On the Use of Artificial Intelligence to Define Tank Transfer Functions

Experimental test facilities are generally characterised using linear transfer functions to relate the wavemaker forcing amplitude to wave elevation at a probe located in the wavetank. Second and third order correction methods are becoming available but are limited to certain ranges of waves in their applicability. Artificial intelligence has been shown to be a suitable tool to find even highly nonlinear functional relationships. This paper reports on a numerical wavetank implemented using the OpenFOAM software package which is characterised using artificial intelligence. The aim of the research is to train neural networks to represent non-linear transfer functions mapping a desired surface-elevation time-trace at a probe to the wavemaker input required to create it. These first results already demonstrate the viability of the approach and the suitability of a single setup to find solutions over a wide range of sea states and wave characteristics.

Electrochemical quantification of accelerated FADGDH rates in aqueous nanodroplets

Enzymes are molecules that catalyze reactions critical to life. These catalysts are often studied in bulk water, where the influence of water volume on reactivity is neglected. Here, we demonstrate rate enhancement of up to two orders of magnitude for enzymes trapped in submicrometer water nanodroplets suspended in 1,2-dichloroethane. When single nanodroplets irreversibly adsorb onto an ultramicroelectrode surface, enzymatic activity is apparent in the amperometric current-time trace if the ultramicroelectrode generates the enzyme cofactor. Nanodroplet volume is easily accessible by integrating the current-time response and using Faraday’s Law. The single nanodroplet technique allows us to plot the enzyme’s activity as a function of nanodroplet size, revealing a strong inverse relationship. Finite element simulations confirm our experimental results and offer insights into parameters influencing single nanodroplet enzymology. These results provide a framework to profoundly influence the understanding of chemical reactivity at the nanoscale.

Cooperation of small rural commodity producers in post-reform Russia: factors and conditions

In this article, the authors, based on the principles of historicism and objectivity, using the statistical method and a systematic approach, analyzed the first steps in the development of cooperative societies in the rural environment using the example of the Volga region provinces. The factors and conditions were identified, the totality of which influenced the rate of spread and development of cooperative forms of management in the peasant environment during the post-reform period. This is, firstly, the urgent economic need for the peasant in inexpensive credit: the lack of financial resources forced them to borrow from usurers at a high interest rate; secondly, the efforts of representatives of the aristocracy, intelligentsia and zemstvos to draw attention to this problem, to promote and demonstrate the first experiences of cooperative work; thirdly, the actions of the state to create and develop cooperative legislation. The authors analyze examples of cooperative endeavors that were initiated by the most enlightened people of their time; trace the activities of the zemstvo in the dissemination of cooperative ideas in the peasant environment, the promotion of cooperative knowledge, assistance in opening cooperative partnerships and the provision of initial loans to peasants by rural credit and savings and loan associations; state measures at the legislative level to activate peasant self-help. The analysis of all the above factors in the development of cooperative societies in the peasant environment allowed the authors, following the ups and downs of the processes described, to draw a conclusion about their interaction and influence on the development of the cooperative movement in Russia. In zemstvo and state circles, an understanding has been formed that without the inclusion of peasants in a market economy, it is impossible to develop the infrastructure of the agricultural sector. At the same time, the authors are convinced that without the gradually emerging objective conditions, all these efforts would hardly have been justified.

Application of Floquet Theory to Human Gait Kinematics and Dynamics

In this work, the lower extremity physiological parameters are recorded during normal walking gait, and the dynamical systems theory is applied towards its stability analysis. The human walking gait pattern of kinematic and dynamical data is approximated to periodic behavior. The embedding dimension analysis of the kinematic variable's time trace and use of Taken's theorem allows us to compute a reduced-order time series that retains the essential dynamics. In conjunction with Floquet Theory, this approach can help study the system's stability characteristics. The Lyapunov-Floquet (L-F) Transformation application results in constructing an invariant manifold resembling the form of a simple oscillator system. It is also demonstrated that the simple oscillator system, when re-mapped back to the original domain, reproduces the original system's time evolution (hip angle or knee angle, for example). A re-initialization procedure is suggested that improves the accuracy between the processed data and actual data. The theoretical framework proposed in this work is validated with the experiments using a motion capture system.

Estimation of Synaptic Activity during Neuronal Oscillations

In the study of brain connectivity, an accessible and convenient way to unveil local functional structures is to infer the time trace of synaptic conductances received by a neuron by using exclusively information about its membrane potential (or voltage). Mathematically speaking, it constitutes a challenging inverse problem: it consists in inferring time-dependent parameters (synaptic conductances) departing from the solutions of a dynamical system that models the neuron’s membrane voltage. Several solutions have been proposed to perform these estimations when the neuron fluctuates mildly within the subthreshold regime, but very few methods exist for the spiking regime as large amplitude oscillations (revealing the activation of complex nonlinear dynamics) hinder the adaptability of subthreshold-based computational strategies (mostly linear). In a previous work, we presented a mathematical proof-of-concept that exploits the analytical knowledge of the period function of the model. Inspired by the relevance of the period function, in this paper we generalize it by providing a computational strategy that can potentially adapt to a variety of models as well as to experimental data. We base our proposal on the frequency versus synaptic conductance curve (f−gsyn), derived from an analytical study of a base model, to infer the actual synaptic conductance from the interspike intervals of the recorded voltage trace. Our results show that, when the conductances do not change abruptly on a time-scale smaller than the mean interspike interval, the time course of the synaptic conductances is well estimated. When no base model can be cast to the data, our strategy can be applied provided that a suitable f−gsyn table can be experimentally constructed. Altogether, this work opens new avenues to unveil local brain connectivity in spiking (nonlinear) regimes.

The Problem of Personal Identity in the Context of the Integrative Approach

This article analyses some categorical and methodological aspects of the problem of identity in the contemporary discourse of the humanities. The paper is relevant, on the one hand, due to the extreme heuristic significance of the concept of identity for studying various aspects of variability and stability in the development of sociocultural subjects and, on the other hand, due to numerous disputes over the essence of this construct and the limits of its application. The integral nature of the phenomenon of identity leads to the need to develop a methodological and conceptual apparatus that would provide a productive version of interdisciplinary interaction, a synthesis of psychological, cultural and historical approaches. Having scrutinized a number of modern psychological and cultural approaches to studying personal identity, the authors conclude that contemporary research on the problem of identity follows the trend of the integrative, systems analysis. The integrative analysis allows us to create a complete picture of the process of self-identification and at the same time trace in detail and describe its individual aspects. The combination of the axiological and the activity concepts of culture within the framework of the synthetic approach allows us to formulate a definition of identity as a sociocultural and social group integration, which forms an individual’s sociocultural subjectivity. The concept of identity as a synthetic theoretical and methodological construct maintains the focus of research attention on the fundamental and irremovable integration of a person into the cultural space, while allowing other options and methods for such an entry. The proposed concept of personal identity in the integrative version is considered as a kind of synthetic methodology, which is a productive way of developing an identity theory and can become a prerequisite for overcoming an identity crisis in cognitive and value aspects.