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The estimated ultimate recovery (EUR) of shale gas wells is influenced by many factors, and the accurate prediction still faces certain challenges. As an artificial intelligence algorithm, deep learning yields notable advantages in nonlinear regression. Therefore, it is feasible to predict the EUR of shale gas wells based on a deep-learning algorithm. In this paper, according to geological evaluation data, hydraulic fracturing data, production data and EUR evaluation results of 282 wells in the WY shale gas field, a deep-learning-based algorithm for EUR evaluation of shale gas wells was designed and realized. First, the existing EUR evaluation methods of shale gas wells and the deep feedforward neural network algorithm was systematically analyzed. Second, the technical process of a deep-learning-based algorithm for EUR prediction of shale gas wells was designed. Finally, by means of real data obtained from the WY shale gas field, several different cases were applied to testify the validity and accuracy of the proposed approach. The results show that the EUR prediction with high accuracy. In addition, the results are affected by the variety and number of input parameters, the network structure and hyperparameters. The proposed approach can be extended to other shale fields using the similar technic process.

Immunosenescence is characterized by an age-related decline in immune system function. Major efforts have been made to identify changes in peripheral blood lymphocyte subsets accompanying immunosenescence in elderly adults. However, the change trends of some lymphocyte subsets with age are still controversial, and populations of advanced ages, such as people in their 80s or 90s, have not yet been thoroughly investigated. To provide further insight, we recruited 957 healthy donors without certain diseases with ages ranging from 20 to 95 years. Peripheral lymphocyte subsets, including T cells, CD4 T cells, CD8 T cells, B cells and NK cells, and the CD4/CD8 ratio were measured by flow cytometry. Additionally, regulatory CD4 T cells with inhibitory functions marked by CD3+CD4+CD25hi and the expression of the costimulatory molecule CD28 on CD8 T cells were evaluated. Sex was considered at the same time. The data indicated that in elderly people, peripheral T (p

Understanding the effects of phytoremediation on ecological environments is a core issue in soil bioremediation. However, the response of soil micro-ecological environment to long-term phytoremediation of symbiotic legume is still unknown. To address this issue, we focused on the changes of soil physicochemical properties, microbial communities, ecological functions, and correlation relationships of microbial populations in the V Ti magnetite mine tailings subsoil and the natural topsoil after three years' in-situ phytoremediation using the symbiotic Pongamia pinnata. The results showed that the bioavailability of soil nutrients and metals had undergone different degrees of significant changes in the two different metallic soil types after phytoremediation. It was revealed by changes in alpha-diversity indices, relative microbial abundance, LEfSe scores, and the number of significant OTUs that long-term phytoremediation using P. pinnata significantly altered soil microbial communities. This shift further caused a significant change in soil ecological functions and microbial community correlations. All changes in ecological functions caused by P. pinnata were in different degrees in the two different soil types. The Bray-Curtis based redundancy analysis (bcRDA) indicated that the shift of microbial communities was driven by several bioavailable nutrients and metals. Therefore, this study proved that long-term phytoremediation of symbiotic legumes could reshape soil microbial communities, and implied that a dramatic change in soil micro-ecological environment and an improvement of soil quality were the results of following long-term phytoremediation using the symbiotic legume.

Hyperglycemia-induced cartilage degeneration induces osteoarthritis (OA). Since oleanolic acid (OLA) have several pharmacological effects such as anti-inflammatory, anti-oxidant, we hypothesized it possesses protection against high glucose injured cartilage. We now report that OLA decreased type X collagen and reversed the cartilage degeneration in growth plate from db/db mice. OLA increased type Ⅱ collagen expression in a concentration-dependent manner (10-50 μΜ) in high glucose-treated chondrocytes. OLA prevented the high glucose induced cell injury and decreased the level of MMP-13, PGE2 and IL-6 due to decreasing mitochondrial membrane potential and stimulated the ATP production. Moreover, OLA treatment inhibited apoptosis. And the reversed SOD2 expression and activity may be ascribed to decreased SOD2 protein degradation by OLA treatment, via PPPAγ. In conclusion, OLA protected against the high-glucose-induced cartilage injury via PPARγ/SOD2 pathway.

Background The severity and outcome of COVID-19 cases has been associated with percentage of circulating lymphocytes (LYM%), levels of C-reactive protein (CRP), interleukin 6 (IL-6), procalcitonin (PCT), lactic acid (LA) and viral load (ORF1ab Ct). However, the predictive power of each of these indicators in disease classification and prognosis remains largely unclear. Methods we retrospectively collected information on the above parameters in 142 patients with COVID-19, stratifying them by survival or disease severity. Findings CRP, PCT, IL-6, LYM% and ORF1ab Ct were significantly altered between survivors and non-survivors. LYM%, CRP and IL-6 were the most sensitive and reliable factors in distinguishing between survivors and non-survivors. These indicators were significantly different between critically ill and severe/moderate patients. Only LYM% levels were significantly different between severe and moderate types. Among all the investigated indicators, LYM% was the most sensitive and reliable in discriminating between critically ill, severe and moderate types, and between survivors and non-survivors. Conclusions CRP, PCT, IL-6, LYM% and ORF1ab Ct, but not LA, could predict prognosis and guide classification of COVID-19 patients. LYM% was the most sensitive and reliable predictor for disease typing and prognosis. We recommend that LYM% be further investigated in the management of COVID-19., Graphical Abstract, Highlights: (1) Inflammatory cytokines, lymphocytes and viral load predict prognosis in COVID-19 patients. (2) Inflammatory cytokines, lymphocytes and viral load indicate disease severity. (3) Lymphocytes and C-reactive protein distinguish between severe and moderate types. (4) Lymphocyte count is the most effective indicator of disease severity and prognosis.

Background Context Polymethylmethacrylate (PMMA) is widely used for pedicle screw augmentation in osteoporosis. Intriguingly, there have been no biomechanical comparisons of the stability of pedicle screws augmented with different volumes of PMMA or studies of the relationship between screw stability and volume of PMMA, especially in different degrees of osteoporosis. Purpose The purposes of the study reported here were to compare screw stability by different volumes of PMMA augmentation, to analyze the relationship between screw stability and PMMA volume, and to make a preliminary determination of the optimum volume of PMMA augmentation for different degrees of osteoporosis. Study Design This study is a biomechanical comparison of pedicle screws augmented with various volumes of PMMA in cadaveric lumbar vertebrae. Methods Thirty-six pedicles from 18 osteoporotic lumbar vertebrae were randomly divided into groups A0 through A5, and 36 pedicles from 18 severely osteoporotic lumbar vertebrae were randomly divided into groups B0 through B5. A different volume of PMMA was injected into each one of groups A0 through A5 (0, 0.5, 1.0, 1.5, 2.0, and 2.5 mL, respectively) and into each one of groups B0 through B5 (0, 1.0, 1.5, 2.0, 2.5, and 3.0 mL, respectively), and then pedicle screws were inserted in all vertebrae. After complete solidification of the PMMA, we examined pedicle X-rays, performed axial pullout tests, and determined the maximum axial pullout strength (F max ) for all samples. Results No PMMA was found around the screws in groups A0 and B0. In groups A1 to A5 and B1 to B5, screws were wrapped by gradually increasing amounts of PMMA. There was no PMMA leakage or screw malpositioning in any samples. The F max in groups A1 through A5 increased by 32.40%, 64.42%, 116.02%, 174.07%, and 207.42%, respectively, compared with that in group A0. There were no significant differences in F max between groups A0 and A1, A1 and A2, A2 and A3, A3 and A4, and A4 and A5 (p>.05), but there were significant differences in F max between any other two groups (p max in groups B1 through B5 increased by 23.48%, 48.40%, 106.60%, 134.73%, and 210.04%, respectively, compared with that in group B0. There were no significant differences in F max between groups B0 and B1, B0 and B2, B1 and B2, B2 and B3, B3 and B4 (p>.05), but there were significant differences in F max between any other two groups (p max and volume of PMMA in both osteoporotic and severely osteoporotic lumbar vertebrae (p Conclusions Polymethylmethacrylate can significantly enhance stability of pedicle screws in both osteoporotic and severely osteoporotic lumbar vertebrae. There is a significant positive correlation between screw stability and volume of PMMA. Within a certain range, nevertheless, increasing the volume of PMMA does not significantly improve screw stability. We suggest that 1.5 and 3 mL, respectively, are the volumes of injected PMMA that will optimize pedicle screw stability in osteoporotic and severely osteoporotic lumbar vertebrae.

Mine tailings contain dangerously high levels of toxic metals which pose a constant threat to local ecosystems. Few naturally grown native plants can colonize tailings site and the existence of their root-associated microbial populations is poorly understood. The objective of this study was to give further insights into the interactions between native plants and their microbiota during natural attenuation of abandoned V–Ti magnetite mine tailings. In the present work, we first examined the native plants’ potential for phytoremediation using plant/soil analytical methods and then investigated the root microbial communities and their inferred functions using 16 S rRNA-based metagenomics. It was found that in V–Ti magnetite mine tailings the two dominant plants Bothriochloa ischaemum and Typha angustifolia were able to increase available nitrogen in the rhizosphere soil by 23.3% and 53.7% respectively. The translocation factors (TF) for both plants indicated that B. ischaemum was able to accumulate Pb (TF = 1.212), while T. angustifolia was an accumulator of Mn (TF = 2.502). The microbial community structure was more complex in the soil associated with T. angustifolia than with B. ischaemum. The presence of both plants significantly reduced the population of Acinetobacter. Specifically, B. ischaemum enriched Massilia, Opitutus and Hydrogenophaga species while T. angustifolia significantly increased rhizobia species. Multivariate analyses revealed that among all tested soil variables Fe and total organic carbon (TOC) could be the key factors in shaping the microbial structure. The putative functional analysis indicated that soil sample of B. ischaemum was abundant with nitrate/nitrite reduction-related functions while that of T. angustifolia was rich in nitrogen fixing functions. The results indicate that these native plants host a diverse range of soil microbes, whose community structure can be shaped by plant types and soil variables. It is also possible that these plants can be used to improve soil nitrogen content and serve as bioaccumulators for Pb or Mn for phytoremediation purposes.

Mine tailings contain toxic metals and can lead to serious pollution of soil environment. Phytoremediation using legumes has been regarded as an eco-friendly way for the rehabilitation of tailings-laden lands but little is known about the changes of microbial structure during the process. In the present study, we monitored the dynamic change of microbiota in the rhizosphere of Pongamia pinnata during a 2-year on-site remediation of vanadium-titanium magnetite tailings. After remediation, overall soil health conditions were significantly improved as increased available N and P contents and enzyme activities were discovered. There was also an increase of microbial carbon and nitrogen contents. The Illumina sequencing technique revealed that the abundance of taxa under Proteobacteria was increased and rhizobia-related OTUs were preferentially enriched. A significant difference was discovered for sample groups before and after remediation. Rhizobium and Nordella were identified as the keystone taxa at genus rank. The functional prediction indicated that nitrogen fixation was enhanced, corresponding well with qPCR results which showed a significant increase of nifH gene copy numbers by the 2nd year. Our findings for the first time elucidated that legume phytoremediation can effectively cause microbial communities to shift in favour of rhizobia in heavy metal contaminated soil.

This paper presented a detailed study of the negative Poisson's ratio (NPR) effect on shrinkage deformation and crushing stress of metallic auxetic reentrant honeycomb under low, medium and high-velocity compressions. Instead of the traditional calculating method for the crushing stress of auxetic honeycomb, the new theoretical formula considering the NPR effect was proposed. The theoretical and finite element (FE) results showed that the crushing stress of reentrant honeycomb had been underestimated according to the traditional nominal stress-strain curve. Not only had that, but also the theoretical results showed that the NPR effect could enhance the inertial effect during dynamic compression. Subsequently, under the medium and high-velocity compressions, the dynamic deformations of reentrant honeycomb were obviously different from that under low-velocity compression and those of metallic cellular materials with positive Poisson's ratio (such as Al foam and traditional hexagonal honeycomb) under medium or high-velocity compressions. In view of these differences, a new shrinkage deformation mechanism of reentrant honeycomb was proposed and a characterization parameter in contrast to the Poisson's ratio was presented to describe its dynamic shrinkage deformation capacity.

This article investigates transmitter design in Rayleigh fading multiple input multiple output (MIMO) channels with spatial correlation when there are channel uncertainties caused by a combined effect of channel estimation error and limited feedback. To overcome the high computational complexity of the optimal transmit power allocation, a simple and suboptimal allocation is proposed by exploiting the transmission constraint and differentiating a bound based on Jensen inequality on the channel capacity. The simulation results show that the mutual information corresponding to the proposed power allocation closely approaches the channel capacity corresponding to the optimal one and meanwhile the computational complexity is greatly reduced.