Twenty-three novel HLA-B alleles identified during intermediate-resolution testing

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65805/1/j.1399-0039.2006.00661.x.pd

Nonfinancial Barriers and Access to Care for U.S. Adults

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90354/1/hesr1308.pd

Labeling lateral prefrontal sulci using spherical data augmentation and context-aware training

The inference of cortical sulcal labels often focuses on deep (primary and secondary) sulcal regions, whereas shallow (tertiary) sulcal regions are largely overlooked in the literature due to the scarcity of manual/well-defined annotations and their large neuroanatomical variability. In this paper, we present an automated framework for regional labeling of both primary/secondary and tertiary sulci of the dorsal portion of lateral prefrontal cortex (LPFC) using spherical convolutional neural networks. We propose two core components that enhance the inference of sulcal labels to overcome such large neuroanatomical variability: (1) surface data augmentation and (2) context-aware training. (1) To take into account neuroanatomical variability, we synthesize training data from the proposed feature space that embeds intermediate deformation trajectories of spherical data in a rigid to non-rigid fashion, which bridges an augmentation gap in conventional rotation data augmentation. (2) Moreover, we design a two-stage training process to improve labeling accuracy of tertiary sulci by informing the biological associations in neuroanatomy: inference of primary/secondary sulci and then their spatial likelihood to guide the definition of tertiary sulci. In the experiments, we evaluate our method on 13 deep and shallow sulci of human LPFC in two independent data sets with different age ranges: pediatric (N=60) and adult (N=36) cohorts. We compare the proposed method with a conventional multi-atlas approach and spherical convolutional neural networks without/with rotation data augmentation. In both cohorts, the proposed data augmentation improves labeling accuracy of deep and shallow sulci over the baselines, and the proposed context-aware training offers further improvement in the labeling of shallow sulci over the proposed data augmentation. We share our tools with the field and discuss applications of our results for understanding neuroanatomical-functional organization of LPFC and the rest of cortex (https://github.com/ilwoolyu/SphericalLabeling). ?? 2021 The Author(s

Data about: Photogeneration, relaxation and many-body effects of excitons and charge carriers in MoS₂, WS₂, and the Mo₀.₆W₀.₄S₂ alloy, probed by transient optical absorption spectroscopy.

The samples studied in this dataset are of MoS2, WS2, and the Mo0.6W0.4S2 alloy. Transient absorption measurements are performed on these multilayered compounds. By varying the pump photon energies and pump photon fluences, we studied the generation and relaxation dynamics of the photogenerated charges and/or excitons. To understand the spectral dynamics in detail, fits are made to the obtained signal. The signal is probed in the visible region and the data set contains the relevant files. </p

Data about: Multiexciton generation in monolayer MoSe₂

In this dataset, transient absorption measurements are performed on a monolayer of MoSe₂. The goal of the measurements is to observe the process of multiexciton generation. To do so, the film is photoexcited at multiple pump energies and pump photon fluences. The film's response is probed in the visible region on time scales of sub-picoseconds to nanoseconds. The obtained response and experimental details are in the attached dataset.</p