Eating Is Not Political Action

Food and environment are cultural stalwarts. Picture the red barn and solitary farmer toiling over fruited plains; or purple mountains majesty reflected in pristine waters. Agriculture and environment are core, distinct, American mythologies that we know are more intertwined than our stories reveal. To create policy at the interface of such centrally important and overlapping American ideals, there are two options. Passive governance fosters markets in which participants make individual choices that aggregate into inadvertent collective action. In contrast, assertive governance allows the public, mediated through elected officials, to enact intentional, goal oriented policy. American mythologies of food and environment arise because each is important culturally and physically. Given their essentiality, we must demand more intentionality, must demand policies not only because they are possible, but because they are thoughtful, effective, goal oriented, and intentional. Food and the environment are both too important to do otherwise. In today’s political climate, finding shared goals will be hard and accidental policy may be the best we can hope for in the short term. Progressive food advocates may settle for passive policies because these policies make fewer normative commitments. For three decades this has been exactly the strategy of environmental advocates. It is the wrong strategy. Without boldly speaking about our goals, even when we know we will fall short, we cannot imagine the big picture that we intend to paint, the new integrated mythology we intend to write

From Few to Many: Using Copulas and Monte Carlo Simulation to Estimate Safety Consequences

With the introduction of more advanced vehicle technology, it is paramount to assess its safety benefit. Advanced driver assistance systems (ADAS) can reduce crashes and mitigate crash severity, if designed appropriately. Driver behavior models are integral to the ADAS design process, complementing time and resource intensive human participant experiments. We introduce a method to model driver responses to forward collision events by quantifying multivariate behavior with copulas and Monte Carlo simulation. This approach capitalizes on the data from small samples of crash events observed in naturalistic or simulator studies. Copulas summarize data by capturing the underlying joint distribution of variables, and Monte Carlo methods can be used to repeatedly sample from these distributions. A driver model can be parameterized with these samples, and run on a desktop driving simulation environment

Solvent Exfoliation of Electronic-Grade, Two-Dimensional Black Phosphorus

Solution dispersions of two-dimensional (2D) black phosphorus (BP), often referred to as phosphorene, are achieved by solvent exfoliation. These pristine, electronic-grade BP dispersions are produced with anhydrous, organic solvents in a sealed tip ultrasonication system, which circumvents BP degradation that would otherwise occur via solvated oxygen or water. Among conventional solvents, n-methyl-pyrrolidone (NMP) is found to provide stable, highly concentrated (~0.4 mg/mL) BP dispersions. Atomic force microscopy, scanning electron microscopy, transmission electron microscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy show that the structure and chemistry of solvent-exfoliated BP nanosheets are comparable to mechanically exfoliated BP flakes. Additionally, residual NMP from the liquid-phase processing suppresses the rate of BP oxidation in ambient conditions. Solvent-exfoliated BP nanosheet field-effect transistors (FETs) exhibit ambipolar behavior with current on/off ratios and mobilities up to ~10000 and ~50 cm^2/(V*s), respectively. Overall, this study shows that stable, highly concentrated, electronic-grade 2D BP dispersions can be realized by scalable solvent exfoliation, thereby presenting opportunities for large-area, high-performance BP device applications.Comment: 6 figures, 31 pages, including supporting informatio

Numerical Simulation of the Trapping Reaction with Mobile and Reacting Traps

We study a variation of the trapping reaction, A+B→A, in which both the traps (A) and the particles (B) undergo diffusion, and the traps upon meeting react according to A+A→0 or A. This two-species reaction-diffusion system is known to exhibit a nontrivial decay exponent for the B particles, and recently renormalization group methods have predicted an anomalous dimension in the BB correlation function. To test these predictions, we develop a computer simulation method, motivated by the technique of Mehra and Grassberger [Phys. Rev. E 65, 050101(R) (2002)], that determines the complete probability distribution of the B particles for a given realization of the A-particle dynamics, thus providing a significant increase in the quality of statistics. Our numerical results indeed reveal the anomalous dimension predicted by the renormalization group, and compare well quantitatively to precisely known values in cases where the problem can be related to a four-walker problem

Did You See That? A Study of Change Blindness

OBJECTIVES Increasing concern has been expressed regarding the safety implications of drivers attempting to use in-vehicle devices other than cellular phones while driving. To address this issue, the effect of cognitive load on visual attention merits investigation. Strayer and Johnston (2001) found invehicle system use, specifically cell-phone use, disrupts performance by diverting attention to an engaging cognitive context other than the one immediately associated with driving. Recarte and Nunes (2000) demonstrated that scanning patterns and visual attention can be disrupted by cognitive load. In-vehicle systems can increase the cognitive load of the driver, making it more difficult for the driver to direct attention to the visual scene. The change blindness phenomenon may be useful way to investigate how cognitive load affects attention. Change blindness is the inability to detect scene change when the change occurs in conjunction with an action such as a blink (O’Regan, Deubel, Clark, and Rensink, 2000), eye movement (Wallis and Bulthoff, 2000), or an image that masks the onset of the change (Simons and Levin, 1998). The aim of this experiment was to study the effect of cognitive loading on individuals’ ability to detect change in their visual environment using a speech-based email task. METHODS Twenty participants completed a series of five conditions. In two of these conditions the participants did just one task: either the e-mail task or the visual search task. In the other three conditions participants completed the e-mail and the visual search tasks concurrently. In one email task condition the speech recognition system worked perfectly. In a second condition, speech recognition errors caused the wrong menu item to be selected. In a third condition, speech recognition errors caused the user to be displaced to the wrong menu. In three of the visual search task conditions participants were asked to identify changes that occurred in visual scenes, using the Rensink, et al. (1997) flicker paradigm while navigating a speech-based e-mail system. The visual task presented a series of four displays. These were: an unaltered image (300ms), a gray screen (1150ms), a second image (300ms), and a gray screen (1150ms). The second image was either the unaltered image or an image altered by the addition or removal of an element. The remaining conditions for both the e-mail task and visual search task were labeled as baseline. The baseline measurements were used to evaluate the effects of cognitive load on detection of scene changes. RESULTS Analyses showed that detection of scene changes took significantly longer when participants were cognitively loaded with the e-mail task (mean 5.05) compared to when they were not (mean 4.35), F(3,67)=11.13, p< 0.0001. Analyses also showed participants took significantly longer to determine that the scene had not changed (mean 5.99) than to detect a change had occurred (mean 3.72), F(2,67)=271.95, p <0.0001. Scene detection accuracy was significantly reduced when participants were cognitively loaded with the e-mail task, F(3,67)=5.47, p0.0010. Speech recognition errors introduced by the researcher had little effect on times to determine scene changes as well as time to detect meaningful and non-meaningful scene changes. CONCLUSION The results of this study demonstrate that change detection is sensitive to cognitive load and that endogenous control of visual attention may have been affected by the introduction of the e-mail system. It also shows that the paradigm of scenes with and without changes seems to be a promising and sensitive tool for measuring the effects of cognitive load on an individual’s ability to detect change. REFERENCES O\u27Regan, J.K., H. Deubel, J.J. Clark, & R.A. Rensink. (2000). Picture changes during blinks: Looking without seeing and seeing without looking. Visual Cognition 7(1-3), 191-211. Recarte, M.A. & Nunes, L.M. (2000). Effects of verbal and spatial imagery tasks to eye fixations while driving. Journal of Experimental Psychology: Applied,6, 31-43 Rensink, R.A., Oregan, J.K., & Clark, J.J. (1997). To see or not see: The need for attention to perceive changes in scenes. Psychological Sciences, 8, 368-373 Simons, D.J. and D.T. Levin. (1998). Failure to detect changes to people during a real-world interaction. Psychonomic Bulletin & Review 5(4), 644-649. Strayer, D.L. & Johnston, W.A. (2001). Driven to distraction: Dual-task studies of simulated driving and conversing on a cellular phone. Psychological Science, 12, 462-466 Wallis, G. and H. Bulthoff. (2000). What’s scene and not seen: Influences of movement and task upon what we see. Visual Cognition 7(1-3), 175-190

Sleep Profiles of Elite Swimmers During Different Training Phases

This study aims to describe the sleeping patterns during different training phases in competitive swimmers. Twelve national- and international-level swimmers (3 females and 9 males) were monitored during 4 different phases, consisting of a preparation training phase, a taper phase, a competition phase, and a rest phase. Sleep parameters were assessed using wrist activity monitors and self-reported sleep diaries. There was a moderately higher (d = 0.70–1.00) sleep onset latency during the competition phase compared with taper, train, and rest phases. Trivial to small differences were observed for total sleep time between phases (d = 0.05–0.40). Sleep efficiency was moderately higher (d = 0.60–0.75) in the training and taper phases compared with competition and rest. Restfulness and fragmentation index (FI) were lowest in the rest with differences between phases being small (d = 0.43–0.51) for restfulness and small to moderate (d = 0.43–0.62) for FI. Time in and out of bed was very largely later (d = 1.96–2.34) in rest compared with the other phases. Total nap time was moderately lower in rest (d = 1.13–1.18) compared with the training and competition phases, whereas there was a small difference (d = 0.46) compared with taper. To conclude, while there were trivial to small differences in sleep quantity between phases, there are small to moderate differences in other sleep parameters. Specifically, sleep onset latency was higher during the competition phase. In addition, this study highlights the substantial between-individual variations in sleep responses during different training phases