巨大芽孢杆菌(Bacillusmegaterium)突变株Bn,B5的生物学特性及在Vc二步发酵中的伴生作用

对选出的巨大芽孢杆菌突变株Bn ,B5进行了生物学特性及发酵条件的研究 ,发现它们具耐低 pH和抗高浓 2KGA特性。可促进氧化葡萄糖酸杆菌生长 ,使其延迟期缩短 ,产酸增加。适宜的通气量下 ,摇瓶糖酸转化率提高 10 %～ 14% ;当发酵 pH为 6 .2～ 6 .6时 ,转化率提高 2 0 %～ 30 %

Formation of epsilon-FeXN/BN magnetic nanocomposite and its thermodynamic and kinetic analyses

A nanocomposite of nanometer-sized magnetic granular epsilon-FeXN embedded in a nonmagnetic amorphous boron nitride matrix was prepared by ball milling mixture of alpha-Fe and hexagonal boron nitride in argon atmosphere. The grain size of the epsilon-FeXN alloy was about 10-20 nm. The nitrogen concentration in the epsilon-FeXN alloy increases with extending milling time. Both thermodynamic calculation and the present experiment show that iron and nitrogen atoms have higher alloying driving force than iron and boron atoms. Analyses of thermodynamics and kinetics about formation of the epsilon-FeXN alloy suggested that the formation of the epsilon-FeXN alloy is related to amorphization of the hexagonal boron nitride and refinement of the alpha-Fe. II was found from the present experiment that a critical grain size of the alpha-Fe reacting with nitrogen in the amorphous boron nitride is about 8 nm.

Li_8SiN_4-Li_3N-BN体系中立方BN转化行为的研究

研究了高温高压下x·Li_8SiN_4-0.1(1-x)·Li_3N-0.9(1-x)·BN体系中立方氮化硼(cBN)的转化行为。Li_8SiN_4的存在可显著改善cBN晶体的发育,提高晶体质量。在4.2～5.5GPa,1340～1750℃范围内确定了x=4.8％时体系的cBN转化区,并对转化区内cBN转化率、平均生长速度、成核速度及破碎强度与转化温度和压力的关系进行了研究。

小波域地震资料的处理方法（WSSP）研究

The modeling formula based on seismic wavelet can well simulate zero - phase wavelet and hybrid-phase wavelet, and approximate maximal - phase and minimal - phase wavelet in a certain sense. The modeling wavelet can be used as wavelet function after suitable modification item added to meet some conditions. On the basis of the modified Morlet wavelet, the derivative wavelet function has been derived. As a basic wavelet, it can be sued for high resolution frequency - division processing and instantaneous feature extraction, in acoordance with the signal expanding characters in time and scale domains by each wavelet structured. Finally, an application example proves the effectiveness and reasonability of the method. Based on the analysis of SVD (Singular Value Decomposition) filter, by taking wavelet as basic wavelet and combining SVD filter and wavelet transform, a new de - noising method, which is Based on multi - dimension and multi-space de - noising method, is proposed. The implementation of this method is discussed the detail. Theoretical analysis and modeling show that the method has strong capacity of de - noising and keeping attributes of effective wave. It is a good tool for de - noising when the S/N ratio is poor. To give prominence to high frequency information of reflection event of important layer and to take account of other frequency information under processing seismic data, it is difficult for deconvolution filter to realize this goal. A filter from Fourier Transform has some problems for realizing the goal. In this paper, a new method is put forward, that is a method of processing seismic data in frequency division from wavelet transform and reconstruction. In ordinary seismic processing methods for resolution improvement, deconvolution operator has poor part characteristics, thus influencing the operator frequency. In wavelet transform, wavelet function has very good part characteristics. Frequency - division data processing in wavelet transform also brings quite good high resolution data, but it needs more time than deconvolution method does. On the basis of frequency - division processing method in wavelet domain, a new technique is put forward, which involves 1) designing filter operators equivalent to deconvolution operator in time and frequency domains in wavelet transform, 2) obtaining derivative wavelet function that is suitable to high - resolution seismic data processing, and 3) processing high resolution seismic data by deconvolution method in time domain. In the method of producing some instantaneous characteristic signals by using Hilbert transform, Hilbert transform is very sensitive to high - frequency random noise. As a result, even though there exist weak high - frequency noises in seismic signals, the obtained instantaneous characteristics of seismic signals may be still submerged by the noises. One method for having instantaneous characteristics of seismic signals in wavelet domain is put forward, which obtains directly the instantaneous characteristics of seismic signals by taking the characteristics of both the real part (real signals, namely seismic signals) and the imaginary part (the Hilbert transfom of real signals) of wavelet transform. The method has the functions of frequency division and noise removal. What is more, the weak wave whose frequency is lower than that of high - frequency random noise is retained in the obtained instantaneous characteristics of seismic signals, and the weak wave may be seen in instantaneous characteristic sections (such as instantaneous frequency, instantaneous phase and instantaneous amplitude). Impedance inversion is one of tools in the description of oil reservoir. one of methods in impedance inversion is Generalized Linear Inversion. This method has higher precision of inversion. But, this method is sensitive to noise of seismic data, so that error results are got. The description of oil reservoir in researching important geological layer, in order to give prominence to geological characteristics of the important layer, not only high frequency impedance to research thin sand layer, but other frequency impedance are needed. It is difficult for some impedance inversion method to realize the goal. Wavelet transform is very good in denoising and processing in frequency division. Therefore, in the paper, a method of impedance inversion is put forward based on wavelet transform, that is impedance inversion in frequency division from wavelet transform and reconstruction. in this paper, based on wavelet transform, methods of time - frequency analysis is given. Fanally, methods above are in application on real oil field - Sansan oil field.

An Algorithm for Group Formation and Maximal Independent Set in an Amorphous Computer

Amorphous computing is the study of programming ultra-scale computing environments of smart sensors and actuators cite{white-paper}. The individual elements are identical, asynchronous, randomly placed, embedded and communicate locally via wireless broadcast. Aggregating the processors into groups is a useful paradigm for programming an amorphous computer because groups can be used for specialization, increased robustness, and efficient resource allocation. This paper presents a new algorithm, called the clubs algorithm, for efficiently aggregating processors into groups in an amorphous computer, in time proportional to the local density of processors. The clubs algorithm is well-suited to the unique characteristics of an amorphous computer. In addition, the algorithm derives two properties from the physical embedding of the amorphous computer: an upper bound on the number of groups formed and a constant upper bound on the density of groups. The clubs algorithm can also be extended to find the maximal independent set (MIS) and $Delta + 1$ vertex coloring in an amorphous computer in $O(log N)$ rounds, where $N$ is the total number of elements and $Delta$ is the maximum degree.

The Dirichlet problem in convex bounded domains for operators with L^\infty-coefficients

M.Hieber, I.Wood: The Dirichlet problem in convex bounded domains for operators with L^\infty-coefficients, Diff. Int. Eq., 20, 7 (2007),721-734.

Boundary triplets and M-functions for non-selfadjoint operators, with applications to elliptic PDEs and block operator matrices

B.M. Brown, M. Marletta, S. Naboko, I. Wood: Boundary triplets and M-functions for non-selfadjoint operators, with applications to elliptic PDEs and block operator matrices, J. London Math. Soc., June 2008; 77: 700-718. The full text of this article will be made available in this repository in June 2009 Sponsorship: EPSRC,INTAS