We investigate uniqueness of solution to the heat equation with a density $\rho$ on complete, non-compact weighted Riemannian manifolds of infinite volume. Our main goal is to identify sufficient conditions under which the solution $u$ vanishes identically, assuming that $u$ belongs to a certain weighted Lebesgue space with exponential or polynomial weight, $L^p_{\phi}$. We distinguish between the cases $p \gt 1$ and $p = 1$ which required stronger assumptions on the manifold and the density function $\rho$. We develop a unified method based on a conformal transformation of the metric, which allows us to reduce the problem to a standard heat equation on a suitably weighted manifold. In addition, we construct explicit counterexamples on model manifolds which demonstrate optimality of our assumptions on the density $\rho$.

Following the pivotal work of Sevastyanov (1957), who considered branching processes with homogeneous Poisson immigration, much has been done to understand the behaviour of such processes under different types of branching and immigration mechanisms. Recently, the case where the times of immigration are generated by a non-homogeneous Poisson process has been considered in depth. In this work, we demonstrate how we can use the framework of point processes in order to go beyond the Poisson process. As an illustration, we show how to transfer techniques from the case of Poisson immigration to the case where it is spanned by a determinantal point process.

This paper introduces an overlapping generations model to explore the interplay between economic growth, the environment, and endogenous technology adoption. Considering an economy with physical capital and publicly funded human capital, the analytical framework extends Prieur and Bréchet (2013, Macroeconomic Dynamics 17, 1135–1157) by incorporating the endogenous technology choice mechanism from Umezuki and Yokoo (2019, Journal of Economic Dynamics & Control 100, 164–175). The analysis focuses on how the choice of capital-intensive technologies impacts environmental dynamics. The model reveals complex equilibrium dynamics, driven by a core trade-off between individuals’ resource allocation on consumption versus environmental protection and firms’ technology decisions.

Constant-force mechanisms (CFMs) are attractive for mechanical energy storage owing to their distinctive force–displacement characteristics, particularly under conditions with limited external load capacity and restricted space. However, conventional CFMs often suffer from short constant-force strokes and inefficient space utilization, which hinder their broader application. To address these limitations, this study exploits the buckling of compliant beams and increases the structural degrees of freedom by adopting a less constrained configuration, which extends the constant-force stroke and space utilization while reducing the required external load, thus improving energy storage efficiency for the same stored elastic energy. A novel catapult was developed through NSGA-II multi-objective optimization, achieving a high energy-to-cost ratio and an extended constant-force stroke. This work presents an effective design approach for motion mechanisms that demand high energy-storage efficiency and high-power output.

The pandemic crisis introduced an unprecedented supply-side shock that was global in scope. Despite historically high levels of prior sovereign debt and low bond yields, macroeconomic policy responses included monetised fiscal expansions of extraordinary magnitude. Conventional theory suggests that the combination of supply contractions with such expansions is inflationary, yet central bank discourse during the pandemic expressed little concern about inflation. Our theoretical analysis suggests the presence of strong inflation forces at the time, likely offset by continuing pessimism shocks, consumption constraints and expectations management. In prominent advanced countries over more than a century, monetised fiscal expansions are shown to have preceded inflation surges, most strongly following signature episodes like WWII.

Crop wild relatives represent an essential reservoir of untapped genetic diversity for crop improvement. Despite sesame (Sesamum indicum L.) being an important oilseed crop, its wild relatives remain underutilized for characterization and breeding efforts. To comprehensively assess their potential, a field evaluation was conducted during the kharif seasons of 2022 and 2023 on 53 accessions belonging to seven wild, three S. indicum accessions, and three cultivated species. Thirty-four agro-morphological traits (18 qualitative, 16 quantitative) were characterized under field conditions. Substantial variability was observed across key traits, including plant height, branching patterns, leaf morphology, corolla structure and pigmentation, capsule size and shape, seed characteristics, and yield-contributing attributes. Multivariate analyses revealed significant clustering patterns, and several traits, notably capsule width, capsule length, corolla length, seed area and test weight, exhibited high heritability. Importantly, certain wild accessions such as IC621506 and IC557250 (early maturity), IC409053, IC204658, IC208661 and IC208662 (greater capsule number), and IC208661, IC208662 and IC409053 (superior seed yield per plant) outperformed cultivated sesame species. These novel accessions constitute valuable genetic resources for broadening the cultivated gene pool and enhancing breeding strategies. This study provides the first comprehensive characterization of morphological diversity in wild sesame species, underscoring their potential utility in developing high-yielding, resilient varieties that can address future agricultural challenges.

This study aimed to evaluate the microclimatic conditions of natural shading provided by Ipês (Handroanthus heptaphyllus [Vell.] Mattos), and of an artificial shading structure characterized by the combination of an aluminized net on the outside and a black polypropylene net on the inside. In addition, their effects were analysed with respect to the physiological and behavioural responses of Holstein cows kept at pasture in a tropical climate. Two paddocks were used, one with trees and the other with trees and an artificial shade structure. Eight multiparous cows were evaluated over 20 non-consecutive days and selected according to their predominant coat colour: four with predominantly white coats and four with predominantly black coats. The experimental days were classified as very hot, with radiation above 625 Wm−2; and hot days, with radiation between 300 and 625 Wm−2. The mean radiant temperature (°C), the radiant heat load (Wm−2) and the black globe humidity index were calculated. The mean radiant temperature for artificial shading was lower for all days (P < 0.05), with values below 30°C during daylight hours. The radiant heat load was lower under the artificial shading structure regardless of the day (P < 0.05), with values below 470 Wm−2. When compared microclimatically with natural shading, artificial shading was more efficient (P < 0.05) in reducing mean radiant temperature and radiant heat load. Although behavioural variation (P < 0.05) was observed, these results were related to the difference in coat pattern. Animals with predominantly black coats grazed in the early morning hours and sought protection as thermal comfort levels rose.

The question of how digital health is regulated has become increasingly important within debates on technology, inequality and global health. While digital health is frequently celebrated for its capacity to expand access, build resilient systems and advance equity, scholars have raised critical concerns about its role in reproducing asymmetries of power. The potential for reproducing rather than curbing inequality is particularly relevant for the Global South. This Special Issue of the International Journal of Law in Context interrogates the ways in which digital health infrastructures, regulatory frameworks and transnational data flows are constitutive of coloniality and neoliberal capitalism. Bringing together socio-legal, feminist and decolonial perspectives, the contributions examine regulation as a terrain in which vulnerabilities, exclusions and structural inequalities are reinforced. Against the celebratory rhetoric of innovation, this collection situates regulation as a key site for understanding the entanglement of digital health with broader histories of coloniality and capitalism.

In this research, a hierarchical dynamic and kinematic modeling framework is proposed for a wheeled-legged manipulator (WLM), explicitly incorporating wheel slip and skid effects through the Gibbs–Appell formulation. Unlike traditional Lagrangian methods that depend on constraint multipliers, the proposed approach unifies the platform and manipulator dynamics while substantially reducing computational complexity. This integration enables efficient handling of nonholonomic constraints without compromising physical fidelity and offers a clear separation between subsystems, allowing the effects of wheel-ground interactions to be analyzed independently from manipulator motions. The proposed formulation is validated through a combination of MATLAB/Webots simulations and laboratory experiments conducted under both dry and wet (soapy ceramic) surface conditions. Experimental results indicate end-effector position deviations of 8–10.5% primarily due to wheel slip and initial joint torque discrepancies of 6.5–20% that progressively diminish as steady-state motion is reached. Comparative evaluation against a conventional Lagrangian model highlights the computational advantage of the Gibbs–Appell formulation, demonstrating reduced assembly time and fewer symbolic differentiation operations. Furthermore, a sensitivity analysis on friction coefficients and slip ratios confirms the robustness of the model to variations in surface conditions. Beyond accurate dynamic prediction, the hierarchical structure enables modular real-time implementation, supporting controller design, trajectory planning, and fault detection. Overall, the results demonstrate that the Gibbs–Appell-based hierarchical modeling framework combines analytical rigor with computational efficiency, providing a robust foundation for control and optimization in advanced wheeled-legged robotic manipulators.