Despite recent advance in bioinspired adhesives, achieving strong adhesion and sealing hemostasis in aqueous and blood environments is challenging. A hyperbranched polymer (HBP) with a hydrophobic ...backbone and hydrophilic adhesive catechol side branches is designed and synthesized based on Michael addition reaction of multi‐vinyl monomers with dopamine. It is demonstrated that upon contacting water, the hydrophobic chains self‐aggregate to form coacervates quickly, displacing water molecules on the adherent surface to trigger increased exposure of catechol groups and thus rapidly strong adhesion to diverse materials from low surface energy to high energy in various environments, such as deionized water, sea water, PBS, and a wide range of pH solutions (pH = 3 to 11) without use of any oxidant. Also, this HBP adhesive (HBPA) exhibits a robust adhesion to fractured bone, precluding the problem of mismatched surface energy and mechanical properties. The HBPA's adhesion is repeatable in a wet condition. Intriguingly, the HBPA is capable of gluing dissimilar materials with distinct properties. Importantly, introducing long alkylamine into this modular hyperbranched architecture contributes to formation of an injectable hemostatic sealant that can rapidly stop visceral bleeding, especially hemorrhage from deep wound.
A hyperbranched polymer adhesive fabricated using a ternary Michael addition reaction of hydrophobic multi‐vinyl monomers with dopamine demonstrates strong underwater adhesion to diverse materials without any oxidant. This is due to water‐triggered fast coacervation and increased outward exposure of catechols. Introducing long‐chain alkylamine contributes to the formation of an injectable hemostatic sealant that can rapidly stop visceral bleeding, especially hemorrhage from deep wound.
Many studies have demonstrated that moral philosophies, such as idealism and relativism, could be used as robust predictors of judgements and behaviours related to common moral issues, such as ...business ethics, unethical beliefs, workplace deviance, marketing practices, gambling, etc. However, little consideration has been given to using moral philosophies to predict environmentally (un)friendly attitudes and behaviours, which could also be classified as moral. In this study, we have assessed the impact of idealism and relativism using the Ethics Position Theory. We have tested its capacity to predict moral identity, moral judgement of social vs. environmental issues, and self-reported pro-environmental behaviours. The results from an online MTurk study of 432 US participants revealed that idealism had a significant impact on all the tested variables, but the case was different with relativism. Consistently with the findings of previous studies, we found relativism to be a strong predictor of moral identity and moral judgement of social issues. In contrast, relativism only weakly interacted with making moral judgements of environmental issues, and had no effects in predicting pro-environmental behaviours. These findings suggest that Ethics Position Theory could have a strong potential for defining moral differences between environmental attitudes and behaviours, capturing the moral drivers of an attitude-behaviour gap, which continuously stands as a barrier in motivating people to become more pro-environmental.
The refractive index of seawater is one of the essential parameters in ocean observation, so it is necessary to achieve high-precision seawater refractive index measurements. In this paper, we ...propose a method for measuring the refractive index of seawater, based on a position-sensitive detector (PSD). A theoretical model was established to depict the correlation between laser spot displacement and refractive index change, utilizing a combination of a position-sensitive detector and laser beam deflection principles. Based on this optical measurement method, a seawater refractive index measurement system was established. To effectively enhance the sensitivity of refractive index detection, a focusing lens was incorporated into the optical path of the measuring system, and simulations were conducted to investigate the impact of focal length on refractive index sensitivity. The calibration experiment of the measuring system was performed based on the relationship between the refractive index of seawater and underwater pressure (depth). By measuring laser spot displacement at different depths, changes in displacement, with respect to both refractive index and depth, were determined. The experimental results demonstrate that the system exhibits a sensitivity of 9.93×10-9 RIU (refractive index unit), and the refractive index deviation due to stability is calculated as ±7.54×10-9 RIU. Therefore, the feasibility of this highly sensitive measurement of seawater refractive index is verified. Since the sensitivity of the refractive index measurement of this measurement system is higher than the refractive index change caused by the wake of underwater vehicles, it can also be used in various applications for underwater vehicle wake measurement, as well as seawater refractive index measurement, such as the motion state monitoring of underwater navigation targets such as AUVs and ROVs.
The seawater refractive index is an essential parameter in ocean observation, making its high-precision measurement necessary. This can be effectively achieved using a position-sensitive ...detector-based measurement system. However, in the actual measurement process, the impact of the jitter signal measurement error on the results cannot be ignored. In this study, we theoretically analysed the causes of long jitter signals during seawater refractive index measurements and quantified the influencing factors. Through this analysis, it can be seen that the angle between the two windows in the seawater refractive index measurement area caused a large error in the results, which could be effectively reduced by controlling the angle to within 2.06°. At the same time, the factors affecting the position-sensitive detector’s measurement accuracy were analysed, with changes to the background light, the photosensitive surface’s size, and the working environment’s temperature leading to its reduction. To address the above factors, we first added a 0.9 nm bandwidth, narrow-band filter in front of the detector’s photosensitive surface during system construction to filter out any light other than that from the signal light source. To ensure the seawater refractive index’s measuring range, a position-sensitive detector with a photosensitive surface size of 4 mm × 4 mm was selected; whereas, to reduce the working environment’s temperature variation, we partitioned the measurement system. To validate the testing error range of the optimised test system, standard seawater samples were measured under the same conditions, showing a reduction in the measurement system’s jitter signal from 0.0022 mm to 0.0011 mm, before and after optimisation, respectively, as well as a reduction in the refractive index’s deviation. The experimental results show that the refractive index of seawater was effectively reduced by adjusting the measurement system’s optical path and structure.
Abstract Data scarcity is one of the critical bottlenecks to utilizing machine learning in material discovery. Transfer learning can use existing big data to assist property prediction on small data ...sets, but the premise is that there must be a strong correlation between large and small data sets. To extend its applicability in scenarios with different properties and materials, here we develop a hybrid framework combining adversarial transfer learning and expert knowledge, which enables the direct prediction of carrier mobility of two-dimensional (2D) materials using the knowledge learned from bulk effective mass. Specifically, adversarial training ensures that only common knowledge between bulk and 2D materials is extracted while expert knowledge is incorporated to further improve the prediction accuracy and generalizability. Successfully, 2D carrier mobilities are predicted with the accuracy over 90% from only crystal structure, and 21 2D semiconductors with carrier mobilities far exceeding silicon and suitable bandgap are successfully screened out. This work enables transfer learning in simultaneous cross-property and cross-material scenarios, providing an effective tool to predict intricate material properties with limited data.
•Walking reduces pre-stimulus alpha power and increases N1 amplitude.•Pre-stimulus alpha predicts N1, P3, and behavior but not post-stimulus alpha.•Post-stimulus alpha power is less modulated by the ...stimulus during walking.•The effect of walking on post-stimulus alpha is dependent on stimulus features.
Walking influences visual processing but the underlying mechanism remains poorly understood. In this study, we investigated the influence of walking on pre-stimulus and stimulus-induced visual neural activity and behavioural performance in a discrimination task while participants were standing or freely walking. The results showed dissociable pre- and post-stimulus influences by the movement state. Walking was associated with a reduced pre-stimulus alpha power, which predicted enhanced N1 and decreased P3 components during walking. This pre-stimulus alpha activity was additionally modulated by time on the task, which was paralleled by a similar behavioural modulation. In contrast, the post-stimulus alpha power was reduced in its modulation due to stimulus onset during walking but showed no evidence of modulation by time on the task. Additionally, stimulus parameters (eccentricity, laterality, distractor presence significantly influenced post-stimulus alpha power, whereas the visually evoked components showed no evidence of such an influence. There was further no evidence of a correlation between pre-stimulus and post stimulus alpha power. We conclude that walking has two dissociable influences on visual processing: while the walking induced reduction in alpha power suggests an attentional state change that relates to visual awareness, the post-stimulus influence on alpha power modulation indicates changed spatial visual processing during walking.
Offshore wind power, with accelerated declining levelized costs, is emerging as a critical building-block to fully decarbonize the world's largest CO
emitter, China. However, system integration ...barriers as well as system balancing costs have not been quantified yet. Here we develop a bottom-up model to test the grid accommodation capabilities and design the optimal investment plans for offshore wind power considering resource distributions, hourly power system simulations, and transmission/storage/hydrogen investments. Results indicate that grid integration barriers exist currently at the provincial level. For 2030, optimized offshore wind investment levels should be doubled compared with current government plans, and provincial allocations should be significantly improved considering both resource quality and grid conditions. For 2050, offshore wind capacity in China could reach as high as 1500 GW, prompting a paradigm shift in national transmission structure, favoring long-term storage in the energy portfolio, enabling green hydrogen production in coastal demand centers, resulting in the world's largest wind power market.
Abstract Background As the significance of artificial intelligence (AI) continues to increase, there is a need for effective scaffolding and support for novice learners. Educators have encountered ...challenges in effectively scaffolding novice learners AI concepts, and providing appropriate motivational support. Research evidence has shown the potential of game‐based approaches to fostering secondary school students' AI literacy and motivation to learn AI. Objectives This study developed an online platform TreasureIsland to gamify ebooks and investigated whether and how students playing with it can effectively enhance their AI literacy. This study aims to contribute an empirical and theoretical basis for AI literacy education and promote the use of gamification that would be broadly applied in other schools. Methods A quasi‐experiment was conducted to evaluate the effects of the proposed gamified approach, which included a control group using an ebook with playful resources. To triangulate the quantitative results obtained from the pre and post‐test, focus group interviews were also conducted. Results The platform was effective in improving students' motivation, self‐efficacy, career interest, and understanding of AI concepts and ethics, but did not enhance their confidence of using AI, and high cognition of applying, evaluating and creating AI. TreasureIsland players demonstrated significant improvement in all affective and cognitive domains, except for the ability to apply, evaluate, and create AI. Interviews revealed that the gamified approach could promote students' AI literacy by adhering to guidelines, including (1) creating a competitive and motivating learning environment through game mechanics, (2) providing scaffolding modules and feedback, and (3) visualising complex AI concepts via simulations. Feedback collected from the study suggested adding pedagogical elements such as flipped classrooms and project‐based learning in future research to improve the instructional design, and enable students to reach a higher level of cognition. Conclusions This study concludes that the use of gamification can provide affective and cognitive support and an enjoyable experience for fostering learners' AI literacy. It helps instructional designers and teachers enrich the pedagogical knowledge related to gamified platform and AI literacy.
Lay Description What is already known about this topic AI literacy is considered as an important digital literacy skill that many secondary schools started to incorporate AI in computer/STEAM curricula. Game‐based approach has been incorporated to foster students' AI literacy and knowledge. Gamification is increasingly used to enhance students' digital literacy skills and learning motivation. What this paper adds We designed a platform to gamify ebooks and compared the effects using merely ebook using a mixed‐methods case study design. Gamifying ebooks can lead to improvement in AI literacy, affective and cognitive engagement. While this pedagogy fostered students' AI knowledge and understanding, it cannot effectively enhance students' higher cognition skills. Implications for practice and/or policy We synthesised the evidence that shows the effectiveness of gamification to foster students' learning motivation, basic understanding of AI knowledge and ethics. We updated the AI literacy framework and explored the relations between students' engagement, and AI knowledge. This study proposed a meaningful measure of AI literacy development through considering affective and cognitive domains.
Abstract
The Japanese government has announced a commitment to net-zero greenhouse gas emissions by 2050. It envisages an important role for hydrogen in the nation’s future energy economy. This paper ...explores the possibility that a significant source for this hydrogen could be produced by electrolysis fueled by power generated from offshore wind in China. Hydrogen could be delivered to Japan either as liquid, or bound to a chemical carrier such as toluene, or as a component of ammonia. The paper presents an analysis of factors determining the ultimate cost for this hydrogen, including expenses for production, storage, conversion, transport, and treatment at the destination. It concludes that the Chinese source could be delivered at a volume and cost consistent with Japan’s idealized future projections.
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