Estimating Brain Age with Global and Local Dependencies

The brain age has been proven to be a phenotype of relevance to cognitive performance and brain disease. Achieving accurate brain age prediction is an essential prerequisite for optimizing the predicted brain-age difference as a biomarker. As a comprehensive biological characteristic, the brain age is hard to be exploited accurately with models using feature engineering and local processing such as local convolution and recurrent operations that process one local neighborhood at a time. Instead, Vision Transformers learn global attentive interaction of patch tokens, introducing less inductive bias and modeling long-range dependencies. In terms of this, we proposed a novel network for learning brain age interpreting with global and local dependencies, where the corresponding representations are captured by Successive Permuted Transformer (SPT) and convolution blocks. The SPT brings computation efficiency and locates the 3D spatial information indirectly via continuously encoding 2D slices from different views. Finally, we collect a large cohort of 22645 subjects with ages ranging from 14 to 97 and our network performed the best among a series of deep learning methods, yielding a mean absolute error (MAE) of 2.855 in validation set, and 2.911 in an independent test set

Co-gasification of digestate and lignite in a downdraft fixed bed gasifier: effect of temperature

To improve energy efficiency and biomass utilization in the process of anaerobic digestion, co-gasification is considered as an effective method to post-treat anaerobic digestion residues. In this work, the effect of temperature (650 °C, 750 °C, 850 °C and 950 °C) on the co-gasification of digestate and lignite was thoroughly investigated in a downdraft fixed bed gasifier. The results showed that the increase of gasification temperature increased the gas yield and the lower heating value (LHV) of product gas. Physicochemical properties of biochar were characterized by physical adsorption analyzer, Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy and thermogravimetric analyzer (TG). It was shown that the average pore diameter increased in the range of 650 °C to 950 °C, while specific surface area and pore volume first increased from 650 °C to 850 °C and then decreased at 950 °C. The Raman analysis of biochar indicated that small aromatic rings condensed to large aromatic ring and increased the content of Caromatic-Calkyl and the crosslinking density at higher temperature. The variation of biochar properties at the higher temperature caused a decrease in the gasification reactivity. With the increase of temperature, the content of carbolic oil in the tar increased, but the contents of light oil, naphthalene oil and washing oil decreased. This study comprehensively analyzed the products properties and demonstrated the feasibility of co-gasification of digestate and lignite

Interaction and Kinetics Study of the Co-Gasification of High-solid Anaerobic Digestate and Lignite

This study aims at investigating the interaction and kinetics behavior of the co-gasification of digestate and lignite. The co-pyrolysis performances of digestate and lignite blended by dry process were better than that blended by wet process, while the wet-blending process could improve the performance in co-gasification stage because of the larger pore diameter and pore volume. When anaerobic digestion (AD) time was 40 days, the synergistic interaction between digestate and lignite were the most remarkable based on the results of thermogravimetric analysis (TG) and the experiments in the lab-scale downdraft fixed bed gasifier. Kinetics study showed that the increase of AD time and the addition of digestate in lignite decreased the activation energy of the co-gasification reaction

Dynamic evaluation method of water-sealed gas for ultra-deep buried fractured tight gas reservoir in Kuqa Depression, Tarim Basin, China

The ultra-deep-buried fractured tight gas reservoir in the Kuqa Depression of the Tarim Basin has developed edge and bottom water. Faults and fractures have become “highways” for water invasion, resulting in the “water sealed gas” effect and reducing gas reservoir recovery. At present, there is a lack of effective evaluation methods. Therefore, based on an analysis of water invasion characteristics of the gas reservoir, a dynamic evaluation method for water-sealed gas in a fractured gas reservoir is established. This method considers two factors: fracture development scale and peripheral water body strength. It is then applied to three developed blocks in the Kuqa ultra-deep layer. The effectiveness of the evaluation results is verified by static and dynamic combination, and countermeasures to improve gas reservoir recovery are proposed. The results indicate that: (1) The non-uniform water invasion of fractures is jointly controlled by structural position, fracture development degree, and fracture network combination, which can be divided into three modes: edge water channeling along the large fracture in the core, edge and bottom water invading along the fracture in the wing, and rapid, violent water flooding of the bottom water along the fracture/small fault in the low part. (2) The replacement coefficient of water invasion in the three typical blocks is 0.2–0.3, indicating that they are sub active water-gas reservoirs. However, the severity of water-sealed gas varies greatly. The more severe the water-sealed gas is, the lower the recovery factor of the gas reservoir. (3) For directionally penetrating large fracture gas reservoirs, water shutoff should be carried out. For fracture network gas reservoirs with high fracture density, mild exploitation can control water, and early drainage can reduce the impact of water invasion, improving gas reservoir recovery. It is concluded that the new method of water-sealed gas dynamic evaluation can provide a reliable basis for evaluating fracture non-uniform water invasion dynamics of the ultra-deep gas reservoir and enhancing oil recovery of the gas reservoir in the Kuqa Depression. This method also supports the formulation of water control policies and the economic and efficient development of ultra-deep gas reservoirs in the Kuqa Depression

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle (UAV) remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching, ridge–furrow full mulching, and flat cropping full mulching in winter wheat. Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV. Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks (ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out. The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status. The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75, a root mean square error of 8.40, and a mean absolute value error of 6.53. Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remote-sensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification. The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching

High B (s) Fe-based nanocrystalline alloy with high impurity tolerance

High B (s) Fe82.5Si3B13P0.5C0.2Cu0.8 alloys with high impurity tolerance were successfully developed and prepared into ribbons with fully amorphous and uniform nanocrystalline microstructure. By comparing samples made with industrial grade and pure raw materials, it is found that the impurities in the commonly used industrial grade raw materials mainly affect the amorphous forming ability and amorphous structure of the as-spun ribbons. The effects of impurities on crystallization behaviors and magnetic properties can be inhibited in the amorphous ribbon production process for the alloys with a high impurity tolerance. The Fe82.5Si3B13P0.5C0.2Cu0.8 nanocrystalline alloy ribbons prepared with industrial grade raw materials exhibit excellent magnetic properties, containing high B (s) over 1.79 T, low H (c) of 9.5 A/m and maximum permeability (mu (m)) of 4 x 10(4), which are similar to the samples made with pure raw materials with unacceptable high cost. Combining the low cost of raw materials, good manufacturability and excellent magnetic properties, the present Fe82.5Si3B13P0.5C0.2Cu0.8 alloy will become a promising candidate for mass production and also provide a good reference for future development of high B (s) nanocrystalline alloys

High B (s) Fe-based nanocrystalline alloy with high impurity tolerance

High B (s) Fe82.5Si3B13P0.5C0.2Cu0.8 alloys with high impurity tolerance were successfully developed and prepared into ribbons with fully amorphous and uniform nanocrystalline microstructure. By comparing samples made with industrial grade and pure raw materials, it is found that the impurities in the commonly used industrial grade raw materials mainly affect the amorphous forming ability and amorphous structure of the as-spun ribbons. The effects of impurities on crystallization behaviors and magnetic properties can be inhibited in the amorphous ribbon production process for the alloys with a high impurity tolerance. The Fe82.5Si3B13P0.5C0.2Cu0.8 nanocrystalline alloy ribbons prepared with industrial grade raw materials exhibit excellent magnetic properties, containing high B (s) over 1.79 T, low H (c) of 9.5 A/m and maximum permeability (mu (m)) of 4 x 10(4), which are similar to the samples made with pure raw materials with unacceptable high cost. Combining the low cost of raw materials, good manufacturability and excellent magnetic properties, the present Fe82.5Si3B13P0.5C0.2Cu0.8 alloy will become a promising candidate for mass production and also provide a good reference for future development of high B (s) nanocrystalline alloys

SeMet alleviates AFB1-induced oxidative stress and apoptosis in rabbit kidney by regulating Nrf2//Keap1/NQO1 and PI3K/AKT signaling pathways

The purpose of this study was to explore the protective effect of SeMet on renal injury induced by AFB1 in rabbits and its molecular mechanism. Forty rabbits of 35 days old were randomly divided into control group, AFB1 group (0.3 mg AFB1/kg b.w), 0.2 mg/kg Se + AFB1 group (0.3 mg AFB1/kg b.w + 0.2 mg SeMet/kg feed) and 0.4 mg/kg Se + AFB1 group (0.3 mg AFB1/kg b.w + 0.4 mg SeMet/kg feed). The SeMet treatment group was fed different doses of SeMet diets every day for 21 days. On the 17–21 day, the AFB1 treatment group, the 0.2 mg/kg Se + AFB1 group and the 0.4 mg/kg Se + AFB1 group were administered 0.3 mg AFB1 /kg b.w by gavage (dissolved in 0.5 ml olive oil) respectively. The results showed that AFB1 poisoning resulted in the changes of renal structure, the increase of renal coefficient and serum biochemical indexes, the ascent of ROS and MDA levels, the descent of antioxidant enzyme activity, and the significant down-regulation of Nrf2, HO-1 and NQO1. Besides, AFB1 poisoning increased the number of renal apoptotic cells, rised the levels of PTEN, Bax, Caspase-3 and Caspase-9, and decreased the levels of PI3K, AKT, p-AKT and Bcl-2. In summary, SeMet was added to alleviate the oxidative stress injury and apoptosis of kidney induced by AFB1, and the effect of 0.2 mg/kg Se + AFB1 is better than 0.4 mg/kg Se + AFB1

DNA BARCODING OF TRADED SHARK FINS, MEAT AND MOBULID GILL PLATES IN SINGAPORE UNCOVERS NUMEROUS THREATENED SPECIES

10.1007/s10592-018-1108-11961393-139