Dynamic feature of flavonoids content in different organs of larch （Larix gmelinii）

Flavonoids in plants is very important in its ecological role and economicvalue. The dynamic features of flavonoids content in different organs of larch (Larix gmelinii) atdifferent light and temperature conditions were investigated in this study. Results showed that theorder of flavonoids content in different organs from high to low was 7.78% (stem bark) > 2.79%(leaves) > 1.72% (branches) > 1.19% (stem xylem)and different organs had a great seasonal variationin flavonoids content, but the change of flavonoids content at different temperature was not obviousin different organs., The content of flavonoids in barck had, a positive correlation withtemperature (R^2=0.75), but that in other organs had slight variation with the change oftemperatures. For all the tested organs, the flavonoids content in summer and autumn wasapproximately 3-4 times higher than in spring and winter. This is attributed to the great stressfrom environmental physical variables such as UV radiation, high temperature that induce theaccumulation of flavonoids. The flavonoid content of sun leaves was evidently higher than that ofshade leaves, and leaves at upper part of canopy had a higher flavonoids content compared with thatat other parts. This result indicates that sun radiation could improve flavonoids production inleaves (R^2=0.76). The flavonoids may actively evolve in plant defenses to environmental stress,protecting larch from the damage of high temperature and radiation, and its main function isdifferent in different organs.

MOLECULAR DYNAMICS SIMULATION ON VIERATIONAL SPECTROSCOPIC FEATURES OF HYDROGEN BONDS IN CRYSTALLINE POLYMERS

Introduction The molecular dynamics simulation technique has recently proved to be a suitable alternative approachfor simulation of vibrational spectroscopy. In this study, molecular dynamics was utilized to understandlow frequency vibrations in highly ordered poly(ρ-phenylene terephthalmide) (PPTA). A key structuralfeature of this polymer is the presence of hydrogen bonds. There is little question that this strong localized

超空泡射弹的结构优化与稳定性分析

Stability is the key issue for kinetic-energy supercavitating projectiles.Our previous work established a six degrees of freedom(DOF)dynamic model for supercavitating projectiles.However,the projectile’s structure did not meet our current design specifications(its sailing distance could reach 100 m at an initial speed of 500 m/s).The emphasis of this study lies in optimizing the projectile’s configuration.Therefore,a program was developed to optimize the projectile’s structure to achieve an optimal design or the largest sailing distance.The program is a working optimal method based on the genetic algorithm(GA).Additionally,the convergence standard and population producing strategy were improved,which greatly elevated the calculation speed and precision.To meet design specifications,the improved GA was combined with the 6DOF model,which establishes a dynamic optimization problem.The new projectile’s structure was obtained by solving this problem.Then,the new structures’dynamic features were compared with the ideals proposed in this paper.The criterion of stability,which is called weakened self-stability,was redefined based on the results.The weakened self-stability is the optimal stability for an actual kinetic projectile motion,and it is instructive for the design of supercavitating projectiles in the future.

Crystal structure of the coxsackievirus A16 RNA-dependent RNA polymerase elongation complex reveals novel features in motif A dynamics

Dear Editor,Coxsackievirus A16(CV A16)and enterovirus 71(EV71)are currently the two primary causative agents of handfoot-and-mouth disease(HFMD)(Solomon et al.,2010;Mao et al.,2014),threatening health of children worldwide.They both belong to the Enterovirus genus of

Topic-Feature Lattices Construction and Visualization for Dynamic Topic Number

The topic recognition for dynamic topic number can realize the dynamic update of super parameters,and obtain the probability distribution of dynamic topics in time dimension,which helps to clear the understanding and tracking of convection text data.However,the current topic recognition model tends to be based on a fixed number of topics K and lacks multi-granularity analysis of subject knowledge.Therefore,it is impossible to deeply perceive the dynamic change of the topic in the time series.By introducing a novel approach on the basis of Infinite Latent Dirichlet allocation model,a topic feature lattice under the dynamic topic number is constructed.In the model,documents,topics and vocabularies are jointly modeled to generate two probability distribution matrices:Documentstopics and topic-feature words.Afterwards,the association intensity is computed between the topic and its feature vocabulary to establish the topic formal context matrix.Finally,the topic feature is induced according to the formal concept analysis(FCA)theory.The topic feature lattice under dynamic topic number(TFL DTN)model is validated on the real dataset by comparing with the mainstream methods.Experiments show that this model is more in line with actual needs,and achieves better results in semi-automatic modeling of topic visualization analysis.

Feature Selection and Feature Learning for High-dimensional Batch Reinforcement Learning: A Survey

Tremendous amount of data are being generated and saved in many complex engineering and social systems every day.It is significant and feasible to utilize the big data to make better decisions by machine learning techniques. In this paper, we focus on batch reinforcement learning(RL) algorithms for discounted Markov decision processes(MDPs) with large discrete or continuous state spaces, aiming to learn the best possible policy given a fixed amount of training data. The batch RL algorithms with handcrafted feature representations work well for low-dimensional MDPs. However, for many real-world RL tasks which often involve high-dimensional state spaces, it is difficult and even infeasible to use feature engineering methods to design features for value function approximation. To cope with high-dimensional RL problems, the desire to obtain data-driven features has led to a lot of works in incorporating feature selection and feature learning into traditional batch RL algorithms. In this paper, we provide a comprehensive survey on automatic feature selection and unsupervised feature learning for high-dimensional batch RL. Moreover, we present recent theoretical developments on applying statistical learning to establish finite-sample error bounds for batch RL algorithms based on weighted Lpnorms. Finally, we derive some future directions in the research of RL algorithms, theories and applications.

The Sharma-Tasso-Olver-Burgers equation:its conservation laws and kink solitons

The present paper deals with the Sharma-Tasso-Olver-Burgers equation(STOBE)and its conservation laws and kink solitons.More precisely,the formal Lagrangian,Lie symmetries,and adjoint equations of the STOBE are firstly constructed to retrieve its conservation laws.Kink solitons of the STOBE are then extracted through adopting a series of newly well-designed approaches such as Kudryashov and exponential methods.Diverse graphs in 2 and 3D postures are formally portrayed to reveal the dynamical features of kink solitons.According to the authors’knowledge,the outcomes of the current investigation are new and have been listed for the first time.

Specific wave structures of a fifth-order nonlinear water wave equation

Investigated in the present paper is a fifth-order nonlinear evolution(FONLE)equation,known as a nonlinear water wave(NLWW)equation,with applications in the applied sciences.More precisely,a traveling wave hypothesis is firstly applied that reduces the FONLE equation to a 1D domain.The Kudryashov methods(KMs)are then adopted as leading techniques to construct specific wave structures of the governing model which are classified as W-shaped and other solitons.In the end,the effect of changing the coefficients of nonlinear terms on the dynamical features of W-shaped and other solitons is investigated in detail for diverse groups of the involved parameters.