cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20279189.v1
title: Additional file 2 of Expanding the CRISPR/Cas genome-editing scope in Xenopus tropicalis

description: Additional file 2: Table S1. Computationally identified total number of potential off-target sites in Xenopus tropicalis genome with up to 5 mismatches to 7 targets. Table S2. 23 potential off-target sites selected for T7EI assay and the corresponding PCR primers for T7EI assay. Table S3. Sequences of all Cas9s tested in this study. Table S4. List of gRNA targeting sequences for various SpCas9 variants, PCR primers for the amplification of gRNA transcription templates, and PCR primers for detecting the targeted loci. Table S5. List of SaCas9 and KKH SaCas9 gRNA targeting sequences, PCR primers for the amplification of gRNA transcription templates, and PCR primers for detecting the targeted loci. Table S6. List of LbCas12a crRNA targeting sequences, T7 primer and single-stranded oligodeoxynucleotides used for the generation of crRNA transcription templates, and PCR primers for detecting the targeted loci.
DOI: 10.6084/m9.figshare.25756800.v1
title: TikTok Research Files

description: Videos glamourising disordered eating practices and body image concerns readily circulate on TikTok. Minimal empirical research has investigated the impact of TikTok content on body image and eating behaviour. The present study aimed to fill this gap in current research by examining the influence of pro-anorexia TikTok content on young women’s body image and degree of internalisation of beauty standards, whilst also exploring the impact of daily time spent on TikTok and the development of disordered eating behaviours. An experimental and cross-sectional design was used to explore body image and internalisation of beauty standards in relation to pro-anorexia TikTok content. Time spent on TikTok was examined in relation to the risk of developing orthorexia nervosa. A sample of 273 female-identifying persons aged 18-28 years were exposed to either pro-anorexia or neutral TikTok content. Pre- and post-test measures of body image and internalisation of beauty standards were obtained. Participants were divided into four groups based on average daily time spent on TikTok. Women exposed to pro-anorexia content displayed the greatest decrease in body image satisfaction and an increase in internalisation of societal beauty standards. Women exposed to neutral content also reported a decrease in body image satisfaction. Participants categorised as high and extreme daily TikTok users reported greater average disordered eating behaviour on the EAT-26 than participants with low and moderate use, however this finding was not statistically significant in relation to orthorexic behaviours. This research has implications for the mental health of young female TikTok users, with exposure to pro-anorexia content having immediate consequences for internalisation and body image dissatisfaction, potentially increasing one’s risk of developing disordered eating beliefs and behaviours.
DOI: 10.6084/m9.figshare.22262554.v1
title: Supplementary Material for: Sensitive periods for the effect of child maltreatment on psychopathology symptoms in adolescence

description: Introduction: Child maltreatment is among the strongest risk factors for mental disorders. However, little is known about whether there are ages when children may be especially vulnerable to its effects. We sought to identify potential sensitive periods when exposure to the 2 most common types of maltreatment (neglect and harsh physical discipline) had a particularly detrimental effect on youth mental health. Methods: Data came from the Future of Families and Child Wellbeing Study (FFCWS), a birth cohort oversampled from “fragile families” (n=3,474). Maltreatment was assessed at 3, 5, and 9 years using an adapted version of the Parent-Child Conflict Tactics Scales (CTS-PC). Using least angle regression, we examined the relationship between repeated measures of exposure to maltreatment on psychopathology symptoms at age 15 (Child Behavior Checklist; CBCL/6-18). For comparison, we evaluated the strength of evidence to support the existence of sensitive periods in relation to an accumulation of risk model. Results: We identified sensitive periods for harsh physical discipline, whereby psychopathology symptom scores were highest among girls exposed at age 9 (r2=0.67 internalizing symptoms; r2=1% externalizing) and among boys exposed at age 5 (r2=0.41%). However, for neglect, the accumulation of risk model explained more variability in psychopathology symptoms for both boys and girls. Conclusion: Child maltreatment may have differential effects based on the child’s sex, type of exposure, and the age it occurs. These findings provide additional evidence for clinicians assessing the benefits and drawbacks of screening efforts and point towards mechanisms driving increased vulnerability to psychopathology.
DOI: 10.6084/m9.figshare.26805724.v1
title: Supplemental Files for the article "Slovak morphological tokenizer using the Byte-Pair Encoding algorithm"

description: This repository contains multiple ZIP archives focused on Slovak language processing, specifically in subword tokenization, model pre-training and model fine-tuning. The first archive (Tokenizers) includes the SKMT Tokenizer, word root dictionaries, and PureBPE tokenization files. The second archive (Text Tokenization and Analysis) contains a script for tokenizing text with three different tokenizers, along with statistical analysis and comparison results. The third archive (Source Codes and Datasets for Training and Fine-Tuning Models) provides source codes and datasets for training and fine-tuning RoBERTa-based models, including sentiment datasets from SlovakBERT and an STS dataset. The final archive (Pre-trained models) contains pre-trained RoBERTa models, SK_BPE and SK_Morph, both trained for 10 epochs.
DOI: 10.6084/m9.figshare.26898166.v1
title: Stronger increase of methane emissions from coastal wetlands by non-native Spartina alterniflora than non-native Phragmites australis_RawData.xlsx

description: In a meta-analysis, we investigated the impact of two invasive species, Spartina alterniflora and Phragmites australis, on coastal wetlands and found an increase in methane emissions, with Phragmites having a lesser effect. We show that the drivers of these increased emissions may be related to individual plant traits rather than sources of organic matter.
DOI: 10.6084/m9.figshare.7925471.v1
title: Anti-infective potential of hydroalcoholic extract of Phyllanthus emblica seeds against selected human-pathogenic bacteria

description: Video (a): Unchallenged <i>C. elegans</i> Video (b): Slowed movement of <i>C. elegans</i> challenged with <i>P. aeruginosa</i> (3<sup>rd </sup>day) Video (c): <i>C. elegans </i>challenged with <i>P aeruginosa</i> Video (d): <i>C. elegans</i> exposed to PESE-treated <i>P. aeruginosa</i><i></i>
DOI: 10.17632/27xtwxfxfv
title: Single-cell mass cytometry profiling of tumor-infiltrating immune cells in pancreatic ductal adenocarcinoma

description: we applied mass cytometry to characterize features of immune components in the PDAC tumor microenvironment. The expression of 33 proteins at the single-cell level was examined in more than two million immune cells obtained from four types of samples, including treatment-naïve PDAC tumors, normal pancreatic tissues, chronic pancreatitis tissues, and blood.
DOI: 10.6084/m9.figshare.1108080.v1
title: Data for tracking year-to-year changes in intestinal nematode communities of rufous mouse lemurs (Microcebus rufus)

description: The dataset for mentioned publication. The data file contains: - sample: identification numbers - date: trapping date in year-month-day format - year: trapping year - name & chip number: individual identifications for each animal -sex: either F(emale) or M(ale) - fec_weight: is the measured weight of feces used for nematode analysis -rawcount: number of the nematodes -nem_count: the actual proportional amount of nematode eggs or larvae (=fecal egg count) - PS1-6: the sequence number for each putative species - spec_count: putative species number (diversity) -contamination: amount of contamination sequences -SRA_id: accession numbers to Short Read Archive
DOI: 10.6084/m9.figshare.13585579.v1
title: Data Sharing from Stomatal responses to carbon dioxide and light require abscisic acid catabolism in Arabidopsis

description: Raw and processed data related to Figures 1-4 and Supplementary Figures S1-S4
DOI: 10.6084/m9.figshare.28355897.v2
title: <b>MH-1M Dataset</b>

description: The rapid and widespread increase of Android malware presents substantial obstacles to cybersecurity research. In order to revolutionize the field of malware research, we present the MH-1M dataset, which is a thorough compilation of <b>1,340,515 APK</b> samples. This dataset encompasses a wide range of diverse attributes and metadata, offering a comprehensive perspective. The utilization of the VirusTotal API guarantees precise assessment of threats by amalgamating various detection techniques. Our research indicates that MH-1M is a highly current dataset that provides valuable insights into the changing nature of malware.MH-1M consists of 23,247 features that cover a wide range of application behavior, from intents::accept to apicalls::landroid/window/splashscreenview.remove. The features are categorized into four primary classifications:Feature TypesValuesAPICalls22,394Intents407OPCodes232Permissions214The dataset is stored efficiently, utilizing a memory capacity of <b>29.0 GB</b>, which showcases its substantial yet controllable magnitude. The dataset consists of <b>1,221,421 benign</b> applications and <b>119,094 malware</b> applications, ensuring a balanced representation for accurate malware detection and analysis.The MH-1M repository also offers a wide variety of metadata from APKs, providing useful data into the development of malicious software over a period of more than ten years. The Android features include a wide variety of metadata, which includes SHA256 hashes, file names, package names, compilation APIs, and various other details. This GitHub repository contains over 400GB of valuable data, making it the largest and most comprehensive dataset available for advancing research and development in Android malware detection.
DOI: 10.6084/m9.figshare.6962867.v1
title: First Draft genome for Pagrus major

description: The red sea bream (<i>Pagrus major</i>) belongs to the family of <i>Sparidea</i>, which includes 35 genera, 132 species and 10 subspecies. <i>Pagrus major</i> genome size was estimated as ~806 Mb using the <i>k-mer</i> method from 190.3 Gb of raw short read sequences, which were generated from Illumina sequencer . Furthermore, 73 Gb of long read sequences which were generated from PacBio sequencing method were assemble into 1657 contigs with the total size of 829.3 Mb with N50 &gt; 2.8 MB.
DOI: 10.17632/jkm5vdz42z
title: Identification of two protein-signaling states delineating transcriptionally heterogeneous human medulloblastoma

description: Dataset 1: Raw data
DOI: 10.17632/vsgsf5pnxf
title: Data for Urban Ecological Hazard-Risk Assessment in Delhi-National Capital Region

description: The satellite datasets were acquired from the openly available Google Earth Engine (GEE) platform from various satellites and sensors. The given dataset was used for computing the ecological hazard risk and vulnerability of Delhi-NCR region using 13 contributing variables, such as built-up density (Landsat; 2020), local climate zones (WUDAPT; 2022), green cover density (Landsat; 2020), rate of built-up growth (Landsat; from 1973 to 2020), loss of green cover (Landsat; 1973 to 2020), land surface temperature (Landsat; May 2022), PCA of biochemical and biophysical variables (Sentinel 2A; May 2022), road density, drainage density, slope and elevation (SRTM DEM), population growth, and population density (GHSL). All the above were prepared using 200x200 m grids and resampled at 10 m spatial resolution. Utilizing the fuzzy-AHP model, all the thematic layers were rescaled based on the weights, where a lower value of the variable indicates lower susceptibility and vice versa.
DOI: 10.6084/m9.figshare.20431536.v2
title: Augmented Reality in Spatial Navigation - literature review table

description: A review of published articles between 1997-2021 on augmented reality in spatial navigation
DOI: 10.6084/m9.figshare.23663979.v2
title: Pre-trained models

description: Pre-trained models for the deep-fus neural network implementation.
DOI: 10.6084/m9.figshare.29149106.v4
title: Dataset

description: this study investigates four decades of sedimentary and morphological changes in the Yangtze Estuary using an integrated framework. Drawing on grain size analysis, grain trend analysis, bathymetric data, and sediment budget calculations (e.g., sediment diversion ratio), we characterize temporal shifts in sediment transport and depocenter dynamics.
DOI: 10.17632/9x4hntz358
title: Assessing innovations for upscaling forest landscape restoration. Werden et al.

description: All data extracted for the analysis presented in Assessing innovations for upscaling forest landscape restoration, Werden et al. 2024.
DOI: 10.17632/g6rz752g3f
title: Operations management model based on 5S, TPM, and SMED to increase the effectiveness of equipment in a plastics company

description: Organizations strive to enhance their operational efficiency, addressing a key challenge faced by companies in the plastics industry: the limited availability of equipment, particularly in relation to molding processes. This equipment scarcity leads to delays in fulfilling customer orders, resulting in customer dissatisfaction. This research delves into the causes of prolonged setup and changeover times, as well as frequent interruptions during the injection molding process. Furthermore, it investigates the suboptimal performance of the injection molding machine, which currently operates at a mere 53.1% efficiency. To address this issue, a Lean Manufacturing model incorporating 5S, TPM, and SMED methodologies, along with standardization, is proposed. The objective is to improve the machine's effectiveness, as measured by the Overall Equipment Effectiveness (OEE) indicator.
DOI: 10.6084/m9.figshare.27135141.v2
title: <b>Digital Nudges and Self-Report Measures among New Gym Members: No Boost in Visits, but Intriguing Self-Reported Insights.</b>

description: This study examines the impact of digital nudges on weekly gym visits (WGVs) frequency and explores how self-reported exercise self-efficacy (ESE), exercise habit strength (EHS), and exercise adherence (EA) influence WGVs among new members.
DOI: 10.6084/m9.figshare.27645690.v2
title: facebook fact checking dataset

description: OverviewThe BuzzFeed dataset, officially known as the BuzzFeed-Webis Fake News Corpus 2016, comprises content from 9 news publishers over a 7-day period close to the 2016 US election. It was created to analyze the spread of misinformation and hyperpartisan content on social media platforms, particularly Facebook.Dataset CompositionNews Articles: The dataset includes 1,627 articles from various sources:<pre></pre>826 from mainstream publishers256 from left-wing publishers545 from right-wing publishersFacebook Posts: Each article is associated with Facebook post data, including metrics like share counts, reaction counts, and comment counts.<pre></pre>Comments: The dataset includes nearly 1.7 million Facebook comments discussing the news content.<pre></pre>Fact-Check Ratings: Each article was fact-checked by professional journalists at BuzzFeed, providing veracity assessments.<pre></pre>Key FeaturesPublisher Information: The dataset covers 9 publishers, including 6 hyperpartisan (3 left-wing and 3 right-wing) and 3 mainstream outlets.<pre></pre>Temporal Aspect: The data was collected over seven weekdays (September 19-23 and September 26-27, 2016).<pre></pre>Verification Status: All publishers included in the dataset had earned Facebook's blue checkmark, indicating authenticity and elevated status.<pre></pre>Metadata: Includes various metrics such as publication dates, post types, and engagement statistics.<pre></pre>Potential ApplicationsThe BuzzFeed dataset is valuable for various research and analytical purposes:News Veracity Assessment: Researchers can use machine learning techniques to classify articles based on their factual accuracy.<pre></pre>Social Media Analysis: The dataset allows for studying how news spreads on platforms like Facebook, including engagement patterns.<pre></pre>Hyperpartisan Content Study: It enables analysis of differences between mainstream and hyperpartisan news sources.<pre></pre>Content Strategy Optimization: Media companies can use insights from the dataset to refine their content strategies.<pre></pre>Audience Analysis: The data can be used for demographic analysis and audience segmentation.<pre></pre>This dataset provides a comprehensive snapshot of news dissemination and engagement on social media during a crucial period, making it a valuable resource for researchers, data scientists, and media analysts studying online information ecosystems.
DOI: 10.17605/osf.io/zfb5e
title: Trajectories of resilience and resilience factors in children, adolescents and young adults – a systematic review and meta-analysis

description: This preregistration is part of a PhD project using the ResiMETA database in order to examine trajectories of resilience and mental distress as well as resilience factors as their predictors in stressor-exposed children, adolescents and young adults.
DOI: 10.6084/m9.figshare.18738428.v1
title: Mouse 16S and Transcriptomic Datasets

description: This repository contains the processed 16S (L6) and transcriptome (count) data for murine experiments in the COPD multi-omics paper.
DOI: 10.6084/m9.figshare.24003885.v1
title: De novo assembly of the complete chloroplast genome of Solanum muricatum

description: Solanum muricatum chloroplast genome is given as its assembled nucleotide sequences (in fasta format), and we include the annotation information of the genomes (in genbank format).
DOI: 10.6084/m9.figshare.29104229.v1
title: Wikberg et al. Feeding benefits

description: Feeding collected during group scan and focal samples.
DOI: 10.17632/5pmnkshffm
title: Network traffic and code for machine learning classification

description: The dataset is a set of network traffic traces in pcap/csv format captured from a single user. The traffic is classified in 5 different activities (Video, Bulk, Idle, Web, and Interactive) and the label is shown in the filename. There is also a file (mapping.csv) with the mapping of the host's IP address, the csv/pcap filename and the activity label. Activities: Interactive: applications that perform real-time interactions in order to provide a suitable user experience, such as editing a file in google docs and remote CLI's sessions by SSH. Bulk data transfer: applications that perform a transfer of large data volume files over the network. Some examples are SCP/FTP applications and direct downloads of large files from web servers like Mediafire, Dropbox or the university repository among others. Web browsing: contains all the generated traffic while searching and consuming different web pages. Examples of those pages are several blogs and new sites and the moodle of the university. Vídeo playback: contains traffic from applications that consume video in streaming or pseudo-streaming. The most known server used are Twitch and Youtube but the university online classroom has also been used. Idle behaviour: is composed by the background traffic generated by the user computer when the user is idle. This traffic has been captured with every application closed and with some opened pages like google docs, YouTube and several web pages, but always without user interaction. The capture is performed in a network probe, attached to the router that forwards the user network traffic, using a SPAN port. The traffic is stored in pcap format with all the packet payload. In the csv file, every non TCP/UDP packet is filtered out, as well as every packet with no payload. The fields in the csv files are the following (one line per packet): Timestamp, protocol, payload size, IP address source and destination, UDP/TCP port source and destination. The fields are also included as a header in every csv file. The amount of data is stated as follows: Bulk : 19 traces, 3599 s of total duration, 8704 MBytes of pcap files Video : 23 traces, 4496 s, 1405 MBytes Web : 23 traces, 4203 s, 148 MBytes Interactive : 42 traces, 8934 s, 30.5 MBytes Idle : 52 traces, 6341 s, 0.69 MBytes The code of our machine learning approach is also included. There is a README.txt file with the documentation of how to use the code.
DOI: 10.17632/9p3kb6x4n7
title: Vibration datasets of beams subjected to free vibration using the smartphone's accelerometer

description: The vibration datasets were acquired from three rectangular beams (Aluminum, Brass, and Copper beams), with different properties and geometric specifications, and with different boundary conditions, as shown in the attached figure. The data collection was performed via the integrated smartphone accelerometer with the following specifications:

- The acquisition was performed using a smartphone with a sampling rate of 100Hz.
- The reference name of the smartphone accelerometer is BOSCH BMC150.
- The three beams have been subjected to free vibration by applying a load and removing it.
- The acquisition includes the vibration data in the vertical direction (Z-axis) according to the smartphone coordinate system.
- The data files contain 3 columns of data, where the first one is according to X-direction, the second is for Y-direction, and the third is for Z-direction (Z-axis).

The objective of this study is to extract the dynamic characteristics of the beams and compare them with the theoretical values in order to present an alternative instrument for mechanical and civil engineering students to practice their theoretical courses in structural vibration.

NB: 
- More details are included in the reference below.
- The reported datasets are entirely linked to the scientific article: "Dynamic characteristics of beams under free vibration using the smartphone - laboratory experiments for education",  So, it is recommended to read it.
DOI: 10.6084/m9.figshare.27966039.v1
title: Genome assembly and annotation of the allotetraploid wild grass <i>Aegilops ventricosa</i> RM271

description: Genome assembly and annotation of the allotetraploid wild grass <i>Aegilops ventricosa</i><i> </i>RM271, which has been published in https://doi.org/10.1016/j.xplc.2024.101131. All the raw sequencing data for <i>Ae. ventricosa</i> RM271 are available in the National Genomics Data Center (https://ngdc.cncb.ac.cn/?lang=en) under BioProject numbers PRJCA018801 (https://ngdc.cncb.ac.cn/bioproject/browse/PRJCA018801).
DOI: 10.17632/9rxg3tc8s2
title: Data, metrics, and methods for arthropod and fungal herbivory at the dawn of angiosperm diversification: The Rose Creek plant assemblage of Nebraska, U.S.A.

description: Raw data and data collection example