Hydrogelation and self-assembly of Fmoc-tripeptides: unexpected influence of sequence on self-assembled fibril structure, and hydrogel modulus and anisotropy

The self-assembly and hydrogelation properties of two Fmoc-tripeptides [Fmoc = N-(fluorenyl-9-methoxycarbonyl)] are investigated, in borate buffer and other basic solutions. A remarkable difference in self-assembly properties is observed comparing Fmoc-VLK(Boc) with Fmoc-K(Boc)LV, both containing K protected by N(epsilon)-tert-butyloxycarbonate (Boc). In borate buffer, the former peptide forms highly anisotropic fibrils which show local alignment, and the hydrogels show flow-aligning properties. In contrast, Fmoc-K(Boc)LV forms highly branched fibrils that produce isotropic hydrogels with a much higher modulus (G' > 10(4) Pa), and lower concentration for hydrogel formation. The distinct self-assembled structures are ascribed to conformational differences, as revealed by secondary structure probes (CD, FTIR, Raman spectroscopy) and X-ray diffraction. Fmoc-VLK(Boc) forms well-defined beta-sheets with a cross-beta X-ray diffraction pattern, whereas Fmoc-KLV(Boc) forms unoriented assemblies with multiple stacked sheets. Interchange of the K and V residues when inverting the tripeptide sequence thus leads to substantial differences in self-assembled structures, suggesting a promising approach to control hydrogel properties.

Dynamic shear modulus of isotropic elastomers

We have investigated the dynamic mechanical behavior of two cross-linked polymer networks with very different topologies: one made of backbones randomly linked along their length; the other with fixed-length strands uniformly cross-linked at their ends. The samples were analyzed using oscillatory shear, at very small strains corresponding to the linear regime. This was carried out at a range of frequencies, and at temperatures ranging from the glass plateau, through the glass transition, and well into the rubbery region. Through the glass transition, the data obeyed the time-temperature superposition principle, and could be analyzed using WLF treatment. At higher temperatures, in the rubbery region, the storage modulus was found to deviate from this, taking a value that is independent of frequency. This value increased linearly with temperature, as expected for the entropic rubber elasticity, but with a substantial negative offset inconsistent with straightforward enthalpic effects. Conversely, the loss modulus continued to follow time-temperature superposition, decreasing with increasing temperature, and showing a power-law dependence on frequency.

Steady periodic water waves with constant vorticity: regularity and local bifurcation

This paper studies periodic traveling gravity waves at the free surface of water in a flow of constant vorticity over a flat bed. Using conformal mappings the free-boundary problem is transformed into a quasilinear pseudodifferential equation for a periodic function of one variable. The new formulation leads to a regularity result and, by use of bifurcation theory, to the existence of waves of small amplitude even in the presence of stagnation points in the flow.

Neural network enhanced generalised minimum variance self-tuning controller for nonlinear discrete-time systems

A neural network enhanced self-tuning controller is presented, which combines the attributes of neural network mapping with a generalised minimum variance self-tuning control (STC) strategy. In this way the controller can deal with nonlinear plants, which exhibit features such as uncertainties, nonminimum phase behaviour, coupling effects and may have unmodelled dynamics, and whose nonlinearities are assumed to be globally bounded. The unknown nonlinear plants to be controlled are approximated by an equivalent model composed of a simple linear submodel plus a nonlinear submodel. A generalised recursive least squares algorithm is used to identify the linear submodel and a layered neural network is used to detect the unknown nonlinear submodel in which the weights are updated based on the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model therefore the nonlinear submodel is naturally accommodated within the control law. Two simulation studies are provided to demonstrate the effectiveness of the control algorithm.

Millimeter-wave measurements of the complex dielectric constant of an advanced thick film UV photoresist

The first measurement of the relative permittivity (εr) and loss tangent (tan δ) of EPON™ SU-8 advanced thick film ultraviolet photoresist is reported at frequencies between 75–110 GHz (W-band). The problems associated with such a measurement are discussed, an error analysis given, and values of εr=1.725±0.08 and tanδ =0.02±0.001 are determined.

Generalised Dirichelt-to-Neumann map in time dependent domains

We study the heat, linear Schrodinger and linear KdV equations in the domain l(t) < x < ∞, 0 < t < T, with prescribed initial and boundary conditions and with l(t) a given differentiable function. For the first two equations, we show that the unknown Neumann or Dirichlet boundary value can be computed as the solution of a linear Volterra integral equation with an explicit weakly singular kernel. This integral equation can be derived from the formal Fourier integral representation of the solution. For the linear KdV equation we show that the two unknown boundary values can be computed as the solution of a system of linear Volterra integral equations with explicit weakly singular kernels. The derivation in this case makes crucial use of analyticity and certain invariance properties in the complex spectral plane. The above Volterra equations are shown to admit a unique solution.

Influence of curd cutting programme and stirring speed on the prediction of syneresis indices in cheese-making using NIR light backscatter

An NIR reflectance sensor, with a large field of view and a fibre-optic connection to a spectrometer for measuring light backscatter at 980 nm, was used to monitor the syneresis process online during cheese-making with the goal of predicting syneresis indices (curd moisture content, yield of whey and fat losses to whey) over a range of curd cutting programmes and stirring speeds. A series of trials were carried out in an 11 L cheese vat using recombined whole milk. A factorial experimental design consisting of three curd stirring speeds and three cutting programmes, was undertaken. Milk was coagulated under constant conditions and the casein gel was cut when the elastic modulus reached 35 Pa. Among the syneresis indices investigated, the most accurate and most parsimonious multivariate model developed was for predicting yield of whey involving three terms, namely light backscatter, milk fat content and cutting intensity (R2 = 0.83, SEy = 6.13 g/100 g), while the best simple model also predicted this syneresis index using the light backscatter alone (R2 = 0.80, SEy = 6.53 g/100 g). In this model the main predictor was the light backscatter response from the NIR light back scatter sensor. The sensor also predicted curd moisture with a similar accuracy.

Generalised Bayesian cloud detection for satellite imagery. part 2: technique and validation for day-time imagery

Numerical Weather Prediction (NWP) fields are used to assist the detection of cloud in satellite imagery. Simulated observations based on NWP are used within a framework based on Bayes' theorem to calculate a physically-based probability of each pixel with an imaged scene being clear or cloudy. Different thresholds can be set on the probabilities to create application-specific cloud masks. Here, the technique is shown to be suitable for daytime applications over land and sea, using visible and near-infrared imagery, in addition to thermal infrared. We use a validation dataset of difficult cloud detection targets for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) achieving true skill scores of 89% and 73% for ocean and land, respectively using the Bayesian technique, compared to 90% and 70%, respectively for the threshold-based techniques associated with the validation dataset.