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Biomimetics
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Editorial Board Members’ Collection Series: Bioinspired Sensorics, Information Processing and...
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Editorial Board Members’ Collection Series: Bioinspired Sensorics, Information Processing and Control

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Bioinspired Sensorics, Information Processing and Control".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 21426

Special Issue Editors

Prof. Andrew Adamatzky

E-Mail Website
Guest Editor
Unconventional Computing Lab, Department of Computer Science and Creative Technology, University of the West of England, Bristol BS16 1QY, UK
Interests: unconventional computing; fungal computing; reaction-diffusion computing; cellular automata; physarum computing; massive parallel computation; applied mathematics; collective intelligence and robotics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Marc Weissburg

E-Mail Website
Guest Editor
Brook Byers Professor of Sustainability and Co-Director of the Center of Biologically Inspired Design, School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
Interests: chemical ecology; sensory ecology; community ecology; biologically inspired design

Special Issue Information

Dear Colleagues,

We are pleased to announce a new Special Issue collection titled “Editorial Board Members' Collection Series: Bioinspired Sensorics, Information Processing and Control”, which will collect papers invited by the Editorial Board Members.

The aim of this collection is to provide a venue for networking and communication between Biomimetics and scholars in the field of bioinspired sensorics, information processing and control. All papers will be published in open-access format following peer review.

Prof. Dr. Andrew Adamatzky
Prof. Dr. Marc Weissburg
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomimetics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

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Research

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12 pages, 2127 KiB  
Article
Structural Transitions of Papain-like Cysteine Proteases: Implications for Sensor Development
by Srdjan Marković, Natalija S. Andrejević, Jelica Milošević and Natalija Đ. Polović
Biomimetics 2023, 8(3), 281; https://doi.org/10.3390/biomimetics8030281 - 1 Jul 2023
Cited by 1 | Viewed by 2079
Abstract
The significant role of papain-like cysteine proteases, including papain, cathepsin L and SARS-CoV-2 PLpro, in biomedicine and biotechnology makes them interesting model systems for sensor development. These enzymes have a free thiol group that is suitable for many sensor designs including strong binding [...] Read more.
The significant role of papain-like cysteine proteases, including papain, cathepsin L and SARS-CoV-2 PLpro, in biomedicine and biotechnology makes them interesting model systems for sensor development. These enzymes have a free thiol group that is suitable for many sensor designs including strong binding to gold nanoparticles or low-molecular-weight inhibitors. Focusing on the importance of the preservation of native protein structure for inhibitor-binding and molecular-imprinting, which has been applied in some efficient examples of sensor development, the aim of this work was to examine the effects of the free-thiol-group’s reversible blocking on papain denaturation that is the basis of its activity loss and aggregation. To utilize biophysical methods common in protein structural transitions characterization, such as fluorimetry and high-resolution infrared spectroscopy, low-molecular-weight electrophilic thiol blocking reagent S-Methyl methanethiosulfonate (MMTS) was used in solution. MMTS binding led to a two-fold increase in 8-Anilinonaphthalene-1-sulfonic acid fluorescence, indicating increased hydrophobic residue exposure. A more in-depth analysis showed significant transitions on the secondary structure level upon MMTS binding, mostly characterized by the lowered content of α-helices and unordered structures (either for approximately one third), and the increase in aggregation-specific β-sheets (from 25 to 52%) in a dose-dependant manner. The recovery of this inhibited protein showed that reversibility of inhibition is accompanied by reversibility of protein denaturation. Nevertheless, a 100-fold molar excess of the inhibitor led to the incomplete recovery of proteolytic activity, which can be explained by irreversible denaturation. The structural stability of the C-terminal β-sheet rich domain of the papain-like cysteine protease family opens up an interesting possibility to use its foldamers as a strategy for sensor development and other multiple potential applications that rely on the great commercial value of papain-like cysteine proteases. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Bioinspired Sensorics, Information Processing and Control)
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11 pages, 4417 KiB  
Article
Multi-Terminal Nonwoven Stochastic Memristive Devices Based on Polyamide-6 and Polyaniline for Neuromorphic Computing
by Nikita Prudnikov, Sergey Malakhov, Vsevolod Kulagin, Andrey Emelyanov, Sergey Chvalun, Vyacheslav Demin and Victor Erokhin
Biomimetics 2023, 8(2), 189; https://doi.org/10.3390/biomimetics8020189 - 3 May 2023
Cited by 6 | Viewed by 1959
Abstract
Reservoir computing systems are promising for application in bio-inspired neuromorphic networks as they allow the considerable reduction of training energy and time costs as well as an overall system complexity. Conductive three-dimensional structures with the ability of reversible resistive switching are intensively developed [...] Read more.
Reservoir computing systems are promising for application in bio-inspired neuromorphic networks as they allow the considerable reduction of training energy and time costs as well as an overall system complexity. Conductive three-dimensional structures with the ability of reversible resistive switching are intensively developed to be applied in such systems. Nonwoven conductive materials, due to their stochasticity, flexibility and possibility of large-scale production, seem promising for this task. In this work, fabrication of a conductive 3D material by polyaniline synthesis on a polyamide-6 nonwoven matrix was shown. An organic stochastic device with a prospective to be used in reservoir computing systems with multiple inputs was created based on this material. The device demonstrates different responses (output current) when different combinations of voltage pulses are applied to the inputs. The approach is tested in handwritten digit image classification task in simulation with the overall accuracy exceeding 96%. This approach is beneficial for processing multiple data flows within a single reservoir device. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Bioinspired Sensorics, Information Processing and Control)
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14 pages, 1359 KiB  
Article
Chemical Memory with Discrete Turing Patterns Appearing in the Glycolytic Reaction
by Jerzy Gorecki and Frantisek Muzika
Biomimetics 2023, 8(2), 154; https://doi.org/10.3390/biomimetics8020154 - 13 Apr 2023
Viewed by 1460
Abstract
Memory is an essential element in information processing devices. We investigated a network formed by just three interacting nodes representing continuously stirred tank reactors (CSTRs) in which the glycolytic reaction proceeds as a potential realization of a chemical memory unit. Our study is [...] Read more.
Memory is an essential element in information processing devices. We investigated a network formed by just three interacting nodes representing continuously stirred tank reactors (CSTRs) in which the glycolytic reaction proceeds as a potential realization of a chemical memory unit. Our study is based on the 2-variable computational model of the reaction. The model parameters were selected such that the system has a stable limit cycle and several distinct, discrete Turing patterns characterized by stationary concentrations at the nodes. In our interpretation, oscillations represent a blank memory unit, and Turing patterns code information. The considered memory can preserve information on one of six different symbols. The time evolution of the nodes was individually controlled by the inflow of ATP. We demonstrate that information can be written with a simple and short perturbation of the inflow. The perturbation applies to only one or two nodes, and it is symbol specific. The memory can be erased with identical inflow perturbation applied to all nodes. The presented idea of pattern-coded memory applies to other reaction networks that allow for discrete Turing patterns. Moreover, it hints at the experimental realization of memory in a simple system with the glycolytic reaction. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Bioinspired Sensorics, Information Processing and Control)
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21 pages, 8497 KiB  
Article
Living Plants Ecosystem Sensing: A Quantum Bridge between Thermodynamics and Bioelectricity
by Alessandro Chiolerio, Giuseppe Vitiello, Mohammad Mahdi Dehshibi and Andrew Adamatzky
Biomimetics 2023, 8(1), 122; https://doi.org/10.3390/biomimetics8010122 - 14 Mar 2023
Cited by 2 | Viewed by 3208
Abstract
The in situ measurement of the bioelectric potential in xilematic and floematic superior plants reveals valuable insights into the biological activity of these organisms, including their responses to lunar and solar cycles and collective behaviour. This paper reports on the “Cyberforest Experiment” conducted [...] Read more.
The in situ measurement of the bioelectric potential in xilematic and floematic superior plants reveals valuable insights into the biological activity of these organisms, including their responses to lunar and solar cycles and collective behaviour. This paper reports on the “Cyberforest Experiment” conducted in the open-air Paneveggio forest in Valle di Fiemme, Trento, Italy, where spruce (i.e., Picea abies) is cultivated. Our analysis of the bioelectric potentials reveals a strong correlation between higher-order complexity measurements and thermodynamic entropy and suggests that bioelectrical signals can reflect the metabolic activity of plants. Additionally, temporal correlations of bioelectric signals from different trees may be precisely synchronized or may lag behind. These correlations are further explored through the lens of quantum field theory, suggesting that the forest can be viewed as a collective array of in-phase elements whose correlation is naturally tuned depending on the environmental conditions. These results provide compelling evidence for the potential of living plant ecosystems as environmental sensors. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Bioinspired Sensorics, Information Processing and Control)
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Other

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29 pages, 4787 KiB  
Perspective
There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines
by Joshua Bongard and Michael Levin
Biomimetics 2023, 8(1), 110; https://doi.org/10.3390/biomimetics8010110 - 8 Mar 2023
Cited by 15 | Viewed by 11676
Abstract
The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven [...] Read more.
The applicability of computational models to the biological world is an active topic of debate. We argue that a useful path forward results from abandoning hard boundaries between categories and adopting an observer-dependent, pragmatic view. Such a view dissolves the contingent dichotomies driven by human cognitive biases (e.g., a tendency to oversimplify) and prior technological limitations in favor of a more continuous view, necessitated by the study of evolution, developmental biology, and intelligent machines. Form and function are tightly entwined in nature, and in some cases, in robotics as well. Thus, efforts to re-shape living systems for biomedical or bioengineering purposes require prediction and control of their function at multiple scales. This is challenging for many reasons, one of which is that living systems perform multiple functions in the same place at the same time. We refer to this as “polycomputing”—the ability of the same substrate to simultaneously compute different things, and make those computational results available to different observers. This ability is an important way in which living things are a kind of computer, but not the familiar, linear, deterministic kind; rather, living things are computers in the broad sense of their computational materials, as reported in the rapidly growing physical computing literature. We argue that an observer-centered framework for the computations performed by evolved and designed systems will improve the understanding of mesoscale events, as it has already done at quantum and relativistic scales. To develop our understanding of how life performs polycomputing, and how it can be convinced to alter one or more of those functions, we can first create technologies that polycompute and learn how to alter their functions. Here, we review examples of biological and technological polycomputing, and develop the idea that the overloading of different functions on the same hardware is an important design principle that helps to understand and build both evolved and designed systems. Learning to hack existing polycomputing substrates, as well as to evolve and design new ones, will have massive impacts on regenerative medicine, robotics, and computer engineering. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Bioinspired Sensorics, Information Processing and Control)
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