cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20325242.v2
title: Supplementary Table 1 from Colour vision in thrips (Thysanoptera)

description: Supplemental Table 1. Summarised results of visual attraction studies in thrips. This table is included as a digital supplement XLS file. Information provided in this table has been updated and modified from [53]. Within each row, each representing one individual study, colour response is ranked with a preference score. A preference score of 1 indicates the colour with the largest number of thrips caught, while increasing numbers (up to 6) indicate colours with fewer thrips caught. When certain colours did not result in significantly different catch numbers, we appended lower-case letters to an equivalent preference score number value. The letters are ordered from the highest catch levels (a) to the lowest catch levels (f). For the graphical display of these colour response results shown in Figure 5, we normalized the greatest preference response (1) to the largest circle (diameter = 1) and gave subsequently lower responses smaller circles (diameter = 0.5, 0.33, 0.25, 0.2, and 0.17). Insignificant differences in preference received equivalently sized circles. For species where multiple studies were available, we averaged the responses and renormalized the largest circle to the best (lowest) mean preference score. Lifestyle, hosts, origin, and distribution information shown in this table was gathered from [46–52]. (NA) Not applicable/Not available. (*) UV reflectance not reported, white -UV assumed. (**) UV reflectance not reported, white +UV assumed. (+) Colour attraction ranking based on several experiments in the same study. (++) Fluorescent yellow caught the most numbers in this study.
DOI: 10.6084/m9.figshare.20325242.v1
title: Supplementary Table 1 from Colour vision in thrips (Thysanoptera)

description: Supplemental Table 1. Summarised results of visual attraction studies in thrips. This table is included as a digital supplement XLS file. Information provided in this table has been updated and modified from [53]. Within each row, each representing one individual study, colour response is ranked with a preference score. A preference score of 1 indicates the colour with the largest number of thrips caught, while increasing numbers (up to 6) indicate colours with fewer thrips caught. When certain colours did not result in significantly different catch numbers, we appended lower-case letters to an equivalent preference score number value. The letters are ordered from the highest catch levels (a) to the lowest catch levels (f). For the graphical display of these colour response results shown in Figure 5, we normalized the greatest preference response (1) to the largest circle (diameter = 1) and gave subsequently lower responses smaller circles (diameter = 0.5, 0.33, 0.25, 0.2, and 0.17). Insignificant differences in preference received equivalently sized circles. For species where multiple studies were available, we averaged the responses and renormalized the largest circle to the best (lowest) mean preference score. Lifestyle, hosts, origin, and distribution information shown in this table was gathered from [46–52]. (NA) Not applicable/Not available. (*) UV reflectance not reported, white -UV assumed. (**) UV reflectance not reported, white +UV assumed. (+) Colour attraction ranking based on several experiments in the same study. (++) Fluorescent yellow caught the most numbers in this study.
DOI: 10.22008/fk2/vocgwd/eolk9s
title: DA17 NG ST14 171G_XRF.xlsx

description: X-Ray Fluorescence data from DA17-NG-ST14 171G
DOI: 10.22008/fk2/vocgwd/udh7o5
title: DA17 NG ST14 171G_organic matter composition.xlsx

description: Total organic carbon (TOC) and total nitrogen (TN) concentrations (%), molecular ratio of total organic carbon to nitrogen (C:N), isotopic composition of organic carbon (δ13Corg; ‰ vs PDB) and nitrogen (δ15N; ‰ vs air). Biogenic silica (BSi) concentrations (mg g-1 dry mass) and fluxes (mg cm2 yr-1).
DOI: 10.22008/fk2/vocgwd/8r7rhg
title: DA17 NG ST14 171G_foraminifera.xlsx

description: Fluxes of planktonic and benthic foraminifera and the proportion of benthic agglutinated taxa (relative to total benthic assemblage). Relative abundances (%) of all foraminifera species/taxa ordered alphabetically
DOI: 10.22008/fk2/vocgwd/ootfig
title: DA17 NG ST14 171G_palynology.xlsx

description: Total dinoflagellate cyst fluxes, relative abundance of dinoflagellate cyst tax/species, flux of Halodinium spp., proportions of reworked Cretaceous/recent dinoflagellate cysts, flux of organic foraminifera linings and the ratio of Autotrophic to Heterotrophic species.
DOI: 10.22008/fk2/vocgwd
title: Data from North-East Greenland shelf marine sediment core DA17-NG-ST14-171G; Marine conditions and development of the Sirius Water polynya on the North-East Greenland shelf during the Younger Dryas-Holocene

description: Downcore data obtained from various analyses of Gravity core DA17-NG-ST14-171G (74° 5.413’ N; 19° 25.862’ W, 341 m water depth, 420 cm sediment recovery) and Rumohr lot core DA17-NG-ST14-168R (74° 5.453' N; 19° 25.901' W, 341 m water depth, 89 cm sediment recovery), retrieved from the North-East Greenland shelf about 30 km offshore the Young Sound-Tyrolerfjord onboard the R/V Dana NorthGreen Expedition in 2017.
DOI: 10.5281/zenodo.6860745
title: Turkish Pedestrian Dataset - TURPED

description: <strong>Data abstract:</strong><br> This Zenodo upload contains the Turkish Pedestrian Dataset (TURPED) for benchmarking and developing pedestrian detection methods for autonomous driving assistance systems. There are three folders named "Annotations", "Image Sets" and "JPEGImages". The annotations folder includes the pedestrian labels for each image in an XML format. The standard Pascal VOC XML annotation format is chosen to ease of use. The TXT files in the image sets folder describe which images are in training/validation/test sets. Finally, the images can be found in the JPEGImages folder in JPEG format.
DOI: 10.5281/zenodo.6860744
title: Turkish Pedestrian Dataset - TURPED

description: <strong>Data abstract:</strong><br> This Zenodo upload contains the Turkish Pedestrian Dataset (TURPED) for benchmarking and developing pedestrian detection methods for autonomous driving assistance systems. There are three folders named "Annotations", "Image Sets" and "JPEGImages". The annotations folder includes the pedestrian labels for each image in an XML format. The standard Pascal VOC XML annotation format is chosen to ease of use. The TXT files in the image sets folder describe which images are in training/validation/test sets. Finally, the images can be found in the JPEGImages folder in JPEG format.
DOI: 10.6084/m9.figshare.20337633
title: Classifying urban form at national scale: The British morphosignatures

description: Data produced for the <em>Classifying urban form at national scale: The British morphosignatures </em>research paper. <br> More details about the project can be found at the project website https://urbangrammarai.xyz. <br> The paper is available from https://doi.org/10.17868/strath.00080527.
DOI: 10.6084/m9.figshare.20337633.v1
title: Classifying urban form at national scale: The British morphosignatures

description: Data produced for the <em>Classifying urban form at national scale: The British morphosignatures </em>research paper. <br> More details about the project can be found at the project website https://urbangrammarai.xyz. <br> The paper is available from https://doi.org/10.17868/strath.00080527.
DOI: 10.6084/m9.figshare.20161244
title: CLER.nvpx.zip

description: NVivo project where reviewed articles are stored, coded and annotated for the purposes of a literature review regarding the issue of scale matches and mismatches in recent ecological literature. The project includes coding matrices and allows for articles' exploration through other tools such as hierarchy charts and frequency count.
DOI: 10.6084/m9.figshare.20161244.v1
title: CLER.nvpx.zip

description: NVivo project where reviewed articles are stored, coded and annotated for the purposes of a literature review regarding the issue of scale matches and mismatches in recent ecological literature. The project includes coding matrices and allows for articles' exploration through other tools such as hierarchy charts and frequency count.
DOI: 10.34740/kaggle/dsv/3960555
title: YouTube Daily
DOI: 10.5519/qd.ma1d3fvt
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4073 records)
DOI: 10.5517/ccdc.csd.cc22c44r
title: CCDC 1917323: Experimental Crystal Structure Determination

description: Related Article: Marwa Mhiri, Mohamed Boujelbene|2021|Polym.Bull.|79|5843|doi:10.1007/s00289-021-03758-y
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25326/366
title: Caravela data

description: Data collected on Caravela, an AutoNaut surface vessel, during Eurec4a 2020. Data is collected into 1 file per sensor, but is raw, uncalibrated and has no quality control.
DOI: 10.6084/m9.figshare.20332689
title: Mapping method for the integrated analysis of gentrification and touristification: the case of Málaga (Spain)

description: This compressed folder contains the information used in the elaboration of the research results.
DOI: 10.6084/m9.figshare.20332689.v1
title: Mapping method for the integrated analysis of gentrification and touristification: the case of Málaga (Spain)

description: This compressed folder contains the information used in the elaboration of the research results.
DOI: 10.5281/zenodo.6861105
title: frequency distribution

description: Data was obtained after a research analysis of environmental radon monitoring in Ghana, carried out in both dry and rainy season
DOI: 10.5281/zenodo.6861104
title: frequency distribution

description: Data was obtained after a research analysis of environmental radon monitoring in Ghana, carried out in both dry and rainy season
DOI: 10.6084/m9.figshare.20337672
title: Velocity, turbulence and sediment deposition in a channel partially filled with a Phragmites australis canopy

description: The experimental data in Table 1 in the paper.
DOI: 10.6084/m9.figshare.20337672.v1
title: Velocity, turbulence and sediment deposition in a channel partially filled with a Phragmites australis canopy

description: The experimental data in Table 1 in the paper.
DOI: 10.21985/n2-hsvg-kt12
title: Text Tables for Data Wrangling
DOI: 10.6084/m9.figshare.20080094.v3
title: DLBS3233

description: Dataset of DLBS3233
DOI: 10.21227/trcf-1s03
title: Dataset for Assessing Water Quality for Drinking and Irrigation Purposes using Machine Learning Models

description: Access to potable water is a critical requirement for human survival. Beyond drinking, water is also necessary for animal consumption, irrigation, as well as domestic and commercial uses. Laboratory assessments of water samples to determine their fitness for use is a vital step in water quality assurance processes. However, laboratory assessments require adherence to stringent measures, which might be difficult to comply with. Machine learning (ML) has emerged in recent years as viable and cheaper solutions to complement (or replace) lab-based assessments, with a caveat of availability of sufficient data to train the ML models. Unfortunately, such data are not always (or sparsely) available, especially in less developed countries. To this end, the work attempts to fill this gap by creating ample sized datasets that can be used to train (and test) ML models. Two datasets are curated in this work, one for drinking water and the other for irrigation water. The datasets were curated by aggregating data from smaller datasets on related concepts, then processed and labelled to make them useful for supervised ML models. To prove the applicability of the curated datasets, they were used to train ML models in a related work and yielded good results.
DOI: 10.34943/3c4ab5ca-cc5d-49f9-bbf9-c17ef7531608
title: Chatham Sound Oxygen Sensor Deployed 2022-07-16

description: The Aanderaa Optode 4531A (S/N 1215) was deployed on 2022-07-16 at Chatham Sound. Chatham Sound is a sound on the North Coast of British Columbia, located between Dundas and Stephens Islands and the Tsimpsean Peninsula near Prince Rupert. This device is a Oxygen Sensor. Oxygen sensors measure dissolved oxygen concentration in seawater. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/12280fe7-bae4-40bc-a46d-d506c9c863bf
title: Chatham Sound Fluorometer Deployed 2022-07-16

description: The WET Labs ECO FLRT 5959 was deployed on 2022-07-16 at Chatham Sound. Chatham Sound is a sound on the North Coast of British Columbia, located between Dundas and Stephens Islands and the Tsimpsean Peninsula near Prince Rupert. This device is a Fluorometer. Fluorometers measure the amount of stimulated electromagnetic radiation (fluorescence) produced by pulses of electromagnetic radiation emitted into the water column. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/8fae2ec5-02fd-4616-9258-b29aeba732ef
title: Chatham Sound Video Camera Deployed 2022-07-16

description: The Axis P1375 Camera SN ACCC8ED935C9 was deployed on 2022-07-16 at Chatham Sound. Chatham Sound is a sound on the North Coast of British Columbia, located between Dundas and Stephens Islands and the Tsimpsean Peninsula near Prince Rupert. This device is a Video Camera. Video cameras record video of characteristics of the surrounding environments and can be deployed on fixed and mobile platforms. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.21227/0fpj-mp91
title: Buddha statue dataset

description:   This dataset is comprised of two parts. In dataset 1, we provide Buddha images, along with positions of hands and faces. Dataset 2 provides Buddha images only and can be used for Buddha statue classification.
DOI: 10.34943/78856e96-ee65-4027-91c7-8cc4b7bdec2d
title: Chatham Sound Camera Lights Deployed 2022-07-16

description: The Ocean Networks Canada Light SN12 was deployed on 2022-07-16 at Chatham Sound. Chatham Sound is a sound on the North Coast of British Columbia, located between Dundas and Stephens Islands and the Tsimpsean Peninsula near Prince Rupert. This device is a Camera Lights. Camera lights are used to improve visibility where cameras are deployed. Light controls and schedules can be remotely-controlled from on-shore using software. The length of time that lights are on is limited in order to minimize impact on the environment. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/4f018954-25dc-4cc2-8341-4f217d489e7f
title: Chatham Sound Camera Lights Deployed 2022-07-16

description: The Ocean Networks Canada Light SN13 was deployed on 2022-07-16 at Chatham Sound. Chatham Sound is a sound on the North Coast of British Columbia, located between Dundas and Stephens Islands and the Tsimpsean Peninsula near Prince Rupert. This device is a Camera Lights. Camera lights are used to improve visibility where cameras are deployed. Light controls and schedules can be remotely-controlled from on-shore using software. The length of time that lights are on is limited in order to minimize impact on the environment. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.5281/zenodo.6860658
title: Provenance of Software Projects hosted on GitLab.com

description: Provenance of Software Projects hosted on GitLab - Data set
DOI: 10.34943/400e548d-7551-430e-bb9e-69743c5aaed9
title: Chatham Sound Conductivity Temperature Depth Deployed 2022-07-16

description: The AML CTD Metrec X 50147 was deployed on 2022-07-16 at Chatham Sound. Chatham Sound is a sound on the North Coast of British Columbia, located between Dundas and Stephens Islands and the Tsimpsean Peninsula near Prince Rupert. This device is a Conductivity Temperature Depth. Conductivity Temperature Depth (CTD) is an instrument package that contains sensors for measuring the conductivity, temperature, and pressure of seawater. Salinity, sound velocity, depth and density are variables that can be derived from sensor measurements. CTDs can carry additional instruments and sensors such as oxygen sensors, turbidity sensors and fluorometers. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.34943/18195c82-ff76-4d39-b6c8-670d3dd0b378
title: Chatham Sound Junction Box Deployed 2022-07-16

description: The ONC Mini Junction Box 012 was deployed on 2022-07-16 at Chatham Sound. Chatham Sound is a sound on the North Coast of British Columbia, located between Dundas and Stephens Islands and the Tsimpsean Peninsula near Prince Rupert. This device is a Junction Box. Junction Boxes supply power and communications to deployed instruments. Junction boxes have a number of serial and ethernet ports, including 400V ethernet ports that enable connections to other junction boxes and high-voltage instruments. Junction boxes can convert high voltages to lower voltages (15V, 24V or 48V) required by many instruments. It was deployed on a fixed platform. Data from this deployment were archived and made available through Ocean Networks Canada's Oceans 3.0 digital infrastructure, with quality assurance and derived data products following established practices.
DOI: 10.6084/m9.figshare.20337696
title: Supplementary Material for: Cognitive Impairments in Patients with GHB Use Disorder Predict Relapse in GHB Use

description: <b><i>Background:</i></b> The recreational use of gamma hydroxybutyrate (GHB) is associated with frequent overdoses, coma and the risk of developing GHB use disorder (GUD). Several studies suggest negative effects of GHB use or related comas on cognition. Since relapse rates are high in GUD and cognitive impairment has been associated with relapse in other substance use disorders, we aimed to (1) investigate the prevalence of cognitive impairment before and after detoxification, (2) analyse the relationship between GHB use, comas, and cognitive impairment, and (3) explore the association between cognitive impairment and relapse after detoxification in GUD patients. <b><i>Methods:</i></b> In these secondary analyses of a prospective cohort study, a consecutive series of patients with GUD (<i>n</i> = 103) admitted for detoxification were recruited at six addiction care facilities in the Netherlands. The Montreal Cognitive Assessment (MoCA) was used to screen for cognitive impairments before and after detoxification. The follow-up duration for the assessment of relapse in GHB use was 3 months. <b><i>Results:</i></b> A substantial number of patients with GUD screened positive for cognitive impairment before (56.3%) and after (30.6%) detoxification. Impairment on the MoCA memory domain was most frequent (58.8%). Cognitive impairment was not related to the severity of GUD or number of GHB-induced comas. Logistic regression analysis showed that only the memory score independently predicted relapse. <b><i>Discussion:</i></b> Cognitive impairment seems highly prevalent among patients with GUD, possibly related to the risk of relapse. The absence of a relationship between the severity of GUD, level of GHB use, the number of GHB-induced comas, and cognitive impairment suggest that other factors may also contribute to the observed cognitive impairment.
DOI: 10.6084/m9.figshare.20337696.v1
title: Supplementary Material for: Cognitive Impairments in Patients with GHB Use Disorder Predict Relapse in GHB Use

description: <b><i>Background:</i></b> The recreational use of gamma hydroxybutyrate (GHB) is associated with frequent overdoses, coma and the risk of developing GHB use disorder (GUD). Several studies suggest negative effects of GHB use or related comas on cognition. Since relapse rates are high in GUD and cognitive impairment has been associated with relapse in other substance use disorders, we aimed to (1) investigate the prevalence of cognitive impairment before and after detoxification, (2) analyse the relationship between GHB use, comas, and cognitive impairment, and (3) explore the association between cognitive impairment and relapse after detoxification in GUD patients. <b><i>Methods:</i></b> In these secondary analyses of a prospective cohort study, a consecutive series of patients with GUD (<i>n</i> = 103) admitted for detoxification were recruited at six addiction care facilities in the Netherlands. The Montreal Cognitive Assessment (MoCA) was used to screen for cognitive impairments before and after detoxification. The follow-up duration for the assessment of relapse in GHB use was 3 months. <b><i>Results:</i></b> A substantial number of patients with GUD screened positive for cognitive impairment before (56.3%) and after (30.6%) detoxification. Impairment on the MoCA memory domain was most frequent (58.8%). Cognitive impairment was not related to the severity of GUD or number of GHB-induced comas. Logistic regression analysis showed that only the memory score independently predicted relapse. <b><i>Discussion:</i></b> Cognitive impairment seems highly prevalent among patients with GUD, possibly related to the risk of relapse. The absence of a relationship between the severity of GUD, level of GHB use, the number of GHB-induced comas, and cognitive impairment suggest that other factors may also contribute to the observed cognitive impairment.