Search

The purpose of this article is to clarify the evolving connotations of “readers” and “books” in public libraries, centers on a thriving segment of library patrons – minor readers. Taking the services for minors in Guangdong China as an example, the study examines and discusses how public libraries can play a proactive role in forging effective connections between readers and books, hence promoting the sustainable development of library services. The author has come to the conclusion that public libraries worldwide must proactively adapt to the ever-evolving environment, cutting-edge technologies, and emerging information needs.

[Objective] For the joint application of double-row high vertical nylon mesh sand barriers and grass checkerboard sand barriers, wind tunnel experimental studies were conducted to optimize the configuration of nylon mesh sand barriers porosity in the joint sand barriers and investigate the sand control benefits of the joint sand barriers under each porosity. [Methods] Based on the wind tunnel simulation experimental data, we carried out the characterization of the changes in the wind velocity flow field, aerodynamic roughness, friction wind velocity, sand transport rate with height, and sand blocking rate of the joint sand barriers with different porosities (40%, 45%, and 55%) at different wind speeds. [Results] (1) The area of wind shadow zone of the joint sand barrier was the largest at 40% porosity of nylon mesh sand barrier under the same wind speed. (2) As the porosity of the nylon mesh sand barrier increases, the aerodynamic roughness and friction wind speed decreased, and the values of aerodynamic roughness and friction wind speed of the joint sand barrier at 40% porosity were the largest at the same wind speed and the same location. (3) The sand transport rate on the surface increased with the increase of wind speed. Inside and on the leeward side of the joint sand barriers, the sand transport rate decreased exponentially with the increase of height, and the sand transport was mainly concentrated at the height of 0~12 cm. (4) Wind speed and sand barrier rate showed a negative correlation; sand barrier rate and porosity also showed a negative correlation, the porosity of 40% of the joint sand barriers had a better sand barrier rate; double rows of high vertical nylon mesh sand barriers and grass checkerboard sand fixation measures combined with the sand barrier rate superposition also existed. [Conclusion] Therefore, the combination of double-row vertical nylon mesh with 40% porosity and grass checkerboards can realize better configuration and sand control benefits.

A new algorithm called YOLO-APDM is proposed to address low quality and multi-scale target detection issues in infrared road scenes. The method reconstructs the neck section of the algorithm using the multi-scale attentional feature fusion idea. Based on this reconstruction, the P2 detection layer is established, which optimizes network structure, enhances multi-scale feature fusion performance, and expands the detection network’s capacity for multi-scale complicated targets. Replacing YOLOv8’s C2f module with C2f-DCNv3 increases the network’s ability to focus on the target region while lowering the amount of model parameters. The MSCA mechanism is added after the backbone’s SPPF module to improve the model’s detection performance by directing the network’s detection resources to the major road target detection zone. Experimental results show that on the FLIR_ADAS_v2 dataset retaining eight main categories, using YOLO-APDM compared to YOLOv8n, mAP@0.5 and mAP@0.5:0.95 increased by 6.6% and 5.0%, respectively. On the M3FD dataset, mAP@0.5 and mAP@0.5 increased by 8.1% and 5.9%, respectively. The number of model parameters and model size were reduced by 8.6% and 4.8%, respectively. The design requirements of the high-precision detection of infrared road targets were achieved while considering the requirements of model complexity control.

Abstract Recent data from human studies and animal models have established roles for type II alveolar epithelial cell (AEC2) injury/apoptosis and monocyte/macrophage accumulation and activation in progressive lung fibrosis. Although the link between these processes is not well defined, we have previously shown that CD36-mediated uptake of apoptotic AEC2s by lung macrophages is sufficient to drive fibrosis. Importantly, apoptotic AEC2s are rich in oxidized phospholipids (oxPL), and amongst its multiple functions, CD36 serves as a scavenger receptor for oxPL. Recent studies have established a role for oxPLs in alveolar scarring, and we hypothesized that uptake and accrual of oxPL by CD36 would cause a macrophage phenotypic change that promotes fibrosis. To test this hypothesis, we treated wild-type and CD36-null mice with the oxPL derivative oxidized phosphocholine (POVPC) and found that CD36-null mice were protected from oxPL-induced scarring. Compared to WT mice, fewer macrophages accumulated in the lungs of CD36-null animals, and the macrophages exhibited a decreased accumulation of intracellular oxidized lipid. Importantly, the attenuated accrual of oxPL in CD36-null macrophages was associated with diminished expression of the profibrotic mediator, TGFβ. Finally, the pathway linking oxPL uptake and TGFβ expression was found to require CD36-mediated activation of Lyn kinase. Together, these observations elucidate a causal pathway that connects AEC2 injury with lung macrophage activation via CD36-mediated uptake of oxPL and suggest several potential therapeutic targets.

Accurate analysis of the strength of steel-fiber-reinforced concrete (SFRC) is important for ensuring construction quality and safety. Cube compression and splitting tensile tests of steel fiber with different varieties, lengths, and dosages were performed, and the effects of different varieties, lengths, and dosages on the compressive and splitting properties of secondary concrete were obtained. It was determined that the compression and splitting strengths of concrete could be effectively improved by the addition of end-hooked and milled steel fibers. The compressive and splitting strengths of concrete can be enhanced by increasing the fiber length and content. However, concrete also exhibits obvious uncertainty owing to the comprehensive influence of steel fiber variety, fiber length, and fiber content. In order to solve this engineering uncertainty, the traditional RBF neural network is improved by using central value and weight learning strategy especially. On this basis, the RBF fuzzy neural network prediction model of the strength of secondary steel fiber-reinforced concrete was innovatively established with the type, length and content of steel fiber as input information and the compressive strength and splitting tensile strength as output information. In order to further verify the engineering reliability of the prediction model, the compressive strength and splitting tensile strength of steel fiber reinforced concrete with rock anchor beams are predicted by the prediction model. The results show that the convergence rate of the prediction model is increased by 15%, and the error between the predicted value and the measured value is less than 10%, which is more efficient and accurate than the traditional one. Additionally, the improved model algorithm is efficient and reasonable, providing technical support for the safe construction of large-volume steel fiber concrete projects, such as rock anchor beams. The fuzzy random method can also be applied to similar engineering fields.