Maurizio Porfiri

PURPOSE: Optical character recognition (OCR), a process that converts printed or handwritten text into machine-readable form, is widely used in assistive technology for people with blindness and low vision. Yet most evaluations rely on static datasets that do not reflect the challenges of mobile use. This study evaluated how OCR performance changes under static and walking conditions relevant to real-world navigation. METHODS: Static tests varied distance from 1-7 metres and viewing angle from 0°-75°. Dynamic tests examined the impact of motion by varying walking speed from 0.8 m/s to 1.8 m/s and compared head-mounted, shoulder-mounted, and handheld positions. We evaluated a smartphone and smart glasses, including the phone's main and ultra-wide cameras, across four OCR engines: Google Vision, PaddleOCR 3.0, EasyOCR, and Tesseract. Dynamic tests used PaddleOCR 3.0. Accuracy was computed at the character level using the Levenshtein ratio against manually defined ground truth. RESULTS: Recognition accuracy declined with increased walking speed and wider viewing angles. Google Vision achieved the highest overall accuracy, with PaddleOCR close behind as the strongest open-source alternative. Across devices, the phone's main camera achieved the highest accuracy, and a shoulder-mounted placement yielded the highest average among body positions; however, differences among shoulder, head, and hand were not statistically significant. CONCLUSION: OCR performance depends on the recognition engine, camera hardware, field of view, device placement, and user motion. OCR systems for navigation should be evaluated under dynamic, mobility-relevant conditions rather than static images alone and designed to balance coverage, recognition accuracy, and practical deployment.

Abstract Euplectella aspergillum is a deep-sea glass sponge that has attracted the interest of the scientific community for almost 150 years, for its surprising adaptations to the asperities of the abyss. The state-of-the-art on this organism focuses on specimens in isolation, but field observations question this premise. Footage from the abyss shows instances in which E. aspergillum live in bouquets comprising several organisms. Through high performance computing of the flow physics of E. aspergillum, we discover a complex hydrodynamic entanglement that favors downstream organisms at no cost to upstream ones. Such an interaction benefits the nutrition, reproduction, and resilience of the bouquet—the first instance of a hydrodynamic advantage that emerges due to purely passive interactions in a group.

The design of control systems for the spatial self-organization of mobile agents is an open challenge across several engineering domains, including swarm robotics and synthetic biology. Here, we propose a bio-inspired leader-follower solution, which is aware of energy constraints of mobile agents and is apt to deal with large swarms. Akin to many natural systems, control objectives are formulated for the entire collective, and leaders and followers are allowed to plastically switch their role in time. We frame a density control problem, modeling the agents’ population via a system of nonlinear partial differential equations. This approach allows for a compact description that inherently avoids the curse of dimensionality and improves analytical tractability. We derive analytical guarantees for the existence of desired steady-state solutions and their global stability for one-dimensional and higher-dimensional problems. We numerically validate our control methodology, offering support to the effectiveness, robustness, and versatility of our proposed bio-inspired control strategy.

How and why base vibration can stabilize an inverted pendulum has puzzled the scientific community for decades, until the work on dynamic stabilization by Pyotr Kapitza pointed at the alternation between unstable and stable modes as a pathway to stability. We report the discovery of a mechanical oscillator that switches between two unstable modes, has an unstable average, and, yet, can be dynamically stabilized. Our system is governed by a modified Meissner's model - a one-degree-of-freedom oscillator where both stiffness and damping are modulated through a square wave to switch between positive and negative values. We theoretically prove the existence of compact antiresonance windows and provide experimental evidence through a cantilever beam oscillator subject to magnetic and aerodynamic forcing. The prospect of dynamic stabilization in the absence of any stable feature has vast implications from network dynamical systems, to structural mechanics and robotics.

Network dynamical systems are ubiquitous in science and engineering. The most basic property of a network dynamical system is its size, which, for scalar dynamics, corresponds to the number of nodes. For linear network systems, recent studies have developed reliable tools for inferring the size of the system from perceptible dynamics (measurements of one or some of the network nodes) across multiple experiments. Here, we extend these tools to nonlinear network systems by putting forward a model-agnostic approach that combines clustering techniques, the use of detection matrices, and spectral analysis. The theoretical premise of the algorithm is that, under mild assumptions, the variation between the dynamics of some nodes across multiple measurements can be used to bound the variation between the dynamics of all nodes across the same measurements. By applying clustering techniques on perceptible dynamics, we identify nearby measurements, about which the variational dynamics are approximately linear and the use of the detection matrix is valid. From the spectrum of the detection matrix, we infer its rank, which corresponds to the size of the nonlinear network system. We demonstrate our approach via numerical experiments on different nonlinear network systems, including different types of hypergraphs. Whether nonlinearity comes from individual dynamics of the nodes or the interactions among them, it is rarely a feature that one can dismiss. Our work paves the way to infer the size of a nonlinear network system when governing equations are unknown and only limited data are accessible.

Whether in search of better trade opportunities or escaping wars, humans have always been on the move. For almost a century, mathematical models of human mobility have been instrumental in the quantification of commuting patterns and migratory fluxes. Equity is a common premise of most of these mathematical models, such that living conditions and job opportunities are assumed to be equivalent across cities. Growing inequalities in modern urban economy and pressing effects of climate change significantly strain this premise. Here, we propose a mobility model that is aware of inequalities across cities in terms of living conditions and job opportunities. Comparing results with real datasets, we show that the proposed model outperforms the state-of-the-art in predicting migration patterns in South Sudan and commuting fluxes in the United States. This model paves the way to critical research on resilience and sustainability of urban systems.

Floods can undermine long-term community viability by depressing housing markets and triggering property abandonment cycles. This study estimates the risk of housing abandonment by integrating traditional flood-risk frameworks with the concept of sub-replacement–a condition where the cost of repairing a house exceeds its market value. We propose a new risk metric that identifies whether a house enters a sub-replacement condition within a given time horizon. Our stochastic model is a time–homogeneous, discrete-time Markov process that incorporates flood hazard, housing exposure, physical vulnerability, and housing market dynamics. We apply the model to two U.S. communities–Pascagoula, Mississippi, and McGregor, Florida. These two communities exhibit similar flood hazard, exposure, and building vulnerability, but markedly different housing market conditions. Despite comparable Average Annual Losses (AAL), the number of houses expected to experience sub-replacement within the next three decades is twenty five times larger in Pascagoula than in McGregor. We also find that the FEMA 50\% rule–which mandates elevation when repair costs exceed 50\% of a home’s market value–reduces AAL by approximately 70\%, but increases sub-replacement risk in areas with depressed housing markets. This risk is especially concerning in Pascagoula, where lower housing prices increase the number of houses expected to enter sub-replacement in the next three decades by a factor of eight. Our findings show that incorporating housing market conditions into flood risk analysis is important for anticipating long-term recovery trajectories and prevent downward spirals of disinvestment and population loss.

Social media platforms have become a key tool for politicians to signal their policy positions and communicate about issues that are salient to them and their constituency. One such issue is gun violence. Grounded in framing and issue-attention cycle theories, this paper analyzes the response of members of the United States (US) Congress to mass shootings on social media. We analyzed 785,881 gun-related tweets from members of the 117th US Congress on X (formerly Twitter) between January 2021 and January 2023. We used logistic regression to model the main effects, implemented the PCMCI+ algorithm for causal discovery, and applied latent Dirichlet allocation topic modeling to evaluate the substantive differences between gun-related tweets from the two parties. Higher fatality counts were positively correlated with the probability of gun-related tweets by Congress members (OR=1.13, 95% CI=[1.12, 1.15], p < 0.001). A causal link was detected between mass shootings and subsequent legislators' activity on X (ρ=0.122, p=0.001). Democrats were more likely to tweet about guns following mass shootings than Republicans (OR=3.60, 95% CI=[3.03, 4.28], p < 0.001), with qualitative differences in tweet substance between parties (community, families, victims, and mass shootings themselves are recurrent topics for Democrats, while Second Amendment rights and crime are frequent for Republicans). The paper suggests that while mass shootings elevate the level of discussion on guns in Congress, they trigger different reactions depending on party affiliation. Congress members tend to focus on topics aligned with party issues, likely reducing the opportunity for policy-making alignment.

AIM: Sensory substitution devices (SSDs) can convert environmental information into an accessible format for people who are blind or have low vision (pBLV). Yet, current SSDs often passively deliver all of the information available with limited user control, potentially leading to confusion and/or cognitive overload. To address this issue, this work proposes a selective, gesture-controlled system intended to improve information relevance and reduce cognitive overload. METHODS: We present Point-To-Tell 2, a system that enables pBLV to privately and efficiently select which information to convey through simple pointing-based gestural control. By integrating a monocular camera with AI-driven pipelines for depth estimation, hand pose tracking, and object detection/segmentation, the system identifies the users' 3D pointing direction and announces the names and distances of objects as they are pointed at, thereby connecting an object's spatial position and identity through hand proprioception. RESULTS: Validation tests in controlled indoor environments show high hand pose tracking accuracy, ensuring reliable ray-casting and object selection despite declining object recognition at longer distances. Distance estimates are stable at close range, though a systematic bias is present. CONCLUSION: This work introduces and technically validates an assistive system designed to improve the usability of assistive technologies by focusing system feedback-potentially reducing users' cognitive load and enhancing their spatial comprehension by leveraging concurrent hand proprioception. Future work will involve user testing and expanding system features to further enhance its practicality across more diverse scenarios.

The inference of metabolic rate from behavioural measurements is an open question in fish biology. Here, we put forward a predictive model of zebrafish (Danio rerio) metabolic rate in still water from mouth opening and pectoral-fin beating. Our analysis revisits experimental results published in this journal, reprocessed to include information about the pectoral-fin beating. Using Cobb-Douglas function, we identify a positive (negative) correlation between metabolic rate and mouth opening amplitude (pectoral-fin amplitude), pointing at the interplay between buccal pumping and pectoral-fin stabilization.

Firearm injuries are a leading cause of death in the United States, surpassing fatalities from motor vehicle crashes. Despite this significant public health risk, Americans continue to purchase firearms in large quantities. Commonly cited drivers of firearm acquisition include fear of violent crime, fear of mass shootings, and panic-buying. Additionally, advocacy groups' activity on social media may capitalize on emotions like fear and influence firearm acquisition. The simultaneous effects of these variables have not been explored in a causal framework. In this study, we aim to elucidate the causal roles of media coverage of firearm laws and regulations, media coverage of mass shootings, media coverage of violent crimes, and the Twitter activity of anti- and proregulation advocacy groups in short-term firearm acquisition in the United States. We collect daily time series for these variables from 2012 to 2020 and employ the PCMCI+ framework to investigate the causal structures among them simultaneously. Our results indicate that the Twitter activity of antiregulation advocacy groups directly drives firearm acquisitions. We also find that media coverage of firearm laws and regulations and media coverage of violent crimes influence firearm acquisition. Although media coverage of mass shootings and online activity of proregulation organizations are potential drivers of firearm acquisition, in the short term, only the lobbying efforts of antiregulation organizations on social media and specific media coverage appear to influence individuals' decisions to purchase firearms.

The reproducibility crisis in bioscience, characterized by inconsistent study results, impedes our understanding of biological processes. Global collaborative studies offer a unique solution to this problem. Here, we present a global collaboration using the zebrafish (Danio rerio) novel tank test, a popular behavioral assay for anxiety-like responses. We analyzed data from 20 laboratories worldwide, focusing on housing conditions and experimental setups. Our study included 488 adult zebrafish, tested for 5 min, focusing on a variety of variables. Key findings show that female zebrafish exhibit more anxiety-like behavior than males, highlighting sex as a critical variable. Housing conditions, including higher stocking densities and specific feed types, also influenced anxiety levels. Optimal conditions (5 fish/L) and nutritionally rich feeds (for example, rotifers) mitigated anxiety-like behaviors. Environmental stressors, such as noise and transportation, significantly impacted behavior. We recommend standardizing testing protocols to account for sex differences, optimal stocking densities, nutritionally rich feeds and minimizing stressors to improve the reliability of zebrafish behavioral studies.

Impulsivity has been proposed as a key driver of obesity. However, evidence linking impulsivity and obesity has relied on the study of individual factors, with limited account for the urban attributes of obesogenic environments. Here, we investigate the relationship between obesity and impulsivity through urban scaling and causal discovery. For 915 cities in the United States of America, we study the prevalence of obesity in adults, attention deficit hyperactivity disorder (ADHD) in children, and relevant urban features. We observe sublinear scaling of obesity and ADHD with population size, these disorders being less prevalent in larger cities. By applying a causal discovery tool to the deviations of cities from the urban scaling laws, we identify an influence of ADHD on obesity, moderated by lifestyle. The strength of these associations is confirmed by individual-level data on a cohort of 19,333 children, wherein we observe that ADHD modulates obesity both directly and indirectly.

The deep-sea sponge <i>Euplectella aspergillum</i> showcases nature’s remarkable ability to adapt to the harshest environments. The skeletal structure of these deep-sea dwellers is optimized to offer both structural rigidity and stress mitigation. This is achieved through its unique structural motifs, exemplified by its hollow lattice structure surrounded by outer helical ridges. Numerical flow simulations unveiled the role of these structures in the optimization of the flow physics both within and outside the deep-sea sponge’s body, resulting in direct benefits for feeding, reproduction, and mechanical stability. Specifically, the helical ridges and lattice structure are responsible for increasing the fluid residence time in the body cavity and reducing the drag force experienced by the body. Although numerical simulations have provided valuable insight, there remains a gap in our ability to experimentally investigate the flow physics of this system. Here, we designed an experimental platform that allowed us to study the hydrodynamic performance of the skeletal adaptations of <i>Euplectella aspergillum</i>. We performed experiments using simplified 3D-printed mock-up models of the deep-sea sponge skeletal adaptations inside a water channel. We measured the drag force over a range of Reynolds numbers from 1000 to 5000 and analyzed its oscillation amplitude and frequency, as well as the average drag coefficient. The study integrates biomimetics and experimental mechanics to develop a deeper understanding of the hydrodynamics of deep-sea sponges. These results will inform the design of buildings, bridges, marine vessels, and other systems that need to effectively withstand hydrodynamic forces or utilize them in passive ventilation.

We address the problem of controlling the density of a large ensemble of follower agents by acting on a group of leader agents that interact with them. Using coupled partial integro-differential equations to describe leader and follower density dynamics, we establish feasibility conditions and develop two control architectures ensuring global stability. The first employs feed-forward control on the followers' and a feedback on the leaders' density. The second implements a dual feedback loop through a reference-governor that adapts the leaders' density based on both populations' measurements. Our methods, initially developed in a one-dimensional setting, are extended to multi-dimensional cases, and validated through numerical simulations for representative control applications, both for groups of infinite and finite size.

Ongoing efforts seek to unravel theories that can make simple, quantitative and reasonably accurate predictions of the morphological adaptive changes that arise with the size variation. Yet, relatively scant attention has been directed towards lateral undulatory locomotion. In the current study, we explore: (i) the constraints imposed by the variation of length and mass in viscous and dry friction environments on the cost of transport (COT) of lateral undulatory locomotion and (ii) the role of the body, environment and input oscillations in such an intricate interplay. In a dry friction environment, minimum COT correlates with stiffer and longer bodies, higher frictional anisotropy and angular amplitudes greater than approximately 10 o . Conversely, a viscous environment favours flexible long bodies, higher frictional anisotropy and angular amplitudes lower than approximately 30 o . In both environments, optimizing mass and maintaining low angular frequencies minimizes COT. Our conclusions are applicable only in the low-Reynolds-number regime, and it is essential to consider the interdependence of parameters when applying the generalized results. Our findings highlight musculoskeletal and biomechanical adaptations that animals may use to mitigate the consequences of size variation and to meet the energetic demands of lateral undulatory locomotion. These insights enhance foundational biomechanics knowledge while offering practical applications in robotics and ecology.

This article examines the long-term impacts of natural hazards caused by patterns of relocation into and out of hazard-exposed communities. We address two main questions: (1) what factors influence permanent relocation decisions in hazard-exposed communities? (2) What are the effects of relocation on the socio-economic and demographic characteristics of these communities? To answer these questions, we review studies on theoretical frameworks, empirical analyses, and simulation-based models. Relocation outcomes result from a complex interplay of household characteristics (e.g., wealth, risk perception, place attachment), community characteristics (e.g., economic opportunities, essential services), and government interventions (e.g., collective risk-reduction measures). The reviewed studies report mixed findings on demographic and socio-economic changes associated with permanent relocation. Large-scale analyses suggest that natural hazards have limited effects on pre-existing population trends, while more granular studies show that specific hazards—such as coastal flooding and sea level rise—can alter local dynamics. Effects on communities socio-economic characteristics also vary. Some communities experience post-hazard gentrification, while others face deepened vulnerabilities, with declining property values trapping residents in high-risk areas. We further review simulation-based models that examine hazard-related relocation and the socio-economic changes it can produce. These models often focus on specific aspects, such as individual decision-making, housing markets, or recovery patterns, without integrating all relevant factors. Finally, we identify key research gaps, including the need for more long-term studies on socio-economic changes in hazard-exposed communities, and greater focus on chronic, low-intensity hazards like tidal flooding.

Purpose: Navigating urban environments poses significant challenges for individuals who are blind or have low vision, especially in areas affected by construction. Construction zones introduce hazards such as uneven surfaces, barriers, hazardous materials, excessive noise, and altered routes that obstruct familiar paths and compromise safety. Although navigation tools assist in trip planning, they often overlook these temporary obstacles. Existing hazard detection systems also struggle with the visual variability of construction sites. Methods: We developed a computer vision--based assistive system integrating three modules: an open-vocabulary object detector to identify diverse construction-related elements, a YOLO-based model specialized in detecting scaffolding and poles, and an optical character recognition module to interpret construction signage. Results: In static testing at seven construction sites using images from multiple stationary viewpoints, the system achieved 88.56% overall accuracy. It consistently identified relevant objects within 2--10 meters and at approach angles up to 75$^{\circ}$. At 2--4 meters, detection was perfect (100%) across all angles. Even at 10 meters, six of seven sites remained detectable within a 15$^{\circ}$ approach. In dynamic testing along a 0.5-mile urban route containing eight construction sites, the system analyzed every frame of a first-person walking video. It achieved 87.26% accuracy in distinguishing construction from non-construction areas, rising to 92.0% with a 50-frame majority vote filter. Conclusion: The system can reliably detect construction sites in real time and at sufficient distances to provide advance warnings, enabling individuals with visual impairments to make safer mobility decisions such as proceeding with caution or rerouting.

PURPOSE: People with blindness and low vision (pBLV) face challenges in navigating. Mobility aids are crucial for enhancing independence and safety. This paper presents an electronic travel aid that leverages a haptic-based, higher-order sensory substitution approach called Virtual Whiskers, designed to help pBLV navigate obstacles effectively, efficiently, and safely. MATERIALS AND METHODS: Virtual Whiskers is equipped with a plurality of modular vibration units that operate independently to deliver haptic feedback to users. Virtual Whiskers features two navigation modes: open path mode and depth mode, each addressing obstacle negotiation from different perspectives. The open path mode detects and delineates a traversable area within an analyzed field of view and then guides the user in the most traversable direction with adaptive vibratory feedback. Depth mode assists users in negotiating obstacles by highlighting spatial areas with prominent obstacles; haptic feedback is generated by re-mapping proximity to vibration intensity. We recruited 10 participants with blindness or low vision for user testing of Virtual Whiskers. RESULTS: Both approaches reduce hesitation time (idle periods) and decrease the number of cane contacts with objects and walls. CONCLUSIONS: Virtual Whiskers is a promising obstacle negotiation strategy that demonstrates great potential to assist with pBLV navigation.

Detecting coupling in network dynamical systems from time series is an open problem in the physics of complex systems. In this Letter, we tackle this issue from a control-theoretic perspective. Drawing inspiration from Kalman's notion of observability, we argue the presence of directional coupling between two units, X→Y, when X is detected as an internal state from the measurement of Y. We illustrate this approach on a series of analytically tractable systems, showcasing how it overcomes limitations of state-of-the-art methods for network inference.

Curbs separate the edge of raised sidewalks from the street and are crucial to locate in urban environments as they help delineate safe pedestrian zones from dangerous vehicular lanes. However, the curbs themselves are also significant navigation hazards, particularly for people who are blind or have low vision (pBLV). The challenges faced by pBLV in detecting and properly orienting themselves for these abrupt elevation changes can lead to falls and serious injuries. Despite recent advancements in assistive technologies, the detection and early warning of curbs remains a largely unsolved challenge. This paper aims to tackle this gap by introducing a novel, multi-faceted sensory substitution approach hosted on a smart wearable; the platform leverages an RGB camera and an embedded system to capture and segment curbs in real time and provide early warning and orientation information. The system utilizes a YOLOv8 segmentation model which has been trained on our custom curb dataset to interpret camera input. The system output consists of adaptive auditory beeps, abstract sonifications, and speech, which convey curb distance and orientation. Through human-subjects experimentation, we demonstrate the effectiveness of the system as compared to the white cane. Results show that our system can provide advanced warning through a larger safety window than the cane, while offering nearly identical curb orientation information. Future enhancements will focus on expanding our curb segmentation dataset, improving distance estimations through advanced 3D sensors and AI-models, refining system calibration and stability, and developing user-centric sonification methods to cater for a diverse range of visual impairments.

In the realm of urban science, scaling laws are essential for understanding the relationship between city population and urban features, such as socioeconomic outputs. Ideally, these laws would be based on complete datasets; however, researchers often face challenges related to data availability and reporting practices, resulting in datasets that include only the highest observations of the urban features (top- k ). A key question that emerges is: Under what conditions can an analysis based solely on top- k observations accurately determine whether a scaling relationship is truly superlinear or sublinear? To address this question, we conduct a numerical study that explores how relying exclusively on reported values can lead to erroneous conclusions, revealing a selection bias that favors sublinear over superlinear scaling. In response, we develop a method that provides robust estimates of the minimum and maximum potential scaling exponents when only top- k observations are available. We apply this method to two case studies involving firearm violence, a domain notorious for its suppressed datasets, and we demonstrate how this approach offers a reliable framework for analyzing scaling relationships with censored data.

Abstract Fish swimming together in schools interact via multiple sensory pathways, including vision, acoustics and hydrodynamics, to coordinate their movements. Disentangling the specific role of each sensory pathway is an open and important question. Here, we propose an information-theoretic approach to dissect interactions between swimming fish based on their movement and the flow velocity at selected measurement points in the environment. We test the approach in a controlled mechanical system constituted by an actively pitching airfoil and a compliant flag that simulates the behaviour of two fish swimming in line. The system consists of two distinct types of interactions – hydrodynamic and electromechanical. By using transfer entropy of the measured time series, we unveil a strong causal influence of the airfoil pitching on the flag undulation with an accurate estimate of the time delay between the two. By conditioning the computation on the flow-speed information, recorded by laser Doppler velocimetry, we discover a significant reduction in transfer entropy, correctly implying the presence of a hydrodynamic pathway of interaction. Similarly, the electromechanical pathway of interaction is identified accurately when present. The study supports the potential use of information-theoretic methods to decipher the existence of different pathways of interaction between schooling fish.

Racial homophily refers to the tendency of individuals to associate with others of the same racial or ethnic background. A recent study found no evidence of racial homophily in responses to mass shooting data visualizations. To increase the likelihood of detecting an effect, we redesigned the experiment by replacing bar charts with anthropographics and expanding the sample size. In a crowdsourced study (N=720), we showed participants a pictograph of mass shooting victims in the United States, with victims from one of three racial groups (Hispanic, Black, or White) highlighted. Each participant was assigned a visualization highlighting either their own racial group or a different racial group, allowing us to assess the influence of racial concordance on changes in affect (emotion). We found that, across all conditions, racial concordance had a modest but significant effect on changes in affect, with participants experiencing greater negative affect change when viewing visualizations highlighting their own race. This study provides initial evidence that racial homophily can emerge in responses to data visualizations, particularly when using anthropographics.

Whether in search of better trade opportunities or escaping wars, humans have always been on the move. For almost a century, mathematical models of human mobility have been instrumental in the quantification of commuting patterns and migratory fluxes. Equity is a common premise of most of these mathematical models, such that living conditions and job opportunities are assumed to be equivalent across cities. Growing inequalities in modern urban economy and pressing effects of climate change significantly strain this premise. Here, we propose a mobility model that is aware of inequalities across cities in terms of living conditions and job opportunities. Comparing results with real datasets, we show that the proposed model outperforms the state-of-the-art in predicting migration patterns in South Sudan and commuting fluxes in the United States. This model paves the way to critical research on resilience and sustainability of urban systems.

This paper investigates the robustness of a novel high-dimensional continuification control method for complex multi-agent systems. We begin by formulating a partial differential equation describing the spatio-temporal density dynamics of swarming agents. A stable control action for the density is then derived and validated under nominal conditions. Subsequently, we discretize this macroscopic strategy into actionable velocity inputs for the system’s agents. Our analysis demonstrates the robustness of the approach beyond idealized assumptions of unlimited sensing and absence of perturbations.

Despite almost a century of research on energetics in biological systems, we still cannot explain energy regulation in social groups, like ant colonies. How do individuals regulate their collective activity without a centralized control system? What is the role of social interactions in distributing the workload amongst group members? And how does the group save energy by avoiding being constantly active? We offer new insight into these questions by studying an intuitive compartmental model, calibrated with and compared to data on ant colonies. The model describes a previously unexplored balance between positive and negative social feedback driven by individual activity: when activity levels are low, the presence of active individuals stimulates inactive individuals to start working; when activity levels are high, however, active individuals inhibit each other, effectively capping the proportion of active individuals at any one time. Through the analysis of the system's stability, we demonstrate that this balance results in energetic spending at the group level growing proportionally slower than the group size. Our finding is reminiscent of Kleiber's law of metabolic scaling in unitary organisms and highlights the critical role of social interactions in driving the collective energetic efficiency of group-living organisms.

Abstract Recently, Succar and Porfiri (Nature Cities 1(3):216–224, 2024) reported sublinear scaling for firearm ownership in the United States. Their analysis hinted at a causal role of prevalence of homicides and firearm accessibility on firearm ownership, supporting self-protection as a driver of firearm ownership. In this study, we propose a microscopic, individual-level model to explain these macroscopic, city-level findings. In the model, individuals dwell in a city and buy a gun if they experience a violent interaction and know a dealer. We examine the model from a network science perspective and show the emergence of sublinear scaling with an exponent matching empirical observations. Beyond scaling, the model provides accurate predictions of city rankings in terms of firearm ownership, underscoring the explanatory power of the self-protection theory.

The reproducibility crisis in bioscience, characterized by inconsistent study results, impedes our understanding of biological processes and global collaborative studies offer a unique solution. This study is the first global collaboration using the zebrafish (Danio rerio) novel tank test, a behavioral assay for anxiety-like responses. We analyzed data from 20 laboratories worldwide, focusing on housing conditions and experimental setups. Our study included 488 adult zebrafish, tested for 5 min, focusing on a variety of variables. Key findings show females exhibit more anxiety-like behavior than males, underscoring sex as a critical variable. Housing conditions, including higher stocking densities and specific feed types, influenced anxiety levels. Optimal conditions (5 fish/L) and nutritionally rich feeds (e.g., rotifers), mitigated anxiety-like behaviors. Environmental stressors, like noise and transportation, significantly impacted behavior. We recommend standardizing protocols to account for sex differences, optimal stocking densities, nutritionally rich feeds, and minimizing stressors to improve zebrafish behavioral study reliability.

BACKGROUND: Visual disability is a growing problem for many middle-aged and older adults. Conventional mobility aids, such as white canes and guide dogs, have notable limitations that have led to increasing interest in electronic travel aids (ETAs). Despite remarkable progress, current ETAs lack empirical evidence and realistic testing environments and often focus on the substitution or augmentation of a single sense. OBJECTIVE: This study aims to (1) establish a novel virtual reality (VR) environment to test the efficacy of ETAs in complex urban environments for a simulated visual impairment (VI) and (2) evaluate the impact of haptic and audio feedback, individually and combined, on navigation performance, movement behavior, and perception. Through this study, we aim to address gaps to advance the pragmatic development of assistive technologies (ATs) for persons with VI. METHODS: The VR platform was designed to resemble a subway station environment with the most common challenges faced by persons with VI during navigation. This environment was used to test our multisensory, AT-integrated VR platform among 72 healthy participants performing an obstacle avoidance task while experiencing symptoms of VI. Each participant performed the task 4 times: once with haptic feedback, once with audio feedback, once with both feedback types, and once without any feedback. Data analysis encompassed metrics such as completion time, head and body orientation, and trajectory length and smoothness. To evaluate the effectiveness and interaction of the 2 feedback modalities, we conducted a 2-way repeated measures ANOVA on continuous metrics and a Scheirer-Ray-Hare test on discrete ones. We also conducted a descriptive statistical analysis of participants' answers to a questionnaire, assessing their experience and preference for feedback modalities. RESULTS: Results from our study showed that haptic feedback significantly reduced collisions (P=.05) and the variability of the pitch angle of the head (P=.02). Audio feedback improved trajectory smoothness (P=.006) and mitigated the increase in the trajectory length from haptic feedback alone (P=.04). Participants reported a high level of engagement during the experiment (52/72, 72%) and found it interesting (42/72, 58%). However, when it came to feedback preferences, less than half of the participants (29/72, 40%) favored combined feedback modalities. This indicates that a majority preferred dedicated single modalities over combined ones. CONCLUSIONS: AT is crucial for individuals with VI; however, it often lacks user-centered design principles. Research should prioritize consumer-oriented methodologies, testing devices in a staged manner with progression toward more realistic, ecologically valid settings to ensure safety. Our multisensory, AT-integrated VR system takes a holistic approach, offering a first step toward enhancing users' spatial awareness, promoting safer mobility, and holds potential for applications in medical treatment, training, and rehabilitation. Technological advancements can further refine such devices, significantly improving independence and quality of life for those with VI.

Homophily refers to the tendency of individuals to associate with others who are similar to them in characteristics, such as, race, ethnicity, age, gender, or interests. In this paper, we investigate if individuals exhibit racial homophily when viewing visualizations, using mass shooting data in the United States as the example topic. We conducted a crowdsourced experiment (N=450) where each participant was shown a visualization displaying the counts of mass shooting victims, highlighting the counts for one of three racial groups (White, Black, or Hispanic). Participants were assigned to view visualizations highlighting their own race or a different race to assess the influence of racial concordance on changes in affect (emotion) and attitude towards gun control. While we did not find evidence of homophily, the results showed a significant negative shift in affect across all visualization conditions. Notably, political ideology significantly impacted changes in affect, with more liberal views correlating with a more negative affect change. Our findings underscore the complexity of reactions to mass shooting visualizations and suggest that future research should consider various methodological improvements to better assess homophily effects.

Fish schooling has attracted the interest of the scientific community for centuries. Energy savings have been long posited to be a key determinant for the emergence of schooling patterns. Yet, current methodologies do not allow the precise quantification of the metabolic rate of specific individuals within the school, typically leaving researchers with only a single, global measurement of metabolic rate for the collective. In this paper, we demonstrate the feasibility of inferring metabolic rate of swimming fish using the mouth-opening frequency, a simple proxy that can be scored utilizing video recordings in the laboratory or in the field, even for small fish. The mouth-opening frequency is independent of hydrodynamic interactions within the school, thereby mitigating potential confounding factors that arise when using locomotory measures associated with tail-beat motion. We assessed the reliability of mouth-opening frequency as a proxy for metabolic rate by conducting experiments on zebrafish (Danio rerio) using swimming respirometry. We varied the flow speed from 0.8 to 3.2 body lengths per second and extracted tail-beat motion and mouth opening from video recordings. Our results revealed a strong correlation between oxygen uptake and mouth-opening frequency for nonzero flow speeds but not in quiescent water. Contrary to our expectations, we did not find evidence in favor of the use of tail-beat frequency as a proxy for metabolic rate. Overall, our results open the door to the study of individual metabolic rates in fish schools without confounding factors related to hydrodynamic interactions.