Numerical Simulations of the Epley Maneuver With Clinical Implications.

OBJECTIVES: Canalith repositioning procedures to treat benign paroxysmal positional vertigo are often applied following standardized criteria, without considering the possible anatomical singularities of the membranous labyrinth for each individual. As a result, certain patients may become refractory to the treatment due to significant deviations from the ideal membranous labyrinth, that was considered when the maneuvers were designed. This study aims to understand the dynamics of the endolymphatic fluid and otoconia, within the membranous labyrinth geometry, which may contribute to the ineffectiveness of the Epley maneuver. Simultaneously, the study seeks to explore methods to avoid or reduce treatment failure. DESIGN: We conducted a study on the Epley maneuver using numerical simulations based on a three-dimensional medical image reconstruction of the human left membranous labyrinth. A high-quality micro-computed tomography of a human temporal bone specimen was utilized for the image reconstruction, and a mathematical model for the endolymphatic fluid was developed and coupled with a spherical particle model representing otoconia inside the fluid. This allowed us to measure the position and time of each particle throughout all the steps of the maneuver, using equations that describe the physics behind benign paroxysmal positional vertigo. RESULTS: Numerical simulations of the standard Epley maneuver applied to this membranous labyrinth model yielded unsatisfactory results, as otoconia do not reach the frontside of the utricle, which in this study is used as the measure of success. The resting times between subsequent steps indicated that longer intervals are required for smaller otoconia. Using different angles of rotation can prevent otoconia from entering the superior semicircular canal or the posterior ampulla. Steps 3, 4, and 5 exhibited a heightened susceptibility to failure, as otoconia could be accidentally displaced into these regions. CONCLUSIONS: We demonstrate that modifying the Epley maneuver based on the numerical results obtained in the membranous labyrinth of the human specimen under study can have a significant effect on the success or failure of the treatment. The use of numerical simulations appears to be a useful tool for future canalith repositioning procedures that aim to personalize the treatment by modifying the rotation planes currently defined as the standard criteria.

Numerical simulations to determine the stimulation of the crista ampullaris during the Head Impulse Test.

The Head Impulse Test, the most widely accept test to assess the vestibular function, comprises rotations of the head based on idealized orientations of the semicircular canals, instead of their individual arrangement specific for each patient. In this study, we show how computational modelling can help personalize the diagnosis of vestibular diseases. Based on a micro-computed tomography reconstruction of the human membranous labyrinth and their simulation using Computational Fluid Dynamics and Fluid-Solid Interaction techniques, we evaluated the stimulus experienced by the six cristae ampullaris under different rotational conditions mimicking the Head Impulse Test. The results show that the maximum stimulation of the crista ampullaris occurs for directions of rotation that are more aligned with the orientation of the cupulae (average deviation from alignment of 4.7°, 9.8°, and 19.4° for the horizontal, posterior, and superior maxima, respectively) than with the planes of the semicircular canals (average deviation from alignment of 32.4°, 70.5°, and 67.8° for the horizontal, posterior, and superior maxima, respectively). A plausible explanation is that when rotations are applied with respect to the center of the head, the inertial forces acting directly over the cupula become dominant over the endolymphatic fluid forces generated in the semicircular canals. Our results indicate that it is necessary to consider cupulae orientation to ensure optimal conditions for testing the vestibular function.

A Goodwin Model Modification and Its Interactions in Complex Networks.

The global economy cannot be understood without the interaction of smaller-scale economies. We addressed this issue by considering a simplified economic model that still preserves the basic features, and analyzed the interaction of a set of such economies and the collective emerging dynamic. The topological structure of the economies' network appears to correlate with the collective properties observed. In particular, the strength of the coupling between the different networks as well as the specific connectivity of each node happen to play a crucial role in the determination of the final state.

Numerical and renormalization group analysis of the phase diagram of a stochastic cubic autocatalytic reaction-diffusion system.

The renormalization group is a set of tools that can be used to incorporate the effect of fluctuations in a dynamical system as a rescaling of the system's parameters. Here, we apply the renormalization group to a pattern-forming stochastic cubic autocatalytic reaction-diffusion model and compare its predictions with numerical simulations. Our results demonstrate a good agreement within the range of validity of the theory and show that external noise can be used as a control parameter in such systems.

Artificial Intelligence Techniques Used to Extract Relevant Information from Complex Social Networks.

Social networks constitute an almost endless source of social behavior information. In fact, sometimes the amount of information is so large that the task to extract meaningful information becomes impossible due to temporal constrictions. We developed an artificial-intelligence-based method that reduces the calculation time several orders of magnitude when conveniently trained. We exemplify the problem by extracting data freely available in a commonly used social network, Twitter, building up a complex network that describes the online activity patterns of society. These networks are composed of a huge number of nodes and an even larger number of connections, making extremely difficult to extract meaningful data that summarizes and/or describes behaviors. Each network is then rendered into an image and later analyzed using an AI method based on Convolutional Neural Networks to extract the structural information.

Intermittent regimes as a synchronization phenomenon in two sets of nonlinear chemical oscillators.

Systems of nonlinear chemical oscillators can exhibit a large diversity of non-trivial states depending on the parameters that characterize them. Among these, a synchronization phenomenon is of special interest due to its direct link with chemical and biological processes in nature. We carry out numerical experiments for two different sets of chemical oscillators with different properties and immersed in a Belousov-Zhabotinsky solution. We document the emergence of different states of synchronization that depend on the parameters characterizing the solution. We also show that, in the interface regions, this system generates a stable dynamics of intermittency between the different synchronization states where interesting phenomena, such as the "devil's staircase," emerge. In general, the added complexity introduced with the additional set of oscillators results in more complex non-trivial synchronization states.

Impact of Enhanced Phagocytosis of Glycated Erythrocytes on Human Endothelial Cell Functions.

Diabetes is associated with a high mortality rate due to vascular complications. Chronic hyperglycemia in diabetes leads to enhanced oxidative stress and glycation. Here, we explored the impact of glycation on human erythrocyte characteristics and capacity to affect endothelial cell function following erythrophagocytosis. Native and glucose-mediated glycated erythrocytes were prepared and characterized in terms of structural and deformability modifications. Erythrocyte preparations were tested for their binding and phagocytosis capacity as well as the potential functional consequences on human endothelial cell lines and primary cultures. Oxidative modifications were found to be enhanced in glycated erythrocytes after determination of their deformability, advanced glycation end-product content and eryptosis. Erythrophagocytosis by endothelial cells was significantly increased when incubated in the presence of glycated erythrocytes. In addition, higher iron accumulation, oxidative stress and impaired endothelial cell permeability were evidenced in cells previously incubated with glycated erythrocytes. When cultured under flow conditions, cellular integrity was disrupted by glycated erythrocytes at microvessel bifurcations, areas particularly prone to vascular complications. This study provides important new data on the impact of glycation on the structure of erythrocytes and their ability to alter endothelial cell function. Increased erythrophagocytosis may have a deleterious impact on endothelial cell function with adverse consequences on diabetic vascular complications.

Assessing the risk of pandemic outbreaks across municipalities with mathematical descriptors based on age and mobility restrictions.

By March 14th 2022, Spain is suffering the sixth wave of the COVID-19 pandemic. All the previous waves have been intimately related to the degree of imposed mobility restrictions and its consequent release. Certain factors explain the incidence of the virus across regions revealing the weak locations that probably require some medical reinforcements. The most relevant ones relate with mobility restrictions by age and administrative competence, i.e., spatial constrains. In this work, we aim to find a mathematical descriptor that could identify the critical communities that are more likely to suffer pandemic outbreaks and, at the same time, to estimate the impact of different mobility restrictions. We analyze the incidence of the virus in combination with mobility flows during the so-called second wave (roughly from August 1st to November 30th, 2020) using a SEIR compartmental model. After that, we derive a mathematical descriptor based on linear stability theory that quantifies the potential impact of becoming a hotspot. Once the model is validated, we consider different confinement scenarios and containment protocols aimed to control the virus spreading. The main findings from our simulations suggest that the confinement of the economically non-active individuals may result in a significant reduction of risk, whose effects are equivalent to the confinement of the total population. This study is conducted across the totality of municipalities in Spain.

Unified representation of Life's basic properties by a 3-species Stochastic Cubic Autocatalytic Reaction-Diffusion system of equations.

Today we can use physics to describe in great detail many of the phenomena intervening in the process of life. But no analogous unified description exists for the phenomenon of life itself. In spite of their complexity, all living creatures are out of equilibrium chemical systems sharing four fundamental properties: they (1) handle information, (2) metabolize, (3) self-reproduce and (4) evolve. This small number of features, which in terran life are implemented with biochemistry, point to an underlying simplicity that can be taken as a guide to motivate and implement a theoretical physics style unified description of life using tools from the non-equilibrium physical-chemistry of extended systems. Representing a system with general rules is a well stablished approach to model building and unification in physics, and we do this here to provide an abstract mathematical description of life. We start by reviewing the work of previous authors showing how the properties in the above list can be individually represented with stochastic reaction-diffusion kinetics using polynomial reaction terms. These include "switches" and computation, the kinetic representation of autocatalysis, Turing instability and adaptation in the presence of both deterministic and stochastic environments. Thinking of these properties as existing on a space-time lattice each of whose nodes are subject to a common mass-action kinetics compatible with the above, leads to a very rich dynamical system which, just as natural life, unifies the above properties and can therefore be interpreted as a high level or "outside-in" theoretical physics representation of life. Taking advantage of currently available advanced computational techniques and hardware, we compute the phase plane for this dynamical system both in the deterministic and stochastic cases. We do simulations and show numerically how the system works. We review how to extract useful information that can be mapped into emergent physical phenomena and attributes of importance in life such as the presence of a "membrane" or the time evolution of an individual system's negentropy or mass. Once these are available, we illustrate how to perform some basic phenomenology based on the model's numerical predictions. Applying the above to the idealization of the general Cell Division Cycle (CDC) given almost 25 years ago by Hunt and Murray, we show from the numerical simulations how this system executes a form of the idealized CDC. We also briefly discuss various simulations that show how other properties of living systems such as migration towards more favorable regions or the emergence of effective Lotka-Volterra populations are accounted for by this general and unified view from the "top" of the physics of life. The paper ends with some discussion, conclusions, and comments on some selected directions for future research. The mathematical techniques and powerful simulation tools we use are all well established and presented in a "didactical" style. We include a very rich but concise SI where the numerical details are thoroughly discussed in a way that anyone interested in studying or extending the results would be able to do so.

Improvement of a Surfactant Blend for Enhanced Oil Recovery in Carbonate Reservoirs by Means of an Ionic Liquid.

The promising experimental performance of surfactant blends encourages their use in recovering the large quantity of crude oil still remaining in carbonate reservoirs. Phase behavior studies were carried out in this work to propose a blend for practical application. To that aim, the surfactants dioctyl sulfosuccinate sodium (AOT) and polyoxyethylene(8) octyl ether carboxylic acid (Akypo LF2) were mixed. A formulation consisting of 1 wt% of AOT50wt%/LF250wt% blend in synthetic sea water (SSW) led to a low value of interfacial tension with crude oil of 1.50·10-2 mN/m, and 0.42 mg/grock of dynamic adsorption. A moderate additional oil recovery (7.3% of the original oil in place) was achieved in a core flooding test. To improve this performance, the surface-active ionic liquid 1-dodecyl-3-methylimidazolium bromide ([C12mim]Br) was added to the system. The electrostatic interactions between the oppositely charged surfactants (AOT and [C12mim]Br) led to a higher surface activity. Thus, a formulation consisting of 0.8 wt% of AOT20.7wt%/[C12mim]Br25.3wt%/LF254wt% in SSW reduced the interfacial tension and surfactant adsorption achieved with the binary blend to 1.14 × 10-2 mN/m and 0.21 mg/grock, respectively. The additional oil recovery achieved with the blend containing the ionic liquid was 11.5% of the original oil in place, significantly improving the efficiency of the binary blend.

A bottom-up approach to construct or deconstruct a fluid instability.

Fluid instabilities have been the subject of study for a long time. Despite all the extensive knowledge, they still constitute a serious challenge for many industrial applications. Here, we experimentally consider an interface between two fluids with different viscosities and analyze their relative displacement. We designed the contents of each fluid in such a way that a chemical reaction takes place at the interface and use this reaction to suppress or induce a fingering instability at will. This process describes a road map to control viscous fingering instabilities in more complex systems via interfacial chemical reactions.

Haemodynamic-dependent arrest of circulating tumour cells at large blood vessel bifurcations as new model for metastasis.

Homing of circulating tumour cells (CTC) at distant sites represents a critical event in metastasis dissemination. In addition to physical entrapment, probably responsible of the majority of the homing events, the vascular system provides with geometrical factors that govern the flow biomechanics and impact on the fate of the CTC. Here we mathematically explored the distribution of velocities and the corresponding streamlines at the bifurcations of large blood vessel and characterized an area of low-velocity at the carina of bifurcation that favours the residence of CTC. In addition to this fluid physics effect, the adhesive capabilities of the CTC provide with a biological competitive advantage resulting in a marginal but systematic arrest as evidenced by dynamic in vitro recirculation in Y-microchannels and by perfusion in in vivo mice models. Our results also demonstrate that viscosity, as a main determinant of the Reynolds number that define flow biomechanics, may be modulated to limit or impair CTC accumulation at the bifurcation of blood vessels, in agreement with the apparent positive effect observed in the clinical setting by anticoagulants in advanced oncology disease.

Risk evaluation at municipality level of a COVID-19 outbreak incorporating relevant geographic data: the study case of Galicia.

The COVID-19 pandemic was an inevitable outcome of a globalized world in which a highly infective disease is able to reach every country in a matter of weeks. While lockdowns and strong mobility restrictions have proven to be efficient to contain the exponential transmission of the virus, its pervasiveness has made it impossible for economies to maintain this kind of measures in time. Understanding precisely how the spread of the virus occurs from a territorial perspective is crucial not only to prevent further infections but also to help with policy design regarding human mobility. From the large spatial differences in the behavior of the virus spread we can unveil which areas have been more vulnerable to it and why, and with this information try to assess the risk that each community has to suffer a future outbreak of infection. In this work we have analyzed the geographical distribution of the cumulative incidence during the first wave of the pandemic in the region of Galicia (north western part of Spain), and developed a mathematical approach that assigns a risk factor for each of the different municipalities that compose the region. This risk factor is independent of the actual evolution of the pandemic and incorporates geographic and demographic information. The comparison with empirical information from the first pandemic wave demonstrates the validity of the method. Our results can potentially be used to design appropriate preventive policies that help to contain the virus.

Highly viscous fluid displaced by a chemically controlled reactive interface.

Displacement of a viscous fluid by a less viscous one is a challenging problem that usually involves the formation of interfacial digitations propagating into each one of the fluids, mixing them and preventing their normal displacement. We propose in this manuscript a protocol that is implemented via numerical simulation of the corresponding equations to improve the efficiency of the displacement. We consider a chemically active interface between the two chemically active fluids that produce a large viscosity interface that facilitates the process. All the relevant parameters of the mechanism are numerically analyzed aiming to optimize the efficiency of the method.

Optimal control of the COVID-19 pandemic: controlled sanitary deconfinement in Portugal.

The COVID-19 pandemic has forced policy makers to decree urgent confinements to stop a rapid and massive contagion. However, after that stage, societies are being forced to find an equilibrium between the need to reduce contagion rates and the need to reopen their economies. The experience hitherto lived has provided data on the evolution of the pandemic, in particular the population dynamics as a result of the public health measures enacted. This allows the formulation of forecasting mathematical models to anticipate the consequences of political decisions. Here we propose a model to do so and apply it to the case of Portugal. With a mathematical deterministic model, described by a system of ordinary differential equations, we fit the real evolution of COVID-19 in this country. After identification of the population readiness to follow social restrictions, by analyzing the social media, we incorporate this effect in a version of the model that allow us to check different scenarios. This is realized by considering a Monte Carlo discrete version of the previous model coupled via a complex network. Then, we apply optimal control theory to maximize the number of people returning to "normal life" and minimizing the number of active infected individuals with minimal economical costs while warranting a low level of hospitalizations. This work allows testing various scenarios of pandemic management (closure of sectors of the economy, partial/total compliance with protection measures by citizens, number of beds in intensive care units, etc.), ensuring the responsiveness of the health system, thus being a public health decision support tool.

Incorporating social opinion in the evolution of an epidemic spread.

The evolution of the COVID19 pandemic worldwide has shown that the most common and effective strategy to control it used worldwide involve imposing mobility constrains to the population. A determinant factor in the success of such policies is the cooperation of the population involved but this is something, at least, difficult to measure. In this manuscript, we propose a method to incorporate in epidemic models empirical data accounting for the society predisposition to cooperate with the mobility restriction policies.

Interface Fingering Instability Triggered by a Density-Coupled Oscillatory Chemical Reaction via Precipitation.

A density fingering hydrodynamic instability is triggered by a chemical reaction at the interface between two fluids. The density instability is controlled by the density gradient between both solutions, while the excitability of the bubble-free Belousov-Zhabotinsky-1,4-cyclohexanedione (BZ-CHD) oscillatory chemical reaction controls the importance of the chemistry in the system. Both parameters are thoroughly analyzed, and the mechanism underlying the instability is unveiled. The experimental observations lead us to modify the existing and accepted models for the BZ-CHD reaction within this context. The important role played by precipitation is considered in this context and included into the model. The modified kinetic model once coupled with fluid dynamics along with the precipitation mechanism was able to reproduce the experimental observations.

Resonant Behavior in a Periodically Forced Nonisothermal Oregonator.

Nonisothermal chemical oscillators are poorly studied systems because chemical oscillations are conventionally studied under isothermal conditions. Coupling chemical reactions with heat generation and removal in a nonisothermal oscillatory system can lead to a highly nontrivial nonlinear dynamic behavior. For the current study, we considered the three-variable Oregonator model with the temperature incorporated as a variable (not a parameter), thus adding an energy balance to the set of equations. The effect of temperature on reaction rates is included through the temperature-dependent reaction rate coefficients (Arrhenius law). To model a continuous operation in a laboratory environment, the system was subjected to external forcing through the coolant temperature and infrared irradiation. By conducting numerical simulations and parametric studies, we found that the system is capable of a resonant behavior exhibiting induced oscillations. Our findings indicate that an external source of heat (e.g., via an infrared light emitting diode) can be used to induce a Hopf bifurcation under resonant conditions in an experimental Belousov-Zhabotinsky reactor.

Turing patterns mediated by network topology in homogeneous active systems.

Mechanisms of pattern formation-of which the Turing instability is an archetype-constitute an important class of dynamical processes occurring in biological, ecological, and chemical systems. Recently, it has been shown that the Turing instability can induce pattern formation in discrete media such as complex networks, opening up the intriguing possibility of exploring it as a generative mechanism in a plethora of socioeconomic contexts. Yet much remains to be understood in terms of the precise connection between network topology and its role in inducing the patterns. Here we present a general mathematical description of a two-species reaction-diffusion process occurring on different flavors of network topology. The dynamical equations are of the predator-prey class that, while traditionally used to model species population, has also been used to model competition between antagonistic features in social contexts. We demonstrate that the Turing instability can be induced in any network topology by tuning the diffusion of the competing species or by altering network connectivity. The extent to which the emergent patterns reflect topological properties is determined by a complex interplay between the diffusion coefficients and the localization properties of the eigenvectors of the graph Laplacian. We find that networks with large degree fluctuations tend to have stable patterns over the space of initial perturbations, whereas patterns in more homogenous networks are purely stochastic.

Urbanity and the dynamics of language shift in Galicia.

Sociolinguistic phenomena often involve interactions across different scales and result in social and linguistic changes that can be tracked over time. Here, we focus on the dynamics of language shift in Galicia, a bilingual community in northwest Spain. Using historical data on Galician and Spanish speakers, we show that the rate at which shift dynamics unfold correlates inversely with the internal complexity of a region (approximated by the proportion of urban area). Less complex areas converge faster to steady states, while more complex ones sustain transitory dynamics longer. We further explore the contextual relevance of each region within the network of regions that constitute Galicia. The network is observed to sustain or reverse the dynamic rates. This model can introduce a competition between the internal complexity of a region and its contextual relevance in the network. Harnessing these sociodynamic features may prove useful in policy making to limit conflicts.