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Wildfire prediction models that can be applied across diverse regions at fine scales (< 100 m) are critical for wildfire management. Remote sensing offers a path forward by providing heterogeneous and dynamic measurements of fuel load, type, and flammability. Machine learning methods such as random forests provide an empirical framework that are high-accuracy, computationally efficient, interpretable and able to model complex ecological relationships. Here we use high resolution (70 m, every 3–5 days) remote sensing observations of evapotranspiration and evaporative stress index, which represent plant water stress, from Ecosystem Spaceborne Thermal Radiometer on Space Station (ECOSTRESS), as well as topography and weather data, to predict burn severity and occurrence for 8 large wildfires that burned 3715 km 2 from 2021 and 2022 in New Mexico, USA. These fires ranged from low to high burn intensity, and covered a diverse range of ecoregions (deserts, grasslands, forests), plant species, and topographies. We used a single model to predict the burn severity of all wildfires one week before occurrence. The prediction accuracy was greatest when using all predictors (ECOSTRESS, weather, topography) (R 2  = 0.77). We assessed the role of spatial autocorrelation in driving model performance by: (1) increasing the sample spacing of our dataset, (2) introducing new predictors that represent spatial structure in the data, and (3) training our model on half the fires and predicting the other half of the fires. We found that after increasing sample spacing, model accuracy declined. However, we found declines in model accuracy were more impacted by decreased training set size compared to the distance spacing-indicating that the models are likely accurately capturing fine-scale processes. Scalability of random forest models was also found to be more challenging for regression problems but was accurate for classification of burned pixel occurrence (total pixel accuracy of 67%). These results provide promising results for application of random forest models to predict fine-scale fire severity and occurrence with applications for fire management.

Wildfires increase runoff and sediment yields that impact downstream ecosystems. While the effects of wildfire on stream water quality are well documented, oceanic responses to wildfire remain poorly understood. Therefore, this study investigated oceanic responses to the 2018 Woolsey Fire using satellite remote sensing and in situ data analyses. We examined 2016–2020 turbidity plume (n = 192) and 2008–2020 fecal indicator bacteria (FIB, n = 15,015) measurements at variable proximity to the Woolsey Fire. Shifts in coastal water quality were more pronounced in the “inside” region, which drained the burn area. The inside region experienced 2018–2019 plume surface area monthly means that were 10 and 9 times greater than 2016–2017 and 2017–2018 monthly means, respectively. Further, linear regressions showed that 2018–2019 three-day precipitation totals produced plumes of greater surface area. We also noted statistically significant increases in the inside region in 2018–2019 total coliform and Enterococcus monthly means that were 9 and 53 times greater than 2008–2018 monthly means, respectively. These results indicate that sediment and microbial inputs to coastal ecosystems can increase substantially post-wildfire at levels relevant to public and environmental health, and underscore the benefit of considering remote sensing and in situ measurements for water quality monitoring.

Vaccination may be critical to curtailing the spread of the SARS-CoV-2 virus responsible for the COVID-19 pandemic, but herd immunity can only be realized with high vaccination coverage. There is a need to identify empirically supported strategies to increase uptake, especially among young adults as this subpopulation has shown relatively poor adherence to physical distancing guidelines. Social norms – estimates of peers’ behavior and attitudes – are robust predictors of health behaviors and norms-based intervention strategies may increase COVID vaccine uptake, once available. This study examined the extent that vaccination intentions and attitudes were associated with estimated social norms as an initial proof-of-concept test. In November of 2020, 647 undergraduate students (46.21% response rate) completed online surveys in which they reported intentions to get COVID and influenza vaccines, perceived importance of these vaccines for young adults, and estimated social norms regarding peers’ vaccination behaviors and attitudes. Students reported significantly greater intentions to get a COVID vaccine (91.64%) than an influenza vaccine (76.04%), and perceived COVID vaccination as significantly more important than influenza vaccination. The sample generally held strong intentions to receive a COVID vaccine and thought that doing so was of high importance, but participants, on average, perceived that other young adults would be less likely to be vaccinated and would not think vaccination was as important. Multiple regression models indicated that estimated social norms were positively associated with participants’ own intentions and perceived importance of getting a COVID vaccine. These significant associations highlight the potential value in developing and testing norms-based intervention strategies, such as personalized normative feedback, to improve uptake of forthcoming COVID vaccines among young adults.

Background This study is a randomized controlled trial evaluating an adaptation of the Future Possible Selves Task (FPST). This adaptation focuses on possible hope for and feared future selves related to drinking alcohol. The study will evaluate whether the FPST can reduce the typical increase in self-concept related to drinking (i.e., drinking identity) and accompanying escalation in alcohol misuse that commonly occurs during the transition out of high school in the United States. Its use of a factorial design will also provide a test of the most optimal FPST condition(s) to do so. Method The study will recruit 528 soon-to-graduate or recently-graduated high school students from the states of Texas and Washington. Recruitment will occur in two waves (once per year) at each site. Participants need to report drinking alcohol within the last year and interest in either decreasing or not increasing their drinking. The study has a 2 (write about future hoped-for self vs. not) × 2 (write about a future feared self vs. not) × 2 (dose: write once vs. write once per week for 3 weeks) design for the FPST. Procedures will occur online. Participants’ drinking identities, drinking behaviors, and other cognitive/affective/motivational factors related to drinking will be evaluated. Participants will be followed up to 12 months post-FPST. Discussion Analyses will evaluate the efficacy of the adapted FPST to prevent the typical escalation of drinking identity and alcohol misuse that commonly accompany the transition out of high school. It is expected that the FPST condition, which includes three doses of writing about a possible hoped-for and feared self, will be most effective in preventing escalation. If successful, the FPST has the potential to be a novel, scalable strategy for the prevention and intervention of alcohol misuse. Trial registration Clinicaltrials.gov registration # NCT06191861, registration date: December 8, 2023.

Corticosteroid-eluting endotracheal tubes (ETTs) were developed and employed in a swine laryngotracheal injury model to maintain airway patency and provide localized drug delivery to inhibit fibrotic scarring. Polycaprolactone (PCL) fibers with or without dexamethasone were electrospun onto the ETT surface PCL-only coated ETTs and placed in native airways of 18 Yorkshire swine. Regular and dexamethasone-PCL coated ETTs were placed in airways of another 18 swine injured by inner laryngeal mucosal abrasion. All groups were evaluated after 3, 7 and 14 days (n = 3/treatment/time). Larynges were bisected and localized stiffness determined by normal indentation, then sequentially matched with histological assessment. In the native airway, tissue stiffness with PCL-only ETT placement increased significantly from 3 to 7 days ( p  = 0.0016) and 3 to 14 days ( p  < 0.0001) while dexamethasone-PCL ETT placement resulted in stiffness decreasing from 7 to 14 days ( p  = 0.031). In the injured airway, localized stiffness at 14 days was significantly greater after regular ETT placement (23.1 ± 0.725 N/m) versus dexamethasone-PCL ETTs (17.10 ± 0.930 N/m, p  < 0.0001). Dexamethasone-loaded ETTs were found to reduce laryngotracheal tissue stiffening after simulated intubation injury compared to regular ETTs, supported by a trend of reduced collagen in the basement membrane in injured swine over time. Findings suggest localized corticosteroid delivery allows for tissue stiffness control and potential use as an approach for prevention and treatment of scarring caused by intubation injury.

Background Several ecological momentary assessment studies have examined event-level associations between motives for cannabis use and cannabis use outcomes (e.g., duration of intoxication, consequences), and endorsing multiple motives during the same observation has been linked to heavier cannabis use and more consequences. However, it remains unclear whether specific combinations of motives are differentially associated with cannabis use outcomes above and beyond the effect of endorsing more motives. Methods We utilized ecological momentary assessment data from 571 young adult females who regularly used cannabis to conduct a multilevel latent class analysis of observations during which multiple motives for cannabis use were endorsed and compared results to those derived from a count of the number of motives endorsed. Results Endorsing more motives (operationalized as a count of motives) was associated with heavier cannabis use and more consequences of use at the event-level. Six common combinations of motives (i.e., classes) were identified in the latent class analysis of observations with multiple motives. Results indicated differences among motive classes with the same number of motives. For example, the two classes characterized by the endorsement of three motives displayed different patterns with one ( coping , social , enhancement ) being consistently associated with heavier use than most classes characterized by endorsing two motives, while the other ( coping , enhancement , medical ) was not consistently associated with heavier use. Further, one class characterized by endorsement of two motives ( coping and medical ) was consistently associated with lighter use and fewer consequences compared to other classes characterized by endorsement of two motives. Conclusion Results indicate that specific combinations of motives are associated with differences in cannabis use outcomes above and beyond the effect of simply endorsing more motives.

Background Laryngeal injury associated with traumatic or prolonged intubation may lead to voice, swallow, and airway complications. The interplay between inflammation and microbial population shifts induced by intubation may relate to clinical outcomes. The objective of this study was to investigate laryngeal mechanics, tissue inflammatory response, and local microbiome changes with laryngotracheal injury and localized delivery of therapeutics via drug-eluting endotracheal tube. Methods A simulated traumatic intubation injury was created in Yorkshire crossbreed swine under direct laryngoscopy. Endotracheal tubes electrospun with roxadustat or valacyclovir- loaded polycaprolactone (PCL) fibers were placed in the injured airway for 3, 7, or 14 days (n = 3 per group/time and ETT type). Vocal fold stiffness was then evaluated with normal indentation and laryngeal tissue sections were histologically examined. Immunohistochemistry and inflammatory marker profiling were conducted to evaluate the inflammatory response associated with injury and ETT placement. Additionally, ETT biofilm formation was visualized using scanning electron microscopy and micro-computed tomography, while changes in the airway microbiome were profiled through 16S rRNA sequencing. Results Laryngeal tissue with roxadustat ETT placement had increasing localized stiffness outcomes over time and histological assessment indicated minimal epithelial ulceration and fibrosis, while inflammation remained severe across all timepoints. In contrast, vocal fold tissue with valacyclovir ETT placement showed no significant changes in stiffness over time; histological analysis presented a reduction in epithelial ulceration and inflammation scores along with increased fibrosis observed at 14 days. Immunohistochemistry revealed a decline in M1 and M2 macrophage markers over time for both ETT types. Among the cytokines, IL-8 levels differed significantly between the roxadustat and valacyclovir ETT groups, while no other cytokines showed statistically significant differences. Additionally, increased biofilm formation was observed in the coated ETTs with notable alterations in microbiota distinctive to each ETT type and across time. Conclusion The injured and intubated airway resulted in increased laryngeal stiffness. Local inflammation and the type of therapeutic administered impacted the bacterial composition within the upper respiratory microbiome, which in turn mediated local tissue healing and recovery.

Los Angeles coastal waters are an ecologically important marine habitat and a famed recreational area for tourists. Constant surveillance is essential to ensure compliance with established health standards and to address the persistent water quality challenges in the region. Remotely sensed datasets are increasingly being applied toward improved detection of water quality by augmenting monitoring programs with spatially intensive and accessible data. This study evaluates the potential of satellite remote sensing to augment traditional monitoring by analyzing the relationship between in situ and satellite-derived turbidity data. Field measurements were performed from July 2021 to March 2024 to build synchronous matchup datasets consisting of satellite and field data. Correlation analysis indicated a positive relationship between satellite-derived and field-measured turbidity (R2 = 0.451). Machine learning models were assessed for predictive accuracy, with the random forest model achieving the highest performance (R2 = 0.632), indicating its robustness in modeling complex turbidity patterns. Seasonal trends revealed higher turbidity during wet months, likely due to stormwater runoff from the Ballona Creek watershed. Despite limitations from cloud cover and spatial resolution, the findings suggest that integrating satellite data with machine learning can enhance large-scale, efficient turbidity monitoring in coastal waters.

Motor vehicle crashes remain a leading cause of death among young adults (ages 18-25) in the United States. Many drivers implicated in these crashes are under the influence of alcohol, cannabis, or the simultaneous use of alcohol and cannabis. Extremely limited research has assessed impaired driving behaviors and their predictors at the daily level. Perceived norms and motives to use substances have empirical support suggesting they may impact impaired driving-related behavior. Novel approaches to assess these associations at the daily level are needed and may inform future intervention and prevention programs. The goal of the current study is to utilize electronic daily assessments to assess driving under the influence of alcohol, cannabis, or simultaneous use and riding with a driver impaired by these substances to assess variability and predictors of these impaired driving-related behaviors at the daily level. This present manuscript details a protocol, measures, and a plan of analyses to assess how within-person differences in perceived norms and motives to use are associated with the likelihood of engaging in impaired driving-related behaviors. Participants include young adults in Washington State who report simultaneous use in the past month and either driving under the influence of alcohol, cannabis, or simultaneous use, or riding with a driver under the influence of both substances in the past 6 months. Individuals who verify their identity and meet eligibility requirements will complete a baseline assessment after which they will be scheduled for training on the daily assessment procedure via Zoom. Next, they will be invited to complete daily surveys on Thursday, Friday, Saturday, and Sunday every other week for 6 months and a 6-month follow up assessment. Analyses will utilize multilevel models with days nested within individuals. The study is currently recruiting participants. A total of 192 participants have been recruited and 100 have completed the study protocol. Data collection is expected to be completed in Fall 2022. This study utilizes a novel design to assess impaired driving and predictors at the daily level among young adults at high risk of impaired driving-related behaviors. Findings will provide unique data that will shape the knowledge base in the field of social science and public health substance use research and that may be helpful for future prevention and intervention efforts on impaired driving.

Two-year college students represent 35% of U.S. undergraduates, yet substance use among them is understudied. Grounded in Social Norms Theory, the present study examined alcohol and cannabis use prevalence and associations between perceived peer use (descriptive norms), approval of use (injunctive norms), and personal use among 2-year students. We also explored whether identification with the reference group or age moderated associations. Data were collected from May through August of 2020 from 1037 2-year college students in Washington State (screening sample) aged 18–29. Of these, 246 participants who reported recent, moderate alcohol and/or cannabis use completed a follow-up survey. Screening survey participants reported past-month alcohol and cannabis use and demographics, while follow-up participants provided data on perceived peer descriptive and injunctive norms and group identification. Screening participants reported drinking an average of 3.32 (SD = 7.76) drinks weekly and being high for 8.18 h (SD = 20.95). Follow-up participants overestimated peer alcohol and cannabis use. Regression analyses showed perceived descriptive alcohol and cannabis norms were positively associated with personal use, and perceived injunctive alcohol norms were positively related to alcohol-related consequences. Differences by student age were also observed. Findings suggest perceived peer norms are risk factors for substance use behaviors among 2-year college students. Tailored normative feedback interventions may reduce high-risk use in this underserved population.