Macroscopic effects of the spectral structure in turbulent flows

Two aspects of turbulent flows have been the subject of extensive, split research efforts: macroscopic properties, such as the frictional drag experienced by a flow past a wall, and the turbulent spectrum. The turbulent spectrum may be said to represent the fabric of a turbulent state; in practice it is a power law of exponent \alpha (the "spectral exponent") that gives the revolving velocity of a turbulent fluctuation (or "eddy") of size s as a function of s. The link, if any, between macroscopic properties and the turbulent spectrum remains missing. Might it be found by contrasting the frictional drag in flows with differing types of spectra? Here we perform unprecedented measurements of the frictional drag in soap-film flows, where the spectral exponent \alpha = 3 and compare the results with the frictional drag in pipe flows, where the spectral exponent \alpha = 5/3. For moderate values of the Reynolds number Re (a measure of the strength of the turbulence), we find that in soap-film flows the frictional drag scales as Re^{-1/2}, whereas in pipe flows the frictional drag scales as Re^{-1/4} . Each of these scalings may be predicted from the attendant value of \alpha by using a new theory, in which the frictional drag is explicitly linked to the turbulent spectrum. Our work indicates that in turbulence, as in continuous phase transitions, macroscopic properties are governed by the spectral structure of the fluctuations.Comment: 6 pages, 3 figure

Large-scale Nonlinear Variable Selection via Kernel Random Features

We propose a new method for input variable selection in nonlinear regression. The method is embedded into a kernel regression machine that can model general nonlinear functions, not being a priori limited to additive models. This is the first kernel-based variable selection method applicable to large datasets. It sidesteps the typical poor scaling properties of kernel methods by mapping the inputs into a relatively low-dimensional space of random features. The algorithm discovers the variables relevant for the regression task together with learning the prediction model through learning the appropriate nonlinear random feature maps. We demonstrate the outstanding performance of our method on a set of large-scale synthetic and real datasets.Comment: Final version for proceedings of ECML/PKDD 201

Proton Driven Plasma Wakefield Acceleration

Plasma wakefield acceleration, either laser driven or electron-bunch driven, has been demonstrated to hold great potential. However, it is not obvious how to scale these approaches to bring particles up to the TeV regime. In this paper, we discuss the possibility of proton-bunch driven plasma wakefield acceleration, and show that high energy electron beams could potentially be produced in a single accelerating stage.Comment: 13 pages, 4 figure

Metal-insulator transition in vanadium dioxide nanobeams: probing sub-domain properties of strongly correlated materials

Many strongly correlated electronic materials, including high-temperature superconductors, colossal magnetoresistance and metal-insulator-transition (MIT) materials, are inhomogeneous on a microscopic scale as a result of domain structure or compositional variations. An important potential advantage of nanoscale samples is that they exhibit the homogeneous properties, which can differ greatly from those of the bulk. We demonstrate this principle using vanadium dioxide, which has domain structure associated with its dramatic MIT at 68 degrees C. Our studies of single-domain vanadium dioxide nanobeams reveal new aspects of this famous MIT, including supercooling of the metallic phase by 50 degrees C; an activation energy in the insulating phase consistent with the optical gap; and a connection between the transition and the equilibrium carrier density in the insulating phase. Our devices also provide a nanomechanical method of determining the transition temperature, enable measurements on individual metal-insulator interphase walls, and allow general investigations of a phase transition in quasi-one-dimensional geometry.Comment: 9 pages, 3 figures, original submitted in June 200

Accelerating electric vehicle uptake: Modelling public policy options on prices and infrastructure

Transitioning to passenger battery electric vehicles (BEV) can mitigate climate change impacts of road transportation. We develop a novel BEV policy model, nesting it within a national-scale macroeconomic system dynamics model (iSDG-Australia) to simulate a suite of policy pathways. We model combinations of infrastructure support and subsidies, which bring forward the price-parity tipping point, thus rapidly accelerating BEVs’ share of new car sales. However, ongoing complementary charging infrastructure investment is critical to reach 100% new BEV car sales by 2050 in Australia. Even with a rapid transition, the modelled fleet would not achieve net-zero greenhouse gas emissions by 2050 due to vehicle longevity; and suddenly ceasing financial incentives could retard BEV sales by a decade. Based on our assumptions, results suggest emissions reductions are maximised by the fastest transition of the passenger vehicle fleet to BEVs, entailing government policy support from 2020 to 2050, for both adequate infrastructure deployment (AUD17.9b) and vehicle rebates (AUD19.5b), which achieves earlier BEV price-parity with fossil-fuelled vehicles

A preliminary study of the effect of closed incision management with negative pressure wound therapy over high-risk incisions

Background Certain postoperative wounds are recognised to be associated with more complications than others and may be termed high-risk. Wound healing can be particularly challenging following high-energy trauma where wound necrosis and infection rates are high. Surgical incision for joint arthrodesis can also be considered high-risk as it requires extensive and invasive surgery and postoperative distal limb swelling and wound dehiscence are common. Recent human literature has investigated the use of negative pressure wound therapy (NPWT) over high-risk closed surgical incisions and beneficial effects have been noted including decreased drainage, decreased dehiscence and decreased infection rates. In a randomised, controlled study twenty cases undergoing distal limb high-energy fracture stabilisation or arthrodesis were randomised to NPWT or control groups. All cases had a modified Robert-Jones dressing applied for 72 h postoperatively and NPWT was applied for 24 h in the NPWT group. Morphometric assessment of limb circumference was performed at six sites preoperatively, 24 and 72 h postoperatively. Wound discharge was assessed at 24 and 72 h. Postoperative analgesia protocol was standardised and a Glasgow Composite Measure Pain Score (GCPS) carried out at 24, 48 and 72 h. Complications were noted and differences between groups were assessed. Results Percentage change in limb circumference between preoperative and 24 and 72 h postoperative measurements was significantly less at all sites for the NPWT group with exception of the joint proximal to the surgical site and the centre of the operated bone at 72 h. Median discharge score was lower in the NPWT group than the control group at 24 h. No significant differences in GCPS or complication rates were noted. Conclusions Digital swelling and wound discharge were reduced when NPWT was employed for closed incision management. Larger studies are required to evaluate whether this will result in reduced discomfort and complication rates postoperatively

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance

Regulating STING in health and disease.

The presence of cytosolic double-stranded DNA molecules can trigger multiple innate immune signalling pathways which converge on the activation of an ER-resident innate immune adaptor named "STimulator of INterferon Genes (STING)". STING has been found to mediate type I interferon response downstream of cyclic dinucleotides and a number of DNA and RNA inducing signalling pathway. In addition to its physiological function, a rapidly increasing body of literature highlights the role for STING in human disease where variants of the STING proteins, as well as dysregulated STING signalling, have been implicated in a number of inflammatory diseases. This review will summarise the recent structural and functional findings of STING, and discuss how STING research has promoted the development of novel therapeutic approaches and experimental tools to improve treatment of tumour and autoimmune diseases

Maternal care boosted by paternal imprinting in mammals.

In mammals, mothers are the primary caregiver, programmed, in part, by hormones produced during pregnancy. High-quality maternal care is essential for the survival and lifelong health of offspring. We previously showed that the paternally silenced imprinted gene pleckstrin homology-like domain family A member 2 (Phlda2) functions to negatively regulate a single lineage in the mouse placenta called the spongiotrophoblast, a major source of hormones in pregnancy. Consequently, the offspring's Phlda2 gene dosage may influence the quality of care provided by the mother. Here, we show that wild-type (WT) female mice exposed to offspring with three different doses of the maternally expressed Phlda2 gene-two active alleles, one active allele (the extant state), and loss of function-show changes in the maternal hypothalamus and hippocampus during pregnancy, regions important for maternal-care behaviour. After birth, WT dams exposed in utero to offspring with the highest Phlda2 dose exhibit decreased nursing and grooming of pups and increased focus on nest building. Conversely, 'paternalised' dams, exposed to the lowest Phlda2 dose, showed increased nurturing of their pups, increased self-directed behaviour, and a decreased focus on nest building, behaviour that was robustly maintained in the absence of genetically modified pups. This work raises the intriguing possibility that imprinting of Phlda2 contributed to increased maternal care during the evolution of mammals