EPR Signals in Melanoprotein Fiber at Low Temperature and under the Influence of Ionizing Radiation

In this paper we studied the EPR signals in the melanoprotein fiber at a temperature of T = 77K and as a result of the exposure to ionizing radiation. These EPR signals are associated with paramagnetic centers localized in the structure of α-keratin, and their intensity increases upon irradiation

DEPENDENCE OF THE CHARACTERISTICS OF THE RADIATION-INDUCED EPR SIGNAL OF ARTIFICIAL HYDROXYAPATITE ON THE SYNTHESIS CONDITIONS

In this work, we studied the effect of synthesis conditions (pH) and annealing of artificial HA samples on the sensitivity to IR irradiation. It is shown that the most promising synthesis conditions for dosimetric studies of artificial HA are solution pH 8.6 and subsequent annealing at Т = 700°С.The work was partially supported by the Ministry of Science and Higher Education of the Russian Federation (through the basic part of the government mandate, project No. FEUZ-2023-0013).Работа выполнена при частичной финансовой поддержке Министерства науки и высшего образования РФ (базовая часть государственного задания, проект № FEUZ-2023-0013)

Computationally-Optimized Bone Mechanical Modeling from High-Resolution Structural Images

Image-based mechanical modeling of the complex micro-structure of human bone has shown promise as a non-invasive method for characterizing bone strength and fracture risk in vivo. In particular, elastic moduli obtained from image-derived micro-finite element (μFE) simulations have been shown to correlate well with results obtained by mechanical testing of cadaveric bone. However, most existing large-scale finite-element simulation programs require significant computing resources, which hamper their use in common laboratory and clinical environments. In this work, we theoretically derive and computationally evaluate the resources needed to perform such simulations (in terms of computer memory and computation time), which are dependent on the number of finite elements in the image-derived bone model. A detailed description of our approach is provided, which is specifically optimized for μFE modeling of the complex three-dimensional architecture of trabecular bone. Our implementation includes domain decomposition for parallel computing, a novel stopping criterion, and a system for speeding up convergence by pre-iterating on coarser grids. The performance of the system is demonstrated on a dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM. Models of distal tibia derived from 3D in-vivo MR images in a patient comprising 200,000 elements required less than 30 seconds to converge (and 40 MB RAM). To illustrate the system's potential for large-scale μFE simulations, axial stiffness was estimated from high-resolution micro-CT images of a voxel array of 90 million elements comprising the human proximal femur in seven hours CPU time. In conclusion, the system described should enable image-based finite-element bone simulations in practical computation times on high-end desktop computers with applications to laboratory studies and clinical imaging

Design Issues for MEMS-Based Pedestrian Inertial Navigation Systems

The paper describes design issues for MEMS-based pedestrian inertial navigation systems. By now the algorithms to estimate navigation parameters for strap-down inertial navigation systems on the basis of plural observations have been already well developed. At the same time mathematical and software processing of information in the case of pedestrian inertial navigation systems has its specificity, due to the peculiarities of their functioning and exploitation. Therefore, there is an urgent task to enhance existing fusion algorithms for use in pedestrian navigation systems. For this purpose the article analyzes the characteristics of the hardware composition and configuration of existing systems of this class. The paper shows advantages of various technical solutions. Relying on their main features it justifies a choice of the navigation system architecture and hardware composition enabling improvement of the estimation accuracy of user position as compared to the systems using only inertial sensors. The next point concerns the development of algorithms for complex processing of heterogeneous information. To increase an accuracy of the free running pedestrian inertial navigation system we propose an adaptive algorithm for joint processing of heterogeneous information based on the fusion of inertial info rmation with magnetometer measurements using EKF approach. Modeling of the algorithm was carried out using a specially developed functional prototype of pedestrian inertial navigation system, implemented as a hardware/software complex in Matlab environment. The functional prototype tests of the developed system demonstrated an improvement of the navigation parameters estimation compared to the systems based on inertial sensors only. It enables to draw a conclusion that the synthesized algorithm provides satisfactory accuracy for calculating the trajectory of motion even when using low-grade inertial MEMS sensors. The developed algorithm can be implemented in the individual navigation equipment designed to solve practical tasks requiring autonomous positioning