Mortality, fertility, and persistent income inequality

Many developing countries are plagued by persistent inequality in income distribution. While a growing body of economic-demographic literature emphasizes differential fertility channel, this paper investigates differential child mortality--differences in child mortality across income groups--as a critical link through which income inequality persists. Using an overlapping generations model in which both child mortality and fertility are endogenously determined by parental choice, this paper demonstrates that differential child mortality and its interaction with differential fertility may generate an "income inequality trap." The trap is characterized by higher child mortality and lower degree of skill formation among the poorer households. The model can also explain the behavior of aggregate fertility and mortality rates for countries at various stages of development, consonant with patterns of demographic transition. The results indicate that provision of public health that raises the productivity of private health spending may be an effective way to reduce income inequality

Theorising a model for teaching and assessing reflective learning in higher education

The importance of reflection in higher education, and across disciplinary fields is widely recognised; it is generally included in university graduate attributes, professional standards and program objectives. Furthermore, reflection is commonly embedded into assessment requirements in higher education subjects, often without necessary scaffolding or clear expectations for students. Despite the rhetoric around the importance of reflection for ongoing learning, there is scant literature on any systematic, developmental approach to teaching reflective learning across higher education programs/courses. Given that professional or academic reflection is not intuitive, and requires specific pedagogic intervention to do well, a program/course-wide approach is essential. This paper draws on current literature to theorise a new, transferable and customisable model for teaching and assessing reflective learning across higher education, which foregrounds and explains the pedagogic field of higher education as a multi-dimensional space. We argue that explicit and strategic pedagogic intervention, supported by dynamic resources, is necessary for successful, broad-scale approaches to reflection in higher education.

Parameter estimation for a phenomenological model of the cardiac action potential

The action potential (ap) of a cardiac cell is made up of a complex balance of ionic currents which flow across the cell membrane in response to electrical excitation of the cell. Biophysically detailed mathematical models of the ap have grown larger in terms of the variables and parameters required to model new findings in subcellular ionic mechanisms. The fitting of parameters to such models has seen a large degree of parameter and module re-use from earlier models. An alternative method for modelling electrically exciteable cardiac tissue is a phenomenological model, which reconstructs tissue level ap wave behaviour without subcellular details. A new parameter estimation technique to fit the morphology of the ap in a four variable phenomenological model is presented. An approximation of a nonlinear ordinary differential equation model is established that corresponds to the given phenomenological model of the cardiac ap. The parameter estimation problem is converted into a minimisation problem for the unknown parameters. A modified hybrid Nelder–Mead simplex search and particle swarm optimization is then used to solve the minimisation problem for the unknown parameters. The successful fitting of data generated from a well known biophysically detailed model is demonstrated. A successful fit to an experimental ap recording that contains both noise and experimental artefacts is also produced. The parameter estimation method’s ability to fit a complex morphology to a model with substantially more parameters than previously used is established.

A Krylov-based finite state projection algorithm for solving the chemical master equation arising in the discrete modelling of biological systems

Biochemical reactions underlying genetic regulation are often modelled as a continuous-time, discrete-state, Markov process, and the evolution of the associated probability density is described by the so-called chemical master equation (CME). However the CME is typically difficult to solve, since the state-space involved can be very large or even countably infinite. Recently a finite state projection method (FSP) that truncates the state-space was suggested and shown to be effective in an example of a model of the Pap-pili epigenetic switch. However in this example, both the model and the final time at which the solution was computed, were relatively small. Presented here is a Krylov FSP algorithm based on a combination of state-space truncation and inexact matrix-vector product routines. This allows larger-scale models to be studied and solutions for larger final times to be computed in a realistic execution time. Additionally the new method computes the solution at intermediate times at virtually no extra cost, since it is derived from Krylov-type methods for computing matrix exponentials. For the purpose of comparison the new algorithm is applied to the model of the Pap-pili epigenetic switch, where the original FSP was first demonstrated. Also the method is applied to a more sophisticated model of regulated transcription. Numerical results indicate that the new approach is significantly faster and extendable to larger biological models.

A continuous time model for election timing

We consider a continuous time model for election timing in a Majoritarian Parliamentary System where the government maintains a constitutional right to call an early election. Our model is based on the two-party-preferred data that measure the popularity of the government and the opposition over time. We describe the poll process by a Stochastic Differential Equation (SDE) and use a martingale approach to derive a Partial Differential Equation (PDE) for the government’s expected remaining life in office. A comparison is made between a three-year and a four-year maximum term and we also provide the exercise boundary for calling an election. Impacts on changes in parameters in the SDE, the probability of winning the election and maximum terms on the call exercise boundaries are discussed and analysed. An application of our model to the Australian Federal Election for House of Representatives is also given.

Analysis of rural activity spaces and transport disadvantage using a multi-method approach

Current knowledge about the relationship between transport disadvantage and activity space size is limited to urban areas, and as a result, very little is known about this link in a rural context. In addition, although research has identified transport disadvantaged groups based on their size of activity space, these studies have, however, not empirically explained such differences and the result is often a poor identification of the problems facing disadvantaged groups. Research has shown that transport disadvantage varies over time. The static nature of analysis using the activity space concept in previous research studies has lacked the ability to identify transport disadvantage in time. Activity space is a dynamic concept; and therefore possesses a great potential in capturing temporal variations in behaviour and access opportunities. This research derives measures of the size and fullness of activity spaces for 157 individuals for weekdays, weekends, and for a week using weekly activity-travel diary data from three case study areas located in rural Northern Ireland. Four focus groups were also conducted in order to triangulate quantitative findings and to explain the differences between different socio-spatial groups. The findings of this research show that despite having a smaller sized activity space, individuals were not disadvantaged because they were able to access their required activities locally. Car-ownership was found to be an important life line in rural areas. Temporal disaggregation of the data reveals that this is true only on weekends due to a lack of public transport services. In addition, despite activity spaces being at a similar size, the fullness of activity spaces of low-income individuals was found to be significantly lower compared to their high-income counterparts. Focus group data shows that financial constraint, poor connections both between public transport services and between transport routes and opportunities forced individuals to participate in activities located along the main transport corridors.

3D ellipsoid fitting for multi-view gait recognition

Gait recognition approaches continue to struggle with challenges including view-invariance, low-resolution data, robustness to unconstrained environments, and fluctuating gait patterns due to subjects carrying goods or wearing different clothes. Although computationally expensive, model based techniques offer promise over appearance based techniques for these challenges as they gather gait features and interpret gait dynamics in skeleton form. In this paper, we propose a fast 3D ellipsoidal-based gait recognition algorithm using a 3D voxel model derived from multi-view silhouette images. This approach directly solves the limitations of view dependency and self-occlusion in existing ellipse fitting model-based approaches. Voxel models are segmented into four components (left and right legs, above and below the knee), and ellipsoids are fitted to each region using eigenvalue decomposition. Features derived from the ellipsoid parameters are modeled using a Fourier representation to retain the temporal dynamic pattern for classification. We demonstrate the proposed approach using the CMU MoBo database and show that an improvement of 15-20% can be achieved over a 2D ellipse fitting baseline.

Quantification of particle emission characteristics and development of an emission model for use in transport microenvironments affected by traffic emissions

Vehicle emitted particles are of significant concern based on their potential to influence local air quality and human health. Transport microenvironments usually contain higher vehicle emission concentrations compared to other environments, and people spend a substantial amount of time in these microenvironments when commuting. Currently there is limited scientific knowledge on particle concentration, passenger exposure and the distribution of vehicle emissions in transport microenvironments, partially due to the fact that the instrumentation required to conduct such measurements is not available in many research centres. Information on passenger waiting time and location in such microenvironments has also not been investigated, which makes it difficult to evaluate a passenger’s spatial-temporal exposure to vehicle emissions. Furthermore, current emission models are incapable of rapidly predicting emission distribution, given the complexity of variations in emission rates that result from changes in driving conditions, as well as the time spent in driving condition within the transport microenvironment. In order to address these scientific gaps in knowledge, this work conducted, for the first time, a comprehensive statistical analysis of experimental data, along with multi-parameter assessment, exposure evaluation and comparison, and emission model development and application, in relation to traffic interrupted transport microenvironments. The work aimed to quantify and characterise particle emissions and human exposure in the transport microenvironments, with bus stations and a pedestrian crossing identified as suitable research locations representing a typical transport microenvironment. Firstly, two bus stations in Brisbane, Australia, with different designs, were selected to conduct measurements of particle number size distributions, particle number and PM2.5 concentrations during two different seasons. Simultaneous traffic and meteorological parameters were also monitored, aiming to quantify particle characteristics and investigate the impact of bus flow rate, station design and meteorological conditions on particle characteristics at stations. The results showed higher concentrations of PN20-30 at the station situated in an open area (open station), which is likely to be attributed to the lower average daily temperature compared to the station with a canyon structure (canyon station). During precipitation events, it was found that particle number concentration in the size range 25-250 nm decreased greatly, and that the average daily reduction in PM2.5 concentration on rainy days compared to fine days was 44.2 % and 22.6 % at the open and canyon station, respectively. The effect of ambient wind speeds on particle number concentrations was also examined, and no relationship was found between particle number concentration and wind speed for the entire measurement period. In addition, 33 pairs of average half-hourly PN7-3000 concentrations were calculated and identified at the two stations, during the same time of a day, and with the same ambient wind speeds and precipitation conditions. The results of a paired t-test showed that the average half-hourly PN7-3000 concentrations at the two stations were not significantly different at the 5% confidence level (t = 0.06, p = 0.96), which indicates that the different station designs were not a crucial factor for influencing PN7-3000 concentrations. A further assessment of passenger exposure to bus emissions on a platform was evaluated at another bus station in Brisbane, Australia. The sampling was conducted over seven weekdays to investigate spatial-temporal variations in size-fractionated particle number and PM2.5 concentrations, as well as human exposure on the platform. For the whole day, the average PN13-800 concentration was 1.3 x 104 and 1.0 x 104 particle/cm3 at the centre and end of the platform, respectively, of which PN50-100 accounted for the largest proportion to the total count. Furthermore, the contribution of exposure at the bus station to the overall daily exposure was assessed using two assumed scenarios of a school student and an office worker. It was found that, although the daily time fraction (the percentage of time spend at a location in a whole day) at the station was only 0.8 %, the daily exposure fractions (the percentage of exposures at a location accounting for the daily exposure) at the station were 2.7% and 2.8 % for exposure to PN13-800 and 2.7% and 3.5% for exposure to PM2.5 for the school student and the office worker, respectively. A new parameter, “exposure intensity” (the ratio of daily exposure fraction and the daily time fraction) was also defined and calculated at the station, with values of 3.3 and 3.4 for exposure to PN13-880, and 3.3 and 4.2 for exposure to PM2.5, for the school student and the office worker, respectively. In order to quantify the enhanced emissions at critical locations and define the emission distribution in further dispersion models for traffic interrupted transport microenvironments, a composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. This model does not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bidirectional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. The CLSE model was also applied at a signalled pedestrian crossing, in order to assess increased particle number emissions from motor vehicles when forced to stop and accelerate from rest. The CLSE model was used to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses including 1 car travelling in 1 direction (/1 direction), 14 cars / 1 direction, 1 bus / 1 direction, 28 cars / 2 directions, 24 cars and 2 buses / 2 directions, and 20 cars and 4 buses / 2 directions. It was found that the total emissions produced during stopping on a red signal were significantly higher than when the traffic moved at a steady speed. Overall, total emissions due to the interruption of the traffic increased by a factor of 13, 11, 45, 11, 41, and 43 for the above 6 cases, respectively. In summary, this PhD thesis presents the results of a comprehensive study on particle number and mass concentration, together with particle size distribution, in a bus station transport microenvironment, influenced by bus flow rates, meteorological conditions and station design. Passenger spatial-temporal exposure to bus emitted particles was also assessed according to waiting time and location along the platform, as well as the contribution of exposure at the bus station to overall daily exposure. Due to the complexity of the interrupted traffic flow within the transport microenvironments, a unique CLSE model was also developed, which is capable of quantifying emission levels at critical locations within the transport microenvironment, for the purpose of evaluating passenger exposure and conducting simulations of vehicle emission dispersion. The application of the CLSE model at a pedestrian crossing also proved its applicability and simplicity for use in a real-world transport microenvironment.

Practical improvements to simultaneous computation of multi-view geometry and radial lens distortion

This paper discusses practical issues related to the use of the division model for lens distortion in multi-view geometry computation. A data normalisation strategy is presented, which has been absent from previous discussions on the topic. The convergence properties of the Rectangular Quadric Eigenvalue Problem solution for computing division model distortion are examined. It is shown that the existing method can require more than 1000 iterations when dealing with severe distortion. A method is presented for accelerating convergence to less than 10 iterations for any amount of distortion. The new method is shown to produce equivalent or better results than the existing method with up to two orders of magnitude reduction in iterations. Through detailed simulation it is found that the number of data points used to compute geometry and lens distortion has a strong influence on convergence speed and solution accuracy. It is recommended that more than the minimal number of data points be used when computing geometry using a robust estimator such as RANSAC. Adding two to four extra samples improves the convergence rate and accuracy sufficiently to compensate for the increased number of samples required by the RANSAC process.

Congo Red adsorption by ball-milled sugarcane bagasse

The adsorption of Congo Red (CR) by ball-milled sugarcane bagasse was evaluated in an aqueous batch system. CR adsorption capacity increased significantly with small changes in bagasse surface area. CR removal decreased with increasing solution pH from 5.0 to 10.0. Maximum adsorption capacity was 38.2 mg/g bagasse at a CR concentration of 500 mg/L. The equilibrium isotherm fitted the Freundlich model and the adsorption kinetics obeyed pseudo-second order equation. CR adsorption obeyed the intra-particle diffusion model very well with bagasse surface area in the range of 0.58–0.66 m2/g, whereas it was controlled by multi-adsorption stages with bagasse surface area in the range of 1.31–1.82 m2/g. Thermodynamic analysis indicated that the adsorption process is an exothermic and spontaneous process. Fourier transform infrared analysis of bagasse containing adsorbed CR indicated interactions between the carboxyl and hydroxyl groups of bagasse and CR function groups.

Towards testing a new first-order decision making model for the procurement of public sector major infrastructure

Given global demand for new infrastructure, governments face substantial challenges in funding new infrastructure and simultaneously delivering Value for Money (VfM). As background to this challenge, a brief review is given of current practice in the selection of major public sector infrastructure in Australia, along with a review of the related literature concerning the Multi-Attribute Utility Approach (MAUA) and the effect of MAUA on the role of risk management in procurement selection. To contribute towards addressing the key weaknesses of MAUA, a new first-order procurement decision making model is mentioned. A brief summary is also given of the research method and hypothesis used to test and develop the new procurement model and which uses competition as the dependent variable and as a proxy for VfM. The hypothesis is given as follows: When the actual procurement mode matches the theoretical/predicted procurement mode (informed by the new procurement model), then actual competition is expected to match optimum competition (based on actual prevailing capacity vis-à-vis the theoretical/predicted procurement mode) and subject to efficient tendering. The aim of this paper is to report on progress towards testing this hypothesis in terms of an analysis of two of the four data components in the hypothesis. That is, actual procurement and actual competition across 87 road and health major public sector projects in Australia. In conclusion, it is noted that the Global Financial Crisis (GFC) has seen a significant increase in competition in public sector major road and health infrastructure and if any imperfections in procurement and/or tendering are discernible, then this would create the opportunity, through the deployment of economic principles embedded in the new procurement model and/or adjustments in tendering, to maintain some of this higher level post-GFC competition throughout the next business cycle/upturn in demand including private sector demand. Finally, the paper previews the next steps in the research with regard to collection and analysis of data concerning theoretical/predicted procurement and optimum competition.

Collaboration : developing integration in multi-purpose services in rural New South Wales, Australia

Introduction: The Multi-purpose Service (MPS) Program was introduced to rural Australia in 1991 as a solution to poor health outcomes in rural compared with metropolitan populations, difficulty in attracting healthcare staff and a lack of viability and range of health services in rural areas. The aim of this study was to describe the main concerns of participants involved in the development of multi-purpose services in rural New South Wales (NSW). This article is abstracted from a larger study and discusses the extent to which collaboration occurred within the new multi-purpose service. Methods: A constructivist grounded theory methodology was used. Participants were from 13 multi-purpose services in rural NSW and 30 in-depth interviews were conducted with 6 community members, 11 managers and 13 staff members who had been involved in the process of developing a multi-purpose service. Results: The main concern of all participants was their anticipation of risk. This anticipation of risk manifested itself in either trust or suspicion and explained their progression through a phase of collaborating. Participants who had trust in other stakeholders were more likely to embrace an integrated health service identity. Those participants, who were suspicious that they would lose status or power, maintained that the previous hospital services provided a better health service and described a coexistence of services within the multi-purpose service. Conclusions: This study provided an insight into the perceptions of community members, staff members and managers involved in the process of developing a multi-purpose service. It revealed that the anticipation of risk was intrinsic to a process of changing from a traditional hospital service to collaborating in a new model of health care provided at a multi-purpose service.

Value co-creation in social marketing wellness services

Customer perceived value is concerned with the experiences of consumers when using a service and is often referred to in the context of service provision or on the basis of service quality (Auh, et al., 2007; Chang, 2008; Jackson, 2007; Laukkanen, 2007; Padgett & Mulvey, 2007; Shamdasani, Mukherjee & Malhotra, 2008). Understanding customer perceived value has benefits for social marketing and allows scholars and practitioners alike to identify why consumers engage in positive social behaviours through the use of services. Understanding consumers’ use of wellness services in particular is important, because the use of wellness services demonstrates the fulfilment of social marketing aims; performing pro-active, positive social behaviours that are of benefit to the individual and to society (Andreasen, 1994). As consumers typically act out of self-interest (Rothschild, 1999), this research posits that a value proposition must be made to consumers in order to encourage behavioural change. Thus, this research seeks to identify how value is created for consumers of wellness services in social marketing. This results in the overall research question of this research: How is value created in social marketing wellness services? A traditional method towards understanding value has been the adoption of an economic approach, which considers the utility gained and where value is a direct outcome of a cost-benefit analysis (Payne & Holt, 1999). However, there has since been a shift towards the adoption of an experiential approach in understanding value. This experiential approach considers the consumption experience of the consumer which extends beyond the service exchange and includes pre- and post-consumption stages (Russell-Bennett, Previte & Zainuddin, 2009). As such, this research uses an experiential approach to identify the value that exists in social marketing wellness services. Four dimensions of value have been commonly conceptualised and identified in the commercial marketing literature; functional, emotional, social, and altruistic value (Holbrook, 1994; Sheth, Newman & Gross, 1991; Sweeney & Soutar, 2001). It is not known if these value dimensions also exist in social marketing. In addition, sources of value said to influence value dimensions have been conceptualised in the literature. Sources of value such as information, interaction, environment, service, customer co-creation, and social mandate have been conceptually identified both in the commercial and social marketing literature (Russell-Bennet, Previte & Zainuddin, 2009; Smith & Colgate, 2007). However, it is not clear which sources of value contribute to the creation of value for users of wellness services. Thus, this research seeks to explore these relationships. This research was conducted using a wellness service context, specifically breast cancer screening services. The primary target consumer of these services is women aged 50 to 69 years old (inclusive) who have never been diagnosed with breast cancer. It is recommended that women in this target group have a breast screen every 2 years in order to achieve the most effective medical outcomes from screening. A two-study mixed method approach was utilised. Study 1 was a qualitative exploratory study that analysed individual-depth interviews with 25 information-rich respondents. The interviews were transcribed verbatim and analysed using NVivo 8 software. The qualitative results provided evidence of the existence of the four value dimensions in social marketing. The results also allowed for the development of a typology of experiential value by synthesising current understanding of the value dimensions, with the activity aspects of experiential value identified by Holbrook (1994) and Mathwick, Malhotra and Rigdon (2001). The qualitative results also provided evidence for the existence of sources of value in social marketing, namely information, interaction, environment and consumer participation. In particular, a categorisation of sources of value was developed as a result of the findings from Study 1, which identify organisational, consumer, and third party sources of value. A proposed model of value co-creation and a set of hypotheses were developed based on the results of Study 1 for further testing in Study 2. Study 2 was a large-scale quantitative confirmatory study that sought to test the proposed model of value co-creation and the hypotheses developed. An online-survey was administered Australia-wide to women in the target audience. A response rate of 20.1% was achieved, resulting in a final sample of 797 useable responses after removing ineligible respondents. Reliability and validity analyses were conducted on the data, followed by Exploratory Factor Analysis (EFA) in PASW18, followed by Confirmatory Factor Analysis (CFA) in AMOS18. Following the preliminary analyses, the data was subject to Structural Equation Modelling (SEM) in AMOS18 to test the path relationships hypothesised in the proposed model of value creation. The SEM output revealed that all hypotheses were supported, with the exception of one relationship which was non-significant. In addition, post hoc tests revealed seven further significant non-hypothesised relationships in the model. The quantitative results show that organisational sources of value as well as consumer participation sources of value influence both functional and emotional dimensions of value. The experience of both functional and emotional value in wellness services leads to satisfaction with the experience, followed by behavioural intentions to perform the behaviour and use the service again. One of the significant non-hypothesised relationships revealed that emotional value leads to functional value in wellness services, providing further empirical evidence that emotional value features more prominently than functional value for users of wellness services. This research offers several contributions to theory and practice. Theoretically, this research addresses a gap in the literature by using social marketing theory to provide an alternative method of understanding individual behaviour in a domain that has been predominantly investigated in public health. This research also clarifies the concept of value and offers empirical evidence to show that value is a multi-dimensional construct with separate and distinct dimensions. Empirical evidence for a typology of experiential value, as well as a categorisation of sources of value is also provided. In its practical contributions, this research identifies a framework that is the value creation process and offers health services organisations a diagnostic tool to identify aspects of the service process that facilitate the value creation process.

User behaviour modelling in a multi-dimensional environment for personalization and recommendation

Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

Test of a model of the effects of parental illness on youth and family functioning

Objective: Parental illness (PI) may have adverse impacts on youth and family functioning. Research in this area has suffered from the absence of a guiding comprehensive framework. This study tested a conceptual model of the effects of PI on youth and family functioning derived from the Family Ecology Framework (FEF; Pedersen & Revenson, 2005). Method. A total of 85 parents with multiple sclerosis and 127 youth completed questionnaires at Time 1 and 12 months later at Time 2. Results. Structural equation modeling results supported the FEF with regards to physical-illness disability. Specifically, the proposed mediators (role redistribution, stress, and stigma) were implicated in the processes that link parental disability to several domains of youth adjustment. The results suggest that the effects of parental depression (PD) are not mediated through these processes; rather, PD directly affects family functioning, which in turn mediates the effects onto youth adjustment. Family functioning further mediated between PD and youth well-being and behavioral-social difficulties. Conclusions. Although results support the effects of parental-illness disability on youth and family functioning via the proposed mediational mechanisms, the additive effects of PD on youth physical and mental health occur through direct and indirect (via family functioning) pathways, respectively.