cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/kf3cwknx4d.1
title: Legume: A free implementation of the guided-mode expansion method for photonic crystal slabs

description: We describe legume, a free electromagnetic solver that implements the guided-mode expansion method for patterned multilayer waveguides, or photonic crystal slabs. legume has a built-in tool for automatic differentiation, which makes it suitable for the inverse design of photonic crystal structures with desired physical properties. Compared to a previous version of the method (M. Minkov et al., 2020 [12]), here we introduce several new features of the code, we discuss additional technical aspects of the method and its numerical implementation. The novel features that are treated in this paper include: (i) the separation of modes according to their mirror symmetry with respect to a vertical symmetry plane of the photonic structure, (ii) the problem of polarization mixing in coupling to far-field radiation modes, and (iii) the description of active two-dimensional layers through a suitably formulated radiation-matter coupling Hamiltonian, allowing to describe the physics of both weakly and strongly coupled exciton-photon modes, the latter leading to photonic crystal polariton eigenmodes. Detailed and direct comparisons with rigorous coupled-wave analysis simulations are used to test the accuracy of the method and the numerical efficiency of the code. These newly added features of the legume code significantly increase the prospective applications of guided-mode expansion, making it a very practical and versatile tool enabling the design of advanced photonic structures and the description of radiation-matter interaction.
DOI: 10.17632/bxfdtv7yb8.1
title: Smart Agriculture: Automated Phytomonitoring Data for Machine Learning

description: The dataset is an array of data that includes:
1. Vegetation indices are indicators calculated as a result of operations with different spectral ranges (channels) and related to plant parameters in a given image pixel.
- Infrared indices: NDVI and IPVI;
- Normalized difference: RVI;
- Global Environmental Monitoring Index: GEMI.
2. Environmental indicators 
- Temperature;
- Pressure;
- Humidity;
- Illumination.
The values of the indicators were obtained by means of automated phytomonitoring on a "smart" vertical farm of the Institute of Scientific Communications (Volgograd, Russia), which is an experimental scientific platform. The dataset time frame covers the period from October 4, 2022 (12:00) to October 10, 2022 (12:35). Data collection was carried out using the patented sensor sensors “Photon”. The indicators in the dataset are given in Russian and English.

Описание на русском языке:
Датасет представляет собой массив данных, в который включены:
1. Вегетационные индексы – это показатели, рассчитываемые в результате операций с разными спектральными диапазонами (каналами) и имеющие отношение к параметрам растения в данном пикселе снимка.
- Инфракрасные индексы: NDVI и IPVI;
- Нормализованный разностный: RVI;
- Индекс глобального мониторинга окружающей среды: GEMI.
2. Показатели окружающей среды:
- Температура;
- Давление;
- Влажность;
- Освещенность.
Значения показателей получены посредством проведения автоматизированного фитомониторинга на «умной» вертикальной ферме Института научных коммуникаций (Волгоград, Россия), являющейся экспериментальной научной площадкой. Временные рамки датасета охватывают период с 4 октября 2022 г. (12:00) до 10 октября 2022 г. (12:35). Сбор данных осуществлен с помощью запатентованных сенсорных датчиков «Фотон». Показатели в датасете приведены на русском и английском языке.
DOI: 10.17632/z6grbpxkc6.1
title: Volatility Index China

description: Data and code for the volatility index China project
DOI: 10.17632/r984znfbkz.1
title: Dermatologic visits in the emergency department before and after the Affordable Care Act 

description: Supplemental Methods 
Supplemental Table 1 & 2
DOI: 10.17632/63zm778szb.3
title: ECG signals (744 fragments)

description: For research purposes, the ECG signals were obtained from the PhysioNet service (http://www.physionet.org) from the MIT-BIH Arrhythmia database. The created database with ECG signals is described below. 1) The ECG signals were from 29 patients: 15 female (age: 23-89) and 14 male (age: 32-89). 2) The ECG signals contained 17 classes: normal sinus rhythm, pacemaker rhythm, and 15 types of cardiac dysfunctions (for each of which at least 10 signal fragments were collected). 3) All ECG signals were recorded at a sampling frequency of 360 [Hz] and a gain of 200 [adu / mV]. 4) For the analysis, 744, 10-second (3600 samples) fragments of the ECG signal (not overlapping) were randomly selected. 5) Only signals derived from one lead, the MLII, were used. 6) Data are in mat format (Matlab).
DOI: 10.17632/8pn3hg99t4.2
title: Face Mask Wearing Image Dataset: Correct vs. Incorrect Usage

description: The Face Mask Wearing Image Dataset is a comprehensive collection of images focused on different types of face masks and their usage. This dataset has been meticulously organized and divided into two main folders: "Correct" and "Incorrect," representing instances of face masks being worn properly and improperly, respectively. Correct: This folder contains images of individuals wearing face masks correctly. It comprises four subfolders, each representing a specific type of face mask: Bandana: Images of individuals wearing bandana-style face masks correctly. Cotton: Images of individuals wearing cloth or cotton face masks correctly. N95: Images of individuals wearing N95 respirators correctly. Surgical: Images of individuals wearing surgical masks correctly. Incorrect: This folder contains images of individuals wearing face masks improperly. Like the "Correct" folder, it also comprises four subfolders corresponding to the different types of face masks: Bandana: Images of individuals wearing bandana-style face masks incorrectly. Cotton: Images of individuals wearing cloth or cotton face masks incorrectly. N95: Images of individuals wearing N95 respirators incorrectly. Surgical: Images of individuals wearing surgical masks incorrectly. Within each of the above subfolders, there are three additional subfolders based on gender: Child: Images of children wearing the specific type of face mask (correctly or incorrectly). Male: Images of males wearing the specific type of face mask (correctly or incorrectly). Female: Images of females wearing the specific type of face mask (correctly or incorrectly). The dataset is designed to cover a diverse range of scenarios and variations in face mask usage across different mask types, age groups, and genders. Total Images: The dataset contains a total of 24,916 images. Usage: The Face Mask Wearing Image Dataset can be used for various research purposes, such as developing and evaluating machine learning algorithms for face mask detection and classification. Researchers can utilize this dataset to train models that can identify and differentiate between correct and incorrect face mask usage, contributing to public health initiatives, and promoting proper mask-wearing behavior.
DOI: 10.17632/4wyfmbxz4d.2
title: Questionnaire for Entrepreneurship Education, Entrepreneurial Self-Efficacy and Entrepreneurial intentions

description: All the items in the questionnaire were adapted from several previous research
DOI: 10.17632/d4fsbn8nzr.1
title: AI of AI in EIA - supplementary data

description: This data set includes output from ChatGPT4 based on a query 14 August 2023. The questions asked are in the dataset.
DOI: 10.17632/dbymbhhpk9.1
title: American Sign Language (ASL) Fingerspelling dataset for Myo Sensor

description: This is the dataset used in the following publication. Please cite this publication if use this dataset: This work was published on the 2017 ACM IUI . @inproceedings{paudyal2016sceptre, title={Sceptre: a pervasive, non-invasive, and programmable gesture recognition technology}, author={Paudyal, Prajwal and Banerjee, Ayan and Gupta, Sandeep KS}, booktitle={Proceedings of the 21st International Conference on Intelligent User Interfaces}, pages={282--293}, year={2016}, organization={ACM} } @inproceedings{paudyal2017dyfav, title={Dyfav: Dynamic feature selection and voting for real-time recognition of fingerspelled alphabet using wearables}, author={Paudyal, Prajwal and Lee, Junghyo and Banerjee, Ayan and Gupta, Sandeep KS}, booktitle={Proceedings of the 22nd International Conference on Intelligent User Interfaces}, pages={457--467}, year={2017}, organization={ACM} } 9 users wore the Myo Armband and data was collected for 5s. for each letter of the alphabet. The first 8 columns contain data for the 8 EMG pods, the next 3 are for Accelerometer, the next 3 are for Gyroscope and the final 3are for Orientation (Roll, Pitch and Yaw)
DOI: 10.17632/sgdn2s5yfc.2
title: One-Year Safety and Efficacy of Tapinarof Cream for the Treatment of Plaque Psoriasis: Results from the PSOARING 3 Trial

description: Supplementary material for article entitled "One-Year Safety and Efficacy of Tapinarof Cream for the Treatment of Plaque Psoriasis: Results from the PSOARING 3 Trial". Includes Supplemental Tables 1-4 and Supplemental Figures 1-5.
DOI: 10.17632/x9wkrghz23.2
title: Brexit Tweets from the morning of it's announcement

description: To further our understanding of public reaction to political movement via social media, this dataset provides 17998 unfiltered tweets taken on the morning that Brexit was announced. This dataset contains metadata such as geolocation as an independent variable, to allow for rigorous qualitative investigation to be used. Additional tweets from trending topics were also taken at the same time provide context on trending themes at the time: - Scotland - Jeramy Corbyn - Nichola Sturgeon - David Cameron - EURefResults - Euromillions - Borris Data was captured with NCapture from QSR.
DOI: 10.17632/m53vz6b7fx.1
title: CP-AnemiC (A Conjunctival Pallor) Dataset from Ghana

description: Licensed biomedical scientists were given a proficiency training at the Centre for Research in Applied Biology, the University of Energy and Natural Resources, Ghana on how to capture conjunctival images from children aged 6-59 months presenting to assigned healthcare facilities within the stated period using electronic instruments (Kobo Collect v2021.2.4, Massachusetts, USA) deployed on mobile tablets (Samsung Galaxy Tab 7A, Samsung, Vietnam). The system consisted of a form to capture biodata of patients (Hb levels, age, gender), and a remark based on the Hb Value obtained during laboratory assessment, and thereafter took a picture of the image of the conjunctiva of the eyes to upload to the database which allows for easy availability and accessibility. To capture the conjunctiva, the lower eyelid was gently pushed back with the thumb with the aid of the index finger. All images were taken by laboratory personnel in ambient natural light with a standard camera of 12MP image resolution mounted on an electronic tablet.
Furthermore, the cameras' spotlights were turned off when capturing the photographs to prevent excessive shine effects created by the picture quality, that is to eradicate ambient light, which dramatically influences detection or classification by the models. This method is a great technique to remove the effect of ambient light on photographs in datasets. The ROI of the conjunctiva of the eyes was extracted after the application of the triangle thresholding algorithm, in combination with the entropy grayscale image algorithm.
The images (dataset) were taken from 10 hospitals situated in Ghana.
DOI: 10.17632/jxmfrvhpyz.2
title: flower images bulk

description: Bulk images of five types of flowers. Images are not separated by flower types. Images are all in one directory. a CSV file is provided for matching image file name with label. Original images source: https://storage.googleapis.com/download.tensorflow.org/example_images/flower_photos.tgz 10 images of each class are removed and put in test set.
DOI: 10.17632/g2vz7gsb64.1
title: Bist_dataset

description: Bist stock data from 1997 - 2021
DOI: 10.17632/24tw36gbcd.1
title: Expansion of Tregs and prevention of pathological neuroinflammation following local delivery of IL2

description: Supplementary Resource 1. High resolution Treg localization in coronal sections of wildtype and αCamKIIIL2 mice. Healthy perfused mouse brains from wildtype and αCamKIIIL2 mice were compared by immunofluorescent confocal imaging. CD4 (green), Foxp3 (red), laminin α4 (vascular basement membrane, white) and DAPI (blue). Left, wildtype mouse. Right, αCamKIIIL2 mouse. High resolution allows zooming and panning for localization of Tregs across the entire coronal section. 

Supplementary Resource 2. Code for single-cell RNA-seq analysis for wildtype vs αCamKIIIL2 mice. Code is provided in .pdf and .Rmd formats. 

Supplementary Resource 3. Code for single-cell RNA-seq analysis for PHP.GFAP-GFP- vs PHP.GFAP-IL2-treated mice. Code is provided in .pdf and .Rmd formats.
DOI: 10.17632/5cvszt4s3f.1
title: Actual operation data of electric vehicles form the NSMC-EV in Beijing

description: Actual operation data of electric vehicles form the National Electric Vehicle Service and Management Center (NSMC-EV) in Beijing, China.
DOI: 10.17632/mhk9g942sr.1
title: FTIR & PL raw data

description: In this data base you will find the original data used to construct the FTIR and PL spectra at the first and second measurements, all graphs were created in OriginPro 2021 software.
DOI: 10.17632/jt22782wjh.1
title: SpectroPhon DBM Subject Data

description: The data table [hydrometer (subject no ID).xlsx] lists raw data from 240 volunteer human subjects acquired during a 90-minute physical activity regimen. Measured included a standard based on change in body mass (water mass loss) corrected for water consumed during the test compared against two photoplethysmographic devices assessing perspiration volume.
DOI: 10.17632/t78b36cwdr.1
title: Dataset: Number of tourists visit

description: Number of Visits by International Tourists to Indonesia by Nationality in 2020 and 2021
DOI: 10.17632/mnhn6xvbrg.1
title: Pavement Condition Index (PCI) Data for 5,271 Urban Roads in León, Guanajuato, Mexico

description: The database consists of 5,271 urban roads evaluated in the City of Léon, Guanajuato, Mexico; it was proportionate by the General Directorate of Public Works of the Municipality of León. This sample includes roads with low, medium, and high traffic levels. The evaluation consisted of determining the type, quantity, and severity of each failure found, following the criteria defined by the Pavement Condition Index (PCI) method established by the United States Corps of Engineers. Seventeen types of damage were analyzed out of the 19 considered by the original method. The reason why only 17 damages were evaluated is that the “Crossing Railroad” is not in charge of the government of Mexico but instead of companies that have a concession for said infrastructure; likewise, the “Freezing” has not been carried out either evaluated, because the minimum temperatures do not reach a level of freezing.

The original PCI method requires obtaining each damage and its severity level, which is measured at three different levels: light, moderate, and severe. Once the data is obtained, the PCI is calculated. For our case, it was decided to add the densities or percentages of the three levels of severity for each damage so that a single percentage of total damage is obtained for each type of failure. However, it should be noted that the PCI was calculated according to the original methodology, considering the three levels of severity corresponding to each type of damage found.

Therefore, the database presented considers 17 damages with a single level of severity, which was determined as the sum of the densities of the three levels considered by the original method; likewise, the PCI shown in the database also corresponds to that calculated with the original method, considering the three levels of severity.

Please read the readme.txt file to find the description of the variables.
DOI: 10.17632/kz5kynyh2c.1
title: Teaching English to Speakers of Other Languages Research Dataset (1977-2020)

description: The Teaching English to Speakers of Other Languages research and publication dataset, which was indexed by Scopus from 1977 to 2020. 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/cphpc3hfmp.2
title: A diverse hidradenitis suppurativa cohort: a retrospective cross-sectional study of 13,130 patients from a large US healthcare system database from 1995-2022 --Supplemental Information

description: Supplemental Information
DOI: 10.17632/vp47g5hfc8.1
title: Open-access database of photovoltaics building integration parameters for different climate zones.

description: An open access database of BIPV results (70 parameters grouped in ten categories) for 127 cities categorized in four zones of cold (low GHI), moderate (medium GHI), warm (high GHI) and hot (very high GHI) solar irradiation conditions.
DOI: 10.17632/zddtpgzv63.2
title: Liquid based cytology pap smear images for multi-class diagnosis of cervical cancer

description: Hospital-based data collected from the real-world clinical setup is very important in medical research. While a publicly available benchmark dataset provides a base for the development of new algorithms and comparison of results, it is important that the developed algorithm works with as much accuracy as possible in the regional context. Hence, improvement in modules may be required for regional adaptation while keeping global standards within sight. 6 As such a total
DOI: 10.17632/zx8pfhdtnb.3
title: Mechanical faults in rotating machinery dataset (normal, unbalance, misalignment, looseness)

description: If you use this dataset, please cite: Lucas Costa Brito, Gian Antonio Susto, Jorge Nei Brito, Marcus Antonio Viana Duarte. Fault Diagnosis using eXplainable AI: A transfer learning-based approach for rotating machinery exploiting augmented synthetic data. Expert Systems with Applications 232(4):120860. DOI: 10.1016/j.eswa.2023.120860

The dataset was developed aiming to address classic faults in rotating machines such as: unbalance, misalignment and mechanical looseness, in addition to the normal operating condition. The faults were introduced on a test bench, being: motor, frequency inverter, bearing house, two bearings, two pulleys, belt and rotor (disc).

20 tests were performed, 5 for each condition (normal, unbalance, misaligment and looseness). Each test consists of 4 sets of 420 signals collected continuously, each file consisting of 25,000 points with the sampling rate set at 25 kHz (420 signals per accelerometer). Resulting in the end of all tests, in a total of 8400 signals per accelerometer. The sequence of tests was randomly defined. Before starting any test, the bench was dismantled and returned to normal operating condition, to later introduce the fault. The experimental procedure allows variations to occur, making the tests closer to industrial reality. 

Each file has (4, 25000), where 4 represents the position of the accelerometers, and 25000 the number of points. The accelerometers were positioned in such a way that:
1 - Vertical side of the coupling (pulley)
2 - Horizontal side of the coupling (pulley)
3 - Vertical side opposite the coupling (disk)
4 - Horizontal side opposite the coupling (disk)

The sequence of tests and operating conditions are:
- Test 01: Normal Condition 
- Test 02: Misalignment 
- Test 03: Normal Condition 
- Test 04: Unbalance
- Test 05: Mechanical Looseness
- Test 06: Normal Condition 
- Test 07: Unbalance
- Test 08: Mechanical Looseness
- Test 09: Normal Condition 
- Test 10: Misalignment
- Test 11: Misalignment
- Test 12: Mechanical Looseness
- Test 13: Misalignment
- Test 14: Mechanical Looseness
- Test 15: Unbalance
- Test 16: Misalignment
- Test 17: Normal Condition 
- Test 18: Unbalance
- Test 19: Mechanical Looseness
- Test 20: Unbalance
DOI: 10.17632/2y752t39yn.1
title: Guangzhou dataset

description: Archived here are the observation- and emission-based model inputs as well as the MCM box model output discussed in the paper: Zhang, Y., Xue, L., Carter, W.P.L., Pei, C., Chen, T., Mu, J., Wang, Y., Zhang, Q., and Wang, W.: Development of Ozone Reactivity Scales for Volatile Organic Compounds in a Chinese Megacity, Atmospheric Chemistry and Physics., in revirw, 2021
DOI: 10.17632/34gffrm87w.1
title: Insufflated Volumes and Electrical Impedance for Cardiac Arrest Resuscitations

description: This dataset contains detailed records of inhaled and exhaled volumes as well as transthoracic impedance, collected during out-of-hospital cardiac arrests (OHCA). The data are grouped by interventions (ie OHCA), with each intervention folder containing both ventilation volume data and transthoracic impedance signals. Each folder corresponds to a unique intervention.

The purpose of this dataset is to provide transthoracic impedance signals and ventilation volumes that can be registered to better interpret these signals. This registration could provide valuable insights into the effectiveness of resuscitation techniques and the physiological response of patients.