cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1270418.10fu
title: SH1270418.10FU

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/sh1270420.10fu
title: SH1270420.10FU

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/sh1270422.10fu
title: SH1270422.10FU

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/sh1270423.10fu
title: SH1270423.10FU

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.ahcwvg
title: Occurrence Download

description: A dataset listing the 5929 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is France",
 "TaxonKey is one of (Mammalia, Amphibia, Aves, Reptilia, Reptilia, Reptilia, Reptilia)"
 ]
}

 The dataset's 5929 records were derived from 16078 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003888-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xq8b5j
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acrochaetium catenulatum",
 "Country is Netherlands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 16 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009282-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dnxnb9
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Galactia nummularia Urb."
 ]
}

 The dataset includes 7 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007194-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15495692
title: Phased Logic Dataset
DOI: 10.5281/zenodo.15495693
title: Phased Logic Dataset
DOI: 10.6084/m9.figshare.29135624
title: Supplementary Material for: Exosomal TIMP4 from myocardial cell relieves heart failure by influencing Th17/Treg Balance

description: Introduction: The progression of heart failure (HF) has been independently linked to both tissue inhibitor of metalloproteinase-4 (TIMP4) and the equilibrium between regulatory T (Treg) as well as T helper 17 (Th17) cells. Despite these associations, the interplay between TIMP4 and the Th17/Treg ratio remains poorly understood. Our research sought to elucidate the impact of TIMP4 on HF pathogenesis, with a particular emphasis on its influence on Th17 and Treg lymphocyte populations.
Methods: Bioinformatics analysis of the GSE196656 dataset was conducted. An isoprenaline-induced Sprague-Dawley rat model of heart failure was used, with rats divided into groups: HF alone, HF with TIMP4 overexpression, and HF with TIMP4 knockdown. Heart failure in primary myocardial cell cultures was induced using Angiotensin II, and exosomes were collected from the culture medium. ELISA, western blot, TUNEL staining, qRT-PCR, RNA extraction analysis the impact of TIMP4 on heart failure. Additionally, purified naïve CD4+ T cells from rats were used in vitro to investigate TIMP4's influence on Th17 and Treg cell differentiation.
Results: Analysis of the GSE196656 dataset revealed significant upregulation of TIMP4 in heart failure. Myocardial exosomal TIMP4 was significantly elevated in the heart failure model. In the experimental rat model, TIMP4 overexpression significantly reduced plasma levels of biomarkers related to heart injury as well as inflammation, enhanced indicators of heart function and suppressed cell death in the heart muscle. Furthermore, TIMP4 overexpression decreased IL-17 levels and the Th17 cell proportion while promoting Treg cell differentiation and increasing IL-10 levels. In vitro studies demonstrated that TIMP4 effectively inhibits the differentiation of Th17 cells and promotes the growth of Treg cells. These effects were observed to vary depending on the dosage.
Conclusion: TIMP4 overexpression exerts a protective effect in heart failure by inhibiting myocardial injury, inflammation, and apoptosis, and by regulating immune cell balance. These findings imply that targeting TIMP4 could potentially serve as a therapeutic strategy for heart failure, as it has the ability to regulate immune responses and minimize damage to the myocardium.
DOI: 10.6084/m9.figshare.29135624.v1
title: Supplementary Material for: Exosomal TIMP4 from myocardial cell relieves heart failure by influencing Th17/Treg Balance

description: Introduction: The progression of heart failure (HF) has been independently linked to both tissue inhibitor of metalloproteinase-4 (TIMP4) and the equilibrium between regulatory T (Treg) as well as T helper 17 (Th17) cells. Despite these associations, the interplay between TIMP4 and the Th17/Treg ratio remains poorly understood. Our research sought to elucidate the impact of TIMP4 on HF pathogenesis, with a particular emphasis on its influence on Th17 and Treg lymphocyte populations.
Methods: Bioinformatics analysis of the GSE196656 dataset was conducted. An isoprenaline-induced Sprague-Dawley rat model of heart failure was used, with rats divided into groups: HF alone, HF with TIMP4 overexpression, and HF with TIMP4 knockdown. Heart failure in primary myocardial cell cultures was induced using Angiotensin II, and exosomes were collected from the culture medium. ELISA, western blot, TUNEL staining, qRT-PCR, RNA extraction analysis the impact of TIMP4 on heart failure. Additionally, purified naïve CD4+ T cells from rats were used in vitro to investigate TIMP4's influence on Th17 and Treg cell differentiation.
Results: Analysis of the GSE196656 dataset revealed significant upregulation of TIMP4 in heart failure. Myocardial exosomal TIMP4 was significantly elevated in the heart failure model. In the experimental rat model, TIMP4 overexpression significantly reduced plasma levels of biomarkers related to heart injury as well as inflammation, enhanced indicators of heart function and suppressed cell death in the heart muscle. Furthermore, TIMP4 overexpression decreased IL-17 levels and the Th17 cell proportion while promoting Treg cell differentiation and increasing IL-10 levels. In vitro studies demonstrated that TIMP4 effectively inhibits the differentiation of Th17 cells and promotes the growth of Treg cells. These effects were observed to vary depending on the dosage.
Conclusion: TIMP4 overexpression exerts a protective effect in heart failure by inhibiting myocardial injury, inflammation, and apoptosis, and by regulating immune cell balance. These findings imply that targeting TIMP4 could potentially serve as a therapeutic strategy for heart failure, as it has the ability to regulate immune responses and minimize damage to the myocardium.
DOI: 10.6084/m9.figshare.29135627
title: Supplementary Material for: Finerenone in primary IgA nephropathy: A matched case-control study

description: Introduction: This study aimed to evaluate whether supplementation of finerenone to renin-angiotensin system inhibitor (RASi) therapy confers additional renoprotective benefit versus RASi therapy only in clinical IgA nephropathy (IgAN).

Methods: Primary IgAN patients administered RASi therapy at Ruijin Hospital from January 2023 to December 2023 were retrospectively enrolled, with an eGFR ≥ 25 mL/min/1.73 m2. IgAN patients treated with steroids or immunosuppressants were excluded. The analyzed patients were divided into the finerenone and RASi groups based on finerenone use status. Patients were selected via 1:1 propensity score matching (PSM) based on age, sex, 24-hour urine protein, eGFR, and SGLT2i use status. The primary endpoint was the change in urinary protein at 9 months compared to baseline. Secondary endpoints included eGFR decline and safety outcomes, with additional data collection at 12 months.

Results: After PSM, 62 patients were included, with 31 in each group. The finerenone group showed a greater reduction in urinary protein (-29.03% vs. 41.47%, p &lt; 0.001) and a slower least-squares mean eGFR slope (1.25 vs. -3.38 mL/min/1.73 m², p = 0.04) at 9 months compared with the RASi group. Subgroup analysis suggested a trend toward greater improvement with SGLT2i addition, but the interaction was not statistically significant (p = 0.31), likely due to the limited sample size. Extended follow-up at 12 months confirmed these findings, demonstrating a sustained reduction in proteinuria (P = 0.001). Hyperkalemia rates remained similar in both groups at 4, 9, and 12 months.

Conclusions: The combination of finerenone with RASi is associated with a greater reduction in urinary protein and potentially better stabilization of eGFR compared with RASi alone in IgAN patients. However, these findings require further validation in prospective studies.
DOI: 10.6084/m9.figshare.29135627.v1
title: Supplementary Material for: Finerenone in primary IgA nephropathy: A matched case-control study

description: Introduction: This study aimed to evaluate whether supplementation of finerenone to renin-angiotensin system inhibitor (RASi) therapy confers additional renoprotective benefit versus RASi therapy only in clinical IgA nephropathy (IgAN).

Methods: Primary IgAN patients administered RASi therapy at Ruijin Hospital from January 2023 to December 2023 were retrospectively enrolled, with an eGFR ≥ 25 mL/min/1.73 m2. IgAN patients treated with steroids or immunosuppressants were excluded. The analyzed patients were divided into the finerenone and RASi groups based on finerenone use status. Patients were selected via 1:1 propensity score matching (PSM) based on age, sex, 24-hour urine protein, eGFR, and SGLT2i use status. The primary endpoint was the change in urinary protein at 9 months compared to baseline. Secondary endpoints included eGFR decline and safety outcomes, with additional data collection at 12 months.

Results: After PSM, 62 patients were included, with 31 in each group. The finerenone group showed a greater reduction in urinary protein (-29.03% vs. 41.47%, p &lt; 0.001) and a slower least-squares mean eGFR slope (1.25 vs. -3.38 mL/min/1.73 m², p = 0.04) at 9 months compared with the RASi group. Subgroup analysis suggested a trend toward greater improvement with SGLT2i addition, but the interaction was not statistically significant (p = 0.31), likely due to the limited sample size. Extended follow-up at 12 months confirmed these findings, demonstrating a sustained reduction in proteinuria (P = 0.001). Hyperkalemia rates remained similar in both groups at 4, 9, and 12 months.

Conclusions: The combination of finerenone with RASi is associated with a greater reduction in urinary protein and potentially better stabilization of eGFR compared with RASi alone in IgAN patients. However, these findings require further validation in prospective studies.
DOI: 10.21227/q07p-8y72
title: "Analytical Vector Impulse Response Calculation for a Circular Aperture, Taking into Account the Boundary Wave Influence"

description: "The paper considers the problem of theoretically determining the spatio-temporal dependence of the pulse field being the response of an aperture in the shape of a circular conductive disk uniformly illuminated by a planar linearly polarized radio wave to a signal in the form of a delta function. Special attention is paid to the phenomenon of the occurrence of surface currents with inhomogeneous directions distribution in the near-boundary ring region. Theoretical relations are given that make it possible to express the polarization multiplier for both the boundary wave generated by these currents and the main radiation. The features related to the vector nature of the field are investigated, each component of the field having a corresponding integral expression of the impulse response composed for, and all the antiderivatives being obtained in an explicit analytical form. Examples of the application of the obtained expressions are presented, and a comparison with the simulation results is performed."
DOI: 10.5281/zenodo.15494101
title: EDF and OCCU Fall Detection Datasets

description: Abstract

Falls are one of the major risks for seniors living alone at home. Fall detection has been widely studied in the computer vision community, especially since the advent of affordable depth sensing technology like the Kinect. Most existing methods assume that the whole fall process is visible to the camera. This is not always the case, however, since the end of the fall can be completely occluded by a certain object, like a bed. For a system to be usable in real life, the occlusion problem must be addressed. To quantify the challenges and assess performance in this topic, we present an occluded fall detection benchmark dataset containing 60 occluded falls for which the end of the fall is completely occluded.

Data Collection

EDF is a non-occlusion fall detection dataset, and OCCU is an occlusion fall detection dataset that were created using Kinect cameras for XBOX 360 with the Microsoft Kinect for Windows SDK Beta at a frame rate of about 30fps. Each of the 5 subjects performed a non-occluded fall along eight directions in each viewpoint in the EDF dataset. Each of the 5 subjects performed six occluded falls in each viewpoint in the OCCU dataset. In the OCCU dataset, the end of the fall is completely occluded by a bed. 

EDF

The EDF dataset is comprised of 25,881 frames and 40 real falls in videos from the first viewpoint, and 24,497 frames and 40 real falls in videos from the second viewpoint. The two viewpoints were recorded at the same time, and thus every event was recorded simultaneously from both viewpoints. Our subjects also performed a total of 30 actions that tend to produce features similar to those of a fall event, namely: 10 examples of picking up something from the floor, 10 cases of sitting on the floor, and 10 examples of lying down on the floor.

OCCU

The OCCU dataset includes 25,618 frames and 30 totally occluded falls in videos from the first viewpoint, and 23,703 frames and 30 totally occluded falls in videos from the second viewpoint, performed by the same subjects. Each viewpoint was recorded at separate times from the other viewpoint, and thus we had no instances where the same events were recorded simultaneously from both viewpoints. Our subjects also performed a total of 80 actions that tended to produce features similar to those of a fall event, namely: 20 examples of picking up something from the floor (all of them are non-occluded), 20 examples of sitting on the floor (all of them are non-occluded), 20 examples of tying shoelaces (all of them are non-occluded), and 21 examples of lying down on the floor(all of them are totally occluded at the end frame).

If you use EDF and/or OCCU in your work, please cite the original publication that presents these datasets:

Zhang, Z., Conly, C., Athitsos, V. (2014). Evaluating Depth-Based Computer Vision Methods for Fall Detection under Occlusions. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8888. Springer, Cham. https://doi.org/10.1007/978-3-319-14364-4_19
DOI: 10.5281/zenodo.15494102
title: EDF and OCCU Fall Detection Datasets

description: Abstract

Falls are one of the major risks for seniors living alone at home. Fall detection has been widely studied in the computer vision community, especially since the advent of affordable depth sensing technology like the Kinect. Most existing methods assume that the whole fall process is visible to the camera. This is not always the case, however, since the end of the fall can be completely occluded by a certain object, like a bed. For a system to be usable in real life, the occlusion problem must be addressed. To quantify the challenges and assess performance in this topic, we present an occluded fall detection benchmark dataset containing 60 occluded falls for which the end of the fall is completely occluded.

Data Collection

EDF is a non-occlusion fall detection dataset, and OCCU is an occlusion fall detection dataset that were created using Kinect cameras for XBOX 360 with the Microsoft Kinect for Windows SDK Beta at a frame rate of about 30fps. Each of the 5 subjects performed a non-occluded fall along eight directions in each viewpoint in the EDF dataset. Each of the 5 subjects performed six occluded falls in each viewpoint in the OCCU dataset. In the OCCU dataset, the end of the fall is completely occluded by a bed. 

EDF

The EDF dataset is comprised of 25,881 frames and 40 real falls in videos from the first viewpoint, and 24,497 frames and 40 real falls in videos from the second viewpoint. The two viewpoints were recorded at the same time, and thus every event was recorded simultaneously from both viewpoints. Our subjects also performed a total of 30 actions that tend to produce features similar to those of a fall event, namely: 10 examples of picking up something from the floor, 10 cases of sitting on the floor, and 10 examples of lying down on the floor.

OCCU

The OCCU dataset includes 25,618 frames and 30 totally occluded falls in videos from the first viewpoint, and 23,703 frames and 30 totally occluded falls in videos from the second viewpoint, performed by the same subjects. Each viewpoint was recorded at separate times from the other viewpoint, and thus we had no instances where the same events were recorded simultaneously from both viewpoints. Our subjects also performed a total of 80 actions that tended to produce features similar to those of a fall event, namely: 20 examples of picking up something from the floor (all of them are non-occluded), 20 examples of sitting on the floor (all of them are non-occluded), 20 examples of tying shoelaces (all of them are non-occluded), and 21 examples of lying down on the floor(all of them are totally occluded at the end frame).

If you use EDF and/or OCCU in your work, please cite the original publication that presents these datasets:

Zhang, Z., Conly, C., Athitsos, V. (2014). Evaluating Depth-Based Computer Vision Methods for Fall Detection under Occlusions. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8888. Springer, Cham. https://doi.org/10.1007/978-3-319-14364-4_19