Terahertz spectroscopy and imaging at the nanoscale for biological and security applications

The chemical specificity of terahertz spectroscopy, when combined with techniques for sub-wavelength sensing, is giving new understanding of processes occurring at the nanometre scale in biological systems and offers the potential for single molecule detection of chemical and biological agents and explosives. In addition, terahertz techniques are enabling the exploration of the fundamental behaviour of light when it interacts with nanoscale optical structures, and are being used to measure ultrafast carrier dynamics, transport and localisation in nanostructures. This chapter will explain how terahertz scale modelling can be used to explore the fundamental physics of nano-optics, it will discuss the terahertz spectroscopy of nanomaterials, terahertz near-field microscopy and other sub-wavelength techniques, and summarise recent developments in the terahertz spectroscopy and imaging of biological systems at the nanoscale. The potential of using these techniques for security applications will be considered.

Flavonoid inhibitory pharmacodynamics on platelet function in physiological environments

The complex relationship between flavonoid-based nutrition and cardiovascular disease may be dissected by understanding the activities of these compounds in biological systems. The aim of the present study was to explore a hierarchy for the importance of dietary flavonoids on cardiovascular health by examining the structural basis for inhibitory effects of common, dietary flavonoids (quercetin, apigenin, and naringenin) and the plasma metabolite, tamarixetin. Understanding flavonoid effects on platelets in vivo can be informed by investigations of the ability of these compounds to attenuate the function of these cells. Inhibition of platelet function in whole blood and plasma was structure-dependent. The order of potency was apigenin > tamarixetin > quercetin = naringenin indicating that in vivo, important functional groups are potentially a methylated B ring, and a non-hydroxylated, planar C ring. Apigenin and the methylated metabolite of quercetin, tamarixetin significantly reduced thrombus volume at concentrations (5 μM) that suggested their reported physiological levels (0.1-1 μM) may exert low levels of inhibition. Flavonoid interactions with erythrocytes, leukocytes and human serum albumin in whole blood reduce their inhibitory activities against platelet function. The diminished inhibitory activity of flavonoids that we observed in whole blood and plasma indicated that these interactions do not overcome the attenuating effects of these compounds. Furthermore, inhibition of platelet aggregation by flavonoids was enhanced with increases in exposure time, indicating the potential for measurable inhibitory effects during resident plasma times. We conclude that flavonoid structures may be a major influence of their activities in vivo with methylated metabolites and those of flavones being more potent than those of flavonols and flavanones.

Control and analysis of oriented thin films of lipid inverse bicontinuous cubic phases using grazing incidence small-angle X‑ray scattering

Lipid cubic phases are complex nanostructures that form naturally in a variety of biological systems, with applications including drug delivery and nanotemplating. Most X-ray scattering studies on lipid cubic phases have used unoriented polydomain samples as either bulk gels or suspensions of micrometer-sized cubosomes. We present a method of investigating cubic phases in a new form, as supported thin films that can be analyzed using grazing incidence small-angle X-ray scattering (GISAXS). We present GISAXS data on three lipid systems: phytantriol and two grades of monoolein (research and industrial). The use of thin films brings a number of advantages. First, the samples exhibit a high degree of uniaxial orientation about the substrate normal. Second, the new morphology allows precise control of the substrate mesophase geometry and lattice parameter using a controlled temperature and humidity environment, and we demonstrate the controllable formation of oriented diamond and gyroid inverse bicontinuous cubic along with lamellar phases. Finally, the thin film morphology allows the induction of reversible phase transitions between these mesophase structures by changes in humidity on subminute time scales, and we present timeresolved GISAXS data monitoring these transformations.

CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

Lattice Boltzmann simulation of viscous fluid systems with elastic boundaries

A lattice Boltzmann model able to simulate viscous fluid systems with elastic and movable boundaries is proposed. By introducing the virtual distribution function at the boundary, the Galilean invariance is recovered for the full system. As examples of application, the how in elastic vessels is simulated with the pressure-radius relationship similar to that of the pulmonary blood vessels. The numerical results for steady how are in good agreement with the analytical prediction, while the simulation results for pulsative how agree with the experimental observation of the aortic flows qualitatively. The approach has potential application in the study of the complex fluid systems such as the suspension system as well as the arterial blood flow.

Nutrimetabonomics: nutritional applications of metabolic profiling

An individual's metabolic phenotype, and ultimately health, is significantly influenced by complex interactions between their genes and the diet. Studying these associations and their downstream biochemical consequences has proven extremely challenging using traditional hypothesis-led strategies. Metabonomics, a systems biology approach, allows the global metabolic response of biological systems to stimuli to be characterised. Through the application of this approach to nutritional-based research, nutrimetabonomics, the biochemical response to dietary inputs is being investigated at greater levels of resolution. This has allowed novel insights to be gained regarding intricate diet-gene interactions and their consequences for health and disease. In this review, we present some of the latest research exploring how nutrimetabonomics can assist in the elucidation of novel biomarkers of dietary behaviour and provide new perspectives on diet-health relationships. The use of this approach to study the metabolic interplay between the gut microbiota and the host is also explored.

LEGO® bricks as building blocks for centimeter-scale biological environments

LEGO bricks are commercially available interlocking pieces of plastic that are conventionally used as toys. We describe their use to build engineered environments for cm-scale biological systems, in particular plant roots. Specifically, we take advantage of the unique modularity of these building blocks to create inexpensive, transparent, reconfigurable, and highly scalable environments for plant growth in which structural obstacles and chemical gradients can be precisely engineered to mimic soil.

A network of integrate and fire neurons for visual selection

Biological systems have facility to capture salient object(s) in a given scene, but it is still a difficult task to be accomplished by artificial vision systems. In this paper a visual selection mechanism based on the integrate and fire neural network is proposed. The model not only can discriminate objects in a given visual scene, but also can deliver focus of attention to the salient object. Moreover, it processes a combination of relevant features of an input scene, such as intensity, color, orientation, and the contrast of them. In comparison to other visual selection approaches, this model presents several interesting features. It is able to capture attention of objects in complex forms, including those linearly nonseparable. Moreover, computer simulations show that the model produces results similar to those observed in natural vision systems.

Thermodynamic Stabillity of Hydrogen-Bonded Systems in Polar and Nonpolar Environments

The thermodynamic properties of a selected set of benchmark hydrogen-bonded systems (acetic acid dimer and the complexes of acetic acid with acetamide and methanol) was studied with the goal of obtaining detailed information on solvent effects on the hydrogen-bonded interactions using water, chloroform, and n-heptane as representatives for a wide range in the dielectric constant. Solvent effects were investigated using both explicit and implicit solvation models. For the explicit description of the solvent, molecular dynamics and Monte Carlo simulations in the isothermal isobaric (NpT) ensemble combined with the free energy perturbation technique were performed to determine solvation free energies. Within the implicit solvation approach, the polarizable continuum model and the conductor-like screening model were applied. Combination of gas phase results with the results obtained from the different solvation models through an appropriate thermodynamic cycle allows estimation of complexation free energies, enthalpies, and the respective entropic contributions in solution. Owing to the strong solvation effects of water the cyclic acetic acid dimer is not stable in aqueous solution. In less polar solvents the double hydrogen bond structure of the acetic acid dimer remains stable. This finding is in agreement with previous theoretical and experimental results. A similar trend as for the acetic acid dimer is also observed for the acetamide complex. The methanol complex was found to be thermodynamically unstable in gas phase as well as in any of the three solvents. (C) 2010 Wiley Periodicals, Inc. J Comput Chem 31: 2046-2055, 2010

Automating the product derivation process of multi-agent systems product lines

Agent-oriented software engineering and software product lines are two promising software engineering techniques. Recent research work has been exploring their integration, namely multi-agent systems product lines (MAS-PLs), to promote reuse and variability management in the context of complex software systems. However, current product derivation approaches do not provide specific mechanisms to deal with MAS-PLs. This is essential because they typically encompass several concerns (e.g., trust, coordination, transaction, state persistence) that are constructed on the basis of heterogeneous technologies (e.g., object-oriented frameworks and platforms). In this paper, we propose the use of multi-level models to support the configuration knowledge specification and automatic product derivation of MAS-PLs. Our approach provides an agent-specific architecture model that uses abstractions and instantiation rules that are relevant to this application domain. In order to evaluate the feasibility and effectiveness of the proposed approach, we have implemented it as an extension of an existing product derivation tool, called GenArch. The approach has also been evaluated through the automatic instantiation of two MAS-PLs, demonstrating its potential and benefits to product derivation and configuration knowledge specification.

Evaluating public risk preferences in forest land-use choices using multi-attribute utility theory

Forest policy decisions inherently involve multiple attributes and risk and uncertainty as they largely deal with complex biological, ecological, and socio-political systems. Identifying risk preferences and quantifying their inter-relationships and tradeoffs are useful in formulating better forest policy. Often, technocrats and experts deal with risky decisions, but ideally, stakeholder risk characteristics should be explicitly considered in making policy decisions. This paper analysed societal risk preferences on public forest land-use attributes using multi-attribute utility theory (MAUT). The results indicate significant risk-averse behaviour towards old-growth forest conservation and forest-based recreation but less risk-averse behaviour towards native timber extraction. Overall, the respondents preferred a more conservative forest land-use option, which is consistent with their risk attitudes. The method provides insights into risk preferences of forest stakeholders, which could lead to better understanding of forest management conflicts. Moreover, the method explicitly distinguishes the technical and value components of the decision and is useful in unravelling public risk preferences in multiple-use forest planning situations.

Detecting inconsistency in biological molecular databases using ontologies

The rapid growth of life science databases demands the fusion of knowledge from heterogeneous databases to answer complex biological questions. The discrepancies in nomenclature, various schemas and incompatible formats of biological databases, however, result in a significant lack of interoperability among databases. Therefore, data preparation is a key prerequisite for biological database mining. Integrating diverse biological molecular databases is an essential action to cope with the heterogeneity of biological databases and guarantee efficient data mining. However, the inconsistency in biological databases is a key issue for data integration. This paper proposes a framework to detect the inconsistency in biological databases using ontologies. A numeric estimate is provided to measure the inconsistency and identify those biological databases that are appropriate for further mining applications. This aids in enhancing the quality of databases and guaranteeing accurate and efficient mining of biological databases.

Modeling and simulation for large scale production systems

Computer modeling and simulation provide a foundation upon which industrial processes and systems can be transformed and innovation dramatically accelerated. Computer modeling and simulation is also an indispensable tool of the information age, used extensively in design, analysis, operations, decision-making, optimization, and education and training. Manufacturing, production and design relies upon simulation to develop efficient production systems and factories that produce quality products. Simulation in industry has yet to meet its full potential. The development of models is very time consuming, particularly for geometries of complex engineering systems such as manufacturing plants, automobiles, aircraft and ships. Computer simulation allows scientists and engineers to understand and predict three-dimensional and time-dependent phenomena in science and engineering discipline. This talk will focus on challenges associated with modeling and simulation in the manufacturing sector and through a number of case studies highlight the benefits gained through the use of such technologies.

Metal catalyzed oxidation of tyrosine residues by different oxidation systems of copper/hydrogen peroxide

Metal-catalysed oxidation (MCO) reactions result in the formation of reactive oxygen species (ROS) in biological systems. These ROS cause oxidative stress that contributes to a number of pathological processes leading to a variety of diseases. Tyrosine is one residue that is very susceptible to oxidative modification and the formation of dityrosine (DT) and 3,4-dihydroxyphenylalanine (DOPA) have been widely reported in a number of diseases. However, the mechanisms of MCO of tyrosine in biological systems are poorly understood and require further investigation. In this study we investigated the mechanism of DT and DOPA formation by MCO using N-acetyl tyrosine ethyl ester as a model for tyrosine in proteins and peptides. The results showed that DT formation could be observed upon Cu²⁺/H₂O₂ oxidation at pH 7.4. Our results indicate that it is unlikely to be via Fenton chemistry since Cu⁺/H₂O₂ oxidative conditions did not lead to the formation of DT.

A tandem liquid chromatography–mass spectrometry (LC–MS) method for profiling small molecules in complex samples

Liquid chromatography–mass spectrometry (LC–MS) methods using either aqueous normal phase (ANP) or reversed phase (RP) columns are routinely used in small molecule or metabolomic analyses. These stationary phases enable chromatographic fractionation of polar and non-polar compounds, respectively. The application of a single chromatographic stationary phase to a complex biological extract results in a significant proportion of compounds which elute in the non-retained fraction, where they are poorly detected because of a combination of ion suppression and the co-elution of isomeric compounds. Thus coverage of both polar and non-polar components of the metabolome generally involves multiple analyses of the same sample, increasing the analysis time and complexity. In this study we describe a novel tandem in-line LC–MS method, in which compounds from one injection are sequentially separated in a single run on both ANP and RP LC-columns. This method is simple, robust, and enables the use of independent gradients customized for both RP and ANP columns. The MS signal is acquired in a single chromatogram which reduces instrument time and operator and data analysis errors. This method has been used to analyze a range of biological extracts, from plant and animal tissues, human serum and urine, microbial cell and culture supernatants. Optimized sample preparation protocols are described for this method as well as a library containing the retention times and accurate masses of 127 compounds.