Macular function in tilted disc syndrome

Tilted disc syndrome can cause visual field defects due to an optic disc anomaly. Recent electrophysiological findings demonstrate reduced central outer retinal function with ophthalmoscopically normal maculae. We measured macular sensitivity with the microperimeter and performed psychophysical assessment of mesopic rod and cone luminance temporal sensitivity (critical fusion frequency)in a 52-year-old male patient with tilted disc syndrome and ophthalmoscopically normal maculae. We found a marked reduction of sensitivity in the central 20 degrees and reduced rod- and cone-mediated mesopic visual function. Our findings extend previous electrophysiological data that suggest an outer retinal involvement of cone pathways and present a case with rod and cone impairment mediated via the magnocellular pathway in uncomplicated tilted disc syndrome.

Prevalence of upper-body symptoms following breast cancer and its relationship with upper-body function and lymphoedema

This investigation describes the prevalence of upper-body symptoms in a population-based sample of women with breast cancer (BC) and examines their relationships with upper-body function (UBF) and lymphoedema, as two clinically important sequelae. Australian women (n=287) with unilateral BC were assessed at three-monthly intervals, from six to 18 months post-surgery (PS). Participants reported the presence and intensity of upper-body symptoms on the treated side. Objective and self-reported UBF and lymphoedema (bioimpedance spectroscopy) were also assessed. Approximately 50% of women reported at least one moderate-to-extreme symptom at 6- and at 18-months PS. There was a significant relationship between symptoms and function (p<0.01), whereby perceived and objective function declined with increasing number of symptoms present. Those with lymphoedema were more likely to report multiple symptoms and presence of symptoms at baseline increased risk of lymphoedema (ORs>1.3, p=0.02). Although, presence of symptoms explained only 5.5% of the variation in the odds of lymphoedema. Upper-body symptoms are common and persistent following breast cancer and are associated with clinical ramifications, including reduced UBF and increased risk of developing lymphoedema. However, using the presence of symptoms as a diagnostic indicator of lymphoedema is limited.

Iteratively specified tree-based regression : theory and trip generation example

Focuses on a study which introduced an iterative modeling method that combines properties of ordinary least squares (OLS) with hierarchical tree-based regression (HTBR) in transportation engineering. Information on OLS and HTBR; Comparison and contrasts of OLS and HTBR; Conclusions.

Quantum theory beyond the physical : information in context

Measures and theories of information abound, but there are few formalised methods for treating the contextuality that can manifest in different information systems. Quantum theory provides one possible formalism for treating information in context. This paper introduces a quantum-like model of the human mental lexicon, and shows one set of recent experimental data suggesting that concept combinations can indeed behave non-separably. There is some reason to believe that the human mental lexicon displays entanglement.

Critical thinking and organisation theory : embedding a process to encourage graduate capabilities

The need for the development of effective business curricula that meets the needs of the marketplace has created an increase in the adoption of core competencies lists identifying appropriate graduate skills. Many organisations and tertiary institutions have individual graduate capabilities lists including skills deemed essential for success. Skills recognised as ‘critical thinking’ are popular inclusions on core competencies and graduate capability lists. While there is literature outlining ‘critical thinking’ frameworks, methods of teaching it and calls for its integration into business curricula, few studies actually identify quantifiable improvements achieved in this area. This project sought to address the development of ‘critical thinking’ skills in a management degree program by embedding a process for critical thinking within a theory unit undertaken by students early in the program. Focus groups and a student survey were used to identify issues of both content and implementation and to develop a student perspective on their needs in thinking critically. A process utilising a framework of critical thinking was integrated through a workbook of weekly case studies for group analysis, discussions and experiential exercises. The experience included formative and summative assessment. Initial results indicate a greater valuation by students of their experience in the organisation theory unit; better marks for mid semester essay assignments and higher evaluations on the university administered survey of students’ satisfaction.

On the nature of over-dispersion in motor vehicle crash prediction models

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros

Differences in the performance of safety performance functions estimated for total crash count and for crash count by crash type

In recent years the development and use of crash prediction models for roadway safety analyses have received substantial attention. These models, also known as safety performance functions (SPFs), relate the expected crash frequency of roadway elements (intersections, road segments, on-ramps) to traffic volumes and other geometric and operational characteristics. A commonly practiced approach for applying intersection SPFs is to assume that crash types occur in fixed proportions (e.g., rear-end crashes make up 20% of crashes, angle crashes 35%, and so forth) and then apply these fixed proportions to crash totals to estimate crash frequencies by type. As demonstrated in this paper, such a practice makes questionable assumptions and results in considerable error in estimating crash proportions. Through the use of rudimentary SPFs based solely on the annual average daily traffic (AADT) of major and minor roads, the homogeneity-in-proportions assumption is shown not to hold across AADT, because crash proportions vary as a function of both major and minor road AADT. For example, with minor road AADT of 400 vehicles per day, the proportion of intersecting-direction crashes decreases from about 50% with 2,000 major road AADT to about 15% with 82,000 AADT. Same-direction crashes increase from about 15% to 55% for the same comparison. The homogeneity-in-proportions assumption should be abandoned, and crash type models should be used to predict crash frequency by crash type. SPFs that use additional geometric variables would only exacerbate the problem quantified here. Comparison of models for different crash types using additional geometric variables remains the subject of future research.

Bayesian multinomial logit: Theory and route choice example

Statisticians along with other scientists have made significant computational advances that enable the estimation of formerly complex statistical models. The Bayesian inference framework combined with Markov chain Monte Carlo estimation methods such as the Gibbs sampler enable the estimation of discrete choice models such as the multinomial logit (MNL) model. MNL models are frequently applied in transportation research to model choice outcomes such as mode, destination, or route choices or to model categorical outcomes such as crash outcomes. Recent developments allow for the modification of the potentially limiting assumptions of MNL such as the independence from irrelevant alternatives (IIA) property. However, relatively little transportation-related research has focused on Bayesian MNL models, the tractability of which is of great value to researchers and practitioners alike. This paper addresses MNL model specification issues in the Bayesian framework, such as the value of including prior information on parameters, allowing for nonlinear covariate effects, and extensions to random parameter models, so changing the usual limiting IIA assumption. This paper also provides an example that demonstrates, using route-choice data, the considerable potential of the Bayesian MNL approach with many transportation applications. This paper then concludes with a discussion of the pros and cons of this Bayesian approach and identifies when its application is worthwhile

BLAST Atlas : a function based multiple genome browser

BLAST Atlas is a visual analysis system for comparative genomics that supports genome-wide gene characterisation, functional assignment and function-based browsing of one or more chromosomes. Inspired by applications such as the WorldWide Telescope, Bing Maps 3D and Google Earth, BLAST Atlas uses novel three-dimensional gene and function views that provide a highly interactive and intuitive way for scientists to navigate, query and compare gene annotations. The system can be used for gene identification and functional assignment or as a function-based multiple genome comparison tool which complements existing position based comparison and alignment viewers.

Political theory and theoretical physics

This paper argues, somewhat along a Simmelian line, that political theory may produce practical and universal theories like those developed in theoretical physics. The reasoning behind this paper is to show that the theory of ‘basic democracy’ may be true by way of comparing it to Einstein’s Special Relativity – specifically concerning the parameters of symmetry, unification, simplicity, and utility. These parameters are what make a theory in physics as meeting them not only fits with current knowledge, but also produces paths towards testing (application). As the theory of ‘basic democracy’ may meet these same parameters, it could settle the debate concerning the definition of democracy. This will be argued firstly by discussing what the theory of ‘basic democracy’ is and why it differs from previous work; secondly by explaining the parameters chosen (as in why these and not others confirm or scuttle theories); and thirdly by comparing how Special Relativity and the theory of ‘basic democracy’ may match the parameters.

Performance analysis of IEEE 802.11 DCF based WNCS networks

Wireless network technologies, such as IEEE 802.11 based wireless local area networks (WLANs), have been adopted in wireless networked control systems (WNCS) for real-time applications. Distributed real-time control requires satisfaction of (soft) real-time performance from the underlying networks for delivery of real-time traffic. However, IEEE 802.11 networks are not designed for WNCS applications. They neither inherently provide quality-of-service (QoS) support, nor explicitly consider the characteristics of the real-time traffic on networked control systems (NCS), i.e., periodic round-trip traffic. Therefore, the adoption of 802.11 networks in real-time WNCSs causes challenging problems for network design and performance analysis. Theoretical methodologies are yet to be developed for computing the best achievable WNCS network performance under the constraints of real-time control requirements. Focusing on IEEE 802.11 distributed coordination function (DCF) based WNCSs, this paper analyses several important NCS network performance indices, such as throughput capacity, round trip time and packet loss ratio under the periodic round trip traffic pattern, a unique feature of typical NCSs. Considering periodic round trip traffic, an analytical model based on Markov chain theory is developed for deriving these performance indices under a critical real-time traffic condition, at which the real-time performance constraints are marginally satisfied. Case studies are also carried out to validate the theoretical development.

Rayleigh theory of ultrasound scattering applied to liquid-filled contrast nanoparticles

We present a novel modified theory based upon Rayleigh scattering of ultrasound from composite nanoparticles with a liquid core and solid shell. We derive closed form solutions to the scattering cross-section and have applied this model to an ultrasound contrast agent consisting of a liquid-filled core (perfluorooctyl bromide, PFOB) encapsulated by a polymer shell (poly-caprolactone, PCL). Sensitivity analysis was performed to predict the dependence of the scattering cross-section upon material and dimensional parameters. A rapid increase in the scattering cross-section was achieved by increasing the compressibility of the core, validating the incorporation of high compressibility PFOB; the compressibility of the shell had little impact on the overall scattering cross-section although a more compressible shell is desirable. Changes in the density of the shell and the core result in predicted local minima in the scattering cross-section, approximately corresponding to the PFOB-PCL contrast agent considered; hence, incorporation of a lower shell density could potentially significantly improve the scattering cross-section. A 50% reduction in shell thickness relative to external radius increased the predicted scattering cross-section by 50%. Although it has often been considered that the shell has a negative effect on the echogeneity due to its low compressibility, we have shown that it can potentially play an important role in the echogeneity of the contrast agent. The challenge for the future is to identify suitable shell and core materials that meet the predicted characteristics in order to achieve optimal echogenity.

Widening the gap between measurement and modelling of secondary organic aerosol properties?

The link between measured sub-saturated hygroscopicity and cloud activation potential of secondary organic aerosol particles produced by the chamber photo-oxidation of α-pinene in the presence or absence of ammonium sulphate seed aerosol was investigated using two models of varying complexity. A simple single hygroscopicity parameter model and a more complex model (incorporating surface effects) were used to assess the detail required to predict the cloud condensation nucleus (CCN) activity from the subsaturated water uptake. Sub-saturated water uptake measured by three hygroscopicity tandem differential mobility analyser (HTDMA) instruments was used to determine the water activity for use in the models. The predicted CCN activity was compared to the measured CCN activation potential using a continuous flow CCN counter. Reconciliation using the more complex model formulation with measured cloud activation could be achieved widely different assumed surface tension behavior of the growing droplet; this was entirely determined by the instrument used as the source of water activity data. This unreliable derivation of the water activity as a function of solute concentration from sub-saturated hygroscopicity data indicates a limitation in the use of such data in predicting cloud condensation nucleus behavior of particles with a significant organic fraction. Similarly, the ability of the simpler single parameter model to predict cloud activation behaviour was dependent on the instrument used to measure sub-saturated hygroscopicity and the relative humidity used to provide the model input. However, agreement was observed for inorganic salt solution particles, which were measured by all instruments in agreement with theory. The difference in HTDMA data from validated and extensively used instruments means that it cannot be stated with certainty the detail required to predict the CCN activity from sub-saturated hygroscopicity. In order to narrow the gap between measurements of hygroscopic growth and CCN activity the processes involved must be understood and the instrumentation extensively quality assured. It is impossible to say from the results presented here due to the differences in HTDMA data whether: i) Surface tension suppression occurs ii) Bulk to surface partitioning is important iii) The water activity coefficient changes significantly as a function of the solute concentration.

Organ printing

Organ printing techniques offer the potential to produce living 3D tissue constructs to repair or replace damaged or diseased human tissues and organs. Using these techniques, spatial variations along multiple axes with high geometric complexity can be obtained.. The level of control offered by these technologies to develop printed tissues will allow tissue engineers to better study factors that modulate tissue formation and function, and provide a valuable tool to study the effect of anatomy on graft performance. In this chapter we discuss the history behind substrate patterning and cell and organ printing, and the rationale for developing organ printing techniques with respect to limitations of current clinical tissue engineering strategies to effectively repair damaged tissues. We discuss current 2-dimensional and 3-dimesional strategies for assembling cells as well as the necessary support materials such as hydrogels, bioinks and natural and synthetic polymers adopted for organ printing research. Furthermore, given the current state-of-the-art in organ printing technologies, we discuss some of their limitations and provide recommendations for future developments in this rapidly growing field.