Scholarly Works, Civil and Environmental Engineering

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Atmospheric Deposition of Microplastics in South Central Appalachia in the United States
Elnahas, Adam; Gray, Austin; Lee, Jennie; AlAmiri, Noora; Pokhrel, Nishan; Allen, Steve; Foroutan, Hosein (American Chemical Society, 2024-12-26)
Due to the increased prevalence of plastic pollution globally, atmospheric deposition of microplastics (MPs) is a significant issue that needs to be better understood to identify potential consequences for human health. This study is the first to quantify and characterize atmospheric MP deposition in the Eastern United States. Passive sampling was conducted at two locations within the Eastern United States, specifically in remote South Central Appalachia, from March to September 2023. Each location had five sampling periods, with collections over a 21 day period. Samples were processed to remove biological material, and the presence of MPs was confirmed using Raman spectroscopy to match particles based on polymer similarity. The relative average atmospheric MP deposition in South Central Appalachia was determined to be 68 MPs m^-2 d^-1. Most verified MPs were fibers, and the most abundant polymer type identified was poly(ethylene terephthalate) PETE. This study's average MP deposition rate is qualitatively comparable to rates reported in other studies that employed a similar methodology in a similar landscape. Scaling up our measured deposition rate to all of South Central Appalachia, an area of over 94,000 km² and home to five million people, suggests a yearly MP deposition of approximately 321 metric tonnes. Our study highlights the prevalence of MP deposition in the Eastern United States, providing baseline data for future work to further assess routes of MP introduction.
Establishing performance criteria for evaluating watershed-scale sediment and nutrient models at fine temporal scales
Pandit, Aayush; Hogan, Sarah; Mahoney, David T.; Ford, William I.; Fox, James F.; Wellen, Christopher; Husic, Admin (Pergamon-Elsevier, 2025-01-18)
Watershed water quality models are mathematical tools used to simulate processes related to water, sediment, and nutrients. These models provide a framework that can be used to inform decision-making and the allocation of resources for watershed management. Therefore, it is critical to answer the question “when is a model good enough?” Established performance evaluation criteria, or thresholds for what is considered a ‘good’ model, provide common benchmarks against which model performance can be compared. Since the publication of prior meta-analyses on this topic, developments in the last decade necessitate further investigation, such as the advancement in high performance computing, the proliferation of aquatic sensors, and the development of machine learning algorithms. We surveyed the literature for quantitative model performance measures, including the Nash-Sutcliffe efficiency (NSE), with a particular focus on process-based models operating at fine temporal scales as their performance evaluation criteria are presently underdeveloped. The synthesis dataset was used to assess the influence of temporal resolution (sub-daily, daily, and monthly), calibration duration (< 3 years, 3 to 8 years, and > 8 years), and constituent target units (concentration, load, and yield) on model performance. The synthesis dataset includes 229 model applications, from which we use bootstrapping and personal modeling experience to establish sub-daily and daily performance evaluation criteria for flow, sediment, total nutrient, and dissolved nutrient models. For daily model evaluation, the NSE for sediment, total nutrient, and dissolved nutrient models should exceed 0.45, 0.30, and 0.35, respectively, for ‘satisfactory’ performance. Model performance generally improved when transitioning from short (< 3 years) to medium (3 to 8 years) calibration durations, but no additional gain was observed with longer (> 8 years) calibration. Dissolved nutrient models calibrated to load (e.g., kg/s) out-performed those calibrated to concentration (e.g., mg/L), whereas selection of target units was not significant for sediment and total nutrient models. We recommend the use of concentration rather than load as a water quality modeling target, as load may be biased by strong flow model performance whereas concentration provides a flow-independent measure of performance. Although the performance criteria developed herein are based on process-based models, they may be useful in assessing machine learning model performance. We demonstrate one such assessment on a recent deep learning model of daily nitrate prediction across the United States. The guidance presented here is intended to be used alongside, rather than to replace, the experience and modeling judgement of engineers and scientist who work to maintain our collective water resources.
Analyzing the Efficacy of Water Treatment Disinfectants as Vector Control: The Larvicidal Effects of Silver Nitrate, Copper Sulfate Pentahydrate, and Sodium Hypochlorite on Juvenile Aedes aegypti
Turner, Sydney S.; Smith, James A.; Howle, Sophie L.; Hancock, Patrick I.; Brett, Karin; Davis, Julia; Bruno, Lorin M.; Cecchetti, Victoria; Ford, Clay (MDPI, 2025-01-26)
For communities without access to uninterrupted, piped water, household water storage (HWS) practices can lead to adverse public health outcomes caused by water degradation and mosquito proliferation. With over 700,000 deaths caused by vector-borne diseases annually, the objective of this study was to determine whether water disinfectants, at concentrations deemed safe for human consumption and beneficial for water treatment, are effective in reducing the emergence of adult mosquitoes that transmit disease. Laboratory bioassays, designed to resemble the context of treating HWS containers, were conducted to assess the larvicidal effects of chemicals at concentrations below regulatory limits for drinking water: silver (20, 40, 80 μg/L Ag), copper (300, 600, 1200 μg/L Cu), and chlorine (500, 1000, 2000 ug/L free chlorine). The water disinfectants demonstrated the ability to significantly reduce the population of juvenile Ae. aegypti. Sodium hypochlorite was found to be the most effective in decreasing the survival rate of late first instar larvae, while silver nitrate exhibited the highest effectiveness in inhibiting the emergence of late third instar larvae. Ultimately, this study highlights the potential of an integrated approach to Water, Sanitation, and Health (WASH) solutions with vector control management.
Real-Time Turning Movement, Queue Length, and Traffic Density Estimation and Prediction Using Vehicle Trajectory and Stationary Sensor Data
Shafik, Amr K.; Rakha, Hesham A. (MDPI, 2025-01-30)
This paper introduces a two-stage adaptive Kalman filter algorithm to estimate and predict traffic states required for real-time traffic signal control. Leveraging probe vehicle trajectory and upstream detector data, turning movement (TM) counts in the vicinity of signalized intersections are estimated in the first stage, while the upstream approach density and queue sizes are estimated in the second stage. The proposed approach is evaluated using drone-collected and simulated data from a four-legged signalized intersection in Orlando, Florida. The performance of the two-stage approach is quantified relative to the baseline estimation without a Kalman filter. The results show that the Kalman filter is effective in enhancing traffic state estimates at various market penetration levels, where the filter both improves the estimation accuracy over the baseline case and provides reliable state predictions. In the first stage, the standard deviation (SD) in TM estimates improves by up to 50% compared to the estimates provided by the sole use of probe vehicle headings. The proposed approach also provides predictions with a minimal SD of 92.8 veh/h at a 5% level of market penetration. In the second stage, the proposed queue size estimation method results in an enhancement to the queue size estimation of up to 32.8% compared to the estimates obtained from the baseline approach. In addition, the estimated traffic density is enhanced by up to 18.5%. The proposed two-stage approach demonstrates the capability of providing reliable turning movement predictions across varying levels of market penetration. This highlights the readiness of this approach for practical application in real-time traffic signal control systems.
Adaptive modification of antiviral defense systems in microbial community under Cr-induced stress
Huang, Dan; Liao, Jingqiu; Balcazar, Jose L.; Ye, Mao; Wu, Ruonan; Wang, Dongsheng; Alvarez, Pedro J. J.; Yu, Pingfeng (BioMed Central, 2025-01-31)
Background: The prokaryotic antiviral defense systems are crucial for mediating prokaryote-virus interactions that influence microbiome functioning and evolutionary dynamics. Despite the prevalence and significance of prokaryotic antiviral defense systems, their responses to abiotic stress and ecological consequences remain poorly understood in soil ecosystems. We established microcosm systems with varying concentrations of hexavalent chromium (Cr(VI)) to investigate the adaptive modifications of prokaryotic antiviral defense systems under abiotic stress. Results: Utilizing hybrid metagenomic assembly with long-read and short-read sequencing, we discovered that antiviral defense systems were more diverse and prevalent in heavily polluted soils, which was corroborated by meta-analyses of public datasets from various heavy metal-contaminated sites. As the Cr(VI) concentration increased, prokaryotes with defense systems favoring prokaryote-virus mutualism gradually supplanted those with defense systems incurring high adaptive costs. Additionally, as Cr(VI) concentrations increased, enriched antiviral defense systems exhibited synchronization with microbial heavy metal resistance genes. Furthermore, the proportion of antiviral defense systems carried by mobile genetic elements (MGEs), including plasmids and viruses, increased by approximately 43% and 39%, respectively, with rising Cr concentrations. This trend is conducive to strengthening the dissemination and sharing of defense resources within microbial communities. Conclusions: Overall, our study reveals the adaptive modification of prokaryotic antiviral defense systems in soil ecosystems under abiotic stress, as well as their positive contributions to establishing prokaryote-virus mutualism and the evolution of microbial heavy metal resistance. These findings advance our understanding of microbial adaptation in stressful environments and may inspire novel approaches for microbiome manipulation and bioremediation.
Causal inference to scope environmental impact assessment of renewable energy projects and test competing mental models of decarbonization
Gazar, Amir M.; Borsuk, Mark E.; Calder, Ryan S. D. (IOP Publishing, 2024-11-25)
Environmental impact assessment (EIA), life cycle analysis (LCA), and cost benefit analysis (CBA) embed crucial but subjective judgments over the extent of system boundaries and the range of impacts to consider as causally connected to an intervention, decision, or technology of interest. EIA is increasingly the site of legal, political, and social challenges to renewable energy projects proposed by utilities, developers, and governments, which, cumulatively, are slowing decarbonization. Environmental advocates in the United States have claimed that new electrical interties with Canada increase development of Canadian hydroelectric resources, leading to environmental and health impacts associated with new reservoirs. Assertions of such second-order impacts of two recently proposed 9.5 TWh yr−1 transborder transmission projects played a role in their cancellation. We recast these debates as conflicting mental models of decarbonization, in which values, beliefs, and interests lead different parties to hypothesize causal connections between interrelated processes (in this case, generation, transmission, and associated impacts). We demonstrate via Bayesian network modeling that development of Canadian hydroelectric resources is stimulated by price signals and domestic demand rather than increased export capacity per se. However, hydropower exports are increasingly arranged via long-term power purchase agreements that may promote new generation in a way that is not easily modeled with publicly available data. We demonstrate the utility of causal inference for structured analysis of sociotechnical systems featuring phenomena that are not easily modeled mechanistically. In the setting of decarbonization, such analysis can fill a gap in available energy systems models that focus on long-term optimum portfolios and do not generally represent questions of incremental causality of interest to stakeholders at the local level. More broadly, these tools can increase the evidentiary support required for consequentialist (as opposed to attributional) LCA and CBA, for example, in calculating indirect emissions of renewable energy projects.
Establishing flood thresholds for sea level rise impact communication
Mahmoudi, Sadaf; Moftakhari, Hamed; Munoz, David F.; Sweet, William; Moradkhani, Hamid (Nature Portfolio, 2024-05-18)
Sea level rise (SLR) affects coastal flood regimes and poses serious challenges to flood risk management, particularly on ungauged coasts. To address the challenge of monitoring SLR at local scales, we propose a high tide flood (HTF) thresholding system that leverages machine learning (ML) techniques to estimate SLR and HTF thresholds at a relatively fine spatial resolution (10 km) along the United States’ coastlines. The proposed system, complementing conventional linear- and point-based estimations of HTF thresholds and SLR rates, can estimate these values at ungauged stretches of the coast. Trained and validated against National Oceanic and Atmospheric Administration (NOAA) gauge data, our system demonstrates promising skills with an average Kling-Gupta Efficiency (KGE) of 0.77. The results can raise community awareness about SLR impacts by documenting the chronic signal of HTF and providing useful information for adaptation planning. The findings encourage further application of ML in achieving spatially distributed thresholds.
Optimization of Zn Leaching Recovery from Tire Rubber and High-Purity ZnO Production
Li, Shiyu; Tran, Thien Q.; Ji, Bin; Brand, Alexander S.; Zhang, Wencai (Springer, 2024-12-18)
Waste tire rubber is regarded as a potential source for Zn recovery and recycling. In this study, the occurrence of modes of Zn was first characterized by an electron probe microanalyzer (EPMA), and the result indicated both ZnO and ZnS were present in the tire rubber. The Zn leaching recovery was optimized by response surface methodology, and temperature was identified as the most significant variable. The highest recovery of over 98% was obtained at 90 °C for 400 min when using 2.0 mol/L HNO3 as the lixiviant. After that, the Zn-containing leach liquor was subjected to solvent extraction for further separation and purification using bis(2,4,4-trimethylpentyl) phosphinic acid (Cyanex 272) and 2-ethylhexylphosphonic mono-2-ethylhexyl (PC88A) as extractants. Various parameters, such as equilibrium pH, extractant concentration, and organic-to-aqueous (O/A) ratio, were investigated to maximize the Zn extraction while minimizing the contamination of impurities. The result indicated that 0.1 mol/L Cyanex 272 exhibited a higher separation factor for Zn over major impurities compared to PC88A under the same conditions. To produce the high-purity ZnO, the Zn-loaded organic phase was subjected to stripping tests, and over 92% of Zn was stripped out with trace amounts of impurities. Finally, the pH value of the stripped solution was increased to precipitate Zn, and a final ZnO product with a purity of over 99% was obtained. This study provided a reference for waste tire rubber management and utilization.
Monitoring Wind and Particle Concentrations Near Freshwater and Marine Harmful Algal Blooms (HABs)
Bilyeu, Landon; Gonzalez-Rocha, Javier; Hanlon, Regina; AlAmiri, Noora; Foroutan, Hosein; Alading, Kun; Ross, Shane D.; Schmale, David G. III (Royal Society of Chemistry, 2023-10-05)
Harmful algal blooms (HABs) are a threat to aquatic ecosystems worldwide. New information is needed about the environmental conditions associated with the aerosolization and transport of HAB cells and their associated toxins. This information is critical to help inform our understanding of potential exposures. We used a ground-based sensor package to monitor weather, measure airborne particles, and collect air samples on the shore of a freshwater HAB (bloom of predominantly Rhaphidiopsis, Lake Anna, Virginia) and a marine HAB (bloom of Karenia brevis, Gulf Coast, Florida). Each sensor package contained a sonic anemometer, impinger, and optical particle counter. A drone was used to measure vertical profiles of windspeed and wind direction at the shore and above the freshwater HAB. At the Florida sites, airborne particle number concentrations (cm−3) increased throughout the day and the wind direction (offshore versus onshore) was strongly associated with these particle number concentrations (cm−3). Offshore wind sources had particle number concentrations (cm−3) 3 to 4 times higher than those of onshore wind sources. A predictive model, trained on a random set of weather and particle number concentrations (cm−3) collected over the same time period, was able to predict airborne particle number concentrations (cm−3) with an R squared value of 0.581 for the freshwater HAB in Virginia and an R squared value of 0.804 for the marine HAB in Florida. The drone-based vertical profiles of the wind velocity showed differences in wind speed and direction at different altitudes, highlighting the need for wind measurements at multiple heights to capture environmental conditions driving the atmospheric transport of aerosolized HAB toxins. A surface flux equation was used to determine the rate of aerosol production at the beach sites based on the measured particle number concentrations (cm−3) and weather conditions. Additional work is needed to better understand the short-term fate and transport of aerosolized cyanobacterial cells and toxins and how this is influenced by local weather conditions.
The impact of deicer and anti-icer use on plant communities in stormwater detention basins: Characterizing salt stress and phytoremediation potential
Long, S.; Rippy, Megan A.; Krauss, Lauren M.; Stacey, M.; Fausey, K. (Elsevier, 2025-01-15)
We present the results of a 1-year study that quantified salt levels in stormwater, soils, and plant tissues from 14 stormwater detention basins across Northern VA in an above-average snow year. We characterize (1) the level of salt stress plants experience, (2) the extent to which current plant communities feature salt tolerant species, and (3) the capacity of these species to phytoremediate soils and reduce the impacts of deicer and anti-icer use. Our results suggest that detention basin vegetation experience a range of salt stress levels that depend on drainage area type (roads: moderate to high > parking lots: low to moderate > pervious areas: none). Established thresholds for salt sensitive vegetation (Na⁺, Cl⁺, electrical conductivity, sodium adsorption ratio, exchangeable sodium percentage) were exceeded at least twice in stormwater or soils from all systems draining roads and half of systems draining parking lots. Winter exceedances were most common, but saline conditions did persist into the growing season, particularly at sites draining roads. Two hundred fifty-five plant species were identified across all detention basins, including 48 natives capable of tolerating elevated salt levels (electrical conductivity ≥2 dS/m). Within-tissue concentrations of sodium and chloride ions were highest in Typha (latifolia and angustifolia) (11.1 mg Na⁺/g; 30 mg Cl⁻ /g), making it our top phytoremediation candidate. Scaling these concentrations up, we estimate that a standard-size highway detention basin (2000–3000 m²) with 100 % cattail cover can phytoremediate up to 100 kg of Na⁺ and 200 kg of Cl⁻ per year. Uptake at this level is not sufficient to offset winter salt application, constituting only 5–6 % of basin inputs. This suggests that phytoremediation should not be considered a standalone solution to basin salinization, although it could be one approach of many in a broader salt management strategy.
Simple Energy Model for Hydrogen Fuel Cell Vehicles: Model Development and Testing
Ahn, Kyoungho; Rakha, Hesham A. (MDPI, 2024-12-18)
Hydrogen fuel cell vehicles (HFCVs) are a promising technology for reducing vehicle emissions and improving energy efficiency. Due to the ongoing evolution of this technology, there is limited comprehensive research and documentation regarding the energy modeling of HFCVs. To address this gap, the paper develops a simple HFCV energy consumption model using new fuel cell efficiency estimation methods. Our HFCV energy model leverages real-time vehicle speed, acceleration, and roadway grade data to determine instantaneous power exertion for the computation of hydrogen fuel consumption, battery energy usage, and overall energy consumption. The results suggest that the model’s forecasts align well with real-world data, demonstrating average error rates of 0.0% and −0.1% for fuel cell energy and total energy consumption across all four cycles. However, it is observed that the error rate for the UDDS drive cycle can be as high as 13.1%. Moreover, the study confirms the reliability of the proposed model through validation with independent data. The findings indicate that the model precisely predicts energy consumption, with an error rate of 6.7% for fuel cell estimation and 0.2% for total energy estimation compared to empirical data. Furthermore, the model is compared to FASTSim, which was developed by the National Renewable Energy Laboratory (NREL), and the difference between the two models is found to be around 2.5%. Additionally, instantaneous battery state of charge (SOC) predictions from the model closely match observed instantaneous SOC measurements, highlighting the model’s effectiveness in estimating real-time changes in the battery SOC. The study investigates the energy impact of various intersection controls to assess the applicability of the proposed energy model. The proposed HFCV energy model offers a practical, versatile alternative, leveraging simplicity without compromising accuracy. Its simplified structure reduces computational requirements, making it ideal for real-time applications, smartphone apps, in-vehicle systems, and transportation simulation tools, while maintaining accuracy and addressing limitations of more complex models.
Evidence of horizontal gene transfer and environmental selection impacting antibiotic resistance evolution in soil-dwelling Listeria
Goh, Ying-Xian; Anupoju, Sai Manohar Balu; Nguyen, Anthony; Zhang, Hailong; Ponder, Monica A.; Krometis, Leigh-Anne H.; Pruden, Amy; Liao, Jingqiu (Nature Research, 2024-11-19)
Soil is an important reservoir of antibiotic resistance genes (ARGs) and understanding how corresponding environmental changes influence their emergence, evolution, and spread is crucial. The soil-dwelling bacterial genus Listeria, including L. monocytogenes, the causative agent of listeriosis, serves as a keymodel for establishing this understanding. Here, we characterize ARGs in 594 genomes representing 19 Listeria species that we previously isolated from soils in natural environments across the United States. Among the five putatively functional ARGs identified, lin,which confers resistance to lincomycin, is the most prevalent, followed by mprF, sul, fosX, and norB. ARGs are predominantly found in Listeria sensu stricto species, with those more closely related to L. monocytogenes tending to harbor more ARGs. Notably, phylogenetic and recombination analyses provide evidence of recent horizontal gene transfer (HGT) in all five ARGs within and/or across species, likelymediated by transformation rather than conjugation and transduction. In addition, the richness and genetic divergence of ARGs are associated with environmental conditions, particularly soil properties (e.g., aluminum and magnesium) and surrounding land use patterns (e.g., forest coverage). Collectively, our data suggest that recent HGT and environmental selection play a vital role in the acquisition and diversification of bacterial ARGs in natural environments.
Assessment of the Production Variability and Composite Performance Index for Conventional and High Reclaimed Asphalt Pavement Balanced Mix Design Mixtures
Tong, Bilin; Habbouche, Jhony; Diefenderfer, Stacey D.; Flintsch, Gerardo W.; Boz, Ilker (Sage, 2024-11-08)
The balanced mix design (BMD) concept enables the design of engineered mixtures containing conventional and high reclaimed asphalt pavement (HRAP) contents, moving beyond the constraints of traditional volumetric design methodologies. During production, the designed mixture undergoes verification and potential modifications at the plant to accommodate actual production and field circumstances, regardless of the mix design method. This study assessed the impact of production and associated performance variability on a volumetrically designed control mixture and five mixtures designed with the BMD concept. This investigation showed relatively precise gradation control, but exceedances of volumetric property tolerances were observed in BMD-optimized mixtures during production. Performance, including durability, cracking, and rutting susceptibility, was evaluated using the Cantabro test, indirect tensile cracking test (IDT-CT), and asphalt pavement analyzer (APA) test, respectively. Test results uncovered that produced mixtures may become unbalanced. Observations from the Cantabro test and IDT-CT highlighted the necessity and effectiveness of employing the BMD for HRAP mixtures. The potential aging effect introduced during the reheating process may compromise durability and cracking resistance. In addition, a three-dimensional plot with a revised composite performance index (CPIR) was used to optimize the process of evaluating the mixture “balance” status among multiple primary performances. It revealed that almost all produced HRAP mixtures demonstrated a well-balanced status. Finally, agencies can use the CPIR as part of their acceptance program for BMD mixtures to determine a pay factor for possible bonuses or penalties.
Multi-level performance evaluation of BMD surface mixtures with conventional and high RAP contents: a case study in Virginia
Tong, Bilin; Habbouche, Jhony; Diefenderfer, Stacey D.; Flintsch, Gerardo W. (Taylor & Francis, 2024-03-07)
This study investigated one control and five Balanced Mix Design (BMD) optimised asphalt surface mixtures, four of which had high reclaimed asphalt pavement (RAP) contents (HRAP mixtures), using laboratory performance tests characterised with different levels of complexity. The performance of the evaluated mixtures was assessed based on durability, rutting resistance, and cracking resistance as emphasized by BMD. The study explored the ranking of a single index and correlations among various indices. Assisted by 3-Dimensional and ternary plots, this study also proposed a novel composite performance index [CPI] that combines major indices (durability, cracking, and rutting) to evaluate the performance of BMD optimised mixtures. The results revealed discrepancies between basic/intermediate performance test results and advanced performance test results. The comparisons conducted also underscored the beneficial impacts derived from using softer binders and/or recycling agents in HRAP mixtures. Furthermore, the findings indicated that the BMD approach can serve as an effective framework for designing asphalt mixtures that simultaneously enhance both fatigue and rutting performance. Moreover, the study revealed HRAP BMD surface mixtures can exhibit superior overall performance when compared to conventionally designed control mixtures.
Performance of four cardiac output monitoring techniques vs. intermittent pulmonary artery thermodilution during a modified passive leg raise maneuver in isoflurane-anesthetized dogs
Paranjape, Vaidehi V.; Henao-Guerrero, Natalia; Menciotti, Giulio; Saksena, Siddharth (Frontiers, 2023-09-14)
Objective: This study investigated the performance among four cardiac output (CO) monitoring techniques in comparison with the reference method intermittent pulmonary artery thermodilution (iPATD) and their ability to diagnose fluid responsiveness (FR) during a modified passive leg raise (PLRM) maneuver in isoflurane-anesthetized dogs undergoing acute blood volume manipulations. The study also examined the simultaneous effect of performing the PLRM on dynamic variables such as stroke distance variation (SDV), peak velocity variation (PVV), and stroke volume variation (SVV). Study design: Prospective, nonrandomized, crossover design. Study animals: Six healthy male Beagle dogs. Methods: The dogs were anesthetized with propofol and isoflurane and mechanically ventilated under neuromuscular blockade. After instrumentation, they underwent a series of sequential, nonrandomized steps: Step 1: baseline data collection; Step 2: removal of 33 mL kg−1 of circulating blood volume; Step 3: blood re-transfusion; and Step 4: infusion of 20 mL kg−1 colloid solution. Following a 10-min stabilization period after each step, CO measurements were recorded using esophageal Doppler (EDCO), transesophageal echocardiography (TEECO), arterial pressure waveform analysis (APWACO), and electrical cardiometry (ECCO). Additionally, SDV, PVV, and SVV were recorded. Intermittent pulmonary artery thermodilution (iPATDCO) measurements were also recorded before, during, and after the PLRM maneuver. A successful FR diagnosis made using a specific test indicated that CO increased by more than 15% during the PLRM maneuver. Statistical analysis was performed using one-way analysis of variance for repeated measures with post hoc Tukey test, linear regression, Lin’s concordance correlation coefficient (ρc), and Bland–Altman analysis. Statistical significance was set at p < 0.05. Results: All techniques detected a reduction in CO (p < 0.001) during hemorrhage and an increase in CO after blood re-transfusion and colloid infusion (p < 0.001) compared with baseline. During hemorrhage, CO increases with the PLRM maneuver were as follows: 33% for iPATD (p < 0.001), 19% for EC (p = 0.03), 7% for APWA (p = 0.97), 39% for TEE (p < 0.001), and 17% for ED (p = 0.02). Concurrently, decreases in SVV, SDV, and PVV values (p < 0.001) were also observed. The percentage error for TEE, ED, and EC was less than 30% but exceeded 55% for APWA. While TEECO and ECCO slightly underestimated iPATDCO values, EDCO and APWACO significantly overestimated iPATDCO values. TEE and EC exhibited good and acceptable agreement with iPATD. However, CO measurements using all four techniques and iPATD did not differ before, during, and after PLRM at baseline, blood re-transfusion, and colloid infusion. Conclusion and clinical relevance: iPATD, EC, TEE, and ED effectively assessed FR in hypovolemic dogs during the PLRM maneuver, while the performance of APWA was unacceptable and not recommended. SVV, SDV, and PVV could be used to monitor CO changes during PLRM and acute blood volume manipulations, suggesting their potential clinical utility.
Effects of the Traditional and Flipped Classrooms on Undergraduate Student Opinions and Success
Hotle, Susan; Garrow, Laurie A. (ASCE, 2016-01)
The flipped classroom is becoming increasingly popular at universities because of its perceived benefits in promoting active learning and decreasing educational costs. Studies have found positive benefits associated with flipped classrooms; however, many have failed to control for confounding factors. Examples of confounding factors include comparing courses taught by different instructors or across courses taught in different semesters using different quizzes. The objective of this paper is to compare the traditional and flipped classrooms in an undergraduate civil engineering course while controlling for potential confounding factors. The quasi-experimental study incorporates students’ online behaviors, in-class performance, office hour attendance, and responses to both attitudinal and behavioral questions to assess student opinions and learning outcomes. It was found that student performance on quizzes was not significantly different across the traditional and flipped classrooms. A key shortcoming noted with the flipped classroom was students’ inability to ask questions during lectures. Students in flipped classrooms were more likely to attend office hours compared to traditional classroom students, but the difference was not statistically significant. Future research should explore whether students’ inability to ask questions when the material is presented in flipped classrooms affects learning outcomes.
The Role of Competitor Pricing in Multiairport Choice
Hotle, Susan; Garrow, Laurie A. (Sage, 2014-01)
This paper investigates how competitors’ low-fare offerings in multi-airport regions influence the online search behavior of customers at a major carrier's website. Clickstream data from a major U.S. airline are combined with detailed information about competitors’ low-fare offerings for 10 directional markets. The use of a truncated negative binomial model allows the prediction of the number of searches on the carrier's website as a function of low-fare offerings for the same airport pair as well as for competing airport pairs in the region. The study finds that the number of searches decreases as the difference between the carrier's lowest fare and competitors’ lowest fare increases. However, trip characteristics have more impact on search behavior than do the fare variables. Overall search on the carrier's website is limited, with less than 5% of customers searching for fares across multiple airports. The findings provide insight into the role of competitor pricing on multiairport choice as it relates to customers’ online search behavior.
Cannabis pollen dispersal across the United States
Nimmala, Manu; Ross, Shane D.; Foroutan, Hosein (Nature Portfolio, 2024-09-04)
For the recently legalized US hemp industry (Cannabis sativa), cross-pollination between neighboring fields has become a significant challenge, leading to contaminated seeds, reduced oil yields, and in some cases, mandated crop destruction. As a step towards assessing hemp cross-pollination risk, this study characterizes the seasonal and spatial patterns in windborne hemp pollen dispersal spanning the conterminous United States (CONUS). By leveraging meteorological data obtained through mesoscale model simulations, we have driven Lagrangian Stochastic models to simulate wind-borne hemp pollen dispersion across CONUS on a county-by-county basis for five months from July to November, encompassing the potential flowering season for industrial hemp. Our findings reveal that pollen deposition rates escalate from summer to autumn due to the reduction in convective activity during daytime and the increase in wind shear at night as the season progresses. We find diurnal variations in pollen dispersion: nighttime conditions favor deposition in proximity to the source, while daytime conditions facilitate broader dispersal albeit with reduced deposition rates. These shifting weather patterns give rise to specific regions of CONUS more vulnerable to hemp cross-pollination.
Toward Collaborative Adaptation: Assessing Impacts of Coastal Flooding at the Watershed Scale
Mitchell, Allison; Bukvic, Anamaria; Shao, Yang; Irish, Jennifer L.; McLaughlin, Daniel L. (Springer Nature, 2022-12)
The U.S. Mid-Atlantic coastal region is experiencing higher rates of SLR than the global average, especially in Hampton Roads, Virginia, where this acceleration is primarily driven by land subsidence. The adaptation plans for coastal flooding are generally developed at the municipal level, ignoring the broader spatial implications of flooding outside the individual administrative boundaries. Flood impact assessments at the watershed scale would provide a more holistic perspective on what is needed to synchronize the adaptation efforts between the neighboring administrative units. This paper evaluates flooding impacts from sea level rise (SLR) and storm surge among watersheds in Hampton Roads to identify those most at risk of coastal flooding over different time horizons. It also explores the implications of flooding on the municipalities, the land uses, and land covers throughout this region within the case study watershed. The 2% Annual Exceedance Probability (AEP) storm surge flood hazard data and NOAA’s intermediate SLR projections were used to develop flooding scenarios for 2030, 2060, and 2090 and delineate land areas at risk of combined flooding. Findings show that five out of 98 watersheds will substantially increase in inundation, with two intersecting multiple municipalities. They also indicate significant inundation of military, commercial, and industrial land uses and wetland land covers. Flooding will also impact residential land use in urban areas along the Elizabeth River and Hampton city, supporting the need for collaborative adaptation planning on hydrologically influenced spatial scales.
The Impact of advance purchase deadlines on airline consumers’ search and purchase behaviors
Hotle, Susan; Castillo, Marco; Garrow, Laurie A.; Higgins, Matthew J. (Elsevier, 2015-12)
Airlines frequently use advance purchase ticket deadlines to segment consumers. Few empirical studies have investigated how individuals respond to advance purchase deadlines and price uncertainties induced by these deadlines. We model the number of searches (and purchases) for specific search and departure dates using an instrumental variable approach that corrects for price endogeneity. Results show that search and purchase behaviors vary by search day of week, days from departure, lowest offered fares, variation in lowest offered fares across competitors, and market distance. After controlling for the presence of web bots, we find that the number of consumer searches increases just prior to an advance purchase deadline. This increase can be explained by consumers switching their desired departure dates by one or two days to avoid higher fares that occur immediately after an advance purchase deadline has passed. This reallocation of demand has significant practical implications for the airline industry because the majority of revenue management and scheduling decision support systems currently do not incorporate these behaviors.

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