Anomalous Hall effect in the noncollinear antiferromagnet Mn5Si3

Metallic antiferromagnets with noncollinear orientation of magnetic moments provide a playground for investigating spin-dependent transport properties by analysis of the anomalous Hall effect. The intermetallic compound Mn5Si3 is an intinerant antiferromagnet with collinear and noncollinear magnetic structures due to Mn atoms on two inequivalent lattice sites. Here, magnetotransport measurements on polycrystalline thin films and a single crystal are reported. In all samples, an additional contribution to the anomalous Hall effect attributed to the noncollinear arrangment of magnetic moments is observed. Furthermore, an additional magnetic phase between the noncollinear and collinear regimes above a metamagnetic transition is resolved in the single crystal by the anomalous Hall effect.Comment: 7 pages, 4 figure

Anomalous Hall effect in the noncollinear antiferromagnet Mn5Si3

Metallic antiferromagnets with noncollinear orientation of magnetic moments provide a playground for investigating spin-dependent transport properties by analysis of the anomalous Hall effect. The intermetallic compound Mn5Si3 is an intinerant antiferromagnet with collinear and noncollinear magnetic structures due to Mn atoms on two inequivalent lattice sites. Here, magnetotransport measurements on polycrstalline thin films and a single crystal are reported. In all samples, an additional contribution to the anomalous Hall effect attributed to the noncollinear arrangment of magnetic moments is observed. Furthermore, an additional magnetic phase between the noncollinear and collinear regimes above a metamagnetic transition is resolved in the single crystal by the anomalous Hall effect

Assessment of accuracy of an artificial intelligence algorithm to detect melanoma in images of skin lesions

A high proportion of suspicious pigmented skin lesions referred for investigation are benign. Techniques to improve the accuracy of melanoma diagnoses throughout the patient pathway are needed to reduce the pressure on secondary care and pathology services

Switching of a large anomalous Hall effect between metamagnetic phases of a non-collinear antiferromagnet

The anomalous Hall effect (AHE), which in long-range ordered ferromagnets appears as a voltage transverse to the current and usually is proportional to the magnetization, often is believed to be of negligible size in antiferromagnets due to their low uniform magnetization. However, recent experiments and theory have demonstrated that certain antiferromagnets with a non-collinear arrangement of magnetic moments exhibit a sizeable spontaneous AHE at zero field due to a non-vanishing Berry curvature arising from the quantum mechanical phase of the electron’s wave functions. Here we show that antiferromagnetic Mn5Si3 single crystals exibit a large AHE which is strongly anisotropic and shows multiple transitions with sign changes at different magnetic fields due to field-induced rearrangements of the magnetic structure despite only tiny variations of the total magnetization. The presence of multiple non-collinear magnetic phases offers the unique possiblity to explore the details of the AHE and the sensitivity of the Hall effect on the details of the magnetic texture

Switching of a large anomalous Hall effect between metamagnetic phases of a non-collinear antiferromagnet

The anomalous Hall effect (AHE), which in long-range ordered ferromagnets appears as a voltage transverse to the current and usually is proportional to the magnetization, often is believed to be of negligible size in antiferromagnets due to their low uniform magnetization. However, recent experiments and theory have demonstrated that certain antiferromagnets with a non-collinear arrangement of magnetic moments exhibit a sizeable spontaneous AHE at zero field due to a non-vanishing Berry curvature arising from the quantum mechanical phase of the electron’s wave functions. Here we show that antiferromagnetic Mn5Si3 single crystals exibit a large AHE which is strongly anisotropic and shows multiple transitions with sign changes at different magnetic fields due to field-induced rearrangements of the magnetic structure despite only tiny variations of the total magnetization. The presence of multiple non-collinear magnetic phases offers the unique possiblity to explore the details of the AHE and the sensitivity of the Hall effect on the details of the magnetic texture

Strategien für die Melissezüchtung (Melissa officinalis)

Es wurden 120 Melisseherkünfte in Feldversuchen evaluiert. In diesem Material wurde die Variabilität für Winterhärte, Gehalt und Zsammensetzung des ätherischen Öls, Rosmarinsäuregehalt und eingeschränkt Blattertrag beschrieben. Die beschriebene Variabilität ermöglichte die Entwicklung homozygoter Linien mit hoher Eigenleistung für die genannten Zuchtziele bis zur I4-Inzuchtgeneration. Die Kreuzung definierter Linien ermöglichte die Schaffung eines neuen Genpools als Ausgansmaterial für die Entwicklung weiterer aussichtsreicher Linien. Stichwörter: Melisse, Melissa officinalis L., Winterhärte, ätherisches Öl, Rosmarinsäure, ZüchtungBreeding strategies for lemon balm (Melissa officinalis)Evaluation was carried out in field experiments with 120 accessions of lemon balm. This material was characterized for winter hardiness, amount and composition of essential oil, amount of rosmarinic acid and, to a certain degree, for yield of leaves. The characterized variability opened the possibility to develop homozygous lines for the mentioned breeding goals up to inbreed generation I4. Crossing of defined lines created a new gene pool of basic material for development of new promising lines. Keywords: lemon balm, Melissa officinalis L., winter hardiness, essential oil, rosmarinic acid, breedin

Maximum Entropy Reconstructions of Dynamic Signaling Networks from Quantitative Proteomics Data

Advances in mass spectrometry among other technologies have allowed for quantitative, reproducible, proteome-wide measurements of levels of phosphorylation as signals propagate through complex networks in response to external stimuli under different conditions. However, computational approaches to infer elements of the signaling network strictly from the quantitative aspects of proteomics data are not well established. We considered a method using the principle of maximum entropy to infer a network of interacting phosphotyrosine sites from pairwise correlations in a mass spectrometry data set and derive a phosphorylation-dependent interaction network solely from quantitative proteomics data. We first investigated the applicability of this approach by using a simulation of a model biochemical signaling network whose dynamics are governed by a large set of coupled differential equations. We found that in a simulated signaling system, the method detects interactions with significant accuracy. We then analyzed a growth factor mediated signaling network in a human mammary epithelial cell line that we inferred from mass spectrometry data and observe a biologically interpretable, small-world structure of signaling nodes, as well as a catalog of predictions regarding the interactions among previously uncharacterized phosphotyrosine sites. For example, the calculation places a recently identified tumor suppressor pathway through ARHGEF7 and Scribble, in the context of growth factor signaling. Our findings suggest that maximum entropy derived network models are an important tool for interpreting quantitative proteomics data

Data-driven Soft Sensors in the Process Industry

In the last two decades Soft Sensors established themselves as a valuable alternative to the traditional means for the acquisition of critical process variables, process monitoring and other tasks which are related to process control. This paper discusses characteristics of the process industry data which are critical for the development of data-driven Soft Sensors. These characteristics are common to a large number of process industry fields, like the chemical industry, bioprocess industry, steel industry, etc. The focus of this work is put on the data-driven Soft Sensors because of their growing popularity, already demonstrated usefulness and huge, though yet not completely realised, potential. A comprehensive selection of case studies covering the three most important Soft Sensor application fields, a general introduction to the most popular Soft Sensor modelling techniques as well as a discussion of some open issues in the Soft Sensor development and maintenance and their possible solutions are the main contributions of this work