Non-stationary covariance function modelling in 2D least-squares collocation

Standard least-squares collocation (LSC) assumes 2D stationarity and 3D isotropy, and relies on a covariance function to account for spatial dependence in the ob-served data. However, the assumption that the spatial dependence is constant through-out the region of interest may sometimes be violated. Assuming a stationary covariance structure can result in over-smoothing of, e.g., the gravity field in mountains and under-smoothing in great plains. We introduce the kernel convolution method from spatial statistics for non-stationary covariance structures, and demonstrate its advantage fordealing with non-stationarity in geodetic data. We then compared stationary and non-stationary covariance functions in 2D LSC to the empirical example of gravity anomaly interpolation near the Darling Fault, Western Australia, where the field is anisotropic and non-stationary. The results with non-stationary covariance functions are better than standard LSC in terms of formal errors and cross-validation against data not used in the interpolation, demonstrating that the use of non-stationary covariance functions can improve upon standard (stationary) LSC

On the Discovery of Monocular Rivalry by Tscherning in 1898:Translation and Review

Monocular rivalry was named by Breese in 1899. He made prolonged observation of superimposed orthogonal gratings; they fluctuated in clarity with either one or the other grating occasionally being visible alone. A year earlier, Tscherning observed similar fluctuations with a grid of vertical and horizontal lines and with other stimuli; we draw attention to his prior account. Monocular rivalry has since been shown to occur with a wide variety of superimposed patterns with several independent rediscoveries of it. We also argue that Helmholtz described some phenomenon other than monocular rivalry in 1867

From DPSIR the DAPSI(W)R(M) Emerges… a Butterfly – ‘protecting the natural stuff and delivering the human stuff’

The complexity of interactions and feedbacks between human activities and ecosystems can make the analysis of such social-ecological systems intractable. In order to provide a common means to understand and analyse the links between social and ecological process within these systems, a range of analytical frameworks have been developed and adopted. Following decades of practical experience in implementation, the Driver Pressure State Impact Response (DPSIR) conceptual framework has been adapted and re-developed to become the D(A)PSI(W)R(M). This paper describes in detail the D(A)PSI(W)R(M) and its development from the original DPSIR conceptual frame. Despite its diverse application and demonstrated utility, a number of inherent shortcomings are identified. In particular the DPSIR model family tend to be best suited to individual environmental pressures and human activities and their resulting environmental problems, having a limited focus on the supply and demand of benefits from nature. We present a derived framework, the “Butterfly”, a more holistic approach designed to expand the concept. The “Butterfly” model, moves away from the centralised accounting framework approach while more-fully incorporating the complexity of social and ecological systems, and the supply and demand of ecosystem services, which are central to human-environment interactions

HIV-1 co-receptor usage:influence on mother-to-child transmission and pediatric infection

Viral CCR5 usage is not a predictive marker of mother to child transmission (MTCT) of HIV-1. CXCR4-using viral variants are little represented in pregnant women, have an increased although not significant risk of transmission and can be eventually also detected in the neonates. Genetic polymorphisms are more frequently of relevance in the child than in the mother. However, specific tissues as the placenta or the intestine, which are involved in the prevalent routes of infection in MTCT, may play an important role of selective barriers

Clinical significance of HIV-1 coreceptor usage

The identification of phenotypically distinct HIV-1 variants with different prevalence during the progression of the disease has been one of the earliest discoveries in HIV-1 biology, but its relevance to AIDS pathogenesis remains only partially understood. The physiological basis for the phenotypic variability of HIV-1 was elucidated with the discovery of distinct coreceptors employed by the virus to infect susceptible cells. The role of the viral phenotype in the variable clinical course and treatment outcome of HIV-1 infection has been extensively investigated over the past two decades. In this review, we summarize the major findings on the clinical significance of the HIV-1 coreceptor usage