Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

POSITIVE FILTERED P_N METHOD FOR LINEAR TRANSPORT EQUATIONS AND THE ASSOCIATED OPTIMIZATION ALGORITHM

We propose a positive, accurate moment closure for linear kinetic transport equations based on a filtered spherical harmonic (FP_N) expansion in the angular variable. The FP_N moment equations are accurate approximations to linear kinetic equations, but they are known to suffer from the occurrence of unphysical, negative particle concentrations. The new positive filtered P_N (FP_N+) closure is developed to address this issue. The FP_N+ closure approximates the kinetic distribution by a spherical harmonic expansion that is non-negative on a finite, predetermined set of quadrature points. With an appropriate numerical PDE solver, the FP_N+ closure generates particle concentrations that are guaranteed to be non-negative. Under an additional, mild regularity assumption, we prove that as the moment order tends to infinity, the FP_N+ approximation converges, in the L2 sense, at the same rate as the FP_N approximation; numerical tests suggest that this assumption may not be necessary. By numerical experiments on the challenging line source benchmark problem, we confirm that the FP_N+ method indeed produces accurate and non-negative solutions. To apply the FP_N+ closure on problems at large temporal-spatial scales, we develop a positive asymptotic preserving (AP) numerical PDE solver. We prove that the propose AP scheme maintains stability and accuracy with standard mesh sizes at large temporal-spatial scales, while, for generic numerical schemes, excessive refinements on temporal-spatial meshes are required. We also show that the proposed scheme preserves positivity of the particle concentration, under some time step restriction. Numerical results confirm that the proposed AP scheme is capable for solving linear transport equations at large temporal-spatial scales, for which a generic scheme could fail. Constrained optimization problems are involved in the formulation of the FP_N+ closure to enforce non-negativity of the FP_N+ approximation on the set of quadrature points. These optimization problems can be written as strictly convex quadratic programs (CQPs) with a large number of inequality constraints. To efficiently solve the CQPs, we propose a constraint-reduced variant of a Mehrotra-predictor-corrector algorithm, with a novel constraint selection rule. We prove that, under appropriate assumptions, the proposed optimization algorithm converges globally to the solution at a locally q-quadratic rate. We test the algorithm on randomly generated problems, and the numerical results indicate that the combination of the proposed algorithm and the constraint selection rule outperforms other compared constraint-reduced algorithms, especially for problems with many more inequality constraints than variables.

Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

Are we too busy to volunteer? The relationship between time and volunteering using the 1997 ABS Time Use Data

Time availability is a key concept in relation to volunteering, leading to organisations and governments targeting those outside paid work as a potential source of volunteers. It may be that factors such as a growth in female participation in the labour market and an increase in work hours will lead to more people saying they are simply too busy to volunteer This paper discusses how social and economic change, such as changing work patterns, are impacting on time availability. Using the 1997 ABS Time Use data, it identifies a predictive model of spare time by looking at demographic, life stage and employment related variables. Results confirm that those outside paid work, particularly the young, males and those without partners or children, are the groups most likely to have time to spare. These groups do not currently report high rates of volunteering. The paper concludes by questioning the premise that people will volunteer simply because they have time to spare. This is just one component of a range of motivations and factors that influence the decision to volunteer.

Effect of storage time and conditions on the hardness and cooking quality of adzuki (Vigna angularis)

A storage trial of two varieties of adzuki (Vigna angularis), Bloodwood and Erimo, produced in Australia, was conducted to determine the effect of various combinations of temperature, humidity and length of storage on bean quality. The beans were stored for up to 6 mo under the following conditions: temperature (10, 20 and 30degreesC), relative humidity (RH) (40 and 65%). Storage of adzuki at elevated temperature (30degreesC) and low relative humidity (40%) resulted in the greatest loss of bean moisture, increase in hydration times and decrease in bean cooking quality, i.e. increased hardness of cooked beans. The best storage conditions for the preservation of adzuki quality were 10degreesC and 65% RH.

Dormancy release in Lolium rigidum seeds is a function of thermal after-ripening time and seed water content

Dormancy release in seeds of Lolium rigidum Gaud. (annual ryegrass) was investigated in relation to temperature and seed water content. Freshly matured seeds were collected from cropping fields at Wongan Hills and Merredin, Western Australia. Seeds from Wongan Hills were equilibrated to water contents between 6 and 18% dry weight and after-ripened at constant temperatures between 9 and 50degreesC for up to 23 weeks. Wongan Hills and Merredin seeds at water contents between 7 and 17% were also after-ripened in full sun or shade conditions. Dormancy was tested at regular intervals during after-ripening by germinating seeds on agar at 12-h alternating 15degreesC (dark) and 25degreesC (light) periods. Rate of dormancy release for Wongan Hills seeds was a positive linear function of after-ripening temperature above a base temperature (T-b) of 5.4degreesC. A thermal after-ripening time model for dormancy loss accounting for seed moisture in the range 6-18% was developed using germination data for Wongan Hills seeds after-ripened at constant temperatures. The model accurately predicted dormancy release for Wongan Hills seeds after-ripened under naturally fluctuating temperatures. Seeds from Merredin responded similarly but had lower dormancy at collection and a faster rate of dormancy release in seeds below 9% water content.

Time- and Fluid-Sensitive Resuscitation for Hemodynamic Support of Children in Septic Shock Barriers to the Implementation of the American College of Critical Care Medicine/Pediatric Advanced Life Support Guidelines in a Pediatric Intensive Care Unit in a Developing World

Objectives: To analyze mortality rates of children with severe sepsis and septic shock in relation to time-sensitive fluid resuscitation and treatments received and to define barriers to the implementation of the American College of Critical Care Medicine/Pediatric Advanced Life Support guidelines in a pediatric intensive care unit in a developing country. Methods: Retrospective chart review and prospective analysis of septic shock treatment in a pediatric intensive care unit of a tertiary care teaching hospital. Ninety patients with severe sepsis or septic shock admitted between July 2002 and June 2003 were included in this study. Results: Of the 90 patients, 83% had septic shock and 17% had severe sepsis; 80 patients had preexisting severe chronic diseases. Patients with septic shock who received less than a 20-mL/kg dose of resuscitation fluid in the first hour of treatment had a mortality rate of 73%, whereas patients who received more than a 40-mL/kg dose in the first hour of treatment had a mortality rate of 33% (P < 0.05.) Patients treated less than 30 minutes after diagnosis of severe sepsis and septic shock had a significantly lower mortality rate (40%) than patients treated more than 60 Minutes after diagnosis (P < 0.05). Controlling for the risk of mortality, early fluid resuscitation was associated with a 3-fold reduction in the odds of death (odds ratio, 0.33; 95% confidence interval, 0.13-0.85). The most important barriers to achieve adequate severe sepsis and septic shock treatment were lack of adequate vascular access, lack of recognition of early shock, shortage of health care providers, and nonuse of goals and treatment protocols. Conclusions: The mortality rate was higher for children older than years, for those who received less than 40 mL/kg in the first hour, and for those whose treatment was not initiated in the first 30 Minutes after the diagnosis of septic shock. The acknowledgment of existing barriers to a timely fluid administration and the establishment of objectives to overcome these barriers may lead to a more successful implementation of the American College of Critical Care Medicine guidelines and reduced mortality rates for children with septic shock in the developing world.

Effect of storage time and conditions on the cotyledon cell wall of the adzuki bean (Vigna angularis)

Two varieties of adzuki grown in Australia, Bloodwood and Erimo, were stored for up to 6 months at three temperatures (10, 20 and 30 degreesC), and two relative humidities (RH; 40 and 65%). The amount of cell wall material increased with time under all storage conditions. This increase was greatest at 30 degreesC and 40% RH. Storage time and conditions did not affect the total pectin levels in the cell wall. Erimo constantly exhibited a higher total pectin level than Bloodwood. The Bloodwood soluble pectin, Ca++ and Mg++ and Erimo Ca++ in the cell wall remained stable during storage, while the Erimo soluble pectin and Mg++ exhibited a slight decrease at 20 and 30 degreesC after 3 months of storage. (C) 2002 Elsevier Science Ltd. All rights reserved.

Position paper on time and event-triggered communication services in the context of e-manufacturing

Modern factories are complex systems where advances in networking and information technologies are opening new ways towards higher efficiency. Such move is being driven by market rules with ever-increasing competition levels, in search for faster time-to-market, improved process yield, non-stop operations, flexible manufacturing and tighter supply-chain coupling. All these aims present a common requirement, i.e. a realtime flow of information, from the plant-floor up to the management, maintenance, suppliers and clients, to support accurate monitoring and control of the factory. This stresses the importance achieved by the communication infrastructure in modern manufacturing industry. This paper presents the authors view concerning the current trends in modern factory communication systems. It addresses the problems of seamlessly integrating different information flows with diverse requirements, mainly in terms of timeliness. In this aspect, the debate between event-triggered and time-triggered communication is revisited as well as the joint support for both types of traffic. Finally, a view of where factory communication systems are moving to is also presented, showing the impact of open and widely available technologies.

Predictive value of serologic tests in the diagnosis and follow-up of patients with paracoccidioidomycosis

A serologic study was undertaken in a group of 43 patients with active paracoccidioidomycosis who were treated in the same form (ketoconazole), for identical periods of time (6 months), and folio wed-up for various periods posttherapy. The tests employed were agar gel immunodiffusion (AGID) and complement fixation (FC). Also studied were 50 sera from patients with proven histoplasmosis and pulmonary aspergilloma, 30 patients with culturaly proven tuberculosis as well as 92 specimens from healthy individuals, residents in the endemic area for paracoccidioidomycosis. A single lot of yeast filtrate antigen was used throughout the study. The value of each test was measured according to GALEN and GAMBINO6. Both tests were highly sensitive, 89 and 93% respectively. Regarding their specificity, the AGID was totally specific while the CF exhibited 96.6% and 97% specificity in front of tuberculosis patients and healthy individuals respectively and 82% in comparison with patients with other mycoses. The concept of predictive value, that is, the certainty one has in accepting a positive test as diagnostic of paracoccidioidomycosis, favored the AGID procedure (100%) over the CF test. The latter could sort out with 93% certainty a patient with paracoccidioidomycosis among a group of healthy individuals and with 97.5% in the case of TB patients; when the group in question was composed by individuals with other deep mycoses, such certainty was lower (81%). The above results indicate that both the AGID and the CF tests furnish results of high confidence; one should not relay, however, in the CF alone as a means to establish the specific diagnosis of paracoccidioidomycosis.

Human activity recognition with accelerometry: novel time and frequency features

Human Activity Recognition systems require objective and reliable methods that can be used in the daily routine and must offer consistent results according with the performed activities. These systems are under development and offer objective and personalized support for several applications such as the healthcare area. This thesis aims to create a framework for human activities recognition based on accelerometry signals. Some new features and techniques inspired in the audio recognition methodology are introduced in this work, namely Log Scale Power Bandwidth and the Markov Models application. The Forward Feature Selection was adopted as the feature selection algorithm in order to improve the clustering performances and limit the computational demands. This method selects the most suitable set of features for activities recognition in accelerometry from a 423th dimensional feature vector. Several Machine Learning algorithms were applied to the used accelerometry databases – FCHA and PAMAP databases - and these showed promising results in activities recognition. The developed algorithm set constitutes a mighty contribution for the development of reliable evaluation methods of movement disorders for diagnosis and treatment applications.

VEGF and TNF up-regulate, NSAID down-regulate SOX18 protein level in HUVEC

Angiogenesis, the process of generating new blood vessels, is essential to embryonic development, organ formation, tissue regeneration and remodeling, reproduction and wound healing. Also, it plays an important role in many pathological conditions, including chronic inflammation and cancer. Angiogenesis is regulated by a complex interplay of growth factors, inflammatory mediators, adhesion molecules, morphogens and guidance molecules. Transcription factor SOX18 is transiently expressed in nascent endothelial cells during embryonic development and postnatal angiogenesis, but little is known about signaling pathways controlling its expression. The aim of this study was to investigate whether pro-angiogenic molecules and pharmacological inhibitors of angiogenesis modulate SOX18 expression in endothelial cells. Therefore, we treated human umbilical vein endothelial cells (HUVEC) with angiogenic factors, extracellular matrix proteins, inflammatory cytokines and nonsteroidal anti-inflammatory drugs (NSAID) and monitored SOX18 expression. We have observed that the angiogenic factor VEGF and the inflammatory cytokine TNF increase, while the NSAID ibuprofen and NS398 decrease the SOX18 protein level. These results for the first time demonstrate that SOX18 expression is modulated by factors and drugs known to positively or negatively regulate angiogenesis. This opens the possibility of pharmacological manipulation of SOX18 gene expression in endothelial cells to stimulate or inhibit angiogenesis.

Learning-induced plasticity in human audition: Objects, time, and space.

The human auditory system is comprised of specialized but interacting anatomic and functional pathways encoding object, spatial, and temporal information. We review how learning-induced plasticity manifests along these pathways and to what extent there are common mechanisms subserving such plasticity. A first series of experiments establishes a temporal hierarchy along which sounds of objects are discriminated along basic to fine-grained categorical boundaries and learned representations. A widespread network of temporal and (pre)frontal brain regions contributes to object discrimination via recursive processing. Learning-induced plasticity typically manifested as repetition suppression within a common set of brain regions. A second series considered how the temporal sequence of sound sources is represented. We show that lateralized responsiveness during the initial encoding phase of pairs of auditory spatial stimuli is critical for their accurate ordered perception. Finally, we consider how spatial representations are formed and modified through training-induced learning. A population-based model of spatial processing is supported wherein temporal and parietal structures interact in the encoding of relative and absolute spatial information over the initial ∼300ms post-stimulus onset. Collectively, these data provide insights into the functional organization of human audition and open directions for new developments in targeted diagnostic and neurorehabilitation strategies.

Mental health and growing up factsheet. Cannabis and mental health: information for young people.

About this leaflet This is one in a series of leaflets for parents, teachers and young people entitled Mental Health and Growing Up. These leaflets aim to provide practical, up-to-date information about mental health problems (emotional, behavioural and psychiatric disorders) that can affect children and young people. This leaflet gives you some basic facts about cannabis and also how it might affect your mental health. Introduction Lots of young people want to know about drugs. Often, people around you are taking them, and you may wonder how it will make you feel. You may even feel under pressure to use drugs in order to fit in, or be â?~coolâ?T. You may have heard that cannabis is no worse than cigarettes, or that it is harmless. What is cannabis? The cannabis plant is a member of the nettle family that has grown wild throughout the world for centuries. People have used it for lots of reasons, other than the popular relaxing effect. It comes in two main forms: ï,§ resin, which is a brown black lump also known as bhang, ganja or hashish ï,§ herbal cannabis, which is made up of the dried leaves and flowering tops, and is known as grass, marijuana, spliff, weed, etc. Skunk cannabis is made from a cannabis plant that has more active chemicals in it (THC), and the effect on your brain is stronger. Because â?~streetâ?T cannabis varies so much in strength, you will not be able to tell exactly how it will make you feel at any particular time. What does it do to you? When you smoke cannabis, the active compounds reach your brain quickly through your bloodstream. It then binds/sticks to a special receptor in your brain. This causes your nerve cells to release different chemicals, and causes the effects that you feel. These effects can be enjoyable or unpleasant. Often the bad effects take longer to appear than the pleasant ones. ï,§ Good/pleasant effects: You may feel relaxed and talkative, and colours or music may seem more intense. ï,§ Unpleasant effects: Feeling sick/panicky, feeling paranoid or hearing voices, feeling depressed and unmotivated. Unfortunately, some people can find cannabis addictive and so have trouble stopping use even when they are not enjoying it. The effects on your mental health Using cannabis triggers mental health problems in people who seemed to be well before, or it can worsen any mental health problems you already have. Research has shown that people who are already at risk of developing mental health problems are more likely to start showing symptoms of mental illness if they use cannabis regularly. For example if someone in your family has depression or schizophrenia, you are at higher risk of getting these illness when you use cannabis. The younger you are when you start using it, the more you may be at risk. This is because your brain is still developing and can be more easily damaged by the active chemicals in cannabis. If you stop using cannabis once you have started to show symptoms of mental illness, such as depression, paranoia or hearing voices, these symptoms may go away. However, not everyone will get better just by stopping smoking. If you go on using cannabis, the symptoms can get worse. It can also make any treatment that your doctor might prescribe for you, work less well. Your illness may come back more quickly, and more often if you continue to use cannabis once you get well again. Some people with mental health problems find that using cannabis makes them feel a bit better for a while. Unfortunately this does not last, and it does nothing to treat the illness. In fact, it may delay you from getting help you need and the illness may get worse in the longer term. [For the full factsheet, click on the link above]This resource was contributed by The National Documentation Centre on Drug Use.