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Eyewitness Recognition Is a Aesthetic Lookup Task.
Besides, the B-TiO2/NDIEHTh@Au-Pd NHs photoanode offers a significantly cathodically shifted water oxidation potential, reduced charge transfer resistance, better surface injection efficiency, and most importantly, superior photostability compared to the B-TiO2/NDIEHTh NHs photoanode. The enhancement in the different photoelectrochemical performances could be attributed to the various advantages of LSPR, such as enhanced light absorbance, light concentration, hot electron injection, and plasmon-induced resonance energy transfer.Multi-dimensional metal oxides have become a promising alternative electrode material for supercapacitors due to their inherent large surface area. Herein, P-doped NiCo2O4/NiMoO4 multi-dimensional nanostructures are synthesized on carbon clothes (CC) with a continuous multistep strategy. Especially, P has the best synergistic effect with transition metals, such as optimal deprotonation energy and OH- adsorption energy, which can further enhance electrochemical reaction activity. For the above reasons, the P-NiCo2O4/NiMoO4@CC electrode exhibits an ultra-high specific capacitance of 2334.0 F g-1 at 1 A g-1. After 1500 cycles at a current density of 10 A g-1, its specific capacity still maintains 93.7%. Besides, a P-NiCo2O4/NiMoO4@CC//activated carbon device (hybrid supercapacitor or device) was also prepared with a maximum energy density of 45.1 Wh kg-1 at a power density of 800 W kg-1. In particular, the capacity retention rate is still 89.97% after 8000 cycles due to its excellent structural stability. Our work demonstrates the vast potential of multi-dimensional metal oxides in energy storage.Shape-controlled synthesis is essential for functional nanomaterials, allowing deeper insights intothe relationship between the structures and the catalytic properties. Synthesis of nanocrystals with particular morphologies are usually studied independently among various synthetic methods, those underline that different surface capping ligands or shape-directing agents bring about disparate shapes. However, a single quantitative parameter method is still lacking to realize precise control of well-defined morphology nanocrystals, especially anisotropic structures, which is essential to understanding the growth process of nanocrystals. Herein, we proposed a single-parameter-tuned synthesis strategy for preparation of shape-controlled gold nanocrystals by regulating the amount of iron carbonyl, by which we produced highly monodisperse Au nanocrystals with various shapes in organic phase including nanoplates (diameter of 16.02 ± 1.13 nm and thickness of 5.35 ± 0.58 nm), nanorods (length of 37.53 ± 3.73 nm and width of 5.26 ± 0.37 nm) and nanospheres (diameter of 8.26 ± 0.38 nm). The single-parameter-tuned method reveals the dual roles of iron carbonyl for controlling the shapes of gold nanocrystals including reductant and oxidative etchant and empowers versatility in synthetic methodology for other noble metals. Moreover, catalytic activity shifting in shapes of nanocrystals was revealed based on the reduction of 4-nitrophenol, showing that the as-synthesized Au nanoplates displayed the enhanced catalytic performance with the lowest activation energy. Our work provides a brand-new pathway for shape-controlled synthesis of noble-metal nanocrystals and has a strong practical value in application fields.Most recent research on human tool use highlighted how people might integrate multiple sources of information through different neurocognitive systems to exploit the environment for action. This mechanism of integration is known as "action reappraisal". click here In the present eye-tracking study, we further tested the action reappraisal idea by devising a word-priming paradigm to investigate how semantically congruent (e.g., "nail") vs. semantically incongruent words (e.g., "jacket") that preceded the vision of tools (e.g., a hammer) may affect participants' visual exploration of them. We found an implicit modulation of participants' temporal allocation of visuospatial attention as a function of the object-word consistency. Indeed, participants tended to increase over time their fixations on tools' manipulation areas under semantically congruent conditions. Conversely, participants tended to concentrate their visual-spatial attention on tools' functional areas when inconsistent object-word pairs were presented. These results support and extend the information-integrated perspective of the action reappraisal approach. Also, these findings provide further evidence about how higher-level semantic information may influence tools' visual exploration.Embedded feature selection algorithms, such as support vector machine based recursive feature elimination (SVM-RFE), have proven to be effective for many real applications. However, due to the model selection problem, SVM-RFE naturally suffers from a heavy computational burden as well as high computational complexity. To solve these issues, this paper proposes using an optimized extreme learning machine (OELM) model instead of SVM. This model, referred to as OELM-RFE provides an efficient active set solver for training the OELM algorithm. We also present an effective alpha seeding algorithm to efficiently solve successive quadratic programming (QP) problems inherent in OELM. One of the salient characteristics of OELM-RFE is that it has only one tuning parameter the penalty constant C. Experimental results from work on benchmark datasets show that OELM-RFE tends to have higher prediction accuracy than SVM-RFE, and requires fewer model selection efforts. In addition, the alpha seeding method works better on more datasets.Many schools and universities have seen a significant increase in the spread of COVID-19. As such, a number of non-pharmaceutical interventions have been proposed including distancing requirements, surveillance testing, and updating ventilation systems. Unfortunately, there is limited guidance for which policy or set of policies are most effective for a specific school system. We develop a novel approach to model the spread of SARS-CoV-2 quanta in a closed classroom environment that extends traditional transmission models that assume uniform mixing through air recirculation by including the local spread of quanta from a contagious source. In addition, the behavior of students with respect to guideline compliance was modeled through an agent-based simulation. Estimated infection rates were on average lower using traditional transmission models compared to our approach. Further, we found that although ventilation changes were effective at reducing mean transmission risk, it had much less impact than distancing practices.
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