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While the 3D printing technology for cementitious composites has developed rapidly, a combination of 3DP technology and lightweight engineered cementitious composites (LWECCs) could improve many aspects of the construction industry. In this study, a fibre-reinforced high-performance LWECC for extrusion-based printing was proposed. First, six LWECCs were prepared, incorporating two kinds of hollow glass microspheres (HGMs) in varying replacement ratios of fly ash (FA) at 60 wt%, 80 wt%, and 100 wt%. In addition, polyvinyl alcohol (PVA) fibre was introduced given its shrinkage resistance and improvement in printability performance. Thereafter, fresh property (slump loss and setting time), unconfined compression strength (UCS), and flexural strength experiments thoroughly investigated the optimised LWECC design, which was later calibrated for the printing procedure via a printability assessment, including extrudability and buildability. The UCS, flexural strength, and densities of the printed and cast specimens were compared. Lastly, a microstructural investigation using a scanning electron microscope described the reinforcement mechanism of PVA fibre upon the performance of the printed structures and HGMs. The addition of HGMs significantly improve the lightweight property that reaches a value at 1384 kg/m3 but inevitably negates mechanical properties. The printed LWECC obtains 33.6 MPa for UCS and 9.29 MPa for flexural strength. When the printed filament was perpendicular to loading direction, superior toughness was observed, creating a 63% and 40% increase for UCS and flexural strength, respectively. [ABSTRACT FROM AUTHOR]

Electromagnetic wave (EMW) pollution poses a tremendous effect on information security and human health. However, ordinary concrete structure incorporated by ferrite fiber lacks EMW absorption flexibility to form electromagnetic superstructures. 3D printing technology paves an effective way to facilitate the anisotropy of electromagnetic absorption capacity by generating directional effects on ferrite fiber. This research evaluates the influence of 3D-printed fiber-oriented superstructure on EMW absorption performance with an equivalent waveguide attenuator model. The microwave-absorbing cementitious composite (10% magnetite and 25% copper slag) was prepared to incorporate 0.5 wt% copper fibers (CF) and steel fibers (SF), respectively. Absorption elements in each group are prepared by laminar parallel printing, cross-printing, and zigzag printing. In addition, the EMW absorption capability (ranging from 2 GHz to 18 GHz) was investigated by the Naval Research Laboratory (NRL) equipment. The overall EMW absorption performance of the SF samples is superior to CF samples. The optimized order of the EMW absorption performance of CF-reinforced samples is determined as zigzag, parallel, and cross printing, while SF is parallel, cross, and zigzag printing methodology. Overall, the laminar parallel printed steel fiber element gave the best shot with a peak reflectivity of − 16.34 dB and an absorption bandwidth of 13.15 GHz. Meanwhile, SF-reinforced specimens all demonstrated absorption peaks around 8 GHz, while CF-incorporated samples' absorption peaks appeared at both 8 GHz and 12 GHz, offering multiple design and application choices according to engineering requirements. Finally, an equivalent attenuator model is suggested for illustrating the superimposed reinforcement, spatial impedance matching, and multiple scattering of dielectric properties. • The prominent fiber orientation effect induced by 3D printing facilitates the enhancement of EMW anisotropic properties. • Copper fibers with slender dimensions form abundant and flexible multi-size equivalent waveguide attenuator structures that promote vector superposition and interference effects, exhibiting RL peaks at both 7 GHz and 12 GHz. • The steel fiber-reinforced samples are superior to the fine copper fiber samples in terms of overall electromagnetic absorption performance. The steel fibers and the surrounding concrete exhibit various gradients in their ability to adsorb EMW, resulting in a completely absorbing superstructure. • The electromagnetic wave absorption mechanism of the equivalent waveguide attenuator model for the fiber-reinforced composite is analyzed in detail. [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]

• A novel method was proposed for predicting permeability and unconfined compressive strength of pervious concrete. • 270 samples were prepared for building the dataset. • Permeable and mechanical properties of pervious concrete were elucidated. • Beetle antennae search was firstly used to tune the hyper-parameters of support vector regression. • The support vector regression model tuned by beetle antennae search algorithm has high prediction accuracy. Pervious concrete is a widely used construction material thanks to its good drainage characteristics. Before application, its most important properties, i.e. the permeability coefficient (PC) and 28-day unconfined compressive strength (UCS) are required to be tested. However, conducting PC and UCS tests with multiple influencing variables is time-consuming and costly. To address this issue, this paper proposed, for the first time, an evolved support vector regression (ESVR) tuned by beetle antennae search (BAS) to accurately and effectively predict the PC and UCS of pervious concrete. To prepare the dataset of the ESVR model, 270 specimens in total were prepared and casted in a controlled environment in the laboratory. The water-to-cement (w/c) ratio, aggregate-to-cement (a/c) ratio, and aggregate size were selected as the crucial influencing variables for the inputs, while PC and UCS were the outputs of this model. The results indicate that both the PC and UCS firstly increased and then decreased with increasing w/c ratio. As the a/c ratio increased, PC increased, while UCS decreased. Moreover, BAS is more reliable and efficient than random hyper-parameter selection for hyper-parameter tuning. A low root-mean-square error (RMSE) and high correlation coefficient (R) indicate a relatively high predictive capability of the proposed ESVR model. The sensitivity analysis (SA) suggests the a/c ratio and aggregate size were the most sensitive variables for UCS and PC, respectively. This pioneering work provides a simple and convenient method for evaluating PC and UCS of pervious concrete. [ABSTRACT FROM AUTHOR]

Abstract The increasing electromagnetic energy and multiple reflections of electromagnetic wave (EMW) produce various negative impact on the human body, equipment, information security and even military defense structures. In this study, a new electromagnetic wave EMW absorbing cementitious composite incorporating copper slag and powder was manufactured to accommodate the rapid development of 3D printing technology. The microscale morphology and chemical compositions of adopted absorbents were examined through scanning electron microscopy (SEM), energy dispersive spectrophotometry (EDS), and X-ray fluorescence (XRF). Electromagnetic parameters for copper slag and powder were measured in the range of 1–18 GHz. Then seven cementitious composites incorporating 0-30 wt% copper slag were manufactured to access and evaluate the printable capability for extrusion-based printing. Five mass ratios (2–10 wt%) of copper powder were thereafter incorporated to the printability-optimized composite for further enhancement of EMW absorption. Based on the printable capacity, reflectivity tests using network analyzer over the 1–18 GHz range showed that the cementitious composite with 25 wt% copper slag and 6 wt% copper powder performed a favorable EMW absorption capacity with a 10.2 dB peak reflection loss value and a 3.48 GHz absorption band. In addition, the influence of macroscale configuration includes surfaces roughness and thickness on the EMW absorption were elaborated. The results provide experimental basis and references for functionalizing and intelligenting the cementitious composite for application in infrastructures. [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]

• Nano-graphite as a functional filler incorporated into concrete can significantly improve its electrical conductivity. Meanwhile, the proper amount of nano-graphite addition can also increase its mechanical strength. • The addition of copper slag improved the mechanical properties and electrical conductivity of ECCC. • The chemical activation improved the reactivity of the volcanic ash in the fly ash–cement system. The ultrasonic vibration process facilitates the uniform distribution of nano-graphite. • Combined activation is the best method to improve mechanical properties and electrical conductivity, possessing the advantages of chemical and ultrasonic activation. Electrically conductive cementitious composite (ECCC) features structural material functions, electrical conductivity, and piezoresistivity properties broadly applied in snow melting, electromagnetic shielding, cathodic protection system, and structural health monitoring (SHM). Nano-graphite is an ideal ECCC functional filler since its ability to fill molecular pores, reduce concrete shrinkage and significantly improve their electrical conductivity. However, nano-graphite is high-cost and its excessive amounts can lead to particle agglomeration. Therefore, copper slag (CS) can partially replace NG to beneficially reuse the waste by-products and save energy for protecting the environment. Nevertheless, a single blend of fillers hardly exploits the potential mechanical and conductive properties. Consequently, different activation methods were adopted to obtain desirable dispersion and performances. This paper explored the influences of chemical alkali excitation, ultrasonic vibration, and combined activation on copper slag and nano-graphite wrapped ECCC. Experimental results from a total of 387 ECCC specimens with 16 design ratios demonstrated that the combined treatment of alkali excitation and ultrasonic vibration was superior to any single treatment. The optimal samples based on 3 wt% ratio of NG and 60 wt% of copper slag activated with combined treatment exhibited 44.55 MPa compressive strength, 6.65 MPa flexural strength, and 8180 Ω·cm electrical resistance. Lastly, an SEM was conducted to analyze the microstructure of the mixture and ECCC and a schematic diagram was proposed. [ABSTRACT FROM AUTHOR]

Hepatic carcinoma (HC) is one of the leading causes of cancer-related death, and the incidence keeps high in the world. The vital role of circular RNAs (circRNAs) in HC development has been revealed to some extent. Circ_0000775, a novel circRNA, has never been thoroughly studied regarding HC. Online datasets were utilized to obtain expression pattern of genes in tumor tissues. RT-qPCR and western blot examined the RNA and protein levels of indicated genes. ChIP, DNA pull down, RNA pull down, RIP and luciferase reporter assays were carried out to verify correlation between different factors. Supported by RT-qPCR and western blot analyses, transwell and wound healing assay were implemented for detecting cell migration and invasion and EMT. Additionally, cell EMT was also evaluated via cell morphology observation for calculation of spindle cell number. High expression of circ_0000775 in HC cells was induced by transcriptionally stimulation by TCF7L2. Circ_0000775 in cytoplasm recruited IGF2BP2 to enhance the mRNA stability of CDC27, thus positively modulating CDC27 expression. Circ_0000775 exacerbated HC cell migration, invasion and EMT through CDC27. TCF7L2 promoted the transcription of circ_0000775, and circ_0000775 recruited IGF2BP2 to maintain CDC27 mRNA stability, thereby facilitating HC cell migration, invasion and EMT. [ABSTRACT FROM AUTHOR]

• WGP mortar activated by mechanical, chemical, hydrothermal, and combined treatment approaches. • UCS, flexural strength, ASR expansion, and microstructure were investigated. • The mechanical activation significantly enhanced the mechanical performance. • The chemical activation enhanced strength at early ages but negates ASR expansion. • The hydrothermal activation improved strength and is the best method to diminish the ASR expansion. • The combined activation was the optimal method to increase mechanical performance. Land disposal of waste glass results in hazardous environmental contamination. Such waste material should be reclaimed because it is inert and consequently nondegradable. The main component of glass is silica showing pozzolanic properties in cementitious matrices. Thus, the use of waste glass as a supplementary cementitious material in concrete is a sustainable solution to the land disposal of such waste materials. However, concrete incorporating waste glass suffers from deleterious expansion arising from alkali-silica reaction (ASR). This paper shows the effects of different activation approaches, including mechanical, chemical, hydrothermal, and combined activation, used to mitigate ASR. To this aim, activated waste glass powder (WGP) was produced using the aforementioned approaches and used in concrete as sand replacement at percentages of 0%, 10%, 20%, and 30%. The water to cement ratio remained unchanged for all mixes. Results showed that the combined activation was the optimal approach to increase mechanical property. The hydrothermal activation effectively reduced the detrimental ASR expansion, while the chemical treatment induced excessive expansion even for mixtures with a low WGP content of 10%. Also, microstructural analyses showed erosion on the surface of WGP activated by chemical and combined activation methods. Besides, few CH crystals were observed on 75 μm WGP mortar samples, illustrating the excellent pozzolanic activity on finer WGP. [ABSTRACT FROM AUTHOR]

• EMW-absorbing composite containing 6 wt% copper powder and 25 wt% copper slag. • EMW superstructures using 3D-printed oriented copper fiber upon microwave reflectivity. • Equivalent waveguide attenuator model and mechanism is proposed. • The copper fiber-reinforced element through crossed printing is the optimized configuration. • The superstructure creates a −20.43 dB reflectivity peak with an 11.79 GHz bandwidth. Electromagnetic wave (EMW) pollution negatively impacts information, equipment security, and the human body. However, neither powder phase absorbent nor ferrite fiber using traditional casting methodology cannot form electromagnetic superstructure to flexibly enhance EMW absorbing capacity. Thereby, ferrite fiber absorbent in well-oriented manner by 3D printing can be a feasible solution in EMW absorption due to its structural EMW anisotropy property. In this study, the influence of EMW superstructures using 3D-printed oriented copper fiber upon microwave reflectivity is investigated, and an equivalent waveguide attenuator model is proposed. First, an EMW-absorbing composite containing 6 wt% copper powder and 25 wt% copper slag is prepared. In copper slag cementitious composite, copper fiber (CF) and steel fiber (SF) are incorporated at 0.5 wt% separately. In each group, EMW-absorbing elements are manufactured through casting, laminar parallel printing, and cross printing. The superstructure anisotropy and EMW absorption performance are investigated through a network analyzer. The cross superstructure is outstanding in low-frequency absorption, while the parallel superstructure demonstrates desirable reflectivity at a high-frequency range. The copper fiber-reinforced element produced through crossed printing is determined as the optimized configuration, reaching a −20.43 dB reflectivity peak with an 11.79 GHz bandwidth. Lastly, an equivalent waveguide attenuator model is proposed to explain the superposition enhancement of the dielectric property, space impedance matching, and multiple scattering. [ABSTRACT FROM AUTHOR]

A multitude of antimony tailings (AT) solid wastes haphazardly accumulated in the open environment resulted in significant land resource occupation and serious ecological environment damage. AT as the fine aggregate additive in concrete is an effective approach for achieving solid waste resource utilization. Currently, 3D-printed AT concrete offers notable benefits in design flexibility, precision, material efficiency, productivity, and sustainability compared to conventional concrete. However, traditional AT-concrete is plagued by drawbacks including uneven strength distribution, protracted construction periods, and considerable resource consumption. Furthermore, the low reactivity and non-degradability of AT necessitate implementing modified activation techniques in AT concrete. This paper employs four modification methods (physical grinding, alkali excitation, hydrothermal activation, and combined activation) to activate AT. The modified AT is incorporated into concrete at five ratios (0 %,10 %, 20 %, 30 %, and 40 %) and integrated into a 3D printing system, manufacturing a total of 450 samples for mechanical property experiments. The result demonstrates that the combined modification method emerges as the optimal choice for enhancing the unconfined compressive strength (65.7 MPa) and flexural strength (12.9 MPa) in 3D printing. The SEM results revealed that the combined modification, alkali excitation, and hydrothermal activation led to AT depolymerization and sediment adsorption. Abundant C-S-H gel and a handful of Ca(OH) 2 crystals were observed on the physically modified AT (30 μm) surface, indicating sufficient pozzolanic reaction on 3D printed fine AT. • The 3D-printed method generally illustrates excellent impacts in strength enhancement. • AT physical modification achieves a substantial 20 % increase in mechanical properties. • Alkali-excitation modification notably increased the strength of low-content AT mortars by 35 %. • Hydrothermal modification boosts mix properties by 28% within a replacement ratio of 0 % to 30 %. [ABSTRACT FROM AUTHOR]

• A new program evaluating the impact of graphite and slag, and curing time. • Optimized slag and graphite to achieve balanced electrical and mechanical properties. • A microstructural interpretation to reveal distributions of conductive filler and C-S-H gel. Electrically conductive cementitious composites (ECCCs) have become a significant research interest in structural health monitoring. The use of graphite in ECCCs can significantly improve their electrical performance, however, with unsatisfactory friction resistance because of the graphite's smooth micro-surfaces. Slag can be incorporated with graphites into ECCCs to achieve good performance in both of mechanical resistance and electrical conductivity. This study investigated the impact of graphite and slag on the electrical and mechanical behaviors of ECCCs. Two hundred and eighty ECCC specimens were prepared with two different types of slags and with various conductivity ingredient fractions and curing times. The specimens were tested for compressive strength, flexural strength, and electrical resistance. It was concluded the 4% graphite content in ECCCs can significantly enhance electrical conductivity with moderate decrease in compressive and flexural strengths. Slags were found to improve both electrical conductivity and mechanical properties of ECCCs. The best results could be obtained with optimized contents of steel slag, blast furnace slag, and graphite. Finally, the microstructural mechanisms of the ECCC specimens were analyzed using scanning electron microscope (SEM) for graphite and slag. Variable sensitivity analysis was performed to allow for optimization of ingredient contents. [ABSTRACT FROM AUTHOR]

• The industrial by-products, solid wastes, carbon materials are discussed. • The steel fiber and ferrite exhibit satisfied EMW absorbing mechanical resistance. • The resonance materials improve EMW absorbing capacity with inferior strength. • The multi-phase and multi-layer composites and macrostructure are prospective. • The combination of 3D printing and EMW absorbing brings advantages. The ever increasing electromagnetic energy and multiple reflections of electromagnetic wave (EMW) impair human health and information security. The EMW absorbing cementitious material paves an innovative way to improve EMW absorbing performance of concrete structures. This study will elaborate on the EMW absorbing mechanism including energy exhaustion and impedance matching. A comprehensive review on the raw absorbent cementitious materials and the relevant preparation methods to be integrated into EMW absorbing concrete. Two new theoretical models are proposed including optimization zone model and equivalent electromagnetic parameter model to improve the current transform line model. Subsequently, the measurement and evaluation methodologies for EMW absorbing performance of cementitious materials are summarized. The expected research topics and applications of EMW absorbing cementitious materials are suggested. Through this critical review on the research status of EMW absorbing concrete, suggestions for optimizing the performance and workability of cementitious material are made to promote large-scale 3D printing technology. [ABSTRACT FROM AUTHOR]

• Four nano-sized graded absorbents were explored. • The 5 wt% coupling agent and 10 wt% dispersant was validated for graded absorbent. • The double-layer structure was made using spraying and extruding methodology. • The EMW mechanism for the graded double-layer structure was firstly summarized. • Theoretical calculation optimized a 15 mm absorbing layer and 15 mm impedance layer. The ever-increasing electromagnetic wave (EMW) energy and its reflections may impair human health and information security. An ordinary EMW-absorbing structure usually exhibits limited EMW-reflecting capacity given its ungraded structure in both the micro and macro scales. In this study, four nano-sized graded absorbents are explored by wrapping carbonyl-iron powder with nano-sized silicon dioxide. The micro-scale wrapping effects are assessed via a scanning electron microscopy experiment to identify the best sample, including a 5 wt% coupling agent and a 10 wt% dispersant in CIP ethanol. The 10 mm thick concrete matching layer containing the graded absorbent is built using spraying methodology, and the 15 mm thick absorption layer is fabricated using extruding methodology. The mercury intrusion porosimetry experiments show that the sprayed matching layer incurs maximum porosity at 19.8% while the 3D extruded layer ensures the minimum porosity at 11.13%, strengthening the laminar grading effect to improve the EMW impedance matching. The Naval Research Laboratory experiments corroborate that double-layer structures improve the EMW-reflecting capacity compared to their single-absorption-layer counterparts and that the double-layer element containing the best wrapping effect absorbent yields the best reflection loss value, with a minimum of −14.7 dB and a 9.72 GHz effective bandwidth. The EMW-reflecting mechanism for the novel graded double-layer structure containing the graded nano-sized absorbent is then summarized. Theoretical calculations using the transform line theory suggest that a 15 mm absorbing layer and a 15 mm impedance matching layer is specified as the most optimized configuration, with −10.47 dB in average reflection, −15.18 dB in maximum RL, and 9.56 GHz in effective bandwidth. [ABSTRACT FROM AUTHOR]

Electromagnetic wave (EMW) pollution impairs the performance of equipment, facilities, information security, and human health. Ordinary, plain cementitious composite has limited EMW-reflecting capacity. To correct this, a macrostructure EMW absorbing element has been developed to reduce EMW pollution. As conventional casting of macrostructures is not cost-effective and lacks quality because of the demand for special formwork, 3D printing technology offers greater design flexibility, higher efficiency, and improved mechanical properties. Moreover, the surface texture of 3D-printed material exhibits natural corrugation to enhance EMW reflection further. In this study, novel wave-shaped EMW absorbing elements were fabricated using 3D cementitious printing technology. The EMW absorbing performance was analyzed by the naval research laboratory (NRL) system in the range of 1 GHz–18 GHz. Significant improvement of reflectivity was observed, especially in the low-frequency range. The optimum configuration was identified through effectiveness evaluation to be a K 3 sample with 45 mm of heave height and 2/3 tan(θ), exhibiting a minimum reflectivity −43.7 dB, mean reflectivity −25 dB, and an absorbing bandwidth of 18 GHz. The experimental reflectivity was also simulated by the finite element method, which agrees with the experimental results. The synthetic vector electromagnetic field distribution was also studied to explore space impedance characteristics. Moreover, the finite element method attempted to correct drawbacks in experiments, including multiple direction reflection measurement and wave-number interruption. Based on simulation calibration, the influence of wave-shaped parameters (heave height and tangent value) upon EMW absorbing capacity was induced accurately. [ABSTRACT FROM AUTHOR]

• Kaempferol maintains cell viability and membrane integrity in RGC cells injured by high glucose • Kaempferol reduces apoptosis and caspase-3 activity in RGC cells exposed to high glucose • Kaempferol inhibits ROS in RGC exposed to high glucose • Kaempferol protected RGC cells by modulating ERK activation and VASH1 expression Kaempferol is a medicinal flavonol derived from the roots of Kaempferia galanga L. Kaempferol can affect cell survival, apoptosis, and anti-oxidation, though its role and underlying mechanism in retinal ganglion cells with high-glucose injury remains unclear. In this study, we explored kaempferol's role in high-glucose injury in cells from the retinal ganglion cell (RGC) line. RGC cells were isolated and then cultured in high glucose (55 mmol/L) for 0 h, 12 h, 24 h, 48 h, or 72 h, and results showed decreased cell viability at 48 h and 72 h. We treated RGC cells with different concentrations of kaempferol (0 μmol/L, 20 μmol/L, 40 μmol/L, 60 μmol/L, 80 μmol/L, or 100 μmol/L) and high-glucose (55 mmol/L) for 48 h. The data indicated inhibited lactate dehydrogenase leakage, apoptosis, caspase-3 activity, and reactive oxygen species (ROS) levels. Moreover, whereas cell viability increased in RGC cells that were incubated with kaempferol (60 μmol/L, 80 μmol/L, or 100 μmol/L) and glucose (55 mmol/L), compared with glucose alone. Kaempferol (60 μmol/L) elevated ERK phosphorylation and vasohibin-1 (VASH1) expression, and inhibition of ERK phosphorylation reversed the effect of kaempferol (60 μmol/L) on VASH1 expression in RGC cells with high-glucose injury. Additionally, interference of VASH1 by VASH1 siRNA markedly reversed the effects of kaempferol (60 μmol/L) on cell viability, caspase-3 activity, and ROS levels in RGC cells with high glucose injury. Taken together, the results suggest that kaempferol protected retinal ganglion cells from high-glucose-induced injury via ERK and VASH1 signaling. [ABSTRACT FROM AUTHOR]

In the manufacturing process of 3D Concrete Printing (3DCP), defects and anomalies have a significant impact on both the success rate and the quality of the final products, underscoring the need for real-time monitoring. Currently, monitoring is primarily based on manual observation and existing automated methods are limited in real-time performance and accuracy. This study introduced a real-time and highly accurate defect detection and measurement system for using deep learning (DL) and computer vision (CV) techniques. A range of improvement methods were applied in YOLOv7, showing better capacities of accuracy and speed for detecting defects in 3DCP than current cutting-edge detectors such as YOLOv8. Notably, the virtual high-fidelity data were produced by DL based data augmentation strategy and their effects were assessed. Replacing real data as the training dataset, the generated virtual data were used in the models to improve measurement accuracy. Applying the proposed method, the comprehensive insights into 3DCP defects were obtained. Consequently, the relationship formula between defect frequency and printer parameters was investigated by the proposed method, guiding operators in effectively controlling printer parameters and preventing breakpoint defects during the printing process. • An innovative model based on dual deep learning technologies. • A range of improved methods used in the detector. • High-precision detection and measurement of 3DCP anomalies. • The relationship formula between defect frequency and printer parameters. [ABSTRACT FROM AUTHOR]

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]

[Display omitted] • Steam curing parameters (temperature rise rate, sustained temperature time, and sustained temperature) have a great influence on compressive properties of 3D printed concrete. • Anisotropy, a crucial characteristic of 3D printed concrete can be significantly influenced by steam curing. • Machine learning technology shows accurate and reliable performance in predicting compressive strength considering anisotropy and steam curing condition. • Beetle antennae search automatically tunes the hyperparameters of machine learning models. The 3D concrete printing (3DCP) technique piques the curiosity of several researchers and enterprises. However, there are few systematic investigations into how curing conditions influence the mechanical performance of 3DCP. This study aims to investigate the effect of various steam curing conditions (temperature rise rate, retention capacity, and sustained temperature) on the performance properties of 3D printing concrete materials at various ages of curing. A thorough test comprises macroscopic and microscopic analysis was conducted. In addition, the best conditions for steam curing are established for compressive characteristics in different directions. Then the anisotropy of mechanical properties of printed materials are studied under various curing settings. This study has contributed to the theoretical research on the influence of steam curing conditions on printed components. In addition, the experimental results were used to create two machine learning (ML) models and the beetle antennae search (BAS) technique was utilised. According to test data, the model is carried out to achieve the mechanical performance prediction of steam curing concrete. To automatically find optimal hyperparameters of ML models, the BAS algorithm was proposed, providing a solid guarantee for the rapid construction of the model. [ABSTRACT FROM AUTHOR]

Small signal stability of permanent magnet synchronous generator (PMSG)-based wind turbines connected to the power grid should be studied properly in order to facilitate damping strategy design. In this paper, unified small-signal models for different types of PMSGs are developed to study their small-signal stability. The models are composed of mechanical systems, electrical systems and control systems. A two-mass shaft model for the mechanical system is provided to analyze the dynamic and steady-state behaviors of the wind turbine and generator rotor. Meanwhile, PMSG, converter system and transmission line are separately modeled to build unified small-signal models for three PMSG-based wind turbine generator systems (WTGS). Then, based on unified small-signal models, eigenvalue analysis is conducted to determine the relation between different oscillation modes and state variables through calculating participation factors. With modal analysis, the developed small signal models are able to find out all types of oscillation modes for PMSGs connected to the power grid, which are subsynchronous oscillation (SSO), subsynchronous control interaction (SSCI) and low-frequency oscillation, including frequency and damping of each oscillation mode. Different initial values of the small signal models can influence both frequencies and damping ratios of oscillation modes, which lay basis for further damping strategy study. [ABSTRACT FROM AUTHOR]

The performance of ground anchor often employed in retaining the stability of onshore structures depends largely on its interface shear behavior. Interface characterization using pullout tests on element specimens of ground anchor is a versatile approach for determining its interface shear behavior. This research combines laboratory experiments and data-driven modeling to investigate the effect of free/bond lengths as a critical configuration condition of element specimen on the interface characterization results of ground anchors. Machine Learning models such as back propagation neural network (BPNN), random forest (RF), and support vector regression (SVR) were employed. Moreover, the particle swarm optimization (PSO) algorithm was used to improve the process. The results indicate that variations in free/bond lengths have a negligible effect on the trends of interface bond curves when bond lengths reach 90–100 mm. Moreover, when the bond and free lengths are set to 80 mm and 20 mm, respectively, the configuration conditions of the element specimen have a limited effect on the average interface shear strength. The PSO-BPNN model provided the most accurate predictions, which closely followed the experimental results compared to RF and SVR models. Compared to the other models, it reached a greater correlation coefficient (0.9975) and a lower root-mean-square error (14.89 kPa). Moreover, Partial dependence plot (PDP) is introduced to visualize the established machine learning model. • Study evaluates ground anchor shear behavior using lab tests and machine learning, focusing on free/bond length effects. • Free/bond length variations minimally affect ground anchor bond strength at 90–100 mm lengths. • PSO-BPNN model excels in anchorage bond strength prediction, achieving a 0.9975 correlation coefficient. • Ideal anchor test configuration: 80 mm bond and 20 mm free lengths for consistent shear strength. • PDP effectively illustrates key feature impacts on bond force in PSO-BPNN model predictions. [ABSTRACT FROM AUTHOR]

• The rubber-modified recycled aggregate concrete (RRAC) can be fabricated for low-carbon sustainability. The incorporation of RA and RPs can reduce the strength loss when concrete is exposed to high temperature. • Enhanced peak strain can be obtained through increasing the content of RA and RPs. The properties of RRAC are sensitive to the exposed temperature. • The hyperparameters of machine learning (ML) models were successfully tuned by beetle antennae search (BAS) algorithm. The established ML models possessed high accuracy and good generalisation performance. • The BPNN model possessed highest R value and lowest RMSE value compared to RF, LR, and MLR models, thus it had best prediction performance on the database in this study. The recycled aggregate (RA) and waste rubber particles (RPs) can be combined to prepare rubber-modified recycled aggregate concrete (RRAC) effectively contributing to low-carbon sustainability. However, the mechanical characteristics of RRAC must be investigated before the practical application. To this end, this study focused on the uniaxial compressive strength (UCS) and corresponding peak strain of RRAC with versatile design mixtures (i.e. varying contents of RA and RPs) after exposure to different temperatures ranging from 25 °C (room temperature) to 600 °C. The test results exhibited the negative relationship between UCS and RA replacement ratio, RPs content, and temperature. However, RPs positively affected both the loss of UCS and peak strain when RRAC was exposed to high temperatures. Besides, four machine learning (ML) models were developed based on a relatively comprehensive dataset including 120 groups of experimental results. The beetle antennae search (BAS) algorithm was applied to tune the hyperparameter of ML models. The high correlation coefficients (0.9721 for UCS and 0.9441 for peak strain) were determined in modelling using back propagation neural network (BPNN), presenting its accuracy and reliability. Furthermore, BPNN possessed optimal prediction performance since the lower root mean square error (RMSE) and higher correlation coefficient were obtained compared to the other three ML models (random forest, logistic regression, and multiple linear regression). [ABSTRACT FROM AUTHOR]

Sensing technologies demonstrate promising potential in providing the construction industry with a safe, productive, and high-quality process. The majority of sensing technologies in the construction research area have been focused on construction automation research in prefabrication, on-site operation, and logistics. However, most of these technologies are either not implemented in real construction projects or are at the very early stages in practice. The corresponding applications are far behind, even in extensively researched aspects such as Radio Frequency Identification, ultra-wideband technology, and Fiber Optic Sensing technology. This review systematically investigates the current status of sensing technologies in construction from 187 articles and explores the reasons responsible for their slow adoption from 69 articles. First, this paper identifies common sensing technologies and investigates their implementation extent. Second, contributions and limitations of sensing technologies are elaborated to understand the current status. Third, key factors influencing the adoption of sensing technologies are extracted from construction stakeholders' experience. Demand towards sensing technologies, benefits and suitability of them, and barriers to their adoption are reviewed. Lastly, the governance framework is determined as the research tendency facilitating sensing technologies adoption. This paper provides a theoretical basis for the governance framework development. It will promote the sensing technologies adoption and improve construction performance including safety, productivity, and quality. [ABSTRACT FROM AUTHOR]

In order to tackle the environmental problems induced by Portland cement production and industrial solid wastes landfilling, this study aims to develop novel ternary cementless fly ash-based geopolymer by recycling red mud and blast furnace slag industrial solid wastes. The fresh-state properties, mechanical strength, water permeability, phase assemblage and microstructure were systematically investigated to evaluate the performance variation and reveal the hydration mechanism for geopolymers with different mixing proportions. The results showed that a higher slag content or a lower red mud content could result in the higher fluidity and shorter setting time for fresh mixture. The existence of slag promoted the transformation of N-A-S-H to C-A-S-H gel, which contributed to higher compressive strength and better resistance to water penetration. However, an excessive incorporation of 30% red mud may impede the generation of N-A-S-H gel and form more flocculent-like loose hydrates, thus to mildly degrade the mechanical strength and anti-permeability. The synergetic utilization of red much and blast furnace slag in fly ash-based geopolymer led to much less CO 2 emission compared with the condition that red much or slag was singly added, which demonstrated prominent environmental advantages for such kind of ternary cementless geopolymer with equivalent mechanical strength. [Display omitted] • A series of novel cementless geopolymers with ternary solid wastes were designed with low CO 2 emission. • Synergetic utilization of red mud and slag endowed fly ash-based geopolymer with adaptive fresh properties. • The influential mechanisms of red mud and slag on strength and permeability of geopolymer were clarified. • The hydration products and microstructure of geopolymer with red mud and slag were revealed. [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]

• Compressive strength varies with AT levels and specimen orientation, highlighting the complex factors influencing concrete strength. • Highest strength of 105 MPa is found in 75 % AT mold-cast due to improved microstructure from AT-cement reactions. • Flexural strength shows variations across orientations and AT concentrations, improving up to 75% AT due to matrix integration. • Porosity changes with AT levels; more AT increases water absorption and pore formation due to higher silicon dioxide content. • GHG emissions drop by 8.63% with 100% AT; 75% AT best balances sustainability with mechanical strength in 3DPC. 3D printed concrete (3DPC) is an innovative solution offering faster construction, reduced waste, and greater design flexibility. Antimony tailings (AT) enhance the material's durability and strength while promoting sustainability by reducing waste. This provides a cost-effective and eco-friendly solution for construction. Based on it, this research tries to verify the viability of a 3D printing concrete with up to 100 % AT by assessing its fluidity, extrudability, buildability, and strength. This study used five different replacement percentages (0 %, 25 %, 50 %, 75 % and 100 %) of AT to partially replace the silica sand in the mix. Additionally, 1 % of the polyvinyl alcohol (PVA) fibers were used to improve the flexural capacity of the mixes because of the non-availability of the reinforcement in the 3DPC. Results showed that addition produced the highest compressive and flexural strength at 75 %AT. There was a smaller reduction in the compressive and flexural strength at 75 %AT anisotropically. The highest porosity was observed in the 100 %AT mix due to higher water absorption than control. This shows that the mix with 75 %AT can not only meet the printability requirements but can provide better strength which is beneficial for the practical application of 3D concrete printing. [ABSTRACT FROM AUTHOR]

This paper examines the influence of novel sugar beetroot-based micro sheets (SMSs) on the hydration of cement. The SMS material was added to cement pastes in different concentrations and the hydration kinetics of the cementitious composites were studied via cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The effect of SMS on the hydration development of cement, change in the pore size distribution and microstructural evolution were also quantified. The CV and EIS results revealed that the synergetic effect of the reactive SMS surface functional groups and tricalcium silicate (C 3 S) increased the ionic strength of the pore solution, ion diffusion rate and charge transport properties within the cementitious pastes. The CV and EIS measurements correlated well with the two main indicators of the cement hydration rate: the degree of hydration (DOH) and the calcium hydroxide (Ca(OH) 2) content. The delineated hydration kinetics suggested that the SMS sheets accelerate the dissolution of C 3 S and increase the hydration depth by channelling water from the pore solution to the unhydrated cement core thereby amplifying the growth of the hydration phases. As a result, the mechanical properties of the SMS doped cementitious composites were improved. The proposed SMS sheets are a potential sustainable and renewable biomaterial for improving the performance and reducing the carbon footprint of cementitious materials. [ABSTRACT FROM AUTHOR]

Highlights • The compressive strength of lightweight self-compacting concrete was modelled intelligently. • Beetle antennae search algorithm was firstly used to tune hyper-parameters of random forest. • The importance of different input variables was measured. Abstract Self-compacting concrete (SCC) can achieve compaction into every part of the formwork through its own weight without any segregation of the coarse aggregate. Lightweight concrete (LWC) can reduce the dead load of the structure by incorporating the lightweight aggregate (LWA). In recent years, more and more studies have focused on combining the advantages of SCC and LWC to produce lightweight self-compacting concrete (LWSCC). As one of the most important mechanical properties, uniaxial compressive strength (UCS) values need to be tested before field application of this new material. However, conducting UCS tests with multiple influencing variables is time-consuming and costly. To address this issue, this paper proposed, for the first time, a beetle antennae search (BAS) algorithm based random forest (RF) model to accurately and effectively predict the UCS of LWSCC. This model was developed and verified using data from LWSCC laboratory formulation. Results show that BAS was efficient in searching the optimum hyper-parameters of RF. The proposed BAS-RF model achieved high predictive accuracy indicated by a high correlation coefficient (0.97). In addition, by measuring the variable importance, we conclude that temperature was the most sensitive to UCS development, followed by scoria content and water-to-binder (w/b) ratio, while UCS was less sensitive to fiber content. This pioneering work provides a simple and convenient method for evaluating UCS of LWSCC at varying temperatures. [ABSTRACT FROM AUTHOR]

Abstract The coalcrete, a new supporting material produced by jet grouting (JG) technique was firstly studied for improving soft coal mass to support roadways in Guobei coal mine, China. Young's modulus is an essential indicator to evaluate the deformation-resisting ability of coalcretes. In this study, for determining Young's modulus of coalcretes efficiently, an intelligent technique was proposed using the support vector machine (SVM) and beetle antennae search (BAS). The hyper-parameters of SVM were firstly tuned by BAS, and then the SVM-BAS model with optimum hyper-parameters was employed to model the non-linear relationship between the inputs (coal content, water content, cement content, and curing time) and output (Young's modulus). By combining these variables, 360 coalcrete samples in total were prepared and tested for establishing the dataset. The results show that BAS is more reliable and efficient than the trial–and–error tuning method. Moreover, by comparison with other baseline models such as back-propagation neural network (BPNN), logistic regression (LR) and multiple linear regression (MLR), the optimized SVM-BAS model is more reliable, accurate and less time consuming for predicting Young's modulus of coalcretes. Besides, by conducting sensitivity analysis (SA), the importance of different input variables was determined. This pioneering work provides guidelines for predicting Young's modulus of coalcretes and designing proper JG parameters in engineering applications. Highlights • The jet grouting technique was firstly utilized in underground coal mine for generating coalcrete to reinforce the roadway stability • A total of 360 specimens were tested to determine the deformation-resisting ability of coalcrete. • A support vector machine model was proposed for predicting Young's modulus of coalcrete. • The hyperparameters of support vector machine were tuned by beetle antennae search algorithm. [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]

• The MD models of the interface between waste-oil recycled asphalt and aggregate were characterized and established. • The evolutionary process of dynamic water intrusion into recycled asphalt molecular was revealed. • The deterioration mechanism of recycled asphalt-aggregate interface adhesion was demonstrated. The integrity of the asphalt-aggregate interface is challenged by the dynamic water pressure under traffic loads, especially for recycled asphalt mixtures that represent lower moisture damage resistance by comparing with virgin asphalt mixtures. The effect of dynamic water pressure on the microscale interfacial adhesion properties between the waste-oil recycled asphalt and aggregate was comprehensively investigated based on the molecular dynamic simulation. The molecular models of recycled asphalt and aggregate were calibrated based on the chemical and physical analysis in experiments. The interfacial contact models between recycled asphalt with different regenerants (waste cooking oil-WCO, waste vegetable oil-WVO, and waste engine oil-WEO) and basalt aggregate were established, which also incorporated the thermodynamic process of water intrusion into the interface. The interface behaviors were studied by analyzing the cohesion energy of asphalt, the adhesion energy of interface, and the distribution of asphalt and water concentration on the aggregate surface. The results demonstrated that the dynamic water pressure can accelerate the water to penetrate the asphalt film. The recycled asphalt was pushed away from the basalt aggregate surface after the water film was formed at the interface, where the four components of asphalt leave the interface at different rates. Compared with the other two kinds of waste-oil recycled asphalt and conventional recycled asphalt, the WEO recycled asphalt-aggregate interface represented the optimum moisture damage resistance. The decrease of interface adhesion energy is about 55.7 % subjected to the coupling effects of the high-temperature and dynamic water pressure at 0.5 MPa. [ABSTRACT FROM AUTHOR]

• Backbone neighborhood distribution points are reduced to facilitate classification. • Dual-scale backbone features are combined for accurate width measurement direction. • A detailed visual measurement process of crack width is proposed. • A visual measurement method of crack width that is closer to reality is used to obtain more accurate results. State-of-the-art machine-vision systems have limitations associated with crack width measurements. The sample points used to describe the crack width are often subjectively defined by experimenters, which obscures the crack width ground truth. Consequently, in most related studies, the uncontrollable system errors of vision modules result in unsatisfactory measurement accuracy. In this study, the cracks of a reservoir dam are taken as objects, and a new crack backbone refinement algorithm and width-measurement scheme are proposed. The algorithm simplifies the redundant data in the crack image and improves the efficiency of crack-shape estimation. Further, an effective definition of crack width is proposed that combines the macroscale and microscale characteristics of the backbone to obtain accurate and objective sample points for width description. Compared with classic methods, the average simplification rate of the crack backbone and the average error rate of direction determination are all improved. The results of a series of experiments validate the efficacy of the proposed method by showing that it can improve detection automation and has potential engineering application. [ABSTRACT FROM AUTHOR]

• The cement content and curing time positively affect the mechanical properties of GRFP tendon reinforced cemented soil comprising unconfined compressive strength (UCS) and ultimate pullout strengths (T p), whereas the water content generally has a negative effect. • The 10-fold cross-validation and beetle antennae search (BAS) effectively tune the hyperparameters of the support vector regression (SVR) models for UCS and T p. • The outstanding performance of the BAS-SVR model is shown in high correlation coefficients (UCS: 0.988, T p : 0.972) and low RMSE values (UCS: 313 kPa, T p : 167 kPa). • The multi-objective optimisation design solusions for UCS-cost and T p -cost are both successfully obtained through generating Pareto fronts based on MOBAS-SVR. • Sensitivity analysis determines the most significant varible among all the input features is cement content. Rebar reinforced cemented soil is employed widely to solve the weak foundation problem led by sludge particularly. Nowadays, the glass fiber-reinforced polymer (GFRP) becomes a new tendon material instead of steel to avoid the performance degradation resulting from steel corrosion. The interface bond strength of GFRP tendon-reinforced cemented soils (GTRCS) displays its excellent mechanical capacity. Nevertheless, its application is obstructed by the deficient studies between the bond strength and influence factors. Therefore, this study investigates the effects of varying water contents (C w : 50%-90%), cement proportions (C c : 6%-30%), and curing periods (T c : 28 days, 90 days) on both pullout strength (T p) and unconfined compression strength (UCS) of GTRCS. The results showed that the pullout strength and compressive strength were positively related to T c and C c and negatively related to C w. Besides, these experimental results were also utilised to develop support vector regression (SVR) models. The beetle antennae search (BAS) algorithm was used to adjust the SVR's hyperparameters. The high correlation coefficients (0.988 for UCS and 0.972 for T p) proved the reliability of the established BAS-SVR models. In addition, the multi-objective beetle antennae search algorithm (MOBAS-SVR) was developed for bi-objective optimisation designs (UCS-cost and T p -cost). Finally, sensitivity analysis was conducted to range the significance of variables for T p and UCS. [ABSTRACT FROM AUTHOR]

Recycled aggregate concrete (RAC) made from construction and demolition wastes has several environmental benefits. Fire is one of the most common disasters in buildings, and RAC is a brittle construction material; therefore, the bearing capacity of RAC structures under high temperatures should be considered. According to previous studies, crumb rubber made of waste tires can further reduce damages to RAC under high temperatures. Meanwhile, fracture behaviors are one of the key characteristics of concrete materials that need to be considered, but few studies have focused on their behavior when subjected to elevated temperatures. Rubber-modified RAC (RRAC) notched beam specimens with three recycled aggregate substitutions (0%, 50%, and 100%), and four rubber contents (0%, 2%, 4%, and 6%), exposed to high temperatures (200 °C, 400 °C, and 600 °C), were tested using the three-point bending test. The fracture behaviors of the RRAC, including the crack mouth opening displacement, fracture energy, and fracture toughness were analyzed. The results show that the effect of rubber particles on the unstable fracture toughness is greater than that on the initial cracking toughness of RAC after exposure to high temperatures. However, the enhanced effect of rubber on the fracture resistance decreases after subjecting it to a high-temperature treatment owing to the softening and eventual decomposition of rubber at high temperatures. Consequently, in order to avoid the drawbacks introduced by rubber, a rubber content of more than 4% is not recommended considering the mechanical and fracture performance of RRAC. • The fracture behaviors of rubber-modified recycled concrete (RRAC) were studied. • Thermal damage increases the fracture energy and fracture toughness of RRAC. • Double-K criterion was employed to analyzed the fracture performance of RRAC. • The mesostructure of RRAC after high-temperature treatment was explored. • The optimal ratio of rubber content was obtained. [ABSTRACT FROM AUTHOR]

• A novel fibre-jacket-reinforced mould is developed for 3D printing application. • Effect of hybrid fibre on tensile and flexural properties is investigated. • A properly designed printing path can improve the strength of 3D-printed mortar. • A model is developed to predict the bending capacities of the reinforced specimens. Recently, 3D printing technology has been rapidly developing in the construction sector around the world. However, the insufficient tensile and flexural strengths of the printed material is a crucial problem due to the difficulty of applying steel reinforcement. As a printable material, fibres can be added to the mixture to improve the post-cracking behaviour and toughness of reinforced mortar. Therefore, the present study proposes a 3D-printed fibre-reinforced mortar frame with basalt and carbon fibres to develop a fibre-jacket-reinforced specimen. Specimens with different numbers of reinforcing layers (two, four and six layers) and four different printing paths were fabricated to investigate the strengthening effect on both flexural and tensile capacities. Results from both tests show that a properly designed printing path can significantly improve the tensile and flexural strengths of 3D-printed mortar due to the fibre alignment effect. The strength of fibre-jacket-reinforced specimens is enhanced to a different extent compared with the strength of cast specimens without fibre (with maximum flexural strengths of up to 167% and splitting tensile strengths of up to 128% compared with the respective strengths of the control groups). Meanwhile, both strengths of the fibre-jacket-reinforced specimens with six reinforcement layers almost reach the same strengths of a fully printed fibre-reinforced specimen, but the amount of fibre is reduced by half. In addition, an electromechanical impedance (EMI) technique is applied to monitor the damage during the loading process and an analytical model is developed to predict the enhanced bending capacities of the proposed fibre-jacket-reinforced specimens. [ABSTRACT FROM AUTHOR]

The integration of generative design (GD) and building information modelling (BIM), as a new technology consolidation, can facilitate the constructability of GD's automatic design solutions, while improving BIM's capability in the early design phase. Thus, there has been an increasing interest to study GD-BIM, with current focuses mainly on exploring applications and investigating tools. However, there are a lack of studies regarding methodological relationships and skill requirement based on different development objectives or GD properties; thus, the threshold of developing GD-BIM still seems high. This study conducts a critical review of current approaches for developing GD in BIM, and analyses methodological relationships, skill requirements, and improvement of GD-BIM development. Accordingly, novel perspectives of objective-oriented, GD component-based, and skill-driven GD-BIM development as well as reference guides are proposed. Finally, future research directions, challenges, and potential solutions are discussed. This research aims to guide designers in the building industry to properly determine approaches for developing GD-BIM and inspire researchers' future studies. [ABSTRACT FROM AUTHOR]

• A multi-output model was firstly applied for predicting pervious concrete properties. • A bio-inspired algorithm was modified to tune hyperparameters of the multi-output model. • A number of pervious concrete samples were prepared in laboratory to test the model. Pervious concrete can purify water, mitigate storm water runoff and reduce the urban heat island effect due to its larger porosity. However, its highly porous inner structure causes a lower compressive strength in comparison with normal concrete. Therefore it is vital to accurately predict the two basic parameters: permeability coefficient (PC) and uniaxial compressive strength (UCS) before field application to reduce time and cost of a construction project. As traditional mathematical models cannot model the highly nonlinear relationships between PC (or UCS) and its constituents, this study addresses this problem by applying a hybrid artificial intelligence model: multi-output least squares support vector regression (MOLSSVR). This model can also improve the prediction accuracy by utilizing the relationship between the two outputs: PC and UCS. In addition, the hyperparameters of MOLSSVR are tuned by a beetle-antennae search (BAS) algorithm which is modified by incorporating self-adaptive inertia weight and Levy flight. To train the proposed model, a large number of pervious concrete samples with different mixture proportions were prepared in laboratory. The results show that the searching efficiency of the modified BAS is significantly higher than that of BAS. The proposed hybrid model achieves better prediction accuracy than other models in the literature. This method can be used to address other multi-output problems in civil engineering. [ABSTRACT FROM AUTHOR]