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This paper aims to explore the correlate relationship between particle size composition and porosity of particles and reveal its influence mechanism. First, aggregate particles were divided into coarse aggregate, medium aggregate and fine aggregate. Combination of the particle size ratio and mixing proportion of each grade aggregate were used to characterize the particle size distribution. Second, a mixture proportion triangular coordinate system was proposed; and a series of void ratio contour maps of granular mixtures were plotted in the coordinates based on results of the discrete element numerical simulation test. Finally, correlation between mixture composition and porosity has been analysed. It was found that (1) The void ratio of mixtures with different particle size ratio combinations is mainly different from the size and distribution. (2) Both proportion and particle size composition of coarse aggregate are main factors affecting the change of porosity. (3) For mixtures with the maximum particle size of 16 mm, various particle size ratios within that definition of coarse aggregate are possible. Suitable combination schemes of particle size ratio for each grade of aggregate are recommended for the gradation evaluation and design. (4) The relationship between gradations and voids for the granular mixtures has been established and quantitatively characterised.. [ABSTRACT FROM AUTHOR]

This paper aims to explore the correlate relationship between particle size composition and porosity of particles and reveal its influence mechanism. First, aggregate particles were divided into coarse aggregate, medium aggregate and fine aggregate. Combination of the particle size ratio and mixing proportion of each grade aggregate were used to characterize the particle size distribution. Second, a mixture proportion triangular coordinate system was proposed; and a series of void ratio contour maps of granular mixtures were plotted in the coordinates based on results of the discrete element numerical simulation test. Finally, correlation between mixture composition and porosity has been analysed. It was found that (1) The void ratio of mixtures with different particle size ratio combinations is mainly different from the size and distribution. (2) Both proportion and particle size composition of coarse aggregate are main factors affecting the change of porosity. (3) For mixtures with the maximum particle size of 16 mm, various particle size ratios within that definition of coarse aggregate are possible. Suitable combination schemes of particle size ratio for each grade of aggregate are recommended for the gradation evaluation and design. (4) The relationship between gradations and voids for the granular mixtures has been established and quantitatively characterised.. [ABSTRACT FROM AUTHOR]

Background: Guanine nucleotide-binding protein 2 (GNBP2) is a GTPase that has critical roles in host immunity and some types of cancer, but its function in clear cell renal cell carcinoma (ccRCC) is not fully understood. Objective: This work explored the role of GNBP2 in ccRCC progression and the underlying molecular mechanism. Methods: Two public human cancer databases TNMplot and TISIDB were employed to analyze the expression pattern of GNBP2 during ccRCC progression and the correlation between GNBP2 expression and clinical features of ccRCC patients. GNBP2 functions in ccRCC cells were determined by EdU staining, flow cytometry, scratch wound assay, transwell assay, and xenograft model. Gene expression was evaluated using qPCR, Western blot, immunofluorescence staining, and immunohistochemical staining. Results: GNBP2 expression was significantly elevated in ccRCC tissues and increased gradually with the increasing tumor grades. Patients with higher GNBP2 expression had shorter overall survival times. Knockdown of GNBP2 suppressed tumor cell proliferation and cell cycle progression and reduced the capability of migration and invasion, while GNBP2 overexpression exhibited protumor effects. GNBP2 silencing by RNA interference significantly inhibited the tumor growth of tumor-bearing nude mice and decreased the proliferation marker Ki67. Mechanistically, GNBP2 downregulation suppressed the STAT3 signaling transduction, as it reduced the phosphorylation of STAT3 and modulated the expression of the target genes, including c-Myc, MMP2, N-cadherin, and E-cadherin. Conclusion: These findings reveal that GNBP2 promotes ccRCC progression by regulating STAT3 signaling transduction, indicating that GNBP2 might be a promising molecular target for ccRCC therapy. [ABSTRACT FROM AUTHOR]

Oxide heterostructures exhibit many intriguing properties. Here we provide design principles for inducing multiple topological states in (001) (AMO3)1/( A M ′ O3)1 oxide superlattices. Aided by first-principles calculations and model analysis, we show that a (SrMO3)1/(Sr M ′ O3)1 superlattice (M = Nb, Ta and M ′ = Rh, Ir) is a strong topological insulator with Z2 index (1;001). More remarkably, a (SrMoO3)1/(SrIrO3)1 superlattice exhibits multiple coexisting topological insulator (TI) and topological Dirac semi-metal (TDS) states. The TDS state has a pair of type-II Dirac points near the Fermi level and symmetry-protected Dirac node lines. The surface TDS Dirac cone is sandwiched by two surface TI Dirac cones in the energy-momentum space. The non-trivial topological properties arise from the band inversion between d orbitals of two dissimilar transition metal atoms and a particular parity property of (001) superlattice geometry. Our work demonstrates how to induce non-trivial topological states in (001) perovskite oxide heterostructures by rational design. [ABSTRACT FROM AUTHOR]

Oxide heterostructures exhibit many intriguing properties. Here we provide design principles for inducing multiple topological states in (001) (AMO3)1/( A M ′ O3)1 oxide superlattices. Aided by first-principles calculations and model analysis, we show that a (SrMO3)1/(Sr M ′ O3)1 superlattice (M = Nb, Ta and M ′ = Rh, Ir) is a strong topological insulator with Z2 index (1;001). More remarkably, a (SrMoO3)1/(SrIrO3)1 superlattice exhibits multiple coexisting topological insulator (TI) and topological Dirac semi-metal (TDS) states. The TDS state has a pair of type-II Dirac points near the Fermi level and symmetry-protected Dirac node lines. The surface TDS Dirac cone is sandwiched by two surface TI Dirac cones in the energy-momentum space. The non-trivial topological properties arise from the band inversion between d orbitals of two dissimilar transition metal atoms and a particular parity property of (001) superlattice geometry. Our work demonstrates how to induce non-trivial topological states in (001) perovskite oxide heterostructures by rational design. [ABSTRACT FROM AUTHOR]

Background: M7G modification is extremely vital for the development of many cancers, especially tumor immunity. M7G modification is a novel functional regulator of miRNA, and the researches on m7G-related miRNAs in kidney renal clear cell carcinoma (KIRC) are still insufficient. This research aims to establish a risk signature on the foundation of m7G-associated miRNAs, which can precisely forecast the prognosis of KIRC patients. Methods: Transcriptome data and clinical data used in this study come from The Cancer Genome Atlas database. Our team utilized univariable Cox, Lasso and multivariable Cox analyses to construct a m7G-associated miRNAs risk signature that can forecast the prognosis of KIRC patients. Kaplan-Meier method, time-dependent receiver operating characteristic (ROC) curve, and the independent analysis of risk signatures were employed to verify the predictability and accuracy of the risk signature. Subsequently, based on CIBERSORT, ESTIMATE and ssGSEA algorithms, we speculated the potential impact of the proposed risk signature on tumor immune microenvironment. Ultimately, by virtue of the risk signature and tumor immunity, the hub genes affecting the prognosis of KIRC patients were screened out. Results: Our team established and verified a prognostic signature comprising 7 m7G-associated miRNAs (miR-342-3p, miR-221-3p, miR-222-3p, miR-1277-3p, miR-6718-5p, miR-1251-5p, and miR-486-5p). The results of the Kaplan-Meier survival analysis revealed that the prognosis of KIRC sufferers in the high-risk group was often unsatisfactory. The accuracy of the prediction ability of the risk signature was verified by calculating the area under the ROC curve. Univariate-multivariate Cox analyses further showed that this risk signature could be utilized as an independent prognosis-related biomarker for KIRC sufferers. The results of the immune analysis revealed that remarkable diversities existed in immune status and tumor microenvironment between high-risk and low-risk groups. On the foundation of the proposed risk signature and other clinical factors, a nomogram was established to quantitatively forecast the survival of KIRC sufferers at 1, 3 and 5 years. Conclusion: Based on m7G-related miRNAs, a risk signature was successfully constructed, which could precisely forecast the prognosis of sufferers and guide personalized immunotherapy for KIRC patients. [ABSTRACT FROM AUTHOR]

Time series prediction refers to the learning of existing observed data of a parameter and predicting its future evolution. Based on the application of machine/deep learning methods in the field of engineering geology, it is desirable to predict the time series evolution of microseismic parameters in the process of rockburst development. Our study explores key microseismic indices that help describe the development process of rockbursts based on abundant rockburst data obtained from deep underground engineering construction. The integrated process of dynamic moving-window method and improved convolutional neural network (CNN) realizes the evolution prediction of multiple microseismic parameters or their different combinations, and the modified model structures of a univariate, multivariate input and a single-step, multi-step output are established. Various models of the multiple microseismic parameters for the CNN-based time series prediction are innovated, including a univariate prediction model, a multiple parallel series model, a multiple input series model, and a multivariate multi-step prediction model. Model training, testing, and interpretation of the rockburst risk and comparative analyses of the different models are performed for the complete process of multiple rockbursts. The results show that the proposed models can well predict the evolution trends in the various key characteristics during rockbursts. The predicted trend of multiple microseismic parameters provides time labels for rockburst prediction and risk judgement, which is conducive to rockburst early warning. This study provides a new research idea for the prediction and early warning of rockbursts in the field of deep underground and mining engineering. [ABSTRACT FROM AUTHOR]

Water inrush is a serious geological disaster in tunnel. For the effective prevention and control of the occurrence of water inrush, a static-dynamic water inrush risk assessment method is proposed by considering the Micangshan tunnel as an example. First, four possible types of water inrush phenomenon are identified based on the geological and hydrogeological conditions of the tunnel: water inrush in water-bearing cracks, fault fracture zones, karst pipelines, and karst caves. Next, evaluation indexes that affect water inrush are determined. By combining the index weight value calculated by analytic hierarchy process (AHP) with the index quantitative value, the static water inrush disaster evaluation model is established, which provides a basis for tunnel design. Finally, with the combination of the static evaluation model and advanced forecast method, a dynamic risk prediction method of water inrush is established, which provides guidance for safe construction. The results confirm that the proposed method is a reliable theoretical basis for early assessment and prediction of tunnel water inrush disasters. [ABSTRACT FROM AUTHOR]

We use first-principles methods to study doped strong ferroelectrics (taking BaTiO3 as a prototype). Here, we find a strong coupling between itinerant electrons and soft polar phonons in doped BaTiO3, contrary to Anderson/Blount's weakly coupled electron mechanism for "ferroelectric-like metals". As a consequence, across a polar-to-centrosymmetric phase transition in doped BaTiO3, the total electron-phonon coupling is increased to about 0.6 around the critical concentration, which is sufficient to induce phonon-mediated superconductivity of about 2 K. Lowering the crystal symmetry of doped BaTiO3 by imposing epitaxial strain can further increase the superconducting temperature via a sizable coupling between itinerant electrons and acoustic phonons. Our work demonstrates a viable approach to modulating electron-phonon coupling and inducing phonon-mediated superconductivity in doped strong ferroelectrics and potentially in polar metals. Our results also show that the weakly coupled electron mechanism for "ferroelectric-like metals" is not necessarily present in doped strong ferroelectrics. Usually the coupling between polar phonons and itinerant electrons is weak in polar metals. Here, the authors show that in doped ferroelectrics (approximate polar metals), this coupling can be increased across the structural phase transition and as a result, phonon-mediated superconductivity emerges. [ABSTRACT FROM AUTHOR]

The effects of heat treatment on microstructure, mechanical properties, corrosion resistance and cytotoxicity of extruded Mg-2Zn-1Mn (wt.%) alloy were investigated for biomedical application in this study. The extruded alloy was T4 treated at 510 °C for 4 h and T5 treated at 200 °C for 16 h separately. The extruded Mg-Zn-Mn alloy mainly consists of MgxMny phases. After T4 treatment, the amount of MgxMny phases decreases and average grain size rises from 8 to 24 μm. After T5 treatment, Mg7Zn3 phase newly precipitates along the grain boundaries and the size of grain remains similar. Compared with the T4-treated samples, the extruded and T5-treated samples exhibit higher mechanical properties. The T5-treated samples have an ultimate tensile stress of 273 MPa and an elongation of 19.7%. On the other hand, T4-treated samples present higher corrosion resistance in electrochemical tests. The degradation rates of extruded, T4-treated and T5-treated samples are 0.44 mm/year, 0.48 mm/year and 0.50 mm/year, respectively, in Ringer's solution at 37 ± 0.2 °C. In addition, T4-treated alloy does not induce toxicity to the L-929 cells in in vitro cytotoxicity test. [ABSTRACT FROM AUTHOR]

High pressure water jet removing impurities in formations is a new way developed recently to increase oil production and injected-water. First of all, this paper presents the main reasons of formation plugging, the basic principles of high pressure rotating water jets removing impurities and the laws of the tool's rotating speeds, impact pressure and relations between impact pressure and nozzle stand-off. The field-test results obtained from over 500 oil and water-injection wells in Liaohe, Shengli, Zhongyuan, Huabei etc., indicate that this technology has such advantages as simplicity of use, cost effective, high success rate, wide adaptability, and significant effectiveness. From this, it is profitable and promising to increase production in highly water-cut oilfields. [ABSTRACT FROM AUTHOR]

Studies the structure of liquid hypoeutectic aluminum (Al)-iron (Fe) alloy and its change with different thermal histories. Structure factors of Al-Fe melts at 675 degrees Centigrade; Structure factors of the nonsuperheated and superheated Al melts.

Using X-ray diffraction, the structure factors of molten Al−Fe alloys were determined as a function of composition at a constant 1 550°C. The nearest neighbour distance and coordination number are given. Both structure factors and total density functions could be well reproduced by a micro-inhomogeneous model. The entire concentration region can be divided into four intervals with Al, Al7Fe, Al5Fe2, Fe3Al and Fe acting as borders. Alloys situated at the borders of the concentration intervals contain clusters of one type whose composition represents that of the alloy in question. The alloys between the borders contain clusters of the two border types. [ABSTRACT FROM AUTHOR]