Microbial Reduction of Lepidocrocite γ-FeOOH by Shewanella putrefaciens; The Formation of Green Rust

Dissimilatory iron-reducing bacteria (DIRB) couple the oxidation of organic matter or H₂ to the reduction of iron oxides. The bacterial reduction of a most common well-crystallised ferric oxyhydroxide, -FeOOH was investigated using DIRB Shewanella putrefaciens, strain CIP 8040. Experiments were conducted in the presence of neither organic buffer nor phosphate, with formate as electron donor, bicarbonate, and anthraquinone-2,6-disulfonate (AQDS, a humic acid analogue) that influenced the extent of ferric oxide bioreduction. The production of Fe²⁺ was followed with time. The solid phases obtained after bacterial iron reduction were analysed by transmission Mössbauer spectroscopy (TMS) and X-ray diffraction (XRD). Biogenic formation of green rust 1 compound, which contains carbonate anions, [Fe^II ₂Fe^III ₂(OH)₈]²⁺[CO₃ ^2–]^2– was observed. TMS was used to follow the evolution of the green rust abundance during the bacterial culture.     

A design strategy of achievable linear optics for a complex storage ring lattice

A design strategy is discussed in this paper,and it provides much convenience for effectively exploring achievable linear optics and globally investigating the flexibility of a complex lattice with superperiodicity.A matching method of fractional steps,which means separately finding the standard cell setting and the matching cell setting,is adopted to simplify the complexity of the linear beam optics design in the complex lattice.The multi-objective genetic algorithm is used to find most of all the stable linear optics,and reach a target solution after multi-generational propagation,both in the standard cell and the matching cell.A fitting algorithm with gradient information is used to restore the periodicity and symmetry of the lattice,and finely adjust the linear optics for further optimization.This design strategy is applied in the Shanghai Synchrotron Radiation Facility(SSRF)storage ring,and the results are presented.     

Investigation on optimization design of equivalent water depth truncated mooring system

The oil industry is now increasingly concentrating their efforts and activities in connection with developing fields in deeper waters, ranging typically from 500 m to 3000 m worldwide. However, the modeling of a full-depth system has become difficult presently; no tank facility is sufficiently large to perform the testing of a complete FPS with compliant mooring in 1000 m to 3000 m depth, within reasonable limits of model scale. Until recently, the most feasible procedure to meet this challenge seems to be the so-called “hybrid model testing technique”. To implement this technique, the first and important step is to design the equivalent water depth truncated mooring system. In this work, the optimization design of the equivalent water depth truncated mooring system in hybrid model testing for deep sea platforms is investigated. During the research, the similarity of static characteristics between the truncated and full depth system is mainly considered. The optimization mathematical model for the equivalent water depth truncated system design is set up by using the similarity in numerical value of the static characteristics between the truncated system and the full depth one as the objective function. The dynamic characteristic difference between the truncated and full depth mooring system can be minished by selecting proper design rule. To calculate the static characteristics of the mooring system, the fourth order Runge-Kutta method is used to solve the static equilibrium equation of the single mooring line. After the static characteristic of the single mooring line is calculated, the static characteristic of the whole mooring system is calculated with Lagrange numerical interpolation method. The mooring line material database is established and the standard material name and the diameter of the mooring line are selected as the primary key. The improved simulated annealing algorithm for continual & discrete variables and the improved complex algorithm for discrete variables are employed to perform the optimization calculation. The C++ programming language is used to develop the computer program according to the object-oriented programming idea. To perform the optimization calculation with the two algorithms mentioned above respectively and the better result is selected as the final one. To examine the developed program, an example of equivalent water depth truncated mooring system optimum design calculation on a 100,000-t, turret mooring FPSO in water depth of 320 m are performed to obtain the conformation parameters of the truncated mooring system, in which the truncated water depth is 160 m. The model test under some typical environment conditions are performed for both the truncated and the full depth system with model scale factor λ=80. After comparing the corresponding results from the test of the truncated system with those from the full depth system test, it’s found that the truncated mooring system design in this work is successful. Supported by the National Natural Science Foundation of China (Grant Nos. 10602055 and 40776007) and the Natural Science Foundation of China Jiliang University (Grant No. XZ0501)     

Intelligent reversible watermarking technique in medical images using GA and PSO

The advances in recording, editing, and broadcasting multimedia contents in digital form motivate to protect these digital contents from illegal use, such as duplication, manipulation, and redistribution. However, watermarking algorithms are designed to satisfy requirements of applications, as different applications have different concerns. We intend to design a watermarking algorithm for applications which require high embedding capacity and imperceptibility, to maintain the integrity of the host signal as well as embedded information. Reversible watermarking is a promising technique which satisfies our requirements. In this paper, we concentrate on improving the watermark capacity and reducing the perceptual degradation of an image. We investigated the Luo's [1] additive interpolation-error expansion algorithm and enhanced it by incorporating with two intelligent techniques: genetic algorithm (GA), and particle swarm optimization (PSO). Genetic algorithm is applied to exploit the correlation of image pixel values to obtain better estimation of neighboring pixel values, which results in optimal balance between information storage capacity and imperceptibility. Particle swarm optimization (intelligent technique) is also applied for the same purpose. Experimental results show that PSO and GA nearly give the same results, but GA outperforms the PSO. Experimental results also reveal that the proposed strategy outperforms the state of art works in terms of perceptual quality and watermarking payload.     

Synthesis of resonant cavities having continuum spectra by genetic algorithm

This paper proposes a novel method for generating continuum spectra with possible applications in WDM access networks. This new method would allow the development of a simple continuum laser structure with better performances in terms of cost and simplicity than those of present supercontinuum sources. In this aim, we will analyze the possibility to broaden the resonant modes of a Fabry–Perot cavity by operating only on the design of one of the cavity's Bragg mirrors. Firstly we considered the conditions which a Bragg grating must satisfy in order to broaden the resonant modes of a resonant cavity. Because an exact solution is not physical possible, the genetic algorithm is the best available tool for the design of such a grating. An active medium is then added inside the cavity and its behavior below threshold is simulated. The spectra thus simulated are continuum over 5–15 nm.     

货车枕簧丢失故障动态图像识别方法

针对货车运行故障动态图像检测,提出无故障目标识别工作模式,解决货车枕簧丢失故障的自动识别问题。利用Haar特征提取枕簧特征信息,基于AdaBoost算法选取特征并构建层叠分类器,等比缩放搜索窗口检测货车图像,最终分选出无故障的枕簧图像,从而大大地减少了待识别图像的数量,显著地提高了人工识别效率。实验表明,该算法使用的特征简单,搜索策略高效,不受枕簧位置、缩放和旋转的影响,抗噪能力强,对分辨率低、局部遮挡、光照不足或过度曝光等质量较差的图像仍具有很强的适应性,所提出的方案能够满足全天候条件下的货车枕簧目标识别,为货车故障动态图像检测的工程化应用奠定了基础。     

Experimental implementation of a fixed-point duality quantum search algorithm in the nuclear magnetic resonance quantum system

In this work, we demonstrated a fixed-point quantum search algorithm in the nuclear magnetic resonance (NMR) system. We constructed the pulse sequences for the pivotal operations in the quantum search protocol. The experimental results agree well with the theoretical predictions. The generalization of the scheme to the arbitrary number of qubits has also been given.     

Computing the Loewner Driving Process of Random Curves in the Half Plane

We simulate several models of random curves in the half plane and numerically compute the stochastic driving processes that produce the curves through the Loewner equation. Our models include models whose scaling limit is the Schramm-Loewner evolution (SLE) and models for which it is not. We study several tests of whether the driving process is Brownian motion, as it is for SLE. We find that testing only the normality of the process at a fixed time is not effective at determining if the random curves are an SLE. Tests that involve the independence of the increments of Brownian motion are much more effective. We also study the zipper algorithm for numerically computing the driving function of a simple curve. We give an implementation of this algorithm which runs in a time O(N ^1.35) rather than the usual O(N ²), where N is the number of points on the curve.     

Unconstrained and constrained global optimization of polynomial functions in one variable

In Floudas and Visweswaran (1990), a new global optimization algorithm (GOP) was proposed for solving constrained nonconvex problems involving quadratic and polynomial functions in the objective function and/or constraints. In this paper, the application of this algorithm to the special case of polynomial functions of one variable is discussed. The special nature of polynomial functions enables considerable simplification of the GOP algorithm. The primal problem is shown to reduce to a simple function evaluation, while the relaxed dual problem is equivalent to the simultaneous solution of two linear equations in two variables. In addition, the one-to-one correspondence between the x and y variables in the problem enables the iterative improvement of the bounds used in the relaxed dual problem. The simplified approach is illustrated through a simple example that shows the significant improvement in the underestimating function obtained from the application of the modified algorithm. The application of the algorithm to several unconstrained and constrained polynomial function problems is demonstrated.     

Dynamic Global Constraints in Backtracking Based Environments

Global constraints provide strong filtering algorithms to reduce the search space when solving large combinatorial problems. In this paper we propose to make the global constraints dynamic, i.e., to allow extending the set of constrained variables during search. We describe a generic dynamisation technique for an arbitrary monotonic global constraint and we compare it with the semantic-based dynamisation for the alldifferent constraint. At the end we sketch a dynamisation technique for non-monotonic global constraints. A comparison with existing methods to model dynamic problems is given as well.