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Let ${\mathfrak{G}}\subset\mathbb{R}^{3}$ with $vol(\mathfrak{G})\sim L^{3}$. Let ${\mathscr{T}}(x)$ be a Gaussian random field $\forall~x\in\mathfrak{G}$ with expectation $\mathbf{E}[{\mathscr{T}}(x)]=0$ and correlation $\mathbf{E}[{\mathscr{T}}(x)\otimes{\mathscr{T}}(y)]=K(x,y;\lambda)$, an isotropic and regulated kernel with correlation length $\lambda$. The field has a Karhunen-Loeve spectral representation ${\mathscr{T}}(x)=\sum_{I=1}^{\infty}\mathrm{Z}^{1/2}_{I}f_{I}(x)\otimes\mathscr{Z}_{I}$, with eigenvalues $\lbrace\mathrm{Z}_{I}\rbrace$, eigenfunctions $\lbrace f_{I}(x)\rbrace $ and Gaussian random variables $\mathscr{Z}_{I}$ with $\mathbf{E}[\mathscr{Z}_{I}]=0$ and $\mathbf{E}[\mathscr{Z}_{I}\otimes\mathscr{Z}_{J}]=\delta_{IJ}$. If $\mathfrak{G}$ contains incompressible fluid of viscosity $\nu$ with velocity $u_{a}(x,t)$ that evolves via the Navier-Stokes equations with a high 'Reynolds function' $\mathsf{RE}(x,t)=\tfrac{\|u_{a}(x,t)\|L}{\nu} $ then aspects of a turbulent flow with $\mathsf{RE}(x,t)\gg \mathsf{RE}_{*}$, a critical Reynolds number, might be represented by the 'weighted' random field $\mathscr{U}_{a}(x,t)= u_{a}(x,t)+\mathrm{A}u_{a}(x,t)\big(\mathsf{RE}(x,t)-\mathsf{RE}_{*}\big)^{\beta}\sum_{I=1}^{\infty} \mathrm{Z}^{1/2}_{I}f_{I}(x)\otimes\mathscr{Z}_{I}$ where random fluctuations and amplitude scale nonlinearly with $\mathsf{RE}(x,t)$, with mean $\mathbf{E}[{\mathscr{U}}_{a}(x,t)] =u_{a}(x,t)$. In the inviscid limit one can prove an anomalous dissipation-type law \begin{align} \lim_{\nu\rightarrow 0}\bigg(\lim_{u_{a}(x,t)\rightarrow {u}_{a}}\sup~\nu \int_{\mathfrak{G}}\int_{0}^{T}{\mathbf{E}}\bigg[\bigg|{\nabla}_{a}{\mathscr{U}}_{a}(x,s)\bigg|^{2}\bigg]d\mathcal{V}(x) ds\bigg)>0 \end{align} iff $\beta=\tfrac{1}{2}$ and $\sum_{I=1}^{\infty}\mathrm{Z}_{I}\int_{{\mathfrak{G}}}{\nabla}_{a}f_{I}(x){\nabla}^{a}f_{I}(x)d\mathcal{V}(x)>0$., Comment: 58 pages

Wireless local area network (WLAN) access points (APs) are being deployed in high density to improve coverage and throughput. The emerging multiple-input multiple-output (MIMO) implementation for uplink (UL) transmissions promises high per-user throughput and improved aggregate network throughput. However, the high throughput potential of dense UL-MIMO WLAN is impaired by multiple access channel interference and high contention among densely distributed user stations (STAs). We investigate the problem of actualizing the throughput potential of UL-MIMO in high density WLANs via user-AP association. Since user-AP association influences interference and STA contention, a method to optimally distribute STAs among APs is proposed to maximize aggregate users' throughput utility. This problem is transformed into a graph matching problem with the throughput utility function as the graph edge weights. The graph matching problem is solved as a combinatorial problem using a modified classical Kuhn-Munkres algorithm. A dynamic implementation of the proposed algorithm is used to periodically update user-AP associations when there are changes in the network due to new entrants and/or user mobility. Simulated dense UL-MIMO WLAN scenarios reveal that the proposed scheme achieves an average of $36.9 \%$, $33.5 \%$, $20.4 \%$ and $11.3 \%$ gains over the default strongest signal first (SSF) association scheme used in conventional WLAN, Greedy [14], SmartAssoc [13] and best performance first (BPF) [5] algorithms, respectively., Comment: 26 pages, 8 figures

Multimodal large language models (LLMs) have achieved notable success across various domains, while research in the medical field has largely focused on unimodal images. Meanwhile, current general-domain multimodal models for videos still lack the capabilities to understand and engage in conversations about surgical videos. One major contributing factor is the absence of datasets in the surgical field. In this paper, we create a new dataset, Surg-QA, consisting of 102,000 surgical video-instruction pairs, the largest of its kind so far. To build such a dataset, we propose a novel two-stage question-answer generation pipeline with LLM to learn surgical knowledge in a structured manner from the publicly available surgical lecture videos. The pipeline breaks down the generation process into two stages to significantly reduce the task complexity, allowing us to use a more affordable, locally deployed open-source LLM than the premium paid LLM services. It also mitigates the risk of LLM hallucinations during question-answer generation, thereby enhancing the overall quality of the generated data. We further train LLaVA-Surg, a novel vision-language conversational assistant capable of answering open-ended questions about surgical videos, on this Surg-QA dataset, and conduct comprehensive evaluations on zero-shot surgical video question-answering tasks. We show that LLaVA-Surg significantly outperforms all previous general-domain models, demonstrating exceptional multimodal conversational skills in answering open-ended questions about surgical videos. We will release our code, model, and the instruction-tuning dataset.

Gaussian processes (GPs) are canonical as surrogates for computer experiments because they enjoy a degree of analytic tractability. But that breaks when the response surface is constrained, say to be monotonic. Here, we provide a mono-GP construction for a single input that is highly efficient even though the calculations are non-analytic. Key ingredients include transformation of a reference process and elliptical slice sampling. We then show how mono-GP may be deployed effectively in two ways. One is additive, extending monotonicity to more inputs; the other is as a prior on injective latent warping variables in a deep Gaussian process for (non-monotonic, multi-input) non-stationary surrogate modeling. We provide illustrative and benchmarking examples throughout, showing that our methods yield improved performance over the state-of-the-art on examples from those two classes of problems.

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

After decades of brown dwarf discovery and follow-up, we can now infer the functional form of the mass distribution within 20 parsecs, which serves as a constraint on star formation theory at the lowest masses. Unlike objects on the main sequence that have a clear luminosity-to-mass correlation, brown dwarfs lack a correlation between an observable parameter (luminosity, spectral type, or color) and mass. A measurement of the brown dwarf mass function must therefore be procured through proxy measurements and theoretical models. We utilize various assumed forms of the mass function, together with a variety of birthrate functions, low-mass cutoffs, and theoretical evolutionary models, to build predicted forms of the effective temperature distribution. We then determine the best fit of the observed effective temperature distribution to these predictions, which in turn reveals the most likely mass function. We find that a simple power law ($dN/dM \propto M^{-\alpha}$) with $\alpha \approx 0.5$ is optimal. Additionally, we conclude that the low-mass cutoff for star formation is $\lesssim0.005M_{\odot}$. We corroborate the findings of Burgasser (2004) which state that the birthrate has a far lesser impact than the mass function on the form of the temperature distribution, but we note that our alternate birthrates tend to favor slightly smaller values of $\alpha$ than the constant birthrate. Our code for simulating these distributions is publicly available. As another use case for this code, we present findings on the width and location of the subdwarf temperature gap by simulating distributions of very old (8-10 Gyr) brown dwarfs., Comment: 13 pages, 14 figures, 1 table, accepted to ApJ

Significant advances have been achieved through the latest improvements in the photometric observations accomplished by the recent space missions, substantially boosting the study of pulsating stars via asteroseismology. The TESS mission has already proven to be of relevance for pulsating white dwarf and pre-white dwarf stars. We report a detailed asteroseismic analysis of the pulsating PG 1159 star NGC 246 (TIC3905338), the central star of the planetary nebula NGC 246, based on high-precision photometric data gathered by the TESS space mission. We reduced TESS observations of NGC 246 and performed a detailed asteroseismic analysis using fully evolutionary PG 1159 models computed accounting for the complete prior evolution of their progenitors. We constrained the mass of this star by comparing the measured mean period spacing with the average of the computed period spacings of the models and also employed the observed individual periods to search for a seismic stellar model. We extracted 17 periodicities from the TESS light curves from the two sectors where NGC246 was observed. All the oscillation frequencies are associated with g-mode pulsations, with periods spanning from ~1460 to ~1823s. We found a constant period spacing of $\Delta\Pi= 12.9$s, allowing us to deduce that the stellar mass is larger than ~0.87 Mo if the period spacing is assumed to be associated with l= 1 modes, and ~ 0.568 Mo if it is associated with l= 2 modes. The less massive models are more consistent with the distance constraint from Gaia parallax. Although we were not able to find a unique asteroseismic model for this star, the period-to-period fit analyses suggest a high-stellar mass ($\gtrsim$0.74 Mo) when the observed periods are associated with modes with l= 1 only, and both a high ($\gtrsim$ 0.74 Mo) and intermediate (~0.57 Mo) stellar mass when the observed periods are associated with modes with l= 1 and 2., Comment: 14 pages, 11 figures. Accepted for publication in Astronomy & Astrophysics

Motivated by the stability of the electroweak Higgs vacuum we consider the possibility that the Standard Model might work up to large scales between about $10^{10}$ GeV and close to the Planck scale. A plausible scenario is an emergent Standard Model with gauge symmetries originating in some topological like phase transition deep in the ultraviolet. In this case the cosmological constant scale and neutrino masses should be of similar size, suppressed by factor of the large scale of emergence. The key physics involves a subtle interplay of Poincar\'e invariance, mass generation and renormalisation group invariance. The Higgs mass would be environmentally selected in connection with vacuum stability. Consequences for dark matter scenarios are discussed., Comment: 21 pages, Contribution to "The Particle-Gravity Frontier" theme issue in Philosophical Transactions of the Royal Society A, based on the 2022 Humboldt Kolleg in Kitzb\"uhel

A validation methodology is proposed and implemented for natural language software specifications of standard graphics functions. Checks are made for consistency, completeness, and lack of ambiguity in data element and function descriptions. Functions and data elements are maintained in a relational database representation. The appropriate checks are performed by sequences of database operations. The relational database manager INGRES was used to support a prototype implementation of the proposed technique. The methodology supports the development of a scenario-based prototype from the information available in the specification. This permits various function sequences to be checked without implementation of the environment specified. The application of a prototype implementation of the proposed methodology to the specification of the Graphics Kernel System (GKS) software package demonstrates the practicability of the method. Several inconsistencies in GKS related to the definition of data elements have been identified.

The proton spin puzzle has inspired a vast programme of experiments and theoretical work challenging our understanding of QCD and its role in the structure of hadrons.The proton's internal spin structure is connected to chiral symmetry and, through gluon degrees of freedom in the flavour singlet channel, to the physics of the $\eta'$ meson. Why do quarks contribute just about one third of the proton's spin? Why are $\eta'$ mesons and their interactions so sensitive to gluonic degrees of freedom? We review the status of these topics and some key observables for forthcoming experiments., Comment: 14 pages, in memory of Harald Fritzsch, contribution to the WSPC book edited by G. Buchalla, D. L\"ust and Z.-Z. Xing

Discrete symmetries play an important role in particle physics with violation of CP connected to the matter-antimatter imbalance in the Universe. We report the most precise test of P, T and CP invariance in decays of ortho-positronium, performed with methodology involving polarization of photons from these decays. Positronium, the simplest bound state of an electron and positron, is of recent interest with discrepancies reported between measured hyperfine energy structure and theory at the level of $10^{-4}$ signaling a need for better understanding of the positronium system at this level. We test discrete symmetries using photon polarizations determined via Compton scattering in the dedicated J-PET tomograph on an event-by-event basis and without the need to control the spin of the positronium with an external magnetic field, in contrast to previous experiments. Our result is consistent with QED expectations at the level of 0.0007 and one standard deviation., Comment: 17 pages, 10 figures

A complete accounting of nearby objects -- from the highest-mass white dwarf progenitors down to low-mass brown dwarfs -- is now possible, thanks to an almost complete set of trigonometric parallax determinations from Gaia, ground-based surveys, and Spitzer follow-up. We create a census of objects within a Sun-centered sphere of 20-pc radius and check published literature to decompose each binary or higher-order system into its separate components. The result is a volume-limited census of $\sim$3,600 individual star formation products useful in measuring the initial mass function across the stellar ($<8 M_\odot$) and substellar ($\gtrsim 5 M_{Jup}$) regimes. Comparing our resulting initial mass function to previous measurements shows good agreement above 0.8$M_\odot$ and a divergence at lower masses. Our 20-pc space densities are best fit with a quadripartite power law, $\xi(M) = dN/dM \propto M^{-\alpha}$ with long-established values of $\alpha = 2.3$ at high masses ($0.55 < M < 8.00 M_\odot$) and $\alpha = 1.3$ at intermediate masses ($0.22 < M < 0.55 M_\odot$), but at lower masses we find $\alpha = 0.25$ for $0.05 < M <0.22 M_\odot$ and $\alpha = 0.6$ for $0.01 < M < 0.05 M_\odot$. This implies that the rate of production as a function of decreasing mass diminishes in the low-mass star/high-mass brown dwarf regime before increasing again in the low-mass brown dwarf regime. Correcting for completeness, we find a star to brown dwarf number ratio of, currently, 4:1, and an average mass per object of 0.41 $M_\odot$., Comment: Accepted for publication in The Astrophysical Journal Supplement Series. 123 pages with four ancillary files

KIC 8462852 is a star in the Kepler field that exhibits almost unique behaviour. The deep, irregular and aperiodic dips in its light curve have been interpreted as the breakup of a large exocomet on a highly eccentric orbit whose post-disruption material obscures the star. It is hypothesised that a nearby M-dwarf, recently confirmed to be bound to the system, could be exciting planetesimals in a source belt to high eccentricities if its orbit is highly misaligned with the belt: an effect known as the 'Eccentric Kozai-Lidov Mechanism'. To quantify how often this effect is expected to occur, this paper presents a Monte Carlo model of wide binary stars with embedded, misaligned planetesimal belts. These belts collisionally erode over time until they are excited to high eccentricities on secular timescales by a companion star if its orbit is sufficiently misaligned. The large planetesimals then produce an observable dimming signature in the light curve for a set period of time which may or may not overlap with similar events. The model finds that, for dimming events that persist for 100 yr, the most likely companion stars are located at $10^2 - 10^4$ au, the most likely belts are at $10^2-10^3$ au and the system age is most likely to be $10^2 - 10^3$ Myr. However, the probability of observing one or more stars exhibiting this phenomenon in the Kepler field is $1.3 \times 10^{-3}$, such that it is unlikely this mechanism is driving the observations of KIC 8462852., Comment: 23 pages, 24 figures and 2 tables. This is a pre-copyedited, author-produced PDF of an article accepted for publication in MNRAS following peer review