A metacognitive contextual intervention to enhance error awareness and functional outcome following traumatic brain injury: A single-case experimental design

Very few empirically validated interventions for improving metacognitive skills (i.e., self-awareness and self-regulation) and functional outcomes have been reported. This single-case experimental study presents JM, a 36-year-old man with a very severe traumatic brain injury (TBI) who demonstrated long-term awareness deficits. Treatment at four years post-injury involved a metacognitive contextual intervention based on a conceptualization of neuro-cognitive, psychological, and socio-environmental factors contributing to his awareness deficits. The 16-week intervention targeted error awareness and self-correction in two real life settings: (a) cooking at home: and (b) volunteer work. Outcome measures included behavioral observation of error behavior and standardized awareness measures. Relative to baseline performance in the cooking setting, JM demonstrated a 44% reduction in error frequency and increased self-correction. Although no spontaneous generalization was evident in the volunteer work setting, specific training in this environment led to a 39% decrease in errors. JM later gained paid employment and received brief metacognitive training in his work environment. JM's global self-knowledge of deficits assessed by self-report was unchanged after the program. Overall, the study provides preliminary support for a metacognitive contextual approach to improve error awareness and functional Outcome in real life settings.

Artificial pumping errors in the Kool-Parker scaling model of soil moisture hysteresis

Hysteresis models that eliminate the artificial pumping errors associated with the Kool-Parker (KP) soil moisture hysteresis model, such as the Parker-Lenhard (PL) method, can be computationally demanding in unsaturated transport models since they need to retain the wetting-drying history of the system. The pumping errors in these models need to be eliminated for correct simulation of cyclical systems (e.g. transport above a tidally forced watertable, infiltration and redistribution under periodic irrigation) if the soils exhibit significant hysteresis. A modification is made here to the PL method that allows it to be more readily applied to numerical models by eliminating the need to store a large number of soil moisture reversal points. The modified-PL method largely eliminates any artificial pumping error and so essentially retains the accuracy of the original PL approach. The modified-PL method is implemented in HYDRUS-1D (version 2.0), which is then used to simulate cyclic capillary fringe dynamics to show the influence of removing artificial pumping errors and to demonstrate the ease of implementation. Artificial pumping errors are shown to be significant for the soils and system characteristics used here in numerical experiments of transport above a fluctuating watertable. (c) 2005 Elsevier B.V. All rights reserved.

Error-correcting codes on a Bethe-like lattice

We analyse Gallager codes by employing a simple mean-field approximation that distorts the model geometry and preserves important interactions between sites. The method naturally recovers the probability propagation decoding algorithm as a minimization of a proper free-energy. We find a thermodynamical phase transition that coincides with information theoretical upper-bounds and explain the practical code performance in terms of the free-energy landscape.

Developing a scalable model of recombinant protein yield from Pichia pastoris:the influence of culture conditions, biomass and induction regime

Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time.

A review of the surgical options for the correction of presbyopia

Presbyopia is an age-related eye condition where one of the signs is the reduction in the amplitude of accommodation, resulting in the loss of ability to change the eye's focus from far to near. It is the most common age-related ailments affecting everyone around their mid-40s. Methods for the correction of presbyopia include contact lens and spectacle options but the surgical correction of presbyopia still remains a significant challenge for refractive surgeons. Surgical strategies for dealing with presbyopia may be extraocular (corneal or scleral) or intraocular (removal and replacement of the crystalline lens or some type of treatment on the crystalline lens itself). There are however a number of limitations and considerations that have limited the widespread acceptance of surgical correction of presbyopia. Each surgical strategy presents its own unique set of advantages and disadvantages. For example, lens removal and replacement with an intraocular lens may not be preferable in a young patient with presbyopia without a refractive error. Similarly treatment on the crystalline lens may not be a suitable choice for a patient with early signs of cataract. This article is a review of the options available and those that are in development stages and are likely to be available in the near future for the surgical correction of presbyopia.

Canonical solution groups of a homomorphism : manipulator kinematics, nonparametric regression and distributed object systems

The kinematic mapping of a rigid open-link manipulator is a homomorphism between Lie groups. The homomorphisrn has solution groups that act on an inverse kinematic solution element. A canonical representation of solution group operators that act on a solution element of three and seven degree-of-freedom (do!) dextrous manipulators is determined by geometric analysis. Seven canonical solution groups are determined for the seven do! Robotics Research K-1207 and Hollerbach arms. The solution element of a dextrous manipulator is a collection of trivial fibre bundles with solution fibres homotopic to the Torus. If fibre solutions are parameterised by a scalar, a direct inverse funct.ion that maps the scalar and Cartesian base space coordinates to solution element fibre coordinates may be defined. A direct inverse pararneterisation of a solution element may be approximated by a local linear map generated by an inverse augmented Jacobian correction of a linear interpolation. The action of canonical solution group operators on a local linear approximation of the solution element of inverse kinematics of dextrous manipulators generates cyclical solutions. The solution representation is proposed as a model of inverse kinematic transformations in primate nervous systems. Simultaneous calibration of a composition of stereo-camera and manipulator kinematic models is under-determined by equi-output parameter groups in the composition of stereo-camera and Denavit Hartenberg (DH) rnodels. An error measure for simultaneous calibration of a composition of models is derived and parameter subsets with no equi-output groups are determined by numerical experiments to simultaneously calibrate the composition of homogeneous or pan-tilt stereo-camera with DH models. For acceleration of exact Newton second-order re-calibration of DH parameters after a sequential calibration of stereo-camera and DH parameters, an optimal numerical evaluation of DH matrix first order and second order error derivatives with respect to a re-calibration error function is derived, implemented and tested. A distributed object environment for point and click image-based tele-command of manipulators and stereo-cameras is specified and implemented that supports rapid prototyping of numerical experiments in distributed system control. The environment is validated by a hierarchical k-fold cross validated calibration to Cartesian space of a radial basis function regression correction of an affine stereo model. Basic design and performance requirements are defined for scalable virtual micro-kernels that broker inter-Java-virtual-machine remote method invocations between components of secure manageable fault-tolerant open distributed agile Total Quality Managed ISO 9000+ conformant Just in Time manufacturing systems.

Managing uncertainty in complex stochastic models: design and emulation of a Rabies model

In this paper we present a novel method for emulating a stochastic, or random output, computer model and show its application to a complex rabies model. The method is evaluated both in terms of accuracy and computational efficiency on synthetic data and the rabies model. We address the issue of experimental design and provide empirical evidence on the effectiveness of utilizing replicate model evaluations compared to a space-filling design. We employ the Mahalanobis error measure to validate the heteroscedastic Gaussian process based emulator predictions for both the mean and (co)variance. The emulator allows efficient screening to identify important model inputs and better understanding of the complex behaviour of the rabies model.