Electromagnons and instabilities in magnetoelectric materials with non-collinear spin orders

We show that strong electromagnon peaks can be found in absorption spectra of non-collinear magnets exhibiting a linear magnetoelectric effect. The frequencies of these peaks coincide with the frequencies of antiferromagnetic resonances and the ratio of the spectral weights of the electromagnon and antiferromagnetic resonance is related to the ratio of the static magnetoelectric constant and magnetic susceptibility. Using a Kagome lattice antiferromagnet as an example, we show that frustration of spin ordering gives rise to magnetoelastic instabilities at strong spin-lattice coupling, which transform a non-collinear magnetoelectric spin state into a collinear multiferroic state with a spontaneous electric polarization and magnetization. The Kagome lattice antiferromagnet also shows a ferroelectric incommensurate-spiral phase, where polarization is induced by the exchange striction mechanism.Comment: 9 pages, 4 figure

Garuda 5 (khyung lnga): Ecologies of Potency and the Poison-Medicine Spectrum of Sowa Rigpa’s Renowned ‘Black Aconite’ Formula

This article focuses on ethnographic work conducted at the Men-Tsee-Khang (Dharamsala, India) on Garuda 5 (khyung lnga), a commonly prescribed Tibetan medical formula. This medicine’s efficacy as a painkiller and activity against infection and inflammation is largely due to a particularly powerful plant, known as ‘virulent poison’ (btsan dug) as well as ‘the great medicine’ (sman chen), and identified as a subset of Aconitum species. Its effects, however, are potentially dangerous or even deadly. How can these poisonous plants be used in medicine and, conversely, when does a medicine become a poison? How can ostensibly the same substance be both harmful and helpful? The explanation requires a more nuanced picture than mere dose dependency. Attending to the broader ‘ecologies of potency’ in which these substances are locally enmeshed, in line with Sienna Craig’s Efficacy and the Social Ecologies of Tibetan Medicine (2012), provides fertile ground to better understand the effects of Garuda 5 and how potency is developed and directed in practice. I aim to unpack the spectrum between sman (medicine) and dug (poison) in Sowa Rigpa by elucidating some of the multiple dimensions which determine the activity of Garuda 5 as it is formulated and prescribed in India. I thus embrace the full spectrum of potency— the ‘good’ and the ‘bad,’ the ‘wanted’ and the ‘unwanted’—without presuming the universal validity of biomedical notions of toxicity and side effects

Recognition and reconstruction of coherent energy with application to deep seismic reflection data

Reflections in deep seismic reflection data tend to be visible on only a limited number of traces in a common midpoint gather. To prevent stack degeneration, any noncoherent reflection energy has to be removed. In this paper, a standard classification technique in remote sensing is presented to enhance data quality. It consists of a recognition technique to detect and extract coherent energy in both common shot gathers and fi- nal stacks. This technique uses the statistics of a picked seismic phase to obtain the likelihood distribution of its presence. Multiplication of this likelihood distribution with the original data results in a “cleaned up” section. Application of the technique to data from a deep seismic reflection experiment enhanced the visibility of all reflectors considerably. Because the recognition technique cannot produce an estimate of “missing” data, it is extended with a reconstruction method. Two methods are proposed: application of semblance weighted local slant stacks after recognition, and direct recognition in the linear tau-p domain. In both cases, the power of the stacking process to increase the signal-to-noise ratio is combined with the direct selection of only specific seismic phases. The joint application of recognition and reconstruction resulted in data images which showed reflectors more clearly than application of a single technique

Identification of black hole power spectral components across all canonical states

From a uniform analysis of a large (8.5 Ms) Rossi X-ray Timing Explorer data set of Low Mass X-ray Binaries, we present a complete identification of all the variability components in the power spectra of black holes in their canonical states. It is based on gradual frequency shifts of the components observed between states, and uses a previous identification in the black hole low hard state as a starting point. It is supported by correlations between the frequencies in agreement with those previously found to hold for black hole and neutron stars. Similar variability components are observed in neutron stars and black holes (only the component observed at the highest frequencies is different) which therefore cannot depend on source-specific characteristics such as the magnetic field or surface of the neutron star or spin of the black hole. As the same variability components are also observed across the jet-line the X-ray variability cannot originate from the outer-jet but is most likely produced in either the disk or the corona. We use the identification to directly compare the difference in strength of the black hole and neutron star variability and find these can be attributed to differences in frequency and strength of high frequency features, and do not require the absence of any components. Black holes attain their highest frequencies (in the hard-intermediate and very-high states) at a level a factor ~6 below the highest frequencies attained by the corresponding neutron star components, which can be related to the mass difference between the compact objects in these systems.Comment: 17 pages, 16 figures, accepted for publication in Ap

Iron(III)-chelating resins X. Iron detoxification of human plasma with iron(III)-chelating resins

Iron detoxification of human blood plasma was studied with resins containing desferrioxamine B (DFO) or 3-hydroxy-2-methyl-4(1H)-pyridinone (HMP) as iron(III)-chelating groups. The behaviour of four resins was investigated: DFO-Sepharose, HMP-Sepharose and crosslinked copolymers of 1-(ß-acrylamidoethyl)-3-hydroxy-2-methyl-4(1H)-pyridinone (AHMP) with 2-hydroxyethyl methacrylate (HEMA) and of AHMP with N,N-dimethylacrylamide (DMAA). The efficiency of iron detoxification of plasma of the resins was mainly dependent on the affinity of the ligands and the hydrophilicity of the resins. The results of a stability study in phosphate-buffered saline at a physiological pH indicated that AHMP-DMAA was the most stable resin, whereas the Sepharose gels had a relatively lower stability. Experiments with the AHMP-DMAA resin showed that the resin was able to remove iron from plasma with different iron contents, and from plasma poisoned with FeCl3, iron(III) citrate or transferrin. A rapid removal from free serum iron was observed, whereas iron from transferrin was removed slowly afterwards. Only the overload iron was removed since in all cases the normal serum iron level of ca. 1 ppm was obtained

Normal mere exposure effect with impaired recognition in Alzheimer’s disease.

We investigated the mere exposure effect and the explicit memory in Alzheimer’s disease (AD) patients and elderly control subjects, using unfamiliar faces. During the exposure phase, the subjects estimated the age of briefly flashed faces. The mere exposure effect was examined by presenting pairs of faces (old and new) and asking participants to select the face they liked. The participants were then presented with a forced-choice explicit recognition task. Controls subjects exhibited above-chance preference and recognition scores for old faces. The AD patients also showed the mere exposure effect but no explicit recognition. These results suggest that the processes involved in the mere exposure effect are preserved in AD patients despite their impaired explicit recognition. The results are discussed in terms of Seamon et al.’s proposal (1995) that processes involved in the mere exposure effect are equivalent to those subserving perceptual priming. These processes would depend on extrastriate areas which are relatively preserved in AD patients

Introduction | Approaching Potent Substances in Medicine and Ritual across Asia

Introduction to themed research articles on Approaching Potent Substances in Medicine and Ritual across Asia

Towards an Integrative Formative Approach of Data-Driven Decision Making, Assessment for Learning, and Diagnostic Testing

This study concerns the comparison of three approaches to assessment: Data-Driven Decision Making, Assessment for Learning, and Diagnostic Testing. Although the three approaches claim to be beneficial with regard to student learning, no clear study into the relationships and distinctions between these approaches exists to date. The goal of this study was to investigate the extent to which the three approaches can be shaped into an integrative formative approach towards assessment. The three approaches were compared on nine characteristics of assessment. The results suggest that although the approaches seem to be contradictory with respect to some characteristics, it is argued that they could complement each other despite these differences. The researchers discuss how the three approaches can be shaped into an integrative formative approach towards assessmen

Artificial neural networks as a multivariate calibration tool: modelling the Fe-Cr-Ni system in X-ray fluorescence spectroscopy

The performance of artificial neural networks (ANNs) for modeling the Cr---Ni---Fe system in quantitative x-ray fluorescence spectroscopy was compared with the classical Rasberry-Heinrich model and a previously published method applying the linear learning machine in combination with singular value decomposition. Apart from determining if ANNs were capable of modeling the desired non-linear relationships, also the effects of using non-ideal and noisy data were studied. For this goal, more than a hundred steel samples with large variations in composition were measured at their primary and secondary K¿ and Kß lines. The optimal calibration parameters for the Rasberry-Heinrich model were found from this dataset by use of a genetic algorithm. ANNs were found to be robust and to perform generally better than the other two methods in calibrating over large ranges

Modelling the permeability of polymers: a neural network approach

In this short communication, the prediction of the permeability of carbon dioxide through different polymers using a neural network is studied. A neural network is a numeric-mathematical construction that can model complex non-linear relationships. Here it is used to correlate the IR spectrum of a polymer to its permeability. The underlying assumption is that the chemical information hidden in the IR spectrum is sufficient for the prediction. The best neural network investigated so far does indeed show predictive capabilities