Representations of specific acoustic patterns in the auditory cortex and hippocampus

Previous behavioural studies have shown that repeated presentation of a randomly chosen acoustic pattern leads to the unsupervised learning of some of its specific acoustic features. The objective of our study was to determine the neural substrate for the representation of freshly learnt acoustic patterns. Subjects first performed a behavioural task that resulted in the incidental learning of three different noise-like acoustic patterns. During subsequent high-resolution functional magnetic resonance imaging scanning, subjects were then exposed again to these three learnt patterns and to others that had not been learned. Multi-voxel pattern analysis was used to test if the learnt acoustic patterns could be 'decoded' from the patterns of activity in the auditory cortex and medial temporal lobe. We found that activity in planum temporale and the hippocampus reliably distinguished between the learnt acoustic patterns. Our results demonstrate that these structures are involved in the neural representation of specific acoustic patterns after they have been learnt.

Rapid design of discrete orthonormal wavelet transforms using silicon IP components

A rapid design methodology for orthonormal wavelet transform cores has been developed. This methodology is based on a generic, scaleable architecture utilising time-interleaved coefficients for the wavelet transform filters. The architecture has been captured in VHDL and parameterised in terms of wavelet family, wavelet type, data word length and coefficient word length. The control circuit is embedded within the cores and allows them to be cascaded without any interface glue logic for any desired level of decomposition. Case studies for stand alone and cascaded silicon cores for single and multi-stage wavelet analysis respectively are reported. The design time to produce silicon layout of a wavelet based system has been reduced to typically less than a day. The cores are comparable in area and performance to handcrafted designs. The designs are portable across a range of foundries and are also applicable to FPGA and PLD implementations.

An Intelligent Threat Prevention Framework with Heterogeneous Information

Three issues usually are associated with threat prevention intelligent surveillance systems. First, the fusion and interpretation of large scale incomplete heterogeneous information; second, the demand of effectively predicting suspects’ intention and ranking the potential threats posed by each suspect; third, strategies of allocating limited security resources (e.g., the dispatch of security team) to prevent a suspect’s further actions towards critical assets. However, in the literature, these three issues are seldomly considered together in a sensor network based intelligent surveillance framework. To address
this problem, in this paper, we propose a multi-level decision support framework for in-time reaction in intelligent surveillance. More specifically, based on a multi-criteria event modeling framework, we design a method to predict the most plausible intention of a suspect. Following this, a decision support model is proposed to rank each suspect based on their threat severity and to determine resource allocation strategies. Finally, formal properties are discussed to justify our framework.

Development of a rapid, multi-class method for the confirmatory analysis of anti-inflammatory drugs in bovine milk using liquid chromatography tandem mass spectrometry

A rapid liquid chromatography tandem mass spectrometry (LC-MS/MS) method has been developed and validated for the simultaneous identification, confirmation and quantitation of seven licensed anti-inflammatory drugs (AIDS) in bovine milk. The method was validated in accordance with the criteria defined in Commission Decision 2002/657/EC. Two classes of AIDS were investigated, corticosteroids and non-steroidal anti-inflammatory drugs (NSAIDs). The developed method is capable of detecting and confirming dexamethasone (DXM), betamethasone (BTM), prednisolone (FRED), tolfenamic acid (TV), 5-hydroxy flunixin (5-OH-FLU). meloxicam (MLX) and 4-methyl amino antipyrine (4-MAA) at their associated maximum residue limits (MRLs). These compounds represent all the corticosteroids and NSAIDs licensed for use in bovine animals producing milk for human consumption. These compounds have never been analysed before in the same method and also 4-methyl amino antipyrine has never been analysed with the other licensed NSAIDs. The method can be considered rapid as permits the analysis of up to 30 samples in one day. Milk samples are extracted with acetonitrile; sodium chloride is added to aid partition of the milk and acetonitrile mixture. The acetonitrile extract is then subjected to liquid-liquid purification by the addition of hexane. The purified extract is finally evaporated to dryness and reconstituted in a water/acetonitrile mixture and determination is carried out by LC-MS/MS. Decision limit (CC alpha) values and detection capability (CC beta) values have been established for each compound. (C) 2009 Elsevier B.V. All rights reserved.

Multi-UAVs formation autopilot design and performance analysis under interconnection topologies

This paper employs a unique extension-decomposition-aggregation (EDA) scheme to solve the formation flight control problem for multiple unmanned aerial vehicles (UAVs). The corresponding decentralised longitudinal and lateral formation autopilots are novelly designed to maintain the overall formation stability when encountering changes of the formation error and topologies. The concept of propagation layer number (PLN) is also proposed to provide an intuitive criterion to judge which type of formation topology is more suitable to minimise formation error propagation (FEP). The criterion states that the smaller the PLN of the formation is, the quicker the response to the formation error is. A smaller PLN also means that the resulting topology provides better prevention to the FEP. Simulation studies of formation flight of multiple Aerosonde UAVs demonstrate that the designed formation controller based on the EDA strategy performs satisfactorily in maintaining the overall formation stable, and the bidirectional partial-mesh topology is found to provide the best overall response to the formation error propagation based on the PLN criterion.

Decision making in childhood asthma exacerbation – a clinical judgement analysis

Background: Clinical decisions which impact directly on patient safety and quality of care are made during acute asthma attacks by individual doctors on the basis of their knowledge and experience. These include administration of systemic corticosteroids (CS), oral antibiotics, and admission to hospital. Clinical judgement analysis provides a methodology for comparing decisions between practitioners with different training and experience, and improving decision making. Methods: Stepwise linear regression was used to select clinical cues based on visual analogue scale assessments of the propensity of 62 clinicians to prescribe a short course of oral CS (decision 1), a course of antibiotics (decision 2), and/or admit to hospital (decision 3) for 60 â??paperâ?? patients. Results:When compared by specialty, paediatriciansâ?? models for decision 1 were more likely to include as a cue level of alertness (54% v. 16%); for decision 2 presence of crepitations (49% v. 16%), and less likely to include inhaled CS (8% v. 40%), respiratory rate (0% v. 24%), and air entry (70% v. 100%). When compared to other grades, the models derived for decision 3 by consultants/general practitioners were more likely to include wheeze severity as a cue (39% v. 6%). Conclusions: Clinicians differed in their use of individual cues and the number included in their models. Patient safety and quality of care will benefit from clarification of decision making strategies as general learning points during medical training, in the development of guidelines and care pathways, and by clinicians developing self-awareness of their own preferences.