Ahead of COP31, the Turkish Academy of Sciences (TÜBA) prepared this synthesis report, which brings together the collective expertise of 16 scientists from TÜBA Working Groups. Comprising seven chapters, the report charts a science-based path from electrification and zero waste to climate-resilient cities and green industrialisation. It explores how education, technology and artificial intelligence can accelerate climate resilience worldwide. Based on rigorous research, the report provides specific policy recommendations for the COP31 Action Agenda. The report reflects TÜBA's commitment to evidence-based climate science and international cooperation. Designed for scientists, policymakers and diplomats, the report calls for a global consensus based on shared responsibility. As Türkiye prepares to host COP31 in Antalya, this report serves as a scientific guide for climate action. It affirms that, as with lasting peace, lasting sustainability depends on unity across nations and disciplines.
Investigating how experienced developers use agents in building software, including their motivations, strategies, task suitability, and sentiments finds that while experienced developers value agents as a productivity boost, they retain their agency in software design and implementation out of insistence on fundamental software quality attributes.
This systematic review evaluates 55 studies from 2017 to 2023 on the application of machine learning techniques to ASD, highlighting key challenges and opportunities, particularly the need for models that can integrate complex data to improve diagnostic accuracy and treatment outcomes.
Rafael Muñoz-Terol, Jesús Peral, Sandra Amador et al.· Heliyon· 4 citations· ⚡1
This paper identifies two different routes through which models can acquire geometrically separable features: they can learn them from complementary co-occurrence signals in general language data, including text-number co-occurrence and cross-number interaction, or from multi-token addition problems.
This survey model agent state as a dynamic graph, where memories, tools, skills, workflows, and inter-agent relations are represented as typed nodes, edges, and subgraphs updated through schema-constrained rewrites to provide a compact structural lens for designing and governing self-evolving agents.
Yuanyuan Xu, Wenjie Zhang, Yin Chen et al.· 2 citations
A novel quantum generative model for synthesizing tabular data by proposing a quantum generative adversarial network architecture with flexible data encoding and a novel quantum circuit ansatz for effectively modeling tabular data is introduced.
P. Bhardwaj, Caitlin Jones, Lasse Dierich et al.· Scientific Reports· 2 citations
