In this work, self‐healing polyampholyte hydrogels with high mechanical strength in megapascal order, good resilience, improved toughness, and satisfactory conductivity are fabricated via one‐step ...polymerization of positively charged imidazolium‐based ionic liquid monomers containing urea groups and negatively charged 3‐sulfopropyl methacrylate potassium salt monomers followed by subsequent dialysis in water. Dialysis can remove partial counter ions in the original hydrogels to strengthen electrostatic interactions between imidazolium and sulfonate groups and improve mechanical strength of the hydrogels. After dialysis for 3 d, the originally soft hydrogels become mechanically robust with a tensile strength of ≈1.3 MPa, strain at break of ≈720%, and toughness of ≈6.7 MJ m−3. Hydrogen‐bonding interactions between urea groups, which act as sacrificial bonds to dissipate energy, are important to improve the mechanical strength and toughness of the hydrogels. More importantly, the hydrogel can automatically heal from physical cut at room temperature with a healing efficiency of ≈91% because of the reversibility of the electrostatic and hydrogen‐bonding interactions. Because of the undialyzed salts in the hydrogels, the mechanically robust hydrogels possess a satisfactory ionic conductivity of ≈3 S m−1 at room temperature and can serve as highly flexible and stretchable conductors with self‐healing capacity.
Self‐healing polyampholyte hydrogels with high mechanical strength, good resilience, improved toughness, and satisfactory conductivity are fabricated via copolymerization of imidazolium‐based ionic liquid monomers and sulfonate‐containing methacrylate monomers, followed by dialysis in water to partially remove salts. The hydrogels, which are cross linked by reversible electrostatic and hydrogen‐bonding interactions, can automatically heal from physical cut at room temperature to restore mechanical strength and conductivity.
This article studies the problem of distributed formation maneuver control of multiagent systems via complex Laplacian. We will show how to change the translation, scaling, rotation, and also the ...shape of formation continuously by only tuning the positions of the leaders in both 2-D and 3-D spaces, where the rotation of formation in the 3-D space is realized by changing the yaw angle, pitch angle, and roll angle of formation sequentially. Compared with real-Laplacian-based methods, the first advantage of the proposed complex-Laplacian-based approach is that each follower requires fewer neighbors and lesser communication. The second advantage is that nonconvex and nongeneric nominal configurations are allowed and the uniqueness of the complex-constraint-based target formation can be guaranteed by the noncollocated nominal agents. The third advantage is that more formation shapes can be realized by only tuning the positions of the leaders. Two simulation examples are given to illustrate the theoretical results.
Human infection with the novel avian-origin influenza A (H7N9) virus has aroused global concern. In this report, the clinical characteristics of 111 laboratory-confirmed cases in China are presented.
...On March 30, 2013, three patients with fatal cases of rapid, progressive pneumonia were confirmed to be infected with a novel avian-origin influenza A (H7N9) virus that had not been detected in humans and animals previously.
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The new human H7N9 viruses are the product of reassortment of viruses that are of avian origin.
Global attention was soon focused on the situation because of the increasing number of new cases and the high rate of death associated with these infections.
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As of May 9, the World Health Organization (WHO) had reported 131 laboratory-confirmed cases, including 32 deaths.
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However, data on . . .
Photocatalytic hydrogen production has been considered a promising approach to obtain green hydrogen energy. Crystalline porous materials have arisen as key photocatalysts for efficient hydrogen ...production. Here, we report a strategy to in situ photodeposit platinum clusters as cocatalyst on a covalent organic framework, which makes it an efficient photocatalyst for light-driven hydrogen evolution. Periodically dispersed adsorption sites of platinum species are constructed by introducing adjacent hydroxyl group and imine-N in the region of the covalent organic framework structural unit where photogenerated electrons converge, leading to the in situ reduction of the adsorbed platinum species into metal clusters by photogenerated electrons. The widespread platinum clusters on the covalent organic framework expose large active surface and greatly facilitate the electron transfer, finally contributing to a high photocatalytic hydrogen evolution rate of 42432 μmol g
h
at 1 wt% platinum loading. This work provides a direction for structural design on covalent organic frameworks to precisely manipulate cocatalyst morphologies and positions at the atomic level for developing efficient photocatalysts.
This article investigates the localization problem of a network in 2-D and 3-D spaces given the positions of anchor nodes in a global frame and internode relative measurements in local coordinate ...frames. It is assumed that the local frames of different nodes have different unknown orientations. First, an angle-displacement rigidity theory is developed, which can be used to localize all the free nodes by the known positions of the anchor nodes and local relative measurements (local relative position, distance, local relative bearing, angle, or ratio-of-distance measurements). Then, necessary and sufficient conditions for network localizability are given. Finally, a distributed network localization protocol is proposed, which can globally estimate the locations of all the free nodes of a network if the network is infinitesimally angle-displacement rigid. The proposed method unifies local-relative-position-based, distance-based, local-relative-bearing-based, angle-based, and ratio-of-distance-based distributed network localization approaches. The novelty of this article is that the proposed method can be applied in both generic and nongeneric configurations with an unknown global coordinate frame in both 2-D and 3-D spaces.
This paper reviews developments in cascaded microresonator-based matrix switches for silicon photonic interconnection networks in many-core computing applications. Specifically, we emphasize our ...recently proposed 5 times 5 matrix switch comprising two-dimensionally cascaded microring resonator-based electrooptic switches coupled to a waveguide cross-grid on a silicon chip. The cross-grid adopts low-loss low-crosstalk multimode-interference-based waveguide crossings. Such a microresonator-based matrix switch offers nonblocking interconnections among multiple inputs and multiple outputs, with the key merits of i) a tens to hundreds of micrometers-scale footprint, ii) gigabit/second-scale data transmission, iii) nanosecond-speed circuit-switching, iv) 100-muW-scale DC power consumption per link, and v) large-scale integration for networks-on-chips applications. We analyze in detail the microring resonator-based cross-grid switch design for high-data-rate signal transmission in the context of our proposed 5 times 5 matrix switch. We also study the feasibility of large-scale integration of the matrix switch. We report proof-of-concept experiments of a single cross-grid switch element and a 2 times 2 matrix switch, propose design guidelines, and discuss future engineering challenges.
The primary objective in synthetic organic chemistry is to develop highly efficient, selective, and versatile synthetic methodologies, which are essential for discovering new drug candidates and ...agrochemicals. In this study, we present a unified strategy for a one-pot, catalytic enantioselective synthesis of α-alkyl and α,α'-dialkyl pyrrolidine, piperidine, and indolizidine alkaloids using readily available amides and alkynes. This synthesis is enabled by the identification and development of an Ir/Cu/N-PINAP catalyzed highly enantioselective and chemoselective reductive alkynylation of α-unbranched aliphatic amides, which serves as the key reaction. This reaction is combined with Pd-catalyzed tandem reactions in a one-pot approach, enabling the collective, catalytic enantioselective total syntheses of eight alkaloids and an anticancer antipode with 90-98% ee. The methodology's enantio-divergence is exemplified by the one-step access to either enantiomer of alkaloid bgugaine.
This article studies the problem of integrated distributed network localization and formation maneuver control. We develop an integrated relative-measurement-based scheme, which only uses relative ...positions, distances, bearings, angles, ratio-of-distances, or their combination to achieve distributed network localization and formation maneuver control in <inline-formula><tex-math notation="LaTeX">\mathbb {R}^{d} (d \geq 2)</tex-math></inline-formula>. By exploring the localizability and invariance of the target formation, the scale, rotation, and translation of the formation can be controlled simultaneously by only tuning the leaders' positions, i.e., the followers do not need to know parameters of the scale, rotation, and translation of the target formation. The proposed method can globally drive the formation errors to zero in finite time over multilayer <inline-formula><tex-math notation="LaTeX">d\!+\!1</tex-math></inline-formula>-rooted graphs. A simulation example is given to illustrate the theoretical results.
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bstract
Based on the jet image approach, which treats the energy deposition in each calorimeter cell as the pixel intensity, the Convolutional neural network (CNN) method has been found to achieve ...a sizable improvement in jet tagging compared to the traditional jet substructure analysis. In this work, the Mask R-CNN framework is adopted to reconstruct Higgs jets in collider-like events, with the effects of pileup contamination taken into account. This automatic jet reconstruction method achieves higher efficiency of Higgs jet detection and higher accuracy of Higgs boson four-momentum reconstruction than traditional jet clustering and jet substructure tagging methods. Moreover, the Mask R-CNN trained on events containing a single Higgs jet is capable of detecting one or more Higgs jets in events of several different processes, without apparent degradation in reconstruction efficiency and accuracy. The outputs of the network also serve as new handles for the
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background suppression, complementing to traditional jet substructure variables.
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