Solvable model for distribution networks on random graphs

We propose a simple model that captures the salient properties of distribution networks, and study the possible occurrence of blackouts, i.e., sudden failings of large portions of such networks. The model is defined on a random graph of finite connectivity. The nodes of the graph represent hubs of the network, while the edges of the graph represent the links of the distribution network. Both, the nodes and the edges carry dynamical two state variables representing the functioning or dysfunctional state of the node or link in question. We describe a dynamical process in which the breakdown of a link or node is triggered when the level of maintenance it receives falls below a given threshold. This form of dynamics can lead to situations of catastrophic breakdown, if levels of maintenance are themselves dependent on the functioning of the net, once maintenance levels locally fall below a critical threshold due to fluctuations. We formulate conditions under which such systems can be analyzed in terms of thermodynamic equilibrium techniques, and under these conditions derive a phase diagram characterizing the collective behavior of the system, given its model parameters. The phase diagram is confirmed qualitatively and quantitatively by simulations on explicit realizations of the graph, thus confirming the validity of our approach. © 2007 The American Physical Society.

On-chip immunoprecipitation for protein purification

Immunoprecipitation (IP) is one of the most widely used and selective techniques for protein purification. Here, a miniaturised, polymer-supported immunoprecipitation (µIP) method for the on-chip purification of proteins from complex mixtures is described. A 4 µl PDMS column functionalised with covalently bound antibodies was created and all critical aspects of the µIP protocol (antibody immobilisation, blocking of potential non-specific adsorption sites, sample incubation and washing conditions) were assessed and optimised. The optimised µIP method was used to obtain purified fractions of affinity-tagged protein from a bacterial lysate.

Nanotechnology and microfluidics:formulation design and on-chip manufacture of nanoparticles

Nanoparticles offer an ideal platform for the delivery of small molecule drugs, subunit vaccines and genetic constructs. Besides the necessity of a homogenous size distribution, defined loading efficiencies and reasonable production and development costs, one of the major bottlenecks in translating nanoparticles into clinical application is the need for rapid, robust and reproducible development techniques. Within this thesis, microfluidic methods were investigated for the manufacturing, drug or protein loading and purification of pharmaceutically relevant nanoparticles. Initially, methods to prepare small liposomes were evaluated and compared to a microfluidics-directed nanoprecipitation method. To support the implementation of statistical process control, design of experiment models aided the process robustness and validation for the methods investigated and gave an initial overview of the size ranges obtainable in each method whilst evaluating advantages and disadvantages of each method. The lab-on-a-chip system resulted in a high-throughput vesicle manufacturing, enabling a rapid process and a high degree of process control. To further investigate this method, cationic low transition temperature lipids, cationic bola-amphiphiles with delocalized charge centers, neutral lipids and polymers were used in the microfluidics-directed nanoprecipitation method to formulate vesicles. Whereas the total flow rate (TFR) and the ratio of solvent to aqueous stream (flow rate ratio, FRR) was shown to be influential for controlling the vesicle size in high transition temperature lipids, the factor FRR was found the most influential factor controlling the size of vesicles consisting of low transition temperature lipids and polymer-based nanoparticles. The biological activity of the resulting constructs was confirmed by an invitro transfection of pDNA constructs using cationic nanoprecipitated vesicles. Design of experiments and multivariate data analysis revealed the mathematical relationship and significance of the factors TFR and FRR in the microfluidics process to the liposome size, polydispersity and transfection efficiency. Multivariate tools were used to cluster and predict specific in-vivo immune responses dependent on key liposome adjuvant characteristics upon delivery a tuberculosis antigen in a vaccine candidate. The addition of a low solubility model drug (propofol) in the nanoprecipitation method resulted in a significantly higher solubilisation of the drug within the liposomal bilayer, compared to the control method. The microfluidics method underwent scale-up work by increasing the channel diameter and parallelisation of the mixers in a planar way, resulting in an overall 40-fold increase in throughput. Furthermore, microfluidic tools were developed based on a microfluidics-directed tangential flow filtration, which allowed for a continuous manufacturing, purification and concentration of liposomal drug products.

The application of 3D printing to study microfluidic architecture for 'on-chip' mixing systems for SRCD and UV spectroscopy

This paper details methodologies that have been explored for the fast proofing of on-chip architectures for Circular Dichroism techniques. Flow-cell devices fabricated from UV transparent Quartz are used for these experiments. The complexity of flow-cell production typically results in lead times of six months from order to delivery. Only at that point can the on-chip architecture be tested empirically and any required modifications determined ready for the next six month iteration phase. By using the proposed 3D printing and PDMS moulding techniques for fast proofing on-chip architectures the optimum design can be determined within a matter of hours prior to commitment to quartz chip production.

Spatially orthogonal chemical functionalization of a hierarchical pore network for catalytic cascade reactions

The chemical functionality within porous architectures dictates their performance as heterogeneous catalysts; however, synthetic routes to control the spatial distribution of individual functions within porous solids are limited. Here we report the fabrication of spatially orthogonal bifunctional porous catalysts, through the stepwise template removal and chemical functionalization of an interconnected silica framework. Selective removal of polystyrene nanosphere templates from a lyotropic liquid crystal-templated silica sol–gel matrix, followed by extraction of the liquid crystal template, affords a hierarchical macroporous–mesoporous architecture. Decoupling of the individual template extractions allows independent functionalization of macropore and mesopore networks on the basis of chemical and/or size specificity. Spatial compartmentalization of, and directed molecular transport between, chemical functionalities affords control over the reaction sequence in catalytic cascades; herein illustrated by the Pd/Pt-catalysed oxidation of cinnamyl alcohol to cinnamic acid. We anticipate that our methodology will prompt further design of multifunctional materials comprising spatially compartmentalized functions.

Intracellular protein determination using droplet-based immunoassays

This paper describes the implementation of a sensitive, on-chip immunoassay for the analysis of intracellular proteins, developed using microdroplet technology. The system offers a number of analytical functionalities, enabling the lysis of low cell numbers, as well as protein detection and quantification, integrated within a single process flow. Cells were introduced into the device in suspension and were electrically lysed in situ. The cell lysate was subsequently encapsulated together with antibody-functionalized beads into stable, water-in-oil droplets, which were stored on-chip. The binding of intracellular proteins to the beads was monitored fluorescently. By analyzing many individual droplets and quantifying the data obtained against standard additions, we measured the level of two intracellular proteins, namely, HRas-mCitrine, expressed within HEK-293 cells, and actin-EGFP, expressed within MCF-7 cells. We determined the concentrations of these proteins over 5 orders of magnitude, from ~50 pM to 1 µM. The results from this semiautomated method were compared to those for determinations made using Western blots, and were found not only to be faster, but required a smaller number of cells. © 2011 American Chemical Society.

Foreign direct investment and corruption

In the last few decades, the world has witnessed an enormous growth in the volume of foreign direct investment (FDI). The global stock of FDI reached US$ 7.5 trillion in 2003 and accounted for 11% of world Gross Domestic Product, up from 7% in 1990. The sales of multinational enterprises at around US$ 19 trillion were more than double the level of world exports. Substantial FDI inflows went into transition countries. Inflows into one of the region's largest recipient, the Russian Federation, almost doubled, enabling Russia to become one of the five top FDI destinations in 2005-2006. FDI inflows in Russia have increased almost threefold from 13.6% in 2003 to 35% in 2007. In 2003, these flows were twice greater than those into China; whilst in 2007 they were six times larger. Russia's FDI inflows were also about 2.5 times greater than those of Brazil. Efficient government institutions are argued by many economists to foster FDI and growth as a result. However, the magnitude of this effect has yet to be measured. This thesis takes a Political Economy approach to explore, empirically, the potential impact of malfunctioning governmental institutions, proxied by three indices of perceived corruption, on FDI stocks accumulation/distribution within Russia over the period of 2002-2004. Using a regional data-set it concentrates on three areas relating to FDI. Firstly, it considers the significance, the size and the sign of the impact of perceived corruption on accumulation of FDI stocks within Russia. Secondly, it quantifies the impact of perceived corruption on the volume of FDI stocks simultaneously estimating the impact of the investment in public capital such as telecommunications and transportation networks on FDI in the presence of corruption. In particular, it addresses the question whether more corrupt regions in Russia are also those that could have accumulated more of FDI stocks, and investigates whether those 'more corrupt' regions would have had lower level of public capital investment. Finally, it examines whether decentralisation increases or decreases corruption and whether a larger extent of decentralisation has a positive or negative impact on FDI (stocks). The results of three studies are as follows. Firstly, along with market potential, corruption is found to be one of the key factors in explaining FDI distribution within Russia between 2002 and 2004. Secondly, corruption on average is found to be related to FDI positively suggesting that it may act as speed money: to save their time foreign direct investors might be willing to bribe the regional authorities so to move in front of the bureaucratic lines. Thirdly, although when corruption is controlled for, the impact of the latter on unobservable FDI is found to be on average positive, no association between FDI and public investment is observed with the only exception of transportation infrastructure (i.e., railway). The results might suggest therefore that it is possible that not only regions with high levels of perceived corruption attract more FDI but also that expansions in public capital investments are not accompanied by an increase of the volume of FDI (stocks) in regions with high levels of corruption. This casts some doubt on the productivity of the investment in public capital in these regions as it might be that bureaucrats may prefer to use these infrastructural projects for rent extraction. Finally, we find decentralisation to have a significant and positive impact on both FDI stock accumulation and corruption, suggesting that local governments may spend more on public goods to make the area more attractive to foreign investors but at the same time they may be interested into extracting rents from foreign investors. These results support the idea that the regulation of FDI is associated with and facilitated by a larger public sector, which distorts competition and introduces opportunities for rent-seeking by particular economic and political factors.

The Role of protein kinase C modulation in the antiproliferative effects of bistratene A, bryostatin 1 and phorbol esters

PKC-mediated signalling pathways are important in cell growth and differentiation, and aberrations in these pathways are implicated in tumourigenesis. The objective of this project was to clarify the link between cell growth inhibition and PKC modulation.The PKC activators bryostatin 1 and 12-0-tetradecanoylphorbol-13-acetate (TPA) inhibited growth in A549 and MCF-7 adenocarcinoma cells with great potency, and induced HL-60 leukaemia cell differentiation. Bistratene A affected these cells similarly. Experiments were conducted to test the hypotheses that bistratene A exerts its effects via PKC modulation and that characteristics of cytostasis induced by bryostatin 1 and TPA depend upon PKC isozyme-specific events. After incubation of A549 cells with TPA or bistratene A, 2D phosphoprotein electrophoretograrns revealed three proteins phosphorylated by both agents. However, bistratene A was unable to induce the formation of cellular networks on the basement membrane substitute Matrigel, and staurosporine was unable to reverse bistratene A-induced [3H]thymidine uptake inhibition, unlike TPA. Bistratene A did not induce PKC translocation or downregulation, activate or inhibit A549 and MCF-7 cell cytosolic PKC or compete for phorbol ester receptors. Western blot analysis and hydroxylapatite chromatography identified PKC α, ε and ζ in these cells. Bistratene A was unable to activate any of these isoforms. Therefore the agent does not exert its antiproliferative effects by modulation of PKC activity. The abilities of bryostatin 1 and TPA (10nM-1μM) to induce PKC isoform translocation and downregulation were compared with antiproliferative effects. Both agents induced dose-dependent downregulation and translocation of PKC α and ε to particulate and nuclear cell fractions. PKC ζ was translocated to the particulate fraction by both agents in MCF-7 cells. The similarity of PKC isoform redistribution by these agents did not explain their divergent effects on cell growth, and the role of nuclear translocation of PKC in cytostasis was not confirmed by these studies. Alternative factors governing the characteristics of growth inhibition induced by these agents are discussed.

Design and evaluation of a framework for cooperative and adaptive QoS control of DSRC network for road safety applications

Dedicated short-range communications (DSRC) are a promising vehicle communication technique for collaborative road safety applications (CSA). However, road safety applications require highly reliable and timely wireless communications, which present big challenges to DSRC based vehicle networks on effective and robust quality of services (QoS) provisioning due to the random channel access method applied in the DSRC technique. In this paper we examine the QoS control problem for CSA in the DSRC based vehicle networks and presented an overview of the research work towards the QoS control problem. After an analysis of the system application requirements and the DSRC vehicle network features, we propose a framework for cooperative and adaptive QoS control, which is believed to be a key for the success of DSRC on supporting effective collaborative road safety applications. A core design in the proposed QoS control framework is that network feedback and cross-layer design are employed to collaboratively achieve targeted QoS. A design example of cooperative and adaptive rate control scheme is implemented and evaluated, with objective of illustrating the key ideas in the framework. Simulation results demonstrate the effectiveness of proposed rate control schemes in providing highly available and reliable channel for emergency safety messages. © 2013 Wenyang Guan et al.

Bessel beams from semiconductor light sources

We report on recent progress in the generation of non-diffracting (Bessel) beams from semiconductor light sources including both edge-emitting and surface-emitting semiconductor lasers as well as light-emitting diodes (LEDs). Bessel beams at the power level of Watts with central lobe diameters of a few to tens of micrometers were achieved from compact and highly efficient lasers. The practicality of reducing the central lobe size of the Bessel beam generated with high-power broad-stripe semiconductor lasers and LEDs to a level unachievable by means of traditional focusing has been demonstrated. We also discuss an approach to exceed the limit of power density for the focusing of radiation with high beam propagation parameter M2. Finally, we consider the potential of the semiconductor lasers for applications in optical trapping/tweezing and the perspectives to replace their gas and solid-state laser counterparts for a range of implementations in optical manipulation towards lab-on-chip configurations. © 2014 Elsevier Ltd.

Optical trapping with superfocused high-M2 laser diode beam

Many applications of high-power laser diodes demand tight focusing. This is often not possible due to the multimode nature of semiconductor laser radiation possessing beam propagation parameter M2 values in double-digits. We propose a method of 'interference' superfocusing of high-M2 diode laser beams with a technique developed for the generation of Bessel beams based on the employment of an axicon fabricated on the tip of a 100 μm diameter optical fiber with highprecision direct laser writing. Using axicons with apex angle 140º and rounded tip area as small as 10 μm diameter, we demonstrate 2-4 μm diameter focused laser 'needle' beams with approximately 20 μm propagation length generated from multimode diode laser with beam propagation parameter M2=18 and emission wavelength of 960 nm. This is a few-fold reduction compared to the minimal focal spot size of 11 μm that could be achieved if focused by an 'ideal' lens of unity numerical aperture. The same technique using a 160º axicon allowed us to demonstrate few-μm-wide laser 'needle' beams with nearly 100 μm propagation length with which to demonstrate optical trapping of 5-6 μm rat blood red cells in a water-heparin solution. Our results indicate the good potential of superfocused diode laser beams for applications relating to optical trapping and manipulation of microscopic objects including living biological objects with aspirations towards subsequent novel lab-on-chip configurations.

Dynamics of on-line gradient descent learning for multilayer neural networks

We consider the problem of on-line gradient descent learning for general two-layer neural networks. An analytic solution is presented and used to investigate the role of the learning rate in controlling the evolution and convergence of the learning process.

On-line learning in multilayer neural networks

We present an analytic solution to the problem of on-line gradient-descent learning for two-layer neural networks with an arbitrary number of hidden units in both teacher and student networks. The technique, demonstrated here for the case of adaptive input-to-hidden weights, becomes exact as the dimensionality of the input space increases.

Adaptive back-propagation in on-line learning of multilayer networks

An adaptive back-propagation algorithm is studied and compared with gradient descent (standard back-propagation) for on-line learning in two-layer neural networks with an arbitrary number of hidden units. Within a statistical mechanics framework, both numerical studies and a rigorous analysis show that the adaptive back-propagation method results in faster training by breaking the symmetry between hidden units more efficiently and by providing faster convergence to optimal generalization than gradient descent.

Finite-size effects in on-line learning of multilayer neural networks

We complement recent advances in thermodynamic limit analyses of mean on-line gradient descent learning dynamics in multi-layer networks by calculating fluctuations possessed by finite dimensional systems. Fluctuations from the mean dynamics are largest at the onset of specialisation as student hidden unit weight vectors begin to imitate specific teacher vectors, increasing with the degree of symmetry of the initial conditions. In light of this, we include a term to stimulate asymmetry in the learning process, which typically also leads to a significant decrease in training time.