cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/mprjsnr6mp.1
title: Database_Experimental Results_MQI

description: The work herein presented consists of a systematic review of experimental campaigns addressing the assessment of two-leaf stone masonry walls’ mechanical properties. Based on the guidelines provided by Eurocode 8 - part 3 and Italian Code (Table C8.5.1, Circolare n. 7 - 21/01/2019), six different stone masonry types have been defined, namely: Masonry Type 1 (Irregular stone masonry) Masonry Type 2 (Roughly cut stones with wythes of irregular thickness) Masonry Type 3 (Uncut stonework with good texture) Masonry Type 4 (Masonry of irregular soft stone blocks) Masonry Type 5 (Regular masonry of soft stone blocks) Masonry Type 6 (Squared stone masonry) Experimental data collected for the construction of the database refers to the following mechanical parameters: Young’s Modulus (E), Shear Modulus (G), Compressive Strength (fm) and Shear Strength (τ0). Moreover, the data collected corresponds to experimental results resulting from the following testing procedures: Sonic Testing (ST), Flat-Jacks Tests (FJ), Compression Tests (CT), Diagonal-Compression (DC) and Shear-Compression Tests (SC). The comprehensive literature search was carried out on 5 electronic indexing databases: Scopus, Science Direct (SCD), Web of Knowledge (WOK), Civil Engineering Database (ASCE), and MADA RELUIS Database [28]. The research includes papers published between 1960 and May 2020.
DOI: 10.17632/fr7zvy8j5s.1
title: Pulmonary (Lungs)  Sound

description: Data is collected and ground truth classification are performed by Fortis Hospital, Vasant Kunj, New Delhi, India. The pulmonary sound dataset is arranged in two sets: a normal set (11.28%) representing recordings obtained from healthy subjects and an abnormal set (88.72%) containing recordings from pulmonary patients. The lung sound was recorded with an e-stethoscope connected to a laptop via an amplifier. This setup contains e-stethoscope having a chest piece which is contacted to subject having a microphone to record signal (sampling rate 44,100 Hz) connected to a signal amplifier. The signal amplifier kit can specifically amplifies the sound range (70–2000 Hz) for - lung sounds (having amplifier controller, frequency con- troller) connected to earpiece (for listening live recordings) and laptop. A laptop is used to record the signal where the E-stethoscope is connected using an audio input. The dataset contains audio samples which are in a.wav audio format having a single channel with 16 bit per sample, 44,100 Hz sampling rate and 705kbps Bitrate. Each file is 10 s long. 
The data can be used for research purpose only. It is not for commercial purpose. 
Anyone using this data for any Publication need to cite the article: 
Baghel, N., Nangia, V. & Dutta, M.K. ALSD-Net: Automatic lung sounds diagnosis network from pulmonary signals. Neural Comput & Applic 33, 17103–17118 (2021). https://doi.org/10.1007/s00521-021-06302-1
DOI: 10.17632/nx9xbs4rgx.2
title: Artificial Mercosur License Plates

description: In 2018, a new Mercosur license plate standard was published, unifing the identification of vehicles and replacing the present license plate standards of five South America countries. In this new scenario, automatic license plate recognition (ALPR) systems built upon supervised learning algorithms could not be trained due to the lack of available data in real scenarios. So, in order to create a dataset without real samples of the new license plates standard, enabling the trainment of these models, a Mercosur license plate generator was developed to generate artificial license plates images with shadow, occlusion and other variations to mimetize real conditions, and a embeding system with license plate detection (LPD) that detects old 3-letter license plates in images of real scenarios and overwrite it with an artificially generated license plates. The dataset contains images of real scenarios where 3-letter license plates were detected using YOLOv3 (http://arxiv.org/abs/1804.02767) and overwritten by artificially generated images of the new mercosur license plates. It is organized in two folders: images - containing the images (JPEG) of the dataset; and labels - containing text files with the class identification number and the coordinates of the detected license plates in the image, following the Yolo_mark annotation specification (https://github.com/AlexeyAB/darknet#how-to-train-to-detect-your-custom-objects). The images are separated in five classes, identified by a prefix in the filename: 1) monitoring_system_ - 2925 images acquired by a license plate detection model applied in a public videomonitoring system; 2) parking_lot1_ - 566 images of cars in a parking lot acquired using a smartphone camera; 3) parking_lot2_ containing 23 images of the same as parking_lot1_ but acquired using a tablet camera; 4) parking_lot3_ 11 images same as parking_lot1_ but acquired using a different smartphone model; and 5) cropped_parking_lot containing 315 images cropped in the license plate area from parking_lot_ images; Also, there is a CSV file listing all license plates detected in all images, organized in seven columns: image, label, class, x_center, y_center, width and height. The image column is the filename of the image containing the license plate, label is the filename of its recpective annotation, class is the class of the object (in this case, always zero, the index of the license plate object), and x_center, y_center, width and height, the coordinates of the rectangle of the set of pixels representing the license plate in the image, following YOLO annotation standard.
DOI: 10.17632/3ryrpz224h.2
title: Care Arrangements of Frail Older People Living Alone in Italy - IN-AGE Study

description: Data come from the study "Inclusive ageing in place” (IN-AGE), funded by Fondazione Cariplo (Italy), Grant N. 2017-0941, and regarding a purposive sample of 120 individuals aged 65 years and over (males and females). It was a cross-sectional qualitative survey which in 2019 was conducted by face-to-face interviews to frail older people, with physical limitations but without cognitive impairment, and living at home, alone or with a private personal care assistant (PCA), in three Italian Regions (Lombardy, Marche, and Calabria). Both peripheral/degraded areas of urban sites and fragile rural locations were included, with regard to social and material vulnerability aspects (e.g. high presence of older people, high level of unemployment, low level of education, poor provision of services). The dataset regards in particular available care arrangements of older people to perform daily living activities, especially in the presence of functional limitations. In this respect, both informal (e.g. family members) and formal care (e.g. public services) were explored. A semi-structured interview was used. The issues were explored mainly with ad hoc open questions for the survey, adapted from previous studies. The difficulties in carrying out the activities of daily life were detected by administering the ADLs and IADLs scales. 
In order to provide the quantitative analysis (by means of Microsoft Excel 2019), qualitative dimensions were codified, in terms of absence/presence/frequency of the investigated aspects (e.g. yes/no help from the family, PCA, services, friends/neighbours; daily and weekly help). Some more complex quantitative classifications were also used in the analysis. Regarding the level of physical limitations, four grades were provided, corresponding in turn to four levels of functional frailty (mild, moderate, high, very high). Moreover, the following were elaborated: share of family help on total help (up to 50% and over 50% of total help); number of living close by family members who help (who live in the same urban city/rural municipality of respondents); and monthly income brackets. The verbatim transcriptions of the qualitative interviews are not publicly available due to privacy issues. 
Results showed that the support comes mainly still from family members, albeit with decreasing availability, but also from domestic home help (DHH) and PCAs, friends/neighbours, and less from public services. Frequency of help, and living proximity of family members who give support, play a key role. Territorial differentiation emerged, with a worst public service context in the South. It seems overall necessary to improve home services, also through a real formal and informal integration.
The dataset is provided in open format (Microsoft Excel) and includes the following: a “numeric” dataset regarding the unlabelled dimensions used for statistics elaboration; a codebook with the complete variables list and variables labels we used.
DOI: 10.17632/7j9bv9vwsx.3
title: MLRSNet: A Multi-label High Spatial Resolution Remote Sensing Dataset for Semantic Scene Understanding

description: MLRSNet provides different perspectives of the world captured from satellites. That is, it is composed of high spatial resolution optical satellite images. MLRSNet contains 109,161 remote sensing images that are annotated into 46 categories, and the number of sample images in a category varies from 1,500 to 3,000. The images have a fixed size of 256×256 pixels with various pixel resolutions (~10m to 0.1m). Moreover, each image in the dataset is tagged with several of 60 predefined class labels, and the number of labels associated with each image varies from 1 to 13. The dataset can be used for multi-label based image classification, multi-label based image retrieval, and image segmentation. The Dataset includes: 1. Images folder: 46 categories, 109,161 high-spatial resolution remote sensing images. 2. Labels folders: each category has a .csv file. 3. Categories_names. xlsx: Sheet1 lists the names of 46 categories, and the Sheet2 shows the associated multi-label to each category.
DOI: 10.17632/2m6yxvr23h.3
title: Malnutrition and outcomes in cardiac surgery

description: The aim of this study was to investigate the relationship between malnutrition and long-term survival in patients that underwent cardiopulmonary bypass (CPB). The principal question was to assess how the malnutrition contributes to the risk of postoperative mortality in cardiac patients. Materials and Methods. This study analyzed the long-term survival data of mixed cohort of 1187 cardiac patients previously enrolled in a prospective observational study of nutritional screening in cardiac surgery (NCT01366807). Patients were screened using four nutritional screening tools: Nutritional Risk Screening 2002 (NRS-2002), the Malnutrition Universal Screening Tool (MUST), the Mini Nutritional Assessment (MNA), and the Short Nutritional Assessment Questionnaire (SNAQ), Nutritional status was assessed using the Subjective Global Assessment. In total, 449 (37.8%) patients were lost to follow-up after hospitalization, while for the remaining participants, the overall 8-year survival was 68% [95% confidence interval (CI), 59–76] and 77% [95% CI, 73–80] (log-rank, p=0.12) in patients with and without malnutrition risk, respectively. Statistically significant differences in survival were found during the 3-year follow-up of patients with HVD: 83% [95% CI, 74–92] with malnutrition vs. 93% [95% CI, 90–96] without malnutrition (log-rank, p=0.03). The final multivariate Cox regression model revealed logistic EuroSCORE (hazard ratio (HR) 1.337, 95% CI 1.110–1.612), CPB time&lt;110.5 minutes (HR 0.463, 95% CI 0.255–0.842), preoperative albumin (HR 0.799, 95% CI 0.691–0.924), and C-reactive protein (HR 1.106, 95% CI 1.018–1.202) as independent predictors of 3-year survival: In conclusion, preoperative malnutrition is not associated with 8-year mortality in mixed cardiac surgery cohort. However, it may be associated with a worse 3-year outcomes in patients with HVD. These data are the first reflecting the relationship between malnutrition and long term outcome among cardiac patients and may be useful for researchers, conducting studies on nutrition in cardiology for sample size calculation and estimation of clinically relevant end points in future.
DOI: 10.17632/j2hmt7k9fh.1
title: RNA-seq analysis of in vitro polarised human monocyte-derived macrophage transcriptomes
DOI: 10.17632/p2mhd6kz94.1
title: Dataset webometrics 2023

description: Dataset webometrics 2023 with the analysis of the websites of Latin American universities.
DOI: 10.17632/7fg8835b4g.1
title: Dataset Global Fashion Brands - Brand Equity, Ranking, Growth Rate,  COO (2001-2021)

description: Fashion brands appeared in Interbrand’s Top 100 Global Brand list from 2001 to 2021 are included in this dataset. Following fields were extracted from the Interbrand’s annual reports having string values. 	
•	Brand Name 
•	Country of Origin 
•	Region of origin (America, Europe)
•	Industry Sector (Fashion)
•	Industry Sub-sector (Apparel, Cosmetics, Luxury and Sportswear)

Following fields are extracted for each year (2001-2021) having numeric values. 	
•	Brand Ranking
•	Brand Equity (USD billion)
•	Growth in Brand Equity (%)
DOI: 10.17632/jp96vj3frz.1
title: Nano-PCM Intelligence Classification Dataset for Energy Storage and Heat Transfer Analysis using Deep Neural Networks

description: Big data images for free convection flow and heat transfer of nano-encapsulated phase change (NePCM) suspensions. 
The dataset contains 3290 images of temperature fields for natural convection of nano-encapsulated phase change material suspensions in an enclosure. The provides codes try to classify the model parameters using the available images of temperature field. The codes have been provided in Phyton and Matlab languages. 

A sample of the dataset has one normalized temperature image between 0 and 1 as input and four output parameters consisting of Fi, TTF, Ra, and Ste. It has 3290 samples of data. This dataset is derived from the following dataset and article:
Edalatifar, Mohammad; Ghalambaz, Mohammad; Tavakoli, Mohammad Bagher; Setoudeh, Farbod (2023), “Deep Learning Approach to Natural Convection Heat Transfer in a Cavity: A Simulation Dataset for Nano-Encapsulated Phase Change Material Suspensions”, Mendeley Data, V1, doi: 10.17632/j5f6r56jnb.1

M. Edalatifar, M. B. Tavakoli and F. Setoudeh, "A Deep Learning Approach to Predict the Flow Field and Thermal ‎Patterns of Nonencapsulated Phase Change Materials ‎Suspensions in an Enclosure‎", Journal of Applied and Computational Mechanics 2022, Vol. 8, Issue 4, Pages 1270-1278, DOI: 10.22055/jacm.2021.37805.3092.
https://jacm.scu.ac.ir/article_16903.html

The related paper of this dataset has been published as:
Mohammad Ghalambaz, Mohammad Edalatifar, Sara Moradi Maryamnegari, and Mikhail Sheremet, An intelligence parameter classification approach for energy storage and natural convection and heat transfer of nano-encapsulated phase change material: Deep neural networks, Neural Computing and Applications, https://doi.org/10.1007/s00521-023-08708-5
DOI: 10.17632/s973cz2jcd.1
title: Image Dataset for Radish Plant Leaf Disease Detection and Freshness Assessment from Bangladesh

description: Radish Plant
 1 Black leaf spot :526
 2 Downy mildew :601
 3 Mosaic virus :548
 4 Radish flea beetle :513
 5 Fresh leaf :613
DOI: 10.15468/dl.davxvv
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ahmosia galbinea Heinrich, 1926"
 ]
}

 The dataset includes 20 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009320-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/w48t69hg3k.1
title: American Zebra Optimization Algorithm Matlab Code

description: This file contains the Matlab code of a Novel Meta-heuristic Algorithm namely 'American Zebra Optimizer'. Please do contact for any clarification.
DOI: 10.17632/yktyfs9hrm.1
title: Data for 'Monopsony Rent Surcharges for SDG Financing: The Case of Japan'

description: The shortage of financial resources for achieving the Sustainable Development Goals (SDGs) is a serious issue. This study attempts to estimate the amount of monopsony rent surcharges which would be able to be imposed on large corporations in Japan as a financial resource for achieving SDGs. Using the dynamic pseudo-equilibrium approach and mathematical programming, the results show that the average total amount of monopsony rent of 5581 Japanese companies was 10,098.4 billion yen per year in the 2010s. Additionally, the sum of the corporate income tax rate and monopsony rent rate consistently remained at approximately 50% from 1980 to 2020, while the corporate income tax rate declined from approximately 44.7% to less than 27.9%. 

 These folders contain the data and programs used for the above estimation, and a brief explanation of them is given below. 
 You can obtain the results by loading the programs in the folder 'ExcelMacro&MatlabPrograms' while referring to the explanations from 1) to 7).

1) ExcelMacro&MatlabPrograms
This folder includes the program files available for Macro in Excel and MATLAB to do data processing, calculations, and processing of results. 

2) 1RawData
This folder includes the files that had been downloaded accounting data of Japanese listed companies from Nikkei Needs Financial Quest data base.

3) 2ProcessedData
They are the data files processed by loading the programs from 1 to 8 in dataprocessing.xlsb one by one. 

4) 3InputData
This folder includes the processed data after loading ReturntoScale2023L.m and processing the program 9 in dataprocessing.xlsb. They are input data for rent calculation by RentCal2023Japan.m.

5) 4Results
The rent calculation results by RentCal2023Japan.m are in the folder ‘4Results’. 

6) 5ProcessedResults
Macro 123, 13(Ave), 14(T), and 15(TS) in resultprocessing.xlsb were loaded to process the results of the calculation together with input data files to create summary tables of results.

7) Tables
 This folder includes the tables quoted in the manuscript which were created by data extracted from the files in ‘5ProcessedResults’.
DOI: 10.17632/tm72fkfxd5.1
title: Helmet Wearing Image Dataset

description: A comprehensive collection of 6,036 high-resolution images that meticulously document the usage of helmets in real-world scenarios. This dataset offers a diverse range of images, encompassing both correctly worn helmets and instances of incorrect helmet usage. These images were captured using mobile phones, ensuring a practical and accessible perspective on helmet compliance.
DOI: 10.17632/dxdc6nwbwd.1
title: Symbolic test of the Jacobi identity for given generalized ‘Poisson’ bracket

description: Abstract We have developed and provide an algorithm which allows to test the Jacobi identity for a given generalized ‘Poisson’ bracket. Novel frameworks for nonequilibrium thermodynamics have been established, which require that the reversible part of motion of thermodynamically admissible models is described by Poisson brackets satisfying the Jacobi identity in order to ensure the full time-structure invariance of equations of motion for arbitrary function(al)s on state space. For a nonassociative al... Title of program: jacobi2.0 Catalogue Id: ADOE_v1_0 Nature of problem The problem is to evaluate single and nested arbitrary generalized Poisson brackets and the cyclic sum of these in order to test the Jacobi identity on a given state space for systems described in terms of discrete or of continuous variables. The Jacobi identity has to be fulfilled for Poisson brackets consistently describing the reversible dynamics of physical systems as desired, e.g., within the framework of nonequilibrium thermodynamics [1-3]. Versions of this program held in the CPC repository in Mendeley Data ADOE_v1_0; jacobi2.0; 10.1016/S0010-4655(01)00161-8 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.17632/mv436mnrjm.1
title: Colour Detection and Segmentation based Invisible Cloak

description: This research paper presents a fascinating project on creating an "Invisible Cloak" effect using Python and Computer Vision techniques. While true invisibility is still a fantasy, our approach leverages Color Detection and Segmentation to achieve a captivating visual illusion. The system identifies the person wearing the cloak and the background colors, then seamlessly blends the person with the surroundings, giving the appearance of vanishing from view. We explore the potential applications in entertainment, augmented reality, and creative visual effects. The methodology is straightforward, utilizing existing computer vision techniques, making it accessible and capable of real-time processing. However, challenges exist, such as sensitivity to lighting and background complexities. 

This project aims to creates a magical experience by using an Image Processing technique called Color Detection & Segmentation resulting in false sense of Invisibility in the frame.

OBJECTIVES:
1- Capture & Store background frame using Image Acquisition by Store a single frame before starting the infinite loop
2- Detect the defined color using color detection & segmentation algorithm
3- Segment out the defined colored part by generating mask & applying it on frame
4- Generate the final output to create a magical effect by combining frames together, & remove the unnecessary noise from masks.
DOI: 10.17632/shhg3xtshw
title: The Cultural Preparedness of Teachers and Schools for the Implementation of Values Education

description: Study design
The current study aims to investigate teachers’ attitudes towards values education practices and the relationship between school administration, and parental involvement and values education practices of teachers. For this purpose, a quantitative approach was adopted, relying on teachers’ self-evaluations of their experiences of values education in their schools and in their own teaching. The study followed the principles of exploratory quantitative research; therefore, no hypotheses were formulated (Creswell & Creswell, 2018).
Procedure and measures
Data were gathered using pen and paper directly in the workplaces of the teachers. Respondents filled in a questionnaire which consisted of 5 questions, each exploring different aspects of the research objectives. On a 5-point scale they evaluated (1) the subjective importance of different values education goals, (2) personal attitudes towards the need of values education in general, (3) the values education implementation situation in their school, (4) the commitment of fellow teachers and school administration, and parents’ attentiveness to values education, and (5) their own values education practices. The questionnaire was conducted in Lithuanian and was translated to English only during the analysis.