This paper describes an empathic software agent (ESA) interface using eye movement information to facilitate empathy-relevant reasoning and behavior. Eye movement tracking is used to monitor user's attention and interests, and to personalize the agent behaviors. The system reacts to user eye information in real-time, recording eye gaze and pupil dilation data during the learning process. Based on these measures, the ESA infers the focus of attention and motivational status of the learner and responds accordingly with affective (display of emotion) and instructional behaviors. In addition to describing the design and implementation of empathic software agents, this paper will report on some preliminary usability test results concerning how users respond to the empathic functions that are provided.

Automobile industry, Chinese car, Geely, Inter-firm relationships, Product architecture,

PurposeThe overarching theme is the importance of innovations that are created within the emerging economies. More specifically, the article looks at the development of various alternatives to vehicles powered by the internal combustion engine, new energy vehicles (NEVs) within China. Design/methodology/approachThe broad strategic approach of two sectors within the NEV sector in China, the pure electric vehicle (EV) and the low-speed electric vehicle (LSEV) sectors, are compared using recent data and conclusions are drawn. FindingsThe EV sector is viewed by the central government as a key sector for China's future industrial growth and is heavily supported. In contrast, the LSEV sector receives no support from central government and yet clearly outstrips the sales of EVs. The article argues that the latter's success is a reflection of the LSEV sector's focus on business model rather than technological innovation. Practical implicationsThe article highlights the importance of monitoring innovations that come from within emerging economies and also illustrates the benefits that can come from commercially focused innovations rather than those based on technology. Social implicationsFinding alternatives to vehicles powered by fossil fuels is one of the most important challenges facing the world today. This article looks at the search for one alternative and examines its implications. What is original/of value?The article examines a business sector that is peculiarly Chinese and yet has potential implications far beyond China. It also contains recent sales figures and other data collected directly from sources in China.

No abstract

No abstract

International audienceAdapting existing business models for use in developing economies poses particular challenges for established firms. Yet, few studies have separated stable internal factors from the novel external factors that drive change in the existing business model. The Bosch Group's investment in the Chinese automobile aftermarket highlights the impact of four principal external factors—industry, technology, institutions, and market—on business model innovation. A proposed framework comprising these factors offers managers who are charged with expanding into a developing economy guidance in modifying an existing business model to suit local conditions. By so doing, they will be better equipped to ensure the attainment of organizational objectives in their new setting

The volume variation of electrode materials will lead to poor cyclability of lithium-ion batteries during the lithiation/delithiation process. Instead, inner-stress fragmentation is creatively used to change carbon-layer-capped Fe3O4 particles ∼30 nm in diameter into high-density Fe3O4 dots ∼4 nm in size embedded in ultrathin carbon layers. The optimized structure shows a remarkable 45.2% enhancement of lithium storage from 804.7 (the 10th cycle) to 1168.7 mA h g–1 (the 250th cycle) at 500 mA g–1, even retaining 1239.5 mA h g–1 after another 550 cycles. The electrochemical measurements reveal the enhanced capacitive behavior of the high-density Fe3O4 dots@C layers, which have more extra active sites for the insertion/extraction of Li+ ions, confirmed by the differential capacity plots, leading to remarkably increased specific capacity during cycling. The restructured electrode also shows a superior rate capacity and excellent cycling stability (938.7 and 815.4 mA h g–1 over 2000 cycles at 1000 and 2000 mA g–1, respectively). X-ray photoelectron spectroscopy and transmission electron microscopy characterizations show that the optimized structure has stable structural and componential stability even at large rates. This work presents an MOF-guided synthesis of high-density Fe3O4-dots’ anode material optimized by inner-stress fragmentation, showing a feasible route to design high-efficiency electrode materials.

Hyperspectral imaging technology was applied to detect and recognize six different varieties of Longjing fresh tea. The data contained image and spectral information at 370–1042 nm; color and texture features were the foci of the image research. Spectral pre‐processing was performed by multiplicative scatter correction (MSC) and standard normal variate (SNV), and then, we selected the corresponding position variable and vegetation indexes as spectral features. Representative features including the most information were chose by principal component analysis (PCA). A novel back propagation (BP) neural network, with a self‐generated number of hidden layer neurons, was proposed. Using spectral features, image features, and spectral image fusion features as input, three fresh tea recognition models were established: the improved BP neural network, traditional BP neural network, and support vector machine (SVM). Results suggested that the improved BP neural network could promote performance of the model, especially for the spectral pre‐processed data. Mixed‐feature models did better than individual feature models, with 100% accuracy of the predictive set. This study shows that hyperspectral imaging technology can be a potential rapid and nondestructive approach to identify different varieties of Longjing fresh teas. Practical applications This article introduced application of hyperspectral imaging technology to identify Longjing fresh tea of different origins and varieties. Samples were analyzed using spectral and image characteristics. We provided a basis for full utilization of tea characteristics. At the same time, an improved BP neural network, with less calculation complexity and workload than the traditional BP neural network, was proposed. In summary, we outlined a convenient and reliable method for differentiation of Longjing fresh teas. Furthermore, we established a theoretical foundation for development of portable instruments to be used in similar studies.