Institute of Experimental Physics

The effect of Mn-doped zinc ferrite nanoparticles at a low volume concentration (1 × 10−4) on structural changes in the nematic liquid crystals 6CHBT and 5CB, induced by weak magnetic fields, was investigated using surface acoustic wave (SAW) and light transmission (LT) techniques. Structural changes caused by the applied magnetic field, in both increasing and decreasing modes, as well as after pulsed changes, were examined by measuring the responses of SAW attenuation and LT using a linearly polarized laser beam. The influence of nanoparticle shape (rods, needles, and clusters) and temperature on the structural changes was investigated. A shift in the threshold field and the transition temperature was observed. In addition, the magnetic properties of the individual samples in powder form were examined using M–H curves, M–T curves, and XRD patterns. The results obtained from all measurements are compared, and the effectiveness of each technique, considering the influence of nanoparticle shape and suspension stability, was evaluated.

Point-contact Andreev reflection spectroscopy at low temperatures and high magnetic fields has been performed on a noncentrosymmetric $\mathrm{L}{\mathrm{a}}_{3}\mathrm{S}{\mathrm{e}}_{4}$ superconductor with a critical temperature ${T}_{\mathrm{c}}=8$ K. Two superconducting energy gaps ${\mathrm{\ensuremath{\Delta}}}_{1}$ and ${\mathrm{\ensuremath{\Delta}}}_{2}$, with $2{\mathrm{\ensuremath{\Delta}}}_{1}/{k}_{\mathrm{B}}{T}_{\mathrm{c}}\ensuremath{\sim}5.8$ and $2{\mathrm{\ensuremath{\Delta}}}_{2}/{k}_{\mathrm{B}}{T}_{\mathrm{c}}\ensuremath{\sim}2.3$, are directly observed in some of the spectra. The temperature and magnetic field effects help to resolve a two-gap structure even on the most frequent spectra where at low temperatures only a single gap is apparent, reflected in a pair of maxima around the zero bias. Two-gap superconductivity consistently with the point contact Andreev reflection spectroscopy is also supported by the heat capacity and the Hall probe magnetization measurements.

The China Seismo-Electromagnetic Satellite (CSES) was launched successfully in February 2018. It is China’s first satellite to measure geophysical fields with scientific goals in both space and solid earth physics. In this work, we used CSES scalar magnetic data to derive a global lithospheric magnetic field model between ±65° geographic latitudes. The nightside data from March 2018 to November 2022 under quiet space weather conditions were selected. Then, the core and external fields were removed with the CHAOS-7 model. After further data quality control, the data were used to build a lithospheric magnetic field model using a spherical harmonic analysis. The obtained CSES model was compared with the CHAOS-7, CM6, and MF7 models in terms of power spectra and anomaly details, which confirmed that the CSES scalar data had good quality and could provide a reliable lithospheric magnetic field model up to degree 42.

Unusual magnetic properties of Van der Waals type antiferromagnetic semiconductors make them highly attractive for spintronics and optoelectronics. A link between the magnetic and optical properties of those materials, required for practical applications, has not been, however, established so far. Here, we report on a combined experimental and theoretical study of magnetic, optical, and structural properties of bulk CrPS$_{4}$ samples. We find that the magnetic-field-dependent circular polarization degree of the photoluminescence is a direct measure of the net magnetization of CrPS$_{4}$. Complementary, Raman scattering measured as a function of magnetic field and temperature enables the determination of the magnetic susceptibility curve of the material. Our experimental results are backed by Our experimental results are supported by density functional theory calculations that take as input the lattice parameters determined from temperature-dependent X-ray diffraction measurements. This allows us to explain the impact of spin ordering on the spectral position of Raman transitions in CrPS$_4$, as well as anomalous temperature shifts of selected of them. The presented method for all-optical determination of the magnetic properties is highly promising for studies of spin ordering and magnetic phase transitions in single- or a few-layer samples of magnetic layered materials, for which a poor signal-to-noise ratio precludes any reliable neutron scattering or magnetometry measurements.

Abstract The potential of multimodal generative artificial intelligence (mAI) to replicate human grounded language understanding, including the pragmatic, context-rich aspects of communication, remains to be clarified. Humans are known to use salient multimodal features, such as visual cues, to facilitate the processing of upcoming words. Correspondingly, multimodal computational models can integrate visual and linguistic data using a visual attention mechanism to assign next-word probabilities. To test whether these processes align, we tasked both human participants (N = 200) as well as several state-of-the-art computational models with evaluating the predictability of forthcoming words after viewing short audio-only or audio-visual clips with speech. During the task, the model’s attention weights were recorded and human attention was indexed via eye tracking. Results show that predictability estimates from humans aligned more closely with scores generated from multimodal models vs. their unimodal counterparts. Furthermore, including an attention mechanism doubled alignment with human judgments when visual and linguistic context facilitated predictions. In these cases, the model’s attention patches and human eye tracking significantly overlapped. Our results indicate that improved modeling of naturalistic language processing in mAI does not merely depend on training diet but can be driven by multimodality in combination with attention-based architectures. Humans and computational models alike can leverage the predictive constraints of multimodal information by attending to relevant features in the input.

We studied the temperature dependence of the magnetic properties and giant magnetoimpedance, GMI, effect in as-prepared and annealed Co69.2Fe3.6Ni1B12.5Si11Mo1.5C1.2 glass-coated microwires with nearly-zero magnetostriction. Substantial changes in the GMI ratio, ΔZ/Z, value and magnetic field, H, dependence, and in the hysteresis loops upon heating were observed. The modification in the hysteresis loop shape upon heating correlates with a change in the ΔZ/Z (H) dependencies. In as-prepared and most of the heat treated samples the hysteresis loop transformation from inclined to squared upon heating correlates with the change in ΔZ/Z(H) dependencies from double-peak to single-peak. However, the stress-annealed at 118 MPa samples present better thermal stability of the ΔZ/Z(H) dependencies and hysteresis loops. In all the studied samples an increase in the GMI ratio at 300 °C was observed. The origin of the observed temperature dependences is discussed in terms of the Hopkinson effect, temperature dependence and relaxation of internal stresses, induced magnetic anisotropy, and temperature dependence of the magnetostriction coefficient.

Chitosan stabilized iron oxide magnetic nanoparticles (Chit-MNPs) were prepared with the theoretical Chit/Fe3O4 weight ratios equal to 0.5, 1, 2, 3 w/w and characterized by different techniques. The effect of various Chit/Fe3O4 weight ratios on the samples’ hydrodynamic diameter, zeta potential, and isoelectric point was studied by the dynamic light-scattering method. Using TEM analysis, the average magnetic core size was found to be ranging from 6 nm to 9 nm. The obtained results are comparable to those from magnetic measurements. The magnetic measurements confirmed successful chitosan coating on MNPs by means of the decrease in saturation magnetizations from 69.2 emu·g−1 for unmodified MNPs to 66.6, 65.9, 65.5 and 65.2 emu·g−1 for Chit-MNPs at different ratios of Chit/MNPs 0.5, 1, 2, and 3. TGA was used to quantify the amount of chitosan adsorbed on MNPs surface – the max. amount was 0.045 mg chitosan/mg MNPs. The peroxidase-like catalytic activity of unmodified MNPs and chitosan Chit-MNPs in present of a substrate such as N,N-diethyl-p-phenylenediamine sulfate salt (DPD) and hydrogen peroxide was studied. The results confirmed the peroxidase-like activity of samples, – they catalytically oxidise substrate DPD by H2O2 to produce a typical colour reaction. The chitosan coating was found to slightly decrease catalytic activity compared to MNPs at pH 7.4. Despite the fact, these findings can be useful for creating sets of MNPs and Chit-MNPs samples possessing predefined peroxidase-like activity and could be applied for chromogenic reactions in the future.

The identification of crucial targets for hair regrowth in androgenetic alopecia (AGA) involves determining important characteristics and different stages during the process of hair follicle regeneration. Traditional methods for assessing key features and different stages of hair follicle primarily involve taking skin tissue samples and determining them through various staining or other methods. However, non-invasive assessment methods have been long sought. Therefore, in this study, endogenous fluorescence signals from skin keratin and second harmonic signals from skin collagen fibers were utilized as probes, two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) imaging techniques were employed to non-invasively assess hair shafts and collagen fibers in AGA mice in vivo. The TPEF imaging technique revealed that the alternation of new and old hair shafts and the different stages of the growth period in AGA mice were delayed. In addition, SHG imaging found testosterone reduced hair follicle area and miniaturized hair follicles. The non-invasive TPEF and SHG imaging techniques provided important methodologies for determining significant characteristics and different stages of the growth cycle in AGA mice, which will facilitate future non-invasive assessments on human scalps in vivo and reduce the use of animal testing.

A search for physics beyond the Standard Model inducing periodic signals in the dielectron and diphoton invariant mass spectra is presented using 139 fb−1 of s\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\sqrt{s} $$\\end{document} = 13 TeV pp collision data collected by the ATLAS experiment at the LHC. Novel search techniques based on continuous wavelet transforms are used to infer the frequency of periodic signals from the invariant mass spectra and neural network classifiers are used to enhance the sensitivity to periodic resonances. In the absence of a signal, exclusion limits are placed at the 95% confidence level in the two-dimensional parameter space of the clockwork gravity model. Model-independent searches for deviations from the background-only hypothesis are also performed.