Cortical GABAergic interneurons have essential roles for information processing and their dysfunction is implicated in neuropsychiatric disorders. Transcriptional codes are elucidating mechanisms of interneuron specification in the MGE (a subcortical progenitor zone), which regulate their migration, integration, and function within cortical circuitry. Lhx6, a LIM-homeodomain transcription facto...

In this paper, we focus on the automatic differential cryptanalysis of ARX block ciphers with respect to XOR-difference, and develop Mouha et al.’s framework for finding differential characteristics by adding a new method to construct long characteristics from short ones. The new method reduces the searching time a lot and makes it possible to search differential characteristics for ARX block c...

ARX models is a common class of models of dynamical systems. Here, we consider the case when the innovation process is not well described by Gaussian noise and instead propose to model the driving noise as Student's t distributed. The t distribution is more heavy tailed than the Gaussian distribution, which provides an increased robustness to data anomalies, such as outliers and missing observa...

This paper presents steam temperature models for steam distillation pilot-scale (SDPS) by comparing Pseudo Random Binary Sequence (PRBS) versus Multi-Sine (M-Sine) perturbation signal Both perturbation signals were applied to nonlinear steam distillation system to study the capability of these input signals in exciting nonlinearity of system dynamics. In this work, both linear and nonlinear ARX...

We present a methodology for generating probabilistic predictions for the Disturbance Storm Time (Dst) geomagnetic activity index. We focus on the One Step Ahead prediction task and use the OMNI hourly resolution data to build our models. Our proposed methodology is based on the technique of Gaussian Process Regression. Within this framework we develop two models; Gaussian Process Autoregressiv...

Even though efficiency of coal-fired power plant is proportional to operating temperature, increase of operating temperature is limited by a technological level of each power plant components. It is an alternative plan to increase operating pressure up to ultra super critical (USC) point for efficiency enhancement. It is difficult to control the system in that pressure within safety guideline t...

A wide literature is available on the asymptotic behavior of the Durbin-Watson statistic for autoregressive models. However, it is impossible to find results on the Durbin-Watson statistic for autoregressive models with adaptive control. Our purpose is to fill the gap by establishing the asymptotic behavior of the Durbin Watson statistic for ARX models in adaptive tracking. On the one hand, we ...

In this paper, we study differential attacks against ARX schemes. We build upon the generalized characteristics of de Cannière and Rechberger; we introduce new multi-bit constraints to describe differential characteristics in ARX designs more accurately, and quartet constraints to analyze boomerang attacks. We also describe how to propagate those constraints; this can be used either to assist m...

This paper presents an overview and recent advances in impedance-based structural health monitoring. The basic principle behind this technique is to apply high-frequency structural excitations (typically greater than 30kHz) through surface-bonded piezoelectric transducers, and measure the impedance of structures by monitoring the current and voltage applied to the piezoelectric transducers. Cha...

A quasi-linear ARX neural network model (QARXNN) is a nonlinear model built using neural networks (NN). It has a linear-ARX structure where NN is an embedded system to give the parameters for the regression vector. There are two contributions in this paper, 1) Hierarchical Algorithms is proposed for the training of QARXNN model, 2) an adaptive learning is implemented to update learning rate in ...