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Coral reefs are facing a catastrophic decline due to climate-induced bleaching, threatening critical marine biodiversity. Automated, large-scale monitoring is essential; however, modern object detectors are hindered by two fundamental limitations in complex underwater scenes: a spatial reasoning deficit in their decoupled heads, which inhibits robust multi-scale feature integration, and a feature robustness deficit, which renders deterministic networks vulnerable to stochastic visual variations. To address these limitations, we propose Coral-YOLO, a novel framework for detection and forecasting. We introduce the Holistic Attention Block Head (HAB-Head), which enables deep cross-scale reasoning through explicit feature interaction, and MCAttention, a randomized training mechanism that enables the network to learn scale-invariant features with inherent robustness. Evaluated on our newly curated, multi-year CR-Mix dataset, Coral-YOLO achieves a state-of-the-art 50.3% AP (average precision at IoU threshold 0.5:0.95, following COCO metrics), representing a +1.8 percentage point improvement over the YOLOv12-m baseline, with particularly pronounced gains on small objects (+2.6 percentage points in APS). Crucially, its integrated temporal forecasting module achieves 82.7% accuracy in predicting future coral health, substantially outperforming conventional methods. Coral-YOLO sets a new performance benchmark and enables proactive reef conservation. It provides a powerful tool to identify at-risk corals long before severe bleaching becomes visually apparent.

Kagome lattices of various transition metals are versatile platforms for achieving anomalous Hall effects, unconventional charge-density wave orders and quantum spin liquid phenomena due to the strong correlations, spin-orbit coupling and/or magnetic interactions involved in such a lattice. Here, we use laser-based angle-resolved photoemission spectroscopy in combination with density functional theory calculations to investigate the electronic structure of the newly discovered kagome superconductor CsTi 3 Bi 5 , which is isostructural to the AV 3 Sb 5 (A = K, Rb or Cs) kagome superconductor family and possesses a two-dimensional kagome network of titanium. We directly observe a striking flat band derived from the local destructive interference of Bloch wave functions within the kagome lattice. In agreement with calculations, we identify type-II and type-III Dirac nodal lines and their momentum distribution in CsTi 3 Bi 5 from the measured electronic structures. In addition, around the Brillouin zone centre, Z 2 nontrivial topological surface states are also observed due to band inversion mediated by strong spin-orbit coupling. Kagome superconductors host a panoply of condensed matter phenomena, some of which are mediated by band topology. Here, authors use ARPES and DFT to identify type-II and type-III Dirac nodal lines, flat bands and topological surface states in the kagome metal CsTi 3 Bi 5 .

The cascade of correlated topological quantum states in the newly discovered vanadium-based kagome superconductors, AV 3 Sb 5 (A = K, Rb, and Cs), with a Z 2 topological band structure has sparked immense interest. Here, we report the discovery of superconductivity and electronic nematic order in high-quality single-crystals of a new titanium-based kagome metal, CsTi 3 Bi 5 , that preserves the translation symmetry, in stark contrast to the charge density wave superconductor AV 3 Sb 5 . Transport and magnetic susceptibility measurements show superconductivity with an onset superconducting transition temperature T c of approximately 4.8 K. Using the scanning tunneling microscopy/spectroscopy and Josephson scanning tunneling spectroscopy, we demonstrate that the single crystals of CsTi 3 Bi 5 exhibit two distinct superconducting gaps. Furthermore, the superconducting gaps break the six-fold crystal rotational symmetry down to two-fold. At low energies, we find that the quasiparticle interference patterns exhibit rotational-symmetry-breaking C 2 patterns, revealing a nematic ordered normal state with the same nematic direction as in the superconducting state. Our findings uncover a novel superconducting state in CsTi 3 Bi 5 and provide new insights for the intrinsic electron liquid crystal phases in kagome superconductors. The new kagome metals can exhibit unconventional electron correlated states beyond recently discovered kagome superconductors AV 3 Sb 5 . Here, the authors report discovery of superconductivity and intrinsic nematic order in a new titanium-based kagome metal CsTi 3 Bi 5 without charge density wave order.

State-of-the-art historical global burned area (BA) products largely rely on MODIS data, offering long temporal coverage but limited spatial resolution. As a result, small fires and complex landscapes remain underrepresented in global fire history reconstructions. By contrast, Landsat provides the only continuous satellite record extending back to the 1980s, with substantially finer resolution. However, its use at a global scale has long been hindered by infrequent revisit times, cloud contamination, massive data volumes, and processing demands. We compared MODIS FireCCI51 with the only existing Landsat-based global product, GABAM, in a mountainous region characterized by frequent, small-scale fires. GABAM detected a higher number of burn scars, including small events, with higher Producer’s Accuracy (0.68 vs. 0.08) and similar User’s Accuracy (0.85 vs. 0.83). These results emphasize the value of Landsat for reconstructing past fire regimes in complex landscapes. Crucially, recent advances in cloud computing, data cubes, and processing pipelines now remove many of the former barriers to exploiting the Landsat archive globally. A more systematic integration of Landsat data into MODIS-based routines may help produce more complete and accurate databases of historical fire activity, ultimately enabling improved understanding of long-term global fire dynamics.

High temperatures seriously threaten the global yield of maize. The objectives of the present study were to explore the key candidate gene involved in heat shock responses in maize and its potential biological function to heat stress. Here, we identified a Class C heat shock factor, ZmHSF21, from maize leaves and used molecular biological and plant physiological assays to investigate its roles in transgenic Arabidopsis. ZmHSF21 encodes a putative protein of 388 amino acids. We showed that ZmHSF21 was expressed in most tissues of maize with relatively high expression in leaves and silks but rather low in roots and stalks, and its expression level in leaves was significantly up-regulated by heat treatment. We also showed that overexpression of ZmHSF21 in Arabidopsis significantly improved the seed germination frequency and plant survival rate when exposed to heat stress. We demonstrated that, compared with wild-type plants, the activities of peroxidase, superoxide dismutase, and catalase increased while the reactive oxygen species accumulation decreased in ZmHSF21 overexpressors under heat stress conditions. We further demonstrated that ZmHSF21 promoted the transcriptional level of AtAPX2, AtGolS1, and several AtHSPs. Collectively, the first-class C HSF in maize (ZmHSF21) is cloned in this study, and the combined results suggest that ZmHSF21 is a positive regulator of heat shock response and can be applied to develop maize high-temperature-tolerant varieties for more yield.

The control of the Kondo effect is of great interest in single-molecule junction due to its potential applications in spin based electronics. Here, we demonstrate that the Kondo effect is reversibly switched on and off in an iron phthalocyanine (FePc) single-molecule junction by using a superconducting Nb tip. In a scanning tunneling microscope-based Nb-insulator-FePc-Au junction, we achieve a reversible switching between the Kondo dip and inelastic electronic tunneling spectra by simply adjusting the tip-sample distance to tune the tunnel coupling at low temperature. Further approaching the tip leads to the picking up of the molecule to the tip apex, which transfers the geometry of the single-molecule junction into a Nb-FePc-insulator-Au type. As the molecule forms an effective magnetic impurity embedded into the superconducting ground states of the Nb tip, the out-gap Kondo dip switched to an in-gap Yu-Shiba-Rusinov state. Our results open up a new route for manipulating the Kondo effect within a single-molecule junction.

The collective modes of the superconducting order parameter fluctuation can provide key insights into the nature of the superconductor. Recently, a family of superconductors has emerged in non-magnetic kagome materials A V 3 Sb 5 ( A  = K, Rb, Cs), exhibiting fertile emergent phenomenology. However, the collective behaviors of Cooper pairs have not been studied. Here, we report a distinct collective mode in CsV 3- x Ta x Sb 5 using scanning tunneling microscope/spectroscopy. The spectral line-shape is well-described by one isotropic and one anisotropic superconducting gap, and a bosonic mode due to electron-mode coupling. With increasing x , the two gaps move closer in energy, merge into two isotropic gaps of equal amplitude, and then increase synchronously. The mode energy decreases monotonically to well below 2 Δ and survives even after the charge density wave order is suppressed. We propose the interpretation of this collective mode as Leggett mode between different superconducting components or the Bardasis-Schrieffer mode due to a subleading superconducting component. Collective bosonic modes can offer important information for understanding a wide range of superconductors. Here, the authors report evidence of a bosonic mode in the scanning tunnelling spectra of the kagome superconductor CsV 3-x Ta x Sb 5 , which is tentatively interpreted as the Leggett mode.

The development of robust autonomous maritime systems is fundamentally constrained by the “data silo” problem, where valuable operational data from disparate fleets remain isolated due to privacy concerns, severely limiting the scalability of general-purpose navigation intelligence. To address this barrier, we propose a novel Federated Meta-Transfer Learning (FMTL) framework that enables collaborative evolution of unmanned surface vehicle (USV) swarms while preserving data privacy. Our hierarchical approach orchestrates three synergistic stages: (1) transfer learning pre-trains a universal “Sea-Sense” foundation model on large-scale maritime data to establish fundamental navigation priors; (2) federated learning enables decentralized fleets to collaboratively refine this model through encrypted gradient aggregation, forming a distributed cognitive network; (3) meta-learning allows for rapid personalization to individual vessel dynamics with minimal adaptation trials. Comprehensive simulations across heterogeneous fleet distributions demonstrate that our federated model achieves a 95.4% average success rate across diverse maritime scenarios, significantly outperforming isolated specialist models (63.9–73.1%), while enabling zero-shot performance of 78.5% and few-shot adaptation within 8–12 episodes on unseen tasks. This work establishes a scalable, privacy-preserving paradigm for collective maritime intelligence through swarm-based learning.

At present, most of the reported planar pentacoordinate clusters are similar to the isoelectronic substitution of CAl5+, with 18 counting electrons. Meanwhile, the regular planar pentacoordinate boron systems are rarely reported. Hereby, a sulphur-bridged BAl5S5+ system with a five-pointed star configuration and 17 counting electrons is identified at the global energy minimum through the particle-swarm optimization method, based on the previous recognition on bridged sulphur as the peripheral tactics to the stable planar tetracoordinate carbon and boron. Its outstanding stability has been demonstrated by thermodynamic analysis at 900 K, electronic properties and chemical bonding analysis. This study provides adequately theoretical basis and referable data for its experimental capture and testing.

Atomically precise defect engineering is essential to manipulate the properties of emerging topological quantum materials for practical quantum applications. However, this remains challenging due to the obstacles in modifying the typically complex crystal lattice with atomic precision. Here, we report the atomically precise engineering of the vacancy-localized spin–orbit polarons in a kagome magnetic Weyl semimetal Co 3 Sn 2 S 2 , using scanning tunneling microscope. We achieve the step-by-step repair of the selected vacancies, leading to the formation of artificial sulfur vacancies with elaborate geometry. We find that that the bound states localized around these vacancies undergo a symmetry dependent energy shift towards Fermi level with increasing vacancy size. As the vacancy size increases, the localized magnetic moments of spin–orbit polarons become tunable and eventually become itinerantly negative due to spin–orbit coupling in the kagome flat band. These findings provide a platform for engineering atomic quantum states in topological quantum materials at the atomic scale. Defect engineering in topological materials is a frontier that promises tunable physical properties with rich applications. Here, the authors demonstrate the atomically precise engineering of vacancies in a topological semimetal, which locally tunes the magnetic properties.