Biodegradable electrospun fibers for drug delivery

The influences of surfactants and medical drugs on the diameter size and uniformity of electrospun poly(L-lactic acid) (PLLA) fibers were examined by adding various surfactants (cationic, anionic, and nonionic) and typical drugs into the PLLA solution. Significant diameter reduction and uniformity improvement were observed. It was shown that the drugs were capsulated inside of the fibers and the drug release in the presence of proteinase K followed nearly zero-order kinetics due to the degradation of the PLLA fibers. Such ultrafine fiber mats containing drugs may find clinical applications in the future.

基于以太网的工业控制网络

应用传统现场总线的工业控制网络无法实现办公室自动化与工业自动化的无缝结合 .由于以太网在确定性、速度和优先法则等方面性能的提高 ,阻碍以太网应用于实时控制环境的难点已被解决 .以太网早已成为商业管理网络的首要选择 ,那么它应用于企业现场设备控制层是控制网络发展的趋势 ,将极大地促进信息从传感器到管理层的集成

裂缝储层预测技术应用研究

In practice,many fracture reservoir was found,which has giant potential for exporation. For example,in limestone fracture reservoir,igneous rock fracture reservoir and shale fracture reservoir ,there are high yield oil wells found. The fracture reservoir has strong anisotropy and is very difficult to explore and produce.Since 1990’s,the techniques that use structure information and P-WAVE seismic attributes to detect fracture developed very rapidly,include stress and strain analysis,using amplitude,interval velocity,time-difference,azimuthal AVO analysis etc. Based on research and develop these advanced techniques of fracture detect,this paper selected two typical fracture reservoir as target area,according to the characters of research area,selected different techniques to pridect the fracture azimuth and density of target,and at last ,confirmed the favored area. This paper includes six parts:the first chapter mainly addresses the domestic and international research actuality about the fracture prediction and the evolement in ShengLi oil field,then according to the temporal exploration requirement,a research route was established; Based on the close relationship between structural fracture and the geotectonic movement and the procedure of rock distortion，the second chapter research the structural fracture predicting technique which is realized by computing the strain in every geotectonic movement ,which is by use of the forward and inversion of the growing history of structure; The third chapter discussed many kind of traditional techniques for fracture reservoir prediction,and point out their disadvantages.then research and develop the coherence volume computing technique which can distinguish from faults,the seismic wave absorbing technique,and other fracture predicting technique which is by use of seismic attributes ,such as azimuthal AVO FVO etc; The fourth chapter first establish the geological and petrophysical model by use of the existed log and drill well information, then research the variation of amplitude and seismic wave which is caused by fractures.based on it , the fracture predicting technique which is by use of variation of azimuthal impedance is researched;The fifth chapter is a case study,it selects shale fracture reservoir in LuoJia area as target,selects several kind of techniques to apply ,at last ,the fracture distribution of target reservoir and favored area were gotten;the sixth chapter is another case study,it selects limestone fracture reservoir in BoShen6 buried hill as target,selects several kind of techniques to apply,similarly favored area were gotten. Based on deeply research and development of the new techniques for fracture reservoir exploration, This paper selects two fracture reservoirs the most typical in ShengLi as targets to be applied ,good results show up a good application way ,which can be used for reference for future fracture exploration,and it can bring materially economic and social benefit.

锦屏一级水电站高应力大断面地下洞室稳定性分析

According to the feature of high stress and large size underground tunnel , a method named DEFLAC is put forward in this paper. DEFLAC is such a method that use disturbing energy as criteria, and based on the simulating software of FLAC. Finally, the method is applied in the underground powerhouse project of Jin-Ping First-level Hydropower Station. The result is well. And some conclusions are got. (1) Based on the geological features of excavation unloading phenomena, they are concluded to three types, what’s more three corresponding mechanical modes are proposed to explain the unloading phenomena. (2) The relation of two standards , which is called GB50287-99 (T) and BQ ,is studied. And the main difference of them ,when they are applied in high stress zone ,is researched. (3) .A method named DEFLAC is put forward , which is combined disturbing energy method and FLAC simulating software. The two dimension and three dimension explicit finite difference expressions are deduced in this paper. (4) Compared the instability area achieved by FLAC and DEFLAC with the measured result, a conclusion is got. That is a more accurate result can be got by DEFLAC. (5) According to the main powerhouse first layer excavation project, the method to search and analyze the instability blocks is studied in this paper. Finally, the results got by FLAC and DEFLAC are compared .A conclusion is got that DEFLAC can judge the stability of blocks induced by intermittent joints, but Block Theory can’t. So more accurate block amount can be got by DEFLAC. It is an effective method to judge stability of blocks

河流-三角洲储层自动对比微相自动识别原理方法和软件系统

Because of the complexity and particularity, especially the result is more depend on the expert' s experience, the calculate method which is based on the simplicity mathematical model can hardly have any effective role in the oilfield .The coalescent method of artificial intelligence and signal manage in the correlation of reservoir use log curve has been put forward.in this paper. Following the principle of "controlled by classification and correlation by deposit gyration ". The system of correlation has been setup, which can identify "standard layer" first by the improved method of gray connection system, and then on the basis of identified "standard layer", interpret the fault, and last identify the layer in the reservoir. A effective method of "the consistent character of a reservoir "has been adopt to solved the puzzle of interpret the fault. On the basis of sedimentary theory and the quantity analysis of log curve shape of different type microfacies, a serial of different type micofacies' s models has been build that use eight optimized parameters, five of eight rationed parameters being used to describe microfacies with log curve, the distribution area of every parameters for the microfacies has been give. Because the classical math can only be used in the areas that principles are very clearly, not be fit for the description of geology character, so The fuzzy math integrate judgment has been adopt in the using log curve to determine microfacies; the accordance ration is 85 percent. A set of software has been programmed which is on the system of Windows. the software has the integration function of data process, auto-contrast reservoir layer, determination of microfacies using log curve, character the connectivity of sandstones and plotting of geology map. Through the application, this system has high precision and has become a useful tool in the study of geology.

樟柳碱和石杉碱甲对学习和记忆的影响及其有关机制的研究

Two experiments were designed to examine the role of the cholinergic agents, anisodine and huperzine A, and related mechanisms. In experiment 1, the effects of anisodine and huperzine A on rat performance in Morris water maze were observed. It was found that the drugs injected before daily training had significant effect on performance of place navigation task and transfer test, while the drugs injected after daily training, before retest and overtraining had no such effect. the results indicated that the drugs, which only have effects on reference memory related to cognitive mapping strategy, may mediate the acquisition process of memory. In experiment 2, the spontaneous hippocampol neuronal activities and the effects of the drugs on them in awake rabbits were observed. The results showed that anisodine had significant inhibitory effect on the activities, the opposite effect was found in huperzine A. Furthermore, sensory stimulation and administration of huperzine A have similar effects. It was sujested that hipppocampus be directly relavent to transmission of information to memory storage system, in which the role of central cholinergic system is critical.

Roles of Knowledge in Motor Learning

The goal of this thesis is to apply the computational approach to motor learning, i.e., describe the constraints that enable performance improvement with experience and also the constraints that must be satisfied by a motor learning system, describe what is being computed in order to achieve learning, and why it is being computed. The particular tasks used to assess motor learning are loaded and unloaded free arm movement, and the thesis includes work on rigid body load estimation, arm model estimation, optimal filtering for model parameter estimation, and trajectory learning from practice. Learning algorithms have been developed and implemented in the context of robot arm control. The thesis demonstrates some of the roles of knowledge in learning. Powerful generalizations can be made on the basis of knowledge of system structure, as is demonstrated in the load and arm model estimation algorithms. Improving the performance of parameter estimation algorithms used in learning involves knowledge of the measurement noise characteristics, as is shown in the derivation of optimal filters. Using trajectory errors to correct commands requires knowledge of how command errors are transformed into performance errors, i.e., an accurate model of the dynamics of the controlled system, as is demonstrated in the trajectory learning work. The performance demonstrated by the algorithms developed in this thesis should be compared with algorithms that use less knowledge, such as table based schemes to learn arm dynamics, previous single trajectory learning algorithms, and much of traditional adaptive control.

How well do we understand the clusters found in microarray data?

Clare, A. and King R.D. (2002) How well do we understand the clusters found in microarray data? In In Silico Biol. 2, 0046

Fuzzy-Rough Sets Assisted Attribute Selection

R. Jensen and Q. Shen. Fuzzy-Rough Sets Assisted Attribute Selection. IEEE Transactions on Fuzzy Systems, vol. 15, no. 1, pp. 73-89, 2007.

Fuzzy-Rough Attribute Reduction with Application to Web Categorization.

R. Jensen and Q. Shen, 'Fuzzy-Rough Attribute Reduction with Application to Web Categorization,' Fuzzy Sets and Systems, vol. 141, no. 3, pp. 469-485, 2004.

Modifying weighted fuzzy subsethood-based rule models with fuzzy quantifiers

K. Rasmani and Q. Shen. Modifying weighted fuzzy subsethood-based rule models with fuzzy quantifiers. Proceedings of the 13th International Conference on Fuzzy Systems, pages 1679-1684, 2004

Using a logical model to predict the growth of yeast

Whelan, K. E. and King, R. D. Using a logical model to predict the growth of yeast. BMC Bioinformatics 2008, 9:97

Imunoterapia Tumoral com Células Dendríticas

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Farmacêuticas

Mermera: Non-Coherent Distributed Shared Memory for Parallel Computing

The proliferation of inexpensive workstations and networks has prompted several researchers to use such distributed systems for parallel computing. Attempts have been made to offer a shared-memory programming model on such distributed memory computers. Most systems provide a shared-memory that is coherent in that all processes that use it agree on the order of all memory events. This dissertation explores the possibility of a significant improvement in the performance of some applications when they use non-coherent memory. First, a new formal model to describe existing non-coherent memories is developed. I use this model to prove that certain problems can be solved using asynchronous iterative algorithms on shared-memory in which the coherence constraints are substantially relaxed. In the course of the development of the model I discovered a new type of non-coherent behavior called Local Consistency. Second, a programming model, Mermera, is proposed. It provides programmers with a choice of hierarchically related non-coherent behaviors along with one coherent behavior. Thus, one can trade-off the ease of programming with coherent memory for improved performance with non-coherent memory. As an example, I present a program to solve a linear system of equations using an asynchronous iterative algorithm. This program uses all the behaviors offered by Mermera. Third, I describe the implementation of Mermera on a BBN Butterfly TC2000 and on a network of workstations. The performance of a version of the equation solving program that uses all the behaviors of Mermera is compared with that of a version that uses coherent behavior only. For a system of 1000 equations the former exhibits at least a 5-fold improvement in convergence time over the latter. The version using coherent behavior only does not benefit from employing more than one workstation to solve the problem while the program using non-coherent behavior continues to achieve improved performance as the number of workstations is increased from 1 to 6. This measurement corroborates our belief that non-coherent shared memory can be a performance boon for some applications.

Distributed Parallel Computing in Mermera: Mixing Noncoherent Shared Memories

Programmers of parallel processes that communicate through shared globally distributed data structures (DDS) face a difficult choice. Either they must explicitly program DDS management, by partitioning or replicating it over multiple distributed memory modules, or be content with a high latency coherent (sequentially consistent) memory abstraction that hides the DDS' distribution. We present Mermera, a new formalism and system that enable a smooth spectrum of noncoherent shared memory behaviors to coexist between the above two extremes. Our approach allows us to define known noncoherent memories in a new simple way, to identify new memory behaviors, and to characterize generic mixed-behavior computations. The latter are useful for programming using multiple behaviors that complement each others' advantages. On the practical side, we show that the large class of programs that use asynchronous iterative methods (AIM) can run correctly on slow memory, one of the weakest, and hence most efficient and fault-tolerant, noncoherence conditions. An example AIM program to solve linear equations, is developed to illustrate: (1) the need for concurrently mixing memory behaviors, and, (2) the performance gains attainable via noncoherence. Other program classes tolerate weak memory consistency by synchronizing in such a way as to yield executions indistinguishable from coherent ones. AIM computations on noncoherent memory yield noncoherent, yet correct, computations. We report performance data that exemplifies the potential benefits of noncoherence, in terms of raw memory performance, as well as application speed.