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Parametric set-theoretic Yang-Baxter equation: p-racks, solutions & quantum algebras
No full textThe theory of the parametric set-theoretic Yang-Baxter equation is established from a purely algebraic point of view. The first step towards this objective is the introduction of certain generalizations of the familiar shelves and racks called parametric (p)-shelves and racks. These objects satisfy a parametric self-distributivity condition and lead to solutions of the Yang-Baxter equation. Novel, non-reversible solutions are obtained from p-shelf/rack solutions by a suitable parametric twist, whereas all reversible set-theoretic solutions are reduced to the identity map via a parametric twist. The universal algebras associated to both p-rack and generic parametric, set-theoretic solutions are next presented and the corresponding universal ℛ-matrices are derived. The admissible universal Drinfel’d twist is constructed allowing the derivation of the general settheoretic universal ℛ-matrix. By introducing the concept of a parametric coproduct we prove the existence of a parametric co-associativity. We show that the parametric coproduct is an algebra homomorphism and the universal ℛ-matrices satisfy intertwining relations with the algebra coproducts
Parametric set-theoretic Yang-Baxter equation: p-racks, solutions & quantum algebras
No full textThe theory of the parametric set-theoretic Yang-Baxter equation is established from a purely algebraic point of view. The first step towards this objective is the introduction of certain generalizations of the familiar shelves and racks called parametric (p)-shelves and racks. These objects satisfy a parametric self-distributivity condition and lead to solutions of the Yang-Baxter equation. Novel, non-reversible solutions are obtained from p-shelf/rack solutions by a suitable parametric twist, whereas all reversible set-theoretic solutions are reduced to the identity map via a parametric twist. The universal algebras associated to both p-rack and generic parametric, set-theoretic solutions are next presented and the corresponding universal ℛ-matrices are derived. The admissible universal Drinfel’d twist is constructed allowing the derivation of the general settheoretic universal ℛ-matrix. By introducing the concept of a parametric coproduct we prove the existence of a parametric co-associativity. We show that the parametric coproduct is an algebra homomorphism and the universal ℛ-matrices satisfy intertwining relations with the algebra coproducts
Slamming Loads Induced by Dam-Break Flow on Land-Based Oscillating Water Columns: Numerical and Experimental Study
No full textA 3D Reynolds-Averaged Navier-Stokes (RANS) flow solver with a Volume of Fluid (VOF) surface capturing scheme is used to investigate the dam-break flow induced slamming impacts on land-based oscillating water columns (OWC). Comprehensive experiments are conducted to validate the numerical model. It is found that the compressible RANS-VOF solver more accurately captures the key physical processes in this complex fluid-structure interaction process than the incompressible solver. The complete process of dam-break flow impact on OWCs is analyzed in detail, focusing on the relationship between peak forces, moments, slamming pressures, and fluid behaviors. It is found that the peaked vertical loads due to air pressure on the deck of the OWC chamber are non-negligible, particularly for small opening ratios (<3.5%), which has not been previously reported. Additionally, the air pressure on the deck significantly contributes to the moment of the OWC caisson. The distribution of slamming pressure on the front wall, corresponding to peak loading, resembles that of breaking waves in realistic seas. This implies that dam-break flow tests can be used to capture the fundamental physics behind the strong nonlinear waves interacting with OWCs. Numerical simulations are performed to examine the influence of the opening ratio of the OWC chamber on slamming characteristics. It is found that slamming loads on the OWC decrease rapidly with increasing opening ratio in from 0% to 3.5%. However, when the opening ratio exceeds the critical value of 3.5%, the slamming loads change only slightly. Furthermore, during the slamming process, the air pressure inside the chamber is proportional to the velocity of the water surface inside the chamber.</p
The State of Garment Repair and Alteration Services in the UK: Typology, Evaluation of Online Information and Thematic Analysis of Customer Reviews
No full textThe fashion industry is a significant contributor to global environmental degradation, driving up carbon emissions and resource consumption. Many fashion consumers feel guilt associated with contributing to this damage. While garment repair and alteration services (GRAS) offer a pathway to mitigate these impacts by extending the lifespan of clothing, consumer engagement with these services remains low. This study investigates the state of commercial GRAS in the UK, identifying barriers to consumer participation and their potential role in fostering sustainable behaviour. Through a comprehensive typology of UK GRAS providers and a thematic analysis of customer reviews, we reveal obstacles such as limited repair skills, unclear service information, and gaps in consumer trust. Our findings suggest that bridging these informational and service quality gaps could promote greater use of GRAS, aligning the fashion industry more closely with circular economy principles. In addition, we highlight the potential for GRAS to enhance well-being by developing consumer's emotional attachment to clothing and positive feelings. These findings underscore the dual benefits of GRAS for environmental sustainability and consumer well-being, suggesting broader applications for GRAS in shaping more sustainable consumption patterns
The State of Garment Repair and Alteration Services in the UK: Typology, Evaluation of Online Information and Thematic Analysis of Customer Reviews
No full textThe fashion industry is a significant contributor to global environmental degradation, driving up carbon emissions and resource consumption. Many fashion consumers feel guilt associated with contributing to this damage. While garment repair and alteration services (GRAS) offer a pathway to mitigate these impacts by extending the lifespan of clothing, consumer engagement with these services remains low. This study investigates the state of commercial GRAS in the UK, identifying barriers to consumer participation and their potential role in fostering sustainable behaviour. Through a comprehensive typology of UK GRAS providers and a thematic analysis of customer reviews, we reveal obstacles such as limited repair skills, unclear service information, and gaps in consumer trust. Our findings suggest that bridging these informational and service quality gaps could promote greater use of GRAS, aligning the fashion industry more closely with circular economy principles. In addition, we highlight the potential for GRAS to enhance well-being by developing consumer's emotional attachment to clothing and positive feelings. These findings underscore the dual benefits of GRAS for environmental sustainability and consumer well-being, suggesting broader applications for GRAS in shaping more sustainable consumption patterns
Bias-Variance Decomposition Knowledge Distillation for Medical Image Segmentation
No full textKnowledge distillation essentially maximizes the mutual information between teacher and student networks. Typically, a variational distribution is introduced to maximize the variational lower bound. However, the heteroscedastic noises derived from this distribution are often unstable, leading to unreliable data-uncertainty modeling. Our research identifies that bias-variance coupling in knowledge distillation causes this instability. We thus propose Bias-variance dEcomposition kNowledge dIstillatioN (BENIN) approach. Initially, we use bias-variance decomposition to decouple these components. Subsequently, we design a lightweight Feature Frequency Expectation Estimation Module (FF-EEM) to estimate the student's prediction expectation, which helps compute bias and variance. Variance learning measures data uncertainty in the teacher's prediction. A balance factor addresses the bias-variance dilemma. Lastly, the bias-variance decomposition distillation loss enables the student to learn valuable knowledge while reducing noise. Experiments on Synapse and Lits17 medical-image-segmentation datasets validate BENIN's effectiveness. FF-EEM also mitigates high-frequency noise from high mask rates, enhancing data-uncertainty estimation and visualization. Our code is available at https://github.com/duanzhongjian/BENIN
Investigating the effect of climate-related hazards on claim frequency prediction in motor insurance with incomplete data
No full textA climate-related dataset provided by a Greek insurance company is analysed to quantify the risks that weather-related hazards, driven by climate change, pose to motor insurance. However, accurately modelling the relationship between these hazards and claim frequencies is challenging, largely because the available records are incomplete. Specifically, they capture only those storm events that result in at least one claim while omitting unreported events. To address this limitation, we introduce a novel class of compound frequency models for the joint analysis of storm occurrences and the corresponding claim frequencies with accurate predictive power. These models are specifically designed to recover the joint distribution of actual storm events and underlying claim processes even when faced with incomplete data. Additionally, we incorporate geospatial covariates to evaluate their influence on both storm occurrences and claim frequencies. Given Greece’s vulnerability to extreme weather due to its geographical position, understanding the influence of climate change on insurance risks is critical. Notably, our findings reveal a negative intrinsic dependence between actual storm counts and per-storm claim frequencies, suggesting potential diversification benefits for insurers as climate change leads to more frequent weather-related hazards
ABusing Social Media and Sentiment Analysis for Stock Market Prediction
No full textThe stock market plays a crucial role in shaping the global economy, yet the factors influencing its fluctuations remain a subject of ongoing analysis. In recent years, major stock prices have been increasingly impacted by public figures’ opinions shared on social media. These posts, which can be collected and analyzed without explicit consent, present an opportunity for stock market prediction using Sentiment Analysis. However, this raises ethical concerns and questions about the practicality of such an approach. Our research addresses these issues by utilising a widely recognized Kaggle dataset containing tweets about 25 publicly traded companies. After preprocessing the data, we systematically experimented with various classification algorithms and a transformer model. Our findings revealed that the pretrained bidirectional DistilBERT model achieved the highest accuracy at 82.79%. By visualizing the results and comparing them to actual stock prices, we demonstrate the feasibility of leveraging sentiment analysis for stock market predictions based on publicly available data
Seamounts of Cabo Verde: A review of their ecological and economic significance, anthropogenic impacts, and conservation needs
No full textThe deep-sea areas of the Cabo Verde Archipelago remain largely unexplored, with seamounts standing out as the most prominent and abundant geomorphological features. The ecological significance of these underwater structures is well-documented in various regions of the planet, as they often serve as biodiversity hotspots, stepping stones for species connectivity and, in some cases, areas with high levels of endemism. However, the biology and ecology of the seamounts around Cabo Verde are still largely unknown. Preliminary studies of the geomorphology, oceanographic characteristics and ecology of specific features suggest that the Cabo Verde seamount network — comprising 14 known conspicuous seamounts as well as smaller elevations less than 1000 m — harbours high biological diversity. That biodiversity associated with the Cabo Verde seamounts spans a wide range of forms, from microscopic organisms to cetaceans, encompassing both pelagic and benthic communities. Commercial activities associated with seamounts, in particular fishing, are a critical aspect to consider for ecosystem management. Evaluating their current uses, future prospects, and the existing and potential threats the Cabo Verde seamounts face is essential for effective and sustainable marine spatial planning. This study reviews and synthesises the current knowledge on the Cabo Verde seamounts within its Exclusive Economic Zone (EEZ), focusing on their environmental and biological aspects, including geology, oceanography, and associated biological communities. Key topics include primary production, zooplankton communities, benthic organisms, large vertebrates such as elasmobranchs, sea turtles, seabirds, and cetaceans, as well as microbes and trophic linkages. Additionally, this review explores the socio-economic dimensions linked to seamounts, highlighting their importance to the local economy and emphasizing the need for effective marine spatial management plans. These considerations are crucial for balancing conservation efforts with sustainable use, ensuring the long-term health of these vital underwater ecosystems.</p
Conceptualizing Critical Thinking Skills: An Empirical Study of Malaysian Undergraduate Students and Academic Staff
No full textAnalytical and creative thinking are essential skills for employers today. Higher education should therefore be about learning how to think, not just what to think. Despite general agreement on the purpose of university, not all students master thinking skills, in part due to widespread difficulties in comprehending what critical thinking is. Two studies sought to make more widely accessible critical thinking descriptions from a common taxonomy by Facione and to explore perceptions of their relative importance. In Study 1, 19 students and educators co-produced readable descriptions of critical thinking skills that were more understandable than the original set of descriptions, as measured by the Flesch–Kincaid metric. In Study 2, 406 students rated all core skills in the taxonomy as important, with no meaningful differences in opinion across discipline or study year. Students’ insights from the interviews in Study 1 supported this finding. Additionally, students expressed lower perceived self-efficacy in self-regulation skills, which they recognized as underdeveloped within their university curriculum. These findings have broad implications for Asian higher education by breaking down barriers to understanding critical thinking concepts, so that educators can design more engaging and effective learning experiences in the classroom
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