cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13507440
title: Dynamics of reduced genetic diversity in increasingly fragmented populations of Florida Scrub-Jays, Aphelocoma coerulescens

description: Data for "Dynamics of reduced genetic diversity in increasingly fragmented populations of Florida Scrub-Jays, Aphelocoma coerulescens" by TN Nguyen, N Chen, EJ Cosgrove, R Bowman, JW Fitzpatrick, AG Clark, 2022.<br> <br> Details in README.txt. Please contact the authors if you plan on using these data.
DOI: 10.25318/3210044901-fra
title: Production d'énergie renouvelable, Recensement de l’agriculture, 2016, inactif

description: Recensement de l’agriculture, 2011 et 2016. Exploitations agricoles déclarant la production d'énergie renouvelable sur l'exploitation, quel que soit le propriétaire, dans l'année précédant le recensement.
DOI: 10.6084/m9.figshare.19731553.v2
title: PRISMA_2020_checklist for Performance Measurement of University-Industry Collaboration in the Technology Transfer Process A Systematic Literature Review

description: PRISMA_2020_checklist for Performance Measurement of University-Industry Collaboration in the Technology Transfer Process A Systematic Literature Review
DOI: 10.5281/zenodo.6536539
title: Adopting Microservices and DevOps in the Cyber-Physical Systems Domain: A Literature Review and Case Study

description: This repository contains the artifacts for a rapid review and interview-based case study at a company. We analyzed challenges and practices related to microservices and DevOps in the context of the cyber-physical systems (CPS) domain.
DOI: 10.15482/usda.adc/1526423
title: Data from: Mobility of phosphine-susceptible and -resistant Rhyzopertha dominica (Coleoptera: Bostrichidae) and Tribolium castaneum (Coleoptera: Tenebrionidae) after exposure to controlled release materials with existing and novel active ingredients

description: Data collected by Sabita Ranabhat from early Sep 2020 - Jun 2021. It consists of two experiments: one evaluating mobility of Tribolium castaneum and Rhyzopertha dominica after exposure to differently formulated controlled release materials for 0-60 min, and a second experiment looking at median lethal time after exposure to cheesecloth treated with permethrin, deltamethrin, indoxacarb, and dinotefuran between 0-168 h. Tested strains include phosphine-resistant and phosphine-susceptible populations.
DOI: 10.5519/qd.dtd9xln6
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.34622/datarepositorium/h0rcic/pk4ctl
title: Media-sociais-MVL.tab

description: Seguidores e média de interações por post em cada mês no Facebook e Instagram do Museu Virtual da Lusofonia
DOI: 10.34622/datarepositorium/h0rcic/qh3a10
title: Media-sociais-MVL-1.tab

description: Seguidores e média de interações por post em cada mês no Facebook e Instagram do Museu Virtual da Lusofonia
DOI: 10.6084/m9.figshare.19737079
title: Source data for Figure 17 - Pt 1

description: This is the raw data for experimental dataset for Figure 17. This is to be used with https://github.com/denisecailab/minian-validation See the github repo for details.
DOI: 10.6084/m9.figshare.19737079.v1
title: Source data for Figure 17 - Pt 1

description: This is the raw data for experimental dataset for Figure 17. This is to be used with https://github.com/denisecailab/minian-validation See the github repo for details.
DOI: 10.5281/zenodo.5511980
title: Harnessing single cell RNA sequencing to identify dendritic cell types, characterize their biological states and infer their activation trajectory

description: <strong>Summary: </strong>Dendritic cells (DCs) orchestrate innate and adaptive immunity, by translating the sensing of distinct danger signals into the induction of different effector lymphocyte responses, to induce different defense mechanisms suited to face distinct types of threats. Hence, DCs are very plastic, which results from two key characteristics. First, DCs encompass distinct cell types specialized in different functions. Second, each DC type can undergo different activation states, fine-tuning its functions depending on its tissue microenvironment and the pathophysiological context, by adapting the output signals it delivers to the input signals it receives. Hence, to better understand DC biology and harness it in the clinic, we must determine which combinations of DC types and activation states mediate which functions, and how.<br> To decipher the nature, functions and regulation of DC types and their physiological activation states, one of the methods that can be harnessed most successfully is ex vivo single cell RNA sequencing (scRNAseq). However, for new users of this approach, determining which analytics strategy and computational tools to choose can be quite challenging, considering the rapid evolution and broad burgeoning of the field. In addition, awareness must be raised on the need for specific, robust and tractable strategies to annotate cells for cell type identity and activation states. It is also important to emphasize the necessity of examining whether similar cell activation trajectories are inferred by using different, complementary methods. In this chapter, we take these issues into account for providing a pipeline for scRNAseq analysis and illustrating it with a tutorial reanalyzing a public dataset of mononuclear phagocytes isolated from the lungs of naïve or tumor-bearing mice. We describe this pipeline step-by-step, including data quality controls, dimensionality reduction, cell clustering, cell cluster annotation, inference of the cell activation trajectories and investigation of the underpinning molecular regulation. It is accompanied with a more complete tutorial on Github. We anticipate that this method will be helpful for both wet lab and bioinformatics researchers interested in harnessing scRNAseq data for deciphering the biology of DCs or other cell types, and that it will contribute to establishing high standards in the field. <strong>Data: </strong> cDC1_maturation_loom_file.rds : Loom file used for RNA Velocity Analysis <br>
DOI: 10.5281/zenodo.5511979
title: Harnessing single cell RNA sequencing to identify dendritic cell types, characterize their biological states and infer their activation trajectory

description: <strong>Summary: </strong>Dendritic cells (DCs) orchestrate innate and adaptive immunity, by translating the sensing of distinct danger signals into the induction of different effector lymphocyte responses, to induce different defense mechanisms suited to face distinct types of threats. Hence, DCs are very plastic, which results from two key characteristics. First, DCs encompass distinct cell types specialized in different functions. Second, each DC type can undergo different activation states, fine-tuning its functions depending on its tissue microenvironment and the pathophysiological context, by adapting the output signals it delivers to the input signals it receives. Hence, to better understand DC biology and harness it in the clinic, we must determine which combinations of DC types and activation states mediate which functions, and how.<br> To decipher the nature, functions and regulation of DC types and their physiological activation states, one of the methods that can be harnessed most successfully is ex vivo single cell RNA sequencing (scRNAseq). However, for new users of this approach, determining which analytics strategy and computational tools to choose can be quite challenging, considering the rapid evolution and broad burgeoning of the field. In addition, awareness must be raised on the need for specific, robust and tractable strategies to annotate cells for cell type identity and activation states. It is also important to emphasize the necessity of examining whether similar cell activation trajectories are inferred by using different, complementary methods. In this chapter, we take these issues into account for providing a pipeline for scRNAseq analysis and illustrating it with a tutorial reanalyzing a public dataset of mononuclear phagocytes isolated from the lungs of naïve or tumor-bearing mice. We describe this pipeline step-by-step, including data quality controls, dimensionality reduction, cell clustering, cell cluster annotation, inference of the cell activation trajectories and investigation of the underpinning molecular regulation. It is accompanied with a more complete tutorial on Github. We anticipate that this method will be helpful for both wet lab and bioinformatics researchers interested in harnessing scRNAseq data for deciphering the biology of DCs or other cell types, and that it will contribute to establishing high standards in the field. <strong>Data: </strong> cDC1_maturation_loom_file.rds : Loom file used for RNA Velocity Analysis <br>
DOI: 10.3886/e169841
title: Code for "Building a Consumption Poverty Measure: Initial results following recommendations of a federal interagency working group"

description: Consumption is a well-being measure that is determined by a combination of resources (e.g., income, in-kind benefits, assets, debt, time) available households, their circumstances, and their preferences. In this study, we derive consumption poverty statistics using a consumption measure that includes the flow of services from owner occupied housing and vehicles and in-kind transfers. The base data are from the U.S. Consumer Expenditure Survey Interview from 2015 through 2020. The consumption poverty rate (using an absolute threshold anchored to the 2015 relative consumption poverty rate) declines from 16.8 percent in 2015 to 11.5 percent in 2020.
description: U.S. Households.
DOI: 10.3886/e169841v1
title: Code for "Building a Consumption Poverty Measure: Initial results following recommendations of a federal interagency working group"

description: Consumption is a well-being measure that is determined by a combination of resources (e.g., income, in-kind benefits, assets, debt, time) available households, their circumstances, and their preferences. In this study, we derive consumption poverty statistics using a consumption measure that includes the flow of services from owner occupied housing and vehicles and in-kind transfers. The base data are from the U.S. Consumer Expenditure Survey Interview from 2015 through 2020. The consumption poverty rate (using an absolute threshold anchored to the 2015 relative consumption poverty rate) declines from 16.8 percent in 2015 to 11.5 percent in 2020.
description: U.S. Households.
DOI: 10.34740/kaggle/dsv/3602314
title: OpenBook by Botpress - Chatbot Q&A Data
DOI: 10.3886/e169141
title: "Data and Code for: Convincing the Mummy-ji: Improving Mother-in-Law Approval of Family Planning in India"

description: Mothers-in-law, especially those in South Asia, can exert significant influence over women, often even more so than women’s husbands or other household members. Using data from rural India, we first show that mothers-in-law are more likely than husbands to a) disapprove of women’s family planning use; and b) want women to have more children, particularly sons, than what women themselves want. Next, using a field experiment, we show that providing women with vouchers for subsidized family planning services not only enabled them to initiate discussions about family planning with their mothers-in-law, but also increased their mothers-in-law’s approval of family planning. <b> </b> <b> </b>
DOI: 10.3886/e169141v1
title: "Data and Code for: Convincing the Mummy-ji: Improving Mother-in-Law Approval of Family Planning in India"

description: Mothers-in-law, especially those in South Asia, can exert significant influence over women, often even more so than women’s husbands or other household members. Using data from rural India, we first show that mothers-in-law are more likely than husbands to a) disapprove of women’s family planning use; and b) want women to have more children, particularly sons, than what women themselves want. Next, using a field experiment, we show that providing women with vouchers for subsidized family planning services not only enabled them to initiate discussions about family planning with their mothers-in-law, but also increased their mothers-in-law’s approval of family planning. <b> </b> <b> </b>
DOI: 10.15151/esrf-es-810923211
title: Structural Biology at EMBL Grenoble, IBS-CIBB and IAB

description: The proposals covers a broad range of structural biology projects related to pathogen biology, host-pathogen interactions, RNA biology and structure-based drug development that are carried out by PIs at EMBL Grenoble, IBS-CIBB and IAB. The proposers have long-standing experience in the use, as well as the development of beam lines for macromolecular crystallography and have participated in successive BAG applications over the years, mostly at the ESRF but also at other synchrotrons (e.g. Soleil, Petra III, Diamond, SLS).
DOI: 10.5517/ccdc.csd.cc26rchv
title: CCDC 2048247: Experimental Crystal Structure Determination

description: Related Article: Zhiqiang Hao, Junhua Zhang, Xiaoying Zhang, Zhihong Ma, Zhangang Han, Jin Lin, Guo-Liang Lu|2022|Polyhedron|221|115869|doi:10.1016/j.poly.2022.115869
DOI: 10.3886/e169021
title: Data and Code for: How Do Federal Policy Shocks to State Spending Impact Returns to Primary and Secondary Education?

description: This study examines the impact of federal dollars spent on education. Using NIPA and IPEDS data from 2000-2017, this research will employ an event – study, panel VAR to determine the recursive impact of federal education policy on college enrollment. Specifically, this project focuses on race and gender to analyze the Elementary and Secondary Education Act, and Common Core State Standards as random shocks to federal spending. Do federal policy or state standards help educational disparities? Findings indicate decentralized policies or standards must be centrally aligned to be effective in the U.S. Improvements must be made for all demographic groups.
DOI: 10.3886/e169021v1
title: Data and Code for: How Do Federal Policy Shocks to State Spending Impact Returns to Primary and Secondary Education?

description: This study examines the impact of federal dollars spent on education. Using NIPA and IPEDS data from 2000-2017, this research will employ an event – study, panel VAR to determine the recursive impact of federal education policy on college enrollment. Specifically, this project focuses on race and gender to analyze the Elementary and Secondary Education Act, and Common Core State Standards as random shocks to federal spending. Do federal policy or state standards help educational disparities? Findings indicate decentralized policies or standards must be centrally aligned to be effective in the U.S. Improvements must be made for all demographic groups.
DOI: 10.6084/m9.figshare.19740388.v1
title: Survey instrument, Raw Data, and data in PLS format

description: The used survey questionnaire, raw data, and the data used for PLS-based analysis are provided.
DOI: 10.6084/m9.figshare.19740388
title: Survey instrument, Raw Data, and data in PLS format

description: The used survey questionnaire, raw data, and the data used for PLS-based analysis are provided.
DOI: 10.5066/p9k5bejg
title: National Water Model V2.1 retrospective for selected NWIS gage locations, (1979-2020)

description: This dataset contains modeled hourly streamflow in cubic meters per second at each of about eighteen thousand selected operational and water-quality stream gage locations. It was assembled from publicly available retrospective V2.1 National Water Model outputs (See NWM Retrospective source info). The streamflow variable was extracted from model output files and the data were reshaped to optimize read performance. The stream gage locations were derived from several ongoing USGS project gages for evaluation of streamflow, water quality, and real-time monitoring, however only National Water Model identifiers and NHDPlusV2.1 catchment outlet locations (as contained in the National Water Model output files) are used to identify model results. [...]
DOI: 10.25345/c5n29pb1r
title: MassIVE MSV000089451 - GNPS Test Dataset using experimental data
title: This dataset is used as a test to see if GNPS is able to work with the experimental data that has been provided in addition to the more standard data
DOI: 10.6084/m9.figshare.19740373.v1
title: Source data MuecklichShehzad et al 2022.xlsx

description: The Sheet contains raw data discussed and shown in Muecklich et al JID, 2022
DOI: 10.26025/1912/28663
title: Tidal dispersion in short estuaries

description: The salinity distribution of an estuary depends on the balance between the river outflow, which is seaward, and a dispersive salt flux, which is landward. The dispersive salt flux at a fixed cross-section can be divided into shear dispersion, which is caused by spatial correlations of the cross-sectionally varying velocity and salinity, and the tidal oscillatory salt flux, which results from the tidal correlation between the cross-section averaged, tidally varying components of velocity and salinity. The theoretical moving plane analysis of Dronkers and van de Kreeke (1986) indicates that the oscillatory salt flux is exactly equal to the difference between the “local” shear dispersion at a fixed location and the shear dispersion which occurred elsewhere within a tidal excursion – therefore, they refer to the oscillatory salt flux as “nonlocal” dispersion. We apply their moving plane analysis to a numerical model of a short, tidally dominated estuary and provide the first quantitative confirmation of the theoretical result that the spatiotemporal variability of shear dispersion accounts for the oscillatory salt flux. Shear dispersion is localized in space and time and is most pronounced near regions of flow separation. Notably, we find that dispersive processes near the mouth contribute significantly to the overall salt balance, especially under strong river and tidal forcing. Furthermore, while mechanisms of vertical shear dispersion produce the majority of the dispersive salt flux during neap tide and high river flow, lateral mechanisms associated with flow separation provide the dominant mode of dispersion during spring tide and low flow. Dataset used in support of manuscript "Tidal dispersion in short estuaries". The dataset includes the model output from the idealized estuary for 16 different forcing conditions, corresponding to 4 tidal conditions (weak<neap<intm<spring) and 4 river flow conditions (q01<q03<q10<q30), as well as along-channel salinity measurements in the North River (Marshfield, MA, USA) during a 2017 field campaign.
DOI: 10.6084/m9.figshare.19641519
title: Dataset FOR FAIR Project

description: Dataset of 45 patients with their pathology
DOI: 10.6084/m9.figshare.19641519.v1
title: Dataset

description: talks about cardiovascular disease
DOI: 10.5517/ccdc.csd.cc14nq2l
title: CCDC 1062589: Experimental Crystal Structure Determination

description: Related Article: Lu Liu, Qing Wan, Chen Gui, Ping He, Zujin Zhao, Zhiming Wang, Ben Zhong Tang|2022|Chem.Commun.|58|5769|doi:10.1039/D2CC00909A
DOI: 10.5517/ccdc.csd.cc2b5mkq
title: CCDC 2150363: Experimental Crystal Structure Determination

description: Related Article: Margherita Miele, Laura Castoldi, Xenia Simeone, Wolfgang Holzer, Vittorio Pace|2022|Chem.Commun.|58|5761|doi:10.1039/D2CC00886F
DOI: 10.5517/ccdc.csd.cc2b8jjp
title: CCDC 2153152: Experimental Crystal Structure Determination

description: Related Article: Hanna R. Petrosova, Olesia I. Kucheriv, Sergiu Shova, Il'ya A. Gural'skiy|2022|Chem.Commun.|58|5745|doi:10.1039/D2CC01364A
DOI: 10.5517/ccdc.csd.cc2b8jkq
title: CCDC 2153153: Experimental Crystal Structure Determination

description: Related Article: Hanna R. Petrosova, Olesia I. Kucheriv, Sergiu Shova, Il'ya A. Gural'skiy|2022|Chem.Commun.|58|5745|doi:10.1039/D2CC01364A
DOI: 10.5517/ccdc.csd.cc2b8jlr
title: CCDC 2153154: Experimental Crystal Structure Determination

description: Related Article: Hanna R. Petrosova, Olesia I. Kucheriv, Sergiu Shova, Il'ya A. Gural'skiy|2022|Chem.Commun.|58|5745|doi:10.1039/D2CC01364A
DOI: 10.5517/ccdc.csd.cc2bcdpt
title: CCDC 2155916: Experimental Crystal Structure Determination

description: Related Article: Natalia Sawicka, Chloe J. Craze, Peter N. Horton, Simon J. Coles, Emma Richards, Simon J. A. Pope|2022|Chem.Commun.|58|5733|doi:10.1039/D2CC01434C
DOI: 10.5517/ccdc.csd.cc2bcp5l
title: CCDC 2156179: Experimental Crystal Structure Determination

description: Related Article: Jiaxin Tian, Marie Cordier, Christophe Bour, Audrey Auffrant, Vincent Gandon|2022|Chem.Commun.|58|5741|doi:10.1039/D2CC01637K
DOI: 10.5517/ccdc.csd.cc2bn023
title: CCDC 2164174: Experimental Crystal Structure Determination

description: Related Article: Meng-Ying Yao, Yu-Feng Liu, Xin-Xiong Li, Guo-Ping Yang, Shou-Tian Zheng|2022|Chem.Commun.|58|5737|doi:10.1039/D2CC01051H
DOI: 10.35078/noxrd2/vh2i90
title: README research data Sbano et al.tab

description: Readme do processo de pesquisa
DOI: 10.35078/noxrd2/bsgmcd
title: Revised figures.pptx

description: Figuras relacionadas aos resultados da pesquisa
DOI: 10.6084/m9.figshare.19669278
title: Repository_Darnajoux et al_2022_JGR_BGC

description: These files represent the full dataset and the R code to reproduce the Figure and Supplementary Figure from the article "Ammonium sensitivity of biological nitrogen fixation in sulfate-reducing diazotrophs and coastal salt marsh sediments", by Romain Darnajoux, Linta Reji, Xin Rei Zhang, Katja E. Luxem, and Xinning Zhang (Princeton University, Department of Geosciences). <br>
DOI: 10.5281/zenodo.6536565
title: 3D printed photonics devices

description: This data contains the 1-D intensity measurements in xls and pdf file formats along with the device images
DOI: 10.5281/zenodo.6536564
title: 3D printed photonics devices

description: This data contains the 1-D intensity measurements in xls and pdf file formats along with the device images
DOI: 10.5281/zenodo.6536722
title: Microplastic particles in Polymesoda caroliniana

description: Messurement of Microplastic particles in Polymesoda caroliniana
DOI: 10.5281/zenodo.6536721
title: Microplastic particles in Polymesoda caroliniana

description: Messurement of Microplastic particles in Polymesoda caroliniana
DOI: 10.6084/m9.figshare.19145183
title: Computational study of nanoscale mechanical properties of Fe–Cr–Ni alloy

description: Mechanical properties of Fe–Cr–Ni alloy nanowires have been investigated using molecular dynamics simulation with embedded atom method and first principles approach. Various cases of uniaxial tension, compression and shear deformations have been performed and studied in this work. From the first principles calculations, the higher magnitudes of uniaxial and shear deformations resulted in higher probability of martensitic transformations. Before the first yielding, nanowires preserved the elastic stage and then the mechanical deformation proceeded in alternating quasi-elastic and yielding stages. The plastic behaviour was not observed in compression while both tensile and shear deformations showed apparent plastic behaviour. In shear deformation, due to the martensitic phase transformation, the plastic behaviour persisted for total strain of 0.6 which was much larger than that during tensile and compression. This validated the previous experimental observations. In the studied Fe–Cr–Ni nanowires, deformations were controlled by dislocations. Dislocation-mediated twinnings were captured by common neighbour analysis. Twin quantification showed that the twin activity increased with increasing strain rate. Twinnings originated from stacking faults led by 1/6 &lt;112&gt; Shockley partial dislocations. At elevated temperature (beyond 500 K), the materials softening happened, and 316L nanowire became more plastic under a lower stress.