WavNet — Visual saliency detection using Discrete Wavelet Convolutional Neural Network

In the recent advancements in image and video analysis, the detection of salient regions in the image becomes the initial step. This plays a crucial role in deciding the performance of such algorithms. In this work, a Multi-Resolution Feature Extraction (MRFE) technique that makes use of Discrete Wavelet Convolutional Neural Network (DWCNN) for generating features is employed. An Enhanced Feature Extraction (EFE) module extracts additional features from the high level features of the DWCNN, which are used to frame both channel as well as spatial attention models for yielding contextual attention maps. A new hybrid loss function is also proposed, which is a combination of Balanced Cross Entropy (BCE) loss and Edge based Structural Similarity (ESSIM) loss that effectively identifies and segments the salient regions with clear boundaries. The method is tested exhaustively with five different benchmark datasets and is proved superior to the existing state-of-the-art methods with a minimum Mean Absolute error (MAE) of 0.03 and F-measure of 0.956.     

Influence of temperature on acoustic emission source location accuracy in underground structure

An acoustic emission (AE) experiment was carried out to explore the AE location accuracy influenced by temperature. A hollow hemispherical specimen was used to simulate common underground structures. In the process of heating with the flame, the pulse signal of constant frequency was stimulated as an AE source. Then AE signals received by each sensor were collected and used for comparing localization accuracy at different temperatures. Results show that location errors of AE keep the same phenomenon in the early and middle heating stages. In the later stage of heating, location errors of AE increase sharply due to the appearance of cracks. This provides some beneficial suggestions on decreasing location errors of structural cracks caused by temperature and improves the ability of underground structure disaster prevention and control.     

Thiol-Functionalized Covalent Organic Frameworks as Thermal History Indictor for Temperature and Time History Monitoring

Various products, including foods and pharmaceuticals, are sensitive to temperature fluctuations. Thus, temperature monitoring during production, transportation, and storage is critical. Facile indicators are required to monitor temperature conditions via color changes in real time. This study aimed to prepare and apply thiol-functionalized covalent organic frameworks (COFs) as a novel indicator for monitoring thermal history and temperature abuse. The COFs underwent obvious color changes from bright yellow to purple after exposure to different temperatures for varying durations. The reaction kinetics are analyzed under isothermal conditions, which reveal that the order of reaction rates is k_−20°C < k_4°C < k_20°C < k_35°C < k_55°C. The activation energy (E_a) of the COFs is calculated using the Arrhenius equation as 50.71 kJ moL⁻¹. The COFs are capable of sensitive color changes and offer a broad temperature tracking range, thereby demonstrating their application potential for the monitoring of temperature and time exposure history during production, transportation, and storage. This excellent performance thermal history indicator also shows promise for expanding the application field of COFs.     

Structural silicone sealants after exposure to laboratory test for durability assessment

During the service life of structural sealant glazing (SSG) facades, the load-bearing capacity of the silicone bonds needs to be guaranteed. Laboratory tests can assess the durability of SSG-systems based on mechanical characteristics of the bond after simultaneous exposure to both climatic and mechanical loads. This article studies how the material characteristics of two common structural sealants are affected by laboratory and field exposure. Dynamic mechanical analysis (DMA) confirms a reduction in the dynamic modulus of exposed silicone samples. Results from thermogravimetric analysis, Fourier-transform infrared spectroscopy, differential scanning calorimetry, and small-angle X-ray scattering/wide-angle X-ray scattering show differences between the two sealants and indicate no/minor changes in the composition and morphology of the laboratory and field exposed sealants. Mechanical characterization methods, such as DMA, and tensile and shear testing of the structural bond, are shown to be sensitive toward the combined climatic and mechanical loadings, and are hence suitable for studying degradation mechanisms of structural sealants.     

Characteristics and Cryopreservation of Semen of Sex-Reversed Females of Salmonid Fish

Sex reversal has been used as a breeding strategy by salmonid fish to produce genetically and phenotypically single sex populations. Production of all-female fish has great importance for the creation of monosex female triploids of salmonid fish, which are valued for their sterility, lack of female maturation, and larger commercial size. Among salmonids, the majority of rainbow trout (Oncorhynchus mykiss) production is based on all-female production with a high proportion of all-female triploid production in Europe. The main aim of this review is to present the recent knowledge regarding sex-reversed females (SRFs) of salmonid fish. We discuss the methods of sex reversal as well as their effects on the morphology and histology of the reproductive tract. We focus on the characteristics of SRF semen as well as the factors determining semen quality. The lower quality of SRF sperm compared to that of normal males has resulted in the need for the artificial maturation of semen. Most importantly, methods of semen storage—both short-term and long-term (cryopreservation)—that can improve hatchery operations are presented with the special emphasis on recent progress in development of efficient cryopreservation procedures and use of cryopreserved semen in hatchery practice. Moreover, we also address the emerging knowledge concerning the proteomic investigations of salmonid sperm, focusing primarily on the proteomic comparison of normal male and SRF testicular semen and presenting changes in SRF rainbow trout sperm proteome after in vitro incubation in artificial seminal plasma.     

基于GA-BP的汽车风振噪声声品质预测模型

目前对于汽车风振噪声的优化研究主要以声压级（Sound pressure level，SPL）作为单一评价指标，既不能全面反映噪声的物理属性，也无法考虑人耳对噪声的主观认知过程。为准确评价风振噪声，引入声品质，运用大涡模拟（Large eddy simulation，LES）对风振噪声进行数值仿真，根据实车道路试验判断仿真的准确性；对仿真结果进行声品质客观评价与主观评价，综合声品质客观评价参数与声品质主观评价试验结果建立BP神经网络预测模型；利用遗传算法（Genetic algorithm，GA），进一步对BP神经网络的结构参数进行优化，建立GA-BP声品质预测模型。研究结果表明，GA-BP声品质预测模型在训练速度和预测精度上都优于BP神经网络预测模型。预测模型基于声品质主客观评价结果，其预测值可以代替传统的声压级评价指标，为风振噪声提供更为准确合理的评价。     

Dynamic energy and mass balance model for an industrial alkaline water electrolyzer plant process

This paper proposes a parameter adjustable dynamic mass and energy balance simulation model for an industrial alkaline water electrolyzer plant that enables cost and energy efficiency optimization by means of system dimensioning and control. Thus, the simulation model is based on mathematical models and white box coding, and it uses a practicable number of fixed parameters. Zero-dimensional energy and mass balances of each unit operation of a 3 MW, and 16 bar plant process were solved in MATLAB functions connected via a Simulink environment. Verification of the model was accomplished using an analogous industrial plant of the same power and pressure range having the same operational systems design. The electrochemical, mass flow and thermal behavior of the simulation and the industrial plant were compared to ascertain the accuracy of the model and to enable modification and detailed representation of real case scenarios so that the model is suitable for use in future plant optimization studies. The thermal model dynamically predicted the real case with 98.7 % accuracy. Shunt currents were the main contributor to relative low Faraday efficiency of 86 % at nominal load and steady-state operation and heat loss to ambient from stack was only 2.6 % of the total power loss.     

Effects of rice bran fermented with Lactobacillus plantarum on palatability,volatile profiles,and antioxidant activity of brown rice noodles

Brown rice noodles (RN) are typical whole-grain products with health benefits. This study investigated the effects of rice bran fermented with Lactobacillus plantarum on palatability, volatile profiles, and antioxidant activity of brown RN. Three kinds of RN, including RN, brown RN (BRN), and bran fermented RN (BFRN), were involved in this study. The results indicated that bran fermentation reduced the cooking loss of BFRN and improved the elongation and the sensory attributes of brown RN. After fermentation, aldehydes were significantly decreased while alcohols increased, and more pleasant flavours were shown in BFRN. Fermentation increased the content of free phenolics and decreased the content of bound phenolics. Among the four major phenolics detected in this study, ferulic acid was the most abundant one in all three RN samples. The DPPH radical scavenging activity and the ferric reducing antioxidant power of free phenolics in BFRN increased significantly compared to BRN. This study proved that rice bran fermentation is an effective approach to improve palatability, enrich the flavour as well as enhance the antioxidant activity of brown RN, which may facilitate the development of processing technology for brown RN.