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Earlier sources: Fusion
This energy thread follows fusion through original research, public projects, and source reports. Read the evidence below to see which developments are represented in SYMTRI’s archive.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗129 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- arXiv · Published · First archived
CG-HAF: An Interpretable Global-Local Lesion-Burden Fusion Framework for Ordinal Acne Severity Grading in Agentic Skincare Support ↗
Ordinal acne severity grading requires distinguishing visually similar neighboring grades while jointly weighing holistic facial appearance and localized lesion burden - evidence that most existing approaches collapse into a single opaque representation. We introduce CG-HAF, a global-local fusion framework that instead keeps this evidence explicit: averaged holistic severity probabilities from independently trained classifiers are combined with structured lesion-burden descriptors from an object detector (lesion count, detection confidence, lesion area) into a compact representation, from whic…
- OpenAlex · Published · First archived
MF-YOLO: High-Resolution Weighted Feature Fusion with Global-Local Aggregation for Small-Object Detection in UAV Imagery ↗
Small-object representations in unmanned aerial vehicle (UAV) imagery are easily degraded by repeated downsampling, crowded occlusion, and background clutter. We present MF-YOLO, an accuracy-oriented detector based on YOLO11n. It introduces a stride-4 P2 prediction scale, applies Global-to-Local Spatial Aggregation (GLSA) independently to C2–C5 before neck fusion, and connects P2–P5 through a 64-channel Bidirectional Feature Pyramid Network (BiFPN). The contribution lies in the task-specific organization and controlled evaluation of these established components. Across three random seeds, MF-Y…
- OpenAlex · Published · First archived
Explainable Reliability-Gated EEG–EMG Fusion for Offline Early Gesture and Intention Recognition with Potential Relevance to Human–Robot Collaboration ↗
Abstract Early gesture and intention recognition from biosignals may provide a useful perception capability for future human–robot collaboration systems. This study proposes and evaluates an explainable reliability-gated EEG–EMG fusion framework for offline classification of seven upper-limb hand gestures and associated instructed intentions. The framework uses modality-specific EEG and EMG encoders followed by an adaptive reliability gate that learns how much each biosignal modality should contribute to the final prediction. The model was evaluated on synchronized EEG–EMG upper-limb gesture d…
- OpenAlex · Published · First archived
Fuzzy Reverse Neighborhood Discriminant Analysis: Soft Memberships, Adaptive Graphs, and Choquet-Integral Fusion for Robust Feature Extraction ↗
Conventional linear discriminant analysis (LDA) and its graph-based extensions encounter challenges with class overlap, uneven sampling, and inflexible neighborhood selection. Although reverse nearest neighbor (RNN) graphs address data density, standard Reverse Neighborhood Discriminant Analysis (RNDA) relies on hard labels and binary edges. This work introduces Fuzzy Reverse Neighborhood Discriminant Analysis (FRNDA), which incorporates fuzzy class memberships, multiple fuzzy RNN graphs with smoothly decaying edge weights, and Choquet integral-based regularization to model non-additive intera…
- OpenAlex · Published · First archived
Multi-domain feature fusion and machine learning-based SFRA diagnosis of transformer winding faults using a novel fault deviation index ↗
Abstract Sweep Frequency Response Analysis (SFRA) is one of the commonly used techniques for evaluating transformer winding integrity. However, the interpretation of the SFRA results remains qualitative and depends on expert evaluation. In this study, a quantitative, measurement-oriented diagnostic framework based on the advanced normalized Multi-Domain Fault Deviation Index (MFDI) is proposed. Within this method, magnitude, phase, impedance, and resonance-based descriptors are integrated in a unified formulation. The proposed method combines frequency band decomposition with multi-domain feat…
- OpenAlex · Published · First archived
Unified Multi-Application Segmentation of High-Resolution Satellite Images Through Consensus-Based Probabilistic Fusion ↗
Deep-learning-based land cover segmentation models for high-resolution aerial images often suffer from inconsistent performance on unseen data due to limited spatial and temporal dataset ranges alongside inherent labeling inconsistencies. Existing solutions, such as foundation models and unsupervised domain adaptation, offer indirect improvements but require considerable post-processing or transfer learning. To address this limitation, this study introduces a direct dataset integration method that fuses heterogeneous datasets with disparate class compositions into a single operational framewor…
- OpenAlex · Published · First archived
BCAM-AKT2 fusion protein promotes unfolded protein response driven oncogenic signaling in SKOV3 epithelial ovarian cancer cell line ↗
In view of the rapidly increasing evidence that gene fusion mutations are frequent drivers of cancer, a deeper understanding of the molecular and functional hallmarks of specific gene fusions in epithelial ovarian cancer (EOC) is essential. In this work we sought to identify the molecular signature of the BCAM-AKT2 fusion protein in ovarian cancer cell lines and to assess the biological impact of the novel fusion in these cells. Our in-vitro results show that the BCAM-AKT2 fusion protein is engaged in proliferative action within EOC cell lines. Furthermore, RNA-seq analysis shows that the effe…
- OpenAlex · Published · First archived
Design and activity evaluation of long-acting IFN-α2a-ELP fusion proteins ↗
Recombinant interferon-α2a (IFN-α2a) has clinically relevant antiviral and antitumor activity, but its short systemic half-life limits durable exposure after intermittent dosing. Elastin-like polypeptides (ELPs) offer a genetically encoded strategy for extending protein residence time through an expected increase in hydrodynamic size and thermally triggered depot formation. We designed two ELP 120 -based IFN-α2a fusion proteins, ELP 120 -IFN-α2a and IFN-α2a-ELP 120 , to compare the effect of fusion orientation on biophysical behavior, receptor engagement, in vitro activity, pharmacokinetics, a…
- OpenAlex · Published · First archived
Elevated synaptic vesicle fusion with impaired activity-dependent neurotransmission in a genomic ferlinopathy model ↗
Ferlins are a family of Ca 2+ /phospholipid-binding C2 domain transmembrane proteins (e.g. Myoferlin, Dysferlin, Otoferlin) mutated in multiple heritable human disease conditions. The unifying function of all Ferlins is Ca 2+ -dependent vesicle fusion, with roles in muscle formation, membrane repair, and neurotransmission. Drosophila has one well-conserved Ferlin, misfire ( mfr ), which provides the opportunity to test global Ferlin function via single gene manipulation. We find misfire null mutants form and maintain normal muscles with elevated muscle function. Consistently, we find misfire e…
- OpenAlex · Published · First archived
KLDD: Underwater image enhancement via KL-divergence-driven color cast correction and multistage enhancement fusion ↗
Underwater images often suffer from severe color casts, nonuniform illumination, reduced contrast, and blurred details because of wavelength-dependent absorption and light scattering. To address these degradations, this study proposes KLDD, an underwater image enhancement method based on KL-divergence-driven color cast correction and multistage enhancement fusion. First, a KL-divergence-driven adaptive color cast correction module measures the discrepancy between the two-dimensional joint chrominance distributions of an underwater image and a natural reference image in the CIELAB color space.…
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How to assess evidence about Fusion
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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