Sentiment analytics, as a computational method to extract emotion and detect polarity, has gained increasing attention in tourism research. However, issues regarding how to properly apply sentiment analytics are seldom addressed in the tourism literature. This study addresses such methodological challenges by employing the metalearning perspective to examine the design effects on predictive accuracy using a sentiment analysis experiment for Chinese travel news. Our results reveal strong interactions among key design factors of sentiment analytics on predictive accuracy; accordingly, this study formulates a metalearning framework to improve predictive accuracy for computational tourism research. Our study attempts to highlight and improve the methodological relevance and appropriateness of sentiment analytics for future tourism studies.

Reversibly fluorescent switchable materials have important applications in the fields of ultrahigh-density optical data storage, molecular switches, logic gates, molecular wires, optical/electronic devices, sensors, bioimaging and so on. Some systems have been developed based on smart luminescent polymers and organic photoswitchable molecules. However, the use of such materials for practical applications is dramatically restricted by their intrinsic drawbacks such as low ON/OFF ratios, irreversibility and poor environmental resistance. An imperative challenge toward real applications is to design and fabricate photoluminescence switching devices with high on/off contrast and fast response time, and especially to obtain multicolored systems, in which the photoluminescence wavelength can be easily tuned in the visible region. Here we report the first inorganic example of a multicolored photoluminescence switching system by controlling the organization of crown-type polyoxometalates (POMs) and CdSe@CdS core-shell quantum dots (QDs) into the layer-by-layer (LBL) nanostructures. The photoluminescence of this system can be switched on and off reversibly upon application of step potentials for different redox states, owing to the energy transfer between reduced POMs and QDs. This system displays a quick response (off 17 s, on 38 s), high on/off contrast ($91%), good cycling performance (the modulation ratio is only decreased by 19% after 200 cycles) and also has the advantage of low power consumption. Furthermore, reversible four-state fluorescence switching is realized by integrating different-sized QDs in one multifunctional system.

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A carbon nanotube (CNT) based nanoarchitecture is developed for rapid, sensitive and specific detection of cancer cells by using real time electrical impedance sensing. The sensor is constructed with carbon nanotube (CNT) multilayers and EpCAM (epithelial cell adhesion molecule) antibodies, which are assembled on an indium tin oxide (ITO) electrode surface. The binding of tumor cells to EpCAM antibodies causes increase of the electron-transfer resistance. The electrochemical impedance of the prepared biosensors is linear with the logarithm of concentration of the liver cancer cell line (HepG2) within the concentration range of 10 to 10(5) cells per mL. The detection limit for HepG2 cells is 5 cells per mL. The proposed impedimetric sensing devices allow for sensitive and specific detection of cancer cells in whole-blood samples without any sample pretreatment steps.

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