The 'direct costs' of livestock disease: The development of a system of models for the analysis of 30 endemic livestock diseases in Great Britain

The 'direct costs' attributable to 30 different endemic diseases of farm animals in Great Britain are estimated using a standardised method to construct a simple model for each disease that includes consideration of disease prevention and treatment costs. The models so far developed provide a basis for further analyses including cost-benefit analyses for the economic assessment of disease control options. The approach used reflects the inherent livestock disease information constraints, which limit the application of other economic analytical methods. It is a practical and transparent approach that is relatively easily communicated to veterinary scientists and policy makers. The next step is to develop the approach by incorporating wider economic considerations into the analyses in a way that will demonstrate to policy makers and others the importance of an economic perspective to livestock disease issues.

Transition metal-directed self-assembly of calix[4]arene based dithiocarbamate ligands

The transition metal-directed self-assembly of dithiocarbamate ligand functionalised upper and lower rim calix[4]arenes affords novel dimeric bimetallic bis(calix[4]arene) species as determined by a combination of analytical methods including X-ray crystallography. An exception is a zinc(II) dithiocarbamate upper rim calix[4]arene assembly which is monomeric in nature. Electrochemical investigations reveal the bimetallic copper(II) bis(calix[4]arene) systems can electrochemically sense dihydrogen phosphate and carboxylate anions via significant cathodic perturbations of the respective copper(II)/(III) dithiocarbamate oxidation wave.

A Gentle/S approach to robot assisted neuro-rehabilitation

Movement disorders (MD) include a group of neurological disorders that involve neuromotor systems. MD can result in several abnormalities ranging from an inability to move, to severe constant and excessive movements. Strokes are a leading cause of disability affecting largely the older people worldwide. Traditional treatments rely on the use of physiotherapy that is partially based on theories and also heavily reliant on the therapists training and past experience. The lack of evidence to prove that one treatment is more effective than any other makes the rehabilitation of stroke patients a difficult task. UL motor re-learning and recovery levels tend to improve with intensive physiotherapy delivery. The need for conclusive evidence supporting one method over the other and the need to stimulate the stroke patient clearly suggest that traditional methods lack high motivational content, as well as objective standardised analytical methods for evaluating a patient's performance and assessment of therapy effectiveness. Despite all the advances in machine mediated therapies, there is still a need to improve therapy tools. This chapter describes a new approach to robot assisted neuro-rehabilitation for upper limb rehabilitation. Gentle/S introduces a new approach on the integration of appropriate haptic technologies to high quality virtual environments, so as to deliver challenging and meaningful therapies to people with upper limb impairment in consequence of a stroke. The described approach can enhance traditional therapy tools, provide therapy "on demand" and can present accurate objective measurements of a patient's progression. Our recent studies suggest the use of tele-presence and VR-based systems can potentially motivate patients to exercise for longer periods of time. Two identical prototypes have undergone extended clinical trials in the UK and Ireland with a cohort of 30 stroke subjects. From the lessons learnt with the Gentle/S approach, it is clear also that high quality therapy devices of this nature have a role in future delivery of stroke rehabilitation, and machine mediated therapies should be available to patient and his/her clinical team from initial hospital admission, through to long term placement in the patient's home following hospital discharge.

Separation of oligosaccharides from caprine milk whey, prior to prebiotic evaluation

Milk oligosaccharides are believed to have beneficial biological properties. Caprine milk has a relatively high concentration of oligosaccharides in comparison to other ruminant milks and has the closest oligosaccharide profile to human milk. The first stage in recovering oligosaccharides from caprine milk whey, a by-product of cheese making, was accomplished by ultrafiltration to remove proteins and fat globules, leaving more than 97% of the initial carbohydrates, mainly lactose, in the permeate. The ultrafiltered permeate was further processed using a 1 kDa ‘tight’ ultrafiltration membrane, which retained less than 7% of the remaining lactose. The final retentate was fractionated by preparative scale molecular size exclusion chromatography, to yield 28 fractions, of which oligosaccharide-rich fractions were detected somewhere between fractions 9/10 to 16/17, suitable for functionality and gut health promotion testing. All fractions were evaluated for their oligosaccharide and carbohydrate profiles using three complementary analytical methods.

Evoked prior learning experience and approach to learning as predictors of academic achievement

Background. In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students’ perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. Aim. To investigate how students’ evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Sample. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. Method. A 77-item questionnaire was used to gather students’ self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. Results. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was not related to academic achievement, and teaching quality and conceptions of learning were only indirectly related to achievement. Conclusions. Research aimed at understanding how students experience their learning environment and how that experience relates to the quality of their learning needs to be conducted using a wider range of variables and more sophisticated analytical methods. In this study of one context, some of the relations found in earlier bivariate studies, and on which learning intervention strategies have been built, are not confirmed when more holistic teaching–learning contexts are analysed using multi-variable methods.

Raytracing simulation for predicting light pipe transmittance

Daylighting systems can offer energy savings primarily by reducing electric lighting usage. Accurate predictive models of daylighting system performances are crucial for effective design and implementation of this renewable energy technology. A comparative study of predictive methods was performed and the use of a commercial raytracing software program was validated as a method of predicting light pipe performance. Raytracing simulation was shown to more accurately predict transmission effi ciency than existing analytical methods.

Gut microbial activity, implications for health and disease: the potential role of metabolite analysis

Microbial metabolism of proteins and amino acids by human gut bacteria generates a variety of compounds including phenol, indole, and sulfur compounds and branched chain fatty acids, many of which have been shown to elicit a toxic effect on the lumen. Bacterial fermentation of amino acids and proteins occurs mainly in the distal colon, a site that is often fraught with symptoms from disorders including ulcerative colitis (UC) and colorectal cancer (CRC). In contrast to carbohydrate metabolism by the gut microbiota, proteolysis is less extensively researched. Many metabolites are low molecular weight, volatile compounds. This review will summarize the use of analytical methods to detect and identify compounds in order to elucidate the relationship between specific dietary proteinaceous substrates, their corresponding metabolites, and implications for gastrointestinal health.

When long-range zero-lag synchronization is feasible in cortical networks

Many studies have reported long-range synchronization of neuronal activity between brain areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 and 40–80 Hz, respectively. Several studies have reported synchrony with zero phase lag, which is remarkable considering the synaptic and conduction delays inherent in the connections between distant brain areas. This result has led to many speculations about the possible functional role of zero-lag synchrony, such as for neuronal communication, attention, memory, and feature binding. However, recent studies using recordings of single-unit activity and local field potentials report that neuronal synchronization may occur with non-zero phase lags. This raises the questions whether zero-lag synchrony can occur in the brain and, if so, under which conditions. We used analytical methods and computer simulations to investigate which connectivity between neuronal populations allows or prohibits zero-lag synchrony. We did so for a model where two oscillators interact via a relay oscillator. Analytical results and computer simulations were obtained for both type I Mirollo–Strogatz neurons and type II Hodgkin–Huxley neurons. We have investigated the dynamics of the model for various types of synaptic coupling and importantly considered the potential impact of Spike-Timing Dependent Plasticity (STDP) and its learning window. We confirm previous results that zero-lag synchrony can be achieved in this configuration. This is much easier to achieve with Hodgkin–Huxley neurons, which have a biphasic phase response curve, than for type I neurons. STDP facilitates zero-lag synchrony as it adjusts the synaptic strengths such that zero-lag synchrony is feasible for a much larger range of parameters than without STDP.

Mathematical solutions for electricity networks in a low carbon future

Smart meters are becoming more ubiquitous as governments aim to reduce the risks to the energy supply as the world moves toward a low carbon economy. The data they provide could create a wealth of information to better understand customer behaviour. However at the household, and even the low voltage (LV) substation level, energy demand is extremely volatile, irregular and noisy compared to the demand at the high voltage (HV) substation level. Novel analytical methods will be required in order to optimise the use of household level data. In this paper we briefly outline some mathematical techniques which will play a key role in better understanding the customer's behaviour and create solutions for supporting the network at the LV substation level.

A review of Islamic mutual funds’ financial performance and investment style in Muslim and non-Muslim countries

Islamic finance has grown beyond its reputation of providing small-scale banking options and now provides investment and financing options for complex large-scale commercial transactions. Islamic investments are one area that has attracted the attention of investors due to its performance, especially during the economic downturn. The Shari’ah compliance nature of Islamic funds provides an opportunity for those Muslim investors to be part of the global investment sector who have previously been reluctant to invest in conventional mutual funds. The fact that the funds’ managers are prohibited from investing in activities such as weapons production, alcohol production and interest-bearing finance operations, makes Islamic mutual funds also attractive for those Non-Muslim investors who wish to invest ethically. Today there are hundreds of Islamic equity indices offered by Dow Jones, FTSE, MSCI and S&P. Despite the growing importance of Islamic funds, there have been limited studies exploring the performance of Islamic funds worldwide. Due to very limited data sets and not too rigorous analytical methods, these existent studies have neither investigated Islamic funds’ financial performance in noticeable detail nor analysed the investment style of more than six funds. For instance, relevant questions such as the financial performance of Islamic mutual funds’ beyond their investment styles or a difference in performance between funds from Muslim and non-Muslim countries have nearly not been investigated at all. Very recently, a study by Hoepner, Rammal and Rezec (2011) analysed the financial performance and investment style of 262 Islamic equity funds from 20 countries in five regions (Africa, Asia-Pacific, Europe, Gulf Cooperative Council-GCC, and North America). As comparison, previous studies did not even analyse 60 funds. Hoepner et al.’s study sampled a period of two decades and was therefore able to test the performance of the funds during economic booms as well as economic downturns. The findings of the study provide new insights into the performance of Islamic mutual funds in Muslim and Western markets and during financial crisis.

Large deviations of Rouse polymer chain: first passage problem

The purpose of this paper is to investigate several analytical methods of solving first passage (FP) problem for the Rouse model, a simplest model of a polymer chain. We show that this problem has to be treated as a multi-dimensional Kramers' problem, which presents rich and unexpected behavior. We first perform direct and forward-flux sampling (FFS) simulations, and measure the mean first-passage time $\tau(z)$ for the free end to reach a certain distance $z$ away from the origin. The results show that the mean FP time is getting faster if the Rouse chain is represented by more beads. Two scaling regimes of $\tau(z)$ are observed, with transition between them varying as a function of chain length. We use these simulations results to test two theoretical approaches. One is a well known asymptotic theory valid in the limit of zero temperature. We show that this limit corresponds to fully extended chain when each chain segment is stretched, which is not particularly realistic. A new theory based on the well known Freidlin-Wentzell theory is proposed, where dynamics is projected onto the minimal action path. The new theory predicts both scaling regimes correctly, but fails to get the correct numerical prefactor in the first regime. Combining our theory with the FFS simulations lead us to a simple analytical expression valid for all extensions and chain lengths. One of the applications of polymer FP problem occurs in the context of branched polymer rheology. In this paper, we consider the arm-retraction mechanism in the tube model, which maps exactly on the model we have solved. The results are compared to the Milner-McLeish theory without constraint release, which is found to overestimate FP time by a factor of 10 or more.