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.     

Exploration of GH94 Sequence Space for Enzyme Discovery Reveals a Novel Glucosylgalactose Phosphorylase Specificity

The substantial increase in DNA sequencing efforts has led to a rapid expansion of available sequences in glycoside hydrolase families. The ever-increasing sequence space presents considerable opportunities for the search for enzymes with novel functionalities. In this work, the sequence-function space of glycoside hydrolase family 94 (GH94) was explored in detail, using a combined approach of phylogenetic analysis and sequence similarity networks. The identification and experimental screening of unknown clusters led to the discovery of an enzyme from the soil bacterium Paenibacillus polymyxa that acts as a 4-O-β-d -glucosyl-d -galactose phosphorylase (GGalP), a specificity that has not been reported to date. Detailed characterization of GGalP revealed that its kinetic parameters were consistent with those of other known phosphorylases. Furthermore, the enzyme could be used for production of the rare disaccharides 4-O-β-d -glucosyl-d -galactose and 4-O-β-d -glucosyl-l -arabinose. Our current work highlights the power of rational sequence space exploration in the search for novel enzyme specificities, as well as the potential of phosphorylases for rare disaccharide synthesis.     

废气蓄热式热氧化炉装置的安全优化

分析近年来RTO装置发生的安全事故,找出了该类环保装置存在的安全风险,并在储罐与污水池废气分类处理、在线废气浓度检测仪与废气切断阀的位置设置、新风稀释及风机控制、阻火器与爆破片、操作压力、储罐呼吸阀后采用非接触废气罩收集、风机材质等方面提出了建议。     

面粉厂车间楼定向倾倒爆破

该楼体为框架结构,是车间楼和办公楼的结合体,由于加工面粉设备流程的需要,该楼同时承受动荷载和静荷载。楼体按照伸缩缝分为3部分,每部分的结构不相同,同部分不同层结构也各异。在爆破过程中严格控制各种参数,并采取有效的减振与防护措施,使此爆破工程在安全和质量上都达到了预期效果。     

Practical Application of the Probabilistic‐Statistical Model of the Suspension Separation in Hydrocyclones

An effective practical approach that allows not only a significant reduction in the scope of practical experiments in the course of studying suspension separation processes in hydrocyclones, but also makes it possible to assess the intensity of random components of the processes and define the interrelation between such components and hydrodynamics of flows in a hydrocyclone is presented. Within the frames of the developed probabilistic‐statistical model of suspension separation in hydrocyclones on the basis of statistical self‐similarity properties, a relationship was found between determined and random components of the processes. This allowed transitioning from three‐parameter probability density functions for suspension particles in hydrocyclones to two‐parameter functions; thus significantly improving the efficiency of practical application of the developed model.     

斑衣蜡蝉在葡萄上的危害及防治措施

斑衣蜡蝉是一种危害多种林木和果树的重要刺吸性害虫,主要分布于中国、日本、越南、韩国、印度和美国等地。该虫在经济林木中最喜危害葡萄,目前在宁夏地区随着转换寄主,现已扩散到了部分葡萄园,成为贺兰山东麓酿酒葡萄的重要虫害之一。为全面了解其研究进展,本文概述了国内外关于斑衣蜡蝉的寄主植物、形态特征、危害状况、发生规律、生活习性、诱发因素及防治措施等研究现状,以期为防治该虫,寻求进一步研究方向及探讨新的防治途径提供帮助。     

波形驱动下多参数约束高分辨率反演方法——以四川盆地渝西地区龙马溪组页岩气为例

基于叠后地震波形指示反演在薄储层预测方面的优势，以及叠前弹性参数较叠后弹性参数信息更丰富、对储层的敏感性更高的特点，根据岩石物理资料，应用地震驱动+储层构型约束的高精度叠前随机反演方法，探寻定量表征优质薄页岩的技术，以期为深层页岩气地质甜点预测提供技术支撑。首先，基于道集波形相似性、AVO特征和空间距离的三变量优选方法提取结构相似的井数据作为空间估值样本，然后建立待判别道集初始模型；其次，以统计的弹性阻抗作为先验信息，应用“基于叠前道集特征指示的马尔科夫链-蒙特卡洛随机模拟算法”进行叠前地震波形指示反演，最终得到高精度的叠前弹性参数反演成果。实际应用表明，应用所提方法有效预测了龙一段一亚段1-2小层优质页岩厚度，基于特征参数的井震高频模拟精确模拟了龙一段一亚段1-2小层地质甜点参数，为页岩气勘探提供了技术支撑。     

食用槟榔货架期内品质控制研究

目的：探究食用槟榔返卤返白的原因。方法：主要通过搜集2000—2020年涉及食用槟榔卤水专利，以及相关工厂案例进行研究与分析。结果：在食用槟榔卤水的制备过程中原料的粒径大小、环境温度与湿度的高低、样品中水分含量及设备的自动化程度均可能造成食用槟榔返卤返白。结论：加工槟榔时应采取以严格控制水分、复配添加剂使用为主，工艺包装调整为辅,给予低温贮藏市售环境的方法，抑制返卤返白的产生。     

DCNN深度特征与交替方向乘子的相关滤波跟踪

针对采用相关滤波的判别式目标跟踪遇到的瓶颈问题：由于目标快速移动引起边界效应，使得相关滤波器在学习与更新过程中可能会引入错误，最终错误的累积将导致跟踪失败。在采集深度学习特征与样本相似性度量的基础上，提出一种引入交替方向乘子方法的改进相关滤波目标跟踪算法，选择DCNN深度特征有效地表征待跟踪目标的初始状态，通过在线分类过程中样本相似性比对与半监督学习，辅助解决相关滤波器在学习过程中存在的自学习问题。所提目标跟踪算法特别适合训练样本为持续获得的、同时存储空间较小的机器学习过程，提高目标在快速运动与部分遮挡等复杂情况下的跟踪成功率，针对VOT2016标准测试视频的实验表明：当目标面临快速运动时，对比CN、SAMF、STC算法，所提DA-CFT跟踪算法将跟踪成功率分别由60.4%～73.4%、67.2%～82.9%、80.9%～88.1%提升至85.6%～91.0%。     

The generalized Dice similarity measures for Pythagorean fuzzy multiple attribute group decision making

The Pythagorean fuzzy set (PFS) is characterized by two functions expressing the degree of membership and the degree of nonmembership, which square sum of them is equal or less than 1. It was proposed as a generalization of a fuzzy set to deal with indeterminate and inconsistent information. In this study, we shall present some novel Dice similarity measures of PFSs and the generalized Dice similarity measures of PFSs and indicates that the Dice similarity measures and asymmetric measures (projection measures) are the special cases of the generalized Dice similarity measures in some parameter values. Then, we propose the generalized Dice similarity measures-based multiple attribute group decision-making models with Pythagorean fuzzy information. Then, we apply the generalized Dice similarity measures between PFSs to multiple attribute group decision making. Finally, an illustrative example is given to demonstrate the efficiency of the similarity measures for selecting the desirable ERP system.