cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/pp7ypym6s2.1
title: TC records from the northern sea of the Shandong Peninsula over the past 1500 years

description: Modern observational records indicate that the activity of tropical cyclone (TC) has been influenced by changes in tropical sea surface temperatures over the past century. However, due to a lack of direct observational records and the low resolution of current TC reconstructions, further investigation is needed to understand the driving factors behind TC activity. Additionally, key parameters such as TC paths and the extent of their impact remain unclear, with limited research on the characteristics of TC impacts in the northern sea of the Shandong Peninsula. In this study, we utilized sedimentary records from the muddy area to reconstruct the TC impact history in the northern sea of the Shandong Peninsula over the past 1500 years.
DOI: 10.25582/data.2020-06.2002952/2068282
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/99zr9ytgxs.1
title: Mendeley Supplementary Figures for JAAD Original Article：“Widespread atrophic papules and plaques, intermittent abdominal pain, recurrent bowel perforation, and psoas abscess in a 20-year-old man”

description: Supplemental Figures for JAAD Original Article JAAD-D-23-02706: " Widespread atrophic papules and plaques, intermittent abdominal pain, recurrent bowel perforation, and psoas abscess in a 20-year-old man ".
DOI: 10.25582/data.2020-05.1993035/2068283
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25345/c5gm8202w
title: MassIVE MSV000093118 - Profiling of pancreatic adenocarcinoma using artificial intelligence-based integration of multi-omic and computational pathology features: lipid
title: Contemporary analyses focused on a limited number of clinical and molecular features have been unable to accurately predict clinical outcomes in pancreatic ductal adenocarcinoma (PDAC). Here we describe a novel, conceptual approach and use it to analyze clinical, computational pathology, and molecular (DNA, RNA, protein, and lipid) analyte data from 74 patients with resectable PDAC. Multiple, independent, machine learning models were developed and tested on curated single and multi-omic feature/analyte panels to determine their ability to predict clinical outcomes in patients. The multi-omic models predicted recurrence with an accuracy and positive predictive value (PPV) of 0.90, 0.91, and survival of 0.85, 0.87, respectively, outperforming every single-omic model. In predicting survival, we defined a parsimonious model with only 589 multi-omic analytes that had an accuracy and PPV of 0.85. Our approach enables discovery of parsimonious biomarker panels with similar predictive performance to that of larger and resource consuming panels and thereby has a significant potential to democratize precision cancer medicine worldwide.
DOI: 10.17632/2hwx9x2938.1
title: Supplemental Materials for “Population Sociodemographic and Geographic Factors Associated with Dermatologist Distribution in the U.S.”

description: The relationship between dermatologist supply and racial and ethnic distribution of the U.S. population has been unclear. In this cross-sectional study, we found that among urban and suburban counties, greater racial and ethnic diversity is associated with higher dermatologist density. Therefore, the geographic distribution of dermatologists may not explain racial and ethnic disparities in access to care on the county level. This page includes the Supplemental Methods, Supplemental Figure 1, and Supplemental Table 1 for our study.
DOI: 10.25582/data.2020-05.1992243/2068284
title: Data for EMSL Project 51127 from May 2020
DOI: 10.17632/7d962h3wcd.1
title: Knowledge of non-contraceptive benefits of oral contraceptive pills in a low risk female population in Singapore

description: Anonymous dataset collected as part of the, "Knowledge of non-contraceptive benefits of oral contraceptive pills in a low risk female population in Singapore" which explores the knowledge levels regarding non-contraceptive benefits of OCPs among a low-risk population in Singapore, as well as receptiveness towards considering taking OCPs.
DOI: 10.25582/data.2020-06.2002354/2068285
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-05.1991462/2068286
title: Data for EMSL Project 51127 from May 2020
DOI: 10.17632/22p6gh72wp.1
title: Boycott - Scopus Data

description: This is the citation data for Boycott literature
DOI: 10.25582/data.2020-06.1997683/2068287
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1997781/2068288
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2002401/2068289
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2005445/2068290
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1998217/2068291
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1998765/2068292
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1999150/2068293
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2004854/2068294
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/vxpjcjfvth.1
title: Bibliographic survey of microbial diversity from Chilean soils

description: This dataset is a recopilation of research works published from 1975 to 2023 presenting original studies of soil microbial diversity in Chile. The considered microorganisms are bacteria, archaea, and fungi. The studies selected here focused on the diverse environmental biomes represented in Chile, from arid desert and salt flats in the North, to cultivated lands and forests in the medium South, and steppes and glaciers in the extreme South down to the Antarctic peninsula. The dataset includes different methodological approaches such as cultivation, sequencing, metabarcoding, metagenomics, as well as functional characterization of microbial communities. The main objectives of this work are (i) to describe quantitatively and qualitatively the existing research effort for microbial diversity understanding in Chilean soils (i.e., number of studies, type of methodological approaches, and origin of funding), (ii) to compare the extent of research in the different Chilean regions (including the Antarctic Peninsula) and along time since 1975, and (iii) to identify the main research scopes and current knowledge gaps in soil biodiversity in Chile and Antarctic Peninsula. The studies included in this dataset adressed different main concerns, as follows: potential biotechnological applications of soil microorganisms; impact of climate change on soil microorganisms; microbial diversity of extreme environments; identification of new species; effect of disturbances on soil microorganisms; insights in the functionnal capacities of microbial diversity; biogeographic distribution of soil microorganisms.
DOI: 10.25582/data.2020-06.1997736/2068295
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2002564/2068296
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/kkj9m7k8vn.1
title: Replication package for Endogenous Production Networks with Fixed Costs

description: Replication files for "Endogenous Production Networks with Fixed Costs" by Emmanuel Dhyne, Ken Kikkawa, Xianglong Kong, Magne Mogstad, Felix Tintelnot
DOI: 10.25582/data.2020-05.1991104/2068297
title: Data for EMSL Project 51127 from May 2020
DOI: 10.17632/49w2zcjb9h.1
title: Regionalization of Soil Conservation Service Model for Precise Estimation of Direct Runoff: Case Studies across Iran

description: The supplementary data file including time-series of in-situ (ground) daily data of direct runoff and precipitation for 304 watersheds over Iran.
DOI: 10.25582/data.2020-06.2001740/2068298
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/wcjwf6gn56.1
title: Mechanical properties of films bioplastics based in seaweed from scientific literature

description: The present database investigates the effect of different combinations of components on the mechanical properties of seaweed-based bioplastics, with a specific focus on tensile strength and elongation at break, found in the scientific literature of the search engine Scopus. Following the hypothesis that varying compositions will significantly impact these properties, the basis provides a detailed breakdown of the standardized concentrations of each component in mass/mass or volume/volume percentages. Some notable findings include combinations of components that show substantial improvements in strength and elasticity, suggesting a focus on these materials for the development of biopolymeric film technology applications such as sustainable packaging manufacturing. This resource is useful for future research seeking to interpret or improve the properties of seaweed-based bioplastics.
DOI: 10.25582/data.2020-06.2003126/2068299
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/bzd9b94645.1
title: Magnitude of Bone Disease in Transfusion-Dependent (TDT) and Non-Transfusion-Dependent (NTDT) β-Thalassemia Patients

description: This data set represent clinical, hematological and biochemical characteristic of transfusion-dependent and non-transfusion-dependent beta thalassemia patients who were assessed form bone disease using DEXA scan
DOI: 10.25582/data.2020-06.1999030/2068300
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2003500/2068301
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2001067/2068302
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/ftkrz4b2d9.1
title: Google Trends

description: Google Trends search query data
DOI: 10.17632/ftkrz4b2d9.2
title: Google Trends

description: Google Trends search query data
DOI: 10.25582/data.2020-06.1999903/2068303
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/cgbk4ry9yf.1
title: Elemental geochemical composition (TIC, TOC, TS, Sr, Ba) and recovery rate of core LHSD-1.

description: Elemental geochemical composition (TIC, TOC, TS, Sr, Ba) and recovery rate of core LHSD-1.
DOI: 10.17632/m5b542v2y8.1
title: MOx-Sensors Measurements of Formic Acid Treatment against Varroa Mites on Honey Bees

description: Many beekeepers all over the world use formic acid to treat their honey bee colonies against the parasitic mite Varroa destructor. Acid amount, acid concentration and weather conditions are important factors for the success of a treatment. We tested MOx-Sensors to monitor the gas concentration in the hive over time and to enable the implementation of a control loop. The data shows that standard MOx-Sensors, e.g. SGP40, are capable of measuring the change in concentration relevant for the treatment. This data set is accompanying data of the publication "Evaluating and Optimising Formic Acid Treatment against Varroa Mites on Honey Bees with MOx-Sensors and a Control Loop" in Smart Agricultural Technology: https://doi.org/10.1016/j.atech.2023.100342 The data structure is explained in the uploaded readme/ documentation files.
DOI: 10.25582/data.2020-06.2005477/2068304
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/4vrynzy8xs.1
title: Binder-free core-shell MnO2@NiC2O4 electrode for high performance energy storage

description: Binder-free core-shell MnO2@NiC2O4 electrode for high performance energy storage
DOI: 10.25582/data.2020-05.1992361/2068305
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-06.2002814/2068306
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-05.1992263/2068307
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-06.2001644/2068308
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2002903/2068309
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2005180/2068310
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1997856/2068311
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1999151/2068312
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2005080/2068313
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1998158/2068314
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2002615/2068315
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1997905/2068316
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1999652/2068317
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-05.1991378/2068318
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-06.1998774/2068319
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1999641/2068320
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-05.1993277/2068321
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-05.1991418/2068322
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-06.1998188/2068323
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1998687/2068324
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2002811/2068325
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-05.1993241/2068326
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-05.1993348/2068327
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-06.1998725/2068328
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2001613/2068329
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/3pkfjm3n7f.1
title: Association between sleep patterns, lifestyle behaviors, genetic predisposition, and risk of adult-onset asthma

description: Association between sleep patterns, lifestyle behaviors, genetic predisposition, and risk of adult-onset asthma
DOI: 10.25582/data.2020-06.2003735/2068330
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/nvvdvm64p6.1
title: Beyond quantity supplied: Does untimely distribution and access to inadequate farm inputs impact the cocoa sector and the livelihood of farmers in Ghana?

description: The data gives an insight into whether farm inputs for cocoa production in Ghana are distributed and accessed on time and in the needed quantity. The data also quantifies the impact of untimely distribution and access to inadequate farm inputs on the cocoa sector and the livelihood of farmers in Ghana. Furthermore, challenges or causes of untimely distribution and accesses to inadequate farm inputs are explored as well as the measures to ameliorate the challenges.
DOI: 10.25582/data.2020-06.2000798/2068331
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/tttwv52w4j.1
title: Safety of dermatologic medications in pregnancy and lactation: An Update - Part I: Pregnancy

description: Supplemental Table 1: International Grading Classifications for Pregnancy and Lactation
DOI: 10.25582/data.2020-06.2003751/2068332
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2002736/2068333
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2003137/2068334
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-05.1991597/2068335
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-05.1993425/2068336
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-06.1998166/2068337
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2002469/2068338
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2000164/2068339
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2001678/2068340
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2002915/2068341
title: Data for EMSL Project 51127 from June 2020
DOI: 10.17632/s25d8y9pvz.1
title: Single-cell transcriptomics illuminates regulatory steps driving anterior-posterior patterning of Drosophila embryonic mesoderm

description: All single cell sequencing datasets, R scripts and installation instructions. The following instructions allows you to download R and Rstudio to view any gene expression from the single cell datasets. Download R: Visit the Comprehensive R Archive Network (CRAN) website, the official source for R: https://cran.r-project.org/. Choose a CRAN mirror location near you. Select the mirror that's geographically closest to your location for faster download speeds. Click on the appropriate link for your operating system (Windows, macOS, or Linux). Follow the installation instructions for your specific operating system. Typically, this involves downloading the installer and running it. Install R: Run the downloaded installer. Follow the on-screen instructions, including choosing installation options if prompted. Once the installation is complete, you will have R installed on your computer. Download RStudio: Visit the RStudio download page: https://www.rstudio.com/products/rstudio/download/. Scroll down to the "RStudio Desktop" section. Click on the appropriate link for your operating system (Windows, macOS, or Linux). Download the installer for RStudio Desktop. Install RStudio: Run the downloaded RStudio installer. Follow the on-screen instructions to complete the installation. Once you've completed these steps, you'll have both R and RStudio installed on your computer. You can then launch RStudio, and it will automatically detect your R installation and provide an integrated development environment for working with R. You are then able to open up of the four R markdown files (.Rmd) and load in the datasets from the Rds_object folders in order to view the datasets. Descriptions on the R scripts and Rds objects uploaded below: Three folders containing R codes and the input to the codes as Rds object format. Navigate into the folder and open the rmd or r script files with R studio and follow the instruction inside to run codes. All script should be able to run with minor edit to the data path customed to each user. All scripts inside each folders should be able to run without requiring the outputs of other scripts. To visualize gene expression of single cell seq dataset as shown in the paper, use folder "1. UMAP_Gene_Viewer". To reproduce the UMAP and sequencing results from annotated matrix files, use folder "2. UMAP, differential analysis and cell trajectory pipeline". To integrate multiple datasets, use folder 3.
DOI: 10.25582/data.2020-05.1993333/2068342
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-06.1997530/2068343
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1999039/2068344
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1998998/2068345
title: Data for EMSL Project 51127 from June 2020
DOI: 10.57745/uymh8c
title: data_Publi_AS_EA.zip

description: :unav
DOI: 10.25582/data.2020-06.2002109/2068346
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-05.1991271/2068347
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-05.1992369/2068348
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-06.2002139/2068349
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2003092/2068350
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-05.1993386/2068351
title: Data for EMSL Project 51127 from May 2020
DOI: 10.25582/data.2020-06.2003733/2068352
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.1997421/2068353
title: Data for EMSL Project 51127 from June 2020
DOI: 10.25582/data.2020-06.2000998/2068354
title: Data for EMSL Project 51127 from June 2020
DOI: 10.15156/bio/sh273887.07fu
title: SH273887.07FU

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/sh273888.07fu
title: SH273888.07FU

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/sh273889.07fu
title: SH273889.07FU

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.