Quantum chaos for nonstandard symmetry classes in the Feingold-Peres model of coupled tops

We consider two coupled quantum tops with angular momentum vectors L and M. The coupling Hamiltonian defines the Feingold-Peres model, which is a known paradigm of quantum chaos. We show that this model has a nonstandard symmetry with respect to the Altland-Zirnbauer tenfold symmetry classification of quantum systems, which extends the well-known threefold way of Wigner and Dyson (referred to as “standard” symmetry classes here). We identify the nonstandard symmetry classes BDI0 (chiral orthogonal class with no zero modes), BDI1 (chiral orthogonal class with one zero mode), and CI (antichiral orthogonal class) as well as the standard symmetry class AI (orthogonal class). We numerically analyze the specific spectral quantum signatures of chaos related to the nonstandard symmetries. In the microscopic density of states and in the distribution of the lowest positive energy eigenvalue, we show that the Feingold-Peres model follows the predictions of the Gaussian ensembles of random-matrix theory in the appropriate symmetry class if the corresponding classical dynamics is chaotic. In a crossover to mix and near-integrable classical dynamics, we show that these signatures disappear or strongly change

Socio-ecological Factors Associated with Adolescents’ Psychological Well-being: A multilevel analysis

Purpose: Supports and stressors across different ecological systems affect adolescents’ perceptions of psychological well-being. The purpose of this study is to analyze how social support, school experiences, and socio-economic factors relate to psychological well-being among adolescents. Furthermore, our study explores how family income shapes the relationship between social supports and well-being. Method: Multilevel linear regression models were applied to a sample of 19,767 middle and high school students, with students serving as Level 1 and schools as Level 2. Results: Students reporting more support from parents, friends, teachers, and neighbors and better school engagement perceive better psychological well-being. Furthermore, family income moderates the relationship between teacher support and adolescents’ psychological well-being. Implications for social work practice are discussed. Conclusion: Social support plays an important role in promoting adolescents’ psychological well-being. Teacher support is associated with better psychological well-being for all students, and this relationship is strongest for students from higher income families

Robust Inference for the Stepped Wedge Design

Based on a permutation argument, we derive a closed form expression for an estimate of the treatment effect, along with its standard error, in a stepped wedge design. We show that these estimates are robust to misspecification of both the mean and covariance structure of the underlying data-generating mechanism, thereby providing a robust approach to inference for the treatment effect in stepped wedge designs. We use simulations to evaluate the type I error and power of the proposed estimate and to compare the performance of the proposed estimate to the optimal estimate when the correct model specification is known. The limitations, possible extensions, and open problems regarding the method are discussed

Thermus thermophilus HB27株におけるToxin-Antitoxin システムの解析

筑波大学 (University of Tsukuba)201

Learning-guided network fuzzing for testing cyber-physical system defences

The threat of attack faced by cyber-physical systems (CPSs), especially when they play a critical role in automating public infrastructure, has motivated research into a wide variety of attack defence mechanisms. Assessing their effectiveness is challenging, however, as realistic sets of attacks to test them against are not always available. In this paper, we propose smart fuzzing, an automated, machine learning guided technique for systematically finding 'test suites' of CPS network attacks, without requiring any knowledge of the system's control programs or physical processes. Our approach uses predictive machine learning models and metaheuristic search algorithms to guide the fuzzing of actuators so as to drive the CPS into different unsafe physical states. We demonstrate the efficacy of smart fuzzing by implementing it for two real-world CPS testbeds---a water purification plant and a water distribution system---finding attacks that drive them into 27 different unsafe states involving water flow, pressure, and tank levels, including six that were not covered by an established attack benchmark. Finally, we use our approach to test the effectiveness of an invariant-based defence system for the water treatment plant, finding two attacks that were not detected by its physical invariant checks, highlighting a potential weakness that could be exploited in certain conditions.Comment: Accepted by ASE 201

Expediting the accuracy-improving process of SVMs for class imbalance learning

National Research Foundation (NRF) Singapore under International Research Centres in Singapore Funding Initiativ

Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving

In autonomous driving, predicting future events in advance and evaluating the foreseeable risks empowers autonomous vehicles to better plan their actions, enhancing safety and efficiency on the road. To this end, we propose Drive-WM, the first driving world model compatible with existing end-to-end planning models. Through a joint spatial-temporal modeling facilitated by view factorization, our model generates high-fidelity multiview videos in driving scenes. Building on its powerful generation ability, we showcase the potential of applying the world model for safe driving planning for the first time. Particularly, our Drive-WM enables driving into multiple futures based on distinct driving maneuvers, and determines the optimal trajectory according to the image-based rewards. Evaluation on real-world driving datasets verifies that our method could generate high-quality, consistent, and controllable multiview videos, opening up possibilities for real-world simulations and safe planning.Comment: Project page: https://drive-wm.github.io. Code: https://github.com/BraveGroup/Drive-W

Research on the Comprehensive Cognitive Practice Teaching Mode of Engineering Management Majors -Take Jiangxi Normal University as an Example

To improve the quality of talent training, this paper discusses the feasible teaching mode of comprehensive cognitive practice for Engineering Management through summarizing more than ten years of exploration and practice of Jiangxi Normal University. Focusing on the problem of “three focuses and three limits” in the practical teaching of Engineering Management majors, this paper analyzes the four key problems existing in China’s Engineering Management majors, based on the conclusion of the existing comprehensive cognitive practice teaching mode. The paper also puts forward a special comprehensive cognitive practice mode and its implementation path on the account of practical explorations. This mode achieves the “three sharing”, realizes the “linkage of multiple effects”, and obtains the satisfactory teaching effect and social benefit, which can provide a reference for the construction of related discipline in other colleges and universities