Harmonically pump a femtosecond optical parametric oscillator to 1.13 GHz by a femtosecond 515 nm laser

We demonstrate a harmonically pumped femtosecond optical parametric oscillator(OPO)laser using a frequency-doubled mode-locked Yb:KGW laser at a repetition rate of 75.5 MHz as the pump laser.Based on a bismuth borate nonlinear crystal,repetition rates up to 1.13 GHz are realized,which is 15 times that of the pump laser.The signal wavelength is tunable from 700 nm to 887 nm.The maximum power of the signal is 207 m W at the central wavelength of 750 nm and the shortest pulse duration is 117 fs at 780 nm.The beam quality(M^2 factor)in the horizontal and vertical directions of the output beam are 1.077 and 1.141,respectively.     

Optical Trapping with Focused Surface Waves

Near-field optical trapping can be realized with focused evanescent waves that are excited at the water–glass interface due to the total internal reflection, or with focused plasmonic waves excited on the water–gold interface. Herein, the performance of these two kinds of near-field optical trapping techniques is compared using the same optical microscope configuration. Experimental results show that only a single-micron polystyrene bead can be trapped by the focused evanescent waves, whereas many beads are simultaneously attracted to the center of the excited region by focused plasmonic waves. This difference in trapping behavior is analyzed from the electric field intensity distributions of these two kinds of focused surface waves and the difference in trapping behavior is attributed to photothermal effects due to the light absorption by the gold film.     

卷积神经网络用于近红外光谱古筝面板木材分级

目前,我国乐器制作行业在古筝面板用木材等级的筛选上主要依赖于技师主观评判,但此法缺少科学理论的依据,效率低,客观性及出材率的提高等方面受到限制,无法满足乐器市场的大量需求。实现古筝面板用木材快速、智能化的分级工作是一个急需解决的课题。近红外光谱非常适用于测量含氢的有机物质。古筝面板木材主要化学成分的化学键均由含氢基团组成,不同等级板材的化学成分存在差异,这些差异反映在近红外光谱中,为判断木材等级提供了可能。同时卷积神经网络对非线性数据具有较强的特征提取能力,所以提出一种应用卷积神经网络模型对光谱数据进行分析的方法,进而判别木材的等级。应用了Savitzky Golay一阶、二阶微分两种预处理方法和核主成分分析、连续投影算法两种数据压缩方法,通过所设计的卷积神经网络模型以样本识别准确率和模型构建过程中的损失值作为判定指标选出最佳预处理和数据压缩方法。为了提高模型提取分析光谱数据的能力和避免过拟合现象,应用了多通道卷积核、批量归一化和early stopping策略,将通过两层卷积层提取的特征信息送入全连接层,从而充分提取剩余信息,通过Softmax函数获得板材的最终预测等级,从而确定了最终模型。最终Savitzky Golay一阶微分和核主成分分析为最佳数据处理方法,同时得出用于区分不同等级的古筝面板用木材的主要关键谱带,分别为1 163~1 243, 1 346~1 375和1 525~1 584 nm。将该模型应用于测试集样本,古筝面板用木材的等级识别准确率为95.5%。实验结果表明所提出的方法可以高效地处理光谱数据,有效识别区分不同等级的古筝面板用木材的关键特征,从而为广阔的乐器市场提供一定的技术支持。     

Metabolic profiles of dioscin in rats revealed by ultra‐performance liquid chromatography quadrupole time‐of‐flight mass spectrometry

Dioscin (DIS), one of the most abundant bioactive steroidal saponins in Dioscorea sp., is used as a complementary medicine to treat coronary disease and angina pectoris in China. Although the pharmacological activities and pharmacokinetics of DIS have been well demonstrated, information regarding the final metabolic fates is very limited. This study investigated the in vivo metabolic profiles of DIS after oral administration by ultra‐performance liquid chromatography quadrupole time‐of‐flight mass spectrometry method. The structures of the metabolites were identified and tentatively characterized by means of comparing the molecular mass, retention time and fragmentation pattern of the analytes with those of the parent compound. A total of eight metabolites, including seven phase I and one phase II metabolites, were detected and tentatively identified for the first time. Oxidation, deglycosylation and glucuronidation were found to be the major metabolic processes of the compound in rats. In addition, a possible metabolic pathway on the biotransformation of DIS in vivo was proposed. This study provides valuable and new information on the metabolism of DIS, which will be helpful for further understanding its mechanism of action. Copyright © 2015 John Wiley & Sons, Ltd.     

语音通信降噪研究

语音通信系统中，语音通过信道传输将不可避免地引入码间串扰和信号畸变，同时受到噪声污染。本文在分析自适应盲均衡算法CMA(constant modulus algorithm）和改进盲均衡算法的基础上，考虑到自适应盲均衡技术在语音噪声控制方面能力有限，将自适应盲均衡技术与小波包掩蔽阈值降噪算法联合使用，形成一种基带语音增强新方法。仿真试验结果显示自适应盲均衡技术可以使星座图变得清晰而紧凑，有效减小误码率。研究证实该方法在语音信号ISI和畸变严重情况下，在白噪及有色噪声不同的噪声环境中都具有稳定的降噪能力，消噪同时可获得汉语普通话良好的听觉效果。     

不同声音偏好的游客声景观主观评价差异——以丽江大研古镇为例*

古镇作为集自然景观与人文景观一体的景区，具有丰富的声音类型。本研究以大研古镇为例，通过实地调研探究不同声音偏好的游客对古镇声景观的主观评价差异。基于游客的声音偏好，将游客分为偏爱自然声和偏爱人工声两大类。通过因子分析提取游客声景观主观评价的5个主因子：大小、音质、效价、偏好和唤醒。进一步分析发现，这5个因子具有一定的层级性，其中从大小到唤醒代表声景观评价从声音的物理属性向声音的联想评价逐级提升。其中在低层级评价(大小、音质)中，偏好自然声的游客和偏好人工声的游客无显著差异，低层级评价具有稳定性；而在高层级评价(效价、偏好和唤醒)中，偏好人工声的游客更关注古镇声景观的淳朴性和遗产性。因此，游客对声景观的主观评价可视为一种指标，判断景区声景所处的评价阶段，从而为景区声景观改善提供更有针对性的建议。     

浮升力和流动加速对超临界CO2管内流动传热影响

基于单相流体的概念,超临界流体的异常传热行为已经被研究很多年了,但是关于其流动传热机理仍没有统一的认识.本文通过理论分析和实验研究了超临界二氧化碳在竖直管内向上流动过程中,浮升力和流动加速效应对其流动结构和传热过程的影响.结果表明,没有确凿的实验证据表明超临界流体的异常传热行为是浮升力和流动加速直接导致的,存在的估计浮升力和流动加速效应准则均是在常物性流体的基础上,做了大量假设得出的,不同的研究者采用浮升力和流动加速准则分析超临界流体的传热恶化得出的结论不一致.最后,基于拟沸腾理论分析超临界流体的传热恶化过程,提出超临界沸腾数区分了超临界流体正常传热与恶化传热的转换边界,为超临界流体流动传热研究提供新思路,超临界沸腾数对建立用于不同技术的超临界流体动力循环的最佳运行条件具有重要意义.     

Convergence of the viscosity solution of non-autonomous Hamilton-Jacobi equations

In this paper,we investigate the non-autonomous Hamilton-Jacobi equation ■ where H is 1-periodic with respect to t and M is a compact Riemannian manifold without boundary.We obtain the viscosity solution denoted by T_(t_0)~tφ(x) and show T_(t_0)~tφ(x) converges uniformly to a time-periodic viscosity solution u~*(x,t) of ?_tu+H(t,x,?_xu,u)=0.