Nutrient regulation of pancreatic beta-cell function in diabetes: problems and potential solutions

increasing prevalence of obesity combined with longevity will produce an epidemic of Type 2 (non-insulin-dependent) diabetes in the next 20 years. This. disease is associated with defects in insulin secretion, specifically abnormalities of insulin secretory kinetics and pancreatic beta-cell glucose responsiveness. Mechanisms underlying beta-cell dysfunction include glucose toxicity, lipotoxicity and beta-cell hyperactivity. Defects at various sites in beta-cell signal transduction pathways contribute, but no single lesion can account for the common form of Type 2 diabetes. Recent studies highlight diverse beta-cell actions of GLP-1 (glucagon-like peptide-1) and GIP (glucose-dependent insulinotropic polypeptide). These intestinal hormones target the beta-cell to stimulate glucose-dependent insulin secretion through activation of protein kinase A and associated pathways. Both increase gene expression and proinsulin biosynthesis, protect against apoptosis and stimulate replication/neogenesis of beta-cells. Incretin hormones therefore represent an exciting future multi-action solution to correct beta-cell defect in Type 2 diabetes.

Investigation of Utilizing Single Surface Depressions in Optimization of NLF Aerofoil Design

An environment has been created for the optimisation of aerofoil profiles with inclusion of small surface features. For TS wave dominated flows, the paper examines the consequences of the addition of a depression on the aerodynamic optimisation of an NLF aerofoil, and describes the geometry definition fidelity and optimisation algorithm employed in the development process. The variables that define the depression for this optimisation investigation have been fixed, however a preliminary study is presented demonstrating the sensitivity of the flow to the depression characteristics. Solutions to the optimisation problem are then presented using both gradient-based and genetic algorithm techniques, and for accurate representation of the inclusion of small surface perturbations it is concluded that a global optimisation method is required for this type of aerofoil optimisation task due to the nature of the response surface generated. When dealing with surface features, changes in the transition onset are likely to be of a non-linear nature so it is highly critical to have an optimisation algorithm that is robust, suggesting that for this framework, gradient-based methods alone are not suited.

A Hybrid Swarm Based Approach in Addressing University Timetabling Problems

This paper is concerned with the application of an automated hybrid approach in addressing the university timetabling problem. The approach described is based on the nature-inspired artificial bee colony (ABC) algorithm. An ABC algorithm is a biologically-inspired optimization approach, which has been widely implemented in solving a range of optimization problems in recent years such as job shop scheduling and machine timetabling problems. Although the approach has proven to be robust across a range of problems, it is acknowledged within the literature that there currently exist a number of inefficiencies regarding the exploration and exploitation abilities. These inefficiencies can often lead to a slow convergence speed within the search process. Hence, this paper introduces a variant of the algorithm which utilizes a global best model inspired from particle swarm optimization to enhance the global exploration ability while hybridizing with the great deluge (GD) algorithm in order to improve the local exploitation ability. Using this approach, an effective balance between exploration and exploitation is attained. In addition, a traditional local search approach is incorporated within the GD algorithm with the aim of further enhancing the performance of the overall hybrid method. To evaluate the performance of the proposed approach, two diverse university timetabling datasets are investigated, i.e., Carter's examination timetabling and Socha course timetabling datasets. It should be noted that both problems have differing complexity and different solution landscapes. Experimental results demonstrate that the proposed method is capable of producing high quality solutions across both these benchmark problems, showing a good degree of generality in the approach. Moreover, the proposed method produces best results on some instances as compared with other approaches presented in the literature.

A Hybrid Imperialist Approach in Solving University Timetabling Problems. Information Sciences. Vol. 283, 1-21

Generating timetables for an institution is a challenging and time consuming task due to different demands on the overall structure of the timetable. In this paper, a new hybrid method which is a combination of a great deluge and artificial bee colony algorithm (INMGD-ABC) is proposed to address the university timetabling problem. Artificial bee colony algorithm (ABC) is a population based method that has been introduced in recent years and has proven successful in solving various optimization problems effectively. However, as with many search based approaches, there exist weaknesses in the exploration and exploitation abilities which tend to induce slow convergence of the overall search process. Therefore, hybridization is proposed to compensate for the identified weaknesses of the ABC. Also, inspired from imperialist competitive algorithms, an assimilation policy is implemented in order to improve the global exploration ability of the ABC algorithm. In addition, Nelder–Mead simplex search method is incorporated within the great deluge algorithm (NMGD) with the aim of enhancing the exploitation ability of the hybrid method in fine-tuning the problem search region. The proposed method is tested on two differing benchmark datasets i.e. examination and course timetabling datasets. A statistical analysis t-test has been conducted and shows the performance of the proposed approach as significantly better than basic ABC algorithm. Finally, the experimental results are compared against state-of-the art methods in the literature, with results obtained that are competitive and in certain cases achieving some of the current best results to those in the literature.

Distribution-based adaptive bounding genetic algorithm for continuous optimisation problems

A new search-space-updating technique for genetic algorithms is proposed for continuous optimisation problems. Other than gradually reducing the search space during the evolution process with a fixed reduction rate set ‘a priori’, the upper and the lower boundaries for each variable in the objective function are dynamically adjusted based on its distribution statistics. To test the effectiveness, the technique is applied to a number of benchmark optimisation problems in comparison with three other techniques, namely the genetic algorithms with parameter space size adjustment (GAPSSA) technique [A.B. Djurišic, Elite genetic algorithms with adaptive mutations for solving continuous optimization problems – application to modeling of the optical constants of solids, Optics Communications 151 (1998) 147–159], successive zooming genetic algorithm (SZGA) [Y. Kwon, S. Kwon, S. Jin, J. Kim, Convergence enhanced genetic algorithm with successive zooming method for solving continuous optimization problems, Computers and Structures 81 (2003) 1715–1725] and a simple GA. The tests show that for well-posed problems, existing search space updating techniques perform well in terms of convergence speed and solution precision however, for some ill-posed problems these techniques are statistically inferior to a simple GA. All the tests show that the proposed new search space update technique is statistically superior to its counterparts.

Comparisons of plankton at 59 degrees N and 37 degrees N during two Lagrangian drift experiments in the North Atlantic in June and July 1996

Data are summarised for two Lagrangian experiments in the North Atlantic in early summer 1996. At 59 degreesN 20 degreesW, plankton dynamics was studied in an SF, tracer release experiment within a mesoscale eddy over a 9-day period. At 37 degreesN 20 degreesW, a second experiment followed a drifting buoy for 7 days. The data obtained in these two experiments have been averaged for 3 depth strata; the euphotic zone, the surface mixed layer (SML), and the seasonal thermocline immediately beneath the surface mixed layer. At 59 degreesN, the euphotic zone was only marginally deeper than the SML, but at 37 degreesN the SML was ca 30 m and the euphotic depth was ca 110 m. At 37 degreesN, nutrient concentrations in the SML were low but significant new production occurred in the thermocline because of light penetration into the nutricline. The particulate organic carbon (POC) concentration of the SML at 59 degreesN was 13-15 mu mol C kg(-1), but at 37 degreesN POC concentrations were 4 mu mol C kg(-1). These POC measurements include biota and detritus. As a way of investigating latitudinal differences in the plankton communities, estimates have been made of the carbon and nitrogen content of phytoplankton, bacterioplankton, microzooplankton and mesozooplankton. At both 59 degreesN and 37 degreesN, phytoplankton was the largest component, accounting for ca 50% of the planktonic biomass in the SML. At 59 degreesN, microzooplankton was 16% of the planktonic carbon, but at 37 degreesN this reduced to 8% of the total. Mesozooplankton was a relatively constant proportion (ca 20%) of the planktonic carbon in the SML at both 59 degreesN and 37 degreesN. Bacterioplankton was 14% of the biomass at 59 degreesN, increasing to 24% in the microbial loop-dominated system at 37 degreesN. Mean carbon fixation rate in the oligotrophic southern station was 24% of that at the north, with more carbon fixation below the SML at 37 degreesN than at 59 degreesN. Respiration rates showed little variation with latitude, and the rates at 37 degreesN were 80% of those at 59 degreesN. Nitrate and ammonium uptake rates were very low in the oligotrophic conditions in the SML at 37 degreesN, but nitrate uptake in the euphotic zone was comparable to that at 59 degreesN. Ammonium uptake by phytoplankton was also significantly greater at 37 degreesN, in both the euphotic zone and thermocline, but uptake in the SML was only 20% of that in the SML at 59 degreesN. (C) 2001 Elsevier Science Ltd. All rights reserved.

Surrogate-Based Optimization Using Multifidelity Models with Variable Parameterization and Corrected Space Mapping

Surrogate-based-optimization methods provide a means to achieve high-fidelity design optimization at reduced computational cost by using a high-fidelity model in combination with lower-fidelity models that are less expensive to evaluate. This paper presents a provably convergent trust-region model-management methodology for variableparameterization design models: that is, models for which the design parameters are defined over different spaces. Corrected space mapping is introduced as a method to map between the variable-parameterization design spaces. It is then used with a sequential-quadratic-programming-like trust-region method for two aerospace-related design optimization problems. Results for a wing design problem and a flapping-flight problem show that the method outperforms direct optimization in the high-fidelity space. On the wing design problem, the new method achieves 76% savings in high-fidelity function calls. On a bat-flight design problem, it achieves approximately 45% time savings, although it converges to a different local minimum than did the benchmark.

Optimization through quantum annealing: theory and some applications

Quantum annealing is a promising tool for solving optimization problems, similar in some ways to the traditional ( classical) simulated annealing of Kirkpatrick et al. Simulated annealing takes advantage of thermal fluctuations in order to explore the optimization landscape of the problem at hand, whereas quantum annealing employs quantum fluctuations. Intriguingly, quantum annealing has been proved to be more effective than its classical counterpart in many applications. We illustrate the theory and the practical implementation of both classical and quantum annealing - highlighting the crucial differences between these two methods - by means of results recently obtained in experiments, in simple toy-models, and more challenging combinatorial optimization problems ( namely, Random Ising model and Travelling Salesman Problem). The techniques used to implement quantum and classical annealing are either deterministic evolutions, for the simplest models, or Monte Carlo approaches, for harder optimization tasks. We discuss the pro and cons of these approaches and their possible connections to the landscape of the problem addressed.

Inter-professional working in child protection with families with long-term and complex needs

Within the United Kingdom there is growing awareness of the need to identify and support the small number of children who are living in families experiencing multiple problems. Research indicates that adverse experiences in childhood can result in poor outcomes in adulthood in terms of lack of employment, poorer physical and mental health and increases in social problems experienced. It is acknowledged that most of these children are known to child welfare professionals and that some are referred to social services, subsequently entering the child protection system. This paper reports research conducted with twenty-eight experienced child welfare professionals. It explores their views about families known to the child protection system with long-term and complex needs in relation to the characteristics of children and their families; the process of intervention with families; and the effects of organisational arrangements on practice. The research indicates that these families are characterised by the range and depth of the problems experienced by the adults, such as domestic violence, mental health difficulties and substance misuse problems, and the need for professionals to have good inter-personal skills and access to specialist therapeutic services if families are to be supported to address their problems.

A critical review of some recent developments in quantitative research on gender and achievement in the United Kingdom

Over recent years the findings of a number of quantitative research studies have been published in the UK on gender and achievement. Much of this work has emanated from Stephen Gorard and his colleagues and has not only been highly critical of existing approaches to handling quantitative data but has also suggested a number of alternative and, what they claim to be, more valid ways of measuring differential patterns of achievement and underachievement between groups. This article shows how much of this work has been based upon rather under-developed measures of achievement and underachievement that tend, in turn, to generate a number of misleading findings that have questionable implications for practice. It will be argued that this body of work provides a useful case study in the problems of quantitative research that fails to engage adequately with the substantive theoretical and empirical literature and considers some of the implications of this for future research in this area.

Effects of the Interaction Between Reaction Component of Personal Need for Structure and Role Perceptions on Employee Attitudes in Long-Term Care for Elderly People

This study examined the interaction of reaction component of personal need for structure (reaction to lack of structure, RLS) and role perceptions in predicting job satisfaction, job involvement, affective commitment, and occupational identity among employees working in long-term care for elderly people. High-RLS employees experienced more role conflict, had less job satisfaction, and experienced lower levels of occupational identity than did low-RLS employees. We found individual differences in how problems in roles affected employees' job attitudes. High-RLS employees experienced lower levels of job satisfaction, job involvement, and affective commitment, irrespective of role-conflict levels. Low-RLS employees experienced detrimental job attitudes only if role-conflict levels were high. Our results suggest that high-RLS people benefit less from low levels of experienced role conflicts.

Power allocation strategies across N orthogonal channels for single-relay networks at both source and relay

We consider a wireless relay network with one source, one relay and one destination, where communications between nodes are preformed over N orthogonal channels. This, for example, is the case when orthogonal frequency division multiplexing is employed for data communications. Since the power available at the source and relay is limited, we study optimal power allocation strategies at the source and relay in order to maximize the overall source-destination capacity. Depending on the availability of the channel state information at both the source and relay or only at the relay, power allocation is performed at both the source and relay or only at the relay. Considering different setups for the problem, various optimization problems are formulated and solved. Some properties of the optimal solution are also proved.

A pilot study of a family focused, psychosocial intervention with war-exposed youth at risk of attack and abduction in north-eastern Democratic Republic of Congo

Rural communities in the Haut-Uele Province of northern Democratic Republic of Congo live in constant danger of attack and/or abduction by units of the Lord's Resistance Army operating in the region. This pilot study sought to develop and evaluate a community-participative psychosocial intervention involving life skills and relaxation training and Mobile Cinema screenings with this war-affected population living under current threat. 159 war-affected children and young people (aged 7-18) from the villages of Kiliwa and Li-May in north-eastern DR Congo took part in this study. In total, 22% of participants had been abduction previously while 73% had a family member abducted. Symptoms of post-traumatic stress reactions, internalising problems, conduct problems and pro-social behaviour were assessed by blinded interviewers at pre- and post-intervention and at 3-month follow-up. Participants were randomised (with an accompanying caregiver) to 8 sessions of a group-based, community-participative, psychosocial intervention (n=79) carried out by supervised local, lay facilitators or a wait-list control group (n=80). Average seminar attendance rates were high: 88% for participants and 84% for caregivers. Drop-out was low: 97% of participants were assessed at post-intervention and 88% at 3 month follow-up. At post-test, participants reported significantly fewer symptoms of post-traumatic stress reactions compared to controls (Cohen's d=0.40). At 3 month follow up, large improvements in internalising symptoms and moderate improvements in pro-social scores were reported, with caregivers noting a moderate to large decline in conduct problems among the young people. Trial Registration clinicalTrials.gov, Identifier: NCT01542398.

A hybrid harmony search with arithmetic crossover operation for economic dispatch

Economic dispatch (ED) problems often exhibit non-linear, non-convex characteristics due to the valve point effects. Further, various constraints and factors, such as prohibited operation zones, ramp rate limits and security constraints imposed by the generating units, and power loss in transmission make it even more challenging to obtain the global optimum using conventional mathematical methods. Meta-heuristic approaches are capable of solving non-linear, non-continuous and non-convex problems effectively as they impose no requirements on the optimization problems. However, most methods reported so far mainly focus on a specific type of ED problems, such as static or dynamic ED problems. This paper proposes a hybrid harmony search with arithmetic crossover operation, namely ACHS, for solving five different types of ED problems, including static ED with valve point effects, ED with prohibited operating zones, ED considering multiple fuel cells, combined heat and power ED, and dynamic ED. In this proposed ACHS, the global best information and arithmetic crossover are used to update the newly generated solution and speed up the convergence, which contributes to the algorithm exploitation capability. To balance the exploitation and exploration capabilities, the opposition based learning (OBL) strategy is employed to enhance the diversity of solutions. Further, four commonly used crossover operators are also investigated, and the arithmetic crossover shows its efficiency than the others when they are incorporated into HS. To make a comprehensive study on its scalability, ACHS is first tested on a group of benchmark functions with a 100 dimensions and compared with several state-of-the-art methods. Then it is used to solve seven different ED cases and compared with the results reported in literatures. All the results confirm the superiority of the ACHS for different optimization problems.

Efficient Processing of Spatial Group Keyword Queries

With the proliferation of geo-positioning and geo-tagging techniques, spatio-textual objects that possess both a geographical location and a textual description are gaining in prevalence, and spatial keyword queries that exploit both location and textual description are gaining in prominence. However, the queries studied so far generally focus on finding individual objects that each satisfy a query rather than finding groups of objects where the objects in a group together satisfy a query.

We define the problem of retrieving a group of spatio-textual objects such that the group's keywords cover the query's keywords and such that the objects are nearest to the query location and have the smallest inter-object distances. Specifically, we study three instantiations of this problem, all of which are NP-hard. We devise exact solutions as well as approximate solutions with provable approximation bounds to the problems. In addition, we solve the problems of retrieving top-k groups of three instantiations, and study a weighted version of the problem that incorporates object weights. We present empirical studies that offer insight into the efficiency of the solutions, as well as the accuracy of the approximate solutions.