iMap4: An Open Source Toolbox for the Statistical Fixation Mapping of Eye Movement data with Linear Mixed Modeling.

A major challenge in modern eye movement research is to statistically map where observers are looking, by isolating the significant differences between groups and conditions. Compared to signals of contemporary neuroscience measures, such as M/EEG and fMRI, eye movement data are sparser with much larger variations in space across trials and participants. As a result, the implementation of a conventional linear modeling approach on two-dimensional fixation distributions often returns unstable estimations and underpowered results, leaving this statistical problem unresolved (Liversedge, Gilchrist, & Everling. 2011). Here, we present a new version of the iMap toolbox (Caldara and Miellet, 2011) which tackles this issue by implementing a statistical framework comparable to those developped in state-of the- art neuroimaging data processing toolboxes. iMap4 uses univariate, pixel-wise Linear Mixed Models (LMM) on the smoothed fixation data, with the flexibility of coding for multiple between- and within- subject comparisons and performing all the possible linear contrasts for the fixed effects (main effects, interactions, etc.). Importantly, we also introduced novel nonparametric tests based on resampling to assess statistical significance. Finally, we validated this approach by using both experimental and Monte Carlo simulation data. iMap4 is a freely available MATLAB open source toolbox for the statistical fixation mapping of eye movement data, with a user-friendly interface providing straightforward, easy to interpret statistical graphical outputs. iMap4 matches the standards of robust statistical neuroimaging methods and represents an important step in the data-driven processing of eye movement fixation data, an important field of vision sciences

Meeting abstract: iMap 4: An Open Source Toolbox for the Statistical Fixation Mapping of Eye Movement data with Linear Mixed Modeling.

A major challenge in modern eye movement research is to statistically map where observers are looking at, as well as isolating statistical significant differences between groups and conditions. Compared to signals of contemporary neuroscience measures, such as M/EEG and fMRI, eye movement data are sparse with much larger variations across trials and participants. As a result, the implementation of a conventional Hierarchical Linear Model approach on two-dimensional fixation distributions often returns unstable estimations and underpowered results, leaving this statistical problem unresolved. Here, we tackled this issue by using the statistical framework implemented in diverse state-of-the-art neuroimaging data processing toolboxes: Statistical Parametric Mapping (SPM), Fieldtrip and LIMO EEG. We first estimated the mean individual fixation maps per condition by using trimmean to account for the sparseness and the high variations of fixation data. We then applied a univariate, pixel-wise linear mixed model (LMM) on the smoothed fixation data with each subject as a random effect, which offers the flexibility to code for multiple between- and within- subject comparisons. After this step, our approach allows to perform all the possible linear contrasts for the fixed effects (main effects, interactions, etc.). Importantly, we also introduced a novel spatial cluster test based on bootstrapping to assess the statistical significance of the linear contrasts. Finally, we validated this approach by using both experimental and computer simulation data with a Monte Carlo approach. iMap 4 is a freely available MATLAB open source toolbox for the statistical fixation mapping of eye movement data, with a user-friendly interface providing straightforward, easy to interpret statistical graphical outputs and matching the standards in robust statistical neuroimaging methods. iMap 4 represents a major step in the processing of eye movement fixation data, paving the way to a routine use of robust data-driven analyses in this important field of vision sciences. Meeting abstract presented at VSS 2015

MULTIRESOLUTION SEGMENTATION FOR EXTRACTING PLASTIC GREENHOUSES FROM DEIMOS-2 IMAGERY

Abstract. Accurate greenhouse mapping can support environment monitoring and resource management. In an object-based image analysis (OBIA) approach focused on plastic covered greenhouses (PCG) classification, the segmentation is a crucial step for the goodness of the final results. Multiresolution segmentation (MRS) is one of the most used algorithms in OBIA approaches, being greatly enabled by the advent of the commercial software eCognition. Therefore, in addition to the segmentation algorithm used, it is very important to count on tools to assess the quality of segmentation results from digital images in order to obtain the most similar segments to the real PCG objects. In this work, several factors affecting MRS such as the type of input image and the best MRS parameters (i.e., scale, compactness and shape), have been analysed. In this regard, more than 2800 segmentations focused on PCG land cover were conducted from four pre-processed Deimos-2 very high-resolution (VHR) satellite orthoimages taken in the Southeast of Spain (Almería). Specifically, one multispectral and one pansharpened Deimos-2 orthoimages, both with and without atmospheric correction were tested in this work. The free access AssesSeg command line tool, based on a modified version of the supervised discrepancy measure named Euclidean Distance 2 (ED2), was used to determine the best MRS parameters for all the VHR satellite images. According to both the supervised discrepancy measure ED2 and visual perception, the best segmentation on PCG was obtained over the atmospherically corrected pansharpened Deimos-2 orthoimage, achieving very good results

Measurement and physical interpretation of the mean motion of turbulent density patterns detected by the BES system on MAST

The mean motion of turbulent patterns detected by a two-dimensional (2D) beam emission spectroscopy (BES) diagnostic on the Mega Amp Spherical Tokamak (MAST) is determined using a cross-correlation time delay (CCTD) method. Statistical reliability of the method is studied by means of synthetic data analysis. The experimental measurements on MAST indicate that the apparent mean poloidal motion of the turbulent density patterns in the lab frame arises because the longest correlation direction of the patterns (parallel to the local background magnetic fields) is not parallel to the direction of the fastest mean plasma flows (usually toroidal when strong neutral beam injection is present). The experimental measurements are consistent with the mean motion of plasma being toroidal. The sum of all other contributions (mean poloidal plasma flow, phase velocity of the density patterns in the plasma frame, non-linear effects, etc.) to the apparent mean poloidal velocity of the density patterns is found to be negligible. These results hold in all investigated L-mode, H-mode and internal transport barrier (ITB) discharges. The one exception is a high-poloidal-beta (the ratio of the plasma pressure to the poloidal magnetic field energy density) discharge, where a large magnetic island exists. In this case BES detects very little motion. This effect is currently theoretically unexplained.Comment: 28 pages, 15 figures, submitted to PPC

Electroacupuncture activates corticotrophin-releasing hormone-containing neurons in the paraventricular nucleus of the hypothalammus to alleviate edema in a rat model of inflammation

<p>Abstract</p> <p>Background</p> <p>Studies show that electroacupuncture (EA) has beneficial effects in patients with inflammatory diseases. This study investigated the mechanisms of EA anti-inflammation, using a rat model of complete Freund's adjuvant (CFA)-induced hind paw inflammation and hyperalgesia.</p> <p>Design</p> <p>Four experiments were conducted on male Sprague-Dawley rats (n = 6–7/per group). Inflammation was induced by injecting CFA into the plantar surface of one hind paw. Experiment 1 examined whether EA increases plasma adrenocorticotropic hormone (ACTH) levels. Experiments 2 and 3 studied the effects of the ACTH and corticotropin-releasing hormone (CRH) receptor antagonists, ACTH_(11–24)and astressin, on the EA anti-edema. Experiment 4 determined whether EA activates CRH neurons in the paraventricular nucleus of the hypothalammus. EA treatment, 10 Hz at 3 mA and 0.1 ms pulse width, was given twice for 20 min each, once immediately post and again 2 hr post-CFA. Plasma ACTH levels, paw thickness, and paw withdrawal latency to a noxious thermal stimulus were measured 2 h and 5 h after the CFA.</p> <p>Results</p> <p>EA significantly increased ACTH levels 5 h (2 folds) after CFA compared to sham EA control, but EA alone in naive rats and CFA alone did not induce significant increases in ACTH. ACTH_(11–24)and astressin blocked EA anti-edema but not EA anti-hyperalgesia. EA induced phosphorylation of NR1, an essential subunit of the N-methyl-D-aspartic acid (NMDA) receptor, in CRH-containing neurons of the paraventricular nucleus.</p> <p>Conclusion</p> <p>The data demonstrate that EA activates CRH neurons to significantly increase plasma ACTH levels and suppress edema through CRH and ACTH receptors in a rat model of inflammation.</p

Extending the large molecule limit: The role of Fermi resonance in developing a quantum functional group

Polyatomic molecules equipped with optical cycling centers (OCCs), enabling continuous photon scattering during optical excitation, are exciting candidates for advancing quantum information science. However, as these molecules grow in size and complexity the interplay of complex vibronic couplings on optical cycling becomes a critical, but relatively unexplored consideration. Here, we present an extensive exploration of Fermi resonances in large OCC-containing molecules, surpassing the constraints of harmonic approximation. High-resolution dispersed laser-induced fluorescence and excitation spectroscopy reveal Fermi resonances in calcium and strontium phenoxides and their derivatives. This resonance manifests as vibrational coupling leading to intensity borrowing by combination bands near optically active harmonic bands. The resulting additional vibration-changing decays require more repumping lasers for effective optical cycling. To mitigate these effects, we explore altering vibrational energy level spacing through substitutions on the phenyl ring or changes in the OCC itself. While the complete elimination of vibrational coupling in complex molecules remains challenging, our findings underscore the potential for significant mitigation, opening new avenues for optimizing optical cycling in large polyatomic molecules.Comment: 8 pages, 4 figures, 1 table, SI (15 pages

Combustion and gasification characteristics of chars from four commercially significant coals of different rank. Final report

The combustion and gasification kinetics of four size graded coal chars were investigated experimentally in Combustion Engineering's Drop Tube Furnace System (DTFS). The chars were prepared in the DTFS from commercially significant coals representing a wide range of rank; these included a Pittsburgh No. 8 Seam hvAb coal, an Illinois No. 6 Seam hvCb coal, a Wyoming Sub C, and a Texas Lignite A. Additionally, a number of standard ASTM and special bench scale tests were performed on the coals and chars to characterize their physicochemical properties. Results showed that the lower rank coal chars were more reactive than the higher rank coal chars and that combustion reactions of chars were much faster than the corresponding gasification reactions. Fuel properties, temperature, and reactant gas partial pressure had a significant influence on both combustion and gasification, and particle size had a mild but discernible influence on gasification. Fuel reactivities were closely related to pore structure. Computer simulation of the combustion and gasification performances of the subject samples in the DTFS supported the experimental findings

Budget Processes: Theory and Experimental Evidence

This paper studies budget processes, both theoretically and experimentally. We compare the outcomes of bottom-up and top-down budget processes. It is often presumed that a top-down budget process leads to a smaller overall budget than a bottom-up budget process. Ferejohn and Krehbiel (1987) showed theoretically that this need not be the case. We test experimentally the theoretical predictions of their work. The evidence from these experiments lends strong support to their theory, both at the aggregate and the individual subject level