cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28614918.v1
title: Improving lung cancer decision-making using a conversation tool (iDECIDE): a stepped wedge pragmatic clinical trial

description: Lung cancer is a leading cause of cancer-related mortality. However, few treatment decision-making resources exist. In this study, we evaluate a low literacy lung cancer treatment conversation tool to enhance shared decision-making (SDM). The Improving Decision-Making Encounters in Lung Cancer (iDECIDE) pragmatic, stepped-wedge cluster randomized trial evaluates the effectiveness of a conversation tool for patients with lung cancer. Our primary outcome is SDM, a multifaceted outcome consisting of decisional conflict (DCS), decision self-efficacy (DSES), satisfaction with communication (COMRADE), and assessment of lung cancer knowledge. SDM is assessed 2 weeks, 3 months, and 6 months after patients’ treatment decision-making encounter. Each measure within the primary outcome will be assessed separately. We began recruiting patients in 2022 from four health care centers and will conduct outcome assessments at four timepoints over 6 months. We aim to recruit 230 patients by 2025. We seek to address the gaps in NSCLC decision-making support using an innovative trial design to determine whether our conversation tool improves SDM and other patient-centered outcomes. Clinical Trial Registration: NCT05407168 (clinicaltrials.gov) Lung cancer is one of the most deadly cancers. Although there are many treatment options, resources exist to help patients make decisions about treatment for their lung cancer. This study evaluates how well a decision aid helps improve decision-making conversations between patients with lung cancer and their providers. In our study, Improving Decision-Making Encounters In Lung Cancer (iDECIDE), we go through a lung cancer treatment decision aid with patients with lung cancer. We also measure patients’ decisional conflict, decision self efficacy, satisfaction with communication, and knowledge about lung cancer. We measure these concepts before patients make a treatment decision, and then 2 weeks, 3 months, and 6 months after they make their treatment decision. We began recruiting patients for our study in 2022 and recruit patients from four different hospitals in the Portland, Oregon area. Our goal is to recruit 230 patients by the end of 2025. We hope to address gaps in decision-making support for patients with lung cancer by evaluating whether our decision aid improves decision-making conversations between patients and providers.
DOI: 10.6084/m9.figshare.27601035
title: <b>SMRFR: </b><b>A global multilayer soil moisture dataset</b><b> generated using Random Forest from multi-source data</b>

description: Accurate and continuous monitoring of soil moisture (SM) is crucial for a wide range of applications in agriculture, hydrology, and climate modelling. In this study, we present a novel machine learning (ML) based framework for generating a continuously updated, multilayer global SM dataset: SMRFR (Soil Moisture via Random Forest Regression). Leveraging publicly available reanalysis and remote sensing data, SMRFR provides daily SM estimates at five soil layers (0-5, 5-10, 10-30, 30-50 and 50-100 cm) with a spatial resolution of 9 km, covering the period from 2000 to 2023. Evaluation results demonstrate that SMRFR effectively captures both spatial and temporal SM variability. It also exhibits strong generalization capacity, successfully transferring knowledge across continents and accurately capturing transient and seasonal SM dynamics following rainfall events. SMRFR achieved an unbiased root mean square error of 0.0339 m3/m3 on the validation set. Our novel SM dataset offers a basis and valuable reference for agricultural, hydrological, and ecological research, enabling improved analysis and modelling of SM dynamics at regional to global scales. Due to the whole dataset for the global scale is too big (391.59GB) to deposit at once，we uploaded the data of 2000 to figshare. The whole dataset can be accessed at https://doi.org/10.11888/Terre.tpdc.301526.
DOI: 10.15468/dl.6wysz4
title: Occurrence Download

description: A dataset containing 1129 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sitta whiteheadi Sharpe, 1884",
 "HasCoordinate is true",
 "Year is greater than 1989",
 "Year is less than 2026",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is Absent"
 ]
 }
 },
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 1129 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006108-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r4ehpb
title: Occurrence Download

description: A dataset containing 1496218 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lethe drypetis (Hewitson, 1863), Crocidophora habisalis Walker, 1859, Penthema formosanum (Rothschild, 1898), Potanthus confucius (C.Felder & R.Felder, 1862), Henotesia narcissus (Fabricius, 1798), Lethe confusa Aurivillius, 1897, Neope muirheadii (Felder, 1862), Crypsiptya coclesalis (Walker, 1859), Kannabateomys amblyonyx (Wagner, 1845), Myelobia smerintha Hübner, 1821, Pyrausta bambucivora Moore, 1888, Lethe mekara (Moore, 1857), Branchana xanthota Li, 2011, Scaphoideus kumamotonis Matsumura, 1914, Lethe chandica (Moore, 1857), Parlatoria banksiae (Maskell, 1896), Pseudaulacaspis difissata (Brimblecombe, 1959), Pseudaulacaspis grandilobis (Maskell, 1894), Callipappus rubiginosus (Maskell, 1893), Cryptophasa flavolineata (Walker, 1864), Cryptophasa spilonota Scott, 1864, Aleurocanthus banksiae (Maskell, 1896), Cyrioides imperialis (Fabricius, 1801), Phylidonyris niger (Bechstein, 1811), Stegommata sulfuratella Meyrick, 1880, Trichoglossus chlorolepidotus (Kuhl, 1820), Hylaeus perhumilis (Cockerell, 1914), Prosthemadera novaeseelandiae novaeseelandiae, Anthochaera carunculata (Shaw, 1790), Syconycteris australis (Peters, 1867), Lepidosaphes beckii (Newman, 1869), Megachile mucida Cresson, 1878, Osmia bucephala Cresson, 1864, Anthophora ursina Cresson, 1869, Eucera hamata (Bradley, 1942), Plutella porrectella Linnaeus, 1758, Anthocharis midea (Hübner, 1809), Pontia occidentalis (Reakirt, 1866), Phyllotreta nemorum (Linnaeus, 1758), Calesia haemorrhoa Guenée, 1852, Ancistroides nigrita (Latreille, 1824), Gangara thyrsis (Fabricius, 1775), Junonia lavinia Cramer, 1775, Junonia rhadama (Boisduval, 1833), Meridemis detractana (Walker, 1863), Hebomoia glaucippe (Linnaeus, 1758), Epiphyas postvittana (Walker, 1863), Latoia latistriga (Walker, 1855), Parasa latistriga (Walker, 1855), Thyas miniacea Felder & Rogenhofer, 1874)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1496218 records from 611 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006095-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zsqbkj
title: Occurrence Download

description: A dataset containing 773 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-127.71239 -23.00610,-25.28761 -23.00610,-25.28761 18.00610,-127.71239 18.00610,-127.71239 -23.00610))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Coccoloba obovata Kunth"
 ]
}

 The dataset includes 773 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006113-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9fncxd
title: Occurrence Download

description: A dataset containing 773 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-127.71239 -23.00610,-25.28761 -23.00610,-25.28761 18.00610,-127.71239 18.00610,-127.71239 -23.00610))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Coccoloba obovata Kunth"
 ]
}

 The dataset includes 773 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006114-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6xz39b
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((88 31,103 31,103 38,88 38,88 31))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Aix galericulata (Linnaeus, 1758)"
 ]
}

 The dataset includes 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006115-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.23630
title: Images dataset of hairy peach fruits at different ripeness for machine vision in smart orchards
title: 面向智慧果园机器视觉的不同成熟度毛桃果实图像数据集

description: With the development of smart agriculture, precise fruit detection and ripeness classification have become one of the key technologies in intelligent orchard management. In this paper, a high-quality dataset for ripeness classification of hairy peach to enhance the application effectiveness of object detection models for machine vision in smart orchard. The dataset is based on real orchard scenes, using smartphones to record images of hairy peach fruits at different ripeness, covered to three categories: immature, semimature and mature. To ensure data diversity, various factors such as different shooting distances, lighting conditions, and fruit growth states were considered during the collection process. Through excluding images that are too dark, blurry, defocused, heavily occluded, and highly repetitive, those high-quality and representative samples are manually selected according to fruit clarity, composition integrity, and balanced ripeness, a total of 1245 high-resolution images (original dataset to 8.23 GB, augmented dataset to 15.56 GB) were obtained, and 3493 fruit bounding boxes were manually annotated. The dataset provides annotation files in both Pascal VOC and YOLO formats. This dataset performs well with YOLO v8, RT-DETR, and Mamba-YOLO, and provides fundamental data support for the development of visual intelligent system for robots in smart orchard.
description: With the development of smart agriculture, precise fruit detection and ripeness classification have become one of the key technologies in intelligent orchard management. In this paper, a high-quality dataset for ripeness classification of hairy peach to enhance the application effectiveness of object detection models for machine vision in smart orchard. The dataset is based on real orchard scenes, using smartphones to record images of hairy peach fruits at different ripeness, covered to three categories: immature, semimature and mature. To ensure data diversity, various factors such as different shooting distances, lighting conditions, and fruit growth states were considered during the collection process. Through excluding images that are too dark, blurry, defocused, heavily occluded, and highly repetitive, those high-quality and representative samples are manually selected according to fruit clarity, composition integrity, and balanced ripeness, a total of 1245 high-resolution images (original dataset to 8.23 GB, augmented dataset to 15.56 GB) were obtained, and 3493 fruit bounding boxes were manually annotated. The dataset provides annotation files in both Pascal VOC and YOLO formats. This dataset performs well with YOLO v8, RT-DETR, and Mamba-YOLO, and provides fundamental data support for the development of visual intelligent system for robots in smart orchard.
DOI: 10.15468/dl.xctuez
title: Occurrence Download

description: A dataset containing 815394 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Somateria mollissima (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Year is greater than 1989",
 "Year is less than 2026",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is Absent"
 ]
 }
 },
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 815394 records from 157 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006110-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d56due
title: Occurrence Download

description: A dataset containing 237 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oxalis nipponica S.Aoki & J.Murata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is Japan"
 ]
}

 The dataset includes 237 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006116-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.25298
title: Wild boar-borne RNA viruses
title: Wild boar-borne RNA viruses

description: Wild boar-borne RNA viruses were recovered by meta-transcriptomic (MTT) analysis. Sequencing Technology is Illumina.
description: Wild boar-borne RNA viruses were recovered by meta-transcriptomic (MTT) analysis. Sequencing Technology is Illumina.
DOI: 10.15468/dl.d9vt9a
title: Occurrence Download

description: A dataset containing 5122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (BOL.6.4.3_2, BOL.6.1.1_2, BOL.6.2.2_2, BOL.6.2.3_2)",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 5122 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006117-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.24257
title: Coal Mine Roadway Surrounding Rock Stability Dataset and ISCSO-KELM code
title: Coal Mine Roadway Surrounding Rock Stability Dataset and ISCSO-KELM code

description: Coal mine roadway surrounding rock stability dataset 
description: Coal mine roadway surrounding rock stability dataset
DOI: 10.57760/sciencedb.25278
title: L2 Motivation, Foreign Language Enjoyment and Learning Engagement
title: L2 Motivation, Foreign Language Enjoyment and Learning Engagement

description: Taking foreign language enjoyment as mediator, this study aims to explore the mechanism of L2 motivation impacting learning engagement among Chinese college students. Participants were 300 college students from China.
description: Taking foreign language enjoyment as mediator, this study aims to explore the mechanism of L2 motivation impacting learning engagement among Chinese college students. Participants were 300 college students from China.
DOI: 10.57760/sciencedb.j00124.00225
title: Tailoring of Pt particle density on the surface of dealuminated ZSM-5 and its hexane cracking performance
title: 脱铝H-ZSM-5表面Pt颗粒密度调控及其己烷裂解性能研究

description: By acid-treating ZSM-5 zeolite to regulate its silica-to-alumina ratio (SAR) and surface acid sites, combined with loading platinum (Pt) at varying mass percentages via the Metal-Organic Solid-Phase Synthesis method, this study investigated the effect of metal-acid site ratios on the catalytic cracking of n-hexane to propane. Results demonstrated that acid treatment significantly increased the SAR of the zeolite (from 27 to 100), optimized the distribution of surface acidsites, while preserving the MFI topology. Post-Pt loading, the catalyst exhibited highly dispersed Pt nanoparticles (3.3–4.1 nm) without forming crystalline aggregates. Catalytic performance tests revealed that acid treatment enhanced the n-hexane conversion rate from 66% to 88% and propane selectivity from 50% to 57%. Pt loading exhibited a pronounced influence on performance: the medium-loaded catalyst (0.3wt%) achieved the highest propane selectivity (57%) and stability due to optimal metal-acid synergy. XPS and CO-DRIFTS analyses indicated that Pt loading reduced the electron density of oxygen species, thereby strengthening metal-acid interactions. This work provides a catalyst design strategy for the efficient and directional conversion of n-hexane.
description: By acid-treating ZSM-5 zeolite to regulate its silica-to-alumina ratio (SAR) and surface acid sites, combined with loading platinum (Pt) at varying mass percentages via the Metal-Organic Solid-Phase Synthesis method, this study investigated the effect of metal-acid site ratios on the catalytic cracking of n-hexane to propane. Results demonstrated that acid treatment significantly increased the SAR of the zeolite (from 27 to 100), optimized the distribution of surface acidsites, while preserving the MFI topology. Post-Pt loading, the catalyst exhibited highly dispersed Pt nanoparticles (3.3–4.1 nm) without forming crystalline aggregates. Catalytic performance tests revealed that acid treatment enhanced the n-hexane conversion rate from 66% to 88% and propane selectivity from 50% to 57%. Pt loading exhibited a pronounced influence on performance: the medium-loaded catalyst (0.3wt%) achieved the highest propane selectivity (57%) and stability due to optimal metal-acid synergy. XPS and CO-DRIFTS analyses indicated that Pt loading reduced the electron density of oxygen species, thereby strengthening metal-acid interactions. This work provides a catalyst design strategy for the efficient and directional conversion of n-hexane.
DOI: 10.15468/dl.65qthb
title: Occurrence Download

description: A dataset containing 684370 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Malva L."
 ]
}

 The dataset includes 684370 records from 3166 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006111-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6s22fj
title: Occurrence Download

description: A dataset containing 1179 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Japan, China, Russian Federation, Korea (Democratic People’s Republic of))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Chosenia arbutifolia (Pall.) A.K.Skvortsov"
 ]
}

 The dataset includes 1179 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014767-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15165132
title: Data: Brain-computer interface control with artificial intelligence copilots

description: Dataset for "Brain-computer interface control with artificial intelligence copilots"

Abstract

Motor brain-computer interfaces (BCIs) decode neural signals to help people with paralysis move and communicate. Even with important advances in the last two decades, BCIs face key obstacles to clinical viability: BCI performance should strongly outweigh BCI costs and risks. We use shared autonomy, where artificial intelligence (AI) copilots collaborate with BCI users to achieve task goals, to significantly increase the performance of BCIs. We demonstrate this "AI-BCI" in a non-invasive BCI system decoding electroencephalography (EEG). We first contribute a hybrid adaptive decoding approach using a convolutional neural network (CNN) and ReFIT-like Kalman filter (KF), enabling healthy users and a paralyzed participant to autonomously and proficiently control computer cursors and robotic arms with EEG. We then demonstrate AI-BCIs that enable a paralyzed participant to (1) achieve 4.3× higher performance in a cursor control task and (2) control a robotic arm to sequentially move random objects to random locations, a task he could not do without an AI copilot. As AI copilots improve, BCIs designed with shared autonomy may achieve higher performance.
DOI: 10.5281/zenodo.15165133
title: Data: Brain-computer interface control with artificial intelligence copilots

description: Dataset for "Brain-computer interface control with artificial intelligence copilots"

Abstract

Motor brain-computer interfaces (BCIs) decode neural signals to help people with paralysis move and communicate. Even with important advances in the last two decades, BCIs face key obstacles to clinical viability: BCI performance should strongly outweigh BCI costs and risks. We use shared autonomy, where artificial intelligence (AI) copilots collaborate with BCI users to achieve task goals, to significantly increase the performance of BCIs. We demonstrate this "AI-BCI" in a non-invasive BCI system decoding electroencephalography (EEG). We first contribute a hybrid adaptive decoding approach using a convolutional neural network (CNN) and ReFIT-like Kalman filter (KF), enabling healthy users and a paralyzed participant to autonomously and proficiently control computer cursors and robotic arms with EEG. We then demonstrate AI-BCIs that enable a paralyzed participant to (1) achieve 4.3× higher performance in a cursor control task and (2) control a robotic arm to sequentially move random objects to random locations, a task he could not do without an AI copilot. As AI copilots improve, BCIs designed with shared autonomy may achieve higher performance.
DOI: 10.15468/dl.zshtgh
title: Occurrence Download

description: A dataset containing 1455798 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-04-02",
 "EventDate is less than or equal to 2025-05-02",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 1455798 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006243-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5j2drp
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "Geometry POLYGON((-102 -26,103 -26,103 28,-102 28,-102 -26))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Adenophora jasionifolia Franch."
 ]
}

 The dataset includes 48 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011169-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.euh4nk
title: Occurrence Download

description: A dataset containing 158614 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Academy of Natural Sciences Ichthyology Collection"
 ]
}

 The dataset includes 158614 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000549-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.