On the Statistics of Cognitive Radio Capacity in Shadowing and Fast Fading Environments (Journal Version)

In this paper we consider the capacity of the cognitive radio channel in different fading environments under a low interference regime. First we derive the probability that the low interference regime holds under shadow fading as well as Rayleigh and Rician fast fading conditions. We demonstrate that this is the dominant case, especially in practical cognitive radio deployment scenarios. The capacity of the cognitive radio channel depends critically on a power loss parameter, $\alpha$, which governs how much transmit power the cognitive radio dedicates to relaying the primary message. We derive a simple, accurate approximation to $\alpha$ in Rayleigh and Rician fading environments which gives considerable insight into system capacity. We also investigate the effects of system parameters and propagation environment on $\alpha$ and the cognitive radio capacity. In all cases, the use of the approximation is shown to be extremely accurate.Comment: Submitted to the IEEE Transactions on Wireless Commun. The conference version of this paper appears in Proc. IEEE CrownCom, 200

Some Nonlinear Exponential Smoothing Models are Unstable

This paper discusses the instability of eleven nonlinear state space models that underly exponential smoothing. Hyndman et al. (2002) proposed a framework of 24 state space models for exponential smoothing, including the well-known simple exponential smoothing, Holt's linear and Holt-Winters' additive and multiplicative methods. This was extended to 30 models with Taylor's (2003) damped multiplicative methods. We show that eleven of these 30 models are unstable, having infinite forecast variances. The eleven models are those with additive errors and either multiplicative trend or multiplicative seasonality, as well as the models with multiplicative errors, multiplicative trend and additive seasonality. The multiplicative Holt-Winters' model with additive errors is among the eleven unstable models. We conclude that: (1) a model with a multiplicative trend or a multiplicative seasonal component should also have a multiplicative error; and (2) a multiplicative trend should not be mixed with additive seasonality.Exponential smoothing, forecast variance, nonlinear models, prediction intervals, stability, state space models.

EFFICIENT MARKETING OF BLUEBERRIES IN MISSISSIPPI AND LOUISIANA

Fresh blueberries are sold through a marketing cooperative of the blueberry industry in Mississippi and Louisiana. Blueberry producers have numerous alternatives in assembling blueberries, and the cooperative needs to know the costs of different systems for assembling berries in order to provide better services to its members. The main objective of this study was to determine an efficient system for handling blueberries in Mississippi and Louisiana. Sixteen models with different combinations of drop stations and shipping points were evaluated. The results of this study will help the Miss-Lou Association and farmers to better develop strategies for handling and marketing blueberries in the future. It will assist the Miss-Lou Association in determining the number, size, and locations of drop stations/shipping points with change in production each year.Marketing,

Eliminating Stripe Artifacts in Light-Sheet Fluorescence Imaging

We report two techniques to mitigate stripe artifacts in light-sheet fluorescence imaging. The first uses an image processing algorithm called the multidirectional stripe remover (MDSR) method to filter stripes from an existing image. The second uses an elliptical holographic diffuser (EHD) with strong scattering anisotropy to prevent stripe formation during image acquisition. These techniques facilitate accurate interpretation of image data, especially in denser samples. They are also facile and cost-effective.Comment: Supplementary Material available at the journal pag

Exponential smoothing and non-negative data

The most common forecasting methods in business are based on exponential smoothing and the most common time series in business are inherently non-negative. Therefore it is of interest to consider the properties of the potential stochastic models underlying exponential smoothing when applied to non-negative data. We explore exponential smoothing state space models for non-negative data under various assumptions about the innovations, or error, process. We first demonstrate that prediction distributions from some commonly used state space models may have an infinite variance beyond a certain forecasting horizon. For multiplicative error models which do not have this flaw, we show that sample paths will converge almost surely to zero even when the error distribution is non-Gaussian. We propose a new model with similar properties to exponential smoothing, but which does not have these problems, and we develop some distributional properties for our new model. We then explore the implications of our results for inference, and compare the short-term forecasting performance of the various models using data on the weekly sales of over three hundred items of costume jewelry. The main findings of the research are that the Gaussian approximation is adequate for estimation and one-step-ahead forecasting. However, as the forecasting horizon increases, the approximate prediction intervals become increasingly problematic. When the model is to be used for simulation purposes, a suitably specified scheme must be employed.forecasting; time series; exponential smoothing; positive-valued processes; seasonality; state space models.

ATR-FTIR spectroscopy detects alterations induced by organotin(IV) carboxylates in MCF-7 cells at sub-cytotoxic/-genotoxic concentrations.

The environmental impact of metal complexes such as organotin(IV) compounds is of increasing concern. Genotoxic effects of organotin(IV) compounds (0.01 μg/ml, 0.1 μg/ml or 1.0 μg/ml) were measured using the alkaline single-cell gel electrophoresis (comet) assay to measure DNA single-strand breaks (SSBs) and the cytokinesis-block micronucleus (CBMN) assay to determine micronucleus formation. Biochemical-cell signatures were also ascertained using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy. In the comet assay, organotin(IV) carboxylates induced significantly-elevated levels of DNA SSBs. Elevated micronucleus-forming activities were also observed. Following interrogation using ATR-FTIR spectroscopy, infrared spectra in the biomolecular range (900 cm-1 – 1800 cm-1) derived from organotin-treated MCF-7 cells exhibited clear alterations in their biochemical-cell fingerprint compared to control-cell populations following exposures as low as 0.0001 μg/ml. Mono-, di- or tri-organotin(IV) carboxylates (0.1 μg/ml, 1.0 μg/ml or 10.0 μg/ml) were markedly cytotoxic as determined by the clonogenic assay following treatment of MCF-7 cells with ≥ 1.0 μg/ml. Our results demonstrate that ATR-FTIR spectroscopy can be applied to detect molecular alterations induced by organotin(IV) compounds at sub-cytotoxic and sub-genotoxic concentrations. This biophysical approach points to a novel means of assessing risk associated with environmental contaminants

Lyapunov Stability Analysis for Invariant States of Quantum Systems

In this article, we propose a Lyapunov stability approach to analyze the convergence of the density operator of a quantum system. In contrast to many previously studied convergence analysis methods for invariant density operators which use weak convergence, in this article we analyze the convergence of density operators by considering the set of density operators as a subset of Banach space. We show that the set of invariant density operators is both closed and convex, which implies the impossibility of having multiple isolated invariant density operators. We then show how to analyze the stability of this set via a candidate Lyapunov operator.Comment: A version of this paper has been accepted at 56th IEEE Conference on Decision and Control 201

Meeting the challenge of diabetes in ageing and diverse populations: a review of the literature from the UK

The impact of type 2 diabetes on ageing societies is great and populations across the globe are becoming more diverse. Complications of diabetes unequally affect particular groups in the UK older people, and people with a South Asian background are two population groups with increased risk whose numbers will grow in the future. We explored the evidence about diabetes care for older people with South Asian ethnicity to understand the contexts and mechanisms behind interventions to reduce inequalities. We used a realist approach to review the literature, mapped the main areas where relevant evidence exists, and explored the concepts and mechanisms which underpinned interventions. From this we constructed a theoretical framework for a programme of research and put forward suggestions for what our analysis might mean to providers, researchers, and policy makers. Broad themes of cultural competency; comorbidities and stratification; and access emerged as mid-level mechanisms which have individualised, culturally intelligent, and ethical care at their heart and through which inequalities can be addressed. These provide a theoretical framework for future research to advance knowledge about concordance; culturally meaningful measures of depression and cognitive impairment; and care planning in different contexts which support effective diabetes care for aging and diverse populations