Graph is an important data representation which appears in a wide diversity of real-world scenarios. Effective graph analytics provides users a deeper understanding of what is behind the data, and ...thus can benefit a lot of useful applications such as node classification, node recommendation, link prediction, etc. However, most graph analytics methods suffer the high computation and space cost. Graph embedding is an effective yet efficient way to solve the graph analytics problem. It converts the graph data into a low dimensional space in which the graph structural information and graph properties are maximumly preserved. In this survey, we conduct a comprehensive review of the literature in graph embedding. We first introduce the formal definition of graph embedding as well as the related concepts. After that, we propose two taxonomies of graph embedding which correspond to what challenges exist in different graph embedding problem settings and how the existing work addresses these challenges in their solutions. Finally, we summarize the applications that graph embedding enables and suggest four promising future research directions in terms of computation efficiency, problem settings, techniques, and application scenarios.
To deter financial misstatements, many companies have recently adopted compensation recovery policies—commonly known as "clawbacks"—that authorize the board to recoup compensation paid to executives ...based on misstated financial reports. Clawbacks have been shown to reduce financial misstatements and increase investors' confidence on earnings information. We show that the benefits come with an unintended consequence of certain firms substituting for accruals management with real transactions management (e.g., reduce research and development R&D expenditures), especially firms with strong incentives to achieve short-term earnings targets, such as firms with high growth or high transient institutional ownership. As such, the total amount of earnings management does not decrease subsequent to clawback adoption. We further show that although real transactions management temporarily boosts those clawback adopters' short-term profitability and stock performance, this trend reverses after three years. In summary, clawbacks may have unexpected effects for a subset of firms whose managers are under greater pressure to meet earnings goals.
We experimentally demonstrate topological edge states arising from the valley-Hall effect in two-dimensional honeycomb photonic lattices with broken inversion symmetry. We break the inversion ...symmetry by detuning the refractive indices of the two honeycomb sublattices, giving rise to a boron nitridelike band structure. The edge states therefore exist along the domain walls between regions of opposite valley Chern numbers. We probe both the armchair and zigzag domain walls and show that the former become gapped for any detuning, whereas the latter remain ungapped until a cutoff is reached. The valley-Hall effect provides a new mechanism for the realization of time-reversal-invariant photonic topological insulators.
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The key to the effective control of a diffusion system lies in how accurately we could predict its unfolding dynamics based on the observation of its current state. However, in the real-world ...applications, it is often infeasible to conduct a timely and yet comprehensive observation due to resource constraints. In view of such a practical challenge, the goal of this work is to develop a novel computational method for performing active observations, termed active surveillance, with limited resources. Specifically, we aim to predict the dynamics of a large spatio-temporal diffusion system based on the observations of some of its components. Towards this end, we introduce a novel measure, the <inline-formula><tex-math notation="LaTeX">\boldsymbol{\gamma }</tex-math> <mml:math><mml:mi>γ</mml:mi></mml:math><inline-graphic xlink:href="yang-ieq1-3023092.gif"/> </inline-formula> value, that enables us to identify the key components by means of modeling a sentinel network with a row sparsity structure. Having obtained a theoretical understanding of the <inline-formula><tex-math notation="LaTeX">\boldsymbol{\gamma }</tex-math> <mml:math><mml:mi>γ</mml:mi></mml:math><inline-graphic xlink:href="yang-ieq2-3023092.gif"/> </inline-formula> value, we design a backward-selection sentinel network mining algorithm (SNMA) for deriving the sentinel network via group sparse Bayesian learning . In order to be practically useful, we further address the issue of scalability in the computation of SNMA, and moreover, extend SNMA to the case of a non-linear dynamical system that could involve complex diffusion mechanisms. We show the effectiveness of SNMA by validating it using both synthetic datasets and five real-world datasets. The experimental results are appealing, which demonstrate that SNMA readily outperforms the state-of-the-art methods.
Although firm-initiated clawbacks reduce accounting manipulation, they also induce managers to engage in suboptimal activities (e.g., reduce research and development (R&D) expenses) to achieve ...earnings targets. To assess the effectiveness of clawback provisions, we examine their impact from debtholders' point of view. We find that banks use more financial covenants and performance pricing provisions in the loan contracts and decrease interest rates after firms initiate clawbacks. Moreover, we also find that loan maturity increases and loan collateral decreases subsequent to clawback adoption. Taken together, our findings indicate that firm-initiated clawback provisions enhance financial reporting quality, thereby reducing the information uncertainty that financing providers face.
Weyl points are isolated degeneracies in reciprocal space that are monopoles of the Berry curvature. This topological charge makes them inherently robust to Hermitian perturbations of the system. ...However, non-Hermitian effects, usually inaccessible in condensed-matter systems, are an important feature of photonic systems, and when added to an otherwise Hermitian Weyl material have been predicted to spread the Berry charge of the Weyl point out onto a ring of exceptional points, creating a Weyl exceptional ring and fundamentally altering its properties. Here, we observe the implications of the Weyl exceptional ring using real-space measurements of an evanescently coupled bipartite optical waveguide array by probing its effects on the Fermi arc surface states and bulk diffraction properties of the two constituent sublattices in an experimental realization of a distributed Berry charge in a topological material.
In this paper, we present a comprehensive review and discussion of the state-of-the-art device technology and application development of GaN-on-Si power electronics. Several device technologies for ...realizing normally off operation that is highly desirable for power switching applications are presented. In addition, the examples of circuit applications that can greatly benefit from the superior performance of GaN power devices are demonstrated. Comparison with other competing power device technology, such as Si superjunction-MOSFET and SiC MOSFET, is also presented and analyzed. Critical issues for commercialization of GaN-on-Si power devices are discussed with regard to cost, reliability, and ease of use.
Interface engineering is a key strategy to deal with the two-dimensional (2D)/three-dimensional (3D) hybrid heterostructure, since the properties of this atomic-layer-thick 2D material can easily be ...impacted by the substrate environment. In this work, the structural, electronic, and optical properties of the 2D/3D heterostructure of monolayer MoS2 on wurtzite GaN surface without and with nitridation interfacial layer are systematically investigated by first-principles calculation and experimental analysis. The nitridation interfacial layer can be introduced into the 2D/3D heterostructure by remote N2 plasma treatment to GaN sample surface prior to stacking monolayer MoS2 on top. The calculation results reveal that the 2D/3D integrated heterostructure is energetically favorable with a negative formation energy. Both interfaces demonstrate indirect band gap, which is a benefit for longer lifetime of the photoexcited carriers. Meanwhile, the conduction band edge and valence band edge of the MoS2 side increases after nitridation treatment. The modification to band alignment is then verified by X-ray photoelectron spectroscopy measurement on MoS2/GaN heterostructures constructed by a modified wet-transfer technique, which indicates that the MoS2/GaN heterostructure without nitridation shows a type-II alignment with a conduction band offset (CBO) of only 0.07 eV. However, by the deployment of interface nitridation, the band edges of MoS2 move upward for ∼0.5 eV as a result of the nitridized substrate property. The significantly increased CBO could lead to better electron accumulation capability at the GaN side. The nitridized 2D/3D heterostructure with effective interface treatment exhibits a clean band gap and substantial optical absorption ability and could be potentially used as practical photocatalyst for hydrogen generation by water splitting using solar energy.
This study examines the effect of firm-level corporate governance on the cost of equity capital in emerging markets and how the effect is influenced by country-level legal protection of investors. We ...find that firm-level corporate governance has a significantly negative effect on the cost of equity capital in these markets. In addition, this corporate governance effect is more pronounced in countries that provide relatively poor legal protection. Thus, in emerging markets, firm-level corporate governance and country-level shareholder protection seem to be substitutes for each other in reducing the cost of equity. Our results are consistent with the finding from McKinsey's surveys that institutional investors are willing to pay a higher premium for shares in firms with good corporate governance, especially when the firms are in countries where the legal protection of investors is weak.
Purpose
Our goal was to use a generative adversarial network (GAN) with feature matching and task‐specific perceptual loss to synthesize standard‐dose amyloid Positron emission tomography (PET) ...images of high quality and including accurate pathological features from ultra‐low‐dose PET images only.
Methods
Forty PET datasets from 39 participants were acquired with a simultaneous PET/MRI scanner following injection of 330 ± 30 MBq of the amyloid radiotracer 18F‐florbetaben. The raw list‐mode PET data were reconstructed as the standard‐dose ground truth and were randomly undersampled by a factor of 100 to reconstruct 1% low‐dose PET scans. A 2D encoder‐decoder network was implemented as the generator to synthesize a standard‐dose image and a discriminator was used to evaluate them. The two networks contested with each other to achieve high‐visual quality PET from the ultra‐low‐dose PET. Multi‐slice inputs were used to reduce noise by providing the network with 2.5D information. Feature matching was applied to reduce hallucinated structures. Task‐specific perceptual loss was designed to maintain the correct pathological features. The image quality was evaluated by peak signal‐to‐noise ratio (PSNR), structural similarity (SSIM), and root mean square error (RMSE) metrics with and without each of these modules. Two expert radiologists were asked to score image quality on a 5‐point scale and identified the amyloid status (positive or negative).
Results
With only low‐dose PET as input, the proposed method significantly outperformed Chen et al.'s method (Chen et al. Radiology. 2018;290:649–656) (which shows the best performance in this task) with the same input (PET‐only model) by 1.87 dB in PSNR, 2.04% in SSIM, and 24.75% in RMSE. It also achieved comparable results to Chen et al.'s method which used additional magnetic resonance imaging (MRI) inputs (PET‐MR model). Experts' reading results showed that the proposed method could achieve better overall image quality and maintain better pathological features indicating amyloid status than both PET‐only and PET‐MR models proposed by Chen et al.
Conclusion
Standard‐dose amyloid PET images can be synthesized from ultra‐low‐dose images using GAN. Applying adversarial learning, feature matching, and task‐specific perceptual loss are essential to ensure image quality and the preservation of pathological features.
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