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Renewable energy‐driven proton exchange membrane water electrolyzer (PEMWE) attracts widespread attention as a zero‐emission and sustainable technology. Oxygen evolution reaction (OER) catalysts with sluggish OER kinetics and rapid deactivation are major obstacles to the widespread commercialization of PEMWE. To date, although various advanced electrocatalysts have been reported to enhance acidic OER performance, Ru/Ir‐based nanomaterials remain the most promising catalysts for PEMWE applications. Therefore, there is an urgent need to develop efficient, stable, and cost‐effective Ru/Ir catalysts. Since the structure‐performance relationship is one of the most important tools for studying the reaction mechanism and constructing the optimal catalytic system. In this review, the recent research progress from the construction of unsaturated sites to gain a deeper understanding of the reaction and deactivation mechanism of catalysts is summarized. First, a general understanding of OER reaction mechanism, catalyst dissolution mechanism, and active site structure is provided. Then, advances in the design and synthesis of advanced acidic OER catalysts are reviewed in terms of the classification of unsaturated active site design, i.e., alloy, core‐shell, single‐atom, and framework structures. Finally, challenges and perspectives are presented for the future development of OER catalysts and renewable energy technologies for hydrogen production. Highly active, cost‐effective, and durable oxygen evolution reaction catalysts are indispensable for promoting the practical application of proton exchange membrane water electrolyzer. Understanding the structure‐activity relationship of catalysts is an important mean to study reaction mechanism and construct optimal catalytic system. In the review, the recent advanced catalysts are summarized based on the construction of unsaturated coordination sites to provide reference and ideas for the rational design of catalysts.

Political misinformation, astroturfing and organised trolling are online malicious behaviours with significant real-world effects that rely on making the voices of the few sounds like the roar of the many. These are especially dangerous when they influence democratic systems and government policy. Many previous approaches examining these phenomena have focused on identifying campaigns rather than the small groups responsible for instigating or sustaining them. To reveal latent (i.e. hidden) networks of cooperating accounts, we propose a novel temporal window approach that can rely on account interactions and metadata alone. It detects groups of accounts engaging in various behaviours that, in concert, come to execute different goal-based amplification strategies, a number of which we describe, alongside other inauthentic strategies from the literature. The approach relies upon a pipeline that extracts relevant elements from social media posts common to the major platforms, infers connections between accounts based on criteria matching the coordination strategies to build an undirected weighted network of accounts, which is then mined for communities exhibiting high levels of evidence of coordination using a novel community extraction method. We address the temporal aspect of the data by using a windowing mechanism, which may be suitable for near real-time application. We further highlight consistent coordination with a sliding frame across multiple windows and application of a decay factor. Our approach is compared with other recent similar processing approaches and community detection methods and is validated against two politically relevant Twitter datasets with ground truth data, using content, temporal, and network analyses, as well as with the design, training and application of three one-class classifiers built using the ground truth; its utility is furthermore demonstrated in two case studies of contentious online discussions.

Open top chambers (OTCs) were adopted as the recommended warming mechanism by the International Tundra Experiment (ITEX) network in the early 1990’s. Since then, OTCs have been deployed across the globe. Hundreds of papers have reported the impacts of OTCs on the abiotic environment and the biota. Here we review the impacts of the OTC on the physical environment, with comments on the appropriateness of using OTCs to characterize the response of biota to warming. The purpose of this review is to guide readers to previously published work and to provide recommendations for continued use of OTCs to understand the implications of warming on low stature ecosystems. In short, the OTC is a useful tool to experimentally manipulate temperature, however the characteristics and magnitude of warming varies greatly in different environments, therefore it is important to document chamber performance to maximize the interpretation of biotic response. When coupled with long-term monitoring, warming experiments are a valuable means to understand the impacts of climate change on natural ecosystems.

[This corrects the article DOI: 10.3389/fphar.2022.801350.].[This corrects the article DOI: 10.3389/fphar.2022.801350.].

Gold (Au) catalysts exhibit a significant size effect, but its origin has been puzzling for a long time. It is generally believed that supported Au clusters are more or less rigid in working condition, which inevitably leads to the general speculation that the active sites are immobile. Here, by using atomic resolution in situ environmental transmission electron microscopy, we report size-dependent structure dynamics of single Au nanoparticles on ceria (CeO₂) in CO oxidation reaction condition at room temperature. While large Au nanoparticles remain rigid in the catalytic working condition, ultrasmall Au clusters lose their intrinsic structures and become disordered, featuring vigorous structural rearrangements and formation of dynamic low-coordinated atoms on surface. Ab initio molecular-dynamics simulations reveal that the interaction between ultrasmall Au cluster and CO molecules leads to the dynamic structural responses, demonstrating that the shape of the catalytic particle under the working condition may totally differ from the shape under the static condition. The present observation provides insight on the origin of superior catalytic properties of ultrasmall gold clusters.

Background: Both cognitive function and cardiorespiratory fitness are significant correlates of physical and mental health. The exploration of innovative school-based PA intervention strategies to improve cognitive function and cardiorespiratory fitness is of great interest for researchers and school educators. This study aimed at examining the effectiveness of the coordinated-bilateral ball skills (CBBS) intervention in improving cognitive function and cardiorespiratory fitness among 4th-grade students. Methods: This study used a two-arm, quasi-experimental research design. The students (n = 347) in the intervention group received 16-weeks of CBBS intervention lessons in basketball and soccer. The students (n = 348) in the comparison group received 16-weeks of regular basketball and soccer lessons. All participants were pre- and post-tested with the d2 Test of Attention and the Progressive Aerobic Cardiovascular Endurance Run (PACER) test before and after the 16-week CBBS intervention. The data were analyzed by means of descriptive statistics and linear mixed models. Results: The linear mixed models yielded a marginal significant interaction effect of time with the group in their concentration (F(1, 680.130) = 3.272, p = 0.071) and a significant interaction effect of time with the group in their attention span (F(1, 785.108) = 4.836, p = 0.028) while controlling for age and the baseline concentration score. The linear mixed model also revealed a significant main effect of time in focused attention (F(1670.605) = 550.096, p = 0.000), attention accuracy (F(1, 663.124) = 61.542, p = 0.000), and cardiorespiratory fitness (F(1, 680.336) = 28.145, p = 0.000), but no significant interaction effect. Conclusions: The CBBS group demonstrated a significant improvement in concentration performance and attention span over time, compared to the comparison group. Both groups improved their focused attention and attention accuracy as well as cardiorespiratory fitness over time. This study suggests that teaching ball skills in team sports for extended periods is instrumental to developing cognitive functions and cardiorespiratory fitness, though the CBBS lessons resulted in greater improvement in concentration performance and attention span.

In this paper, we prove the Hermite–Hadamard–Fejér type inequalities for coordinated h1,h2-convex functions on the rectangle from the plane R2. Some generalizations of the Hermite–Hadamard-type inequalities of two variables are also obtained as a consequence. Some properties of two functionals which are connected with the coordinated h1,h2-convex functions are provided as well. Finally, we give applications of the acquired results to special means of positive real numbers.

In the digital age, digital collection and recording technology can handle various types of tangible and intangible cultural heritage. Virtual tourism technology for cultural heritage has great potential in providing users with personalized experiences, but it also faces the problem of ignoring the personalized needs of different users. To this end, a user behavior classification model for cultural heritage virtual tourism technology and a cultural heritage virtual tourism recommendation model based on matrix factorization and coordinated filtering were developed. In the classification task, this study used Virtual Reality scene action data collected from HTC VIVO devices. In the recommendation task, MovieLens, Amazon-charts, ciao, and Epinions datasets were used. The findings denoted that the accuracy of the raised user behavior classification model was 85.47%, 94.62%, and 80.17% in the controller, head mounted display, and button data, respectively. In the mixed data source, the classification accuracy of the proposed model was 98.42%, and the F1 value was 97.74%. The Recall@20 of virtual tour recommendation model in MovieLens and Amazon-charts Dataset were 72.36% and 72.84%, respectively, with diversity values ranging from 0.7 to 0.9. On the Ciao dataset and Epinions dataset, the Root Mean Squared Error and Mean Absolute Error of the proposed model were 0.937 and 0.701, 1.033 and 0.796, respectively. The experimental results demonstrated that the proposed model improved classification and recommendation performance by innovatively combining additive attention mechanism, contextual multi-arm slot machine algorithm, and deep analysis of user behavior, surpassing standard matrix factorization and collaborative filtering methods. The research results help improve the display and service quality of cultural heritage virtual exhibition halls, effectively protect and inherit intangible cultural heritage, and promote the digital development of cultural resources.

To address the vulnerability of renewable-dominated power grids to cascading failures under extreme conditions and the limitations of existing methods in jointly handling vulnerability identification, energy storage allocation, and online control, this paper proposes an energy-storage-assisted coordinated defense strategy. First, a source-load uncertainty model is constructed and seven typical extreme operating scenarios are identified. Second, a cascading-failure evolution model that accounts for thermal accumulation is established to identify critical vulnerable branches. Third, for areas prone to local disconnection and weak terminal voltages, a coordinated ESS allocation model is developed by jointly considering active power, energy capacity, and reactive power support to determine candidate deployment locations and capacities. Finally, a graph neural network (GNN) is used to extract time-varying topological and electrical-state features, and proximal policy optimization (PPO) is employed to generate coordinated control commands for multiple ESSs, thereby linking overload suppression with voltage support. The results for the modified IEEE 39-bus system show that the proposed method identifies high-risk branches more accurately and forms an integrated defense chain covering identification, allocation, and control. The method reduces thermal stress in critical sections during the early stage of a fault, mitigates load shedding, and enhances system survivability.

Supramolecular adhesives, praised for their stimuli‐responsiveness and reversibility, have gained significant attention. However, most of these adhesives demonstrate low tolerance to extreme environments and exhibit diminished adhesion performance after cyclic adhesion testing. Herein, a hierarchical self‐assembly strategy is introduced for the construction of supramolecular polymer networks (poly(UIO‐TA)) through dynamic disulfide bond crosslinking‐induced assembly of metal‐coordinated nanoparticles (UIO‐TA). The UIO‐TA were synthesized via a stepwise coordination‐driven assembly process, wherein the zirconium ion coordinated with terephthalic acid and thioctic acid. Furthermore, these UIO‐TA were crosslinked through ring‐opening polymerization of dynamic disulfide bonds, resulting in the formation of poly(UIO‐TA). Poly(UIO‐TA) exhibited tough, durable, and reversible adhesion on diverse substrates, maintaining its effectiveness under mild to harsh conditions, including high temperatures (120 °C), organic solvents (e.g., dimethyl sulfoxide, ethanol), and strong acids (e.g., sulfuric acid). The adhesion performance of poly(UIO‐TA) is superior to poly(thioctic acid) (poly(TA)) and most reported supramolecular adhesives. These attributes can be ascribed to the synergistic interplay of metal coordination bonds, hydrogen bonds, and dynamic disulfide bonds. Notably, after the five‐cycle adhesion tests, the adhesion strength of poly(UIO‐TA) increased by ≈2.5 times, which can primarily be attributed to increased cohesion energy resulting from the further ring‐opening polymerization of disulfide bonds. A supramolecular polymer network is constructed through the assembly of metal‐coordinated nanoparticles induced by the crosslinking of dynamic covalent disulfide bond. The resulting supramolecular adhesive exhibited excellent adhesion performance, including strong adhesion strength, exceptional solvent resistance, and distinct reversible adhesion.