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High resolution coherent multidimensional spectroscopy has the ability to reduce congestion and automatically sort peaks by species and quantum numbers, even for simple mixtures and molecules that are extensively perturbed. The two-dimensional version is relatively simple to carry out, and the results are easy to interpret, but its ability to deal with severe spectral congestion is limited. Three-dimensional spectroscopy is considerably more complicated and time-consuming than two-dimensional spectroscopy, but it provides the spectral resolution needed for more challenging systems. This paper describes how to design high resolution coherent 3D spectroscopy experiments so that a small number of strategically positioned 2D scans may be used instead of recording all the data required for a 3D plot. This faster and simpler approach uses new pattern recognition methods to interpret the results. Key factors that affect the resulting patterns include the scanning strategy and the four wave mixing process. Optimum four wave mixing (FWM) processes and scanning strategies have been identified, and methods for identifying the FWM process from the observed patterns have been developed. Experiments based on nonparametric FWM processes provide significant pattern recognition and efficiency advantages over those based on parametric processes. Alternative scanning strategies that use synchronous scanning and asynchronous scanning to create new kinds of patterns have also been identified. Rotating the resulting patterns in 3D space leads to an insight into similarities in the patterns produced by different FWM processes. [ABSTRACT FROM AUTHOR]

Background and Aims: Sobriety checkpoints are an effective strategy to reduce alcohol‐impaired driving, motor vehicle crashes, injuries and fatalities. The aim of this study was to identify the geographic extent over which individual sobriety checkpoints affect alcohol‐impaired driving. Design, Setting, Participants: Spatial ecological panel analysis using geolocated breath test data from the Queensland Police Service, Australia, for January 2012 to June 2018. Data were aggregated over 338 weeks within 528 Statistical Area level 2 (SA2) units (n = 178 464 SA2‐weeks) and 84 Statistical Area level 3 (SA3) units (n = 28 392 SA3‐weeks). SA2 units in Queensland contain a mean population of 8883.5 (SD = 55 018.3) and encompass 468.9 roadway kilometers (SD = 1490.0); SA3 units contain a mean population of 57 201.6 (SD = 29521.6) and encompass 2936.0 roadway kilometers (SD = 7025.0). Measurements Independent measures were the density of sobriety checkpoints conducted per 500 roadway kilometers within local and spatially adjacent space–time units. The dependent measure was the rate of tests that detected breath alcohol concentration (a proxy for blood alcohol concentration [BAC]) greater than the legal maximum value of 0.05% for fully licensed drivers in Queensland. Bayesian hierarchical spatial negative binomial models‐related sobriety checkpoints to the rate of breath tests with BAC ≥ 0.05% within and between space–time units. Findings One additional sobriety checkpoint conducted per 500 roadway kilometers was associated with 2.5% reduction in the rate of breath tests with BAC ≥ 0.05% within local SA2 units (incidence rate ratio [IRR] = 0.975; 95% credibility interval (CrI): 0.973–0.978), and with 5.5% reduction in the rate of breath tests with BAC ≥ 0.05% within local SA3 units (IRR = 0.945; 95%CrI: 0.937–0.953). Associations were attenuated towards null in spatially adjacent units and in temporally lagged units (e.g. SA3‐weeks; adjacent lagged 1 week: IRR = 0.969; 95%CrI: 0.937–1.003). Conclusions: Individual sobriety checkpoints appear to be associated with reductions in nearby alcohol‐impaired driving. Relationships decay after approximately 1 week and beyond local areas containing approximately 60 000 residents and 3000 kilometers of roadway. [ABSTRACT FROM AUTHOR]

Objective: Sobriety checkpoints have strong empirical and theoretical support as an intervention to reduce alcohol‐involved motor vehicle crashes. The purpose of this study was to examine whether checkpoint size (the number of police officers) and checkpoint duration (the amount of time in operation) affect associations between individual checkpoints and subsequent alcohol‐related crash incidence. Method: Queensland Police Service provided latitude–longitude coordinates and date and time data for all breath tests that occurred in Brisbane, Australia, from January 2012 to June 2018. We applied hierarchical cluster analysis to the latitude–longitude coordinates for breath tests, identifying checkpoints as clusters of ≥25 breath tests conducted by ≥3 breath testing devices over a duration of 3 to 8 hours. Generalized linear autoregressive moving average (GLARMA) models related counts of alcohol‐involved motor vehicle crashes to the number of checkpoints conducted per week, as well as 1 week prior and 2 weeks prior. Results: A total of 3420 alcohol‐related crashes occurred and 2069 checkpoints were conducted in Brisbane over the 6.5‐year (339‐week) study period. On average, checkpoints included a mean of 266.0 breath tests (SD = 216.3), 16.4 devices (SD = 13.7), and were 286.3 minutes in duration (SD = 104.2). Each 10 additional checkpoints were associated with a 12% decrease in crash incidence at a lag of 1 week (IRR = 0.88; 95%CI: 0.80, 0.97). We detected no differential associations according to checkpoint size or duration. Conclusions: Sobriety checkpoints are associated with fewer alcohol‐related motor vehicle crashes for around 1 week. Checkpoint size and duration do not appear to affect this relationship. [ABSTRACT FROM AUTHOR]

Purpose: To assess the association of neighborhood demographic and socioeconomic characteristics with COVID-19 incidence and mortality in New York City (NYC) over the first two waves of outbreak.Methods: This retrospective study used neighborhood-level data from 177 modified ZIP code tabulation areas in NYC between March 01, 2020 and April 30, 2021.Results: Neighborhoods that were most severely impacted in wave 1 were also more affected in wave 2. Neighborhoods with a higher percentage of seniors (≥75 years), males, Black and Hispanic population, and large-size households had higher incidence rates of COVID-19 in wave 1 but not in wave 2. Neighborhoods with higher percentage of Black and Hispanic population and lower insurance coverage had higher death rate per capita and case fatality ratio in wave 1, and neighborhoods with higher percentage of Black and Asian population had elevated case fatality ratio in wave 2. Median household income was negatively associated with incidence rate and death rate per capita but not associated with case fatality ratio in both waves. Neighborhoods with more seniors had higher death rate and case fatality ratio in both waves.Conclusions: Neighborhood disparities in COVID-19 incidence and mortality across NYC neighborhoods were dynamic during the first two waves of outbreak. [ABSTRACT FROM AUTHOR]