Effective free energy for pinned membranes

We consider membranes adhered through specific receptor-ligand bonds. Thermal undulations of the membrane induce effective interactions between adhesion sites. We derive an upper bound to the free energy that is independent of interaction details. To lowest order in a systematic expansion we obtain two-body interactions which allow to map the free energy onto a lattice gas with constant density. The induced interactions alone are not strong enough to lead to a condensation of individual adhesion sites. A measure of the thermal roughness is shown to depend on the inverse square root of the density of adhesion sites, which is in good agreement with previous computer simulations.Comment: to appear as a Rapid Communication in Phys. Rev.

Can wearable haptic devices foster the embodiment of virtual limbs?

Increasing presence is one of the primary goals of virtual reality research. A crucial aspect is that users are capable of distinguishing their self from the external virtual world. The hypothesis we investigate is that wearable haptics play an important role in the body experience and could thereby contribute to the immersion of the user in the virtual environment. A within-subject study (n=32) comparing the embodiment of a virtual hand with different implementations of haptic feedback (force feedback, vibrotactile feedback, and no haptic feedback) is presented. Participants wore a glove with haptic feedback devices at thumb and index finger. They were asked to put virtual cubes on a moving virtual target. Touching a virtual object caused vibrotactile-feedback, force-feedback or no feedback depending on the condition. These conditions were provided both synchronously and asynchronously. Embodiment was assessed quantitatively with the proprioceptive drift and subjectively via a questionnaire. Results show that haptic feedback significantly improves the subjective embodiment of a virtual hand and that force feedback leads to stronger responses to certain subscales of subjective embodiment. These outcomes are useful guidelines for wearable haptic designer and represent a basis for further research concerning human body experience, in reality, and in virtual environments

Chemical Reaction Dynamics at Surfaces

Contains reports on four research projects.National Science Foundation (Grant DMR81-19292)National Science Foundation (Grant CHE82-06422)Research CorporationCamille and Henry Dreyfus FoundationMonsant

Evidence for Different Freeze-Out Radii of High- and Low-Energy Pions Emitted in Au+Au Collisions at 1 GeV/nucleon

Double differential production cross sections of negative and positive pions and the number of participating protons have been measured in central Au+Au collisions at 1 GeV per nucleon incident energy. At low pion energies the pi^- yield is strongly enhanced over the pi^+ yield. The energy dependence of the pi^-/pi^+ ratio is assigned to the Coulomb interaction of the charged pions with the protons in the reaction zone. The deduced Coulomb potential increases with increasing pion c.m. energy. This behavior indicates different freeze-out radii for different pion energies in the c.m.~frame.Comment: IKDA is the Institute for Nuclear Physics in Darmstadt/German

Enhanced Out-of-plane Emission of K+ Mesons observed in Au+Au Collisions at 1 AGeV

The azimuthal angular distribution of K+ mesons has been measured in Au + Au collisions at 1 AGeV. In peripheral and semi-central collisions, K+ mesons preferentially are emitted perpendicular to the reaction plane. The strength of the azimuthal anisotropy of K+ emission is comparable to the one of pions. No in-plane flow was found for K+ mesons near projectile and target rapidity.Comment: Accepted for publication in Phys. Rev.Let

Chemical Reaction Dynamics at Surfaces

Contains reports on three research projects.Joint Services Electronics Program (Contract DAAL03-86-K-0002)Joint Services Electronics Program (Contract DAAL03-89-C-0001)National Science Foundation (Grant CHE 85-08734)MIT Energy Laboratory - Synthetic Fuels CenterPetroleum Research Fund (Contract 19014-AC5

Supervillin modulation of focal adhesions involving TRIP6/ZRP-1

Cell–substrate contacts, called focal adhesions (FAs), are dynamic in rapidly moving cells. We show that supervillin (SV)—a peripheral membrane protein that binds myosin II and F-actin in such cells—negatively regulates stress fibers, FAs, and cell–substrate adhesion. The major FA regulatory sequence within SV (SV342-571) binds to the LIM domains of two proteins in the zyxin family, thyroid receptor–interacting protein 6 (TRIP6) and lipoma-preferred partner (LPP), but not to zyxin itself. SV and TRIP6 colocalize within large FAs, where TRIP6 may help recruit SV. RNAi-mediated decreases in either protein increase cell adhesion to fibronectin. TRIP6 partially rescues SV effects on stress fibers and FAs, apparently by mislocating SV away from FAs. Thus, SV interactions with TRIP6 at FAs promote loss of FA structure and function. SV and TRIP6 binding partners suggest several specific mechanisms through which the SV–TRIP6 interaction may regulate FA maturation and/or disassembly

Learning Interpretable Rules for Multi-label Classification

Multi-label classification (MLC) is a supervised learning problem in which, contrary to standard multiclass classification, an instance can be associated with several class labels simultaneously. In this chapter, we advocate a rule-based approach to multi-label classification. Rule learning algorithms are often employed when one is not only interested in accurate predictions, but also requires an interpretable theory that can be understood, analyzed, and qualitatively evaluated by domain experts. Ideally, by revealing patterns and regularities contained in the data, a rule-based theory yields new insights in the application domain. Recently, several authors have started to investigate how rule-based models can be used for modeling multi-label data. Discussing this task in detail, we highlight some of the problems that make rule learning considerably more challenging for MLC than for conventional classification. While mainly focusing on our own previous work, we also provide a short overview of related work in this area.Comment: Preprint version. To appear in: Explainable and Interpretable Models in Computer Vision and Machine Learning. The Springer Series on Challenges in Machine Learning. Springer (2018). See http://www.ke.tu-darmstadt.de/bibtex/publications/show/3077 for further informatio

Chemical Reaction Dynamics at Surfaces

Contains reports on four research projects.Center for Materials Science and EngineeringCamille and Henry Dreyfus FoundationNational Science Foundation (Grant CHE82-06422)Research CorporationNational Science Foundation (CHE85-08734)Synthetic Fuels Center of the Energy Laboratory at M.I.T.Center for Materials Science and EngineeringMonsant