cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25403/upresearchdata.16633576.v2
title: Food security survey City of Tshwane, 2018/19

description: Data was collected from the City of Tshwane. Food security survey data of 777 urban food-insure households in the City of Tshwane. The analysis found that due to income shocks, households adopted a fixed pattern of food group frequencies, mostly cereals. This compromised nutritional safety and calls for income-based policies and nutritional awareness.<br>
DOI: 10.6084/m9.figshare.13365284.v2
title: Single-nucleus chromatin accessibility landscape reveals diversity in regulatory regions across distinct adult rat cortex

description: A reference of snATAC-seq datasets for mammalian cortex tissues is important for the understanding of regulatory specificity and developmental abnormality caused by genetic or environmental alterations. Here, we report an adult rat ATAC-seq profile by producing a total of 11 snATAC-seq libraries profiles from 4 distinct cortex region of female rat. The snATAC-seq read enrichment, fragment size distribution, and reproducibility between replicates demonstrated the high quality of the full dataset.<br>
DOI: 10.6084/m9.figshare.16434903.v1
title: Análisis de tópicos de principales actores políticos españoles

description: Se muestran los principales tópicos asociados a los principales actores políticos en España, durante los períodos electorales previos a las Elecciones Generales de 2016, y 2019. <br>Los actores políticos analizados en este trabajo fueron: <br>PSOE-Pedro SánchezPopular-Rajoy/Pablo Casado<br>Podemos-Iglesias<br>Ciudadanos-Rivera<br>Vox-Abascal<br><br>Se incluyen documentos académicos tomados como referencia para el desarrollo del estudio hecho. <br>Los datos de 2016 y 2019 (primeras elecciones), fueron recabados por el autor, mientras que los relacionados con la segunda elección de 2019 fue completado a partir del proyecto Disinformationpoliticslab, financiado por la Universidad Internacional de la Rioja (UNIR).
DOI: 10.6084/m9.figshare.26840911.v1
title: Synthesizing gas-filled anti-resonant hollow-core fiber Raman lines enables access to the molecular fingerprint region

description: These files include all raw data for this work.
DOI: 10.6084/m9.figshare.19519825.v1
title: March 2022 Covid-19 Twitter Streaming Dataset

description: The file contains Tweet IDs* for COVID-19 related tweets collected in <b>March, 2022</b> from <b>Twitter's COVID-19 Streaming Endpoint </b>via a custom script developed by the <b>Social Media Lab (https://socialmedialab.ca/)</b>.<br>Visit <b>our interactive dashboard at https://stream.covid19misinfo.org</b>/ for a preview and some general stats about this COVID-19 Twitter streaming dataset.<br>For more info about <b>Twitter's COVID-19 Streaming Endpoint</b>, visit <b>https://developer.twitter.com/en/docs/labs/covid19-stream/overview</b><br><b>Note</b>: In accordance with Twitter API Terms, the dataset only includes Tweet IDs (as opposed to the actual tweets and associated metadata). To recollect tweets contained in this dataset, you can use programs such as Hydrator (https://github.com/DocNow/hydrator/) or the Python library Twarc (https://github.com/DocNow/twarc/).
DOI: 10.17632/v5rzykvmzw
title: millennial lecturer data

description: The results of this study prove that the conception of SET theory is still relevant today and also contributes to the government in improving the performance of lecturers in Indonesia.
DOI: 10.6084/m9.figshare.6695228.v1
title: Additional file 2: of DeepCRISPR: optimized CRISPR guide RNA design by deep learning

description: Detailed comparison results for sgRNA on-target efficacy prediction and off-target site prediction. (XLSX 16 kb)
DOI: 10.17632/xj8g9dww5h
title: Raw data - Priming effect in children with Type 1 Diabetes Mellitus

description: Research data
DOI: 10.6084/m9.figshare.17040477.v1
title: R Code from Climate causes shifts in grey seal phenology by modifying age structure

description: R code for statistical analysis and matrix population modelling
DOI: 10.17632/gmm4wzfvz9
title: Unveiling the Role of Hydrate Shedding in Subsea Gas Transportation Accounting for Evolving Shear Strength

description: This data is used to simulate changes in pressure drop within a pipeline due to hydrate generation during the transportation of submarine natural gas pipelines. This data provides valuable insights for managing hydrate-related challenges in submarine pipeline operations, opening new avenues for the efficient utilization of hydrate reservoirs.
DOI: 10.17632/s22446k8z7
title: Teachers' readiness for integrating artificial intelligence into K-12 schools

description: The study examines variables to assess teachers' preparedness for integrating AI into South African schools. The dataset on the Excel sheet consists of 42 columns. The first ten columns comprise demographic variables such as Gender, Years of Teaching Experience (TE), Age Group, Specialisation (SPE), School Type (ST), School Location (SL), School Description (SD), Level of Technology Usage for Teaching and Learning (LTUTL), Undergone Training/Workshop/Seminar on AI Integration into Teaching and Learning Before (TRAIN), and if Yes, Have You Used Any AI Tools to Teach Before (TEACHAI). Columns 11 to 42 contain constructs measuring teachers' preparedness for integrating AI into the school system. These variables are measured on a scale of 1 = strongly disagree to 6 = strongly agree.

AI Ethics (AE): This variable captures teachers' perspectives on incorporating discussions about AI ethics into the curriculum. 

Attitude Towards Using AI (AT): This variable reflects teachers' beliefs about the benefits of using AI in their teaching practices. It includes their expectations of having a positive experience with AI, improving their teaching experience, and enhancing their participation in critical discussions through AI applications.

Technology Integration (TI): This variable measures teachers' comfort in integrating AI tools and technologies into lesson plans. It also assesses their belief that AI enhances the learning experience for students, their proactive efforts to learn about new AI tools, and the importance they place on technology integration for effective AI education.

Social Influence (SI): This variable examines the impact of colleagues, administrative support, peer discussions, and parental expectations on teachers' preparedness to incorporate AI into their teaching practices.

Technological Pedagogical Content Knowledge (TPACK): This variable assesses teachers' ability to use technology to facilitate AI learning. It includes their capability to select appropriate technology for teaching specific AI content, and bring real-life examples into lessons.

AI Professional Development (AIPD): This variable evaluates the impact of professional development training on teachers' ability to teach AI effectively. It includes the adequacy of these programs, teachers' proactive pursuit of further professional development opportunities, and schools' provision of such opportunities.

AI Teaching Preparedness (AITP): This variable measures teachers' feelings of preparedness to teach AI. It includes their belief that their teaching methods are engaging, their confidence in adapting AI content for different student needs, and their proactive efforts to improve their teaching skills for AI education.

Perceived Self-Efficacy to Teaching AI (PSE): This variable captures teachers' confidence in their ability to teach AI concepts, address challenges in teaching AI, and create innovative AI-related teaching materials.
DOI: 10.25386/genetics.6307136.v1
title: Supplemental Material for Marayati et al., 2018

description: The file contains a list of oligo used in this study.
DOI: 10.6084/m9.figshare.13292144.v2
title: Digitisation of Trzhaskovskaya Dirac-Fock Photoionisation Parameters for HAXPES Applications

description: This document provides a digitised version of the tabulated Dirac-Fock photoionisation parameters for HAXPES applications (2018), calculated by M.B. Trzhaskovskaya and V.G. Yarzhemsky. The data from the original paper was mined, checked and deposited into a Microsoft Excel spreadsheet for easy access.
DOI: 10.6084/m9.figshare.26983615.v1
title: GL GM - grids

description: Mat files with EMG signals recorded from the gastrocnemius medialis and gastrocnemius lateralis with one grid of 64 surface electrodes per muscle and edited motor unit pulse trains.
DOI: 10.6084/m9.figshare.6139955.v1
title: Data from McIntire & Juliano 2018

description: raw data and analyses McIntire & Juliano 2018 Ecology<br>
DOI: 10.6084/m9.figshare.7749521.v1
title: SupplTbl.1patryrafatmetabolomics.docx

description: This is a supplementary table file for a metabolomic analysis on conditionally immortalized glomerular endothelial cells<br>
DOI: 10.6084/m9.figshare.7956194.v1
title: Table S2 - WGS and RNAseq summary information

description: Whole-genome sequencing and RNA sequencing summary information.
DOI: 10.6084/m9.figshare.29114447.v1
title: <b>Effects of ARV-110 in the liver proteome in DHT-treated mice.</b>

description: Supplementary Data for:<b>Androgen Receptor PROTAC ARV-110 Ameliorates Metabolic Complications in a Mouse Model of Polycystic Ovary Syndrome</b>Jelina Basnet<sup>1,3,4,5</sup>, Samar Rezq<sup>1,3,4,5</sup>, Alexandra M. Huffman<sup>1,3,4,5</sup>, Tolulope E. Asala<sup>1,3</sup>, Licy L. Yanes Cardozo<sup>1,2,3,4,5,6</sup>, Damian G. Romero<sup>1,3,4,5</sup>Departments of <sup>1</sup>Pharmacology and Toxicology, and <sup>2</sup>Medicine (Endocrinology), <sup>3</sup>Mississippi Center of Excellence in Perinatal Research, <sup>4</sup>Women’s Health Research Center, <sup>5</sup>Cardiovascular-Renal Research Center, University of Mississippi Medical Center, Jackson, Mississippi, USA<b>Effects of ARV-110 in the liver proteome in DHT-treated mice.</b> Mice were treated with dihydrotestosterone (DHT) or control (CON) for 12 weeks. During the last 8 weeks, mice were additionally treated with low-dose ARV-110 (ARV-L, 1 mg/kg/day), high-dose ARV-110 (ARV-H, 10 mg/kg/day), or vehicle (VEH).<br>
DOI: 10.6084/m9.figshare.722921.v1
title: Geometric Morphometrics Workshop

description: Materials accompanying a Geometric Morphometric introductary workshop given June 14th 2013 at the Ecology and Evolution department at Trinity College, Dublin.
DOI: 10.6084/m9.figshare.9249443.v1
title: Table S2 from Adaptation to life on land at high O<sub>2</sub> via transition from ferredoxin-to NADH-dependent redox balance

description: BLAST output for the sequences without EPCs in Ku et al., 2015
DOI: 10.6084/m9.figshare.28658522.v1
title: A summary of fold change values .xlsx

description: This table summarizes fold change values from a gene expression analysis in Anopheles gambiae s.s mosquitoes from Bungoma, Western Kenya compared to the susceptible Kisumu strain
DOI: 10.6084/m9.figshare.29136162.v1
title: Supplementary Figure 1 from Functional characterization of the store-operated calcium entry pathway in naked mole-rat cells

description: supplementary material.rar
DOI: 10.17632/cj3txg633b
title: Painting Style-Based Recognition of Potters: Using Convolutional Neural Network Techniques

description: Measurement data covered in the article ‘Individual Feature-Based Recognition of Pottery Painters: Using Convolutional Neural Network Techniques’, Convolutional Neural Network Prediction Results and Convolutional Neural Network Code
DOI: 10.6084/m9.figshare.10259639.v1
title: Phenological patterns and pollination network structure in a Venezuelan páramo: a community-scale perspective on plant-animal interactions

description: <b>Background</b>: Little information is available about life history of páramo plants such as phenology and plant-animal interactions. <b>Aims</b>: We analysed phenological patterns of flowering and characterised the structure of a plant-pollinator network in a Venezuelan páramo in order to identify key species in this ecosystem. <b>Methods</b>: We counted the number of individuals with flowers of 76 native plant species and recorded their pollinators in 16 permanent plots between 3000 and 4200 m monthly for three years. We used this dataset to develop a plant-pollinator network, on which nine different metrics related to structural properties were calculated. <b>Results</b>: The flowering of most species concentrated during the rainy season (between May and November), however some species have continuous flowering. The guild of floral visitors included hummingbirds, flower piercers, bumblebees, Diptera and Lepidoptera. The plant – flower visitor interaction network did not exhibit nestedness, but showed a significant specialization index (H2) and high values of functional complementarity. <b>Conclusions</b>: Páramo plants have the capacity of maintaining a resident nectarivorus fauna (bumblebees and hummingbirds) because of continuous flower offer during the year. However, the plant – pollinator network identified could be very sensitive to the loss component species, owing to high levels of specialisation and functional complementarity.
DOI: 10.6084/m9.figshare.1506840.v4
title: MPG Ranch ITS amplicon data

description: ITS (fungal) amplicon data from soil study at MPG Ranch. Dates in file names denote sequencing runs at Argonne National Lab. Files beginning with R1 are forward read files (raw fastq files) and files beginning with I1 are index sequences. Concatenate the R1 and I1 files (in alphabetical order) prior to demultiplexing. Full metadata mapping file, with barcodes, for all samples is included. Open reference OTU table (97% identity, singletons removed) taxonomy metadata file, and OTU representative sequence fasta file also included.
DOI: 10.6084/m9.figshare.26308777.v1
title: Federated EMNIST Dataset

description: This dataset is derived from the Leaf repository (https://github.com/TalwalkarLab/leaf) pre-processing of the Extended MNIST dataset, grouping examples by writer. Details about Leaf were published in "LEAF: A Benchmark for Federated Settings" https://arxiv.org/abs/1812.01097<b>Note:</b> This dataset does not include some additional preprocessing that MNIST includes, such as size-normalization and centering. In the Federated EMNIST data, the value of 1.0 corresponds to the background, and 0.0 corresponds to the color of the digits themselves; this is the <i>inverse</i> of some MNIST representations, e.g. in tensorflow_datasets, where 0 corresponds to the background color, and 255 represents the color of the digit.Data set sizes:<i>only_digits=True</i>: 3,383 users, 10 label classestrain: 341,873 examplestest: 40,832 examples<i>only_digits=False</i>: 3,400 users, 62 label classestrain: 671,585 examplestest: 77,483 examplesRather than holding out specific users, each user's examples are split across <i>train</i> and <i>test</i> so that all users have at least one example in <i>train</i> and one example in <i>test</i>. Writers that had less than 2 examples are excluded from the data set.The <code>tf.data.Datasets</code> returned by <code>tff.simulation.datasets.ClientData.create_tf_dataset_for_client</code> will yield <code>collections.OrderedDict</code> objects at each iteration, with the following keys and values, in lexicographic order by key:<code>'label'</code>: a <code>tf.Tensor</code> with <code>dtype=tf.int32</code> and shape [1], the class label of the corresponding pixels. Labels [0-9] correspond to the digits classes, labels [10-35] correspond to the uppercase classes (e.g., label 11 is 'B'), and labels [36-61] correspond to the lowercase classes (e.g., label 37 is 'b').<code>'pixels'</code>: a <code>tf.Tensor</code> with <code>dtype=tf.float32</code> and shape [28, 28], containing the pixels of the handwritten digit, with values in the range [0.0, 1.0].<br><br><br>Args<code>only_</code><code>digits</code>(Optional) whether to only include examples that are from the digits [0-9] classes. If <code>False</code>, includes lower and upper case characters, for a total of 62 class labels.<code>cache_</code><code>dir</code>(Optional) directory to cache the downloaded file. If <code>None</code>, caches in Keras' default cache directory.<br><br><br><br>ReturnsTuple of (train, test) where the tuple elements are <code>tff.simulation.datasets.ClientData</code> objects.
DOI: 10.6084/m9.figshare.12217694.v3
title: Estimating the impacts of habitat loss induced by urbanization on bird local extinctions

description: The dataset contains necessary files to replicate the analyses in the article: Dri, G. F., Fontana, C. S., & de Sales Dambros, C. (2021). Estimating the impacts of habitat loss induced by urbanization on bird local extinctions. <em>Biological Conservation</em>, <em>256</em>, 109064. https://doi.org/10.1016/j.biocon.2021.109064 If additional comments or questions arise, please contact Gabriela Franzoi Dri (gabriela.franzoi@maine.edu)
DOI: 10.17632/kgpyz4cmjg
title: The dataset for the order batching and picker routing problem with category constraint.

description: The dataset contains the order set of 30 days in an O2O grocery, and the detailed results by solving the order batching and picker routing problem with category constraint. The category constraint means that the products includes two categories: food products and non-food products, and the picker must collect non-food products before food products to maintain food safety. There are 800 SKUs in the grocery. We assume that the number of orders in each day is 4000, and the arrival time ranges from 0~750 mins. (1) "Order set folder" includes 9 .mat files, which represent 9 different storage assignment strategies (SASs): random, a-1, a-2, b-1, b-2, c-1, c-2, d-1, and d-2. Each .mat file contains the information of arrival time of orders, the products ordered, and the storage assignments of non-food and food products. (2) Result. xlsx contains the detailed results under different batch-routing algorithms, such as the FCFS algorithms and seed algorithms.
DOI: 10.6084/m9.figshare.12672293.v1
title: MVLR DevOps in an ISO 13485 - Sources

description: Included sources with RQ categorization
DOI: 10.6084/m9.figshare.1394957.v1
title: Good liars are neither ‘Dark’ nor Self-Deceptive

description: Dataset to accompany PLOSOne article PONE-D-14-49497
DOI: 10.6084/m9.figshare.28397135.v1
title: 16s rRNA data of Ningxiang pigs

description: 16s rRNA data of Ningxiang pigs
DOI: 10.6084/m9.figshare.28477148.v2
title: Elevational constraints on flight efficiency shape global gradients in avian wing morphology

description: Data and code to reproduce the analyses and figures presented in the manuscript ''Elevational constraints on flight efficiency shape global gradients in avian wing morphology'' (Current Biology).<b>Dataset 1.xlsx</b> contains the full dataset and the metadata of all variables. The .csv versions of files for use in R scripts are provided in folder<b> R data</b>.The 100 randomly selected phylogenetic trees necessary for reproducing all model results are also provided as <b>100 random trees.rds</b>.The R scripts for reproducing PGLS model results are provided as <b>1. PGLS global models.R </b>(related to Figure 3) and <b>2. PGLS elevation band models.R</b> (related to Figure 4).Code for generating figures and supplementary tables can be found in file <b>3. Figures and tables.R</b>.<br><br>
DOI: 10.6084/m9.figshare.9582962.v1
title: Monitored data on occupants’ presence and actions in an office building (dataset)

description: The present contribution includes occupant presence and behaviour data along with indoor and outdoor environmental data monitored over a period of one year (from 2013-01-01 to 2013-12-31) in an office area of around 200 square meter in a university building in Vienna. Specifically, the data set includes the following: 1. Presence at work station [0:vacant, 1:occupied]2. Window state [0:open, 1:closed]3. Light state [0:off, 1:on]4. Equipment power [W]5. Indoor air temperature [°C]6. Indoor air relative humidity [%]7. Global radiation [W.m-2]8. Air temperature [°C]9. Air relative humidity [%]10. Wind speed [m.s-1]11. Wind direction [degree]<br>Occupant behaviour data and indoor environmental data streams (items 1-6) are stored in 15-min time intervals. Outdoor environmental data streams (items 7-11) are stored in hourly intervals.
DOI: 10.17632/h777x2k5xw
title: Data for: Good for the Environment, Good for Business: Foreign Acquisitions and Energy Intensity

description: Replication Stata code
DOI: 10.6084/m9.figshare.14534844.v2
title: Supplementary Table 1.docx

description: Gene Set Enrichment Analysis of 8- immune related lncRNAs in GBM.
DOI: 10.6084/m9.figshare.21444951.v3
title: Database of water cluster minima

description: See: <br> https://sites.uw.edu/wdbase/database-of-water-clusters/
DOI: 10.6084/m9.figshare.29100680.v1
title: <i>Momotus momota</i> nestling feeding data, October 2024, Madre de Dios, Peru

description: Data regarding the nestling feeding of the Amazonian Motmot (<i>Momotus momota</i>) in southeastern Peru, via remotely-triggered camera footage. Recorded information includes the feeding number (1 through 322), date, time, and prey species identified to the highest possible level.
DOI: 10.17632/7h9mdf5fvt
title: Data for the project management, life cycle inventory, costings and energy production of a ground-mounted photovoltaic farm in Greece

description: The data collected refer to the construction, costings, operation and environmental impacts of a photovoltaic farm and are provided in four separate Excel files with respect to their type and usage. Each file can be used separately for studying an individual topic or in combination with certain of the others to facilitate the study of more complex concepts. 
These four Excel files refer to the following dataset types:  
1.	Project Management Data
2.	Life Cycle Ιnventory (LCI)
3.	Electricity Generation Data
4.	Operational Cost Data
DOI: 10.17632/zwwznn8y2f
title: Data from a cluster analysis of 56 individuals of Gardenia jasminoides Ellis

description: This is the data generated with molecular marker of SSR of 56 cultivars of Gardenia jasminoides Ellis
DOI: 10.17632/c7fmyb9r8g
title: Analisis Usabilitas Sistem Informasi Perpustakaan (Sipus) Integrasi UGM
DOI: 10.6084/m9.figshare.14672784.v1
title: Supplementary Material for: Oral Squamous Cell Carcinoma Bone Invasion: Possible Roles of E-Cadherin in Osteoclastogenesis and Bone Infiltration

description: <b><i>Introduction:</i></b> Squamous cell carcinoma is the most common cancer of the oral cavity. When the tumor invades the bone tissue, the prognostic and survival rates decrease a lot, and the treatment becomes more aggressive, with several damages to the patient and health system. Many of the molecular mechanisms of bone invasion process are not understood yet, but it is already known that one of central processes of tumor evolution – adjacent tissues invasion and metastasis – is a large spectrum of phenotypic changes in epithelial cells to mesenchymal, in a process named as epithelial-mesenchymal transition (EMT). Loss of E-cadherin, an important epithelial cell adhesion protein, is a hallmark of this phenomenon. The objective of this retrospective study is to evaluate the expression of E-cadherin protein, comparing its distribution with clinical characteristics of the patients and possibly relation to EMT. <b><i>Methods:</i></b> Sixty-two cases with respective clinical data were analyzed by comparing immunohistochemical, H and E staining, and clinical data, observing the tumor-bone interface (TBI) and the surrounding tumor that had no direct contact with the bone surface (ST). <b><i>Results:</i></b> Forty cases were positive for E-cadherin (64%) with a heterogeneous pattern. Statistical analysis showed a significant difference between the presence of E-cadherin expression and tobacco smokers. Also, the equal or weaker protein expression in the ST than TBI is related to a worse overall survival. No statistically significant difference in other prognostic factors was observed. <b><i>Conclusion:</i></b> Our results suggest that the tumor cells that interact with the bone tissue could gain molecular changes, like partial EMT and osteoclastogenesis induction, which facilitate their migration and increase the bone resorption, resulting in a worse patient’s prognosis.