Effects of different carbon sources and C/N values on nonvolatile taste components of Pleurotus eryngii

Pleurotus eryngii, the second largest industrial cultivation mushroom in China, is usually cultivated on substrates mainly consisting of sawdust and corncob. In this study, experiments were performed to determine the effects of different carbon sources and C/N values on nonvolatile taste components of P. eryngii. The effects of different carbon sources on nonvolatile taste components levels revealed that sawdust was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while corncob was beneficial to high contents of carbohydrate, polysaccharides and trehalose. At the similar C/N values, relatively higher sawdust content was beneficial to umami amino acid production, while relatively higher corncob content was beneficial to high contents of carbohydrate, polysaccharides and mannitol. Higher C/N value was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while lower C/N value was beneficial to high contents of carbohydrate, polysaccharides and trehalose. These results provided information for P. eryngii fruit body industrial cultivation to obtain specific nonvolatile taste components with high levels.     

泌阳凹陷复杂断块群油气分布控制因素

泌阳凹陷北部斜坡复杂断块群油田以断鼻、断块及断层+岩性油气藏为主,垂向含油层系多,平面上叠合连片,油气主要富集在鼻状构造主体部位的断鼻断块内。通过对研究区油气控制因素的分析,指出继承性的鼻状构造控制了油气聚集方向和富集程度,油气藏含油范围和油气藏高度则主要受断层封闭性和封闭程度的控制,油气分布规律受伸展构造所伴生的各种断块群构造型式的控制。     

A Study on Turbo—rotor Multi—fault Diagnosis Based on a Neural Network

The multi-fault phenomena are common in the turbo-rotor system of a liquid rocket engine.As it has many excellent qualities,the neural network might be used to solve the problems of multi-fault diagnasis of a turbo-rotor system.First,the feature expression of a common turbo-rotor fault was studied in order to build up the standard fault pattern and satisfy the need of neural network studying and diagnosing.Then.the turbo-rotor fault identification and diagnosis problems were investigated by using a BP(back-propaga-tion)neural network.According to the BP neural network problems,the parallel BP neural network method of multi-fault diagnosis and classification was presented and investigated.The results indicated that the parallel Bp neural network method could solve the turbo-rotor multi-fault diagnosis problems.     

江苏复杂小断块油藏老井侧钻实践与认识

利用停关、低效井实施老井侧钻,其条件包括油藏、井身及技术经济等3个方面。侧钻效益的好坏与油藏类型、侧钻目标有着很大关系,侧钻断块油层、挖掘构造高部位剩余油成功率高,边底水、高渗透油藏侧钻效果好。实践表明,老井侧钻是提高江苏复杂小断块油藏开发效果,降低投资、提高效益的一项重要手段。     

千米桥潜山构造特征及其在油气成藏中的作用

千米桥潜山是黄骅坳陷最典型的新生古储型油气藏，恢复潜山古构造是认识其油气藏特征的重点和难点之一，运用地质力学方法研究潜山内幕构造之后认为，该潜山的形成基础是古生界印支期宽缓复背斜，在燕山期挤压构造作用下形成由逆冲叠瓦扇和反冲断层构成的三角带内幕构造，抬升受侵蚀形成潜山主体，喜马拉雅的两次古旋拉张使潜山掀斜定型。晚第三纪以来发生整体热沉降，潜山两侧凹陷沙三段生成油气向潜山侧向运移成藏。     

Operation of superconducting fault current limiter using vacuum interrupter driven by electromagnetic repulsion force for commutating switch

Using conventional high‐temperature superconducting wire, a model superconducting fault current limiter (SFCL) is made and tested. Solenoid coil using Bi2223 silver sheath wire is so made that inductance is as small as possible and a vacuum interrupter is connected in series to it. A conventional reactor coil is connected in parallel. When the fault current flows in this equipment, superconducting wire is quenched and current is transferred into the parallel coil because of voltage drop of superconducting wire. This large current in parallel coil actuates magnetic repulsion mechanism of vacuum interrupter. Due to opening of vacuum interrupter, the current in superconducting wire is broken. By using this equipment, current flow time in superconducting wire can be easily minimized. On the other hand, the fault current is also easily limited by large reactance of parallel coil. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 164(1): 52–61, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20315     

A novel distributed approach to robust fault detection and identification

In this paper, we propose a novel distributed robust fault detection and identification (RFDI) scheme for a class of nonlinear systems. Firstly, a detection and identification estimator—robust fault tracking approximator (RFTA) is designed for online health monitoring. A novel feature of the RFTA is that it can simultaneously detect and accurately identify the shape and magnitude of the fault and disturbance. Moreover, it takes less online training time compared with the traditional neural network based fault diagnosis schemes. For some distributed systems, a network of distributed estimators is constructed where the RFTA is embedded into each estimator. Then we use consensus filter to filter the outputs of each estimator. One of the most important merits of the consensus filter is that its outputs can dramatically improve the accuracy of fault detection and identification. Next, the stability of the distributed RFDI scheme is rigorously investigated. Finally, two numerical examples are given to illustrate the feasibility and effectiveness of the proposed approach.     

Estimation for the number of components in a mixture model using stepwise split-and-merge EM algorithm

The main difficulty with EM algorithm for mixture model concerns the number of components, say g. This is the question of model selection, and the EM algorithm itself could not estimate g. On the contrary, the algorithm requires g to be specified before the remaining parameters can be estimated. To solve this problem, a new algorithm, which is called stepwise split-and-merge EM (SSMEM) algorithm, is proposed. The SSMEM algorithm alternately splits and merges components, estimating g and other parameters of components simultaneously. Also, two novel criteria are introduced to efficiently select the components for split or merge. Experimental results on simulated and real data demonstrate the effectivity of the proposed algorithm.     

Estimating and eliminating redundant data transfers over the web: a fragment based approach

Redundant data transfers over the Web, can be mainly attributed to the repeated transfers of unchanged data. Web caches and Web proxies are some of the solutions that have been proposed, to deal with the issue of redundant data transfers. In this paper we focus on the efficient estimation and reduction of redundant data transfers over the Web. We first prove that a vast amount of redundant data is transferred in Web pages that are considered to carry fresh data. We show this by following an approach based on Web page fragmentation and manipulation. Web pages are broken down to fragments, based on specific criteria. We then deal with these fragments as independent constructors of the Web page and study their change patterns independently and in the context of the whole Web page. After the fragmentation process, we propose solutions for dealing with redundant data transfers. This paper has been based on our previous work on ‘Web Components’ but also on related work by other researchers. It utilises a proxy based, client/server architecture, and imposes changes to the algorithms executed on the Proxy server and on clients. We show that our proposed solution can considerably reduce the amount of redundant data transferred on the Web. Copyright © 2004 John Wiley & Sons, Ltd.