Determining the stereochemical structures of biomolecules is very important for biomedicine, bioscience, and food safety due to distinct biological functions enantiomers. Chiral plasmonic sensors (CPSs) have demonstrated their ultra-sensitive detection ability a few picogram levels excited superchiral electromagnetic field near metasurfaces, which can greatly enhance interaction between lights chiral biomolecules. However, reported CPSs usually rely on intrinsic chiroptical effects that...

Abstract The Plasmon‐exciton strong coupling systems have attracted growing interests due to their powerful ability in manipulating the atomic energy levels, generating coherent quantum eigenstates, and offering promising applications communications, catalysis beyond. Chirality divides plasmon into two intriguing states that enable lots of new physical effects applications. However, between chiral excitons remains largely unexplored. This study demonstrates room‐temperature from one...

An ultra-narrow linewidth fiber ring laser is proposed and demonstrated based on Rayleigh backscattering (RBS) in a tapered optical fiber. The RBS short (∼110 m) acts as mode suppression element suppresses the of single longitudinal (SLM) our work, where stimulated Brillouin scattering largely suppressed. Our experimental results show that an ∼200 Hz achieved. feedback not only key to ensuring SLM oscillation, but also new mechanism further suppress laser.

Collaborative Filtering (CF) is one of the most successful algorithms in recommender systems. However, it suffers from data sparsity and scalability problems. Although many clustering techniques have been incorporated to alleviate these two problems, them fail achieve further significant improvement recommendation accuracy. First all, assume each user or item belongs a single cluster. Since usually users can hold multiple interests items may belong categories, more reasonable that join...

Recently, ranking-oriented collaborative filtering (CF) algorithms have achieved great success in recommender systems. They obtained state-of-the-art performances by estimating a preference ranking of items for each user rather than the absolute ratings on unrated (as conventional rating-oriented CF do). In this paper, we propose new algorithm, called ListCF. Following memory-based framework, ListCF directly predicts total order based similar users' probability distributions over...

The authors propose an automatic modulation classification algorithm to discriminate the radar emitter signals exploiting deep learning of convolutional neural network (CNN) based on a joint feature map. map including time‐frequency and instantaneous autocorrelation (IA) is generated achieve superior performance identification both phase modulated frequency signals. Afterwards, CNN designed extract features Training test samples are evaluate recognition rate CNN. Simulation results show that...

Collaborative filtering (CF) is one of the most effective techniques in recommender systems, which can be either rating oriented or ranking oriented. Ranking-oriented CF algorithms demonstrated significant performance gains terms accuracy, being able to estimate a precise preference items for each user rather than absolute ratings (as rating-oriented do). Conventional memory-based ranking-oriented referred as pairwise algorithms. They represent set preferences on pair similarity calculations...

In the Integrated Project Delivery (IPD) method, collaboration as a key factor can determine project's success directly. This study shows that is affected by two basic governance mechanisms: formal contracts and trust including goodwill competence trust. We found positively affects collaboration, while has an inverted U-shaped effect on collaboration. Analysis are related to Moreover, affect differently when they combined with contracts.

It is a research hot spot in cognitive electronic warfare systems to classify the electromagnetic signals of radar or communication system according their modulation characteristics. We construct multilayer hybrid machine learning network for classification seven types different modulation. extract signal features exploiting set algorithms such as time-frequency analysis, discrete Fourier transform, and instantaneous autocorrelation accomplish automatic using naive Bayesian support vector...

As a typical relational contracting (RC) method, integrated project delivery (IPD) attaches importance to key parties’ teamwork effectiveness. This study aims elucidate the relationship between RC norms and IPD effectiveness from social capital (SC) perspective examine moderating role of building information modeling (BIM) application level. Survey data 144 respondents were analyzed using structural equation modeling. The results show that both cognitive SC (shared vision) (trust) partially...

Remote sensing image fusion (RSIF) can generate an integrated with high spatial and spectral resolution. The fused remote is conducive to applications including disaster monitoring, ecological environment investigation, dynamic monitoring. However, most existing deep learning based RSIF methods require ground truths (or reference images) train a model, the acquisition of difficult problem. To address this, we propose semisupervised method on multiscale conditional generative adversarial...

There usually exist many news articles written in different languages about a hot event. The are ways to reflect standpoints. For example, the Chinese agencies and Western have published report same of Liu Xiaobo's Nobel Prize English languages, respectively. share something fact common, but they focus on aspects order standpoints In this paper, we investigate task multilingual summarization for purpose finding summarizing major differences between event languages. We propose novel...

Solving electronic structure problems represents a promising field of applications for quantum computers. Currently, much effort is spent in devising and optimizing algorithms near-term processors, with the aim outperforming classical counterparts on selected problem instances using limited resources. These methods are still expected to feature runtime preventing simulations large scale bulk systems. In this work, we propose strategy extend scope computational machine learning potential...