Recurrence plots provide a graphical representation of the recurrent patterns in a timeseries, the quantification of which is a relatively new field. Here we derive analytical expressions which relate the values of key statistics, notably determinism and entropy of line length distribution, to the correlation sum as a function of embedding dimension. These expressions are obtained by deriving t...

BACKGROUND Gemcitabine is a pyrimidine nucleoside analog that is a commonly used chemotherapeutic agent for unresectable or recurrent biliary tract cancer (BTC). Several molecules involved in gemcitabine metabolism, including human equilibrative nucleoside transporter (hENT1), deoxycytidine kinase (dCK), and ribonucleotide reductase subunit M1 (RRM1), have been investigated as predictive biomar...

Each smile is unique: one person surely smiles in different ways (e.g. closing/opening the eyes or mouth). Given one input image of a neutral face, can we generate multiple smile videos with distinctive characteristics? To tackle this one-to-many video generation problem, we propose a novel deep learning architecture named Conditional MultiMode Network (CMM-Net). To better encode the dynamics o...

One of the essential problems in synthesizing expressive talking avatar is how to model the interactions between emotional facial expressions and lip movements. Traditional methods either simplify such interactions through separately modeling lip movements and facial expressions, or require substantial high quality emotional audio-visual bimodal training data which are usually difficult to coll...

A new hybrid PSO-EA-DEPSO algorithm based on particle swarm optimization (PSO), evolutionary algorithm (EA), and differential evolution (DE) is presented for training a recurrent neural network (RNN) for multiple-input multiple-output (MIMO) channel prediction. This algorithm is shown to outperform RNN predictors trained off-line by PSO, EA, and DEPSO as well as a linear predictor trained by th...

We submitted two systems to the SemEval2016 Task 12: Clinical TempEval challenge, participating in Phase 1, where we identified text spans of time and event expressions in clinical notes and Phase 2, where we predicted a relation between an event and its parent document creation time. For temporal entity extraction, we find that a joint inference-based approach using structured prediction outpe...

Abstract This paper investigates the event-based state estimation for discrete-time recurrent delayed semi-Markovian neural networks. An event-triggering protocol is introduced to find measurement output with a specific triggering condition so as lower burden of data communication. A novel summation inequality established existence asymptotic stability error system. The problem addressed here c...

Researchers have documented that children of depressed mothers are at elevated risk for developing a depressive disorder themselves. There is currently little understanding, however, of what factors place these children at elevated risk. In the present study, the authors investigated whether never-disordered daughters whose mothers have experienced recurrent episodes of depression during their ...