A Photonic Crystal Slab Laplace Differentiator

We introduce an implementation of a Laplace differentiator based on a photonic crystal slab that operates at transmission mode. We show that the Laplace differentiator can be implemented provided that the guided resonances near the $\Gamma$ point exhibit an isotropic band structure. Such a device may facilitate nanophotonics-based optical analog computing for image processing.Comment: Primary text 6 pages, 5 figures; Supplementary material 5 pages, 3 figure

Cloud Computing for Detecting High-Order Genome-Wide Epistatic Interaction via Dynamic Clustering

Backgroud: Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. Results: In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Conclusions: Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS

How Consumers\u27 Attitudes towards Alternative Food Network Affect Their Consumption Satisfaction - Empirical Evidence from Zhengzhou

With the continuous development of economic globalization and the increasingly diversified food culture of people, food hygiene and safety have become hot topics that have attracted much attention. The continuous occurrence of vicious food safety accidents has caused people to pay great attention to food safety. It is necessary to re-examine the issue that has risen to the height of national public safety, and it is necessary to increase the supervision of food safety. Based on 280 valid questionnaire data of alternative food network (AFN) in Zhengzhou, using structural equation model, this study investigates how consumers\u27 attitudes towards AFN affect their consumption satisfaction. The results show that: the attitude towards AFN has a direct positive impact on consumer satisfaction, and indirectly affects satisfaction by affecting the perceived quality of consumers, and has an indirect positive impact on satisfaction through influencing the participation of AFN activities. The policy implications are: implement participatory security system, learn from the commercialization of mainstream food network, pay more attention to the quality of products, pay more attention to the needs of consumers and establish a "food community"

A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methods

Multi-task learning (MTL) has become increasingly popular in natural language processing (NLP) because it improves the performance of related tasks by exploiting their commonalities and differences. Nevertheless, it is still not understood very well how multi-task learning can be implemented based on the relatedness of training tasks. In this survey, we review recent advances of multi-task learning methods in NLP, with the aim of summarizing them into two general multi-task training methods based on their task relatedness: (i) joint training and (ii) multi-step training. We present examples in various NLP downstream applications, summarize the task relationships and discuss future directions of this promising topic.Comment: Accepted to EACL 2023 as regular long pape

Zc(3900)Z_c(3900) as a DDˉ∗D\bar{D}^* molecule from the pole counting rule

A comprehensive study on the nature of the $Z_c(3900)$ resonant structure is carried out in this work. By constructing the pertinent effective Lagrangians and considering the important final-state-interaction effects, we first give a unified description to all the relevant experimental data available, including the $J/\psi\pi$ and $\pi\pi$ invariant mass distributions from the $e^+e^-\to J/\psi\pi\pi$ process, the $h_c\pi$ distribution from $e^+e^-\to h_c\pi\pi$ and also the $D\bar D^{*}$ spectrum in the $e^+e^-\to D\bar D^{*}\pi$ process. After fitting the unknown parameters to the previous data, we search the pole in the complex energy plane and find only one pole in the nearby energy region in different Riemann sheets. Therefore we conclude that $Z_c(3900)$ is of $D\bar D^*$ molecular nature, according to the pole counting rule method~[Nucl.~Phys.~A543, 632 (1992); Phys.~Rev.~D 35,~1633 (1987)]. We emphasize that the conclusion based upon the pole counting method is not trivial, since both the $D\bar D^{*}$ contact interactions and the explicit $Z_c$ exchanges are introduced in our analyses and they lead to the same conclusion.Comment: 21 pages, 9 figures. To match the published version in PRD. Additional discussion on the spectral density function is include

Numerical Investigation on Primary Atomization Mechanism of Hollow Cone Swirling Sprays

The atomization process of swirling sprays in gas turbine engines has been investigated using a LES-VOF model. With fine grid resolution, the ligament and droplet formation processes are captured in detail. The spray structure of fully developed sprays and the flow field are observed firstly. A central recirculation zone is generated inside the hollow cone section due to the entrainment of air by the liquid sheet and strong turbulent structures promote the breakup of ligaments. At the exit of injector nozzle, surface instability occurs due to disturbance factors. Axial and transverse mode instabilities produce a net-like structure ligament zone. Finally, the generation mechanism of the droplet is analyzed. It is found that the breakup mechanism of ligaments is located at the Raleigh capillary region. Axial symmetry oscillation occurs due to the surface tension force and the capillary waves pinch off from the neck of the ligaments. Secondary breakup and coalescence occur at the “droplet zone,” resulting in a wider distribution curve at the downstream area