Putting yourself in someone else's shoes: The impact of a location-based,collaborative role-playing game on behaviour

The goal of this study was to probe the effectiveness of a mobile game-based learning approach in modifying behavioural outcomes and competence. The experiment was set against the background of low rates of laymen providing CPR during sudden cardiac arrests. A post-test control group design was used to contrast and evaluate the effects of the two different types of learning. Two hundred two students were randomly assigned to two conditions, a game-based variant simulating an emergency situation (experimental group), and an instruction-based approach (control group). After the intervention participants completed a questionnaire assessing self-prediction, self-efficacy, attitude, subjective norm, empathy and competence. The largest arguably significant difference between the two groups showed in self-prediction and capacity beliefs. Results further revealed a positive relationship between self-prediction and the variables attitude and self-efficacy. The type of scenario did not translate into the other concepts we assessed, though, and results were inconclusive regarding the effectiveness of the type of learning scenario and CPR knowledge. We explain the small effect size partly by the experimental procedure and the design of the game intervention, which is discussed in the course of this article.     

苏通GIL运输专用机具动力电池类型探讨

GIL运输专用机具是为安全、可靠、高效地完成苏通GIL综合管廊工程GIL单元的运输任务而研制的专用机具,其中动力电池系统设计是整机设计的重点之一。通过对各种常见动力电池优缺点的分析,并结合苏通GIL运输专用机具对动力电池的需求分析,确定了动力电池系统的技术路线,为苏通GIL运输专用机具的研制提供了坚实的基础。     

减震隔声降噪地垫的研发

介绍我国分户楼板隔声及其隔声研究现状,详细阐述多层复合结构的减震隔声降噪地垫的结构、性能和安装,减震隔声降噪地垫与木地板配合使用,将其铺装于扫平层的140 mm厚现浇钢筋混凝土楼板之上,经江苏省建工建材检测中心检测,撞击声隔声为61 dB,能很好地满足住宅分户楼板撞击声隔声L'nT,W≤65 dB的要求。     

An infinite chain, {[Ni(tn)2]3[Fe(CN)4(μ-CN)2]2}n,a new catalyst for electrochemical-driven water splitting and photochemical-driven hydrogen evolution from water under blue light

A new catalyst for both water reduction and oxidation, based on an infinite chain, {[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n, is formed by the reaction of NiCl₂, 1,3-propanediamine (tn) and K₃ [Fe(CN)₆]. {[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n can electro-catalyze hydrogen evolution from a neutral aqueous buffer (pH 7.0) with a turnover frequency (TOF) of 1561 mol of hydrogen per mole of catalyst per hour (H₂/mol catalyst/h) at an overpotential (OP) of 837 mV {[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n also can electro-catalyze O₂ production from water with a TOF of ～45 mol O₂ (mol cat)^?1s^?1 at an OP of 591 mV. Under blue light (λ = 469 nm), together with CdS nanorods (CdS NRs) as a photosensitizer, and ascorbic acid (H₂A) as a sacrificial electron donor, {[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n can photo-catalyze hydrogen generation from an aqueous buffer (pH 4.0) with a turnover number (TON) of 11,450 mol H₂ per mole of catalyst (mol of H₂ (mol of cat)^?1) during 10 h irradiation. The average of apparent quantum yield (AQY) is as high as 40.96% during 10 h irradiation. Studies indicate that {[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n exists in two forms: a cyano-bridged chain ({[Ni(tn)₂]₃ [Fe(CN)₄ (μ-CN)₂]₂}_n) in solid, and a salt ([Ni(tn)₂]₃ [Fe(CN)₆]₂) in aqueous media; Catalytic reaction occurs on the nickel center of [Ni(tn)₂]²⁺, and the introduction of [Fe(CN)₆]^3- can improve the catalytic efficiency of [Ni(tn)₂]²⁺ for H₂ or O₂ generation. We hope these findings can afford a new method for the design of catalysts for both water reduction and oxidation.     

Failure load prediction and optimisation for adhesively bonded joints enabled by deep learning and fruit fly optimisation

Adhesively bonded joints have been extensively employed in the aeronautical and automotive industries to join thin-layer materials for developing lightweight components. To strengthen the structural integrity of joints, it is critical to estimate and improve joint failure loads effectually. To accomplish the aforementioned purpose, this paper presents a novel deep neural network (DNN) model-enabled approach, and a single lap joint (SLJ) design is used to support research development and validation. The approach is innovative in the following aspects: (i) the DNN model is reinforced with a transfer learning (TL) mechanism to realise an adaptive prediction on a new SLJ design, and the requirement to re-create new training samples and re-train the DNN model from scratch for the design can be alleviated; (ii) a fruit fly optimisation (FFO) algorithm featured with the parallel computing capability is incorporated into the approach to efficiently optimise joint parameters based on joint failure load predictions. Case studies were developed to validate the effectiveness of the approach. Experimental results demonstrate that, with this approach, the number of datasets and the computational time required to re-train the DNN model for a new SLJ design were significantly reduced by 92.00% and 99.57% respectively, and the joint failure load was substantially increased by 9.96%.     

Adaptability analysis of design for additive manufacturing by using fuzzy Bayesian network approach

The rapid development of Additive Manufacturing (AM) has been conspicuous and appealing towards manufacturing end-use products and components over the past decade. The continual advancement of AM has brought many advantages such as personalization and customization, reduction of material waste, cutting off the existence of special tooling during fabrication, etc. However, the AM approach has its limitations, such as a lack of knowledge of AM process activities and the progressive industrialization of AM, which makes the design process activities unstable, unpredictable, and have a limited effect. The concept of “design for AM (DFAM)” is increasing, which means we have the opportunity to concentrate almost totally on product functioning. Therefore, the entire design paradigm must be revised to accommodate new production capabilities, geometries, and parameters to avoid molding or machine tooling technology constraints. Few studies have attempted to provide systematic and quantitative knowledge of the relationship between these elements and the feasibility of the design process, making it difficult for designers to assess and control AM industrialization. For this reason, DFAM is needed to reform AM from rapid manufacturing to a mainstream manufacturing method. This paper put forward a framework based on the Fuzzy Bayesian Network (FBN) for DFAM decision-making. Twenty impact factors were encapsulated from experts’ experience and existing literature to investigate the potential adaptability of DFAM. The proposed approach uses expert knowledge and Fuzzy Set Theory (FST) presented with Triangular Fuzzy Numbers (FFN) to perceive the uncertainties. The Bayesian Network (BN) captures the causal relationships and dependencies among the impact components and analyzes the DFAM adaptability for robust probabilistic reasoning. A robot arm claw was used to show the effectiveness of our approach. The results showed that FBN could be used to guide DFAM adaptability in the manufacturing industry.     

Effects of deformation rate on properties of Nd,Y-codoped CaF2 transparent ceramics

Different deformation rates of Nd,Y-codoped CaF₂ transparent ceramics were prepared by ceramization of single crystals. The deformation rate effects on the crystallization behaviors, microstructures, mechanical properties, and optical performances were investigated for the first time. The results indicate that the comprehensive performances of Nd,Y-codoped CaF₂ ceramic (△a?=?62%) are the most optimal compared with other ceramics having different deformation rates (△a?=?34%, 40%, 50%, and 75%). In further investigations of the optical properties, the Nd,Y-codoped CaF₂ ceramic (△a?=?62%) sample exhibited a high transparency (T_a?>?91%, 3-mm thick，250?～?1200?nm), low light scattering, superior fracture toughness (K_1c?～?0.71?MPa·m^1/2), strong fluorescence emission, long lifetime (τ?=?348.72?μs), and broad FWHM (29.2?nm), promising a good candidate for high-power laser material.     

10MW级深冷液化空气储能发电系统自动启动控制方法研究

以10 MW级深冷液化空气储能发电系统为研究对象,简要介绍了技术原理、系统构成、主要设备及工艺流程,并从自动控制视角,分别设计了储、释能阶段的启动方法。基于该自动启动方法,可完成储能阶段空气净化及压缩、空气液化、储热和蓄冷子系统的联合运行以及释能阶段储热、蓄冷和膨胀发电子系统的联合运行,实现了储能阶段自动达到额定出液量及释能阶段自动满足额定发电量的需求,提高了能量型机械储能系统对电网负荷变化的响应速度。     

油田地面集输管线腐蚀穿孔防治措施研究

影响油田安全生产并存在安全隐患的重要原因之一是地面集输管线的腐蚀穿孔。本文将围绕着如何进行油田地面集输管线腐蚀穿孔防止展开叙述,从建设管线的管材质量以及设计结构和风格、介质等方面进行分析和总结,严格执行防腐穿孔技术。     

汽车主模型ABS轻量化后地板检测模块的设计制造研究

后地板检测模块在燃油车与电动车内饰切换时拆卸频繁,为操作方便,需将后地板模块轻量化。而传统铝制模块密度大,质量易超标,因此,有必要采用轻量化材料如丙烯腈-丁二烯-苯乙烯共聚物(ABS)塑料来制备后地板检测模块。ABS材料密度小,成本低,但硬度低,强度弱,表面光洁度差。为解决这些问题,采用铝制骨架与ABS模块喷漆相结合的设计方式,通过设计阶段的强度计算,确定了质量轻、强度与表面质量均满足要求的后地板检测模块的设计方法。