cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1558149.v1
title: Woodlot, Dataset #3 - Comparing Distance and Diameter of Trees Using Transect Techniques

description: The data was collected at the woodlot of York University Campus on Wednesday, September 23, 2015 at 4:10 pm to 4:50 pm contributed by J. Quach, L. Tran, Amin A., S. Alvi and I. Darman. At arrival on the woodlot, our group started walking from the edge of the woodlot until reaching the centre of the woodlot in a straight line, extending the transect tape along the way. Every instance an adult tree is encountered, the diameter at breast height (DBH) was measured in metres using transect measuring tape from chest level and after the nearest tree is encountered, the distance between each pair of trees is measured in metres using transect measuring tape. Furthermore, the adult trees of each pair were observed through one’s field of vision and labeled from a scale of 0 to 2, where 0 meaning the tree is dead, 1 meaning the tree is living and 2 meaning the tree has a huge green canopy. These steps are then replicated for a total of 10 times for each pair of trees. The purpose of this experiment indicates that the data shown marks the distinction of proximity between each pair of trees varying on growth conditions and sizes, where it can be a useful indicator whether an ecosystem is endangered or not, as well to be useful to other fields of research.
DOI: 10.6084/m9.figshare.25965436.v1
title: BME688_bacterial_culture_time-series.zip

description: Background The dataset represents the time-series of the released gases of different concentrations of bacteria that were cultured in blood agar plates. Using the BME688 gas sensor from Bosch Sensortec, the released gases during bacterial growth were monitored and logged in real-time for 20-24 hours. The measurements took place inside an incubator at ~37 degC.Dataset descriptionThe dataset includes measurements of Escherichia Coli ATCC25922, Enterococcus Faecalis ATCC29212, Streptococcus agalactiae ATCC13813 and Pseudomonas aeruginosa ATCC25668. The column headers are the time in hours followed by the concentrations from lowest to highest in cfu/mL. Finally, the file names include the date of the measurement in the format YYYY-MM-DD and the name of the bacterium measured. Publication linkhttps://ieeexplore.ieee.org/abstract/document/10541905<b>DOI:</b><b> </b>10.1109/JSEN.2024.3402828Panteli, Christoforos, Marios Stylianou, Andreas Anastasiou, and Chrysafis Andreou. "Gas-Phase Detection of UTI-causing Bacteria using Off-the-Shelf Gas Sensors and Change-Point Detection." <i>IEEE Sensors Journal</i> (2024).<br>
DOI: 10.1594/pangaea.841933
title: Carbonate system during the May 2013 MedSeA cruise

description: The 2013 MedSeA oceanographic cruise along the Mediterranean Sea was an essential part of the European project "Mediterranean Sea Acidification in a changing climate - MEDSEA" (http://medsea-project.eu/) , within the FP7 Cooperation program. The MedSeA campaign is also part of an international program GEOTRACES that aims to characterize and study the seawater dissolved elements.Potentiometric titration of Alkalinity was measured in a closed cell, according to the DOE handbook of methods for CO2 analysis (DOE, 1994; http://cdiac.ornl.gov/oceans/DOE_94.pdf). The precision of AT analysis was determined to be ± 2 µmol/kg. The accuracy of AT measurements was determined to be ± 1 µmol kg-1 by analyzing Certified Reference Material (Andrew Dickson, CA, USA).Potentiometric titration of Inorganic Carbon was measured in a closed cell, according to the DOE handbook of methods for CO2 analysis (DOE, 1994; http://cdiac.ornl.gov/oceans/DOE_94.pdf). The precision of CT analysis was determined to be ± 4 µmol/kg. The accuracy of CT measurements was determined to be ± 4 µmol/kg by analyzing Certified Reference Material (Andrew Dickson, CA, USA).
DOI: 10.6084/m9.figshare.82880.v1
title: Enhancer of the rudimentary gene homologue () expression pattern in sporadic human breast cancer and normal breast tissue-3

description: Fold more abundant in breast tumours as compared to normal breast tissue (mean expression in normal breast was set = 1.0). N: normal breast; T: invasive breast cancer.<b>Copyright information:</b>Taken from "Enhancer of the rudimentary gene homologue () expression pattern in sporadic human breast cancer and normal breast tissue"http://www.biomedcentral.com/1471-2407/8/145BMC Cancer 2008;8():145-145.Published online 23 May 2008PMCID:PMC2426700.
DOI: 10.1594/pangaea.116197
title: Total carbon dioxide and total alkalinity at station TT049_29-2
DOI: 10.1594/pangaea.129300
title: Total organic carbon from CTD cast KIWI-6/22-3
DOI: 10.17632/gsvbn5gt7r
title: DEVELOPMENT OF LITERACY-BASED NORMATIVE DATA FOR THE WESTERN APHASIA BATTERY (WAB-K)

description: A noteworthy discovery pertains to the possibility of misdiagnosing anomic aphasia as a false positive, especially in individuals who are illiterate and have normal performance on all subtests except for naming. The study highlights the need of considering literacy levels when assessing WAB-K results in order to avoid making inaccurate diagnoses.
The percentile scores in the appendix provide a method for evaluating individual performance on each subtest and can aid in identifying language anomalies in non-aphasic brain-injured individuals, such as those with dementia.
This research provides normative data on the WAB-K for individuals aged 45 and above who are illiterate, semi-literate, or literate. The results highlight the potential constraints of specific subgroups in persons with low literacy levels, underscoring the significance of include literacy level information while administering the WAB-K test to ensure accurate diagnostic interpretation, especially in cases with anomic aphasia. Percentile ratings are a valuable method for evaluating individuals with language impairments who are not experiencing aphasia in clinical environments.
DOI: 10.17632/pfs488kjyg
title: Data for "Insecticide Monitoring in Cattle Dip with an E-Nose System and Room Temperature Screen-Printed ZnO Gas Sensors".

description: Data for the MDPI Agriculture submission of a paper titled "Insecticide Monitoring in Cattle Dip with an E-Nose System and Room Temperature Screen-Printed ZnO Gas Sensors."
DOI: 10.17632/vhng7jdvfb
title: Reference and Target Datasets with the Point-Descriptor-Precedence representation

description: There are four reference datasets generated using the animations given in slides 1-4 of the Animation.pptx: Reference Movement Pattern with one-point, two-points, four-points, and two-points for the length, width and speed analysis. The animations are stored in the video format and then a sequence of images were extracted to create static reference datasets/movement patterns. The Target dataset consists of 46 vehicles and is created using the animation given in Target.pptm, which has a built in macro to run the simulation and save it in a video format. The video is then used to extract images which matched exactly with the reference datasets. This resulted in finding the exact matches of the reference datasets. The code is written in Python and can be run with any Python IDE.
DOI: 10.6084/m9.figshare.26379301.v2
title: <b>Comparative Analysis of different Machine Learning Algorithms for Urban Footprint Extraction in Diverse Urban Contexts Using High-Resolution Remote Sensing Imagery</b>

description: The data involved in this paper is from https://www.planet.com/explorer/. The resolution is 3m, and there are 3 main bands, RGB. Since the platform can only download a certain amount of data after applying for an account in the form of education, and at the same time the data is only retained for one month, we chose 8 major cities for the study, 2 images per city. we also provide detailed information on the data visualization and classification results that we have tested and retained in a PPT file called paper, we also provide detailed information on the data visualization and classification results of our tests in a PPT file called paper-result, which can be easily reviewed by reviewers. At the same time, reviewers can also download the data to verify the applicability of the results based on the coordinates of the data sources provided in this paper.<br>The algorithms consist of three main types, one is based on traditional algorithms including object-based and pixel-based, in which we tested the generalization ability of four classifiers, including Random Forest, Support Vector Machine, Maximum Likelihood, and K-mean, in the form of classification in this different way. In addition, we tested two of the more mainstream deep learning classification algorithms, U-net and deeplabV3, both of which can be found and applied in the ArcGIS pro software. The traditional algorithms can be found by checking <b>https://pro.arcgis.com/en/pro-app/latest/help/analysis/image-analyst/the-image-classification-wizard.htm</b> to find the running process, while the related parameter settings and Sample selection rules can be found in detail in the article. Deep learning algorithms can be found at <b>https://pro.arcgis.com/en/pro-app/latest/help/analysis/deep-learning/deep-learning-in-arcgis-pro.htm</b>, and the related parameter settings and sample selection rules can be found in detail in the article. Finally, the big model is based on the SAM model, in which the running process of SAM is from <b>https://github.com/facebookresearch/segment-anything</b>, and you can also use the official Meta segmentation official website to provide a web-based segmentation platform for testing <b>https:// segment-anything.com/</b>. However, the official website has restrictions on the format of the data and the scope of processing.
DOI: 10.6084/m9.figshare.27641982.v4
title: Data from: Responses of subsoil organic carbon to climate warming and cooling is determined by microbial community rather than its molecular composition

description: Little is currently known about how long-term climate changes modulate the relationship between soil organic carbon (SOC) molecular composition, microbial community and SOC storage, and the mechanisms involved. Here, we show substantial changes in subsoil SOC in the Qinghai-Tibetan alpine grasslands over 16 years of soil warming and cooling. Warming reduced SOC content by 8.5%, while cooling increased it by 7.0%. Neither warming nor cooling affected plant- and microbial-derived molecular components. However, warming elevated fungal-to-bacterial biomass ratio (F/B) and gram-positive to gram-negative bacterial biomass ratio (G+/G-) by 15.0% and 8.6%, respectively, whereas cooling reduced them by 4.5% and 9.6%. Warming reduced SOC storage by directly increasing F/B and G+/G- and indirectly decreasing the soil carbon-to-nitrogen ratio, whereas cooling enhanced SOC storage primarily by decreasing F/B. Conventional warming experiments, which consider only climate warming and neglect cooling, may underestimate the negative impacts of warming on subsoil SOC pools in alpine grasslands.
DOI: 10.1594/pangaea.129306
title: Total organic carbon from CTD cast KIWI-6/4-1
DOI: 10.1594/pangaea.129311
title: Total organic carbon from CTD cast KIWI-6/8-2
DOI: 10.6084/m9.figshare.20406279.v1
title: Supplementary data for Islam et al. 2022 - PCAWG reanalysis

description: All results from the <em>de novo </em>extraction of mutational signatures from the Pan-Cancer Analysis of Whole Genomes (PCAWG) dataset.
DOI: 10.6084/m9.figshare.23504010.v1
title: HMAP Dataset 14: Galapagos Marine Reserve, Ecuador II

description: Although commercial fishing activity commenced in Galapagos during the 1920s, it was not until 1997 that the systematic collection of fishing and biological data was initiated by the newly-founded Participatory Programme of Fisheries Monitoring and Research (PIMMP). Since then, the PIMPP has collected on a daily basis site-specific catches and effort data for the main fisheries of the GMR. Consequently, a large and complex amount of fishing related data has been generated. All this data was reviewed, standardized and edited by researchers of the CDF between March 2005 and December 2007. In addition, a range of primary source material was used to assemble pre-1997 data on the sea cucumber, spiny lobster and finfish fisheries.
DOI: 10.6084/m9.figshare.4519724.v1
title: Proteomics in cardiovascular disease: recent progress and clinical implication and implementation

description: <b>Introduction</b>: Although multiple efforts have been initiated to shed light into the molecular mechanisms underlying cardiovascular disease, it still remains one of the major causes of death worldwide. Proteomic approaches are unequivocally powerful tools that may provide deeper understanding into the molecular mechanisms associated with cardiovascular disease and improve its management. <b>Areas covered</b>: Cardiovascular proteomics is an emerging field and significant progress has been made during the past few years with the aim of defining novel candidate biomarkers and obtaining insight into molecular pathophysiology. To summarize the recent progress in the field, a literature search was conducted in PubMed and Web of Science. As a result, 704 studies from PubMed and 320 studies from Web of Science were retrieved. Findings from original research articles using proteomics technologies for the discovery of biomarkers for cardiovascular disease in human are summarized in this review. <b>Expert commentary</b>: Proteins associated with cardiovascular disease represent pathways in inflammation, wound healing and coagulation, proteolysis and extracellular matrix organization, handling of cholesterol and LDL. Future research in the field should target to increase proteome coverage as well as integrate proteomics with other omics data to facilitate both drug development as well as clinical implementation of findings.
DOI: 10.1594/pangaea.129304
title: Total organic carbon from CTD cast KIWI-6/3-17
DOI: 10.1594/pangaea.129310
title: Total organic carbon from CTD cast KIWI-6/8-13
DOI: 10.17632/8fr59wg748
title: raw_fastq

description: Raw fastq files for a Mock Microbial community
DOI: 10.17632/vg5f62mmv7
title: Supplemental Table II

description: Most Common Signs, Symptoms, and Diagnostic Modalities for Diagnosing Carpal Tunnel Syndrome
DOI: 10.6084/m9.figshare.19607190.v2
title: Supplementary Dataset 1

description: <strong>The diversity of quinoa morphological traits and seed metabolic composition</strong> Iman Tabatabaei, Saleh Alseekh, Mohammad Shahid, Ewa Leniak, Mateusz Wagner, Henda Mahmoudi, Sumitha Thushar, Alisdair R. Fernie, Kevin M. Murphy, Sandra M. Schmöckel, Mark Tester, Bernd Mueller-Roeber, Aleksandra Skirycz, Salma Balazadeh
DOI: 10.6084/m9.figshare.22300303.v1
title: ROB2_IRPG_beta_v9.xlsm

description: RoB2 Excel Sheet - Risk of bias sheet for randomized controlled trial for Cochrane paper
DOI: 10.6084/m9.figshare.28735742.v1
title: 灵芝来源的活性miRNA的筛选及验证——以KRAS基因为靶点--毕业论文附表.xlsx

description: 胰腺癌是最致命的癌症之一。不幸的是，现有的治疗胰腺癌的化疗药物会产生明显的副作用，并且胰腺癌容易对这些化疗药物产生耐药性。因此，迫切需要开发新的药物，为胰腺癌患者提供更多的治疗选择。与传统的蛋白质靶向和基于DNA的药物相比，基于核糖核酸（RNA）的药物由于其独特的物理化学和生理特性，近年来受到了广泛的关注。 KRAS突变在肿瘤中占比非常高（如胰腺癌90%），但直接靶向KRAS的小分子药物研发困难。灵芝是一种传统中药，具有多种药理活性，但其来源的miRNA研究较少。本课题基于灵芝来源的miRNA在胰腺癌新药开发中的潜力，聚焦于KRAS基因，旨在从灵芝miRNA中筛选出能下调KRAS基因的miRNA，为胰腺癌新药开发提供了新思路。在之前的研究中，我们通过高通量测序鉴定出了灵芝中存在的milRNAs共168个。首先我们利用现有的四个预测网站（MiRanda、RNAhybrid、PITA和Targetscan）对这168个miRNA进行初步预测分析。对以上四个网站的结果取交集进行汇总后，初步筛选出48个miRNA。 随后，为了进一步验证这48个miRNA靶向KRAS基因的活性，我们通过qRT-PCR实验进行验证。首先我们成功构建了25个miRNA载体质粒，质粒扩繁后进行了去内毒素提取，然后转染到PANC-1人胰腺癌细胞中，孵育36h后提取细胞总RNA，逆转录为cDNA，最后进行qRT-PCR实验。结果表明，miR-0001和miR-0002转染PANC-1细胞后可下调KRAS基因的表达，其余23个miRNA均表现出上调的作用。 最后，我们对筛选出来的miR-0001和miR-0002进行药效评价。在CCK8细胞增殖实验中，细胞分别转染mimics0001，mimics0002和mimics0000。mimics0000作为阴性对照。结果表明，mimics0001和mimics0002起到抑制PANC-1细胞增殖的作用。细胞转染mimics0001和mimics0002后的细胞抑制率分别是40.72%和20.49%。在体内裸鼠成瘤实验中，给药14天后，mimics0001组、mimics0002组和吉西他滨组的瘤体积明显小于mimics0000组和生理盐水组的瘤体积。mimics0000组的抑瘤率是29.94%，而mimics0001组、mimics0002组和吉西他滨组的抑瘤率分别是87.90%，81.69%和80.99%，与mimics0000组间均有统计学差异（P&lt;0.01）。说明mimics0001和mimics0002起到明显抑制胰腺癌肿瘤的作用。 本课题首次提出灵芝miRNA跨界调控人KRAS基因的设想，为中药来源的miRNA在肿瘤治疗中的应用提供了新思路,同时也为从天然药物中挖掘功能性miRNA提供了实例。
DOI: 10.6084/m9.figshare.28928150.v1
title: The Implementation of Online Blended Learning Best Practices within Hospitality Higher Education - Impacts on Student Engagement

description: In hospitality higher education, there remains a critical gap in understanding how to effectively measure student engagement within online blended learning environments within hospitality higher education. Existing methods overlook the complex behaviours, motivations and contextual influences that shape genuine, authentic participation. This study addresses this gap by applying Redmond's Online Engagement Framework (2018) to evaluate how best practice engagement strategies – incorporating cognitive, emotional, behavioural, social and collaborative dimensions in an online hospitality blended learning module impacts student motivation and engagement. The research aims to enhance and inform digital pedagogical approaches and offer transferable insights for broader implementation in hospitality higher education institutions.A mixed–methods research design was employed, involving analysis of learner logs, focus group interviews, discussion forums, Canvas LMS Data Analytics and student surveys from a small hospitality student cohort. Thematic content analysis revealed successful engagement outcomes such as enhanced active participation, strong peer support and increased student satisfaction in the delivery and module design. However, challenges were also evident, including student cognitive overload, emotional disengagement and technological barriers. The findings indicate a need for additional collaborative group tasks and assessments to deepen engagement and alleviate pressures on individual learners. This study contributes to the evolving landscape of online hospitality education by offering practical strategies that foster meaningful student engagement that informs future improvements in online hospitality higher education learning design, pedagogical practice and delivery.
DOI: 10.1594/pangaea.129288
title: Total organic carbon from CTD cast KIWI-6/1-11
DOI: 10.17632/fhyy8ztcjx
title: Code repository for "Intermediation Frictions in Debt Relief: Evidence from CARES Act Forbearance"

description: Code repository and pseudo-data for the paper "Intermediation Frictions in Debt Relief: Evidence from CARES Act Forbearance"; to accompany the published paper appearing in the Journal of Financial Economics.
DOI: 10.6084/m9.figshare.15102012.v1
title: Cleaned_Data Survey & AI Indicators_202010110.xlsx

description: This study examines an artificial intelligence (AI)- powered automated system that uses speech and facial recognition to track both teacher and learner behavior, expressions, and exchanges in real-time in a one-to-one 25-minute online English class. Within 72 hours of the online class, a learner engagement survey was completed by each learner. The study also correlated the learners’ self-reported engagement with the engagement variables extracted by the AI.
DOI: 10.1594/pangaea.121335
title: Total carbon dioxide and alkalinity at station TT012_5-CTD73
DOI: 10.1594/pangaea.121337
title: Total carbon dioxide and alkalinity at station TT012_5-CTD77
DOI: 10.17632/pwfddp8m76
title: Effects of High-Intensity Personalized Temporal Interference Targeting Striatum on Structure-Function Coupling and Topology of Brain Networks: A Crossover Double-Blind Randomized Sham-Controlled Trial

description: The dataset comprises functional connectivity (FC) and structural connectivity (SC) matrices derived from a crossover, double-blind, randomized controlled trial of Temporal Interference (TI) stimulation. Four distinct matrices are presented: TI-S1 and TI-S2 functional and structural connectivity matrices, alongside corresponding Sham-S1 and Sham-S2 matrices. These matrices, constructed using the Dosenbach 160-region atlas, represent brain network connections before and after stimulation, enabling comprehensive analysis of neural network modifications induced by personalized right striatum TI stimulation in 28 healthy participants.
DOI: 10.17632/th7fztbrv9
title: Data for: USING MACHINE LEARNING TO PREDICT OVARIAN CANCER

description: Supplementary data 1: It contains the original raw data. Supplementary data 2: It contains a list of biomarkers, their abbreviations, and their descriptions used in the study. Supplementary data 3: It contains the imputed version of the training data without the biomarker CA72-4. Supplementary data 4: It contains the raw training data. Supplementary data 5: It contains the raw test data.
DOI: 10.6084/m9.figshare.21322401.v10
title: A kriging interpolation model for geographical flows

description: This dataset contains the code and data used in the case study mentioned in the paper "A kriging interpolation model for geographical flows".<b>Title </b>A kriging interpolation model for geographical flows<b>Abstract</b>The kriging model can accommodate various spatial supports and has been extensively applied in hydrology, meteorology, soil science, and other domains. With the expansion of applications, it is essential to extend the kriging model for new spatial support of high-dimensional data. Geographical flows can depict the movements of geographical objects and imply the underlying mobility patterns in geographical phenomena. However, due to the bias, sparsity, and uneven quality of flow data in the real world, research about flows remains hindered by the lack of complete flow data and effective flow interpolation methods. In this study, we design a kriging interpolation model for flows based on several flow-related concepts and the autocorrelation of flows. We also analyze the second-order stationarity and anisotropy in the flow spatial random field. To illustrate the effectiveness and applicability of our method, we conduct two case studies. The former case study compares several experiments of flow density interpolation using Beijing mobile signaling data and illustrates the conditions of applicable areas. The latter case study extends our model to other flow attributes, such as travel time uncertainty, using Beijing taxi origin-destination flow data. The results of these cases demonstrate the effectiveness and high accuracy of our model.<br>
DOI: 10.1594/pangaea.116049
title: Total carbon dioxide and total alkalinity at station TT043_13-18
DOI: 10.1594/pangaea.116060
title: Total carbon dioxide and total alkalinity at station TT043_17-23
DOI: 10.6084/m9.figshare.3552168.v1
title: Supplement 1. R code to compute nonparametric estimates of drift, total sigma, diffusion, jump intensity, and jump magnitude for a univariate time series supplied by the user.

description: File List Bandi4d.r Description Bandi4d.r contains R code to compute nonparametric estimates of drift, total sigma, diffusion, jump intensity and jump magnitude for a univariate time series supplied by the user. Comment lines specify the inputs to the function and the outputs from the function. The code may be called from an R program as an external function, or it may be placed in-line within a R program.
DOI: 10.6084/m9.figshare.9211643.v5
title: Tetrapod uCT scan data: pathologies

description: from this paper:Herbst, E.C., Doube, M., Smithson, T.R., Clack, J.A., Hutchinson, J.R. 2019. Bony lesions in early tetrapods and the evolution of mineralized tissue repair. Paleobiology, in press. <br>see table in supp info for more specimen metadata: doi:10.5061/dryad.30kp1qg<br>Crassigyrinus and Eoherpeton early tetrapod postcranial elements with pathologies (8 scan datasets as .zip archives):<br>1. Crassigyrinus NHMUKVPR10000_healed_rib_fragment<br>2. Crassigyrinus NMSG1984.15.1ABC L fibula, L ilium, L femur<br>3. Crassigyrinus NMSG1984.15.2 metatarsal pathology<br>4. Crassigyrinus NMSG1984.15.3_L ischium R tibia R fibula, presacral rib<br>5. Crassigyrinus NHMUK R1000_rib fragment_high resolution: sampled_every_5th slice6. Crassigyrinus NMSG1984.15.3 tibia_proximal_only_higher_resolution- every 2nd slice7. Eoherpeton NMS G 1993.56.25 R fibula distal section high resolution<br>8. Eoherpeton R_fibula &b Neural Arches_1993.56.25, 33A &33B_8bit<br>