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Comparative analyses of phylogenetic trees typically require identical taxon sets, however, in practice, trees often include distinct but overlapping taxa. Pruning non-shared leaves discards phylogenetic signal, whereas tree completion can preserve both taxa and branch-length information. This work introduces a polynomial-time algorithm for set-wide completion of phylogenetic trees with partial taxon overlap. The proposed method identifies and extracts maximal completion subtrees that frequently appear across the source trees and constructs a weighted majority-rule consensus. Branch lengths are scaled using rates derived from common leaves. Each consensus subtree is inserted at the position that minimizes the quadratic distance error measured against information from the source trees, with candidate positions restricted to the original branches of the target tree. We demonstrate that the algorithm runs in polynomial time and preserves distances among the original taxa, yielding a unique completion that is order-independent with respect to the processing order of target trees. An experimental evaluation on amphibians, mammals, sharks, and squamates shows that the proposed method con

The blue shark (Prionace glauca) exhibits a striking dorsoventral color gradient, transitioning from vibrant blue dorsally to silver and white ventrally, a pattern widely interpreted as pelagic countershading. Despite its ecological significance, the physical basis of this coloration remains unresolved. Here we show that this color system does not arise from dermal chromatophores, as in most vertebrates, but from a previously unrecognised photonic architecture housed within the pulp cavity of individual dermal denticles that cover the skin. Optical imaging reveals discrete color domains within denticle crowns, while external denticle morphology remains similar across color zones. Using spectroscopy, micro-computed tomography, histology, and correlative electron microscopy, we demonstrate that color variation is organized across coupled micro- and nanoscale architectures. In blue denticles, iridophores and melanophores form a densely packed tessellated reflector-absorber system within an expanded crown-restricted pulp cavity. Transition-zone denticles exhibit partial cellular layering, whereas white denticles lack melanophores and contain only reflective cells. At the nanoscale, ord

Observational studies have made substantial progress in characterizing quenching as a function of stellar mass and environment, but they are often limited in their ability to constrain quenching timescales and to determine the dominant environmental process responsible for the shutting down of star formation. To address this, we combine recent Sloan Digital Sky Survey (SDSS) observations with the SHARK v2.0 semi-analytic model to study the quenching of satellite galaxies in groups and clusters. We generate mock SDSS-like observations to calibrate the hot halo and cold interstellar medium (ISM) gas stripping prescriptions against observed satellite quenched fractions, finding that the previously adopted stripping prescriptions in SHARK v2.0 are too aggressive and overestimate the quenched fraction of satellite galaxies. Reducing the efficiency of both hot and cold gas stripping yields excellent agreement with observations for low- and intermediate-mass satellite galaxies. We use the calibrated model to investigate quenching timescales and find that satellites quench more quickly in clusters compared to groups, with timescales that generally decrease with increasing stellar mass. The

The recent widespread adoption of drones for studying marine animals provides opportunities for deriving biological information from aerial imagery. The large scale of imagery data acquired from drones is well suited for machine learning (ML) analysis. Development of ML models for analyzing marine animal aerial imagery has followed the classical paradigm of training, testing, and deploying a new model for each dataset, requiring significant time, human effort, and ML expertise. We introduce Frame Level ALIgment and tRacking (FLAIR), which leverages the video understanding of Segment Anything Model 2 (SAM2) and the vision-language capabilities of Contrastive Language-Image Pre-training (CLIP). FLAIR takes a drone video as input and outputs segmentation masks of the species of interest across the video. Notably, FLAIR leverages a zero-shot approach, eliminating the need for labeled data, training a new model, or fine-tuning an existing model to generalize to other species. With a dataset of 18,000 drone images of Pacific nurse sharks, we trained state-of-the-art object detection models to compare against FLAIR. We show that FLAIR massively outperforms these object detectors and perfo

Clustering algorithms often assume all features contribute equally to the data structure, an assumption that usually fails in high-dimensional or noisy settings. Feature weighting methods can address this, but most require additional parameter tuning. We propose SHARK (Shapley Reweighted $k$-means), a feature-weighted clustering algorithm motivated by the use of Shapley values from cooperative game theory to quantify feature relevance, which requires no additional parameters beyond those in $k$-means. We prove that the $k$-means objective can be decomposed into a sum of per-feature Shapley values, providing an axiomatic foundation for unsupervised feature relevance and reducing Shapley computation from exponential to polynomial time. SHARK iteratively re-weights features by the inverse of their Shapley contribution, emphasising informative dimensions and down-weighting irrelevant ones. Experiments on synthetic and real-world data sets show that SHARK consistently matches or outperforms existing methods, achieving superior robustness and accuracy, particularly in scenarios where noise may be present. Software: https://github.com/rickfawley/shark.

SHARK-NIR is a new compact instrument for coronagraphic imaging, direct imaging, and coronagraphic spectroscopy in the near-infrared wavelengths mounted at LBT. Taking advantage of the telescope's adaptive optics system, it provides high contrast imaging with coronagraphic and spectroscopic capabilities and is focused on the direct imaging of exoplanets and circumstellar discs. We present SHINS, the SHARK-NIR instrument control software, mainly realized with the TwiceAsNice framework from MPIA - Heidelberg and the ICE framework using the C++ programming language. We describe how we implemented the software components controlling several instrument subsystems, through the adaptation of already tested libraries from other instruments at LBT, such as LINC-NIRVANA. The scientific detector comes with its own readout electronic and control software interfaced with our software through INDI. We describe the C++ core software Observation Control Software, responsible for dispatching commands to the subsystems, also implementing a software solution to avoid a potential collision between motorized components, fully transparent to final users. It exposes an ICE interface and can be controlled

The presence of strong correlations between super-massive black hole (SMBH) masses and galaxy properties like stellar mass have been well-established in the local Universe, but how these scaling relations evolve with cosmic time is yet to be settled in both observations and theoretical models. Recent works have also highlighted the role of galaxy morphology on the scatter of the SMBH-galaxy mass scaling relations, while the impact of other galaxy properties remains poorly studied, like the role of galaxy environment. We use the state-of-the-art SHARK v2.0 semi-analytic model to explore the evolution of these galaxy-SMBH scaling relations to expand the available predictions from theoretical models to contrast with existing and upcoming observations. We find the relations between SMBH masses and both total and bulge stellar mass predicted by SHARK v2.0 to be in good overall agreement with observational measurements across a wide range of redshift and stellar masses. These scaling relations show a significant evolution as a function of cosmic time in SHARK v2.0, with SMBH masses $\sim1$ dex lower at $z=0$ compared to $z=9$ at fixed stellar mass and the scatter increasing by a factor o

The traditional integer-pixel displacement search algorithm of digital image correlation method has low computational efficiency and has been gradually eliminated, and some intelligent optimization algorithms have their own strengths and weaknesses. The white shark optimizer has excellent global search capabilities. However, its calculation is cumbersome, programming complex and inefficient. In order to improve the computational efficiency of the white shark optimizer, it is improved by using the Tent map, introducing the dynamic nonlinear time factor, setting the automatic termination condition and adding the three-step search method. The improved white shark optimizer is applied to the integer-pixel displacement search. In order to improve the accuracy and efficiency of sub-pixel displacement calculation, an improved surface fitting method is proposed by combining bicubic interpolation, improved white shark optimizer and surface fitting method. Through grayscale interpolation, the distance between the fitting points is reduced, and the accuracy of search of the surface fitting method is further improved. The performance of the improved white shark optimizer and the improved surfa

In the context of SHARK-NIR (System for coronagraphy with High Order adaptive optics in Z and H band), we present the development of SHINS, the SHARK-NIR INstrument control Software, in particular focusing on the changes introduced during the Assembly, Integration, and Test (AIT) phase. SHARK-NIR observing sessions will be carried out with "ESO-style" Observation Blocks (OBs) based on so-called Templates scripts that will be prepared by observers. We decided to develop Templates also for the large number of AIT tests (flexures, coronagraphic mask alignment, scientific camera performances...). Here we present the adopted HTTP API for the OBs generation and a web-based frontend that implements it. Taking advantage of this approach, we decided to expose APIs also for individual device movement and monitoring, as well as for general status. These APIs are then used in the web-based instrument control and synoptic panels. During the recent AIT phase, a potential collision issue between two motorized components emerged. While we are exploring the possibility of a hardware interlock, we present a software solution developed at the Observation Software level, that is also available while u

As models become larger, ML accelerators are a scarce resource whose performance must be continually optimized to improve efficiency. Existing performance analysis tools are coarse grained, and fail to capture model performance at the machine-code level. In addition, these tools often do not provide specific recommendations for optimizations. We present xPU-Shark, a fine-grained methodology for analyzing ML models at the machine-code level that provides actionable optimization suggestions. Our core insight is to use a hardware-level simulator, an artifact of the hardware design process that we can re-purpose for performance analysis. xPU-Shark captures traces from production deployments running on accelerators and replays them in a modified microarchitecture simulator to gain low-level insights into the model's performance. We implement xPU-Shark for our in-house accelerator and used it to analyze the performance of several of our production LLMs, revealing several previously-unknown microarchitecture inefficiencies. Leveraging these insights, we optimize a common communication collective by up to 15% and reduce token generation latency by up to 4.1%.

This paper introduces an autonomous UAV vision system for continuous, real-time tracking of marine animals, specifically sharks, in dynamic marine environments. The system integrates an onboard computer with a stabilised RGB-D camera and a custom-trained OSTrack pipeline, enabling visual identification under challenging lighting, occlusion, and sea-state conditions. A key innovation is the inter-UAV handoff protocol, which enables seamless transfer of tracking responsibilities between drones, extending operational coverage beyond single-drone battery limitations. Performance is evaluated on a curated shark dataset of 5,200 frames, achieving a tracking success rate of 81.9\% during real-time flight control at 100 Hz, and robustness to occlusion, illumination variation, and background clutter. We present a seamless UAV handoff framework, where target transfer is attempted via high-confidence feature matching, achieving 82.9\% target coverage. These results confirm the viability of coordinated UAV operations for extended marine tracking and lay the groundwork for scalable, autonomous monitoring.

We explore how the choice of galaxy formation model affects the predicted properties of high-redshift galaxies. Using the FLARES zoom resimulation strategy, we compare the EAGLE hydrodynamics model and the GALFORM, L-Galaxies, SC-SAM and SHARK semi-analytic models (SAMs) at $5\leq z \leq 12$. The first part of our analysis examines the stellar mass functions, stellar-to-halo mass relations, star formation rates, and supermassive black hole (SMBH) properties predicted by the different models. Comparisons are made with observations, where relevant. We find general agreement between the range of predicted and observed stellar mass functions. The model predictions differ considerably when it comes to SMBH properties, with GALFORM and SHARK predicting between 1.5-3 dex more massive SMBHs ($M_{\rm BH}>10^6\ {\rm M_\odot}$) than L-Galaxies and SC-SAM, depending on redshift. The second half of our analysis focuses on passive galaxies. We show that in L-Galaxies and SC-SAM, environmental quenching of satellites is the prevalent quenching mechanism, with active galactic nuclei (AGN) feedback having little effect at the redshifts probed. On the other hand, $\sim40\%$ of passive galaxies pr

Unlike human intestines, which are long, hollow tubes, the intestines of sharks and rays contain interior helical structures surrounding a cylindrical hole. One function of these structures may be to create asymmetric flow, favoring passage of fluid down the digestive tract, from anterior to posterior. Here, we design and 3D print biomimetic models of shark intestines, in both rigid and deformable materials. We use the rigid models to test which physical parameters of the interior helices (the pitch, the hole radius, the tilt angle, and the number of turns) yield the largest flow asymmetries. These asymmetries exceed those of traditional Tesla valves, structures specifically designed to create flow asymmetry without any moving parts. When we print the biomimetic models in elastomeric materials so that flow can couple to the structure's shape, flow asymmetry is significantly amplified; it is 7-fold larger in deformable structures than in rigid structures. Last, we 3D-print deformable versions of the intestine of a dogfish shark, based on a tomogram of a biological sample. This biomimic produces flow asymmetry comparable to traditional Tesla valves. The ability to influence the direc

Since volcanic activity was first discovered on Io from Voyager images in 1979, changes on Io's surface have been monitored from both spacecraft and ground-based telescopes. Here, we present the highest spatial resolution images of Io ever obtained from a ground-based telescope. These images, acquired by the SHARK-VIS instrument on the Large Binocular Telescope, show evidence of a major resurfacing event on Io's trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images show that a plume deposit from a powerful eruption at Pillan Patera has covered part of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io's surface using adaptive optics at visible wavelengths.

The combination of detection techniques enhances our ability to identify companions orbiting nearby stars. We employed high-contrast imaging to constrain mass and separation of possible companions responsible for the significant proper motion anomalies of the nearby stars HIP 11696, HIP 47110 and HIP 36277. These targets were observed using the LBT's high-contrast camera, SHARK-NIR, in H-band using a Gaussian coronagraph, and with the LMIRCam instrument in the L'-band and using a vAPP coronagraph. Both observations were conducted simultaneously. Additionally, constraints at short separations from the host star are derived analyzing the renormalized unit weight error (RUWE) values from the Gaia catalogue. We find that the companion responsible for the anomaly signal of HIP 11696 is likely positioned at a distance from 2.5 to 28 astronomical units from its host. Its mass is estimated to be between 4 and 16 Jupiter masses, with the greater mass possible only at the upper end of the separation range. Similar limits were obtained for HIP 47110 where the companion should reside between 3 and 30 au with a mass between 3 and 10 MJup. For HIP 36277, we identified a faint stellar companion a

We present a model of radio continuum emission associated with star formation (SF) and active galactic nuclei (AGN) implemented in the Shark semi-analytic model of galaxy formation. SF emission includes free-free and synchrotron emission, which depend on the free-electron density and the rate of core-collapse supernovae with a minor contribution from supernova remnants, respectively. AGN emission is modelled based on the jet production rate, which depends on the black hole mass, accretion rate and spin, and includes synchrotron self-absorption. Shark reproduces radio luminosity functions (RLFs) at 1.4 GHz and 150 MHz for 0 $\leq$ z $\leq$ 4, and scaling relations between radio luminosity, star formation rate and infrared luminosity of galaxies in the local and distant universe in good agreement with observations. The model also reproduces observed number counts of radio sources from 150 MHz to 8.4 GHz to within a factor of two on average, though larger discrepancies are seen at the very bright fluxes at higher frequencies. We use this model to understand how the radio continuum emission from radio-quiet AGNs can affect the measured RLFs of galaxies. We find current methods to exclu