cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/r7797b7g8x.1
title: Grid data for topography and backscatter maps of massive gas hydrate recovery area between the Umitaka Spur and the Ogi Spur in the Sea of Japan

description:  Massive gas hydrates of biogenic methane were recovered from mound structures at ~20 km northeast to the Umitaka Spur in the Sea of Japan. Mound structures at the Umitaka Spur are associated with thermogenic methane. This is owing to influence of hydrocarbon source rocks at deep sediment depths. These source rocks are widely distributed for the oil and gas fields along the eastern margin of the Sea of Japan. Therefore, the local occurrence of intensive biogenic methane production suggests unique trigger in deep. Investigation of this area and comparison with the Umitaka spur will be useful for understanding complicated nature in deep sediment depths.
 Geophysical data for topography and backscatter maps were obtained during the 1K17 cruise (July 2017) and the 2K19 cruise (July 2019) by R/V Kaiyo Maru No.1 and R/V Kaiyo Maru No.2 of the Kaiyo Engineering Co., Ltd. (http://kaiyoeng.com/eng/), respectively. Data for the southern part of the focused area was obtained during the 1K17 cruise and northern part, during the 2K19 cruise. The equipment attached to the ship bottom was used (EM122 and EM304 of Kongsberg during the 1K17 cruise and the 2K19 cruise, respectively). Raw data of the equipment was processed using a software, MarineDiscovery, of Ocean High Technology Institute, Inc. (https://www.ohti.co.jp/www/en/products/software/marinediscovery/) and converted into ~25 m mesh (0.8 second) grid data for both topographic map and backscatter. Grid data covering both areas was prepared only for topography map due to difficulty in calibration for sound intensity.

Uploaded data
Topography map of northern area (Topography map of northern area.pdf)
Topography map of southern area (Topography map of southern area.pdf)

Grid data for topography at northern area (2K19_Joetsu_LM_DP.grd)
Grid data for topography at southern area (1K17_Izumozaki_DP.grd)
Grid data for topography_marged (1K17_2K19_Joetsu_LM_DP.grd)

Grid data for backscatter at northern area (2K19_Joetsu_LM_BS.grd)
Grid data for backscatter at southern area (1K17_Izumozaki_BS.grd)
DOI: 10.25345/c5ks6j558
title: MassIVE Reanalysis RMSV000000354.4365 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, PHOSPHO1 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.17632/hd38mw6z9x.1
title: Sub-bottom profiles at massive gas hydrate recovery area between the Umitaka Spur and the Ogi Spur in the Sea of Japan

description: Massive gas hydrates of biogenic methane were recovered from mound structures at ~20 km northeast to the Umitaka Spur in the Sea of Japan. Mound structures at the Umitaka Spur are associated with thermogenic methane. This is owing to influence of hydrocarbon source rocks at deep sediment depths. These source rocks are widely distributed for the oil and gas fields along the eastern margin of the Sea of Japan. Therefore, the local occurrence of intensive biogenic methane production suggests unique trigger in deep. Investigation of this area and comparison with the Umitaka spur will be useful for understanding complicated nature in deep sediment depths.
Sub-bottom profiles (SBPs) were obtained during the 7K18 cruise (September 2018) and the 2K19 cruise (July 2019) by R/V Kaiyo Maru No.7 and R/V Kaiyo Maru No.2 of the Kaiyo Engineering Co., Ltd. (http://kaiyoeng.com/eng/), respectively. A sub bottom profiler (2000DSS of EdgeTech) was towed during the 7K18 cruise and four SBPs (SBP_Site4-A, _Site4-B, _Site5-D, and _Site5-E, respectively) crossing the mound structures were obtained. Position of the towed profiler was obtained by an ultra-short baseline (USBL) acoustic positioning system (cNODE MiniS 34-180 of Kongsberg Maritime) attached to the profiler. SBPs during the 2K19 cruise were obtained using an equipment attached to the ship bottom (TOPAS PS18 of Kongsberg). Two SBPs (SBP_B and _G, respectively) were obtained.

Uploaded data
Topography map with locations of 6 SBPs

SBP (7K18); four SBPs obtained during the 7K18 cruise

SBP (2K19); two SBPs obtained during the 2K19 cruise

SEG-Y (7K18); four SEG-Y files from the 7K18 cruise

SEG-Y (2K19) and SEG-Y (2K19)_2; two SEG-Y files from the 2K19 cruise
(note that file format “.seg” in SEG-Y (2K19) was changed to “.sgy” in SEG-Y (2K19)_2)

Profiler track (7K18); track of towed sub bottom profiler during the 7K18 cruise
Column “J” and “K” of “Original data” are used for “for Generic Mapping Tools”.

Profiler track (2K19); track of sub bottom profiler (same with ship track) during the 2K19 cruise
Column “I” and “J” of “Original data” are used for “for Generic Mapping Tools”.
DOI: 10.17632/33tbmnspd7.1
title: Long days restore regular oestrous cyclicity in mice lacking circadian rhythms

description: Many female mammals have recurring cycles of ovulation and sexual behaviours that are regulated by reproductive hormones and confer reproductive success. In addition to sexual behaviours, circadian behaviour rhythms of locomotor activity also fluctuate across the oestrous cycle in rodents. Moreover, there is a bidirectional relationship between circadian rhythms and oestrous cyclicity since mice with disrupted circadian rhythms also have compromised oestrous cycles resulting in fewer pregnancies. In the present study, we assessed whether extending day length, which alters circadian rhythms, normalises oestrous cyclicity in mice. We found that Period (Per) 1/2/3 triple knockout (KO) mice, that have disabled canonical molecular circadian clocks, have markedly disrupted oestrous cycles. Surprisingly, extending the day length by only 2 hours per day restored regular 4- or 5-day oestrous cycles to Per1/2/3 KO mice. Longer days have also induced consistent 4-day, rather than 5-day, oestrous cycles in C57BL/6J mice. These data demonstrate that extending daytime light exposure could be used for enhancing reproductive success.
DOI: 10.25345/c5g15tc1f
title: MassIVE Reanalysis RMSV000000354.4366 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, TTC23L [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c5b853j72
title: MassIVE Reanalysis RMSV000000354.4367 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, EPS8L1 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.5281/zenodo.4322990
title: Collapse and Continuity: A multi-proxy reconstruction of settlement organization and population trajectories in the Northern Fertile Crescent during the 4.2kya Rapid Climate Change event (dataset and R scripts)

description: The present digital archive is the outcome of the paper: <strong>Lawrence, D., Palmisano, A., and de Gruchy, M.W., 2021. Collapse and Continuity: A multi-proxy reconstruction of settlement organization and population trajectories in the Northern Fertile Crescent during the 4.2kya Rapid Climate Change event</strong>. <em><strong>PLoS ONE</strong></em><strong>,</strong> <strong><em>16</em></strong>(1). The dataset included here provides a collection of <strong>920 </strong>radiocarbon dates and <strong>1070</strong> sites from archaeological surveys. In addition, the digital archive related to this paper provides reproducible analyses in the form of three scripts written in R statistical computing language.
DOI: 10.5281/zenodo.4322989
title: Collapse and Continuity: A multi-proxy reconstruction of settlement organization and population trajectories in the Northern Fertile Crescent during the 4.2kya Rapid Climate Change event (dataset and R scripts)

description: The present digital archive is the outcome of the paper: <strong>Lawrence, D., Palmisano, A., and de Gruchy, M.W., 2021. Collapse and Continuity: A multi-proxy reconstruction of settlement organization and population trajectories in the Northern Fertile Crescent during the 4.2kya Rapid Climate Change event</strong>. <em><strong>PLoS ONE</strong></em><strong>,</strong> <strong><em>16</em></strong>(1). The dataset included here provides a collection of <strong>920 </strong>radiocarbon dates and <strong>1070</strong> sites from archaeological surveys. In addition, the digital archive related to this paper provides reproducible analyses in the form of three scripts written in R statistical computing language.
DOI: 10.25345/c56h4cr3x
title: MassIVE Reanalysis RMSV000000354.4368 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, SERPINB11 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.25345/c52r3nx95
title: MassIVE Reanalysis RMSV000000354.4369 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, ENTPD7 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.5281/zenodo.6225932
title: Data for 'Multi-modal microscopy imaging with the OpenFlexure Delta Stage'

description: Image data for 'Multi-modal microscopy imaging with the OpenFlexure Delta Stage'
DOI: 10.6084/m9.figshare.14822256.v5
title: Datasets on South Korean manufacturing factories’ electricity consumption and demand response participation

description: This study describes the release of electricity consumption data of some manufacturing factories located in South Korea that participate in the demand response (DR) market. The data (in kilowatt) comprise individual factories’ total power usage details that were acquired using advanced metering infrastructures. They further contain details on the manufacture types, DR participation dates, mandatory reduction capacities, and response capacities of the factories. For data acquisition, 10 manufacturing companies are representatively selected according to the process regularity and company size standard of this study. Entire datasets are newly collected and available at one-minute intervals for a period of 7 months from 1 March to 30 September 2019. These datasets can be used in a variety of ways to contribute to the functioning of power systems and markets, including the conduction of industrial load characteristic analysis for load flexibility, estimation of demand-side considerations for virtual power plant design, and determination of energy markets and incentives to achieve carbon neutrality targets at the national level.
DOI: 10.5519/qd.hmlttenp
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (77 records)
DOI: 10.5281/zenodo.6225993
title: Data for 'Multi-modal microscopy imaging with the OpenFlexure Delta Stage'

description: Image data for 'Multi-modal microscopy imaging with the OpenFlexure Delta Stage'
DOI: 10.5281/zenodo.6225931
title: Data for 'Multi-modal microscopy imaging with the OpenFlexure Delta Stage'

description: Image data for 'Multi-modal microscopy imaging with the OpenFlexure Delta Stage'
DOI: 10.5281/zenodo.6225853
title: Open access data from the International Design Engineering Annual (IDEA) Challenge 2021

description: Open access dataset from the IDEA challenge 2021. The generation of this dataset has been undertaken as part of the ProtoTwin project (Improving the product development process through integrated revision control and twinning of digital-physical models during prototyping). The work was conducted at the University of Bristol in the Design and Manufacturing Futures Lab (http://www.dmf-lab.co.uk) and is funded by the Engineering and Physical Sciences Research Council (EPSRC), Grant reference EP/R032696/1. The dataset was generated in collaboration with the Norwegian Technical University (NTNU), University of Zagreb and University of Twente. For more information please contact Mark (mark.goudswaard @ bristol.ac.uk) or James ( james.gopsill @ bristol.ac.uk)
DOI: 10.25345/c5tb0xw45
title: MassIVE Reanalysis RMSV000000354.4370 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, MEMO1 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.5281/zenodo.6225803
title: Erythroxylum confusum SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6225802
title: Erythroxylum confusum SPAdes preassembly

description: .
DOI: 10.5281/zenodo.6226037
title: CERN Dataset

description: CERN, the European Organization for Nuclear Research, is one of the world's largest and most respected centres for scientific research. ________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
DOI: 10.5281/zenodo.6226036
title: CERN Dataset

description: CERN, the European Organization for Nuclear Research, is one of the world's largest and most respected centres for scientific research. ________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
DOI: 10.25345/c5pk0729q
title: MassIVE Reanalysis RMSV000000354.4371 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, WNT9B [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.17632/6kygnybg7x.2
title: Design of a Neural Fuzzy Damper Vibration to Improve the Stability of Electric Power Systems

description: In this Paper a New Design Methodology for The Vibration Damper for Synchronous Machine Depends On Adaptive Neuro Fuzzy Inference System, Is Proposed in Order to Reduce the Oscillation Voltage in Electrical System and Find Out the Effectiveness of Proposed Damper in The Stability of the System, It Was Compared with Traditionally Power System Stabilizer.
The New Damper Is Based On Adaptive Neuro Fuzzy Inference System Which Process the Signal of Rotation Speed of the Generator Then Control of the Excitation of Synchronous Machine, The Designed Damper Showed Ability to Reduce Amplitude Vibrations Arising from Failures and Thus Reduce the Time of Damping by Providing Additional Effort to Signal Entered to The Excitation System, compared with A Conventional Vibration Damper and Its Performance Is Better Than a Conventional Vibration Damper.
The Proposed Design Offers a Good Possibility of Further Improving the Dynamic Stability and Thus the Stability of the Electrical System.
DOI: 10.25345/c5js9h851
title: MassIVE Reanalysis RMSV000000354.4372 - CCMS MassIVE Knowledge Base (MassIVE-KB) MS-GF+ reanalysis of Bioplex AP-MS Dataset for Library Construction, FAM8A1 [launched by fce971e5ede541cca3fc5307a73294d8]
title: Center for Computational Mass Spectrometry (CCMS) systematic reanalysis of public proteomics mass spectrometry (MS) datasets provides a public, large-scale and comparable set of dataset reanalyses results including detailed provenance records. To further facilitate the broad reusability of public proteomics MS data, these reanalyses were also used to build the MassIVE Knowledge Base (MassIVE-KB) spectral library, a community-wide resource derived from hundreds of millions of identified spectra from tens of terabytes of mass spectrometry data.
DOI: 10.17632/4k64fwnp4k.5
title: Deep-learning-based Segmentation of Fundus Photographs to Detect Central Serous Chorioretinopathy

description: https://doi.org/10.1167/tvst.11.2.22
Simple Code Implementation for Deep Learning–Based Segmentation to Evaluate Central Serous Chorioretinopathy in Fundus Photography, TVST, 2022

We developed a pix2pix deep learning model for segmentation of subretinal fluid area in fundus photographs to detect central serous chorioretinopathy (CSC).

The total dataset included fundus photographs and a segmentation image dataset from 194 eyes with CSC from the medical centers and publicly accessible datasets. Additionally, we recruited 93 fundus photographs of the healthy eyes from the same center to build a classification model to discriminate CSC from normal retina. 

Manual segmentation is a tedious and time-consuming task that requires domain-specific knowledge. Initially, one ophthalmologist manually screened the fundus photography images with CSC. We asked three ophthalmologists including two licensed ophthalmologists (grader 1 & 2) and one ophthalmology resident (grader 3) to segment the entire SRF area in the retinal images. 

First, we prepared the dataset in Google Drive. Second, the users can upload the code file in Google Drive and open the file on the Google Drive page on the web browser. Third, prepare the dataset in Google Drive and match the folder location of the code with the address of the actual folders. In our experiment as an example, we saved the training dataset at "csc/segmentation/train/" and the test dataset at "csc/segmentation/test/" in our own Google Drive. Fourth, click the play button to the left of the code cell one by one. The second code cell links the datasets to this Colaboratory notebook using Google Drive. 

The manuscript of the study was accepted to TVST, ARVO journal.
DOI: 10.17632/55yj7ypsmm.1
title: Nanoscale chemical mapping of exometabolites at fungal-mineral interfaces

description: STXM-NEXAFS data at C(K) and Fe(L) absorption edges of fungal hyphae (PSI - Psilocybe subviscida, PAI - Paxillus involutus, GYM - Gymnopus confluence) grown on silicon nitride membrane windows alone or in contact with quartz (Q) or goethite (Q).
DOI: 10.17632/v7mvmvkn54.1
title: Kinematic plate modelling of the Goban Spur margin, offshore Ireland, with deforming zones constrained by seismic reflection data

description: GPlates data files used to generate deformable plate model (model 4) in Yang and Welford (2022).
DOI: 10.17632/7zgm6bg9y9.1
title: Data from: Bitomský et al. Stoichiometry versus ecology: the relationships between genome size and guanine-cytosine content, and tissue nitrogen and phosphorus in grassland herbs

description: Data from: Bitomský et al. Stoichiometry versus ecology: the relationships between genome size and guanine-cytosine content, and tissue nitrogen and phosphorus in grassland herbs

File "Bitomsky2022_Genome_NP_stoichiometry_data.xls" includes genome size, guanine-cytosine content, tissue N, tissue P and tissue NP measurements (+ other relevant information, such as ploidy levels, flow cytometry results and references).

File "Bitomsky2022_phylogeny.txt" is the phylogenetic tree used in this paper (newick format).
DOI: 10.17632/gjcyvs5nfx.2
title: Dataset for a Study titled "Drug Utilization Pattern and Adverse Drug Reactions of Chemotherapy in Pediatric Patients" at Muhimbili National Hospital Data

description: Cancer is a non-communicable disease (NCDs) that reduces the quality of life. It is a group of diseases that involves abnormal cell growth that invades or spreads to other parts of the body. The study that generated this dataset aimed to assess the utilisation pattern and adverse drug reactions (ADRs) of chemotherapy in paediatric patients at Muhimbili National Hospital (MNH), Dar es Salaam, Tanzania. 

A descriptive cross-sectional study was conducted for three months from February to April 2021 in paediatric cancer patients undergoing chemotherapy at MNH. A total of 123 Children diagnosed with cancer and on chemotherapy during the study period were enrolled. Patients’ socio-demographics, clinical information, chemotherapy status, prescribed medications and prevalence of ADRs were collected from patient files.

Presented are underlining data (in Microsoft Excel format) containing the data from the extraction of data from patient files. The first sheet contains paediatric.xlsx contains raw data before analysis in two sheets. One sheet called patients having demographic information about the patients. The second sheet contains information about the medications used by a patient. The two sheets are linked by patient_ID. R statistical software was used to combine the files to form a combined dataset called combined.xlsx which has information about patients and the medications they use. Along with the datasets there is an R script (analysis.R) that was used for data analysis which can be used to reproduce the whole analysis. The data collection tool has also been added as a word document.