以学生为中心的有机化学在线教学及成绩评定

Under the "constructing Chinese Golden Lessons" and "ensuring learning undisrupted when classes are disrupted" appealed by Ministry of Education, we implemented organic chemistry online teaching schemes including self-study courses online, resolving doubts and expanding webcast explanation, classification-summarization and doing exercises online, as well as online discussion-answering. Students' performance was scored based process assessment including 10% self-study online, 10% resolving doubts and expanding webcast, 10% classification-summarization and doing exercises online, 5% online discussion-answering, 15% mid-term examination, and 50% semester final examination. The goal of student-centered teaching was achieved and teaching quality during epidemic period was ensured.     

Enhancement of the conductivity detection signal in capillary electrophoresis systems using neutral cyclodextrins as sweeping agents

Conductivity detection is a universal detection technique often encountered in electrophoretic separation systems, especially in modern chip‐electrophoresis based devices. On the other hand, it is sparsely combined with another contemporary trend of enhancing limits of detection by means of various preconcentration strategies. This can be attributed to the fact that a preconcentration experimental setup usually brings about disturbances in a conductivity baseline. Sweeping with a neutral sweeping agent seems a good candidate for overcoming this problem. A neutral sweeping agent does not hinder the conductivity detection while a charged analyte may preconcentrate on its boundary due to a decrease in its effective mobility. This study investigates such sweeping systems theoretically, by means of computer simulations, and experimentally. A formula is provided for the reliable estimation of the preconcentration factor. Additionally, it is demonstrated that the conductivity signal can significantly benefit from slowing down the analyte and thus the overall signal enhancement can easily overweight amplification caused solely by the sweeping process. The overall enhancement factor can be deduced a priori from the linearized theory of electrophoresis implemented in the PeakMaster freeware. Sweeping by neutral cyclodextrin is demonstrated on an amplification of a conductivity signal of flurbiprofen in a real drug sample. Finally, a possible formation of unexpected system peaks in systems with a neutral sweeping agent is revealed by the computer simulation and confirmed experimentally.     

Real-time Event Recognition and Analysis System for Nanopore Study

To achieve fast and accurate analysis of weak current signal of nanopore-based single molecule detection, an online data process based on adaptive threshold algorithm with data buffering technique and finite impulse response filtering was designed. A software system based on the data process was developed for online recognition and analysis of nanopore events during nanopore experiment. To testify the performance of the algorithm and software system, ideal signals with different noise level (20–100 pA) were generated at bandwidth ranging from 3 kHz to 100 kHz. The result showed that this software system was stable at different bandwidths and sampling rates and could be used in analyzing the signals at high noise. The proposed software system was further applied to aerolysin nanopore experiment for detection of poly(dA)₄ molecules. The results showed that the data process system could be applied in real nanopore recording experiment with high accuracy and speed.     

物理化学课程在线教学实践与效果分析

The main measures and experiences of online physical chemistry teaching through Ding Talk platform in Bohai University was introduced. Through the practice of the whole semester, it can be seen that the modular teaching mode of "simplicity-detail-induction" constructed by physical chemistry teaching team is conducive to match students with different self-learning abilities with different levels of teaching. The question-and-answer video induction class can fully arouse students' learning enthusiasm, which is favorable for the perfect realization of teaching and teacher-student interaction. With the double guarantee of meticulous and transparent teaching management and the accompanying process assessment, the overall goal achievement degree of the whole semester reached beyond 80%, and the sub-goal achievement degree reached over 60%, which provided reference for relevant teaching.     

New type of dry substances content meter using microwaves for application in biogas plants

Dry substances (DS) are an important index for monitoring and controlling anaerobic co-digestion in biogas plants. We have developed and tested an online meter that measures suspended solids by means of the reflection coefficient of an exiting microwave signal, which is dependent on the dielectric properties of the suspensions. Intelligent models based on partial least squares regression (PLSR) and artificial neural network (ANN) for calibration allow exact and reproducible measurements under different circumstances. This measuring method is appropriate for contactless and online measurements of dry substance contents in biogas plants in a large range from 2–14%.     

UOOC平台与腾讯课堂相结合的“在线异步教学”

新冠病毒大规模爆发,在线教学成为教师首选。而避免网络拥堵和保证学习效果是在线教学面临的两难问题。我们借助于UOOC平台和腾讯课堂,以"聚合物结构与性能"课程为样本,实践了新型"线上异步教学"模式。其中,SPOC课程便于学生自主安排时间;"章节测验"和"生生互评"则有利于学生获得多角度反馈;小课题侧重于案例分析,引导学生开展探究式学习。总体而言,"在线异步教学"模式打破了教与学的时空限制,保证了疫情期间的教学质量,也为打造"金课"奠定了基础。     

基于紫外光谱的水体硝酸盐浓度混合预测模型研究

水体中的硝酸盐浓度过高不仅会造成水环境污染而且会对人类身体健康造成很大威胁,传统的检测硝酸盐的方法检测时间长且操作复杂。针对水体中硝酸盐氮难以快速在线检测的问题,基于紫外吸收光谱,提出了一种混合预测模型结合光谱积分快速定量检测水体中硝酸盐浓度的方法。混合预测模型为低浓度样本建立的双波长法预测模型与高浓度样本建立的偏最小二乘支持向量机(LS-SVM)预测模型数据融合之后的模型。按照合适的浓度梯度配备了19组硝酸盐氮标准溶液,通过实验测得不同浓度硝酸盐氮样本的光谱数据。首先基于双波长法对所有样本进行回归分析,按照A=A₂₂₀-2A₂₇₅计算不同实验样本的吸光度A,其中A₂₂₀和A₂₇₅是220和275 nm处样本的吸光度,将吸光度A与样本浓度值进行线性回归,拟合出样本浓度的预测值。结果显示当样本浓度较小时,相关性很好,r为0.997 4,随着实验样本浓度的上升,曲线发生严重的非线性漂移,因此双波长法只适合低浓度样本预测模型的建立。对于高浓度样本,光谱重叠严重,适合建立非线性的预测模型,支持向量机(SVM)与LS-SVM都适合小样本的非线性数据建模,LS-SVM预测精度稍高,运算速度稍快。通过对所有的实验样本进行全波长光谱积分,比较相邻样本光谱积分的变化率可以筛选出样本的临界浓度值,4 mg·L-1的硝酸盐样本积分值前后变化率最大,因此选择4 mg·L-1作为临界浓度值较为合适。浓度高于4 mg·L-1的实验样本建立LS-SVM预测模型,通过交叉验证的方法选择出合适的参数,正则化参数γ=50,核函数选择高斯核,核函数宽度σ２=0.36,训练样本之后进行回归;其余样本建立双波长法预测模型,最后进行两种模型的数据融合,形成从低浓度到高浓度的水体中硝酸盐浓度的检测。为了验证混合预测模型的预测精度,另外建立了SVM,LS-SVM,偏最小二乘(PLS)等模型,并求出r,预测值与真实浓度值平均绝对误差(MAE)和均方根误差(RMSE)对模型进行评价。验证结果表明,相比于SVM,LS-SVM和PLS等模型,提出的混合模型回归的相关系数为0.999 86,分别提高了1.8%,1.6%和0.45%,预测值与真实浓度的平均绝对误差为2.55%,分别降低了6.27%,4.49%和1.01%,均方根误差为0.303,为四种预测模型中最小,SVM与LS-SVM的相对误差相对较高,PLS模型相对误差上下波动比较大,混合预测模型相对误差最为稳定,并保持在较低水平,由此可见混合预测模型的预测效果明显优于其他几种模型。并与文献[5-7]中的测量方法进行对比,该混合预测方法可以简单快速的测量水体中硝酸盐氮的浓度,且不需要试剂,无二次污染,与文献[9]中的预测模型相比,预测精度明显提高。因此提出的混合模型可正确快速地预测水体中硝酸盐氮的浓度,可为在线监测水体中硝酸盐浓度提供有效的技术参考。     

在线二维柱切换-超高效液相色谱法同时测定明目地黄丸中莫诺苷、马钱苷、芍药苷、丹皮酚的含量

建立了二维柱切换-超高效液相色谱法同时测定明目地黄丸中莫诺苷、马钱苷、芍药苷、丹皮酚含量的方法.一维色谱柱为Thermo Accucore XL C18(250mm×2.1 mm,4μm),二维色谱柱为DIONEX Acclaimphenyl-1(150mm ×4.6mm,3μm),一维分析流动相为乙腈-水,梯度洗脱,二维分析流动相为乙腈-水,等度洗脱,14.5 min进行阀切换;检测波长:0～14.5 min为240 nm,14.5～ 30 min为275 nm,流速:0.5 mL/min,柱温:30℃.30 min即可完成明目地黄丸中莫诺苷、马钱苷、芍药苷、丹皮酚的含量测定,并有效地将莫诺苷同分异构体分离.莫诺苷、马钱苷、芍药苷、丹皮酚的线性范围分别为7.6 ～ 377 mg/L,9.2～ 459 mg/L,8.4～419 mg,/L和8.2 ～ 409 mg/L,相关系数为0.9999,加样回收率为98.3％～ 100.2％.本方法快捷高效,可对控制明目地黄丸质量提供参考.     

Online self-calibration for mobile vision based on laser imaging and computer algorithms

A self-calibration technique for mobile three-dimensional vision is presented. This technique determines the vision parameters during the vision task based on computer algorithms and image processing. The three-dimensional vision is performed by a Bezier network based on laser line projection. This network provides the data to perform the online self-calibration when the vision system is modified. Here, the changes of the extrinsic and intrinsic parameters are determined. The structure of the network is performed by the line shifting provided by the surface depth. From this structure, the data for the initial calibration and online self-calibration are deduced. In this manner, the calibrated references and physical measurements are avoided to perform the online self-calibration. Therefore, calibration limitations caused by online modifications are overcome to perform the mobile vision. Thus, the proposed self-calibration improves the accuracy and performance of the mobile vision. It is because online data of calibrated references are not passed to the vision system. This procedure represents a contribution in the field of the online recalibration, which is performed based on calibrated references. To elucidate this contribution, an evaluation is performed based on the self-calibration methods, which are reported in the recent years. Also, the time processing is described.     

“互联网+”背景下基础化学原理实验在线学习与考试系统的开发与实践

在移动互联网的飞速发展与智能手机等移动终端日趋普及的情况下,设计开发了基于移动端的基础化学原理实验在线学习与考试系统。该系统包括化学实验室安全教育与考试、实验基础理论学习、试题库资源、移动端在线考试、成绩管理和统计分析等五大功能。该系统的开发建设顺应了"互联网+教育"的发展趋势,有利于学生自主学习,节约考试资源。