Still standing, still here, still dancing.

A personal narrative is presented which explores the author's experiences on teaching-learning process and her insights on language, culture and learning

LRR Voices: Health & Safety for Unorganized, Immigrant Workers

Pam Tau Lee is Labor Coordinator at the Labor Occupational Health Program at the University of California, Berkeley, and serves on the boards of the National Toxic Campaign Fund, National People of Color Environmental Summit, and the Chinese Progressive Association, She recently returned from Slovakia where she collaborated with environmentalists and worker representatives in setting up a participatory approach to health and safety research. LRR asked Lee to comment on the crucial role labor can play in the area of health and safety for unorganized, immigrant workers

Role of multi-level states on quantum-dot emission in photonic-crystal cavities

Semiconductor quantum dots embedded in photonic-crystal nanostructures have been the subject of intense study. In this context, quantum dots are often considered to be simple two-level emitters, i.e., the complexities arising from the internal finestructure are neglected. We show that due to the intricate spatial variations of the electric field polarization found in photonic crystal, the two orthogonal finestructure states of quantum dots in general both couple significantly to a cavity mode, implying that the two-level description is not sufficient. As a consequence the emission dynamics and spectra, which are often recorded in experiments, are modified both in the weak- and strong-coupling regimes. The proposed effects are found to be significant for system parameters of current state-of-the-art photonic-crystal cavities

Phase diagram of symmetric binary mixtures at equimolar and non-equimolar concentrations: a systematic investigation

We consider symmetric binary mixtures consisting of spherical particles with equal diameters interacting via a hard-core plus attractive tail potential with strengths epsilon_{ij}, i,j=1,2, such that epsilon_{11} = epsilon_{22} > epsilon_{12}. The phase diagram of the system at all densities and concentrations is investigated as a function of the unlike-to-like interaction ratio delta = epsilon_{12}/epsilon_{11} by means of the hierarchical reference theory (HRT). The results are related to those of previous investigations performed at equimolar concentration, as well as to the topology of the mean-field critical lines. As delta is increased in the interval 0 < delta < 1, we find first a regime where the phase diagram at equal species concentration displays a tricritical point, then one where both a tricritical and a liquid-vapor critical point are present. We did not find any clear evidence of the critical endpoint topology predicted by mean-field theory as delta approaches 1, at least up to delta=0.8, which is the largest value of delta investigated here. Particular attention was paid to the description of the critical-plus-tricritical point regime in the whole density-concentration plane. In this situation, the phase diagram shows, in a certain temperature interval, a coexistence region that encloses an island of homogeneous, one-phase fluid.Comment: 27 pages + 20 figure

Learning Semantic Representations for the Phrase Translation Model

This paper presents a novel semantic-based phrase translation model. A pair of source and target phrases are projected into continuous-valued vector representations in a low-dimensional latent semantic space, where their translation score is computed by the distance between the pair in this new space. The projection is performed by a multi-layer neural network whose weights are learned on parallel training data. The learning is aimed to directly optimize the quality of end-to-end machine translation results. Experimental evaluation has been performed on two Europarl translation tasks, English-French and German-English. The results show that the new semantic-based phrase translation model significantly improves the performance of a state-of-the-art phrase-based statistical machine translation sys-tem, leading to a gain of 0.7-1.0 BLEU points