Observation of sub-Doppler absorption in the /Lambda-type three-level Doppler-broadened cesium system

Thanks to the atomic coherence in coupling laser driven atomic system, sub-Doppler absorption has been observed in Doppler-broadened cesium vapor cell via the /Lambda-type three-level scheme. The linewidth of the sub-Doppler absorption peak become narrower while the frequency detuning of coupling laser increases. The results are in agreement with the theoretical prediction by G. Vemuri et al.[PRA,Vol.53(1996) p.2842].Comment: 12 pages, 5 figures, to appear on Applied Physics

PillarNeSt: Embracing Backbone Scaling and Pretraining for Pillar-based 3D Object Detection

This paper shows the effectiveness of 2D backbone scaling and pretraining for pillar-based 3D object detectors. Pillar-based methods mainly employ randomly initialized 2D convolution neural network (ConvNet) for feature extraction and fail to enjoy the benefits from the backbone scaling and pretraining in the image domain. To show the scaling-up capacity in point clouds, we introduce the dense ConvNet pretrained on large-scale image datasets (e.g., ImageNet) as the 2D backbone of pillar-based detectors. The ConvNets are adaptively designed based on the model size according to the specific features of point clouds, such as sparsity and irregularity. Equipped with the pretrained ConvNets, our proposed pillar-based detector, termed PillarNeSt, outperforms the existing 3D object detectors by a large margin on the nuScenes and Argoversev2 datasets. Our code shall be released upon acceptance

Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

In this paper, we propose a robust 3D detector, named Cross Modal Transformer (CMT), for end-to-end 3D multi-modal detection. Without explicit view transformation, CMT takes the image and point clouds tokens as inputs and directly outputs accurate 3D bounding boxes. The spatial alignment of multi-modal tokens is performed by encoding the 3D points into multi-modal features. The core design of CMT is quite simple while its performance is impressive. It achieves 74.1\% NDS (state-of-the-art with single model) on nuScenes test set while maintaining faster inference speed. Moreover, CMT has a strong robustness even if the LiDAR is missing. Code is released at https://github.com/junjie18/CMT

Triglyceride glucose index is associated with functional coronary artery stenosis in hypertensive patients

BackgroundThe triglyceride glucose (TyG) index is an effective method for determining insulin resistance (IR). Limited research has explored the connection between the TyG index and functionally significant stenosis in hypertensive patients. Furthermore, the connections between the TyG index, fat attenuation index (FAI) and atherosclerotic plaque characteristics are also worth exploring.MethodsThe study screened 1622 hypertensive participants without coronary artery disease history who underwent coronary computed tomography angiography. The TyG index was calculated as ln (fasting glucose [mg/dL] * fasting TG [mg/dL]/2). Adverse plaque characteristics (HRPCs), high-risk plaques (HRPs), FAI, and CT-derived fractional flow reserve (FFRCT) were analyzed and measured for all patients. Functionally significant stenosis causing ischemia is defined as FFRCT ≤ 0.80. Two patient groups were created based on the FFRCT: the FFRCT < 0.80 group and the FFRCT > 0.80 group. In hypertensive patients, the association between the TyG index and FFRCT was examined applying a logistic regression model.ResultsThe TyG index was higher for people with FFRCT ≤ 0.80 contrast to those with FFRCT > 0.80. After controlling for additional confounding factors, the logistic regression model revealed a clear connection between the TyG index and FFRCT ≤ 0.80 (OR = 1.718, 95% CI 1.097–2.690, p = 0.018). The restricted cubic spline analysis displayed a nonlinear connection between the TyG index and FFRCT ≤ 0.80 (p for nonlinear = 0.001). The TyG index increased the fraction of individuals with HRPs and HRPCs, FAI raised, and FFRCT decreased (p < 0.05). The multivariate linear regression analysis illustrated a powerfulcorrelation between high TyG index levels and FAI, FFRCT, positive remodeling (PR), and low-attenuation plaque (LAPs) (standardized regression coefficients: 0.029 [p = 0.007], -0.051 [p < 0.001], 0.029 [p = 0.027], and 0.026 [p = 0.046], separately).ConclusionIn hypertensive patients, the TyG index showed an excellent association with a risk of FFRCT ≤ 0.80. Additionally, the TyG index was also linked to FAI, FFRCT, PR, and LAPs

Development of an RNA–protein crosslinker to capture protein interactions with diverse RNA structures in cells

Characterization of RNA–protein interaction is fundamental for understanding the metabolism and function of RNA. UV crosslinking has been widely used to map the targets of RNA-binding proteins, but is limited by low efficiency, requirement for zero-distance contact, and biases for single-stranded RNA structure and certain residues of RNA and protein. Here, we report the development of an RNA–protein crosslinker (AMT–NHS) composed of a psoralen derivative and an N-hydroxysuccinimide ester group, which react with RNA bases and primary amines of protein, respectively. We show that AMT–NHS can penetrate into living yeast cells and crosslink Cbf5 to H/ACA snoRNAs with high specificity. The crosslinker induced different crosslinking patterns than UV and targeted both single- and double-stranded regions of RNA. The crosslinker provides a new tool to capture diverse RNA–protein interactions in cells

Dynamic Recrystallization Behavior and Corrosion Resistance of a Dual-Phase Mg-Li Alloy

The hot deformation and dynamic recrystallization behavior of the dual-phase Mg-9Li-3Al-2Sr-2Y alloy had been investigated using a compression test. The typical dual-phase structure was observed, and average of grain size of as-homogenized alloy is about 110 µm. It mainly contains β-Li, α-Mg, Al4Sr and Al2Y phases. The dynamic recrystallization (DRX) kinetic was established based on an Avrami type equation. The onset of the DRX process occurred before the peak of the stress–strain flow curves. It shows that the DRX volume fraction increases with increasing deformation temperature or decreasing strain rate. The microstructure evolution during the hot compression at various temperatures and strain rates had been investigated. The DRX grain size became larger with the increasing testing temperature or decreasing strain rate because the higher temperature or lower strain rate can improve the migration of DRX grain boundaries. The fully recrystallized microstructure can be achieved in a small strain due to the dispersed island-shape α-Mg phases, continuous the Al4Sr phases and spheroidal Al2Y particles, which can accelerate the nucleation. The continuous Al4Sr phases along the grain boundaries are very helpful for enhancing the corrosion resistance of the duplex structured Mg-Li alloy, which can prevent the pitting corrosion and filiform corrosion

PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

In this paper, we propose PETRv2, a unified framework for 3D perception from multi-view images. Based on PETR, PETRv2 explores the effectiveness of temporal modeling, which utilizes the temporal information of previous frames to boost 3D object detection. More specifically, we extend the 3D position embedding (3D PE) in PETR for temporal modeling. The 3D PE achieves the temporal alignment on object position of different frames. A feature-guided position encoder is further introduced to improve the data adaptability of 3D PE. To support for high-quality BEV segmentation, PETRv2 provides a simply yet effective solution by adding a set of segmentation queries. Each segmentation query is responsible for segmenting one specific patch of BEV map. PETRv2 achieves state-of-the-art performance on 3D object detection and BEV segmentation. Detailed robustness analysis is also conducted on PETR framework. We hope PETRv2 can serve as a strong baseline for 3D perception. Code is available at \url{https://github.com/megvii-research/PETR}.Comment: Tech Report. Code is available at \url{https://github.com/megvii-research/PETR