Coloring random graphs and maximizing local diversity

We study a variation of the graph coloring problem on random graphs of finite average connectivity. Given the number of colors, we aim to maximize the number of different colors at neighboring vertices (i.e. one edge distance) of any vertex. Two efficient algorithms, belief propagation and Walksat are adapted to carry out this task. We present experimental results based on two types of random graphs for different system sizes and identify the critical value of the connectivity for the algorithms to find a perfect solution. The problem and the suggested algorithms have practical relevance since various applications, such as distributed storage, can be mapped onto this problem.

DFIG machine design for maximizing power output based on surrogate optimization algorithm

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Statistical mechanics of mutual information maximization

An unsupervised learning procedure based on maximizing the mutual information between the outputs of two networks receiving different but statistically dependent inputs is analyzed (Becker S. and Hinton G., Nature, 355 (1992) 161). By exploiting a formal analogy to supervised learning in parity machines, the theory of zero-temperature Gibbs learning for the unsupervised procedure is presented for the case that the networks are perceptrons and for the case of fully connected committees.

The development of a modified dissolution method suitable for investigating powder mixtures

A novel dissolution method was developed, suitable for powder mixtures, based on the USP basket apparatus. The baskets were modified such that the powder mixtures were retained within the baskets and not dispersed, a potential difficulty that may arise when using conventional USP basket and paddle apparatus. The advantages of this method were that the components of the mixtures were maintained in close proximity, maximizing any drug:excipient interaction and leading to more linear dissolution profiles. Two weakly acidic model drugs, ibuprofen and acetaminophen, and a selection of pharmaceutical excipients, including potential dissolution-enhancing alkalizing agents, were chosen for investigation. Dissolution profiles were obtained for simple physical mixtures. The f1 fit factor values, calculated using pure drug as the reference material, demonstrated a trend in line with expectations, with several dissolution enhancers apparent for both drugs. Also, the dissolution rates were linear over substantial parts of the profiles. For both drugs, a rank order comparison between the f1 fit factor and calculated dissolution rate, obtained from the linear section of the dissolution profile, demonstrated a correlation using a significance level of P=0.05. The method was proven to be suitable for discriminating between the effects of excipients on the dissolution of the model drugs. The method design produced dissolution profiles where the dissolution rate was linear for a substantial time, allowing determination of the dissolution rate without mathematical transformation of the data. This method may be suitable as a preliminary excipient-screening tool in the drug formulation development process.

Optimization of facility location-allocation problem in customer-driven supply chain

This paper develops and applies an integrated multiple criteria decision making approach to optimize the facility location-allocation problem in the contemporary customer-driven supply chain. Unlike the traditional optimization techniques, the proposed approach, combining the analytic hierarchy process (AHP) and the goal programming (GP) model, considers both quantitative and qualitative factors, and also aims at maximizing the benefits of deliverer and customers. In the integrated approach, the AHP is used first to determine the relative importance weightings or priorities of alternative locations with respect to both deliverer oriented and customer oriented criteria. Then, the GP model, incorporating the constraints of system, resource, and AHP priority is formulated to select the best locations for setting up the warehouses without exceeding the limited available resources. In this paper, a real case study is used to demonstrate how the integrated approach can be applied to deal with the facility location-allocation problem, and it is proved that the integrated approach outperforms the traditional costbased approach.

Developing a decomposable measure of profit efficiency using DEA

In for-profit organizations efficiency measurement with reference to the potential for profit augmentation is particularly important as is its decomposition into technical, and allocative components. Different profit efficiency approaches can be found in the literature to measure and decompose overall profit efficiency. In this paper, we highlight some problems within existing approaches and propose a new measure of profit efficiency based on a geometric mean of input/output adjustments needed for maximizing profits. Overall profit efficiency is calculated through this efficiency measure and is decomposed into its technical and allocative components. Technical efficiency is calculated based on a non-oriented geometric distance function (GDF) that is able to incorporate all the sources of inefficiency, while allocative efficiency is retrieved residually. We also define a measure of profitability efficiency which complements profit efficiency in that it makes it possible to retrieve the scale efficiency of a unit as a component of its profitability efficiency. In addition, the measure of profitability efficiency allows for a dual profitability interpretation of the GDF measure of technical efficiency. The concepts introduced in the paper are illustrated using a numerical example.

Vector bending sensors based on fibre Bragg gratings inscribed by infrared femtosecond laser

A novel, direction-sensitive bending sensor based on an asymmetric fiber Bragg grating (FBG) inscribed by an infrared femtosecond laser was demonstrated. The technique is based on tight transverse confinement of the femto-inscribed structures and can be directly applied in conventional, untreated singlemode fibers. The FBG structure was inscribed by an amplified, titanium sapphire laser system. The grating cross-section was elongated along the direction of the laser beam with the transverse dimensions of approximately 1 by 2 μm. It was suggested that the sensitivity of the device can be improved by inscribing smaller spatial features and by implementing more complex grating designs aimed at maximizing the effect of strain.

Minimizing unsatisfaction in colourful neighbourhoods

Colouring sparse graphs under various restrictions is a theoretical problem of significant practical relevance. Here we consider the problem of maximizing the number of different colours available at the nodes and their neighbourhoods, given a predetermined number of colours. In the analytical framework of a tree approximation, carried out at both zero and finite temperatures, solutions obtained by population dynamics give rise to estimates of the threshold connectivity for the incomplete to complete transition, which are consistent with those of existing algorithms. The nature of the transition as well as the validity of the tree approximation are investigated.

Pre-conception care : current practice and methods of provision

This thesis examines the present provisions for pre-conception care and the views of the providers of services. Pre-conception care is seen by some clinicians and health educators as a means of making any necessary changes in life style, corrections to imbalances in the nutritional status of the prospective mother (and father) and the assessment of any medical problems, thus maximizing the likelihood of the normal development of the baby. Pre-conception care may be described as a service to bridge the gap between the family planning clinic and the first ante-natal booking appointment. There were three separate foci for the empirical research - the Foresight organisation (a charity which has pioneered pre-conception care in Britain); the pre-conception care clinic at the West London Hospital, Hammersmith; and the West Midlands Regional Health Authority. The six main sources of data were: twenty five clinicians operating Foresight pre-conception clinics, couples attending pre-conception clinics, committee members of the Foresight organisation, staff of the West London Hospital pre-conception clinic, Hammersmith, District Health Education Officers working in the West Midlands Regional Health Authority and the members of the Ante-Natal Care Action Group, a sub-group of the Regional Health Advisory Group on Health Promotion and Preventive Medicine. A range of research methods were adopted. These were as follows: questionnaires and report forms used in co-operation with the Foresight clinicians, interviews, participant observation discussions and informal meetings and, finally, literature and official documentation. The research findings illustrated that pre-conception care services provided at the predominantly private Foresight clinics were of a rather `ad hoc' nature. The type of provision varied considerably and clearly reflected the views held by its providers. The protocol which had been developed to assist in the standardization of results was not followed by the clinicians. The pre-conception service provided at the West London Hospital shared some similarities in its approach with the Foresight provision; a major difference was that it did not advocate the use of routine hair trace metal analysis. Interviews with District Health Education Officers and with members of the Ante Natal Care Action Group revealed a tentative and cautious approach to pre-conception care generally and to the Foresight approach in particular. The thesis concludes with a consideration of the future of pre-conception care and the prospects for the establishment of a comprehensive pre-conception care service.

Improving recombinant eukaryotic membrane protein yields in Pichia pastoris:the importance of codon optimization and clone selection

In the last 15 years, 80% of all recombinant proteins reported in the literature were produced in the bacterium, Escherichia coli, or the yeast, Pichia pastoris. Nonetheless, developing effective general strategies for producing recombinant eukaryotic membrane proteins in these organisms remains a particular challenge. Using a validated screening procedure together with accurate yield quantitation, we therefore wished to establish the critical steps contributing to high yields of recombinant eukaryotic membrane protein in P. pastoris. Whilst the use of fusion partners to generate chimeric constructs and directed mutagenesis have previously been shown to be effective in bacterial hosts, we conclude that this approach is not transferable to yeast. Rather, codon optimization and the preparation and selection of high-yielding P. pastoris clones are effective strategies for maximizing yields of human aquaporins.

Network lifetime maximization with cross-layer design in wireless sensor networks

This paper investigates a cross-layer design approach for minimizing energy consumption and maximizing network lifetime (NL) of a multiple-source and single-sink (MSSS) WSN with energy constraints. The optimization problem for MSSS WSN can be formulated as a mixed integer convex optimization problem with the adoption of time division multiple access (TDMA) in medium access control (MAC) layer, and it becomes a convex problem by relaxing the integer constraint on time slots. Impacts of data rate, link access and routing are jointly taken into account in the optimization problem formulation. Both linear and planar network topologies are considered for NL maximization (NLM). With linear MSSS and planar single-source and single-sink (SSSS) topologies, we successfully use Karush-Kuhn-Tucker (KKT) optimality conditions to derive analytical expressions of the optimal NL when all nodes are exhausted simultaneously. The problem for planar MSSS topology is more complicated, and a decomposition and combination (D&C) approach is proposed to compute suboptimal solutions. An analytical expression of the suboptimal NL is derived for a small scale planar network. To deal with larger scale planar network, an iterative algorithm is proposed for the D&C approach. Numerical results show that the upper-bounds of the network lifetime obtained by our proposed optimization models are tight. Important insights into the NL and benefits of cross-layer design for WSN NLM are obtained.

Adaptive congestion control of DSRC vehicle networks for collaborative road safety applications

Congestion control is critical for the provisioning of quality of services (QoS) over dedicated short range communications (DSRC) vehicle networks for road safety applications. In this paper we propose a congestion control method for DSRC vehicle networks at road intersection, with the aims of providing high availability and low latency channels for high priority emergency safety applications while maximizing channel utilization for low priority routine safety applications. In this method a offline simulation based approach is used to find out the best possible configurations of message rate and MAC layer backoff exponent (BE) for a given number of vehicles equipped with DSRC radios. The identified best configurations are then used online by an roadside access point (AP) for system operation. Simulation results demonstrated that this adaptive method significantly outperforms the fixed control method under varying number of vehicles. The impact of estimation error on the number of vehicles in the network on system level performance is also investigated.

Novel speech signal processing algorithms for high-accuracy classification of Parkinson's disease

There has been considerable recent research into the connection between Parkinson's disease (PD) and speech impairment. Recently, a wide range of speech signal processing algorithms (dysphonia measures) aiming to predict PD symptom severity using speech signals have been introduced. In this paper, we test how accurately these novel algorithms can be used to discriminate PD subjects from healthy controls. In total, we compute 132 dysphonia measures from sustained vowels. Then, we select four parsimonious subsets of these dysphonia measures using four feature selection algorithms, and map these feature subsets to a binary classification response using two statistical classifiers: random forests and support vector machines. We use an existing database consisting of 263 samples from 43 subjects, and demonstrate that these new dysphonia measures can outperform state-of-the-art results, reaching almost 99% overall classification accuracy using only ten dysphonia features. We find that some of the recently proposed dysphonia measures complement existing algorithms in maximizing the ability of the classifiers to discriminate healthy controls from PD subjects. We see these results as an important step toward noninvasive diagnostic decision support in PD.

Team working in intensive care:current evidence and future endeavors

Purpose of review: It has recently been argued that the future of intensive care medicine will rely on high quality management and teamwork. Therefore, this review takes an organizational psychology perspective to examine the most recent research on the relationship between teamwork, care processes, and patient outcomes in intensive care. Recent findings: Interdisciplinary communication within a team is crucial for the development of negotiated shared treatment goals and short-team patient outcomes. Interventions for maximizing team communication have received substantial interest in recent literature. Intensive care coordination is not a linear process, and intensive care teams often fail to discuss how to implement goals, trigger and align activities, or reflect on their performance. Despite a move toward interdisciplinary team working, clinical decision-making is still problematic and continues to be perceived as a top-down and authoritative process. The topic of team leadership in intensive care is underexplored and requires further research. Summary: Based on findings from the most recent research evidence in medicine and management, four principles are identified for improving the effectiveness of team working in intensive care: engender professional efficacy, create stable teams and leaders, develop trust and participative safety, and enable frequent team reflexivity.

Performance analysis of ONOE protocol - an IEEE 802.11 link adaptation algorithm

Link adaptation (LA) plays an important role in adapting an IEEE 802.11 network to wireless link conditions and maximizing its capacity. However, there is a lack of theoretic analysis of IEEE 802.11 LA algorithms. In this article, we propose a Markov chain model for an 802.11 LA algorithm (ONOE algorithm), aiming to identify the problems and finding the space of improvement for LA algorithms. We systematically model the impacts of frame corruption and collision on IEEE 802.11 network performance. The proposed analytic model was verified by computer simulations. With the analytic model, it can be observed that ONOE algorithm performance is highly dependent on the initial bit rate and parameter configurations. The algorithm may perform badly even under light channel congestion, and thus, ONOE algorithm parameters should be configured carefully to ensure a satisfactory system performance. Copyright © 2011 John Wiley & Sons, Ltd.