An Improved Prioritized DDPG Based on Fractional-Order Learning Scheme.

Although deep deterministic policy gradient (DDPG) algorithm gets widespread attention as a result of its powerful functionality and applicability for large-scale continuous control, it cannot be denied that DDPG has problems such as low sample utilization efficiency and insufficient exploration. Therefore, an improved DDPG is presented to overcome these challenges in this article. Firstly, an optimizer based on fractional gradient is introduced into the algorithm network, which is conductive to increase the speed and accuracy of training convergence. On this basis, high-value experience replay based on weight-changed priority is proposed to improve sample utilization efficiency, and aiming to have a stronger exploration of the environment, an optimized exploration strategy for boundary action space is adopted. Finally, our proposed method is tested through the experiments of gym and pybullet platform. According to the results, our method speeds up the learning process, obtains higher average rewards in comparison with other algorithms.

Long-term spaceflight composite stress induces depressive behaviors in model rats through disrupting hippocampus synaptic plasticity.

INTRODUCTION: Long-term spaceflight composite stress (LSCS) can cause adverse effects on human systems, including the central nervous system, which could trigger anxiety and depression. AIMS: This study aimed to identify changes in hippocampus synaptic plasticity under LSCS. METHODS: The present study simulated the real long-term space station environment by conducting a 42-day experiment that involved simulating microgravity, isolation, noise, circadian rhythm disruptions, and low pressure. The mood and behavior of the rats were assessed by behavior test. Transmission electron microscopy and patch-clamp were used to detect the changes in synapse morphology and electrophysiology, and finally, the expression of NMDA receptor channel proteins was detected by western blotting. RESULTS: The results showed that significant weight loss, anxiety, and depressive behaviors in rats were observed after being exposed to LSCS environment for 42 days. The synaptic structure was severely damaged, manifested as an obvious decrease in postsynaptic density thickness and synaptic interface curvature (p < 0.05; p < 0.05, respectively). Meanwhile, LTP was significantly impaired (p < 0.0001), and currents in the NMDAR channel were also significantly reduced (p < 0.0001). Further analysis found that LSCS decreased the expression of two key subtype proteins on this channel. CONCLUSION: These results suggested that LSCS-induced depressive behaviors by impairing synaptic plasticity in rat hippocampus.

Integrated metabolome and transcriptome analyses provide insight into the effect of red and blue LEDs on the quality of sweet potato leaves.

Red and blue light-emitting diodes (LEDs) affect the quality of sweet potato leaves and their nutritional profile. Vines cultivated under blue LEDs had higher soluble protein contents, total phenolic compounds, flavonoids, and total antioxidant activity. Conversely, chlorophyll, soluble sugar, protein, and vitamin C contents were higher in leaves grown under red LEDs. Red and blue light increased the accumulation of 77 and 18 metabolites, respectively. Alpha-linoleic and linolenic acid metabolism were the most significantly enriched pathways based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. A total of 615 genes were differentially expressed between sweet potato leaves exposed to red and blue LEDs. Among these, 510 differentially expressed genes were upregulated in leaves grown under blue light compared with those grown under red light, while the remaining 105 genes were expressed at higher levels in the latter than in the former. Among the KEGG enrichment pathways, blue light significantly induced anthocyanin and carotenoid biosynthesis structural genes. This study provides a scientific reference basis for using light to alter metabolites to improve the quality of edible sweet potato leaves.

Composite robust control of uncertain nonlinear systems with unmatched disturbances using policy iteration.

In this paper, the composite robust control problem of uncertain nonlinear systems with unmatched disturbances is investigated. In order to improve the robust control performance, the integral sliding mode control method is considered together with H∞ control for nonlinear systems. By designing a disturbance observer with a new structure, the estimations of disturbances can be obtained with small errors, which are used to construct sliding mode control policy and avoid high gains. On the basis of ensuring the accessibility of specified sliding surface, the guaranteed cost control problem of nonlinear sliding mode dynamics is considered. To overcome the difficulty of robust control design caused by nonlinear characteristics, a modified policy iteration method based on sum of squares is proposed to solve the H∞ control policy of the nonlinear sliding mode dynamics. Finally, the effectiveness of the proposed robust control method is verified by simulation tests.

Weighted Gene Co-Expression Network Analysis to Explore Hub Genes of Resveratrol Biosynthesis in Exocarp and Mesocarp of 'Summer Black' Grape.

Resveratrol is a polyphenol compound beneficial to human health, and its main source is grapes. In the present study, the molecular regulation of resveratrol biosynthesis in developing grape berries was investigated using weighted gene co-expression network analysis (WGCNA). At the same time, the reason for the resveratrol content difference between grape exocarp (skin) and mesocarp (flesh) was explored. Hub genes (CHS, STS, F3'5'H, PAL, HCT) related to resveratrol biosynthesis were screened with Cytoscape software. The expression level of hub genes in the exocarp was significantly higher than that in the mesocarp, and the expressions of the hub genes and the content of resveratrol in exocarp peaked at the maturity stage. While the expression levels of PAL, CHS and STS in the mesocarp, reached the maximum at the maturity stage, and F3'5'H and HCT decreased. These hub genes likely play a key role in resveratrol biosynthesis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis further indicated that resveratrol biosynthesis was related to flavonoid biosynthesis, phenylalanine metabolism, phenylpropanoid biosynthesis, and stilbene biosynthesis pathways. This study has theoretical significance for exploring genes related to resveratrol biosynthesis in the exocarp and mesocarp of grapes, and provides a theoretical basis for the subsequent function and regulatory mechanism of hub genes.

Event-Triggered Adaptive Control of Uncertain Nonlinear Systems With Composite Condition.

This article concentrates on the event-based collaborative design for strict-feedback systems with uncertain nonlinearities. The controller is designed based on neural network (NN) weights adaptive law. The controller and NN weights adaptive law are only updated at the triggering instants determined by a novel composite triggering threshold. Considering the conservativeness of event condition, the state-model error is integrated into constructing the composite condition and NN weights adaptive law. In the context of the proposed mechanism, the requirements of system information and the allowable range of event-triggering error are relaxed. The number of triggering instants is greatly reduced without deteriorating the system performance. Moreover, the stability of the closed-loop is proved by the Lyapunov method following time-interval and sampling instants. Simulation results show the effectiveness of the scheme proposed in this article.

H∞ Codesign for Uncertain Nonlinear Control Systems Based on Policy Iteration Method.

In this article, the problem of H∞ codesign for nonlinear control systems with unmatched uncertainties and adjustable parameters is investigated. The main purpose is to solve the adjustable parameters and H∞ controller simultaneously so that better robust control performance can be achieved. By introducing a bounded function and defining a special cost function, the problem of solving the Hamilton-Jacobi-Isaacs equation is transformed into an optimization problem with nonlinear inequality constraints. Based on the sum of squares technique, a novel policy iteration algorithm is proposed to solve the problem of the H∞ codesign. Moreover, one modified algorithm for optimizing the robust performance index is given. The convergence and the performance improvement of new iteration policy algorithms are proved. Simulation results are presented to demonstrate the effectiveness of the proposed algorithms.

Syndrome Differentiation of Chinese Medicine in Mars 500 Long-Term Closed Environment.

OBJECTIVE: To summarize and elucidate the characteristics and evolvement of Chinese medicine (CM) patterns reflecting the physical and mental conditions of participants in the Mars 500 long-term closed environment. METHODS: The DS01-T Digital TCM Four-Diagnostic Instrument and CM Inquiring Diagnostic Questionnaire were used to collect information from 6 participants in the Mars 500 International Joint Research Project, through diagnostic methods of observation, palpation and inquiry according to CM theory. During the 520 days of the experiment, data collection was performed 37 times; a total of over 400 digital images of tongues and facial complexion and over 20,000 data were collected. These data were then analyzed by a team of experts in CM, statistics, and data mining. RESULTS: The CM pattern evolvement of participants in the long-term closed environment followed some common trends. Qi deficiency was the main CM pattern observed, with individual features depending on constitutional differences [manifested in varying degrees of accompanying patterns of Gan (Liver) qi stagnation, Pi (Spleen) deficiency, dampness encumbering, or yin deficiency]. CONCLUSION: The research has verified the effectiveness of CM syndrome differentiation based on the four diagnostic methods, which should serve as a solid foundation for observation, monitoring, and intervention in regard to the health conditions of astronauts in long-term space flights in the future.

Quantization-Based Adaptive Actor-Critic Tracking Control With Tracking Error Constraints.

In this paper, the problem of adaptive actor-critic (AC) tracking control is investigated for a class of continuous-time nonlinear systems with unknown nonlinearities and quantized inputs. Different from the existing results based on reinforcement learning, the tracking error constraints are considered and new critic functions are constructed to improve the performance further. To ensure that the tracking errors keep within the predefined time-varying boundaries, a tracking error transformation technique is used to constitute an augmented error system. Specific critic functions, rather than the long-term cost function, are introduced to supervise the tracking performance and tune the weights of the AC neural networks (NNs). A novel adaptive controller with a special structure is designed to reduce the effect of the NN reconstruction errors, input quantization, and disturbances. Based on the Lyapunov stability theory, the boundedness of the closed-loop signals and the desired tracking performance can be guaranteed. Finally, simulations on two connected inverted pendulums are given to illustrate the effectiveness of the proposed method.

Epidemiological and molecular characteristics of emergent dengue virus in Yunnan Province near the China-Myanmar-Laos border, 2013-2015.

BACKGROUND: Yunnan Province is located in southwestern China and neighbors the Southeast Asian countries, all of which are dengue-endemic areas. In 2000-2013, sporadic imported cases of dengue fever (DF) were reported almost annually in Yunnan Province. During 2013-2015, we confirmed that a large-scale indigenous DF outbreak emerged in cities of Yunnan Province near the China-Myanmar-Laos border. METHODS: Epidemiological characteristics of DF in Yunnan Province during 2013-2015 were evaluated by retrospective analysis. A total of 232 dengue virus (DENV)-positive sera were randomly collected for sequence analysis of the capsid/premembrane region of DENV from patients with DF in Yunnan Province. The envelope gene of DENV isolates was also amplified and sequenced. Phylogenetic analyses were performed using the neighbor-joining method with the Tajima-Nei model. RESULTS: Phylogenetically, all DENV-positive samples could be classified into DENV-1 genotype I and DENV-2 Asian I genotype during 2013-2015 and DENV-4 genotype I in 2015 from Ruili City; and DENV-3 genotype II in 2013 and DENV-2 Cosmopolitan genotype in 2015 from Xishuangbanna Prefecture. CONCLUSIONS: Our results indicated that imported DF from patients from Laos and Myanmar was the primary cause of the DF epidemic in Yunnan Province. Additionally, DENV strains of all four serotypes were identified in indigenous cases in Yunnan Province during the same time period, while the dengue epidemic pattern observed in southwestern Yunnan showed characteristics of a hypoendemic nature: circulation of DENV-1 and DENV-2 over consecutive years.