Origin and Detection of Microstructural Clustering in Fluids with Spatial-Range Competitive Interactions

Fluids with competing short-range attractions and long-range repulsions mimic dispersions of charge-stabilized colloids that can display equilibrium structures with intermediate range order (IRO), including particle clusters. Using simulations and analytical theory, we demonstrate how to detect cluster formation in such systems from the static structure factor and elucidate links to macrophase separation in purely attractive reference fluids. We find that clusters emerge when the thermal correlation length encoded in the IRO peak of the structure factor exceeds the characteristic lengthscale of interparticle repulsions. We also identify qualitative differences between the dynamics of systems that form amorphous versus micro-crystalline clusters.Comment: 6 pages, 5 figure

The self-assembly of DNA Holliday junctions studied with a minimal model

In this paper, we explore the feasibility of using coarse-grained models to simulate the self-assembly of DNA nanostructures. We introduce a simple model of DNA where each nucleotide is represented by two interaction sites corresponding to the phosphate-sugar backbone and the base. Using this model, we are able to simulate the self-assembly of both DNA duplexes and Holliday junctions from single-stranded DNA. We find that assembly is most successful in the temperature window below the melting temperatures of the target structure and above the melting temperature of misbonded aggregates. Furthermore, in the case of the Holliday junction, we show how a hierarchical assembly mechanism reduces the possibility of becoming trapped in misbonded configurations. The model is also able to reproduce the relative melting temperatures of different structures accurately, and allows strand displacement to occur.Comment: 13 pages, 14 figure

Starting to smoke: a qualitative study of the experiences of Australian indigenous youth

BackgroundAdult smoking has its roots in adolescence. If individuals do not initiate smoking during this period it is unlikely they ever will. In high income countries, smoking rates among Indigenous youth are disproportionately high. However, despite a wealth of literature in other populations, there is less evidence on the determinants of smoking initiation among Indigenous youth. The aim of this study was to explore the determinants of smoking among Australian Indigenous young people with a particular emphasis on the social and cultural processes that underlie tobacco use patterns among this group. MethodsThis project was undertaken in northern Australia. We undertook group interviews with 65 participants and individual in-depth interviews with 11 youth aged 13–20 years led by trained youth ‘peer researchers.’ We also used visual methods (photo-elicitation) with individual interviewees to investigate the social context in which young people do or do not smoke. Included in the sample were a smaller number of non-Indigenous youth to explore any significant differences between ethnic groups in determinants of early smoking experiences. The theory of triadic influence, an ecological model of health behaviour, was used as an organising theory for analysis. ResultsFamily and peer influences play a central role in smoking uptake among Indigenous youth. Social influences to smoke are similar between Indigenous and non-Indigenous youth but are more pervasive (especially in the family domain) among Indigenous youth. While Indigenous youth report high levels of exposure to smoking role models and smoking socialisation practices among their family and social networks, this study provides some indication of a progressive denormalisation of smoking among some Indigenous youth. ConclusionsFuture initiatives aimed at preventing smoking uptake in this population need to focus on changing social normative beliefs around smoking, both at a population level and within young peoples’ immediate social environment. Such interventions could be effectively delivered in both the school and family environments. Specifically, health practitioners in contact with Indigenous families should be promoting smoke free homes and other anti-smoking socialisation behaviours

Applying psychological theory to evidence-based clinical practice : identifying factors predictive of managing upper respiratory tract infections without antibiotics

Background: Psychological models can be used to understand and predict behaviour in a wide range of settings. However, they have not been consistently applied to health professional behaviours, and the contribution of differing theories is not clear. The aim of this study was to explore the usefulness of a range of psychological theories to predict health professional behaviour relating to management of upper respiratory tract infections (URTIs) without antibiotics. Methods: Psychological measures were collected by postal questionnaire survey from a random sample of general practitioners (GPs) in Scotland. The outcome measures were clinical behaviour (using antibiotic prescription rates as a proxy indicator), behavioural simulation (scenario-based decisions to managing URTI with or without antibiotics) and behavioural intention (general intention to managing URTI without antibiotics). Explanatory variables were the constructs within the following theories: Theory of Planned Behaviour (TPB), Social Cognitive Theory (SCT), Common Sense Self-Regulation Model (CS-SRM), Operant Learning Theory (OLT), Implementation Intention (II), Stage Model (SM), and knowledge (a non-theoretical construct). For each outcome measure, multiple regression analysis was used to examine the predictive value of each theoretical model individually. Following this 'theory level' analysis, a 'cross theory' analysis was conducted to investigate the combined predictive value of all significant individual constructs across theories. Results: All theories were tested, but only significant results are presented. When predicting behaviour, at the theory level, OLT explained 6% of the variance and, in a cross theory analysis, OLT 'evidence of habitual behaviour' also explained 6%. When predicting behavioural simulation, at the theory level, the proportion of variance explained was: TPB, 31%; SCT, 26%; II, 6%; OLT, 24%. GPs who reported having already decided to change their management to try to avoid the use of antibiotics made significantly fewer scenario-based decisions to prescribe. In the cross theory analysis, perceived behavioural control (TPB), evidence of habitual behaviour (OLT), CS-SRM cause (chance/bad luck), and intention entered the equation, together explaining 36% of the variance. When predicting intention, at the theory level, the proportion of variance explained was: TPB, 30%; SCT, 29%; CS-SRM 27%; OLT, 43%. GPs who reported that they had already decided to change their management to try to avoid the use of antibiotics had a significantly higher intention to manage URTIs without prescribing antibiotics. In the cross theory analysis, OLT evidence of habitual behaviour, TPB attitudes, risk perception, CS-SRM control by doctor, TPB perceived behavioural control and CS-SRM control by treatment entered the equation, together explaining 49% of the variance in intention. Cnclusion: The study provides evidence that psychological models can be useful in understanding and predicting clinical behaviour. Taking a theory-based approach enables the reation of a replicable methodology for identifying factors that predict clinical behaviour. Hwever, a number of conceptual and methodological challenges remain