Superthermal ion signatures of auroral acceleration processes

The retarding ion mass spectrometer on the Dynamics Explorer 1 spacecraft has generated a unique data set which documents, among other things, the occurrence of non-Maxwellian superthermal features in the auroral topside ionosphere distribution functions. In this paper, we provide a representative sampling of the observed features and their spatial morphology as observed at altitudes in the range from a few thousand kilometers to a few earth radii. At lower altitudes, these features appear at auroral latitudes separating regions of polar cap and subauroral light ion polar wind. The most common signature is the appearance of an upgoing energetic tail having conical lobes representing significant ion heat and number flux in all species, including O+. Transverse ion heating below the observation point at several thousand kilometers is clearly associated with O+ outflows. In some events observed, transverse acceleration apparently involves nearly the entire thermal plasma, the distribution function becomes highly anisotropic with T⊥ > T∥, and may actually develop a minimum at zero velocity, i.e., become a torus having as its axis the local magnetic field direction. At higher altitudes, the localized dayside source region appears as a field aligned flow which is dispersed tailward across the polar cap according to parallel velocity by antisunward convective flow, so that upflowing low energy O+ ions appear well within the polar cap region. While this flow can appear beamlike in a given location, the energy dispersion observed implies a very broad energy distribution at the source, extending from a few tenths of an eV to in excess of 50 eV. On the nightside, upgoing ion beams are found to be latitudinally bounded by regions of ion conics whose half angles increase with increasing separation from the beam region, indicating low altitude transverse acceleration in immediate proximity to, and below, the parallel acceleration region. These observations reveal a clear distinction between classical polar wind ion outflow and O+ enhanced superthermal flows, and confirm the importance of low altitude transverse acceleration in ionospheric plasma transport, as suggested by previous observations.

Identification of novel cholesteatoma-related gene expression signatures using full-genome microarrays

This study demonstrates that the expression profile of cholesteatoma is similar to a metastatic tumour and chronically inflamed tissue. Based on the investigated profiles we present novel protein-protein interaction and signal transduction networks, which include cholesteatoma-regulated transcripts and may be of great value for drug targeting and therapy development.

Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm

The personalised conditioning system (PCS) is widely studied. Potentially, it is able to reduce energy consumption while securing occupants’ thermal comfort requirements. It has been suggested that automatic optimised operation schemes for PCS should be introduced to avoid energy wastage and discomfort caused by inappropriate operation. In certain automatic operation schemes, personalised thermal sensation models are applied as key components to help in setting targets for PCS operation. In this research, a novel personal thermal sensation modelling method based on the C-Support Vector Classification (C-SVC) algorithm has been developed for PCS control. The personal thermal sensation modelling has been regarded as a classification problem. During the modelling process, the method ‘learns’ an occupant’s thermal preferences from his/her feedback, environmental parameters and personal physiological and behavioural factors. The modelling method has been verified by comparing the actual thermal sensation vote (TSV) with the modelled one based on 20 individual cases. Furthermore, the accuracy of each individual thermal sensation model has been compared with the outcomes of the PMV model. The results indicate that the modelling method presented in this paper is an effective tool to model personal thermal sensations and could be integrated within the PCS for optimised system operation and control.