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Equitable Infrastructure Management: A Systematic Literature Review
No full textTransportation infrastructure plays a vital role in driving prosperity but can also disproportionately burden communities, highlighting the importance of equity in infrastructure management. Despite over a decade of research, a comprehensive review of the state of the art and a clear research agenda across various infrastructure sectors remain lacking. Key questions include identifying primary research areas, evaluating geographic research coverage on equity across the US, and analyzing publishing trends, including top journals and publishers. This study conducts a thorough literature review on equity in infrastructure management, beginning with representative keywords to screen 1,405 articles from the Scopus database. Using Natural Language Processing techniques, relevant papers were filtered, resulting in 279 articles selected for in-depth analysis. Text mining approaches, including thematic analysis and topic modeling, provided insights into current research trends, gaps, and opportunities for advancing equity-related studies in infrastructure management. Findings emphasize the need for expanded geographic diversity, interdisciplinary collaboration, and broader research thrusts to advance equitable infrastructure systems
Hourly Simulated Power Production Data with Snow Loss Model at Existing Utility-Scale PV Sites (\u3e5 MW) in the U.S. Eastern Interconnection in 2018
No full textProject Summary: We ran PySAM power production simulations for utility-scale (\u3e5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2018. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory\u27s Utility-Scale Solar 2024 Edition dataset. See 2018_PV_existing_site_metadata.csv file for individual site metadata
Hourly Simulated Power Production Data with No Snow Loss Model at Existing Utility-Scale PV Sites (\u3e5 MW) in the U.S. Eastern Interconnection in 2022
No full textProject Summary: We ran PySAM power production simulations for utility-scale (\u3e5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2022. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory\u27s Utility-Scale Solar 2024 Edition dataset. See 2022_PV_existing_site_metadata.csv file for individual site metadata
Implementation of Machine Learning Algorithms for Mapping the Geological Units in the Vicinity of Posidonius Crater and the Eastern Rim of Mare Serenitatis
No full textRemote Sensing facilitates the systematic mapping of lunar geological units by integrating spectral, morphological and topographic data. The Moon’s diverse lithology, impact structures and space weathering effects provide an ideal site for the automated geological classification. This study utilized the Moon Mineralogy Mapper (M3) and Lunar Orbital Laser Altimeter (LOLA) data to implement two machine learning algorithms (random forest (RF) and support vector machine (SVM)) for classifying geological units in the Posidonius crater and eastern rim of Mare Serenitatis. Published geological maps were used to define training regions with spectral profiles of geological units serving as key parameters, supplemented by LOLA-derived elevation parameters. Classification was tested using training datasets of 30%, 50% and 70% to evaluate the data density effects on model performance. The highest classification accuracy was achieved with 70% training data, yielding an overall accuracy (OA) of 90.09% for RF and 78.4% OA for SVM, demonstrating RF’s superior performance. To evaluate the significance of mineralogical versus multi-sensor datasets, an independent RF classification was conducted using only M3 spectral bands. The standalone spectral data yielded an OA of 86%, demonstrating that mineralogical information alone provides robust classification but benefits significantly from the integration of topographic parameters. Inclusion of LOLA-derived parameters improved lithological boundary delineated by enhancing geomorphic contrast, mechanical competence differentiation and space weathering effects. For comparative assessment, a spectral matching technique using the Spectral Information Divergence (SID) algorithm was applied to the M3 dataset. The SID-based classification produced significantly lower accuracy (OA = 27.56%), highlighting the limitations of traditional spectral similarity approaches in geological mapping compared to machine learning models. This study highlights the potential of integrating multi-sensor datasets with machine learning algorithms for high accuracy lunar geological mapping. The proposed methodology provides a scalable and reproducible framework for automated geological classification on the Moon and other planetary bodies
Unveiling the Role of Coffee-Ring Effect in High-Resolution Rivulet-Type Conductive Line Formation
No full textThis study aims to investigate the effects of particle size and concentration on the formation of rivulet-type conductive lines based on detailed physical insights into the formation of coffee-ring patterns. Rather than being a phenomenon to be avoided, the coffee-ring effect can be strategically used to fabricate high-resolution conductive lines with multiring patterns. We first characterized the coffee-ring patterns formed by the evaporation of a single nanofluid droplet with silver particles. It was observed that increasing the particle concentration resulted in thicker and wider deposition patterns, with only minor dimensional variations caused by differences in particle size. Based on these insights, multiple nanofluid droplets were sequentially deposited, and their interactions were analyzed to form rivulet-type conductive lines, consequently determining the optimal center-to-center droplet spacing. Sheet resistance was measured using the well-known four-point probe method to assess the electrical performance. The results demonstrated that a higher particle concentration enhanced particle packing density, improved current flow, and significantly reduced sheet resistance
Minority Representation in State Departments of Transportation: A Descriptive Analysis
No full textThe transportation industry, a cornerstone of the US economy, faces a growing need to enhance diversity and inclusion to address persistent representation gaps across gender, race, and other dimensions. With many state Department of Transportation (DOT) employees nearing retirement, this challenge becomes even more pressing. This study provides a comprehensive analysis of 208,552 state DOT employee profiles, comparing workforce representation to American Community Survey data to quantify diversity gaps and highlight regional patterns. Results show that women account for only 22.51% of the workforce, while non-white groups represent 16.65%, with significant disparities across states. Notably, some states stand out by adopting innovative approaches like outreach programs, mentorship initiatives, and inclusive hiring practices that have effectively improved representation. By uncovering these gaps and successes, this research offers valuable insights to guide policymakers and DOT leaders in creating a more equitable and forward-thinking workforce
CORTICAL ACTIVATION PATTERNS IN A RAPID MOTOR DECISION-MAKING TASK IN YOUNGER AND OLDER ADULTS: AN fNIRS STUDY
No full textOlder adults often exhibit declines in executive control and rapid motor decision-making, which can impact everyday tasks such as driving or cooking. This study examined agerelated differences in dorsolateral prefrontal cortex (dlPFC) activation during two motor decision-making tasks using functional near-infrared spectroscopy (fNIRS). Twenty-nine younger and twenty-seven older adults completed the Object Hit (OH) and Object Hit & Avoid (OHA) tasks in the Kinarm End-Point system, which assessed perceptual-motor speed, coordination, and executive control. Results indicated that older adults exhibited significantly lower processing rates, reduced accuracy, and increased spatial errors. These deficits remained after adjusting for psychomotor speed. fNIRS results showed greater bilateral dlPFC activation in older adults across both tasks, aligning with compensatory models such as CRUNCH and STAC-r. These findings suggest that older adults recruit additional cognitive resources to maintain performance and emphasize the use of fNIRS to understand age-related changes in cognitive and motor integration
Lessons Learned from the Usability Assessment of an EHR-Based Tool to Support Adherence to Antihypertensive Medications
No full textBackground/Objective Uncontrolled hypertension is common and frequently related to inadequate adherence to prescribed medications, resulting in suboptimal blood pressure control and increased healthcare utilization. Although healthcare providers have the opportunity to improve medication adherence, they may lack the tools to address adherence at the point of care. This study aims to assess the usability of a digital tool designed to improve medication adherence and blood pressure control among patients with hypertension who are not adherent to therapy. By evaluating usability, the study seeks to refine the tool\u27s design, underscore the role of technology in managing hypertension, and provide insights to inform clinical decisions. Methods We performed qualitative usability testing of an electronic health record (EHR)-integrated intervention with medical assistants (MAs) and primary care providers (PCPs) from a large integrated health system. Usability was assessed with these end-users using the think aloud and near live approaches. This evaluation was guided by two frameworks: the End-User Computing Satisfaction Index (EUCSI) and the Technology Acceptance Model (TAM). Interviews were analyzed using a thematic analysis approach. Results Thematic saturation was reached after usability testing was performed with 10 participants, comprising 5 PCPs and 5 MAs. The study identified several strengths within the content, format, ease of use, timeliness, accuracy, and usefulness of the tool, including the user-friendly content presentation, the usefulness of adherence information, and timely alerts that fit into the workflow. Challenges centered around alert visibility and specificity of information. Conclusion Leveraging the two conceptual frameworks (TAM and EUCSI) to test the usability of the medication adherence tool was helpful. The tool\u27s several strengths and opportunities for improvement were found. The resulting suggestions will be used to support the enhancement of the design for optimal implementation in a clinical trial
Correction: Machinability of Solution Strengthened Ferritic Ductile Iron (International Journal of Metalcasting, (2025), 10.1007/s40962-025-01678-5)
No full textIn the original online version of this article there was an error in Fig. 1. The values in the Tested UTS MPa (ksi) column were incomplete. The original article was corrected
How to Boost Productivity Using Kanban Boards
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