Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney,Melbourne and Brisbane

In recent years, artificial intelligence (AI) is being increasingly utilised in disaster management activities. The public is engaged with AI in various ways in these activities. For instance, crowdsourcing applications developed for disaster management to handle the tasks of collecting data through social media platforms, and increasing disaster awareness through serious gaming applications. Nonetheless, there are limited empirical investigations and understanding on public perceptions concerning AI for disaster management. Bridging this knowledge gap is the justification for this paper. The methodological approach adopted involved: Initially, collecting data through an online survey from residents (n = 605) of three major Australian cities; Then, analysis of the data using statistical modelling. The analysis results revealed that: (a) Younger generations have a greater appreciation of opportunities created by AI-driven applications for disaster management; (b) People with tertiary education have a greater understanding of the benefits of AI in managing the pre- and post-disaster phases, and; (c) Public sector administrative and safety workers, who play a vital role in managing disasters, place a greater value on the contributions by AI in disaster management. The study advocates relevant authorities to consider public perceptions in their efforts in integrating AI in disaster management.     

城市街道峡谷单侧自然通风研究进展

自然通风广泛存在于城市之中，了解城市自然通风建筑室内环境质量现状及存在的问题，是改善城市建筑室内环境质量的基础. 通过文献整理，首先研究城市街道峡谷中单侧自然通风的驱动因素，其次从建筑几何特征、通风能力、污染率、颗粒物浓度以及街谷设施等方面综述单侧自然通风的相关研究，最后提出建议. 研究表明，合理的展弦比、更好的城市布局以及精心的街谷设施设计能够最大限度地利用单侧自然通风，提升城市街道峡谷的室内环境品质.     

自重湿陷性黄土地基预钻孔浸水处理的可靠度设计方法

为解决传统预浸水法存在的浸水时间长、浸水处理范围难以确定等不足,基于土体中水分运移规律,依据可靠度理论、极限状态设计方法及复合 Poisson 过程原理,提出一种消除黄土湿陷性的处理浸水方法——预钻孔浸水法。给出了利用预钻孔浸水法对自重湿陷性黄土地基进行浸水时,水平向及竖直向浸水影响范围的确定模型;在此基础上结合达西定律给出了浸水孔设计参数如孔深、孔间距及浸水孔个数的确定方法。结合铜川某工程,设计进行了现场预钻孔浸水试验,对该方法的合理性进行了验证,并通过现场钻探、现场勘探、室内湿陷性试验等方法对该方法的处理效果进行了评价。该浸水方法具有浸水时间短、浸水影响范围可根据浸水孔布设进行控制等优点,且浸水处理效果良好,完全符合施工要求。     

Additive manufacturing,quasi-static and dynamic compressive behaviours of ceramic lattice structures

Ceramic lattice structures (CLSs) are used for construction in common and extreme environments because of the extraordinary properties of ceramics. In this study, we designed and additively manufactured CLSs with distinct structural parameters to explore their quasi-static and dynamic compressive behaviours in detail. It was demonstrated that both the relative density (?ρ) and inclination angle (ω) had a significant impact on the quasi-static and dynamic mechanical properties of the CLSs. Furthermore, the mathematical relationships between the quasi-static compressive properties, including quasi-static compressive strength (QS), quasi-static Young’s modulus (QY), and quasi-static energy absorption (QE), versus ?ρ and ω obeyed the Gibson–Ashby and Deshpande and Fleck models, respectively. It was revealed by experiment and simulation that as the stiffness increased, the quasi-static failure mode of the CLSs changed from a parallel-vertical-inclined mixed mode to a parallel-vertical mode. In addition, the relationship between the dynamic mechanical properties of the CLSs versus ?ρ and ω also followed the Gibson–Ashby and Deshpande and Fleck models. The exceptional dynamic increase factor indicated that CLSs are highly suitable for extreme environments. These findings will aid in the research and development of customised additively manufactured CLSs.     

基于ERNIE-BiGRU模型的摘要语步自动识别研究

学术文献的摘要是对文献主要内容的浓缩,摘要不同部分的语步具有不同的信息,语步的自动识别和抽取对于学术摘要的后续研究有着重要的应用价值,而目前语步识别的研究相对较少,并且相关算法的效果还需要提高。针对上述问题,该文提出了一种基于ERNIE-BiGRU模型的语步识别算法。该算法首先结合中文句法分析理论提出基于句法依存关系的多语步结构拆分法,对学术文献摘要多语步结构进行自动拆分,获得多个单语步结构;然后构建用于训练的单语步结构语料库,并利用知识增强语义表示预训练模型,训练出句子级词向量;最后将训练出的单语步结构词向量信息输入双向门限循环单元(BiGRU)进行摘要语步自动化识别,取得了良好的效果。实验结果表明,该算法具有较好的鲁棒性和较高的识别精度,在结构化和非结构化摘要上的识别准确率分别达到了96.57%和93.75%。     

Tuning lattice strain in biphenylene for enhanced electrocatalytic oxygen reduction reaction in proton exchange membrane fuel cells

As proton-exchange membrane fuel cell technology has grown and developed, there has been increasing demand for the design of novel catalyst architectures to achieve high power density and realize wide commercialization. Herein, based on the two-dimensional biphenylene, we compare the oxygen reduction reaction (ORR) activity on the active sites with different biaxial lattice strains using first-principles calculations. The ORR free energy diagrams of biphenylene monolayers with varying lattice strains suggest that the biaxial tensile strains are unfavorable for catalytic activity. In contrast, the biaxial compressive strains could improve the catalytic performance. The biphenylene systems with the strain of ?2% ～ ?6% (S_{-0.02～-0.06}) display overpotentials of 0.37–0.49 V. This performance is comparable to or better than the Pt (111) surface. The Bader charge transfer of adsorbed O species on various biaxial strain biphenylene catalysts could be a describer to examine the catalytic activity. The catalysts possessed the moderate transferred charge of O adsorbed species often promotes catalytic process and give the high catalysis efficiency. Overall, this work suggests that the lattice strain strategy can significantly enhance the catalytic activity of biphenylene materials and further provide guidance to design biphenylene-based catalysts in various chemical reactions.     

A dynamic hybrid trust network-based dual-path feedback consensus model for multi-attribute group decision-making in intuitionistic fuzzy environment

This paper proposes a dual-path feedback consensus model based on dynamic hybrid trust relationships to solve multi-attribute group decision-making problems in intuitionistic fuzzy environment. This model comprises two main parts: (a) the construction of a dynamic hybrid trust network among decision makers (DMs) and (b) the formation of a dual-path feedback mechanism to improve the group consensus. In the first part, a hybrid trust network is constructed by combining DMs’ prior knowledge of each other and the preference similarities between them. Then, the hybrid trust network is dynamically updated iteratively to reflect the changes in the trust relationships in the process of joint decision-making. In the second part, DMs with low consensus degrees are identified and provided with either a preference or weight adjustment path to improve the group consensus. The preference adjustment path is activated for DMs who agree to modify their preferences, and a nonlinear programming model is proposed to help DMs improve consensus degrees while minimizing adjustment cost. The weight adjustment path is activated for DMs who stick to their own opinions and refuse to make changes, and their weights is adjusted accordingly. An illustrative example along with the related sensitivity analysis and comparative study are used to verify the effectiveness of the proposed model.     

Effect of PyC interface phase on the cyclic ablation resistance and flexural properties of two-dimensional Cf/HfC composites

Composites based on hafnium carbide and reinforced with continuous naked carbon fiber with and without PyC interface were prepared at low temperature by precursor infiltration and pyrolysis and chemical vapor deposition method. The microstructure, mechanical property, cyclic ablation and fiber bundle push-in tests of the composites were investigated. The results show that after three times ablation cycles, the bending strength of samples without PyC interface decreased by 63.6 %; the bending strength of samples with PyC interface only decreased by 37.8 %. The force displacement curve of the samples with PyC interface presented a well pseudoplastic deformation state. The mechanical behavior difference of two kinds of composites was due to crucial function of PyC interface phase including protection of fiber and weakening of fiber/matrix interface.     

On the design of secure primitives for real world applications

This editorial paper provides an overview of new advances on hardware security challenges and promising solutions for real world applications. It first presents the increasing hardware vulnerabilities with the emergence of diverse computing platforms. Then, it details the technical challenges, research opportunities, and potential solutions to cyber-attacks on -physical- devices.