Medicolegal forensic entomology relies largely on blow fly (Diptera: Calliphoridae) activity to estimate a minimum postmortem interval (mPMI). The prevailing assumption, that blow flies are inactive at night, leads to the exclusion of nocturnal colonization from mPMI estimates. Artificial light at night (ALAN), however, especially from the increasing use of light emitting diode (LED) streetlights, may alter this innate behavior. Baited traps were deployed at two sites: one natural site that was dark at night (unlit) and one undeveloped but with infrastructure site that was LED-illuminated at night (lit). Samples were collected during daytime and nighttime periods. A total of 1,544 blow flies representing seven species were collected. Only six flies (0.4% of the total) were captured at night, four in unlit and two in lit environments, indicating minimal nighttime activity. These results suggest that, under current conditions, ALAN is unlikely to induce nocturnal blow fly behavior and impact mPMI estimations. Further research across diverse taxa and environments is needed to better understand the effects of ALAN on insects of forensic importance.
Most coastal urban environments are characterized by a large concentration of shipping ports, walkways, and other built infrastructures. These are commonly associated with high levels of artificial light at night (ALAN), a pervasive anthropogenic driver that erodes natural light cycles and impacts the ecology of benthic communities. However, it is not well known whether the spatial configuration of coastal built structures may influence the effects of light pollution on community structure. Here, we conducted field surveys in natural rocky habitats and on breakwaters directly lit by streetlights (ALAN), and in matched unlit zones (without-ALAN), along the coast of northern and central Chile (20°S-32°S), to examine the influence of light pollution on the diel activity and density of the intertidal grazer guild and on the biomass of their main food resource, biofilm, in both habitat types. The patchy distribution of artificial light on the breakwaters seems to allow the co-occurrence of diurnal and nocturnal grazers at night, resulting in no major alteration of grazer densities with light pollution. The density and night-time activity of diurnal grazer species increased in parallel with an increase in the biofilm biomass under lit conditions in the topographically more homogeneous natural rocky habitat. On the lit breakwaters, biofilm also increased but no change in grazer densities was found, most likely related to the presence of dark zones. Our results indicate that the influence of coastal streetlight pollution on benthic grazers can be dampened by the presence of among-boulder interstices in the built structure. Increases in biofilm, the main food of grazers, by artificial light, may reinforce grazing pressure in both rocky habitats. Promoting a balanced mix of built habitats and conserving urban natural rocky shores while reducing coastal light pollution from streetlights could help prevent impacts on different functional groups due to accelerated urban infrastructure expansion.
Thermal management is a critical challenge for semiconductor light-emitting diodes (LEDs), as inadequate heat dissipation reduces luminous efficiency and shortens the devices' lifespan. Thus, there is an urgent need for more effective cooling strategies to enhance the energy efficiency of LEDs. LED streetlights, which operate primarily at night and experience high chip temperatures, could benefit greatly from improved thermal management. In this study, we introduce a sky-facing radiative cooling strategy for outdoor LED streetlights, an innovative yet less explored approach for thermal management of optoelectronics. Our method employs a nanoporous polyethylene (nanoPE) material that possesses both infrared transparency and visible reflectivity. This approach enables the direct release of heat generated by the LED through a sky-facing radiative cooling channel, while also reflecting a significant portion of the light back for illumination. By incorporating nanoPE as a cover for sky-facing LED lights, we achieved a remarkable temperature reduction of 7.8 °C in controlled laboratory settings and 4.4 °C in outdoor environments. These reductions were accompanied by an efficiency improvement of approximately 5% and 4%, respectively. This enhanced efficiency translates into substantial annual energy savings, estimated at 1.9 terawatt-hours when considering the use of LED streetlights in the United States. Furthermore, this electricity saving corresponds to a reduction of approximately 1.3 million metric tons of CO2 emissions, equivalent to 0.03% of the total annual CO2 emissions by the United States in 2018.
One of the most dramatic changes occurring on our planet is the ever-increasing extensive use of artificial light at night, which drastically altered the environment to which nocturnal animals are adapted. Such light pollution has been identified as a driver in the dramatic insect decline of the past years. One nocturnal species group experiencing marked declines are moths, which play a key role in food webs and ecosystem services such as plant pollination. Moths can be easily monitored within the illuminated area of a streetlight, where they typically exhibit disoriented behavior. Yet, little is known about their behavior beyond the illuminated area. Harmonic radar tracking enabled us to close this knowledge gap. We found a significant change in flight behavior beyond the illuminated area of a streetlight. A detailed analysis of the recorded trajectories revealed a barrier effect of streetlights on lappet moths whenever the moon was not available as a natural celestial cue. Furthermore, streetlights increased the tortuosity of flights for both hawk moths and lappet moths. Surprisingly, we had to reject our fundamental hypothesis that most individuals would fly toward a streetlight. Instead, this was true for only 4% of the tested individuals, indicating that the impact of light pollution might be more severe than assumed to date. Our results provide experimental evidence for the fragmentation of landscapes by streetlights and demonstrate that light pollution affects movement patterns of moths beyond what was previously assumed, potentially affecting their reproductive success and hampering a vital ecosystem service.
Artificial light at night (ALAN), from streetlights and other sources, is ubiquitous across modern towns and cities and has wide-ranging impacts upon the natural environment. The extent, spectra and timing of light influence the physiology, behaviour and fitness of individuals of many species, shape the structure of ecological communities and the functioning of ecosystems. To date, however, it has been challenging to characterize this lighting at sufficiently fine spatial resolutions across city-wide extents. Here, we apply a Monte Carlo radiative transfer model to simulate in three dimensions the light environment resulting from emission from streetlights using the city of Exeter, UK, as an exemplar. We show that this technique can model the evolving lighting landscape of modern cities at scales, and through observables, suitable for both ecological studies and lighting professionals. We estimate measures of melatonin suppression, induced photosynthesis and phytochrome photostationary state from our models, probing how the transition towards light-emitting diode street lighting impacts physiological processes in plants and animals throughout the city. Our simulations illustrate that although the area lit by ALAN is decreasing overall at metre scales, which is lit is becoming more hostile towards many organisms.
Artificial Light at Night (ALAN) disrupts the natural circadian rhythms of animals, often extending the activity of diurnal species into nocturnal periods. To mitigate ALAN's ecological impacts and reduce energy consumption, many municipalities have implemented Part-Night Lighting (PNL), which involves switching off streetlights during core nighttime hours. However, the effects of such temporal lighting reductions on animal activity patterns remain poorly understood. We investigate how PNL influences daily singing behavior in European Robins Erithacus rubecula during spring in an urban area of France, where streetlights are turned off between 11 p.m. and 6 a.m., creating brief illumination windows at dawn and dusk. We hypothesized that PNL would reduce the effects of ALAN on Robin vocal activity compared to Full-Night Lighting (FNL). Using passive acoustic monitoring, we recorded Robin song activity across three types of sites (unlit, PNL, and FNL) and four time periods (dawn, morning, afternoon, dusk). Robins sang significantly earlier at FNL and PNL sites than at unlit sites during dawn and morning, and later during dusk, with no significant differences between FNL and PNL. In the afternoon, song activity tended to be delayed at PNL sites compared to both FNL and unlit sites. Our findings indicate that even short illumination periods at dawn and dusk under PNL do not replicate unlit conditions. In an urban context, the similarity in vocal activity between PNL and FNL sites suggests that residual light from nearby lit areas and/or lingering effects of ALAN may continue to influence animal behavior under PNL regimes.
Inadequate visibility is a critical factor contributing to the heightened occurrence of nighttime accidents at highway intersections. The installation of smart streetlights which are equipped to detect vehicle positions and speed information, thereby dynamically adjusting illumination, offers a promising solution to significantly reduce nighttime accident rates while conserving lighting energy. Nevertheless, as vehicles travel through illuminated intersections in a relative high speed and enter unlighted highway segments, drivers often experience dynamic visual illusions during dark adaptation, consequently impairing their stress response capacity and generating driving safety concerns. Therefore, we investigate the collaborative impact of illumination gradient and vehicle speed at intersection exits on driver stress response, aiming to provide a theoretical foundation for gradual illumination designs dynamically aligning with various vehicle speeds. Specifically, with reaction time employed as a metric to quantify driver stress response, and intersection area illuminance and vehicle speed utilized as input parameters, a safety assessment method for illumination gradients at exit sections is developed using variance analysis and multiple comparison techniques. Subsequently, a high-fidelity nighttime driving simulation platform is established, integrating initial illuminance, vehicle speed, and illumination gradient distance within exit sections as influential factors. Through simulated driving experiments, the collaborative effects of illumination gradient schemes and vehicle speed on reaction time is systematically examined. Ultimately, we propose optimal illumination gradient schemes and the minimum required number of streetlights for exit sections corresponding to specific vehicle speeds. Results reveal that exit section illumination is unnecessary when the vehicle speed is below 40 km·h-1. For vehicle speeds of 50, 60, and 70 km·h-1, the minimum required exit section lengths are determined to be 35, 70, and 105 m, respectively. Moreover, it is established that a minimum of one streetlight is indispensable within the exit section at a speed limit of 50 km·h-1, while at 60 km·h-1, at least two streetlights are required. Lastly, under a speed limit of 70 km·h-1, the exit section should accommodate no fewer than three streetlights to ensure optimal safety conditions.
Disproportionately more of the world's fatalities and injuries on the roads occur in low- and middle-income countries, despite these countries having approximately only 60% of the world's vehicles. Injury rates due to motor-vehicles are related to a complex multidimensional array of risk factors, embedded in the social and economic infrastructure of a country or region. Whether environmental infrastructure factors differ in determining the risk of an injury for motor vehicle occupants compared to pedestrians and other vulnerable road users has not been extensively studied. We explored the role of environmental infrastructure factors on motor-vehicle-related non-fatal injury using the Prospective Urban and Rural Epidemiology (PURE) cohort study of 162,793 adults from 23 high-, middle- and low-income countries. As expected, low-income countries had slightly higher motor vehicle injury rates, with pedestrians tending to have higher injury rates in these countries. There was considerable variation in motor vehicle injury rates within country-income-categories, while there were similarities in motor vehicle injury rates despite large differences in motorization of countries. There was a meaningful community effect on motor vehicle injury rates. We found that community-level infrastructure risk factors for motor vehicle injuries differed for car occupants and for pedestrians, with road quality and alcohol use being the main factors associated with an injury for car occupants, while poor roadside infrastructure (streetlights, sidewalks) and alcohol use were the main risk factors for an injury as a pedestrian. Active transport, such as walking and bicycling, are being promoted as leading to healthy lifestyle habits and reduced pollution. These require improved walkability for pedestrians, but also separation from motorized vehicles, which leads to recommending that low-and middle-income countries devote more funds for roadway quality and streetlight infrastructure. Policies to reduce motor vehicle injuries should be supported at the national level, but should be specific at the community level, since they must be focused on the specific local infrastructure. Countermeasures for reducing road transport injuries for pedestrians have different risk factors than for reducing injuries for car occupants.
This study investigates the determinants of vulnerable road user (VRU) crash severity by accounting for unobserved heterogeneity both across and within crash subpopulations. Conventional single-model approaches assume homogeneous effects across all crashes, potentially masking context-dependent severity mechanisms. Crash data for 15,578 pedestrian and 11,433 bicyclist collisions occurring at or near intersections in 20 California cities (2016-2025) were extracted from the Statewide Integrated Traffic Records System (SWITRS). A two-stage analytical framework was employed. First, latent class analysis identified three distinct crash typologies for each VRU mode based on movement patterns, lighting, weather, and collision factors. Second, mixed logit (MXL) models were estimated for each latent class to capture within-cluster heterogeneity through random parameters. Pseudo-elasticity analysis quantified the practical magnitude of variable effects. Temporal stability was assessed by estimating separate models across pre-COVID, during-COVID, and post-COVID periods. Truck involvement, dark conditions without streetlights, and state highway location consistently elevated severe outcome odds across all clusters for both VRU types, while VRU age 65+ shifted injury distributions toward moderate rather than the most severe outcomes. Critically, several factors exhibited context-dependent effects. VRU fault increased severity when drivers traveled straight, but decreased severity in turning-driver crashes for bicyclists, indicating fundamentally different causal mechanisms. State highway effects ranged from the strongest fatal predictor in straight-driver pedestrian crashes to non-significant in other configurations. Different random parameters were identified across clusters, confirming that unobserved heterogeneity operates through distinct mechanisms in different crash contexts. Crash severity determinants are both universally important and context-dependent, with the same variable capable of opposing effects across crash configurations. These findings demonstrate that aggregate models pooling heterogeneous crash types obscure critical variation and support the adoption of context-sensitive approaches to crash modeling.
Artificial light at night (ALAN) is an increasingly significant environmental disturbance, as it disrupts natural light-dark cycles that regulate daily and seasonal physiological processes and phenological events of all organisms. The use of artificial lighting in urban areas is rapidly increasing each year due to the rising number of unregulated vehicles, as well as the widespread installation of decorative lights, digital advertising boards, and streetlights. The objective of this research was to determine the impacts of artificial light at night (ALAN) on various ornamental garden plants such as Dieffenbachia seguine, Lawsonia inermis, Alocasia cucullata, Cynodon dactylon and Dypsis lutescens through the analyses of chlorophyll fluorescence transients, specific and phenomenological energy fluxes, density of functional PSII RCs, quantum yields (Fv/Fm, ϕE0), non-photochemical quenching (Kn) and photochemical quenching (Kp), superoxide dismutase (SOD) activity, and concentrations of chlorophylls, malondialdehyde (MDA) and starch content. The results of the present study highlight that plant responses to ALAN vary among species. The present investigation demonstrates that D. lutescens and C. dactylon exhibit pronounced sensitivity to ALAN, whereas D. seguine, L. inermis, and A. cucullata display a comparatively higher degree of tolerance. These findings underscore the need to preferentially select ALAN-tolerant species for urban plantation programs to minimize the ecological consequences associated with light pollution. Moreover, the study identifies specific photosynthetic parameters (OJIP transients, ET/CS, RC/CS, Kp, Kn, and PICS) along with key biochemical indicators (SOD activity, MDA accumulation, and chlorophyll content) as reliable diagnostic markers for distinguishing ALAN-sensitive and ALAN-tolerant species, thereby supporting informed species selection for sustainable urban greening.
Utility poles are critical in supporting various electrical and communication infrastructure systems, including power transmission lines, streetlights, telephone networks, and cable services. Each type of pole whether steel, aluminum, or fiber-reinforced polymer (FRP) is designed with specific applications and performance characteristics in mind. This study presents a Quality Function Deployment (QFD) framework tailored for industrial applications, focusing on enhancing information integration to guide the selection of the most suitable pole type. The research examines advancements in utility pole technologies and management practices over the past two decades. Through market surveys, focus group discussions and individual interviews, ten KPIs were identified: service life, safety performance, overall cost, color retention, conductivity resistance, weight, production duration, transportability, installation approach, and wind resistance. Based on these KPIs, decision-makers outlined nine functional requirements that, when met, would enhance user satisfaction. The proposed framework was developed to support analytical evaluation and selection of the optimal pole type by aligning client needs with technical specifications. Using the QFD approach, the FRP pole emerged as the top-performing alternative, receiving a score of 4.12 out of 5. This framework provides a structured method for decision-makers to evaluate electrical pole options based on project-specific criteria, enabling informed and client-focused choices in early design phases.
Light pollution from artificial light at night (ALAN) is a significant environmental problem with far-reaching consequences for ecological systems. Recent innovations in light-emitting diode (LED) technology may offer sustainable outdoor lighting solutions, but scientific evidence is lacking. We investigated the effects of various LED lighting properties (color temperature, light intensity, and luminaire shape), individually and in combination, on flight-active and ground-dwelling arthropods. We therefore conducted a field experiment at 3 forest field sites in Switzerland with standardized LED streetlights. Over the course of 3 summers, we monitored flight-active insects and ground-dwelling arthropods with automated flight-interception and pitfall traps. The absence of light reduced the number of arthropods caught by 91%. However, when lighting was necessary, dimming lights by 50% and using focused luminaires resulted in reductions of 22% and 42%, respectively. Light color influenced arthropod responses only when combined with dimming. Our results underscore the ecological benefits of darkness and the complex interactions among lighting properties. An optimized combination of these properties, particularly well-focused and dimmed LED luminaires, represents a practical and effective measure to reduce the ecological impacts of ALAN and promote the conservation of nocturnal species. Mitigación del impacto de la contaminación lumínica sobre los artrópodos con base en las propiedades de los diodos emisores de luz Resumen La contaminación lumínica provocada por la luz artificial nocturna (LAN) es un problema ambiental importante con consecuencias de gran alcance para los ecosistemas. Las recientes innovaciones en la tecnología de diodos emisores de luz (LED) pueden ofrecer soluciones sustentables para la iluminación exterior, pero faltan pruebas científicas. Investigamos los efectos de diversas propiedades de la iluminación LED (temperatura de color, intensidad luminosa y forma de la luminaria), tanto individualmente como en combinación, sobre los artrópodos voladores y terrestres. Para ello, realizamos un experimento de campo en tres bosques de Suiza con focos LED estandarizados. Durante tres veranos, monitoreamos los insectos voladores y los artrópodos terrestres con trampas automáticas de interceptación de vuelo y trampas de caída. La ausencia de luz redujo el número de artrópodos capturados en un 91%. Sin embargo, cuando era necesario iluminar, la reducción de la intensidad de la luz en un 50% y el uso de luminarias enfocadas dieron lugar a reducciones del 22% y del 42%, respectivamente. El color de la luz solo influyó en las respuestas de los artrópodos cuando se combinó con la atenuación. Nuestros resultados subrayan los beneficios ecológicos de la oscuridad y las complejas interacciones entre las propiedades de la iluminación. Una combinación óptima de estas propiedades, en particular luminarias LED bien enfocadas y atenuadas, representa una medida práctica y eficaz para reducir los impactos ecológicos de la LAN y promover la conservación de las especies nocturnas. 夜间人工光源(artificial light at night, ALAN)造成的光污染是一项严重的环境问题, 并对生态系统具有深远影响。近期关于发光二极管(light emitting diode, LED)技术的创新成果可能为户外照明提供可持续解决方案, 但尚且缺乏相关的科学证据。本研究分析了LED照明特性(色温、光强和灯具形状)对活跃飞行和地面栖息的节肢动物的影响, 包括这些特性的单独作用和组合作用。为此, 我们在瑞士三个森林实验站点用标准化LED路灯进行了野外实验。我们在三个夏季利用自动飞行拦截陷阱和坑式陷阱监测了活跃飞行的昆虫和地面栖息的节肢动物。在无光条件下, 捕获到的节肢动物数量减少了91%。然而, 当必须使用照明时, 将灯光调暗50%和使用聚焦灯具可分别导致捕获量减少22%和42%。色温仅在调暗亮度的情况下才会影响节肢动物的反应。我们的研究结果强调了黑暗的生态效益以及照明特性之间的复杂相互作用。这些特性的最优组合(特别是高度聚焦且调暗的LED灯具), 可作为一项实用且有效的措施, 来减少ALAN的生态影响并促进对夜行性物种的保护。【翻译:胡怡思;审校:聂永刚】.
Artificial light at night (ALAN), a pollutant closely linked to urbanization, is rapidly increasing worldwide. ALAN poses growing ecological challenges by altering wildlife movement and habitat use. However, many species have distinct and sometimes flexible behavioral responses to ALAN. Caracals (Caracal caracal) are an adaptable terrestrial carnivore capable of inhabiting urban areas yet are also sensitive to humans. We investigated how ALAN influences caracal movement, habitat selection, and foraging behavior using GPS collars and behavioral data at night. We assessed the role of direct and indirect ALAN, including total upward radiance, public streetlights, and urban skyglow, on adult (n = 17) and subadult (n = 7) caracals of both sexes using integrated step selection functions (iSSFs) to evaluate movement and habitat selection and resource selection functions (RSFs) to examine habitat selection while foraging (i.e., kill sites). We found that caracals avoided direct ALAN, as upward radiance strongly drove movement patterns. Caracals simultaneously selected areas closer to urbanization, and subadults had greater tolerance to ALAN than adults. Additionally, the interplay between urbanization and age class indicates a complex relationship in which ALAN and urbanization both constrain and potentially benefit caracals. We also found that caracal foraging was primarily influenced by direct ALAN via public street lighting, with avoidance of highly illuminated areas. Our findings illustrate that artificial light sources influence distinct yet interconnected behaviors. ALAN is a pollutant that will continue to impact wildlife and therefore disentangling how and where ALAN influences species, and the relative importance of direct and indirect ALAN, can inform mitigation and conservation strategies.
This longitudinal study leveraged data from the China Health and Retirement Longitudinal Study (CHARLS, 2015 wave) which contains longitudinal data from 28 provinces across the country to examine the synergistic impacts of chronic nocturnal light and air pollution (PM2.5) exposure on cardiovascular diseases (CVDs) as well as how two neuropsychological disorders (depression and cognitive impairment) mediate that effect among middle-aged and older adults in China. Using multivariable-adjusted mixed-effects logistic regression models, we identified significant interaction effects between annual changes in artificial light at night (ΔALAN) and PM2.5 exposure on hypertension (OR = 1.32, 95% CI: 1.12-1.56, p = 0.013), heart disease (OR = 1.24, 95% CI: 1.05-1.47, p = 0.028), and stroke (OR = 1.18, 95% CI: 1.02-1.36, p = 0.042). Notably, depressive symptoms and cognitive impairment mediated 18.7% and 12.3% of the total CVD risk, respectively. Subgroup analyses revealed heightened vulnerability in women (OR 1.42 vs. men OR 1.03) and adults aged ≥75 years (1.8-fold greater than younger groups). Our findings underscore the necessity of dual interventions: (1) environmental policies targeting nighttime light reduction (e.g., dimmable LED streetlights) together with air quality improvement, and (2) community-based mental health programs aiming to mitigate neuropsychological mediators. These integrated strategies could substantially alleviate the CVD burden in aging populations exposed to urbanization-driven environmental stressors.
Artificial light at night (ALAN) can be an anthropogenic stressor, yet its effects on wildlife, especially diurnal insects, remain poorly understood. We test how ALAN influences larval growth, development, and performance of monarch butterflies (Danaus plexippus) reared on two host milkweed species (Asclepias syriaca and A. incarnata). Field experiments with four cohorts over 2 years revealed that exposure to ALAN from white LED streetlights consistently increased caterpillar growth rates by nearly 16% and shortened larval development time, resulting in an 8% increase in adult fresh mass across both plant species. Nonetheless, ALAN had little effect on wing loading (fresh mass to wing surface area) or adult dry mass. Host plant interacted with ALAN to impact wing morphology: butterflies reared on A. syriaca had 7% larger wings under ALAN, while those on A. incarnata were not affected. Seasonality profoundly shaped monarch life history traits, with the migratory generation developing in late summer (August-September) exhibiting slower growth, extended developmental periods, and emerging with 44% less body mass and 30% reduced wing loading capacity compared to early summer (June-July) breeding generations. Finally, a path analysis revealed that ALAN enhanced larval growth, on par with the effects of feeding on A. syriaca compared to A. incarnata, increasing fresh mass and wing size by accelerating investment in early development. Our findings underscore that light pollution at night alters the entire developmental trajectory of these holometabolous insects, highlighting its strong capacity to reshape insect life histories in the Anthropocene.
Public streetlights are universally used to improve visibility after dark and improve residents' safety. However, anthropogenic light negatively impacts human health and well-being, biodiversity and energy consumption. Anthropogenic light impacts could be mitigated by technological changes optimising light characteristics, yet we know little of light colour temperature's influence on well-being. Here, we aim to examine the impact of exposure to LED streetlights of 2700K, 4000K and 6500K on the impression of light, the feeling of safety, and the well-being (affect, self-reported stress and physiological stress). We used a parallel group field experiment with 77 participants, over 18 years old, in a small Swiss town with controlled light settings. Participants were randomly allocated to a light treatment through computer-generated randomisation. With 25-26 participants per treatment, we showed that participants had better impressions of warmer temperatures than of cold ones. Light temperatures did not influence affect, the feeling of safety or self-reported stress, yet the decrease in cortisol was stronger under 6500K than under 2700K. The observed lower hormonal stress levels in 6500K lights can be attributed to their resemblance to daytime light temperatures, while preferences for warmer lights reflect the expectations for night-time situations.
Mass-based filtering significantly reduces the peptide candidate pool for subsequent scoring in database search algorithms. While useful, filtering based on one property may lead to exclusion of non-abundant spectra and uncharacterized peptides – potentially exacerbating the streetlight effect. Here we present ProteoRift, a novel attention and multitask deep-network, which can predict multiple peptide properties (length, missed cleavages, and modification status) directly from spectra 77.8% of the time. Integrating ProteoRift into an end-to-end pipeline significantly reduces the search space compared to mass-only filtering. This delivers 8x to 12x speedups while maintaining peptide deduction accuracy comparable to established algorithmic techniques. We also developed uncertainty estimation metrics, which can distinguish between in-distribution and out-of-distribution data (ROC-AUC 0.99) and predict high-scoring mass spectra against the correct peptide (ROC-AUC 0.94). These models and metrics are integrated in an end-to-end pipeline available at https://github.com/pcdslab/ProteoRift .
Pedestrian-motor vehicle crashes are a major cause of preventable injury in urban environments. They have increased markedly over the past several decades, especially overnight, and with a disproportionate impact on pedestrians of color. Streetlights represent a potential tool to combat these trends, but empirical studies of their relationship with pedestrian trauma are limited. We use geospatial data from Boston (2016-2023) to assess the relationship between streetlight density (lights/road kilometer) by census tract on (1) pedestrian crashes, (2) changes in crash rates over time, (3) racial disparities in crash incidence, and (4) proportion of crashes occurring overnight. Pedestrian crashes decreased from 2016 to 2023 from 616 (0.55/km) to 421 (0.37/km), with higher streetlight densities associated with greater overall reductions (an additional -0.002 crashes/km/year per streetlight/km (95% CI [-0.003, -0.001]). Persistent racial disparities were observed, with 0.04 additional crashes/km/year (95% CI [0.02, 0.06]) per 10% residents of color. However, this association decreased by 0.004 crashes/km/year (95% CI [-0.01, -0.001]), and higher streetlight densities were associated with greater reductions (additional annual decrease of 0.0004 crashes/km/year for every streetlight/km (95% CI [-0.001, -0.0001]). Finally, the proportion of crashes occurring overnight increased from 37.6% to 45.1%. Streetlight density was negatively associated with overnight timing (adjusted odds ratio of 0.991; 95% CI [0.986, 0.997] per streetlight/km) but had no relationship with the time trend. We conclude that there may be a beneficial relationship between streetlight density and pedestrian safety, where census tracts with higher streetlight densities demonstrated greater improvements in overall crash rates and racial disparities.
Temporal instability in crash risk determinants is well-established in the highway safety literature. However, most prior studies imposed restrictive assumptions of parameter homogeneity within each calendar year, thereby precluding the identification of intra-year heterogeneity in covariate effects. This study addresses this gap by investigating seasonal variation in the determinants of injury severity for vulnerable road users. Using four years (2019-2022) of police-reported pedestrian and bicyclist crash data from the state of North Carolina, U.S.A., partially temporally constrained random parameter logit models are estimated. Temporal analyses are conducted to examine the dynamics of these variations across different time periods. Key findings reveal that crashes involving vulnerable road users peak in the falls, followed by the summers, with the winters exhibiting the lowest frequency (with the exception of 2020). Older vulnerable road users were found to be particularly at risk during the fall season. Lighting condition is a consistent significant contributor to severe crash outcomes across all seasons except springs. Speed limits are consistently significant on controlled-access roadways (≥60 mph) and arterials (40-55 mph) across most seasons, although the influence is greater on arterials and more consistent in the summer and fall seasons. Additionally, a higher proportion of non-intersection crashes involving vulnerable road users is consistently observed. Policy recommendations drawn from the analysis include extending pedestrian signal timing and awareness campaigns for older VRUs in the fall (as seen in Japan), stricter speed enforcement and traffic-calming on high-speed arterials in the summer and fall, and enhanced lighting and visibility in the fall and winter (e.g., streetlight upgrades and reflective-gear distribution as seen in New York City). These findings provide policymakers with seasonally responsive strategies to improve safety outcomes for vulnerable road users.