Neural Connectivity with Hidden Gaussian Graphical State-Model

The noninvasive procedures for neural connectivity are under questioning. Theoretical models sustain that the electromagnetic field registered at external sensors is elicited by currents at neural space. Nevertheless, what we observe at the sensor space is a superposition of projected fields, from the whole gray-matter. This is the reason for a major pitfall of noninvasive Electrophysiology methods: distorted reconstruction of neural activity and its connectivity or leakage. It has been proven that current methods produce incorrect connectomes. Somewhat related to the incorrect connectivity modelling, they disregard either Systems Theory and Bayesian Information Theory. We introduce a new formalism that attains for it, Hidden Gaussian Graphical State-Model (HIGGS). A neural Gaussian Graphical Model (GGM) hidden by the observation equation of Magneto-encephalographic (MEEG) signals. HIGGS is equivalent to a frequency domain Linear State Space Model (LSSM) but with sparse connectivity prior. The mathematical contribution here is the theory for high-dimensional and frequency-domain HIGGS solvers. We demonstrate that HIGGS can attenuate the leakage effect in the most critical case: the distortion EEG signal due to head volume conduction heterogeneities. Its application in EEG is illustrated with retrieved connectivity patterns from human Steady State Visual Evoked Potentials (SSVEP). We provide for the first time confirmatory evidence for noninvasive procedures of neural connectivity: concurrent EEG and Electrocorticography (ECoG) recordings on monkey. Open source packages are freely available online, to reproduce the results presented in this paper and to analyze external MEEG databases

Likelihood-based Imprecise Regression

We introduce a new approach to regression with imprecisely observed data, combining likelihood inference with ideas from imprecise probability theory, and thereby taking different kinds of uncertainty into account. The approach is very general and applicable to various kinds of imprecise data, not only to intervals. In the present paper, we propose a regression method based on this approach, where no parametric distributional assumption is needed and interval estimates of quantiles of the error distribution are used to identify plausible descriptions of the relationship of interest. Therefore, the proposed regression method is very robust. We apply our robust regression method to an interesting question in the social sciences. The analysis, based on survey data, yields a relatively imprecise result, reflecting the high amount of uncertainty inherent in the analyzed data set

Role of the Srs2-Rad51 Interaction Domain in Crossover Control in Saccharomyces cerevisiae.

Saccharomyces cerevisiae Srs2, in addition to its well-documented antirecombination activity, has been proposed to play a role in promoting synthesis-dependent strand annealing (SDSA). Here we report the identification and characterization of an SRS2 mutant with a single amino acid substitution (srs2-F891A) that specifically affects the Srs2 pro-SDSA function. This residue is located within the Srs2-Rad51 interaction domain and embedded within a protein sequence resembling a BRC repeat motif. The srs2-F891A mutation leads to a complete loss of interaction with Rad51 as measured through yeast two-hybrid analysis and a partial loss of interaction as determined through protein pull-down assays with purified Srs2, Srs2-F891A, and Rad51 proteins. Even though previous work has shown that internal deletions of the Srs2-Rad51 interaction domain block Srs2 antirecombination activity in vitro, the Srs2-F891A mutant protein, despite its weakened interaction with Rad51, exhibits no measurable defect in antirecombination activity in vitro or in vivo Surprisingly, srs2-F891A shows a robust shift from noncrossover to crossover repair products in a plasmid-based gap repair assay, but not in an ectopic physical recombination assay. Our findings suggest that the Srs2 C-terminal Rad51 interaction domain is more complex than previously thought, containing multiple interaction sites with unique effects on Srs2 activity

Continuous time controller based on SMC and disturbance observer for piezoelectric actuators

Abstract – In this work, analog application for the Sliding Mode Control (SMC) to piezoelectric actuators (PEA) is presented. DSP application of the algorithm suffers from ADC and DAC conversions and mainly faces limitations in sampling time interval. Moreover piezoelectric actuators are known to have very large bandwidth close to the DSP operation frequency. Therefore, with the direct analog application, improvement of the performance and high frequency operation are expected. Design of an appropriate SMC together with a disturbance observer is suggested to have continuous control output and related experimental results for position tracking are presented with comparison of DSP and analog control application

A near infrared frequency comb for Y+J band astronomical spectroscopy

Radial velocity (RV) surveys supported by high precision wavelength references (notably ThAr lamps and I2 cells) have successfully identified hundreds of exoplanets; however, as the search for exoplanets moves to cooler, lower mass stars, the optimum wave band for observation for these objects moves into the near infrared (NIR) and new wavelength standards are required. To address this need we are following up our successful deployment of an H band(1.45-1.7{\mu}m) laser frequency comb based wavelength reference with a comb working in the Y and J bands (0.98-1.3{\mu}m). This comb will be optimized for use with a 50,000 resolution NIR spectrograph such as the Penn State Habitable Zone Planet Finder. We present design and performance details of the current Y+J band comb.Comment: Submitted to SPIE, conference proceedings 845

Gravitational waves: search results, data analysis and parameter estimation

The Amaldi 10 Parallel Session C2 on gravitational wave (GW) search results, data analysis and parameter estimation included three lively sessions of lectures by 13 presenters, and 34 posters. The talks and posters covered a huge range of material, including results and analysis techniques for ground-based GW detectors, targeting anticipated signals from different astrophysical sources: compact binary inspiral, merger and ringdown; GW bursts from intermediate mass binary black hole mergers, cosmic string cusps, core-collapse supernovae, and other unmodeled sources; continuous waves from spinning neutron stars; and a stochastic GW background. There was considerable emphasis on Bayesian techniques for estimating the parameters of coalescing compact binary systems from the gravitational waveforms extracted from the data from the advanced detector network. This included methods to distinguish deviations of the signals from what is expected in the context of General Relativity