Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Expression Pattern of the Alpha-Kafirin Promoter Coupled with a Signal Peptide from Sorghum bicolor L. Moench

Regulatory sequences with endosperm specificity are essential for foreign gene expression in the desired tissue for both grain quality improvement and molecular pharming. In this study, promoters of seed storage α-kafirin genes coupled with signal sequence (ss) were isolated from Sorghum bicolor L. Moench genomic DNA by PCR. The α-kafirin promoter (α-kaf) contains endosperm specificity-determining motifs, prolamin-box, the O2-box 1, CATC, and TATA boxes required for α-kafirin gene expression in sorghum seeds. The constructs pMB-Ubi-gfp and pMB-kaf-gfp were microprojectile bombarded into various sorghum and sweet corn explants. GFP expression was detected on all explants using the Ubi promoter but only in seeds for the α-kaf promoter. This shows that the α-kaf promoter isolated was functional and demonstrated seed-specific GFP expression. The constructs pMB-Ubi-ss-gfp and pMB-kaf-ss-gfp were also bombarded into the same explants. Detection of GFP expression showed that the signal peptide (SP)::GFP fusion can assemble and fold properly, preserving the fluorescent properties of GFP.

Preliminary characterisation of tumor necrosis factor alpha and interleukin-10 responses to chlamydia pecorum infection in the koala (Phascolarctos cinereus)

Debilitating infectious diseases caused by Chlamydia are major contributors to the decline of Australia's iconic native marsupial species, the koala (Phascolarctos cinereus). An understanding of koala chlamydial disease pathogenesis and the development of effective strategies to control infections continue to be hindered by an almost complete lack of species-specific immunological reagents. The cell-mediated immune response has been shown to play an influential role in the response to chlamydial infection in other hosts. The objective of this study, hence, was to provide preliminary data on the role of two key cytokines, pro-inflammatory tumour necrosis factor alpha (TNFα) and anti-inflammatory interleukin 10 (IL10), in the koala Chlamydia pecorum response. Utilising sequence homology between the cytokine sequences obtained from several recently sequenced marsupial genomes, this report describes the first mRNA sequences of any koala cytokine and the development of koala specific TNFα and IL10 real-time PCR assays to measure the expression of these genes from koala samples. In preliminary studies comparing wild koalas with overt chlamydial disease, previous evidence of C. pecorum infection or no signs of C. pecorum infection, we revealed strong but variable expression of TNFα and IL10 in wild koalas with current signs of chlamydiosis. The description of these assays and the preliminary data on the cell-mediated immune response of koalas to chlamydial infection paves the way for future studies characterising the koala immune response to a range of its pathogens while providing reagents to assist with measuring the efficacy of ongoing attempts to develop a koala chlamydial vaccine.

TNF and TNF receptor expression and insulin sensitivity in human omental and subcutaneous adipose tissue--influence of BMI and adipose distribution

Tumour necrosis factor (TNF)alpha is implicated in the relationship between obesity and insulin resistance/ type 2 diabetes. In an effort to understand this association better we (i) profiled gene expression patterns of TNF, TNFR1 and TNFR2 and (ii) investigated the effects of TNF on glucose uptake in isolated adipocytes and adipose tissue explants from omental and subcutaneous depots from lean, overweight and obese individuals. TNF expression correlated with expression of TNFR2, but not TNFR1, and TNF and TNFR2 expression increased in obesity. TNFR1 expression was higher in omental than in subcutaneous adipocytes. Expression levels of TNF or either receptor did not differ between adipocytes from individuals with central and peripheral obesity. TNF only suppressed glucose uptake in insulin-stimulated subcutaneous tissue and this suppression was only observed in tissue from lean subjects. These data support a relationship between the TNF system and body mass index (BMI), but not fat distribution, and suggest depot specificity of the TNF effect on glucose uptake. Furthermore, adipose tissue from obese subjects already appears insulin 'resistant' and this may be a result of the increased TNF levels.

Letter Reply: Distribution of TNFA haplotypes in healthy Caucasians: Comment on the articles by Newton et al and Zeggini et al

We thank Ploski and colleagues for their interest in our study. The explanation for the difference in our findings is a typographic error in Table 2 of our article, whereby the alleles for marker TNF ⫺1031 were labeled incorrectly...

Spatial distribution of selected persistent organic pollutants (POPs) in Australia's atmosphere

A nation-wide passive air sampling campaign recorded concentrations of persistent organic pollutants in Australia's atmosphere in 2012. XAD-based passive air samplers were deployed for one year at 15 sampling sites located in remote/background, agricultural and semi-urban and urban areas across the continent. Concentrations of 47 polychlorinated biphenyls ranged from 0.73 to 72 pg m-3 (median of 8.9 pg m-3) and were consistently higher at urban sites. The toxic equivalent concentration for the sum of 12 dioxin-like PCBs was low, ranging from below detection limits to 0.24 fg m-3 (median of 0.0086 fg m-3). Overall, the levels of polychlorinated biphenyls in Australia were among the lowest reported globally to date. Among the organochlorine pesticides, hexachlorobenzene had the highest (median of 41 pg m-3) and most uniform concentration (with a ratio between highest and lowest value [similar]5). Bushfires may be responsible for atmospheric hexachlorobenzene levels in Australia that exceeded Southern Hemispheric baseline levels by a factor of [similar]4. Organochlorine pesticide concentrations generally increased from remote/background and agricultural sites to urban sites, except for high concentrations of [small alpha]-endosulfan and DDTs at specific agricultural sites. Concentrations of heptachlor (0.47-210 pg m-3), dieldrin (ND-160 pg m-3) and trans- and cis-chlordanes (0.83-180 pg m-3, sum of) in Australian air were among the highest reported globally to date, whereas those of DDT and its metabolites (ND-160 pg m-3, sum of), [small alpha]-, [small beta]-, [gamma]- and [small delta]-hexachlorocyclohexane (ND-6.7 pg m-3, sum of) and [small alpha]-endosulfan (ND-27 pg m-3) were among the lowest.