Tungsten disulfide-gold nanohole hybrid metasurfaces for nonlinear metalens in the visible region

Recently, nonlinear hybrid metasurface comes into an attractive new concept in the research of nanophotonics and nanotechnology. It is composed of semiconductors with an intrinsically large nonlinear susceptibility and traditional plasmonic metasurfaces, offering opportunities for efficiently generating and manipulating nonlinear optical responses. A high second-harmonic generation (SHG) conversion efficiency has been demonstrated in the mid-infrared region by using multi-quantum-well (MQW) based plasmonic metasurfaces. However, it has yet to be demonstrated in the visible region. Here we present a new type of nonlinear hybrid metasurfaces for the visible region, which consists of a single layer of tungsten disulfide (WS2) and a phased gold nanohole array. The results indicate that a large SHG susceptibility of ~0.1 nm/V at 810 nm is achieved, which is 2~3 orders of magnitude larger than that of typical plasmonic metasurfaces. Nonlinear metalenses with the focal lengths of 30 {\mu}m, 50 {\mu}m and 100 {\mu}m are demonstrated experimentally, providing a direct evidence for both generating and manipulating SH signals based on the nonlinear hybrid metasurfaces. It shows great potential applications in designing of integrated, ultra-thin, compacted and efficient nonlinear optical devices, such as frequency converters, nonlinear holography and generation of nonlinear optical vortex beam

Efficient Neural Query Auto Completion

Query Auto Completion (QAC), as the starting point of information retrieval tasks, is critical to user experience. Generally it has two steps: generating completed query candidates according to query prefixes, and ranking them based on extracted features. Three major challenges are observed for a query auto completion system: (1) QAC has a strict online latency requirement. For each keystroke, results must be returned within tens of milliseconds, which poses a significant challenge in designing sophisticated language models for it. (2) For unseen queries, generated candidates are of poor quality as contextual information is not fully utilized. (3) Traditional QAC systems heavily rely on handcrafted features such as the query candidate frequency in search logs, lacking sufficient semantic understanding of the candidate. In this paper, we propose an efficient neural QAC system with effective context modeling to overcome these challenges. On the candidate generation side, this system uses as much information as possible in unseen prefixes to generate relevant candidates, increasing the recall by a large margin. On the candidate ranking side, an unnormalized language model is proposed, which effectively captures deep semantics of queries. This approach presents better ranking performance over state-of-the-art neural ranking methods and reduces $\sim$95\% latency compared to neural language modeling methods. The empirical results on public datasets show that our model achieves a good balance between accuracy and efficiency. This system is served in LinkedIn job search with significant product impact observed.Comment: Accepted at CIKM 202

An Application of Deep Learning for Sweet Cherry Phenotyping using YOLO Object Detection

Tree fruit breeding is a long-term activity involving repeated measurements of various fruit quality traits on a large number of samples. These traits are traditionally measured by manually counting the fruits, weighing to indirectly measure the fruit size, and fruit colour is classified subjectively into different color categories using visual comparison to colour charts. These processes are slow, expensive and subject to evaluators' bias and fatigue. Recent advancements in deep learning can help automate this process. A method was developed to automatically count the number of sweet cherry fruits in a camera's field of view in real time using YOLOv3. A system capable of analyzing the image data for other traits such as size and color was also developed using Python. The YOLO model obtained close to 99% accuracy in object detection and counting of cherries and 90% on the Intersection over Union metric for object localization when extracting size and colour information. The model surpasses human performance and offers a significant improvement compared to manual counting.Comment: Published in 25th International Conference on Image Processing, Computer Vision, & Pattern Recognition (IPCV'21

Variational approach to p-Laplacian fractional differential equations with instantaneous and non-instantaneous impulses

In this paper, we examine the existence of solutions of p-Laplacian fractional differential equations with instantaneous and non-instantaneous impulses. New criteria guaranteeing the existence of infinitely many solutions are established for the considered problem. The problem is reduced to an equivalent form such that the weak solutions of the problem are defined as the critical points of an energy functional. The main result of the present work is established by using a variational approach and a mountain pass lemma. Finally, an example is given to illustrate our main result

Instability of chromosome number and DNA methylation variation induced by hybridization and amphidiploid formation between Raphanus sativus L. and Brassica alboglabra Bailey

<p>Abstract</p> <p>Background</p> <p>Distant hybridization can result genome duplication and allopolyploid formation which may play a significant role in the origin and evolution of many plant species. It is unclear how the two or more divergent genomes coordinate in one nucleus with a single parental cytoplasm within allopolyploids. We used cytological and molecular methods to investigate the genetic and epigenetic instabilities associated with the process of distant hybridization and allopolyploid formation, measuring changes in chromosome number and DNA methylation across multiple generations.</p> <p>Results</p> <p>F₁plants from intergeneric hybridization between <it>Raphanus sativus </it>L. (2n = 18, RR) and <it>Brassica alboglabra </it>Bailey (2n = 18, CC) were obtained by hand crosses and subsequent embryo rescue. Random amplification of polymorphic DNA (RAPD) markers were used to identify the F₁hybrid plants. The RAPD data indicated that the hybrids produced specific bands similar to those of parents and new bands that were not present in either parent. Chromosome number variation of somatic cells from allotetraploids in the F₄to F₁₀generations showed that intensive genetic changes occurred in the early generations of distant hybridization, leading to the formation of mixopolyploids with different chromosome numbers. DNA methylation variation was revealed using MSAP (methylation-sensitive amplification polymorphism), which showed that cytosine methylation patterns changed markedly in the process of hybridization and amphidiploid formation. Differences in cytosine methylation levels demonstrated an epigenetic instability of the allopolyploid of <it>Raphanobrassica </it>between the genetically stable and unstable generations.</p> <p>Conclusions</p> <p>Our results showed that chromosome instability occurred in the early generations of allopolyploidy and then the plants were reverted to largely euploidy in later generations. During this process, DNA methylation changed markedly. These results suggest that, epigenetic mechanisms play an important role in intergeneric distant hybridization, probably by maintaining a genetic balance through the modification of existing genetic materials.</p