cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20356354
title: Additional file 2 of Accommodating heterogeneous missing data patterns for prostate cancer risk prediction

description: Additional file 2: R code for all 1,024 models available at https://riskcalc.org/ExtendedPBCG/ .
DOI: 10.6084/m9.figshare.20356354.v1
title: Additional file 2 of Accommodating heterogeneous missing data patterns for prostate cancer risk prediction

description: Additional file 2: R code for all 1,024 models available at https://riskcalc.org/ExtendedPBCG/ .
DOI: 10.6084/m9.figshare.20356411
title: Additional file 1 of Development of dual reporter vector system for estimating translational activity of regulatory elements

description: Additional file 1 Supplementary Tables.
DOI: 10.6084/m9.figshare.20356411.v1
title: Additional file 1 of Development of dual reporter vector system for estimating translational activity of regulatory elements

description: Additional file 1 Supplementary Tables.
DOI: 10.6084/m9.figshare.20356494.v1
title: Additional file 2 of Geospatial analysis of cesarean section in Iran (2016–2020): exploring clustered patterns and measuring spatial interactions of available health services

description: Additional file 2.
DOI: 10.6084/m9.figshare.20356494
title: Additional file 2 of Geospatial analysis of cesarean section in Iran (2016–2020): exploring clustered patterns and measuring spatial interactions of available health services

description: Additional file 2.
DOI: 10.6084/m9.figshare.20356497
title: Additional file 3 of Geospatial analysis of cesarean section in Iran (2016–2020): exploring clustered patterns and measuring spatial interactions of available health services

description: Additonal file 3.
DOI: 10.6084/m9.figshare.20356497.v1
title: Additional file 3 of Geospatial analysis of cesarean section in Iran (2016–2020): exploring clustered patterns and measuring spatial interactions of available health services

description: Additonal file 3.
DOI: 10.6084/m9.figshare.20356521.v1
title: Additional file 1 of Maternal and neonatal safety outcomes after SAR-CoV-2 vaccination during pregnancy: a systematic review and meta-analysis

description: Additional file 1: Supplemental Figure 1. The effect of Mido(L)-ATRA on the content of Annexin V+ cells. HL-60 cells were treated with 0.25 μM modistaurin (M(L)) and/or 0.1 μM ATRA for 6 d. HL-60Res and U937 cells were treated with 0.1 μM modistaurin (M(L)) and/or 1 μM ATRA for 12 and 8 d, respectively. (A) The column graph of the content of Annexin V+ cells in three cell lines. Each value represents the mean ± SD of three independent measurements. (B) Representative scattered plotgrams of Annexin V expression. Results were representative among three independent experiments. Supplemental Figure 2. The effect of Mido(H)-ATRA on the content of CD11b+ cells. Cells were treated with 0.5 μM midostaurin (M(H)) and/or ATRA for 2 d. (A) The column graph of CD11b expression in three cell lines. Each value represents the mean ± SD of three independent measurements. ***P&lt;0.005, versus DMSO-treated cells. (B) Representative histograms of CD11b expression with high dose midostaurin and/or ATRA. Results were representative among three independent experiments. Supplemental Figure 3. Most membranes were cut prior to hybridization. Original blots of the immunoblot detection shown in Fig 2A-Fig 2B, Fig 3D, Fig 4A-Fig 4C, Fig 5A and Fig 5E.
DOI: 10.6084/m9.figshare.20356521
title: Additional file 1 of Maternal and neonatal safety outcomes after SAR-CoV-2 vaccination during pregnancy: a systematic review and meta-analysis

description: Additional file 1: Supplemental Figure 1. The effect of Mido(L)-ATRA on the content of Annexin V+ cells. HL-60 cells were treated with 0.25 μM modistaurin (M(L)) and/or 0.1 μM ATRA for 6 d. HL-60Res and U937 cells were treated with 0.1 μM modistaurin (M(L)) and/or 1 μM ATRA for 12 and 8 d, respectively. (A) The column graph of the content of Annexin V+ cells in three cell lines. Each value represents the mean ± SD of three independent measurements. (B) Representative scattered plotgrams of Annexin V expression. Results were representative among three independent experiments. Supplemental Figure 2. The effect of Mido(H)-ATRA on the content of CD11b+ cells. Cells were treated with 0.5 μM midostaurin (M(H)) and/or ATRA for 2 d. (A) The column graph of CD11b expression in three cell lines. Each value represents the mean ± SD of three independent measurements. ***P&lt;0.005, versus DMSO-treated cells. (B) Representative histograms of CD11b expression with high dose midostaurin and/or ATRA. Results were representative among three independent experiments. Supplemental Figure 3. Most membranes were cut prior to hybridization. Original blots of the immunoblot detection shown in Fig 2A-Fig 2B, Fig 3D, Fig 4A-Fig 4C, Fig 5A and Fig 5E.
DOI: 10.6084/m9.figshare.20356570
title: Additional file 1 of A Southeast Asian expert consensus on the management of major depressive disorder with suicidal behavior in adults under 65 years of age

description: Additional file 1: Supplementary information. Ratings of clinical scenario for achieving consensus.
DOI: 10.6084/m9.figshare.20356570.v1
title: Additional file 1 of A Southeast Asian expert consensus on the management of major depressive disorder with suicidal behavior in adults under 65 years of age

description: Additional file 1: Supplementary information. Ratings of clinical scenario for achieving consensus.
DOI: 10.6084/m9.figshare.20356606
title: Additional file 1 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 1: Table S1. Bridge markers between Cross A and Cross B_1.
DOI: 10.6084/m9.figshare.20356606.v1
title: Additional file 1 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 1: Table S1. Bridge markers between Cross A and Cross B_1.
DOI: 10.6084/m9.figshare.20356609
title: Additional file 2 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 2: Table S2. Primer information.
DOI: 10.6084/m9.figshare.20356609.v1
title: Additional file 2 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 2: Table S2. Primer information.
DOI: 10.6084/m9.figshare.20356618
title: Additional file 4 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 4: Table S4. Marker information from GRAS-Di.
DOI: 10.6084/m9.figshare.20356621
title: Additional file 5 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 5 :Table S5. Results of local BLAST with tartary buckwheat genome.
DOI: 10.6084/m9.figshare.20356612
title: Additional file 3 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 3: Table S3. Results of local BLAST.
DOI: 10.6084/m9.figshare.20356612.v1
title: Additional file 3 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 3: Table S3. Results of local BLAST.
DOI: 10.6084/m9.figshare.20356618.v1
title: Additional file 4 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 4: Table S4. Marker information from GRAS-Di.
DOI: 10.6084/m9.figshare.20356621.v1
title: Additional file 5 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 5 :Table S5. Results of local BLAST with tartary buckwheat genome.
DOI: 10.6084/m9.figshare.20356624
title: Additional file 6 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 6: Table S6. Gene list of tartary buckweat which located within 200 kb up and down from the homologous region of qMT3_RCK_STS1.
DOI: 10.6084/m9.figshare.20356627
title: Additional file 7 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 7: Table S7. World buckwheat germplasms used in this study.
DOI: 10.6084/m9.figshare.20356627.v1
title: Additional file 7 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 7: Table S7. World buckwheat germplasms used in this study.
DOI: 10.6084/m9.figshare.20356624.v1
title: Additional file 6 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 6: Table S6. Gene list of tartary buckweat which located within 200 kb up and down from the homologous region of qMT3_RCK_STS1.
DOI: 10.6084/m9.figshare.20356630
title: Additional file 8 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 8: Table S8. Segregation of flower morphology.
DOI: 10.6084/m9.figshare.20356630.v1
title: Additional file 8 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 8: Table S8. Segregation of flower morphology.
DOI: 10.6084/m9.figshare.20356633
title: Additional file 9 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 9: Table S9. Summary of the reference databases.
DOI: 10.6084/m9.figshare.20356633.v1
title: Additional file 9 of Genetic basis of maturity time is independent from that of flowering time and contributes to ecotype differentiation in common buckwheat (Fagopyrum esculentum Moench)

description: Additional file 9: Table S9. Summary of the reference databases.
DOI: 10.34740/kaggle/ds/2357495
title: Italy Residents Trends 2030 vs. 2022
DOI: 10.5281/zenodo.6880840
title: Technology transfer from Nordic capital parenting companies to Lithuanian and Estonian subsidiaries or joint capital com-panies: the analysis of the obtained primary data

description: Scientific literature describes various factors influencing knowledge transfer and successful adoption, assimilation, transformation, and exploitation. These four components are mostly related to the absorptive capacity of the company. However, more factors influence both developments of innovations or patents and the lack of ability to use external and internal information (knowledge).<strong> </strong>Using external knowledge is often associated with previous experience or even a point of view towards investment in innovation or developing patents. Thus, the companies might be divided into innovators and imitators. The research addresses several problems (questions). What external factors are influencing knowledge transfer and further development of innovation? What factors are influencing absorptive capacity? What factors are essential in cooperation and knowledge transfer to switch from a linear to a circular economy? To collect data, a computer-assisted telephone interviewing method was used. The survey was addressed to subsidiaries, joint companies, Lithuanian-Nordic, Estonian-Nordic capital companies, or companies in close collaboration with the Nordic countries. 158 companies from Estonia and Lithuania agreed to answer all questions. The survey involves companies of various sizes and ages from different business sectors. Reliability was denoted as Cronbach's alpha has been estimated. KMO test was used to measure whether data is suitable for principal component analysis. Additionally, PCA was performed. PCA reduced the number of variables into an extracted number of components. The separate row of the component defined a linear composite of the component score that would be the expected value of associated variable. The data set may be used to develop interlinkages among the research mentioned above questions, and results of introducing innovation, the company's size, and age might be used as control variables. The article aims to analyze factors determining innovation development and their interlinkages while technology is transferred from Nordic parenting companies to the subsidiaries. The article's results contribute to the interdisciplinary knowledge transfer, innovations, and internationalization field.
DOI: 10.5281/zenodo.6880839
title: Technology transfer from Nordic capital parenting companies to Lithuanian and Estonian subsidiaries or joint capital com-panies: the analysis of the obtained primary data

description: Scientific literature describes various factors influencing knowledge transfer and successful adoption, assimilation, transformation, and exploitation. These four components are mostly related to the absorptive capacity of the company. However, more factors influence both developments of innovations or patents and the lack of ability to use external and internal information (knowledge).<strong> </strong>Using external knowledge is often associated with previous experience or even a point of view towards investment in innovation or developing patents. Thus, the companies might be divided into innovators and imitators. The research addresses several problems (questions). What external factors are influencing knowledge transfer and further development of innovation? What factors are influencing absorptive capacity? What factors are essential in cooperation and knowledge transfer to switch from a linear to a circular economy? To collect data, a computer-assisted telephone interviewing method was used. The survey was addressed to subsidiaries, joint companies, Lithuanian-Nordic, Estonian-Nordic capital companies, or companies in close collaboration with the Nordic countries. 158 companies from Estonia and Lithuania agreed to answer all questions. The survey involves companies of various sizes and ages from different business sectors. Reliability was denoted as Cronbach's alpha has been estimated. KMO test was used to measure whether data is suitable for principal component analysis. Additionally, PCA was performed. PCA reduced the number of variables into an extracted number of components. The separate row of the component defined a linear composite of the component score that would be the expected value of associated variable. The data set may be used to develop interlinkages among the research mentioned above questions, and results of introducing innovation, the company's size, and age might be used as control variables. The article aims to analyze factors determining innovation development and their interlinkages while technology is transferred from Nordic parenting companies to the subsidiaries. The article's results contribute to the interdisciplinary knowledge transfer, innovations, and internationalization field.
DOI: 10.25430/researchdata.cab.unipd.it.00000655
title: Multiple exhumation episodes during the Cenozoic Tibetan Plateau build-up
DOI: 10.5281/zenodo.6880890
title: Radio-frequency C-V measurements with subattofarad sensitivity: data and analysis script

description: The attached files include: QCoDeS database containing all of the raw data underlying the results presented in the publication "Radio-frequency CV measurements with subattofarad sensitivity" by F.K. Malinowski at al. published in Physical Review Applied in 2022 Jupyter Notebook file with Python scripts, that processes the raw data and outputs the figures embedded in the publication (except for the schematics of the devices and the rf circuitry).
DOI: 10.5281/zenodo.5534233
title: Radio-frequency C-V measurements with subattofarad sensitivity: data and analysis script

description: The attached files include: QCoDeS database containing all of the raw data underlying the results presented in the publication "Radio-frequency CV measurements with subattofarad sensitivity" by F.K. Malinowski at al. published in Physical Review Applied in 2022 Jupyter Notebook file with Python scripts, that processes the raw data and outputs the figures embedded in the publication (except for the schematics of the devices and the rf circuitry).
DOI: 10.25914/ynmw-et66
title: Anglo-Australian Telescope (AAT) data archive
DOI: 10.6084/m9.figshare.17060144
title: Soil carbon increase with straw returning: New evidence from soil extracellular enzymes

description: Straw returning is an effective practice to sequester soil carbon in agricultural soils. However, the response of soil extracellular enzyme activities (EEAs) to straw returning and their linkages to soil carbon pools remain poorly understood. Here, we present a global meta-analysis on the effect of straw returning on soil hydrolytic carbon-acquiring (<em>C-acq</em>) EEAs and their relationships with soil carbon pools in agricultural ecosystems. On average, straw returning increased <em>C-acq</em> EEAs by 23.2%, soil microbial biomass carbon (MBC) content by 29.2%, and soil organic carbon (SOC) storage by 21.1%, relative to no straw returning. The effect of straw returning on MBC content and SOC storage is best explained by their positive relationships with <em>C-acq</em> EEAs: when straw returning strongly stimulates <em>C-acq</em> EEAs, MBC content and SOC storage increase; conversely, when straw returning weakly stimulates <em>C-acq</em> EEAs, MBC content and SOC storage decline. Furthermore, soil pH and straw amount best predicted the straw returning effects on <em>C-acq</em> EEAs. Our results provide the first evidence that <em>C-acq</em> EEAs are linked to soil carbon increases under straw returning in agricultural ecosystems. Incorporating the soil microbial effects of straw returning revealed here on agricultural soils into Earth system models could improve predictions of soil carbon dynamics.
DOI: 10.6084/m9.figshare.17060144.v2
title: Soil carbon increase with straw returning: New evidence from soil extracellular enzymes

description: Straw returning is an effective practice to sequester soil carbon in agricultural soils. However, the response of soil extracellular enzyme activities (EEAs) to straw returning and their linkages to soil carbon pools remain poorly understood. Here, we present a global meta-analysis on the effect of straw returning on soil hydrolytic carbon-acquiring (<em>C-acq</em>) EEAs and their relationships with soil carbon pools in agricultural ecosystems. On average, straw returning increased <em>C-acq</em> EEAs by 23.2%, soil microbial biomass carbon (MBC) content by 29.2%, and soil organic carbon (SOC) storage by 21.1%, relative to no straw returning. The effect of straw returning on MBC content and SOC storage is best explained by their positive relationships with <em>C-acq</em> EEAs: when straw returning strongly stimulates <em>C-acq</em> EEAs, MBC content and SOC storage increase; conversely, when straw returning weakly stimulates <em>C-acq</em> EEAs, MBC content and SOC storage decline. Furthermore, soil pH and straw amount best predicted the straw returning effects on <em>C-acq</em> EEAs. Our results provide the first evidence that <em>C-acq</em> EEAs are linked to soil carbon increases under straw returning in agricultural ecosystems. Incorporating the soil microbial effects of straw returning revealed here on agricultural soils into Earth system models could improve predictions of soil carbon dynamics.
DOI: 10.6084/m9.figshare.17060144.v1
title: Soil carbon increase with straw returning: New evidence from soil extracellular enzymes

description: Straw returning is an effective practice to sequester soil carbon in agricultural soils. However, the response of soil extracellular enzyme activities (EEAs) to straw returning and their linkages to soil carbon pools remain poorly understood. Here, we present a global meta-analysis on the effect of straw returning on soil hydrolytic carbon-acquiring (<em>C-acq</em>) EEAs and their relationships with soil carbon pools in agricultural ecosystems. On average, straw returning increased <em>C-acq</em> EEAs by 23.2%, soil microbial biomass carbon (MBC) content by 29.2%, and soil organic carbon (SOC) storage by 21.1%, relative to no straw returning. The effect of straw returning on MBC content and SOC storage is best explained by their positive relationships with <em>C-acq</em> EEAs: when straw returning strongly stimulates <em>C-acq</em> EEAs, MBC content and SOC storage increase; conversely, when straw returning weakly stimulates <em>C-acq</em> EEAs, MBC content and SOC storage decline. Furthermore, soil pH and straw amount best predicted the straw returning effects on <em>C-acq</em> EEAs. Our results provide the first evidence that <em>C-acq</em> EEAs are linked to soil carbon increases under straw returning in agricultural ecosystems. Incorporating the soil microbial effects of straw returning revealed here on agricultural soils into Earth system models could improve predictions of soil carbon dynamics.
DOI: 10.5281/zenodo.6453023
title: Classification of tropical cyclone containing images using a convolutional neural network: performance and sensitivity to the learning dataset

description: NXTensor extraction library, experiment code, tropical cyclone and background images and their metadata generated from the meterological reanalysis ERA5 and MERRA-2 according to the HURDAT2 cyclone tracks. Version specifications: NXTensor: v0.3.3.10 Experiment code: v2.0.3 Image sets: v1
DOI: 10.5281/zenodo.6564304
title: API Description-Based Conformance Assessment of Architectural Design Decision: Dataset and Code

description: This is the dataset and related code artifact for the article "API Description-Based Conformance Assessment of Architectural Design Decision". <strong>Abstract of the article:</strong> Microservice APIs are often designed based on Domain-Driven Design. It can be challenging to judge the quality<br> of the relation between such a design and the implemented API, especially when facing frequent releases and changes in an API and its design models. Conformance assessment aims to improve software quality by bridging the gap between design and implementation. However, manual conformance assessment is time-intensive and error prone. This paper proposes a novel approach for automated conformance assessment of API designs in relation to API design decisions. Our approach aims to provide<br> the first fully automated conformance assessment approach based solely on the code of API Descriptions such as OpenAPI. We<br> applied and exemplified our approach for checking conformance to the patterns and practices in an API design decision for mapping links in a system’s domain model to API representations. The total accuracy score (F1-measure) for decision option identification in our multi-case study for this decision is 97.22%.