Modelling Instance-Level Annotator Reliability for Natural Language Labelling Tasks

When constructing models that learn from noisy labels produced by multiple annotators, it is important to accurately estimate the reliability of annotators. Annotators may provide labels of inconsistent quality due to their varying expertise and reliability in a domain. Previous studies have mostly focused on estimating each annotator's overall reliability on the entire annotation task. However, in practice, the reliability of an annotator may depend on each specific instance. Only a limited number of studies have investigated modelling per-instance reliability and these only considered binary labels. In this paper, we propose an unsupervised model which can handle both binary and multi-class labels. It can automatically estimate the per-instance reliability of each annotator and the correct label for each instance. We specify our model as a probabilistic model which incorporates neural networks to model the dependency between latent variables and instances. For evaluation, the proposed method is applied to both synthetic and real data, including two labelling tasks: text classification and textual entailment. Experimental results demonstrate our novel method can not only accurately estimate the reliability of annotators across different instances, but also achieve superior performance in predicting the correct labels and detecting the least reliable annotators compared to state-of-the-art baselines.Comment: 9 pages, 1 figures, 10 tables, 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL2019

Spin fluctuations and charge properties of core shell C80_{80}+M13_{13} (V, Mn, Cr, Ni, Co)

Transition metal clusters have a broad spectrum of potential applications in electronic and magnetic devices owing to their unique properties. Protective shells such as fullerene C$_{80}$ can be introduced to improve their stability. In this study, we optimized five core shell structures, C$_{80}$+M$_{13}$ (V, Mn, Cr, Ni, Co), and calculated their electromagnetic properties using density functional theory.We determined that there is electron transfer between C$_{80}$ and the transition metal clusters near the Fermi surface, and that the d orbitals contribute most to the magnetism of the structure. C$_{80}$+Ni$_{13}$ was antiferromagnetic. The magnetic properties of the clusters were significantly altered, revealing antiferromagnetism. The results establish a theoretical starting point for tuning the electronic and magnetic properties of 13-atom clusters embedded in fullerene cages

Bond relaxation, electronic and magnetic behavior of 2D metals structures Y on Li(110) surface

We investigated the bond, electronic and magnetic behavior of adsorption Yttrium atoms on Lithium (110) surface using a combination of Bond-order-length-strength(BOLS) correlation and density-functional theory(DFT). We found that adsorption Y atoms on Li(110) surfaces form two-dimensional (2D) geometric structures of hexagon, nonagon, solid hexagonal, quadrangle and triangle. The consistent with the magnetic moment are 6.66{\mu}B, 5.54{\mu}B, 0.28{\mu}B, 1.04{\mu}B, 2.81{\mu}B, respectively. In addition, this work could pave the way for design new 2D metals electronic and magnetic properties

Dynamic analysis and optimal control of a novel fractional-order 2I2SR rumor spreading model

In this paper, a novel fractional-order 2I2SR rumor spreading model is investigated. Firstly, the boundedness and uniqueness of solutions are proved. Then the next-generation matrix method is used to calculate the threshold. Furthermore, the stability of rumor-free/spreading equilibrium is discussed based on fractional-order Routh–Hurwitz stability criterion, Lyapunov function method, and invariance principle. Next, the necessary conditions for fractional optimal control are obtained. Finally, some numerical simulations are given to verify the results

Semi-wave and spreading speed of the nonlocal Fisher-KPP equation with free boundaries

In Cao, Du, Li and Li [8], a nonlocal diffusion model with free boundaries extending the local diffusion model of Du and Lin [12] was introduced and studied. For Fisher-KPP type nonlinearities, its long-time dynamical behaviour is shown to follow a spreading-vanishing dichotomy. However, when spreading happens, the question of spreading speed was left open in [8]. In this paper we obtain a rather complete answer to this question. We find a condition on the kernel function such that spreading grows linearly in time exactly when this condition holds, which is achieved by completely solving the associated semi-wave problem that determines this linear speed; when the kernel function violates this condition, we show that accelerating spreading happens

Hierarchical Modes Exploring in Generative Adversarial Networks

In conditional Generative Adversarial Networks (cGANs), when two different initial noises are concatenated with the same conditional information, the distance between their outputs is relatively smaller, which makes minor modes likely to collapse into large modes. To prevent this happen, we proposed a hierarchical mode exploring method to alleviate mode collapse in cGANs by introducing a diversity measurement into the objective function as the regularization term. We also introduced the Expected Ratios of Expansion (ERE) into the regularization term, by minimizing the sum of differences between the real change of distance and ERE, we can control the diversity of generated images w.r.t specific-level features. We validated the proposed algorithm on four conditional image synthesis tasks including categorical generation, paired and un-paired image translation and text-to-image generation. Both qualitative and quantitative results show that the proposed method is effective in alleviating the mode collapse problem in cGANs, and can control the diversity of output images w.r.t specific-level features

Topological Bonding and Electronic properties of Cd43_{43}Te28_{28} semiconductor material with microporous structure

CdTe is II-VI semiconductor material with excellent characteristics and has demonstrated promising potential for application in the photovoltaic field. The electronic properties of Cd43Te28 with microporous structures have been investigated based on density functional theory. The newly established binding-energy and bond-charge model have been used to convert the value of Hamiltonian into bonding values. We provide a method for describing topological chemical bonds by atomic coordinates and wave phases. We also discuss the dynamic process of the wave function with time and the magic cube matrix. This study provides an innovative method and technology for the accurate analysis of the topological bonding and electronic properties of microporous semiconductor materials

Recent advances in drug delivery of celastrol for enhancing efficiency and reducing the toxicity

Celastrol is a quinone methyl triterpenoid monomeric ingredient extracted from the root of Tripterygium wilfordii. Celastrol shows potential pharmacological activities in various diseases, which include inflammatory, obesity, cancer, and bacterial diseases. However, the application prospect of celastrol is largely limited by its low bioavailability, poor water solubility, and undesired off-target cytotoxicity. To address these problems, a number of drug delivery methods and technologies have been reported to enhance the efficiency and reduce the toxicity of celastrol. We classified the current drug delivery technologies into two parts. The direct chemical modification includes nucleic acid aptamer–celastrol conjugate, nucleic acid aptamer–dendrimer–celastrol conjugate, and glucolipid–celastrol conjugate. The indirect modification includes dendrimers, polymers, albumins, and vesicular carriers. The current technologies can covalently bond or encapsulate celastrol, which improves its selectivity. Here, we present a review that focalizes the recent advances of drug delivery strategies in enhancing the efficiency and reducing the toxicity of celastrol