Effectiveness of Wastewater-Based Epidemiology as an Early Warning Tool to Detect SARS-CoV-2 (COVID-19)

Medical diagnostic tests to detect Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) for individuals in the United States were initially limited to people who were traveling or symptomatic to track disease incidence due to the cost of providing testing for all people in a community on a routine basis. As an alternative to randomly sampling large groups of people to track disease incidence at significant cost, wastewater-based epidemiology (WBE) is a well-established and cost-effective technique to passively measure the prevalence of disease in communities without requiring invasive testing. WBE can also be used as a forecasting tool since the virus is shed in individuals prior to developing symptoms that might otherwise prompt testing. This study applied the WBE approach to understand its effectiveness as a possible forecasting tool by monitoring the SARS-CoV-2 levels in raw wastewater sampled from sewer lift stations at a large public university campus setting including dormitories, academic buildings, and athletic facilities. The WBE analysis was conducted by sampling from building-specific lift stations and enumerating target viral copies using RT-qPCR analysis. The WBE results were compared with the 7-day rolling averages of confirmed infected individuals for the following week after the wastewater sample analysis. In most cases, changes in the WBE outcomes were followed by similar trends in the clinical data. The positive predictive value of the applied WBE approach was 86% for the following week of the sample collection. In contrast, positive correlations between the two data with Spearmen correlation (rs) ranged from 0.16 to 0.36. A stronger correlation (rs = 0.18 to 0.51) was observed when WBE results were compared with COVID-19 cases identified on the next day of the sampling events. The P value of 0.007 for Dorm A suggests high significance, while moderate significance was observed for the other dormitories (B, C, and D). The outcomes of this investigation demonstrate that WBE can be a valuable tool to track the progression of diseases like COVID-19 seven days before diagnostic cases are confirmed, allowing authorities to take necessary measures in advance and also enable authorities to decide to reopen a facility after a quarantine.

Optimum selection of common master image for ground deformation monitoring based on PS-DInSAR technique

Considering the joint effects of various factors such as temporal baseline, spatial baseline, thermal noise, the difference of Doppler centroid frequency and the error of data processing on the interference correlation, an optimum selection method of common master images for ground deformation monitoring based on the permanent scatterer and differential SAR interferometry （PS-DInSAR） technique is proposed, in which the joint correlation coeficient is used as the evaluation function. The principle and realization method of PS-DInSAR technology is introduced, the factors affecting the DInSAR correlation are analysed, and the joint correlation function model and its solution are presented. Finally an experiment for the optimum selection of common master images is performed by using 25 SAR images over Shanghai taken by the ERS-1/2 as test data. The results indicate that the optimum selection method for PS-DInSAR common master images is effective and reliable.

Spatial-Temporal Ground Deformation Study of Baotou Based on the PS-InSAR Method

Ground subsidence is an emerging geological hazard in Baotou,Inner Mongolia.Four areas of Baotou with relatively large subsidence range and rate were selected for analysis.Focusing on investigation of ground subsidence using PS-In SAR technology,a total of 43 frames of ALOS PALSAR images yielded a SAR data span from December 2006 to January 2011,allowing ground subsidence scope,subsidence velocity,time-series deformation to be obtained.Major causes and influencing factors of the ground subsidence are closely related to soft soil consolidation and compaction and the decrease in the level of groundwater caused by increased development and utilization of groundwater.

Boost-Phase ballistic missile trajectory estimation with ground based radar

A conditional boost-phase trajectory estimation method based on ballistic missile （BM） information database and classification is developed to estimate and predict boos-phase BM trajectory. The main uncertain factors to describe BM dynamics equation are reduced to the control law of trajectory pitch angle in boost-phase. After the BM mass at the beginning of estimation, the BM attack angle and the modification of engine thrust denoting BM acceleration are modeled reasonably, the boost-phase BM trajectory estimation with ground based radar is well realized. The validity of this estimation method is testified by computer simulation with a typical example.

Extended state observer-based control with an adjustable parameter for a large ground-based telescope

The high-precision requirements will always be constrained due to the complicated operating conditions of the ground-based telescope. Owing to various internal and external disturbances, it is necessary to study a control method, which should have a good ability on disturbance rejection and a good adaptability on system parameter variation. The traditional proportional-integral(PI) controller has the advantage of simple and easy adjustment, but it cannot deal with the disturbances well in different situations. This paper proposes a simplified active disturbance rejection control law, whose debugging is as simple as the PI controller, and with better disturbance rejection ability and parameter adaptability. It adopts a simplified second-order extended state observer(ESO) with an adjustable parameter to accommodate the significant variation of the inertia during the different design stages of the telescope. The gain parameter of the ESO can be adjusted online with a recursive least square estimating method once the system parameter has changed significantly. Thus, the ESO can estimate the total disturbances timely and the controller will compensate them accordingly. With the adjustable parameter of the ESO, the controller can always achieve better performance in different applications of the telescope. The simulation and experimental verification of the control law was conducted on a 1.2-meter ground based telescope. The results verify the necessity of adjusting the parameter of the ESO, and demonstrate better disturbance rejection ability in a large range of speed variations during the design stages of the telescope.

Knowledge-based bridge detection from SAR images

Automatic bridge detection is an important application of SAR images. Differed from the classical CFAR method, a new knowledge-based bridge detection approach is proposed. The method not only uses the backscattering intensity difference between targets and background but also applies the contextual information and spatial relationship between objects. According to bridges＇ special characteristics and scattering properties in SAR images, the new knowledge-based method includes three processes： river segmentation, potential bridge areas detection and bridge discrimination. The application to AIRSAR data shows that the new method is not sensitive to rivers＇ shape. Moreover, this method can detect bridges successfully when river segmentation is not very exact and is more robust than the radius projection method.

Satellite-based RAR performance simulation for measuring directional ocean wave spectrum based on SAR inversion spectrum

Some missions have been carried out to measure wave directional spectrum by synthetic aperture radar （SAR） and airborne real aperture radar （RAR） at a low incidence.Both them have their own advantages and limitations.Scientists hope that SAR and satellite-based RAR can complement each other for the research on wave properties in the future.For this study,the authors aim to simulate the satellite-based RAR system to validate performance for measuring the directional wave spectrum.The principal measurements are introduced and the simulation methods based on the one developed by Hauser are adopted and slightly modified.To enhance the authenticity of input spectrum and the wave spectrum measuring consistency for SAR and satellite-based RAR,the wave height spectrum inversed from Envisat ASAR data by cross spectrum technology is used as the input spectrum of the simulation system.In the process of simulation,the sea surface,backscattering signal,modulation spectrum and the estimated wave height spectrum are simulated in each look direction.Directional wave spectrum are measured based on the simulated observations from 0 ？ to 360 ？ .From the estimated wave spectrum,it has an 180 ？ ambiguity like SAR,but it has no special high wave number cut off in all the direction.Finally,the estimated spectrum is compared with the input one in terms of the dominant wave wavelength,direction and SWH and the results are promising.The simulation shows that satellite-based RAR should be capable of measuring the directional wave properties.Moreover,it indicates satellite-based RAR basically can measure waves that SAR can measure.

Long-term gravity changes in Chinese mainland from GRACE and ground-based gravity measurements

A long-term （9 years） gravity change in Chinese mainland is obtained on the basis of observation of the ground-based national gravity network. The result shows several features that may be related to sore, large-scale groundwater pumping in North China, glacier-water flow and storage in Tianshan region, and pre seismic gravity changes of the 2008 MsS. 0 Wenchuan earthquake, which are spatially similar to co-seismi, changes but reversed in sign. These features are also shown in the result of the satellite-based GRACE obser vation, after a height effect is corrected with GPS data.

0-10 KM TEMPERATURE AND HUMIDITY PROFILES RETRIEVAL FROM GROUND-BASED MICROWAVE RADIOMETER

Deviation exists between measured and simulated microwave radiometer sounding data. The bias results in low-accuracy atmospheric temperature and humidity profiles simulated by Back Propagation artificial neural network models. This paper evaluated a retrieving atmospheric temperature and humidity profiles method by adopting an input data adjustment-based Back Propagation artificial neural networks model. First, the sounding data acquired at a Nanjing meteorological site in June 2014 were inputted into the Mono RTM Radiative transfer model to simulate atmospheric downwelling radiance at the 22 spectral channels from 22.234 GHz to 58.8 GHz, and we performed a comparison and analysis of the real observed data; an adjustment model for the measured microwave radiometer sounding data was built. Second, we simulated the sounding data of the 22 channels using the sounding data acquired at the site from 2011 to 2013. Based on the simulated rightness temperature data and the sounding data, BP neural network-based models were trained for the retrieval of atmospheric temperature, water vapor density and relative humidity profiles. Finally, we applied the adjustment model to the microwave radiometer sounding data collected in July 2014, generating the corrected data. After that, we inputted the corrected data into the BP neural network regression model to predict the atmospheric temperature, vapor density and relative humidity profile at 58 high levels from 0 to 10 km. We evaluated our model's effect by comparing its output with the real measured data and the microwave radiometer's own second-level product. The experiments showed that the inversion model improves atmospheric temperature and humidity profile retrieval accuracy; the atmospheric temperature RMS error is between 1 K and 2.0 K; the water vapor density's RMS error is between 0.2 g/m^3 and 1.93 g/m3; and the relative humidity's RMS error is between 2.5% and 18.6%.

Ground Motion and Site Effects on Performance-Based Design

The objective of Performance-Based Earthquake Engineering （PBEE） is the analysis of performance objectives with a specified annual probability of exceedance. Increasingly undesirable performance is caused by increasing levels of strong ground motion having decreasing annual probabilities of exceedance. The development of this methodology includes three steps： （1） evaluation of the distribution of ground motion at a site; （2） evaluation of the distribution of system response; （3） evaluation of the probability of exceeding decision variables within a given time period, given appropriate damage measures. The work has taken a systematic approach to determine the impact of increasing levels of detail in site characterization on the accuracy of ground motion and site effects predictions. Complementary studies have investigated the use of the following models for evaluating site effects： （1） amplification factors defined on the basis of generalized site categories, （2） one-dimensional ground response analysis, and （3） two-dimensional ground response analysis for surface topography on ground motion. The paper provides a brief synthesis of ground motion and site effects analysis procedures within a Performance-Based Design framework. It focuses about the influence on the evaluation of site effects in some active regions by different shear waves velocity measurements Down Hole （D-H）, Cross Hole （C-H）, Seismic Dilatometer Marchetti Test （SDMT） and by different variation of shear modulus and damping ratio with strain level and depth from different laboratory dynamic tests for soil characterization： Resonant Column Test （RCT）, Cyclic Loading Torsional Shear Test （CLTST）.

Validation of total ozone data between satellite and ground-based measurements at Zhongshan and Syowa stations in Antarctica

We present validation between total ozone from satellite and ground-based observations of the Dobson and Brewer spectrometers and ozone radiosonde at Zhongshan and Syowa Antarctic research stations, for September 2004 to March 2009. Results show that mean bias error between Zhongshan （Syowa） and Ozone Monitor Instrument Total Ozone Mapping Spectrometer （OMI-TOMS） data are -0.06%＋3.32% （-0.44%：i：2.41%）; between it and OMI Multi Axis Differential Optical Absorption Spec- troscopy （OMI-DOAS） data, the error is -0.34%--4.99% （-0.22%~4.85%）. Mean absolute bias error values of OMI-TOMS data are less than those of OMI-DOAS. This means that total ozone of OMI-TOMS is closer to ground-based observation than that of OMI-DOAS. Comparison between direct observational total ozone of ground-based and integrated ozone from the ozone profile measured by ozone radiosonde shows that ozone amount calculated with the Solar Backscatter Ultraviolet （SBUV） method above balloon burst height is similar to corresponding Microwave Limb Sounder （MLS） data. Therefore, MLS data can be substituted with SBUV data to estimate ozone amount above that level. Mean bias error of the MLS ozone column is 2% compared with the ozonesonde column, with standard deviation within 9.5%. Comparison of different layers from ozone profiler and MLS data indi- cates that at the 215 hPa layer, the MLS ozone value is high, with relative deviation more than 20%. At the 100 hPa and 68 l^Pa layers, the MLS ozone value is also high. This deviation is mainly in spring, during Antarctic ozone hole appearance. In this period, at the height of severe ozone loss, relative deviation of MLS ozone values is especially large.

Trends in gravity changes from 2009 to 2013 derived from ground-based gravimetry and GRACE data in North China

North China is a key region for studying geophysical progress. In this study, ground-based and Gravity Recovery and Climate Experiment（GRACE） gravity data from 2009 to 2013 are used to calculate the gravity change rate（GCR） using the polynomial fitting method. In general, the study area was divided into the Shanxi rift, Jing-Jin-Ji（Beijing-Tianjin-Hebei Province）, and Bohai Bay Basin（BBB） regions. Results of the distribution of the GCR determined from ground-based gravimetry show that the GCR appears to be ＂negativepositive-negative＂ from west to east, which indicates that different geophysical mechanisms are involved in the tectonic activities of these regions. However, GRACE solutions are conducted over a larger spatial scale and are able to show a difference between southern and northern areas and a mass redistribution of land water storage.

A Differential Optical Absorption Spectroscopy Method for X_(CO_2) Retrieval from Ground-Based Fourier Transform Spectrometers Measurements of the Direct Solar Beam

A differential optical absorption spectroscopy （DOAS）-like algorithm is developed to retrieve the column-averaged dry- air mole fraction of carbon dioxide from ground-based hyper-spectral measurements of the direct solar beam. Different to the spectral fitting method, which minimizes the difference between the observed and simulated spectra, the ratios of multiple channel-pairs--one weak and one strong absorption channel--are used to retrieve Xc02 from measurements of the shortwave infrared （SWIR） band. Based on sensitivity tests, a super channel-pair is carefully selected to reduce the effects of solar lines, water vapor, air temperature, pressure, instrument noise, and frequency shift on retrieval errors. The new algorithm reduces computational cost and the retrievals are le^s sensitive to temperature and H20 uncertainty than the spectral fitting method. Multi-day Total Carbon Column Observing Network （TCCON） measurements under clear-sky conditions at two sites （Tsukuba and Bremen） are used to derive Xc02 for the algorithm evaluation and validation. The DOAS-like results agree very well with those of the TCCON algorithm after correction of an airmass-dependent bias.

Knowledge-based detection method for SAR targets

When the classical constant false-alarm rate （CFAR） combined with fuzzy C-means （FCM） algorithm is applied to target detection in synthetic aperture radar （SAR） images with complex background, CFAR requires block-by-block estimation of clutter models and FCM clustering converges to local optimum. To address these problems, this paper pro-poses a new detection algorithm： knowledge-based combined with improved genetic algorithm-fuzzy C-means （GA-FCM） algorithm. Firstly, the algorithm takes target region＇s maximum and average intensity, area, length of long axis and long-to-short axis ratio of the external ellipse as factors which influence the target appearing probabil- ity. The knowledge-based detection algorithm can produce preprocess results without the need of estimation of clutter models as CFAR does. Afterward the GA-FCM algorithm is improved to cluster pre-process results. It has advantages of incorporating global optimizing ability of GA and local optimizing ability of FCM, which will further eliminate false alarms and get better results. The effectiveness of the proposed technique is experimentally validated with real SAR images.

Ground-based remote sensing of atmospheric total column CO_2 and CH_4 by direct sunlight in Hefei

Fourier transform spectrometry has played an important role in the three-dimensional greenhouse gas monitoring as the focus of attention on global warming in the past few years. In this paper, a ground-based low-resolution remote sensing system measuring the total columns of CO2 and CH4 is developed, which tracks the sun automatically and records the spectra in real-time and has the advantages of portability and low cost. A spectral inversion algorithm based on nonlinear least squares spectral fitting procedure for determining the column concentrations of these species is described. Atmospheric transmittance spectra are computed line-by-line in the forward model and observed on-line by direct solar radiation. Also, the wavelength shifts are introduced and the influence of spectral resolution is discussed. Based on this system and algorithm, the vertical columns of O2, CO2, and CH4 are calculated from total atmospheric observation transmittance spectra in Hefei, and the results show that the column averaged dry-air mole fractions of CO2 and CH4 are measured with accuracies of 3.7% and 5%, respectively. Finally, the H2O columns are compared with the results observed by solar radiometer at the same site and the calculated correlation coefficient is 0.92, which proves that this system is suitable for field campaigns and used to monitor the local greenhouse gas sources under the condition of higher accuracy, indirectly.

Primary Analysis of Sounding Data from a Multi-channel Parallel Ground-based Microwave Radiometer

The sounding data of a multi-channel parallel ground-based microwave radiometer （MWR） in Fuzhou station in July and August in 2016 were compared with the sounding data of a radiosonde in the same position in the same period. The results showed that the correlations between the two types of temperature or humidity detected by the microwave radiometer and the radiosonde were significant at 0.05 level, indicating that the overall changing trends of temperature or humidity detected by the two devices were similar. The temperature detected by the microwave radiometer and the radiosonde decreased with the increase of height. The difference between the changes in the height of the zero layer detected by the micro- wave radiometer and the radiosonde was not significant, and their trends were basically the same.

Ground-Based Cloud Using Exponential Entropy/Exponential Gray Entropy and UPSO

Objective and accurate classification model or method of cloud image is a prerequisite for accurate weather monitoring and forecast.Thus safety of aircraft taking off and landing and air flight can be guaranteed.Thresholding is a kind of simple and effective method of cloud classification.It can realize automated ground-based cloud detection and cloudage observation.The existing segmentation methods based on fixed threshold and single threshold cannot achieve good segmentation effect.Thus it is difficult to obtain the accurate result of cloud detection and cloudage observation.In view of the above-mentioned problems,multi-thresholding methods of ground-based cloud based on exponential entropy/exponential gray entropy and uniform searching particle swarm optimization(UPSO)are proposed.Exponential entropy and exponential gray entropy make up for the defects of undefined value and zero value in Shannon entropy.In addition,exponential gray entropy reflects the relative uniformity of gray levels within the cloud cluster and background cluster.Cloud regions and background regions of different gray level ranges can be distinguished more precisely using the multi-thresholding strategy.In order to reduce computational complexity of original exhaustive algorithm for multi-threshold selection,the UPSO algorithm is adopted.It can find the optimal thresholds quickly and accurately.As a result,the real-time processing of segmentation of groundbased cloud image can be realized.The experimental results show that,in comparison with the existing groundbased cloud image segmentation methods and multi-thresholding method based on maximum Shannon entropy,the proposed methods can extract the boundary shape,textures and details feature of cloud more clearly.Therefore,the accuracies of cloudage detection and morphology classification for ground-based cloud are both improved.

一种Vcm-Based10位16M采样率低功耗逐次逼近型模数转换器

针对无线传感网络中低功耗无线传感器的应用,设计了一种采样速率为16MSPS,精度10bit的全差分超低功耗逐次逼近型模数转换器(SAR ADC).提出一种基于Vcm-Based参考电压的开关切换逻辑,减少DAC模块参考电压开关切换的功耗.同时,DAC电容阵列模块采用分段式结构,单位电容采用优化的MOM电容,有效提高ADC的匹配性和精度;此外采用了双尾电流型动态锁存比较器,实现功耗的最优化.芯片采用CMOS 65nm工艺设计,后仿结果显示在1.2V电源电压及16MSPS采样率下,ADC有效位数达到9.42bit,功耗为140μW,品质因数(FOM)为12.8fJ/Conversion-step.

Probabilistic analysis for the response of nonlinear base isolation system under the ground excitation induced by high dam flood discharge

According to theoretical analysis, a general characteristic of the ground vibration induced by high dam flood discharge is that the dominant frequency ranges over several narrow frequency bands, which is verified by observations from the Xiangjiaba Hydropower Station. Nonlinear base isolation is used to reduce the structure vibration under ground excitation and the advantage of the isolation application is that the low-frequency resonance problem does not need to be considered due to its excitation characteristics, which significantly facilitate the isolation design. In order to obtain the response probabilistic distribution of a nonlinear system, the state space split technique is modified. As only a few degrees of freedom are subjected to the random noise, the probabilistic distribution of the response without involving stochastic excitation is represented by the δ function. Then, the sampling property of the δ function is employed to reduce the dimension of the Fokker-Planck-Kolmogorov （FPK） equation and the low-dimensional FPK equation is solvable with existing methods. Numerical results indicate that the proposed approach is effective and accurate. Moreover, the response probabilistic distributions are more reasonable and scientific than the peak responses calculated by conventional time and frequency domain methods.

基于GB-SAR的矿山边坡局部变形演化与失稳预测

为了提高地基合成孔径雷达(ground-based synthetic aperture radar, GB-SAR)边坡监测效果与失稳预测能力,在广东省某石灰石矿山架设地基雷达,开展实地监测试验,结合矿山地质条件与监测数据研究不同类型的岩体变形演化特征,根据变形特征选择位移最大点的监测数据利用速度倒数法进行失稳预测。通过分析典型案例的监测数据来优化速度倒数法的算法,进而对矿山试验数据进行研究。研究结果表明:通过分析雷达三维模型变形图的局部位移差异,能够初步判断边坡岩体的变形破坏方式;适当增大移动平均滤波法的移动时间周期C,能够更早地发现灾害征兆,更好地识别岩体加速变形阶段及临滑阶段。研究结果可为基于雷达的滑坡预测提供参考。