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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.
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Open in the map ↗127 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.
- OpenAlex · Published · First archived
RESCUE-AR: Responsive Sensor-Fusion for Civil-Protection and Disaster Response Using Mobile Augmented Reality ↗
Rapid situational awareness is a cornerstone of effective civil protection and disaster response, demanding highly resilient localization and decision-support capabilities under challenging environmental conditions. This paper presents RESCUE-AR (Responsive Sensor-Fusion for Civil-Protection and Disaster Response Using Mobile Augmented Reality), a conceptual and methodological framework for mobile Augmented Reality (AR) systems designed to support emergency operations through heterogeneous and adaptive sensor fusion. This work formalizes the mathematical and algorithmic architecture of the RES…
- OpenAlex · Published · First archived
Classification by Feature Fusion: The Impact of Linguistic Features on Sentiment Analysis in Turkish Texts ↗
The rapid rise of e-commerce platforms has transformed user reviews into a significant data source. While these reviews present an important opportunity to understand user sentiments, conducting sentiment analysis in the Turkish language poses various challenges. The complex linguistic structure of Turkish and the limited number of studies in the literature restrict the accuracy and scope of analyses in this domain. Particularly, punctuation marks, grammatical structures, and other linguistic features are key aspects to consider during the sentiment analysis process. In this study, the TRSAv1…
- OpenAlex · Published · First archived
An iterative knowledge extraction and dual-channel fusion framework for clinical differential diagnosis ↗
For common diseases in the cardiovascular, cerebrovascular, and respiratory systems that present with overlapping clinical manifestations (for instance, chest tightness and shortness of breath), accurate identification is critical for formulating effective treatment plans. However, the unstructured nature of medical records and the implicit relationships embedded in medical knowledge pose significant challenges to automated diagnosis. Existing methods overlook medical commonsense and triplet relational structures, rendering them incapable of capturing symptom–disease associations and consequen…
- OpenAlex · Published · First archived
FusionEP: Adaptive Cross-Modal Deep Fusion Network for Essential Protein Identification via Multi-Omics Integration and Contrastive Learning ↗
Identifying essential proteins lays a foundation for dissecting disease mechanisms and mining therapeutic targets. Existing algorithms mostly adopt unimodal inputs and struggle to capture multi-level biological interactions from genomics, subcellular localization and proteomics. We present FusionEP, which is an adaptive cross-modal deep fusion network built upon contrastive learning to predict essential proteins. FusionEP integrates gene expression profiles, subcellular localization features, and protein interaction map structures. For gene expression information, we design a six-layer Transfo…
- OpenAlex · Published · First archived
MSMFusion: A Method for Multiscale Dual-Path State Space Modeling for Multimodal Medical Image Fusion ↗
Multimodal medical image fusion aims to integrate information from different imaging techniques to generate a single fused image that is comprehensive and rich in detail. Structural and functional imaging provide high-resolution anatomical details and tissue metabolic information, respectively. Complementary fusion improves quantitative fusion quality and preserves structural and functional information in one view, which aids clinical interpretation. Currently, convolutional neural network-based methods struggle to efficiently capture global features, whereas Transformer-based models excel at…
- OpenAlex · Published · First archived
Photon production from gluon splitting and fusion induced by a magnetic field of arbitrary strength in relativistic heavy-ion collisions ↗
We compute the yield and elliptic flow coefficient for photons produced during the pre-equilibrium stage of semi-central relativistic heavy-ion collisions from the gluon fusion and splitting processes induced by the presence of a magnetic field. The calculation is performed for arbitrary values of the field strength. The pre-equilibrium gluon distribution is modeled with a glasma-inspired Bose-Einstein occupation factor, as well as with an anisotropic distribution that accounts for the rapid initial expansion along the beam axis. In both cases, we find a very good agreement between the calcula…
- arXiv · Published · First archived
Relativistic Six-Fluid Rotating-Plasma Force-Balance Equilibria for p-11B Fusion Conditions in Spherical Tori ↗
We formulate an axisymmetric spherical torus (ST) six-component magnetofluid equilibrium model for p_11B plasmas composed of thermal and suprathermal proton, boron, and electron fluids. The model is designed for p_11B parameter regimes where ion energies, strong current drive, energetic electron populations, and ion-electron temperature separation can render a single_fluid static_equilibrium description inadequate. It generalizes rotating_plasma equilibrium theory by incorporating relativistic thermal enthalpy corrections to the electron fluids via h(T/m_ec^2) and by constructing modified flux…
- OpenAlex · Published · First archived
Dynamic Hierarchical Attention Fusion Spatio-Temporal Network for Next POI Recommendation ↗
Next point-of-interest (POI) recommendation seeks to predict the POI that a user will visit next from historical check-in records. Accurate recommendations require modeling POI relations and user trajectory patterns. Existing methods remain limited in representing continuous spatial influence decay, reliability-filtered temporal associations, semantic hierarchies, and multi-membership attributes. Furthermore, user trajectories may contain relatively persistent behavioral regularities and short-term variations within a check-in sequence, while standard time-domain models do not explicitly decom…
- OpenAlex · Published · First archived
Review of Sintering Methods and Polymer Materials for Powder Bed Fusion Technology ↗
As a sustainable additive manufacturing method, powder bed fusion (PBF) technology has emerged as one of the important fabrication methods for mass production. The technology has several advantages, such as environmental friendliness, recyclability of materials, and being support-free, which make it have great potential in high-efficiency and green manufacturing. The sintering methods for PBF technology mainly have three technical routes: (1) conventional selective laser sintering (SLS); (2) high-speed sintering (HSS)/multi-jet fusion (MJF); (3) microwave heating (MH). This work systematically…
- OpenAlex · Published · First archived
A State Monitoring Method for Shear Hinges in Floating Slab Tracks Based on FMTF and PCNN-RWKV Fusion Network ↗
Floating slab track (FST) is a core vibration and noise reduction technology in urban rail transit. Shear hinges, key connectors of floating slabs, greatly affect rail transit operational stability and safety. Limited by complex operating conditions and weak feature extraction of traditional signal processing, existing methods yield inadequate feature representation, low diagnosis accuracy, and poor anti-noise performance. This study develops a novel shear hinge state recognition network combining Frequency Domain Markov Transition Field (FMTF), Parallel Convolutional Neural Network (PCNN), an…
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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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