A general model of error-prone PCR

In this paper, we generalise a previously-described model of the error-prone polymerase chain reaction (PCR) reaction to conditions of arbitrarily variable amplification efficiency and initial population size. Generalisation of the model to these conditions improves the correspondence to observed and expected behaviours of PCR, and restricts the extent to which the model may explore sequence space for a prescribed set of parameters. Error-prone PCR in realistic reaction conditions is predicted to be less effective at generating grossly divergent sequences than the original model. The estimate of mutation rate per cycle by sampling sequences from an in vitro PCR experiment is correspondingly affected by the choice of model and parameters. (c) 2005 Elsevier Ltd. All rights reserved.

A dual QPSK soft-demapper for multiband OFDM exploiting time-domain spreading and guard interval diversity

When considering the relative fast processing speeds and low power requirements for Wireless Personal Area Networks (WPAN) including Wireless Universal Serial Bus (WUSB) consumer based products, then the efficiency and cost effectiveness of these products become paramount. This paper presents an improved soft-output QPSK demapper suitable for the products above that not only exploits time diversity and guard carrier diversity, but also merges the demapping and symbol combining functions together to minimize CPU cycles, or memory access dependant upon the chosen implementation architecture. The proposed demapper is presented in the context of Multiband OFDM version of Ultra Wideband (UWB) (ECMA-368) as the chosen physical implementation for high-rate Wireless US8(1).

Insights into redox cycling of sulfur and iron in peatlands using high-resolution diffusive equilibrium thin film (DET) gel probe sampling

High spatial resolution vertical profiles of pore-water chemistry have been obtained for a peatland using diffusive equilibrium in thin films (DET) gel probes. Comparison of DET pore-water data with more traditional depth-specific sampling shows good agreement and the DET profiling method is less invasive and less likely to induce mixing of pore-waters. Chloride mass balances as water tables fell in the early summer indicate that evaporative concentration dominates and there is negligible lateral flow in the peat. Lack of lateral flow allows element budgets for the same site at different times to be compared. The high spatial resolution of sampling also enables gradients to be observed that permit calculations of vertical fluxes. Sulfate concentrations fall at two sites with net rates of 1.5 and 5.0nmol cm− 3 day− 1, likely due to a dominance of bacterial sulfate reduction, while a third site showed a net gain in sulfate due to oxidation of sulfur over the study period at an average rate of 3.4nmol cm− 3 day− 1. Behaviour of iron is closely coupled to that of sulfur; there is net removal of iron at the two sites where sulfate reduction dominates and addition of iron where oxidation dominates. The profiles demonstrate that, in addition to strong vertical redox related chemical changes, there is significant spatial heterogeneity. Whilst overall there is evidence for net reduction of sulfate within the peatland pore-waters, this can be reversed, at least temporarily, during periods of drought when sulfide oxidation with resulting acid production predominates.

An efficient shock capturing algorithm for compressible flows in a duct of variable cross-section

A numerical scheme is presented for the solution of the Euler equations of compressible flow of a gas in a single spatial co-ordinate. This includes flow in a duct of variable cross-section as well as flow with slab, cylindrical or spherical symmetry and can prove useful when testing codes for the two-dimensional equations governing compressible flow of a gas. The resulting scheme requires an average of the flow variables across the interface between cells and for computational efficiency this average is chosen to be the arithmetic mean, which is in contrast to the usual ‘square root’ averages found in this type of scheme. The scheme is applied with success to five problems with either slab or cylindrical symmetry and a comparison is made in the cylindrical case with results from a two-dimensional problem with no sources.

Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks

An input variable selection procedure is introduced for the identification and construction of multi-input multi-output (MIMO) neurofuzzy operating point dependent models. The algorithm is an extension of a forward modified Gram-Schmidt orthogonal least squares procedure for a linear model structure which is modified to accommodate nonlinear system modeling by incorporating piecewise locally linear model fitting. The proposed input nodes selection procedure effectively tackles the problem of the curse of dimensionality associated with lattice-based modeling algorithms such as radial basis function neurofuzzy networks, enabling the resulting neurofuzzy operating point dependent model to be widely applied in control and estimation. Some numerical examples are given to demonstrate the effectiveness of the proposed construction algorithm.

An LMS style variable tap-length algorithm for structure adaptation

Searching for the optimum tap-length that best balances the complexity and steady-state performance of an adaptive filter has attracted attention recently. Among existing algorithms that can be found in the literature, two of which, namely the segmented filter (SF) and gradient descent (GD) algorithms, are of particular interest as they can search for the optimum tap-length quickly. In this paper, at first, we carefully compare the SF and GD algorithms and show that the two algorithms are equivalent in performance under some constraints, but each has advantages/disadvantages relative to the other. Then, we propose an improved variable tap-length algorithm using the concept of the pseudo fractional tap-length (FT). Updating the tap-length with instantaneous errors in a style similar to that used in the stochastic gradient [or least mean squares (LMS)] algorithm, the proposed FT algorithm not only retains the advantages from both the SF and the GD algorithms but also has significantly less complexity than existing algorithms. Both performance analysis and numerical simulations are given to verify the new proposed algorithm.

Variable selection for financial distress classification using a genetic algorithm

This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature.

Variable step-size LMS blind CDMA multiuser detectors

Adaptive least mean square (LMS) filters with or without training sequences, which are known as training-based and blind detectors respectively, have been formulated to counter interference in CDMA systems. The convergence characteristics of these two LMS detectors are analyzed and compared in this paper. We show that the blind detector is superior to the training-based detector with respect to convergence rate. On the other hand, the training-based detector performs better in the steady state, giving a lower excess mean-square error (MSE) for a given adaptation step size. A novel decision-directed LMS detector which achieves the low excess MSE of the training-based detector and the superior convergence performance of the blind detector is proposed.

Análise de dados coletados por respondent-driven sampling(RDS): um estudo da prevalência de HIV e fatores associados entre mulheres trabalhadoras do sexo em 10 cidades brasileiras

O grupo das mulheres trabalhadoras do sexo (MTS) é reconhecido como uma populaçãode maior risco à infecção pelo HIV, tanto pela prevalência elevada, como por suavulnerabilidade social como pelos fatores relacionados à própria atividade profissional. Porém, arealização de estudos nos subgrupos de maior risco ao HIV mediante estratégias convencionaisde amostragem é, em geral, problemática por essas populações possuírem pequena magnitudeem termos populacionais e por estarem vinculados a comportamentos estigmatizados ouatividades ilegais. Em 1997, foi proposto um método de amostragem probabilística parapopulações de difícil acesso denominado Respondent-Driven Sampling (RDS). O método éconsiderado como uma variante da amostragem em cadeia e possibilita a estimação estatísticados parâmetros de interesse. Na literatura internacional, para análise de dados coletados porRDS, muitos autores têm utilizado técnicas estatísticas multivariadas tradicionais, sem levar emconta a estrutura de dependência das observações, presente nos dados coletados por RDS.A presente tese tem por objetivo contribuir para suprir informações sobre as práticas derisco relacionadas ao HIV entre as mulheres trabalhadoras do sexo (MTS) com odesenvolvimento de método estatístico para análise de dados coletados com o método deamostragem RDS. Com tal finalidade, foram utilizadas as informações coletadas na PesquisaCorrente da Saúde realizada em dez cidades brasileiras, com 2.523 MTS recrutadas por RDS,entre os anos de 2008 e 2009. O questionário foi autopreenchido e incluiu módulos sobrecaracterísticas da atividade profissional, práticas sexuais, uso de drogas, testes periódicos deHIV, e acesso aos serviços de saúde.Primeiramente, foram descritos alguns pressupostos do RDS e todas as etapas deimplantação da pesquisa. Em seguida, foram propostos métodos de análise multivariada, considerando o RDS como um desenho complexo de amostragem.