A Bayesian latent class safety performance function for identifying motor vehicle crash blackspots

The current state of the practice in Blackspot Identification (BSI) utilizes safety performance functions based on total crash counts to identify transport system sites with potentially high crash risk. This paper postulates that total crash count variation over a transport network is a result of multiple distinct crash generating processes including geometric characteristics of the road, spatial features of the surrounding environment, and driver behaviour factors. However, these multiple sources are ignored in current modelling methodologies in both trying to explain or predict crash frequencies across sites. Instead, current practice employs models that imply that a single underlying crash generating process exists. The model mis-specification may lead to correlating crashes with the incorrect sources of contributing factors (e.g. concluding a crash is predominately caused by a geometric feature when it is a behavioural issue), which may ultimately lead to inefficient use of public funds and misidentification of true blackspots. This study aims to propose a latent class model consistent with a multiple crash process theory, and to investigate the influence this model has on correctly identifying crash blackspots. We first present the theoretical and corresponding methodological approach in which a Bayesian Latent Class (BLC) model is estimated assuming that crashes arise from two distinct risk generating processes including engineering and unobserved spatial factors. The Bayesian model is used to incorporate prior information about the contribution of each underlying process to the total crash count. The methodology is applied to the state-controlled roads in Queensland, Australia and the results are compared to an Empirical Bayesian Negative Binomial (EB-NB) model. A comparison of goodness of fit measures illustrates significantly improved performance of the proposed model compared to the NB model. The detection of blackspots was also improved when compared to the EB-NB model. In addition, modelling crashes as the result of two fundamentally separate underlying processes reveals more detailed information about unobserved crash causes.

Do Measurement Errors in GDP Announcements Cause Output Fluctuations?

This thesis studies empirically whether measurement errors in aggregate production statistics affect sentiment and future output. Initial announcements of aggregate production are subject to measurement error, because many of the data required to compile the statistics are produced with a lag. This measurement error can be gauged as the difference between the latest revised statistic and its initial announcement. Assuming aggregate production statistics help forecast future aggregate production, these measurement errors are expected to affect macroeconomic forecasts. Assuming agents’ macroeconomic forecasts affect their production choices, these measurement errors should affect future output through sentiment. This thesis is primarily empirical, so the theoretical basis, strategic complementarity, is discussed quite briefly. However, it is a model in which higher aggregate production increases each agent’s incentive to produce. In this circumstance a statistical announcement which suggests aggregate production is high would increase each agent’s incentive to produce, thus resulting in higher aggregate production. In this way the existence of strategic complementarity provides the theoretical basis for output fluctuations caused by measurement mistakes in aggregate production statistics. Previous empirical studies suggest that measurement errors in gross national product affect future aggregate production in the United States. Additionally it has been demonstrated that measurement errors in the Index of Leading Indicators affect forecasts by professional economists as well as future industrial production in the United States. This thesis aims to verify the applicability of these findings to other countries, as well as study the link between measurement errors in gross domestic product and sentiment. This thesis explores the relationship between measurement errors in gross domestic production and sentiment and future output. Professional forecasts and consumer sentiment in the United States and Finland, as well as producer sentiment in Finland, are used as the measures of sentiment. Using statistical techniques it is found that measurement errors in gross domestic product affect forecasts and producer sentiment. The effect on consumer sentiment is ambiguous. The relationship between measurement errors and future output is explored using data from Finland, United States, United Kingdom, New Zealand and Sweden. It is found that measurement errors have affected aggregate production or investment in Finland, United States, United Kingdom and Sweden. Specifically, it was found that overly optimistic statistics announcements are associated with higher output and vice versa.

Essays on Labor Market Frictions, Technological Change and Macroeconomic Fluctuations

The dissertation consists of an introductory chapter and three essays that apply search-matching theory to study the interaction of labor market frictions, technological change and macroeconomic fluctuations. The first essay studies the impact of capital-embodied growth on equilibrium unemployment by extending a vintage capital/search model to incorporate vintage human capital. In addition to the capital obsolescence (or creative destruction) effect that tends to raise unemployment, vintage human capital introduces a skill obsolescence effect of faster growth that has the opposite sign. Faster skill obsolescence reduces the value of unemployment, hence wages and leads to more job creation and less job destruction, unambiguously reducing unemployment. The second essay studies the effect of skill biased technological change on skill mismatch and the allocation of workers and firms in the labor market. By allowing workers to invest in education, we extend a matching model with two-sided heterogeneity to incorporate an endogenous distribution of high and low skill workers. We consider various possibilities for the cost of acquiring skills and show that while unemployment increases in most scenarios, the effect on the distribution of vacancy and worker types varies according to the structure of skill costs. When the model is extended to incorporate endogenous labor market participation, we show that the unemployment rate becomes less informative of the state of the labor market as the participation margin absorbs employment effects. The third essay studies the effects of labor taxes on equilibrium labor market outcomes and macroeconomic dynamics in a New Keynesian model with matching frictions. Three policy instruments are considered: a marginal tax and a tax subsidy to produce tax progression schemes, and a replacement ratio to account for variability in outside options. In equilibrium, the marginal tax rate and replacement ratio dampen economic activity whereas tax subsidies boost the economy. The marginal tax rate and replacement ratio amplify shock responses whereas employment subsidies weaken them. The tax instruments affect the degree to which the wage absorbs shocks. We show that increasing tax progression when taxation is initially progressive is harmful for steady state employment and output, and amplifies the sensitivity of macroeconomic variables to shocks. When taxation is initially proportional, increasing progression is beneficial for output and employment and dampens shock responses.

Large Low-Frequency Fluctuations in the Velocity of a Driven Vortex Lattice in a Single Crystal of 2H-NbSe2 Superconductor

The driven state of a well-ordered flux line lattice in a single crystal of 2H-NbSe2 in the time domain has revealed the presence of substantial fluctuations in velocity, with large and distinct time periods (similar to seconds). A superposition of a periodic drive in the driven vortex lattice causes distinct changes in these fluctuations. We propose that prior to the onset of the peak effect there exists a heretofore unexplored regime of coherent dynamics, with unexpected behavior in velocity fluctuations.

Mechanism of RNA Translocation by a Viral Packaging Motor

Molecular motors are proteins that convert chemical energy into mechanical work. The viral packaging ATPase P4 is a hexameric molecular motor that translocates RNA into preformed viral capsids. P4 belongs to the ubiquitous class of hexameric helicases. Although its structure is known, the mechanism of RNA translocation remains elusive. Here we present a detailed kinetic study of nucleotide binding, hydrolysis, and product release by P4. We propose a stochastic-sequential cooperative model to describe the coordination of ATP hydrolysis within the hexamer. In this model the apparent cooperativity is a result of hydrolysis stimulation by ATP and RNA binding to neighboring subunits rather than cooperative nucleotide binding. Simultaneous interaction of neighboring subunits with RNA makes the otherwise random hydrolysis sequential and processive. Further, we use hydrogen/deuterium exchange detected by high resolution mass spectrometry to visualize P4 conformational dynamics during the catalytic cycle. Concerted changes of exchange kinetics reveal a cooperative unit that dynamically links ATP binding sites and the central RNA binding channel. The cooperative unit is compatible with the structure-based model in which translocation is effected by conformational changes of a limited protein region. Deuterium labeling also discloses the transition state associated with RNA loading which proceeds via opening of the hexameric ring. Hydrogen/deuterium exchange is further used to delineate the interactions of the P4 hexamer with the viral procapsid. P4 associates with the procapsid via its C-terminal face. The interactions stabilize subunit interfaces within the hexamer. The conformation of the virus-bound hexamer is more stable than the hexamer in solution, which is prone to spontaneous ring openings. We propose that the stabilization within the viral capsid increases the packaging processivity and confers selectivity during RNA loading. Finally, we use single molecule techniques to characterize P4 translocation along RNA. While the P4 hexamer encloses RNA topologically within the central channel, it diffuses randomly along the RNA. In the presence of ATP, unidirectional net movement is discernible in addition to the stochastic motion. The diffusion is hindered by activation energy barriers that depend on the nucleotide binding state. The results suggest that P4 employs an electrostatic clutch instead of cycling through stable, discrete, RNA binding states during translocation. Conformational changes coupled to ATP hydrolysis modify the electrostatic potential inside the central channel, which in turn biases RNA motion in one direction. Implications of the P4 model for other hexameric molecular motors are discussed.

EPR Evidence for Premonitory Charge-Ordering Fluctuations in Hydrothermally Grown Pr0.57Ca0.41Ba0.02MnO3 Nanowires

Electron paramagnetic resonance (EPR) and magnetic properties of nanowires of Pr0.57Ca0.41Ba0.02MnO3 (PCBMO) are studied and compared with those of the bulk material. PCBMO nanowires with diameter of 80-90 nm and length of similar to 3.5 mu m were synthesized by a low reaction temperature hydrothermal method and the bulk sample was prepared following a solid-state reaction route. The samples were characterized by X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The bulk PCBMO manganite exhibits charge order at 230 K along with a ferromagnetic transition at 110 K. However, superconducting quantum interference device measurements on the PCBMO nanowires show a complete `melting' of charge ordering and a ferromagnetic transition at 115 K. This result is confirmed by the EPR intensity behavior as well. However, the EPR line width, which is reflective of the spin dynamics, shows a shallow minimum for nanowires at the temperature corresponding to the charge-ordering transition, i.e., 230 K. We interpret this result as an indication of the presence of charge-ordering fluctuations in the nanowires even though the static charge order is absent, thus heralding the occurrence of charge order in the bulk sample.

Bond graph model of doubly fed three phase induction motor using the Axis Rotator element for frame transformation

Induction motor is a typical member of a multi-domain, non-linear, high order dynamic system. For speed control a three phase induction motor is modelled as a d–q model where linearity is assumed and non-idealities are ignored. Approximation of the physical characteristic gives a simulated behaviour away from the natural behaviour. This paper proposes a bond graph model of an induction motor that can incorporate the non-linearities and non-idealities thereby resembling the physical system more closely. The model is validated by applying the linearity and idealities constraints which shows that the conventional ‘abc’ model is a special case of the proposed generalised model.

The effects of entacapone on cardiorespiratory, autonomic, and clinical responses in L-dopa-treated patients with Parkinson's disease

Rest tremor, rigidity, and slowness of movements-considered to be mainly due to markedly reduced levels of dopamine (DA) in the basal ganglia-are characteristic motor symptoms of Parkinson's disease (PD). Although there is yet no cure for this illness, several drugs can alleviate the motor symptoms. Among these symptomatic therapies, L-dopa is the most effective. As a precursor to DA, it is able to replace the loss of DA in the basal ganglia. In the long run L-dopa has, however, disadvantages. Motor response complications, such as shortening of the duration of drug effect ("wearing-off"), develop in many patients. In addition, extensive peripheral metabolism of L-dopa by aromatic amino acid decarboxylase and catechol-O-methyltransferase (COMT) results in its short half-life, low bioavailability, and reduced efficacy. Entacapone, a nitrocatechol-structured compound, is a highly selective, reversible, and orally active inhibitor of COMT. It increases the bioavailability of L-dopa by reducing its peripheral elimination rate. Entacapone extends the duration of clinical response to each L-dopa dose in PD patients with wearing-off fluctuations. COMT is important in the metabolism of catecholamines. Its inhibition could, therefore, theoretically lead to adverse cardiovascular reactions, especially in circumstances of enhanced sympathetic activity (physical exercise). PD patients may be particularly vulnerable to such effects due to high prevalence of cardiovascular autonomic dysfunction, and the common use of monoamine oxidase B inhibitor selegiline, another drug with effects on catecholamine metabolism. Both entacapone and selegiline enhance L-dopa's clinical effect. Their co-administration may therefore lead to pharmacodynamic interactions, either beneficial (improved L-dopa efficacy) or harmful (increased dyskinesia). We investigated the effects of repeated dosing (3-5 daily doses for 1-2 weeks) of entacapone 200 mg administered either with or without selegiline (10 mg once daily), on several safety and efficacy parameters in 39 L-dopa-treated patients with mild to moderate PD in three double-blind placebo-controlled, crossover studies. In the first two, the cardiovascular, clinical, and biochemical responses were assessed repeatedly for 6 hours after drug intake, first with L-dopa only (control), and then after a 2 weeks on study drugs (entacapone vs. entacapone plus selegiline in one; entacapone vs. selegiline vs. entacapone plus selegiline in the other). The third study included cardiovascular reflex and spiroergometric exercise testing, first after overnight L-dopa withdrawal (control), and then after 1 week on entacapone plus selegiline as adjuncts to L-dopa. Ambulatory ECG was recorded in two of the studies. Blood pressure, heart rate, ECG, cardiovascular autonomic function, cardiorespiratory exercise responses, and the resting/exercise levels of circulating catecholamines remained unaffected by entacapone, irrespective of selegiline. Entacapone significantly enhanced both L-dopa bioavailability and its clinical response, the latter being more pronounced with the co-administration of selegiline. Dyskinesias were also increased during simultaneous use of both entacapone and selegiline as L-dopa adjuncts. Entacapone had no effect on either work capacity or work efficiency. The drug was well tolerated, both with and without selegiline. Conclusions: the use of entacapone-either alone or combined with selegiline-seems to be hemodynamically safe in L-dopa-treated PD patients, also during maximal physical effort. This is in line with the safety experience from larger phase III studies. Entacapone had no effect on cardiovascular autonomic function. Concomitant administration of entacapone and selegiline may enhance L-dopa's clinical efficacy but may also lead to increased dyskinesia.

Long-lived giant number fluctuations in a swarming granular nematic

Coherently moving flocks of birds, beasts, or bacteria are examples of living matter with spontaneous orientational order. How do these systems differ from thermal equilibrium systems with such liquid crystalline order? Working with a fluidized monolayer of macroscopic rods in the nematic liquid crystalline phase, we find giant number fluctuations consistent with a standard deviation growing linearly with the mean, in contrast to any situation where the central limit theorem applies. These fluctuations are long-lived, decaying only as a logarithmic function of time. This shows that flocking, coherent motion, and large-scale inhomogeneity can appear in a system in which particles do not communicate except by contact.

Generalized survival in step fluctuations

The properties of the generalized survival probability, that is, the probability of not crossing an arbitrary location R during relaxation, have been investigated experimentally (via scanning tunneling microscope observations) and numerically. The results confirm that the generalized survival probability decays exponentially with a time constant tau(s)(R). The distance dependence of the time constant is shown to be tau(s)(R)=tau(s0)exp[-R/w(T)], where w(2)(T) is the material-dependent mean-squared width of the step fluctuations. The result reveals the dependence on the physical parameters of the system inherent in the prior prediction of the time constant scaling with R/L-alpha, with L the system size and alpha the roughness exponent. The survival behavior is also analyzed using a contrasting concept, the generalized inside survival S-in(t,R), which involves fluctuations to an arbitrary location R further from the average. Numerical simulations of the inside survival probability also show an exponential time dependence, and the extracted time constant empirically shows (R/w)(lambda) behavior, with lambda varying over 0.6 to 0.8 as the sampling conditions are changed. The experimental data show similar behavior, and can be well fit with lambda=1.0 for T=300 K, and 0.5