Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.     

热作模具钢表面激光堆焊耐磨合金层的研究

本文主要通过在H13钢上用大功率CO_2激光束进行堆焊,阐述了激光堆焊工艺变化对堆焊组织和性能的影响,在本试验条件下,得到了高密度弥散金属化合物组织的激光堆焊层,平均硬度为HV800,与基体呈冶金结合,耐磨性比H13模具钢提高149%。     

混合型表面活性剂液膜法处理含酚废水研究

研究了兰－１１３Ｂ＝Ｓｐａｎ－８０－－煤油ＮａＯＨ液膜体系处理苯酚废水的最佳操作工用于对高浓度含酚废水进行处理，实验结果表明，混合型表面活性剂各项指标均较好，除酚效率可达９９％以上，对内相ＮａＯＨ的最佳浓度的确定给出了估算方法。     

混凝土结构非线性全过程分析中的迭代控制法研究

在深入研究各类迭代控制法的基础上，针对混凝土结构的非线性全过程分析，在常规的位移和弧长控制法中引入了简单适用的考虑路径搜寻和单因加速的方法，明显改善了收敛情况。     

高强铝合金断裂韧性的研究现状及展望

通过对三种裂纹模式的概述，引出了铝合金断裂韧性的概念及断裂判据，重点评述了影响高强铝合金断裂韧性的内在与外在因素，以及断裂韧性与其它力学性能间的关系，最后提出了几个在今后的研究及应用中需要重点解决的问题。     

催化技术在降低汽油机排放方面的应用

本文介绍了当前催化技术在改善和降低汽油机排放方面的应用情况，指出：催化技术是改善汽油机排放的一种有效措施和重要手段。     

基于约束优化的联想记忆模型学习算法

本文提出了一种对称互连神经元网络的学习策略,利用全局约束优化方法确定连接权。优化过程采用了梯度下降技术。这种学习算法可以保证训练样本成为系统的稳定吸引子,并且具有优化意义上的最大吸引域。本文讨论了网络的存储容量,训练样本的渐近稳定性和吸引域大小。计算机实验结果说明了学习算法的优越性。     

一种派生式与创成式相结合的CAPP系统

本文结合为某机械厂开发的实用计算机辅助工艺设计系统(JJCAPP),论述了一种兼有派生式和创成式特点的综合式工艺自动设计方法.     

气藏水平井非稳态产能预测新方法研究

针对高产气藏储层特征,建立起气藏水平井非稳态产能预测模型,对高产气藏的产能进行分析和预测.实例分析表明,通过该模型形成的基于气藏与井筒耦合作用的非稳态产能预测新方法,对于单井产能预测具有优越性、长远性和实用性.该方法可直接利用不稳定压力测试成果进行预测,还可通过生产动态资料拟合来确定地层参数和预测,也可用来研究不同工作制度、完井方式,以及增产措施改善情况下的产能变化,为衰竭式开采的气藏工程研究提供了先进的手段.