Phase Transition of Finite Size Quark Droplets with Isospin Chemical Potential in the Nanbu--Jona-Lasinio Model

Making use of the NJL model and the multiple reflection expansion pproximation, we study the phase transition of the finite size droplet with u and d quarks. We find that the dynamical masses of u, d quarks are different, and the chiral symmetry can be restored at different critical radii for u, d quark. It rovides a clue to understand the effective nucleon mass splitting in nuclear matter. Meanwhile, it shows that the maximal isospin chemical potential at zero temperature is much smaller than the mass of pion in free space.Comment: 12 pages, 3 figures. To appear in Physical Review

A New Similarity Measure between Intuitionistic Fuzzy Sets and Its Application to Pattern Recognition

As a generation of ordinary fuzzy set, the concept of intuitionistic fuzzy set (IFS), characterized both by a membership degree and by a nonmembership degree, is a more flexible way to cope with the uncertainty. Similarity measures of intuitionistic fuzzy sets are used to indicate the similarity degree between intuitionistic fuzzy sets. Although many similarity measures for intuitionistic fuzzy sets have been proposed in previous studies, some of those cannot satisfy the axioms of similarity or provide counterintuitive cases. In this paper, a new similarity measure and weighted similarity measure between IFSs are proposed. It proves that the proposed similarity measures satisfy the properties of the axiomatic definition for similarity measures. Comparison between the previous similarity measures and the proposed similarity measure indicates that the proposed similarity measure does not provide any counterintuitive cases. Moreover, it is demonstrated that the proposed similarity measure is capable of discriminating difference between patterns

Two Criteria for Model Selection in Multiclass Support Vector Machines

Practical applications call for efficient model selection criteria for multiclass support vector machine (SVM) classification. To solve this problem, this paper develops two model selection criteria by combining or redefining the radius–margin bound used in binary SVMs. The combination is justified by linking the test error rate of a multiclass SVM with that of a set of binary SVMs. The redefinition, which is relatively heuristic, is inspired by the conceptual relationship between the radius–margin bound and the class separability measure. Hence, the two criteria are developed from the perspective of model selection rather than a generalization of the radius–margin bound for multiclass SVMs. As demonstrated by extensive experimental study, the minimization of these two criteria achieves good model selection on most data sets. Compared with the k-fold cross validation which is often regarded as a benchmark, these two criteria give rise to comparable performance with much less computational overhead, particularly when a large number of model parameters are to be optimized

Vertical distributions of non-methane hydrocarbons and halocarbons in the lower troposphere over northeast China

Vertical distributions of air pollutants are crucial for understanding the key processes of atmospheric transport and for evaluating chemical transport models. In this paper, we present measurements of non-methane hydrocarbons (NMHCs) and halocarbons obtained from an intensive aircraft study over northeast (NE) China in summer 2007. Most compounds exhibited a typical negative profile of decreasing mixing ratios with increasing altitude, although the gradients differed with different species. Three regional plumes with enhanced VOC mixing ratios were discerned and characterized. An aged plume transported from the northern part of the densely populated North China Plain (NCP; i.e. Beijing-Tianjin area) showed relatively higher levels of HCFC-22, 1,2-dichloroethane (1,2-DCE) and toluene. In comparison, the plume originating from Korea had higher abundances of CFC-12, tetrachloroethene (C2Cl4) and methyl chloride (CH3Cl), while regional air masses from NE China contained more abundant light alkanes. By comparing these results with the earlier PEM-West B (1994) and TRACE-P (2001) aircraft measurements, continuing declining trends were derived for methyl chloroform (CH3CCl3), tetrachloromethane (CCl4) and C2Cl4 over the greater China-northwestern Pacific region, indicating the accomplishment of China in reducing these compounds under the Montreal protocol. However, the study also provided evidence for the continuing emissions of several halocarbons in China in 2007, such as CFCs (mainly from materials in stock) and HCFCs. © 2011 Elsevier Ltd

FEND: A Future Enhanced Distribution-Aware Contrastive Learning Framework for Long-tail Trajectory Prediction

Predicting the future trajectories of the traffic agents is a gordian technique in autonomous driving. However, trajectory prediction suffers from data imbalance in the prevalent datasets, and the tailed data is often more complicated and safety-critical. In this paper, we focus on dealing with the long-tail phenomenon in trajectory prediction. Previous methods dealing with long-tail data did not take into account the variety of motion patterns in the tailed data. In this paper, we put forward a future enhanced contrastive learning framework to recognize tail trajectory patterns and form a feature space with separate pattern clusters. Furthermore, a distribution aware hyper predictor is brought up to better utilize the shaped feature space. Our method is a model-agnostic framework and can be plugged into many well-known baselines. Experimental results show that our framework outperforms the state-of-the-art long-tail prediction method on tailed samples by 9.5% on ADE and 8.5% on FDE, while maintaining or slightly improving the averaged performance. Our method also surpasses many long-tail techniques on trajectory prediction task.Comment: Accepted for publication at the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023 (CVPR 2023

A new upscaling method for microscopic fluid flow based on digital rocks

This report presents our new findings in microscopic fluid flow based on digital rocks. Permeability of digital rocks can be estimated by pore-scale simulations using the Stokes equation, but the computational cost can be extremely high due to the complicated pore geometry and the large number of voxels. In this study, a novel method is proposed to simplify the three-dimensional pore-scale simulation to multiple decoupled two- dimensional ones, and each two-dimensional simulation provides the velocity distribution over a slice. By this decoupled simulation approach, the expensive simulation based on the Stokes equation is conducted only on two-dimensional domains, and the final three- dimensional simulation of Darcy equation using the finite difference method is very cheap. The proposed method is validated by both sandstone and carbonate rock samples and shows significant enhancement in the computational speed. This work sheds light on large-scale microscopic fluid flow based on digital rocks.Cited as: Liao, Q., Xue, L., Wang, B., Lei, G. A new upscaling method for microscopic fluid flow based on digital rocks. Advances in Geo-Energy Research, 2022, 6(4): 357-358. https://doi.org/10.46690/ager.2022.04.1