In this paper, we propose a novel method called Rotational Region CNN (R 2 CNN) for detecting arbitrary-oriented texts in natural scene images. The framework is based on Faster R-CNN [1] architecture. First, we use the Region Proposal Network (RPN) to generate axis-aligned bounding boxes that enclose the texts with different orientations. Second, for each axis-aligned text box proposed by RPN, we extract its pooled features with different pooled sizes and the concatenated features are used to simultaneously predict the text/non-text score, axis-aligned box and inclined minimum area box. At last, we use an inclined non-maximum suppression to get the detection results. Our approach achieves competitive results on text detection benchmarks : ICDAR 2015 and ICDAR 2013.

No abstract

No abstract

TianQin is a proposed geocentric space-based gravitational wave observatory mission, which requires time-delay interferometry (TDI) to cancel laser frequency noise. With high demands for precision, solar-wind plasma environment at ∼ 10 5 km above the Earth may constitute a nonnegligible noise source to laser interferometric measurements between satellites, as charged particles perturb the refractivity along light paths. In this paper, we first assess the plasma noises along single links from space-weather models and numerical orbits, and analyze the time and frequency domain characteristics. Particularly, to capture the plasma noise in the entire measurement band of 10 −4 − 1 Hz, we have performed additional space-weather magnetohydrodynamic simulations in finer spatial and temporal resolutions and utilized Kolmogorov spectra in high-frequency data generation. Then we evaluate the residual plasma noises of the first-and second-generation TDI combinations. Both analytical and numerical estimations have shown that under normal solar conditions the plasma noise after TDI is less than the secondary noise requirement. Moreover, TDI is shown to exhibit moderate suppression on the plasma noise below ∼ 10 −2 Hz due to noise correlation between different arms, when compared with the secondary noise before and after TDI.

No abstract

It was observed that the two types of stretched wool fibers could be characterized by the IR transmittance peaks at 1620 ~ 1630 cm-1 and 1510 ~ 1520 cm-1. It was evidenced that upon stretching the secondary structure of the wool fibers transformed from alpha helix, the typical secondary structure of raw wool, to beta pleated sheet, the typical secondary structure of native silk, which was supported by the change in cross-sectional morphology and stress-strain curve.

No abstract

Arsenic (As) is widespread in the environment and causes numerous health problems. Rhodopseudomonas palustris has been regarded as a good model organism for studying arsenic detoxification since it was first demonstrated to methylate environmental arsenic by conversion to soluble or gaseous methylated species. However, the detailed arsenic resistance mechanisms remain unknown though there are at least three arsenic-resistance operons (ars1, ars2, and ars3) in R. palustris. In this study, we investigated how arsenic multi-operons contributed to arsenic detoxification in R. palustris. The expression of ars2 or ars3 operons increased with increasing environmental arsenite (As(III)) concentrations (up to 1.0 mM) while transcript of ars1 operon was not detected in the middle log-phase (55 h). ars2 operon was actively expressed even at the low concentration of As(III) (0.01 μM), whereas the ars3 operon was expressed at 1.0 μM of As(III), indicating that there was a differential regulation mechanism for the three arsenic operons. Furthermore, ars2 and ars3 operons were maximally transcribed in the early log-phase where ars2 operon was 5.4-fold higher than that of ars3 operon. A low level of ars1 transcript was only detected at 43 h (early log-phase). Arsenic speciation analysis demonstrated that R. palustris could reduce As(V) to As(III). Collectively, strain CGA009 detoxified arsenic by using arsenic reduction and methylating arsenic mechanism, while the latter might occur with the presence of higher concentrations of arsenic.