Semantic word shifts in a scientific domain

Understanding semantic word shifts in scientific domains is essential for facilitating interdisciplinary communication. Using a data set of published papers in the field of information retrieval (IR), this paper studies the semantic shifts of words in IR based on mining per-word topic distribution over time. We propose that semantic word shifts not only occur over time, but also over topics. The shifts are examined from two perspectives, the topic-level and the context-level. According to the over-time word-topic distribution, stable words and unstable words are recognized. The diverging and converging trends in the unstable type reveal characteristics of the topic evolution process. The context-level shifts are further detected by similarities between word vectors. Our work associates semantic word shifts with the evolving of topics, which facilitates a better understanding of semantic word shifts from both topics and contexts.     

咖啡渣活性炭的制备、表征及其对Cr(Ⅵ)的吸附机制研究

以碘吸附值为评价指标，活化时间、活化温度和浸渍比为影响因素，采用响应面法试验设计对磷酸活化法制备咖啡渣活性炭的工艺条件进行优化，并通过静态吸附试验研究了不同吸附时间、溶液pH值和吸附温度条件下，活性炭对水溶液中Cr（Ⅵ）吸附性能的影响，最后利用Langmuir、Freundlich吸附等温方程、准一级动力学方程、准二级动力学方程和颗粒内部扩散方程进行拟合。试验结果表明，制备咖啡渣活性炭的最佳工艺条件为活化时间1 h、活化温度498℃、浸渍比1.72；在此条件下活性炭得率为30.4%，碘吸附值为（799±16）mg/g，比表面积为1 006 m²/g，孔容为0.779 cm³/g、微孔孔容为0.051 cm³/g、平均孔径为3.088 nm。较低pH值和较高温度能够促进活性炭对Cr（Ⅵ）的吸附；Langmuir等温方程能够更好地描述活性炭对Cr（Ⅵ）的吸附效果；活性炭对Cr（Ⅵ）的吸附分3个阶段：快速吸附阶段、慢速吸附阶段和吸附平衡阶段，10 min内可完成吸附总量的79%，360 min内达到吸附平衡，该吸附过程符合准二级吸附动力学方程。分析表明咖啡渣活性炭对Cr（Ⅵ）的吸附主要为单分子层的化学吸附。     

Headspace fingerprinting approach to identify the major pathway influencing volatile patterns of vinasse-cured duck processed by high pressure,as well as its impact on physicochemical and sensory attributes

As a decisive attribute, flavour could be influenced by HP treatments through multiple physical and chemical pathways within the high pressure (HP)-assisted meat curing process. This investigation aimed to identify the major pathway influencing volatile flavour patterns of two representative vinasse-cured duck (VCD) products with HP treatments (150–300 MPa/15 min), including wet and dry types, by employing headspace fingerprinting as an untargeted approach. Results suggested that HP treatments greatly lowered moisture contents and increased Warner-Bratzler shear force and thiobarbituric acid reactive substances of the cured samples. According to multivariate models, the volatile flavour patterns of the HP-processed VCD could be clearly separated from the unprocessed samples, but the VCD pressurised at different intensities represented similar volatile fingerprinting, which was validated by e-nose analysis. The discriminant analysis (OPLS-DA) model outlined vinasse-derived ethanol, acetic acid, 3-methyl-1-butanol, 2-methyl-1-butanol, phenethyl alcohol and 2-methyl-3-octanone as the major discriminant aromas across the unpressurised and pressurised samples.     

Image and Feature Space Based Domain Adaptation for Vehicle Detection

The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space. We employ objectives of the generative adversarial network and cycle consistency loss for image style transfer in image space. For feature space, we align feature distributions between the source domain and the target domain to improve the detection accuracy. Experiments are carried out using the method with two different datasets, proving that this technique effectively improves the accuracy of vehicle detection in the target domain.     

A novel method based on convolutional neural networks for deriving standard 12-lead ECG from serial 3-lead ECG

Frontiers of Information Technology & Electronic Engineering - Reconstruction of a 12-lead electrocardiogram (ECG) from a serial 3-lead ECG has been researched in the past to satisfy the need...     

基于UG的正交车铣加工回转体表面微观残留仿真

正交车铣加工的回转体表面由铣刀与工件的复合相对运动形成,其形成机理独特,多个参数影响其表面微观形貌。为研究切削参数对正交车铣回转体表面微观残留的影响,基于UG建立了正交车铣回转体表面的仿真加工方法,并通过Vericut构建了虚拟五轴车铣加工环境,由此仿真研究了周向每齿进给量对正交车铣回转体表面微观残留的影响,发现已加工表面微观残留高度随周向每齿进给量增加显著增大。     

PET的紫外老化性能及机理研究

采用力学、紫外-可见光分析和热失质等测试手段研究了PET改性料的紫外老化性能及老化机理。结果表明:复合助剂的加入能显著提升体系的力学性能保持率,进而提升其紫外老化寿命,提升的幅度随复合助剂中耐紫外剂含量的增加而显著增加。DSC分析表明,随着复合助剂的引入和老化的进行,改性料结晶度增加。文中进一步讨论了PET改性料的紫外老化机理。紫外-可见光分析表明,紫外老化能产生醌类和双醌类物质,进而提升PET改性料的紫外吸收度。     

不同有机物对硝酸盐氮测试的影响

研究了红糖、葡萄糖、乙酸钠、甲醇、乙醇、乙酸、丙酸、丁酸、正戊酸、混合有机溶剂等10种不同有机物对麝香草酚光谱法和离子色谱法测试硝酸盐氮的影响。结果表明,溶液中含有红糖或葡萄糖时,均会对麝香草酚法测试硝酸盐氮造成影响,使得测试结果偏大;在无硝酸根离子存在时,红糖和葡萄糖的质量浓度与硝酸盐氮的测试浓度非线性相关;而乙酸钠、甲醇、乙醇、乙酸、丙酸、丁酸、正戊酸和混合有机溶剂则对麝香草酚法测试硝酸盐氮没有影响。实验发现,红糖和葡萄糖在浓硫酸的作用下与麝香草酚发生Molisch反应,形成有色复合物和红棕色不溶性沉淀。实验采用离子色谱法测试硝酸盐氮时,红糖和葡萄糖等糖类有机物对测试结果均无影响。     

防止输送带打滑的新方法

针对目前输送带打滑的问题,通过对输送带打滑原理的分析,要想解决输送带的打滑,就需要动态调整输送带的张力。基于此设计了一种短距离输送机的输送带自动张紧装置,该装置通过2个电液推杆来张紧输送带,并给出了具体的自动控制策略,能很好地解决输送带打滑问题。