A manipulator size optimization method based on dexterous workspace volume

Background: Manipulators for robots are required to have high manipulability for adaptability in different tasks. However, general methods for designing manipulators with high manipulability are deficient. Here, aiming at improving the manipulability of the six degrees-of-freedom (DOF) manipulator, a method for optimizing structure size parameters based on the dexterous workspace volume is proposed. Methods: Firstly, the kinematic analysis of the manipulator is performed. Then, the manipulability of the single working point of the manipulator is judged based on reachability in different postures. The workspace of the manipulator is discretized to obtain the volume of the overall dexterous workspace. By taking the maximum volume of the dexterous workspace as the optimization goal, Genetic Algorithm (GA) is used to optimize the structure size parameters to achieve optimal manipulability. AUBO 6-DOF manipulator is defined and analyzed as an example. Results: The optimization results indicate that the dexterous workspace of the manipulator expands in volume and its manipulability is improved. The validity of the proposed optimization method is verified by comparing the distribution of dexterous workspace of the manipulator. Conclusions: This article proposes an optimization method for the structure size parameters of a 6-DOF manipulator, which can be implemented to improving the manipulability of the manipulator.

Cardiovagal Baroreflex Hysteresis Using Ellipses in Response to Postural Changes

The cardiovagal branch of the baroreflex is of high clinical relevance when detecting disturbances of the autonomic nervous system. The hysteresis of the baroreflex is assessed using provoked and spontaneous changes in blood pressure. We propose a novel ellipse analysis to characterize hysteresis of the spontaneous respiration-related cardiovagal baroreflex for orthostatic test. Up and down sequences of pressure changes as well as the working point of baroreflex are considered. The EuroBaVar data set for supine and standing was employed to extract heartbeat intervals and blood pressure values. The latter values formed polygons into which a bivariate normal distribution was fitted with its properties determining proposed ellipses of baroreflex. More than 80% of ellipses are formed out of nonoverlapping and delayed up and down sequences highlighting baroreflex hysteresis. In the supine position, the ellipses are more elongated (by about 46%) and steeper (by about 4.3° as median) than standing, indicating larger heart interval variability (70.7 versus 47.9 ms) and smaller blood pressure variability (5.8 versus 8.9 mmHg) in supine. The ellipses show a higher baroreflex sensitivity for supine (15.7 ms/mmHg as median) than standing (7 ms/mmHg). The center of the ellipse moves from supine to standing, which describes the overall sigmoid shape of the baroreflex with the moving working point. In contrast to regression analysis, the proposed method considers gain and set-point changes during respiration, offers instructive insights into the resulting hysteresis of the spontaneous cardiovagal baroreflex with respiration as stimuli, and provides a new tool for its future analysis.

How synchrony and metastable network dynamics are affected in fast and slow timescales with aging: Implication for Cognition

Both healthy and pathological aging exhibits gradual deterioration of structure but interestingly in healthy aging adults often maintains a high level of cognitive performance in a variety of cognitively demanding task till late age. What are the relevant network measures that could possibly track these dynamic changes which may be critically relevant for maintenance of cognitive functions through lifespan and how does these measures affected by the specific alterations in underlying anatomical connectivity till day remains an open question. In this work, we propose that whole-brain computational models are required to test the hypothesis that aging affects the brain network dynamics through two highly relevant network measures synchrony and metastability. Since aging entails complex processes involving multiple timescales we test the additional hypothesis that whether these two network measures remain invariant or exhibit different behavior in the fast and slow timescales respectively. The altered global synchrony and metastability with aging can be related to shifts in the dynamic working point of the system based on biophysical parameters e.g., time delay, and inter-areal coupling constrained by the underlying structural connectivity matrix.Using diffusion tensor imaging (DTI) data, we estimate structural connectivity (SC) of individual group of participants and obtain network level synchrony, metastability indexing network dynamics from resting state functional MRI data for both young and elderly participants in the age range of 18-89 years. Subsequently, we simulate a whole-brain Kuramoto model of coupled oscillators with appropriate conduction delay and interareal coupling strength to test the hypothesis of shifting of dynamic working point with age-associated alteration in network dynamics in both neural and ultraslow BOLD signal time scales. Specifically, we investigate the age-associated difference in metastable brain dynamics across large-scale neurocognitive brain networks e.g., salience network (SN), default mode network (DMN), and central executive network (CEN) to test spatio-temporal changes in default to executive coupling hypothesis with age. Interestingly, we find that the metastability of the SN increases substantially with age, whereas the metastability of the CEN and DMN networks do not substantially vary with age suggesting a clear role of conduction delay and global coupling in mediating altered dynamics in these networks. Moreover, our finding suggests that the metastability changes from slow to fast timescales confirming previous findings that variability of brain signals relates differently in slower and faster time scales with aging. However, synchrony remains invariant network measure across timescales and agnostic to the filtering of fast signals. Finally, we demonstrate both numerically and analytically long-range anatomical connections as oppose to shot-range or mid-range connection alterations is responsible for the overall neural difference in large-scale brain network dynamics captured by the network measure metastability. In summary, we propose a theoretical framework providing a systematic account of tracking age-associated variability and synchrony at multiple time scales across lifespan which may pave the way for developing dynamical theories of cognitive aging.

PARAMETRIC SYNTHESIS OF A MOVING OBJECT STABILIZER

The problem of choosing the variable parameters of a stabilizer of an object which minimize an additive quadratic integral functional reflecting the complex of requirements for a closed stabilization system is considered. To solve the problem a combined method of parametric synthesis of the stabilizer, which is a sequential combination of the Sobol grid method and the Nelder-Mead method, is proposed. At the first stage of the method by applying the Sobolev grid method a working point of the closed system in the pace of its variable parameters is transferred into a neighborhood of the quality functional global minimum point. Then at the second stage the Nelder-Mead method is used to relocated the working point into a small neighborhood of the global minimum. The method proposed comprises a particular algorithm for choosing the weight coefficient of the additive quality functional as well as makes use of the stabilization object state vector main coordinates, which provide the most adequate description of its dynamic features. The properties of a mathematical model of controlled system with discontinuous stabilization process control are studied numerically. The analysis of the plots in the dynamical system state phase space indicates non-spiral approach of the system to its equilibrium state. The synthesized control is realized in the form of a sequence of switchovers.

Methodology for criteria-based assessment of energy efficiency of main pipeline pumps

В настоящее время об энергоэффективности насосного агрегата судят на основании результатов приемо-сдаточных испытаний - по значению КПД в номинальной рабочей точке. Опыт эксплуатации насосов на объектах нефтепроводного транспорта показывает, что реальная рабочая точка насоса отличается от номинальной. Данное расхождение объясняется вариативностью режимов работы насосных установок. В этой связи предлагается оценивать энергоэффективность насоса по результатам испытаний исходя из реальных условий функционирования насосного оборудования - в рабочем диапазоне, необходимом для перекачки нефти (нефтепродуктов) с учетом изменения потребной подачи и напора гидросистемы. Существующие методики оценки энергоэффективности насосов в рабочем диапазоне имеют ограничения для применения на объектах магистральных нефтепроводов. В настоящей работе предлагается использовать с этой целью критериальную оценку по характерным точкам в диапазоне подач. Сформулированы основные положения разработанной методики. Сделан вывод о том, что ее применение при приемо-сдаточных испытаниях позволит улучшить качество оборудования, поставляемого на производственные объекты, а следовательно, энергоэффективность НПС. Currently, energy efficiency of a pumping unit is assessed based on the acceptance test results according to the efficiency value at the nominal working point. The experience of operating pumps at oil pipeline transportation facilities shows that the actual working point of the pump differs from the nominal one. This discrepancy is explained by the variability of the pumping unit process modes. In this connection, it is proposed to evaluate pump’s energy efficiency based on the test results under the actual operating conditions of the pumping equipment, in the operating range required for pumping oil (petroleum products), taking into account the change in the required supply and hydraulic system pressure. The existing methods for assessing energy efficiency of pumps in the operating range have limitations for use at main oil pipeline facilities. This study proposes to use a criteria-based assessment using characteristic points in the supply range for this purpose. The basic principles of the developed method are formulated. It is concluded that its application during the acceptance tests will improve the quality of equipment supplied to production facilities, and hence the PS energy efficiency.

MR. Estimator, a toolbox to determine intrinsic timescales from subsampled spiking activity

Here we present our Python toolbox “MR. Estimator” to reliably estimate the intrinsic timescale from electrophysiologal recordings of heavily subsampled systems. Originally intended for the analysis of time series from neuronal spiking activity, our toolbox is applicable to a wide range of systems where subsampling—the difficulty to observe the whole system in full detail—limits our capability to record. Applications range from epidemic spreading to any system that can be represented by an autoregressive process. In the context of neuroscience, the intrinsic timescale can be thought of as the duration over which any perturbation reverberates within the network; it has been used as a key observable to investigate a functional hierarchy across the primate cortex and serves as a measure of working memory. It is also a proxy for the distance to criticality and quantifies a system’s dynamic working point.