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Despite the growing numbers of forcibly displaced persons worldwide, many people living under conflict choose not to flee. Individuals face two lotteries - staying or leaving - characterized by two distributions of potential outcomes. This paper proposes to model the choice between these two lotteries using quantile maximization as opposed to expected utility theory. The paper posits that risk-averse individuals aim at minimizing losses by choosing the lottery with the best outcome at the lower end of the distribution, whereas risk-tolerant individuals aim at maximizing gains by choosing the lottery with the best outcome at the higher end of the distribution. Using a rich set of household and conflict panel data from Nigeria, the paper finds that risk-tolerant individuals have a significant preference for staying and risk-averse individuals have a significant preference for fleeing, in line with the predictions of the quantile maximization model. These findings are in contrast to findings on economic migrants, and call for separate policies toward economic and forced migrants.

The Israeli-Palestinian conflict started on 7 October 2023, have resulted thus far to over 48,000 people killed including more than 17,000 children with a majority from Gaza, more than 30,000 people injured, over 10,000 missing, and over 1 million people displaced, fleeing conflict zones. The infrastructure damage includes the 87\% of housing units, 80\% of public buildings and 60\% of cropland 17 out of 36 hospitals, 68\% of road networks and 87\% of school buildings damaged. This conflict has as well launched an online discussion across various social media platforms. Telegram was no exception due to its encrypted communication and highly involved audience. The current study will cover an analysis of the related discussion in relation to different participants of the conflict and sentiment represented in those discussion. To this end, we prepared a dataset of 125K messages shared on channels in Telegram spanning from 23 October 2025 until today. Additionally, we apply the same analysis in two publicly available datasets from Twitter containing 2001 tweets and from Reddit containing 2M opinions. We apply a volume analysis across the three datasets, entity extraction and then proce

When `cyber' is used as a prefix, attention is typically drawn to the technological and spectacular aspects of war and conflict -- and, by extension, security. We offer a different approach to engaging with and understanding security in such contexts, by foregrounding the everyday -- mundane -- experiences of security within communities living with and fleeing from war. We do so through three vignettes from our field research in Colombia, Lebanon and Sweden, respectively, and by highlighting the significance of ethnography for security research with communities living in regions afflicted by war. We conclude by setting out a call to action for security researchers and practitioners to consider such lived experiences in the design of security technology that aims to cater to the needs of communities in `global conflict and disaster regions'.

Extreme weather events are projected to intensify global migration, increase resource competition, and amplify socio-spatial phenomena, including intergroup conflicts, socioeconomic inequalities, and unplanned displacements, among others. Addressing these challenges requires consolidating heterogeneous data to identify, estimate, and predict the dynamical process behind climate-induced movements. We propose a novel hybrid approach to reconstruct hazard-induced displacements by analysing the statistical properties of a diffusion process (walks) that explores the spatial network constructed from real displacements. The likely trajectories produced by the walks inform the typical journey of individuals, identifying potential hazards that may be encountered when fleeing high-risk areas. As a proof of concept, we apply this method to Somalia's detailed displacement tracking matrix, containing 20,220 movements dating from February 8 to June 18, 2025. We reconstruct the likely routes that displaced persons could have taken when fleeing areas affected by conflict or climate hazards. We find that individuals using the most likely paths based on current flows would experience mainly droughts

Wildlife monitoring with drones must balance competing demands: approaching close enough to capture behaviorally-relevant video while avoiding stress responses that compromise animal welfare and data validity. Human operators face a fundamental attentional bottleneck: they cannot simultaneously control drone operations and monitor vigilance states across entire animal groups. By the time elevated vigilance becomes obvious, an adverse flee response by the animals may be unavoidable. To solve this challenge, we present an edge-native, behavior-adaptive drone system for wildlife monitoring. This configurable decision-support system augments operator expertise with automated group-level vigilance monitoring. Our system continuously tracks individual behaviors using YOLOv11m detection and YOLO-Behavior classification, aggregates vigilance states into a real-time group stress metric, and provides graduated alerts (alert vigilance to flee response) with operator-tunable thresholds for context-specific calibration. We derive service-level objectives (SLOs) from video frame rates and behavioral dynamics: to monitor 30fps video streams in real-time, our system must complete detection and cla

This paper investigates the encirclement control problem involving two groups using a non-cooperative differential game approach. The active group seeks to chase and encircle the passive group, while the passive group responds by fleeing cooperatively and simultaneously encircling the active group. Instead of prescribing an expected radius or a predefined path for encirclement, we focus on the whole formation manifold of the desired relative configuration, two concentric circles, by allowing permutation, rotation, and translation of players. The desired relative configurations arise as the steady state resulting from Nash equilibrium strategies and are achieved in an intrinsic way by designing the interaction graphs and weight function of each edge. Furthermore, the asymptotic convergence to the desired manifold is guaranteed. Finally, numerical simulations demonstrate encirclement and counter-encirclement scenarios, verifying the effectiveness of our strategies.

Integration of diverse data will be a pivotal step towards improving scientific explorations in many disciplines. This work establishes a vision-language model (VLM) that encodes videos with text input in order to classify various behaviors of a mouse existing in and engaging with their environment. Importantly, this model produces a behavioral vector over time for each subject and for each session the subject undergoes. The output is a valuable dataset that few programs are able to produce with as high accuracy and with minimal user input. Specifically, we use the open-source Qwen2.5-VL model and enhance its performance through prompts, in-context learning (ICL) with labeled examples, and frame-level preprocessing. We found that each of these methods contributes to improved classification, and that combining them results in strong F1 scores across all behaviors, including rare classes like freezing and fleeing, without any model fine-tuning. Overall, this model will support interdisciplinary researchers studying mouse behavior by enabling them to integrate diverse behavioral features, measured across multiple time points and environments, into a comprehensive dataset that can addr

Migration patterns are complex and context-dependent, with the distances migrants travel varying greatly depending on socio-economic and demographic factors. While global migration studies often focus on Western countries, there is a crucial gap in our understanding of migration dynamics within the African continent, particularly in West Africa. Using data from over 60,000 individuals from eight West African countries, this study examines the determinants of migration distance in the region. Our analysis reveals a bimodal distribution of migration distances: while most migrants travel locally within a hundred km, a smaller yet significant portion undertakes long-distance journeys, often exceeding 3,000 km. Socio-economic factors such as employment status, marital status and level of education play a decisive role in determining migration distances. Unemployed migrants, for instance, travel substantially farther (1,467 km on average) than their employed counterparts (295 km). Furthermore, we find that conflict-induced migration is particularly variable, with migrants fleeing violence often undertaking longer and riskier journeys. Our findings highlight the importance of considering

Gathering information about where to migrate is an important part of the migration process, especially during forced migration, when people must make rapid decisions under uncertainty. This study examines how forced migration relates to online information-seeking on Wikipedia. Focusing on the 2022 Russian invasion of Ukraine, we analyze how the resulting refugee crisis, which led to over six million Ukrainians fleeing across Europe, shaped views of Wikipedia articles about European cities. We compare changes in views of Ukrainian-language Wikipedia articles, used as a proxy for information-seeking by Ukrainians, with those in four other language editions. Our findings show that views of Ukrainian-language articles about European cities correlate more strongly with the number of Ukrainian refugees applying for temporary protection in European countries than views in other languages. Because Poland and Germany became the main destinations for refugees, we examine these countries more closely and find that applications for temporary protection in Polish and German cities are also more strongly correlated with views of their Ukrainian-language Wikipedia articles. We further analyze the

When approached by predators, prey must decide whether to flee or remain and fight. The economics of such decisions are underlain by the trade-off between current and residual fitness. The trade-off predicts that (i) breeders should be less prone than non-breeders to flee from approaching predators, as breeders can lose their investment into current reproduction; (ii) among breeders, parents should increasingly defend their offspring with increasing investment into the brood (brood value hypothesis), at least until the offspring can independently take part in anti-predator defenses; and (iii) for a similar investment into reproduction, breeders with lower perspectives to fledge or wean their young should invest less into offspring defense. We tested these predictions in a colonially breeding seabird, the king penguin (Aptenodytes patagonicus). Specifically, we considered how antipredator behaviors varied according to life history stage (molting, courting, breeding), offspring age and their dependence on parents for antipredator defenses, and the timing of breeding, with late breeders being very unlikely to fledge offspring in this species. Using non-lethal human approaches to mimic

Conventional wisdom holds that a misaligned artificial superintelligence (ASI) will destroy humanity. But the problem of constraining a powerful agent is not new. I apply classic economic logic of interjurisdictional competition, all-encompassing interest, and trading on credit to the threat of misaligned ASI. Even while granting AI-safety canon some of its strongest assumptions, I show that an acquisitive ASI refrains from full predation under surprisingly weak conditions. When humans can flee to rivals, inter-ASI competition creates a market that tempers predation. When trapped by a monopolist ASI, its "encompassing interest" in humanity's output makes it a rational autocrat rather than a ravager. And when the ASI has no long-term stake, our ability to withhold future output incentivizes it to trade on credit rather than steal. In each extension, humanity's welfare progressively worsens. But each case suggests that catastrophe is not a foregone conclusion. The dismal science, ironically, offers an optimistic take on our superintelligent future.

Chase-and-run dynamics, in which one population pursues another that flees from it, are found throughout nature, from predator-prey interactions in ecosystems to the collective motion of cells during development. Intriguingly, in many of these systems, the movement is not straight; instead, 'runners' veer off at an angle from their pursuers. This angled movement often exhibits a consistent left-right asymmetry, known as lateralisation or chirality. Inspired by such phenomena in zebrafish skin patterns and evasive animal motion, we explore how chirality shapes the emergence of patterns in nonlocal (integro-differential) advection-diffusion models. We extend such models to allow movement at arbitrary angles, uncovering a rich landscape of behaviours. We find that chirality can enhance pattern formation, suppress oscillations, and give rise to entirely new dynamical structures, such as rotating pulses of chasers and runners. We also uncover how chase-and-run dynamics can cause populations to mix or separate. Through linear stability analysis, we identify physical mechanisms that drive some of these effects, whilst also exposing striking limitations of this theory in capturing more com

An asymptotically flat hairy black hole (HBH) can exhibit distinct characteristics when compared to the Schwarzschild black hole, due to the evasion of no-hair theorem by minimally coupling the Einstein gravity with a scalar potential which possesses asymmetric vacua, i.e, a false vacuum $(φ=0)$ and a true vacuum $(φ=φ_1)$. In this paper, we investigate the geodesic motion of both massive test particles and photons in the vicinity of HBH with $φ_1=0.5$ and $φ_1=1.0$ by analyzing their effective potentials derived from the geodesic equation. By fixing $φ_1$, the effective potential of a massive test particle increases monotonically when its angular momentum $L$ is very small. When $L$ increases to a critical value, the effective potential possesses an inflection point which is known as the innermost stable of circular orbit (ISCO), where the test particle can still remain stable in a circular orbit with a minimal radius without being absorbed by the HBH or fleeing to infinity. Beyond the critical value of $L$, the effective potential possesses a local minimum and a local maximum, indicating the existence of unstable and stable circular orbits, respectively. Moreover, the HBH possess

Controlling multi-agent systems is a persistent challenge in organismal, robotic and social collectives, especially when agents exhibit stochastic indecisiveness -- frequently switching between conflicting behavioral rules. Here, we investigate the control of such noisy indecisive collectives through the lens of century-old sheepdog trials, where small groups of sheep exhibit unpredictable switching between fleeing and following behaviors. Unlike cohesive large flocks, these small indecisive groups are difficult to control, yet skilled dog-handler teams excel at both herding and precisely splitting them (shedding) on demand. Using a stochastic model, we introduce two central parameters -- pressure (stimulus intensity) and lightness (response isotropy) -- to simulate and quantify herding and shedding dynamics. Surprisingly, we find that stochastic indecisiveness, typically perceived as a challenge, can be leveraged as a critical tool for efficient control, enabling controlled herding and splitting of noisy groups. Building on these insights, we develop the Indecisive Swarm Algorithm (ISA) for artificial agents and benchmark its performance against standard algorithms, including the

Recent work has identified cosmic ray events as an error source limiting the lifetime of quantum data. These errors are correlated and affect a large number of qubits, leading to the loss of data across a quantum chip. Previous works attempting to address the problem in hardware or by building distributed systems still have limitations. We approach the problem from a different perspective, developing a new hybrid hardware-software-based strategy based on the 2-D surface code, assuming the parallel development of a hardware strategy that limits the phonon propagation radius. We propose to flee the area: move the logical qubits far enough away from the strike's epicenter to maintain our logical information. Specifically, we: (1) establish the minimum hardware requirements needed for our approach; (2) propose a mapping for moving logical qubits; and (3) evaluate the possible choice of the code distance. Our analysis considers two possible cosmic ray events: those far from both ``holes'' in the surface code and those near or overlapping a hole. We show that the probability that the logical qubit will be destroyed can be reduced from 100% to the range 4% to 15% depending on the time req

We study stability issue of reset and impulsive switched systems. We find time constraints (dwell time and flee time) on switching signals which stabilize a given reset switched system. For a given collection of matrices, we find an assignment of resets and time constraints on switching signals which guarantee stability of the reset switched system. Similar results are obtained for impulsive switched systems as well. Two techniques, namely, analysis of flow of the system and the multiple Lyapunov function approach is used to obtain the results. The results are later generalized to obtain mode-dependent time constraints for stability of these systems.

Cops and Robber is a family of two-player games played on graphs in which one player controls a number of cops and the other player controls a robber. In alternating turns, each player moves (all) their figures. The cops try to capture the robber while the latter tries to flee indefinitely. In this paper we consider a variant of the game played on a planar graph where the robber moves between adjacent vertices while the cops move between adjacent faces. The cops capture the robber if they occupy all incident faces. We prove that a constant number of cops suffices to capture the robber on any planar graph of maximum degree $Δ$ if and only if $Δ\leq 4$.