Sum-frequency generation from etchless lithium niobate empowered by dual quasi-bound states in the continuum

The miniaturization of nonlinear light sources is central to the integrated photonic platform, driving a quest for high-efficiency frequency generation and mixing at the nanoscale. In this quest, the high-quality ($Q$) resonant dielectric nanostructures hold great promise, as they enhance nonlinear effects through the resonantly local electromagnetic fields overlapping the chosen nonlinear materials. Here, we propose a method for the enhanced sum-frequency generation (SFG) from etcheless lithium niobate (LiNbO$_{3}$) by utilizing the dual quasi-bound states in the continuum (quasi-BICs) in a one-dimensional resonant grating waveguide structure. Two high-$Q$ guided mode resonances corresponding to the dual quasi-BICs are respectively excited by two near-infrared input beams, generating a strong visible SFG signal with a remarkably high conversion efficiency of $3.66\times10^{-2}$ (which is five orders of magnitude higher than that of LiNbO$_{3}$ films of the same thickness) and a small full-width at half-maximum less than 0.2 nm. The SFG efficiency can be tuned via adjusting the grating geometry parameter or choosing the input beam polarization combination. Furthermore, the generated SFG signal can be maintained at a fixed wavelength without the appreciable loss of efficiency by selectively exciting the angular-dependent quasi-BICs, even if the wavelengths of input beams are tuned within a broad spectral range. Our results provide a simple but robust paradigm of high-efficiency frequency conversion on an easy-fabricated platform, which may find applications in nonlinear light sources and quantum photonics

Spatiotemporal dynamics of activation in motor and language areas suggest a compensatory role of the motor cortex in second language processing

The involvement of the motor cortex in language understanding has been intensively discussed in the framework of embodied cognition. Although some studies have provided evidence for the involvement of the motor cortex in different receptive language tasks, the role that it plays in language perception and understanding is still unclear. In the present study, we explored the degree of involvement of language and motor areas in a visually presented sentence comprehension task, modulated by language proficiency (L1: native language, L2: second language) and linguistic abstractness (literal, metaphorical, and abstract). Magnetoencephalography data were recorded from 26 late Chinese learners of English. A cluster-based permutation F-test was performed on the amplitude of the source waveform for each motor and language region of interest (ROI). Results showed a significant effect of language proficiency in both language and motor ROIs, manifested as overall greater involvement of language ROIs (short insular gyri and planum polare of the superior temporal gyrus) in the L1 than the L2 during 300–500 ms, and overall greater involvement of motor ROI (central sulcus) in the L2 than the L1 during 600–800 ms. We interpreted the over-recruitment of the motor area in the L2 as a higher demand for cognitive resources to compensate for the inadequate engagement of the language network. In general, our results indicate a compensatory role of the motor cortex in L2 understanding.Peer reviewe

AoM: Detecting Aspect-oriented Information for Multimodal Aspect-Based Sentiment Analysis

Multimodal aspect-based sentiment analysis (MABSA) aims to extract aspects from text-image pairs and recognize their sentiments. Existing methods make great efforts to align the whole image to corresponding aspects. However, different regions of the image may relate to different aspects in the same sentence, and coarsely establishing image-aspect alignment will introduce noise to aspect-based sentiment analysis (i.e., visual noise). Besides, the sentiment of a specific aspect can also be interfered by descriptions of other aspects (i.e., textual noise). Considering the aforementioned noises, this paper proposes an Aspect-oriented Method (AoM) to detect aspect-relevant semantic and sentiment information. Specifically, an aspect-aware attention module is designed to simultaneously select textual tokens and image blocks that are semantically related to the aspects. To accurately aggregate sentiment information, we explicitly introduce sentiment embedding into AoM, and use a graph convolutional network to model the vision-text and text-text interaction. Extensive experiments demonstrate the superiority of AoM to existing methods. The source code is publicly released at https://github.com/SilyRab/AoM.Comment: Findings of ACL 202

On the Convergence of Solutions for SPDEs under Perturbation of the Domain

We investigate the effect of domain perturbation on the behavior of mild solutions for a class of semilinear stochastic partial differential equations subject to the Dirichlet boundary condition. Under some assumptions, we obtain an estimate for the mild solutions under changes of the domain

Fast Iterative Graph Computation: A Path Centric Approach

Abstract—Large scale graph processing represents an inter-esting challenge due to the lack of locality. This paper presents PathGraph for improving iterative graph computation on graphs with billions of edges. Our system design has three unique features: First, we model a large graph using a collection of tree-based partitions and use an path-centric computation rather than vertex-centric or edge-centric computation. Our parallel computation model significantly improves the memory and disk locality for performing iterative computation algorithms. Second, we design a compact storage that further maximize sequential access and minimize random access on storage media. Third, we implement the path-centric computation model by using a scatter/gather programming model, which parallels the iterative computation at partition tree level and performs sequential updates for vertices in each partition tree. The experimental results show that the path-centric approach outperforms vertex-centric and edge-centric systems on a number of graph algorithms for both in-memory and out-of-core graphs

Evaluation the activity of alveolar echinococcosis: A comparison between 18F-FDG PET and spectral CT

AbstractPurposeTo assess the iodine concentration of hepatic alveolar echinococcosis (HAE) using spectral computed tomography (CT) with comparison of [18F] fluorodeoxyglucose positron-emission tomography (18F-FDG PET), and to estimate the value of spectral CT for evaluation of HAE activity.Materials and methods18 patients with histologically confirmed or clinically proved HAE underwent spectral CT and 18F-FDG PET examinations. After three-phase scanning, the quantitative iodine-based material decomposition images and optimal monochromatic image of spectral CT were reconstructed and iodine concentration (IC) was measured in different organizational structures.Results18F-FDG PET identified increased metabolic activity in the corresponding lesions in 13 patients (13/18, 72.2%). The iodine concentration in marginal zone of lesion were significantly higher than in solid component of lesion and normal liver parenchyma during PVP and VP. The iodine value of edge tissue of the lesion and normal liver and iodine value of normal liver tissues showed statistically significant difference (P < 0.001). There was correlation between IC and SUVmax in marginal zone of HAE lesion, it was highest during PVP (r = 0.873, p < 0.001). There was low correlation between CT values and SUVmax.ConclusionThere was good correlation between spectral CT and 18F-FDG PET. Spectral CT could be recommended as a more practical tool in the clinical routine

Efficient Energy Conversion through Vortex Arrays in the Turbulent Magnetosheath

Turbulence is often enhanced when transmitted through a collisionless plasma shock. We investigate how the enhanced turbulent energy in the Earth's magnetosheath effectively dissipates via vortex arrays. This research topic is of great importance as it relates to particle energization at astrophysical shocks across the universe. Wave modes and intermittent coherent structures are the key candidate mechanisms for energy conversion in turbulent plasmas. Here, by comparing in-situ measurements in the Earth's magnetosheath with a theoretical model, we find the existence of vortex arrays at the transition between the downstream regions of the Earth's bow shock. Vortex arrays consist of quasi-orthogonal kinetic waves and exhibit both high volumetric filling factors and strong local energy conversion, thereby showing a greater dissipative energization than traditional waves and coherent structures. Therefore, we propose that vortex arrays are a promising mechanism for efficient energy conversion in the sheath regions downstream of astrophysical shocks