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We present applications of the full-wave solver, Petra-M code for Earth magnetospheric plasma wave physics by leveraging the current effort of the radio frequency wave project. Because the Petra-M code uses the modular finite element method (MFEM) library, the boundary shapes, plasma density profiles, and realistic planetary magnetic fields can be easily adapted. In order to incorporate realistic Earth’s magnetic field into the Petra-M, we utilize the self-consistent magnetospheric flux models for compressed and stretched magnetic fields and realistic magnetospheric magnetic field geometries extracted from global MHD simulations. Using Petra-M code, we then examine ultra-low frequency (ULF) wave propagations in various magnetic field shapes. For example, left-handed polarized electromagnetic ion cyclotron waves in Earth’s dipole and compressed magnetic field are examined to consider waves in the inner and dayside outer magnetospheres, respectively. Mode-converted Alfvén wave propagation is also demonstrated in the compressed (dayside), stretched(nightside), and realistically stretched magnetic field (magnetotail). Therefore, the Petra-M code successfully demonstrates magnetospheric plasma wave propagation despite the spatial scale differences between the fusion devices (~m) and Earth’s magnetosphere (103 − 104km). 

OBJECTIVES: Prediction and determination of drug efficacy for radiographic progression is limited by the heterogeneity inherent in axial spondyloarthritis (axSpA). We investigated whether unbiased clustering analysis of phenotypic data can lead to coherent subgroups of axSpA patients with a distinct risk of radiographic progression. METHODS: A group of 412 patients with axSpA was clustered in an unbiased way using a agglomerative hierarchical clustering method, based on their phenotype mapping. We used a generalised linear model, naïve Bayes, Decision Trees, K-Nearest-Neighbors, and Support Vector Machines to construct a consensus classification method. Radiographic progression over 2 years was assessed using the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). RESULTS: axSpA patients were classified into three distinct subgroups with distinct clinical characteristics. Sex, smoking, HLA-B27, baseline mSASSS, uveitis, and peripheral arthritis were the key features that were found to stratifying the phenogroups. The three phenogroups showed distinct differences in radiographic progression rate (p<0.05) and the proportion of progressors (p<0.001). Phenogroup 2, consisting of male smokers, had the worst radiographic progression, while phenogroup 3, exclusively suffering from uveitis, showed the least radiographic progression. The axSpA phenogroup classification, including its ability to stratify risk, was successfully replicated in an independent validation group. CONCLUSIONS: Phenotype mapping results in a clinically relevant classification of axSpA that is applicable for risk stratification. Novel coupling between phenotypic features and radiographic progression can provide a glimpse into the mechanisms underlying divergent and shared features of axSpA. 

Abstract The anomalous diffusion of resonant protons in parallel and perpendicular velocity space by kinetic Alfvén waves is discussed. The velocity diffusion coefficient is calculated by employing an autocorrelation function for proton trajectories. It is found that for protons resonant with the waves, the perpendicular diffusion coefficient decays away for a sufficiently long time, but parallel diffusion monotonically increases in time until it saturates at a certain level. This result indicates that a portion of resonant protons can undergo anomalous diffusion along the background magnetic field even if the intensity of the kinetic Alfvén wave is sufficiently low. The present findings imply that under suitable conditions, astrophysical charged-particle acceleration can take place in the parallel direction. 

Abstract We present a background model for dark matter searches using an array of NaI(Tl) crystals in the COSINE-100 experiment that is located in the Yangyang underground laboratory. The model includes background contributions from both internal and external sources, including cosmogenic radionuclides and surface $$^{210}$$ 210 Pb contamination. To build the model in the low energy region, with a threshold of 1 keV, we used a depth profile of $$^{210}$$ 210 Pb contamination in the surface of the NaI(Tl) crystals determined in a comparison between measured and simulated spectra. We also considered the effect of the energy scale errors propagated from the statistical uncertainties and the nonlinear detector response at low energies. The 1.7 years COSINE-100 data taken between October 21, 2016 and July 18, 2018 were used for this analysis. Our Monte Carlo simulation provides a non-Gaussian peak around 50 keV originating from beta decays of bulk $$^{210}$$ 210 Pb in a good agreement with the measured background. This model estimates that the activities of bulk $$^{210}$$ 210 Pb and $$^{3}$$ 3 H are dominating the background rate that amounts to an average level of $$2.85\pm 0.15$$ 2.85 ± 0.15  counts/day/keV/kg in the energy region of (1–6) keV, using COSINE-100 data with a total exposure of 97.7 kg $$\cdot $$ · years.