Butachlor is an herbicide extensively employed in rice cultivation, which has historically been under-investigated for its toxicological impacts on terrestrial vegetation. This study examines the dose-dependent effects of butachlor on the germination and antioxidant defense mechanisms in the seeds of Asian tape grass [Vallisneria natans (Lour.) H. Hara], an important submerged plant species widely distributed in the agricultural ponds. Employing a hydroponic setup, seeds were exposed to four concentrations of butachlor (0, 20, 200, and 2000 μg active ingredients L-1), and cultivated under controlled light conditions to quantify germination rates and assess oxidative stress responses. Our findings showed that butachlor concentrations up to 20 μg L-1 had no effect on the germination rate of V. natans seeds, while germination rates decreased by 6.0% and 8.7% at 200 and 2000 μg L-1, respectively. At 2000 μg L-1, malondialdehyde (MDA) content increased by 5.7 nmol g-1 FW, and catalase (CAT) activity declined by 21%, indicating oxidative damage. Additionally, the antioxidants proline (Pro) and glutathione (GSH) were upregulated under 20 μg L-1 butachlor treatment after 12 h, contributing to reactive oxygen species (ROS) scavenging and cellular stability. This study highlights the nuanced interactions between butachlor exposure and the antioxidant defenses in V. natans, providing valuable insights into the ecological impacts of herbicide pollution. Understanding these interactions is crucial for developing sustainable agricultural practices and for the management of herbicide resistance in aquatic systems.

Autistic high school students overwhelmingly have a poor experience of school. Research into this stage of life is limited, and researchers have tended not to talk to autistic students directly, instead hearing from non-autistic observers such as teachers and parents. This study aimed to address this gap in our knowledge by interviewing autistic students in mainstream high schools about their experience of school and their ideas for how this could be improved. Ten autistic students (13 to 20 years old) in Australian high schools were interviewed. Students overwhelmingly reported a negative experience. Most said their ideal school would be one where teachers and peers had greater understanding about autism and teachers had training in autism. By including the student voice, this research makes a valuable contribution to our understanding of autistic students’ school experience, adding depth and detail, and including what they would like to see changed. Importantly, the interview data also challenged misconceptions about what autistic students prioritised. The voice of autistic teens can make an important contribution to policies and practices aimed at improving their experience of school.

The growth of small perturbations in isotropic turbulence is studied using massive ensembles of direct numerical simulations. These ensembles capture the evolution of the ensemble-averaged flow field and the ensemble variance in the fully nonlinear regime of perturbation growth. Evolution equations for these two fields are constructed by applying the ensemble average operator to the Navier–Stokes equations and used to study uncertainty growth in scale and physical space. It is shown that uncertainty growth is described by a flux of energy from the ensemble-averaged flow to the ensemble variance. This flux is formally equivalent to the subgrid scale (SGS) energy fluxes of the turbulence cascade, and can be interpreted as an inverse uncertainty cascade from small to large scales. In the absence of information sources (measurements), the uncertainty cascade is unsteady and leads to the progressive filtering of the small scales in the ensemble-averaged flow, a process that represents the loss of predictability due to chaos. Similar to the kinetic energy cascade, the uncertainty cascade displays an inertial range with a constant average uncertainty flux, which is bounded from below by the average kinetic energy dissipation. Locally in space, uncertainty fluxes differ from the SGS energy fluxes at the same scale, but both have similar statistics and are significantly correlated with each other in space. This suggests that uncertainty propagation is partly connected to the energy cascade and that they share similar mechanisms. These findings open avenues to model uncertainty propagation in turbulence following an approach similar to the SGS models in large-eddy simulations. This is relevant not only to efficiently assess the reliability and accuracy of turbulence forecasts, but also to design uncertainty-robust reconstruction techniques for data assimilation or SGS modelling.

Each year, over 100,000 dogs are imported into Germany from other EU countries by animal welfare organisations, mainly from Romania. This study conducted a systematic content analysis of websites belonging to 241 animal welfare organisations that rehome dogs from southern and eastern Europe to Germany. Assessment included transparency, legal compliance, and availability of educational and medical information for adopters. The study shows that many organisations lacked information regarding dogs’ origins, transport methods, or health status which sometimes makes it difficult to distinguish between dog rescue and illegal dog trade. Photos were mainly used in adoption advertisements and behavioural descriptions were only included in two-thirds of the dog advertisements which poses a risk of increased dog relinquishment post-adoption due to behavioural unsuitability. Information on vector-borne diseases and typical behaviour of imported rescue dogs was not provided comprehensively. Few organisations violated legal standards, offering underage or banned breeds and failing to use the TRACES transport system. Most organisations relied upon private foster homes, while few had no temporary housing available in Germany. Although most claimed to conduct pre-adoption checks, comprehensive contract details were rarely published. The number of existing animal welfare organisations that rehome dogs from southern and eastern Europe to Germany is unable to be determined due to high fluctuation and the lack of central registry. Inadequate health disclosures and behavioural descriptions risk poor adoption matches and increased returns. Lack of legal compliance may endanger both animal and public welfare and opens the door to illegal dog trade. Sustainable animal protection requires better adopter education, reliable medical testing, and local engagement in source countries to reduce reliance upon transnational rehoming.

The simulation of turbulent flow requires many degrees of freedom to resolve all the relevant time and length scales. However, due to the dissipative nature of the Navier–Stokes equations, the long-term dynamics is expected to lie on a finite-dimensional invariant manifold with fewer degrees of freedom. In this study, we build low-dimensional data-driven models of pressure-driven flow through a circular pipe. We impose the ‘shift-and-reflect’ symmetry to study the system in a minimal computational cell (e.g. the smallest domain size that sustains turbulence) at a Reynolds number of 2500. We build these models by using autoencoders to parametrise the manifold coordinates and neural ordinary differential equation to describe their time evolution. Direct numerical simulations (DNSs) typically require of the order of $\mathcal{O}(10^5)$ degrees of freedom, while our data-driven framework enables the construction of models with fewer than 20 degrees of freedom. Remarkably, these reduced-order models effectively capture crucial features of the flow, including the streak breakdown. In short-time tracking, these models accurately track the true trajectory for one Lyapunov time, as well as the leading Lyapunov exponent, while at long-times, they successfully capture key aspects of the dynamics such as Reynolds stresses and energy balance. The model can quantitatively capture key characteristics of the flow, including the streak breakdown and regeneration cycle. Additionally, we report new exact coherent states found in the DNS with the aid of these low-dimensional models. This approach leads to the discovery of seventeen previously unknown solutions within the turbulent pipe flow system, notably featuring relative periodic orbits characterised by the longest reported periods for such flow conditions.

In the field of parafoil airdrop path planning, the inherent complexity and time-sensitive nature of mission requirements necessitate rapid path generation through low-order mathematical models that approximate the system’s true dynamics. This study presents a novel sparse identification framework for constructing a parafoil path planning approximate model. Leveraging high-fidelity 9-degree-of-freedom (9 DOF) dynamic simulation data as training inputs, our method identifies simple nonlinear relationships between 3D positional coordinates (for spatial targeting) and yaw angle (for directional control), which are critical path planning parameters. Compared to conventional 4 DOF models, experimental validation using field airdrop data reveals that the proposed sparse model achieves enhanced predictive accuracy while maintaining computational efficiency. Quantitative analysis demonstrates reductions in root mean square error (RMSE) by approximately 12.96% (horizontal position), 54.44% (height) and 37.96% (yaw angle). The efficacy is further confirmed through successful fixed-point homing across diverse initial deployment scenarios, underscoring its potential for parafoil path planning.

One of the most incredible aspects of the Mexican Baja Peninsula is the immense wealth of plant and animal diversity it holds. The human communities living alongside this richness have boundless intimate knowledge of its natural history, potentially with novel insights into the ecological and evolutionary processes shaping the diversity of plants and animals. These same human communities have likely also witnessed changes to these natural environments over their lifetimes, particularly as the effects of global change are being felt by similar rural communities around the world. However, because the area is so remote, they often have little access to scientific data or current information about the causes or effects of the changes they observe. Using a thematic analysis of recorded conversations, this project seeks to connect remote rural ranches in Mexico with scientists, to gather data on the issues that matter most to the community members, and work to find collaborative solutions. Through thematic analysis of recorded conversations, our research reveals that unpredictable climate variability, including droughts, hurricanes, and shifting seasonal patterns, poses significant challenges to ranching livelihoods. Ranchers’ deep ecological knowledge provides critical insights into the stresses of changing and increasingly unpredictable environmental trends. By integrating local perspectives with scientific approaches, this study highlights the potential for collaborative biodiversity research.

The atomic bombings of Hiroshima and Nagasaki reshaped international politics and the field of International Relations. But one question—“How should the atomic bomb be used?”—has been largely overlooked in political science. This article recovers American deliberations on alternative nuclear use options before August 1945, including the “noncombat demonstration,” targeting military installations, giving advance warning, and striking more symbolically valuable cities. We develop theoretical insights on the value of staging violent spectacles and the emotive power of visible destruction. We then use a wide range of sources to show that U.S. leaders selected an ostentatiously lethal means of atomic debut due to concerns about conventional military inferiority vis-à-vis the Soviet Union, the desire to instill a widespread view of the bomb’s revolutionary character, and the imperative of shaping the postwar international order. This study advances our understanding of the post-1945 international order and the performative dimensions of political violence.

The vast presence of populism in contemporary political discourse has introduced a narrative steeped in nostalgia, evoking images of a revered national past and delineating a stark division between the ‘authentic us’ and the ‘alien them’. While these messages resonate with a substantial portion of citizens, they concurrently foster identity-driven animosity and derogation. In a pre-registered experiment in the Netherlands (with data collected between January and March 2023), we distinguish the influence of nostalgic narratives and scapegoating on societal sentiments, revealing their pivotal role in exacerbating current levels of polarization. Our findings underscore the potential of nostalgic narratives to shape affective sentiments towards ideological and social in-groups, while also influencing sentiments towards out-groups. Messages featuring scapegoats were found to intensify positive sentiment towards in-groups, while simultaneously diminishing positive sentiment towards out-groups. This research underscores a crucial mechanism underpinning the ebb and flow of identity-based sentiments. The results indicate that nostalgic discourse, particularly when intertwined with scapegoating, can serve as a catalyst for the intensification of in-group affinity and the exacerbation of out-group aversion. In essence, our study underscores the far-reaching implications of nostalgic narratives in perpetuating societal animosity and polarization and sheds light on a critical facet of contemporary political discourse.