Fitting host-parasitoid models with CV² > 1 using hierarchical generalized linear models

The powerful general Pacala-Hassell host-parasitoid model for a patchy environment, which allows host density–dependent heterogeneity (HDD) to be distinguished from between-patch, host density–independent heterogeneity (HDI), is reformulated within the class of the generalized linear model (GLM) family. This improves accessibility through the provision of general software within well–known statistical systems, and allows a rich variety of models to be formulated. Covariates such as age class, host density and abiotic factors may be included easily. For the case where there is no HDI, the formulation is a simple GLM. When there is HDI in addition to HDD, the formulation is a hierarchical generalized linear model. Two forms of HDI model are considered, both with between-patch variability: one has binomial variation within patches and one has extra-binomial, overdispersed variation within patches. Examples are given demonstrating parameter estimation with standard errors, and hypothesis testing. For one example given, the extra-binomial component of the HDI heterogeneity in parasitism is itself shown to be strongly density dependent.

Maximum-likelihood estimator for coarse carrier frequency offset estimation in OFDM systems

Orthogonal frequency division multiplexing (OFDM) systems are more sensitive to carrier frequency offset (CFO) compared to the conventional single carrier systems. CFO destroys the orthogonality among subcarriers, resulting in inter-carrier interference (ICI) and degrading system performance. To mitigate the effect of the CFO, it has to be estimated and compensated before the demodulation. The CFO can be divided into an integer part and a fractional part. In this paper, we investigate a maximum-likelihood estimator (MLE) for estimating the integer part of the CFO in OFDM systems, which requires only one OFDM block as the pilot symbols. To reduce the computational complexity of the MLE and improve the bandwidth efficiency, a suboptimum estimator (Sub MLE) is studied. Based on the hypothesis testing method, a threshold Sub MLE (T-Sub MLE) is proposed to further reduce the computational complexity. The performance analysis of the proposed T-Sub MLE is obtained and the analytical results match the simulation results well. Numerical results show that the proposed estimators are effective and reliable in both additive white Gaussian noise (AWGN) and frequency-selective fading channels in OFDM systems.

Polyunsaturated fatty acids in the pathogenesis and treatment of multiple sclerosis

Epidemiological, biochemical, animal model and clinical trial data described in this overview strongly suggest that polyunsaturated fatty acids, particularly n-6 fatty acids, have a role in the pathogenesis and treatment of multiple sclerosis (MS). Data presented provides further evidence for a disturbance in n-6 fatty acid metabolism in MS. Disturbance of n-6 fatty acid metabolism and dysregulation of cytokines are shown to be linked and a "proof of concept clinical trial" further supports such a hypothesis. In a randomised double-blind, placebo controlled trial of a high dose and low dose selected GLA (18:3n-6)-rich oil and placebo control, the high dose had a marked clinical effect in relapsing-remitting MS, significantly decreasing the relapse rate and the progression of disease. Laboratory findings paralleled clinical changes in the placebo group in that production of mononuclear cell pro-inflammatory cytokines (TNF-alpha, IL-1 beta) was increased and anti-inflammatory TGF-beta markedly decreased with loss of membrane n-6 fatty acids linoleic (18:2n-6) and arachidonic acids (20:4n-6). In contrast there were no such changes in the high dose group. The improvement in disability (Expanded Disability Status Scale) in the high dose suggests there maybe a beneficial effect on neuronal lipids and neural function in MS. Thus disturbed n-6 fatty acid metabolism in MS gives rise to loss of membrane long chain n-6 fatty acids and loss of the anti-inflammatory regulatory cytokine TGF-beta, particularly during the relapse phase, as well as loss of these important neural fatty acids for CNS structure and function and consequent long term neurological deficit in MS.