In western China, Shu Road culture is a typical example of regional trade, transportation, and cultural fusion. Semantic fragmentation, audience cognitive differences, and a tardy effect evaluation are still present in cross-cultural communication. In this article, provide a prediction model that combines an attention-...
Abstract Non-suicidal self-injury (NSSI) represents a major health concern among adolescents with depression, yet no pharmacotherapies are specifically approved for NSSI. Selective serotonin reuptake inhibitors (SSRIs), commonly prescribed for adolescent depression, show inconsistent efficacy for NSSI, highlighting the...
Dan Qiao, Yujiao Wen, Vince D. Calhoun et al.· npj Mental Health Research· 0 citations
Inter-satellite links (ISLs) in large LEO constellations vary quickly with time, and their rapid change makes future link-state prediction a practical concern. Predicting ISLs with reasonable accuracy benefits routing decisions, resource scheduling, and overall network stability. Existing methods are still limited in s...
The increasing availability of heterogeneous data has transformed the scope and capabilities of predictive modeling across scientific, social, and environmental domains. Modern predictive systems no longer rely on a single structured dataset collected under controlled conditions. Instead, relevant information is distri...
ABSTRACT Gut microbiome‐based machine learning models for Type 2 Diabetes (T2D) classification often generalize poorly across cohorts due to population‐specific abundance variations—a practical challenge termed the abundance paradox. To capture conserved features beyond abundance, we developed DS‐GAT‐CP (Dual‐Stream Gr...
Changjian Wu, Ping Wei, Xuhui Wang et al.· iMetaMed· 0 citations
Abstract: Modern e-commerce platforms process catalogs exceeding hundreds of millions of items and billions of user-item interaction edges, creating severe computational bottlenecks for real-time personalized recommendation. While Graph Neural Networks (GNNs) capture higher-order collaborative signals and structural re...
Sonu Kumar Singh· Zenodo (CERN European Organi...· 0 citations
Federated Graph Learning (FGL) enables privacy-preserving collaborative training of Graph Neural Networks (GNNs) across distributed clients. In practice, discrepancies in local class distributions and graph structures result in non-independent and identically distributed (non-IID) data across clients, while heterogeneo...
Flood risk in dense urban environments such as Mumbai is spatially non-uniform and time-varying, making single-value, city-wide forecasts inadequate for emergency planning. This paper presents DisasterFlow AI, an end-to-end disaster-intelligence prototype that represents the city as a graph of 140 spatial monitoring no...
Among the principal functions of intelligent transportation systems, traffic flow prediction stands out as a critical one. Purely data-driven methods face the bottleneck of insufficient generalization capability in scenarios involving sparse data, noise interference, and anomalous events, while classical traffic flow t...
Juhan Zhu· Theoretical and Natural Scie...· 0 citations
The quick evolution of LLM-based social bots has changed online manipulation in a fundamental way. Current botnet platforms, like GraphMind, carry out complex and contextually aware interactions locally and construct intricate humanlike networks (for instance, small-world connectivity, homophily, and community structur...
Osman Ilyas· Zenodo (CERN European Organi...· 0 citations
ABSTRACT Ion–pair binding energy is a fundamental property that governs the physicochemical behavior of ionic liquids (ILs), influencing ion dissociation, transport, interfacial behavior, and field‐driven extraction processes across a wide range of applications. Accurate prediction of this quantity is therefore essenti...
Abu Taqui Md Tahsin, Paul Trusov, Rafid Bendimerad et al.· Journal of Computational Che...· 0 citations
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
MIT News · Artificial Intelligence· news.mit.eduJul 15, 2026
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Microsoft Research Blog· microsoft.comJul 13, 2026
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduJul 6, 2026
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
