cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/pf2bvmfsmb
title: Data of 'Radiation dose in CT-based active surveillance of small renal masses may be reduced by 75%. A retrospective exploratory multiobserver study'

description: Active surveillance is increasingly utilized in managing small renal masses (SRM), regardless of patient age. The follow-up protocol most commonly used includes contrast-enhanced abdominal CT scanning. The cumulative radiation dose incurred in serial imaging as part of active surveillance is a concern. There is an unmet need for reducing radiation dose while preserving the accuracy and reproducibility needed in radiographic measurements such that small changes in renal mass size can be appreciated. Using a simulation technique, we investigated the accuracy and reproducibility of low-dose CT (75% dose reduction) compared to normal-dose CT to assess maximum axial renal tumor diameter. Open access CT datasets from the 2019 Kidney and Kidney Tumor Segmentation Challenge were used. We hypothesized that contrast-enhanced low-dose CT with a 75% reduction in radiation dose could be used interchangeably with normal-dose CT in terms of accuracy and reproducibility in determining the maximum diameter of SRMs. We found similar accuracy and reproducibility of low-dose versus normal-dose CT, which suggests these modalities can be used interchangeably for the assessment of maximal axial tumor diameter. The data deposited here consists of 2 CSV files with tumor diameter measurements completed by six observers evaluating 40 cases of low-dose CT and normal-dose CT, respectively. Furthermore, an additional CSV file contains the identification number (i.e., patient_id) in relation to the 2019 Kidney and Kidney Tumor Segmentation Challenge dataset. In addition, a PDF file is provided with key images of caliper placements for each case (n=40) and observer (n=6), as well as the tumor, CT, and patient details. The presented data may stimulate future research investigating low-dose CT for active surveillance of small renal masses.
DOI: 10.17632/vrzbmvngnw
title: Replication data for "Are Trade Wars Class Wars? The Importance of Trade-Induced Horizontal Inequality"

description: This package contains replication data for the paper ""Are Trade Wars Class Wars? The Importance of Trade-Induced Horizontal Inequality."
DOI: 10.17632/h86g2n3p42
title: National Bio-ethanol Supply and Demand Forecast and Electric Vehicle Sales Dataset

description: (1) Ethanol, Corn, Bioethanol, gasoline price and production history monthly data sets, a total of 8 tables (2) Historical monthly data set of electric vehicle output and energy consumption conversion rate (a total of nine tables from four data sources) (3) GHG, CPI, GDP historical data set (a total of 3 tables) (4) SEDS supply and demand data table (one table) (5) OR matrix between states in the United States (1 table) (6) Simulation model planning algorithm output results (5 tables)
DOI: 10.17632/rdhys9n968
title: De-Risking Renewable Energy Investments in Developing Countries: A Multilateral Guarantee Mechanism. Matthäus and Mehling
DOI: 10.6084/m9.figshare.19715020.v1
title: Phenotype Representation Learning (PRL) - LUAD/LUSC 5x

description: Pre-trained weights on Barlow Twins LUAD/LUSC at 5X magnification with 60% background limit.
DOI: 10.6084/m9.figshare.840519.v3
title: Fang et al. 2012

description: SNP data from Fang et al. 2012 Taxon names are genus/subpsecies, such that Zl = Zea luxurians, Zd = Zea diploperennis, Tdact = Tripsacum dactyloides, etc. http://www.genetics.org/content/191/3/883.abstract
DOI: 10.6084/m9.figshare.22277278.v1
title: MS Waves in Martian Ionosphere

description: The data for producing Figure 2 are saved in the file ''figure2_data'', which can be restored and displayed respectively by the IDL procedure ''tplot_restore'' and ''tplot'' provided by the publicly available SPEDAS software (http://spedas.org). The variables named as ''wave_powspec'', ''wave_waveangle'', ''wave_elliptict'' are power spectral density, wave normal angle and ellipticity, respectively. The variables named as ''mvn_B_full_fac_bp_x'', ''mvn_B_full_fac_bp_y'', ''mvn_B_full_fac_bp_z'' are radial, azimuthal and field-aligned components of magnetic field in the mean field-aligned coordinate system, respectively. The data for producing Figure 4 are saved in the file ''figure4_data'', which can be restored by the IDL procedure ''restore''. The proton velocity distributions, wave growth rates and wave power spectral densities are stored in the variable ''proton_psd'', ''growth_rate'' and ''wave_power'', respectively.
DOI: 10.17632/sg9kwnwcp6
title: sEMG database of the MYO bracelet for hand gestures

description: The data were collected with the MYO armband for four different hand movements: fist, cylindrical grip, spherical grip and tip pinch. 225 tests were obtained from different users for each movement and a total of 900 tests for the four movements. Each Prueba*** file corresponds to a different person. The age range is 20 to 45 years of the male and female gender. Each of the tests contains 9 different attributes. The first eight columns correspond to each of the sEMG sensors, column 9 contains sampling time information. Each test includes 998 samples per sensor. The total time sampled was 5 seconds for each movement.
DOI: 10.17632/y9xp33y5d4
title: Data for: Intertidal foraminifera in the Spartina patens floral zone of the LaHave Estuary, Canada: a baseline for assessing organic pollution remediation

description: Intertidal foraminifera in the Spartina patens zone in the LaHave Estuary, Lunenburg County, Nova Scotia, Canada, sampled July 2017.
DOI: 10.6084/m9.figshare.13720693.v1
title: Supplementary Material for: Visual Analysis of Biomarkers Reveals Differences in Lipid Profiles and Liver Enzymes before and after Gastric Sleeve and Bypass

description: <b><i>Introduction:</i></b> Bariatric surgery results in both intentional and unintentional metabolic changes. In a high-volume bariatric center, extensive laboratory panels are used to monitor these changes pre- and postoperatively. Consecutive measurements of relevant biochemical markers allow exploration of the health state of bariatric patients and comparison of different patient groups. <b><i>Objective:</i></b> The objective of this study is to compare biomarker distributions over time between 2 common bariatric procedures, i.e., sleeve gastrectomy (SG) and gastric bypass (RYGB), using visual analytics. <b><i>Methods:</i></b> Both pre- and postsurgical (6, 12, and 24 months) data of all patients who underwent primary bariatric surgery were collected retrospectively. The distribution and evolution of different biochemical markers were compared before and after surgery using asymmetric beanplots in order to evaluate the effect of primary SG and RYGB. A beanplot is an alternative to the boxplot that allows an easy and thorough visual comparison of univariate data. <b><i>Results:</i></b> In total, 1,237 patients (659 SG and 578 RYGB) were included. The sleeve and bypass groups were comparable in terms of age and the prevalence of comorbidities. The mean presurgical BMI and the percentage of males were higher in the sleeve group. The effect of surgery on lowering of glycated hemoglobin was similar for both surgery types. After RYGB surgery, the decrease in the cholesterol concentration was larger than after SG. The enzymatic activity of aspartate aminotransferase, alanine aminotransferase, and alkaline phosphate in sleeve patients was higher presurgically but lower postsurgically compared to bypass values. <b><i>Conclusions:</i></b> Beanplots allow intuitive visualization of population distributions. Analysis of this large population-based data set using beanplots suggests comparable efficacies of both types of surgery in reducing diabetes. RYGB surgery reduced dyslipidemia more effectively than SG. The trend toward a larger decrease in liver enzyme activities following SG is a subject for further investigation.
DOI: 10.17632/bhwfs7xc9x
title: Supplementary Materials "Predictors of surgical treatment burden, outcomes and overall survival in older adults with basal cell carcinoma: results from the prospective, multicenter BATOA cohort"

description: Supplementary Materials for: van Winden MEC, Bronkhorst EM, Visch MB, Krekels GAM, van der Geer S, Damen GWJA, Amir A, Aben KKH, Gerritsen MJP, van de Kerkhof PCM, de Jong EMGJ, Lubeek SFK. Predictors of surgical treatment burden, outcomes and overall survival in older adults with basal cell carcinoma: results from the prospective, multicenter BATOA cohort. Supplemental Fig 1. Flow-chart of the inclusion Supplemental Fig 2. The questionnaire used to evaluate treatment burden and cosmetic result Supplemental Fig 3. Treatment burden results Supplemental Fig 4. Cosmetic results Supplemental Table I. Specifications of complications Supplemental Table II. Complications per tumor location Supplemental Table III. Results of the step-down procedure used in multivariable analyses (Cox regression) of covariates possibly associated with short-term survival.
DOI: 10.17632/dghwc85p9v
title: Temperature sensitivity of soil organic carbon and its components on the Tibetan Plateau

description: This excel document contains all the data related to soil incubation and soil properties for the study entitled “Soil microbial and edaphic properties determine temperature sensitivity of soil organic carbon and its components on the Tibetan Plateau” .
DOI: 10.17632/m5jk7wzyg7
title: Food Delivery Apps (DoorDash, Grubhub & UberEats) Reviews

description: This dataset contains user-generated reviews collected from the Google Play Store for three major food delivery applications: DoorDash, Grubhub, and Uber Eats. The dataset was compiled through web scraping on November 10, 2023, and includes various attributes that capture user sentiments, textual content, and keyword-based analysis related to the Technology Acceptance Model (TAM).
Data Collection Process:

 Source: Google Play Store user reviews 
 Scraping Method: A Python-based web scraping script
 Language: English-language reviews from the US were retained
 Final Dataset Size (after cleaning): 1,694,581 reviews
 Processing Tools: Python (pandas, NRCLex, nltk, seaborn, sklearn, vaderSentiment, numpy, matplotlib)
 Sentiment Classification:
 Positive: 4-5 star ratings
 Neutral: 3-star ratings
 Negative: 1-2 star ratings
 Lexicon-Based Sentiment Analysis: VADER and AFINN scores were calculated to enhance sentiment classification accuracy.

Dataset Columns & Descriptions:
Column Name Description
content The full text of the user review.
score The star rating given by the user (1-5).
thumbsUpCount The number of likes (thumbs up) a review received.
Apps The app to which the review belongs (DoorDash, Grubhub, or Uber Eats).
sentiment The sentiment category assigned based on the star rating (Positive, Neutral, Negative).
afinn_score Sentiment score based on the AFINN lexicon (higher values indicate positive sentiment, lower values indicate negative sentiment).
vader_neg Negative sentiment score assigned by VADER (closer to 1 indicates stronger negativity).
vader_neu Neutral sentiment score assigned by VADER (closer to 1 indicates a more neutral review).
vader_pos Positive sentiment score assigned by VADER (closer to 1 indicates stronger positivity).
vader_compound Overall sentiment score from VADER.
word_count The total number of words in the review .
Ease_of_Use A value indicating whether the review contains keywords related to perceived ease of use (1 = present and positive, -1 = present and negative, 0 = absent).
Intention_to_Use A value indicating whether the review contains keywords related to perceived intention to use the app (1 = present and positive, -1 = present and negative, 0 = absent).
Usefulness A value indicating whether the review contains keywords related to perceived usefulness of the app (1 = present and positive, -1 = present and negative, 0 = absent).

Potential Use Cases:
 Sentiment Analysis of user experiences with food delivery apps.
 User Behavior Analysis to identify factors influencing app adoption.
 TAM Model Validation in the context of online food delivery services.
 Comparative Analysis of DoorDash, Grubhub, and Uber Eats based on user feedback.
 Natural Language Processing (NLP) & Machine Learning Applications for review classification.
DOI: 10.17632/t64dbpv63x
title: Riparian buffer zone quantitative effectiveness review database

description: The quantitative effectiveness review of RBZ width yielded 79 studies. These were subdivided into 474 database rows, where studies generated multiple rows across differing experimental parameters of width, vegetation, rainfall intensity and slope.
DOI: 10.17632/bhwvm6889n
title: Fire resistance evaluation through artificial intelligence - A case for timber structures

description: Used in the following article: Naser MZ. Fire resistance evaluation through artificial intelligence-A case for timber structures. Fire Safety Journal. 2019 Apr 1;105:1-8. https://doi.org/10.1016/j.firesaf.2019.02.002
DOI: 10.17632/468rykr8vp
title: Cloud Desktop (VDI) project and product type test datasets

description: This dataset is collected from standardized project information on multiple popular desktop cloud solutions. This dataset allows researchers and developers to compare the performance metrics of different desktop cloud products based on real data and evaluate the strengths and weaknesses. This dataset contains test results of different vendor products under different hardware configurations and network conditions. All data is strictly desensitized. We hope to promote the development of desktop cloud technology through data sharing, and we welcome community feedback to improve the dataset.
DOI: 10.6084/m9.figshare.12855563.v1
title: IN_mW_Aug2020.csv

description: Dataset for the manuscript "Predicting Heterogeneous Ice Nucleation With a Data-Driven Approach" (DOI: 10.1038/s41467-020-18605-3)
DOI: 10.6084/m9.figshare.14061815.v1
title: CTRPv2 PSet

description: https://github.com/bhklab/Gene_Expression_Bimodality
DOI: 10.17632/nk6vnxm8wj
title: Small Hydropower Plants

description: Articles about small hydropower plants
DOI: 10.17632/sbyj5f6c3k
title: EEG data: anxiety patients & control group

description: The final sample included 47 participants: 24 anxiety patients and 23 volunteers without any neurological or psychiatric diagnoses as control group. Demographic information and clinical features are presented in Table 1. The selection criteria for the patient group were the following: right-handedness, age from 18 to 45 years, the presence of a leading anxiety and additional depressive syndrome, F41.0 (mixed anxiety and depressive disorder) or F41.2 (panic disorder) diagnosis according to ICD-10, and the duration of the disorder from six months to 5 years. Data collecting EEG data was acquired for each participant during the active tasks and the baseline. EEG was recorded using a 19-channel Electroencephalograph-analyzer EEGA-21/26 “Encephalan-131-03”. Data was sampled at 256 Hz with filter settings of 0.5 to 60 Hz in DC acquisition mode with impedances kept below 10 kΩ. Electrodes were positioned using the 10-20 international system. We also used four electrodes to record the electrooculogram (horizontal and vertical), electrocardiogram and electromyogram. All electrodes were referenced to A1 and A2 located on the left and right mastoids, respectively. 2.6. Data processing and analysis Processing (including filtering, artifact minimization, epoch division, fast Fourier transform, spectral analysis, data export) was performed using the embedded commercial software “Encephalan-EEGA-pro” (Medicom-MTD) and LORETA software. EEG records for each subject were divided into five groups according to stimuli – baseline, observation, imagination, execution, execution+observation together. The registered fragments were cleared of artifacts, then were processed with Fast Fourier Transform in 3 frequency bands: alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-24 Hz).
DOI: 10.17632/wgsycmpcjn
title: Glutamine Synthetase Promotes Radiation Resistance via Facilitating Nucleotide Metabolism and Subsequent DNA Damage Repair

description: RNA sequencing and metabonomics data
DOI: 10.17632/789mzts524
title: The content of elements in 426 wines

description: The content of elements in 426 wines (Muscat, Riesling, Chardonnay, Merlot and Cabernet)
DOI: 10.17632/3fj3dnmczx
title: Microinfusion of 5-Fluorouracil Using a Tattooing Machine in Keloid Treatment: A Retrospective Review of Clinical Cases

description: Supplemental Material
DOI: 10.17632/4kmn36rr3y
title: Sustainable Management Publication Dataset (1992-2019)

description: The sustainable management reseach & publication dataset, subject area of business-management-accounting and economics-econometrics-finance, which was indexed by Scopus from 1992 to 2019. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
DOI: 10.17632/55rddfmfsz
title: Thermal Comfort Dataset - Darjeeling, 2015
DOI: 10.17632/jdd5j5tndv
title: Tcruzi-VMT: Video Microscopy and Motion Trajectories Dataset

description: The Tcruzi-VMT dataset provides a collection of videos and trajectories from parasitological analyses of Trypanosoma cruzi (T. cruzi), the etiological agent of Chagas disease, as used in our papers [1][2]. The videos were captured using optical microscopy with dye-free samples, enabling the analysis of parasite movement in its trypomastigote blood form. The dataset highlights T. cruzi exhibiting collateral motion, while blood cells perform fluctuating and PTZ motions. All trajectories were validated by specialists.

Video sets for training and testing are available. Videos are up to 10 seconds long, with a frame rate of approximately 30 frames per second (fps) and a resolution of 640 x 480 pixels. Both the training and testing sets contain videos with parasites in distinct microscope fields of view. Note: (1) The V1.avi video is available at https://doi.org/10.1371/journal.pone.0095398.s001. (2) The V4.avi video has no parasites. For further details, we recommend consulting [1].

Trajectory sets for training and testing are available. Each line of the CSV file is a trajectory step. Each step consists of the following fields: video name (Video); trajectory number (Trajectory); frame number (Frame); x position (Px); y position (Py); and label, with 0 for cell and 1 for parasite (Class). For further details, we recommend consulting [2].

The dataset can be used for studies on parasite motility, motion pattern analysis, and parasite detection. It is particularly valuable in parasitology, biophysics, AI research on motility-based diagnostics, and related fields.

If you use this dataset, please cite the following papers:

[1] Martins GL, Ferreira DS, Ramalho GLB (2021). Collateral motion saliency-based model for Trypanosoma cruzi detection in dye-free blood microscopy. Computers in Biology and Medicine 132:104220, ISSN 0010-4825, https://doi.org/10.1016/j.compbiomed.2021.104220

[2] Martins GL, Ferreira DS, Carneiro CM, Nogueira-Paiva NC, Bianchi AGC (2024). Trajectory-driven computational analysis for element characterization in Trypanosoma cruzi video microscopy. PLoS ONE 19(6): e0304716. https://doi.org/10.1371/journal.pone.0304716

Acknowledgment

The Immunopathology Laboratory of the Nucleus of Research in Biological Sciences (NUPEB) at the Federal University of Ouro Preto (UFOP) provided the videos used in this research, with special thanks to Dra. Cláudia M. Carneiro and Dra. Nivia C. N. de Paiva for their assistance in video analysis. Additional contributions came from the Parasite Biology Laboratory of the Faculty of Medicine at the National Autonomous University of Mexico (UNAM), with appreciation to Dra. Paz M. S. Schettino, Dra. Margarita C. Bravo, and Dra. Any L. F. Villegas, as well as expert TLC. David V. Perales.

Valuable insights and support that enriched the development of this project were provided, particularly by Dr. Daniel S. Ferreira, Dr. Geraldo L. B. Ramalho, and Dra. Andrea G. Campos, as well as by other collaborators.
DOI: 10.17632/nstgdfbxsh
title: Influence of agronomic parameters and storage parameters on the frying color of French fry potatoes (solanum tuberosum L.)

description: This dataset was used to calculate the regressions presented in the publication: "Influence of agronomic parameters and storage parameters on the frying color of French fry potatoes (solanum tuberosum L.)".
Data were created during a two year field trial at two locations in Bavaria, Southern Germany. In the trials two nitrogen fertilization rates as well as three harvest dates per location were tested. The so produced material was subsequently stored at two storage temperatures (7.5°C and 6.0°C). Quality sampling in terms of frying color was done monthly with a 20 tuber sample from December to March. The baking color assessment was done with an optoelectronic method, which expresses frying color as R/G-ratio after the 3-Minute Baking test. Additionally reducing sugar content was assessed encymatically for selected samples.
DOI: 10.17632/7v65s7k4y8
title: Datasets for the Project Portfolio Selection and Scheduling Problem

description: The primary objective of the Project Portfolio Selection and Scheduling Problem (PPSSP) is to maximise the total portfolio value through the selection and scheduling of a subset of projects subject to various operational constraints. This dataset includes a set of synthetically generated problem instances for two recently-proposed, generalised models of the PPSSP.  These problem instances can be used by researchers to compare the performance of heuristic and meta-heuristic solution strategies. In addition, the Python program used to generate the problem instances is supplied, allowing researchers to generate new problem instances.

The first model, extended from [1], is a project-oriented model such that projects are independently selected and scheduled, subject to various operational constraints such as prerequisites and mutual exclusion groups.  In the second model, originally proposed in [2], the projects are grouped into predetermined sets, referred to as options. Selection is made on the options, such that all projects within an option must be implemented if the option is selected. However, projects can be independently scheduled, within a fixed window. Furthermore, a project may be present in any number of options, but its cost is only counted once if it is selected as part of multiple options.  

Instances in the project_instances folder are divided into three sub-folders (250, 500, 1000) based on the number of projects contained in the problem. Within each sub-folder, instances are named "PI_{index}_{number of projects}_{number of planning years}_{proportion of budget for initiating projects}_{proportion of budget for maintaining ongoing projects}_{time discount rate}.json".

Instances in the option_instances folder are divided into four sub-folders (25, 50, 100, 250) based on the number of families contained in the problem. Within each sub-folder, instances are named "OI_{number of families}_{number of projects}_{proportion of divestment projects}_{yearly budget deviation}_{number of planning years}.json".

[1] K. R. Harrison, S. Elsayed, I. L. Garanovich, T. Weir, M. Galister, S. Boswell, R. Taylor, R. Sarker, A hybrid multi-population approach to the project portfolio selection and scheduling problem for future force design, IEEE Access 9 (2021) 83410–83430.

[2] K. R. Harrison, S. M. Elsayed, I. L. Garanovich, T. Weir, S. G. Boswell, R. A. Sarker, A new model for the project portfolio selection and scheduling problem with defence capability options, in: K. R. Harrison, S. M. Elsayed, I. L. Garanovich, T. Weir, S. G. Boswell, R. A. Sarker (Eds.), Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling, Springer International Publishing, 2022, pp. 89–123. doi:10.1007/978-3-030-88315-7_5.