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Carbon fibers (CFs) are experiencing a growing demand owing to their low specific weight, exceptional mechanical properties, superior temperature, and corrosion resistance, however, their sustainability and energy consumption during manufacturing is still a challenge. Therefore, reclamation of waste CFs and their reformatting has gained significant attention. Herein, we synthesized a chemically degradable vitrimer matrix by curing bisphenol‐A diglycidyl ether (BADGE) with 2‐aminophenyl disulfide (2‐AFD) and further utilized the matrix for the development of CF reinforced composites (CFRCs) through vacuum‐assisted resin infusion molding (VARIM) process. The obtained vitrimeric system and its composites show excellent mechanical, self‐adhering, shape‐memory, and reprocessing properties. Meanwhile, the developed CFRP vitrimer composites can be rapidly dissolved in thiol solvent (1‐octanethiol), resulting in the efficient recycling of CFs. X‐ray diffraction, scanning electron microscopy, and Raman spectroscopy validate that the chemical structure of the recycled fibers closely resembles the structure of the original CFs. The recycled CFs were further used to prepare second generation composite materials with excellent thermal, dynamic, and mechanical properties for nonstructural applications (e.g., sports, automotive, etc.). Thus, with an effective CF recycling method, this study can assist in preparing reliable, long‐term functional, recyclable, and high‐performance composites. [ABSTRACT FROM AUTHOR]

This study systematically reviews the integration of artificial intelligence (AI) and remote sensing technologies to address the issue of crop water stress caused by rising global temperatures and climate change; in particular, it evaluates the effectiveness of various non-destructive remote sensing platforms (RGB, thermal imaging, and hyperspectral imaging) and AI techniques (machine learning, deep learning, ensemble methods, GAN, and XAI) in monitoring and predicting crop water stress. The analysis focuses on variability in precipitation due to climate change and explores how these technologies can be strategically combined under data-limited conditions to enhance agricultural productivity. Furthermore, this study is expected to contribute to improving sustainable agricultural practices and mitigating the negative impacts of climate change on crop yield and quality. [ABSTRACT FROM AUTHOR]

This study examined the effects of different forage sources on the ruminal bacteriome, growth performance, and carcass characteristics of Hanwoo steers during the fattening stage. In Korea, where high-concentrate feeding is common, selecting suitable forage is crucial for sustainable beef production. Fifteen 23-month-old Hanwoo steers, weighing an average of 679.27 ± 43.60 kg, were fed the following five different forage sources: oat hay (OAT), rye silage (RYE), Italian ryegrass (IRS), barley forage (BAR), and rice straw silage (RSS), alongside 1.5 kg of dry matter concentrate daily for five months. Carcass traits were evaluated post-slaughter, and rumen fluid samples were analyzed using full-length 16S rRNA gene sequencing to determine the bacteriome composition. The forage source significantly affected the alpha-diversity indices and bacteriome biomarkers linked to the feed efficiency and ruminal fermentation. Differences in the backfat thickness and meat yield index were noted, with alpha-diversity indices correlating with carcass traits. The phylum Planctomycetota, especially the family Thermoguttaceae, was linked to nitrogen fixation in high-protein diets like IRS, while the genus Limimorpha emerged as a biomarker for the meat yield. These findings highlight the importance of forage selection during late fattening to optimize beef production, considering diet and bacteriome shifts. [ABSTRACT FROM AUTHOR]

This paper considers the valuation of a vulnerable option when underlying stock is subject to liquidity risks. That is, it is assumed that the underlying stock is not perfectly liquid. We establish a framework where the stock price follows the stochastic volatility model and the option contains the default risk of the option issuer. In addition, we assume that liquidity risks are caused by stochastic market liquidity, and the default occurs at the first jump time of a stochastic Poisson process, which has a stochastic default intensity process consisting of both idiosyncratic and systematic components. By employing a change of measure, we derive an analytical formula for the value of a vulnerable option. Finally, we present several numerical examples to illustrate the sensitivity of significant parameters. [ABSTRACT FROM AUTHOR]

Piezoelectric materials with tunable photoluminescence have gained widespread attention for their application in optical communications and optoelectronic sensing devices. This has provided new opportunities to explore the possibility of developing flexible piezoelectric devices with both piezoelectricity and photoluminescence for multifunctional applications. In this study, we prepared a crystalline Pr‐doped perovskite BaTiO3 (BPTO) film on a flexible mica substrate using the radio‐frequency (RF) sputtering technique. The photoluminescence intensity remarkably increased by about 210% when external mechanical stress was applied to the film. This remarkable increase in photoluminescence is attributed to lattice distortion and a decrease in crystal symmetry. The BPTO film also exhibited reversible and high‐endurance behavior even after 103 fatigue bending cycles. Moreover, the BPTO film was utilized as a piezoelectric nanogenerator device, which demonstrated a maximum output voltage of about 2.68 V when external stress was applied through palm tapping. The nanogenerator device yielded an instantaneous output power of 1.80 μW with an external load resistance of 0.8 MΩ. These versatile and robust properties of the BPTO film demonstrate its potential for future development of lead‐free self‐powered optoelectronic sensing applications, such as artificial intelligence and biomedical devices. [ABSTRACT FROM AUTHOR]

Research highlights: The increasing rates of mental health disorders during the COVID-19 pandemic have popularized the notion of access to natural environments as a solution, leading to a surge in demand for urban green spaces. The concentration of natural volatile organic compounds (NVOCs) in forests, resulting from plant metabolism, plays a crucial role in forest-based healing and ecosystem health. Background and objectives: This study aimed to investigate how tree spacing influences NVOC concentrations within forest ecosystems using passive samplers, thereby enhancing the understanding of optimal forest management practices to promote human health benefits. Methods: We employed passive samplers to investigate tree spacing effects on NVOC concentrations. We placed passive samplers among trees in the study area to measure NVOC concentrations in individual trees and analyzed the relationship between NVOC concentration and tree spacing and structure. Results: A multiple regression analysis using distance decay models showed that a tree spacing of 2.7–3 m had a significant impact on NVOC concentrations. These findings provide a better understanding of how tree structure, tree spacing, and microclimate within the forest influence NVOC concentration. Conclusion: These findings have important implications for forest management and the design of forest landscapes to promote human health and well-being by considering the spatial distribution of NVOC concentrations. [ABSTRACT FROM AUTHOR]