Dynamically manipulating topological physics and edge modes in a single degenerate optical cavity

We propose a scheme to simulate topological physics within a single degenerate cavity, whose modes are mapped to lattice sites. A crucial ingredient of the scheme is to construct a sharp boundary so that the open boundary condition can be implemented for this effective lattice system. In doing so, the topological properties of the system can manifest themselves on the edge states, which can be probed from the spectrum of an output cavity field. We demonstrate this with two examples: a static Su-Schrieffer-Heeger chain and a periodically driven Floquet topological insulator. Our work opens up new avenues to explore exotic photonic topological phases inside a single optical cavity.Comment: 6 pages, 5 figure

Device modeling of superconductor transition edge sensors based on the two-fluid theory

In order to support the design and study of sophisticated large scale transition edge sensor (TES) circuits, we use basic SPICE elements to develop device models for TESs based on the superfluid-normal fluid theory. In contrast to previous studies, our device model is not limited to small signal simulation, and it relies only on device parameters that have clear physical meaning and can be easily measured. We integrate the device models in design kits based on powerful EDA tools such as CADENCE and OrCAD, and use them for versatile simulations of TES circuits. Comparing our simulation results with published experimental data, we find good agreement which suggests that device models based on the two-fluid theory can be used to predict the behavior of TES circuits reliably and hence they are valuable for assisting the design of sophisticated TES circuits.Comment: 10pages,11figures. Accepted to IEEE Trans. Appl. Supercon

Enrichment of Phosphate on Ferrous Iron Phases during Bio-Reduction of Ferrihydrite *

The reduction of less stable ferric hydroxides and formation of ferrous phases is critical for the fate of phosphorus in anaerobic soils and sediments. The interaction between ferrous iron and phosphate was investigated experimentally during the reduction of synthetic ferrihydrite with natural organic materials as carbon source. Ferrihydrite was readily reduced by dissimilatory iron reducing bacteria (DIRB) with between 52 % and 73 % Fe(III) converted to Fe(II) after 31 days, higher than without DIRB. Formation of ferrous phases was linearly coupled to almost complete removal of both aqueous and exchangeable phosphate. Simple model calculations based on the incubation data suggested ferrous phases bound phosphate with a molar ratio of Fe(II):P between 1.14- 2.25 or a capacity of 246- 485 mg·P·g −1 Fe(II). XRD analysis indicated that the ratio of Fe(II): P was responsible for the precipitation of vivianite (Fe3(PO4)2·8H2O), a dominant Fe(II) phosphate mineral in incubation systems. When the ratio of Fe(II):P was more than 1.5, the precipitation of Fe(II) phosphate was soundly crystallized to vivianite. Thus, reduction of ferric iron provides a mechanism for the further removal of available phosphate via the production of ferrous phases, with anaerobic soils and sediments potentially exhibiting a higher capacity to bind phosphate than some aerobic systems

Molecular Cloning and Expression Analysis of a MADS-Box Gene (GbMADS2) from Ginkgo biloba

As a kind of transcription factors gene family, MADS-box genes play an important role in plant development processes. To find genes involved in the floral transition of Ginkgo biloba, a MADS-box gene, designated as GbMADS2, was cloned from G. biloba based on EST sequences by RT-PCR. Sequence analysis results showed that the cDNA sequence of GbMADS2 contained a 663 bp length ORF encoding 221 amino acids protein, which displayed typical structure of plant MADS-box protein including MADS, I, and K domains and C terminus. The sequence of GbMADS2 protein was highly homologous to those of MADS-box proteins from other plant species with the highest homologous to AGAMOUS (CyAG) from Cycas revoluta. The phylogenetic tree analysis revealed that GbMADS2 belonged to AGAMOUS clade genes. Real-time PCR analysis indicated that expression levels of GbMADS2 gene in female and male flower were significantly higher than those in root, stem, and leaves, and that GbMADS2 expression level increased along with time of flower development. The spatial and time-course expression profile of GbMADS2 implied that GbMADS2 might be involved in development of reproductive organs. The isolation and expression analysis of GbMADS2 provided basis for further studying the molecular mechanism of flower development in G. biloba

Study on the characteristics of mold in military aviation material warehouse

Aviation equipment warehouse is responsible for the combat training task of the army. The existence of mold in the warehouse reduces the quality and performance of equipment, and the quality of storage equipment directly affects the strength of aviation equipment support ability. In this paper, the main characteristics of storage mold were studied, the micro morphology and colony characteristics of storage mold were analyzed, and the main types of mold in aviation material warehouse were introduced, which provided a theoretical basis for further research on the growth and control of mold

BGM-Net: Boundary-Guided Multiscale Network for Breast Lesion Segmentation in Ultrasound.

Automatic and accurate segmentation of breast lesion regions from ultrasonography is an essential step for ultrasound-guided diagnosis and treatment. However, developing a desirable segmentation method is very difficult due to strong imaging artifacts e.g., speckle noise, low contrast and intensity inhomogeneity, in breast ultrasound images. To solve this problem, this paper proposes a novel boundary-guided multiscale network (BGM-Net) to boost the performance of breast lesion segmentation from ultrasound images based on the feature pyramid network (FPN). First, we develop a boundary-guided feature enhancement (BGFE) module to enhance the feature map for each FPN layer by learning a boundary map of breast lesion regions. The BGFE module improves the boundary detection capability of the FPN framework so that weak boundaries in ambiguous regions can be correctly identified. Second, we design a multiscale scheme to leverage the information from different image scales in order to tackle ultrasound artifacts. Specifically, we downsample each testing image into a coarse counterpart, and both the testing image and its coarse counterpart are input into BGM-Net to predict a fine and a coarse segmentation maps, respectively. The segmentation result is then produced by fusing the fine and the coarse segmentation maps so that breast lesion regions are accurately segmented from ultrasound images and false detections are effectively removed attributing to boundary feature enhancement and multiscale image information. We validate the performance of the proposed approach on two challenging breast ultrasound datasets, and experimental results demonstrate that our approach outperforms state-of-the-art methods