John D. Bullough

Periodically, concerns are raised within the research community about the effects on circadian and sleep-related outcomes resulting from changes to and from daylight saving time (DST). To better understand these concerns, we collected varied circadian and sleep-related outcomes from healthy individuals immediately before and after the spring DST transition. Subjects wore calibrated, personal light sensors that measured light exposure (amount, duration, time) and wrist actigraphs to quantify the synchrony between the 24-hour light-dark exposure and the 24-hour activity-rest cycles. Sleep onset, offset, and time in bed were obtained from the wrist actigraphs. Dim light melatonin onset (DLMO) was also measured before and after DST transition. Predicted minimum core body temperature (CBTmin p) times were calculated from the light exposure data. Karolinska Sleepiness Score (KSS) ratings were collected four times a day. Health-related outcomes were not examined. The spring DST transition had modest (statistically insignificant) effects on the weekly averages of time in bed (≤ 21 min), subjective sleepiness (KSS < 0.48), and the synchrony between the light and activity cycles (phasor magnitude ≤ 0.08 units). After the transition to DST, CBTmin p was slightly delayed, whereas DLMO and mid-sleep were slightly advanced. For this cohort, the spring transition to DST had little if any effect on a variety of circadian and sleep-related outcomes. The transition appears to have caused a small disassociation in the relative timing of the circadian phase markers, which may or may not be of some significance for health and wellbeing.

Fire blight, caused by the bacterium Erwinia amylovora, is a major problem for apple and pear growers. Antibiotics (streptomycin and kasugamycin) are commonly applied during apple blossom in spring to control fire blight. Various alternative strategies for controlling fire blight have been attempted, but they are often less effective and sometimes more costly than antibiotic treatments. Although the catalyzation products of water by nanoparticles (NPs) of the mineral titanium dioxide (TiO₂) and UV radiation have been shown to be a highly effective bactericide, they have not been demonstrated to control fire blight. We conducted field studies at a research orchard in central New York and a commercial orchard in eastern New York. We found that applying low concentrations (450 to 1,300 ppm) of TiO₂ NPs combined with natural solar radiation controlled fire blight as effectively as streptomycin, both at the research orchard and at the commercial orchard. TiO₂ NPs are priced comparably to streptomycin, suggesting that TiO₂ NP photocatalysis may be a cost-effective strategy for controlling fire blight. [ ] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

The present study focused on the consistency in perceiving the intended function of a simulated service vehicle when its color, the color of its flashing lights, and its flashing light pattern varied. Tests were conducted during the day and at night. Participants driving along a test track were presented with a red or yellow vehicle equipped with either red or yellow flashing lights. Although driving speed differed only between ambient lighting conditions (daytime and nighttime), consistency in the participants’ perceptions of the simulated situation (emergency or nonemergency) was higher when the color of the vehicle was the same as the flashing lights. Ambient lighting conditions also significantly influenced participants’ judgments of each situation because the color of the vehicle was more apparent during the day than during the night with only headlight illumination on the vehicle. The flash pattern (faster or slower) had a negligible impact on participants’ perception of the simulated situation. These results reinforce previous findings that coordinating the colors of the flashing lights and the vehicle better informs drivers about the situations they encounter along the road, improving the safety of emergency responders and other service workers.

Retroreflective markings provide important visual information to drivers about emergency vehicles and the incidents at which they are working. A stationary outdoor field study to investigate the impacts of emergency vehicle marking color, retroreflectivity level, and spatial patterns on drivers’ ability to see nearby emergency responders was carried out. The study also examined the impacts of a wearable flashing light-emitting diode (LED) light. Based on the results, agencies should use materials with higher levels of retroreflectivity carefully, especially when they will be covering large-area vehicle surfaces. Limiting the maximum retroreflectivity level to no greater than American Society for Testing and Materials Type III may help lessen negative impacts of bright reflective materials on drivers’ ability to see emergency responders. As long as the average reflectivity of different color combinations is similar to that of red and yellow reflective markings, chevron patterns with those color combinations will not reduce emergency responder visibility. Outline patterns of reflective markings on vehicles performed similarly at night to patterns covering most of the vehicle surface. The effectiveness of using high-retroreflectivity materials in an outline pattern in combination with lower- (or non-) retroreflectivity materials elsewhere on the surface should be studied. Wearable flashing LED lights can make emergency responders easier to see at night, provided they do not increase glare to approaching drivers.

With the growing interest in designing circadian-effective lighting, it is becoming increasingly important to determine how different lighting designs aimed at supporting circadian entrainment might also affect visual performance, preference, discomfort glare and lighting power density (LPD). These outcome measures were simultaneously examined in a controlled setting at night. Four ceiling lighting configurations, using combinations of direct and indirect lighting, were implemented along with one design that utilised local lighting. Every design delivered the same high level of circadian-effective lighting to participants. Saliva samples were obtained to measure nocturnal melatonin suppression. Two visual performance computer tasks together with subjective assessments of sleepiness, discomfort glare and preference were administered to participants. LPDs were determined. None of the lighting configurations created unacceptable levels of discomfort glare, and only one was above the required maximum allowable LPD. Lighting configuration had no differential effect on nocturnal melatonin suppression, visual performance and sleepiness. While the results show that a wide range of lighting approaches can meet visual, non-visual and energy objectives, the majority of participants preferred the local lighting over the ceiling-mounted lighting.

This study aimed to investigate the impact of automotive headlights of different correlated colour temperatures (CCT) on the visual and non-visual performance of drivers. Forty drivers participated in the study, driving in a simulated night road for 45 min in three sessions. The LED headlights had CCTs of 3176 K, 4358 K and 6923 K, with an illuminance of 5 lx perpendicular to the participants’ eyes. Heart rate variability (HRV), psychomotor vigilance task and Karolinska sleepiness scale were measured before and after driving. At the end of the trials, achromatic far and near visual acuity tests, as well as achromatic far and near contrast sensitivity tests, were conducted. The study revealed that CCT did not affect achromatic far and near visual acuity. However, CCT had an impact on achromatic near and far contrast sensitivity, with higher CCT resulting in improved achromatic contrast sensitivity. As the CCT decreased, participants exhibited increased reaction time, made more errors, and reported higher sleepiness. The most significant physiological changes in HRV, including alterations in low frequency (LF), high frequency (HF) and LF/HF, were observed at lower CCT. The findings of this study suggest that both the visual and non-visual performance of drivers were enhanced when high CCTs were used for automotive LED headlights.

In order to find optimized headlight distributions based on real traffic data, a three-step approach has been chosen. Since the complete investigations are too extensive to fit into one single publication, this paper is the second of three papers. Over the course of these papers, a novel way to optimize automotive light distributions based on real-life traffic and eye-tracking data is presented. Over all three papers, 119 test subjects participated in the studies, with over 15,000 km of driving, including recordings of gaze behavior, light data, detection distances and other objects in traffic. In the first paper, an ideal headlight distribution for straight roads with no other road users was identified. The second paper aims to collect the data required to modify this idealized headlight distribution for use on real roads. The first step is to find the extent to which real roads differ from an ideal, straight road. To do this, the German traffic space was analyzed. A new test vehicle recorded video and GPS data over a selected route. The video data were then evaluated by a machine learning algorithm. Object recognition software was used to find different traffic participants and road signs. Camera calibrations were used to find the exact angles of these objects. Using publicly available road data combined with the recorded GPS data, the video data were split into different road categories, and traffic object distributions were calculated for urban roads, country roads and motorways. The resulting analyses provided representative distributions of vehicles and highway signs along different types of roadways and roadway geometries. The GPS data were also used to find the curvature distributions along the selected route. These data were then used to optimize segment sizes for an adaptive driving beam. Overall, increasing the number of segments above 100 did not have appreciable benefits. These data will also be used in the third paper, where along the same route, the gaze distribution of drivers was recorded and analyzed.

In order to find optimized headlight distributions based on real traffic data, a three-step approach has been chosen. The complete investigations are too extensive to fit into a single paper; this paper is the last of a three part series. Over the three papers, a novel way to optimize automotive headlight distributions based on real-life traffic and eye tracking data is presented. Across all three papers, a total of 119 test subjects participated in the studies with over 15,000 km of driving, including recordings of gaze behaviour, light data, detection distances, and other objects in traffic. In this third paper, driver gaze behaviour is recorded while driving a 128 km round course, covering urban roads, country roads, and motorways. This gaze behaviour is then analysed and compared to prior work covering driver gaze behaviour. Comparing the gaze distributions with roadway object distributions from part two of this series, Analysis of Real-World Traffic Data in Germany and combining them with the idealized baseline headlight distribution from part one, different optimized headlight distributions can be generated. These headlight distributions can be optimized for different driving requirements based on the data that is used and weighting the different road types differently. The resulting headlight distribution is then compared to a standard light distribution in terms of the required luminous flux, angular distribution, and overall shape. Nonetheless, it is the overall approach that has been taken that we see as the primary novel outcome of this investigation, even more than the actual distribution resulting from this effort.