Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms

This paper studies a new task of federated learning (FL) for semantic parsing, where multiple clients collaboratively train one global model without sharing their semantic parsing data. By leveraging data from multiple clients, the FL paradigm can be especially beneficial for clients that have little training data to develop a data-hungry neural semantic parser on their own. We propose an evaluation setup to study this task, where we re-purpose widely-used single-domain text-to-SQL datasets as clients to form a realistic heterogeneous FL setting and collaboratively train a global model. As standard FL algorithms suffer from the high client heterogeneity in our realistic setup, we further propose a novel LOss Reduction Adjusted Re-weighting (Lorar) mechanism to mitigate the performance degradation, which adjusts each client's contribution to the global model update based on its training loss reduction during each round. Our intuition is that the larger the loss reduction, the further away the current global model is from the client's local optimum, and the larger weight the client should get. By applying Lorar to three widely adopted FL algorithms (FedAvg, FedOPT and FedProx), we observe that their performance can be improved substantially on average (4%-20% absolute gain under MacroAvg) and that clients with smaller datasets enjoy larger performance gains. In addition, the global model converges faster for almost all the clients.Comment: ACL 2023 long pape

Federated Cross Learning for Medical Image Segmentation

Federated learning (FL) can collaboratively train deep learning models using isolated patient data owned by different hospitals for various clinical applications, including medical image segmentation. However, a major problem of FL is its performance degradation when dealing with the data that are not independently and identically distributed (non-iid), which is often the case in medical images. In this paper, we first conduct a theoretical analysis on the FL algorithm to reveal the problem of model aggregation during training on non-iid data. With the insights gained through the analysis, we propose a simple and yet effective method, federated cross learning (FedCross), to tackle this challenging problem. Unlike the conventional FL methods that combine multiple individually trained local models on a server node, our FedCross sequentially trains the global model across different clients in a round-robin manner, and thus the entire training procedure does not involve any model aggregation steps. To further improve its performance to be comparable with the centralized learning method, we combine the FedCross with an ensemble learning mechanism to compose a federated cross ensemble learning (FedCrossEns) method. Finally, we conduct extensive experiments using a set of public datasets. The experimental results show that the proposed FedCross training strategy outperforms the mainstream FL methods on non-iid data. In addition to improving the segmentation performance, our FedCrossEns can further provide a quantitative estimation of the model uncertainty, demonstrating the effectiveness and clinical significance of our designs. Source code will be made publicly available after paper publication.Comment: 10 pages, 4 figure

Atmospheric nitrous acid (HONO) at a rural coastal site in North China: Seasonal variations and effects of biomass burning

Nitrous acid (HONO) plays a significant role in atmospheric chemistry due to its contribution to hydroxyl radical (OH). However, no scientific consensus has been achieved about the daytime HONO formation mechanisms. To identify the seasonal variations of HONO chemistry and the impacts of biomass burning (BB), we performed a two-phased field study in winter-spring and summer (covering a harvest season) in 2017 at a rural coastal site in North China. Though the mean HONO concentration in winter-spring (0.26 +/- 0.28 ppbv) was higher than in summer (0.17 + 0.19 ppbv), the maximum HONO concentrations were comparable (similar to 2 ppbv) in the two campaigns. Both the HONO/NOx ratio and nocturnal heterogeneous conversion efficiency of HONO (C-HONO) in summer were over twice of that in winter-spring. The daytime budget analysis also revealed that the strength of P(othe)r (i.e., the HONO sources apart from the reaction of OH + NO) in summer was double of that in winter-spring. BB affected the HONO concentration by enhancing the contribution of heterogeneous HONO production on the aerosol surface but weakening the role of photo-related HONO formation. HONO photolysis was a significant source of OH in both winter-spring and summer, and its contribution could be further enhanced during the BB episode in summer. Our study demonstrates the significant seasonal variations of HONO and the effects of BB, and suggests needs for more multi-season observations and considerations of BB, especially during the harvest time, in HONO research

OGLE-2018-BLG-0532Lb: Cold Neptune With Possible Jovian Sibling

We report the discovery of the planet OGLE-2018-BLG-0532Lb, with very obvious signatures in the light curve that lead to an estimate of the planet-host mass ratio $q=M_{\rm planet}/M_{\rm host}\simeq 1\times10^{-4}$. Although there are no obvious systematic residuals to this double-lens/single-source (2L1S) fit, we find that $\chi^2$ can be significantly improved by adding either a third lens (3L1S, $\Delta\chi^2=81$) or second source (2L2S, $\Delta\chi^2=65$) to the lens-source geometry. After thorough investigation, we conclude that we cannot decisively distinguish between these two scenarios and therefore focus on the robustly-detected planet. However, given the possible presence of a second planet, we investigate to what degree and with what probability such additional planets may affect seemingly single-planet light curves. Our best estimates for the properties of the lens star and the secure planet are: a host mass $M\sim 0.25\,M_\odot$, system distance $D_L\sim 1\,$kpc and planet mass $m_{p,1}= 8\,M_\oplus$ with projected separation $a_{1,\perp}=1.4\,$au. However, there is a relatively bright $I=18.6$ (and also relatively blue) star projected within $<50\,$mas of the lens, and if future high-resolution images show that this is coincident with the lens, then it is possible that it is the lens, in which case, the lens would be both more massive and more distant than the best-estimated values above.Comment: 48 pages, 9 figures, 7 table

LncRNA KCNQ1OT1 Mediates Pyroptosis in Diabetic Cardiomyopathy

Background/Aims: Diabetic cardiomyopathy (DCM) is a common complication of diabetes and can cause heart failure, arrhythmia and sudden death. The pathogenesis of DCM includes altered metabolism, mitochondrial dysfunction, oxidative stress, inflammation, cell death and extracellular matrix remodeling. Recently, pyroptosis, a type of programmed cell death related to inflammation, was proven to be activated in DCM. However, the molecular mechanisms underlying pyroptosis in DCM remain elusive. The long non-coding RNA (lncRNA) Kcnq1ot1 participates in many cardiovascular diseases. This study aims to clarify whether Kcnq1ot1 affects cardiac pyroptosis in DCM. Methods: AC16 cells and primary cardiomyocytes were incubated with 5.5 and 50 mmol/L glucose. Diabetic mice were induced with streptozotocin (STZ). Kcnq1ot1 was silenced both in vitro and in vivo. qRT-PCR was used to detect the expression level of Kcnq1ot1. Immunofluorescence, qRT-PCR and western blot analyses were used to detect the degree of pyroptosis. Echocardiography, hematoxylin and eosin staining, and Masson’s trichrome staining were used to detect the cardiac function and morphology in mice. Cell death and function were detected using TUNEL staining, immunofluorescence staining and Ca2+ measurements. Results: The expression of Kcnq1ot1 was increased in patients with diabetes, high glucose-induced cardiomyocytes and diabetic mouse cardiac tissue. Silencing Kcnq1ot1 alleviated pyroptosis by targeting miR-214-3p and caspase-1. Furthermore, silencing Kcnq1ot1 reduced cell death, cytoskeletal structure abnormalities and calcium overload in vitro and improved cardiac function and morphology in vivo. Conclusion: Kcnq1ot1 is overexpressed in DCM, and silencing Kcnq1ot1 inhibits pyroptosis by influencing miR-214-3p and caspase-1 expression. We clarified for the first time that Kcnq1ot1 could be a new therapeutic target for DCM

SpitzerSpitzer Parallax of OGLE-2018-BLG-0596: A Low-mass-ratio Planet around an M-dwarf

We report the discovery of a $Spitzer$ microlensing planet OGLE-2018-BLG-0596Lb, with preferred planet-host mass ratio $q \sim 2\times10^{-4}$. The planetary signal, which is characterized by a short $(\sim 1~{\rm day})$ "bump" on the rising side of the lensing light curve, was densely covered by ground-based surveys. We find that the signal can be explained by a bright source that fully envelops the planetary caustic, i.e., a "Hollywood" geometry. Combined with the source proper motion measured from $Gaia$, the $Spitzer$ satellite parallax measurement makes it possible to precisely constrain the lens physical parameters. The preferred solution, in which the planet perturbs the minor image due to lensing by the host, yields a Uranus-mass planet with a mass of $M_{\rm p} = 13.9\pm1.6~M_{\oplus}$ orbiting a mid M-dwarf with a mass of $M_{\rm h} = 0.23\pm0.03~M_{\odot}$. There is also a second possible solution that is substantially disfavored but cannot be ruled out, for which the planet perturbs the major image. The latter solution yields $M_{\rm p} = 1.2\pm0.2~M_{\oplus}$ and $M_{\rm h} = 0.15\pm0.02~M_{\odot}$. By combining the microlensing and $Gaia$ data together with a Galactic model, we find in either case that the lens lies on the near side of the Galactic bulge at a distance $D_{\rm L} \sim 6\pm1~{\rm kpc}$. Future adaptive optics observations may decisively resolve the major image/minor image degeneracy.Comment: 34 pages, 8 figures, Submitted to AAS journa

KMT-2016-BLG-1397b: KMTNET-only Discovery of a Microlens Giant Planet

We report the discovery of a giant planet in the KMT-2016-BLG-1397 microlensing event, which was found by The Korea Microlensing Telescope Network alone. The timescale of this event is tE = 40.0 ± 0.5 days, and the mass ratio between the lens star and its companion is q = 0.016 ± 0.002. The planetary perturbation in the light curve is a smooth bump, resulting in the classical binary-lens/binary-source (2L1S/1L2S) degeneracy. We measure the V − I color of the (putative) two sources in the 1L2S model, and then effectively rule out the binary-source solution. The finite-source effect is marginally detected. Combined with the limits on the blend flux and the probability distribution of the source size normalized by the Einstein radius ρ, a Bayesian analysis yields the lens mass M_L = 0.45^(+0.33)_(-0.28) M⊙, at distance of D_L = 6.60^(+1.10)_(-1.30) kpc. Thus, the companion is a super-Jupiter of a mass m_p = 7.0^(+5.2)_(-4.3) M_J, at a projected separation r_⊥ = 5.1^(+1.5)_(-1.7) au, indicating that the planet is well beyond the snow line of the host star