cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.jmezsw
title: Occurrence Download

description: A dataset containing 1136 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ceratogymna elata (Temminck, 1831)"
 ]
}

 The dataset includes 1136 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0125828-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ve394z
title: Occurrence Download

description: A dataset containing 131 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Shorea selanica (Wight & Arn.) Blume"
 ]
}

 The dataset includes 131 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0225399-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.62tp4y
title: Occurrence Download

description: A dataset containing 296 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Nepal",
 "TaxonKey is Polygonatum Mill."
 ]
}

 The dataset includes 296 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0125831-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kjqgra
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Phialina Höhn."
 ]
}

 The dataset includes 15 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0422555-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u25qbm
title: Occurrence Download

description: A dataset containing 3491 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Biological survey of lakes and reservoirs from Sardinia and Piedmont (Italy), a georeferenced dataset from the project LIFE INHABIT"
 ]
}

 The dataset includes 3491 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0125855-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zux3gu
title: Occurrence Download

description: A dataset containing 148252 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Setophaga occidentalis (J.K.Townsend, 1837)"
 ]
}

 The dataset includes 148252 records from 111 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0225413-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aeztkj
title: Occurrence Download

description: A dataset containing 109 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Carpha capitellata (Nees) Boeckeler"
 ]
}

 The dataset includes 109 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0125853-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rdeznm
title: Occurrence Download

description: A dataset containing 173 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year 1990-2018",
 {
 "or" : [
 "DatasetKey is NMNH Extant Specimen Records (USNM, US)",
 "DatasetKey is Salud coralina de las comunidades arrecifales de la Isla Cayo Serrana durante la Expedición Seaflower 2016 - Proyecto Colombia BIO"
 ]
 },
 "TaxonKey is Undaria agaricites (Linnaeus, 1758)"
 ]
}

 The dataset includes 173 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007078-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9g5yjv
title: Occurrence Download

description: A dataset containing 29017 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is TEPB - Herbário Graziela Barroso"
 ]
}

 The dataset includes 29017 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023359-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jzu7j9
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-94.5260679999999951 39.0543758000000025, -94.5260679999999951 39.0567411399999997, -94.5260679999999951 39.0582053899999977, -94.5260679999999951 39.0606833599999987, -94.5260679999999951 39.0622602500000013, -94.5260679999999951 39.0641750500000029, -94.5260679999999951 39.0656393000000008, -94.5234747100000021 39.0656393000000008, -94.5218961100000001 39.0656393000000008, -94.5193026900000035 39.0656393000000008, -94.5158072199999992 39.0656393000000008, -94.5127628999999985 39.0656393000000008, -94.5127628999999985 39.0634992399999987, -94.5127628999999985 39.0616970800000018, -94.5127628999999985 39.0597822800000003, -94.5127628999999985 39.0583180300000024, -94.5127628999999985 39.0561779599999994, -94.5127628999999985 39.0543758000000025, -94.5161454899999995 39.0543758000000025, -94.5187389099999962 39.0543758000000025, -94.5220088599999997 39.0543758000000025, -94.5244895200000030 39.0543758000000025, -94.5260679999999951 39.0543758000000025))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 7 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094524-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fetohe
title: Occurrence Download

description: A dataset containing 917 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Leopardus pardalis (Linnaeus, 1758)"
 ]
}

 The dataset includes 917 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007078-180412121330197/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8qnq6q
title: Occurrence Download

description: A dataset containing 4639 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Vallisneria spiralis L.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4639 records from 150 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058490-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jfjy7p
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sempervivum leucanthum Pancic"
 ]
}

 The dataset includes 34 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0123013-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2gsdbg
title: Occurrence Download

description: A dataset containing 20291 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "HasCoordinate is true",
 "TaxonKey is Gammarus pulex (Linnaeus, 1758)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 20291 records from 154 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007079-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.azhjvn
title: Occurrence Download

description: A dataset containing 104 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Senecio pohlii Sch.Bip."
 ]
}

 The dataset includes 104 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0124313-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aqujtm
title: Occurrence Download

description: A dataset containing 1829 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 "GadmGid is one of (COL.4.5_2)"
 ]
}

 The dataset includes 1829 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058494-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kkzfb3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-94.6660537000000062 39.1183515999999969, -94.6660537000000062 39.1192320400000000, -94.6660537000000062 39.1205233499999991, -94.6660537000000062 39.1215798799999988, -94.6660537000000062 39.1229885799999977, -94.6660537000000062 39.1242212000000009, -94.6646449999999930 39.1242212000000009, -94.6632362900000004 39.1242212000000009, -94.6622384599999975 39.1242212000000009, -94.6607123699999988 39.1242212000000009, -94.6594210599999997 39.1242212000000009, -94.6583058300000033 39.1242212000000009, -94.6576014799999967 39.1242212000000009, -94.6566036499999939 39.1242212000000009, -94.6558993000000015 39.1242212000000009, -94.6558993000000015 39.1234581499999976, -94.6558993000000015 39.1222842299999982, -94.6558993000000015 39.1216385800000026, -94.6558993000000015 39.1205233499999991, -94.6558993000000015 39.1191733400000032, -94.6558993000000015 39.1183515999999969, -94.6574253900000002 39.1183515999999969, -94.6585406199999966 39.1183515999999969, -94.6597145399999960 39.1183515999999969, -94.6607123699999988 39.1183515999999969, -94.6621797699999945 39.1183515999999969, -94.6631775999999974 39.1183515999999969, -94.6647036899999961 39.1183515999999969, -94.6660537000000062 39.1183515999999969))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094564-220831081235567/datasets/export for details.
DOI: 10.15468/dl.0gkups
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Bufoceratias wedli (Pietschmann, 1926)"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007079-180730143533302/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6gfjcg
title: Occurrence Download

description: A dataset containing 153946 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Festuca pratensis Huds."
 ]
}

 The dataset includes 153946 records from 690 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028514-230530130749713/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.25189484.v1
title: A blocked staggered-level design for an experiment with two hard-to-change factors

description: Staggered-level designs have been introduced in the literature as cost-efficient and statistically efficient alternatives to split-plot and split-split-plot designs for experiments with multiple hard-to-change factors. In this article, we present an application of a staggered-level design to a staple fiber cutting process at Eastman. The experiment was run in blocks and involved one quantitative hard-to-change factor, one two-level categorical hard-to-change factor, and three quantitative easy-to-change factors. We review existing work on staggered-level designs, discuss D-, A- and I-optimal staggered-level designs and blocked staggered-level designs, and perform an analysis of the data from the staple fiber cutting experiment.
DOI: 10.15468/dl.fgqa85
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CatalogNumber is 568453",
 "Country is Colombia",
 "Elevation 1775.0-2577.0m",
 "TaxonKey is Trichodrymonia metamorphophylla (Donn.Sm.) M.M.Mora & J.L.Clark"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026946-240626123714530/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.25555227
title: Optimal constrained design of control charts using stochastic approximations

description: In statistical process monitoring, control charts typically depend on a set of tuning parameters besides its control limit(s). Proper selection of these tuning parameters is crucial to their performance. In a specific application, a control chart is often designed for detecting a target process distributional shift. In such cases, the tuning parameters should be chosen such that some characteristic of the out-of-control (OC) run length of the chart, such as its average, is minimized for detecting the target shift, while the control limit is set to maintain a desired in-control (IC) performance. However, explicit solutions for such a design are unavailable for most control charts, and thus numerical optimization methods are needed. In such cases, Monte Carlo-based methods are often a viable alternative for finding suitable design constants. The computational cost associated with such scenarios is often substantial, and thus computational efficiency is a key requirement. To address this problem, a two-step design based on stochastic approximations is presented in this paper, which is shown to be much more computationally efficient than some representative existing methods. A detailed discussion about the new algorithm’s implementation along with some examples are provided to demonstrate the broad applicability of the proposed methodology for the optimal design of univariate and multivariate control charts. Computer codes in the Julia programming language are also provided in the supplemental material.
DOI: 10.6084/m9.figshare.25555227.v1
title: Optimal constrained design of control charts using stochastic approximations

description: In statistical process monitoring, control charts typically depend on a set of tuning parameters besides its control limit(s). Proper selection of these tuning parameters is crucial to their performance. In a specific application, a control chart is often designed for detecting a target process distributional shift. In such cases, the tuning parameters should be chosen such that some characteristic of the out-of-control (OC) run length of the chart, such as its average, is minimized for detecting the target shift, while the control limit is set to maintain a desired in-control (IC) performance. However, explicit solutions for such a design are unavailable for most control charts, and thus numerical optimization methods are needed. In such cases, Monte Carlo-based methods are often a viable alternative for finding suitable design constants. The computational cost associated with such scenarios is often substantial, and thus computational efficiency is a key requirement. To address this problem, a two-step design based on stochastic approximations is presented in this paper, which is shown to be much more computationally efficient than some representative existing methods. A detailed discussion about the new algorithm’s implementation along with some examples are provided to demonstrate the broad applicability of the proposed methodology for the optimal design of univariate and multivariate control charts. Computer codes in the Julia programming language are also provided in the supplemental material.
DOI: 10.6084/m9.figshare.25189484
title: A blocked staggered-level design for an experiment with two hard-to-change factors

description: Staggered-level designs have been introduced in the literature as cost-efficient and statistically efficient alternatives to split-plot and split-split-plot designs for experiments with multiple hard-to-change factors. In this article, we present an application of a staggered-level design to a staple fiber cutting process at Eastman. The experiment was run in blocks and involved one quantitative hard-to-change factor, one two-level categorical hard-to-change factor, and three quantitative easy-to-change factors. We review existing work on staggered-level designs, discuss D-, A- and I-optimal staggered-level designs and blocked staggered-level designs, and perform an analysis of the data from the staple fiber cutting experiment.
DOI: 10.6084/m9.figshare.26026601
title: Multimodal recognition and prognostics based on features extracted via multisensor degradation modeling

description: Remaining useful life (RUL) prediction is an important issue in prognostics and health management (PHM). Numerous studies have been conducted to construct degradation models for RUL prediction. However, their models fail to handle the scenarios where multiple failure modes exist, especially when the failure modes are unknown (unlabeled) beforehand and need to be recognized. This paper develops a multimodal recognition and prognostic method based on features extracted <i>via</i> multisensor degradation modeling. Specifically, we assume the failure mode of a unit follows a multinomial distribution. Given the failure mode distribution, we characterize the degradation status of the unit <i>via</i> degradation models based on each sensor signal and a constructed health index (HI). Our innovative idea is to extract features as the derivatives of the degradation status to comprehensively utilize information from multiple sensors for more effective failure mode recognition and RUL prediction. We develop a fusion coefficient-integrated expectation-maximization (FCIEM) algorithm to estimate model parameters by using data from historical units. Finally, we recognize the failure mode and predict the RUL of in-service units based on their extracted features and degradation status. Numerical experiments and a case study of aircraft engines were conducted to evaluate the performance of our proposed method.
DOI: 10.6084/m9.figshare.26026601.v1
title: Multimodal recognition and prognostics based on features extracted via multisensor degradation modeling

description: Remaining useful life (RUL) prediction is an important issue in prognostics and health management (PHM). Numerous studies have been conducted to construct degradation models for RUL prediction. However, their models fail to handle the scenarios where multiple failure modes exist, especially when the failure modes are unknown (unlabeled) beforehand and need to be recognized. This paper develops a multimodal recognition and prognostic method based on features extracted <i>via</i> multisensor degradation modeling. Specifically, we assume the failure mode of a unit follows a multinomial distribution. Given the failure mode distribution, we characterize the degradation status of the unit <i>via</i> degradation models based on each sensor signal and a constructed health index (HI). Our innovative idea is to extract features as the derivatives of the degradation status to comprehensively utilize information from multiple sensors for more effective failure mode recognition and RUL prediction. We develop a fusion coefficient-integrated expectation-maximization (FCIEM) algorithm to estimate model parameters by using data from historical units. Finally, we recognize the failure mode and predict the RUL of in-service units based on their extracted features and degradation status. Numerical experiments and a case study of aircraft engines were conducted to evaluate the performance of our proposed method.
DOI: 10.15468/dl.c8wya6
title: Occurrence Download

description: A dataset containing 113 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material citation, Specimen)",
 "DatasetKey is one of (Digitalización y Sistematización de las Colecciones Biológicas Nacionales del Instituto de Biología, UNAM (vertebrados), Estado actual de la distribución de los anfibios y reptiles de la Región de Los Tuxtlas, UCM Amphibian and Reptile Collection (Arctos), Estudio herpetofaunístico de la Sierra Mazateca, Oaxaca, México, Inventario de la biodiversidad de vertebrados terrestres de los Chimalapas, Oaxaca, Museum of Comparative Zoology, Harvard University, Formación de una base de datos y elaboración de un atlas de la herpetofauna de México (Anfibiosreptiles), Herpetofauna del Estado de Veracruz, Apoyo a las colecciones biológicas de la Facultad de Ciencias de la UNAM: Fase 1 (MZFC_HE), Apoyo a las colecciones biológicas de la Facultad de Ciencias de la UNAM: Fase 1 (Herpetológica))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "PublishingOrg is one of (ff90b050-c256-11db-b71b-b8a03c50a862, 4cadac10-3e7b-11d9-8439-b8a03c50a862, b4640710-8e03-11d8-b956-b8a03c50a862)",
 "TaxonKey is Sceloporus salvini Günther, 1890",
 "Year 1950-2024"
 ]
}

 The dataset includes 113 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026947-240626123714530/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.26314543
title: <b>A</b><b>daptation strategies of giant viruses </b><b>to </b><b>low-temperature marine ecosystems</b>

description: Nucleotide (fna folder)<i> </i>and protein (faa folder) sequences of Antarctic and Patagonian GVMAGs generated in this study. in-house Python scripts
DOI: 10.6084/m9.figshare.26314543.v1
title: <b>A</b><b>daptation strategies of giant viruses </b><b>to </b><b>low-temperature marine ecosystems</b>

description: Nucleotide (fna folder)<i> </i>and protein (faa folder) sequences of Antarctic and Patagonian GVMAGs generated in this study. in-house Python scripts