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Quantum-dot fabrication and characterization is a well-established technology, which is used in photonics, quantum optics, and nanoelectronics. Four quantum-dots placed at the corners of a square form a unit cell, which can hold a bit of information and serve as a basis for quantum-dot cellular automata (QCA) nanoelectronic circuits. Although several basic QCA circuits have been designed, fabricated, and tested, proving that quantum-dots can form functional, fast and low-power nanoelectronic circuits, QCA nanoelectronics still remain at its infancy. One of the reasons for this is the lack of design automation tools, which will facilitate the systematic design of large QCA circuits that contemporary applications demand. Here we present novel, programmable QCA circuits, which are based on crossbar architecture. These circuits can be programmed to implement any Boolean function in analogy to CMOS field-programmable gate arrays and open the road that will lead to full design automation of QCA nanoelectronic circuits. Using this architecture we designed and simulated QCA circuits that proved to be area efficient, stable, and reliable. [ABSTRACT FROM AUTHOR]

A cellular non-linear network (CNN) is a uniform regular array of locally connected continuous-state machines, or nodes, which update their states simultaneously in discrete time. A microbial fuel cell (MFC) is an electro-chemical reactor using the metabolism of bacteria to drive an electrical current. In a CNN model of the MFC, each node takes a vector of states which represent geometrical characteristics of the cell, like the electrodes or impermeable borders, and quantify measurable properties like bacterial population, charges produced and hydrogen ion concentrations. The model allows the study of integral reaction of the MFC, including temporal outputs, to spatial disturbances of the bacterial population and supply of nutrients. The model can also be used to evaluate inhomogeneous configurations of bacterial populations attached on the electrode biofilms. [ABSTRACT FROM AUTHOR]

The congregation of crowd undoubtedly constitutes an important risk factor, which may endanger the safety of the gathered people. The solution reported against this significant threat to citizens safety is to consider careful planning and measures. Thereupon, in this paper, we address the crowd evacuation problem by suggesting an innovative technological solution, namely, the use of mobile robot agents. The contribution of the proposed evacuation system is twofold: (i) it proposes an accurate Cellular Automaton simulation model capable of assessing the human behavior during emergency situations and (ii) it takes advantage of the simulation output to provide sufficient information to the mobile robotic guide, which in turn approaches and redirects a group of people towards a less congestive exit at a time. A custom-made mobile robotic platform was accordingly designed and developed. Last, the performance of the proposed robot guided evacuation model has been examined in real-world scenarios exhibiting significant performance improvement during the crucial first response time window. [ABSTRACT FROM PUBLISHER]

Computational functionality has been implemented successfully on chemical reactions in living systems. In the case of Belousov–Zhabotinsky (BZ) reaction, this was achieved by using collision-based techniques and by exploiting the light sensitivity of BZ. In order to unveil the computational capacity of the light sensitive BZ medium and the possibility to implement re-configurable logic, the design of multiple logic gates in a fixed BZ reservoir was investigated. The three basic logic gates (namely NOT, OR and AND) were studied to prove the Turing completeness of the architecture. Namely, all possible Boolean functions can be implemented as a combination of these logic gates. Nonetheless, a more complicated logic function was investigated, aiming to illustrate further capabilities of a fixed size BZ reservoir. The experiments executed within this study were implemented with a Cellular Automata (CA)-based model of the Oregonator equations that simulate excitation and wave propagation on a light sensitive BZ thin film. Given that conventional or von Neumann architecture computations is proved possible on the proposed configuration, the next step would be the realization of unconventional types of computation, such as neuromorphic and fuzzy computations, where the chemical substrate may prove more efficient than silicon. • Chemical reactions in living systems can implement computational functions. • Belousov–Zhabotinsky reaction is light sensitive and that can achieves its control. • The design of multiple logic gates in a fixed BZ reservoir was investigated. • Three basic logic gates NOT, OR and AND were implemented in the fixed reservoir. • The possibility to implement re-configurable logic is proven. [ABSTRACT FROM AUTHOR]

Belousov-Zhabotinsky (BZ) thin layer solution is a fruitful substrate for designing unconventional computing devices. A range of logical circuits, wet electronic devices, and neuromorphic prototypes have been constructed. Information processing in BZ computing devices is based on interaction of oxidation (excitation) wave fronts. Dynamics of the wave fronts propagation is programed by geometrical constraints and interaction of colliding wave fronts is tuned by illumination. We apply the principles of BZ computing to explore a geometry of street networks. We use two-variable Oregonator equations, the most widely accepted and verified in laboratory experiments BZ models, to study propagation of excitation wave fronts for a range of excitability parameters, with gradual transition from excitable to subexcitable to nonexcitable. We demonstrate a pruning strategy adopted by the medium with decreasing excitability when wider and ballistically appropriate streets are selected. We explain mechanics of streets selection and pruning. The results of the paper will be used in future studies of studying dynamics of cities and characterizing geometry of street networks. [ABSTRACT FROM AUTHOR]

A network design problem is to select a subset of links in a transport network that satisfy passengers or cargo transportation demands while minimizing the overall costs of the transportation. We propose a mathematical model of the foraging behaviour of slime mould P. polycephalum to solve the network design problem and construct optimal transport networks. In our algorithm, a traffic flow between any two cities is estimated using a gravity model. The flow is imitated by the model of the slime mould. The algorithm model converges to a steady state, which represents a solution of the problem. We validate our approach on examples of major transport networks in Mexico and China. By comparing networks developed in our approach with the man-made highways, networks developed by the slime mould, and a cellular automata model inspired by slime mould, we demonstrate the flexibility and efficiency of our approach. [ABSTRACT FROM AUTHOR]

The current paper proposes a hierarchical reinforcement learning (HRL) method to decompose a complex task into simpler sub-tasks and leverage those to improve the training of an autonomous agent in a simulated environment. For practical reasons (i.e., illustrating purposes, easy implementation, user-friendly interface, and useful functionalities), we employ two Python frameworks called TextWorld and MiniGrid. MiniGrid functions as a 2D simulated representation of the real environment, while TextWorld functions as a high-level abstraction of this simulated environment. Training on this abstraction disentangles manipulation from navigation actions and allows us to design a dense reward function instead of a sparse reward function for the lower-level environment, which, as we show, improves the performance of training. Formal methods are utilized throughout the paper to establish that our algorithm is not prevented from deriving solutions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2023 Petsanis, Keroglou, Kapoutsis, Kosmatopoulos and Sirakoulis.)

Presence sensing systems are gaining importance and are utilized in various contexts such as smart homes, Ambient Assisted Living (AAL) and surveillance technology. Typically, these systems utilize motion sensors or cameras that have a limited field of view, leading to potential monitoring gaps within a room. However, humans release carbon dioxide (CO 2 ) through respiration which spreads within an enclosed space. Consequently, an observable rise in CO 2 concentration is noted when one or more individuals are present in a room. This study examines an approach to detect the presence or absence of individuals indoors by analyzing the ambient air's CO 2 concentration using simple Markov Chain Models. The proposed scheme achieved an accuracy of up to 97% in both experimental and real data demonstrating its efficacy in practical scenarios., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2023 Karasoulas, Keroglou, Katsiri and Sirakoulis.)

Introduction: Recent advances in Artificial Intelligence (AI) and Computer Vision (CV) have led to automated pose estimation algorithms using simple 2D videos. This has created the potential to perform kinematic measurements without the need for specialized, and often expensive, equipment. Even though there's a growing body of literature on the development and validation of such algorithms for practical use, they haven't been adopted by health professionals. As a result, manual video annotation tools remain pretty common. Part of the reason is that the pose estimation modules can be erratic, producing errors that are difficult to rectify. Because of that, health professionals prefer the use of tried and true methods despite the time and cost savings pose estimation can offer., Methods: In this work, the gait cycle of a sample of the elderly population on a split-belt treadmill is examined. The Openpose (OP) and Mediapipe (MP) AI pose estimation algorithms are compared to joint kinematics from a marker-based 3D motion capture system (Vicon), as well as from a video annotation tool designed for biomechanics (Kinovea). Bland-Altman (B-A) graphs and Statistical Parametric Mapping (SPM) are used to identify regions of statistically significant difference., Results: Results showed that pose estimation can achieve motion tracking comparable to marker-based systems but struggle to identify joints that exhibit small, but crucial motion., Discussion: Joints such as the ankle, can suffer from misidentification of their anatomical landmarks. Manual tools don't have that problem, but the user will introduce a static offset across the measurements. It is proposed that an AI-powered video annotation tool that allows the user to correct errors would bring the benefits of pose estimation to professionals at a low cost., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Menychtas, Petrou, Kansizoglou, Giannakou, Grekidis, Gasteratos, Gourgoulis, Douda, Smilios, Michalopoulou, Sirakoulis and Aggelousis.)

An accurate modelling of bio-electrochemical processes that govern Microbial Fuel Cells (MFCs) and mapping their behavior according to several parameters will enhance the development of MFC technology and enable their successful implementation in well defined applications. The geometry of the electrodes is among key parameters determining efficiency of MFCs due to the formation of a biofilm of anodophilic bacteria on the anode electrode, which is a decisive factor for the functionality of the device. We simulate the bio-electrochemical processes in an MFC while taking into account the geometry of the electrodes. Namely, lattice Boltzmann methods are used to simulate the fluid dynamics and the advection-diffusion phenomena in the anode compartment. The model is verified on voltage and current outputs of a single MFC derived from laboratory experiments under continuous flow. Conclusions can be obtained from a parametric analysis of the model concerning the design of the geometry of the anode compartment, the positioning and microstructure of the anode electrode, in order to achieve more efficient overall performance of the system. An example of such a parametric analysis is presented here, taking into account the positioning of the electrode in the anode compartment.

Unconventional computing is about breaking boundaries in thinking, acting and computing. Typical topics of this non-typical field include, but are not limited to physics of computation, non-classical logics, new complexity measures, novel hardware, mechanical, chemical and quantum computing. Unconventional computing encourages a new style of thinking while practical applications are obtained from uncovering and exploiting principles and mechanisms of information processing in and functional properties of, physical, chemical and living systems; in particular, efficient algorithms are developed, (almost) optimal architectures are designed and working prototypes of future computing devices are manufactured. This article includes idiosyncratic accounts of 'unconventional computing' scientists reflecting on their personal experiences, what attracted them to the field, their inspirations and discoveries., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Physarum Polycephalum is a single cell visible by unaided eye. This is a plasmodial, vegetative stage of acellular slime mould. This single cell has myriad of nuclei which contribute to a network of bio-chemical oscillators responsible for the slime mould's distributed sensing, concurrent information processing and decision making, and parallel actuation. When presented with a spatial configuration of sources of nutrients, the slime mould spans the sources with networks of its protoplasmic tube. These networks belong to a family of planar proximity graphs. The protoplasmic networks also show a degree of similarity to vehicular transport networks. Previously, we have shown that the foraging behaviour of the slime mould can be applied in archaeological research to complement and enhance conventional geographic information system tools. The results produced suffered from limitation of a flat substrate: transport routes imitated by the slime mould did not reflect patterns of elevations. To overcome the limitation of the 'flat world' we constructed a three-dimensional model of Balkans. In laboratory experiments and computer modelling we uncovered patterns of the foraging behaviour that might shed a light onto development of Roman roads in the Balkans during the imperial period (1st century BC - 4th century AD).

Theoretical constructs of logical gates implemented with plant roots are morphological computing asynchronous devices. Values of Boolean variables are represented by plant roots. A presence of a plant root at a given site symbolises the logical True, an absence the logical False. Logical functions are calculated via interaction between roots. Two types of two-inputs-two-outputs gates are proposed: a gate 〈x, y〉→〈xy, x+y〉 where root apexes are guided by gravity and a gate 〈x,y〉→〈x¯y,x〉 where root apexes are guided by humidity. We propose a design of binary half-adder based on the gates., (Copyright © 2017 Elsevier B.V. All rights reserved.)

The Microbial Fuel Cell (MFC) is a bio-electrochemical transducer converting waste products into electricity using microbial communities. Cellular Automaton (CA) is a uniform array of finite-state machines that update their states in discrete time depending on states of their closest neighbors by the same rule. Arrays of MFCs could, in principle, act as massive-parallel computing devices with local connectivity between elementary processors. We provide a theoretical design of such a parallel processor by implementing CA in MFCs. We have chosen Conway's Game of Life as the 'benchmark' CA because this is the most popular CA which also exhibits an enormously rich spectrum of patterns. Each cell of the Game of Life CA is realized using two MFCs. The MFCs are linked electrically and hydraulically. The model is verified via simulation of an electrical circuit demonstrating equivalent behaviours. The design is a first step towards future implementations of fully autonomous biological computing devices with massive parallelism. The energy independence of such devices counteracts their somewhat slow transitions-compared to silicon circuitry-between the different states during computation.

Safe evacuation of people from building and outdoor environments, and search and rescue operations, always will remain actual in course of all socio-technological developments. Modern facilities offer a range of automated systems to guide residents towards emergency exists. The systems are assumed to be infallible. But what if they fail? How occupants not familiar with a building layout will be looking for exits in case of very limited visibility where tactile sensing is the only way to assess the environment? Analogous models of human behaviour, and socio-dynamics in general, are provided to be fruitful ways to explore alternative, or would-be scenarios. Crowd, or a single person, dynamics could be imitated using particle systems, reaction-diffusion chemical medium, electro-magnetic fields, or social insects. Each type of analogous model offer unique insights on behavioural patterns of natural systems in constrained geometries. In this particular paper we have chosen leeches to analyse patterns of exploration. Reasons are two-fold. First, when deprived from other stimuli leeches change their behavioural modes in an automated regime in response to mechanical stimulation. Therefore leeches can give us invaluable information on how human beings might behave under stress and limited visibility. Second, leeches are ideal blueprints of future soft-bodied rescue robots. Leeches have modular nervous circuitry with a rich behavioral spectrum. Leeches are multi-functional, fault-tolerant with autonomous inter-segment coordination and adaptive decision-making. We aim to answer the question: how efficiently a real building can be explored and whether there any dependencies on the pathways of exploration and geometrical complexity of the building. In our case studies we use templates made on the floor plan of real building., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)