Maximum Entropy Heterogeneous-Agent Mirror Learning

Multi-agent reinforcement learning (MARL) has been shown effective for cooperative games in recent years. However, existing state-of-the-art methods face challenges related to sample inefficiency, brittleness regarding hyperparameters, and the risk of converging to a suboptimal Nash Equilibrium. To resolve these issues, in this paper, we propose a novel theoretical framework, named Maximum Entropy Heterogeneous-Agent Mirror Learning (MEHAML), that leverages the maximum entropy principle to design maximum entropy MARL actor-critic algorithms. We prove that algorithms derived from the MEHAML framework enjoy the desired properties of the monotonic improvement of the joint maximum entropy objective and the convergence to quantal response equilibrium (QRE). The practicality of MEHAML is demonstrated by developing a MEHAML extension of the widely used RL algorithm, HASAC (for soft actor-critic), which shows significant improvements in exploration and robustness on three challenging benchmarks: Multi-Agent MuJoCo, StarCraftII, and Google Research Football. Our results show that HASAC outperforms strong baseline methods such as HATD3, HAPPO, QMIX, and MAPPO, thereby establishing the new state of the art. See our project page at https://sites.google.com/view/mehaml

Expression of miR-126 and its potential function in coronary artery disease

Objective: This study aimed to explore the role of miR-126 in coronary artery disease (CAD) patients and the potential gene targets of miR-126 in atherosclerosis.Methodology: A total of 60 CAD patients and 25 healthy control subjects were recruited in this study. Among the 60 CAD patients, 18 cases were diagnosed of stable angina pectoris (SAP), 20 were diagnosed of unstable angina pectoris (UAP) and 22 were diagnosed of acute myocardial infarction (AMI). Plasma miR-126 levels from both groups of participants were analyzed by real-time quantitative PCR. ELISA was used to measure plasma level of placenta growth factor (PLGF).Results: The results showed that the miR-126 expression was significantly down-regulated in the circulation of CAD patients compared with control subjects (P<0.01). Plasma PLGF level was significantly upregulated in patients with unstable angina pectoris and acute myocardial infarction (AMI) compared with controls (both P<0.01) the miR-126 expression in AMI was significantly associated with PLGF.Conclusion: miR-126 may serve as a novel biomarker for CAD.Keywords: miR-126; PLGF; PCR; coronary artery disease; atherosclerosi

Salivary endocrine response following a maximal incremental cycling protocol with local vibration.

The aim of this study was to compare the effects of vibration (Vib versus noVib) during a maximal graded cycling exercise on hormonal response, precisely on cortisol (C) and testosterone (T). Twelve active males (25 ± 5yrs; 181 ± 5cm; 80.7 ± 11.1kg) randomly performed two maximal incremental cycling tests on two separate days and at the same time of the day (09:00). The protocol consisted of incremental steps of 3 min duration performed on a PowerBIKETM that induces vibration cycling. The study was a repeated measures design and participants performed the test with and without vibration. Gas exchange and heart rate (HR) were continuously assessed and blood lactate (Bla) was recorded at the end of each incremental stage. Saliva samples were collected before and immediately after the test, and analysed for (C) and (T). The results show that C and T increased in both cycling conditions; however, the C's magnitude of change was significantly higher by 83% after Vib cycling in comparison to the no Vib (p = 0.014), whereas the T's magnitude of change were not statistically different between trials (p = 0.715). Vibration induced a decrease of the T/C ratio (p = 0.046) but no significant changes were observed following noVib (p = 0.476). As a conclusion, the investigation suggests that adding mechanical vibration to cycling may potentiate a catabolic exercise-induced state, which could have potential clinical implications in rehabilitation and injury treatment. Sport experts should take this message home to carefully plan the recovery process and time during training and competitions

Expression of miR-126 and its potential function in coronary artery disease.

Objective: This study aimed to explore the role of miR-126 in coronary artery disease (CAD) patients and the potential gene targets of miR-126 in atherosclerosis. Methodology: A total of 60 CAD patients and 25 healthy control subjects were recruited in this study. Among the 60 CAD patients, 18 cases were diagnosed of stable angina pectoris (SAP), 20 were diagnosed of unstable angina pectoris (UAP) and 22 were diagnosed of acute myocardial infarction (AMI). Plasma miR-126 levels from both groups of participants were analyzed by real-time quantitative PCR. ELISA was used to measure plasma level of placenta growth factor (PLGF). Results: The results showed that the miR-126 expression was significantly down-regulated in the circulation of CAD patients compared with control subjects (P<0.01). Plasma PLGF level was significantly upregulated in patients with unstable angina pectoris and acute myocardial infarction (AMI) compared with controls (both P<0.01) the miR-126 expression in AMI was significantly associated with PLGF. Conclusion: miR-126 may serve as a novel biomarker for CAD

BASED ON THE WORKBENCH CONCRETE TRUCK MIXER BLADE STRESS ANALYSIS

Traditional method to calculate stress,concrete mixer truck mixing blades are usually of blade stirring power can be converted to uniformly distributed load,but due to the mixing blade in the process of acting force between concrete and is not evenly distributed,so that the calculation results have larger error. In order to accurately obtain the fluid load on the mixing blades. This study used the fluid-structure coupling analysis method,provided application of CFX and ANSYS Workbench numerical simulation analysis was carried out on the mixing blade,then it got the stress of mixing blade in the process of mixing and discharge,and compared with traditional stress analysis results. Analysis results show that the mixing blade root stress value,and the largest parts move biggest blade end,it offers the reliable basis for the intensity of the blade

Prediction of Plant Height in \u3ci\u3eArabidopsis thaliana\u3c/i\u3e Using DNA Methylation Data

Prediction of complex traits using molecular genetic information is an active area in quantitative genetics research. In the postgenomic era, many types of -omic (e.g., transcriptomic, epigenomic, methylomic, and proteomic) data are becoming increasingly available. Therefore, evaluating the utility of this massive amount of information in prediction of complex traits is of interest. DNA methylation, the covalent change of a DNA molecule without affecting its underlying sequence, is one quantifiable form of epigenetic modification. We used methylation information for predicting plant height (PH) in Arabidopsis thaliana nonparametrically, using reproducing kernel Hilbert spaces (RKHS) regression. Also, we used different criteria for selecting smaller sets of probes, to assess how representative probes could be used in prediction instead of using all probes, which may lessen computational burden and lower experimental costs. Methylation information was used for describing epigenetic similarities between individuals through a kernel matrix, and the performance of predicting PH using this similarity matrix was reasonably good. The predictive correlation reached 0.53 and the same value was attained when only preselected probes were used for prediction. We created a kernel that mimics the genomic relationship matrix in genomic best linear unbiased prediction (G-BLUP) and estimated that, in this particular data set, epigenetic variation accounted for 65% of the phenotypic variance. Our results suggest that methylation information can be useful in whole-genome prediction of complex traits and that it may help to enhance understanding of complex traits when epigenetics is under examination