We developed a table-top setup to perform magneto-optical pump-probe measurements with the possibility to independently tune the photon-energy of both pump and probe beams in the 0.5 eV-3.5 eV range. Our apparatus relies on a commercial turn-key amplified laser system, able to generate light pulses with duration shorter than or comparable to 100 fs throughout the whole spectral range. The repetition rate of the source can be modified via the computer in the 1 kHz to 1 MHz range. A commercial balanced detector is connected to a high-frequency digitizer, allowing for a highly-sensitive detection scheme: rotations of the probe polarization as small as 70 μdeg can be measured. Additionally, a DC magnetic field as high as 9 T and voltages in the kV regime can be applied on the sample. A cryostat allows us to precisely set the temperature of the specimen in the 4 K-420 K interval. We prove the performance of our setup by measuring the ultrafast demagnetization of a cobalt crystal as a function of a wide variety of experimental parameters.
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http://dx.doi.org/10.1063/5.0024449 | DOI Listing |
Langmuir
January 2025
Department of Chemistry, University of Utah, 315 South 1400 East, Salt Lake City, Utah 84112-0850, United States.
Modification of silica interfaces by covalent attachment of functional ligands is a primary means of controlling the interfacial chemistry of porous silicas used in separations, environmental cleanup, and biosensing. Recently, modification of hydrophobic, -alkyl-silane-functionalized interfaces has been achieved through self-assembly of zwitterionic phospholipids or mixed-charged surfactants to form "hybrid bilayers", producing interfaces that mimic lipid-bilayer partitioning and provide shape-selective partitioning of aromatic hydrocarbons. Charged headgroups, however, introduce electrostatic interactions that strongly influence the retention of ionizable solutes and require careful control over pH and ionic strength in the solution phase.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
School of Mechanical Engineering, Shandong University, Jinan, China.
Extensive research on retinal layer segmentation (RLS) using deep learning (DL) is mostly approaching a performance plateau, primarily due to reliance on structural information alone. To address the present situation, we conduct the first study on the impact of multi-spectral information (MSI) on RLS. Our experimental results show that incorporating MSI significantly improves segmentation accuracy for retinal layer optical coherence tomography (OCT) images.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Biophysics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Rice (Oryza sativa) is a vital food crop and staple diet for most of the world's population. Poor dietary choices have had a significant role in the development of type-2 diabetes in the population that relies on rice and rice-starch-based foods. Hence, our study investigated the in vitro digestion and glycemic indices of certain indigenous rice cultivars and the factors influencing these indices.
View Article and Find Full Text PDFPeerJ
January 2025
Institute of Science and Environment, University of Saint Joseph, Macao, Macao S.A.R., China.
While soundscapes shape the structure and function of auditory systems over evolutionary timescales, there is limited information regarding the adaptation of wild fish populations to their natural acoustic environments. This is particularly relevant for freshwater ecosystems, which are extremely diverse and face escalating pressures from human activities and associated noise pollution. The Siamese fighting fish is one of the most important cultured species in the global ornamental fish market and is increasingly recognized as a model organism for genetics and behavioural studies.
View Article and Find Full Text PDFPLoS One
January 2025
Computer Engineering, CCSIT, King Faisal University, Al Hufuf, Kingdom of Saudi Arabia.
The health of poultry flock is crucial in sustainable farming. Recent advances in machine learning and speech analysis have opened up opportunities for real-time monitoring of the behavior and health of flock. However, there has been little research on using Tiny Machine Learning (Tiny ML) for continuous vocalization monitoring in poultry.
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