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

Incorporating weather into regionwide safety planning prediction models

Predicting safety on roadways is standard practice for road safety professionals and has a corresponding extensive literature. The majority of safety prediction models are estimated using roadway segment and intersection (microscale) data, while more recently efforts have been undertaken to predict safety at the planning level (macroscale). Safety prediction models typically include roadway, operations, and exposure variables—factors known to affect safety in fundamental ways. Environmental variables, in particular variables attempting to capture the effect of rain on road safety, are difficult to obtain and have rarely been considered. In the few cases weather variables have been included, historical averages rather than actual weather conditions during which crashes are observed have been used. Without the inclusion of weather related variables researchers have had difficulty explaining regional differences in the safety performance of various entities (e.g. intersections, road segments, highways, etc.) As part of the NCHRP 8-44 research effort, researchers developed PLANSAFE, or planning level safety prediction models. These models make use of socio-economic, demographic, and roadway variables for predicting planning level safety. Accounting for regional differences - similar to the experience for microscale safety models - has been problematic during the development of planning level safety prediction models. More specifically, without weather related variables there is an insufficient set of variables for explaining safety differences across regions and states. Furthermore, omitted variable bias resulting from excluding these important variables may adversely impact the coefficients of included variables, thus contributing to difficulty in model interpretation and accuracy. This paper summarizes the results of an effort to include weather related variables, particularly various measures of rainfall, into accident frequency prediction and the prediction of the frequency of fatal and/or injury degree of severity crash models. The purpose of the study was to determine whether these variables do in fact improve overall goodness of fit of the models, whether these variables may explain some or all of observed regional differences, and identifying the estimated effects of rainfall on safety. The models are based on Traffic Analysis Zone level datasets from Michigan, and Pima and Maricopa Counties in Arizona. Numerous rain-related variables were found to be statistically significant, selected rain related variables improved the overall goodness of fit, and inclusion of these variables reduced the portion of the model explained by the constant in the base models without weather variables. Rain tends to diminish safety, as expected, in fairly complex ways, depending on rain frequency and intensity.

Subjective blur limits for higher order aberrations

Purpose: We compared subjective blur limits for defocus and the higher-order aberrations of coma, trefoil, and spherical aberration. ---------- Methods: Spherical aberration was presented in both Zernike and Seidel forms. Black letter targets (0.1, 0.35, and 0.6 logMAR) on white backgrounds were blurred using an adaptive optics system for six subjects under cycloplegia with 5 mm artificial pupils. Three blur criteria of just noticeable, just troublesome, and just objectionable were used.---------- Results: When expressed as wave aberration coefficients, the just noticeable blur limits for coma and trefoil were similar to those for defocus, whereas the just noticeable limits for Zernike spherical aberration and Seidel spherical aberration (the latter given as an “rms equivalent”) were considerably smaller and larger, respectively, than defocus limits.---------- Conclusions: Blur limits increased more quickly for the higher order aberrations than for defocus as the criterion changed from just noticeable to just troublesome and then to just objectionable.

Psychometric analysis of the Brisbane Practice Environment Measure (B-PEM)

Purpose: To undertake rigorous psychometric testing of the newly developed contemporary work environment measure (the Brisbane Practice Environment Measure [B-PEM]) using exploratory factor analysis and confirmatory factor analysis. Methods: Content validity of the 33-item measure was established by a panel of experts. Initial testing involved 195 nursing staff using principal component factor analysis with varimax rotation (orthogonal) and Cronbach's alpha coefficients. Confirmatory factor analysis was conducted using data from a further 983 nursing staff. Results: Principal component factor analysis yielded a four-factor solution with eigenvalues greater than 1 that explained 52.53% of the variance. These factors were then verified using confirmatory factor analysis. Goodness-of-fit indices showed an acceptable fit overall with the full model, explaining 21% to 73% of the variance. Deletion of items took place throughout the evolution of the instrument, resulting in a 26-item, four-factor measure called the Brisbane Practice Environment Measure-Tested. Conclusions: The B-PEM has undergone rigorous psychometric testing, providing evidence of internal consistency and goodness-of-fit indices within acceptable ranges. The measure can be utilised as a subscale or total score reflective of a contemporary nursing work environment. Clinical Relevance: An up-to-date instrument to measure practice environment may be useful for nursing leaders to monitor the workplace and to assist in identifying areas for improvement, facilitating greater job satisfaction and retention.

Comparing charge transport predictions for a ternary electrolyte using the Maxwell–Stefan and Nernst–Planck equations

In this work, we investigate and compare the Maxwell–Stefan and Nernst–Planck equations for modeling multicomponent charge transport in liquid electrolytes. Specifically, we consider charge transport in the Li+/I−/I3−/ACN ternary electrolyte originally found in dye-sensitized solar cells. We employ molecular dynamics simulations to obtain the Maxwell–Stefan diffusivities for this electrolyte. These simulated diffusion coefficients are used in a multicomponent charge transport model based on the Maxwell– Stefan equations, and this is compared to a Nernst–Planck based model which employs binary diffusion coefficients sourced from the literature. We show that significant differences between the electrolyte concentrations at electrode interfaces, as predicted by the Maxwell–Stefan and Nernst–Planck models, can occur. We find that these differences are driven by a pressure term that appears in the Maxwell–Stefan equations. We also investigate what effects the Maxwell–Stefan diffusivities have on the simulated charge transport. By incorporating binary diffusivities found in the literature into the Maxwell–Stefan framework, we show that the simulated transient concentration profiles depend on the diffusivities; however, the simulated equilibrium profiles remain unaffected.

A validated self-administered female pelvic floor questionnaire

Introduction and hypothesis: The aim of this study was to validate a self-administered version of the already validated interviewer-administered Australian pelvic floor questionnaire. Methods: The questionnaire was completed by 163 women attending an urogynecological clinic. Face and convergent validity was assessed. Reliability testing and comparison with the interviewer-administered version was performed in a subset of 105 patients. Responsiveness was evaluated in a subset of 73 women. Results: Missing data did not exceed 4% for any question. Cronbach’s alpha coefficients were acceptable in all domains. Kappa coefficients for the test–retest analyses varied from 0.64–1.0. Prolapse symptoms correlated significantly with the pelvic organ prolapse quantification. Urodynamics confirmed the reported symptom stress incontinence in 70%. The self and interviewer administered questionnaires demonstrated equivalence. Effect sizes ranged from 0.6 to 1.4. Conclusions: This self-administered pelvic floor questionnaire assessed pelvic floor function in a reproducible and valid fashion and due to its responsiveness, can be used for routine clinical assessment and outcome research.

Robust multidisciplinary design optimisation using CFD and advanced evolutionary algorithms

Computation Fluid Dynamics (CFD) has become an important tool in optimization and has seen successful in many real world applications. Most important among these is in the optimisation of aerodynamic surfaces which has become Multi-Objective (MO) and Multidisciplinary (MDO) in nature. Most of these have been carried out for a given set of input parameters such as free stream Mach number and angle of attack. One cannot ignore the fact that in aerospace engineering one frequently deals with situations where the design input parameters and flight/flow conditions have some amount of uncertainty attached to them. When the optimisation is carried out for fixed values of design variables and parameters however, one arrives at an optimised solution that results in good performance at design condition but poor drag or lift to drag ratio at slightly off-design conditions. The challenge is still to develop a robust design that accounts for uncertainty in the design in aerospace applications. In this paper this issue is taken up and an attempt is made to prevent the fluctuation of objective performance by using robust design technique or Uncertainty.

Shock control bump design optimization on Natural Laminar Aerofoil

The chapter investigates Shock Control Bumps (SCB) on a Natural Laminar Flow (NLF) aerofoil; RAE 5243 for Active Flow Control (AFC). A SCB approach is used to decelerate supersonic flow on the suction/pressure sides of transonic aerofoil that leads delaying shock occurrence or weakening of shock strength. Such an AFC technique reduces significantly the total drag at transonic speeds. This chapter considers the SCB shape design optimisation at two boundary layer transition positions (0 and 45%) using an Euler software coupled with viscous boundary layer effects and robust Evolutionary Algorithms (EAs). The optimisation method is based on a canonical Evolution Strategy (ES) algorithm and incorporates the concepts of hierarchical topology and parallel asynchronous evaluation of candidate solution. Two test cases are considered with numerical experiments; the first test deals with a transition point occurring at the leading edge and the transition point is fixed at 45% of wing chord in the second test. Numerical results are presented and it is demonstrated that an optimal SCB design can be found to significantly reduce transonic wave drag and improves lift on drag (L/D) value when compared to the baseline aerofoil design.

Response shift, recall bias and their effect on measuring change in health-related quality of life amongst older hospital patients

Background: Assessments of change in subjective patient reported outcomes such as health-related quality of life (HRQoL) are a key component of many clinical and research evaluations. However, conventional longitudinal evaluation of change may not agree with patient perceived change if patients' understanding of the subjective construct under evaluation changes over time (response shift) or if patients' have inaccurate recollection (recall bias). This study examined whether older adults' perception of change is in agreement with conventional longitudinal evaluation of change in their HRQoL over the duration of their hospital stay. It also investigated this level of agreement after adjusting patient perceived change for recall bias that patients may have experienced. Methods: A prospective longitudinal cohort design nested within a larger randomised controlled trial was implemented. 103 hospitalised older adults participated in this investigation at a tertiary hospital facility. The EQ-5D utility and Visual Analogue Scale (VAS) scores were used to evaluate HRQoL. Participants completed EQ-5D reports as soon as they were medically stable (within three days of admission) then again immediately prior to discharge. Three methods of change score calculation were used (conventional change, patient perceived change and patient perceived change adjusted for recall bias). Agreement was primarily investigated using intraclass correlation coefficients (ICC) and limits of agreement. Results: Overall 101 (98%) participants completed both admission and discharge assessments. The mean (SD) age was 73.3 (11.2). The median (IQR) length of stay was 38 (20-60) days. For agreement between conventional longitudinal change and patient perceived change: ICCs were 0.34 and 0.40 for EQ-5D utility and VAS respectively. For agreement between conventional longitudinal change and patient perceived change adjusted for recall bias: ICCs were 0.98 and 0.90 respectively. Discrepancy between conventional longitudinal change and patient perceived change was considered clinically meaningful for 84 (83.2%) of participants, after adjusting for recall bias this reduced to 8 (7.9%). Conclusions: Agreement between conventional change and patient perceived change was not strong. A large proportion of this disagreement could be attributed to recall bias. To overcome the invalidating effect of response shift (on conventional change) and recall bias (on patient perceived change) a method of adjusting patient perceived change for recall bias has been described.

Sodium niobate adsorbents doped with tantalum (TaV) for the removal of bivalence radioactive ions in waste waters

Sodium niobates doped with different amount of tantalum (TaV) were prepared via thermal reaction process. It was found pure nanofibril and bar-like solids can be obtained when tantalum was introduced into the reaction system. For the well-crystallized fibril solids, the Na+ ions are difficult to be exchanged, and the radioactive ions such as Sr2+ and Ra2+ ions just deposit on the surface of the fibers during the sorption process, resulting in lower sorption capacity and distribution coefficients (Kd)`. However, the bar-like solids are poorly-crystallized and have lots of exchangeable Na+ ions. They are able to remove highly hazardous bivalent radioactive isotopes such as Sr2+ and Ra2+ ions. Even in the presence of lots of Na+ ions, they also have higher Kd. More importantly, such sorption finally intelligently triggers considerable collapse of the structure, resulting in the entrapment of the toxic bivalent cations permanently in the solids so that they can be safely disposed. This study highlights new opportunities for the preparation of Nb-based adsorbents to efficiently remove the toxic radioactive ions from contaminated water.

Bubble rise velocity and trajectory in xanthan gum crystal suspension

An experimental set-up was used to visually observe the characteristics of bubbles as they moved up a column holding xanthan gum crystal suspensions. The bubble rise characteristics in xanthan gum solutions with crystal suspension are presented in this paper. The suspensions were made by using different concentrations of xanthan gum solutions with 0.23 mm mean diameter polystyrene crystal particles. The influence of the dimensionless quantities; namely the Reynolds number, Re, the Weber number, We, and the drag co-efficient, cd, are identified for the determination of the bubble rise velocity. The effect of these dimensionless groups together with the Eötvös number, Eo, the Froude number, Fr, and the bubble deformation parameter, D, on the bubble rise velocity and bubble trajectory are analysed. The experimental results show that the average bubble velocity increases with the increase in bubble volume for xanthan gum crystal suspensions. At high We, Eo and Re, bubbles are spherical-capped and their velocities are found to be very high. At low We and Eo, the surface tension force is significant compared to the inertia force. The viscous forces were shown to have no substantial effect on the bubble rise velocity for 45 < Re < 299. The results show that the drag co-efficient decreases with the increase in bubble velocity and Re. The trajectory analysis showed that small bubbles followed a zigzag motion while larger bubbles followed a spiral motion. The smaller bubbles experienced less horizontal motion in crystal suspended xanthan gum solutions while larger bubbles exhibited a greater degree of spiral motion than those seen in the previous studies on the bubble rise in xanthan gum solutions without crystal.

A first extension of geometric control theory to underwater vehicles

This paper serves as a first study on the implementation of control strategies developed using a kinematic reduction onto test bed autonomous underwater vehicles (AUVs). The equations of motion are presented in the framework of differential geometry, including external dissipative forces, as a forced affine connection control system. We show that the hydrodynamic drag forces can be included in the affine connection, resulting in an affine connection control system. The definitions of kinematic reduction and decoupling vector field are thus extended from the ideal fluid scenario. Control strategies are computed using this new extension and are reformulated for implementation onto a test-bed AUV. We compare these geometrically computed controls to time and energy optimal controls for the same trajectory which are computed using a previously developed algorithm. Through this comparison we are able to validate our theoretical results based on the experiments conducted using the time and energy efficient strategies.

Geometric Control Theory and its Application to Underwater Vehicles

This dissertation is based on theoretical study and experiments which extend geometric control theory to practical applications within the field of ocean engineering. We present a method for path planning and control design for underwater vehicles by use of the architecture of differential geometry. In addition to the theoretical design of the trajectory and control strategy, we demonstrate the effectiveness of the method via the implementation onto a test-bed autonomous underwater vehicle. Bridging the gap between theory and application is the ultimate goal of control theory. Major developments have occurred recently in the field of geometric control which narrow this gap and which promote research linking theory and application. In particular, Riemannian and affine differential geometry have proven to be a very effective approach to the modeling of mechanical systems such as underwater vehicles. In this framework, the application of a kinematic reduction allows us to calculate control strategies for fully and under-actuated vehicles via kinematic decoupled motion planning. However, this method has not yet been extended to account for external forces such as dissipative viscous drag and buoyancy induced potentials acting on a submerged vehicle. To fully bridge the gap between theory and application, this dissertation addresses the extension of this geometric control design method to include such forces. We incorporate the hydrodynamic drag experienced by the vehicle by modifying the Levi-Civita affine connection and demonstrate a method for the compensation of potential forces experienced during a prescribed motion. We present the design method for multiple different missions and include experimental results which validate both the extension of the theory and the ability to implement control strategies designed through the use of geometric techniques. By use of the extension presented in this dissertation, the underwater vehicle application successfully demonstrates the applicability of geometric methods to design implementable motion planning solutions for complex mechanical systems having equal or fewer input forces than available degrees of freedom. Thus, we provide another tool with which to further increase the autonomy of underwater vehicles.

The delta-phase spectrum with application to voice activity detection and speaker recognition

For several reasons, the Fourier phase domain is less favored than the magnitude domain in signal processing and modeling of speech. To correctly analyze the phase, several factors must be considered and compensated, including the effect of the step size, windowing function and other processing parameters. Building on a review of these factors, this paper investigates a spectral representation based on the Instantaneous Frequency Deviation, but in which the step size between processing frames is used in calculating phase changes, rather than the traditional single sample interval. Reflecting these longer intervals, the term delta-phase spectrum is used to distinguish this from instantaneous derivatives. Experiments show that mel-frequency cepstral coefficients features derived from the delta-phase spectrum (termed Mel-Frequency delta-phase features) can produce broadly similar performance to equivalent magnitude domain features for both voice activity detection and speaker recognition tasks. Further, it is shown that the fusion of the magnitude and phase representations yields performance benefits over either in isolation.

Cancer-related symptom clusters for symptom management in outpatients after commencing adjuvant chemotherapy, at 6 months, and 12 months

Goals of work: The aim of this secondary data analysis was to investigate symptom clusters over time for symptom management of a patient group after commencing adjuvant chemotherapy. Materials and methods: A prospective longitudinal study of 219 cancer outpatients conducted within 1 month of commencing chemotherapy (T1), 6 months (T2), and 12 months (T3) later. Patients' distress levels were assessed for 42 physical symptoms on a clinician-modified Rotterdam Symptom Checklist. Symptom clusters were identified in exploratory factor analyses at each time. Symptom inclusion in clusters was determined from structure coefficients. Symptoms could be associated with multiple clusters. Stability over time was determined from symptom cluster composition and the proportion of symptoms in the initial symptom clusters replicated at later times. Main results Fatigue and daytime sleepiness were the most prevalent distressing symptoms over time. The median number of concurrent distressing symptoms approximated 7, over time. Five consistent clusters were identified at T1, 2, and T3. An additional two clusters were identified at 12 months, possibly due to less variation in distress levels. Weakness and fatigue were each associated with two, four, and five symptom clusters at T1, T2, and T3, respectively, potentially suggesting different causal mechanisms. Conclusion: Stability is a necessary attribute of symptom clusters, but definitional clarification is required. We propose that a core set of concurrent symptoms identifies each symptom cluster, signifying a common cause. Additional related symptoms may be included over time. Further longitudinal investigation is required to identify symptom clusters and the underlying causes.