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Newly emerged acoustic barriers provide effective solutions for noise reductions of varied kinds in which acoustic barriers made of Fano resonance-based space-coiling metamaterial are reported to have promising application prospects for their broadband noise reduction ability and good ventilation performance. However, current Fano resonance-based acoustic ventilation barriers are hard to practically apply since most of them are difficult to manufacture or install. To this end, this research proposes a novel acoustic ventilation barrier based on block-shaped space-coiling metamaterial, which is not only as functional as other acoustic ventilation barriers but also easy to manufacture and install. To obtain a more in-depth understanding of the noise reduction effect, the influence of the design parameters on transmission loss is numerically studied. Additionally, we conduct both numerical and experimental studies on the transmission loss and the ventilation performance of a full-scale meta-unit. Furthermore, through the corresponding optimization process, the proposed acoustic ventilation barrier can have transmission loss consistently above 10 dB across the frequency range of 495~1063 Hz. Lastly, a composite ventilation acoustic barrier obtained by stacking two layers of different proposed metamaterials is presented, which achieves multiband noise reduction performance across the ultra-broad frequency range of 479~1758 Hz. [ABSTRACT FROM AUTHOR]

Spiking neural networks (SNNs) are generating wide attention due to their brain-like simulation capabilities and low energy consumption. Converting artificial neural networks (ANNs) to SNNs provides great advantages, combining the high accuracy of ANNs with the robustness and energy efficiency of SNNs. Existing point clouds processing SNNs have two issues to be solved: first, they lack a specialized surrogate gradient function; second, they are not robust enough to process a real-world dataset. In this work, we present a high-accuracy converted SNN for 3D point cloud processing. Specifically, we first revise and redesign the Spiking X-Convolution module based on the X-transformation. To address the problem of non-differentiable activation function arising from the binary signal from spiking neurons, we propose an effective adjustable surrogate gradient function, which can fit various models well by tuning the parameters. Additionally, we introduce a versatile ANN-to-SNN conversion framework enabling modular transformations. Based on this framework and the spiking X-Convolution module, we design the Spiking PointCNN, a highly efficient converted SNN for processing 3D point clouds. We conduct experiments on the public 3D point cloud datasets ModelNet40 and ScanObjectNN, on which our proposed model achieves excellent accuracy. Code will be available on GitHub. [ABSTRACT FROM AUTHOR]

Potential damage caused by earthquakes combined with reduced comfort due to traffic has become a big challenge when designing modern buildings, and base-isolation is one of the most effective solutions to such a problem. However, most isolation bearings cannot provide sufficient mitigation for both earthquakes and traffic-induced vibrations simultaneously. To this end, this research proposes a new type of three-dimensional isolation bearing for the mitigation of both earthquake effects and traffic-induced vibrations, which is composited by a thick rubber bearing, an auto-reset flat sliding bearing, and a double concave friction pendulum bearing. In this study, the analytical hysteresis model of the proposed isolation bearing was derived and experimentally validated. In addition, the fatigue performance and vertical compression performance of the proposed isolation bearing was tested and analyzed. Finally, the mitigation effect for traffic-induced vibrations of the proposed isolation bearing was validated through a field test. [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]

The excessive deflection of large-span cantilever cast prestressed concrete (LCCPC) box girders has always been a complex problem to be solved in bridge engineering. To analyze the effect of shear deformation at segmental joints on the deflection of LCCPC box girders, comparison tests were carried out on three prestressed concrete (PC) I-girders with joints and a PC I-girder without joints, and a finite element simulation method of segmental joints was proposed based on the tests. Subsequently, finite element analysis was conducted on a test girder and the Assistant Shipping Channel Bridge of Humen Bridge (a PC continuous rigid frame bridge with a main span of 270 m) using this method. The experimental and theoretical analysis results showed that the effect of the shear deformation at joints compared to the deformation at midspan of the girder specimens was negligible. Deformation at midspan of the specimens would not significantly increase, even if shear rigidity at the joints was significantly reduced or there were more joints in the girder specimen. The effect of shear deformation at segmental joints on the deflection of LCCPC box girders was quite small and thus insignificant. [ABSTRACT FROM AUTHOR]

Since the reform and opening up in 1978, China's economy has grown significantly, but rural development still lags. China has implemented a rural revitalization strategy to reduce the gap between urban and rural areas. Meanwhile, the digital economy has gradually become a new economic growth engine for China. With the digitalization of rural industries, the digital economy gradually integrated into rural development and revitalization. However, how the digital economy impacts rural revitalization remains unclear. Based on the entropy method, previous studies measured rural revitalization levels from the perspectives of economy, civilization, and ecological environment. In this paper, using panel data from 11 prefecture-level cities in Zhejiang Province from 2011 to 2019, we use the entropy method to quantify the development level of the digital economy, industrial upgrading, and rural revitalization. Then, we investigate the relationship among them using fixed effect regression. The empirical results show that the digital economy obviously promotes rural revitalization. The mediation effect test shows that industrial upgrading plays a mediating mechanism between the digital economy and rural revitalization. In addition, heterogeneity analysis reveals that the promotion effect of the digital economy on rural development in southwestern Zhejiang is stronger than that of northeastern Zhejiang. The results imply that government should strengthen digital infrastructure construction in rural areas to promote rural revitalization. Moreover, rural areas with different economic development levels should implement a differentiated rural revitalization strategy. [ABSTRACT FROM AUTHOR]

Aspergillus flavus is a saprophytic soil fungus that infects and contaminates seed crops with the highly carcinogenic aflatoxin, which brings health hazards to animals and humans. In this study, bacterial strains B1 and B2 isolated from the rhizosphere soil of camellia sinensis had significant antagonistic activities against A. flavus. Based on the phylogenetic analysis of 16SrDNA gene sequence, bacterial strains B1 and B2 were identified as Bacillus tequilensis and Bacillus velezensis, respectively. In addition, the transcriptome analysis showed that some genes related to A. flavus growth and aflatoxin synthesis were differential expressed and 16 genes in the aflatoxin synthesis gene cluster showed down-regulation trends when inhibited by Bacillus velezensis strain B2. We guessed that the Bacillus velezensis strain B2 may secrete some secondary metabolites, which regulate the related gene transcription of A. flavus to inhibit growth and aflatoxin production. In summary, this work provided the foundation for the more effective biocontrol of A. flavus infection and aflatoxin contamination by the determination of differential expression of genes related to growth and aflatoxin synthesis in A. flavus when inhibited by B. velezensis strain B2. [ABSTRACT FROM AUTHOR]

A new reliability estimation method based on partial multiplicative dimensional reduction is proposed for probabilistic and non-probabilistic hybrid structural systems. The proposed method is characterized by decorrelating interval input variables from random input variables using the partial multiplicative dimensional reduction method in conjunction with the weakest-link theory. In this method, the failure statistics of the original performance function are equivalent to a statical chain of two elements, in which one of the two elements represents the failures due to random input variables and the other represents the failures due to interval variables. Rather than yielding an estimated interval of failure probability, the proposed method produces a single value for failure probability, which is more meaningful for engineering. In addition, the accuracy, validity, and superiority of the proposed method are demonstrated, and the error-related properties of the proposed method are investigated. [ABSTRACT FROM AUTHOR]

Waste poly(ethylene terephthalate) (PET) drinking bottles and end-of-life scrap rubber tires are common municipal solid wastes discarded and produced every day, which are usually disposed of in landfills and stockpiles, occupying a great quantity of land and causing serious environmental issues. This study aims to first turn waste PET into two value-added derived additives under the chemical treatment of two amines, namely triethylenetetramine (TETA) and ethanolamine (EA), respectively, and then adopt them in association with crumb rubber (CR) to modify virgin bitumen for preparing various rubberized asphalt mixtures. Subsequently, the high- and low-temperature properties of the rubberized binder modified by PET additives (PET-TETA and PET-EA) were comparatively characterized through dynamic shear rheometer (DSR) and bending beam rheometer (BBR) tests, while the rutting resistance, fatigue resistance, and dynamic modulus of the further fabricated mixtures were evaluated and validated through mixture tests. The results obtained indicate that 2 wt.% PET-TETA and PET-EA contribute to increase the rutting failure temperature of asphalt rubber from 82.2 °C to 85.5 °C and 84.2 °C, respectively, retaining the high grade of PG 82; the low-temperature grade of asphalt rubber slightly decreased from PG-28 to PG-22 as the additive was added; the rut depth slightly changed from 3.10 mm to nearly 3.70 mm; and PET-TETA exhibits the potential to be capable of extending the fatigue life of asphalt rubber in contrast with PET-EA at different stress levels within 450 kPa. Based on the findings of this study, the developed recycling approach is considered to be applicable to not only alleviate the environmental concerns caused by the landfills and stockpiles of those wastes but also make them valuable for building more durable pavement. [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]