Magnetic carbon xerogels for the catalytic wet peroxide oxidation of sulfamethoxazole in environmentally relevant water matrices

Novel magnetic carbon xerogels consisting of interconnected carbon microspheres with iron and/or cobalt microparticles embedded in their structure were developed by a simple route. As inferred from the characterization data, materials with distinctive properties may be directly obtained upon inclusion of iron and/or cobalt precursors during the sol-gel polymerization of resorcinol and formaldehyde, followed by thermal annealing. The unique properties of these magnetic carbon xerogels were explored in the catalytic wet peroxide oxidation (CWPO) of an antimicrobial agent typically found throughout the urban water cycle – sulfamethoxazole (SMX). A clear synergistic effect arises from the inclusion of cobalt and iron in carbon xerogels (CX/CoFe),the resulting magnetic material revealing a better performance in the CWPO of SMX at the ppb level(500 microg L−1) when compared to that of monometallic carbon xerogels containing only iron or cobalt.This effect was ascribed to the increased accessibility of highly active iron species promoted by the simultaneous incorporation of cobalt.The performance of the CWPO process in the presence of CX/CoFe was also evaluated in environmentally relevant water matrices, namely in drinking water and secondary treated wastewater, considered in addition to ultrapure water. It was found that the performance decreases when applied to more complex water and wastewater samples. Nevertheless, the ability of the CWPO technology for the elimination of SMX in secondary treated wastewater was unequivocally shown, with 96.8% of its initial content being removed after 6 h of reaction in the presence of CX/CoFe, at atmospheric pressure, room temperature(T = 25◦C), pH = 3, [H2O2]0= 500 mg L−1and catalyst load = 80 mg L−1. A similar performance (97.8% SMX removal) is obtained in 30 min when the reaction temperature is slightly increased up to 60◦C in an ultra-pure water matrix. Synthetic water containing humic acid, bicarbonate, sulphate or chloride, was also tested. The results suggest the scavenging effect of the different anions considered, as well as the negative impact of dissolved organic matter typically found in secondary treated wastewater, as simulated by the presence of humic acid.An in-situ magnetic separation procedure was applied for catalyst recovery and re-use during reusability cycles performed to mimic real-scale applications. CWPO runs performed with increased SMX concentration (10 mg L−1), under a water treatment process intensification approach, allowed to evalu-ate the mineralization levels obtained, the antimicrobial activity of the treated water, and to propose adegradation mechanism for the CWPO of SMX.

Implementation and Validation of a Self-Consumption Maximization Energy Management Strategy in a Vanadium Redox Flow BIPV Demonstrator

This paper presents the results of the implementation of a self-consumption maximization strategy tested in a real-scale Vanadium Redox Flow Battery (VRFB) (5 kW, 60 kWh) and Building Integrated Photovoltaics (BIPV) demonstrator (6.74 kWp). The tested energy management strategy aims to maximize the consumption of energy generated by a BIPV system through the usage of a battery. Whenever possible, the residual load is either stored in the battery to be used later or is supplied by the energy stored previously. The strategy was tested over seven days in a real-scale VRF battery to assess the validity of this battery to implement BIPV-focused energy management strategies. The results show that it was possible to obtain a self-consumption ratio of 100.0%, and that 75.6% of the energy consumed was provided by PV power. The VRFB was able to perform the strategy, although it was noticed that the available power (either to charge or discharge) varied with the state of charge.

Numerical modelling and full scale testing of load bearing steel walls under real fires

Fire safety has become an important part in structural design due to the ever increasing loss of properties and lives during fires. Fire rating of load bearing wall systems made of Light gauge Steel Frames (LSF) is determined using fire tests based on the standard time-temperature curve given in ISO 834. However, modern residential buildings make use of thermoplastic materials, which mean considerably high fuel loads. Hence a detailed fire research study into the performance of load bearing LSF walls was undertaken using a series of realistic design fire curves developed based on Eurocode parametric curves and Barnett’s BFD curves. It included both full scale fire tests and numerical studies of LSF walls without any insulation, and the recently developed externally insulated composite panels. This paper presents the details of fire tests first, and then the numerical models of tested LSF wall studs. It shows that suitable finite element models can be developed to predict the fire rating of load bearing walls under real fire conditions. The paper also describes the structural and fire performances of externally insulated LSF walls in comparison to the non-insulated walls under real fires, and highlights the effects of standard and real fire curves on fire performance of LSF walls.

Finite element modelling of load bearing steel stud walls under real building fires

Fire safety has become an important part in structural design due to the ever increasing loss of properties and lives during fires. Conventionally the fire rating of load bearing wall systems made of Light gauge Steel Frames (LSF) is determined using fire tests based on the standard time-temperature curve given in ISO 834 (ISO, 1999). The standard time-temperature curve given in ISO 834 (ISO, 1999) originated from the application of wood burning furnaces in the early 1900s. However, modern commercial and residential buildings make use of thermoplastic materials, which mean considerably high fuel loads. Hence a detailed fire research study into the performance of LSF walls was undertaken using the developed real fire curves based on Eurocode parametric curves (ECS, 2002) and Barnett’s BFD curves (Barnett, 2002) using both full scale fire tests and numerical studies. It included LSF walls without any insulation, and the recently developed externally insulated composite panel system. This paper presents the details of the numerical studies and the results. It also includes brief details of the development of real building fire curves and experimental studies.

Outdoor production of Isochrysis galbana (T-iso) in industrial scale photobioreactors and modelling of its photosynthesis and respiration rate

Isochrysis galbana is a widely-used strain in aquaculture in spite of its low productivity. To maximize the productivity of processes based on this microalgae strain, a model was developed considering the influence of irradiance, temperature, pH and dissolved oxygen concentration on the photosynthesis and respiration rate. Results demonstrate that this strain tolerates temperatures up to 35ºC but it is highly sensitive to irradiances higher than 500 µE·m-2·s-1 and dissolved oxygen concentrations higher than 11 mg·l-1. With the researcher group of the “Universidad de Almeria”, the developed model was validated using data from an industrial-scale outdoor tubular photobioreactor demonstrating that inadequate temperature and dissolved oxygen concentrations reduce productivity to half that which is maximal, according to light availability under real outdoor conditions. The developed model is a useful tool for managing working processes, especially in the development of new processes based on this strain and to take decisions regarding optimal control strategies. Also the outdoor production of Isochrysis galbana T-iso in industrial size tubular photobioreactors (3.0 m3) has been studied. Experiments were performed modifying the dilution rate and evaluating the biomass productivity and quality, in addition to the overall performance of the system. Results confirmed that T-iso can be produced outdoor at commercial scale in continuous mode, productivities up to 20 g·m-2·day-1 of biomass rich in proteins (45%) and lipids (25%) being obtained. The utilization of this type of photobioreactors allows controlling the contamination and pH of the cultures, but daily variation of solar radiation imposes the existence of inadequate dissolved oxygen concentration and temperature at which the cells are exposed to inside the reactor. Excessive dissolved oxygen reduced the biomass productivity to 68% of maximal, whereas inadequate temperature reduces to 63% of maximal. Thus, optimally controlling these parameters the biomass productivity can be duplicated. These results confirm the potential to produce this valuable strain at commercial scale in optimally designed/operated tubular photobioreactors as a biotechnological industry.

Real-time performance modelling of a sustained attention to response task

Vigilance declines when exposed to highly predictable and uneventful tasks. Monotonous tasks provide little cognitive and motor stimulation and contribute to human errors. This paper aims to model and detect vigilance decline in real time through participant’s reaction times during a monotonous task. A lab-based experiment adapting the Sustained Attention to Response Task (SART) is conducted to quantify the effect of monotony on overall performance. Then relevant parameters are used to build a model detecting hypovigilance throughout the experiment. The accuracy of different mathematical models are compared to detect in real-time – minute by minute - the lapses in vigilance during the task. We show that monotonous tasks can lead to an average decline in performance of 45%. Furthermore, vigilance modelling enables to detect vigilance decline through reaction times with an accuracy of 72% and a 29% false alarm rate. Bayesian models are identified as a better model to detect lapses in vigilance as compared to Neural Networks and Generalised Linear Mixed Models. This modelling could be used as a framework to detect vigilance decline of any human performing monotonous tasks.

Markov modelling of the IEEE 802.11 DCF for real-time applications with periodic traffic

Popular wireless network standards, such as IEEE 802.11/15/16, are increasingly adopted in real-time control systems. However, they are not designed for real-time applications. Therefore, the performance of such wireless networks needs to be carefully evaluated before the systems are implemented and deployed. While efforts have been made to model general wireless networks with completely random traffic generation, there is a lack of theoretical investigations into the modelling of wireless networks with periodic real-time traffic. Considering the widely used IEEE 802.11 standard, with the focus on its distributed coordination function (DCF), for soft-real-time control applications, this paper develops an analytical Markov model to quantitatively evaluate the network quality-of-service (QoS) performance in periodic real-time traffic environments. Performance indices to be evaluated include throughput capacity, transmission delay and packet loss ratio, which are crucial for real-time QoS guarantee in real-time control applications. They are derived under the critical real-time traffic condition, which is formally defined in this paper to characterize the marginal satisfaction of real-time performance constraints.

Visualisation modelling in 3D of an alluvial aquifer system at a valley-wide scale to understand groundwater status : Lockyer, QLD

Visualisation provides a method to efficiently convey and understand the complex nature and processes of groundwater systems. This technique has been applied to the Lockyer Valley to aid in comprehending the current condition of the system. The Lockyer Valley in southeast Queensland hosts intensive irrigated agriculture sourcing groundwater from alluvial aquifers. The valley is around 3000 km2 in area and the alluvial deposits are typically 1-3 km wide and to 20-35 m deep in the main channels, reducing in size in subcatchments. The configuration of the alluvium is of a series of elongate “fingers”. In this roughly circular valley recharge to the alluvial aquifers is largely from seasonal storm events, on the surrounding ranges. The ranges are overlain by basaltic aquifers of Tertiary age, which overall are quite transmissive. Both runoff from these ranges and infiltration into the basalts provided ephemeral flow to the streams of the valley. Throughout the valley there are over 5,000 bores extracting alluvial groundwater, plus lesser numbers extracting from underlying sandstone bedrock. Although there are approximately 2500 monitoring bores, the only regularly monitored area is the formally declared management zone in the lower one third. This zone has a calibrated Modflow model (Durick and Bleakly, 2000); a broader valley Modflow model was developed in 2002 (KBR), but did not have extensive extraction data for detailed calibration. Another Modflow model focused on a central area river confluence (Wilson, 2005) with some local production data and pumping test results. A recent subcatchment simulation model incorporates a network of bores with short-period automated hydrographic measurements (Dvoracek and Cox, 2008). The above simulation models were all based on conceptual hydrogeological models of differing scale and detail.

Modelling and performance evaluation of the IEEE 802.11 DCF for real-time control

Popular wireless networks, such as IEEE 802.11/15/16, are not designed for real-time applications. Thus, supporting real-time quality of service (QoS) in wireless real-time control is challenging. This paper adopts the widely used IEEE 802.11, with the focus on its distributed coordination function (DCF), for soft-real-time control systems. The concept of the critical real-time traffic condition is introduced to characterize the marginal satisfaction of real-time requirements. Then, mathematical models are developed to describe the dynamics of DCF based real-time control networks with periodic traffic, a unique feature of control systems. Performance indices such as throughput and packet delay are evaluated using the developed models, particularly under the critical real-time traffic condition. Finally, the proposed modelling is applied to traffic rate control for cross-layer networked control system design.

Bayesian mixtures for modelling complex medical data : a case study in Parkinson’s disease

Mixture models are a flexible tool for unsupervised clustering that have found popularity in a vast array of research areas. In studies of medicine, the use of mixtures holds the potential to greatly enhance our understanding of patient responses through the identification of clinically meaningful clusters that, given the complexity of many data sources, may otherwise by intangible. Furthermore, when developed in the Bayesian framework, mixture models provide a natural means for capturing and propagating uncertainty in different aspects of a clustering solution, arguably resulting in richer analyses of the population under study. This thesis aims to investigate the use of Bayesian mixture models in analysing varied and detailed sources of patient information collected in the study of complex disease. The first aim of this thesis is to showcase the flexibility of mixture models in modelling markedly different types of data. In particular, we examine three common variants on the mixture model, namely, finite mixtures, Dirichlet Process mixtures and hidden Markov models. Beyond the development and application of these models to different sources of data, this thesis also focuses on modelling different aspects relating to uncertainty in clustering. Examples of clustering uncertainty considered are uncertainty in a patient’s true cluster membership and accounting for uncertainty in the true number of clusters present. Finally, this thesis aims to address and propose solutions to the task of comparing clustering solutions, whether this be comparing patients or observations assigned to different subgroups or comparing clustering solutions over multiple datasets. To address these aims, we consider a case study in Parkinson’s disease (PD), a complex and commonly diagnosed neurodegenerative disorder. In particular, two commonly collected sources of patient information are considered. The first source of data are on symptoms associated with PD, recorded using the Unified Parkinson’s Disease Rating Scale (UPDRS) and constitutes the first half of this thesis. The second half of this thesis is dedicated to the analysis of microelectrode recordings collected during Deep Brain Stimulation (DBS), a popular palliative treatment for advanced PD. Analysis of this second source of data centers on the problems of unsupervised detection and sorting of action potentials or "spikes" in recordings of multiple cell activity, providing valuable information on real time neural activity in the brain.

Numerical modelling of non-load bearing light gauge cold-formed steel frame walls under fire conditions

Recently an innovative composite panel system was developed, where a thin insulation layer was used externally between two plasterboards to improve the fire performance of light gauge cold-formed steel frame walls. In this research, finite-element thermal models of both the traditional light gauge cold-formed steel frame wall panels with cavity insulation and the new light gauge cold-formed steel frame composite wall panels were developed to simulate their thermal behaviour under standard and realistic fire conditions. Suitable apparent thermal properties of gypsum plasterboard, insulation materials and steel were proposed and used. The developed models were then validated by comparing their results with available fire test results. This article presents the details of the developed finite-element models of small-scale non-load-bearing light gauge cold-formed steel frame wall panels and the results of the thermal analysis. It has been shown that accurate finite-element models can be used to simulate the thermal behaviour of small-scale light gauge cold-formed steel frame walls with varying configurations of insulations and plasterboards. The numerical results show that the use of cavity insulation was detrimental to the fire rating of light gauge cold-formed steel frame walls, while the use of external insulation offered superior thermal protection to them. The effects of real fire conditions are also presented.

Cell migration and proliferation on homogeneous and non-homogeneous domains : modelling on the scale of individuals and populations

Cell migration is a behaviour critical to many key biological effects, including wound healing, cancerous cell invasion and morphogenesis, the development of an organism from an embryo. However, given that each of these situations is distinctly different and cells are extremely complicated biological objects, interest lies in more basic experiments which seek to remove conflating factors and present a less complex environment within which cell migration can be experimentally examined. These include in vitro studies like the scratch assay or circle migration assay, and ex vivo studies like the colonisation of the hindgut by neural crest cells. The reduced complexity of these experiments also makes them much more enticing as problems to mathematically model, like done here. The primary goal of the mathematical models used in this thesis is to shed light on which cellular behaviours work to generate the travelling waves of invasion observed in these experiments, and to explore how variations in these behaviours can potentially predict differences in this invasive pattern which are experimentally observed when cell types or chemical environment are changed. Relevant literature has already identified the difficulty of distinguishing between these behaviours when using traditional mathematical biology techniques operating on a macroscopic scale, and so here a sophisticated individual-cell-level model, an extension of the Cellular Potts Model (CPM), is been constructed and used to model a scratch assay experiment. This model includes a novel mechanism for dealing with cell proliferations that allowed for the differing properties of quiescent and proliferative cells to be implemented into their behaviour. This model is considered both for its predictive power and used to make comparisons with the travelling waves which result in more traditional macroscopic simulations. These comparisons demonstrate a surprising amount of agreement between the two modelling frameworks, and suggest further novel modifications to the CPM that would allow it to better model cell migration. Considerations of the model’s behaviour are used to argue that the dominant effect governing cell migration (random motility or signal-driven taxis) likely depends on the sort of invasion demonstrated by cells, as easily seen by microscopic photography. Additionally, a scratch assay simulated on a non-homogeneous domain consisting of a ’fast’ and ’slow’ region is also used to further differentiate between these different potential cell motility behaviours. A heterogeneous domain is a novel situation which has not been considered mathematically in this context, nor has it been constructed experimentally to the best of the candidate’s knowledge. Thus this problem serves as a thought experiment used to test the conclusions arising from the simulations on homogeneous domains, and to suggest what might be observed should this non-homogeneous assay situation be experimentally realised. Non-intuitive cell invasion patterns are predicted for diffusely-invading cells which respond to a cell-consumed signal or nutrient, contrasted with rather expected behaviour in the case of random-motility-driven invasion. The potential experimental observation of these behaviours is demonstrated by the individual-cell-level model used in this thesis, which does agree with the PDE model in predicting these unexpected invasion patterns. In the interest of examining such a case of a non-homogeneous domain experimentally, some brief suggestion is made as to how this could be achieved.

Local stress-strain distribution and load transfer across cartilage matrix at micro-scale using combined microscopy-based finite element method

Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.