cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3885695
title: Planilha desenvolvida para o artigo intitulado "APLICAÇÃO DA MICROMEDIÇÃO PARA RACIONALIZAÇÃO DO USO DA ÁGUA EM CAMPUS UNAPLICAÇÃO DA MICROMEDIÇÃO PARA RACIONALIZAÇÃO DO USO DA ÁGUA EM CAMPUS UNIVERSITÁRIOIVERSITÁRIO"

description: Segunda versão da planilhas desenvolvidas para o artigo intitulado “APLICAÇÃO DA MICROMEDIÇÃO PARA RACIONALIZAÇÃO DO USO DA ÁGUA EM CAMPUS UNIVERSITÁRIO”. Ele foi submetido no CIEA - CONGRESSO INTERNACIONAL DE ENGENHARIA AMBIENTAL. 1. Na planilha “Banco de dados_R6” estão todos os dados usados na pesquisa.
description: A realização do estudo permitiu evidenciar quais equipamentos usam mais água no seu funcionamento, aponta a necessidade de substituição destes por novos equipamentos hidráulicos economizadores, além de expor a indispensabilidade de manutenções preditivas e corretivas mais frequentes para a obtenção de índices de uso de água menores do que os observados.
DOI: 10.6084/m9.figshare.13272052.v1
title: Additional file 1 of Do nuclear magnetic resonance (NMR)-based metabolomics improve the prediction of pregnancy-related disorders? Findings from a UK birth cohort with independent validation

description: Additional file 1: Table S1. A list of the nuclear magnetic resonance (NMR)-derived metabolomic traits used in this study. Table S2. The retained predictors for the risk factor prediction models for all pregnancy-related disorders. Table S3. The retained predictors for the metabolomic prediction models for all pregnancy-related disorders. Table S4. The retained predictors for the combined risk factor and metabolomic prediction models for all pregnancy-related disorders. Table S5. The predictors that were retained in the combined risk factor and metabolite model for all pregnancy-related disorders. Table S6. The area under the curve and 95% confidence intervals for each prediction model for each pregnancy-related disorder. Table S7. A sensitivity analysis on the association between body mass index (BMI) and each pregnancy-related disorder in the UK Better Eating and Activity Trial (UPBEAT), the Born in Bradford study and the Born in Bradford study women who had a BMI ≥30 kg/m2. Table S8. The area under the curve and 95% confidence intervals for prediction models trained in one pregnancy-related disorder and tested for another pregnancy-related disorder. Table S9. The area under the curve and 95% confidence intervals for prediction models trained in Born in Bradford and validated at an earlier timepoint in the UK Pregnancies Better Eating and Activity Trial. Table S10. The correlation between metabolites measured in the UK Pregnancies Better Eating and Activity Trial at 15-18+6 weeks gestation and 27-28+8 weeks gestation.
DOI: 10.6084/m9.figshare.13272055
title: Additional file 1 of A fixed reconstruction of fully edentulous patients with immediate function using an apically tapered implant design: a retrospective clinical study

description: Additional file 1.
DOI: 10.6084/m9.figshare.13272052
title: Additional file 1 of Do nuclear magnetic resonance (NMR)-based metabolomics improve the prediction of pregnancy-related disorders? Findings from a UK birth cohort with independent validation

description: Additional file 1: Table S1. A list of the nuclear magnetic resonance (NMR)-derived metabolomic traits used in this study. Table S2. The retained predictors for the risk factor prediction models for all pregnancy-related disorders. Table S3. The retained predictors for the metabolomic prediction models for all pregnancy-related disorders. Table S4. The retained predictors for the combined risk factor and metabolomic prediction models for all pregnancy-related disorders. Table S5. The predictors that were retained in the combined risk factor and metabolite model for all pregnancy-related disorders. Table S6. The area under the curve and 95% confidence intervals for each prediction model for each pregnancy-related disorder. Table S7. A sensitivity analysis on the association between body mass index (BMI) and each pregnancy-related disorder in the UK Better Eating and Activity Trial (UPBEAT), the Born in Bradford study and the Born in Bradford study women who had a BMI ≥30 kg/m2. Table S8. The area under the curve and 95% confidence intervals for prediction models trained in one pregnancy-related disorder and tested for another pregnancy-related disorder. Table S9. The area under the curve and 95% confidence intervals for prediction models trained in Born in Bradford and validated at an earlier timepoint in the UK Pregnancies Better Eating and Activity Trial. Table S10. The correlation between metabolites measured in the UK Pregnancies Better Eating and Activity Trial at 15-18+6 weeks gestation and 27-28+8 weeks gestation.
DOI: 10.6084/m9.figshare.13272055.v1
title: Additional file 1 of A fixed reconstruction of fully edentulous patients with immediate function using an apically tapered implant design: a retrospective clinical study

description: Additional file 1.
DOI: 10.14457/tu.the.2019.761
title: Marketing-operations interface: a study of compound bullwhip effect and information sharing in supply chain

description: The inquiry of how the interface between marketing and operations would affect the supply chain performance in term of bullwhip effect is addressed in this dissertation through three separate but correlated studies.In the first study, the bullwhip effect is analytically measured in a simple two-stage supply chain with one supplier, and one retailer who experiences a compound demand of a first-order autoregressive process and a stochastic retail price. Our study demonstrated that the bullwhip effect can be, under certain conditions, stronger or weaker than the case where the price is not considered. In addition, quantitative analysis is also performed to study the behavior of the bullwhip effect. It is found that the magnitude of both lead time and autocorrelation coefficient impacts on bullwhip effect has been affected by the appearance of price and its interactions with demand.In the second study, the bullwhip effect is analytically measured for a two-stage supply chain, including a manufacturer, and a retailer who serves a marketdemand. The demand is assumed to be a combination of a first-order autoregressive process, a retail price (set by the retailer), and an asymmetric customer reference price (representing for customer valuation). Furthermore, a series of existence conditions of the bullwhip effect with positively, negatively, and no correlated demands is identified by examining the compound effect of the autocorrelation, retail and reference prices, as well as the demand-price interactions. In addition, it is also found that the bullwhip effect in the case of demand with retail and reference prices is eitherstronger or weaker than that of demand without these prices in several scenarios. The finding indicates that an under- or over-estimating issue may arise if the retail and reference prices are not properly considered. Moreover, the behaviors of the bullwhip effect with respect to different model parameters are both analytically and numerically explored. The results offer some valuable insights, which lead to useful managerial implications.In the third study, value of information sharing is measured in a two-stage supply chain consisting of a manufacturer and two retailers. These retailers arecompeting in a market with multiple customer segments, including loyal, switching, and stockpiling ones, by using their price promotions. With this setting, the value of information sharing has been quantified under no information, information with and without disclosure agreement. It is found that while the information sharing is always valuable for the non-disclosure agreement, this might not be the case for a disclosure one. In addition, conditions, where information sharing with disclosure agreement is not beneficial, have been analytically determined. Then, this measurement under varying model’s parameters are explored both numerically and analytically. The results provide useful managerial insights on when an information sharing agreementoffers the most benefit.
DOI: 10.14457/tu.the.2019.762
title: การศึกษาเปรียบเทียบความเกี่ยวข้องกับมูลค่ากิจการ (value relevance) ของกำไรทางบัญชีแต่ละประเภท

description: การค้นคว้าอิสระนี้มีวัตถุประสงค์เพื่อศึกษาเปรียบเทียบความเกี่ยวข้องกับมูลค่ากิจการของกำไรทางบัญชีทั้ง 5 ประเภท อันได้แก่ 1) กำไรขั้นต้น 2) กำไรก่อนดอกเบี้ย ภาษี ค่าเสื่อมราคาและค่าตัดจำหน่าย 3) กำไรก่อนดอกเบี้ยและภาษี 4) กำไรสุทธิ และ 5) กำไรขาดทุนเบ็ดเสร็จ รวมถึงศึกษาเพิ่มเติมเกี่ยวกับองค์ประกอบของกำไรขาดทุนเบ็ดเสร็จอื่นด้วย การศึกษานี้ใช้การวิเคราะห์สมการถดถอยเชิงพหุคูณวิเคราะห์ข้อมูลของกิจการที่จดทะเบียนในตลาดหลักทรัพย์แห่งประเทศไทยในทุกกลุ่มอุตสาหกรรม ระหว่างปี พ.ศ. 2554 ถึง 2561 รวม 8 ปี ทำให้ได้กลุ่มตัวอย่างจำนวน 3,311 ตัวอย่าง โดยได้วิเคราะห์ข้อมูลทั้งในภาพรวมและแยกรายอุตสาหกรรม รวมถึงศึกษาผลกระทบจากความล่าช้าด้านเวลาและเสถียรภาพทางการเมืองที่มีต่อความเกี่ยวข้องกับมูลค่ากิจการด้วยผลการศึกษาพบว่า กำไรทางบัญชีทั้ง 5 ประเภทล้วนมีความสัมพันธ์ในทิศทางเดียวกับราคาหลักทรัพย์ โดยรายการที่มีความเกี่ยวข้องกับมูลค่ากิจการมากที่สุด คือ กำไรสุทธิ และกำไรขาดทุนเบ็ดเสร็จ อีกทั้งยังพบว่ากำไรสุทธิมีความเกี่ยวข้องกับมูลค่ากิจการมากที่สุดในอุตสาหกรรมส่วนใหญ่ ยกเว้นกลุ่มอุตสาหกรรมอสังหาริมทรัพย์และก่อสร้างและกลุ่มอุตสาหกรรมทรัพยากรที่พบว่ากำไรขาดทุนเบ็ดเสร็จมีความเกี่ยวข้องกับมูลค่ากิจการมากที่สุด นอกจากนี้ ผลการศึกษายังพบว่า วันที่กำไรทางบัญชีทุกประเภทมีความเกี่ยวข้องกับมูลค่ากิจการมากที่สุด คือ ณ วันที่ภายหลังวันสิ้นสุดการนำส่งงบการเงิน 16 วัน และเสถียรภาพทางการเมืองมีส่วนสนับสนุนในเชิงบวกต่อความสัมพันธ์ระหว่างราคาหลักทรัพย์และกำไรทางบัญชีทุกประเภท
DOI: 10.21227/nb88-4136
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 90+ different keywords and hashtags that are commonly used while referencing the pandemic. 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.The paper associated with this dataset is available here: Design and analysis of a large-scale COVID-19 tweets dataset-------------------------------------Related: Coronavirus (COVID-19) Tweets Sentiment Trend (Global), Coronavirus (COVID-19) Tweets Dataset and Tweets Originating from India During COVID-19 Lockdowns 1, 2, 3, 4-------------------------------------Below is the quick overview of this dataset.— Dataset name: GeoCOV19Tweets Dataset— Number of tweets : 267,314 tweets— Coverage : Global— Language : English (EN)— Dataset usage terms : By using this dataset, you agree to (i) use the content of this dataset and the data generated from the content of this dataset for non-commercial research only, (ii) remain in compliance with Twitter's Developer Policy and (iii) cite the following paper:Lamsal, R. Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence (2020). https://doi.org/10.1007/s10489-020-02029-z— Primary dataset : Coronavirus (COVID-19) Tweets Dataset (COV19Tweets Dataset)— Dataset updates : Everyday— Active keywords and hashtags: keywords.tsvPlease visit this page (primary dataset) for details regarding the collection date and time (and other notes) of each CSV file present in this dataset.
DOI: 10.6084/m9.figshare.870121.v8
title: Measuring innovation using Fortune 500 rankings (2006-2018)

description: This is a time-series extract from Fortune 500 (2006 to 2018) showing ranking of several companies over that period. Described in a blog post linked below. This is data to show a proxy of innovation measurement from changes in sales (which Fortune 500 measures) over time. <br> <br>This data could be used for Science Policy to indicate where in the economy innovation (in the form of rising sales) is taking place. Now updated for 2016 data. Now updated with 2018 Fortune 500 data (22.5.18).<br>Facebook continues to make moves up the F500 in 2018.
DOI: 10.6084/m9.figshare.870121.v9
title: Measuring innovation using Fortune 500 rankings (2006-2018)

description: This is a time-series extract from Fortune 500 (2006 to 2018) showing ranking of several companies over that period. Described in a blog post linked below. This is data to show a proxy of innovation measurement from changes in sales (which Fortune 500 measures) over time. <br> <br>This data could be used for Science Policy to indicate where in the economy innovation (in the form of rising sales) is taking place. Now updated for 2016 data. Now updated with 2018 Fortune 500 data (22.5.18). Updated graphic with 2020 Fortune 500 data.<br>Facebook continues to make moves up the F500 in 2018.
DOI: 10.6084/m9.figshare.870121.v10
title: Measuring innovation using Fortune 500 rankings (2006-2018)

description: This is a time-series extract from Fortune 500 (2006 to 2018) showing ranking of several companies over that period. Described in a blog post linked below. This is data to show a proxy of innovation measurement from changes in sales (which Fortune 500 measures) over time. <br> <br>This data could be used for Science Policy to indicate where in the economy innovation (in the form of rising sales) is taking place. Now updated for 2016 data. Now updated with 2018 Fortune 500 data (22.5.18). Updated graphic with 2020 Fortune 500 data.<br>Facebook continues to make moves up the F500 in 2018.
DOI: 10.6084/m9.figshare.13272332.v1
title: Resident Attrition Study Data

description: Resident attrition data - Obstetrics and gynaecology
DOI: 10.6084/m9.figshare.13272332
title: Resident Attrition Study Data

description: Resident attrition data - Obstetrics and gynaecology
DOI: 10.17632/6c56r7ngyb.5
title: Data for: Selection or drift: the population biology underlying transposon insertion sequencing experiments

description: Code to create the figures in article "Selection or drift: the population biology underlying transposon insertion sequencing experiments".
DOI: 10.5517/ccdc.csd.cc1ljfxg
title: CCDC 1475566: Experimental Crystal Structure Determination

description: Related Article: Pierre Farger, Cédric Leuvrey, Guillaume Rogez, Michel François, Pierre Rabu, Emilie Delahaye|2019|Cryst.Growth Des.|19|4264|doi:10.1021/acs.cgd.8b01725
DOI: 10.15156/bio/sh1909274.08fu
title: SH1909274.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1909275.08fu
title: SH1909275.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1909276.08fu
title: SH1909276.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1909277.08fu
title: SH1909277.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1909278.08fu
title: SH1909278.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1909279.08fu
title: SH1909279.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1909280.08fu
title: SH1909280.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1909281.08fu
title: SH1909281.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.