Predicting bacterial transport through saturated porous media using an automated machine learning model

Escherichia coli, as an indicator of fecal contamination, can move from manure-amended soil to groundwater under rainfall or irrigation events. Predicting its vertical transport in the subsurface is essential for the development of engineering solutions to reduce the risk of microbiological contamination. In this study, we collected 377 datasets from 61 published papers addressing E. coli transport through saturated porous media and trained six types of machine learning algorithms to predict bacterial transport. Eight variables, including bacterial concentration, porous medium type, median grain size, ionic strength, pore water velocity, column length, saturated hydraulic conductivity, and organic matter content were used as input variables while the first-order attachment coefficient and spatial removal rate were set as target variables. The eight input variables have low correlations with the target variables, namely, they cannot predict target variables independently. However, using the predictive models, input variables can effectively predict the target variables. For scenarios with higher bacterial retention, such as smaller median grain size, the predictive models showed better performance. Among six types of machine learning algorithms, Gradient Boosting Machine and Extreme Gradient Boosting outperformed other algorithms. In most predictive models, pore water velocity, ionic strength, median grain size, and column length showed higher importance than other input variables. This study provided a valuable tool to evaluate the transport risk of E.coli in the subsurface under saturated water flow conditions. It also proved the feasibility of data-driven methods that could be used for predicting other contaminants’ transport in the environment

Transient Focal Cerebral Ischemia/Reperfusion Induces Early and Chronic Axonal Changes in Rats: Its Importance for the Risk of Alzheimer's Disease

The dementia of Alzheimer's type and brain ischemia are known to increase at comparable rates with age. Recent advances suggest that cerebral ischemia may contribute to the pathogenesis of Alzheimer's disease (AD), however, the neuropathological relationship between these two disorders is largely unclear. It has been demonstrated that axonopathy, mainly manifesting as impairment of axonal transport and swelling of the axon and varicosity, is a prominent feature in AD and may play an important role in the neuropathological mechanisms in AD. In this study, we investigated the early and chronic changes of the axons of neurons in the different brain areas (cortex, hippocampus and striatum) using in vivo tracing technique and grading analysis method in a rat model of transient focal cerebral ischemia/reperfusion (middle cerebral artery occlusion, MCAO). In addition, the relationship between the changes of axons and the expression of β-amyloid 42 (Aβ42) and hyperphosphorylated Tau, which have been considered as the key neuropathological processes of AD, was analyzed by combining tracing technique with immunohistochemistry or western blotting. Subsequently, we found that transient cerebral ischemia/reperfusion produced obvious swelling of the axons and varicosities, from 6 hours after transient cerebral ischemia/reperfusion even up to 4 weeks. We could not observe Aβ plaques or overexpression of Aβ42 in the ischemic brain areas, however, the site-specific hyperphosphorylated Tau could be detected in the ischemic cortex. These results suggest that transient cerebral ischemia/reperfusion induce early and chronic axonal changes, which may be an important mechanism affecting the clinical outcome and possibly contributing to the development of AD after stroke

In-Depth Method Investigation for Determination of Boron in Silicate Samples Using an Improved Boron–Mannitol Complex Digestion Method by Inductively Coupled Plasma Mass Spectrometry

In this paper, a boron–mannitol complex wet acid digestion method proposed for the accurate determination of boron in silicate samples by inductively coupled plasma mass spectrometry (ICP-MS) was investigated in detail for the first time. With the addition of 50 μL of mannitol (2% wt.) into the mixture of 0.6 mL of concentrated HF and 30 μL of concentrated HNO3, the 50 mg of silicate sample was effectively decomposed after being heated overnight with optional pre-ultrasonic treatment. Following fluoride formation prevention by 8% HNO3 (wt.) and fluoride decomposition using 6% HCl (wt.), the samples were fluxed in 2.0 mL of 40% HNO3 (wt.) for 4 h and aged overnight. By diluting 1000-fold using 2% HNO3 (wt.) solution, the samples were directly quantified by an ICP-MS, showing boron recoveries of the standard materials including diabase W-2, basalt JB-2a, and rhyolite JR-2 in the range of 95.5–105.5% (n = 5). For this wet acid method, it was found that the contents of boron had no obvious difference under digestion temperatures of 65, 100, and 140 °C. It was also found that the ICP-MS quantification accuracy deteriorated at the mass of 11B when boron content was about 7250 ng yielding positive bias with average recoveries of 115.5–119.8% (n = 5), while the determination results remained unaffected at the mass of 10B. Furthermore, the digestion efficiency of boron by laboratory high-pressure closed digestion method was assessed. The boron recoveries with samples treated by the high-pressure closed digestion method were found to vary within 49.5–98.0% (n = 5) and even lowered down to 31.1% when skipping pressure relief procedure. The long-term quantification stability study showed that the boron content generally declined in one month for the high-pressure closed digestion method and exhibited no significant changes for the proposed method. By applying such an improved boron–mannitol complex digestion method, the boron concentration in the studied silicate standard materials were accurately determined, providing critical data for further boron isotope analyses and associated geochemical studies. This in-depth method investigation for silicate boron determination demonstrates the feasibility of this boron–mannitol complex strategy under a wide digestion temperature of 65–140 °C, and also sheds light on the extensive applications of boron as a geological tracer

Effect of Gas Flow Rates in Laser Ablation System on Accuracy and Precision of Zircon U-Pb Dating Analysis by LA-ICP-MS

BACKGROUND： Despite zircon U-Pb dating analysis by LA-ICP-MS receiving wide acceptance, it remains a challenge to obtain results with high accuracy and precision. It is known that gas flow rates of LA system can affect the signal stability of ICP-MS and thus result in impacts on analytical uncertainty of zircon U-Pb dating. However, the exact effects and mechanism of gas flow rates on zircon U-Pb dating analysis are still unclear. OBJECTIVES： To thoroughly understand the influence of gas flow rates on the analytical uncertainty of zircon U-Pb dating, and to provide valuable information to propose a reliable and robust LA-ICP-MS approach for zircon U-Pb dating analysis. METHODS: By applying zircon standard samples of Harvard 91500 and Plešovice as researching subjects, ICP-MS connected to a 193nm nanosecond laser ablation system was used to investigate the influence of gas flow rate settings on accuracy and precision of U-Pb dating analysis. RESULTS: With fixed make-up gas (Ar) of 1.0L/min, the average 206Pb/238U ages of Harvard 91500 were found to increase from 1002.0±10.4Ma (1σ) to 1083.0±6.8Ma (1σ) with increasing carrier gas (He) from 0.2 to 1.2L/min. Thus, it was clear that the sample aerosol transportation efficiency can greatly affect the analytical accuracy of zircon U-Pb dating. Furthermore, when the He flow rate was higher than 0.8L/min, the analytical accuracy and precision of zircon U-Pb dating decreased due to the increased signal intensity oscillations and formation of oxides from the introduction of large particles of sample aerosols. The comparison of the data of Plešovice obtained under 0.95/0.8, 0.80/0.8 and 0.8/0.6L/min for He/Ar gas flow rate patterns indicated that there were no significant differences in U/Pb weighted average age. However, the relative deviation of 1σ single-point analysis was the smallest (1.4%) when the Ar and He flow rates were both 0.8L/min. CONCLUSIONS: The analytical accuracy and precision of zircon U-Pb dating by LA-ICP-MS can be improved by optimizing the gas flow rate setting of carrier gas and make-up gas, and highly recommending 0.8L/min of both Ar and He

Incentive Mechanism for Edge-Computing-Based Blockchain

Blockchain has been gradually applied to different Internet of Things (IoT) platforms. As the efficiency of the blockchain mainly depends on the network computing capability, how to make sure the acquisition of the computational resources and participation of the devices would be the driving force. In this work, we focus on investigating incentive mechanism for rational miners to purchase the computational resources. A edge computing-based blockchain network is considered, where the edge service provider (ESP) can provide computational resources for the miners. Accordingly, we formulate a two-stage Stackelberg game between the miners and ESP. The aim is to investigate Stackelberg equilibrium of the optimal mining strategy under the two different mining schemes, in order to find the optimal incentive for the ESP and miners to choose auto-fit strategies. Through theoretical analysis and numerical simulation, we can demonstrate the effectiveness of the proposed scheme on encouraging devices to participate the blockchain.peerReviewe

Purification and Characterization of a Novel ~18 kDa Antioxidant Protein from Ginkgo biloba Seeds

Ginkgo biloba seeds are widely used as a food and traditional medicine in China. In the present study, a novel antioxidant protein named GBSP was purified from Ginkgo biloba seeds. The protein (GBSP) was purified by homogenization of Ginkgo biloba seed powder in saline solution, 70% ammonium sulphate precipitation, filtration on a DEAE-Cellulose52 anion exchange column, gel filtration on a Sephadex G-50 column, and preparative chromatography on a C18 column using RP-HPLC. GBSP showed an apparent molecular weight of 18 kDa by SDS-PAGE and MALDI-TOF/MS analyses. The amino acid sequence obtained by MALDI-TOF/TOF MS analysis showed GBSP was a novel protein, as no matching protein in was found the database. The protein exhibited significant antioxidant activities against free radicals such as DPPH, ABTS and superoxide anion and showed higher activity than α-tocopherol in a linoleic acid emulsion assay system. Furthermore, GBSP exhibited notable reducing power and a strong chelating effect on Cu2+and Fe2+. Therefore, the present study demonstrates, for the first time, that this novel protein from Ginkgo biloba seeds is an excellent antioxidant

Purification and Characterization of a Novel ~18 kDa Antioxidant Protein from Ginkgo biloba Seeds

Ginkgo biloba seeds are widely used as a food and traditional medicine in China. In the present study, a novel antioxidant protein named GBSP was purified from Ginkgo biloba seeds. The protein (GBSP) was purified by homogenization of Ginkgo biloba seed powder in saline solution, 70% ammonium sulphate precipitation, filtration on a DEAE-Cellulose52 anion exchange column, gel filtration on a Sephadex G-50 column, and preparative chromatography on a C18 column using RP-HPLC. GBSP showed an apparent molecular weight of 18 kDa by SDS-PAGE and MALDI-TOF/MS analyses. The amino acid sequence obtained by MALDI-TOF/TOF MS analysis showed GBSP was a novel protein, as no matching protein in was found the database. The protein exhibited significant antioxidant activities against free radicals such as DPPH, ABTS and superoxide anion and showed higher activity than α-tocopherol in a linoleic acid emulsion assay system. Furthermore, GBSP exhibited notable reducing power and a strong chelating effect on Cu2+and Fe2+. Therefore, the present study demonstrates, for the first time, that this novel protein from Ginkgo biloba seeds is an excellent antioxidant