The Electrochemical Response of Single Crystalline Copper Nanowires to Atmospheric Air and Aqueous Solution

In this paper, single crystalline copper nanowires (CuNWs) have been electrochemically grown through anodic aluminum oxide template. The environmental stability of the as‐obtained CuNWs in both 40% relative humidity (RH) atmosphere and 0.1 m NaOH aqueous solution has been subsequently studied. In 40% RH atmosphere, a uniform compact Cu₂O layer is formed as a function of exposure time following the logarithmic law and epitaxially covers the CuNW surfaces. It is also found that the oxide layers on CuNWs are sequentially grown when subjected to the cyclic voltammetry measurement in 0.1 m NaOH solution. An epitaxially homogeneous Cu₂O layer is initially formed over the surface of the CuNW substrates by solid‐state reaction (SSR). Subsequently, the conversion of Cu₂O into epitaxial CuO based on the SSR takes place with the increase of applied potential. This CuO layer is partially dissolved in the solution forming Cu(OH)₂, which then redeposited on the CuNW surfaces (i.e., dissolution‐redeposition (DR) process) giving rise to a mixed polycrystalline CuO/Cu(OH)₂ layer. The further increase of applied potential allows the complete oxidation of Cu₂O into CuO to form a dual‐layer structure (i.e., CuO inner layer and Cu(OH)₂ outer layer) with random orientations through an enhanced DR process.     

Experimental analysis of fuel from fish processing industry waste in a diesel engine

In the present work, biofuel derived from industrial fish processing industry waste is used in diesel engines to study its suitability . Biofuel from industry fish waste is produced through catalytic cracking, and its quality has been improved through distillation. A single cylinder 4.5 kW at 1500 rpm was used to find the suitability of biofuel and undistilled biofuel in diesel engine. Experimental results show that the brake thermal efficiency of biofuel and undistilled biofuel is similar. Brake thermal efficiency for diesel, undistilled biofuel and biofuel is 29.98, 32.12 and 32.4%, respectively, at 80% load. Carbon monoxide, unburnt hydrocarbons, particulate matter and oxides of nitrogen emissions increase with undistilled biofuel compared to biofuel. There is a small reduction in carbon dioxide emission with undistilled biofuel compared to biofuel. Even though the cylinder pressure is high with undistilled biofuel, the intensity of premixed combustion is lower than distilled biofuel. The ignition delay and combustion duration increase with undistilled biofuel. Finally, it is concluded that the fuel derived from fish processing industry waste can be used as a fuel for diesel engine after distillation.     

Incentives for quality improvement efforts coordination in supply chains with partial cost allocation contract

In this paper, we consider quality improvement efforts coordination in a two-stage decentralised supply chain with a partial cost allocation contract. The supply chain consists of one supplier and one manufacturer, both of which produce defective products. Two kinds of failure cost occur within the supply chain: internal and external. The supplier and the manufacturer determine their individual quality levels to maximise their own profits. We propose a partial cost allocation contract, under which the external failure cost is allocated between the manufacturer and the supplier at different rates based on information derived from failure root cause analysis. If the quality levels of the supplier and the manufacturer are observable, we show that the partial cost allocation contract coordinates the supply chain, provided that the failure root cause analysis does not erroneously identify the manufacturer’s fault as the supplier’s, and the supplier does not take responsibility for the manufacture’s fault. In the single moral hazard model, where only the quality level of the supplier is unobservable, the optimal share rates require the supplier to take some responsibility for the manufacture’s fault. However, in the double moral hazard model, where quality levels of the supplier and the manufacturer are unobservable to each other, the optimal share rates require the supplier not to take responsibility for the manufacturer’s fault. It is noted that the root cause analysis conducted by the manufacturer may have its disadvantage in attributing the fault to the supplier when both sides are at fault. We also propose a contract based on the dual root cause analysis to reduce the supplier’s penalty cost. Numerical results illustrate that the partial cost allocation contract satisfies the fairness criterion compared with the traditional cost allocation contract.     

Bamboo reinforced concrete: a critical review

The use of small diameter whole-culm (bars) and/or split bamboo (a.k.a. splints or round strips) has often been proposed as an alternative to relatively expensive reinforcing steel in reinforced concrete. The motivation for such replacement is typically cost—bamboo is readily available in many tropical and sub-tropical locations, whereas steel reinforcement is relatively more expensive—and more recently, the drive to find more sustainable alternatives in the construction industry. This review addresses such ‘bamboo-reinforced concrete’ and assesses its structural and environmental performance as an alternative to steel reinforced concrete. A prototype three bay portal frame, that would not be uncommon in regions of the world where bamboo-reinforced concrete may be considered, is used to illustrate bamboo reinforced concrete design and as a basis for a life cycle assessment of the same. The authors conclude that, although bamboo is a material with extraordinary mechanical properties, its use in bamboo-reinforced concrete is an ill-considered concept, having significant durability, strength and stiffness issues, and does not meet the environmentally friendly credentials often attributed to it.     

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are translated incorrect, the final translation results’ quality can still be guaranteed. In order to solve the problem of mistranslation and missed translation effectively, and improve the accuracy and completeness of long sentence translation in machine translation, this paper proposes a key information fused neural machine translation model based on Transformer. The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder. After the same encoding as the source language text, it is fused with the output of the source language text encoded by the encoder, then the key information is processed and input into the decoder. With incorporating keyword information from the source language sentence, the model’s performance in the task of translating long sentences is very reliable. In order to verify the effectiveness of the method of fusion of key information proposed in this paper, a series of experiments were carried out on the verification set. The experimental results show that the Bilingual Evaluation Understudy (BLEU) score of the model proposed in this paper on the Workshop on Machine Translation (WMT) 2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset. The experimental results show the advantages of the model proposed in this paper.     

Estimating Facial Reflectance Properties Using Shape-from-Shading

In this paper we show how to estimate facial surface reflectance properties (a slice of the BRDF and the albedo) in conjunction with the facial shape from a single image. The key idea underpinning our approach is to iteratively interleave the two processes of estimating reflectance properties based on the current shape estimate and updating the shape estimate based on the current estimate of the reflectance function. For frontally illuminated faces, the reflectance properties can be described by a function of one variable which we estimate by fitting a curve to the scattered and noisy reflectance samples provided by the input image and estimated shape. For non-frontal illumination, we fit a smooth surface to the scattered 2D reflectance samples. We make use of a novel statistical face shape constraint which we term ‘model-based integrability’ which we use to regularise the shape estimation. We show that the method is capable of recovering accurate shape and reflectance information from single grayscale or colour images using both synthetic and real world imagery. We use the estimated reflectance measurements to render synthetic images of the face in varying poses. To synthesise images under novel illumination, we show how to fit a parametric model of reflectance to the estimated reflectance function.     

Sliding Mode Control with Adaptive Fuzzy Dead-Zone Compensation of an Electro-hydraulic Servo-System

Electro-hydraulic servo-systems are widely employed in industrial applications such as robotic manipulators, active suspensions, precision machine tools and aerospace systems. They provide many advantages over electric motors, including high force to weight ratio, fast response time and compact size. However, precise control of electro-hydraulic systems, due to their inherent nonlinear characteristics, cannot be easily obtained with conventional linear controllers. Most flow control valves can also exhibit some hard nonlinearities such as dead-zone due to valve spool overlap. This work describes the development of an adaptive fuzzy sliding mode controller for an electro-hydraulic system with unknown dead-zone. The boundedness and convergence properties of the closed-loop signals are proven using Lyapunov stability theory and Barbalat’s lemma. Numerical results are presented in order to demonstrate the control system performance.