Fluorescent Double Network Hydrogels with Ionic Responsiveness and High Mechanical Properties for Visual Detection

We developed a fluorescent double network hydrogel with ionic responsiveness and high mechanical properties for visual detection.The nanocomposite hydrogel of laponite and polyacrylamide serves as the first network,while the ionic cross-linked hydrogel of terbium ions and sodium alginate serves as the second network.The double-network structure,the introduction of nanoparticles and the reversible ionic crosslinked interactions confer high mechanical properties to the hydrogel.Terbium ions are not only used as the ionic cross-linked points,but also used as green emitters to endow hydrogels with fluorescent properties.On the basis of the “antenna effect” of terbium ions and the ion exchange interaction,the fluorescence of the hydrogels can make selective responses to various ions(such as organic acid radical ions,transition metal ions) in aqueous solutions,which enables a convenient strategy for visual detection toward ions.Consequently,the fluorescent double network hydrogel fabricated in this study is promising for use in the field of visual sensor detection.

Refinement of Adaptive Dynamical Simulation of Quantum Mechanical Double Slit Interference Phenomenon

We applied adaptive dynamics to double slit interference phenomenon using particle model and obtained partial successful results in our previous report. The patterns qualitatively corresponded well with experiments. Several properties such as concave single slit pattern and large influence of slight displacement of the emission position were different from the experimental results. In this study we tried other slit conditions and obtained consistent patterns with experiments. We do not claim that the adaptive dynamics is the principle of quantum mechanics, but the present results support the probability of adaptive dynamics as the candidate of the basis of quantum mechanics. We discuss the advantages of the adaptive dynamical view for foundations of quantum mechanics.

Clothing Parsing Based on Multi-Scale Fusion and Improved Self-Attention Mechanism

Due to the lack of long-range association and spatial location information,fine details and accurate boundaries of complex clothing images cannot always be obtained by using the existing deep learning-based methods.This paper presents a convolutional structure with multi-scale fusion to optimize the step of clothing feature extraction and a self-attention module to capture long-range association information.The structure enables the self-attention mechanism to directly participate in the process of information exchange through the down-scaling projection operation of the multi-scale framework.In addition,the improved self-attention module introduces the extraction of 2-dimensional relative position information to make up for its lack of ability to extract spatial position features from clothing images.The experimental results based on the colorful fashion parsing dataset(CFPD)show that the proposed network structure achieves 53.68%mean intersection over union(mIoU)and has better performance on the clothing parsing task.

Hierarchical multihead self-attention for time-series-based fault diagnosis

Fault diagnosis is important for maintaining the safety and effectiveness of chemical process.Considering the multivariate,nonlinear,and dynamic characteristic of chemical process,many time-series-based data-driven fault diagnosis methods have been developed in recent years.However,the existing methods have the problem of long-term dependency and are difficult to train due to the sequential way of training.To overcome these problems,a novel fault diagnosis method based on time-series and the hierarchical multihead self-attention(HMSAN)is proposed for chemical process.First,a sliding window strategy is adopted to construct the normalized time-series dataset.Second,the HMSAN is developed to extract the time-relevant features from the time-series process data.It improves the basic self-attention model in both width and depth.With the multihead structure,the HMSAN can pay attention to different aspects of the complicated chemical process and obtain the global dynamic features.However,the multiple heads in parallel lead to redundant information,which cannot improve the diagnosis performance.With the hierarchical structure,the redundant information is reduced and the deep local time-related features are further extracted.Besides,a novel many-to-one training strategy is introduced for HMSAN to simplify the training procedure and capture the long-term dependency.Finally,the effectiveness of the proposed method is demonstrated by two chemical cases.The experimental results show that the proposed method achieves a great performance on time-series industrial data and outperforms the state-of-the-art approaches.

A theoretical study of the signal enhancement mechanism of coaxial DP-LIBS

In the field of dual-pulse laser-induced breakdown spectroscopy(DP-LIBS)research,the pursuit of methods for determining pulse intervals and other parameters quickly and conveniently in order to achieve optimal spectral signal enhancement is paramount.To aid researchers in identification of optimal signal enhancement conditions and more accurate interpretation of the underlying signal enhancement mechanisms,theoretical simulations of the spatiotemporal processes of coaxial DP-LIBS-induced plasma have been established in this work.Using a model based on laser ablation and two-dimensional axisymmetric fluid dynamics,plasma evolutions during aluminum–magnesium alloy laser ablation under single-pulse and coaxial dualpulse excitations have been simulated.The influences of factors,such as delay time,laser fluence,plasma temperature,and particle number density,on the DP-LIBS spectral signals are investigated.Under pulse intervals ranging from 50 to 1500 ns,the time evolutions of spectral line intensity,dual-pulse emission enhancement relative to the single-pulse results,laser irradiance,spatial distribution of plasma temperature and species number density,as well as laser irradiance shielded by plasma have been obtained.The study indicates that the main reason behind the radiation signal enhancement in coaxial DP-LIBS-induced plasma is attributed to the increased species number density and plasma temperature caused by the second laser,and it is inferred that the shielding effect of the plasma mainly occurs in the boundary layer of the stagnation point flow over the target surface.This research provides a theoretical basis for experimental research,parameter optimization,and signal enhancement tracing in DP-LIBS.

Double deck bridge behavior and failure mechanism under seismic motions using nonlinear analyzes

This paper investigates the behavior and the failure mechanism of a double deck bridge constructed in China through nonlinear time history analysis. A parametric study was conducted to evaluate the influence of different structural characteristics on the behavior of the double deck bridge under transverse seismic motions, and to detect the effect of bi- directional loading on the seismic response of this type of bridge. The results showed that some characteristics, such as the variable lateral stiffness, the foundation modelling, and the longitudinal reinforcement ratio of the upper and lower columns of the bridge pier bents have a major impact on the double deck bridge response and its failure mechanism under transverse seismic motions. It was found that the soft story failure mechanism ：is not unique to the double deck bridge and its occurrence is related to some conditions and structural characteristics of the bridge structure. The analysis also showed that the seismic vulnerability of the double deck bridge under bi-directional loading： was severely increased compared to the bridge response under unidirectional transverse loading, and out-of-phase movements were triggered between adjacent girders.

Mathematical Model and Geometrical Model of Double Pitch ZN-type Worm Gear Set Based on Generation Mechanism

The current researches on the tooth surface mathematical equations and the theory of gearing mainly pay attention to the ordinary type worm gear set（e.g., ZN, ZA, or ZK）. The research of forming mechanism and three-dimensional modeling method for the double pitch worm gear set is not enough. So there are some difficulties in mathematical model deducing and geometry modeling of double pitch ZN-type worm gear set based on generation mechanism. In order to establish the mathematical model and the precise geometric model of double pitch ZN-type worm gear set, the structural characteristics and generation mechanism of the double pitch ZN-type worm gear set are investigated. Mathematical model of the ZN-type worm gear set is derived based on its generation mechanism and the theory of gearing. According to the mathematical model of the worm gear set which has been developed, a geometry modeling method of the double pitch ZN-type worm and worm gear is presented. Furthermore, a geometrical precision calculate method is proposed to evaluate the geometrical quality of the double pitch worm gear set. As a result, the maximum error is less than 6′10–4 mm in magnitude, thus the model of the double pitch ZN-type worm gear set is available to meet the requirements of finite element analysis and engineering application. The derived mathematical model and the proposed geometrical modeling method are helpful to guiding the design, manufacture and contact analysis of the worm gear set.

Sentiment classification model for bullet screen based on self-attention mechanism

With the development of short video industry,video and bullet screen have become important ways to spread public opinions.Public attitudes can be timely obtained through emotional analysis on bullet screen,which can also reduce difficulties in management of online public opinions.A convolutional neural network model based on multi-head attention is proposed to solve the problem of how to effectively model relations among words and identify key words in emotion classification tasks with short text contents and lack of complete context information.Firstly,encode word positions so that order information of input sequences can be used by the model.Secondly,use a multi-head attention mechanism to obtain semantic expressions in different subspaces,effectively capture internal relevance and enhance dependent relationships among words,as well as highlight emotional weights of key emotional words.Then a dilated convolution is used to increase the receptive field and extract more features.On this basis,the above multi-attention mechanism is combined with a convolutional neural network to model and analyze the seven emotional categories of bullet screens.Testing from perspectives of model and dataset,experimental results can validate effectiveness of our approach.Finally,emotions of bullet screens are visualized to provide data supports for hot event controls and other fields.

Evaluation of the Double Snap-Through Mechanism on the Wave Energy Converter’s Performance

Lower efficiencies induce higher energy costs and pose a barrier to wave energy devices'commercial applications.Therefore,the efficiency enhancement of wave energy converters has received much attention in recent decades.The reported research presents the double snap-through mechanism applied to a hemispheric point absorber type wave energy converter(WEC)to improve the energy absorption perfomance.The double snap-through mechanism comprises four oblique springs mounted in an X-configuration.This provides the WEC with different dynamic stability behaviors depending on the particular geometric and physical parameters employed.The efficiency of these different WEC behaviors(linear,bistable,and tristable)was initially evaluated under the action of regular waves.The results for bistable or tristable responses indicated significant improvements in the WEC's energy capture efficiency.Furthermore,the WEC frequency bandwidth was shown to be significantly enlarged when the tristable mode was in operation.However,the corresponding tristable trajectory showed intra-well behavior in the middle potential well,which induced a more severe low-energy absorption when a small wave amplitude acted on the WEC compared to when the bistable WEC was employed.Nevertheless,positive effects were observed when appropriate initial conditions were imposed.The results also showed that for bistable or tristable responses,a suitable spring stiffness may cause the buoy to oscillate in high energy modes.

DOUBLE SYNERGISTIC EFFECTS AND EXTRACTION KINETICS OF A MICELLE MIXED EXTRACTANT SYSTEM I DOUBLE(KINETIC AND THERMODYNAMIC)SYNERGISTIC EFFECTS AND EXTRACTION MECHANISMS

The equilibria and kinetic characteristics of a micelle mixed extractant system-D2 EHPA-MPA（MPA-monoalkyl phosphoric acid with long carbon chain and micellization）in extractionof the Al3+ions were studied.It was found that the system has double synergistic effects on theextraction of the Al3+ions.The compositions of the synergistic complexes were determined andthe synergistic reaction equations were obtained.

Keyphrase Generation Based on Self-Attention Mechanism

Keyphrase greatly provides summarized and valuable information.This information can help us not only understand text semantics,but also organize and retrieve text content effectively.The task of automatically generating it has received considerable attention in recent decades.From the previous studies,we can see many workable solutions for obtaining keyphrases.One method is to divide the content to be summarized into multiple blocks of text,then we rank and select the most important content.The disadvantage of this method is that it cannot identify keyphrase that does not include in the text,let alone get the real semantic meaning hidden in the text.Another approach uses recurrent neural networks to generate keyphrases from the semantic aspects of the text,but the inherently sequential nature precludes parallelization within training examples,and distances have limitations on context dependencies.Previous works have demonstrated the benefits of the self-attention mechanism,which can learn global text dependency features and can be parallelized.Inspired by the above observation,we propose a keyphrase generation model,which is based entirely on the self-attention mechanism.It is an encoder-decoder model that can make up the above disadvantage effectively.In addition,we also consider the semantic similarity between keyphrases,and add semantic similarity processing module into the model.This proposed model,which is demonstrated by empirical analysis on five datasets,can achieve competitive performance compared to baseline methods.

Mechanism of Excited State Double Proton Transfer in 2-Amino-3-Methoxypyridine and Acetic Acid Complex

The excited-state double-proton transfer （ESDPT） mechanism of 2-amino-3-methoxypyridine and acetic acid com- plex is studied by the density functional theory （DFT） and time-dependent DFT with CAM-B3LYP functional. The complex is connected through two different types of inter-molecular hydrogen bonds. After photo-excitation, both hydrogen bonds get strengthened, which can facilitate the ESDPT reaction. The scanned potential energy curve along the proton transfer coordinate indicates that the ESDPT reaction proceeds in a stepwise pattern.

A Double Network Hydrogel with High Mechanical Strength and Shape Memory Properties

Double network(DN)hydrogels as one kind of tough gels have attracted extensive at-tention for their potential applications in biomedical and load-bearing fields.Herein,we import more functions like shape memory into the conventional tough DN hydro-gel system.We synthesize the PEG-PDAC/P(AAm-co-AAc)DN hydrogels,of which the first network is a well-defined PEG(polyethylene glycol)network loaded with PDAC(poly(acryloyloxyethyltrimethyl ammonium chloride))strands,while the second network is formed by copolymerizing AAm(acrylamide)with AAc(acrylic acid)and cross-linker MBAA(N;N′-methylenebisacrylamide).The PEG-PDAC/P(AAm-co-AAc)DN gels exhibits high mechanical strength.The fracture stress and toughness of the DN gels reach up to 0.9 MPa and 3.8 MJ/m^3,respectively.Compared with the conventional double network hydrogels with neutral polymers as the soft and ductile second network,the PEG-PDAC/P(AAm-co-AAc)DN hydrogels use P(AAm-co-AAc),a weak polyelectrolyte,as the second network.The AAc units serve as the coordination points with Fe^3+ions and physically crosslink the second network,which realizes the shape memory property activated by the reducing ability of ascorbic acid.Our results indicate that the high mechanical strength and shape memory properties,probably the two most important characters related to the potential application of the hydrogels,can be introduced simultaneously into the DN hydrogels if the functional monomer has been integrated into the network of DN hydrogels smartly.

Effect of double aging on mechanical properties and microstructure of EV31A alloy

To improve the ductility of a commercial Mg−rare earth alloy EV31A(Mg−3Nd−1.5Gd−0.3Zn−0.5Zr),a heat treatment method called double aging is explored,and its effect on mechanical properties and microstructure of the alloy is studied.Ultimate strength and elongation of the alloy can be increased to 288 MPa and 6.6%by the optimum double aging process,compared to 273 MPa and 4.9%after single aging.Time consumption of the aging process is also significantly decreased from 16 h(single aging)to 2 h.HAADF-STEM characterization shows that the primary precipitate isβ'phase,which is similar toβ'phase in Mg−Nd binary alloy.By double aging,theβ'phase is finer and more densely distributed compared with single aging,with approximately double density and half size,which explains the improvement in strength and ductility.

Mechanical performance and texture characteristic of an IF steel containing Nb and Ti by double cold rolling

Single cold rolling and double cold rolling were applied to hot rolled strips with different reduction ratios. The evolutions of { 100}, { 111} and Goss face texture during double rolling were investigated by comparing the orientation distribution function （ODF） of the double rolled sample with that of the single rolled one. The double cold rolling texture is characterized by a higher γ-texture and a lower α-texture, and the { 111}〈112〉 component is improved remarkably. Based on the TEM observation and mechanical properties test, it is found that the reduction ratio assignment significantly affects the texture variation, as-annealing microstructures, and properties of the double cold rolled samples. These results may provide a theoretical guide for the industrial production of double cold rolled IF steel.

A Consortium Blockchain-enabled Double Auction Mechanism for Peer-to-peer Energy Trading among Prosumers

This paper investigates a double auction-based peer-to-peer(P2P)energy trading market for a community of renewable prosumers with private information on reservation price and quantity of energy to be traded.A novel competition padding auction(CPA)mechanism for P2P energy trading is proposed to address the budget deficit problem while holding the advantages of the widely-used Vickrey-Clarke-Groves mechanism.To illustrate the theoretical properties of the CPA mechanism,the sufficient conditions are identified for a truth-telling equilibrium with a budget surplus to exist,while further proving its asymptotical economic efficiency.In addition,the CPA mechanism is implemented through consortium blockchain smart contracts to create safer,faster,and larger P2P energy trading markets.The proposed mechanism is embedded into blockchain consensus protocols for high consensus efficiency,and the budget surplus of the CPA mechanism motivates the prosumers to manage the blockchain.Case studies are carried out to show the effectiveness of the proposed method.

Phase-dependent double optomechanically induced transparency in a hybrid optomechanical cavity system with coherently mechanical driving

We propose a scheme that can generate tunable double optomechanically induced transparency in a hybrid optomechanical cavity system.In this system, the mechanical resonator of the optomechanical cavity is coupled with an additional mechanical resonator and the additional mechanical resonator can be driven by a weak external coherently mechanical driving field.We show that both the intensity and the phase of the external mechanical driving field can control the propagation of the probe field, including changing the transmission spectrum from double windows to a single-window.Our study also provides an effective way to generate intensity-controllable, narrow-bandwidth transmission spectra, with the probe field modulated from excessive opacity to remarkable amplification.

Double optomechanical transparency with direct mechanical interaction

We present a mechanism for double transparency in an optomechanical system. This mechanism is based on the coupling of a moving cavity mirror to a second mechanical oscillator. Due to the purely mechanical coupling and the radiation pressure, three pathways are established for excitations of the probe photons into the cavity photons. Destructive interference occurs at two different frequencies, leading to double transparency to the probe field, It is the coupling strength between the mechanical oscillators that determines the locations of the transparency windows. Moreover, the normal splitting appears for the generated Stokes field and the four-wave mixing process is inhibited on resonance.