Rethinking Similarity Search: Embracing Smarter Mechanisms over Smarter Data

In this vision paper, we propose a shift in perspective for improving the effectiveness of similarity search. Rather than focusing solely on enhancing the data quality, particularly machine learning-generated embeddings, we advocate for a more comprehensive approach that also enhances the underpinning search mechanisms. We highlight three novel avenues that call for a redefinition of the similarity search problem: exploiting implicit data structures and distributions, engaging users in an iterative feedback loop, and moving beyond a single query vector. These novel pathways have gained relevance in emerging applications such as large-scale language models, video clip retrieval, and data labeling. We discuss the corresponding research challenges posed by these new problem areas and share insights from our preliminary discoveries

RNA-seq liver transcriptome analysis reveals an activated MHC-I pathway and an inhibited MHC-II pathway at the early stage of vaccine immunization in zebrafish

BACKGROUND: Zebrafish (Danio rerio) is a prominent vertebrate model of human development and pathogenic disease and has recently been utilized to study teleost immune responses to infectious agents threatening the aquaculture industry. In this work, to clarify the host immune mechanisms underlying the protective effects of a putative vaccine and improve its immunogenicity in the future efforts, high-throughput RNA sequencing technology was used to investigate the immunization-related gene expression patterns of zebrafish immunized with Edwardsiella tarda live attenuated vaccine. RESULTS: Average reads of 18.13 million and 14.27 million were obtained from livers of zebrafish immunized with phosphate buffered saline (mock) and E. tarda vaccine (WED), respectively. The reads were annotated with the Ensembl zebrafish database before differential expressed genes sequencing (DESeq) comparative analysis, which identified 4565 significantly differentially expressed genes (2186 up-regulated and 2379 down-regulated in WED; p<0.05). Among those, functional classifications were found in the Gene Ontology database for 3891 and in the Kyoto Encyclopedia of Genes and Genomes database for 3467. Several pathways involved in acute phase response, complement activation, immune/defense response, and antigen processing and presentation were remarkably affected at the early stage of WED immunization. Further qPCR analysis confirmed that the genes encoding the factors involved in major histocompatibility complex (MHC)-I processing pathway were up-regulated, while those involved in MHC-II pathway were down-regulated. CONCLUSION: These data provided insights into the molecular mechanisms underlying zebrafish immune response to WED immunization and might aid future studies to develop a highly immunogenic vaccine against gram-negative bacteria in teleosts

Diffusion Shape Prior for Wrinkle-Accurate Cloth Registration

Registering clothes from 4D scans with vertex-accurate correspondence is challenging, yet important for dynamic appearance modeling and physics parameter estimation from real-world data. However, previous methods either rely on texture information, which is not always reliable, or achieve only coarse-level alignment. In this work, we present a novel approach to enabling accurate surface registration of texture-less clothes with large deformation. Our key idea is to effectively leverage a shape prior learned from pre-captured clothing using diffusion models. We also propose a multi-stage guidance scheme based on learned functional maps, which stabilizes registration for large-scale deformation even when they vary significantly from training data. Using high-fidelity real captured clothes, our experiments show that the proposed approach based on diffusion models generalizes better than surface registration with VAE or PCA-based priors, outperforming both optimization-based and learning-based non-rigid registration methods for both interpolation and extrapolation tests.Comment: Project page: https://www-users.cse.umn.edu/~guo00109/projects/3dv2024

Dressing Avatars: Deep Photorealistic Appearance for Physically Simulated Clothing

Despite recent progress in developing animatable full-body avatars, realistic modeling of clothing - one of the core aspects of human self-expression - remains an open challenge. State-of-the-art physical simulation methods can generate realistically behaving clothing geometry at interactive rates. Modeling photorealistic appearance, however, usually requires physically-based rendering which is too expensive for interactive applications. On the other hand, data-driven deep appearance models are capable of efficiently producing realistic appearance, but struggle at synthesizing geometry of highly dynamic clothing and handling challenging body-clothing configurations. To this end, we introduce pose-driven avatars with explicit modeling of clothing that exhibit both photorealistic appearance learned from real-world data and realistic clothing dynamics. The key idea is to introduce a neural clothing appearance model that operates on top of explicit geometry: at training time we use high-fidelity tracking, whereas at animation time we rely on physically simulated geometry. Our core contribution is a physically-inspired appearance network, capable of generating photorealistic appearance with view-dependent and dynamic shadowing effects even for unseen body-clothing configurations. We conduct a thorough evaluation of our model and demonstrate diverse animation results on several subjects and different types of clothing. Unlike previous work on photorealistic full-body avatars, our approach can produce much richer dynamics and more realistic deformations even for many examples of loose clothing. We also demonstrate that our formulation naturally allows clothing to be used with avatars of different people while staying fully animatable, thus enabling, for the first time, photorealistic avatars with novel clothing.Comment: SIGGRAPH Asia 2022 (ACM ToG) camera ready. The supplementary video can be found on https://research.facebook.com/publications/dressing-avatars-deep-photorealistic-appearance-for-physically-simulated-clothing

Genome Sequence of the Versatile Fish Pathogen Edwardsiella tarda Provides Insights into its Adaptation to Broad Host Ranges and Intracellular Niches

BACKGROUND:Edwardsiella tarda is the etiologic agent of edwardsiellosis, a devastating fish disease prevailing in worldwide aquaculture industries. Here we describe the complete genome of E. tarda, EIB202, a highly virulent and multi-drug resistant isolate in China. METHODOLOGY/PRINCIPAL FINDINGS:E. tarda EIB202 possesses a single chromosome of 3,760,463 base pairs containing 3,486 predicted protein coding sequences, 8 ribosomal rRNA operons, and 95 tRNA genes, and a 43,703 bp conjugative plasmid harboring multi-drug resistant determinants and encoding type IV A secretion system components. We identified a full spectrum of genetic properties related to its genome plasticity such as repeated sequences, insertion sequences, phage-like proteins, integrases, recombinases and genomic islands. In addition, analysis also indicated that a substantial proportion of the E. tarda genome might be devoted to the growth and survival under diverse conditions including intracellular niches, with a large number of aerobic or anaerobic respiration-associated proteins, signal transduction proteins as well as proteins involved in various stress adaptations. A pool of genes for secretion systems, pili formation, nonfimbrial adhesions, invasions and hemagglutinins, chondroitinases, hemolysins, iron scavenging systems as well as the incomplete flagellar biogenesis might feature its surface structures and pathogenesis in a fish body. CONCLUSION/SIGNIFICANCE:Genomic analysis of the bacterium offered insights into the phylogeny, metabolism, drug-resistance, stress adaptation, and virulence characteristics of this versatile pathogen, which constitutes an important first step in understanding the pathogenesis of E. tarda to facilitate construction of a practical effective vaccine used for combating fish edwardsiellosis

Edwardsiella Comparative Phylogenomics Reveal the New Intra/Inter-Species Taxonomic Relationships, Virulence Evolution and Niche Adaptation Mechanisms

Edwardsiella bacteria are leading fish pathogens causing huge losses to aquaculture industries worldwide. E. tarda is a broad-host range pathogen that infects more than 20 species of fish and other animals including humans while E. ictaluri is host-adapted to channel catfish causing enteric septicemia of catfish (ESC). Thus, these two species consist of a useful comparative system for studying the intricacies of pathogen evolution. Here we present for the first time the phylogenomic comparisons of 8 genomes of E. tarda and E. ictaluri isolates. Genome-based phylogenetic analysis revealed that E. tarda could be separate into two kinds of genotypes (genotype I, EdwGI and genotype II, EdwGII) based on the sequence similarity. E. tarda strains of EdwGI were clustered together with the E. ictaluri lineage and showed low sequence conservation to E. tarda strains of EdwGII. Multilocus sequence analysis (MLSA) of 48 distinct Edwardsiella strains also supports the new taxonomic relationship of the lineages. We identified the type III and VI secretion systems (T3SS and T6SS) as well as iron scavenging related genes that fulfilled the criteria of a key evolutionary factor likely facilitating the virulence evolution and adaptation to a broad range of hosts in EdwGI E. tarda. The surface structure-related genes may underlie the adaptive evolution of E. ictaluri in the host specification processes. Virulence and competition assays of the null mutants of the representative genes experimentally confirmed their contributive roles in the evolution/niche adaptive processes. We also reconstructed the hypothetical evolutionary pathway to highlight the virulence evolution and niche adaptation mechanisms of Edwardsiella. This study may facilitate the development of diagnostics, vaccines, and therapeutics for this under-studied pathogen

Impact Velocity Measurement Method Based on Trajectory and Impact Position

The impact velocity of falling weight is an instantaneous quantity. Currently, measurement of impact velocity relies on high-speed sensors to capture the moment of impact. The trajectory-position measurement method (TPMM) is proposed in this study. The main steps are: (1) The impact position is used to capture the impact time. It can be measured when the falling weight is stationary. (2) The discrete falling trajectory is measured and a new empirical regression algorithm is proposed to fit the expression of falling trajectory. (3) The impact velocity is obtained by taking the impact time into the first derivative of the trajectory expression. For 1&ndash;5 m falling height, the simulation shows that the relative maximum error and relative expanded uncertainty of the proposed method are less than 0.481% and 0.442%, respectively. Then, the actual experiment is carried out to verify the simulation. The proposed method has high accuracy and low uncertainty. The reasons are: (1) Only a low-speed displacement sensor is need for impact velocity measurement. It is easier to improve accuracy and stability of a low-speed sensor. (2) The empirical regression algorithm can improve the stability of falling trajectory fitting

Response of <i>Cucumis sativus</i> to Neighbors in a Species-Specific Manner

Plants exhibit various behaviors of growth and allocation that play an important role in plant performance and social interaction as they grow together. However, it is unclear how Cucumis sativus plants respond to different neighbors. Here, we performed 5 neighbor combinations with C. sativus as the focal species. The selected materials of C. sativus responded to neighbors and exhibited different behavior strategies in a species-specific manner. All competition treatments reduced the growth of C. sativus seedlings to a certain extent, but only the Eruca sativa neighbor treatment reached a significant level in total root length and shoot biomass. Compared with growing under solitary conditions, focal plants avoided, tended to and did not change their allocation to their nearby plants. The larger the biomass of their neighbors, the stronger the inhibition of the focal plants. In addition, no significant correlations between growth and allocation variables were found, suggesting that growth and allocation are two important aspects of C. sativus behavioral strategies. Our findings provide reference and support for agricultural production of C. sativus, but further research and practice are still needed