State-dependent switched Hopfield neural network (SSHNN) is expected to display even richer dynamical behaviors in contrast with conventional Hopfield neural networks (HNNs). Considering these two reasons, this
Perhaps surprisingly, the between‐group activation results from fNIRS were statistically stronger than the results using fMRI. This pilot study is the first fNIRS investigation of executive function for individuals with type 1 diabetes. The results suggest that fNIRS is a promising functional ...
Single-cell RNA sequencing (scRNA-seq) technology has only recently matured. Emerging scRNA-seq studies have transformed our understanding of cell biology and human disease. An important step in scRNA-seq analysis is to identify cell populations or types by clustering1. Knowledge of cell types can...
We propose that an accurate de novo prediction of chromatin folding requires a multimodal neural network incorporating both DNA sequence and cell-type-specific genomic features. For practicality, it should also use a minimal set of inputs without compromising performance. Based on these principles, we...
An overlapped type of local neural network is proposed to improve accuracy of the flux decline prediction in crossflow membrane filtration (CMF) of colloidal suspensions. This network combines the advantages of the multilayer feedforward back-propagation neural network and the radial basis function netwo...
type proportions through neural network systems. These models eliminate the need for an additional step to learn cell type gene signatures from scRNA-seq data [20,21,29]. However, a common limitation of these models is that they deconvolve the spots in a given ST dataset independently, without...
function for all x ∈ R n . If x = 0 is asymptotically stable and V (x) is radially unbounded, then x = 0 is globally asymptotically stable. We carry the assumption that g(0) ≡ 0 so that 0 is the zero solution of (1). 2 Convergence Criteria In 1954, Krasovskii [3] establishe...
of neurons that are not yet completely integrated into the local circuits helps to ensure that maturation and homeostatic function of neuronal networks in the brain proceed correctly. External signals from brain microenvironment together with intrinsic signaling pathways determine whether a particular neuron...
In each Multi-head Self-attention layer, the attention function is performed H times in parallel. The CLS of O, considered as latent space of each cell, is used as input of the whole conjunction neural network cell type classifier. Meanwhile, the attention of class (CLS) token to gene ...
The standardization is a recommended procedure for performing efficient backpropagation in neural networks40. In Cellcano’s first-round prediction, we first train an MLP model with a ReLU activation function to capture the non-linear mapping between the Xref and Cref. For a multi-class ...