Predicting passive dispersal using particle hitting distance estimates in the near field in rivers - C. R. Farrow; A. Jabbari; J. D. Ackerman (Limnology and Oceanography, 2026)
Particles, including biologically relevant ones, released in rivers may interact with the bed multiple times throughout their dispersal downstream. Passive dispersal is influenced by local variations in bed morphometry and hydrodynamics, especially in the near field—the area downstream of a point source where complete mixing across the river's width has not yet occurred. We examined predictors (e.g., depth [], shear velocity [], velocity at 50% ) of the distance at which particles first contact the bed (hitting distance) using a theoretical model of turbulent transport. We identified as the strongest predictor of hitting distance and tested how different estimates of affected model predictions. We aimed to determine whether increased sampling effort (e.g., multiple estimates in a reach) improves the accuracy of the model. Specifically, we compared a reach‐based derived from the depth–slope product (DSP) vs. local estimates based on velocity measurements at 50% H , calculated using the turbulent kinetic energy method. We evaluated predictions against empirical data from three river reaches (Conestogo, Grand, and Speed rivers) with different hydrodynamic conditions (e.g., H −1 ). Model predictions based on reach‐averaged or single values (RMSE local = 2–3 m) were more accurate than DSP‐derived estimates (RMSE DSP = 3–7 m) and an implementation that accounts for longitudinal variations in local (RMSE modelled = 1–8 m). Our results suggest that accounting for variations in bed morphometry and hydrodynamics improves predictions of particle transport and dispersal at reach scales.

Targeted Profiling of Signaling Molecules in Papaver rhoeas L. Reveals that Onset and Control of Benzylisoquinoline Alkaloid Biosynthesis Corresponds with Cytokinins, Independent of Light - Zeynab Azimychetabi; Anna B. Kisiala; Erin N. Morrison; Scott C. Farrow; R. J. Neil Emery (Journal of Plant Growth Regulation, 2026)

The effects of age on associations between pre-school children's eating behaviour traits and diet quality - Alissa J. Burnett; Catherine G. Russell; Claire Farrow; Alison C. Spence; Anthony Worsley; Kathleen E. Lacy (Appetite, 2024)

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

Evaluation of the Potential Antimicrobial Resistance Transfer from a Multi-Drug Resistant Escherichia coli to Salmonella in Dairy Calves - T. S. Edrington; R. L. Farrow; M. E. Hume; P. N. Anderson; G. R. Hagevoort; D. J. Caldwell; T. R. Callaway; R. C. Anderson; D. J. Nisbet (Current Microbiology, 2013)

Integration of deep transcript and targeted metabolite profiles for eight cultivars of opium poppy - Isabel Desgagné-Penix; Scott C. Farrow; Dustin Cram; Jacek Nowak; Peter J. Facchini (Plant Molecular Biology, 2012)

Acyl-Homoserine-Lactone Autoinducer in the Gastrointesinal Tract of Feedlot Cattle and Correlation to Season, E. Coli O157:H7 Prevalence, and Diet - T. S. Edrington; R. L. Farrow; V. Sperandio; D. T. Hughes; T. E. Lawrence; T. R. Callaway; R. C. Anderson; D. J. Nisbet (Current Microbiology, 2009)

Patterns of cytokinins and leaf gas exchange among canopy layers of a mature sugar maple (Acer saccharum) stand - Ian Reeves; Scott C. Farrow; R. J. Neil Emery (Trees, 2007)

Evaluating response surface designs for uncertainty analysis and prescriptive applications of a large-scale water quality model - Martin T. Schultz; Mitchell J. Small; Paul S. Fischbeck; R. Scott Farrow (Environmental Modeling & Assessment, 2006)

Genomic structure, expression, and chromosome mapping of the mouse homologue for the WSL-1 ( DR3 , Apo3 , TRAMP , LARD , TR3 , TNFRSF12 ) gene - Eddie C. Y. Wang; Jeremy Kitson; Anette Thern; Jill Williamson; Stuart N. Farrow; Michael J. Owen (Immunogenetics, 2001)

Gastroesophageal reflux disease, use of H2 receptor antagonists, and risk of esophageal and gastric cancer - Diana C. Farrow; Thomas L. Vaughan; Carol Sweeney; Marilie D. Gammon; Wong-Ho Chow; Harvey A. Risch; Janet L. Stanford; Philip D. Hansten; Susan T. Mayne; Janet B. Schoenberg; Heidi Rotterdam; Habibul Ahsan; et al. (Cancer Causes & Control, 2000)