Effects of different carbon sources and C/N values on nonvolatile taste components of Pleurotus eryngii

Pleurotus eryngii, the second largest industrial cultivation mushroom in China, is usually cultivated on substrates mainly consisting of sawdust and corncob. In this study, experiments were performed to determine the effects of different carbon sources and C/N values on nonvolatile taste components of P. eryngii. The effects of different carbon sources on nonvolatile taste components levels revealed that sawdust was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while corncob was beneficial to high contents of carbohydrate, polysaccharides and trehalose. At the similar C/N values, relatively higher sawdust content was beneficial to umami amino acid production, while relatively higher corncob content was beneficial to high contents of carbohydrate, polysaccharides and mannitol. Higher C/N value was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while lower C/N value was beneficial to high contents of carbohydrate, polysaccharides and trehalose. These results provided information for P. eryngii fruit body industrial cultivation to obtain specific nonvolatile taste components with high levels.     

Using electroencephalogram to continuously discriminate feelings of personal thermal comfort between uncomfortably hot and comfortable environments

Thermal comfort is an important factor for the design of buildings. Although it has been well recognized that many physiological parameters are linked to the state of thermal comfort or discomfort of humans, how to use physiological signal to judge the state of thermal comfort has not been well studied. In this paper, the feasibility of continuously determining feelings of personal thermal comfort was discussed by using electroencephalogram (EEG) signals in private space. In the study, 22 subjects were exposed to thermally comfortable and uncomfortably hot environments, and their EEG signals were recorded. Spectral power features of the EEG signals were extracted, and an ensemble learning method using linear discriminant analysis or support vector machine as a sub-classifier was used to build the discriminant model. The results show that an average discriminate accuracy of 87.9% can be obtained within a detection window of 60 seconds. This study indicates that it is feasible to distinguish whether a person feels comfortable or too hot in their private space by multi-channel EEG signals without interruption and suggests possibility for further applications in neuroergonomics.     

DST在塔河油田碳酸岩油藏的应用

塔河油田碳酸岩油藏是定容体油藏,若发育的裂缝、溶洞延伸不远,定容体的规模较小,则无开采价值,因此有必要判断钻遇的储集体规模大小.小定容体最显著的特征就是天然能量消耗和地层压力下降明显,DST测试是判断定容体油藏的好方法.由于常规测试受岩性、裂缝产状、泥浆侵入、含液性、地层各向异性等因素的不确定影响,使得常规测试储层响应特征具有多重性,只能初步判断裂缝溶洞的发育带,因此可以利用DST测试技术了解显示层段产液性质和产能,判断油气水层.     

矩形垂直筛板的流体力学性能研究

在600mm的有机玻璃冷模塔中,用水-空气体系测定矩形垂直筛板的塔板压降、漏液和雾沫夹带等流体力学性能,确定了合理的塔板结构,使其具有较高的气液通量和较宽的操作范围,空塔动能因子最大可达3.0kg1/2(m1/2.s)-1,液流强度可达21.6m3/(m.h)。并对不同气液流量下塔板的流体力学实验数据进行关联和分析,得出了矩形垂直筛板的干板压降计算关联式以及漏液率随液流强度和空塔动能因子的变化关系,为矩形垂直筛板的设计提供了依据。与新垂直筛板相比,矩形垂直筛板具有更低的塔板压降。     

H9000 V4.0计算机监控系统技术特点概要

为了满足三峡右岸电站的应用需要,在H9000 V3.0计算机监控系统的基础上研制开发了H9000 V4.0系统,改进和完善了原系统已有功能,开发了新功能,进一步提高了系统的性能指标和可靠性指标。文中主要介绍H9000 V4.0系统的设计原则,以及数据采集、人机联系、报表定制、Web信息发布、历史数据管理等主要新功能。     

多民族区域移民安置工作的探索

新疆吉林台水电站水库移民的特点是,少数民族多,牧业人口多,人均补偿投资多。其移民安置工作中遵循“政府负责,投资包干,业主参与,综合监理”的方针,建章立制,牢固树立依法行政的思想,做到有章可循,严格管理;认真编制、审核、执行移民计划;认真核定移民补偿实物量,发放补偿证,充分尊重移民意愿,保障少数民族移民的合法权益;抓好移民安置单项工程的建设,加强行政领导,加强移民干部队伍的建设;从而基本做到了政府满意,移民和业主满意。     

大宁调蓄水库防渗工程应用效果监测及评价

基于大宁调蓄水库库区监测数据,分析库外地下水位与库水位之间的相关性,总结地下水位变化规律,同时采用水量平衡法对库区渗漏量进行定量计算,进而对防渗工程的应用效果进行评价.结果表明,防渗措施起到了阻隔库水外渗的作用,与无防渗工程时相比,库区渗漏量显著减少.     

MapReduce Workload Modeling with Statistical Approach

Large-scale data-intensive cloud computing with the MapReduce framework is becoming pervasive for the core business of many academic, government, and industrial organizations. Hadoop, a state-of-the-art open source project, is by far the most successful realization of MapReduce framework. While MapReduce is easy- to-use, efficient and reliable for data-intensive computations, the excessive configuration parameters in Hadoop impose unexpected challenges on running various workloads with a Hadoop cluster effectively. Consequently, developers who have less experience with the Hadoop configuration system may devote a significant effort to write an application with poor performance, either because they have no idea how these configurations would influence the performance, or because they are not even aware that these configurations exist. There is a pressing need for comprehensive analysis and performance modeling to ease MapReduce application development and guide performance optimization under different Hadoop configurations. In this paper, we propose a statistical analysis approach to identify the relationships among workload characteristics, Hadoop configurations and workload performance. We apply principal component analysis and cluster analysis to 45 different metrics, which derive relationships between workload characteristics and corresponding performance under different Hadoop configurations. Regression models are also constructed that attempt to predict the performance of various workloads under different Hadoop configurations. Several non-intuitive relationships between workload characteristics and performance are revealed through our analysis and the experimental results demonstrate that our regression models accurately predict the performance of MapReduce workloads under different Hadoop configurations.     

钙锌稳定剂的质量控制

从标准化和性能的角度对商品化的钙锌稳定剂的质量进行了分析.根据钙锌稳定剂PVC物料的热稳定性和流变性,以及PVC制品的工程使用性能和卫生性能,提出了控制PVC制品用钙锌稳定剂质量的方法.