cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/kn46886xvw
title: AudioMagnetoTelluric (AMT) and Geochemical data in the Campi Flegrei caldera

description: EDI files of the AMT data and Geochemical data used in the article "Reservoir structure, hydraulic properties and fluid-related seismicity at the Campi Flegrei geothermal system inferred by audiomagnetotelluric surveying" submitted to Journal of Geophysical Research Solid Earth
DOI: 10.6084/m9.figshare.23820606.v1
title: <b>HLA Typing for Deceased Donors</b>

description: Allele-level HLA typing of 60 deceased donors determined using next-generation sequencing
DOI: 10.6084/m9.figshare.25868737.v2
title: device_attributes_combined.json

description: Contains attributes of perovskites solar devices
DOI: 10.17632/8z639k7b8v
title: Data on Retinal Images of Hypertensive Retinopathy and Glaucoma Patients

description: This dataset contains 110 blood vessels extracted from Digital Retinal Images for Optic Nerve Segmentation Database (DRIONS-DB) publicly available database. It could be used to diagnose several ophthalmic diseases such as Hypertensive retinopathy, Diabetic Retinopathy, Glaucoma etc.
DOI: 10.17632/y9bmtf4xmr
title: SorghumWeedDataset_Segmentation

description: Purpose of dataset creation: ‘SorghumWeedDataset_Segmentation’ is created to address real-time weed challenges precisely and encourage weed research using computer vision applications. About the dataset: ‘SorghumWeedDataset_Segmentation’ is a crop-weed research dataset with 5555 manually pixel-wise annotated data segments from 252 data samples which can be used for object detection, instance segmentation, and semantic segmentation. The data segments consist of sorghum samplings (Class 0), Grasses (Class 1), and Broad-leaf weeds (Class 2) which are the three research objects focused during this data acquisition process. The TVT (Train: Validate: Test) ratio is set as 8:1:1 to split the data samples into training, validation, and testing. The ground truth preparation is carried out by manually annotating the data segments pixel-wise, using VIA (VGG Image Annotator) software. The respective annotation files for training, validation, and testing are provided in JSON, CSV, and COCO formats. Equipment used for data acquisition: To record a rich set of information on the research objects, a state-of-the-art instrument - Canon EOS 80D – a Digital Single Lens Reflex (DSLR) camera with a sensor type of 22.3mm x 14.9 mm CMOS is used. Data type, format, and size: Each data sample is an RGB image represented in JPEG format with 6000 × 4000 pixels making an average size of 13MB. This rich set of information from the data sample assisted in annotating data segments of plant length lesser than 0.5cm. Temporal coverage: Data is acquired during April and May 2023. To generalize the dataset, data is acquired in various light and weather conditions with varying distances. Geographical coverage: Data is acquired from Sri Ramaswamy Memorial (SRM) Care Farm, Chengalpattu district, Tamil Nadu, India. To the best of our knowledge, ‘SorghumWeedDataset_Segmentation’ is the first open-access crop-weed research dataset from Indian fields for segmentation that deals with weed issues in uniform and random crop-spacing fields. Expected outcome: The expected outcome of this dataset will be an Artificial Intelligence (AI) model that localizes and segments all the research objects present in a particular data sample. Detailed description: A detailed description of the dataset and data acquisition process is given in the data article entitled “ ‘SorghumWeedDataset_Classification’ And ‘SorghumWeedDataset_Segmentation’ Datasets For Classification, Detection, and Segmentation In Deep Learning “. (Submitted in the journal ‘Data in Brief’ on 25/09/2023 and awaiting publication) Citation: If you find this dataset helpful and use it in your work, kindly cite this dataset using “Michael, Justina; M, Thenmozhi (2023), “SorghumWeedDataset_Segmentation”, Mendeley Data, V1, doi: 10.17632/y9bmtf4xmr.1” Further queries: If any queries/suggestions concerning this dataset, please e-mail us at thenmozm@srmist.edu.in [corresponding author]
DOI: 10.6084/m9.figshare.5128207.v1
title: Supplementary Material for: A Pathological Scoring System to Predict Renal Outcome in Diabetic Nephropathy

description: <b><i>Background:</i></b> With the association between diabetic nephropathy (DN) and renal outcome being increasingly clear, we aimed at creating a new DN pathological scoring system that could predict the renal outcome. <b><i>Methods:</i></b> We studied 205 patients with DN confirmed by renal biopsy, sometime between March 1985 and January 2010, who met the inclusion criteria. Renal biopsy included clinical parameters and Tervaert classifications. Hazard ratios (HRs) for death-censored end-stage renal disease (ESRD) were estimated by adjusted Cox proportional-hazards regression. The overall pathological risk score (D-score) was calculated by summing the products of beta coefficient and bootstrap-inclusion fractions, its predictive utility evaluated by Kaplan-Meier methods and c-statistics for a 10-year risk of ESRD. <b><i>Results:</i></b> The D-scores of glomerular classes 1, 2A, 2B, 3, and 4 were, respectively, 0, 3, 4, 6, and 6. Those of interstitial fibrosis and tubular atrophy classes 0, 1, 2, and 3 were 0, 7, 9, and 11, and those of interstitial inflammation classes 0, 1, and 2 were 0, 3, and 4, respectively. The D-score of hyalinosis class 2 was 3 and that of arteriosclerosis class 2 was 1. So, a patient's D-score could be 0-25. HRs for ESRD in patients with D-score ≤14, 15-18, 19-21, and 22-25 were, respectively, 1.00 (reference) 16.21 (95% confidence interval (CI), 1.86-140.90), 19.78 (95% CI, 2.15-182.40), and 45.46 (95% CI, 4.63-446.68) after adjusting for clinical factors. The c-statistics suggested a better predictive ability for a 10-year renal death with models that included the D-score. <b><i>Conclusion:</i></b> Prediction of DN patients' renal outcome was better with the D-score than without it. Patients with a D-score ≤14 had excellent renal prognosis.
DOI: 10.6084/m9.figshare.7391282.v2
title: Output: meta-regression Accuracy adults

description: Output: meta-regression accuracy adults
DOI: 10.17632/b4mn99zhfd
title: Метаэтика. Теоретический обзор

description: Книга представляет собой первый на русском языке систематический обзор метаэтики – дисциплины, которая пытается ответить на наиболее важные и глубокие вопросы относительно морали. Существуют ли моральные ценности? Какова их природа? Объективны ли они? Что означают наши моральные высказывания? При ответе на данные вопросы затрагиваются семантические, метафизические, эпистемологические и психологические аспекты морали. Дается подробный обзор наиболее известных метаэтических теорий: нон-натурализма, натурализма, конструктивизма, релятивизма, моральной теории ошибки, фикционализма и различных разновидностей нонкогнитивизма – эмотивизма, прескриптивизма, квазиреализма, норм-экспрессивизма и других. Книга предполагает некоторое первоначальное знакомство с философией и может быть использована в качестве учебного пособия для студентов философских факультетов высших учебных заведений.
DOI: 10.17632/gkdmdh5y5d
title: (Dataset)Fostering Collaboration and Critical Thinking

description: The topic focuses on fostering collaboration and critical thinking by integrating generative AI tools in education, emphasizing student-centered approaches, favorable perceptions, and ethical considerations. This entails exploring diverse experiences, investigating educators' roles, and collaborating to develop tailored AI tools for enhanced learning outcomes.
DOI: 10.17632/p42xjtv8pv
title: UCM_FibIoT2024

description: The UCM_FibIoT2024 dataset is a detailed collection of data aimed at improving the understanding of Distributed Denial of Service (DDoS) attacks against smart home central control units, specifically the Fibaro Home Center 3. This dataset documents various types of DDoS attacks, including TCP SYN flood, ICMP flood, and HTTP flood, to provide insight into their impact on the functionality and availability of IoT devices.

Data collection was performed on a local network using the hping3 tool for SYN and ICMP flood attacks, and the LOIC tool for HTTP flood attacks. Network traffic was captured using Wireshark software, and the dataset is available in both PCAP and CSV formats for detailed analysis. The captured data includes key attributes such as timestamps, source and destination IP addresses, protocols, packet lengths, and port numbers.

The primary goal of this dataset is to facilitate the simulation and analysis of DDoS attacks on smart home central control units, providing a resource for researchers focused on cybersecurity and IoT device protection. By examining the network traffic logs and packet captures, researchers can identify attack patterns, understand the dynamics of different types of DDoS attacks, and develop effective mitigation mechanisms.

The dataset is organized to include detailed logs of each attack, such as start and end times, frame numbers, and total number of attack packets. For ease of use, the data is organized into folders, and the SYN flood attack data is further subdivided by the ports targeted (80, 443, and 500).

The UCM_FibIoT2024 dataset serves as a valuable tool for analyzing and developing defenses against DDoS attacks on IoT devices. It provides a practical resource for researchers and cybersecurity professionals to effectively simulate, analyze, and mitigate DDoS attacks.
DOI: 10.6084/m9.figshare.14211299.v1
title: mBio_Wang_etal_2020_supplement_TableS17

description: <b>Supplemental Table S17. Oligonucleotides used in this study.</b>
DOI: 10.6084/m9.figshare.17430020.v1
title: Supplementary Material for: Oxygen Saturation Index in Neonates with a Congenital Diaphragmatic Hernia: A Retrospective Cohort Study

description: <b><i>Introduction:</i></b> The oxygenation index (OI) is a marker for respiratory disease severity and adverse neonatal outcomes. The oxygen saturation index (OSI) is an alternative that allows for continuous noninvasive monitoring, but evidence for clinical use in critically ill neonates is scarce. The aim of this study was to evaluate the OSI as compared to the OI in term neonates with a congenital diaphragmatic hernia (CDH). <b><i>Methods:</i></b> A single-center retrospective cohort study was conducted including all live-born infants with an isolated CDH between June 2017 and December 2020. Paired values of the OI and OSI in the first 24 h after birth were collected. The relation between OI and OSI measurements was assessed, taking into account arterial pH, body temperature, and preductal versus postductal location of oxygen saturation measurement or arterial blood sampling. The predictive values for pulmonary hypertension, need for extracorporeal membrane oxygenation therapy, and survival at discharge were evaluated. <b><i>Results:</i></b> Of 33 subjects included, 398 paired values of the OI (median 5.8 [3.3–17.2]) and OSI (median 7.3 [3.6–14.4]) were collected. The OI and OSI correlated strongly (<i>r</i> = 0.77, <i>p</i> &lt; 0.001). The OSI values corresponding to the clinically relevant OI values (10, 15, 20, and 40) were 8.9, 10.9, 12.9, and 20.9, respectively. The predictive values of the OI and OSI were comparable for all adverse neonatal outcomes. No difference was found in the area under the receiver operating characteristic curves for the OI and the OSI for adverse neonatal outcomes. <b><i>Conclusions:</i></b> The OSI could replace the OI in clinical practice in infants with a CDH.
DOI: 10.6084/m9.figshare.23786388.v1
title: Multispectral camera

description: Dataset created with multiespectral camera micasense Readege 3.Stereo effect has been already fixed and all leaf segmented. The dataset is divided in the different diseased and in healthy. To use the dataset the dataset has to be reorganize into healthy and diseased (As in example). Each sub folder contains each sub spectral chanel (Red, Green, Blue, Infra red, Red edge)
DOI: 10.6084/m9.figshare.26380267.v1
title: Telemedizin per Datenbrille im CBRN-SchutzanzugTelemedicine via data glasses in CBRN protection suit

description: Daten zur Studie "Telemedizin über Datenbrille im CBRN-Schutzanzug"Data for study "Telemedicine via data glasses in CBRN protection suit"
DOI: 10.6084/m9.figshare.5442418.v1
title: Supplementary Material for: Genome-Wide Analysis of Pancreatic Cancer Using Microarray-Based Techniques

description: <i>Background/Aims:</i> Microarray-based comparative genomic hybridisation (CGH) has allowed high-resolution analysis of DNA copy number alterations across the entire cancer genome. Recent advances in bioinformatics tools enable us to perform a robust and highly sensitive analysis of array CGH data and facilitate the discovery of novel cancer-related genes. <i>Methods:</i> We analysed a total of 29 pancreatic ductal adenocarcinoma (PDAC) samples (6 cell lines and 23 microdissected tissue specimens) using 1-Mb-spaced CGH arrays. The transcript levels of all genes within the identified regions of genetic alterations were then screened using our Pancreatic Expression Database. <i>Results:</i> In addition to 238 high-level amplifications and 35 homozygous deletions, we identified 315 minimal common regions of ‘non-random’ genetic alterations (115 gains and 200 losses) which were consistently observed across our tumour samples. The small size of these aberrations (median size of 880 kb) contributed to the reduced number of candidate genes included (on average 12 Ensembl-annotated genes). The database has further specified the genes whose expression levels are consistent with their copy number status. Such genes were <i>UQCRB</i>, <i>SQLE</i>, <i>DDEF1</i>, <i>SLA</i>, <i>ERICH1</i> and <i>DLC1</i>, indicating that these may be potential target candidates within regions of aberrations. <i>Conclusion:</i> This study has revealed multiple novel regions that may indicate the locations of oncogenes or tumour suppressor genes in PDAC. Using the database, we provide a list of novel target genes whose altered DNA copy numbers could lead to significant changes in transcript levels in PDAC.
DOI: 10.6084/m9.figshare.6989315.v1
title: Tracking data, Subject (b) MC and Motion

description: Motion tracking data from subject (b) with MC and motion.Aij is the i,j element of the transformation matrix
DOI: 10.6084/m9.figshare.1033772.v1
title: LOCATION DEPENDENT RB MULTICAST ROUTING IN WIRELESS SENSOR NETWORKS USING GPS BASED SYSTEM

description: -Multicast routing protocol gives much importance to the priory creation of multicast tree.<br>This priory creation can be done with the help of multicast members, which require individual node to<br>maintain state information. In dynamic network if proper communication is not there, it's not possible to<br>transmit data. In receiver depend multicasting based on the geographical location; it should specify<br>which the correct way to forward the packet is. In this paper we include that Multicast Members are<br>directly sending request to the Source Node, if the requesting files are not available in Multicast Region.<br>Then the Source Node will directly send the requesting file to Multicast Members with the help of RB<br>header.
DOI: 10.6084/m9.figshare.14601723.v1
title: Appendix 6.1 WeChat data

description: The dataset contains WeChat posts uploaded by 47 most influential WeChat official accounts from November 2018 to December 2019.
DOI: 10.6084/m9.figshare.19209753.v1
title: Gill Transcriptome & Annotation

description: A gill and transcriptome for lake sturgeon.
DOI: 10.6084/m9.figshare.22640998.v1
title: Qualitative Feedback_Students and SPs

description: Compilation and thematic analysis of Qualitative feedback from Students and Standardised Patients
DOI: 10.6084/m9.figshare.28668500.v1
title: Supplementary Material for: Epithelioid malignant peripheral nerve sheath tumor of the breast with breast cancer in the contralateral breast : Case report

description: Introduction: Malignant peripheral nerve sheath tumors (MPNST) are common in the peripheral nerves of the head, neck, and limbs, with few reports of their occurrence in the breasts, and the epithelioid type is rare. Here, we aimed to report a case of an epithelioid malignant peripheral nerve sheath tumor of the breast.
Case Presentation: A 76-year-old woman presented with bilateral breast masses. Pathological findings showed a 60-mm invasive ductal carcinoma (T3N0M0 Stage IIB) on the right breast and an epithelioid malignant peripheral nerve sheath tumor on the left breast. After surgical resection, the patient was treated with endocrine therapy alone for right breast cancer, and no recurrence was observed 4 years after surgery.
Conclusion: Reports of malignant peripheral nerve sheath tumors in the breasts are rare. The pathological analysis showed atypia of spindle cells, positive staining for vimentin, S100, SOX10, and epithelial-like cells, and positive staining for cytokeratin AE1/AE3. H3K27me3 is reportedly absent in typical malignant peripheral nerve sheath tumors; however, it is expressed in epithelioid types. It sometimes occurs in patients with a germline mutation in SMARCB1/INI1, where INI1 is absent in tumor cells. In this case, the tumor cells expressed H3K27me3 and also maintained INI1.
DOI: 10.17632/m68gwfnfcc
title: Dataset for Basic ENT training for enhanced healthcare worker Knowledge, Attitudes, and Practices in a resource-limited setting: a pre-post and post-post cross-sectional study

description: This data assessed the knowledge, attitudes, and practice (KAP) of healthcare workers (HCWs) with regard to basic Ear, Nose, and Throat (ENT) disease management both before and after training. A physical training workshop was conducted, preceded by a pre-training survey, and followed by immediate and five-month post-training assessments of KAP. The training significantly improved HCWs' KAP related to ENT disease management, supporting the importance of targeted, sustainable training interventions in resource-limited settings. 

In assessing knowledge, each correct response scored one, an incorrect or 'I do not know' response scored zero, and the percentage of correct responses to questions was recorded as the knowledge score. Statements assessing attitudes and beliefs were categorised on a 4-point Likert scale as 'strongly agree,' 'agree,' 'disagree,' and 'strongly disagree.' In contrast, those assessing practices were categorised as 'all the time,' 'some of the time,' 'hardly ever,' and 'never.' We reversed the Likert scale for the statements 'I feel discussing patients for referral with the receiving doctor is unnecessary in Zambia' and 'I feel ENT conditions are difficult to assess, diagnose, and manage', considering the negative style of questioning. With practices, the proportions of participants in agreement with each statement and practicing a stated task were calculated, as were the percentage of participants with access to diagnostic and treatment aids.
DOI: 10.6084/m9.figshare.27644262.v1
title: <b>The Politics of Human Rights: Understanding How Regime Similarity Affects Naming and Shaming at the Universal Periodic Review</b>

description: How do dyadic relations affect a state’s human rights naming and shaming strategy? We argue that institutional and ideational factors influence democratic states’ understanding of human rights values while in non-democratic states, political factors dominate states’ calculus. Based on ingroup-outgroup perception, pairs of states interact differently in international human rights politics. Our quantitative analyses demonstrate that states with similar regime types are more lenient in providing recommendations at the United Nations Universal Periodic Review (UPR) and are also more likely to accept one another’s recommendations. Our paper illustrates the dynamic nature of naming and shaming. This paper contributes to the literature by demonstrating regime type as an underlying factor influencing dyadic interactions on human rights issues. Our findings have implications for policymakers who wish to improve human rights in other states.
DOI: 10.6084/m9.figshare.28533098.v1
title: 4D water droplet collision datasets

description: We share the simulated water droplet collision datasets modeled with the Navier-Stokes Cahn-Hilliard equations. This data is used to validate our deep-learning 4D reconstruction algorithm, as reported in "4D-ONIX for reconstructing 3D movies from sparse X-ray projections via deep learning" [1]. The datasets are simulated for two scenarios: reproducible processes and quasi-reproducible processes. We share the training datasets and the ground truth files for both scenarios. The ground truth files are 3D movies of droplet collision simulation. The training datasets are simulated projection pairs for the experiment of X-ray Multi-Projection Imaging (XMPI) [2, 3]. The two projections are 23.8° apart. For the reproducible process, the ground truth file contains a single 3D movie with 75 timestamps. The size of each 3D object is 128×128×128. The training dataset contains 16 XMPI experiments of this dynamical process, measured from 16 random angles. The angles differences among the 16 projection pairs are: 0°,2°,13°,16°,26°,28°,43°,52°,64°,74°,87°,95°,102°,115°,130°,144°. For the quasi-reproducible process, the ground truth file contains 16 simulations of droplet collision with a 10% variance in collision velocities and a 10% variance in droplet size. A single projection pair with random orientation (same as the reproducible process) of the sample was selected from each simulation to form a training dataset. Please refer to our article for the difference between reproducible and quasi-reproducible processes and details about collision simulation and projection generation.References: <br>[1] Zhang, Yuhe, et al. "4D-ONIX: A deep learning approach for reconstructing 3D movies from sparse X-ray projections." <i>arXiv preprint arXiv:2401.09508</i> (2024).<br>[2] Villanueva-Perez, Pablo, et al. "Hard x-ray multi-projection imaging for single-shot approaches." Optica 5.12 (2018): 1521-1524.<br>[3] Villanueva-Perez, Pablo, et al. "Megahertz X-ray Multi-projection imaging." arXiv preprint arXiv:2305.11920 (2023).
DOI: 10.6084/m9.figshare.9114503.v1
title: Questionnaire-PEFR-chronic respiratory symptoms

description: Questionnaire for collecting data on chronic respiratory symptoms and cooking smoke exposure.
DOI: 10.6084/m9.figshare.22362943.v1
title: Complete Genome

description: Complete genome of <strong>Acinetobacter baumannii strain 04117201 isolate DstkR-1</strong>
DOI: 10.6084/m9.figshare.22679461.v1
title: shear

description: The bulk and shear datasets for the Materials Project used in Matformer: https://github.com/YKQ98/Matformer