N-(Quinolin-8-yl)quinoline-2-carbox­amide

In the title compound, C19H13N3O, the dihedral angle between the two quinoline systems is 11.54 (3)°. The mol­ecular conformation is stabilized by intra­molecular N—H⋯N and C—H⋯O hydrogen bonds, with N—H⋯N being bifurcated towards the two N atoms of the two quinoline rings. In the crystal, there are weak intermolecular π–π inter­actions present involving the quinoline rings [centroid–centroid distance 3.7351 (14) Å]

Tetra-n-butyl­ammonium tricyanido[N-(2-pyridyl­carbon­yl)pyridine-2-carbox­imidato]ferrate(III) dihydrate

In the title compound, (C16H36N)[Fe(C12H8N3O2)(CN)3]·2H2O, the tetra-n-butyl­ammonium ion has a tetra­hedral configuration around the N atom, while the FeIII atom of the tricyanido[N-(2-pyridyl­carbon­yl)pyridine-2-carboximidato]iron(III) anion adopts a distorted octa­hedral geometry. O—H⋯O and O—H⋯N hydrogen bonds link the components in the crystal structure

Type-I superconductivity in Al6_6Re

While the pure elements tend to exhibit Type-I rather than Type-II superconductivity, nearly all compound superconductors are Type-II, with only a few known exceptions. We report single crystal growth and physical characterization of the rhenium aluminide Al$_6$Re, which we conclude is a Type-I superconductor based on magnetization, ac-susceptibility, and specific-heat measurements. This detection of superconductivity, despite the strong similarity of Al$_6$Re to a family of W and Mo aluminides that do not superconduct, suggests that these aluminides are an ideal testbed for identifying the relative importance of valence electron count and inversion symmetry in determining whether a material will superconduct.Comment: 9 pages, 7 figures, CIF file as ancillar

High Levels of 17 β

Purpose. To determine the serum levels of sex steroids and tear matrix metalloproteinases (MMP) 2 and 9 concentrations in postmenopausal women with dry eye. Methods. Forty-four postmenopausal women with dry eye and 22 asymptomatic controls were enrolled. Blood was drawn and analyzed for serum levels of sex steroids and lipids. Then, the following tests were performed: tear collection, Ocular Surface Disease Index (OSDI) questionnaire, fluorescein tear film break-up time (TBUT), corneal fluorescein staining, Schirmer test, and conjunctival impression cytology. The conjunctival mRNA expression and tear concentrations of MMP-2 and MMP-9 were measured. Results. Serum 17β-estradiol levels were significantly higher in the dry eye subjects than in the controls (P=0.03), whereas there were no significant differences in levels of testosterone, dehydroepiandrosterone sulfate (DHEA-S), and progesterone. Tear MMP-2 and MMP-9 concentrations (P<0.001), as well as the MMP-9 mRNA expression in conjunctival samples (P=0.02), were significantly higher in dry eye subjects than in controls. Serum 17β-estradiol levels were positively correlated with tear MMP-2 and MMP-9 concentrations and negatively correlated with Schirmer test values. Conclusions. High levels of 17β-estradiol are associated with increased matrix metalloproteinase-2 and metalloproteinase-9 activity in tears of postmenopausal women with dry eye

Solvothermal synthesis of ternary sulfides of Sb2_xBixS3 (x=0.4,1) with 3D flower-like architectures

Flower-like nanostructures of Sb2 − xBixS3(x = 0.4, 1.0) were successfully prepared using both antimony diethyldithiocarbamate [Sb(DDTC)3] and bismuth diethyldithiocarbamate [Bi(DDTC)3] as precursors under solvothermal conditions at 180 °C. The prepared Sb2 − xBixS3 with flower-like 3D architectures were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectrometry (EDS), high-resolution transmission electron microscopy (HRTEM), and selected area electron diffraction (SAED). The flower-like architectures, with an average diameter of ~4 μm, were composed of single-crystalline nanorods with orthorhombic structures. The optical absorption properties of the Sb2 − xBixS3 nanostructures were investigated by UV–Visible spectroscopy, and the results indicate that the Sb2 − xBixS3 compounds are semiconducting with direct band gaps of 1.32 and 1.30 eV for x = 0.4 and 1.0, respectively. On the basis of the experimental results, a possible growth mechanism for the flower-like Sb2 − xBixS3 nanostructures is suggested

High-topological-number skyrmions and phase transition in two-dimensional frustrated J1J_1-J2J_2 magnets

With the rapidly expanded field of two-dimensional(2D) magnetic materials, the frustrated magnetic skyrmions are attracting growing interest recently. Here, based on hexagonal close-packed (HCP) lattice of $J_1$-$J_2$ Heisenberg spins model, we systematically investigate the frustrated skyrmions and phase transition by micromagnetic simulations and first-principles calculations. The results show that four spin phases of antiferromagnetic, labyrinth domain, skyrmion and ferromagnetic textures are determined by the identified ranges of $J_1$-$J_2$. Importantly, skyrmion phase with an increasing topological number ($Q$) covers a wider $J_1$-$J_2$ area. Then, the diameter of skyrmions can be tuned by the frustration strength ($|J_2/J_1|$) or external magnetic field. Besides, a phase transition from N$\acute{e}$el to Bloch type skyrmion is observed due to the change of the helicity with the variation of $|J_2/J_1|$. Furthermore, as increasing magnetic field, the skyrmions with high $Q$ ($\ge 3$) tend to split into the ones with $Q=1$, thereby achieving a lower systematic energy. Additionally, we find that the CoCl$_2$ monolayer satisfies the requirement of the frustrated $J_1$-$J_2$ magnet, and the related magnetic behaviors agree with the above conclusions. The frustration-induced skyrmions are stable without the manipulation of temperature and magnetic field. Our results may open a possible way toward spintronic applications based on High-topological-number and nanoscale topological spin textures of skyrmions.Comment: 7 pages, 5 figure

In vivo MRI based prostate cancer localization with random forests and auto-context model

Prostate cancer is one of the major causes of cancer death for men. Magnetic resonance (MR) imaging is being increasingly used as an important modality to localize prostate cancer. Therefore, localizing prostate cancer in MRI with automated detection methods has become an active area of research. Many methods have been proposed for this task. However, most of previous methods focused on identifying cancer only in the peripheral zone (PZ), or classifying suspicious cancer ROIs into benign tissue and cancer tissue. Few works have been done on developing a fully automatic method for cancer localization in the entire prostate region, including central gland (CG) and transition zone (TZ). In this paper, we propose a novel learning-based multi-source integration framework to directly localize prostate cancer regions from in vivo MRI. We employ random forests to effectively integrate features from multi-source images together for cancer localization. Here, multi-source images include initially the multi-parametric MRIs (i.e., T2, DWI, and dADC) and later also the iteratively-estimated and refined tissue probability map of prostate cancer. Experimental results on 26 real patient data show that our method can accurately localize cancerous sections. The higher section-based evaluation (SBE), combined with the ROC analysis result of individual patients, shows that the proposed method is promising for in vivo MRI based prostate cancer localization, which can be used for guiding prostate biopsy, targeting the tumor in focal therapy planning, triage and follow-up of patients with active surveillance, as well as the decision making in treatment selection. The common ROC analysis with the AUC value of 0.832 and also the ROI-based ROC analysis with the AUC value of 0.883 both illustrate the effectiveness of our proposed method

Scaling of global input–output networks

Examining scaling patterns of networks can help understand how structural features relate to the behavior of the networks. Input–output networks consist of industries as nodes and inter-industrial exchanges of products as links. Previous studies consider limited measures for node strengths and link weights, and also ignore the impact of dataset choice. We consider a comprehensive set of indicators in this study that are important in economic analysis, and also examine the impact of dataset choice, by studying input–output networks in individual countries and the entire world. Results show that Burr, Log-Logistic, Log-normal, and Weibull distributions can better describe scaling patterns of global input–output networks. We also find that dataset choice has limited impacts on the observed scaling patterns. Our findings can help examine the quality of economic statistics, estimate missing data in economic statistics, and identify key nodes and links in input–output networks to support economic policymaking