The flow over delta wings at low speeds with leading edge separation

A low speed investigation of the flow over a 40 degree apex angle delta wing with sharp leading edges had been made in order to ascertain details of the flow in the viscous region near the leading edge of the suction surface of the wing. A physical picture of the flow was obtained from the surface flow and a smoke technique of flow visualization, combined with detailed measurements of total head, dynamic pressure, flow directions and vortex core positions in the flow above the wing

Stochastic Perturbations of Periodic Orbits with Sliding

Vector fields that are discontinuous on codimension-one surfaces are known as Filippov systems and can have attracting periodic orbits involving segments that are contained on a discontinuity surface of the vector field. In this paper we consider the addition of small noise to a general Filippov system and study the resulting stochastic dynamics near such a periodic orbit. Since a straight-forward asymptotic expansion in terms of the noise amplitude is not possible due to the presence of discontinuity surfaces, in order to quantitatively determine the basic statistical properties of the dynamics, we treat different parts of the periodic orbit separately. Dynamics distant from discontinuity surfaces is analyzed by the use of a series expansion of the transitional probability density function. Stochastically perturbed sliding motion is analyzed through stochastic averaging methods. The influence of noise on points at which the periodic orbit escapes a discontinuity surface is determined by zooming into the transition point. We combine the results to quantitatively determine the effect of noise on the oscillation time for a three-dimensional canonical model of relay control. For some parameter values of this model, small noise induces a significantly large reduction in the average oscillation time. By interpreting our results geometrically, we are able to identify four features of the relay control system that contribute to this phenomenon.Comment: 44 pages, 9 figures, submitted to: J Nonlin. Sc

Deep Remix: Remixing Musical Mixtures Using a Convolutional Deep Neural Network

Audio source separation is a difficult machine learning problem and performance is measured by comparing extracted signals with the component source signals. However, if separation is motivated by the ultimate goal of re-mixing then complete separation is not necessary and hence separation difficulty and separation quality are dependent on the nature of the re-mix. Here, we use a convolutional deep neural network (DNN), trained to estimate 'ideal' binary masks for separating voice from music, to perform re-mixing of the vocal balance by operating directly on the individual magnitude components of the musical mixture spectrogram. Our results demonstrate that small changes in vocal gain may be applied with very little distortion to the ultimate re-mix. Our method may be useful for re-mixing existing mixes

New and emerging technologies for the treatment of inherited retinal diseases: a horizon scanning review.

The horizon scanning review aimed to identify new and emerging technologies in development that have the potential to slow or stop disease progression and/or reverse sight loss in people with inherited retinal diseases (IRDs). Potential treatments were identified using recognized horizon scanning methods. These included a combination of online searches using predetermined search terms, suggestions from clinical experts and patient and carer focus groups, and contact with commercial developers. Twenty-nine relevant technologies were identified. These included 9 gene therapeutic approaches, 10 medical devices, 5 pharmacological agents, and 5 regenerative and cell therapies. A further 11 technologies were identified in very early phases of development (typically phase I or pre-clinical) and were included in the final report to give a complete picture of developments 'on the horizon'. Clinical experts and patient and carer focus groups provided helpful information and insights, such as the availability of specialised services for patients, the potential impacts of individual technologies on people with IRDs and their families, and helped to identify additional relevant technologies. This engagement ensured that important areas of innovation were not missed. Most of the health technologies identified are still at an early stage of development and it is difficult to estimate when treatments might be available. Further, well designed trials that generate data on efficacy, applicability, acceptability, and costs of the technologies, as well as the long-term impacts for various conditions are required before these can be considered for adoption into routine clinical practice