cDNA cloning and overexpression of acidic ribosomal phosphoprotein P1 gene (RPLP1) from the Giant Panda

RPLP1 is one of acidic ribosomal phosphoproteins encoded by RPLP1 gene, which plays an important role in the elongation step of protein synthesis. The cDNA of RPLP1 was cloned successfully for the first time from the Giant Panda (Ailuropoda melanoleuca) using RT-PCR technology, which was also sequenced, analyzed preliminarily and expressed in E. coli. The cDNA fragment cloned is 449bp in size, containing an open reading frame of 344bp encoding 114 amino acids. Alignment analysis indicated that the nucleotide sequence and the deduced amino acid sequence are highly conserved to other five species studied, including Homo sapiens, Mus musculus, Rattus norvegicus, Bos Taurus and Sus scrofa. The homologies for nucleotide sequences of Giant Panda PPLP1 to that of these species are 92.4%, 89.8%, 89.0%, 91.3% and 87.5%, while the homologies for amino acid sequences are 96.5%, 94.7%, 95.6%, 96.5% and 88.6%. Topology prediction showed there are three Casein kinase II phosphorylation sites and two N-myristoylation sites in the RPLP1 protein of the Giant Panda (Ailuropoda melanoleuca). The RPLP1 gene was overexpressed in E. coli and the result indicated that RPLP1 fusion with the N-terminally His-tagged form gave rise to the accumulation of an expected 18kDa polypeptide, which was in accordance with the predicted protein and could also be used to purify the protein and study its function.

双向联想记忆神经网络的一种编码策略

本文提出一种双向联想记忆神经网络的按‘位’加权编码策略，并给出了求取权值的速推算法．它将Ｋｏｓｋｏ双向联想记忆神经网络按海明距离进行模式匹配的原则，修正为按加权海明距离进行模式匹配，从而可以使得对不满足连续性的所谓“病态结构”的一类样本模式集，同样具有良好的联想能力．对二值图象模式存贮、联想的计算机模拟实验表明，此方法具有优良的性能和实用价值。

基于量子蒙特卡罗的地震波反演方法

The primary approaches for people to understand the inner properties of the earth and the distribution of the mineral resources are mainly coming from surface geology survey and geophysical/geochemical data inversion and interpretation. The purpose of seismic inversion is to extract information of the subsurface stratum geometrical structures and the distribution of material properties from seismic wave which is used for resource prospecting, exploitation and the study for inner structure of the earth and its dynamic process. Although the study of seismic parameter inversion has achieved a lot since 1950s, some problems are still persisting when applying in real data due to their nonlinearity and ill-posedness. Most inversion methods we use to invert geophysical parameters are based on iterative inversion which depends largely on the initial model and constraint conditions. It would be difficult to obtain a believable result when taking into consideration different factors such as environmental and equipment noise that exist in seismic wave excitation, propagation and acquisition. The seismic inversion based on real data is a typical nonlinear problem, which means most of their objective functions are multi-minimum. It makes them formidable to be solved using commonly used methods such as general-linearization and quasi-linearization inversion because of local convergence. Global nonlinear search methods which do not rely heavily on the initial model seem more promising, but the amount of computation required for real data process is unacceptable. In order to solve those problems mentioned above, this paper addresses a kind of global nonlinear inversion method which brings Quantum Monte Carlo (QMC) method into geophysical inverse problems. QMC has been used as an effective numerical method to study quantum many-body system which is often governed by Schrödinger equation. This method can be categorized into zero temperature method and finite temperature method. This paper is subdivided into four parts. In the first one, we briefly review the theory of QMC method and find out the connections with geophysical nonlinear inversion, and then give the flow chart of the algorithm. In the second part, we apply four QMC inverse methods in 1D wave equation impedance inversion and generally compare their results with convergence rate and accuracy. The feasibility, stability, and anti-noise capacity of the algorithms are also discussed within this chapter. Numerical results demonstrate that it is possible to solve geophysical nonlinear inversion and other nonlinear optimization problems by means of QMC method. They are also showing that Green’s function Monte Carlo (GFMC) and diffusion Monte Carlo (DMC) are more applicable than Path Integral Monte Carlo (PIMC) and Variational Monte Carlo (VMC) in real data. The third part provides the parallel version of serial QMC algorithms which are applied in a 2D acoustic velocity inversion and real seismic data processing and further discusses these algorithms’ globality and anti-noise capacity. The inverted results show the robustness of these algorithms which make them feasible to be used in 2D inversion and real data processing. The parallel inversion algorithms in this chapter are also applicable in other optimization. Finally, some useful conclusions are obtained in the last section. The analysis and comparison of the results indicate that it is successful to bring QMC into geophysical inversion. QMC is a kind of nonlinear inversion method which guarantees stability, efficiency and anti-noise. The most appealing property is that it does not rely heavily on the initial model and can be suited to nonlinear and multi-minimum geophysical inverse problems. This method can also be used in other filed regarding nonlinear optimization.

地震波阻抗反演的迭代正则化算法

Post-stack seismic impedance inversion is the key technology of reservoir prediction and identification. Geophysicists have done a lot of research for the problem, but the developed methods still cannot satisfy practical requirements completely. The results of different inversion methods are different and the results of one method used by different people are different too. The reasons are due to the quality of seismic data, inaccurate wavelet extraction, errors between normal incidence assumption and real situation, and so on. In addition, there are two main influence factors: one is the band-limited property of seismic data; the other is the ill-posed property of impedance inversion. Thus far, the most effective way to solve the band-limited problem is the constrained inversion. And the most effective way to solve ill-posed problems is the regularization method assisted with proper optimization techniques. This thesis systematically introduces the iterative regularization methods and numerical optimization methods for impedance inversion. A regularized restarted conjugate gradient method for solving ill-posed problems in impedance inversion is proposed. Theoretic simulations are made and field data applications are performed. It reveals that the proposed algorithm possesses the superiority to conventional conjugate gradient method. Finally, non-smooth optimization is proposed as the further research direction in seismic impedance inversion according to practical situation.

金融工作者的抑郁症状的影响因素及其形成机制研究

Ill-health prevails in the workplace. A key problem encountered in the area of stress management is a lack of research into the way job burnout turns into mental problems, especially depressive symptoms, the most prevalent and costly psychiatric condition in the workplace. This research belongs to a cross-discipline area of industrial psychiatry and organizational behavior, which has seldom been investigated before. This research will contribute to the theoretical development of organizational behavior, especially to stress management and industrial psychiatry. This study aims to explore etiological factors and mechanisms of depressive symptoms of workers in the financial industry. By using literature review, semi-structured interviews and surveys as the major research methods, this Ph.D. study systematically investigated the risk factors of workers’ depressive symptoms within and outside of the work area. These risk factors are worker-work environment fits, work family conflicts, and workers’ psychological vulnerabilities to depression. A thorough literature review and 20 semi-structured interviews of brokers in different kinds of financial markets show the feasibility and necessity of this Ph.D. study when it comes to the issue of financial workers’ depressive symptoms. Two surveys of workplace-etiological factors of depressive symptoms were conducted among 244 financial workers and 1024 financial workers. This cross-sample verification showed that worker-work environment fit was a good framework to study risk factors of workers’ depressive symptoms. Results revealed that job demands-abilities misfit could lead to job burnout which in turn contributed to worker’s depressive symptoms; besides this, work effort-reward imbalance could directly cause workers’ depressive symptoms. Emotional labor enhanced the positive effect of job burnout on workers’ depressive symptoms. In the third study, a prominent risk factor outside of the work area, namely work family conflict, and workers’ psychological vulnerabilities of depression were included with workplace etiological factors to investigate the overall predictive model of depressive symptoms of financial workers. The survey was conducted among the same 1024 financial workers. Results indicated that work effort-reward imbalance, job burnout and work interfering in family life were three external etiological factors of workers’ depressive symptoms. Neuroticism, autonomy and low emotional intelligence were three individual etiological factors which had a positive effect on workers’ depressive symptoms. Moreover, neuroticism enhanced the relationship between job burnout and depressive symptoms as well as between work interfering in family life and depressive symptoms. Autonomy aggravated the relationship between job burnout and depressive symptoms. However, emotional intelligence attenuated the relationship between job burnout and depressive symptoms as well as between work effort-reward imbalance and depressive symptoms. Besides, workers’ dysfunctional attitudes played a partial mediating role in the relationships between above etiological factors and depressive symptoms. In the same sample, research evidence of impairments of workers’ depressive symptoms to their work-life quality was also obtained. Specifically, depressive symptoms could predict workers’ presenteeism, absenteeism and turnover intention. Their subjective well-being was also lowered when suffering more severe depressive symptoms. This research provides a theoretical basis to management practices targeted to set up the Employee Assistance Program or even more specilised rehabilitation programs for workers with depressive symptoms so as to improve their work-life quality and and establish a harmonious enterprise.

An Optimal Scale for Edge Detection

Many problems in early vision are ill posed. Edge detection is a typical example. This paper applies regularization techniques to the problem of edge detection. We derive an optimal filter for edge detection with a size controlled by the regularization parameter $\\ lambda $ and compare it to the Gaussian filter. A formula relating the signal-to-noise ratio to the parameter $\\lambda $ is derived from regularization analysis for the case of small values of $\\lambda$. We also discuss the method of Generalized Cross Validation for obtaining the optimal filter scale. Finally, we use our framework to explain two perceptual phenomena: coarsely quantized images becoming recognizable by either blurring or adding noise.

How do Humans Determine Reflectance Properties under Unknown Illumination?

Under normal viewing conditions, humans find it easy to distinguish between objects made out of different materials such as plastic, metal, or paper. Untextured materials such as these have different surface reflectance properties, including lightness and gloss. With single isolated images and unknown illumination conditions, the task of estimating surface reflectance is highly underconstrained, because many combinations of reflection and illumination are consistent with a given image. In order to work out how humans estimate surface reflectance properties, we asked subjects to match the appearance of isolated spheres taken out of their original contexts. We found that subjects were able to perform the task accurately and reliably without contextual information to specify the illumination. The spheres were rendered under a variety of artificial illuminations, such as a single point light source, and a number of photographically-captured real-world illuminations from both indoor and outdoor scenes. Subjects performed more accurately for stimuli viewed under real-world patterns of illumination than under artificial illuminations, suggesting that subjects use stored assumptions about the regularities of real-world illuminations to solve the ill-posed problem.

Planning for Conjunctive Goals

The problem of achieving conjunctive goals has been central to domain independent planning research; the nonlinear constraint-posting approach has been most successful. Previous planners of this type have been comlicated, heuristic, and ill-defined. I have combined and distilled the state of the art into a simple, precise, implemented algorithm (TWEAK) which I have proved correct and complete. I analyze previous work on domain-independent conjunctive planning; in retrospect it becomes clear that all conjunctive planners, linear and nonlinear, work the same way. The efficiency of these planners depends on the traditional add/delete-list representation for actions, which drastically limits their usefulness. I present theorems that suggest that efficient general purpose planning with more expressive action representations is impossible, and suggest ways to avoid this problem.

UV Raman spectroscopic study on the synthesis mechanism of zeolite X

The synthesis of zeolite X is characterized by UV Raman spectroscopy, NMR spectroscopy, and X-ray diffraction. UV Raman spectra of the liquid phase of the synthesis system indicate that AI(OH); species are incorporated into silicate species, and the polymeric silicate species are depolymerized into monomeric silicate species during the early stage of zeolite formation. An. intermediate species possessing Raman bands at 307, 503, 858 and 1020 cm(-1) is detected during the crystallization ill the solid phase transformation. The intermediate species is attributed to the beta cage, the secondary building unit of zeolite X. A model for the formation of zeolite X is proposed, which involves four-membered rings connecting to each other via six-membered ring to form beta cages, then the beta cages interconnect via double six-membered rings to form the framework of zeolite X. (C) 2001 Elsevier Science B.V. All rights reserved.

On the correlation between microstructural changes of Ag-H-ZSM-5 catalysts and their catalytic performances in the selective catalytic reduction of NOx by methane

The silver catalyzed, selective catalytic reduction (SCR) of nitrogen oxides (NOx) by CH4, is shown to be a structure-sensitive reaction. Pretreatment has a great affect on the catalytic performances. Upon thermal treatment in inert gas stream, thermal induced changes in silver morphology lead to the formation of reduced silver species of clusters and particles. Catalysis over this catalyst indicates an initially higher activity but lower selectivity for the CH4-SCR of NOx Reaction induced restructuring of silver results in the formation of ill-defined silver oxides. This, in turn, impacts the adsorption properties and diffusivity of oxygen over silver catalyst, results in the decrease in activity but increase in selectivity of Ag-H-ZSM-5 catalyst for the CH4-SCR of NO.. (c) 2004 Elsevier B.V. All rights reserved.

Strategies for surgically assisted rapid maxillary expansion according to the region of transverse maxillary deficiency

This study evaluated different techniques for surgically assisted rapid maxillary expansion (SARME) according to the type of transverse maxillary deficiency using computed tomography (CT). Six adult patients with bilateral transverse maxillary deficiencies underwent SARME. the patients were equally divided into three groups: Group I, maxillary atresia in both the anterior and posterior regions; Group II, greater maxillary atresia in the anterior region; and Group ill, increased maxillary atresia in the posterior region. in Group I, a subtotal Le Fort I osteotomy was used. in Group II, a subtotal Le Fort I osteotomy was used without pterygomaxillary suture disjunction. in Group III, a subtotal Le Fort I osteotomy was used with pterygomaxillary suture disjunction and fixation of the anterior nasal spine with steel wire. the midpalatal suture opening was evaluated preoperatively and immediately after the activation period using CT. for Group I, the opening occurred parallel to midpalatal suture; for Group II, the opening comprised a V-shape with a vertex on the posterior nasal spine; and for Group III, the opening comprised a V-shape with a vertex at the anterior nasal spine. the conclusion was that the SARME technique should be individualized according to the type of transverse maxillary deficiency.

Identification, Selection, and Enrichment of Cardiomyocyte Precursors

The large-scale production of cardiomyocytes is a key step in the development of cell therapy and tissue engineering to treat cardiovascular diseases, particularly those caused by ischemia. the main objective of this study was to establish a procedure for the efficient production of cardiomyocytes by reprogramming mesenchymal stem cells from adipose tissue. First, lentiviral vectors expressing neoR and GFP under the control of promoters expressed specifically during cardiomyogenesis were constructed to monitor cell reprogramming into precardiomyocytes and to select cells for amplification and characterization. Cellular reprogramming was performed using 5'-azacytidine followed by electroporation with plasmid pOKS2a, which expressed Oct4, Sox2, and Klf4. Under these conditions, GFP expression began only after transfection with pOKS2a, and less than 0.015% of cells were GFP(+). These GFP(+) cells were selected for G418 resistance to find molecular markers of cardiomyocytes by RT-PCR and immunocytochemistry. Both genetic and protein markers of cardiomyocytes were present in the selected cells, with some variations among them. Cell doubling time did not change after selection. Together, these results indicate that enrichment with vectors expressing GFP and neoR under cardiomyocyte-specific promoters can produce large numbers of cardiomyocyte precursors (CMPs), which can then be differentiated terminally for cell therapy and tissue engineering.

A dichotomic search algorithm for mining and learning in domain-specific logics

Ferr?, S. and King, R. D. (2004) A dichotomic search algorithm for mining and learning in domain-specific logics. Fundamenta Informaticae. IOS Press. To appear

Towards Fuzzy Compositional Modelling

X. Fu, Q. Shen and R. Zhao. 'Towards fuzzy compositional modelling,' In Proceedings of the 16th International Conference on Fuzzy Systems, 2007, pp. 1233-1238. Sponsorship: EPSRC

Irrelevant or Indispensable? ESDP, the ?War on Terror' and the Fallout from Iraq

Shepherd, Alistair, 'Irrelevant or Indispensable? ESDP, the ?War on Terror' and the Fallout from Iraq', International Politics (2006) 43(1) pp.71-92 RAE2008