Results 101 to 110 of about 18,495 (249)
Catalytically Enhanced Near Room‐Temperature Hydrogen Sensing Using Pd‐ZnO Colloidal Crystals
Pd‐decorated ZnO colloidal crystal monolayers demonstrate excellent performance across a wide hydrogen concentration range at 33°C, with high selectivity and reproducible device fabrication. The sensors show strong responses even at low‐ppm H2 concentrations and an ultra‐low detection limit of 82 ppb, indicating their suitability for diverse hydrogen ...
Hamidah Alluhaybi +13 more
wiley +1 more source
Oligomerizing Pluronic triblock copolymers provides a processing strategy for tuning the mechanical properties and stimuli‐responsive behaviors of micellar hydrogels. Varying oligomer fraction produces hydrogels spanning brittle to highly extensible responses; maintaining micellar architectures enables cooling‐induced reverse thermal shape memory and ...
Gourav Kumbhojkar +8 more
wiley +1 more source
One‐Step Curcumin‐Mediated Multiphoton Lithography for Bioactive 3D Scaffolds
Curcumin‐mediated multiphoton lithography enables one‐step fabrication of highly architected complex gelatin methacryloyl scaffolds by exploiting curcumin as a multifunctional bioactive photoinitiator. The resulting 3D structures support mesenchymal stem cell adhesion, proliferation, and migration, while exhibiting dual antibacterial activity through ...
Myrto Charitaki +7 more
wiley +1 more source
Memristive‐Gated RC‐Delay Synaptic Transistors for Time‐Encoded Analog in‐Memory Computing
A Memristive‐Gated Transistor for Time‐Encoded Analog In‐Memory Computing — By exploiting the RC delay of a self‐rectifying interface‐type memristor, nonlinear I–V distortion is structurally bypassed, enabling 3‐bit nonvolatile memory, spike‐timing‐based analog encoding, and hardware‐calibrated reservoir‐computing validation within a unified device ...
Yun‐Seo Shin +7 more
wiley +1 more source
This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). This package can be used to solve single and multi-objective discrete and continuous optimization problems using EDAs based on undirected and directed ...
Roberto Santana +7 more
doaj
How do probabilistic graphical models and graph neural networks look at network data?
Graphs are a powerful data structure for representing relational data and are widely used to describe complex real-world systems. Probabilistic graphical models (PGMs) and graph neural networks (GNNs) can both leverage graph-structured data, but their ...
Michela Lapenna, Caterina De Bacco
doaj +1 more source
We consider the estimation of the marginal likelihood in Bayesian statistics, with primary emphasis on Gaussian graphical models, where the intractability of the marginal likelihood in high dimensions is a frequently researched problem.
Eric Chuu +3 more
doaj +1 more source
Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis. [PDF]
Cai MB +4 more
europepmc +1 more source
Recent advances in probabilistic graphical models
Probabilistic graphical models constitute a fundamental tool for the development of intelligent systems.
Concha Bielza +2 more
openaire +2 more sources

