Locally generated particulate pollution and respiratory symptoms in young children

BACKGROUND: Particulate matter <10 mum (PM(10)) from fossil fuel combustion is associated with an increased prevalence of respiratory symptoms in children and adolescents. However, the effect of PM(10) on respiratory symptoms in young children is unclear. METHODS: The association between primary PM(10) (particles directly emitted from local sources) and the prevalence and incidence of respiratory symptoms was studied in a random sample cohort of 4400 Leicestershire children aged 1-5 years surveyed in 1998 and again in 2001. Annual exposure to primary PM(10) was calculated for the home address using the Airviro dispersion model and adjusted odds ratios (ORS) and 95% confidence intervals were calculated for each microg/m(3) increase. RESULTS: Exposure to primary PM(10) was associated with the prevalence of cough without a cold in both 1998 and 2001, with adjusted ORs of 1.21 (1.07 to 1.38) and 1.56 (1.32 to 1.84) respectively. For night time cough the ORs were 1.06 (0.94 to 1.19) and 1.25 (1.06 to 1.47), and for current wheeze 0.99 (0.88 to 1.12) and 1.28 (1.04 to 1.58), respectively. There was also an association between primary PM(10) and new onset symptoms. The ORs for incident symptoms were 1.62 (1.31 to 2.00) for cough without a cold and 1.42 (1.02 to 1.97) for wheeze. CONCLUSION: In young children there was a consistent association between locally generated primary PM(10) and the prevalence and incidence of cough without a cold and the incidence of wheeze which was independent of potential confounders.

Markers Models in Survival Analysis and Applications to Issues Associated with AIDS

Jewell and Kalbfleisch (1992) consider the use of marker processes for applications related to estimation of the survival distribution of time to failure. Marker processes were assumed to be stochastic processes that, at a given point in time, provide information about the current hazard and consequently on the remaining time to failure. Particular attention was paid to calculations based on a simple additive model for the relationship between the hazard function at time t and the history of the marker process up until time t. Specific applications to the analysis of AIDS data included the use of markers as surrogate responses for onset of AIDS with censored data and as predictors of the time elapsed since infection in prevalent individuals. Here we review recent work on the use of marker data to tackle these kinds of problems with AIDS data. The Poisson marker process with an additive model, introduced in Jewell and Kalbfleisch (1992) may be a useful "test" example for comparison of various procedures.

Retinol-binding protein 4 is associated with components of the metabolic syndrome, but not with insulin resistance, in men with type 2 diabetes or coronary artery disease

AIMS/HYPOTHESIS: Retinol-binding protein 4 (RBP4) has recently been reported to be associated with insulin resistance and the metabolic syndrome. This study tested the hypothesis that RBP4 is a marker of insulin resistance and the metabolic syndrome in patients with type 2 diabetes or coronary artery disease (CAD) or in non-diabetic control subjects without CAD. METHODS: Serum RBP4 was measured in 365 men (126 with type 2 diabetes, 143 with CAD and 96 control subjects) and correlated with the homeostasis model assessment of insulin resistance index (HOMA-IR), components of the metabolic syndrome and lipoprotein metabolism. RBP4 was detected by ELISA and validated by quantitative Western blotting. RESULTS: RBP4 concentrations detected by ELISA were shown to be strongly associated with the results gained in quantitative Western blots. There were no associations of RBP4 with HOMA-IR or HbA(1c) in any of the groups studied. In patients with type 2 diabetes there were significant positive correlations of RBP4 with total cholesterol, LDL-cholesterol, VLDL-cholesterol, plasma triacylglycerol and hepatic lipase activity. In patients with CAD, there were significant associations of RBP4 with VLDL-cholesterol, plasma triacylglycerol and hepatic lipase activity, while non-diabetic control subjects without CAD showed positive correlations of RBP4 with VLDL-cholesterol and plasma triacylglycerol. CONCLUSIONS/INTERPRETATION: RBP4 does not seem to be a valuable marker for identification of the metabolic syndrome or insulin resistance in male patients with type 2 diabetes or CAD. Independent associations of RBP4 with pro-atherogenic lipoproteins and enzymes of lipoprotein metabolism indicate a possible role of RBP4 in lipid metabolism.

Human temporal bones versus mechanical model to evaluate three middle ear transducers

A life-size mechanical middle ear model and human temporal bones were used to evaluate three different middle ear transducers for implantable hearing aids: the driving rod transducer (DRT), the floating mass transducer (FMT) or vibrant sound bridge, and the contactless transducer (CLT). Results of the experiments with the mechanical model were within the range of the results for human temporal bones. However, results with the mechanical model showed better reproducibility. The handling of the mechanical model was considerably simpler and less time-consuming. Systematic variations of mounting parameters showed that the angle of the rod has virtually no effect on the output of the DRT, the mass loading on the cable of the FMT has a larger impact on the output than does the tightness of crimping, and the output level of the CLT can be increased by 10 dB by optimizing the mounting parameters.

Monte Carlo simulation of a dynamic MLC based on a multiple source model

Detailed knowledge of the characteristics of the radiation field shaped by a multileaf collimator (MLC) is essential in intensity modulated radiotherapy (IMRT). A previously developed multiple source model (MSM) for a 6 MV beam was extended to a 15 MV beam and supplemented with an accurate model of an 80-leaf dynamic MLC. Using the supplemented MSM and the MC code GEANT, lateral dose distributions were calculated in a water phantom and a portal water phantom. A field which is normally used for the validation of the step and shoot technique and a field from a realistic IMRT treatment plan delivered with dynamic MLC are investigated. To assess possible spectral changes caused by the modulation of beam intensity by an MLC, the energy spectra in five portal planes were calculated for moving slits of different widths. The extension of the MSM to 15 MV was validated by analysing energy fluences, depth doses and dose profiles. In addition, the MC-calculated primary energy spectrum was verified with an energy spectrum which was reconstructed from transmission measurements. MC-calculated dose profiles using the MSM for the step and shoot case and for the dynamic MLC case are in very good agreement with the measured data from film dosimetry. The investigation of a 13 cm wide field shows an increase in mean photon energy of up to 16% for the 0.25 cm slit compared to the open beam for 6 MV and of up to 6% for 15 MV, respectively. In conclusion, the MSM supplemented with the dynamic MLC has proven to be a powerful tool for investigational and benchmarking purposes or even for dose calculations in IMRT.

Modeling of diesel particulate filter filtration and regeneration for transient driving schedules

Due to their high thermal efficiency, diesel engines have excellent fuel economy and have been widely used as a power source for many vehicles. Diesel engines emit less greenhouse gases (carbon dioxide) compared with gasoline engines. However, diesel engines emit large amounts of particulate matter (PM) which can imperil human health. The best way to reduce the particulate matter is by using the Diesel Particulate Filter (DPF) system which consists of a wall-flow monolith which can trap particulates, and the DPF can be periodically regenerated to remove the collected particulates. The estimation of the PM mass accumulated in the DPF and total pressure drop across the filter are very important in order to determine when to carry out the active regeneration for the DPF. In this project, by developing a filtration model and a pressure drop model, we can estimate the PM mass and the total pressure drop, then, these two models can be linked with a regeneration model which has been developed previously to predict when to regenerate the filter. There results of this project were: 1 Reproduce a filtration model and simulate the processes of filtration. By studying the deep bed filtration and cake filtration, stages and quantity of mass accumulated in the DPF can be estimated. It was found that the filtration efficiency increases faster during the deep-bed filtration than that during the cake filtration. A “unit collector” theory was used in our filtration model which can explain the mechanism of the filtration very well. 2 Perform a parametric study on the pressure drop model for changes in engine exhaust flow rate, deposit layer thickness, and inlet temperature. It was found that there are five primary variables impacting the pressure drop in the DPF which are temperature gradient along the channel, deposit layer thickness, deposit layer permeability, wall thickness, and wall permeability. 3 Link the filtration model and the pressure drop model with the regeneration model to determine the time to carry out the regeneration of the DPF. It was found that the regeneration should be initiated when the cake layer is at a certain thickness, since a cake layer with either too big or too small an amount of particulates will need more thermal energy to reach a higher regeneration efficiency. 4 Formulate diesel particulate trap regeneration strategies for real world driving conditions to find out the best desirable conditions for DPF regeneration. It was found that the regeneration should be initiated when the vehicle’s speed is high and during which there should not be any stops from the vehicle. Moreover, the regeneration duration is about 120 seconds and the inlet temperature for the regeneration is 710K.

Analysis of atmospheric transport and the effects of seasonal and interannual transport variability on measurements made at the Pico Mountain observatory

A non-hierarchical K-means algorithm is used to cluster 47 years (1960–2006) of 10-day HYSPLIT backward trajectories to the Pico Mountain (PM) observatory on a seasonal basis. The resulting cluster centers identify the major transport pathways and collectively comprise a long-term climatology of transport to the observatory. The transport climatology improves our ability to interpret the observations made there and our understanding of pollution source regions to the station and the central North Atlantic region. I determine which pathways dominate transport to the observatory and examine the impacts of these transport patterns on the O3, NOy, NOx, and CO measurements made there during 2001–2006. Transport from the U.S., Canada, and the Atlantic most frequently reaches the station, but Europe, east Africa, and the Pacific can also contribute significantly depending on the season. Transport from Canada was correlated with the North Atlantic Oscillation (NAO) in spring and winter, and transport from the Pacific was uncorrelated with the NAO. The highest CO and O3 are observed during spring. Summer is also characterized by high CO and O3 and the highest NOy and NOx of any season. Previous studies at the station attributed the summer time high CO and O3 to transport of boreal wildfire emissions (for 2002–2004), and boreal fires continued to affect the station during 2005 and 2006. The particle dispersion model FLEXPART was used to calculate anthropogenic and biomass-burning CO tracer values at the station in an attempt to identify the regions responsible for the high CO and O3 observations during spring and biomass-burning impacts in summer.

Development of a continuum mechanics model of passive skeletal muscle

Skeletal muscle force evaluation is difficult to implement in a clinical setting. Muscle force is typically assessed through either manual muscle testing, isokinetic/isometric dynamometry, or electromyography (EMG). Manual muscle testing is a subjective evaluation of a patient’s ability to move voluntarily against gravity and to resist force applied by an examiner. Muscle testing using dynamometers adds accuracy by quantifying functional mechanical output of a limb. However, like manual muscle testing, dynamometry only provides estimates of the joint moment. EMG quantifies neuromuscular activation signals of individual muscles, and is used to infer muscle function. Despite the abundance of work performed to determine the degree to which EMG signals and muscle forces are related, the basic problem remains that EMG cannot provide a quantitative measurement of muscle force. Intramuscular pressure (IMP), the pressure applied by muscle fibers on interstitial fluid, has been considered as a correlate for muscle force. Numerous studies have shown that an approximately linear relationship exists between IMP and muscle force. A microsensor has recently been developed that is accurate, biocompatible, and appropriately sized for clinical use. While muscle force and pressure have been shown to be correlates, IMP has been shown to be non-uniform within the muscle. As it would not be practicable to experimentally evaluate how IMP is distributed, computational modeling may provide the means to fully evaluate IMP generation in muscles of various shapes and operating conditions. The work presented in this dissertation focuses on the development and validation of computational models of passive skeletal muscle and the evaluation of their performance for prediction of IMP. A transversly isotropic, hyperelastic, and nearly incompressible model will be evaluated along with a poroelastic model.

Long-Range Pollution Transport: Trans-Atlantic Mechanisms and Lagrangian Modeling Methods

Over the past several decades, it has become apparent that anthropogenic activities have resulted in the large-scale enhancement of the levels of many trace gases throughout the troposphere. More recently, attention has been given to the transport pathway taken by these emissions as they are dispersed throughout the atmosphere. The transport pathway determines the physical characteristics of emissions plumes and therefore plays an important role in the chemical transformations that can occur downwind of source regions. For example, the production of ozone (O3) is strongly dependent upon the transport its precursors undergo. O3 can initially be formed within air masses while still over polluted source regions. These polluted air masses can experience continued O3 production or O3 destruction downwind, depending on the air mass's chemical and transport characteristics. At present, however, there are a number of uncertainties in the relationships between transport and O3 production in the North Atlantic lower free troposphere. The first phase of the study presented here used measurements made at the Pico Mountain observatory and model simulations to determine transport pathways for US emissions to the observatory. The Pico Mountain observatory was established in the summer of 2001 in order to address the need to understand the relationships between transport and O3 production. Measurements from the observatory were analyzed in conjunction with model simulations from the Lagrangian particle dispersion model (LPDM), FLEX-PART, in order to determine the transport pathway for events observed at the Pico Mountain observatory during July 2003. A total of 16 events were observed, 4 of which were analyzed in detail. The transport time for these 16 events varied from 4.5 to 7 days, while the transport altitudes over the ocean ranged from 2-8 km, but were typically less than 3 km. In three of the case studies, eastward advection and transport in a weak warm conveyor belt (WCB) airflow was responsible for the export of North American emissions into the FT, while transport in the FT was governed by easterly winds driven by the Azores/Bermuda High (ABH) and transient northerly lows. In the fourth case study, North American emissions were lofted to 6-8 km in a WCB before being entrained in the same cyclone's dry airstream and transported down to the observatory. The results of this study show that the lower marine FT may provide an important transport environment where O3 production may continue, in contrast to transport in the marine boundary layer, where O3 destruction is believed to dominate. The second phase of the study presented here focused on improving the analysis methods that are available with LPDMs. While LPDMs are popular and useful for the analysis of atmospheric trace gas measurements, identifying the transport pathway of emissions from their source to a receptor (the Pico Mountain observatory in our case) using the standard gridded model output, particularly during complex meteorological scenarios can be difficult can be difficult or impossible. The transport study in phase 1 was limited to only 1 month out of more than 3 years of available data and included only 4 case studies out of the 16 events specifically due to this confounding factor. The second phase of this study addressed this difficulty by presenting a method to clearly and easily identify the pathway taken by only those emissions that arrive at a receptor at a particular time, by combining the standard gridded output from forward (i.e., concentrations) and backward (i.e., residence time) LPDM simulations, greatly simplifying similar analyses. The ability of the method to successfully determine the source-to-receptor pathway, restoring this Lagrangian information that is lost when the data are gridded, is proven by comparing the pathway determined from this method with the particle trajectories from both the forward and backward models. A sample analysis is also presented, demonstrating that this method is more accurate and easier to use than existing methods using standard LPDM products. Finally, we discuss potential future work that would be possible by combining the backward LPDM simulation with gridded data from other sources (e.g., chemical transport models) to obtain a Lagrangian sampling of the air that will eventually arrive at a receptor.

The pollen tube: a soft shell with a hard core

Plant cell expansion is controlled by a fine-tuned balance between intracellular turgor pressure, cell wall loosening and cell wall biosynthesis. To understand these processes, it is important to gain in-depth knowledge of cell wall mechanics. Pollen tubes are tip-growing cells that provide an ideal system to study mechanical properties at the single cell level. With the available approaches it was not easy to measure important mechanical parameters of pollen tubes, such as the elasticity of the cell wall. We used a cellular force microscope (CFM) to measure the apparent stiffness of lily pollen tubes. In combination with a mechanical model based on the finite element method (FEM), this allowed us to calculate turgor pressure and cell wall elasticity, which we found to be around 0.3 MPa and 20–90 MPa, respectively. Furthermore, and in contrast to previous reports, we showed that the difference in stiffness between the pollen tube tip and the shank can be explained solely by the geometry of the pollen tube. CFM, in combination with an FEM-based model, provides a powerful method to evaluate important mechanical parameters of single, growing cells. Our findings indicate that the cell wall of growing pollen tubes has mechanical properties similar to rubber. This suggests that a fully turgid pollen tube is a relatively stiff, yet flexible cell that can react very quickly to obstacles or attractants by adjusting the direction of growth on its way through the female transmitting tissue.

Does flow experience lead to risk? How and for whom

Background: Previous research has focused on the positive consequences of flow, an intrinsically rewarding state of deep absorption. In contrast, the present research links flow to impaired risk awareness and to risky behaviour. We expected flow to enhance self-efficacy beliefs, which in turn were hypothesised to result in low risk awareness and risky behaviour in sports. In addition, we predicted that individuals' level of experience in the activity would moderate the expected effects. Methods: One study with kayakers (Study 1) and two studies with rock climbers (Studies 2 and 3) were conducted. Kayakers completed a survey while still on the river; climbers responded during and upon completion of a climb. Results: In all studies flow was related to risk awareness. Study 2 additionally showed its association with risky behaviour. Studies 2 and 3 revealed that these relationships were mediated by self-efficacy. The mediations were moderated by level of experience (Study 3). Conclusions: The results indicated that inexperienced but not experienced participants respond to self-efficacy beliefs evoked by flow with impaired risk awareness and with risky behaviour. Theoretical implications for flow and risk research as well as practical implications for risk prevention are discussed.

A Finite Model Property for Gödel Modal Logics

A new semantics with the finite model property is provided and used to establish decidability for Gödel modal logics based on (crisp or fuzzy) Kripke frames combined locally with Gödel logic. A similar methodology is also used to establish decidability, and indeed co-NP-completeness for a Gödel S5 logic that coincides with the one-variable fragment of first-order Gödel logic.

Prognosis of Children with HIV-1 Infection Starting Antiretroviral Therapy in Southern Africa: A Collaborative Analysis of Treatment Programs

BACKGROUND: Prognostic models for children starting antiretroviral therapy (ART) in Africa are lacking. We developed models to estimate the probability of death during the first year receiving ART in Southern Africa. METHODS: We analyzed data from children ≤10 years old who started ART in Malawi, South Africa, Zambia or Zimbabwe from 2004-2010. Children lost to follow-up or transferred were excluded. The primary outcome was all-cause mortality in the first year of ART. We used Weibull survival models to construct two prognostic models: one with CD4%, age, WHO clinical stage, weight-for-age z-score (WAZ) and anemia and one without CD4%, because it is not routinely measured in many programs. We used multiple imputation to account for missing data. RESULTS: Among 12655 children, 877 (6.9%) died in the first year of ART. 1780 children were lost to follow-up/transferred and excluded from main analyses; 10875 children were included. With the CD4% model probability of death at 1 year ranged from 1.8% (95% CI: 1.5-2.3) in children 5-10 years with CD4% ≥10%, WHO stage I/II, WAZ ≥-2 and without severe anemia to 46.3% (95% CI: 38.2-55.2) in children <1 year with CD4% <5%, stage III/IV, WAZ< -3 and severe anemia. The corresponding range for the model without CD4% was 2.2% (95% CI: 1.8-2.7) to 33.4% (95% CI: 28.2-39.3). Agreement between predicted and observed mortality was good (C-statistics=0.753 and 0.745 for models with and without CD4% respectively). CONCLUSION: These models may be useful to counsel children/caregivers, for program planning and to assess program outcomes after allowing for differences in patient disease severity characteristics.

A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations

In the context of expensive numerical experiments, a promising solution for alleviating the computational costs consists of using partially converged simulations instead of exact solutions. The gain in computational time is at the price of precision in the response. This work addresses the issue of fitting a Gaussian process model to partially converged simulation data for further use in prediction. The main challenge consists of the adequate approximation of the error due to partial convergence, which is correlated in both design variables and time directions. Here, we propose fitting a Gaussian process in the joint space of design parameters and computational time. The model is constructed by building a nonstationary covariance kernel that reflects accurately the actual structure of the error. Practical solutions are proposed for solving parameter estimation issues associated with the proposed model. The method is applied to a computational fluid dynamics test case and shows significant improvement in prediction compared to a classical kriging model.

Flow disturbances in stent-related coronary evaginations: a computational fluid-dynamic simulation study

Aims: Angiographic ectasias and aneurysms in stented segments have been associated with late stent thrombosis. Using optical coherence tomography (OCT), some stented segments show coronary evaginations reminiscent of ectasias. The purpose of this study was to explore, using computational fluid-dynamic (CFD) simulations, whether OCT-detected coronary evaginations can induce local changes in blood flow. Methods and results: OCT-detected evaginations are defined as outward bulges in the luminal vessel contour between struts, with the depth of the bulge exceeding the actual strut thickness. Evaginations can be characterised cross ectionally by depth and along the stented segment by total length. Assuming an ellipsoid shape, we modelled 3-D evaginations with different sizes by varying the depth from 0.2-1.0 mm, and the length from 1-9 mm. For the flow simulation we used average flow velocity data from non-diseased coronary arteries. The change in flow with varying evagination sizes was assessed using a particle tracing test where the particle transit time within the segment with evagination was compared with that of a control vessel. The presence of the evagination caused a delayed particle transit time which increased with the evagination size. The change in flow consisted locally of recirculation within the evagination, as well as flow deceleration due to a larger lumen - seen as a deflection of flow towards the evagination. Conclusions: CFD simulation of 3-D evaginations and blood flow suggests that evaginations affect flow locally, with a flow disturbance that increases with increasing evagination size.