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The Late Bronze Age relic is only the fourth tauriform discovered on the island. Bulls were symbolic animals across much of the prehistoric Mediterranean. Breakthroughs, discoveries, and DIY tips sent six days a week. A hiker recently noticed an out-of-place object in his path while trekking through the hills of Mallorca, Spain . After reviewing the artifact, archaeologists now believe the 1.25-inch-long relic is a rare example of a metal bull sculpture that dates back over 3,000 years.

Surrogate models (including deep neural networks and other machine learning algorithms in supervised learning) are capable of approximating arbitrarily complex, high-dimensional input-output problems in science and engineering, but require a thorough data-agnostic uncertainty quantification analysis before these can be deployed for any safety-critical application. The standard approach for data-agnostic uncertainty quantification is to use conformal prediction (CP), a well-established framework to build uncertainty models with proven statistical guarantees that do not assume any shape for the error distribution of the surrogate model. However, since the classic statistical guarantee offered by CP is given in terms of bounds for the marginal coverage, for small calibration set sizes (which are frequent in realistic surrogate modelling that aims to quantify error at different regions), the potentially strong dispersion of the coverage distribution around its average negatively impacts the relevance of the uncertainty model's statistical guarantee, often obtaining coverages below the expected value, resulting in a less applicable framework. After providing a gentle presentation of uncertainty quantification for surrogate models for machine learning practitioners, in this paper we bridge the gap by proposing a new statistical guarantee that offers probabilistic information for the coverage of a single conformal predictor. We show that the proposed framework converges to the standard solution offered by CP for large calibration set sizes and, unlike the classic guarantee, still offers relevant information about the coverage of a conformal predictor for small data sizes. We validate the methodology in a suite of examples, and implement an open access software solution that can be used alongside common conformal prediction libraries to obtain uncertainty models that fulfil the new guarantee.

Wildfires pose a threat to ecosystems, economies and public safety, particularly in Mediterranean regions such as Spain. Accurate predictive models require high-resolution spatio-temporal data to capture complex dynamics of environmental and human factors. To address the scarcity of fine-grained wildfire datasets in Spain, we introduce IberFire: a spatio-temporal dataset with 1 km x 1 km x 1-day resolution, covering mainland Spain and the Balearic Islands from December 2007 to December 2024. IberFire integrates 120 features across eight categories: auxiliary data, fire history, geography, topography, meteorology, vegetation indices, human activity and land cover. All features and processing rely on open-access data and tools, with a publicly available codebase ensuring transparency and applicability. IberFire offers enhanced spatial granularity and feature diversity compared to existing European datasets, and provides a reproducible framework. It supports advanced wildfire risk modelling via Machine Learning and Deep Learning, facilitates climate trend analysis, and informs fire prevention and land management strategies. The dataset is freely available on Zenodo to promote open research and collaboration.

Following our shape-matching experiments described in Sec. The recorded time values align with the accuracy measurements presented in Figure 1b. Moreover, it's possibly also necessary to adapt a network architecture that predicts the

This leads to a drastic reduction in computation and memory costs, e.g., up to

Dolly Parton's sister asks for prayers for music icon, 79, amid mystery health battle Bloodcurdling videos shows girl aged 12 subway surfing days before she and friend, 13, died during 3.10am stunt Trump's mass deportation effort removed staggering amount of migrants from US in first year of term: 'Just the beginning' Mom-of-two hospitalized, her son left suicidal and their dog dead... after a simple mistake turns $500K home into a death trap Popular actress shocks fans with'unrecognizable' appearance after suffering heartbreaking tragedy Selena Gomez's'disgusting' habit on her wedding day exposed by eagle-eyed fans despite star's efforts to hide it Charlie Kirk leaked text confirms he was livid about'bullying' Jewish donors: 'I'm leaving pro-Israel cause' She's accused of'murder-for-hire' plot against her famous TV star husband. Now there's a shock twist in the case... and she's forced to stare her demons in the face Man is arrested on terror charges over disturbing Halloween display of fake body bags with town official's titles Space agency breaks silence on'foreign' interstellar object soaring past Mars: 'A rare visitor' 'Disneyland of grocery stores' reveals items most hit by tariffs and the fan favorite it STOPPED buying from China Space agency breaks silence on'foreign' interstellar object soaring past Mars: 'A rare visitor' READ MORE: Mysterious interstellar visitor spotted above Mars appears as'massive cylindrical craft' The European Space Agency (ESA) has finally shared new details about the mysterious interstellar visitor days after its closest approach to Mars . The object, dubbed 3I/ATLAS, came within 18.6 million miles of the Red Planet on October 3, and while NASA quickly uploaded images captured by its Perseverance rover on the Martian surface, ESA had remained quiet until now . The ESA's ExoMars Trace Gas Orbiter (TGO) captured images of the object, appearing as a tiny, blurry white dot in a series of images. The object's icy nucleus and its surrounding halo of gas and dust, called a coma, could not be distinguished separately, but the faint glow was clearly visible against the blackness of space.