Capillary electrochromatography: a versatile instrumental technique for nanodomain interaction studies

This doctoral thesis describes the development of a miniaturized capillary electrochromatography (CEC) technique suitable for the study of interactions between various nanodomains of biological importance. The particular focus of the study was low-density lipoprotein (LDL) particles and their interaction with components of the extracellular matrix (ECM). LDL transports cholesterol to the tissues through the blood circulation, but when the LDL level becomes too high the particles begin to permeate and accumulate in the arteries. Through binding sites on apolipoprotein B-100 (apoB-100), LDL interacts with components of the ECM, such as proteoglycans (PGs) and collagen, in what is considered the key mechanism in the retention of lipoproteins and onset of atherosclerosis. Hydrolytic enzymes and oxidizing agents in the ECM may later successively degrade the LDL surface. Metabolic diseases such as diabetes may provoke damage of the ECM structure through the non-enzymatic reaction of glucose with collagen. In this work, fused silica capillaries of 50 micrometer i.d. were successfully coated with LDL and collagen, and steroids and apoB-100 peptide fragments were introduced as model compounds for interaction studies. The LDL coating was modified with copper sulphate or hydrolytic enzymes, and the interactions of steroids with the native and oxidized lipoproteins were studied. Lipids were also removed from the LDL particle coating leaving behind an apoB-100 surface for further studies. The development of collagen and collagen decorin coatings was helpful in the elucidation of the interactions of apoB-100 peptide fragments with the primary ECM component, collagen. Furthermore, the collagen I coating provided a good platform for glycation studies and for clarification of LDL interactions with native and modified collagen. All methods developed are inexpensive, requiring just small amounts of biomaterial. Moreover, the experimental conditions in CEC are easily modified, and the analyses can be carried out in a reasonable time frame. Other techniques were employed to support and complement the CEC studies. Scanning electron microscopy and atomic force microscopy provided crucial visual information about the native and modified coatings. Asymmetrical flow field-flow fractionation enabled size measurements of the modified lipoproteins. Finally, the CEC results were exploited to develop new sensor chips for a continuous flow quartz crystal microbalance technique, which provided complementary information about LDL ECM interactions. This thesis demonstrates the potential of CEC as a valuable and flexible technique for surface interaction studies. Further, CEC can serve as a novel microreactor for the in situ modification of LDL and collagen coatings. The coatings developed in this study provide useful platforms for a diversity of future investigations on biological nanodomains.

A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

Role of magnesium ion on the interaction between chromomycin A3 and deoxyribonucleic acid

Abstract is not available.

Novel modulation strategy for a CLC resonant dual active bridge

This paper proposes a novel modulation strategy for a phase controlled Capacitor-Inductor-Capacitor (CLC) Resonant Dual Active Bridge (RDAB). The proposed modulation strategy improves the soft turn-on, Zero-Current-Switching (ZCS) and Zero-Voltage-Switching (ZVS) range of the converter while only minimally increasing the required reactive currents in the ac link. A mathematical analysis of the proposed modulation scheme is presented along with a theoretical loss comparison between several modulation strategies. The proposed modulation strategy was implemented and the experimental results are presented.

Complete genome sequence and integrated protein localization and interaction map for alfalfa dwarf virus, which combines properties of both cytoplasmic and nuclear plant rhabdoviruses

Summary We have determined the full-length 14,491-nucleotide genome sequence of a new plant rhabdovirus, alfalfa dwarf virus (ADV). Seven open reading frames (ORFs) were identified in the antigenomic orientation of the negative-sense, single-stranded viral RNA, in the order 3′-N-P-P3-M-G-P6-L-5′. The ORFs are separated by conserved intergenic regions and the genome coding region is flanked by complementary 3′ leader and 5′ trailer sequences. Phylogenetic analysis of the nucleoprotein amino acid sequence indicated that this alfalfa-infecting rhabdovirus is related to viruses in the genus Cytorhabdovirus. When transiently expressed as GFP fusions in Nicotiana benthamiana leaves, most ADV proteins accumulated in the cell periphery, but unexpectedly P protein was localized exclusively in the nucleus. ADV P protein was shown to have a homotypic, and heterotypic nuclear interactions with N, P3 and M proteins by bimolecular fluorescence complementation. ADV appears unique in that it combines properties of both cytoplasmic and nuclear plant rhabdoviruses.

Creating employability skills in SMEs: Modification through interaction

This paper is concerned with the degree to which the graduate skills required by industry are developed in Australian universities. Despite acknowledgement of the need to increase the graduate skills of students, it would seem that the stated intentions of Australian universities in this respect do not yet meet the expectations of industry. The development of an enterprise program at the University of Tasmania provides by way of example, support that the development of industry-desired skills is possible alongside the desirable knowledge outcomes of a university. It is argued that lecturers and students must give and accept more responsibility for learning to enable the development of desirable graduate skills.

Experimental investigation of interaction of strong shock heated oxygen gas on the surface of ZrO2 - a novel method to understand re-combination heating

Interaction of shock heated test gas in the free piston driven shock tube with bulk and thin film of cubic zirconium dioxide (ZrO2) prepared by combustion method is investigated. The test samples before and after exposure to the shock wave are analyzed by X-ray diffraction (XRD), X-Ray Photoelectron Spectroscopy (XPS) and Scanning Electron Microscope (SEM). The study shows transformation of metastable cubic ZrO2 to stable monoclinic ZrO2 phase after interacting with shock heated oxygen gas due to the heterogeneous catalytic recombination surface reaction.

Middleware for Mobile Sensing Applications in Urban Environments

Sensor networks represent an attractive tool to observe the physical world. Networks of tiny sensors can be used to detect a fire in a forest, to monitor the level of pollution in a river, or to check on the structural integrity of a bridge. Application-specific deployments of static-sensor networks have been widely investigated. Commonly, these networks involve a centralized data-collection point and no sharing of data outside the organization that owns it. Although this approach can accommodate many application scenarios, it significantly deviates from the pervasive computing vision of ubiquitous sensing where user applications seamlessly access anytime, anywhere data produced by sensors embedded in the surroundings. With the ubiquity and ever-increasing capabilities of mobile devices, urban environments can help give substance to the ubiquitous sensing vision through Urbanets, spontaneously created urban networks. Urbanets consist of mobile multi-sensor devices, such as smart phones and vehicular systems, public sensor networks deployed by municipalities, and individual sensors incorporated in buildings, roads, or daily artifacts. My thesis is that "multi-sensor mobile devices can be successfully programmed to become the underpinning elements of an open, infrastructure-less, distributed sensing platform that can bring sensor data out of their traditional close-loop networks into everyday urban applications". Urbanets can support a variety of services ranging from emergency and surveillance to tourist guidance and entertainment. For instance, cars can be used to provide traffic information services to alert drivers to upcoming traffic jams, and phones to provide shopping recommender services to inform users of special offers at the mall. Urbanets cannot be programmed using traditional distributed computing models, which assume underlying networks with functionally homogeneous nodes, stable configurations, and known delays. Conversely, Urbanets have functionally heterogeneous nodes, volatile configurations, and unknown delays. Instead, solutions developed for sensor networks and mobile ad hoc networks can be leveraged to provide novel architectures that address Urbanet-specific requirements, while providing useful abstractions that hide the network complexity from the programmer. This dissertation presents two middleware architectures that can support mobile sensing applications in Urbanets. Contory offers a declarative programming model that views Urbanets as a distributed sensor database and exposes an SQL-like interface to developers. Context-aware Migratory Services provides a client-server paradigm, where services are capable of migrating to different nodes in the network in order to maintain a continuous and semantically correct interaction with clients. Compared to previous approaches to supporting mobile sensing urban applications, our architectures are entirely distributed and do not assume constant availability of Internet connectivity. In addition, they allow on-demand collection of sensor data with the accuracy and at the frequency required by every application. These architectures have been implemented in Java and tested on smart phones. They have proved successful in supporting several prototype applications and experimental results obtained in ad hoc networks of phones have demonstrated their feasibility with reasonable performance in terms of latency, memory, and energy consumption.

On a generalized dynamic model of bi-state social interaction processes

A non-linear model, construed as a generalized version of the models put forth earlier for the study of bi-state social interaction processes, is proposed in this study. The feasibility of deriving the dynamics of such processes is demonstrated by establishing equivalence between the non-linear model and a higher order linear model.

Non-target species interaction with sodium fluoroacetate (1080) meat bait for controlling feral pigs (Sus scrofa)

Fresh meat baits containing sodium fluoroacetate (1080) are widely used for controlling feral pigs in Queensland, but there is a potential poisoning risk to non-target species. This study investigated the non-target species interactions with meat bait by comparing the time until first approach, investigation, sample and consumption, and whether dying bait green would reduce interactions. A trial assessing species interactions with undyed bait was completed at Culgoa Floodplain National Park, Queensland. Meat baits were monitored for 79 consecutive days with camera traps. Of 40 baits, 100% were approached, 35% investigated (moved) and 25% sampled, and 25% consumed. Monitors approached (P < 0.05) and investigated (P < 0.05) the bait more rapidly than pigs or birds, but the median time until first sampling was not significantly different (P > 0.05), and did not consume any entire bait. A trial was conducted at Whetstone State Forest, southern Queensland, with green-dyed and undyed baits monitored for eight consecutive days with cameras. Of 60 baits, 92% were approached and also investigated by one or more non-target species. Most (85%) were sampled and 57% were consumed, with monitors having slightly more interaction with undyed baits than with green-dyed baits. Mean time until first approach and sample differed significantly between species groups (P = 0.038 and 0.007 respectively) with birds approaching sooner (P < 0.05) and monitors sampling later (P < 0.05) than other (unknown) species (P > 0.05). Undyed bait was sampled earlier (mean 2.19 days) than green-dyed bait (2.7 days) (P = 0.003). Data from the two trials demonstrate that many non-target species regularly visit and sample baits. The use of green-dyed baits may help reduce non-target uptake, but testing is required to determine the effect on attractiveness to feral pigs. Further research is recommended to quantify the benefits of potential strategies to reduce the non-target uptake of meat baits to help improve the availability of bait to feral pigs.

Selectivity in the Interaction of Electron Donor and Acceptor Molecules with Graphene and Single-Walled Carbon Nanotubes

Interaction of electron donor and acceptor molecules with graphene samples prepared by different methods as well as with single-walled carbon nanotubes (SWNTs) has been investigated by isothermal titration calorimetry (ITC). The ITC interaction energies of the graphene samples and SWNTs with electron acceptor molecules are higher than those with electron donor molecules. Thus, tetracyanoethylene (TCNE) shows the highest interaction energy with both graphene and SWNTs. The interaction energy with acceptor molecules varies with the electron affinity as well as with the charge-transfer transition energy for different aromatics. Metallic SWNTs interact reversibly with electron acceptor molecules, resulting in the opening of a gap.

Localised spin wave modes in a Heisenberg ferromagnet with biquadratic interaction

The presence of biquadratic exchange in a one-dimensional ferromagnetic Heisenberg chain with an impurity spin is shown to change the nature of the impurity modes and its eigenvalues considerably which can be observed experimentally.