Even though carbon fibres (CFs) have been increasingly used, their end-of-life (EOL) handling presents a challenge. To address this issue, we evaluated the use of recycled CFs (rCFs), produced through pyrolysis, as rovings to be used in textile reinforced concrete structures. Mechanical processing (hammer mill) with varying machine settings was then used to assess EOL handling, considering the separation potential of rCFs and the length of separated rCFs. The results showed that rCF rovings can be separated from concrete with an average of 87 wt.-%, whereas the highest rCF length and separation yield were observed in different machine settings. In addition, a techno-environmental assessment on the mechanical process was performed to compare different machine settings. The machine settings with the highest yield of rCF rovings also had the highest fine fraction that cannot be further separated. Furthermore, life cycle assessment (LCA) was conducted covering three life cycles of CFs and an additional LCA for comparing rCF with virgin CF. LCA results revealed that CF reinforced plastic and concrete productions are the two main contributors to environmental impacts. The comparative LCA between virgin CF and rCF also showed that using rCF is environmentally advantageous, as virgin CF production causes 230% more global warming potential compared to rCF. Future studies assessing different allocation approaches, quantifying the quality of rCF, and its inclusion in LCA are relevant.
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http://dx.doi.org/10.1177/0734242X241237197 | DOI Listing |
BMC Public Health
January 2025
Department of Statistics and Data Science, Jahangirnagar University, Dhaka, 1342, Bangladesh.
Background: Child mortality is a reliable and significant indicator of a nation's health. Although the child mortality rate in Bangladesh is declining over time, it still needs to drop even more in order to meet the Sustainable Development Goals (SDGs). Machine Learning models are one of the best tools for making more accurate and efficient forecasts and gaining in-depth knowledge.
View Article and Find Full Text PDFObjectives: This study aimed to develop a prediction model for the detection of early sepsis-associated acute kidney injury (SA-AKI), which is defined as AKI diagnosed within 48 hours of a sepsis diagnosis.
Design: A retrospective study design was employed. It is not linked to a clinical trial.
JMIR Mhealth Uhealth
January 2025
Institute for AI and Informatics in Medicine, Technical University of Munich, Munich, Germany.
Background: Artificial intelligence (AI) has already revolutionized the analysis of image, text, and tabular data, bringing significant advances across many medical sectors. Now, by combining with wearable inertial measurement units (IMUs), AI could transform health care again by opening new opportunities in patient care and medical research.
Objective: This systematic review aims to evaluate the integration of AI models with wearable IMUs in health care, identifying current applications, challenges, and future opportunities.
Philos Trans A Math Phys Eng Sci
January 2025
Department of Computer Science & Gonda Brain Science Center & BINA Nano-Technology Center Bar Ilan University, Bar Ilan University, Israel.
The emergence of collective order in swarms from local, myopic interactions of their individual members is of interest to biology, sociology, psychology, computer science, robotics, physics and economics. , whose members unknowingly work towards a common goal, are particularly perplexing: members sometimes take individual actions that maximize collective utility, at the expense of their own. This seems to contradict expectations of individual rationality.
View Article and Find Full Text PDFJAMA Surg
January 2025
Division of Transplant Surgery, Department of Surgery, Mayo Clinic Arizona, Phoenix.
Importance: Normothermic machine perfusion (NMP) has been shown to reduce peritransplant complications. Despite increasing NMP use in liver transplant (LT), there is a scarcity of real-world clinical experience data.
Objective: To compare LT outcomes between donation after brain death (DBD) and donation after circulatory death (DCD) allografts preserved with NMP or static cold storage (SCS).
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