Evaluating the intonation of non-native speakers of English using a computerised test battery

This study investigates the intonation of Chinese and Arabic learners of English using the computerized test battery Profiling Elements of Prosody for Speech and Communication (PEPS-C). The aims were to ascertain which aspects of intonation are difficult for these learners, and to determine whether PEPS-C can be used to assess the intonation of adult learners. Although some results were significantly different from native-speaker data, raw scores showed that the learner groups performed well in most tasks, which may indicate that the learners' level is too high for the PEPS-C to be useful. However, the PEPS-C did reveal that Arabic learners performed significantly worse at contrastive stress placement, and Chinese learners performed significantly worse assessing likes and dislikes.

Early identification of stimulant treatment responders, partial responders and non-responders using objective measures in children and adolescents with hyperkinetic disorder

Background: The aim of this study was to evaluate stimulant medication response following a single dose of methylphenidate (MPH) in children and young people with hyperkinetic disorder using infrared motion analysis combined with a continuous performance task (QbTest system) as objective measures. The hypothesis was put forward that a moderate testdose of stimulant medication could determine a robust treatment response, partial response and non-response in relation to activity, attention and impulse control measures. Methods: The study included 44 children and young people between the ages of 7-18 years with a diagnosis of hyperkinetic disorder (F90 & F90.1). A single dose-protocol incorporated the time course effects of both immediate release MPH and extended release MPH (Concerta XL, Equasym XL) to determine comparable peak efficacy periods post intake. Results: A robust treatment response with objective measures reverting to the population mean was found in 37 participants (84%). Three participants (7%) demonstrated a partial response to MPH and four participants (9%) were determined as non-responders due to deteriorating activity measures together with no improvements in attention and impulse control measures. Conclusion: Objective measures provide early into prescribing the opportunity to measure treatment response and monitor adverse reactions to stimulant medication. Most treatment responders demonstrated an effective response to MPH on a moderate testdose facilitating a swift and more optimal titration process.

Neurofuzzy control using Kalman filtering state feedback with coloured noise for unknown non-linear processes

This paper presents a controller design scheme for a priori unknown non-linear dynamical processes that are identified via an operating point neurofuzzy system from process data. Based on a neurofuzzy design and model construction algorithm (NeuDec) for a non-linear dynamical process, a neurofuzzy state-space model of controllable form is initially constructed. The control scheme based on closed-loop pole assignment is then utilized to ensure the time invariance and linearization of the state equations so that the system stability can be guaranteed under some mild assumptions, even in the presence of modelling error. The proposed approach requires a known state vector for the application of pole assignment state feedback. For this purpose, a generalized Kalman filtering algorithm with coloured noise is developed on the basis of the neurofuzzy state-space model to obtain an optimal state vector estimation. The derived controller is applied in typical output tracking problems by minimizing the tracking error. Simulation examples are included to demonstrate the operation and effectiveness of the new approach.

Hierarchical control and optimisation of the Tennessee Eastman process

Based on integrated system optimisation and parameter estimation a method is described for on-line steady state optimisation which compensates for model-plant mismatch and solves a non-linear optimisation problem by iterating on a linear - quadratic representation. The method requires real process derivatives which are estimated using a dynamic identification technique. The utility of the method is demonstrated using a simulation of the Tennessee Eastman benchmark chemical process.

Replication enhancer elements within the open reading frame of tick-borne encephalitis virus and their evolution within the Flavivirus genus

We provide experimental evidence of a replication enhancer element (REE) within the capsid gene of tick-borne encephalitis virus (TBEV, genus Flavivirus). Thermodynamic and phylogenetic analyses predicted that the REE folds as a long stable stem–loop (designated SL6), conserved among all tick-borne flaviviruses (TBFV). Homologous sequences and potential base pairing were found in the corresponding regions of mosquito-borne flaviviruses, but not in more genetically distant flaviviruses. To investigate the role of SL6, nucleotide substitutions were introduced which changed a conserved hexanucleotide motif, the conformation of the terminal loop and the base-paired dsRNA stacking. Substitutions were made within a TBEV reverse genetic system and recovered mutants were compared for plaque morphology, single-step replication kinetics and cytopathic effect. The greatest phenotypic changes were observed in mutants with a destabilized stem. Point mutations in the conserved hexanucleotide motif of the terminal loop caused moderate virus attenuation. However, all mutants eventually reached the titre of wild-type virus late post-infection. Thus, although not essential for growth in tissue culture, the SL6 REE acts to up-regulate virus replication. We hypothesize that this modulatory role may be important for TBEV survival in nature, where the virus circulates by non-viraemic transmission between infected and non-infected ticks, during co-feeding on local rodents.

Occupants’ behavioural adaptation in workplaces with non-central heating and cooling systems

Occupants’ behaviour when improving the indoor environment plays a significant role in saving energy in buildings. Therefore the key step to reducing energy consumption and carbon emissions from buildings is to understand how occupants interact with the environment they are exposed to in terms of achieving thermal comfort and well-being; though such interaction is complex. This paper presents a dynamic process of occupant behaviours involving technological, personal and psychological adaptations in response to varied thermal conditions based on the data covering four seasons gathered from the field study in Chongqing, China. It demonstrates that occupants are active players in environmental control and their adaptive responses are driven strongly by ambient thermal stimuli and vary from season to season and from time to time, even on the same day. Positive, dynamic, behavioural adaptation will help save energy used in heating and cooling buildings. However, when environmental parameters cannot fully satisfy occupants’ requirements, negative behaviours could conflict with energy saving. The survey revealed that about 23% of windows are partly open for fresh air when air-conditioners are in operation in summer. This paper addresses the issues how the building and environmental systems should be designed, operated and managed in a way that meets the requirements of energy efficiency without compromising wellbeing and productivity.

Corporate social responsibility in construction and engineering firms: key elements of effective strategy

Through multiple case studies of firms we argue that firms that have developed corporate responsibility strategies, albeit informally at first, do so by making intentional, informed and collective choices about CSR initiatives. More precisely, we point to the importance of considering corporate identity in making these choices and to the process of adaptive coordination, which includes both responding to and influencing the CSR environment. We conclude that CSR strategic landscape are determined more and more by the astute and careful management of a network of cooperative and competitive stakeholder interests which possess both tangible and intangible value to a firm.

Modular non-computational-connectionist-hybrid neural network approach to robotic systems

Spiking neural networks are usually limited in their applications due to their complex mathematical models and the lack of intuitive learning algorithms. In this paper, a simpler, novel neural network derived from a leaky integrate and fire neuron model, the ‘cavalcade’ neuron, is presented. A simulation for the neural network has been developed and two basic learning algorithms implemented within the environment. These algorithms successfully learn some basic temporal and instantaneous problems. Inspiration for neural network structures from these experiments are then taken and applied to process sensor information so as to successfully control a mobile robot.

An Earth Observation Land Data Assimilation System (EO-LDAS)

Current methods for estimating vegetation parameters are generally sub-optimal in the way they exploit information and do not generally consider uncertainties. We look forward to a future where operational dataassimilation schemes improve estimates by tracking land surface processes and exploiting multiple types of observations. Dataassimilation schemes seek to combine observations and models in a statistically optimal way taking into account uncertainty in both, but have not yet been much exploited in this area. The EO-LDAS scheme and prototype, developed under ESA funding, is designed to exploit the anticipated wealth of data that will be available under GMES missions, such as the Sentinel family of satellites, to provide improved mapping of land surface biophysical parameters. This paper describes the EO-LDAS implementation, and explores some of its core functionality. EO-LDAS is a weak constraint variational dataassimilationsystem. The prototype provides a mechanism for constraint based on a prior estimate of the state vector, a linear dynamic model, and EarthObservationdata (top-of-canopy reflectance here). The observation operator is a non-linear optical radiative transfer model for a vegetation canopy with a soil lower boundary, operating over the range 400 to 2500 nm. Adjoint codes for all model and operator components are provided in the prototype by automatic differentiation of the computer codes. In this paper, EO-LDAS is applied to the problem of daily estimation of six of the parameters controlling the radiative transfer operator over the course of a year (> 2000 state vector elements). Zero and first order process model constraints are implemented and explored as the dynamic model. The assimilation estimates all state vector elements simultaneously. This is performed in the context of a typical Sentinel-2 MSI operating scenario, using synthetic MSI observations simulated with the observation operator, with uncertainties typical of those achieved by optical sensors supposed for the data. The experiments consider a baseline state vector estimation case where dynamic constraints are applied, and assess the impact of dynamic constraints on the a posteriori uncertainties. The results demonstrate that reductions in uncertainty by a factor of up to two might be obtained by applying the sorts of dynamic constraints used here. The hyperparameter (dynamic model uncertainty) required to control the assimilation are estimated by a cross-validation exercise. The result of the assimilation is seen to be robust to missing observations with quite large data gaps.

Improving insight and non-insight problem solving with brief interventions

Developing brief training interventions that benefit different forms of problem solving is challenging. In earlier research, Chrysikou (2006) showed that engaging in a task requiring generation of alternative uses of common objects improved subsequent insight problem solving. These benefits were attributed to a form of implicit transfer of processing involving enhanced construction of impromptu, on-the-spot or ‘ad hoc’ goal-directed categorizations of the problem elements. Following this, it is predicted that the alternative uses exercise should benefit abilities that govern goal-directed behaviour, such as fluid intelligence and executive functions. Similarly, an indirect intervention – self-affirmation (SA) – that has been shown to enhance cognitive and executive performance after self-regulation challenge and when under stereotype threat, may also increase adaptive goal-directed thinking and likewise should bolster problem-solving performance. In Experiment 1, brief single-session interventions, involving either alternative uses generation or SA, significantly enhanced both subsequent insight and visual–spatial fluid reasoning problem solving. In Experiment 2, we replicated the finding of benefits of both alternative uses generation and SA on subsequent insight problem-solving performance, and demonstrated that the underlying mechanism likely involves improved executive functioning. Even brief cognitive– and social–psychological interventions may substantially bolster different types of problem solving and may exert largely similar facilitatory effects on goal-directed behaviours.

The role of prophage-like elements in the diversity of Salmonella enterica serovars

The Salmonella enterica serovar Typhi CT18 (S. Typhi) chromosome harbours seven distinct prophage-like elements, some of which may encode functional bacteriophages. In silico analyses were used to investigate these regions in S. Typhi CT18, and ultimately compare these integrated bacteriophages against 40 other Salmonella isolates using DNA microarray technology. S. Typhi CT18 contains prophages that show similarity to the lambda, Mu, P2 and P4 bacteriophage families. When compared to other S. Typhi isolates, these elements were generally conserved, supporting a clonal origin of this serovar. However, distinct variation was detected within a broad range of Salmonella serovars; many of the prophage regions are predicted to be specific to S. Typhi. Some of the P2 family prophage analysed have the potential to carry non-essential "cargo" genes within the hyper-variable tail region, an observation that suggests that these bacteriophage may confer a level of specialisation on their host. Lysogenic bacteriophages therefore play a crucial role in the generation of genetic diversity within S. enterica. (C) 2004 Elsevier Ltd. All rights reserved.

Artefact-oriented business process modelling: an ontological dependency approach

Business process modelling can help an organisation better understand and improve its business processes. Most business process modelling methods adopt a task- or activity-based approach to identifying business processes. Within our work, we use activity theory to categorise elements within organisations as being either human beings, activities or artefacts. Due to the direct relationship between these three elements, an artefact-oriented approach to organisation analysis emerges. Organisational semiotics highlights the ontological dependency between affordances within an organisation. We analyse the ontological dependency between organisational elements, and therefore produce the ontology chart for artefact-oriented business process modelling in order to clarify the relationship between the elements of an organisation. Furthermore, we adopt the techniques from semantic analysis and norm analysis, of organisational semiotics, to develop the artefact-oriented method for business process modelling. The proposed method provides a novel perspective for identifying and analysing business processes, as well as agents and artefacts, as the artefact-oriented perspective demonstrates the fundamental flow of an organisation. The modelling results enable an organisation to understand and model its processes from an artefact perspective, viewing an organisation as a network of artefacts. The information and practice captured and stored in artefact can also be shared and reused between organisations that produce similar artefacts.

Bacillus subtilis natto: a non-toxic source of poly-γ-glutamic acid that could be used as a cryoprotectant for probiotic bacteria

It is common practice to freeze dry probiotic bacteria to improve their shelf life. However, the freeze drying process itself can be detrimental to their viability. The viability of probiotics could be maintained if they are administered within a microbially produced biodegradable polymer - poly-γ-glutamic acid (γ-PGA) - matrix. Although the antifreeze activity of γ-PGA is well known, it has not been used for maintaining the viability of probiotic bacteria during freeze drying. The aim of this study was to test the effect of γ-PGA (produced by B. subtilis natto ATCC 15245) on the viability of probiotic bacteria during freeze drying and to test the toxigenic potential of B. subtilis natto. 10% γ-PGA was found to protect Lactobacillus paracasei significantly better than 10% sucrose, whereas it showed comparable cryoprotectant activity to sucrose when it was used to protect Bifidobacterium breve and Bifidobacterium longum. Although γ-PGA is known to be non-toxic, it is crucial to ascertain the toxigenic potential of its source, B. subtilis natto. Presence of six genes that are known to encode for toxins were investigated: three component hemolysin (hbl D/A), three component non-haemolytic enterotoxin (nheB), B. cereus enterotoxin T (bceT), enterotoxin FM (entFM), sphingomyelinase (sph) and phosphatidylcholine-specific phospholipase (piplc). From our investigations, none of these six genes were present in B. subtilis natto. Moreover, haemolytic and lecithinase activities were found to be absent. Our work contributes a biodegradable polymer from a non-toxic source for the cryoprotection of probiotic bacteria, thus improving their survival during the manufacturing process.

A SEPALLATA gene is involved in the development and ripening of strawberry (Fragaria X ananassa Duch.) fruit, a non-climacteric tissue

Climacteric and non-climacteric fruits have traditionally been viewed as representing two distinct programmes of ripening associated with differential respiration and ethylene hormone effects. In climacteric fruits, such as tomato and banana, the ripening process is marked by increased respiration and is induced and co-ordinated by ethylene, while in non-climacteric fruits, such as strawberry and grape, it is controlled by an ethylene-independent process with little change in respiration rate. The two contrasting mechanisms, however, both lead to texture, colour, and flavour changes that probably reflect some common programmes of regulatory control. It has been shown that a SEPALLATA(SEP)4-like gene is necessary for normal ripening in tomato. It has been demonstrated here that silencing a fruit-related SEP1/2-like (FaMADS9) gene in strawberry leads to the inhibition of normal development and ripening in the petal, achene, and receptacle tissues. In addition, analysis of transcriptome profiles reveals pleiotropic effects of FaMADS9 on fruit development and ripening-related gene expression. It is concluded that SEP genes play a central role in the developmental regulation of ripening in both climacteric and non-climacteric fruits. These findings provide important information to extend the molecular control of ripening in a non-climacteric fruit beyond the limited genetic and cultural options currently available.

Online bayesian inference in some time-frequency representations of non-stationary processes

The use of Bayesian inference in the inference of time-frequency representations has, thus far, been limited to offline analysis of signals, using a smoothing spline based model of the time-frequency plane. In this paper we introduce a new framework that allows the routine use of Bayesian inference for online estimation of the time-varying spectral density of a locally stationary Gaussian process. The core of our approach is the use of a likelihood inspired by a local Whittle approximation. This choice, along with the use of a recursive algorithm for non-parametric estimation of the local spectral density, permits the use of a particle filter for estimating the time-varying spectral density online. We provide demonstrations of the algorithm through tracking chirps and the analysis of musical data.