季节昼夜影响自发动功的易诱性测定

《灵枢·顺气一日分为四时篇》曰:“春生、夏长、秋收、冬藏,是气之常也,人亦应之。以一日分为四时,朝则为春,日中为夏,日入为秋,夜半为冬。”此实为“天人相应”的直接写照。那么,炼自发动功是否存在着这种“相应”,四时季节,

点穴自发动功治疗不寐症

我们应用点穴自发动功治疗不寐症,获得了较好的疗效,兹将方法介绍如下。一、练功要领取站桩式,领会下列步骤的精神:百会上竖,两眼内视,舌尖轻抵上腭,上下齿轻叩,自然呼吸,呼气至丹田,头身正直,鼻尖对脐,含胸拔背,收腹蓄臂,命门穴放松,松腰落胯,两膝微屈,两足平行与肩同宽,重心落在足跟,全身由上至下外松暨内松,做到排除杂念,听而不闻,视而不见,以待内气微动。

自发动功功法试析

自发动功是指以练功过程中大部分练功者自然发生身体外部运动为主要特征的一类气功功种。本文对《自发动功》(胡耀贞创)等九种目前较流行的自发动功的功法进行综合对比,总结它们的异同点,并对此类功法的一般功理做了初步思考。一、调身以站式为主,以松为基本原则。九种功法中,除《鹤翔庄站桩功法》和《松动大象功》要求只采取站式外,其余均是在首选站式的同时,也可根据练功者的身体状况而采取坐式或卧式。

气功与超心理学

气功是现代人对中国古代被称为“导引、吐纳、炼丹、守神、存想、静坐、坐禅”等一类心身锻炼方法选定的称呼。比较一下现代各种流派对这一称呼下的定义,虽然说法不一,但可找出一个共同点,即都认为气功是培育人体内气(指元或真气)的一种锻炼方法,不少定义还进一步指出:功夫高深者,还可将这一内气外放,对人或物产生各种效应。

选择气功功法的基本原则

习练气功要取得成功,必须具备“财(投资)、侣(伴侣)、师(老师)、地(场所)”,还要讲究“志(志趣和毅力)、法(功法)、悟(悟性)、性(功德)。”我国著名的功法就有好几百种,选择的时候首先要看自己的身体如何。年纪比较大的体质一般比较差,还有年纪虽然不太大而不太健康的,要选择侧重于强身的功法,练了一段时间,身体比较强壮了,也就是“

Research on resting spontaneous brain activity and functional connectivity of acupuncture at uterine acupoints

Objective The resting-state functional magnetic resonance imaging(rs-f MRI)method was used to observe brain activity and its functional connection upon electroacupuncture stimulation at bilateral uterine acupoints(EX-CA1),as well as to investigate the mechanism of acupuncture in the treatment of gynecological diseases.Methods Twenty-two healthy female subjects were stimulated by electroacupuncture at bilateral uterine acupoints;rs-f MRI data of the brain were acquired and standardized.Degree centrality(DC),amplitude of low-frequency fluctuation(ALFF),and regional homogeneity(ReHo)were used to analyze local spontaneous brain activity via acupuncture.An independent component analysis was used to evaluate the functional connectivity of the resting brain networks after acupuncture.Results Analytical results showed that the neural activity intensity of the precuneus lobe,orbitofrontal cortex,lingual gyrus,amygdala,and posterior central gyrus decreased after acupuncture(voxel P<0.001,cluster P<0.05).Functional connectivity analysis revealed weakened auditory and right frontal-parietal networks(voxel P<0.001,cluster P<0.05),enhanced visual network(voxel P<0.001,cluster P<0.05),and synergistic auditory network and hypothalamic-pituitary system.Conclusion Significant differences in neural activity and functional connectivity in specific brain regions were observed after acupuncture intervention at uterine acupoints;the hypothalamic-pituitary system also showed various active states in different brain regions.It is speculated that the effective mechanism of acupuncture at uterine acupoints is related to the regulation of reproductive hormones,emotional changes,and somatic sensations.Therefore,the methods used in this study could clarify the neural mechanism of uterine-point acupuncture in the treatment of gynecological diseases and may serve as a reference for other studies pertaining to acupuncture.

练气功的身体反应

为了使初学和自学气功的人了解练功时出现的各种身体反应,并且让大家搞清楚哪些是良性反应,哪些是不良反应以及解决的办法,这样就可避免出现思想紧张、无所适从、不可理解及产生恐惧的心理,防止产生偏差。

养生&体育 小同大异

说到养生,大家可能很自然地想到体育运动。觉得两者大同小异,其实,它们是小同而大异。首先,养生与体育运动的预期目标不同。体育追求的是强健,养生追求的则是康健。古希腊奥林匹克运动会是为训练战士设置的,为了提高士兵战斗训练的兴趣。所以,目标是更快、更高、更强。在当时的作战条件下,士兵的体魄强壮与否,会对一些战斗的胜负产生重大的甚至是决定性的影响。

Shadow obstacle model for realistic corner-turning behavior in crowd simulation

This paper describes a novel model known as the shadow obstacle model to generate a realistic comer-tuming behavior in crowd simulation. The motivation for this model comes from the observation that people tend to choose a safer route rather than a shorter one when turning a comer. To calculate a safer route, an optimization method is proposed to generate the corner-turning rule that maximizes the viewing range for the agents. By combining psychological and physical forces together, a full crowd simulation framework is established to provide a more realistic crowd simulation. We demonstrate that our model produces a more realistic comer-turning behavior by comparison with real data obtained from the experiments. Finally, we per- form parameter analysis to show the believability of our model through a series of experiments.

Fast implementation of kernel simplex volume analysis based on modified Cholesky factorization for endmember extraction

Endmember extraction is a key step in the hyperspectral image analysis process. The kernel new simplex growing algorithm （KNSGA）, recently developed as a nonlinear alternative to the simplex growing algorithm （SGA）, has proven a promising endmember extraction technique. However, KNSGA still suffers from two issues limiting its application. First, its random initialization leads to inconsistency in final results; second, excessive computation is caused by the iterations of a simplex volume calculation. To solve the first issue, the spatial pixel purity index （SPPI） method is used in this study to extract the first endrnember, eliminating the initialization dependence. A novel approach tackles the second issue by initially using a modified Cholesky fac- torization to decompose the volume matrix into triangular matrices, in order to avoid directly computing the determinant tauto- logically in the simplex volume formula. Theoretical analysis and experiments on both simulated and real spectral data demonstrate that the proposed algorithm significantly reduces computational complexity, and runs faster than the original algorithm.

A survey of photon mapping state-of-the-art research and future challenges

Global illumination is the core part of photo-realistic rendering. The photon mapping algorithm is an effective method for computing global illumination with its obvious advantage of caustic and color bleeding rendering. It is an active research field that has been developed over the past two decades. The deficiency of precise details and efficient rendering are still the main challenges of photon mapping. This report reviews recent work and classifies it into a set of categories including radiance estimation, photon relaxation, photon tracing, progressive photon mapping, and parallel methods. The goals of our report are giving readers an overall introduction to photon mapping and motivating further research to address the limitations of existing methods.

Quantum-dot cellular automata based reversible low power parity generator and parity checker design for nanocommunication

Quantum-dot cellular automata （QCA） is an emerging area of research in reversible computing. It can be used to design nanoscale circuits. In nanocommunication, the detection and correction of errors in a received message is a major factor. Besides, device density and power dissipation are the key issues in the nanocommunication architecture. For the first time, QCA-based designs of the reversible low-power odd parity generator and odd parity checker using the Feynman gate have been achieved in this study. Using the proposed parity generator and parity checker circuit, a nanocommunication architecture is pro- posed. The detection of errors in the received message during transmission is also explored. The proposed QCA Feynman gate outshines the existing ones in terms of area, cell count, and delay. The quantum costs of the proposed conventional reversible circuits and their QCA layouts are calculated and compared, which establishes that the proposed QCA circuits have very low quantum cost compared to conventional designs. The energy dissipation by the layouts is estimated, which ensures the possibility ofQCA nano-device serving as an alternative platform for the implementation of reversible circuits. The stability of the proposed circuits under thermal randomness is analyzed, showing the operational efficiency of the circuits. The simulation results of the proposed design are tested with theoretical values, showing the accuracy of the circuits. The proposed circuits can be used to design more complex low-power nanoscale lossless cation architecture such as nano-transmitters and nano-receivers

Local uncorrelated local discriminant embedding for face recognition

The feature extraction algorithm plays an important role in face recognition. However, the extracted features also have overlapping discriminant information. A property of the statistical uncorrelated criterion is that it eliminates the redundancy among the extracted discriminant features, while many algorithms generally ignore this property. In this paper, we introduce a novel feature extraction method called local uncorrelated local discriminant embedding(LULDE). The proposed approach can be seen as an extension of a local discriminant embedding(LDE)framework in three ways. First, a new local statistical uncorrelated criterion is proposed, which effectively captures the local information of interclass and intraclass. Second, we reconstruct the affinity matrices of an intrinsic graph and a penalty graph, which are mentioned in LDE to enhance the discriminant property. Finally, it overcomes the small-sample-size problem without using principal component analysis to preprocess the original data, which avoids losing some discriminant information. Experimental results on Yale, ORL, Extended Yale B, and FERET databases demonstrate that LULDE outperforms LDE and other representative uncorrelated feature extraction methods.

Design and simulation of a standing wave oscillator based PLL

A standing wave oscillator(SWO) is a perfect clock source which can be used to produce a high frequency clock signal with a low skew and high reliability. However, it is difficult to tune the SWO in a wide range of frequencies. We introduce a frequency tunable SWO which uses an inversion mode metal-oxide-semiconductor(IMOS) field-effect transistor as a varactor, and give the simulation results of the frequency tuning range and power dissipation. Based on the frequency tunable SWO, a new phase locked loop(PLL) architecture is presented. This PLL can be used not only as a clock source, but also as a clock distribution network to provide high quality clock signals. The PLL achieves an approximately 50% frequency tuning range when designed in Global Foundry 65 nm 1P9 M complementary metal-oxide-semiconductor(CMOS) technology, and can be used directly in a high performance multi-core microprocessor.

A consensus model for group decision making under interval type-2 fuzzy environment

We propose a new consensus model for group decision making(GDM) problems, using an interval type-2 fuzzy environment. In our model, experts are asked to express their preferences using linguistic terms characterized by interval type-2 fuzzy sets(IT2 FSs), because these can provide decision makers with greater freedom to express the vagueness in real-life situations. Consensus and proximity measures based on the arithmetic operations of IT2 FSs are used simultaneously to guide the decision-making process. The majority of previous studies have taken into account only the importance of the experts in the aggregation process, which may give unreasonable results. Thus, we propose a new feedback mechanism that generates different advice strategies for experts according to their levels of importance. In general, experts with a lower level of importance require a larger number of suggestions to change their initial preferences. Finally, we investigate a numerical example and execute comparable models and ours, to demonstrate the performance of our proposed model. The results indicate that the proposed model provides greater insight into the GDM process.