26800 research outputs found
Sort by
Iterative Driven Competency-Based Assessment in a First-Year Engineering Computation Module
No full textThis Complete Evidence Based Practice paper will explore one tool for supporting competency based assessment in a first-year engineering course. Competency-based assessment in a first-year engineering computation module offers a pathway to improve student engagement and enhance learning outcomes. Shifting the focus from traditional one-try assessment to a more dynamic evaluation of core computational skills—such as algorithmic loops, plotting, and functions—can enable deeper personalized learning experiences. The primary challenge is creating a more responsive, interactive relationship with every student, regardless of their previous content knowledge. Autograding systems can play a pivotal role in this relationship by providing instant, real-time feedback on students\u27 efforts. One approach to autograding systems is to allow autograding to occur during the assessment in an iterative process. To be effective, these systems must be designed to not only evaluate correctness but also analyze visual outputs like graphs and assess the intermediate steps of computation. This immediate iterative feedback loop follows the techniques content experts often deploy to solve challenging problems. This technique guides students to identify and correct mistakes as they learn, fostering deeper engagement with the material. By integrating real-time feedback driven evaluations, educators can create a more engaging learning environment that promotes essential computational reasoning skills. However, crafting automated feedback is time intensive and cost prohibitive, especially the first time. Collaborating problem sets, documenting observations and improvements we can aid to reduce these negative obstacles for broad implementation. In this paper we document the process implemented to transition a first-year engineering class MATLAB assessment into an autograded environment. We will demonstrate techniques to evaluate the components of a proper figure, and ways to randomize a problem in the commercial Mathworks Grader environment. We will compare student performance on the assessment, student’s perception on the experience and explore the effect on uniqueness in submissions. The students\u27 performance will be compared with a prior year\u27s standard assessment results, and students\u27 perception will be compared with a common end of course survey. Uniqueness of submissions will be evaluated with a tool to identify a percentage of similar lines of code. In the process of running an autograded environment educators are exposed to every early submission, so a metric of identifying which assessment objectives are the most challenging is collected as well. Through implementation of autograded assignments, our courses have identified a decrease in the time to engage with a challenging problem and ask questions. One core issue identified in deployment is the challenge in creating multiple problem sets or banks and the difficulty in writing broad validation code. The anticipated survey and performance results will discuss observed student performance, perception and the amount of non-unique submissions. This approach supports individual learning needs and better prepares students for future computational engineering challenges by making assessment a more dynamic and impactful part of their educational experience
Performance Characterization of a Point-Cloud-Based Path Planner in Off-Road Terrain
No full textWe present a comprehensive evaluation of a point-cloud-based navigation stack, MUONS, for autonomous off-road navigation. Performance is characterized by analyzing the results of 30,000 planning and navigation trials in simulation and validated through field testing. Our simulation campaign considers three kinematically challenging terrain maps and twenty combinations of seven path-planning parameters. In simulation, our MUONS-equipped AGV achieved a 0.98 success rate and experienced no failures in the field. By statistical and correlation analysis, we determined that the Bi-RRT expansion radius used in the initial planning stages is most correlated with performance in terms of planning time and traversed path length. Finally, we observed that the proportional variation due to changes in the tuning parameters is remarkably well correlated to performance in field testing. This finding supports the use of Monte-Carlo simulation campaigns for performance assessment and parameter tuning
The Impact of SGLT2 Inhibitors on Pulmonary Artery Pressures and Pulmonary Hemodynamics in Patients With Heart Failure: A Systematic Review
Full text linkBackground: Heart failure is a major global health burden associated with high morbidity and mortality. Elevated pulmonary artery pressures (PAP) are linked to worse outcomes in heart failure patients. Sodium–glucose cotransporter 2 (SGLT2) inhibitors, initially developed for diabetes, have demonstrated cardiovascular benefits, but their specific effects on pulmonary hemodynamics remain unclear.
Methods: This systematic review analyzed randomized controlled trials and observational cohort studies evaluating the effects of SGLT2 inhibitors on mean pulmonary artery pressure (mPAP) and pulmonary artery systolic pressure (PASP) in heart failure patients. A comprehensive search of PubMed, Embase, Cochrane Library, and Scopus databases was conducted until August 2024. Studies were appraised using PRISMA and AMSTAR guidelines, the Cochrane bias tool, and the Newcastle–Ottawa Scale.
Hypothesis: SGLT2 inhibitors reduce PAPs in heart failure patients, leading to beneficial pulmonary hemodynamic effects.
Results: Six studies (four RCTs and two observational; n = 346) were included. At rest, pooled analysis of three trials showed a significant reduction in mPAP (MD −1.41 mmHg; 95% CI −2.80 to −0.01; p = 0.05; I2 = 12%). During exercise, two studies demonstrated a nonsignificant reduction in mPAP (MD −3.12 mmHg; 95% CI −7.60 to 1.36; p = 0.17; I2 = 54%). For PASP, pooled analysis of four studies suggested a nonsignificant reduction (MD −6.72 mmHg; 95% CI −14.98 to 1.54; p = 0.11; I2 = 96%), but sensitivity analysis excluding one outlier yielded a significant effect (MD −2.76 mmHg; 95% CI −4.99 to −0.53; p = 0.02; I2 = 0%). Secondary outcomes included significant reductions in PCWP, PADP, and NT-proBNP.
Conclusion: SGLT2 inhibitors demonstrate beneficial effects on pulmonary pressures and hemodynamics in patients with heart failure, with consistent trends toward lower mPAP, PASP, and PCWP. Although results are influenced by study heterogeneity, the overall evidence suggests meaningful hemodynamic improvements. Larger, long-term randomized trials are warranted to clarify subgroup effects (HFrEF vs. HFpEF and dapagliflozin vs. empagliflozin) and establish clinical implications
Engineering the Immune Response to Biomaterials
No full textBiomaterials are increasingly used as implants in the body, but they often elicit tissue reactions due to the immune system recognizing them as foreign bodies. These reactions typically involve the activation of innate immunity and the initiation of an inflammatory response, which can persist as chronic inflammation, causing implant failure. To reduce these risks, various strategies have been developed to modify the material composition, surface characteristics, or mechanical properties of biomaterials. Moreover, bioactive materials have emerged as a new class of biomaterials that can induce desirable tissue responses and form a strong bond between the implant and the host tissue. In recent years, different immunomodulatory strategies have been incorporated into biomaterials as drug delivery systems. Furthermore, more advanced molecule and cell-based immunomodulators have been developed and integrated with biomaterials. These emerging strategies will enable better control of the immune response to biomaterials and improve the function and longevity of implants and, ultimately, the outcome of biomaterial-based therapies
Climate change threatens water resources for major field crops in the Serbian Danube River Basin by the mid-21st century
Full text linkStudy region: Serbian Danube River Basin Study focus: As climate change makes weather patterns more erratic, water supply for agriculture is becoming increasingly uncertain. This is concerning in the Serbian Danube River Basin, where crops are mainly rainfed and the growing season is becoming warmer and drier. Assessing the balance between future agricultural water demand and availability in a changing climate is critical to address agricultural water scarcity. To understand how changing climate will affect water availability during 2041–2070, we used the Soil and Water Assessment Tool+ hydrological model with field-scale crop rotations and irrigated extent data and forced with regional climate model data under two representative concentration pathways (RCP4.5 and RCP8.5). New hydrological insights for the region: Declining precipitation, increasing evaporative demand, and lack of widespread irrigation will intensify green water (i.e., soil moisture from rainfall that rainfed systems rely on) scarcity and crop water stress across the spring-planted, rainfed cropping systems in Serbia during the peak growing season. Irrigated fields, currently rare, are barely offsetting green water scarcity and crop water stress and will need to increase irrigation by 10–20 % just to maintain current levels of green water scarcity and crop water stress. These findings highlight that agricultural producers in Serbia will need to adjust agricultural practices and likely expand irrigation to tackle increased water demand, but this may reduce blue water availability
Developing a Benchmarking Methodology for Concrete Global Warming Potentials in North America
No full textThe objective of this paper is to develop a methodology for estimating the statistical distributions associated with cradle-to-gate (A1-A3) concrete global warming potentials (GWPs) within the United States. When applied, this methodology serves as a framework for identifying benchmarks for product-level GWP. Cement production contributes to approximately 90% of the GWP for concrete mixtures. In this study, publicly available environmental product declarations for Type I/II, Type IL, and Type III cements were collected and the best fitting distributions for the cement GWPs were established and used in Monte Carlo simulations for analyzing the impact of cement on concrete GWP benchmarks. The distribution parameters for GWPs of concretes incorporating each of the three cement types were calculated and applied to determine 20th percentile, 40th percentile, and average GWP reference values. Additionally, the concrete GWP results were compared to the national industry-average GWP for the same concrete class. While this paper focuses on exploring the statistical distributions to develop a benchmarking methodology for concrete A1-A3 GWPs, this methodology can be expanded to explore the distributions of other products, product classes, life cycle inventory modules, and environmental impact indicators
ThermalTrack Dataset- Training Images- Fused RGB LWIR- sequence 4
Full text linkWe present a wheel track detection system that leverages RGB- Thermal (RGB-T) imaging, where thermal channels reveal critical temperature differentials between compacted tracks and loose snow- tracks exhibit higher thermal inertia and lower reflectivity, emitting stronger radiation signatures even in visually homogeneous conditions. By fusing these distinctive thermal patterns with RGB spatial information, our method reliably identifies navigable tracks, enabling robust path-following in complete white-out conditions where snow textures and terrain features become indistinguishable
ThermalTrack Dataset- Training Images- Fused RGB LWIR- sequence 8
Full text linkWe present a wheel track detection system that leverages RGB- Thermal (RGB-T) imaging, where thermal channels reveal critical temperature differentials between compacted tracks and loose snow- tracks exhibit higher thermal inertia and lower reflectivity, emitting stronger radiation signatures even in visually homogeneous conditions. By fusing these distinctive thermal patterns with RGB spatial information, our method reliably identifies navigable tracks, enabling robust path-following in complete white-out conditions where snow textures and terrain features become indistinguishable
INITIAL FUNGAL DECOMPOSER COMMUNITY DETERMINES WOOD-DERIVED CARBON IN DISCRETE SOIL CARBON POOLS IN ASPEN CLEARCUTS
Full text linkSoil carbon storage can be affected by forest management activities that alter the amount of biomass at a site, including slash retention and salvage harvesting. Initial fungal colonization of retained biomass may affect soil carbon storage due to differences in fungal decomposition strategies. To examine the effect of wood addition on wood-derived soil carbon storage and the interaction between initial fungal decomposer communities and wood application depth, δ13C modified wood inoculated with white- or brown-rot fungi was applied to soils across Michigan’s Upper Peninsula. Wood-derived carbon was assessed after 3.5 years in bulk soil samples and in three discrete soil carbon density fractions. Linear mixed-effects models were used to assess these interactions. Wood addition significantly increased wood-derived soil carbon storage, regardless of wood application depth. Inoculation by white-rot fungal species resulted in significantly greater carbon storage than brown-rot fungal inoculation in bulk soil. When wood was added to the soil surface, results suggest that wood-derived C is greatest in the most stable C density fraction. Additionally, when wood was added to the soil surface, weak evidence suggested that white-rot inoculation resulted in greater carbon storage than brown-rot inoculation across all density fractions. These results demonstrate that initial fungal decomposer community colonization can affect soil carbon storage