cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24304615.v2
title: BEH 3843 Appendix

description: <b>Figure A1.</b> Summaries of the data set for (A, B) the binomial and (C, D) the negative binomial regressions within the exploration model (Model 3). (A, B) The proportion of zero (white bars) and not-zero (black bars) distances for each time period on <i>Karaftohelix editha</i> (A; <i>N </i>= 192 in total) and <i>K. gainesi</i> (B; <i>N </i>= 182). (C, D) The approximate crawled distances in the wild (i.e., exploration) except for the zero data for each time period on <i>K. editha</i> (C; <i>N</i> = 100) and <i>K. gainesi</i> (D; <i>N</i> = 175). Night: 00:00–06:00, morning: 06:00–12:00, afternoon: 12:00–18:00, and evening period: 18:00–24:00.<b>Table A1.</b> Information of snail individuals used in each experiment.<b>Table A2.</b> The dataset of the laboratory experiments under ordinary conditions in this study.<b>Table A3.</b> The dataset of the laboratory experiments under stimulated conditions in this study.<b>Table A4.</b> The whole dataset of the field experiments in this study.<b>Table A5.</b> Explanatory variables, Df, residual deviance, AIC scores of each model.
DOI: 10.6084/m9.figshare.24304615.v1
title: BEH 3843 Appendix

description: <b>Figure A1.</b> Summaries of the data set for (A, B) the binomial and (C, D) the negative binomial regressions within the exploration model (Model 3). (A, B) The proportion of zero (white bars) and not-zero (black bars) distances for each time period on <i>Karaftohelix editha</i> (A; <i>N </i>= 192 in total) and <i>K. gainesi</i> (B; <i>N </i>= 182). (C, D) The approximate crawled distances in the wild (i.e., exploration) except for the zero data for each time period on <i>K. editha</i> (C; <i>N</i> = 100) and <i>K. gainesi</i> (D; <i>N</i> = 175). Night: 00:00–06:00, morning: 06:00–12:00, afternoon: 12:00–18:00, and evening period: 18:00–24:00.<b>Table A1.</b> Information of snail individuals used in each experiment.<b>Table A2.</b> The dataset of the laboratory experiments under ordinary conditions in this study.<b>Table A3.</b> The dataset of the laboratory experiments under stimulated conditions in this study.<b>Table A4.</b> The whole dataset of the field experiments in this study.<b>Table A5.</b> Explanatory variables, Df, residual deviance, AIC scores of each model.
DOI: 10.25919/5xny-r560
title: RV Investigator Voyage IN2023_E01 End of Voyage (EOV) Archive

description: This record describes the End of Voyage (EOV) data archive from the Marine National Facility (MNF) RV Investigator voyage IN2023_E01, titled "Sea trials and calibrations." The voyage took place between January 7, 2023 and January 12, 2023 (AEST), departing from Fremantle and returning to Fremantle. For further information please refer to the voyage documentation links. Instruments used and data collected include: Regular measurements: Lowered ADCP (LADCP), Acoustic Doppler Current Profiler (ADCP; 75, 150 KHz ), Greenhouse Gas Analysers (Picarro), CTD, Hydrochemistry, Fisheries Echosounder (EK60, EK80), Multibeam Echosounder (EM710, EM122), Sub-bottom Profiler (SBP120), GPS Positioning System, Doppler Velocity Log, Thermosalinographs (TSG), Fluorometer, Oxygen Optode, Infrared Sea Surface Temperature Autonomous Radiometer (ISAR), pCO2, Gravimeter, Atmospheric Temperature, Humidity, Pressure, Wind and Rain sensors, Photosynthetically Active Radiation (PAR) sensor, Precision Infrared Radiometer (PIR), Precision Spectral Pyranometer (PSP), Starboard and Portside Radiometers, Air Sampler, Ultra Short BaseLine Underwater Positioning System (USBL), Weather Radar, Expendable Bathythermographs (XBTs). Voyage-specific measurements: Video, Accelerometer. The archive for the IN2023_E01 EOV raw data is curated by the CSIRO National Collections and Marine Infrastructure (NCMI) Information and Data Centre (IDC) in Hobart, with a permanent archive at the CSIRO Data Access Portal (https://data.csiro.au/), providing access to voyage participants and processors of the data collected on the voyage. All voyage documentation is available electronically to MNF support via the local network. Applications to access voyage documentation by non-CSIRO participants can be made via data-requests-hf@csiro.au.
DOI: 10.6084/m9.figshare.24458953
title: Spectra-As content

description: Raw data for 'Regional and Global Hotspots of Topsoil Arsenic Contamination'
DOI: 10.15151/esrf-es-1330070542
title: Methanogens influenced corrosion mechanisms of metallic components in the natural gas network

description: This project aims to understand, within a logic of power-to-gas, the corrosion mechanism of metallic components used for the natural gas network in the perspective of hydrogen storage. The presence of hydrogenothrophic microorganisms (methanogens) in natural gas deposits, where electrochemically produced hydrogen is stored, can strongly affect both the fuel stability and the degradation rate of metallic pipelines, leading to strong economic losses. This corrosion mechanism is strongly related to the methanogenesis process, which is still not well documented. With the proposed experiment we intend to evaluate the oxidative states and degree of crystallinity of corrosion products formed on the surface of four alloys (carbon steel, duplex stainless steel, electrolytic copper and duplex brass), exposed to both a methanogens-rich solution (from a biogas plant) and a sterile condition to elucidate on the methanogenesis/corrosion mechanism and to evaluate the severity of the corrosive attack.
DOI: 10.5281/zenodo.8086353
title: Annexes to the EFSA external scientific report on the standard regulatory action for retrospective cumulative risk assessment of pesticides in MCRA

description: Annexes to the EFSA external scientific report on the standard regulatory action for retrospective cumulative risk assessment of pesticides in MCRA.


Harmonized methodology for retrospective dietary cumulative risk assessment (CRA) of pesticides was established by the European Commission (EC) and the European Food Safety Authority (EFSA) in 2018, in close collaboration with the Dutch National Institute for Public Health and the Environment (RIVM). An update of this regulatory methodology (RM) was proposed and adopted by EFSA in 2022 in a CRA on craniofacial alterations. This updated RM was implemented in version 10 of the MCRA software and validated as part of the first action defined in the third framework partnership agreements between EFSA and RIVM. This report describes the implementation of this updated methodology in the MCRA software for risk assessment. This is done from a proposed framework of standard regulatory actions (SRAs). SRAs offer a user-friendly and simple to use option for regulators to perform retrospective and prospective CRAs in MCRA according to agreed-upon RMs. In particular, this report provides guidance on the use of an SRA for a retrospective dietary CRA for craniofacial alterations according to the updated RM in MCRA version 10.


Detailed results of the comparison between reported by MCRA and EFSA’s SAS® software and MCRA formatted input files for the catalogues and secondary data are presented in the following annexes:



	
Annex A – Comparison of the MOET at different percentiles reported by MCRA and EFSA’s SAS® software for retrospective dietary CRA of craniofacial alterations. 
	

	
Annex B – Comparison of risk-driver contributions reported by MCRA and EFSA’s SAS® software for retrospective dietary CRA of craniofacial alterations. 
	




	

	
Annex C – MCRA formatted input data file containing the primary entity catalogues for the SRA on retrospective dietary CRA of craniofacial alterations. 
	
	

	
Annex D – MCRA formatted input data file containing the secondary data for the SRA on retrospective dietary CRA of craniofacial alterations. 
	
	

	
Annex E – MCRA formatted input data file containing the unit- variability factors for the Tier II calculations of the SRA on retrospective dietary CRA of craniofacial alterations. 
	
	

	
Annex F – MCRA formatted input data file containing the unit- variability factors for the Tier I calculations of the SRA on retrospective dietary CRA of craniofacial alterations. 
	



 
description: EU; xlsx; supportmcra@rivm.nl
DOI: 10.5281/zenodo.8086352
title: Annexes to the EFSA external scientific report on the standard regulatory action for retrospective cumulative risk assessment of pesticides in MCRA

description: Annexes to the EFSA external scientific report on the standard regulatory action for retrospective cumulative risk assessment of pesticides in MCRA.


Harmonized methodology for retrospective dietary cumulative risk assessment (CRA) of pesticides was established by the European Commission (EC) and the European Food Safety Authority (EFSA) in 2018, in close collaboration with the Dutch National Institute for Public Health and the Environment (RIVM). An update of this regulatory methodology (RM) was proposed and adopted by EFSA in 2022 in a CRA on craniofacial alterations. This updated RM was implemented in version 10 of the MCRA software and validated as part of the first action defined in the third framework partnership agreements between EFSA and RIVM. This report describes the implementation of this updated methodology in the MCRA software for risk assessment. This is done from a proposed framework of standard regulatory actions (SRAs). SRAs offer a user-friendly and simple to use option for regulators to perform retrospective and prospective CRAs in MCRA according to agreed-upon RMs. In particular, this report provides guidance on the use of an SRA for a retrospective dietary CRA for craniofacial alterations according to the updated RM in MCRA version 10.


Detailed results of the comparison between reported by MCRA and EFSA’s SAS® software and MCRA formatted input files for the catalogues and secondary data are presented in the following annexes:



	
Annex A – Comparison of the MOET at different percentiles reported by MCRA and EFSA’s SAS® software for retrospective dietary CRA of craniofacial alterations. 
	

	
Annex B – Comparison of risk-driver contributions reported by MCRA and EFSA’s SAS® software for retrospective dietary CRA of craniofacial alterations. 
	




	

	
Annex C – MCRA formatted input data file containing the primary entity catalogues for the SRA on retrospective dietary CRA of craniofacial alterations. 
	
	

	
Annex D – MCRA formatted input data file containing the secondary data for the SRA on retrospective dietary CRA of craniofacial alterations. 
	
	

	
Annex E – MCRA formatted input data file containing the unit- variability factors for the Tier II calculations of the SRA on retrospective dietary CRA of craniofacial alterations. 
	
	

	
Annex F – MCRA formatted input data file containing the unit- variability factors for the Tier I calculations of the SRA on retrospective dietary CRA of craniofacial alterations. 
	



 
description: EU; xlsx; supportmcra@rivm.nl
DOI: 10.6084/m9.figshare.21961079
title: final data for SECRIS effect.7z

description: Up-regulated secretory phospholipase A<sub>2</sub> (sPLA<sub>2</sub>) in tumors has been proposed as a stimulus to trigger drug release from liposomes for therapeutic effects. Yet current strategy in developing sPLA<sub>2</sub>-responsive liposomes merely considering substrate preference suffers from limited membrane disruptive effects induced by enzymatic hydrolysis and safety issues resulted from overuse of sPLA<sub>2</sub>-preferred lipids. Here, a membrane-destabilzing mechanism captilizing on enzymatic extraction and transition of facial amphiphiles (FAs) within lipid membranes was introduced. Enzymatic degradation of FA-modified lipids, a process invovling substrate extraction of lipids out of membranes and cleavage of <i>sn-2</i> ester bonds by sPLA<sub>2</sub>, rotation and interface settling of detached FAs, caused tremendous efflux of payloads from liposomes, coined as SECRIS effect. At the presence of sPLA<sub>2</sub>, Liposomes containing FA-modified lipids showed enhanced drug release, excellent anti-tumor efficacy and reduced adverse syndromes when delivering oxaliplatin (L-OHP) compared to conventional sPLA<sub>2</sub>-liable formulations. Discovery of SECRIS effect paves the road to engineer liposome platforms with high responsiveness and good safety profiles for treatment of sPLA<sub>2</sub>-positive tumors.
DOI: 10.6084/m9.figshare.21961079.v1
title: final data for SECRIS effect.7z

description: Current strategy in developing secretory phospholipase A2 (sPLA2)-responsive liposomes merely considering substrate preference suffers from limited membrane disruptive effects induced by enzymatic hydrolysis and safety issues resulted from overuse of sPLA2–preferred lipids. Here, a state-of-the-art membrane-destabilzing mechanism captilizing on enzymatic extraction and transition of facial amphiphile (FA) within lipid membranes was introduced. Enzymatic degradation of FA-modified lipids, a process invovling substrate extraction of lipids out of membranes and cleavage of <em>sn-2</em> ester bonds by sPLA2, rotation and interface settling of detached FAs, caused tremendous efflux of payloads from liposomes, coined as SECRIS effect. Liposomes endowed with such effect showed enhanced drug release，excellent anti-tumor efficacy and reduced adverse syndromes when delivering oxaliplatin (L-OHP). Our discovery demonstrates a brand-new way in design of enzyme-liable nano-vesicles by fully exploiting special motion of substrates and their metabolites.
DOI: 10.17632/s5zfvsw5kv.1
title: Date Fruit Dataset for Inspection and Grading

description: Date fruit is the most valuable and helpful in the world. It is consumed due to rich nutrients and a high diet. In this dataset, we have acquired images of different varieties of data fruit (Aseel, Gajar, Kupro and Fasli toto). Dried date fruit processing is a challenging task because processing requires skilled labor to segregate date fruit according to varieties and grading scaling to export in the international market. The dataset contains raw images of four date fruit varieties and is stored in folders Aseel, Gajar, Kupro, and Fasli toto. These are further divided into sub-folders like Large, Medium, and Small due to the size of the data fruit. Each size folder contains Grade-1, Grade-2, and Grade-3 folders. The acquired data will be utilized to develop an intelligent system for grading and inspection. The images were captured in a controlled environment with a defined distance between the camera and the object.
DOI: 10.17632/s5zfvsw5kv.2
title: Date Fruit Dataset for Inspection and Grading

description: Date palm  fruits are the most valuable and helpful in the world. It is consumed due to rich nutrients and a high diet. In this dataset, we have offered images of different varieties of date palm fruits (Aseel, Fasli toto, Gajar, and, Kupro). Dried date palm  fruit processing is a challenging task because processing requires skilled labor to segregate date fruit according to varieties and grading scaling to export in the international market. The dataset contains raw images of four date fruit varieties and is stored in folders Aseel, Fasli Toto, Gajar, and Kupro. These are further divided into sub-folders like Large, Medium, and Small due to the size of the date fruit. Each size folder contains Grade-1, Grade-2, and Grade-3 folders. The acquired data will be utilized to develop an intelligent system for grading and inspection. The images were captured in a controlled environment with a defined distance between the camera and the object.
DOI: 10.17632/s5zfvsw5kv.3
title: Date Fruit Dataset for Inspection and Grading

description: Date palm fruits are the most valuable and helpful in the world. It is consumed due to rich nutrients and a high diet. In this dataset, we have offered images of different varieties of date palm fruits (Aseel, Fasli toto, Gajar, and, Kupro). Dried date palm fruit processing is a challenging task because processing requires skilled labor to segregate date fruit according to varieties and grading scaling to export in the international market. The dataset contains raw images of four date fruit varieties and is stored in folders Aseel, Fasli Toto, Gajar, and Kupro. These are further divided into sub-folders like Large, Medium, and Small due to the size of the date fruit. Each size folder contains Grade-1, Grade-2, and Grade-3 folders. The acquired data will be utilized to develop an intelligent system for grading and inspection. The images were captured in a controlled environment with a defined distance between the camera and the object. Additionally, The augmentation has been performed to increase the size of dataset for the training and testing of deep learning models.
DOI: 10.17632/bw9md35c29.2
title: Identifying User Stories in Issues records

description: Nowadays most software development companies have adopted agile development methodologies, which suggest capturing requirements through user stories. However, user stories are too often poorly written in practice and exhibit inherent quality defects. In addition, it is common to find the user stories of a software project immersed in large volumes of issues request logs from software quality tracking systems, which makes difficult to process them later. In order to solve these defects and to formulate high quality requirements, a current trend is the application of computational linguistic techniques to identify and then process user stories. To train the models, data were taken from public sources that contain issues from real software development projects. These sources contain positive examples of user stories in the format “As a (type of user), I want (goal), [so that (some reason)]” and negative examples (erroneous user stories or sentences with a similar syntaxis to user stories but with a different purpose). To obtain a larger data set suitable for testing the models, an algorithm was implemented for generating additional examples by splitting and mixing positive examples into random parts using the Tokenizer of TensorFlow. In order to differentiate the examples to which each classification class belonged, a manual classification work was performed, which may have introduced to the model some human error index since there was no record of the previously classified data. The resulting dataset includes a total of 7997 positive and negative examples, of which 2618 are positive, and the rest are negative. Therefore, a binary classification problem is presented, where the issues classified as user stories belong to the positive class and the rest to the negative class.
DOI: 10.5281/zenodo.10052917
title: seismic data

description: The file contains three types of earthquake data: natural earthquakes, explosions, and collapses.
DOI: 10.5281/zenodo.10052916
title: seismic data

description: The file contains three types of earthquake data: natural earthquakes, explosions, and collapses.
DOI: 10.6084/m9.figshare.24236434
title: Underlying data for "Steady global surface warming from 1973 to 2022 but increased warming rate after 1990" (10.1038/s43247-023-01061-4)

description: Surface temperature datasets for Samset et al. 2023, Communications Earth & Environment, 10.1038/s43247-023-01061-4. ("Steady global surface warming from 1973 to 2022 but increased warming rate after 1990").Observational and model based surface temperature anomalies are provided, with and without the Green's function based filtering applied.<br>
DOI: 10.6084/m9.figshare.24459277
title: References for Systematic Literature Review.pdf

description: References for Systematic Literature Review: <b>Design Dimensions of Virtual Collaborative Learning – Synthesizing Iterative Research</b><br>
DOI: 10.6084/m9.figshare.24459277.v1
title: References for Systematic Literature Review.pdf

description: References for Systematic Literature Review: <b>Design Dimensions of Virtual Collaborative Learning – Synthesizing Iterative Research</b><br>
DOI: 10.6084/m9.figshare.24459256
title: Table_M3.xlsx

description: The table contains information on the location of selected earthquake located in Israel
DOI: 10.6084/m9.figshare.24459256.v1
title: Table_M3.xlsx

description: The table contains information on the location of selected earthquake located in Israel
DOI: 10.6084/m9.figshare.24459205.v1
title: mini Seed files

description: This files contain mini Seed data of ten recorded earthquakes located in Israel and recorded by the Israeli Seismic Network. Seismograms are in displacement after instrument effect is removed.
DOI: 10.6084/m9.figshare.24459205
title: mini Seed files

description: This files contain mini Seed data of ten recorded earthquakes located in Israel and recorded by the Israeli Seismic Network. Seismograms are in displacement after instrument effect is removed.
DOI: 10.5281/zenodo.10052995
title: Databases needed to run snakemake classifier

description: Parsed Silva and Unite databases required as input for a snakemake workflow used to classify 18S and ITS1 sequences
DOI: 10.5281/zenodo.10052996
title: Databases needed to run snakemake classifier

description: Parsed Silva and Unite databases required as input for a snakemake workflow used to classify 18S and ITS1 sequences
DOI: 10.35003/cuhk5i
title: Replication Data for: The effect of target properties on transient crater scaling for simple craters.

description: The effects of the coefficient of friction and porosity on impact cratering are not sufficiently considered in scaling laws that predict the crater size from a known impactor size, velocity, and mass. We carried out a systematic numerical study employing more than 1000 two-dimensional models of simple crater formation under lunar conditions in targets with varying properties. A simple numerical setup is used where targets are approximated as granular or brecciated materials, and any compression of porous materials results in permanent compaction. The results are found to be consistent with impact laboratory experiments for water, low-strength and low-porosity materials (e.g., wet sand), and sands. Using this assumption, we found that both the friction coefficient and porosity are important for estimating transient crater diameters as is the strength term in crater scaling laws, i.e., the effective strength. The effects of porosity and friction coefficient on impact cratering were parameterized and incorporated into π group scaling laws, and predict transient crater diameters within an accuracy of ±5% for targets with friction coefficients f ≥ 0.4 and porosities Φ = 0–30%. Moreover, 90 crater scaling relationships are made available and can be used to estimate transient crater diameters on various terrains and geological units with different coefficient of friction, porosity, and cohesion. The derived relationships are most robust for targets with Φ &gt; 10–15%, applicable for a lunar environment, and could therefore yield significant insights into the influence of target properties on cratering statistics.
DOI: 10.35003/cuhk5i/bxtxud
title: jgre20717-fig-0007-m.png

description: :unav
DOI: 10.35003/cuhk5i/rpzkhi
title: Data.txt

description: :unav
DOI: 10.35003/cuhk5i/538ojz
title: jgre20717-fig-0001-m.png

description: :unav
DOI: 10.35003/cuhk5i/uo0guw
title: jgre20717-sup-0002-data_s2.tab

description: :unav
DOI: 10.35003/cuhk5i/z2vqxn
title: jgre20717-fig-0006-m.png

description: :unav
DOI: 10.35003/cuhk5i/skrizg
title: jgre20717-sup-0001-data_s1.docx

description: :unav
DOI: 10.35003/cuhk5i/cbntzj
title: jgre20717-fig-0008-m.png

description: :unav
DOI: 10.35003/cuhk5i/3x1fle
title: jgre20717-fig-0003-m.png

description: :unav
DOI: 10.35003/cuhk5i/qfnuij
title: jgre20717-fig-0002-m.png

description: :unav
DOI: 10.35003/cuhk5i/psnzpw
title: jgre20717-fig-0004-m.png

description: :unav
DOI: 10.35003/cuhk5i/yhbsto
title: jgre20717-fig-0005-m.png

description: :unav