The structure of a novel compound from Adansonia digitata has been elucidated, and its H and C NMR spectra have been assigned employing a variety of one-dimensional and two-dimensional NMR techniques without degradative chemistry. The Advanced Chemistry Development ACD/Structure Elucidator software was important for determining part of this structure that contained a fused bicyclic system with very few hydrogen atoms, which in turn, exhibited essentially no discriminating HMBC connectivities throughout that portion of the molecule. Copyright © 2016 John Wiley & Sons, Ltd.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5319920 | PMC |
http://dx.doi.org/10.1002/mrc.4466 | DOI Listing |
Sensors (Basel)
December 2024
College of Computer and Information Sciences (CCIS), King Saud University, Riyadh 11543, Saudi Arabia.
One of the most promising applications for electroencephalogram (EEG)-based brain-computer interfaces (BCIs) is motor rehabilitation through motor imagery (MI) tasks. However, current MI training requires physical attendance, while remote MI training can be applied anywhere, facilitating flexible rehabilitation. Providing remote MI training raises challenges to ensuring an accurate recognition of MI tasks by healthcare providers, in addition to managing computation and communication costs.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Electrical Engineering, University of Belgrade, 11000 Belgrade, Serbia.
Traditional tactile brain-computer interfaces (BCIs), particularly those based on steady-state somatosensory-evoked potentials, face challenges such as lower accuracy, reduced bit rates, and the need for spatially distant stimulation points. In contrast, using transient electrical stimuli offers a promising alternative for generating tactile BCI control signals: somatosensory event-related potentials (sERPs). This study aimed to optimize the performance of a novel electrotactile BCI by employing advanced feature extraction and machine learning techniques on sERP signals for the classification of users' selective tactile attention.
View Article and Find Full Text PDFPathogens
November 2024
College of Information Engineering, Yangzhou University, Yangzhou 225009, China.
This paper presents a novel methodology for plant disease detection using YOLOv8 (You Only Look Once version 8), a state-of-the-art object detection model designed for real-time image classification and recognition tasks. The proposed approach involves training a custom YOLOv8 model to detect and classify various plant conditions accurately. The model was evaluated using a testing subset to measure its performance in detecting different plant diseases.
View Article and Find Full Text PDFMolecules
December 2024
Department of Chemistry, RCSI, University of Medicine and Health Sciences, 123 St Stephen's Green, Dublin 2, D02 YN77 Dublin, Ireland.
The term "fluorescence" was first proposed nearly two centuries ago, yet its application in clinical medicine has a relatively brief history coming to the fore in the past decade. Nowadays, as fluorescence is gradually expanding into more medical applications, fluorescence image-guided surgery has become the new arena for this technology. It allows surgical teams to real-time visualize target tissues or anatomies intraoperatively to increase the precision of resection or preserve vital structures during open or laparoscopic surgeries.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Radiology and Interventional Radiology, Lausanne University Hospital, Lausanne University, 1015 Lausanne, Switzerland.
Background/objectives: Recent advancements in artificial intelligence (AI) have spurred interest in developing computer-assisted analysis for imaging examinations. However, the lack of high-quality datasets remains a significant bottleneck. Labeling instructions are critical for improving dataset quality but are often lacking.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!