In situ structures of the segmented genome and RNA polymerase complex inside a dsRNA virus.

Viruses in the Reoviridae, like the triple-shelled human rotavirus and the single-shelled insect cytoplasmic polyhedrosis virus (CPV), all package a genome of segmented double-stranded RNAs (dsRNAs) inside the viral capsid and carry out endogenous messenger RNA synthesis through a transcriptional enzyme complex (TEC). By direct electron-counting cryoelectron microscopy and asymmetric reconstruction, we have determined the organization of the dsRNA genome inside quiescent CPV (q-CPV) and the in situ atomic structures of TEC within CPV in both quiescent and transcribing (t-CPV) states. We show that the ten segmented dsRNAs in CPV are organized with ten TECs in a specific, non-symmetric manner, with each dsRNA segment attached directly to a TEC. The TEC consists of two extensively interacting subunits: an RNA-dependent RNA polymerase (RdRP) and an NTPase VP4. We find that the bracelet domain of RdRP undergoes marked conformational change when q-CPV is converted to t-CPV, leading to formation of the RNA template entry channel and access to the polymerase active site. An amino-terminal helix from each of two subunits of the capsid shell protein (CSP) interacts with VP4 and RdRP. These findings establish the link between sensing of environmental cues by the external proteins and activation of endogenous RNA transcription by the TEC inside the virus

Precise QCD predictions on top quark pair production mediated by massive color octet vector boson at hadron colliders

We present a theoretical framework for systematically calculating next-to-leading order (NLO) QCD effects to various experimental observables in models with massive COVB in a model independent way at hadron colliders. Specifically, we show the numerical results for the NLO QCD corrections to total cross sections, invariant mass distribution and AFB of top quark pairs production mediated by a massive COVB in both the fixed scale (top quark mass) scheme and the dynamical scale (top pair invariant mass) scheme. Our results show that the NLO QCD calculations in the dynamical scale scheme is more reasonable than the fixed scheme and the naive estimate of the NLO effects by simple rescaling of the LO results with the SM NLO K-factor is not appropriate.Comment: 6 pages, 5 figures, 2 tables; version published in EPJ

Top quark pair production at small transverse momentum in hadronic collisions

We investigate the transverse momentum resummation for top quark pair production at hadron colliders using the soft-collinear effective theory and the heavy-quark effective theory. We derive the factorization formula for $t\bar{t}$ production at small pair transverse momentum, and show in detail the procedure for calculating the key ingredient of the factorization formula: the next-to-leading order soft functions. We compare our numerical results with experimental data and find that they are consistent within theoretical and experimental uncertainties. To verify the correctness of our resummation formula, we expand it to the next-to-leading order and the next-to-next-to-leading order, and compare those expressions with the exact fixed-order results numerically. Finally, using the results of transverse momentum resummation, we discuss the transverse-momentum-dependent forward-backward asymmetry at the Tevatron.Comment: 39 pages, 7 figures, 1 table; final version in PR

Retrieving Ground-Level PM2.5 Concentrations in China (2013–2021) with a Numerical Model-Informed Testbed to Mitigate Sample Imbalance-Induced Biases

Ground-level PM2.5 data derived from satellites with machine learning are crucial for health and climate assessments, however, uncertainties persist due to the absence of spatially covered observations. To address this, we propose a novel testbed using untraditional numerical simulations to evaluate PM2.5 estimation across the entire spatial domain. The testbed emulates the general machine-learning approach, by training the model with grids corresponding to ground monitor sites and subsequently testing its predictive accuracy for other locations. Our approach enables comprehensive evaluation of various machine-learning methods’ performance in estimating PM2.5 across the spatial domain for the first time. Unexpected results are shown in the application in China, with larger PM2.5 biases found in densely populated regions with abundant ground observations across all benchmark models, challenging conventional expectations and are not explored in the recent literature. The imbalance in training samples, mostly from urban areas with high emissions, is the main reason, leading to significant overestimation due to the lack of monitors in downwind areas where PM2.5 is transported from urban areas with varying vertical profiles. Our proposed testbed also provides an efficient strategy for optimizing model structure or training samples to enhance satellite-retrieval model performance. Integration of spatiotemporal features, especially with CNN-based deep-learning approaches like the ResNet model, successfully mitigates PM2.5 overestimation (by 5–30 µg m-3) and corresponding exposure (by 3 million people • µg m-3) in the downwind area over the past nine years (2013–2021) compared to the traditional approach. Furthermore, the incorporation of 600 strategically positioned ground-measurement sites identified through the testbed is essential to achieve a more balanced distribution of training samples, thereby ensuring precise PM2.5 estimation and facilitating the assessment of associated impacts in China. In addition to presenting the retrieved surface PM2.5 concentrations in China from 2013 to 2021, this study provides a testbed dataset derived from physical modeling simulations which can serve to evaluate the performance of data-driven methodologies, such as machine learning, in estimating spatial PM2.5 concentrations for the community

Model independent analysis of top quark forward-backward asymmetry at the Tevatron up to \mathcal{O}(\as^2/\Lambda^2)

We present the complete calculations of the forward-backward asymmetry ($A_{\rm FB}$) and the total cross section of top quark pair production induced by dimension-six four quark operators at the Tevatron up to \mathcal{O}(\as^2/\Lambda^2). Our results show that next-to-leading order (NLO) QCD corrections can change $A_{\rm FB}$ and the total cross section by about 10%. Moreover, NLO QCD corrections reduce the dependence of $A_{\rm FB}$ and total cross section on the renormalization and factorization scales significantly. We also evaluate the total cross section and the charge asymmetry ($A_{\rm C}$) induced by these operators at the Large Hadron Collider (LHC) up to \mathcal{O}(\as^2/\Lambda^2), for the parameter space allowed by the Tevatron data. We find that the value of $A_{\rm C}$ induced by these operators is much larger than SM prediction, and LHC has potential to discover these NP effects when the measurement precision increases.Comment: 25 pages, 10 figures; final version in PR

N′-(3-Bromo-4-methoxy­benzyl­idene)nicotinohydrazide monohydrate

In the title compound, C14H12BrN3O2·H2O, the benzene ring is oriented at a dihedral angle of 39.66 (11)° with respect to the pyridine ring. The solvent water mol­ecule links with the organic compound via O—H⋯O, O—H⋯N and N—H⋯O hydrogen bonding