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A hybrid symbolic-numerical approach for ruled surface detection and parameterization
Full text linkRuled surfaces play a crucial role in geometric modeling and computer-aided design (CAD) due to their structural simplicity and broad practical applications. In this paper, we present a novel hybrid symbolic-numerical approach for determining whether an implicitly or parametrically defined surface is ruled.
Unlike previous methods, which are either purely symbolic or require complex numerical optimization techniques, our approach extends symbolic algorithms to numerical inputs given in an approximate form. This is a significant advancement, as previous symbolic methods required exact algebraic information. Our algorithm, in contrast, is designed to handle approximate data while preserving efficiency and robustness.
For implicitly defined surfaces, our method relies on computing two planar curve parameterizations. If these curves are rational, the surface is ruled. If they are only approximately rational, we introduce the concept of ϵ-ruled surfaces, allowing us to classify surfaces that are 'almost ruled” within a given numerical tolerance. For parametrically defined surfaces, we analyze whether an existing rational parameterization can be rewritten in the standard ruled form:
One of the key advantages of our method is its efficiency. Rather than relying on complex implicitization or high-dimensional computations, it only requires the parameterization of two curves, making it computationally efficient and practical for real-world applications Our results show that this hybrid symbolic-numeric framework significantly outperforms previous methods, particularly in handling geometric input data that is not perfectly exact. This breakthrough provides a powerful tool for geometric modeling, enabling more accurate and efficient ruled surface detection in industrial and scientific applications
Más allá del laboratorio : ciencia, talento y diplomacia científica entre España y EE. UU.
No full textPetrochemical Fantasies. The Art and Energy of American Comics [reseña de libro]
No full textReseña del libro: Daniel Worden, Petrochemical Fantasies. The Art and Energy of American Comics(Columbus: The Ohio State University Press, 2024), 212 pp
With or without oil "Nordsjøen" and the persistence of Norwegian exceptionalism
No full textFilms provide fertile ground for examining how arguments about the Anthropocene are produced. In "Nordsjøen" (The Burning Sea, 2021), an oil spill is an opportunity to lay out a perspective of Norway and its relationship with fossil fuels. This article shows how, through an exercise of effacing and erasures, the film bends three basic rules of the catastrophe genre to conceive a society that parallels central notions of Norwegian exceptionalism. The disappearance of a struggle between ‘good’ and ‘evil,’ the elimination of economic or political greed, and the respect for scientific knowledge allow for the display of a society without struggles, guaranteeing well-being and nurturing a relation with more-than-human nature. In this context, oil extraction is presented as an encapsulated episode that, while having provided economic affluence for the country, has not affected an otherwise romanticized idea of the relation with the tenets of national exceptionality: economic equality, consensual politics and harmony with nature.Las películas son un campo fértil para explorar la producción de argumentos sobre el Antropoceno. En "Nordsjøen" (Mar del Norte, 2021), un derrame petrolero es la oportunidad para exponer una perspectiva sobre Noruega y su relación con los combustibles fósiles. Este artículo muestra cómo, mediante un ejercicio de borramientos y recortes, la película manipula tres reglas básicas del género de catástrofe para presentar una sociedad en línea con las nociones centrales del excepcionalismo noruego. La desaparición del conflicto entre el bien y el mal, la eliminación de la avaricia política o económica y el respeto por el conocimiento científico ayudan a mostrar una sociedad sin conflictos, que garantiza el bienestar y el cuidado dela naturaleza más que humana. En este contexto, la extracción de petróleo es presentada como un episodio encapsulado que, además de haber provisto beneficios económicos para el país, no ha afectado la idea romantizada de la relación entre Noruega y las ideas fundantes de la excepcionalidad nacional: igualdad económica, consenso político y armonía con la naturaleza
Electric Vehicle Route Optimization: An End-to-End Learning Approach with Multi-Objective Planning
Full text linkTraditional routing algorithms optimizing for distance or travel time are inadequate for electric vehicles (EVs), which require energy-aware planning considering battery constraints and charging infrastructure. This work presents an energy-optimal routing system for EVs that integrates personalized consumption modeling with real-time environmental data. The system employs a Long Short-Term Memory (LSTM) neural network to predict State-of-Charge (SoC) consumption from real-world driving data, learning directly from spatiotemporal features including velocity, temperature, road inclination, and traveled distance. Unlike physics-based models requiring difficult-to-obtain parameters, this approach captures nonlinear dependencies and temporal patterns in energy consumption. The routing framework integrates static map data, dynamic traffic conditions, weather information, and charging station locations into a weighted graph representation. Edge costs reflect predicted SoC drops, while node penalties account for traffic congestion and charging opportunities. An enhanced A* algorithm finds optimal routes minimizing energy consumption. Experimental validation on a Nissan Leaf shows that the proposed end-to-end SoC estimator significantly outperforms traditional approaches. The model achieves an RMSE of 36.83 and an ?2 of 0.9374, corresponding to a 59.91% reduction in error compared to physics-based formulas. Real-world testing on various routes further confirms its accuracy, with a Mean Absolute Error in the total route SoC estimation of 2%, improving upon the 3.5% observed for commercial solutions.European UnionMinisterio de Ciencia, Innovación y UniversidadesAgencia Estatal de InvestigaciónComunidad de Madri
Far-reaching hunter-gatherer networks during the Last Glacial Maximum in Western Europe
Full text linkSocial networking is an essential feature of hunter-gatherer societies. It fosters the circulation of goods and information and enables kinship ties across different scales, including long-distance contacts. While such behaviors are
known since at least the Upper Palaeolithic, evidence for geographically extensive social networks remains scarce.
This evidence is limited to indirect inferences based on shared cultural traits, “art” styles, and symbolic items, while
lithic raw material movements are mostly local and regional, with few cases exceeding 300 kilometers. We provide
geochemical evidence for the largest confirmed distance between the source and discard location of a knapped
lithic object in Palaeolithic Europe. Solutrean artifacts discarded at Peña Capón, Central Iberia, were sourced in
Southwest France, 600 to 700 kilometers away. This demonstrates social networks of unprecedented geographic
scale maintained during ∼1400 years during the Last Glacial Maximum. It also suggests that stone tools were exchanged as symbolic items to solidify social contacts and sustain far-reaching networks as risk-buffering mechanisms among widely dispersed hunter-gatherers.European Research Council (ERC
Creencias y actitudes lingüísticas de estudiantes de español como lengua extranjera hacia la variación dialectal del español
Full text linkLa lengua española se caracteriza por ser pluricéntrica y plurinormativa, de manera que sus diferentes variedades se encuentran
teóricamente en pie de igualdad, según es defendido por la política panhispánica de la Real Academia Española y de la Asociación
de Academias de la Lengua Española. No obstante, esta circunstancia no impide que, de facto, existan normas más prestigiosas
y relevantes a nivel mundial. La enseñanza de ELE no es ajena a
esta circunstancia y la centralidad que tenga una variedad en los
planes de estudio va con frecuencia en detrimento del conocimiento de las demás. Las creencias y actitudes lingüísticas (CAL)
de los discentes hacia la diversidad geolectal son relevantes de
cara a la planificación lingüística y, por ello, esta monografía se
propone hacer una revisión de la bibliografía existente sobre esta
materia. En sus diversos capítulos, se revisarán de manera teórica
la metodología de estudio de las creencias y actitudes lingüísticas
junto con los trabajos publicados hasta la fecha con el objetivo de
servir de estado de la cuestión y de punto de partida para futuras
investigaciones
A probabilistic alert system for extreme wind events prediction using quantile regression ensembles
Full text linkAnticipar y mitigar el impacto de los eventos de viento extremo es cada vez más crítico a medida que la energía eólica se convierte en un componente central de los sistemas energéticos modernos. Sin embargo, los enfoques predictivos existentes a menudo tienen dificultades para capturar la incertidumbre y la variabilidad inherentes a los datos de viento, lo que limita su eficacia en la gestión del riesgo. Esta investigación tiene como objetivo desarrollar un sistema de alerta probabilístico que permita predecir de manera eficaz la ocurrencia de dichos eventos extremos. Para ello, se propone un marco novedoso que combina regresión cuantílica y estimación de densidad mediante núcleos, con el fin de construir un sistema de predicción en conjunto robusto. Al integrar las predicciones individuales de regresión cuantílica a través de múltiples cuantiles, el marco propuesto captura la variabilidad y la incertidumbre inherentes a los datos de viento. Además, las salidas probabilísticas del modelo en conjunto se calibran mediante regresión isotónica, lo que da lugar a distribuciones refinadas que se ajustan estrechamente a las tasas observadas de ocurrencia de eventos extremos. El marco fue validado utilizando datos reales de un parque eólico en España, mostrando mejoras sustanciales con respecto a los clasificadores binarios probabilísticos convencionales, tanto en precisión como en calibración de las probabilidades de eventos extremos. Estos resultados ponen de relieve el potencial del sistema propuesto para mejorar la toma de decisiones operativas y la resiliencia de la infraestructura de energía eólica frente a condiciones meteorológicas extremas.Anticipating and mitigating the impact of extreme wind events is increasingly critical as wind power becomes a central component of modern energy systems. However, existing predictive approaches often struggle to capture the uncertainty and variability inherent in wind data, limiting their effectiveness in risk management. This research aims to develop a probabilistic alert system to predict the occurrence of such extreme events effectively. To achieve this, a novel framework is proposed, combining quantile regression and kernel density estimation, to construct a robust predictive ensemble system. By integrating individual quantile regression predictions across multiple quantiles, the proposed framework captures the inherent variability and uncertainty of wind data. Additionally, the ensemble model’s probabilistic outputs are calibrated using isotonic regression, yielding refined distributions that closely align with observed extreme event occurrence rates. The framework was validated using real-world data from a wind farm in Spain, showing substantial improvements over conventional probabilistic binary classifiers in both accuracy and calibration of extreme event probabilities. These findings highlight the potential of the proposed system to enhance operational decision-making and resilience in wind power infrastructure under extreme weather conditions.Agencia Estatal de InvestigaciónComunidad de Madri