A Flexure-Based Displacement Reducer Capable of Achieving Very Large Reduction Ratio

Piezo actuators and giant magnetostrictive actuators are widely used in micropositioning and micromanipulating devices. Due to their limited output stroke, flexure-based displacement amplifiers are usually employed to meet the large-stroke requirements. Although amplifiers increase the stroke of the actuators, they lower the resolution of the motion, making it difficult to obtain positioning of nanometer or even sub-nanometer resolution. To achive very high resolution from these actuators, a compact flexure-based displacement reducer, which shows the capability of obtaining very large reduction ratio, is proposed in this work. The reducer contains two bridge-type flexure mechanisms connected in a way that the output of the reducer equals the difference of the outputs of the two mechanisms (thus is called the bridge-type differential displacement reducer). If the two bridge-type flexure mechanisms are identical, no matter how large the input is, the output will always be 0, indicating an infinite reduction ratio theoretically. Therefore, introducing a slight difference between the two mechanisms can yield a very large reduction ratio. A kinetostatic model for the reducer is developed, base on which a reducer exhibiting a reduction ratio of 100 is designed and prototyped. The results of the kinetostatic model, the finite element model and the experiment agree well with each other, validating the effectiveness of the proposed reducer and the correctness of kinetostatic model.

Romania: Transnational and National Tensions Beyond the New Wave

The chapter on Romania examines post 2008 Romanian cinema through the dual prism of its film festival successes and the developing strand of genre-based popular films. Offering an account that goes beyond the critical successes of the New Wave films, the chapter discusses the difficulty of national productions to reach local audiences despite the increased adoption of genre. It also provides some explanations for the limited output of Romanian cinema, which is notable despite the increase in European and Balkan co-productions.

NONPARAMETRIC NONLINEARITY IDENTIFICATION WITH AN UPDATED EKF APPROACH USING DYNAMIC RESPONSE FUSION

Most parametric nonlinear behavior identification methods require an assumed mathematical model to describe the hysteretic behavior of structural members or substructures. Due to the individuality of various construction materials and structural systems, it is challenging to forecast the real nonlinear performance of a structure member or a substructure under dynamic loadings with a general parametric model in prior. In this paper, a nonparametric nonlinear restoring force (NRF) identification approach with limited output and unknown input is proposed by employing a double Chebyshev polynomial combined with an updated Extended Kalman filter (U-EKF) approach, where the observation equation is updated without using external excitation information. Moreover, data fusion is used to deal with the drift problem in dynamic response forecasting. The proposed approach is validated numerically with multi-degree-of-freedom (MDOF) structures equipped with various nonlinear members, including MR damper (damping-dominant) and SMA damper (stiffness-dominant) employed to mimic different structural nonlinear behavior. Moreover, a four-story shear frame model, including MR damper on the fourth floor, is employed to experimentally validate the approach. Identified results show that the proposed algorithm can identify structural nonlinear behavior in a nonparametric way without using excitation as an input, which is helpful for structural damage diagnosis where nonlinearity and loading profile should be considered.

Quantifying Experiences with Telepractice for Aphasia Therapy: A Text Mining Analysis of Client Response Data

Measures of satisfaction following treatment for aphasia have been limited. The challenge associated with reduced verbal output among many persons with aphasia (PWA) has reportedly been a key reason measures of treatment satisfaction have been limited. A novel approach to measure treatment satisfaction is the use of content analysis (CA), which uses the presence of certain words, themes, or concepts to explore outcomes such as treatment satisfaction particularly among individuals who generate limited output. CA utilizes responses and response patterns to assign meaning to client responses. The aim of this study was to use CA to measure posttreatment satisfaction with a telepractice approach for aphasia treatment. Seventeen PWA received 12 treatment sessions over a 6-week period. At the conclusion of the treatment, CA was utilized to explore patient satisfaction with this treatment approach. The participants reported an overall positive sentiment for the telepractice approach. Two primary topics emerged which were healthcare provider and healthcare delivery, where text analysis revealed discussion of these topics to be centered around being “helpful” and “being effective.” This study demonstrated that CA can be an effective approach for determining satisfaction with aphasia treatment particularly among PWA with limited verbal abilities.

ALGORITHMS OF SYSTEM SYNTHESIS FOR STABILIZING UNCERTAIN DYNAMIC OBJECTS

The article deals with the formation of stable algorithms for the system synthesis for the stabilizing uncertain dynamic objects based on the method of local optimization in the presence of approximate mathematical models. The article analyzes the issues of building adaptive control systems using the concept of roughness, taking into account the assessment of the maximum allowable discrepancy between the object and its model. Some of the most constructive algorithms for determining pseudo-inverse matrices are given. When calculating the pseudo-inverse matrix of the control object, modified QR decomposition algorithms are used, obtained by deleting or assigning a column. The obtained algorithms allow us to conclude that the stabilization systems can be built on the basis of the local optimization method in the presence of approximate mathematical models. At the same time, it turns out that the asymptotic stability, i.e., the limited output with a limited input, can be achieved with sufficiently rough estimates of the object parameters and external perturbations using regular methods.

Roadmap for advanced aqueous batteries: From design of materials to applications

Safety concerns about organic media-based batteries are the key public arguments against their widespread usage. Aqueous batteries (ABs), based on water which is environmentally benign, provide a promising alternative for safe, cost-effective, and scalable energy storage, with high power density and tolerance against mishandling. Research interests and achievements in ABs have surged globally in the past 5 years. However, their large-scale application is plagued by the limited output voltage and inadequate energy density. We present the challenges in AB fundamental research, focusing on the design of advanced materials and practical applications of whole devices. Potential interactions of the challenges in different AB systems are established. A critical appraisal of recent advances in ABs is presented for addressing the key issues, with special emphasis on the connection between advanced materials and emerging electrochemistry. Last, we provide a roadmap starting with material design and ending with the commercialization of next-generation reliable ABs.