On the construction of probabilistic Newton-type algorithms

It has recently been shown that many of the existing quasi-Newton algorithms can be formulated as learning algorithms, capable of learning local models of the cost functions. Importantly, this understanding allows us to safely start assembling probabilistic Newton-type algorithms, applicable in situations where we only have access to noisy observations of the cost function and its derivatives. This is where our interest lies. We make contributions to the use of the non-parametric and probabilistic Gaussian process models in solving these stochastic optimisation problems. Specifically, we present a new algorithm that unites these approximations together with recent probabilistic line search routines to deliver a probabilistic quasi-Newton approach. We also show that the probabilistic optimisation algorithms deliver promising results on challenging nonlinear system identification problems where the very nature of the problem is such that we can only access the cost function and its derivative via noisy observations, since there are no closed-form expressions available

Numerical determination of the effective moments of non-spherical particles

Dielectric characterisation of polarisable particles, and prediction of the forces and torques exerted upon them, relies on the knowledge of the effective, induced dipole moment. In turn, through the mechanism of depolarisation, the induced dipole moment of a particle is strongly dependent upon its shape. Since realistic shapes create modelling difficulties, the ‘spherical particle’ approximation is often invoked. However, in many cases, including biological dielectric spectroscopy and dielectrophoresis, this assumption is a poor one. For example, human erythrocytes are essentially oblate spheroids with indented sides, while viruses and bacteria often have elongated cigar shapes. Since shape-dependent polarisation both strongly influences the accuracy of conventional dielectric characterisation methods using Maxwell’s mixture formula and confounds accurate prediction of dielectrophoretic forces and torques, it is important to develop means to treat non-spherical particles. In this paper, we demonstrate a means to extract the dipole moment directly from numerical solutions of the induced electrostatic potential when a particle is placed in a uniform electric field. The accuracy of the method is demonstrated for a range of particle shapes: spherical, ellipsoidal, truncated cylinders and an approximation of an erythrocyte, the red blood cell

Gluon Emission of Heavy Quarks: Dead Cone Effect

The lowest-order induced soft gluon radiation processes of heavy quarks have been analyzed to quantify the dead cone effect. This effect is most likely expected to suppress significantly the energy loss of charm quarks passing an amorphous color-neutral deconfined medium, as has been concluded from recent experiments at RHIC

Diagnostic system design for the Ion Auxiliary Propulsion System (IAPS). Flight tests of two 8 cm mercury ion

The mechanical, thermal, electrical design and the ground test results of four types of detectors are explained. The DSS is designed to measure the thruster efflux material deposition and S/C potential relative to the local plasma in the vicinity of two 8 cm mercury ion thrusters. The DSS consists of two quartz crystal microbalance (QCM) detectors, one potential probe, nine solar cell arrays, seven ion collectors and two electronic packages

Statistical decision problems in large scale biological experiments Final report

Statistical decision theory applied to problems associated with Martian biological exploration progra

Continuation of studies in statistical decision theory in large scale biological experiments Final report, 1 May 1965 - 31 Jul. 1966

Statistical decision theory applied to Martian atmosphere analysis, life detection experiments, and gas chromatogram measurements of n-alkane distributions in material

Environmental Volunteering: Motivations, Modes and Outcomes

Volunteers play a key role in natural resource management: their commitment, time and labour constitute a major contribution towards managing environments in Australia and throughout the world. From the point of view of environmental managers much interest has focussed on defining tasks suitable to volunteers. However, we argue that an improved understanding of what motivates volunteers is required to sustain volunteer commitments to environmental management in the long term. This is particularly important given that multiple government programs rely heavily on volunteers in Australia, a phenomenon also noted in the UK, Canada, and the USA. Whilst there is considerable research on volunteering in other sectors (e.g. health), there has been relatively little attention paid to understanding environmental volunteering. Drawing on the literature from other sectors and environmental volunteering where available, we present a set of six broad motivations underpinning environmental volunteers and five different modes that environmental volunteering is manifested. We developed and refined the sets of motivations and modes through a pilot study involving interviews with volunteers and their coordinators from environmental groups in Sydney and the Bass Coast. The pilot study data emphasise the importance of promoting community education as a major focus of environmental volunteer groups and demonstrate concerns over the fine line between supporting and abusing volunteers given their role in delivering environmental outcomes.environment, volunteering, motivation, Natural Resource Management (NRM)