Influence of Intelligent Technology Applications on the Learning Effect: Virtual Reality as an Example

With the continuous application of intelligent technology, Virtual Reality (VR) technology has become a hot topic of development. VR has unique advantages in the field of the teaching due to its characteristics of immersion, interaction and sociality. Therefore, it is necessary to pay attention to the influencing factors of VR teaching on learning effect, to improve the quality of courses through improvement of relevant influencing factors and to help to reverse further development of VR technology. A questionnaire survey on influencing factors of teaching application of VR technology on the learning effect of college students was conducted. Through data collection of students of various majors and grades in multiple comprehensive universities, statistical analysis and regression empirical analysis were carried out. Results show that different majors, grades, and students’ autonomous learning ability have different influences on the teaching application of VR technology. In addition, there are many influencing factors such as network fluency, situational sense of interaction, teachers’ teaching ability and the difficulty of course design, etc. According to the conclusions, some suggestions on improving VR teaching and learning effect are put forward. It is expected to improve the learning effect and efficiency of college students under the application of VR teaching, and promote the further development of VR teaching

An Improved Energy Management Strategy of Diesel-Electric Hybrid Propulsion System Based on FNN-DP Strategy

Diesel-electric hybrid propulsion system (HPS) is widely applied for shunting locomotive due to the characteristics of flexible configuration, economic and environmental protection in the world. Energy management strategy (EMS) is an important design factor of HPS that can optimize the energy distribution of each power sources, improve system efficiency, and reduce fuel consumption. In this paper, the model of HPS for shunting locomotive and system operating profile are firstly carried out. Then the EMS consist of the conventional rule-based (RB) strategy rule, and a fuzzy neural network base on dynamic programming (FNN-DP) strategy are studied. Finally, the simulations were carried out with these EMSs in the system model at full operating conditions to derive the fuel consumption. The conclusion is that the theoretical optimal solution of DP provides reference and guidance for the fuzzy neural network strategy to improve the rules, and the fuel consumption of the FNN-DP strategy is 10.2% lower than the conventional RB strategy

Evidence for quasi-two-dimensional superconductivity in infinite-layer nickelates

After being expected as a promising analogue to cuprates for decades, superconductivity was recently discovered in infinite-layer nickelates, providing new opportunities to explore mechanisms of high-temperature superconductivity. However, in sharp contrast to the single-band quasi-two-dimensional superconductivity in cuprates, nickelates exhibit a multi-band electronic structure and an unexpected isotropic superconductivity as reported recently, which challenges the cuprate-like picture in nickelates. Here, we show the superconductivity in nickelates is actually anisotropic and quasi-two-dimensional in nature, as that in cuprates. By synthesizing high-quality lanthanide nickelate films with enhanced crystallinity and superconductivity ($T_{c}^{onset}$ = 18.8 K, $T_{c}^{zero}$ = 16.5 K), strong anisotropic magnetotransport behaviors have been observed. The quasi-two-dimensional nature is further confirmed by the existence of a cusp-like peak of the angle-dependent $T_{c}$, and a Berezinskii-Kosterlitz-Thouless transition near $T_{c}$. Our work thus suggests a quasi-two-dimensional superconductivity in infinite-layer nickelates, implying a single-3$d_{x^2-y^2}$-band cuprate-like picture may remain valid in these compounds.Comment: 32 pages, 4 main figures, 6 extended dat

Synthesis of Oxide Interface-Based Two-Dimensional Electron Gas on Si

Two-dimensional electron gas (2DEG) at the interface of amorphous Al2O3/SrTiO3 (aAO/STO) heterostructures has received considerable attention owing to its convenience of fabrication and relatively high mobility. The integration of these 2DEG heterostructures on a silicon wafer is highly desired for electronic applications but remains challanging up to date. Here, conductive aAO/STO heterostructures have been synthesized on a silicon wafer via a growth-and-transfer method. A scanning transmission electron microscopy image shows flat and close contact between STO membranes and a Si wafer. Electron energy loss spectroscopic measurements reveal the interfacial Ti valence state evolution, which identifies the formation of 2D charge carriers confined at the interface of aAO/STO. This work provides a feasible strategy for the integration of 2DEG on a silicon wafer and other desired substrates for potential functional and flexible electronic devices