Le, Vi T.; Dannenberg, Andrew L. (2020). Moving Toward Physical Activity Targets by Walking to Transit: National Household Transportation Survey, 2001-2017. American Journal Of Preventive Medicine, 59(3), E115 – E123.
View Publication
Abstract
Introduction: Public transportation systems can help people engage in physical activity. This study assesses sociodemographic correlates and trends in the daily time spent walking to and from transit in the U.S. from 2001 to 2017. Methods: This cross-sectional study used data from the 2001, 2009, and 2017 National Household Transportation Survey. Data were analyzed in 2019 to assess the daily level of physical activity attained solely by walking to and from transit. Regression models were used to examine predictors of daily transit-associated walking. Results: Compared with the full National Household Transportation Survey sample, transit users who walked to and from transit tended to be younger, from households earning <$25,000 per year, in areas with rail infrastructure, and did not have a household-owned car. Transit walkers spent a median of 20 minutes per day (95% CI=18.5, 21.5) walking to and from transit in 2017, compared with a median of 19 minutes (95% CI=17.5, 20.5) in 2001. Among transit walkers, daily transitassociated physical activity was 27% higher for those residing in areas with rail infrastructure (adjusted coefficient=1.27, 95% CI=1.11, 1.46) and 34% higher for those from households earning $99,999 per year (adjusted coefficient=1.34, 95% CI=1.15, 1.56). Conclusions: As documented in a growing literature, most public transit trips include at least some walking; thus, efforts to encourage transit use are favorable to public health. Continued monitoring by transportation surveys is important as new forms of mobility and changing demographics may impact future transit use and associated physical activity. (C) 2020 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
Keywords
Physical Activity; Household Surveys; Public Transit; Cross-sectional Method; Public Health; Walking; Exercise; Research Funding; Transportation; Replacing Sedentary Time; Public-transit; Travel; Mortality; Adults; Health; Work
Schell, Christopher J.; Dyson, Karen; Fuentes, Tracy L.; Des Roches, Simone; Harris, Nyeema C.; Miller, Danica Sterud; Woelfle-Erskine, Cleo A.; Lambert, Max R. (2020). The Ecological and Evolutionary Consequences of Systemic Racism in Urban Environments. Science, 369(6510), 1446.
View Publication
Abstract
Urban areas are dynamic ecological systems defined by interdependent biological, physical, and social components. The emergent structure and heterogeneity of urban landscapes drives biotic outcomes in these areas, and such spatial patterns are often attributed to the unequal stratification of wealth and power in human societies. Despite these patterns, few studies have effectively considered structural inequalities as drivers of ecological and evolutionary outcomes and have instead focused on indicator variables such as neighborhood wealth. In this analysis, we explicitly integrate ecology, evolution, and social processes to emphasize the relationships that bind social inequities-specifically racism-and biological change in urbanized landscapes. We draw on existing research to link racist practices, including residential segregation, to the heterogeneous patterns of flora and fauna observed by urban ecologists. In the future, urban ecology and evolution researchers must consider how systems of racial oppression affect the environmental factors that drive biological change in cities. Conceptual integration of the social and ecological sciences has amassed considerable scholarship in urban ecology over the past few decades, providing a solid foundation for incorporating environmental justice scholarship into urban ecological and evolutionary research. Such an undertaking is necessary to deconstruct urbanization's biophysical patterns and processes, inform equitable and anti-racist initiatives promoting justice in urban conservation, and strengthen community resilience to global environmental change.
Keywords
New-york; Climate-change; Land-cover; Socioeconomic-status; Ecosystem Services; Oxidative Stress; Green Spaces; Gene Flow; Justice; Cities
Guan, Jinping; Zhang, Kai; Shen, Qing; He, Ying. (2020). Dynamic Modal Accessibility Gap: Measurement and Application Using Travel Routes Data. Transportation Research: Part D, 81.
View Publication
Abstract
Accessibility is a key concept in transportation research and an important indicator of people's quality of life. With the development of big data analytics, dynamic accessibility that captures the temporal variations of accessibility becomes an important research focus. Few prior studies focus on comparative measures of dynamic accessibility to Points of Interest (POIs) by alternative travel modes. To fill this research gap, we propose a new index called dynamic modal accessibility gap (DMAG), which draws upon available data on residents' real travel routes using different travel modes, as well as the data on POIs. We study the DMAG in the real-travel covered area, assuming POIs are only useful if it is within someone's real-travel covered area. We then apply this DMAG methodology to Shanghai's central city and peripheral area. In both cases, we measure the accessibility for public and private travel modes. As an example, one-week taxi GPS and metro smart card data, and POIs data are used to generate the DMAG index for 30-minute and 60-minute trip durations for weekdays and holidays. Results show that DMAG can reflect the pattern of temporal variations. The proposed DMAG analytical framework, which can be applied at both the user and the system levels, can support urban and transportation planning, and promote social equity and livability.
Keywords
Air Travel; Choice Of Transportation; Urban Transportation; Transportation Planning; Urban Planning; Smart Cards; Inner Cities; Route Choice; Shanghai (china); Dynamic Accessibility; Modal Accessibility Gap (mag); Points Of Interest (pois); Public And Private Travel Modes; Temporal Variations; Scale Residential Areas; Transport; Time; Dimensions; Employment; Indicator; Choice; Boston; Car
Lee, Wonil; Migliaccio, Giovanni C.; Lin, Ken-Yu; Seto, Edmund Y. W. (2020). Workforce Development: Understanding Task-Level Job Demands-Resources, Burnout, and Performance in Unskilled Construction Workers. Safety Science, 123.
View Publication
Abstract
This study examines how task demands and personal resources affect unskilled construction worker productivity and safety performance. It extends the job demands-resources (JD-R) burnout model to show how job characteristics interact with burnout to influence performance. A modified model was designed to measure burnout, with exhaustion and disengagement among unskilled construction workers taken into consideration. An observational study was conducted in a laboratory environment to test the research hypotheses and assess the prediction accuracies of outcome constructs. Twenty-two subjects participated in multiple experiments designed to expose them to varying levels of task-demands and to record their personal resources as they performed common construction material-handling tasks. Specifically, both surveys and physiological measurements using wearable sensors were used to operationalize the model constructs. Moreover, partial least squares structural equation modeling was applied to analyze data collected at the task and individual levels. Exhaustion and disengagement exhibited different relationships with productivity and safety performance outcomes as measured by unit rate productivity and ergonomic behavior, respectively. Subjects with high burnout and high engagement showed high productivity but low safety performance. Thus, exhausted workers stand a greater chance of failing to comply with safety. As the sample and the task performed in the experiment do not cover the experience and trade of all construction workers, our findings are limited in their application to entry-level and unskilled workers, whose work is mainly manual material-handling tasks.
Keywords
Construction Workers; Structural Equation Modeling; Job Descriptions; Labor Productivity; Labor Supply; Burnout; Job Demand-resources Model; Partial Least Squares Structural Equation Modeling; Productivity; Safety; Wearable Sensors; Biomechanics; Construction Industry; Ergonomics; Occupational Health; Occupational Safety; Occupational Stress; Personnel; Statistical Analysis; Workforce Development; Understanding Task-level Job Demands-resources; Unskilled Construction Workers; Task Demands; Personal Resources; Unskilled Construction Worker Productivity; Job Demands-resources Burnout Model; Job Characteristics Interact; Exhaustion; Disengagement; Outcome Constructs; Varying Levels; Task-demands; Common Construction Material-handling Tasks; Physiological Measurements; Model Constructs; Individual Levels; Unit Rate Productivity; High Burnout; Low Safety Performance; Exhausted Workers; Entry-level; Unskilled Workers; Manual Material-handling Tasks; Heart-rate-variability; Labor Productivity Trends; Physiological Demands; Emotional Exhaustion; Safety Climate; Role Stress; Engagement; Fatigue; Workload; Task Analysis; Workforce; Level (quantity); Construction Materials; Personnel Management; Materials Handling; Multivariate Statistical Analysis
Shang, Luming; Aziz, Ahmed M. Abdel. (2020). Stackelberg Game Theory-Based Optimization Model for Design of Payment Mechanism in Performance-Based PPPs. Journal Of Construction Engineering And Management, 146(4).
View Publication
Abstract
Payment mechanisms lie at the heart of public-private partnership (PPP) contracts. A good design of the payment mechanism should consider the owner's goals in the project, allocate risks appropriately to stakeholders, and assure satisfactory performance by providing reasonable compensation to the private developer. This paper proposes a Stackelberg game theory-based model to assist public agencies in designing payment mechanisms for PPP transportation projects. The interests of both public and private sectors are considered and reflected by a bilevel objective function. The model aims to search for solutions that maximize a project's overall performance for the sake of social welfare while simultaneously maximizing return for the sake of private investment. A variable elimination method and genetic algorithm are used to solve the optimization model. A case study based on a real PPP project is discussed to validate the effectiveness of the proposed model. The solutions provided by the model reveal that the optimal payment mechanism structure could be established such that it would satisfy owners' requirements for overall project performance while optimizing project total payments to contractors.
Keywords
Construction Industry; Contracts; Financial Management; Game Theory; Genetic Algorithms; Investment; Optimisation; Organisational Aspects; Project Management; Public Administration; Transportation; Public-private Partnership Contracts; Good Design; Private Developer; Stackelberg Game Theory-based Model; Ppp Transportation Projects; Public Sectors; Private Sectors; Private Investment; Ppp Project; Optimal Payment Mechanism Structure; Project Performance; Project Total Payments; Stackelberg Game Theory-based Optimization Model; Performance-based Ppps; Public-private Partnerships; Analytic Hierarchy Process; Weighted Sum Method; Multiobjective Optimization; Algorithm; Incentives; Projects; Network; Success; Branch
Abdirad, Hamid; Dossick, Carrie Sturts. (2020). Rebaselining Asset Data for Existing Facilities and Infrastructure. Journal Of Computing In Civil Engineering, 34(1).
View Publication
Abstract
This paper introduces rebaselining as a workflow for collecting reliable and verifiable asset management data for existing facilities and infrastructure. Reporting on two action research case studies with two public owners in the US, this research structures rebaselining in four phases: (1) preparing technology enablers, (2) collecting data from existing documents, (3) conducting field verification, and (4) updating asset management databases. These workflows address some of the common challenges in managing existing assets, including the fast-paced changes in asset data requirements, the inaccuracies in data and documentation of these existing assets portfolios, and the need to update data and documents over their life cycle. The findings set the groundwork for implementing workflow by mapping the rebaselining business processes in each phase, listing the technological requirements for these processes, and explaining the feasibility and examples of customizing building information modeling (BIM) platforms for rebaselining workflows. This customization of BIM platforms aims to offer simplified solutions that reduce the facility management staff's need for advanced BIM software knowledge.
Keywords
Asset Management; Building Management Systems; Business Data Processing; Database Management Systems; Facilities Management; Production Engineering Computing; Project Management; Risk Analysis; Software Tools; Reliable Asset Management Data; Verifiable Asset Management Data; Action Research Case Studies; Public Owners; Research Structures; Technology Enablers; Asset Management Databases; Facility Management Staff; Rebaselining Workflows; Technological Requirements; Rebaselining Business Processes; Existing Assets Portfolios; Documentation; Asset Data Requirements; Managing Existing Assets; Information; Bim; Existing Buildings; Infrastructure; Asset Data; Rebaselining
Habibnezhad, Mahmoud; Puckett, Jay; Jebelli, Houtan; Karji, Ali; Fardhosseini, Mohammad Sadra; Asadi, Somayeh. (2020). Neurophysiological Testing for Assessing Construction Workers’ Task Performance at Virtual Height. Automation In Construction, 113.
View Publication
Abstract
Falling from heights is the primary cause of death and injuries at construction sites. As loss of balance has a fundamental effect on falling, it is important to understand postural regulation behavior during construction tasks at heights, especially those that require precise focus in an upright standing position (therefore, a dual-task demand on focus). Previous studies examined body sway during a quiet stance and dual tasks to understand latent factors affecting postural balance. Despite the success of these studies in discovering underlying factors, they lack a comprehensive analysis of a task's simultaneous cognitive load, postural sway, and visual depth. To address this limitation, this paper aims to examine construction workers' postural stability and task performance during the execution of visual construction tasks while standing upright on elevated platforms. To that end, two non-intrusive neurophysiological tests, a hand-steadiness task (HST) and a pursuit task (PT), were developed for construction tasks in a virtual environment (VE) as performance-based means to assess the cognitive function of workers at height. Workers' postural stability was measured by recording the mapped position of the Center of Pressure (COP) of the body on a posturography force plate, and the postural sway metrics subsequently calculated. A laboratory experiment was designed to collect postural and task performance data from 18 subjects performing the two batteries of tests in the virtual environment. The results demonstrated a significant decrease in the Root-Mean Square (RMS) of COP along the anterior-posterior axis during the Randomized Pursuit Task (RPT) and maximum body sway of the center of pressure (COP) in the mediolateral direction during both tests. Also, subjects exposed to high elevation predominately exhibit higher accuracy for RPT (P-value = 0.02) and lower accuracy for HST (P-value = 0.05). The results show that the combination of elevation-related visual depth and low-complexity dual tasks impairs task performance due to the elevation-induced visual perturbations and anxiety-driven motor responses. On the other hand, in the absence of visual depth at height, high task complexity surprisingly improves the pursuit tracking performance. As expected, during both tasks, alterations in postural control were manifested in the form of a body sway decrement as a compensatory postural strategy for accomplishing tasks at high elevation.
Keywords
Task Performance; Construction Workers; Test Design; Cognitive Load; Standing Position; Sitting Position; Neurophysiological Test; Postural Stability; Virtual Reality; Workers' Safety At Height; Fall-risk; Reaction-time; Fear; Real; Acrophobia; Balance; Safety
Lee, Yong-Cheol; Shariatfar, Moeid; Rashidi, Abbas; Lee, Hyun Woo. (2020). Evidence-Driven Sound Detection for Prenotification and Identification Of Construction Safety Hazards and Accidents. Automation In Construction, 113.
View Publication
Abstract
As the construction industry experiences a high rate of casualties and significant economic loss associated with accidents, safety has always been a primary concern. In response, several studies have attempted to develop new approaches and state-of-the-art technology for conducting autonomous safety surveillance of construction work zones such as vision-based monitoring. The current and proposed methods including human inspection, however, are limited to consistent and real-time monitoring and rapid event recognition of construction safety issues. In addition, the health and safety risks inherent in construction projects make it challenging for construction workers to be aware of possible safety risks and hazards according to daily planned work activities. To address the urgent demand of the industry to improve worker safety, this study involves the development of an audio-based event detection system to provide daily safety issues to laborers and through the rapid identification of construction accidents. As an evidence-driven approach, the proposed framework incorporates the occupational injury and illness manual data, consisting of historical construction accident data classified by types of sources and events, into an audio-based safety event detection framework. This evidence-driven framework integrated with a daily project schedule can automatically provide construction workers with prenotifications regarding safety hazards at a pertinent work zone as well as consistently contribute to enhanced construction safety monitoring by audio-based event detection. By using a machine learning algorithm, the framework can clearly categorize the narrowed-down sound training data according to a daily project schedule and dynamically restrict sound classification types in advance. The proposed framework is expected to contribute to an emerging knowledge base for integrating an automated safety surveillance system into occupational accident data, significantly improving the accuracy of audio-based event detection.
Keywords
Construction Projects; Occupational Hazards; Construction Workers; Construction; System Safety; Video Surveillance; Work-related Injuries; Audio-based Accident Recognition; Autonomous Safety Surveillance; Construction Safety; Evidence-driven Sound Event Detection; Accident Prevention; Accidents; Audio Acoustics; Classification (of Information); Construction Industry; Health Hazards; Health Risks; Knowledge Based Systems; Learning Algorithms; Losses; Machine Learning; Monitoring; Motion Compensation; Occupational Diseases; Steel Beams And Girders; Audio-based; Construction Accidents; Construction Work Zones; Historical Construction; Sound Event Detection; State-of-the-art Technology; Vision Based Monitoring; Algorithm; System
Shang, Luming; Lee, Hyun Woo; Dermisi, Sofia; Choe, Youngjun. (2020). Impact of Energy Benchmarking and Disclosure Policy on Office Buildings. Journal Of Cleaner Production, 250.
View Publication
Abstract
Building energy benchmarking policies require owners to publicly disclose their building's energy performance. In the US, the adoption of such policies is contributing to an increased awareness among tenants and buyers and is expected to motivate the owners of less efficient buildings to invest in energy efficiency improvements. However, there is a lack of studies specifically aimed at investigating the impact of such policies on office buildings among major cities through quantitative analyses. In response, this study evaluated the effectiveness of the benchmarking policy on energy efficiency improvements decision-making and on real estate performances, by applying two interrupted time series analyses to office buildings in downtown Chicago. The initial results indicate a lack of statistically strong evidence that the policy affected the annual vacancy trend of the energy efficient buildings (represented by ENERGY STAR labeled buildings). However, the use of interrupted time series in a more in-depth analysis shows that the policy is associated with a 6.7% decrease in vacancy among energy efficient buildings. The study proposed a method to quantitatively evaluate the impact of energy policies on the real estate performance of office buildings, and the result confirms the positive impact of energy-efficient retrofits on the real estate performance. The study findings support the reasoning behind the owners' decision in implementing energy efficiency improvements in their office buildings to remain competitive in the market. (C) 2019 Elsevier Ltd. All rights reserved.
Keywords
Office Buildings; Building Failures; Time Series Analysis; Real Property; Energy Consumption; Metropolis; Building Performance; Chicago (ill.); Building Energy Benchmarking And Disclosure Policies; Building Energy Efficiency; Time Series Modeling; Energy Star (program); Building Management Systems; Buildings (structures); Decision Making; Energy Conservation; Maintenance Engineering; Time Series; Disclosure Policy; Energy Benchmarking Policies; Building; Benchmarking Policy; Energy Efficiency Improvements Decision-making; Estate Performance; Energy Efficient Buildings; Energy Star; Energy Policies; Energy-efficient Retrofits; Interrupted Time-series; Regression; Behavior; Designs; Building Energy Benchmarking And; Disclosure Policies; Buildings; Cities; Energy Efficiency; Energy Policy; Markets; Quantitative Analysis; United States