cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1271758.09fu
title: SH1271758.09FU

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/sh1271759.09fu
title: SH1271759.09FU

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/sh1271760.09fu
title: SH1271760.09FU

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/sh1271761.09fu
title: SH1271761.09FU

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: 10.6084/m9.figshare.14927008
title: Additional file 1 of Solitary vaginal paraganglioma with mature sacrococcygeal teratoma: a rare case report

description: Additional file 1.
DOI: 10.6084/m9.figshare.14927008.v1
title: Additional file 1 of Solitary vaginal paraganglioma with mature sacrococcygeal teratoma: a rare case report

description: Additional file 1.
DOI: 10.6073/pasta/61fb86fedc656cd13b3d52d76abd8566
title: EXPOS Model for Estimating Topographic Exposure to Wind

description: EXPOS is a simple model of topographic exposure to wind that utilizes digital elevation data to predict which points on a landscape are exposed to or protected from a given wind direction. The model was developed to approximate the effects of topography on hurricane wind flow at a landscape scale (~ 10 km).
 The model requires an accurate digital elevation map and a specified wind direction. Each point on the elevation map is then classified as protected or exposed, depending on whether or not it falls within the wind shadow cast by points upwind. The wind shadow is estimated by assuming that the wind bends downward no more than a fixed inflection angle from the horizontal as it passes over a height of land. The effects of topographic features beyond the margins of the input elevation map are of course not predicted by the model.
 For a given landscape and wind direction, predicted protected areas decrease in size as the inflection angle increases. Application of the model in studies of two recent hurricanes suggests that the probability of wind damage in protected areas also decreases as the inflection angle increases. An inflection angle of about 5 to 10 degrees was found to give good results.
 For more information on the EXPOS model, please see the published paper (Boose, E. R., D. R. Foster, and M. Fluet. 1994. Hurricane impacts to tropical and temperate forest landscapes. Ecological Monographs 64: 369-400). Additional information is contained in the documentation that accompanies the program.
 For an updated version of the EXPOS model in R and Python, please see HF447.
DOI: 10.6073/pasta/aec07a3538ccf5a70e7e9f8d22994021
title: Luquillo Experimental Forest Canopy Trimming Experiment CTE2 2015-2020 30-minute abiotic data

description: The data archive is here: https://doi.org/10.2737/RDS-2021-0028 please use this DOI when citing this dataset.
 This data publication contains 30-minute values for abiotic field data from 3 treated and 3 control plots from the Canopy Trimming Experiment (CTE) located near El Verde Field Station in the Luquillo Experimental Forest (El Yunque National Forest), Puerto Rico collected from 2015 through 2020. In December of 2014 (CTE2), in 0.09 hectare (ha) square plots near the El Verde Field Station the forest canopy was trimmed and the canopy debris was littered to the forest floor. The plot size and trim amounts were based on the patch disturbance after the two most recent hurricanes before 2017, both category 3 hurricanes at the location of El Verde: Hugo in September 1989, and Georges in September 1998. Data were collected in the inner 0.04 ha quadrants of the 0.09 ha trimmed plots to minimize edge effects. Each plot was made up of 16 subplots with different data types collected in each subplot. There were 3 sets of control and treated plots, with each set near El Verde field station. Field data include 30-minute: solar radiation, soil profile volumetric water content, shallow soil volumetric water content, canopy leaf saturation, litter leaf saturation, air temperature, soil temperature, air relative humidity, vapor pressure, and throughfall. Field data were collected by one automatic sensor in each plot inside a designated subplot, except: soil profile volumetric water content, canopy leaf saturation, and litter leaf saturation; each were collected in three subplots.
 Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
DOI: 10.6084/m9.figshare.14926787
title: Additional file 1 of Prognostic signature composed of transcription factors accurately predicts the prognosis of gastric cancer patients

description: Additional file 1: Table S1. Clinical information of the TCGA-STAD cohort. Table S2. Differentially expressed transcription factors in the TCGA-STAD cohort. Table S3. Transcription factors in modules related to gastric cancer. Table S4. predicts target genes of hub TFs.
DOI: 10.3886/icpsr38973.v1
title: Survey of Consumer Attitudes and Behavior, August 2020
title: Version 1

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter.
The surveys conducted in 2020 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, computers, and other durables.
Also explored in this survey were respondents' vehicle financing, past prices, political affiliation, the coronavirus, and the election. Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this survey series is to forecast changes in aggregate consumer behavior.
description: This survey is a rotating panel design. For each monthly sample, an independent cross-section sample of households is drawn. The respondents chosen in this drawing are then reinterviewed six months later. The result is a rotating panel design, and the total sample for any one survey is normally made up of 60 percent new respondents with 40 percent being interviewed for the second time.
description: The data are not weighted, however, this collection contains three weight variables; <b>WT_AD</b> (Adult weight), <b>WT_HH</b> (Household weight), <b>WT</b> (Household weight (WT_HH renamed)) and that must be used in any analysis. For more information on weights and sampling, please refer to the documentation and/or visit the Surveys of Consumers Website.
description: National sample of telephone numbers from cell (RDD) sampling frame.
description: Datasets: 
DS0: Study-Level Files
DS1: Public-Use Data
DS2: Restricted-Use Data
description: Persons aged 18 years or older living in households with telephones in the coterminous United States. Smallest Geographic Unit: FIPS code
description: computer-assisted telephone interview (CATI)Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the P.I. Codebook.Additional information on the Surveys of Consumers can be found by visiting the Surveys of Consumers Website.
DOI: 10.3886/icpsr38973
title: Survey of Consumer Attitudes and Behavior, August 2020
title: Archival Version

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter.
The surveys conducted in 2020 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, computers, and other durables.
Also explored in this survey were respondents' vehicle financing, past prices, political affiliation, the coronavirus, and the election. Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this survey series is to forecast changes in aggregate consumer behavior.
description: This survey is a rotating panel design. For each monthly sample, an independent cross-section sample of households is drawn. The respondents chosen in this drawing are then reinterviewed six months later. The result is a rotating panel design, and the total sample for any one survey is normally made up of 60 percent new respondents with 40 percent being interviewed for the second time.
description: The data are not weighted, however, this collection contains three weight variables; <b>WT_AD</b> (Adult weight), <b>WT_HH</b> (Household weight), <b>WT</b> (Household weight (WT_HH renamed)) and that must be used in any analysis. For more information on weights and sampling, please refer to the documentation and/or visit the Surveys of Consumers Website.
description: National sample of telephone numbers from cell (RDD) sampling frame.
description: Datasets: 
DS0: Study-Level Files
DS1: Public-Use Data
DS2: Restricted-Use Data
description: Persons aged 18 years or older living in households with telephones in the coterminous United States. Smallest Geographic Unit: FIPS code
description: computer-assisted telephone interview (CATI)Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the P.I. Codebook.Additional information on the Surveys of Consumers can be found by visiting the Surveys of Consumers Website.
DOI: 10.6084/m9.figshare.14926733.v1
title: Additional file 2 of Construction of a risk prediction model for Alzheimer’s disease in the elderly population

description: Additional file 2.
DOI: 10.6084/m9.figshare.14927045.v1
title: Additional file 1 of Development and clinical validation of a novel six-gene signature for accurately predicting the recurrence risk of patients with stage II/III colorectal cancer

description: Additional file 1: Table S1. Details of baseline information in GSE143985, GSE17536, GSE29621, GSE92921 and qRT-PCR data from 66 samples, respectively. Table S2. The forward and reverse primers for qRT-PCR. Table S3. Univariate Cox results of four cohorts revealed a total of 13 stable genes (red mark) were significantly associated with RFS.
DOI: 10.6073/pasta/c5381cec9bfc1c3d444a6f709cb0ddec
title: HURRECON Model for Estimating Hurricane Wind Speed, Direction and Damage

description: HURRECON is a simple meteorological model that estimates hurricane surface wind speed and direction based on the track, size, and intensity of a hurricane and the surface type (land or water). The model also estimates Fujita-scale wind damage as a function of peak 1/4 mile wind speed and wind gust factor. Estimates can be generated for a single site or a rectangular region. The model is based on published empirical studies of many hurricanes.
 HURRECON can be used to study the impacts of individual hurricanes or to reconstruct the hurricane disturbance regime for a particular region. For more information on the most recent version of the model please see the published paper (Boose, E. R., K. E. Chamberlin and D. R. Foster. 2001. Landscape and regional impacts of hurricanes in New England. Ecological Monographs 71: 27-48). Additional information is contained in the documentation that accompanies the program.
 For an updated version of the HURRECON model in R and Python, please see HF446.
DOI: 10.6084/m9.figshare.22790602
title: Additional file 3 of Integrated analysis of circulating and tissue proteomes reveals that fibronectin 1 is a potential biomarker in papillary thyroid cancer

description: Additional file 3: Supplementary Table S3. Differentially expressed proteins between healthy controls (HCs) and papillary thyroid cancer patients'serum samples.
DOI: 10.6084/m9.figshare.17023774.v2
title: Value of glycogen synthase 2 in intrahepatic cholangiocarcinoma prognosis assessment and its influence on the activity of cancer cells

description: Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver tumor with increasing incidence worldwide. Metabolic reprogramming caused by metabolic related gene disorders is a prominent hallmark of tumors, among which Glycogen Synthase 2 (GYS2) is the key gene responsible for regulating cellular energy metabolism, and its expression disorders are closely related to various tumors and glycometabolic diseases. However, we still know nothing about its role in ICC. This study is intended to reveal the functional role of GYS2 in the ICC progress and explore the underlying mechanism. Based on the integrated pan-cancer analysis of GYS2 in the GEPIA database, the expression of GYS2 in paired ICC and adjacent non tumor tissues was detected by qPCR. It was found that the expression of GYS2 was significantly down-regulated in ICC. Further analysis showed that its low expression was not only associated with the degree of pathological differentiation, tumor size, microvascular invasion and lymph node metastasis, but also an independent risk factor for unfavorable prognosis. Functional studies have shown that GYS2 overexpression can significantly impair the proliferation, replication, cloning, migration and invasion of cholangiocarcinoma cells, while the silencing GYS2 dramatically promotes the development of the aforementioned phenotypes, the underlying mechanism may be that GYS2 activates the P53 pathway. In conclusions,low GYS2 expression in ICC predicted unfavorable patient outcomes; GYS2 overexpression could significantly impair the proliferation, migration and invasion of cholangiocarcinoma cells via activating the P53 pathway and GYS2 was expected to become a potential therapeutic target for such patients.
DOI: 10.6084/m9.figshare.14927045
title: Additional file 1 of Development and clinical validation of a novel six-gene signature for accurately predicting the recurrence risk of patients with stage II/III colorectal cancer

description: Additional file 1: Table S1. Details of baseline information in GSE143985, GSE17536, GSE29621, GSE92921 and qRT-PCR data from 66 samples, respectively. Table S2. The forward and reverse primers for qRT-PCR. Table S3. Univariate Cox results of four cohorts revealed a total of 13 stable genes (red mark) were significantly associated with RFS.
DOI: 10.6084/m9.figshare.14926730
title: Additional file 1 of Construction of a risk prediction model for Alzheimer’s disease in the elderly population

description: Additional file 1.
DOI: 10.6084/m9.figshare.17023774.v1
title: Value of Glycogen Synthase 2 in intrahepatic cholangiocarcinoma prognosis assessment and its influence on the activity of cancer cells

description: Intrahepatic cholangiocarcinoma is the second most common primary liver tumor with increasing incidence worldwide. Metabolic reprogramming caused by metabolic related gene disorders is a prominent hallmark of tumors, among which Glycogen Synthase 2 (GYS2) is the key gene responsible for regulating cellular energy metabolism, and its expression disorders are closely related to various tumors and glycometabolic diseases. However, we still know nothing about its role in intrahepatic cholangiocarcinoma. The purpose of this study was to uncover the functional role of GYS2 in the progression ICC and explore the underlying mechanism. Firstly, we performed an integrated pan-cancer analysis of GYS2 in the Gene Expression Profiling Interactive Analysis database and further detected the expression of GYS2 in paired intrahepatic cholangiocarcinoma and adjacent non-tumor tissues by qPCR, then we analyzed the relationship between the expression level and clinicopathologic factors as well as the effect on the survival of patients. Finally, we identified the effect on the biological behavior of cholangiocarcinoma cells by cellular and molecular experiments. The expression of GYS2 was significantly downregulated in intrahepatic cholangiocarcinoma. The low expression of GYS2 was not only associated with the degree of pathological differentiation, tumor size, microvascular invasion and lymph node metastasis, but also an independent risk factor for unfavorable prognosis. Functional studies have shown that GYS2 overexpression can significantly impair the proliferation, replication, cloning, migration and invasion of cholangiocarcinoma cells, while the silencing GYS2 dramatically promotes the development of the aforementioned phenotypes, the underlying mechanism may be that GYS2 activates the P53 pathway. In conclusions, low GYS2 expression in intrahepatic cholangiocarcinoma predicted unfavorable patient outcomes; GYS2 overexpression can significantly impair the proliferation, migration and invasion of cholangiocarcinoma cells via activating the P53 pathway and GYS2 was expected to become a potential therapeutic target for such patients.
DOI: 10.6084/m9.figshare.14926787.v1
title: Additional file 1 of Prognostic signature composed of transcription factors accurately predicts the prognosis of gastric cancer patients

description: Additional file 1: Table S1. Clinical information of the TCGA-STAD cohort. Table S2. Differentially expressed transcription factors in the TCGA-STAD cohort. Table S3. Transcription factors in modules related to gastric cancer. Table S4. predicts target genes of hub TFs.
DOI: 10.6084/m9.figshare.14926730.v1
title: Additional file 1 of Construction of a risk prediction model for Alzheimer’s disease in the elderly population

description: Additional file 1.
DOI: 10.6084/m9.figshare.14926733
title: Additional file 2 of Construction of a risk prediction model for Alzheimer’s disease in the elderly population

description: Additional file 2.