Results 201 to 210 of about 73,457 (292)

Symptom-level interactions between digital addiction and psychological resources: a large-scale cross-validation study. [PDF]

Front Psychol
Aldemir A.
europepmc   +1 more source

SigmaFormer: Augmenting transformer encoders with COSMO sigma profiles for pure component property prediction

AIChE Journal, EarlyView.
Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim, Silabrata Pahari, Joseph Sang‐Il Kwon   +2 more
wiley   +1 more source

Membrane insertion of mitochondrial-encoded proteins regulates ribosome decoding speed. [PDF]

Nat Struct Mol Biol
Schöndorf T, Petrychenko V, Kotan I, Dahal D, Napieraj N, Cruz-Zaragoza LD, Wang C, Urbach O, Gall T, Dennerlein S, Kramer G, Fischer N, Rehling P.   +12 more
europepmc   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Spectroscopic Investigation of the Interaction Between a Spermine-Functionalized Porphyrin and TERRA G-Quadruplexes. [PDF]

Int J Mol Sci
Travagliante G, Gaeta M, Campanella G, Yatsunyk LA, D'Urso A.   +4 more
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Topology-Induced Reduction in the Order-Disorder Transition in AB Block Copolymer: A Unit-Matched Comparison of Diblock, Multiblock, Comb, and Star Architectures. [PDF]

Polymers (Basel)
Huh J.
europepmc   +1 more source

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets

Advanced Intelligent Discovery, EarlyView.
An experimental‐to‐computational workflow is presented that transforms experimental 3D focused ion beam‐scanning electron microscopy data into a simulation‐ready digital microstructure for multiphase functional materials. Using heavy‐rare‐earth‐free Nd–Fe–B magnets as a model system, the approach quantifies grain connectivity across complex secondary ...
Nikita Kulesh, Anton Bolyachkin, Hajime Nakamura, Tadakatsu Ohkubo, Hossein Sepehri‐Amin   +4 more
wiley   +1 more source

Morphometric analysis of the thymic epithelial cell network using integrated and orthogonal digital pathology approaches. [PDF]

Commun Biol
Lagou MK, Markaki MP, Vodopyanov S, Argyris DG, Karagiorgis GK, Gunther-Cummins L, Hardas A, Panorias C, DesMarais S, Entenberg C, Carpenter RS, Filippou PS, Guzik H, Nishku X, Churaman J, DesMarais V, Macaluso FP, Maryanovich M, Angelopoulou K, Poutahidis T, Karagiannis GS.   +20 more
europepmc   +1 more source