Results 51 to 60 of about 2,835 (238)
Temporal Interference Stimulation Enhances Neural Regeneration
Temporal interference (TI) stimulation is proposed as a non‐invasive approach to enhance neural regeneration in the deep brain. Theta‐band TI modulation selectively promotes neural progenitor cell differentiation in vitro and augments hippocampal neurogenesis in amouse model of Alzheimer's disease‐like amyloidosis.
Sofia Peressotti +15 more
wiley +1 more source
ABSTRACT Blood‐based liquid biopsies hold transformative potential for non‐invasive cancer management, but current approaches relying on rare circulating tumor components limit their broad clinical utility. Platelets, abundant in blood and mediating diverse cancer‐associated responses, represent a compelling yet largely unexplored alternative.
Yan Ma +28 more
wiley +1 more source
This study establishes a CT‐based radiomics framework to quantify intratumoral heterogeneity (ITH) in HNSCC. Using unsupervised clustering, tumor ROIs and VOIs are analyzed to calculate 2D/3D ITH scores. The score shows strong predictive value for prognosis and immunotherapy response, and is associated with tumor metabolism and immune microenvironment,
Xinwei Chen +15 more
wiley +1 more source
Gap‐Seeded Nucleation of Single Ag Nanoparticles for Filamentary Memristors
A new fabrication method for filamentary Ag memristors is presented. Single Ag nanoparticles are nucleated at predefined locations in a Pt gap via an aqueous electroless plating process. Conditioned into a memristor, small footprints of < 100 × 100 nm2 and low switching voltages were realized.
Markus Fischer‐Butesheva +11 more
wiley +1 more source
Automatic Determination of Quasicrystalline Patterns from Microscopy Images
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender +2 more
wiley +1 more source
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian +12 more
wiley +1 more source
Geometry Systems for Lattice-Based Reconfigurable Space Structures [PDF]
We describe analytical methods for the design of the discrete elements of ultralight lattice structures. This modular, building block strategy allows for relatively simple element manufacturing, as well as relatively simple robotic assembly of low mass ...
Cheung, Kenneth +5 more
core +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Mirrored Light Field Video Camera Adapter [PDF]
This paper proposes the design of a custom mirror-based light field camera adapter that is cheap, simple in construction, and accessible. Mirrors of different shape and orientation reflect the scene into an upwards-facing camera to create an array of ...
Corke, Peter +3 more
core +2 more sources
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri +6 more
wiley +1 more source

