Institute for Cross-Disciplinary Physics and Complex Systems

Abstract Philaenus spumarius represents the primary vector of the bacterium Xylella fastidiosa in Europe; hence, control measures are directed toward it, with a need for alternatives aligned with the agricultural sustainability criteria. Entomopathogenic ascomycetes (EA) show promise by infecting P. spumarius via endophytic colonization, though their sublethal effects on behavior remain understudied. This study assessed the effects of Metarhizium brunneum strain EAMa 01/58-Su on P. spumarius survival and feeding behavior, using the Electrical Penetration Graph technique. We provide the first evidence of endophytic colonization of olive plants by EA, occurring in both treated and distant untreated leaves. Foliar application enabled the dual establishment of M. brunneum as both epiphytic and endophytic, significantly disrupting vector feeding. Insects fed on M. brunneum sprayed leaves showed a more total and unsuccessful probing events, longer non-probing (np) periods, and reduced xylem contact (Xc) duration. Additionally, successful xylem probing (with xylem ingestion) was significantly delayed. Interestingly, a reduction in waveform N events and their duration in M. brunneum— non-sprayed leaves was detected, suggesting a systemic effect of the fungal colonization on the plant preference by the vector that could ultimately disrupt Xf retention mechanisms. In contrast, the drench application of M. brunneum in the olive saplings did not result in endophytic colonization or significant effects on the insect behavior compared with control plants. These findings provide the basis for future experiments on Xf transmission and support the potential of M. brunneum as a biocontrol agent beyond its conventional use against vector populations on cover crops.

Knee osteoarthritis (KOA) is characterized by pain, stiffness, and functional limitation. Aerobic exercise (AE) is a key treatment with proven benefits. To determine the most effective AE intensity for KOA. Searches were performed in seven databases, including randomized controlled trials with AE-only groups. Outcomes assessed were pain, walking and sit-to-stand performance, stiffness, and disability. Methodological quality and bias were evaluated. Bayesian random-effects network meta-analyses compared AE intensities, reporting standardized mean differences (Hedges' g) with 95% credible intervals. Certainty of evidence was rated using GRADE. Fifteen studies were included (mean PEDro score: 5.93), showing "some concerns" or "high risk" of bias. Two meta-analyses (pain and walking performance) were conducted. Comparisons between AE intensities showed non-significant, imprecise results with very low certainty of evidence. Evidence is insufficient to identify the optimal AE intensity for KOA. Limitations include high risk of bias, wide credible intervals, and reliance on indirect comparisons. In this context, clinicians should apply a structured, patient-centered approach to AE prescription, considering gradual progression and monitoring of tolerance, and combine AE with other recommended interventions. High-quality trials with direct comparisons of AE intensity should be conducted for this inconclusive gap.

Stroke disrupts brain function beyond focal lesions, altering multiscale temporal dynamics essential for information processing. We investigated intrinsic neural timescales (INT) and other properties of long-range temporal correlations, using longitudinal fMRI data from 15 ischemic stroke patients across 6 months, and compared them to age-matched controls. Results show that stroke patients exhibited significantly prolonged INT in multiple cortical regions, reflecting slowed temporal dynamics and disrupted hierarchy. These dynamic changes persisted through recovery and were more pronounced in patients with poor outcomes, especially within cognitive control networks. Computational modeling suggested that stroke-induced INT prolongation driven by heightened neuronal excitability reflects a dynamic shift towards criticality. Our findings position long-range temporal correlations and INT as potential biomarkers for monitoring and predicting functional recovery. This framework provides a novel perspective on stroke-induced brain changes and suggests avenues for targeted neurorehabilitation using interventions aiming at restoring intrinsic temporal dynamics.

Abstract Symmetry restrictions limit the types of tasks that can be achieved with a given set of quantum states. Therefore, any breaking of these symmetries could potentially be exploited as a resource for quantum communication. Here we demonstrate this operationally by certifying asymmetry in the configuration of the Bloch vectors of a set of three unknown qubit states within the dimensionally bounded prepare-and-measure scenario. To do this, we construct a linear witness from three simpler witnesses as building blocks, each featuring, along with two binary measurement settings, three preparations; two of them are associated with the certification task, while the third one serves as an auxiliary. The final witness is chosen to self-test some target configuration. We numerically derive a bound <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mi>Q</mml:mi> <mml:mrow> <mml:mtext>mirror</mml:mtext> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> for any mirror-symmetric configuration, thereby certifying asymmetry if this bound is exceeded (e.g. experimentally) for the unknown qubit configuration. We also consider the gap <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mo stretchy="false">(</mml:mo> <mml:msub> <mml:mi>Q</mml:mi> <mml:mrow> <mml:mtext>max</mml:mtext> </mml:mrow> </mml:msub> <mml:mo>−</mml:mo> <mml:msub> <mml:mi>Q</mml:mi> <mml:mrow> <mml:mtext>mirror</mml:mtext> </mml:mrow> </mml:msub> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> </mml:math> between the analytically derived overall quantum maximum <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mi>Q</mml:mi> <mml:mrow> <mml:mtext>max</mml:mtext> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> and the mirror-symmetric bound, and use it as a quantifier of asymmetry in the target configuration. Numerical optimization shows that the most asymmetric configuration then forms a right scalene triangle on the unit Bloch sphere. Finally, we implement our protocol on a public quantum processor, where a clear violation of the mirror-symmetric bound certifies asymmetry in the configuration of our experimental triple of qubit states.

ABSTRACTThe relationship between ecosystem complexity and stability remains unresolved and a mechanistic explanation for the stunning levels of biodiversity observed in communities and ecosystems is still lacking. The theoretical study of the stability of ecological communities has long been dominated by the assumption that populations are homogeneous. However, populations are structured, consisting of individuals that differ in multiple traits—such as size or developmental stage—with specific energetic demands and use of space and resources. Stage‐specific interactions, such as asymmetric competition for resources or predation targeting particular life stages, are widespread in nature and strongly shape ecological dynamics. Recent theoretical work further demonstrates that differences in juvenile versus adult foraging capacity and predation risk can promote the persistence of larger and more complex communities than those predicted by unstructured models. Here, we develop a general framework to integrate population structure into community stability analyses and show that stage‐dependent interactions are key to stability. Specifically, while cross‐stage predator–prey interactions enhance stability, competition across different stages destabilises the community. Our results offer new insights into the stability‐diversity paradox by showing that stage‐structured interactions can effectively increase the magnitude of negative feedbacks and compress the unstable region. Overall, we emphasise the critical role of population structure, an often neglected feature of natural systems, in the stability of ecological communities.

Abstract Open many-body quantum systems can exhibit intriguing nonequilibrium phases of matter, such as time crystals. In these phases, the state of the system spontaneously breaks the time-translation symmetry of the dynamical generator, which typically manifests through persistent oscillations of an order parameter. A paradigmatic model displaying such a symmetry breaking is the boundary time crystal (BTC), which has been extensively analyzed experimentally and theoretically. Despite the broad interest in these nonequilibrium phases, their thermodynamics and their fluctuating behavior remain largely unexplored, in particular for the case of coupled time crystals. In this work, we consider two interacting BTCs and derive a consistent interpretation of their thermodynamic behavior. We fully characterize their average dynamics and the behavior of their quantum fluctuations, which allows us to demonstrate the presence of quantum and classical correlations in both the stationary and the time-crystal phases displayed by the system. We furthermore exploit our theoretical derivation to explore possible applications of time crystals as quantum batteries, demonstrating their ability to efficiently store energy.

Time irreversibility refers to the property of some dynamical systems and time series of being statistically different when observed backward in time. While the theoretical foundations of irreversibility date back to the origin of statistical physics, the analysis of such property in real-world time series has only recently gained momentum. We present irreversibility, an open-source Python (version ≥ 3.11) package aimed at providing a large set of irreversibility metrics and tests and at facilitating their use. Besides the tests themselves, it includes a set of utilities, like functions to downsample and manipulate the time series, and to optimise the parameters of the metrics. By providing a unified software package, irreversibility simplifies the analysis of real data, allowing the researcher to compare multiple tests and obtain a better and more reproducible view of the underlying system. In this contribution we explore the features of the package and provide examples of its use.

Cyberbullying (CB) has emerged as a growing concern among adolescents, with nearly 10% of European children affected monthly and almost half experiencing it at least once. Unlike traditional bullying, CB thrives in digital environments where anonymity and impunity are prevalent. Despite its increasing prevalence, understanding the causal mechanisms behind CB remains challenging due to the limitations of conventional statistical methods, which often rely on correlations and are prone to spurious associations. In this paper, we introduce a novel human–machine consensus framework for causal discovery, aimed at supporting social scientists in unraveling the complex dynamics of CB. We leverage recent advances in data-driven causal inference, particularly the use of Directed Acyclic Graphs (DAGs), to identify and interpret causal relationships from observational data. Our approach integrates automatic causal discovery algorithms with expert knowledge, addressing the limitations of both purely algorithmic and purely expert-driven methods, and allows for the creation of a model ensemble estimation of the causal effects. To enhance interpretability and usability, we advocate for the use of Probabilistic Graphical Causal Models (PGCMs), or Bayesian Networks, which combine probabilistic reasoning with graphical representation. This hybrid methodology not only mitigates cognitive biases and inconsistencies in expert input but also fosters transparency and critical reflection in model construction. Cyberbullying serves as a compelling case study where ethical constraints preclude experimental designs, highlighting the value of interpretable, expert-informed causal models for guiding policy and intervention strategies.

La vid es uno de los cultivos más emblemáticos del mundo. No solo es la base de la producción de vino, un motor económico y cultural en países de clima mediterráneo tales como España, Italia o Francia, sino que también forma parte de su paisaje, historia e identidad gastronómica.