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Optimization of Hybrid CompositeβMetal Joints: Single Pin
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The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.Deepening the understanding of composite and metal joint methodologies applied in the aerospace industry is crucial for minimizing operational expenditures. Current investigations are focusing on innovative joining techniques that incorporate additive manufactured rivet pins. This research aims to analyze the mechanical strength of these joints for the effective optimization of pin profiles. Through extensive study of the impact of pin geometry on joint performance, we derived the optimal pin design, considering various initial parameters with the objective of minimizing stress concentration in the pin structure. The joint configurations of metal to composite interfaces were systematically examined using finite element analysis and lap shear testing, which included a singular pin and an adhesive-bonding layer. Numerical simulations reveal that the maximum shear stress in the pin is located at the junction between the base of the pin and the metal plate. By optimizing the shape and dimensions of the pin, both the shear and axial stresses can be significantly mitigated. Following the numerical optimization process, a series of enhanced pins have been produced via additive manufacturing techniques to facilitate mechanical testing. The experimental data obtained align closely with the simulation results, thereby reinforcing the validity of the optimization. The optimal configuration for a single pin, involving a 60Β° angle and a total height of 3.43 mm, achieves the minimum shear stress. Based on these findings, further investigations are underway to explore optimized designs utilizing multiple pins. This paper presents the results of the single pin study, whereas the findings pertaining to the ongoing investigation on the multi-pin configuration will be disseminated in subsequent publications.This research was funded by the collaborative Ph.D. program of Zhongyuan University of Technology (Discipline construction funds, 4600-12120009). The study is also partially supported by the Royal Society grant IEC\NSFC\233524
Carbonated Aggregates and Basalt Fiber-Reinforced Polymers: Advancing Sustainable Concrete for Structural Use
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The original contributions presented in this study are included in the article. Further inquiries can be directed at the corresponding author.In the transition towards a circular economy, redesigning construction materials for enhanced sustainability becomes crucial. To contribute to this goal, this paper investigates the integration of carbonated aggregates (CAs) and basalt fibre-reinforced polymers (BFRPs) in concrete infrastructures as an alternative to natural sand (NS) and steel reinforcement. CA is manufactured using accelerated carbonation that utilizes CO2 to turn industrial byproducts into mineralised products. The structural performance of CA and BFRP-reinforced concrete simply supported slab was investigated through conducting a series of experimental tests to assess the key structural parameters, including bond strength, bearing capacity, failure behavior, and cracking bbehaviour. Carbon footprint analysis (CFA) was conducted to understand the environmental impact of incorporating BFRP and CA. The results indicate that CA exhibits a higher water absorption rate compared to NS. As the CA ratio increased, the ultrasonic pulse velocity (UPV), compressive, tensile, and flexural strength decreased, and the absorption capacity of concrete increased. Furthermore, incorporating 25% CA in concrete has no significant effect on the bond strength of BFRP. However, the load capacity decreased with an increasing CA replacement ratio. Finally, integrating BFRP and 50% of CA into concrete slabs reduced the slabβs CFA by 9.7% when compared with steel-reinforced concrete (RC) slabs.This research received no external funding
Biogenic COβ Emissions in the EU Biofuel and Bioenergy Sector: Mapping Sources, Regional Trends, and Pathways for Capture and Utilisation
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The datasets generated during and/or analysed during the current study are available in the OpenAIRE Zenodo repository, https://doi.org/10.5281/zenodo.14651075.The European biofuel and bioenergy industry faces increasing challenges in achieving sustainable energy production while meeting carbon neutrality targets. This study provides a detailed analysis of biogenic emissions from biofuel and bioenergy production, with a focus on key sectors such as biogas, biomethane, bioethanol, syngas, biomass combustion, and biomass pyrolysis. Over 18,000 facilities were examined, including their feedstocks, production processes, and associated greenhouse gas emissions. The results highlight forestry residues as the predominant feedstock and expose significant disparities in infrastructure and technology adoption across EU Member States. While countries like Sweden and Germany lead in emissions management and carbon capture through bioenergy production with carbon capture and storage systems (BECCS), other regions face deficiencies in bioenergy infrastructure. The findings underscore the potential of BECCS and similar carbon management technologies to achieve negative emissions and support the European Green Dealβs climate neutrality goals. This work serves as a resource for policymakers, industry leaders, and researchers, fostering informed strategies for the sustainable advancement of the biofuels sector.This project has received funding from the European Unionβs Horizon 2020 research and innovation program under grant agreement no. 101084405 (CRONUS)
Prediction of Diabetes Using Statistical and Machine Learning Modelling Techniques
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The data can be shared upon request.Statistical and machine learning modelling techniques have been effectively used in the healthcare domain and the prediction of epidemiological chronic diseases such as diabetes, which is classified as an epidemic due to its high rates of global prevalence. These techniques are useful for the processes of description, prediction, and evaluation of various diseases, including diabetes. This paper models diabetes disease in Saudi Arabia using the most relevant risk factors, namely smoking, obesity, and physical inactivity for adults aged β₯25 years. The aim of this study is based on developing statistical and machine learning models for the purpose of studying the trends in incidence rates of diabetes over 15 years (1999β2013) and to obtain predictions for future levels of the disease up to 2025, to support health policy planning and resource allocation for controlling diabetes. Different models were developed, namely Multiple Linear Regression (MLR), Support Vector Regression (SVR), Bayesian Linear Regression (BLM), Adaptive Neuro-Fuzzy Inference model (ANFIS), and Artificial Neural Network (ANN). The performance of the developed models is evaluated using four statistical metrices: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and coefficient of determination R-squared. Based on the results, it can be observed that the overall performance for all proposed models was reasonably good; however, the best results were achieved by the ANFIS model with RMSE = 0.04 and R2 = 0.99 for menβs training data, and RMSE = 0.02 and R2 = 0.99 for womenβs training data.This research received no external funding
Accelerating Loss Recovery for Content Delivery Network
Get PDFThis article has supplementary downloadable material available at https://doi.org/10.1109/TC.2025.3558020, provided by the authors. Digital Object Identifier 10.1109/TC.2025.3558020Packet losses significantly impact the user experience of content delivery network (CDN) services such as live streaming and data backup-and-archiving. However, our production network measurement studies show that the legacy loss recovery is far from satisfactory due to the wide-area loss characteristics (i.e., dynamics and burstiness) in the wild. In this paper, we propose a sender-side Adaptive ReTransmission scheme, ART, which minimizes the recovery time of lost packets with minimal redundancy cost. Distinguishing itself from forward-error-correction (FEC), which preemptively sends redundant data packets to prevent loss, ART functions as an automatic-repeat-request (ARQ) scheme. It applies redundancy specifically to lost packets instead of unlost packets, thereby addressing the characteristic patterns of wide-area losses in real-world scenarios. We implement ART upon QUIC protocol and evaluate it via both trace-driven emulation and real-world deployment. The results show that ART reduces up to 34% of flow completion time (FCT) for delay-sensitive transmissions, improves up to 26% of goodput for throughput-intensive transmissions, reduces 11.6% video playback rebuffering, and saves up to 90% of redundancy cost.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62202473 and 62441230);
Science Fund for Creative Research Groups of the National Natural Science Foundation of China (Grant Number: 62221003);
Key Program of the National Natural Science Foundation of China (Grant Number: 61932016 and 62132011);
National Science Foundation for Distinguished Young Scholars of China (Grant Number: 62425201)
Concept and preliminary structural analysis of a crater-covering dome for future lunar habitats
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The datasets utilised and/or analysed during the current study are available from the corresponding author upon reasonable request.The prospect of establishing a human presence on the Moon has transitioned from the realm of science fiction to an achievable goal. The long-term objective of the Artemis program is to establish a habitat on the Moon that would enable crews to remain on the lunar surface for extended periods. The developmental pathway for such facilities culminates in structures that are manufactured and constructed predominantly from materials sourced on the lunar surface, in alignment with the In-Situ Resource Utilization (ISRU) concept. This paper presents a conceptual lunar habitat that was created by covering 17 m diameter crater in the Mare Tranquillitatis with a structure made from a lunar regolith-based geopolymer. Five shapes of the covering lid were analysed, including: two concave domes with rises of 0.5 m and 1 m; a flat circular slab; and two convex domes with rises of 0.5 m and 1 m. Structural analysis was performed using the Finite Element Method, employing material data from existing literature as well as original strength tests of alkali-activated material based on lunar regolith simulants conducted by the authors. Each model of structure was subjected to dead loads and varying levels of internal air pressure. The numerical analysis revealed the advantages of concave-shaped structures, where internal pressure induced compressive stress within the cross-section, thereby mitigating the risks of air leakage and decompression of the habitat and taking advantage of material in which compressive strength is higher than tensile strength.Research funded by Silesian University of Technology, grant number: 03/020/BKM24/0174. The collaboration resulted from CSTO2NE project co-funded by Horizon Europe MSCA Staff Exchange GA No. 101086302 and a grant from the Ministry of Science and Higher Education of the Republic of Poland under the name βInternational Co-financed Projects No. 5470/HE/2023/2β
On Compulsory Licensing of Trade Secrets to Safeguard Public Health
No full textA preprint version of the article is available at SSRN: https://ssrn.com/abstract=4771745 . It has not been certified by peer review.In the pharmaceutical sector an increasing number of new medicines are large-molecule products, namely biologics derived from living organisms, rather than small-molecule drugs synthesised from chemicals. Unlike small-molecule medicines, which are relatively easy to manufacture, large-molecule products are less stable and harder to produce. We investigate whether the current UK legal system provides an appropriate balance between the protection provided to technology owners and the public interest in accessing medical technologies, especially in times of emergencies. At present, UK law facilitates compulsory licensing of patents but has no equivalent scheme for trade secrets. Our analysis of the legal constraints on potential reforms suggests that a mechanism for compulsory licensing of trade secrets would be compatible with UK domestic law, the European Convention on Human Rights, the World Trade Organization Agreement on Trade-Related Aspects of Intellectual Property Rights and other international agreements, provided appropriate safeguards are put in place to balance the rights of intellectual property holders with the public interest. The article contributes a detailed framework for the compulsory licensing of trade secrets, drawing parallels with voluntary technology transfer agreements, including provisions for defining the scope of transfer, maintaining confidentiality, restricting future use, providing fair compensation and ensuring enforceability
βSpace invadersβ revisited: counter-narratives of two (b)older south Asian female academics
Get PDFIn this paper, we revisit Puwarβs concept of βspace invaderβ as two (b)older South Asian female academics at a later stage in their professional lives. Drawing on Critical Race Theory and a counter-storytelling approach, we reflexively narrate our analysis of a series of research conversations through the catalyst of βspace invaderβ, and how this led us to explore stages of voice across space and time. Including conversational metaphors in places, we proudly centre our mother tongue languages (Hindi and Panjabi) as we reflect through the scents of our storied memories. We discuss how our professional and community-based equity roles and experiences entwine as an embodiment of driving racial justice. We use metaphoric hooks to chart our herstories of hope as we navigate White fragility and often hostile spaces, seeking refuge in βsafeβ and supportive spaces as a form of collective healing through speaking, listening and simply being βourselvesβ. Through our research conversations, we analyse the traumas, isolation and contentment of working at the margins of decision-making spaces, and the challenges of βtrespassingβ across boundaries towards the centre, where we have never really belonged, yet courageously taken the journey. βSpace Invadersβ revisited has required us both to analyse the painful racialised memories of our bodies, minds and souls, the visceral violence of racism, the silencing (and confident roars) of our voices, and racial battle fatigue
Energy Minimization for UAV-Enabled Covert Offloading MEC Systems
Get PDFIn this work, a covert offloading framework is established for unmanned aerial vehicle (UAV) system. Specifically, one UAV-enabled mobile edge computing (MEC) server is deployed to assist the offloading for multiple ground users, while the offloading behavior might be exposed and detected due to the existence of a malicious warden. To enhance the covertness, each user splits a part of its power to transmit jamming signal, and the relationship between users' power split ratio and the warden's minimum detection error probability (DEP) is investigated. Then, an efficient energy minimization algorithm is designed by optimizing users' power split, computing resource allocation and deployment of the UAV-MEC server jointly, subject to specific covertness, power and transmission rate constraints. Finally, simulation results are provided to demonstrate the effectiveness of our covert offloading design.This work was supported in part by the National Key R&D Program
of China under Grant 2023YFB2603500, in part by the National Natural
Science Foundation of China under Grant 62271419, Grant 62301462, Grant 62361136810, and Grant U2268201, in part by UKRI Postdoc Guarantee.
project S-ISAC [grant number EP/Z002435/1] and EU MSCA Postdoctoral
Fellowships [grant number 101154926]
Residual Income Valuation and Stock Returns. Evidence from a Value-to-Price Investment Strategy
Get PDFJEL classification: G11, G12, G14.This is a working paper. It is not certified by peer review.This paper contributes to the accounting and asset pricing anomalies literature by investigating the performance of value-to-price strategies, and the relationship between value-to-price ratio and several risk proxies. If the value-to-price ratio successfully predicts future returns at stock level, we hypothesize that portfolio sorts based on the V/P ratio generate excess returns and consist of companies that are undervalued for prolonged periods. Overlapping and non-overlapping returns are used to test the risk/mispricing explanation of the value-to-price strategy. Results, for the US market from 1987 to 2015, show that high V/P portfolios outperform low V/P portfolios across horizons extending from one to three years. The V/P ratio is positively correlated to future stock returns after controlling for several firm characteristics, which are well known risk proxies. Findings also indicate that profitability and investment add explanatory power to the Fama and French three factor model and for stocks with V/P ratio close to 1. However, these factors cannot explain all variation in excess returns especially for years two and three and for stocks with high V/P ratio. Finally, portfolios with the highest V/P stocks pick companies that are significantly mispriced relative to their equity (investment) and profitability growth persistence in the future
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