Wetting and interfacial reactions in liquid Au-Ti alloys / ZrO2 system

This study investigates wetting of zirconia by Au-Ti alloys containing 0.6–4 wt% Ti in view of brazing zirconia to titanium with pure gold for biomedical applications. Experiments were carried out using sessile and dispensed drop methods under high vacuum at 1040–1250 °C. Bulk drops and Au-Ti / ZrO₂ interfaces were characterized by SEM and FEG-SEM with EDXS analysis. While Au does not wet zirconia, the contact angle θ being ∼ 120°, the addition of Ti in Au leads to a significant improvement of wetting due to the formation of a wettable oxide layer at Au-Ti / ZrO₂ interface. The nature of this oxide was determined by X-ray diffraction of the reaction layer after the detachment of the droplet from the substrate or after the dissolution of the droplet. The mechanism of formation and growth of the oxide layer and its growth kinetics were determined based on fine analysis of the Au-Ti / oxide layer / ZrO₂ interfacial system.     

面向回归测试的代码变更影响度量模型

软件待测版本相对上一个版本的代码变更,会对已有特性带来潜在的质量风险,这一风险水平直接与回归测试用例的优先级相关联.回归测试设计过程中的一个重要问题是如何衡量代码变更对回归测试用例优先级的影响.本文在回归测试用例优先级评估模型的基础上,从测试覆盖的角度建立起回归测试用例与代码变更的直接关联,从代码整体耦合性的角度建立起回归测试用例与代码变更的间接关联,分析了代码变更对回归测试的显性影响和隐性影响,进而结合回归测试用例优先级的评估要求提出了一个新的度量模型.实验结果显示,使用该模型度量代码变更对回归测试用例优先级的影响水平,可以得到比较全面和客观的定量结果,从而为回归测试用例优先级的评估提供有效的支持.     

On-line monitoring of key nutrients in yoghurt samples using digitally labelled Raman spectroscopy

On-line monitoring of the fermentation process is essential for improving the quality of yoghurt products. We developed an on-line monitoring system based on digitally labelled Raman spectroscopy (DLRS). In DLRS, the strategy of Monte Carlo competitive adaptive reweighted sampling selection was proposed to isolate spectral bands according to a high-density discrete wavelet transform domain, which greatly suppressed the matrix effect on the calibration models. We demonstrated the feasibility of DLRS using 72 practical samples, and 4 key nutrients protein, fat, sucrose and total solids were determined simultaneously. The satisfactory results indicate that the DLRS system has capability for on-line monitoring of 4 key nutrients during yoghurt fermentation, thus enabling intelligent control of yoghurt production.