ALBERT

Description: On-site analysis is an efficient approach to facilitate analysis at the location of the system under investigation as it can result in more accurate, more precise and quickly available analytical data. In our work, a novel self-made thermal desorption based interface was fabricated to couple solid-phase microextraction with ion mobility spectrometry for on-site water analysis. The portable interface can be connected with the front-end of an ion mobility spectrometer directly without other modifications. The analytical performance was evaluated via the extraction of chemical warfare agents and simulants in water samples. Several parameters including ionic strength and extraction time have been investigated in detail. The application of the developed method afforded satisfactory recoveries ranging from 72.9% to 114.4% when applied to the analysis of real water samples.

Description: The increasing number of Chinese sensor types used for terrestrial remote sensing has necessitated an additional effort to evaluate and standardize the data they acquire. In this study, we assessed the potential use of GF-1 WFV (Wild Field Camera), ZY-3 MUX (Multi-spectral camera), and HJ-1 CCD (Charge Coupled Device) sensor data for grassland monitoring by comparing spectral field measurements, vegetation coverage, and the leaf area index (LAI) of grassland stands with reflectance in the red and near-infrared bands and the Normalized Difference Vegetation Index (NDVI). Based on spectral field measurements, the characteristic differences of spectral response functions of the sensors were analyzed. Based on simulations using the SAIL bidirectional canopy reflectance model coupled with the PROSPECT leaf optical properties model (PROSAIL), we investigated the effects of changes in the sensors’ zenith angle caused by side sway. The following conclusions were drawn. (1) Differences in the adjusted coefficients of determination (R2) exist when comparing correlations between the reflectances from the three sensor types in different bands. The values of R2 are 0.556–0.893 and 0.819–0.850 for the infrared and red bands, respectively, and these data show a better correlation for the red band than for the infrared band. Fitted slope equations revealed inconsistencies in the data between the different sensor types. In the red band, GF-1 WFV and HJ-1 CCD data are the most consistent, but in the near-infrared band, GF-1 WFV and ZY-3 MUX data are the most consistent; (2) The correlation of NDVIs obtained from the different sensor types is high (R2 between 0.758 and 0.852); however, the consistency is low in that the NDVI based on GF-1 WFV data is significantly higher than that based on ZY-3 MUX and HJ-1 CCD data. In contrast, the mean difference is small between the NDVIs based on ZY-3 MUX and HJ-1 CCD; (3) Correlation analysis between ground grass-coverage and measured LAI data shows that the three sensor types are better at estimating coverage than the LAI, and that the GF-1 WFV sensor gave the best performance; (4) Changes in the sensors’ zenith angle caused by side sway were proven to have greater impact on reflectance and NDVI than the spectral response function; (5) For LAI values of 0–3, the NDVI changes significantly with increasing LAI, and differences between the three sensor types are obvious. For LAI > 3.5, the NDVI appears to experience a saturated tendency, which greatly reduces the differences between the sensors.

Description: Prostate cancer (PCa) is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI), smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR) and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs) = 1.79–4.41). GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032) and 5.33 (p = 0.046), respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007) and 3.11 (p = 0.024), respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041). These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa.

Description: Train wheel sets must be periodically inspected for possible or actual premature failures and it is very significant to record the wear history for the full life of utilization of wheel sets. This means that an online measuring system could be of great benefit to overall process control. An online non-contact method for measuring a wheel set’s geometric parameters based on the opto-electronic measuring technique is presented in this paper. A charge coupled device (CCD) camera with a selected optical lens and a frame grabber was used to capture the image of the light profile of the wheel set illuminated by a linear laser. The analogue signals of the image were transformed into corresponding digital grey level values. The ‘mapping function method’ is used to transform an image pixel coordinate to a space coordinate. The images of wheel sets were captured when the train passed through the measuring system. The rim inside thickness and flange thickness were measured and analyzed. The spatial resolution of the whole image capturing system is about 0.33 mm. Theoretic and experimental results show that the online measurement system based on computer vision can meet wheel set measurement requirements.

Description: Energies, Vol. 11, Pages 1619: Study on the Propagation Characteristics of Partial Discharge in Switchgear Based on Near-Field to Far-Field Transformation Energies doi: 10.3390/en11071619 Authors: Yang Qi Yang Fan Bing Gao Yang Mengzhuo Ammad Jadoon Yu Peng Tian Jie Ultra-high frequency (UHF) electromagnetic (EM) signals generated by the partial discharge (PD) process of high-voltage equipment are now widely used in PD detection. The computation of EM propagation generated by a local discharge source using a uniformly hardwiring source can hardly reveal the discharge characteristics. In this paper, a method of near-field to far-field transformation is proposed to realize the study of the propagation characteristics of the PD signal. A short gap discharge model is established to get the near-field electromagnetics and the proposed method is validated by comparing the directly calculated results with the results of the near-field source. In the end, a model of switchgear is employed to study the propagation characteristics of the EM signal based on the proposed method. Via numerical calculation, the influence of the equipment in the switchgear on the propagation of the discharge EM is studied. It is found that the direction of the discharge source has a significant effect on the distribution of the electric field, which indicates that the discharge source cannot be simplified to a uniformly hardwiring source. In addition, it is also obtained that the amplitude of the electric field shows the same trend with the growth of the discharge channel, which gives a method for evaluating the development of the PD. Particularly, the near-field to far-field transformation can provide an effective method for studying the propagation of discharge EM waves in large-scale equipment.

Description: Water, Vol. 10, Pages 742: Application of SWAT Model with CMADS Data to Estimate Hydrological Elements and Parameter Uncertainty Based on SUFI-2 Algorithm in the Lijiang River Basin, China Water doi: 10.3390/w10060742 Authors: Yang Cao Jing Zhang Mingxiang Yang Xiaohui Lei Binbin Guo Liu Yang Zhiqiang Zeng Jiashen Qu The China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool model (CMADS) have been widely applied in recent years because of their accuracy. An evaluation of the accuracy and efficiency of the Soil and Water Assessment Tool (SWAT) model and CMADS for simulating hydrological processes in the fan-shaped Lijiang River Basin, China, was carried out. The Sequential Uncertainty Fitting (SUFI-2) algorithm was used for parameter sensitivity and uncertainty analysis at the daily scale. The pair-wise correlation between parameters and the uncertainties associated with equifinality in model parameter estimation were investigated. The results showed that the SWAT model performed well in predicting daily streamflow for the calibration period (2009–2010). The correlation coefficient (R2) was 0.92, and the Nash-Sutcliffe model efficiency coefficient (NSE) was 0.89. For the validation period (2011–2018), R2 = 0.89, NSE = 0.88, and reasonable values for the P-factor, R-factor, and percent bias (PBIAS) were obtained. In addition, the spatial and temporal variation of evapotranspiration (ET), surface runoff, and groundwater discharge were analyzed. The results clearly showed that spatial variation in surface runoff and groundwater discharge are strongly related to precipitation, while ET is largely controlled by land use types. The contributions to the water budget by surface runoff, groundwater discharge, and lateral flow were very different in flood years and dry years.

Description: IJERPH, Vol. 15, Pages 1278: Spatiotemporal Assessment of PM2.5-Related Economic Losses from Health Impacts during 2014–2016 in China International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15061278 Authors: Yang Yang Liwen Luo Chao Song Hao Yin Jintao Yang Background: Particulate air pollution, especially PM2.5, is highly correlated with various adverse health impacts and, ultimately, economic losses for society, however, few studies have undertaken a spatiotemporal assessment of PM2.5-related economic losses from health impacts covering all of the main cities in China. Methods: PM2.5 concentration data were retrieved for 190 Chinese cities for the period 2014–2016. We used a log-linear exposure–response model and monetary valuation methods, such as value of a statistical life (VSL), amended human capital (AHC), and cost of illness to evaluate PM2.5-related economic losses from health impacts at the city level. In addition, Monte Carlo simulation was used to analyze uncertainty. Results: The average economic loss was 0.3% (AHC) to 1% (VSL) of the total gross domestic product (GDP) of 190 Chinese cities from 2014 to 2016. Overall, China experienced a downward trend in total economic losses over the three-year period, but the Beijing–Tianjin–Hebei, Shandong Peninsula, Yangtze River Delta, and Chengdu-Chongqing regions experienced greater annual economic losses. Conclusions: Exploration of spatiotemporal variations in PM2.5-related economic losses from long-term health impacts could provide new information for policymakers regarding priority areas for PM2.5 pollution prevention and control in China.

Description: Energies, Vol. 10, Pages 1401: Experimental Investigation of Flow Domain Division in Beds Packed with Different Sized Particles Energies doi: 10.3390/en10091401 Authors: Xin Yang Tianhong Yang Zenghe Xu Bin Yang Seepage in a medium packed with particles of variable granular size can be seen in many fields of engineering applications. Due to the relative complex spatial aspect of pore geometry, there are notable differences in the critical parameters of flow transition (Reynolds number and Forchheimer number) between different structures. It is difficult to distinguish the available range of seepage equations and predict the water flux accurately. This work aims to establish the relationship between particle size and flow transition. This is conducted according to the results of flow region division, which obtains the application range for seepage equations. Experiments were carried out in sand columns with nine different particle sizes of sand with mean diameters of 0.0375, 0.1125, 0.225, 0.45, 0.8, 1.5, 2.18, 3.555 and 7.125 mm. Four flow regimes were identified (pre-Darcy regime, Darcy regime, Forchheimer regime and turbulent regime). The experimental data indicate that the permeability increases exponentially and the inertia factor reduces exponentially with an increase in particle diameter. The inertial effect becomes more significant in the medium with larger particles than with finer particles when the flow transition occurs.

Description: Remote Sensing, Vol. 9, Pages 904: A Small UAV Based Multi-Temporal Image Registration for Dynamic Agricultural Terrace Monitoring Remote Sensing doi: 10.3390/rs9090904 Authors: Ziquan Wei Yifeng Han Mengya Li Kun Yang Yang Yang Yi Luo Sim-Heng Ong Terraces are the major land-use type of agriculture and support the main agricultural production in southeast and southwest China. However, due to smallholder farming, complex terrains, natural disasters and illegal land occupations, a light-weight and low cost dynamic monitoring of agricultural terraces has become a serious concern for smallholder production systems in the above area. In this work, we propose a small unmanned aerial vehicle (UAV) based multi-temporal image registration method that plays an important role in transforming multi-temporal images into one coordinate system and determines the effectiveness of the subsequent change detection for dynamic agricultural terrace monitoring. The proposed method consists of four steps: (i) guided image filtering based agricultural terrace image preprocessing, (ii) texture and geometric structure features extraction and combination, (iii) multi-feature guided point set registration, and (iv) feature points based image registration. We evaluated the performance of the proposed method by 20 pairs of aerial images captured from Longji and Yunhe terraces, China using a small UAV (the DJI Phantom 4 Pro), and also compared against four state-of-the-art methods where our method shows the best alignments in most cases.

Description: Remote sensing image registration plays an important role in military and civilian fields, such as natural disaster damage assessment, military damage assessment and ground targets identification, etc. However, due to the ground relief variations and imaging viewpoint changes, non-rigid geometric distortion occurs between remote sensing images with different viewpoint, which further increases the difficulty of remote sensing image registration. To address the problem, we propose a multi-viewpoint remote sensing image registration method which contains the following contributions. (i) A multiple features based finite mixture model is constructed for dealing with different types of image features. (ii) Three features are combined and substituted into the mixture model to form a feature complementation, i.e., the Euclidean distance and shape context are used to measure the similarity of geometric structure, and the SIFT (scale-invariant feature transform) distance which is endowed with the intensity information is used to measure the scale space extrema. (iii) To prevent the ill-posed problem, a geometric constraint term is introduced into the L2E-based energy function for better behaving the non-rigid transformation. We evaluated the performances of the proposed method by three series of remote sensing images obtained from the unmanned aerial vehicle (UAV) and Google Earth, and compared with five state-of-the-art methods where our method shows the best alignments in most cases.