Search

Accurately predicting whether a short video will be liked by viewers is a topic of interest to media researchers. This study used an electroencephalogram (EEG) to record neural activity in 109 participants as they watched short videos (16 clips per person) to see which neural signals reflected viewers' preferences. The results showed that, compared with the short videos they disliked, individuals would experience positive emotions [indexed by a higher theta power, lower (beta – theta)/(beta + theta) score], more relaxed states (indexed by a lower beta power), lower levels of mental engagement and alertness [indexed by a lower beta/(alpha + theta) score], and devote more attention (indexed by lower alpha/theta) when watching short videos they liked. We further used artificial neural networks to classify the neural signals of different preferences induced by short videos. The classification accuracy was the highest when using data from bands over the whole brain, which was 75.78%. These results may indicate the potential of EEG measurement to evaluate the subjective preferences of individuals for short videos.

Bioinks are employed in the fabrication of 3D scaffolds containing cells and macromolecules that can be applied in regenerative medicine. The use of such bioinks facilitates the controlled introduction and localization of macromolecules, bioactives and cells for the biofabrication of living tissues. To enable the successful preparation of the bioinks, strategies involving the use of so-called cross linkers, which may be ionic, chemical, photo-etc.based, are employed. Some of these strategies such as the use of glutaraldehyde as a crosslinker or harsh crosslinking conditions may however compromise the cytocompatibility of the bioink. To circumvent this challenge, the employment of click chemistry technology has been proposed. This is because, click chemistry can enable the preparation of well-tuned bioinks in the absence of problematic cross-linkers, while ensuring that favorable gelation rate, degradation rate, and cell viability properties of the bioinks are not compromised. Indeed, the bio-orthogonal nature of click chemistry has been suggested to enhance the maintenance of high cell viability in scaffolds. In this regard, the current study explored the potential of using different click chemistries in specific bioprinting techniques. Major bioinks produced using click chemistry were also identified, with existing challenges and future trends discussed. It is anticipated that this review will be invaluable to the tissue engineering field by providing an important resource for bioengineers and a basis of future decisions regarding the selection of the preferred click chemistry for specific bioink functionalities.

Supervised deep learning models have been widely used in the construction of bearing health indicators (HIs) for performance degradation. Such models require a series of model improvement combinations, which are dependent on manual experience, to extract HIs. Additionally, noise leads to a large, extracted health indicator value that easily exceeds the preset threshold, causing an incorrect evaluation of health status. Therefore, this paper proposes an improved and unsupervised stacked auto-encoder without an output label layer and with local weighted regression and smoothing scatterplot (Lowess). That is, a stacked auto-encoder adds a Lowess filter after each hidden layer to perform multiple de-noising operations. We used encoders and decoders at several hidden layers within a stacked noise auto-encoder (though only with an output layer) to extract HIs and directly eliminate the noise from the original bearing vibration. Hence, our proposed method reduces the modeling complexity. The results show that our proposed method outperforms others of its type, such as stacked auto-encoders, stacked de-noising auto-encoders, deep belief neural networks, root-mean-square kurtosis, empirical mode decomposition, singular-value decomposition-K-medoids, and self-organizing map networks. Moreover, by using the monotonicity evaluating indicator, the extracted HI curve was found to be smoother than in other models and the probability of erroneous judgments for bearing performance degradation assessment was reduced.

In this study, medical hydrogels (TGs) were fabricated based on thiolate-modified chitosan (TCS) and methacrylate gelatin (GelMA) using the Thiol-Michael addition reaction. The hydrogels were formed via the Michael reaction between TCS and GelMA and determined to have an equilibrium swelling rate of more than 1100% while simultaneously providing a moist environment for the wound, and limiting crust formation. The porosity of the prepared hydrogel was also shown to have a positive correlation with the concentration of the thiolated chitosan in the formulation. A positive correlation between hydrogel strain and stress properties and increasing concentrations of thiolated chitosan was also observed. The cytocompatibility of the prepared hydrogels was also tested and confirmed using CCK-8 assay after 5 days of culture, and the best antimicrobial properties were observed with the hydrogel containing TCS and GelMA in the mass ratio of 1:2. The present study was, therefore, able to highlight the potential of a simple and low-cost approach to developing cytocompatible hydrogels with antibacterial properties and tunable mechanical properties based on the well-studied GelMA. This study implies that the produced hydrogels can have future applications in fabricating skin wound healing dressings.

A suspension that can be sprayed onto substrates was developed to form a superhydrophobic/oleophilic surface. Lyophobic slippery surfaces were prepared by infusing perfluorinated lubricants into the superhydrophobic coating to repel almost all liquids with low surface tension values, including hexane, kerosene, and diesel oil, showing a transition between superoleophilicity and lyophobicity. In addition, the traveling speeds of liquids appeared to be negatively correlated with the kinematic viscosity. In the anti-icing tests, the droplet was pinned after contacting a 0 °C textured superhydrophobic surface for a few seconds because of the meniscus caused by the condensation of atmospheric humidity; by contrast, on the lyophobic slippery surface, a water droplet could easily slide even at −20 °C, demonstrating superior icing resistance.

A superhydrophobic steel surface was prepared through a facile method: combining hydrogen peroxide and an acid (hydrochloric acid or nitric acid) to obtain hierarchical structures on steel, followed by a surface modification treatment. Empirical grid maps based on different volumes of H2O2/acid were presented, revealing a wettability gradient from “hydrophobic” to “rose effect” and finally to “lotus effect”. Surface grafting has been demonstrated to be realized only on the oxidized area. As-prepared superhydrophobic surfaces exhibited excellent anti-icing properties according to the water-dripping test under overcooled conditions and the artificial “steam-freezing” (from 50 °C with 90% humidity to the −20 °C condition) test. In addition, the surfaces could withstand peeling with 3M adhesive tape at least 70 times with an applied pressure of 31.2 kPa, abrasion by 400 grid SiC sandpaper for 110 cm under 16 kPa, or water impacting for 3 h without losing superhydrophobicity, suggesting superior mechanical durability. Moreover, outstanding corrosion resistance and UV-durability were obtained on the prepared surface. This successful fabrication of a robust, anti-icing, UV-durable, and anticorrosion superhydrophobic surface could yield a prospective candidate for various practical applications.