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.     

Vulnerable objects detection for autonomous driving: A review

Object detection performed by Autonomous Vehicles (AV)s is a crucial operation that comes ahead of various autonomous driving tasks, such as object tracking, trajectories estimation, and collision avoidance. Dynamic road elements (pedestrians, cyclists, vehicles) impose a greater challenge due to their continuously changing location and behaviour. This paper presents a comprehensive review of the state-of-the-art object detection technologies focusing on both the sensory systems and algorithms used. It begins with a brief introduction on the autonomous driving operations and challenges. Then, different sensory systems employed on existing AVs are elaborated while illustrating their advantages, limitations and applications. Also, sensory systems employed by different research are reviewed. Moreover, due to the significant role Deep Neural Networks (DNN)s are playing in object detection tasks, different DNN-based networks are also highlighted. Afterwards, previous research on dynamic objects detection performed by AVs are reviewed in tabular forms. Finally, a conclusion summarizes the outcomes of the review and suggests future work towards the development of vehicles with higher automation levels.     

Mechanical properties and wear behavior of Tin+1(Al,A)Cn (A = Ga,In, Sn,n = 1, 2) via quasi-high-entropy of single atomic thick A layer

The strengthening method of multi-element M-site solid solution is a common approach to improve mechanical properties of MAX phase ceramic. However, the research on capability of multi-element A-site solid solution to improve mechanical properties has rarely been reported. Thereupon, quasi-high-entropy MAX phase ceramic bulks of Ti₂(Al_1?xA_x)C and Ti₃(Al_1?xA_x)C₂ (A = Ga, In, Sn, x = 0.2, 0.3, 0.4) were successfully synthesized by in situ vacuum hot pressing via multi-elements solid solution. The multi-elements solid solution in single-atom thick A layer was confirmed by X-ray diffraction and X-ray photoelectron spectroscopy as well as by energy dispersive X-ray spectroscopy mappings. Effects of doped multi-elements contents on the phase, microstructure, mechanical properties, and high temperature tribological behaviors were studied. Results demonstrated that the Vickers hardness, anisotropic flexural strength, fracture toughness, and tribological properties of Ti–Al–C based MAX ceramics could be remarkably improved by constitution of quasi-high-entropy MAX phase in A layers. Moreover, the strengthening and wear mechanisms were also discussed in detail. This method of multi-element solid solution at A-site provides new way to enhance mechanical properties of other MAX phase ceramics.     

Development of vibration damping materials based on butyl rubber: A study of the phase equilibrium,rheological, and dynamic properties of compositions

A detailed study of butyl rubber-based vibration damping formulations linking their composition, morphology, phase structure, viscosity, mechanical loss factor, and other characteristics is presented for the first time. High performance of the compositions including aromatic petroleum oil is explained by limited solubility of the plasticizer that leads to the formation of a highly-viscous emulsion (η_20°C ≈ 1000 Pa·s) consisting of a swollen butyl rubber matrix and dispersed oil droplets in the broad composition range. Chalk is found to be the best inorganic filler as its spherical particles provide strong adhesion to the reinforcing layer of aluminum foil. Aiming to eliminate ecologically unfriendly aromatic compounds, a new low-cost binding agent formulation based on butyl rubber mixed with polyisobutylene and highly refined mineral oil is suggested. Being environmentally safe, it possesses high viscosity of 1000–3000 Pa·s, cohesion strength of 3.5–5.0 N/cm, penetration of 4.5–6.0 mm, and mechanical loss factor up to 0.34 at room temperature, which are as good as, or even better than, the properties of currently produced vibration damping materials containing aromatic compounds. New materials can be used in car and aircraft parts for effective vibration isolation.     

Microstructural and mechanical properties assessment of transient liquid phase bonding of CoCuFeMnNi high entropy alloy

The transient liquid phase (TLP) bonding of CoCuFeMnNi high entropy alloy (HEA) was studied. The TLP bonding was performed using AWS BNi-2 interlayer at 1050 °C with the TLP bonding time of 20, 60, 180 and 240 min. The effect of bonding time on the joint microstructure was characterized by SEM and EDS. Microstructural results confirmed that complete isothermal solidification occurred approximately at 240 min of bonding time. For samples bonded at 20, 60 and 180 min, athermal solidification zone was formed in the bonding area which included Cr-rich boride and Mn₃Si intermetallic compound. For all samples, the γ solid solution was formed in the isothermal solidification zone of the bonding zone. To evaluate the effect of TLP bonding time on mechanical properties of joints, the shear strength and micro-hardness of joints were measured. The results indicated a decrement of micro-hardness in the bonding zone and an increment of micro-hardness in the adjacent zone of joints. The minimum and maximum values of shear strength were 100 and 180 MPa for joints with the bonding time of 20 and 240 min, respectively.     

Achieving excellent energy storage density of Pb0.97La0.02(ZrxSn0.05Ti0.95-x)O3 ceramics by the B-site modification

The applications of antiferroelectric (AFE) materials in miniaturized and integrated electronic devices are limited by their low energy density. To address the above issue, the antiferroelectricity of the reinforced material was designed to improve its AFE-ferroelectric (FE) phase transition under electric fields. In this present study, the composition of Zr⁴⁺ (0.72 Å) and Ti⁴⁺ (0.605 Å) at B-site of Pb_0.97La_0.02(Zr_xSn_0.05Ti_0.95-x)O₃ ceramics with orthogonal reflections are synthesized via the tape-casting method. These ceramics are modified to enhance their antiferroelectricity by reducing their tolerance factor. A recoverable energy storage density W_rec 12.1 J/cm³ was obtained for x = 0.93 under 376 kV/cm, which is superior value than reported until now in lead-based energy storage systems. Moreover, the discharge energy density can reach 10.23 J/cm³, and 90 % of which can be released within 5.66 μs. This work provides a new window and potential materials for further industrialization of pulse power capacitors.     

高熵形状记忆合金的研究进展

高熵形状记忆合金是在等原子比NiTi合金的基础上,结合高熵合金的概念,逐渐发展起来的一种新型高温形状记忆合金。近年来,已开发出了综合性能优异的(TiZrHf)50(NiCoCu)50系和(TiZrHf)50(NiCuPd)50系高熵形状记忆合金,引起了广泛的关注和研究兴趣。本文从物相组成、微观组织、马氏体相变行为、形状记忆效应和超弹性等角度出发,综述了高熵形状记忆合金的研究进展,并对高熵形状记忆合金未来的研究重点进行了展望。     

一种植物油中苯并（a）芘含量测定的固相萃取前处理方法

为了建立一种准确性高、成本低的植物油中苯并(a)芘测定的样品前处理方法，基于GB 5009.7—2016以自制氧化铝柱为固相萃取柱，采用单因素试验对称样量、洗脱剂量、洗脱流速、吸附剂存放时间、吸附剂量这5个影响植物油中苯并（a）芘洗脱的因素进行研究，优化前处理条件，并对测定方法进行考察。结果表明：优化的前处理条件为称样量0.100 0 g、洗脱剂量120 mL、吸附剂（氧化铝）量22 g、洗脱流速1滴/2 s、吸附剂存放时间少于12周；方法检出限为0.2 μg/L，样品加标回收率为94.23%～100.00%，RSD为1.20%～7.36%；同一样品测定结果与SGS测定值接近，相对平均偏差为2.36%～3.50%。说明本试验方法测定结果准确，可应用于油脂企业植物油中痕量苯并（a）芘的测定。     

食品安全国家标准中维生素的测定方法及进展

人体所必需的营养素除了蛋白质、脂类、糖类等能量物质外,维生素也是不可或缺的营养物质,是评价其营养质量的关键指标。检测食品中的维生素含量,是有效保证其质量与安全的必要条件。因此,对现有国家标准食品中维生素的检测方法进行综述,总结各方法的前处理及检出限等,为增强检测工作效率,以及食品检测方法的研究和发展提供参考。     

A Highly Sensitive,Reversible, and Bidirectional Humidity Actuator by Calcium Carbonate Ionic Oligomers Incorporated Poly(Vinylidene Fluoride)

Sensitivity and multi-directional motivation are major two factors for developing optimized humidity-response materials, which are promising for sensing, energy production, etc. Organic functional groups are commonly used as the water sensitive units through hydrogen bond interactions with water molecules in actuators. The multi-coordination ability of inorganic ions implies that the inorganic ionic compounds are potentially superior water sensitive units. However, the particle forms of inorganic ionic compounds produced by classical nucleation limit the number of exposed ions to interact with water. Recent progress on the inorganic ionic oligomers has broken through the limitation of classical nucleation, and realized the molecular-scaled incorporation of inorganic ionic compounds into an organic matrix. Here, the incorporation of hydrophilic calcium carbonate ionic oligomers into hydrophobic poly(vinylidene fluoride) (PVDF) is demonstrated. The ultra-small calcium carbonate oligomers within a PVDF film endow it with an ultra-sensitive, reversible, and bidirectional response. The motivation ability is superior to other bidirectional humidity-actuators at present, which realizes self-motivation on an ice surface, converting the chemical potential energy of the humidity gradient from ice to kinetic energy.