20,451 research outputs found
Thermodynamic evidence for pressure-induced bulk superconductivity in the Fe-As pnictide superconductor CaFe2As2
We report specific-heat and resistivity experiments performed in parallel in
a Bridgman-type of pressure cell in order to investigate the nature of
pressure-induced superconductivity in the iron pnictide compound CaFe2As2. The
presence of a pronounced specific-heat anomaly at Tc reveals a bulk nature of
the superconducting state. The thermodynamic transition temperature differs
dramatically from the onset of the resistive transition. Our data indicates
that superconductivity occurs in the vicinity of a crystallographic phase
transition. We discuss the discrepancy between the two methods as caused by
strain-induced superconducting precursors formed above the bulk thermodynamic
transition due to the vicinity of the structural instability
Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis
We propose a novel denoising framework for task functional Magnetic Resonance
Imaging (tfMRI) data to delineate the high-resolution spatial pattern of the
brain functional connectivity via dictionary learning and sparse coding (DLSC).
In order to address the limitations of the unsupervised DLSC-based fMRI
studies, we utilize the prior knowledge of task paradigm in the learning step
to train a data-driven dictionary and to model the sparse representation. We
apply the proposed DLSC-based method to Human Connectome Project (HCP) motor
tfMRI dataset. Studies on the functional connectivity of cerebrocerebellar
circuits in somatomotor networks show that the DLSC-based denoising framework
can significantly improve the prominent connectivity patterns, in comparison to
the temporal non-local means (tNLM)-based denoising method as well as the case
without denoising, which is consistent and neuroscientifically meaningful
within motor area. The promising results show that the proposed method can
provide an important foundation for the high-resolution functional connectivity
analysis, and provide a better approach for fMRI preprocessing.Comment: 8 pages, 3 figures, MLMI201
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