Design and synthesis of hierarchical MnO2 nanospheres/carbon nanotubes/conducting polymer ternary composite for high performance electrochemical electrodes.

For efficient use of metal oxides, such as MnO(2) and RuO(2), in pseudocapacitors and other electrochemical applications, the poor conductivity of the metal oxide is a major problem. To tackle the problem, we have designed a ternary nanocomposite film composed of metal oxide (MnO(2)), carbon nanotube (CNT), and conducting polymer (CP). Each component in the MnO(2)/CNT/CP film provides unique and critical function to achieve optimized electrochemical properties. The electrochemical performance of the film is evaluated by cyclic voltammetry, and constant-current charge/discharge cycling techniques. Specific capacitance (SC) of the ternary composite electrode can reach 427 F/g. Even at high mass loading and high concentration of MnO(2) (60%), the film still showed SC value as high as 200 F/g. The electrode also exhibited excellent charge/discharge rate and good cycling stability, retaining over 99% of its initial charge after 1000 cycles. The results demonstrated that MnO(2) is effectively utilized with assistance of other components (fFWNTs and poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) in the electrode. Such ternary composite is very promising for the next generation high performance electrochemical supercapacitors.

Radium and barium removal through blending hydraulic fracturing fluids with acid mine drainage.

Wastewaters generated during hydraulic fracturing of the Marcellus Shale typically contain high concentrations of salts, naturally occurring radioactive material (NORM), and metals, such as barium, that pose environmental and public health risks upon inadequate treatment and disposal. In addition, fresh water scarcity in dry regions or during periods of drought could limit shale gas development. This paper explores the possibility of using alternative water sources and their impact on NORM levels through blending acid mine drainage (AMD) effluent with recycled hydraulic fracturing flowback fluids (HFFFs). We conducted a series of laboratory experiments in which the chemistry and NORM of different mix proportions of AMD and HFFF were examined after reacting for 48 h. The experimental data combined with geochemical modeling and X-ray diffraction analysis suggest that several ions, including sulfate, iron, barium, strontium, and a large portion of radium (60-100%), precipitated into newly formed solids composed mainly of Sr barite within the first ∼ 10 h of mixing. The results imply that blending AMD and HFFF could be an effective management practice for both remediation of the high NORM in the Marcellus HFFF wastewater and beneficial utilization of AMD that is currently contaminating waterways in northeastern U.S.A.

A Dynamic Directional Model for Effective Brain Connectivity using Electrocorticographic (ECoG) Time Series.

We introduce a dynamic directional model (DDM) for studying brain effective connectivity based on intracranial electrocorticographic (ECoG) time series. The DDM consists of two parts: a set of differential equations describing neuronal activity of brain components (state equations), and observation equations linking the underlying neuronal states to observed data. When applied to functional MRI or EEG data, DDMs usually have complex formulations and thus can accommodate only a few regions, due to limitations in spatial resolution and/or temporal resolution of these imaging modalities. In contrast, we formulate our model in the context of ECoG data. The combined high temporal and spatial resolution of ECoG data result in a much simpler DDM, allowing investigation of complex connections between many regions. To identify functionally segregated sub-networks, a form of biologically economical brain networks, we propose the Potts model for the DDM parameters. The neuronal states of brain components are represented by cubic spline bases and the parameters are estimated by minimizing a log-likelihood criterion that combines the state and observation equations. The Potts model is converted to the Potts penalty in the penalized regression approach to achieve sparsity in parameter estimation, for which a fast iterative algorithm is developed. The methods are applied to an auditory ECoG dataset.

Percutaneous Revision of a Testicular Prosthesis is Safe, Cost-effective, and Provides Good Patient Satisfaction.

Office-based percutaneous revision of a testicular prosthesis has never been reported. A patient received a testicular prosthesis but was dissatisfied with the firmness of the implant. In an office setting, the prosthesis was inflated with additional fluid via a percutaneous approach. Evaluated outcomes included patient satisfaction, prosthesis size, recovery time, and cost savings. The patient was satisfied, with no infection, leak, or complication after more than 1 year of follow-up, at significantly less cost than revision surgery. Percutaneous adjustment of testicular prosthesis fill-volume can be safe, inexpensive, and result in good patient satisfaction.

FUELGEN: effective evolutionary design of refuellings for pressurized water reactors

The paper describes the design of an efficient and robust genetic algorithm for the nuclear fuel loading problem (i.e., refuellings: the in-core fuel management problem) - a complex combinatorial, multimodal optimisation., Evolutionary computation as performed by FUELGEN replaces heuristic search of the kind performed by the FUELCON expert system (CAI 12/4), to solve the same problem. In contrast to the traditional genetic algorithm which makes strong requirements on the representation used and its parameter setting in order to be efficient, the results of recent research results on new, robust genetic algorithms show that representations unsuitable for the traditional genetic algorithm can still be used to good effect with little parameter adjustment. The representation presented here is a simple symbolic one with no linkage attributes, making the genetic algorithm particularly easy to apply to fuel loading problems with differing core structures and assembly inventories. A nonlinear fitness function has been constructed to direct the search efficiently in the presence of the many local optima that result from the constraint on solutions.

Automatic and effective multi-dimensional parallelisation of structured mesh based codes

The most common parallelisation strategy for many Computational Mechanics (CM) (typified by Computational Fluid Dynamics (CFD) applications) which use structured meshes, involves a 1D partition based upon slabs of cells. However, many CFD codes employ pipeline operations in their solution procedure. For parallelised versions of such codes to scale well they must employ two (or more) dimensional partitions. This paper describes an algorithmic approach to the multi-dimensional mesh partitioning in code parallelisation, its implementation in a toolkit for almost automatically transforming scalar codes to parallel form, and its testing on a range of ‘real-world’ FORTRAN codes. The concept of multi-dimensional partitioning is straightforward, but non-trivial to represent as a sufficiently generic algorithm so that it can be embedded in a code transformation tool. The results of the tests on fine real-world codes demonstrate clear improvements in parallel performance and scalability (over a 1D partition). This is matched by a huge reduction in the time required to develop the parallel versions when hand coded – from weeks/months down to hours/days.

Effective e-moderation in e-courses

E-learning promises people the ability to learn at a time and place to suit their needs. However, we frequently assume they can automatically adapt to an online environment. This is not the case. They need focussed support on their journey of development from e-user to e-learner. However, many fail to complete this journey. It is essential we identify how best to support them if we are to fully realise the potential of e-learning. This paper builds on previous research and presents an e-moderation activity model for tutor-led courses.

Magnetic damping of levitated liquid droplets in AC and DC field

The intense AC magnetic field required to produce levitation in terrestrial conditions, along with the buoyancy and thermo-capillary forces, results in turbulent convective flow within the droplet. The use of a homogenous DC magnetic field allows the convective flow to be damped. However the turbulence properties are affected at the same time, leading to a possibility that the effective turbulent damping is considerably reduced. The MHD modified K-Omega turbulence model allows the investigation of the effect of magnetic field on the turbulence. The model incorporates free surface deformation, the temperature dependent surface tension, turbulent momentum transport, electromagnetic and gravity forces. The model is adapted to incorporate a periodic laser heating at the top of the droplet, which have been used to measure the thermal conductivity of the material by calculating the phase lag between the frequency of the laser heating and the temperature response at the bottom. The numerical simulations show that with the gradual increase of the DC field the fluid flow within the droplet is initially increasing in intensity. Only after a certain threshold magnitude of the field the flow intensity starts to decrease. In order to achieve the flow conditions close to the ‘laminar’ a D.C. magnetic field >4 Tesla is required to measure the thermal conductivity accurately. The reduction in the AC field driven flow in the main body of the drop leads to a noticeable thermo-capillary convection at the edge of the droplet. The uniform vertical DC magnetic field does not stop a translational oscillation of the droplet along the field, which is caused by the variation in total levitation force due to the time-dependent surface deformation.

Barriers to effective pain management in sickle cell disease

Sickle cell disease (SCD) is a long-term condition that would benefit from a long-term conditions approach to its care and management. SCD is growing in prevalence, affecting 10,000-12,000 people in the UK, with SCD sufferers having an increased life expectancy from in the past. The most problematic aspect of managing SCD is management of the pain from vaso-occlusive crises. Vaso-occlusive pain is the most common reason for hospital admissions in people with SCD and accounts for large numbers of accident and emergency (A&E) attendances. A literature review was carried out to examine the management of vaso-occlusive pain in SCD. The review identified three main barriers to effective pain management in SCD: the manifestation of vaso-occlusive pain, the sociocultural factors affecting pain assessment, and the concerns regarding addiction and pseudo-addiction. Addressing these barriers will allow people with SCD to have their pain managed more effectively, improve their quality of life and potentially reduce A&E attendances and admissions to hospital.

Can effective teaching and learning strategies help student nurses to retain drug calculation skills?

Student nurses need to develop and retain drug calculation skills in order accurately to calculate drug dosages in clinical practice. If student nurses are to qualify and be fit to practise accurate drug calculation skills, then educational strategies need to not only show that the skills of student nurses have improved but that these skills have been retained over a period of time. A quasi-experimental approach was used to test the effectiveness of a range of strategies in improving retention of drug calculation skills. The results from an IV additive drug calculation test were used to compare the drug calculation skills of student nurses between two groups of students who had received different approaches to teaching drug calculation skills. The sample group received specific teaching and learning strategies in relation to drug calculation skills and the second group received only lectures on drug calculation skills. All test results for students were anonymous. The results from the test for both groups were statistically analysed using the Mann Whitney test to ascertain whether the range of strategies improved the results for the IV additive test. The results were further analysed and compared to ascertain the types and numbers of errors made in each of the sample groups. The results showed that there is a highly significant difference between the two samples using a two-tailed test (U=39.5, p<0.001). The strategies implemented therefore did make a difference to the retention of drug calculation skills in the students in the intervention group. Further research is required into the retention of drug calculation skills by students and nurses, but there does appears to be evidence to suggest that sound teaching and learning strategies do result in better retention of drug calculation skills.