cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24968940.v5
title: Microscopy Image Dataset for Deep Learning-Based Quantitative Assessment of Pulmonary Vascular Changes

description: Pulmonary hypertension (PH) is a syndrome complex that accompanies a number of diseases of different etiologies, associated with basic mechanisms of structural and functional changes of the pulmonary circulation vessels and revealed pressure increasing in the pulmonary artery. The structural changes in the pulmonary circulation vessels are the main limiting factor determining the prognosis of patients with PH. Thickening and irreversible deposition of collagen in the pulmonary artery branches walls leads to rapid disease progression and a therapy effectiveness decreasing. In this regard, histological examination of the pulmonary circulation vessels is critical both in preclinical studies and clinical practice. However, measurements of quantitative parameters such as the average vessel outer diameter, the vessel walls area, and the hypertrophy index claimed significant time investment and the requirement for specialist training to analyze micrographs.A dataset of pulmonary circulation vessels for pathology assessment using semantic segmentation techniques based on deep-learning is presented in this work. 609 original microphotographs of vessels, numerical data from experts' measurements, and microphotographs with outlines of these measurements for each of the vessels are presented. Furthermore, here we cite an example of a deep learning pipeline using the U-Net semantic segmentation model to extract vascular regions. The presented database will be useful for the development of new software solutions for the analysis of histological micrograph.
DOI: 10.6084/m9.figshare.26075494.v1
title: Firm level data for Estimating Digital Product Trade through Corporate Revenue Data

description: This dataset includes the firm level data generated in the manuscript "Estimating Digital Product Trade Through Corporate Revenue Data" by Viktor Stojkoski, Philipp Koch, Eva Coll, and César A. Hidalgo<br>We include four .csv files:<br>1) all_country_trade_ot_intervals.csv - Country level bilateral trade estimates per digital product category using the subsidiary assignment.2) all_country_trade_hq_intervals.csv - Country level bilateral trade estimates per digital product category using the headquarters assignment.3) all_firm_trade_ot_intervals.csv - Firm level bilateral trade estimates per digital product category using the subsidiary assignment.4) all_firm_trade_hq_intervals.csv - Firm level bilateral trade estimates per digital product category using the headquarters assignment.<br>The documents have the following columns:firm - name of parent company/app developer (only for the firm level data)year - year of tradecategory - digital categoryiso_o - exporter countryiso_d - importer countrytrade_value_pred - estimated trade valuelb_value - lower bound for the 95% confidence interval of the estimated trade valueub_value - upper bound for the 95% confidence interval of the estimated trade value<br>We also provide two lists that have details on the developers and firms included in our estimations: apps_unique_category_entries.csv and firms_unique_category_entries. The first list (apps_unique_category_entries.csv) includes the name of the app developer, their category and the country where they are registered. The second list, includes the firms, their digital categories, countries where they are registered, and their parent company.
DOI: 10.17632/rd9b4kg9yz
title: ICI-5 Flow and Histology Data

description: Flow cytometry and histology data for ICI-5. PMBC data from day 21 will be published under separate dataset due to lack of storage. Rest of information is available on figshare (see link below).
DOI: 10.6084/m9.figshare.24233629.v16
title: <b>Unlocking Optimal ORM Database Designs: Accelerated Tradeoff Analysis with Transformers</b>

description: Optimizing object-relational database mapping (ORM) design is essential for software system performance. However, current ORM design tools widely used in practice offer limited support for evaluating performance implications. State-of-the-art relying on systematic tradeoff analysis provides greater assistance but becomes impractical for large-scale, real-world systems. In this paper, we introduce an innovative solution grounded in machine learning to efficiently and scalably identify optimal ORM database tradeoffs.Our approach involves training a transformer model using a dataset of formally analyzed object-relational database designs to identify Pareto-optimal design tradeoffs, significantly reducing the number of design candidates. The extensive experiments across various software database systems demonstrate the high effectiveness of the approach in identifying optimal design alternatives overlooked by leading ORM tools. Additionally, our results show a remarkable 98.21 % improvement in analysis efficiency compared to the current state-of-the-art, reducing tradeoff analysis time from over 15 days to around 18 minutes on average.<br><br>
DOI: 10.17632/fsd2cgcmc8
title: Characterization and prediction of gambling behavior in adolescents using the COM-B model

description: Raw paired data from 354 students, aged 14-16 years (both inclusive), 52.54% female, taken in three waves (2016, 2017 and 2018). 
The variable_description folder contains the text files (docx and pdf formats) in which the measured variables are described, in English (variable_description_en-US) and Spanish (variable_description_ES). The variables measure sociodemographic data and constructs that are considered risk or protective factors for gambling-related problems, according to the existing literature.
In the "Data" folder, two data file formats are available, in RData format and in CSV format.
With these data we have tried to understand gambling behavior in adolescents and to interpret the risk and protective factors according to the COM-B model ( Capability Opportunity Motivation-Behavior)
DOI: 10.6084/m9.figshare.20775412.v1
title: DataStatus

description: Table of datasets and associated metadata for reproducing SI Fig 2
DOI: 10.6084/m9.figshare.25757376.v1
title: Supplementary Material for: Self-Recording of Eye Movements in Amyotrophic Lateral Sclerosis (ALS) Patients Using a Smartphone Eye-Tracking App (EyePhone)

description: Introduction: Amyotrophic Lateral Sclerosis (ALS) can affect various eye movements, making eye tracking a potential means for disease monitoring. In this study, we evaluated the feasibility of ALS patients self-recording their eye movements using the "EyePhone", a smartphone eye-tracking application. 
Methods: We prospectively enrolled ten participants and provided them with an iPhone equipped with the EyePhone app and a PowerPoint presentation with step-by-step recording instructions. The goal was for the participants to record their eye movements (saccades and smooth pursuit) without the help of the study team. Afterward, a trained physician administered the same tests using video-oculography (VOG) goggles and asked the participants to complete a questionnaire regarding their self-recording experience. 
Results: All participants successfully completed the self-recording process without assistance from the study team. Questionnaire data indicated that participants viewed self-recording with EyePhone favorably, considering it easy and comfortable. Moreover, 70% indicated that they prefer self-recording to being recorded by VOG goggles.
Conclusion: With proper instruction, ALS patients can effectively use the EyePhone to record their eye movements, potentially even in a home environment. These results demonstrate the potential for smartphone eye-tracking technology as a viable and self-administered tool for monitoring disease progression in ALS, reducing the need for frequent clinic visits.
DOI: 10.17632/26zfwd5fd9
title: Psychological Profiles of Therapeutic and Mastery Exercisers

description: ABSTRACT: Most reasons for exercise can be grouped into health-related ‘therapeutic’ and challenge-related ‘mastery’ categories. Since these motives are not independent of personal needs and expectations, their associated psychological profiles may vary. In this preliminary cross-sectional investigation, we tested the possible differences in life-satisfaction, optimism, pessimism, and perceived stress between therapeutic and mastery exercisers as well as a non-exercising control group. Individuals who exercised for mastery reasons reported superior mental health profile in three out of the four dependent measures while those who exercised for therapeutic reasons did not differ from the non-exercising control group in any of the measures. Further, a composite score of mental health profile, derived from the difference between the sums of positive and negative measures, revealed that mastery exercisers reported the most favorable profile. Their mental health profile emerged to be superior to non-exercisers, but it did not differ statistically significantly from the profile of the therapeutic exercisers. The latter two groups did not differ from each other on this composite measure. These preliminary findings suggest that two very general motives for exercise might be associated with different psychological profiles, which merits future research attention.
DOI: 10.17028/rd.lboro.20296914.v1
title: Supplementary information files for Fast and ballistic contractions involve greater neuromuscular power production in older adults during resistance exercise

description: Supplementary Information files for article<strong> </strong>Fast and ballistic contractions involve greater neuromuscular power production in older adults during resistance exercise <br> Purpose: Neuromuscular power is critical for healthy ageing. Conventional older adult resistance training (RT) guidelines typically recommend lifting slowly (2-s; CONV), whereas fast/explosive contractions performed either non-ballistically (FAST-NB) or ballistically (FAST-B, attempting to throw the load) may involve greater acute power production, and could ultimately provide a greater chronic power adaptation stimulus. To compare the neuromechanics (power, force, velocity, and muscle activation) of different types of concentric isoinertial RT contractions in older adults. Methods: Twelve active older adult males completed three sessions, each randomly assigned to one type of concentric contraction (CONV or FAST-NB or FAST-B). Each session involved lifting a range of loads (20–80%1RM) using an instrumented isoinertial leg press dynamometer that measured power, force, and velocity. Muscle activation was assessed with surface electromyography (sEMG). Results: Peak and mean power were markedly different, according to the concentric contraction explosive intent FAST-B &gt; FAST-NB &gt; CONV, with FAST-B producing substantially more power (+ 49 to 1172%, P ≤ 0.023), force (+ 10 to 136%, P &lt; 0.05) and velocity (+ 55 to 483%, P ≤ 0.025) than CONV and FAST-NB contractions. Knee and hip extensor sEMG were typically higher during FAST-B than CON (all P &lt; 0.02) and FAST-NB (≤ 50%1RM, P ≤ 0.001). Conclusions: FAST-B contractions produced markedly greater power, force, velocity and muscle activation across a range of loads than both CONV or FAST-NB and could provide a more potent RT stimulus for the chronic development of older adult power.
DOI: 10.17632/kb36mjdmsn
title: Dataset for an Interpretable Classification Model for Systemic Lupus Erythematosus 

description: The dataset used in this study is from the Sultan Qaboos University Hospital’s Rheumatology clinic collected by (Al Sawafi S., 2021). It includes 214 Omani patient records from 2006 to 2019 that have met the entry criteria set by EULAR. Entry criteria require a positive Antinuclear Antibodies test (ANA test) after which the rest of the classification additive criteria are applied. Of the 219 patients 138 are diagnosed with SLE, this was also confirmed by a physician on case-by-case bases. The remaining 81 patients have other control diseases. The dataset includes demographic data, clinical data, and laboratory data.
We developed an early detection model for SLE with an interpretation functionality that establishes trust in prediction. SHAP interpretation tool was implemented to explain and justify individual predictions and thereby eliminate any risk of misclassification. Additionally, a minimum set of 13 early predictors achieved the highest scores of 0.95 AUC and 0.89 F-1 metric. With these scores, our model can reasonably predict the presence or absence of SLE. The features comprise demographic and clinical symptoms available at physicians at early stages. It was found that four clinical features had the highest influence on the prediction in addition to the patient’s age. 
Alopecia, renal, ACL, and hemolytic anemia are all indicators of lupus activity at varying rates, combined with the patient’s age and age-onset the model was able to establish a profile of the disease relative to Omanis. It was found that the four critical features are more frequent in other Arab cohorts and the model has the potential to be extended to include those ethnicities.
With such scores, our model can predict with reasonable certainty the presence and absence of SLE. This can alert physicians to investigate further with the help of immunological tests such as antinuclear antibodies test and Anti-dsDNA test. Future work includes training the model to categorize non-SLE patients into “possible-SLE” and “highly unlikely” that can help monitor patients suspected of developing SLE in the future. The symptom frequency also dictates that some features carry more weight in classification than other features, thus Class-Weight classification can be applied against normal classifiers to hopefully obtain better performance.
DOI: 10.6084/m9.figshare.20076107.v1
title: Data for Tidal Harmonic Analysis

description: NOAA tidal level data for 2016-2022 in Delaware Bay
DOI: 10.6084/m9.figshare.21101686.v3
title: Effect of probiotics for regulation of inflammatory response in radiation-induced enteritis

description: <strong>Effect of probiotics for regulation of inflammatory response in radiation-induced enteritis</strong>
DOI: 10.6084/m9.figshare.25273717.v2
title: Test datasets of TSTA.

description: TSTA 是一种基于线程和 SIMD 的梯形成对/多序列比对方法。该数据集用于测试TSTA算法在真实和模拟数据上的速度。
DOI: 10.15468/dl.drxsrb
title: Occurrence Download

description: A dataset containing 3547009 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Fabaceae",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 3547009 records from 1361 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013416-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ppey6w
title: Occurrence Download

description: A dataset containing 908 records in GBIF matching the query:
SELECT
 '608' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude, 0) AS cell, -- NO randomization
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= 66.79314043790278
 AND decimalLatitude &lt;= 72.77152049497572
 AND decimalLongitude &gt;= -53.99976350162573
 AND decimalLongitude &lt;= -35.92015691852831
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND (coordinateUncertaintyInMeters &lt;= 100 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 908 records were derived from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000707-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21223/p3/uzvdw6
title: Replication data for: Qualification of a Plant Disease Simulation Model; performance of the LATEBLIGHT Model for Nir-Eliyahu, Israel, 2000-20001

description: The concept of model qualification, i.e., discovering the domain over which a validated model may be properly used, was illustrated with LATEBLIGHT, a mathematical model that simulates the effect of weather, host growth and resistance, and fungicide use on asexual development and growth of Phytophthora infestans on potato foliage. Lateblight epidemics from Ecuador, Mexico, Israel, and the United States involving 13 potato cultivars (32 epidemics in total) were compared with model predictions using graphical and statistical tests. Fungicides were not applied in any of the epidemics. For the simulations, a host resistance level was assigned to each cultivar based on general categories reported by local investigators. For eight cultivars, the model predictions fit the observed data. For four cultivars, the model predictions overestimated disease, likely due to inaccurate estimates of host resistance. Model predictions were inconsistent for one cultivar and for one location. It was concluded that the domain of applicability of LATEBLIGHT can be extended from the range of conditions in Peru for which it has been previously validated to those observed in this study. A sensitivity analysis showed that, within the range of values observed empirically, LATEBLIGHT is more sensitive to changes in variables related to initial inoculum and to weather than to changes in variables relating to host resistance.
DOI: 10.21223/p3/xd4apa
title: Replication data for: Qualification of a Plant Disease Simulation Model; performance of the LATEBLIGHT Model for Nir-Oz, Israel, 2000-2001

description: The concept of model qualification, i.e., discovering the domain over which a validated model may be properly used, was illustrated with LATEBLIGHT, a mathematical model that simulates the effect of weather, host growth and resistance, and fungicide use on asexual development and growth of Phytophthora infestans on potato foliage. Lateblight epidemics from Ecuador, Mexico, Israel, and the United States involving 13 potato cultivars (32 epidemics in total) were compared with model predictions using graphical and statistical tests. Fungicides were not applied in any of the epidemics. For the simulations, a host resistance level was assigned to each cultivar based on general categories reported by local investigators. For eight cultivars, the model predictions fit the observed data. For four cultivars, the model predictions overestimated disease, likely due to inaccurate estimates of host resistance. Model predictions were inconsistent for one cultivar and for one location. It was concluded that the domain of applicability of LATEBLIGHT can be extended from the range of conditions in Peru for which it has been previously validated to those observed in this study. A sensitivity analysis showed that, within the range of values observed empirically, LATEBLIGHT is more sensitive to changes in variables related to initial inoculum and to weather than to changes in variables relating to host resistance.
DOI: 10.21223/p3/3hyq86
title: Replication data for: Qualification of a Plant Disease Simulation Model; performance of the LATEBLIGHT Model for Sta Catalina CIP, Ecuador, 1999-2000

description: The concept of model qualification, i.e., discovering the domain over which a validated model may be properly used, was illustrated with LATEBLIGHT, a mathematical model that simulates the effect of weather, host growth and resistance, and fungicide use on asexual development and growth of Phytophthora infestans on potato foliage. Lateblight epidemics from Ecuador, Mexico, Israel, and the United States involving 13 potato cultivars (32 epidemics in total) were compared with model predictions using graphical and statistical tests. Fungicides were not applied in any of the epidemics. For the simulations, a host resistance level was assigned to each cultivar based on general categories reported by local investigators. For eight cultivars, the model predictions fit the observed data. For four cultivars, the model predictions overestimated disease, likely due to inaccurate estimates of host resistance. Model predictions were inconsistent for one cultivar and for one location. It was concluded that the domain of applicability of LATEBLIGHT can be extended from the range of conditions in Peru for which it has been previously validated to those observed in this study. A sensitivity analysis showed that, within the range of values observed empirically, LATEBLIGHT is more sensitive to changes in variables related to initial inoculum and to weather than to changes in variables relating to host resistance.
DOI: 10.21223/p3/gtv7y4
title: Replication data for: Qualification of a Plant Disease Simulation Model; performance of the LATEBLIGHT Model for Mivtakhim, Israel, 2000-2001

description: The concept of model qualification, i.e., discovering the domain over which a validated model may be properly used, was illustrated with LATEBLIGHT, a mathematical model that simulates the effect of weather, host growth and resistance, and fungicide use on asexual development and growth of Phytophthora infestans on potato foliage. Lateblight epidemics from Ecuador, Mexico, Israel, and the United States involving 13 potato cultivars (32 epidemics in total) were compared with model predictions using graphical and statistical tests. Fungicides were not applied in any of the epidemics. For the simulations, a host resistance level was assigned to each cultivar based on general categories reported by local investigators. For eight cultivars, the model predictions fit the observed data. For four cultivars, the model predictions overestimated disease, likely due to inaccurate estimates of host resistance. Model predictions were inconsistent for one cultivar and for one location. It was concluded that the domain of applicability of LATEBLIGHT can be extended from the range of conditions in Peru for which it has been previously validated to those observed in this study. A sensitivity analysis showed that, within the range of values observed empirically, LATEBLIGHT is more sensitive to changes in variables related to initial inoculum and to weather than to changes in variables relating to host resistance.