Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.

Review of theoretical models of electromagnetic NDT and their applications

There is an increasing interest in modelling electromagnetic methods of NDT - particularly eddy currents. A collaboration within the International Institute of Welding led to a survey intended to explain to non mathematicians the present scope of modelling. The present review commences with this survey and then points out some of the developments and some of the outstanding problems in transferring modelling into industry.

Demonstration models of the cost and benefits of BVD and Johne's contol on cattle farms

Demonstration models of the costs of BVD and Johnes in dairy and beef cattle and the costs and benefits of control have been developed. An example applied to BVD in dairy cattle is presented. Downloadable versions of the models, together with supporting material on how to use them are available to veterinarians from a dedicated website.

Demonstration models of the cost and benefits of BVD and Johne's contol on cattle farms

Demonstration models of the costs of BVD and Johnes in dairy and beef cattle and the costs and benefits of control have been developed. An example applied to BVD in dairy cattle is presented. Downloadable versions of the models, together with supporting material on how to use them are available to veterinarians from a dedicated website.

Parametric accelerated failure time models with random effects and an application to kidney transplant survival

Accelerated failure time models with a shared random component are described, and are used to evaluate the effect of explanatory factors and different transplant centres on survival times following kidney transplantation. Different combinations of the distribution of the random effects and baseline hazard function are considered and the fit of such models to the transplant data is critically assessed. A mixture model that combines short- and long-term components of a hazard function is then developed, which provides a more flexible model for the hazard function. The model can incorporate different explanatory variables and random effects in each component. The model is straightforward to fit using standard statistical software, and is shown to be a good fit to the transplant data. Copyright (C) 2004 John Wiley Sons, Ltd.

Cognitive behaviour therapy for psychosis: current evidence and future directions

The past decade has seen considerable growth in the evidence base of cognitive behavioural therapy for psychosis. Consistent reports of moderate effect sizes have led to such interventions being recommended as part of routine clinical practice. Most of this evidence is based on a generic form of CBT for psychosis applied to a heterogeneous group. An increase in the effectiveness of cognitive behavioural interventions may require new protocols. Such therapeutic developments should be based on the theoretical understanding of the psychological processes associated with specific forms of psychotic presentation. The current evidence base of CBT for psychosis is reviewed, and barriers that have held back the development of this research are discussed.

Cognitive therapy for anxiety disorders: current status and future directions.

This paper reviews recent theoretical, conceptual and practice developments in cognitive-behaviour therapy (CBT) for anxiety disorders. The empirical status of CBT for anxiety disorders is reviewed and recent advances in the field are outlined. Challenges for the future development of CBT for the anxiety disorders are examined in relation to the efficacy, effectiveness and cost-effectiveness of the approach. It is concluded that the major challenge currently facing CBT for anxiety disorders in the UK is how to meet the increased demand for provision whilst maintaining high levels of efficacy and effectiveness. It is suggested that the creation of an evidence base for the dissemination of CBT needs to become a priority for empirical investigation in order effectively to expand the provision of CBT for anxiety disorders.

Energetics of climate models: net energy balance and meridional enthalpy transport

We analyze the publicly released outputs of the simulations performed by climate models (CMs) in preindustrial (PI) and Special Report on Emissions Scenarios A1B (SRESA1B) conditions. In the PI simulations, most CMs feature biases of the order of 1 W m −2 for the net global and the net atmospheric, oceanic, and land energy balances. This does not result from transient effects but depends on the imperfect closure of the energy cycle in the fluid components and on inconsistencies over land. Thus, the planetary emission temperature is underestimated, which may explain the CMs' cold bias. In the PI scenario, CMs agree on the meridional atmospheric enthalpy transport's peak location (around 40°N/S), while discrepancies of ∼20% exist on the intensity. Disagreements on the oceanic transport peaks' location and intensity amount to ∼10° and ∼50%, respectively. In the SRESA1B runs, the atmospheric transport's peak shifts poleward, and its intensity increases up to ∼10% in both hemispheres. In most CMs, the Northern Hemispheric oceanic transport decreases, and the peaks shift equatorward in both hemispheres. The Bjerknes compensation mechanism is active both on climatological and interannual time scales. The total meridional transport peaks around 35° in both hemispheres and scenarios, whereas disagreements on the intensity reach ∼20%. With increased CO 2 concentration, the total transport increases up to ∼10%, thus contributing to polar amplification of global warming. Advances are needed for achieving a self-consistent representation of climate as a nonequilibrium thermodynamical system. This is crucial for improving the CMs' skill in representing past and future climate changes.

Integrated motivational interviewing and cognitive behavioural therapy for people with psychosis and comorbid substance misuse: randomised controlled trial

Objectives To evaluate the effectiveness of integrated motivational interviewing and cognitive behaviour therapy in addition to standard care for patients with psychosis and a co-morbid substance use problem. Design Two-centre, open, rater-blind randomised controlled trial Setting UK Secondary Care Participants 327 patients with clinical diagnoses of schizophrenia, schizophreniform or schizoaffective disorder and DSM-IV diagnoses of drug and/or alcohol dependence or abuse Interventions Participants were randomly allocated to integrated motivational interviewing and cognitive behaviour therapy or standard care. Therapy has two phases. Phase one – “motivation building” – concerns engaging the patient, then exploring and resolving ambivalence for change in substance use. Phase two –“Action” – supports and facilitates change using cognitive behavioural approaches. Up to 26 therapy sessions were delivered over one year. Main outcomes The primary outcome was death from any cause or admission to hospital in the 12 months after therapy. Secondary outcomes were frequency and amount of substance use (Timeline Followback), readiness to change, perceived negative consequences of use, psychotic symptom ratings, number and duration of relapses, global assessment of functioning and deliberate self harm, at 12 and 24 months, with additional Timeline Followback assessments at 6 and 18 months. Analysis was by intention-to-treat with robust treatment effect estimates. Results 327 participants were randomised. 326 (99.7%) were assessed on the primary outcome, 246 (75.2%) on main secondary outcomes at 24 months. Regarding the primary outcome, there was no beneficial treatment effect on hospital admissions/ death during follow-up, with 20.2% (33/163) of controls and 23.3% (38/163) of the therapy group deceased or admitted (adjusted odds-ratio 1.16; P= 0.579; 95% confidence interval 0.68 to 1.99). For secondary outcomes there was no treatment effect on frequency of substance use or perceived negative consequences, but a statistically significant effect of therapy on amount used per substance-using day (adjusted odds-ratios: (a) for main substance 1.50; P=0.016; 1.08 to 2.09, (b) all substances 1.48; P=0.017; 1.07 to 2.05). There was a statistically significant treatment effect on readiness to change use at 12 months (adjusted odds-ratio 2.05; P=0.004; 1.26 to 3.31), not maintained at 24 months. There were no treatment effects on assessed clinical outcomes. Conclusions Integrated motivational interviewing and cognitive behaviour therapy for people with psychosis and substance misuse does not improve outcome in terms of hospitalisation, symptom outcomes or functioning. It does result in a reduction in amount of substance use which is maintained over the year’s follow up. Trial registration Current Controlled Trials: ISRCTN14404480

Cannabidiol exerts anti-convulsant effects in animal models of temporal lobe and partial seizures

Cannabis sativa has been associated with contradictory effects upon seizure states despite its medicinal use by numerous people with epilepsy. We have recently shown that the phytocannabinoid cannabidiol (CBD) reduces seizure severity and lethality in the well-established in vivo model of pentylenetetrazoleinduced generalised seizures, suggesting that earlier, small-scale clinical trials examining CBD effects in people with epilepsy warrant renewed attention. Here, we report the effects of pure CBD (1, 10 and 100 mg/kg) in two other established rodent seizure models, the acute pilocarpine model of temporal lobe seizure and the penicillin model of partial seizure. Seizure activity was video recorded and scored offline using model-specific seizure severity scales. In the pilocarpine model CBD (all doses) significantly reduced the percentage of animals experiencing the most severe seizures. In the penicillin model, CBD (�10 mg/kg) significantly decreased the percentage mortality as a result of seizures; CBD (all doses) also decreased the percentage of animals experiencing the most severe tonic–clonic seizures. These results extend the anticonvulsant profile of CBD; when combined with a reported absence of psychoactive effects, this evidence strongly supports CBD as a therapeutic candidate for a diverse range of human epilepsies.

Markov models of aging: theory and practice

We review and structure some of the mathematical and statistical models that have been developed over the past half century to grapple with theoretical and experimental questions about the stochastic development of aging over the life course. We suggest that the mathematical models are in large part addressing the problem of partitioning the randomness in aging: How does aging vary between individuals, and within an individual over the lifecourse? How much of the variation is inherently related to some qualities of the individual, and how much is entirely random? How much of the randomness is cumulative, and how much is merely short-term flutter? We propose that recent lines of statistical inquiry in survival analysis could usefully grapple with these questions, all the more so if they were more explicitly linked to the relevant mathematical and biological models of aging. To this end, we describe points of contact among the various lines of mathematical and statistical research. We suggest some directions for future work, including the exploration of information-theoretic measures for evaluating components of stochastic models as the basis for analyzing experiments and anchoring theoretical discussions of aging.