The distribution and spread of citrus canker in Emerald, Australia

Citrus canker is a disease of citrus and closely related species, caused by the bacterium Xanthomonas citri subsp. citri. This disease, previously exotic to Australia, was detected on a single farm [infested premise-1, (IP1). IP is the terminology used in official biosecurity protocols to describe a locality at which an exotic plant pest has been confirmed or is presumed to exist. IP are numbered sequentially as they are detected] in Emerald, Queensland in July 2004. During the following 10 months the disease was subsequently detected on two other farms (IP2 and IP3) within the same area and studies indicated the disease first occurred on IP1 and spread to IP2 and IP3. The oldest, naturally infected plant tissue observed on any of these farms indicated the disease was present on IP1 for several months before detection and established on IP2 and IP3 during the second quarter (i.e. autumn) 2004. Transect studies on some IP1 blocks showed disease incidences ranged between 52 and 100% (trees infected). This contrasted to very low disease incidence, less than 4% of trees within a block, on IP2 and IP3. The mechanisms proposed for disease spread within blocks include weather-assisted dispersal of the bacterium (e.g. wind-driven rain) and movement of contaminated farm equipment, in particular by pivot irrigator towers via mechanical damage in combination with abundant water. Spread between blocks on IP2 was attributed to movement of contaminated farm equipment and/or people. Epidemiology results suggest: (i) successive surveillance rounds increase the likelihood of disease detection; (ii) surveillance sensitivity is affected by tree size; and (iii) individual destruction zones (for the purpose of eradication) could be determined using disease incidence and severity data rather than a predefined set area.

Kava Anxiety Depression Spectrum Study (KADSS): a mixed methods RCT using an aqueous extract of Piper methysticum

Objectives: To report on the design, significance and potential impacts of the first documented human clinical trial assessing the anxiolytic and thymoleptic efficacy of an aqueous monoextract of Piper methysticum (kava). The significance of the qualitative element of our clinical trial is also explored. The Kava Anxiety Depression Spectrum Study (KADSS) is a 3-week placebocontrolled, double-blind, cross-over trial involving 60 adult participants (18—65) with elevated stable anxiety and varying levels of depressive symptoms. Aims: The aims of KADSS are: (1) to determine whether an aqueous standardised extract of kava is effective for the treatment of anxiety; (2) to assess the effects of kava on differing levels of depression; and (3) to explore participants’ experience of taking kava via qualitative research. The study also provides preliminary assessment of the safety of an aqueous extract of kava in humans. Conclusion: If results reveal that the aqueous kava preparation exerts significant anxiolytic effects and appears safe, potentially beneficial impacts may occur. Data supporting a safe and effective kava extract may encourage a re-introduction of kava to Europe, UK and Canada. This may provide a major socioeconomic benefit to Pacific Island nations, and to sufferers of anxiety disorders.

The Kava Anxiety Depression Spectrum Study (KADSS): A randomized, placebo-controlled, cross-over trial using an aqueous extract of Piper methysticum.

Rationale: Piper methysticum (Kava) has been withdrawn in European, British, and Canadian markets due to concerns over hepatotoxic reactions. The WHO recently recommended research into “aqueous” extracts of Kava. Objective: The objective of this study was to conduct the first documented human clinical trial assessing the anxiolytic and antidepressant efficacy of an aqueous extract of Kava. Design and participants: The Kava Anxiety Depression Spectrum Study was a 3-week placebo-controlled, double-blind crossover trial that recruited 60 adult participants with 1 month or more of elevated generalized anxiety. Five Kava tablets per day were prescribed containing 250 mg of kavalactones/day. Results: The aqueous extract of Kava reduced participants' Hamilton Anxiety Scale score in the first controlled phase by −9.9 (CI = 7.1, 12.7) vs. −0.8 (CI = −2.7, 4.3) for placebo and in the second controlled phase by −10.3 (CI = 5.8, 14.7) vs. +3.3 (CI = −6.8, 0.2). The pooled effect of Kava vs. placebo across phases was highly significant (p < 0.0001), with a substantial effect size (d = 2.24, η² [sub]p[sub] = 0.428). Pooled analyses also revealed highly significant relative reductions in Beck Anxiety Inventory and Montgomery–Asberg Depression Rating Scale scores. The aqueous extract was found to be safe, with no serious adverse effects and no clinical hepatotoxicity. Conclusions: The aqueous Kava preparation produced significant anxiolytic and antidepressant activity and raised no safety concerns at the dose and duration studied. Kava appears equally effective in cases where anxiety is accompanied by depression. This should encourage further study and consideration of globally reintroducing aqueous rootstock extracts of Kava for the management of anxiety.

Developing the descriptions of landmark teaching styles : a spectrum inventory

Mosston & Ashworth‟s Spectrum of Teaching styles was first published in 1966 and is potentially the longest surviving model of teaching within the field of physical education. Its longevity and influence is surely testament to its value and influence. Many tools have also been developed through the years based on The Spectrum of Teaching Styles. In 2005 as part of a doctoral study, this tool was developed by the author, Dr Edwards and Dr Ashworth for researchers and teachers to identify which teaching styles were being utilised from The Spectrum when teaching physical education. It could also be utilised for self-assessment of the teaching styles and individual uses, or those who work with Physical Education Teacher Education courses. The development of this tool took approximately 4 months, numerous emails and meetings. This presentation will outline this process, along with the reasons why such a tool was developed and the differences between it and others like it.

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.

The use of phase in complex spectrum subtraction for robust speech recognition

In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

Gender inequality and the spread of HIV-AIDS in India

Purpose The purpose of the paper is to analyze the low status of women as being a major contributor for the observed gender inequality in the spread of HIV/AIDS in India. Design/methodology/approach The paper uses data from National Aids Control Organization (NACO), National Family Health Survey (NFHS 3), and the Directorate of Economics and Statistics. Findings This study highlights the problems facing women in deterring the spread of HIV/AIDS in India. The status and empowerment of women are important variables in combating the disease among both men and women in India. Literacy, education, exposure to the media, labor market participation, awareness of HIV/AIDS, and economic independence are important considerations in improving the status of women in India. Policymakers need to focus on gender inequality in order to combat the spread of HIV/AIDS in India. Originality/value While absolute figures indicate men are more likely to be infected with HIV/AIDS, the rate of decline is higher for men compared to women in India. We explore several plausible explanations for such observed inequality in the spread of HIV/AIDS across gender. In particular, a potentially important factor - the low status of women in society is attributable as an impediment to the spread of the disease. A case study of the relationship between gender empowerment and the spread of HIV/AIDS in the state with the highest concentration, Manipur, provides more insight to the difficulties faced by women in combating HIV/AIDS in India.

The delta-phase spectrum with application to voice activity detection and speaker recognition

For several reasons, the Fourier phase domain is less favored than the magnitude domain in signal processing and modeling of speech. To correctly analyze the phase, several factors must be considered and compensated, including the effect of the step size, windowing function and other processing parameters. Building on a review of these factors, this paper investigates a spectral representation based on the Instantaneous Frequency Deviation, but in which the step size between processing frames is used in calculating phase changes, rather than the traditional single sample interval. Reflecting these longer intervals, the term delta-phase spectrum is used to distinguish this from instantaneous derivatives. Experiments show that mel-frequency cepstral coefficients features derived from the delta-phase spectrum (termed Mel-Frequency delta-phase features) can produce broadly similar performance to equivalent magnitude domain features for both voice activity detection and speaker recognition tasks. Further, it is shown that the fusion of the magnitude and phase representations yields performance benefits over either in isolation.

Single crystal Raman spectroscopy of brandholzite Mg[Sb(OH)6]2•6H2O and bottinoite Ni[Sb(OH)6]2•6H2O and the polycrystalline Raman spectrum of mopungite Na[Sb(OH)6]

The single crystal Raman spectra of minerals brandholzite and bottinoite, formula M[Sb(OH)6]2•6H2O, where M is Mg+2 and Ni+2 respectively, and the non-aligned Raman spectrum of mopungite, formula Na[Sb(OH)6], are presented for the first time. The mixed metal minerals comprise of alternating layers of [Sb(OH)6]-1 octahedra and mixed [M(H2O)6]+2 / [Sb(OH)6]-1 octahedra. Mopungite comprises hydrogen bonded layers of [Sb(OH)6]-1 octahedra linked within the layer by Na+ ions. The spectra of the three minerals were dominated by the Sb-O symmetric stretch of the [Sb(OH)6]-1 octahedron, which occurs at approximately 620 cm-1. The Raman spectrum of mopungite showed many similarities to spectra of the di-octahedral minerals informing the view that the Sb octahedra gave rise to most of the Raman bands observed, particularly below 1200 cm-1. Assignments have been proposed based on the spectral comparison between the minerals, prior literature and density field theory calculations of the vibrational spectra of the free [Sb(OH)6]-1 and [M(H2O)6]+2 octahedra by a model chemistry of B3LYP/6-31G(d) and lanl2dz for the Sb atom. The single crystal data spectra showed good mode separation, allowing the majority of the bands to be assigned a symmetry species of A or E.

Analysis of detection performance in spectrum sensing optimisation for long sensing periods

Spectrum sensing optimisation techniques maximise the efficiency of spectrum sensing while satisfying a number of constraints. Many optimisation models consider the possibility of the primary user changing activity state during the secondary user's transmission period. However, most ignore the possibility of activity change during the sensing period. The observed primary user signal during sensing can exhibit a duty cycle which has been shown to severely degrade detection performance. This paper shows that (a) the probability of state change during sensing cannot be neglected and (b) the true detection performance obtained when incorporating the duty cycle of the primary user signal can deviate significantly from the results expected with the assumption of no such duty cycle.

Your voice counts : Listening to the voice of high school students with autism spectrum disorder

Supporting students with Autism Spectrum Disorders (ASD) in inclusive settings presents both opportunities and significant challenges to school communities. This study, which explored the lived-experience of nine students with ASD in an inclusive high school in Australia, is based on the belief that by listening to the voices of students, school communities will be in a better position to collaboratively create supportive learning and social environments. The findings of this small-scale study deepen our knowledge from the student perspective of the inclusive educational practices that facilitate and constrain the learning and participation of students with ASD. The students’ perspectives were examined in relation to the characteristics of successful inclusive schools identified by Kluth. Implications for inclusive educational practice that meets the needs of students with ASD are presented.

Spectrum sensing using two-stage detection to compensate for reduced primary user duty cycle

Spectrum sensing is considered to be one of the most important tasks in cognitive radio. One of the common assumption among current spectrum sensing detectors is the full presence or complete absence of the primary user within the sensing period. In reality, there are many situations where the primary user signal only occupies a portion of the observed signal and the assumption of primary user duty cycle not necessarily fulfilled. In this paper we show that the true detection performance can degrade from the assumed achievable values when the observed primary user exhibits a certain duty cycle. Therefore, a two-stage detection method incorporating primary user duty cycle that enhances the detection performance is proposed. The proposed detector can improve the probability of detection under low duty cycle at the expense of a small decrease in performance at high duty cycle.