Estimating hidden relationships in dynamical systems: Discovering drivers of infection rates of COVID-19

Discovering causal influences among internal variables is a fundamental goal of complex systems research. This paper presents a framework for uncovering hidden relationships from limited time-series data by combining methods from nonlinear estimation and information theory. The approach is based on two sequential steps: first, we reconstruct a more complete state of the underlying dynamical system, and second, we calculate mutual information between pairs of internal state variables to detail causal dependencies. Equipped with time-series data related to the spread of COVID-19 from the past three years, we apply this approach to identify the drivers of falling and rising infections during the three main waves of infection in the Chicago metropolitan region. The unscented Kalman filter nonlinear estimation algorithm is implemented on an established epidemiological model of COVID-19, which we refine to include isolation, masking, loss of immunity, and stochastic transition rates. Through the systematic study of mutual information between infection rate and various stochastic parameters, we find that increased mobility, decreased mask use, and loss of immunity post sickness played a key role in rising infections, while falling infections were controlled by masking and isolation.

Home-care educational interventions to prevent complications in patients with Ventricular Assist Devices: a systematic review

Background

The implantation of ventricular assist devices is the only effective alternative to cardiac transplantation in patients with chronic heart failure, in terms of survival and quality of life. However, their implantation can lead to physical and psychological complications, potentially preventable, especially in the long term, through patients' education. This research aimed to summarize the current best evidence on educational strategies towards patients after implantation of ventricular assist devices, in home-care setting, to reduce the major related complications, namely driveline infections, gastrointestinal bleeding and psychological complications.

Study Design

Systematic review.

Methods

Title and abstract selection, full-text screening, study quality assessment, and data extraction followed the PRISMA protocol and the Cochrane Handbook for Systematic Reviews of Interventions. The search was conducted through consultation of databases such as Medline, Scopus, EMBASE, and Web of Science, during the period from March 2022 to December 2022, in relation to English-language articles, from search strings processing and inclusion and exclusion criteria.

Results

Of the 1,231 items identified, 9 were selected because consistent with the inclusion criteria. The most effective educational interventions toward patients with ventricular assist devices were identified, delivered by multidisciplinary teams coordinated by a professional expert in management of ventricular assist devices, and regularly conducted. In particular, gastrointestinal bleeding and driveline infections could be prevented and reduced by complex, multimodal educational interventions, including telephone and app interventions. Educational strategies based on verbal instructions, hands-on demonstrations, innovative technologies, and active involvement of families/caregivers were particularly effective in preventing psychological complications.

Conclusions

Investing time and resources in educating patients with ventricular assist devices is mandatory, given the significant impact of educational outcomes on complications' reduction. Moreover, educational interventions geared towards patient's psychological well-being, brings positive outcomes on patient's compliance too, resulting in promising clinical outcomes. However, more in-depth research is needed, to support professionals in developing effective educational plans for such fragile and complex patients.

Molecular dynamics of ionic polymer-metal composites

Ionic polymer-metal composites (IPMCs) constitute a promising class of soft, active materials with potentially ubiquitous use in science and engineering. Realizing the full potential of IPMCs calls for a deeper understanding of the mechanisms underpinning their most intriguing characteristics: the ability to deform under an electric field and the generation of a voltage upon mechanical deformation. These behaviours are tightly linked to physical phenomena at the level of atoms, including rearrangements of ions and molecules, along with the formation of sub-nanometre thick double layers on the surface of the metal electrodes. Several continuum theories have been developed to describe these phenomena, but their experimental and theoretical validation remains incomplete. IPMC modelling at the atomistic scale could beget valuable support for these efforts, by affording granular analysis of individual atoms. Here, we present a simplified atomistic model of IPMCs based on classical molecular dynamics. The three-dimensional IPMC membrane is constrained by two smooth walls, a simplified analogue of metal electrodes, impermeable only to counterions. The electric field is applied as an additional force acting on all the atoms. We demonstrate the feasibility of simulating counterions' migration and pile-up upon the application of an electric field, similar to experimental observations. By analysing the spatial configuration of atoms and stress distribution, we identify two mechanisms for stress generation. The presented model offers new insight into the physical underpinnings of actuation and sensing in IPMCs. This article is part of the theme issue 'Progress in mesoscale methods for fluid dynamics simulation'.

Decoding collective communications using information theory tools

Organisms have evolved sensory mechanisms to extract pertinent information from their environment, enabling them to assess their situation and act accordingly. For social organisms travelling in groups, like the fish in a school or the birds in a flock, sharing information can further improve their situational awareness and reaction times. Data on the benefits and costs of social coordination, however, have largely allowed our understanding of why collective behaviours have evolved to outpace our mechanistic knowledge of how they arise. Recent studies have begun to correct this imbalance through fine-scale analyses of group movement data. One approach that has received renewed attention is the use of information theoretic (IT) tools like mutual information, transfer entropy and causation entropy, which can help identify causal interactions in the type of complex, dynamical patterns often on display when organisms act collectively. Yet, there is a communications gap between studies focused on the ecological constraints and solutions of collective action with those demonstrating the promise of IT tools in this arena. We attempt to bridge this divide through a series of ecologically motivated examples designed to illustrate the benefits and challenges of using IT tools to extract deeper insights into the interaction patterns governing group-level dynamics. We summarize some of the approaches taken thus far to circumvent existing challenges in this area and we conclude with an optimistic, yet cautionary perspective.

Flow monitoring with a camera: a case study on a flood event in the Tiber River

Monitoring surface water velocity during flood events is a challenging task. Techniques based on deploying instruments in the flow are often unfeasible due to high velocity and abundant sediment transport. A low-cost and versatile technology that provides continuous and automatic observations is still not available. Among remote methods, large-scale particle image velocimetry (LSPIV) is an optical method that computes surface water velocity maps from videos recorded with a camera. Here, we implement and critically analyze findings obtained from a recently introduced LSPIV experimental configuration during a flood event in the Tiber River at a cross section located in the center of Rome, Italy. We discuss the potential of LSPIV observations in challenging environmental conditions by presenting results from three tests performed during the hydrograph flood peak and recession limb of the event for different illumination and weather conditions. The obtained surface velocity maps are compared to the rating curve velocity and to benchmark velocity values. Experimental findings show that optical methods should be preferred in extreme conditions. However, their practical implementation may be associated with further hurdles and uncertainties.

Fish and robot dancing together: bluefin killifish females respond differently to the courtship of a robot with varying color morphs

The experimental integration of bioinspired robots in groups of social animals has become a valuable tool to understand the basis of social behavior and uncover the fundamental determinants of animal communication. In this study, we measured the preference of fertile female bluefin killifish (Lucania goodei) for robotic replicas whose aspect ratio, body size, motion pattern, and color morph were inspired by adult male killifish. The motion of the fish replica was controlled via a robotic platform, which simulated the typical courtship behavior observed in killifish males. The positional preferences of females were measured for three different color morphs (red, yellow, and blue). While variation in preference was high among females, females tend to spend more time in the vicinity of the yellow painted robot replicas. This preference may have emerged because the yellow robot replicas were very bright, particularly in the longer wavelengths (550–700 nm) compared to the red and blue replicas. These findings are in agreement with previous observations in mosquitofish and zebrafish on fish preference for artificially enhanced yellow pigmentation.

Zebrafish response to robotic fish: preference experiments on isolated individuals and small shoals

Recently developed bioinspired robots imitate their live counterparts in both aspect and functionality. Nevertheless, whether these devices can be integrated within the ecological niche inspiring their design is seldom tested experimentally. An elemental research question concerns the feasibility of modulating spontaneous behaviour of animal systems through bioinspired robotics. The following study explores the possibility of engineering a robotic fish capable of influencing the behaviour of live zebrafish (Danio rerio) in a dichotomous preference test. While we observe that the preference for the robotic fish never exceeds the preference for a conspecific, our data show that the robot is successful in attracting both isolated individuals and small shoals and that such capability is influenced by its bioinspired features. In particular, we find that the robot's undulations enhance its degree of attractiveness, despite the noise inherent in the actuation system. This is the first experimental evidence that live zebrafish behaviour can be influenced by engineered robots. Such robotic platforms may constitute a valuable tool to investigate the bases of social behaviour and uncover the fundamental determinants of animal functions and dysfunctions.

Pinning control of complex networks via edge snapping

In this paper, we propose a hierarchy of novel decentralized adaptive pinning strategies for controlled synchronization of complex networks. This hierarchy addresses the fundamental need of selecting the sites to pin through a fully decentralized approach based on edge snapping. Specifically, we present three different strategies of increasing complexity which use a combination of network evolution and adaptation of the coupling and control gains. Theoretical results are complemented by extensive numerical investigations of the performance of the proposed strategies on a set of testbed examples.