Results 201 to 210 of about 26,053 (287)

Review of Memristors for In‐Memory Computing and Spiking Neural Networks

Advanced Intelligent Systems, EarlyView.
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari, Teresa Serrano‐Gotarredona, Bernabé Linares‐Barranco   +2 more
wiley   +1 more source

An Expanded Toolbox for Versatile Chemical Editing of Adeno‐Associated Virus

Angewandte Chemie, EarlyView.
We describe technology to introduce diverse non‐natural chemical functionalities site‐specifically into the capsid of adeno‐associated virus through genetic code expansion, and using them to engineer this leading vector for human gene therapy for enhanced tissue specificity and reduced immunogenicity Abstract Site‐specific incorporation of noncanonical
Quan Pham, Jake Glicksman, Boyang Han, David Koo, Conor Loynd, Soumya Jyoti Singha Roy, Abhishek Chatterjee   +6 more
wiley   +2 more sources

Quantum resilient security framework for privacy preserving AI in Apple MM1 on device architecture. [PDF]

Sci Rep
Umer N, Deng M, Zhang Y, Zhang M, Khan S.   +4 more
europepmc   +1 more source

Cryptographic Migration Dataset: Pre-Quantum to Post-Quantum

Pallarés de Bonrostro, Javier, González-Tablas, Ana Isabel   +1 more
openalex   +1 more source

Predicting Materials Thermodynamics Enabled by Large Language Model‐Driven Dataset Building and Machine Learning

Advanced Intelligent Systems, EarlyView.
Illustration of text data mining of rare earth mineral thermodynamic parameters with the large language model‐powered LMExt. A dataset is built with mined thermodynamic properties. Subsequently, a machine learning model is trained to predict formation enthalpy from the dataset.
Juejing Liu, Haydn Anderson, Noah I. Waxman, Vsevolod Kovalev, Byron Fisher, Elizabeth Li, Xiaofeng Guo   +6 more
wiley   +1 more source

Universal Catalyst Design Framework for Electrochemical Hydrogen Peroxide Synthesis Facilitated by Local Atomic Environment Descriptors

Angewandte Chemie, EarlyView.
A universal catalyst design framework integrating weighted atom‐centered symmetry function (wACSF) descriptors with machine learning accurately predicts adsorption energies for 2e− water oxidation reaction. Microkinetic modeling and experimental validation confirm the framework's universality, establishing a powerful paradigm for rational ...
Zhijian Liu, Yan Liu, Yuqi Zhang, Yeyu Deng, Zhong Zheng, Ruth Knibbe, Tianxiang Gao, Mingzhe Li, Ziye Wang, Bingqian Zhang, Xue Jia, Di Zhang, Heng Liu, Xuqiang Shao, Zhengyang Gao, Li Wei, Hao Li, Weijie Yang   +17 more
wiley   +2 more sources

Quantum secured blockchain framework for enhancing post quantum data security. [PDF]

Sci Rep
Reddy NR, Suryadevara S, Reddy KGR, Umamaheswari R, Guttula R, Kotoju R.   +5 more
europepmc   +1 more source

Post-Quantum Cryptography: Preparing Cybersecurity for the Quantum Computing Era

Dipendra Kumar Air
openalex   +1 more source

Extended version: enabling lattice-based post-quantum cryptography on the opentitan platform [PDF]

Tobias Stelzer, Felix Oberhansl, Jonas Schupp, Patrick Karl, Horia Turcuman   +4 more
openalex   +1 more source

QS4D: Quantization‐Aware Training for Efficient Hardware Deployment of Structured State‐Space Sequential Models

Advanced Intelligent Systems, EarlyView.
Quantization‐aware training creates resource‐efficient structured state space sequential S4(D) models for ultra‐long sequence processing in edge AI hardware. Including quantization during training leads to efficiency gains compared to pure post‐training quantization.
Sebastian Siegel, Ming‐Jay Yang, Younes Bouhadjar, Maxime Fabre, Emre Neftci, John Paul Strachan   +5 more
wiley   +1 more source