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The joint torque estimation model based on surface electromyography (sEMG) signals needs to recalibrate the model parameters when used for joint torque estimation at different volunteers. However, the feature transferability drops significantly in higher task-specific layers, which reduce the performance of the model. The generalization of joint torque estimation models among different volunteers has become a challenge. In this paper, a fast calibration method based on a deep adaptive regression network is proposed to reduce the frequency and time of model recalibration when volunteers change. The proposed method associates source domain (SD) data with target domain (TD) data through migration learning. The maximum mean difference (MMD) adaptive method is used to migrate the model trained in the SD dataset to the TD dataset, which avoids the recalibration required in the joint torque estimation model. The experimental results show that the proposed method can improve the migration ability of the model used for estimating joint torque and achieve the generalization application of the model on different volunteer datasets. Moreover, the proposed method can reduce the calibration operations and iterations of the model caused by volunteer changes and improve the speed of joint torque estimation. The optimal normalized root mean square error (NRMSE) and Pearson correlation coefficient (ρ) of knee extension/flexion joint torque estimation reached 0.02198/0.02565 and 0.9892/0.9839, respectively. [ABSTRACT FROM AUTHOR]

To understand the effects of tellurium (Te) inclusions on the device performance of CdZnTe radiation detectors, the perturbation of the electrical field in and around Te inclusions was studied in CdZnTe single crystals via Kelvin probe force microscopy (KPFM). Te inclusions were proved to act as lower potential centers with respect to surrounding CdZnTe matrix. Based on the KPFM results, the energy band diagram at the Te/CdZnTe interface was established, and the bias-dependent effects of Te inclusion on carrier transportation is discussed. [ABSTRACT FROM AUTHOR]

This paper uses a numerical simulation method based on synthesized oblique velocity to simulate the process of submerged oblique jet scouring of the sand bed. The concept of the initial scouring equilibrium state is introduced, and curves showing the variation of scour hole depth over time at varying angles are fitted based on experimental data. This enables predicting the scour hole depth at any point during the scouring process and the time required to reach the initial scouring equilibrium state. An ultrasonic displacement sensor was used to measure the depth and width of the scour holes accurately. The evolution of the scour holes formed by the submerged oblique jet on the sand bed was systematically studied within the range of oblique angles from θ = 30°–80°. The flow structure during the scouring process and its interaction with sediment movement were further revealed through numerical simulations. The synthesized oblique velocity method effectively addresses the complexity of simulating the oblique jet. This provides a new approach to investigating the submerged oblique jet scouring of the sand bed. The findings of this study offer valuable guidance for practical applications, such as underwater equipment cleaning and deep-sea dredging. • A numerical method based on synthesized oblique velocity is used to simulate the submerged jet scouring of the sand bed. • The accuracy and validity of the numerical model are verified through experiments. • Revealing the evolution of scouring holes on the erodible sand bed and the flow structure within the flow field. • The concept of the initial scouring equilibrium state is introduced, depicting the changes in the scour hole depth over time. [ABSTRACT FROM AUTHOR]

High-performance environment-friendly piezoelectric potassium sodium niobate (KNN)-based thin films have been emerged as promising lead-free candidates, while their substrate-dependent piezoelectricity faces the lack of high-quality information due to restraints in measurements. Although piezoresponse force microscopy (PFM) is a potential measuring tool, still its regular mode is not considered as a reliable characterization method for quantification. After combining machine-learning enabled analysis using PFM datasets, it is possible to measure piezoelectric properties quantitatively. Here we utilized advanced PFM technology empowered by machine learning to measure and compare the piezoelectricity of KNN based thin films on different substrates. The results provide a better understanding of the relationship between structures and piezoelectric properties of the thin films. [ABSTRACT FROM AUTHOR]

Most ferroelectric transitions occur ultrafast and are time independent. However, here in (1-x) (Bi 0.5 Na 0.5 )TiO 3 -xBaTiO 3 , we have found a ferroelectric phase transition induced solely by increasing waiting time at certain temperatures (isothermal phase transition). Through cooling, a unique metastable state between a relaxor ferroelectric and a ferroelectric is unveiled, which in essence is initially a short-range ordered glassy state and then can evolve into a long-range ordered ferroelectric state through the isothermal process. It is also found that these isothermal ferroelectric transitions only occur within a specific temperature region with different waiting time needed. These features of isothermal phase transition can be understood by Landau theory analysis with the consideration of random defects as a competition between the thermodynamically favored long-range ordered state and the kinetically frustrated short-range ordered glassy state from random defects. This study offers a precise experimental as well as a phenomenological interpretation on the isothermal ferroelectric transition, which may help to further clarify the intricate structure-property relationship in this important lead-free piezoelectric material and other related systems. [ABSTRACT FROM AUTHOR]

Lead-free (Na 0 .5 Bi 0.5 ) 0.95 Ba 0.05 TiO 3 (0.95NBT–0.05BT) thin films were deposited on polycrystalline Ni substrates by using the RF high-pressure sputtering system. Microstructural studies by high resolution X-ray diffraction reveal that the as-deposited 0.95NBT–0.05BT thin films are polycrystalline structures. The piezoelectric property measurements by a piezoresponse force microscopy exhibit that the polycrystalline 0.95NBT–0.05BT thin films have an excellent piezoelectric response. It is indicated that the as-grown 0.95NBT–0.05BT thin films have the potential for the development of the structural health monitoring systems and related device applications. [ABSTRACT FROM AUTHOR]