Sustainable Road Management in Texas : network-level flexible pavement structural condition analysis using data mining techniques

The research team recognized the value of network-level Falling Weight Deflectometer (FWD) testing to evaluate the structural condition trends of flexible pavements. However, practical limitations due to the cost of testing, traffic control and safety concerns and the ability to test a large network may discourage some agencies from conducting the network-level FWD testing. For this reason, the surrogate measure of the Structural Condition Index (SCI) is suggested for use. The main purpose of the research presented in this paper is to investigate data mining strategies and to develop a prediction method of the structural condition trends for network-level applications which does not require FWD testing. The research team first evaluated the existing and historical pavement condition, distress, ride, traffic and other data attributes in the Texas Department of Transportation (TxDOT) Pavement Maintenance Information System (PMIS), applied data mining strategies to the data, discovered useful patterns and knowledge for SCI value prediction, and finally provided a reasonable measure of pavement structural condition which is correlated to the SCI. To evaluate the performance of the developed prediction approach, a case study was conducted using the SCI data calculated from the FWD data collected on flexible pavements over a 5-year period (2005 – 09) from 354 PMIS sections representing 37 pavement sections on the Texas highway system. The preliminary study results showed that the proposed approach can be used as a supportive pavement structural index in the event when FWD deflection data is not available and help pavement managers identify the timing and appropriate treatment level of preventive maintenance activities.

Does metabolic compensation explain the majority of less-than-expected weight loss in obese adults during a short-term severe diet and exercise intervention?

Objective: We investigated to what extent changes in metabolic rate and composition of weight loss explained the less-than-expected weight loss in obese men and women during a diet-plus-exercise intervention. Design: 16 obese men and women (41 ± 9 years; BMI 39 ± 6 kg/m2) were investigated in energy balance before, after and twice during a 12-week VLED (565–650 kcal/day) plus exercise (aerobic plus resistance training) intervention. The relative energy deficit (EDef) from baseline requirements was severe (74-87%). Body composition was measured by deuterium dilution and DXA and resting metabolic rate (RMR) by indirect calorimetry. Fat mass (FM) and fat-free mass (FFM) were converted into energy equivalents using constants: 9.45 kcal/gFM and 1.13 kcal/gFFM. Predicted weight loss was calculated from the energy deficit using the '7700 kcal/kg rule'. Results: Changes in weight (-18.6 ± 5.0 kg), FM (-15.5 ± 4.3 kg), and FFM (-3.1 ± 1.9 kg) did not differ between genders. Measured weight loss was on average 67% of the predicted value, but ranged from 39 to 94%. Relative EDef was correlated with the decrease in RMR (R=0.70, P<0.01) and the decrease in RMR correlated with the difference between actual and expected weight loss (R=0.51, P<0.01). Changes in metabolic rate explained on average 67% of the less-than-expected weight loss, and variability in the proportion of weight lost as FM accounted for a further 5%. On average, after adjustment for changes in metabolic rate and body composition of weight lost, actual weight loss reached 90% of predicted values. Conclusion: Although weight loss was 33% lower than predicted at baseline from standard energy equivalents, the majority of this differential was explained by physiological variables. While lower-than-expected weight loss is often attributed to incomplete adherence to prescribed interventions, the influence of baseline calculation errors and metabolic down-regulation should not be discounted.

Genetic algorithms to schedule container transfers at multimodal terminals

Optimising the container transfer schedule at the multimodal terminals is known to be NP-hard, which implies that the best solution becomes computationally infeasible as problem sizes increase. Genetic Algorithm (GA) techniques are used to reduce container handling/transfer times and ships' time at the port by speeding up handling operations. The GA is chosen due to the relatively good results that have been reported even with the simplest GA implementations to obtain near-optimal solutions in reasonable time. Also discussed, is the application of the model to assess the consequences of increased scheduled throughput time as well as different strategies such as the alternative plant layouts, storage policies and number of yard machines. A real data set used for the solution and subsequent sensitivity analysis is applied to the alternative plant layouts, storage policies and number of yard machines.

Understanding teachers' reporting of child sexual abuse : measurement methods matter

The present study considered factors influencing teachers' reporting of child sexual abuse (CSA). Conducted in three Australian jurisdictions with different reporting laws and policies, the study focused on teachers' actual past and anticipated future reporting of CSA. A sample of 470 teachers within randomly selected rural and urban schools was surveyed, to identify training and experience; knowledge of reporting legislation and policy; attitudes; and reporting practices. Factors influencing actual past reporting and anticipated future reporting were identified using logistic regression modelling. This is the first study to simultaneously examine the effect of important influences in reporting practice using both retrospective and prospective approaches across jurisdictions with different reporting laws. Teachers who have actually reported CSA in the past are more likely have higher levels of policy knowledge, and hold more positive attitudes towards reporting CSA along three specific dimensions: commitment to the reporting role; confidence in the system's effective response to their reporting; and they are more likely to be able to override their concerns about the consequences of their reporting. Teachers indicating intention to report hypothetical scenarios are more likely to hold reasonable grounds for suspecting CSA, to recognise that significant harm has been caused to the child, to know that their school policy requires a report, and to be able to override their concerns about the consequences of their reporting.

Innovative damage assessment of steel truss bridges using modal strain energy correlation

As a part of vital infrastructure and transportation network, bridge structures must function safely at all times. Bridges are designed to have a long life span. At any point in time, however, some bridges are aged. The ageing of bridge structures, given the rapidly growing demand of heavy and fast inter-city passages and continuous increase of freight transportation, would require diligence on bridge owners to ensure that the infrastructure is healthy at reasonable cost. In recent decades, a new technique, structural health monitoring (SHM), has emerged to meet this challenge. In this new engineering discipline, structural modal identification and damage detection have formed a vital component. Witnessed by an increasing number of publications is that the change in vibration characteristics is widely and deeply investigated to assess structural damage. Although a number of publications have addressed the feasibility of various methods through experimental verifications, few of them have focused on steel truss bridges. Finding a feasible vibration-based damage indicator for steel truss bridges and solving the difficulties in practical modal identification to support damage detection motivated this research project. This research was to derive an innovative method to assess structural damage in steel truss bridges. First, it proposed a new damage indicator that relies on optimising the correlation between theoretical and measured modal strain energy. The optimisation is powered by a newly proposed multilayer genetic algorithm. In addition, a selection criterion for damage-sensitive modes has been studied to achieve more efficient and accurate damage detection results. Second, in order to support the proposed damage indicator, the research studied the applications of two state-of-the-art modal identification techniques by considering some practical difficulties: the limited instrumentation, the influence of environmental noise, the difficulties in finite element model updating, and the data selection problem in the output-only modal identification methods. The numerical (by a planer truss model) and experimental (by a laboratory through truss bridge) verifications have proved the effectiveness and feasibility of the proposed damage detection scheme. The modal strain energy-based indicator was found to be sensitive to the damage in steel truss bridges with incomplete measurement. It has shown the damage indicator's potential in practical applications of steel truss bridges. Lastly, the achievement and limitation of this study, and lessons learnt from the modal analysis have been summarised.

The utilization of waste date seed as bio-oil and activated carbon by pyrolysis process

The renovation of biomass waste in the form of date seed waste into activated carbon and biofuel by fixed bed pyrolysis reactor has been focused in this study to obtain gaseous, liquid, and solid products. The date seed in particle form is pyrolysed in an externally heated fixed bed reactor with nitrogen as the carrier gas. The reactor is heated from 400◦C to 600◦C. A maximum liquid yield of 50wt.% and char of 30wt.% are obtained at a reactor bed temperature of 500◦C with a running time of 120 minutes. The oil is found to possess favorable flash point and reasonable density and viscosity. The higher calorific value is found to be 28.636 MJ/kg which is significantly higher than other biomass derived. Decolonization of 85–97% is recorded for the textile effluent and 75–90% for the tannery effluent, in all cases decreasing with temperature increase. Good adsorption capacity of the prepared activated carbon in case of diluted textile and tannery effluent was found.

Fixed bed pyrolysis of date seed waste for liquid oil production

The conversion of biomass waste in the form of date seed into pyrolysis oil by fixed bed pyrolysis reactor has been taken into consideration in this study. A fixed bed pyrolysis has been designed and fabricated for obtaining liquid fuel from these date seeds. The major component of the system are fixed bed pyrolysis reactor, liquid condenser and liquid collector. The date seed in particle form is pyrolysed in an externally heated 7.6 cm diameter and 46 cm high fixed bed reactor with nitrogen as the carrier gas. The reactor is heated by means of a biomass source cylindrical heater from 4000C to 6000C. The products are oil, char and gas. The reactor bed temperature, running time and feed particle size are considered as process parameters. The parameters are found to influence the product yield significantly. A maximum liquid yield of 50 wt.% is obtained at a reactor bed temperature of 5000 C for a feed size volume of 0.11- 0.20 cm3 with a running time of 120 minutes. The pyrolysis oil obtained at this optimum process conditions are analyzed for some fuel properties and compared with some other biomass derived pyrolysis oils and also with conventional fuels. The oil is found to possess favorable flash point and reasonable density and viscosity. The higher calorific value is found to be 28.636 MJ/kg which is significantly higher than other biomass derived pyrolysis oils.

Spatial inequalities in colorectal and breast cancer survival : premature deaths and associated factors

This study examines the influence of cancer stage, distance to treatment facilities and area disadvantage on breast and colorectal cancer spatial survival inequalities. We also estimate the number of premature deaths after adjusting for cancer stage to quantify the impact of spatial survival inequalities. Population-based descriptive study of residents aged <90 years in Queensland, Australia diagnosed with primary invasive breast (25,202 females) or colorectal (14,690 males, 11,700 females) cancers during 1996-2007. Bayesian hierarchical models explored relative survival inequalities across 478 regions. Cancer stage and disadvantage explained the spatial inequalities in breast cancer survival, however spatial inequalities in colorectal cancer survival persisted after adjustment. Of the 6,019 colorectal cancer deaths within 5 years of diagnosis, 470 (8%) were associated with spatial inequalities in non-diagnostic factors, i.e. factors beyond cancer stage at diagnosis. For breast cancers, of 2,412 deaths, 170 (7%) were related to spatial inequalities in non-diagnostic factors. Quantifying premature deaths can increase incentive for action to reduce these spatial inequalities.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Pyrolysis decomposition of mahogony seeds (Swietenia macrophylla) for alternative fuel oil

A fixed bed pyrolysis has been designed and fabricated for obtaining liquid fuel from Mahogany seeds. The major components of the system are fixed bed pyrolysis reactor, liquid condenser and liquid collectors. The Mahogany seed in particle form is pyrolysed in an externally heated 10 cm diameter and 36 cm high fixed bed reactor with nitrogen as the carrier gas. The reactor is heated by means of a biomass source cylindrical heater from 450oC to 600oC. The products are oil, char and gas. The reactor bed temperature, running time and feed particle size are considered as process parameters. A maximum liquid yield of 54wt% of biomass feed is obtained with particle size of 1.18 mm at a reactor bed temperature of 5500C with a running time of 90 minutes. The oil is found to possess favorable flash point and reasonable density and viscosity. The higher calorific value is found to be 39.9 MJ/kg which is higher than other biomass derived pyrolysis oils.

Fixed bed pyrolysis of pulm seed waste for liquid oil production

Among various thermo-chemical conversion processes, pyrolysis is considered as an emerging technology for liquid oil production. The conversion of biomass waste in the form of plum seed into pyrolysis oil by fixed bed pyrolysis reactor has been taken into consideration in this study. A fixed bed pyrolysis has been designed and fabricated for obtaining liquid fuel from this plum seeds. The major component of the system are fixed bed pyrolysis reactor, liquid condenser and liquid collectors. The plum seed in particle form is pyrolysed in an externally heated 7.6 cm diameter and 46 cm high fixed bed reactor with nitrogen as the carrier gas. The reactor is heated by means of a biomass source cylindrical heater from 4000C to 6000C. The products are oil, char and gas. The reactor bed temperature, running time and feed particle size are considered as process parameters. The parameters are found to influence the product yield significantly. A maximum liquid yield of 39 wt% of biomass feed is obtained with particle size of 2.36-4.75 mm at a reactor bed temperature of 520oC with a running time of 120 minutes. The pyrolysis oil obtained at this optimum process conditions are analyzed for some fuel properties and compared with some other biomass derived pyrolysis oils and conventional fuels. The oil is found to possess favorable flash point and reasonable density and viscosity. The higher calorific value is found to be 22.39 MJ/kg which is higher than other biomass derived pyrolysis oils.

Production of liquid fuel and activated carbon from mahogany seed by using pyrolysis technology

The renovation of biomass waste in the form of Mahogany seed waste into bio-fuel as well as activated carbon by fixed bed pyrolysis reactor has been taken into consideration in this study. The mahogany seed in particle form is pyrolyzed in an enormously heated fixed bed reactor with nitrogen as the carrier gas. The reactor is heated from 4000C to 6000C using a external heater in which rice husk and charcoal are used as the heater biomass fuel. Reactor bed temperature, running time and feed particle size have been varied to get the optimum operating conditions of the system. The parameters are found to influence the product yields to a large extent. A maximum liquid and char yield are 49 wt. % and 35 wt. % respectively obtained at a reactor bed temperature 5000C when the running time is 90 minutes. Acquired pyrolyzed oil at these optimal process conditions were analyzed for some of their properties as an alternative fuel. The oil possesses comparable flame temperature, favorable flash point and reasonable viscosity along with somewhat higher density. The kinematic viscosity of the derived fuel is 3.8 cSt and density is 1525 kg/m3. The higher calorific value is found 32.4 MJ/kg which is significantly higher than other biomass derived fuel. Moderate adsorption capacity of the prepared activated carbon in case of methyl blue & tea water was also revealed.

Infertility in Australia circa 1980 : an historical population perspective on the uptake of fertility treatment by Australian women born in 1946-51

Objective: To estimate the prevalence of lifetime infertility in Australian women born in 1946-51 and examine their uptake of treatment. Methods: Participants in the Australian Longitudinal Study on Women's Health born in 1946-51 (n=13,715) completed up to four mailed surveys from 1996 to 2004. The odds of infertility were estimated using logistic regression with adjustment for socio-demographic and reproductive factors. Results: Among participants, 92.1% had been pregnant. For women who had been pregnant (n=12738): 56.5% had at least one birth but no pregnancy loss (miscarriage and/or termination); 39.9% experienced both birth and loss; and 3.6% had a loss only. The lifetime prevalence of infertility was 11.0%. Among women who reported infertility (n=1511), 41.7% used treatment. Women had higher odds of infertility when they had reproductive histories of losses only (OR range 9.0-43.5) or had never been pregnant (OR=15.7, 95%CI 11.8-20.8); and higher odds for treatment: losses only (OR range 2.5-9.8); or never pregnant (1.96, 1.28-3.00). Women who delayed their first birth until aged 30+ years had higher odds of treatment (OR range 3.2-4.3). Conclusions: About one in ten women experienced infertility and almost half used some form of treatment, especially those attempting pregnancy after 1980. Older first time mothers had an increased uptake of treatment as assisted reproductive technologies (ART) developed. Implications: This study provided evidence of the early uptake of treatment prior to 1979 when the national register of invasive ART was developed and later uptake prior to 1998 when data on non-invasive ART were first collected.

Infertility resolved with or without fertility treatment in Australian women aged 31-36 years: A prospective, population-based study [abstract]

Birth outcomes during a three year period were compared for women with a history of infertility who did or did not use fertility treatment with hormones and/or in vitro fertilisation. Participants in the Australian Longitudinal Study on Women’s Health born in 1973-78 were randomly selected from the universal public health insurance database and completed up to five mailed surveys (1996-2009). Participants reported on their infertility and use of treatment at age 28-33 years (survey 4 (S4) in 2006) and 31-36 years (survey 5 (S5) in 2009). The odds of resolved infertility at S5 were estimated using logistic regression with adjustment for age, area of residence, private health insurance and male infertility. Among 7280 women who responded to both S4 and S5, 18.6% (n=1378) reported infertility. More than half (n=804, 56.8%) of these women did not use treatment and 43.9% (n=347) gave birth between S4 and S5. Compared to infertile women who did not use treatment, women who used treatment were more likely at S5 to have recently given birth (odds ratio (OR) = 1.59, 95% CI 1.26-2.00) or be pregnant (OR = 1.77, 1.27-2.46). Further, women who used treatment were more likely to have twins (3.37, 1.18-9.62), premature births (1.52, 0.95-2.43), or low birthweight babies (1.83, 0.70-2.53) compared to women who gave birth without using treatment. Many women aged up to 36 years with a history of infertility can conceive naturally over a three year period without the use of treatment.Women who have never had a prior birth may need to use treatment to resolve their infertility but they are at higher risk of poorer perinatal outcomes, such as premature or low birthweight babies.

Visual sensitivity loss in the central thirty degrees of visual field is associated with diabetic peripheral neuropathy

Aims/hypothesis: Impaired central vision has been shown to predict diabetic peripheral neuropathy (DPN). Several studies have demonstrated diffuse retinal neurodegenerative changes in diabetic patients prior to retinopathy development, raising the prospect that non-central vision may also be compromised by primary neural damage. We hypothesise that type 2 diabetic patients with DPN exhibit visual sensitivity loss in a distinctive pattern across the visual field, compared with a control group of type 2 diabetic patients without DPN. Methods: Increment light sensitivity was measured by standard perimetry in the central 30 degree of visual field for two age-matched groups of type 2 diabetic patients, with and without neuropathy (n=40/30). Neuropathy status was assigned using the neuropathy disability score. Mean visual sensitivity values were calculated globally, for each quadrant and for three eccentricities (0-10 degree , 11-20 degree and 21-30 degree ). Data were analysed using a generalised additive mixed model (GAMM). Results: Global and quadrant between-group visual sensitivity mean differences were marginally but consistently lower (by about 1 dB) in the neuropathy cohort compared with controls. Between-group mean differences increased from 0.36 to 1.81 dB with increasing eccentricity. GAMM analysis, after adjustment for age, showed these differences to be significant beyond 15 degree eccentricity and monotonically increasing. Retinopathy levels and disease duration were not significant factors within the model (p=0.90). Conclusions/interpretation: Visual sensitivity reduces disproportionately with increasing eccentricity in type 2 diabetic patients with peripheral neuropathy. This sensitivity reduction within the central 30 degree of visual field may be indicative of more consequential loss in the far periphery.