Vortices in equilibrium scalar electrodynamics

Scalar electrodynamics can be used to investigate the formation of cosmic strings in the early universe. We present the results of lattice Monte Carlo simulations of an effective three-dimensional U(1)+Higgs theory that describes the equilibrium properties of finite-temperature scalar electrodynamics near the transition. A gauge-invariant criterion for the existence of a vortex is used in measuring the properties of the vortex network in the equilibrium state both in the Coulomb and in the Higgs phase of the system. The naive definition of the vortex density becomes meaningless in the continuum limit and special care is needed in extracting physical quantities. Numerical evidence for a physical discontinuity in the vortex density is given.Comment: 4 pages. Talk given by A. Rajantie at PASCOS-98, March 199

The GROUSE project III: Ks-band observations of the thermal emission from WASP-33b

In recent years, day-side emission from about a dozen hot Jupiters has been detected through ground-based secondary eclipse observations in the near-infrared. These near-infrared observations are vital for determining the energy budgets of hot Jupiters, since they probe the planet's spectral energy distribution near its peak. The aim of this work is to measure the Ks-band secondary eclipse depth of WASP-33b, the first planet discovered to transit an A-type star. This planet receives the highest level of irradiation of all transiting planets discovered to date. Furthermore, its host-star shows pulsations and is classified as a low-amplitude delta-Scuti. As part of our GROUnd-based Secondary Eclipse (GROUSE) project we have obtained observations of two separate secondary eclipses of WASP-33b in the Ks-band using the LIRIS instrument on the William Herschel Telescope (WHT). The telescope was significantly defocused to avoid saturation of the detector for this bright star (K~7.5). To increase the stability and the cadence of the observations, they were performed in staring mode. We collected a total of 5100 and 6900 frames for the first and the second night respectively, both with an average cadence of 3.3 seconds. On the second night the eclipse is detected at the 12-sigma level, with a measured eclipse depth of 0.244+0.027-0.020 %. This eclipse depth corresponds to a brightness temperature of 3270+115-160 K. The measured brightness temperature on the second night is consistent with the expected equilibrium temperature for a planet with a very low albedo and a rapid re-radiation of the absorbed stellar light. For the other night the short out-of-eclipse baseline prevents good corrections for the stellar pulsations and systematic effects, which makes this dataset unreliable for eclipse depth measurements. This demonstrates the need of getting a sufficient out-of-eclipse baseline.Comment: 12 pages, 10 figures. Accepted for publication in Astronomy and Astrophysic

Masses and Phase Structure in the Ginzburg-Landau Model

We study numerically the phase structure of the Ginzburg-Landau model, with particular emphasis on mass measurements. There is no local gauge invariant order parameter, but we find that there is a phase transition characterized by a vanishing photon mass. For type I superconductors the transition is of 1st order. For type II 1st order is excluded by susceptibility analysis, but the photon correlation length suggests 2nd order critical behaviour with \nu ~ 1/2. The scalar mass, in contrast, does not show clear critical behaviour in the type II regime for V \to \infty, contrary to the conventional picture.Comment: 16 pages, 6 figures. More data gathered, allowing more definite conclusion

Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).Peer reviewe

Parameter estimators of random intersection graphs with thinned communities

This paper studies a statistical network model generated by a large number of randomly sized overlapping communities, where any pair of nodes sharing a community is linked with probability $q$ via the community. In the special case with $q=1$ the model reduces to a random intersection graph which is known to generate high levels of transitivity also in the sparse context. The parameter $q$ adds a degree of freedom and leads to a parsimonious and analytically tractable network model with tunable density, transitivity, and degree fluctuations. We prove that the parameters of this model can be consistently estimated in the large and sparse limiting regime using moment estimators based on partially observed densities of links, 2-stars, and triangles.Comment: 15 page

Levodopa-Induced Changes in Electromyographic Patterns in Patients with Advanced Parkinson's Disease

Levodopa medication is the most efficient treatment for motor symptoms of Parkinson's disease (PD). Levodopa significantly alleviates rigidity, rest tremor, and bradykinesia in PD. The severity of motor symptoms can be graded with UPDRS-III scale. Levodopa challenge test is routinely used to assess patients' eligibility to deep-brain stimulation (DBS) in PD. Feasible and objective measurements to assess motor symptoms of PD during levodopa challenge test would be helpful in unifying the treatment. Twelve patients with advanced PD who were candidates for DBS treatment were recruited to the study. Measurements were done in four phases before and after levodopa challenge test. Rest tremor and rigidity were evaluated using UPDRS-III score. Electromyographic (EMG) signals from biceps brachii and kinematic signals from forearm were recorded with wireless measurement setup. The patients performed two different tasks: arm isometric tension and arm passive flexion-extension. The electromyographic and the kinematic signals were analyzed with parametric, principal component, and spectrum-based approaches. The principal component approach for isometric tension EMG signals showed significant decline in characteristics related to PD during levodopa challenge test. The spectral approach on passive flexion-extension EMG signals showed a significant decrease on involuntary muscle activity during the levodopa challenge test. Both effects were stronger during the levodopa challenge test compared to that of patients' personal medication. There were no significant changes in the parametric approach for EMG and kinematic signals during the measurement. The results show that a wireless and wearable measurement and analysis can be used to study the effect of levodopa medication in advanced Parkinson's disease.Peer reviewe

Signal features of surface electromyography in advanced Parkinson's disease during different settings of deep brain stimulation

Objective: Electromyography (EMG) and acceleration (ACC) measurements are potential methods for quantifying efficacy of deep brain stimulation (DBS) treatment in Parkinson's disease (PD). The treatment efficacy depends on the settings of DBS parameters (pulse amplitude, frequency and width). This study quantified, if EMG and ACC signal features differ between different DBS settings and if DBS effect is unequal between different muscles. Methods: EMGs were measured from biceps brachii (BB) and tibialis anterior (TA) muscles of 13 PD patients. ACCs were measured from wrists. Measurements were performed during seven different settings of DBS and analyzed using methods based on spectral analysis, signal morphology and nonlinear dynamics. Results: The results showed significant within-subject differences in the EMG signal kurtosis, correlation dimension, recurrence rate and EMG-ACC coherence between different DBS settings for BB but not for TA muscles. Correlations between EMG feature values and clinical rest tremor and rigidity scores were weak but significant. Conclusions: Surface EMG features differed between different DBS settings and DBS effect was unequal between upper and lower limb muscles. Significance: EMG changes pointed to previously defined optimal settings in most of patients, which should be quantified even more deeply in the upcoming studies. (C) 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.Peer reviewe

Changes in elbow flexion EMG morphology during adjustment of deep brain stimulator in advanced Parkinson's disease

Publisher Copyright: © 2022 Ruonala et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Objective Deep brain stimulation (DBS) is an effective treatment for motor symptoms of advanced Parkinson's disease (PD). Currently, DBS programming outcome is based on a clinical assessment. In an optimal situation, an objectively measurable feature would assist the operator to select the appropriate settings for DBS. Surface electromyographic (EMG) measurements have been used to characterise the motor symptoms of PD with good results; with proper methodology, these measurements could be used as an aid to program DBS. Methods Muscle activation measurements were performed for 13 patients who had advanced PD and were treated with DBS. The DBS pulse voltage, frequency, and width were changed during the measurements. The measured EMG signals were analysed with parameters that characterise the EMG signal morphology, and the results were compared to the clinical outcome of the adjustment. Results The EMG signal correlation dimension, recurrence rate, and kurtosis changed significantly when the DBS settings were changed. DBS adjustment affected the signal recurrence rate the most. Relative to the optimal settings, increased recurrence rates (median ± IQR) 1.1 ± 0.5 (-0.3 V), 1.3 ± 1.1 (+0.3 V), 1.7 ± 0.4 (-30 Hz), 1.7 ± 0.8 (+30 Hz), 2.0 ± 1.7 (+30 μs), and 1.5 ± 1.1 (DBS off) were observed. With optimal stimulation settings, the patients' Unified Parkinson's Disease Rating Scale motor part (UPDRS-III) score decreased by 35% on average compared to turning the device off. However, the changes in UPRDS-III arm tremor and rigidity scores did not differ significantly in any settings compared to the optimal stimulation settings. Conclusion Adjustment of DBS treatment alters the muscle activation patterns in PD patients. The changes in the muscle activation patterns can be observed with EMG, and the parameters calculated from the signals differ between optimal and non-optimal settings of DBS. This provides a possibility for using the EMG-based measurement to aid the clinicians to adjust the DBS.Peer reviewe

Insulin autoantibodies as determined by competitive radiobinding assay are positively correlated with impaired beta-cell function — The Ulm-Frankfurt population study

Out of a random population of 4208 non-diabetic pupils without a family history of Type I diabetes 44 (1.05%) individuals had islet cell antibody (ICA) levels greater or equal to 5 Juvenile Diabetes Foundation (JDF) units. 39 of these ICA-positives could be repeatedly tested for circulating insulin autoantibodies (CIAA) using a competitive radiobinding assay. The results were compared with the insulin responses in the intravenous glucose tolerance tests (IVGTT) and with HLA types. Six pupils were positive for CIAA. All of them had complement-fixing ICA, and 5 of them were HLA-DR4 positive. Three of the 6 showed a first-phase insulin response below the first percentile of normal controls. Our data indicate that in population-based studies CIAA can be considered as a high risk marker for impaired beta-cell function in non-diabetic ICA-positive individuals