Fermi Surface of KFe2_2As2_2 from Quantum Oscillations in Magnetostriction

We present a study of the Fermi surface of KFe$_2$As$_2$ single crystals. Quantum oscillations were observed in magnetostriction measured down to 50 mK and in magnetic fields $H$ up to 14 T. For $H \parallel c$, the calculated effective masses are in agreement with recent de Haas-van Alphen and ARPES experiments, showing enhanced values with respect to the ones obtained from previous band calculations. For $H \parallel a$, we observed a small orbit at a cyclotron frequency of 64 T, characterized by an effective mass of $\sim 0.8 m_e$, supporting the presence of a three-dimensional pocket at the Z-point.Comment: SCES Conference, Tokyo 201

Lack of coupling between superconductivity and orthorhombic distortion in stoichiometric single-crystalline FeSe

The coupling between superconductivity and othorhombic distortion is studied in vapor-grown FeSe single crystals using high-resolution thermal-expansion measurements. In contrast to the Ba122-based (Ba122) superconductors, we find that superconductivity does not reduce the orthorhombicity below Tc. Instead we find that superconductivity couples strongly to the in-plane area, which explains the large hydrostatic pressure effects. We discuss our results in light of the spinnematic scenario and argue that FeSe has many features quite different from the typical Fe-based superconductors

Disordered Topological Insulators via C∗C^*-Algebras

The theory of almost commuting matrices can be used to quantify topological obstructions to the existence of localized Wannier functions with time-reversal symmetry in systems with time-reversal symmetry and strong spin-orbit coupling. We present a numerical procedure that calculates a Z_2 invariant using these techniques, and apply it to a model of HgTe. This numerical procedure allows us to access sizes significantly larger than procedures based on studying twisted boundary conditions. Our numerical results indicate the existence of a metallic phase in the presence of scattering between up and down spin components, while there is a sharp transition when the system decouples into two copies of the quantum Hall effect. In addition to the Z_2 invariant calculation in the case when up and down components are coupled, we also present a simple method of evaluating the integer invariant in the quantum Hall case where they are decoupled.Comment: Added detail regarding the mapping of almost commuting unitary matrices to almost commuting Hermitian matrices that form an approximate representation of the sphere. 6 pages, 6 figure

Classification of graph C*-algebras with no more than four primitive ideals

We describe the status quo of the classification problem of graph C*-algebras with four primitive ideals or less

Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors

Selection of tuning parameters in bridge regression models via Bayesian information criterion

We consider the bridge linear regression modeling, which can produce a sparse or non-sparse model. A crucial point in the model building process is the selection of adjusted parameters including a regularization parameter and a tuning parameter in bridge regression models. The choice of the adjusted parameters can be viewed as a model selection and evaluation problem. We propose a model selection criterion for evaluating bridge regression models in terms of Bayesian approach. This selection criterion enables us to select the adjusted parameters objectively. We investigate the effectiveness of our proposed modeling strategy through some numerical examples.Comment: 20 pages, 5 figure

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine: Brussels, Belgium. 15-18 March 2016.

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Biogenesis of mitochondrial porin

We review here the present knowledge about the pathway of import and assembly of porin into mitochondria and compare it to those of other mitochondrial proteins. Porin, like all outer mitochondrial membrane proteins studied so far is made as a precursor without a cleavble lsquosignalrsquo sequence; thus targeting information must reside in the mature sequence. At least part of this information appears to be located at the amino-terminal end of the molecule. Transport into mitochondria can occur post-translationally. In a first step, the porin precursor is specifically recognized on the mitochondrial surface by a protease sensitive receptor. In a second step, porin precursor inserts partially into the outer membrane. This step is mediated by a component of the import machinery common to the import pathways of precursor proteins destined for other mitochondrial subcompartments. Finally, porin is assembled to produce the functional oligomeric form of an integral membrane protein wich is characterized by its extreme protease resistance