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This study investigated high-strength pervious concrete (HSPC) containing recycled concrete aggregate (RCA) of two sizes including large (9.5–12.5 mm) and small (4.75–9.5 mm). Ultra-high-performance mortar (UHPM) was employed to enhance the interface transition zone between the mortar matrix and RCA. A novel approach using sustainable binder replacements, including high-volume ground bottom ash (GBA), fly ash (FA), and calcium stearate (CS), was adopted. HSPC mixtures were evaluated for compressive strength, void ratio, permeability, water absorption ratio (WAR), clogging resistance, water contact angle, and microstructural properties using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD). The achieved results revealed that replacing binder with CS decreased density and reduced compressive strength by 8-23%. The CS formed an overhydrophobic or superhydrophobic coating with a water contact angle of 140–150°, maintaining permeability above 1 mm/s after five clogging cycles. HSPC with 10% CS and small RCA exhibited a WAR of 0.09-0.77 mm, significantly lower than HSPC without CS. The XRD confirmed that CS released calcium ions, promoting additional C–S–H formation. The SEM revealed increased porosity in CS-modified paste, contributing to reduced compressive strength. The EDS indicated reduced calcium (Ca) and silicon (Si) contents, suggesting reactions between CS derived calcium ions and SiO2 in GBA and FA. These findings highlight the potential of CS-modified HSPC to achieve clogging resistance while maintaining acceptable permeability, despite reduced strength. These findings indicated the potential for CS-modified HSPC to provide clogging resistance.

Abstract This paper focuses on the methodology for evaluating the degree of total curling in concrete pavement using machine learning. Deflection induced by falling weight deflectometer (FWD) testing is known as a direct correlation to total curling including built-in and daily curling. However, deflection measurement in the in-service road is also affected by others, such as environmental conditions, pavement geometry, subgrade stiffness, and mixture design. Thus, it is challenging to determine the level of curling from FWD data due to the complexity of influencing parameters. To navigate this complexity, prominent machine learning models are exploited to identify a non-linear relationship between curling and FWD deflections. A finite-element simulation of FWD is conducted to generate a vast data set, and a robust regression model is trained to estimate the total effective temperature difference (TETD) to quantify the effects of curling. Since input parameters for testing pavements can be measurable in the field, curling from TETD can be readily obtained using the proposed methodology. Comparative simulations highlight that the proposed models, with an MAE less than 0.5 °C significantly outperform the multiple regression performance, which registers an MAE of 3.45 °C in TETD, particularly in offering cost-effective and noise-tolerant prediction.

This narrative review on the use of biophotonics therapies for management of oral diseases is written as a tribute to Prof. Crispian Scully. His seminal contributions to the field are highlighted by the detailed, comprehensive description of clinical presentations of oral diseases. This has enabled a more thorough, fundamental understanding of many of these pathologies by research from his group as well as inspired mechanistic investigations in many groups globally. In the same vein, a major emphasis of this narrative review is to focus on the evidence from human case reports rather than in vitro or in vivo animal studies that showcases the growing and broad impact of biophotonics therapies. The similarities and differences between two distinct forms of low‐dose biophotonics treatments namely photodynamic therapy and photobiomodulation therapy are discussed. As evident in this review, a majority of these reports provide promising evidence for their clinical efficacy. However, a lack of adequate technical details, precise biological rationale, and limited outcome measures limits the current utility of these treatments. Future investigations should attempt to address these shortcomings and develop better designed, rigorous, controlled studies to fully harness the tremendous potential of low‐dose biophotonics therapies. [ABSTRACT FROM AUTHOR]

This paper presents a novel moving target deception jamming method against synthetic aperture radar (SAR)-ground moving target indication (GMTI) based on fast azimuth-domain block EM calculation. In this method, a fast electromagnetic(EM) calculation based on equivalent bistatic scattered fields is used to simulate the scattering characteristics of moving false target, which greatly improves the computational efficiency. With the azimuth-domain block implementation, the jammer’s frequency response (JFR) can be calculated by fast searching and interpolating with EM database, and the computation load is further reduced. The implementation and the performance of the proposed method are discussed. Comparing with the traditional methods based on a point model, the proposed method is able to generate more verisimilar moving false targets for different attitudes and resolutions. The simulation experiments are provided to demonstrate the validity of the proposed method.

This paper presents the findings of an investigation on early-age thermal behavior of concrete segmental box girders using finite element (FE) analysis. A FE segmental box-girder diaphragm model was created to evaluate the effect of its flanges, webs, volume-to-surface area ratio (V/A), and heat of cement hydration on the temperature development of the segment at an early age. Isothermal calorimetry testing was conducted on the cementitious materials of four normal and a high-strength concrete mix designs to obtain the heat of hydration and temperature rise, which then were used in the preprocessing of the FE schemes. Based on the investigation on 3 different model shapes consisting of the full-, no-flange-, and core-segment models, the no-flange-segment model was selected as the simplified and representative model for segmental box-girder diaphragms in thermal analysis. Additionally, a parametric study on various V/A of the no-flange- segment model indicates that the segmental box-girder diaphragms are considered mass concrete when using high-strength concrete regardless of the V/A, and measures should be implemented to prevent unexpected thermal cracking.