Across 198 community-collected prompts and nine commercial APIs, psychological manipulation outperformed technical obfuscation, attack transfer across models was limited to 16.9% of transformations, and Claude 4 models showed higher failure rates than earlier Claude versions.
Moisture-Driven Morphology Changes in the Thermal and Dielectric Properties of TPU-Based Syntactic Foams
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abstract
Syntactic foams are a promising candidate for applications in marine and oil and gas industries in underwater cables and pipelines due to their excellent insulation properties. The effective transmission of electrical energy through cables requires insulation materials with a low loss factor and low dielectric constant. Similarly, in transporting fluid through pipelines, thermal insulation is crucial. However, both applications are susceptible to potential environmental degradation from moisture exposure, which can significantly impact the material's properties. This study addresses the knowledge gap by examining the implications of prolonged moisture exposure on TPU and TPU-derived syntactic foam via various multi-scale materials characterization methods. The research focuses on a flexible syntactic foam created using selective laser sintering and thermoplastic polyurethane elastomer (TPU) reinforced with glass microballoons (GMB). The study specifically explores the impact of moisture exposure duration and GMB volume fraction on microphase morphological changes, their associated mechanisms, and their influence on thermal transport and dielectric properties.
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PrompTrend: Continuous Community-Driven Vulnerability Discovery and Assessment for Large Language Models
Across 198 community-collected prompts and nine commercial APIs, psychological manipulation outperformed technical obfuscation, attack transfer across models was limited to 16.9% of transformations, and Claude 4 models showed higher failure rates than earlier Claude versions.