The self-organization capabilities of massive aerial swarms pose challenges to conventional methods of grouping aerial targets. These traditional approaches struggle with issues such as stability, ...reliability, and the recognition of deep intentions. To overcome these challenges, we propose an architecture called Unsupervised Contrastive Learning for Aerial Targets Grouping (UCL-ATG). Our approach utilizes random time periods within the scenario as training batches for contrastive learning. The UCL-ATG model consists of four key modules: feature extraction, time series generation, fine-tuning, and clustering. The feature extraction and time series generation modules form the network architecture of Contrastive Predictive Coding (CPC). Positive and negative samples are obtained using different sampling methods. To effectively collaborate with the clustering module, we design a contrastive predictive loss function specifically tailored for clustering. This enables the extraction of low-dimensional representations that capture the high-dimensional temporal characteristics of aircraft. Furthermore, we introduce a real-time fine-tuner to enhance the model's transferability to specific tasks. The inclusion of the real-time fine-tuner greatly alleviates problems associated with evolving confrontation styles and unevenly distributed datasets, as confirmed by the performance on the validation set. Extensive comparative experimental results demonstrate our model's superior training outcomes and its ability to extract improved clustering features. In wargame applications, our model no longer relies solely on static position information of the aircraft. It exhibits outstanding capabilities in historical information memory, information synthesis, and even demonstrates aptitude in identifying friend or foe and making tactical inferences.
Sustainable development is the theme of world economic development in the 21st century. As a key part of sustainable development, sustainable land use (SLU) encompasses economic development and ...environmentally friendly and social progress. In recent decades, China has formulated many environmental regulatory policies to achieve sustainable development and "carbon peaking and carbon neutrality (double-carbon)" goals, among which the carbon emission trading scheme (CETS) is the most representative and provides valuable research. In this paper, we aimed to reflect the spatio-temporal evolution of SLU in China under the influence of environmental regulatory policies through an indicator measurement strategy based on the DID estimation method. The study conclusions are as follows: (1) The CETS can effectively improve SLU from the perspectives of economic development and environmentally friendly progress, and the impact has primarily been in the pilot areas. And, its effectiveness is closely linked to local locational factors. (2) With respect to the dimension of economic development, the CETS has not changed the provincial distribution patterns of SLU; rather, it continues to remain "high to low, east to west". However, regarding the environmentally friendly progress dimension, the CETS has significantly changed the provincial distribution patterns of SLU, which are characterized by spatial agglomeration with urban agglomerations such as the Pearl River Delta (PRD) and the Yangtze River Delta (YRD) as the core. (3) The screening results of the SLU indicators based on economic development showed that the CETS primarily improved the innovation capacities of pilot regions, and the impacts on economic levels were relatively small. Similarly, the screening results of the SLU indicators based on environmentally friendly progress showed that the CETS had primarily acted on reducing pollution emission intensity and strengthening greening construction, revealing only short-term effects on improving energy use efficiency. Based on the above, this paper explored the meaning and role of the CETS in more detail, with a view to providing insight into the implementation and formulation of environmental regulation policies.
Aims/Introduction
To compare the association of hypertension plus hyperuricemia with four insulin resistance surrogates, including glucose and triglycerides (TyG index), TyG index with body mass ...index (TyG‐BMI), the ratio of triglycerides divided by high‐density lipoprotein cholesterol (TG/HDL‐C) and metabolic score for insulin resistance (METS‐IR).
Materials and Methods
Data from a cross‐sectional epidemiological study enrolling a representative population sample aged ≥65 years were used to calculate the four indexes. The association with hypertension plus hyperuricemia and insulin resistance surrogates was examined with multivariate logistic regression and receiver operating characteristic.
Results
A total of 4,352 participants were included, including 93 (2.1%) patients with hyperuricemia alone, 2,875 (66.1%) with hypertension alone and 587 (13.5%) with hypertension plus hyperuricemia. Mutivariate logistic regression showed that TyG index, TyG‐BMI, TG/HDL‐C and METS‐IR were all significantly correlated with hyperuricemia, hypertension and hypertension plus hyperuricemia. Compared with the lowest quartile, the odds ratios (OR) of the highest quartile of the four indicators for hypertension plus hyperuricemia were TyG index: OR 6.39 (95% confidence interval CI 4.17–9.78); TyG‐BMI: OR 8.54 (95% CI 5.58–13.09); TG/HDL‐C: OR 7.21 (95% CI 4.72–11.01); METS‐IR: OR 9.30 (95% CI 6.00–14.43), respectively. TyG‐BMI and METS‐IR had moderate discriminative abilities for hypertension plus hyperuricemia and the AUC values were 0.72 (95% CI 0.70–0.74) and 0.73 (95% CI 0.70–0.75).
Conclusions
The present study suggested that TyG index, TyG‐BMI, TG/HDL‐C and METS‐IR had a significant correlation with hypertension plus hyperuricemia, and TyG‐BMI and METS‐IR had discriminative abilities for hypertension plus hyperuricemia.
Our study suggested that glucose and triglycerides (TyG index), TyG index with body mass index, the ratio of triglycerides divided by high‐density lipoprotein cholesterol and metabolic score for insulin resistance had a significant correlation with hypertension plus hyperuricemia, and TyG index with body mass index and metabolic score for insulin resistance had discriminative abilities for hypertension plus hyperuricemia.
Abstract
This paper proposes an algorithm for missile manoeuvring based on a hierarchical proximal policy optimization (PPO) reinforcement learning algorithm, which enables a missile to guide to a ...target and evade an interceptor at the same time. Based on the idea of task hierarchy, the agent has a two-layer structure, in which low-level agents control basic actions and are controlled by a high-level agent. The low level has two agents called a guidance agent and an evasion agent, which are trained in simple scenarios and embedded in the high-level agent. The high level has a policy selector agent, which chooses one of the low-level agents to activate at each decision moment. The reward functions for each agent are different, considering the guidance accuracy, flight time, and energy consumption metrics, as well as a field-of-view constraint. Simulation shows that the PPO algorithm without a hierarchical structure cannot complete the task, while the hierarchical PPO algorithm has a 100% success rate on a test dataset. The agent shows good adaptability and strong robustness to the second-order lag of autopilot and measurement noises. Compared with a traditional guidance law, the reinforcement learning guidance law has satisfactory guidance accuracy and significant advantages in average time and average energy consumption.
Based on the theory of strategic alliances and social networks, this article empirically studies the relationship between partnership, information sharing, and sustainable performance through a ...questionnaire survey of Chinese sports equipment manufacturers. The findings show that partnerships have a positive impact on sustainable performance; that information sharing plays a role in mediating the relationships between trust, cooperation, and sustainable performance; and that government support can positively impact the effect of partnerships on sustainable performance. Through empirical research, this article proves the mechanism of the impact of partnership on alliance performance, further expands the theoretical basis for enterprises’ establishment of strategic alliances, and has important enlightening significance for enterprises within alliances aiming to rationally use the networks inside and outside their alliances to obtain knowledge and resources and improve their sustainable performance.
Abstract Precast Concrete Sandwich Panel (PCSP) is composed of concrete load-bearing panels, thermal insulation panels, and decorative panels, which are assembled through connectors, integrating ...load-bearing, thermal insulation, and decorative functions. The connector bears the main shear force between the wall panels, and the shear resistance and insulation performance of the connector largely determine the mechanical stability and insulation effect of the wall panels, which is a key component in PCSPs. The current common practice is to cross assemble stainless steel insulation (SSI) connectors and Glass-Fiber-Reinforced Plastic (GFRP) connectors into PCSPs, which can reduce building energy consumption and save resources while meeting strength and insulation requirements. A large-scale pull-out test on a PCSP with intersecting SSI-GFRP connectors was conducted in this paper. The damage process and damage pattern of PCSP were observed and the shear performance of SSI-GFRP connectors was analyzed. Secondly, a numerical analysis model of the test PCSP was built using ABAQUS finite element software and its validity was verified through the test data. In addition, parameters such as connector diameter, connector number ratio and concrete strength were analyzed for their effect on the shear performance of SSI-GFRP connectors and it was found that connector diameter and connector number ratio had a significant effect. Finally, it is found that there are some differences between the classical theory for calculating the shear performance of SSI-GFRP connectors and the actual results. A theoretical correction factor ( ζ ) is given to improve the accuracy of the calculation of the classical theory, and its influencing factors and changing rules are investigated.
This study investigates the associations among member ability, member relationships, knowledge sharing, and innovation performance in eSports industry knowledge alliance. A survey strategy and ...purposive sampling were applied, and the analysis was conducted on a sample of 311 senior managers from the China eSports Association. The hypotheses were tested using SPSS 24.0 software and AMOS 24.0 software. This study shows that member ability and member relationships have both a direct and indirect effect on innovation performance. Firstly, member ability, member relationships, and member knowledge sharing significantly impact the innovation performance of eSports industry knowledge alliances. Secondly, member knowledge sharing plays a mediating role in the effect of member ability and membership relationship on innovation performance. This pioneering article explores the interaction mechanisms between member ability, member relationships, and innovation performance in eSports industry knowledge alliance. The research results are conducive to the development of the eSports industry toward deep integration and sustainable development and provide a reference for similar knowledge-intensive enterprise alliance behaviors.
The reconnaissance of high-value targets is prerequisite for effective operations. The recent appreciation of deep reinforcement learning (DRL) arises from its success in navigation problems, but due ...to the competitiveness and complexity of the military field, the applications of DRL in the military field are still unsatisfactory. In this paper, an end-to-end DRL-based intelligent reconnaissance mission planning is proposed for dual unmanned aerial vehicle (dual UAV) cooperative reconnaissance missions under high-threat and dense situations. Comprehensive consideration is given to specific mission properties and parameter requirements through the whole modelling. Firstly, the reconnaissance mission is described as a Markov decision process (MDP), and the mission planning model based on DRL is established. Secondly, the environment and UAV motion parameters are standardized to input the neural network, aiming to deduce the difficulty of algorithm convergence. According to the concrete requirements of non-reconnaissance by radars, dual-UAV cooperation and wandering reconnaissance in the mission, four reward functions with weights are designed to enhance agent understanding to the mission. To avoid sparse reward, the clip function is used to control the reward value range. Finally, considering the continuous action space of reconnaissance mission planning, the widely applicable proximal policy optimization (PPO) algorithm is used in this paper. The simulation is carried out by combining offline training and online planning. By changing the location and number of ground detection areas, from 1 to 4, the model with PPO can maintain 20% of reconnaissance proportion and a 90% mission complete rate and help the reconnaissance UAV to complete efficient path planning. It can adapt to unknown continuous high-dimensional environmental changes, is generalizable, and reflects strong intelligent planning performance.
Big data mining and analytics help uncover hidden patterns and correlations in business. It serves as the optimal tool to interpret the behavior of companies in specific environments. Built on the ...large amount of data obtained from various sources, this paper examines the relationship between the tone of corporate social responsibility(CSR) reports and the degree of information asymmetry between investors and managers. Python software is used for data collection, text analysis, and word frequency statistics. The results show that the tone of the social responsibility report reduces the degree of information asymmetry, indicating that the tone of the social responsibility report has an incremental information effect. Further analysis shows that the tone of CSR reports significantly reduces information asymmetry in companies with optimistic forecasts and high media attention.
A system with multiple cooperating unmanned aerial vehicles (multi-UAVs) can use its advantages to accomplish complicated tasks. Recent developments in deep reinforcement learning (DRL) offer good ...prospects for decision-making for multi-UAV systems. However, the safety and training efficiencies of DRL still need to be improved before practical use. This study presents a transfer-safe soft actor-critic (TSSAC) for multi-UAV decision-making. Decision-making by each UAV is modeled with a constrained Markov decision process (CMDP), in which safety is constrained to maximize the return. The soft actor-critic-Lagrangian (SAC-Lagrangian) algorithm is combined with a modified Lagrangian multiplier in the CMDP model. Moreover, parameter-based transfer learning is used to enable cooperative and efficient training of the tasks to the multi-UAVs. Simulation experiments indicate that the proposed method can improve the safety and training efficiencies and allow the UAVs to adapt to a dynamic scenario.
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