Hot Clusters Research Articles

Spatial clustering of heroin-related overdose incidents: a case study in Cincinnati, Ohio

BackgroundDrug overdose is one of the top leading causes of accidental death in the U.S., largely due to the opioid epidemic. Although the opioid epidemic is a nationwide issue, it has not affected the nation uniformly.MethodsWe combined multiple data sources, including emergency medical service response, American Community Survey data, and health facilities datasets to analyze distributions of heroin-related overdose incidents in Cincinnati, Ohio at the census block group level. The Ripley’s K function and the local Moran’s I statistics were performed to examine geographic variation patterns in heroin-related overdose incidents within the study area. Then, conditional cluster maps were plotted to examine a relationship between heroin-related incident rates and sociodemographic characteristics of areas as well as the resources for opioid use disorder treatment.ResultsThe global spatial analysis indicated that there was a clustered pattern of heroin-related overdose incident rates at every distance across the study area. The univariate local spatial analysis identified 7 hot spot clusters, 27 cold spot clusters, and 1 outlier cluster. Conditional cluster maps showed characteristics of neighborhoods with high heroin overdose rates, such as a higher crime rate, a high percentage of the male, a high poverty level, a lower education level, and a lower income level. The hot spots in the Southwest areas of Cincinnati had longer distances to opioid treatment programs and buprenorphine prescribing physicians than the median, while the hot spots in the South-Central areas of the city had shorter distances to those health resources.ConclusionsOur study showed that the opioid epidemic disproportionately affected Cincinnati. Multi-phased spatial clustering models based on various data sources can be useful to identify areas that require more policy attention and targeted interventions to alleviate high heroin-related overdose rates.

Concentration asymmetry and carbon enrichment in titanium carbide and silicon carbide clusters

The mass spectra of metal clusters obtained by gas aggregation and laser vaporization techniques show variations of the abundance with cluster size, and the best-known manifestation is the magic numbers. The case of nanoalloys adds structural and chemical richness, and asymmetry in the atomic concentrations is sometimes observed. This is the case with ${\mathrm{Ti}}_{x}{\mathrm{C}}_{y}$ and ${\mathrm{Si}}_{x}{\mathrm{C}}_{y}$ clusters, for which the experiments performed until now reveal an enrichment of the clusters in carbon. The structure of the mass spectrum arises when hot clusters evaporate atoms to cool down. By performing density functional calculations, complemented by a thermochemical formalism to obtain Gibbs free energies, we have found that for each cluster in the families ${\mathrm{Ti}}_{x}{\mathrm{C}}_{y}$ and ${\mathrm{Si}}_{x}{\mathrm{C}}_{y}$ with $x$ = 1--4 and $y$ = 1--4, it is easier to remove titanium or silicon atoms as compared to removing carbon atoms, and this explains the carbon enrichment systematically observed in the experiments. The conclusion is that the broad compositional trends expected in the formation of alloy nanoclusters can be anticipated from calculations of the evaporation energies of the alloy components, and this may be particularly interesting in the field of catalysis.

Visualization and analysis of mapping knowledge domains for coronavirus research.

Background:In recent years, many countries around the world have been threatened by COVs. The aim of this study was to better grasp developments and trends in research on coronavirus around the world and to promote theoretical research into their prevention and control.Methods:Research on coronavirus was reviewed and analyzed using bibliometrics based on a total of 4860 publications collected from the Web of Science Core Collection database. Yearly quantitative distribution of literature, country/region distribution, organization distribution, main source journal distribution, subject category distribution, research knowledge bases, and research hotspots and frontiers were all analyzed, and CiteSpace and VOSviewer were used to plot knowledge domain maps, Excel was used to plot keyword strategy diagram.Results:Coronavirus research could be roughly divided into 4 stages: preliminary development stage (before 2000), rapid growth stage (2000–2005), slow decline stage (2006–2011) and sustained growth stage (since 2012). America had taken the leading position in this field. The study of COVs involves many subject categories, mainly includes virology, veterinary sciences, biology, and immunology. At present, the key words in the field of coronavirus research were mainly divided into 6 major hot clusters, namely, the introduction and structure analysis of coronavirus, the research on the outbreak source and transmission of coronavirus, the research on the infection pathway of coronavirus in human body, the research on the pathogenesis of coronavirus, the research on the diagnosis and symptoms of coronavirus infection, and the research on the treatment of coronavirus.Conclusion:Coronavirus, which occurs all over the world, often causes huge casualties and economic losses, and poses a serious threat to the safe and stable operation of the social and economic system. Objective literature review and analysis can help scholars in related fields to deepen their overall understanding. And, there are several key issues that should be further explored in future research.

Spatial Inequalities and Influencing Factors of Self-Rated Health and Perceived Environmental Hazards in a Metropolis: A Case Study of Zhengzhou City, China.

Research on environmental pollution and public health has aroused increasing concern from international scholars; particularly, environmental hazards are among the important issues in China, focusing public attention on significant health risks. However, there are few studies concentrated on how perceived environmental hazards are characterized by spatial variation and on the impact of these risks on residents’ health. Based on a large-scale survey of Zhengzhou City in 2020, we investigated how the self-rated health of residents and the environmental hazards perceived by them were spatially inequal at a fine (subdistrict) scale in Zhengzhou City, China, and examined the relationship among self-rated health, environmental hazards, and geographical context. The Getis–Ord Gi* method was applied to explore the spatially dependent contextual (neighborhood) effect on environmental health inequality, and the ordered multivariate logistic regression method was used to examine the correlative factors with environmental hazards, geographical context, and health inequality. The results reveal that self-rated health and environmental hazards were disproportionately distributed across the whole city and that these distributions showed certain spatial cluster characteristics. The hot spot clusters of self-rated health had favorable environmental quality where the hot spot clusters of environmental hazards were located and vice versa. In addition, health inequality was evident and was related to gender, income level, educational attainment, and housing area of residents, and the inequalities of environmental hazards existed with respect to income and housing area. Meanwhile, environmental risk inequalities associated with the social vulnerability of residents (the poor and those with low educational attainment) were obvious, with those residents experiencing a disproportionately high exposure to environmental hazards and reporting bad health conditions. The role of the geographical context (subdistrict location feature) also helps to explain the spatial distribution of health and environmental inequalities. Residents with better exposure to green coverage generally reported higher levels of self-rated health condition. In addition, the geographical location of the subdistrict also had a significant impact on the difference in residents’ self-rated health status. The purpose of this study is to provide reference for policy makers to optimize the spatial pattern of urban public services and improve public health and environmental quality at a fine scale.

Using ADS–B Data to Understand Overflight Altitude Characteristics at Hawai‘i Volcanoes National Park

Air tour management plans for U.S. national park units are developed by the Federal Aviation Administration (FAA) and the National Park Service (NPS). The FAA recommends pilots fly higher than 2,000 feet above ground level (AGL) over parks, wildlife refuges, and areas with wilderness characteristics. Management of air tours is important for mitigating visual and noise impacts. Understanding air tour travel patterns has been problematic because objective location data have been difficult to obtain. A newer technology, Automatic Dependent Surveillance–Broadcast (ADS–B), can be used to accurately track overflights. Prior ADS–B studies of air tours conducted limited analysis with respect to altitude characteristics. Thus, the purpose of this study was to determine how overflights spatially vary across altitudes and determine altitude trends for primary flight corridors. Results suggest overflights trend along the east side of the park and 74.59 percent of waypoints within a 0.5-mile buffer around the park boundary had altitudes less than 2,000 feet above ground level (AGL). Results revealed that as altitude increased, overflight density decreased. Using hot spot clustering analysis, overflight lateral pattern differences were determined for altitudes lower than 2,000 feet AGL compared to altitudes higher than 2,000 feet AGL. This study also identified one primary flight corridor with average altitudes mostly below 2,000 feet AGL. Managers can use these results to inform the development of air tour management plans and monitor compliance.

A Preliminary Study on Humpback Whales Lunge Feeding in the New York Bight, United States

Humpback whales (Megaptera novaeangliae) have recently been observed feeding in the New York Bight (NYB), the section of ocean from Montauk, New York to Cape May, New Jersey, United States (US). This feeding technique brings humpback whales to the surface of the water which puts them at a greater risk of vessel strike. The NYB is already an area of concern due to shipping traffic leading to the Ports of New York and New Jersey (PNYNJ). In this study, data collected by Gotham Whale from 2011 to 2019 were analyzed on humpback whales lunge feeding in the NYB apex, near the entrance to the PNYNJ. Clusters of lunge feeding were investigated, along with the water depths of lunge feeding locations. Using ArcGISPro, six significant hot spot clusters were identified, and water depth of lunge feeding locations ranged from 4.50 to 35.00 m with a mean of 14.83 m. The results of this study provide the first documentation on potential lunge feeding hot spot clusters in the NYB apex. Future studies should obtain comprehensive data looking at the amount of time humpback whales in the NYB are spending on the surface and time they are spending feeding in shipping lanes. This information will be important for the management of marine mammals in this area and may help to mitigate and reduce the incidence of boat strikes to humpback whales in this region.

Spatiotemporal analysis to understand overflight travel patterns at HawaiI Volcanoes National Park

Overflights, especially low-level flights, have a measurable impact on the acoustic environment of the areas they traverse. This is of particular concern to protected areas with a mission of protecting natural resources, cultural resources, and the visitor experience. Yet, understanding overflight travel patterns at parks and protected areas has proven difficult to determine. Recent technology makes it possible to collect accurate overflight data allowing researchers to quantify travel patterns across a protected area. Location data, including x, y, and z data, can be used to quantitatively assess effects of overflights and to inform solutions to protect resources and the visitor experience. Therefore, the purpose of this study was to spatiotemporally quantify overflight travel patterns at Hawai'i Volcanoes National Park using data derived from Automatic Dependent Surveillance-Broadcast (ADS-B) technology. Location data, a digital grid, and hot spot clustering were used to identify spaces with a statistically-significant high volume of overflights. Some of these spaces overlap with terrestrial visitor attraction locations, suggesting potential for degraded visitor experience. Specifically, results indicate a spatial trend of low-flying overflights along the eastside of the park, a high volume of overflights near Nāpau Trailhead and Nāpau Crater, and spatial clustering of overflights varies across hour of the day. The described methods provide a foundation for future research and the results are useful for informing the designation of lateral and minimum altitude parameters for low-level overflights such as air tours.

Microbial diversity and ecology of geothermal springs in the high-grade metamorphic terrain of Sri Lanka

The current study evaluated the bacterial diversity of six hot water spring clusters in Sri Lanka by Illumina MiSeq sequencing of the V3–V4 region of the 16S rRNA gene. Bacterial abundance measures and diversity statistics were assessed using QIIME2 metagenomics workflow, and the results were compared according to the region, the water temperature at the surface (36–59 °C), and pH (6.25–8.35). The predominant phyla observed were Proteobacteria, Actinobacteria, Firmicutes, [Thermi], and Cyanobacteria. A low abundance of Bacteroidetes, Chloroflexi, Acidobacteria, TM7, and Spirochaetes was detected in most of the springs. Several important bacterial species such as Deinococcus geothermalis that can tolerate Martian-like conditions, genera such as Legionella and Campylobacter that contain pathogenic species, sulfur metabolizing Desulfovibrio, Desulfatirhabdium, Desulforhabdus, Desulfacinum, Thermodesulfovibrio, Desulfovirga, and Thiobacter species, and several other species with the potential practical industrial application were detected. Several opportunistic human pathogens were detected in the water samples and raised a public health concern about the management of post-bathing water. Based on the Bray Curtis beta diversity metric, the microbial distribution correlated with temperature rather than the geographic distance. This study provides valuable new insights into the bacterial diversity of the hot springs in Sri Lanka. Future research needs to be conducted on industrially important thermophiles identified in this study.

Phase transformations in composite films of the system Se-Cu, obtained using explosive crystallization and thermal annealing

The results of experimental studies of the phase transformation in composite films of the Se-Cu system obtained in vacuum as a result of the sequential thermal deposition of selenium and copper on a glass substrate are presented. At a fixed thickness of the selenium layer (45 nm), the effect of the thickness of the copper layer (40-115 nm) on the phase composition of the synthesized films formed as a result of explosive crystallization occurring during the interaction of hot copper clusters with low-melting selenium was studied. It was found that the subsequent thermal annealing of the synthesized films is accompanied by a significant change in their phase composition and optical transmission spectra. Keywords: phase transformations, composite films of the Se-Cu system, explosive crystallization, thermal annealing, optical properties.

Фазовые превращения в композитных пленках системы Se-Cu, полученных взрывной кристаллизацией и термическим отжигом

The results of experimental studies of the phase transformation in composite films of the Se-Cu system obtained in vacuum as a result of the sequential thermal deposition of selenium and copper on a glass substrate are presented. At a fixed thickness of the selenium layer (45 nm), the effect of the thickness of the copper layer (40 - 115 nm) on the phase composition of the synthesized films formed as a result of explosive crystallization occurring during the interaction of hot copper clusters with low-melting selenium was studied. It was found that the subsequent thermal annealing of the synthesized films is accompanied by a significant change in their phase composition and optical transmission spectra.

The Effects of Thermal-Spatial Behaviours of Land Covers on Urban Heat Islands in Semi-Arid Climates

In recent decades, unsustainable urban development stemming from uncontrolled changes in land cover and the accumulation of population and activities have given rise to adverse environmental consequences, such as the formation of urban heat islands (UHIs) and changes in urban microclimates. The formation and intensity of UHIs can be influenced not only by the type of land cover, but also by other factors, such as the spatial patterns of thermal clusters (e.g., dimensions, contiguity, and integration). By emphasising the differences between semi-arid and cold-and-humid climates in terms of the thermal-spatial behaviours of various types of land cover in these climates, this paper aims to assess the behavioural patterns of thermal clusters in Tehran, Iran. To this end, the relationship between the land surface temperature (LST) and the types of land cover is first demonstrated using combined multispectral satellite images taken by Operational Land Imager (OLI), Thermal Infrared Sensor (TIRS) of the Landsat8 and MODIS, and Sentinel satellites to determine LST and land cover. The effects of different behavioural patterns of thermal clusters on the formation of daytime urban heat islands are then analysed through spatial cross-correlation analysis. Lastly, the thermal behaviours of each cluster are separately examined to reveal how their spatial patterns, such as contiguity, affect the intensity and formation of UHI, with the assumption that each point in a contiguous surface may exhibit different thermal behaviours, depending on its distance from the edge or centre. The results of this study show that the daytime UHIs do not occur in the central parts of Tehran, and instead they are created in the surrounding layer, which mostly consists of barren cover. This finding contrasts with previous research conducted regarding cities located in cold-and-humid climates. Our research also finds that the more compact the hot and cool clusters are, the more contiguous they become, which leads to an increase in UHIs. The results suggest that for every 100 pix/km2 increase, the cluster temperature increases by approximately 0.7–1 °C. Additionally, placing cool clusters near or in combination with hot clusters interrupts the effect of the hot clusters, leading to a significant temperature reduction. The paper concludes with recommendations for potential sustainable and context-based solutions to UHI problems in semi-arid climates that relate to the determination of the optimal contiguity distance and land use integration patterns for thermal clusters.

A Spatial Analysis of Tuberculosis Related Mortality in South Africa.

Background: South Africa, with an estimated annual tuberculosis (TB) incidence of 360,000 cases in 2019, remains one of the countries with the largest burden of TB in the world. The identification of highly burdened TB areas could support public health policy planners to optimally target resources and TB control and prevention interventions. Objective: To investigate the spatial epidemiology and distribution of TB mortality in South Africa in 2010 and its association with area-level poverty and HIV burden. Methods: The study analysed a total of 776,176 TB deaths for the period 2005–2015. Local and global and spatial clustering of TB death rates were investigated by Global and Local Moran’s Indices methods (Moran’s I). The spatial regression analysis was employed to assess the effect of poverty and HIV on TB mortality rates. Results: There was a significant decrease in TB mortality rate, from 179 per 100,000 population in 2005 to 60 per 100,000 population in 2015. The annual TB mortality rate was higher among males (161.5 per 100,000 male population; (95% confidence interval (CI) 132.9, 190.0) than among females (123.2 per 100,000 female population; (95% CI 95.6, 150.8)). The 35–44 age group experienced higher TB mortality rates, regardless of gender and time. Hot spot clusters of TB mortality were found in the South-Eastern parts of the country, whereas cold spot clusters were largely in the north-eastern parts. Tuberculosis death rates were positively associated with poverty, as measured by the South African Multidimension Poverty Index (SAMPI) as well TB death rates in the neighbouring districts. Conclusion: The findings of this study revealed a statistically significant decrease in TB deaths and a disproportionate distribution of TB deaths among certain areas and population groups in South Africa. The existence of the identified inequalities in the burden of TB deaths calls for targeted public health interventions, policies, and resources to be directed towards the most vulnerable populations in South Africa.

Resonant and non-resonant relaxation of globular clusters

ABSTRACT Globular clusters contain a finite number of stars. As a result, they inevitably undergo secular evolution (‘relaxation’) causing their mean distribution function (DF) to evolve on long time-scales. On one hand, this long-term evolution may be interpreted as driven by the accumulation of local deflections along each star’s mean field trajectory – so-called ‘non-resonant relaxation’ (NR). On the other hand, it can be thought of as driven by non-local, collectively dressed, and resonant couplings between stellar orbits, a process termed ‘resonant relaxation’ (RR). In this paper, we consider a model globular cluster represented by a spherical, isotropic isochrone DF, and compare in detail the predictions of both RR and NR theories against tailored direct N-body simulations. In the space of orbital actions (namely the radial action and total angular momentum), we find that both RR and NR theories predict the correct morphology for the secular evolution of the cluster’s DF, although the NR theory overestimates the amplitude of the relaxation rate by a factor of ∼2. We conclude that the secular relaxation of hot isotropic spherical clusters is not dominated by collectively amplified large-scale potential fluctuations, despite the existence of a strong ℓ = 1 damped mode. Instead, collective amplification affects relaxation only marginally even on the largest scales. The predicted contributions to relaxation from smaller scale fluctuations are essentially the same from RR and NR theories.

Spatial and temporal analysis of myocardial infarction incidence in Zanjan province, Iran

BackgroundMyocardial Infarction (MI) is a major important public health concern and has huge burden on health system across the world. This study aimed to explore the spatial and temporal analysis of the incidence of MI to identify potential clusters of the incidence of MI patterns across rural areas in Zanjan province, Iran.Materials & methodsThis was a retrospective and geospatial analysis study of the incidence of MI data from nine hospitals during 2014–2018. Three different spatial analysis methods (Spatial autocorrelation, hot spot analysis and cluster and outlier analysis) were used to identify potential clusters and high-risk areas of the incidence of MI at the study area.ResultsThree thousand eight hundred twenty patients were registered at Zanjan hospitals due to MI during 2014–2018. The overall age-adjusted incidence rate of MI was 343 cases per 100,000 person which was raised from 88 cases in 2014 to 114 cases in 2018 per 100,000 person-year (a 30% increase, P < 0.001). Golabar region had the highest age-adjusted incidence rate of MI (515 cases per 100,000 person). Five hot spots and one high-high cluster were detected using spatial analysis methods.ConclusionThis study showed that there is a great deal of spatial variations in the pattern of the incidence of MI in Zanjan province. The high incidence rate of MI in the study area compared to the national average, is a warning to local health authorities to determine the possible causes of disease incidence and potential drivers of high-risk areas. The spatial cluster analysis provides new evidence for policy-makers to design tailored interventions to reduce the incidence of MI and allocate health resource to unmet need areas.

Multivariate geotechnical zonation of seismic site effects with clustering-blended model for a city area, South Korea

The site classification system in the seismic design code and its dependent zonation should be guaranteed to represent the local spatial uncertainty of subsurface features, but have been uniformly used based on the site response parameters. Spatial interpolation-based zonation is only practically feasible if there are clear-cut stochastic/spatial correlations in geotechnical/geophysical measurements. The geology and terrain features can be substituted as an influential proxy for site amplification. To develop cluster-oriented zonation considering the spatial heterogeneity of the different site response parameters focusing on an uninvestigated area, this study proposes a new approach for multivariate site classification blended with geographic information system (GIS)-based spatial clustering and machine learning (ML)-based clustering ensemble technologies. GIS-based clustering characterizes a hot spot cluster with statistical and spatial correlation values of the site response parameters and defines the relative weight using the Gi∗Z-score as the index of spatial heterogeneity. ML-based clustering ensembles aim to combine the clustering model in terms of consistency and performance, and are designed for optimization through a consensus function by comparing the fitness with the site classification system to obtain better results than individual clustering algorithms. The novelty of the proposed workflow is the stepwise improvement of the proposed models compared with the zonation phases and practical methods.

Research on Spatial Patterns and Sustainable Development of Rural Tourism Destinations in the Yellow River Basin of China

Rural tourism is a new point of growth for tourism and the economy in the context of the new normalization of the economy and is of great significance in achieving the complementary coordination and integration of urban and rural areas, promoting rural transformation, and increasing farmers’ incomes. The trends of rural tourism development mechanisms studied on a spatial scale can be used to interpret the sustainable development of rural tourism from different perspectives. Based on the data of key rural tourism villages in China’s Yellow River Basin (hereinafter referred to as the Yellow River Basin), kernel density estimation and spatial hot spot clustering methods were used in the present study to analyze the spatial distribution pattern and sustainable development mechanisms of these villages. The results showed that the spatial distribution of the key villages presents greater concentrations in the west and south than in the east and north, respectively. The spatial distribution of the key villages was found to be primarily affected by factors such as historical culture, transportation locations, economic level, and topography. Finally, the sustainable development mechanisms of rural tourism are proposed, and corresponding suggestions are provided from the perspectives of sustainable livelihoods, operation management, and marketing.

A Machine Learned Approach to Identify the Anomalies in Load Pattern of Pakistan

The energy crisis of Pakistan is worsening day by day for different explicit and implicit reasons. Load pattern and its use in the studies of power system is a vital area. Here it is used for the identification and analysis of anomalies in the load pattern of Pakistan while using Support Vector Regressor Machine as a Machine Learning tool. The training phase has been provided with retrospective data of electrical load, temperature, and relative humidity so as to predict the future electrical load in the testing phase, based on the then data of temperature and relative humidity. Based on temperature, three groups of electrical load have been opted based on particle swarm optimization clustering namely moderate, cold and hot. The difference curve between the actual load and predicted load illustrated various anomalies in all of the three clusters. The high numbers of anomalies were found in the hot cluster whilst confirming the dependence of load pattern upon the weather parameters. The analysis of the difference curve between the patterns portrays to be deformed enormously. The analysis of the anomalies has also being carried out in terms of contextualized parameters.

Greater Sydney SARS-CoV-2 Observations from the 16th of June to the 13th of July

The Greater Sydney region is undergoing an outbreak of a COVID-19 Delta variant, which is much more transmissible than the variants we have observed in previous outbreaks in Australia. The aim of this report is to analyse the outbreak and the current impacts of the non-pharmaceutical interventions. While earlier results indicated that interventions were decreasing the growth rate, it has since been increasing with new hot spot clusters arising daily.

Ultrafast optical melting of trimer superstructure in layered 1T\u2032-TaTe2

Quasi-two-dimensional transition-metal dichalcogenides are a key platform for exploring emergent nanoscale phenomena arising from complex interactions. Access to the underlying degrees-of-freedom on their natural time scales motivates the use of advanced ultrafast probes sensitive to self-organised atomic-scale patterns. Here, we report the ultrafast investigation of TaTe2, which exhibits unique charge and lattice trimer order characterised by a transition upon cooling from stripe-like chains into a (3 × 3) superstructure of trimer clusters. Utilising MeV-scale ultrafast electron diffraction, we capture the photo-induced TaTe2 structural dynamics – exposing a rapid ≈ 1.4 ps melting of its low-temperature ordered state followed by recovery via thermalisation into a hot cluster superstructure. Density-functional calculations indicate that the initial quench is triggered by intra-trimer Ta charge transfer which destabilises the clusters, unlike melting of charge density waves in other TaX2 compounds. Our work paves the way for further exploration and ultimately rapid optical and electronic manipulation of trimer superstructures.

A Spatial Comparison of Roadway Lighting and Nonmotorist Crashes in Cambridge, MA

Dark lighting conditions, including those occurring at dawn and dusk, are correlated with increased nonmotorist crash frequency owing to reduced visibility, but little research has been done that investigates the spatial relationship between roadway lights and nonmotorist crashes on a community scale. This research used kernel density estimation methods to calculate the commonalities between geolocated streetlight data and non-motorist-vehicle crashes from 2010 to 2018 in Cambridge, Massachusetts. It was observed that dawn, dusk, and darkness showed a significant correlation between nonmotorist crashes and the absence of roadway lighting, all exceeding the control analysis undertaken with crashes occurring in daylight. The Getis-Ord [Formula: see text] hot spot cluster analysis indicated that areas with the greatest density of streetlights were associated with fewer nonmotorist crash hot spots. Future research seeks to corroborate these findings with data from other cities and to assess roadway lighting as a facet of pedestrian network connectivity.