Pattern transition and regulation in a subthalamopallidal network under electromagnetic effect

Although the significant roles of magnetic induction and electromagnetic radiation in the neural system have been widely studied, their influence on Parkinson's disease (PD) has yet to be well explored. By virtue of the magnetic flux variable, this paper studies the transition of firing patterns induced by magnetic induction and the regulation effect of external magnetic radiation on the firing activities of the subthalamopallidal network in basal ganglia. We find: (i) The network reproduces five typical waveforms corresponding to the severity of symptoms: weak cluster, episodic, continuous cluster, episodic, and continuous wave. (ii) Magnetic induction is a double-edged sword for the treatment of PD. Although the increase of magnetic coefficient may lead the physiological firing activity to transfer to pathological firing activity, it also can regulate the pathological intensity firing activity with excessive β-band power transferring to the physiological firing pattern with weak β-band power. (iii) External magnetic radiation could inhibit continuous tremulous firing and β-band power of subthalamic nucleus (STN), which means the severity of symptoms weakened. Especially, the bi-parameter plane of the regulation region shows that a short pulse period of magnetic radiation and a medium level of pulse percentage can well regulate pathological oscillation. This work helps to understand the firing activity of the subthalamopallidal network under electromagnetic effect. It may also provide insights into the mechanisms behind the electromagnetic therapy of PD-related firing activity.     

基于视觉辐条图案识别方法的蓝宝石引晶机制研究

工业生产蓝宝石晶体过程中,引晶步骤有着至关重要的地位。引晶必须在温度梯度较小,温度分布趋于稳定的条件下进行。目前,工业生产蓝宝石主要依靠人工经验操控籽晶杆实现引晶操作,但是人工引晶操作的准确性不高会导致成品品质不佳、资源浪费。为此,本文提出一种基于蓝宝石视觉辐条图案识别方法来检测蓝宝石熔体状态自由液面状态,从而实现一种高效率引晶的机制。此方法利用经典骨架化算法细化辐条图案,Harris算子实现特征信息的提取,提取的特征信息放入运动轨迹模型中判断熔体稳定性,分析液面温度分布稳定性从而实现引晶。结果表明,此算法具有有效性,蓝宝石晶体引晶效率大大提高,生产出的成品良率也有提升,可有效指导蓝宝石的工业生产。     

基于流量测点的热网变动阻力系数优化辨识

随着供热计量系统的普及，系统可以根据负荷的变化进行调整，管网的阻力系数随即发生变化。对变动阻力系数进行优化辨识是了解供热管网实时运行状况的有效手段。提出一种基于流量监测数据的供热管网变动阻力系数优化辨识方法，并利用遗传算法进行求解。对洛阳市某小区供暖季管网实际运行数据进行验证，辨识结果的相对误差在5%以内。结果表明：该方法可以在只有流量观测数据时得到精度较高的供热管网变动阻力系数，为供热系统的运行调节提供指导。     

基于PI法的门源MS6.4地震前震中附近地震热点图像异常变化研究

基于1980年以来青海省和甘肃省区域地震台网的定位地震目录，分析了研究区最小完备震级，选取空间网格尺度为0.2°×0.2°、地震活动异常学习时间段和预测时间段均为3 a，应用图像信息（PI）法，分析了门源M_S6.4地震发生前震中附近地震热点图像的异常变化过程。结果表明，在2013年1月1日至2016年1月1日的预测时间窗内，冷龙岭断裂和祁连山北缘断裂附近存在明显的地震热点，且地震热点图像颜色偏深，发震概率较高，向前滑动至2014年1月1日至2017年1月1日，2015年1月1日至2018年1月1日和2016年1月1日至2019年1月1日3个预测时间窗，此两断裂附近仍存在地震热点，地震热点图像颜色逐渐由深变浅，而门源M_S6.4地震就落在PI法得到的地震热点内。门源M_S6.4地震前存在明显的地震热点，且地震热点相对集中，地震热点图像颜色由深变浅，震后消失；在祁连山北缘断裂附近，地震热点持续存在，分布较集中，地震热点图像颜色也呈由深变浅的过程。未来需关注祁连山北缘断裂，附近有发生强震的可能。     

基于电化学老化衰退模型的锂离子动力电池外特性

当前锂离子动力电池电化学模型存在模型复杂、建模难度大、计算效率低、老化评估效果差的问题,本文提出一种考虑电池衰退老化的机理模型(ADME).本文首先通过有限差分法对伪二维(P2D)电化学模型进行离散降阶处理,得到简化伪二维(SP2D)模型.在SP2D模型的基础上,基于阴阳两极发生的副反应导致的衰退老化现象,提出一种考虑电池衰退老化的机理模型.其次,使用多变量偏差补偿最小二乘法实现模型参数辨识.最后通过动力电池衰退老化性能循环实验,对比分析了恒流、脉冲工况下SP2D模型和ADME模型的终端电压输出.结果表明:ADME模型较为简单、计算效率和估算精度高,可以有效评估电池容量老化衰退,得到理想的锂离子动力电池外特性曲线.     

Time-averaged flow characteristics and mixing properties of double-concentric jets

We examined the flow behaviors and mixing characteristics of double-concentric jets using laser-assisted smoke flow visualization method to analyze typical flow patterns and binary boundary detection technique to investigate jet spread width. Time-averaged velocity vectors, streamline patterns, velocity distributions, turbulence properties, and vorticity contours were analyzed using Particle Image Velocimetry (PIV). Topological flow patterns were analyzed to interpret the vortical flow structures. Mixing properties were investigated using a tracer-gas concentration detection method. Four characteristic modes were observed: annular flow dominated mode, transition mode, central jet dominated mode-low shear, and central jet dominated mode-high shear. The jets’ mixing properties were enhanced by two major phenomena: the merging of annular flow and central jet at the centerline and the large turbulence fluctuations produced in the flow field. The merging of the jets induced stagnation points on the central axis in the annular flow dominated mode, which caused reverse flow on the central axis and drastic turbulence fluctuations of the near field region. When the central jet penetrated the recirculation region in the other three modes, the stagnation points on the central axis and the reverse flow vanished. Therefore, the mixing behaviors were prominently enhanced in the annular flow dominated mode.     

The chemical profile of active fraction of Kalimeris indica and its quantitative analysis

Kalimeris indica (L) Sch-Bip is a medicinal plant used by the Miao ethnic group in the Guizhou province of China. It is widely used as a fresh vegetable to treat colds, diarrhea and gastric ulcers. However, few studies have been conducted on the mechanism of its effect on colds, and its quality control. The anticomplement and antitussive activities of different polar extracts of K. indica were evaluated. Fifty-nine compounds, mainly including phenols and flavonoids, were identified in K. indica extract by ultra-high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry. A method was established through ultra-high-performance liquid chromatography with a photodiode array to simultaneously determine the anticomplement and antitussive activity of five compounds in K. indica combining chemical identification with chemometrics for discrimination and quality assessment. Also, 3,5-dicaffeoylquinic acid and 4,5-dicaffeoylquinic acid exhibited significantly higher anticomplementary activity than the other three compounds. The quantitative data were further analyzed by principal component analysis and orthogonal partial least-squares discriminant analysis. Heatmap visualization was conducted to clarify the distribution of the major compounds in different geographical origins. Screening pharmacological activities by a combination of chemometrics and chemical identification might be an effective method for the quality control of K. indica.     

不同结构绝对光栅尺的误码机制研究

针对光栅尺具有断电位置复位、无累计误差、高精度优点, 在光学隔振平台上分别建立开放式和封闭式绝对光栅尺实验系统, 绝对光栅尺采用图像识别原理, 以气浮直线电机ArotechABL1500为参考对象, 使用激光干涉仪RENISHAW XL-80校核精度, 研究不同结构绝对光栅尺的误码特点及原因。通过对比实验及研究分析, 表明封闭式绝对尺相对于开放式绝对尺的误码率要高, 开放式绝对式光栅尺的误码率为3%, 封闭式绝对式光栅尺的误码率为8%。     

Studies on metabolism of total glucosides of paeony from Paeoniae Radix Alba in rats by UPLC‐Q‐TOF‐MS/MS

Total glucosides of paeony are the active constituents of Paeoniae Radix Alba. In this study, a novel strategy was proposed to find more metabolites and the differences between paeoniflorin, albiflorin and total glucosides of paeony (TGP). This strategy was characterized as follows: firstly, the animals were divided into three groups (paeoniflorin, albiflorin and TGP) to identify the source of TGP metabolites from paeoniflorin or albiflorin; secondly, a generic information‐dependent acquisition scan for the low‐level metabolites was triggered by the multiple mass defect filter and dynamic background subtraction; thirdly, the metabolites were identified with a combination of data‐processing methods including mass defect filtering, neutral loss filtering and product ion filtering; finally, a comparative study was used in the metabolism of paeoniflorin, albiflorin and TGP. Based on the strategy, 18 metabolites of TGP, 10 metabolites of paeoniflorin and 13 metabolites of albiflorin were identified respectively. The results indicated that the hydrolysis, conjugation reaction and oxidization were the major metabolic pathways, and the metabolic sites were the glycosidic linkage, the ester bond and the benzene ring. This study is first to explore the metabolism of TGP, and these findings enhance our understanding of the metabolism and the interactions of paeoniflrin and albiflorin in TGP. Copyright © 2015 John Wiley & Sons, Ltd.     

基于超限学习机算法的空间目标材质多色测光识别研究

随着各国航天活动的增多，空间目标的数量和种类不断增加，对空间目标进行编目识别是各国空间目标监视领域的重要研究内容。对空间目标进行识别，主要是为了获得其表面材质、姿态、形状、关键载荷等信息，而表面材质信息的获取是开展目标光学特性及状态认知研究的基础。搭建空间目标表面材质多色测光测量系统，整套系统部署在光学暗室内，以减少杂散光对测量结果的影响。光源采用太阳模拟器，光谱等级A级；探测器采用美国ASD公司生产的FieldSpec4地物光谱仪，波长范围350～2 500 nm，光谱分辨率1 nm，光纤置于电控转台上，能对待测样片实现不同观测几何下的测量。利用Johnson-Cousins UBVRI五色分光系统对8种常用表面材质（砷化镓、氧化铝、氧化聚酰亚胺薄膜、黑漆、环氧漆、镀铝聚酰亚胺薄膜、钛青蓝漆、白漆）在不同观测几何条件下的10种色指数数据进行实验测量，每种色指数分别测得30组实验数据。采用传统的1-sigma不确定框方法（即对于给定材质的若干组实验数据，计算其每种色指数的平均值和标准差，以平均值为中心，以标准差的两倍为边长画出色指数不确定框），在最理想的识别情况下，通过R-I和B-R色指数不确定框能对砷化镓、氧化铝、氧化聚酰亚胺薄膜、钛青蓝漆四种材质进行识别；利用B-V和B-R色指数不确定框可以将环氧漆、白漆识别出来，剩余两种材质黑漆和镀铝聚酰亚胺薄膜无法通过以上色指数进行识别。但是1-sigma不确定框方法存在两个主要问题：一是需要知道待测材质对特定波段敏感的先验信息，来确定所用的色指数类型；二是识别率容易受测试样本数量的影响，可靠性差。超限学习机算法是一种利用随机化隐层节点和和最小二乘求解方式进行训练的机器学习算法，具备学习效率快，泛化性能好，不容易陷入局部最优解等优势，被广泛应用于对数据的分类和回归分析中。因此引入超限学习机算法，将色指数数据按照2∶1的比例随机分为训练样本和测试样本，共进行三次随机试验。在训练样本中，对每种材质按照1∶8的顺序进行编号，即编号1∶8的测试样本分别有20个，分别包含10种色指数数据；在测试样本中同样对其按照已知归属材质对应编号。采用决定系数和计算时间作为判断ELM算法准确性和实时性的判断指标。结果表明：无论是对单一材质进行识别，还是对所有测试材质样本，训练样本决定系数在0.98以上，测试样本决定系数在0.96以上，每次试验中最多有3组色指数数据无法识别；所需总时间最长在0.07 s内完成，甚至可以达到0.002 s，识别效率和可靠性远高于传统的1-sigma不确定框法，表明ELM算法能对空间目标常用材质进行准确快速识别。相关研究可为空间非合作目标的外形、姿态等状态信息反演提供技术支持。