Magentic-Field Induced Quantum Phase Transition and Critical Behavior in a Gapped Spin System TlCuCl3_3

Magnetization measurements were performed on TlCuCl$_3$ with gapped ground state. The critical density and the magnetic phase diagram were obtained. The interacting constant was obtained as $U/k_{\rm B} = 313$ K. The experimental phase boundary for $T < 5$ K agrees perfectly with the magnon BEC theory based on the Hartree-Fock approximation with realistic dispersion relations and $U/k_{\rm B} = 320$ K. The exponent $\phi$ obtained with all the data points for $T < 5$ K is $\phi = 1.99$, which is somewhat larger than theoretical exponent $\phi_{\rm BEC} =3/2$. However, it was found that the exponent converges at $\phi_{\rm BEC} =3/2$ with decreasing fitting window.Comment: 2 pages, 2 figures, Submitted to Proceedings of International Conference on Magnetism (ICM2006

Learning cover context-free grammars from structural data

We consider the problem of learning an unknown context-free grammar when the only knowledge available and of interest to the learner is about its structural descriptions with depth at most $\ell.$ The goal is to learn a cover context-free grammar (CCFG) with respect to $\ell$, that is, a CFG whose structural descriptions with depth at most $\ell$ agree with those of the unknown CFG. We propose an algorithm, called $LA^\ell$, that efficiently learns a CCFG using two types of queries: structural equivalence and structural membership. We show that $LA^\ell$ runs in time polynomial in the number of states of a minimal deterministic finite cover tree automaton (DCTA) with respect to $\ell$. This number is often much smaller than the number of states of a minimum deterministic finite tree automaton for the structural descriptions of the unknown grammar

Mechanisms Underlying Robustness and Tunability in a Plant Immune Signaling Network

SummaryThe plant immune signaling network needs to be robust against attack from fast-evolving pathogens and tunable to optimize immune responses. We investigated the basis of robustness and tunability in the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, phytoalexin-deficient 4, and salicylate sectors, which together govern up to 80% of the PTI levels, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, contributed centrally to network robustness via its inhibition of the jasmonate sector. The model’s multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability

Inducing Probabilistic Grammars by Bayesian Model Merging

We describe a framework for inducing probabilistic grammars from corpora of positive samples. First, samples are {\em incorporated} by adding ad-hoc rules to a working grammar; subsequently, elements of the model (such as states or nonterminals) are {\em merged} to achieve generalization and a more compact representation. The choice of what to merge and when to stop is governed by the Bayesian posterior probability of the grammar given the data, which formalizes a trade-off between a close fit to the data and a default preference for simpler models (`Occam's Razor'). The general scheme is illustrated using three types of probabilistic grammars: Hidden Markov models, class-based $n$-grams, and stochastic context-free grammars.Comment: To appear in Grammatical Inference and Applications, Second International Colloquium on Grammatical Inference; Springer Verlag, 1994. 13 page

Ultralong Copper Phthalocyanine Nanowires with New Crystal Structure and Broad Optical Absorption

The development of molecular nanostructures plays a major role in emerging organic electronic applications, as it leads to improved performance and is compatible with our increasing need for miniaturisation. In particular, nanowires have been obtained from solution or vapour phase and have displayed high conductivity, or large interfacial areas in solar cells. In all cases however, the crystal structure remains as in films or bulk, and the exploitation of wires requires extensive post-growth manipulation as their orientations are random. Here we report copper phthalocyanine (CuPc) nanowires with diameters of 10-100 nm, high directionality and unprecedented aspect ratios. We demonstrate that they adopt a new crystal phase, designated eta-CuPc, where the molecules stack along the long axis. The resulting high electronic overlap along the centimetre length stacks achieved in our wires mediates antiferromagnetic couplings and broadens the optical absorption spectrum. The ability to fabricate ultralong, flexible metal phthalocyanine nanowires opens new possibilities for applications of these simple molecules

An algebraic Birkhoff decomposition for the continuous renormalization group

This paper aims at presenting the first steps towards a formulation of the Exact Renormalization Group Equation in the Hopf algebra setting of Connes and Kreimer. It mostly deals with some algebraic preliminaries allowing to formulate perturbative renormalization within the theory of differential equations. The relation between renormalization, formulated as a change of boundary condition for a differential equation, and an algebraic Birkhoff decomposition for rooted trees is explicited

Automatic eduction and statistical analysis of coherent structures in the wall region of a confine plane

This paper describes a vortex detection algorithm used to expose and statistically characterize the coherent flow patterns observable in the velocity vector fields measured by Particle Image Velocimetry (PIV) in the impingement region of air curtains. The philosophy and the architecture of this algorithm are presented. Its strengths and weaknesses are discussed. The results of a parametrical analysis performed to assess the variability of the response of our algorithm to the 3 user-specified parameters in our eduction scheme are reviewed. The technique is illustrated in the case of a plane turbulent impinging twin-jet with an opening ratio of 10. The corresponding jet Reynolds number, based on the initial mean flow velocity U0 and the jet width e, is 14000. The results of a statistical analysis of the size, shape, spatial distribution and energetic content of the coherent eddy structures detected in the impingement region of this test flow are provided. Although many questions remain open, new insights into the way these structures might form, organize and evolve are given. Relevant results provide an original picture of the plane turbulent impinging jet

Medical Students\u27 Experiences and Outcomes Using a Virtual Human Simulation to Improve Communication Skills: Mixed Methods Study

Background: Attending to the wide range of communication behaviors that convey empathy is an important but often underemphasized concept to reduce errors in care, improve patient satisfaction, and improve cancer patient outcomes. A virtual human (VH)–based simulation, MPathic-VR, was developed to train health care providers in empathic communication with patients and in interprofessional settings and evaluated through a randomized controlled trial. Objective: This mixed methods study aimed to investigate the differential effects of a VH-based simulation developed to train health care providers in empathic patient-provider and interprofessional communication. Methods: We employed a mixed methods intervention design, involving a comparison of 2 quantitative measures—MPathic-VR–calculated scores and the objective structured clinical exam (OSCE) scores—with qualitative reflections by medical students about their experiences. This paper is a secondary, focused analysis of intervention arm data from the larger trial. Students at 3 medical schools in the United States (n=206) received simulation to improve empathic communication skills. We conducted analysis of variance, thematic text analysis, and merging mixed methods analysis. Results: OSCE scores were significantly improved for learners in the intervention group (mean 0.806, SD 0.201) compared with the control group (mean 0.752, SD 0.198; F1,414=6.09; P=.01). Qualitative analysis revealed 3 major positive themes for the MPathic-VR group learners: gaining useful communication skills, learning awareness of nonverbal skills in addition to verbal skills, and feeling motivated to learn more about communication. Finally, the results of the mixed methods analysis indicated that most of the variation between high, middle, and lower performers was noted about nonverbal behaviors. Medium and high OSCE scorers most often commented on the importance of nonverbal communication. Themes of motivation to learn about communication were only present in middle and high scorers. Conclusions: VHs are a promising strategy for improving empathic communication in health care. Higher performers seemed most engaged to learn, particularly nonverbal skills