Alloy-Strain-Output Induced Lattice Dislocation in Ni3FeN/Ni3Fe Ultrathin Nanosheets for Highly Efficient Overall Water Splitting

Designing highly efficient, stable and low-cost bifunctional electrocatalysts based on in-situ microstructure evolution, especially achieving partial lattice dislocation on highly crystalline texture, to catalyze hydrogen evolution reaction (HER) and oxygen...

Molecular Dynamics Study of Nonequilibrium [112] Tilt Grain Boundaries in Ni and their Relaxation under Cyclic Deformation

Atomic structure of nonequilibrium [112] tilt grain boundaries in nickel containing disclination dipoles is studied by means of molecular dynamics simulations. Initial systems for simulations are constructed by joining together pieces of two bicrystals one of which contains a symmetric tilt GB S=11 / 62.96° and the other a GB S=105 / 57.12°, or S=125 / 55.39°, or S=31 / 52.20°, so disclination dipoles with strengths w = 5.84°, 7.58° and 10.76° are created. Stress maps plotted after relaxation at zero temperature indicate the presence of high long-range stresses induced by disclination dipoles. Excess energy of GBs due to the nonequilibrium structure is calculated. Effect of oscillating tension-compression stresses on the nonequilibrium GB structure is studied at temperature T = 300 K. The simulations show that the oscillating stress results in a generation of partial lattice dislocations by the GB, their glide across grains and sink at appropriate surfaces that results in a compensation of the disclination stress fields and recovery of an equilibrium GB structure and energy.

Learning Representations for Weakly Supervised Natural Language Processing Tasks

Finding the right representations for words is critical for building accurate NLP systems when domain-specific labeled data for the task is scarce. This article investigates novel techniques for extracting features from n-gram models, Hidden Markov Models, and other statistical language models, including a novel Partial Lattice Markov Random Field model. Experiments on part-of-speech tagging and information extraction, among other tasks, indicate that features taken from statistical language models, in combination with more traditional features, outperform traditional representations alone, and that graphical model representations outperform n-gram models, especially on sparse and polysemous words.

EXTENSIONS OF PARTIAL LATTICE-VALUED POSSIBILISTIC MEASURES FROM NESTED DOMAINS

We investigate a partial non-numerical possibilistic measure taking its values in a complete lattice and defined on a nested system of subsets of the universe under consideration. Our aim is to extend this measure conservatively to the power-set of all systems of this universe using the same idea as that when introducing outer measures. Hence, we ascribe to each subset of the universe its minimal (in the sense of set inclusion) covering by a set from the nested domain and define its possibility degree as identical with the value ascribed to this covering. Also analyzed is the case when they are two lattice-valued possibilistic measures on the same universe, each with its own nested domain and our aim is to define one possibilistic measure on the power-set in question in a way sophistically taking profit of the information offered by both the particular partial lattice-valued measures.