An ESDIRK method with sensitivity analysis capabilities

A new algorithm for numerical sensitivity analysis of ordinary differential equations (ODEs) is presented. The underlying ODE solver belongs to the Runge–Kutta family. The algorithm calculates sensitivities with respect to problem parameters and initial conditions, exploiting the special structure of the sensitivity equations. A key feature is the reuse of information already computed for the state integration, hereby minimizing the extra effort required for sensitivity integration. Through case studies the new algorithm is compared to an extrapolation method and to the more established BDF based approaches. Several advantages of the new approach are demonstrated, especially when frequent discontinuities are present, which renders the new algorithm particularly suitable for dynamic optimization purposes.     

Structural dependence of chemical durability in modified aluminoborate glasses

Alkali and alkaline earth aluminoborate glasses feature high resistance to cracking under sharp contact loading compared to other oxide glasses. However, due to the high content of hygroscopic B₂O₃, it is expected that applications of these glasses could be hindered by poor chemical durability in aqueous solutions. Indeed, the compositional and structural dependence of their dissolution kinetics remains unexplored. In this work, we correlate the dissolution rates of aluminoborate glasses in acidic, neutral, and basic solutions with the structural changes induced by varying the aluminum-to-boron ratio. In detail, we investigate a total of seventeen magnesium, lithium, and sodium aluminoborate glasses with fixed modifier content of 25 mol%. We show that the structural changes induced by alumina depend on the network modifier. We also demonstrate a correlation between the chemical durability at various pH values and the structural changes in Mg-, Li- and Na-aluminoborate glasses. The substitution of alumina by boron oxide leads to a general decrease in chemical corrosion in neutral and acidic solutions. The lowest dissolution rate value is observed in Mg-aluminoborate glasses, as a consequence of the intermediate character of magnesium which can increase the network cross-linking. For basic solutions, the chemical durability is almost constant for the different amount of alumina in the three series, likely because B₂O₃ is susceptible to nucleophilic attack, which is favored in high-OH⁻ solutions.     

Elasticity,hardness, and fracture toughness of sodium aluminoborosilicate glasses

Due to an increasing demand for oxide glasses with a better mechanical performance, there is a need to improve our understanding of the composition-structure-mechanical property relations in these brittle materials. At present, some properties such as Young's modulus can to a large extent be predicted based on the chemical composition, while others—in particular fracture-related properties—are typically optimized based on a trial-and-error approach. In this work, we study the mechanical properties of a series of 20 glasses in the quartenary Na₂O–Al₂O₃–B₂O₃–SiO₂ system with fixed soda content, thus accessing different structural domains. Ultrasonic echography is used to determine the elastic moduli and Poisson's ratio, while Vickers indentation is used to determine hardness. Furthermore, the single-edge precracked beam method is used to estimate the fracture toughness (K_Ic) for some compositions of interest. The compositional evolutions of Vickers hardness and Young's modulus are in good agreement with those predicted from models based on bond constraint density and strength. Although there is a larger deviation, the overall compositional trend in K_Ic can also be predicted by a model based on the strength of the bonds assumed to be involved in the fracture process.     

Gravitational drainage of compressible organic materials

A model was developed to simulate drainage of compressible particle suspensions, and study how cake compression and volumetric load influence the process. The input parameters were settling velocity, cake resistance and compressibility. These parameters were found using a new experimental method. Dextran‐MnO₂ particle suspensions were drained as these resemble organic waste slurries with respect to settling and compressibility. It was demonstrated that cake compressibility must be taken into account to obtain adequate simulations. This implies that pressurized filtration resistances cannot be used for drainage simulations. In the filtration step, a distinct increase of dry matter from top to bottom of the cake was observed. During the subsequent consolidation, the cake compressed and a uniform dry matter profile was found. The final dry matter content of the cake increased with feed concentration and volumetric load. The drainage time increased proportionally with feed concentration and, more importantly, proportionally with squared volumetric load. © 2010 American Institute of Chemical Engineers AIChE J, 2010     

Controlled release of biocide from silica microparticles in wood paint

Porous microparticles represent an attractive encapsulation platform as they provide a feasible route to a wide range of encapsulated chemical compounds. This assures an increased lifetime of the encapsulated compound by protecting it from the surrounding environment as well as providing a way to control the release rate. Porous microparticles encapsulating the commonly used biocide for wood protection, 3-iodoprop-2-ynyl N-butylcarbamate (IPBC), have been synthesized. The microparticles are spherical with an average size distribution of roughly 1 μm as determined by scanning electron microscopy (SEM). Determination of the release rate of the biocide from microcapsules incorporated into the paint film has been performed under diluted conditions. These experiments show that a slower release of the biocide can be obtained by encapsulation. Additionally, the microparticles have been shown to prolong the biocidal effect of the fungicide under accelerated weathering tests by protecting the biocide from UV-induced chemical degradation.     

A Chip for an Implantable Neural Stimulator

This paper describes a chip for a multichannel neural stimulator for functional electrical stimulation (FES). The purpose of FES is to restore muscular control in disabled patients. The chip performs all the signal processing required in an implanted neural stimulator. The power and digital data transmission to the stimulator passes through a 5 MHz inductive link. From the signals transmitted to the stimulator, the chip is able to generate charge-balanced current pulses with a controllable length up to 256 s and an amplitude up to 2 mA, for stimulation of nerve fibers. The quiescent current consumption of the chip is approx. 650 A at supply voltages of 6–12 V, and its size is 3.9×3.5 mm². It has 4 output channels for use in a multipolar cuff electrode.     

Selecting informative data for developing peptide-MHC binding predictors using a query by committee approach

Strategies for selecting informative data points for training prediction algorithms are important, particularly when data points are difficult and costly to obtain. A Query by Committee (QBC) training strategy for selecting new data points uses the disagreement between a committee of different algorithms to suggest new data points, which most rationally complement existing data, that is, they are the most informative data points. In order to evaluate this QBC approach on a real-world problem, we compared strategies for selecting new data points. We trained neural network algorithms to obtain methods to predict the binding affinity of peptides binding to the MHC class I molecule, HLA-A2. We show that the QBC strategy leads to a higher performance than a baseline strategy where new data points are selected at random from a pool of available data. Most peptides bind HLA-A2 with a low affinity, and as expected using a strategy of selecting peptides that are predicted to have high binding affinities also lead to more accurate predictors than the base line strategy. The QBC value is shown to correlate with the measured binding affinity. This demonstrates that the different predictors can easily learn if a peptide will fail to bind, but often conflict in predicting if a peptide binds. Using a carefully constructed computational setup, we demonstrate that selecting peptides with a high QBC performs better than low QBC peptides independently from binding affinity. When predictors are trained on a very limited set of data they cannot be expected to disagree in a meaningful way and we find a data limit below which the QBC strategy fails. Finally, it should be noted that data selection strategies similar to those used here might be of use in other settings in which generation of more data is a costly process.     

Upscaling and automation of electrophysiology: toward high throughput screening in ion channel drug discovery

Effective screening of large compound libraries in ion channel drug discovery requires the development of new electrophysiological techniques with substantially increased throughputs compared to the conventional patch clamp technique. Sophion Bioscience is aiming to meet this challenge by developing two lines of automated patch clamp products, a traditional pipette-based system called Apatchi-1, and a silicon chip-based system QPatch. The degree of automation spans from semi-automation (Apatchi-1) where a trained technician interacts with the system in a limited way, to a complete automation (QPatch 96) where the system works continuously and unattended until screening of a full compound library is completed. The performance of the systems range from medium to high throughputs.     

Relaxing PWQ Lyapunov stability criteria for PWA systems

The note addresses the calculation of piecewise quadratic (PWQ) Lyapunov functions for PWA (piecewise affine) systems. New LMI relaxations are proposed. These relaxations have been found to be effective in cases where the traditional relaxations fail.     

A patchy approximation of explicit model predictive control

The explicit solution of multi-parametric optimisation problems (MPOP) has been used to construct an off-line solution to relatively small- and medium-sized constrained control problems. The control design principles are based on receding horizon optimisation and generally use linear prediction models for the system dynamics. In this context, it can be shown that the optimal control law is a piecewise linear (PWL) state feedback defined over polytopic cells of the state space. However, as the complexity of the related optimisation problems increases, the memory footprint and implementation of such explicit optimal solution may be burdensome for the available hardware, principally due to the high number of polytopic cells in the state-space partition. In this article we provide a solution to this problem by proposing a patchy PWL feedback control law, which intend to approximate the optimal control law. The construction is based on the linear interpolation of the exact solution at the vertices of a feasible set and the solution of an unconstrained linear quadratic regulator (LQR) problem. With a hybrid patchy control implementation, we show that closed-loop stability is preserved in the presence of additive measurement noise despite the existence of discontinuities at the switch between the overlapping regions in the state-space partition.