Solid state NMR and X-ray diffraction studies of α-d-galacturonic acid monohydrate

Crystalline a-d-galacturonic acid monohydrate has been studied by 13C CPMAS NMR and X-ray crystallography. The molecular dynamics were investigated by evaluating 13C spin-lattice relaxation in the rotating frame (T1?) and chemical-shift-anisotropy properties of each carbon. Only limited molecular motions can be detected in the low frequency

Compressed sensing for enhanced through-the-wall radar imaging

Through-the-wall radar imaging (TWRI) is an emerging technology that aims to capture scenes behind walls and other visually opaque materials. The abilities to sense through walls are highly desirable for both military and civil applications, such as search and rescue missions, surveillance, and reconnaissance. TWRI systems, however, face with several challenges including prolonged data acquisition, large objects, strong wall clutter, and shadowing effects, which limit the radar imaging performances and hinder target detection and localization

A Rank-Deficient and Sparse Penalized Optimization Model for Compressive Indoor Radar Target Localization

This paper proposes a rank-deficient and sparse penalized optimization method for addressing the problem of through-wall radar imaging (TWRI) in the presence of structured wall clutter. Compressive TWRI enables fast data collection and accurate target localization, but faces with the challenges of incomplete data measurements and strong wall clutter. This paper handles these challenges by formulating the task of wall-clutter removal and target image reconstruction as a joint low-rank and sparse regularized minimization problem. In this problem,  the low-rank regularization is used to capture the low-dimensional structure of the wall signals and the sparse penalty is employed to represent the image of the indoor targets. We introduce an iterative algorithm based on the forward-backward proximal gradient technique to solve the large-scale optimization problem, which simultaneously removes unwanted wall clutter and reconstruct an image of indoor targets. Simulated and real radar data are used to validate the effectiveness of the proposed rank-deficient and sparse regularized optimization approach

Potential of mean force and the charge reversal of rodlike polyions

A simple model is presented to calculate the potential of mean force between a polyion and a multivalent counterion inside a polyelectrolite solution. We find that under certain conditions the electrostatic interactions can lead to a strong attraction between the polyions and the multivalent counterions, favoring formation of overcharged polyion-counterion complexes. It is found that small concentrations of salt enhance the overcharging, while an excessive amount of salt hinders the charge reversal. The kinetic limitations to overcharging are also examined.Comment: To be published in the special issue of Molecular Physics in honor of Prof. Ben Wido

Evolving modular soft robots without explicit inter-module communication using local self-attention

Modularity in robotics holds great potential. In principle, modular robots can be disassembled and reassembled in different robots, and possibly perform new tasks. Nevertheless, actually exploiting modularity is yet an unsolved problem: controllers usually rely on inter-module communication, a practical requirement that makes modules not perfectly interchangeable and thus limits their flexibility. Here, we focus on Voxel-based Soft Robots (VSRs), aggregations of mechanically identical elastic blocks. We use the same neural controller inside each voxel, but without any inter-voxel communication, hence enabling ideal conditions for modularity: modules are all equal and interchangeable. We optimize the parameters of the neural controller—shared among the voxels—by evolutionary computation. Crucially, we use a local self-attention mechanism inside the controller to overcome the absence of inter-module communication channels, thus enabling our robots to truly be driven by the collective intelligence of their modules. We show experimentally that the evolved robots are effective in the task of locomotion: thanks to self-attention, instances of the same controller embodied in the same robot can focus on different inputs. We also find that the evolved controllers generalize to unseen morphologies, after a short fine-tuning, suggesting that an inductive bias related to the task arises from true modularity

The mean-field theory for attraction between like-charged macromolecules

A mean-field theory based on Gibbs-Bogoliubov inequality is constructed to study the interactions between two like-charged polyions. It is shown that contrary to the previously established paradigm, a properly constructed mean-field theory can quantitatively account for the attractive interactions between two like-charged rods.Comment: 5 pages, 2 figures, elsart.sty neede

Finite Size Polyelectrolyte Bundles at Thermodynamic Equilibrium

We present the results of extensive computer simulations performed on solutions of monodisperse charged rod-like polyelectrolytes in the presence of trivalent counterions. To overcome energy barriers we used a combination of parallel tempering and hybrid Monte Carlo techniques. Our results show that for small values of the electrostatic interaction the solution mostly consists of dispersed single rods. The potential of mean force between the polyelectrolyte monomers yields an attractive interaction at short distances. For a range of larger values of the Bjerrum length, we find finite size polyelectrolyte bundles at thermodynamic equilibrium. Further increase of the Bjerrum length eventually leads to phase separation and precipitation. We discuss the origin of the observed thermodynamic stability of the finite size aggregates

WeakIdent: Weak formulation for Identifying Differential Equations using Narrow-fit and Trimming

Data-driven identification of differential equations is an interesting but challenging problem, especially when the given data are corrupted by noise. When the governing differential equation is a linear combination of various differential terms, the identification problem can be formulated as solving a linear system, with the feature matrix consisting of linear and nonlinear terms multiplied by a coefficient vector. This product is equal to the time derivative term, and thus generates dynamical behaviors. The goal is to identify the correct terms that form the equation to capture the dynamics of the given data. We propose a general and robust framework to recover differential equations using a weak formulation, for both ordinary and partial differential equations (ODEs and PDEs). The weak formulation facilitates an efficient and robust way to handle noise. For a robust recovery against noise and the choice of hyper-parameters, we introduce two new mechanisms, narrow-fit and trimming, for the coefficient support and value recovery, respectively. For each sparsity level, Subspace Pursuit is utilized to find an initial set of support from the large dictionary. Then, we focus on highly dynamic regions (rows of the feature matrix), and error normalize the feature matrix in the narrow-fit step. The support is further updated via trimming of the terms that contribute the least. Finally, the support set of features with the smallest Cross-Validation error is chosen as the result. A comprehensive set of numerical experiments are presented for both systems of ODEs and PDEs with various noise levels. The proposed method gives a robust recovery of the coefficients, and a significant denoising effect which can handle up to $100\%$ noise-to-signal ratio for some equations. We compare the proposed method with several state-of-the-art algorithms for the recovery of differential equations

The Aesthetics of Chinese Classical Theatre - A Performer’s View

In my thesis, I discuss the fundamental aesthetic philosophy underlying the traditions of Chinese Classical Theatre. I use the term “Chinese Classical Theatre” when referring particularly to Kunqu and Jingju (Peking Opera), since these two particular genres and their artistic values most clearly represent the characteristics of Chinese Traditional Theatre or Xiqu as a classical dramatic system. The term “Chinese Traditional Theatre” or Xiqu is used in a wider and more generic sense, to include all the many varieties of traditional and regional theatre. In the first chapter, I look at the broad historical development of Xiqu, from its original sources to its supreme expression – Kunqu and Jingju. In the second, the focus is on the essence of Taoism, which is the starting point of Chinese traditional aesthetics. Taoism and Buddhism have given Chinese artists total freedom from all limitations; and have inspired them to seek a truth beyond appearance. The third chapter concentrates on Confucianism, its contribution to ancient art education, and its influence on Xiqu stylization, in particular the art of different role-types and the function of percussive music. The fundamental concept of general education and the method of Xiqu training will be explored in the fourth chapter. I examine the Keban 科班 － the old system according to which Xiqu actors were trained; and use video materials to illustrate the modern Chinese institutions for training in the Classical Theatre. In the fifth and last chapter, through the analysis of two less than successful examples, I explore, at a deeper level, the core of Chinese traditional aesthetics and how that core can be lost or preserved in the process of reform