Exploring trait- and state-based dietary restraint using ecological momentary assessment - Rebecca L. Elsworth; Elanor C. Hinton; Julian P. Hamilton-Shield; Natalia S. Lawrence; Jeffrey M. Brunstrom (Appetite, 2026)

Public perceptions of aquaculture in Maine: The role of place-based values - Emily Whitmore; Anne Langston Noll; Christopher Davis; Thomas Safford; Lawrence Hamilton (Aquaculture, 2025)

Development of Momentary Appetite Capture (MAC): A versatile tool for monitoring appetite over long periods - Rebecca L. Elsworth; Elanor C. Hinton; Annika N. Flynn; Lucy H. Merrell; Julian P. Hamilton-Shield; Natalia S. Lawrence; Jeffrey M. Brunstrom (Appetite, 2024)

Using ecological momentary assessment to investigate trait- and state-based dietary restraint in everyday life - Rebecca Elsworth; Elanor C. Hinton; Natalia Lawrence; Julian Hamilton-Shield; Jeffrey Brunstrom (Appetite, 2023)

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Sex differences in changes of protein synthesis with rapamycin treatment are minimized when metformin is added to rapamycin - Christopher A. Wolff; Marcus M. Lawrence; Hunter Porter; Qian Zhang; Justin J. Reid; Jaime L. Laurin; Robert V. Musci; Melissa A. Linden; Frederick F. Peelor; Jonathan D. Wren; Joseph S. Creery; Kyle J. Cutler; et al. (GeroScience, 2021)

Self-assessed understanding of climate change - Lawrence C. Hamilton (Climatic Change, 2018)

Staying in place during times of change in Arctic Alaska: the implications of attachment, alternatives, and buffering - Henry P. Huntington; Philip A. Loring; Glenna Gannon; Shari Fox Gearheard; S. Craig Gerlach; Lawrence C. Hamilton (Regional Environmental Change, 2018)

Wildfire, climate, and perceptions in Northeast Oregon - Lawrence C. Hamilton; Joel Hartter; Barry D. Keim; Angela E. Boag; Michael W. Palace; Forrest R. Stevens; Mark J. Ducey (Regional Environmental Change, 2016)

Experimental evidence indicates that native freshwater fish outperform introduced Gambusia in mosquito suppression when water temperature is below 25°C - Craig Lawrence; Neil Rutherford; Rod Hamilton; Dean Meredith (Hydrobiologia, 2016)

What people know - Lawrence Hamilton (Journal of Environmental Studies and Sciences, 2015)

Arctic warming and your weather: public belief in the connection - Lawrence C. Hamilton; Mary Lemcke‐Stampone (International Journal of Climatology, 2014)
Will Arctic warming affect mid‐latitude weather? Many researchers think so, and have addressed this question through scientific articles and news media. Much of the public accepts such a connection as well. Across three New Hampshire surveys with more than 1500 interviews, 60% of respondents say they think future Arctic warming would have major effects on their weather. Arctic/weather responses changed little after Superstorm Sandy brushed the region, but exhibit consistently strong partisan divisions that grow wider with education. Belief in an Arctic/weather connection also varies, in a nonlinear pattern, with the temperature anomaly around day of interview. Interviewed on unseasonably warm or cool days, respondents are more likely to think that Arctic warming would have major effects on their weather. This unscientific response seems to mirror the scientific discussion about extremes.

Education, politics and opinions about climate change evidence for interaction effects - Lawrence C. Hamilton (Climatic Change, 2011)

Regional variation in perceptions about climate change - Lawrence C. Hamilton; Barry D. Keim (International Journal of Climatology, 2009)
A 2007 survey covering rural areas in nine US states provides data on perceived local impacts of climate change. Perceptions vary from region to region, with a pattern suggesting links to real climate—specifically to winter warming in snow country. A multivariate analysis using mixed‐effects ordered logit regression confirms a significant perception‐temperature relationship, net of individual background and ideological characteristics, and of regional variations. These findings invite more detailed research. Copyright © 2009 Royal Meteorological Society

Toward understanding the human dimensions of the rapidly changing arctic system: insights and approaches from five HARC projects - Henry P. Huntington; Lawrence C. Hamilton; Craig Nicolson; Ronald Brunner; Amanda Lynch; Astrid E. J. Ogilvie; Alexey Voinov (Regional Environmental Change, 2007)

Ski areas, weather and climate: time series models for New England case studies - Lawrence C. Hamilton; Cliff Brown; Barry D. Keim (International Journal of Climatology, 2007)
Wintertime warming trends experienced in recent decades, and predicted to increase in the future, present serious challenges for ski areas and whole regions that depend on winter tourism. Most research on this topic examines past or future climate‐change impacts at yearly to decadal resolution, to obtain a perspective on climate‐change impacts. We focus instead on local‐scale impacts of climate variability, using detailed daily data from two individual ski areas. Our analysis fits ARMAX (autoregressive moving average with exogenous variables) time series models that predict day‐to‐day variations in skier attendance from a combination of mountain and urban weather, snow cover and cyclical factors. They explain half to two‐thirds of the variation in these highly erratic series, with no residual autocorrelation. Substantively, model results confirm the “backyard hypothesis” that urban snow conditions significantly affect skier activity; quantify these effects alongside those of mountain snow and weather; show that previous‐day conditions provide a practical time window; find no monthly effects net of weather; and underline the importance of a handful of high‐attendance days in making or breaking the season. Viewed in the larger context of climate change, our findings suggest caution regarding the efficacy of artificial snowmaking as an adaptive strategy, and of smoothed yearly summaries to characterize the timing‐sensitive impacts of weather (and hence, high‐variance climate change) on skier activity. These results elaborate conclusions from our previous annual‐level analysis. More broadly, they illustrate the potential for using ARMAX models to conduct integrated, dynamic analysis across environmental and social domains. Copyright © 2007 Royal Meteorological Society

The influence of human activity in the Arctic on climate and climate impacts - Henry P. Huntington; Michelle Boyle; Gwenn E. Flowers; John W. Weatherly; Lawrence C. Hamilton; Larry Hinzman; Craig Gerlach; Rommel Zulueta; Craig Nicolson; Jonathan Overpeck (Climatic Change, 2007)

Hinge peptide combinatorial libraries for inhilbitors of botulinum neurotoxins and saxitoxin: Deconvolution strategy - Graham J. Moore; Diana M. Moore; Samir S. Roy; Lawrence J. Hayden; Murray G. Hamilton; Nora W. C. Chan; William E. Lee (Molecular Diversity, 2006)

Letters - Scott Kiewit; Richard G. Reid; Lawrence S. Hamilton (Journal of Forestry, 2004)

Social Change, Ecology and Climate in 20th-Century Greenland - Lawrence Hamilton; Per Lyster; Oddmund Otterstad (Climatic Change, 2000)