An Integrated Bayesian and Machine Learning Approach Application to Identification of Groundwater Contamination Source Parameters

The identification of groundwater contamination source parameters is an important prerequisite for the control and risk assessment of groundwater contamination. This study developed an innovative approach for the optimal design of observation well locations and the high-precision identification of groundwater contamination source parameters. The approach involves Bayesian theory and integrates Markov Chain Monte Carlo, Bayesian design, information entropy, machine learning, and surrogate modeling. The optimal observation well locations are determined by information entropy, which is adopted to mine valuable information about unknown groundwater contamination source parameters from measurements of contaminant concentration according to Bayesian design. After determining the optimal observation well locations, the identification of groundwater contamination source parameters is implemented through a Bayesian-based Differential Evolution Adaptive Metropolis with Discrete Sampling–Markov Chain Monte Carlo approach. However, the processes of both determination and identification are time-consuming because the original simulation model (that is, the contaminant transport model) needs to be invoked multiple times. To overcome this challenge, a machine learning approach, that is, Multi-layer Perceptron, is used to build a surrogate model for the original simulation model, which can greatly accelerate the determination and identification processes. Finally, two hypothetical numerical case studies involving homogeneous and heterogeneous cases are used to verify the performance of the proposed approach. The results show that the optimal design of observation well locations and high-precision identification of groundwater contamination source parameters can be implemented accurately and effectively by using the proposed approach. In summary, this study highlights that the integrated Bayesian and machine learning approach provides a promising solution for high-precision identification of groundwater contamination source parameters

Role of Heat Treatment on Atomic Order and Ordering Domains in Ni45Co5Mn36.6In13.4 Ribbons

The effects of cooling rate and annealed temperature on the state of atomic order and microstructure of L21 domains of Ni45Co5Mn36.6In13.4 ribbons are investigated comprehensively. The state of atomic order is quantitatively studied by in situ X-ray diffraction (XRD), and the microstructure of ordered domains is revealed by transmission electron microscopy (TEM). As-spun ribbons show B2 structure of low atomic order, exhibiting the dispersive L21 domains’ morphology. By applying heat treatment around the order–disorder transition temperature followed by furnace cooling or quenching into water, respectively, we found the strong dependence of ordered domains on cooling rates. Furnace cooling samples show L21 domains with small sized antiphase boundary, revealing a high degree of atomic order, while quenching hinders the formation of ordered domains. Annealing above the order–disorder transition temperature followed by quenching preserves the disordered atomic state with the mixture of L21 structure in B2 matrix

Introducing N2-Fixing Tree Species into Eucalyptus Plantation in Subtropical China Alleviated Carbon and Nitrogen Constraints within Soil Aggregates

Soil extracellular enzymatic activity (EEA) and extracellular enzymatic stoichiometry (EES) within aggregates indicate variations in soil-nutrient effectiveness and the nutrient requirements of microorganisms. However, the responses of soil EEA and EES after introducing N2-fixing tree species into Eucalyptus plantations are poorly understood. Therefore, we examined soils from a 15-year-old pure Eucalyptus urophylla plantation (PP) and mixed E. urophylla and Acacia mangium plantation (MP) based on the theory of EEA and EES at the aggregate scale. Aggregates were separated into four fractions using a dry-sieving procedure: >2, 1–2, 0.25–1, and <0.25 mm. We measured the EEA of soil carbon (C)-, nitrogen (N)-, and phosphorus (P)-acquiring enzymes, and examined potential factors (soil physicochemical properties, microbial biomass, and litterfall [LF]) that may influence EEA and EES. Significantly higher (p < 0.05) EEA levels in all aggregates were found in MP than in PP. The average natural logarithmic ratio of C-, N-, and P-acquiring enzyme activities in our study was 1.44:1.21:1, which deviated from the global mean ratio of 1:1:1 and implied that soil microbes were limited by C and N. Moreover, the enzyme C:N ratio (EC:N), C:P ratio (EC:P), and vector length (VL) were markedly lower (p < 0.05) in bulk soil and most aggregates in MP compared to PP, suggesting that C limitation was more serious in PP than in MP. Furthermore, while the vector angle (VA) of bulk soil and four aggregate sizes were all <45° in both the PP and the MP, they were markedly higher (p < 0.05) in bulk soil and >2 mm aggregate in MP than in PP. This indicated that mixing N2-fixing species with Eucalyptus alleviated but did not eliminate N limitation. Our study also found that nitrate nitrogen (NO3−-N), total nitrogen (TN), and microbial biomass C:P ratio (MBC:MBP) were the main factors driving changes in EEA, while LF was a key factor controlling EES (p < 0.05). Overall, introducing N2-fixing species into the Eucalyptus plantation alleviated but did not eliminate C and N limitation. The results provide specific recommendations for soil-nutrient management in Eucalyptus plantations in subtropical China

Introducing N₂-Fixing Tree Species into <i>Eucalyptus</i> Plantation in Subtropical China Alleviated Carbon and Nitrogen Constraints within Soil Aggregates

Soil extracellular enzymatic activity (EEA) and extracellular enzymatic stoichiometry (EES) within aggregates indicate variations in soil-nutrient effectiveness and the nutrient requirements of microorganisms. However, the responses of soil EEA and EES after introducing N2-fixing tree species into Eucalyptus plantations are poorly understood. Therefore, we examined soils from a 15-year-old pure Eucalyptus urophylla plantation (PP) and mixed E. urophylla and Acacia mangium plantation (MP) based on the theory of EEA and EES at the aggregate scale. Aggregates were separated into four fractions using a dry-sieving procedure: >2, 1–2, 0.25–1, and p C:N), C:P ratio (EC:P), and vector length (VL) were markedly lower (p p 2 mm aggregate in MP than in PP. This indicated that mixing N2-fixing species with Eucalyptus alleviated but did not eliminate N limitation. Our study also found that nitrate nitrogen (NO3−-N), total nitrogen (TN), and microbial biomass C:P ratio (MBC:MBP) were the main factors driving changes in EEA, while LF was a key factor controlling EES (p 2-fixing species into the Eucalyptus plantation alleviated but did not eliminate C and N limitation. The results provide specific recommendations for soil-nutrient management in Eucalyptus plantations in subtropical China

Knockdown of Gastrin Promotes Apoptosis of Gastric Cancer Cells by Decreasing ROS Generation

Overexpressed gastrin is reported to promote oncogenesis and development of gastric cancer by inhibiting apoptosis of cancer cells; however, the underlying mechanism remains unclear. Our study is aimed at revealing the mechanism underlying the effect of gastrin on apoptosis of gastric cancer cells. Gastrin-interfering cell line was constructed by stably transfecting gastrin-specific pshRNA plasmid to gastric cancer cell line BGC-823. Then, differentially expressed proteins between untreated BGC-823 and gastrin-interfering BGC-823 cell lines were detected by the iTRAQ technique. GO and KEGG analysis was used to analyze the differentially expressed genes that code these differentially expressed proteins. The Annexin V-FITC staining assay was used to detect gastric cancer cell apoptosis. The DCFH-DA fluorescent probe staining assay was used to measure intracellular ROS. Mitochondrial membrane potential was detected by flow cytometry. Western blot was used to analyze the mitochondria respiratory chain proteins and apoptosis-related proteins. A total of 107 differentially expressed proteins were identified by iTRAQ. GO and KEGG analysis showed that proteins coded by the corresponding differentially expressed genes were mainly enriched in the mitochondrial oxidative respiratory chain, and the expression of three proteins (COX17, COX5B, ATP5J) was upregulated. The three proteins with higher scores were verified by Western blot. The apoptosis rate of the gastrin knockdown cancer cell was significantly increased; meanwhile, gastrin knockdown leads to increase of membrane potential and decrease of intracellular ROS production. Additionally, Bax was significantly increased, whereas NF-κB-p65 and Bcl-2 were downregulated after knockdown of gastrin. Concomitantly, pretreatment with NAC reversed the effect of gastrin on the Bax and Bcl-2 expression. Gastrin promotes the production of ROS from mitochondria, activates NF-κB, and inhibits apoptosis via modulating the expression level of Bcl-2 and Bax

Vegetation Restoration with Mixed N2-Fixer Tree Species Alleviates Microbial C and N Limitation in Surface Soil Aggregates in South Subtropical Karst Area, China

Soil extracellular enzyme stoichiometry (EES) is the essential predictor in nutrient status and resource limitation of soil microorganisms, whose metabolism has a vital role in biogeochemical cycling and ecosystem function. However, little is known about how N2-fixer tree species with different planting patterns affect soil nutrient resources in terms of extracellular enzyme activity (EEA) or EES within aggregates in degraded karst ecosystems. In this study, we evaluated soil EEA and EES related to carbon (C), nitrogen (N), and phosphorus (P) cycles across two eight-year-old pure plantations of legume species [Dalbergia odorifera T. Chen (PD) and Acrocarpus fraxinifolius Wight ex Arn. (PA)] and a mixed plantation of the two tree species listed above (MP). Meanwhile, a nearby undisturbed shrubland was used as a control (CK). We concluded that the activities of C-, N-, and P-acquiring enzyme increased to different degrees in the N2-fixer tree species stands (particularly in MP) compared to CK in all aggregates. Compared to CK, MP significantly increased by 39.0%, 54.0%, 39.3%, and 24.8% in total C-acquiring EEA, 41.1%, 60.5%, 47.8%, and 12.5% in total N-acquiring EEA, and 100.4%, 79.7%, 69.2%, and 56.4% in total P-acquiring EEA within &gt;2 mm, 1&ndash;2 mm, 0.25&ndash;1 mm, and &lt;0.25 mm aggregates, respectively. Furthermore, the logarithmic transformed ratio of C-, N-, and P-acquiring enzyme activities was 1.20:1.08:1, which deviated from the global ratio (1:1:1). Vector analysis of EEA showed that the vector length (VL) within aggregates was significantly lower than that of CK in all stands of N2-fixer species except PD; while in all treatments, vector angle (VA) was &lt;45&deg; for all aggregate sizes, except in MP, where VA reached 45&deg; for &lt;0.25 mm aggregate. These indicated soil microbes were limited by C and N together. However, MP significantly alleviated microbial C and N limitation than CK (p &lt; 0.05). There were obvious positive relationships between enzyme C:N, C:P, and N:P ratios. VL was markedly negatively linked to VA. EES was markedly related to most soil nutrients and microbial biomass stoichiometry ratios. Changes in soil EEA and EES were primarily driven by available phosphorus (AP), microbial biomass carbon (MBC), soil C:N and MBN:MBP ratios. Together, our results demonstrate the influences after introducing N2-fixer tree species (particularly MP) for vegetation recovery on soil microbial nutrient limitation and ecological processes in aggregate level and will contribute to the development of ecological restoration practices and fertility management in degraded karst ecosystems of southwest China