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1. Computational Modeling of Regional Dynamics of Pandemic Behavior using Psychologically Valid Agents

   https://doi.org/10.21203/rs.3.rs-4189570/v1  

   Pirolli, Peter; Teng, Choh Man; Lebiere, Christian; Mitsopoulos, Konstantinos; Morrison, Don; Orr, Mark (April 2024, Research Square)

   Abstract Regional Psychologically Valid Agents (R-PVAs) are computational models representing cognition and behavior of regional populations. R-PVAs are developed using ACT-R—a computational implementation of the Common Model of Cognition. We developed R-PVAs to model mask-wearing behavior in the U.S. over the pre-vaccination phase of COVID-19 using regionally organized demographic, psychographic, epidemiological, information diet, and behavioral data. An R-PVA using a set of five regional predictors selected by stepwise regression, a psychological self-efficacy process, and context-awareness of the effective transmission number,R_t, yields good fits to the observed proportion of the population wearing masks in 50 U.S. states [R²= 0.92]. An R-PVA based on regional Big 5 personality traits yields strong fits [R²= 0.83]. R-PVAs can be probed with combinations of population traits and time-varying context to predict behavior. R-PVAs are a novel technique to understand dynamical, nonlinear relations amongst context, traits, states, and behavior based on cognitive modeling. 

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2. Role of meteorological factors in the transmission of SARS-CoV-2 in the United States

   https://doi.org/10.1038/s41467-021-23866-7  

   Ma, Yiqun; Pei, Sen; Shaman, Jeffrey; Dubrow, Robert; Chen, Kai (June 2021, Nature Communications)

   Abstract Improved understanding of the effects of meteorological conditions on the transmission of SARS-CoV-2, the causative agent for COVID-19 disease, is needed. Here, we estimate the relationship between air temperature, specific humidity, and ultraviolet radiation and SARS-CoV-2 transmission in 2669 U.S. counties with abundant reported cases from March 15 to December 31, 2020. Specifically, we quantify the associations of daily mean temperature, specific humidity, and ultraviolet radiation with daily estimates of the SARS-CoV-2 reproduction number (R_t) and calculate the fraction ofR_tattributable to these meteorological conditions. Lower air temperature (within the 20–40 °C range), lower specific humidity, and lower ultraviolet radiation were significantly associated with increasedR_t. The fraction ofR_tattributable to temperature, specific humidity, and ultraviolet radiation were 3.73% (95% empirical confidence interval [eCI]: 3.66–3.76%), 9.35% (95% eCI: 9.27–9.39%), and 4.44% (95% eCI: 4.38–4.47%), respectively. In total, 17.5% ofR_twas attributable to meteorological factors. The fractions attributable to meteorological factors generally were higher in northern counties than in southern counties. Our findings indicate that cold and dry weather and low levels of ultraviolet radiation are moderately associated with increased SARS-CoV-2 transmissibility, with humidity playing the largest role. 

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3. Remote sensing: generation of long‐term kelp bed data sets for evaluation of impacts of climatic variation

   https://doi.org/10.1002/ecy.3031  

   Hamilton, Sara L.; Bell, Tom W.; Watson, James R.; Grorud‐Colvert, Kirsten A.; Menge, Bruce A. (April 2020, Ecology)

   Abstract A critical tool in assessing ecosystem change is the analysis of long‐term data sets, yet such information is generally sparse and often unavailable for many habitats. Kelp forests are an example of rapidly changing ecosystems that are in most cases data poor. Because kelp forests are highly dynamic and have high intrinsic interannual variability, understanding how regional‐scale drivers are driving kelp populations—and particularly how kelp populations are responding to climate change—requires long‐term data sets. However, much of the work on kelp responses to climate change has focused on just a few, relatively long‐lived, perennial, canopy‐forming species. To understand how kelp populations with different life history traits are responding to climate‐related variability, we leverage 35 yr of Landsat satellite imagery to track the population size of an annual, ruderal kelp,Nereocystis luetkeana, across Oregon. We found high levels of interannual variability inNereocystiscanopy area and varying population trajectories over the last 35 yr. Surprisingly, OregonNereocystispopulation sizes were unresponsive to a 2014 marine heat wave accompanied by increases in urchin densities that decimated northern CaliforniaNereocystispopulations. Some OregonNereocystis populations have even increased in area relative to pre‐2014 levels. Analysis of environmental drivers found thatNereocystispopulation size was negatively correlated with estimated nitrate levels and positively correlated with winter wave height. This pattern is the inverse of the predicted relationship based on extensive prior work on the perennial kelpMacrocystis pyriferaand may be related to the annual life cycle ofNereocystis. This article demonstrates (1) the value of novel remote sensing tools to create long‐term data sets that may challenge our understanding of nearshore marine species and (2) the need to incorporate life history traits into our theory of how climate change will shape the ocean of the future. 

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4. Inferring dolphin population status: using unoccupied aerial systems to quantify age‐structure

   https://doi.org/10.1111/acv.12978  

   Vivier, F.; Andrés, C.; Gonzalvo, J.; Fertitta, K.; van_Aswegen, M.; Foroughirad, V.; Mann, J.; McEntee, M.; Wells, R_S; Bejder, L. (August 2024, Animal Conservation)

   Abstract Assessing trends in population abundance and demographics is crucial for managing long‐lived and slow‐reproducing species. Obtaining demographic data, and age‐structure information, is challenging, notably for cetaceans. To address this, we combined Unoccupied Aerial System (UAS; drone) photogrammetry data with long‐term (>20 years) photo identification data to assess the age‐structure of the critically endangered sub‐population of common bottlenose dolphins (Tursiops truncatus) of the Gulf of Ambracia, Greece. We compared our findings with two extensively studied non‐endangered bottlenose dolphin populations (T. aduncusin Shark Bay, Australia, andT. truncatusin Sarasota Bay, USA). Using a log‐linear model, we estimated the total body lengths (TL) of 160 known‐aged dolphins between 2021 and 2023 from blowhole‐to‐dorsal‐fin distance (BHDF) measurements collected during surfacing. Subsequently, we tested four growth models to establish an age‐length growth curve. We assessed the sub‐population's age‐structure using three methods: (1) UAS‐derived TL estimates, (2) age‐length growth curve and (3) long‐term monitoring data (i.e. actual age‐structure). UAS‐measured TL (247.6 ± 32.2 cm) and UAS‐estimated TL (246.0 ± 34.7 cm) of the Greek sub‐population showed no differences. The Richards Growth model suggested an asymptotic length of 258.5 cm. In Greece, resulting age‐structure estimates across the three methods revealed no significant differences (P > 0.1). The Gulf of Ambracia and Shark Bay populations shared similar age‐structures, while Sarasota had higher proportions of 2–10 year‐olds and lower proportions of 10+ year‐olds. All populations had a comparable proportion of 0–2 year‐olds (~14%), indicating a similar reproductive rate. Our findings suggest stability in the Greek sub‐population; however, additional monitoring of reproductive parameters is essential before concluding its status. We demonstrated the effectiveness of UAS‐photogrammetry in rapidly quantifying population age‐structure, including scenarios with limited or no demographic data. This technique shows promise for enhancing precision, timeliness, cost‐effectiveness and efficiency in population monitoring and informing timely conservation management decisions. 

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5. Lung parenchyma transverse relaxation rates at 0.55 T

   https://doi.org/10.1002/mrm.29541  

   Li, Bochao; Lee, Nam G; Cui, Sophia X; Nayak, Krishna S (April 2023, Magnetic Resonance in Medicine)

   PurposeTo determineR₂and transverse relaxation rates in healthy lung parenchyma at 0.55 T. This is important in that it informs the design and optimization of new imaging methods for 0.55T lung MRI. MethodsExperiments were performed in 3 healthy adult volunteers on a prototype whole‐body 0.55T MRI, using a custom free‐breathing electrocardiogram‐triggered, single‐slice echo‐shifted multi‐echo spin echo (ES‐MCSE) pulse sequence with respiratory navigation. Transverse relaxation ratesR₂and and off‐resonance ∆fwere jointly estimated using nonlinear least‐squares estimation. These measurements were compared againstR₂estimates from T₂‐prepared balanced SSFP (T₂‐Prep bSSFP) and estimates from multi‐echo gradient echo, which are used widely but prone to error due to different subvoxel weighting. ResultsThe meanR₂and values of lung parenchyma obtained from ES‐MCSE were 17.3 ± 0.7 Hz and 127.5 ± 16.4 Hz (T₂ = 61.6 ± 1.7 ms;  = 9.5 ms ± 1.6 ms), respectively. The off‐resonance estimates ranged from −60 to 30 Hz. TheR₂from T₂‐Prep bSSFP was 15.7 ± 1.7 Hz (T₂ = 68.6 ± 8.6 ms) and from multi‐echo gradient echo was 131.2 ± 30.4 Hz ( = 8.0 ± 2.5 ms). Paired t‐test indicated that there is a significant difference between the proposed and reference methods (p < 0.05). The meanR₂estimate from T₂‐Prep bSSFP was slightly smaller than that from ES‐MCSE, whereas the mean and estimates from ES‐MCSE and multi‐echo gradient echo were similar to each other across all subjects. ConclusionsJoint estimation of transverse relaxation rates and off‐resonance is feasible at 0.55 T with a free‐breathing electrocardiogram‐gated and navigator‐gated ES‐MCSE sequence. At 0.55 T, the meanR₂of 17.3 Hz is similar to the reported meanR₂of 16.7 Hz at 1.5 T, but the mean of 127.5 Hz is about 5–10 times smaller than that reported at 1.5 T. 

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