Thickness Dependence of Magnetic Blocking in Granular Thin Films with Interacting Magnetic Particles

Interparticle interaction among single domain nanosize magnetic particles embedded in nonmagnetic matrix was studied. Attention was paid to concentrated Cu–Co granular thin films with a fixed magnetic volume fraction (20%). By analyzing theoretical models and comparing with experimental results, a dimensional constraint on the magnetic properties was found. As the film thickness reduces toward the thin limit the interparticle interaction plays important roles in modifying the magnetic behavior. The dipolar interaction energy was calculated among magnetic particles including far-neighbor interaction for films with different thickness values. When magnetization variation is included in the calculation, the resulting calculated interaction energy versus film thickness shows remarkable agreement with the variation of experimental observed peak temperature derived from magnetic blocking curves

Graph Classification Gaussian Processes via Spectral Features

Graph classification aims to categorise graphs based on their structure and node attributes. In this work, we propose to tackle this task using tools from graph signal processing by deriving spectral features, which we then use to design two variants of Gaussian process models for graph classification. The first variant uses spectral features based on the distribution of energy of a node feature signal over the spectrum of the graph. We show that even such a simple approach, having no learned parameters, can yield competitive performance compared to strong neural network and graph kernel baselines. A second, more sophisticated variant is designed to capture multi-scale and localised patterns in the graph by learning spectral graph wavelet filters, obtaining improved performance on synthetic and real-world data sets. Finally, we show that both models produce well calibrated uncertainty estimates, enabling reliable decision making based on the model predictions

Transductive Kernels for Gaussian Processes on Graphs

Kernels on graphs have had limited options for node-level problems. To address this, we present a novel, generalized kernel for graphs with node feature data for semi-supervised learning. The kernel is derived from a regularization framework by treating the graph and feature data as two Hilbert spaces. We also show how numerous kernel-based models on graphs are instances of our design. A kernel defined this way has transductive properties, and this leads to improved ability to learn on fewer training points, as well as better handling of highly non-Euclidean data. We demonstrate these advantages using synthetic data where the distribution of the whole graph can inform the pattern of the labels. Finally, by utilizing a flexible polynomial of the graph Laplacian within the kernel, the model also performed effectively in semi-supervised classification on graphs of various levels of homophily

Markers of Inflammation in Bacterial Diarrhea among Travelers, with a Focus on Enteroaggregative Escherichia coli Pathogenicity

The intestinal inflammatory response of traveler's diarrhea acquired in Goa, India, and Guadalajara, Mexico, was studied. Fecal lactoferrin was found in stool samples in which enteroaggregative Escherichia coli (EAEC), enterotoxigenic E. coli, or Salmonella or Shigella species were isolated, with Shigella-positive cases showing the highest level. Samples from cases of Shigella-associated diarrhea had the highest concentrations of fecal cytokines. Travelers to India who had EAEC-associated diarrhea showed elevated levels of interleukin (IL)-8 (median, 341.15 pg/mL) and IL-1β (median, 749.90 pg/mL). Although 15 travelers to Mexico who had EAEC-associated diarrhea had a median concentration of 0 pg/mL for both IL-8 and IL-1β, 2 had high levels of IL-8 (1853 and 11,786 pg/mL), and 5 showed elevated levels of IL-1β (1-1240 pg/mL). Samples from patients in India who had pathogen-negative diarrhea or from patients in Mexico who had asymptomatic EAEC infection were negative for cytokines. Bacterial pathogens causing traveler's diarrhea commonly produce intestinal inflammation, although a subset of patients with EAEC-associated diarrhea fail to develop an inflammatory respons

Infection by Wolbachia bacteria and its influence on the reproduction of the stored-product psocid, Liposcelis tricolor

Wolbachia are maternally inherited intracellular bacteria that infect a wide range of arthropods and nematodes and are associated with various reproductive abnormalities in their hosts. The infection by Wolbachia of the psocid, Liposcelis tricolor (Psocoptera: Liposcelididae), was investigated using long PCR amplification of the wsp gene that codes for a Wolbachia surface protein. The results showed that L. tricolor was positive for Wolbachia. Phylogenetic analysis showed that the Wolbachia found in L. tricolor was related to the B-group. Wolbachia infection in L. tricolor could be removed through antibiotic treatment. The results of crosses including ♀W+ x ♂ W+, ♀ W− x ♂W+, ♀ W+ x ♂ W−, and ♀W− x ♂ W−, suggested that the removal of Wolbachia resulted in lower egg production by L. tricolor. The mean embryonic mortality of offspring produced by L. tricolor without Wolbachia was significantly higher than that of control

A Case of Successful Treatment of Recurrent Urinary Tract infection By Extended-Spectrum Β-Lactamase Producing

Recurrent urinary tract infections (UTIs) are a challenging clinical entity that can be frustrating for patient and physician alike. Repeated rounds of antibiotics can select for multidrug-resistant organisms, further complicating care. We describe the successful use of fecal microbiota transplantation (FMT) for the treatment of recurrent extended-spectrum β-lactamase (ESBL)-producin

Generalized twisted modules associated to general automorphisms of a vertex operator algebra

We introduce a notion of strongly C^{\times}-graded, or equivalently, C/Z-graded generalized g-twisted V-module associated to an automorphism g, not necessarily of finite order, of a vertex operator algebra. We also introduce a notion of strongly C-graded generalized g-twisted V-module if V admits an additional C-grading compatible with g. Let V=\coprod_{n\in \Z}V_{(n)} be a vertex operator algebra such that V_{(0)}=\C\one and V_{(n)}=0 for n<0 and let u be an element of V of weight 1 such that L(1)u=0. Then the exponential of 2\pi \sqrt{-1} Res_{x} Y(u, x) is an automorphism g_{u} of V. In this case, a strongly C-graded generalized g_{u}-twisted V-module is constructed from a strongly C-graded generalized V-module with a compatible action of g_{u} by modifying the vertex operator map for the generalized V-module using the exponential of the negative-power part of the vertex operator Y(u, x). In particular, we give examples of such generalized twisted modules associated to the exponentials of some screening operators on certain vertex operator algebras related to the triplet W-algebras. An important feature is that we have to work with generalized (twisted) V-modules which are doubly graded by the group C/Z or C and by generalized eigenspaces (not just eigenspaces) for L(0), and the twisted vertex operators in general involve the logarithm of the formal variable.Comment: Final version to appear in Comm. Math. Phys. 38 pages. References on triplet W-algebras added, misprints corrected, and expositions revise

Superconductivity up to 30 K in the vicinity of quantum critical point in BaFe2_{2}(As1−x_{1-x}Px_{x})2_{2}

We report bulk superconductivity induced by an isovalent doping of phosphorus in BaFe$_{2}$(As$_{1-x}$P$_{x}$)$_{2}$. The P-for-As substitution results in shrinkage of lattice, especially for the FeAs block layers. The resistivity anomaly associated with the spin-density-wave (SDW) transition in the undoped compound is gradually suppressed by the P doping. Superconductivity with the maximum $T_c$ of 30 K emerges at $x$=0.32, coinciding with a magnetic quantum critical point (QCP) which is evidenced by the disappearance of SDW order and the linear temperature-dependent resistivity in the normal state. The $T_c$ values were found to decrease with further P doping, and no superconductivity was observed down to 2 K for $x\geq$ 0.77. The appearance of superconductivity in the vicinity of QCP hints to the superconductivity mechanism in iron-based arsenides.Comment: 9 pages, 4 figures; more data; to appear in Journal of Physics: Condensed Matte

Iga-Biome Profiles Correlate With Clinical Parkinson\u27s Disease Subtypes

BACKGROUND: Parkinson\u27s disease is a heterogeneous neurodegenerative disorder with distinctive gut microbiome patterns suggesting that interventions targeting the gut microbiota may prevent, slow, or reverse disease progression and severity. OBJECTIVE: Because secretory IgA (SIgA) plays a key role in shaping the gut microbiota, characterization of the IgA-Biome of individuals classified into either the akinetic rigid (AR) or tremor dominant (TD) Parkinson\u27s disease clinical subtypes was used to further define taxa unique to these distinct clinical phenotypes. METHODS: Flow cytometry was used to separate IgA-coated and -uncoated bacteria from stool samples obtained from AR and TD patients followed by amplification and sequencing of the V4 region of the 16 S rDNA gene on the MiSeq platform (Illumina). RESULTS: IgA-Biome analyses identified significant alpha and beta diversity differences between the Parkinson\u27s disease phenotypes and the Firmicutes/Bacteroides ratio was significantly higher in those with TD compared to those with AR. In addition, discriminant taxa analyses identified a more pro-inflammatory bacterial profile in the IgA+ fraction of those with the AR clinical subclass compared to IgA-Biome analyses of those with the TD subclass and with the taxa identified in the unsorted control samples. CONCLUSION: IgA-Biome analyses underscores the importance of the host immune response in shaping the gut microbiome potentially affecting disease progression and presentation. In the present study, IgA-Biome analyses identified a unique proinflammatory microbial signature in the IgA+ fraction of those with AR that would have otherwise been undetected using conventional microbiome analysis approaches

Iga-Biome Profiles Correlate With Clinical Parkinson\u27s Disease Subtypes

BACKGROUND: Parkinson\u27s disease is a heterogeneous neurodegenerative disorder with distinctive gut microbiome patterns suggesting that interventions targeting the gut microbiota may prevent, slow, or reverse disease progression and severity. OBJECTIVE: Because secretory IgA (SIgA) plays a key role in shaping the gut microbiota, characterization of the IgA-Biome of individuals classified into either the akinetic rigid (AR) or tremor dominant (TD) Parkinson\u27s disease clinical subtypes was used to further define taxa unique to these distinct clinical phenotypes. METHODS: Flow cytometry was used to separate IgA-coated and -uncoated bacteria from stool samples obtained from AR and TD patients followed by amplification and sequencing of the V4 region of the 16 S rDNA gene on the MiSeq platform (Illumina). RESULTS: IgA-Biome analyses identified significant alpha and beta diversity differences between the Parkinson\u27s disease phenotypes and the Firmicutes/Bacteroides ratio was significantly higher in those with TD compared to those with AR. In addition, discriminant taxa analyses identified a more pro-inflammatory bacterial profile in the IgA+ fraction of those with the AR clinical subclass compared to IgA-Biome analyses of those with the TD subclass and with the taxa identified in the unsorted control samples. CONCLUSION: IgA-Biome analyses underscores the importance of the host immune response in shaping the gut microbiome potentially affecting disease progression and presentation. In the present study, IgA-Biome analyses identified a unique proinflammatory microbial signature in the IgA+ fraction of those with AR that would have otherwise been undetected using conventional microbiome analysis approaches