Affordances and Feedback in Nuance-Oriented Interfaces

Virtual Environments (VEs) and perceptive user interfaces must deal with complex users and their modes of interaction. One way to approach this problem is to recognize users’ nuances (subtle conscious or unconscious actions). In exploring nuance-oriented interfaces, we attempted to let users work as they preferred without being biased by feedback or affordances in the system. The hope was that we would discover the users’ innate models of interaction. The results of two user studies were that users are guided not by any innate model but by affordances and feedback in the interface. So, without this guidance, even the most obvious and useful components of an interface will be ignored

A First Step Towards Nuance-Oriented Interfaces for Virtual Environments

Designing usable interfaces for virtual environments (VEs) is not a trivial task. Much of the difficulty stems from the complexity and volume of the input data. Many VEs, in the creation of their interfaces, ignore much of the input data as a result of this. Using machine learning (ML), we introduce the notion of a nuance that can be used to increase the precision and power of a VE interface. An experiment verifying the existence of nuances using a neural network (NN) is discussed and a listing of guidelines to follow is given. We also review reasons why traditional ML techniques are difficult to apply to this problem

Crystal growth and ambient and high pressure study of the reentrant superconductor Tm_2Fe_3Si_5

We report single crystal growth of the reentrant superconductor Tm_2Fe_3Si_5, and measurements of the anisotropic static magnetic susceptibility \chi(T) and isothermal magnetization M(H), ac susceptibility \chi_ac(T), electrical resistivity \rho(T) and heat capacity C(T) at ambient pressure and \chi_ac(T) at high pressure. The magnetic susceptibility along the c-axis \chi_c(T) shows a small maximum around 250 K and does not follow the Curie-Weiss behavior while the magnetic susceptibility along the a-axis \chi_a(T) follows a Curie-Weiss behavior between 130 K and 300 K with a Weiss temperature \theta and an effective magnetic moment \mu_eff which depend on the temperature range of the fit. The easy axis of magnetization is perpendicular to the c-axis and \chi_a/\chi_c = 3.2 at 1.8 K. The ambient pressure \chi_ac(T) and C(T) measurements confirm bulk antiferromagnetic ordering at T_N = 1.1 K. The sharp drop in \chi_ac below T_N is suggestive of the existence of a spin-gap. We observe superconductivity only under applied pressures P\geq 2 kbar. The temperature-pressure phase diagram showing the non-monotonic dependence of the superconducting transition temperature T_c on pressure P is presented.Comment: 7 pages, 8 figure

Canonical representation for electrons and its application to the Hubbard model

A new representation for electrons is introduced, in which the electron operators are written in terms of a spinless fermion and the Pauli operators. This representation is canonical, invertible and constraint-free. Importantly, it simplifies the Hubbard interaction. On a bipartite lattice, the Hubbard model is reduced to a form in which the exchange interaction emerges simply by decoupling the Pauli subsystem from the spinless fermion bath. This exchange correctly reproduces the large $U$ superexchange. Also derived, for $U=\pm\infty$, is the Hamiltonian to study Nagaoka ferromagnetism. In this representation, the infinite-$U$ Hubbard problem becomes elegant and easier to handle. Interestingly, the ferromagnetism in Hubbard model is found to be related to the gauge invariance of the spinless fermions. Generalization of this representation for the multicomponent fermions, a new representation for bosons, the notion of a `soft-core' fermion, and some interesting unitary transformations are introduced and discussed in the appendices.Comment: 10+ pages, 3 Figure

Consideraciones en torno al problema de la fe y la razón en la obra literaria de Ramon Llull

Backbone mimicry by the formation of closed-loop $C_7,C_{10}$ and $C_{13}$ (mimics of $\gamma-, \beta-$ and $\alpha$-turns) conformations through side chain–main chain hydrogen bonds by polar groups is a frequent observation in protein structures. A data set of 250 non-homologous and high-resolution protein crystal structures was used to analyze these conformations for their characteristic features. Seven out of the nine polar residues (Ser, Thr, Asn, Asp, Gln, Glu and His) have hydrogen bonding groups in their side chains which can participate in such mimicry and as many as 15% of all these polar residues engage in such conformations. The distributions of dihedral angles of these mimics indicate that only certain combinations of the dihedral angles involved aid the formation of these mimics. The observed examples were categorized into various classes based on these combinations, resulting in well defined motifs. Asn and Asp residues show a very high capability to perform such backbone secondary structural mimicry. The most highly mimicked backbone structure is of the$C_{10}$ conformation by the Asx residues. The mimics formed by His, Ser, Thr and Glx residues are also discussed. The role of such conformations in initiating the formation of regular secondary structures during the course of protein folding seems significant