Familial influence on offspring gambling: a cognitive mechanism for transmission of gambling behavior in families

Background. The problem-gambling literature has identified a range of individual, cognitive, behavioral and emotional factors as playing important roles in the development, maintenance and treatment of problem gambling. However, familial factors have often been neglected. The current study aims to investigate the possible influence of parental factors on offspring gambling behavior. Method. A total of 189 families (546 individuals) completed several questionnaires including the South Oaks Gambling Screen (SOGS) and the Gambling Related Cognition Scale (GRCS). The relationships were examined using Pearson product-moment correlations and structural equation modeling (SEM) analyses. Results. Results showed that generally parents' (especially fathers') gambling cognitions and gambling behaviors positively correlated with offspring gambling behaviors and cognitions. However, SEM analyses showed that although parental gambling behavior was directly related to offspring gambling behavior, parental cognitions were not related to offspring gambling behavior directly but indirectly via offspring cognitions. Conclusion. The findings show that the influence of parental gambling cognition on offspring gambling behavior is indirect and via offspring cognitions. The results suggest a possible cognitive mechanism of transmission of gambling behavior in the family from one generation to the next.

Acute alcohol consumption and mechanism of injury

Objective: The purpose of this study was to determine whether injury mechanism among injured patients is differentially distributed as a function of acute alcohol consumption (quantity, type, and drinking setting). Method: A cross-sectional study was conducted between October 2000 and October 2001 in the Gold Coast Hospital Emergency Department, Queensland, Australia. Data were collected quarterly over a 12-month period. Every injured patient who presented to the emergency department during the study period for treatment of an injury sustained less than 24 hours prior to presentation was approached for interview. The final sample comprised 593 injured patients (males = 377). Three measures of alcohol consumption in the 6 hours prior to injury were obtained from self-report: quantity, beverage type, and drinking setting. The main outcome measure was mechanism of injury which was categorized into six groups: road traffic crash (RTC), being hit by or against something, fall, cut/piercing, overdose/poisoning, and miscellaneous. Injury intent was also measured (intentional vs unintentional). Results: After controlling for relevant confounding variables, neither quantity nor type of alcohol was significantly associated with injury mechanism. However, drinking setting (i.e., licensed premise) was significantly associated with increased odds of sustaining an intentional versus unintentional injury (odds ratio [OR] = 2.79, 95% confidence interval [CI] = 1.4-5.6); injury through being hit by/against something versus other injury types (OR = 2.59, 95% CI = 1.4-4.9); and reduced odds of sustaining an injury through RTC versus non-RTC (OR = 0.02, 95% CI = 0.004-0.9), compared with not drinking alcohol prior to injury. Conclusions: No previous analytical studies have examined the relationship between injury mechanism and acute alcohol consumption (quantity, type, and setting) across all types of injury and all injury severities while controlling for potentially important confounders (demographic and situational confounders, risk-taking behavior, substance use, and usual drinking patterns). These data suggest that among injured patients, mechanism of injury is not differentially distributed as a function of quantity or type of acute alcohol consumption but may be differentially distributed as a function of drinking setting (i.e., RTC, intentional injury, being hit). Therefore, prevention strategies that focus primarily on the quantity and type of alcohol consumed should be directed generically across injury mechanisms and not limited to particular cause of injury campaigns.

Agent-orientated auction mechanism and strategy design

Agent-based technology is playing an increasingly important role in today’s economy. Usually a multi-agent system is needed to model an economic system such as a market system, in which heterogeneous trading agents interact with each other autonomously. Two questions often need to be answered regarding such systems: 1) How to design an interacting mechanism that facilitates efficient resource allocation among usually self-interested trading agents? 2) How to design an effective strategy in some specific market mechanisms for an agent to maximise its economic returns? For automated market systems, auction is the most popular mechanism to solve resource allocation problems among their participants. However, auction comes in hundreds of different formats, in which some are better than others in terms of not only the allocative efficiency but also other properties e.g., whether it generates high revenue for the auctioneer, whether it induces stable behaviour of the bidders. In addition, different strategies result in very different performance under the same auction rules. With this background, we are inevitably intrigued to investigate auction mechanism and strategy designs for agent-based economics. The international Trading Agent Competition (TAC) Ad Auction (AA) competition provides a very useful platform to develop and test agent strategies in Generalised Second Price auction (GSP). AstonTAC, the runner-up of TAC AA 2009, is a successful advertiser agent designed for GSP-based keyword auction. In particular, AstonTAC generates adaptive bid prices according to the Market-based Value Per Click and selects a set of keyword queries with highest expected profit to bid on to maximise its expected profit under the limit of conversion capacity. Through evaluation experiments, we show that AstonTAC performs well and stably not only in the competition but also across a broad range of environments. The TAC CAT tournament provides an environment for investigating the optimal design of mechanisms for double auction markets. AstonCAT-Plus is the post-tournament version of the specialist developed for CAT 2010. In our experiments, AstonCAT-Plus not only outperforms most specialist agents designed by other institutions but also achieves high allocative efficiencies, transaction success rates and average trader profits. Moreover, we reveal some insights of the CAT: 1) successful markets should maintain a stable and high market share of intra-marginal traders; 2) a specialist’s performance is dependent on the distribution of trading strategies. However, typical double auction models assume trading agents have a fixed trading direction of either buy or sell. With this limitation they cannot directly reflect the fact that traders in financial markets (the most popular application of double auction) decide their trading directions dynamically. To address this issue, we introduce the Bi-directional Double Auction (BDA) market which is populated by two-way traders. Experiments are conducted under both dynamic and static settings of the continuous BDA market. We find that the allocative efficiency of a continuous BDA market mainly comes from rational selection of trading directions. Furthermore, we introduce a high-performance Kernel trading strategy in the BDA market which uses kernel probability density estimator built on historical transaction data to decide optimal order prices. Kernel trading strategy outperforms some popular intelligent double auction trading strategies including ZIP, GD and RE in the continuous BDA market by making the highest profit in static games and obtaining the best wealth in dynamic games.

Self-assembly-driven electrospinning:the transition from fibers to intact beaded morphologies

Polymer beads have attracted considerable interest for use in catalysis, drug delivery, and photo­nics due to their particular shape and surface morphology. Electrospinning, typically used for producing nanofibers, can also be used to fabricate polymer beads if the solution has a sufficiently low concentration. In this work, a novel approach for producing more uniform, intact beads is presented by electrospinning self-assembled block copolymer (BCP) solutions. This approach allows a relatively high polymer concentration to be used, yet with a low degree of entanglement between polymer chains due to microphase separation of the BCP in a selective solvent system. Herein, to demonstrate the technology, a well-studied polystyrene-poly(ethylene butylene)–polystyrene triblock copolymer is dissolved in a co-solvent system. The effect of solvent composition on the characteristics of the fibers and beads is intensively studied, and the mechanism of this fiber-to-bead is found to be dependent on microphase separation of the BCP.

A gender study investigating physics self-efficacy

The underrepresentation of women in physics has been well documented and a source of concern for both policy makers and educators. My dissertation focuses on understanding the role self-efficacy plays in retaining students, particularly women, in introductory physics. I use an explanatory mixed methods approach to first investigate quantitatively the influence of self-efficacy in predicting success and then to qualitatively explore the development of self-efficacy. In the initial quantitative studies, I explore the utility of self-efficacy in predicting the success of introductory physics students, both women and men. Results indicate that self-efficacy is a significant predictor of success for all students. I then disaggregate the data to examine how self-efficacy develops differently for women and men in the introductory physics course. Results show women rely on different sources of self-efficacy than do men, and that a particular instructional environment, Modeling Instruction, has a positive impact on these sources of self-efficacy. In the qualitative phase of the project, this dissertation focuses on the development of self-efficacy. Using the qualitative tool of microanalysis, I introduce a methodology for understanding how self-efficacy develops moment-by-moment using the lens of self-efficacy opportunities. I then use the characterizations of self-efficacy opportunities to focus on a particular course environment and to identify and describe a mechanism by which Modeling Instruction impacts student self-efficacy. Results indicate that the emphasizing the development and deployment of models affords opportunities to impact self-efficacy. The findings of this dissertation indicate that introducing key elements into the classroom, such as cooperative group work, model development and deployment, and interaction with the instructor, create a mechanism by which instructors can impact the self-efficacy of their students. Results from this study indicate that creating a model to impact the retention rates of women in physics should include attending to self-efficacy and designing activities in the classroom that create self-efficacy opportunities.

Energy-efficient self -organization of wireless acoustic sensor networks for ground target tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Energy-Efficient Self-Organization of Wireless Acoustic Sensor Networks for Ground Target Tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

The Catalytic Mechanism of the Marine-Derived Macrocyclase, PATGmac

Acknowledgements This work received financial support from the European Union (FEDER funds through COMPETE) and National Funds (FCT, Fundação para a Ciência e Tecnologia) through Projects EXCL/QEQ-COM/ 0394/2012, EXCL-II/QEQ-COM/0394/2012, and Pest-C/EQB/LA0006/2013. NFB would like to thank the Fundação para a Ciência e a Tecnologia (FCT) for her IF starting grant (IF/01355/2014).

Necessary conditions for the emergence of homochirality via autocatalytic self-replication

We analyze a recent proposal for spontaneous mirror symmetry breaking based on the coupling of first-order enantioselective autocatalysis and direct production of the enantiomers that invokes a critical role for intrinsic reaction noise. For isolated systems, the racemic state is the unique stable outcome for both stochastic and deterministic dynamics when the system is in compliance with the constraints dictated by the thermodynamics of chemical reaction processes. In open systems, the racemic outcome also results for both stochastic and deterministic dynamics when driving the auto-catalysis unidirectionally by external reagents. Nonracemic states can result in the latter only if the reverse reactions are strictly zero: these are kinetically controlled outcomes for small populations and volumes, and can be simulated by stochastic dynamics. However, the stability of the thermodynamic limit proves that the racemic outcome is the unique stable state for strictly irreversible externally driven autocatalysis. These findings contradict the suggestion that the inhibition requirement of the Frank autocatalytic model for the emergence of homochirality may be relaxed in a noise-induced mechanism.

Mechanism that dictates pore width and <111>a pore propagation in InP

We report a mechanism for pore growth and propagation based on a three-step charge transfer model. The study is supported by electron microscopy analysis of highly doped n-InP samples anodised in aqueous KOH. The model and experimental data are used to explain propagation of pores of characteristic diameter preferentially along the <111>A directions. We also show evidence for deviation of pore growth from the <111>A directions and explain why such deviations should occur. The model is self-consistent and predicts how carrier concentration affects the internal dimensions of the porous structures.

Self-healing of cracks during ductile regime machining of silicon: Insights from molecular dynamics simulation

During nanoindentation and ductile-regime machining of silicon, a phenomenon known as “self-healing” takes place in that the microcracks, microfractures, and small spallings generated during the machining are filled by the plastically flowing ductile phase of silicon. However, this phenomenon has not been observed in simulation studies. In this work, using a long-range potential function, molecular dynamics simulation was used to provide an improved explanation of this mechanism. A unique phenomenon of brittle cracking was discovered, typically inclined at an angle of 45° to 55° to the cut surface, leading to the formation of periodic arrays of nanogrooves being filled by plastically flowing silicon during cutting. This observation is supported by the direct imaging. The simulated X-ray diffraction analysis proves that in contrast to experiments, Si-I to Si-II (beta tin) transformation during ductile-regime cutting is highly unlikely and solid-state amorphisation of silicon caused solely by the machining stress rather than the cutting temperature is the key to its brittle-ductile transition observed during the MD simulations

Crystallization on the Mesoscale : Self-Assembly of Iron Oxide Nanocubes into Mesocrystals

Self-assembly of nanoparticles is a promising route to form complex, nanostructured materials with functional properties. Nanoparticle assemblies characterized by a crystallographic alignment of the nanoparticles on the atomic scale, i.e. mesocrystals, are commonly found in nature with outstanding functional and mechanical properties. This thesis aims to investigate and understand the formation mechanisms of mesocrystals formed by self-assembling iron oxide nanocubes. We have used the thermal decomposition method to synthesize monodisperse, oleate-capped iron oxide nanocubes with average edge lengths between 7 nm and 12 nm and studied the evaporation-induced self-assembly in dilute toluene-based nanocube dispersions. The influence of packing constraints on the alignment of the nanocubes in nanofluidic containers has been investigated with small and wide angle X-ray scattering (SAXS and WAXS, respectively). We found that the nanocubes preferentially orient one of their {100} faces with the confining channel wall and display mesocrystalline alignment irrespective of the channel widths.  We manipulated the solvent evaporation rate of drop-cast dispersions on fluorosilane-functionalized silica substrates in a custom-designed cell. The growth stages of the assembly process were investigated using light microscopy and quartz crystal microbalance with dissipation monitoring (QCM-D). We found that particle transport phenomena, e.g. the coffee ring effect and Marangoni flow, result in complex-shaped arrays near the three-phase contact line of a drying colloidal drop when the nitrogen flow rate is high. Diffusion-driven nanoparticle assembly into large mesocrystals with a well-defined morphology dominates at much lower nitrogen flow rates. Analysis of the time-resolved video microscopy data was used to quantify the mesocrystal growth and establish a particle diffusion-based, three-dimensional growth model. The dissipation obtained from the QCM-D signal reached its maximum value when the microscopy-observed lateral growth of the mesocrystals ceased, which we address to the fluid-like behavior of the mesocrystals and their weak binding to the substrate. Analysis of electron microscopy images and diffraction patterns showed that the formed arrays display significant nanoparticle ordering, regardless of the distinctive formation process.  We followed the two-stage formation mechanism of mesocrystals in levitating colloidal drops with real-time SAXS. Modelling of the SAXS data with the square-well potential together with calculations of van der Waals interactions suggests that the nanocubes initially form disordered clusters, which quickly transform into an ordered phase.

The role of oxidative stress as an underlying mechanism in life-history trade-offs

A key aspect underpinning life-history theory is the existence of trade-offs. Trade-offs occur because resources are limited, meaning that individuals cannot invest in all traits simultaneously, leading to costs for traits such as growth and reproduction. Such costs may be the reason for the sub-maximal growth rates that are often observed in nature, though the fitness consequences of these costs would depend on the effects on lifetime reproductive success. Recently, much attention has been given to the physiological mechanism that might underlie these life-history trade-offs, with oxidative stress (OS) playing a key role. OS is characterised by a build-up of oxidative damage to tissues (e.g. protein, lipids and DNA) from attack by reactive species (RS). RS, the majority of which are by-products of metabolism, are usually neutralised by antioxidants, however OS occurs when there is an imbalance between the two. There are two main theories linking OS with growth and reproduction. The first is that traits like growth and reproduction, being metabolically demanding, lead to an increase in RS production. The second involves the diversion of resources away from self-maintenance processes (e.g. the redox system) when individuals are faced with enhanced growth or reproductive expenditure. Previous research investigating trade-offs involving growth or reproduction and self-maintenance has been equivocal. One reason for this could be that associations among redox biomarkers can vary greatly so that the biomarker selected for analysis can influence the conclusion reached about an individual’s oxidative status. Therefore the first aim of my thesis was to explore the strength and pattern of integration of five biomarkers of OS (three antioxidants, one damage and one general oxidation measure) in wild blue tit (Cyanistes caeruleus) adults and nestlings (Chapter 2). In doing so, I established that all five biomarkers should be included in future analyses, thus using this collection of biomarkers I explored my next aims; whether enhanced growth (Chapters 3 and 4) or reproductive effort (Chapter 5) can lead to increased OS levels, if these traits are traded off against self-maintenance. I accomplished these aims using both a meta-analytic and experimental approach, the latter involving manipulation of brood size in wild blue tits in order to experimentally alter growth rate of nestlings and provisioning rate (a proxy for reproductive expenditure) of adults. I also investigated the potential for redox integration to be used as an index of body condition (Chapter 2), allowing predictions about future fitness consequences of changes to oxidative state to be made. A growth – self-maintenance trade off was supported by my meta-analytic results (Chapter 4) which found OS to be a constraint on growth. However, when faced with experimentally enhanced growth, animals were typically not able to adjust this trade-off so that oxidative damage resulted. This might support the idea that energetically expensive growth causes resources to be diverted away from the redox system; however, antioxidants did not show an overall reduction in response to growth in the meta-analysis suggesting that oxidative costs of growth may result from increased RS production due to the greater metabolism needed for enhanced growth. My experimental data (Chapter 3) showed a similar pattern, with raised protein damage levels (protein carbonyls; PCs) in the fastest growing blue tit chicks in a brood, compared with their slower growing sibs. These within-brood differences in OS levels likely resulted from within-brood hierarchies and might have masked any between-brood differences, which were not observed here. Despite evidence for a growth – self-maintenance trade off, my experimental results on blue tits found no support for the hypothesis that self-maintenance is also traded off against reproduction, another energetically demanding trait. There was no link between experimentally altered reproductive expenditure and OS, nor was there a direct correlation between reproductive effort and OS (Chapter 5). However, there are various factors that likely influence whether oxidative costs are observed, including environmental conditions and whether such costs are transient. This emphasises the need for longitudinal studies following the same individuals over multiple years and across a wide range of habitats that differ in quality. This would allow investigation into how key life events interact; it might be that raised OS levels from rapid early growth have the potential to constrain reproduction or that high parental OS levels constrain offspring growth. Any oxidative costs resulting from these life-history trade-offs have the potential to impact on future fitness. Redox integration of certain biomarkers might prove to be a useful tool in making predictions about fitness, as I found in Chapter 2, as well as establishing how the redox system responds, as a whole, to changes to growth and reproduction. Finally, if the tissues measured can tolerate a given level of OS, then the level of oxidative damage might be irrelevant and not impact on future fitness at all.

Model Probability in Self-organising Maps

Growing models have been widely used for clustering or topology learning. Traditionally these models work on stationary environments, grow incrementally and adapt their nodes to a given distribution based on global parameters. In this paper, we present an enhanced unsupervised self-organising network for the modelling of visual objects. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product.

PROLINE-BASED CHIRAL STATIONARY PHASES: INSIGHTS INTO THE MECHANISM OF CHIRAL SELECTIVITY

Proline (Pro) is a unique amino acid that has been examined previously as a potential chiral selector for high-performance liquid chromatography. In recent years, a new class of promising Pro based enantioselective stationary phases has been studied and the longer peptides were found to be competitive with commercial chiral stationary phases (CSPs). Here, we aim to perform a comprehensive examination of a t-butoxycarbonyl- (t-Boc-) terminated monoproline selector. This selector was grafted through an amide linkage to an aminopropyl siloxane-terminated Si (111) wafer and to a silicon atomic force microscopy tip. To ensure a flat, homogeneous overlayer of selectors suitable for force spectrometric measurements, the prepared surfaces were characterized using XPS, AFM and contact angle measurements. Chemical force spectrometry (CFS) has been used to examine the chiral discrimination in our monoproline CSP by measuring the interaction forces between two D- or L-monoproline monolayers in water and in the presence of a series of amino acids in solution to explore the degree to which binding of amino acids impacts self-selectivity. Chemical force titration (CFT) has been used to observe the influence of variations in pH on the binding interaction of proline modified chiral surfaces. Here we aim to explore the connection between side-chain hydrophobicity and differences in the nature of the binding between different ionic forms of amino acids and the t-Boc-Pro interface, and thereby to gain insight into the mechanism of chiral selectivity. The CFS results show several trends for different proline selector/amino acid combinations and indicate that the binding characteristics of amino acid to the proline surface is strongly dependent on the amino acid side chain where hydrophilic side chain amino acids exhibit a selectivity opposite to that seen for those with hydrophobic side chains. The CFT studies also provide valuable insights into interactions between the proline selector and the amino acids under a wide range of pH conditions, indicating that protonated amine groups of alanine and serine are closely involved in the binding mechanism to proline surfaces. On the other hand, the presence of the second carboxylic group in aspartic acid plays an important role while interacting with proline.