结合背景差分和显著值筛选的运动检测算法

本文为降低背景干扰,提出了一种结合背景差分和显著值筛选的运动检测方法。该方法将VIBE运动检测方法看作一个前置处理过程,用于粗定位可疑目标区域。然后在这些可疑目标区域上,提出一种基于稀疏表示和组合Lasso回归的显著值计算方法,计算可疑区域图像块的显著值。最后通过滤除显著值过小的可疑区域图像块来降低背景干扰,提高运动检测的精确度指标。在Changedetection.net的数据子集上的仿真实验结果表明,该方法的召回率和精确度指标都较高,而且平均检测耗时少。     

中药提取过程在线紫外动态趋势回归分析及终点判定

随着中药生产行业的转变,中药生产过程现代化成为了必然趋势。而目前由于缺乏有效的在线检测手段,中药生产检测滞后性大,产品质量参差不齐。针对中药提取过程在线监控及终点判定的问题,基于朗伯比尔定律及中药提取动力学方程建立提取液紫外吸光度随时间变化模型,并提出动态分析及终点判断方法, 该方法包括紫外吸光度序列拟合、稳健性分析以及终点计算。以千年健提取过程为例,使用本实验室自主研发的中药提取液在线采样系统进行光谱收集,并对离线样本求取其有效固体物质含量作为参考。分析过程中,首先对实时检测的光谱进行插值及滤波处理,计算230.2～400 nm紫外谱区的吸光度均值并结合前期数据组成吸光度均值序列;随后,进行了该吸光度序列与提取液固体含量之间的相关分析,得到线性相关系数r2=0.9828,证明二者存在较强的线性关系;最终对吸光度均值序列进行动态模型稳健回归及提取终点判定。结果表明：回归过程通过稳健性分析能够充分识别出测量异常点,提高了拟合曲线与原始吸光度的复相关系数,使其达到0.99,并通过终点判定将千年健提取时间由最初人工设定的180 min缩短至122 min。实验证明,紫外在线监控方法实现了提取过程的在线监控及终点判定,对稳定产品质量、提高经济效益具有重要意义。     

Principle of Unattainability of absolute zero temperature,the Third Law of Thermodynamics,and projective quantum measurements

The Principle of Unattainability rules out the attainment of absolute zero temperature by any finite physical means, no matter how idealised they could be. Nevertheless, we clarify that the Third Law of Thermodynamics, as defined by Nernst's heat theorem statement, is distinct from the Principle of Unattainability in the sense that the Third Law is mathematically equivalent only to the unattainability of absolute zero temperature by quasi-static adiabatic processes. This, on the one hand, leaves open the possibility of attainability of absolute zero by non-adiabatic means, without violating the Third Law. On the other hand, we point out some apparent incompatibility between the Postulate of Projective Measurement in quantum mechanics and the Principle of Unattainability in that projective measurements of energy could result in zero temperature.     

A strategy for multivariate calibration based on modified single-index signal regression: Capturing explicit non-linearity and improving prediction accuracy

In this paper, a modified single-index signal regression (mSISR) method is proposed to construct a nonlinear and practical model with high-accuracy. The mSISR method defines the optimal penalty tuning parameter in P-spline signal regression (PSR) as initial tuning parameter and chooses the number of cycles based on minimizing root mean squared error of cross-validation (RMSECV). mSISR is superior to single-index signal regression (SISR) in terms of accuracy, computation time and convergency. And it can provide the character of the non-linearity between spectra and responses in a more precise manner than SISR. Two spectra data sets from basic research experiments, including plant chlorophyll nondestructive measurement and human blood glucose noninvasive measurement, are employed to illustrate the advantages of mSISR. The results indicate that the mSISR method (i) obtains the smooth and helpful regression coefficient vector, (ii) explicitly exhibits the type and amount of the non-linearity, (iii) can take advantage of nonlinear features of the signals to improve prediction performance and (iv) has distinct adaptability for the complex spectra model by comparing with other calibration methods. It is validated that mSISR is a promising nonlinear modeling strategy for multivariate calibration.     

环己烷13C NMR化学位移的预测

通过计算机辅助方法对¹³C NMR化学位移进行预测.这个方法包括分子拓扑指数和几何参数特征值的计算及对所选特征进行的变量压缩,并对所选共振碳的化学位移与其提取的特征进行多元回归分析,从而得出其相关数学模型.本文预测了环己烷中45个仲碳原子的¹³C化学位移,其标准误差约为1.4ppm.     

化学诱导动态核极化

简要概述了化学诱导动态核极化(CIDNP)的发展历史、原理及在自由基反应机理研究方面的应用。     

On Relativistic Generalization of Gravitational Force

In relativistic theories, the assumption of proper mass constancy generally holds. We study gravitational relativistic mechanics of point particle in the novel approach of proper mass varying under Minkowski force action. The motivation and objective of this work are twofold: first, to show how the gravitational force can be included in the Special Relativity Mechanics framework, and, second, to investigate possible consequences of the revision of conventional proper mass concept (in particular, to clarify a proper mass role in the divergence problem). It is shown that photon motion in the gravitational field can be treated in terms of massless refracting medium, what makes the gravity phenomenon compatible with SR Mechanics framework in the variable proper mass approach. Specifically, the problem of point particle in the spherical symmetric stationary gravitational field is studied in SR-based Mechanics, and equations of motion in the Lorentz covariant form are obtained in the relativistic Lagrangean problem formulation. The dependence of proper mass on potential field strength is derived from the Euler-Lagrange equations as well. One of new results is the elimination of conventional 1/r divergence, which is known to be not removable in Schwarzschild gravitomechanics. Predictions of particle and photon gravitational properties are in agreement with GR classical tests under weak-field conditions; however, deviations rise with potential field strength. The conclusion is made that the approach of field-dependent proper mass is perspective for development of SR gravitational mechanics and further studies of gravitational problems.     

Combined prostate diffusion tensor imaging and dynamic contrast enhanced MRI at 3T — quantitative correlation with biopsy

The purpose of this work was to compare diagnostic accuracy of Diffusion Tensor Imaging (DTI), dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) and their combination in diagnosing prostate cancer. Twenty-five patients with clinical suspicion of prostate cancer underwent MRI, prior to transrectal ultrasound-guided biopsies. MRI data were correlated to biopsy results. Logistic regression models were constructed for the DTI parameters, DCE MRI parameters, and their combination. The areas under the receiver operator characteristic curves (AUC) were compared between the models. The nonparametric Wilcoxon signed rank test was used for statistical analysis. The sensitivity and specificity values were respectively 81% (74–87%) and 85% (79–90%) for DTI and 63% (55–70%) and 90% (85–94%) for DCE. The combination “DTI or DCE MRI” had 100% (97–100%) sensitivity and 77% (69–83%) specificity, while “DTI and DCE MRI” had 44% (37–52%) sensitivity and 98% (94–100%) specificity. The AUC for DTI+DCE parameters was significantly higher than that for either DTI (0.96 vs. 0.92, P=.0143) or DCE MRI parameters (0.96 vs. 0.87, P=.00187) alone. In conclusion, the combination of DTI and DCE MRI has significantly better accuracy in prostate cancer diagnosis than either technique alone.     

Controls over spatial and seasonal variations on isotopic composition of the precipitation along the central and eastern portion of Brazil

Based on Global Network Isotopes in Precipitation (GNIP) isotopic data set, a review of the spatial and temporal variability of δ¹⁸O and δ²H in precipitation was conducted throughout central and eastern Brazil, indicating that dynamic interactions between Intertropical and South Atlantic Convergence Zones, Amazon rainforest, and Atlantic Ocean determine the variations on the isotopic composition of precipitation over this area. Despite the seasonality and latitude effects observed, a fair correlation with precipitation amount was found. In addition, Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) air mass back trajectories were used to quantify the factors controlling daily variability in stable isotopes in precipitation. Through a linear multiple regression analysis, it was observed that temporal variations were consistent with the meteorological parameters derived from HYSPLIT, particularly precipitation amount along the trajectory and mix depth, but are not dependent on vapour residence time in the atmosphere. These findings also indicate the importance of convective systems to control the isotopic composition of precipitation in tropical and subtropical regions.     

基于高光谱成像技术的番茄叶片灰霉病早期检测研究

提出了独立软模式法(SIMCA)的番茄叶片灰霉病特征波段图像的提取,并通过多元线性回归法(MLR)提取波段融合图像,通过最小距离法获取番茄灰霉病患病信息的技术路线。利用680～740 nm波段的方差图像和建模能力参数提取的特征波段,并作为输入变量进行MLR分析,在0.5准确率阈值下,准确率均大于99%,说明特征波段可以实现番茄叶片灰霉病的检测,并利用MLR回归系数提取波段融合图像,通过最小距离法获取番茄灰霉病患病信息,结果表明所提出的方法具有很好的预测能力,为番茄灰霉病的早期检测提供了一种新方法,且大大降低了高光谱图像的数据处理时间。