北斗星历解析及实时卫星位置解算实现

利用 C 语言编程进行北斗卫星星历数据的实时读取，更新结构体的卫星轨道参数， 从而实现北斗卫星位置的解算，并与武汉大学数据中心提供的北斗精密星历作比较，对解算的卫星位置结果进行评估，最大误差不超过 3.5 米，满足实际应用需要。     

Characteristic tryptic peptides and gelling properties of porcine skin gelatin affected by thermal action

Thermal action in extraction process had effects on characteristic tryptic peptides identification and gelling properties of porcine gelatin. SDS-PAGE, HPLC-LTQ/Orbitrap high-resolution mass spectrometry, texture analyser and rheometer were used to evaluate collagen depolymerisation degree, characteristic tryptic peptides and gelling properties of gelatins prepared in various thermal actions. Results showed that with increasing temperature and time, depolymerisation degree enlarged, while gel strength, gelling and melting temperature decreased. Mass spectra showed that 47 and 49 common characteristic tryptic peptides were identified in gelatins extracted at 50 °C and 100 °C with various times, respectively. Moreover, 34 common characteristic tryptic peptides were identified in all gelatin samples. Further comparison between this work and our previous investigations yielded 20 common characteristic tryptic peptides, which stably exist in various thermal actions. These common characteristic tryptic peptides may be very helpful for the accurate authentication of porcine gelatin.     

Authenticity green coffee bean species and geographical origin using near-infrared spectroscopy combined with chemometrics

To prevent the adulteration of agricultural resources and provide a solution to enhance the green coffee bean supply chain, authentication using the near-infrared spectroscopy (NIRS) technique was investigated. Partial least square with discrimination analysis (PLS-DA) models combined with various preprocessing methods were built from NIR spectra of 153 Vietnamese green coffee samples. The model combined with the standard normal variate and the first order of derivative yielded excellent performance in predicting coffee species with the error cross-validation of 0.0261. PLS-DA model of mean centre and first-order derivative spectra also yielded good performance in verifying geographical indication of green coffee with the error of 0.0656. By contrast, the predicting abilities of post-harvest methods were poor. The overall results showed a high potential of the NIRS in online authentication practices.     

多晶硅表面金属催化化学腐蚀法制绒研究现状

在多晶硅太阳能电池的生产过程中, 金刚线切割技术(Diamond wire sawn, DWS)具有切割速度快、精度高、原材料损耗少等优点, 受到了广泛关注。金刚线切割多晶硅表面形成的损伤层较浅, 与传统的酸腐蚀制绒技术无法匹配, 金属催化化学腐蚀法应运而生。金属催化化学腐蚀法制绒具有操作简单、结构可控且易形成高深宽比的绒面等优点, 具有广阔的应用前景。本文总结了不同类型的金属催化剂在制绒过程中的腐蚀机理及其形成的绒面结构, 深入分析和讨论了具有代表性的银、铜的单一及复合催化腐蚀过程及绒面结构和电池片性能。最后对金刚线切割多晶硅片表面的金属催化化学腐蚀法存在的问题进行了分析, 并展望了未来的研究方向。     

Relationships of tensile strength with crosslink density for the high-carbon black-filled EPDM compounds with various softeners

Equilibrium swelling and rheological tests were adopted to systematically investigate the effects of softener type and dosage on the crosslink densities. The results turned out that the chemical crosslink density could be distinguished from the physical crosslink density by comparing the results of equilibrium swelling and rheological tests. The liquid butadiene (LB) as a softener leads to the greatest reduction in crosslink density, followed by polyethylene wax (PW) and paraffinic oil (PO). The tensile strength decreases with increasing PO content while shows peak values with increase of LB and PW contents. The dependencies of chemical crosslink density on the aging time under 150°C are quite different for the three softeners, which can be expected from the double crosslinking networks consisting of small softener and large main crosslinking networks. Further investigation has been performed to correlate the tensile strength with chemical crosslink density of ethylene propylene diene monomer elastomer vulcanizates. Three different linear relationships can be obtained for the softeners independent of the aging time. It can now be expected from this study that the role of some new softeners in rubber compounds is not only confined to plasticization but also forms crosslinking networks in the peroxide-cured rubbers.     

Hydrogeochemical Processes and Inverse Modeling for a Multilayer Aquifer System in the Yuaner Coal Mine,Huaibei Coalfield,China

Coal mining can dramatically change hydrogeological conditions and induce serious environmental problems. Fifty groundwater samples were collected from the main aquifers in the Yuaner coal mine (Anhui Province, China). The results show that the main hydrogeochemical processes in the mine include dissolution, precipitation, pyrite oxidation, desulfurization, and cation exchange. The Neogene porous aquifer is affected by groundwater flow conditions; its main hydrogeochemical processes are dissolution of carbonate minerals and gypsum, and cation exchange. The Permian coal measure’s fractured sandstone aquifer was confirmed to be controlled by the region’s geological structure; its main hydrogeochemical processes are desulfurization and cation exchange. The Carboniferous Taiyuan limestone aquifer was determined by both groundwater flow conditions and regional geological structure; its main hydrogeochemical processes are dissolution of carbonate minerals and gypsum, pyrite oxidation, and cation exchange. Additionally, hydrogeochemical inverse modeling of the groundwater flow path confirm the hydrochemistry results and principal component analysis.

     

A self-adaptive synthetic over-sampling technique for imbalanced classification

Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning.     

Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

高碘酸盐的活化及降解水体有机污染物研究进展

根据高碘酸盐活化方式、活化机理和相关自由基种类等方面,叙述了国内外高碘酸盐高级氧化体系降解水体有机污染物方面的工作。基于氧化剂为高碘酸盐的高级氧化技术氧化能力强,能在较宽的pH范围内高效降解包括抗氧化能力极强的全氟辛酸(PFOA)在内的多种有机污染物,在水处理领域具有较好的应用潜力。依据目前的研究现状,结合实际需求,认为进行废水处理的小试或者中试、优化活化理论研究,以及明确各活性物质对有机物选择性降解的机理,是将来需要关注的问题以及研究方向。