Large two-level magnetoresistance effect in doped manganite grain boundary junctions

We performed a systematic analysis of the tunneling magnetoresistance (TMR) effect in single grain boundary junctions formed in epitaxial La(2/3)Ca(1/3)MnO(3) films deposited on SrTiO(3) bicrystals. For magnetic fields H applied parallel to the grain boundary barrier, an ideal two-level resistance switching behavior with sharp transitions is observed with a TMR effect of up to 300% at 4.2 K and still above 100% at 77 K. Varying the angle between H and the grain boundary results in differently shaped resistance vs H curves. The observed behavior is explained within a model of magnetic domain pinning at the grain boundary interface.Comment: 4 pages, 3 figures, to appear in Phys. Rev. B (Rapid Comm.

A model for spin-polarized transport in perovskite manganite bi-crystal grain boundaries

We have studied the temperature dependence of low-field magnetoresistance and current-voltage characteristics of a low-angle bi-crystal grain boundary junction in perovskite manganite La_{2/3}Sr_{1/3}MnO_3 thin film. By gradually trimming the junction we have been able to reveal the non-linear behavior of the latter. With the use of the relation M_{GB} \propto M_{bulk}\sqrt{MR^*} we have extracted the grain boundary magnetization. Further, we demonstrate that the built-in potential barrier of the grain boundary can be modelled by V_{bi}\propto M_{bulk}^2 - M_{GB}^2. Thus our model connects the magnetoresistance with the potential barrier at the grain boundary region. The results indicate that the band-bending at the grain boundary interface has a magnetic origin.Comment: 9 pages, 5 figure

Low frequency 1/f noise in doped manganite grain-boundary junctions

We have performed a systematic analysis of the low frequency 1/f-noise in single grain boundary junctions in the colossal magnetoresistance material La_{2/3}Ca_{1/3}MnO_{3-delta}. The grain boundary junctions were formed in epitaxial La_{2/3}Ca_{1/3}MnO_{3-delta} films deposited on SrTiO_3 bicrystal substrates and show a large tunneling magnetoresistance of up to 300% at 4.2 K as well as ideal, rectangular shaped resistance versus applied magnetic field curves. Below the Curie temperature T_C the measured 1/f noise is dominated by the grain boundary. The dependence of the noise on bias current, temperature and applied magnetic field gives clear evidence that the large amount of low frequency noise is caused by localized sites with fluctuating magnetic moments in a heavily disordered grain boundary region. At 4.2 K additional temporally unstable Lorentzian components show up in the noise spectra that are most likely caused by fluctuating clusters of interacting magnetic moments. Noise due to fluctuating domains in the junction electrodes is found to play no significant role.Comment: 9 pages, 7 figure

A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images

Oral cancer incidence is rapidly increasing worldwide. The most important determinant factor in cancer survival is early diagnosis. To facilitate large scale screening, we propose a fully automated pipeline for oral cancer detection on whole slide cytology images. The pipeline consists of fully convolutional regression-based nucleus detection, followed by per-cell focus selection, and CNN based classification. Our novel focus selection step provides fast per-cell focus decisions at human-level accuracy. We demonstrate that the pipeline provides efficient cancer classification of whole slide cytology images, improving over previous results both in terms of accuracy and feasibility. The complete source code is available at https://github.com/MIDA-group/OralScreen.Comment: Accepted to ICIAR 202

Extrinsic Magnetotransport Phenomena in Ferromagnetic Oxides

This review is focused on extrinsic magnetotransport effects in ferromagnetic oxides. It consists of two parts; the second part is devoted to an overview of experimental data and theoretical models for extrinsic magnetotransport phenomena. Here a critical discussion of domain-wall scattering is given. Results on surfacial and interfacial magnetism in oxides are presented. Spin-polarized tunnelling in ferromagnetic junctions is reviewed and grain-boundary magnetoresistance is interpreted within a model of spin-polarized tunnelling through natural oxide barriers. The situation in ferromagnetic oxides is compared with data and models for conventional ferromagnets. The first part of the review summarizes basic material properties, especially data on the spin-polarization and evidence for half-metallicity. Furthermore, intrinsic conduction mechanisms are discussed. An outlook on the further development of oxide spin-electronics concludes this review.Comment: 133 pages, 47 figures, submitted to Rep. Prog. Phy

Automated density-based counting of FISH amplification signals for HER2 status assessment

Background: Automated image analysis can make quantification of FISH signals in histological sections more efficient and reproducible. Current detection-based methods, however, often fail to accurately quantify densely clustered FISH signals. Methods: We propose a novel density-based approach to quantifying FISH signals. Instead of detecting individual signals, this approach quantifies FISH signals in terms of the integral over a density map predicted by Deep Learning. We apply the density-based approach to the task of counting and determining ratios of ERBB2 and CEN17 signals and compare it to common detection-based and area-based approaches. Results: The ratios determined by our approach were strongly correlated with results obtained by manual annotation of individual FISH signals (Pearson's r = 0.907). In addition, they were highly consistent with cutoff-scores determined by a pathologist (balanced concordance = 0.971). The density-based approach generally outperformed the other approaches. Its superiority was particularly evident in the presence of dense signal clusters. Conclusions: The presented approach enables accurate and efficient automated quantification of FISH signals. Since signals in clusters can hardly be detected individually even by human observers, the density-based quantification performs better than detection-based approaches

Engineering mesoscale structures with distinct dynamical implications

The dynamics of networks of interacting systems depends intricately on the interaction topology. When the dynamics is explored, generally the whole topology has to be considered. However, here we show that there are certain mesoscale subgraphs that have precise and distinct consequences for the system-level dynamics. In particular, if mesoscale symmetries are present then eigenvectors of the Jacobian localize on the symmetric subgraph and the corresponding eigenvalues become insensitive to the topology outside the subgraph. Hence, dynamical instabilities associated with these eigenvalues can be analysed without considering the topology of the embedding network. While such instabilities are thus generated entirely in small subgraphs, they generally do not remain confined to the subgraph once the instability sets in and thus have system-level consequences. Here we illustrate the analytical investigation of such instabilities in an ecological metapopulation model consisting of a network of delay-coupled delay oscillators.</p