The application of affine projection to the development of a siren noise cancellation system

Emergency vehicles use high-amplitude sirens to warn pedestrians and other road users of their presence. Unfortunately, the siren noise enters the vehicle and corrupts the intelligibility of two-way radio voice com-munications from the emergency vehicle to a control room. Often the siren has to be turned off to enable the control room to hear what is being said which subsequently endangers people's lives. A digital signal processing (DSP) based system for the cancellation of siren noise embedded within speech is presented. The system has been tested with the least mean square (LMS), normalised least mean square (NLMS) and affine projection algorithm (APA) using recordings from three common types of sirens (two-tone, wail and yelp) from actual test vehicles. It was found that the APA with a projection order of 2 gives comparably improved cancellation over the LMS and NLMS with only a moderate increase in algorithm complexity and code size. Therefore, this siren noise cancellation system using the APA offers an improvement in cancellation achieved by previous systems. The removal of the siren noise improves the response time for the emergency vehicle and thus the system can contribute to saving lives. The system also allows voice communication to take place even when the siren is on and as such the vehicle offers less risk of danger when moving at high speeds in heavy traffic.

Physics-based modelling for remote sensing of snow

Remote sensing is the only practicable means to observe snow at large scales. Measurements from passive microwave instruments have been used to derive snow climatology since the late 1970’s, but the algorithms used were limited by the computational power of the era. Simplifications such as the assumption of constant snow properties enabled snow mass to be retrieved from the microwave measurements, but large errors arise from those assumptions, which are still used today. A better approach is to perform retrievals within a data assimilation framework, where a physically-based model of the snow properties can be used to produce the best estimate of the snow cover, in conjunction with multi-sensor observations such as the grain size, surface temperature, and microwave radiation. We have developed an existing snow model, SNOBAL, to incorporate mass and energy transfer of the soil, and to simulate the growth of the snow grains. An evaluation of this model is presented and techniques for the development of new retrieval systems are discussed.

Design and development of a low NOx Coanda ejector burner

Small gaseous combustion systems are being targeted by strict pollution legislation which will provide challenges to reduce the NOx being emitted. A novel type of gas burner has been successfully designed and developed which incorporates a Coanda ejector to promote recirculation of flue gas from the burner exit. This provides a combustion system which gives very low emissions of NOx and CO, whilst maintaining a high degree of flame stability over a range of air/fuel ratios and fuel flow rates. Recirculation of flue gas was obtained by manipulating the aerodynamics of the system, without the aid of external duct work or moving parts. The design of the burner allowed very low pollutant emissions near stoichiometric conditions, resulting in high temperatures of the exit gas. Potential applications of this type of burner are in small and intermediate furnaces where low NOx emissions are required. Moreover, very high-temperature applications, such as glass furnaces could benefit in both cost and pollutant emissions from such a burner.

Theoretical perspectives on the development of a meta-methodology for value management

This paper provides a new set of theoretical perspectives on the topic of value management in building procurement. On the evidence of the current literature it is possible to identify two distinct methodologies which are based on different epistemological positions. An argument is developed which sees these two methodologies to be complementary. A tentative meta-methodology is then outlined for matching methodologies to different problem situations. It is contended however that such a meta-methodology could never provide a prescriptive guide. Its usefulness lies in the way in which it provides the basis for reflective practice. Of central importance is the need to understand the problem context within which value management is to be applied. The distinctions between unitary, pluralistic and coercive situations are seen to be especially significant.

Development of a light scatter sensor technology for on-line monitoring of milk coagulation and whey separation

The objective of this study was to investigate a novel light backscatter sensor, with a large field of view relative to curd size, for continuous on-line monitoring of coagulation and syneresis to improve curd moisture content control. A three-level, central composite design was employed to study the effects of temperature, cutting time, and CaCl2 addition on cheese making parameters. The sensor signal was recorded and analyzed. The light backscatter ratio followed a sigmoid increase during coagulation and decreased asymptotically after gel cutting. Curd yield and curd moisture content were predicted from the time to the maximum slope of the first derivative of the light backscatter ratio during coagulation and the decrease in the sensor response during syneresis. Whey fat was affected by coagulation kinetics and cutting time, suggesting curd rheological properties at cutting are dominant factors determining fat losses. The proposed technology shows potential for on-line monitoring of coagulation and syneresis. 2007 Elsevier Ltd. All rights reserved..

Development of a semantic graph-based scene description

Software representations of scenes, i.e. the modelling of objects in space, are used in many application domains. Current modelling and scene description standards focus on visualisation dimensions, and are intrinsically limited by their dependence upon their semantic interpretation and contextual application by humans. In this paper we propose the need for an open, extensible and semantically rich modelling language, which facilitates a machine-readable semantic structure. We critically review existing standards and techniques, and highlight a need for a semantically focussed scene description language. Based on this defined need we propose a preliminary solution, based on hypergraph theory, and reflect on application domains.

Maximising concurrency and scalability in a consistent, causal, distributed virtual reality system, whilst minimising the effect of network delays

The development of large scale virtual reality and simulation systems have been mostly driven by the DIS and HLA standards community. A number of issues are coming to light about the applicability of these standards, in their present state, to the support of general multi-user VR systems. This paper pinpoints four issues that must be readdressed before large scale virtual reality systems become accessible to a larger commercial and public domain: a reduction in the effects of network delays; scalable causal event delivery; update control; and scalable reliable communication. Each of these issues is tackled through a common theme of combining wall clock and causal time-related entity behaviour, knowledge of network delays and prediction of entity behaviour, that together overcome many of the effects of network delay.

Maximising concurrency and scalability in a consistent, causal, distributed virtual reality system, whilst minimising the effect of network delays

The development of large scale virtual reality and simulation systems have been mostly driven by the DIS and HLA standards community. A number of issues are coming to light about the applicability of these standards, in their present state, to the support of general multi-user VR systems. This paper pinpoints four issues that must be readdressed before large scale virtual reality systems become accessible to a larger commercial and public domain: a reduction in the effects of network delays; scalable causal event delivery; update control; and scalable reliable communication. Each of these issues is tackled through a common theme of combining wall clock and causal time-related entity behaviour, knowledge of network delays and prediction of entity behaviour, that together overcome many of the effects of network delays.

Development of a miniaturised microarray-based assay for the rapid identification of antimicrobial resistance genes in Gram-negative bacteria

We describe the development of a miniaturised microarray for the detection of antimicrobial resistance genes in Gram-negative bacteria. Included on the array are genes encoding resistance to aminoglycosides, trimethoprim, sulphonamides, tetracyclines and beta-lactams, including extended-spectrum beta-lactamases. Validation of the array with control strains demonstrated a 99% correlation between polymerase chain reaction and array results. There was also good correlation between phenotypic and genotypic results for a large panel of Escherichia coli and Salmonella isolates. Some differences were also seen in the number and type of resistance genes harboured by E. coli and Salmonella strains. The array provides an effective, fast and simple method for detection of resistance genes in clinical isolates suitable for use in diagnostic laboratories, which in future will help to understand the epidemiology of isolates and to detect gene linkage in bacterial populations. (C) 2008 Published by Elsevier B.V. and the International Society of Chemotherapy.

The integration of proteomics and systems approaches to map regulatory mechanisms underpinning platelet function.

Platelets in the circulation are triggered by vascular damage to activate, aggregate and form a thrombus that prevents excessive blood loss. Platelet activation is stringently regulated by intracellular signalling cascades, which when activated inappropriately lead to myocardial infarction and stroke. Strategies to address platelet dysfunction have included proteomics approaches which have lead to the discovery of a number of novel regulatory proteins of potential therapeutic value. Global analysis of platelet proteomes may enhance the outcome of these studies by arranging this information in a contextual manner that recapitulates established signalling complexes and predicts novel regulatory processes. Platelet signalling networks have already begun to be exploited with interrogation of protein datasets using in silico methodologies that locate functionally feasible protein clusters for subsequent biochemical validation. Characterization of these biological systems through analysis of spatial and temporal organization of component proteins is developing alongside advances in the proteomics field. This focused review highlights advances in platelet proteomics data mining approaches that complement the emerging systems biology field. We have also highlighted nucleated cell types as key examples that can inform platelet research. Therapeutic translation of these modern approaches to understanding platelet regulatory mechanisms will enable the development of novel anti-thrombotic strategies.

An evaluation of the spatiotemporal structure of large-scale European drought within the HiGEM climate model

We compare the characteristics of synthetic European droughts generated by the HiGEM1 coupled climate model run with present day atmospheric composition with observed drought events extracted from the CRU TS3 data set. The results demonstrate consistency in both the rate of drought occurrence and the spatiotemporal structure of the events. Estimates of the probability density functions for event area, duration and severity are shown to be similar with confidence > 90%. Encouragingly, HiGEM is shown to replicate the extreme tails of the observed distributions and thus the most damaging European drought events. The soil moisture state is shown to play an important role in drought development. Once a large-scale drought has been initiated it is found to be 50% more likely to continue if the local soil moisture is below the 40th percentile. In response to increased concentrations of atmospheric CO2, the modelled droughts are found to increase in duration, area and severity. The drought response can be largely attributed to temperature driven changes in relative humidity. 1 HiGEM is based on the latest climate configuration of the Met Office Hadley Centre Unified Model (HadGEM1) with the horizontal resolution increased to 1.25 x 0.83 degrees in longitude and latitude in the atmosphere and 1/3 x 1/3 degrees in the ocean.

Towards global drought early warning capability: expanding international cooperation for the development of a framework for global drought monitoring and forecasting

Drought is a global problem that has far-reaching impacts and especially 47 on vulnerable populations in developing regions. This paper highlights the need for a Global Drought Early Warning System (GDEWS), the elements that constitute its underlying framework (GDEWF) and the recent progress made towards its development. Many countries lack drought monitoring systems, as well as the capacity to respond via appropriate political, institutional and technological frameworks, and these have inhibited the development of integrated drought management plans or early warning systems. The GDEWS will provide a source of drought tools and products via the GDEWF for countries and regions to develop tailored drought early warning systems for their own users. A key goal of a GDEWS is to maximize the lead time for early warning, allowing drought managers and disaster coordinators more time to put mitigation measures in place to reduce the vulnerability to drought. To address this, the GDEWF will take both a top-down approach to provide global real-time drought monitoring and seasonal forecasting, and a bottom-up approach that builds upon existing national and regional systems to provide continental to global coverage. A number of challenges must be overcome, however, before a GDEWS can become a reality, including the lack of in-situ measurement networks and modest seasonal forecast skill in many regions, and the lack of infrastructure to translate data into useable information. A set of international partners, through a series of recent workshops and evolving collaborations, has made progress towards meeting these challenges and developing a global system.

Ovarian expression of insulin-like peptide 3 (INSL3) and its receptor (RXFP2) during development of bovine antral follicles and corpora lutea and measurement of circulating INSL3 levels during synchronized estrous cycles

Insulin-like peptide 3 (INSL3), a major product of testicular Leydig cells, is also expressed by the ovary but its functional role remains poorly understood. Here, we quantified expression of INSL3 and its receptor RXFP2 in theca interna (TIC) and granulosa (GC) compartments of developing bovine antral follicles and in corpora lutea (CL). INSL3 and RXFP2 mRNA levels were much higher in TIC than GC and increased progressively during follicle maturation with INSL3 peaking in large (11-18mm) estrogen-active follicles and RXFP2 peaking in 9-10mm follicles before declining in larger (11-18mm) follicles. Expression of both INSL3 and RXFP2 in CL was much lower than in TIC. In situ hybridization and immunohistochemistry confirmed abundant expression of INSL3 mRNA and protein in TIC. These observations indicate follicular TIC rather than CL as the primary site of both INSL3 production and action, implying a predominantly auto-/paracrine role in TIC. To corroborate the above findings, we showed that in vitro exposure of TIC to a luteinizing concentration of LH greatly attenuated expression of both INSL3 and its receptor while increasing progesterone secretion and expression of STAR and CYP11A1. Moreover, in vivo, a significant cyclic variation in plasma INSL3 was observed during synchronized estrous cycles. INSL3 and estradiol-17β followed a similar pattern, both increasing after luteolysis, before falling sharply after the LH surge. Thus, theca-derived INSL3, likely from the dominant pre-ovulatory follicle, is detectable in peripheral blood of cattle and expression is down-regulated during luteinisation induced by the pre-ovulatory LH surge. Collectively, these findings underscore the likely role of INSL3 as an important intrafollicular modulator of TIC function/steroidogenesis, whilst raising doubts about its potential contribution to CL function.

Fractional order modeling of large three-dimensional RC networks

An incidence matrix analysis is used to model a three-dimensional network consisting of resistive and capacitive elements distributed across several interconnected layers. A systematic methodology for deriving a descriptor representation of the network with random allocation of the resistors and capacitors is proposed. Using a transformation of the descriptor representation into standard state-space form, amplitude and phase admittance responses of three-dimensional random RC networks are obtained. Such networks display an emergent behavior with a characteristic Jonscher-like response over a wide range of frequencies. A model approximation study of these networks is performed to infer the admittance response using integral and fractional order models. It was found that a fractional order model with only seven parameters can accurately describe the responses of networks composed of more than 70 nodes and 200 branches with 100 resistors and 100 capacitors. The proposed analysis can be used to model charge migration in amorphous materials, which may be associated to specific macroscopic or microscopic scale fractal geometrical structures in composites displaying a viscoelastic electromechanical response, as well as to model the collective responses of processes governed by random events described using statistical mechanics.