Gel-casting of transparent magnesium aluminate spinel ceramics fabricated by spark plasma sintering (SPS)

In this paper, a transparent magnesium aluminate spinel ceramic was fabricated through the newest colloidal gel casting method, using a synthetic powder with the average particle size of 90 nm and Isobutylene-Maleic Anhydride (ISOBAM) additive. ISOBAM served as both a dispersant and a gelation agent to achieve a dense body. Also, the suspension rheological behavior was optimized by the solid loading of 85 wt%, the additive content of 0.7 wt%, and the gelation time of 350 s. This led to a green body with a density equal to 65% of theoretical density and the green strength of 14.48 MPa. The results revealed that the reduction of porosity and the uniform distribution of pores in the green body (smaller than half of the initial powder particle size, 35 nm), as accompanied by spark plasma sintering (SPS), resulted in the final body density of 99.97%, as well as the high in-line transmittance of 86.7% at the wavelength of 1100 nm.     

Loadbearing capacity of infill masonry walls considering the deformation‐based membrane effect

According to currently valid codes, it is not possible to determine the loadbearing capacity of unreinforced infill walls considering the deformation‐based membrane effect by incorporating the exact support conditions. One reason for this is the lack of a validated calculation procedure, which in addition to the equilibrium conditions also realistically represents the compatibility conditions of these systems. In the present paper, therefore, a new non‐linear analytical calculation procedure is presented. The main focus of the analysis of walls subject to area loading is the incorporation of the support conditions and thus the consideration of the deformation‐based membrane compressive force. Through generalised formulation and a standardised notation of the determination equations, different material behaviours and various support conditions can be taken into account with few parameters. On the action side, both lighter loading like wind loads and heavier loading like explosion loads can be considered. Through the implementation of the partial factor concept, it is possible to comply with the requirements of European codes and thus ensure the applicability of the analysis model.     

基于ARIMA和BP神经网络的生态系统服务价值预测仿真

针对现有生态系统服务价值预测体系误差大、研究不足等问题,本文构建了面向未来生态服务价值的预测机制。该机制采用主成分分析法和Person相关系数法,建立了以GDP、人口、土地利用率、土地管理政策和城市人口密度为驱动力的生态系统服务价值关联矩阵,提出了基于ARIMA和BP神经网络的生态系统服务价值的时间序列预测机制。为验证预测机制有效性,本文选取中国主要土地利用类型代表省份的真实土地数据集进行分析,研究结果表明本文建立的预测模型平均绝对误差仅为0.023,且从预测结果来看,未来草地生态会向较好趋势发展,林地生态发展不容乐观。     

基于深度学习的秀丽隐杆线虫显微图像分割方法

利用计算机实现自动、准确的秀丽隐杆线虫(C.elegans)的各项形态学参数分析,至关重要的是从显微图像上分割出线虫体态,但由于显微镜下的图像噪声较多,线虫边缘像素与周围环境相似,而且线虫的体态具有鞭毛和其他附着物需要分离,多方面因素导致设计一个鲁棒性的C.elegans分割算法仍然面临着挑战。针对这些问题,提出了一种基于深度学习的线虫分割方法,通过训练掩模区域卷积神经网络(Mask R-CNN)学习线虫形态特征实现自动分割。首先,通过改进多级特征池化将高级语义特征与低级边缘特征融合,结合大幅度软最大损失(LMSL)损失算法改进损失计算;然后,改进非极大值抑制;最后,引入全连接融合分支等方法对分割结果进行进一步优化。实验结果表明,相比原始的Mask R-CNN,该方法平均精确率(AP)提升了4.3个百分点,平均交并比(mIOU)提升了4个百分点。表明所提出的深度学习分割方法能够有效提高分割准确率,在显微图像中更加精确地分割出线虫体。     

植物浸取剂原地浸出离子型稀土矿中试模拟

分别以“散样重装”和保持矿体原样的离子型稀土矿为原料，开展植物浸取剂浸出稀土的小试和“原地浸出”中试模拟试验。探讨了试验动力学，探索了植物浸取剂浓度和用量对浸出的影响，并它的渗透性和浸取性能与硫酸铵为浸出剂时的进行了对比。结果表明，植物浸取剂浸出稀土过程的动力学符合“收缩未反应核模型”；128.2 kg浓度为2%植物浸取剂浸出451 kg稀土矿是合适的；保持矿体原样的稀土矿渗透性较差，植物浸取剂的水平平均渗透速度、垂直平均渗透速度、浸出率分别为0.141 cm/min、0.213 cm/min、94.40%，均好于硫酸铵的。     

Thermomechanical properties of alumina-filled plasticized polylactic acid: Effect of alumina loading percentage

Polylactic acid (PLA) is one of the most widely studied renewable and biodegradable polyesters and is expected to replace petrochemical-based synthetic polymers. In this study, we investigated the effect of the alumina volume fraction on the thermal and mechanical properties of polyethylene glycol (PEG)-plasticized PLA. The alumina particles were treated with maleic acid to improve their interaction with the PLA matrix. The field-emission scanning electron microscopy results revealed that the addition of alumina eliminated voids, leading to improved interfacial interactions between the PLA and alumina particles. The thermal conductivity of the neat PLA increased from 0.278 to 0.66?wm^?1 k^?1 with the addition of 30% alumina, which accounts for 137% increase. The tensile strength and Young's modulus of the neat PLA dropped by 52% and 56%, respectively, on the addition of 15% PEG plasticizer. However, the elongation at break increased from 5.4% to 207%, which was associated with a drop on the glass transition temperature values. The dynamic mechanical analysis results showed a drop in the storage modulus and height of the tan δ peak, revealing the increased flexibility of the composite after the inclusion of the plasticizer. The addition of 30% alumina exhibited a 41.6% increase on the stiffness of the PEG-blended PLA.     

The use of Nannochloropsis sp. as a source of omega‐3 fatty acids in dry pasta: chemical,technological and sensory evaluation

Nannochloropsis is a microalga characterised by having high amounts of eicosapentaenoic acid (EPA), a fatty acid known for its health benefits. The aim of this study was to elaborate dry pasta with a significant contribution of EPA using Nannochloropsis sp., without affecting the quality product and with good consumer acceptance. Technological quality was analysed in terms of cooking properties and texture profile. Cooked pasta was characterised through proximal composition, phenolic compound, fatty acid content and sensorial analysis. It was possible to replace up to 30% of wheat flour with microalgae without affecting the technological quality of pasta and with a significant contribution of EPA to the daily diet (0.237 g per 100 g pasta). The incorporation of 10% and 20% Nannochloropsis in pasta formulation allowed to decrease the n6:n3 ratio from 25:1 to 5:1 and 2:1, respectively. Therefore, the microalgae are an interesting ingredient to increase EPA consumption in products like pasta, while the sensory evaluation confirms the possibility towards a commercial approach.