B→KB\to K Transition Form Factor with Tensor Current within the kTk_T Factorization Approach

In the paper, we apply the $k_T$ factorization approach to deal with the $B\to K$ transition form factor with tensor current in the large recoil regions. Main uncertainties for the estimation are discussed and we obtain $F_T^{B\to K}(0)=0.25\pm0.01\pm0.02$, where the first error is caused by the uncertainties from the pionic wave functions and the second is from that of the B-meson wave functions. This result is consistent with the light-cone sum rule results obtained in the literature.Comment: 8 pages, 4 figures, references adde

Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach

Recent years have witnessed the rapid development of human activity recognition (HAR) based on wearable sensor data. One can find many practical applications in this area, especially in the field of health care. Many machine learning algorithms such as Decision Trees, Support Vector Machine, Naive Bayes, K-Nearest Neighbor, and Multilayer Perceptron are successfully used in HAR. Although these methods are fast and easy for implementation, they still have some limitations due to poor performance in a number of situations. In this paper, we propose a novel method based on the ensemble learning to boost the performance of these machine learning methods for HAR

A new state-of-charge estimation method for electric vehicle lithium-ion batteries based on multiple input parameter fitting model

Copyright © 2017 John Wiley & Sons, Ltd. The estimation of state-of-charge (SOC) is crucial to determine the remaining capacity of the Lithium-Ion battery, and thus plays an important role in many electric vehicle control and energy storage management problems. The accuracy of the estimated SOC depends mostly on the accuracy of the battery model, which is mainly affected by factors like temperature, State of Health (SOH), and chemical reactions. Also many characteristic parameters of the battery cell, such as the output voltage, the internal resistance and so on, have close relations with SOC. Battery models are often identified by a large amount of experiments under different SOCs and temperatures. To resolve this difficulty and also improve modeling accuracy, a multiple input parameter fitting model of the Lithium-Ion battery and the factors that would affect the accuracy of the battery model are derived from the Nernst equation in this paper. Statistics theory is applied to obtain a more accurate battery model while using less measurement data. The relevant parameters can be calculated by data fitting through measurement on factors like continuously changing temperatures. From the obtained battery model, Extended Kalman Filter algorithm is applied to estimate the SOC. Finally, simulation and experimental results are given to illustrate the advantage of the proposed SOC estimation method. It is found that the proposed SOC estimation method always satisfies the precision requirement in the relevant Standards under different environmental temperatures. Particularly, the SOC estimation accuracy can be improved by 14% under low temperatures below 0 °C compared with existing methods. Copyright © 2017 John Wiley & Sons, Ltd

Reviewing Clinical Effectiveness of Active Training Strategies of Platform-Based Ankle Rehabilitation Robots

Objective; This review aims to provide a systematical investigation of clinical effectiveness of active training strategies applied in platform-based ankle robots. Method. English-language studies published from Jan 1980 to Aug 2017 were searched from four databases using key words of “Ankle” AND “Robot” AND “Effect OR Improv OR Increas.” Following an initial screening, three rounds of discrimination were successively conducted based on the title, the abstract, and the full paper. Result. A total of 21 studies were selected with 311 patients involved; of them, 13 studies applied a single group while another eight studies used different groups for comparison to verify the therapeutic effect. Virtual-reality (VR) game training was applied in 19 studies, while two studies used proprioceptive neuromuscular facilitation (PNF) training. Conclusion. Active training techniques delivered by platform ankle rehabilitation robots have been demonstrated with great potential for clinical applications. Training strategies are mostly combined with one another by considering rehabilitation schemes and motion ability of ankle joints. VR game environment has been commonly used with active ankle training. Bioelectrical signals integrated with VR game training can implement intelligent identification of movement intention and assessment. These further provide the foundation for advanced interactive training strategies that can lead to enhanced training safety and confidence for patients and better treatment efficacy

Finite dimensional integrable Hamiltonian systems associated with DSI equation by Bargmann constraints

The Davey-Stewartson I equation is a typical integrable equation in 2+1 dimensions. Its Lax system being essentially in 1+1 dimensional form has been found through nonlinearization from 2+1 dimensions to 1+1 dimensions. In the present paper, this essentially 1+1 dimensional Lax system is further nonlinearized into 1+0 dimensional Hamiltonian systems by taking the Bargmann constraints. It is shown that the resulting 1+0 dimensional Hamiltonian systems are completely integrable in Liouville sense by finding a full set of integrals of motion and proving their functional independence.Comment: 10 pages, in LaTeX, to be published in J. Phys. Soc. Jpn. 70 (2001

Tailoring liquid crystal honeycombs by head-group choice in bird-like bent-core mesogens

We introduce a new class of mesogens that are bird-like in shape and form honeycomb-type supramolecular liquid crystals. They have a bent pi-conjugated aromatic core as wings, a linear or branched chain as the tail and a selection of functional headgroups. Honeycombs of non-centrosymmetric trigonal type (p3m1) are obtained, along with two different complex honeycomb superlattices (p31m and p2gg) and a randomized hexagonal mesophase (p6mm). The key determinant of the self-assembled structure is the nature of interaction of the headgroup with the glycerols at the ends of the wings. The structure depends on whether the sub-columns lying along the edges of the prismatic cells contain pure or mixed headgroups and wing-end hydrogen-bonding groups. Its assembly is further controlled by reducing the tail-chain volume, inducing out-of-plane buckling of the honeycomb. These two modes of symmetry breaking lead to structural polarity both in- and out-of-plane, opening the way to applications in devices relying on properties such as ferroelectricity and second harmonic generation

Trigonal columnar self-assembly of bent phasmid mesogens

Three compounds with a bent rod-like aromatic core and with three alkoxy chains at each end were synthesised by click reaction. The compounds form a columnar liquid crystal phase with non-centrosymmetric trigonal p31m symmetry, the columns having a 3-arm star-like cross-section