AcneTyper: An automatic diagnosis method of dermoscopic acne image via self-ensemble and stacking.

Background: Acne is a skin lesion type widely existing in adolescents, and poses computational challenges for automatic diagnosis. Computer vision algorithms are utilized to detect and determine different subtypes of acne. Most of the existing acne detection algorithms are based on the facial natural images, which carry noisy factors like illuminations.

AcneGrader: An ensemble pruning of the deep learning base models to grade acne.

Background: Acne is one of the most common skin lesions in adolescents. Some severe or inflammatory acne leads to scars, which may have major impacts on patients' quality of life or even job prospects. Grading acne plays an important role in diagnosis, and the diagnosis is made by counting the number of acne.

DiaMole: Mole Detection and Segmentation Software for Mobile Phone Skin Images.

Results: This study developed mole detection and segmentation software DiaMole using mobile phone images. DiaMole utilized multiple deep learning algorithms for the object detection problem and mole segmentation problem. An object detection algorithm generated a rectangle tightly surrounding a mole in the mobile phone image.

Chemical vapor deposition of thin crystals of layered semiconductor SnS2 for fast photodetection application.

Layered two-dimensional (2D) semiconductors, such as MoS(2) and SnS(2), have been receiving intensive attention due to their technological importance for the next-generation electronic/photonic applications. We report a novel approach to the controlled synthesis of thin crystal arrays of SnS(2) at predefined locations on chip by chemical vapor deposition with seed engineering and have demonstrated their application as fast photodetectors with photocurrent response time ∼ 5 μs. This opens a pathway for the large-scale production of layered 2D semiconductor devices, important for applications in integrated nanoelectronic/photonic systems.

Multiscale simulation on a light-harvesting molecular triad.

We have investigated the effect of solvation and confinement on an artificial photosynthetic material, carotenoid-porphyrin-C(60) molecular triad, by a multiscale approach and an enhanced sampling technique. We have developed a combined approach of quantum chemistry, statistical physics, and all-atomistic molecular dynamics simulation to determine the partial atomic charges of the ground-state triad. To fully explore the free energy landscape of triad, the replica exchange method was applied to enhance the sampling efficiency of the simulations.