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With the rapid development of Internet of Things (IoT) technology, the people's demand for the viewing experience of large-scale sport events is increasing. However, due to the significant concentration of time and space in large-scale sports events, which leads to a surge in computation-intensive tasks, making traditional network models difficult to cope with such high demands. Fortunately, with the advantages of flexible deployment of Unmanned Aerial Vehicles (UAVs), UAV-assisted edge computing technology provides an innovative solution. This paper studies the resource allocation problem in UAV-assisted edge computing system for large-scale sport events. Our goal is to minimize system energy consumption while satisfying system performance. We formulate the problem as a long-term stochastic optimization problem. To address this issue, we propose the efficient dynamic resource allocation (EDRA) algorithm. By employing stochastic optimization techniques, the original problem is decomposed into multiple sub-problems that can be solved in parallel. We solve each subproblem through convex optimization and linear programming. Through theoretical analysis, we prove the gap between the proposed solution and the optimal solution. Experiments shows that the EDRA algorithm can reduce energy consumption by 32.4% compared to advanced algorithms while ensuring stronger system performance.

Grounded in the moral conflicts experienced by sports fans when their favored teams are involved in scandal events that violate implicit social contracts, this research develops the sports fan moral consistency maintenance model to explain how fans restore psychological balance and maintain loyalty. Across three experimental studies ( N  = 1179), we examine the cognitive and emotional mechanisms that shape loyalty recovery in the sports context. Study 1 shows that contractual violations significantly increase cognitive dissonance, which elicits both anger and shame. Study 2 reveals that cognitive dissonance undermines loyalty recovery through anger, while the pathway from shame to loyalty recovery is not significant. Study 3 further shows that fan identification moderates the emotional pathway. Highly identified fans show weaker anger and relatively stronger shame than low-identified fans. This pattern slightly reduces the negative association between anger and loyalty recovery, although the shame-loyalty link itself remains non-significant. These findings indicate that anger is a robust mediator of loyalty loss among sports fans, whereas shame represents a potential but still unconfirmed route to loyalty repair. The proposed model extends the understanding of moral emotion and cognitive dissonance in sports fan behavior and offers new implications for managing team scandals and repairing audience-team relationships.

This study considered the role of coal as China’s basic energy source and examines the development of the coal industry. We focused on the intelligent development of coal mines, and introduced the “Chinese mode” of intelligent mining in underground coal mines, which uses complete sets of technical equipment to propose classification and grading standards. In view of the basic characteristics and technical requirements of intelligent coal mine systems, we established a digital logic model and propose an information entity and knowledge map construction method. This involves an active information push strategy based on a knowledge demand model and an intelligent portfolio modeling and distribution method for collaborative control of coal mines. The top-level architecture of 5G+ intelligent coal mine systems combines intelligent applications such as autonomous intelligent mining, human–machine collaborative rapid tunneling, unmanned auxiliary transportation, closed-loop safety control, lean collaborative operation, and intelligent ecology. Progress in intelligent mining technology was described in terms of a dynamic modified geological model, underground 5G network and positioning technology, intelligent control of the mining height and straightness of the longwall working face, and intelligent mining equipment. The development of intelligent coal mines was analyzed in terms of its imbalances, bottlenecks, and the compatibility of large-scale systems. Implementation ideas for promoting the development of intelligent coal mines were proposed, such as establishing construction standards and technical specifications, implementing classification and grading standards according to mining policy, accelerating key technology research, and building a new management and control model.

The NLRP3 inflammasome is a fundamental component of the innate immune system, yet its excessive activation is intricately associated with viral pathogenesis. Porcine reproductive and respiratory syndrome virus type 2 (PRRSV-2), belonging to the family Arteriviridae , triggers dysregulated cytokine release and interstitial pneumonia, which can quickly escalate to acute respiratory distress and death. However, a mechanistic understanding of PRRSV-2 progression remains unclear. Here, we screen that PRRSV-2 nsp2 activates the NLRP3 inflammasome, thereby instigating a state of hyperinflammation. Mechanistically, PRRSV-2 nsp2 interacts with the nucleotide-binding and oligomerization (NACHT) domain of NLRP3, augmenting IKKβ recruitment to driving NLRP3 translocation to the dispersed trans -Golgi network (dTGN) for oligomerization. This process facilitates ASC polymerization, culminating in the activation of the NLRP3 inflammasome. In addition, the IKKβ-dependent NLRP3 translocation to the dTGN is pivotal for pseudorabies virus (PRV) and encephalomyocarditis virus (EMCV)-induced inflammatory responses. Collectively, these results elucidate a novel mechanism of NLRP3 inflammasome activation during PRRSV-2 infection, providing valuable insights into PRRSV-2 pathogenesis.

Single blade centrifugal pump is suitable for transporting sewage water with large obstacles in diameter, which is required to achieve high performance. The blade inlet angle is a parameter that affects the performance of the single blade centrifugal pump. However, the selection of blade inlet angle is frequently based on experiences and demonstrates certain arbitrariness. Therefore, six impellers with different blade inlet angles are designed using ANSYS Bladegen and NX software. These impellers are categorized into Groups 1 and 2. The blade inlet angle of the impellers in Group1/Group2 increases/decreases from the front shroud to the rear one, respectively. Subsequently, the numerical simulation is carried out to investigate the effect of the blade inlet angle on the performance of the single blade pump. The blade inlet angle has more obvious influence on the head, efficiency, and shaft power for the impellers in Group 1 than those in Group 2. The lowest pressure is negative for one of the impellers in Group 1. Moreover, an optimum blade inlet angle improves the pump performance. In addition, the alternating load is small on the blades of the impellers in Group 2. The present results are helpful in designing the single blade centrifugal pump and improving its performance.

The main contribution of this work is a comprehensive overview of the many years of research on various inter-facial forces with distinct flow structure transitions in liquid-gas multiphase flow in vertical columns. Injecting a gas phase into a liquid phase result in a fluid dynamic phenomenology that is substantial, magnetizing, and fascinating. Bubble columns modelling functioning in the bubbly, slug, churn, and annular turbulent flow regime is a major challenge due to their complicated and ephemeral nature. An important modelling choice is how to represent the bubble size distribution. This may be accomplished in several ways, from the relatively simple one of utilizing a single representative bubble size to more intricate techniques. To evaluate the computational findings, we have analysed and discussed several turbulence models in this comparative research. Furthermore, this review summarises the current inter-facial force models, which include turbulent dispersion force, lift force, drag force, wall lubrication force, and virtual mass force. The models of Grace, Tomiyama, Zuber, Antel, Legendre, Burns, and Naumann universal Hosokawa are used, respectively.

Modeling and system identification are critical for the design, simulation, and navigation of underwater vehicles. This study presents a six degree-of-freedom (DoF) nonlinear model for a finless underactuated underwater vehicle, incorporating port-starboard symmetry and cross-flow terms. Then, hydrodynamic damping parameters are identified using an optimized Extended Kalman Filter (EKF), establishing a steady validation framework for computational fluid dynamics (CFD) simulation coefficients. Additionally, system identification is further enhanced with a Long Short-Term Memory (LSTM) neural network and a comprehensive dataset construction method, enabling time-series predictions of linear and angular velocities. To mitigate position divergence in dead reckoning (DR) caused by LSTM, a Nonlinear Explicit Complementary Filter (NECF) is integrated for attitude estimation, providing accurate yaw computation and reliable localization without dependence on acoustic sensors or machine vision. Finally, validation and evaluation are conducted to demonstrate model accuracy, EKF convergence, and the reliability of LSTM-based navigation.

This work minimizes battery pack enclosure mass (kg) and peak deformation (mm) under a side-pole impact condition and validates the results by finite-element reruns complemented by coupon-level material tests. A 64-run optimal Latin hypercube dataset trained ARD Matérn-5/2 Gaussian-process surrogates, and NSGA-II performed a multi-objective search on a manufacturability grid (Δt = 0.5 mm). Decision-making processes used knee-region filtering and TOPSIS in the normalized objective space with robustness checks (uncertainty inflation, weight perturbation, and cross-kernel audit). The representative optimum reduced mass from 149.40 kg to 115.20 kg (−22.89%) while keeping peak deformation essentially unchanged (66.17 → 66.25 mm) in independent reruns. To examine material dependence, an orthotropic CFRP cross-check was performed by substituting the upper cover and side walls: the iso-thickness mapping yields 90.40 kg with 68.67 mm (+3.65% vs. aluminum x⋆), whereas a constrained iso-mass setting (H1 = 7.0 mm, H2 = 7.0 mm) gives 111.70 kg with 80.85 mm (+22.04%). The observed trends are consistent with the laminate’s lower transverse-shear moduli and shear-sensitive load paths; damage evolution and lay-up optimization are outside the present scope. The workflow provides a reproducible route to balance lightweighting and deformation control for battery pack enclosures.

The work is devoted to an analysis of interference torque of a gas-dynamic bearing gyroscope, while a condition with uniformly changed specific force and carrier angular velocity are taken into account. A five-degrees-of-freedom (5-DOF) model is established considering the translation and tilt of the rotor, which solves dynamic rotor equations and the Reynolds equation simultaneously. The model makes it possible to obtain the rotor trajectory under time-transient specific force and carrier angular velocity. The interference torque of the gyroscope is analyzed based on the rotor trajectory. Results indicate that the gas-dynamic bearings show a significant hysteresis effect with a perturbation of bearing force or bearing moment, which indicates the necessity of transient research. Interference torque is large when the carrier angular velocity starts to change or stops to change, and when the specific force stops to change. When the specific force change rate is less than 8.4 km/s3 with no change of the carrier angular velocity, the condition could be simplified as a steady state, which is consistent with the previous study.

Understanding human mobility is of great significance for sustainable transportation planning. Long-term travel delay change is a key metric to measure human mobility evolution in cities. However, it is challenging to quantify the long-term travel delay because it happens in different modalities, e.g., subway, taxi, bus, and personal cars, with implicated coupling. More importantly, the data for long-term multi-modal delay modeling is challenging to obtain in practice. As a result, the existing travel delay measurements mainly focus on either single-modal system or short-term mobility patterns, which cannot reveal the long-term travel dynamics and the impact among multi-modal systems. In this paper, we perform a travel delay measurement study to quantify and understand long-term multi-modal travel delay. Our measurement study utilizes a 5-year dataset of 8 million residents from 2013 to 2017 including a subway system with 3 million daily passengers, a 15 thousand taxi system, a 10 thousand personal car system, and a 13 thousand bus system in the Chinese city Shenzhen. We share new observations as follows: (1) the aboveground system has a higher delay increase overall than that of the underground system but the increase of it is slow down; (2) the underground system infrastructure upgrades decreases the aboveground system travel delay increase in contrast to the increase the underground system travel delay caused by the aboveground system infrastructure upgrades; (3) the travel delays of the underground system decreases in the higher population region and during the peak hours.