Understanding the Performance of Melt-Extruded Poly(ethylene oxide)–Bicalutamide Solid Dispersions: Characterisation of Microstructural Properties Using Thermal, Spectroscopic and Drug Release Methods

In this article, we have prepared hot-melt-extruded solid dispersions of bicalutamide (BL) using poly(ethylene oxide) (PEO) as a matrix platform. Prior to preparation, miscibility of PEO and BL was assessed using differential scanning calorimetry (DSC). The onset of BL melting was signi?cantly depressed in the presence of PEO, and using Flory– Huggins (FH) theory, we identi?ed a negative value of -3.4, con?rming miscibility. Additionally, using FH lattice theory, we estimated the Gibbs free energy of mixing which was shown to be negative, passing through a minimum at a polymer fraction of 0.55. Using these data, solid dispersions at drug-to-polymer ratios of 1:10, 2:10 and 3:10 were prepared via hot-melt extrusion. Using a combination of DSC, powder X-ray diffractometry and scanning electron
microscopy, amorphous dispersions of BL were con?rmed at the lower two drug loadings. At the 3:10 BL to PEO ratio, crystalline BL was detected. The percent crystallinity of PEO was reduced by approximately 10% in all formulations following extrusion. The increased amorphous content within PEO following extrusion accommodated amorphous BL at drug to polymer loadings up to 2:10; however, the increased amorphous domains with PEO following extrusion were not suf?cient to fully accommodate BL at drug-to-polymer ratios of 3:10.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised. (C) 2011 Elsevier Ltd. All rights reserved.

Electrical methods of controlling bacterial adhesion and biofilm on device surfaces.

This review will summarize the significant body of research within the field of electrical methods of controlling the growth of microorganisms. We examine the progress from early work using current to kill bacteria in static fluids to more realistic treatment scenarios such as flow-through systems designed to imitate the human urinary tract. Additionally, the electrical enhancement of biocide and antibiotic efficacy will be examined alongside recent innovations including the biological applications of acoustic energy systems to prevent bacterial surface adherence. Particular attention will be paid to the electrical engineering aspects of previous work, such as electrode composition, quantitative electrical parameters and the conductive medium used. Scrutiny of published systems from an electrical engineering perspective will help to facilitate improved understanding of the methods, devices and mechanisms that have been effective in controlling bacteria, as well as providing insights and strategies to improve the performance of such systems and develop the next generation of antimicrobial bioelectric materials.

TIME-RESOLVED OPTICAL-EMISSION AND ELECTRON-ENERGY DISTRIBUTION FUNCTION MEASUREMENTS IN RF PLASMAS

Comparisons between experimentally measured time-dependent electron energy distribution functions and optical emission intensities are reported for low-frequency (100 and 400 kHz) radio-frequency driven discharges in argon. The electron energy distribution functions were measured with a time-resolved Langmuir probe system. Time-resolved optical emissions of argon resonance lines at 687.1 and 750.4 nm were determined by photon-counting methods. Known ground-state and metastable-state excitation cross sections were used along with the measured electron energy distribution functions to calculate the time dependence of the optical emission intensity. It was found that a calculation using only the ground-state cross sections gave the best agreement with the time dependence of the measured optical emission. Time-dependent electron density, electron temperature, and plasma potential measurements are also reported.

Development and comparison of a Primer-Probe Energy Transfer based assay and a 5 ' conjugated Minor Groove Binder assay for sensitive real-time PCR detection of infectious laryngotracheitis virus

In this study the design and development of two real-time PCR assays for the rapid, sensitive and specific detection of infectious laryngotracheitis virus (ILTV) DNA is described. A Primer-Probe Energy Transfer (PriProET) assay and 5' conjugated Minor Groove Binder (MGB) method are compared and contrasted. Both have been designed to target the thymidine kinase gene of the ILTV genome. Both PriProET and MGB assays are capable of detecting 20 copies of a DNA standard per reaction and are linear from 2 x 10(8) to 2 x 10(2) copies/mu l. Neither PriProET, nor MGB reacted with heterologous herpesviruses, indicating a high specificity of the two methods as novel tools for virus detection and identification. This study demonstrates the suitability of PriProET and 5' conjugated MGB probes as real-time PCR chemistries for the diagnosis of respiratory diseases caused by ILTV. (C) 2011 Elsevier B.V. All rights reserved.

B-spline methods in R-matrix theory for scattering in two-electron systems

The use of B-spline basis sets in R-matrix theory for scattering processes has been investigated. In the present approach a B-spline basis is used for the description of the inner region, which is matched to the physical outgoing wavefunctions by the R-matrix. Using B-splines, continuum basis functions can be determined easily, while pseudostates can be included naturally. The accuracy for low-energy scattering processes is demonstrated by calculating inelastic scattering cross sections for e colliding on H. Very good agreement with other calculations has been obtained. Further extensions of the codes to quasi two-electron systems and general atoms are discussed as well as the application to (multi) photoionization.

Digital Methods for Process Development in Manufacturing and Their Relevance to Value Driven Design

This paper examines the applicability of a digital manufacturing framework to the implementation of a Value Driven Design (VDD) approach for the development of a stiffened composite panel. It presents a means by which environmental considerations can be integrated with conventional product and process design drivers within a customized, digital environment. A composite forming process is used as an exemplar for the work which creates a collaborative environment for the integration of more traditional design drivers with parameters related to manufacturability as well as more sustainable processes and products. The environmental stakeholder is introduced to the VDD process through a customized product/process/resource (PPR) environment where application specific power consumption and material waste data has been measured and characterised in the process design interface. This allows the manufacturing planner to consider power consumption as a concurrent design driver and the inclusion of energy as a parameter in a VDD approach to the development of efficiently manufactured, sustainable transport systems.

Strategies for Energy-Efficient Resource Management of Hybrid Programming Models

Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.

Exchange potential from the common energy denominator approximation for the Kohn-Sham Green's function: Application to (hyper)polarizabilities of molecular chains

An approximate Kohn-Sham (KS) exchange potential v(xsigma)(CEDA) is developed, based on the common energy denominator approximation (CEDA) for the static orbital Green's function, which preserves the essential structure of the density response function. v(xsigma)(CEDA) is an explicit functional of the occupied KS orbitals, which has the Slater v(Ssigma) and response v(respsigma)(CEDA) potentials as its components. The latter exhibits the characteristic step structure with "diagonal" contributions from the orbital densities \psi(isigma)\(2), as well as "off-diagonal" ones from the occupied-occupied orbital products psi(isigma)psi(j(not equal1)sigma). Comparison of the results of atomic and molecular ground-state CEDA calculations with those of the Krieger-Li-Iafrate (KLI), exact exchange (EXX), and Hartree-Fock (HF) methods show, that both KLI and CEDA potentials can be considered as very good analytical "closure approximations" to the exact KS exchange potential. The total CEDA and KLI energies nearly coincide with the EXX ones and the corresponding orbital energies epsilon(isigma) are rather close to each other for the light atoms and small molecules considered. The CEDA, KLI, EXX-epsilon(isigma) values provide the qualitatively correct order of ionizations and they give an estimate of VIPs comparable to that of the HF Koopmans' theorem. However, the additional off-diagonal orbital structure of v(xsigma)(CEDA) appears to be essential for the calculated response properties of molecular chains. KLI already considerably improves the calculated (hyper)polarizabilities of the prototype hydrogen chains H-n over local density approximation (LDA) and standard generalized gradient approximations (GGAs), while the CEDA results are definitely an improvement over the KLI ones. The reasons of this success are the specific orbital structures of the CEDA and KLI response potentials, which produce in an external field an ultranonlocal field-counteracting exchange potential. (C) 2002 American Institute of Physics.

Monte Carlo radiation hydrodynamics:Methods, tests and application to Type Ia supernova ejecta

In astrophysical systems, radiation-matter interactions are important in transferring energy and momentum between the radiation field and the surrounding material. This coupling often makes it necessary to consider the role of radiation when modelling the dynamics of astrophysical fluids. During the last few years, there have been rapid developments in the use of Monte Carlo methods for numerical radiative transfer simulations. Here, we present an approach to radiation hydrodynamics that is based on coupling Monte Carlo radiative transfer techniques with finite-volume hydrodynamical methods in an operator-split manner. In particular, we adopt an indivisible packet formalism to discretize the radiation field into an ensemble of Monte Carlo packets and employ volume-based estimators to reconstruct the radiation field characteristics. In this paper the numerical tools of this method are presented and their accuracy is verified in a series of test calculations. Finally, as a practical example, we use our approach to study the influence of the radiation-matter coupling on the homologous expansion phase and the bolometric light curve of Type Ia supernova explosions. © 2012 The Authors Monthly Notices of the Royal Astronomical Society © 2012 RAS.

Voltage Sensing Using an Asynchronous Charge-to-Digital Converter for Energy-Autonomous Environments

In future systems with relatively unreliable and unpredictable energy sources such as harvesters, the system power supply may become non-deterministic. For energy effective operations, Vdd is an important parameter in any meaningful system control mechanism. Reliable and accurate on-chip voltage sensors are therefore indispensible for the power and computation management of such systems. Existing voltage sensing methods are not suitable because they usually require a stable and known reference (voltage, current, time, frequency, etc.), which is difficult to obtain in this environment. This paper describes an autonomous reference-free voltage sensor designed using an asynchronous counter powered by the charge on a capacitor and a small controller. Unlike existing methods, the voltage information is directly generated as a digital code. The sensor, fabricated in the 180 nm technology node, was tested successfully through performing measurements over the voltage range from 1.8 V down to 0.8 V.

The opportunities and limitations of using CFD in the development of wave energy converters

Most Wave Energy Converters (WECs) being developed are fundamentally different from known marine structures. Limited experience is a fundamental challenge for the design, especially issues concerning load assumptions and power estimates. Reynolds-Averaged Navier-Stokes (RANS) CFD methods are being used successfully in many areas of marine engineering. They have been shown to accurately simulate many hydrodynamic effects and are a helpful tool for investigating complex flows. The major drawback is the significant computational power required and the associated overhead with pre and post-processing. This paper presents the challenges and advantages in the application of RANS CFD methods in the design process of a wave energy converter and compares the time, labour and ultimately financial requirements for obtaining practical results.