The magnetic exchange parameters and anisotropy of the quasi-two dimensional antiferromagnet NiPS3_3

Neutron inelastic scattering has been used to measure the magnetic excitations in powdered NiPS$_3$, a quasi-two dimensional antiferromagnet with spin $S = 1$ on a honeycomb lattice. The spectra show clear, dispersive magnons with a $\sim 7$ meV gap at the Brillouin zone center. The data were fitted using a Heisenberg Hamiltonian with a single-ion anisotropy assuming no magnetic exchange between the honeycomb planes. Magnetic exchange interactions up to the third intraplanar nearest-neighbour were required. The fits show robustly that NiPS$_3$ has an easy axis anisotropy with $\Delta = 0.3$ meV and that the third nearest-neighbour has a strong antiferromagnetic exchange of $J_3 = -6.90$ meV. The data can be fitted reasonably well with either $J_1 < 0$ or $J_1 > 0$, however the best quantitative agreement with high-resolution data indicate that the nearest-neighbour interaction is ferromagnetic with $J_1 = 1.9$ meV and that the second nearest-neighbour exchange is small and antiferromagnetic with $J_2 = -0.1$ meV. The dispersion has a minimum in the Brillouin zone corner that is slightly larger than that at the Brillouin zone center, indicating that the magnetic structure of NiPS$_3$ is close to being unstable.Comment: 21 pages, 7 figures, 33 reference

Robustness assessment approaches for steel framed structures under catastrophic events

The current study deals with the robustness assessment methods of steel framed buildings under catastrophic events. Two steel framed buildings, designed according to old and new seismic Italian codes, have been herein analysed, by considering the uncertainties of both the material strength and the applied loads, through two investigation methods. First, within the methodologies used for robustness assessment under seismic loads, a deterministic method, framed within the Performance Based Seismic Design (PBSD), has been applied. Later on, the robustness of studied structures under different column-removed conditions, related to different catastrophic events (blast, impact, fire and so on), has been assessed by means of two forcebased analysis techniques (a literature approach and a more advanced procedure) in order to estimate their resistance against progressive collapse. The application of the two methods has allowed to calculate the robustness index of examined structures, by taking into account the influence of both the catenary effect phenomenon and different beam-to-column joints, with the final aim to show their behavioural difference in terms of robustness

Calibrating chemical multisensory devices for real world applications: An in-depth comparison of quantitative Machine Learning approaches

Chemical multisensor devices need calibration algorithms to estimate gas concentrations. Their possible adoption as indicative air quality measurements devices poses new challenges due to the need to operate in continuous monitoring modes in uncontrolled environments. Several issues, including slow dynamics, continue to affect their real world performances. At the same time, the need for estimating pollutant concentrations on board the devices, espe- cially for wearables and IoT deployments, is becoming highly desirable. In this framework, several calibration approaches have been proposed and tested on a variety of proprietary devices and datasets; still, no thorough comparison is available to researchers. This work attempts a benchmarking of the most promising calibration algorithms according to recent literature with a focus on machine learning approaches. We test the techniques against absolute and dynamic performances, generalization capabilities and computational/storage needs using three different datasets sharing continuous monitoring operation methodology. Our results can guide researchers and engineers in the choice of optimal strategy. They show that non-linear multivariate techniques yield reproducible results, outperforming lin- ear approaches. Specifically, the Support Vector Regression method consistently shows good performances in all the considered scenarios. We highlight the enhanced suitability of shallow neural networks in a trade-off between performance and computational/storage needs. We confirm, on a much wider basis, the advantages of dynamic approaches with respect to static ones that only rely on instantaneous sensor array response. The latter have been shown to be best choice whenever prompt and precise response is needed

Thermal stability and aggregation of sulfolobus solfataricus b-glycosidase are dependent upon the N-e-methylation of specific lysyl residues: critical role of in vivo post-translational modifications.

Methylation in vivo is a post-translational modification observed in several organisms belonging to eucarya, bacteria, and archaea. Although important implications of this modification have been demonstrated in several eucaryotes, its biological role in hyperthermophilic archaea is far from being understood. The aim of this work is to clarify some effects of methylation on the properties of β-glycosidase from Sulfolobus solfataricus, by a structural comparison between the native, methylated protein and its unmethylated counterpart, recombinantly expressed in Escherichia coli. Analysis by Fourier transform infrared spectroscopy indicated similar secondary structure contents for the two forms of the protein. However, the study of temperature perturbation by Fourier transform infrared spectroscopy and turbidimetry evidenced denaturation and aggregation events more pronounced in recombinant than in native β-glycosidase. Red Nile fluorescence analysis revealed significant differences of surface hydrophobicity between the two forms of the protein. Unlike the native enzyme, which dissociated into SDS-resistant dimers upon exposure to the detergent, the recombinant enzyme partially dissociated into monomers. By electrospray mapping, the methylation sites of the native protein were identified. A computational analysis of β-glycosidase three-dimensional structure and comparisons with other proteins from S. solfataricus revealed analogies in the localization of methylation sites in terms of secondary structural elements and overall topology. These observations suggest a role for the methylation of lysyl residues, located in selected domains, in the thermal stabilization of β-glycosidase from S. solfataricu

Independent component analysis of interictal fMRI in focal epilepsy: comparison with general linear model-based EEG-correlated fMRI

The general linear model (GLM) has been used to analyze simultaneous EEG–fMRI to reveal BOLD changes linked to interictal epileptic discharges (IED) identified on scalp EEG. This approach is ineffective when IED are not evident in the EEG. Data-driven fMRI analysis techniques that do not require an EEG derived model may offer a solution in these circumstances. We compared the findings of independent components analysis (ICA) and EEG-based GLM analyses of fMRI data from eight patients with focal epilepsy. Spatial ICA was used to extract independent components (IC) which were automatically classified as either BOLD-related, motion artefacts, EPI-susceptibility artefacts, large blood vessels, noise at high spatial or temporal frequency. The classifier reduced the number of candidate IC by 78%, with an average of 16 BOLD-related IC. Concordance between the ICA and GLM-derived results was assessed based on spatio-temporal criteria. In each patient, one of the IC satisfied the criteria to correspond to IED-based GLM result. The remaining IC were consistent with BOLD patterns of spontaneous brain activity and may include epileptic activity that was not evident on the scalp EEG. In conclusion, ICA of fMRI is capable of revealing areas of epileptic activity in patients with focal epilepsy and may be useful for the analysis of EEG–fMRI data in which abnormalities are not apparent on scalp EEG

Large parallel and perpendicular electric fields on electron spatial scales in the terrestrial bow shock

Large parallel ($\leq$ 100 mV/m) and perpendicular ($\leq$ 600 mV/m) electric fields were measured in the Earth's bow shock by the vector electric field experiment on the Polar satellite. These are the first reported direct measurements of parallel electric fields in a collisionless shock. These fields exist on spatial scales comparable to or less than the electron skin depth (a few kilometers) and correspond to magnetic field-aligned potentials of tens of volts and perpendicular potentials up to a kilovolt. The perpendicular fields are amongst the largest ever measured in space, with energy densities of $\epsilon_0 E^2/ n k_b T_e$ of order 10%. The measured parallel electric field implies that the electrons can be demagnetized, which may result in stochastic (rather than coherent) electron heating