cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1345779
title: Tokio Year-Long Dataset

description: This dataset contains the Darshan logs from which the feature vectors generated for "A Year in the Life of a Parallel File System" by Lockwood et al, presented at the 2018 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'18), were derived. The Darshan logs are stored in the binary format dictated by Darshan 3.1 as generated on the Cori, Edison, and Mira systems.

This dataset also includes the feature vectors used in the aforementioned paper, encoded in CSV format.  These feature vectors are identical to those also included in the tokio-abcutils code repository that contains all analysis and figures presented. They are simply duplicated here for convenience.

This tar file contains the following:


	README.md - This file
	LICENSE.md - The license under which these data have been published
	INDEX.csv - An index of all Darshan logs included in this dataset. It contains
	
		<code>log_file</code>: the name of each Darshan log
		<code>date</code>: The date on which the job was run and the log was generated
		<code>compute_system</code>: Whether the job was run on Edison, Cori, or Mira
		<code>file_system</code>: The file system on which the job was run. Required to disambiguate jobs run on Edison, which has three file systems.
		<code>application</code>: The name of the benchmark application used to generate the data. IOR and HACC benchmarks are named accordingly; <code>dbscan_read</code> is BD-CATS and <code>vpicio_uni</code> is VPIC.
		<code>shared_or_fpp</code>: Whether the job generated file-per-process or single-shared-file I/O. Required to disambiguate IOR jobs which were run in both modes.
		<code>read_or_write</code>: Whether the job predominantly performed reads or writes. Requires to disambiguate IOR jobs which were run in both modes.
		<code>md5</code>: The MD5 digest for the Darshan log.
	
	
	darshan_logs/ - Directory containing actual Darshan logs. Logs are sorted into subdirectories according to the year and month in which they were generated.
	summaries/ - Directory containing the feature vector CSVs that fed into the plots presented in the paper. Identical to the eponymous files in the tokio-abcutils release's <code>summaries</code> subdirectory.
	index_darshan_logs.py - The script used to generate <code>INDEX.csv</code> from the individual Darshan logs. Useful to determine exactly how the columns in INDEX.csv map to the raw data in each log.
	organize_logs_by_date.py - The script used to collect the Darshan logs into date-indexed subdirectories. Provided for provenance.
DOI: 10.5281/zenodo.1345780
title: Tokio Year-Long Dataset

description: This dataset contains the Darshan logs from which the feature vectors generated for "A Year in the Life of a Parallel File System" by Lockwood et al, presented at the 2018 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'18), were derived. The Darshan logs are stored in the binary format dictated by Darshan 3.1 as generated on the Cori, Edison, and Mira systems.

This dataset also includes the feature vectors used in the aforementioned paper, encoded in CSV format.  These feature vectors are identical to those also included in the tokio-abcutils code repository that contains all analysis and figures presented. They are simply duplicated here for convenience.

This tar file contains the following:


	README.md - This file
	LICENSE.md - The license under which these data have been published
	INDEX.csv - An index of all Darshan logs included in this dataset. It contains
	
		<code>log_file</code>: the name of each Darshan log
		<code>date</code>: The date on which the job was run and the log was generated
		<code>compute_system</code>: Whether the job was run on Edison, Cori, or Mira
		<code>file_system</code>: The file system on which the job was run. Required to disambiguate jobs run on Edison, which has three file systems.
		<code>application</code>: The name of the benchmark application used to generate the data. IOR and HACC benchmarks are named accordingly; <code>dbscan_read</code> is BD-CATS and <code>vpicio_uni</code> is VPIC.
		<code>shared_or_fpp</code>: Whether the job generated file-per-process or single-shared-file I/O. Required to disambiguate IOR jobs which were run in both modes.
		<code>read_or_write</code>: Whether the job predominantly performed reads or writes. Requires to disambiguate IOR jobs which were run in both modes.
		<code>md5</code>: The MD5 digest for the Darshan log.
	
	
	darshan_logs/ - Directory containing actual Darshan logs. Logs are sorted into subdirectories according to the year and month in which they were generated.
	summaries/ - Directory containing the feature vector CSVs that fed into the plots presented in the paper. Identical to the eponymous files in the tokio-abcutils release's <code>summaries</code> subdirectory.
	index_darshan_logs.py - The script used to generate <code>INDEX.csv</code> from the individual Darshan logs. Useful to determine exactly how the columns in INDEX.csv map to the raw data in each log.
	organize_logs_by_date.py - The script used to collect the Darshan logs into date-indexed subdirectories. Provided for provenance.
DOI: 10.5281/zenodo.1442534
title: Maja Look-Up Tables For Venµs Satellite, For A Continental Aerosol Model

description: This archive contains the look-up tables used by MAJA atmospheric correction software, used to process Venµs satellite data. These look-up tables correspond to a continental model.

V1.1 corrects for a bug in VE_TEST_GIP_L2DIRT_L_ALLSITES_00010_20000101_99991231.HDR, (Direct Transmission file) which contained references to Diffuse transmission files for bands 7 to 12.

V1.2 corrects a typo in VE_TEST_GIP_L2ALBD_L_ALLSITES_00010_20000101_99991231.HDR
DOI: 10.17632/dt2ncczrms.1
title: Dismissal of RNA Polymerase II Underlies a Large Ligand-induced Enhancer Decommissioning Program

description: Nuclear receptors induce both transcriptional activation and repression programs responsible for development, homeostasis, and disease. Here, we report a previously overlooked enhancer decommissioning strategy underlying a large estrogen receptor alpha (ERα)-dependent transcriptional repression program. The unexpected signature for this E2-induced program resides in indirect recruitment of ERα to a large cohort of pioneer factor basally active FOXA1-bound enhancers that lack cognate ERα DNA-binding elements. Surprisingly, these basally active estrogen-repressed (BAER) enhancers are decommissioned by ERα-dependent recruitment of the histone demethylase KDM2A, functioning independently of its demethylase activity. Rather, KDM2A tethers the E3 ubiquitin-protein ligase NEDD4 to ubiquitylate/dismiss Pol II to abrogate eRNA transcription, with consequent target gene downregulation. Thus, our data reveal that Pol II ubiquitylation/dismissal may serve as a potentially broad strategy utilized by indirectly bound nuclear receptors to abrogate large programs of pioneer factor-mediated, eRNA-producing enhancers.
DOI: 10.17632/jvs5w3hz3h.2
title: VDSP instances

description: These are the 69 instances used in the article: B. Domínguez-Martín, I. Rodríguez-Martín, J.J. Salazar-González, 2017. An exact algorithm for a Vehicle-and-Driver Scheduling Problem. Computers & Operations Research, vol. 81, pp.247-256. https://doi.org/10.1016/j.cor.2016.12.022. The instance name gives information about the number of nodes, the number of vehicles of each type available at the depots, and the class of the instance. For example, n16-1-1-1-1a.dat is an instance with 16 nodes, including the depots, one vehicle of each type at each depot, and the class of the instance is a. These data files have the same format as the classical CVRP instances from the literature, but some new parameters have been added. That is: The first line contains the name of the instance. The next lines contain: TYPE = ‘CVRP’ because the instances are CVRP instances adapted to our problem. DIMENSION = the number of nodes, including the depots EDGE_WEIGHT_TYPE = ‘EUC_2D’ because we use the Eucliden distance for all our instances. The next lines contains the capacity of the vehicles of type 1 (CAPACITY Y) and the capacity of the vehicles of type 2 (CAPACITY X). VEHICLES1 and VEHICLES 2 denotes the number of vehicles of type 2 available at first and second depot, respectively. DRIVERS1 and DRIVERS2 denotes the number of vehicle of type 1 available ar first and seconds depot, respectively. The lines after NODE_COORD_SECTION contain the following information: n x y where n=customer number (1 and the last number correspond to the depots), x=x coordinate, y=y coordinate. The lines after DEMAND_SECTION show the following information: n d where n=customer number (0 and the last number correspond to the depots), d=customer demand(0 for the depots and 1 for the customers) Finally, DEPOT_SECTION1 and DEPOT_SECTION2 indicate that the first and the last node represent the first and the second depot, respectively.
DOI: 10.17632/w5sbtwy8y9.1
title: DVRP instances

description: These are the 25 instances used in the article: B. Domínguez-Martín, I. Rodríguez-Martín, J.J. Salazar-González, 2018. The Driver and Vehicle Routing Problem. Computers & Operations Research, vol. 92, pp.56-64. https://doi.org/10.1016/j.cor.2017.12.010 There are instances with 10, 15, 20, 25, and 30 nodes, five of each size. Instances' names give information about the number of nodes. For example, n10-1.dat is the first instance with 10 nodes. In each file, the first lines contain: NAME = the name of the instances TYPE = does not apply here EDGE_WEIGHT_TYPE = ‘EUC_2D’ because we use the Eucliden distance for all our instances. DIMENSION = the number of nodes, including the depots The lines after NODE_COORD_SECTION contain the following information: n x y where n = node number x = x coordinate, y = y coordinate. Finally, DEPOT_SECTION1 and DEPOT_SECTION2 indicate that the first and the last node represent the first and the second depot, respectively.
DOI: 10.17632/w5sbtwy8y9.2
title: DVRP instances

description: These are the 25 instances, wiht 10, 15, 20, and 25 nodes, used in the article: Domínguez-Martín B., Rodríguez-Martín I., Salazar-González J.J. (2018) The Driver and Vehicle Routing Problem. Computers & Operations Research, vol. 92, pp.56-64. https://doi.org/10.1016/j.cor.2017.12.010, plus another 16 instances with 50 nodes used in: Domínguez-Martín B., Rodríguez-Martín I., Salazar-González JJ. (2018) A Heuristic Approach to the Driver and Vehicle Routing Problem. In: Cerulli R., Raiconi A., Voß S. (eds) Computational Logistics. ICCL 2018. Lecture Notes in Computer Science, vol 11184, pp 295-305. Springer, Cham. https://doi.org/10.1007/978-3-030-00898-7_19 Instances' names give information about the number of nodes. For example, n10-1.dat is the first instance with 10 nodes. In each file, the first lines contain: NAME = the name of the instances TYPE = does not apply here EDGE_WEIGHT_TYPE = ‘EUC_2D’ because we use the Eucliden distance for all our instances. DIMENSION = the number of nodes, including the depots The lines after NODE_COORD_SECTION contain the following information: n x y where n = node number x = x coordinate, y = y coordinate. Finally, DEPOT_SECTION1 and DEPOT_SECTION2 indicate that the first and the last node represent the first and the second depot, respectively.
DOI: 10.5258/soton/d0597
title: Dataset for Closed-Loop Corrective Beam Shaping for Laser Processing of Curved Surfaces

description: This dataset supports the publication:
Daniel J. Heath, Benita S. Mackay, James A. Grant-Jacob, Yunhui Xie, Richard O. C. Oreffo, Robert W. Eason, Ben Mills
Closed-Loop Corrective Beam Shaping for Laser Processing of Curved Surfaces
Journal of Micromechanics and MicroengineeringThis dataset contains data for the following figures:Fig. 1  motivation3D20180718_2.png
Fig. 2  updatedExpSetup20180723.png
Fig. 3  3Ddemo20180718.png
Fig. 4  topDownView.png
Fig. 5  maskShift.png
Fig. 6  pixShift20180718.png
Fig. 7  tiSphereQuad20180713.png
Fig. 8  tiSphereQuadLimsv3_20180726.pngDate of data collection: 2017/05/24 - 29/08/2018Information about geographic location of data collection: University of Southampton, U.K.Date that the file was created: [09, 2018]Funded by EPSRC (EP/N509747/1).
DOI: 10.17632/7psjn7wrfp.1
title: RIG-I uses an ATPase-powered translocation-throttling mechanism for kinetic proofreading of RNAs and oligomerization. Devarkar et al

description: Biotin-Streptavidin displacement Assays and EMSA Gel Scans
DOI: 10.17632/wr7w5zxzp6.1
title: Quantitative matching of clutch size in reciprocating hermaphroditic worms
DOI: 10.5281/zenodo.1346095
title: Datasets for "BB correction" algorithm evaluation and analysis

description: The datasets contain the raw and processed data relevant to the "BB (black body) correction" method, an algorithm to correct for scattering and systematic bias in quantitative neutron imaging from experimental measurements. Five CT datasets imaging various hydrogenous and non hydrogenous  materials are uploaded. The raw data folders for each dataset contains the sample projections over the tomographic range as well as the image used for referencing: the dark current, the open beam files and the additional "BB images", obtained with an interposed grid of neutron absorbers (BBs) from which scattering and bias components are estimated. The processed folders contain the CT reconstruction with and without the BB correction. All processing was done with the MuhRec open source software (https://zenodo.org/record/1311698#.W30exxixVtg)
description: This project receives funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 654000
description: {"references": ["https://doi.org/10.1371/journal.pone.0210300"]}
DOI: 10.5281/zenodo.1444069
title: Data And Source Codes Used In "Development Of A Global Quasi-3-D Multiscale Modeling Framework:  I. Vector Vorticity Model On Cubed Sphere As Cloud-Resolving Component"

description: Data and Source Codes used in the paper "Development of a Global Quasi-3-D Multiscale Modeling Framework:  I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component"

Advection Test (ADV): East-West       A_TST (100km, Cube), C_TST (25km,  Cube), E_TST (5km,  Cube),

                                     North-South    K_TST (100km,  Cube), M_TST (25km, Cube), O_TST (5km,  Cube) 

Barotropic Test (BAR): A_TST5 (100km, Cube), Y_TST4 (100km, RLL), C_TST3 (5km, Cube), C_TST1 (5km, RLL)

Baroclinic Test (BCL): J_TST30 (100km, Cube), J_TST20 (100km, RLL)
DOI: 10.5281/zenodo.1444070
title: Data And Source Codes Used In "Development Of A Global Quasi-3-D Multiscale Modeling Framework:  I. Vector Vorticity Model On Cubed Sphere As Cloud-Resolving Component"

description: Data and Source Codes used in the paper "Development of a Global Quasi-3-D Multiscale Modeling Framework:  I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component"

Advection Test (ADV): East-West       A_TST (100km, Cube), C_TST (25km,  Cube), E_TST (5km,  Cube),

                                     North-South    K_TST (100km,  Cube), M_TST (25km, Cube), O_TST (5km,  Cube) 

Barotropic Test (BAR): A_TST5 (100km, Cube), Y_TST4 (100km, RLL), C_TST3 (5km, Cube), C_TST1 (5km, RLL)

Baroclinic Test (BCL): J_TST30 (100km, Cube), J_TST20 (100km, RLL)
DOI: 10.5281/zenodo.1346094
title: Datasets for "BB correction" algorithm evaluation and analysis

description: The datasets contain the raw and processed data relevant to the "BB (black body) correction" method, an algorithm to correct for scattering and systematic bias in quantitative neutron imaging from experimental measurements. Five CT datasets imaging various hydrogenous and non hydrogenous  materials are uploaded. The raw data folders for each dataset contains the sample projections over the tomographic range as well as the image used for referencing: the dark current, the open beam files and the additional "BB images", obtained with an interposed grid of neutron absorbers (BBs) from which scattering and bias components are estimated. The processed folders contain the CT reconstruction with and without the BB correction. All processing was done with the MuhRec open source software (https://zenodo.org/record/1311698#.W30exxixVtg)
description: This project receives funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 654000
description: {"references": ["https://doi.org/10.1371/journal.pone.0210300"]}
DOI: 10.5281/zenodo.1443440
title: Riigikaitse Ja Avalik Arvamus 2000-01

description: EV Kaitseministeeriumi tellitud regulaaruuringu "Riigikaitse ja avalik arvamus" andmestik 2000-01
description: Andmetele ligipääsu taotlemiseks palun võtta ühendust Eesti Sotsiaalteadusliku Andmearhiiviga aadressil socarch@psych.ut.ee
DOI: 10.5281/zenodo.1443441
title: Riigikaitse Ja Avalik Arvamus 2000-01

description: EV Kaitseministeeriumi tellitud regulaaruuringu "Riigikaitse ja avalik arvamus" andmestik 2000-01
description: Andmetele ligipääsu taotlemiseks palun võtta ühendust Eesti Sotsiaalteadusliku Andmearhiiviga aadressil socarch@psych.ut.ee
DOI: 10.17632/5thy2mcwn7.4
title: Data for Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

description: Data underlying figures and relative risk curves within the article. Provides readers the mean value and uncertainty intervals for prevalence of current drinking, drinks per day by location, relative risks by outcome and dose, along with results for the weighted all-cause relative risk curve used to justify TMREL within the study. Based off sources mentioned in Appendix I. From Abstract in linked paper: Background Alcohol use is a leading risk factor for death and disability, but its overall association with health remains complex given the possible protective effects of moderate alcohol consumption on some conditions. With our comprehensive approach to health accounting within the Global Burden of Diseases, Injuries, and Risk Factors Study 2016, we generated improved estimates of alcohol use and alcohol-attributable deaths and disability-adjusted life-years (DALYs) for 195 locations from 1990 to 2016, for both sexes and for 5-year age groups between the ages of 15 years and 95 years and older. Methods Using 694 data sources of individual and population-level alcohol consumption, along with 592 prospective and retrospective studies on the risk of alcohol use, we produced estimates of the prevalence of current drinking, abstention, the distribution of alcohol consumption among current drinkers in standard drinks daily (defined as 10 g of pure ethyl alcohol), and alcohol-attributable deaths and DALYs. We made several methodological improvements compared with previous estimates: first, we adjusted alcohol sales estimates to take into account tourist and unrecorded consumption; second, we did a new meta-analysis of relative risks for 23 health outcomes associated with alcohol use; and third, we developed a new method to quantify the level of alcohol consumption that minimises the overall risk to individual health
DOI: 10.17632/h8jrmjjjbh.1
title: OTUB2 promotes cancer metastasis via Hippo independent activation of YAP and TAZ, Zhang et al.

description: The transcriptional regulators YAP and TAZ play important roles in development, physiology and tumorigenesis and are negatively controlled by the Hippo pathway. Upon activation of Hippo signaling, YAP and TAZ are phosphorylated by LATS1/2 and Casein 1δ/ε kinases, leading to poly-ubiquitination by SCF E3 ubiquitin ligase and proteasomal degradation. Although YAP/ TAZ proteins are frequently activated in human malignancies in which the Hippo pathway is still active, it is yet unknown whether YAP/TAZ can be stabilized via deubiquitination and thereby escape from the negative Hippo control. Here, by a gain-of-function cancer metastasis screen we discovered OTUB2 as a cancer stemness and metastasis-promoting factor that deubiquitinates and activates YAP/TAZ. We found OTUB2 to be poly-SUMOylated on Lysine 233 and this SUMOylation enables it to bind YAP/TAZ. We also identified an as yet unknown SUMO-interacting motif (SIM) in YAP and TAZ required for their association with SUMOylated OTUB2. Importantly, EGF and oncogenic KRAS induce OTUB2 poly-SUMOylation and thereby activating YAP/TAZ. Our results not only establish OTUB2 as an essential modulator of YAP/TAZ, but also reveal a novel regulatory mechanism via which YAP/TAZ activity is induced by oncogenic KRAS.
DOI: 10.17632/pr246v6594.1
title: Synthetic Edges for Corner Training DATA

description: The training dataset is composed by 31x31pixels images of synthetic edges of 38160 (73.6%) CORNERS and 13680 (26.4%) NO-CORNERS. We generated, from the central pixel, two line segments, L1 and L2, that are oriented by the angles a1 and a2 respectively as shown in "line-segments.png". The angles vary from 0° to 355°, in increments of 5°. When the inner angle between L1 and L2 is less than 140°, the descriptor that is associated to the central pixel belongs to the CORNER Class. Otherwise, a greater angle is considered a straight line and the central pixel belongs to the NO-CORNER class. Aiming to obtain a noise-robust corner detector, we generated ten images with salt and pepper noise with 0.04 as noise density, for each combination (L1,L2) as shown in "dataset.png".
DOI: 10.5061/dryad.2122768.1/1.1
title: Nieto_Quintano_et_al_DATAplots

description: Plot level tree data (DBH&gt;10 cm) for 4 25-ha plots in the Bateke Plateau  (plots LWR1 and LWR2 in Lefini Reserve and plots LLR1 and LLR2 in Lesio Louna Reserve)
DOI: 10.5061/dryad.2122768.1/2.1
title: Nieto_Quintano_et_at_DATAsubplots

description: Species composition data (presence/absence) for 1-ha subplots, situated inside 4 plots of 25-ha (plots LWR1 and LWR2 in Lefini Reserve and plots LLR1 and LLR2 in Lesio Louna Reserve), located in the Bateke Plateau (Republic of Congo)
DOI: 10.5061/dryad.2122768.2/1.2
title: Nieto_Quintano_et_al_DATAplots

description: Plot level tree data (DBH&gt;10 cm) for 4 25-ha plots in the Bateke Plateau  (plots LWR1 and LWR2 in Lefini Reserve and plots LLR1 and LLR2 in Lesio Louna Reserve)
DOI: 10.5061/dryad.2122768.2/2.2
title: Nieto_Quintano_et_at_DATAsubplots

description: Species composition data (presence/absence) for 1-ha subplots, situated inside 4 plots of 25-ha (plots LWR1 and LWR2 in Lefini Reserve and plots LLR1 and LLR2 in Lesio Louna Reserve), located in the Bateke Plateau (Republic of Congo)
DOI: 10.5061/dryad.2122768.2/3.2
title: Nieto_Quintano_et_al_DATASubplots_Grass_Saplings

description: Subplot level grass data (Above ground Carbon stocks) for 4 25-ha plots in the Bateke Plateau  (plots LWR1 and LWR2 in Lefini Reserve and plots LLR1 and LLR2 in Lesio Louna Reserve), and Subplot level saplings/shrubs data (Above ground Carbon stocks) for 4 25-ha plots in the Bateke Plateau  (plots LWR1 and LWR2 in Lefini Reserve and plots LLR1 and LLR2 in Lesio Louna Reserve).