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

A modified dual-band microstrip monopole antenna

A modified microstrip-fed planar monopole antenna with open circuited coupled line is presented in this paper. The operational bandwidth of the proposed antenna covers the 2.4 GHz ISM band (2.42-2.48 GHz) and the 5 GHz WLAN band (5 GHz to 6 GHz). The radiating elements occupy a small area of 23×8 mm2. The Finite Difference Time Domain method is used to predict the input impedance of the antenna. The calculated return loss shows very good agreement with measured data. Reasonable antenna gain is observed across the operating band. The measured radiation patterns are similar to those of a simple monopole antenna.

Extinction risk in cloud forest fragments under climate change and habitat loss

Aim: To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location: Cloud forests in Mexico. Methods: Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results: Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions: Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. © 2013 John Wiley & Sons Ltd.

Inferring lung cancer risk factor patterns through joint Bayesian spatio-temporal analysis

Background: Preventing risk factor exposure is vital to reduce the high burden from lung cancer. The leading risk factor for developing lung cancer is tobacco smoking. In Australia, despite apparent success in reducing smoking prevalence, there is limited information on small area patterns and small area temporal trends. We sought to estimate spatio-temporal patterns for lung cancer risk factors using routinely collected population-based cancer data. Methods: The analysis used a Bayesian shared component spatio-temporal model, with male and female lung cancer included separately. The shared component reflected exposure to lung cancer risk factors, and was modelled over 477 statistical local areas (SLAs) and 15 years in Queensland, Australia. Analyses were also run adjusting for area-level socioeconomic disadvantage, Indigenous population composition, or remoteness. Results: Strong spatial patterns were observed in the underlying risk factor exposure for both males (median Relative Risk (RR) across SLAs compared to the Queensland average ranged from 0.48-2.00) and females (median RR range across SLAs 0.53-1.80), with high exposure observed in many remote areas. Strong temporal trends were also observed. Males showed a decrease in the underlying risk across time, while females showed an increase followed by a decrease in the final two years. These patterns were largely consistent across each SLA. The high underlying risk estimates observed among disadvantaged, remote and indigenous areas decreased after adjustment, particularly among females. Conclusion: The modelled underlying exposure appeared to reflect previous smoking prevalence, with a lag period of around 30 years, consistent with the time taken to develop lung cancer. The consistent temporal trends in lung cancer risk factors across small areas support the hypothesis that past interventions have been equally effective across the state. However, this also means that spatial inequalities have remained unaddressed, highlighting the potential for future interventions, particularly among remote areas.

A hybrid of modified PSO and local search on a multi-robot search system

Particle swarm optimization (PSO), a new population based algorithm, has recently been used on multi-robot systems. Although this algorithm is applied to solve many optimization problems as well as multi-robot systems, it has some drawbacks when it is applied on multi-robot search systems to find a target in a search space containing big static obstacles. One of these defects is premature convergence. This means that one of the properties of basic PSO is that when particles are spread in a search space, as time increases they tend to converge in a small area. This shortcoming is also evident on a multi-robot search system, particularly when there are big static obstacles in the search space that prevent the robots from finding the target easily; therefore, as time increases, based on this property they converge to a small area that may not contain the target and become entrapped in that area.Another shortcoming is that basic PSO cannot guarantee the global convergence of the algorithm. In other words, initially particles explore different areas, but in some cases they are not good at exploiting promising areas, which will increase the search time.This study proposes a method based on the particle swarm optimization (PSO) technique on a multi-robot system to find a target in a search space containing big static obstacles. This method is not only able to overcome the premature convergence problem but also establishes an efficient balance between exploration and exploitation and guarantees global convergence, reducing the search time by combining with a local search method, such as A-star.To validate the effectiveness and usefulness of algorithms,a simulation environment has been developed for conducting simulation-based experiments in different scenarios and for reporting experimental results. These experimental results have demonstrated that the proposed method is able to overcome the premature convergence problem and guarantee global convergence.

Comparing multilevel and Bayesian spatial random effects survival models to assess geographical inequalities in colorectal cancer survival: a case study

Background Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Methods Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia. Results Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. Conclusions With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings

Predicting health programme participation: A gravity‐based, hierarchical modelling approach

Statistical analyses of health program participation seek to address a number of objectives compatible with the evaluation of demand for current resources. In this spirit, a spatial hierarchical model is developed for disentangling patterns in participation at the small area level, as a function of population-based demand and additional variation. For the former, a constrained gravity model is proposed to quantify factors associated with spatial choice and account for competition effects, for programs delivered by multiple clinics. The implications of gravity model misspecification within a mixed effects framework are also explored. The proposed model is applied to participation data from a no-fee mammography program in Brisbane, Australia. Attention is paid to the interpretation of various model outputs and their relevance for public health policy.

A new tip area function for instrumented nanoindentation at extremely small contact depths

The accuracy of measurement of mechanical properties of a material using instrumented nanoindentation at extremely small penetration depths heavily relies on the determination of the contact area of the indenter. Our experiments have demonstrated that the conventional area function could lead to a significant error when the contact depth was below 40. nm, due to the singularity in the first derivation of the function in this region and thus, the resultant unreasonable sharp peak on the function curve. In this paper, we proposed a new area function that was used to calculate the contact area for the indentations where the contact depths varied from 10 to 40. nm. The experimental results have shown that the new area function has produced better results than the conventional function. © 2011 Elsevier B.V.

A multilevel study of area socio-economic status and food purchasing behaviour

Objective: This study examined the association between area socioeconomic status (SES) and food purchasing behaviour.----- Setting: Melbourne city, Australia, 2003.----- Participants: Residents of 2,564 households located in 50 small areas.----- Design: Data were collected by mail survey (64.2% response rate). Area SES was indicated by the proportion of households in each area earning less than Aus$400 per week, and individual-level socioeconomic position was measured using education, occupation, and household income. Food purchasing was measured on the basis of compliance with dietary guideline recommendations (for grocery foods) and variety of fruit and vegetable purchase. Multilevel regression examined the association between area SES and food purchase after adjustment for individual-level demographic (age, sex, household composition) and socioeconomic factors.----- Results: Residents of low SES areas were significantly less likely than their counterparts in advantaged areas to purchase grocery foods that were high in fibre and low in fat, salt, and sugar; and they purchased a smaller variety of fruits. There was no evidence of an association between area SES and vegetable variety.----- Conclusions In Melbourne, area SES was associated with some food purchasing behaviours independent of individual-level factors, suggesting that areas in this city may be differentiated on the basis of food availability, accessibility, and affordability, making the purchase of some types of foods more difficult in disadvantaged areas.

Effect of optical aberrations on the color appearance of small defocused lights

We investigated influences of optics and surround area on color appearance of defocused, small narrow band photopic lights (1’ arc diameter, λmax 510 - 628 nm) centered within a black annulus and surrounded by a white field. Participants included seven normal trichromats with L- or M-cone biased ratios. We controlled chromatic aberration with elements of a Powell achromatizing lens and corrected higher-order aberrations with an adaptive-optics system. Longitudinal chromatic aberrations, but not monochromatic aberrations, are involved in changing appearance of small lights with defocus. Surround field structure is important because color changes were not observed when lights were presented on a uniform white surround.

Physical characteristics of small ions and their interaction with ultrafine particles in the urban environment

In recent years, the effect of ions and ultrafine particles on ambient air quality and human health has been well documented, however, knowledge about their sources, concentrations and interactions within different types of urban environments remains limited. This thesis presents the results of numerous field studies aimed at quantifying variations in ion concentration with distance from the source, as well as identifying the dynamics of the particle ionisation processes which lead to the formation of charged particles in the air. In order to select the most appropriate measurement instruments and locations for the studies, a literature review was also conducted on studies that reported ion and ultrafine particle emissions from different sources in a typical urban environment. The initial study involved laboratory experiments on the attachment of ions to aerosols, so as to gain a better understanding of the interaction between ions and particles. This study determined the efficiency of corona ions at charging and removing particles from the air, as a function of different particle number and ion concentrations. The results showed that particle number loss was directly proportional to particle charge concentration, and that higher small ion concentrations led to higher particle deposition rates in all size ranges investigated. Nanoparticles were also observed to decrease with increasing particle charge concentration, due to their higher Brownian mobility and subsequent attachment to charged particles. Given that corona discharge from high voltage powerlines is considered one of the major ion sources in urban areas, a detailed study was then conducted under three parallel overhead powerlines, with a steady wind blowing in a perpendicular direction to the lines. The results showed that large sections of the lines did not produce any corona at all, while strong positive emissions were observed from discrete components such as a particular set of spacers on one of the lines. Measurements were also conducted at eight upwind and downwind points perpendicular to the powerlines, spanning a total distance of about 160m. The maximum positive small and large ion concentrations, and DC electric field were observed at a point 20 m downwind from the lines, with median values of 4.4×103 cm-3, 1.3×103 cm-3 and 530 V m-1, respectively. It was estimated that, at this point, less than 7% of the total number of particles was charged. The electrical parameters decreased steadily with increasing downwind distance from the lines but remained significantly higher than background levels at the limit of the measurements. Moreover, vehicles are one of the most prevalent ion and particle emitting sources in urban environments, and therefore, experiments were also conducted behind a motor vehicle exhaust pipe and near busy motorways, with the aim of quantifying small ion and particle charge concentration, as well as their distribution as a function of distance from the source. The study found that approximately equal numbers of positive and negative ions were observed in the vehicle exhaust plume, as well as near motorways, of which heavy duty vehicles were believed to be the main contributor. In addition, cluster ion concentration was observed to decrease rapidly within the first 10-15 m from the road and ion-ion recombination and ion-aerosol attachment were the most likely cause of ion depletion, rather than dilution and turbulence related processes. In addition to the above-mentioned dominant ion sources, other sources also exist within urban environments where intensive human activities take place. In this part of the study, airborne concentrations of small ions, particles and net particle charge were measured at 32 different outdoor sites in and around Brisbane, Australia, which were classified into seven different groups as follows: park, woodland, city centre, residential, freeway, powerlines and power substation. Whilst the study confirmed that powerlines, power substations and freeways were the main ion sources in an urban environment, it also suggested that not all powerlines emitted ions, only those with discrete corona discharge points. In addition to the main ion sources, higher ion concentrations were also observed environments affected by vehicle traffic and human activities, such as the city centre and residential areas. A considerable number of ions were also observed in a woodland area and it is still unclear if they were emitted directly from the trees, or if they originated from some other local source. Overall, it was found that different types of environments had different types of ion sources, which could be classified as unipolar or bipolar particle sources, as well as ion sources that co-exist with particle sources. In general, fewer small ions were observed at sites with co-existing sources, however particle charge was often higher due to the effect of ion-particle attachment. In summary, this study quantified ion concentrations in typical urban environments, identified major charge sources in urban areas, and determined the spatial dispersion of ions as a function of distance from the source, as well as their controlling factors. The study also presented ion-aerosol attachment efficiencies under high ion concentration conditions, both in the laboratory and in real outdoor environments. The outcomes of these studies addressed the aims of this work and advanced understanding of the charge status of aerosols in the urban environment.

The effect of very small air gaps on small field dosimetry

The purpose of this study was to investigate the effect of very small air gaps (less than 1 mm) on the dosimetry of small photon fields used for stereotactic treatments. Measurements were performed with optically stimulated luminescent dosimeters (OSLDs) for 6 MV photons on a Varian 21iX linear accelerator with a Brainlab μMLC attachment for square field sizes down to 6 mm × 6 mm. Monte Carlo simulations were performed using EGSnrc C++ user code cavity. It was found that the Monte Carlo model used in this study accurately simulated the OSLD measurements on the linear accelerator. For the 6 mm field size, the 0.5 mm air gap upstream to the active area of the OSLD caused a 5.3 % dose reduction relative to a Monte Carlo simulation with no air gap. A hypothetical 0.2 mm air gap caused a dose reduction > 2 %, emphasizing the fact that even the tiniest air gaps can cause a large reduction in measured dose. The negligible effect on an 18 mm field size illustrated that the electronic disequilibrium caused by such small air gaps only affects the dosimetry of the very small fields. When performing small field dosimetry, care must be taken to avoid any air gaps, as can be often present when inserting detectors into solid phantoms. It is recommended that very small field dosimetry is performed in liquid water. When using small photon fields, sub-millimetre air gaps can also affect patient dosimetry if they cannot be spatially resolved on a CT scan. However the effect on the patient is debatable as the dose reduction caused by a 1 mm air gap, starting out at 19% in the first 0.1 mm behind the air gap, decreases to < 5 % after just 2 mm, and electronic equilibrium is fully re-established after just 5 mm.

A waste management system for small and medium enterprises engaged in office building retrofit projects

Waste management and minimisation is considered to be an important issue for achieving sustainability in the construction industry. Retrofit projects generate less waste than demolitions and new builds, but they possess unique features and require waste management approaches that are different to traditional new builds. With the increasing demand for more energy efficient and environmentally sustainable office spaces, the office building retrofit market is growing in capital cities around Australia with a high level of refurbishment needed for existing aging properties. Restricted site space and uncertain delivery process in these projects make it a major challenge to manage waste effectively. The labour-intensive nature of retrofit projects creates the need for the involvement of small and medium enterprises (SMEs) as subcontractors in on-site works. SMEs are familiar with on-site waste generation but are not as actively motivated and engaged in waste management activities as the stakeholders in other construction projects in the industry. SMEs’ responsibilities for waste management in office building retrofit projects need to be identified and adapted to the work delivery processes and the waste management system supported by project stakeholders. The existing literature provides an understanding of how to manage construction waste that is already generated and how to increase the waste recovery rate for office building retrofit projects. However, previous research has not developed theories or practical solutions that can guide project stakeholders to understand the specific waste generation process and effectively plan for and manage waste in ongoing project works. No appropriate method has been established for the potential role and capability of SMEs to manage and minimise waste from their subcontracting works. This research probes into the characteristics of office building retrofit project delivery with the aim to develop specific tools to manage waste and incorporate SMEs in this process in an appropriate and effective way. Based on an extensive literature review, the research firstly developed a questionnaire survey to identify the critical factors of on-site waste generation in office building retrofit projects. Semi-structured interviews were then utilised to validate the critical waste factors and establish the interrelationships between the factors. The interviews served another important function of identifying the current problems of waste management in the industry and the performance of SMEs in this area. Interviewees’ opinions on remedies to the problems were also collected. On the foundation of the findings from the questionnaire survey and semi-structured interviews, two waste planning and management strategies were identified for the dismantling phase and fit-out phase of office building retrofit projects, respectively. Two models were then established to organize SMEs’ waste management activities, including a work process-based integrated waste planning model for the dismantling phase and a system dynamics model for the fit-out phase. In order to apply the models in real practice, procedures were developed to guide SMEs’ work flow in on-site waste planning and management. In addition, a collaboration framework was established for SMEs and other project stakeholders for effective waste planning and management. Furthermore, an organisational engagement strategy was developed to improve SME waste management practices. Three case studies were conducted to validate and finalise the research deliverables. This research extends the current literature that mostly covers waste management plans in new build projects, by presenting the knowledge and understanding of addressing waste problems in retrofit projects. It provides practical tools and guidance for industry practitioners to effectively manage the waste generation processes in office building retrofit projects. It can also promote industry-level recognition of the role of SMEs and their performance in on-site waste management.

Phase III trial comparing paclitaxel poliglumex (CT-2103, PPX) in combination with carboplatin versus standard paclitaxel and carboplatin in the treatment of PS 2 patients with chemotherapy-naïve advanced non-small cell lung cancer

INTRODUCTION: Performance status (PS) 2 patients with non-small cell lung cancer (NSCLC) experience more toxicity, lower response rates, and shorter survival times than healthier patients treated with standard chemotherapy. Paclitaxel poliglumex (PPX), a macromolecule drug conjugate of paclitaxel and polyglutamic acid, reduces systemic exposure to peak concentrations of free paclitaxel and may lead to increased concentrations in tumors due to enhanced vascular permeability. METHODS: Chemotherapy-naive PS 2 patients with advanced NSCLC were randomized to receive carboplatin (area under the curve = 6) and either PPX (210 mg/m/10 min without routine steroid premedication) or paclitaxel (225 mg/m/3 h with standard premedication) every 3 weeks. The primary end point was overall survival. RESULTS: A total of 400 patients were enrolled. Alopecia, arthralgias/myalgias, and cardiac events were significantly less frequent with PPX/carboplatin, whereas grade ≥3 neutropenia and grade 3 neuropathy showed a trend of worsening. There was no significant difference in the incidence of hypersensitivity reactions despite the absence of routine premedication in the PPX arm. Overall survival was similar between treatment arms (hazard ratio, 0.97; log rank p = 0.769). Median and 1-year survival rates were 7.9 months and 31%, for PPX versus 8 months and 31% for paclitaxel. Disease control rates were 64% and 69% for PPX and paclitaxel, respectively. Time to progression was similar: 3.9 months for PPX/carboplatin versus 4.6 months for paclitaxel/carboplatin (p = 0.210). CONCLUSION: PPX/carboplatin failed to provide superior survival compared with paclitaxel/carboplatin in the first-line treatment of PS 2 patients with NSCLC, but the results with respect to progression-free survival and overall survival were comparable and the PPX regimen was more convenient. © 2008International Association for the Study of Lung Cancer.