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Electrically conductive cementitious composite (ECCC) can be utilized in traffic detection, structural health monitoring (SHM), and pavement deicing. Graphite is a popular conductive filler given its outstanding electrical resistance behavior, but its flat micro‐surface decreases the friction resistance, reducing mechanical strength. However, slag solids can substitute part of the graphite with their considerable conductivity and superior mechanical characteristics. In this research, 27 ECCC composites are developed incorporated by combined graphite powder (GP), blast furnace slag (GGBS), and steel slag (SS). Flexural, unconfined compressive strength (UCS) experiments, and resistance experiments with failure mode evaluations are carried out to explore the influence of proposed conductive fillers with different fractions. Results show the graphite strongly improves conductivity but dramatically reduces mechanical performance. Both steel slag and GGBS reduced the compressive and flexural strength after their replacement ratio exceeded 20%. Additionally, compared with GGBS, SS demonstrated a better influence on mechanical and conductive performance. A 15 wt% ratio of GGBS, 20 wt% of SS, and 4 wt% of GP are explored as the optimum design with 3.4 MPa of flexural strength, 36 MPa of compressive strength, and 7,779 Ω cm of resistance. Lastly, a microstructural investigation is conducted to explore the mechanical and conductive mechanism of ECCC. [ABSTRACT FROM AUTHOR]

Recently, impacts of microRNAs have been unraveled in human diseases, and we aimed to confirm the role of miR‐30b/30d in fulminant hepatic failure (FHF). Expression of miR‐30b/30d and CEACAM1 in serum of FHF patients and healthy people was measured by reverse transcription quantitative polymerase chain reaction (RT‐qPCR) and Western blot analysis. Mice FHF models were established by injection of D‐Galn and lipopolysaccharide, and were treated with miR‐30b/30d mimics. Oxidative stress, liver injury, and inflammatory reaction in mouse liver tissues were measured using oxidative stress‐related factor kits, hematoxylin–eosin staining and enzyme‐linked immunosorbent assay, respectively. Moreover, cell cycle distribution and apoptosis of hepatocytes of mice were determined by flow cytometry, and the target relation between miR‐30b/30d and CEACAM1 was confirmed by bioinformatic method and dual luciferase reporter gene assay. MiR‐30b/30d expression was positively, and CEACAM1 expression was negatively related to prognosis of FHF patients. Up‐regulation of miR‐30b/30d attenuated oxidative stress, liver injury, and inflammatory reaction, and improved survival rate of FHF mice. Furthermore, elevated miR‐30b/30d ameliorated apoptosis and cell cycle arrest of hepatocytes of FHF mice. CEACAM1 was a target gene of miR‐30b/30d. This study highlights that up‐regulated miR‐30b/30d attenuates the progression of FHF by targeting CEACAM1, which may be helpful to FHF treatment. [ABSTRACT FROM AUTHOR]

Self‐compacting concrete (SCC) is a cementitious composite which serves complex formworks without mechanical vibrations with superior deformability and high resistance to segregation. Besides, the recycled aggregate concrete (RAC) is also developing rapidly and along with the ever‐increasing sustainable demand for infrastructure. The combination of the fibers, RAC, and SCC may create advantages for the construction industry. In this study, the polypropylene (PP) fiber at 0.1, 0.15, 0.2, and 0.25% volume fractions and steel fibers at 0.25, 0.5, 0.75, and 1% volume fractions are introduced into fiber‐reinforced recycled aggregate self‐compacting concrete (FR‐RASCC). Both fresh property and hardened mechanical performance, comprising compressive and tensile strengths and modulus of elasticity are analyzed. The fibers validate the optimal 0.1% volume fraction for PP fiber and 0.75% volume fraction for steel fiber. In addition, the results are proved to enhance the mechanical properties and reduce cracking despite the negative impact on the fresh property. Moreover, the experimental outcomes are compared with previous researches to establish the linear model, demonstrating the relationship between fiber fraction and the mechanical properties. [ABSTRACT FROM AUTHOR]

Self‐compacting concrete (SCC) has developed rapidly in modern concrete structures to accommodate the need of high deformability and considerable resistance to segregation. The lightweight aggregate called scoria is also utilized to manufacture lightweight self‐compacting concrete (LWSCC) to improve the strength‐to‐weight ratio with considerable cost beneficial. Meanwhile, the LWSCC employs fibers (polypropylene [PP] and steel) equipping different replacement ratios of traditional aggregates, the SCC will be invented to reveal balanced fresh property, spalling behavior, mechanical performance especially at elevated temperatures. In this study, eight LWSCC mix designs were explored with varying fiber ratios by volume of PP fiber (0.1, 0.15, 0.20, and 0.25%) and steel fiber (0.25, 0.5, 0.75, and 1.0%). The effects of different fiber types and ratios are tested with fresh properties (slump flow and J‐ring), hardened mechanical performance (compressive and tensile strength at 20°C) and high temperature resistance (compressive and tensile strength, mass loss and spalling) after 28‐day curing at 100, 300, 600, and 900°C. The 0.25% optimum fiber ratio for PP fiber mix and 0.75% for steel fiber mix are determined with balanced fresh properties as well as high‐temperature resistance for the hardened properties. [ABSTRACT FROM AUTHOR]

Summary: This investigation studied the coalcrete, a new supporting material produced by jet grouting (JG) for supporting surrounding coal seams. For support design, the unconfined compressive strength (UCS) of the coalcrete is an essential parameter to evaluate the jet grouting effect in coal mines. In this study, an intelligent technique was proposed for predicting the UCS of the coalcrete by combining back propagation neural network (BPNN) and beetle antennae search (BAS). The architecture of BPNN was first tuned by BAS, and then, the optimized BPNN‐BAS model was subsequently used for nonlinear relationship modeling. Several crucial influencing variables including water‐cement ratio, coal‐grout ratio, and curing time were selected as the inputs. By combining these variables, 360 coalcrete samples were prepared in a controlled laboratory environment and tested for establishing the dataset. The results demonstrate that BAS can tune the BPNN architecture more efficiently compared with random selection. Moreover, in comparison with multiple regression (MLR) and logistic regression (LR), and support vector machine (SVM), the optimized BPNN‐BAS model is more reliable and accurate for predicting coalcrete strength. Sensitivity analysis (SA) was used to obtain the variable importance, and the results demonstrate that curing time affects the UCS of the coalcrete most strongly, followed by water‐cement ratio and coal‐grout ratio. The success of this study provides an accurate and brief approach to coalcrete strength prediction. [ABSTRACT FROM AUTHOR]

As large-scale wind farms (WFs) are integrated with the power grid, the interaction between the WF and the grid may excite torsional vibration of the shaft of the wind turbine. To study the shaft's torsional vibration characteristics of a doubly fed induction generator (DFIG)-based WF, a detailed small-signal model of DFIG is established first. Then the small-signal model for a WF composed of multiple DFIGs is developed on the basis of the single-machine model. Modal analysis is employed to investigate the torsional vibration characteristics of a WF made up of several identical DFIGs, whose accuracy is also demonstrated through time-domain simulation. To simplify the torsional vibration analysis for the DFIG-based WF, a reduced-order equivalent model is proposed. The results obtained from modal analysis show that the equivalent model not only precisely maintains all the torsional vibration modes of the original small-signal model but also greatly reduces the computation complexity. With the equivalent model, the 'curse of dimensionality' problem is solved in torsional vibration analysis for large WFs, which is of great help in the design of further damping schemes. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]