Structure and palaeoenvironmental implications of inter-branch coenosteum-rich skeleton in corymbose Acropora species

Coral reefs provide an increasingly important archive of palaeoclimate data that can be used to constrain climate model simulations. Reconstructing past environmental conditions may also provide insights into the potential of reef systems to survive changes in the Earth’s climate. Reef-based palaeoclimate reconstructions are predominately derived from colonies of massive Porites, with the most abundant genus in the Indo-Pacific—Acropora—receiving little attention owing to their branching growth trajectories, high extension rates and secondary skeletal thickening. However, inter-branch skeleton (consisting of both coenosteum and corallites) near the bases of corymbose Acropora colonies holds significant potential as a climate archive. This region of Acropora skeleton is atypical, having simple growth trajectories with parallel corallites, approximately horizontal density banding, low apparent extension rates and a simple microstructure with limited secondary thickening. Hence, inter-branch skeleton in Acropora bears more similarities to the coralla of massive corals, such as Porites, than to traditional Acropora branches. Cyclic patterns of Sr/Ca ratios in this structure suggest that the observed density banding is annual in nature, thus opening up the potential to use abundant corymbose Acropora for palaeoclimate reconstruction.

Utilizing reactive capability of PV inverters and battery systems to improve voltage profile of a residential distribution feeder

Significant increase in installation of rooftop Photovoltaic (PV) in the Low-Voltage (LV) residential distribution network has resulted in over voltage problems. Moreover, increasing peak demand creates voltage dip problems and make voltage profile even worse. Utilizing the reactive power capability of PV inverter (RCPVI) can improve the voltage profile to some extent. Resistive caharcteristic (higher R/X ratio) limits the effectiveness of reactive power to provide voltage support in distribution network. Battery Energy Storage (BES), whereas, can store the excess PV generation during high solar insolation time and supply the stored energy back to the grid during peak demand. A coordinated algorithm is developed in this paper to use the reactive capability of PV inverter and BES with droop control. Proposed algorithm is capable to cater the severe voltage violation problem using RCPVI and BES. A signal flow is also mentioned in this research work to ensure smooth communication between all the equipments. Finally the developed algorithm is validated in a test distribution network.

Item reputation-aware recommender systems

Recommender systems provide personalized advice for customers online based on their own preferences, while reputation systems generate a community advice on the quality of items on the Web. Both systems use users’ ratings to generate their output. In this paper, we propose to combine reputation models with recommender systems to enhance the accuracy of recommendations. The main contributions include two methods for merging two ranked item lists which are generated based on recommendation scores and reputation scores, respectively, and a personalized reputation method to generate item reputations based on users’ interests. The proposed merging methods can be applicable to any recommendation methods and reputation methods, i.e., they are independent from generating recommendation scores and reputation scores. The experiments we conducted showed that the proposed methods could enhance the accuracy of existing recommender systems.

Memory management and parallelization of data intensive all-to-all comparison in shared-memory systems

This thesis presents a novel program parallelization technique incorporating with dynamic and static scheduling. It utilizes a problem specific pattern developed from the prior knowledge of the targeted problem abstraction. Suitable for solving complex parallelization problems such as data intensive all-to-all comparison constrained by memory, the technique delivers more robust and faster task scheduling compared to the state-of-the art techniques. Good performance is achieved from the technique in data intensive bioinformatics applications.

Canards in advection-reaction-diffusion systems in one spatial dimension

This thesis contains a mathematical investigation of the existence of travelling wave solutions to singularly perturbed advection-reaction-diffusion models of biological processes. An enhanced mathematical understanding of these solutions and models is gained via the identification of canards (special solutions of fast/slow dynamical systems) and their role in the existence of the most biologically relevant, shock-like solutions. The analysis focuses on two existing models. A new proof of existence of a whole family of travelling waves is provided for a model describing malignant tumour invasion, while new solutions are identified for a model describing wound healing angiogenesis.

Increasing leucine concentration stimulates mechanistic target of rapamycin signaling and cell growth in C2C12 skeletal muscle cells

Leucine is a key amino acid for initiating translation in muscle cells, but the dose-dependent effects of leucine on intracellular signaling are poorly characterized. This study examined the effect that increasing doses of leucine would have on changes in mechanistic target of rapamycin (mTOR)–mediated signaling, rates of protein synthesis, and cell size in C2C12 cells. We hypothesized that a leucine “threshold” exists, which represents the minimum stimulus required to initiate mTOR signaling in muscle cells. Acute exposure to 1.5, 3.2, 5.0, and 16.1 mM leucine increased phosphorylation of mTORSer2448 (~1.4-fold; P < .04), 4E-BP1 Thr37/46 (~1.9-fold; P < .001), and rpS6Ser235/6 (~2.3-fold; P < .001). However, only p70S6kThr389 exhibited a dose-dependent response to leucine with all treatments higher than control (~4-fold; P < .001) and at least 5 mM higher than the 1.5-mM concentration (1.2-fold; P < .02). Rates of protein synthesis were not altered by any treatment. Seven days of exposure to 0.5, 1.5, 5.0, and 16.5 mM leucine resulted in an increase in cell size in at least 5 mM treatments (~1.6-fold, P < .001 vs control). Our findings indicate that even at low leucine concentrations, phosphorylation of proteins regulating translation initiation signaling is enhanced. The phosphorylation of p70S6kThr389 follows a leucine dose-response relationship, although this was not reflected by the acute protein synthetic response. Nevertheless, under the conditions of the present study, it appears that leucine concentrations of at least 5 mM are necessary to enhance cell growth.

Rethinking the value of simulation methods in the information systems research field : a call for reconstructing contribution for a broader audience

The impact of simulation methods for social research in the Information Systems (IS) research field remains low. A concern is our field is inadequately leveraging the unique strengths of simulation methods. Although this low impact is frequently attributed to methodological complexity, we offer an alternative explanation – the poor construction of research value. We argue a more intuitive value construction, better connected to the knowledge base, will facilitate increased value and broader appreciation. Meta-analysis of studies published in IS journals over the last decade evidences the low impact. To facilitate value construction, we synthesize four common types of simulation research contribution: Analyzer, Tester, Descriptor, and Theorizer. To illustrate, we employ the proposed typology to describe how each type of value is structured in simulation research and connect each type to instances from IS literature, thereby making these value types and their construction visible and readily accessible to the general IS community.

Assessing agronomic and environmental implications of different N fertilisation strategies in subtropical grain cropping systems on Oxisols

A multi-season 15N tracer recovery experiment was conducted on an Oxisol cropped with wheat, maize and sorghum to compare crop N recoveries of different fertilisation strategies and determine the main pathways of N losses that limit N recovery in these agroecosystems. In the wheat and maize seasons, 15N-labelled fertiliser was applied as conventional urea (CONV) and urea coated with a nitrification inhibitor (DMPP). In sorghum, the fate of 15N-labelled urea was monitored in this crop following a legume ley pasture (L70) or a grass ley pasture (G100). The fertiliser N applied to sorghum in the legume-cereal rotation was reduced (70 kg N ha−1) compared to the grass-cereal (100 kg N ha−1) to assess the availability of the N residual from the legume ley pasture. Average crop N recoveries were 73 % (CONV) and 77 % (DMPP) in wheat and 50 % (CONV) and 51 % (DMPP) in maize, while in sorghum were 71 % (L70) and 53 % (G100). Data gathered in this study indicate that the intrinsic physical and chemical conditions of Oxisols can be extremely effective in limiting N losses via deep leaching or denitrification. Elevated crop 15N recoveries can be therefore obtained in subtropical Oxisols using conventional urea while in these agroecosystems DMPP urea has no significant scope to increase fertiliser N recovery in the crop. Overall, introducing a legume phase to limit the fertiliser N requirements of the following cereal crop proved to be the most effective strategy to reduce N losses and increase fertiliser N recovery.

Multi-agent systems for modeling high penetration photovoltaic system impacts in distribution networks

This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

Ibuprofen supplementation and its effects on NF-KB activation in skeletal muscle following resistance exercise

Resistance exercise triggers a subclinical inflammatory response that plays a pivotal role in skeletal muscle regeneration. Nuclear factor‐κB (NF‐κB) is a stress signalling transcription factor that regulates acute and chronic states of inflammation. The classical NF‐κB pathway regulates the early activation of post‐exercise inflammation; however there remains scope for this complex transcription factor to play a more detailed role in post‐exercise muscle recovery. Sixteen volunteers completed a bout of lower body resistance exercise with the ingestion of three 400 mg doses of ibuprofen or a placebo control. Muscle biopsy samples were obtained prior to exercise and at 0, 3 and 24 h post‐exercise and analysed for key markers of NF‐κB activity. Phosphorylated p65 protein expression and p65 inflammatory target genes were elevated immediately post‐exercise independent of the two treatments. These changes did not translate to an increase in p65 DNA binding activity. NF‐κB p50 protein expression and NF‐κB p50 binding activity were lower than pre‐exercise at 0 and 3 h post‐exercise, but were elevated at 24 h post‐exercise. These findings provide novel evidence that two distinct NF‐κB pathways are active in skeletal muscle after resistance exercise. The initial wave of activity involving p65 resembles the classical pathway and is associated with the onset of an acute inflammatory response. The second wave of NF‐κB activity comprises the p50 subunit, which has been previously shown to resolve an acute inflammatory program. The current study showed no effect of the ibuprofen treatment on markers of the NF‐κB pathway, however examination of the within group effects of the exercise protocol suggests that this pathway warrants further research.

Altering the redox state of skeletal muscle by glutathione depletion increases the exercise-activation of PGC-1α

We investigated the relationship between mitochondrial biogenesis, cell signalling and antioxidant enzymes by depleting skeletal muscle glutathione with diethyl maleate (DEM) which resulted in a demonstrable increase in oxidative stress during exercise. Animals were divided into six groups: (1) sedentary control rats; (2) sedentary rats treated with DEM; (3) exercise control rats euthanized immediately after exercise; (4) exercise rats + DEM; (5) exercise control rats euthanized 4 h after exercise, and; (6) exercise rats + DEM euthanized 4 h after exercise. Exercising animals ran on the treadmill at a 10% gradient at 20 m/min for the first 30 min. The speed was then increased every 10 min by 1.6 m/min until exhaustion. There was a reduction in total glutathione in the skeletal muscle of DEM treated animals compared to the control animals (P<0.05). Within the control group, total glutathione was higher in the sedentary group compared to after exercise (P<0.05). DEM treatment also significantly increased oxidative stress, as measured by increased plasma F2-isoprostanes (P<0.05). Exercising animals given DEM showed a significantly greater increase in peroxisome proliferator activated receptor γ coactivator-1α(PGC-1α) mRNA compared to the control animals that were exercised (P<0.05). This study provides novel evidence that by reducing the endogenous antioxidant glutathione in skeletal muscle and inducing oxidative stress through exercise, PGC-1α gene expression was augmented. These findings further highlight the important role of exercise induced oxidative stress in the regulation of mitochondrial biogenesis.

A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics

Partial shading and rapidly changing irradiance conditions significantly impact on the performance of photovoltaic (PV) systems. These impacts are particularly severe in tropical regions where the climatic conditions result in very large and rapid changes in irradiance. In this paper, a hybrid maximum power point (MPP) tracking (MPPT) technique for PV systems operating under partially shaded conditions witapid irradiance change is proposed. It combines a conventional MPPT and an artificial neural network (ANN)-based MPPT. A low cost method is proposed to predict the global MPP region when expensive irradiance sensors are not available or are not justifiable for cost reasons. It samples the operating point on the stairs of I–V curve and uses a combination of the measured current value at each stair to predict the global MPP region. The conventional MPPT is then used to search within the classified region to get the global MPP. The effectiveness of the proposed MPPT is demonstrated using both simulations and an experimental setup. Experimental comparisons with four existing MPPTs are performed. The results show that the proposed MPPT produces more energy than the other techniques and can effectively track the global MPP with a fast tracking speed under various shading patterns.

Caribbean schooling and the social divide – what will it take to change neo-colonial education systems?

When Professor N’Dri Assie-Lumumba asked me to reflect on what ‘ubuntu’ might mean in the context of education in the Caribbean, the first thing that came to mind was an image of pit latrines in impoverished primary schools in poor countries. In this essay, I argue that the continuing problem of pit latrines in these schools symbolizes the failure to solve the problem of poverty, neglect and inadequate provision of education services for people at the bottom rungs of Caribbean and other decolonising societies. I ask what implications the ‘ubuntu’ concept chosen for the 2015 CIES conference would have for reforming education in a direction that combines global reform, ethics and good sense. Educators rarely consider toilets when they are thinking about what is needed to reform the system. But talking about toilets draws attention to the entrenched inequity that persists in education systems across the globe – an inequity that forces many schools and young people to remain at the base of the social pyramid, and that perpetuates a dysfunctional model of education holding back many societies. Starting from the twin images of social pyramids and toilets, we can ask some pointed questions about education reform.

Incorporation of road safety into road management systems

Road collisions negatively affect the lives of hundreds of Canadians per year. Unfortunately, safety has been typically neglected from management systems. It is common to find that a great deal of effort has been devoted to develop and implement systems capable of achieving and sustaining good levels of condition. It is relatively recent that road safety has become an important objective. Managing a network of roads is not an easy task; it requires long, medium and short term plans to maintain, rehabilitate and upgrade aging assets, reduce and mitigate accident exposure, likelihood and severity. This thesis presents a basis for incorporating road safety into road management systems; two case studies were developed; one limited by available data and another from sufficient information. A long term analysis was used to allocate improvements for condition and safety of roads and bridges, at the network level. It was confirmed that a safety index could be used to obtain a first cut model; meanwhile potential for improvement which is a difference between observed and predicted number of accidents was capable of capturing the degree of safety of individual segments. It was found that the completeness of the system resulted in savings because of the economies obtained from trade-off optimization. It was observed that safety improvements were allocated at the beginning of the analysis in order to reduce the extent of issues, which translated into a systematic reduction of potential for improvement up to a point of near constant levels, which were hypothesized to relate to those unavoidable collisions from human error or vehicle failure.

Design, construction and evaluation of systems to predict risk in obstetrics

We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy. We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.