Design of hollow core step-index antiresonant fiber with stepped refractive indices cladding.

With the benefits of low latency, wide transmission bandwidth, and large mode field area, hollow-core antiresonant fiber (HC-ARF) has been a research hotspot in the past decade. In this paper, a hollow core step-index antiresonant fiber (HC-SARF), with stepped refractive indices cladding, is proposed and numerically demonstrated with the benefits of loss reduction and bending improvement. Glass-based capillaries with both high (n = 1.45) and low (as low as n = 1.36) refractive indices layers are introduced and formatted in the cladding air holes. Using the finite element method to perform numerical analysis of the designed fiber, results show that at the laser wavelengths of 980 and 1064 nm, the confinement loss is favorably reduced by about 6 dB/km compared with the conventional uniform cladding HC-ARF. The bending loss, around 15 cm bending radius of this fiber, is also reduced by 2 dB/km. The cladding air hole radius in this fiber is further investigated to optimize the confinement loss and the mode field diameter with single-mode transmission behavior. This proposed HC-SARF has great potential in optical fiber transmission and high energy delivery.

Deep transfer learning for characterizing chondrocyte patterns in phase contrast X-Ray computed tomography images of the human patellar cartilage.

Phase contrast X-ray computed tomography (PCI-CT) has been demonstrated to be effective for visualization of the human cartilage matrix at micrometer resolution, thereby capturing osteoarthritis induced changes to chondrocyte organization. This study aims to systematically assess the efficacy of deep transfer learning methods for classifying between healthy and diseased tissue patterns. We extracted features from two different convolutional neural network architectures, CaffeNet and Inception-v3 for characterizing such patterns. These features were quantitatively evaluated in a classification task measured by the area (AUC) under the Receiver Operating Characteristic (ROC) curve as well as qualitative visualization through a dimension reduction approach t-Distributed Stochastic Neighbor Embedding (t-SNE). The best classification performance, for CaffeNet, was observed when using features from the last convolutional layer and the last fully connected layer (AUCs >0.91). Meanwhile, off-the-shelf features from Inception-v3 produced similar classification performance (AUC >0.95). Visualization of features from these layers further confirmed adequate characterization of chondrocyte patterns for reliably distinguishing between healthy and osteoarthritic tissue classes. Such techniques, can be potentially used for detecting the presence of osteoarthritis related changes in the human patellar cartilage.

[QTL mapping for contents of main carotenes and lycopene in carrot (Daucus carota L.)].

An F2 population derived from two carrot inbred lines, P50006 and HCM A.C. with high carotene accumulation, was developed and used to map and analyze quantitative trait locus (QTL) associated with the accumulation of alpha and beta-carotene, total carotene and lycopene. Broad-sense heritabilities of these traits were 0.75, 0.50, 0.31, and 0.93, respectively. A genetic map with 91 SRAP (Sequence-related amplified polymorphism) markers was developed, which spanned 502.9 cM in 9 linkage groups with a mean marker interval of 5.5 cM. Mixed-model-based composite interval mapping was performed to analyze QTL and epistasis effects. One major QTL each for beta-carotene, total carotene and lycopene accumulation were detected which can explain 12.79%, 12.87%, and 14.61% of total phenotypic variations, respectively. Additive genetic variance was primarily responsible for genetic variability in all three major QTL. In addition, a pair of epistasis QTL for beta-carotene and lycopene accumulation was detected, which were able to explain 15.1% and 6.5% of total phenotypic variation, respectively. The dominant x additive and dominant x dominant interaction variance were primary epistasis effect for beta-carotene and lycopene. These SRAP markers linked to QTL could be used in selection or QTL pyramiding for high carotene and lycopene content in carrot breeding.