Infrastructure Engineering - Research Publications
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ItemVery early onset of amiodarone-induced pulmonary toxicity.(The Korean Society of Cardiology, 2013-10)Amiodarone is a widely used antiarrhythmic agent. Among its various adverse effects, amiodarone-induced pulmonary toxicity (APT) is the most life threatening complication, which has been described mostly in patients who have been in treatment with high accumulative doses for a long duration of time. However, amiodarone therapy in short-term duration induced APT was rarely reported. We describe a case of a 54-year-old man who is presented with symptoms of APT after a few days of therapy for post-myocardial infarction ventricular tachycardia. For early diagnosis and successful treatment, awareness and high suspicion of this rare type of early onset APT is crucial in patients with amiodarone therapy.
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ItemEndoplasmic reticulum stress promotes LIPIN2-dependent hepatic insulin resistance.(American Diabetes Association, 2011-04)OBJECTIVE: Diet-induced obesity (DIO) is linked to peripheral insulin resistance-a major predicament in type 2 diabetes. This study aims to identify the molecular mechanism by which DIO-triggered endoplasmic reticulum (ER) stress promotes hepatic insulin resistance in mouse models. RESEARCH DESIGN AND METHODS: C57BL/6 mice and primary hepatocytes were used to evaluate the role of LIPIN2 in ER stress-induced hepatic insulin resistance. Tunicamycin, thapsigargin, and lipopolysaccharide were used to invoke acute ER stress conditions. To promote chronic ER stress, mice were fed with a high-fat diet for 8-12 weeks. To verify the role of LIPIN2 in hepatic insulin signaling, adenoviruses expressing wild-type or mutant LIPIN2, and shRNA for LIPIN2 were used in animal studies. Plasma glucose, insulin levels as well as hepatic free fatty acids, diacylglycerol (DAG), and triacylglycerol were assessed. Additionally, glucose tolerance, insulin tolerance, and pyruvate tolerance tests were performed to evaluate the metabolic phenotype of these mice. RESULTS: LIPIN2 expression was enhanced in mouse livers by acute ER stress-inducers or by high-fat feeding. Transcriptional activation of LIPIN2 by ER stress is mediated by activating transcription factor 4, as demonstrated by LIPIN2 promoter assays, Western blot analyses, and chromatin immunoprecipitation assays. Knockdown of hepatic LIPIN2 in DIO mice reduced fasting hyperglycemia and improved hepatic insulin signaling. Conversely, overexpression of LIPIN2 impaired hepatic insulin signaling in a phosphatidic acid phosphatase activity-dependent manner. CONCLUSIONS: These results demonstrate that ER stress-induced LIPIN2 would contribute to the perturbation of hepatic insulin signaling via a DAG-protein kinase C ε-dependent manner in DIO mice.
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ItemThe within-day behaviour of 6 minute rainfall intensity in Australia(COPERNICUS GESELLSCHAFT MBH, 2011)Abstract. The statistical behaviour and distribution of high-resolution (6 min) rainfall intensity within the wet part of rainy days (total rainfall depth >10 mm) is investigated for 42 stations across Australia. This paper compares nine theoretical distribution functions (TDFs) in representing these data. Two goodness-of-fit statistics are reported: the Root Mean Square Error (RMSE) between the fitted and observed within-day distribution; and the coefficient of efficiency for the fit to the highest rainfall intensities (average intensity of the 5 highest intensity intervals) across all days at a site. The three-parameter Generalised Pareto distribution was clearly the best performer. Good results were also obtained from Exponential, Gamma, and two-parameter Generalized Pareto distributions, each of which are two parameter functions, which may be advantageous when predicting parameter values. Results of different fitting methods are compared for different estimation techniques. The behaviour of the statistical properties of the within-day intensity distributions was also investigated and trends with latitude, Köppen climate zone (strongly related to latitude) and daily rainfall amount were identified. The latitudinal trends are likely related to a changing mix of rainfall generation mechanisms across the Australian continent.
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ItemThe Murrumbidgee soil moisture monitoring network data set(American Geophysical Union, 2012-07-17)This paper describes a soil moisture data set from the 82,000 km2 Murrumbidgee River Catchment in southern New South Wales, Australia. Data have been archived from the Murrumbidgee Soil Moisture Monitoring Network (MSMMN) since its inception in September 2001. The Murrumbidgee Catchment represents a range of conditions typical of much of temperate Australia, with climate ranging from semiarid to humid and land use including dry land and irrigated agriculture, remnant native vegetation, and urban areas. There are a total of 38 soil moisture-monitoring sites across the Murrumbidgee Catchment, with a concentration of sites in three subareas. The data set is composed of 0–5 (or 0–8), 0–30, 30–60, and 60–90 cm average soil moisture, soil temperature, precipitation, and other land surface model forcing at all sites, together with other ancillary data. These data are available on the World Wide Web at http://www.oznet.org.au.
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ItemAnalytical methods for ecosystem resilience: A hydrological investigation(AMERICAN GEOPHYSICAL UNION, 2012-10-16)In recent years a number of papers have quantitatively explored multiple steady states and resilience within a wide range of hydrological systems. Many have identified multiple steady states by conducting simulations from different initial state variables and a few have used the more advanced technique of equilibrium or limit cycle continuation analysis to quantify how the number of steady states may change with a single model parameter. However, like resilience investigations into other natural systems, these studies often omit explanation of these fundamental resilience science techniques; rely on complex numerical methods rather than analytical methods; and overlook use of more advanced techniques from nonlinear systems mathematics. In the interests of wider adoption of advanced resilience techniques within hydrology, and advancing resilience science more broadly, this paper details fundamental methods for quantitative resilience investigations. Using a simple model of a spatially lumped unconfined aquifer, one and two parameter continuation analysis was undertaken algebraically. The shape of each steady state attractor basin was then quantified using Lyapunov stability curves derived at a range of precipitation rates, but was found to be inconsistent with the resilience behavior demonstrated by stochastic simulations. Most notably, and contrary to standard resilience concepts, the switching between steady states from wet or dry periods (and vice versa) did not occur by crossing of the threshold between the steady states. It occurred by exceedance of the two steady-state domain, producing a counterclockwise hysteresis loop. Additionally, temporary steady states were identified that could not have been detected using equilibrium continuation with a constant forcing rate. By combining these findings with the Lyapunov stability curves, new measures of resilience were developed for endogenous disturbances to the model and for the recovery from disturbances exogenous to the model.
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ItemSeasonal and event dynamics of spatial soil moisture patterns at the small catchment scale(AMERICAN GEOPHYSICAL UNION, 2012-10-27)Our understanding of short- and long-term dynamics of spatial soil moisture patterns is limited due to measurement constraints. Using new highly detailed data, this research aims to examine seasonal and event-scale spatial soil moisture dynamics in the topsoil and subsoil of the small spruce-covered Ẅstebach catchment, Germany. To accomplish this, univariate and geo-statistical analyses were performed for a 1 year long 4-D data set obtained with the wireless sensor network SoilNet. We found large variations in spatial soil moisture patterns in the topsoil, mostly related to meteorological forcing. In the subsoil, temporal dynamics were diminished due to soil water redistribution processes and root water uptake. Topsoil range generally increased with decreasing soil moisture. The relationship between the spatial standard deviation of the topsoil soil moisture (SDθ) and mean water content (θ) showed a convex shape, as has often been found in humid temperate climate conditions. Observed scatter in topsoil SD θ(θ) was explained by seasonal and event-scale SD θ(θ) dynamics, possibly involving hysteresis at both time scales. Clockwise hysteretic SDθ(θ) dynamics at the event scale were generated under moderate soil moisture conditions only for intense precipitation that rapidly wetted the topsoil and increased soil moisture variability controlled by spruce throughfall patterns. This hysteretic effect increased with increasing precipitation, reduced root water uptake, and high groundwater level. Intense precipitation on dry topsoil abruptly increased SDθ but only marginally increased mean soil moisture. This was due to different soil rewetting behavior in drier upslope areas (hydrophobicity and preferential flow caused minor topsoil recharge) compared with the moderately wet valley bottom (topsoil water storage), which led to a more spatially organized pattern. This study showed that spatial soil moisture patterns monitored by a wireless sensor network varied with depth, soil moisture content, seasonally, and within single wetting and drying episodes. This was controlled by multiple factors including soil properties, topography, meteorological forcing, vegetation, and groundwater.
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ItemAssimilation of stream discharge for flood forecasting: The benefits of accounting for routing time lags(AMERICAN GEOPHYSICAL UNION, 2013-04-01)General filtering approaches in hydrologic data assimilation, such as the ensemble Kalman filter (EnKF), are based on the assumption that uncertainty of the current background prediction can be reduced by correcting errors in the state variables at the same time step. However, this assumption may not be valid when assimilating stream discharge into hydrological models to correct soil moisture storage due to the time lag between the soil moisture and the discharge. In this paper, we explore the utility of an ensemble Kalman smoother (EnKS) for addressing this time-lag issue. The EnKF and the EnKS are compared for two different updating schemes with the probability distributed model (PDM) via synthetic experiments: (i) updating soil moisture only and (ii) updating soil moisture and routing states simultaneously. The results show that the EnKS is superior to the EnKF when only soil moisture is updated, while the EnKS and the EnKF exhibit similar results when both soil moisture and routing storages are updated. This suggests that the EnKS can better improve the stream flow forecasting for models that do not adopt storage-based routing schemes (e.g., unit-hydrograph-based routing). For models with dynamic routing stores, errors in soil moisture are transferred to the routing stores, which can be corrected effectively by real-time filters. The EnKS-based soil moisture updating scheme is also tested with the GR4H model, for which unit-hydrograph-based routing is used. The result confirms that the EnKS is superior to the EnKF in improving both soil moisture and stream flow forecasting.
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ItemDe-noising of passive and active microwave satellite soil moisture time series(AMERICAN GEOPHYSICAL UNION, 2013-07-28)Satellite microwave retrievals and in situ measurements of surface soil moisture are usually compared in the time domain. This paper examines their differences in the conjugate frequency domain to develop a spectral description of the satellite data, suggesting the presence of stochastic random and systematic periodic errors. Based on a semiempirical model of the observed power spectral density, we describe systematic designs of causal and noncausal filters to remove these erroneous signals. The filters are applied to the retrievals from active and passive satellite sensors and evaluated against field data from the Murrumbidgee Basin, southeast Australia, to show substantive increase in linear correlations.
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ItemEstimating global arthropod species richness: refining probabilistic models using probability bounds analysis(SPRINGER, 2013-02)A key challenge in the estimation of tropical arthropod species richness is the appropriate management of the large uncertainties associated with any model. Such uncertainties had largely been ignored until recently, when we attempted to account for uncertainty associated with model variables, using Monte Carlo analysis. This model is restricted by various assumptions. Here, we use a technique known as probability bounds analysis to assess the influence of assumptions about (1) distributional form and (2) dependencies between variables, and to construct probability bounds around the original model prediction distribution. The original Monte Carlo model yielded a median estimate of 6.1 million species, with a 90 % confidence interval of [3.6, 11.4]. Here we found that the probability bounds (p-bounds) surrounding this cumulative distribution were very broad, owing to uncertainties in distributional form and dependencies between variables. Replacing the implicit assumption of pure statistical independence between variables in the model with no dependency assumptions resulted in lower and upper p-bounds at 0.5 cumulative probability (i.e., at the median estimate) of 2.9-12.7 million. From here, replacing probability distributions with probability boxes, which represent classes of distributions, led to even wider bounds (2.4-20.0 million at 0.5 cumulative probability). Even the 100th percentile of the uppermost bound produced (i.e., the absolutely most conservative scenario) did not encompass the well-known hyper-estimate of 30 million species of tropical arthropods. This supports the lower estimates made by several authors over the last two decades.
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