Wide-band spectral power fluctuations characterize the response of simulated cortical networks to increasing stimulus intensity

The hippocampus is an anatomically distinct region of the medial temporal lobe that plays a critical role in the formation of declarative memories. Here we show that a computer simulation of simple compartmental cells organized with basic hippocampal connectivity is capable of producing stimulus intensity sensitive wide-band fluctuations of spectral power similar to that seen in real EEG. While previous computational models have been designed to assess the viability of the putative mechanisms of memory storage and retrieval, they have generally been too abstract to allow comparison with empirical data. Furthermore, while the anatomical connectivity and organization of the hippocampus is well defined, many questions regarding the mechanisms that mediate large-scale synaptic integration remain unanswered. For this reason we focus less on the specifics of changing synaptic weights and more on the population dynamics. Spectral power in four distinct frequency bands were derived from simulated field potentials of the computational model and found to depend on the intensity of a random input. The majority of power occurred in the lowest frequency band (3-6 Hz) and was greatest to the lowest intensity stimulus condition (1% maximal stimulus). In contrast, higher frequency bands ranging from 7-45 Hz show an increase in power directly related with an increase in stimulus intensity. This trend continues up to a stimulus level of 15% to 20% of the maximal input, above which power falls dramatically. These results suggest that the relative power of intrinsic network oscillations are dependent upon the level of activation and that above threshold levels all frequencies are damped, perhaps due to over activation of inhibitory interneurons.

Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Power quality improvements in low voltage distribution networks containing distributed energy resources

In this thesis various schemes using custom power devices for power quality improvement in low voltage distribution network are studied. Customer operated distributed generators makes a typical network non-radial and affect the power quality. A scheme considering different algorithm of DSTATCOM is proposed for power circulation and islanded operation of the system. To compensate reactive power overflow and facilitate unity power factor, a UPQC is introduced. Stochastic analysis is carried out for different scenarios to get a comprehensive idea about a real life distribution network. Combined operation of static compensator and voltage regulator is tested for the optimum quality and stability of the system.

Preparation and characterization of poly(lactic-co-glycolic acid) microparticles containing DNA molecules encoding a malaria vaccine candidate

Background A novel ultrasonic atomization approach for the formulation of biodegradable poly(lactic-co-glycolic acid) (PLGA) microparticles of a malaria DNA vaccine is presented. A 40 kHz ultrasonic atomization device was used to create the microparticles from a feedstock containing 5 volumes of 0.5% w/v PLGA in acetone and 1 volume of condensed DNA which was fed at a flow rate of 18ml h-1. The plasmid DNA vectors encoding a malaria protein were condensed with a cationic polymer before atomization. Results High levels of gene expression in vitro were observed in COS-7 cells transfected with condensed DNA at a nitrogen to phosphate (N/P) ratio of 10. At this N/P ratio, the condensed DNA exhibited a monodispersed nanoparticle size (Z-average diameter of 60.8 nm) and a highly positive zeta potential of 38.8mV. The microparticle formulations of malaria DNA vaccine were quality assessed and it was shown that themicroparticles displayed high encapsulation efficiencies between 82-96% and a narrow size distribution in the range of 0.8-1.9 μm. In vitro release profile revealed that approximately 82% of the DNA was released within 30 days via a predominantly diffusion controlledmass transfer system. Conclusions This ultrasonic atomization technique showed excellent particle size reproducibility and displayed potential as an industrially viable approach for the formulation of controlled release particles.

Rapid production of a plasmid DNA encoding a malaria vaccine candidate via amino-functionalized poly(GMA-co-EDMA) monolith

Malaria is a global health problem; an effective vaccine is urgently needed. Due to the relative poverty and lack of infrastructure in malaria endemic areas, DNA-based vaccines that are stable at ambient temperatures and easy to formulate have great potential. While attention has been focused mainly on antigen selection, vector design and efficacy assessment, the development of a rapid and commercially viable process to manufacture DNA is generally overlooked. We report here a continuous purification technique employing an optimized stationary adsorbent to allow high-vaccine recovery, low-processing time, and, hence, high-productivity. A 40.0 mL monolithic stationary phase was synthesized and functionalized with amino groups from 2-Chloro-N,N- diethylethylamine hydrochloride for anion-exchange isolation of a plasmid DNA (pDNA) that encodes a malaria vaccine candidate, VR1020-PyMSP4/5. Physical characterization of the monolithic polymer showed a macroporous material with a modal pore diameter of 750 nm. The final vaccine product isolated after 3 min elution was homogeneous supercoiled plasmid with gDNA, RNA and protein levels in keeping with clinical regulatory standards. Toxicological studies of the pVR1020-PyMSP4/5 showed a minimum endotoxin level of 0.28 EU/m.g pDNA. This cost-effective technique is cGMP compatible and highly scalable for the production of DNA-based vaccines in commercial quantities, when such vaccines prove to be effective against malaria. © 2008 American Institute of Chemical Engineers.

Performance of R-N(R′)-R″ functionalised poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate) monolithic sorbent for plasmid DNA adsorption

High-throughput plasmid DNA (pDNA) manufacture is obstructed predominantly by the performance of conventional stationary phases. For this reason, the search for new materials for fast chromatographic separation of pDNA is ongoing. A poly(glycidyl methacrylate-co-ethylene glycol dimethacrylate) (GMA-EGDMA) monolithic material was synthesised via a thermal-free radical reaction, functionalised with different amino groups from urea, 2-chloro-N,N-diethylethylamine hydrochloride (DEAE-Cl) and ammonia in order to investigate their plasmid adsorption capacities. Physical characterisation of the monolithic polymer showed a macroporous polymer having a unimodal pore size distribution pivoted at 600 nm. Chromatographic characterisation of the functionalised polymers using pUC19 plasmid isolated from E. coli DH5α-pUC19 showed a maximum plasmid adsorption capacity of 18.73 mg pDNA/mL with a dissociation constant (KD) of 0.11 mg/mL for GMA-EGDMA/DEAE-Cl polymer. Studies on ligand leaching and degradation demonstrated the stability of GMA-EGDMA/DEAE-Cl after the functionalised polymers were contacted with 1.0 M NaOH, which is a model reagent for most 'cleaning in place' (CIP) systems. However, it is the economic advantage of an adsorbent material that makes it so attractive for commercial purification purposes. Economic evaluation of the performance of the functionalised polymers on the grounds of polymer cost (PC)/mg pDNA retained endorsed the suitability of GMA-EGDMA/DEAE-Cl polymer.

The suitability of DEAE-Cl active groups on customized poly(GMA-co-EDMA) continuous stationary phase for fast enzyme-free isolation of plasmid DNA

The creation of a commercially viable and a large-scale purification process for plasmid DNA (pDNA) production requires a whole-systems continuous or semi-continuous purification strategy employing optimised stationary adsorption phase(s) without the use of expensive and toxic chemicals, avian/bovine-derived enzymes and several built-in unit processes, thus affecting overall plasmid recovery, processing time and economics. Continuous stationary phases are known to offer fast separation due to their large pore diameter making large molecule pDNA easily accessible with limited mass transfer resistance even at high flow rates. A monolithic stationary sorbent was synthesised via free radical liquid porogenic polymerisation of ethylene glycol dimethacrylate (EDMA) and glycidyl methacrylate (GMA) with surface and pore characteristics tailored specifically for plasmid binding, retention and elution. The polymer was functionalised with an amine active group for anion-exchange purification of pDNA from cleared lysate obtained from E. coli DH5α-pUC19 pellets in RNase/protease-free process. Characterization of the resin showed a unique porous material with 70% of the pores sizes above 300 nm. The final product isolated from anion-exchange purification in only 5 min was pure and homogenous supercoiled pDNA with no gDNA, RNA and protein contamination as confirmed with DNA electrophoresis, restriction analysis and SDS page. The resin showed a maximum binding capacity of 15.2 mg/mL and this capacity persisted after several applications of the resin. This technique is cGMP compatible and commercially viable for rapid isolation of pDNA.

Bayesian networks for information synthesis in complex systems

This thesis introduces a method of applying Bayesian Networks to combine information from a range of data sources for effective decision support systems. It develops a set of techniques in development, validation, visualisation, and application of Complex Systems models, with a working demonstration in an Australian airport environment. The methods presented here have provided a modelling approach that produces highly flexible, informative and applicable interpretations of a system's behaviour under uncertain conditions. These end-to-end techniques are applied to the development of model based dashboards to support operators and decision makers in the multi-stakeholder airport environment. They provide highly flexible and informative interpretations and confidence in these interpretations of a system's behaviour under uncertain conditions.

MIMO enhanced slotted cooperation in urban vehicular networks

The requirement of isolated relays is one of the prime obstacles in utilizing sequential slotted cooperative protocols for Vehicular Ad-hoc Networks (VANET). Significant research advancement has taken place to improve the diversity multiplexing trade-off (DMT) of cooperative protocols in conventional mobile networks without much attention on vehicular ad-hoc networks. We have extended the concept of sequential slotted amplify and forward (SAF) protocols in the context of urban vehicular ad-hoc networks. Multiple Input Multiple Output (MIMO) reception is used at relaying vehicular nodes to isolate the relays effectively. The proposed approach adds a pragmatic value to the sequential slotted cooperative protocols while achieving attractive performance gains in urban VANETs. We have analysed the DMT bounds and the outage probabilities of the proposed scheme. The results suggest that the proposed scheme can achieve an optimal DMT similar to the DMT upper bound of the sequential SAF. Furthermore, the outage performance of the proposed scheme outperforms the SAF protocol by 2.5 dB at a target outage probability of 10-4.

Multi-objective models and techniques for analysing the absolute capacity of railway networks

Railway capacity determination and expansion are very important topics. In prior research, the competition between different entities such as train services and train types, on different network corridors however have been ignored, poorly modelled, or else assumed to be static. In response, a comprehensive set of multi-objective models have been formulated in this article to perform a trade-off analysis. These models determine the total absolute capacity of railway networks as the most equitable solution according to a clearly defined set of competing objectives. The models also perform a sensitivity analysis of capacity with respect to those competing objectives. The models have been extensively tested on a case study and their significant worth is shown. The models were solved using a variety of techniques however an adaptive E constraint method was shown to be most superior. In order to identify only the best solution, a Simulated Annealing meta-heuristic was implemented and tested. However a linearization technique based upon separable programming was also developed and shown to be superior in terms of solution quality but far less in terms of computational time.

Empirical modelling of the relationship between bus and car speeds on signalised urban networks

Vehicle speed is an important attribute for analysing the utility of a transport mode. The speed relationship between multiple modes of transport is of interest to traffic planners and operators. This paper quantifies the relationship between bus speed and average car speed by integrating Bluetooth data and Transit Signal Priority data from the urban network in Brisbane, Australia. The method proposed in this paper is the first of its kind to relate bus speed and average car speed by integrating multi-source traffic data in a corridor-based method. Three transferable regression models relating not-in-service bus, in-service bus during peak periods, and in-service bus during off-peak periods with average car speed are proposed. The models are cross-validated and the interrelationships are significant.

Fine-grained plant classification using convolutional neural networks for feature extraction

We present an overview of the QUT plant classification system submitted to LifeCLEF 2014. This system uses generic features extracted from a convolutional neural network previously used to perform general object classification. We examine the effectiveness of these features to perform plant classification when used in combination with an extremely randomised forest. Using this system, with minimal tuning, we obtained relatively good results with a score of 0:249 on the test set of LifeCLEF 2014.

Capacity determination and expansion models for rail networks

This thesis focused upon the development of improved capacity analysis and capacity planning techniques for railways. A number of innovations were made and were tested on a case study of a real national railway. These techniques can reduce the time required to perform decision making activities that planners and managers need to perform. As all railways need to be expanded to meet increasing demands, the presumption that analytical capacity models can be used to identify how best to improve an existing network at least cost, was fully investigated. Track duplication was the mechanism used to expanding a network's capacity, and two variant capacity expansion models were formulated. Another outcome of this thesis is the development and validation of bi objective models for capacity analysis. These models regulate the competition for track access and perform a trade-off analysis. An opportunity to develop more general mulch-objective approaches was identified.

Impact of mobility constraints on epidemic broadcast mechanisms in delay-tolerant networks

In this paper, we investigate the effect of mobility constraints on epidemic broadcast mechanisms in DTNs (Delay-Tolerant Networks). Major factors affecting epidemic broadcast performances are its forwarding algorithm and node mobility. The impact of forwarding algorithm and node mobility on epidemic broadcast mechanisms has been actively studied in the literature, but those studies generally use unconstrained mobility models. The objective of this paper is therefore to quantitatively investigate the effect of mobility constraints on epidemic broadcast mechanisms. We evaluate the performances of three classes of epidemic broadcast mechanisms - P-BCAST (PUSH-based BroadCast), SA-BCAST (Self-Adaptive BroadCast), and HP-BCAST (History-based P-BCAST) - with a random waypoint mobility model with mobility constraints. Our finding includes that the existence of mobility constraints significantly improves the reach ability and dissemination speed of epidemic broadcast mechanisms while degrading their efficiency.