Optical imaging of resonant electrical carrier injection into individual quantum dots

We image the micro-electroluminescence (EL) spectra of self-assembled InAs quantum dots (QDs) embedded in the intrinsic region of a GaAs p-i-n diode and demonstrate optical detection of resonant carrier injection into a single QD. Resonant tunneling of electrons and holes into the QDs at bias voltages below the flat-band condition leads to sharp EL lines characteristic of individual QDs, accompanied by a spatial fragmentation of the surface EL emission into small and discrete light- emitting areas, each with its own spectral fingerprint and Stark shift. We explain this behavior in terms of Coulomb interaction effects and the selective excitation of a small number of QDs within the ensemble due to preferential resonant tunneling paths for carriers.Comment: 4 page

Why are Retirement Rates So High at Age 65?

In most data sets of labor force participation of the elderly, an empirical regularity that emerges is that retirement rates are particularly high at age 65. While there are numerous economic reasons why individuals may choose to retire at 65, empirical models that have attempted to explain the age-65 spike have met with limited success. Interpreted another way, while many models would predict a jump in the hazard rate at age 65, the magnitude of the spike indicates excessive response given the economic considerations that retirees typically face. This paper considers the puzzle of why retirement rates are so high at age 65 and explores a variety of explanations.

Three Models of Retirement: Computational Complexity Versus Predictive Validity

Empirical analysis often raises questions of approximation to underlying individual behavior. Closer approximation may require more complex statistical specifications, On the other hand, more complex specifications may presume computational facility that is beyond the grasp of most real people and therefore less consistent with the actual rules that govern their behavior, even though economic theory may push analysts to increasingly more complex specifications. Thus the issue is not only whether more complex models are worth the effort, but also whether they are better. We compare the in-sample and out-of-sample predictive performance of three models of retirement -- "option value," dynamic programming, and probit -- to determine which of the retirement rules most closely matches retirement behavior in a large firm. The primary measure of predictive validity is the correspondence between the model predictions and actual retirement under the firm's temporary early retirement window plan. The "option value" and dynamic programming models are considerably more successful than the less complex probit model in approximating the rules individuals use to make retirement decisions, but the more complex dynamic programming rule approximates behavior no better than the simpler option value rule.

Building validation tools for knowledge-based systems

The Expert Systems Validation Associate (EVA), a validation system under development at the Lockheed Artificial Intelligence Center for more than a year, provides a wide range of validation tools to check the correctness, consistency and completeness of a knowledge-based system. A declarative meta-language (higher-order language), is used to create a generic version of EVA to validate applications written in arbitrary expert system shells. The architecture and functionality of EVA are presented. The functionality includes Structure Check, Logic Check, Extended Structure Check (using semantic information), Extended Logic Check, Semantic Check, Omission Check, Rule Refinement, Control Check, Test Case Generation, Error Localization, and Behavior Verification

A probabilistic approach to composite micromechanics

Probabilistic composite micromechanics methods are developed that simulate expected uncertainties in unidirectional fiber composite properties. These methods are in the form of computational procedures using Monte Carlo simulation. A graphite/epoxy unidirectional composite (ply) is studied to demonstrate fiber composite material properties at the micro level. Regression results are presented to show the relative correlation between predicted and response variables in the study

O Brasil no cenário mundial de lácteos.

bitstream/item/65424/1/COT-51-O-Brasil-no-cenario.pd

Magnetic-crystallographic phase diagram of superconducting parent compound Fe1+x_{1+x}Te

hrough neutron diffraction experiments, including spin-polarized measurements, we find a collinear incommensurate spin-density wave with propagation vector $\mathbf k =$ ($0.4481(4) \, \,0 \, \, \frac1 2$) at base temperature in the superconducting parent compound Fe$_{1+x}$Te. This critical concentration of interstitial iron corresponds to $x \approx 12$ and leads crystallographic phase separation at base temperature. The spin-density wave is short-range ordered with a correlation length of 22(3) \AA, and as the ordering temperature is approached its propagation vector decreases linearly in the H-direction and becomes long-range ordered. Upon further populating the interstitial iron site, the spin-density wave gives way to an incommensurate helical ordering with propagation vector $\mathbf k =$ ($0.3855(2) \, \,0 \, \, \frac1 2$) at base temperature. For a sample with $x \approx 9(1)$, we also find an incommensurate spin-density wave that competes with the bicollinear commensurate ordering close to the N\'eel point. The shifting of spectral weight between competing magnetic orderings observed in several samples is supporting evidence for the phase separation being electronic in nature, and hence leads to crystallographic phase separation around the critical interstitial iron concentration of 12%. With results from both powder and single crystal samples, we construct a magnetic-crystallographic phase diagram of Fe$_{1+x}$Te for $ 5% < x <17%