Following a bioterrorism event, an incident or unified command is established, the impacted area characterized, and response work zones set up based on the extent of indoor/outdoor contamination. The personnel decontamination line, established in the contamination reduction zone, is essential for ensuring potentially biohazardous contamination on worker personal protective equipment (PPE) does not migrate outside of this zone. During personnel decontamination, conventional backpack or portable garden-type sprayers are often used to distribute liquid decontaminant onto PPE surfaces to physically remove and/or inactivate the contaminant. This process can lead to migration of biological contaminants and produces large volumes of liquid waste. A comparison of the performance of electrostatic sprayers and conventional backpack sprayers in personnel biological decontamination revealed that the electrostatic sprayer generated substantially less liquid runoff (∼75X), which would minimize waste generation and disposal costs following an event. Pilot-scale tests using manikins with PPE showed decontamination efficacy greater than 6 log10 reduction (liquid and aerosol inoculation of spores) for the conventional backpack sprayer while decontamination was effective but incomplete with the electrostatic sprayer (<6 log10 reduction) with residual spores detected at "hard-to-reach" areas. Decontamination efficacy of the electrostatic sprayer was improved by increasing the spray time, as greater than 6 log10 reduction was then observed (liquid and aerosol inoculation). Spore reaerosolization was higher during decontamination with the conventional backpack sprayer. The electrostatic sprayer as used in our study presents a viable decontamination option for a personnel decontamination line following biological agent contamination incidents.

An environmentally friendly extraction strategy based on an MSAT (Medium Scale Ambient Temperature) system was applied to Quercus ilex and Quercus robur acorns with the aim of maximizing polyphenolic yield and antioxidant activity while minimizing solvent consumption. Operational parameters were first optimized for Quercus ilex using a BBD-RSM (Box-Behnken response surface methodology), where the optimum working zone corresponds to the values of 200 g of acorn, 100 mL of extracting solvent, and 0.5 dispersant/acorn ratio. Subsequently, these conditions were applied to Quercus robur to enable an interspecific comparison. Extracts were evaluated in terms of total polyphenolic content, antioxidant activity, reducing sugars, proteins, targeted polyphenols quantified by UHPLC-QToF, and antimicrobial activity. Optimal extractions from Quercus ilex reached 25,072 mgGAE L-1 and 162 mmolTE L-1, while Quercus robur extracts showed markedly superior values of 35,822 mgGAE L-1 and 234 mmolTE L-1. Polyphenol quantification revealed higher concentrations of gallotannins in Quercus robur and procyanidins and catechin in Quercus ilex. The extracts showed strong antibacterial activity, especially Quercus ilex against S. aureus with a MIC ≤ 0.63%. Furthermore, it has been demonstrated for the first time that acorn extracts can inhibit the growth of Phytophthora cinnamomi in vitro, with Quercus robur extracts having a MIC ≤ 0.1% and Quercus ilex extracts ≤ 1%.

This paper addresses the challenge of real-time safety assessment in multi-lane highway work zones by introducing two key innovations. First, we formulate a Comprehensive Collision Risk Index (CCRI) that synergistically combines Equivalent Time-to-Collision (ETTC), Time-to-Dangerous-Collision (TDTC) and normalized collision energy into a single, physically interpretable metric. Second, we map discrete conflict events into a continuous risk field via an adaptive, bandwidth-weighted Kernel Density Estimation (KDE), enabling dynamic, spatially resolved delineation of low/medium/high risk zones. Building upon these indicators, we design a multibranch deep fusion network that fuses temporal cues, graph-based interactions, risk-field patches, and global traffic context via an attention-based fusion module. Evaluated on UAV-derived vehicle trajectories from the Kunshan segment of the Beijing–Shanghai Expressway, the proposed framework achieves 90.6% overall accuracy, a macro-AUC of 0.97, and a high-risk recall of 79.4%, representing improvements of 5%–12% points over single-modality and early-fusion baselines. Ablation studies confirm that CCRI and the risk-field branch contribute most critically to performance gains. The approach supports real-time warnings, variable speed limits, and lane-closure planning in complex work-zone environments.

Applications of Commercial Truck Dash Cameras for Work Zone Inspection and Monitoring

The article primarily presents ecological analytical studies on the waste generated in the production areas of the Baku Steel Company. It was determined that during various steel casting and processing operations in several production areas of the enterprise, different types of waste are formed in gaseous-aerosol, liquid, and solid states, each with distinct compositions and properties. Based on our preliminary scientific research, the actual composition and concentration levels of harmful substances released into the atmosphere at different times in both the working and sanitary protection zones were identified. Additionally, the composition of industrial wastewater and solid wastes generated by the enterprise was analyzed. The gaseous emissions at Baku Steel Company were measured using a Drager Tubes LLG gas detector device, while the analyses of water samples taken before and after purification from various departments of the plant were conducted using the ICP-OES GBC Quantima device. The article also provides scientific explanations on the negative environmental and human health impacts caused by heavy metals present in the industrial waste formed in the production areas of this enterprise. Key words: ecological analytical assessments, steel casting, sanitary protection zone, working zone, industrial waste

The question of the appropriateness of using the archaic term “tooterman” in relation to the relatively immobile coke mass in the lower part of blast furnaces was raised. For the first time, an attempt was made to summarize information about changes in coke characteristics depending on its location in local MCM zones, for which a conditional division of the MCM into three interdependent but functionally different parts: the upper central superheater (feeding), the middle part between the air blast and cast iron nozzles (working), and the lower part located in the sump (MKM working zone). The conditions for the use of coke in local parts of the MCM were comprehensively considered. New data about the increase in melting intensity on the size of the living part of the MCM has been extracted. It has been shown that the very changes in the intensity of smelting are done to ensure the life of the tuyere part by heating with coke. It is shown by comparing the structure of the MCM of two Japanese blast furnaces cooled during operation that working at a reduced smelting intensity leads to the degeneration of the stable axial zone of low-mobility materials above the tuyere horizon, thereby changing the conditions for preliminary coke heating and its supply to the lower parts of the MCM. The known mechanism of coke piece destruction by liquid metal flowing past them with carbonization of the latter needs to be clarified, since liquid slag formed on the tuyeres during oxidation of Fe, Si, Mn, and P components of cast iron also moves through the sub-tuyere coke mass, The restoration of these oxides requires additional consumption of coke carbon. Based on the generalization of research data and theoretical principles of the blast furnace process, the sequence of coke combustion processes in the MCM sub-bed array is proposed. The mechanism of erosive influx onto the coke massif, which is located in the zone of intense molten flow, has been clarified. It is shown that in this array, there is not one process of coke consumption for metallurgical reactions, as previously thought, but three. The influence of MCM “survivability” on the technical and economic indicators of smelting has been assessed.

Variable Speed Limit (VSL) control is essential for managing highway tunnel maintenance work, as it adjusts speed limits based on road conditions to regulate traffic flow. Developing a VSL control strategy that balances traffic efficiency and safety during maintenance can be challenging. This paper addresses this issue by proposing a VSL control strategy based on Model Predictive Control (MPC) that considers the spatial characteristics of traffic flow in a tunnel maintenance work zone. The strategy aims to minimise total travel time, reduce speed variance, and maximise traffic flow through a multi-objective optimisation approach using a Non-dominated Sorting Genetic Algorithm II (NSGA-II). With the Qinling Tiantai Mountain Tunnel selected as the experimental object, a simulation section is constructed based on the SUMO model with the measured data, and a comparative experiment of different speed limit control cycles in the maintenance work zone is designed. The results show that the method of this paper can effectively reduce the total travel time under the influence of maintenance operations by more than 17.5%, reduce the standard deviation of speed by about 22.1%, and enhance the traffic volume by about 7.8%, which can effectively improve the efficiency of road access and safety level.

This study investigates crash severity risk modeling strategies for work zones involving large vehicles (i.e., trucks, buses, and vans) under crash data imbalance between low-severity (LS) and high-severity (HS) crashes. We utilized crash data involving large vehicles in South Carolina work zones from 2014 to 2018, which included four times more LS crashes than HS crashes. The objective of this study is to evaluate the crash severity prediction performance of various statistical, machine learning, and deep learning models under different feature selection and data balancing techniques. Findings highlight a disparity in LS and HS predictions, with lower accuracy for HS crashes owing to class imbalance and feature overlap. Discriminative mutual information (DMI) yields the most effective feature set for predicting HS crashes without requiring data balancing, particularly when paired with gradient boosting models and deep neural networks, such as CatBoost, NeuralNetTorch, XGBoost, and LightGBM. Data balancing techniques, such as NearMiss-1, maximize HS recall when combined with DMI-selected features and certain models, such as LightGBM, making them well suited for HS crash prediction. Conversely, RandomUnderSampler, HS Class Weighting, and RandomOverSampler achieve more balanced performance, which is defined as an equitable trade-off between LS and HS metrics, especially when applied to NeuralNetTorch, NeuralNetFastAI, CatBoost, LightGBM, and Bayesian mixed logit (BML) using merged feature sets or models without feature selection. The insights from this study offer safety analysts guidance on selecting models, feature selection, and data balancing techniques aligned with specific safety goals, providing a robust foundation for enhancing work-zone crash severity prediction.

Rear-end collisions involving maintenance vehicles remain a critical source of severe injuries and fatalities in highway work zones. Existing studies on Rear Impact Guards (RIGs) and Truck-Mounted Attenuators (TMAs) have primarily relied on vehicle-based acceleration metrics or low-speed tests, leaving uncertainty regarding their performance under high-energy impact conditions. This study investigates occupant injury risk and vehicle crash behavior through full-scale frontal impact tests conducted at 80 km/h using a 2002 Renault SM520 passenger car against (1) a truck equipped with a RIG and (2) the same truck equipped with a TMA. Hybrid III 50th percentile ATDs, high-speed imaging, and multi-axis accelerometers were employed to measure occupant kinematics and injury responses. Occupant Risk Indices (THIV (Theoretical Head Impact Velocity), ASI (Acceleration Severity Index), PHD (Post-impact Head Deceleration), and ORA (Occupant Ridedown Acceleration)) and the ATD-based HIC36 were evaluated to assess crash severity. The RIG test exhibited severe underride, resulting in an HIC36 value of 1810, far exceeding the FMVSS 208 limit. In contrast, the TMA significantly reduced occupant injury risk, lowering HIC36 by 83.5%, and maintained controlled vehicle deceleration without compartment intrusion. Comparisons between FSM-based indices and ATD-measured injury responses revealed discrepancies in impact timing and occupant motion, highlighting limitations of current evaluation methodologies. The findings demonstrate the necessity of high-speed testing and ATD-based injury assessment for accurately characterizing RIG/TMA performance and provide evidence supporting improvements to roadside safety hardware standards and work-zone protection strategies.

Enhancing safety in work zones: the influence of speed feedback on driving behavior.

Assessing workers’ neuro-physiological stress responses to augmented reality safety warnings in immersive virtual roadway work zones

Investigating implementation practices and initiatives for using blue light to enhance work zone safety in the United States

Impact of HMI on Driver Behavior and Safety in Rural Work Zones: A Naturalistic Driving Approach

Road safety issues in Low to Middle-Income Countries and the key causal factors are well documented in the literature. However, an issue that is often overlooked is the safety hazards posed by road work zones or partially completed road segments that have not followed adequate safety measures to safeguard the road users. The stoppage of road works occurs due to various issues, with financial reasons being the primary cause in developing countries. These sites are left unattended for months, exposing road users to numerous hazards that may result in road crashes. Considering road agencies face major budget constraints, it is unlikely that all road segments can be completed within a short time. Therefore, there needs to be a process to expedite the evaluation of these road segments to prioritize mitigation measures to reduce the safety risk. This research aims to provide a framework for assessing the risks associated with partially completed roads. First, the key safety issues were identified through a comprehensive road safety inspection across several types of sites where partially completed road segments were present. Risk assessment of these segments was done based on the level of exposure of the safety issue to road users, the likelihood of the safety issue causing a road crash, and the severity in the event of a road crash. Then, decision-makers can identify and prioritize critical projects that align with the available budget, ensuring that resources are allocated effectively to achieve the maximum impact on road safety. This proactive approach examines critical road design elements, such as geometry, pavement quality, signage, etc, providing actionable insights to mitigate risks. The integration of these methodologies ensures a holistic understanding of safety challenges, enabling the development of targeted interventions to improve safety on partially completed roads.

With the gradual increase in the demand for daily maintenance, repair, and expansion, work zones have become critical nodes influencing traffic flow characteristics in freeways. Timely guidance of driving behavior is a crucial means to enhance operational efficiency within these zones. This research focuses on the guidance strategy toward better driving behavior by considering the characteristics of different sections in typical freeway work zones. By analyzing four major types of adverse driving behaviors—distracted driving, emergency braking, aggressive merging, and slow driving—at vulnerable points within work zones, this study developed comprehensive guidance strategies from both road-side and vehicle-side approaches. Drivers’ compliance rates with these guidance strategies were assessed through static desktop cognitive experiments, and these strategies’ effectiveness in improving vehicle operational characteristics was verified using VISSIM simulations. The study results demonstrate that the proposed guidance strategies for driving behavior in freeway work zones enhance traffic operation conditions significantly. These strategies reduce travel time by 65.81%, decrease average delays by 71.98%, and reduce stops by 80%. Furthermore, the effectiveness of improvements varies among the four adverse driving behaviors. From the perspectives of shortening travel time, minimizing delays, and reducing queue lengths, the strategy targeting slow driving results in the most improvement, with an overall guidance rate of 56%, while the strategy addressing distracted driving results in relatively lower improvement at 33%.

Highway work zones are hazardous areas where construction and maintenance activities occur alongside active traffic, posing significant safety challenges for on-site workers. This study investigates the effectiveness of hazard mitigation strategies from the workers’ perspective, focusing on safety, mobility, comfort and adaptability. Fourteen mitigation strategies were evaluated using the best–worst method (BWM), a multi-criteria decision-making (MCDM) approach, across three types of work zones: utility, maintenance and construction. Findings show that the importance of safety and mobility varies by work zone type; safety is most critical in the utility type, while mobility is prioritized in the construction type due to its influence on traffic flow and worker risk. Key effective strategies include enhanced traffic control devices, speed enforcement and intrusion alert systems. Automatic flagging devices are helpful in utility and maintenance work zones, while dynamic systems like variable speed limits and intelligent transportation systems improve safety in construction work zones.

Purpose The construction industry frequently encounters problems with low productivity leading to delays in project schedules. This delay is often addressed by increasing manpower to perform adjacent tasks simultaneously. Although this approach can theoretically expedite project completion, it often results in spatial conflicts, as work teams must coordinate their movements within limited spaces. These conflicts cause congestion and reduced productivity, highlighting the need for better spatial planning strategies to align manpower increases with efficient crew movement. Design/methodology/approach This study employs simulation to investigate spatial management strategies for mitigating the negative effects of increased manpower. The analysis focuses on the interior finishing of flooring areas, which are subdivided into smaller zones to represent distinct workspaces. Task durations are estimated using a beta distribution, with potential spatial conflicts considered. Several alternative strategies for organizing the workflow are then tested to identify the most effective approaches for optimizing spatial planning. Findings The findings show that three spatial management strategies significantly improved performance. First, defining clear work zones reduced spatial conflicts by 68.3% and cut delays from 12.97% over the ideal two-team time in the unplanned case to 3.47%. Second, implementing structured work patterns, such as the serpentine approach, further limited team interference and provided a more predictable workflow. Third, combining work zones with optimized starting positions achieved near-ideal performance, with only 1.01% delay over the ideal and 94.7% fewer conflicts than the unplanned scenario, demonstrating the strong impact of strategic spatial planning on reducing delays and enhancing resource use. Originality/value This paper contributes to the research field by highlighting the critical role of strategic spatial planning as well as providing guidance for practitioners with directly applicable on-site spatial management strategies for avoiding production congestion when increasing manning.

Driveway assistance devices (DADs) provide traffic control at low-volume access points on one-lane, two-way work zones without the need for flaggers. Interim approval for the optional use of DAD at residential driveways was granted, along with a name change to Residential Driveway Temporary Signal, by the Federal Highway Administration in January 2025. Before this, the DAD was considered an experimental device, with little available guidance toward the configuration and use of the device. This lack of uniform guidance resulted in the implementation of DAD signal arrangements, arrow colors, and auxiliary signage that varied across the United States. Because of the lack of uniformity, much is still unknown about the optimal designs of the signal display and auxiliary signage to provide the highest comprehension and compliance. To address these issues, a nationwide online survey of drivers was conducted to determine the DAD signal configurations and auxiliary sign messages that most effectively communicate the proper action when encountering the DAD. A total of 1,015 responses were received from respondents in 49 states. The survey results suggested that the DAD auxiliary signs most effectively conveyed the proper driver action if the message included the word “Turn” as opposed to “Yield” and if an NTOR sign was included. Furthermore, yellow flashing arrows showed considerably less uncertainty concerning the proper driver action compared with red flashing arrows. Considering the DAD signal head configuration, the horizontal and doghouse configurations more effectively conveyed the proper driver action compared with the red-over-yellow arrows configuration.

This study evaluates the effectiveness of Speed Safety Camera (SSC) deployments in reducing traffic speeds through four interstate work zones in Indiana in accordance with Indiana State Law House Enrolled Act (HEA) 1015. The initial deployment of SSC was along the interstate I-70 in August 2024, with deployments on I-69, I-465, and I-65 subsequently following in 2025. To evaluate the impact of SSC deployments in Indiana, connected passenger car and connected truck data were used to quantify the change in speed characteristics before and during the SSC deployments. Approximately 100 million passenger vehicle records and 3 million commercial truck records were analyzed. That Connected Vehicle data was used to count the number of spot speeds, at 0.1-mile intervals, that were 11 mph or more over the work zone speed limit over the entire work zone. The length of those study segments ranged from 3 to 10 miles. Across 443 SSC deployment days between 14 August 2024 and 11 July 2025, the study found 34% reductions on average in the percentage of passenger vehicle spot speeds exceeding the work zone speed limit by 11 mph or more on weekdays between 6 AM and 6 PM. For commercial trucks, there was a 41% reduction across the study sites.

In work zone traffic management, warning systems provide road users with real-time traffic conditions through messages or signals. This process aims to adjust driver speeds and headway distribution to affect the smoothness of traffic flow, ultimately achieving safer and more efficient traffic operations. This study examined the distributions of time headways for different vehicle types when traveling upstream of freeway work zones equipped with advanced warning systems. Data were collected through video footage and field observations at two locations on Interstate 80 in Nebraska. Statistical tests were performed to compare headway distributions during periods with active and inactive warning systems. The results indicated that, overall, the activation of the advanced warning systems altered the traffic headway distributions. Specifically: (1) the overall mean headway was significantly smaller under warning conditions compared to no-warning conditions; (2) the mean headway for passenger cars following other vehicles was significantly greater under warning conditions compared to no-warning conditions; and (3) all lead-follow pairs involving a heavy vehicle showed no significant difference in the mean headways with or without activated warning systems. This study also identified the best-fitting distribution models for empirical headways influenced by advanced warning systems. The parametric lognormal distribution and non-parametric Gaussian kernel distribution models were found to provide the best fit, depending on the type of vehicles in lead-follow pairs.