Semi-sparsity Priors for Image Structure Analysis and Extraction

Image structure-texture decomposition is a long-standing and fundamental problem in both image processing and computer vision fields. In this paper, we propose a generalized semi-sparse regularization framework for image structural analysis and extraction, which allows us to decouple the underlying image structures from complicated textural backgrounds. Combining with different textural analysis models, such a regularization receives favorable properties differing from many traditional methods. We demonstrate that it is not only capable of preserving image structures without introducing notorious staircase artifacts in polynomial-smoothing surfaces but is also applicable for decomposing image textures with strong oscillatory patterns. Moreover, we also introduce an efficient numerical solution based on an alternating direction method of multipliers (ADMM) algorithm, which gives rise to a simple and maneuverable way for image structure-texture decomposition. The versatility of the proposed method is finally verified by a series of experimental results with the capability of producing comparable or superior image decomposition results against cutting-edge methods.Comment: 18 page

Intrinsic Image Transfer for Illumination Manipulation

This paper presents a novel intrinsic image transfer (IIT) algorithm for illumination manipulation, which creates a local image translation between two illumination surfaces. This model is built on an optimization-based framework consisting of three photo-realistic losses defined on the sub-layers factorized by an intrinsic image decomposition. We illustrate that all losses can be reduced without the necessity of taking an intrinsic image decomposition under the well-known spatial-varying illumination illumination-invariant reflectance prior knowledge. Moreover, with a series of relaxations, all of them can be directly defined on images, giving a closed-form solution for image illumination manipulation. This new paradigm differs from the prevailing Retinex-based algorithms, as it provides an implicit way to deal with the per-pixel image illumination. We finally demonstrate its versatility and benefits to the illumination-related tasks such as illumination compensation, image enhancement, and high dynamic range (HDR) image compression, and show the high-quality results on natural image datasets

Profiles of calreticulin and Ca2+ concentration under low temperature and salinity stress in the mud crab, Scylla paramamosain

Calreticulin (CRT) is an important molecular chaperon crucial to survival of organisms under adverse conditions. In this study, the potential roles of CRT in the mud crab, Scylla paramamosain, were investigated. Firstly, SpCRT gene expression was detected in various tissues of S. paramamosain with the highest expression found in the hepatopancreas. To evaluate potential role of SpCRT in cold adaption, sub-adult crabs were subjected to temperatures of 10, 15, 20 and 25 degrees C and the profiles of SpCRT gene were determined in the hepatopancreas, chela muscle and gills. The results showed that the expressions of SpCRT mRNA in these tissues were significantly higher for those crabs exposed to low temperatures of 10 and 15 degrees C as compared to those exposed to the higher temperatures, indicating SpCRT was involved in cold adaptation-probably through facilitating protein folding. When low temperature 10 degrees C or 15 degrees C was further combined with high and low salinity stress, the expression of SpCRT mRNA at low salinity (10 ppt) was in most cases significantly higher than that at high salinity (35 ppt), suggesting that under low temperatures, low salinity may represents a more stressful condition to the crab than high salinity. It was also shown that when crabs challenged by 10 degrees C, Ca2+ concentration increased rapidly in the hepatopancreas and an in vitro experiment further showed that the expression of SpCRT mRNA increased concurrently with added Ca2+ concentration; these results together imply that Ca2+ probably plays a major role in low temperature signaling, which induces expression of genes related to cold adaption, such as CRT

Semi-Sparsity for Smoothing Filters

In this paper, we propose an interesting semi-sparsity smoothing algorithm based on a novel sparsity-inducing optimization framework. This method is derived from the multiple observations, that is, semi-sparsity prior knowledge is more universally applicable, especially in areas where sparsity is not fully admitted, such as polynomial-smoothing surfaces. We illustrate that this semi-sparsity can be identified into a generalized $L_0$-norm minimization in higher-order gradient domains, thereby giving rise to a new "feature-aware" filtering method with a powerful simultaneous-fitting ability in both sparse features (singularities and sharpening edges) and non-sparse regions (polynomial-smoothing surfaces). Notice that a direct solver is always unavailable due to the non-convexity and combinatorial nature of $L_0$-norm minimization. Instead, we solve the model based on an efficient half-quadratic splitting minimization with fast Fourier transforms (FFTs) for acceleration. We finally demonstrate its versatility and many benefits to a series of signal/image processing and computer vision applications

MXene-based Membranes for Drinking Water Production

The soaring development of industry exacerbates the shortage of fresh water, making drinking water production an urgent demand. Membrane techniques feature the merits of high efficiency, low energy consumption, and easy operation, deemed as the most potential technology to purify water. Recently, a new type of two-dimensional materials, MXenes as the transition metal carbides or nitrides in the shape of nanosheets, have attracted enormous interest in water purification due to their extraordinary properties such as adjustable hydrophilicity, easy processibility, antifouling resistance, mechanical strength, and light-to-heat transformation capability. In pioneering studies, MXene-based membranes have been evaluated in the past decade for drinking water production including the separation of bacteria, dyes, salts, and heavy metals. This review focuses on the recent advancement of MXene-based membranes for drinking water production. A brief introduction of MXenes is given first, followed by descriptions of their unique properties. Then, the preparation methods of MXene membranes are summarized. The various applications of MXene membranes in water treatment and the corresponding separation mechanisms are discussed in detail. Finally, the challenges and prospects of MXene membranes are presented with the hope to provide insightful guidance on the future design and fabrication of high-performance MXene membranes

Fuzzy decision making method based on CoCoSo with critic for financial risk evaluation

The financial risk evaluation is critically vital for enterprises to identify the potential financial risks, provide decision basis for financial risk management, and prevent and reduce risk losses. In the case of considering financial risk assessment, the basic problems that arise are related to strong fuzziness, ambiguity and inaccuracy. q-rung orthopair fuzzy set (q-ROFS), portrayed by the degrees of membership and non-membership, is a more resultful tool to seize fuzziness. In this article, the novel q-rung orthopair fuzzy score function is given for dealing the comparison problem. Later, the and operations are explored and their interesting properties are discussed. Then, the objective weights are calculated by CRITIC (Criteria Importance Through Inter-criteria Correlation). Moreover, we present combined weights that reflects both subjective preference and objective preference. In addition, the q-rung orthopair fuzzy MCDM (multi-criteria decision making) algorithm based on CoCoSo (Combined Compromise Solution) is presented. Finally, the feasibility of algorithm is stated by a financial risk evaluation example with corresponding sensitivity analysis. The salient features of the proposed algorithm are that they have no counter-intuitive case and have a stronger capacity in differentiating the best alternative. First published online 03 March 202

Feature extraction for license plate location based on L0-norm smoothing

We propose a simple feature extraction algorithm for license plate location, which can reduce the occurrence of pseudo-licenses significantly. Our scheme arises from a novel L-0 -norm image smoothing, in which the multiple local textures in the complex backgrounds can be suppressed remarkably without changing the structures and edges of the license objects. Due to this "edgeaware" property, we then combine a feature filtering with an efficient binarized image, a simple multi-scale image analysis algorithm, to remove the potential false license plates. Finally, we extract license plates with a projection method. Experimental results show the proposed method provides a flexible and powerful way to the license plate location in complex backgrounds

The effects of feeding ration and cheliped autotomy on the growth and expression of ecdysteroid receptor in early juvenile mud crabs, Scylla paramamosain

This study investigated the combined effects of feeding ration and cheliped autotomy on the intermolt duration, molting success, molt increments in size and weight, and ecdysteroid receptor gene (SpEcR) expression of early juvenile mud crab Scylla paramamosain. Newly molted second stage juvenile crabs (C2) were subjected to four feeding conditions; optimal, suboptimal (1/2 optimal), low (1/4 optimal) ration and starvation, and autotomy (intact vs. cheliped autotomy) in a 4 x 2 factorial design until all crabs successfully molted or died. A significant interaction of feeding ration and cheliped autotomy on intermolt duration was identified. With reduced feeding ration, both intact and cheliped autotomized crabs showed increased time and desynchrony of molting, but decreased carapace size and body weight. Importantly, all crabs with different feeding rations even the low ration had high rates of molting success (> 95%), while the crabs subjected to starvation died without molting. When fed optimal ration, the mean intermolt duration of the cheliped autotomized crabs was significantly prolonged, while no such effect was found between autotomized and intact crabs subjected to suboptimal or low feeding ration. The qRT-PCR revealed that the expression of SpEcR showed a general trend of inhibited by reduced feeding ration, which was consistent with observed significantly increased intermolt duration. Interestingly, the transcript level of SpEcR was only significantly affected by cheliped autotomy under the optimal and suboptimal feeding rations but not for the low feeding ration. Together, the results of this study suggest that the S. paramamosain early juveniles have a strong tolerance for fluctuations in food availability. In addition, the availability of food and limb autotomy could significantly affect growth, molting duration and synchrony of the crabs, which appeared to reflect in SpEcR expression level that involved in the regulation of molting and limb regeneration process of the juvenile crabs