Estimation of Extreme Quantiles for Functions of Dependent Random Variables

We propose a new method for estimating the extreme quantiles for a function of several dependent random variables. In contrast to the conventional approach based on extreme value theory, we do not impose the condition that the tail of the underlying distribution admits an approximate parametric form, and, furthermore, our estimation makes use of the full observed data. The proposed method is semiparametric as no parametric forms are assumed on all the marginal distributions. But we select appropriate bivariate copulas to model the joint dependence structure by taking the advantage of the recent development in constructing large dimensional vine copulas. Consequently a sample quantile resulted from a large bootstrap sample drawn from the fitted joint distribution is taken as the estimator for the extreme quantile. This estimator is proved to be consistent. The reliable and robust performance of the proposed method is further illustrated by simulation.Comment: 18 pages, 2 figure

Enhancing Motor Imagery Decoding in Brain Computer Interfaces using Riemann Tangent Space Mapping and Cross Frequency Coupling

Objective: Motor Imagery (MI) serves as a crucial experimental paradigm within the realm of Brain Computer Interfaces (BCIs), aiming to decoding motor intentions from electroencephalogram (EEG) signals. Method: Drawing inspiration from Riemannian geometry and Cross-Frequency Coupling (CFC), this paper introduces a novel approach termed Riemann Tangent Space Mapping using Dichotomous Filter Bank with Convolutional Neural Network (DFBRTS) to enhance the representation quality and decoding capability pertaining to MI features. DFBRTS first initiates the process by meticulously filtering EEG signals through a Dichotomous Filter Bank, structured in the fashion of a complete binary tree. Subsequently, it employs Riemann Tangent Space Mapping to extract salient EEG signal features within each sub-band. Finally, a lightweight convolutional neural network is employed for further feature extraction and classification, operating under the joint supervision of cross-entropy and center loss. To validate the efficacy, extensive experiments were conducted using DFBRTS on two well-established benchmark datasets: the BCI competition IV 2a (BCIC-IV-2a) dataset and the OpenBMI dataset. The performance of DFBRTS was benchmarked against several state-of-the-art MI decoding methods, alongside other Riemannian geometry-based MI decoding approaches. Results: DFBRTS significantly outperforms other MI decoding algorithms on both datasets, achieving a remarkable classification accuracy of 78.16% for four-class and 71.58% for two-class hold-out classification, as compared to the existing benchmarks.Comment: 22 pages, 7 figure

Degraded planetary tracking control of an omni-directional vectored-thruster aerostat

The problem of horizontal-plane tracking control of an omni-directional, four vectored-thruster aerostat when subjected to actuator failure is considered. The actuator failures result in the aerostat becoming underactuated, so it can only effect surge force and pure yaw moment about the body centre. To achieve accurate position control in the horizontal plane, direct position control is used instead of heading control. This mode of controller is called degraded tracking control in contrast to full authority control of the overactuated four vectored-thruster aerostat. This degraded tracking controller uses commanded yaw rate to track lateral position, and yaw moment to eliminate lateral position error, therefore yaw angle is not directly controlled. To guarantee the stability of the yaw motion, a Virtual Reference Point (VRP) tracking strategy is proposed, where the VRP is used instead of the body center (BC) in position tracking. The VRP generates a negative compensated force in the surge direction which makes the side-force and yaw moment have the same sign and so ensure that the aerostat is in a stable tracking configuration. Meanwhile the VRP also decreases the transmission ratio of commanded yaw rate to commanded lateral velocity, making the aerostat's yaw motion vary slowly during transitional phase, so steady position tracking is obtained

Effect of rs1344706 in the ZNF804A gene on the brain network.

ZNF804A rs1344706 (A/C) was the first SNP that reached genome-wide significance for schizophrenia. Recent studies have linked rs1344706 to functional connectivity among specific brain regions. However, no study thus far has examined the role of this SNP in the entire functional connectome. In this study, we used degree centrality to test the role of rs1344706 in the whole-brain voxel-wise functional connectome during the resting state. 52 schizophrenia patients and 128 healthy controls were included in the final analysis. In our whole-brain analysis, we found a significant interaction effect of genotype × diagnosis at the precuneus (PCU) (cluster size = 52 voxels, peak voxel MNI coordinates: x = 9, y = - 69, z = 63, F = 32.57, FWE corrected P < 0.001). When we subdivided the degree centrality network according to anatomical distance, the whole-brain analysis also found a significant interaction effect of genotype × diagnosis at the PCU with the same peak in the short-range degree centrality network (cluster size = 72 voxels, F = 37.29, FWE corrected P < 0.001). No significant result was found in the long-range degree centrality network. Our results elucidated the contribution of rs1344706 to functional connectivity within the brain network, and may have important implications for our understanding of this risk gene's role in functional dysconnectivity in schizophrenia

A Single Residue Mutation in the Gαq Subunit of the G Protein Complex Causes Blindness in Drosophila.

Heterotrimeric G proteins play central roles in many signaling pathways, including the phototransduction cascade in animals. However, the degree of involvement of the G protein subunit Gαq is not clear since animals with previously reported strong loss-of-function mutations remain responsive to light stimuli. We recovered a new allele of Gαq in Drosophila that abolishes light response in a conventional electroretinogram assay, and reduces sensitivity in whole-cell recordings of dissociated cells by at least five orders of magnitude. In addition, mutant eyes demonstrate a rapid rate of degeneration in the presence of light. Our new allele is likely the strongest hypomorph described to date. Interestingly, the mutant protein is produced in the eyes but carries a single amino acid change of a conserved hydrophobic residue that has been assigned to the interface of interaction between Gαq and its downstream effector, PLC. Our study has thus uncovered possibly the first point mutation that specifically affects this interaction in vivo

Giant room temperature anomalous Hall effect and magnetically tuned topology in the ferromagnetic Weyl semimetal Co2MnAl

Weyl semimetals (WSM) have been extensively studied due to their exotic properties such as topological surface states and anomalous transport phenomena. Their band structure topology is usually predetermined by material parameters and can hardly be manipulated once the material is formed. Their unique transport properties appear usually at very low temperature, which sets challenges for practical device applications. In this work, we demonstrate a way to modify the band topology via a weak magnetic field in a ferromagnetic topological semimetal, Co2MnAl, at room temperature. We observe a tunable, giant anomalous Hall effect, which is induced by the transition between Weyl points and nodal rings as rotating the magnetization axis. The anomalous Hall conductivity is as large as that of a 3D quantum anomalous Hall effect (QAHE), with the Hall angle reaching a record value (21%) at the room temperature among magnetic conductors. Furthermore, we propose a material recipe to generate the giant anomalous Hall effect by gaping nodal rings without requiring the existence of Weyl points. Our work reveals an ideal intrinsically magnetic platform to explore the interplay between magnetic dynamics and topological physics for the development of a new generation of spintronic devices.Comment: 4 figures, 8 pages for the main text. The supplementary materials are included to

The Technology of Mould Steel for Online Pre-hardening

AbstractThis article describes a production method of mould steel pre-hardening, and focus on the advantage of this method, The technical core of method is the variable frequency and variable amplitude pulse uniform high-precision temperature control, which achieved by using strong-medium-weak water cooling, gas-water cooling and gas mist cooling composite cooling control technology. Optimizing the cooling rate path is a good method of optimizing quenched organization and structure