敦煌卷子《张仲景五脏论》中“四色神丹”考

敦煌卷子P.2115、S.5614《张仲景五脏论》中“四色神丹”一方,只有方名及功用,而无具体的药物组成。查考宋代及宋以前书籍,可见到《伤寒论.伤寒例》中的“神丹”方,《抱朴子内篇.金丹》中之“神丹”,《千金要方》中之“神丹方”及《太平惠民和剂局方》、《苏沈良方》、《医方类聚》等书中所载之“四神丹”。本文对上述方剂进行分析后,认为“四色神丹”系指《太平惠民和剂局方》中所载之“四神丹”,其跟道教与医学的融合关系密切。

陈永涛:神学与处境(四)

诚然,神学与处境之间的关系向来是神学工作者相当重视的问题。根据毕文斯（Stephen B.Bevans）的理解,在现今的处境下,神学必须是处境性的。

西藏宗教美术的浪漫主义性格

非现实主义性格中包含着浓厚的现实气息。完全虚构的幻想性格,是理性思维与形象思维的结合,是模式化与想象力的结合。主观的、超自然的艺术,观念性的、象征性的艺术。它朝着宗教的境界升华,朝着集体主义性质的精神大家庭回归。

Neural Network Method for Colorimetry Calibration of Video Cameras

To transfer the color data from a device (video camera) dependent color space into a device? independent color space, a multilayer feedforward network with the error backpropagation (BP) learning rule, was regarded as a nonlinear transformer realizing the mapping from the RGB color space to CIELAB color space. A variety of mapping accuracy were obtained with different network structures. BP neural networks can provide a satisfactory mapping accuracy in the field of color space transformation for video cameras.

Study on Tri-Stimulus Transformation

To decrease number of samples for the implementation of color space transformation, a method for modeling the chromatic characterization of video cameras was proposed. An additional transformation was required to predict output RGB values for an input color. This additional transformation was based on spectral reflectance relationship. The transformed color coordinates were taken as inputs of a multilayer neural network. Based on network outputs, the RGB values to be predicted were calculated. Experimental results were given to illustrate the performance of the method. Even though much less number of training samples are used, this method can also perform well on this color space transformation.

EFFECTIVE FEATURE ANALYSIS FOR COLOR IMAGE SEGMENTATION

An approach for color image segmentation is proposed based on the contributions of color features to segmentation rather than the choice of a particular color space. The determination of effective color features depends on the analysis of various color features from each tested color image via the designed feature encoding. It is different from the pervious methods where self organized feature map (SOFM) is used for constructing the feature encoding so that the feature encoding can self organize the effective features for different color images. Fuzzy clustering is applied for the final segmentation when the well suited color features and the initial parameter are available. The proposed method has been applied in segmenting different types of color images and the experimental results show that it outperforms the classical clustering method. The study shows that the feature encoding approach offers great promise in automating and optimizing the segmentation of color images.

Beneficial effects of moderate voluntary physical exercise and its biological mechanisms on brain health

This article reviewed the beneficial effects of moderate voluntary physical exercise on brain health according to the studies on humans and animals, which includes improving psychological status and cognitive function, enhancing psychological well-being, decreasing the risks of Alzheimer＇s disease （AD） and dementia, and promoting the effects of antidepressant and anxiolytic. The possible underlying neurobiological mechanisms are involved up-active and down-active pathways. The up-active pathway is associated with enhancements of several neurotransmitters systems afferent to hippocampus, including norepinephrine （NE）, serotonin （5-Hydroxytryptamine, 5-HT）, acetylcholine （ACh） and γ-aminobutyric acid （GABA）. The down-active pathway is mainly concerned with up-regulation of the brain-derived neurotrophic factor （BDNF） and neurogenesis. It is suggested that NE activation via β-adrenergic receptors may be essential for exercise-induced BDNF up-regulation. The possible intracellular signaling pathways of NE-mediated BDNF up-expression may be involved in GPCR-MAPK-PI-3K crosstalk and positive feedback.

洛阳刘心剪纸:在传承中绚丽绽放

＂逛洛阳老城,赏牡丹纸雕。＂说的就是独具特色的洛阳刘心剪纸。凭借一腔热血和激情,十五载日夜坚守与创新,刘心集百家之所长,独辟蹊径,将洛阳剪纸这一非物质文化遗产再现异彩。二月的古都,春寒料峭,本刊记者走进始建于隋朝的洛阳老城丽景门,踏上西大街古色古香的青石板路,一间不太显眼的临街青砖瓦房店铺隐于熙熙攘攘的游客人流之中。

Research on train integrated positioning based on grey neural network

Train positioning is the key to ensure the transportation and efficient operation of the railway.Due to the low accuracy and the poor real-time of the train positioning,a train positioning system based on global navigation satellite system/inertial measurement unit/odometer(GNSS/IMU/ODO)combination framework and a train integrated positioning method based on grey neural network are put forward.A data updating method based on the established grey prediction model of train positioning is put forward,which uses the accumulation and summary of the grey theory for the rough prediction of the data.The purpose of the method is to reduce the noise of the original data.Moreover,the radial basis function(RBF)neural network is introduced to correct residual sequence of the grey prediction model.Compared with the single model calibration,this method can make full use of the advantages of each model,thus getting a high positioning accuracy in the case of small samples and poor information.Experiments show that the method has good real-time performance and high accuracy,and has certain application value.

Stereo garage parking space allocation model and simulation analysis

Based on grey neural network and particle swarm optimization algorithm,an automated stereo garage decision model is proposed to solve the problems of long waiting queue and low efficiency of automated parking garage.The gray neural network is used to forecast the stay time of the vehicle and particle swarm optimization algorithm is used to allocate the parking spaces in the stereo garage.The proposed stereo garage mathematical model is established on condition that vehicle arrival interval obeys Poisson distribution.The performance of stereo garage is evaluated by the average waiting time,average waiting queue length,average service time and average energy consumption of the customers.By comparing the efficiency indexes of the existing model based on near-distribution principle and the proposed model based on gray neural network and particle swarm algorithm,it is proved that the proposed model based on gray neural network and particle swarm algorithm is effective in improving the efficiency of garage operation and reducing the energy consumption of garage.

Real-Time Face Tracking and Recognition in Video Sequence

A framework of real time face tracking and recognition is presented, which integrates skin color based tracking and PCA/BPNN (principle component analysis/back propagation neural network) hybrid recognition techniques. The algorithm is able to track the human face against a complex background and also works well when temporary occlusion occurs. We also obtain a very high recognition rate by averaging a number of samples over a long image sequence. The proposed approach has been successfully tested by many experiments, and can operate at 20 frames/s on an 800 MHz PC.

Galileo and Kepler： On Theoremata Circa Centrum Gravitatis Solidorum and Mysterium Cosmographicum

This paper deals with two case studies： （a） The role played by geometry and physical objects in Galileo＇s Theoremata Circa Centrum Gravitatis Solidorum comparing with Archimedean approach-mental experiments, and method of composition and de-composition, circumscribed and inscribed figures on centre of gravity studies; （b） The complex network of relations, which in Mysterium Cosmographicum, links the experimental part of astronomy to the theoretical aspect and, in the case of Kepler, the metaphysical aspect. The authors focus their efforts on understanding why Kepler reached such a strange, genial and original connection between practice and theory. The aim of this paper is to discuss the relationship between physics-mathematics （-metaphysics） and between experiments-observations-theory in the work of two scientists, Galileo and Kepler.

Function chain neural network prediction on heat transfer performance of oscillating heat pipe based on grey relational analysis

As for the factors affecting the heat transfer performance of complex and nonlinear oscillating heat pipe (OHP),grey relational analysis (GRA) was used to deal with the relationship between heat transfer rate of a looped copper-water OHP and charging ratio,inner diameter,inclination angel,heat input,number of turns,and the main influencing factors were defined.Then,forecasting model was obtained by using main influencing factors (such as charging ratio,interior diameter,and inclination angel) as the inputs of function chain neural network.The results show that the relative average error between the predicted and actual value is 4%,which illustrates that the function chain neural network can be applied to predict the performance of OHP accurately.

Prediction Model of Sewing Technical Condition by Grey Neural Network

The grey system theory and the artificial neural network technology were applied to predict the sewing technical condition. The representative parameters, such as needle, stitch, were selected. Prediction model was established based on the different fabrics’ mechanical properties that measured by KES instrument. Grey relevant degree analysis was applied to choose the input parameters of the neural network. The result showed that prediction model has good precision. The average relative error was 4.08% for needle and 4.25% for stitch.

Application of gray correlation analysis and artificial neural network in rock mass blasting

Studied forecasting and controlling the blasting fragmentation by using artifi- cial neural network for multi-ingredients. At the same time, according to the characteris- tic of multi-parameters input to network model, the gray correlation theory was employed to find out key factors, which can not only save time of computation and parameters in- put, but improve the stability of the model.

Color space lip segmentation for drivers＇ fatigue detection

to the chroma distribution diversity （CDD） between lip color and skin color, the lip color area is segmented by the back propagation neural network （BPNN） with three typical color features. Isolated noisy points of the lip color area in binary image are eliminated by a proposed re- gion connecting algorithm. An improved integral projection algorithm is presented to locate the lip boundary. Whether a driver is fatigued is recognized by the ratio of the frame number of the images with mouth opening continuously to the total image frame number in every 20s. The experiments show that the proposed algorithm provides higher correct rate and reliability for fatigue driving detec- tion, and is superior to the single color feature-based method in the lip color segmention. Besides, it improves obviously the accuracy and speed of the lip boundary location compared with the traditional integral projection algrothm.

System Dynamics Approach to Urban Water Demand Forecasting—A Case Study of Tianjin

A system dynamics approach to urban water demand forecasting was developed based on the analysis of urban water resources system, which was characterized by multi-feedback and nonlinear interactions among sys-tem elements. As an example, Tianjin water resources system dynamic model was set up to forecast water resources demand of the planning years. The practical verification showed that the relative error was lower than 10%. Fur-thermore, through the comparison and analysis of the simulation results under different development modes pre-sented in this paper, the forecasting results of the water resources demand of Tianjin was achieved based on sustain-able utilization strategy of water resources.