Synchrotron radiation sources INDUS-1 and INDUS-2

The synchrotron radiation sources, INDUS-1 and INDUS-2 are electron storage rings of 450 MeV and 2 GeV beam energies respectively. INDUS-1 is designed to produce VUV radiation whereas INDUS-2 will be mainly used to produce x-rays. INDUS-1 is presently undergoing commissioning whereas INDUS-2 is under construction. Both these rings have a common injector system comprising of a microtron and a synchrotron. Basic design features of these sources and their injector system are discussed in this paper. The radiation beamlines to be set up on these sources are also described

Nanocrystalline Zr3Al Made through Amorphization by Repeated Cold Rolling and Followed by Crystallization

The intermetallic compound Zr3Al is severely deformed by the method of repeated cold rolling. By X-ray diffraction it is shown that this leads to amorphization. TEM investigations reveal that a homogeneously distributed debris of very small nanocrystals is present in the amorphous matrix that is not resolved by X-ray diffraction. After heating to 773 K, the crystallization of the amorphous structure leads to a fully nanocrystalline structure of small grains (10 - 20 nm in diameter) of the non-equilibrium Zr2Al phase. It is concluded that the debris retained in the amorphous phase acts as nuclei. After heating to 973 K the grains grow to about 100 nm in diameter and the compound Zr3Al starts to form, that is corresponding to the alloy composition

Quality Control of Motor Unit Number Index (MUNIX) Measurements in 6 Muscles in a Single-Subject “Round-Robin” Setup

Background Motor Unit Number Index (MUNIX) is a neurophysiological measure that provides an index of the number of lower motor neurons in a muscle. Its performance across centres in healthy subjects and patients with Amyotrophic Lateral Sclerosis (ALS) has been established, but inter-rater variability between multiple raters in one single subject has not been investigated. Objective To assess reliability in a set of 6 muscles in a single subject among 12 examiners (6 experienced with MUNIX, 6 less experienced) and to determine variables associated with variability of measurements. Methods Twelve raters applied MUNIX in six different muscles (abductor pollicis brevis (APB), abductor digiti minimi (ADM), biceps brachii (BB), tibialis anterior (TA), extensor dig. brevis (EDB), abductor hallucis (AH)) twice in one single volunteer on consecutive days. All raters visited at least one training course prior to measurements. Intra- and inter-rater variability as determined by the coefficient of variation (COV) between different raters and their levels of experience with MUNIX were compared. Results Mean intra-rater COV of MUNIX was 14.0% (±6.4) ranging from 5.8 (APB) to 30.3% (EDB). Mean inter-rater COV was 18.1 (±5.4) ranging from 8.0 (BB) to 31.7 (AH). No significant differences of variability between experienced and less experienced raters were detected. Conclusion We provide evidence that quality control for neurophysiological methods can be performed with similar standards as in laboratory medicine. Intra- and inter-rater variability of MUNIX is muscle-dependent and mainly below 20%. Experienced neurophysiologists can easily adopt MUNIX and adequate teaching ensures reliable utilization of this method

D-4F, an apoA-1 mimetic, decreases airway hyperresponsiveness, inflammation, and oxidative stress in a murine model of asthma

Asthma is characterized by oxidative stress and inflammation of the airways. Although proinflammatory lipids are involved in asthma, therapies targeting them remain lacking. Ac-DWFKAFYDKVAEKFKEAFNH2 (4F) is an apolipoprotein (apo)A-I mimetic that has been shown to preferentially bind oxidized lipids and improve HDL function. The objective of the present study was to determine the effects of 4F on oxidative stress, inflammation, and airway resistance in an established murine model of asthma. We show here that ovalbumin (OVA) -sensitization increased airway hyperresponsiveness, eosinophil recruitment, and collagen deposition in lungs of C57BL/6J mice by a mechanism that could be reduced by 4F. OVA sensitization induced marked increases in transforming growth factor (TGF)β-1, fibroblast specific protein (FSP)-1, anti-T15 autoantibody staining, and modest increases in 4-hydroxynonenal (4-HNE) Michael\u27s adducts in lungs of OVA-sensitized mice. 4F decreased TGFβ-1, FSP-1, anti-T15 autoantibody, and 4-HNE adducts in the lungs of the OVA-sensitized mice. Eosinophil peroxidase (EPO) activity in bronchial alveolar lavage fluid (BALF), peripheral eosinophil counts, total IgE, and proinflammatory HDL (p-HDL) were all increased in OVA-sensitized mice. 4F decreased BALF EPO activity, eosinophil counts, total IgE, and p-HDL in these mice. These data indicate that 4F reduces pulmonary inflammation and airway resistance in an experimental murine model of asthma by decreasing oxidative stress

Energetics and atomic mechanisms of dislocation nucleation in strained epitaxial layers

We study numerically the energetics and atomic mechanisms of misfit dislocation nucleation and stress relaxation in a two-dimensional atomistic model of strained epitaxial layers on a substrate with lattice misfit. Relaxation processes from coherent to incoherent states for different transition paths are studied using interatomic potentials of Lennard-Jones type and a systematic saddle point and transition path search method. The method is based on a combination of repulsive potential minimization and the Nudged Elastic Band method. For a final state with a single misfit dislocation, the minimum energy path and the corresponding activation barrier are obtained for different misfits and interatomic potentials. We find that the energy barrier decreases strongly with misfit. In contrast to continuous elastic theory, a strong tensile-compressive asymmetry is observed. This asymmetry can be understood as manifestation of asymmetry between repulsive and attractive branches of pair potential and it is found to depend sensitively on the form of the potential.Comment: 11 pages, 9 figures, to appear in Phys. Rev.

Head-down tilt bed rest with or without artificial gravity is not associated with motor unit remodeling

© 2020, The Author(s). Purpose: The objective of this study was to assess whether artificial gravity attenuates any long-duration head-down 60 bed rest (HDBR)-induced alterations in motor unit (MU) properties. Methods: Twenty-four healthy participants (16 men; 8 women; 26–54 years) underwent 60-day HDBR with (n = 16) or without (n = 8) 30 min artificial gravity daily induced by whole-body centrifugation. Compound muscle action potential (CMAP), MU number (MUNIX) and MU size (MUSIX) were estimated using the method of Motor Unit Number Index in the Abductor digiti minimi and tibialis anterior muscles 5 days before (BDC-5), and during day 4 (HDT4) and 59 (HDT59) of HDBR. Results: The CMAP, MUNIX, and MUSIX at baseline did not change significantly in either muscle, irrespective of the intervention (p > 0.05). Across groups, there were no significant differences in any variable during HDBR, compared to BDC-5. Conclusion: Sixty days of HDBR with or without artificial gravity does not induce alterations in motor unit number and size in the ADM or TA muscles in healthy individuals

Behaviour of motor unit action potential rate, estimated from surface EMG, as a measure of muscle activation level

BACKGROUND: Surface electromyography (EMG) parameters such as root-mean-square value (RMS) are commonly used to assess the muscle activation level that is imposed by the central nervous system (CNS). However, RMS is influenced not only by motor control aspects, but also by peripheral properties of the muscle and recording setup. To assess motor control separately, the number of motor unit action potentials (MUAPs) per second, or MUAP Rate (MR) is a potentially useful measure. MR is the sum of the firing rates of the contributing MUs and as such reflects the two parameters that the CNS uses for motor control: number of MUs and firing rate. MR can be estimated from multi-channel surface EMG recordings. The objective of this study was to explore the behaviour of estimated MR (eMR) in relation to number of active MUs and firing rate. Furthermore, the influence of parameters related to peripheral muscle properties and recording setup (number of fibers per MU, fiber diameter, thickness of the subcutaneous layer, signal-to-noise-ratio) on eMR was compared with their influence on RMS. METHODS: Physiological parameters were varied in a simulation model that generated multi-channel EMG signals. The behaviour of eMR in simulated conditions was compared with its behaviour in experimental conditions. Experimental data was obtained from the upper trapezius muscle during a shoulder elevation task (20–100 N). RESULTS: The simulations showed strong, monotonously increasing relations between eMR and number of active MUs and firing rate (r(2 )> 0.95). Because of unrecognized superimpositions of MUAPs, eMR was substantially lower than the actual MUAP Rate (aMR). The percentage of detected MUAPs decreased with aMR, but the relation between eMR and aMR was rather stable in all simulated conditions. In contrast to RMS, eMR was not affected by number of fibers per MU, fiber diameter and thickness of the subcutaneous layer. Experimental data showed a strong relation between eMR and force (individual second order polynomial regression: 0.96 < r(2 )< 0.99). CONCLUSION: Although the actual number of MUAPs in the signal cannot be accurately extracted with the present method, the stability of the relation between eMR and aMR and its independence of muscle properties make eMR a suitable parameter to assess the input from the CNS to the muscle at low contraction levels non-invasively

Fuzzy min-max neural networks for categorical data: application to missing data imputation

The fuzzy min–max neural network classifier is a supervised learning method. This classifier takes the hybrid neural networks and fuzzy systems approach. All input variables in the network are required to correspond to continuously valued variables, and this can be a significant constraint in many real-world situations where there are not only quantitative but also categorical data. The usual way of dealing with this type of variables is to replace the categorical by numerical values and treat them as if they were continuously valued. But this method, implicitly defines a possibly unsuitable metric for the categories. A number of different procedures have been proposed to tackle the problem. In this article, we present a new method. The procedure extends the fuzzy min–max neural network input to categorical variables by introducing new fuzzy sets, a new operation, and a new architecture. This provides for greater flexibility and wider application. The proposed method is then applied to missing data imputation in voting intention polls. The micro data—the set of the respondents’ individual answers to the questions—of this type of poll are especially suited for evaluating the method since they include a large number of numerical and categorical attributes

Techniques of EMG signal analysis: detection, processing, classification and applications

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications