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The performance of missing transverse momentum reconstruction and its significance with the ATLAS detector using 140 fb(-1) of root s = 13 TeV pp collisions
No full textThis paper presents the reconstruction ofmissing transverse momentum (pmissT ) in proton–proton collisions, at a center-of-mass energy of 13 TeV. This is a challenging task involving many detector inputs, combining fully calibrated electrons, muons, photons, hadronically decaying τ -leptons, hadronic jets, and soft activity from remaining tracks. Possible double counting of momentum is avoided by applying a signal ambiguity resolution procedure which rejects detector inputs that have already been used...ATLAS Collaboratio
Difficulty of Achieving High Precision with Low Base Rates for High-Stakes Intervention
No full textAutomated detectors are routinely used in learning analytics for high-stakes, high-risk interventions. Such interventions depend on detectors with a low rate of false positives (i.e., predicting the construct is present when it is not present) in order to avoid giving an intervention where it is not needed, especially when such interventions can be costly or even harmful. This in turn suggests that such a detector needs to have high precision at the cut-off used by the detector for decision-making. However, high precision is difficult to achieve for the common case where the base rate of the target construct is low. In this paper, we demonstrate the difficulty of achieving high precision for low base rates, and demonstrate how other metrics (such as F1, Kappa, Specificity, and AUC ROC) are insufficient for this specific use case and situation, despite their merits and advantages for other use cases and situations
AI Model Modulation with Logits Redistribution
No full textPoster Session 9Large-scale models are typically adapted to meet the diverse requirements of model owners and users. However, maintaining multiple specialized versions of the model is inefficient. In response, we propose Aim, a novel model modulation paradigm that enables a single model to exhibit diverse behaviors to meet the specific end requirements. Aim enables two key modulation modes: utility and focus modulations. The former provides model owners with dynamic control over output quality to deliver varying utility levels, and the latter offers users precise control to shift model’s focused input features. Aim introduces a logits redistribution strategy that operates in a training data-agnostic and retraining-free manner. We establish a formal foundation to ensure Aim’s regulation capability, based on the statistical properties of logits ordering via joint probability distributions. Our evaluation confirms Aim’s practicality and versatility for AI model modulation, with tasks spanning image classification, semantic segmentation and text generation, and prevalent architectures including ResNet, SegFormer and Llama.Zihan Wang, Zhongkui Ma, Xinguo Feng, Zhiyang Mei, Ethan Ma, Derui Wang, Minhui Xue, Guangdong Ba
Towards net zero aviation: exploring safe hydrogen refuelling at airports
No full textData source: Supplementary materials, https://doi.org/10.1016/j.jatrs.2024.100048Hydrogen flight is one important part of the way to net zero aviation. However, safety challenges around refuelling are not well understood but are paramount to enable airports to be more comfortable with using hydrogen in the airport environment. This study investigates safety considerations of hydrogen aircraft refuelling at airports. Technical and human factor risks are explored as well as risk assessment models. Two focus groups were conducted in 2022. Data was analysed using NVivo, revealing major themes including the mental and physical performance of refuellers, technical aspects of refuelling stations, environmental factors, and the use of risk assessment models. These findings contribute significantly to an understanding of hydrogen refuelling challenges in busy airport environments. Recommendations help airports preparing for hydrogen as a fuel source, further supporting the transition towards net zero aviation. Future research could focus on carrying out experiments analysing chemical reactions between kerosene and hydrogen vapours and testing the identified risk assessment tools in different airport environments
Impact of Fire-Retardant coating on the residual compressive strength of hybrid Fibre-Reinforced polymer tubes exposed to elevated temperature
No full textEnhancing the fire resistance of fibre-reinforced polymer (FRP) composites is vital for ensuring structural safety in fire-prone infrastructures. This study investigates the thermal degradation and residual compressive strength of filament-wound hybrid fibre-reinforced polymer (HFRP) tubes exposed to temperatures ranging from 25 °C to 350 °C. The tubes, composed of 50 % carbon fibre and 50 % E-glass fibre, with a 60:40 fibre–resin ratio, were subjected to thermal conditioning to simulate real-world fire exposure. For uncoated tubes, a balance between resin post-curing and pyrolytic degradation preserves compressive strength up to 200 °C, but strength sharply decreases beyond this threshold due to intensified pyrolysis, with virtually no residual strength at 350 °C. Fire-retardant coatings, Nullifire SC902, activate above 200 °C, providing limited protection, and the samples retain 20–21 % of their original compressive strength at 350 °C. As revealed by complementary Scanning Electron Microscopy (SEM), Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), and Fourier Transform Infrared Spectroscopy (FTIR) analyses, key degradation mechanisms include matrix degradation and cracking and fibre exposure. Overall, the fire-retardant coating offers some benefits at higher temperatures, but its effectiveness is limited by activation thresholds and prolonged exposure. The findings show the need for further optimisation of fire-resistant systems for HFRP composites to improve their safety and durability in fire-prone applications
Mixed methods framework for implementation research in the architecture, engineering, construction and operations industry
No full textThe adoption of novel construction technologies, practices, and policies, despite the existence of credible and feasible research, remains a significant challenge. This issue is further compounded by the limited number of comprehensive studies on research design specifically aimed at implementation. In response to this gap, the present study seeks to develop a framework that enhances the dissemination of innovative research outputs by integrating implementation science principles within mixed research designs. The research is conducted as a systematic literature review (SLR), wherein 47 relevant sources were selected following two rounds of filtration based on the preferred reporting items for systematic meta-analysis (PRISMA) guidelines.
The selected studies were categorised according to their year of publication and source, employing descriptive analysis. A subsequent thematic analysis of these sources revealed the potential applications of implementation science, including the development of frameworks, policy formulation, implementation strategies, and the analysis of framework users. The resulting framework posits that implementation domains and objectives must be considered in conjunction with factors such as research priorities, function, timing, dependencies, and integration with research methods. This study underscores the importance of designing research with a focus on implementation to enhance the effective dissemination of research findings within the construction industry
Corporate sexual orientation equality and dividend payout
No full textData source: supplementary material, https://doi.org/10.1080/1351847X.2025.2461212We examine the effect of a firm’s Lesbian, Gay, Bisexual, and Transgender (LGBT)-friendly policies on its dividend payout and find a significantly positive association. We propose two alternate arguments to explain this association. The disbursement of higher dividends could potentially alleviate the perception of agency costs arising from better treatment of LGBT employees. Alternatively, firms could pay higher dividends (i.e. deplete cash) to increase their bargaining power with labor. Our results support the agency argument. Our findings are robust to alternative models and measures
Secure electric vehicle charging infrastructure in smart cities: a blockchain-based smart Contract approach
No full textIncreasing adoption of electric vehicles (EVs) and the expansion of EV charging infrastructure present opportunities for enhancing sustainable transportation within smart cities. However, the interconnected nature of EV charging stations (EVCSs) exposes this infrastructure to various cyber threats, including false data injection, man-in-the-middle attacks, malware intrusions, and denial of service attacks. Financial attacks, such as false billing and theft of credit card information, also pose significant risks to EV users. In this work, we propose a Hyperledger Fabric-based blockchain network for EVCSs to mitigate these risks. The proposed blockchain network utilizes smart contracts to manage key processes such as authentication, charging session management, and payment verification in a secure and decentralized manner. By detecting and mitigating malicious data tampering or unauthorized access, the blockchain system enhances the resilience of EVCS networks. A comparative analysis of pre- and post-implementation of the proposed blockchain network demonstrates how it thwarts current cyberattacks in the EVCS infrastructure. Our analyses include performance metrics using the benchmark Hyperledger Caliper test, which shows the proposed solution’s low latency for real-time operations and scalability to accommodate the growth of EV infrastructure. Deployment of this blockchain-enhanced security mechanism will increase user trust and reliability in EVCS systems
LiDAR-based scaling of OpenSim musculoskeletal human models is a viable alternative to marker-based approaches - A preliminary study.
No full textData source: supplementary data, https://doi.org/10.1016/j.jbiomech.2024.112439Biomechanical analysis is increasingly being undertaken in field-based settings, often using inertial sensors or video-based pose estimation. These advancements necessitate more practical and accessible scaling methods as alternatives to traditional laboratory-based techniques like optical marker-based scaling. LiDAR scanning is a technique that could provide a reliable and efficient means of scaling biomechanical models. This study tested a scaling method for OpenSim models and comparing outcomes with those of traditional marker-based scaling in healthy adult participants. An anatomical skeleton was inferred from a LiDAR scan taken with an iPad. Key skeletal landmarks were then used to generate scaling factors using statistical shape models. The scaling factors of the pelvis, femur and tibia body segments derived from the LiDAR-based method demonstrated excellent reliability, with repeated scans of seven subjects producing an ICC value of 0.961. When comparing the scaling factors of eight additional subjects with the current gold standard technique of marker-based optical motion capture, a Bland-Altman analysis revealed differences of -0.5% ± 5.3 (95CI = [-10.8, 10]). Joint kinematics calculated using LiDAR scaled models had an average RMSD of 3.7° ± 0.1°when compared with those calculated with a marker-scaled model. These results indicate that a LiDAR-based scaling method can address the challenge of accurate and reliable scaling methods that are practical for use in the field. Future work with larger cohorts and diverse populations, and scaling of other body segments will provide further validation and enhance the generalizability and robustness of this approach
Mesoscale analysis of rubber particle effect on flexural strength of crumb rubber concrete
No full textFlexural strength is an indirect indicator for measuring the concrete's resistance to tensile stress caused by bending, shrinkage and temperature changes. This study aims to study the flexural strength of crumb rubber concrete (CRC) through mesoscale simulation and experimental testing. The internal structure of CRC was regarded as a five-phase material consisting of rubber, coarse aggregate, mortar, coarse aggregate-mortar interfacial transition zone (A-M ITZ), and rubber-mortar interfacial transition zone (R-M ITZ). The flexural strength of CRC specimens containing rubber particles of different contents, shapes, and sizes was calculated and compared.
Mesoscale simulation showed that the addition of rubber reduces the flexural strength of concrete, and the reduction rate is mainly controlled by the content rather than the size, shape, and distribution of rubber particles. The thickness of R-M ITZ is around 0.05 mm, and its effect on the flexural strength of CRC is as low as 1.15% which can be ignored. The incorporation of rubber particles increases the heterogeneity of the internal structure of concrete, which increases the discreteness of the concrete's flexural strength. Numerical simulation also verified that treating the rubber particles as pores did not change the damage pattern of the CRC specimens and resulted in negligible differences in flexural strength. Rubber particles can be simulated through pores when analyze their effect on the flexural strength of concrete