Spin-other-orbit operator in the tensorial form of second quantization

The tensorial form of the spin-other-orbit interaction operator in the formalism of second quantization is presented. Such an expression is needed to calculate both diagonal and off-diagonal matrix elements according to an approach, based on a combination of second quantization in the coupled tensorial form, angular momentum theory in three spaces (orbital, spin and quasispin), and a generalized graphical technique. One of the basic features of this approach is the use of tables of standard quantities, without which the process of obtaining matrix elements of spin-other-orbit interaction operator between any electron configurations is much more complicated. Some special cases are shown for which the tensorial structure of the spin-other-orbit interaction operator reduces to an unusually simple form

Oxygen uptake estimation in humans during exercise using a Hammerstein model

This paper aims to establish a block-structured model to predict oxygen uptake in humans during moderate treadmill exercises. To model the steady state relationship between oxygen uptake (oxygen consumption) and walking speed, six healthy male subjects walked on a motor driven treadmill with constant speed from 2 to 7 km/h. The averaged oxygen uptake at steady state (VO 2) was measured by a mixing chamber based gas analysis and ventilation measurement system (AEI Moxus Metabolic Cart). Based on these reliable date, a nonlinear steady state relationship was successfully established using Support Vector Regression methods. In order to capture the dynamics of oxygen uptake, the treadmill velocity was modulated using a Pseudo Random Binary Signal (PRBS) input. Breath by breath analysis of all subjects was performed. An ARX model was developed to accurately reproduce the measured oxygen uptake dynamics within the aerobic range. Finally, a Hammerstein model was developed, which may be useful for implementing a control system for the regulation of oxygen uptake during treadmill exercises. © 2007 Biomedical Engineering Society

Optimizing heart rate regulation for safe exercise

Safe exercise protocols are critical for effective rehabilitation programs. This paper aims to develop a novel control strategy for an automated treadmill system to reduce the danger of injury during cardiac rehabilitation. We have developed a control-oriented nonparametric Hammerstein model for the control of heart rate during exercises by using support vector regression and correlation analysis. Based on this nonparametric model, a model predictive controller has been built. In order to guarantee the safety of treadmill exercise during rehabilitation, this new automated treadmill system is capable of optimizing system performance over predefined ranges of speed and acceleration. The effectiveness of the proposed approach was demonstrated with six subjects by having their heart rate track successfully a predetermined heart rate. © 2009 Biomedical Engineering Society

Discriminating the origin of fish from closely related water bodies by combining NMR spectroscopy with statistical analysis and machine learning

Pikeperch, perch and bream are among the most traded and valued fish species in North-Eastern Europe. Therefore, it is necessary to be able to distinguish fish from different lakes and coastal sea regions to ensure a good traceability of products in the fish market and to protect both consumers and fish stocks. Untargeted metabolomics using nuclear magnetic resonance (NMR) spectroscopy is a suitable tool for this purpose. It is an established method for determining various properties of biological and living systems, such as health, origin, type, etc. Statistical methods including principal component analysis (PCA) and linear discriminant analysis (LDA) are typically applied to NMR data to correlate spectra with a particular research question. Herein we examine fish from three closely related water bodies and demonstrate that reliable determination of the water body that a particular fish originates from by traditional statistical analysis (PCA and LDA) of fish NMR spectra is not possible. In contrast, determining the fish species is possible. We proceed to show that machine learning methods perform better and that a combination of statistical analysis (LDA) and random forest (RF), a supervised machine learning technique, allows reliable determination of the originating water body, while being also tolerant to seasonal variations. This is an improvement over prior work, which has dealt with more clearly distinguished origins of fish. Exceptional accuracy was achieved in correctly assigning fish to their origin even in a scenario where two of the water bodies are connected by a river through which the fish are known to migrate. Since determining the origin of fish is important in environmental protection, we recommend following up this approach and using it as the basis of a robust tool for environmental protection and other monitoring purposes

Evaluation of cartilage integrity following administration of oral and intraarticular nifedipine in a murine model of osteoarthritis

Abstract Osteoarthritis (OA) ranks as the prevailing type of arthritis on a global scale, for which no effective treatments are currently available. Arterial hypertension is a common comorbidity in OA patients, and antihypertensive drugs, such as nifedipine (NIF), may affect the course of OA progression. The aim of this preclinical study was to determine the effect of nifedipine on healthy and OA cartilage, depending on its route of administration. In this study, we used the destabilization of medial meniscus to develop a mouse model of OA. Nifedipine was applied per os or intraarticularly (i.a.) for 8 weeks to both mice with OA and healthy animals. Serum biomarker concentrations were evaluated using the Luminex platform and alterations in the knee cartilage were graded according to OARSI histological scores and investigated immunohistochemically. Nifedipine treatment per os and i.a. exerted protective effects, as assessed by the OARSI histological scores. However, long-term nifedipine i.a. injections induced the deterioration of healthy cartilage. Lubricin, cartilage intermediate layer matrix protein (CILP), collagen type VI (COLVI), CILP, and Ki67 were upregulated by the nifedipine treatment. Serum biomarkers MMP-3, thrombospondin-4, and leptin were upregulated in the healthy groups treated with nifedipine, while only the levels of MMP-3 were significantly higher in the OA group treated with nifedipine per os compared to the untreated group. In conclusion, this study highlights the differential effects of nifedipine on cartilage integrity, depending on the route of administration and cartilage condition