Understanding the dynamics of host-parasite interactions is essential for uncovering the ecological and evolutionary processes shaping natural populations. In this study, we investigated the spatial and temporal patterns of prevalence of the cestode Schistocephalus solidus in 4 Alaskan populations of threespine stickleback (Gasterosteus aculeatus) over 11 years (1996 to 2006). Additionally, we assessed host tolerance through key indicators such as the Parasite Index and the presence of fibrotic scar tissue, a specialized form of resistance in this system. We observed fibrosis formation in both infected and uninfected fish across all populations, with notable year-to-year variability in Cornelius Lake. Here, fibrosis prevalence ranged from 9% in 1997 to 63% in 1998, coinciding with the highest cestode prevalence recorded in this population. Willow Lake stickleback displayed persistently high Parasite Indices, with parasite weights occasionally exceeding host eviscerated weights, and experienced a potential epizootic from 2000 to 2005. Cestode prevalence remained stable in Rocky and Cornelius Lakes and was consistently low in Lazy Lake. Our findings demonstrate significant variation in cestode prevalence, parasite burden, and resistance mechanisms among populations and between years. Importantly, the decoupling of fibrosis formation from infection status highlights the multifaceted nature of host-parasite interactions. Our study emphasizes the value of long-term datasets in revealing spatial and temporal patterns in host-parasite dynamics. Future research integrating ecological and genetic frameworks will be critical for elucidating the drivers of resistance and tolerance and their evolutionary implications.

Employing a self-paced reading experiment, a read-aloud production task and a pen-and-paper questionnaire, we examined if Turkish (L2) and native (L1) speakers of English rely on similar or different mechanisms in comprehending and producing English subject–verb number agreement. The results showed that the syntactic distance of an attractor to the head noun affected the L1 speakers’ parsing decisions, while the L2 speakers were influenced by its linear proximity to the verb. The results also showed singular attraction in comprehension for both groups and (a tendency for) plural attraction in production. We argue that L1 and L2 speakers differ in the sources of attraction and in their cue weighting/encoding while processing and producing S-V agreement. Whereas syntactic proximity is more crucial in the L1 speakers’ agreement computation, L2 speakers weigh linear distance cue more heavily. We also argue that S-V agreement computation is governed through different mechanisms in comprehension and production.

Expositions of the fine-tuning argument (FTA) typically aim only to show that cosmic fine-tuning is evidence for theism over specific versions of naturalism. But, construed as an argument for theism, that modest contention threatens the FTA with insignificance, as there may be other hypotheses that better explain fine-tuning than either theism or one’s preferred formulation of naturalism. Adopting a Bayesian framework, I assess four such possibilities: the simulation hypothesis, teleological cosmopsychism, axiarchism, and teleological laws. I conclude that theism is superior to all four.

This case note critically analyses Justice Malek Mathiang Malek v The Minister of Justice and Constitutional Affairs, a case that challenged President Mayardit’s dismissal of 14 judges in the East African Court of Justice as unlawful under South Sudan’s Transitional Constitution and the Treaty for the Establishment of the East African Community. The court upheld the challenge and ordered the president to reinstate the judges to their previous positions. However, instead of reinstating them, the judges were asked to reapply, which they refused to do, saying that they should be reinstated automatically. The case is a significant development for at least two reasons: 1) it is the first ever case to overrule President Mayardit’s Republican Decree; 2) it is a triumph for the rule of law in that the court declared that the president and his government are subject to the law – like all the governments of the partner states.

The analysis and interpretation of radiocarbon dates can involve many steps, such as switching between units or time-scales, assessing the impacts of contamination, applying marine or other offsets, inspecting calibration curves, calibrating dates, extracting probabilities from calibrated distributions, and analysing and plotting multiple dates. Here, we present rice, a new open-source R package which, together with other packages such as rbacon, Bchron, coffee and clam, enables users to perform such calculations within R, thus allowing most of the steps from data entry to calibration, age-modeling and subsequent analysis and interpretation of time-series to be performed within a single widely-used, multi-platform, transparent and open-source software environment. All calculation steps are documented and can be inspected, and users can also write new/enhanced functions. The package could thus prove useful in both educational and research settings.

Generating accurate and executable code using Large Language Models (LLMs) remains a significant challenge for underrepresented programming languages, such as Prolog and Lisp, due to the scarcity of public training data compared to high-resource languages like Python. This paper introduces a generalizable Reinforcement Learning (RL) approach that combines small-scale versions of the Qwen2.5-Coder model with Group Relative Policy Optimization (GRPO) to enable effective code generation through reasoning. To address the limitations of sparse datasets, we integrate execution-driven feedback directly into the RL loop, utilizing a reward system that exploits both logical correctness and structural formatting. Experimental results on GSM8K dataset demonstrate significant improvements in reasoning quality and code accuracy across underrepresented languages. These findings underscore the potential of our approach to benefit a wide range of programming languages lacking extensive training resources by leveraging symbolic reasoning and interpreter-based feedback.

The accuracy and precision of radiocarbon dating largely depend on the quality of sample preparation prior to measurement. Proper selection of material, identification of potential contaminants, and application of appropriate purification procedures are the basis of reliable 14C analyses. Modern preparation laboratories not only support the process of obtaining reliable results but also play a key role in integrating the scientific community and educating future geochronologists. In 2025, a new Laboratory of Preparation for Radiocarbon Dating (LBC14) was established at Maria Curie-Skłodowska University in Lublin, Poland. The laboratory has been adapted for the selection and purification of macroscopic organic samples, such as charcoal, wood, peat, organic sediments, macrofossils, and bone—both unburned and cremated. The protocols used are acid-base-acid (ABA), ultrafiltration, and apatite preparation, modified according to the material’s state of preservation. The paper presents the scope of the new laboratory, the procedures used, and the first results of dating performed at the AMS Laboratory at ETH Zurich. The presented initiative is an important step towards the development of 14C research infrastructure in Poland and the construction of sustainable, interdisciplinary standards for working with dating material.

Let l and p be distinct primes, let F be a local field with residue field of characteristic p, and let $\mathfrak {X}$ be the irreducible component of the moduli space of Langlands parameters for $GL_3$ over $\mathbb {Z}_l$ corresponding to parameters of Steinberg type. We show that $\mathfrak {X}$ is Cohen–Macaulay and compute explicit equations for it. We also compute the Weil divisor class group of the special fibre of $\mathfrak {X}$, motivated by work of Manning for $GL_2$. Our methods involve the calculation of the cohomology of certain vector bundles on the flag variety, and build on work of Snowden, Vilonen–Xue, and Ngo.

Environmental water delivery is implemented globally to redress the ecological impacts of river regulation and consumptive water use. Allocation must balance the competing (and often conflicting) needs of humans, a diversity of water-dependent species and abiotic processes in the managed system. To optimize water allocation for conservation we developed a novel optimization framework that integrated a genetic algorithm with an integrated systems model to refine near-optimal allocations that maximize outcomes for a shrub (Duma florulenta), tree (Eucalyptus camaldulensis) and tree frog (Ranoidea raniformis) in one of the world’s most regulated catchments: the Murray–Darling Basin (Australia). Our algorithm weighted 16 wetland attributes and optimized those weights to prioritize allocation over a 25-year forecast window. The best-performing solutions required no additional resources but improved outcomes for the two priority plants and doubled the surviving frog populations. Modifying the multi-user model to only consider R. raniformis improved outcomes for that species at the expense of the two plant species, highlighting the risks of allocating a shared resource through a single-species lens. We demonstrate the value of optimization and multi-species approaches as decision-support tools for environmental water allocation and similar resource allocation problems in conservation.

The introduction to this forum outlines the many ways neoliberal thinkers have apprehended nature over the past century and why this oeuvre has been largely overlooked by historians. The intellectual history of neoliberalism and the study of the environmental crisis have both become sprawling but largely unconnected academic corpuses. This forum has been assembled to act as a conduit and thus help cultivate a new subfield of neoliberal environmental thought. By studying neoliberals as a “thought collective,” an approach pioneered two decades ago by Dieter Plehwe and Bernhard Walpen, it becomes possible to perceive how their environmental frameworks were conceived, debated, and disseminated. The existence of a neoliberal thought collective does not mean that there is a single market-conforming approach to managing environmental problems; rather, there is a wide array of frameworks cohered by a shared canon and worldview. The articles in this forum hint at the creativity and eclecticism of neoliberal bricoleurs, whose arguments range from climate denial, to selfish bees, to privatizing the Moon. As editors, we suggest three reasons for studying neoliberal environmental thought: to better perceive and thwart the thought collective’s objectives, to guard oneself against unconsciously adopting “green” neoliberal frameworks, and to engage fruitfully with the work of a worthy adversary to further the construction of post-neoliberal frameworks and their adjunct intellectual infrastructure.

This research sought to update understanding following improvements to treatment and deepen the understanding of the mortality risk associated with Type 1 or Type 2 diabetes, including relative risk in the presence of co-morbidities. Specifically, we developed a model to provide mortality predictions at a granular level for lives with and without diabetes. The model is tailored for use by the insurance industry to provide an updated source from which to appreciate the risk posed when underwriting people with diabetes. By providing an updated and deeper understanding of mortality risk, the research’s aim is to improve access to insurance for those individuals living with diabetes. The model combines industry standard underwriting risk factors, such as age, gender, deprivation index, body mass index (BMI), smoker status, blood pressure (BP) and cholesterol level, with various co-morbidities related to diabetes. A comprehensive analysis of mortality risk factors, between 2010 and 2019, for people with and without diabetes is undertaken on over 1.2 million records based on Clinical Practice Research Datalink (CPRD), Hospital Episode Statistics (HES) and Office for National Statistics (ONS) death registrations data. Cox proportional hazards models are used to estimate the probability of death, stratified by gender across three distinct populations: Type 1 diabetes, Type 2 diabetes and a general population sample. The model outputs produced are permutations of the following: gender; population split by general sample, Type 1 and Type 2 diabetes; and a time-dependent exponential model and a time-invariant homogeneous model. A Shiny model application allows interaction with the model outputs (https://0jv7e6-scott-reid.shinyapps.io/diabmdl/) and spreadsheets provide additional explanation. Useful insights were obtained through industry discussions on the variation of existing market practice against that implied by the results. Key rating factors were generally aligned with market practice, such as age, BMI, BP, cholesterol and years since a diabetes diagnosis. However, for a few significant mortality risks impacting co-morbidities, the results did not adhere to prior expectations. Exploratory work suggested that the order and sequencing of key co-morbidities for diabetes must be included in future model development.

The advancement of AI relies on text and data mining (TDM) to acquire training data, yet its large-scale algorithmic crawling activities fundamentally conflict with copyright regimes. Through comparative legal research, this article reveals the divergent governance approaches and efficacy deficiencies within the three major jurisdictions of the European Union, the United States and China. We argue that the current regulatory model adopted by the EU may adversely affect the dynamism of Europe’s AI industry. At the policy level, the EU should construct a synergistic “Cost-Benefit-Governance” framework, reducing compliance costs through differentiated regulation, collective licensing, and fiscal support measures. It should also leverage unified internal rules and international multilateral platforms to foster governance consensus. In legal practice, the EU should advance the clarification and tiered application of copyright exceptions. This can be achieved by refining rules, implementing data classification governance and innovating safe harbour liability mechanisms to enhance legal predictability, thereby balancing technological innovation and copyright protection. This framework aims to mitigate the inhibitory effect of current systems on AI innovation and address jurisdictional barriers through international cooperation.

Public humanities often require an expert in one area to learn another field or skill on-the-fly or to collaborate effectively across boundaries of specialization. Fear of the unknown combines with taken-for-granted assumptions about standard forms of humanities work to prevent our pursuit of promising public humanities projects and careers. Even veteran scholars with expertise important to public life shrink when going outside the comfort zone of academia to engage with audiences via new formats and professional pathways. A recognition of this need to upskill has emerged from a recent surge of research on public humanities in practice. This comic introduces The How-To Issue of Public Humanities, which provides instruction manuals for doing public humanities, meeting people where they are via media, formats, and professions that require conceptual understanding of what these new platforms offer and technical training in the nuts-and-bolts of these spaces. The piece identifies four pillars of public humanities (upskilling, teaming, universal design, and authority sharing), maps the phases of a public humanities project (dream, plan, create, improve), provides a toolkit of key concepts and strategies for the field, includes a directory of examples and instruction manuals, and provides guidance for sustainability and evaluation in public humanities.

To address the problems of insufficient adaptability of photovoltaic (PV) cleaning robots in mountainous environments, where it is challenging to balance cleaning repeatability and cleaning integrity, this paper proposes a three-legged compound mobile mechanism and conducts optimization of its key parameters. First, the topological structure of the mechanism is designed based on the locomotion mode of inchworms. Combined with the requirements of PV panel cleaning tasks and the characteristics of cleaning methods, a compound motion mode integrating linear cleaning and rotational cleaning is adopted to determine the final structural configuration of the mechanism. Second, considering the relationship between the key parameters of the mechanism and the robot’s cleaning repeatability as well as cleaning integrity, a comprehensive performance index is constructed. The genetic algorithm is introduced for parameter optimization. Simulation results show that the optimal solution occurs at the larger step length and the maximum unilateral width of the cleaning mechanism within the valid interval. Finally, a prototype was fabricated for experiments. The results demonstrate that the robot can maintain stable adsorption on inclined and undulating PV panels, and the actual cleaning path is consistent with the theoretical trajectory, verifying the effectiveness of the design and the accuracy of the theoretical analysis in this paper.

While Structural Health Monitoring (SHM) has been widely studied, its reliability in real-world applications remains challenged by pronounced operational variability, particularly when system behavior changes discretely between operating regimes. Such methods generally rely on baseline comparisons; however, under multiple operating regimes, the baseline becomes distributed across several distinct regions, each associated with a specific regime. This multi-baseline behavior complicates anomaly detectability, as variations induced by changing operating conditions may mask the subtle changes caused by structural degradation. The challenge is particularly pronounced for systems exhibiting regime-dependent behavior, where transitions between approximately stationary conditions occur frequently and are difficult to isolate. To address this, an efficient probabilistic multi-model framework is proposed, in which each operating regime is represented by a locally Vector Autoregressive (VAR) model. A Bayesian formulation is adopted to account for parameter uncertainty explicitly and to enable sequential updating, allowing the regime models to adapt as additional data become available—an important feature for early-stage SHM. New observations are evaluated against the ensemble of regime-specific VAR models using the marginal likelihood, enabling assessment of statistical consistency with the learned reference behavior. Persistently low consistency is interpreted as indicative of anomalies, which may reflect structural changes or evolving degradation. The proposed method is demonstrated using vibration data from gearboxes onboard a Crew Transfer Vessel operating under multiple regimes. Despite the limitations and uncertainties inherent to early-phase SHM, the framework successfully identifies deviations from the learned reference behavior within consistent operating conditions, demonstrating its potential for SHM under realistic, time-varying operation.

Across global and Pacific contexts, inclusive education policies often struggle to move from adoption to practice, leaving a persistent gap between commitments and classroom realities. In Vanuatu, inclusive education is both a constitutional and a statutory obligation: the Constitution of the Republic of Vanuatu guarantees equal rights without discrimination, the Education Act No. 9 of 2014 mandates culturally relevant schooling, and Vanuatu 2030: The People’s Plan: National Sustainable Development Plan 2016–2030 positions inclusion as central to national progress. Building on this foundation, the Ministry of Education and Training has launched the Inclusive Education and Training (IET) Policy 2025–2030, which sets ambitious goals for equitable access, teacher development, and systemic transformation. This article applies the Kokonas Research Methodology (KRM), a Vanuatu-born Indigenous implementation framework grounded in kastom (customary knowledge) and storian (dialogue), to the IET Policy. KRM structures implementation through five stages — initiation, validation, intervention, monitoring and support, and replication — which are mapped to policy priorities to demonstrate how culturally grounded processes can guide enactment in practice. Findings highlight the national significance of KRM in strengthening legitimacy and ownership of reforms in Vanuatu, while also offering transferable lessons for other Pacific countries and contributing to wider Asia-Pacific debates on inclusive education.