Changes in the U.S. beef cow-calf industry, 1993-1997.

"N238.598"--P. [4] of cover.

Monitoring PAHs in the Brisbane River and Moreton Bay, Australia, using semipermeable membrane devices and EROD activity in yellowfin bream, Acanthopagrus australis

Two water quality monitoring strategies designed to sample hydrophobic organic contaminants have been applied and evaluated across an expected concentration gradient in PAHs in the Moreton region. Semipermeable membrane devices (SPMDs) that sequester contaminants via passive diffusion across a membrane were used to evaluate the concentration of PAHs at four and five sites in spring and summer 2001/2002, respectively. In addition, induction of hepatic cytochrome P4501, EROD activity, in yellowfin bream, Acanthopagrus australis, captured in the vicinity of SPMD sampling sites following deployment in summer was used as a biomarker of exposure to PAHs and related chemicals. SPMDs identified a clear and reproducible gradient in PAH contamination with levels increasing from east to west in Moreton Bay and upstream in the Brisbane River. The highest PAH concentrations expressed as B(a)P-toxicity equivalents (TEQs) were found in urban areas, which were also furthest upstream and experienced the least flushing. Cytochrome P4501 induction in A. australis was similar at all sites. The absence of clear trends in EROD activity may be attributable to factors not measured in this study or variable residency time of A. australis in contaminated areas. It is also possible that fish in the Moreton region are displaying enzymatic adaptation, which has been reported previously for fish subjected to chronic exposure to organic contaminants. These potential interferences complicate interpretation of EROD activity from feral biota. It is, therefore, suggested that future monitoring combine the two methods by applying passive sampler extracts to in vitro EROD assays. (C) 2004 Elsevier Ltd. All rights reserved.

Using nitrogen stable isotope ratios (delta N-15) of macroalgae to determine the effectiveness of sewage upgrades: changes in the extent of sewage plumes over four years in Moreton Bay, Australia

Nitrogen loading to aquatic ecosystems from sewage is recognised worldwide as a growing problem. The use of nitrogen stable isotopes as a means of discerning sewage nitrogen in the environment has been used annually by the Ecosystem Health Monitoring Program in Moreton Bay (Australia) since 1997 when the technique was first developed. This (sewage plume mapping) technique, which measures the delta(15)N isotopic signature of the red macroalga Catenella nipae after incubation in situ, has demonstrated a large reduction in the magnitude and spatial extent of sewage nitrogen within Moreton Bay over the past 5 years. This observed reduction coincides with considerable upgrades to the nitrogen removal efficacy at several sewage treatment plants within the region. This paper describes the observed changes and evaluates whether they can be attributed to the treatment upgrades. (c) 2004 Published by Elsevier Ltd.

Design options for sample-based mortality surveillance

Background Reliable information on causes of death is a fundamental component of health development strategies, yet globally only about one-third of countries have access to such information. For countries currently without adequate mortality reporting systems there are useful models other than resource-intensive population-wide medical certification. Sample-based mortality surveillance is one such approach. This paper provides methods for addressing appropriate sample size considerations in relation to mortality surveillance, with particular reference to situations in which prior information on mortality is lacking. Methods The feasibility of model-based approaches for predicting the expected mortality structure and cause composition is demonstrated for populations in which only limited empirical data is available. An algorithm approach is then provided to derive the minimum person-years of observation needed to generate robust estimates for the rarest cause of interest in three hypothetical populations, each representing different levels of health development. Results Modelled life expectancies at birth and cause of death structures were within expected ranges based on published estimates for countries at comparable levels of health development. Total person-years of observation required in each population could be more than halved by limiting the set of age, sex, and cause groups regarded as 'of interest'. Discussion The methods proposed are consistent with the philosophy of establishing priorities across broad clusters of causes for which the public health response implications are similar. The examples provided illustrate the options available when considering the design of mortality surveillance for population health monitoring purposes.

Using nitrogen stable isotope ratios ( d15N) of macroalgae to monitor changes in the extent of sewage impacts in Moreton Bay, Australia

During the past decade the use of stable isotopes to investigate transport pathways of nutrients in aquatic ecosystems has contributed new understanding and knowledge to many aspects of ecology; from the trophic structure of food webs to the spatial extent of nutrient discharges. At the same time aquatic monitoring programs around the world have become more interested in quantifying ecosystem health rather than simply measuring the physical and chemical properties of water (nutrients, pH, temperature and turbidity). A novel technique was initiated in 1998 as part of the development of the Ecosystem Health Monitoring Program in S.E. Queensland Australia (EHMP) using changes in the 15N value of the red macroalgae Catenella nipae, to indicate regions impacted by sewage nitrogen. Sewage plume mapping, using the 15N of C. nipae, has demonstrated that over the past 5 years there has been a large reduction in the magnitude and spatial extent of 15N enrichment at sites close to sewage treatment plants (STPs) discharging into Moreton Bay. This presentation will discuss how the 15N signatures of the C. nipae in the plume at the mouth of the Brisbane River have declined since it was first sampled in 1998 and will evaluate causes that may be responsible for these variations. A series of laboratory experiments were conducted to investigate how environmental conditions influence the 15N signature of C, nipae over the incubation period. These data will be used to discuss the observed in situ decline in 15N in an attempt to determine if the reduction can be attributed solely to improvements in the wastewater discharge.

Decision support system for inspection and maintenance:a case of oil pipelines

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is unproductive. A risk-based decision support system (DSS) that reduces the amount of time spent on inspection has been presented. The risk-based DSS uses the analytic hierarchy process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of occurrence of these risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost and the cumulative effect of failure is determined through probability analysis. The model optimizes the cost of pipeline operations by reducing subjectivity in selecting a specific inspection method, identifying and prioritizing the right pipeline segment for inspection and maintenance, deriving budget allocation, providing guidance to deploy the right mix labor for inspection and maintenance, planning emergency preparation, and deriving logical insurance plan. The proposed methodology also helps derive inspection and maintenance policy for the entire pipeline system, suggest design, operational philosophy, and construction methodology for new pipelines.

Risk-based maintenance model for offshore oil and gas pipelines:a case study

Offshore oil and gas pipelines are vulnerable to environment as any leak and burst in pipelines cause oil/gas spill resulting in huge negative Impacts on marine lives. Breakdown maintenance of these pipelines is also cost-intensive and time-consuming resulting in huge tangible and intangible loss to the pipeline operators. Pipelines health monitoring and integrity analysis have been researched a lot for successful pipeline operations and risk-based maintenance model is one of the outcomes of those researches. This study develops a risk-based maintenance model using a combined multiple-criteria decision-making and weight method for offshore oil and gas pipelines in Thailand with the active participation of experienced executives. The model's effectiveness has been demonstrated through real life application on oil and gas pipelines in the Gulf of Thailand. Practical implications. Risk-based inspection and maintenance methodology is particularly important for oil pipelines system, as any failure in the system will not only affect productivity negatively but also has tremendous negative environmental impact. The proposed model helps the pipelines operators to analyze the health of pipelines dynamically, to select specific inspection and maintenance method for specific section in line with its probability and severity of failure.

A risk-based model for inspection and maintenance of cross-country petroleum pipeline

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests efficient design and operation philosophy, construction methodology and logical insurance plans. The risk-based model uses Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

The move to servitization (from a product service system point of view)

Product Service Systems (PSSs) emphasize the substitution of products with services. The term “Servitisation” was introduced by Sandra Vendermerwe in the 80s to represent the addition of services to increase a company’s competitive edge. Key to PSS, and Servitisation more generally, is the “informated product”. The informated product enables health monitoring of the product in use and can be key to a workable PSS. This paper reviews the evolution of servitisation and the associated business benefit. It also then reviews the concept of informated product reconfiguration techniques and remote services that enables PSS to be delivered.

Analytic hierarchy process analyses risk of operating cross-country petroleum pipelines in India

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction methodology, and logical insurance plans. The risk-based model uses the analytic hierarchy process (AHP), a multiple-attribute decision-making technique, to identify the factors that influence failure on specific segments and to analyze their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

Real-time temperature estimation for power MOSFETs considering thermal ageing effects

This paper presents a novel real-time power-device temperature estimation method that monitors the power MOSFET's junction temperature shift arising from thermal aging effects and incorporates the updated electrothermal models of power modules into digital controllers. Currently, the real-time estimator is emerging as an important tool for active control of device junction temperature as well as online health monitoring for power electronic systems, but its thermal model fails to address the device's ongoing degradation. Because of a mismatch of coefficients of thermal expansion between layers of power devices, repetitive thermal cycling will cause cracks, voids, and even delamination within the device components, particularly in the solder and thermal grease layers. Consequently, the thermal resistance of power devices will increase, making it possible to use thermal resistance (and junction temperature) as key indicators for condition monitoring and control purposes. In this paper, the predicted device temperature via threshold voltage measurements is compared with the real-time estimated ones, and the difference is attributed to the aging of the device. The thermal models in digital controllers are frequently updated to correct the shift caused by thermal aging effects. Experimental results on three power MOSFETs confirm that the proposed methodologies are effective to incorporate the thermal aging effects in the power-device temperature estimator with good accuracy. The developed adaptive technologies can be applied to other power devices such as IGBTs and SiC MOSFETs, and have significant economic implications.

Mitigating inconsistencies by coupling data cleaning, filtering, and contextual data validation in wireless sensor networks

With the advent of peer to peer networks, and more importantly sensor networks, the desire to extract useful information from continuous and unbounded streams of data has become more prominent. For example, in tele-health applications, sensor based data streaming systems are used to continuously and accurately monitor Alzheimer's patients and their surrounding environment. Typically, the requirements of such applications necessitate the cleaning and filtering of continuous, corrupted and incomplete data streams gathered wirelessly in dynamically varying conditions. Yet, existing data stream cleaning and filtering schemes are incapable of capturing the dynamics of the environment while simultaneously suppressing the losses and corruption introduced by uncertain environmental, hardware, and network conditions. Consequently, existing data cleaning and filtering paradigms are being challenged. This dissertation develops novel schemes for cleaning data streams received from a wireless sensor network operating under non-linear and dynamically varying conditions. The study establishes a paradigm for validating spatio-temporal associations among data sources to enhance data cleaning. To simplify the complexity of the validation process, the developed solution maps the requirements of the application on a geometrical space and identifies the potential sensor nodes of interest. Additionally, this dissertation models a wireless sensor network data reduction system by ascertaining that segregating data adaptation and prediction processes will augment the data reduction rates. The schemes presented in this study are evaluated using simulation and information theory concepts. The results demonstrate that dynamic conditions of the environment are better managed when validation is used for data cleaning. They also show that when a fast convergent adaptation process is deployed, data reduction rates are significantly improved. Targeted applications of the developed methodology include machine health monitoring, tele-health, environment and habitat monitoring, intermodal transportation and homeland security.