And why 2026 could be a big year for spotting auroras. Northern lights shine in the night sky over the landscape in northeastern Germany on January 19, 2026. Breakthroughs, discoveries, and DIY tips sent six days a week. Still, patient stargazers will be rewarded with a memorable planetary alignment. And for those readers joining us from the Southern Hemisphere, there's also the Alpha Centaurids meteor shower to look forward to.

Winter officially arrives on Sunday, December 21. A view of the Geminid meteor shower and stargazing at the Tunnel View of Yosemite National Park on December 14, 2023. Breakthroughs, discoveries, and DIY tips sent every weekday. As one might expect from a month full of long, dark nights, December is a highlight for those with a penchant for looking to the stars . This year, the stargazing on offer promises to be particularly good.

Predicting the spread of wildfires is essential for effective fire management and risk assessment. With the fast advancements of artificial intelligence (AI), various deep learning models have been developed and utilized for wildfire spread prediction. However, there is limited understanding of the advantages and limitations of these models, and it is also unclear how deep learning-based fire spread models can be compared with existing non-AI fire models. In this work, we assess the ability of five typical deep learning models integrated with weather and environmental variables for wildfire spread prediction based on over ten years of wildfire data in the state of Hawaii. We further use the 2023 Maui fires as a case study to compare the best deep learning models with a widely-used fire spread model, FARSITE. The results show that two deep learning models, i.e., ConvLSTM and ConvLSTM with attention, perform the best among the five tested AI models. FARSITE shows higher precision, lower recall, and higher F1-score than the best AI models, while the AI models offer higher flexibility for the input data. By integrating AI models with an explainable AI method, we further identify important weather and environmental factors associated with the 2023 Maui wildfires.

Three meteor showers will peak this month. This delightfully detailed false color image of Saturn is a combination of three images taken in January 1998 by the Hubble Space Telescope and shows the ringed planet in reflected infrared light. Different colors indicated varying heights and compositions of cloud layers generally thought to consist of ammonia ice crystals. The eye-catching rings cast a shadow on Saturn's upper hemisphere, while the bright stripe seen within the left portion of the shadow is infrared sunlight streaming through the large gap in the rings known as the Cassini Division. Breakthroughs, discoveries, and DIY tips sent every weekday.

Section A.1 outlines the generation process of the SynRS3D dataset, including the tools and It also covers the licenses for these plugins. Section A.4 describes the experimental setup and the selection of hyperparameters for the RS3DAda method. Section A.5 presents the ablation study results and analysis for the RS3DAda method. Section A.6 provides supplementary experimental The generation workflow of SynRS3D involves several key steps, from initializing sensor and sunlight parameters to generating the layout, geometry, and textures of the scene. Initialization: Set up the sensor and sunlight parameters using uniform and normal distributions to simulate various conditions.

This task combines land cover mapping, which is closely related to semantic segmentation in computer vision, and height estimation.

Comet C/2025 A6 (Lemmon) was only discovered in January 2025. Breakthroughs, discoveries, and DIY tips sent every weekday. Stargazers will be happy to know that October will see the cosmos compensating for a couple of relatively lean months.There will be a whole bunch of celestial bodies to see over the next month, including the year's largest and brightest full moon, the arrival of a brand new comet, two meteor showers and a good chance to see our solar system's favorite big fella in all his glory. October's full moon finds our closest celestial companion at its perigee, i.e. the point at which it's closest to the Earth. This means that this month's full moon will be [drum roll] a supermoon!

Improving context faithfulness in large language models is essential for developing trustworthy retrieval augmented generation systems and mitigating hallucinations, especially in long-form question answering (LFQA) tasks or scenarios involving knowledge conflicts. Existing methods either intervene LLMs only at inference without addressing their inherent limitations or overlook the potential for self-improvement. In this paper, we introduce GenDiE (Generate, Discriminate, Evolve), a novel self-evolving framework that enhances context faithfulness through fine-grained sentence-level optimization. GenDiE combines both generative and discriminative training, equipping LLMs with self-generation and self-scoring capabilities to facilitate iterative self-evolution. This supports both data construction for model alignment and score-guided search during inference. Furthermore, by treating each sentence in a response as an independent optimization unit, GenDiE effectively addresses the limitations of previous approaches that optimize at the holistic answer level, which may miss unfaithful details. Experiments on ASQA (in-domain LFQA) and ConFiQA (out-of-domain counterfactual QA) datasets demonstrate that GenDiE surpasses various baselines in both faithfulness and correctness, and exhibits robust performance for domain adaptation.