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  • Data set of DLV code and simulation algorithms of ProPrivacy
    Data Types:
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    • Dataset
    • File Set
  • See the paper related to these dataset
    Data Types:
    • Software/Code
    • Image
    • Dataset
  • This repository provides the supplementary R code and data to reproduce the experiments in the following paper : "Highly accurate diagnosis of papillary thyroid carcinomas based on personalized pathways coupled with machine learning ". These include: 1. The main method function R file 2. The main script R file 3. The datasets for the development/validation cohorts (R data file format) 4. The pathway information (R data file format)
    Data Types:
    • Software/Code
    • Dataset
  • Data related to the publication: "A Map of Human Type 1 Diabetes Progression by Imaging Mass Cytometry". Damond N, Engler S, Zanotelli VRT, Schapiro D, Wasserfall CH, Kusmartseva I, Nick HS, Thorel F, Herrera PL, Atkinson MA and Bodenmiller B. Cell Metab. 2019 Mar 5;29(3):755-768.e5. https://doi.org/10.1016/j.cmet.2018.11.014 We used imaging mass cytometry to simultaneously image 37 biomarkers with single-cell and spatial resolution in pancreas sections from 12 human donors at different stages of type 1 diabetes. CODE: - Python script for coordinate transformation - Functions for custom histoCAT neighborhood analysis DATA: - Single-cell data - Islet-level data - Cell type information - Cell relationships (cell-cell neighborhoods and cell-islet relationships) - Donors and image metadata. - Subset containing the data for 100 images from 3 donors IMAGES: - Image stacks (37 channels) for all donors (one .7z file per donor, numbers indicate nPOD case IDs) - Cell masks - Panel file with information related to antibodies and metal tags - Metadata file linking donor information to images - Metadata file linking image stack slices and panel information - Subset containing 100 images from 3 donors
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • File Set
  • Data set for 'SPACE SYNTAX AND THE HISTORIC URBAN CORE OF ŁÓDŹ' article Author: Mariusz Lamprecht, PhD, Institute of the Built Environment and Spatial Policy, Faculty of Geographical Sciences, University of Łódź mariusz.lamprecht@geo.uni.lodz.pl
    Data Types:
    • Other
    • Software/Code
    • Geospatial Data
    • Tabular Data
    • Dataset
    • Document
    • File Set
  • This dataset contains information from the Colombian (2016-2017) Time-Use Survey (ENUT in Spanish) and Mexican (2014)Time-Use Survey. It contains unpaid housework and income information, at the household level, of "pure" working-class households, i.e., households with only waged workers.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
  • Title of article: Hidden properties of city plans. A case study of Łódź Author: Mariusz Lamprecht, PhD, Institute of the Built Environment and Spatial Policy, Faculty of Geographical Sciences, University of Łódź mariusz.lamprecht@geo.uni.lodz.pl The set of data presented in the article in figures 3-12 (shp files).
    Data Types:
    • Other
    • Software/Code
    • Geospatial Data
    • Tabular Data
    • Dataset
    • Document
    • File Set
  • There is a perpetual challenge of nurse retention in rural areas in many countries and has major consequences on the accessibility of health services in rural areas. The focus of the study will be in central Alberta. The purpose of this research is to identify the factors that affect nurse retention and how the organizational culture and academic preparation affect nurse retention in rural areas. Additionally, this exploration will be key in identifying strategies that may be utilized in dealing with the nurse retention. Mixed methodology will be utilized in this research including the following steps: a qualitative method comprising of initial set of interviews, followed by a survey from a larger sample of registered nurses who graduated within the last 2 years. The questions in the survey will be informed by the responses from the initial interviews. Literature review on rural nursing retention and recruitment challenge will be done on studies that have been done on this subject matter in other jurisdictions within rural and urban Canada. Gaps will be identified in the studies that have been done. Findings from the study will be shared with AHS for consideration and will inform the need for future studies in this subject area. Keywords: retention and recruitment, organizational factors, academic factors, qualitative themes, qualitative data, mixed methodology
    Data Types:
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    • Dataset
  • Questionário e Banco de Dados referentes ao artigo "Fatores que influenciam a participação dos consumidores no Turismo Eletrônico", publicado pela Revista Brasileira de Pesquisa em Turismo - RBTUR.
    Data Types:
    • Software/Code
    • Dataset
    • Document
  • Here are all the raw data about the study of "Decoding and Systematization of Medical Imaging Features of Multiple Human Malignancies". Including the proposed correlation atlas to clarify the relationship between medical imaging features and human malignancies, and the CT image dataset of 1000 lung cancer patients for discovering the pattern of distribution of values of the texture features and explaining the visual difference of different image feature values, and all of the source code of this study.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • File Set