Creating Singing Vocal Expressions by means of Interactive Evolutionary Computation

Today, researches for singing by computer have attracted attention. VOCALOID is an application to realize that aim. By inputing lyrics and melody, users can make songs sung by the computer. In order to make the singing voice more "human", users must control frequency curve very carefully. Comparing with inputing lyrics or melody, this controlling presents heavy overhead for users. In this research, we propose a system for easily optimizing frequency curves. This system searches for parameters with a type of GA called Interactive Evolutionary Computation (IEC). On the other hand, the system using IEC has a phase for users to evaluate, we need to consider the tiredness of users. This tiredness is connected to the effectiveness of the search with GA. In this research, for the analysis of the tiredness of users, we evaluated the convergence performance of GA to fit the goal which is known in advance. As a result, we found that our method has better convergence performance than a previous method

Temperature compensation via cooperative stability in protein degradation

Temperature compensation is a notable property of circadian oscillators that indicates the insensitivity of the oscillator system's period to temperature changes; the underlying mechanism, however, is still unclear. We investigated the influence of protein dimerization and cooperative stability in protein degradation on the temperature compensation ability of two oscillators. Here, cooperative stability means that high-order oligomers are more stable than their monomeric counterparts. The period of an oscillator is affected by the parameters of the dynamic system, which in turn are influenced by temperature. We adopted the Repressilator and the Atkinson oscillator to analyze the temperature sensitivity of their periods. Phase sensitivity analysis was employed to evaluate the period variations of different models induced by perturbations to the parameters. Furthermore, we used experimental data provided by other studies to determine the reasonable range of parameter temperature sensitivity. We then applied the linear programming method to the oscillatory systems to analyze the effects of protein dimerization and cooperative stability on the temperature sensitivity of their periods, which reflects the ability of temperature compensation in circadian rhythms. Our study explains the temperature compensation mechanism for circadian clocks. Compared with the no-dimer mathematical model and linear model for protein degradation, our theoretical results show that the nonlinear protein degradation caused by cooperative stability is more beneficial for realizing temperature compensation of the circadian clock.Comment: 27 pages, 5 figure

Re-purposing Heterogeneous Generative Ensembles with Evolutionary Computation

Generative Adversarial Networks (GANs) are popular tools for generative modeling. The dynamics of their adversarial learning give rise to convergence pathologies during training such as mode and discriminator collapse. In machine learning, ensembles of predictors demonstrate better results than a single predictor for many tasks. In this study, we apply two evolutionary algorithms (EAs) to create ensembles to re-purpose generative models, i.e., given a set of heterogeneous generators that were optimized for one objective (e.g., minimize Frechet Inception Distance), create ensembles of them for optimizing a different objective (e.g., maximize the diversity of the generated samples). The first method is restricted by the exact size of the ensemble and the second method only restricts the upper bound of the ensemble size. Experimental analysis on the MNIST image benchmark demonstrates that both EA ensembles creation methods can re-purpose the models, without reducing their original functionality. The EA-based demonstrate significantly better performance compared to other heuristic-based methods. When comparing both evolutionary, the one with only an upper size bound on the ensemble size is the best.Comment: Accepted as a full paper for the Genetic and Evolutionary Computation Conference - GECCO'2

L-carnitine prevents lenvatinib-induced muscle toxicity without impairment of the anti-angiogenic efficacy

Lenvatinib is an oral tyrosine kinase inhibitor that acts on multiple receptors involved in angiogenesis. Lenvatinib is a standard agent for the treatment of several types of advanced cancers; however, it frequently causes muscle-related adverse reactions. Our previous study revealed that lenvatinib treatment reduced carnitine content and the expression of carnitine-related and oxidative phosphorylation (OXPHOS) proteins in the skeletal muscle of rats. Therefore, this study aimed to evaluate the effects of L-carnitine on myotoxic and anti-angiogenic actions of lenvatinib. Co-administration of L-carnitine in rats treated with lenvatinib for 2 weeks completely prevented the decrease in carnitine content and expression levels of carnitine-related and OXPHOS proteins, including carnitine/organic cation transporter 2, in the skeletal muscle. Moreover, L-carnitine counteracted lenvatinib-induced protein synthesis inhibition, mitochondrial dysfunction, and cell toxicity in C2C12 myocytes. In contrast, L-carnitine had no influence on either lenvatinib-induced inhibition of vascular endothelial growth factor receptor 2 phosphorylation in human umbilical vein endothelial cells or angiogenesis in endothelial tube formation and mouse aortic ring assays. These results suggest that L-carnitine supplementation could prevent lenvatinib-induced muscle toxicity without diminishing its antineoplastic activity, although further clinical studies are needed to validate these findings