Electrocatalytic oxidation of ascorbic acid using a single layer of gold nanoparticles immobilized on 1,6-hexanedithiol modified gold electrode

This paper describes the electrocatalytic oxidation of ascorbic acid (AA) in phosphate buffer solution by the immobilized citrate capped gold nanoparticles (AuNPs) on 1,6-hexanedithiol (HDT) modified Au electrode. X-ray photoelectron spectrum (XPS) of HDT suggests that it forms a monolayer on Au surface through one of the two single bondSH groups and the other single bondSH group is pointing away from the electrode surface. The free single bondSH groups of HDT were used to covalently attach colloidal AuNPs. The covalent attachment of AuNPs on HDT monolayer was confirmed from the observed characteristic carboxylate ion stretching modes of citrate attached with AuNPs in the infra-red reflection absorption spectrum (IRRAS) in addition to a higher reductive desorption charges obtained for AuNPs immobilized on HDT modified Au (Au/HDT/AuNPs) electrode in 0.1 M KOH when compared to HDT modified Au (Au/HDT) electrode. The electron transfer reaction of [Fe(CN)6]4−/3− was markedly hindered at the HDT modified Au (Au/HDT) electrode while it was restored with a peak separation of 74 mV after the immobilization of AuNPs on Au/HDT (Au/HDT/AuNPs) electrode indicating a good electronic communication between the immobilized AuNPs and the underlying bulk Au electrode through a HDT monolayer. The Cottrell slope obtained from the potential-step chronoamperometric measurements for the reduction of ferricyanide at Au/HDT/AuNPs was higher than that of bare Au electrode indicating the increased effective surface area of AuNPs modified electrode. The Au/HDT/AuNPs electrode exhibits excellent electrocatalytic activity towards the oxidation of ascorbic acid (AA) by enhancing the oxidation peak current to more than two times with a 210 mV negative shift in the oxidation potential when compared to a bare Au electrode. The standard heterogeneous electron transfer rate constant (ks) calculated for AA oxidation at Au/HDT/AuNPs electrode was 5.4 × 10−3 cm s−1. The oxidation peak of AA at Au/HDT/AuNPs electrode was highly stable upon repeated potential cycling. Linear calibration plot was obtained for AA over the concentration range of 1–110 μM with a correlation coefficient of 0.9950. The detection limit of AA was found to be 1 μM. The common physiological interferents such as glucose, oxalate ions and urea do not show any interference within the detection limit of AA. The selectivity of the AuNPs modified electrode was illustrated by the determination of AA in the presence of uric acid.

Ranking based clustering for social event detection

The problem of clustering a large document collection is not only challenged by the number of documents and the number of dimensions, but it is also affected by the number and sizes of the clusters. Traditional clustering methods fail to scale when they need to generate a large number of clusters. Furthermore, when the clusters size in the solution is heterogeneous, i.e. some of the clusters are large in size, the similarity measures tend to degrade. A ranking based clustering method is proposed to deal with these issues in the context of the Social Event Detection task. Ranking scores are used to select a small number of most relevant clusters in order to compare and place a document. Additionally,instead of conventional cluster centroids, cluster patches are proposed to represent clusters, that are hubs-like set of documents. Text, temporal, spatial and visual content information collected from the social event images is utilized in calculating similarity. Results show that these strategies allow us to have a balance between performance and accuracy of the clustering solution gained by the clustering method.

Clinical data warehousing : a business analytics approach for managing health data

Heterogeneous health data is a critical issue when managing health information for quality decision making processes. In this paper we examine the efficient aggregation of lifestyle information through a data warehousing architecture lens. We present a proof of concept for a clinical data warehouse architecture that enables evidence based decision making processes by integrating and organising disparate data silos in support of healthcare services improvement paradigms.

The Craving Experience Questionnaire : a brief, theory-based measure of consummatory desire and craving

Background and Aims Research into craving is hampered by lack of theoretical specification and a plethora of substance-specific measures. This study aimed to develop a generic measure of craving based on elaborated intrusion (EI) theory. Confirmatory factor analysis (CFA) examined whether a generic measure replicated the three-factor structure of the Alcohol Craving Experience (ACE) scale over different consummatory targets and time-frames. Design Twelve studies were pooled for CFA. Targets included alcohol, cigarettes, chocolate and food. Focal periods varied from the present moment to the previous week. Separate analyses were conducted for strength and frequency forms. Setting Nine studies included university students, with single studies drawn from an internet survey, a community sample of smokers and alcohol-dependent out-patients. Participants A heterogeneous sample of 1230 participants. Measurements Adaptations of the ACE questionnaire. Findings Both craving strength [comparative fit indices (CFI = 0.974; root mean square error of approximation (RMSEA) = 0.039, 95% confidence interval (CI) = 0.035–0.044] and frequency (CFI = 0.971, RMSEA = 0.049, 95% CI = 0.044–0.055) gave an acceptable three-factor solution across desired targets that mapped onto the structure of the original ACE (intensity, imagery, intrusiveness), after removing an item, re-allocating another and taking intercorrelated error terms into account. Similar structures were obtained across time-frames and targets. Preliminary validity data on the resulting 10-item Craving Experience Questionnaire (CEQ) for cigarettes and alcohol were strong. Conclusions The Craving Experience Questionnaire (CEQ) is a brief, conceptually grounded and psychometrically sound measure of desires. It demonstrates a consistent factor structure across a range of consummatory targets in both laboratory and clinical contexts.

A numerical method for the fractional Fitzhugh–Nagumo monodomain model

A fractional FitzHugh–Nagumo monodomain model with zero Dirichlet boundary conditions is presented, generalising the standard monodomain model that describes the propagation of the electrical potential in heterogeneous cardiac tissue. The model consists of a coupled fractional Riesz space nonlinear reaction-diffusion model and a system of ordinary differential equations, describing the ionic fluxes as a function of the membrane potential. We solve this model by decoupling the space-fractional partial differential equation and the system of ordinary differential equations at each time step. Thus, this means treating the fractional Riesz space nonlinear reaction-diffusion model as if the nonlinear source term is only locally Lipschitz. The fractional Riesz space nonlinear reaction-diffusion model is solved using an implicit numerical method with the shifted Grunwald–Letnikov approximation, and the stability and convergence are discussed in detail in the context of the local Lipschitz property. Some numerical examples are given to show the consistency of our computational approach.

Hydrostratigraphic analysis of the MADE site with full-resolution GPR and direct-push hydraulic profiling

Full-resolution 3D Ground-Penetrating Radar (GPR) data were combined with high-resolution hydraulic conductivity (K) data from vertical Direct-Push (DP) profiles to characterize a portion of the highly heterogeneous MAcro Dispersion Experiment (MADE) site. This is an important first step to better understand the influence of aquifer heterogeneities on observed anomalous transport. Statistical evaluation of DP data indicates non-normal distributions that have much higher similarity within each GPR facies than between facies. The analysis of GPR and DP data provides high-resolution estimates of the 3D geometry of hydrostratigraphic zones, which can then be populated with stochastic K fields. The lack of such estimates has been a significant limitation for testing and parameterizing a range of novel transport theories at sites where the traditional advection-dispersion model has proven inadequate.

Food structure : its formation and relationships with other properties

Food materials are complex in nature as it has heterogeneous, amorphous, hygroscopic and porous properties. During processing, microstructure of food materials changes which significantly affects other properties of food. An appropriate understanding of the microstructure of the raw food material and its evolution during processing is critical in order to understand and accurately describe dehydration processes and quality anticipation. This review critically assesses the factors that influence the modification of microstructure in the course of drying of fruits and vegetables. The effect of simultaneous heat and mass transfer on microstructure in various drying methods is investigated. Effects of changes in microstructure on other functional properties of dried foods are discussed. After an extensive review of the literature, it is found that development of food structure significantly depends on fresh food properties and process parameters. Also, modification of microstructure influences the other properties of final product. An enhanced understanding of the relationships between food microstructure, drying process parameters and final product quality will facilitate the energy efficient optimum design of the food processor in order to achieve high-quality food

Mice behaviorally selected for high Pavlovian fear memory exhibit fear generalization, HPA-axis alterations and increased basal activity in cortico-limbic circuits

Biological factors underlying individual variability in fearfulness and anxiety have important implications for stress-related psychiatric illness including PTSD and major depression. Using an advanced intercross line (AIL) derived from C57BL/6 and DBA/2J mouse strains and behavioral selection over 3 generations, we established two lines exhibiting High or Low fear behavior after fear conditioning. Across the selection generations, the two lines showed clear differences in training and tests for contextual and conditioned fear. Before fear conditioning training, there were no differences between lines in baseline freezing to a novel context. However, after fear conditioning High line mice demonstrated pronounced freezing in a new context suggestive of poor context discrimination. Fear generalization was not restricted to contextual fear. High fear mice froze to a novel acoustic stimulus while freezing in the Low line did not increase over baseline. Enhanced fear learning and generalization are consistent with transgenic and pharmacological disruption of the hypothalamic-pituitary-adrenal axis (HPA-axis) (Brinks, 2009, Thompson, 2004, Kaouane, 2012). To determine whether there were differences in HPA-axis regulation between the lines, morning urine samples were collected to measure basal corticosterone. Levels of secreted corticosterone in the circadian trough were analyzed by corticosterone ELISA. High fear mice were found to have higher basal corticosterone levels than low line animals. Examination of hormonal stress response components by qPCR revealed increased expression of CRH mRNA and decreased mRNA for MR and CRHR1 in hypothalamus of high fear mice. These alterations may contribute to both the behavioral phenotype and higher basal corticosterone in High fear mice. To determine basal brain activity in vivo in High and Low fear mice we used manganese-enhanced magnetic resonance imaging (MEMRI). Analysis revealed a pattern of basal brain activity made up of amygdala, cortical and hippocampal circuits that was elevated in the High line. Ongoing studies also seek to determine the relative balance of excitatory and inhibitory tone in the amygdala and hippocampus and the neuronal structure of its neurons. While these heterogeneous lines are selected on fear memory expression, HPA-axis alterations and differences in hippocampal activity segregate with the behavioral phenotypes. These differences are detectable in a basal state strongly suggesting these are biological traits underlying the behavioral phenotype (Johnson et al, 2011).

An examination of isotherm generation : impact of bottle-point method upon potassium ion exchange with strong acid cation resin

This paper relates to the importance of impact of the chosen bottle-point method when conducting ion exchange equilibria experiments. As an illustration, potassium ion exchange with strong acid cation resin was investigated due to its relevance to the treatment of various industrial effluents and groundwater. The “constant mass” bottle-point method was shown to be problematic in that depending upon the resin mass used the equilibrium isotherm profiles were different. Indeed, application of common equilibrium isotherm models revealed that the optimal fit could be with either the Freundlich or Temkin equations, depending upon the conditions employed. It could be inferred that the resin surface was heterogeneous in character, but precise conclusions regarding the variation in the heat of sorption were not possible. Estimation of the maximum potassium loading was also inconsistent when employing the “constant mass” method. The “constant concentration” bottle-point method illustrated that the Freundlich model was a good representation of the exchange process. The isotherms recorded were relatively consistent when compared to the “constant mass” approach. Unification of all the equilibrium isotherm data acquired was achieved by use of the Langmuir Vageler expression. The maximum loading of potassium ions was predicted to be at least 116.5 g/kg resin.

Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

Napping, development and health from 0 to 5 years : a systematic review

Background Duration and quality of sleep affect child development and health. Encouragement of napping in preschool children has been suggested as a health-promoting strategy. Objectives The aim of this study is to assess evidence regarding the effects of napping on measures of child development and health. Design This study is a systematic review of published, original research articles of any design. Subjects Children aged 0–5 years. Method Electronic database search was performed following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and assessment of research quality was carried out following a Grading of Recommendations, Assessment, Development and Evaluations (GRADE) protocol. Results Twenty-six articles met inclusion criteria. These were of heterogeneous quality; all had observational designs (GRADE-low). Development and health outcomes included salivary cortisol, night sleep, cognition, behaviour, obesity and accidents. The findings regarding cognition, behaviour and health impacts were inconsistent, probably because of variation in age and habitual napping status of the samples. The most consistent finding was an association between napping and later onset, shorter duration and poorer quality of night sleep, with evidence strongest beyond the age of 2 years. Limitations Studies were not randomised. Most did not obtain data on the children's habitual napping status or the context of napping. Many were reliant on parent report rather than direct observation or physiological measurement of sleep behaviour. Conclusions The evidence indicates that beyond the age of 2 years napping is associated with later night sleep onset and both reduced sleep quality and duration. The evidence regarding behaviour, health and cognition is less certain. There is a need for more systematic studies that use stronger designs. In preschool children presenting with sleep problems clinicians should investigate napping patterns.

Creative graduate pathways within and beyond the creative industries

This special issue explores the nuances of graduate creative work, the kinds of value that creative graduates add through work of various types, graduate employability issues for creative graduates, emerging and developing creative career identities and the implications for educators who are tasked with developing a capable creative workforce. Extent literature tends to characterise creative careers as either ‘precarious’ and insecure, or as the engine room of the creative economy. However, in actuality, the creative workforce is far more heterogeneous than either of these positions suggest, and creative careers are far more complex and diverse than previously thought. The task of creative educators is also much more challenging than previously supposed. In this introductory article, we commence by providing a brief overview of the creative labour debates, and the evidence for each position. We present the latest literature in this area that starts to speak to how diverse and complex the landscape of creative work actually is. We then introduce each of the articles in this special issue and indicate how they contribute to a more multi-faceted picture of creative activity, and the lives and career trajectories of graduates from creative degrees.

Flying robots to the rescue

UAVs could one day save the lives of lost civilians and those sent to find them, and a competition in outback Australia is proving how soon that day might come. We have all seen news stories of people who ventured beyond the day-to-day reach of the community and got lost: search parties are formed, aircraft drafted in, and often large sums of money expended in the quest to find them.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

A semi-alternating direction method for a 2-D fractional FitzHugh–Nagumo monodomain model on an approximate irregular domain

A FitzHugh-Nagumo monodomain model has been used to describe the propagation of the electrical potential in heterogeneous cardiac tissue. In this paper, we consider a two-dimensional fractional FitzHugh-Nagumo monodomain model on an irregular domain. The model consists of a coupled Riesz space fractional nonlinear reaction-diffusion model and an ordinary differential equation, describing the ionic fluxes as a function of the membrane potential. Secondly, we use a decoupling technique and focus on solving the Riesz space fractional nonlinear reaction-diffusion model. A novel spatially second-order accurate semi-implicit alternating direction method (SIADM) for this model on an approximate irregular domain is proposed. Thirdly, stability and convergence of the SIADM are proved. Finally, some numerical examples are given to support our theoretical analysis and these numerical techniques are employed to simulate a two-dimensional fractional Fitzhugh-Nagumo model on both an approximate circular and an approximate irregular domain.