Theoretical studies of low-frequency Alfvén modes in tokamak plasmas

Linear wave properties of the low-frequency Alfvén modes (LFAMs) observed in the DIII-D tokamak experiments with reversed magnetic shear [Nucl. Fusion 61, 016029 (2021)] are theoretically studied and delineated based on the general fishbone-like dispersion relation. By adopting the representative experimental equilibrium parameters, it is found that, in the absence of energetic ions, the LFAM is a kinetic ballooning mode instability of reactive-type with a dominant Alfvénic polarization. More specifically, due to diamagnetic and trapped particle effects, the LFAM can be coupled with the beta-induced Alfvén-acoustic mode in the low-frequency region (frequency much less than the thermal-ion transit and/or bounce frequency); or with the beta-induced Alfvén eigenmode in the high frequency region (frequency higher than or comparable to the thermal-ion transit frequency); resulting in reactive-type instabilities. Moreover, the ‘Christmas light’ and ‘mountain peak’ spectral patterns of LFAMs as well as the dependence of instability drive on the electron temperature observed in the experiments can be theoretically interpreted by varying the relevant physical parameters. Conditions when dissipative-type instabilities may set in are also discussed.

Alpha-to-beta- and gamma-band activity reflect predictive coding in affective visual processing

Processing of negative affective pictures typically leads to desynchronization of alpha-to-beta frequencies (ERD) and synchronization of gamma frequencies (ERS). Given that in predictive coding higher frequencies have been associated with prediction errors, while lower frequencies have been linked to expectations, we tested the hypothesis that alpha-to-beta ERD and gamma ERS induced by aversive pictures are associated with expectations and prediction errors, respectively. We recorded EEG while volunteers were involved in a probabilistically cued affective picture task using three different negative valences to produce expectations and prediction errors. Our data show that alpha-to-beta band activity after stimulus presentation was related to the expected valence of the stimulus as predicted by a cue. The absolute mismatch of the expected and actual valence, which denotes an absolute prediction error was related to increases in alpha, beta and gamma band activity. This demonstrates that top-down predictions and bottom-up prediction errors are represented in typical spectral patterns associated with affective picture processing. This study provides direct experimental evidence that negative affective picture processing can be described by neuronal predictive coding computations.

Exploration of Physicochemical Parameters of Natural Origin Polymers

Background: Natural polymers are fascinating category of small chain molecules originating for the natural resources, and few examples include Sodium Alginate and Xanthan Gum which are water-soluble in the nature; used for mainly food packaging, biomedical and pharmaceutical applications. In proposed research work, an effort was made to overcome the polymer challenges emerging from the development of polymer blends, as the miscibility between polymers, is a vital aspect. Objective: This work focuses on the miscibility studies of natural origin polymers. In regards to that, Sodium Alginate/ Xanthan Gum blends were prepared in variable concentrations in aqueous medium and it was utilized for viscosity analysis, FTIR, Ultraviolet spectroscopic studies at variable temperatures. Methods: It was observed that the developed, Sodium Alginate / Xanthan Gum blends are miscible with each other at most of the temperatures (at 20°C, 40°C and 60°C) considering their viscosity parameters, FTIR and UV spectral data. Results: Viscosity studies revealed that the miscibility windows of polymeric ratio increases as the temperature increases whereas FTIR spectral patterns exhibited that the composition having 60:40 ratio of polymers exhibits high intensity stretches and represented to be miscible when compared to other combinations. Conclusion: The present study has reported the simple and efficient method in exploration of the miscibility windows of Sodium alginate and Xanthan gum blend.

Preferential Solvation of 4-Carboxyl-2, 6-Dinitrophenylazohydroxynaphthalenes in Mixed Hydroxylic Solvents

Background: The applications of a group of 4-carboxyl-2,6-dintrophenylazohydroxynaphathalenes, AZ-01 to 04, as colourants, chemosensors or synthetic intermediates have been limited by their solubility.Aim: To investigate the effect of solvent mixture composition on the solubility, solution thermodynamics and position of equilibrium processes of the dyes.Method: The UV-visible spectral patterns of the dyes in binary mixtures including Methanol:Water, Ethanol:Water, Methanol:Ethanol, Methanol:Propan-1-ol, Methanol:Propan-2-ol, Propan-1-ol:Water and Propan-2-ol:Water were acquired. The type and quantitative estimation of solute-solvent interactions at play were determined by fitting spectral patterns to solvent parameters using multilinear regression.Results: Preferential solvation was detected by the non-ideality of the plots of E12 as against the mole fractions of co-solvent in all binary mixtures. In pure solvents, the spectral shifts of AZ-01, 03 and 04, which exist predominantly in the hydrazone form, were affected by polarity of solvent milieu while solvent basicity and acidity, in that order, were the significant parameters for AZ-02. In aqueous alcoholic mixtures, solvent polarity was contributory, although to different degrees, to the observed spectral data of the four dyes. However, solvent acidity and basicity were the primary determinants of spectral shifts observed with AZ-04 and AZ-03 respectively. Spectra-structure relationships identified the formation of the charged hydrazone tautomer which requires stabilisation by polar solvent milieu as responsible for the observed trend. In addition, interactions between new aggregated solvent-solvent species and the propionic acid substituent present in AZ-03 contributed to its spectral shifts.Conclusion: The solvatochromic properties of the phenylazonaphthalene series in binary mixtures have been successfully studied.

SCALING UP SAGEBRUSH CHEMISTRY WITH NEAR-INFRARED SPECTROSCOPY AND UAS-ACQUIRED HYPERSPECTRAL IMAGERY

Sagebrush ecosystems (Artemisia spp.) face many threats including large wildfires and conversion to invasive annuals, and thus are the focus of intense restoration efforts across the western United States. Specific attention has been given to restoration of sagebrush systems for threatened herbivores, such as Greater Sage-Grouse (Centrocercus urophasianus) and pygmy rabbits (Brachylagus idahoensis), reliant on sagebrush as forage. Despite this, plant chemistry (e.g., crude protein, monoterpenes and phenolics) is rarely considered during reseeding efforts or when deciding which areas to conserve. Near-infrared spectroscopy (NIRS) has proven effective in predicting plant chemistry under laboratory conditions in a variety of ecosystems, including the sagebrush steppe. Our objectives were to demonstrate the scalability of these models from the laboratory to the field, and in the air with a hyperspectral sensor on an unoccupied aerial system (UAS). Sagebrush leaf samples were collected at a study site in eastern Idaho, USA. Plants were scanned with an ASD FieldSpec 4 spectroradiometer in the field and laboratory, and a subset of the same plants were imaged with a SteadiDrone Hexacopter UAS equipped with a Rikola hyperspectral sensor (HSI). All three sensors generated spectral patterns that were distinct among species and morphotypes of sagebrush at specific wavelengths. Lab-based NIRS was accurate for predicting crude protein and total monoterpenes (R2 = 0.7–0.8), but the same NIRS sensor in the field was unable to predict either crude protein or total monoterpenes (R2 < 0.1). The hyperspectral sensor on the UAS was unable to predict most chemicals (R2 < 0.2), likely due to a combination of too few bands in the Rikola HSI camera (16 bands), the range of wavelengths (500–900 nm), and small sample size of overlapping plants (n = 28–60). These results show both the potential for scaling NIRS from the lab to the field and the challenges in predicting complex plant chemistry with hyperspectral UAS. We conclude with recommendations for next steps in applying UAS to sagebrush ecosystems with a variety of new sensors.

Dynamic variations of resting-state BOLD signal spectra in white matter

Recent studies have demonstrated that the mathematical model used for analyzing and interpreting fMRI data in gray matter (GM) is inappropriate for detecting or describing blood-oxygenation-level-dependent (BOLD) signals in white matter (WM). In particular the hemodynamic response function (HRF) which serves as the regressor in general linear models is different in WM compared to GM. We recently reported measurements of the frequency contents of resting-state time courses in WM that showed distinct power spectra which depended on local structural-vascular-functional associations. In addition, multiple studies of GM have revealed how functional connectivity between regions, as measured by the correlation between BOLD time series, varies dynamically over time. We therefore investigated whether and how BOLD signals from WM in a resting state varied over time. We measured voxel-wise spectrograms, which reflect the time-varying spectral patterns of WM time courses. The results suggest that the spectral patterns are non-stationary but could be categorized into five modes that recurred over time. These modes showed distinct spatial distributions of their occurrences and durations, and the distributions were highly consistent across individuals. In addition, one of the modes exhibited a strong coupling of its occurrence between GM and WM across individuals, and two communities of WM voxels were identified according to the hierarchical structures of transitions among modes. Moreover, the total number of transitions in each community predicts specific human behaviors. Last, these modes are coupled to the shape of instantaneous HRFs. Our findings extend previous studies and reveal the non-stationary nature of spectral patterns of BOLD signals over time, providing a spatial-temporal-frequency characterization of resting-state signals in WM.

Physicochemical Properties of Sago Ozone Oxidation: The Effect of Reaction Time, Acidity, and Concentration of Starch

The disadvantageous properties of sago starch has limited its application in food and industrial processes. The properties of sago starch can be improved by changing its physicochemical and rheological characteristics. This study examined the influence of reaction time, acidity, and starch concentration on the oxidation of sago starch with ozone, a strong oxidant. Swelling, solubility, carbonyl, carboxyl, granule morphology, thermal profile, and functional groups are comprehensively observed parameters. With starch concentrations of 10–30% (v/w) and more prolonged oxidation, sago starch was most soluble at pH 10. The swelling power decreased with a longer reaction time, reaching the lowest pH 10. In contrast, the carbonyl and carboxyl content exhibited the same pattern as solubility. A more alkaline environment tended to create modified starch with more favorable properties. Over time, oxidation shows more significant characteristics, indicating a superb product of this reaction. At the starch concentration of 20%, modified sago starch with the most favorable properties was created. When compared to modified starch, native starch is generally shaped in a more oval and irregular manner. Additionally, native starch and modified starch had similar spectral patterns and identical X-ray diffraction patterns. Meanwhile, oxidized starch had different gelatinization and retrogradation temperatures to those of the native starch.

Alpha-to-beta- and gamma-band activity reflect predictive coding in affective visual processing

Processing of negative affective pictures typically leads to desynchronization of alpha-to-beta frequencies (ERD) and synchronization of gamma frequencies (ERS). Given that in predictive coding higher frequencies have been associated with prediction errors, while lower frequencies have been linked to expectations, we tested the hypothesis that alpha-to-beta ERD and gamma ERS induced by aversive pictures are associated with expectations and prediction errors, respectively. We recorded EEG while volunteers were involved in a probabilistically cued affective picture task using three different negative valences to produce expectations and prediction errors. Our data show that alpha-to-beta band activity was related to the expected valence of the stimulus as predicted by a cue. The absolute mismatch of the expected and actual valence, which denotes an absolute prediction error was related to gamma band activity. This demonstrates that top-down predictions and bottom-up prediction errors are represented in specific spectral patterns associated with affective picture processing.

Synthesis, Characterization, and DFT Studies of N-(3,5-Bis(trifluoromethyl)benzyl)stearamide

The novel N-(3,5-bis(trifluoromethyl)benzyl)stearamide 3 was prepared in moderate yield by a solventless direct amidation reaction of stearic acid 1 with 3,5-bis(trifluoromethyl)benzylamine 2 at 140 °C for 24 h under metal- and catalyst-free conditions. This practical method was conducted in air without any special treatment or activation. The fatty acid amide 3 was fully characterized by IR, UV–Vis, 1D and 2D NMR spectroscopy, mass spectrometry, and elemental analysis. Moreover, molecular electrostatic potential studies, determination of quantum descriptors, fundamental vibrational frequencies, and intensity of vibrational bands were computed by density functional theory (DFT) using the B3LYP method with 6-311+G(d,p) basis set in gas phase. Simulation of the infrared spectrum using the results of these calculations led to good agreement with the observed spectral patterns.