Results 101 to 110 of about 31,026 (252)

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Deep Neural Network Model of Ultrafast 2D Direction‐of‐Arrival Estimation Using Planar Arrays for Multi‐Octave‐Band Digital Receiver Applications

IET Radar, Sonar & Navigation
This study presents a deep neural network (DNN) model for multi‐octave‐band direction‐finding (MOB‐DF) estimation using a broadband DF‐array and multi‐layer perceptron (MLP).
Chen Wu, Qi Er Teng, Raffi Fox
doaj   +1 more source

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley   +1 more source

Designing Wire Mazes for Replicating Natural Echoes to Study Bat Biosonar Function

Advanced Intelligent Systems, EarlyView.
A validated framework combining efficient physical modeling (multiple scattering model) and deep learning is presented to guide wire‐maze design for bat biosonar studies. This approach rapidly generates large datasets to test acoustic distinguishability among wire arrangements.
Chunlin Jia, Gengkai Hu, Boo Cheong Khoo, Rolf Müller   +3 more
wiley   +1 more source

A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines

Advanced Intelligent Systems, EarlyView.
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe, Eleonora Raimondo, Andrea Grimaldi, Pedram Khalili Amiri, Stefano Chiappini, Anna Giordano, Mario Carpentieri, Hyunsoo Yang, Massimo Chiappini, Giovanni Finocchio   +9 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

National and International Monitoring of Student Literacy and Numeracy Attainment: The Case for Rigorous Macro and Micro Analysis

Australian Journal of Social Issues, EarlyView.
ABSTRACT In her 2024 paper Are Australian students' academic skills declining? Interrogating 25 years of national and international standardised assessment data, Larsen compiled an impressive summary of major international (PISA, PIRLS and TIMSS) and national (NAPLAN) standardised assessments pertaining to literacy and numeracy.
Pamela C. Snow, Tanya A. Serry, Jennifer Buckingham, Lorraine S. Hammond, Stephen Dinham, Eamon Charles, Tessa A. Weadman, Nathanial R. Swain, Susan Hiland, Tessa Daffern   +9 more
wiley   +1 more source

Compositionally Engineered Carboxymethyl Cellulose‐Based Optical Fibers With Exceptionally Low Optical Loss and Quantitative Humidity Sensing

Advanced Physics Research, EarlyView.
Carboxymethyl cellulose‐based biopolymer optical fibers are fabricated using aqueous wet spinning. The fibers exhibit record‐low optical attenuation in polysaccharide‐based waveguides while maintaining efficient transmission across the visible‐to‐near‐infrared region of the electromagnetic spectrum.
Jani Patrakka, Alizee Sanouillet, Ville Hynninen, Nonappa   +3 more
wiley   +1 more source

Technology Transfer to Underwater Archaeology: The LAHKE Project at the Submerged Neolithic Site of La Marmotta

Archaeological Prospection, EarlyView.
ABSTRACT This document is a report on the field application of non‐invasive geophysical and robotic prospecting methods at the submerged Neolithic site of La Marmotta (Lake Bracciano, Italy), within the LAHKE (LAke Heritage Knowledge and Exploration) project; the study focuses on the practical validation, adaptation and transfer of existing ...
dell' Erba Ramiro, Cupertino Giacomo, Cipollini Angelo, Luciano Blasi, Quattrucci Luca   +4 more
wiley   +1 more source