L边密度计稳定性监控及U、Pu测量

本文采用金属Zr片作为质控样品监控L边密度计的长期稳定性，在此基础上采用L边密度计测量系列水相U标准溶液和水相Pu标准溶液，绘制水相U工作曲线和水相Pu工作曲线，建立了L边密度计测量U、Pu的分析方法，并采用该工作曲线测量了系列U和Pu标准溶液。结果显示，该方法既可测量水相U、Pu，也可测量有机相U、Pu，对于10 g/L以上的U溶液，测量结果的相对偏差小于5%；对于5 g/L以上的Pu溶液，测量结果的相对偏差小于1.7%。以上结果表明，本文所建立的L边密度计测量U、Pu的方法准确度良好，可用于实际U、Pu的测量。     

Application of artificial neural network optimization for resilient ceramic parts fabricated by direct ink writing

Geometries of ceramic parts for high-temperature sealing have great influence on their compression-resilience behaviors. In this work, an accurate and large-scale artificial neural network (ANN) was established to match the relationship between structural parameters and mechanical properties of ZrO₂ parts fabricated by 3D printing. Four geometry parameters of the designed ZrO₂ parts were imported as input and apparent Young's modulus and maximum deformation simulated by finite element method (FEM) were imported as output. FEM calculation provided 400 groups of data for the training of ANN, which greatly improved the predicted accuracy of the network. The predicted results show the mechanical performance of the parts with a range of modulus from 9.24 × 10⁻³ GPa to 100.35 × 10⁻³ GPa and a range of maximum deformation from 2.32% to 5.80% can be forecasted with error less than 8%. Based on the optimized structural parameters, the designed ZrO₂ parts were fabricated by Direct Ink Writing (DIW) technique. The experimental compression-rebound property is comparable to that of ANN prediction. It demonstrates that the combined method of ANN and FEM is a preferable way to optimize the structure and guide the fabrication of complex ceramic parts by 3D printing method.     

全自动集装箱码头装卸系统质量管理

全自动集装箱码头装卸系统集成了当今世界各项先进技术,在研发、制造、调试过程中,都要坚持质量第一、安全第一的原则,确保各项技术参数可靠,设备运行稳定。在总结国内几个全自动码头装卸系统的质量管理方法与经验的基础上,结合自动化码头自身特点,给出全自动集装箱码头装卸系统主要质量管理方法,进一步丰富发展自动化码头装卸系统建造过程中的“不欠债离岸”质量管理理念。     

No-reference quality assessment of dynamic sports videos based on a spatiotemporal motion model

This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.     

Partial electrode method for loss and physical parameter determination of piezoceramics: Simplification,error investigation and applicability

The IEEE standard to determine physical parameters of piezoceramics has been utilized for decades by many researchers, yet it omits presence of important loss factors and possesses serious deficits that restrict accurate parameter determination. To resolve these issues, the partial electrode (PE) method was previously proposed, though the focus has been merely made on development of the method itself. In this study, we provide method simplification and more detailed analysis. The omission of unnecessary samples greatly boosts experiment and analysis process. To prove that the PE method is reliable, possible causes of errors were investigated; it is shown that they were either negligibly small or can be resolved with proper calibration. Furthermore, Applicability of PE method to various types of piezoceramic materials and compatibility with impedance analyzers are shown. Finally, PE method is proved to be reliable and can be alternative to IEEE Standard on Piezoelectricity.     

Correlation between instrumental stress and oral processing property of chicken broiler breast under wooden breast myopathy

Wooden breast myopathy affects the quality of fresh and processed chicken breast muscle. The objective of this study was to construct a classification method by instrumental stress, and the effects of wooden breast myopathy on meat quality and oral processing property, and was to explore correlations between stress and oral processing parameters. The severity of wooden breast myopathy was highly correlated to fillet weight (R² = 0.740), thickness (R² = 0.826) and hardness (R² = 0.803) (P < 0.01). The 3D scatter model based on stress is robust and reliable to classify the fillets into four categories (normal, mild, moderate and severe wooden breast fillets), avoiding manual grading. Moisture, fat, collagen, pH, drip loss, cooking loss, thawing loss, purge loss, hardness, gumminess and chewiness significantly increased with the severity of wooden breast myopathy, whereas fat, ash and water/salt-soluble protein contents significantly decreased (P < 0.05). Shear force reached the maximum (36.32 N) when this myopathy was moderate. The myopathy led to an increase in masseter activity and the particle size of the bolus. Significantly higher correlations between stress, Dx(50) (R² = 0.790), Dx(90) (R² = 0.771) and D[4,3] (R² = 0.797) were found (P < 0.01). This study also showed that jaw movement and muscle activity could be used to understand the links between physical property and orally sensory property.     

Real-time molecular characterization of air pollutants in a Hong Kong residence: Implication of indoor source emissions and heterogeneous chemistry

Due to the high health risks associated with indoor air pollutants and long-term exposure, indoor air quality has received increasing attention. In this study, we put emphasis on the molecular composition, source emissions, and chemical aging of air pollutants in a residence with designed activities mimicking ordinary Hong Kong homes. More than 150 air pollutants were detected at molecular level, 87 of which were quantified at a time resolution of not less than 1 hour. The indoor-to-outdoor ratios were higher than 1 for most of the primary air pollutants, due to emissions of indoor activities and indoor backgrounds (especially for aldehydes). In contrast, many secondary air pollutants exhibited higher concentrations in outdoor air. Painting ranked first in aldehyde emissions, which also caused great enhancement of aromatics. Incense burning had the highest emissions of particle-phase organics, with vanillic acid and syringic acid as markers. The other noteworthy fingerprints enabled by online measurements included linoleic acid, cholesterol, and oleic acid for cooking, 2,5-dimethylfuran, stigmasterol, iso-/anteiso-alkanes, and fructose isomers for smoking, C₂₈-C₃₄ even n-alkanes for candle burning, and monoterpenes for the use of air freshener, cleaning agents, and camphor oil. We showed clear evidence of chemical aging of cooking emissions, giving a hint of indoor heterogeneous chemistry. This study highlights the value of organic molecules measured at high time resolutions in enhancing our knowledge on indoor air quality.