Results 171 to 180 of about 1,044,682 (335)
What the nature of natural language tells us about how to make natural-language-like programming languages more natural [PDF]
Jerry R. Hobbs
openalex +1 more source
Recycling of Thermoplastics with Machine Learning: A Review
This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque+5 more
wiley +1 more source
MobsPy: A programming language for biochemical reaction networks. [PDF]
Cravo F, Prakash G, Függer M, Nowak T.
europepmc +1 more source
Control Separation in programming languages [PDF]
Michael James Lemon+2 more
openalex +1 more source
Understanding Functional Materials at School
This review outlines strategies for effectively teaching nanoscience in schools, focusing on challenges such as scale comprehension and curriculum integration. Emphasizing inquiry‐based learning and chemistry core concepts, it showcases hands‐on activities, digital tools, and interdisciplinary approaches.
Johannes Claußnitzer, Jürgen Paul
wiley +1 more source
GraphPPL.jl: A Probabilistic Programming Language for Graphical Models. [PDF]
Nuijten WWL, Bagaev D, de Vries B.
europepmc +1 more source
Rationale for the design of the Ada programming language [PDF]
Jean D. Ichbiah+5 more
openalex +1 more source
Enthesis injuries are a worldwide healthcare problem. Biomimetic electrospun enthesis fascicle‐inspired scaffolds, with and without nano‐mineralization are developed. Human Mesenchymal Stromal cells (hMSCs) express the most balanced enthesis markers on the non‐mineralized scaffolds.
Alberto Sensini+11 more
wiley +1 more source
Dynamic flow control through active matter programming language. [PDF]
Yang F+4 more
europepmc +1 more source
Steep‐Switching Memory FET for Noise‐Resistant Reservoir Computing System
We demonstrate the steep‐switching memory FET with CuInP2S6/h‐BN/α‐In2Se3 heterostructure for application in noise‐resistant reservoir computing systems. The proposed device achieves steep switching characteristics (SSPGM = 19 mV/dec and SSERS = 23 mV/dec) through stabilization between CuInP2S6 and h‐BN.
Seongkweon Kang+6 more
wiley +1 more source