cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/622n2yjg4w
title: ADBSat: Methodology of a novel panel method tool for aerodynamic analysis of satellites

description: ADBSat is a novel software that determines the aerodynamic properties of any body in free-molecular flow. Its main advantage is the fast approximation of the aerodynamics of spacecraft in the lower end of the low-Earth orbit altitude range. It is a novel implementation of a panel method, where the body is represented as a set of fundamental elements and the sum of their individual aerodynamic properties makes up the properties of the whole. ADBSat's approach treats the shape as a set of flat triangular plates. These are read from a CAD geometry file in the Wavefront format, which can be created with most common CAD programs. A choice of gas-surface interaction models is available to represent the physics of free-molecular flow under different conditions. Its modular design means that other models can be easily and quickly implemented. It also benefits from a new shading algorithm for fast determination of elemental flow exposure. An example case is presented to show the capability and functionality of the program.
DOI: 10.17632/r3bxp8mskj
title: GPT-4o for early-stage ovarian cancer diagnosis using pelvic computed tomography images

description: This dataset provides the CT videos and GPT-4o results of the 15 participants from TCGA-OV dataset to reproduce the GPT-4o experiment of the diagnosis of ovarian cancer.
DOI: 10.6084/m9.figshare.24916458.v1
title: Short and sweet - Multiple mini case studies as a form of rigorous case study research

description: Case study research is one of the most widely used research methods in Information Systems. In recent years, an increasing number of publications have used case studies with few sources of evidence, such as single interviews per case. While there is much methodological guidance on rigorously conducting multiple case studies, it remains unclear how researchers can achieve an acceptable level of rigour for this emerging type of multiple case study with few sources of evidence, i.e., multiple mini case studies. In this context, we synthesise methodological guidance for multiple case study research from a cross-disciplinary perspective to develop an analytical framework. Furthermore, we calibrate this analytical framework to multiple mini case studies by reviewing previous IS publications that use multiple mini case studies to provide guidelines to conduct multiple mini case studies rigorously. We also offer a conceptual definition of multiple mini case studies, distinguish them from other research approaches, and identify research situations for which the use of multiple mini case studies can be considered a pragmatic and rigorous approach (e.g., to research emerging and innovative phenomena).
DOI: 10.6084/m9.figshare.3512714.v1
title: Supplement 1. Database of wood density for species naturally occurring in Central and in South America.

description: File List list-references.txt wood-density-file.txt Description The list-references.txt file contains the list of literature sources consulted to produce the wood-density-file.txt wood density dataset. All valid species names were checked against the Missouri Botanical Garden's website (06/2004). In file list-references.txt, c olumn names are as follows. (1) CODE - conventional code for the literature source (2) LOCMEAS - country of study (or region, if applicable) (3) NBSPP - number of valid species in the dataset (4) REFERENCE - literature source for the dataset (several sources if applicable) In file wood-density-file.txt, column names are as follows. (1) FAMILY - family name for the species (according to the revised Angiosperm Phylogeny Group's classification) (2) GENUS - genus name (3) SPECIES - species name (4) WSG - mean wood species gravity for the species (5) NB - total number of literature values for the species (6) to (68) -- one column per literature source. Column name corresponds to the CODE entry in file list-references.txt (69) MEANELEV - mean elevation of the voucher speciemen for the species (70) SDELEV - standard deviation of the mean elevation (71) to (79) -- presence-absence variables for the nine ecoregions as described in the main text (see Fig. 1)
DOI: 10.17632/f52y9zkpzm
title: RNF31 inhibition sensitizes tumors to bystander killing by innate and adaptive immune cells

description: Tumor escape mechanisms for immunotherapy include deficiencies in antigen presentation, diminishing adaptive CD8+ T cell antitumor activity. Although innate NK cells are triggered by loss of MHC class I, their response is often inadequate. To increase tumor susceptibility to both innate and adaptive immune elimination, we performed parallel genome-wide CRISPR-Cas9 knockout screens under NK and CD8+ T cell pressure. We identified all components, RNF31, RBCK1, and SHARPIN, of the linear ubiquitination chain assembly complex (LUBAC). Genetic and pharmacologic ablation of RNF31, an E3 ubiquitin ligase, strongly sensitized melanoma, breast and colorectal cancer cells to both NK and CD8+ T cell killing. This occurred in a TNF-dependent manner, causing loss of A20 and non-canonical IKK complexes from TNF Receptor Complex I. Corroborating this preclinically, a small molecule RNF31 inhibitor sensitized human colon carcinoma organoids to TNF and greatly enhanced immune bystander killing of antigen-loss and antigen presentation machinery-deficient tumor cells. These results merit exploration of RNF31 inhibition as a clinical pharmacological opportunity for immunotherapy-refractory cancers.
DOI: 10.17632/k4pmt4ttn5
title: Data for: The spillover effects of MD&A disclosures for real investment: The role of industry competition

description: This dataset contains, for each firm and fiscal year, the tone of dislosures in the Management Discussion and Analysis (MD&A), the tone of common disclosures in the MD&A, and the tone of firm-specific disclosures in the MD&A.
DOI: 10.17632/t27jvj4vz2
title: CCLEfullyIntercepted_EXP_CNV_miRNA_DataSET

description: The CCLE data was obtained from https://depmap.org/portal/download/. This includes the CCLE expression data. We obtained the RNAseq TPM gene expression data for protein coding genes, also Log2 transformed with a pseudocount of 1 and the HGNC and Entrez ID identifiers (“DepMap, Broad (2021): DepMap 21Q3 Public. figshare. Dataset,” n.d.)⁠. The miRNA expression data was also obtained from Depmap (Cancer Cell Line Encyclopedia Consortium, 2015; J et al., 2012).  We also obtained the CCLE ABSOLUTE copy number analysis results of 2019 (G. M et al., 2019)⁠  and mapped the CNV data of the corresponding miRNAs to the raw segmented copy-number profiles in the .seg file format (hg19) of
CCLE DNA Copy Number using the GRCh38.87 version of the genome. A full interception of all datasets was performed to have a complete dataset for 904 cell lines and 18431 instances including 541 miRNAs. For a full description check our publication here: https://www.sciencedirect.com/science/article/pii/S258900422101378X

The data set is formated to be used by BioNetUCR, available here: bionet.prislab.org/download

DepMap, Broad (2021): DepMap 21Q3 Public. figshare. Dataset. (n.d.). Retrieved September 2, 2021, from https://figshare.com/articles/dataset/DepMap_21Q3_Public/15160110/2?file=29124102

Cancer Cell Line Encyclopedia Consortium,  and G. of D. S. in C. C. (2015). Pharmacogenomic agreement between two cancer cell line data sets. Nature, 528(7580), 84–87. https://doi.org/10.1038/NATURE15736

M, G., FW, H., J, J.-V., GV, K., CC, L., ER, M., … WR, S. (2019). Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature, 569(7757), 503–508. https://doi.org/10.1038/S41586-019-1186-3
DOI: 10.17632/w2b8kx2bvn
title: Dataset of Foramen Magnum for sex determination

description: Data augmentation, the dataset consisted of 2280 images, which were split into a training set (92%, 2100 images), validation set (5%, 120 images), and test set (3%, 60 images). 
This dataset was exported via roboflow.com on June 20, 2024 at 1:07 PM GMT

Roboflow is an end-to-end computer vision platform that helps you
* collaborate with your team on computer vision projects
* collect & organize images
* understand and search unstructured image data
* annotate, and create datasets
* export, train, and deploy computer vision models
* use active learning to improve your dataset over time

For state of the art Computer Vision training notebooks you can use with this dataset,
visit https://github.com/roboflow/notebooks

To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com

The dataset includes 2280 images.
Sex-determination-wUCa are annotated in Tensorflow Object Detection format.

The following pre-processing was applied to each image:
* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Resize to 640x640 (Stretch)

The following augmentation was applied to create 5 versions of each source image:
* 50% probability of horizontal flip
* 50% probability of vertical flip
* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise
* Random rotation of between -15 and +15 degrees
* Random brigthness adjustment of between -15 and +15 percent
* Random exposure adjustment of between -10 and +10 percent
* Random Gaussian blur of between 0 and 2.5 pixels
* Salt and pepper noise was applied to 0.14 percent of pixels
DOI: 10.5281/zenodo.14198918
title: AWS Spot Price History

description: AWS Spot Price History

This dataset tracks historical prices for AWS spot prices across all regions. It is updated automatically on the 1st of each month to contain data from the previous month.

Data format

Each month of data is stored as a ZStandard-compressed `.tsv.zst` file in the `prices` folder.

The data format matches that returned by AWS's `describe-spot-instance-prices`, with the exception that availability zones have been replaced by their global ID. For instance, here are some example lines from one capture:

euc1-az2        i4i.8xlarge     Linux/UNIX      1.231800        2023-02-28T23:59:57+00:00euc1-az3        r5b.8xlarge     Red Hat Enterprise Linux        0.749600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     SUSE Linux      0.744600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     Linux/UNIX      0.619600        2023-02-28T23:59:58+00:00euc1-az3        m5n.4xlarge     Red Hat Enterprise Linux        0.476000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Red Hat Enterprise Linux        0.492000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     SUSE Linux      0.471000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     SUSE Linux      0.487000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     Linux/UNIX      0.346000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Linux/UNIX      0.362000        2023-02-28T23:59:59+00:00

When fetching spot instance pricing from AWS, results contain some prices from the previous month so that the price is known at the start of the month. These prices are adjusted in this dataset to be at the exact start of the month UTC:

euw3-az2        g4dn.4xlarge    Linux/UNIX      0.558600        2023-01-01T00:00:00+00:00

For data from 2023-01 and before, this data was fetched more than one month at a time. This should have no negative impact unless, for example, an instance type was retired before the month began (and there should therefore be no price). These older files also only contain default regions. Data from 2023-02 and later contains all regions, including opt-in regions.

Using data

You can process each month individually. If you need the entire data stream at once, you can cat all files to `zst` together:

cat prices/*/*.tsv.zst | zstd -d
DOI: 10.5281/zenodo.14254097
title: AWS Spot Price History

description: AWS Spot Price History

This dataset tracks historical prices for AWS spot prices across all regions. It is updated automatically on the 1st of each month to contain data from the previous month.

Data format

Each month of data is stored as a ZStandard-compressed `.tsv.zst` file in the `prices` folder.

The data format matches that returned by AWS's `describe-spot-instance-prices`, with the exception that availability zones have been replaced by their global ID. For instance, here are some example lines from one capture:

euc1-az2        i4i.8xlarge     Linux/UNIX      1.231800        2023-02-28T23:59:57+00:00euc1-az3        r5b.8xlarge     Red Hat Enterprise Linux        0.749600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     SUSE Linux      0.744600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     Linux/UNIX      0.619600        2023-02-28T23:59:58+00:00euc1-az3        m5n.4xlarge     Red Hat Enterprise Linux        0.476000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Red Hat Enterprise Linux        0.492000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     SUSE Linux      0.471000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     SUSE Linux      0.487000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     Linux/UNIX      0.346000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Linux/UNIX      0.362000        2023-02-28T23:59:59+00:00

When fetching spot instance pricing from AWS, results contain some prices from the previous month so that the price is known at the start of the month. These prices are adjusted in this dataset to be at the exact start of the month UTC:

euw3-az2        g4dn.4xlarge    Linux/UNIX      0.558600        2023-01-01T00:00:00+00:00

For data from 2023-01 and before, this data was fetched more than one month at a time. This should have no negative impact unless, for example, an instance type was retired before the month began (and there should therefore be no price). These older files also only contain default regions. Data from 2023-02 and later contains all regions, including opt-in regions.

Using data

You can process each month individually. If you need the entire data stream at once, you can cat all files to `zst` together:

cat prices/*/*.tsv.zst | zstd -d
DOI: 10.5281/zenodo.14254112
title: AWS Spot Price History

description: AWS Spot Price History

This dataset tracks historical prices for AWS spot prices across all regions. It is updated automatically on the 1st of each month to contain data from the previous month.

Data format

Each month of data is stored as a ZStandard-compressed `.tsv.zst` file.

The data format matches that returned by AWS's `describe-spot-instance-prices`, with the exception that availability zones have been replaced by their global ID. For instance, here are some example lines from one capture:

euc1-az2        i4i.8xlarge     Linux/UNIX      1.231800        2023-02-28T23:59:57+00:00euc1-az3        r5b.8xlarge     Red Hat Enterprise Linux        0.749600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     SUSE Linux      0.744600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     Linux/UNIX      0.619600        2023-02-28T23:59:58+00:00euc1-az3        m5n.4xlarge     Red Hat Enterprise Linux        0.476000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Red Hat Enterprise Linux        0.492000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     SUSE Linux      0.471000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     SUSE Linux      0.487000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     Linux/UNIX      0.346000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Linux/UNIX      0.362000        2023-02-28T23:59:59+00:00

When fetching spot instance pricing from AWS, results contain some prices from the previous month so that the price is known at the start of the month. These prices are adjusted in this dataset to be at the exact start of the month UTC:

euw3-az2        g4dn.4xlarge    Linux/UNIX      0.558600        2023-01-01T00:00:00+00:00

For data from 2023-01 and before, this data was fetched more than one month at a time. This should have no negative impact unless, for example, an instance type was retired before the month began (and there should therefore be no price). These older files also only contain default regions. Data from 2023-02 and later contains all regions, including opt-in regions.

Using data

You can process each month individually. If you need the entire data stream at once, you can cat all files to `zst` together:

cat prices/*/*.tsv.zst | zstd -d
DOI: 10.5281/zenodo.14254124
title: AWS Spot Price History

description: AWS Spot Price History

This dataset tracks historical prices for AWS spot prices across all regions. It is updated automatically on the 1st of each month to contain data from the previous month.

Data format

Each month of data is stored as a ZStandard-compressed .tsv.zst file.

The data format matches that returned by AWS's describe-spot-instance-prices, with the exception that availability zones have been replaced by their global ID. For instance, here are some example lines from one capture:

euc1-az2        i4i.8xlarge     Linux/UNIX      1.231800        2023-02-28T23:59:57+00:00euc1-az3        r5b.8xlarge     Red Hat Enterprise Linux        0.749600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     SUSE Linux      0.744600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     Linux/UNIX      0.619600        2023-02-28T23:59:58+00:00euc1-az3        m5n.4xlarge     Red Hat Enterprise Linux        0.476000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Red Hat Enterprise Linux        0.492000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     SUSE Linux      0.471000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     SUSE Linux      0.487000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     Linux/UNIX      0.346000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Linux/UNIX      0.362000        2023-02-28T23:59:59+00:00

When fetching spot instance pricing from AWS, results contain some prices from the previous month so that the price is known at the start of the month. These prices are adjusted in this dataset to be at the exact start of the month UTC:

euw3-az2        g4dn.4xlarge    Linux/UNIX      0.558600        2023-01-01T00:00:00+00:00

For data from 2023-01 and before, this data was fetched more than one month at a time. This should have no negative impact unless, for example, an instance type was retired before the month began (and there should therefore be no price). These older files also only contain default regions. Data from 2023-02 and later contains all regions, including opt-in regions.

Using data

You can process each month individually. If you need the entire data stream at once, you can cat all files to zst together:

cat prices/*/*.tsv.zst | zstd -d
DOI: 10.5281/zenodo.14647491
title: AWS Spot Price History

description: AWS Spot Price History

This dataset tracks historical prices for AWS spot prices across all regions. It is updated automatically on the 1st of each month to contain data from the previous month.

Data format

Each month of data is stored as a ZStandard-compressed .tsv.zst file.

The data format matches that returned by AWS's describe-spot-instance-prices, with the exception that availability zones have been replaced by their global ID. For instance, here are some example lines from one capture:

euc1-az2        i4i.8xlarge     Linux/UNIX      1.231800        2023-02-28T23:59:57+00:00euc1-az3        r5b.8xlarge     Red Hat Enterprise Linux        0.749600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     SUSE Linux      0.744600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     Linux/UNIX      0.619600        2023-02-28T23:59:58+00:00euc1-az3        m5n.4xlarge     Red Hat Enterprise Linux        0.476000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Red Hat Enterprise Linux        0.492000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     SUSE Linux      0.471000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     SUSE Linux      0.487000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     Linux/UNIX      0.346000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Linux/UNIX      0.362000        2023-02-28T23:59:59+00:00

When fetching spot instance pricing from AWS, results contain some prices from the previous month so that the price is known at the start of the month. These prices are adjusted in this dataset to be at the exact start of the month UTC:

euw3-az2        g4dn.4xlarge    Linux/UNIX      0.558600        2023-01-01T00:00:00+00:00

For data from 2023-01 and before, this data was fetched more than one month at a time. This should have no negative impact unless, for example, an instance type was retired before the month began (and there should therefore be no price). These older files also only contain default regions. Data from 2023-02 and later contains all regions, including opt-in regions.

Using data

You can process each month individually. If you need the entire data stream at once, you can cat all files to zst together:

cat prices/*/*.tsv.zst | zstd -d
DOI: 10.5281/zenodo.15007243
title: AWS Spot Price History

description: AWS Spot Price History

This dataset tracks historical prices for AWS spot prices across all regions. It is updated automatically on the 1st of each month to contain data from the previous month.

Data format

Each month of data is stored as a ZStandard-compressed .tsv.zst file.

The data format matches that returned by AWS's describe-spot-instance-prices, with the exception that availability zones have been replaced by their global ID. For instance, here are some example lines from one capture:

euc1-az2        i4i.8xlarge     Linux/UNIX      1.231800        2023-02-28T23:59:57+00:00euc1-az3        r5b.8xlarge     Red Hat Enterprise Linux        0.749600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     SUSE Linux      0.744600        2023-02-28T23:59:58+00:00euc1-az3        r5b.8xlarge     Linux/UNIX      0.619600        2023-02-28T23:59:58+00:00euc1-az3        m5n.4xlarge     Red Hat Enterprise Linux        0.476000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Red Hat Enterprise Linux        0.492000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     SUSE Linux      0.471000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     SUSE Linux      0.487000        2023-02-28T23:59:59+00:00euc1-az3        m5n.4xlarge     Linux/UNIX      0.346000        2023-02-28T23:59:59+00:00euc1-az2        m5n.4xlarge     Linux/UNIX      0.362000        2023-02-28T23:59:59+00:00

When fetching spot instance pricing from AWS, results contain some prices from the previous month so that the price is known at the start of the month. These prices are adjusted in this dataset to be at the exact start of the month UTC:

euw3-az2        g4dn.4xlarge    Linux/UNIX      0.558600        2023-01-01T00:00:00+00:00

For data from 2023-01 and before, this data was fetched more than one month at a time. This should have no negative impact unless, for example, an instance type was retired before the month began (and there should therefore be no price). These older files also only contain default regions. Data from 2023-02 and later contains all regions, including opt-in regions.

Using data

You can process each month individually. If you need the entire data stream at once, you can cat all files to zst together:

cat prices/*/*.tsv.zst | zstd -d