Imagery rescripting as a brief stand-alone treatment for depressed patients with intrusive memories

Many depressed patients report intrusive and distressing memories of specific events in their lives. Where present, these memories are believed to act as a maintaining factor. A series of ten patients with major depressive disorder and intrusive memories, many of them reporting severe, chronic, or recurrent episodes of depression, were given an average of 8.1 sessions of imagery rescripting as a stand-alone treatment. Hierarchical linear modelling demonstrated large treatment effects that were well maintained at one year follow-up. Seven patients showed reliable improvement, and six patients clinically significant improvement. These gains were achieved entirely by working through patients' visual imagination and without verbal challenging of negative beliefs. Spontaneous changes in beliefs, rumination, and behaviour were nevertheless observed. (C) 2009 Elsevier Ltd. All rights reserved.

The combined effect of the application of a biocontrol agent Paecilomyces lilacinus, with various practices for the control of root-knot nematodes

The effectiveness of a formulated product containing spores of the naturally occurring fungus Paecilomyces lilacinus, strain 251, was evaluated against root-knot nematodes in pot and greenhouse experiments. Decrease of second-stage juveniles hatching from eggs was recorded by using the bio-nematicide at a dose of 4 kg ha(-1), while a further decrease was recorded by doubling the dose. However, the mortality rate decreased by increasing the inoculum level. Application of P. lilacinus and Bacillus firmus, singly or together in pot experiments, provided effective control of second-stage juveniles, eggs or egg masses of root-knot nematodes. In a greenhouse experiment, the bio-nematicide was evaluated for its potential to control root-knot nematodes either as a stand-alone method or in combination with soil solarization. Soil was solarized for 15 d and the bio-nematicide was applied just after the removal of the plastic sheet. Soil solarization for 15 d either alone or combined with the use of P. lilacinus did not provide satisfactory control of root-knot nematodes. The use of oxamyl, which was applied 2 weeks before and during transplanting, gave results similar to the commercial product containing P. lilacinus but superior to soil solarization. (C) 2007 Elsevier Ltd. All rights reserved.

Effects of a non-chemical nematicide combined with soil solarization for the control of root-knot nematodes

The effectiveness of a formulated bio-nematicide product containing lyophilized bacteria spores of Bacillus firmus was evaluated against root-knot nematodes (RKN) in greenhouse and field experiments. A decrease of second stage juveniles hatching from eggs was recorded by using the bio-nematicide at a dose of 0.9 g kg(-1) of soil while further a decrease was recorded by doubling the dose. However, the mortality rate decreased as the inoculurn level increased. Exposure of either second stage juveniles or egg masses to temperatures of 35-40 degrees C for 1-4 weeks had a marked effect on their survival. In a field experiment, the bio-nematicide was evaluated for its potential to control RKN either as a stand-alone method or in combination with soil solarization. The latter was tested for 15-30 days and the bionematicide was applied just before soil coverage with the plastic sheet or just after its removal. Soil solarization either for 15-30 days provided satisfactory control of RKN. The combination of soil solarization with the bio-nematicide improved nematode control and gave results similar to the chemical treatment. (c) 2007 Elsevier Ltd. All rights reserved.

Wireless sensor networks

This paper provides an introduction to Wireless Sensor Networks (WSN), their applications in the field of control engineering and elsewhere and gives pointers to future research needs. WSN are collections of stand-alone devices which, typically, have one or more sensors (e.g. temperature, light level), some limited processing capability and a wireless interface allowing communication with a base station. As they are usually battery powered, the biggest challenge is to achieve the necessary monitoring whilst using the least amount of power.

A data forest: multi-dimensional visualization

As Terabyte datasets become the norm, the focus has shifted away from our ability to produce and store ever larger amounts of data, onto its utilization. It is becoming increasingly difficult to gain meaningful insights into the data produced. Also many forms of the data we are currently producing cannot easily fit into traditional visualization methods. This paper presents a new and novel visualization technique based on the concept of a Data Forest. Our Data Forest has been designed to be used with vir tual reality (VR) as its presentation method. VR is a natural medium for investigating large datasets. Our approach can easily be adapted to be used in a variety of different ways, from a stand alone single user environment to large multi-user collaborative environments. A test application is presented using multi-dimensional data to demonstrate the concepts involved.

Multiple PID mapping using neural networks in a MIMO steam generator system

A neural network was used to map three PID operating regions for a two-input two-output steam generator system. The network was used in stand alone feedforward operation to control the whole operating range of the process, after being trained from the PID controllers corresponding to each control region. The network inputs are the plant error signals, their integral, their derivative and a 4-error delay train.

Impact of a new anisotropic rheology on simulations of Arctic sea ice

new rheology that explicitly accounts for the subcontinuum anisotropy of the sea ice cover is implemented into the Los Alamos sea ice model. This is in contrast to all models of sea ice included in global circulation models that use an isotropic rheology. The model contains one new prognostic variable, the local structure tensor, which quantifies the degree of anisotropy of the sea ice, and two parameters that set the time scale of the evolution of this tensor. The anisotropic rheology provides a subcontinuum description of the mechanical behavior of sea ice and accounts for a continuum scale stress with large shear to compression ratio and tensile stress component. Results over the Arctic of a stand-alone version of the model are presented and anisotropic model sensitivity runs are compared with a reference elasto-visco-plastic simulation. Under realistic forcing sea ice quickly becomes highly anisotropic over large length scales, as is observed from satellite imagery. The influence of the new rheology on the state and dynamics of the sea ice cover is discussed. Our reference anisotropic run reveals that the new rheology leads to a substantial change of the spatial distribution of ice thickness and ice drift relative to the reference standard visco-plastic isotropic run, with ice thickness regionally increased by more than 1 m, and ice speed reduced by up to 50%.

The simulation of the opposing fluxes of latent heat and CO2 over various land-use types: coupling a gas exchange model to a mesoscale atmospheric model

A mesoscale meteorological model (FOOT3DK) is coupled with a gas exchange model to simulate surface fluxes of CO2 and H2O under field conditions. The gas exchange model consists of a C3 single leaf photosynthesis sub-model and an extended big leaf (sun/shade) sub-model that divides the canopy into sunlit and shaded fractions. Simulated CO2 fluxes of the stand-alone version of the gas exchange model correspond well to eddy-covariance measurements at a test site in a rural area in the west of Germany. The coupled FOOT3DK/gas exchange model is validated for the diurnal cycle at singular grid points, and delivers realistic fluxes with respect to their order of magnitude and to the general daily course. Compared to the Jarvis-based big leaf scheme, simulations of latent heat fluxes with a photosynthesis-based scheme for stomatal conductance are more realistic. As expected, flux averages are strongly influenced by the underlying land cover. While the simulated net ecosystem exchange is highly correlated with leaf area index, this correlation is much weaker for the latent heat flux. Photosynthetic CO2 uptake is associated with transpirational water loss via the stomata, and the resulting opposing surface fluxes of CO2 and H2O are reproduced with the model approach. Over vegetated surfaces it is shown that the coupling of a photosynthesis-based gas exchange model with the land-surface scheme of a mesoscale model results in more realistic simulated latent heat fluxes.

Random Prism: a noise-tolerant alternative to Random Forests

Ensemble learning can be used to increase the overall classification accuracy of a classifier by generating multiple base classifiers and combining their classification results. A frequently used family of base classifiers for ensemble learning are decision trees. However, alternative approaches can potentially be used, such as the Prism family of algorithms that also induces classification rules. Compared with decision trees, Prism algorithms generate modular classification rules that cannot necessarily be represented in the form of a decision tree. Prism algorithms produce a similar classification accuracy compared with decision trees. However, in some cases, for example, if there is noise in the training and test data, Prism algorithms can outperform decision trees by achieving a higher classification accuracy. However, Prism still tends to overfit on noisy data; hence, ensemble learners have been adopted in this work to reduce the overfitting. This paper describes the development of an ensemble learner using a member of the Prism family as the base classifier to reduce the overfitting of Prism algorithms on noisy datasets. The developed ensemble classifier is compared with a stand-alone Prism classifier in terms of classification accuracy and resistance to noise.

Cyborgs in space

Practical realisation of Cyborgs opens up significant new opportunities in many fields. In particular when it comes to space travel many of the limitations faced by humans, in stand-alone form, are transposed by the adoption of a cyborg persona. In this article a look is taken at different types of Brain-Computer interface which can be employed to realise Cyborgs, biology-technology hybrids. e approach taken is a practical one with applications in mind, although some wider implications are also considered. In particular results from experiments are discussed in terms of their meaning and application possibilities. e article is written from the perspective of scientific experimentation opening up realistic possibilities to be faced in the future rather than giving conclusive comments on the technologies employed. Human implantation and the merger of biology and technology are though important elements.

The Joint UK Land Environment Simulator (JULES), model description – part 1: energy and water fluxes

This manuscript describes the energy and water components of a new community land surface model called the Joint UK Land Environment Simulator (JULES). This is developed from the Met Office Surface Exchange Scheme (MOSES). It can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. The JULES model has been coupled to the Met Office Unified Model (UM) and as such provides a unique opportunity for the research community to contribute their research to improve both world-leading operational weather forecasting and climate change prediction systems. In addition JULES, and its forerunner MOSES, have been the basis for a number of very high-profile papers concerning the land-surface and climate over the last decade. JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

Optimization of a sea ice model using basinwide observations of Arctic sea ice thickness, extent, and velocity

A stand-alone sea ice model is tuned and validated using satellite-derived, basinwide observations of sea ice thickness, extent, and velocity from the years 1993 to 2001. This is the first time that basin-scale measurements of sea ice thickness have been used for this purpose. The model is based on the CICE sea ice model code developed at the Los Alamos National Laboratory, with some minor modifications, and forcing consists of 40-yr ECMWF Re-Analysis (ERA-40) and Polar Exchange at the Sea Surface (POLES) data. Three parameters are varied in the tuning process: Ca, the air–ice drag coefficient; P*, the ice strength parameter; and α, the broadband albedo of cold bare ice, with the aim being to determine the subset of this three-dimensional parameter space that gives the best simultaneous agreement with observations with this forcing set. It is found that observations of sea ice extent and velocity alone are not sufficient to unambiguously tune the model, and that sea ice thickness measurements are necessary to locate a unique subset of parameter space in which simultaneous agreement is achieved with all three observational datasets.

Responding to the EU Emissions Trading Scheme: an empirical analysis of corporate carbon disclosure strategy

The purpose of this paper is to explore how companies that hold carbon trading accounts under European Union Emissions Trading Scheme (EU ETS) respond to the climate change by using disclosures on carbon emissions as a means to generate legitimacy compared to others. The study is based on disclosures made in annual reports and stand-alone sustainability reports of UK listed companies from 2001- 2012. The study uses content analysis to capture both the quality and volume of the carbon disclosures. The results show that there is a significant increase in both the quality and volume of the carbon disclosures after the launch of EU ETS. Companies with carbon trading accounts provide greater detailed disclosures as compared to the others without an account. We also find that company size is positively correlated with the disclosures while the association with the industry produces an inconclusive result.

A method to assess individual research outputs

We present here a straightforward method which can be used to obtain a quantitative indication of an individual research output for an academic. Different versions, selections and options are presented to enable a user to easily calculate values both for stand-alone papers and overall for the collection of outputs for a person. The procedure is particularly useful as a metric to give a quantitative indication of the research output of a person over a time window. Examples are included to show how the method works in practice and how it compares to alternative techniques.

Progress report on longitudinal and cross-sectional study of carbon disclosure strategies: evidence from UK listed companies

Global warming has attracted attention from all over the world and led to the concern about carbon emission. Kyoto Protocol, as the first major international regulatory emission trading scheme, was introduced in 1997 and outlined the strategies for reducing carbon emission (Ratnatunga et al., 2011). As the increased interest in carbon reduction the Protocol came into force in 2005, currently there are already 191 nations ratifying the Protocol(UNFCCC, 2012). Under the cap-and-trade schemes, each company has its carbon emission target. When company’s carbon emission exceeds the target the company will either face fines or buy emission allowance from other companies. Thus unlike most of the other social and environmental issues carbon emission could trigger cost for companies in introducing low-emission equipment and systems and also emission allowance cost when they emit more than their targets. Despite the importance of carbon emission to companies, carbon emission reporting is still operating under unregulated environment and companies are only required to disclose when it is material either in value or in substances (Miller, 2005, Deegan and Rankin, 1997). Even though there is still an increase in the volume of carbon emission disclosures in company’s financial reports and stand-alone social and environmental reports to show their concern of the environment and also their social responsibility (Peters and Romi, 2009), the motivations behind corporate carbon emission disclosures and whether carbon disclosures have impact on corporate environmental reputation and financial performance have not yet to explore. The problems with carbon emission lie on both the financial side and non-financial side of corporate governance. On one hand corporate needs to spend money in reducing carbon emission or paying penalties when they emit more than allowed. On the other hand as the public are more interested in environmental issues than before carbon emission could also impact on the image of corporate regarding to its environmental performance. The importance of carbon emission issue are beginning to be recognized by companies from different industries as one of the critical issues in supply chain management (Lee, 2011) and 80% of companies analysed are facing carbon risks resulting from emissions in the companies’ supply chain as shown in a study conducted by the Investor Responsibility Research Centre Institute for Corporate Responsibility (IRRCI) and over 80% of the companies analysed found that the majority of greenhouse gas (GHG) emission are from electricity and other direct suppliers (Trucost, 2009). The review of extant literature shows the increased importance of carbon emission issues and the gap in the study of carbon reporting and disclosures and also the study which links corporate environmental reputation and corporate financial performance with carbon reporting (Lohmann, 2009a, Ratnatunga and Balachandran, 2009, Bebbington and Larrinaga-Gonzalez, 2008). This study would focus on investigating the current status of UK carbon emission disclosures, the determinant factors of corporate carbon disclosure, and the relationship between carbon emission disclosures and corporate environmental reputation and financial performance of UK listed companies from 2004-2012 and explore the explanatory power of classical disclosure theories.