Non-LTE Calculations of the Fe I 6173 {\AA} Line in a Flaring Atmosphere

The Fe I 6173 {\AA} line is widely used in the measurements of vector magnetic fields by instruments including the Helioseismic and Magnetic Imager (HMI). We perform non-local thermodynamic equilibrium calculations of this line based on radiative hydrodynamic simulations in a flaring atmosphere. We employ both a quiet-Sun atmosphere and a penumbral atmosphere as the initial one in our simulations. We find that, in the quiet-Sun atmosphere, the line center is obviously enhanced during an intermediate flare. The enhanced emission is contributed from both radiative backwarming in the photosphere and particle beam heating in the lower chromosphere. A blue asymmetry of the line profile also appears due to an upward mass motion in the lower chromosphere. If we take a penumbral atmosphere as the initial atmosphere, the line has a more significant response to the flare heating, showing a central emission and an obvious asymmetry. The low spectral resolution of HMI would indicate some loss of information but the enhancement and line asymmetry are still kept. By calculating polarized line profiles, we find that the Stokes I and V profiles can be altered as a result of flare heating. Thus the distortion of this line has a crucial influence on the magnetic field measured from this line, and one should be cautious in interpreting the magnetic transients observed frequently in solar flares.Comment: 12 pages, 5 figures, accepted by ApJ

响应面法优化热回流提取光甘草定工艺研究

Objective: To study the extraction process of glabridin from Glycyrrhiza glabra. Methods: The solid-liquid ratio, extraction time and extraction temperature are the three main factors in the experiment, and the extract solvent is ethyl acetate. Establish the response surface quadratic regression equation of glabridin extraction rate and purity. Results:The results indicate that the optimum conditions for glabridin are as follows: solvent is ethyl acetate, extraction time is 90 min, the ratio of solvent to solid is 35 ∶1 (ml/g), and extraction temperature is 44.7 ℃, purity and the maximum yield of Extraction of glabridin are 6.96% and 0.241%, The validation test shows that the experimental values of the model are 0.235% and 6.05% . Conclusion: The model equation can predict the experimental results, it can be used as reference in industrial production. 目的  研究光果甘草中光甘草定的提取工艺。 方法  以乙酸乙酯为提取溶剂，选择料液比、提取时间和提取温度3个因素进行中心组合实验，建立光甘草定提取率和纯度的响应面，建立光甘草定提取率和纯度的二次回归方程。 结果  光甘草定提取的最佳工艺条件为：乙酸乙酯为提取溶剂，提取时间90min，提取温度44.7℃，料液比1:35。该条件下光甘草定提取率预测值为0.241%，纯度为6.96%，验证值为0.235%与6.05%。 结论  所得模型方程能较好地预测实验结果，工业生产中可应用参考

COMPARISON OF THE ACCURACY OF THREE WRIST-WORN TRACKING DEVICES WHEN MEASURING HEART RATE DURING AEROBIC EXERCISE

The study aimed to assess the accuracy of the three wrist-worn heart rate monitors compared with a chest strap monitor at different aerobic exercise levels. Ten college students completed a three-level incremental load training on the elliptical machine with different brands of wrist-worn tracking devices including the Apple Iwatch7, Huawei Runner and Garmin 945. Polar H10 was used to measure HR as the gold standard. Huawei Runner showed the best agreement with Polar H10 (r = 0.981) followed by the Apple Iwatch (r = 0.973), the Garmin 945 was the most imprecise device (r= 0.866) when exercising on elliptical trainer. The paired relative error showed the best correlation between the Apple Iwatch7 and polar H10 both during exercise at 0.0 (± 0.5) and during resting at -0.1 (± 0.4). The mean output value ratio of Apple Iwatch7 was 78.10% (± 13.30%), while there wasn’t the missing HR data in the Huawei and Garmin devices. There was no significant difference between left and right hands. The Apple and Huawei devices measured HR with acceptable accuracy during aerobic exercise. While the proportion of missing HR data of Apple Iwatch is more than 20% during exercise in order to ensure the accuracy of measurement by deleting potentially problematic data automatically. This problem needs to be considered for high-precision continuous monitoring scenarios