Results 201 to 210 of about 29,786 (308)

Nano‐Confined Radical Anion as An NIR‐II Photothermal Immunogenic Amplifier for In Situ Cancer Vaccination

Advanced Science, EarlyView.
A nano‐confined radical anion acts as a photothermal immunogenic amplifier. Kinetically stabilized nanoparticles couple high near‐infrared‐II (NIR‐II) photothermal efficacy with glutathione (GSH) depletion to boost reactive oxygen species (ROS) and immunogenic cell death (ICD).
Mengxin Mu, Mengyu Guo, Jun Guan, Xiaofeng He, Mingdi Hu, Fene Gao, Klaus Müllen, Chendong Ji, Chunying Chen, Meizhen Yin   +9 more
wiley   +1 more source

Data management issues in mobile ad hoc networks. [PDF]

Proc Jpn Acad Ser B Phys Biol Sci, 2017
Hara T.
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Cross-Layer Service Discovery Mechanism for OLSRv2 Mobile Ad Hoc Networks. [PDF]

Sensors (Basel), 2015
Vara MI, Campo C.
europepmc   +1 more source

MANETs: Internet Connectivity and Transport Protocols

, 2007
A Mobile Ad hoc Network (MANET) is a collection of mobile nodes connected together over a wireless medium, which self-organize into an autonomous multi-hop wireless network.
Ancillotti, Emilio
core  

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Mobility based key management technique for multicast security in mobile ad hoc networks. [PDF]

ScientificWorldJournal, 2015
Madhusudhanan B, Chitra S, Rajan C.
europepmc   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Securing mobile ad hoc networks using danger theory-based artificial immune algorithm. [PDF]

PLoS One, 2015
Abdelhaq M, Alsaqour R, Abdelhaq S.
europepmc   +1 more source