Performance Analysis of Dual Unipolar/Bipolar Spectral Code in Optical CDMA Systems

This study analyzes and calculates dual unipolar and bipolar coded configurations of spectral-amplitude-coding opticalcode division multiple access (SAC-OCDMA) systems by using simulation methods. The important feature of theSAC-OCDMA systems is that multiple access interference (MAI) can be eliminated by code sequences of a fixed inphasecross-correlation value. This property can be effectively canceled multiple access interference by using balancedetection schemes. This study uses Walsh-Hadamard codes as signature codes for the unipolar and bipolar schemes.The coder and decoder structures are based on optical filters of fiber Bragg gratings (FBGs). The simulation results ofunipolar/bipolar coding structures are first presented by commercial simulation obtained using OptiSystem software.The simulation results show that the bit error rate (BER) through use of the bipolar coding method is superior to theunipolar scheme, especially when the received effect power is large. When the system needs good performance totransmit multimedia data, we can use bipolar scheme in the network. If the users only transmit voice data, the unipolarmethod can be employed. The eye diagram also shows that the bipolar encoding structure exhibits a wider openingthan the unipolar encoding structure. The flexible implementation of codewords assigns and integratable hardwaredesigns for the scheme with FBGs to realize dual coding OCDMA system is proposed

Modelling the outbreak of infectious disease following mutation from a non-transmissible strain

In-host mutation of a cross-species infectious disease to a form that is transmissible between humans has resulted with devastating global pandemics in the past. We use simple mathematical models to describe this process with the aim to better understand the emergence of an epidemic resulting from such a mutation and the extent of measures that are needed to control it. The feared outbreak of a human–human transmissible form of avian influenza leading to a global epidemic is the paradigm for this study. We extend the SIR approach to derive a deterministic and a stochastic formulation to describe the evolution of two classes of susceptible and infected states and a removed state, leading to a system of ordinary differential equations and a stochastic equivalent based on a Markov process. For the deterministic model, the contrasting timescale of the mutation process and disease infectiousness is exploited in two limits using asymptotic analysis in order to determine, in terms of the model parameters, necessary conditions for an epidemic to take place and timescales for the onset of the epidemic, the size and duration of the epidemic and the maximum level of the infected individuals at one time. Furthermore, the basic reproduction number is determined from asymptotic analysis of a distinguished limit. Comparisons between the deterministic and stochastic model demonstrate that stochasticity has little effect on most aspects of an epidemic, but does have significant impact on its onset particularly for smaller populations and lower mutation rates for representatively large populations. The deterministic model is extended to investigate a range of quarantine and vaccination programmes, whereby in the two asymptotic limits analysed, quantitative estimates on the outcomes and effectiveness of these control measures are established

Optimal modelling and experimentation for the improved sustainability of microfluidic chemical technology design

Optimization of the dynamics and control of chemical processes holds the promise of improved sustainability for chemical technology by minimizing resource wastage. Anecdotally, chemical plant may be substantially over designed, say by 35-50%, due to designers taking account of uncertainties by providing greater flexibility. Once the plant is commissioned, techniques of nonlinear dynamics analysis can be used by process systems engineers to recoup some of this overdesign by optimization of the plant operation through tighter control. At the design stage, coupling the experimentation with data assimilation into the model, whilst using the partially informed, semi-empirical model to predict from parametric sensitivity studies which experiments to run should optimally improve the model. This approach has been demonstrated for optimal experimentation, but limited to a differential algebraic model of the process. Typically, such models for online monitoring have been limited to low dimensions. Recently it has been demonstrated that inverse methods such as data assimilation can be applied to PDE systems with algebraic constraints, a substantially more complicated parameter estimation using finite element multiphysics modelling. Parametric sensitivity can be used from such semi-empirical models to predict the optimum placement of sensors to be used to collect data that optimally informs the model for a microfluidic sensor system. This coupled optimum modelling and experiment procedure is ambitious in the scale of the modelling problem, as well as in the scale of the application - a microfluidic device. In general, microfluidic devices are sufficiently easy to fabricate, control, and monitor that they form an ideal platform for developing high dimensional spatio-temporal models for simultaneously coupling with experimentation. As chemical microreactors already promise low raw materials wastage through tight control of reagent contacting, improved design techniques should be able to augment optimal control systems to achieve very low resource wastage. In this paper, we discuss how the paradigm for optimal modelling and experimentation should be developed and foreshadow the exploitation of this methodology for the development of chemical microreactors and microfluidic sensors for online monitoring of chemical processes. Improvement in both of these areas bodes to improve the sustainability of chemical processes through innovative technology. (C) 2008 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved

Exploiting Evolution for an Adaptive Drift-Robust Classifier in Chemical Sensing

Gas chemical sensors are strongly affected by drift, i.e., changes in sensors' response with time, that may turn statistical models commonly used for classification completely useless after a period of time. This paper presents a new classifier that embeds an adaptive stage able to reduce drift effects. The proposed system exploits a state-of-the-art evolutionary strategy to iteratively tweak the coefficients of a linear transformation able to transparently transform raw measures in order to mitigate the negative effects of the drift. The system operates continuously. The optimal correction strategy is learnt without a-priori models or other hypothesis on the behavior of physical-chemical sensors. Experimental results demonstrate the efficacy of the approach on a real problem

Speciation controls on Ni adsorption to birnessite and organo-birnessite

Nickel (Ni) is an essential micronutrient for phytoplankton. Its importance to both the modern and ancient Earth system has encouraged development of Ni and its isotopes as biogeochemical tracers. To interpret these signatures however, understanding of how Ni and its isotopes are recorded in marine archives is required. Here we simulate different inorganic and organic Ni species in seawater and investigate their adsorption behaviours to variably crystalline phyllomanganates and organo-mineral phyllomanganate. We conduct pH adsorption edge experiments to determine the binding affinity of the different Ni species to the minerals and then perform desorption experiments to operationally define Ni bonding strength. We also use thermodynamic surface complexation modelling to constrain Ni adsorption mechanisms. From the adsorption edges and stability constants generated from our modelling, the binding affinity increases in the order of Ni-formate+ (aq) NiCl+ (aq) ∼ Ni2+ (aq). For the organo-mineral however, Ni desorption at pH 8 is non quantitative and similar for all three experiments, and is significantly higher compared to the variably crystalline phyllomanganates. Although both our adsorption and desorption experiments were performed over 48 h, it is possible that desorption is somewhat slower than adsorption such that a longer desorption period may result in further Ni loss to solution and thus greater adsorption reversibility. Taken together however, the Ni-formate+ (aq) and Ni organo-birnessite desorption experiments suggest that Ni bonding strength is decreased by the presence of organic carbon, compared to NiCl+ (aq) and Ni2+ (aq). Because bonding strength governs equilibrium stable isotope fractionation, we use our experimental findings to suggest how Ni speciation in seawater might influence Ni isotope behaviour during adsorption to phyllomanganate. We find that our suggestions are consistent with isotopic measurements from natural sediments. Although the balance of Ni adsorption versus incorporation during uptake to phyllomanganates may play a greater part in explaining the variation in the Ni isotope composition in Mn-rich sediments, Ni speciation and the presence of organics might increase the range of δ60Ni values measured in natural settings

Hidden symmetry of the three-dimensional Einstein-Maxwell equations

It is shown how to generate three-dimensional Einstein-Maxwell fields from known ones in the presence of a hypersurface-orthogonal non-null Killing vector field. The continuous symmetry group is isomorphic to the Heisenberg group including the Harrison-type transformation. The symmetry of the Einstein-Maxwell-dilaton system is also studied and it is shown that there is the $SL(2,{\bf R})$ transformation between the Maxwell and the dilaton fields. This $SL(2,{\bf R})$ transformation is identified with the Geroch transformation of the four-dimensional vacuum Einstein equation in terms of the Ka{\l}uza-Klein mechanism.Comment: 5 page

Structural, Magnetic and Transport Properties of B-Site Substituted Perovskite La0.7Sr0.3MnO3

In this chapter, in order to understand the structural related magnetic and transport properties of B site substituted perovskites La0.7Sr0.3MnO3 (LSMO), we have systematically investigated the effects of replacing some of the Mn with nonmagnetic elements Ti, Zr, Cu, Al, Zn and magnetic elements Co, Ni, Cr, Fe. The structural, magnetic and electrical phase transitions and transport properties of these compounds were investigated by neutron diffraction, magnetization and electric resistivity measurements

Variational Approximations in a Path-Integral Description of Potential Scattering

Using a recent path integral representation for the T-matrix in nonrelativistic potential scattering we investigate new variational approximations in this framework. By means of the Feynman-Jensen variational principle and the most general ansatz quadratic in the velocity variables -- over which one has to integrate functionally -- we obtain variational equations which contain classical elements (trajectories) as well as quantum-mechanical ones (wave spreading).We analyse these equations and solve them numerically by iteration, a procedure best suited at high energy. The first correction to the variational result arising from a cumulant expansion is also evaluated. Comparison is made with exact partial-wave results for scattering from a Gaussian potential and better agreement is found at large scattering angles where the standard eikonal-type approximations fail.Comment: 35 pages, 3 figures, 6 tables, Latex with amsmath, amssymb; v2: 28 pages, EPJ style, misprints corrected, note added about correct treatment of complex Gaussian integrals with the theory of "pencils", matches published versio