REGULATION OF PRODUCTION OF PARATHYROID HORMONE－RELATED PEPTIDE （PTHrP） AND EXPRESSION OF ITS mRNA IN A HUMANLIVER－DERIVED CE

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Seabed scene simulation and its realization in extending Vega

Realistic simulation of underwater scene is always difficult because of the special and complex vision effects in underwater space. Seabed is an important part of underwater environment. This paper describes the methods for seabed scene simulation based on OpenGL. It includes construction of fluetuant terrain based on the random sinusoidal algorithm, simulation of seabed flicker effect by means of circular texture mapping and generation of turbidity effect by using fog techniques. For the application based on the leading high level 3D development environment-Vega, underwater scene simulation is still a difficulty since there is no module for it. Based on the analysis of Vega software and the research on seabed scene simulation methods, a Vega extending module named “Underwater Space” was created through developing module class and extending lynx interface. The module class was designed through developing DLL written in C . The Lynx was extended through developing keyword configure file, GUI configure file and lynx plug-in DLL. The problem that Vega can‘t simulate underwater space, is elementarily resolved. The results show that this module is efficient, easy using, and the seabed scene images am vivid.     

Identity-based threshold decryption on access structure

For the applied limitation of the existing threshold decryption schemes based on the (t, n) structure, an identity-based threshold decryption scheme which can be applied on the access structure is proposed through designing a special distribution algorithm of the private key shares. The generation and distribution of private key shares, the encryption, the decryption and the combination are introduced in detail. The validity and security of the scheme are proved and analyzed. Comparisons with the existing schemes show that the proposed scheme is more flexible.     

Tool sequence optimization based on three logical modes of robot control via CPLEX optimization

Cluster tools have advantages of shorter cycle times, faster process development, and better yield for less contamination. The sequence of dual-arm cluster tools is a complex logistics process during the semiconductor production. Efficient use of cluster tools is naturally very significant to competitive fab operations. Generating an optimized sequence in a computationally efficient manner and assessing the quality of the requirements to improve the fab production are the key factors for semiconductor manufacturing productivity. The Petri net modeling is introduced to minimize the makespan of the process for the three different logical modes and select a better mode after comparing the makespan among the three logical modes. The tool sequence optimization problem is formulated as optimization firing transition sequences based on the Petri net and then the formulation is converted to be linearly solved by the branch-and-cut method in the standard commercial solver CPLEX. Special methods for the linear conversion are highlighted. Due to the limited calculation time requirement for the real production and the large scale of the problem, special methods for the efficiency tuning are applied according to the characteristics of the problem. Numerical testing is supported by one of the most advanced semiconductor enterprises and the computational results show significant improvement compared with the traditional manual sequence results.     

Poisson noise removal based on nonlocal total variation with Euler’s elastica pre-processing

An enhancement-based Poisson denoising method for photon-limited images is presented. The noisy image is firstly pre-processed for enhancing incomplete object information, and then it is denoised while preserving the restored structural details. A variational regularization model based on Euler’s elastica (EE) is proposed for image enhancement pre-processing. A nonlocal total variation (NLTV) regularization model is then employed in the second stage of image denoising. The above two optimization problems are solved by the alternating direction method of multipliers (ADMM). For Poissonian images with low image peak values, experiments demonstrate the validity and efficiency of the proposed method for both restoring geometric structure and removing noise.     

Inventory,Classification, and Analysis of Special Management Areas Associated with U.S. Coastal Programs

Area-based management approaches may be beneficial in integrating sectoral, single-purpose laws and regulations; however, these benefits may not be attained if special area designations are equally sectoral or single-purpose in nature. Over 60 types of special management areas were documented under U.S. coastal programs, and a new classification scheme was developed to allow comparisons and analyses across programs. Results indicate that requirements and incentives for special area designations under the Coastal Zone Management Act did little to standardize or influence area-based management systems associated with state and territory coastal programs. Further, the absence of clear patterns within and between coastal programs with respect to special area policies suggests a limited commitment to this important aspect of coastal management. Continued research is needed to document the effectiveness of the various area-based management approaches presented in this article.     

Semiparametric specification of the utility function in a travel mode choice model

We propose a semiparametric approach that can capture the nonlinearity of deterministic components of the utility functions in discrete choice models and demonstrate it by analyzing travel mode choice behaviour for an interregional trip. The proposed smoothing spline-based specification method can be used to make ex ante evaluations regarding the parametric specifications of the deterministic utility functions in discrete choice models.