The Triaxial Rotation Vibration Model in the Xe-Ba Region

The axial Rotation Vibration Model is here extended to describe also triaxial equilibrium shapes with beta and gamma vibrations allowing for the interaction between vibrations and rotations. This Triaxial Rotation Vibration Model (TRVM) is applied to Xe and Ba isotopes with mass numbers between 120 and 130. This area has recently been pointed out to be the O(6) limit of the Interacting Boson Approximation (IBA). The present work shows that the TRVM can equally well describe these nuclei concerning their excitation energies and E2 branching ratios.Comment: 11 pages, 2 figure

Topological descriptors for 3D surface analysis

We investigate topological descriptors for 3D surface analysis, i.e. the classification of surfaces according to their geometric fine structure. On a dataset of high-resolution 3D surface reconstructions we compute persistence diagrams for a 2D cubical filtration. In the next step we investigate different topological descriptors and measure their ability to discriminate structurally different 3D surface patches. We evaluate their sensitivity to different parameters and compare the performance of the resulting topological descriptors to alternative (non-topological) descriptors. We present a comprehensive evaluation that shows that topological descriptors are (i) robust, (ii) yield state-of-the-art performance for the task of 3D surface analysis and (iii) improve classification performance when combined with non-topological descriptors.Comment: 12 pages, 3 figures, CTIC 201

Description of even-even triaxial Nuclei within the Coherent State and the Triaxial Rotation-Vibration Models

The coherent state model (CSM) and the triaxial rotation-vibration model (TRVM) are alternatively used to describe the ground, gamma and beta bands of 228Th. CSM is also applied to the nuclei 126Xe and 130Ba, which were recently considered in TRVM. The two models are compared with respect to both their underlying assumptions and to their predicted results for energy levels and E2 branching ratios. Both models describe energies and quadrupole transitions of 228Th equally well and in good agreement with experiment, if the 0$_3^+$ level at 1120 keV is interpreted as the head of the beta band. The other two 0$^+$ levels at 832 and 939 keV are most likely not of a pure quadrupole vibration nature as has already been pointed out in the literature.Comment: 31 pages, RevTeX, 6 figure

Performance Evaluation of Manifold Algorithms on a P300 Paradigm Based Online BCI Dataset

Healthcare field is highly benefited by incorporating BCI for detection and diagnosis of some health related detriment as well as rehabilitation and restoration of certain disabilities. An EEG dataset acquired from 15 high-functioning ASD patients, while they were undergoing a P300 experiment in a virtual reality platform, was analysed in this paper using three algorithms. Performance of Bayes Linear Discriminant Analysis (BLDA) was predominant over Convolutional Neural Network (CNN) and Random Undersampling (RUS) Boosting. BLDA rendered 73% overall accuracy in predicting target and the best accuracy for each subject using CNN or BLDA yielded an overall accuracy of 76%

Software defect prediction: do different classifiers find the same defects?

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.During the last 10 years, hundreds of different defect prediction models have been published. The performance of the classifiers used in these models is reported to be similar with models rarely performing above the predictive performance ceiling of about 80% recall. We investigate the individual defects that four classifiers predict and analyse the level of prediction uncertainty produced by these classifiers. We perform a sensitivity analysis to compare the performance of Random Forest, Naïve Bayes, RPart and SVM classifiers when predicting defects in NASA, open source and commercial datasets. The defect predictions that each classifier makes is captured in a confusion matrix and the prediction uncertainty of each classifier is compared. Despite similar predictive performance values for these four classifiers, each detects different sets of defects. Some classifiers are more consistent in predicting defects than others. Our results confirm that a unique subset of defects can be detected by specific classifiers. However, while some classifiers are consistent in the predictions they make, other classifiers vary in their predictions. Given our results, we conclude that classifier ensembles with decision-making strategies not based on majority voting are likely to perform best in defect prediction.Peer reviewedFinal Published versio

Learning vector quantization and relevances in complex coefficient space

In this contribution, we consider the classification of time series and similar functional data which can be represented in complex Fourier and wavelet coefficient space. We apply versions of learning vector quantization (LVQ) which are suitable for complex-valued data, based on the so-called Wirtinger calculus. It allows for the formulation of gradient-based update rules in the framework of cost-function-based generalized matrix relevance LVQ (GMLVQ). Alternatively, we consider the concatenation of real and imaginary parts of Fourier coefficients in a real-valued feature vector and the classification of time-domain representations by means of conventional GMLVQ. In addition, we consider the application of the method in combination with wavelet-space features to heartbeat classification

Vitronectin Increases Vascular Permeability by Promoting VE-Cadherin Internalization at Cell Junctions

Cross-talk between integrins and cadherins regulates cell function. We tested the hypothesis that vitronectin (VN), a multi-functional adhesion molecule present in the extracellular matrix and plasma, regulates vascular permeability via effects on VE-cadherin, a critical regulator of endothelial cell (EC) adhesion.Addition of multimeric VN (mult VN) significantly increased VE-cadherin internalization in human umbilical vein EC (HUVEC) monolayers. This effect was blocked by the anti-α(V)β(3) antibody, pharmacological inhibition and knockdown of Src kinase. In contrast to mult VN, monomeric VN did not trigger VE-cadherin internalization. In a modified Miles assay, VN deficiency impaired vascular endothelial growth factor-induced permeability. Furthermore, ischemia-induced enhancement of vascular permeability, expressed as the ratio of FITC-dextran leakage from the circulation into the ischemic and non-ischemic hindlimb muscle, was significantly greater in the WT mice than in the Vn(-/-) mice. Similarly, ischemia-mediated macrophage infiltration was significantly reduced in the Vn(-/-) mice vs. the WT controls. We evaluated changes in the multimerization of VN in ischemic tissue in a mouse hindlimb ischemia model. VN plays a previously unrecognized role in regulating endothelial permeability via conformational- and integrin-dependent effects on VE-cadherin trafficking.These results have important implications for the regulation of endothelial function and angiogenesis by VN under normal and pathological conditions

Purification, characterization, and cloning of a bifunctional molybdoenzyme with hydratase and alcohol dehydrogenase activity

A bifunctional hydratase/alcohol dehydrogenase was isolated from the cyclohexanol degrading bacterium Alicycliphilus denitrificans DSMZ 14773. The enzyme catalyzes the addition of water to α,β-unsaturated carbonyl compounds and the subsequent alcohol oxidation. The purified enzyme showed three subunits in SDS gel, and the gene sequence revealed that this enzyme belongs to the molybdopterin binding oxidoreductase family containing molybdopterins, FAD, and iron-sulfur clusters

Stimulation of the Sphenopalatine Ganglion Induces Reperfusion and Blood-Brain Barrier Protection in the Photothrombotic Stroke Model

The treatment of stroke remains a challenge. Animal studies showing that electrical stimulation of the sphenopalatine ganglion (SPG) exerts beneficial effects in the treatment of stroke have led to the initiation of clinical studies. However, the detailed effects of SPG stimulation on the injured brain are not known.The effect of acute SPG stimulation was studied by direct vascular imaging, fluorescent angiography and laser Doppler flowmetry in the sensory motor cortex of the anaesthetized rat. Focal cerebral ischemia was induced by the rose bengal (RB) photothrombosis method. In chronic experiments, SPG stimulation, starting 15 min or 24 h after photothrombosis, was given for 3 h per day on four consecutive days. Structural damage was assessed using histological and immunohistochemical methods. Cortical functions were assessed by quantitative analysis of epidural electro-corticographic (ECoG) activity continuously recorded in behaving animals.Stimulation induced intensity- and duration-dependent vasodilation and increased cerebral blood flow in both healthy and photothrombotic brains. In SPG-stimulated rats both blood brain-barrier (BBB) opening, pathological brain activity and lesion volume were attenuated compared to untreated stroke animals, with no apparent difference in the glial response surrounding the necrotic lesion.SPG-stimulation in rats induces vasodilation of cortical arterioles, partial reperfusion of the ischemic lesion, and normalization of brain functions with reduced BBB dysfunction and stroke volume. These findings support the potential therapeutic effect of SPG stimulation in focal cerebral ischemia even when applied 24 h after stroke onset and thus may extend the therapeutic window of currently administered stroke medications