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Despite rapid commercialization of surgical robots, their autonomy and real-time decision-making remain limited in practice. To address this gap, we propose ArthroCut, an autonomous policy learning framework that upgrades knee arthroplasty robots from assistive execution to context-aware action generation. ArthroCut fine-tunes a Qwen--VL backbone on a self-built, time-synchronized multimodal dataset from 21 complete cases (23,205 RGB--D pairs), integrating preoperative CT/MR, intraoperative NDI tracking of bones and end effector, RGB--D surgical video, robot state, and textual intent. The method operates on two complementary token families -- Preoperative Imaging Tokens (PIT) to encode patient-specific anatomy and planned resection planes, and Time-Aligned Surgical Tokens (TAST) to fuse real-time visual, geometric, and kinematic evidence -- and emits an interpretable action grammar under grammar/safety-constrained decoding. In bench-top experiments on a knee prosthesis across seven trials, ArthroCut achieves an average success rate of 86% over the six standard resections, significantly outperforming strong baselines trained under the same protocol. Ablations show that TAST is the p

Spatial patterns of stellar elemental abundances encode rich information about a galaxy's formation history. We analyze the radial, vertical, and azimuthal variations of metals in stars, both today and at formation, in the FIRE-2 cosmological simulations of Milky Way (MW)-mass galaxies, and we compare with the MW. The radial gradient today is steeper (more negative) for younger stars, which agrees with the MW, although radial gradients are shallower in FIRE-2. Importantly, this age dependence was present already at birth: radial gradients today are only modestly ($\lesssim$ 0.01 dex kpc$^{-1}$) shallower than at birth. Disk vertical settling gives rise to negative vertical gradients across all stars, but vertical gradients of mono-age stellar populations are weak. Similar to the MW, vertical gradients in FIRE-2 are shallower at larger radii, but they are overall shallower in FIRE-2. This vertical dependence was present already at birth: vertical gradients today are only modestly ($\lesssim$ 0.1 dex kpc$^{-1}$) shallower than at birth. Azimuthal scatter is nearly constant with radius, and it is nearly constant with age $\lesssim$ 8 Gyr ago, but increases for older stars. Azimuthal s

Background. Osteoarthritis affects about 528 million people worldwide, causing pain and stiffness in the joints. Arthroplasty is commonly performed to treat joint osteoarthritis, reducing pain and improving mobility. Nevertheless, a significant share of patients remain unsatisfied with their surgery. Personalised arthroplasty was introduced to improve surgical outcomes however current solutions require delays, making it difficult to integrate in clinical routine. We propose a fully automated workflow to design patient-specific implants for total knee arthroplasty. Methods. The proposed pipeline first uses artificial neural networks to segment the femur and tibia proximal and distal extremities. Then the full bones are reconstructed using augmented statistical shape models, combining shape and landmarks information. Finally, 77 morphological parameters are computed to design patient-specific implants. The developed workflow has been trained on 91 CT scans and evaluated on 41 CT scans, in terms of accuracy and execution time. Results. The workflow accuracy was $0.4\pm0.2mm$ for segmentation, $1.0\pm0.3mm$ for full bone reconstruction, and $2.2\pm1.5mm$ for anatomical landmarks determ

Audio event classification has recently emerged as a promising approach in medical applications. In total hip arthroplasty (THA), intra-operative hammering acoustics provide critical cues for assessing the initial stability of the femoral stem, yet variability due to femoral morphology, implant size, and surgical technique constrains conventional assessment methods. We propose the first deep learning framework for this task, employing a TimeMIL model trained on Log-Mel Spectrogram features and enhanced with pseudo-labeling. On intra-operative recordings, the method achieved 91.17 % +/- 2.79 % accuracy, demonstrating reliable estimation of stem stability. Comparative experiments further show that reducing the diversity of femoral stem brands improves model performance, although limited dataset size remains a bottleneck. These results establish deep learning-based audio event classification as a feasible approach for intra-operative stability assessment in THA.

Details of the contents and the formulations of the Born rule changed considerably from its inception by Born in 1926 to the present day. This paper traces the early history of the Born rule 100 years ago, its generalization (essential for today's quantum optics and quantum information theory) to POVMs around 50 years ago, and a modern derivation from an intuitive definition of the notion of a quantum detector. It is based to a large extent on little known results from the recent books 'Coherent Quantum Physics' (2019) by A. Neumaier and 'Algebraic Quantum Physics, Vol. 1' (2024) by A. Neumaier and D. Westra, Also discussed is the extent to which the various forms of the Born rule have, like any other statement in physics, a restricted domain of validity, which leads to problems when applied outside this domain.

In the past, the development of vaccines and immunotherapeutics relied heavily on trial-and-error experimentation and extensive in vivo testing, often requiring years of pre-clinical and clinical trials. Today, artificial intelligence (AI) and deep learning (DL) are actively transforming vaccine and immunotherapeutic design, by (i) offering predictive frameworks that support rapid, data-driven decision-making; (ii) increasingly being implemented as time- and resource-efficient strategies that integrate computational models, systems vaccinology, and multi-omics data to better phenotype, differentiate, and classify patient diseases and cancers; predict patients' immune responses; and identify the factors contributing to optimal vaccine and immunotherapeutic protective efficacy; (iii) refining the selection of B- and T-cell antigen/epitope targets to enhance efficacy and durability of immune protection; and (iv) enabling a deeper understanding of immune regulation, immune evasion, immune checkpoints, and regulatory pathways. The future of AI and DL points toward (i) replacing animal preclinical testing of drugs, vaccines, and immunotherapeutics with computational-based models, as rece

In this paper, we revisit the Kaluza-Klein theory from the perspective of the classification of elementary particles based on the coadjoint orbit method. We study the momentum map of the corresponding symmetry group $G_1$ which conserves the hyperbolic metric. We show that the electric charge is not frame-invariant, in contradiction with the experimental observations. In other words, it is not the symmetry group of the Universe today as we know it. To avert this paradox, we scale the fifth coordinate and consider the limit when the cylinder radius vanishes. For the corresponding group $G_0$, the charge is invariant. On this ground, we propose a cosmological scenario in which the elementary particles of the early Universe are classified from the momenta of the group $G_1$, next the three former dimensions inflate quickly while the fifth one shrinks, leading to the 4D era in which as today the particles are characterized by the momenta of the group $G_0$. By this mechanism, the elementary particles can acquire electric charge as a by-product of the 4 + 1 symmetry breaking of the Universe. This work opens the way to the geometric quantization of charged elementary particles. We constr

Nearly one million total hip and knee arthroplasties (THA/TKA) are performed annually in the United States, with most patients discharged home and prescribed home exercise programs (HEPs) to enhance lower extremity function. Traditional paper-based HEPs, while accessible and low-cost, often lack engagement and real-time feedback, which are critical for adherence and performance optimization. Extended reality (XR) and telehealth (TH) systems offer promising solutions, combining engagement and feedback, though each has limitations. To address these gaps, we designed and executed a pilot study that compared exercise performance in individuals with THA/TKA using a conventional paper-based HEP versus a proof-of-concept system, dubbed Tele-PhyT, that included the ideal characteristics of a future XR technology that would enable seamless HEP-TH systems, with robust marker-less full body tracking, real-time visual feedback, and performance quantification. The pilot study used a randomized cross-over design and targeted two types of users: therapists and patients. Participants favored Tele- PhyT for its real-time feedback and ease of use, and noted its potential to improve HEP adherence and

This paper analyzes the effective field theory perspective on modern physics through the lens of the quantum theory of gravitational interaction. The historical part argues that the search for a theory of quantum gravity stimulated the change in outlook that characterizes the modern approach to the Standard Model of particle physics and General Relativity. We present some landmarks covering a long period, i.e., from the beginning of the 1930s until 1994, when, according to Steven Weinberg, the modern bottom-up approach to General Relativity began. Starting from the first attempt to apply the quantum field theory techniques to perturbatively quantize Einstein's theory, we explore its developments and interaction with the top-down approach encoded by String Theory. In the last part of the paper, we focus on this last approach to describe the relationship between our modern understanding of String Theory and Effective Field Theory in today's panorama. To this end, the non-historical part briefly explains the modern concepts of moduli stabilization and Swampland to understand another change in focus that explains the present framework where some string theorists move.

Total hip arthroplasty (THA) is a widely used surgical procedure in orthopedics. For THA, it is of clinical significance to analyze the bone structure from the CT images, especially to observe the structure of the acetabulum and femoral head, before the surgical procedure. For such bone structure analyses, deep learning technologies are promising but require high-quality labeled data for the learning, while the data labeling is costly. We address this issue and propose an efficient data annotation pipeline for producing a deep learning-oriented dataset. Our pipeline consists of non-learning-based bone extraction (BE) and acetabulum and femoral head segmentation (AFS) and active-learning-based annotation refinement (AAR). For BE we use the classic graph-cut algorithm. For AFS we propose an improved algorithm, including femoral head boundary localization using first-order and second-order gradient regularization, line-based non-maximum suppression, and anatomy prior-based femoral head extraction. For AAR, we refine the algorithm-produced pseudo labels with the help of trained deep models: we measure the uncertainty based on the disagreement between the original pseudo labels and the

For most writers the science is either an exotic setting or a source of thrilling conflict that would drive the story forward. For a communicator it is the other way around - the science is neatly wrapped in a package of literary tools that make it "invisible" while it remains tangible and most importantly - it can be conveyed to the reader in understandable terms. There are many examples showing how these seemingly contradicting goals can complement each other successfully. I will review how the science was communicated by mainstream and genre writers of yesterday and today, and in different (not necessarily anglophone) cultures. I will bring forward the best and the worst examples that illuminate various astronomical concepts. Finally, I will discuss how we can use them both in outreach and education. Contrary to many similar summaries I will concentrate on some often overlooked mainstream literary examples, including the plays The Physicists by Friedrich Dürrenmatt and Copenhagen by Michael Frayn, the novel White Garments by Vl. Dudintsev and even an episode of the Inspector Morse TV show, featuring scientists. I will also mention in passing a few less well known genre books.

We will give a simple, unified, possible explanation of several debated genetic issues on today's humans, Neandertals and Denisovans. In particular it is shown by means of a simple mathematical model why there is little genetic variation in todays's human population or in Western Neandertal population, why all mtDNA and y-chromosomes in today's humans seem to have African origin with no trace of Neandertal nor Denosovan mtDNA or y-chromosomes, why a big part of the European gene pool is young (from Neolitic time), and why today's East Asians have mode Neandertal genes than today's Europeans.

Total hip arthroplasty (THA) relies on accurate landmark detection from radiographic images, but unstructured data caused by irregular patient postures or occluded anatomical markers pose significant challenges for existing methods. To address this, we propose UNSCT-HRNet (Unstructured CT - High-Resolution Net), a deep learning-based framework that integrates a Spatial Relationship Fusion (SRF) module and an Uncertainty Estimation (UE) module. The SRF module, utilizing coordinate convolution and polarized attention, enhances the model's ability to capture complex spatial relationships. Meanwhile, the UE module which based on entropy ensures predictions are anatomically relevant. For unstructured data, the proposed method can predict landmarks without relying on the fixed number of points, which shows higher accuracy and better robustness comparing with the existing methods. Our UNSCT-HRNet demonstrates over a 60% improvement across multiple metrics in unstructured data. The experimental results also reveal that our approach maintains good performance on the structured dataset. Overall, the proposed UNSCT-HRNet has the potential to be used as a new reliable, automated solution for T

Today, high-performance thermoelectric and thermomagnetic materials operating in the low-temperature regime, particularly below the boiling point of liquid nitrogen remain scarce. Most thermomagnetic materials reported to date exhibit a strong Nernst signal along specific crystallographic directions in their single-crystal form. However, their performance typically degrades significantly in the polycrystalline form. Here, we report an improved Nernst thermopower of $\sim$ 128 $μ$V/K at 30 K and 14 T in polycrystalline compensated semimetal ScSb, in comparison to that was observed in single crystal ScSb previously. The magnetic field dependence of Nernst thermopower shows a linear and non-saturating behavior up to 14 T. The maximum Nernst power factor reaches to $\sim 240 \times 10^{-4}$ W m$^{-1}$ K$^{-2}$ and Nernst figure of merit reaches to $\sim 11 \times 10^{-4}$ K$^{-1}$. Polycrystalline ScSb also shows a large non-saturating magnetoresistance of $\sim 940 \%$ at 2 K and 14 T. These enhanced properties originate from better electron-hole compensation, as revealed by Hall resistivity measurements. The cubic symmetry and absence of anisotropy in ScSb allow its polycrystalline f

Within the framework of a model universe with time variable space dimension (TVSD), known as decrumpling or TVSD model, we show the present value of the deceleration parameter is negative implying that the universe is accelerating today. Our study is based on a flat universe with the equation of state parameter to be $ω(z=0) \approx -1$ today. More clearly, decrumpling model tells us the universe is accelerating today due to the cosmological constant which is the simplest candidate for the dark energy.

A low-cost, accurate device to measure and record knee range of motion (ROM) is of the essential need to improve confidence in at-home rehabilitation. It is to reduce hospital stay duration and overall medical cost after Total Knee Arthroplasty (TKA) procedures. The shift in Medicare funding from pay-as-you-go to the Bundled Payments for Care Improvement (BPCI) has created a push towards at-home care over extended hospital stays. It has heavily affected TKA patients, who typically undergo physical therapy at the clinic after the procedure to ensure full recovery of ROM. In this paper, we use accelerometers to create a ROM sensor that can be integrated into the post-operative surgical dressing, so that the cost of the sensors can be included in the bundled payments. In this paper, we demonstrate the efficacy of our method in comparison to the baseline computer vision method. Our results suggest that calculating angular displacement from accelerometer sensors demonstrates accurate ROM recordings under both stationary and walking conditions. The device would keep track of angle measurements and alert the patient when certain angle thresholds have been crossed, allowing patients to rec

The impact of rapid rotation on stellar evolution theory remains poorly understood as of today. Vega is a special object in this context as spectroscopic and interferometric studies have shown that it is a rapid rotator seen nearly pole one, a rare orientation particularly interesting for seismic studies. In this paper we present a first systematic search for pulsations in Vega. The goal of the present work is to detect for the first time pulsations in a rapidly rotating star seen nearly pole-on. Vega was monitored in quasi-continuous high-resolution echelle spectroscopy. A total of 4478 spectra were obtained within 3 individual runs in 2008, 2009 and 2010 at high resolution. This data set should represent the most extensive high S/N, high resolution quasi-continuous survey obtained on Vega as of today. Equivalent photospheric absorption profiles were calculated for the stellar spectrum, but also for the telluric lines acting as a radial velocity reference. Residual velocities were analysed and periodic low amplitude variations, potentially indicative of stellar pulsations, detected. All three data sets revealed the presence of residual periodic variations: 5.32 and 9.19 c/d, (A ap

Inhomogeneous big bang nucleosynthesis (BBN) produces a spatially inhomogeneous distribution of element abundances at $T \sim 10^9$ K, but subsequent element diffusion will tend to erase these inhomogeneities. We calculate the cosmological comoving diffusion length for the BBN elements. This diffusion length is limited by atomic scattering and is therefore dominated by diffusion when the atoms are neutral, between the redshifts of recombination and reionization. We find that the comoving diffusion length today is $d_{com} \approx 70$ pc for all of the elements of interest except $^7$Li, for which $d_{com}$ is an order of magnitude smaller because $^7$Li remains ionized throughout the relevant epoch. This comoving diffusion length corresponds to a substellar baryonic mass scale and is roughly equal to the horizon scale at BBN. These results lend support to the possibility that inhomogeneities on scales larger than the horizon at BBN could lead to a spatially inhomogeneous distribution of elements today, while purely subhorizon fluctuations at BBN can result only in a homogeneous element distribution at present.

A violation of Bell-CHSH inequalities does not justify speculations about quantum non-locality, conspiracy and retro-causation. Such speculations are rooted in a belief that setting dependence of hidden variables in a probabilistic model, called a violation of measurement independence, would mean a violation of experimenters freedom of choice. This belief is unfounded because it is based on a questionable use of Bayes Theorem and on incorrect causal interpretation of conditional probabilities. In Bell-local realistic model, hidden variables describe only photonic beams created by a source, thus they cannot depend on randomly chosen experimental settings. However, if hidden variables describing measuring instruments are correctly incorporated into a contextual probabilistic model a violation of inequalities and an apparent violation of no-signaling reported in Bell tests can be explained without evoking quantum nonlocality. Therefore, for us, a violation of Bell-CHSH inequalities proves only that hidden variables have to depend on settings confirming contextual character of quantum observables and an active role played by measuring instruments. Bell thought that he had to choose bet