Age-related loss of brain volume and T2 relaxation time in youth with type 1 diabetes

OBJECTIVE: Childhood-onset type 1 diabetes is associated with neurocognitive deficits, but there is limited evidence to date regarding associated neuroanatomical brain changes and their relationship to illness variables such as age at disease onset. This report examines age-related changes in volume and T2 relaxation time (a fundamental parameter of magnetic resonance imaging that reflects tissue health) across the whole brain. RESEARCH DESIGN AND METHODS: Type 1 diabetes, N = 79 (mean age 20.32 ± 4.24 years), and healthy control participants, N = 50 (mean age 20.53 ± 3.60 years). There were no substantial group differences on socioeconomic status, sex ratio, or intelligence quotient. RESULTS: Regression analyses revealed a negative correlation between age and brain changes, with decreasing gray matter volume and T2 relaxation time with age in multiple brain regions in the type 1 diabetes group. In comparison, the age-related decline in the control group was small. Examination of the interaction of group and age confirmed a group difference (type 1 diabetes vs. control) in the relationship between age and brain volume/T2 relaxation time. CONCLUSIONS: We demonstrated an interaction between age and group in predicting brain volumes and T2 relaxation time such that there was a decline in these outcomes in type 1 diabetic participants that was much less evident in control subjects. Findings suggest the neurodevelopmental pathways of youth with type 1 diabetes have diverged from those of their healthy peers by late adolescence and early adulthood but the explanation for this phenomenon remains to be clarified.

Employer's management of part-time student labour

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"Silly hours" : facilitating more effective part-time work arrangements through job design

Part-time employment presents a conundrum in that it facilitates work-life priorities, while also, compared to equivalent full-time roles, attracting penalties such as diminished career prospects and lower commensurate remuneration. Recently, some promising theoretical developments in the job/work design literature suggest that consideration of work design may redress some of the penalties associated with part-time work. Adopting the framework of the Elaborated Model of Work Design by Parker and colleagues (2001), we examined this possibility through interviews with part-time professional service employees and their supervisors. The findings revealed that in organizations characterised by cultural norms of extended working hours and a singular-focused commitment to work, part-time roles were often inadequately re-designed when adapted from full-time arrangements. The findings also demonstrated that certain work design characteristics (e.g. predictability of work-flow, interdependencies with co-workers) render some roles more suitable for part-time arrangements than others. The research provides insights into gaps between policy objectives and outcomes associated with part-time work, challenges assumptions about the limitations of part-time roles, and suggests re-design strategies for more effective part-time arrangements.

Development of novel vaccine strategies to prevent genital tract chlamydial infections

Chlamydia trachomatis is the most prevalent bacterial sexually transmitted infection in the developed world and the leading cause of preventable blindness worldwide. As reported by the World Health Organization in 2001, there are approximately 92 million new infections detected annually, costing health systems billions of dollars to treat not only the acute infection, but also to treat infection-associated sequelae. The majority of genital infections are asymptomatic, with 50-70% going undetected. Genital tract infections can be easily treated with antibiotics when detected. Lack of treatment can lead to the development of pelvic inflammatory disease, ectopic pregnancies and tubal factor infertility in women and epididymitis and prostatitis in men. With infection rates on the continual rise and the large number of infections going undetected, there is a need to develop an efficacious vaccine which prevents not only infection, but also the development of infection-associated pathology. Before a vaccine can be developed and administered, the pathogenesis of chlamydial infections needs to be fully understood. This includes the kinetics of ascending infection and the effects of inoculating dose on ascension and development of pathology. The first aim in this study was to examine these factors in a murine model. Female BALB/c mice were infected intravaginally with varying doses of C. muridarum, the mouse variant of human C. trachomatis, and the ascension of infection along the reproductive tract and the time-course of infection-associated pathology development, including inflammatory cell infiltration, pyosalpinx and hydrosalpinx, were determined. It was found that while the inoculating dose did affect the rate and degree of infection, it did not affect any of the pathological parameters examined. This highlighted that the sexual transmission dose may have minimal effect on the development of reproductive sequelae. The results of the first section enabled further studies presented here to use an optimal inoculating dose that would ascend the reproductive tract and cause pathology development, so that vaccine efficacy could be determined. There has been a large amount of research into the development of an efficacious vaccine against genital tract chlamydial infections, with little success. However, there have been no studies examining the effects of the timing of vaccination, including the effects of vaccination during an active genital infection, or after clearance of a previous infection. These are important factors that need to be examined, as it is not yet known whether immunization will enhance not only the individual's immune response, but also pathology development. It is also unknown whether any enhancement of the immune responses will cause the Chlamydia to enter a dormant, persistent state, and possibly further enhance any pathology development. The second section of this study aimed to determine if vaccination during an active genital tract infection, or after clearance of a primary infection, enhanced the murine immune responses and whether any enhanced or reduced pathology occurred. Naïve, actively infected, or previously infected animals were immunized intranasally or transcutaneously with the adjuvants cholera toxin and CpG-ODN in combination with either the major outer membrane protein (MOMP) of C. muridarum, or MOMP and ribonucleotide reductase small chain protein (NrdB) of C. muridarum. It was found that the systemic immune responses in actively or previously infected mice were altered in comparison to animals immunized naïve with the same combinations, however mucosal antibodies were not enhanced. It was also found that there was no difference in pathology development between any of the groups. This suggests that immunization of individuals who may have an asymptomatic infection, or may have been previously exposed to a genital infection, may not benefit from vaccination in terms of enhanced immune responses against re-exposure. The final section of this study aimed to determine if the vaccination regimes mentioned above caused in vivo persistence of C. muridarum in the upper reproductive tracts of mice. As there has been no characterization of C. muridarum persistence in vitro, either ultrastructurally or via transcriptome analysis, this was the first aim of this section. Once it had been shown that C. muridarum could be induced into a persistent state, the gene transcriptional profiles of the selected persistent marker genes were used to determine if persistent infections were indeed present in the upper reproductive tracts of the mice. We found that intranasal immunization during an active infection induced persistent infections in the oviducts, but not the uterine horns, and that intranasal immunization after clearance of infection, caused persistent infections in both the uterine horns and the oviducts of the mice. This is a significant finding, not only because it is the first time that C. muridarum persistence has been characterized in vitro, but also due to the fact that there is minimal characterization of in vivo persistence of any chlamydial species. It is possible that the induction of persistent infections in the reproductive tract might enhance the development of pathology and thereby enhance the risk of infertility, factors that need to be prevented by vaccination, not enhanced. Overall, this study has shown that the inoculating dose does not affect pathology development in the female reproductive tract of infected mice, but does alter the degree and rate of ascending infection. It has also been shown that intranasal immunization during an active genital infection, or after clearance of one, induces persistent infections in the uterine horns and oviducts of mice. This suggests that potential vaccine candidates will need to have these factors closely examined before progressing to clinical trials. This is significant, because if the same situation occurs in humans, a vaccine administered to an asymptomatic, or previously exposed individual may not afford any extra protection and may in fact enhance the risk of development of infection-associated sequelae. This suggests that a vaccine may serve the community better if administered before the commencement of sexual activity.

Discovering the best feature extraction and selection algorithms for spontaneous facial expression recognition

Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.

A Bayesian‐Markov process for reliability prediction

Accurate reliability prediction for large-scale, long lived engineering is a crucial foundation for effective asset risk management and optimal maintenance decision making. However, a lack of failure data for assets that fail infrequently, and changing operational conditions over long periods of time, make accurate reliability prediction for such assets very challenging. To address this issue, we present a Bayesian-Marko best approach to reliability prediction using prior knowledge and condition monitoring data. In this approach, the Bayesian theory is used to incorporate prior information about failure probabilities and current information about asset health to make statistical inferences, while Markov chains are used to update and predict the health of assets based on condition monitoring data. The prior information can be supplied by domain experts, extracted from previous comparable cases or derived from basic engineering principles. Our approach differs from existing hybrid Bayesian models which are normally used to update the parameter estimation of a given distribution such as the Weibull-Bayesian distribution or the transition probabilities of a Markov chain. Instead, our new approach can be used to update predictions of failure probabilities when failure data are sparse or nonexistent, as is often the case for large-scale long-lived engineering assets.

Optimal coordination of overcurrent relays in distribution systems with distributed generators based on differential evolution algorithm

Distributed generators (DGs) are defined as generators that are connected to a distribution network. The direction of the power flow and short-circuit current in a network could be changed compared with one without DGs. The conventional protective relay scheme does not meet the requirement in this emerging situation. As the number and capacity of DGs in the distribution network increase, the problem of coordinating protective relays becomes more challenging. Given this background, the protective relay coordination problem in distribution systems is investigated, with directional overcurrent relays taken as an example, and formulated as a mixed integer nonlinear programming problem. A mathematical model describing this problem is first developed, and the well-developed differential evolution algorithm is then used to solve it. Finally, a sample system is used to demonstrate the feasiblity and efficiency of the developed method.

Optimal sitting and sizing of distributed generators considering plug-in electric vehicles

Some uncertainties such as the stochastic input/output power of a plug-in electric vehicle due to its stochastic charging and discharging schedule, that of a wind unit and that of a photovoltaic generation source, volatile fuel prices and future uncertain load growth, all together could lead to some risks in determining the optimal siting and sizing of distributed generators (DGs) in distributed systems. Given this background, under the chance constrained programming (CCP) framework, a new method is presented to handle these uncertainties in the optimal sitting and sizing problem of DGs. First, a mathematical model of CCP is developed with the minimization of DGs investment cost, operational cost and maintenance cost as well as the network loss cost as the objective, security limitations as constraints, the sitting and sizing of DGs as optimization variables. Then, a Monte Carolo simulation embedded genetic algorithm approach is developed to solve the developed CCP model. Finally, the IEEE 37-node test feeder is employed to verify the feasibility and effectiveness of the developed model and method. This work is supported by an Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) Project on Intelligent Grids Under the Energy Transformed Flagship, and Project from Jiangxi Power Company.

Time limitations in NAPLAN numeracy tests

The article discusses evidence that time prevented many students from showing what they could do in the 2010 Year 7 and 9 NAPLAN numeracy tests. In addition to analysing the available data, the article discusses some NAPLAN numeracy questions that contribute to this problem. It is suggested that schools should investigate whether time limitation is a problem for their own students. The article discusses the implications of these findings for teachers preparing students for NAPLAN tests and for the developers of the tests.

A sequential Monte Carlo algorithm to incorporate model uncertainty in Bayesian sequential design

Here we present a sequential Monte Carlo (SMC) algorithm that can be used for any one-at-a-time Bayesian sequential design problem in the presence of model uncertainty where discrete data are encountered. Our focus is on adaptive design for model discrimination but the methodology is applicable if one has a different design objective such as parameter estimation or prediction. An SMC algorithm is run in parallel for each model and the algorithm relies on a convenient estimator of the evidence of each model which is essentially a function of importance sampling weights. Other methods for this task such as quadrature, often used in design, suffer from the curse of dimensionality. Approximating posterior model probabilities in this way allows us to use model discrimination utility functions derived from information theory that were previously difficult to compute except for conjugate models. A major benefit of the algorithm is that it requires very little problem specific tuning. We demonstrate the methodology on three applications, including discriminating between models for decline in motor neuron numbers in patients suffering from neurological diseases such as Motor Neuron disease.

Change Point Estimation in Monitoring Survival Time

Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

Limestone and speleothem trace element geochemistry as tools for palaeoclimatic reconstruction, Mount Etna region, central-coastal Queensland

This study investigated potential palaeoclimate proxies provided by rare earth element (REE) geochemistry in speleothems and in clay mineralogy of cave sediments. Speleothem and sediment samples were collected from a series of cave fill deposits that occurred with rich vertebrate fossil assemblages in and around Mount Etna National Park, Rockhampton (central coastal Queensland). The fossil deposits range from Plio- Pleistocene to Holocene in age (based on uranium/thorium dating) and appear to represent depositional environments ranging from enclosed rainforest to semi-arid grasslands. Therefore, the Mount Etna cave deposits offer the perfect opportunity to test new palaeoclimate tools as they include deposits that span a known significant climate shift on the basis of independent faunal data. The first section of this study investigates the REE distribution of the host limestone to provide baseline geochemistry for subsequent speleothem investigations. The Devonian Mount Etna Beds were found to be more complex than previous literature had documented. The studied limestone massif is overturned, highly recrystallised in parts and consists of numerous allochthonous blocks with different spatial orientations. Despite the complex geologic history of the Mount Etna Beds, Devonian seawater-like REE patterns were recovered in some parts of the limestone and baseline geochemistry was determined for the bulk limestone for comparison with speleothem REE patterns. The second part of the study focused on REE distribution in the karst system and the palaeoclimatic implications of such records. It was found that REEs have a high affinity for calcite surfaces and that REE distributions in speleothems vary between growth bands much more than along growth bands, thus providing a temporal record that may relate to environmental changes. The morphology of different speleothems (i.e., stalactites, stalagmites, and flowstones) has little bearing on REE distributions provided they are not contaminated with particulate fines. Thus, baseline knowledge developed in the study suggested that speleothems were basically comparable for assessing palaeoclimatically controlled variations in REE distributions. Speleothems from rainforest and semi-arid phases were compared and it was found that there are definable differences in REE distribution that can be attributed to climate. In particular during semiarid phases, total REE concentration decreased, LREE became more depleted, Y/Ho increased, La anomalies were more positive and Ce anomalies were more negative. This may reflect more soil development during rainforest phases and more organic particles and colloids, which are known to transport REEs, in karst waters. However, on a finer temporal scale (i.e. growth bands) within speleothems from the same climate regime, no difference was seen. It is suggested that this may be due to inadequate time for soil development changes on the time frames represented by differences in growth band density. The third part of the study was a reconnaissance investigation focused on mineralogy of clay cave sediments, illite/kaolinite ratios in particular, and the potential palaeoclimatic implications of such records. Although the sample distribution was not optimal, the preliminary results suggest that the illite/kaolinite ratio increased during cold and dry intervals, consistent with decreased chemical weathering during those times. The study provides a basic framework for future studies at differing latitudes to further constrain the parameters of the proxy. The identification of such a proxy recorded in cave sediment has broad implications as clay ratios could potentially provide a basic local climate proxy in the absence of fossil faunas and speleothem material. This study suggests that REEs distributed in speleothems may provide information about water throughput and soil formation, thus providing a potential palaeoclimate proxy. It highlights the importance of understanding the host limestone geochemistry and broadens the distribution and potential number of cave field sites as palaeoclimate information no longer relies solely on the presence of fossil faunas and or speleothems. However, additional research is required to better understand the temporal scales required for the proxies to be recognised.

Critical time scales for advection–diffusion–reaction processes

The concept of local accumulation time (LAT) was introduced by Berezhkovskii and coworkers in 2010–2011 to give a finite measure of the time required for the transient solution of a reaction–diffusion equation to approach the steady–state solution (Biophys J. 99, L59 (2010); Phys Rev E. 83, 051906 (2011)). Such a measure is referred to as a critical time. Here, we show that LAT is, in fact, identical to the concept of mean action time (MAT) that was first introduced by McNabb in 1991 (IMA J Appl Math. 47, 193 (1991)). Although McNabb’s initial argument was motivated by considering the mean particle lifetime (MPLT) for a linear death process, he applied the ideas to study diffusion. We extend the work of these authors by deriving expressions for the MAT for a general one–dimensional linear advection–diffusion–reaction problem. Using a combination of continuum and discrete approaches, we show that MAT and MPLT are equivalent for certain uniform–to-uniform transitions; these results provide a practical interpretation for MAT, by directly linking the stochastic microscopic processes to a meaningful macroscopic timescale. We find that for more general transitions, the equivalence between MAT and MPLT does not hold. Unlike other critical time definitions, we show that it is possible to evaluate the MAT without solving the underlying partial differential equation (pde). This makes MAT a simple and attractive quantity for practical situations. Finally, our work explores the accuracy of certain approximations derived using the MAT, showing that useful approximations for nonlinear kinetic processes can be obtained, again without treating the governing pde directly.

Driver response time of queuing vehicles at urban signalized intersections

Driver response (reaction) time (tr) of the second queuing vehicle is generally longer than other vehicles at signalized intersections. Though this phenomenon was revealed in 1972, the above factor is still ignored in conventional departure models. This paper highlights the need for quantitative measurements and analysis of queuing vehicle performance in spontaneous discharge pattern because it can improve microsimulation. Video recording from major cities in Australia plus twenty two sets of vehicle trajectories extracted from the Next Generation Simulation (NGSIM) Peachtree Street Dataset have been analyzed to better understand queuing vehicle performance in the discharge process. Findings from this research will alleviate driver response time and also can be used for the calibration of the microscopic traffic simulation model.