cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/6gbvz65kbx.1
title: Practical aspects of real-time pure shift HSQC experiments

description: Readme text file: === Experimental data including results of Matlab simulation [\data] \data\Figure-1 Sample: mixture of 80 mM D-glucose, 75 mM D-trehalose, 56 mM D-raffinose, and 30 mM alpha-cyclodextrin in D2O. gHSQC.fid: conventional gHSQC experiment rtPS-gHSQC_processed.fid: real-time pure shift gHSQC experiment after processing (extra data points dropped) rtPS-gHSQC_raw-data.fid: raw data of real-time pure shift gHSQC experiment before processing (extra data points are included) \data\Figure-3\experiments (data for Figure-3 left) The following list contains raw-data [*raw*.fid] and processed [*proc*.fid] data for real-time pure shift gHSQC experiments. Sample:2,3-dibromothiophene in dmso-d6. The total time of J-refocusing was incremented from 20ms to 500ms. Filenames are: *taup-XXXms*.fid, where XXX refers to the total duration of the J-refocusing period. Matlab simulations of these experiments (Figure-3 right) are in \data\Figure-3\simulation\taup-XXXms \data\Figure-4 Sample:2,3-dibromothiophene in dmso-d6. Real-time pure shift gHSQC experiments where the following notations are used in the filenames: BIRD-b3: experiments using both 180 carbon inversion pulses (the modified BIRD version) BIRD-b0: experiments omitting the 2nd 180 carbon inversion pulses (the original BIRD version) noCTP: gradient pulses are not applied in the real-time loop zCTP: gradient pulses using the z-axis are applied in the real-time loop scyc-n: phase sequencing methods are not employed in the real-time loop scyc-m16: MLEV-16 phase sequencing method is applied in the real-time loop ph2: Only 2 steps are used from the phase cycle (4 scan experiments) ph4: All 4 steps are used from the phase cycle which includes x,y on the real-time loop (4 scan experiments) raw: raw data proc: processed data (dropppoints are dropped) \data\Figure-5\experiments (data for Figure-5 left) The following list contains raw-data [*raw*.fid] and processed [*proc*.fid] data for real-time pure shift gHSQC experiments. Sample: 2,3-dibromothiophene in dmso-d6. The BIRD echo time was arrayed according to 1JCH=130,150,170,190,210 (optimum setting is 190). Matlab simulations of these experiments (Figure-5 right) are in \data\Figure-5\simulation\j1xh-XXXHz \data\Figure-6 Sample:1%H2O in D2O doped with CuSO4. Data files are named according to their reference in Figure-6 a.fid Conventional proton experiment b.fid Real-time acquisition without gradient pulses (using phase cycle) c.fid Real-time acquisition with gradient pulses along the z-axis d.fid Real-time acquisition using xy-gradient pulses. === Macro files[\maclib] _droppts1 _droppts2 go_UoM_2d_rt_PS_gHSQC _kp_cycles _kp_npoints UoM_bip125 UoM_makePS9 UoM_nowt UoM_proc_2d_rt UoM_save_2d_rt UoM_setup_2d_rt_BIRD_HSQC UoM_unpureshift === Manual[\manual] A pdf file includes installation and manual for the experiments. === Pulse sequence files [\psglib] UoM_1d_rt_PS_gHSQC.c === Wavelib files[\wavelib] kp_WURST40 kp2_wurst180
DOI: 10.17632/77w6mfzwzj.3
title: Mexico's forest diversity: site locations for trees

description: The data are associated with the following article (please look there for all information): Ricker, M., M.Á. Castillo-Santiago, G. Gutiérrez-García, E.M. Martínez, and E. Mondragón. Dataset about Mexico’s forest diversity: site locations of tree species, wood densities, and geographic database of forest-vegetation provinces. Data in Brief. Under review (January 2024).
DOI: 10.17632/mrj57rwdp2.1
title: Outcomes of Systemic Janus Kinase Inhibitors Following Prior Dupilumab Use for Atopic Dermatitis: An Evidence-Based Review

description: Atopic dermatitis (AD) is a common, chronic, highly pruritic, inflammatory condition. Although several Janus kinase inhibitors (JAKi) have recently been approved for moderate-to-severe AD, limited guidance is available regarding the role of systemic JAKi in patients who have previously utilized dupilumab. We conducted a systematic review to evaluate JAKi outcomes for this specific population.
DOI: 10.17632/xr8td57bk9.1
title: Collection of water samples

description: Collection of water samples
DOI: 10.17632/y63frd6pmf.6
title: Multimodal Hinglish Tweet  Dataset for  Deep Pragmatic Analysis

description: This dataset was meticulously curated to encapsulate tweets that vividly express raw emotions, sentiments, feelings, and textual gestures related to various situations of conflict. This includes, but is not limited to, wars, crises, civil unrest, and world wars I, II, III, etc. The fundamental objective of creating this dataset is to enable the development of digital applications capable of discerning the genuine emotional pulse of digitally empowered citizens. In essence, these tools aim to empower both the general public and government authorities with real-time insights into public sentiment, enhancing their understanding and responsiveness to critical situations.
DOI: 10.17632/gs4ppd7sz3.2
title: The Chinese and English Learner Language Corpus (CELL Corpus)

description: The Chinese and English Learner Language Corpus (referred to as ‘the CELL Corpus’ hereafter) is designed as a learner language corpus. The CELL Corpus, as a learner language corpus, is thus designed as a collection of text data chiefly composed of Chinese and English academic essay-type assignments written by university undergraduate students. The students submitted their academic essays as assignments for the assessment purpose of the courses they enrolled for, which suggests the authenticity of the text data collected. In addition to the text data, the CELL Corpus is also designed to include the meta data of the students whose academic essays were collected. The meta data collected represent five types of demographic information of the students, which are namely: age, gender, place of birth, first language and public examination results for Chinese Language and English Language. The two datasets (i.e. text data and meta data) of the CELL Corpus are delineated in the following sub-sections.

The datasets uploaded on this webpage are solely utilized for the establishment of the CELL Corpus (https://cellcorpusouhk.com/). Approval from the authors must be sought if anyone would like to download the datasets for research purposes.
DOI: 10.17632/fs9xxhh5yh.2
title: Global indicators for pedestrian streets by city

description: This dataset contains two indicators regarding pedestrianized roads in several cities around the globe. Namely, the dataset describes the "Total length of Pedestrian Streets (km)" and the "Share of Pedestrian Streets (%)" by city. We used OpenStreetMap (OSM) geospatial data and integrate the EU and OECD definition of cities to create comparable global indicators. The results reveal a chasm in car-free development mainly between Southern and Western European cities and their peers in other continents. Further details can be seen in the following paper: Bartzokas-Tsiompras, A., & Photis, Y.N., Utilizing OpenStreetMap data to measure and compare pedestrian street lengths in 992 cities around the world, IOP Conf. Ser.: Earth Environ. Sci, 2021.
DOI: 10.17632/cx67bdkfrg.1
title: Accompanying files for STAR Protocol: "Genome-scale chemogenomic CRISPR screens in human cells using the TKOv3 library"

description: Additional files to help implement CRISPR screens with the TKOv3. This include scripts for trimming sequences and for implementing dark cycles on the NextSeq500 platform.
DOI: 10.17632/p6sfdpjpj2.2
title: Jeong et al, 2022, Measurement of ciliary beating and fluid flow in the zebrafish adult telencephalon

description: In this dataset, we are providing MATLAB codes to analyse ciliary beating and cerebrospinal fluid flow in the zebrafish forebrain. Test datasets are also included. Please refer to the manuscript text Jeong et al, STAR protocol, 2022 for more details on how to use the codes and the expected outcomes.
DOI: 10.17632/39kzs5pxmk.1
title: TLFS23 - Tamil Language Finger Spelling Image Dataset

description: Tamil is an Indian Language of an remarkable antiquity that stands proudly as one of the oldest languages in the world. We have compiled a dataset for Tamil Language Finger Spelling which has finger representations for all 247 Tamil letters. TLFS23 is an elaborate dataset that comprises 248 classes of at least 1000 images in each class contributing to a massive 2,55,155 images in total. Each class represents Tamil characters finger spelled by participants of a diverse age group. Tamil has 12 Uyir ezuthukal (vowels), 18 Mei ezuthukal (consonants), 216 Uyir Mei ezuthukal (combination of consonant and vowels) and 1 Ayudha ezuthu (special character). This dataset has unique binary equivalent representations for all 247 characters of the Tamil language. The dataset could be used by scholars and researchers to develop vision based systems to assist the speech disabled.
DOI: 10.17632/358bfdjvwg.1
title: Atomic Mass – Energy-Primary Colour

description: Lot of out of text question arise in childhood mind during study in between different problems. Like – E=mc2 ; then ,what is the relation of E (energy) with “c2”? Different food item, Bettery;etc. have energy; in which “c2 or,the reation of the speed of ligft with it , or,why the orbit of electron of an Atom is like this etc. The calculations or, formulae which have shown in this is based on Every element are created from the collaboration of different energy. This energy known as heat energy, magnetic energy , light energy etc.
DOI: 10.17632/rc6rwf7c8n.1
title: Prediction Mechanisms for Monitoring State of Cloud Resources Using Markov Chain Model

description: To evaluate our mechanisms, we have considered a dataset that has been released by Google in May 2011. This dataset represents 29 days of status information about a cluster of 11k physical machines that are operated as a single unit. It contains a realistic mixture of workloads, as it was collected from a Cluster of nonhomogeneous machines. This Cluster was composed of three different platforms and a variety of memory/compute ratios. The platforms are; Type A includes 126 machines, Type B includes about 10K machines, and Type C includes 7950 machines with top configuration. We focused on the Type C platform as CPU and memory size measurements are normalized to the configuration of the largest machines. The exact machine configurations, exact numbers of CPU cores and bytes of memory, were normalized to the configuration of the largest machine. The dataset contains percentages of used resources by each task and requests to allocate these resources. We focused only on data that belongs to the usage of resources, which include measurements of CPU usage, memory space usage, and some other measurements. For simplicity, CPU, and memory measurements were focused on, where each file is organized as the following: the first column is the occurrence time, the second column is CPU measurements, and the third column is memory measurements.
DOI: 10.17632/vj6ztpt96d.2
title: Dataset: Feminine Hygiene Product Lifecycle Inventory and Impact Assessment

description: A lifecycle assessment (LCA) of feminine hygiene products was completed with three samples considered representative of sanitary pads, tampons and menstrual cups. Gabi LCA software was used to organize inventory data with the ILCD lifecycle impact assessment method used to determine mid-point and normalized impact scores. Data from the Ecoinvent database, and literature were used to complete the assessment. The dataset includes product details (mass and materials), lifecycle inventory (LCI) data and lifecycle impact assessment (LCIA) results for all mass and energy flows. Hait and Powers [2019 ] used the data in a comparative LCA. Three representative samples selected to identify materials and mass of products (sanitary pad, tampon, menstrual cup). U by Kotex® Security® Maxi Pads and U by Kotex® Click® Tampons. Menstrual cup produced by DivaCup. The materials that comprise these products were identified primarily based on manufacturer specifications and through literature review. Both Kimberly-Clark and DivaCup list the materials in each of their feminine hygiene products on their respective websites. The average total weight and composition of tampons and sanitary pads were directly measured. GaBi LCA software was used to construct life cycle plans for each of the menstrual products as well as to populate those plans with processes in the life cycle of each product. The GaBi package includes a database of life cycle inventories for the production of several materials and energy sources. EcoInvent, v3.3 database was also used for materials not available directly through GaBi. The Gabi software was also used to determine mid-point and normalized mid-point categories for each of several indications. ILCD methodology for mid-point analysis was selected to use suitable characterization factors and contributing flows. Mid-point scores were divided by the normalization factor to provide a single overall and unitless score for each product. A. Hait, A., S.E. Powers, The Value of Reusable Feminine Hygiene Products Evaluated by Comparative Environmental Life Cycle Assessment, Under review, Resources, Conservation & Recycling (2019)
DOI: 10.17632/f5s6cxk38f.1
title: Debt Literacy

description: Data collected in the study: Short-term Infographics-based Debt Education Improves Debt Literacy: The Role of Visual Attention on Positives and Negatives of Debt, Numerical, Graph, and Linguistic Literacy An experimental design with repeated measures and an internal comparison group was applied to study the process and results of infographics-based debt education. In testing 108 participants, we used eye tracker, a series of infographics, as well as scales of debt, numerical, graph, and linguistic literacy. Based on the literature review, which suggests that visual attention focused on the positives and negatives of borrowing, as well as numerical, graph, and linguistic literacy, could affect debt literacy education, we hypothesize that: H1. Participants focusing visual attention on infographics longer show better debt literacy education results. H2. Participants with higher numerical, graph, and linguistic literacy show better debt literacy education results. Verification of these hypotheses was conducted in an experimental design with repeated measures and with an internal comparison group. The results confirm that short-term infographics-based debt education can improve debt literacy significantly. The difference in processing the educational contents that were not known to participants before the educational session suggests that participants with better information literacy make more considerable debt literacy progress. Specifically, we found that numerical literacy is a significant mediator of debt education results, depending on the initial level of debt literacy; this relation is moderated by the focus of visual attention on risk-related information. We found no significant relationship between debt literacy education results and those of graph and linguistic literacy.
DOI: 10.17632/h4j5y95278.1
title: TPU-PLA orthoses_3DP+gcode

description: Details on TPU and TPU-PLA orthoses design are presented in a pdf. Samples' g-codes are included.
DOI: 10.17632/by9wy6fxsr.2
title: Imagery Dataset for Condition Monitoring of Synthetic Fibre Ropes

description: The dataset comprises images of synthetic fiber rope (SFR) intended for condition monitoring and predicting remaining useful life (RUL). These images were acquired using a Basler acA2000 camera equipped with a Basler C11-5020-12M-P Premium 12-megapixel lens.

We have created an extensive dataset containing a total of 3,089 raw images along with their annotations, representing both typical and defective synthetic fiber ropes (SFRs). The images in the dataset were recorded at a frame rate of 165 frames per second (FPS) and had a resolution of 2000 x 1080 pixels. This dataset encompasses a diverse range of potential defect scenarios that can occur during the SFRs' operational lifespan. These scenarios include, but are not limited to normal, and strand core out conditions. Additionally, it consists of image dataset named ‘extra’ depicting the images that need to be neglected in case of generative models.

The primary purpose of this dataset is to support computer vision applications, including object detection, classification, and segmentation. These applications aim to identify and analyze defects in SFRs effectively. The availability of this dataset will greatly facilitate the development and assessment of robust defect detection algorithms.
DOI: 10.17632/tdyvg3n3mz.1
title: Магистерская диссертация 《Прогнозный анализ и оценка экономической деятельности компании на основе ее финансовой отчетности》Шан Юйжу

description: Дополнительные файлы к магистерской диссертации. Процесс расчета данных в приложении.
DOI: 10.17632/d3d4h5bvss.2
title: Protocol for assessing neighborhood physical disorder using the YOLOv8 deep learning mode

description: These compressed files contain the Python code and models mentioned in the paper "Protocol for Evaluating Neighborhood Physical Disorder Incorporating Multiple Street View Sources." The paper provides detailed steps for neighborhood physical disorder assessment using multiple data sources (commercial street views, self-collected street views).

Code:
Includes Python computational code related to the steps mentioned in the paper.

YOLOv8 Model:
This is a Python implementation of the YOLOv8 architecture, including trained models for prediction.
DOI: 10.17632/3cv9mvckkh.2
title: Acoustic emission

description: Audio files of acoustic emissions of data, which are presented in "Detection of acoustic emission from nanofiber nonwovens under tensile strain – an ultrasonic test setup for critical medical device components" 
3 audio files of PLLA*S, PLLA*M, and PLLA*L,
and 3 audio files of incomplete stretched samples of PLLA*M

one principle sketch: Air coupled AE setup
DOI: 10.17632/cwbf2z7tch.1
title: Environmental Sensory Tendencies Dataset

description: This dataset was conducted to investigate the profound impact of human activities on the environment, based on scientific data, recognizing the potential of environmental problems to turn into devastating crises if appropriate measures are not taken. It emphasizes the important role of education in developing environmental awareness, knowledge and sensitivity to counter adverse environmental consequences. For this purpose, a dataset was created for the emotional tendencies of university students, who represent a demographic that has the potential to influence the sustainable future of the world. A survey data including 33 different variables was collected from 388 university students in Turkey. Environmental Sensory Tendencies Dataset is intended to provide valuable guidance for the development of effective environmental education programs and policies aimed at increasing university students' awareness and participation in environmental issues. Our research underlines the vital importance of developing responsible attitudes and behaviors to effectively address environmental challenges and thereby contribute to a healthier and more sustainable global ecosystem. This study will make a significant contribution to the literature and highlight the interconnection between human actions and environmental well-being.
DOI: 10.17632/36fjrg9s69.1
title: Dataset for COVID-19 segmentation and severity scoring

description: In this dataset, we present a set of chest X-ray images of COVID-19 positive and negative patients, with the aim of performing segmentation and scoring of disease-affected areas in the lungs. The total number of images is 1,364. Of them, 580 are COVID-19 positive images (43%) and 784 images show no findings (57%). Each COVID-19 image contains the segmentation mask of the COVID-19-affected area and the associated severity score.

We collected and pre-processed four publicly available datasets used for the classification of COVID-19 and pneumonia, namely:
•	Actualmed COVID-19 Chest X-ray Dataset containing 49 images of COVID-19 patients [1];
•	COVID-19 Radiography Database containing 104 images of COVID-19 patients [2];
•	COVID Chest X-Ray Dataset  containing 399 images of COVID-19 patients [3];
•	Figure1 COVID Chest X-ray Dataset containing 28 images of COVID-19 patients [4].

Then, two senior radiologists in our team, from the United States and Russia, annotated anteroposterior and posteroanterior radiographs. Each annotator has more than 10 years of experience and has been working extensively during the COVID-19 pandemic. The annotators labeled the datasets independently. Despite being time-consuming, this allowed us to get a consensus severity score of COVID-19-positive patients. Each patient has been labeled on a scale from 0 to 6, where 0 means no findings, while 6 is a severe form of COVID-19 which affects more than 85% of the lungs.

In addition to COVID-19 data, we also used two datasets with normal lungs without any pneumonia or any other abnormalities. Those healthy lung images have also been validated by the same two radiologists. Those images are represented by two datasets, namely:
•	Chest X-ray Normal Dataset containing 431 images of patients with no findings [5];
•	RSNA Normal Dataset containing 353 images of patients with no findings [6].

References:
1. 	Wang L, Wong A, Qiu ZL, McInnis P, Chung A, Gunraj H, et al. Actualmed COVID-19 Chest X-ray Dataset Initiative. 2020. Available: https://github.com/agchung/Actualmed-COVID-chestxray-dataset
2. 	COVID-19 Radiography Database. Available: https://www.kaggle.com/tawsifurrahman/covid19-radiography-database
3. 	COVID-19 Image Data Collection. 2020. Available: https://github.com/ieee8023/covid-chestxray-dataset
4. 	Wang L, Wong A, Qiu ZL, McInnis P, Chung A, Gunraj H, et al. Figure 1 COVID-19 Chest X-ray Dataset Initiative. 2020. Available: https://github.com/agchung/Figure1-COVID-chestxray-dataset
5. 	Chest X-Ray Images (Pneumonia). Available: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia
6. 	RSNA Pneumonia Detection Challenge. Available: https://www.kaggle.com/c/rsna-pneumonia-detection-challenge
DOI: 10.17632/3b3hn3688f.1
title: A new theory binds subatomic particles' mass to the square of the magnetic flux quantum, sets a new interpretation for mass and the significance of the wave function.

description: The motivation for investigating the issues presented in this article stemmed from a need to understand better the relationship in long-established physics formulas and extract the information they provided using conventional methods. Based on the definition of magnetic flux quantization, which is based on a combination of fundamental physical constants, the Planck constant, and the particle’s elementary charge, this work explores the results that arise when this equation is combined with the equation of the Bohr-level electrostatic force acting on the electron, which leads to a new mathematical relationship between the combined expressions. The new relationship yields novel theoretical findings related to the known universal constants. Following this insight, the formalism developed in this paper indicates that the mass of the electron and other subatomic particles is associated with the magnitude of the square of the magnetic flux quantum, which makes up the particle. This conclusion is not as strange as it may seem, as the square of the magnetic flux quantum appears in the context of magnetic energy in a current loop and, according to Einstein’s special theory of relativity, energy is equivalent to mass. Another aspect described at the end of this paper demonstrates the connection between the square of the magnetic flux quantum through the Bohr radius and the significance of the wave function in the atom. The theoretical results are in full accordance with experimental results published by NIST CODATA 2018 that I’ve used, which validates the existence of the relationship.