Results 161 to 170 of about 12,102,780 (375)
Number of different binary functions generated by NK-Kauffman networks and the emergence of genetic robustness [PDF]
David Romero, Federico Zertuche
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On properties of binary random numbers [PDF]
openaire +1 more source
Engineering Strategies for 2D Layered Tin Halide Perovskite Field‐Effect Transistors
2D halide perovskites are promising candidates for field‐effect transistor (FET) applications due to their high stability and suppressed ion migration in the presence of bulky organic spacers. This review systematically summarizes the optimization engineering strategies of 2D perovskite FETs and future challenges, which provide guidance for developing ...
Shuanglong Wang+4 more
wiley +1 more source
Poly(heptazine) imides (PHIs), a crystalline carbon nitride subclass, intercalate metals to deliver high stability, tunable electronics, and efficient charge separation. These features enable solar‐driven applications such as hydrogen evolution, CO₂ reduction, and organic synthesis.
Gabriel A. A. Diab+6 more
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Bounds on the number of iterations for turbo-like code ensembles over the binary erasure channel [PDF]
Igal Sason, Gil Wiechman
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Extremal Binary PFAs with Small Number of States [PDF]
Stijn Cambie, Michiel de Bondt, Henk Don
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Versatile Cell Penetrating Peptide for Multimodal CRISPR Gene Editing in Primary Stem Cells
CRISPR machinery in diverse molecular formats (DNA, RNA, and ribonucleic protein) is complexed into nanoparticles with the cell‐friendly arginine‐alanine‐leucine‐alanine (RALA) cell‐penetrating peptide. Nanoparticles are delivered to primary mesenchymal stem cells ex vivo or locally in vivo to facilitate multimodal CRISPR gene editing. This RALA‐CRISPR
Joshua P. Graham+9 more
wiley +1 more source
A new Binary Number Code and a Multiplier, based on 3 as semi-primitive root of 1 mod 2^k
Nico F. Benschop
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TEACHING THE BINARY NUMBER SYSTEM IN SCRATCH [PDF]
X.Tangirov M.Ubaydullayeva
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Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery
This study provides an efficient approach to train a machine learning model by merging heterogeneous literature data to predict suitable polymers for siRNA delivery. Without the need for extensive laboratory synthesis, the machine learning enabled a virtual screening and successfully predicted a polymer that is validated for effective gene silencing in
Felix Sieber‐Schäfer+10 more
wiley +1 more source