Results 121 to 130 of about 162,086 (291)
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley +1 more source
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source
The Interoperability Challenge in DFT Workflows Across Implementations
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen +13 more
wiley +1 more source
Graphical user interface design for a calibration device for infrared tympanic thermometers
This study presents the development of a laboratory calibration device for infrared tympanic thermometers (ITTs), incorporating a high-stability gray-body cavity as an approximation to a blackbody radiation source.
Margarita Kaplun Mucharrafille +4 more
doaj +1 more source
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia +2 more
wiley +1 more source
An electromagnetic manipulation system enhances magnetic field strength in the Z‐direction for 3D control of microrobots and nanoparticles. Featuring eight metal‐core coils and two air‐core coils arranged hemispherically, it ensures unimpeded workspace access and integrates imaging tools.
Nader Latifi Gharamaleki +4 more
wiley +1 more source
Novel method and tool to identify solitary waves in the Martian plasma environment
This paper introduces a method and an innovative graphical user interface (GUI) tool to identify bipolar solitary wave structures in the Mars Atmosphere and Volatile EvolutioN (MAVEN) mission dataset.
Sahil Pandey, Amar Kakad, Bharati Kakad
doaj +1 more source
SuperResNET is a powerful integrated software that reconstructs network architecture and molecular distribution of subcellular structures from single molecule localization microscopy datasets. SuperResNET segments the nuclear pore complex and corners, extracts size, shape, and network features of all segmented nuclear pores and uses modularity analysis
Yahongyang Lydia Li +6 more
wiley +1 more source
This work presents a flexible, battery‐free sensor that forms a closed‐loop feedback system for smart compression therapy devices. Its scalable surface‐mount manufacturing, compact form factor, and wireless communication enable seamless integration with a wide range of active compression garments, improving user experience and therapeutic outcomes ...
Sinuo Zhao +11 more
wiley +1 more source

