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Transfer Learning-Enhanced Multi-objective Predictive Control for Electric Vehicular Platoon
Get PDFThe growing adoption of connected and automated vehicles has led to significant advancements in intelligent transportation. The computational efficiency stands as a critical bottleneck in the commercialization of connected and automated vehicles. This paper proposes a novel transfer learning-enhanced multi-objective predictive control strategy to mitigate the adverse effects of computational burden for vehicular platoon. A data-driven platoon model is established with subspace identification to characterize the non-ideal driving behavior and complex powertrain structure of electric vehicles. To balance multi-objective conflicts among driving safety, driving comfort and energy economy, a multi-objective cost function incorporating the predictive sequence is designed. Then, a grey wolf optimizer is devised to guide the search process, with the goal of achieving globally optimal trade-offs. Here, the knowledge of vehicle in the source domain, such as data-driven model and controller hyperparameters, is transferred to vehicles in the target domain. Based on the knowledge, each vehicle in the target domain just should update the knowledge in terms of the individual dynamic characteristic and tasks. With in this mind, a transfer learning-enhanced multi-objective predictive control strategy is developed to enhance the performance of tasks in the target domain. Finally, a hardware-in-the-loop experiment platform with the Carmaker and the driving simulator is conducted. The experimental results demonstrate that our proposed transfer learning-enhanced multi-objective predictive control strategy could improve the 28.8% computational efficiency while ensuring the satisfied platoon tracking performance
Atomic-Scale Optical Microscopy with Continuous-Wave Mid-Infrared Radiation
Get PDFUnderstanding matter at the most fundamental level requires optical microscopy with ever-higher spatial resolution. Scanning near-field optical microscopy (SNOM) has enabled important advances, circumventing the diffraction limit of light by confining it to the apex of a sharp metallic tip. However, the mesoscopic tip geometry restricts the spatial resolution to the nanometer scale. Here, using a conventional tabletop continuous-wave mid-infrared laser and intensity-based detection we observe optical signals modulated on Ångstrom length scales, consistent with light emission from atomically confined tunneling currents. The emergence of near-field optical tunneling emission (NOTE) ─ considered a strong-field excitation process ─ under continuous-wave driving is remarkable, as it typically requires ultrashort high-intensity laser pulses. Further, we find that anharmonic tip oscillation can influence the signal and propose strategies to mitigate this effect. Our findings enable the use of this tunneling-mediated contrast mechanism with standard optical setups, establishing a pathway to optical imaging with unprecedented resolution.</p
Textile-Reinforced Mortar (TRM) for retrofitting masonry structures:advantages, challenges and future potential
Get PDFTextile-reinforced mortar (TRM) has emerged as a promising technique for retrofitting masonry structures due to its distinct advantages over traditional methods, such as increased strength and deformation capacity, improved crack resistance, and enhanced durability. This paper presents a comprehensive review of TRM technologies, highlighting their advantages over traditional fibre-reinforced polymer (FRP) systems, including improved fire resistance, reversibility, and compatibility with historic substrates. This paper also provide insights into the current state of knowledge, reviews the benefits, practical limitations, and future potential of TRM in retrofitting applications. The benefits include its lightweight nature, ease of application, and compatibility with various substrate materials, making it suitable for a wide range of masonry structures. Practical limitations, such as the need for skilled application and concerns over long-term performance, are also discussed critically. Lastly, the study explores recent innovations in textile materials and eco-friendly mortars, emphasizing the role of TRM in advancing sustainable construction practices. By identifying current challenges and future research directions, this work aims to support the broader adoption of TRM systems in both heritage conservation and modern structural engineering
Potentially modifiable factors associated with longitudinal health-related quality of life in the National Unified Renal Translational Research Enterprise CKD (NURTuRE-CKD) cohort
No full textIntroductionPeople with non-dialysis-dependent chronic kidney disease (NDD-CKD) experience worse health-related quality of life (HRQoL) than those without. This study hypothesised that potentially modifiable factors affecting longitudinal HRQoL in a NDD-CKD cohort could be identified in order to identify potential therapeutic targets for improving HRQoL outcomes.MethodsThe NURTuRE-CKD cohort study recruited 2996 participants with NDD-CKD from UK nephrology centres from 2017. Sociodemographic, medical history, medication, anthropometric, biomarker and patient-reported outcome measure (PROM) data were collected at baseline and first follow-up. HRQoL was measured at second follow-up. The primary outcome was HRQoL measured by EQ-5D-5L, mapped to EQ-5D-3L index value and visual analogue score (VAS). Multivariable mixed effects linear regression models were adjusted and fit to examine the effect of potentially modifiable factors at baseline on longitudinal EQ-5D-3L index value. Similar models were also fit to assess the effects of change in these factors across follow-up on index value and VAS.Results2062 participants (68.8%) attended first and 1019 (34.0%) second follow-up. EQ-5D-5L responses worsened over time for index value, VAS and in each dimension. Baseline factors independently associated with worse longitudinal HRQoL were obesity, smoking, sarcopenia, pain, breathlessness, weakness, anxiety, depression and raised parathyroid hormone (PTH), whereas renin-angiotensin-system inhibitor use at baseline was associated with improved HRQoL. The status of factors across follow-up such as persistent obesity, new sarcopenia, increasing phosphate, new and persistent anxiety and depression, and worsening pain were associated with worse HRQoL, whereas improved acidosis, improved pain and weakness were associated with improved HRQoL.ConclusionSeveral potentially modifiable factors independently associated with HRQoL, and NDD-CKD interventions should consider these as therapeutic targets, as well as part of holistic CKD care
Machine Learning powered Design of Eco-Friendly Prestressed Concrete Sleepers
No full textPrestressed concrete sleepers are integral to structural safety of railway infrastructures. Industry challenges have been encountered in reducing the carbon footprint of this vital railway component. This research is therefore the first to establish machine learning (ML) techniques to design and optimise embodied carbon (EC) of prestressed concrete railway sleepers. To achieve this, over 3,000 datasets from industrial design sources was collected, through a combination of experimental predictions with EN 13230 compliance, and design data. Advanced ML models (Bayesian ridge, Random Forest and Deep learning) have been established to predict and optimize both capacity and embodied carbon impact of eco-friendly prestressed concrete sleepers. The designed machine learning models exhibit excellent outcome for both capacity prediction and carbon prediction. Our results reveal that Bayesian Ridge (R2 = 1.0000) displays the optimum performance for carbon prediction. Bayesian ridge and random forest models appear better for sleepers’ capacity and carbon predictions. The insight offers new reliable tools for the capacity design of railway sleepers while reducing environmental impact, practically driving decarbonization in the railway industry and potentially leading to time and cost savings
The biosocial life of nostalgia, memory, and emotion
No full textIncorporation of the body's biological processes has a long history of being tentatively applied in geography at the risk of being deemed ‘deterministic’. This paper, however, develops an original conceptual approach, ‘biosocial geography’, to consider the body’s social and biological worlds in tandem. And in doing so, it demonstrates how a consideration of biological/neurological processes that enrich the study of memory and emotion. Specifically, this paper incorporates biological knowledge of neurological networks to enhance geography’s understanding of nostalgia, a bittersweet emotional response to the past, to demonstrate how the processes of nostalgia can enrich an individual’s connection with their immediate environment. Drawing upon in-depth interviews, mobile video ethnography, four biosensing measures (heart rate, electrodermal activity, skin temperature, and blood volume pulse), and GPS tracking from residents in three areas of Birmingham (UK), it is shown that nostalgia is a moment where the entanglement of the body and its surroundings establishes an emotional and memorial flow between bodies and space. This paper demonstrates a union of conceptual and methodological developments in the biological sciences to develop a novel way to investigate memory that incorporates knowledge from the cognitive/biological sciences and social sciences to enrich understandings of body, memory, emotion, and place
Formation of (Ti,W)Fe<sub>2</sub> C14 laves phase in the W-Ti-Fe system and the impact on mechanical properties
Get PDFTungsten-based alloys utilising coherent intermetallic strengthening offer a route to improved high temperature strength. Recently proposed W-Ti-Fe alloys employ B2 TiFe phase in an A2 BCC matrix to achieve this strengthening, however, other phases such as the TiFe2 Laves phase can form at higher temperatures. In this study, the formation of the (Ti,W)Fe2 C14 phase in a BCC W-rich matrix is observed in a W–16Ti–4Fe (at%) alloy produced by vacuum arc-melting and annealing at 1400 °C. There was no evidence for the formation of either the TiFe B2 or W6Fe7 μ phase from analysis of the TEM diffraction patterns. The C14 Laves phase was found to have a composition of 8.8 ± 0.2 W, 23.3 ± 0.2Ti and 68.0 ± 0.8Fe (at%) consistent with (Ti,W)Fe2. This formed a continuous region along the boundaries between the W-rich BCC prior-dendrites, as well as in smaller isolated precipitates. The prior dendritic regions consisted of W-rich BCC phase with a composition of 84.10 ± 0.41 W, 13.94 ± 0.73Ti and 1.94 ± 0.73Fe (at%). Thermodynamic calculations using CALPHAD predicted the formation of a W rich BCC phase and a Ti and Fe rich liquid phase initially, which was not consistent with the presented experimental findings. A revised calculation which reduced the stability of the μ phase at high temperatures led to an improved prediction, consistent with the experimental results. To investigate the mechanical impact of the C14 phase, a combination of Continuous Stiffness Measurement (CSM) nanoindentation and high-speed nanoindentation mapping was used to measure the comparative hardness of the matrix and precipitate phases, which showed that the C14 phase exhibits a very high hardness relative to the W-rich matrix phase. An average nanohardness of 6.25 ± 0.03 GPa was measured at depth of 1.5 μm using CSM nanoindentation, which is higher than comparable B2 reinforced WTiFe alloys.</p
Smart Contracts and SME Resilience:Business Model Adaptation and International Considerations
Get PDFSmart contracts (SCs), appended to a blockchain, protect digital environments and their resources, processes and structures, reducing mismatches between legal and actual rights and ownership. They enhance digital resilience by improving transparency, traceability and trust in digital transactions. Utilizing SCs requires businesses to adapt their models, revenue streams and customer relationships. For small and medium-sized enterprises (SMEs), SCs present challenges, requiring proactive decision-making for their effective utilization and the trade-offs involved. By employing the integrated multilayer ISM-MICMAC-SWARA framework (Interpretive Structural Modelling, Cross-Impact Matrix Multiplication Applied to Classification and Stepwise Weight Assessment Ratio Analysis), we explain the complex interrelationships among the challenges and propose mitigating risk management strategies. We identify technical limitations and human errors as key drivers, confidentiality and manipulation as linkage challenges and fraud and hacking as dependence challenges. These findings highlight the interconnected nature of the challenges and their impact on SMEs, and we emphasize the need for targeted resilience strategies. Our research highlights the global dimension of SC adoption. When deploying SCs, SMEs must navigate international regulations, cross-border transactions and cultural diversity. This global perspective informs smart contracts' strategic, business and organizational aspects. Our findings offer insights for academics, industry leaders, managers and policymakers seeking to understand the potential and risks of adopting SCs in SMEs
Living with palindromic rheumatism:a qualitative interview study
Get PDFObjectivesPalindromic rheumatism (PR) is an unpredictable and under-researched inflammatory condition, and patients with PR are at risk of developing inflammatory arthritis (IA). This study aimed to explore patients’ perceptions and experiences of living with PR, including symptoms, impact, treatment outcomes and potential progression to IA.MethodsPatients were recruited from ongoing cohort studies identifying individuals at risk of developing IA. Semi-structured interviews were conducted at two UK sites. Data were analysed using reflexive thematic analysis. Patient research partners co-produced the interview schedule and contributed to coding decisions.ResultsEight patients were interviewed. Three themes (seven subthemes) were identified: experiencing symptoms (symptoms, perceptions of triggers, referral experiences); impact of symptoms (activity limitations, psychological impact); treatment expectations and knowledge seeking (treatment outcomes and progression, information and support needs). Symptom severity was likened to that associated with severe physical injury, and PR impacted on daily activities and caused psychological distress, but referral delays were frequently reported. Patients expressed concerns about taking medication for PR, primarily due to side effects. Most highlighted a lack of information about PR (e.g. medication options and self-management advice) but varied in how much they wanted to understand about PR progression and treatment options.ConclusionThis study captured valuable insights into the perceptions and experiences of PR, from the perspective of patients. Findings highlight the severity of symptoms and impact of the condition. Further work to standardize classification criteria and outcome measurement in PR is critical to facilitate meaningful clinical trials in this area.</div
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