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Geotechnical engineering involves various types of uncertainties, as it always deals with highly variable natural materials. Reliability-based design/analysis can play at least a complementary role in the design approach. In this paper, reliability analysis of anti-sliding of retaining wall with the parameters treated as random variables is performed based on the concept of random fields. Both friction angle and cohesion of soils near the interface along the base of retaining wall are treated as Gaussian fields. The spatial correlation and cross correlation of the variables are calculated by a specific covariance function and the seismic loads act on retaining walls are also taken into account. Examples are illustrated to verify the accuracy of the proposed approach. It is found from the numerical results that the spatial correlation of shear strength has an important influence on the probability of the anti-sliding failure of retaining wall. Moreover, the numerical results obtained from the proposed method are in full agreement with those obtained from Monte Carlo simulations. Therefore, the proposed method provides a new view to study the stability of a retaining wall subjected to seismic loads.

Background The pathogenesis underlying the alterations of orbital architecture in Graves’ orbitopathy (GO) is not yet fully understood. The present study aimed to investigate the association of DNA methylation in peripheral blood and orbital volumetry in Chinese patients with GO. Methods A total of 35 GO subjects (70 orbits) were subjected to CT scan. The total cross-sectional area of the extraocular muscles (orbital muscles, OM), total orbit area (TOA), and the exophthalmometry were measured and OM/TOA ratio was calculated. Targeted bisulfite sequencing was performed on seven candidate genes. Results No significant correlation was established between the DNA methylation levels of these genes and exophthalmometry. The MBP methylation level was found to be correlated with OM/TOA ratio (P < 0.05). Multiple linear regression analysis on parameters including age, sex, TRAb, duration of GO, and DNA methylation levels of seven genes with OM/TOA ratio confirmed that MBP and OM/TOA ratio had a significant correlation (P < 0.05). The partial least squares analysis showed that the top three genes with the highest loadings were MBP, BOLL, and BECN1 and that OM/TOA ratio affected the DNA methylation block than exophthalmometry. Conclusions This study provided preliminary evidence that MBP is a potential gene associated with OM enlargement in GO patients according to the combination of DNA methylation sequencing and orbital CT measurement.

Background Graves’ orbitopathy (GO) is an autoimmune disease with mechanical impairment of orbital muscles and lacrimal gland dysfunction. The frequently used methods of assessing GO activity include Clinical Activity Score (CAS), CT, and MRI. These approaches are mainly associated with orbital muscles; however, there are not many studies that focus on the lacrimal gland inflammation of GO patients. Objective The aim of this study is to assess the usefulness of 99mTc-DTPA single-photon emission (SPE) CT/CT in evaluating the lacrimal gland inflammation in GO, as compared with other methods. Methods A retrospective analysis of 48 patients with active GO compared with 33 controls was conducted. All subjects underwent clinical–endocrinological analyses, CAS evaluation, CT scans, and SPECT/CT examination. Lacrimal gland dimensions were determined and analyzed. Results The lacrimal glands in patients with GO were significantly larger in all measured dimensions (P < 0.001) on CT scans relative to those in controls. Increased lacrimal gland diethylene triamine pentaacetic acid (DTPA) uptake ratios (P < 0.001) were displayed in active GO patients compared to controls and were also correlated with thyrotropin receptor antibody levels. The cut-off value for discriminating active and inactive disease was calculated to be 1.735, with specificity of 82.6% and sensitivity of 74.2%. SPECT/CT uptake ratios and CAS values were positively correlated in all GO patients. SPECT/CT uptake ratios were also positively correlated with CT measurements including lacrimal gland volume and coronal width in GO patients. Conclusions These data indicated that lacrimal gland SPECT/CT images can serve as a good tool for assessing the inflammation and disease activity of GO.

A thorough understanding of inner ear anatomy is important for investigators. However, investigation of the mouse inner ear is difficult due to the limitations of imaging techniques. X-ray phase contrast tomography increases contrast 100-1,000 times compared with conventional X-ray imaging. This study aimed to investigate inner ear anatomy in a fresh post-mortem mouse using X-ray phase contrast tomography and to provide a comprehensive atlas of microstructures with less tissue deformation. All experiments were performed in accordance with our institution's guidelines on the care and use of laboratory animals. A fresh mouse cadaver was scanned immediately after sacrifice using an inline phase contrast tomography system. Slice images were reconstructed using a filtered back-projection (FBP) algorithm. Standardized axial and coronal planes were adjusted with a multi-planar reconstruction method. Some three-dimensional (3D) objects were reconstructed by surface rendering. The characteristic features of microstructures, including otoconia masses of the saccular and utricular maculae, superior and inferior macula cribrosae, single canal, modiolus, and osseous spiral lamina, were described in detail. Spatial positions and relationships of the vestibular structures were exhibited in 3D views. This study investigated mouse inner ear anatomy and provided a standardized presentation of microstructures. In particular, otoconia masses were visualized in their natural status without contrast for the first time. The comprehensive anatomy atlas presented in this study provides an excellent reference for morphology studies of the inner ear.

Using a melt-mixing technique, ethylene–vinyl acetate (EVA) copolymers based composites containing Multi-Wall Carbon nanotubes (MWCNTs), aluminum trihydrate (ATH), zinc borate (ZB), and gadolinium oxide (Gd2O3) were fabricated. Then, the as-prepared samples were irradiated with an electron beam (EB) at the dose range varied from 0 to 275 kGy. Moreover, we investigated the properties of irradiated and unirradiated samples. Morphological observation showed good dispersion of MWCNTs and other additives in EVA. Furthermore, the gel content, mechanical properties, the limit oxygen index (LOI) values of irradiated composites increased to 28.4% after 250 kGy after irradiated. All the conclusions indicated that the comprehensive properties of the WMCNTs/EVA composites were improved by using high energy electron beam irradiation.

Normally, modeling 3D face is an effective way for pose-invariant recognition, yet its expensive computation significantly discourages potential applications. In this paper, a simple and fully automatic panoramic image-based pose-invariant face recognition method is proposed to present excellent accuracy with low complexity. In this paper, a face shape model with local morphing treatment is first constructed and considered as the alignment standard to deal with all of the possible geometric distortion problems. During the recognition phase, a proposed systematically designed algorithm with morphing and the selection function are both utilized to significantly ease the negative effects of various poses within ±45° in yaw and ±22.5° in pitch. As demonstrated in experimental results, a similar accuracy as that of the 3D start-of-the-arts is achieved with much less computational complexity.

Existing learning-based atmospheric particle-removal approaches such as those used for rainy and hazy images are designed with strong assumptions regarding spatial frequency, trajectory, and translucency. However, the removal of snow particles is more complicated because it possess the additional attributes of particle size and shape, and these attributes may vary within a single image. Currently, hand-crafted features are still the mainstream for snow removal, making significant generalization difficult to achieve. In response, we have designed a multistage network codenamed DesnowNet to in turn deal with the removal of translucent and opaque snow particles. We also differentiate snow into attributes of translucency and chromatic aberration for accurate estimation. Moreover, our approach individually estimates residual complements of the snow-free images to recover details obscured by opaque snow. Additionally, a multi-scale design is utilized throughout the entire network to model the diversity of snow. As demonstrated in experimental results, our approach outperforms state-of-the-art learning-based atmospheric phenomena removal methods and one semantic segmentation baseline on the proposed Snow100K dataset in both qualitative and quantitative comparisons. The results indicate our network would benefit applications involving computer vision and graphics.

Recent studies on category relations have shown the promising progress in addressing classification problems. Existing works independently consider the known relation and classifier optimization, and thus restrain the room for performance improvement. In this work, a new loss function is proposed to leverage the underlining relations among categories and classifiers. In addition, the bipolar relation (BR) graph is employed to formulate a general form for diverse relations. This bipolar graph is automatically learnt for reliving the constraints which may happen during the cost minimization. Extensive experiments on three benchmarks with various hypotheses and graphs demonstrate that our method can offer a significant performance improvement by jointly learning from both BR graph and hypothesis, in particular on a small training dataset scenario that suffers from severe overfitting problem.

A contrast enhancement method termed stratified parametric-oriented histogram equalization (SPOHE) is proposed to effectively provide a regional enhanced effect without visual artifacts, e.g., halo or blocking artifacts, which is normally incurred in the former simplified enhancement methods. First, the stratified sampling theory is applied to uniformly sample the original image through many divided strata with the size defined by the two parameters ( $\alpha $ , $\beta $ ). Second, the required statistical information is efficiently derived through the integral image concept. Finally, the corrected SPOHE is also proposed to further improve the contrast with limited tradeoff computations. The experimental results demonstrate that the proposed scheme yields a cumulative distribution function similar to the actual one for an accurate contrast enhancement performance while significantly reducing the computational complexity. Moreover, compared with the former speed-oriented methods, good contrast and artifact-free results can be achieved simultaneously.

Local image contrast enhancement methods extract more informative details comparing with the global methods. Yet, the traditional schemes require to access all of the pixels in a local region to obtain the cumulative distribution function (cdf) for further enhancement, i.e., adaptive histogram equalization (AHE), and thus the time complexity drastically increases accordingly when the block size increases. Consequently, some speed-up ingenuities such as block-wise strategy and simple proportionally averaging manner are employed to cope with this issue, yet serious blocking artifact or low contrast issues are accompanied. In this study, a local enhancement method, namely corrected parametric-oriented histogram equalization (CPOHE), is proposed to effectively yield enhanced results with high contrast and artifact-free texture using the concept of integral image, and further correct the accompanied distortion. As documented in the experimental results, the proposed method provides a high practical value for applied in visual perception, biometric, and tracking/detection applications.

Digital multitoning is an extension of halftoning for rendering more than two tones at each pixel for higher image quality. Although a lot of effort has been put in generating dispersed dots previously, the blue-noise feature can hardly be achieved for those printers utilizing the electrophotography (EP) process to avoid the physically unstable isolated dots. To overcome this issue, Chandu et al. proposed a screening method for yielding green-noise dot clusters, yet noisy multitone texture was accompanied. This degrades the visual quality and the stability of tone rendering. In this paper, a significantly improved homogeneity of clustered dots can be achieved by the proposed screening method based upon the new inter-iterative clustered-dot direct multi-bit search algorithm. Compared with the former approaches, the inter-iteration design leads to less error by the updated initial multitone patterns. As demonstrated in the experimental results, both of the high homogenous multitone texture and less noisy perception at all absorptance levels are offered in contrast to the former Chandu et al. ’s results. The high-quality output proves it as a very competitive candidate for EP printers, e.g., laser printers.

In recent years, wavelet transform has been widely applied in multimedia signal processing and digital watermarking is involved for ensuring security. This study presents a blind wavelet-based watermarking incorporated with the Human Visual System (HVS), which embeds watermarks into detail-subband coefficients. Since imperceptibility is the most significant issue in watermarking, the approximation band is maintained constant, while the detail subbands are modified to carry information. The perceptual embedded weights for all subbands are determined according to the Just Noticeable Distortion (JND) criterion. The strength of the modification is investigated to provide a balanced result between robustness and image quality. In the decoder, the Least-Mean-Square (LMS) is employed to predict the original detail-subband coefficients and then extract the embedded watermarks. As documented in the experimental results, the proposed method provides good robustness and excellent image quality.

The conventional dual-mode halftoning methods achieve high quality halftone patterns by easing smooth artifact and preserving image details. However, the boundaries between low- and high-frequency image regions still present undesired texture in some particular cases, which significantly degrades the visual quality. In this work, a multi-mode halftoning method is proposed to deal with the object map artifact and boundary artifact simultaneously. In addition, the new absorptance-frequency stacking constraint is also employed to solve the noisy textures of the halftone outputs. As documented in the experimental results, high quality halftone outputs can be obtained, proving that the proposed method can be a competitive candidate for electrophotographic printers.

Error diffusion is an efficient halftone method for mainly being applied on printers. The promising high image quality and processing efficiency endorse it as a popular and competitive candidate in halftoning and multitoning applications. The multitoning is an extension of halftoning, adopting more than two-tone levels for the improvement of the similarity between an original image and the converted image. Yet, the banding effect, indicating the areas with discontinuous tone level, disturbs the visual perception, and thus seriously degrades image quality. To solve the banding effect, the tone-replacement strategy is proposed in this paper. As documented in the experimental results, excellent tone-similarity as that of the original image and promising reconstructed dot-distribution can be provided simultaneously. Comparing with the former banding-free methods, the apparent improvements/features suggest that the proposed method can be a very competitive candidate for multitoning applications.

Compared to the error diffusion, dot diffusion provides an additional pixel-level parallelism for digital halftoning. However, even though its periodic and blocking artifacts had been eased by previous works, it was still far from satisfactory in terms of the blue noise spectrum perspective. In this work, we strengthen the relationship among the pixel locations of the same processing order by an iterative halftoning method, and the results demonstrate a significant improvement. Moreover, a new approach of deriving the averaged power spectrum density (APSD) is proposed to avoid the regular sampling of the well-known Bartlett's procedure which inaccurately presents the halftone periodicity of certain halftoning techniques with parallelism. As a result, the proposed dot diffusion is substantially superior to the state-of-the-art parallel halftoning methods in terms of visual quality and artifact-free property, and competitive runtime to the theoretical fastest ordered dithering is offered simultaneously., Comment: Accepted to IEEE Trans. on Image Processing

Formerly, dimensionality reduction techniques are effective ways for extracting statistical significance of features from their original dimensions. However, the dimensionality reduction also induces an additional complexity burden which may encumber the real efficiency. In this paper, a technique is proposed for the reduction of the dimension of samples rather than the features in the former schemes, and it is able to additionally reduce the computational complexity of the applied systems during the reduction process. This method effectively reduces the redundancies of a sample, in particular for those objects which possess partially symmetric property, such as human face, pedestrian, and license plate. As demonstrated in the experiments, based upon the premises of faster speeds in training and detection by a factor of 4.06 and 1.24, respectively, similar accuracies to the ones without considering the proposed method are achieved. The performance verifies that the proposed technique can offer competitive practical values in pattern recognition related fields.

The pedestrian detection is a popular research field in recent years, yet the low-resolution issue is rarely discussed for yielding detection accuracy for drivers. In this study, a hierarchical pedestrian detection system is proposed to cope with this issue. In which, two independent features, orientation and magnitude, are adopted as descriptors for pedestrians. Moreover, the proposed probability-based pedestrian mask pre-filtering (PPMPF) is utilized to initially filter out non-pedestrian regions meanwhile retaining most of the real pedestrians. In experimental results, the use of the two proposed features can provide superior performance than the former well-known histogram of oriented gradient (HOG; high accuracy) and the edgelet (high processing efficiency) simultaneously without carrying their lacks. Moreover, the PPMPF can also boost the processing efficiency by a factor of around 2.82 in contrast to the system without this pre-filtering strategy. Thus, the proposed method can be a very competitive candidate for intelligent surveillance applications.

In this study, a high accuracy fingerprint classification method is proposed to enhance the performance in terms of efficiency for fingerprint recognition system. The recognition system has been considered as a reliable mechanism for criminal identification and forensic for its invariance property, yet the huge database is the key issue to make the system obtuse. In former works, the pre-classifying manner is an effective way to speed up the process, yet the accuracy of the classification dominates the further recognition rate and processing speed. In this paper, a rule-based fingerprint classification method is proposed, wherein the two features, including the types of singular points and the number of each type of point are adopted to distinguish different fingerprints. Moreover, when fingerprints are indistinguishable, the proposed Center-to-Delta Flow (CDF) and Balance Arm Flow (BAF) are catered for further classification. As documented in the experimental results, a good accuracy rate can be achieved, which endorses the effectiveness of the fingerprint classification scheme for the further fingerprint recognition system.

Moving object detection is an important and fundamental step for intelligent video surveillance systems because it provides a focus of attention for post-processing. A multilayer codebook-based background subtraction (MCBS) model is proposed for video sequences to detect moving objects. Combining the multilayer block-based strategy and the adaptive feature extraction from blocks of various sizes, the proposed method can remove most of the nonstationary (dynamic) background and significantly increase the processing efficiency. Moreover, the pixel-based classification is adopted for refining the results from the block-based background subtraction, which can further classify pixels as foreground, shadows, and highlights. As a result, the proposed scheme can provide a high precision and efficient processing speed to meet the requirements of real-time moving object detection.

The NLRP12 (NLR family, pyrin domain containing 12) serves as a suppressor factor in the inflammatory response and protects the host against inflammation-induced damage. In the present study, we aimed to study the polymorphisms of NLRP12 gene and its association with susceptibility to non-specific digestive disorder (NSDD) in rabbits. We re-sequenced the entire coding region of the rabbit NLRP12 gene and detected a total of 19 SNPs containing 14 synonymous and five non-synonymous variations. Among them, the coding SNP (c.1682A>G), which would carry a potential functional implication, was subsequently subjected to genotyping for case- control association study (272 cases and 267 controls). The results revealed that allele A was significantly protective against NSDD with an odds ratio value of 0.884 (95% confidence interval, 0.788 to 0.993; p = 0.038). We also experimentally induced NSDD in growing rabbits by feeding a fibre-deficient diet and subsequently investigated NLRP12 mRNA expression. The mRNA expression of NLRP12 in healthy status was significantly higher than that in severe NSDD (p = 0.0016). The highest expression was observed in individuals carrying the protective genotype AA (p = 0.0108). These results suggested that NLRP12 was significantly associated with the NSDD in rabbits. However, the precise molecular mechanism of NLRP12 involving in the development of rabbit NSDD requires further research.

The myostatin (MSTN) gene, as a negative regulator of skeletal muscle growth, has been proposed to be associated with production traits in farm animals. In the present study, a T/C variant at -125 bp (relative to ATG start codon) of 5'regulatory region of rabbit MSTN was identified by direct sequencing. Two hundred and twenty two rabbits, which were randomly sampled from 3 breeds (Ira rabbits, Champagne rabbits and Tianfu black rabbits), were genotyped by high-resolution melting (HRM). Comparing the genotyping results of 47 samples with direct sequencing, the HRM showed high sensitivity (0.96) and high specificity (0.98). In the three rabbit breeds, the allele C was the predominant allele. The polymorphic site showed high heterozygosity (He = 0.48) and high effective number of alleles (Ne = 1.91). The genetic diversity was reasonably informative (0.25

Graphene-metal oxide composites as supercapacitor electrodes combine the large pseudocapacitance of metal oxides with the fascinating electrical and mechanical properties and large surface area of graphene. The synthetic methods for composites are reviewed, including in-siu synthesis, solution mixing, hydrothermal method, microware irradiation and electrochemical deposition. Among these techniques, the hydrothermal method offers an effective and simple way to anchor metal oxides on the 2D graphene sheet uniformly. Consequently, the composites exhibit high capacity, high rate capability and well reversibility, presenting promising prospects as supercapacitor electrode material.

Block truncation coding (BTC) is an efficient compression technique with extremely low computational complexity. However, the blocking and false contour effects are two major deficiencies in BTC which cause severe perceptual artifacts. The former scheme, error-diffused BTC (EDBTC), can significantly improve the above issues through the visual low-pass compensation on the bitmap, which thus widens its possible application market, yet the corresponding security issue may limit its value. In this paper, a method namely complementary hiding EDBTC is developed to cope the above issue. This paper is managed by firstly discussing when a single watermark is embedded, and then multiple watermarks are employed to test the limitation of the proposed scheme. Herein, an adaptive external bias factor is employed to control the watermark embedding, and this factor also affects the image quality and robustness simultaneously. Experimental results demonstrate that the proposed method only requires an extremely small external bias factor to carry watermarks, which enables a high capacity scenario without significantly damaging image quality.

Block truncation coding (BTC) has been considered as a highly efficient compression technique for decades, but the blocking artifact is its main issue. The halftoning-based BTC has significantly eased this issue, yet an apparent impulse noise artifact is accompanied. In this study, an improved BTC, termed adaptive dot-diffused BTC (ADBTC), is proposed to further improve the visual quality. Also, this method provides an additional flexibility on the compression ratios determination in contrast to the former fixed and few number of configuration possibilities. As documented in the experimental results, the proposed method achieves the superior image quality regarding the five various objective IQA methods. As a result, it is a very competitive approach for the needs of both high frame rate and high-resolution image compression.