Intrinsic kinetics of titania photocatalysis : simplified models for their investigation

Even though titanium dioxide photocatalysis has been promoted as a leading green technology for water purification, many issues have hindered its application on a large commercial scale. For the materials scientist the main issues have centred the synthesis of more efficient materials and the investigation of degradation mechanisms; whereas for the engineers the main issues have been the development of appropriate models and the evaluation of intrinsic kinetics parameters that allow the scale up or re-design of efficient large-scale photocatalytic reactors. In order to obtain intrinsic kinetics parameters the reaction must be analysed and modelled considering the influence of the radiation field, pollutant concentrations and fluid dynamics. In this way, the obtained kinetic parameters are independent of the reactor size and configuration and can be subsequently used for scale-up purposes or for the development of entirely new reactor designs. This work investigates the intrinsic kinetics of phenol degradation over titania film due to the practicality of a fixed film configuration over a slurry. A flat plate reactor was designed in order to be able to control reaction parameters that include the UV irradiance, flow rates, pollutant concentration and temperature. Particular attention was paid to the investigation of the radiation field over the reactive surface and to the issue of mass transfer limited reactions. The ability of different emission models to describe the radiation field was investigated and compared to actinometric measurements. The RAD-LSI model was found to give the best predictions over the conditions tested. Mass transfer issues often limit fixed film reactors. The influence of this phenomenon was investigated with specifically planned sets of benzoic acid experiments and with the adoption of the stagnant film model. The phenol mass transfer coefficient in the system was calculated to be km,phenol=8.5815x10-7Re0.65(ms-1). The data obtained from a wide range of experimental conditions, together with an appropriate model of the system, has enabled determination of intrinsic kinetic parameters. The experiments were performed in four different irradiation levels (70.7, 57.9, 37.1 and 20.4 W m-2) and combined with three different initial phenol concentrations (20, 40 and 80 ppm) to give a wide range of final pollutant conversions (from 22% to 85%). The simple model adopted was able to fit the wide range of conditions with only four kinetic parameters; two reaction rate constants (one for phenol and one for the family of intermediates) and their corresponding adsorption constants. The intrinsic kinetic parameters values were defined as kph = 0.5226 mmol m-1 s-1 W-1, kI = 0.120 mmol m-1 s-1 W-1, Kph = 8.5 x 10-4 m3 mmol-1 and KI = 2.2 x 10-3 m3 mmol-1. The flat plate reactor allowed the investigation of the reaction under two different light configurations; liquid and substrate side illumination. The latter of particular interest for real world applications where light absorption due to turbidity and pollutants contained in the water stream to be treated could represent a significant issue. The two light configurations allowed the investigation of the effects of film thickness and the determination of the catalyst optimal thickness. The experimental investigation confirmed the predictions of a porous medium model developed to investigate the influence of diffusion, advection and photocatalytic phenomena inside the porous titania film, with the optimal thickness value individuated at 5 ìm. The model used the intrinsic kinetic parameters obtained from the flat plate reactor to predict the influence of thickness and transport phenomena on the final observed phenol conversion without using any correction factor; the excellent match between predictions and experimental results provided further proof of the quality of the parameters obtained with the proposed method.

An improved model of tumour-immune system interactions

The immune system plays an important role in defending the body against tumours and other threats. Currently, mechanisms involved in immune system interactions with tumour cells are not fully understood. Here we develop a mathematical tool that can be used in aiding to address this shortfall in understanding. This paper de- scribes a hybrid cellular automata model of the interaction between a growing tumour and cells of the innate and specific immune system including the effects of chemokines that builds on previous models of tumour-immune system interactions. In particular, the model is focused on the response of immune cells to tumour cells and how the dynamics of the tumour cells change due to the immune system of the host. We present results and predictions of in silico experiments including simulations of Kaplan-Meier survival-like curves.

Surface plasmon hybridization and exciton coupling

We derive a semianalytical model to describe the interaction of a single photon emitter and a collection of arbitrarily shaped metal nanoparticles. The theory treats the metal nanoparticles classically within the electrostatic eigenmode method, wherein the surface plasmon resonances of collections of nanoparticles are represented by the hybridization of the plasmon modes of the noninteracting particles. The single photon emitter is represented by a quantum mechanical two-level system that exhibits line broadening due to a finite spontaneous decay rate. Plasmon-emitter coupling is described by solving the resulting Bloch equations. We illustrate the theory by studying model systems consisting of a single emitter coupled to one, two, and three nanoparticles, and we also compare the predictions of our model to published experimental data. ©2012 American Physical Society.

The developmental consequences of rare chromosome disorders : two case reports

Aim: As molecular and cytogenetic testing becomes increasingly sophisticated, more individuals are being diagnosed with rare chromosome disorders. Yet despite a burgeoning knowledge about biomedical aspects, little is known about implications for psychosocial development. The scant literature gives a general impression of deficits and adverse developmental outcomes. Method: Developmental data were obtained from two 16 year olds diagnosed with a rare chromosome disorder – a girl with 8p23.1 and a boy with 16q11.2q12.1. Measures of intellectual ability, academic achievement, and other aspects of functioning were administered at multiple time points from early childhood to adolescence. Results: Both adolescents experienced initial delays in motor and language development. Although the girl’s intelligence is assessed as being in the average range, she experiences difficulties with motor planning, spelling and writing. The boy has been diagnosed with a mild intellectual disability and demonstrates mild autistic features. Conclusions: The two case descriptions are in marked contrast to the published literature about these two chromosome anomalies. Both adolescents are developing much more positively than would be expected on the basis of the grim predictions of their paediatricians and the negative reports in the literature. It is concluded that, for most rare chromosome disorders, the range of possible developmental outcomes is currently unknown.

A molecular phylogeny for the Tribe Dacini (Diptera: Tephritidae) : systematic and biogeographic implications

With well over 700 species, the Tribe Dacini is one of the most species-rich clades within the dipteran family Tephritidae, the true fruit flies. Nearly all Dacini belong to one of two very large genera, Dacus Fabricius and Bactrocera Macquart. The distribution of the genera overlap in or around the Indian subcontinent, but the greatest diversity of Dacus is in Africa and the greatest diversity of Bactrocera is in south-east Asia and the Pacific. The monophyly of these two genera has not been rigorously established, with previous phylogenies only including a small number of species and always heavily biased to one genus over the other. Moreover, the subgeneric taxonomy within both genera is complex and the monophyly of many subgenera has not been explicitly tested. Previous hypotheses about the biogeography of the Dacini based on morphological reviews and current distributions of taxa have invoked an out-of-India hypothesis; however this has not been tested in a phylogenetic framework. We attempted to resolve these issues with a dated, molecular phylogeny of 125 Dacini species generated using 16S, COI, COII and white eye genes. The phylogeny shows that Bactrocera is not monophyletic, but rather consists of two major clades: Bactrocera s.s. and the ‘Zeugodacus group of subgenera’ (a recognised, but informal taxonomic grouping of 15 Bactrocera subgenera). This ‘Zeugodacus’ clade is the sister group to Dacus, not Bactrocera and, based on current distributions, split from Dacus before that genus moved into Africa. We recommend that taxonomic consideration be given to raising Zeugodacus to genus level. Supportive of predictions following from the out-of-India hypothesis, the first common ancestor of the Dacini arose in the mid-Cretaceous approximately 80 mya. Major divergence events occurred during the Indian rafting period and diversification of Bactrocera apparently did not begin until after India docked with Eurasia (50–35 mya). In contrast, diversification in Dacus, at approximately 65 mya, apparently began much earlier than predicted by the out-of-India hypothesis, suggesting that, if the Dacini arose on the Indian plate, then ancestral Dacus may have left the plate in the mid to late Cretaceous via the well documented India–Madagascar–Africa migration route. We conclude that the phylogeny does not disprove the predictions of an out-of-India hypothesis for the Dacini, although modification of the original hypothesis is required.

A computer model to simulate scoliosis surgery

Use of patient-specific computer models as a pre-operative planning tool permits predictions of the likely deformity correction and allows a more detailed investigation of the biomechanical influence of different surgical procedures on the scoliotic spinal anatomy. In this paper, patient-specific computer models are used of adolescent idiopathic scoliosis patients who underwent a single rod anterior procedure at the Mater Children’s Hospital in Brisbane, to predict deformity correction and to investigate the change in biomechanics of the scoliotic spine due to surgical compressive forces applied during implant placement.

Insights into historical drainage evolution based on the phylogeography of the chevron snakehead fish (Channa striata) in the Mekong Basin

1. The phylogeography of freshwater taxa is often integrally linked with landscape changes such as drainage re-alignments that may present the only avenue for historical dispersal for these taxa. Classical models of gene flow do not account for landscape changes and so are of little use in predicting phylogeography in geologically young freshwater landscapes. When the history of drainage formation is unknown, phylogeographical predictions can be based on current freshwater landscape structure, proposed historical drainage geomorphology, or from phylogeographical patterns of co-distributed taxa. 2. This study describes the population structure of a sedentary freshwater fish, the chevron snakehead (Channa striata), across two river drainages on the Indochinese Peninsula. The phylogeographical pattern recovered for C. striata was tested against seven hypotheses based on contemporary landscape structure, proposed history and phylogeographical patterns of codistributed taxa. 3. Consistent with the species ecology, analysis of mitochondrial and microsatellite loci revealed very high differentiation among all sampled sites. A strong signature of historical population subdivision was also revealed within the contemporary Mekong River Basin (MRB). Of the seven phylogeographical hypotheses tested, patterns of co-distributed taxa proved to be the most adequate for describing the phylogeography of C. striata. 4. Results shed new light on SE Asian drainage evolution, indicating that the Middle MRB probably evolved via amalgamation of at least three historically independent drainage sections and in particular that the Mekong River section centred around the northern Khorat Plateau in NE Thailand was probably isolated from the greater Mekong for an extensive period of evolutionary time. In contrast, C. striata populations in the Lower MRB do not show a phylogeographical signature of evolution in historically isolated drainage lines, suggesting drainage amalgamation has been less important for river landscape formation in this region.

Eliciting Expert Knowledge in Conservation Science

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.

An investigation on the accuracy of regional ocean models through field trials

Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Although these models provide information at a unprecedented resolutions and have proven to increase accuracy and effectiveness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles. For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current velocity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.

Maintaining a cognitive map in darkness : the need to fuse boundary knowledge with path integration

Spatial navigation requires the processing of complex, disparate and often ambiguous sensory data. The neurocomputations underpinning this vital ability remain poorly understood. Controversy remains as to whether multimodal sensory information must be combined into a unified representation, consistent with Tolman's "cognitive map", or whether differential activation of independent navigation modules suffice to explain observed navigation behaviour. Here we demonstrate that key neural correlates of spatial navigation in darkness cannot be explained if the path integration system acted independently of boundary (landmark) information. In vivo recordings demonstrate that the rodent head direction (HD) system becomes unstable within three minutes without vision. In contrast, rodents maintain stable place fields and grid fields for over half an hour without vision. Using a simple HD error model, we show analytically that idiothetic path integration (iPI) alone cannot be used to maintain any stable place representation beyond two to three minutes. We then use a measure of place stability based on information theoretic principles to prove that featureless boundaries alone cannot be used to improve localization above chance level. Having shown that neither iPI nor boundaries alone are sufficient, we then address the question of whether their combination is sufficient and - we conjecture - necessary to maintain place stability for prolonged periods without vision. We addressed this question in simulations and robot experiments using a navigation model comprising of a particle filter and boundary map. The model replicates published experimental results on place field and grid field stability without vision, and makes testable predictions including place field splitting and grid field rescaling if the true arena geometry differs from the acquired boundary map. We discuss our findings in light of current theories of animal navigation and neuronal computation, and elaborate on their implications and significance for the design, analysis and interpretation of experiments.

Beat phenomena in metal nanowires, and their implications for resonance-based elastic property measurements

The elastic properties of 1D nanostructures such as nanowires are often measured experimentally through actuation of the nanowire at its resonance frequency, and then relating the resonance frequency to the elastic stiffness using elementary beam theory. In the present work, we utilize large scale molecular dynamics simulations to report a novel beat phenomenon in [110]oriented Ag nanowires. The beat phenomenon is found to arise from the asymmetry of the lattice spacing in the orthogonal elementary directions of the [110] nanowire, i.e. the [-110] and [001] directions, which results in two different principal moments of inertia. Because of this, actuations imposed along any other direction are found to decompose into two orthogonal vibrational components based on the actuation angle relative to these two elementary directions, with this phenomenon being generalizable to <110> FCC nanowires of different materials (Cu, Au, Ni, Pd and Pt). The beat phenomenon is explained using a discrete moment of inertia model based on the hard sphere assumption, the model is utilized to show that surface effects enhance the beat phenomenon, while the effect is reduced with increasing nanowires cross-sectional size or aspect ratio. Most importantly, due to the existence of the beat phenomena, we demonstrate that in resonance experiments only a single frequency component is expected to be observed, particularly when the damping ratio is relatively large or very small. Furthermore, for a large range of actuation angles, the lower frequency is more likely to be detected than the higher one, which implies that experimental predictions of Young’s modulus obtained from resonance may in fact be under predictions. The present study therefore has significant implications for experimental interpretations of Young’s modulus as obtained via resonance testing.

Surface effects on the dual-mode vibration of <110> silver nanowires with different cross-sections

Dual-mode vibration of nanowires has been reported experimentally through actuation of the nanowire at its resonance frequency, which is expected to open up a variety of new modalities for the NEMS that could operate in the nonlinear regime. In the present work, we utilize large scale molecular dynamics simulations to investigate the dual-mode vibration of <110> Ag nanowires with triangular, rhombic and truncated rhombic cross-sections. By incorporating the generalized Young-Laplace equation into Euler-Bernoulli beam theory, the influence of surface effects on the dual-mode vibration is studied. Due to the different lattice spacing in principal axes of inertia of the {110} atomic layers, the NW is also modeled as a discrete system to reveal the influence from such specific atomic arrangement. It is found that the <110> Ag NW will under a dual-mode vibration if the actuation direction is deviated from the two principal axes of inertia. The predictions of the two first mode natural frequencies by the classical beam model appear underestimated comparing with the MD results, which are found to be enhanced by the discrete model. Particularly, the predictions by the beam theory with the contribution of surface effects are uniformly larger than the classical beam model, which exhibit better agreement with MD results for larger cross-sectional size. However, for ultrathin NWs, current consideration of surface effects is still experiencing certain inaccuracy. In all, for all different cross-sections, the inclusion of surface effects is found to reduce the difference between the two first mode natural frequencies. This trend is observed consistent with MD results. This study provides a first comprehensive investigation on the dual-mode vibration of <110> oriented Ag NWs, which is supposed to benefit the applications of NWs that acting as a resonating beam.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

A particle-based micromechanics approach to simulate structural changes of plant cells during drying

This paper is concerned with applying a particle-based approach to simulate the micro-level cellular structural changes of plant cells during drying. The objective of the investigation was to relate the micro-level structural properties such as cell area, diameter and perimeter to the change of moisture content of the cell. Model assumes a simplified cell which consists of two basic components, cell wall and cell fluid. The cell fluid is assumed to be a Newtonian fluid with higher viscosity compared to water and cell wall is assumed to be a visco-elastic solid boundary located around the cell fluid. Cell fluid is modelled with Smoothed Particle Hydrodynamics (SPH) technique and for the cell wall; a Discrete Element Method (DEM) is used. The developed model is two-dimensional, but accounts for three-dimensional physical properties of real plant cells. Drying phenomena is simulated as fluid mass reductions and the model is used to predict the above mentioned structural properties as a function of cell fluid mass. Model predictions are found to be in fairly good agreement with experimental data in literature and the particle-based approach is demonstrated to be suitable for numerical studies of drying related structural deformations. Also a sensitivity analysis is included to demonstrate the influence of key model parameters to model predictions.

High temperatures-related elderly mortality varied greatly from year to year : important information for heat-warning systems

We examined the variation in association between high temperatures and elderly mortality (age ≥ 75 years) from year to year in 83 US cities between 1987 and 2000. We used a Poisson regression model and decomposed the mortality risk for high temperatures into: a “main effect” due to high temperatures using lagged non-linear function, and an “added effect” due to consecutive high temperature days. We pooled yearly effects across both regional and national levels. The high temperature effects (both main and added effects) on elderly mortality varied greatly from year to year. In every city there was at least one year where higher temperatures were associated with lower mortality. Years with relatively high heat-related mortality were often followed by years with relatively low mortality. These year to year changes have important consequences for heat-warning systems and for predictions of heat-related mortality due to climate change.