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This research paper explores ways to apply Federated Learning (FL) and Differential Privacy (DP) techniques to population-scale Electrocardiogram (ECG) data. The study learns a multi-label ECG classification model using FL and DP based on 1,565,849 ECG tracings from 7 hospitals in Alberta, Canada. The FL approach allowed collaborative model training without sharing raw data between hospitals while building robust ECG classification models for diagnosing various cardiac conditions. These accurate ECG classification models can facilitate the diagnoses while preserving patient confidentiality using FL and DP techniques. Our results show that the performance achieved using our implementation of the FL approach is comparable to that of the pooled approach, where the model is trained over the aggregating data from all hospitals. Furthermore, our findings suggest that hospitals with limited ECGs for training can benefit from adopting the FL model compared to single-site training. In addition, this study showcases the trade-off between model performance and data privacy by employing DP during model training. Our code is available at https://github.com/vikhyatt/Hospital-FL-DP., Comment: Accepted for ICMHI 2024

This study investigates the escape of Mercury's sodium-group ions (Na+-group, including ions with m/q from 21 to 30 amu/e) and their dependence on true anomaly angle (TAA), i.e., Mercury's orbital phase around the Sun, using measurements from MESSENGER. The measurements are categorized into solar wind, magnetosheath, and magnetosphere, and further divided into four TAA intervals. Na+-group ions form escape plumes in the solar wind and magnetosheath, with higher fluxes along the solar wind's motional electric field. The total escape rates vary from 0.2 to 1 times 10^{25} atoms/s with the magnetosheath being the main escaping region. These rates exhibit a TAA dependence, peaking near the perihelion and similar during Mercury's remaining orbit. Despite Mercury's tenuous exosphere, Na+-group ions escape rate is comparable to other inner planets. This can be attributed to several processes, including that Na+-group ions may include several ion species, efficient photoionization frequency for elements within Na+-group, etc., Comment: 21 pages, 4 figures

One straightforward metric to evaluate a survival prediction model is based on the Mean Absolute Error (MAE) -- the average of the absolute difference between the time predicted by the model and the true event time, over all subjects. Unfortunately, this is challenging because, in practice, the test set includes (right) censored individuals, meaning we do not know when a censored individual actually experienced the event. In this paper, we explore various metrics to estimate MAE for survival datasets that include (many) censored individuals. Moreover, we introduce a novel and effective approach for generating realistic semi-synthetic survival datasets to facilitate the evaluation of metrics. Our findings, based on the analysis of the semi-synthetic datasets, reveal that our proposed metric (MAE using pseudo-observations) is able to rank models accurately based on their performance, and often closely matches the true MAE -- in particular, is better than several alternative methods., Comment: Accepted to ICML 2023

Implementing arbitrary single-qubit gates with near perfect fidelity is among the most fundamental requirements in gate-based quantum information processing. In this work, we fabric a transmon qubit with long coherence times and demonstrate single-qubit gates with the average gate error below $10^{-4}$, i.e. $(7.42\pm0.04)\times10^{-5}$ by randomized benchmarking (RB). To understand the error sources, we experimentally obtain an error budget, consisting of the decoherence errors lower bounded by $(4.62\pm0.04)\times10^{-5}$ and the leakage rate per gate of $(1.16\pm0.04)\times10^{-5}$. Moreover, we reconstruct the process matrices for the single-qubit gates by the gate set tomography (GST), with which we simulate RB sequences and obtain single-qubit fedlities consistent with experimental results. We also observe non-Markovian behavior in the experiment of long-sequence GST, which may provide guidance for further calibration. The demonstration extends the upper limit that the average fidelity of single-qubit gates can reach in a transmon-qubit system, and thus can be an essential step towards practical and reliable quantum computation in the near future.

In general, slow solar wind from the streamer belt forms a high plasma beta equatorial plasma sheet around the heliospheric current sheet (HCS) crossing, namely the heliospheric plasma sheet (HPS). Current Parker Solar Probe (PSP) observations show that the HCS crossings near the Sun could be full or partial current sheet crossing (PCS), and they share some common features but also have different properties. In this work, using the PSP observations from encounters 4 to 10, we identify streamer belt solar wind from enhancements in plasma beta, and we further use electron pitch angle distributions to separate it into HPS solar wind that around the full HCS crossings and PCS solar wind that in the vicinity of PCS crossings. Based on our analysis, we find that the PCS solar wind has different characteristics as compared with HPS solar wind: a) PCS solar wind could be non-pressure-balanced structures rather than magnetic holes, and the total pressure enhancement mainly results from the less reduced magnetic pressure; b) some of the PCS solar wind are mirror unstable; c) PCS solar wind is dominated by very low helium abundance but varied alpha-proton differential speed. We suggest the PCS solar wind could originate from coronal loops deep inside the streamer belt, and it is pristine solar wind that still actively interacts with ambient solar wind, thus it is valuable for further investigations on the heating and acceleration of slow solar wind.

We explore the topology-disorder phase diagram by simulating one-dimensional Su-Schrieffer-Heeger (SSH) model with quasiperiodic disorder using a programmable superconducting simulator. We experimentally map out and identify various trivial and topological phases with extended and localized bulk states. We find that in the topological phase the bulk states can be critically localized without mobility edge or contain both critically and completely localized states. In addition, there exist trivial and topological intermediate phases with mobility edge and coexistence of extended and completely localized states. The presence of the surprisingly rich phases in the simple SSH model with quasiperiodic disorder sheds new light on the investigation of the topological and localization phenomena in condensed-matter physics., Comment: 5 pages, 4 figures

Pandemic outbreaks such as COVID-19 occur unexpectedly, and need immediate action due to their potential devastating consequences on global health. Point-of-care routine assessments such as electrocardiogram (ECG), can be used to develop prediction models for identifying individuals at risk. However, there is often too little clinically-annotated medical data, especially in early phases of a pandemic, to develop accurate prediction models. In such situations, historical pre-pandemic health records can be utilized to estimate a preliminary model, which can then be fine-tuned based on limited available pandemic data. This study shows this approach -- pre-train deep learning models with pre-pandemic data -- can work effectively, by demonstrating substantial performance improvement over three different COVID-19 related diagnostic and prognostic prediction tasks. Similar transfer learning strategies can be useful for developing timely artificial intelligence solutions in future pandemic outbreaks., Comment: Accepted for NeurIPS 2022 TS4H workshop

Electrocardiogram (ECG) abnormalities are linked to cardiovascular diseases, but may also occur in other non-cardiovascular conditions such as mental, neurological, metabolic and infectious conditions. However, most of the recent success of deep learning (DL) based diagnostic predictions in selected patient cohorts have been limited to a small set of cardiac diseases. In this study, we use a population-based dataset of >250,000 patients with >1000 medical conditions and >2 million ECGs to identify a wide range of diseases that could be accurately diagnosed from the patient's first in-hospital ECG. Our DL models uncovered 128 diseases and 68 disease categories with strong discriminative performance., Comment: Accepted in Medical Imaging meets NeurIPS 2021 https://www.cse.cuhk.edu.hk/~qdou/public/medneurips2021/88_ECG_for_high-throughput_screening_of_multiple_diseases_final_version.pdf

At Mercury, several processes can release ions and neutrals out of the planet's surface. Here we present enhancements of dayside planetary ions in the solar wind entry layer during flux transfer event (FTE) "showers" near Mercury's northern magnetospheric cusp. The FTE showers correspond to the intervals of intense magnetopause reconnection of Mercury's magnetosphere, which form a solar wind entry layer equatorward of the magnetospheric cusps. In this entry layer, solar wind ions are accelerated and move downward (i.e. planetward) toward the cusps, which sputter upward-moving planetary ions within 1 minute. The precipitation rate is enhanced by an order of magnitude during FTE showers and the neutral density of the exosphere can vary by >10% due to this FTE-driven sputtering. These in situ observations of enhanced planetary ions in the entry layer likely correspond to an escape channel of Mercury's planetary ions, and the large-scale variations of the exosphere observed on minute-timescales by Earth observatories. Comprehensive, future multi-point measurements made by BepiColombo will greatly enhance our understanding of the processes contributing to Mercury's dynamic exosphere and magnetosphere., Comment: 34 pages, 10 figures, 1 table

This review summarizes the research of Mercury's magnetosphere in the Post-MESSENGER era and compares its dynamics to those in other planetary magnetospheres, especially to those in Earth's magnetosphere. This review starts by introducing the planet Mercury, including its interplanetary environment, magnetosphere, exosphere, and conducting core. The frequent and intense magnetic reconnection on the dayside magnetopause, which is represented by the flux transfer event "shower", is reviewed on how they depend on magnetosheath plasma beta and magnetic shear angle across the magnetopause, following by how they contribute to the flux circulation and magnetosphere-surface-exosphere coupling. In the next, the progress of Mercury's magnetosphere under extreme solar events, including the core induction and the reconnection erosion on the dayside magnetosphere, the responses of the nightside magnetosphere, are reviewed. Then, the dawn-dusk properties of the plasma sheet, including the features of the ions, the structure of the current sheet, and the dynamics of magnetic reconnection, are summarized. The last topic reviews the particle energization in Mercury's magnetosphere, which includes the energization of the Kelvin-Helmholtz waves on the magnetopause boundaries, reconnection-generated magnetic structures, and the cross-tail electric field. In each chapter, the last section discusses the open questions related with each topic, which can be considered by the simulations and the future spacecraft mission. We close by summarizing the future BepiColombo opportunities, which is a joint mission between ESA and JAXA, and is en route to Mercury., Comment: 50 pages, 28 figures, 4 tables, Published by Science China Earth Sciences

The 12-lead electrocardiogram (ECG) is a commonly used tool for detecting cardiac abnormalities such as atrial fibrillation, blocks, and irregular complexes. For the PhysioNet/CinC 2020 Challenge, we built an algorithm using gradient boosted tree ensembles fitted on morphology and signal processing features to classify ECG diagnosis. For each lead, we derive features from heart rate variability, PQRST template shape, and the full signal waveform. We join the features of all 12 leads to fit an ensemble of gradient boosting decision trees to predict probabilities of ECG instances belonging to each class. We train a phase one set of feature importance determining models to isolate the top 1,000 most important features to use in our phase two diagnosis prediction models. We use repeated random sub-sampling by splitting our dataset of 43,101 records into 100 independent runs of 85:15 training/validation splits for our internal evaluation results. Our methodology generates us an official phase validation set score of 0.476 and test set score of -0.080 under the team name, CVC, placing us 36 out of 41 in the rankings., Comment: 4 pages, 4 figures, 2020 Computing in Cardiology (CinC) PhysioNet Challenge

MESSENGER has observed a lot of dawn-dusk asymmetries in Mercury's magnetotail, such as the asymmetries of the cross-tail current sheet thickness and the occurrence of flux ropes, dipolarization events and energetic electron injections. In order to obtain a global pictures of Mercury's magnetotail dynamics and the relationship between these asymmetries, we perform global simulations with the magnetohydrodynamics with embedded particle-in-cell (MHD-EPIC) model, where Mercury's magnetotail region is covered by a PIC code. Our simulations show that the dawnside current sheet is thicker, the plasma density is larger, and the electron pressure is higher than the duskside. Under a strong IMF driver, the simulated reconnection sites prefer the dawnside. We also found the dipolarization events and the planetward electron jets are moving dawnward while they are moving towards the planet, so that almost all dipolarization events and high-speed plasma flows concentrate in the dawn sector. The simulation results are consistent with MESSENGER observations.

Using 3D particle-in-cell (PIC) simulations, we study magnetic reconnection with the x-line being spatially confined in the current direction. We include thick current layers to prevent reconnection at two ends of a thin current sheet that has a thickness on an ion inertial (di) scale. The reconnection rate and outflow speed drop significantly when the extent of the thin current sheet in the current direction is < O(10 di). When the thin current sheet extent is long enough, we find it consists of two distinct regions; an inactive region (on the ion-drifting side) exists adjacent to the active region where reconnection proceeds normally as in a 2D case. The extent of this inactive region is ~ O(10 di), and it suppresses reconnection when the thin current sheet extent is comparable or shorter. The time-scale of current sheet thinning toward fast reconnection can be translated into the spatial-scale of this inactive region; because electron drifts inside the ion diffusion region transport the reconnected magnetic flux, that drives outflows and furthers the current sheet thinning, away from this region. This is a consequence of the Hall effect in 3D. While this inactive region may explain the shortest possible azimuthal extent of dipolarizing flux bundles at Earth, it may also explain the dawn-dusk asymmetry observed at the magnetotail of Mercury, that has a global dawn-dusk extent much shorter than that of Earth., Comment: 9 pages, 9 figures, submitted to JGR on 01/23/2019