The influence of semantics and numerical representation on the SNARC effect. [PDF]
Sci RepKang T, Liu Y, Qu M, Wang R, Tang T.
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Threshold Concepts and Concept Networks in Evolution Education: An Experimental Intervention Study
Science Education, EarlyView.ABSTRACT This study analyzes the effect of different instructions on threshold concepts within material covering natural selection on students' use of concepts about evolution. Moreover, it examines students' use of concepts as interconnected networks when reasoning about natural selection and analyzes how these concepts relate to each other regarding ...
Helena Aptyka +2 more
wiley +1 more source
A large language model framework for literature-based disease-gene association prediction. [PDF]
Brief BioinformLi PH +5 more
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Integrating multimodal data and machine learning for entrepreneurship research
Strategic Entrepreneurship Journal, EarlyView.Abstract Research Summary Extant research in neuroscience suggests that human perception is multimodal in nature—we model the world integrating diverse data sources such as sound, images, taste, and smell. Working in a dynamic environment, entrepreneurs are expected to draw on multimodal inputs in their decision making.
Yash Raj Shrestha, Vivianna Fang He
wiley +1 more source
Towards theoretically understanding how long-term memory semantics can support working memory performance. [PDF]
Q J Exp Psychol (Hove)Hart R, Logie RH, Brown Nicholls LA.
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Small, EarlyView.Chalcogenide materials emerge as efficient agents for water purification, enabling adsorptive and photocatalytic removal of dyes, pharmaceuticals, and pesticides. This review highlights recent advances in synthesis, structural tuning, and pollutant interaction mechanisms, while addressing challenges of toxicity and scalability. Insights into the future
Damilola Caleb Akintayo +2 more
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A Possible Worlds Semantics for Trustworthy Non-Deterministic Computations [PDF]
Ekaterina Kubyshkina, Giuseppe Primiero
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MSSA: multi-stage semantic-aware neural network for binary code similarity detection. [PDF]
PeerJ Comput SciWan B, Zhou J, Wang Y, Chen F, Qian Y.
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Self‐Driving Microscopes: AI Meets Super‐Resolution Microscopy
Small Methods, EarlyView.This review examines the use of machine learning to automate super‐resolution optical microscopy, enabling the microscope to autonomously make decisions on what, when, and how to image. By eliminating the need for human intervention, this approach has the potential to enhance the versatility and accessibility of super‐resolution microscopy.
Edward N. Ward +3 more
wiley +1 more source
Game Semantics for Higher-Order Unitary Quantum Computation [PDF]
Samson Abramsky, Radha Jagadeesan
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