Asymmetry, Gap Opening and High Accretion Rate on DM Tau: A Hypothesis Based on Interaction of Magnetized Disk Wind with Planet

Over two hundred protoplanetary disk systems have been resolved by ALMA, and the vast majority suggest the presence of planets. The dust gaps in transition disks are considered evidence of giant planets sculpting gas and dust under appropriate disk viscosity. However, the unusually high accretion rates in many T Tauri stars hosting transition disks challenge this theory. As the only disk currently observed with high turbulence, the high accretion rate ($\sim10^{-8.3}M_{\odot}/yr$) observed in DM Tau indicates the presence of strong turbulence may within the system. Considering the recent theoretical advancements in magnetized disk winds is challenging the traditional gap-opening theories and viscosity-driven accretion models, our study presents a pioneering simulation incorporating a simplified magnetized disk wind model to explain the observed features in DM Tau. Employing multi-fluid simulations with an embedded medium mass planet, we successfully replicate the gap formation and asymmetric structures evident in ALMA Band 6 and the recently JVLA 7 mm observations. Our results suggest that when magnetized disk wind dominate the accretion mode of the system, it's entirely possible for a planet with a medium mass to exist within the gap inside 20 au of DM Tau. This means that DM Tau may not be as turbulence as imagined. However, viscosity within the disk should also contribute a few turbulence to maintain disk stability.Comment: 13 pages, 4 figures, accepted by ApJ. Welcome any comments and suggestions

Fertilizer Use in China: The Role of Agricultural Support Policies

Using a decomposition method, this paper proposes an analytical framework to investigate the mechanisms by which agricultural support policies affect farmers’ use of fertilizers in agriculture in China. The mechanisms are decomposed into “three effects” (structural, scale, and technological effects). It is found that China’s agricultural support polices have significantly contributed to the increased use of agricultural fertilizers through encouraging farmers to bring more land under cultivation (the scale effect). Meanwhile, some policies have also helped reduce fertilizer consumption when farmers were motivated to increase the area of grains crops (the structural effect). The role of technological progress in affecting fertilizer consumption (the technological effect) appears to be minimal and uncertain. Compared to direct subsidies, indirect subsidies play a much greater role in affecting farmers’ production decision making and are more environmentally consequential. This paper argues that some of China’s agricultural support policies are not well aligned with one key objective of the country’s rural policies—improving environmental sustainability. It is recommended that the government takes measures to reform agricultural support policies and to reconcile agricultural and rural policies in order to achieve sustainable rural development

Using planet migration and dust drift to weigh protoplanetary discs

ALMA has spatially resolved over 200 annular structures in protoplanetary discs, many of which are suggestive of the presence of planets. Constraining the mass of these putative planets is quite degenerate for it depends on the disc physical properties, and for simplicity a steady-state is often assumed whereby the planet position is kept fixed and there is a constant source of dust at the outer edge of the disc. Here we argue against this approach by demonstrating how the planet and dust dynamics can lift degeneracies of such steady-state models. We take main disc parameters from the well-known protoplanetary disc HD 163296 with a suspected planet at $R\approx 86$~au as an example. By running gas and dust hydrodynamical simulations post-processed with dust radiative transfer calculations, we first find steady-state disc and planet parameters that reproduce ALMA continuum observations fairly well. For the same disc mass, but now allowing the planet to migrate in the simulation, we find that the planet undergoes runaway migration and reaches the inner disc in $\sim 0.2$ Myr. Further, decreasing the disc mass slows down planet migration, but it then also increases the dust's radial drift, thereby depleting the disc dust faster. We find that the opposing constraints of planet migration and dust drift require the disc mass to be at most 0.025~\msun, must less massive than previously estimated, and for the dust to be porous rather than compact. We propose that similar analysis should be extended to other sources with suspected planetary companions.Comment: 15 pages, 9 figures, resubmitted to MNRAS, version addressing referee's comment

Chaotic Type I Migration in Turbulent Discs

By performing global hydrodynamical simulations of accretion discs with driven turbulence models, we demonstrate that elevated levels of turbulence induce highly stochastic migration torques on low-mass companions embedded in these discs. This scenario applies to planets migrating within gravito-turbulent regions of protoplanetary discs as well as stars and black holes embedded in the outskirts of active galactic nuclei (AGN) accretion discs. When the turbulence level is low, linear Lindblad torques persists in the background of stochastic forces and its accumulative effect can still dominate over relatively long timescales. However, in the presence of very stronger turbulence, classical flow patterns around the companion embedded in the disc are disrupted, leading to significant deviations from the expectations of classical Type I migration theory over arbitrarily long timescales. Our findings suggest that the stochastic nature of turbulent migration can prevent low-mass companions from monotonically settling into universal migration traps within the traditional laminar disc framework, thus reducing the frequency of three-body interactions and hierarchical mergers compared to previously expected. We propose a scaling for the transition mass ratio from classical to chaotic migration $q\propto \alpha_R$, where $\alpha_R$ is the Reynolds viscosity stress parameter, which can be further tested and refined by conducting extensive simulations over the relevant parameter space.Comment: 6 pages, 7 figures, accepted by MNRAS Letters. Welcome any comments and suggestions

Network-Based Regularization for Generalized Linear Models

Network-based regularization has achieved success in variable selection for high-dimensional biological data due to its ability to incorporate correlations among genomic features. This package provides procedures of network-based variable selection for generalized linear models (Ren et al. (2017) and Ren et al.(2019) ). Continuous, binary, and survival response are supported. Robust network-based methods are available for continuous and survival responses

Uncertainty-Aware Unlikelihood Learning Improves Generative Aspect Sentiment Quad Prediction

Recently, aspect sentiment quad prediction has received widespread attention in the field of aspect-based sentiment analysis. Existing studies extract quadruplets via pre-trained generative language models to paraphrase the original sentence into a templated target sequence. However, previous works only focus on what to generate but ignore what not to generate. We argue that considering the negative samples also leads to potential benefits. In this work, we propose a template-agnostic method to control the token-level generation, which boosts original learning and reduces mistakes simultaneously. Specifically, we introduce Monte Carlo dropout to understand the built-in uncertainty of pre-trained language models, acquiring the noises and errors. We further propose marginalized unlikelihood learning to suppress the uncertainty-aware mistake tokens. Finally, we introduce minimization entropy to balance the effects of marginalized unlikelihood learning. Extensive experiments on four public datasets demonstrate the effectiveness of our approach on various generation templates1

Exposure assessment of dietary cadmium: findings from shanghainese over 40 years, China

BACKGROUND: Environmental exposure to cadmium causes renal dysfunction and bone damage. Cadmium contamination in food is regarded as the main environmental source of non-occupational exposure. The aim of this study was to assess the contribution of dietary cadmium exposure in environmental cadmium exposure and its health risk among adults in Shanghai, China. METHODS: A cross-sectional survey about food consumption was conducted in 2008 among 207 citizens aged over 40 years in Shanghai, China. The food frequency questionnaire was combined with food, tobacco and water cadmium exposure to estimate the daily environmental cadmium exposure in both point and probabilistic estimations. Urine and blood samples of the participants were analyzed for internal exposure to total cadmium. Correlation analysis was conducted between the internal cadmium exposure and environmental cadmium exposure. RESULTS: According to the point estimation, average daily environmental cadmium exposure of the participants was 16.7 μg/day and approached 33.8% of the provisional tolerable daily intake (PTDI). Dietary and tobacco cadmium exposure approached 25.8% and 7.9% of the PTDI, respectively. Males had higher levels of dietary cadmium exposure than females (p?=?0.002). The probabilistic model showed that 93.4% of the population did not have any health risks from dietary cadmium exposure. By sensitivity analysis, tobacco consumption, tobacco cadmium level, cadmium in vegetables and cadmium in rice accounted for 27.5%, 24.9%, 20.2% and 14.6% of the total cadmium exposure, respectively. The mean values of urinary and blood cadmium among the study population were 0.5 μg/L and 1.9 μg/L, respectively. Positive correlations were observed between environmental cadmium exposure and blood cadmium (R?=?0.52, P<0.01), tobacco cadmium intake and blood cadmium excluding non-smokers (R?=?0.26, P?=?0.049<0.05), and urine cadmium and age (R?=?0.15, P?=?0.037). CONCLUSIONS: It has been suggested that there is no increased health risk among adult residents in Shanghai, China because of recent total cadmium exposure. Vegetables and rice were the main sources of dietary cadmium intake. Tobacco cadmium exposure, which accounted for approximately 25% of the total dietary cadmium exposure, was another important source of non-occupational cadmium exposure

Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation

Inverse path tracing has recently been applied to joint material and lighting estimation, given geometry and multi-view HDR observations of an indoor scene. However, it has two major limitations: path tracing is expensive to compute, and ambiguities exist between reflection and emission. Our Factorized Inverse Path Tracing (FIPT) addresses these challenges by using a factored light transport formulation and finds emitters driven by rendering errors. Our algorithm enables accurate material and lighting optimization faster than previous work, and is more effective at resolving ambiguities. The exhaustive experiments on synthetic scenes show that our method (1) outperforms state-of-the-art indoor inverse rendering and relighting methods particularly in the presence of complex illumination effects; (2) speeds up inverse path tracing optimization to less than an hour. We further demonstrate robustness to noisy inputs through material and lighting estimates that allow plausible relighting in a real scene. The source code is available at: https://github.com/lwwu2/fiptComment: Updated experiment results; modified real-world section

Identification of Prognostic Genes and Pathways in Lung Adenocarcinoma Using a Bayesian Approach

Lung cancer is the leading cause of cancer-associated mortality in the United States and the world. Adenocarcinoma, the most common subtype of lung cancer, is generally diagnosed at the late stage with poor prognosis. In the past, extensive effort has been devoted to elucidating lung cancer pathogenesis and pinpointing genes associated with survival outcomes. As the progression of lung cancer is a complex process that involves coordinated actions of functionally associated genes from cancer-related pathways, there is a growing interest in simultaneous identification of both prognostic pathways and important genes within those pathways. In this study, we analyse The Cancer Genome Atlas lung adenocarcinoma data using a Bayesian approach incorporating the pathway information as well as the interconnections among genes. The top 11 pathways have been found to play significant roles in lung adenocarcinoma prognosis, including pathways in mitogen-activated protein kinase signalling, cytokine-cytokine receptor interaction, and ubiquitin-mediated proteolysis. We have also located key gene signatures such as RELB, MAP4K1, and UBE2C. These results indicate that the Bayesian approach may facilitate discovery of important genes and pathways that are tightly associated with the survival of patients with lung adenocarcinoma