This present study developed two predictive and associative Bayesian network models to forecast the tolerable travel time of university students to campus. This study considered the built environment experiences of university students during their early life-course as the main predictors of this study. The Bayesian network models were hybridized with the Pearson chi-square test to select the most relevant variables to predict the tolerable travel time. Two predictive models were developed. The first model was applied only to the variables of the built environment, while the second model was applied to all variables that were identified using the Pearson chi-square tests. The results showed that most students were inclined to choose the tolerable travel time of 0–20 min. Among the built environment predictors, the availability of residential buildings in the neighborhood in the age periods of 14–18 was the most important. Taking all the variables into account, distance from students’ homes to campuses was the most important. The findings of this research imply that the built environment experiences of people during their early life-course may affect their future travel behaviors and tolerance. Besides, the outcome of this study can help planners create more sustainable commute behaviors among people in the future by building more compact and mixed-use neighborhoods.

A technique for ion beam crystallization of InAs/GaAs(001) nanostructures with quantum dots is proposed. The GaAs and InAs sputtering yields in the energy range EAr+= 200–300 eV and argon beam...

The ion beam deposition of photoactive silicon nanolayers through the bombardment of a single-crystal silicon target with an Ar+ion beam has been analyzed using computer simulation. The model thus...

Flexible graphite foils with varying thicknesses (S = 282 ± 5 μm, M = 494 ± 7 μm, L = 746 ± 8 μm) and an initial density of 0.70 g/cm³ were obtained using the nitrate method. The specific electrical and thermal conductivity of these foils were investigated. As the density increased from 0.70 g/cm³ to 1.75 g/cm³, the specific electrical conductivity increased from 69 to 192 kS/m and the thermal conductivity increased from 109 to 326 W/(m·K) due to the rolling of graphite foils. The study showed that conductivity and anisotropy depend on the shape, orientation, and contact area of thermally expanded graphite (TEG) mesoparticles (mesostructural factor), and the crystal structure of nanocrystallites (nanostructural factor). A proposed mesostructural model explained these increases, with denser foils showing elongated, narrowed TEG particles and larger contact areas, confirmed by electron microscopy results. For graphite foils 200 and 750 μm thick, increased density led to a larger coherent scattering region, likely due to the rotation of graphite mesoparticles under mechanical action, while thinner foils ( 1.7 g/cm³ showed increased plastic deformation, indicated by a sharp reduction in the coherent scattering region size. This was also evident from the decrease in misorientation angles with increasing density. Rolling reduced nanocrystallite misorientation angles along the rolling direction compared to the transverse direction (TD) (for 1.75 g/cm³ density ΔMA = 1.2° (S), 2.6° (M), and 2.4° (L)), explaining the observed anisotropy in the electrical and mechanical properties of the rolled graphite foils. X-ray analysis confirmed the preferred nanocrystallite orientation and anisotropy coefficients (A) using Kearns parameters, which aligned well with experimental measurements (for L series foils calculated as: A_0.70 = 1.05, A_1.30 = 1.10, and A_1.75 = 1.16). These calculated values corresponded well with the experimental measurements of specific electrical conductivity, where the anisotropy coefficient changed from 1.00 to 1.16 and mechanical properties varied from 0.98 to 1.13.

We describe a new method for the formation of special positioning marks on the surface of one- and two-dimensional objects, which makes it possible to fix local regions of investigation in scanning...

The features of InAs quantum dots obtained on GaAs(001) single-crystal substrates by ion-beam sputtering were investigated. It has been shown that in the range of ion energies of 150 to 200 eV at a temperature of 500 °C and a beam current of 120 µA InAs quantum dots with average dimensions below 15 nm and a surface density of 10¹¹ cm⁻² are formed. The technique of controlled doping of InAs/GaAs nanostructures using a SnTe solid-state source was proposed. It has been established that a maximum donor concentration of 8.7·10¹⁸ cm⁻³ in the GaAs spacer layer is reached at an evaporation temperature of 415 °С. At the same time, impurity accumulation in the growth direction was observed. We have shown that increasing the impurity doping of the GaAs barrier layer increases the intensity of photoluminescence peaks of the ground state and the first excited state of the InAs quantum dots.