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

Influence of the Feed Moisture, Rotor Speed, and Blades Gap on the Performances of a Biomass Pulverization Technology

Recently, a novel biomass pulverization technology was proposed by our group. In this paper, further detailed studies of this technology were carried out. The effects of feed moisture and crusher operational parameters (rotor speed and blades gap) on product particle size distribution and energy consumption were investigated. The results showed that higher rotor speed and smaller blades gap could improve the hit probability between blades and materials and enhance the impacting and grinding effects to generate finer products, however, resulting in the increase of energy consumption. Under dry conditions finer particles were much more easily achieved, and there was a tendency for the specific energy to increase with increasing feed moisture. Therefore, it is necessary for the raw biomass material to be dried before pulverization

Semi-Supervised Learning for Sparsely-Labeled Sequential Data: Application to Healthcare Video Processing

Labeled data is a critical resource for training and evaluating machine learning models. However, many real-life datasets are only partially labeled. We propose a semi-supervised machine learning training strategy to improve event detection performance on sequential data, such as video recordings, when only sparse labels are available, such as event start times without their corresponding end times. Our method uses noisy guesses of the events' end times to train event detection models. Depending on how conservative these guesses are, mislabeled false positives may be introduced into the training set (i.e., negative sequences mislabeled as positives). We further propose a mathematical model for estimating how many inaccurate labels a model is exposed to, based on how noisy the end time guesses are. Finally, we show that neural networks can improve their detection performance by leveraging more training data with less conservative approximations despite the higher proportion of incorrect labels. We adapt sequential versions of MNIST and CIFAR-10 to empirically evaluate our method, and find that our risk-tolerant strategy outperforms conservative estimates by 12 points of mean average precision for MNIST, and 3.5 points for CIFAR. Then, we leverage the proposed training strategy to tackle a real-life application: processing continuous video recordings of epilepsy patients to improve seizure detection, and show that our method outperforms baseline labeling methods by 10 points of average precision

Upregulation of lncRNA NR_046683 Serves as a Prognostic Biomarker and Potential Drug Target for Multiple Myeloma

Aim: To investigate the prognostic value of lncRNA NR_046683 in multiple myeloma (MM).Methods: High-throughput lncRNA array was combined with bioinformatics techniques to screen differentially expressed lncRNA in MM. qRT-PCR was adopted to determine the expression of target lncRNAs in MM patients and controls.Results: It was found for the first time that lncRNA NR_046683 is closely related to the prognosis of MM. It was also detected in tumor cell lines KM3, U266, especially in drug-resistant cell lines KM3/BTZ and MM1R. The NR_046683 expression differed significantly in patients of different MM subtypes and staging. Moreover, the overexpression of NR-046683 is closely related to β2-microglobulin. We also found that the overexpression of NR-046683 correlates to chromosomal aberrations, such as del(13q14), gain 1q21, and t(4;14).Conclusion: lncRNA NR_046683 can serve as a novel biomarker for potential drug target and prognostic prediction in MM

Widely Targeted Metabolomics Revealed the Dynamic Changes of Metabolites during the Formation of Goose Fatty Liver

To understand the composition and dynamic changes of metabolites during the formation of goose fatty liver, the metabolite profiles of goose liver at three overfeeding stages were analyzed using widely targeted metabolomics. Three 70-day-old Landes geese with similar body conditions from the same batch were selected randomly for slaughter at the early (day 7), middle (day 16) and late (day 25) overfeeding stages, separately. The tip of the larger liver lobe was collected for widely targeted metabolomic analysis. The results showed that: (1) a total of 1 153 metabolites belonging to 19 classes including amino acids, organic acids, nucleotides and lipids were detected in the liver of geese at the three overfeeding stages; (2) principal component analysis (PCA) showed significant differences in the metabolic profiles of goose liver at the three stages, and identified 142 and 92 differential metabolites at the early versus middle stage, and the middle versus late stage, respectively, the major ones being amino acids and their derivatives, as well as organic acids and their derivatives; and (3) Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analysis indicated that the pathways involved in fatty acid biosynthesis, vitamin B6 metabolism, linoleic acid metabolism, lysine degradation, arginine biosynthesis, arachidonic acid metabolism and amino acid biosynthesis changed significantly during the formation of goose fatty liver. This study found that most of the differential metabolites were involved in fatty acid synthesis during goose fatty liver formation. Moreover, the contents of transport-related metabolites showed a continuous increasing trend. Findings in this study will not only enrich the theoretical knowledge of poultry liver metabolism, but also provide a theoretical basis for the precise nutritional regulation and efficient production of high-quality goose fatty liver

Exogenous spermidine improved drought tolerance in Ilex verticillata seedlings

Winterberry (Ilex verticillata (L.) A. Gray) is a recently introduced ornamental tree species in China that has not been closely investigated for its drought resistance. In this study, we used two-year-old cuttings from I. verticillata (L.) A. Gray and two representative varieties derived from it, I. verticillata ‘Oosterwijk’ and I. verticillata ‘Jim Dandy’, as materials to investigate how this plant responds to drought stress and whether exogenous spermidine (SPD) can alleviate the negative effects caused by drought stress. The results showed that as the degree of drought stress increased, the leaves of winterberry seedlings became chlorotic, and their edges became dry. Similarly, the relative water content, specific leaf weight, chlorophyll content, leaf nitrogen content, net photosynthetic rate, stomatal conductance and transpiration rate were significantly reduced, whereas the content of malondialdehyde continuously increased with the degree of drought stress. The activities of superoxide dismutase, peroxidase, and catalase increased under moderate drought stress and then decreased under severe drought stress. The levels of soluble sugar and abscisic acid continued to increase, while those of auxin and gibberellic acid decreased. When compared with individual drought stress, an increase in the amount of external SPD clearly alleviated the effect of drought stress on winterberry seedlings. The combined phenotypes and physiological indices of the winterberry leaves under drought stress conditions revealed that the drought resistance of the native species was significantly higher than its two varieties. This finding serves as an important theoretical foundation for the popularization and application of I. verticillata (L.) A. Gray and the two varieties

Crucial Role of miR-433 in Regulating Cardiac Fibrosis

Dysregulation of microRNAs has been implicated in many cardiovascular diseases including fibrosis. Here we report that miR-433 was consistently elevated in three models of heart disease with prominent cardiac fibrosis, and was enriched in fibroblasts compared to cardiomyocytes. Forced expression of miR-433 in neonatal rat cardiac fibroblasts increased proliferation and their differentiation into myofibroblasts as determined by EdU incorporation, α-SMA staining, and expression levels of fibrosis-associated genes. Conversely, inhibition of miR-433 exhibited opposite results. AZIN1 and JNK1 were identified as two target genes of miR-433. Decreased level of AZIN1 activated TGF-β1 while down-regulation of JNK1 resulted in activation of ERK and p38 kinase leading to Smad3 activation and ultimately cardiac fibrosis. Importantly, systemic neutralization of miR-433 or adeno-associated virus 9 (AAV9)-mediated cardiac transfer of a miR-433 sponge attenuated cardiac fibrosis and ventricular dysfunction following myocardial infarction. Thus, our work suggests that miR-433 is a potential target for amelioration of cardiac fibrosis

Introducing Chinese Students to Finnish Universities with Tourism Purpose

Tourism is an important section of the global market. Nowadays Finland is becoming a pop- ular tourist destination towards Chinese people, who are drastically growing into one of the world largest tourism consumer groups. Finland is well known for its outstanding quality of education and natural attractions. A start-up travel agency sees this trend as an opportunity, and is planning to arrange a Finnish study tour for Chinese university students, offering them opportunities to broaden their views and experience culture exchange. The purpose of the thesis is to conduct market research on tourism and education in both Finland and China. Author first paint a general picture of China’s outbound tourism including the trend, sustainability and customer behaviour in the aspect of study tours. In addition, author also explores the background information on the Finnish education and tourism. At last, the au- thor conducts a survey towards potential customers in order to provide the case agency with resourceful data and recommendation for organizing the study tour. Data from survey was collected through questionnaire. A quantitative data collecting method is involved in the questionnaire. 193 Chinese bachelor students from Northern China were treated as potential customers in the survey. The results indicate that there is a high de- mand for a study tour in Finland among the targeted Chinese students, but many factors such as culture differences, timing and budget appear to be potential threads that hinders some of them from joining the study tour. As a conclusion, the data and information collected from the research suggests that it is feasible to introduce Chinese student to Finland through study tour, however the company must be taken into consideration when planning the tour according to customers’ prefer- ences

Semiparametric Spatial Econometric Analysis of Household Consumption Based on Ordinary Linear Regression Model

In order to solve the problem that the image processing time is too long in the use of the original college education information power method.Therefore, the design of the fractional differential equation of higher education information power method. According to the information source, a combination of various methods is set to complete the data collection.Compared with the content of fractional differential equation, the fractional differential equation is selected to complete the image information processing. Develop the processing process and select the appropriate equipment to complete the image processing.Set up experimental equipment, select experimental samples to obtain experimental results. Compared with the original method, the image processing time of this method is significantly shorter than that of the original method.Therefore, this method is more efficient for image processing and has a more obvious effect on the informatization of university education