Uncovering interactions in the frequency domain

Oscillatory activity plays a critical role in regulating biological processes at levels ranging from subcellular, cellular, and network to the whole organism, and often involves a large number of interacting elements. We shed light on this issue by introducing a novel approach called partial Granger causality to reliably reveal interaction patterns in multivariate data with exogenous inputs and latent variables in the frequency domain. The method is extensively tested with toy models, and successfully applied to experimental datasets, including (1) gene microarray data of HeLa cell cycle; (2) in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of a sheep; and (3) in vivo LFPs recorded from distributed sites in the right hemisphere of a macaque monkey

A Multiclass Cumulative Prospect Theory-Based Stochastic User Equilibrium Model with Path Constraints in Degradable Transport Networks

The limited driving range and the unavailability or insufficiency of battery charging/swapping stations cause the so-called range anxiety issue for traffic assignment involving battery electric vehicle (BEV) users. In addition, expected utility theory-based stochastic user equilibrium (EUT-SUE) model generates the perfectly rational issue when the travellers make route choice decisions. To tackle these two problems, this article improves the cumulative prospect theory-based stochastic user equilibrium (CPT-SUE) model in a degradable transport network through incorporating the constraints of multiple user classes and distance limit. In this degradable network, the travellers experience stochastic travel times due to network link capacity degradations. For this improved CPT-SUE model, the equivalent variational inequality (VI) model and associated method of successive averages (MSA) based solution are provided. The improved CPT-SUE model is tested and compared with the EUT-SUE model with distance limit, with results showing that the improved CPT-SUE model can handle jointly the range anxiety issue and the perfectly rational issue

Global Adaptive Generative Adjustment

Many traditional signal recovery approaches can behave well basing on the penalized likelihood. However, they have to meet with the difficulty in the selection of hyperparameters or tuning parameters in the penalties. In this article, we propose a global adaptive generative adjustment (GAGA) algorithm for signal recovery, in which multiple hyperpameters are automatically learned and alternatively updated with the signal. We further prove that the output of our algorithm directly guarantees the consistency of model selection and the asymptotic normality of signal estimate. Moreover, we also propose a variant GAGA algorithm for improving the computational efficiency in the high-dimensional data analysis. Finally, in the simulated experiment, we consider the consistency of the outputs of our algorithms, and compare our algorithms to other penalized likelihood methods: the Adaptive LASSO, the SCAD and the MCP. The simulation results support the efficiency of our algorithms for signal recovery, and demonstrate that our algorithms outperform the other algorithms

Modal and strength analysis of coal mine mobile refuge chamber

Structural strength, stiffness, etc. are essential safety performances of mine refuge chamber. In this article, the safety performance of the chamber which is under the impact load was evaluated by the method of numerical analysis. First of all, according to some relative standards, a chamber model was established by applying numerical modeling software. In this way, a method of finite element analysis (FEA) was instituted and we used AUTODUN to simulate the process of transmission of blast waves in the underworkings. On the basis of Fourier transform theory, the spectrum analysis of the blast waves acting on the chamber has been done. In order to obtain the natural frequency, a model analysis of the chamber was made by applying OPTISTRUCT. Then the main frequency and the natural frequency were compared. The result shows that the resonance will not happen so that the safety performance of the chamber meets the demand of engineering safety. The structural strength of the chamber was analyzed by using LS-DYNA, and the result comes out that the pressure throughout the chamber will not cause damage to the chamber. After that, according to the simulation results, we proposed some pieces of advice which will be meaningful for the design and the improvement of the chamber

Research and progress of front-end readout prototype system for GRANDProto300

GRANDProto300 is the planned 300-antenna pathfinder array of the Giant Radio Array for Neutrino Detection (GRAND), of which the first 100 detection units have been already produced. Its main goal is to demonstrate the viability of the detection of the radio emission from air showers initiated by inclined ultra-high-energy cosmic rays with energies of $10^{16.5}$ to $10^{18.5}$ eV, covering the purported transition region from their Galactic to extragalactic origin. The front-end readout system of each detection unit of GRANDProto300 processes signals from the radio antenna and the particle detector, generates the first-level trigger, and communicates with a central processing station. Based on earlier designs, we have built the first prototype of this system using two development boards and one self-designed front-end board. We present our new design that is improved and more economical than the earlier one, as well as test results and prospects for future work.Comment: Presented at the 38th International Cosmic Ray Conference (ICRC 2023