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This study suggested that slow stamen movement in Lychnis cognata presents pollen gradually to pollinators, representing an adaptation to decrease interference between dehisced and dehiscing anthers and pistils that could promote pollen export and deposits. Adaptations that decrease both male-male sexual interference and male-female sexual interference should be recognized as important selective forces in floral evolution. This study also proposed that other selective pressures, including pollen dispensing mechanisms, pollen longevity, pollinator behavior and weather, might contribute to floral evolution.

Deep learning has become a recent, modern technique for big data processing, with promising results and large potential. For recommender systems, user and item information can be used as input vectors to perform prediction tasks. However, augmenting the number of layers to improve feature extraction will increase the computational complexity considerably and may not achieve the desired results. This paper proposes a method called attention convolution collaborative filtering (Att-ConvCF), which integrates an attention mechanism with a collaborative filtering model to improve the effectiveness of the feature extraction by reassigning the weights of feature vectors. Descriptive documents for the items are used to enrich the background information through a convolutional neural network. Finally, extensive experiments with realworld datasets were performed, and the results showed that Att-ConvCF could effectively extract the feature values of the data and significantly outperform the existing recommendation models. INDEX TERMS Attention mechanism, collaborative filtering, recommender system.

Red mud as a waste material is produced in large quantities by the aluminum industry. Heat activation has been used to enhance sorption capacity of red mud for its beneficial reuse as an effective sorbent. In this study, heat-activated red mud (HARM) was investigated for its Cd(II) sorption capacity under various process conditions (Cd concentration, pH and contact time) using response surface methodology (RSM). Analysis with RSM identified pH as the most important process parameter. The positive correlation between higher pH and greater Cd(II) sorption was likely due to: (i) decreased proton competition with Cd(II) for sorption sites at higher pH; (ii) enhanced sorption via ion exchange by monovalent Cd species from hydrolysis at higher pH; and (iii) improved thermodynamics of sorption at higher pH as protons are being released as products. Further analysis indicated the sorption process was thermodynamically favorable with a negative change in Gibbs free energy. Additionally, the sorption process exhibited a positive change in enthalpy, indicative of endothermic nature of sorption; this is consistent with sorption increase at higher temperature. These findings provide needed insight into the mechanisms underlying Cd(II) sorption by HARM for more effective applications of heat-activated red mud as sorbents for Cd(II) removal.