Ab-initio angle and energy resolved photoelectron spectroscopy with time-dependent density-functional theory

We present a time-dependent density-functional method able to describe the photoelectron spectrum of atoms and molecules when excited by laser pulses. This computationally feasible scheme is based on a geometrical partitioning that efficiently gives access to photoelectron spectroscopy in time-dependent density-functional calculations. By using a geometrical approach, we provide a simple description of momentum-resolved photoe- mission including multi-photon effects. The approach is validated by comparison with results in the literature and exact calculations. Furthermore, we present numerical photoelectron angular distributions for randomly oriented nitrogen molecules in a short near infrared intense laser pulse and helium-(I) angular spectra for aligned carbon monoxide and benzene.Comment: Accepted for publication on Phys. Rev.

On a generalized gravitational Aharonov-Bohm effect

A massless spinor particle is considered in the background gravitational field due to a rotating body. In the weak field approximation it is shown that the solution of the Weyl equations depend on the angular momentum of the rotating body, which does not affect the curvature in this approximation. This result may be looked upon as a generalization of the gravitational Aharonov-Bohm effect.Comment: 10 pages, LATEX fil

Antibonding Ground state of Adatom Molecules in Bulk Dirac Semimetals

The ground state of the diatomic molecules in nature is inevitably bonding, and its first excited state is antibonding. We demonstrate theoretically that, for a pair of distant adatoms placed buried in three-dimensional-Dirac semimetals, this natural order of the states can be reversed and an antibonding ground state occurs at the lowest energy of the so-called bound states in the continuum. We propose an experimental protocol with the use of a scanning tunneling microscope tip to visualize the topographic map of the local density of states on the surface of the system to reveal the emerging physics

Distribution-Based Categorization of Classifier Transfer Learning

Transfer Learning (TL) aims to transfer knowledge acquired in one problem, the source problem, onto another problem, the target problem, dispensing with the bottom-up construction of the target model. Due to its relevance, TL has gained significant interest in the Machine Learning community since it paves the way to devise intelligent learning models that can easily be tailored to many different applications. As it is natural in a fast evolving area, a wide variety of TL methods, settings and nomenclature have been proposed so far. However, a wide range of works have been reporting different names for the same concepts. This concept and terminology mixture contribute however to obscure the TL field, hindering its proper consideration. In this paper we present a review of the literature on the majority of classification TL methods, and also a distribution-based categorization of TL with a common nomenclature suitable to classification problems. Under this perspective three main TL categories are presented, discussed and illustrated with examples

Efeito do detergente neutro na mortalidade de ninfas da bemisia tabaci biótipo b no feijoeiro comum.

Tendo em vista os riscos que envolvem o uso de inseticidas convencionais, principalmente aqueles associados à saúde do homem, a organismos benéficos, à poluição do ambiente e a seleção de resistência às formulações sintéticas por parte da mosca-branca, o presente trabalho teve como objetivo avaliar o efeito do detergente neutro na mortalidade de ninfas do 2º ínstar da B. tabaci biótipo B e de ninfas em desenvolvimento até o 4º ínstar no feijoeiro comum.CONAFE

Efeito de óleos vegetais e mineral sobre ovos da mosca-branca Bemisia tabaci biótipo B.

Este trabalho teve como objetivo avaliar o efeito de óleos vegetais e mineral sobre ovos de Bemisia tabaci biótipo B no feijoeiro comum Phaseolus vulgaris.Conpeex 2010