cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/w6cxr8yc7p
title: Boğaziçi University Mouse Dynamics Dataset

description: Mouse dynamics is a hot topic under study in session-based authentication and intrusion detection in privileged access management systems. We contribute to this topic, which develops with the increase of big data capabilities, with a data set that is missing in the field. This data article describes an extensive dataset with free usage mouse dynamics data. This dataset has 7 variables and 24 users with 2550 hours of active usage data. Each user has training data, internal attack test data, and external attack test data. An application in Python programming language that continuously listens to mouse movements and mouse clicks and writes them into a file with a timestamp, foremost window name, and mouse action details, is implemented. Among 24 unique users, we labeled 5 users with the least amount of data as external users since their data would be weak for training purposes and we can test external threat detection. Each user has training data consist of 12 days with the most frequent mouse usage and reminder days of data are used for internal attack test data. This dataset is highly suitable for testing the under-development procedures against the insider threat, remote unauthorized access, and physical access.
DOI: 10.17632/xhfg7zktjp
title: Sears et al 2023

description: Supplemental material.
DOI: 10.6084/m9.figshare.22060481.v1
title: Microcomputed tomography data

description: This dataset contains summaries of the microcomputed tomography data for the cortical bone in the shaft as well as trabecular bone in the distal shaft and condyles. There are also excel sheets for each bone of the data collected from BoneJ. Raw data (microCT images) weren't provided because they are huge files. If you need these files, please fill free to ask me.
DOI: 10.17632/k4v97324c3
title: Surgical treatment in PCOS

description: The aim of this work was to improve the results of infertility treatment in PCOS by optimizing surgical tactics. We analyzed the surgical treatment of infertility in PCOS, its effectiveness was evaluated by changes in the hormonal profile, ultrasound parameters, the frequency of the menstrual cycle recovery, spontaneous and induced pregnancies after the surgical treatment. The study revealed high effectiveness of both methods of surgical treatment (laparoscopic ovarian drilling and laparoscopic ovarian wedge resection) in relation to the frequency of the menstrual cycle recovery, the achievement of pregnancy.
DOI: 10.17632/zsdtztk7mm
title: Specialization and Performance in Private Equity: Evidence from the Hotel Industry [replication package]

description: This zip file contains the replication package for "Specialization and Performance in Private Equity: Evidence from the Hotel Industry" by Christophe Spaenjers and Eva Steiner, to be published in the Journal of Financial Economics. As this project relies on proprietary data from different sources, the data sets included in this package for replication show pseudo values, not any real data. See readme for more information.
DOI: 10.6084/m9.figshare.19236489.v1
title: DATA.pdf

description: research data
DOI: 10.17632/42w6s27d2n
title: 고인용 논문을 발표한 연구

description: 2014-2018년간의 Scopus 등재 논문 기준, 주제분야별로 인용수가 가장 높은 논문을 발표한 연구
DOI: 10.17632/cksmdjw8gy
title: Aloe Vera Diseases Dataset for Classification of Aloe Vera Diseases Using Machine Learning

description: This dataset serves as a valuable resource for researchers and practitioners in the fields of agriculture, machine learning, and computer vision, with a primary focus on the classification of diseases affecting Aloe vera plants. The dataset encompasses three main categories: Background Removed Aloe Vera Disease Dataset, Original Aloe Vera Disease Dataset, and Augmented Aloe Vera Disease Dataset. Each category contains images representing the diverse conditions of Aloe Vera plants, including Fresh, Rot, and Rust. By providing variations such as background removed images, original images, and augmented images, this dataset facilitates robust algorithm development and evaluation. Researchers can leverage these datasets to train and test machine learning models for accurate classification and early detection of Aloe Vera diseases. The dataset aims to accelerate advancements in agricultural technology, crop protection, and sustainable farming practices through innovative applications of computer vision and machine learning. 

A total of 2307 images of Fresh, Rust, and Rot Aloe Vera were collected from a rooftop garden in Jhenaidah and Munshigonj, Bangladesh, between November 2023 and January 2024. Subsequently, 9000 augmented images were generated from these originals using techniques such as flip, rotation, noise, shift, brighten, and zoom, aimed at increasing the dataset size while maintaining an image size of 800x800 pixels.

Folder Structure:
1. Augmented Aloe Vera Disease Dataset:
 Number of datasets: 9000
 Data format : .jpg

2. Background Removed Aloe Vera Disease Dataset:
 Number of datasets: 2450
 Data format : .png

3. Original Aloe Vera Disease Dataset:
 Number of datasets: 2307
 Data format : .jpg
DOI: 10.17632/g8p5xxpcz5
title: LINF_200016600

description: Pre-mRNA-splicing factor 38
Leishmania infantum (strain JPCM5)
DOI: 10.17632/kphrvvgwwz
title: Data for: Length–weight relationships for seven neotropical freshwater fish species endemic to Central America

description: In support of the manuscript by Bagley et al. (2022), this repository provides the raw data length data [standard length (SL), mm] and weight (g) data for determining length–weight relationships for Central American freshwater fishes in our study, as well as the corresponding collections information. The data are provided in a single Excel spreadsheet file named "Bagley_et_al_2022_DataS1.xlsx." Sites shown in Figure 1 of the manuscript correspond directly to localities provided (with latitude and longitude in decimal degrees) in the spreadsheet file in this accession.

REFERENCES
Bagley JC, Breitman MF, Johnson JB (2022) Length–weight relationships for seven neotropical freshwater fish species endemic to Central America. Acta Ichthyologica et Piscatoria.
DOI: 10.17632/y6wbt9snv7
title: Assessing the accuracy of ChatGPT references in head and neck and ENT disciplines

description: Purpose
ChatGPT has gained popularity as a web application since its release in 2022. While artificial intelligence (AI) systems’ potential in scientific writing is widely discussed, their reliability in reviewing literature and providing accurate references remains unexplored. This study examines the reliability of references generated by ChatGPT language models in the Head and Neck field.


Methods
Twenty clinical questions were generated across different Head and Neck disciplines, to prompt ChatGPT versions 3.5 and 4.0 to produce texts on the assigned topics. The generated references were categorized as “true,” “erroneous,” or “inexistent” based on congruence with existing records in scientific databases.


Results
ChatGPT 4.0 outperformed version 3.5 in terms of reference reliability. However, both versions displayed a tendency to provide erroneous/non-existent references.


Conclusions
It is crucial to address this challenge to maintain the reliability of scientific literature. Journals and institutions should establish strategies and good-practice principles in the evolving landscape of AI-assisted scientific writing.
DOI: 10.17632/f395tsv6g7
title: Data for: Developing a Dynamic Energy Budget model to project potential effects of deep-sea mining plumes on the Atlantic deep-sea mussel, Bathymodiolus azoricus

description: 1. Excel file:
All equations and input values used in the DEB model, along with the corresponding outputs, for each of the simulations conducted.
Input and output values replaced in the base EwE model, for each of the scenarios tested.

3. R code:
Complete simulation for sensitivity analysis.
DOI: 10.17632/f7tmmjsc3y
title: Banana Grading

description: Dataset used for the banana grading system using multi-input deep learning model with RGB and Hyperspectral Imaging
DOI: 10.6084/m9.figshare.26074660.v1
title: HiGTS_2001s3

description: HiGTS is a high temporal resolution global gridded dataset of human thermal stress metrics. Derived using climate variables from ERA5-Land and ERA5, the HiGTS consists of hourly gridded maps of Universal Thermal Climate Index (UTCI), Universal Thermal Stress (UTS), and daily Thermal Stress Duration (TSD) at 0.1° × 0.1° spatial resolution over the global land surface from January 1, 2000 to December 31, 2023.HiGTS_2001s3 contains the data from July 1, 2001 to September 30, 2001.
DOI: 10.17632/pc2td87chw
title: Cognition on Neuroplasticity

description: Cognition on Neuroplasticity with mediating effect of Risk Absorption
DOI: 10.17632/ps8grwfy2d
title: Data for: Psychopathy and Impulsivity: the relationship of the Psychopathy Checklist-Revised to different forms of impulsivity

description: Scores from prisoners and patients on the UPPS-P measures of impulsivity and the PCL-R (or SV) measure of psychopathy
DOI: 10.6084/m9.figshare.6796232.v1
title: 16S rRNA sequences

description: 16S rRNA gene high-throughput amplicon sequencing of grapevine rhizosphere samples
DOI: 10.17632/jx32k7hmyb
title: Dataset of Mazovian (Poland) Road Network for Graph Neural Networks

description: This dataset was developed for the project of analyzing the transport network in the Mazowieckie Voivodeship and comprises a wide range of traffic-related information. The data were collected from various sources, including road technical quality and road incident data from the Polish General Directorate for National Roads and Motorways, travel time information from Google Maps, data obtained from reverse geocoding, population density data from the GUS database, and specific weather conditions for roads.

Key Features of the Dataset:

Multidimensional Information: The dataset includes information on the date, days of the week, holidays, time (in minutes), and various temporal parameters (T1 - T24).

Road and Node Identifiers: Each record contains identifiers for the road (roadId), the start node (start_node), and the end node (end_node).

Traffic Factors: It includes key traffic information such as the traffic factor (trafficFactor), midlongitude and midlatitude of the road segment (midLongitude, midLatitude), and details about the number of lanes, road width, presence of two-way traffic (two_ways), and traffic density (density).

Weather Conditions: The dataset accounts for various weather conditions, including heavy rain, partial rain, no rain, partial clouds, heavy clouds, clear sky, storms, and fog.

Prediction Outcomes: Data include results on traffic speed (result_speed) and conditions such as shuttle traffic (result_shuttle), full (result_fullyclosed) and partial (result_partiallyclosed) road closures, and the presence of traffic lights (result_trafficlight).

Data Collection Period:

Traffic data were collected from May 25, 2022, to June 22, 2022, providing a comprehensive view of traffic conditions over a nearly one-month period.
Data Preparation Process:

The collected data were unified and processed to create one large CSV file.
This file was then divided into 384 smaller files, each representing the state of the transport network at a specific moment.
This dataset forms a comprehensive basis for analyzing and forecasting traffic conditions, offering extensive possibilities for use in machine learning models.
DOI: 10.17632/sjfpwph3xw
title: Supplementary Material

description: Venous thromboembolism risk is lower in patients with atopic dermatitis than other immune-mediated inflammatory diseases: A retrospective, observational, comparative cohort study using US claims data
DOI: 10.6084/m9.figshare.15015357.v1
title: Supplementary Material for: Lymphocyte-to-Monocyte Ratio Is a Predictive Biomarker of Response to Treatment with Nivolumab for Gastric Cancer

description: <b><i>Introduction:</i></b> Patients with unresectable or recurrent gastric cancer who have an objective response (OR) to nivolumab monotherapy are expected to have a good long-term prognosis. However, the OR rate for nivolumab treatment is low at 11%, and there is a need for biomarkers to predict the treatment response. This study aimed to analyze the significance of systemic inflammation-related variables and clinicopathologic characteristics as predictive markers of response to nivolumab monotherapy in patients with advanced gastric cancer. <b><i>Methods:</i></b> In this retrospective cohort study, we enrolled 71 consecutive patients who received nivolumab monotherapy for unresectable or recurrent gastric cancer. Receiver operating characteristic curve analysis was performed to determine the cutoff values of systemic inflammation-related variables, predictors of treatment response, and other prognostic factors related to nivolumab therapy. We focused on systemic inflammation-related variables measured before nivolumab induction and 2 weeks after its first administration and performed multivariate analysis to assess whether they could be used as prognostic factors. <b><i>Results:</i></b> Multivariate analysis revealed that a lymphocyte-to-monocyte ratio (LMR) of ≤3.28 after 2 weeks of initial nivolumab treatment (2wLMR) is a statistically significant predictor of treatment response (<i>p</i> = 0.012). The progression-free survival (PFS) rate of patients with liver metastasis was significantly worse than that of the other patients (1-year PFS: 0.0 vs. 24.4%, respectively; <i>p</i> = 0.005). The overall survival (OS) of patients with a low 2wLMR was significantly longer than that in patients with a high 2wLMR (1-year OS: 37.4 vs. 18.9%, respectively; <i>p</i> = 0.022). <b><i>Conclusions:</i></b> Thus, the 2wLMR could be a useful biomarker to predict response to nivolumab treatment and the prognosis of unresectable and recurrent gastric cancer.
DOI: 10.6084/m9.figshare.21587451.v4
title: Data for "Plant C:N ratio predicts community composition changes under N addition in an alpine meadow"

description: Plant functional traits play important roles in determining plant responses to environmental change and further shaping community composition, but the role of plant stoichiometry remains poorly understood in regulating community responses to continually increased nitrogen (N) deposition. Here, we used a five-year manipulative experiment with six N addition rates (N<sub>rate</sub>) to explore how the N response of different plant functional groups links to aboveground plant carbon-to-N ratio in an alpine meadow. We found that functional groups with higher C:N tended to grow better and have greater abundance over increasing N<sub>rate</sub>, yet those with lower C:N were at risk of loss, subsequently mitigating the N-caused decline in community-level plant C:N. This was mainly due to that functional groups with higher C:N not only possessed higher N use efficiency but also had greater competitiveness for aboveground light due to higher plant height. Our results show that the N responses of different herbaceous plants can be well explained by plant C:N. Thus, we suggest the prediction of plant community composition changes under N deposition would be greatly improved by considering this easily measured stoichiometric trait. Here we share our dataset related to our manuscript.
DOI: 10.17632/626cszwvm2
title: Tofacitinib for cutaneous and pulmonary sarcoidosis: a case series

description: Figure 1. 63-year-old patient with severe photo-aggravated cutaneous sarcoidosis at baseline and after 2 months of treatment with oral tofacitinib showing reduction in erythema, induration and extent of skin involvement.
DOI: 10.17632/tg2gpf4jwh
title: Seasonal burden of National Emergency Department visits due to hidradenitis suppurativa

description: Supplementary tables for HS seasonal burden manuscript in JAAD.
DOI: 10.17632/6sxmnmx9wt
title: HCC-GPCR

description: Identification of novel prognostic and systemic treatment sensitivity markers for hepatocellular carcinoma through the analysis of G protein-coupled receptor-related genes
DOI: 10.6084/m9.figshare.1224333.v1
title: Nature of Expertise Fingerprints - Experiment 3

description: Data from Experiment 3 of Thompson, M. B. & Tangen, J. M. (2014). The nature of expertise in fingerprint matching: Experts can do a lot with a little. PLOS ONE. The demographic information of experts has been removed in order to maintain confidentiality.
DOI: 10.17632/nvg4c74thw
title: SORS spectra of COVID-19 Vaccine

description: Spatially Offset Raman Spectra of 45 genuine covid-19 vaccines,  and surrogates for potential and intercepted falsified vaccines . The Raman spectra were collected using a handheld commercial SORS instrument (Resolve, Agilent Technologies, Oxfordshire, UK).
DOI: 10.17632/cgtg4bhrtf
title: Bahasa Madura Corpus Dataset

description: This bilingual corpus is built and organized based on the Bible Translation from Indonesian to Madurese. This corpus contains more than 30,000 sentences from Indonesian - Madurese. The data is collected in text form with .xls and txt formats, using tab separators. We have also supplemented this dataset with the English translation of the Bible.
DOI: 10.17632/t8bxg423yk
title: COVID-19 Twitter Word2Vec Model

description: This is a small Word2Vec Model n-gram (n= 1-3) built from Twitter chatter about COVID-19. The objective of this model is to capture semantic representations of COVID-19-related concepts. We will be updating this dataset over time. Please see the following script if you are having difficulty loading the model: https://bitbucket.org/asarker/lexexp
DOI: 10.17632/tnk42hhjjk
title: Parallel Corpus Dataset of Indonesian and Bengkulu Malay Language

description: This is a parallel corpus dataset in which each sentence has a corresponding pair. This dataset is specifically created to facilitate the use of machine learning in the field of translation. The dataset is meticulously compiled to encompass various contexts and topics, enabling users to expand their understanding of the use of everyday language, language variations, as well as expressions and typical idioms from both languages.

This dataset is independently compiled, with a total of 5261 sentences formed through the collection of online sources for the Indonesian language. Additionally, it utilizes the Malay language dictionary from the Bengkulu library, located in the city of Bengkulu, Bengkulu Province, Indonesia.
DOI: 10.6084/m9.figshare.20657694.v1
title: LC-MS and gene expression.xlsx

description: Metabolites of the fecal supernatants were analyzed at Chalmers Mass Spectrometry Infrastructure (Gothenburg, Sweden) using a non‐targeted liquid chromatography–mass spectrometry (LC‐MS) approach. Briefly, the analyses were carried out using reversed‐phase chromatography and hydrophilic interaction chromatography with both positive and negative electrospray ionization. The samples of each study group were analyzed in separate batches, which included its own quality control samples. The analytical workflow named “notame”, described by Zheng et al, was used to pre‐process the acquired data and included drift correction within and between batches, data imputation was done using the <em>missForest</em> R package and clustering of features was done to remove weak and repeated features(24). Log10 transformation was applied prior between‐batch‐correction to reduce possible batch effects caused by the instrument <br> For gene expression data, a custom RT² PCR Array (Qiagen) was analyzed in a Quantstudio 12K Flex Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) using the RT² qPCR SYBR Green ROX MasterMix (Qiagen). The gene expression custom array comprised 96 genes (supplementary table 1), including 5 housekeeping (HK) genes (GAPDH, HPRT1, RPLP0, ACTB, B2M) and quality 4 controls (positive PCR control, reverse transcription control, genomic DNA control, negative template control). All samples passed the quality controls. Missing values and CT values &gt;38 were set to 38. Genes were excluded from the analysis if &gt;50% of the samples had missing or very high CT values (CT&gt;36). In total, 18 genes were excluded from the Caco-2 cell analysis, and 19 genes were excluded from the colonoid analysis. Normalized values are expressed as 2-(CT Target gene-mean CT of HK genes)
DOI: 10.6084/m9.figshare.27087931.v1
title: Coastal SES in CCA_2nd revision.pdf

description: A systematic literature review was conducted on papers studying coastal socio-ecological systems (SES) in adaptation to climate change, with the aim of supporting sustainable coastal management and contributing to achieving the UN SDGs.
DOI: 10.17632/k3b363f3vz
title: Composite Dataset of Lumbar Spine Mid-Sagittal Images with Annotations and Clinically Relevant Spinal Measurements

description: This composite dataset comprising of mid-sagittal views of lumbar spine is composed of images of lumbar spine with ground truth images duly labelled/annotated as well the spinal measurements. The purpose of creating this dataset was to establish a strong correlation in the images with the spinal measurements being clinically relevant. Presently, these measurements are being taken either completely through manual methods or by the use of computer assisted tools. The spinal measurements are clinically significant for a spinal surgeon before suggesting or shortlisting suitable surgical intervention procedure. Traditionally, the spinal surgeon evaluates the condition of the patient before surgical procedure in order to ascertain the usefulness of the adopted procedure. It also helps the surgeon in establishing a relation regarding effectiveness of the procedure adopted. For example, in case of spinal fusion procedure, will the fusion procedure be able to restore the spinal balance is a question for which the answered is obtained through making relevant spinal measurements, including lumbar lordotic curve angle, both segmental and for whole lumbar spine, lumbosacral angle, spinal heights, dimensions of vertebral bodies etc. The Composite Dataset is acquired in following steps:- 1. Exporting mid-sagittal view from the MRI dataset. (Originally taken from Sudirman, Sud; Al Kafri, Ala; natalia, friska; Meidia, Hira; Afriliana, Nunik; Al-Rashdan, Wasfi; Bashtawi, Mohammad; Al-Jumaily, Mohammed (2019), “Label Image Ground Truth Data for Lumbar Spine MRI Dataset”, Mendeley Data, V2, doi: 10.17632/zbf6b4pttk.2). The original dataset comprises of axial views with annotations however, to determine the efficacy of spinal deformities and analyzing spinal balance sagittal views are used instead. 2. Manual labelling of lumbar vertebral bodies from L1 to L5 and first sacrum bone. Total 6 regions were labelled in consultation with expert radiologists followed by validation by expert spinal surgeon. 3. Performing fully automatic spinal measurements, including, vertebral bodies identification and labelling, lumbar height, lumbosacral angle, lumbar lordotic angle, estimation of spinal curve, intervertebral body dimensions, vertebral body dimensions. All the angular measurements are in degrees, whereas the distance measurements are in millimeters. A total of 514 images and annotations with spinal measurements can be downloaded with request to please cite out work in your research.