聚乳酸改性及其在包装材料中的应用

聚乳酸(PLA)是一种具有高强度、高模量、透明性、生物降解性和生物相容性的生物基热塑性聚酯,已发展成为具有一定竞争力的商业化材料,并有望在包装领域逐步替代传统的石油基聚合物。然而,PLA的应用却受其本身固有的结晶速率慢、结晶度低和脆性大等缺点的限制。近年来,研究人员做了大量工作以解决PLA的上述技术瓶颈。本文综述了PLA在成核结晶与增韧改性领域的研究进展以及PLA在包装材料中的应用。

Synthesis, Characterization, and Antifungal Evaluation of Thiolactomycin Derivatives

5-Substituted benzylidene 3-acylthiotetronic acids are antifungal.A series of 3-acylthiotetronic acid derivatives with varying substitutions at the 5-position were designed,synthesized,and characterized,based on the binding pose of 3-acyl thiolactone with the protein C171Q KasA.Fungicidal activities of these compounds were screened against Valsa Mali,Curvularia lunata,Fusarium graminearum,and Fusarium oxysporum f.sp.lycopersici.Most target compounds exhibited excellent fungicidal activities against target fungi at the concentration of 50μg·mL-1.Compounds 11c and 11i displayed the highest activity with a broad spectrum.The median effective concentration(EC50)values of 11c and 11i were 1.9–10.7 and 3.1–7.8μg·mL-1,respectively,against the tested fungi,while the EC50 values of the fungicides azoxystrobin,carbendazim,and fluopyram were respectively 0.30,4.22,and>50μg·mL-1 against V.Mali;6.7,41.7,and 0.18μg·mL-1 against C.lunata;22.4,0.42,and 0.43μg·mL-1 against F.graminearum;and 4.3,0.12,and>50μg·mL-1 against F.oxysporum f.sp.lycopersici.The structures and activities of the target compounds against C.lunata were analyzed to obtain a statistically significant comparative molecular field analysis(CoMFA)model with high prediction abilities(q2=0.9816,r2=0.8060),and its reliability was verified.The different substituents on the benzylidene at the 5-position had significant effects on the activity,while the introduction of a halogen atom at the benzene ring of benzylidene was able to improve the activity against the tested fungi.

基于强化学习的舰载机保障作业实时调度方法

衡量航母作战性能的重要指标是舰载机出动架次率,而影响舰载机出动架次率的关键因素是舰载机保障作业调度效率.舰载机保障作业调度是指在有限时间、空间和资源约束的前提下合理安排舰载机所需保障作业顺序并高效完成舰载机的作业保障.现有基于最优化方法(动态规划、线性规划等)和启发式方法(如遗传算法、粒子群等)的求解策略仅适用于保障作业可预知情况下的作业调度,很难满足高动态作战场景下的实时保障作业调度需求.基于此,本文提出了一种新的基于DQN(deep Q-network)的舰载机保障作业实时调度方法,将舰载机保障作业调度问题建模成部分可观测马尔科夫决策过程(partially observable Markov decision processes)问题,利用全局与长期收益对保障作业调度过程进行优化,并通过离线学习和在线调配的学习决策框架进行解决.经过仿真实验验证,该方法能显著提高舰载机保障作业调度效率并满足实时决策环境的需要.

Rapid and Sparse Labeling of Neurons Based on the Mutant Virus-Like Particle of Semliki Forest Virus

Sparse labeling of neurons contributes to uncovering their morphology, and rapid expression of a fluorescent protein reduces the experiment range. To achieve the goal of rapid and sparse labeling of neurons in vivo, we established a rapid method for depicting the fine structure of neurons at 24 h post-infection based on a mutant viruslike particle of Semliki Forest virus. Approximately 0.014 fluorescent focus-forming units of the mutant virus-like particle transferred enhanced green fluorescent protein into neurons in vivo, and its affinity for neurons in vivo was stronger than for neurons in vitro and BHK21(baby hamster kidney) cells. Collectively, the mutant virus-likeparticle provides a robust and convenient way to reveal the fine structure of neurons and is expected to be a helper virus for combining with other tools to determine their connectivity. Our work adds a new tool to the approaches for rapid and sparse labeling of neurons in vivo.

Treatment of coking wastewater by a novel electric assisted micro-electrolysis filter

A newly designed electric assisted micro-electrolysis filter（E-ME） was developed to investigate its degradation efficiency for coking wastewater and correlated characteristics. The performance of the E-ME system was compared with separate electrolysis（SE） and micro-electrolysis（ME） systems. The results showed a prominent synergistic effect on COD removal in E-ME systems. Gas chromatography/mass spectrometry（GC–MS） analysis confirmed that the applied electric field enhanced the degradation of phenolic compounds.Meanwhile, more biodegradable oxygen-bearing compounds were detected. SEM images of granular activated carbon（GAC） showed that inactivation and blocking were inhibited during the E-ME process. The effects of applied voltage and initial p H in E-ME systems were also studied. The best voltage value was 1 V, but synergistic effects existed even with lower applied voltage. E-ME systems exhibited some p H buffering capacity and attained the best efficiency in neutral media, which means that there is no need to adjust p H prior to or during the treatment process. Therefore, E-ME systems were confirmed as a promising technology for treatment of coking wastewater and other refractory wastewater.

Fluorescence lifetime based distance measurement illustrates conformation changes of PYL10-CL2 upon ABA binding in solution state

Forster resonance energy transfer(FRET)is a widely used distance measurement method to illustrate protein conformational dynamics.The FRET method relies on the distance between donor and acceptor,as well as the labelling efficiency,the size and the properties of the fluorophores.Here,we labelled a pair of small fluorophores and calculated the energy transferred efficiency through fluorescence lifetime analysis,which can provide more reliable distance measurement than intensity attenuation.The donor fluorophore,7-hydroxycoumarin-4-yl-ethylglycine(HC),was genetically incorporated into specific sites of PYL10,obtaining complete labelling efficiency.The acceptor fluorophore,Alexa488,was labelled through the disulfide bond,whose labelling efficiency was estimated through both absorption peaks and lifetime populations.Fluorescence lifetime and anisotropy analysis showed ABA-induced local conformation changes and dynamics of several HC incorporation sites of PYL10.The lifetime-based FRET distance measurement illustrated the conformation changes of PYL10 with or without ABA application,which is consistent with the previously reported crystal structures.

Transferring priors from virtual data for crowd counting in real world

In recent years,crowd counting has increasingly drawn attention due to its widespread applications in the field of computer vision.Most of the existing methods rely on datasets with scarce labeled images to train networks.They are prone to suffer from the over-fitting problem.Further,these existing datasets usually just give manually labeled annotations related to the head center position.This kind of annotation provides limited information.In this paper,we propose to exploit virtual synthetic crowd scenes to improve the performance of the counting network in the real world.Since we can obtain people masks easily in a synthetic dataset,we first learn to distinguish people from the background via a segmentation network using the synthetic data.Then we transfer the learned segmentation priors from synthetic data to real-world data.Finally,we train a density estimation network on real-world data by utilizing the obtained people masks.Our experiments on two crowd counting datasets demonstrate the effectiveness of the proposed method.

Trajectory distributions:A new description of movement for trajectory prediction

Trajectory prediction is a fundamental and challenging task for numerous applications,such as autonomous driving and intelligent robots.Current works typically treat pedestrian trajectories as a series of 2D point coordinates.However,in real scenarios,the trajectory often exhibits randomness,and has its own probability distribution.Inspired by this observation and other movement characteristics of pedestrians,we propose a simple and intuitive movement description called a trajectory distribution,which maps the coordinates of the pedestrian trajectory to a 2D Gaussian distribution in space.Based on this novel description,we develop a new trajectory prediction method,which we call the social probability method.The method combines trajectory distributions and powerful convolutional recurrent neural networks.Both the input and output of our method are trajectory distributions,which provide the recurrent neural network with sufficient spatial and random information about moving pedestrians.Furthermore,the social probability method extracts spatio-temporal features directly from the new movement description to generate robust and accurate predictions.Experiments on public benchmark datasets show the effectiveness of the proposed method.