Estimation of Pb Content Using Reflectance Spectroscopy in Farmland Soil near Metal Mines, Central China

The contamination of farmlands with hazardous metals from mining puts the safety of agricultural commodities at risk. For remediation, it is crucial to map the spatial distribution of contaminated soil. Typical sampling-based procedures are time-consuming and labor-intensive. The use of visible, near-infrared, and short-wave infrared reflectance (VNIR-SWIR) spectroscopy to detect soil heavy metal pollution is an alternative. With the aim of investigating a methodology of detecting the most sensitive bands using VNIR-SWIR spectra to find lead (Pb) anomalies in agriculture soil near mining activities, the area in Xiaoqinling Mountain, downstream from a series of active gold mines, was selected to test the feasibility of utilizing VNIR-SWIR spectroscopy to map soil Pb. A total of 115 soil samples were collected for laboratory Pb analysis and spectral measurement. Partial least squares regression (PLSR) was adopted to estimate the soil Pb content by building the prediction model, and the model was optimized by finding the optimal number of bands involved. The spatial distribution of Pb concentration was mapped using the ordinary kriging (OK) interpolation method. This study found that five spectral bands (522 nm, 1668 nm, 2207 nm, 2296 nm, and 2345 nm) were sensitive to soil Pb content. The optimized prediction model’s coefficient of determination (R2), residual prediction deviation (RPD), and root mean square error (RMSE) were 0.711, 1.860, and 0.711 ln(mg/kg), respectively. Additionally, the result of OK interpolation was convincing and accurate (R2 = 0.775, RMSE = 0.328 ln(mg/kg)), comparing maps from estimated and ground truth data. This study proves that it is feasible to use VNIR-SWIR spectral data for in situ estimation of the soil Pb content

Single Current Feedback Control Strategy of an LCL Grid-Connected Inverter Based on GI-ESO and Delay Compensation

This paper presents a new control structure to improve the performance of LCL grid-connected inverters. First, the conventional linear extended state observer (LESO) has difficulty rejecting periodic disturbances, so the proposed method adds an internal model of disturbances into LESO to enhance the harmonic suppression ability. Second, the phase lag caused by the digital delay and LCL resonance make it difficult to ensure the stability of the system. In this paper, the proposed method adds phase compensation for the ESO loop, thus enlarging the stability region of the system with no additional sensors being required. Third, the design of the controller parameters is simplified and the frequency performance analysis of the system is given. Finally, the simulation and experimental results show that the proposed method has good harmonic suppression capability and robust stability

Spatial Assessment of Jerusalem Artichoke’s Potential as an Energy Crop in the Marginal Land of the Shaanxi Province, China

As a foodstuff crop, Jerusalem artichoke has a promising prospect for providing sustainable feed-stock sources for bioenergy development. Due to relatively limited cultivated land resources in China, it is crucial to evaluate Jerusalem artichoke’s potential production capacity in marginal land. Based on Jerusalem artichoke’s growth and photosynthetic characteristics, the agricultural production systems simulator model (APSIM) and multi-factor integrated assessment method were integrated to provide an operational method for comprehensively evaluating the marginal land resources suitable for developing the plantation of Jerusalem artichoke in the Shaanxi province, China. The results showed that 0.73 million ha of marginal land was suitable for Jerusalem artichoke cultivation in the Shaanxi province, and 5.4 million ha of marginal land was fairly suitable for Jerusalem artichoke cultivation, with the yield reaching 44,289 kg/ha and 38,861 kg/ha, respectively. The suitable land resources are mainly located in Yan’an (0.18 million ha), Hanzhong (0.13 million ha), and Baoji (0.08 million ha), most of which are moderate dense grassland (accounting for 50.6% of suitable land), dense grassland (accounting for 16.2% of suitable land), shrubland (accounting for 14.7% of suitable land), and sparse forest land (accounting for 9.18% of suitable land). The findings of this study can be used to establish targeted policies for Jerusalem artichoke development in China and other countries, particularly those along the Silk Road

Spatial Assessment of Jerusalem Artichoke’s Potential as an Energy Crop in the Marginal Land of the Shaanxi Province, China

As a foodstuff crop, Jerusalem artichoke has a promising prospect for providing sustainable feed-stock sources for bioenergy development. Due to relatively limited cultivated land resources in China, it is crucial to evaluate Jerusalem artichoke’s potential production capacity in marginal land. Based on Jerusalem artichoke’s growth and photosynthetic characteristics, the agricultural production systems simulator model (APSIM) and multi-factor integrated assessment method were integrated to provide an operational method for comprehensively evaluating the marginal land resources suitable for developing the plantation of Jerusalem artichoke in the Shaanxi province, China. The results showed that 0.73 million ha of marginal land was suitable for Jerusalem artichoke cultivation in the Shaanxi province, and 5.4 million ha of marginal land was fairly suitable for Jerusalem artichoke cultivation, with the yield reaching 44,289 kg/ha and 38,861 kg/ha, respectively. The suitable land resources are mainly located in Yan’an (0.18 million ha), Hanzhong (0.13 million ha), and Baoji (0.08 million ha), most of which are moderate dense grassland (accounting for 50.6% of suitable land), dense grassland (accounting for 16.2% of suitable land), shrubland (accounting for 14.7% of suitable land), and sparse forest land (accounting for 9.18% of suitable land). The findings of this study can be used to establish targeted policies for Jerusalem artichoke development in China and other countries, particularly those along the Silk Road

Estimation of Pb Content Using Reflectance Spectroscopy in Farmland Soil near Metal Mines, Central China

The contamination of farmlands with hazardous metals from mining puts the safety of agricultural commodities at risk. For remediation, it is crucial to map the spatial distribution of contaminated soil. Typical sampling-based procedures are time-consuming and labor-intensive. The use of visible, near-infrared, and short-wave infrared reflectance (VNIR-SWIR) spectroscopy to detect soil heavy metal pollution is an alternative. With the aim of investigating a methodology of detecting the most sensitive bands using VNIR-SWIR spectra to find lead (Pb) anomalies in agriculture soil near mining activities, the area in Xiaoqinling Mountain, downstream from a series of active gold mines, was selected to test the feasibility of utilizing VNIR-SWIR spectroscopy to map soil Pb. A total of 115 soil samples were collected for laboratory Pb analysis and spectral measurement. Partial least squares regression (PLSR) was adopted to estimate the soil Pb content by building the prediction model, and the model was optimized by finding the optimal number of bands involved. The spatial distribution of Pb concentration was mapped using the ordinary kriging (OK) interpolation method. This study found that five spectral bands (522 nm, 1668 nm, 2207 nm, 2296 nm, and 2345 nm) were sensitive to soil Pb content. The optimized prediction model’s coefficient of determination (R2), residual prediction deviation (RPD), and root mean square error (RMSE) were 0.711, 1.860, and 0.711 ln(mg/kg), respectively. Additionally, the result of OK interpolation was convincing and accurate (R2 = 0.775, RMSE = 0.328 ln(mg/kg)), comparing maps from estimated and ground truth data. This study proves that it is feasible to use VNIR-SWIR spectral data for in situ estimation of the soil Pb content

Gadd45a opens up the promoter regions of miR-295 facilitating pluripotency induction

MicroRNAs (miRNAs) play crucial roles in the establishment of pluripotent state by controlling pluripotent network. However, the molecular mechanisms controlling miRNAs during somatic cell reprogramming remain obscure. In this study, we show Gadd45a (growth arrest and DNA-damage-inducible protein 45a) enhances reprogramming by activating miR-295. Furthermore, we show that Gadd45a binds the promoter regions of miR-295. Nuclease accessibility assay indicates that Gadd45a opens the promoter regions of miR-295. Levels of H3K9Ac and H3K27Ac on the promoter regions of miR-295 were also increased. In conclusion, our results indicate that Gadd45a relaxes the promoter regions of miR-295 and promotes the expression of miR-295 during reprogramming, implying a concise mechanism of Gadd45a and miR-290 cluster cooperation in cell-fate determination

The Molecular Mechanisms Underlying the Hijack of Host Proteins by the 1918 Spanish Influenza Virus

The 1918 Spanish influenza A virus (IAV) caused one of the most serious pandemics in history. The nonstructural protein 1 (NS1) of the 1918 IAV hijacks the interaction between human CrkII and JNK1. Little is, however, known about its molecular mechanism. Here, we performed X-ray crystallography, NMR relaxation dispersion experiment, and fluorescence spectroscopy to determine the structural, kinetic, and thermodynamic mechanisms underlying the hijacking of CrkII by 1918 IAV NS1. We observed that the interaction between a proline-rich motif in NS1 and the N-terminal SH3 domain of CrkII displays strikingly rapid kinetics and exceptionally high affinity with 100-fold faster <i>k</i>_on and 3300-fold lower <i>K</i>_d compared to those for the CrkII–JNK1 interaction. These results provide molecular insight into the mechanism by which 1918 IAV NS1 hijacks CrkII and disrupts its interactions with critical cellular signaling proteins