Towards Robust Curve Text Detection with Conditional Spatial Expansion

It is challenging to detect curve texts due to their irregular shapes and varying sizes. In this paper, we first investigate the deficiency of the existing curve detection methods and then propose a novel Conditional Spatial Expansion (CSE) mechanism to improve the performance of curve text detection. Instead of regarding the curve text detection as a polygon regression or a segmentation problem, we treat it as a region expansion process. Our CSE starts with a seed arbitrarily initialized within a text region and progressively merges neighborhood regions based on the extracted local features by a CNN and contextual information of merged regions. The CSE is highly parameterized and can be seamlessly integrated into existing object detection frameworks. Enhanced by the data-dependent CSE mechanism, our curve text detection system provides robust instance-level text region extraction with minimal post-processing. The analysis experiment shows that our CSE can handle texts with various shapes, sizes, and orientations, and can effectively suppress the false-positives coming from text-like textures or unexpected texts included in the same RoI. Compared with the existing curve text detection algorithms, our method is more robust and enjoys a simpler processing flow. It also creates a new state-of-art performance on curve text benchmarks with F-score of up to 78.4$\%$.Comment: This paper has been accepted by IEEE International Conference on Computer Vision and Pattern Recognition (CVPR 2019

Analysis of a hysteresis-controlled self-oscillating class-D amplifier

This paper gives the first systematic perturbation analysis of the audio distortion and mean switching period for a self-oscillating class-D amplifier. Explicit expressions are given for all the principal components of audio distortion, for a general audio input signal; the specific example of a sinusoidal input is also discussed in some detail, yielding an explicit closed-form expression for the total harmonic distortion (THD). A class-D amplifier works by converting a low-frequency audio input signal to a high-frequency train of rectangular pulses, whose widths are slowly modulated according to the audio signal. The audiofrequency components of the pulse-train are designed to agree with those of the audio signal. In many varieties of class-D amplifier, the pulse-train is generated using a carrier wave of fixed frequency, well above the audio range. In other varieties, as here, there is no such fixed-frequency clock, and the local frequency of the pulse-train varies in response to the audio input. Such self-oscillating designs pose a particular challenge for comprehensive mathematical modelling; we show that in order to properly account for the local frequency variations, a warped-time transformation is necessary. The systematic nature of our calculation means it can potentially be applied to a range of other self-oscillating topologies. Our results for a general input allow ready calculation of distortion diagnostics such as the intermodulation distortion (IMD), which prior analyses, based on sinusoidal input, cannot provide

Validation of a rapid and sensitive LC-MS/ MS method for determination of exemestane and its metabolites, 17β-hydroxyexemestane and 17β-hydroxyexemestane-17-O-β-D-glucuronide: Application to human pharmacokinetics study

10.1371/journal.pone.0118553PLoS ONE103e011855

Insights into the Ecological Roles and Evolution of Methyl-Coenzyme M Reductase-Containing Hot Spring Archaea

Several recent studies have shown the presence of genes for the key enzyme associated with archaeal methane/alkane metabolism, methyl-coenzyme M reductase (Mcr), in metagenome-assembled genomes (MAGs) divergent to existing archaeal lineages. Here, we study the mcr-containing archaeal MAGs from several hot springs, which reveal further expansion in the diversity of archaeal organisms performing methane/alkane metabolism. Significantly, an MAG basal to organisms from the phylum Thaumarchaeota that contains mcr genes, but not those for ammonia oxidation or aerobic metabolism, is identified. Together, our phylogenetic analyses and ancestral state reconstructions suggest a mostly vertical evolution of mcrABG genes among methanogens and methanotrophs, along with frequent horizontal gene transfer of mcr genes between alkanotrophs. Analysis of all mcr-containing archaeal MAGs/genomes suggests a hydrothermal origin for these microorganisms based on optimal growth temperature predictions. These results also suggest methane/alkane oxidation or methanogenesis at high temperature likely existed in a common archaeal ancestor

Effects of shortening and baking temperature on quality, MCPD ester and glycidyl ester content of conventional baked cake

The quality of a baked product can be greatly affected by the choice of shortening. However, a palm-based shortening can be contaminated by monochlropropanol (MCPD) ester and glycidyl ester (GE) as it is a product derived from a refined palm oil. MCPD esters and GE can be transferred into a baked product through further processing. Therefore, this study aimed to evaluate the effects of different palm-based shortening on the qualities of cake, MCPD esters and GE content during a conventional baking system. Commercial margarine, palm olein, palm mid-fraction, and soft and hard stearin were used in a cake recipe, baked at different baking temperatures (160, 180 and 200 °C) for 20 min. First, the quality characteristics of baked cake (moisture content, texture profile and surface color) was analysed. Second, the MCPD esters and GE content, acylglycerol composition and oxidation status of the fats portion from baked cake were investigated. The results showed soft stearin, palm olein and margarine delivered a similar volume, surface color, and texture to the finished product. An elevated baking temperature was detrimental to the quality characteristics of all the studied samples and delivered a finished product with extra hardness and low moisture. The free fatty acid content and specific extinction value showed that the fat portions were significantly oxidized at high baking temperatures. In addition, 2- and 3-MCPD esters were stable during baking, but GE showed that it was vulnerable to the heating process and constantly degrades when the baking temperature increased. In short, the finished products were in better quality (physical and texture properties) when lower baking temperature (160 °C) was used, especially when margarine, soft stearin and palm olein were used as the shortening. Hard stearin naturally contains lower MCPD esters and GE, but it was not able to provide similar qualities as compared to margarine sample

Traffic dynamics in scale-free networks with limited packet-delivering capacity

We propose a limited packet-delivering capacity model for traffic dynamics in scale-free networks. In this model, the total node's packet-delivering capacity is fixed, and the allocation of packet-delivering capacity on node $i$ is proportional to $k_{i}^{\phi}$, where $k_{i}$ is the degree of node $i$ and $\phi$ is a adjustable parameter. We have applied this model on the shortest path routing strategy as well as the local routing strategy, and found that there exists an optimal value of parameter $\phi$ leading to the maximal network capacity under both routing strategies. We provide some explanations for the emergence of optimal $\phi$

Dicarbonyl­chlorido(phen­oxy­thio­carbonyl-κ2 C,S)bis­(triphenyl­phosphane-κP)molybdenum(II)

In the title complex, [Mo(C7H5OS)Cl(C18H15P)2(CO)2], the geometry around the metal atom is a capped octa­hedron. The phen­oxy­thio­carbonyl ligand coordinates the MoII atom through the C and S atoms. A one-dimensional structure is formed by π–π inter­molecular inter­actions and a supra­molecular aggregation is determined by inter­molecular C—H⋯O, C—H⋯Cl, C—H⋯π(arene) hydrogen bonds and CO⋯π(arene) inter­actions [O⋯centroid distances = 3.485 (4) and 3.722 (3) Å]

The Reading of Components of Diabetic Retinopathy: An Evolutionary Approach for Filtering Normal Digital Fundus Imaging in Screening and Population Based Studies

In any diabetic retinopathy screening program, about two-thirds of patients have no retinopathy. However, on average, it takes a human expert about one and a half times longer to decide an image is normal than to recognize an abnormal case with obvious features. In this work, we present an automated system for filtering out normal cases to facilitate a more effective use of grading time. The key aim with any such tool is to achieve high sensitivity and specificity to ensure patients' safety and service efficiency. There are many challenges to overcome, given the variation of images and characteristics to identify. The system combines computed evidence obtained from various processing stages, including segmentation of candidate regions, classification and contextual analysis through Hidden Markov Models. Furthermore, evolutionary algorithms are employed to optimize the Hidden Markov Models, feature selection and heterogeneous ensemble classifiers. In order to evaluate its capability of identifying normal images across diverse populations, a population-oriented study was undertaken comparing the software's output to grading by humans. In addition, population based studies collect large numbers of images on subjects expected to have no abnormality. These studies expect timely and cost-effective grading. Altogether 9954 previously unseen images taken from various populations were tested. All test images were masked so the automated system had not been exposed to them before. This system was trained using image subregions taken from about 400 sample images. Sensitivities of 92.2% and specificities of 90.4% were achieved varying between populations and population clusters. Of all images the automated system decided to be normal, 98.2% were true normal when compared to the manual grading results. These results demonstrate scalability and strong potential of such an integrated computational intelligence system as an effective tool to assist a grading service