Coordinating decentralized learning and conflict resolution across agent boundaries

It is crucial for embedded systems to adapt to the dynamics of open environments. This adaptation process becomes especially challenging in the context of multiagent systems because of scalability, partial information accessibility and complex interaction of agents. It is a challenge for agents to learn good policies, when they need to plan and coordinate in uncertain, dynamic environments, especially when they have large state spaces. It is also critical for agents operating in a multiagent system (MAS) to resolve conflicts among the learned policies of different agents, since such conflicts may have detrimental influence on the overall performance. The focus of this research is to use a reinforcement learning based local optimization algorithm within each agent to learn multiagent policies in a decentralized fashion. These policies will allow each agent to adapt to changes in environmental conditions while reorganizing the underlying multiagent network when needed. The research takes an adaptive approach to resolving conflicts that can arise between locally optimal agent policies. First an algorithm that uses heuristic rules to locally resolve simple conflicts is presented. When the environment is more dynamic and uncertain, a mediator-based mechanism to resolve more complicated conflicts and selectively expand the agents' state space during the learning process is harnessed. For scenarios where mediator-based mechanisms with partially global views are ineffective, a more rigorous approach for global conflict resolution that synthesizes multiagent reinforcement learning (MARL) and distributed constraint optimization (DCOP) is developed. These mechanisms are evaluated in the context of a multiagent tornado tracking application called NetRads. Empirical results show that these mechanisms significantly improve the performance of the tornado tracking network for a variety of weather scenarios. The major contributions of this work are: a state of the art decentralized learning approach that supports agent interactions and reorganizes the underlying network when needed; the use of abstract classes of scenarios/states/actions that efficiently manages the exploration of the search space; novel conflict resolution algorithms of increasing complexity that use heuristic rules, sophisticated automated negotiation mechanisms and distributed constraint optimization methods respectively; and finally, a rigorous study of the interplay between two popular theories used to solve multiagent problems, namely decentralized Markov decision processes and distributed constraint optimization

TPD52L2 as a potential prognostic and immunotherapy biomarker in clear cell renal cell carcinoma

BackgroundTumor Protein D52-Like 2 (TPD52L2) is a tumor-associated protein that participates in B-cell differentiation. However, the role of TPD52L2 in the pathological process of clear cell renal cell carcinoma (ccRCC) is unclear.MethodsMultiple omics data of ccRCC samples were obtained from public databases, and 5 pairs of ccRCC tissue samples were collected from the operating room. Wilcox, chi-square test, Kaplan-Meier method, receiver operating characteristic curve, regression analysis, meta-analysis, and correlation analysis were used to clarify the relationship of TPD52L2 with clinical features, prognosis, and immune microenvironment. Functional enrichment analysis was performed to reveal the potential pathways in which TPD52L2 participates in the progression of ccRCC. The siRNA technique was used to knockdown in the expression level of TPD52L2 in 786-O cells to verify its effect on ccRCC progression.ResultsFirst, TPD52L2 was found to be upregulated in ccRCC at both mRNA and protein levels. Second, TPD52L2 was significantly associated with poor prognosis and served as an independent prognostic factor. Moreover, TPD52L2 expression was regulated by DNA methylation, and some methylation sites were associated with ccRCC prognosis. Third, TPD52L2 overexpression may participate in the pathological process through various signaling pathways such as cytokine-cytokine receptor interactions, PI3K-Akt, IL-17, Wnt, Hippo signaling pathway, and ECM-receptor interactions. Interestingly, TPD52L2 expression level was also closely related to the abundance of various immune cells, immune checkpoint expression, and TMB. Finally, in vitro experiments confirmed that knocking down TPD52L2 can inhibit the proliferation, migration, and invasion abilities of ccRCC cells.ConclusionThis study for the first time revealed the upregulation of TPD52L2 expression in ccRCC, which is closely associated with poor prognosis of patients and is a potentially valuable therapeutic and efficacy assessment target for immunotherapy

Design and operational parameters optimisation of a citrus substrate filling and transporting machine

Aiming to address the problem of low mechanisation of filling and transporting citrus seedling pots in China, a new type of pot filling and transporting machine with 120 pots at a time was designed. Based on the study of flow characteristics of the seedling substrate, key components of the filling and transporting machines, such as the hopper component, transmission mechanism, flip mechanism, and steering mechanism, were designed. The effects of the opening width of the hopper, the rotating speed of the stirring shaft, the moisture content of the seedling substrate, and the forward speed of the transporting device on the filling effect of the seedling pot were studied by the experimental method, and the optimal operation parameters were determined. The prototype tests were repeated 3 times with the best combination of parameters. The test results indicate that the machine was in good condition for loading and unloading. The number of filling pots was 120 once, and the average filling time was 40 s. The average filling mass was 1.881 kg, 0.006 kg different from the predicted value of 1.887 kg, and the relative error was 0.32%. The coefficient of variation of the mass was 2.97%, which was 0.12% different from the predicted value of 2.85%, and the relative error was 4.0%. This designed machine can provide a reference for developing and optimising the citrus substrate filling and transporting machine

Exploring the relationship between abnormally high expression of NUP205 and the clinicopathological characteristics, immune microenvironment, and prognostic value of lower-grade glioma

Nuclear pore complex (NPC) is a major transport pivot for nucleocytoplasmic molecule exchange. Nucleoporin 205 (NUP205)—a main component of NPC—plays a key regulatory role in tumor cell proliferation; however, few reports document its effect on the pathological progression of lower-grade glioma (LGG). Therefore, we conducted an integrated analysis using 906 samples from multiple public databases to explore the effects of NUP205 on the prognosis, clinicopathological characteristics, regulatory mechanism, and tumor immune microenvironment (TIME) formation in LGG. First, multiple methods consistently showed that the mRNA and protein expression levels of NUP205 were higher in LGG tumor tissue than in normal brain tissue. This increased expression was mainly noted in the higher WHO Grade, IDH-wild type, and 1p19q non-codeleted type. Second, various survival analysis methods showed that the highly expressed NUP205 was an independent risk indicator that led to reduced survival time of patients with LGG. Third, GSEA analysis showed that NUP205 regulated the pathological progress of LGG via the cell cycle, notch signaling pathway, and aminoacyl-tRNA biosynthesis. Ultimately, immune correlation analysis suggested that high NUP205 expression was positively correlated with the infiltration of multiple immune cells, particularly M2 macrophages, and was positively correlated with eight immune checkpoints, particularly PD-L1. Collectively, this study documented the pathogenicity of NUP205 in LGG for the first time, expanding our understanding of its molecular function. Furthermore, this study highlighted the potential value of NUP205 as a target of anti-LGG immunotherapy

Towards Multiagent Meta-level Control

Embedded systems consisting of collaborating agents capable of interacting with their environment are becoming ubiquitous. It is crucial for these systems to be able to adapt to the dynamic and uncertain characteristics of an open environment. In this paper, we argue that multiagent meta-level control (MMLC) is an effective way to determine when this adaptation process should be done and how much effort should be invested in adaptation as opposed to continuing with the current action plan. We describe a reinforcement learning based approach to learn decentralized meta-control policies offline. We then propose to use the learned reward model as input to a global optimization algorithm to avoid conflicting meta-level decisions between coordinating agents. Our initial experiments in the context of NetRads, a multiagent tornado tracking application show that MMLC significantly improves performance in a 3-agent network

Variations in Summer Precipitation According to Different Grades and Their Effects on Summer Drought/Flooding in Haihe River Basin

The variations in summer precipitation according to different grades and their effects on summer drought/flooding in the Haihe River basin were analyzed using the daily precipitation data from 161 meteorological stations from 1972 to 2021. The results showed that the number of rainy days (NRD) in summer in the Haihe River basin significantly declined in the past 50 years, mainly due to the reduction in the number of light-rain days. The precipitation amount (PA) exhibited prominent interdecadal characteristics, showing an upward tendency in the past 20 years accompanied by a remarkable increase in the proportion of torrential rain. The NRD in the northern part of the basin significantly decreased, while the PA in the southeast showed an increasing trend. Summer drought/flooding was strongly linked to the changes in the NRD and was predominantly affected by intense precipitation, with contribution rates of 5.5%, 16.8%, 31.2%, and 46.5% from light, moderate, heavy, and torrential rain, respectively. The effects of torrential rain increased in recent decades, particularly in the flooding scenarios. In addition, July was the critical period for summer drought/flooding, with the major influence of heavy and torrential rain. The most intense summer rainfall event in the Haihe River basin could contribute from 15% to 29% of total precipitation, resulting in changes in the severity and state of summer drought/flooding, which indicated that the precipitation process had a decisive impact on seasonal drought/flooding. Therefore, when predicting summer precipitation in the Haihe River basin, it is necessary to pay attention to the intense rainfall events during critical periods

SLAM Back-End Optimization Algorithm Based on Vision Fusion IPS

SLAM (Simultaneous Localization and Mapping) is mainly composed of five parts: sensor data reading, front-end visual odometry, back-end optimization, loopback detection, and map building. And when visual SLAM is estimated by visual odometry only, cumulative drift will inevitably occur. Loopback detection is used in classical visual SLAM, and if loopback is not detected during operation, it is not possible to correct the positional trajectory using loopback. Therefore, to address the cumulative drift problem of visual SLAM, this paper adds Indoor Positioning System (IPS) to the back-end optimization of visual SLAM, and uses the two-label orientation method to estimate the heading angle of the mobile robot as the pose information, and outputs the pose information with position and heading angle. It is also added to the optimization as an absolute constraint. Global constraints are provided for the optimization of the positional trajectory. We conducted experiments on the AUTOLABOR mobile robot, and the experimental results show that the localization accuracy of the SLAM back-end optimization algorithm with fused IPS can be maintained between 0.02 m and 0.03 m, which meets the requirements of indoor localization, and there is no cumulative drift problem when there is no loopback detection, which solves the problem of cumulative drift of the visual SLAM system to some extent

Inflammatory cytokines in highly myopic eyes.

Currently, myopic retinopathy is the most common irreversible blinding disease but its pathophysiology is not completely clear. A cross-sectional, observational study was conducted in a single center to analyze aqueous samples from highly myopic eyes (axial length >25 mm, n = 92) and ametropic or mild myopic eyes (n = 88) for inflammatory cytokines. Vascular endothelial growth factor (VEGF), Interleukin 6 (IL-6), and matrix metalloproteinase-2 (MMP-2) were measured using an enzyme-linked immunosorbent assay. IL-6 and MMP-2 were significantly higher in the highly myopic eyes than in the non-high myopic eyes (IL-6: 11.90 vs. 4.38 pg/mL, p < 0.0001; MMP-2: 13.10 vs. 8.82 ng/mL, p = 0.0003) while adjusting for age, gender, and intraocular pressure. There was a significant positive association between levels of IL-6 and MMP-2 in aqueous humor and the axial lengths of the eye globes (IL-6, β = 0.065, p < 0.0001, n = 134; MMP-2, β = 0.097, p < 0.0001, n = 131). Conversely, VEGF in aqueous humor was significantly lower in the highly myopic eyes than in the non-high myopic eyes (45.56 vs. 96.90 pg/mL, p < 0.0001, n = 153) while age, gender, and intraocular pressure were adjusted. The results suggest that low-grade intraocular inflammation may play an important role in the development and progression of high myopia and myopic retinopathy

Inflammatory cytokines in highly myopic eyes.

Currently, myopic retinopathy is the most common irreversible blinding disease but its pathophysiology is not completely clear. A cross-sectional, observational study was conducted in a single center to analyze aqueous samples from highly myopic eyes (axial length >25 mm, n = 92) and ametropic or mild myopic eyes (n = 88) for inflammatory cytokines. Vascular endothelial growth factor (VEGF), Interleukin 6 (IL-6), and matrix metalloproteinase-2 (MMP-2) were measured using an enzyme-linked immunosorbent assay. IL-6 and MMP-2 were significantly higher in the highly myopic eyes than in the non-high myopic eyes (IL-6: 11.90 vs. 4.38 pg/mL, p < 0.0001; MMP-2: 13.10 vs. 8.82 ng/mL, p = 0.0003) while adjusting for age, gender, and intraocular pressure. There was a significant positive association between levels of IL-6 and MMP-2 in aqueous humor and the axial lengths of the eye globes (IL-6, β = 0.065, p < 0.0001, n = 134; MMP-2, β = 0.097, p < 0.0001, n = 131). Conversely, VEGF in aqueous humor was significantly lower in the highly myopic eyes than in the non-high myopic eyes (45.56 vs. 96.90 pg/mL, p < 0.0001, n = 153) while age, gender, and intraocular pressure were adjusted. The results suggest that low-grade intraocular inflammation may play an important role in the development and progression of high myopia and myopic retinopathy