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At least 109 records · Page 6

Shifting institutional culture to develop climate solutions with Open Science

This call to action by Drs. Johnson and Wilkinson is part of a mosaic of voices sharing tangible progress within the climate movement 1,2. This call speaks to us as environmental and Earth scientists motivated by the urgency of climate change and social inequity and who contribute to finding science-driven climate solutions as part of our daily jobs. Unfortunately, we are often unable to efficiently move this critical and urgent work forward because we are impeded by cumbersome daily workflows and restrictive workplace cultures. Our workplaces have not kept pace with the modern realities of data-intensive science: increasing data volumes and storage needs, rapidly evolving technology, new skill requirements, and a growing need for extensive and diverse collaboration. Struggling with old approaches and learning new ones in isolation can fuel burnout and turnover, preventing us from working on science-driven climate solutions effectively.

open science↗

Crowdsourcing for Innovative Personal Protection Technology

Personal protective equipment (PPE) plays a vital role in safeguarding workers from workplace hazards and minimizing exposure to harmful substances or conditions. To meet the changing needs and challenges faced by workers in various industries, PPE is continuously evolving. As new technologies emerge, advances in materials, design, and functionality contribute to PPE improvements. By incorporating personal protective technology (PPT) into traditional PPE, worker safety and well-being can be further enhanced. Crowdsourcing can harness a wide range of perspectives and expertise to identify novel technologies, materials, designs, or applications that can revolutionize PPE and improve worker protection. Partnering with the National Aeronautics and Space Administration (NASA) Center for Center of Excellence for Collaborative Innovation (CoECI), the National Institute for Occupational Safety and Health (NIOSH) National Personal Protection Technology Laboratory (NPPTL) launched three crowdsourcing challenges. These challenges aimed to promote innovation in several PPE areas: protective clothing, counterfeit respirators, and respirator fit. Preliminary results produced promising technologies and approaches promoting improved awareness, comfort, adaptability, and effectiveness against workplace hazards.

crowdsourcing↗

Integrating Electric Vehicle Charging Infrastructure into Commercial Buildings and Mixed-Use Communities: Design, Modeling, and Control Optimization Opportunities: Preprint

This paper discusses modeling and field studies of controlled EV charging that have been performed with the goal of minimizing requirements for infrastructure upgrades, minimizing building peak demand charges, and maximizing the use of on-site generation. We present a large-scale workplace charging pilot of a demand-controlled scheduled EV charging system with over 250 active daily commuters, successfully demonstrating management of aggregate charging power to avoid new infrastructure investments, mitigate peak demand charges, and provide cost-effective workplace charging to users. In addition to understanding opportunities for demand management, integrating these controllable loads into the energy modeling process for new buildings will also be necessary. This paper then presents an example energy modeling process that evaluates the potential effects of EV charging on building load profiles and infrastructure requirements for a mixed-use community. Finally, we discuss an illustration of how EV charging can be controlled to be synergistic with other building loads and distributed generation.

buildings↗

Managing fatigue in operational settings. 1: Physiological considerations and countermeasures

The authors consider three aspects of managing fatigue in the workplace. They provide a brief overview of important scientific findings related to sleep and circadian physiology that establish the psychobiological foundation of fatigue. Their major focus is on the relevance of these findings to operational settings. In addition, they provide examples to describe practical fatigue countermeasures that can be used in operational settings.

Review, Tutorial↗

Case studies of robots and automation as health/safety interventions in small manufacturing enterprises

This article reviews the experiences of 63 case studies of small businesses (<250 employees) with manufacturing automation equipment acquired through a health/safety intervention grant program. The review scope included equipment technologies classified as industrial robots (n = 17), computer numerical control (CNC) machining (n = 29), or other programmable automation systems (n = 17). Descriptions of workers' compensation (WC) claim injuries and identified risk factors that motivated the acquisition of the equipment were extracted from grant applications. Other aspects of the employer experiences, including qualitative and quantitative assessment of effects on risk factors for musculoskeletal disorders (MSD), effects on productivity, and employee acceptance of the intervention were summarized from the case study reports. Case studies associated with a combination of large reduction in risk factors, lower cost per affected employee, and reported increases in productivity were CNC stone cutting system, CNC/vertical machining system, automated system for bottling, CNC/routing system for plastics products manufacturing, and a CNC/Cutting system for vinyl/carpet. Six case studies of industrial robots reported quantitative reductions in MSD risk factors in these diverse manufacturing industries: snack foods; photographic film, paper, plate, and chemical; machine shops; leather goods and allied products; plastic products; and iron and steel forging. Furthermore, this review of health/safety intervention case studies indicates that advanced (programmable) manufacturing automation, including industrial robots, reduced workplace musculoskeletal risk factors, and improved process productivity in most cases.

42 ENGINEERING↗

Volatile organic compound emissions from 4D printing: Effects of material composition and external stimulus

4D printing of stimuli-responsive materials extends 3D printing by enabling the fabricated structures to transform their shapes and properties over time in response to external stimuli. Numerous research efforts have been dedicated to developing new smart materials, enhancing material printability, and ensuring time-evolving properties. Meanwhile, the use of smart materials and external stimuli in 4D printing has introduced the possibility of air emissions that can potentially deteriorate the indoor air quality at the workplace and pose continuous health hazards to users during the production and use phases. These potential air emissions caused by 4D printing have not yet been assessed in current literature, leading to unknown occupational hazards and human health effects. This study focuses on stereolithography-based 4D printing with constrained thermo-mechanics and builds an emission model to quantify the volatile organic compound emissions from printing, shape programming, and shape recovery stages. The established model mathematically links the emission characteristics with material compositional design and stimuli-response mechanisms. Additionally, shape fixity and recovery abilities are considered to analyze the trade-off between the air emissions and stimuli-response performance of 4D printed parts. Case study results suggest that the methacrylate-based thermo-responsive material with higher glass transition temperature leads to higher air emissions, surpassing the permissible exposure level in the indoor environment. By altering the thermo-temporal conditions, a 61.29% reduction in emission yield can be achieved while ensuring a satisfactory shape memory performance.

36 MATERIALS SCIENCE↗

The impacts of building characteristics, social psychological and cultural factors on indoor environment quality productivity belief

Indoor environmental quality (IEQ) plays a key role in determining occupants' productivity at work; however, analyses of the interconnected factors among building physical, attitudinal, social and demographic components in one study are lacking. To fill this research gap, this study investigates these interconnected factors' influence on occupants’ IEQ-productivity belief, defined as a personal, subjective evaluation of the linkage between the impacts of five IEQ aspects (the quality of indoor temperature, air, natural and electric lighting, and acoustics) and productivity. A cross-sectional survey data was collected in university offices from six countries (Brazil, Italy, Poland, Switzerland, Taiwan and the U.S.). Results of multiple linear regression models indicate that IEQ satisfaction is the strongest positive predictor of the IEQ-productivity belief and this relationship is stronger in private offices. Country of residence is the second primary predictor. Several attitudinal-behavioral factors, including thermal comfort, perceived ease of controlling indoor environmental features, and attitudes toward sharing controls are all positively associated with IEQ-productivity belief. Interestingly, the level of control accessibility to light switches has the strongest impact as opposed to other controls. On the other hand, group norms and conformity intention are not significant predictors. Regarding demographics, men are more likely than women to perceive the IEQs to have positive impacts on their productivity, without considering other variables in the regression model; however, women are more likely than men to consider all IEQs as having positive impacts on productivity, after considering other variables. Furthermore, our findings provide suggestions for prioritizing wellness in the workplace since the early design stage.

99 GENERAL AND MISCELLANEOUS↗

Intersecting heuristic adaptive strategies, building design and energy saving intentions when facing discomfort environment: A cross-country analysis

Occupants' adaptive strategies play an important role in the energy consumption of office buildings. Previous research has mostly focused on the adaptive strategies triggered by occupants' indoor discomfort; however, it is crucial to understand if specific adaptive strategies are linked to occupants' energy-saving intentions. This study explores the relationships among employees’ heuristic decision-making in their first choice of adaptive strategies (technological solutions or personal adjustments) when facing extreme discomfort conditions, and their energy-saving intentions, then links these patterns with building design, workplace contextual factors, and demographics. A cross-sectional survey was collected among university employees from China, Brazil, Italy, Poland, Switzerland, and the US. Our results demonstrated that the accessibility to indoor environmental controls (IECs) and office type are the significant factors for adaptive strategies. There was a positive relationship between the number of IEC features and the percentage of employees choosing a technological solution. When feeling too hot, occupants in private offices are more likely to adopt a technological solution, whereas occupants in cubicles are more likely to choose a personal adjustment. Occupants with energy-saving intentions are less likely to choose thermostat adjustments or use portable devices as adaptive strategies than their counterparts. Lastly, the cluster analysis suggests females were more likely to use adaptive strategies for energy-saving purposes than males. The majority of occupants would turn on/off lighting to save energy. The study provides the contributions in the connection between the heuristic decision-making process and energy-saving intentions and recommendations on design strategies for building architects, engineers, and managers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

COVID-19 dynamics across the US: A deep learning study of human mobility and social behavior

This paper presents a deep learning framework for epidemiology system identification from noisy and sparse observations with quantified uncertainty. The proposed approach employs an ensemble of deep neural networks to infer the time-dependent reproduction number of an infectious disease by formulating a tensor-based multi-step loss function that allows us to efficiently calibrate the model on multiple observed trajectories. The method is applied to a mobility and social behavior-based SEIR model of COVID-19 spread. The model is trained on Google and Unacast mobility data spanning a period of 66 days, and is able to yield accurate future forecasts of COVID-19 spread in 203 US counties within a time-window of 15 days. Interestingly, a sensitivity analysis that assesses the importance of different mobility and social behavior parameters reveals that attendance of close places, including workplaces, residential, and retail and recreational locations, has the largest impact on the effective reproduction number. Furthermore, the model enables us to rapidly probe and quantify the effects of government interventions, such as lock-down and re-opening strategies. Taken together, the proposed framework provides a robust workflow for data-driven epidemiology model discovery under uncertainty and produces probabilistic forecasts for the evolution of a pandemic that can judiciously provide information for policy and decision making. All codes and data accompanying this manuscript are available at https://github.com/PredictiveIntelligenceLab/DeepCOVID19.

60 APPLIED LIFE SCIENCES↗

Data mining of plug-in electric vehicles charging behavior using supply-side data

This paper aims to better understand the charging patterns of plug-in electric vehicles (PEVs) and identify factors that may significantly impact PEVs’ charging behavior. We collected 189,864 supply-side charging session data over 13 months from 821 charging stations in Illinois from ChargePoint. Through descriptive and regression analyses, we characterize the distributions of key charging behavior indicators, including charging location, dwell time, and battery start state of charge (SOC), and quantify the impacts of closely related factors on these charging behaviors. In this work, we find that: (1) PEVs are more likely to charge in the morning at multifamily commercial locations with a lower start SOC compared with single family residential locations; (2) Weekday and morning sessions are more likely to utilize workplace charging and have shorter dwell time compared with weekend and afternoon sessions; (3) Single family residential area and locations with Levels 1/2 chargers have a higher start SOC and longer dwell time compared with other locations and DC fast chargers (DCFCs). These findings provide policy insights to identify potential time and locations to incentivize PEVs for grid services, as well as identify critical location categories for further charging infrastructure investment to better reduce range anxiety and promote PEV adoption.

33 ADVANCED PROPULSION SYSTEMS↗

Public Health Response and Medical Management of Internal Contamination in Past Radiological or Nuclear Incidents: A Review

Following a radiological or nuclear emergency, workers, responders and the public may be internally contaminated with radionuclides. Screening, monitoring and assessing any internal contamination and providing necessary medical treatment, especially when a large number of individuals are involved, is challenging. Experience gained and lessons learned from the management of previous incidents would help to identify gaps in knowledge and capabilities on preparedness for and response to radiation emergencies. In this paper, eight largescale and five workplace radiological and nuclear incidents are reviewed cross 14 technical areas, under the broader topics of emergency preparedness, emergency response and recovery processes. The review findings suggest that 1) new strategies, algorithms and technologies are explored for rapid screening of large populations; 2) exposure assessment and dose estimation in emergency response and dose reconstruction in recovery process are supported by complementary sources of information, including ‘citizen science’; 3) surge capacity for monitoring and dose assessment is coordinated through national and international laboratory networks; 4) evidence-based guidelines for medical management and follow-up of internal contamination are urgently needed; 5) mechanisms for international and regional access to medical countermeasures are investigated and implemented; 6) long-term health and medical follow up programs are designed and justified; and 7) capabilities and capacity developed for emergency response are sustained through adequate resource allocation, routine nonemergency use of technical skills in regular exercises, training, and continuous improvement.

61 RADIATION PROTECTION AND DOSIMETRY↗

Machine learning-based real-time monitoring system for smart connected worker to improve energy efficiency

Recent advances in machine learning and computer vision brought to light technologies and algorithms that serve as new opportunities for creating intelligent and efficient manufacturing systems. In this study, the real-time monitoring system of manufacturing workflow for the Smart Connected Worker (SCW) is developed for the small and medium-sized manufacturers (SMMs), which integrates state-of-the-art machine learning techniques with the workplace scenarios of advanced manufacturing systems. Specifically, object detection and text recognition models are investigated and adopted to ameliorate the labor-intensive machine state monitoring process, while artificial neural networks are introduced to enable real-time energy disaggregation for further optimization. The developed system achieved efficient supervision and accurate information analysis in real-time for prolonged working conditions, which could effectively reduce the cost related to human labor, as well as provide an affordable solution for SMMs. The competent experiment results also demonstrated the feasibility and effectiveness of integrating machine learning technologies into the realm of advanced manufacturing systems.

42 ENGINEERING↗

High-Sensitivity NO 2 Gas Sensor: Exploiting UV-Enhanced Recovery in a Hexadecafluorinated Iron Phthalocyanine-Reduced Graphene Oxide

Monitoring ultralow nitrogen dioxide (NO 2 ) concentrations is crucial for air quality management and public health. However, the existing NO 2 gas sensors have several defects, like high cost and power consumption, and exhibit poor selectivity. This study addresses these challenges by presenting a novel hexadecafluorinated iron phthalocyanine-reduced graphene oxide (FePcF 16 -rGO) covalent hybrid sensor for NO 2 detection. This innovative approach, which overcomes the limitations of fabrication cost, energy efficiency, and gas selectivity, is a significant step forward in gas sensor technology. The sensor demonstrates exceptional sensitivity toward ultralow NO 2 concentrations (15.14% response for 100 ppb) with a rapid 60 s UV light-induced recovery. Additionally, the sensor exhibits high selectivity for NO 2 , achieving a limit of detection (LOD) of 8.59 ppb. This approach paves the way for developing cost-effective, energy-efficient, and miniature NO 2 monitoring devices for improved environmental monitoring and enhanced safety in workplaces where NO 2 exposure is a concern.

36 MATERIALS SCIENCE↗

Mortality among Tennessee Eastman Corporation (TEC) uranium processing workers, 1943–2019

Background: There are few occupational studies of women exposed to ionizing radiation. During World War II, the Tennessee Eastman Corporation (TEC) operated an electromagnetic field separation facility of 1152 calutrons to obtain enriched uranium (235U) used for the Hiroshima atomic bomb. Thousands of women were involved in these operations. Materials and methods: We report a new study was conducted of 13,951 women and 12,699 men employed at TEC between 1943 and 1947 for at least 90 days. Comprehensive dose reconstruction techniques were used to estimate lung doses from the inhalation of uranium dust based on airborne measurements. Vital status through 2018/2019 was obtained from the National Death Index, Social Security Death Index, Tennessee death records and online public record databases. Analyses included standardized mortality ratios (SMRs) and Cox proportional hazards models. Results: Most workers were hourly (77.7%), white (95.6%), born before 1920 (58.3%), worked in dusty environments (57.0%), and had died (94.9%). Vital status was confirmed for 97.4% of the workers. Women were younger than men when first employed: mean ages 25.0 years and 33.0 years, respectively. The estimated mean absorbed dose to the lung was 32.7 mGy (max 1048 mGy) for women and 18.9 mGy (max 501 mGy) for men. The mean dose to thoracic lymph nodes (TLNs) was 127 mGy. Statistically significant SMRs were observed for lung cancer (SMR 1.25; 95% CI 1.19, 1.31; n = 1654), nonmalignant respiratory diseases (NMRDs) (1.23; 95% CI 1.19, 1.28; n = 2585), and cerebrovascular disease (CeVD) (1.13; 95% CI 1.08, 1.18; n = 1945). For lung cancer, the excess relative rate (ERR) at 100 mGy (95% CI) was 0.01 (–0.10, 0.12; n = 652) among women, and –0.15 (–0.38, 0.07; n = 1002) among men based on a preferred model for men with lung doses <300 mGy. NMRD and non-Hodgkin lymphoma were not associated with estimated absorbed dose to the lung or TLN. Conclusions: There was little evidence that radiation increased the risk of lung cancer, suggesting that inhalation of uranium dust and the associated high-LET alpha particle exposure to lung tissue experienced over a few years is less effective in causing lung cancer than other types of exposures. There was no statistically significant difference in the lung cancer risk estimates between men and women. The elevation of certain causes of death such as CeVD is unexplained and will require additional scrutiny of workplace or lifestyle factors given that radiation is an unlikely contributor since only the lung and lymph nodes received appreciable dose.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Visualizing the NIOSH Pocket Guide: Open-source web application for accessing and exploring the NIOSH Pocket Guide to Chemical Hazards

The NIOSH Pocket Guide to Chemical Hazards is a trusted resource that displays key information for a collection of chemicals commonly encountered in the workplace. Entries contain chemical structures—occupational exposure limit information ranging from limits based on full-shift time-weighted averages to acute limits such as short-term exposure limits and immediately dangerous to life or health values, as well as a variety of other data such as chemical-physical properties and symptoms of exposure. The NIOSH Pocket Guide (NPG) is available as a printed, hardcopy book, a PDF version, an electronic database, and a downloadable application for mobile phones. All formats of the NIOSH Pocket Guide allow users to access the data for each chemical separately, however, the guide does not support data analytics or visualization across chemicals. This project reformatted existing data in the NPG to make it searchable and compatible with exploration and analysis using a web application. The resulting application allows users to investigate the relationships between occupational exposure limits, the range and distribution of occupational exposure limits, and the specialized sorting of chemicals by health endpoint or to summarize information of particular interest. These tasks would have previously required manual extraction of the data and analysis. The usability of this application was evaluated among industrial hygienists and researchers and while the existing application seems most relevant to researchers, the open-source code and data are amenable to modification by users to increase customization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mentoring in the USDA Forest Service: A Survey of Aquatic Professionals

Abstract Mentoring is suggested as an important strategy to promote workplace inclusivity and is shown to be positively associated with high employee morale, yet mentee needs and experiences may not be universal. To evaluate mentoring impacts from the perspective of USDA Forest Service employees, we conducted an online survey of 251 aquatic professionals, including managers and scientists. 70% of respondents had mentors, and mentorship status did not vary across demographic characteristics. Previous mentoring relationships were most frequently identified as “informal” rather than “formal”; female employees were more likely to desire formal mentoring. Mentored respondents found their work more challenging, fulfilling, and valuable than unmentored respondents. Mentees looked for mentors who could provide constructive feedback, speak candidly, use active listening skills, and who cared about their careers. Overall, respondents were satisfied with their mentors’ skills. Despite strong demand for mentoring, access to mentors among aquatic professionals appears low across all categories.

Forestry↗

Chelation Model Validation: Modeling of a Plutonium-238 Inhalation Incident Treated with DTPA at Los Alamos National Laboratory

Accidental inhalation of plutonium at the workplace is a non-negligible risk, even when rigorous safety standards are in place. The intake and retention of plutonium in the human body may be a source of concern. Thus, if there is a suspicion of a significant intake of plutonium, medical countermeasures such as chelation treatment may be administered to the worker. The present work aimed to interpret the bioassay data of a worker involved in an inhalation incident due to a glovebox breach at Los Alamos National Laboratory’s plutonium facility. The worker was treated with intravenous injections of calcium salts of diethylenetriaminepentaacetic acid (DTPA) in an attempt to reduce the amount of plutonium from the body and therefore reduce the internal radiation dose. It is well known in the internal dosimetry field that the administration of chelation treatment poses additional challenges to the dose assessment. Hence, a recently developed chelation model was used for the modeling of the bioassay data. The objectives of this work are to describe the incident, model the chelation-affected and non-affected bioassay data, estimate the plutonium intake, and assess the internal radiation dose.

238Pu↗

A 291-day Evaluation of the Performance of a Consumer-grade Temporal Radon Detector

Affordable, accurate, and robust temporal measurement devices are desirable for screening and assessment of radon levels in private homes and workplaces. This research expands upon prior research, using the RadonFTlab RadonEye device through a comparison of multiple samples of this instrument with a laboratory-grade instrument, the Saphymo AlphaGUARD, over a more extensive period than reported previously. Data were collected over 291 d in a poorly ventilated basement space in an occupied building. Environmental conditions varied naturally, changing both the radon source term and radon entry into the space approximating typically deployed conditions. The R-squared linear regression correlation coefficient and relative sensitivities of each RadonEye with the AlphaGUARD were computed. Altogether temporal and diurnal variations were also studied. The sensitivities of all RadonEyes and the AlphaGUARD agreed to within 22% throughout the entire deployment period.

47 OTHER INSTRUMENTATION↗