护环液压胀形法的新发展及外补液胀形法的生产应用

本文论述了现有液压胀形法生产护环所存在的不足,介绍了新一代液压胀形工艺即外补液胀形的原理、优点,以及在我国首次生产应用中所显示出的明显的技术经济效益。     

场效应晶体管弧焊逆变器可靠性研究

本文讨论了功率MOSFET晶体管弧焊逆变器的工作可靠性及其影响因素，并指出了弧焊逆变器设计中应注意的问题。     

长轴表面激光淬火变形与控制

应用激光淬火强化技术控制长轴的淬火变形，分析了激光淬火变形的原因和影响因素。研究结果表明，激光淬火不仅可使长轴振摆变形量控制在很小的范围内，而且可将已变形的长轴校直到很高的精度。     

Novel Ag-AgBr decorated composite membrane for dye rejection and photodegradation under visible light

Photocatalytic membranes have received increasing attention due to their excellent separation and photodegradation of organic contaminants in wastewater. Herein, we bound Ag-AgBr nanoparticles onto a synthesized polyacrylonitrile-ethanolamine (PAN-ETA) membrane with the aid of a chitosan (CS)-TiO₂ layer via vacuum filtration and in-situ partial reduction. The introduction of the CS-TiO₂ layer improved surface hydrophilicity and provided attachment sites for the Ag-AgBr nanoparticles. The PAN-ETA/CS-TiO₂/Ag-AgBr photocatalytic membranes showed a relatively high water permeation flux (~ 47 L·m^–2·h^–1·bar^–1) and dyes rejection (methyl orange: 88.22%; congo red: 95%; methyl blue: 97.41%; rose bengal: 99.98%). Additionally, the composite membranes exhibited potential long-term stability for dye/salt separation (dye rejection: ~97%; salt rejection: ~6.5%). Moreover, the methylene blue and rhodamine B solutions (20 mL, 10 mg·L⁻¹) were degraded approximately 90.75% and 96.81% in batch mode via the synthesized photocatalytic membranes under visible light irradiation for 30 min. This study provides a feasible method for the combination of polymeric membranes and inorganic catalytic materials.     

A level set based immersed boundary method for simulation of non-isothermal viscoelastic melt filling process

In this work, the polymer melt filling process is simulated by using a coupled finite volume and level-set based immersed boundary (LS-IB) method. Firstly, based on a shape level set (LS) function to represent the mold boundary, a LS-IB method is developed to model the complex mold walls. Then the non-isothermal melt filling process is simulated based on non-Newtonian viscoelastic equations with differ-ent Reynolds numbers in a circular cavity with a solid core, and the effects of Reynolds number on the flow patterns of polymer melt are presented and compared with each other. And then for a true polymer melt with a small Reynolds number that varies with melt viscosity, the moving interface, the temperature distributions and the molecular deformation are shown and analyzed in detail. At last, as a commonly used application case, a socket cavity with seven inserts is investigated. The corresponding physical quantities, such as the melt velocity, molecular deformation, normal stresses, first normal stress differ-ence, temperature distributions and frozen layer are analyzed and discussed. The results could provide some predictions and guidance for the polymer processing industry.     

Modified g-C3N4 derived from ionic liquid and urea for promoting visible-light photodegradation of organic pollutants

In this work, modified g-C₃N₄ was fabricated successfully by calcination of ionic liquid (IL) and urea. The addition of IL changed the polymerization mode of urea, induced the self-assembly of urea molecules, modified the morphological structure of the tightly packed g-C₃N₄, and extended the electron conjugation system. When using 1-butyl-3-methylimidazolium chloride ([Bmim]Cl) as a modifier, the heteroatom Cl could be inserted into the g-C₃N₄ to optimize the electronic structure. The results of characterizations indicate that the unique structure of modified g-C₃N₄ has an expanded electron delocalization range, introduces an interlayer charge transmission channel, promotes the charge transmission, reduces the band gap, enhances the absorption of visible light, and inhibits electron-hole recombination. Modified g-C₃N₄ showed excellent photocatalytic performance for the degradation of rhodamine B and tetracycline. Furthermore, the effect of different anions in 1-butyl-3-methylimidazolium salts ([Bmim]Cl, [Bmim]Br, [Bmim][BF₄], and [Bmim][PF₆]) on the structure and function of g-C₃N₄ are discussed.     

基于非线性回归的含隐节点低压配电网参数和拓扑联合辨识

低压配电网参数和拓扑缺乏维护,精度较低,阻碍了在此基础上的各种高级应用的可靠实现.为此,提出了一种基于非线性回归的含隐节点低压配电网参数和拓扑联合辨识方法.首先,分析了现有基于线性电压回归的参数和拓扑辨识方法的不足.其次,基于线路的非线性电压降方程推导出任意两节点串、并联关系的判据,建立了基于节点多时段有功、无功负荷和电压幅值量测的非线性参数估计模型,提出了自下而上的参数估计和拓扑重建算法.最后,采用实际数据和低压配电网算例验证了所提方法的有效性.     

某机械公司前处理和电泳废水处理工程实例

某主要生产驾驶舱和建筑机械的公司在生产过程中采用的电泳涂装工艺产生了一定量的前处理和电泳废水,其中磷化等工序还产生了含磷废水。为执行政府的节能减排政策和实现含磷废水零排放,对前处理非磷工序和电泳的混合废水采用“混凝+活性污泥+砂滤+活性炭吸附”的工艺进行处理,对含磷废水采用“混凝+活性污泥+砂滤+活性炭吸附+精密过滤+离子交换+反渗透”的工艺。经处理后,出水达到《污水综合排放标准》(GB 8978-1996)的一级标准,回用中水达到企业标准。少量含磷浓缩液和干化污泥委外处理,避免了二次污染。     

Trace Identification and Visualization of Multiple Benzimidazole Pesticide Residues on Toona sinensis Leaves Using Terahertz Imaging Combined with Deep Learning

Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in plants, it poses great challenges for practical identification. This study proposed a state-of-the-art method for the rapid identification of trace (10 mg·L⁻¹) and multiple similar benzimidazole pesticide residues on the surface of Toona sinensis leaves, mainly including benzoyl (BNL), carbendazim (BCM), thiabendazole (TBZ), and their mixtures. The new method combines high-throughput terahertz (THz) imaging technology with a deep learning framework. To further improve the model reliability beyond the THz fingerprint peaks (BNL: 0.70, 1.07, 2.20 THz; BCM: 1.16, 1.35, 2.32 THz; TBZ: 0.92, 1.24, 1.66, 1.95, 2.58 THz), we extracted the absorption spectra in frequencies of 0.2–2.2 THz from images as the input to the deep convolution neural network (DCNN). Compared with fuzzy Sammon clustering and four back-propagation neural network (BPNN) models (TrainCGB, TrainCGF, TrainCGP, and TrainRP), DCNN achieved the highest prediction accuracies of 100%, 94.51%, 96.26%, 94.64%, 98.81%, 94.90%, 96.17%, and 96.99% for the control check group, BNL, BCM, TBZ, BNL + BCM, BNL + TBZ, BCM + TBZ, and BNL + BCM + TBZ, respectively. Taking advantage of THz imaging and DCNN, the image visualization of pesticide distribution and residue types on leaves was realized simultaneously. The results demonstrated that THz imaging and deep learning can be potentially adopted for rapid-sensing detection of trace multi-residues on leaf surfaces, which is of great significance for agriculture and food safety.     

Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters

RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as biomarkers. This study used machine learning to reduce gene/non-coding RNA features. Dorsolateral prefrontal cortex (dlpfc) RNA-seq data from 254 individuals was obtained from the CommonMind consortium. The average predictive accuracy for SCZ patients was 67% based on coding genes, and 96% based on long non-coding RNAs (lncRNAs). Machine learning is a powerful algorithm to reduce functional biomarkers in SCZ patients. The lncRNAs capture the characteristics of SCZ tissue more accurately than mRNA as the former regulate every level of gene expression, not limited to mRNA levels.