CuInS2/SiNWs/Si composite material for application as potential photoelectrode for photoelectrochemical hydrogen generation

This work aims at developing a new composite material based on nanosized semiconducting CuInS₂ (CIS) particles combined with silicon nanowires grown on a silicon substrate (SiNWs/Si) for photoelectrochemical (PEC)-splitting of water. The CIS particles were prepared via a colloidal method using N-methylimidazole (NMI) as the solvent and an annealing treatment. The SiNWs were obtained by chemical etching of silicon (100) substrates assisted by a metal. The CIS/SiNWs/Si composite material was obtained by deposition of an aliquot of a suspension of CIS particles onto the SiNWs/Si substrate, using spin coating followed by a drying step. The XRD pattern demonstrated that CuInS₂ grows in the tetragonal/chalcopyrite phase, while SiNWs/Si presents a cubic structure. The SEM images show semi-spherical particles (～10 nm) distributed on the surface of silicon nanowires (～10 μm). The EIS measurements reveal n-type conductivity for CIS, SiNWs/Si and CIS/SiNWs/Si materials, which could favour the oxidation reaction of water molecules.     

Overseas Cooperation of Chinese Oil Enterprises in 2017

This paper analyzes the status quo and progress of overseas oil and gas business cooperation built by Chinese oil enterprises in 2017. With the slow recovery of the oil and gas industries as a whole, the overseas oil and gas business of Chinese oil enterprises has continued to grow in size, and all-round cooperation progress was made along the Belt and Road. Breakthroughs were made in oil and gas cooperation between China and the United States. In the meantime, new features have emerged in the overseas cooperation of Chinese enterprises, and a pattern of diversified investors has basically taken shape.     

Preparation of biaxially textured Ce1-x(Y0.2Zr0.8)xOδ buffer layers on RABiTS NiW tapes by chemical solution deposition

Highly (100)-oriented Ce_1-x(Y_0.2Zr_0.8)_xO_δ (CYZO) films were prepared on biaxially textured NiW substrates by a chemical solution deposition approach using metal inorganic salts as starting materials. It has been found that both the preferential orientation and surface roughness of CYZO films decrease gradually with increasing of the doping percentage of Y³⁺ and Zr⁴⁺ ions. The epitaxial growth relationship of (220)_CYZO//(200)_NiW and [00?l]_CYZO//[001]_NiW was demonstrated by XRD texture measurement as well as atomic resolution STEM observation. XRD, Raman and XPS spectra results indicate that Y³⁺ and Zr⁴⁺ ions were indeed introduced into CeO₂ lattice to substitute Ce⁴⁺ ions and form cubic fluorite CYZO solid solution. Moreover, CeO₂ buffer layer can be endowed a strong enough capability to prevent element diffusion through co-doping of yttrium and zirconium, provided that an optimal doping ratio of them is adopted. This will provide a new approach to fabricating strong-barrier single buffer layer for coated conductor.     

Moderate lameness leads to marked behavioral changes in dairy cows

Lameness is one of the most prevalent diseases affecting the welfare of cows in modern dairy production. Lameness leads to behavioral changes in severely lame cows, which have been investigated in much detail. For early detection of lameness, knowledge of the effects of moderate lameness on cow behavior is crucial. Therefore, the behavior of nonlame and moderately lame cows was compared on 17 Swiss dairy farms. On each farm, 5 to 11 nonlame (locomotion score 1 of 5) and 2 to 7 moderately lame (locomotion score 3 of 5) cows were selected for data collection in two 48-h periods (A, B) separated by an interval of 6 to 10 wk. Based on visual locomotion scoring, 142 nonlame and 66 moderately lame cows were examined in period A and 128 nonlame and 53 moderately lame cows in period B. Between these 2 periods, the cows underwent corrective hoof trimming. Lying behavior, locomotor activity, and neck activity were recorded by accelerometers (MSR145 data logger, MSR Electronics GmbH, Seuzach, Switzerland), and feeding and rumination behaviors by noseband sensors (RumiWatch halter, ITIN + HOCH GmbH, Liestal, Switzerland). Furthermore, visits to the brush and the concentrate feeder, and the milking order position were recorded. In comparison with nonlame cows, moderately lame cows had a longer lying duration, a longer average lying bout duration, and a greater lateral asymmetry in lying duration. Average locomotor activity, locomotor activity during 1 h after feed delivery or push-ups, and average neck activity were lower in moderately lame cows. Eating time and the number of eating chews (jaw movements) were reduced in moderately lame compared with nonlame cows, whereas no effect of moderate lameness was evident for ruminating time, number of ruminating chews and boluses, and average number of ruminating chews per bolus. Moderately lame cows visited the concentrate feeder and the brush less frequently, and they were further back in the milking order compared with nonlame cows. In conclusion, nonlame and moderately lame cows differed in a biologically relevant way in many of the behavioral variables investigated in this study. Therefore, the use of these behavioral changes seems to be promising to develop a tool for early lameness detection.     

Prediction of rock mass P wave velocity using blasthole drilling information

In this paper, the development of the models for the prediction of rock mass P wave velocity is presented. For model development, the database of 53 cases including widely used and recorded drilling parameters and P wave velocity was constructed from the field studies conducted in 13 open pit lignite mines. Both conventional linear, non-linear multiple regression and Adaptive Neuro Fuzzy Inference System (ANFIS) were used for model development. Prediction performance indicators showed that ANFIS model presented the best performance and it can successfully be used for the preliminary prediction of P wave velocities of rock masses.     

Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

A Novel Beam Search to Improve Neural Machine Translation for English-Chinese

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, overcoming the weaknesses of conventional phrase-based translation systems. Although NMT based systems have gained their popularity in commercial translation applications, there is still plenty of room for improvement. Being the most popular search algorithm in NMT, beam search is vital to the translation result. However, traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural machine translation improvements based on a novel beam search evaluation function. And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations. In the experiments, we conducted extensive experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments. The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.