RESUMO
We present a simple theoretical model that predicts the thermal conductivity of SiO2 layers with embedded Ge quantum dots (QDs). Overall, the resulting nanoscale architecture comprising the structural relaxation in the SiO2 matrix, deviation in mass density of the QDs compared to the surrounding matrix and local strains associated with the dots are all likely to enhance phonon scattering and thus reduce the thermal conductivity in these systems. We have found that the conductivity reduction can be predicted by the dot-induced local elastic perturbations in SiO2. Our model is able to explain not only this large reduction but also the magnitude and temperature variation of the thermal conductivity with size and density of the dots. Within the error range, the theoretical calculations of the temperature-dependent thermal conductivity in different samples are in close agreement with the experimental measurements. Including the details of the strain fields in oxidized Si nanostructured layers is therefore essential for a better prediction of the heat pathways in on-chip thermoelectric devices and circuits.
RESUMO
This study assessed the performance of patients with Parkinson's disease (PD) in the Stroop test. Twenty-seven patients with PD (17 men, 10 women; mean age, 63.3 +/- 10.5 years) and 27 age-matched controls (14 men, 13 women; mean age, 63.5 +/- 9.2 years) were administered the color-naming, word-reading, and incongruent color-word-naming tasks in the Stroop test. Compared with the normal control group, the PD group had slower speeds for all three tasks and greater Stroop interference, indicating a response inhibition deficit in PD patients. Further analysis indicated that slowness during color naming might be due to motor slowness, rather than a central cognitive processing problem in color discrimination. In conclusion, the performance of the PD group on the three tasks of the Stroop test suggests that the PD patients were deficient in motor responses and cognitive inhibitory abilities.