The use of ZIP and CART to model cryptosporidiosis in relation to climatic variables

This research assesses the potential impact of weekly weather variability on the incidence of cryptosporidiosis disease using time series zero-inflated Poisson (ZIP) and classification and regression tree (CART) models. Data on weather variables, notified cryptosporidiosis cases and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Both time series ZIP and CART models show a clear association between weather variables (maximum temperature, relative humidity, rainfall and wind speed) and cryptosporidiosis disease. The time series CART models indicated that, when weekly maximum temperature exceeded 31°C and relative humidity was less than 63%, the relative risk of cryptosporidiosis rose by 13.64 (expected morbidity: 39.4; 95% confidence interval: 30.9–47.9). These findings may have applications as a decision support tool in planning disease control and risk management programs for cryptosporidiosis disease.

Gaseous air pollution and emergency hospital visits for hypertension in Beijing, China : a time-stratified case-crossover study

Background: A number of epidemiological studies have been conducted to research the adverse effects of air pollution on mortality and morbidity. Hypertension is the most important risk factor for cardiovascular mortality. However, few previous studies have examined the relationship between gaseous air pollution and morbidity for hypertension. ---------- Methods: Daily data on emergency hospital visits (EHVs) for hypertension were collected from the Peking University Third Hospital. Daily data on gaseous air pollutants (sulfur dioxide (SO2) and nitrogen dioxide (NO2)) and particulate matter less than 10 μm in aerodynamic diameter (PM10) were collected from the Beijing Municipal Environmental Monitoring Center. A time-stratified case-crossover design was conducted to evaluate the relationship between urban gaseous air pollution and EHVs for hypertension. Temperature and relative humidity were controlled for. ---------- Results: In the single air pollutant models, a 10 μg/m3 increase in SO2 and NO2 were significantly associated with EHVs for hypertension. The odds ratios (ORs) were 1.037 (95% confidence interval (CI): 1.004-1.071) for SO2 at lag 0 day, and 1.101 (95% CI: 1.038-1.168) for NO2 at lag 3 day. After controlling for PM10, the ORs associated with SO2 and NO2 were 1.025 (95% CI: 0.987-1.065) and 1.114 (95% CI: 1.037-1.195), respectively.---------- Conclusion: Elevated urban gaseous air pollution was associated with increased EHVs for hypertension in Beijing, China.

Bayesian spatiotemporal analysis of socio-ecologic drivers of Ross River Virus transmission in Queensland, Australia

This study aims to examine the impact of socio-ecologic factors on the transmission of Ross River virus (RRV) infection and to identify areas prone to social and ecologic-driven epidemics in Queensland, Australia. We used a Bayesian spatiotemporal conditional autoregressive model to quantify the relationship between monthly variation of RRV incidence and socio-ecologic factors and to determine spatiotemporal patterns. Our results show that the average increase in monthly RRV incidence was 2.4% (95% credible interval (CrI): 0.1–4.5%) and 2.0% (95% CrI: 1.6–2.3%) for a 1°C increase in monthly average maximum temperature and a 10 mm increase in monthly average rainfall, respectively. A significant spatiotemporal variation and interactive effect between temperature and rainfall on RRV incidence were found. No association between Socio-economic Index for Areas (SEIFA) and RRV was observed. The transmission of RRV in Queensland, Australia appeared to be primarily driven by ecologic variables rather than social factors.

Evidence of disagreement between patient-perceived change and conventional longitudinal evaluation of change in health-related quality of life among older adults

Objective: To identify agreement levels between conventional longitudinal evaluation of change (post–pre) and patient-perceived change (post–then test) in health-related quality of life. Design: A prospective cohort investigation with two assessment points (baseline and six-month follow-up) was implemented. Setting: Community rehabilitation setting. Subjects: Frail older adults accessing community-based rehabilitation services. Intervention: Nil as part of this investigation. Main measures: Conventional longitudinal change in health-related quality of life was considered the difference between standard EQ-5D assessments completed at baseline and follow-up. To evaluate patient-perceived change a ‘then test’ was also completed at the follow-up assessment. This required participants to report (from their current perspective) how they believe their health-related quality of life was at baseline (using the EQ-5D). Patient-perceived change was considered the difference between ‘then test’ and standard follow-up EQ-5D assessments. Results: The mean (SD) age of participants was 78.8 (7.3). Of the 70 participants 62 (89%) of data sets were complete and included in analysis. Agreement between conventional (post–pre) and patient-perceived (post–then test) change was low to moderate (EQ-5D utility intraclass correlation coefficient (ICC)¼0.41, EQ-5D visual analogue scale (VAS) ICC¼0.21). Neither approach inferred greater change than the other (utility P¼0.925, VAS P¼0.506). Mean (95% confidence interval (CI)) conventional change in EQ-5D utility and VAS were 0.140 (0.045,0.236) and 8.8 (3.3,14.3) respectively, while patient-perceived change was 0.147 (0.055,0.238) and 6.4 (1.7,11.1) respectively. Conclusions: Substantial disagreement exists between conventional longitudinal evaluation of change in health-related quality of life and patient-perceived change in health-related quality of life (as measured using a then test) within individuals.

The delta-phase spectrum with application to voice activity detection and speaker recognition

For several reasons, the Fourier phase domain is less favored than the magnitude domain in signal processing and modeling of speech. To correctly analyze the phase, several factors must be considered and compensated, including the effect of the step size, windowing function and other processing parameters. Building on a review of these factors, this paper investigates a spectral representation based on the Instantaneous Frequency Deviation, but in which the step size between processing frames is used in calculating phase changes, rather than the traditional single sample interval. Reflecting these longer intervals, the term delta-phase spectrum is used to distinguish this from instantaneous derivatives. Experiments show that mel-frequency cepstral coefficients features derived from the delta-phase spectrum (termed Mel-Frequency delta-phase features) can produce broadly similar performance to equivalent magnitude domain features for both voice activity detection and speaker recognition tasks. Further, it is shown that the fusion of the magnitude and phase representations yields performance benefits over either in isolation.

Computed success rates of various carrier phase integer estimation solutions and their comparison with statistical success rates

The success rate of carrier phase ambiguity resolution (AR) is the probability that the ambiguities are successfully fixed to their correct integer values. In existing works, an exact success rate formula for integer bootstrapping estimator has been used as a sharp lower bound for the integer least squares (ILS) success rate. Rigorous computation of success rate for the more general ILS solutions has been considered difficult, because of complexity of the ILS ambiguity pull-in region and computational load of the integration of the multivariate probability density function. Contributions of this work are twofold. First, the pull-in region mathematically expressed as the vertices of a polyhedron is represented by a multi-dimensional grid, at which the cumulative probability can be integrated with the multivariate normal cumulative density function (mvncdf) available in Matlab. The bivariate case is studied where the pull-region is usually defined as a hexagon and the probability is easily obtained using mvncdf at all the grid points within the convex polygon. Second, the paper compares the computed integer rounding and integer bootstrapping success rates, lower and upper bounds of the ILS success rates to the actual ILS AR success rates obtained from a 24 h GPS data set for a 21 km baseline. The results demonstrate that the upper bound probability of the ILS AR probability given in the existing literatures agrees with the actual ILS success rate well, although the success rate computed with integer bootstrapping method is a quite sharp approximation to the actual ILS success rate. The results also show that variations or uncertainty of the unit–weight variance estimates from epoch to epoch will affect the computed success rates from different methods significantly, thus deserving more attentions in order to obtain useful success probability predictions.

Test and evaluation of non conventional instrument transformers and sampled value process bus on Powerlink's transmission network

IEC 61850 Process Bus technology has the potential to improve cost, performance and reliability of substation design. Substantial costs associated with copper wiring (designing, documentation, construction, commissioning and troubleshooting) can be reduced with the application of digital Process Bus technology, especially those based upon international standards. An IEC 61850-9-2 based sampled value Process Bus is an enabling technology for the application of Non-Conventional Instrument Transformers (NCIT). Retaining the output of the NCIT in its native digital form, rather than conversion to an analogue output, allows for improved transient performance, dynamic range, safety, reliability and reduced cost. In this paper we report on a pilot installation using NCITs communicating across a switched Ethernet network using the UCAIug Implementation Guideline for IEC 61850-9-2 (9-2 Light Edition or 9-2LE). This system was commissioned in a 275 kV Line Reactor bay at Powerlink Queensland’s Braemar substation in 2009, with sampled value protection IEDs 'shadowing' the existing protection system. The results of commissioning tests and twelve months of service experience using a Fibre Optic Current Transformer (FOCT) from Smart Digital Optics (SDO) are presented, including the response of the system to fault conditions. A number of remaining issues to be resolved to enable wide-scale deployment of NCITs and IEC 61850-9-2 Process Bus technology are also discussed.

Inclusion of PMU current phasor measurements in a power system state estimator

Three different methods of inclusion of current measurements by phasor measurement units (PMUs) in a power sysetm state estimator is investigated. A comprehensive formulation of the hybrid state estimator incorporating conventional, as well as PMU measurements, is presented for each of the three methods. The behaviour of the elements because of the current measurements in the measurement Jacobian matrix is examined for any possible ill-conditioning of the state estimator gain matrix. The performance of the state estimators are compared in terms of the convergence properties and the varian in the estimated states. The IEEE 14-bus and IEEE 300-bus systems are used as test beds for the study.

Pressure, oxygen tension and temperature in the periosteal callus during bone healing - An in vivo study in sheep

Adequate blood supply and sufficient mechanical stability are necessary for timely fracture healing. Damage to vessels impairs blood supply; hindering the transport of oxygen which is an essential metabolite for cells involved in repair. The degree of mechanical stability determines the mechanical conditions in the healing tissues. The mechanical conditions can influence tissue differentiation and may also inhibit revascularization. Knowledge of the actual conditions in a healing fracture in vivo is extremely limited. This study aimed to quantify the pressure, oxygen tension and temperature in the external callus during the early phase of bone healing. Six Merino-mix sheep underwent a tibial osteotomy. The tibia was stabilized with a standard mono-lateral external fixator. A multi-parameter catheter was placed adjacent to the osteotomy gap on the medial aspect of the tibia. Measurements of oxygen tension and temperature were performed for ten days post-op. Measurements of pressure were performed during gait on days three and seven. The ground reaction force and the interfragmentary movements were measured simultaneously. The maximum pressure during gait increased (p=0.028) from three (41.3 [29.2-44.1] mm Hg) to seven days (71.8 [61.8-84.8] mm Hg). During the same interval, there was no change (p=0.92) in the peak ground reaction force or in the interfragmentary movement (compression: p=0.59 and axial rotation: p=0.11). Oxygen tension in the haematoma (74.1 mm Hg [68.6-78.5]) was initially high post-op and decreased steadily over the first five days. The temperature increased over the first four days before reaching a plateau at approximately 38.5 degrees C on day four. This study is the first to report pressure, oxygen tension and temperature in the early callus tissues. The magnitude of pressure increased even though weight bearing and IFM remained unchanged. Oxygen tensions were initially high in the haematoma and fell gradually with a low oxygen environment first established after four to five days. This study illustrates that in bone healing the local environment for cells may not be considered constant with regard to oxygen tension, pressure and temperature.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design

Diversification and value-at-risk

A pervasive and puzzling feature of banks’ Value-at-Risk (VaR) is its abnormally high level, which leads to excessive regulatory capital. A possible explanation for the tendency of commercial banks to overstate their VaR is that they incompletely account for the diversification effect among broad risk categories (e.g., equity, interest rate, commodity, credit spread, and foreign exchange). By underestimating the diversification effect, bank’s proprietary VaR models produce overly prudent market risk assessments. In this paper, we examine empirically the validity of this hypothesis using actual VaR data from major US commercial banks. In contrast to the VaR diversification hypothesis, we find that US banks show no sign of systematic underestimation of the diversification effect. In particular, diversification effects used by banks is very close to (and quite often larger than) our empirical diversification estimates. A direct implication of this finding is that individual VaRs for each broad risk category, just like aggregate VaRs, are biased risk assessments.

Sparseness vs estimating conditional probabilities : some asymptotic results

One of the nice properties of kernel classifiers such as SVMs is that they often produce sparse solutions. However, the decision functions of these classifiers cannot always be used to estimate the conditional probability of the class label. We investigate the relationship between these two properties and show that these are intimately related: sparseness does not occur when the conditional probabilities can be unambiguously estimated. We consider a family of convex loss functions and derive sharp asymptotic results for the fraction of data that becomes support vectors. This enables us to characterize the exact trade-off between sparseness and the ability to estimate conditional probabilities for these loss functions.

Relationship between physical activity and stiff or painful joints in mid-aged women and older women: a 3-year prospective study

This prospective study examined the association between physical activity and the incidence of self-reported stiff or painful joints (SPJ) among mid-age women and older women over a 3-year period. Data were collected from cohorts of mid-age (48–55 years at Time 1; n = 4,780) and older women (72–79 years at Time 1; n = 3,970) who completed mailed surveys 3 years apart for the Australian Longitudinal Study on Women's Health. Physical activity was measured with the Active Australia questions and categorized based on metabolic equivalent value minutes per week: none (<40 MET.min/week); very low (40 to <300 MET.min/week); low (300 to <600 MET.min/week); moderate (600 to <1,200 MET.min/week); and high (1,200+ MET.min/week). Cohort-specific logistic regression models were used to examine the association between physical activity at Time 1 and SPJ 'sometimes or often' and separately 'often' at Time 2. Respondents reporting SPJ 'sometimes or often' at Time 1 were excluded from analysis. In univariate models, the odds of reporting SPJ 'sometimes or often' were lower for mid-age respondents reporting low (odds ratio (OR) = 0.77, 95% confidence interval (CI) = 0.63–0.94), moderate (OR = 0.82, 95% CI = 0.68–0.99), and high (OR = 0.75, 95% CI = 0.62–0.90) physical activity levels and for older respondents who were moderately (OR = 0.80, 95% CI = 0.65–0.98) or highly active (OR = 0.83, 95% CI = 0.69–0.99) than for those who were sedentary. After adjustment for confounders, these associations were no longer statistically significant. The odds of reporting SPJ 'often' were lower for mid-age respondents who were moderately active (OR = 0.71, 95% CI = 0.52–0.97) than for sedentary respondents in univariate but not adjusted models. Older women in the low (OR = 0.72, 95% CI = 0.55–0.96), moderate (OR = 0.54, 95% CI = 0.39–0.76), and high (OR = 0.61, 95% CI = 0.46–0.82) physical activity categories had lower odds of reporting SPJ 'often' at Time 2 than their sedentary counterparts, even after adjustment for confounders. These results are the first to show a dose–response relationship between physical activity and arthritis symptoms in older women. They suggest that advice for older women not currently experiencing SPJ should routinely include counseling on the importance of physical activity for preventing the onset of these symptoms.