cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/s4ydf6kb8y.1
title: Association of food insecurity on gut microbiome and metabolome profiles in a diverse college-based sample

description: Voluntary caloric restriction (e.g., eating disorders) often results in alterations in the gut microbiota composition and function. However, these findings may not translate to food insecurity, where an individual experiences inconsistent access to healthy food options. In this study we compared the fecal microbiome and metabolome of racially and ethnically diverse first year college students (n=60) experiencing different levels of food access. Students were dichotomized into food secure (FS) and food insecure (FI) groups using a validated, 2-question screener assessing food security status over the previous 30 days. Fecal samples were collected up to 5 days post survey-completion. Gut microbiome and metabolome were established using 16S rRNA amplicon sequencing, targeted liquid chromatography-tandem mass spectrometry, and gas chromatography-mass spectrometry. FI students experienced significantly greater microbial diversity with increased abundance of Enterobacteriaceae and Eisenbergiella, while FS students had greater abundance of Megasphaera and Holdemanella. Metabolites related to energy transfer and gut-brain-axis communication (picolinic acid, phosphocreatine, 2-pyrrolidinone) were elevated in FI students (q < 0.05). These findings suggest that food insecurity is associated with differential gut microbial and metabolite composition for which the future implications are unknown. Further work is needed to elucidate the longitudinal metabolic effects of food insecurity and how gut microbes influence metabolic outcomes.
DOI: 10.17632/d9899vc48f.1
title: Distributional impacts of cash transfers on the multidimensional poverty of refugees: The Emergency Social Safety Net in Turkey

description: This code accompanies the paper Robson, Vollmer, Doğan & Grede, (2024), “Distributional Impacts of Cash Transfers on the Multidimensional Poverty of Refugees: The Emergency Social Safety Net in Turkey”, World Development. In the paper, we analyse the impact of the Emergency Social Safety Net (ESSN) cash programme on the multidimensional poverty of refugees in Turkey, using a purpose-built Refugee Multidimensional Poverty Index. We conduct a causal analysis of both average and distributional impacts of the ESSN on the incidence and intensity of multidimensional poverty, and decompose effects for separate dimensions and indicators of poverty. Here, we provide code for the paper in R and Stata. In the R Script, we include programmes to estimate probabilistic potential outcomes, using the beta-binomial distribution. The data we used was the Comprehensive Vulnerability Monitoring Exercise (CVME), is a confidential, so is not uploaded here. Please contact us if you have any questions.
DOI: 10.15468/dl.x4ravf
title: Occurrence Download

description: A dataset containing 74040 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Biological Collection of the National Taiwan Museum, Taipei, Taiwan"
 ]
}

 The dataset includes 74040 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009319-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/y4j3zyfxtb.1
title: Digital study materials - Santangelo et al. (2020) Cortex

description: There is a growing consensus on the role played by the hippocampus and the medial prefrontal cortex in autobiographical memory. However, it is not clear whether and how these key regions play a central role in enabling forms of enhanced memory, such as highly superior autobiographical memory (HSAM). Here, we investigated the role of the hippocampus, the ventromedial (vmPFc) and dorsomedial (dmPFc) prefrontal cortices in discriminating older vs. newer autobiographical events in a group of rare individuals with HSAM through multivoxel pattern analysis of functional neuroimaging data. During fMRI scanning, participants with HSAM and normal memory controls were asked to recollect remote and more recent events. We found a stronger neural signature of older vs. newer autobiographical memories within the vmPFc of HSAM subjects as compared to controls. In this brain region, the discriminability between the multivariate neural patterns of the two types of memories increased as a function of the temporal distance that separated older and newer events in HSAM subjects. Comparable neural patterns of older vs. newer memories were found instead within the dmPFc and hippocampus of both groups. Overall, these findings highlight for the first time that HSAM relies on enhanced vmPFc specialization to represent past experiences, therefore contributing to uncover the neurobiological mechanisms potentially enabling enhanced forms of memory. Implications of the current findings for the extant models of autobiographical memory are discussed.
DOI: 10.17632/snkd93bnjr.1
title: A dataset for microscopic peripheral blood cell images for development of automatic recognition systems

description: The dataset contains a total of 17,092 images of individual normal cells, which were acquired using the analyzer CellaVision DM96 in the Core Laboratory at the Hospital Clinic of Barcelona. The dataset is organized in the following eight groups: neutrophils, eosinophils, basophils, lymphocytes, monocytes, immature granulocytes (promyelocytes, myelocytes, and metamyelocytes), erythroblasts and platelets or thrombocytes. The size of the images is 360 x 363 pixels, in format JPG, and they were annotated by expert clinical pathologists. The images were captured from individuals without infection, hematologic or oncologic disease and free of any pharmacologic treatment at the moment of blood collection. This high-quality labelled dataset may be used to train and test machine learning and deep learning models to recognize different types of normal peripheral blood cells. To our knowledge, this is the first publicly available set with large numbers of normal peripheral blood cells, so that it is expected to be a canonical dataset for model benchmarking.
DOI: 10.17632/t9tkghy3w6.1
title: Data for:Reconstructing the source and growth of the Makran Accretionary Complex: Constraints from detrital zircon U-Pb geochronology

description: Supporting information for this paper includes: Figure S1- Plane and crossed polarized light microphotographs of the analyzed samples. Figure S2- Classification of the detrital sandstones from the Makran ophiolitic complex in the provenance discrimination diagrams. Figure S3- Concordia diagrams of samples 16R59,16R64, 16R65, 16R67 from the Makran ophiolitic mélange. Figure S4- Concordia diagrams of samples, 16R68, 16R80, 16R84and 16R86 from the Makran ophiolitic mélange. Table S1- Sandstone framework model for detritus of Makran ophiolitic mélange complex. Table S2- Zircon U-Pb age data for the OMC detrital zircons. Table S3- Zircon Lu-Hf isotope data and model ages for the OMC detrital zircons.
DOI: 10.17632/xgw6bg3g8h.1
title: Dataset for gait analysis and assessment of fall risk for older adults

description: This five-part dataset is intended for human gait analysis in an older adult population (37 women and seven men; age 69.98 ± 8.57 years, body mass index 27.71 ± 4.57). Part 1 compromises demographic data for the 44 participants, along with the results of the Short Physical Performance Battery (SPPB) motor function test and the Mini-Mental State Examination (MMSE). We used the MMSE to ensure the participants could understand the experimental protocol instructions. Part 2 presents the anthropometric measurements of the participants. Part 3 shows the results for each item of the Gait component of the Performance Oriented Mobility Assessment (POMA-G). Part 4 contains five files per participant, storing motion-capture data for the lower limb in the Coordinate 3D (C3D) format. These files were generated using a Vicon motion analysis system, consisting of 24 reflective markers and seven cameras (Vantage V5) sampled at 100 Hz. Part 5 contains 26 gait parameters for each C3D file obtained using Nexus 2.9.3.
DOI: 10.17632/94ksjgbwnz.1
title: MBD: Multi-Biometric Dataset

description: This dataset includes samples of fingerprint, finger vein, iris and thermal face images
DOI: 10.17632/63sms5tr7z.1
title: Value Premium and Macroeconomic Variables

description: Stata scripts to replicate the main results of the paper
DOI: 10.17632/np54zjkvxr.2
title: Dataset for: Clonal dynamics of haematopoiesis across the human lifespan

description: These are the datasets to support the manuscript (updated 9th August, 2022 to replace corrupted file in original submission):

Clonal dynamics of haematopoiesis across the human lifespan

Emily Mitchell1,2,3, Michael Spencer Chapman1,#, Nicholas Williams1,#, Kevin J Dawson1,#, Nicole Mende2, Emily F Calderbank2, Hyunchul Jung1, Thomas Mitchell1, Tim Coorens1, David H Spencer4, Heather Machado1, Henry Lee-Six1, Megan Davies5, Daniel Hayler2, Margarete Fabre1,2,3, Krishnaa Mahbubani6,7, Fede Abascal1, Alex Cagan1, George Vassiliou1,2,3, Joanna Baxter3, Inigo Martincorena1, Michael R Stratton1, David Kent8, Krishna Chatterjee9, Kourosh Saeb Parsy6,7, Anthony R Green2,3, Jyoti Nangalia1,2,3*, Elisa Laurenti2,3*, Peter J Campbell1,2*.

# These authors contributed equally.
* These authors contributed equally.

Affiliations

(1)	Wellcome Sanger Institute, Hinxton, CB10 1SA, UK.
(2)	Wellcome-MRC Cambridge Stem Cell Institute, Cambridge Biomedical Campus, Cambridge, CB2 0AW, UK.
(3)	Department of Haematology, University of Cambridge, Cambridge, CB2 2XY, UK.
(4)	Department of Medicine, McDonnell Genome Institute, Washington University, St. Louis, MO, USA.
(5)	Cambridge Molecular Diagnostics, Milton Road, Cambridge, CB4 0FW, UK.
(6)	Department of Surgery, University of Cambridge, Cambridge, CB2 0QQ, UK.
(7)	Cambridge Biorepository for Translational Medicine, NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge CB2 2XY, UK.
(8)	York Biomedical Research Institute, Department of Biology, University of York, York, YO10 5DD, UK.
(9)	Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK.
DOI: 10.17632/t2pzcb37y8.1
title: Pan-genome data for the genes in "Prediction of antibiotic resistance in Escherichia coli from large-scale pan-genome data"

description: The pan-genome data for the paper under review. Files are in fasta format.
DOI: 10.17632/xv6fk2mmh9.1
title: Data files: GenAI Detection Tools, Adversarial Techniques and Implications for Inclusivity in Higher Education

description: This data consists of samples of human and AI generated short form content in the form of MS Word files. AI generated samples are subjected to adversarial techniques to evade content detection by GenAI text detectors. Our accompanying paper 'GenAI Detection Tools, Adversarial Techniques and Implications for Inclusivity in Higher Education' discusses the results of the testing. This data can be used to test how effective AI text detectors are at determining whether a sample is human or machine generated. We identify how the application of adversarial techniques reduces the ability of AI text detectors to accurately determine the source of the sample.
DOI: 10.17632/yjz85cb3m7.1
title: Covid-19 Student Marks

description: Student Marks in English and non-English subjects, before and after Covid-19
DOI: 10.17632/fcgrnj2jvf.1
title: Trends in the Digital marketing research

description: All 1604 Publications on the topic of the Digital marketing research on Scopus for bibliometric analysis!
DOI: 10.17632/9n4s2mng7x.1
title: Supplementary Data for Cholesterol Metabolite 27-Hydroxycholesterol Enhances the Secretion of Extracellular Vesicles by a Mitochondrial ROS-Induced dysregulation of Lysosomes

description: This is Supplementary Data for the manuscript "Cholesterol Metabolite 27-Hydroxycholesterol Enhances the Secretion of Extracellular Vesicles by a Mitochondrial ROS-Induced dysregulation of Lysosomes"
DOI: 10.17632/8smtb27h5j.1
title: Bank Specific Factors And Non-performing Loans of Commercial Banks In Liberia

description: This study investigates the nexus between bank-specific factors and nonperforming loans (NPLs) in Liberia's commercial banks through a retrospective panel study design, employing a quantitative approach based on the Moral Hazard Theory. Targeting the nine listed commercial banks in Liberia, the study focuses on key variables: return on equity (ROE), return on assets (ROA), bank cost efficiency, and bank income diversification. Data were sourced from certified audited records, and descriptive statistics, including correlation analysis via SPSS software, were applied. Results reveal a significant negative correlation (r = -0.957, p = 0.043) between ROE and NPLs at LBDI Bank. Conversely, no significant associations are found between ROA, bank cost efficiency, and bank income diversification with NPLs in commercial banks. The study underscores the centrality of ROE in influencing NPLs and recommends future research to incorporate a broader spectrum of both bank-specific and economic factors over an extended study period of 10-15 years for a comprehensive understanding of nonperforming loans in Liberia's commercial banks.
DOI: 10.17632/7jmgfk4fd9.1
title: A Dataset for Multimodal Music Information Retrieval of Sotho-Tswana Music Videos

description: The dataset is a multimodal dataset for music information retrieval of under-resourced Sotho-Tswana language. The MIR tasks for which the dataset can be used for, include multimodal music sentiment analysis, multimodal music genre classification, multimodal language identification in music videos, and recommender systems. Although the primary source of the musical videos is YouTube, several processes have been performed on the dataset, such as segmentation, separation of the audio modality from the visual modality, and extraction of spectral-based acoustic features, together with enriched manual annotations of the following metadata, language, genre, lyrics and meaning of song. The dataset is ideal for training deep learning models, and the recommended fusion method for combining the features of the audio and visual modalities is the decision-level (late) fusion method. In addition to the musical video clips, part of the dataset includes various CSV files and Jupyter notebooks.
DOI: 10.17632/yy7hxp5td4.1
title: Arsenic Trioxide Rescues Structural p53 Mutations through a Cryptic Allosteric Site

description: TP53 is the most frequently mutated gene in cancer, yet these mutations remain therapeutically non-actionable. Major challenges in drugging p53 mutations include heterogeneous mechanisms of inactivation and the absence of broadly-applicable allosteric sites. Here we report the identification of small molecules including arsenic trioxide (ATO), an established agent in treating acute promyelocytic leukemia, as cysteine-reactive compounds that rescue structural p53 mutations. Crystal structures of arsenic-bound p53 mutants reveal a cryptic allosteric site involving three arsenic coordinating cysteines within the DNA-binding domain, distal to the zinc-binding site. Arsenic binding stabilizes the DNA-binding loop-sheet-helix motif alongside the overall β-sandwich fold, endowing p53 mutants with thermostability and transcriptional activity. In cellular and mouse xenograft models, ATO reactivates mutant p53 for tumor suppression. Investigation of the most frequent twenty-five p53 mutations informs patient stratification for clinical exploration. Our results provide mechanistic basis for repurposing ATO to target p53 mutations for widely-applicable yet personalized cancer therapies.
DOI: 10.17632/mfky2jttwp.3
title: Low back pain and associated risk factors among medical students in Bangladesh: A cross-sectional study

description: Background: Low back pain (LBP) is one of the leading causes of disability worldwide. Different studies showed the high prevalence of LBP among medical students. However, no study has been conducted on Bangladeshi medical students. Objective: This study evaluated the prevalence, characteristics, and associated risk factors among medical students in Bangladesh. Materials and Methods: A cross-sectional study was conducted from October to December 2020 among randomly selected 240 medical students and medical interns in Faridpur Medical College, Bangladesh, using an online questionnaire. In data analysis, chi-square test and binary logistic regression were performed, and a p-value of &lt; 0.05 was regarded as statistically significant. Results: A total of 207 participants responded, with a response rate of 82.8%. The mean age of the participants was 22.36 ± 1.915 years. The point, 6-month, and 12-month prevalence of LBP was 25.6%, 46.9%, and 63.3%, respectively. In most participants, LBP was localized (53.2%), recurrent (64.9%), undiagnosed (70.8%), affected for a short period (55%), and relieved without taking any treatment (60.4%). Participants who had a significantly higher 12-month prevalence of LBP included females (72.2% vs 52.2%), with BMI &gt;25 kg/m2 (73.2% vs 56.7%), those who performed physical activity at low to moderate frequency (72.4% vs 29.5%), those who spent &gt; 6 hours/day by sitting (71.3% vs 45.3%), and those who did not have enough rest time (92.7% vs 56%). Ergonomic features of chairs, such as having back support, adjustable back support, and adjustable sitting surface, significantly (p &lt; 0.05) influenced the outcomes. Conclusion: The prevalence of LBP among medical students in Bangladesh was high, and most of the risk factors associated with the high prevalence of LBP were modifiable. Hence, LBP can be prevented by implementing preventive strategies and providing ergonomic training and physical activity facilities.
DOI: 10.17632/2hthy8r3dt.1
title: Assessing the asymmetric war-growth nexus in Afghanistan

description: This dataset has been collected from the WDI (World Development Indicators) and the US Department of Defense and used for empirical analysis and test of competing hypotheses on the asymmetric nexus and effects of civil wars on the economic growth in Afghanistan.
DOI: 10.17632/5rkzmm35c2.1
title: Data for: New Assay to Diagnose and Differentiate between Mycobacterium tuberculosis complex and Nontuberculous mycobacteria

description: This is a data set, uploaded in response to Reviewer 2.
DOI: 10.17632/z3wnfnck7t.1
title: Hospitals in New York City, U.S.

description: Introduction
This data shows the places of hospitals. We found a hospital in Manhattan in nyc and mapped it out. It would be very helpful in case of an emergency to know in advance where the hospitals are located and whether or not they have ICUs.
Data
This data was collected and produced from a single source. 
Hospitals in NYC from October 2023 were identified using facility searches for Google Map.
The data were then geocoded using ArcGIS Online software for visualization.
Results
There are about 11 large hospitals in Manhattan, New York. In addition, there  are 4 Intensive Care Unit in NYC : NYC Health + Hospitals / Metropolitan, NewYork-Presbyterian Lower Manhattan Hospital, NYU Langone Health, Lenox Hill Hospital.

Conclusion 
When you are shopping or dining in New York and suddenly become ill or feel badly, if you have this data you can get to the hospital without having to use an ambulance. This data will not only contribute to your safe and secure trip, but will even eliminate your unnecessary expenses.
DOI: 10.17632/yk8wj7xgdg.1
title: Immunostimulatory cancer-associated fibroblast subpopulations can predict immunotherapy response in head and neck cancer

description: RNA-Sequencing Data Associated with the manuscript "Immunostimulatory cancer-associated fibroblast subpopulations can predict immunotherapy response in head and neck cancer." Includes integrated single-cell RNA-Sequencing data & VIPER inferred protein activity matrix uploaded as Seurat Objects with patient and cluster metadata included, as well as sub-clustered fibroblast Seurat object and spatial geomx data. Also includes bulk RNA-Sequencing datasets of responders vs non-responders to treatment and bulk RNA-Sequencing datasets of sorted fibroblast populations used for cluster phenotyping and ex vivo co-culture experiments.
DOI: 10.17632/mg6hf878mv.1
title: Data for: Trust or social preferences? A cross-cultural experiment.

description: Data set from economic games
DOI: 10.17632/jcvsm27smf.1
title: Capsule hotel Data

description: Service experience in capsule hotels from Tripadvisor
DOI: 10.17632/nvxjm84n6f.1
title: Mobile Applications images & Logos

description: A mobile applications images and logos dataset typically consists of a collection of images representing the logos or user interfaces of various mobile apps. These datasets are commonly used for tasks such as logo recognition, mobile app classification, brand detection, and user interface analysis in the fields of computer vision and machine learning.
Dataset Components:
Images of Logos: This includes a wide variety of app logos, ranging from popular apps to lesser-known ones. Logos can be in different formats (e.g., PNG, JPG) and may vary in size and resolution. The dataset might contain both full-color logos and monochrome variations.

App Icons: Apart from the logo, the dataset may contain app icons as they appear on mobile devices' home screens. These icons are typically square or rounded in shape, with resolutions like 512x512 or 1024x1024 pixels.

User Interface (UI) Screenshots: Some datasets also include screenshots of the mobile app’s interface, capturing various screens like the home screen, settings, or functional pages. This component is useful for UI/UX analysis, app design comparison, or screen element recognition.

Class Labels: Each image in the dataset is usually associated with metadata or labels. These labels may include:

App Name: The name of the mobile application.
Category: The app’s category (e.g., Social Media, Finance, Gaming, etc.).
Brand Name: The brand associated with the app (e.g., Facebook, Twitter).
Platform: The operating system for which the app was developed (iOS, Android).
Resolution: The size or pixel dimensions of the image.
Image Annotations: Some datasets may provide additional annotations, such as bounding boxes around logos or key design elements. These annotations are essential for object detection or logo localization tasks.

Typical Uses:
Logo Recognition: Mobile app logos are used in machine learning algorithms to recognize brands or products automatically from images or videos.

App Classification: The dataset can help classify images of app interfaces into predefined categories, such as social media, gaming, or finance.

Brand Analysis: The dataset allows researchers to study how logos evolve over time, or how brand identity is reflected in app icons.

User Interface (UI) Research: UI screenshots can be analyzed to understand app design patterns, common layouts, or usability across different categories of mobile applications.

Collection Process:
Web Scraping: App logos, icons, and UI screenshots are often collected from app stores (Google Play, Apple App Store) through web scraping techniques.

Manual Curation: In some cases, datasets are manually curated, where researchers download app images and organize them according to specific categories or criteria.
DOI: 10.17632/5kbjrgsncf.2
title: Medical Imagining (CT scan, MRI, X-ray, and Microscopic Imagery) Data

description: The respective data is comprised of 5 different datasets of medical images collected by the contributors, which can be used for classifying Lung Cancer, Bone Fracture, Brain tumor, Skin Lesions, and Renal Malignancy, respectively. The data also includes multiple disease and malignancy images for the respective dataset. 
The classification for the diseases can be done by using ResNet50 CNN architecture and other DCNN models. This data is also been used in a research article by the contributor.