The contact process is a simple model for the spread of an infection in a structured population. We consider a variant of this process on Bienaymé–Galton–Watson trees, where vertices are equipped with a random fitness representing inhomogeneous transmission rates among individuals. In this paper, we establish conditions under which this inhomogeneous contact process exhibits a phase transition. We first prove that, if certain mixed moments of the joint offspring and fitness distribution are finite, then the survival threshold is strictly positive. Further, we can show that, if slightly different mixed moments are infinite, then this implies that there is no phase transition and that the process survives with positive probability for any choice of the infection parameter. A similar dichotomy is known for the contact process on a Bienaymé–Galton–Watson tree. However, we can show that the introduction of fitness means that we have to take into account the combined effect of fitness and offspring distribution to decide which scenario occurs.

The appeal of quadruped robots lies not only in their ability to mimic the diverse and agile locomotion of animals but also in their potential to integrate with human artistic expression to achieve complex multi-skill movements. Continuous multi-skill motion in quadruped robots requires the realization of diverse, continuous, and long-horizon behaviors, involving a broader state space and more complex motion generation and transitions. This presents significant challenges, including sparse rewards, incomplete data, long-horizon motion planning, and the design of fine-grained motion transitions. In this work, we categorize quadruped robot skills into three types: rhythmic motions, expressive motions, and high-dynamic motions and generate reference trajectories for each category using central pattern generators, animation design, and motion capture, respectively. We then design an asymmetric neural network architecture and employ an imitation–reinforcement learning algorithm to train policies for generating these three types of motions. By composing multiple motion skill trajectories, we avoid long-horizon motion planning; by leveraging reinforcement learning, we enable smooth and continuous skill transitions; and by introducing a two-stage reference state initialization curriculum, the robot is able to switch from arbitrary states to the target motion skill. Moreover, during training, the policy imitates only key characteristics of the reference motions rather than strictly tracking fixed trajectories, making it more robust. Finally, we achieve robust motion skill generation and seamless transitions on a quadruped robot equipped with a 6-DoF manipulator, validating the effectiveness and feasibility of the proposed multi-skill generation and transition method.

Metaphony provides a unique window into the nature of the capacities of phonological grammars. The representational issues metaphonic processes highlight are exactly those core to computational analysis. Prominent examples of such processes, under various systems of phonological and morphological representation, are examined using algebraic methods, which describe the structure that arises when certain sequences exhibit the same behaviours. This analysis clarifies how representational choices interact with computational complexity. In particular, the simplest characterisations are obtained when the patterns are analysed at the syllabic level, as opposed to the segmental level, and when distinct morphemes are not demarcated by morpheme boundaries but by morphologically marked phonological material. Furthermore, these analyses speak directly to issues in learning, acquisition, production and perception.

We investigated associations between food liking and risk of health outcomes in a prospective cohort and explored if associations were potentially explained by body mass index (BMI). We included 182,181 participants from UK Biobank. Food liking was measured using a 9-point hedonic scale, covering liking (points 6-9)/disliking (points 1-5) for high fat savoury (HFSa), high fat sweet (HFSw), vegetable, low fat savoury (LFSa), and fruit-based, low fat sweet (LFSw) foods. Cox proportional hazard models assessed associations with health outcomes, as hazard ratios (HR) with 95% confidence intervals (CI), adjusted for relevant confounders. Compared to disliking, liking HFSa was associated with higher risks of type-2-diabetes (T2D) (HR 1.14; 95% CI: 1.09-1.19) and lung cancer (HR 1.10; 95% CI: 1.01-1.20). Liking HFSw was associated with higher risks of all-cause mortality, and cancer (HR range 1.03-1.07; 95% CI range: 1.00-1.14). Liking LFSa was associated with lower risks of all-cause mortality, T2D, cardiovascular disease (CVD), all-cause cancer, and colorectal cancer (HR range 0.85-0.97; 95% CI range: 0.79-0.99). Liking LFSw was associated with lower risks of T2D, CVD, and colorectal cancer (HR range 0.91-0.96; 95% CI range: 0.86-1.00). Associations between food liking and health outcomes differed between food groups, with most appearing not to be attenuated after adjusting for BMI. The key findings were that associations with adverse health outcomes were strongest for higher-fat containing food preference patterns, while sweet preference alone was not associated with increased risk. Our study highlighted the potential role of food liking in designing and targeting health promotion interventions.

For large-scale problems, efficiently optimizing task allocation with local communication and computing resources is challenging. Existing algorithms often fall short in task allocation computation time. Inspired by Bayesian estimation, we propose a parametric heuristic algorithm for redundant agents that can effectively perform dynamic task allocation in distributed architectures. Firstly, the method includes a confidence proxy-driven posterior correction algorithm (CPPCA), which can iteratively satisfy the constraint of the number of agents for each task based on local communication. We also prove that CPPCA can strictly converge after the number of neighbors is larger than a certain value. Then, we design a greedy swapping algorithm (GSA) to reduce the total cost while satisfying the constraints. It is also proved that the algorithm can converge in a finite number of steps under the condition that the communication graph is connected. Finally, the feasibility of the method is verified by simulation experiments. It shows that the confidence proxy-driven posterior correction and greedy swapping (CPPC-GS) method has significant advantages over the baseline algorithms in solving large-scale problems under the premise of redundant agents. It also has good results in the face of dynamic task allocation. Furthermore, the virtual-real fusion experiment bridges the “modeling gap” by validating the algorithm’s resilience to real-world engineering constraints, such as non-ideal communication and hardware heterogeneity, ensuring a seamless transition from theoretical frameworks to robust practical deployment.

Maternal obesity has been associated with an increased risk of oxidative and metabolic disorders in offspring later in life. This study investigates the therapeutic effects of N-acetylcysteine (NAC), a potent antioxidant, on obesity-induced inflammation, oxidative stress and impaired glucose metabolism in an experimental rat model. Maternal obesity was induced in female rats by administering a high-fat diet (HFD) (60% kcal from fat). NAC was given via intragastric gavage at a dose of 150 mg/kg. Female rats were mated at 12 weeks of age, and the respective diets were maintained throughout gestation and lactation. The experiment was concluded on postnatal day 28, at which point the offspring’s blood samples and liver tissues were collected for analysis. Following standard histological processing, immunohistochemical staining was performed to detect oxidative markers in liver tissue sections. In the HFD + NAC group, NAC supplementation ameliorated histological damage in both mothers and offspring’s liver tissues. NAC treatment reduced 8-OHdG expression in the HFD + NAC group, indicating a protective effect against oxidative stress. NAC also had a modulatory effect on oxidative stress markers such as total oxidant status, oxidative stress index, PON1, ARES and malondialdehyde. HFD induces hepatic injury and oxidative stress in both dams and their offspring, contributing to impaired metabolic programming. Maternal NAC supplementation partially ameliorated these effects by reducing oxidative damage and improving glucose metabolism. However, its protective effects were limited, particularly in restoring antioxidant enzyme activity and fully normalizing metabolic parameters.

The increasing adoption of robotic manipulators in the industry has brought the issue of robotic device safety to the forefront, particularly in the context of collaborative robotics. Among the main challenges, the evaluation of impacts with operators and objects in the workspace represents a critical issue, as accurately quantifying the magnitude of collisions is a complex task. Although current regulations propose various models for impact assessment, the suggested approaches are often oversimplified and not easily applicable in complex scenarios. To overcome this limitation, this study proposes the development of an effective mass impact model that simulates the collision between two bodies as an interaction between two lumped masses. The model is developed for both two-dimensional and three-dimensional analyses. Furthermore, it is implemented in a generic form and using a lumped-parameter robot model. This formulation enables the creation of a highly versatile model capable of overcoming the lack of knowledge of inertial parameters of robots. The approach is experimentally validated by means of a SCARA robot that collides with a cart, demonstrating the model’s applicability and accuracy.

Technology has created opportunities to explore non-traditional data sources for investigating patterns in community composition and biodiversity over time. Television shows set in natural environments implicitly contain ecological information. Through an investigative lens, we explored the potential utility of this data source for describing community composition and diversity trends given uncertainties in footage collection. We reviewed 14 seasons of the TV series Survivor (2016–2023) to quantify animal frequency and total appearances, describing the animals observed and calculating common diversity metrics. A total of 40 301 individuals representing 182 taxa were identified, with species accumulation analysis estimating up to 198 identifiable taxa detectable from Survivor footage. The number of animals observed was inherently biased towards more charismatic fauna, while the proportion of screen time was predominately given over to invertebrates. Temporal analyses suggested slight declines in biodiversity and species richness. However, we note several limitations that constrain the use of these data, particularly the unknown amount of sampling effort, as well as the absence of temporal and spatial information necessary for more robust analyses. Although we are currently sceptical of its application in ecological and conservation research, this data source may have greater value if paired with additional contextual information and metadata.