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Qualitative research in health care: Analysing qualitative data
This is the second in a series of three articles Contrary to popular perception, qualitative research can produce vast amounts of data. These may include verbatim notes or tra...
Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration
Much medical research is observational. The reporting of observational studies is often of insufficient quality. Poor reporting hampers the assessment of the strengths and weakn...
Inference of Population Structure Using Multilocus Genotype Data: Linked Loci and Correlated Allele Frequencies
Abstract We describe extensions to the method of Pritchard et al. for inferring population structure from multilocus genotype data. Most importantly, we develop methods that all...
Organizational Learning: The Contributing Processes and the Literatures
This paper differs from previous examinations of organizational learning in that it is broader in scope and more evaluative of the literatures. Four constructs related to organi...
Lead Iodide Perovskite Sensitized All-Solid-State Submicron Thin Film Mesoscopic Solar Cell with Efficiency Exceeding 9%
We report on solid-state mesoscopic heterojunction solar cells employing nanoparticles (NPs) of methyl ammonium lead iodide (CH(3)NH(3))PbI(3) as light harvesters. The perovskit...
Cancer statistics, 2024
Abstract Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population‐based c...
The MR-Base platform supports systematic causal inference across the human phenome
Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SM...
WHO Declares COVID-19 a Pandemic.
The World Health Organization (WHO) on March 11, 2020, has declared the novel coronavirus (COVID-19) outbreak a global pandemic (1). At a news briefing , WHO Director-General, D...
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complex data. We consider the problem of constructing a rep...