Active inference and oculomotor pursuit: the dynamic causal modelling of eye movements.

This paper introduces a new paradigm that allows one to quantify the Bayesian beliefs evidenced by subjects during oculomotor pursuit. Subjects' eye tracking responses to a partially occluded sinusoidal target were recorded non-invasively and averaged. These response averages were then analysed using dynamic causal modelling (DCM). In DCM, observed responses are modelled using biologically plausible generative or forward models - usually biophysical models of neuronal activity

The 1996 research assessment exercise : the library and information management panel

Reports on the 1996 Research Assessment Exercise (RAE), the fourth such exercise aimed at providing funding councils of UK universities (including former polytechnics) with the necessary data to rate the quality of UK academic research for predetermined units of assessment in order to fund research selectively. Previous RAEs were conducted in 1986, 1989, and 1992 (for a report of the 1992 RAE see JOLIS 26 (3) Sep 94, 141-7 (LISA ref. 9409765)). Reports generally on the work of the Library and Information Management Panel in agreeing criteria specific to their assessment task, particularly the five principal modes of publication: research monographs; articles in scholarly periodicals; refereed conference papers; published research reports; and book chapters. Discusses the methodology used by the Panel, research submissions received and the overall results

Draft Genome Sequence of the Serratia rubidaea CIP 103234T Reference Strain, a Human-Opportunistic Pathogen.

We provide here the first genome sequence of a Serratia rubidaea isolate, a human-opportunistic pathogen. This reference sequence will permit a comparison of this species with others of the Serratia genus

Protein kinase A (PKA) phosphorylation of Shp2 inhibits its phosphatase activity and modulates ligand specificity.

Pathological cardiac hypertrophy (an increase in cardiac mass resulting from stress-induced cardiac myocyte growth) is a major factor underlying heart failure. Src homology 2 domain-containing phosphatase (Shp2) is critical for cardiac function as mutations resulting in loss of Shp2 catalytic activity are associated with congenital cardiac defects and hypertrophy. We have identified a novel mechanism of Shp2 inhibition that may promote cardiac hypertrophy. We demonstrate that Shp2 is a component of the A-kinase anchoring protein (AKAP)-Lbc complex. AKAP-Lbc facilitates protein kinase A (PKA) phosphorylation of Shp2, which inhibits Shp2 phosphatase activity. We have identified two key amino acids in Shp2 that are phosphorylated by PKA: Thr73 contributes a helix-cap to helix αB within the N-terminal SH2 domain of Shp2, whereas Ser189 occupies an equivalent position within the C-terminal SH2 domain. Utilizing double mutant PKA phospho-deficient (T73A/S189A) and phospho-mimetic (T73D/S189D) constructs, in vitro binding assays, and phosphatase activity assays, we demonstrate that phosphorylation of these residues disrupts Shp2 interaction with tyrosine-phosphorylated ligands and inhibits its protein tyrosine phosphatase activity. Overall, our data indicate that AKAP-Lbc integrates PKA and Shp2 signaling in the heart and that AKAP-Lbc-associated Shp2 activity is reduced in hypertrophic hearts in response to chronic β-adrenergic stimulation and PKA activation. Thus, while induction of cardiac hypertrophy is a multifaceted process, inhibition of Shp2 activity through AKAP-Lbc-anchored PKA is a previously unrecognized mechanism that may promote this compensatory response

Diagnostic accuracy of a brief screening tool forAttention Deficit/Hyperactivity Disorder in UK prison inmates

BackgroundAttention deficit hyperactivity disorder (ADHD) is overrepresented in prison, making it imperative to identify a screening tool that can be quickly applied to efficiently detect the disorder. We explored the discrimination ability of a widely used ADHD screen, the Barkley Adult ADHD Rating Scale (BAARS-IV), against a clinical diagnostic interview. A brief version of the screen was then developed in order to simplify its use in the prison context, and maximize its diagnostic properties.MethodA cross-sectional study of 390 male prison inmates was performed in the UK, all participants were screened and interviewed via the Diagnostic Interview for ADHD in Adults 2.0 (DIVA-2).ResultsA total of 47 (12.1%) inmates screened positive for ADHD using the full BAARS-IV, and 96 (24.6%) were clinically diagnosed, for a sensitivity of 37.9 and a specificity of 96.3. Our models identified the six items that most predicted ADHD diagnosis, with adjusted odds ratios ranging from 2.66 to 4.58. Sensitivity, specificity and accuracy were 0.82, 0.84 and 0.84, respectively, for the developed brief scale, and 0.71, 0.85 and 0.81 for its validation. Weighted probability scores produced an area under the curve of 0.89 for development, and 0.82 for validation of the brief scale.ConclusionsThe original BAARS-IV performed poorly at identifying prison inmates with ADHD. Our developed brief scale substantially improved diagnostic accuracy. The brief screening instrument has great potential to be used as an accurate and resource-effective tool to screen young people and adults for likely ADHD in the criminal justice system.</jats:sec

An Agent-Based Model of Mediterranean Agricultural Land-Use/Cover Change for Examining Wildfire Risk

Humans have a long history of activity in Mediterranean Basin landscapes. Spatial heterogeneity in these landscapes hinders our understanding about the impacts of changes in human activity on ecological processes, such as wildfire. The use of spatially-explicit models that simulate processes at fine scales should aid the investigation of spatial patterns at the broader, landscape scale. Here, we present an agent-based model of agricultural land-use decision-making to examine the importance of land tenure and land use on future land cover. The model considers two 'types' of land-use decision-making agent with differing perspectives; 'commercial' agents that are perfectly economically rational, and 'traditional' agents that represent part-time or 'traditional' farmers that manage their land because of its cultural, rather than economic, value. The structure of the model is described and results are presented for various scenarios of initial landscape configuration. Land-use/cover maps produced by the model are used to examine how wildfire risk changes for each scenario. Results indicate that land tenure configuration influences trajectories of land use change. However, simulations for various initial land-use configurations and compositions converge to similar states when land-tenure structure is held constant. For the scenarios considered, mean wildfire risk increases relative to the observed landscape. Increases in wildfire risk are not spatially uniform however, varying according to the composition and configuration of land use types. These unexpected spatial variations in wildfire risk highlight the advantages of using a spatially-explicit agent-based model of land use/cover change.Land Use/Cover Change, Land Tenure, Wildfire, Mediterranean-Type Ecosystem, Agriculture, Spatial Heterogeneity

Auto-tail dependence coefficients for stationary solutions of linear stochastic recurrence equations and for GARCH(1,1)

We examine the auto-dependence structure of strictly stationary solutions of linear stochastic recurrence equations and of strictly stationary GARCH(1, 1) processes from the point of view of ordinary and generalized tail dependence coefficients. Since such processes can easily be of infinite variance, a substitute for the usual auto-correlation function is needed

Whole-Genome Sequence of a European Clone II and OXA-72-Producing Acinetobacter baumannii Strain from Serbia.

We report here the draft genome sequence of a carbapenem-resistant Acinetobacter baumannii strain isolated from a patient, a strain which previously stayed in Serbia. This isolate possessed the blaOXA-72 carbapenemase gene. The draft genome sequence consists of a total length of 3.91 Mbp, with an average G+C content of 38.8%

System interactions of stormwater management using sustainable urban drainage systems and green infrastructure

This study explores system interactions of stormwater management solutions using Sustainable Urban Drainage System (SuDS) and Green Infrastructure (GI) within the wider urban landscape. A series of interdependencies between urban components relating to stormwater management are identified. These include physical interdependency, geographical interdependency, cyber interdependency and logical interdependency, as defined by Peerenboom (2001). Stormwater management using SuDS/GI are viewed according to their Hydrological, Ecological and the Built Environment functions during events up to the design rain (non-flood condition) and during controlled exceedance and uncontrolled inundation (flood condition). The inclusion of SuDS/GI into the urban fabric is shown to modify urban functional and relational interdependencies under both these conditions. Within the context of the UK, there are fragmented responsibilities across planning scales created by SuDS/GI solutions which have not addressed the relational complexities that exist between agencies and competent authorities. The paper identifies the key barriers towards effective adoption of SuDS/GI within the context of the UK as physical barriers, perception/information barriers and organisational barriers.This work is part of the Blue Green Cities project funded by the UK Engineering and Physical Sciences Research Council, grant EP/K013661/1.This is the final version of the article. It first appeared from Taylor & Francis via http://dx.doi.org/10.1080/1573062X.2015.103608

A network approach for managing and processing big cancer data in clouds

Translational cancer research requires integrative analysis of multiple levels of big cancer data to identify and treat cancer. In order to address the issues that data is decentralised, growing and continually being updated, and the content living or archiving on different information sources partially overlaps creating redundancies as well as contradictions and inconsistencies, we develop a data network model and technology for constructing and managing big cancer data. To support our data network approach for data process and analysis, we employ a semantic content network approach and adopt the CELAR cloud platform. The prototype implementation shows that the CELAR cloud can satisfy the on-demanding needs of various data resources for management and process of big cancer data