硫酸镁调节SO2衍生物对大鼠海马神经元钠通道的刺激作用

利用全细胞膜片钳技术研究了硫酸镁(MgSO4)对SO2衍生物刺激大鼠海马神经元电压门控性钠通道的调节作用.结果表明,MgSO4对SO2衍生物增大大鼠海马神经元钠电流的效应具有抑制作用,此作用随着SO2衍生物浓度的增加而减弱,随着MgSO4浓度的增加而增强.不同时间加入MgSO4均会显著抑制SO2衍生物增大钠电流的效应,说明MgSO4不仅对SO2衍生物增大钠电流的效应具有抑制作用,而且可即时和延效性地抑制此损伤效应的发生.研究结果提示,硫酸镁对SO2衍生物刺激大鼠海马神经元钠通道具有抑制作用,这可能是MgSO4对SO2引发的中枢神经系统损伤具有防护和治疗作用的机制之一.图4参14     

Adjusting age and stage distributions for misclassification errors

Ecologists often use samples from the age or stage structure of a population to make inferences about population-level processes and to parameterize matrix models. Typically, researchers make a simplifying assumption that age and stage classes are determined without error, when in fact some level of misclassification often can be expected. If unaccounted for, misclassification will lead to overly optimistic levels of precision and can cause biased estimates of age or stage structure. Although several studies have used information from known-age individuals to quantify errors in age or stage distribution, the problem of estimating the age or stage structure in face of such errors has received comparably little attention. In this paper, we describe a general statistical framework for estimating the true stage distribution of a sample when misclassification rates can be estimated. The estimation process requires auxiliary information on misclassification rates, such as data from individuals of known age. We analyze age-structured harvest records from black bears in Pennsylvania to illustrate how incorporating misclassification errors leads to changes in point estimates and provides a measure of precision.     

Spatio-temporal characteristics and control strategies in the early period of COVID-19 spread: a case study of the mainland China

Environmental Science and Pollution Research - COVID-19 has caused huge impacts on human health and the economic operation of the world. Analyzing and summarizing the early propagation law can help...     

Nano Fe2O3 embedded in montmorillonite with citric acid enhanced photocatalytic activity of nanoparticles towards diethyl phthalate

Nano-Fe₂O₃ embedded in montmorillonite particles (Fe-Mt) were prepared to degrade diethyl phthalate (DEP) with citric acid (CA) under xenon light irradiation. Compared to pristine montmorillonite (Na-Mt), the embedding process increased 14.5-fold of iron content and 1.8-fold of specific surface area. The synthesized Fe-Mt have more oxygen vacancies than Fe₂O₃ nanoparticles (nFe₂O₃), which could induce more reactive oxygen species (ROSs) generation in the presence of CA under xenon lamp irradiation. Fe-Mt with CA enhanced photo-assisted degradation of DEP 2.5 times as compared to nFe₂O₃ with CA. Quenching experiments, electron paramagnetic resonance (EPR) spectroscopy and identification of products confirmed that surface-bound ?OH was the main radical to degrade DEP. Common anions (i.e., NO₃^?, CO₃^2?, Cl^?) and humic acid could compete ?OH with DEP and cause slower degradation of DEP. The removal efficiency of DEP was more than 56% with Fe-Mt after three recycles, and the dissolved Fe concentration from Fe-Mt was below 75 μmol/L, indicating Fe-Mt had a good stability as a catalyst. Fe-Mt together with CA appeared to be a promising strategy to remove organic pollutants in surface water, or topsoil under solar irradiation.     

Denitrification and microbial community in MBBR using A. donax as carbon source and biofilm carriers for reverse osmosis concentrate treatment

In this study,raw Arundo donax(A.donax)pieces were applied as carbon source and biofilm carriers for denitrification in a lab-scale moving bed biofilm reactor(MBBR)for the treatment of reverse osmosis concentrate gathered from local wastewater reuse plant.At stable phase(about 60 days),efficient denitrification performance was obtained with73.2%±19.5%NO_(3-)~-N average removal and 8.10±3.45 g N/(m~3·day)NO_(3-)~-N average volumetric removal rate.Mass balance analysis showed that 4.84 g A.donax was required to remove 1 g TN.Quantitative real-time PCR analysis results showed that the copy numbers of 16S r-RNA,narG,nirS,nosZ and anammox gene of carrier biofilm and suspended activated sludge in the declination phase(BF2 and AS2)were lower than those of samples in the stable phase(BF1 and AS1),and relatively higher copy numbers of nirS and nirK genes with lower abundance of narG and nosZ genes were observed.High-throughput sequencing analysis was conducted for BF2 and AS2,and similar dominant phyla and classes with different abundance were obtained.The class Gammaproteobacteria affiliated with the phylum Proteobacteria was the most dominant microbial community in both BF2(52.6%)and AS2(41.7%).The PICRUSt prediction results indicated that 33 predictive specific genes were related to denitrification process,and the relative abundance of 18 predictive specific genes in BF2 were higher than those in AS2.     

深圳市一次典型污染天气污染特征分析研究——以2016年3月空气质量为例

2016年3月31日,深圳市及其周边地区出现典型的区域性空气污染事件,多数地区的AQI超过了100.主要污染物浓度和气象要素的逐小时变化表明,该次污染天气主要是在不利气象条件下,由污染物区域传输和二次污染物生成共同导致的.进一步的后向轨迹分析表明,污染日抵达深圳市的气团可能从东莞、广州和佛山等地区携带了大量污染物,并且移动速度缓慢,造成了深圳较为严重的污染天气,而污染日前和污染日后抵达深圳市的气团有利于污染物的稀释扩散,因此空气质量较好.     

Responses of Soil CO<Subscript>2</Subscript> Efflux to Precipitation Pulses in Two Subtropical Forests in Southern China

This study was designed to examine the responses of soil CO₂ efflux to precipitation pulses of varying intensities using precipitation simulations in two subtropical forests [i.e., mixed and broadleaf forests (MF and BF)] in southern China. The artificial precipitation event was achieved by spraying a known amount of water evenly in a plot (50 × 50 cm²) over a 30 min period, with intensities ranging from 10, 20, 50 and 100 mm within the 30 min. The various intensities were simulated in both dry season (in December 2007) and wet (in May 2008) season. We characterized the dynamic patterns of soil CO₂ efflux rate and environmental factors over the 5 h experimental period. Results showed that both soil moisture and soil CO₂ efflux rate increased to peak values for most of the simulated precipitation treatments, and gradually returned to the pre-irrigation levels after irrigation in two forests. The maximum peak of soil CO₂ efflux rate occurred at the 10 mm precipitation event in the dry season in BF and was about 3.5 times that of the pre-irrigation value. The change in cumulative soil CO₂ efflux following precipitation pulses ranged from −0.68 to 1.72 g CO₂ m⁻² over 5 h compared to the pre-irrigation levels and was generally larger in the dry season than in the wet season. The positive responses of soil CO₂ efflux to precipitation pulses declined with the increases in precipitation intensity, and surprisingly turned to negative when precipitation intensity reached 50 and 100 mm in the wet season. These findings indicated that soil CO₂ efflux could be changed via pulse-like fluxes in subtropical forests in southern China as fewer but extreme precipitation events occur in the future.     

濮阳市秋冬季大气细颗粒物污染特征及来源解析

濮阳市作为京津冀周边地区大气污染传输通道城市之一,秋冬季重污染天气频发,空气污染问题严峻.为了研究濮阳市秋冬季大气细颗粒物污染特征及其主要来源,于2017年10月15日至2018年1月13日在濮阳市3个国控点对PM_(2.5)进行了手工膜采样与化学组分分析,并结合PMF受体模型,开展了细颗粒物来源解析研究.结果表明,濮阳市2017年秋冬季PM_(2.5)平均质量浓度为94. 16μg·m~(-3),濮水河管理处的污染状况最严重,进入采暖季后3站点均表现为重度及严重污染事件频发,轻度污染发生频率降低,重污染发生时NO_2与CO浓度升高明显. PM_(2.5)中的主要组分为水溶性离子(52. 33%)、碳质组分(25. 32%)和地壳元素(0. 08%),NO_3~-的含量高而SO_4~(2-)的浓度水平较低.重污染发生时,PM_(2.5)中水溶性离子、OC、EC和K浓度都出现了明显的升高,而地壳元素浓度降低.采样期间濮阳市的硫氮转化率水平较高,大气氧化性较强,硫氮转化促进了重污染的发生.濮阳市2017年NOx、CO和VOCs排放量较高,来源解析结果表明,濮阳市秋冬季PM_(2.5)主要来源分别为二次无机盐(37%)、工业源(16%)、二次有机气溶胶SOA(14%)、生物质燃烧源(12%)、移动源(9%)、燃煤源(7%)和扬尘源(4%).可见,二次转化在濮阳重污染的形成过程中起到重要作用,要减轻大气细颗粒物污染,需要重点控制工业源、生物质燃烧、移动源和民用散煤燃烧的排放.     

Fault detection approach for systems involving soft sensors

This paper develops a new approach for fault detection which involves soft sensors for process monitoring. Unlike existing approaches, which compare current measurements, or linear combinations thereof, to values of these measurements representing normal operations, the methodology presented here deals directly with the state estimates that need to be monitored. The advantage of such an approach is that the effect of abnormal process conditions on the state variables can be directly observed and that it is possible to include nonlinear relationships between measurements and states. At the same time, this type of approach has the drawback that the variances of the unmeasured states are not equal to the variances of the actual process variables due to the use of a soft sensor. However, for many popular soft sensor techniques, such as Kalman filters and related approaches, it is possible to compute variances of the predicted states that correspond to normal operating conditions. This paper presents a general framework for using soft sensors for process monitoring, i.e., soft sensor design and computation of the statistics that represent normal operating conditions, and illustrates this framework in three specific applications. It should be pointed out that the contribution of this work does not lie with the soft sensor design or the computation of the statistics itself as either part has individually already been addressed in the existing literature. However, the authors are not aware of any studies where both tasks are combined for process monitoring, which forms the contribution of this work.     

Elution of p-Dichlorobenzene through compacted soil with alcohol-water mixtures

p-Dichlorobenzene (p-DCB) was eluted through a compacted ferruginous clay with dilute aqueous solutions of methanol, ethanol, n- and i-propanols, and n- and i-butanols. The presence of the alcohols results in very marked increases in the concentrations of p-DCB in the effluents from the clay-packed columns. Flux of p-DCB through the columns increases with increasing chain length of the alcohol, and normal alcohols increase the flux somewhat more than corresponding branched alcohols. Flux increases with increasing mole fraction of the alcohol. Flux enhancement is due almost exclusively to enhancement of the solubility of p-DCB.