The link between infrastructure charges and housing affordability in Australia: Where is the empirical evidence?

Developer paid charges or contributions are a commonly used infrastructure funding mechanism for local governments. However, developers claim that these costs are merely passed on to home buyers, with adverse effects to housing affordability. Despite a plethora of government reports and industry advocacy, there remains no empirical evidence in Australia to confirm or quantify this passing on effect to home buyers and hence no data for which governments to base policy decision upon. This paper examines the question of who really pays for urban infrastructure and the impact of infrastructure charges on housing affordability. It presents the findings of a number of international empirical studies that provide evidence that infrastructure charges do increase house prices. Based on international findings, and in the absence of any Australian research, then these findings suggest that if the international findings are transferable, then there is empirical evidence to support the proposition that developer paid infrastructure charges are a significant contributor to increasing house prices.

Promoting Statistical Literacy Through Data Modelling in the Early School Years

This chapter addresses data modelling as a means of promoting statistical literacy in the early grades. Consideration is first given to the importance of increasing young children’s exposure to statistical reasoning experiences and how data modelling can be a rich means of doing so. Selected components of data modelling are then reviewed, followed by a report on some findings from the third-year of a three-year longitudinal study across grades one through three.

Remote sensing and core data needed to support planning and policy decision making

A variety of sustainable development research efforts and related activities are attempting to reconcile the issues of conserving our natural resources without limiting economic motivation while also improving our social equity and quality of life. Land use/land cover change, occurring on a global scale, is an aggregate of local land use decisions and profoundly impacts our environment. It is therefore the local decision making process that should be the eventual target of many of the ongoing data collection and research efforts which strive toward supporting a sustainable future. Satellite imagery data is a primary source of data upon which to build a core data set for use by researchers in analyzing this global change. A process is necessary to link global change research, utilizing satellite imagery, to the local land use decision making process. One example of this is the NASA-sponsored Regional Data Center (RDC) prototype. The RDC approach is an attempt to integrate science and technology at the community level. The anticipated result of this complex interaction between research and the decision making communities will be realized in the form of long-term benefits to the public.

Is bus overrepresented in Bluetooth MAC Scanner data? Is MAC-ID really unique?

One of the concerns about the use of Bluetooth MAC Scanner (BMS) data, especially from urban arterial, is the bias in the travel time estimates from multiple Bluetooth devices being transported by a vehicle. For instance, if a bus is transporting 20 passengers with Bluetooth equipped mobile phones, then the discovery of these mobile phones by BMS will be considered as 20 different vehicles, and the average travel time along the corridor estimated from the BMS data will be biased with the travel time from the bus. This paper integrates Bus Vehicle Identification system with BMS network to empirically evaluate such bias, if any. The paper also reports an interesting finding on the uniqueness of MAC IDs.

Dispositional resistance to change : measurement equivalence and the link to personal values across 17 nations

The concept of dispositional resistance to change has been introduced in a series of exploratory and confirmatory analyses through which the validity of the Resistance to Change (RTC) Scale has been established (S. Oreg, 2003). However, the vast majority of participants with whom the scale was validated were from the United States. The purpose of the present work was to examine the meaningfulness of the construct and the validity of the scale across nations. Measurement equivalence analyses of data from 17 countries, representing 13 languages and 4 continents, confirmed the cross-national validity of the scale. Equivalent patterns of relationships between personal values and RTC across samples extend the nomological net of the construct and provide further evidence that dispositional resistance to change holds equivalent meanings across nations.

Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets

Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1–28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.

Investigating the link between transit oriented development and sustainable travel behavior in Brisbane : a case-control study

The purpose of this research is to empirically test the prevailing view that transit oriented development enhances the use of more sustainable modes of transport using Brisbane, Australia as a case. Transit oriented development has been adopted as a new policy tool to reduce car-based travel worldwide. Despite being a billion dollar investment, the impacts of transit oriented development on promoting sustainable travel behavior is not conclusive. The research uses a case-control approach to empirically investigate this relationship based on travel behavior data collected from 88 individuals living in two contrasting neighborhoods in Brisbane: Kelvin Grove Urban Village – a transit oriented development, and Annerley – a traditional suburb (non-transit oriented development). A comparative investigation of travel behavior was subsequently conducted using distance travelled by modes and purposes between the neighborhoods. Results show that the availability of opportunity and services located within the transit oriented development reduces the car use by 5% and increases the use of active transport by 4%. The findings in this research support the implementation of TOD policies in Brisbane.

Investigating the link between carbon dioxide emissions and transport-related social exclusion in rural Northern Ireland

Carbon dioxide (CO2) is considered the most harmful of the greenhouse gases. Despite policy efforts, transport is the only sector experiencing an increase in the level of CO2 emissions and thereby possesses a major threat to sustainable development. In contrast, a reduced level of mobility has been associated with an increasing risk of being socially excluded. However, despite being the two key elements in transport policy, little effort has so far been made to investigate the links between CO2 emissions and social exclusion. This research contributes to this gap by analysing data from 157 weekly activity-travel diaries collected in rural Northern Ireland. CO2 emission levels were calculated using average speed models for different modes of transport. Regression analyses were then conducted to identify the socio-spatial patterns associated with these CO2 emissions, mode choice behaviour, and patterns of participation in activities. This research found that despite emitting a higher level of carbon dioxide, groups in rural areas possess the risk of being socially excluded due to their higher levels of mobility.

Shortest path and vehicle trajectory aided map-matching for low frequency GPS data

Map-matching algorithms that utilise road segment connectivity along with other data (i.e.position, speed and heading) in the process of map-matching are normally suitable for high frequency (1 Hz or higher) positioning data from GPS. While applying such map-matching algorithms to low frequency data (such as data from a fleet of private cars, buses or light duty vehicles or smartphones), the performance of these algorithms reduces to in the region of 70% in terms of correct link identification, especially in urban and sub-urban road networks. This level of performance may be insufficient for some real-time Intelligent Transport System (ITS) applications and services such as estimating link travel time and speed from low frequency GPS data. Therefore, this paper develops a new weight-based shortest path and vehicle trajectory aided map-matching (stMM) algorithm that enhances the map-matching of low frequency positioning data on a road map. The well-known A* search algorithm is employed to derive the shortest path between two points while taking into account both link connectivity and turn restrictions at junctions. In the developed stMM algorithm, two additional weights related to the shortest path and vehicle trajectory are considered: one shortest path-based weight is related to the distance along the shortest path and the distance along the vehicle trajectory, while the other is associated with the heading difference of the vehicle trajectory. The developed stMM algorithm is tested using a series of real-world datasets of varying frequencies (i.e. 1 s, 5 s, 30 s, 60 s sampling intervals). A high-accuracy integrated navigation system (a high-grade inertial navigation system and a carrier-phase GPS receiver) is used to measure the accuracy of the developed algorithm. The results suggest that the algorithm identifies 98.9% of the links correctly for every 30 s GPS data. Omitting the information from the shortest path and vehicle trajectory, the accuracy of the algorithm reduces to about 73% in terms of correct link identification. The algorithm can process on average 50 positioning fixes per second making it suitable for real-time ITS applications and services.

The link between marketing instruments and customer perceptions

Measuring marketing effectiveness is a major challenge for marketing academics and practitioners. An investigation that uses dependence analysis to examine the link between objective marketing instruments and subjective customer perceptions of them is missing from existing approaches. In examining this link, the present article redresses this deficit. A conceptual model is developed in order to structure and explain the effects of instruments on perceptions for 3 marketing instrument categories (value, relationship, and brand). The links are analyzed in an empirical study with bank customers. Instruments are measured by using objective internal data. Perceptions are measured based on a customer survey. The relationships between instruments and perceptions are examined using regression analysis. Most of the effects of instruments on perceptions are significant, signaling that the activities conducted are perceived as intended. In particular, some interesting results become evident, such as the negative effect on relationship perceptions of follow-up calls subsequent to direct mail services.

Estimating link-dependent origin-destination matrices from sample trajectories and traffic counts

Origin-Destination matrices (ODM) estimation can benefits of the availability of sample trajectories which can be measured thanks to recent technologies. This paper focus on the case of transport networks where traffic counts are measured by magnetic loops and sample trajectories available. An example of such network is the city of Brisbane, where Bluetooth detectors are now operating. This additional data source is used to extend the classical ODM estimation to a link-specific ODM (LODM) one using a convex optimisation resolution that incorporates networks constraints as well. The proposed algorithm is assessed on a simulated network.

Is there a link between poverty and food security?

This paper addresses the gap in economic theory underlying the multidimensional concept of food security and observed data by deriving a composite food security index using the latent class model. The link between poverty and food security is then examined using the new food security index and the robustness of the link is compared with two unidimensional measures often used in the literature. Using Vietnam as a case study, it was found that a weak link exists for the rural but not for the urban composite food security index. The unidimensional measures on the other hand show a strong link in both the rural and urban regions. The results on the link are also different and mixed when two poverty types given by persistent and transient poverty are considered. These findings have important policy implications for a targeted approach to addressing food security.

A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. © 2013 Mechelli et al.

Epithiospecifier protein activity in broccoli: The link between terminal alkenyl glucosinolates and sulphoraphane nitrile

The chemical nature of the hydrolysis products from the glucosinolate-myrosinase system depends on the presence or absence of supplementary proteins, such as epithiospecifier proteins (ESPs). ESPs (non-catalytic cofactors of myrosinase) promote the formation of epithionitriles from terminal alkenyl glucosinolates and as recent evidence suggests, simple nitriles at the expense of isothiocyanates. The ratio of ESP activity to myrosinase activity is crucial in determining the proportion of these nitriles produced on hydrolysis. Sulphoraphane, a major isothiocyanate produced in broccoli seedlings, has been found to be a potent inducer of phase 2 detoxification enzymes. However, ESP may also support the formation of the non-inductive sulphoraphane nitrile. Our objective was to monitor changes in ESP activity during the development of broccoli seedlings and link these activity changes with myrosinase activity, the level of terminal alkenyl glucosinolates and sulphoraphane nitrile formed. Here, for the first time, we show ESP activity increases up to day 2 after germination before decreasing again to seed activity levels at day 5. These activity changes paralleled changes in myrosinase activity and terminal alkenyl glucosinolate content. There is a significant relationship between ESP activity and the formation of sulforaphane nitrile in broccoli seedlings. The significance of these findings for the health benefits conferred by eating broccoli seedlings is briefly discussed.

Crinkles in connectivity: combining genetics and other types of biological data to estimate movement and interbreeding between populations

Marine species generally have large population sizes, continuous distributions and high dispersal capacity. Despite this, they are often subdivided into separate populations, which are the basic units of fisheries management. For example, populations of some fisheries species across the deep water of the Timor Trench are genetically different, inferring minimal movement and interbreeding. When connectivity is higher than the Timor Trench example, but not so high that the populations become one, connectivity between populations is crinkled. Crinkled connectivity occurs when migration is above the threshold required to link populations genetically, but below the threshold for demographic links. In future, genetic estimates of connectivity over crinkled links could be uniquely combined with other data, such as estimates of population size and tagging and tracking data, to quantify demographic connectedness between these types of populations. Elasmobranch species may be ideal targets for this research because connectivity between populations is more likely to be crinkled than for finfish species. Fisheries stock-assessment models could be strengthened with estimates of connectivity to improve the strategic and sustainable harvesting of biological resources.