天灸对精神分裂症患者血脂及阴性症状的影响

目的：观察天灸对精神分裂症患者血脂异常及阴性症状的影响。方法：将100例精神分裂症血脂异常患者随机分为治疗组和对照组，每组各50例。治疗组给予天灸治疗，对照组给予辛伐他汀治疗，2组疗程均为60d。检测2组治疗前后血清总胆固醇（TC）、三酰甘油（TG）、低密度脂蛋白胆固醇（LDL-C）、高密度脂蛋白胆固醇（HDL-C），测定中医症状积分及PANSS量表阴性症状积分。结果：中医症状疗效总有效率治疗组为87.23%，对照组为58.70%，差异有统计学意义（P＜0.01）。治疗组治疗前后HDL-L组内比较，差异有统计学意义（P<0.01），2组TC、TG、LDL-C组内及组间比较，差异均有统计学意义（P＜0.01，P<0.05）；PANSS量表阴性症状积分治疗组治疗前后组内比较及治疗后与对照组比较，差异均有统计学意义（P＜0.01）。结论：天灸能改善精神分裂症患者血脂水平及缓解中医症状、阴性症状，值得临床推广应用。     

高分五号卫星大气参数探测综述

高分五号卫星搭载了大气痕量气体差分吸收光谱仪、主要温室气体探测仪、大气多角度偏振探测仪、大气环境红外甚高分辨率探测仪、可见短波红外高光谱相机和全谱段光谱成像仪共6台载荷,对全球环境监测及中国大气气溶胶、臭氧、二氧化硫、二氧化氮、二氧化碳、甲烷和云等多个环境与气象综合监测方面有着重要的意义。为了更好的了解高分五号卫星任务的大气监测内容,本文对高分五号卫星其中的4个大气探测载荷特征和数据处理算法进展进行了总结,涉及各个载荷参数信息、算法介绍和产品初步结果等相关内容。高分五号卫星是中国专门用于大气环境监测任务的遥感卫星,随着后续卫星的发射升空,将对中国乃至全球大气环境监测提供强有力的数据支撑。     

http://www.sciencedirect.com/science/article/pii/S1674987111000600

Detailed studies on Late Devonian to Early Carboniferous carbonate rocks in central Hunan, southern China have led to the recognition of 25 lithofacies which can be grouped into:(1) inner ramp peritidal platform,(2) inner ramp organic bank and mound.(3) mid ramp,(4) outer ramp,and(5) shelf basin fades associations.The peritidal platform fades association dominates the Zimenqiao Formation (Namurian A or late Datangian) and is characterized by gypsum and dolostone-containing sequences, indicating a peritidal platform environment.The other four fades associations dominate the Menggongao Formation(late Famennian).Liujiatang Formation(Tournaisian or Yangruanian).Shidengzi Formations (early Visean or early Datangian).Five upward-shallowing cycles were distinguished in these three Formations.The predominant fades associations developed in each Formation demonstrate an overall transgression-regression cycle in the Late Devonian to Early Carboniferous in central Hunan.The overall transgressive sequence was preserved in the Shaodong.Menggongao.and Liujiatang Formations,and the overall regressive sequence was preserved in the Liujiatang.Shidengzi.Ceshui and Zimenqiao Formations.     

萍乡市土地利用变化及生态环境质量评价

文中基于2002、2007、2013和2018年Landsat遥感数据,采用支持向量机法提取了萍乡市的土地利用信息,通过提取绿度指标、干度指标、湿度指标和热度指标,利用主成分分析法构建萍乡市遥感生态指数(RSEI),分析了2002—2018年萍乡市的土地利用变化及生态环境情况.结果表明:1)2002—2018年建设用地持续增多,水域、林地和耕地先减后增,总体呈减少态势;草地先增后减,总体呈增加态势;未利用地先减后增,总体呈增加态势.2)2002—2018年萍乡市的生态环境以"一般"和"良好"为主,各区县的生态环境存在很大的差异性.3)林地、草地和水域位置的生态环境相对偏好,而建设用地和未利用地位置的生态环境相对偏差.     

十脉冲下限压型SPD级间串联退耦电感前后能级匹配研究

退耦电感是限压型浪涌保护器(SPD)级联配合核心元件, 对于限压型SPD能级匹配具有重要影响。针对退耦电感与限压型SPD能级匹配问题, 基于行波传输理论建立多级限压型SPD能量匹配模型, 并结合更接近自然雷击的10个8/20μs多脉冲试验进行研究, 试验结果可知: 恒定波阻抗下, 增大SPD线路间退耦电感值, 可有效减缓雷电瞬态过电压上升速率。SPD并联时, 氧化锌压敏电阻压敏电压对前后级分流比影响较小, 与残压值呈正相关关系。SPD级联电感值越大, 前级SPD泄流越多, 后级SPD箝压水平越高, 能级匹配效果越好。当出现磁饱和时, 前级SPD泄流显著降低, 后级SPD的泄流显著增加, 为避免出现该现象, 实际装设SPD时, 级间选装的退耦电感值在合理范围内应稍大于理论电感值。      

基于Pitzer模型预测Na-K-Ca-Mg-Cl-H2O溶液的密度

天然水体系的体积性质与压力、温度、组成的相关性(PVTx性质)研究在地球化学、盐湖化工等领域有广泛的应用。密度是卤水最基本的体积性质,不仅可以通过实验测定,还可以用理论模型进行预测。建立富钾卤水密度与组成、温度的关联模型有助于认识钾在复杂卤水中的富集、迁移规律。为了构建基于Pitzer离子相互作用模型的卤水密度预测方法,本文用高精度振荡管密度计测定了常压下KCl、CaCl₂纯盐溶液以及最高离子强度为11.8 mol·kg^-1的混合溶液在283~323 K下的密度,用所测得的密度通过Pitzer离子相互作用模型拟合得到多温下Pitzer单电解质参数和Pitzer混合参数。用Pitzer模型参数计算了Na-K-Ca-Mg-Cl-H₂O体系293~313 K的密度,计算密度值与实验值的相对偏差在±0.25%以内,计算的结果整体上要优于文献值,文献在计算中均未考虑Pitzer混合参数项。结果表明,K、Ca、Cl离子间的相互作用对于Na-K-Ca-Mg-Cl-H₂O溶液的密度有显著的影响,本文获得的Pitzer参数反映了这些离子间的相互作用,可用于计算含有K、Ca、Cl离子的复杂卤水密度的预测。     

XRF半定量分析技术在矿石光片鉴定中的应用

偏光显微镜反光镜下鉴定金属矿物是最常用、最快捷有效的方法,然而鉴定结果容易受到鉴定者主观因素或磨片情况的影响。为了更快速、准确地在反光镜下鉴定矿物,利用XRF半定量分析技术快速、无损、前处理简单等特点,以及磨平抛光的矿石矿物在半定量分析过程中能较好地避免楔入效应和阴影效应的有利因素,采取了先用XRF半定量分析测得的结果去反推矿物,再在显微镜下鉴定矿物的方法。以多金属硫化物矿石、含铀多金属矿石及含微量铀的矿石样品为例进行鉴定,结果表明,在鉴定前知道光片上的元素及其质量分数,通过地球化学方法和经验法反推矿物,结合显微镜观察需要鉴定的矿物,可有效避免忽略掉透明/半透明矿物（锡石）、小粒径矿物（沥青铀矿）、易混淆矿物（铀黑）,提高光片鉴定工作的效率和准确性。     

一种三江平原湿地的植被冠层叶绿素反演

针对三江平原洪河湿地保护区内主要特征植被冠层的叶绿素含量,采用PROSAIL模型从物理角度进行反演。首先将叶面积指数、叶片结构参数、等价水厚度、叶绿素实测含量等一些植被理化参数的实测值输入模型得到模拟光谱数据,然后与实测光谱数据对比验证其准确性。在模型中,通过固定其他参量不变,取叶绿素含量为唯一值时,考察在不同叶面积指数下叶绿素含量对冠层反射率的影响。结果显示,植被冠层叶绿素含量的敏感波段为555nm和720nm。基于PROSAIL模型的叶绿素反演方法较传统的统计模型相比是较好且稳健的方法。     

Seasonal statistical analysis of the impact of meteorological factors on fine particle pollution in China in 2013–2017

Based on long-term PM_2.5 data observed at high temporal and spatial resolution, the relationships between PM_2.5, primary emission, and weather factors in China during four seasons were examined using statistical analysis. The results reveal that primary emission plays a decisive role in the spatial distribution and seasonal variability of PM_2.5, except in western China, where PM_2.5 is controlled by dust weather. In addition to the accumulation of primary emissions, unfavorable meteorological conditions for the diffusion of air pollution lead to the occurrence of PM_2.5 pollution. The significant dynamic factors affecting PM_2.5 concentration are surface wind speed, planet boundary layer height, and ventilation coefficient, especially in winter. The ventilation coefficient is inversely correlated with PM_2.5. Better ventilation is more favorable for the dilution and outflow of local PM_2.5. However, in spring and autumn, ventilation coefficient and PM_2.5 are positively correlated over the southern regions with low emission, indicating that ventilation also affects the inflow of PM_2.5 from outside the region. Wind shear, 850 hPa divergence, and vertical velocity have insignificant effects on the long-term variations in PM_2.5. The significant thermal factor is 850 hPa temperature in winter, except in the Pearl River Delta and Xinjiang regions. In spring, the influence of each thermal factor is weak. In summer, the influences of temperature and humidity are more significant than in spring. In autumn, the influence of humidity is relatively obvious, compared with other thermal factors. The correlation coefficients between multi-factors regressed and observed PM_2.5 concentrations pass the 95% confidence test, and are higher than that of single-factor regression over most regions. The observed data from December 2016 to February 2017 were chosen to test the regression equation. The test result reveals that the regression equation is effective for predicting PM_2.5 concentrations over regions with high primary emission.