Corrosion behaviors of carbon steel induced by life activities of Phaeodactylum tricornutum in a marine environment

Microbiologically influenced corrosion induced by bacteria has been studied for many years. Corrosion is known to be sensitive to the presence of microalgae, such as Phaeodactylum tricornutum. However, the life activity of P. tricornutum that influences the general and localized corrosion of carbon steel is not fully understood. The current study uses a combination of immersion tests and electrochemical experiments with a detailed surface characterization to reveal the naturally formed corrosion products with/without the presence of P. tricornutum. The results show that samples suffer from pitting corrosion and the averaged pit depths are approximately 15 μm under a light–dark cycle condition or a 24-h constant light condition. Meanwhile, the corrosion products are mainly comprised of γ-FeOOH and Fe₃O₄ in a constant light condition. However, γ-FeOOH, Fe₃O₄, and FeCO₃ are found in a light–dark cycle. This study proposes the fundamental mechanisms of the effect of P. tricornutum life activities on the corrosion performance of Q235 carbon steel, to fulfill the knowledge gaps of the presence of microalgae inducing the general and pitting corrosion of carbon steel.     

Effect of microstructural features on the corrosion behavior of severely deformed Al–Mg–Si alloy

The aim of this study was to determine the influence of severe plastic deformation processing and the changes in microstructure resulting therefrom on the corrosion resistance of an Al–Mg–Si alloy. The alloy was processed using incremental equal channel angular pressing, which caused a reduction in grain size from 15 to 0.9 µm. The grain refinement was accompanied by an increase in the number of grain boundaries and dislocations, and by changes in grain orientation. However, there was no change in the size and number of intermetallic particles, which presumably resulted in a constant number of galvanic couplings. Electrochemical experiments revealed only slight differences between the samples before and after processing. Higher potential transients/oscillations upon immersion and increased corrosion currents in the vicinity of corrosion potential point to slightly higher reactivity of the most refined material. This indicates that intermetallic particles are the most crucial microstructural elements in terms of corrosion resistance. Their impact exceeds that of grain boundaries, in particular, at the stage of corrosion initiation. The development of corrosion attack is controlled more by the microstructure of the matrix as the grain refinement resulted in a less pronounced corrosion attack in comparison with the coarse-grained sample.     

FPGA-based implementation of classification techniques: A survey

Recently, a number of classification techniques have been introduced. However, processing large dataset in a reasonable time has become a major challenge. This made classification task more complex and expensive in calculation. Thus, the need for solutions to overcome these constraints such as field programmable gate arrays (FPGAs). In this paper, we give an overview of the various classification techniques. Then, we present the existing FPGA based implementation of these classification methods. After that, we investigate the confronted challenges and the optimizations strategies. Finally, we highlight the hardware accelerator architectures and tools for hardware design suggested to improve the FPGA implementation of classification methods.     

Residual attention-based tracking-by-detection network with attention-driven data augmentation

Tracking-by-detection (TBD) is a significant framework for visual object tracking. However, current trackers are usually updated online based on random sampling with a probability distribution. The performance of the learning-based TBD trackers is limited by the lack of discriminative features, especially when the background is full of semantic distractors. We propose an attention-driven data augmentation method, in which a residual attention mechanism is integrated into the TBD tracking network as supplementary references to identify discriminative image features. A mask generating network is used to simulate changes in target appearances to obtain positive samples, where attention information and image features are combined to identify discriminative features. In addition, we propose a method for mining hard negative samples, which searches for semantic distractors with the response of the attention module. The experiments on the OTB2015, UAV123, and LaSOT benchmarks show that this method achieves competitive performance in terms of accuracy and robustness.     

杂化包覆玄武岩鳞片/环氧涂料制备与性能

本文在环氧涂料中添加玄武岩鳞片，提高其防腐蚀性能。针对玄武岩鳞片的团聚问题，通过机械力化学改性工艺，采用正硅酸四乙酯、HY-311型钛酸酯偶联剂、E-44型环氧树脂对玄武岩鳞片进行杂化包覆，结果表明，杂化包覆后玄武岩鳞片的沉降时间从2h提高至96 h。杂化包覆玄武岩鳞片添加量为20%涂层的性能最优，附着力为13.40 MPa，耐盐雾时间为2000 h，在3.5%NaCl溶液中浸泡2000 h后，0.01 Hz的阻抗模值仍然有5.15×109 Ω·cm2。     

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.     

Colossal dielectric response and relaxation behavior in novel system of Zr4+ and Nb5+ co-substituted CaCu3Ti4O12 ceramics

In this work, we developed a novel system of isovalent Zr⁴⁺ and donor Nb⁵⁺ co-doped CaCu₃Ti₄O₁₂ (CCTO) ceramics to enhance dielectric response. The influences of Zr⁴⁺ and Nb⁵⁺ co-substituting on the colossal dielectric response and relaxation behavior of the CCTO ceramics fabricated by a conventional solid-phase synthesis method were investigated methodically. Co-doping of Zr⁴⁺ and Nb⁵⁺ ions leads to a significant reduction in grain size for the CCTO ceramics sintered at 1060 °C for 10 h. XRD and Raman results of the CaCu₃Ti_3.8-xZr_xNb_0.2O₁₂ (CCTZNO) ceramics show a cubic perovskite structure with space group Im-3. The first principle calculation result exhibits a better thermodynamic stability of the CCTO structure co-doped with Zr⁴⁺ and Nb⁵⁺ ions than that of single-doped with Zr⁴⁺ or Nb⁵⁺ ion. Interestingly, the CCTZNO ceramics exhibit greatly improved dielectric constant (~10⁵) at a frequency range of 10²–10⁵ Hz and at a temperature range of 20–210 °C, indicating a giant dielectric response within broader frequency and temperature ranges. The dielectric properties of CCTZNO ceramics were analyzed from the viewpoints of defect-dipole effect and internal barrier layer capacitance (IBLC) model. Accordingly, the immensely enhanced dielectric response is primarily ascribed to the complex defect dipoles associated with oxygen vacancies by co-doping Zr⁴⁺ and Nb⁵⁺ ions into CCTO structure. In addition, the obvious dielectric relaxation behavior has been found in CCTZNO ceramics, and the relaxation process in middle frequency regions is attributed to the grain boundary response confirmed by complex impedance spectroscopy and electric modulus.     

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.     

Effects of Cu on the corrosion behavior and microstructure of Mg–Zn–Ca bulk metallic glass

For the purpose of developing biodegradable magnesium alloys with suitable properties for biomedical applications, Mg–Zn–Ca–Cu metallic glasses were prepared by copper mold injection methods. In the present work, the effect of Cu doping on mechanical properties, corrosion behavior, and glass-forming ability of Mg₆₆Zn₃₀Ca₄ alloy was studied. The experimental findings demonstrated that the incorporation of Cu decreases the corrosion resistance of alloys, but increases the microhardness and degradation rate slightly. However, the addition of a trace amount of Cu can make the samples have antibacterial properties. Therefore, Mg–Zn–Ca–Cu has great advantages in clinical implantation and is the potential implant material.