Ferroelectricity, the electrostatic counterpart to ferromagnetism, has long been thought to be incompatible with metallicity due to screening of electric dipoles and external electric fields by itinerant charges. Recent measurements, however, demonstrated signatures of ferroelectric switching in the electrical conductance of bilayers and trilayers of WTe2, a semimetallic transition metal dichalcogenide with broken inversion symmetry. An especially promising aspect of this system is that the density of electrons and holes can be continuously tuned by an external gate voltage. This degree of freedom enables measurement of the spontaneous polarization as free carriers are added to the system. Here we employ capacitive sensing in dual-gated mesoscopic devices of bilayer WTe2 to directly measure the spontaneous polarization in the metallic state and quantify the effect of free carriers on the polarization in the conduction and valence bands, separately. We compare our results to a low-energy model for the electronic bands and identify the layer-polarized states that contribute to transport and polarization simultaneously. Bilayer WTe2 is thus shown to be a fully tunable ferroelectric metal and an ideal platform for exploring polar ordering, ferroelectric transitions, and applications in the presence of free carriers.

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A novel single phase Phase-Locked Loop (PLL) is proposed in this paper to accurately and rapidly estimate the instantaneous phase angle of a grid. A conjugate rotating vector pair is proposed and defined to synthesize the single phase signal in the stationary reference frame. With this concept, the proposed PLL innovatively sets one phase input of the PARK transformation to a constant zero. By means of a proper cancellation, a zero steady state phase angle estimation error can be achieved, even under magnitude and frequency variations. The proposed PLL structure is presented together with guidelines for parameters adjustment. The performance of the proposed PLL is verified by comprehensive experiments. Satisfactory phase angle estimation can be achieved within one input signal cycle, and the estimation error can be totally eliminated in four input cycles for the most severe conditions.

There are large number of transient signals will be produced when the operation mode is changed. And the frequency of the transient signals distributed in wide range. The most of them are damped and oscillated. The impedance is a popular feature in power system, and it has been widely used in relay protection and fault location. So the impedance calculation based on the damped sinusoidal signal have been the important way to diagnosis the fault, locate the fault and so on. But the methods used now are based on the fundamental impedance calculation theory, lacking theoretical basis. In fact, the traditional methods for fundamental signal calculation are not appropriate for the quantitative analysis of damped sinusoidal signal. The paper analyzed the impedance calculation based on damped sinusoidal signal, combined the features of damped sinusoidal signals and the traditional impedance calculation method. The two typical signal analysis methods for damped sinusoidal signal extraction are used to calculate the accurate impedance based on the different extraction results. And the analysis laid a foundation for the impedance calculation using damped sinusoidal signals.

Abstract. Two exterior trajectory models of guided bomb in aircraft coordinate system (ACS) and body coordinate system (BCS) are built for simulation and analysis under different meteorological conditions. Simulation errors of different modelling methods are studied and analyzed to verify the rationality of modelling method adopted in this paper, which also indicates the efficient path to decrease simulation error and improve precision.

As an important part of the school, the university library is an academic institution that serves teaching and scientific research with main service objects of teachers and students. After clarifying the reading connotation of university library readers against the background of the new era, through the analysis of the current situation and existing problems of the supply side of university libraries, it is found that insufficient effective communication, relatively single reading carrier, insufficient interactivity of reader activity, and monotonous reading space and environment restrict the development of university libraries. In the context of the new era, university libraries should start from themselves, keep up with the pace of the times, focus on readers to reform from the supply side, establish effective communication by setting up full-time departments, multifariously enrich library resources with pertinence, realize the diversification of resource carriers and independent diversification of channels, carry out interactive brand activities while enhancing interactivity and understanding the needs of readers, improve the quality and efficiency of library services, and let the resources and services of libraries adapt to the diverse needs of users, so as to promote the sustainable and healthy development of libraries and contribute to the development of universities and society.

Speech emotion recognition (SER) promotes the development of intelligent devices, which enable natural and friendly human-computer interactions. However, the recognition performance of existing approaches is significantly reduced on unseen datasets, and the lack of sufficient training data limits the generalizability of deep learning models. In this work, we analyze the impact of the domain generalization method on cross-corpus SER and propose an adversarial domain generalized transformer (ADoGT), which is aimed at learning a shared feature distribution for the source and target domains. Specifically, we investigate the effect of domain adversarial learning by eliminating nonaffective information. We also combine the center loss with the softmax function as joint supervision to learn discriminative features. Moreover, we introduce unsupervised transfer learning to extract additional features, and incorporate a gated fusion model to learn the complementary information of the features learned by the supervised feature extractor and pretrained model. The proposed transformer based domain generalization method is evaluated using four emotional datasets. We also provide an ablation study of different domain adversarial model structures and feature fusion models. The results of comparative experiments demonstrate the effectiveness of the proposed ADoGT.