Xinyu Wu

Since the bilateral commerce between the USA and China changes greatly and Chinese government continues to reform and delegate power in the economic field, it is of importance to study the Uniform Commercial Code of the USA. The study specifically studies the features of modal verbs in the UCC through the comparison with the United States Code and Frown. With the help of Antconc, the distribution of modal verbs, the modal value of the three sets of corpora are examined and analyzed based on the theory of Halliday’s systemic-functional grammar. The results show that there are significant differences between the three sets of corpora and the three main features of modal verbs in the UCC are: the high frequency use of may, the relatively lower frequency use of legal modal verb shall, and the much higher frequency of must and may not. The seemingly contrary usages within the UCC are discussed and explained with the background of the legislation and the legal thoughts of the major legislator in a sociosemiotic approach. With both the quantitative and qualitative analysis combining the examples, the study hopes to shed light on the related legal translation and further enhance the understanding of the modal verbs in the UCC as well as legal discourse in a more general context.

This paper presents a bioinspired lower extremity exoskeleton robot. The proposed exoskeleton robot can be adjusted in structure to meet the wearer’s height of 150–185 cm and has a good gait stability. In the gait control part, a method of identifying different locomotion modes is proposed; five common locomotion modes are considered in this paper, including sitting down, standing up, level-ground walking, ascending stairs, and descending stairs. The identification is depended on angle information of the hip, knee, and ankle joints. A deep locomotion mode identification model based on long-short term memory architecture is proposed in this paper for exploiting the angle data. We conducted two experiments to verify the effectiveness of the proposed method. Experimental results show that the DLMIM is capable of learning inherent characteristics of joint angles and achieves more accurate identification than the other models. The last experiment demonstrates that the DLMIM can recognize transitions between different locomotion modes in time and the real-time performance varies with each individual.

In this paper, we investigate the impact of economic policy uncertainty on the conditional dependence between China and U.S. stock markets by employing the Copula-mixed-data sampling framework. In the case of EPU, we consider the global EPU, the American EPU, and the China EPU. The empirical analysis based on the Shanghai Stock Exchange Composite index in China and the S&P 500 index in the U.S. shows that the tail dependence between China and U.S. stock markets is symmetrical, and the t Copula outperforms alternative Copulas in terms of in-sample goodness of fit. In particular, we find that the t Copula-MIDAS model with EPU dominates the traditional time-varying t Copula in terms of in-sample fitting. Moreover, we observe that both the GEPU and AEPU have a significantly positive impact on the conditional dependence between China and U.S. stock markets, whereas CEPU has no significant impact. The tail dependence between China and U.S. stock markets exhibits an increasing trend, particularly in the recent years.

Stroke and other neurological disorders have an effect on mobility which has a significant impact on independence and quality of life. The core rehabilitation requirements for patients with lower limb motor dysfunction are gait training, restand, and mobility. In this work, we introduce a newly developed multifunctional wheelchair that we call “ReChair” and evaluated its performance preliminarily. ReChair seamlessly integrates the mobility, gait training, and multiposture transformation. ReChair driving and multiposture transformation are done using the voice, button, and mobile terminal control. This work describes the functional requirements, mechanical structure, and control system and the overall evaluation of ReChair including the kinematic simulation of the multiposture transformation and passive lower limb rehabilitation training to quantitatively verify the motion capability of ReChair, the voice control system evaluation that shows how the voice recognition system is suitable for home environment, the sensorless speed detection test results that indicate how the wheel speeds measured by sensorless method are appropriate for travelling control, and the passive and balance training test results that show how the lower limb rehabilitation training in daily life by ReChair is convenient. Finally, the experimental results show that ReChair meets the patients’ requirements and has practical significance. It is cost-effective, easy to use, and supports multiple control modes to adapt to different rehabilitation phases.

Lumbar Exoskeleton, as an important instance of wearable exoskeleton, has broad application prospects in logistics, construction, and other industries. Specifically, in the working scenarios that require long-term and repeated bending and rising movements, active lumbar exoskeleton can provide effective protection and flexible assistance to wear’s waist muscles and bones, which will significantly reduce the risk of lumbar muscle strain. How to improve the human-machine coupling and enhance the assistance performance are the main challenges for ALE’s development. Based on the biomechanical analysis of the movement of lifting heavy objects from bottom up, this paper proposes a lightweight but powerful ALE, named as SIAT-WEXv2, which can output maximum assistive force of 28 N. Additionally, we use robust fuzzy adaptive algorithm to improve SIAT-WEXv2’s antidisturbance ability, so that it can provide continuous and supple assistance for wearer. Electromyography signals of the lumbar erector spinae from ten subjects in two experimental cases were collected to evaluate the effectiveness of our new ALE. The experimental results indicate that the reduction of iEMG signal at LES decreased monotonically from 60% ± 5.5% to 40.5% ± 6.5% as the weight of lifting load increased from 0 to 25 kg.