Host-guest interaction of cucurbit[8]uril with n-(3-aminopropyl)cyclohexylamine: Cyclohexyl encapsulation triggered ternary complex

2018 by the authors. The host-guest interaction of a series of cyclohexyl-appended guests with cucurbit[8]uril (Q[8] ) was studied by 1 H NMR spectroscopy, isothermal titration calorimetry (ITC), and X-ray crystallography. The X-ray structure revealed that two cycloalkane moieties can be simultaneously encapsulated in the hydrophobic cavity of the Q[8] host to form a ternary complex for the first time

A deep-learning-based approach for seismic surface-wave dispersion inversion (SfNet) with application to the Chinese mainlandKey points

Surface-wave tomography is an important and widely used method for imaging the crust and upper mantle velocity structure of the Earth. In this study, we proposed a deep learning (DL) method based on convolutional neural network (CNN), named SfNet, to derive the vS model from the Rayleigh wave phase and group velocity dispersion curves. Training a network model usually requires large amount of training datasets, which is labor-intensive and expensive to acquire. Here we relied on synthetics generated automatically from various spline-based vS models instead of directly using the existing vS models of an area to build the training dataset, which enhances the generalization of the DL method. In addition, we used a random sampling strategy of the dispersion periods in the training dataset, which alleviates the problem that the real data used must be sampled strictly according to the periods of training dataset. Tests using synthetic data demonstrate that the proposed method is much faster, and the results for the vS model are more accurate and robust than those of conventional methods. We applied our method to a dataset for the Chinese mainland and obtained a new reference velocity model of the Chinese continent (ChinaVs-DL1.0), which has smaller dispersion misfits than those from the traditional method. The high accuracy and efficiency of our DL approach makes it an important method for vS model inversions from large amounts of surface-wave dispersion data

Simultaneous removal of NO(x)and SO(2)using two-stage O(3)oxidation combined with Ca(OH)(2)absorption

This paper proposes two-stage O(3)oxidation combined with Ca(OH)(2)for simultaneous removal of NO(x)and SO2(NOx: Nitrogen oxides including NO, NO(2)and N2O5). In two-stage oxidation, NO was first oxidized to NO(2)in an oxidation tube, and NO(2)was further oxidized into N(2)O(5)in the spray tower. NO(x)and SO(2)were simultaneously removed in the spray tower. This method can effectively reduce the extra waste of O(3)caused by the decomposition of N2O5, especially at high temperature. Effects of various factors on denitrification efficiency were investigated. The results showed that the NO(x)removal efficiency decreased and O(3)extra consumption ratio increased with the increase of oxidation temperature or oxidation reaction time. When the O-3/NO molar ratio was 1.8, one-stage O(3)oxidation at 150(o)C extra wasted 33.3% of O-3. With the increase of O(3)concentration at site 2, the NO(x)removal efficiency first increased and then stabilized. Compared with the one-stage O(3)oxidation-absorption, the two-stage oxidation-absorption improved NO(x)removal efficiency from 62.5% to 89%. In addition, the increase of CaSO(3)slurry concentration had little effect on the denitrification efficiency

Distributed Face Recognition in Wireless Sensor Networks

As one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past few years. In order to construct an autonomous and robust biometric security system, this paper explores the application of face recognition technique in wireless sensor networks. Given the limited technological resources of sensor nodes, new challenges remain to be met. In this work, a facial component-based recognition mechanism is firstly applied to ensure the recognition accuracy. Secondly, in order to address the problem of resource constraints, a distributed scheme based on K-d trees is deployed for both the face image transmission and retrieval. According to the simulation results, the proposed method is capable of achieving considerable energy efficiency, while assuring the recognition accuracy

Directing curli polymerization with DNA origami nucleators

The physiological or pathological formation of fibrils often relies on molecular-scale nucleators that finely control the kinetics and structural features. However, mechanistic understanding of how protein nucleators mediate fibril formation in cells remains elusive. Here, we develop a CsgB-decorated DNA origami (CB-origami) to mimic protein nucleators in Escherichia coli biofilm that direct curli polymerization. We show that CB-origami directs curli subunit CsgA monomers to form oligomers and then accelerates fibril formation by increasing the proliferation rate of primary pathways. Fibrils grow either out from (departure mode) or towards the nucleators (arrival mode), implying two distinct roles of CsgB: as nucleation sites and as trap sites to capture growing nanofibrils in vicinity. Curli polymerization follows typical stop-and-go dynamics but exhibits a higher instantaneous elongation rate compared with independent fibril growth. This origami nucleator thus provides an in vitro platform for mechanistically probing molecular nucleation and controlling directional fibril polymerization for bionanotechnology

Diverse Supramolecular Nanofiber Networks Assembled by Functional Low-Complexity Domains

Self-assembling supramolecular nanofibers, common in the natural world, are of fundamental interest and technical importance to both nanotechnology and materials science. Despite important advances, synthetic nanofibers still lack the structural and functional diversity of biological molecules, and the controlled assembly of one type of molecule into a variety of fibrous structures with wide-ranging functional attributes remains challenging. Here, we harness the low-complexity (LC) sequence domain of fused in sarcoma (FUS) protein, an essential cellular nuclear protein with slow kinetics of amyloid fiber assembly, to construct random copolymer-like, multiblock, and self-sorted supramolecular fibrous networks with distinct structural features and fluorescent functionalities. We demonstrate the utilities of these networks in the templated, spatially controlled assembly of ligand-decorated gold nanoparticles, quantum dots, nanorods, DNA origami, and hybrid structures. Owing to the distinguishable nanoarchitectures of these nanofibers, this assembly is structure-dependent. By coupling a modular genetic strategy with kinetically controlled complex supramolecular self-assembly, we demonstrate that a single type of protein molecule can be used to engineer diverse one-dimensional supramolecular nanostructures with distinct functionalities