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Study protocol of short versus long-term levetiracetam in brain tumors (LIBRA): a phase 3 randomized controlled trial
BACKGROUND: Seizures are common in patients with brain tumors, impacting daily life and healthcare burden. In contemporary neuro-oncology practice, levetiracetam is the most commonly prescribed anti-seizure medication (ASM). Although the practice is widely variable, levetiracetam is usually used for 2-3 years following surgery to prevent further seizures. However, the incidence of seizures post antitumoral treatment… →
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Development and validation of a nomogram to pediatric postoperative pulmonary complications following thoracic surgery
CONCLUSION: The nomogram, based on four objective and easily assessed factors, demonstrates excellent predictive performance for pediatric postoperative pulmonary complications after one-lung ventilation, enabling early risk assessment and targeted interventions to improve patient outcomes. →
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Computational modelling and neural correlates of reinforcement learning following three-week escitalopram: a double-blind, placebo-controlled semi-randomised study
Reinforcement learning is a fundamental aspect of adaptive behaviour, since it involves the acquisition and updating of associations between actions and their outcomes based on the rewarding or punishing consequences. Acute experimental manipulations of serotonin have provided compelling evidence for its role in reinforcement learning. However, it remains unknown how more chronic manipulation of serotonin,… →
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Technology Innovation Institute TII Releases Falcon-H1: Hybrid Transformer-SSM Language Models for Scalable, Multilingual, and Long-Context Understanding
Technology Innovation Institute TII Releases Falcon-H1: Hybrid Transformer-SSM Language Models for Scalable, Multilingual, and Long-Context Understanding As language models scale, balancing expressivity, efficiency, and adaptability becomes increasingly challenging. Transformer architectures dominate due to their strong performance across a wide range of tasks but are computationally expensive—particularly for long-context scenarios—due to the quadratic complexity of self-attention.… →
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This AI Paper Introduces MathCoder-VL and FigCodifier: Advancing Multimodal Mathematical Reasoning with Vision-to-Code Alignment
«`html Advancing Multimodal Mathematical Reasoning with Vision-to-Code Alignment Multimodal mathematical reasoning enables machines to solve problems involving both textual information and visual components such as diagrams and figures. This capability is essential in education, automated tutoring, and document analysis, where problems are often presented with a combination of text and images. A significant challenge in… →
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Google DeepMind Releases Gemma 3n: A Compact, High-Efficiency Multimodal AI Model for Real-Time On-Device Use
Google DeepMind Releases Gemma 3n: A Compact, High-Efficiency Multimodal AI Model for Real-Time On-Device Use As demand for faster, smarter, and more private AI on mobile devices grows, researchers are reimagining how AI models operate. The next generation of AI is not only lighter and faster but also designed for local deployment. By embedding intelligence… →
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RXTX: A Machine Learning-Guided Algorithm for Efficient Structured Matrix Multiplication
RXTX: A Machine Learning-Guided Algorithm for Efficient Structured Matrix Multiplication Discovering faster algorithms for matrix multiplication is a key pursuit in computer science and numerical linear algebra. Since the contributions of Strassen and Winograd in the late 1960s, several strategies have emerged, including gradient-based methods, heuristic techniques, group-theoretic frameworks, graph-based random walks, and deep reinforcement… →
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From Protocol to Production: How Model Context Protocol (MCP) Gateways Enable Secure, Scalable, and Seamless AI Integrations Across Enterprises
From Protocol to Production: How Model Context Protocol (MCP) Gateways Enable Secure, Scalable, and Seamless AI Integrations Across Enterprises The Model Context Protocol (MCP) has become essential for integrating AI models with broader software ecosystems. Developed by Anthropic, MCP standardizes how a language model or autonomous agent discovers and invokes external services, including REST APIs,… →
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Avoid These Five Pitfalls at Your Next Hackathon
Carolyn Geason-Beissel/MIT SMR | Getty Images Hackathons are a valuable tool for spurring innovative solutions to challenging problems, but they can fail badly. This can be particularly disheartening considering the substantial time, money, and other resources invested in preparation, organization, and execution. So, what causes them to go wrong? In my research, I observed 48… →
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A Step-by-Step Implementation Tutorial for Building Modular AI Workflows Using Anthropic’s Claude Sonnet 3.7 through API and LangGraph
«`html A Step-by-Step Implementation Tutorial for Building Modular AI Workflows Using Anthropic’s Claude Sonnet 3.7 through API and LangGraph In this tutorial, we provide a practical guide for implementing LangGraph, a streamlined, graph-based AI orchestration framework, integrated seamlessly with Anthropic’s Claude API. Through detailed, executable code optimized for Google Colab, developers learn how to build… →