Combined large-N_c and heavy-quark operator analysis for the chiral Lagrangian with charmed baryons

The chiral $SU(3)$ Lagrangian with charmed baryons of spin $J^P=1/2^+$ and $J^P=3/2^+$ is analyzed. We consider all counter terms that are relevant at next-to-next-to-next-to-leading order (N$^3$LO) in a chiral extrapolation of the charmed baryon masses. At N$^2$LO we find 16 low-energy parameters. There are 3 mass parameters for the anti-triplet and the two sextet baryons, 6 parameters describing the meson-baryon vertices and 7 symmetry breaking parameters. The heavy-quark spin symmetry predicts four sum rules for the meson-baryon vertices and degenerate masses for the two baryon sextet fields. Here a large-$N_c$ operator analysis at NLO suggests the relevance of one further spin-symmetry breaking parameter. Going from N$^2$LO to N$^3$LO adds 17 chiral symmetry breaking parameters and 24 symmetry preserving parameters. For the leading symmetry conserving two-body counter terms involving two baryon fields and two Goldstone boson fields we find 36 terms. While the heavy-quark spin symmetry leads to $36-16=20$ sum rules, an expansion in $1/N_c$ at next-to-leading order (NLO) generates $36-7= 29$ parameter relations. A combined expansion leaves 3 unknown parameters only. For the symmetry breaking counter terms we find 17 terms, for which there are $17-9=8$ sum rules from the heavy-quark spin symmetry and $17-5=12$ sum rules from a $1/N_c$ expansion at NLO.Comment: 34 pages - one table - corrections applie

Kernel combination via debiased object correspondence analysis

This paper addresses the problem of combining multi-modal kernels in situations in which object correspondence information is unavailable between modalities, for instance, where missing feature values exist, or when using proprietary databases in multi-modal biometrics. The method thus seeks to recover inter-modality kernel information so as to enable classifiers to be built within a composite embedding space. This is achieved through a principled group-wise identification of objects within differing modal kernel matrices in order to form a composite kernel matrix that retains the full freedom of linear kernel combination existing in multiple kernel learning. The underlying principle is derived from the notion of tomographic reconstruction, which has been applied successfully in conventional pattern recognition. In setting out this method, we aim to improve upon object-correspondence insensitive methods, such as kernel matrix combination via the Cartesian product of object sets to which the method defaults in the case of no discovered pairwise object identifications. We benchmark the method against the augmented kernel method, an order-insensitive approach derived from the direct sum of constituent kernel matrices, and also against straightforward additive kernel combination where the correspondence information is given a priori. We find that the proposed method gives rise to substantial performance improvements

"Context effects in a negative externality experiment"

This study investigates the degree to which framing and context influence observed rates of free-riding behavior in a negative externality laboratory experiment. Building on the work of Andreoni (1995a) and Messer et al. (2007) we frame the decision not to contribute to a public fund as generating a negative externality on other group members. The experimental treatments involving 252 subjects vary communication, voting, and the status quo of the initial endowment. Results indicate that allowing groups the opportunity to communicate and vote significantly reduces rates of free-riding, and this effect is especially pronounced when initial endowments are placed in the private as opposed to the public fund.Negative externality; voluntary contribution mechanism; cheap talk; voting; status quo bias; experimental economics

Quantum secret sharing between m-party and n-party with six states

We propose a quantum secret sharing scheme between $m$-party and $n$-party using three conjugate bases, i.e. six states. A sequence of single photons, each of which is prepared in one of the six states, is used directly to encode classical information in the quantum secret sharing process. In this scheme, each of all $m$ members in group 1 choose randomly their own secret key individually and independently, and then directly encode their respective secret information on the states of single photons via unitary operations, then the last one (the $m$th member of group 1) sends $1/n$ of the resulting qubits to each of group 2. By measuring their respective qubits, all members in group 2 share the secret information shared by all members in group 1. The secret message shared by group 1 and group 2 in such a way that neither subset of each group nor the union of a subset of group 1 and a subset of group 2 can extract the secret message, but each whole group (all the members of each group) can. The scheme is asymptotically 100% in efficiency. It makes the Trojan horse attack with a multi-photon signal, the fake-signal attack with EPR pairs, the attack with single photons, and the attack with invisible photons to be nullification. We show that it is secure and has an advantage over the one based on two conjugate bases. We also give the upper bounds of the average success probabilities for dishonest agent eavesdropping encryption using the fake-signal attack with any two-particle entangled states. This protocol is feasible with present-day technique.Comment: 7 page

A novel approach to modelling and simulating the contact behaviour between a human hand model and a deformable object

A deeper understanding of biomechanical behaviour of human hands becomes fundamental for any human hand-operated Q2 activities. The integration of biomechanical knowledge of human hands into product design process starts to play an increasingly important role in developing an ergonomic product-to-user interface for products and systems requiring high level of comfortable and responsive interactions. Generation of such precise and dynamic models can provide scientific evaluation tools to support product and system development through simulation. This type of support is urgently required in many applications such as hand skill training for surgical operations, ergonomic study of a product or system developed and so forth. The aim of this work is to study the contact behaviour between the operators’ hand and a hand-held tool or other similar contacts, by developing a novel and precise nonlinear 3D finite element model of the hand and by investigating the contact behaviour through simulation. The contact behaviour is externalised by solving the problem using the bi-potential method. The human body’s biomechanical characteristics, such as hand deformity and structural behaviour, have been fully modelled by implementing anisotropic hyperelastic laws. A case study is given to illustrate the effectiveness of the approac