DOI: 10.4119/unibi/2967500
title: Data Publication for: Cooperative Behavior in the Workplace: Empirical Evidence from the Agent-Deed-Consequences Model of Moral Judgment

description: Moral judgment is of critical importance in the work context because of its implicit or explicit omnipresence in a wide range of work-place practices. The moral aspects of actual behaviors, intentions, and consequences represent areas of deep preoccupation, as exemplified in current corporate social responsibility programs, yet there remain ongoing debates on the best understanding of how such aspects of morality (behaviors, intentions, and consequences) interact. The ADC Model of moral judgment integrates the theoretical insights of three major moral theories (virtue ethics, deontology, and consequentialism) into a single model, which explains how moral judgment occurs in parallel evaluation processes of three different components: the character of a person (Agent-component); their actions (Deed-component); and the consequences brought about in the situation (Consequences-component). The model offers the possibility of overcoming difficulties encountered by single or dual-component theories. We designed a 2x2x2-between-subjects design vignette experiment with a Germany-wide sample of employed respondents (N=1,349) to test this model. Results showed that the Deed-component affects willingness to cooperate in the work context, which is mediated via moral judgements. These effects also varied depending on the levels of the Agent- and Consequences-component. Thereby, the results exemplify the usefulness of the ADC Model in the work context by showing how the distinct components of morality affect moral judgement.
DOI: 10.57745/k5wkhy
title: DataVerse_Animal_balanced diet.xlsx

description: AA plasma concentrations for Animal manuscript on balanced and unbalanced diets
DOI: 10.5281/zenodo.7428249
title: Company data

description: Company data for featured example in "A Network Spectral Approach to Identify Organizational Weaknesses and Assess Strategic Robustness"
DOI: 10.5281/zenodo.7428248
title: Company data

description: Company data for featured example in "A Network Spectral Approach to Identify Organizational Weaknesses and Assess Strategic Robustness"
DOI: 10.6084/m9.figshare.21665598.v1
title: LUMICAN MODULATES ADIPOCYTE FUNCTION IN OBESITY-ASSOCIATED TYPE 2 DIABETES

description: Obesity-associated type 2 diabetes (DM) leads to adipose tissue dysfunction. Lumican is a proteoglycan implicated in obesity, insulin resistance (IR), and adipocyte dysfunction. Using human visceral adipose tissue (VAT) from subjects with and without DM, we studied lumican effects on adipocyte function. Lumican was increased in VAT and adipocytes in DM. Lumican knockdown in adipocytes decreased lipolysis and improved adipogenesis and insulin sensitivity in VAT adipocytes in DM, while treatment with human recombinant lumican increased lipolysis and impaired insulin-sensitivity in an ERK-dependent manner. We demonstrate that lumican impairs adipocyte metabolism, partially via ERK signaling, and is a potential target for developing adipose tissue-targeted therapeutics in DM.
DOI: 10.5281/zenodo.7427907
title: Four-dimensional horizontal wind fields retrieved from FY4B GIIRS during typhoon Mulan (2022)

description: This dataset is the four-dimensional (time, pressure, u, v) wind fields retrieved from FY4B GIIRS observations during typhoon Mulan (2022) with a 15-minute interval.
DOI: 10.5281/zenodo.7427906
title: Four-dimensional horizontal wind fields retrieved from FY4B GIIRS during typhoon Mulan (2022)

description: This dataset is the four-dimensional (time, pressure, u, v) wind fields retrieved from FY4B GIIRS observations during typhoon Mulan (2022) with a 15-minute interval.
DOI: 10.5281/zenodo.7428386
title: Barriers, Enablers and Referral Patterns of General Practitioners, Physiotherapists, and People with Osteoarthritis to Exercise Treatments

description: An online survey was circulated to people with osteoarthritis, physiotherapists, and general practitioners in Ireland from March-September 2021. Data collected from these surveys is presented in this dataset.
DOI: 10.5281/zenodo.7428385
title: Barriers, Enablers and Referral Patterns of General Practitioners, Physiotherapists, and People with Osteoarthritis to Exercise Treatments

description: An online survey was circulated to people with osteoarthritis, physiotherapists, and general practitioners in Ireland from March-September 2021. Data collected from these surveys is presented in this dataset.
DOI: 10.34740/kaggle/dsv/4706701
title: Number of Deaths by Risk Factor
DOI: 10.5281/zenodo.5849267
title: Attributing decadal climate variability in coastal sea-level trends

description: The data produced from analysis to be published in Ocean Science Discussions, paper entitled "Attributing decadal climate variability in coastal sea-level trends". NetCDF contains the following sets of fields: 1. Indexing: An <em>index</em> and location (<em>lat, lon</em>) of the coastal grid cells, a locator index attributing each cell to Atlantic, Pacific and Indian Ocean basin, a <em>time</em> (decimal year) index. 2. NEMO model trends (<em>nemo_&lt;component&gt;_trend</em>): Rolling decadal trends at each coastal grid cell from the NEMO model run for steric, manometric (dynamic) and GRD. The sum of these components gives the equivalent to absolute sea level trend. 3. Climate and oceanographic mode indices: The rolling decadal trends in climate indices and the AMOC index calculated from the AMOC model (<em>ci_trend</em>) and their names (<em>ci_index</em>). 4. Empirical Orthogonal Function spatial pattern (<em>eof_&lt;basin&gt;_&lt;component&gt;_D</em>) and Principal Component time series (<em>eof_&lt;basin&gt;_&lt;component&gt;_PC</em>)<em> </em>of the NEMO model trends. 5. Coefficient of linear regression between PC and climate indices (<em>recon_&lt;basin&gt;_&lt;component&gt;_beta</em>) and the rolling trend time series at each grid cell from the reconstruction, sum{ci_trend*beta} (<em>recon_&lt;basin&gt;_&lt;component&gt;_trend</em>). In 4 and 5, the indices are given by basin. The total coastline is a concatenation of the Atlantic, Pacific and Indian basin data in that order. The absolute SSH is given by the sum of components. i.e. the SSH for all coastal cells in order <em>index</em>: recon_sum_trend([index(Atlantic_index); index(Pacific_index); index(Indian_index)] = ... [recon_Atlantic_manometric_trend+recon_Atlantic_steric_trend+recon_Atlantic_grd_trend; ... recon_Pacific_manometric_trend+recon_Pacific_steric_trend+recon_Pacific_grd_trend; ... recon_Indian_manometric_trend+recon_Indian_steric_trend+recon_Indian_grd_trend]
DOI: 10.5281/zenodo.7385454
title: High trophic level feedbacks on global ocean carbon uptake and marine ecosystem dynamics under climate change (Dupont et al., GBC)

description: Files used to make the analysis in the paper "High trophic level feedbacks on global ocean carbon uptake and marine ecosystem dynamics under climate change" (Dupont et al., accepted in GBC) - HTL_LTL_figures.ipynb is the python notebook in which are computed the different terms to make the figures of the paper - histrcp85.1-PISAPE-N-OW** and piCtrl2-PISAPE-N-OW** files contain the raw outputs of the one way (OW) simulation - histrcp85.1-PISAPE-N-TW* and piCtrl2-PISAPE-N-TW* files contain the raw outputs of the two way (TW) simulation - all files ending with *rmp_f.nc/ *regrid.nc/ *f20.nc are regridded files to make maps used in the paper. More details can be found in the python noteboook (briefly, dAT_* = change in active export, dDIC_*= change in dissolved inorganic carbon, dEPC200_* = change in carbon export at 200m depth, OW/TW_dBMape* = OW/TW change in small high trophic levels biomass, OW/TW_dBMmeszo* = OW/TW change in mesozooplankton biomass) - egestt2_2.nc, excrett2_2.nc and graztt2_2.nc are the outputs of egestion, excretion and grazing terms used to compute the active export (AT).
DOI: 10.5281/zenodo.7385453
title: High trophic level feedbacks on global ocean carbon uptake and marine ecosystem dynamics under climate change (Dupont et al., GBC)

description: Files used to make the analysis in the paper "High trophic level feedbacks on global ocean carbon uptake and marine ecosystem dynamics under climate change" (Dupont et al., accepted in GBC) - HTL_LTL_figures.ipynb is the python notebook in which are computed the different terms to make the figures of the paper - histrcp85.1-PISAPE-N-OW** and piCtrl2-PISAPE-N-OW** files contain the raw outputs of the one way (OW) simulation - histrcp85.1-PISAPE-N-TW* and piCtrl2-PISAPE-N-TW* files contain the raw outputs of the two way (TW) simulation - all files ending with *rmp_f.nc/ *regrid.nc/ *f20.nc are regridded files to make maps used in the paper. More details can be found in the python noteboook (briefly, dAT_* = change in active export, dDIC_*= change in dissolved inorganic carbon, dEPC200_* = change in carbon export at 200m depth, OW/TW_dBMape* = OW/TW change in small high trophic levels biomass, OW/TW_dBMmeszo* = OW/TW change in mesozooplankton biomass) - egestt2_2.nc, excrett2_2.nc and graztt2_2.nc are the outputs of egestion, excretion and grazing terms used to compute the active export (AT).
DOI: 10.6084/m9.figshare.21710759
title: Field Biogeochemistry raw data

description: Raw data for the Publication Kolzenburg et al. (2022)
DOI: 10.6084/m9.figshare.21710759.v1
title: Field Biogeochemistry raw data

description: Raw data for the Publication Kolzenburg et al. (2022)
DOI: 10.6084/m9.figshare.21130151
title: MaterialBERT for natural language processing of materials science texts

description: A BERT (Bidirectional Encoder Representations from Transformers) model, which we named “MaterialBERT”, has been generated using scientific papers in wide area of material science as a corpus. A new vocabulary list for tokenizer was generated using material science corpus. Two BERT models with different vocabulary lists for the tokenizer, one with the original one made by Google and the other newly made by the authors, were generated. Word vectors embedded during the pre-training with the two MaterialBERT models reasonably reflect the meanings of materials names in material-class clustering and in the relationship between base materials and their compounds or derivatives for not only inorganic materials but also organic materials and organometallic compounds. Fine-tuning with CoLA (The Corpus of Linguistic Acceptability) using the pre-trained MaterialBERT showed a higher score than the original BERT. The two MaterialBERTs could be also utilized as a starting point for transfer learning of a narrower domain-specific BERT.
DOI: 10.6084/m9.figshare.21130151.v2
title: MaterialBERT for natural language processing of materials science texts

description: A BERT (Bidirectional Encoder Representations from Transformers) model, which we named “MaterialBERT”, has been generated using scientific papers in wide area of material science as a corpus. A new vocabulary list for tokenizer was generated using material science corpus. Two BERT models with different vocabulary lists for the tokenizer, one with the original one made by Google and the other newly made by the authors, were generated. Word vectors embedded during the pre-training with the two MaterialBERT models reasonably reflect the meanings of materials names in material-class clustering and in the relationship between base materials and their compounds or derivatives for not only inorganic materials but also organic materials and organometallic compounds. Fine-tuning with CoLA (The Corpus of Linguistic Acceptability) using the pre-trained MaterialBERT showed a higher score than the original BERT. The two MaterialBERTs could be also utilized as a starting point for transfer learning of a narrower domain-specific BERT.
DOI: 10.6084/m9.figshare.21130151.v1
title: MaterialBERT for Natural Language Processing of Materials Science Texts

description: A BERT (Bidirectional Encoder Representations from Transformers) model, which we named “MaterialBERT,” has been generated using scientific papers in wide area of material science as a corpus. A new vocabulary list for tokenizer was generated using material science corpus. Two BERT models with different vocabulary lists for the tokenizer, one with the original one made by Google and the other newly made by the authors, were generated. Word vectors embedded during the pre-training with the two MaterialBERT models reasonably reflect the meanings of materials names in material-class clustering and in the relationship between base materials and their compounds or derivatives for not only inorganic materials but also organic materials and organometallic compounds. Fine-tuning with CoLA (The Corpus of Linguistic Acceptability) using the pre-trained MaterialBERT showed a higher score than the original BERT. The two MaterialBERTs could be also utilized as a starting point for transfer learning of a narrower domain-specific BERT.
DOI: 10.6084/m9.figshare.19085880
title: Direct feature extraction from two-dimensional X-ray diffraction images of semiconductor thin films for fabrication analysis

description: We built a workflow for the fabrication analysis of thin films by applying machine-learning (ML) techniques directly to the measurement data. This will lower the problem in cost of synthesizing and analyzing samples to improve the fabrication conditions. The workflow combines two ML techniques: non-negative matrix factorization (NMF) and variational autoencoder (VAE). The measurement data were two-dimensional X-ray diffraction of indium-gallium oxide system thin films. The thin films were fabricated by physical vapor techniques under multiple conditions. First, the workflow was applied to the data of the thin films fabricated through pulsed laser deposition as a proof of concept. We found that our workflow extracted features that represented crystallinity differences in addition to substrate differences. Second, VAE was analyzed to determine whether it could generate new data from its latent space. The latent space of the VAE, which learned the extracted features, represented the relationship between the fabrication conditions such as laser intensities and crystallinity. Third, the inference ability of the new data fabricated through sputtering was evaluated. The capability of the workflow we confirmed will support researchers in improving fabrication conditions by visually comparing various fabricated samples.
DOI: 10.6084/m9.figshare.19614424.v1
title: Tuning of Bayesian optimization for materials synthesis: simulation of the one-dimensional case

description: Materials exploration requires the optimization of a multidimensional space including the chemical composition and synthesis parameters such as temperature and pressure. Bayesian optimization has attracted attention as a method for efficient multidimensional optimization. Appropriate choices of the acquisition function and initial values of the hyperparameters of the kernel functions are essential for the Bayesian optimization of synthesis conditions in a small number of experiments. However, to date, there has been little discussion on how to tune Bayesian optimization for materials exploration, and no guidelines have been provided for materials scientists. In this study, we investigated the optimum initial values of the hyperparameters in Bayesian optimization using one-dimensional model functions that mimic actual materials syntheses. The optimal lengthscale and variance for different process windows of materials synthesis were investigated. It was shown that the use of an appropriate acquisition function and suitable initial values of the hyperparameters of the kernel functions enable the optimization of synthesis conditions in a small number of trials. These results provide insight for enabling fully automated and autonomous materials synthesis using Bayesian optimization and robotics for materials exploration.
DOI: 10.6084/m9.figshare.19614424
title: Tuning of Bayesian optimization for materials synthesis: simulation of the one-dimensional case

description: Materials exploration requires the optimization of a multidimensional space including the chemical composition and synthesis parameters such as temperature and pressure. Bayesian optimization has attracted attention as a method for efficient multidimensional optimization. Appropriate choices of the acquisition function and initial values of the hyperparameters of the kernel functions are essential for the Bayesian optimization of synthesis conditions in a small number of experiments. However, to date, there has been little discussion on how to tune Bayesian optimization for materials exploration, and no guidelines have been provided for materials scientists. In this study, we investigated the optimum initial values of the hyperparameters in Bayesian optimization using one-dimensional model functions that mimic actual materials syntheses. The optimal lengthscale and variance for different process windows of materials synthesis were investigated. It was shown that the use of an appropriate acquisition function and suitable initial values of the hyperparameters of the kernel functions enable the optimization of synthesis conditions in a small number of trials. These results provide insight for enabling fully automated and autonomous materials synthesis using Bayesian optimization and robotics for materials exploration.
DOI: 10.6084/m9.figshare.19085877
title: Direct <i>in-situ</i> temperature measurement for lamp-based heating device

description: Despite a wide variety of its practical applications, handiness, and cost-effectiveness, the advance of lamp-based heating devices is obstructed by one technical difficulty in measuring the temperature on a heated material. This difficulty originates in the combination of a polychromatic light source and a radiation thermometer that determines temperature from radiation (i.e. light). A new system developed in this study overcomes this intrinsic difficulty by measuring exclusively the radiation from the heated material, allowing us to perform the direct and <i>in-situ</i> measurement of temperature in a light-based heating device (an arc image furnace). Test measurements demonstrated the reliability of temperature measurement using the developed system as well as its promising potential for the determination of emissivity at high temperature particularly in the infrared region.