Cooperative edge offloading to nearby end devices via Device-to-Device (D2D) links in edge networks with sliced computing resources has mainly been studied for end devices (helper nodes) that are stationary (or follow predetermined mobility paths) and for independent computation tasks. However, end devices are often mobile, and a given application request commonly requires a set of dependent computation tasks. We formulate a novel model for the cooperative edge offloading of dependent computation tasks to mobile helper nodes. We model the task dependencies with a general task dependency graph. Our model employs the state-of-the-art deep-learning-based PECNet mobility model and offloads a task only when the sojourn time in the coverage area of a helper node or Multi-access Edge Computing (MEC) server is sufficiently long. We formulate the minimization problem for the consumed battery energy for task execution, task data transmission, and waiting for offloaded task results on end devices. We convert the resulting non-convex mixed integer nonlinear programming problem into an equivalent quadratically constrained quadratic programming (QCQP) problem, which we solve via a novel Energy-Efficient Task Offloading (EETO) algorithm. The numerical evaluations indicate that the EETO approach consistently reduces the battery energy consumption across a wide range of task complexities and task completion deadlines and can thus extend the battery lifetimes of mobile devices operating with sliced edge computing resources.

Soil–rock mixture is a special geological material between homogeneous soil masses and fractured rock masses. In this study, the shear characteristics, movement and failure characteristics of particles and the evolution law of cracks were studied by direct shear tests and particle flow numerical simulations. The results show that the shear stress-shear displacement curves of the soil–rock mixture can be roughly classified into three stages: elastic stage, plastic stage and strain softening stage, and there was a "jump" phenomenon. The higher the rock content was, the more obvious the phenomenon. The shear strength and its indices of the soil–rock mixture did not increase with increasing rock content, but there was an "optimal rock content". According to the experimental and simulation results, particle breakage can be divided into three types: slight failure, partial failure and complete failure. The crack propagation characteristics can be divided into three stages, and the crack propagation depth increases with increasing shear displacement. It increases with increasing vertical stress and decreases with increasing block rock content.

The rapid growth of electric vehicles (EVs) and photovoltaic (PV) generation creates substantial power peaks that strain local electrical infrastructure. Coordinated bidirectional charging can mitigate these challenges while delivering benefits such as lower costs, improved PV utilization, and reduced emissions. This paper develops a framework for fleet charging that combines station assignment with a two-stage scheduling approach. A heuristic assignment method allocates EVs to uni- and bidirectional charging stations, ensuring efficient use of limited infrastructure. Building on these assignments, charging power is optimized in two stages: a Mixed-Integer Linear Program (MILP) generates day-ahead schedules from forecasts, while an intraday heuristic-based MILP adapts them to unplanned arrivals and forecast errors through lightweight re-optimization. A Python -based simulator is developed to evaluate the framework under stochastic PV, load, price, and EV conditions. Results show that the approach reduces costs and emissions compared to alternative methods, improves the utilization of bidirectional infrastructure, scales efficiently to large fleets, and remains robust under significant uncertainty, highlighting its potential for practical deployment.

Samples of rock coupling joints were collected from the Jiangluling Tunnel of the G214 line in Qinghai province. Models with surface topographies similar to these joints were manually created. Freezing shear tests under different normal stress conditions were conducted to study the shear mechanical properties of these models. On this basis, the integral form of the peak shear strength criterion of frozen joints was proposed. Results show that the shear process of the ice layer can be divided into four stages, namely, initial deformation, continuously increasing shear stress, ice shearing, and residual shear. During the continuously increasing shear stress stage, the stress‐strain curve is concave, and elastic deformation is not evident. Furthermore, the increase rate of shear stress generally rises as normal stress intensifies. In the ice shearing stage, shear stress does not decrease instantaneously, but plastic deformation is now detectable. When the opening degree is greater than the undulation difference of the joint surface under the action of all levels of normal stress, the shear stress in the ice sharply increases and drops due to local failure and reicing. Then, evident difference between the shear processes under freezing and normal temperature conditions was then obtained. On this basis, the failure forms of joint surfaces, theory of ice adhesion strength under different opening degrees and morphologies, and the shear failure forms of frozen joints under different conditions were considered. The integral form of the peak shear strength criterion of frozen joints was proposed. These results can lay a theoretical foundation for the stability analysis of rock mass engineering in permafrost areas.