Discover articles, books and research

Our analyses of whole-genome variants show that the American parasites belong to a well-supported monophyletic clade. We hypothesize that the required adaptation to American vectors created a severe bottleneck, reducing the effective introduction to a few lineages.

This study proposes a machine learning inversion method based on multi-domain vibration features. Dynamic responses are generated with a 2.5-dimensional finite-element–boundary-element model, from which peak strain, dominant frequency, low-frequency energy ratio, strain attenuation gradient, and time–frequency entropy are extracted; random forest (RF) and s…

Starting from the background of the outbreak of New Coronavirus, in order to realize the function of automatically identifying the required items by machine, the support vector machine algorithm in the neural network and the traditional computer vision algorithm opencv were used.

Different from the macro basis function analysis model, our proposed method uses the formulations derived by the local Rao-Wilton-Glisson basis functions. PSA is not only used to accelerate the matrix-vector product (MVP) inside the single unit but also adopted to decrease the calculation burden of the coupling between the different cells.

In FE, a user can learn specific function of encrypted messages by restricted functional key and reveal nothing else about the messages. Inner product encryption (IPE) is a special type of functional encryption where the decryption algorithm, given a ciphertext related to a vector x and a secret key related to a vector y, computes the inner product x·y.

Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. Signature genes were identified through Least Absolute Shrinkage and Selection Operator (LASSO) regression, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Random Forest (RF) algorithms.

The Adam optimizer is used in the DNN model to ensure the stability and accuracy of the model in the gradient descent process, and the prediction effect is compared with the back propagation neural network (BPNN), K-nearest neighbor (KNN), and support vector regression model (SVR).

The article considers the problem of finding the optimal on average control of the trajectories of continuous stochastic systems with incomplete feedback. This class of problems includes control problems in which the initial states are described by a given distribution law; random effects on the control object are taken into account; and it is also assumed…

By employing electroencephalography (EEG) recordings from 21 participants undergoing the Trier Social Stress Test (TSST), we propose a machine learning (ML)-driven methodology to decode the Big Five personality traits—Extraversion (Ex), Agreeableness (A), Neuroticism (N), Conscientiousness (C), and Openness (O)—using classification algorithms such as suppor…

The energy transfer vector is driven by the spatial gradient of the local magnetic energy density, transforming ambient wave-fronts into directional kinetic energy. Finally, the framework enforces the strict electrostatic boundary constraint of net-current neutrality (Net Current = 0) within the expanding space-plasma cytosol to prevent localized dielectric…

Methods Whole blood from the tail tip and one piece of stool were used as pre-samples of injection. Next, a plasmid vector containing the human erythropoietin (hEPO) gene was injected into mice through intravenous (IV), intraperitoneal (IP), or local muscular (IM) injection.

The energy transfer vector is driven by the spatial gradient of the local magnetic energy density, transforming ambient wave-fronts into directional kinetic energy. Finally, the framework enforces the strict electrostatic boundary constraint of net-current neutrality (Net Current = 0) within the expanding space-plasma cytosol to prevent localized dielectric…