Description: Dynamic calibration is one of the important ways to acquire the dynamic performance parameters of a pressure sensor. This research focuses on the processing method for the output of calibrated pressure sensor, and mainly attempts to solve the problem of extracting the true information of step response under strong interference noise. A dynamic calibration system based on a shock tube is established to excite the time-domain response signal of a calibrated pressure sensor. A key processing on difference modeling is applied for the obtained signal, and several generating sequences are established. A fusion process for the generating sequences is then undertaken, and the true information of the step response of the calibrated pressure sensor can be obtained. Finally, by implementing the common QR decomposition method to deal with the true information, a dynamic model characterizing the dynamic performance of the calibrated pressure sensor is established. A typical pressure sensor was used to perform calibration tests and a frequency-domain experiment for the sensor was also conducted. Results show that the proposed method could effectively filter strong interference noise in the output of the sensor and the corresponding dynamic model could effectively characterize the dynamic performance of the pressure sensor.

Description: This paper reports the mineralogical and geochemical compositions of the Late Permian C2, C5a, C5b, C6a, and C6b semianthracite coals from the Mahe mine, northeastern Yunnan, China. Minerals in the coals are mainly made up of quartz, chamosite, kaolinite, mixed-layer illite/smectite (I/S), pyrite, and calcite; followed by anatase, dolomite, siderite, illite and marcasite. Similar to the Late Permian coals from eastern Yunnan, the authigenic quartz and chamosite were precipitated from the weathering solution of Emeishan basalt, while kaolinite and mixed-layer I/S occurring as lenses or thin beds were related to the weathering residual detrital of Emeishan basalt. However, the euhedral quartz and apatite particles in the Mahe coals were attributed to silicic-rock detrital input. It further indicates that there has been silicic igneous eruption in the northeastern Yunnan. Due to the silicic rock detrital input, the Eu/Eu* value of the Mahe coals is lower than that of the Late Permian coals from eastern Yunnan, where the detrital particles were mainly derived from the basalt. The high contents of Sc, V, Cr, Co, Ni, Cu, Ga, and Sn in the Mahe coals were mainly derived from the Kangdian Upland.

Description: Land-surface reflectance, estimated from satellite observations through atmospheric corrections, is an essential parameter for further retrieval of various high level land-surface parameters, such as leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and surface albedo. Although great efforts have been made, land-surface reflectance products still contain considerable noise caused by, e.g., cloud or mixed-cloud pixels, which results in temporal and spatial inconsistencies in subsequent downstream products. In this study, a new method is developed to remove the residual clouds in the Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface reflectance product and reconstruct time series of surface reflectance for the red, near infrared (NIR), and shortwave infrared (SWIR) bands. A smoothing method is introduced to calculate upper envelopes of vegetation indices (VIs) from the surface reflectance data and the cloud contaminated reflectance data are identified using the time series VIs and the upper envelopes of the time series VIs. Surface reflectance was then reconstructed according to cloud-free surface reflectance by incorporating the upper envelopes of the time series VIs as constraint conditions. The method was applied to reconstruct time series of surface reflectance from MODIS/TERRA surface reflectance product (MOD09A1). Temporal consistency analysis indicates that the new method can reconstruct temporally-continuous time series of land-surface reflectance. Comparisons with cloud-free MODIS/AQUA surface reflectance product (MYD09A1) over the BELMANIP (Benchmark Land Multisite Analysis and Intercomparison of Products) sites in 2003 demonstrate that the new method provides better performance for the red band (R2 = 0.8606 and RMSE = 0.0366) and NIR band (R2 = 0.6934 and RMSE = 0.0519), than the time series cloud detection (TSCD) algorithm (R2 = 0.5811 and RMSE = 0.0649; and R2 = 0.5005 and RMSE = 0.0675, respectively).

Description: PM2.5 (Particulate Matter 2.5) samples were collected at Mount Heng and analyzed for polycyclic aromatic hydrocarbons (PAHs). During sampling, a sandstorm from northern China struck Mount Heng and resulted in a mean PM2.5 concentration of 150.61 μg/m3, which greatly exceeded the concentration measured under normal conditions (no sandstorm: 58.50 μg/m3). The average mass of PAHs in PM2.5 was 30.70 μg/g, which was much lower than in the non-sandstorm samples (80.80 μg/g). Therefore, the sandstorm increased particle levels but decreased PAH concentrations due to dilution and turbulence. During the sandstorm, the concentrations of 4- and 5-ring PAHs were below their detection limits, and 6-ring PAHs were the most abundant. Under normal conditions, the concentrations of 2-, 3- and 6-ring PAHs were higher, and 4- and 5-ring PAHs were lower relative to the other sampling sites. In general, the PAH contamination was low to medium at Mount Heng. Higher LMW (low molecular weight) concentrations were primarily linked to meteorological conditions, and higher HMW (high molecular weight) concentrations primarily resulted from long-range transport. Analysis of diagnostic ratios indicated that PM2.5 PAHs had been emitted during the combustion of coal, wood or petroleum. The transport characteristics and origins of the PAHs were investigated using backwards Lagrangian particle dispersion modeling. Under normal conditions, the “footprint” retroplumes and potential source contributions of PAHs for the highest and lowest concentrations indicated that local sources had little effect. In contrast, long-range transport played a vital role in the levels of PM2.5 and PAHs in the high-altitude atmosphere.

Description: An electronic nose (e-nose) was used to characterize sesame oils processed by three different methods (hot-pressed, cold-pressed, and refined), as well as blends of the sesame oils and soybean oil. Seven classification and prediction methods, namely PCA, LDA, PLS, KNN, SVM, LASSO and RF, were used to analyze the e-nose data. The classification accuracy and MAUC were employed to evaluate the performance of these methods. The results indicated that sesame oils processed with different methods resulted in different sensor responses, with cold-pressed sesame oil producing the strongest sensor signals, followed by the hot-pressed sesame oil. The blends of pressed sesame oils with refined sesame oil were more difficult to be distinguished than the blends of pressed sesame oils and refined soybean oil. LDA, KNN, and SVM outperformed the other classification methods in distinguishing sesame oil blends. KNN, LASSO, PLS, and SVM (with linear kernel), and RF models could adequately predict the adulteration level (% of added soybean oil) in the sesame oil blends. Among the prediction models, KNN with k = 1 and 2 yielded the best prediction results.

Description: Vibration sensor data from a mechanical system are often associated with important measurement information useful for machinery fault diagnosis. However, in practice the existence of background noise makes it difficult to identify the fault signature from the sensing data. This paper introduces the time-frequency manifold (TFM) concept into sensor data denoising and proposes a novel denoising method for reliable machinery fault diagnosis. The TFM signature reflects the intrinsic time-frequency structure of a non-stationary signal. The proposed method intends to realize data denoising by synthesizing the TFM using time-frequency synthesis and phase space reconstruction (PSR) synthesis. Due to the merits of the TFM in noise suppression and resolution enhancement, the denoised signal would have satisfactory denoising effects, as well as inherent time-frequency structure keeping. Moreover, this paper presents a clustering-based statistical parameter to evaluate the proposed method, and also presents a new diagnostic approach, called frequency probability time series (FPTS) spectral analysis, to show its effectiveness in fault diagnosis. The proposed TFM-based data denoising method has been employed to deal with a set of vibration sensor data from defective bearings, and the results verify that for machinery fault diagnosis the method is superior to two traditional denoising methods.

Description: Sensors, Vol. 18, Pages 1240: Key Processes of Silicon-On-Glass MEMS Fabrication Technology for Gyroscope Application Sensors doi: 10.3390/s18041240 Authors: Zhibo Ma Yinan Wang Qiang Shen Han Zhang Xuetao Guo MEMS fabrication that is based on the silicon-on-glass (SOG) process requires many steps, including patterning, anodic bonding, deep reactive ion etching (DRIE), and chemical mechanical polishing (CMP). The effects of the process parameters of CMP and DRIE are investigated in this study. The process parameters of CMP, such as abrasive size, load pressure, and pH value of SF1 solution are examined to optimize the total thickness variation in the structure and the surface quality. The ratio of etching and passivation cycle time and the process pressure are also adjusted to achieve satisfactory performance during DRIE. The process is optimized to avoid neither the notching nor lag effects on the fabricated silicon structures. For demonstrating the capability of the modified CMP and DRIE processes, a z-axis micro gyroscope is fabricated that is based on the SOG process. Initial test results show that the average surface roughness of silicon is below 1.13 nm and the thickness of the silicon is measured to be 50 μm. All of the structures are well defined without the footing effect by the use of the modified DRIE process. The initial performance test results of the resonant frequency for the drive and sense modes are 4.048 and 4.076 kHz, respectively. The demands for this kind of SOG MEMS device can be fulfilled using the optimized process.

Description: Entropy, Vol. 19, Pages 609: Maximum Entropy-Copula Method for Hydrological Risk Analysis under Uncertainty: A Case Study on the Loess Plateau, China Entropy doi: 10.3390/e19110609 Authors: Aijun Guo Jianxia Chang Yimin Wang Qiang Huang Zhihui Guo Copula functions have been extensively used to describe the joint behaviors of extreme hydrological events and to analyze hydrological risk. Advanced marginal distribution inference, for example, the maximum entropy theory, is particularly beneficial for improving the performance of the copulas. The goal of this paper, therefore, is twofold; first, to develop a coupled maximum entropy-copula method for hydrological risk analysis through deriving the bivariate return periods, risk, reliability and bivariate design events; and second, to reveal the impact of marginal distribution selection uncertainty and sampling uncertainty on bivariate design event identification. Particularly, the uncertainties involved in the second goal have not yet received significant consideration. The designed framework for hydrological risk analysis related to flood and extreme precipitation events is exemplarily applied in two catchments of the Loess plateau, China. Results show that (1) distribution derived by the maximum entropy principle outperforms the conventional distributions for the probabilistic modeling of flood and extreme precipitation events; (2) the bivariate return periods, risk, reliability and bivariate design events are able to be derived using the coupled entropy-copula method; (3) uncertainty analysis highlights the fact that appropriate performance of marginal distribution is closely related to bivariate design event identification. Most importantly, sampling uncertainty causes the confidence regions of bivariate design events with return periods of 30 years to be very large, overlapping with the values of flood and extreme precipitation, which have return periods of 10 and 50 years, respectively. The large confidence regions of bivariate design events greatly challenge its application in practical engineering design.

Description: Sustainability, Vol. 10, Pages 928: Carbon Footprint and Driving Forces of Saline Agriculture in Coastally Reclaimed Areas of Eastern China: A Survey of Four Staple Crops Sustainability doi: 10.3390/su10040928 Authors: Jianguo Li Wenhui Yang Yi Wang Qiang Li Lili Liu Zhongqi Zhang Carbon emissions have always been a key issue in agricultural production. Due to the specific natural factors in the soil of saline agriculture, there are distinctive characteristics in saline agricultural production as compared with traditional agricultural zones. Here, we have adopted the theory of life cycle assessment and employed the Intergovernmental Panel on Climate Change (IPCC) greenhouse gas (GHG) field calculation to estimate the GHG emissions, derived from the staple crop productions (i.e., barley, wheat, corn and rice). In addition, our study further analyzed the main driving forces of carbon emissions and proposed some effective measures to reduce them. Our results have showed that: (1) carbon footprint from the four crops in the study area varies from 0.63 to 0.77 kg CO2 eq·kg−1, which is higher than that from traditional agriculture; (2) GHG emissions from Fertilizer-Nitrogen (N) manufacture and inorganic N application have contributed to the greatest percentage of carbon footprint. Compared with traditional agricultural zones, fertilizer-N application and paddy irrigation involved with crop productions have overall greater contributions to carbon footprint; (3) carbon emissions from saline agriculture can be reduced significantly by planting-breeding combination to reduce the amount of N fertilizer application, improving the traditional rotation system, and developing water-saving agriculture and ecological agriculture.

Description: Water, Vol. 10, Pages 949: Characterization of Karst Conduit Network Using Long-Distance Tracer Test in Lijiang, Southwestern China Water doi: 10.3390/w10070949 Authors: Jihong Qi Mo Xu Xinyu Cen Lu Wang Qiang Zhang The Ancient City in Lijiang of southwestern China was endowed as World Cultural Heritage by UNESCO, and the karst springs located in Black Dragon Pool are its main water source. However, the springs have dried up several times in recent years, which caused serious damages to the landscape as well as the city water supply. Triggered by the dried-up event in Black Dragon Pool, a long-distance artificial tracer test up to 17 km was employed to investigate the karst conduit network distributing in the study area. Based on the tracer concentration breakthrough curves (BTCs), the hydraulic connection from the same injection point (located in a giant depression named the Jiuzi Sea) to the springs on both sides of the topography watershed was proven, and the conduit structure was discussed. According to the characteristics of BTCs and considering the low tracer concentration and tracer recovery, a conceptual structure of leaky reservoir with threshold effect above a certain groundwater level was established to interpret why the springs in Black Dragon Pool dried up several times in history, but those in the Ancient City never did. Furthermore, a method of injecting surface water into the Jiuzi Sea to raise the groundwater level up to the height of Black Dragon Pool was proposed to restore the springs. Our study provides insights into the long-distance artificial tracer test, and opens a new avenue for groundwater resource recovery of this Ancient City.