723 research outputs found
One-Versus-Others Attention: Scalable Multimodal Integration
Multimodal learning models have become increasingly important as they surpass
single-modality approaches on diverse tasks ranging from question-answering to
autonomous driving. Despite the importance of multimodal learning, existing
efforts focus on NLP applications, where the number of modalities is typically
less than four (audio, video, text, images). However, data inputs in other
domains, such as the medical field, may include X-rays, PET scans, MRIs,
genetic screening, clinical notes, and more, creating a need for both efficient
and accurate information fusion. Many state-of-the-art models rely on pairwise
cross-modal attention, which does not scale well for applications with more
than three modalities. For modalities, computing attention will result in
operations, potentially requiring considerable amounts of
computational resources. To address this, we propose a new domain-neutral
attention mechanism, One-Versus-Others (OvO) attention, that scales linearly
with the number of modalities and requires only attention operations, thus
offering a significant reduction in computational complexity compared to
existing cross-modal attention algorithms. Using three diverse real-world
datasets as well as an additional simulation experiment, we show that our
method improves performance compared to popular fusion techniques while
decreasing computation costs
GraFT: Gradual Fusion Transformer for Multimodal Re-Identification
Object Re-Identification (ReID) is pivotal in computer vision, witnessing an
escalating demand for adept multimodal representation learning. Current models,
although promising, reveal scalability limitations with increasing modalities
as they rely heavily on late fusion, which postpones the integration of
specific modality insights. Addressing this, we introduce the \textbf{Gradual
Fusion Transformer (GraFT)} for multimodal ReID. At its core, GraFT employs
learnable fusion tokens that guide self-attention across encoders, adeptly
capturing both modality-specific and object-specific features. Further
bolstering its efficacy, we introduce a novel training paradigm combined with
an augmented triplet loss, optimizing the ReID feature embedding space. We
demonstrate these enhancements through extensive ablation studies and show that
GraFT consistently surpasses established multimodal ReID benchmarks.
Additionally, aiming for deployment versatility, we've integrated neural
network pruning into GraFT, offering a balance between model size and
performance.Comment: 3 Borderline Reviews at WACV, 8 pages, 5 figures, 8 table
Wastewater treatment using artificial wetlands
In the study described in this paper, pilot scale vertical
flow wetlands were evaluated as a potential wastewater
treatment system for agricultural wastewater exiting from
swine farm. The criteria used for evaluation were based on
water quality requirements for irrigation
Nutzung gewalthaltiger Bildschirmspiele als lĂ€ngsschnittlicher Risikofaktor fĂŒr Cyberbullying in der frĂŒhen Adoleszenz
"Die Studie untersucht mittels Cross-Lagged-Panel-Design lĂ€ngsschnittliche ZusammenhĂ€nge zwischen gewalthaltiger Bildschirmspielnutzung und Cyberbullying. Zur ErklĂ€rung dieser ZusammenhĂ€nge werden die Selektions- und die Sozialisationshypothese ĂŒberprĂŒft. Traditionelles Bullying, Viktimisierung, offene und relationale Aggression werden als mögliche Kovariaten von Cyberbullying mitberĂŒcksichtigt. Im Zeitabstand eines Jahres wurden SelbsteinschĂ€tzungen von 271 Jugendlichen (10-13 Jahre) zu zwei Messzeitpunkten erhoben. Mittels Strukturgleichungsmodellen konnte gezeigt werden, dass die Nutzung gewalthaltiger Bildschirmspiele ein Risikofaktor fĂŒr Cyberbullying, traditionelles Bullying und offene Aggression (Sozialisationseffekt) ist. Zudem ist traditionelles Bullying ein Risikofaktor fĂŒr gewalthaltige Bildschirmspielnutzung (Selektionseffekt)." (Autorenreferat)"This study investigates longitudinal associations between violent video game playing und cyberbullying using a Cross-Lagged-Panel Design. The selection and the socialization hypothesis were tested as possible explanations. Traditional bullying, victimization, overt and relational aggression were considered as covariates in the analyses. Within one year, self-reports were collected from 271 adolescents, aged between 10 and 13 years, at two measurement occasions. Structural-Equation-Models identified violent video game playing as a longitudinal risk factor for cyberbullying, traditional bullying and overt aggression (socialization effect). Furthermore, traditional bullying was found as a longitudinal risk factor for violent video game playing (selection effect)." (author's abstract
Transformations of the National:Rammsteinâs âDeutschlandâ as a Provocation of German History
This contribution examines the nexus between âthe politicalâ and popular music from an interdisciplinary perspective. Using Rammsteinâs highly provocative single âDeutschlandâ (2019) as an example, this case study showcases multiple different and often contradictory readings of the bandâs work with a view to its textual, visual, sonic and performative dimensions. Overall, this contribution suggests that the political in Rammstein oscillates between self-reference and historical reference, between deconstruction and marketability, and between scandalous irony and ambiguous sincerity
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Dengue and Zika virus infections in children elicit cross-reactive protective and enhancing antibodies that persist long term.
Dengue virus serotypes 1 to 4 (DENV1â4) and Zika virus (ZIKV) are mosquito-borne flaviviruses that induce both virus-specific and broadly reactive antibodies. A first DENV infection is thought to induce antibodies that wane over 2 years to titers that can subsequently enhance severe dengue disease. Secondary DENV infection with a different serotype is thought to induce stable, cross-serotype protective antibodies. Low dengue disease incidence after the recent Zika pandemic led to the hypothesis that ZIKV infection is also transiently cross protective. We investigated antibody kinetics in 4189 children up to 11 years after one and multiple DENV and ZIKV infections in longitudinal cohorts in Nicaragua. We used a DENV inhibition enzyme-linked immunosorbent assay (iELISA), which measures antibodies associated with protection against dengue and Zika disease and with enhancement of dengue disease severity. Unexpectedly, we found that overall DENV iELISA titers stabilized by 8 months after primary DENV infection to a half-life longer than a human life and waned, although gradually, after secondary DENV infection. Similarly, DENV iELISA titers were stable or rose after primary ZIKV infection but declined in individuals with histories of DENV and ZIKV infection. In contrast, kinetics of anti-ZIKV antibodies after ZIKV infection were similar regardless of prior DENV immunity. We observed heterogeneity in DENV iELISA titer, suggesting that individual antibody titer set point, rather than waning, is important for future dengue disease risk. Together, these findings change our understanding of anti-flavivirus antibody kinetics and have implications for measuring vaccine efficacy and for predicting future dengue and Zika outbreaks
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