Study on the Height of the Mining-Induced Water-Conducting Fracture Zone Under the Q 2l Loess Cover of the Jurassic Coal Seam in Northern Shaanxi,China

A method to calculate the height of a water-conducting fractured zone (HWCFZ) was developed based on the plate and shell theory, and the development of the HWCFZ in bedrock and Q2l loess strata is discussed in detail. First, the subsidence-deflection curve equation of the overlying stratum is theoretically derived, and then the ultimate deflection and free space height of rock strata are calculated. Moreover, the strata tensile strain is calculated by using integral calculus. In addition, the failure state of the rock is analyzed by comparing the theoretically calculated tensile strain with the experimentally measured yield tensile strain, allowing one to attain the maximum value of HWCFZ. This approach was tested at the Jinjitan coal mine; the theoretically predicted, experimentally measured, and numerically computed maximum HWCFZ values were 189.5, 187.3, and 188.5 m, respectively, demonstrating the accuracy of the proposed method. These results are highly significant for safe and environment-friendly coal mining in northwest Shaanxi, China.     

太赫兹脉冲焦平面成像技术的发展与应用

作为太赫兹技术中的重要组成部分,太赫兹脉冲焦平面成像一经问世就引起了行业内的广泛关注,人们引入了各种方法去提升此成像技术的测量性能,同时也尝试将此成像技术应用于不同的工业和基础研究领域。本文综述了近年来人们对太赫兹脉冲焦平面成像的技术改良和应用研究,包括提升成像系统的空间分辨率、信噪比、信息获取能力,以及将此成像技术应用于光谱识别检测、超表面器件功能验证、太赫兹特殊光束测量、太赫兹表面波观测等,希望该综述能够推动太赫兹脉冲焦平面成像的进一步技术革新和应用拓展。     

应用型电气自动化人才培养模式的改革与创新

根据电气工程及其自动化这门专业的特点以及学这门专业的学生的知识和能力体系的要求,对我国现在的人才培养的模式进行了一定的改革。对专业的基础课和实践教学环节都进行了一定程度的改革与创新,优化了专业课中的人才培养方面的方案。对于教学内容和教学方法进行了一定程度上的调整和完善。     

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.