Results 261 to 270 of about 1,095,825 (329)

Local dependence in random graph models: characterization, properties and statistical inference. [PDF]

J Am Stat Assoc, 2015
Schweinberger M, Handcock MS.
europepmc   +1 more source

Computational Modeling of Reticular Materials: The Past, the Present, and the Future

Advanced Materials, EarlyView.
Reticular materials are advanced materials with applications in emerging technologies. A thorough understanding of material properties at operating conditions is critical to accelerate the deployment at an industrial scale. Herein, the status of computational modeling of reticular materials is reviewed, supplemented with topical examples highlighting ...
Wim Temmerman, Ruben Goeminne, Kuber Singh Rawat, Veronique Van Speybroeck   +3 more
wiley   +1 more source

Role Analysis in Networks using Mixtures of Exponential Random Graph Models. [PDF]

J Comput Graph Stat, 2015
Salter-Townshend M, Murphy TB.
europepmc   +1 more source

Thermal Processing Creates Water‐Stable PEDOT:PSS Films for Bioelectronics

Advanced Materials, Volume 37, Issue 13, April 2, 2025.
Instead of using chemical cross–linkers, it is shown that PEDOT:PSS thin films for bioelectronics become water‐stable after a simple heat treatment. The heat treatment is compatible with a range of rigid and elastomeric substrates and films are stable in vivo for >20 days.
Siddharth Doshi, Margaux O. A. Forner, Pingyu Wang, Salim El Hadwe, Amy T. Jin, Gerwin Dijk, Kenneth Brinson, Juhwan Lim, Antonio Dominguez‐Alfaro, Carina Yi Jing Lim, Alberto Salleo, Damiano G. Barone, Guosong Hong, Mark L. Brongersma, Nicholas A. Melosh, George G. Malliaras, Scott T. Keene   +16 more
wiley   +1 more source

Using Exponential Random Graph Models to Analyze the Character of Peer Relationship Networks and Their Effects on the Subjective Well-being of Adolescents. [PDF]

Front Psychol, 2017
Jiao C, Wang T, Liu J, Wu H, Cui F, Peng X.   +5 more
europepmc   +1 more source

Recognizing random intersection graphs

, 2000
Erich Prisner
openalex   +1 more source

Machine‐Learning‐Aided Advanced Electrochemical Biosensors

Advanced Materials, EarlyView.
Electrochemical biosensors are highly sensitive, portable, and versatile. Advanced nanomaterials enhance their performance, while machine learning (ML) improves data analysis, minimizes interference, and optimizes sensor design. Despite progress in both fields, their combined potential in diagnostics remains underexplored.
Andrei Bocan, Roozbeh Siavash Moakhar, Carolina del Real Mata, Max Petkun, Tristan De Iure‐Grimmel, Sripadh Guptha Yedire, Hamed Shieh, Arash Khorrami Jahromi, Sahar Sadat Mahshid, Sara Mahshid   +9 more
wiley   +1 more source

Parameter tuning patterns for random graph coloring with quantum annealing. [PDF]

PLoS One, 2012
Titiloye O, Crispin A.
europepmc   +1 more source

Рецензия на книгу Kolchin V. F. “Random Graphs”

, 2000
Vladimir Vatutin, Vladimir Vatutin
openalex   +2 more sources

A Multimodal Humidity Adaptive Optical Neuron Based on a MoWS2/VOx Heterojunction for Vision and Respiratory Functions

Advanced Materials, EarlyView.
A multifunctional memristor is demonstrated for in‐memory sensing and computing, leveraging a MoWS₂/VOx heterojunction to enable high ON/OFF ratio up to 10⁸ with ultralow operating voltages of ±0.2 V. This bio‐inspired multimodal design exhibits tunable synaptic behavior across electrical, optical, and humidity stimuli, enabling in situ modulation of ...
Abdul Momin Syed, Dhananjay D. Kumbhar, Hanrui Li, Manoj Kumar Rajbhar, Dayanand Kumar, Pratibha Pal, Nimer Wehbe, Mohamed ben Hassine, Nazek El‐Atab   +8 more
wiley   +1 more source