Simulation of photodetection using finite-difference time-domain method with application to near-field subwavelength imaging based on nanoscale semiconductor photodetector array

Simulation of detecting photoelectrons using multi-level multi-electron (MLME) finite-difference time-domain (FDTD) method with an application to near-field subwavelength imaging based on semiconductor nanophotodetector (NPD) array is reported. The photocurrents from the photodiode pixels are obtained to explore the resolution of this novel NPD device for subwavelength imaging. One limiting factor of the NPD device is the optical power coupling between adjacent detector pixels. We investigate such power coupling in the presence of absorbing media as well as the spatial distributions of the electric field and photoelectron density using the MLME FDTD simulation. Our results show that the detection resolution is about one tenth of the operating wavelength, which is comparable to that of a near-field scanning optical microscope based on metal clad tapered fiber.Comment: 7 pages, 4 figure

CG-fusion CAM: Online segmentation of laser-induced damage on large-aperture optics

Online segmentation of laser-induced damage on large-aperture optics in high-power laser facilities is challenged by complicated damage morphology, uneven illumination and stray light interference. Fully supervised semantic segmentation algorithms have achieved state-of-the-art performance, but rely on plenty of pixel-level labels, which are time-consuming and labor-consuming to produce. LayerCAM, an advanced weakly supervised semantic segmentation algorithm, can generate pixel-accurate results using only image-level labels, but its scattered and partially under-activated class activation regions degrade segmentation performance. In this paper, we propose a weakly supervised semantic segmentation method with Continuous Gradient CAM and its nonlinear multi-scale fusion (CG-fusion CAM). The method redesigns the way of back-propagating gradients and non-linearly activates the multi-scale fused heatmaps to generate more fine-grained class activation maps with appropriate activation degree for different sizes of damage sites. Experiments on our dataset show that the proposed method can achieve segmentation performance comparable to that of fully supervised algorithms

Discrepant diversity patterns and function of bacterial and fungal communities on an earthquake-prone mountain gradient in Northwest Sichuan, China

Patterns of microbial diversity on elevational gradients have been extensively studied, but little is known about those patterns during the restoration of earthquake-fractured alpine ecosystems. In this study, soil properties, soil enzyme activities, abundance and diversity of soil bacterial and fungal communities at four positions along a 2.6-km elevational gradient in the Snow Treasure Summit National Nature Reserve, located in Pingwu County, Southwest China. Although there were no significant changes in the soil chemical environment, bacterial and fungal communities were significantly different at different elevations. The overall fungal community presented an N-shaped diversity pattern with increasing elevation, while bacterial diversity decreased significantly with elevation. Changes in microbial diversity were associated with soil phosphorus, plant litter, and variations in dominant microbial taxa. Differences in enzyme activities among elevations were regulated by microbial communities, with changes in catalase and acid phosphatase activities mainly controlled by Acidobacteria and Planctomycetaceae bacteria, respectively (catalase: p < 0.001; acid phosphatase: p < 0.01), and those in β-glucosidase, sucrase, and urease activities mainly controlled by fungi. The β-glucosidase and sucrase were both positively correlated with Herpotrichiellaceae, and urease was positively correlated with Sebacinaceae (p < 0.05). These findings contribute to the conservation and management of mountain ecosystems in the face of changing environmental conditions. Further research can delve into the specific interactions between microbial communities, soil properties, and vegetation to gain deeper insights into the intricate ecological dynamics within earthquake-prone mountain ecosystems

Cross-Database Analysis Reveals Sensitive Biomarkers for Combined Therapy for ERBB2+ Gastric Cancer

Exploring ERBB2-related pathways will help us finding sensitive molecules and potential combined therapeutic targets of ERBB2-targeted therapy for ERBB2+ gastric cancer (GC). In this study, we performed a cross-databases study focused on ERBB2+ GC. The data of ERBB2+ GC deposited in the cancer genome atlas (TCGA), gene expression omnibus (GEO), InBio MapTM, cancer cell line encyclopedia (CCLE), and cancer therapeutics response portal (CTRP) were analyzed. The correlation of expression levels of candidate and IC50 of candidate genes-targeted drugs were verified on NCI-N87 and MKN-45 GC cell lines. We found that RARA, THRA, CACNB1, and TOP2A are drug sensitive biomarkers of ERBB2-targeted treatment with FDA-approved drugs. All these genes act through Myc signaling pathway. Myc is the downstream hub gene of both ERBB2 and RARA. The expression of RARA, THRA, and CACNB1 were negatively correlated with Myc activation, while ERBB2 and TOP2A positively correlated with Myc activation. SH3BGRL3, SH3BGRL, and NRG2 were identified as potential ligands of ERBB2. The ERBB2+ GC with RARA amplification demonstrated better prognosis than those without RARA amplification, while overexpression of NRG2 and SH3BGRL correlated with poor prognosis in ERBB2+ GC. About 90% of ERBB2+ GC was compatible with chromosome instability (CIN) subtype of TCGA, which overlaps with intestinal-type GC in Lauren classification. In validating experiments, combination of Lapatinib and all-trans retinoic acid (ATRA) synergistically suppresses cell growth, and accompanied by decreased expression of MYC. In conclusions, we identified several predicting biomarkers for ERBB2-targeted therapy and corresponding histological features of ERBB2+ GC. Combination of ERBB2 antagonist or RARA agonist may be effective synergistic regimens for ERBB2+ GC

Integrated Photonics for NASA Applications

No abstract availabl

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Giant energy absorption capacity of graphene-based carbon honeycombs

Cellular energy absorbing materials (EAMs) are used in a wide range of important applications from aircrafts to helmets. The energy absorption capacities (EAC) of the conventional EAMs (e.g., aluminum foams, steel foams, cellular bulk metallic glasses, and carbon nanotube buckypaper) are generally on the order of 1–100 J/g, and it remains a challenge to find new EAMs with higher EACs. Here we reveal via molecular dynamics simulations that, in the in-plane direction, graphene-based carbon honeycombs (GCHs) have an extremely large EAC, up to 2400 J/g, much higher than those of all aforementioned cellular EAMs. In the out-of-plane direction, GCHs also possess a high anti-penetration EAC of 3400 J/g, which is close to that of graphene and ∼10 times higher than that of steel sheets. The giant EAC of GCHs originates from their three-dimensional graphene structures consisting of high-energy sp2 and sp3 bonds which provide a high plateau stress in a long strain range. Our findings may open up opportunities for designing light, thin, yet exceptionally strong energy absorbing systems