Topological States in Twisted Pillared Phononic Plates

In recent years, the advances in topological insulator in the fields of condensed matter have been extended to classical wave systems such as acoustic and elastic waves. However, the quantitative robustness study of topological states which is indispensable in practical realization is rarely reported. In this work, we proposed topologically protected edge states with zigzag, bridge and armchair interfaces in a new twisted phononic plate. The robustness of non-trivial band gap in bulk structure is clearly presented versus twisted angles, revealing a threshold of 5 degrees which is the key fundamental information for the robustness of topological edge states. We further defined a localized displacement ratio as an efficient parameter to characterize edge states. Due to the different orientation of the three interfaces, zigzag and bridge edge states show higher quantitative robustness in their localized displacement ratio. A map of robustness as a function of both frequency and twisted angle highlights the better performance of the topological zigzag edge state. Robustness is evaluated for twisted angle and for all possible types of interfaces for the first time, which benefits for the design and fabrication of solid functional devices with great potential applications

Adaptive Locality Preserving Regression

This paper proposes a novel discriminative regression method, called adaptive locality preserving regression (ALPR) for classification. In particular, ALPR aims to learn a more flexible and discriminative projection that not only preserves the intrinsic structure of data, but also possesses the properties of feature selection and interpretability. To this end, we introduce a target learning technique to adaptively learn a more discriminative and flexible target matrix rather than the pre-defined strict zero-one label matrix for regression. Then a locality preserving constraint regularized by the adaptive learned weights is further introduced to guide the projection learning, which is beneficial to learn a more discriminative projection and avoid overfitting. Moreover, we replace the conventional `Frobenius norm' with the special l21 norm to constrain the projection, which enables the method to adaptively select the most important features from the original high-dimensional data for feature extraction. In this way, the negative influence of the redundant features and noises residing in the original data can be greatly eliminated. Besides, the proposed method has good interpretability for features owing to the row-sparsity property of the l21 norm. Extensive experiments conducted on the synthetic database with manifold structure and many real-world databases prove the effectiveness of the proposed method.Comment: The paper has been accepted by IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), and the code can be available at https://drive.google.com/file/d/1iNzONkRByIaUhXwdEhOkkh_0d2AAXNE8/vie

Inverse design of topological metaplates for flexural waves with machine learning

The mechanical analog to the topological insulators brings anomalous elastic wave properties which diversifies classic wave functions for potential broad applications. To obtain topological mechanical wave states with good quality at desired frequency ranges, it needs repetitive trials of different geometric parameters with traditional forward designs. In this work, we develop an inverse design of topological edge states for flexural wave using machine learning method which is promising for instantaneous design. Nonlinear mapping function from input targets to output desired parameters are adopted in artificial neural networks where the data sets for training are generated by the plane wave expansion method. Topological edge states are then realized and compared for different bandgap width conditions with such inverse designs, proving that wide bandgap can promote the confinement of the topological edge states. Finally, direction selective propagations with sharp turns are further demonstrated as anomalous wave behaviors. The machine learning inverse design of topological states for flexural wave provides an efficient way to design practical devices with targeted needs for potential applications such as signal processing, sensing and energy harvesting

Methodology for updating GO-FLOW model to handle scenario changes in nuclear power plants

The design of a nuclear power plant is proved to be safe enough in various hypothetical operation scenarios after strict safety assessment. One of the important tasks of operational risk management in a nuclear power plant is to evaluate whether any configuration change of the nuclear power plant can still achieve its expected safety and economic goals. This paper proposes a system reliability modeling and analysis method based on two-layers hierarchical GO-FLOW model. By flexibly adjusting the parameters of a GO-FLOW model, the model can adapt to the changes of success criteria and various configuration of the modeled system, thus avoiding the extra workload brought by re-modeling and improving the efficiency of risk management in nuclear power plants

Sound transmission loss of windows on high speed trains

The window is one of the main components of the high speed train car body structure through which noise can be transmitted. To study the windows’ acoustic properties, the vibration of one window of a high speed train has been measured for a running speed of 250 km/h. The corresponding interior noise and the noise in the wheel-rail area have been measured simultaneously. The experimental results show that the window vibration velocity has a similar spectral shape to the interior noise. Interior noise source identification further indicates that the window makes a contribution to the interior noise. Improvement of the window’s Sound Transmission Loss (STL) can reduce the interior noise from this transmission path. An STL model of the window is built based on wave propagation and modal superposition methods. From the theoretical results, the window’s STL property is studied and several factors affecting it are investigated, which provide indications for future low noise design of high speed train windows

Mediator recruits the cohesin loader Scc2 to RNA Pol II-transcribed genes and promotes sister chromatid cohesion.

[EN]The ring-like cohesin complex plays an essential role in chromosome segregation, organization, and double-strand break repair through its ability to bring two DNA double helices together. Scc2 (NIPBL in humans) together with Scc4 functions as the loader of cohesin onto chromosomes. Chromatin adapters such as the RSC complex facilitate the localization of the Scc2-Scc4 cohesin loader. Here, we identify a broad range of Scc2-chromatin protein interactions that are evolutionarily conserved and reveal a role for one complex, Mediator, in the recruitment of the cohesin loader. We identified budding yeast Med14, a subunit of the Mediator complex, as a high copy suppressor of poor growth in Scc2 mutant strains. Physical and genetic interactions between Scc2 and Mediator are functionally substantiated in direct recruitment and cohesion assays. Depletion of Med14 results in defective sister chromatid cohesion and the decreased binding of Scc2 at RNA Pol II-transcribed genes. Previous work has suggested that Mediator, Nipbl, and cohesin connect enhancers and promoters of active mammalian genes. Our studies suggest an evolutionarily conserved fundamental role for Mediator in the direct recruitment of Scc2 to RNA Pol II-transcribed genes

Urban integrated meteorological observations: practice and experience in Shanghai, China

Observations of atmospheric conditions and processes in citiesare fundamental to understanding the interactions between the urban surface and weather/climate, improving the performance of urban weather, air quality and climate models, and providing key information for city end-users (e.g. decision-makers, stakeholders, public). In this paper, Shanghai's urban integrated meteorological observation network (SUIMON) and some examples of intended applications are introduced. Its characteristics include being: multi- purpose (e.g. forecast, research, service), multi-function (high impact weather, city climate, special end-users), multi-scale (e.g. macro/meso-, urban-, neighborhood, street canyon), multi-variable (e.g. thermal, dynamic, chemical, bio-meteorological, ecological), and multi- platform (e.g. radar, wind profiler, ground-based, satellite based, in-situ observation/ sampling). Underlying SUIMON is a data management system to facilitate exchange of data and information. The overall aim of the network is to improve coordination strategies and instruments; to identify data gaps based on science and user driven requirements; and to intelligently combine observations from a variety of platforms by using a data assimilation system that is tuned to produce the best estimate of the current state of the urban atmosphere

Coupling Dynamic Behavior Characteristics of a Spacecraft Beam with Composite Laminated Structures and Large-Scale Motions

A nonlinear dynamic modeling method for a spacecraft body composed of a laminated composite beam undergoing large rotation is proposed in this paper. To study the characteristics of a laminated composite beam attached to a spacecraft body for the dynamic systems, the deformation description of a laminated beam is established with the consideration of laying angles and laying layers, and the displacement-strain relations is acquired based on the global-local higher-order shear deformation theory. Accordingly, a nonlinear dynamic model of the spacecraft body composed of a laminated composite beam is deduced using Hamilton variational principle. And the complete coupling terms for the laminated material properties are considered unlike any other singular or unidirectional materials. Then, the dynamic behavior of the spacecraft system is analyzed by comparison of an orthogonal-symmetric, singular, and unidirectional laminated beam. The results show that the laminated composite structures have significant influences on the dynamics properties of spacecraft compared with conventional equivalent singular or unidirectional materials. Hence, the nonlinear model is well suitable for approaching the problem of coupling relationship between geometric nonlinearity and large rotation motions. These conclusions will have significant theory and engineering practice values for coupling dynamics properties of laminated beams