Complex Electromechanical Process Research Articles

Murburn concept in cellular function and bioenergetics, Part 1: Understanding murzymes at the molecular level

Bioenergetics is the study of how life-activities are powered within the cell. This also deals with the interactive exchange of matter/radiation between cellular components and their environment, and the accompanying changes thereof. The acclaimed bioenergetics paradigm has relied on “electron transport chains” and selective/stoichiometric electrogenic “ion-pumping” mediated by vectorial protein-embedded membranes. Therein, an electrochemical gradient was deemed to be the driving force for chemical reactions leading to ATP production, physical thermogenesis by uncoupling proteins, and complex electromechanical processes like information relay along the axon. On one hand, this vitally deterministic perception requires the membrane proteins to “intelligently” manipulate ion-fluxes and generate/harness an electrochemical gradient by a gambit-type logic. At the other hand, it also seeks that the same gradient should cyclically control the membrane-proteins’ activity. Our recent pursuits have questioned such traditional perspectives and advocated the alternate explanation of murburn concept, leading to a revamping of the macroscopic treatments of overall thermodynamic, kinetic, mechanistic, and evolutionary (probability) considerations. The current review aims to consolidate the murburn paradigm of bioenergetics, wherein murzymes initiate redox processes by effective charge separation and diffusible reactive species formation, enabling cells to work as simple chemical engines. Herein, we discuss the reaction chemistry of some simple enzyme systems and also delve into protein complex arrays mediated powering routines like mitochondrial respiration-thermogenesis and chloroplast-centered photosynthesis. Furthermore, we remark that the “water–ion–molecules” phase continuum is actually discretized into dynamically fluctuating coacervates and express concern over the marginalization of sound chemico-physical ideas by the bioenergetics community.

A Unifying Framework Underlying Mechanotransduction in the Somatosensory System

Rodents use their whiskers to sense their surroundings. As most of the information available to the somatosensory system originates in whiskers' primary afferents, it is essential to understand the transformation of whisker motion into neuronal activity. Here, we combined in vivo recordings in anesthetized rats with mathematical modeling to ascertain the mechanical and electrical characteristics of mechanotransduction. We found that only two synergistic processes, which reflect the dynamic interactions between (1) receptor and whisker and (2) receptor and surrounding tissue, are needed to describe mechanotransduction during passive whiskers deflection. Interactions between these processes may account for stimulus-dependent changes in the magnitude and temporal pattern of tactile responses on multiple scales. Thus, we are able to explain complex electromechanical processes underlying sensory transduction using a simple model, which captures the responses of a wide range of mechanoreceptor types to diverse sensory stimuli. This compact and precise model allows for a ubiquitous description of how mechanoreceptors encode tactile stimulus.

Networked sensing for high-speed machining processes based on CORBA

The goal of this paper is to show preliminary results concerning the development of an open software platform supported by portable, low-cost technologies accepted worldwide (i.e., real-time CORBA), aiming at networked monitoring of a complex electromechanical process. A high-speed machining process was selected as a case study. Preliminary results in the networked real-time monitoring of a high-speed machining process were encouraging in spite of constraints dictated by computerized numerical control. The results also corroborated the viability of the platform for monitoring on the basis of current communications and computation technologies using open architectures.

Controlling a complex electromechanical process on the basis of a neurofuzzy approach

This paper shows the viability of implementing a control strategy based on the internal-model control paradigm, which is a useful synergy of a dynamic ANN trained from real-life data and used to predict process output and a fuzzy-logic control (FLC) that enhances the control system's overall performance. A force control problem involving a complex electromechanical system, represented here by the machining process, is considered as a case study. The main goal is to control a single-output variable, cutting force, by changing a single-input variable, feed rate. The proposed neurofuzzy-control (NFC) scheme consists of a dynamic model using ANNs to estimate process output, and a fuzzy-logic controller (FLC) with the same static gain as the inverse model to determine the control inputs (feed rate) necessary to keep the cutting force constant. Four approaches, the fuzzy-logic controller (FLC), the direct inverse controller based on ANNs (DIC-NN), the internal-model controller (IMC-NN) and a neurofuzzy controller (NFC), are simulated and their performances are assessed in terms of several performance measurements. The results demonstrate that the NFC strategy provides better disturbance rejection than the IMC-NN and the FLC for the cases analyzed.