A large body of previous neuroimaging studies suggests that multiple languages are processed and organized in a single neuroanatomical system the bilingual brain, although differential activation may be seen some because different proficiency levels and/or age acquisition two languages. However, one important possibility is involve interleaved but functionally independent neural populations within given cortical region, thus, distinct patterns computations pivotal for processing Using...

The performance of the existing sparse Bayesian learning (SBL) methods for off-grid direction-of-arrival (DOA) estimation is dependent on tradeoff between accuracy and computational workload. To speed up SBL method while remain a reasonable accuracy, this letter describes computationally efficient root DOA estimation, which adopts coarse grid considers sampled locations in as adjustable parameters. We utilize an expectation-maximization algorithm to iteratively refine illustrate that each...

Written Chinese as a logographic system was developed over 3,000 y ago. Historically, children have learned to read by learning associate the visuo-graphic properties of characters with lexical meaning, typically through handwriting. In recent years, however, many use electronic communication devices based on pinyin input method, which associates phonemes and English letters characters. When key in letters, their spelling no longer depends reproducing that are indispensable reading, and,...

Abstract Aim The long‐term cyclical patterns of C hina's geopolitical shifts are great interest to scholars and the public, but date there has been no satisfactory explanation for alternating occupancy country's pastoral agrarian polities. We fill this gap by differentiating agroecological settings these polities over time quantitatively analysing relationships between climate change historical variations. Location hina. Methods Our dataset comprised 38 palaeohydroclimate reconstructions,...

The effect of mutual coupling between array elements is known to substantially degrade direction-of-arrival (DOA) estimation performance. Rank-reduction (RARE) methods can eliminate the without loss aperture. However, they might yield serious ambiguous DOA estimates in some scenarios. This letter proposes a modified RARE algorithm for estimation, which overcomes problem by recursively building up matrices. Moreover, due utilization an additional unique structure coefficients, new method give...

The activities of the brain and heart are dynamic, chaotic, possibly intrinsically coordinated. This study aims to investigate effect Mindfulness-Based Stress Reduction (MBSR) program on chaoticity electronic heart, explore their potential correlation. Electroencephalogram (EEG) electrocardiogram (ECG) were recorded at beginning an 8-week standard MBSR training course after course. EEG spectrum analysis was carried out, wavelet entropies (WE) (together with reconstructed cortical sources)...

Abstract Motivation: Recently developed network component analysis (NCA) approach is promising for gene regulatory reconstruction from microarray data. The existing NCA algorithm an iterative method which has two potential limitations: computational instability and multiple local solutions. subsequently NCA-r with Tikhonov regularization can help solve the first issue but cannot completely handle second one. Here we develop a novel Fast Network Component Analysis (FastNCA) analytical...

Chanting and praying are among the most popular religious activities, which said to be able alleviate people's negative emotions. However, neural mechanisms underlying this mental exercise its temporal course have hardly been investigated. Here, we used event-related potentials (ERPs) explore effects of chanting name a Buddha (Amitābha) on brain's response viewing pictures that were fear- stress-provoking. We recorded analyzed electroencephalography (EEG) data from 21 Buddhists with...

This study examines the state and trait effects of short-term mindfulness-based stress reduction (MBSR) training using convolutional neural networks (CNN) based deep learning methods traditional machine methods, including shallow ConvNets as well support vector (SVM) with features extracted from common spatial pattern (CSP) filter bank CSP (FBCSP).

For many signal sources such as speech with distinct, nonwhite power spectral densities, second-order statistics of the received mixture can be exploited for separation. Without knowledge noise correlation matrix, we propose a simple and yet effective extraction method source separation under unknown temporally white noise. This new unbiased extractor is derived from matrix pencil formed between output autocorrelation matrices at different delays. Based on pencil, an ESPRIT-type algorithm to...

Underdetermined direction-of-arrival (DOA) estimation for wideband signals by sparse arrays is discussed in the framework of Bayesian learning (SBL). The problem transformed to recovering multiple nonnegative vectors, which share same support but correspond distinct overcomplete basis matrices, from their noise contaminated linear combination vectors. A two-layer model established, and a hyperparameter vector, reveals true DOAs, set control this common sparsity model....

Intelligent reflecting surface (IRS) has emerged as a promising technology for improving the spectrum and energy efficiency of next-generation wireless communications. Accurately acquiring channel state information (CSI) IRS-assisted system is an essential task reaping passive beamforming gain IRS. However, it quite difficult to directly obtain CSI due inability signal processing at In this paper, we investigate downlink estimation problem massive MIMO systems. We first present new sparse...

Electroencephalography (EEG) is widely used for mental stress classification, but effective feature extraction and transfer across subjects remain challenging due to its variability. In this paper, a novel deep neural network combining convolutional (CNN) adversarial theory, named symmetric (SDCAN), proposed classification based on EEG. The inference introduced automatically capture invariant discriminative features from raw EEG, which aims improve the accuracy generalization ability...

A novel deflation approach to direction of arrival (DOA) estimation for symmetric uniform linear array is proposed in this letter cope with the scenario where both uncorrelated sources and coherent are presented. The first estimated using conventional subspace methods, then their effect eliminated by two methods: one exploits configuration array, other utilizes oblique projection. After deflation, a Toeplitz matrix constructed DOA remaining sources. number resolved our can exceed elements....

In this paper, we propose a novel correlation coefficient based on order statistics and rearrangement inequality. The proposed represents compromise between the Pearson's linear two rank-based coefficients, namely Spearman's rho Kendall's tau. Theoretical derivations show that our possesses same basic properties as three classical coefficients. Experimental studies four models six biosignals performs better than coefficients when measuring associations; whereas it is well able to detect...

This paper considers linear precoder optimization problems for multiple-input multiple-output (MIMO) systems. In addition to the conventionally used sum-power constraint, maximum eigenvalue constraint on precoding matrix is also considered so as account power limitations imposed each antenna by linearity of its own amplifier in practical implementations. A framework employing directional derivative developed obtain optimal designs different criteria including maximizing information rate and...

During hard times, religious chanting/praying is widely practiced to cope with negative or stressful emotions. While the underlying neural mechanism has not been investigated a sufficient extent. A previous event-related potential study showed that chanting could significantly diminish late-positive induced by stimuli. However, regulatory role of subcortical brain regions, especially amygdala, in this process remains unclear. This multi-modal MRI aimed further clarify effectiveness for...

This study aims to examine the impact of heavy use tablets on preschoolers’ executive function during Dimensional Change Card Sort (DCCS) task using functional near-infrared spectroscopy (fNIRS). Altogether, 38 Chinese preschoolers (Mage = 5.0 years, SD 0.69 17 girls) completed tasks before COVID-19 lockdown. Eight children never used tablets, while 16 were diagnosed as ‘heavy-user’. The results indicated that: (1) ‘non-user’ outperformed ‘heavy-user’ with a significantly higher correct rate...

For semantic segmentation of remote sensing images (RSI), trade-off between representation power and location accuracy is quite important. How to get the effectively an open question, where current approaches utilizing very deep models result in complex with large memory consumption. In contrast previous work that utilizes dilated convolutions or models, we propose a novel two-stream neural network for RSI (RSI-Net) obtain improved performance through modeling propagating spatial contextual...