学情调查和数据驱动专业基础课教学探索

文章以“数字电子技术基础”课程为对象,设计了基于教学数据和问卷调查的教学框架。通过学生情况调查和雨课堂教学数据掌握学习状态和学习能力,针对性设计了个性化作业布置、拓展延伸、疫情线上自学跟学双通道等特色教学方式。结课问卷表明教学设计得到了良好评价和认可。     

分布式多元随机动态场景生成及快速精准场景降维算法

高比例新能源及多源耦合是电力系统发展的重要特征,这也为系统稳定经济运行提出了新挑战。该文以园区型多能系统为对象,研究了分布式多元随机动态场景分析,从多时空角度有效量化不确定因素给系统造成的影响,可为系统灵活重构、多维度协同运行与决策提供有力模型与场景支撑。首先由预测误差驱动拟合多元功率预测误差概率分布,全面反映随机功率出力信息,提高模型泛化性;以时序相关范围参数为数据驱动关联变量,高效动态控制波动强度;最终场景生成利用逆变换映射思想保证置信度。然后针对典型场景提取,提出一种综合递归聚类思想的多段嵌套削减算法,结合改进Wasserstein距离指标,兼具准确、时效、稳定方面的优势。最后由对比实验论证该方法的前沿有效性。     

Evidence of fluid evolution of Baoshan Cu−Pb−Zn polymetallic deposit: Constraints from in-situ sulfur isotope and trace element compositions of pyrite

In-situ LA-ICP-MS and S isotopes of pyrite from the Baoshan Cu polymetallic deposit were conducted to investigate the ore-forming process and the enrichment mechanism of elements. Three generations of pyrite (Py I, Py II, and Py III) in the skarn-type ores and pyrite in the carbonate-hosted sulfide ores from central, western, and northern (C_Py, W_Py, and N_Py) mining districts are selected for comparison. Compared with Py I and Py III, the contents of most elements in Py II are apparently higher. The As and Se contents are high within a wide range and are decoupled in the growth band of the C_Py. The highest As, Se, and Pb contents were found in W_Py and N_Py. These results indicate the drastic changes in the temperature and fluid mixing during the mineralization. The occurrence of fluctuation and change in temperature and f(O₂) was triggered by intermittent pulses of magmatic-hydrothermal fluids, mixing with meteoric water, and water−rock interactions. The sulfur isotopes of all species of pyrite indicated the magmatic source. The change in the f(O₂) conditions caused slight differences in the sulfur isotope compositions. Consequently, a metallogenic model was proposed to explain the ore-forming processes.     

检测仪器及消解方式对罗布麻微量元素检测效果的影响

目的 探索罗布麻微量元素适宜的检测条件。方法 以新疆产罗布麻和白麻叶及其制品罗布麻茶为实验材料, 比较了电感耦合等离子体质谱法(inductively coupled plasma mass spectrometry, ICP-MS)和电感耦合等离子体原子发射光谱法(inductively coupled plasma atomic emission spectrometry, ICP-AES)2种仪器对其Li、B、Cr、Fe、Mn、Cu、Zn、Se和Sr 9种微量元素的检测效果, 同时对比了3种不同的湿法消解方式对检测结果的影响。结果 采用不同酸解液的3种湿法消解方法, 硝酸/过氧化氢消解液处理条件较温和, 元素损失量较少, 检测结果稍高于浓硝酸/高氯酸消解液处理的结果, 但所耗消解时间更长。对于易挥发元素Se, 选用酸性和氧化性较弱的硝酸/过氧化氢消解液更适宜。在本试验条件下, 罗布麻体内的Li和Cr 2种微量元素不宜采用ICP-AES仪器检测, 可选用ICP-MS, 而对于难电离元素Se则正好相反。结论 检测罗布麻微量元素含量时, 应根据待检测元素类型特征, 选择适宜的检测仪器。     

A benchmark data set for two-phase Coriolis metering

For more than a decade there has been growing interest in the use of Coriolis mass flow metering applied to two-phase (gas/liquid) and multiphase (oil/water/gas) conditions. It is well-established that the mass flow and density measurements generated from multiphase flows are subject to large errors, and a variety of physical models and correction techniques have been proposed to explain and/or to compensate for these errors. One difficulty is the absence of a common basis for comparing correction techniques, because different flowtube designs and configurations, as well as liquid and gas properties, may result in quite different error curves. Furthermore, some researchers with interests in the modelling aspects of the field may not have suitable multiphase laboratory facilities to generate their own data sets. This paper offers a small data set that may be used by researchers as a benchmark i.e. a common data set for comparing correction techniques. The data set was collected at the UK National Flow Laboratory TUV-NEL, using air and a viscous oil, and provides experimental points over a wide flow range (8:1 turndown) and with Gas Volume Fraction (GVF) values up to 60%. As a first investigation using the benchmark data set, we consider how data sparsity (i.e. the flow rate and GVF spacing in the experimental grid) affects the accuracy of a correction model. A range of neural network models are evaluated, based on different subsets of the benchmark data set. The data set and some exemplary code are provided with the paper. Additional data sets are available on a web site created to support this initiative.     

针对多种处理痕迹的数字语音取证算法

现有的数字语音取证研究主要集中于对单一的某种操作进行检测，无法对不相关的操作进行判断。针对该问题，提出了一种能够同时检测经过变调、低通滤波、高通滤波和加噪这四种操作的数字语音取证方法。首先，计算语音的归一化梅尔频率倒谱系数（MFCC）统计矩特征；然后通过多个二分类器对特征进行训练，并组合投票得到多分类器；最后使用该多分类器对待测语音进行分类。在TIMIT以及UME语音库上的实验结果表明，归一化MFCC统计矩特征在库内实验中均达到了97%以上的检测率，且在对MP3压缩鲁棒性测试的实验中，检测率仍能保持在96%以上。     

TBP-TEVA萃取色层分离-α能谱法测定辐照镎靶溶解液中痕量236Pu的可行性

²³⁶Pu的含量控制是钚热源的一项重要参数，通过α能谱准确测量镎靶溶解液中痕量²³⁶Pu，建立镎靶辐照靶件溶解液中钚的分离方法。根据杂质组成特点采用TBP-TEVA萃取色层双柱分离，用氨基磺酸亚铁以及亚硝酸钠对钚进行调价，对靶件溶解液中的Al、Fe、U、Th和Np等进行分离，去污系数均大于10⁴，钚的回收率为90.7%。研究大量²³⁸Pu对α能谱测定²³⁶Pu的干扰，结果表明，大量²³⁸Pu会造成仪器本底升高，²³⁸Pu能谱峰分辨率降低；在7 500 Bq ²³⁸Pu干扰下，测量4.3 h 时，²³⁶Pu的最小可检测活度为1.20×10^-2 Bq（当量质量为6.11×10^-16 g）。计算结果表明，镎靶溶解液样品中钚的同位素比值n(²³⁶Pu)/n(²³⁸Pu) ≥4.63×10^-8时，取合适的样品量使得电沉积源中²³⁸Pu 活度在 450~7 500 Bq范围内，均可测量其中的痕量²³⁶Pu，同时可准确测定同位素比值n(²³⁶Pu)/n(²³⁸Pu)。     

Integration of machine learning and first principles models

Model building and parameter estimation are traditional concepts widely used in chemical, biological, metallurgical, and manufacturing industries. Early modeling methodologies focused on mathematically capturing the process knowledge and domain expertise of the modeler. The models thus developed are termed first principles models (or white-box models). Over time, computational power became cheaper, and massive amounts of data became available for modeling. This led to the development of cutting edge machine learning models (black-box models) and artificial intelligence (AI) techniques. Hybrid models (gray-box models) are a combination of first principles and machine learning models. The development of hybrid models has captured the attention of researchers as this combines the best of both modeling paradigms. Recent attention to this field stems from the interest in explainable AI (XAI), a critical requirement as AI systems become more pervasive. This work aims at identifying and categorizing various hybrid models available in the literature that integrate machine-learning models with different forms of domain knowledge. Benefits such as enhanced predictive power, extrapolation capabilities, and other advantages of combining the two approaches are summarized. The goal of this article is to consolidate the published corpus in the area of hybrid modeling and develop a comprehensive framework to understand the various techniques presented. This framework can further be used as the foundation to explore rational associations between several models.     

基于三维纳米阵列结构的表面增强拉曼技术研究及其在痕量铀酰离子探测中的应用

表面增强拉曼散射(SERS)是一种新型痕量表征技术，其灵敏度高、样品用量少、特征谱易辨识，尤其适用于铀酰离子等危化品的探测。在过去十几年里, 纳米材料和纳米技术在新兴技术和SERS的应用方面获得了长足发展，将先进的纳米制造技术引入了SERS领域。本文总结了利用光刻、原子层沉积等技术，开发了一系列高质量的三维阵列纳米材料作为SERS基底，并应用于痕量铀酰离子的检测。其中，以Al₂O₃、HfO₂等惰性氧化物包裹修饰的银纳米棒三维阵列作为基底，灵敏度高，稳定性好，根据不同特征的拉曼振动频谱，可识别多个不同种态的铀酰离子，检出限低至nmol/L，具有潜在的实际应用价值。