Research and Practice on the Construction of Professional Cluster in Application-Oriented Local Undergraduate Universities:Taking Environ-mental Chemical Engineering Professional Cluster in Pingdingshan University as an Example

Based on the analysis of the importance of professional cluster construction by ecological theory,with the change of social demand for talents,this paper explores the practice of environmental chemical professional cluster construction in Pingdingshan University,including gradually perfecting teaching conditions and reforming teaching mode,breaking through the limitations of resources,integrating the boundaries of colleges and departments,integrating multiple resources,innovating systems and mechanisms,reconstructing professional clusters,decon-structing professional connotations,reorganizing curriculum systems,etc.,in order to better build the ecological chain network of education in application-oriented colleges and universities,realize the deep integration of industry and education,train future-oriented interdisciplinary applied talents of new engineering,and realize the construction of characteristic professional cluster in application-oriented colleges.

Orbital angular momentum-mediated machine learning for high-accuracy mode-feature encoding

Machine learning with optical neural networks has featured unique advantages of the information processing including high speed,ultrawide bandwidths and low energy consumption because the optical dimensions(time,space,wavelength,and polarization)could be utilized to increase the degree of freedom.However,due to the lack of the capability to extract the information features in the orbital angular momentum(OAM)domain,the theoretically unlimited OAM states have never been exploited to represent the signal of the input/output nodes in the neural network model.Here,we demonstrate OAM-mediated machine learning with an all-optical convolutional neural network(CNN)based on Laguerre-Gaussian(LG)beam modes with diverse diffraction losses.The proposed CNN architecture is composed of a trainable OAM mode-dispersion impulse as a convolutional kernel for feature extraction,and deep-learning diffractive layers as a classifier.The resultant OAM mode-dispersion selectivity can be applied in information mode-feature encoding,leading to an accuracy as high as 97.2%for MNIST database through detecting the energy weighting coefficients of the encoded OAM modes,as well as a resistance to eavesdropping in point-to-point free-space transmission.Moreover,through extending the target encoded modes into multiplexed OAM states,we realize all-optical dimension reduction for anomaly detection with an accuracy of 85%.Our work provides a deep insight to the mechanism of machine learning with spatial modes basis,which can be further utilized to improve the performances of various machine-vision tasks by constructing the unsupervised learning-based auto-encoder.

贞芪扶正胶囊辅助治疗艾滋病作用机制的网络药理学分析及分子对接验证

目的利用网络药理学方法及分子对接技术分析贞芪扶正胶囊辅助治疗艾滋病的分子机制。方法通过TCMSP获取贞芪扶正胶囊组方药物活性成分及作用靶点,通过GeneCards、OMIM及DrugBank数据库获取艾滋病相关靶点;通过STRING 11.5数据库构建交集靶点PPI网络,并采用Cytoscape 3.9.1软件进行网络拓扑分析;采用Metascape数据库对核心靶点进行GO功能和KEGG通路富集分析;运用Cytoscape 3.9.1构建贞芪扶正胶囊成分-靶点-通路网络;利用Autodock Tools软件对核心靶点与活性成分进行分子对接。结果获得贞芪扶正胶囊31个活性成分及180个作用靶点,确定TNF、IL6、AKT1、IL1B、TP53、VEGFA、RELA、EGFR、CASP3为核心靶点。GO功能富集分析获得生物过程1436条、细胞组分53条、分子功能117条。KEGG通路富集分析获得167条通路,与癌症、糖尿病并发症的AGE-RAGE信号通路、IL-17信号通路等密切相关。分子对接结果显示,AKT1、TNF等核心靶点与槲皮素、山柰酚、木犀草素等成分有良好的结合活性。结论贞芪扶正胶囊治疗艾滋病的主要活性成分为槲皮素、山柰酚、木犀草素,可能通过IL-17信号通路辅助治疗艾滋病。

Morphable three-dimensional electronic mesofliers capable of on-demand unfolding

Development of miniaturized three-dimensional(3 D)fliers with integrated functional components has important implications to a diverse range of engineering areas.Among the various active and passive miniaturized 3 D fliers reported previously,a class of 3 D electronic fliers inspired by wind-dispersed seeds show promising potentials,owing to the lightweight and noiseless features,aside from the stable rotational fall associated with a low falling velocity.While on-demand shape-morphing capabilities are essential for those 3 D electronic fliers,the realization of such miniaturized systems remains very challenging,due to the lack of fast-response 3 D actuators that can be seamlessly integrated with 3 D electronic fliers.Here we develop a type of morphable3 D mesofliers with shape memory polymer(SMP)-based electrothermal actuators,capable of large degree of actuation deformations,with a fast response(e.g.,~1 s).Integration of functional components,including sensors,controllers,and chip batteries,enables development of intelligent 3 D mesoflier systems that can achieve the on-demand unfolding,triggered by the processing of real-time sensed information(e.g.,acceleration and humidity data).Such intelligent electronic mesofliers are capable of both the low-air-drag rising and the low-velocity falling,and thereby,can be used to measure the humidity fields in a wide 3 D space by simple hand throwing,according to our demonstrations.The developed electronic mesofliers can also be integrated with other types of physical/chemical sensors for uses in different application scenarios.