Optically gated beating-heart imaging

The constant motion of the beating heart presents an obstacle to clear optical imaging, especially 3D imaging, in small animals where direct optical imaging would otherwise be possible. Gating techniques exploit the periodic motion of the heart to computationally "freeze" this movement and overcome motion artefacts. Optically gated imaging represents a recent development of this, where image analysis is used to synchronize acquisition with the heartbeat in a completely non-invasive manner. This article will explain the concept of optical gating, discuss a range of different implementation strategies and their strengths and weaknesses. Finally we will illustrate the usefulness of the technique by discussing applications where optical gating has facilitated novel biological findings by allowing 3D in vivo imaging of cardiac myocytes in their natural environment of the beating heart

Secure tenure for home ownership and economic development on land subject to native title

The public policy debate on land rights, the struggle of Indigenous peoples to have their pre-colonial possession of land recognised and interests in how land rights might be exercised to fulfil Indigenous peoples’ hopes for economic development and home ownership.Those people who have had their native title rights and interests in land legally recognised are contemplating the implications for their future prosperity. They are pondering the types of investments they can make to develop their land for social and economic purposes, the use and development rights they might temporarily exchange for income, or, as a last resort, the rights and interests they are prepared to relinquish in return for compensation. Western Australia (WA) presents a unique case in the Australian context because, unlike other states and the Northern Territory, WA does not have a statutory Aboriginal land rights system despite its large and remote Aboriginal population. What is termed ‘Aboriginal land’ in Western Australia covers approximately 12 per cent of the state but has generally been granted at the discretion of the Minister for Lands, or else is held in trust as a reserve for the ‘use and benefit of Aboriginal inhabitants’.1 This estate has not been transferred to Aboriginal ownership under state legislation on the basis of statutory rights conferred on Aboriginal people as the result of a formal claim based on their cultural connections to the land or waters. According to the former Aboriginal and Torres Strait Islander Social Justice Commissioner Tom Calma (AHRC 2005), this reflects ‘protection’ style legislation from the 19th century, which has been the basis of calls for reform of the system since the early 1980s (Seaman 1984; Bonner 1996; Casey 2007)

Approximate selective inference via maximum likelihood

This article considers a conditional approach to selective inference via approximate maximum likelihood for data described by Gaussian models. There are two important considerations in adopting a post-selection inferential perspective. While one of them concerns the effective use of information in data, the other aspect deals with the computational cost of adjusting for selection. Our approximate proposal serves both these purposes-- (i) exploits the use of randomness for efficient utilization of left-over information from selection; (ii) enables us to bypass potentially expensive MCMC sampling from conditional distributions. At the core of our method is the solution to a convex optimization problem which assumes a separable form across multiple selection queries. This allows us to address the problem of tractable and efficient inference in many practical scenarios, where more than one learning query is conducted to define and perhaps redefine models and their corresponding parameters. Through an in-depth analysis, we illustrate the potential of our proposal and provide extensive comparisons with other post-selective schemes in both randomized and non-randomized paradigms of inference

The solution path of the generalized lasso

We present a path algorithm for the generalized lasso problem. This problem penalizes the $\ell_1$ norm of a matrix D times the coefficient vector, and has a wide range of applications, dictated by the choice of D. Our algorithm is based on solving the dual of the generalized lasso, which greatly facilitates computation of the path. For $D=I$ (the usual lasso), we draw a connection between our approach and the well-known LARS algorithm. For an arbitrary D, we derive an unbiased estimate of the degrees of freedom of the generalized lasso fit. This estimate turns out to be quite intuitive in many applications.Comment: Published in at http://dx.doi.org/10.1214/11-AOS878 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

3D + time blood flow mapping using SPIM-microPIV in the developing zebrafish heart

We present SPIM-μPIV as a flow imaging system, capable of measuring in vivo flow information with 3D micron-scale resolution. Our system was validated using a phantom experiment consisting of a flow of beads in a 50 μm diameter FEP tube. Then, with the help of optical gating techniques, we obtained 3D + time flow fields throughout the full heartbeat in a ∼3 day old zebrafish larva using fluorescent red blood cells as tracer particles. From this we were able to recover 3D flow fields at 31 separate phases in the heartbeat. From our measurements of this specimen, we found the net pumped blood volume through the atrium to be 0.239 nL per beat. SPIM-μPIV enables high quality in vivo measurements of flow fields that will be valuable for studies of heart function and fluid-structure interaction in a range of small-animal models