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As an important issue in sentiment analysis, sentence-level polarity classification plays a critical role in many opinion-mining applications such as opinion question answering, opinion retrieval and opinion summarization. Employing a supervised learning paradigm to train a classifier from sentences often faces the data sparseness problem owing to the short-length limit introduced to texts. In this article, regarding this problem, we exploit two different feature sets learned from external data sets as additional features to enrich data representation: one is a latent topic feature set obtained using a topic model, and the other is a related word feature set derived using word embeddings. Furthermore, we propose an ensemble approach by using these additional features to guide the design of different members of the ensemble. Experimental results on the public movie review dataset demonstrate that the enriched representations are effective for improving the performance of polarity classification, and the proposed ensemble approach can further improve the overall performance.

We investigate the coherent perfect absorption laser points (CPA-LPs) in anti-parity–time-symmetric photonic crystals. CPA-LPs, which correspond to the poles of reflection and transmission, can be found in the parameter space composed of gain–loss factor and angular frequency. Discrete exceptional points (EPs) split as the gain–loss factor increases. The CPA-LPs sandwiched between the EPs are proved to be defective modes. The localization of light field and the bulk effect of gain/loss in materials induce a sharp change in phase of the reflection coefficient near the CPA-LPs. Consequently, a large spatial Goos–Hänchen shift, which is proportional to the slope of phase, can be achieved around the CPA-LPs. The study may find great applications in highly sensitive sensors.

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Four saline lakes in the northeast of Qaidam Basin were selected to explore the distribution characteristics and influencing factors of uranium isotopes in lake waters with high evaporation background. The 238U concentration and the activity ratios of 234U/238U ([234U/238U]AR) showed that there was no significant change in the same lake, but there was a certain degree of difference in the distribution between different lakes. We found that aqueous 238U concentration within a certain range increased with an increase in TDS (total dissolved solid) and salinity, as was also the case with pH. As in natural waters, the pH affects the speciation of 238U, but TDS and salinity affect the adsorption process of aqueous 238U. Further, the replenishment of water will also affect the uranium isotope concentration for lakes, but it is not the main influencing factor for saline lakes. Therefore, we suggest that pH is the dominant factor affecting changes in aqueous 238U concentration of the sampled saline lakes. The [234U/238U]AR in these saline lakes are closely related to the input water and the associated water–rock interactions involving sediments, atmosphere dust, and organic material, etc. during the evolution stage, metamorphous degree, and hydrochemistry of the saline lakes. Lake water samples collected in the maximum and minimum discharge water period, were used to evaluate the seasonal distribution characteristics of aqueous 238U, and we found that 238U concentration did not show an evident change with the seasons in these saline lakes. If the 238U concentration and [234U/238U]AR can remain consistent during a period of time, then the sediment ages and/or sedimentation rates could be determined by lake sediment and/or biogenic carbonate in future, thus allowing for the accurate reconstruction of the paleoclimate and paleoenvironment.