Biosensors as a tool for the antioxidant status evaluation

Antioxidants are one of the main ingredients that protect food attributes by preventing oxidation that occurs during processing, distribution and end preparation of food. Physiological antioxidant protection involves a variety of chemical system of endogenous and exogenous origin in a multiplicity of pathways. Associate to this, researches have been directed in the development of methods as biosensors that can characterize antioxidants capable of removing harmful radicals in living organisms in an adequate way. Biosensors have represented a broad area of technology useful for environmental, food monitoring, clinical applications and can represent a good alternative method to evaluate the antioxidant status.The demonstration of the highlighted current application of biosensor as a potential tool to evaluate the antioxidant status is the main aim of this review.     

基于MODIS数据的山西省PM2.5浓度估算研究

通过ENVI软件对美国国家航空航天局（NASA）发布的MODIS L1B数据进行几何校正、波段合成、重采样、构建查找表等操作,反演了山西省2020年3—8月气溶胶光学厚度（aerosol optical depth,AOD）,用大气气溶胶产品MOD04_3K验证AOD的反演精度,对反演结果中的高度进行订正,分析了山西省AOD时空分布特征,在此基础上建立了AOD与PM_2.5浓度的回归模型,并通过模型验证估算误差。结果表明：（1）MODIS L1B反演结果具有较高的精度,与大气气溶胶产品MOD04_3K数据的相关系数为0.934。（2）在时间分布上,AOD存在明显的季节性差异,夏季AOD均值远高于春季;在空间分布上,AOD呈现由北向南逐渐增加的趋势,高值主要出现在山西省南部的临汾市和运城市。（3）整体、春季、夏季3类回归模型的平均相对误差分别为25.91%,27.62%,23.87%,表明模型的拟合效果较好,可较为准确地估算PM_2.5浓度。     

Fixed Rank Filtering for Spatio-Temporal Data

Datasets from remote-sensing platforms and sensor networks are often spatial, temporal, and very large. Processing massive amounts of data to provide current estimates of the (hidden) state from current and past data is challenging, even for the Kalman filter. A large number of spatial locations observed through time can quickly lead to an overwhelmingly high-dimensional statistical model. Dimension reduction without sacrificing complexity is our goal in this article. We demonstrate how a Spatio-Temporal Random Effects (STRE) component of a statistical model reduces the problem to one of fixed dimension with a very fast statistical solution, a methodology we call Fixed Rank Filtering (FRF). This is compared in a simulation experiment to successive, spatial-only predictions based on an analogous Spatial Random Effects (SRE) model, and the value of incorporating temporal dependence is quantified. A remote-sensing dataset of aerosol optical depth (AOD), from the Multi-angle Imaging SpectroRadiometer (MISR) instrument on the Terra satellite, is used to compare spatio-temporal FRF with spatial-only prediction. FRF achieves rapid production of optimally filtered AOD predictions, along with their prediction standard errors. In our case, over 100,000 spatio-temporal data were processed: Parameter estimation took 64.4 seconds and optimal predictions and their standard errors took 77.3 seconds to compute. Supplemental materials giving complete details on the design and analysis of a simulation experiment, the simulation code, and the MISR data used are available on-line.     

Application of LIBS to the in-line process control of liquid high-alloy steel under pressure

A process optimization and control system called VAI-CON Chem has been developed that uses laser-induced breakdown spectroscopy (LIBS) to quasi-continuously chemically analyze liquid high-alloy steel under pressure. The beam from a Nd:YAG laser, located on safe ground and operating at its fundamental wavelength, is guided by a mirror system to a process tuyere below bath level. Passing through the ∼1.5 m long tuyere, the beam is then focused onto the steel bath. Light emitted from the induced plasma passes back through the tuyere, which is coupled to a fiber optic cable that carries the information over a distance of approximately 10 m back to an Echelle spectrometer located beside the laser. Calibrations were performed using the complete system, located in a laboratory, during system testing. An induction furnace was used to simulate the AOD converter, wherein the samples were molten and superheated to a temperature of ∼1600 °C and kept at a pressure of ∼1.7 bar under an argon atmosphere. Twelve different high alloyed reference samples taken from normal AOD production with Fe concentrations of >48 wt.% and non-Fe element concentrations of up to 25 wt.% were available for calibration. The mean residual deviations (defined as the square root of the variance of the concentration ratios determined by LIBS and the reference element concentration ratios) obtained were close to those reported for other comparable high-alloy samples that were investigated at room temperature under normal atmospheric pressure.     

基于CALIOP和MODIS数据的气溶胶时空分布特征对比分析

利用两个AERONET站点（Hangzhou_ZFU、SACOL）的Level 2 气溶胶光学厚度（aerosol optical depth, AOD）数据对比验证CALIOP Level 2 AOD数据。结果表明：Hangzhou_ZFU、SACOL站的相关系数为0.87、0.85,回归方程的斜率为0.76、0.92,这表明CALIOP AOD与AERONET AOD显著相关,在这两个站点及附近区域具有适应性。基于2008~2015年无云条件下的CALIOP Level 3月气溶胶产品和同期的MODIS Terra/Aqua Level 3月气溶胶产品,对比分析中国东南和西北区域气溶胶光学厚度（aerosol optical depth, AOD）时空分布特征。分析表明：中国东南区域AOD季节与空间变化明显,AOD高值主要分布在长三角、珠三角等地,且夏季最高、春季次之,秋冬季相当。MODIS AOD月均值保持在在0.25~0.8之间,且与CALIOP 夜间AOD值接近,但与CALIOP白天AOD值差异较大,最大相差值可达0.45。中国西北区域两种卫星获取的AOD值空间分布非常相似,其高值区都位于塔里木盆地、准格尔盆地和柴达木盆地;AOD值春季最高,夏季减少、冬季次之、秋季最低;MODIS AOD值波动显著且普遍高于CALIOP AOD值。     

Long-term trend in aerosol optical depth from 1980 to 2001 in north China

Using the Total Ozone Mapping Spectrometer （TOMS） monthly aerosol optical depth （AOD） at 500 nm data from 1980 to 2001 in north China, the spatial and temporal variations of AOD were examined. Seasonal AODs in Taklimakan Desert were 0.69 and 0.44 in spring and summer, respectively, which were mainly due to frequent occurrences of dust events in this region. Dust activities in spring also led to high aerosol loading in Gobi Desert and in northeast China where spring AODs were 0.33 and 0.29, respectively. Heavily impacted by events such as volcano eruption, forest fires and extraordinary dust storms, AODs showed large inter-annual variations. A decreasing tendency in AOD was observed in north China during 1980-1991, though a reverse tendency was revealed during 1997-2001, especially for spring AOD in northeast China. Further study is required to figure out how much human activities have contributed to the AOD tendency in north China.     

AEDAL在青岛、渤海及黄海探测的定标反演

在不进行大气参数假设和加载其他辅助设备的情况下,通过对AEDAL机载大气环境探测激光雷达探测数据的分析,证明了用Slope法对空基激光雷达进行定标反演的可行性。AEDAL的定标反演结果,生动地展现了青岛地区及渤海、黄海海域气溶胶垂直分布、边界层结构及边界层光学厚度的重要特征。首先,冷锋过境,边界层高度明显下降的同时,气溶胶出现多层分布的现象,海区气溶胶垂直分布较陆地有明显的沉降现象。其次,青岛地区整个边界层光学厚度表现为城区最大、丘陵地区最小、渤海海区介于两者之间的分布特点,海区边界层光学厚度变化相对平缓,迎风坡附近的边界层光学厚度较周围有所增大。青岛至渤海这一区域,晴朗天气下边界层光学厚度的大小介于0.15～0.35之间,雾天则在0.3～0.45之间,而黄海海域则可达到0.55左右。这说明,青岛地区边界层气溶胶主要来自于城市和海洋,在冬季季风对气溶胶分布起作用的同时,山脉及地面风场对边界层气溶胶的输送有重要影响。     

Long-term trend in aerosol optical depth from 1980 to 2001 in north China

Using the Total Ozone Mapping Spectrometer (TOMS) monthly aerosol optical depth (AOD) at 500 nm data from 1980 to 2001 in north China, the spatial and temporal variations of AOD were examined. Seasonal AODs in Taldimakan Desert were 0.69 and 0.44 in spring and summer,respectively, which were mainly due to frequent occurrences of dust events in this region. Dust activities in spring also led to high aerosol loading in Gobi Desert and in northeast China where spring AODs were 0.33 and 0.29, respectively. Heavily impacted by events such as volcano eruption, forest fires and extraordinary dust storms, AODs showed large inter-annual variations. A decreasing tendency in AOD was observed in north China during 1980-1991, though a reverse tendency was revealed during 1997-2001, especially for spring AOD in northeast China. Further study is required to figure out how much human activities have contributed to the AOD tendency in north China.     

基于星载激光雷达数据的海面风速探测

使用新版(Version 3.01)星载激光雷达CALIPSO Level 1剖面数据和Level 2的大气气溶胶光学厚度(AOD)数据反演全球海面风速。将AOD数据用于大气双程透射率的校正。对CALIPSO所采集的2007年1月、4月、7月和10月532nm波长无云激光测量数据进行应用计算,采用532nm退偏比经验修正海面白帽及水下次表层水体散射的影响,同时选用准同步的AMSR-E海面风速测量值为真值进行对比。对应2007年的4个月,由CALIPSO星载激光雷达532nm单脉冲测量数据反演海面风速的标准偏差分别为1.24、1.24、1.24、1.20m/s,由5km滚动平均数据反演海面风速的标准偏差分别为0.98、1.02、0.98、0.94m/s。结果表明,采用的数据反演方法可行且数据利用率得到提高。     

非线性最优化的MODIS气溶胶多参数反演研究

为了弥补地基观测气溶胶光学厚度(Aerosol Optical Depth, AOD)范围受限等缺点,通过卫星影像反演AOD的方法逐渐兴起,而简化气溶胶反演算法（Simplified Aerosol Retrieval Algorithm, SARA）与传统反演方法相比更具普适性。为进一步提升精度,提出了一种非线性最优化的中分辨率成像光谱仪（Moderate-resolution Imaging Spectroradiometer,MODIS）气溶胶多参数反演方法。该方法以SARA反演的AOD为初始值,对AOD、单次散射反照率(Single Scattering Albedo, SSA)(ω)、不对称性因子(Asymmetric Factor, ASY)(g)、地表反射率拟合参数（ρ′s=k*ρs+b）同时优化,以期得到最优解。结果表明,同等条件下,非线性最优化方法明显优于SARA。单点精度验证结果与全球气溶胶自动观测网(Aerosol Robotic Network, AERONET)相比,非线性最优化方法的相关系数为0.8118,优于SARA的0.2624。与官方气溶胶产品(MOD04)相比,7月6日非线性最优化方法的相关系数为0.7612,优于SARA的0.5916;5月3日非线性最优化方法的相关系数为0.9036,优于SARA的0.8788。