Phase Separation and Magnetic Order in K-doped Iron Selenide Superconductor

Alkali-doped iron selenide is the latest member of high Tc superconductor family, and its peculiar characters have immediately attracted extensive attention. We prepared high-quality potassium-doped iron selenide (KxFe2-ySe2) thin films by molecular beam epitaxy and unambiguously demonstrated the existence of phase separation, which is currently under debate, in this material using scanning tunneling microscopy and spectroscopy. The stoichiometric superconducting phase KFe2Se2 contains no iron vacancies, while the insulating phase has a \surd5\times\surd5 vacancy order. The iron vacancies are shown always destructive to superconductivity in KFe2Se2. Our study on the subgap bound states induced by the iron vacancies further reveals a magnetically-related bipartite order in the superconducting phase. These findings not only solve the existing controversies in the atomic and electronic structures in KxFe2-ySe2, but also provide valuable information on understanding the superconductivity and its interplay with magnetism in iron-based superconductors

Sign-reversal of the in-plane resistivity anisotropy in hole-doped iron pnictides

The in-plane anisotropy of the electrical resistivity across the coupled orthorhombic and magnetic transitions of the iron pnictides has been extensively studied in the parent and electron-doped compounds. All these studies universally show that the resistivity $\rho_{a}$ across the long orthorhombic axis $a_{O}$ - along which the spins couple antiferromagnetically below the magnetic transition temperature - is smaller than the resistivity $\rho_{b}$ of the short orthorhombic axis $b_{O}$, i. e. $\rho_{a}<\rho_{b}$. Here we report that in the hole-doped compounds Ba$_{1-x}$K$_{x}$Fe$_{2}$As$_{2}$, as the doping level increases, the resistivity anisotropy initially becomes vanishingly small, and eventually changes sign for sufficiently large doping, i. e. $\rho_{b}<\rho_{a}$. This observation is in agreement with a recent theoretical prediction that considers the anisotropic scattering of electrons by spin-fluctuations in the orthorhombic/nematic state.Comment: This paper has been replaced by the new version offering new explanation of the experimental results first reported her

Fuzzy Fibers: Uncertainty in dMRI Tractography

Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and rendering probabilistic tractograms, which estimate precision in the face of measurement noise and artifacts. However, we also address aspects that have received less attention so far, such as model selection, partial voluming, and the impact of parameters, both in preprocessing and in fiber tracking itself. We conclude by giving impulses for future research

Local antiferromagnetic exchange and collaborative Fermi surface as key ingredients of high temperature superconductors

Cuprates, ferropnictides and ferrochalcogenides are three classes of unconventional high-temperature superconductors, who share similar phase diagrams in which superconductivity develops after a magnetic order is suppressed, suggesting a strong interplay between superconductivity and magnetism, although the exact picture of this interplay remains elusive. Here we show that there is a direct bridge connecting antiferromagnetic exchange interactions determined in the parent compounds of these materials to the superconducting gap functions observed in the corresponding superconducting materials. High superconducting transition temperature is achieved when the Fermi surface topology matches the form factor of the pairing symmetry favored by local magnetic exchange interactions. Our result offers a principle guide to search for new high temperature superconductors.Comment: 12 pages, 5 figures, 1 table, 1 supplementary materia

Giant Superfluorescent Bursts from a Semiconductor Magnetoplasma

Currently, considerable resurgent interest exists in the concept of superradiance (SR), i.e., accelerated relaxation of excited dipoles due to cooperative spontaneous emission, first proposed by Dicke in 1954. Recent authors have discussed SR in diverse contexts, including cavity quantum electrodynamics, quantum phase transitions, and plasmonics. At the heart of these various experiments lies the coherent coupling of constituent particles to each other via their radiation field that cooperatively governs the dynamics of the whole system. In the most exciting form of SR, called superfluorescence (SF), macroscopic coherence spontaneously builds up out of an initially incoherent ensemble of excited dipoles and then decays abruptly. Here, we demonstrate the emergence of this photon-mediated, cooperative, many-body state in a very unlikely system: an ultradense electron-hole plasma in a semiconductor. We observe intense, delayed pulses, or bursts, of coherent radiation from highly photo-excited semiconductor quantum wells with a concomitant sudden decrease in population from total inversion to zero. Unlike previously reported SF in atomic and molecular systems that occur on nanosecond time scales, these intense SF bursts have picosecond pulse-widths and are delayed in time by tens of picoseconds with respect to the excitation pulse. They appear only at sufficiently high excitation powers and magnetic fields and sufficiently low temperatures - where various interactions causing decoherence are suppressed. We present theoretical simulations based on the relaxation and recombination dynamics of ultrahigh-density electron-hole pairs in a quantizing magnetic field, which successfully capture the salient features of the experimental observations.Comment: 21 pages, 4 figure

Structural analysis of MDM2 RING separates degradation from regulation of p53 transcription activity

MDM2–MDMX complexes bind the p53 tumor-suppressor protein, inhibiting p53's transcriptional activity and targeting p53 for proteasomal degradation. Inhibitors that disrupt binding between p53 and MDM2 efficiently activate a p53 response, but their use in the treatment of cancers that retain wild-type p53 may be limited by on-target toxicities due to p53 activation in normal tissue. Guided by a novel crystal structure of the MDM2–MDMX–E2(UbcH5B)–ubiquitin complex, we designed MDM2 mutants that prevent E2–ubiquitin binding without altering the RING-domain structure. These mutants lack MDM2's E3 activity but retain the ability to limit p53′s transcriptional activity and allow cell proliferation. Cells expressing these mutants respond more quickly to cellular stress than cells expressing wild-type MDM2, but basal p53 control is maintained. Targeting the MDM2 E3-ligase activity could therefore widen the therapeutic window of p53 activation in tumors

Metabolic effects of diets differing in glycaemic index depend on age and endogenous GIP

Aims/hypothesis High- vs low-glycaemic index (GI) diets unfavourably affect body fat mass and metabolic markers in rodents. Different effects of these diets could be age-dependent, as well as mediated, in part, by carbohydrate-induced stimulation of glucose-dependent insulinotrophic polypeptide (GIP) signalling. Methods Young-adult (16 weeks) and aged (44 weeks) male wild-type (C57BL/6J) and GIP-receptor knockout (Gipr −/− ) mice were exposed to otherwise identical high-carbohydrate diets differing only in GI (20–26 weeks of intervention, n = 8–10 per group). Diet-induced changes in body fat distribution, liver fat, locomotor activity, markers of insulin sensitivity and substrate oxidation were investigated, as well as changes in the gene expression of anorexigenic and orexigenic hypothalamic factors related to food intake. Results Body weight significantly increased in young-adult high- vs low-GI fed mice (two-way ANOVA, p < 0.001), regardless of the Gipr genotype. The high-GI diet in young-adult mice also led to significantly increased fat mass and changes in metabolic markers that indicate reduced insulin sensitivity. Even though body fat mass also slightly increased in high- vs low-GI fed aged wild-type mice (p < 0.05), there were no significant changes in body weight and estimated insulin sensitivity in these animals. However, aged Gipr −/− vs wild-type mice on high-GI diet showed significantly lower cumulative net energy intake, increased locomotor activity and improved markers of insulin sensitivity. Conclusions/interpretation The metabolic benefits of a low-GI diet appear to be more pronounced in younger animals, regardless of the Gipr genotype. Inactivation of GIP signalling in aged animals on a high-GI diet, however, could be beneficial

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Muscle-specific overexpression of AdipoR1 or AdipoR2 gives rise to common and discrete local effects whilst AdipoR2 promotes additional systemic effects

Hypoadiponectinemia and adiponectin resistance are implicated in the aetiology of obesity-related cardiometabolic disorders, hence represent a potential therapeutic axis. Here we characterised the effects of in vivo electrotransfer-mediated overexpression of the adiponectin receptors, AdipoR1 or AdipoR2, into tibialis anterior muscle (TAM) of lean or obese mice. In lean mice, TAM-specific overexpression of AdipoR1 (TAMR1) or AdipoR2 (TAMR2) increased phosphorylation of AMPK, AKT and ERK and expression of the insulin responsive glucose transporter glut4. In contrast, only TAMR2 increased pparα and a target gene acox1. These effects were decreased in obese mice despite no reduction in circulating adiponectin levels. TAMR2 also increased expression of adipoQ in TAM of lean and obese mice. Furthermore, in obese mice TAMR2 promoted systemic effects including; decreased weight gain; reduced epididymal fat mass and inflammation; increased epididymal adipoQ expression; increased circulating adiponectin. Collectively, these results demonstrate that AdipoR1 and AdipoR2 exhibit overlapping and distinct effects in skeletal muscle consistent with enhanced adiponectin sensitivity but these appear insufficient to ameliorate established obesity-induced adiponectin resistance. We also identify systemic effects upon TAMR2 in obese mice and postulate these are mediated by altered myokine production. Further studies are warranted to investigate this possibility which may reveal novel therapeutic approaches

A multi-biometric iris recognition system based on a deep learning approach

YesMultimodal biometric systems have been widely applied in many real-world applications due to its ability to deal with a number of significant limitations of unimodal biometric systems, including sensitivity to noise, population coverage, intra-class variability, non-universality, and vulnerability to spoofing. In this paper, an efficient and real-time multimodal biometric system is proposed based on building deep learning representations for images of both the right and left irises of a person, and fusing the results obtained using a ranking-level fusion method. The trained deep learning system proposed is called IrisConvNet whose architecture is based on a combination of Convolutional Neural Network (CNN) and Softmax classifier to extract discriminative features from the input image without any domain knowledge where the input image represents the localized iris region and then classify it into one of N classes. In this work, a discriminative CNN training scheme based on a combination of back-propagation algorithm and mini-batch AdaGrad optimization method is proposed for weights updating and learning rate adaptation, respectively. In addition, other training strategies (e.g., dropout method, data augmentation) are also proposed in order to evaluate different CNN architectures. The performance of the proposed system is tested on three public datasets collected under different conditions: SDUMLA-HMT, CASIA-Iris- V3 Interval and IITD iris databases. The results obtained from the proposed system outperform other state-of-the-art of approaches (e.g., Wavelet transform, Scattering transform, Local Binary Pattern and PCA) by achieving a Rank-1 identification rate of 100% on all the employed databases and a recognition time less than one second per person