The development of scalable and passive coatings that can adapt to seasonal temperature changes while maintaining superhydrophobic self‐cleaning functions is crucial for their practical applications. ...However, the incorporation of passive cooling and heating functions with conflicting optical properties in a superhydrophobic coating is still challenging. Herein, an all‐in‐one coating inspired by the hierarchical structure of a lotus leaf that combines surface wettability, optical structure, and temperature self‐adaptation is obtained through a simple one‐step phase separation process. This coating exhibits an asymmetrical gradient structure with surface‐embedded hydrophobic SiO2 particles and subsurface thermochromic microcapsules within vertically distributed hierarchical porous structures. Moreover, the coating imparts superhydrophobicity, high infrared emission, and thermo‐switchable sunlight reflectivity, enabling autonomous transitions between radiative cooling and solar warming. The all‐in‐one coating prevents contamination and over‐cooling caused by traditional radiative cooling materials, opening up new prospects for the large‐scale manufacturing of intelligent thermoregulatory coatings.
Inspired by the longitudinal gradient and surface structure of the lotus leaf, this study presents an all‐in‐one coating that integrates superhydrophobicity, thermal‐responsive sunlight reflectivity, and high infrared emission through a simple one‐step process. The coating enables automatic transitions between radiative cooling and solar warming, preventing overcooling and contamination, offering a novel approach for large‐scale production of smart thermoregulatory coatings.
Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is ...to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision.
•A multiple flood vulnerability assessment approach is proposed.•The approach is based on FCEM and CDDM.•Relationship between exposure, sensitivity, and adaptive capacity is considered.•Six multiple flood vulnerability types and four levels are developed.•A decision-making process for rational allocation of limited resources is proposed.
Isolation bearings have been a widely applied seismic strengthening technique in above ground structures. Whereas, the sliding isolation bearings were seldom used in underground structures. This ...study aims to explore the feasibility of sliding isolation bearings reducing the seismic response of underground structures. The collapse mechanism of underground structures was firstly analyzed by taking the Daikai Station as an example. Numerical results demonstrated that the collapse of the structure was due to the poor ductility of the intermediate columns. Therefore, the sliding isolation bearing could be installed between the columns and the beam to reduce the lateral deformations of columns. In order to determine an appropriate coefficient for sliding bearings, static analyses for the capacity of columns were conducted. Moreover, the performances of a beam-bearing-column system were also investigated. Finally, seismic responses of the underground structure retrofitted with bearings were studied. Numerical results presented that the responses of both columns and the whole structure were reduced remarkably. Moreover, the frictional coefficient of bearing influencing the seismic responses of underground structures was discussed. And some interesting conclusions were also obtained for the seismic design of underground structures.
With the development of positive psychology, prosocial behavior has received widespread attention from researchers. Some studies have shown that emotion has a significant influence on individual ...prosocial behavior, but little research has studied the effect of different types of empathy on college students' prosocial behaviors. The current study examined the mediating effects of gratitude among the associations between different types of empathy (perspective-taking, fantasy, empathic concern, and personal distress) and prosocial behavior among Chinese college students. For the study, we used the Prosocial Tendency Measurement questionnaire, the Hebrew version of Interpersonal Reactivity Index-C, and The Gratitude Questionnaire that investigated 1,037 participants. The results indicated that gratitude played a mediating role between perspective-taking and prosocial behavior, fantasy and prosocial behavior, empathic concern and prosocial behavior, and personal distress and prosocial behavior, respectively. The current study contributes to a better understanding of the relationship between empathy and prosocial behavior.
•We detect the impacting mechanisms of investor attention on crude oil prices.•We construct a proxy for investor attention in crude oil market based on the GSVI.•Investor attention has significant ...negative impact on oil prices during 2004–2016.•Investor attention contributes 15% to the long-run fluctuation of WTI oil prices.
In order to investigate the impacting mechanism of investors’ attention and crude oil prices, we construct a direct, timely and unambiguous proxy for investor attention in crude oil market by aggregating the Google search volume index (GSVI). Based on the GSVI, we employ the Structural Vector Autoregression (SVAR) model to empirically explore the impact of investor attention on WTI crude oil price from January 2004 to November 2016. The results indicate that: (1) investor attention does have significant negative impact on WTI crude oil price during the sample period; (2) investor attention shocks contributes 15% to the long-run fluctuation of WTI crude oil price during the sample period, which is second only to that of supply shocks (69%) among the contributors concerned; and (3) when the business cycle stays in expansion, it has positive influence on both investor attention and WTI crude oil price. Meanwhile, our robustness check, using Brent crude oil price and a different construction form of the GSVI, confirms that the central results are reliable.
A series of Mn-Co-Ni-O/LaMnO3 composite materials were synthesized through the sol-gel method. The structure of these powders changed from the spinel to a spinel-perovskite mixed phase as the content ...of LaMnO3 increased from 0 to 50%. Meanwhile, some grains of composite material were refined to form many small particles and distributed among the porous microparticles. According to the absorption spectra of composite samples, the strong absorption structures appeared in visible ranges, especially between 400 and 730 nm. The photocatalytic degradation of tetracycline under the visible light irradiation indicated that the percentage of LaMnO3 at 50% exhibited the highest degradation rate (70.2%) in 150 min. Its high photocatalytic activity was mainly due to the large surface area, strong visible light absorption and increased ratio of Mn3+/Mn4+ ions. These new micro-structured photocatalysts were expected to show considerable potential applications in the water treatment.
Hydrogen has become a versatile and clean alternative to meet increasingly urgent energy demands since its high heating value and renewability. However, considering the hazards of hydrogen storage ...and transport, in-situ production processes are drawing more attention. Among all the hydrogen carriers, methanol has become one of the research focuses due to its high H/C ratio, flexibility and sustainability. Regarded as the core of hydrogen supply system, catalysts with higher activity, selectivity and stability are continuously developed for improved efficiency. In this review, two groups of catalysts were investigated namely copper-based and group VIII metal-based catalysts. Not only macro indicators such as feedstock conversion and product selectivity, but also micro interaction and reaction mechanism were elaborated, with respect to the effects of promoters, supports, synthesis methods and binary metal components. Notably, several reaction pathways and catalysts deactivation mechanisms were suggested based on this series of inspection of the structure-reactivity relationship, along with a general perception that large surface area, well dispersed metals, small particle size and synergy effects significantly improve the catalytic performance. Accordingly, a novel concept of single-atom catalysts (SACs) was introduced aimed at efficient hydrogen production under more moderate conditions, by combining the advantages of heterogeneous and homogeneous catalysis. Additionally, an efficient reforming process is required by properly regulating the feed flow and heat flow through a coupled system. Conclusively, a thorough supply and demand network of hydrogen based on methanol was presented, giving an overview for on-board applications of hydrogen energy.
•H2 production from CH3OH reforming proves potential for on-board applications.•Flexible reforming processes are suggested for ICEs, SOFCs and PEMFCs.•Advanced preparation methods and experimental results are investigated in detail.•In-depth mechanism elaboration and SACs are involved for further research.•A supply-demand network of hydrogen from methanol reforming is suggested.
Abstract
Atomically dispersed transition metals on carbon-based aromatic substrates are an emerging class of electrocatalysts for the electroreduction of CO
2
. However, electron delocalization of ...the metal site with the carbon support via d-π conjugation strongly hinders CO
2
activation at the active metal centers. Herein, we introduce a strategy to attenuate the d-π conjugation at single Ni atomic sites by functionalizing the support with cyano moieties. In situ attenuated total reflection infrared spectroscopy and theoretical calculations demonstrate that this strategy increases the electron density around the metal centers and facilitates CO
2
activation. As a result, for the electroreduction of CO
2
to CO in aqueous KHCO
3
electrolyte, the cyano-modified catalyst exhibits a turnover frequency of ~22,000 per hour at −1.178 V versus the reversible hydrogen electrode (RHE) and maintains a Faradaic efficiency (FE) above 90% even with a CO
2
concentration of only 30% in an H-type cell. In a flow cell under pure CO
2
at −0.93 V versus RHE the cyano-modified catalyst enables a current density of −300 mA/cm
2
with a FE above 90%.
Visual object tracking is challenging as target objects often undergo significant appearance changes caused by deformation, abrupt motion, background clutter and occlusion. In this paper, we exploit ...features extracted from deep convolutional neural networks trained on object recognition datasets to improve tracking accuracy and robustness. The outputs of the last convolutional layers encode the semantic information of targets and such representations are robust to significant appearance variations. However, their spatial resolution is too coarse to precisely localize targets. In contrast, earlier convolutional layers provide more precise localization but are less invariant to appearance changes. We interpret the hierarchies of convolutional layers as a nonlinear counterpart of an image pyramid representation and exploit these multiple levels of abstraction for visual tracking. Specifically, we adaptively learn correlation filters on each convolutional layer to encode the target appearance. We hierarchically infer the maximum response of each layer to locate targets. Extensive experimental results on a largescale benchmark dataset show that the proposed algorithm performs favorably against state-of-the-art methods.
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