MR image reconstruction from under-sampled measurements using local and global sparse representations

This work presented a new model by enforcing both local and global sparsity, which captures both the patch-level and global sparse structures of the anatomical images. Using a model split approach, the image reconstruction quality can be iteratively further improved. Our simulation results demonstrate that, the proposed method outperform those existing methods using only the patch-level or global sparse structure

Wizundry: A Cooperative Wizard of Oz Platform for Simulating Future Speech-based Interfaces with Multiple Wizards

Wizard of Oz (WoZ) as a prototyping method has been used to simulate intelligent user interfaces, particularly for speech-based systems. However, as our societies' expectations on artificial intelligence (AI) grows, the question remains whether a single Wizard is sufficient for it to simulate smarter systems and more complex interactions. Optimistic visions of 'what artificial intelligence (AI) can do' places demands on WoZ platforms to simulate smarter systems and more complex interactions. This raises the question of whether the typical approach of employing a single Wizard is sufficient. Moreover, while existing work has employed multiple Wizards in WoZ studies, a multi-Wizard approach has not been systematically studied in terms of feasibility, effectiveness, and challenges. We offer Wizundry, a real-time, web-based WoZ platform that allows multiple Wizards to collaboratively operate a speech-to-text based system remotely. We outline the design and technical specifications of our open-source platform, which we iterated over two design phases. We report on two studies in which participant-Wizards were tasked with negotiating how to cooperatively simulate an interface that can handle natural speech for dictation and text editing as well as other intelligent text processing tasks. We offer qualitative findings on the Multi-Wizard experience for Dyads and Triads of Wizards. Our findings reveal the promises and challenges of the multi-Wizard approach and open up new research questions.Comment: 34 page

Image Super-Resolution using Efficient Striped Window Transformer

Transformers have achieved remarkable results in single-image super-resolution (SR). However, the challenge of balancing model performance and complexity has hindered their application in lightweight SR (LSR). To tackle this challenge, we propose an efficient striped window transformer (ESWT). We revisit the normalization layer in the transformer and design a concise and efficient transformer structure to build the ESWT. Furthermore, we introduce a striped window mechanism to model long-term dependencies more efficiently. To fully exploit the potential of the ESWT, we propose a novel flexible window training strategy that can improve the performance of the ESWT without additional cost. Extensive experiments show that ESWT outperforms state-of-the-art LSR transformers, and achieves a better trade-off between model performance and complexity. The ESWT requires fewer parameters, incurs faster inference, smaller FLOPs, and less memory consumption, making it a promising solution for LSR.Comment: SOTA lightweight super-resolution transformer. 8 pages, 9 figures and 6 tables. The Code is available at https://github.com/Fried-Rice-Lab/FriedRiceLa

STGIN: Spatial-Temporal Graph Interaction Network for Large-scale POI Recommendation

In Location-Based Services, Point-Of-Interest(POI) recommendation plays a crucial role in both user experience and business opportunities. Graph neural networks have been proven effective in providing personalized POI recommendation services. However, there are still two critical challenges. First, existing graph models attempt to capture users' diversified interests through a unified graph, which limits their ability to express interests in various spatial-temporal contexts. Second, the efficiency limitations of graph construction and graph sampling in large-scale systems make it difficult to adapt quickly to new real-time interests. To tackle the above challenges, we propose a novel Spatial-Temporal Graph Interaction Network. Specifically, we construct subgraphs of spatial, temporal, spatial-temporal, and global views respectively to precisely characterize the user's interests in various contexts. In addition, we design an industry-friendly framework to track the user's latest interests. Extensive experiments on the real-world dataset show that our method outperforms state-of-the-art models. This work has been successfully deployed in a large e-commerce platform, delivering a 1.1% CTR and 6.3% RPM improvement.Comment: accepted by CIKM 202

Morphological Redescription and SSU rDNA-based Phylogeny of Two Freshwater Ciliates, Uronema nigricans and Lembadion lucens (Ciliophora, Oligohymenophorea), with Discussion on the Taxonomic Status of Uronemita sinensis

Liu, Mingjian, Li, Lifang, Qu, Zhishuai, Luo, Xiaotian, Al-Farraj, Saleh A., Lin, Xiaofeng, Hu, Xiaozhong (2017): Morphological Redescription and SSU rDNA-based Phylogeny of Two Freshwater Ciliates, Uronema nigricans and Lembadion lucens (Ciliophora, Oligohymenophorea), with Discussion on the Taxonomic Status of Uronemita sinensis. Acta Protozoologica 56 (1): 17-37, DOI: 10.4467/16890027AP.17.003.6967, URL: https://www.mendeley.com/catalogue/cb3bc4f7-739f-32f8-92cd-7da31a838cb6

Aerosol scattering of vortex beams transmission in hazy atmosphere

Mie theory is widely used for the simulation and characterization of optical interaction with scattering media, such atmospheric pollutants. The complex refractive index of particle plays an important role in determining the scattering and absorption of light. Complex optical fields, such as vortex beams, will interact with scattering particulates differently to plane wave or Gaussian optical fields. By considering the three typical aerosol particles compositions that lead to haze in the atmosphere, distinctive scattering dynamic were identified for vortex beams as compared to Gaussian beams. Using parameters similar to real world atmospheric conditions, a new aerosol particle model is proposed to efficiently and concisely describe the aerosol scattering. Numerical simulations indicate unique signatures in the scattering dynamics of the vortex beams that can indicate particles composition and also suggest that potentially there is higher optical transmission of vortex beams propagating in certain hazy environments

Cloning and Characterization of TaTGW-7A Gene Associated with Grain Weight in Wheat via SLAF-seq-BSA

Thousand-grain weight (TGW) of wheat (Triticum aestivum L.) contributes significantly to grain yield. In the present study, a candidate gene associated with TGW was identified through specific-locus amplified fragment sequencing (SLAF-seq) of DNA bulks of recombinant inbred lines (RIL) derived from the cross between Jing 411 and Hongmangchun 21. The gene was located on chromosome 7A, designated as TaTGW-7A with a complete genome sequence and an open reading frame (ORF). A single nucleotide polymorphism (SNP) was present in the first exon between two alleles at TaTGW-7A locus, resulting in a Val to Ala substitution, corresponding to a change from higher to lower TGW. Cleaved amplified polymorphic sequence (CAPS) (TGW7A) and InDel (TG9) markers were developed to discriminate the two alleles TaTGW-7Aa and TaTGW-7Ab for higher and lower TGW, respectively. A major QTL co-segregating with TaTGW-7A explained 21.7–27.1% of phenotypic variance for TGW in the RIL population across five environments. The association of TaTGW-7A with TGW was further validated in a natural population and Chinese mini-core collections. Quantitative real-time PCR revealed higher transcript levels of TaTGW-7Aa than those of TaTGW-7Ab during grain development. High frequencies of the superior allele TaTGW-7Aa for higher TGW in Chinese mini-core collections (65.0%) and 501 wheat varieties (86.0%) indicated a strong and positive selection of this allele in wheat breeding. The molecular markers TGW7A and TG9 can be used for improvement of TGW in breeding programs

The 11th annual meeting of China Earthquake Prediction Forum held on Aug. 15—19, 2023 in Kangding City, Sichuan Province

The 11th annual meeting of China Earthquake Prediction Forum (CEPF), which was co-sponsored by Prediction Committee of Seismological Society of China and Sichuan Earthquake Agency, was held on Aug. 15—19, 2023 in Kangding City，Sichuan Province. More than 100 persons from 8 universities, 4 institutes of Chinese Academy of Sciences and 23 Institutes and Provincial Earthquake Agencies of China Earthquake Administration attended this conference. 12 special topics had been set up for academic exchange. 96 conference articles were collected before the meeting, in which 87 articles had been passed pier reviewing and will be published by the joural of Seismological and Geomagnetic Observation and Research in Supplementary Issue of 2023. During the 2 days room meeting, there were 23 orals and 55 posters presented, where 6 invited key note speakers presented the research current advances of earthquake prediction practice in China, the designing of gravity instrument for continuous measurement aiming at earthquake prediction research, the application of machine learning to diagnose aftershock pattern, the progress of tsunami research in Southeast China. There were 6 young presenters got excellent poster awards who obtained the permission of oral presentation in the following annual meeting of China Earthquake Prediction Forum. A popular science lecture on Xianshuihe fault zone was organized for the one day field training course held in the southern segment of Xianshuihe fault after the room meeting of this conference. A short panel discussion on how to enhance the capability of hunting precursors and prediction efficiency in high risk area was conducted. All the attendees enjoyed the successful conference both in scientific exchange and in onsite training course of active fault