EEG signals analysis using multiscale entropy for depth of anesthesia monitoring during surgery through artificial neural networks

In order to build a reliable index to monitor the depth of anesthesia (DOA), many algorithms have been proposed in recent years, one of which is sample entropy (SampEn), a commonly used and important tool to measure the regularity of data series. However, SampEn only estimates the complexity of signals on one time scale. In this study, a new approach is introduced using multiscale entropy (MSE) considering the structure information over different time scales. The entropy values over different time scales calculated through MSE are applied as the input data to train an artificial neural network (ANN) model using bispectral index (BIS) or expert assessment of conscious level (EACL) as the target. To test the performance of the new index's sensitivity to artifacts, we compared the results before and after filtration by multivariate empirical mode decomposition (MEMD). The new approach via ANN is utilized in real EEG signals collected from 26 patients before and after filtering by MEMD, respectively; the results show that is a higher correlation between index from the proposed approach and the gold standard compared with SampEn. Moreover, the proposed approach is more structurally robust to noise and artifacts which indicates that it can be used for monitoring the DOA more accurately.This research was financially supported by the Center for Dynamical Biomarkers and Translational Medicine, National Central University, Taiwan, which is sponsored by Ministry of Science and Technology (Grant no. MOST103-2911-I-008-001). Also, it was supported by National Chung-Shan Institute of Science & Technology in Taiwan (Grant nos. CSIST-095-V301 and CSIST-095-V302) and National Natural Science Foundation of China (Grant no. 51475342)

Both doublecortin and doublecortin-like kinase play a role in cortical interneuron migration

Type I lissencephaly, a genetic disease characterized by disorganized cortical layers and gyral abnormalities, is associated with severe cognitive impairment and epilepsy. Two genes, LIS1 and doublecortin (DCX), have been shown to be responsible for a large proportion of cases of type I lissencephaly. Both genes encode microtubule-associated proteins that have been shown to be important for radial migration of cortical pyramidal neurons. To investigate whether DCX also plays a role in cortical interneuron migration, we inactivated DCX in the ganglionic eminence of rat embryonic day 17 brain slices using short hairpin RNA. We found that, when DCX expression was blocked, the migration of interneurons from the ganglionic eminence to the cerebral cortex was slowed but not absent, similar to what had previously been reported for radial neuronal migration. In addition, the processes of DCX-deficient migrating interneurons were more branched than their counterparts in control experiments. These effects were rescued by DCX overexpression, confirming the specificity to DCX inactivation. A similar delay in interneuron migration was observed when Doublecortin-like kinase (DCLK), a microtubule-associated protein related to DCX, was inactivated, although the morphology of the cells was not affected. The importance of these genes in interneuron migration was confirmed by our finding that the cortices of Dcx, Dclk, and Dcx/Dclk mutant mice contained a reduced number of such cells in the cortex and their distribution was different compared with wild-type controls. However, the defect was different for each group of mutant animals, suggesting that DCX and DCLK have distinct roles in cortical interneuron migration

All-optical wavelength conversion using mode switching in InP microdisc laser

Wavelength conversion using an indium phosphide based microdisc laser (MDL) heterogeneously integrated on a silicon-on-insulator waveguide is reported. Several lasing modes are present within the disc cavity, between which wavelength conversion can be performed by mode switching and spectral filtering. For the first time, low-power wavelength up- and downconversion using one single MDL is demonstrated. Operation with a bit error rate below 10(-9) at 2.5 Gbit/s and operation below the forward-error-correction limit of 10(-3) at 10 Gbit/s are shown without the use of additional seeding beams

Nonreciprocal Wavefront Engineering with Time-Modulated Gradient Metasurfaces

We propose a paradigm to realize nonreciprocal wavefront engineering using time-modulated gradient metasurfaces. The essential building block of these surfaces is a subwavelength unit cell whose reflection coefficient oscillates at low frequency. We demonstrate theoretically and experimentally that such modulation permits tailoring the phase and amplitude of any desired nonlinear harmonic and determines the behavior of all other emerging fields. By appropriately adjusting the phase delay applied to the modulation of each unit cell, we realize time-modulated gradient metasurfaces that provide efficient conversion between two desired frequencies and enable nonreciprocity by (i) imposing drastically different phase gradients during the up/down conversion processes and (ii) exploiting the interplay between the generation of certain nonlinear surface and propagative waves. To demonstrate the performance and broad reach of the proposed platform, we design and analyze metasurfaces able to implement various functionalities, including beam steering and focusing, while exhibiting strong and angle-insensitive nonreciprocal responses. Our findings open an alternative direction in the field of gradient metasurfaces, in which wavefront control and magnetic-free nonreciprocity are locally merged to manipulate the scattered fields

Stabilized conforming nodal integration: Exactness and variational justification

In most Galerkin mesh-free methods, background integration cells partitioning the problem domain are required to evaluate the weak form. It is therefore worthwhile to consider these methods using the notions of domain decomposition with the integration cells being the subdomains. Presuming that the analytical solution is admissible in the trial solution, domain and boundary integration exactness, which depend on the orders of the employed trial solution and the required solution exactness, are identified for the strict satisfaction of traction reciprocity and natural boundary condition in the weak form. Unfortunately, trial solutions constructed by many mesh-free approximants contain non-polynomial terms which cannot be exactly integrated by Gaussian quadratures. Recently, stabilized conforming (SC) nodal integration for Galerkin mesh-free methods was proposed and illustrated to be linearly exact. This paper will discuss how linear exactness is ensured and how spurious oscillation encountered by direct nodal integration is suppressed in SC nodal integration from a domain decomposition point of view. Moreover, it will be shown that SC nodal integration can be formulated by the Hellinger-Reissner Principle and thus justified in the classical variational sense. Applications of the method to straight beam, plate and curved beam problems are presented. © 2004 Elsevier B.V. All rights reserved.postprin

Quinoidization of regioregular oligo(THIENO[3,4-b]THIOPHENE)s

Caracterización de oligotiofenosUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Design and multiplier-less implementation of a class of two-channel PR FIR filterbanks and wavelets with low system delay

In this paper, a new method for designing two-channel PR FIR filterbanks with low system delay is proposed. It is based on the generalization of the structure previously proposed by Phoong et al. Such structurally PR filterbanks are parameterized by two functions (β(z) and α(z)) that can be chosen as linear-phase FIR or allpass functions to construct FIR/IIR filterbanks with good frequency characteristics. The case of using identical β(z) and α(z) was considered by Phoong et al. with the delay parameter M chosen as 2N - 1. In this paper, the more general case of using different nonlinear-phase FIR functions for β(z) and α(z) is studied. As the linear-phase constraint is relaxed, the lengths of β(z) and α(z) are no longer restricted by the delay parameters of the filterbanks. Hence, higher stopband attenuation can still be achieved at low system delay. The design of the proposed low-delay filterbanks is formulated as a complex polynomial approximation problem, which can be solved by the Remez exchange algorithm or analytic formula with very low complexity. In addition, the orders and delay parameters can be estimated from the given filter specifications using a simple empirical formula. Therefore, low-delay two-channel PR filterbanks with flexible stopband attenuation and cutoff frequencies can be designed using existing filter design algorithms. The generalization of the present approach to the design of a class of wavelet bases associated with these low-delay filterbanks and its multiplier-less implementation using the sum of powers-of-two coefficients are also studied.published_or_final_versio

History of early life adversity is associated with increased food addiction and sex-specific alterations in reward network connectivity in obesity.

Background:Neuroimaging studies have identified obesity-related differences in the brain's resting state activity. An imbalance between homeostatic and reward aspects of ingestive behaviour may contribute to obesity and food addiction. The interactions between early life adversity (ELA), the reward network and food addiction were investigated to identify obesity and sex-related differences, which may drive obesity and food addiction. Methods:Functional resting state magnetic resonance imaging was acquired in 186 participants (high body mass index [BMI]: ≥25: 53 women and 54 men; normal BMI: 18.50-24.99: 49 women and 30 men). Participants completed questionnaires to assess ELA (Early Traumatic Inventory) and food addiction (Yale Food Addiction Scale). A tripartite network analysis based on graph theory was used to investigate the interaction between ELA, brain connectivity and food addiction. Interactions were determined by computing Spearman rank correlations, thresholded at q < 0.05 corrected for multiple comparisons. Results:Participants with high BMI demonstrate an association between ELA and food addiction, with reward regions playing a role in this interaction. Among women with high BMI, increased ELA was associated with increased centrality of reward and emotion regulation regions. Men with high BMI showed associations between ELA and food addiction with somatosensory regions playing a role in this interaction. Conclusions:The findings suggest that ELA may alter brain networks, leading to increased vulnerability for food addiction and obesity later in life. These alterations are sex specific and involve brain regions influenced by dopaminergic or serotonergic signalling