Probabilistic Prediction of Chaotic Time Series Using Similarity of Attractors and LOOCV Predictable Horizons for Obtaining Plausible Predictions

This paper presents a method for probabilistic prediction of chaotic time series. So far, we have developed several model selection methods for chaotic time series prediction, but the methods cannot estimate the predictable horizon of predicted time series. Instead of using model selection methods employing the estimation of mean square prediction error (MSE), we present a method to obtain a probabilistic prediction which provides a prediction of time series and the estimation of predictable horizon. The method obtains a set of plausible predictions by means of using the similarity of attractors of training time series and the time series predicted by a number of learning machines with different parameter values, and then obtains a smaller set of more plausible predictions with longer predictable horizons estimated by LOOCV (leave-one-out cross-validation) method. The effectiveness and the properties of the present method are shown by means of analyzing the result of numerical experiments.22nd International Conference, ICONIP 2015, November 9-12, 2015, Istanbul, Turke

Single-crystal growth and dependences on the hole concentration and magnetic field of the magnetic ground state in the edge-sharing CuO2_2 chain system Ca2+x_{2+x}Y2−x_{2-x}Cu5_5O10_{10}

We have succeeded in growing large-size single-crystals of Ca$_{2+x}$Y$_{2-x}$Cu$_5$O$_{10}$ with $0 \le x \le 1.67$ and measured the magnetic susceptibility, specific heat and magnetization curve, in order to study the magnetic ground state in the edge-sharing CuO$_2$ chain as a function of hole concentration and magnetic field. In $0 \le x \le 1.3$, it has been found that an antiferromagnetically ordered phase with the magnetic easy axis along the b-axis is stabilized and that a spin-flop transition occurs by the application of magnetic fields parallel to the b-axis. The antiferromagnetic transition temperature decreases with increasing $x$ and disappears around $x =$ 1.4. Alternatively, a spin-glass phase appears around $x = 1.5$. At $x = 1.67$ where the hole concentration is $\sim$ 1/3 per Cu, it appears that a spin-gap state is formed owing to the formation of spin-singlet pairs. No sign of the coexistence of an antiferromagnetically ordered state and a spin-gap one suggested in Ca$_{1-x}$CuO$_2$ has been found in Ca$_{2+x}$Y$_{2-x}$Cu$_5$O$_{10}$.Comment: 13 pages, 12 figures, 1 tabl

Effects of hole-doping on the magnetic ground state and excitations in the edge-sharing CuO2_2 chains of Ca2+x_{2+x}Y2−x_{2-x}Cu5_5O10_{10}

Neutron scattering experiments were performed on the undoped and hole-doped Ca$_{2+x}$Y$_{2-x}$Cu$_5$O$_{10}$, which consists of ferromagnetic edge-sharing CuO$_2$ chains. It was previously reported that in the undoped Ca$_2$Y$_2$Cu$_5$O$_{10}$ there is an anomalous broadening of spin-wave excitations along the chain, which is caused mainly by the antiferromagnetic interchain interactions [Matsuda $et$ $al.$, Phys. Rev. B 63, 180403(R) (2001)]. A systematic study of temperature and hole concentration dependencies of the magnetic excitations shows that the magnetic excitations are softened and broadened with increasing temperature or doping holes irrespective of $Q$ direction. The broadening is larger at higher $Q$. A characteristic feature is that hole-doping is much more effective to broaden the excitations along the chain. It is also suggested that the intrachain interaction does not change so much with increasing temperature or doping although the anisotropic interaction and the interchain interaction are reduced. In the spin-glass phase ($x$=1.5) and nearly disordered phase ($x$=1.67) the magnetic excitations are much broadened in energy and $Q$. It is suggested that the spin-glass phase originates from the antiferromagnetic clusters, which are caused by the hole disproportionation.Comment: 8 pages, submitted to Phys. Rev.

Relaxin-1–deficient mice develop an age-related progression of renal fibrosis

Relaxin-1–deficient mice develop an age-related progression of renal fibrosis.BackgroundRelaxin (RLX) is a peptide hormone that stimulates the breakdown of collagen in preparation for parturition and when administered to various models of induced fibrosis. However, its significance in the aging kidney is yet to be established. In this study, we compared structural and functional changes in the kidney of aging relaxin-1 (RLX-/-) deficient mice and normal (RLX+/+) mice.MethodsThe kidney cortex and medulla of male and female RLX+/+ and RLX-/- mice at various ages were analyzed for collagen content, concentration, and types. Histologic analysis, reverse transcription-polymerase chain reaction (RT-PCR) of relaxin and relaxin receptor mRNA expression, receptor autoradiography, glomerular isolation/analysis, and serum/urine analysis were also employed. Relaxin treatment of RLX-/- mice was used to confirm the antifibrotic effects of the peptide.ResultsWe demonstrate an age-related progression of renal fibrosis in male, but not female, RLX-/- mice with significantly (P < 0.05) increased tissue dry weight, collagen (type I) content and concentration. The increased collagen expression in the kidney was associated with increased glomerular matrix and to a lesser extent, interstitial fibrosis in RLX-/- mice, which also had significantly increased serum creatinine (P < 0.05) and urinary protein (P < 0.05). Treatment of RLX-/- mice with relaxin in established stages of renal fibrosis resulted in the reversal of collagen deposition.ConclusionThis study supports the concept that relaxin may provide a means to regulate excessive collagen deposition during kidney development and in diseased states characterized by renal fibrosis

Marimo machines: Oscillators, biosensors and actuators

BackgroundThe green algae balls (Aegagropila linnaei), known as Marimo, are large spherical colonies of live photosynthetic filaments, formed by rolling water currents in freshwater lakes. Photosynthesis therein produces gas bubbles that can attach to the Marimo, consequently changing its buoyancy. This property allows them to float in the presence of light and sink in its absence.ResultsWe demonstrate that this ability can be harnessed to make actuators, biosensors and bioprocessors (oscillator, logic gates). Factors affecting Marimo movement have been studied to enable the design, construction and testing of working prototypes.ConclusionsA novel actuator design is reported, incorporating an enhanced bubble retention system and the design and optimisation of a bio-oscillator is demonstrated. A range of logic gates (or, and, nor, nand, xor) implementable with Marimo have been proposed

Efficiency of Peptide Nucleic Acid-Directed PCR Clamping and Its Application in the Investigation of Natural Diets of the Japanese Eel Leptocephali

Polymerase chain reaction (PCR)-clamping using blocking primer and DNA-analogs, such as peptide nucleotide acid (PNA), may be used to selectively amplify target DNA for molecular diet analysis. We investigated PCR-clamping efficiency by studying PNA position and mismatch with complementary DNA by designing PNAs at five different positions on the nuclear rDNA internal transcribed spacer 1 of the Japanese eel Anguilla japonica in association with intra-specific nucleotide substitutions. All five PNAs were observed to efficiently inhibit amplification of a fully complementary DNA template. One mismatch between PNA and template DNA inhibited amplification of the template DNA, while two or more mismatches did not. DNA samples extracted from dorsal muscle and intestine of eight wild-caught leptochephalus larvae were subjected to this analysis, followed by cloning, nucleotide sequence analysis, and database homology search. Among 12 sequence types obtained from the intestine sample, six were identified as fungi. No sequence similarities were found in the database for the remaining six types, which were not related to one another. These results, in conjunction with our laboratory observations on larval feeding, suggest that eel leptocephali may not be dependent upon living plankton for their food source

Prediction of Promiscuous P-Glycoprotein Inhibition Using a Novel Machine Learning Scheme

BACKGROUND: P-glycoprotein (P-gp) is an ATP-dependent membrane transporter that plays a pivotal role in eliminating xenobiotics by active extrusion of xenobiotics from the cell. Multidrug resistance (MDR) is highly associated with the over-expression of P-gp by cells, resulting in increased efflux of chemotherapeutical agents and reduction of intracellular drug accumulation. It is of clinical importance to develop a P-gp inhibition predictive model in the process of drug discovery and development. METHODOLOGY/PRINCIPAL FINDINGS: An in silico model was derived to predict the inhibition of P-gp using the newly invented pharmacophore ensemble/support vector machine (PhE/SVM) scheme based on the data compiled from the literature. The predictions by the PhE/SVM model were found to be in good agreement with the observed values for those structurally diverse molecules in the training set (n = 31, r(2) = 0.89, q(2) = 0.86, RMSE = 0.40, s = 0.28), the test set (n = 88, r(2) = 0.87, RMSE = 0.39, s = 0.25) and the outlier set (n = 11, r(2) = 0.96, RMSE = 0.10, s = 0.05). The generated PhE/SVM model also showed high accuracy when subjected to those validation criteria generally adopted to gauge the predictivity of a theoretical model. CONCLUSIONS/SIGNIFICANCE: This accurate, fast and robust PhE/SVM model that can take into account the promiscuous nature of P-gp can be applied to predict the P-gp inhibition of structurally diverse compounds that otherwise cannot be done by any other methods in a high-throughput fashion to facilitate drug discovery and development by designing drug candidates with better metabolism profile