Near integrability of kink lattice with higher order interactions

In the paper, we make use of Manton's analytical method to investigate the force between kink and the anti-kink with large distance in $1+1$ dimensional field theory. The related potential has infinite order corrections of exponential pattern, and coefficients for each order are determined. These coefficients can also be obtained by solving the equation of the fluctuation around the vacuum. At the lowest order, the kink lattice represents the Toda lattice. With higher order correction terms, the kink lattice can represent one kind of the generic Toda lattice. With only two sites, the kink lattice is classically integrable. If the number of sites of the lattice is larger than two, the kink lattice is not integrable but a near integrable system. We take use of the Flaschka's variables to study the Lax pair of the kink lattice. These Flaschka's variables have interesting algebraic relations and the non-integrability can be manifested. We also discussed the higher Hamiltonians for the deformed open Toda lattice, which has a similar result as the ordinary deformed Toda

Toda chain from the kink-antikink lattice

In this paper, we have studied the kink and antikink solutions in several neutral scalar models in 1+1 dimension. We follow the standard approach to write down the leading order and the second order force between long distance separated kink and antikink. The leading order force is proportional to exponential decay with respect to the distance between the two nearest kinks or antikinks. The second order force have a similar behavior with the larger decay factor, namely $3\over 2$. We make use of these properties to construct the kink lattice. The dynamics of the kink lattice with leading order force can be identified as ordinary nonperiodic Toda lattice. Also the periodic Toda lattice can be obtained when the number of kink lattice is even. The system of kink lattice with force up to the next order corresponds to a new specific deformation of Toda lattice system. There is no well study on this deformation in the integrable literatures.We found that the deformed Toda system are near integrable system, since the integrability are hindered by high order correction terms. Our work provides a effective theory for kink interactions and a new near or quasi integrable model.Comment: 20 pages no figure

Decentralized Risk-Aware Tracking of Multiple Targets

We consider the setting where a team of robots is tasked with tracking multiple targets with the following property: approaching the targets enables more accurate target position estimation, but also increases the risk of sensor failures. Therefore, it is essential to address the trade-off between tracking quality maximization and risk minimization. In our previous work, a centralized controller is developed to plan motions for all the robots -- however, this is not a scalable approach. Here, we present a decentralized and risk-aware multi-target tracking framework, in which each robot plans its motion trading off tracking accuracy maximization and aversion to risk, while only relying on its own information and information exchanged with its neighbors. We use the control barrier function to guarantee network connectivity throughout the tracking process. Extensive numerical experiments demonstrate that our system can achieve similar tracking accuracy and risk-awareness to its centralized counterpart.Comment: DARS2022 submission preprin

Natural van der Waals heterostructural single crystals with both magnetic and topological properties

Heterostructures having both magnetism and topology are promising materials for the realization of exotic topological quantum states while challenging in synthesis and engineering. Here, we report natural magnetic van der Waals heterostructures of (MnBi2Te4)m(Bi2Te3)n that exhibit controllable magnetic properties while maintaining their topological surface states. The interlayer antiferromagnetic exchange coupling is gradually weakened as the separation of magnetic layers increases, and an anomalous Hall effect that is well coupled with magnetization and shows ferromagnetic hysteresis was observed below 5 K. The obtained homogeneous heterostructure with atomically sharp interface and intrinsic magnetic properties will be an ideal platform for studying the quantum anomalous Hall effect, axion insulator states, and the topological magnetoelectric effect.Comment: 40 pages, 15 figure

Pharmacokinetic, acute toxicity, and pharmacodynamic studies of semen strychni total alkaloid microcapsules

Purpose: To investigate the safety and effectiveness of semen strychni total alkaloid microcapsules (SSTAM), compared with semen strychni total alkaloids (SSTA). Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed to assess pharmacokinetics of brucine and strychnine in rats. Acute toxicity was investigated in pre-test and formal experiments in mice. The pharmacodynamics of SSTAM and SSTA were evaluated by their analgesic and anti-inflammatory activities. Results: With respect to brucine, the half-life of SSTA group (1.6 mg/kg), low-dose SSTAM group (6 mg/kg) and high-dose SSTAM group (10 mg/kg) was 5.723, 9.321 and 9.025 h, respectively. With respect to strychnine, the half-life of SSTA group, low-dose SSTAM group and high-dose SSTAM group was 4.065, 8.819 and 8.654 h, respectively. The LD50 values of SSTAM group and SSTA group were 236.59 and 30.27 mg/kg, respectively. The pain inhibition rates of SSTAM groups (25 and 50 mg/kg) were higher than that of SSTA group (p < 0.05) while the pain threshold values of the SSTAM groups (25 and 50 mg/kg) were higher than that of blank control (p < 0.01) and SSTA groups (p < 0.01) at 60 min and 120 min. The inhibition rates of the SSTAM groups (25 and 50 mg/kg) were higher than that of SSTA group based on ear swelling and cotton ball granulation tests. Compared with blank control and SSTA groups, the absorbance values of SSTAM groups (25 and 50 mg/kg) were lower (p < 0.01). Conclusion: SSTAM increases the dosage of administration but reducea the toxicity of the alkaloids in rats, and is thus a potentially safe and effective drug delivery system

DuetFace: Collaborative Privacy-Preserving Face Recognition via Channel Splitting in the Frequency Domain

With the wide application of face recognition systems, there is rising concern that original face images could be exposed to malicious intents and consequently cause personal privacy breaches. This paper presents DuetFace, a novel privacy-preserving face recognition method that employs collaborative inference in the frequency domain. Starting from a counterintuitive discovery that face recognition can achieve surprisingly good performance with only visually indistinguishable high-frequency channels, this method designs a credible split of frequency channels by their cruciality for visualization and operates the server-side model on non-crucial channels. However, the model degrades in its attention to facial features due to the missing visual information. To compensate, the method introduces a plug-in interactive block to allow attention transfer from the client-side by producing a feature mask. The mask is further refined by deriving and overlaying a facial region of interest (ROI). Extensive experiments on multiple datasets validate the effectiveness of the proposed method in protecting face images from undesired visual inspection, reconstruction, and identification while maintaining high task availability and performance. Results show that the proposed method achieves a comparable recognition accuracy and computation cost to the unprotected ArcFace and outperforms the state-of-the-art privacy-preserving methods. The source code is available at https://github.com/Tencent/TFace/tree/master/recognition/tasks/duetface.Comment: Accepted to ACM Multimedia 202

Friend Ranking in Online Games via Pre-training Edge Transformers

Friend recall is an important way to improve Daily Active Users (DAU) in online games. The problem is to generate a proper lost friend ranking list essentially. Traditional friend recall methods focus on rules like friend intimacy or training a classifier for predicting lost players' return probability, but ignore feature information of (active) players and historical friend recall events. In this work, we treat friend recall as a link prediction problem and explore several link prediction methods which can use features of both active and lost players, as well as historical events. Furthermore, we propose a novel Edge Transformer model and pre-train the model via masked auto-encoders. Our method achieves state-of-the-art results in the offline experiments and online A/B Tests of three Tencent games.Comment: Accepted by the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023