Signaling mechanisms of GPCR ligands

G protein-coupled receptors constitute one of the major classes of drug targets, so understanding the mechanisms of signaling through these receptors is of great importance. This review covers some of the recent advances in G protein-coupled receptor signaling. A high resolution structure of the beta(2)-adrenergic receptor has been reported, as well as several molecular switches involved in receptor activation. It has also been realised that receptors and G proteins and their subunits may not always separate upon receptor activation. The definition of the ability of these receptors to signal has been expanded considerably with the realisation that some signaling may occur independently of G proteins, that some signaling events may differ in their pharmacological profiles and that formation of heterodimers of these receptors may provide new avenues for both signaling and drug design.

Polymer-drug conjugates: current status and future trends

Polymer conjugates are nano-sized, multicomponent constructs already in the clinic as anticancer compounds, both as single agents or as elements of combinations. They have the potential to improve pharmacological therapy of a variety of solid tumors. Polymer-drug conjugation promotes passive tumor targeting by the enhanced permeability and retention (EPR) effect and allows for lysosomotropic drug delivery following endocytic capture. In the first part of this review, we analyze the promising results arising from clinical trials of polymer-bound chemotherapy. The experience gained on these studies provides the basis for the development of a more sophisticated second-generation of polymer conjugates. However, many challenges still lay ahead providing scope to develop and refine this field. The "technology platform'' of polymer therapeutics allows the development of both new and exciting polymeric materials, the incorporation of novel bioactive agents and combinations thereof to address recent advances in drug therapy. The rational design of polymer drug conjugates is expected to realize the true potential of these "nanomedicines".

Cognitive therapy for anxiety disorders: current status and future directions.

This paper reviews recent theoretical, conceptual and practice developments in cognitive-behaviour therapy (CBT) for anxiety disorders. The empirical status of CBT for anxiety disorders is reviewed and recent advances in the field are outlined. Challenges for the future development of CBT for the anxiety disorders are examined in relation to the efficacy, effectiveness and cost-effectiveness of the approach. It is concluded that the major challenge currently facing CBT for anxiety disorders in the UK is how to meet the increased demand for provision whilst maintaining high levels of efficacy and effectiveness. It is suggested that the creation of an evidence base for the dissemination of CBT needs to become a priority for empirical investigation in order effectively to expand the provision of CBT for anxiety disorders.

Landscape of intelligent cores: An autonomic multi-agent approach for space application

Space applications are challenged by the reliability of parallel computing systems (FPGAs) employed in space crafts due to Single-Event Upsets. The work reported in this paper aims to achieve self-managing systems which are reliable for space applications by applying autonomic computing constructs to parallel computing systems. A novel technique, 'Swarm-Array Computing' inspired by swarm robotics, and built on the foundations of autonomic and parallel computing is proposed as a path to achieve autonomy. The constitution of swarm-array computing comprising for constituents, namely the computing system, the problem / task, the swarm and the landscape is considered. Three approaches that bind these constituents together are proposed. The feasibility of one among the three proposed approaches is validated on the SeSAm multi-agent simulator and landscapes representing the computing space and problem are generated using the MATLAB.

Intelligent agents: are they feasible in swarm-array computing?

The work reported in this paper proposes 'Intelligent Agents', a Swarm-Array computing approach focused to apply autonomic computing concepts to parallel computing systems and build reliable systems for space applications. Swarm-array computing is a robotics a swarm robotics inspired novel computing approach considered as a path to achieve autonomy in parallel computing systems. In the intelligent agent approach, a task to be executed on parallel computing cores is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and can be seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-* objectives of autonomic computing. The approach is validated on a multi-agent simulator.

Developments in block copolymer science and technology

Focuses on recent advances in research on block copolymers, covering chemistry (synthesis), physics (phase behaviors, rheology, modeling), and applications (melts and solutions). Written by a team of internationally respected scientists from industry and academia, this text compiles and reviews the expanse of research that has taken place over the last five years into one accessible resource. Ian Hamley is the world-leading scientist in the field of block copolymer research Presents the recent advances in the area, covering chemistry, physics and applications. Provides a broad coverage from synthesis to fundamental physics through to applications Examines the potential of block copolymers in nanotechnology as self-assembling soft materials

A phosphorus analogue of Bis(eta(4)-cyclobutadiene)iron(0)

Iron is a pivotal element in organometallic chemistry, enabling fundamental insights with high-impact applications.[1] Ferrocene derivatives have countless uses,[2] and the recent advances in iron catalysis are equally impressive.[3]

Achieving whole-life value: The challenges of service-led construction

Major construction clients are increasingly looking to procure built facilities on the basis of added value, rather than capital cost. Recent advances in the procurement of construction projects have emphasised a whole-life value approach to meeting the client’s objectives, with strategies put in place to encourage long-term commitment and through-life service provision. Construction firms are therefore increasingly required to take on responsibility for the operation and maintenance of the construction project on the client’s behalf - with the emphasis on value and service. This inevitably throws up a host of challenges, not the least of which is the need for construction firms to manage and accommodate the new emphasis on service. Indeed, these ‘service-led’ projects represent a new realm of construction projects where the rationale for the project is driven by client’s objectives with some aspect of service provision. This vision of downstream service delivery increases the number of stakeholders, adds to project complexity and challenges deeply-ingrained working practices. Ultimately it presents a major challenge for the construction sector. This paper sets out to unravel some of the many implications that this change brings with it. It draws upon ongoing research investigating how construction firms can adapt to a more service-orientated built environment and add value in project-based environments. The conclusions lay bare the challenges that firms face when trying to compete on the basis of added-value and service delivery. In particular, how it affects deeply-ingrained working practices and established relationships in the sector.

Measuring departures from Hardy-Weinberg: a Markov chain Monte Carlo method for estimating the inbreeding coefficient

Many well-established statistical methods in genetics were developed in a climate of severe constraints on computational power. Recent advances in simulation methodology now bring modern, flexible statistical methods within the reach of scientists having access to a desktop workstation. We illustrate the potential advantages now available by considering the problem of assessing departures from Hardy-Weinberg (HW) equilibrium. Several hypothesis tests of HW have been established, as well as a variety of point estimation methods for the parameter which measures departures from HW under the inbreeding model. We propose a computational, Bayesian method for assessing departures from HW, which has a number of important advantages over existing approaches. The method incorporates the effects-of uncertainty about the nuisance parameters--the allele frequencies--as well as the boundary constraints on f (which are functions of the nuisance parameters). Results are naturally presented visually, exploiting the graphics capabilities of modern computer environments to allow straightforward interpretation. Perhaps most importantly, the method is founded on a flexible, likelihood-based modelling framework, which can incorporate the inbreeding model if appropriate, but also allows the assumptions of the model to he investigated and, if necessary, relaxed. Under appropriate conditions, information can be shared across loci and, possibly, across populations, leading to more precise estimation. The advantages of the method are illustrated by application both to simulated data and to data analysed by alternative methods in the recent literature.

Normality mining: privacy implications of behavioral profiles drawn from GPS enabled mobile phones

There is growing interest in the ways in which the location of a person can be utilized by new applications and services. Recent advances in mobile technologies have meant that the technical capability to record and transmit location data for processing is appearing in off-the-shelf handsets. This opens possibilities to profile people based on the places they visit, people they associate with, or other aspects of their complex routines determined through persistent tracking. It is possible that services offering customized information based on the results of such behavioral profiling could become commonplace. However, it may not be immediately apparent to the user that a wealth of information about them, potentially unrelated to the service, can be revealed. Further issues occur if the user agreed, while subscribing to the service, for data to be passed to third parties where it may be used to their detriment. Here, we report in detail on a short case study tracking four people, in three European member states, persistently for six weeks using mobile handsets. The GPS locations of these people have been mined to reveal places of interest and to create simple profiles. The information drawn from the profiling activity ranges from intuitive through special cases to insightful. In this paper, these results and further extensions to the technology are considered in light of European legislation to assess the privacy implications of this emerging technology.

Bayesian estimation of the spatial Durbin error model with an application to voter turnout in the 2004 presidential election

The potential for spatial dependence in models of voter turnout, although plausible from a theoretical perspective, has not been adequately addressed in the literature. Using recent advances in Bayesian computation, we formulate and estimate the previously unutilized spatial Durbin error model and apply this model to the question of whether spillovers and unobserved spatial dependence in voter turnout matters from an empirical perspective. Formal Bayesian model comparison techniques are employed to compare the normal linear model, the spatially lagged X model (SLX), the spatial Durbin model, and the spatial Durbin error model. The results overwhelmingly support the spatial Durbin error model as the appropriate empirical model.

Energy consumption feedback in perspective: integrating Australian data to meta-analyses on in home displays

Providing homeowners with real-time feedback on their electricity consumption through a dedicated display device has been shown to reduce consumption by approximately 6-10%. However, recent advances in smart grid technology have enabled larger sample sizes and more representative sample selection and recruitment methods for display trials. By analyzing these factors using data from current studies, this paper argues that a realistic, large-scale conservation effect from feedback is in the range of 3-5%. Subsequent analysis shows that providing real-time feedback may not be a cost effective strategy for reducing carbon emissions in Australia, but that it may enable additional benefits such as customer retention and peak-load shift.