The BAD project: data mining, database and prediction of protein adsorption on surfaces

Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

Tracking control of a class of Hamiltonian mechanical systems with disturbances

This paper presents a trajectory-tracking control strategy for a class of mechanical systems in Hamiltonian form. The class is characterised by a simplectic interconnection arising from the use of generalised coordinates and full actuation. The tracking error dynamic is modelled as a port-Hamiltonian Systems (PHS). The control action is designed to take the error dynamics into a desired closed-loop PHS characterised by a constant mass matrix and a potential energy with a minimum at the origin. A transformation of the momentum and a feedback control is exploited to obtain a constant generalised mass matrix in closed loop. The stability of the close-loop system is shown using the close-loop Hamiltonian as a Lyapunov function. The paper also considers the addition of integral action to design a robust controller that ensures tracking in spite of disturbances. As a case study, the proposed control design methodology is applied to a fully actuated robotic manipulator.

Behaviour of LSF floor systems with improved joist sections under fire conditions

Fire safety design of buildings is essential to safeguard lives and minimize the loss of damage to properties. Light-weight cold-formed steel channel sections along with fire resistive plasterboards are used to construct light gauge steel frame floor systems to provide the required fire resistance rating. However, simply adding more plasterboard layers is not an efficient method to increase FRR. Hence this research focuses on using joists with improved joist section profiles such as hollow flange sections to increase the structural capacity of floor systems under fire conditions and thus their FRR. In this research, the structural and thermal behaviour of LSF floor systems made of LiteSteel Beams with different plasterboard and insulation configurations was investigated using four full scale tests under standard fires. Based on the ultimate failure load of the floor joist at ambient temperature, transient state fire tests were conducted for different Load Ratios. These fire tests showed that the new LSF floor system has improved the FRR well above that of those made of lipped channel sections. The joist failure was predominantly due to local buckling of LSB compression flanges near mid-span with severe yielding of tension flanges. Fire tests have provided valuable structural and thermal performance data of tested floor systems that included time-temperature profiles, and failure times and temperatures. Average failure temperatures of LSB joists and reduced yield strengths were used to predict their ultimate moment capacities, which were compared with corresponding test capacities. This allowed an assessment in relation to the accuracy of current design rules for steel joists at elevated temperatures. This paper presents the details of full scale fire tests of LSF floor systems made of LSB joists with different plasterboard and insulation configurations and their results along with some important findings.

Determining reverse salient types and evolutionary dynamics of technology systems with performance disparities

Technological system evolution is marked by the uneven evolution of constituent sub-systems. Subsequently, system evolution is hampered by the resulting state of unevenness, or reverse salience, which results from the presence of the sub-system that delivers the lowest level of performance with respect to other sub-systems, namely, the reverse salient. In this paper, we develop absolute and proportional performance gap measures of reverse salience and, in turn, derive a typology of reverse salients that distinguishes alternative dynamics of change in the evolving system. We subsequently demonstrate the applicability of the measures and the typology through an illustrative empirical study of the PC (personal computer) technological system that functions as a gaming platform. Our empirical analysis demonstrates that patterns of temporal dynamics can be distinguished with the measurement of reverse salience, and that distinct paths of technological system evolution can be identified as different types of reverse salients emerge over time.