Hydrodynamic oscillations and variable swimming speed in squirmers close to repulsive walls

We present a lattice Boltzmann study of the hydrodynamics of a fully resolved squirmer, radius R, confined in a slab of fluid between two no-slip walls. We show that the coupling between hydrodynamics and short-range repulsive interactions between the swimmer and the surface can lead to hydrodynamic trapping of both pushers and pullers at the wall, and to hydrodynamic oscillations in the case of a pusher. We further show that a pusher moves significantly faster when close to a surface than in the bulk, whereas a puller undergoes a transition between fast motion and a dynamical standstill according to the range of the repulsive interaction. Our results critically require near-field hydrodynamics; they further suggest that it should be possible to control density and speed of squirmers at a surface by tuning the range of steric and electrostatic swimmer-wall interactions.Comment: 5 + 8 pages, 4 + 4 Figure

Snow depth measurement via time lapse photography and automated image recognition

January 2019.Includes bibliographical references.Seasonal snow is a crucial component of water supply in Colorado and the western United States. Measurement of snow accumulation through the winter and spring allows water managers to forecast water supply for the growing season and take actions to ease flooding and drought. The Natural Resources Conservation Service’s (NRCS) snow telemetry (SNOTEL) network provides real-time data at a high cost per station and at single points. An evaluation of existing field measurements of snow depth taken in 2009 and 2010 was undertaken to determine if fine resolution depth measurements are justified. Fassnacht et al. (in press) showed that the snow depth variability can be substantial even at fine resolution. However, these data required extensive labor to collect and only represented one measurement in time. A low-cost method to measure snow variability around these stations or in underrepresented areas could improve snow forecasts by quantifying the representativeness of data from the current network. To this end, we trialed a method combining time lapse photography and computer vision techniques to find snow depth at five sites in Colorado during water year 2018. Different site configurations were trialed, and a best operating procedure was determined. The data gathered were not more accurate than current ultrasonic or laser snow depth measurement technologies. However, the low cost and versatility of this method may make it more applicable in certain situations

Consumer Awareness of the Jersey Fresh Promotional Program

The Jersey Fresh marketing program, one of the nation’s leading examples of state-sponsored agricultural marketing promotion, enables consumers to easily identify quality fresh produce from New Jersey by promoting locally grown fruits and vegetables in the market with Jersey Fresh’s logos. This study utilizes a consumer survey to evaluate the effectiveness of the Jersey Fresh Program in terms of the impact the promotional logos have on consumers. The results of this study provide valuable information that may be used to improve the Jersey Fresh Program, and also may be used in the promotion of other New Jersey farm products as well as products in other states which have similar promotional programs. Among other things, this study demonstrated that the Jersey Fresh promotional program has created significant brand awareness among New Jersey consumers and that consumers are willing to purchase Jersey Fresh produce when it’s available. Consumers reported seeing the Jersey Fresh logo most frequently on in-store produce displays. What’s more, women were more likely than men to be aware of Jersey Fresh, as were married people. Survey participants believed Jersey Fresh produce to be better than produce in other states in terms of quality and freshness. Moreover, consumers associate the Jersey Fresh logo with locally grown, quality produce. Suggestions that emerged from the study include increasing the availability of Jersey Fresh produce during the production seasons would ensure continued consumer patronage. Also, increasing promotions of Jersey Fresh produce in supermarkets may further increase the popularity of Jersey Fresh produce. The study showed that a vii majority of consumers were willing to pay only a small percentage premium for Jersey Fresh produce over the market prices for other fresh produce; therefore, significant price differentials are not recommended for Jersey Fresh produce. The results of this study lead to a better understanding of New Jersey consumers’ shopping behavior, their preferences towards local produce and their demographic composition. The results may be especially encouraging to those developing marketing strategies for Jersey Fresh produce or for other similar New Jersey consumer products.Consumer/Household Economics, Marketing,

Prediction-Based Learning and Processing of Event Knowledge.

Knowledge of common events is central to many aspects of cognition. Intuitively, it seems as though events are linear chains of the activities of which they are comprised. In line with this intuition, a number of theories of the temporal structure of event knowledge have posited mental representations (data structures) consisting of linear chains of activities. Competing theories focus on the hierarchical nature of event knowledge, with representations comprising ordered scenes, and chains of activities within those scenes. We present evidence that the temporal structure of events typically is not well-defined, but it is much richer and more variable both within and across events than has usually been assumed. We also present evidence that prediction-based neural network models can learn these rich and variable event structures and produce behaviors that reflect human performance. We conclude that knowledge of the temporal structure of events in the human mind emerges as a consequence of prediction-based learning

Returns to the Jersey Fresh Promotional Program: The Impacts of Promotional Expenditures on Farm Cash Receipts in New Jersey

In 1984, the Jersey Fresh program was implemented by the New Jersey Department of Agriculture and was the first state-funded marketing campaign for agricultural products produced in New Jersey. In an effort to spur demand for New Jersey farm products, this program was designed to increase consumer awareness of the state’s agricultural products as well as to encourage food retailers to promote Jersey Fresh products. With funding from the USDA’s Federal-State Marketing Improvement Program, the New Jersey Department of Agriculture commissioned this study to determine the impact of Jersey Fresh promotion on farmer cash receipts in New Jersey. The econometric analysis was focused on the fruit and vegetable sectors, the primary commodity areas expected to benefit most directly from Jersey Fresh promotion. Study results show that: • For every dollar spent on the Jersey Fresh Promotional Program through 2000, New Jersey’s agricultural fruit and vegetable sector revenues increased by $31.54 (2003 dollars). • The additional economic activity created in the agricultural industry also had impacts on other parts of the economy, namely agricultural suppliers and service providers. In fact, each dollar spent on Jersey Fresh promotion resulted in an additional$22.95 of sales in agricultural support industries and other related industries. • In total, each dollar spent on Jersey Fresh promotion resulted in $54.49 of increased economic output in the State. Adjusting all dollars to 2003 levels, this means that the$1.16 million spent on the Jersey Fresh program in 2000 increased fruit and vegetable cash receipts by $36.6 million and created an additional$26.6 million in economic activity within agricultural support industries. The total statewide economic impact of the Jersey Fresh program was therefore an estimated $63.2 million. The economic activity generated through Jersey Fresh promotion also impacts local, state, and federal taxes. An analysis of these tax impacts shows that New Jersey’s State and local tax revenues increased by$2.2 million in 2000 due to the increased economic activity attributable to Jersey Fresh promotion. Comparing this return to the 2000 program budget of $1.16 million, the Jersey Fresh program appears to be better than revenue-neutral.Agribusiness, Marketing,

The 6 minute walk in idiopathic pulmonary fibrosis: longitudinal changes and minimum important difference

The response characteristics of the 6 minute walk test (6MWT) in studies of idiopathic pulmonary fibrosis (IPF) are only poorly understood, and the change in walk distance that constitutes the minimum important difference (MID) over time is unknown

Universally Sloppy Parameter Sensitivities in Systems Biology

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring \emph{in vivo} biochemical parameters is difficult, and collectively fitting them to other data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a `sloppy' spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.Comment: Submitted to PLoS Computational Biology. Supplementary Information available in "Other Formats" bundle. Discussion slightly revised to add historical contex