Marmots do not consistently use their left eye to respond to an approaching threat but those that did fled sooner.

In many vertebrates, the brain's right hemisphere which is connected to the left visual field specializes in the processing of information about threats while the left hemisphere which is connected to the right visual field specializes in the processing of information about conspecifics. This is referred to as hemispheric lateralization. But individuals that are too predictable in their response to predators could have reduced survival and we may expect selection for somewhat unpredictable responses. We studied hemispheric lateralization in yellow-bellied marmots Marmota flaviventer, a social rodent that falls prey to a variety of terrestrial and aerial predators. We first asked if they have lateralized responses to a predatory threat. We then asked if the eye that they used to assess risk influenced their perceptions of risk. We recorded the direction marmots were initially looking and then walked toward them until they fled. We recorded the distance that they responded to our experimental approach by looking, the eye with which they looked at us, and the distance at which they fled (i.e., flight initiation distance; FID). We found that marmots had no eye preference with which they looked at an approaching threat. Furthermore, the population was not comprised of individuals that responded in consistent ways. However, we found that marmots that looked at the approaching person with their left eye had larger FIDs suggesting that risk assessment was influenced by the eye used to monitor the threat. These findings are consistent with selection to make prey less predictable for their predators, despite underlying lateralization

Flavor-Safe Light Squarks in Higgs-Anomaly Mediation

We consider a simple setup with light squarks which is free from the gravitino and SUSY flavor problems. In our setup, a SUSY breaking sector is sequestered from the matter and gauge sectors, and it only couples to the Higgs sector directly with $\mathcal{O}(100)\,$TeV gravitino. Resulting mass spectra of sfermions are split: the first and second generation sfermions are light as $\mathcal{O}(1)\,$TeV while the third generation sfermions are heavy as $\mathcal{O}(10)\,$TeV. The light squarks of $\mathcal{O}(1)\,$TeV can be searched at the (high-luminosity) LHC and future collider experiments. Our scenario can naturally avoid too large flavor-changing neutral currents and it is consistent with the $\epsilon_K$ constraint. Moreover, there are regions explaining the muon $g-2$ anomaly and bottom-tau/top-bottom-tau Yukawa coupling unification simultaneously.Comment: 19 pages, 12 figures, v2: footnotes and references added, typos collected, to appear in JHE

ARE BASIC SCIENCE AND BIOTECHNOLOGY COMPLEMENTARY ACTIVITIES?

Enhancing agricultural productivity depends greatly on the management of information flows between basic and applied research. A framework is developed to examine the mutual relationship between molecular biological research and agricultural biotechnology innovations. Preliminary results provide a basis for university decision-making in both the short and long run.Research and Development/Tech Change/Emerging Technologies,

Heavy Quarkonium Dissociation Cross Sections in Relativistic Heavy-Ion Collisions

Many of the hadron-hadron cross sections required for the study of the dynamics of matter produced in relativistic heavy-ion collisions can be calculated using the quark-interchange model. Here we evaluate the low-energy dissociation cross sections of $J/\psi$, $\psi'$, $\chi$, $\Upsilon$, and $\Upsilon'$ in collision with $\pi$, $\rho$, and $K$, which are important for the interpretation of heavy-quarkonium suppression as a signature for the quark gluon plasma. These comover dissociation processes also contribute to heavy-quarkonium suppression, and must be understood and incorporated in simulations of heavy-ion collisions before QGP formation can be established through this signature.Comment: 38 pages, in LaTe

Adaptive confidence intervals for regression functions under shape constraints

Adaptive confidence intervals for regression functions are constructed under shape constraints of monotonicity and convexity. A natural benchmark is established for the minimum expected length of confidence intervals at a given function in terms of an analytic quantity, the local modulus of continuity. This bound depends not only on the function but also the assumed function class. These benchmarks show that the constructed confidence intervals have near minimum expected length for each individual function, while maintaining a given coverage probability for functions within the class. Such adaptivity is much stronger than adaptive minimaxity over a collection of large parameter spaces.Comment: Published in at http://dx.doi.org/10.1214/12-AOS1068 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org