The inverse scattering transform (IST) is a mathematical transformation that can be used to derive RF pulses from functions called continuous spectra describing the final state of the spin system. This paper reviews three seemingly unrelated numerical algorithms that have appeared in the literature, and shows that they are all derivable from the IST. When the continuous spectra are rational, the finite rank kernel method is used to convert the IST to a matrix equation that is easily solved. Another algorithm, equivalent to the so-called "layer stripping" algorithm used in seismology, is derived by assuming that the spectra are Fourier series. Finally, the Shinnar-Le Roux (SLR) algorithm is derived by assuming that the spectra are ratios of Fourier series. With proper interconversion between the rational, series, and ratio of series forms of the continuous spectra, these algorithms generate RF pulses with identical or nearly identical shapes and performance properties, and can be regarded as equivalent.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1002/mrm.1910290408 | DOI Listing |
We report the radiation-induced darkening (RD) effect caused by X-ray radiation and the bleaching effect caused by D/H/N loading in self-developed Yb-doped large mode-area photonic crystal fibers (LMA PCFs). The decrease in the slope efficiency caused by irradiation decays exponentially with an increase in the X-ray radiation doses, and the radiation-induced gain variation (RIGV) showed a linear decay trend with increasing irradiation doses. The slope efficiency of Yb-doped LMA PCF, which significantly degraded from 71.
View Article and Find Full Text PDFRapid Commun Mass Spectrom
May 2025
Department of Chemistry, The University of North Texas, Denton, Texas, USA.
Rationale: Fentanyl and fentanyl analogs continue to pose a serious threat to the public health. The vast number of fentanyl analogs emerging on the black-market call for optimized analytical methods for the detection, analysis, and characterization of these extremely dangerous drugs.
Methods: Atmospheric pressure solids analysis probe (ASAP) mass spectrometry was used for the rapid analysis of 250 synthetic opioid standards, including 211 fentanyl analogs, 32 non-fentanyl related opioids, and 8 fentanyl precursors.
J Vis Exp
January 2025
Fever Outpatient Clinic, Dongzhimen Hospital, Affiliated to Beijing University of Chinese Medicine;
Non-invasive assessment of pulmonary nodule malignancy remains a critical challenge in lung cancer diagnosis. Traditional methods often lack precision in differentiating benign from malignant nodules, particularly in the early stages. This study introduces an approach using multifractal spectrum analysis to quantitatively evaluate pulmonary nodule characteristics.
View Article and Find Full Text PDFAnal Biochem
January 2025
Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Zagazig University, Zagazig, 44519, Egypt.
This work represents different spectrophotometric techniques for concurrent quantification of Indacaterol (IND) and Mometasone furoate (MOM); co-formulated inhalation capsules to control asthma symptoms. Direct spectrophotometric (D) approach was applied for IND assay. While, absorption factor (AF), ratio difference (RD), mean centering of the ratio spectra (MC), and continuous wavelet transform (CW) techniques were utilized for MOM quantification.
View Article and Find Full Text PDFBioinformatics
January 2025
Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, W12 0NN, United Kingdom.
Unlabelled: Metabolomics extensively utilizes Nuclear Magnetic Resonance (NMR) spectroscopy due to its excellent reproducibility and high throughput. Both one-dimensional (1D) and two-dimensional (2D) NMR spectra provide crucial information for metabolite annotation and quantification, yet present complex overlapping patterns which may require sophisticated machine learning algorithms to decipher. Unfortunately, the limited availability of labeled spectra can hamper application of machine learning, especially deep learning algorithms which require large amounts of labelled data.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!