Science – Page 14 – Minority Mindset

When Worries Vote: Election Polls and the Economy

31.01.2026 by qfx

A new analysis reveals how shifting economic anxieties-from inflation to trade policy-have influenced U.S. presidential election polls in recent cycles.

Decoding Sepsis: A New Approach to Early Detection

31.01.2026 by qfx

Time series relational data, despite its inherent complexity, can be effectively flattened into a manageable format, allowing for analysis and potentially revealing underlying patterns obscured by its original structure.

Researchers have developed a novel machine learning method for identifying sepsis earlier and with greater clarity by leveraging the power of relational data.

Beyond Fusion: Mastering Multi-Modal Time Series Prediction

31.01.2026 by qfx

A large language model orchestrates the dynamic allocation of temporal experts within a Mixture-of-Experts model through generated modulation signals, effectively enabling cross-modal control over time series computation and demonstrating a system where adaptability becomes intrinsic to its operational state-a characteristic of all evolving systems.

A new framework intelligently routes information across different data streams to dramatically improve the accuracy of forecasting complex time-dependent events.

Tracking the Pulse of Protest: How AI Can Decode Social Movements

31.01.2026 by qfx

$Social movements, as measured by online discourse surrounding #MeToo and Black Lives Matter, exhibit fluctuating periods of heightened visibility-distinguished by a threshold of [latex]\mu + 2\sigma[/latex]-that reveal the ephemeral nature of public attention and the difficulty of sustaining momentum beyond transient spikes in conversation.$

New research introduces a computational tool that analyzes online conversations surrounding movements like #MeToo and #BlackLivesMatter, offering a deeper understanding of how public discourse evolves across different platforms.

Fluid Flow Forecasts: Can AI Master the Equations?

30.01.2026 by qfx

Leveraging physics-informed disentanglement and text-embedded position embeddings, a novel framework-LLM4Fluid-achieves robust generalization across diverse fluid flow scenarios by creating near-orthogonal, physics-disentangled representations and bridging semantic and physical modalities, overcoming the limitations of scenario-specific methods.

A new approach harnesses the power of artificial intelligence to predict complex fluid dynamics with unprecedented accuracy and efficiency.

Unlocking Time-Series Forecasting with Spectral Diffusion

30.01.2026 by qfx

During a diffusion process, strategically layering noise addition-beginning with lower amplitude components-effectively prolongs the preservation of critical structural information by decelerating the degradation of dominant frequencies.

A new approach integrates spectral decomposition into diffusion models to improve the accuracy of long-term time-series predictions.

Navigating the AI Paradox

30.01.2026 by qfx

The taxonomy delineates the spectrum of risks and harms associated with artificial intelligence, categorizing potential negative outcomes to facilitate a structured understanding of the challenges inherent in its development and deployment.

Successfully deploying artificial intelligence requires more than just optimizing benefits and risks-it demands a new approach to managing inherent tensions.

Unlocking the Secrets of Exoplanet Atmospheres

30.01.2026 by qfx

A comparative analysis of spectral modification techniques reveals that PERTURB-c consistently clusters modified spectra around the target, demonstrating its efficiency in high-correlation data, while SHAP analysis produces a substantial number of out-of-distribution spectra, highlighting its limitations in such environments.

A new interpretability framework sheds light on the ‘black box’ of machine learning models used to analyze distant worlds.

Mapping Resilience: How AI Reveals Climate Risk and Human Flourishing

30.01.2026 by qfx

Across US counties from January 2013 to June 2023, the spatial distribution of latent climate risk demonstrably correlates with dimensions of human flourishing, with areas exhibiting higher risk generally showing diminished flourishing-a relationship established by analyzing standardized paths descending from climate risk factors, as detailed in preceding work →.

New research leverages artificial intelligence and social media data to pinpoint the geographic connections between climate vulnerability and well-being across the United States.

The Rise of Dangerous DIY AI

30.01.2026 by qfx

As artificial intelligence models become smaller and more efficient, the potential for misuse grows, even with limited computing resources.