Large Scale Simulations of Hippocampal-Neocortical Interactions in a Parallel Version of Genesis

A hippocampal-CA3 memory model was constructed with PGENESIS, a recently developed version of GENESIS that allows for distributed processing of a neural network simulation. A number of neural models of the human memory system have identified the CA3 region of the hippocampus as storing the declarative memory trace. However, computational models designed to assess the viability of the putative mechanisms of storage and retrieval have generally been too abstract to allow comparison with empirical data. Recent experimental evidence has shown that selective knock-out of NMDA receptors in the CA1 of mice leads to reduced stability of firing specificity in place cells. Here a similar reduction of stability of input specificity is demonstrated in a biologically plausible neural network model of the CA3 region, under conditions of Hebbian synaptic plasticity versus an absence of plasticity. The CA3 region is also commonly associated with seizure activity. Further simulations of the same model tested the response to continuously repeating versus randomized nonrepeating input patterns. Each paradigm delivered input of equal intensity and duration. Non-repeating input patterns elicited a greater pyramidal cell spike count. This suggests that repetitive versus non-repeating neocortical inpus has a quantitatively different effect on the hippocampus. This may be relevant to the production of independent epileptogenic zones and the process of encoding new memories.

A thermal expulsion approach to homogeneous large-volume methacrylate monolith preparation; enabling large-scale rapid purification of biomolecules

Numerous efforts have been dedicated to the synthesis of large-volume methacrylate monoliths for large-scale biomolecules purification but most were obstructed by the enormous release of exotherms during preparation, thereby introducing structural heterogeneity in the monolith pore system. A significant radial temperature gradient develops along the monolith thickness, reaching a terminal temperature that supersedes the maximum temperature required for structurally homogenous monoliths preparation. The enormous heat build-up is perceived to encompass the heat associated with initiator decomposition and the heat released from free radical-monomer and monomer-monomer interactions. The heat resulting from the initiator decomposition was expelled along with some gaseous fumes before commencing polymerization in a gradual addition fashion. Characteristics of 80 mL monolith prepared using this technique was compared with that of a similar monolith synthesized in a bulk polymerization mode. An extra similarity in the radial temperature profiles was observed for the monolith synthesized via the heat expulsion technique. A maximum radial temperature gradient of only 4.3°C was recorded at the center and 2.1°C at the monolith peripheral for the combined heat expulsion and gradual addition technique. The comparable radial temperature distributions obtained birthed identical pore size distributions at different radial points along the monolith thickness.

Development of a pilot-scale bacterial fermentation for plasmid-based biopharmaceutical production using a stoichiometric medium

The recognition of the potential efficacy of plasmid DNA (pDNA) molecules as vectors in the treatment and prevention of emerging diseases has birthed the confidence to combat global pandemics. This is due to the close-to-zero safety concern associated with pDNA vectors compared to viral vectors in cell transfection and targeting. Considerable attention has been paid to the potential of pDNA vectors but comparatively less thought has been given to the practical challenges in producing large quantities to meet current rising demands. A pilot-scale fermentation scheme was developed by employing a stoichiometrically-designed growth medium whose exceptional plasmid yield performance was attested in a shake flask environment for pUC19 and pEGFP-N1 transformed into E. coliDH5α and E. coliJM109, respectively. Batch fermentation of E. coliDH5α-pUC19 employing the stoichiometric medium displayed a maximum plasmid volumetric and specific yield of 62.6 mg/L and 17.1 mg/g (mg plasmid/g dry cell weight), respectively. Fed-batch fermentation of E. coliDH5α-pUC19 on a glycerol substrate demonstrated one of the highest ever reported pilot-scale plasmid specific yield of 48.98 mg/g and a volumetric yield of 0.53 g/L. The attainment of high plasmid specific yields constitutes a decrease in plasmid manufacturing cost and enhances the effectiveness of downstream processes by reducing the proportion of intracellular impurities. The effect of step-rise temperature induction was also considered to maximize ColE1-origin plasmid replication.

Large-scale habitat mapping using vision-based AUVs : experiences, challenges & vehicle design

This paper overviews the development of a vision-based AUV along with a set of complementary operational strategies to allow reliable autonomous data collection in relatively shallow water and coral reef environments. The development of the AUV, called Starbug, encountered many challenges in terms of vehicle design, navigation and control. Some of these challenges are discussed with focus on operational strategies for estimating and reducing the total navigation error when using lower-resolution sensing modalities. Results are presented from recent field trials which illustrate the ability of the vehicle and associated operational strategies to enable rapid collection of visual data sets suitable for marine research applications.

Psychological well-being status among medical and dental students in Makkah, Saudi Arabia: A cross-sectional study

Objectives Medical and dental students experience poor psychological well-being relative to their peers. This study aimed to assess the psychological well-being among medical and dental students in Saudi Arabia, identify the high-risk groups and assess the association between the psychological well-being and the academic performance. Methods In this cross-sectional study, 422 preclinical medical and dental students at Umm Al-Qura University, Saudi Arabia, were recruited to assess their depression, anxiety, stress, self-efficacy and satisfaction with life levels using 21-items Depression Anxiety Stress Scale (DASS-21), General Self-Efficacy (GSE) scale and Satisfaction With Life Scale (SWLS). Students’ academic weighted grades were obtained later. Descriptive statistics and univariate general linear model were used to analyse data. Results High levels of depression (69.9%), anxiety (66.4%) and stress (70.9%) were indicated, whereas self-efficacy (mean = 27.22, sd = 4.85) and life satisfaction (mean = 23.60, sd = 6.37) were within the normal range. Female medical students had higher psychological distress in contrast to dental students. In general, third-year students were more depressed and stressed in comparison with second-year students, except for stress among dental students. Moreover, all females had higher self-efficacy than males. Life satisfaction was higher within the second-year and high family income students. Depression was the only psychological variable correlated with the academic performance. Conclusion High levels of psychological distress were found. Female medical students had higher psychological distress than males, whereas male dental students had higher distress than female. Medical students at third year were more depressed and stressed. Dental students were more depressed in the third year, but more stressed in the second year. Attention should be directed towards reducing the alarming levels of depression, anxiety and stress among medical and dental students.

Scale adaptive tracking using mean shift and efficient feature matching

The mean shift tracker has achieved great success in visual object tracking due to its efficiency being nonparametric. However, it is still difficult for the tracker to handle scale changes of the object. In this paper, we associate a scale adaptive approach with the mean shift tracker. Firstly, the target in the current frame is located by the mean shift tracker. Then, a feature point matching procedure is employed to get the matched pairs of the feature point between target regions in the current frame and the previous frame. We employ FAST-9 corner detector and HOG descriptor for the feature matching. Finally, with the acquired matched pairs of the feature point, the affine transformation between target regions in the two frames is solved to obtain the current scale of the target. Experimental results show that the proposed tracker gives satisfying results when the scale of the target changes, with a good performance of efficiency.

Synthetic rating system for railway bridge management

This thesis developed a condition assessment and rating method to identify those bridges in a network which are in most need of repair for an effective life cycle management. The method estimates the contribution of critical factors towards bridge deterioration and uses structural analysis to overcome the subjectivity of traditional current condition assessment methods. This research was a part of the CRC project titled 'Life Cycle Management of Railway Bridges'. Efficient usage of resources and enhancing the safety and serviceability of railway bridges are the significant outcomes of using the proposed method.

Cross-scale biophysics modelling of F-actin cytoskeleton in cell

This thesis is a comparative study of the modelling of mechanical behaviours of F-actin cytoskeleton which is an important structural component in living cells. A new granular model was developed for F-actin cytoskeleton based on the concept of multiscale modelling. This framework overcomes difficulties encountered in physical modelling of cytoskeleton in conventional continuum mechanics modelling, and the computational challenges in all-atom molecular dynamics simulation. The thermostat algorithm was further modified to better predict the thermodynamic properties of F-actin cytoskeleton in modelling. This multiscale modelling framework was applied in explaining the physical mechanisms of cytoskeleton responses to external mechanical loads.

Locally weighted learning methods for non-rigid robot control

This thesis develops a novel approach to robot control that learns to account for a robot's dynamic complexities while executing various control tasks using inspiration from biological sensorimotor control and machine learning. A robot that can learn its own control system can account for complex situations and adapt to changes in control conditions to maximise its performance and reliability in the real world. This research has developed two novel learning methods, with the aim of solving issues with learning control of non-rigid robots that incorporate additional dynamic complexities. The new learning control system was evaluated on a real three degree-of-freedom elastic joint robot arm with a number of experiments: initially validating the learning method and testing its ability to generalise to new tasks, then evaluating the system during a learning control task requiring continuous online model adaptation.

Development and validation of the Self-Gifting Consumer Behaviour scale

Self-gifting consumer behaviour (SGCB) is on the rise as consumers seek reward and therapeutic benefits from their shopping experiences. SGCB is defined as personally symbolic, self-communication through special indulgences, which tend to be premeditated and highly context bound. Prior research into the measurement of this growing behavioural phenomenon has been fragmented because of differences in conceptualisation. This research builds upon the prior literature and through a series of qualitative and quantitative studies, develops a valid, multidimensional measure of SGCB that will be useful for future quantitative inquiry into self-gifting consumption.

The validity of personal disturbance scale (DSSI/sAD) in people with diabetes mellitus, using longitudinal data

Despite being used since 1976, Delusions-Symptoms-States-Inventory/states of Anxiety and Depression (DSSI/sAD) has not yet been validated for use among people with diabetes. The aim of this study was to examine the validity of the personal disturbance scale (DSSI/sAD) among women with diabetes using Mater-University of Queensland Study of Pregnancy (MUSP) cohort data. The DSSI subscales were compared against DSM-IV disorders, the Mental Component Score of the Short Form 36 (SF-36 MCS), and Center for Epidemiologic Studies Depression Scale (CES-D). Factor analyses, odds ratios, receiver operating characteristic (ROC) analyses and diagnostic efficiency tests were used to report findings. Exploratory factor analysis and fit indices confirmed the hypothesized two-factor model of DSSI/sAD. We found significant variations in the DSSI/sAD domain scores that could be explained by CES-D (DSSI-Anxiety: 55%, DSSI-Depression: 46%) and SF-36 MCS (DSSI-Anxiety: 66%, DSSI-Depression: 56%). The DSSI subscales predicted DSM-IV diagnosed depression and anxiety disorders. The ROC analyses show that although the DSSI symptoms and DSM-IV disorders were measured concurrently the estimates of concordance remained only moderate. The findings demonstrate that the DSSI/sAD items have similar relationships to one another in both the diabetes and non-diabetes data sets which therefore suggest that they have similar interpretations.

Histogram matching and global initialization for laser-only SLAM in large unstructured environments

This paper presents an enhanced algorithm for matching laser scan maps using histogram correlations. The histogram representation effectively summarizes a map's salient features such that pairs of maps can be matched efficiently without any prior guess as to their alignment. The histogram matching algorithm has been enhanced in order to work well in outdoor unstructured environments by using entropy metrics, weighted histograms and proper thresholding of quality metrics. Thus our large-scale scan-matching SLAM implementation has a vastly improved ability to close large loops in real-time even when odometry is not available. Our experimental results have demonstrated a successful mapping of the largest area ever mapped to date using only a single laser scanner. We also demonstrate our ability to solve the lost robot problem by localizing a robot to a previously built map without any prior initialization.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

Building cross-scale models of epigenetic mechanisms

Epigenetic changes correspond to heritable modifications of the chromosome structure, which do not involve alteration of the DNA sequence but do affect gene expression. These mechanisms play an important role in normal cell differentiation, but aberration is associated also with several diseases, including cancer and neural disorders. In consequence, despite intensive studies in recent years, the contribution of modifications remains largely unquantified due to overall system complexity and insufficient data. Computational models can provide powerful auxiliary tools to experimentation, not least as scales from the sub-cellular through cell populations (or to networks of genes) can be spanned. In this paper, the challenges to development, of realistic cross-scale models, are discussed and illustrated with respect to current work.

Behaviour of LSF floor systems with improved joist sections under fire conditions

Fire safety design of buildings is essential to safeguard lives and minimize the loss of damage to properties. Light-weight cold-formed steel channel sections along with fire resistive plasterboards are used to construct light gauge steel frame floor systems to provide the required fire resistance rating. However, simply adding more plasterboard layers is not an efficient method to increase FRR. Hence this research focuses on using joists with improved joist section profiles such as hollow flange sections to increase the structural capacity of floor systems under fire conditions and thus their FRR. In this research, the structural and thermal behaviour of LSF floor systems made of LiteSteel Beams with different plasterboard and insulation configurations was investigated using four full scale tests under standard fires. Based on the ultimate failure load of the floor joist at ambient temperature, transient state fire tests were conducted for different Load Ratios. These fire tests showed that the new LSF floor system has improved the FRR well above that of those made of lipped channel sections. The joist failure was predominantly due to local buckling of LSB compression flanges near mid-span with severe yielding of tension flanges. Fire tests have provided valuable structural and thermal performance data of tested floor systems that included time-temperature profiles, and failure times and temperatures. Average failure temperatures of LSB joists and reduced yield strengths were used to predict their ultimate moment capacities, which were compared with corresponding test capacities. This allowed an assessment in relation to the accuracy of current design rules for steel joists at elevated temperatures. This paper presents the details of full scale fire tests of LSF floor systems made of LSB joists with different plasterboard and insulation configurations and their results along with some important findings.