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Glioblastoma is the most malignant type of central nervous system tumor with GBM subtypes cleaved based on molecular level gene alterations. These alterations are also happened to affect the histology. Thus, it can cause visible changes in…

Quantitative Methods · Quantitative Biology 2020-10-28 Navodini Wijethilake , Mobarakol Islam , Dulani Meedeniya , Charith Chitraranjan , Indika Perera , Hongliang Ren

Characterizing ion adsorption and diffusion in porous carbons is essential to understand the performance of such materials in a range of key technologies such as energy storage and capacitive deionisation. Nuclear Magnetic Resonance (NMR)…

Materials Science · Physics 2023-05-08 Anagha Sasikumar , Céline Merlet

Nuclear magnetic resonance spectroscopy (MRS) allows for the determination of atomic structures and concentrations of different chemicals in a biochemical sample of interest. MRS is used in vivo clinically to aid in the diagnosis of several…

Medical Physics · Physics 2021-05-04 Zohaib Iqbal , Dan Nguyen , M. Albert Thomas , Steve Jiang

Particle-based modeling of materials at atomic scale plays an important role in the development of new materials and understanding of their properties. The accuracy of particle simulations is determined by interatomic potentials, which…

Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic resonance imaging that allows simultaneous measurement of multiple tissue properties in a single, time-efficient acquisition. Standard MRF reconstructs…

Computer Vision and Pattern Recognition · Computer Science 2018-12-20 Ilkay Oksuz , Gastao Cruz , James Clough , Aurelien Bustin , Nicolo Fuin , Rene M. Botnar , Claudia Prieto , Andrew P. King , Julia A. Schnabel

Accurate spectral analysis of high-energy astrophysical sources often relies on comparing observed data to incident spectral models convolved with the instrument response. However, for Gamma-Ray Bursts and other high-energy transient events…

Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable tool in chemistry and biology but often suffers from long experimental time. We present a proof-of-concept of application of deep learning and neural network for…

Medical Physics · Physics 2019-05-15 Xiaobo Qu , Yihui Huang , Hengfa Lu , Tianyu Qiu , Di Guo , Tatiana Agback , Vladislav Orekhov , Zhong Chen

The metabolic process in a cell is modeled with the use of the Fourier transformation. The histograms of the invariant measures of chaotic attractors are constructed. In particular, a scenario of adaptation of the metabolic process under a…

Chaotic Dynamics · Physics 2017-07-17 V. I Grytsay

Magnetic resonance imaging (MRI) is the cornerstone technique for diagnostic medicine, biology, and neuroscience. This imaging method is highly innovative, noninvasive and its impact continues to grow. It can be used for measuring changes…

Plasmonics is a research area merging the fields of optics and nanoelectronics by confining light with relatively large free-space wavelength to the nanometer scale - thereby enabling a family of novel devices. Current plasmonic devices at…

For many complex systems the interaction of different scales is among the most interesting and challenging features. It seems not very successful to extract the physical properties in different scale regimes by the existing approaches, such…

Fluid Dynamics · Physics 2015-05-14 L. P. Wang , Y. X. Huang

The coupling of an electron monochromator (EM) to a mass spectrometer (MS) has created a new analytical technique, EM-MS, for the investigation of electrophilic compounds. This method provides a powerful tool for molecular identification of…

Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of…

It is common to measure a single sample using multiple different microscopy methods that have variable scales, rotation and translation. Registering hyperspectral images of two dimensional materials is particularly difficult due to the lack…

Materials Science · Physics 2022-07-12 Kirby Schmidt , Anthony Trofe , Tetyana Ignatova

High harmonic spectroscopy has the potential to combine attosecond temporal with sub-Angstrom spatial resolution of the early nuclear and multielectron dynamics in molecules. It involves strong field ionization of the molecule by the IR…

Atomic Physics · Physics 2013-08-08 Valeria Serbinenko , Olga Smirnova

Representation learning frameworks in unlabeled time series have been proposed for medical signal processing. Despite the numerous excellent progresses have been made in previous works, we observe the representation extracted for the time…

Signal Processing · Electrical Eng. & Systems 2024-01-12 Luyuan Xie , Cong Li , Xin Zhang , Shengfang Zhai , Yuejian Fang , Qingni Shen , Zhonghai Wu

Agentic language models compose multi step reasoning chains, yet intermediate steps can be corrupted by inconsistent context, retrieval errors, or adversarial inputs, which makes post hoc evaluation too late because errors propagate before…

Machine Learning · Computer Science 2025-11-11 Valentin Noël

The miniaturisation of transistors is approaching its limits due to challenges in heat management and information transfer speed. To overcome these obstacles, emerging technologies such as spintronics are being developed, which leverage the…

Purpose: Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. The authors have investigated a photon-counting spectral…

Medical Physics · Physics 2021-01-21 Erik Fredenberg , Magnus Hemmendorff , Bjorn Cederstrom , Magnus Aslund , Mats Danielsson

Magnetic Resonance Spectroscopic Imaging (MRSI) is a valuable tool for studying metabolic activities in the human body, but the current applications are limited to low spatial resolutions. The existing deep learning-based MRSI…

Image and Video Processing · Electrical Eng. & Systems 2022-06-22 Siyuan Dong , Gilbert Hangel , Wolfgang Bogner , Georg Widhalm , Karl Rössler , Siegfried Trattnig , Chenyu You , Robin de Graaf , John Onofrey , James Duncan