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Symptom phenotypes are one of the key types of manifestations for diagnosis and treatment of various disease conditions. However, the diversity of symptom terminologies is one of the major obstacles hindering the analysis and knowledge sharing of various types of symptom-related medical data particularly in the fields of Traditional Chinese Medicine (TCM). Objective: This study aimed to construct an Integrated Ontology of symptom phenotypes (ISPO) to support the data mining of Chinese EMRs and real-world study in TCM field. Methods: To construct an integrated ontology of symptom phenotypes (ISPO), we manually annotated classical TCM textbooks and large-scale Chinese electronic medical records (EMRs) to collect symptom terms with support from a medical text annotation system. Furthermore, to facilitate the semantic interoperability between different terminologies, we incorporated public available biomedical vocabularies by manual mapping between Chinese terms and English terms with cross-references to source vocabularies. In addition, we evaluated the ISPO using independent clinical EMRs to provide a high-usable medical ontology for clinical data analysis. Results: By integrating 78,696 inpatient cases of EMRs, 5 biomedical vocabularies, 21 TCM books and dictionaries, ISPO provides 3,147 concepts, 23,475 terms, and 55,552 definition or contextual texts. Adhering to the taxonomical structure of the related anatomical systems of symptom phenotypes, ISPO provides 12 top-level categories and 79 middle-level sub-categories. The validation of data analysis showed the ISPO has a coverage rate of 95.35%, 98.53% and 92.66% for symptom terms with occurrence rates of 0.5% in additional three independent curated clinical datasets, which can demonstrate the significant value of ISPO in mapping clinical terms to ontologies., Comment: 39 pages, 6 figures, 6 tables

Consider an eigenfunction of the Laplacian on a torus. How small can its $L^2$-norm be on small balls? We provide partial answers to this question by exploiting the distribution of integer points on spheres, basic properties of polynomials, and Nazarov--Tur\'an type estimates for exponential polynomials. Applications to quantum limits and control theory are given., Comment: 18 pages

Magnetic field line curvature (FLC) scattering is an effective mechanism for collisionless particle scattering. In the terrestrial magnetosphere, the FLC scattering plays an essential role in shaping the outer boundary of protons radiation belt, the rapid decay of ring current, and the formation of proton isotropic boundary (IB). However, previous studies have yet to adequately investigate the influence of FLC scattering on charged particles in the Earth's dayside magnetosphere, particularly in the off-equatorial magnetic minima regions. This study employs T89 magnetic field model to investigate the impacts of FLC scattering on ring current protons in the dayside magnetosphere, with a specific focus on the off-equatorial minimum regions. We analyze the spatial distributions of single and dual magnetic minima regions, adiabatic parameter, and pitch angle diffusion coefficients due to FLC scattering as functions of $Kp$. The results show that the effects of FLC scattering are significant not only on the dusk and dawn sides but also in the off-equatorial minima regions on the noon. Additionally, we investigate the role of dipole tilt angle in the hemispheric asymmetry of FLC scattering effects. The dipole tilt angle controls the overall displacement of the dayside magnetosphere, resulting in different FLC scattering effects in the two hemispheres. Our study holds significance for understanding the FLC scattering effects in the off-equatorial region of Earth's dayside magnetosphere and for constructing a more accurate dynamic model of particles.

In this paper, we prove that there exists a Zariski dense open subset $U$ in the parameter space of all elementary $p$-covers of the projective line that ramified at exactly one point, defined over the rationals, such that for every curve $X$ in $U(\overline{Q})$ and for any prime $p$ large enough, the reduction of $X$ at all primes lying over $p$ achieves its generic Newton slopes.

On compact Riemannian manifolds with chaotic geometries, specifically those exhibiting the random wave model conjectured by Berry, we derive heuristically a homogeneous kinetic wave equation that is universal for all such manifolds., Comment: 9 pages

A superradiant cloud of ultralight bosons near a rotating black hole provides a smoking gun for particle physics in the infrared. However, tidal perturbations from a nearby binary companion can destabilise the boson cloud and even terminate superradiance. In this work, we consider the backreaction of superradiance termination to the dynamics of general binary orbits parametrised by their semi-latus rectum, eccentricity and inclination angle. Our analysis focuses on Extreme Mass Ratio Inspiral (EMRI) systems and employs the period-average approximation to derive evolution equations of these binary parameters in the Newtonian limit. We find that the binary evolution history can be significantly modulated by the backreaction towards large circular equatorial orbits with reduced termination rate. This process can generically happen even away from the resonance bands. Our work therefore serves as a first step towards probing ultralight bosons through the statistics of EMRI binary parameters in the future., Comment: 13 pages, 5 figures

The Segment Anything Model (SAM) has shown impressive performance when applied to natural image segmentation. However, it struggles with geographical images like aerial and satellite imagery, especially when segmenting mobility infrastructure including roads, sidewalks, and crosswalks. This inferior performance stems from the narrow features of these objects, their textures blending into the surroundings, and interference from objects like trees, buildings, vehicles, and pedestrians - all of which can disorient the model to produce inaccurate segmentation maps. To address these challenges, we propose Geographical SAM (GeoSAM), a novel SAM-based framework that implements a fine-tuning strategy using the dense visual prompt from zero-shot learning, and the sparse visual prompt from a pre-trained CNN segmentation model. The proposed GeoSAM outperforms existing approaches for geographical image segmentation, specifically by 26%, 7%, and 17% for road infrastructure, pedestrian infrastructure, and on average, respectively, representing a momentous leap in leveraging foundation models to segment mobility infrastructure including both road and pedestrian infrastructure in geographical images. The source code can be found on this GitHub repository: https://github.com/rafiibnsultan/GeoSAM/tree/main.

We introduce a simplified model for wave turbulence theory -- the Wick NLS, of which the main feature is the absence of all self-interactions in the correlation expansions of its solutions. For this model, we derive several wave kinetic equations that govern the effective statistical behavior of its solutions in various regimes. In the homogeneous setting, where the initial correlation is translation invariant, we obtain a wave kinetic equation similar to the one predicted by the formal theory. In the inhomogeneous setting, we obtain a wave kinetic equation that describes the statistical behavior of the wavepackets of the solutions, accounting for both the transport of wavepackets and collisions among them. Another wave kinetic equation, which seems new in the literature, also appears in a certain scaling regime of this setting and provides a more refined collision picture., Comment: 44 pages