cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1050401.10fu
title: SH1050401.10FU

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/sh1050439.10fu
title: SH1050439.10FU

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/sh1050440.10fu
title: SH1050440.10FU

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/sh1050443.10fu
title: SH1050443.10FU

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/sh1050444.10fu
title: SH1050444.10FU

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/sh1050445.10fu
title: SH1050445.10FU

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/sh1050448.10fu
title: SH1050448.10FU

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/sh1050452.10fu
title: SH1050452.10FU

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/sh1050455.10fu
title: SH1050455.10FU

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: 10.15468/dl.qx4fq2
title: Occurrence Download

description: A dataset containing 2247 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pleione D.Don"
 ]
}

 The dataset includes 2247 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007644-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qmeyw5
title: Occurrence Download

description: A dataset containing 3021 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Epilobium ciliatum var. ciliatum)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 3021 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007579-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/h056-hb64
title: Gramatika

description: Gramatika is a syntectic GEC dataset for Indonesian. The Gramatika dataset has a total of 1.5 million sentences with 4,666,185 errors. Of all sentences, only 30,000 (2%) are correct sentences with no mistakes. Each sentence has a maximum of 6 errors, and there can only be 2 of the same error type in each sentence.We also split the dataset into three splits: train, dev, and test splits, with the proportion of 8:1:1 (with the size of 1,199,705, 150,171, and 150,124 sentences, respectively). The proportion of valid sentences in each split is 2%; 24,000 in the train split, and 3000 in each dev and test split. Moreover, we also set the proportion of each error type in all splits to be the same, as shown in Table 3.3.2. For example, the proportion of noun errors is 7.5% in all splits, while the proportion of particle errors is also only 0.3% in all splits.
DOI: 10.5281/zenodo.14984946
title: The Effect of Social Media Reliance on the Perception of AI Threats in the Workplace

description: Abstract—Social media dependency has become a significant factor influencing individuals' perceptions of technology, including artificial intelligence (AI) in the workplace. Information about AI circulating on social media can shape perceptions of threats, such as fears of job displacement, skill redundancy, and loss of control in decision-making. This study aims to analyze the relationship between social media dependency and perceived AI threats in the workplace. Data were collected through an online survey in January 2025, involving 403 respondents from various industry sectors in Indonesia. After data cleaning, 255 valid responses were used for analysis. A purposive sampling technique was applied to ensure participation from employees with AI exposure. Structural Equation Modeling (SEM) was employed to examine the relationships between variables. The findings indicate that higher social media dependency is associated with greater perceived AI threats, particularly regarding the perceived unfairness of AI implementation and concerns over skill obsolescence. These results suggest that companies need more transparent communication strategies when implementing AI to reduce employee anxiety and foster a smoother technological adaptation process.
DOI: 10.5281/zenodo.14984947
title: The Effect of Social Media Reliance on the Perception of AI Threats in the Workplace

description: Abstract—Social media dependency has become a significant factor influencing individuals' perceptions of technology, including artificial intelligence (AI) in the workplace. Information about AI circulating on social media can shape perceptions of threats, such as fears of job displacement, skill redundancy, and loss of control in decision-making. This study aims to analyze the relationship between social media dependency and perceived AI threats in the workplace. Data were collected through an online survey in January 2025, involving 403 respondents from various industry sectors in Indonesia. After data cleaning, 255 valid responses were used for analysis. A purposive sampling technique was applied to ensure participation from employees with AI exposure. Structural Equation Modeling (SEM) was employed to examine the relationships between variables. The findings indicate that higher social media dependency is associated with greater perceived AI threats, particularly regarding the perceived unfairness of AI implementation and concerns over skill obsolescence. These results suggest that companies need more transparent communication strategies when implementing AI to reduce employee anxiety and foster a smoother technological adaptation process.
DOI: 10.5281/zenodo.14984983
title: The Effect of Social Media Reliance on the Perception of AI Threats in the Workplace

description: Abstract—Social media dependency has become a significant factor influencing individuals' perceptions of technology, including artificial intelligence (AI) in the workplace. Information about AI circulating on social media can shape perceptions of threats, such as fears of job displacement, skill redundancy, and loss of control in decision-making. This study aims to analyze the relationship between social media dependency and perceived AI threats in the workplace. Data were collected through an online survey in January 2025, involving 403 respondents from various industry sectors in Indonesia. After data cleaning, 255 valid responses were used for analysis. A purposive sampling technique was applied to ensure participation from employees with AI exposure. Structural Equation Modeling (SEM) was employed to examine the relationships between variables. The findings indicate that higher social media dependency is associated with greater perceived AI threats, particularly regarding the perceived unfairness of AI implementation and concerns over skill obsolescence. These results suggest that companies need more transparent communication strategies when implementing AI to reduce employee anxiety and foster a smoother technological adaptation process.
DOI: 10.15468/dl.u4unaa
title: Occurrence Download

description: A dataset containing 541 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Coptotermes formosanus Shiraki, 1909"
 ]
}

 The dataset includes 541 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007645-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.35080/data.c.2021.p18
title: 中国地质调查局: 辽宁省台吉幅(K51E014003)1∶50 000地质图数据库
title: 1:50,000 Geological Map Database of Taiji Map Sheet (K51E014003), Liaoning Province, China

description: 辽宁台吉幅（K51E014003）1∶50 000地质图根据《1∶50 000区域地质调查技术要求》（DD 2019—01）和行业的其他统一标准及要求，充分利用1∶200 000区域地质、1∶250 000区域地质调查工作资料，采用数字地质调查系统（DGSS），进行野外地质填图和数据库建设。通过遥感解译、野外数字填图等手段采集数据，完成辽宁台吉幅1∶50 000地质填图385.2 km<sup>2</sup>，系统编制了辽宁台吉幅1∶50 000地质图、矿产图、建造构造图，并依据《数字地质图空间数据库标准》（DD 2006—06）建立了数据库。图件详细填绘了各地层单位的物质组成和构造组合特点，建立了测区岩石地层格架，分析了各地层层序特征并划分了沉积建造类型。本地质图数据库为MapGIS格式，包括18个沉积（火山）地层单位，数据量为267 MB，其中地质体面实体数据125个、路线长度649 km、地质点<number>1100</number>个、地质（界）线数据332条、293个产状数据、摄像（照片）数据403个，薄片66件，锆石U–Pb测年数据6件、光释光测年数据4件、岩石地球化学分析数据70件。该图幅建立了辽西中生代陆相地层格架，确定了各期火山岩的岩性、岩相、火山构造特征及其形成时代，恢复了古火山机构。反映了1∶50 000区域地质调查基础性成果，对中生代陆相地层对比研究具有重要的科学研究价值。本数据库建立过程始终坚持完善的质量控制体系，确保了数据的真实性、可靠性和准确性，对该区矿产地质调查、地质灾害防治及生态环境保护、工程施工等提供基础地质支撑。对区内地层进行了详细调查研究，查明了各地层单位的物质组成、地层层序、沉积环境、形成时代，系统地建立了测区岩石地层格架，详细划分为13个组，18个地层填图单位，1个侵入岩填图单位。通过分析岩石组合、地层层序特征，识别出碳酸盐岩建造、陆相火山沉积建造、复陆屑建造等3种沉积建造类型，进一步划分为10种沉积相。
DOI: 10.35080/data.c.2021.p09
title: 中国地质调查局: 内蒙古哈珠东山幅(K47E011012)1∶50 000地质图数据库
title: 1:50,000 Geological Map Database of Hazhudongshan Map Sheet (K47E011012), Inner Mongolia, China

description: 内蒙古哈珠东山幅（K47E011012）1∶50 000区域地质图数据库在充分利用1∶200 000区域地质、1∶50 000矿产调查成果的基础上，根据《1∶50 000区域地质调查技术要求》和《数字地质图空间数据库》技术标准，采用数字地质调查系统（DGSS），结合遥感、物化探、路线地质调查和实测剖面等多种手段综合填绘而成，是内蒙古北山地区具有重要参考意义的成果图件之一。图件详细填绘了白山岩浆弧的物质组成和构造组合特点，对泥盆系、石炭系、白垩系等沉积建造类型进行了重新划分，把区内的侵入岩划分为晚石炭世和早二叠世两期，并构建了相对完善的岩浆演化序列。新获得白山组一批高精度锆石U–Pb同位素测年资料（298.7～327.9 Ma），限定其形成时代为石炭世。提出了区内石炭纪的岩浆岩形成于与俯冲作用相关的陆缘弧环境，中晚二叠世北山地区已转入造山后伸展阶段的认识。该数据库是哈珠东山幅配套的数据文件，包含6个正式地层单位、2期岩浆事件和2期构造变形。采集薄片分析样品94件，岩石全分析样品19件，锆石U–Pb年龄样品10件，化石样品7件，基本化学分析样2件，新发现矿化点1处。这些数据反映了北山地区1∶50 000区域地质调查最新示范性成果，对后续填图具有参考和借鉴意义，同时为研究北山地区古亚洲洋的俯冲极性及构造演化提供依据与关键性的基础数据。
DOI: 10.35080/data.c.2021.p20
title: 中国地质调查局: 宁夏石塘岭幅(J48E018017)1∶50 000地质图数据库
title: 1:50,000 Geological Map Database of Shitangling Map Sheet(J48E018017), Ningxia, China

description: 宁夏回族自治区石塘岭幅 （J48E018017）1∶50 000区域地质图数据库基于数字地质调查系统建立，实现了设计地质图、野外地质填图、室内综合整理、最终成果表达的全程数字化，有效开展了对各类数据的一体化描述、存储、组织和利用。将沉积旋回划分与年代学分析相结合，系统开展测区第四纪地层多重划分与对比，建立等时地层对比格架，恢复盆地沉积充填过程，查明断裂活动性；重新建立了测区古近纪—新近纪地层系统，划分出11个填图单元，并确立了新近纪彰恩堡组与干河沟组之间存在沉积间断，二者之间为不整合接触关系。本数据库共包含矢量化的地质图一幅，样品179件，素描图86件，图片253张，内容详实、可利用度高，为厘定青藏高原东北缘地区新近系—古近系地层序列及新构造–活动构造特征提供了详实的基础性数据资料支撑；为总结新构造–活动构造发育区填图技术方法提供了依据。
DOI: 10.15468/dl.f23xae
title: Occurrence Download

description: A dataset containing 3113 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Epilobium ciliatum subsp. glandulosum (Lehm.) Hoch & P.H.Raven)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 3113 records from 155 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007647-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28551308
title: Canopy nitrogen application greatly enhances forest productivity

description: we established a large-scale field experiment in 2013 comparing the effects of CAN with UAN on forest productivity at three N-addition rates (0, 25 or 50 kg N ha–1 yr–1). This experiment consists of 20 circular plots (four per unique treatment) each with 34 m diameter, and has been going on with N additions for a decade in a temperate deciduous forest located in Dabie Mountain, central China (details in Materials and Methods). To directly evaluate how canopy N application affect forest productivity, we measured leaf litterfall plus branch, stem wood, and fine root production during the N treatment periods. We conducted 9260 leaf litterfall measurements using litter traps (1 m × 1 m) between 2017 and 2022. Leaf litterfall production was monitored weekly over four consecutive years (2017–2020) to assess temporal dynamics. We measured fine root production using the ingrowth core method every three months from May 2017 to March 2019 across a total of 720 locations. In each plot, we measured the diameter at breast height (DBH) and height of all trees with DBH ≥ 3 cm in 2012, 2017, and 2022. Using region-specific allometric equations, we then calculated the annual net primary productivity (NPP) over the ten-year period. We calculated ∆C/∆N by dividing the difference in NPP between N addition plots and control plots by the amount of added N. Additionally, we employed a 15N tracer (99.3 atom% 15NH415NO3) to track the fate and redistribution of added N within the forest ecosystem, including leaves, branches, stem wood, fine roots, mineral soil, and organic soil.
DOI: 10.6084/m9.figshare.25689600
title: coding data for cases.xls

description: This study analyzed the causes about netizens’ oppositional opinion toward public policy news in 54 cases from 2018 to 2023 in Weibo using qualitative comparative analysis.
DOI: 10.6084/m9.figshare.25689600.v1
title: coding data for cases.xls

description: This study analyzed the causes about netizens’ oppositional opinion toward public policy news in 54 cases from 2018 to 2023 in Weibo using qualitative comparative analysis.
DOI: 10.35080/data.c.2021.p02
title: 中国地质调查局: 甘新交界黑山梁幅(K46E015018)1∶50 000地质图数据库
title: 1:50,000 geological map dataset of Heishanliang Map Sheet (K46E015018) in the Gansu-Xinjiang border area, China

description: 甘新交界黑山梁幅（K46E015018）1∶50 000地质图数据库是在充分收集前人调查研究成果，吸取中澳合作填图和中加合作填图经验基础上开展区域地质调查工作的结果。调查路线的设计部署以垂直构造线的穿越路线为主、追索路线为辅，不着重强调路线密度，以最大限度收集野外第一手资料为目的，达到精细刻画地质体的目标，最终形成地质图数据集，数据量约为166 MB。本次调查将多种遥感影像资料充分应用到路线地质调查过程中，在中天山原划前寒武纪地质体中解体并厘定出前寒武纪变质沉积岩、新元古代闪长质片麻岩以及早古生代弧岩浆岩组合，对其展布范围和时代进行了约束；详细填绘了中天山南缘构造混杂岩的组成和变形特征；精细刻画了红柳河一带中天山及其南缘构造带的物质组成和结构构造。图幅的表达尽量实现地质体的展布、属性和演化特征的多层次表达，达到了客观性与认识性的统一，实现了构造—岩性实体填图。本数据集的形成为讨论中亚造山带南缘的构造演化以及东天山和北山的构造衔接关系提供野外地质证据。数据集的形成过程和表达形式对于后续地质调查工作具有参考和借鉴意义。
DOI: 10.6084/m9.figshare.28551257
title: <i>P. destructans Meta Raw Data</i>

description: This is raw Pd metabolomics data after IVA, EMC and IVA-EMC co-treatment of volatile organic compounds within the bat cave environment.
DOI: 10.6084/m9.figshare.28551257.v1
title: <i>P. destructans Meta Raw Data</i>

description: This is raw Pd metabolomics data after IVA, EMC and IVA-EMC co-treatment of volatile organic compounds within the bat cave environment.
DOI: 10.6084/m9.figshare.28551257.v2
title: <i>P. destructans Meta Raw Data</i>

description: This is raw Pd metabolomics data after IVA, EMC and IVA-EMC co-treatment of volatile organic compounds within the bat cave environment.