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The seismic performance of rubber concrete-layered periodic foundations are significantly influenced by their design, in which the band gaps play a paramount role. Aiming at providing better designs for these foundations, this study first proposes and validates the analytical formulas to approximate the bounds of the first few band gaps. In addition, the mapping relations linking the frequencies of different band gaps are presented. Furthermore, an optimal design method for these foundations is developed, which is validated through an engineering example. It is demonstrated that ensuring the superstructure's resonance zones are completely covered by the corresponding periodic foundation's band gaps can achieve satisfactory vibration attenuation effects, which is a good strategy for the design of rubber concrete layered periodic foundations. [ABSTRACT FROM AUTHOR]

Time history response derivatives with respect to the design variables are frequently used in optimization design, damage detection, structural control, etc. This paper proposes a substructuring method for efficient calculation of higher order time history response derivatives of large-scale structures. First, the global structure is disassembled into several small substructures and the substructural displacement is projected onto the range space of a few substructural master eigenvectors. Afterwards, the derivative of substructural master eigenvectors of a few substructures containing the design variables are assembled to form the reduced first, second, and higher order sensitivity equations with a size of the number of master eigenvectors. The equivalent eigenvector which relates the slave and master eigenvectors is derived to compensate for the inertial effect of discarded slave eigenvectors. Finally, the first, second, and higher order time history response derivatives of global large-scale structure are efficiently solved from the reduced sensitivity equations by using Newmark- β method. A numerical one-bay plane frame and a numerical highway bridge are applied to verify the accuracy and efficiency of proposed substructuring method. [ABSTRACT FROM AUTHOR]

For the highly interacting machining features, Layered Projection Decomposition Method presents inferior recognition efficiency and accuracy, due to its high-cost 3D projection and failures in determining projection faces for internal occluded faces. To address these issues, we propose a potential hybrid recognition framework. We first introduce a straightforward adjacent projection wire (APW) over UV wires, automatically restoring the full projection wires from highly interacting features. Building on APWs, an efficient hybrid boundary representation and its corresponding unambiguous primitive definitions are proposed by combining with graph-based boundary representations. Subsequently, we design an efficient primitive decomposition method by introducing primitive boundary matching to decide the initial projection faces, and introducing iterative projection boundary expansion to complete the full primitives from occluded faces. Moreover, we establish an efficient Graph Neural Network to learn the distinguishable distributions over the decomposed primitives. Specifically, an Adjacency Attention Unit is proposed to automatically perceive the influence weight of adjacent nodes, leading to more discriminative self-adaptive shape embedding for efficient primitive recognition. Finally, we summarize convenient reconstruction rules to correct the wrong predictions of feature faces with indistinguishable adjacent relationships. To evaluate the effectiveness of the proposed recognition framework, CAD models of complex aircraft structural parts are collected to present a challenging machining feature dataset. Extensive numerical experiments demonstrate that the proposed hybrid recognition framework enables significant improvements over the state-of-the-art machining feature recognition techniques. [ABSTRACT FROM AUTHOR]

Deep reinforcement learning (DRL) exploits the powerful representational capabilities of deep neural networks (DNNs) and has achieved significant success. However, compared to DNNs, spiking neural networks (SNNs), which operate on binary signals, more closely resemble the biological characteristics of efficient learning observed in the brain. In SNNs, spiking neurons exhibit complex dynamic characteristics and learn based on principles of biological plasticity. Inspired by the brain's efficient computational mechanisms, information encoding plays a critical role in these networks. We propose an intrinsic plasticity coding improved spiking actor network (IP-SAN) for RL to achieve effective decision-making. The IP-SAN integrates adaptive population coding at the network level with dynamic spiking neuron coding at the neuron level, improving spatiotemporal state representation and promoting more accurate biological simulation. Experimental results show that our IP-SAN outperforms several state-of-the-art methods in five continuous control tasks. [ABSTRACT FROM AUTHOR]

Dimensional analysis is applied to study the pounding response of two inelastic multidegree of freedom (MDOF) structures under simplified earthquake excitation. The forces and deformations of the collision processes are simulated by adopting the improved Kelvin pounding model. The inelastic characteristics of MDOF structures are described by the bilinear interstory resistance model, and the representations of dimensionless impact force and the dimensionless motion equation in the pounding process are derived. On the basis of the above-mentioned theoretical deduction, the superiority of the improved Kelvin model is verified by comparing the impact response of the improved Kelvin model and the Kelvin model. Finally, the validity of the proposed theoretical method is further proved by the comparison between results from the shaking table tests of adjacent four-story and three-story steel frame structures and the corresponding numerical results obtained by the MATLAB program. [ABSTRACT FROM AUTHOR]

Neuropathic pain is a severe problem that is difficult to treat clinically. Reducing abnormal remodeling of dendritic spines/synapses and increasing the anti-inflammatory effects in the spinal cord dorsal horn are potential methods to treat this disease. Previous studies have reported that electroacupuncture (EA) could increase the pain threshold after peripheral nerve injury. However, the underlying mechanism is unclear. P2X7 receptors (P2X7R) mediate the activation of microglia and participate in the occurrence and development of neuropathic pain. We hypothesized that the effects of EA on relieving pain may be related to the downregulation of the P2X7R. Spinal nerve ligation (SNL) rats were used as a model in this experiment, and 2'(3')-O-(4-benzoyl)benzoyl ATP (BzATP) was used as a P2X7R agonist. We found that EA treatment decreased dendritic spine density, inhibited synaptic reconstruction and reduced inflammatory response, which is consistent with the decrease in P2X7R expression as well as the improved neurobehavioral performance. In contrast to the beneficial effects of EA, BzATP enhanced abnormal remodeling of dendritic spines/synapses and inflammation. Furthermore, the EA-mediated positive effects were reversed by BzATP, which is consistent with the increased P2X7R expression. These findings indicated that EA improves neuropathic pain by reducing abnormal dendritic spine/synaptic reconstruction and inflammation via suppressing P2X7R expression. [ABSTRACT FROM AUTHOR]

Neuropathic pain is a severe problem that is difficult to treat clinically. Reducing abnormal remodeling of dendritic spines/synapses and increasing the anti-inflammatory effects in the spinal cord dorsal horn are potential methods to treat this disease. Previous studies have reported that electroacupuncture (EA) could increase the pain threshold after peripheral nerve injury. However, the underlying mechanism is unclear. P2X7 receptors (P2X7R) mediate the activation of microglia and participate in the occurrence and development of neuropathic pain. We hypothesized that the effects of EA on relieving pain may be related to the downregulation of the P2X7R. Spinal nerve ligation (SNL) rats were used as a model in this experiment, and 2'(3')-O-(4-benzoyl)benzoyl ATP (BzATP) was used as a P2X7R agonist. We found that EA treatment decreased dendritic spine density, inhibited synaptic reconstruction and reduced inflammatory response, which is consistent with the decrease in P2X7R expression as well as the improved neurobehavioral performance. In contrast to the beneficial effects of EA, BzATP enhanced abnormal remodeling of dendritic spines/synapses and inflammation. Furthermore, the EA-mediated positive effects were reversed by BzATP, which is consistent with the increased P2X7R expression. These findings indicated that EA improves neuropathic pain by reducing abnormal dendritic spine/synaptic reconstruction and inflammation via suppressing P2X7R expression. [ABSTRACT FROM AUTHOR]

In this paper, a symmetrical twin-tower structure with chassis connected with passive dampers is coupled as 2-DOF (degree of freedom) model. Using the stationary white noise as seismic excitation, the frequency–response function and the vibration energy expression of the symmetrical twin-tower structure are established based on the simplified 2-DOF model. Furthermore, based on the principle of minimum energy, the analytical expressions of the optimization parameters of two kinds of passive dampers are deduced, and the effectiveness of the dampers with optimized coefficients on structural control is verified by numerical examples of 2-DOF and MDOF (multi-degree-of-freedom) systems, respectively. Finally, the control effects of the two kinds of dampers under different control strategies on the responses of displacement of the top, base shear, structural vibration energy, and maximum inter-story drift of the symmetrical twin-tower structure are discussed through three-dimensional finite element numerical examples. It is verified that the analytical expressions of optimum parameters of the two kinds of dampers proposed based on the 2-DOF model are also beneficial to reduce the responses of the MDOF systems and actual engineering. [ABSTRACT FROM AUTHOR]

• •A novel isolation bearing with variable stiffness is proposed. • •Cyclic behavior of proposed bearing is investigated based on quasi-static test. • •A theoretical model is derived which can estimate cyclic behavior of bearing. • •Vibration mitigation of bearing are validated under multi-source traffic vibrations. To reduce the effect of train-induced vibration on the structure and improve the serviceability of structures, this study proposes a novel isolation bearing with a simple configuration and low cost, having a wide market prospect. Compared with bearing with constant stiffness, the novel bearing can achieve a broadband vibration isolation effect. Based on quasi-static tests, the behavior of the bearing is investigated, and the analytical hysteresis model of the bearing is derived and validated. Furthermore, comprehensive on-site assessments amidst multi-source traffic vibration scenarios are conducted to validate the vibration mitigation of the isolation bearing. The findings reveal that while at varying preloads and amplitudes, the hysteretic properties remain remarkably stable, except in the case of small amplitude cycles. The theoretical hysteresis model aligns closely with the test result, accurately capturing the cyclic behavior. The bearing significantly reduces the response of structures under multi-source transport vibrations. [ABSTRACT FROM AUTHOR]

The chitosan/gelatin hydrogel incorporated with biphasic calcium phosphate nanoparticles (BCP-NPs) as scaffold (CGB) for bone tissue engineering was reported in this article. Such nanocomposite hydrogels were fabricated by using cycled freeze-thawing method, of which physicochemical and biological properties were regulated by adjusting the weight ratio of chitosan/gelatin/BCP-NPs. The needle-like BCP-NPs were dispersed into composites uniformly, and physically cross-linked with chitosan and gelatin, which were identified via Scanning Electron Microscope (SEM) images and Fourier Transform Infrared Spectroscopy (FT-IR) analysis. The porosity, equilibrium swelling ratio, and compressive strength of CGB scaffolds were mainly influenced by the BCP-NPs concentration. In vitro degradation analysis in simulated body fluids (SBF) displayed that CGB scaffolds were degraded up to at least 30 wt% in one month. Also, CCK-8 analysis confirmed that the prepared scaffolds had a good cytocompatibility through in culturing with bone marrow mesenchymal stem cells (BMSCs). Finally, In vivo animal experiments revealed that new bone tissue was observed inside the scaffolds, and gradually increased with increasing months, when implanted CGB scaffolds into large necrotic lesions of rabbit femoral head. The above results suggested that prepared CGB nanocomposites had the potential to be applied in bone tissue engineering. [ABSTRACT FROM AUTHOR]

3D reconstruction of a large-scale electrical substation scene (ESS) is fundamental to navigation, information inquiry, and supervisory control of 3D scenes. However, automatic reconstruction of ESS from a raw LiDAR point cloud is challenging due to its incompleteness, noise and anisotropy in density. We propose an automatic and efficient approach to reconstruct ESSs, by mapping raw LiDAR data to our well-established electrical device database (EDD). We derive a flexible and hierarchical representation of the ESS automatically by exploring the internal topology of the corresponding LiDAR data, followed by extracting various devices from the ESS. For each device, a quality mesh model is retrieved in the EDD, based on the proposed object descriptor that can balance descriptiveness, robustness and efficiency. With the high-level representation of the ESS, we map all retrieved models into raw data to achieve a high-fidelity scene reconstruction. Extensive experiments on large and complex ESSs modeling demonstrate the efficiency and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Based on the 3-single-degree-of-freedom (SDOF) model of twin-tower structures linked by the sky-bridge and passive control devices, the frequency functions and the vibration energy expressions of the structures are derived by using the stationary white noise as the seismic excitation. The analytical formulas for determining the connecting optimum parameters of viscoelastic damper (VED) represented by the Kelvin model and the viscous fluid damper (VFD) represented by Maxwell model are proposed using the principle of minimizing the average vibration energy of either the single tower or the twin tower. Three pairs of representative numerical examples of twin-tower-connected structures are used to verify the correctness of the theoretical approach. The optimum parametric analysis demonstrates that the control performance is not sensitive to damper damping ratio of VED and relaxation time of VFD. The effectiveness of the proposed control strategies based on the 3-SDOF models is also proved to be applicable to multi-degree-of-freedom systems. The theoretical analysis and numerical results indicate that the seismic response and vibration energy of the twin-tower-connected structures are mitigated greatly under the two types of dampers. The presented control strategies of VED and VFD can help engineers in application of coupled structures. [ABSTRACT FROM AUTHOR]

• Electroacupuncture improves neuropathic pain. • Electroacupuncture promotes the change in microglial polarization from M1 phenotype to M2 phenotype in SNL rats. • PD-L1 knockdown activates the MAPK signaling pathway. • Electroacupuncture suppresses neuropathic pain by promoting PD-L1 expression. As a common clinical disease, neuropathic pain is difficult to be cured with drugs. The occurrence and progression of pain is closely related to the response of spinal microglia. As part of the regulation of microglial activity, PD-L1 plays a critical role. Loss of PD-L1 promoted the polarization of M1-like microglia. Increased expression of PD-L1 promoted M2-like polarization. Electroacupuncture has a significant analgesic effect in clinical practice, but its specific mechanism remains to be further explored. In this study, we verified the role of PD-L1 in EA analgesia and the underlying molecular mechanism through spinal nerve ligation (SNL) in rats and lipopolysaccharide (LPS)-treated BV2 microglial cells. For behavioral studies of rats, mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) were measured, and spinal cord neuros were examined under transmission electron microscopy to determine changes to their myelin structure. The expression levels of PD-L1 and M1/M2-specific markers in rat spinal cord and BV2 microglial cells were measured by enzyme-linked immunosorbent assay, flow cytometry, immunofluorescence staining and Western blot analysis. Our study showed that EA increased the pain threshold, reduced the destruction of myelin structure, promoted the expression of PD-L1 and PD-1, inhibited the MAPK signaling pathway, and promoted the conversion of microglial polarization from the M1 phenotype to the M2 phenotype in SNL rats. PD-L1 knockdown reversed these effects of EA. In addition, PD-L1 knockdown activated the MAPK signaling pathway, promoted microglial polarization to the M1 phenotype, decreased the expression of anti-inflammatory mediators and increased the expression of proinflammatory factors in LPS-stimulated BV2 microglial cells. Our results showed that EA may regulate the excitability of primary afferent neurons through PD-L1 and then inhibit the MAPK signaling pathway to promote the transformation of activated M1 microglia into M2 microglia, reduce inflammatory reactions, and finally achieve analgesic effects. A therapy targeting PD-L1 may be an effective strategy for treating neuropathic pain. [ABSTRACT FROM AUTHOR]

Automatic modeling of indoor scenes from raw point data has received considerable attention due to its wide applications in computer graphics and robotics. The raw point data, however, always suffer from incompleteness, noise and anisotropy in density, which make rapid reconstruction fairly challenging. To overcome these challenges, in this paper, we explore the repeatability and regularity of man-made structures, which is the crux of our automatic reconstruction of indoor scenes. As observed, repetitive structures oftentimes exhibit in indoor scenes, such as classrooms, meeting rooms, and auditoria. We detect repetitions hierarchically and extract each repetitive object separately in these scenes. The object is represented with a set of key points which are extracted by leveraging both the local and global information of the data. By retrieving the most similar models from the shape database, we align them with the input data to obtain a high-quality virtual representation of the scene, which is quite faithful to the original geometry. In contrast to previous methods, we discover the high-level structure of the scene and can obtain a complete reconstruction efficiently even in the presence of noise and incomplete scans. A variety of indoor scenes have been tested to verify the effectiveness and the robustness of our proposed method. [ABSTRACT FROM AUTHOR]

Air pollution poses significant health and economic challenges globally and specifically affecting China. Although air pollution has been associated with decreased productivity and biases in decision-making, its effect on the development of digital finance has received limited attention in the literature. By employing city-level data from China covering the period from 2013 to 2020, this research examines the impact of air pollution on digital finance. The results show that deteriorating air quality has a negligible impact on digitalization, whereas it has a negative impact on financial inclusion, measured by usage and coverage metrics. The negative impact on financial inclusion is more noticeable in economically weaker and less developed urban areas and low R&D than in developed areas and economically robust cities. The mechanism analysis shows that air pollution reduces human capital quality, resulting in a decline in financial inclusivity. These findings have significant policy implications, underscoring the necessity for approaches that simultaneously tackle air pollution and foster financial innovation. [ABSTRACT FROM AUTHOR]

Glass, with its unique amorphous properties, offers low thermal conductivity, high catalytic activity, insensitivity to interfacial lattice mismatch, and the absence of grain boundaries. Melt‐quenched organic–inorganic hybrid glass has recently gained significant attention as an emerging material because of its excellent processability and formability. Here, an SbCl3(C25H46ClN)x halide with a low melting point (90 °C) and significant formability is reported. Both the crystalline and glass states of SbCl3(C25H46ClN)x have double broadband emission, and the glass state exhibits negative thermal quenching, which is rare in metal halides. Interestingly, the luminescence properties of SbCl3(C25H46ClN)x glass with different x values differ. This feature is utilized to design multimodal anti‐counterfeiting and information encryption applications. Additionally, The inherent melt processing capability of SbCl3(C25H46ClN)x allows it to be shaped into various forms suitable for practical applications. SbCl3(C25H46ClN)x scintillator screens (diameter 2.2 cm) are successfully prepared by low‐temperature melting, achieving an X‐ray imaging resolution of 18 line pairs per millimeter (18 lp mm−1). This study demonstrates the potential of melt‐processed organic–inorganic hybrid glass SbCl3(C25H46ClN)x in anti‐counterfeiting, information encryption, and X‐ray detection. [ABSTRACT FROM AUTHOR]

Calcium–alumino–silicate–hydrate (CaO–Al2O3–SiO2–H2O, or C–A–S–H) gel, which is the binding phase of cement-based materials, greatly influences concrete mechanical properties and durability. However, the atomic-scale kinetics of the aluminosilicate network condensation remains puzzling. Here, based on reactive molecular dynamics simulations of C–A–S–H systems formation with varying Al/Ca molar ratios, we study the kinetic mechanism of the hydrated aluminosilicate gels upon precipitation. We show that the condensation activation energy decreases with the Al/Ca molar ratio, which suggests that the concentration of the Al polytopes has a great effect on controlling the kinetics of the gelation reaction. Significantly, we demonstrate that 5-fold Al atoms are mainly forming at high Al/Ca molar ratios since there are insufficient hydrogen cations or extra calcium cations to compensate the negatively charged Al polytopes at high Al/Ca molar ratios during accelerated aging. [ABSTRACT FROM AUTHOR]

Improvements in neuronal plasticity are considered to be conducive to recovery from neuropathic pain. Electroacupuncture (EA) is regarded as an effective rehabilitation method for neuropathic pain. However, the effects and potential mechanism associated with EA-induced repair of hyperesthesia are not fully understood. Evidence has suggested that the adenosine A2A receptor (A2AR) and the cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA) pathway play an important role in improving neuropathic pain. Here, we examined the function of EA in promoting neuronal plasticity in spinal nerve ligation (SNL) rats. The A2AR antagonist SCH58261, A2AR agonist 2-p-(2-carboxyethyl)phenethylamino-50-N-ethylcarboxamido adenosine HCl (CGS21680) and A2AR siRNA were used to confirm the relationship between A2AR and the cAMP/PKA pathway as well as the effects of A2AR on EA-induced improvements in neurobehavioral state and neuronal plasticity. Mechanical withdrawal threshold (MWT), thermal withdrawal latency (TWL), HE staining, Western blotting, RT-PCR, immunofluorescence, enzyme-linked immunosorbent assay, Nissl staining, silver staining, Golgi-Cox staining and transmission electron microscopy were used to evaluate the changes in neurobehavioral performance, protein expression, neuronal structure and dendrites/synapses. The results showed that EA and CGS21680 improved the behavioral performance, neuronal structure and dendritic/synaptic morphology of SNL rats, consistent with higher expression levels of A2AR, cAMP and PKA. In contrast to the positive effects of EA, SCH58261 inhibited dendritic growth and promoted dendritic spine/synaptic remodeling. In addition, the EA-induced improvement in neuronal plasticity was inhibited by SCH58261 and A2AR siRNA, consistent with lower expression levels of A2AR, cAMP and PKA, and worse behavioral performance. These results indicate that EA suppresses SNL-induced neuropathic pain by improving neuronal plasticity via upregulating the A2AR/cAMP/PKA signaling pathway. • Electroacupuncture improves neuropathic pain. • Neuropathic pain leads to changes in the plasticity of neurons. • Electroacupuncture inhibits neuropathic pain-induced changes in neuronal plasticity. • Electroacupuncture suppresses neuropathic pain by the A2AR/cAMP/PKA pathway. [ABSTRACT FROM AUTHOR]

• Shaking table test of a hybrid passive control system. • The effect of different forms of seismic isolation on the effect is studied. • The damper does not perform well under the excitation of pulsed seismic waves. • The hybrid passive control system has higher robustness and redundancy. In this paper, the effects of control of a hybrid passive control system with energy consumption between the isolated structure and the adjacent structure, which was proposed recently by other researchers, is studied by shaking table test. Compared with a single seismic isolation system, this hybrid control system combines seismic isolation technique with damper energy dissipation and has strong robustness with application to seismic waves in different frequency domains. By inputting seismic waves in different frequency domains through shaking table tests, the effects of the control systems with different vibration reduction and isolation schemes under different frequency domain ground motions are studied. Finally, the finite element numerical simulations are compared with the test results. Research results show that, compared with ordinary periodic seismic waves, the long-period seismic waves have more obvious effects on structural displacement and acceleration, the overturning effect of high-rise isolated structures and the possibility of displacement over-limit of isolation bearings. For isolated structures, the multiple isolation has the best effect of vibration control. After connecting adjacent structure with viscous dampers, the hybrid passive control system is established and the seismic isolation performance of the isolated structure is further strengthened. The hybrid passive control system studied in this paper can effectively solve the problems existing in high-rise isolated structures, such as structural overturning and bearing displacement overrun and so on, and has a better control effect on structural responses under different frequency domain seismic excitations. [ABSTRACT FROM AUTHOR]

Spherical harmonics are a favorable technique for 3D representation, employing a frequency‐based approach through the spherical harmonic transform (SHT). Typically, SHT is performed using equiangular sampling grids. However, these grids are non‐uniform on spherical surfaces and exhibit local anisotropy, a common limitation in existing spherical harmonic decomposition methods. This paper proposes a 3D representation method using Fibonacci Spherical Harmonics (FSH3D). We introduce a spherical Fibonacci grid (SFG), which is more uniform than equiangular grids for SHT in the frequency domain. Our method employs analytical weights for SHT on SFG, effectively assigning sampling errors to spherical harmonic degrees higher than the recovered band‐limited function. This provides a novel solution for spherical harmonic transformation on non‐equiangular grids. The key advantages of our FSH3D method include: 1) With the same number of sampling points, SFG captures more features without bias compared to equiangular grids; 2) The root mean square error of 32‐degree spherical harmonic coefficients is reduced by approximately 34.6% for SFG compared to equiangular grids; and 3) FSH3D offers more stable frequency domain representations, especially for rotating functions. FSH3D enhances the stability of frequency domain representations under rotational transformations. Its application in 3D shape reconstruction and 3D shape classification results in more accurate and robust representations. Our code is publicly available at https://github.com/Miraclelzk/Fibonacci-Spherical-Harmonics. [ABSTRACT FROM AUTHOR]

The vital importance of rapid and accurate detection of food borne pathogens has driven the development of biosensor to prevent food borne illness outbreaks. Electrochemical DNA biosensors offer such merits as rapid response, high sensitivity, low cost, and ease of use. This review covers the following three aspects: food borne pathogens and conventional detection methods, the design and fabrication of electrochemical DNA biosensors and several techniques for improving sensitivity of biosensors. We highlight the main bioreceptors and immobilizing methods on sensing interface, electrochemical techniques, electrochemical indicators, nanotechnology, and nucleic acid-based amplification. Finally, in view of the existing shortcomings of electrochemical DNA biosensors in the field of food borne pathogen detection, we also predict and prospect future research focuses from the following five aspects: specific bioreceptors (improving specificity), nanomaterials (enhancing sensitivity), microfluidic chip technology (realizing automate operation), paper-based biosensors (reducing detection cost), and smartphones or other mobile devices (simplifying signal reading devices). [ABSTRACT FROM AUTHOR]

Recycled aggregate derived from construction and demolition (C&D) waste offers new opportunities for the construction industry due to the shortage of natural aggregate. This study presents the feasibility of utilizing recycled fine aggregate (RFA) in ultra-high performance concrete (UHPC) to alleviate autogenous shrinkage, mitigate environmental effects, and further improve mechanical strengths. Three types of RFA with different particle sizes (0–0.6 mm, 0.6–1.18 mm, and 1.18–2.36 mm) are pre-saturated and then used as substitutes for quartz sand in UHPC. The influences of pre-saturated RFA on the workability, internal relative humidity, autogenous shrinkage, compressive strength, resistance to chloride ion penetration, and microstructure of UHPC are investigated. Experimental results showed that, compared to the plain UHPC, incorporation of 20 % RFA with particle size of 1.18–2.36 mm provides efficient internal curing, maintaining a higher internal relative humidity, and thus reducing autogenous shrinkage by 78.5 % at the age of 7 days. The compressive strengths of the UHPC containing 20 % RFA with particle size of 1.18–2.36 mm shows 7.1 % increase at the ages of 28 days. While it has a negligible effect on the fluidity and resistance to chloride penetration. The underlying mechanisms for the enhancement of properties involve the improved hydration degree of UHPC due to internal curing, which optimizes the structure of the interface transition zone and reduces the number of large pores. Furthermore, the sustainability analysis indicated that the use of RFA in UHPC exhibits 7.0 % lower carbon emissions and 7.8 % lower energy consumption, respectively. This study successfully proposes an effective approach for mitigating the autogenous shrinkage of UHPC without sacrificing strengths. • A method of preparing low shrinkage and high-strength ultra-high performance concrete using recycled fine aggregate is designed. • The water storage-release effects of recycled fine aggregates with different particle sizes are investigated, as well as the mechanisms of their influence on the macro- and micro-properties of UHPC. • The effect of recycled fine aggregates with different particle sizes on the microhardness of the interface transition zone at the UHPC is investigated. • The environmental impact of UHPC preparation using recycled fine aggregate is assessed. [ABSTRACT FROM AUTHOR]

• Electroacupuncture at special acupoints can improve the symptoms of neuropathic pain. • Electroacupuncture can have an effect on the ascending transmission of pain signals. • Electroacupuncture can inhibit excitatory postsynaptic potential(EPSP). To observe the impacts of electroacupuncture (EA) stimulation at "Zusanli and Kunlun Points" on spinal dorsal horn microglia activation in L5 spinal nerve ligation (SNL) rats and BNDF, P2 × 4 and GABAAγ2, and the changes in spinal dorsal horn synaptic plasticity in model rats. Adult male SD rats (180–220 g) were selected and randomly divided into 6 groups, including the sham group, the SNL group, the SNL + EA group, the SNL+5-BDBD group, the SNL + EA + 5-BDBD group and the SNL + FEA group. The changes in the Iba-1, BDNF, P2 × 4 and GABAAγ2 in the spinal cord of rats were observed by Western blotting, immunofluorescence, RT-PCR and other techniques; the long-term changes in the potential after the excitatory synapse of the spinal dorsal horn in rats were observed by in vivo electrophysiological technique. After 7 days of intervention, the fluorescence intensity (FI) of P2 × 4 and Iba-1 in the SNL + EA group was lower than that in the SNL group and higher than that in the sham group(P < 0.01), but the FI of GABA A γ2 was higher than that in the SNL group(P < 0.01); the expression of Iba-1, BDNF and P2 × 4 proteins in the SNL + EA group, the SNL+5-BDBD group and the SNL + EA + 5-BDBD group was significantly lower than that in the SNL + FEA group(P < 0.05), but the expression of GABAAγ2 protein was higher (P < 0.05); after treatment with EA, the expression levels of Iba-1 mRNA and P2 × 4 mRNA in the SNL + EA group were lower than those in the SNL group(P < 0.01), but the expression levels of GABAAγ2 mRNA were higher (P < 0.01). Meanwhile, long-term potentiation changes could not be induced in the SNL + EA group. The EA stimulation at "Zusanli" and "Kunlun" points can improve the pain threshold of rats with neuropathic pain (NP), inhibit the excitatory postsynaptic potential (EPSP), and weaken the excitatory transmission efficiency between synapses during NP. [ABSTRACT FROM AUTHOR]

AbstractWith the high-speed and high-frequency operation of CPU chips, as well as miniaturization and dense assembly of integrated circuits, the heat generated by the Raspberry Pi CPU is constantly increasing. To address the urgent need for efficient Raspberry Pi CPU heat dissipation and ensure normal operation within a safe temperature range, this study first established a model to simulate the CPU's thermal physics parameters during operation using CFD simulation software. An experimental platform was then set up to validate the CFD simulation results. Based on the validated CFD model, initial heat dissipation design was carried out. On this basis, the heat dissipation system was optimized by altering the heat sink’s length, width, fin height, thickness, spacing, and the thermal grease’s thermal conductivity between the heat sink and CPU chip. A surrogate model was established using the response surface methodology, and the NSGA-II genetic algorithm was employed for multi-objective optimization of the heat dissipation system’s cooling performance. Compared to the initial solution, the chip temperature was reduced by 6.19 °C, but the heat sink mass was increased by 0.65 g. By conducting multi-objective optimization design and making reasonable choices for the parameters, a suitable and an optimum design, in terms of both economics and efficiency, is obtained. These results demonstrate that this research can provide theoretical guidance and technical support for practical production. Furthermore, the methods and findings from this study can be applied to the design of heat dissipation systems for similar applications. [ABSTRACT FROM AUTHOR]

In order to address the limitations of recycled aggregate concrete prepared from recycled fine aggregates (RFA), the utilization of nanomaterials has been demonstrated as an innovative and effective approach. This study aimed to enhance the performance of ultra-high performance concrete (UHPC) reinforced with recycled fine aggregates (RFA) by incorporating industrial-grade graphene oxide (GO). The effects of GO on various aspects of UHPC, including workability, mechanical properties, autogenous shrinkage, permeability, interfacial transition zone (ITZ), and microstructure, were thoroughly investigated. The results demonstrated that the addition of RFA significantly reduced the early compressive strength of UHPC and increased water permeability and chloride ion penetration. However, it effectively mitigated autogenous shrinkage, and the 7-day autogenous shrinkage was reduced by 61.07%. Moreover, increasing the GO content improved the compressive strength and transport performance of RFA-reinforced GO-UHPC. The incorporation of GO led to a substantial enhancement in the tensile strength of UHPC due to its bridging effect and changes in pore structure, thereby improving the interface bonding between steel fibers and the matrix. At a critical GO content of 0.06%, the autogenous shrinkage was further reduced by 54,85%, and the compressive and tensile strengths were improved by 8.24% and 28.39%, respectively, with an increase in the matrix density. The addition of GO promoted the formation of more calcium silicate hydrate, resulting in a more homogeneous microstructure and an increased proportion of small pores in the ITZ. Overall, this study highlights the synergistic effect of GO and RFA in UHPC as a promising approach for developing low-cost, environmentally friendly, and sustainable building materials. • A method of preparing low-cost, environmentally friendly, and sustainable UHPC using industrial-grade graphene oxide and recycled fine aggregate are proposed. • The synergistic influence mechanisms of industrial-grade graphene oxide and recycled fine aggregate on the early autogenous shrinkage of UHPC are investigated. • The addition of industrial-grade graphene oxide enhances the mechanical properties and chloride penetration resistance of UHPC containing recycled fine aggregate. • The improvement of industrial graphene oxide on the pore structure of matrix and the interfacial transition zone of recycled fine aggregate interface are revealed. [ABSTRACT FROM AUTHOR]

• An enhanced mix design method of SCC with 20% FA and 10% BFS was implemented. • The threshold formula was modified by modifying the equivalent packing density. • The concept of mortar volume was introduced to correct the mortar film thickness. • The accuracies of the improved method were greater than 91.3%. This study aims to use the mixture design method to optimize self-compacting concrete (SCC) and manufacture SCC with excellent workability using recycled coarse aggregate (RCA) and a ternary cementitious system. The influences of incorporated RCA on the rheological thresholds of SCC with a fixed content of fly ash (FA) and blast furnace slag (BFS) are investigated based on paste rheological threshold theory and material packing characteristics. The original rheological model is improved by introducing the volume of adhesive mortar and modifying the equivalent packing density and mortar film thickness. The improved model is incorporated into the original theoretical system to apply the optimized mix design method to SCC. Moreover, experiments are conducted with different volumes of water, water-powder ratios and RCA replacement levels to verify the applicability of the optimized method. The results indicate that the proposed models can accurately predict the yield strength threshold and plastic viscosity threshold of fresh SCC. Furthermore, compared to the original model, predictions are 53% more accurate with the modified model. [ABSTRACT FROM AUTHOR]

LiDAR point clouds often suffer from sparsity and uneven distributions in outdoor scenes, leading to the poor performance of cutting-edge 3D object detectors. In this paper, we propose Point-Rich, which is designed to improve the performance of 3D object detection. Point-Rich consists of two key modules: HighDensity and HighLight. The HighDensity module addresses the issue of density imbalance by enhancing the point cloud density. The HighLight module leverages image semantic features to enrich the point clouds. Importantly, Point-Rich imposes no restrictions on the 3D object detection architecture and remains unaffected by feature or depth blur. The experimental results show that compared with the Pointpillars on the KITTI dataset, the mAP of Point-Rich under the bird's eyes view improves by 5.53% on average. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a simple yet efficient framework for finding a set of sparse correspondences between two non-rigid shapes using a tensor-based optimization technique. To make the matching consistent, we propose to use third-order potentials to define the similarity tensor measure between triplets of feature points. Given two non-rigid 3D models, we first extract two sets of feature points residing in shape extremities, and then build the similarity tensor as a combination of the geodesic-based and prior-based similarities. The hyper-graph matching problem is formulated as the maximization of an objective function over all possible permutations of points, and it is solved by a tensor power iteration technique, which involves row/column normalization. Finally, a consistent set of discrete correspondences is automatically obtained. Various experimental results have demonstrated the superiority of our proposed method, compared with several state-of-the-art methods. Highlights • We propose a non-rigid shape correspondence algorithm. • We incorporate both the local and global potentials into the similarity measure. • Our method is fully automatic and easy to implement. • It generates quality correspondences for a wide variety of model pairs. [ABSTRACT FROM AUTHOR]

• Polypropylene fiber (PPF) and nano-CaCO 3 (NC) are considered to enhance the engineering properties of RAC. • Mechanical properties of RAC can be improved as NC and PPF are used. • Microscopic structure of PPF-RAC can be significantly improved with the incorporation of NC. Fiber materials and nanomaterials are often added to recycled aggregate concrete (RAC) to compensate for the adverse effects caused by recycled concrete aggregate (RCA). Polypropylene fiber (PPF) and nano-CaCO 3 (NC) are considered having great potentials to improve the engineering properties of RAC due to their high yield, large reserve, and low price. Based on this, the current study recommended adding NC as an extra material to PPF-reinforced recycled aggregate concrete to compensate for its performance inadequacies. To fully expose the joint reinforcing effect, the microstructures and attributes were evaluated, including compressive strength, tensile strength, flexural strength, resistance to chloride ion permeability, drying shrinkage, scanning electron microscope (SEM), X-ray diffraction (XRD), thermogravimetry (TG), and hydration heat. The results showed that 1 wt.% NC contributes to overall improve the mechanical properties and durability performance of RAC incorporated with 0.133 vol.% 12 mm-length PPF. NC promotes the hydration degree of RAC-based cementitious materials and enhance the microstructural density and interfacial bonding capacity between PPF and RAC mortar. In addition, NC can improve the hydration rate and hydration heat of cement-based materials in the early stage, and participates in the chemical reaction of hydration in the later stage, promoting more occurrences of hydration reactions to the more productions of hydrates. Therefore, the comprehensive adoption of NC and PPF is capable of improving the performance enhancement of RAC for durable buildings. [ABSTRACT FROM AUTHOR]

We present a method for automatic reconstruction of the volumetric structures of urban buildings, directly from raw LiDAR point clouds. Given the large-scale LiDAR data from a group of urban buildings, we take advantage of the “divide-and-conquer” strategy to decompose the entire point clouds into a number of subsets, each of which corresponds to an individual building. For each urban building, we determine its upward direction and partition the corresponding point data into a series of consecutive blocks, achieved by investigating the distributions of feature points of the building along the upward direction. Next, we propose a novel algorithm, Spectral Residual Clustering (SRC), to extract the primitive elements within the contours of blocks from the sectional point set, which is formed by registering the series of consecutive slicing points. Subsequently, we detect the geometric constraints among primitive elements through individual fitting, and perform constrained fitting over all primitive elements to obtain the accurate contour. On this basis, we execute 3D modeling operations, like extrusion, lofting or sweeping, to generate the 3D models of blocks. The final accurate 3D models are generated by applying the union Boolean operations over the block models. We evaluate our reconstruction method on a variety of raw LiDAR scans to verify its robustness and effectiveness. [ABSTRACT FROM AUTHOR]

• Waste drinking bottles are chemically recycled into PET additive for asphalt modification. • PET additive can promote the massive use of RCA in sustainable asphalt pavement. • The moisture-induced damage resistance of asphalt mixtures containing RCA can be significantly enhanced with the incorporation of PET additive. Waste polyethylene terephthalate (PET) plastic and construction and demolition waste are main municipal solid wastes. If they are not properly disposed of, they will cause continuous damage to the ecological environment. Previous studies have shown that recycled concrete aggregate (RCA) can be successfully adopted to replace natural aggregate (NA) for asphalt pavement construction. However, the moisture-induced damage, as one of the pavement engineering performances, is very prominent for asphalt concrete containing RCA (RCA-AC), due to the high absorption of RCA and the weakness of the adhered mortar. Given this, PET additive, derived from waste bottle bodies, is considered to improve the resistance of RCA-AC to moisture-induced damage in this study, which has been previously identified effective to enhance the anti-stripping characteristics of asphalt mixtures containing NA. To achieve this goal, this study applied a series of tests including contact angle, image recognition, boiling water test, immersed Marshall test, freeze–thaw (F-T) splitting test, wheel tracking test, and field emission scanning electron microscope (FESEM) to evaluate the moisture-induced damage of RCA-AC containing PET additive. The results showed that PET additive has a significant ability to improve the bonding strength and adhesion of asphalt binder to RCA and reduce the stripping percentage and moisture-induced susceptibility of RCA-AC, especially under the F-T cycles. In addition, the 60 °C rut deformation resistance of RCA-AC after immersion can be improved as the PET additive is used. Furthermore, the interfacial bonding layers (IBL) of PET additive modified asphalt binder between RCA particles are still existent and its width is not significantly increased after immersion and F-T cycles by contrast to that of virgin binder. In general, the appropriate use of PET additive is a good approach to promote the high-quality recycling of RCA into sustainable asphalt pavement. [ABSTRACT FROM AUTHOR]

The multiple corrosive ions in seawater cause more severe concrete corrosion in tidal and splash zones. To understand the mechanisms of harmful ions in seawater under the real field conditions, four different synthetic multi-ions solutions (NaCl, NaCl + MgCl 2 , NaCl + Na 2 SO 4 and NaCl + MgCl 2 +Na 2 SO 4) were prepared. This study investigated the effects of external multi-ions solutions and repeated drying-wetting cycles on the degradation mechanisms of Portland cement mortar/paste with and without supplementary cementitious materials (SCMs) by using different microstructural techniques. It was found that the multi-ions solutions of Cl− + SO 4 2− and Cl− + Mg2++SO 4 2− aggravated the deterioration of mortar samples compared to the solution with Cl− alone under drying-wetting cycles. The cracks and larger pores were induced due to the formation of secondary ettringite, and the enlarged size of microvoids in mortar obviously affected the damage evolution and resulted in an accelerated deterioration of mortar samples. In addition, the incorporation of ground blast furnace slag (GBFS) significantly improved the corrosion resistance of cement-based materials and showed more efficient than other pozzolanic materials. This may be due to that aluminum incorporation could bridge the defective silicate chains and increase the polymerization degree of silicate tetrahedra in the C–S–H gel. Moreover, the matrix incorporated GBFS could effectively reduce pore defects and volumes of connected pores and large pores, which enhanced the resistance to multi-ions attack. These results can be provided a theoretical basis on the improvement of concrete durability under severe marine environmental attacks. [ABSTRACT FROM AUTHOR]

• Vagus nerve stimulation (VNS) can reduce myocardial atrophy after acute ischemic stroke; • VNS decreased the amount of Chyamse and inhibited mast cell activation in cardiac tissue after acute ischemic stroke; • VNS reduces the expression of angiotensin II (Ang II) after acute ischemic stroke by inhibiting mast cell activity, thereby alleviating cardiac inflammation and autophagy. Ischemic stroke is one of the leading causes of chronic disability worldwide, and stroke-induced heart damage can lead to death. According to research, patients with a variety of brain disease have good clinical results after vagus nerve stimulation (VNS). After ischemic stroke, mast cells (MCs) degranulate and release a large number of mediators, which may cause systemic inflammation. Chymase secreted by MCs can increase the levels of pathological angiotensin II (AngⅡ), which plays a crucial role in the deterioration of heart disease. Our goal was to develop a minimally invasive, targeted, and convenient VNS approach to assess the impact of VNS and to clarify the relationship between VNS and MCs in the prognosis of patients with myocardial atrophy after acute ischemic stroke. In this study, we verified the role of VNS in the treatment of myocardial atrophy after stroke and its molecular mechanism using a rat model of middle cerebral artery occlusion (MCAO/r). Behavioral studies were assessed using neurobehavioral deficit scores. Enzyme-linked immunosorbent assays, immunofluorescence staining, Western blotting and qRT-PCR were used to analyze the expression levels of myocardial atrophy, MC and inflammatory markers in rat hearts. VNS improved myocardial atrophy in MCAO/r rats, inhibited MC activation, reduced the expression of chymase and AngⅡ, and inhibited the expression of proinflammatory factors. The chymase activator C48/80 reversed these effects of VNS. Chymase activation inhibited the effect of VNS on myocardial atrophy in MCAO/r rats, increased AngⅡ expression and aggravated inflammation and autophagy. The myocardial atrophy of MCAO/r rats was improved after chymase inhibition, and AngⅡ expression, inflammation and autophagy were reduced. Our results suggest that VNS may reduce the expression of chymase and AngⅡ by inhibiting MC activation, thereby improving myocardial atrophy and reducing inflammation and autophagy in MCAO/r rats. Inhibition of MC activation may be an effective strategy for treating myocardial atrophy after stroke. VNS inhibits MC activation and reduces the expression of chymase and AngII, thereby alleviating myocardial atrophy, inflammation and autophagy after stroke. [ABSTRACT FROM AUTHOR]

Background. Electroacupuncture (EA) has benefits for neuropathic pain. However, the underlying mechanisms are still unknown. The current study explores the underlying mechanisms of EA in neuropathic pain of chronic constriction injury (CCI) rats. Material/Methods. Overall, 126 Sprague-Dawley (200-250 g) rats were divided into nine groups randomly: the sham-operated, CCI, CCI+EA, CCI+sham EA, CCI+NS, CCI+AAV-NC, CCI+AAV-miR-206-3p, CCI+EA+NS, and CCI+EA+AAV-miR-206-3p groups. The animals were sacrificed 14 days postsurgery. Mechanical withdrawal threshold (MWT) and thermal withdrawal latency (TWL) tests were used to determine differences in neurobehavioral manifestations. qPCR, western blotting, and immunofluorescence (IF) were carried out to detect the expression levels of miR-206-3p, BDNF, BAX/Bcl-2, TNF-α, and IL-6. Nissl staining was measured to observe morphological changes in neurons. Transmission electron microscopy (TEM) was employed to evaluate microscopic changes in dorsal horn synapses. Results. Hyperalgesia was reduced markedly by EA in the CCI model. The expression level of miR-206-3p was elevated, whereas the expression levels of BDNF, BAX/Bcl-2, TNF-α, and IL-6 were decreased in EA-treated CCI rats. However, a miR-206-3p inhibitor partially abrogated the analgesic effect of EA and resulted in poor behavioral performance and the BDNF, BAX/Bcl-2, TNF-α, and IL-6 expression was elevated as well. Conclusions. EA can relieve neuropathic pain by regulating the miR-206-3p/BDNF pathway, thus exerting anti-inflammatory and antiapoptotic effect. [ABSTRACT FROM AUTHOR]

This paper studies the similarities and the differences between natural aggregate concrete (NAC) beams and recycled aggregate concrete (RAC) beams in terms of concrete material properties, bearing capacity, and crack resistance and further proposes correction formulas for cracking moment calculation of RAC beams that consider different recycled aggregate substitution ratios. First, the basic mechanical properties (e.g., cube compressive strength, axial compressive strength, and elastic modulus) of RAC blocks were tested; second, comparative bending tests of RAC beams and natural aggregate concrete beams were conducted, in order to obtain the cracking moments, yield bending moments, ultimate bending moments, mid-span deflections and crack development forms; finally, numerical simulations were performed to investigate the cracking performances of RAC beams. Through analyzing the experimental results, it is found that the crack development pattern of RAC beams resembles that of natural aggregate concrete beams, while the cracking performance of RAC beams significantly deviates from that of NAC beams. Finally, the correction formulas for the cracking moment calculation of RAC beams are proposed based on the numerical simulation results and verified by data from other researchers, which can be regarded as a correction for the cracking moment calculation formulas in the current code for RAC beams with respect to varied recycled concrete aggregate substitution ratios. [ABSTRACT FROM AUTHOR]

Background: The left ventricular noncompaction cardiomyopathy (LVNC) is a rare subtype of cardiomyopathy associated with a high risk of heart failure (HF), thromboembolism, arrhythmia, and sudden cardiac death.Methods: The proband with overlap phenotypes of LVNC and hypertrophic cardiomyopathy (HCM) complicates atrial fibrillation (AF), ventricular tachycardia (VT), and HF due to the diffuse myocardial lesion, which were diagnosed by electrocardiogram, echocardiogram and cardiac magnetic resonance imaging. Peripheral blood was collected from the proband and his relatives. DNA was extracted from the peripheral blood of proband for high-throughput target capture sequencing. The Sanger sequence verified the variants. The protein was extracted from the skin of the proband and healthy volunteer. The expression difference of desmocollin2 was detected by Western blot.Results: The novel heterozygous truncated mutation (p.K47Rfs*2) of the DSC2 gene encoding an important component of desmosomes was detected by targeted capture sequencing. The western blots showed that the expressing level of functional desmocollin2 protein (~ 94kd) was lower in the proband than that in the healthy volunteer, indicating that DSC2 p.K47Rfs*2 obviously reduced the functional desmocollin2 protein expression in the proband.Conclusion: The heterozygous DSC2 p.K47Rfs*2 remarkably and abnormally reduced the functional desmocollin2 expression, which may potentially induce the overlap phenotypes of LVNC and HCM, complicating AF, VT, and HF. [ABSTRACT FROM AUTHOR]

As an important force-bearing component, aircraft fuel tank is localized at wings, fuselage, and empennage of an aircraft. To prevent the leakage or potential hazard of an aircraft fuel tank, the seal quality of fasteners on the fuel tank skin must be carefully inspected. Due to the limited space during inspection and its complex internal structures, it is challenging for current techniques to effectively inspect aircraft fuel tank. In this article, we introduce an aircraft sealant inspection system (ASInspS) to achieve accurate and reliable internal inspection for fuel tanks. For the hardware part, we utilize a high-precision 3-D scanner and a visual–inertial odometry (VIO) to acquire point clouds and poses, simultaneously. We then design three key modules to achieve the sealant inspection with high accuracy and reliability. First, the scanner positioning module aims to acquire the 6-D poses of the 3-D scanner, in which we propose two key improvements, that is, event-based mask (EvMask) and adaptive keyframe selection, to improve the robustness of feature tracking. Second, the seal area reconstruction module follows a coarse-to-fine strategy to achieve the accurate registration and then to create high-quality point cloud models of fuel tanks. Meanwhile, the results of fine alignment will be used to correct the accumulated drift error in the first module, which allows the system to ensure the high accuracy under complex scenes. Third, the sealant inspection module is built to conduct the accurate and reliable sealant measurement. The quantitative results demonstrate that our sealant inspection system can guarantee the precision (on different scales) at whatever the stage of the positioning, registration, or index measurement. The results also indicate that our ASInspS performs with high reliability even under a complex and closed aircraft fuel tank. [ABSTRACT FROM AUTHOR]

Accurate localization of gangue plays an essential role in the vision-based gangue sorting system. However, the gangue commonly has indistinguishable appearances and is stacked with coals in a cluttered mining environment, posing challenges for efficient gangue identification and volume measurement from images. In this article, we propose a novel inspection framework for fully automated gangue localization and volume measurement based on deep learning and point cloud processing techniques. To efficiently perform gangue inspection, first, a 3-D scanning system is assembled to automatically capture the clear images and 3-D point clouds of gangue. Second, instead of relying on handcrafted features, a data-driven approach streamlined gangue detection network (SGDNet) is proposed to detect gangue from images. In particular, we design an adaptive fusion unit (AFU) to fuse multiple hierarchical features and assign adaptive weights to different scales of feature maps via the attention mechanism in convolutional neural networks, which can include more location details of gangue. Furthermore, we project the gangue detection results into the 3-D scanning space and introduce a simplified 3-D object segmentation algorithm based on a surface curvature filter to extract the points of gangue. The extracted points can then be used to perform volume calculations. Several experiments are performed to demonstrate the priority of the proposed SGDNet and the effectiveness of the presented gangue localization and volume measurement framework. [ABSTRACT FROM AUTHOR]

In the aviation industry, the demand for high accuracy airplane product is growing, which makes precise production of airplane parts and accurate manufacturing increasingly important. To this end, it is crucial to be able to accurately measure the whole surface of an aircraft. 3-D laser scanner is widely utilized to capture the local shapes, represented as 3-D point clouds, of an object from different viewpoints. Multiview registration of point clouds is therefore a critical step to obtain the whole shape of an object. In this article, we propose a global registration framework to simultaneously align multiple point clouds with target detection and hierarchical optimization for aircraft inspection. By placing some targets (i.e., markers) surrounding an aircraft, we first scan the aircraft by putting a laser scanner around the aircraft at various stations, resulting in a number of laser scans which contain the point clouds of aircraft parts as well as targets. By detecting the centers of targets automatically, all partial point clouds are initially aligned to the global coordinate system. Furthermore, we tackle the influence of nonuniform distribution of point cloud density on registration accuracy, which has not been extensively studied so far, due to the large size of the aircraft. Existing approaches cannot directly apply to large size point clouds’ registration due to the aforementioned challenge. To address this issue, we propose a density-invariant area-based method to measure the overlapped region. On this basis, a hierarchical optimization registration method is used to achieve multiview registration of aircraft point clouds, and thereby the entire geometry shape of the aircraft is accurately obtained. A variety of experiments on real raw data demonstrate the effectiveness and robustness of our proposed framework. [ABSTRACT FROM AUTHOR]

• AuNPs were modified by using acrylamide. • GO nanosheets were modified by using dithiothreitol. • AuNPs@GO nanosheets were fabricated via "click chemistry". • Micropatterned AuNPs@GO nanosheets were manufactured via a predesigned mask. Here, the micropatterned gold nanoparticles (AuNPs) on graphene oxide (GO) nanosheet (AuNPs@GO) was fabricated via thiol-Michael addition click reaction under ultraviolet (UV) light. First, AuNPs and GO were both functionalized by acrylamide and dithiothreitol, respectively, which were characterized by transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS), dynamic light scattering (DLS) and ultraviolet–visible spectroscopy (UV–vis). The size of acrylamide modified AuNPs increased to 52.8 ± 16.5 nm compared to bare AuNPs (44.1 ± 14.5 nm). The AuNPs@GO could be fabricated under the UV-light, and the UV–vis signal varied depending on the concentration of AuNPs. Also, the micropatterned structure of AuNPs@GO nanosheet was accomplished by using a designed mask, which showed a high potential for cancer diagnosis and therapy. [ABSTRACT FROM AUTHOR]

Spinal cord injury (SCI) is a serious neurological disease without efficacious drugs. Anti-apoptosis and suppressing dendritic/synaptic degeneration in the anterior horn are essential targets after SCI. Previous studies found that hyperbaric oxygen therapy (HBOT) significantly protected rats after SCI. However, its potential effects and mechanisms remain unknown. The BDNF/TrkB signaling pathways evidently contribute to the SCI recovery. Currently, we mainly investigate the potential effects and mechanism of HBOT on anti-apoptosis and ameliorating impaired dendrites, dendritic spines and synapses after SCI. Establish SCI model and randomly divide rats into 5 groups. After SCI, rats were subjected to HBOT. ANA-12 is the specific inhibitor of BDNF/TrkB signal pathway. Changes in neurological deficit, neuronal morphology, apoptosis, protein expression and dendrite/synapse were examined by Basso–Beattie–Bresnahan (BBB) locomotor rating scale, Hematoxylin-eosin (HE) and Nissl staining, TUNEL staining, RT-PCR, Western blot, immunofluorescence and Golgi-Cox staining. We found HBOT suppressed dendritic/synaptic degeneration and alleviated apoptosis, consistent with the increase of BDNF and TrkB expression and improved neurological recovery. In contrast to the positive effects of HBOT, inhibitor increased degeneration and apoptosis. Moreover, we observed that these HBOT-mediated protective effects were significantly inhibited by inhibitor, consistent with the lower expression of BDNF/TrkB and worse neurobehavioral state. These findings suggest that hyperbaric oxygen therapy ameliorates spinal cord injury-induced neurological impairment by anti-apoptosis and suppressing dendritic/synaptic degeneration via upregulating the BDNF/TrkB signaling pathways. • HBOT decreased apoptosis and suppressed dendritic/synaptic degeneration in the anterior horn after SCI. • The BDNF/TrkB signaling pathways had positive effects on anti- apoptosis and suppressing dendritic/synaptic degeneration. • HBOT reduced apoptosis and attenuated degeneration of dendrite and synapse via upregulating BDNF/TrkB signaling pathways. [ABSTRACT FROM AUTHOR]

The utilization of recycled concrete aggregate (RCA) from construction and demolition wastes to produce pervious concrete show various environmental benefits in the construction of sponge city. However, its durability performance in an acid rain attack environment has received less attention. This study aims to understand the deterioration of mechanical properties and microstructure of pervious recycled aggregate concrete (PRAC) exposed to simulated acid rain attack and drying-wetting cycles. The effects of the ground granulated blast-furnace slag (GGBS) replacement ratios, the silica fume (SF) replacement ratios and the erosion times on the mass loss, compressive strength, relative dynamic elastic modulus, permeability coefficient and porosity of PRAC were evaluated. The results demonstrated that the acid rain attack caused obvious mass loss and compressive strength reduction for PRAC without pozzolanic additives, thus resulted in increase on the permeability coefficient and porosity. Moreover, the physicochemical properties of PRAC decreased strongly with the increase of acid rain exposure time. Nevertheless, the addition of 20%GGBF and 7%SF in PRAC showed better resistance to acid attack due to the synergistic effect. The microscopic characterization revealed that the added pozzolanic additives declined the content of calcium hydroxide of matrix in PRAC and thereby inhibited the formation of gypsum, which delayed the acid rain erosion process. • Pervious recycled aggregate concrete with supplemental cementitious materials based on response surface methodology were designed. • The mass, strength indices, water permeability and degradation resistance of PRAC exposed to acid rain attack were measured. • Degradation mechanism of PRAC under acid rain attack were revealed. • The incorporation of 20%GGBS and 7%SF in PRAC showed better resistance to acid rain attack due to its synergistic effects. [ABSTRACT FROM AUTHOR]

• Three heuristic algorithms for reliability estimation. • Reducing redundant samplings using breadth-first search of a grid tree. • Securing a prescribed accuracy of reliability. • Detecting large curvatures on the limit state surface. • Fast computation of the reliability index via a deleting process. A complete search of the input space is crucial for securing the accuracy of reliability estimation, but conventional search algorithm-based methods require a large number of samples to visit the entire input space. To this end, this paper presents three heuristic algorithms for reliability estimation based on breadth-first search (BFS) of a grid tree (GT), namely the reliability accuracy supervised search algorithm (RASSA), the limit state surface resolution supervised search algorithm (LSSRSSA), and the reliability index precision supervised search algorithm (RIPSSA). All the proposed algorithms are characterized by traversing the entire input space through a GT while simultaneously reducing redundant samplings through BFS, and each one has its own special advantage as follows: RASSA can guarantee a prescribed accuracy of reliability estimation; LSSRSSA is able to probe large curvatures on limit-state surfaces; and RIPSSA quickly computes the reliability index. The computational costs and limitations of the proposed algorithms are analyzed. In addition, the accuracy, efficiency, and practicality of the proposed algorithm are validated through comparisons with other methods and an engineering application. [ABSTRACT FROM AUTHOR]

Recycled polypropylene (rPP) wastes have been used to improve the high-temperature performance of asphalt. However, the high melting temperature of rPP does not match the conventional mixing temperature of bitumen, resulting in more energy consumption and emissions. Therefore, this study adopted dicumyl peroxide (DCP) to chemically degrade the rPP through a melt-shear processing method to obtain the corresponding modifiers (rPPM) with better flowability at a lower temperature. Torque rheology, melt flow rate (MFR) and thermogravimetry analysis (TGA) characteristics of rPPM incorporated with different dosages (1‰, 3‰, and 5‰) of DCP were compared to that of rPP. Correspondingly, the rPPM modified asphalt (rPPMA) were characterized by penetration, softening point, viscosity, and the dynamic shear rheology (DSR) tests. The TGA test showed that the rPPMs have a lower thermal stability as compared to rPP, and the MFR of rPPM can be up to 1900% larger than that of the rPP. The rPPMs can contribute to increasing the softening point and reducing by almost 50% penetration of virgin binder, which are reflected that they can improve the high-temperature performance of virgin binder. The DSR results stated that rPPM can provide a slightly improved deformation resistance and a lower anti-fatigue characteristic, comparative capacities, as well as a relatively lower deformation resistance and higher fatigue failure to the virgin binder, respectively. Accordingly, 3‰ DCP is optimally recommended to degrade rPP to obtain the modifier for the cleaner production and enhancement of modified binders. [ABSTRACT FROM AUTHOR]

Recycled polypropylene (rPP) wastes have been used to improve the high-temperature performance of asphalt. However, the high melting temperature of rPP does not match the conventional mixing temperature of bitumen, resulting in more energy consumption and emissions. Therefore, this study adopted dicumyl peroxide (DCP) to chemically degrade the rPP through a melt-shear processing method to obtain the corresponding modifiers (rPPM) with better flowability at a lower temperature. Torque rheology, melt flow rate (MFR) and thermogravimetry analysis (TGA) characteristics of rPPM incorporated with different dosages (1‰, 3‰, and 5‰) of DCP were compared to that of rPP. Correspondingly, the rPPM modified asphalt (rPPMA) were characterized by penetration, softening point, viscosity, and the dynamic shear rheology (DSR) tests. The TGA test showed that the rPPMs have a lower thermal stability as compared to rPP, and the MFR of rPPM can be up to 1900% larger than that of the rPP. The rPPMs can contribute to increasing the softening point and reducing by almost 50% penetration of virgin binder, which are reflected that they can improve the high-temperature performance of virgin binder. The DSR results stated that rPPM can provide a slightly improved deformation resistance and a lower anti-fatigue characteristic, comparative capacities, as well as a relatively lower deformation resistance and higher fatigue failure to the virgin binder, respectively. Accordingly, 3‰ DCP is optimally recommended to degrade rPP to obtain the modifier for the cleaner production and enhancement of modified binders. [ABSTRACT FROM AUTHOR]

With the continuous paving of roads around the world, the huge consumption of natural aggregate (NA) obtained through widespread excavation and extraction is now an inevitable part of highway construction. To alleviate this phenomenon, the use of recycled concrete aggregates (RCA) is considered beneficial to potentially substitute these aggregates in asphalt mixtures while concurrently providing secondary environmental, economic, and societal benefits. Nevertheless, engineering asphalt mixtures containing RCA to meet desired performance properties still poses several challenges and uncertainties for practitioners. Based on this, the present work reviews the previous relevant literature on this topic and summarizes the potential use of RCA for asphalt pavement related applications. An important characteristic of RCA is that it consists of various interfacial transition zones (ITZs) and voids caused by adhered mortar which leads to higher water-absorption and crushing characteristics as compared to NA. The treating methods used such as mechanical processing, calcium carbonate bio-deposition, and pozzolanic materials incorporation have been shown to be effective to improve the quality of RCA. The structural and material durability of RCA-asphalt pavement is closely dependent on its mix design, moisture-induced damage, and high and low temperature properties, which is in direct relation to the overall properties of RCA. Moreover, the shape variability of RCA during mixture preparation leads to the change in design gradation and its influence on the properties of RCA-asphalt mixtures should be carefully considered. The total substitution of coarse NA by RCA in asphalt pavement can be reached as long as the engineering properties, particularly the moisture susceptibility, are satisfactorily addressed. Overall, the potential application of RCA is a promising candidate to replace the excessive use of NA for the construction of high quality and sustainable asphalt pavements of the future. •Physicochemical characteristics and quality improvement methods of RCA are introduced. •Moisture-induced damage of RCA-asphalt mixtures is the most focused issue. •Sustainable use of RCA in asphalt pavement can be achieved. •Overall properties of RCA-asphalt mixture can be reached to the field application requirement. [ABSTRACT FROM AUTHOR]

[Display omitted] • Porous BPS hydrogel was fabricated. • BPS hydrogel was fast biomineralized using urease. • The bone-like apatite was formed on biomineralized BPS hydrogels. • The cytocompatibility of biomimeralized BPS hydrogels was improved. The development of biomineralized hydrogels with excellent cytocompatibility is of great importance for tissue engineering applications. Here, porous polyvinyl alcohol/alginate/biphasic calcium phosphate (BPS) hydrogels were fabricated via chemical and physical crosslinking methods, and the BPS hydrogels were in vitro biomineralized using urease in saturated calcium-phosphorus solution. For comparison, the BPS hydrogels were also treated using simulated body fluid (SBF) and Dulbecco's modified Eagle's medium with fetal bovine serum (DMEM-FBS), respectively. The physicochemical characterizations confirmed that bone-like apatite was quickly formed on the urease-biomineralized BPS hydrogels compared to the SBF and DMEM-FBS treated hydrogels. Additionally, the bone marrow derived mesenchymal stem cells (BMSCs), adhered and proliferated on the biomineralized hydrogels, were systematically analyzed using cell counting kit-8 (CCK-8). This paper demonstrated the potential urease for fast in vitro biomineralization on hydrogels to improve the cytocompatibility for bone tissue engineering applications. [ABSTRACT FROM AUTHOR]

The damages triggered by the long-term corrosion, external disturbance, and uneven support pressure result in defective states of sewer pipes. Nowadays, the sewer pipe images are easily captured by closed-circuit televisions (CCTV) and quick-view (QV). However, the defect detection and grading still depend on human visual interpretation mainly, which are time-consuming, subjective and costing. Therefore, an efficient, accurate and automated method for sewer pipe defect localization and fine-grained classification is needed. To this end, this work introduces a novel two-stage learning-based method, to endow the capability of object detection network for the sewer pipe defect detection and fine-grained classification simultaneously, over all defect regions by exploiting the multi-layer global feature fusion techniques. Specifically, based on a two-stage object detection network, the strengthened region proposal network (SRPN) first generates representative region proposals by fusing multi-scale feature maps from the backbone network for defect region localization. Instead of only extracting the proposed regions for defect classification, we concatenate the proposed region feature and the global contextual feature from the corresponding image, to enhance feature representation of the fine-grained defect classification network. Extensive experiments demonstrate that our learning-based method gets the state-of-the-art performance for sewer pipe defect localization and fine-grained classification, compared with the several classical learning-based methods, according to the solid experiments. Furthermore, our method has been applied for sewer pipe inspection in many China cities. [ABSTRACT FROM AUTHOR]

In the above article , Grant number SBK2019010120 should be changed to BK20190016. [ABSTRACT FROM AUTHOR]

The detection of tunnel surface defects is the very important part to ensure tunnel safety. Traditional tunnel detection mainly relies on naked-eye inspection, which is time-consuming and error-prone. In the past few years, many defect detection methods based on computer vision have been introduced. However, these methods with manual feature extraction do not perform well in detecting tunnel defects due to the complicated background of tunnel surfaces. To address these problems, this paper proposes a novel tunnel defect inspection method based on the Mask R-CNN. To improve the accuracy of the network, we endow it with a path augmentation feature pyramid network (PAFPN) and an edge detection branch. These improvements are easy to implement, with subtle extra memory and computational overhead. In this paper, we perform a detailed study of the PAFPN and the edge detection branch, and the experiment results show their robustness and accuracy in tunnel defect detection and segmentation. [Display omitted] • Identifying tunnel defects from complex background is challenging. • Using a modified Mask R-CNN to detect and segment tunnel defects. • Endowing Mask R-CNN with a path augmentation feature pyramid network. • Adding an edge detection branch to improve the accuracy of the model. [ABSTRACT FROM AUTHOR]