A systematic comparison of supervised classifiers

Pattern recognition techniques have been employed in a myriad of industrial, medical, commercial and academic applications. To tackle such a diversity of data, many techniques have been devised. However, despite the long tradition of pattern recognition research, there is no technique that yields the best classification in all scenarios. Therefore, the consideration of as many as possible techniques presents itself as an fundamental practice in applications aiming at high accuracy. Typical works comparing methods either emphasize the performance of a given algorithm in validation tests or systematically compare various algorithms, assuming that the practical use of these methods is done by experts. In many occasions, however, researchers have to deal with their practical classification tasks without an in-depth knowledge about the underlying mechanisms behind parameters. Actually, the adequate choice of classifiers and parameters alike in such practical circumstances constitutes a long-standing problem and is the subject of the current paper. We carried out a study on the performance of nine well-known classifiers implemented by the Weka framework and compared the dependence of the accuracy with their configuration parameter configurations. The analysis of performance with default parameters revealed that the k-nearest neighbors method exceeds by a large margin the other methods when high dimensional datasets are considered. When other configuration of parameters were allowed, we found that it is possible to improve the quality of SVM in more than 20% even if parameters are set randomly. Taken together, the investigation conducted in this paper suggests that, apart from the SVM implementation, Weka's default configuration of parameters provides an performance close the one achieved with the optimal configuration

Embryonic and foetal mortality in buffalo species.

The aim of this study was to verify the incidence of late embryonic mortality (between 25 and 45 days post-insemination; LEM) and foetal mortality (between 45 and 70 days postinsemination; FM) in buffaloes synchronized and mated by AI during the transitional period. The trial was performed on 288 multiparous Mediterranean Buffaloes, synchronized and inseminated by AI. Trans-rectal ultrasonography was performed 25, 45, and 70 days post-insemination to assess embryonic development. Milk samples were collected on Days 10, 20, 25, 30, and 45 post-insemination to determine progesterone concentration in whey. Pregnancy rate on Day 25 after AI was 48.6% but declined to 35.4% and to 30.6% by Day 45 and 70 respectively, representing a LEM of 27.1% and a FM of 13.7%. Progesterone concentration was higher (P<0.01) in pregnant compared to LEM buffaloes after 20 days post-insemination. Differences (P<0.05) were found between FM and LEM buffaloes on Days 25 and 30. Furthermore, progesterone concentration in pregnant buffaloes was higher (P=0.09) than that of FM buffaloes on Day 30 and 45. In conclusion, the success of application of reproductive biotechnologies in the transitional period depends from the incidence of embryonic and foetal mortality

Resolving the nature of electronic excitations in resonant inelastic x-ray scattering

The study of elementary bosonic excitations is essential toward a complete description of quantum electronic solids. In this context, resonant inelastic X-ray scattering (RIXS) has recently risen to becoming a versatile probe of electronic excitations in strongly correlated electron systems. The nature of the radiation-matter interaction endows RIXS with the ability to resolve the charge, spin and orbital nature of individual excitations. However, this capability has been only marginally explored to date. Here, we demonstrate a systematic method for the extraction of the character of excitations as imprinted in the azimuthal dependence of the RIXS signal. Using this novel approach, we resolve the charge, spin, and orbital nature of elastic scattering, (para-)magnon/bimagnon modes, and higher energy dd excitations in magnetically-ordered and superconducting copper-oxide perovskites (Nd2CuO4 and YBa2Cu3O6.75). Our method derives from a direct application of scattering theory, enabling us to deconstruct the complex scattering tensor as a function of energy loss. In particular, we use the characteristic tensorial nature of each excitation to precisely and reliably disentangle the charge and spin contributions to the low energy RIXS spectrum. This procedure enables to separately track the evolution of spin and charge spectral distributions in cuprates with doping. Our results demonstrate a new capability that can be integrated into the RIXS toolset, and that promises to be widely applicable to materials with intertwined spin, orbital, and charge excitations

Na2IrO3 as a spin-orbit-assisted antiferromagnetic insulator with a 340 meV gap

We study Na2IrO3 by ARPES, optics, and band structure calculations in the local-density approximation (LDA). The weak dispersion of the Ir 5d-t2g manifold highlights the importance of structural distortions and spin-orbit coupling (SO) in driving the system closer to a Mott transition. We detect an insulating gap {\Delta}_gap = 340 meV which, at variance with a Slater-type description, is already open at 300 K and does not show significant temperature dependence even across T_N ~ 15 K. An LDA analysis with the inclusion of SO and Coulomb repulsion U reveals that, while the prodromes of an underlying insulating state are already found in LDA+SO, the correct gap magnitude can only be reproduced by LDA+SO+U, with U = 3 eV. This establishes Na2IrO3 as a novel type of Mott-like correlated insulator in which Coulomb and relativistic effects have to be treated on an equal footing.Comment: Accepted in Physical Review Letters. Auxiliary and related material can be found at: http://www.phas.ubc.ca/~quantmat/ARPES/PUBLICATIONS/articles.htm

The symmetry of charge order in cuprates

Charge-ordered ground states permeate the phenomenology of 3d-based transition metal oxides, and more generally represent a distinctive hallmark of strongly-correlated states of matter. The recent discovery of charge order in various cuprate families fueled new interest into the role played by this incipient broken symmetry within the complex phase diagram of high-Tc superconductors. Here we use resonant X-ray scattering to resolve the main characteristics of the charge-modulated state in two cuprate families: Bi2201 and YBCO. We detect no signatures of spatial modulations along the nodal direction in Bi2201, thus clarifying the inter-unit-cell momentum-structure of charge order. We also resolve the intra-unit-cell symmetry of the charge ordered state, which is revealed to be best represented by a bond-order with modulated charges on the O-2p orbitals and a prominent d-wave character. These results provide insights on the microscopic description of charge order in cuprates, and on its origin and interplay with superconductivity.Comment: A high-resolution version with supplementary material can be found at: http://www.phas.ubc.ca/~quantmat/ARPES/PUBLICATIONS/Articles/CDW_symmetry.pd

Rashba spin-splitting control at the surface of the topological insulator Bi2Se3

The electronic structure of Bi2Se3 is studied by angle-resolved photoemission and density functional theory. We show that the instability of the surface electronic properties, observed even in ultra-high-vacuum conditions, can be overcome via in-situ potassium deposition. In addition to accurately setting the carrier concentration, new Rashba-like spin-polarized states are induced, with a tunable, reversible, and highly stable spin splitting. Ab-initio slab calculations reveal that these Rashba state are derived from the 5QL quantum-well states. While the K-induced potential gradient enhances the spin splitting, this might be already present for pristine surfaces due to the symmetry breaking of the vacuum-solid interface.Comment: A high-resolution version can be found at http://www.physics.ubc.ca/~quantmat/ARPES/PUBLICATIONS/Articles/BiSe_K.pd

Correlations between climate network and relief data

Peer reviewedPublisher PD