Results 121 to 130 of about 136,680 (281)
Evaluation of Subject-Specific Heuristics for Initial Learning Environments: A Pilot Study [PDF]
Heuristic evaluation is a “discount” technique for finding usability problems in well-established domains. This paper presents thirteen suggested heuristics for initial learning environments (ILEs).
McKay, Fraser, Kölling, Michael
core
Heuristics? What about them? –Review on the operation of heuristics in chemical education in the past two decades [PDF]
Heuristics are evident in students’ reasoning processes in chemical education. This review of heuristics is a novel attempt to understand the use of heuristics in chemical education in the last two decades.
Rajashri, Priyadarshini +1 more
core +1 more source
A latent diffusion‐based framework is proposed for designing functionally graded metamaterials with perfect connectivity. By integrating vector‐quantized latent representations with mechanistic guidance, the framework enables accurate inverse design toward target elastic properties.
Jongbin Yu, Dosung Lee, Namjung Kim
wiley +1 more source
CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang +4 more
wiley +1 more source
TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao +8 more
wiley +1 more source
Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi +7 more
wiley +1 more source
A deep learning–driven pipeline mining 246 million protein sequences uncovers AhPETase, an evolutionarily distinct PET hydrolase. Engineered variant AhPETaseM1 degrades post‐consumer PET microplastics under physiological conditions and reverses microplasticinduced cytotoxicity in human lung and colon cells, establishing enzymatic microplastic ...
Yuxuan Wang +9 more
wiley +1 more source
STWave transforms massive microscopic‐resolution spatial transcriptomics into interpretable fine‐scale tissue maps through patch‐wise inference, wavelet‐based multi‐scale encoding, and dual‐domain reconstruction. It reduces noise while preserving weak spatial signals, enabling efficient analysis of 6 40 000 spots of 2.47 GB GPU memory and revealing ...
Tao Jiang +9 more
wiley +1 more source
Quantum‐Trained AI Enables Inverse Design of Organic Frontier Orbitals at Billion‐Scale
Quantum‐trained AI links molecular substructures to frontier‐orbital energetics and enables interpretable screening across nearly one billion GDB‐13 molecules. By combining fragment‐ and ring‐level insights with donor–acceptor energy alignment against ITIC, the framework narrows an immense chemical space to a small set of promising candidates and ...
Yeongnam Ko, Se Jin Kim, Ki Chul Kim
wiley +1 more source

