Author：Goodman, DS

Author：Han, JW

Author：Sun, JT;Liu, LZ;Zhang, Y;Guo, MM;Zhou, B

Abstract:The spent ternary lithium-ion batteries were utilized as the precursors to prepare Sm-Mn and Sm-Co perovskite oxides (SmMnO3-spent ternary lithium-ion battery [STLIB] and SmCoO3-STLIB) for the first time. Their catalytic activities were evaluated by catalytic oxidation of propylene glycol methyl ether. Compared with that of the catalysts synthesized by analytical reagents, the catalytic activities of SmMnO3-STLIB and SmCoO3-STLIB had been significantly enhanced. The analysis of X-ray photoelectron spectroscopy (XPS) showed that the molar ratios of Mn4+/Mn3+ and O-ads/O-latt of SmMnO3-STLIB were higher than that of pure SmMnO3 and the Co3+/Co2+ ratios of SmCoO3-STLIB was much larger than that of pure SmCoO3. The hydrogen temperature-programmed reduction (H-2-TPR) and N-2 adsorption-desorption tests determined that the reducibilities and specific surface areas of SmMnO3-STLIB and SmCoO3-STLIB were also superior to pure catalysts. Ultimately, the by-products of the catalytic oxidation of propylene glycol methyl ether over SmMnO3-STLIB were also detected by gas chromatography-mass spectrometry (GC-MS). This work will provide a demonstration for the resource utilization of spent lithium ions batteries and the analysis of the increased activity obtained by using spent lithium ions batteries as the precursors to prepare catalysts.

Author：Chen, J;Wang, X;Li, QR

Author：Kuo, CC;Ni, YL;Wu, CH;Duh, RR;Chen, MY;Chang, CC

Abstract:Purpose Studies have reported negative effects of felt accountability on employees' extra-role behavior. Deviating from that focus, this study proposes that leadership plays a role in shaping the implications of felt accountability for employees' extra-role behavior. We propose that under high transformational leadership, felt accountability can motivate employees to engage in task-relevant information elaboration and facilitate innovative work behavior, a form of extra-role behavior that seeks to improve the work environment. Design/methodology/approach We conducted a pilot study to validate measurements of felt accountability and task-relevant information elaboration in a sample of 202 employees. We then conducted the main study using a time-lagged, multisource survey design with a sample of 120 supervisor-employee pairs. Findings The results from the main study reveal that the association between felt accountability and task-related information elaboration is positive and stronger when transformational leadership is higher. Furthermore, task-relevant information elaboration positively predicts innovative work behavior. Finally, when transformational leadership is higher, the mediation effect of task-relevant information elaboration on the association between felt accountability and innovative work behavior is stronger. Originality/value Our study indicates that felt accountability can have positive implications for employees' extra-role behavior contingent on leadership styles. In contrast to previous studies that emphasize the negative implications of felt accountability on employees' behavior, our study depicts when and why felt accountability can have positive implications on employees' behavior.

Author：Hung,Juann H.;Chen,Yang

Author：Chan, KY;Yuen, KKF;Kwong, CK

Author：Chang, V;Ramachandran, M;Wills, G;Walters, RJ;Li, CS;Watters, P

Abstract:Research associated with Big Data in the Cloud will be important topic over the next few years. The topic includes work on demonstrating architectures, applications, services, experiments and simulations in the Cloud to support the cases related to adoption of Big Data. A common approach to Big Data in the Cloud to allow better access, performance and efficiency when analysing and understanding the data is to deliver Everything as a Service. Organisations adopting Big Data this way find the boundaries between private clouds, public clouds and Internet of Things (IoT) can be very thin. Volume, variety, velocity, veracity and value are the major factors in Big Data systems but there are other challenges to be resolved. The papers of this special issue address a variety of issues and concerns in Big Data, including: searching and processing Big Data, implementing and modelling event and workflow systems, visualisation modelling and simulation and aspects of social media. (C) 2016 Published by Elsevier B.V.

Author：Zhong, Q;Zhu, K;Gao, L;Chen, Q;Feng, G;Ming, WK;Huang, F;Liu, T;Hao, D;Yan, N;Jian, T

Author：Yin, JL

Author：Li, PP;Zhou, SS;Zhou, AJ

Abstract:© 2016 The International Association for Chinese Management Research. It is unusual for any speech to maintain strong influence over the general strategies of an organization and the behavior of its employees over time. ‘Haier Is a Sea’, presented by Zhang Ruimin, the chief executive officer (CEO) of Haier, more than twenty years ago, is an exception. This commentary identifies the core features of sea as a metaphor, explores the philosophical roots of this metaphor, and discusses the implications.

Author：Liu, QL;Chen, FY;Ding, F;Alsaedi, A;Hayat, T

Abstract:Many dynamic processes in practice have nonlinear characteristics and must be described by using nonlinear models. It remains to be a challenging problem to build the models of such nonlinear systems and to estimate their parameters. This article studies the parameter estimation problem for a class of Hammerstein-Wiener nonlinear systems based on non-uniform sampling. By means of the auxiliary model identification idea, an auxiliary model-based recursive least squares algorithm is derived for the systems. In order to enhance the computational efficiency, an auxiliary model-based hierarchical least squares algorithm is proposed by utilizing the hierarchical identification principle. The simulation results confirm the effectiveness of the proposed algorithms.

Author：Briel, H

Author：Carciofo, R

Abstract:Eveningness has previously been associated with more frequent mind wandering (MW). The current study re-investigated this association for components of circadian functioning, and MW typology. Questionnaire measures of Morning Affect, Eveningness, and (amplitude) Distinctness, deliberate and spontaneous MW, problem-solving daydreams, sleep quality, personality, affect, and life satisfaction were completed by 265 university students (aged 18-33, mean = 20.78), who also reported the peak time for daily MW and problem-solving daydreams. Spontaneous MW correlated with low Morning Affect and stronger Distinctness; these all correlated with poor sleep quality, less conscientiousness, less positive affect, less life satisfaction, more neuroticism, and more negative affect. Problem-solving daydreams positively correlated with Morning Affect. Significant mediators between morningness-eveningness and spontaneous MW were sleep quality, positive affect, and conscientiousness, which were also significant with Morning Affect as the predictor for spontaneous MW; sleep quality and positive affect were significant with Distinctness as the predictor for spontaneous MW. Exploratory path analysis indicated inter-relationships between Eveningness, Morning Affect, subjective sleep quality, conscientiousness, spontaneous MW, and negative affect. Spontaneous and deliberate MW showed some evidence of peak frequency at the non-preferred time-of-day. These results indicate that components of circadian functioning have varying relationships with different types of mind wandering/daydreaming.

Author：Wen, CH;Jia, F;Hao, JL

Abstract:Purpose Using intraday data, the authors explore the forecast ability of one high frequency order flow imbalance measure (OI) based on the volume-synchronized probability of informed trading metric (VPIN) for predicting the realized volatility of the index futures on the China Securities Index 300 (CSI 300). Design/methodology/approach The authors employ the heterogeneous autoregressive model for realized volatility (HAR-RV) and compare the forecast ability of models with and without the predictive variable, OI. Findings The empirical results demonstrate that the augmented HAR model incorporating OI (HARX-RV) can generate more precise forecasts, which implies that the order imbalance measure contains substantial information for describing the volatility dynamics. Originality/value The study sheds light on the relation between high frequency trading behavior and volatility forecasting in China's index futures market and reveals the underlying market mechanisms of liquidity-induced volatility.

Author：Guan,Steven

Author：Qin, MC

Abstract:STRING is an important concept in geometry and physics, and is closely related to the distribution of energy system. This paper finds a geometric phenomenon that some properties of two-dimension STRING also exists in multiple-dimension STRING and proposes a STRING theorem from a dimension to high dimension. On this basis, an algorithm is designed to demonstrate the theorem and verify it. The concept of quantum energy density function is established to reveal the energy density conversion rule, and change trend between low-dimensional space and high-dimensional space in the framework of string theory.

Author：Yan Chan,Kit;Fung Yuen,Kevin Kam;Palade,Vasile;Yue,Yong

Author：Sturup, S

Author：Lu, QF;Sun, FQ;Dai, YB;Wang, YY;Liu, L;Wang, ZH;Wang, SQ;Zhang, T

Abstract:Imbuing artificial sensory system with intelligence of the biological counterpart is limited by challenges in emulating perceptual learning ability at the device level. In biological systems, stimuli from the surrounding environment are detected, transmitted, and processed by receptor, afferent nerve, and brain, respectively. This process allows the living creatures to identify the potential hazards and improve their adaptability in various environments. Here, inspired by the biological olfaction system, a gas sensory system with perceptual learning is developed. As a proof-of-concept, H2S gas with various concentrations is used as the stimulation and the stimuli will be converted to pulse-like physiological signals in the designed system, which consists of a gas sensor, a flexible oscillator, and a memristor-type artificial synapse. Furthermore, the learning ability is implemented using a supervised learning method based on k-nearest neighbors (KNN) algorithm. The recognition accuracy can be enhanced by repeating training, illustrating a great potential to be used as the neuromorphic sensory system with a learning ability for the applications in robotics.