Infrastructure Engineering - Research Publications
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ItemPrivacy- and context-aware release of trajectory data(ACM, 2020-03)The availability of large-scale spatio-temporal datasets along with the advancements in analytical models and tools have created a unique opportunity to create valuable insights into managing key areas of society from transportation and urban planning to epidemiology and natural disasters management. This has encouraged the practice of releasing/publishing trajectory datasets among data owners. However, an ill-informed publication of such rich datasets may have serious privacy implications for individuals. Balancing privacy and utility, as a major goal in the data exchange process, is challenging due to the richness of spatio-temporal datasets. In this article, we focus on an individual's stops as the most sensitive part of the trajectory and aim to preserve them through spatio-temporal perturbation. We model a trajectory as a sequence of stops and moves and propose an efficient algorithm that either substitutes sensitive stop points of a trajectory with moves from the same trajectory or introduces a minimal detour if no safe Point of Interest (POI) can be found on the same route. This hinders the amount of unnecessary distortion, since the footprint of the original trajectory is preserved as much as possible. Our experiments shows that our method balances user privacy and data utility: It protects privacy through preventing an adversary from making inferences about sensitive stops while maintaining a high level of similarity to the original dataset.
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ItemCharacterizing dominant hydrological processes under uncertainty: evaluating the interplay between model structure, parameter sampling, error metrics, and data information content(Copernicus Publications, 2020-03-23)<p>Hydrological models are conventionally evaluated in terms of their response surface or likelihood surface constructed with the model parameter space. To evaluate models as hypotheses, we developed the method of <em>Flux Mapping</em> to construct a hypothesis space based on model process representation. Here we defined the hypothesis space based on dominant runoff generating mechanisms, and acceptable model runs are defined as total simulated flow with similar (and minimal) model error simulated by distinct combinations of runoff components. We demonstrate that the hypothesis space in each modeling case is the result of interplay between the factors of model structure, parameter sampling, choice of error metric, and data information content. The aim of this study is to disentangle the role of each factor in this interplay. We used two model structures (SACRAMENTO and SIMHYD), two parameter sampling approaches (small samples based on guided-search and large samples based on Latin Hypercube Sampling), three widely used error metrics (NSE, KGE, and WIA &#8212; Willmott&#8217;s Index of Agreement), and hydrological data from a range of Australian catchments. First, we characterized how the three error metrics behave under different error regimes independent of any modeling. We then conducted a series of controlled experiments, i.e. a type of one-factor-at-a-time sensitivity analysis, to unpack the role of each factor in runoff simulation. We show that KGE is a more reliable error metric compared to NSE and WIA for model evaluation. We also argue that robust error metrics and sufficient parameter sampling are necessary conditions for evaluating models as hypotheses under uncertainty. We particularly argue that sampling sufficiency, regardless of the sampling strategy, should be further evaluated based on its interaction with other modeling factors determining the model response. We conclude that the interplay of these modeling factors is complex and unique to each modeling case, and hence generalizing model-based inferences should be done with caution particularly in characterizing hydrological processes in large-sample hydrology.</p>
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ItemNo Preview AvailableThe acceptability and uptake of smartphone tracking for COVID-19 in Australia(Center for Open Science, 2020)
In response to the COVID-19 pandemic, many Governments are instituting mobile tracking technologies to perform rapid contact tracing. However, these technologies are only effective if the public is willing to use them, implying that their perceived public health benefits must outweigh personal concerns over privacy and security. The Australian federal government recently launched the `COVIDSafe' app, designed to anonymously register nearby contacts. If a contact later identifies as infected with COVID-19, health department officials can rapidly followup with their registered contacts to stop the virus' spread. The current study assessed attitudes towards three tracking technologies (telecommunication network tracking, a government app, and Apple and Google's Bluetooth exposure notification system) in two representative samples of the Australian public prior to the launch of COVIDSafe. We compared these attitudes to usage of the COVIDSafe app after its launch in a further two representative samples of the Australian public. Using Bayesian methods, we find widespread acceptance for all tracking technologies, however, observe a large intention-behaviour gap between people’s stated attitudes and actual uptake of the COVIDSafe app. We consider the policy implications of these results for Australia and the world at large.
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ItemSatellite cell-specific ablation of Cdon impairs integrin activation, FGF signalling, and muscle regeneration.(Wiley, 2020-08)BACKGROUND: Perturbation in cell adhesion and growth factor signalling in satellite cells results in decreased muscle regenerative capacity. Cdon (also called Cdo) is a component of cell adhesion complexes implicated in myogenic differentiation, but its role in muscle regeneration remains to be determined. METHODS: We generated inducible satellite cell-specific Cdon ablation in mice by utilizing a conditional Cdon allele and Pax7 CreERT2 . To induce Cdon ablation, mice were intraperitoneally injected with tamoxifen (tmx). Using cardiotoxin-induced muscle injury, the effect of Cdon depletion on satellite cell function was examined by histochemistry, immunostaining, and 5-ethynyl-2'-deoxyuridine (EdU) incorporation assay. Isolated myofibers or myoblasts were utilized to determine stem cell function and senescence. To determine pathways related to Cdon deletion, injured muscles were subjected to RNA sequencing analysis. RESULTS: Satellite cell-specific Cdon ablation causes impaired muscle regeneration with fibrosis, likely attributable to decreased proliferation, and senescence, of satellite cells. Cultured Cdon-depleted myofibers exhibited 32 ± 9.6% of EdU-positive satellite cells compared with 58 ± 4.4% satellite cells in control myofibers (P < 0.05). About 32.5 ± 3.7% Cdon-ablated myoblasts were positive for senescence-associated β-galactosidase (SA-β-gal) while only 3.6 ± 0.5% of control satellite cells were positive (P < 0.001). Transcriptome analysis of muscles at post-injury Day 4 revealed alterations in genes related to mitogen-activated protein kinase signalling (P < 8.29 e-5 ) and extracellular matrix (P < 2.65 e-24 ). Consistent with this, Cdon-depleted tibialis anterior muscles had reduced phosphorylated extracellular signal-regulated kinase (p-ERK) protein levels and expression of ERK targets, such as Fos (0.23-fold) and Egr1 (0.31-fold), relative to mock-treated control muscles (P < 0.001). Cdon-depleted myoblasts exhibited impaired ERK activation in response to basic fibroblast growth factor. Cdon ablation resulted in decreased and/or mislocalized integrin β1 activation in satellite cells (weak or mislocalized integrin1 in tmx = 38.7 ± 1.9%, mock = 21.5 ± 6%, P < 0.05), previously linked with reduced fibroblast growth factor (FGF) responsiveness in aged satellite cells. In mechanistic studies, Cdon interacted with and regulated cell surface localization of FGFR1 and FGFR4, likely contributing to FGF responsiveness of satellite cells. Satellite cells from a progeria model, Zmpste24-/- myofibers, showed decreased Cdon levels (Cdon-positive cells in Zmpste24-/- = 63.3 ± 11%, wild type = 90 ± 7.7%, P < 0.05) and integrin β1 activation (weak or mislocalized integrin β1 in Zmpste24-/- = 64 ± 6.9%, wild type = 17.4 ± 5.9%, P < 0.01). CONCLUSIONS: Cdon deficiency in satellite cells causes impaired proliferation of satellite cells and muscle regeneration via aberrant integrin and FGFR signalling.
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ItemMitochondrial Quality Control in the Heart: New Drug Targets for Cardiovascular Disease.(The Korean Society of Cardiology, 2020-05)Despite considerable efforts to prevent and treat cardiovascular disease (CVD), it has become the leading cause of death worldwide. Cardiac mitochondria are crucial cell organelles responsible for creating energy-rich ATP and mitochondrial dysfunction is the root cause for developing heart failure. Therefore, maintenance of mitochondrial quality control (MQC) is an essential process for cardiovascular homeostasis and cardiac health. In this review, we describe the major mechanisms of MQC system, such as mitochondrial unfolded protein response and mitophagy. Moreover, we describe the results of MQC failure in cardiac mitochondria. Furthermore, we discuss the prospects of 2 drug candidates, urolithin A and spermidine, for restoring mitochondrial homeostasis to treat CVD.
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ItemZNF746/PARIS overexpression induces cellular senescence through FoxO1/p21 axis activation in myoblasts.(Springer Science and Business Media LLC, 2020-05-12)Various stresses, including oxidative stress, impair the proliferative capacity of muscle stem cells leading to declined muscle regeneration related to aging or muscle diseases. ZNF746 (PARIS) is originally identified as a substrate of E3 ligase Parkin and its accumulation is associated with Parkinson's disease. In this study, we investigated the role of PARIS in myoblast function. PARIS is expressed in myoblasts and decreased during differentiation. PARIS overexpression decreased both proliferation and differentiation of myoblasts without inducing cell death, whereas PARIS depletion enhanced myoblast differentiation. Interestingly, high levels of PARIS in myoblasts or fibroblasts induced cellular senescence with alterations in gene expression associated with p53 signaling, inflammation, and response to oxidative stress. PARIS overexpression in myoblasts starkly enhanced oxidative stress and the treatment of an antioxidant Trolox attenuated the impaired proliferation caused by PARIS overexpression. FoxO1 and p53 proteins are elevated in PARIS-overexpressing cells leading to p21 induction and the depletion of FoxO1 or p53 reduced p21 levels induced by PARIS overexpression. Furthermore, both PARIS and FoxO1 were recruited to p21 promoter region and Trolox treatment attenuated FoxO1 recruitment. Taken together, PARIS upregulation causes oxidative stress-related FoxO1 and p53 activation leading to p21 induction and cellular senescence of myoblasts.
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ItemGrowth differentiation factor 15 protects against the aging-mediated systemic inflammatory response in humans and mice.(Wiley, 2020-08)Mitochondrial dysfunction is associated with aging-mediated inflammatory responses, leading to metabolic deterioration, development of insulin resistance, and type 2 diabetes. Growth differentiation factor 15 (GDF15) is an important mitokine generated in response to mitochondrial stress and dysfunction; however, the implications of GDF15 to the aging process are poorly understood in mammals. In this study, we identified a link between mitochondrial stress-induced GDF15 production and protection from tissue inflammation on aging in humans and mice. We observed an increase in serum levels and hepatic expression of GDF15 as well as pro-inflammatory cytokines in elderly subjects. Circulating levels of cell-free mitochondrial DNA were significantly higher in elderly subjects with elevated serum levels of GDF15. In the BXD mouse reference population, mice with metabolic impairments and shorter survival were found to exhibit higher hepatic Gdf15 expression. Mendelian randomization links reduced GDF15 expression in human blood to increased body weight and inflammation. GDF15 deficiency promotes tissue inflammation by increasing the activation of resident immune cells in metabolic organs, such as in the liver and adipose tissues of 20-month-old mice. Aging also results in more severe liver injury and hepatic fat deposition in Gdf15-deficient mice. Although GDF15 is not required for Th17 cell differentiation and IL-17 production in Th17 cells, GDF15 contributes to regulatory T-cell-mediated suppression of conventional T-cell activation and inflammatory cytokines. Taken together, these data reveal that GDF15 is indispensable for attenuating aging-mediated local and systemic inflammation, thereby maintaining glucose homeostasis and insulin sensitivity in humans and mice.
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ItemVision-based automated crack detection using convolutional neural networks for condition assessment of infrastructure(SAGE PUBLICATIONS LTD, 2020-11-01)With the growing number of aging infrastructure across the world, there is a high demand for a more effective inspection method to assess its conditions. Routine assessment of structural conditions is a necessity to ensure the safety and operation of critical infrastructure. However, the current practice to detect structural damages, such as cracks, depends on human visual observation methods, which are prone to efficiency, cost, and safety concerns. In this article, we present an automated detection method, which is based on convolutional neural network models and a non-overlapping window-based approach, to detect crack/non-crack conditions of concrete structures from images. To this end, we construct a data set of crack/non-crack concrete structures, comprising 32,704 training patches, 2074 validation patches, and 6032 test patches. We evaluate the performance of our approach using 15 state-of-the-art convolutional neural network models in terms of number of parameters required to train the models, area under the curve, and inference time. Our approach provides over 95% accuracy and over 87% precision in detecting the cracks for most of the convolutional neural network models. We also show that our approach outperforms existing models in literature in terms of accuracy and inference time. The best performance in terms of area under the curve was achieved by visual geometry group-16 model (area under the curve = 0.9805) and best inference time was provided by AlexNet (0.32 s per image in size of 256 × 256 × 3). Our evaluation shows that deeper convolutional neural network models have higher detection accuracies; however, they also require more parameters and have higher inference time. We believe that this study would act as a benchmark for real-time, automated crack detection for condition assessment of infrastructure.
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ItemOn investigating the potential effects of private autonomous vehicle use on home/work relocations and commute times(Elsevier Inc., 2020-01-01)The current study is motivated by the need to better understand the potential impacts that vehicular automation may have on individual decisions of residential and work relocation in a future autonomous vehicle (AV) scenario. The study employs a multivariate approach to model five behavioral dimensions simultaneously: (1) technology-savviness (TS) propensity, (2) interest in productive use of travel time (IPTT) propensity, (3) interest in work relocation, (4) interest in residential relocation, and (5) tolerance to an increase in commute travel time. Data from a web-based survey of commuters in 2017 in the Dallas-Fort Worth Metropolitan Area (DFW) is employed. The results show that both TS and IPTT, as well as demographic variables, impact relocation decisions when individuals have a private AV available for their commute. Importantly, there is considerable heterogeneity across individuals in the willingness to relocate and/or accept longer commute times in an AV future. As such, our model results may be used to inform inputs to land use and travel demand models in an AV future. Also, our results suggest that the magnitude of value of travel time savings (VTTS) decrease considered in many earlier AV impact simulation studies may be much higher than reality. Relative to 50% and even 100% VTTS decreases assumed in many studies, our results suggest a much more modest 30% or so overall decrease in VTTS because of the ability to commute in a privately-owned AV. Finally, our results do predict a rather substantial extent of urban sprawl due to AVs, potentially up to a 68% increase in the horizontal spread of cities such as Dallas-Fort Worth, unless proactive planning and policies are implemented to avert such consequences of AVs.
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ItemA comparison of online and in-person activity engagement: The case of shopping and eating meals(Elsevier BV, 2020-05)The virtual (online) and physical (in-person) worlds are increasingly inter-connected. Although there is considerable research into the effects of information and communication technologies (ICT) on activity-travel choices, there is little understanding of the inter-relationships between online and in-person activity participation and the extent to which the two worlds complement one another or substitute for one another. Shopping is one of the activity realms in which the virtual and physical spaces are increasingly interacting. This paper aims to unravel the relationships between online and in-person activity engagement in the shopping domain, while explicitly distinguishing between shopping for non-grocery goods, grocery products, and ready-to-eat meals. Data from the 2017 Puget Sound household travel survey is used to estimate a multivariate ordered probit model of the number of days in a week that a sample of households engages in in-person activity engagement and online activity engagement for each of these shopping activity types – leading to a model of six endogenous outcomes. Model results show that there are intricate complementary and substitution effects between in-person and online shopping activities, that these activities are considered as a single packaged bundle, and that the frequencies of these activities are significantly affected by income, built environment attributes, and household structure. The findings suggest that travel forecasting models should incorporate model components that capture the interplay between in-person and online shopping engagement and explicitly distinguish between non-grocery and grocery shopping activities. Policies that help bridge the digital divide so that households of all socio-economic strata can access goods and services in the virtual world would help improve quality of life for all. Finally, the paper highlights the need to bring passenger and freight demand modeling, at least within urban contexts, into a single integrated structure.