Feasibility study of large-scale mass customization 3D printing framework system with a case study on Nanjing Happy Valley East Gate

At present, the development and implementation of digital transformation are the keys to promoting high-quality industry development. The new digital fabrication method of robotic 3D printing is a research area being studied by many to tackle the issue of the declining productivity of traditional construction methods. Although many studies have been done, most of the current 3D printing projects are facing limitations in terms of scale. In order to bridge the gap, this article proposed a mass customization 3D printing framework system for large-scale projects. This article discusses how mass customization is made possible through the joint operation of the FUROBOT software and 3D printing hardware. By taking the east gate of Nanjing Happy Valley Plaza as a case study, the article demonstrates and studies the feasibility of the large-scale mass customization 3D printing framework system.     

An Enhanced Beetle Antennae Search Algorithm Based Comprehensive Water Quality Index for Urban River Water Quality Assessment

Water Resources Management - Urban river not only has the important function in urban hydrological environment, but also is an area for entertainment. Water quality assessment is the core technique...     

Effect of MoS2/PTFE coatings on performance of Si3N4/TiC ceramics in dry sliding against WC/Co

To enhance the tribological performance of Si₃N₄/TiC ceramics, MoS₂/PTFE composite coatings were deposited on the ceramic substrate through spraying method. The micrographs and basic properties of the MoS₂/PTFE coated samples were investigated. Dry sliding friction experiments against WC/Co ball were performed with the coated ceramics and traditional ones. These results showed that the composite coatings could significantly reduce the friction coefficient of ceramics, and protect the substrate from adhesion wear. The primary tribological mechanisms of the coated ceramics were abrasive wear, coating spalling and delamination, and the tribological property was transited from slight wear to serious wear with the increase of load because of the lower surface hardness and shear strength. The possible mechanisms for the effects of MoS₂/PTFE composite coatings on the friction performance of ceramics were discussed.     

A Novel LRRK2 Variant p.G2294R in the WD40 Domain Identified in Familial Parkinson’s Disease Affects LRRK2 Protein Levels

Leucine-rich repeat kinase 2 (LRRK2) is a major causative gene of late-onset familial Parkinson’s disease (PD). The suppression of kinase activity is believed to confer neuroprotection, as most pathogenic variants of LRRK2 associated with PD exhibit increased kinase activity. We herein report a novel LRRK2 variant—p.G2294R—located in the WD40 domain, detected through targeted gene-panel screening in a patient with familial PD. The proband showed late-onset Parkinsonism with dysautonomia and a good response to levodopa, without cognitive decline or psychosis. Cultured cell experiments revealed that p.G2294R is highly destabilized at the protein level. The LRRK2 p.G2294R protein expression was upregulated in the patient’s peripheral blood lymphocytes. However, macrophages differentiated from the same peripheral blood showed decreased LRRK2 protein levels. Moreover, our experiment indicated reduced phagocytic activity in the pathogenic yeasts and α-synuclein fibrils. This PD case presents an example wherein the decrease in LRRK2 activity did not act in a neuroprotective manner. Further investigations are needed in order to elucidate the relationship between LRRK2 expression in the central nervous system and the pathogenesis caused by altered LRRK2 activity.     

基于SRAM的通用存算一体架构平台在物联网中的应用

最近,存算一体(IMC)架构引起了广泛关注,并被认为有望成为突破冯诺依曼瓶颈的新型计算机架构,特别是在数据密集型(data-intensive)计算中能够带来显著的性能和功耗优势.其中,基于SRAM的IMC架构方案也被大量研究与应用.该文在一款基于SRAM的通用存算一体架构平台——DM-IMCA的基础上,探索IMC架构在物联网领域中的应用价值.具体来说,该文选取了物联网中包括信息安全、二值神经网络和图像处理在内的多个轻量级数据密集型应用,对算法进行分析或拆分,并将关键算法映射到DM-IMCA中的SRAM中,以达到加速应用计算的目的.实验结果显示,与基于传统冯诺依曼架构的基准系统相比,利用DM-IMCA来实现物联网中的轻量级计算密集型应用,可获得高达24倍的计算加速比.     

基于大数据深度学习的输电塔结构抗风易损性评估

为了有效预测输电网系统在强风作用下的响应，并开展高效精准的性能评估，文章提出了基于深度学习模型的风致易损性评估框架。以某具备健康监测系统的输电塔结构为例，首先对监测数据进行清洗和重构，通过大数据深度学习建立荷载输入和响应输出的等效映射模型，然后通过数值模拟生成灾害强度均匀的风场数据并由深度学习模型预测输电塔关键杆件响应，计算不同性能水准的易损性曲线。研究结果表明，经训练的深度学习模型可以涵盖实际工程中存在的各类不确定性因素，有效映射复杂风环境下输电塔结构的动力响应。提出的框架方法可以避免单纯通过数值模型制备大量动态响应数据，更高效地进行输电网系统风致易损性评估。     

基于有限元的区域分解方法在永磁聚焦系统仿真中的应用

随着计算机技术以及并行求解技术的发展,区域分解方法越来越多地应用于计算电磁学的各个领域.针对微波管中的永磁聚焦系统仿真,该文提出一种基于有限元的非重叠区域分解方法,其引入一种新型传输条件,并采用内罚的方式推导出有限元弱形式.该区域分解法的最大优势是不需要引入多余的未知量,并且最终集成的有限元矩阵满足对称正定性,适合采用预处理共轭梯度法进行矩阵方程的求解.该文仿真了多个微波管永磁聚焦系统,并与商业软件Maxwell进行了详细的对比,结果表明所提出的区域分解方法和Maxwell精度相当,却拥有着更加优越的计算性能.     

As the number falls,alternatives to the Hagberg–Perten falling number method: A review

This review examines the application, limitations, and potential alternatives to the Hagberg–Perten falling number (FN) method used in the global wheat industry for detecting the risk of poor end-product quality mainly due to starch degradation by the enzyme α-amylase. By viscometry, the FN test indirectly detects the presence of α-amylase, the primary enzyme that digests starch. Elevated α-amylase results in low FN and damages wheat product quality resulting in cakes that fall, and sticky bread and noodles. Low FN can occur from preharvest sprouting (PHS) and late maturity α-amylase (LMA). Moist or rainy conditions before harvest cause PHS on the mother plant. Continuously cool or fluctuating temperatures during the grain filling stage cause LMA. Due to the expression of additional hydrolytic enzymes, PHS has a stronger negative impact than LMA. Wheat grain with low FN/high α-amylase results in serious losses for farmers, traders, millers, and bakers worldwide. Although blending of low FN grain with sound wheat may be used as a means of moving affected grain through the marketplace, care must be taken to avoid grain lots from falling below contract-specified FN. A large amount of sound wheat can be ruined if mixed with a small amount of sprouted wheat. The FN method is widely employed to detect α-amylase after harvest. However, it has several limitations, including sampling variability, high cost, labor intensiveness, the destructive nature of the test, and an inability to differentiate between LMA and PHS. Faster, cheaper, and more accurate alternatives could improve breeding for resistance to PHS and LMA and could preserve the value of wheat grain by avoiding inadvertent mixing of high- and low-FN grain by enabling testing at more stages of the value stream including at harvest, delivery, transport, storage, and milling. Alternatives to the FN method explored here include the Rapid Visco Analyzer, enzyme assays, immunoassays, near-infrared spectroscopy, and hyperspectral imaging.