Undergraduate teaching audit and evaluation (UTAE) is a new type of evaluation pattern, which is extremely important for a university to improve its quality assurance system and enhance teaching quality. Selecting an optimal university for benchmarking through UTAE to promote the quality of teaching can be regarded as a complex multicriteria decision making (MCDM) problem. Furthermore, in the process of UTAE, experts' evaluations over the teaching quality of universities are often imprecise and fuzzy due to the subjective nature of human thinking. In this paper, we propose a new UTAE approach based on q-rung orthopair fuzzy sets and the multiattribute border approximation area comparison (MABAC) method for evaluating and selecting the best university for benchmarking. The introduced method deals with the linguistic assessments given by experts by using q-ROFSs, assigns the weights of audit elements based on the indifference threshold-based attribute ratio analysis method, and acquires the ranking of universities with an extended MABAC method. The feasibility and effectiveness of the proposed q-rung orthopair fuzzy MABAC method is demonstrated through a realistic UTAE example. Results show that the UTAE method being proposed is valid and practical for UTAE.

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In this work, the dynamics of a prototypical heavy–light–heavy abstract reaction, Cl(2P) + HCl → HCl + Cl(2P), is investigated both by constructing a new potential energy surface (PES) and by rate coefficient calculations. Both the permutation invariant polynomial neural network method and the embedded atom neural network (EANN) method, based on ab initio MRCI-F12+Q/AVTZ level points, are used for obtaining globally accurate full-dimensional ground state PES, with the corresponding total root mean square error being only 0.043 and 0.056 kcal/mol, respectively. In addition, this is also the first application of the EANN in a gas-phase bimolecular reaction. The saddle point of this reaction system is confirmed to be nonlinear. In comparison with both the energetics and rate coefficients obtained on both PESs, we find that the EANN is reliable in dynamic calculations. A full-dimensional approximate quantum mechanical method, ring-polymer molecular dynamics with a Cayley propagator, is employed to obtain the thermal rate coefficients and kinetic isotopic effects of the title reaction Cl(2P) + XCl→ XCl + Cl(2P) (H, D, Mu) on both new PESs, and the kinetic isotope effect (KIE) is also obtained. The rate coefficients reproduce the experimental results at high temperatures perfectly but with moderate accuracy at lower temperatures, but the KIE is with high accuracy. The similar kinetic behavior is supported by quantum dynamics using wave packet calculations as well.

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In this study, a preparation method for the high-temperature pressure sensor based on the piezoresistive effect of p-type SiC is presented. The varistor with a positive trapezoidal shape was designed and etched innovatively to improve the contact stability between the metal and SiC varistor. Additionally, the excellent ohmic contact was formed by annealing at 950 °C between Ni/Al/Ni/Au and p-type SiC with a doping concentration of 1018cm−3. The aging sensor was tested for varistors in the air of 25 °C–600 °C. The resistance value of the varistors initially decreased and then increased with the increase of temperature and reached the minimum at ~450 °C. It could be calculated that the varistors at ~100 °C exhibited the maximum temperature coefficient of resistance (TCR) of ~−0.35%/°C. The above results indicated that the sensor had a stable electrical connection in the air environment of ≤600 °C. Finally, the encapsulated sensor was subjected to pressure/depressure tests at room temperature. The test results revealed that the sensor output sensitivity was approximately 1.09 mV/V/bar, which is better than other SiC pressure sensors. This study has a great significance for the test of mechanical parameters under the extreme environment of 600 °C.