Detecting Generalized Synchronization Between Chaotic Signals: A Kernel-based Approach

A unified framework for analyzing generalized synchronization in coupled chaotic systems from data is proposed. The key of the proposed approach is the use of the kernel methods recently developed in the field of machine learning. Several successful applications are presented, which show the capability of the kernel-based approach for detecting generalized synchronization. It is also shown that the dynamical change of the coupling coefficient between two chaotic systems can be captured by the proposed approach.Comment: 20 pages, 15 figures. massively revised as a full paper; issues on the choice of parameters by cross validation, tests by surrogated data, etc. are added as well as additional examples and figure

SYZ mirror symmetry for hypertoric varieties

We construct a Lagrangian torus fibration on a smooth hypertoric variety and a corresponding SYZ mirror variety using $T$-duality and generating functions of open Gromov-Witten invariants. The variety is singular in general. We construct a resolution using the wall and chamber structure of the SYZ base.Comment: v_2: 31 pages, 5 figures, minor revision. To appear in Communications in Mathematical Physic

Safety and feasibility of switching from phenytoin to levetiracetam monotherapy for glioma-related seizure control following craniotomy: a randomized phase II pilot study

Seizures are common in patients with gliomas, and phenytoin (PHT) is frequently used to control tumor-related seizures. PHT, however, has many undesirable side effects (SEs) and drug interactions with glioma chemotherapy. Levetiracetam (LEV) is a newer antiepileptic drug (AED) with fewer SEs and essentially no drug interactions. We performed a pilot study testing the safety and feasibility of switching patients from PHT to LEV monotherapy for postoperative control of glioma-related seizures. Over a 13-month period, 29 patients were randomized in a 2:1 ratio to initiate LEV therapy within 24 h of surgery or to continue PHT therapy. 6 month follow-up data were available for 15 patients taking LEV and for 8 patients taking PHT. In the LEV group, 13 patients (87%) were seizure-free. In the PHT group, 6 patients (75%) were seizure-free. Reported SEs at 6 months was as follows (%LEV/%PHT group): dizziness (0/14), difficulty with coordination (0/29), depression (7/14) lack of energy or strength (20/43), insomnia (40/43), mood instability (7/0). The pilot data presented here suggest that it is safe to switch patients from PHT to LEV monotherapy following craniotomy for supratentorial glioma. A large-scale, double-blinded, randomized control trial of LEV versus PHT is required to determine seizure control equivalence and better assess differences in SEs

Analysis of Reactivity Temperature Coefficient for Light Water Moderated HEU-UAl 4 and LEU-UO 2 Lattices of MNSR

Abstract: Analysis of the Reactivity Temperature Coefficient (RTC) of the Ghana Research Reactor-1 using the reference HEU-UAl 4 and then the LEU-UO 2 fuel currently being developed under the RETR programme was carried out to determine the Fuel Temperature Coefficient (FTC) and Moderator Temperature Coefficient (MTC) using SCUBA, a locally developed FORTRAN 95 code. The contribution of each isotope present in the fuel cell to RTC was determined by analyzing the temperature effect on the thermal fission factor (η) and the thermal utilization factor (f). The average values of the core RTC for the temperature range of 15 o C to 140 o C at the beginning of life of the core were observed to be -0.70×10 -4 and -2.061×10 -4 for the HEU-UAl 4 and the LEU-UO 2 respectively

Music recommendation according to human motion based on kernel CCA-based relationship

In this article, a method for recommendation of music pieces according to human motions based on their kernel canonical correlation analysis (CCA)-based relationship is proposed. In order to perform the recommendation between different types of multimedia data, i.e., recommendation of music pieces from human motions, the proposed method tries to estimate their relationship. Specifically, the correlation based on kernel CCA is calculated as the relationship in our method. Since human motions and music pieces have various time lengths, it is necessary to calculate the correlation between time series having different lengths. Therefore, new kernel functions for human motions and music pieces, which can provide similarities between data that have different time lengths, are introduced into the calculation of the kernel CCA-based correlation. This approach effectively provides a solution to the conventional problem of not being able to calculate the correlation from multimedia data that have various time lengths. Therefore, the proposed method can perform accurate recommendation of best matched music pieces according to a target human motion from the obtained correlation. Experimental results are shown to verify the performance of the proposed method