1,900-Year-Old Roman Latrine Sheds Light on Ancient Concrete's Durability

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Researchers are studying a nearly 2,000-year-old Roman latrine to better understand why Roman concrete has remained remarkably durable over millennia. The ancient building material has long puzzled scientists, as many Roman structures continue to stand while modern concrete deteriorates far more quickly. Analysis of the latrine's construction is providing new clues about the composition and techniques behind Roman concrete's longevity. The findings contribute to a growing body of research aimed at unlocking the secrets of this ancient material, which could inform more sustainable modern construction methods.

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Kivex Launches as Open-Source Icon Library Supporting Eight Dev Frameworks

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Developer Builds Focused Script-Timing Tool, Learns One Feature Beats Feature Bloat

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Developer Adds Native GBNF Grammar Support to Local LLM Structured-Output Library

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AMID Framework Uses Multi-Agent AI to Automate Medical Imaging Model Development

Researchers have introduced AMID, an Autonomous Multi-Agent framework designed to automate the development of medical imaging machine learning models. The framework addresses longstanding challenges in the field, including modality-specific experimentation, strict validation protocols, and regulatory compliance requirements. AMID is built on two core innovations: Data-Conditioned Method Planning, which tailors development pathways to specific datasets and available resources, and Verification-Guided Two-Stage Optimization, which balances broad solution exploration with rigorous auditing standards. Unlike general-purpose machine learning automation tools, AMID is purpose-built for medical imaging workflows, aiming to replace manual, bespoke engineering processes with an efficient agentic pipeline. The framework represents a significant step toward making AI-assisted medical model development both scalable and auditable.

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