朱良春教授“虫蚁搜剔通络法在心系病中的应用”学术经验浅析

络病概念萌芽于《黄帝内经》,发展于汉代,鼎盛于清代,当代医家做出了巨大的贡献,并初步形成“络病证治”体系,为络病学科的建立奠定了理论基础。本研究简单回顾络病思想的源流,重点介绍朱良春教授《虫类药的应用》对络病学说产生的影响以及朱老学术经验“虫蚁搜剔通络法在心系病中的应用”等。

搜络逐瘀法治疗腰椎间盘突出症临床观察

目的：探讨搜络逐瘀法治疗腰椎间盘突出症的临床疗效。方法：120例腰椎间盘突出症患者．按随机数字表法分为对照组和观察组各60例，对照组采取双氯芬酸钠双释放肠溶胶囊及甲钴胺片治疗，观察组用肾痹汤治疗，服药3周。所有患者均经3个月随访，观察比较两组治疗前后疼痛视觉模拟评分（VAS）、日本骨科协会（JOA）评分、临床疗效及不良反应发生率。结果：两组治疗后及末次随访时两组VAS及JOA评分均较治疗前显著改善（P〈0．05），观察组在治疗后及末次随访时VAS及JOA评分均较对照组改善明显（P〈0．05）；治疗后观察组临床疗效与对照组比较差异无统计学意义（P〉0．05），末次随访时观察组临床疗效明显优于对照组（P〈0．05）。结论：搜络逐瘀法治疗腰椎间盘突出症能够缓解腰椎间盘突出引起的症状和体征。

活血搜风涤痰通络法治疗偏头68例

偏头痛是临床常见病,近几年来有上升的趋势。笔者从医30余年来,探索应用活血搜风涤痰通络法治疗本病,取得了较好的疗效,现介绍如下: 1.临床资料 1.1 一资资料 本组68例,均为门诊患者。其中男22例,女46例;年龄19—55岁,平均36.5岁。职业:工人16例,居民12例,农民30例,干部10例。病程最短5个月,最长21年。

以搜剔通络法治疗71例糖尿病周围神经病变患者的结果分析

糖尿病周围神经病变（DPN）是糖尿病常见的慢性并发症，严重影响患者的生活质量。随着临床电生理研究的深入开展，证明其并非糖尿病的晚期并发症，发生在糖尿病初期者并不少见，总的发病率高达90％以上，发病机制尚未完全清楚，亦无特异的治疗方法。我们采用虫蚁搜逐的动物类药为主，配以活血养血之品而组成中药水丸制剂——九虫丹，治疗DPN71例，现将结果报告如下。

络病学说探析

"久病入络"是络病的主要病机,"络脉阻滞"是络病最基本的病理改变。络脉为病均有不同程度的气郁、血阻或痰结等"络瘀"表现,"通络"是总治则,细之又有"祛邪通络"、"扶正通络"两大类及宣络、透络、清络、活络、柔络、通络、搜络诸法。

搜剔肺络法对难治性哮喘患者诱导痰IL-1β水平的影响

目的:探讨搜剔肺络法(苏子降气汤加蜈蚣全蝎)对难治性哮喘患者诱导痰白细胞介素1β(IL-1β)水平的影响。方法:将上海中医药大学2所附属医院收治的60例难治性哮喘患者采用随机信封法分为治疗组和对照组每组30例。2组均给予西药三联吸入治疗,治疗组在此基础上给予苏子降气汤加蜈蚣全蝎中药汤剂治疗,对照组给予苏子降气汤治疗,疗程12周。比较2组患者哮喘控制测试(ACT)评分、肺功能、诱导痰IL-1β水平以及血常规、肝肾功能等安全性指标。结果:治疗后2组ACT评分、第1秒用力呼气量(FEV 1.0)、第1秒用力呼气量与用力肺活量比值(FEV 1.0/FVC)较治疗前升高,IL-1β较治疗前下降,治疗组改善程度明显优于对照组,差异均有统计学意义(P<0.05或P<0.01)。治疗前后,2组患者外周血嗜酸性粒细胞水平均未见明显变化,2组患者治疗后各项安全性指标均在正常范围内。结论:搜剔肺络法可有效改善难治性哮喘患者哮喘控制水平和肺功能,降低诱导痰IL-1β水平,其作用机制可能与抑制细胞焦亡有关。

大黄虫丸对博来霉素致肺纤维化模型大鼠MMP-2和TGF-β1的影响

目的基于"肺系络病"理论,研究搜剔肺络法代表方大黄虫丸对博来霉素致肺纤维化模型大鼠胶原沉积的影响。方法选雄性SD大鼠60只,随机分为6组即空白组、模型组、醋酸泼尼松组、大黄虫丸小剂量组、大黄虫丸中剂量组、大黄虫丸大剂量组,每组10只。于造模28天后常规每日一次灌胃给药,给药30天后麻醉取肺组织,进行HE、Masson染色、免疫组化检测基质金属蛋白酶-2(MMP-2)的表达,ELISA检测血清转化生长因子β1(TGF-β1)的含量,观察并比较各指标的组间差异。结果在MMP-2表达方面,与模型组、醋酸泼尼松组相比,大黄虫丸各剂量组表达明显减弱(P<0.05),并与胶原沉积的高低相一致。在血清TGF-β1含量方面,模型组及各药物干预组与空白组比较无明显差异(P>0.05);本研究说明大黄虫丸对肺纤维化模型大鼠具有一定的治疗作用,并优于西药激素的治疗效果,其治疗作用是通过对MMP-2的表达抑制实现的,其并不能抑制肺组织TGF-β1的产生。结论大黄虫丸可能通过抑制MMP-2的表达发挥抗纤维化的作用。

叶天士“久病入络”学术思想及络治法探析

络脉遍及全身,纵横交错,沟通表里两经、脏腑官窍、四肢百骸。邪气侵袭人体,首先侵及络脉,并通过络脉传入经脉、脏腑等。叶天士在总结前人经验的基础上,提出"久病入络"的观点,认为凡痛证,初起在气者,伤经,当以治气、理气为主;久病在血者,伤络,当以治血、活血为先。叶天士的络治法不同于一般的理气逐血之法,而是在"络以通为用"的原则下,归纳出多种通络方法,如辛温通络法、搜邪通络法、活血化瘀通络法、降气通络法、补虚通络法等,使血无凝滞、气血宣通而病自愈。

大黄?虫丸对博来霉素致肺纤维化模型大鼠胶原蛋白和肺组织羟脯氨酸的影响

目的基于"肺系络病"理论,研究搜剔肺络法代表方大黄虫丸对博来霉素致肺纤维化模型大鼠胶原蛋白含量和肺组织羟脯氨酸(hydroxyproline,HYP)的影响。方法选择雄性SD大鼠60只,随机分为6组即空白组、模型组、醋酸泼尼松组、大黄虫丸低剂量组、大黄虫丸中剂量组、大黄虫丸高剂量组,每组10只。于造模28天后常规每日一次灌胃给药,给药30天后麻醉取肺组织,进行HE、Masson染色,肺组织胶原蛋白含量测定,肺组织HYP含量测定,并比较各指标的组间差异。结果胶原含量的高低方面,与模型组、醋酸泼尼松组相比,大黄虫丸各剂量组表达明显减弱(P<0.05);在HYP含量测定方面,模型组及各药物干预组明显高于空白组(P<0.05),模型组与醋酸泼尼松组及大黄虫丸各剂量组两两之间无明显差异(P>0.05)。本研究说明大黄虫丸对肺纤维化模型大鼠具有一定的治疗作用,并优于西药激素的治疗效果,且其治疗作用是通过对胶原蛋白的表达抑制实现的,其并不能抑制肺组织HYP的产生。结论大黄虫丸可能通过抑制胶原蛋白的表达发挥抗纤维化的作用。

Wind speed forecasting based on wavelet decomposition and wavelet neural networks optimized by the Cuckoo search algorithm

Wind speed forecasting is of great importance for wind farm management and plays an important role in grid integration. Wind speed is volatile in nature and therefore it is difficult to predict with a single model. In this study, three hybrid multi-step wind speed forecasting models are developed and compared — with each other and with earlier proposed wind speed forecasting models. The three models are based on wavelet decomposition(WD), the Cuckoo search(CS) optimization algorithm, and a wavelet neural network(WNN). They are referred to as CS-WD-ANN(artificial neural network), CS-WNN, and CS-WD-WNN, respectively. Wind speed data from two wind farms located in Shandong, eastern China, are used in this study. The simulation result indicates that CS-WD-WNN outperforms the other two models, with minimum statistical errors. Comparison with earlier models shows that CS-WD-WNN still performs best, with the smallest statistical errors. The employment of the CS optimization algorithm in the models shows improvement compared with the earlier models.

Conformations and Metal Ion Affinities of Glutamine Binding with Alkali and Alkaline Earth Metal Cations： an ab initio Study

Conformations and reaction energetics are important for understanding the interactions be- tween biomolecules and metal ions. In this work, we report a systematic ab initio study on the conformations and metal ion affinities of glutamine （Gln） binding with alkali and alkaline earth metal ions. An efficient and reliable method of searching low energy conformations of metalated Gln is proposed and applied to the complexes of Gln.Gln.M^＋/＋＋（M＋/＋＋=Li^＋、Na^＋、K^＋、Rb^＋、Cs^＋、Be^＋＋、Mg^＋＋、Ca^＋＋、Sr^＋＋ and Ba^＋＋）.. In addition to all conformers known in literatures, many new important conformations are located, demonstrating the power of the new method and the necessity of the conformational search performed here. The metal coordination modes, relative energies, dipole moments, and equilibrium distributions of all important conformations of Gln.M^＋/＋＋ are calculated by the methods of B3LYP, BHandHLYP, and MP2. IR spectra and metalation enthalpies and free energies are also presented and compared with the available experiments. The results form an extensive database for systematic examination of the metalation properties of Gln.

Neural Network Based Algorithm and Simulation of Information Fusion in the Coal Mine

The concepts of information fusion and the basic principles of neural networks are introduced. Neural net-works were introduced as a way of building an information fusion model in a coal mine monitoring system. This assures the accurate transmission of the multi-sensor information that comes from the coal mine monitoring systems. The in-formation fusion mode was analyzed. An algorithm was designed based on this analysis and some simulation results were given. Finally,conclusions that could provide auxiliary decision making information to the coal mine dispatching officers were presented.

Routing Protocol Based on Grover’s Searching Algorithm for Mobile Ad-hoc Networks

In Mobile Ad-hoc Networks (MANETs), routing protocols directly affect various indices of network Quality of Service (QoS), so they play an important role in network performance. To address the drawbacks associated with traditional routing protocols in MANETs, such as poor anti-fading performance and slow convergence rate, for basic Dynamic Source Routing (DSR), we propose a new routing model based on Grover's searching algorithm. With this new routing model, each node maintains a node vector function, and all the nodes can obtain a node probability vector using Grover's algorithm, and then select an optimal routing according to node probability. Simulation results show that compared with DSR, this new routing protocol can effectively extend the network lifetime, as well as reduce the network delay and the number of routing hops. It can also significantly improve the anti-jamming capability of the network.

Present Tectonic Stress Field in the Capital Region of China Inverted from Focal Mechanisms of Small and Strong Earthquakes

A dense seismic network was installed in the capital region of China in recent years,which makes it possible to resolve the focal mechanisms of small earthquakes. We gathered large earthquake focal mechanisms from the last fifty years and moderate or small earthquake focal mechanisms from between 2002 and 2004,and calculated the present tectonic stress field of the capital region by the grid search method, which weighs different sized earthquakes and can improve the accuracy of the stress field inversion. The analysis of inversion results of different sub-regions shows that the azinuth of the maximum principal compressive stress axis is NE43°- 86° in the Beijing-Zhangjiakou-Datong area,NE38°-86° in the Tangshan area,and NE79°- 81° in the Xingtai area. Inversion results of this paper are similar to previous results,which proves the correctness of the approach. As revealed by the results,the stress field of the capital region is characterized by overall consistency and sub-regional differences. This study provides reference for earthquake mechanism explanation and geodynamics research.

An Effective Fault Diagnosis Method for Aero Engines Based on GSA-SAE

The health status of aero engines is very important to the flight safety.However,it is difficult for aero engines to make an effective fault diagnosis due to its complex structure and poor working environment.Therefore,an effective fault diagnosis method for aero engines based on the gravitational search algorithm and the stack autoencoder(GSA-SAE)is proposed,and the fault diagnosis technology of a turbofan engine is studied.Firstly,the data of 17 parameters,including total inlet air temperature,high-pressure rotor speed,low-pressure rotor speed,turbine pressure ratio,total inlet air temperature of high-pressure compressor and outlet air pressure of high-pressure compressor and so on,are preprocessed,and the fault diagnosis model architecture of SAE is constructed.In order to solve the problem that the best diagnosis effect cannot be obtained due to manually setting the number of neurons in each hidden layer of SAE network,a GSA optimization algorithm for the SAE network is proposed to find and obtain the optimal number of neurons in each hidden layer of SAE network.Furthermore,an optimal fault diagnosis model based on GSA-SAE is established for aero engines.Finally,the effectiveness of the optimal GSA-SAE fault diagnosis model is demonstrated using the practical data of aero engines.The results illustrate that the proposed fault diagnosis method effectively solves the problem of the poor fault diagnosis result because of manually setting the number of neurons in each hidden layer of SAE network,and has good fault diagnosis efficiency.The fault diagnosis accuracy of the GSA-SAE model reaches 98.222%,which is significantly higher than that of SAE,the general regression neural network(GRNN)and the back propagation(BP)network fault diagnosis models.

Distributed Localization Algorithm for Wireless Sensor Network Based on Multidimensional Scaling and the Shortest Path Distance Correction

Sensor localization is crucial for the configuration and applications of wireless sensor network (WSN). A novel distributed localization algorithm, MDS-DC was proposed for wireless sensor network based on multidimensional scaling (MDS) and the shortest path distance correction. In MDS-DC, several local positioning regions with reasonable distribution were firstly constructed by an adaptive search algorithm, which ensures the mergence between the local relative maps of the adjacent local position regions and can reduce the number of common nodes in the network. Then, based on the relationships between the estimated distances and actual distances of anchors, the distance estimation vectors of sensors around anchors were corrected in each local positioning region. During the computations of the local relative coordinates, an iterative process, which is the combination of classical MDS algorithm and SMACOF algorithm, was applied. Finally, the global relative positions or absolute positions of sensors were obtained through merging the relative maps of all local positioning regions. Simulation results show that MDS-DC has better performances in positioning precision, energy efficiency and robustness to range error, which can meet the requirements of applications for sensor localization in WSN.

Network coding resources optimization with transmission delay constraint in multicast networks

Minimizing network coding resources of multicast networks,such as the number of coding nodes or links,has been proved to be NP-hard,and taking propagation delay into account makes the problem more complicated. To resolve this optimal problem,an integer encoding routing-based genetic algorithm( REGA) is presented to map the optimization problem into a genetic algorithm( GA)framework. Moreover,to speed up the search process of the algorithm,an efficient local search procedure which can reduce the searching space size is designed for searching the feasible solution.Compared with the binary link state encoding representation genetic algorithm( BLSGA),the chromosome length of REGA is shorter and just depends on the number of sinks. Simulation results show the advantages of the algorithm in terms of getting the optimal solution and algorithmic convergence speed.

On Minimizing Delay with Probabilistic Splitting of Traffic Flow in Heterogeneous Wireless Networks

In the paper,we propose a framework to investigate how to effectively perform traffic flow splitting in heterogeneous wireless networks from a queue point.The average packet delay in heterogeneous wireless networks is derived in a probabilistic manner.The basic idea can be understood via treating the integrated heterogeneous wireless networks as different coupled and parallel queuing systems.The integrated network performance can approach that of one queue with maximal the multiplexing gain.For the purpose of illustrating the effectively of our proposed model,the Cellular/WLAN interworking is exploited.To minimize the average delay,a heuristic search algorithm is used to get the optimal probability of splitting traffic flow.Further,a Markov process is applied to evaluate the performance of the proposed scheme and compare with that of selecting the best network to access in terms of packet mean delay and blocking probability.Numerical results illustrate our proposed framework is effective and the flow splitting transmission can obtain more performance gain in heterogeneous wireless networks.