135 research outputs found

    Toward reliable signals decoding for electroencephalogram: A benchmark study to EEGNeX

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    This study examines the efficacy of various neural network (NN) models in interpreting mental constructs via electroencephalogram (EEG) signals. Through the assessment of 16 prevalent NN models and their variants across four brain-computer interface (BCI) paradigms, we gauged their information representation capability. Rooted in comprehensive literature review findings, we proposed EEGNeX, a novel, purely ConvNet-based architecture. We pitted it against both existing cutting-edge strategies and the Mother of All BCI Benchmarks (MOABB) involving 11 distinct EEG motor imagination (MI) classification tasks and revealed that EEGNeX surpasses other state-of-the-art methods. Notably, it shows up to 2.1%-8.5% improvement in the classification accuracy in different scenarios with statistical significance (p < 0.05) compared to its competitors. This study not only provides deeper insights into designing efficient NN models for EEG data but also lays groundwork for future explorations into the relationship between bioelectric brain signals and NN architectures. For the benefit of broader scientific collaboration, we have made all benchmark models, including EEGNeX, publicly available at (https://github.com/chenxiachan/EEGNeX).Comment: 19 pages, 6 figure

    Mechanical Behavior and Application of a Novel Supporting and Retaining Structure for Slope

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    This paper proposed a novel supporting and retaining structure used to high-steep building slope reinforcement. It combined with an anti-sliding pile and an inclined supporting column, which is used as a fulcrum on the upper part of pile. The mechanical characteristics of the novel supporting and retaining structure are studied firstly by two mechanical methods and two numerical methods, respectively. Result shows that the axial force will be evenly distributed along the column body and it provide a quite resistant force, meanwhile. There are two shear force concentrated areas of the anti-sliding pile, one is from the top of the embedded area of the pile body to the potential slip plane, the other is at the joint. Subsequently, the results of these methods are compared synthetically and the differences between the results are also discussed. It shows that a large shear force and moment will be caused at the restrained end of the pile body by the force method and 2D numerical model 1. And in Wenkler model and the 2D numerical model 2, the rock is considered non-rigid, the anti-sliding pile will produce a certain amount of deflection under the sliding thrust, which reduces the shear force and moment at the top of the embedded area of the pile body. Finally, the novel supporting and retaining structure is applied to the site, and the monitoring data shows that the novel supporting and retaining structure is economic and effective for the reinforcement of the high-steep building slope

    LLE Score:A New Filter-based Unsupervised Feature Selection Method Based on Nonlinear Manifold Embedding and Its Application to Image Recognition

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    The task of feature selection is to find the most representative features from the original high-dimensional data. Because of the absence of the information of class labels, selecting the appropriate features in unsupervised learning scenarios is much harder than that in supervised scenarios. In this paper, we investigate the potential of locally linear embedding (LLE), which is a popular manifold learning method, in feature selection task. It is straightforward to apply the idea of LLE to the graph-preserving feature selection framework. However, we find that this straightforward application suffers from some problems. For example, it fails when the elements in the feature are all equal; it does not enjoy the property of scaling invariance and cannot capture the change of the graph efficiently. To solve these problems, we propose a new filter-based feature selection method based on LLE in this paper, which is named as LLE score. The proposed criterion measures the difference between the local structure of each feature and that of the original data. Our experiments of classification task on two face image data sets, an object image data set, and a handwriting digits data set show that LLE score outperforms state-of-the-art methods, including data variance, Laplacian score, and sparsity score

    Theoretical Study on Relaxed Surrounding Rock Pressure on Shallow Bias Neighborhood Tunnels under Seismic Load

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    To study the distribution of relaxed surrounding rock pressure on the shallow bias neighborhood tunnels under the combined action of horizontal and vertical earthquake force, finite element software was used for failure mode analysis. Moreover, with the pseudo-static method, the calculation formula for the relaxed pressure on the shallow bias neighborhood tunnels was derived and used to analyze the variation of the rupture angle of these tunnels under the action of the seismic force. The study shows that: shallow bias neighborhood tunnels basically follow a “W” failure pattern under the combined action of horizontal and vertical seismic force, and the failure scope of the surrounding rock is controlled by four rupture angles. Rupture angles β2 and β3 between the deep and shallow tunnels of the shallow bias neighborhood tunnels are not affected by the surface slope. For tunnels with the same grade of the surrounding rock, the greater the seismic intensity, the smaller the value of β2, and the greater the value of β3. While at the same seismic intensity, the higher the grade of the surrounding rock, the smaller the β2 and β3. Ruptures angles β1 and β4 are influenced by the surface slope, seismic intensity and surrounding rock grades. A steeper surface slope leads to a smaller β1 and a greater β4; β1 increase and β4 decrease with increasing seismic intensity; while, β1 and β4 both show a decreasing trend with an increasing rock grade

    Using polysaccharides for the enhancement of functionality of foods: A review

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    peer-reviewedBackground: Flavor, taste and functional ingredients are important ingredients of food, but they are easily lost or react during heating and are not stable. Carbohydrate-carbohydrate interactions (CCIs) and carbohydrate-protein interactions (CPIs) are involved in a variety of regulatory biological processes in nature, including cell differentiation, proliferation, adhesion, inflammation and immune responses. Polysaccharides have high molecular weights and many intramolecular hydrogen bonds, can be easily modified chemically and biochemically to enhance bioadhesive and biostability of tissues. Therefore, polysaccharides are the foundation for building complex and stable biosystems that are non-toxic with highydrophilicity and easily biodegradable. Scope and approach: In this review, we summarize the principles and applications of polysaccharide delivery systems in a variety of foods. Key findings and conclusions: This review focuses on the self-assembly of carbohydrates with complex structures and discusses the latest advances in self-assembly systems. The host-guest complexes formed by polyvalent sugar conjugates have the potential to provide, control or target delivery or release systems. They can also extend the shelf life of food and prevent oxidation and isomerization during food storage. Moreover, very few studies have outlined a comprehensive overview of the use of various types of food polysaccharide matrixes for the assembly and protection of food ingredients, which is a very important area for further study

    Basalt-polypropylene fiber reinforced concrete for durable and sustainable pipe production. Part 1: experimental program

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    This is the peer reviewed version of the following article: [ Deng, Z, Liu, X, Chen, P, et al. Basalt-polypropylene fiber reinforced concrete for durable and sustainable pipe production. Part 1: Experimental program. Structural Concrete. 2022; 23: 311– 327. https://doi.org/10.1002/suco.202000759], which has been published in final form at https://onlinelibrary.wiley.com/doi/abs/10.1002/suco.202000759. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.An experimental program consisting in producing and testing reinforced concrete pipes (RCPs) under the three-edge bearing tests considering different types of reinforcement was carried out. Four types of RCPs were produced, these reinforced with: (1) polypropylene macrofibers; (2) basalt microfibers; (3) combination of both (hybrid reinforcement); and (4) plain concrete. The analysis of the crack patterns and both service and ultimate mechanical responses allowed concluding that the use of fibers do not lead to an effective increase of the first cracking load; however, both types of fibers allowed a better crack width control respect to the standard RCP. In this regard, basalt microfiber reinforced concrete led to a better response caused by concentrated loads (jacketing) whilst polypropylene macrofibers increased the concrete pipe performance in terms of bearing capacity and flexural crack control. The hybrid fiber reinforced concrete was found to be the most suitable alternative for increasing the load bearing capacity and the crack width control for service loads. These incipient experimental results permit to conclude that this type of hybrid basalt-polypropylene fiber reinforced concretes are an interesting alternative to traditional steel-cage RCPs.This work is supported by the National Key Research and Development Program of China (2018YFC1504802), Natural Science Foundation Project of Chongqing, Chongqing Science and Technology Commission (cstc2018jscxmszdX0071), Postgraduate Research Innovation Project of Chongqing (CYS19005, CYS18026). In addition, Prof. Albert de la Fuente also wants to express his gratitude to the Spanish Ministry of Science and Innovation for the financial support received under the scope of the project CREEF (PID2019-108978RB-C32).Peer ReviewedPostprint (author's final draft
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