cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.ju8nuv
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Geometry POLYGON ((-115.399 35.31712, -115.3994 35.31691, -115.3998 35.31668, -115.4002 35.31644, -115.4005 35.31618, -115.4008 35.31591, -115.4012 35.31562, -115.4014 35.31532, -115.4017 35.31501, -115.402 35.31468, -115.4022 35.31435, -115.4024 35.31401, -115.4026 35.31366, -115.4028 35.3133, -115.4029 35.31293, -115.403 35.31256, -115.4031 35.31219, -115.4032 35.31181, -115.4032 35.31143, -115.4032 35.31105, -115.4032 35.31066, -115.4032 35.31028, -115.4032 35.3099, -115.4031 35.30952, -115.403 35.30915, -115.4021 35.30618, -115.4019 35.30581, -115.4018 35.30545, -115.4016 35.30509, -115.4014 35.30474, -115.4012 35.3044, -115.401 35.30407, -115.4007 35.30376, -115.4005 35.30345, -115.4002 35.30315, -115.3998 35.30287, -115.3995 35.3026, -115.3992 35.30235, -115.3988 35.30211, -115.3984 35.30189, -115.398 35.30168, -115.3976 35.30149, -115.3972 35.30132, -115.3968 35.30116, -115.3963 35.30103, -115.3959 35.30091, -115.3954 35.30081, -115.395 35.30073, -115.3945 35.30067, -115.3941 35.30063, -115.3936 35.30061, -115.3931 35.30061, -115.3927 35.30063, -115.3922 35.30067, -115.3917 35.30073, -115.3913 35.30081, -115.3908 35.30091, -115.3904 35.30102, -115.3899 35.30116, -115.3895 35.30131, -115.3891 35.30149, -115.3865 35.30261, -115.3861 35.3028, -115.3857 35.30301, -115.3854 35.30323, -115.385 35.30347, -115.3846 35.30373, -115.3843 35.30399, -115.384 35.30428, -115.3837 35.30457, -115.3834 35.30488, -115.3832 35.3052, -115.3829 35.30553, -115.3827 35.30587, -115.3825 35.30622, -115.3823 35.30658, -115.3822 35.30694, -115.3821 35.30731, -115.382 35.30768, -115.3819 35.30806, -115.3818 35.30844, -115.3818 35.30882, -115.3818 35.3092, -115.3818 35.30959, -115.3819 35.30997, -115.3819 35.31034, -115.382 35.31072, -115.3822 35.31109, -115.3823 35.31145, -115.3825 35.31181, -115.3839 35.31461, -115.384 35.31497, -115.3843 35.31531, -115.3845 35.31565, -115.3847 35.31598, -115.385 35.31629, -115.3853 35.3166, -115.3856 35.31689, -115.386 35.31716, -115.3863 35.31742, -115.3867 35.31767, -115.3871 35.3179, -115.3875 35.31811, -115.3879 35.3183, -115.3883 35.31848, -115.3887 35.31864, -115.3892 35.31878, -115.3896 35.3189, -115.3901 35.31899, -115.3906 35.31907, -115.391 35.31913, -115.3915 35.31917, -115.392 35.31919, -115.3925 35.31919, -115.3929 35.31917, -115.3934 35.31912, -115.3939 35.31906, -115.3943 35.31898, -115.3948 35.31887, -115.3953 35.31875, -115.3957 35.31861, -115.3961 35.31844, -115.3966 35.31826, -115.3986 35.31732, -115.399 35.31712))",
 {
 "not" : {
 "TaxonKey" : [
 "is Plantae"
 ]
 }
 },
 {
 "not" : {
 "TaxonKey" : [
 "is Aves"
 ]
 }
 },
 "Year is greater than or equal to 1926",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053526-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sgwq2b
title: Occurrence Download

description: A dataset containing 93268 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Adoxa moschatellina, Alliaria petiolata, Allium ursinum, Anemone nemorosa, Anemone ranunculoides, Arum maculatum, Cardamine bulbifera, Euphorbia amygdaloides, Ficaria verna, Galium odoratum, Lathyrus vernus, Mercurialis perennis, Oxalis acetosella, Paris quadrifolia, Polygonatum verticillatum, Primula elatior, Pulmonaria obscura, Ranunculus auricomus, Stellaria holostea, Viola reichenbachiana)",
 "BasisOfRecord is Specimen",
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 93268 records from 335 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053507-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14164657
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.ma9n5t
title: Occurrence Download

description: A dataset containing 1299 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is one of (Ecuador, Peru)",
 "Geometry POLYGON((-84.28475 -18.74956,-71.44995 -18.74956,-70.53817 -19.87149,-68.46186 -18.67719,-66.5743 -19.59666,-65.28558 -17.54677,-71.44995 2.63582,-84.28475 2.63582,-84.28475 -18.74956))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Canidae"
 ]
}

 The dataset includes 1299 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053527-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4m4fnr
title: Occurrence Download

description: A dataset containing 161 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Swedish Malaise Trap Project (SMTP) - Rogadinae"
 ]
}

 The dataset includes 161 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053529-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.88qthn
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Geometry POLYGON ((-115.4073 35.40486, -115.4069 35.40462, -115.4066 35.4044, -115.4062 35.40419, -115.4058 35.404, -115.4054 35.40383, -115.4049 35.40367, -115.4045 35.40353, -115.4041 35.40341, -115.4036 35.40331, -115.4032 35.40323, -115.4027 35.40317, -115.4022 35.40313, -115.4018 35.4031, -115.4013 35.4031, -115.4009 35.40311, -115.4004 35.40315, -115.3999 35.4032, -115.3995 35.40327, -115.399 35.40337, -115.3986 35.40348, -115.3981 35.40361, -115.3977 35.40375, -115.3973 35.40392, -115.3969 35.4041, -115.3965 35.4043, -115.3961 35.40452, -115.3958 35.40475, -115.3954 35.40499, -115.3951 35.40526, -115.3948 35.40553, -115.3945 35.40582, -115.3926 35.40772, -115.3923 35.40803, -115.392 35.40835, -115.3918 35.40867, -115.3915 35.40901, -115.3913 35.40936, -115.3912 35.40972, -115.391 35.41008, -115.3909 35.41045, -115.3908 35.41082, -115.3907 35.4112, -115.3906 35.41158, -115.3906 35.41197, -115.3906 35.41235, -115.3906 35.41274, -115.3906 35.41312, -115.3907 35.4135, -115.3908 35.41388, -115.3909 35.41425, -115.391 35.41462, -115.3912 35.41498, -115.3914 35.41534, -115.3916 35.41568, -115.3918 35.41602, -115.392 35.41635, -115.3923 35.41666, -115.3926 35.41697, -115.3929 35.41726, -115.3932 35.41753, -115.3936 35.4178, -115.3939 35.41804, -115.3943 35.41828, -115.3947 35.41849, -115.3951 35.41869, -115.3955 35.41887, -115.396 35.41903, -115.3964 35.41918, -115.3968 35.4193, -115.3973 35.41941, -115.3986 35.41968, -115.399 35.41976, -115.3995 35.41983, -115.3999 35.41987, -115.4004 35.4199, -115.4008 35.41991, -115.4013 35.4199, -115.4017 35.41987, -115.4022 35.41982, -115.4026 35.41976, -115.4031 35.41967, -115.4035 35.41957, -115.404 35.41945, -115.4064 35.4187, -115.4069 35.41855, -115.4073 35.41839, -115.4077 35.41822, -115.4081 35.41802, -115.4085 35.41781, -115.4088 35.41758, -115.4092 35.41734, -115.4095 35.41708, -115.4099 35.41681, -115.4102 35.41652, -115.4105 35.41622, -115.4107 35.41592, -115.411 35.41559, -115.4112 35.41526, -115.4114 35.41492, -115.4116 35.41457, -115.4118 35.41422, -115.4119 35.41386, -115.412 35.41349, -115.4121 35.41312, -115.4122 35.41274, -115.4122 35.41236, -115.4123 35.41198, -115.4123 35.4116, -115.4122 35.41123, -115.4122 35.41085, -115.4121 35.41047, -115.412 35.4101, -115.4119 35.40974, -115.4117 35.40937, -115.4116 35.40902, -115.4114 35.40867, -115.4112 35.40834, -115.4109 35.40801, -115.4107 35.40769, -115.4104 35.40738, -115.4101 35.40709, -115.4098 35.4068, -115.4095 35.40654, -115.4076 35.40511, -115.4073 35.40486))",
 {
 "not" : {
 "TaxonKey" : [
 "is Plantae"
 ]
 }
 },
 {
 "not" : {
 "TaxonKey" : [
 "is Aves"
 ]
 }
 },
 "Year is greater than or equal to 1926",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053530-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17938740
title: raw NMR noesy data L12andL41
DOI: 10.5281/zenodo.17938741
title: raw NMR noesy data L12andL41
DOI: 10.6084/m9.figshare.30877076
title: 受控装置（拍翼）动态控制数据输出

description: 本研究针对拍翼飞机中强非线性、多通道耦合及复杂气动扰动等控制问题，提出了一种基于架构的环境自适应级联控制切换方法的PID控制方法。基于MWORKS。Sysplorer，构建了一个物理控制闭环。经典的PID作为外环的主环路，PID、非线性补偿PID和SMC作为内环，形成嵌套结构，利用MATLAB / Simulink进行交叉验证。通过扰动量子化参数k工作条件分为高、中、低扰动以切换策略，在经典的振翼频率为15赫兹，相位滞后可受限，控制精度和计算效率均可优化。该方法提升了抗扰度，适应复杂频域扰动，并为飞机控制提供了高度稳健且工程可行的方案。平台配置：MWORKS.sysplorer 中的 CAD 工具箱促进了多体模型的直接导入以进行控制，成为模型构建和实时仿真的基础。MATLAB/Simulink作为国际知名的领先仿真软件，支持数据后处理和算法交叉验证，确保初始条件和扰动设置的一致性。轨迹跟踪：系统跟踪正弦曲线（z = 5sin（0.5t））以评估动态响应。绩效指标：均方根误差（RMSE）测量跟踪准确性;调整时间表示误差收敛到稳态值±2%所需的时间;最大超冲代表瞬态过程中观察到的最高偏差;计算时间表示每个仿真步骤的平均持续时间。数据分析：本研究利用MWORKS构建了振翼飞机的物理控制仿真平台。系统探险者。物理控制数据分别导出为PID、非线性PID和滑动模式控制（SMC）模块。随后，轨迹收集并导出了每个算法的Y跟踪、姿态响应和控制输出数据。随后，SPSS和Python被用于联合数据处理。首先，3σ准则消除了因瞬时传感器失效产生的离群值，并进行了线性插值以确保数据完整性。同时，时间轴被均匀重置为零，控制量归一化为[-1， 1]区间。利用统计方法计算了RMSE、IAE和调整时间等定量指标，以分析性能差异。最后，通过专业可视化呈现了对比结果，为算法优化提供了实用基础。
DOI: 10.6084/m9.figshare.30877076.v1
title: 受控装置（拍翼）动态控制数据输出

description: 本研究针对拍翼飞机中强非线性、多通道耦合及复杂气动扰动等控制问题，提出了一种基于架构的环境自适应级联控制切换方法的PID控制方法。基于MWORKS。Sysplorer，构建了一个物理控制闭环。经典的PID作为外环的主环路，PID、非线性补偿PID和SMC作为内环，形成嵌套结构，利用MATLAB / Simulink进行交叉验证。通过扰动量子化参数k工作条件分为高、中、低扰动以切换策略，在经典的振翼频率为15赫兹，相位滞后可受限，控制精度和计算效率均可优化。该方法提升了抗扰度，适应复杂频域扰动，并为飞机控制提供了高度稳健且工程可行的方案。平台配置：MWORKS.sysplorer 中的 CAD 工具箱促进了多体模型的直接导入以进行控制，成为模型构建和实时仿真的基础。MATLAB/Simulink作为国际知名的领先仿真软件，支持数据后处理和算法交叉验证，确保初始条件和扰动设置的一致性。轨迹跟踪：系统跟踪正弦曲线（z = 5sin（0.5t））以评估动态响应。绩效指标：均方根误差（RMSE）测量跟踪准确性;调整时间表示误差收敛到稳态值±2%所需的时间;最大超冲代表瞬态过程中观察到的最高偏差;计算时间表示每个仿真步骤的平均持续时间。数据分析：本研究利用MWORKS构建了振翼飞机的物理控制仿真平台。系统探险者。物理控制数据分别导出为PID、非线性PID和滑动模式控制（SMC）模块。随后，轨迹收集并导出了每个算法的Y跟踪、姿态响应和控制输出数据。随后，SPSS和Python被用于联合数据处理。首先，3σ准则消除了因瞬时传感器失效产生的离群值，并进行了线性插值以确保数据完整性。同时，时间轴被均匀重置为零，控制量归一化为[-1， 1]区间。利用统计方法计算了RMSE、IAE和调整时间等定量指标，以分析性能差异。最后，通过专业可视化呈现了对比结果，为算法优化提供了实用基础。
DOI: 10.15468/dl.7c4yvy
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Geometry POLYGON ((-115.3916 35.40487, -115.3912 35.40489, -115.3907 35.40492, -115.3902 35.40498, -115.3897 35.40506, -115.3893 35.40515, -115.3888 35.40527, -115.3884 35.40541, -115.3879 35.40556, -115.3875 35.40574, -115.3871 35.40593, -115.3867 35.40614, -115.3863 35.40637, -115.3859 35.40662, -115.3856 35.40687, -115.3853 35.40715, -115.3849 35.40744, -115.3846 35.40774, -115.3844 35.40806, -115.3841 35.40838, -115.3839 35.40872, -115.3836 35.40907, -115.3835 35.40942, -115.3833 35.40979, -115.3831 35.41016, -115.383 35.41053, -115.3829 35.41091, -115.3829 35.4113, -115.3828 35.41168, -115.3828 35.41207, -115.3827 35.41466, -115.3827 35.41504, -115.3828 35.41543, -115.3828 35.41582, -115.3829 35.4162, -115.383 35.41658, -115.3831 35.41696, -115.3833 35.41732, -115.3835 35.41769, -115.3837 35.41804, -115.3839 35.41838, -115.3841 35.41871, -115.3844 35.41904, -115.3847 35.41935, -115.385 35.41964, -115.3853 35.41993, -115.3857 35.4202, -115.386 35.42045, -115.3864 35.42069, -115.3868 35.42091, -115.3872 35.42111, -115.3876 35.4213, -115.3881 35.42146, -115.3885 35.42161, -115.389 35.42174, -115.3894 35.42185, -115.3899 35.42194, -115.3904 35.42201, -115.3908 35.42206, -115.3913 35.42209, -115.3918 35.42209, -115.3959 35.42207, -115.3963 35.42205, -115.3968 35.42202, -115.3973 35.42197, -115.3977 35.42189, -115.3982 35.4218, -115.3986 35.42169, -115.3991 35.42156, -115.3995 35.42141, -115.3999 35.42124, -115.4004 35.42105, -115.4008 35.42085, -115.4011 35.42063, -115.4015 35.42039, -115.4019 35.42014, -115.4022 35.41987, -115.4025 35.41959, -115.4028 35.41929, -115.4031 35.41899, -115.4034 35.41867, -115.4036 35.41834, -115.4038 35.418, -115.404 35.41765, -115.4042 35.41729, -115.4044 35.41693, -115.4045 35.41656, -115.4046 35.41618, -115.4047 35.4158, -115.4047 35.41542, -115.4048 35.41504, -115.4048 35.41465, -115.4047 35.41222, -115.4047 35.41184, -115.4047 35.41145, -115.4046 35.41107, -115.4045 35.4107, -115.4044 35.41033, -115.4043 35.40996, -115.4041 35.4096, -115.4039 35.40925, -115.4037 35.4089, -115.4035 35.40857, -115.4032 35.40824, -115.4029 35.40793, -115.4027 35.40763, -115.4023 35.40734, -115.402 35.40707, -115.4017 35.40681, -115.4013 35.40656, -115.4009 35.40633, -115.4005 35.40612, -115.4001 35.40592, -115.3997 35.40574, -115.3993 35.40558, -115.3988 35.40544, -115.3984 35.40532, -115.3979 35.40521, -115.3975 35.40513, -115.397 35.40507, -115.3966 35.40502, -115.3961 35.405, -115.3921 35.40487, -115.3916 35.40487))",
 {
 "not" : {
 "TaxonKey" : [
 "is Plantae"
 ]
 }
 },
 {
 "not" : {
 "TaxonKey" : [
 "is Aves"
 ]
 }
 },
 "Year is greater than or equal to 1926",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053533-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j36br9
title: Occurrence Download

description: A dataset containing 36323 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Biowide Species data"
 ]
}

 The dataset includes 36323 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053534-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9k4h3e
title: Occurrence Download

description: A dataset listing the 1451 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((111.7601 1.04547,112.25716 1.04547,112.25716 1.35025,111.7601 1.35025,111.7601 1.04547))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 1451 records were derived from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053520-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sabg88
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
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 {
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 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053535-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p14vck4t
title: Generated Burn Severity Offset Correction Values for a Composite Burn Index Field Plot Dataset

description: Phenological correction of pre- and post-fire imagery is used to improve remotely-sensed burn severity predictions by standardizing vegetation greenness between image pairs. However, the efficacy of existing methods across diverse fire conditions and scenarios remains underexplored. In this study, we evaluated the impact of phenological offset corrections across various methodological decision points and fire-prone environments to support analyst decision making. We generated burn severity spectral values for a dataset of Composite Burn Index (CBI) field plots across the continental US. The effectiveness of offset correction was tested across image selection techniques, spectral indices, offset generation methods, and burn perimeter sources. We compared the influence of offset corrections on the modeled relationship with CBI, agreement between burn severity thresholds, and potential bias. We found that applying offset correction consistently improved the modeled relationship with CBI by addressing extreme outlier severity values. However, offset corrections had the potential to introduce bias, systematically lowering severity values and reducing correspondence to burn severity thresholds. Our analysis suggests that offset corrections may offer benefits but also pose tradeoffs to accurately representing remotely-sensed burn severity. The utility of offset corrections may depend on the environment, methods, and scale of analysis considered. We propose a decision-tree framework for analysts to consider when employing offset correction, given their study scope.
DOI: 10.15468/dl.zxszb5
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
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 {
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}

 The dataset includes 24 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053537-251120083545085/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.29116997
title: Pilot Testing the Youth Engaging Transition: Perspectives of Youth, Parents, and School Physical Therapists

description: To investigate the feasibility, acceptability, and relevance of the Youth Engaging Transition (YET) instrument. In this observational study, nine youth (16-21 years) with motor disabilities, their parents, and school physical therapists completed the YET, then triad members gave feedback about the experience (<i>n</i> = 27). Parents and PTs agreed that both sections (S1: Future Plans and S2: Self-Assessment and Goal Planning) were feasible. Three triads questioned the youth’s understanding of the YET. Parents agreed that S1 and S2 were acceptable. Three PTs disagreed that S2 was an appropriate scope/depth. Five triads questioned the YET’s length and repetitiveness. Youth and PTs reported that the YET was relevant. Perhaps due to previous transition planning experience, some parents reported not learning new information by completing the YET. Parents’ and PTs’ ratings were aligned, suggesting a common experience using the YET. Results of this pilot study suggest that the YET has promise as a feasible, acceptable, and relevant transition planning instrument. Larger studies investigating the validity and reliability of the YET should include modifications to the YET, involve other transition team members, and ascertain the team’s previous involvement in the planning process. Future YET iterations will include enhanced cognitive accessibility and shortened length.