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.     

Unconditionally Secure Oblivious Polynomial Evaluation: A Survey and New Results

Oblivious polynomial evaluation (OPE) is a two-party protocol that allows a receiver, R to learn an evaluation f(α), of a sender, S's polynomial f(x), whilst keeping both α and f(x) private. This protocol has attracted a lot of attention recently, as it has wide ranging applications in the field of cryptography. In this article we review some of these applications and, additionally, take an in-depth look at the special case of information theoretic OPE. Specifically, we provide a current and critical review of the existing information theoretic OPE protocols in the literature. We divide these protocols into two distinct cases (three-party and distributed OPE) allowing for the easy distinction and classification of future information theoretic OPE protocols. In addition to this work, we also develop several modifications and extensions to existing schemes, resulting in increased security, flexibility and efficiency. Lastly, we also identify a security flaw in a previously published OPE scheme.     

我国水-能源-粮食耦合关系及影响因素

为缓解我国水、能源和粮食资源紧张问题，促进资源可持续利用，构建水-能源-粮食系统，利用耦合协调度模型对我国的30个省（自治区、直辖市）进行测算,并利用空间杜宾模型分析主要影响因素。结果表明：2003—2017年，我国能源、粮食评价[JP]指数高于水资源评价指数，系统综合评价指数逐年递增；大部分省份耦合协调度处于初级协调水平且呈现逐年上升的态势，个别省份耦合协调度濒临失调；耦合协调度空间自相关性较强，虽有明显波动，但是呈现逐年加强的态势；影响耦合协调度的主要因素有从业人口数、固定资产投资额、人均生产总值、人口总数、[JP]文盲人口占比、工业污染排放、城镇化。     

Effects of red-wine grape pomace on the quality and sensory attributes of beef hamburger patty

This study was conducted to evaluate the effect of red-wine grape pomaces on the quality and sensory attributes of beef hamburger patties. Both phenolic content and antioxidant activity were assessed using Syrah, Merlot and Cabernet Sauvignon pomaces. Following the assessment, hamburger patties were prepared with Merlot pomace at 0%, 2% and 4% for the patty quality and sensory attributes. Grape seeds possessed significantly higher phenolics and antioxidant activities over the seedless pomace (P < 0.05), whereas no significant difference was found for phenolics and antioxidant activities within the seeds and seedless pomaces. The patty pH decreased as the pomace was added for 2% and 4%. Colour values (L*, a* and b*) of patties lowered as the pomace was added. Allo-Kramer shear force and hardness values increased while cooking yield decreased (P < 0.05) with the addition of pomace. No significant difference between control and Merlot patties was found for flavour, juiciness and colour, whereas lower sensory attributes were observed for texture, taste and overall acceptability. It is observed that the addition of fermented red-wine grape pomace provides hamburger patties with health promoting factors such as antioxidant and other functional components, but it also provided darker, sourer and lower cooking yield.     

Effect of heat treatment on structural,morphological, dielectric and magnetic properties of Mg–Zn ferrite nanoparticles

Green combustion was used to prepare a ferrite composition of Mg_0.4Zn_0.6Fe₂O₄ using a blend of fresh lemon juice as a natural fuel-reductant. Effect of heat treatment on phase, morphological, dielectric, and humidity sensor properties is discussed. The formation of a cubic spinel ferrite has been established by XRD-diffraction and vibrational spectroscopic studies. The experimental lattice parameter ranges from 8.3721 to 8.3631 Å. The broadening of octahedral band (υ₂) in the vibrational spectra is an identification for the existence of ferrite nanoparticles in various sizes. The typical crystallite size ranges from 10.2 to 36.9 nm. Using micrographs obtained from field-effect scanning electron microscopy (FESEM), researchers observed a spherical-shaped microstructure with agglomerated nanoparticles. Dielectric investigations have shown that the current ferrite composition has typical dielectric dispersion. The highest reported value for saturation magnetization (M_s) in the present study is 33 emu/g. Magnetic behaviour is primarily influenced by magnetocrystalline anisotropy, cation distribution, and crystallite size. The existence of void spaces in the sintered samples, as well as their porous nature, rendered them suitable for humidity sensor applications. Sintered samples have good sensing capability at 900 °C. The current findings are integrated in terms of cation distribution and magnetocrystalline anisotropy, assuming fine size effects of ferrite nanoparticles.     

Volatile and non-volatile compound profiles of commercial sweet pickled mango and its correlation with consumer preference

Sweet pickled mango named Ma-Muang Bao Chae-Im is a traditional preserved mango from Hat Yai, Thailand. This study investigated (I) volatile and non-volatile compound profiles of commercial Ma-Muang Bao Chae-Im and (II) their relationship to consumer preference. Untargeted metabolomics profiling was performed by gas chromatography-mass quadrupole-time of flight analysis. There were 117 volatile and 44 non-volatile compounds annotated in six commercial brands of Ma-Muang Bao Chae-Im. Furthermore, 46 volatile and 19 non-volatile compounds’ discriminant markers were found by Partial least square discriminant analysis. Among those markers, sorbic and benzoic acid were observed in several brands; moreover, the combination of both compounds altered the volatile profile, especially the ester group. Partial least square regression revealed that overall consumer liking is correlated to 1-heptanol; 1-octanol; acetoin; acetic acid, 2-phenylethyl ester; D-manitol; terpenes and terpenoids, while firmness to sucrose and L-(-)-sorbofuranose. On the other hand, most ester compounds were not related to consumer preference.     

Data fusion and transfer learning empowered granular trust evaluation for Internet of Things

In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability.     

基于魅力工学的传统器物设计评价应用研究

目的 在传统器物的创新设计中,最重要的环节是了解消费者对所使用产品的不同感受与意向并转换为具体的设计要素.研究消费者心理的感性因素与传统器物设计元素之间的联系,确定设计要素,从而对产品进行创新设计,为提升传统器物附加值作出贡献.方法 以中国传统器物茶宠为例,首先对8位相关的茶宠专家进行访谈,通过魅力工学中的评价构造法整理并提取魅力因子,设计出问卷调查表;然后以访谈内容为依据,使用问卷调查法得到大众对茶宠的魅力评价,共回收84份有效问卷;最后应用数量化一类分析茶宠魅力因子影响权重.结果 得到了数量化一类统计表,选取了其中影响因素较大的魅力因子作为茶宠设计前的风格定调考量.结论 通过茶宠的研究案例证明了该理论的可行性,为未来传统器物的设计提供了更多元且新颖的设计依据.