Complete framework for efficient characterisation of non-Markovian processes

A non-Markovian process is one that retains `memory' of its past. A systematic understanding of these processes is necessary to fully describe and harness a vast range of complex phenomena; however, no such general characterisation currently exists. This long-standing problem has hindered advances in understanding physical, chemical and biological processes, where often dubious theoretical assumptions are made to render a dynamical description tractable. Moreover, the methods currently available to treat non-Markovian quantum dynamics are plagued with unphysical results, like non-positive dynamics. Here we develop an operational framework to characterise arbitrary non-Markovian quantum processes. We demonstrate the universality of our framework and how the characterisation can be rendered efficient, before formulating a necessary and sufficient condition for quantum Markov processes. Finally, we stress how our framework enables the actual systematic analysis of non-Markovian processes, the understanding of their typicality, and the development of new master equations for the effective description of memory-bearing open-system evolution.

Functional characterisation of Schistosoma japonicum acetylcholinesterase

BACKGROUND: Acetylcholinesterase (AChE) is an important metabolic enzyme of schistosomes present in the musculature and on the surface of the blood stage where it has been implicated in the modulation of glucose scavenging from mammalian host blood. As both a target for the antischistosomal drug metrifonate and as a potential vaccine candidate, AChE has been characterised in the schistosome species Schistosoma mansoni, S. haematobium and S. bovis, but not in S. japonicum. Recently, using a schistosome protein microarray, a predicted S. japonicum acetylcholinesterase precursor was significantly targeted by protective IgG1 immune responses in S. haematobium-exposed individuals that had acquired drug-induced resistance to schistosomiasis after praziquantel treatment.

RESULTS: We report the full-length cDNA sequence and describe phylogenetic and molecular structural analysis to facilitate understanding of the biological function of AChE (SjAChE) in S. japonicum. The protein has high sequence identity (88 %) with the AChEs in S. mansoni, S. haematobium and S. bovis and has 25 % sequence similarity with human AChE, suggestive of a highly specialised role for the enzyme in both parasite and host. We immunolocalized SjAChE and demonstrated its presence on the surface of adult worms and schistosomula, as well as its lower expression in parenchymal regions. The relatively abundance of AChE activity (90 %) present on the surface of adult S. japonicum when compared with that reported in other schistosomes suggests SjAChE may be a more effective drug or immunological target against this species. We also demonstrate that the classical inhibitor of AChE, BW285c51, inhibited AChE activity in tegumental extracts of paired worms, single males and single females by 59, 22 and 50 %, respectively, after 24 h incubation with 200 μM BW284c51.

CONCLUSIONS: These results build on previous studies in other schistosome species indicating major differences in the enzyme between parasite and mammalian host, and provide further support for the design of an anti-schistosome intervention targeting AChE.

Characterisation of a secretory serine protease inhibitor (SjB6) from Schistosoma japonicum

BACKGROUND: Proteins belonging to the serine protease inhibitor (serpin) superfamily play essential physiological roles in many organisms. In pathogens, serpins are thought to have evolved specifically to limit host immune responses by interfering with the host immune-stimulatory signals. Serpins are less well characterised in parasitic helminths, although some are thought to be involved in mechanisms associated with host immune modulation. In this study, we cloned and partially characterised a secretory serpin from Schistosoma japonicum termed SjB6, these findings provide the basis for possible functional roles.

METHODS: SjB6 gene was identified through database mining of our previously published microarray data, cloned and detailed sequence and structural analysis and comparative modelling carried out using various bioinformatics and proteomics tools. Gene transcriptional profiling was determined by real-time PCR and the expression of native protein determined by immunoblotting. An immunological profile of the recombinant protein produced in insect cells was determined by ELISA.

RESULTS: SjB6 contains an open reading frame of 1160 base pairs that encodes a protein of 387 amino acid residues. Detailed sequence analysis, comparative modelling and structural-based alignment revealed that SjB6 contains the essential structural motifs and consensus secondary structures typical of inhibitory serpins. The presence of an N-terminal signal sequence indicated that SjB6 is a secretory protein. Real-time data indicated that SjB6 is expressed exclusively in the intra-mammalian stage of the parasite life cycle with its highest expression levels in the egg stage (p < 0.0001). The native protein is approximately 60 kDa in size and recombinant SjB6 (rSjB6) was recognised strongly by sera from rats experimentally infected with S. japonicum.

CONCLUSIONS: The significantly high expression of SjB6 in schistosome eggs, when compared to other life cycle stages, suggests a possible association with disease pathology, while the strong reactivity of sera from experimentally infected rats against rSjB6 suggests that native SjB6 is released into host tissue and induces an immune response. This study presents a comprehensive demonstration of sequence and structural-based analysis of a secretory serpin from a trematode and suggests SjB6 may be associated with important functional roles in S. japonicum, particularly in parasite modulation of the host microenvironment.

The role of material characterisation in the crush modelling of thermoplastic composite structures

The predictive capability of high fidelity finite element modelling, to accurately capture damage and crush behaviour of composite structures, relies on the acquisition of accurate material properties, some of which have necessitated the development of novel approaches. This paper details the measurement of interlaminar and intralaminar fracture toughness, the non-linear shear behaviour of carbon fibre (AS4)/thermoplastic Polyetherketoneketone (PEKK) composite laminates and the utilisation of these properties for the accurate computational modelling of crush. Double-cantilever-beam (DCB), four-point end-notched flexure (4ENF) and Mixed-mode bending (MMB) test configurations were used to determine the initiation and propagation fracture toughness in mode I, mode II and mixed-mode loading, respectively. Compact Tension (CT) and Compact Compression (CC) test samples were employed to determine the intralaminar longitudinal tensile and compressive fracture toughness. V-notched rail shear tests were used to measure the highly non-linear shear behaviour, associated with thermoplastic composites, and fracture toughness. Corresponding numerical models of these tests were developed for verification and yielded good correlation with the experimental response. This also confirmed the accuracy of the measured values which were then employed as input material parameters for modelling the crush behaviour of a corrugated test specimen.

Mechanochemical Synthesis of Pharmaceutical Cocrystal Suspensions via Hot Melt Extrusion: Feasibility Studies and Physicochemical Characterisation

Engineered cocrystals offer an alternative solid drug form with tailored physicochemical properties. Interestingly, although cocrystals provide many new possibilities, they also present new challenges, particularly in regard to their design and large-scale manufacture. Current literature has primarily focused on the preparation and characterization of novel cocrystals typically containing only the drug and coformer, leaving the subsequent formulation less explored. In this paper we propose, for the first time, the use of hot melt extrusion for the mechanochemical synthesis of pharmaceutical cocrystals in the presence of a meltable binder. In this approach, we examine excipients that are amenable to hot melt extrusion, forming a suspension of cocrystal particulates embedded in a pharmaceutical matrix. Using ibuprofen and isonicotinamide as a model cocrystal reagent pair, formulations extruded with a small molecular matrix carrier (xylitol) were examined to be intimate mixtures wherein the newly formed cocrystal particulates were physically suspended in a matrix. With respect to formulations extruded using polymeric carriers (Soluplus and Eudragit EPO, respectively), however, there was no evidence within PXRD patterns of either crystalline ibuprofen or the cocrystal. Importantly, it was established in this study that an appropriate carrier for a cocrystal reagent pair during HME processing should satisfy certain criteria including limited interaction with parent reagents and cocrystal product, processing temperature sufficiently lower than the onset of cocrystal Tm, low melt viscosity, and rapid solidification upon cooling.

Characterisation of Large Disturbance Rotor Angle and Voltage Stability in Interconnected Power Networks with Distributed Wind Generation

Wind generation in highly interconnected power networks creates local and centralised stability issues based on their proximity to conventional synchronous generators and load centres. This paper examines the large disturbance stability issues (i.e. rotor angle and voltage stability) in power networks with geographically distributed wind resources in the context of a number of dispatch scenarios based on profiles of historical wind generation for a real power network. Stability issues have been analysed using novel stability indices developed from dynamic characteristics of wind generation. The results of this study show that localised stability issues worsen when significant penetration of both conventional and wind generation is present due to their non-complementary characteristics. In contrast, network stability improves when either high penetration of wind and synchronous generation is present in the network. Therefore, network regions can be clustered into two distinct stability groups (i.e. superior stability and inferior stability regions). Network stability improves when a voltage control strategy is implemented at wind farms, however both stability clusters remain unchanged irrespective of change in the control strategy. Moreover, this study has shown that the enhanced fault ride-through (FRT) strategy for wind farms can improve both voltage and rotor angle stability locally, but only a marginal improvement is evident in neighbouring regions.

A Bias Compensated Cross-Relation approach to Thermocouple Characterisation

The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the in influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

Noise resilient discrete-time cross-relation sensor characterisation

In-situ characterisation of thermocouple sensors is a challenging problem. Recently the authors presented a blind characterisation technique based on the cross-relation method of blind identification. The method allows in-situ identification of two thermocouple probes, each with a different dynamic response, using only sampled sensor measurement data. While the technique offers certain advantages over alternative methods, including low estimation variance and the ability to compensate for noise induced bias, the robustness of the method is limited by the multimodal nature of the cost function. In this paper, a normalisation term is proposed which improves the convexity of
the cost function. Further, a normalisation and bias compensation hybrid approach is presented that exploits the advantages of both normalisation and bias compensation. It is found that the optimum of the hybrid cost function is less biased and more stable than when only normalisation is applied. All results were verified by simulation.

Characterisation of polyethylene powders for rotational moulding and effect of powder size and shape on densification behaviour

The particle size, shape and distribution of a range of rotational moulding polyethylenes (PEs) ground to powder was investigated using a novel visual data acquisition and analysis system (TP Picture®), developed by Total Petrochemicals. Differences in the individual particle shape factors of the powder samples were observed and correlations with the grinding conditions were determined. When heated, the bubble dissolution behaviour of the same powders was investigated and the shape factor correlated with densification rate, bubble size and bubble distribution.

A Bias Compensated Cross-Relation approach to Thermocouple Characterisation

The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.