Civil & Environmental Engineering Research Works

Permanent URI for this collectionhttp://hdl.handle.net/1903/1657

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End date: 2019

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Now showing 1 - 10 of 14
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    Elimination of Bloodstream Infections Associated with Candida albicans Biofilm in Intravascular Catheters
    (MDPI, 2015-06-29) Akbari, Freshta; Kjellerup, Birthe Veno
    Intravascular catheters are among the most commonly inserted medical devices and they are known to cause a large number of catheter related bloodstream infections (BSIs). Biofilms are associated with many chronic infections due to the aggregation of microorganisms. One of these organisms is the fungus Candida albicans. It has shown to be one of the leading causes of catheter-related BSIs. The presence of biofilm on intravascular catheters provide increased tolerance against antimicrobial treatments, thus alternative treatment strategies are sought. Traditionally, many strategies, such as application of combined antimicrobials, addition of antifungals, and removal of catheters, have been practiced, but they were not successful in eradicating BSIs. Since these fungal infections can result in significant morbidity, mortality, and increased healthcare cost, other promising preventive strategies, including antimicrobial lock therapy, chelating agents, alcohol, and biofilm disruptors, have been applied. In this review, current success and failure of these new approaches, and a comparison with the previous strategies are discussed in order to understand which preventative treatment is the most effective in controlling the catheter-related BSIs.
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    Model-Based Design and Formal Verification Processes for Automated Waterway System Operations
    (MDPI, 2016-06-07) Petnga, Leonard; Austin, Mark
    Waterway and canal systems are particularly cost effective in the transport of bulk and containerized goods to support global trade. Yet, despite these benefits, they are among the most under-appreciated forms of transportation engineering systems. Looking ahead, the long-term view is not rosy. Failures, delays, incidents and accidents in aging waterway systems are doing little to attract the technical and economic assistance required for modernization and sustainability. In a step toward overcoming these challenges, this paper argues that programs for waterway and canal modernization and sustainability can benefit significantly from system thinking, supported by systems engineering techniques. We propose a multi-level multi-stage methodology for the model-based design, simulation and formal verification of automated waterway system operations. At the front-end of development, semi-formal modeling techniques are employed for the representation of project goals and scenarios, requirements and high-level models of behavior and structure. To assure the accuracy of engineering predictions and the correctness of operations, formal modeling techniques are used for the performance assessment and the formal verification of the correctness of functionality. The essential features of this methodology are highlighted in a case study examination of ship and lock-system behaviors in a two-stage lock system.
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    Compositional Approach to Distributed System Behavior Modeling and Formal Validation of Infrastructure Operations with Finite State Automata: Application to Viewpoint-Driven Verification of Functionality in Waterways
    (MDPI, 2018-01-12) Austin, Mark A.; Johnson, John
    Now that modern infrastructure systems are moving toward an increased use of automation in their day-to-day operations, there is an emerging need for new approaches to the formal analysis and validation of system functionality with respect to correctness of operations. This paper describes a compositional approach to the multi-level behavior modeling and formal validation of large-scale distributed system operations with hierarchies and networks of finite state automata. To avoid the well-known state explosion problem, we develop a new procedure for viewpoint-action-process traceability, thereby allowing parts of a behavior model not relevant to a specific decision to be removed from consideration. Key features of the methodology are illustrated through the development of behavior models and validation procedures for polite conversation between two individuals, and lockset- and system-level concerns for ships traversing a large-scale waterway system.
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    Advancing Scientific Knowledge: Ethical Issues in the Journal Publication Process
    (MDPI, 2017-12-31) McCuen, Richard H.
    The goal of this paper is to assess the journal publication process from value and ethical perspectives. The specific objectives are: (1) To define fundamental values relevant to scientific journal publication; (2) To identify stakeholders involved in professional journals and their value rights and responsibilities; (3) To discuss the steps of the journal publication process where ethical dilemmas arise and the potential influences of such dilemmas on the advancement of knowledge; and (4) To summarize actions that can minimize unethical practices throughout the steps of the publication process. Values such as honesty, efficiency, accountability, and fairness will be discussed. Issues related to the various stakeholders such as self-citation, plagiarism, dual publication, a lack of timeliness, and issues related to authorship will be a primary focus.
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    A Novel Framework for Sustainable Traffic Safety Programs Using the Public as Sensors of Hazardous Road Information
    (MDPI, 2018-10-26) Chung, Younshik; Won, Minsu
    Traditionally, traffic safety improvement programs (TSIPs) have been based on the number of crashes at a specific location or their severity. However, the crash datasets used for such programs are obtained from the police and include two limitations: not all crashes are collected by the police (most minor and near-miss crashes are not reported), and the traditional process uses crash data recorded for the past two or three years (meaning most data inevitably include a time lag). To overcome these limitations, this study proposes a new approach for a TSIP based on citizen participation through an online survey that is broadcasted through social media. The method uses the public as sensors of hazardous road information, which means that information can be collected on individual experiences of minor crashes and latent risk factors, such as near misses and traffic conflicts. To demonstrate this approach, a case study was carried out in a small district in the city of Goyang, Korea, which has one of the highest usage rates of social media technologies. The proposed method and a traditional method were both assessed.
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    Machine Learning for Projecting Extreme Precipitation Intensity for Short Durations in a Changing Climate
    (MDPI, 2019-05-09) Hu, Huiling; Ayyub, Bilal M.
    Climate change is one of the prominent factors that causes an increased severity of extreme precipitation which, in turn, has a huge impact on drainage systems by means of flooding. Intensity–duration–frequency (IDF) curves play an essential role in designing robust drainage systems against extreme precipitation. It is important to incorporate the potential threat from climate change into the computation of IDF curves. Most existing works that have achieved this goal were based on Generalized Extreme Value (GEV) analysis combined with various circulation model simulations. Inspired by recent works that used machine learning algorithms for spatial downscaling, this paper proposes an alternative method to perform projections of precipitation intensity over short durations using machine learning. The method is based on temporal downscaling, a downscaling procedure performed over the time scale instead of the spatial scale. The method is trained and validated using data from around two thousand stations in the US. Future projection of IDF curves is calculated and discussed.
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    Exploring the Utility of Machine Learning-Based Passive Microwave Brightness Temperature Data Assimilation over Terrestrial Snow in High Mountain Asia
    (MDPI, 2019-09-28) Kwon, Yonghwan; Forman, Barton A.; Ahmad, Jawairia A.; Kumar, Sujay V.; Yoon, Yeosang
    This study explores the use of a support vector machine (SVM) as the observation operator within a passive microwave brightness temperature data assimilation framework (herein SVM-DA) to enhance the characterization of snow water equivalent (SWE) over High Mountain Asia (HMA). A series of synthetic twin experiments were conducted with the NASA Land Information System (LIS) at a number of locations across HMA. Overall, the SVM-DA framework is effective at improving SWE estimates (~70% reduction in RMSE relative to the Open Loop) for SWE depths less than 200 mm during dry snowpack conditions. The SVM-DA framework also improves SWE estimates in deep, wet snow (~45% reduction in RMSE) when snow liquid water is well estimated by the land surface model, but can lead to model degradation when snow liquid water estimates diverge from values used during SVM training. In particular, two key challenges of using the SVM-DA framework were observed over deep, wet snowpacks. First, variations in snow liquid water content dominate the brightness temperature spectral difference (ΔTB) signal associated with emission from a wet snowpack, which can lead to abrupt changes in SWE during the analysis update. Second, the ensemble of SVM-based predictions can collapse (i.e., yield a near-zero standard deviation across the ensemble) when prior estimates of snow are outside the range of snow inputs used during the SVM training procedure. Such a scenario can lead to the presence of spurious error correlations between SWE and ΔTB, and as a consequence, can result in degraded SWE estimates from the analysis update. These degraded analysis updates can be largely mitigated by applying rule-based approaches. For example, restricting the SWE update when the standard deviation of the predicted ΔTB is greater than 0.05 K helps prevent the occurrence of filter divergence. Similarly, adding a thin layer (i.e., 5 mm) of SWE when the synthetic ΔTB is larger than 5 K can improve SVM-DA performance in the presence of a precipitation dry bias. The study demonstrates that a carefully constructed SVM-DA framework cognizant of the inherent limitations of passive microwave-based SWE estimation holds promise for snow mass data assimilation.
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    Nuclear envelope laminopathies: evidence for developmentally inappropriate chromatin-nuclear envelope interactions
    (Springer Nature, 2013-03-18) Perovanovic, Jelena; Jaiswal, Jyoti; Markovic, Nikola; Hoffman, Eric
    During terminal differentiation of cells, there is typically a transition of the nuclear envelope from the Lamin B protein to Lamin A/C proteins. This is commensurate with exit from the cell cycle, and maintenance of the transcriptional programs associated with the terminally differentiated cells. Dominant missense mutations in Lamin A/C cause a broad spectrum of human genetic disorders, where specific point mutations are associated with defects in specific organs or tissues. We have previously presented a model where Lamin A/C mutations disrupt developmentally appropriate interactions between chromatin and the nuclear envelope and lead to poor coordination of E2F cell cycle pathways and terminal differentiation pathways [1]. One of the phenotypes caused by Lamin A/C mutations is Emery Dreifuss Muscular Dystrophy (EDMD). An X-linked recessive phenocopy of EDMD is caused by loss of function of emerin – a binding partner to Lamin A/C at the nuclear envelope. Here, we tested the hypothesis that emerin plays a role in chromatin remodeling via stabilizing nuclear lamina-heterochromatin interactions necessary for appropriate and time dependent muscle differentiation. We used WT and emerin null mouse myogenic stem cells to study transcriptional and epigenetic changes during in vitro exit from the cell cycle and differentiation to the myogenic lineage. Specific cell cycle (E2F) and myogenic genes were analyzed by qPCR and ChlP-qPCR to determine mRNA timing and H3K9me3 enrichment on gene promoters. Nuclear lamina-chromatin colocalization was determined and quantified by confocal imaging and Matlab. Our results showed that TK1 and other cell cycle genes are inappropriately persistently expressed in emerin null cells during differentiation causing delayed exit from cell cycle. Transcripts marking commitment to the myogenic lineage (myogenin and Mef5A) showed delayed activation on both mRNA and protein level. Epigenetic imprints predicted observed deviations from transcriptional timing in emerin null cells, with persistent suppressive chromatin state on myog promoter upon myogenic induction and failure to appropriately establish repressive histone marks (H3K9me3) on Tk1 promoter (cell cycle). Finally, we showed that the early cell cycle exit and terminal differentiation of emerin null myoblasts were accompanied by decreased H3K9me3 staining at the nuclear periphery (lamin A/C immunostaining). Myogenic cells lacking emerin exhibit perturbations in terminal commitment to the myogenic lineage. Our transcriptional, chromatin remodeling and gene promoter accessibility data show that both exit from cell cycle and terminal commitment to myogenesis are disrupted due to inappropriate heterochromatin-nuclear lamina interactions in EMD myogenic cells.
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    Utilization of Dynamic and Static Sensors for Monitoring Infrastructures
    (IntechOpen, 2018-12-12) Fu, Chung C.; Zhu, Yifan; Hou, Kuang-Yuan
    Infrastructures, including bridges, tunnels, sewers, and telecommunications, may be exposed to environmental-induced or traffic-induced deformation and vibrations. Some infrastructures, such as bridges and roadside upright structures, may be sensitive to vibration and displacement where several different types of dynamic and static sensors may be used for their measurement of sensitivity to environmental-induced loads, like wind and earthquake, and traffic-induced loads, such as passing trucks. Remote sensing involves either in situ, on-site, or airborne sensing where in situ sensors, such as strain gauges, displacement transducers, velometers, and accelerometers, are considered conventional but more durable and reliable. With data collected by accelerometers, time histories may be obtained, transformed, and then analyzed to determine their modal frequencies and shapes, while with displacement and strain transducers, structural deflections and internal stress distribution may be measured, respectively. Field tests can be used to characterize the dynamic and static properties of the infrastructures and may be further used to show their changes due to damage. Additionally, representative field applications on bridge dynamic testing, seismology, and earthborn/construction vibration are explained. Sensor data can be analyzed to establish the trend and ensure optimal structural health. At the end, five case studies on bridges and industry facilities are demonstrated in this chapter.
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    Development of a Fatigue Life Assessment Model for Pairing Fatigue Damage Prognoses with Bridge Management Systems
    (IntechOpen, 2018-12-18) Saad, Timothy; Fu, Chung C.; Zhao, Gengwen; Xu, Chaoran
    Fatigue damage is one of the primary safety concerns for steel bridges reaching the end of their design life. Currently, US federal requirements mandate regular inspection of steel bridges for fatigue cracks; however, these inspections rely on visual inspection, which is subjective to the inspector’s physically inherent limitations. Structural health monitoring (SHM) can be implemented on bridges to collect data between inspection intervals and gather supplementary information on the bridges’ response to loads. Combining SHM with finite element analyses, this paper integrates two analysis methods to assess fatigue damage in the crack initiation and crack propagation periods of fatigue life. The crack initiation period is evaluated using S-N curves, a process that is currently used by the FHWA and AASHTO to assess fatigue damage. The crack propagation period is evaluated with linear elastic fracture mechanic-based finite element models, which have been widely used to predict steady-state crack growth behavior. Ultimately, the presented approach will determine the fatigue damage prognoses of steel bridge elements and damage prognoses are integrated with current condition state classifications used in bridge management systems. A case study is presented to demonstrate how this approach can be used to assess fatigue damage on an existing steel bridge.