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Coronavirus outbreaks in 2019 (COVID-19) have been a huge disaster in the fields of health, economics, education, and tourism in the last two years. For diagnosis, a quick interpretation of the COVID-19 chest X-ray image is required. There is also a strong need to find an efficient multiclass segmentation technique for the analysis of COVID-19 X-ray images. Most of the threshold selection techniques are entropy-based. Nevertheless, these techniques suffer from their dependencies on the spatial distribution of grey values. To tackle these issues, a novel non-entropic threshold selection method is proposed, which is the primary key contribution having found a new source of information to the biomedical image processing field. The firsthand Square Error (SE)-based objective function is suggested. The second key contribution is the new optimizer called Fast Cuckoo Search (FCS), which is useful and brings novel ideas into the subject, used to optimize the suggested objective functions for computing the optimal thresholds. To ensure a faster convergence with a quality optimal solution, we include extra exploitation together with a chance factor. The FCS is validated using the well-known classical and CEC 2014 benchmark test functions, which shows a significant improvement over its predecessors—Adaptive Cuckoo Search (ACS) and other state-of-the-art optimizers. Further, the SE minimization-based optimal multilevel thresholding method using the FCS, coined as SE-FCS, is proposed. To experiment, images are considered from the Kaggle Radiography database. We have compared its performances with Tsallis, Kapur's, and Masi entropy-based techniques using well-known segmentation metrics and achieved a performance increase of 2.95%, 5.51% and 10.50%, respectively. The proposed method shows superiority using Friedman's mean rank statistical test and ranked first. [ABSTRACT FROM AUTHOR]

Abstract The significance of neuronal discharge symmetry lies in its reflection of the stability and orderliness within the neuron's activity. This symmetry is correlated with various issues, including the biophysical properties within neurons, network structures, and synaptic transmission. Memristors are highly analogous to neuronal synapses due to their unique memory properties, allowing them to emulate biological neural synapses. In this work, a memristor is employed into the Hindmarsh‐Rose (HR) neuron as a synapse for the construction of a memristive HR neuron. Accompanied with the introducing of the absolute value and signum function, the derived neurons exhibit complex coexisting symmetric firing patterns. The phenomenon of symmetric firing can effectively simulate the depolarization and hyperpolarization processes of neurons, providing a new approach to study the diversity of the brain.

The significance of neuronal discharge symmetry lies in its reflection of the stability and orderliness within the neuron's activity. This symmetry is correlated with various issues, including the biophysical properties within neurons, network structures, and synaptic transmission. Memristors are highly analogous to neuronal synapses due to their unique memory properties, allowing them to emulate biological neural synapses. In this work, a memristor is employed into the Hindmarsh‐Rose (HR) neuron as a synapse for the construction of a memristive HR neuron. Accompanied with the introducing of the absolute value and signum function, the derived neurons exhibit complex coexisting symmetric firing patterns. The phenomenon of symmetric firing can effectively simulate the depolarization and hyperpolarization processes of neurons, providing a new approach to study the diversity of the brain. [ABSTRACT FROM AUTHOR]

Rapid processes in the area of cell biophysics, invasions, or epidemiology are distinguished by the variety of their variants; therefore, they require original methods of mathematical description for long-term prediction of the state of biophysical systems. Without building predictions of the dynamics of biophysical interaction, it is impossible to improve the technology of industrial exploitation of natural objects. Classical models based on systems of differential equations do not describe the dynamics of real processes that are observed during aggressive invasions of alien species. Known models of "predator/prey" systems assumed the cyclical dynamics of two rival species, but in reality, the oscillatory solution of the model's equations is only a mathematical hypothesis. In real biosystems, the variants for the development of scenarios after the introduction of an aggressive predator or parasite are more complicated. Dynamics during invasions becomes extreme. In laboratory experiments with ciliates, instead of asynchronous oscillations with the prey, the infused predator after a rapid outbreak completely destroyed the entire population of prey. Processes with abrupt metamorphoses are extremely relevant, for example, the development of an immune response during the presentation of antigens of new strains of coronavirus and the activation of specific T-lymphocytes of immune memory killer cells to destroy infected cells. Modeling of extreme development in our works is based on the aspects of eventfulness and variability of choice during abrupt changes in the stages of the process under study, for example, adaptation of a parasite against a breeding invader, which is an important way to combat invasions. For rapidly changing biophysical processes, we proposed to expand the models in differential equations with the components of eventfulness, delay, trigger switching, and the logic of switching stages of development. Previously, we proposed an original formalization of the event hierarchy for continuous-discrete time in a hybrid model. In the article, we will present a method for including predicates in the model, i.e., logical functions that allow us to calculate the sequence of changes in the behavior of the invasive process. Our predictive logic approach is important for computational modeling with transformations in dangerous and fast invasive processes and waves of the COVID-19 epidemic based on a comparative analysis of scenarios. Based on the predicative choice of the behavior of a hybrid automaton defined for a set of right-hand sides of systems of differential equations, we also formalize the decision-making logic in scenarios with a controlled impact on biosystems. Post-COVID immunodeficiency is the most complex legacy of the pandemic. [ABSTRACT FROM AUTHOR]

The problem of confirming the correspondence of the dynamics of biophysical processes arising from the incomplete and noisy data obtained during monitoring of the state of bioresources or statistics gathering in a series of laboratory experiments to three behavioral modes of paths of discrete dynamic systems (equilibrium, limiting cycle, or chaos) is considered. It is shown using the examples of real monitoring data and results of laboratory experiments that the data-approximation technique yields a dependence function, which excludes the observed qualitative development of the population process. Attempts to plot regression lines based on the monitoring data for dissipative paths do not yield the necessary information. Known models of biophysics with qualitative changes in the behavior are considered that use characteristics of the reproductive function that cannot be interpreted in terms of the environmental role. The Schwartz derivative depends on the third derivative of the second iteration of the function at the moment of stationary-point stability loss. Criteria for discrete dynamic systems are proposed that can be used to analyze the results of computational simulation from the point of view of biophysical adequacy of occurring nonlinear effects. It is suggested that the rate of population change in the model has a range of negative values and the population reproduction curve has at least two nontrivial stationary points. Consideration of the effect of an aggregated group, arising during invasions, in the action models facilitates an essential interpretation of the behavior of the model path. It is proposed to delimit the nonlinear effects arising in discrete iterative models. In the case of an invasive species that has penetrated into the ecosystem and caused the depletion of its vital resources, a rapid transition to collapse of the new population is possible. Our approach with two-attractor models makes it possible to predict the state of a critically low population of an aggressive intruder. [ABSTRACT FROM AUTHOR]

Formalization in the form of systems of differential equations to describe sharp changes in the development of invasion processes remains an important and urgent problem for mathematical biophysics and bioinformatics. The spread of aggressive biological organisms is accompanied by the rapid phenomena of explosive increase in the dynamics of the population of these dangerous foreign species. Hardly predictable population outbreaks of small insects may continue until the total destruction of forests on large areas. This phenomenon of imbalance affects the entire environment and biochemical processes in the trophic chain of the biosystem. After a rapid uncontrolled (by natural physical factors and a biotic environment) outbreak, degradation of ecosystems and extinction of the invasive species may occur. The fundamental problem of controlling new aggressive species is very important for practical problems of the optimal use of bioresources. The generality of some situations requires special mathematical analysis, which can be constructed by analogy with physical processes with sharp transient regimes. Parametric changes and bifurcations cannot explain the change in behavior, because these reproductive characteristics of aggressive species in a specific biophysical environment are stable during evolutionary adaptation and change only gradually. The simulation of changes in the development rate of individuals in a competitive environment is considered as a hidden factor affecting the realization of critical effects in the dynamics of the population of species with a pronounced staging of ontogenesis. A hybrid model is constructed based on the system of equations describing actual changes in the metabolism rate in ontogenesis, which is applicable to populations in different states of the invasion process. [ABSTRACT FROM AUTHOR]

Crisis processes of biosystems often develop according to scenarios of rapid collapse, which cannot be predicted by statistical methods. This paper develops a method for constructing hybrid computational models using event-hierarchy representation for biophysical processes. System events calculated by the algorithm change the order of calculation of equations according to a given set of rules. The rules of physically conditioned redefinition of the right-hand sides of differential equations are used. The predicates employ the calculations of a group of accompanying characteristics, which are an integral part of the controlled biophysical dynamics. The model is investigated by presenting a computational scenario with a set of parameters, initial values, and an algorithm for making decisions about changing the impact for discrete time. Using computational experiments, a real outcome scenario for a situation that leads to the collapse of a biophysical system at a controlled level of exposure is described. The scenario sets the logic for making control decisions to change the level of external pressure on the natural environment. It is shown as a result of modeling that the transition of the process to an oscillatory mode leads to the choice of a risky control mode. It has been established that the dynamics of many real water populations has a point of threshold reduction in the efficiency of replenishment of stocks. The model scenario uses transformations of the phase portrait of iterations, which, in the presence of disconnected boundaries of the areas of attraction of alternative attractors and a strange chaotic repeller, lead to the uncertainty effects arising due to chaotic modes in a deterministic model. The properties of the described model scenario with a chaotic regime of dynamics are confirmed by the example of the catch of oceanic species of crustaceans. [ABSTRACT FROM AUTHOR]

Apertures are used in optical systems to limit the luminous flux. In the human eye the iris serves this purpose but can be damaged requiring an implant, which to date is static, limiting the optical performance. The authors thus report the development of a prototype demonstrating the feasibility of a flexible dynamic iris implant manufactured with an automated manufacturing technique. The presented actuators are printed via aerosol jet printing allowing a high reliability in produced electrode quality. Through optimization of the actuator design for maximum contraction they demonstrate a pupil area reduction of 13.40% or 6.94% reduction of pupil diameter, respectively. Thereby the prototype demonstrates an illuminance reduction of 18.25% in the central visual axis. Furthermore, they present a first iteration of a bionic closed‐loop control mimicking the human iris reflex thus laying the foundation for a self‐controlled iris implant. [ABSTRACT FROM AUTHOR]

The advances made by microbiome research call for new vocabulary and expansion of our thinking in microbiology. For example, the life-forms presenting in both unicellular and multicellular formats invite us to rethink microbial existence, organization, growth, pathogenicity, and therapeutics in the 21st century. A view of such populations as parts of single organisms with a loose, distributed multicellular organization, introduced here as a germ-ganism, rather than communities, might open up interesting prospects for diagnostics and therapeutics innovation. This study tested and further contextualized the concept of germ-ganism using solid cultures of bacteria and fungi. Based on our findings and the literature reviewed herein, we propose that germ-ganism has synergy with a systems medicine approach by broadening host-environment interactions from cells and microorganisms to a scale of biological ecosystems. Germ-ganism also brings about the possibility of studying the multilevel impacts of novel therapeutic agents within and across networks of microbial ecosystems. The germ-ganism would lend itself, in the long term, to a veritable biocybernetics system, while in the mid-term, we anticipate it will contribute to new diagnostics and therapeutics. Biosecurity applications would be immensely affected by germ-ganism. Industrial applications of germ-ganism are of interest as a more sustainable alternative to costly solutions such as tampered strains/microorganisms. In conclusion, germ-ganism is informed by lessons from microbiome research and invites rethinking microbial existence, organization, and growth as an organism. Germ-ganism has vast ramifications for understanding pathogenicity, and clinical, biosecurity, and biotechnology applications in the current historical moment of the COVID-19 pandemic and beyond. [ABSTRACT FROM AUTHOR]

Teaching Biomedical Engineering now takes place in most technical schools and in some universities. Each of them uses its own curricula, tailored to the goals of education and the qualifications of their staff. This diversity concerns, among other things, the lecture on the subject of biocybernetics. At the birth of the Biomedical Engineering studies (which was launched at the AGH University of Science and Technology a year earlier than in all other Polish universities), the biocybernetics lecture was the first one that the students listened to. Following the example of AGH, other universities also introduced this lecture. Later, however, many universities gave up teaching this subject, and Act 2.0 changed the name of the scientific discipline for many years called "Biocybernetics and Biomedical Engineering" to "Biomedical Engineering", limiting the chances of obtaining degrees in biocybernetics. Nevertheless, at AGH UST, this subject is still taught at the beginning of the Biomedical Engineering course. In the academic year 2021/22, a survey was conducted among the students; having had one semester of lectures, they answered the question: "How will the knowledge of biocybernetics help me in the profession of a biomedical engineering specialist?" This article presents the results of this survey and encourages you to think about it. [ABSTRACT FROM AUTHOR]

Pupil detection in a human eyeimage or video plays a key role in many applications such as eye-tracking, diabetic retinopathy screening, smart homes, iris recognition, etc. Literature reveals pupil detection faces many complications including light reflections, cataract disease, pupil constriction/dilation moments, contact lenses, eyebrows, eyelashes, hair strips, and closed eye. To cope with these challenges, research community has been struggling to devise resilient pupil localization schemes for the image/video data collected using the near-infrared (NIR) or visible spectrum (VS) illumination. This study presents a critical review of numerous pupil detection schemes taken from standard sources. This review includes pupil localization schemes based on machine learning, histogram/thresholding, Integro-differential operator (IDO), Hough transform and among others. The probable pros and cons of each scheme are highlighted. Finally, this study offers recommendations for designing a robust pupil detection system. As scope of pupil detection is very broader, therefore this review would be a great source of information for the relevant research community. [ABSTRACT FROM AUTHOR]

The traditional bionic upper limb structure design is limited by the motion pair and cannot guarantee the flexibility of the mechanical structure. The tensegrity structure has the characteristics of high deformability, strong self-adaptability, and resistance to multi-directional impact. According to the biological characteristics of the upper limbs of the human body, an anatomical study is performed on the upper limb wrist joints that achieve adduction/abduction, flexion/extension, to obtain the relationship between the movements of the related bones and muscles, and to simplify the shape and structure of the wrist. Equivalent mapping of a mechanical model based on two-bar tensile properties. Through the contraction and stretching of the spring, the movement characteristics of the human muscles are realised, and the optimised bionic upper limb wrist tensioning robot without motion pair is further obtained. Adams simulation is used to verify that the bionic tensile wrist can simulate the change movement of the human wrist. The experimental platform was built and a physical prototype was made and the prototype was tested. The results show that the bionic tensile wrist can realise the adaptive motion characteristics of the human wrist well and stably, which proves the validity and feasibility of this design method.

Objectives: In this paper a novel approach regarding image analysis in Machine Vision applications was proposed. Methods: The presented concept consists of two issues: (1) shifting some of the complex image processing and understanding algorithms from a mobile robot to distributed computer, and (2) designing the cognitive system (in a distributed computer) in such a way, that it would be common for numerous robots. The authors of this work focused on image processing, and they propose to accelerate vision understanding by using Cooperative Vision (CoV), i.e., to get video input from cooperating robots and process it in a centralized system. Results: To verify the purposefulness of such approach, a comparative study is currently being conducted, involving a classical single-camera Computer Vision (CV) mobile robot and two (or more) single-camera CV robots cooperating in CoV mode. Conclusions: The CoV system is being designed and implemented so that the algorithm would be able to utilize multiple video sources for recognition of objects on the very same scene. [ABSTRACT FROM AUTHOR]

Special situations, which are difficult to predict and to model by traditional methods, develop rapidly in population processes. A sudden collapse of commercial fish stocks, in addition to outbreaks of forest pests, are among the most economically significant nonlinear phenomena in ecosystems. According to systems analysis of statistical data on the dynamics of catches, the transitional stages of rapid degradation in completely different species of fish and aquatic invertebrates occur in a similar way. The most representative stages of the development of fish resources collapse have been distinguished. Restoration of the already critically depleted aquatic bioresources occurs at different rates. Based on the method of dynamically redefinable hybrid computational structure, we considered situations of collapse that occurred with crab off the coast of Alaska and northern cod off the coast of Canadian provinces of Newfoundland and Labrador. The resulting computational scenarios for collapse manifestation consist of three stages, all the way up to the degradation of bioresources. Bifurcations are implemented purposefully and follow the logic of the process. The modeling method is generalized for cases with stationary food resources and with oscillatory dynamics of food organisms. [ABSTRACT FROM AUTHOR]

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In this study, three types of bionic texture surfaces were designed, based on the microstructure of tree frog and gecko feet, for two typical prosthetic substrates: silicone rubber and thermoplastic polyurethane elastomer (TPU). The surface energy of all bionic texture surfaces, and the relative displacement and energy dissipation of the reciprocating friction between these bionic surfaces and skin, were investigated. The results revealed that the bionic texture of the prosthetic socket surface had an obvious influence on the surface characteristics and reciprocating characteristics of friction with the skin. According to the comprehensive weight rating method, the optimal bionic textures for the silicone rubber substrate were a regular hexagonal prism and a quadrangular prism; for the TPU substrate, only the regular quadrangular prism texture was optimal. These textures can effectively increase the surface energy of the surface of the prosthetic socket, thereby increasing its adhesion to skin and reducing the dissipation of friction energy when it interacts with the stump. This bionic prosthetic socket surface design helps improve the adaptation between the prosthetic socket and the stump.

In this Focused Review, we provide an update about evolving concepts that may link chronic stress and catecholamine autotoxicity with neurodegenerative diseases such as Parkinson's disease. Richard Kvetnansky's contributions to the field of stress and catecholamine systems inspired some of the ideas presented here. We propose that coordination of catecholaminergic systems mediates adjustments maintaining health and that senescence-related disintegration of these systems leads to disorders of regulation and to neurodegenerative diseases such as Parkinson's disease. Chronically repeated episodes of stress-related catecholamine release and reuptake, with attendant increases in formation of the toxic dopamine metabolite 3,4-dihydroxyphenylacetaldehyde, might accelerate this process. [ABSTRACT FROM AUTHOR]

In this review we describe a series of major concepts introduced during the past 150 years that have contributed to our current understanding about how physiological processes required for well-being and survival are regulated. One can theorize that hierarchical networks involving input-output relationships continuously orchestrate and learn adaptive patterns of observable behaviors, cognition, memory, mood, and autonomic systems. Taken together, these networks function as “good regulators” determining levels of internal variables and act as if there were homeostatic comparators (“homeostats”). The consequences of models with vs. without homeostats remain the same in terms of allostatic load and the eventual switch from stabilizing negative feedback loops to destabilizing, pathogenic positive feedback loops. Understanding this switch seems important for comprehending senescence-related, neurodegenerative disorders that involve the autonomic nervous system. Our general proposal is that disintegration of homeostatic systems causes disorders of regulation in degenerative diseases and that medical cybernetics can inspire and rationalize new approaches to treatment and prevention. [ABSTRACT FROM AUTHOR]

The depth measurement error of bionic eyes consisting of two active cameras is derived by considering the eyes' rotation angle errors and image feature extraction errors. The effect factors of the depth measurement are obtained from the calculation formula of depth error. Based on the analysis of these effect factors, some effective guidelines for bionic eyes are proposed to reduce the measurement errors. The guidelines suggest keeping long baseline, observing the target as nearly as possible, controlling two active cameras with the same angular velocity and keeping the target on Zw axis if possible. The simulation experiments and practical experiments in bionic eyes platform validate the effectiveness of the proposed guidelines. [ABSTRACT FROM AUTHOR]

Bioreactors are used for commercial manufacturing of products or as a simplified representation of wastewater treatment plants. If it is taken into account that individual organisms from the population in the bioreactor behave differently, an additional structure such as age can be added to the population. This leads to a nonlinear, hyperbolic, integro-partial differential equation (IPDE) with non-local integral boundary conditions (BC) in the modeling. The steady-states of this system can be uniquely determined by a substitution due to the non-local BC. Using the asymptotic properties of the system, the IPDE is split into finite-dimensional dynamics and infinite dimensional internal dynamics. The internal dynamics are globally exponentially stable. Therefore, a feedforward control based on the finite dimensional dynamics is designed, augmented with a feedback control to compensate for the remaining influence of the internal dynamics on the output. Finally, the control concept is supplemented by an observer. Global exponential attractiveness of certain reference trajectories is proven. The overall control concept is validated experimentally with a bioreactor. A system parameter is identified and it is shown that by applying the control concept, the biomass can track various reference trajectories with small errors. [ABSTRACT FROM AUTHOR]

Preterm birth is a global epidemic affecting millions of mothers across different ethnicities. The cause of the condition remains unknown but has recognised health-based implications, in addition to financial and economic ones. Machine Learning methods have enabled researchers to combine datasets using uterine contraction signals with various forms of prediction machines to improve awareness of the likelihood of premature births. This work investigates the feasibility of enhancing these prediction methods using physiological signals including uterine contractions, and foetal and maternal heart rate signals, for a population of south American women in active labour. As part of this work, the use of the Linear Series Decomposition Learner (LSDL) was seen to lead to an improvement in the prediction accuracies of all models, which included supervised and unsupervised learning models. The results from the supervised learning models showed high prediction metrics upon the physiological signals being pre-processed by the LSDL for all variations of the physiological signals. The unsupervised learning models showed good metrics for the partitioning of Preterm/Term labour patients from their uterine contraction signals but produced a comparatively lower set of results for the various kinds of heart rate signals investigated., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors. Healthcare Technology Letters published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.)

The dynamics of population systems can be observed in chemostat reactors under laboratory conditions. The modeling of these kind of systems leads to a nonlinear, hyperbolic, first-order integro-partial differential equation with integral boundary condition. Hereby, the state is the population density and the input is the restricted dilution rate. Through an appropriate choice of the steady-state input a generalized spectral analysis is carried out. By using this result and a nonlinear mapping the partial differential equation is split into an input/output-normal form and an integral delay equation. Due to the global exponential stability of the integral delay equation, a feedforward controller is designed for the input/output-normal form. This is complemented with a feedback controller to compensate the influence of the integral delay equation on the output. The global exponential attractivity of reference trajectories meeting certain requirements is proven. Simulations show the performance of the controller saturated to the input constraints in dependency of the controller settings. [ABSTRACT FROM AUTHOR]